Biomarkers and Surrogate Markers: An FDA Perspective

PubMed Central

Katz, Russell

2004-01-01

Summary: Interest is increasing rapidly in the use of surrogate markers as primary measures of the effectiveness of investigational drugs in definitive drug trials. Many such surrogate markers have been proposed as potential candidates for use in definitive effectiveness trials of agents to treat neurologic or psychiatric disease, but as of this date, there are no such markers that have been adequately “validated,” that is, shown to predict the effect of the treatment on the clinical outcome of interest. While the current law and regulations permit the United States Food and Drug Administration to base the approval of a drug product on a determination the effect of the drug on an unvalidated surrogate marker (that is, one for which it is not known that an effect on the surrogate actually predicts the desired clinical benefit), there are a number of difficulties in interpreting trials that use surrogate markers as primary measures of drug effect. In this article, the relevant regulatory context will be discussed, as well as the epistemological problems related to the interpretation of clinical trials in which unvalidated surrogate markers are used as primary outcomes. PMID:15717019

Can we predict age at natural menopause using ovarian reserve tests or mother's age at menopause? A systematic literature review.

PubMed

Depmann, Martine; Broer, Simone L; van der Schouw, Yvonne T; Tehrani, Fahimeh R; Eijkemans, Marinus J; Mol, Ben W; Broekmans, Frank J

2016-02-01

This review aimed to appraise data on prediction of age at natural menopause (ANM) based on antimüllerian hormone (AMH), antral follicle count (AFC), and mother's ANM to evaluate clinical usefulness and to identify directions for further research. We conducted three systematic reviews of the literature to identify studies of menopause prediction based on AMH, AFC, or mother's ANM, corrected for baseline age. Six studies selected in the search for AMH all consistently demonstrated AMH as being capable of predicting ANM (hazard ratio, 5.6-9.2). The sole study reporting on mother's ANM indicated that AMH was capable of predicting ANM (hazard ratio, 9.1-9.3). Two studies provided analyses of AFC and yielded conflicting results, making this marker less strong. AMH is currently the most promising marker for ANM prediction. The predictive capacity of mother's ANM demonstrated in a single study makes this marker a promising contributor to AMH for menopause prediction. Models, however, do not predict the extremes of menopause age very well and have wide prediction interval. These markers clearly need improvement before they can be used for individual prediction of menopause in the clinical setting. Moreover, potential limitations for such use include variations in AMH assays used and a lack of correction for factors or diseases affecting AMH levels or ANM. Future studies should include women of a broad age range (irrespective of cycle regularity) and should base predictions on repeated AMH measurements. Furthermore, currently unknown candidate predictors need to be identified.

LPL is the strongest prognostic factor in a comparative analysis of RNA-based markers in early chronic lymphocytic leukemia.

PubMed

Kaderi, Mohd Arifin; Kanduri, Meena; Buhl, Anne Mette; Sevov, Marie; Cahill, Nicola; Gunnarsson, Rebeqa; Jansson, Mattias; Smedby, Karin Ekström; Hjalgrim, Henrik; Jurlander, Jesper; Juliusson, Gunnar; Mansouri, Larry; Rosenquist, Richard

2011-08-01

The expression levels of LPL, ZAP70, TCL1A, CLLU1 and MCL1 have recently been proposed as prognostic factors in chronic lymphocytic leukemia. However, few studies have systematically compared these different RNA-based markers. Using real-time quantitative PCR, we measured the mRNA expression levels of these genes in unsorted samples from 252 newly diagnosed chronic lymphocytic leukemia patients and correlated our data with established prognostic markers (for example Binet stage, CD38, IGHV gene mutational status and genomic aberrations) and clinical outcome. High expression levels of all RNA-based markers, except MCL1, predicted shorter overall survival and time to treatment, with LPL being the most significant. In multivariate analysis including the RNA-based markers, LPL expression was the only independent prognostic marker for overall survival and time to treatment. When studying LPL expression and the established markers, LPL expression retained its independent prognostic strength for overall survival. All of the RNA-based markers, albeit with varying ability, added prognostic information to established markers, with LPL expression giving the most significant results. Notably, high LPL expression predicted a worse outcome in good-prognosis subgroups, such as patients with mutated IGHV genes, Binet stage A, CD38 negativity or favorable cytogenetics. In particular, the combination of LPL expression and CD38 could further stratify Binet stage A patients. LPL expression is the strongest RNA-based prognostic marker in chronic lymphocytic leukemia that could potentially be applied to predict outcome in the clinical setting, particularly in the large group of patients with favorable prognosis.

Significance of DNA Replication Licensing Proteins (MCM2, MCM5 and CDC6), p16 and p63 as Markers of Premalignant Lesions of the Uterine Cervix: Its Usefulness to Predict Malignant Potential

PubMed Central

Saritha, VN; Veena, VS; Krishna, KM Jagathnath; Somanathan, Thara; Sujathan, K

2018-01-01

Cervical cancer continues to be a leading cancer among women in many parts of the world. Nation-wide screening with the Pap smear has not been implemented in India due to the lack of adequately trained cytologists. Identification of biomarkers to predict malignant potential of the identified low risk lesions is essential to avoid excessive retesting and follow up. The current study analyzed the expression patterns of DNA replication licensing proteins, proliferation inhibitor protein p16INK4A and tumor suppresser protein p63 in cervical tissues and smears to assess the ability of these proteins to predict progression. Methods: Cervical smears and corresponding tissues were immunostained using mouse monoclonal antibodies against MCM2, MCM5, CDC6, p16 and p63. Smears were treated with a non-ionic surfactant sodium deoxycholate prior to immuno-cytochemistry. The standard ABC method of immunohistochemistry was performed using DAB as the chromogen. The immunostained samples were scored on a 0-3+ scale and staining patterns of smears were compared with those of tissue sections. Sensitivity and specificity for each of these markers were calculated taking histopathology as the gold standard. Result: All the markers were positive in malignant and dysplastic cells. MCM protein expression was found to be up-regulated in LSIL, HSIL and in malignancies to a greater extent than p16 as well as p63. CDC6 protein was preferentially expressed in high grade lesions and in invasive squamous cell carcinomas. A progressive increase in the expression of DNA replication licensing proteins in accordance with the grades of cervical intraepithelial lesion suggests these markers as significant to predict malignant potential of low grade lesions in cervical smears. Conclusion: MCMs and CDC6 can be applied as biomarkers to predict malignant potential of low grade lesions identified in screening programmes and retesting / follow up might be confined to those with high risk lesions alone so that overuse of resources can be safely avoided. PMID:29373905

Prediction of Poor Ovarian response by Biochemical and Biophysical Markers: A Logistic Regression Model.

PubMed

Jaiswar, S P; Natu, S M; Sujata; Sankhwar, P L; Manjari, Gupta

2015-12-01

To study correlation between ovarian reserve with biophysical markers (antral follicle count and ovarian volume) and biochemical markers (S. FSH, S. Inhibin B, and S. AMH) and use these markers to predict poor ovarian response to ovarian induction. This is a prospective observational study. One hundred infertile women attending the Obst & Gynae Dept, KGMU were recruited. Blood samples were collected on day 2/day 3 for assessment of S. FSH, S. Inhibin B, and S. AMH and TVS were done for antral follicle count and ovarian volume. Clomephene citrate 100 mg 1OD was given from day 2 to 6, and patients were followed up with serial USG measurements. The numbers of dominant follicles (> or = 14 mm) at the time of hCG administration were counted. Patients with <3 follicles in the 1st cycle were subjected to the 2nd cycle of clomephene 100 mg 1OD from day 2 to day 6 with Inj HMG 150 IU given i.m. starting from day 8 and every alternate day until at least one leading follicle attained ≥18 mm. Development of <3 follicles at end of the 2nd cycle was considered as poor response. Univariate analyses showed that s. inhibin B presented the highest (ROCAUC = 0.862) discriminating potential for predicting poor ovarian response, In multivariate logistic regression model, the variables age, FSH, AMH, INHIBIN B, and AFC remained significant, and the resulting model showed a predicted accuracy of 84.4 %. A derived multimarker computation by a logistic regression model for predicting poor ovarian response was obtained through this study. Thus, potential poor responders could be identified easily, and appropriate ovarian stimulation protocol could be devised for such pts.

Predicting Risk of Type 2 Diabetes Mellitus with Genetic Risk Models on the Basis of Established Genome-wide Association Markers: A Systematic Review

PubMed Central

Bao, Wei; Hu, Frank B.; Rong, Shuang; Rong, Ying; Bowers, Katherine; Schisterman, Enrique F.; Liu, Liegang; Zhang, Cuilin

2013-01-01

This study aimed to evaluate the predictive performance of genetic risk models based on risk loci identified and/or confirmed in genome-wide association studies for type 2 diabetes mellitus. A systematic literature search was conducted in the PubMed/MEDLINE and EMBASE databases through April 13, 2012, and published data relevant to the prediction of type 2 diabetes based on genome-wide association marker–based risk models (GRMs) were included. Of the 1,234 potentially relevant articles, 21 articles representing 23 studies were eligible for inclusion. The median area under the receiver operating characteristic curve (AUC) among eligible studies was 0.60 (range, 0.55–0.68), which did not differ appreciably by study design, sample size, participants’ race/ethnicity, or the number of genetic markers included in the GRMs. In addition, the AUCs for type 2 diabetes did not improve appreciably with the addition of genetic markers into conventional risk factor–based models (median AUC, 0.79 (range, 0.63–0.91) vs. median AUC, 0.78 (range, 0.63–0.90), respectively). A limited number of included studies used reclassification measures and yielded inconsistent results. In conclusion, GRMs showed a low predictive performance for risk of type 2 diabetes, irrespective of study design, participants’ race/ethnicity, and the number of genetic markers included. Moreover, the addition of genome-wide association markers into conventional risk models produced little improvement in predictive performance. PMID:24008910

Applying a new mammographic imaging marker to predict breast cancer risk

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-02-01

Identifying and developing new mammographic imaging markers to assist prediction of breast cancer risk has been attracting extensive research interest recently. Although mammographic density is considered an important breast cancer risk, its discriminatory power is lower for predicting short-term breast cancer risk, which is a prerequisite to establish a more effective personalized breast cancer screening paradigm. In this study, we presented a new interactive computer-aided detection (CAD) scheme to generate a new quantitative mammographic imaging marker based on the bilateral mammographic tissue density asymmetry to predict risk of cancer detection in the next subsequent mammography screening. An image database involving 1,397 women was retrospectively assembled and tested. Each woman had two digital mammography screenings namely, the "current" and "prior" screenings with a time interval from 365 to 600 days. All "prior" images were originally interpreted negative. In "current" screenings, these cases were divided into 3 groups, which include 402 positive, 643 negative, and 352 biopsy-proved benign cases, respectively. There is no significant difference of BIRADS based mammographic density ratings between 3 case groups (p < 0.6). When applying the CAD-generated imaging marker or risk model to classify between 402 positive and 643 negative cases using "prior" negative mammograms, the area under a ROC curve is 0.70+/-0.02 and the adjusted odds ratios show an increasing trend from 1.0 to 8.13 to predict the risk of cancer detection in the "current" screening. Study demonstrated that this new imaging marker had potential to yield significantly higher discriminatory power to predict short-term breast cancer risk.

Genetic and epigenetic markers in colorectal cancer screening: recent advances.

PubMed

Singh, Manish Pratap; Rai, Sandhya; Suyal, Shradha; Singh, Sunil Kumar; Singh, Nand Kumar; Agarwal, Akash; Srivastava, Sameer

2017-07-01

Colorectal cancer (CRC) is a heterogenous disease which develops from benign intraepithelial lesions known as adenomas to malignant carcinomas. Acquired alterations in Wnt signaling, TGFβ, MAPK pathway genes and clonal propagation of altered cells are responsible for this transformation. Detection of adenomas or early stage cancer in asymptomatic patients and better prognostic and predictive markers is important for improving the clinical management of CRC. Area covered: In this review, the authors have evaluated the potential of genetic and epigenetic alterations as markers for early detection, prognosis and therapeutic predictive potential in the context of CRC. We have discussed molecular heterogeneity present in CRC and its correlation to prognosis and response to therapy. Expert commentary: Molecular marker based CRC screening methods still fail to gain trust of clinicians. Invasive screening methods, molecular heterogeneity, chemoresistance and low quality test samples are some key challenges which need to be addressed in the present context. New sequencing technologies and integrated omics data analysis of individual or population cohort results in GWAS. MPE studies following a GWAS could be future line of research to establish accurate correlations between CRC and its risk factors. This strategy would identify most reliable biomarkers for CRC screening and management.

Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas.

PubMed

Siegal, Tali

2016-01-01

Sorting and grading of glial tumors by the WHO classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular markers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neuro-oncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with codeletion of 1p/19q chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in glioblastoma of the elderly. The clinical implication of other molecular markers of gliomas like mutations of EGFR and ATRX genes and BRAF fusion or point mutation is highlighted. The potential of molecular biomarker-based classification to guide future therapeutic approach is discussed and accentuated.

Predictive models for customizing chemotherapy in advanced non-small cell lung cancer (NSCLC).

PubMed

Bonanno, Laura

2013-06-01

The backbone of first-line treatment for Epidermal Growth Factor (EGFR) wild-type (wt) advanced Non-small cell lung cancer (NSCLC) patients is the use of a platinum-based chemotherapy combination. The treatment is characterized by great inter-individual variability in outcome. Molecular predictive markers are extremely needed in order to identify patients most likely to benefit from platinum-based treatment and resistant ones, thus optimizing chemotherapy approach in NSCLC. Several components of DNA repair response (DRR) have been investigated as potential predictive markers. Among them, high levels of expression of ERCC1, both at protein and mRNA levels, have been associated with resistance to cisplatin in NSCLC. In addition, low levels of expression of RRM1, a target for gemcitabine, have been associated with improved OS in advanced NSCLC patients treated with cisplatin and gemcitabine. Preclinical data and retrospective analyses showed that BRCA1 is able to induce resistance to cisplatin and sensitivity to antimicrotubule agents. In addition, the mRNA levels of expression of RAP80, encoding for a protein cooperating with BRCA1 in homologous recombination (HR), have demonstrated to further sub-classify low BRCA1 NSCLC tumors, improving the predictive model. On the basis of biological knowledge on DNA repair pathway and recent controversial results from clinical validation of potential molecular markers, integrated analysis of multiple DNA repair components could improve predictive information and pave the way to a new approach to customized chemotherapy clinical trials.

A and MdMYB1 allele-specific markers controlling apple (Malus x domestica Borkh.) skin color and suitability for marker-assisted selection.

PubMed

Zhang, X J; Wang, L X; Chen, X X; Liu, Y L; Meng, R; Wang, Y J; Zhao, Z Y

2014-10-31

Pre-selection for fruit skin color at the seedling stage would be highly advantageous, with marker-assisted selection offering a potential method for apple pre-selection. A and MdMYB1 alleles are allele-specific DNA markers that are potentially associated with apple skin color, and co-segregate with the Rf and Rni loci, respectively. Here, we assessed the potential application of these 2 alleles for marker-assisted breeding across 30 diverse cultivars and 2 apple seedling progenies. The red skin color phenotype was usually associated with the MdMYB1-1 allele and A(1) allele, respectively, while the 2 molecular markers provided approximately 91% predictability in the 'Fuji' x 'Cripps Pink' and 'Fuji' x 'Gala' progenies. The results obtained from the 30 cultivars and 2 progenies were consistent for the 2 molecular markers. Hence, the results supported that Rf and Rni could be located in a gene cluster, or even correspond to alleles of the same gene. Our results are consistent with the hypothesis that red/yellow dimorphism is controlled by a monogenic system, with the presence of the red anthocyanin pigmentation being dominant. In addition, our results supported that the practical utilization of the 2 function markers to efficiently and accurately select red-skinned apple cultivars in apple scion breeding programs.

Metabolite and transcript markers for the prediction of potato drought tolerance.

PubMed

Sprenger, Heike; Erban, Alexander; Seddig, Sylvia; Rudack, Katharina; Thalhammer, Anja; Le, Mai Q; Walther, Dirk; Zuther, Ellen; Köhl, Karin I; Kopka, Joachim; Hincha, Dirk K

2018-04-01

Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

[Prognostic and predictive molecular markers for urologic cancers].

PubMed

Hartmann, A; Schlomm, T; Bertz, S; Heinzelmann, J; Hölters, S; Simon, R; Stoehr, R; Junker, K

2014-04-01

Molecular prognostic factors and genetic alterations as predictive markers for cancer-specific targeted therapies are used today in the clinic for many malignancies. In recent years, many molecular markers for urogenital cancers have also been identified. However, these markers are not clinically used yet. In prostate cancer, novel next-generation sequencing methods revealed a detailed picture of the molecular changes. There is growing evidence that a combination of classical histopathological and validated molecular markers could lead to a more precise estimation of prognosis, thus, resulting in an increasing number of patients with active surveillance as a possible treatment option. In patients with urothelial carcinoma, histopathological factors but also the proliferation of the tumor, mutations in oncogenes leading to an increasing proliferation rate and changes in genes responsible for invasion and metastasis are important. In addition, gene expression profiles which could distinguish aggressive tumors with high risk of metastasis from nonmetastasizing tumors have been recently identified. In the future, this could potentially allow better selection of patients needing systemic perioperative treatment. In renal cell carcinoma, many molecular markers that are associated with metastasis and survival have been identified. Some of these markers were also validated as independent prognostic markers. Selection of patients with primarily organ-confined tumors and increased risk of metastasis for adjuvant systemic therapy could be clinically relevant in the future.

Immunological tumor status may predict response to neoadjuvant chemotherapy and outcome after radical cystectomy in bladder cancer.

PubMed

Tervahartiala, Minna; Taimen, Pekka; Mirtti, Tuomas; Koskinen, Ilmari; Ecke, Thorsten; Jalkanen, Sirpa; Boström, Peter J

2017-10-04

Bladder cancer (BC) is the ninth most common cancer worldwide. Radical cystectomy (RC) with neoadjuvant chemotherapy (NAC) is recommended for muscle-invasive BC. The challenge of the neoadjuvant approach relates to challenges in selection of patients to chemotherapy that are likely to respond to the treatment. To date, there are no validated molecular markers or baseline clinical characteristics to identify these patients. Different inflammatory markers, including tumor associated macrophages with their plastic pro-tumorigenic and anti-tumorigenic functions, have extensively been under interests as potential prognostic and predictive biomarkers in different cancer types. In this immunohistochemical study we evaluated the predictive roles of three immunological markers, CD68, MAC387, and CLEVER-1, in response to NAC and outcome of BC. 41% of the patients had a complete response (pT0N0) to NAC. Basic clinicopathological variables did not predict response to NAC. In contrast, MAC387 + cells and CLEVER-1 + macrophages associated with poor NAC response, while CLEVER-1 + vessels associated with more favourable response to NAC. Higher counts of CLEVER-1 + macrophages associated with poorer overall survival and CD68 + macrophages seem to have an independent prognostic value in BC patients treated with NAC. Our findings point out that CD68, MAC387, and CLEVER-1 may be useful prognostic and predictive markers in BC.

SOX9 as a Predictor for Neurogenesis Potentiality of Amniotic Fluid Stem Cells

PubMed Central

Wei, Pei-Cih; Chao, Angel; Peng, Hsiu-Huei; Chao, An-Shine; Chang, Yao-Lung; Chang, Shuenn-Dyh; Wang, Hsin-Shih; Chang, Yu-Jen; Tsai, Ming-Song; Sieber, Martin; Chen, Hua-Chien; Chen, Shu-Jen; Lee, Yun-Shien

2014-01-01

Preclinical studies of amniotic fluid-derived cell therapy have been successful in the research of neurodegenerative diseases, peripheral nerve injury, spinal cord injury, and brain ischemia. Transplantation of human amniotic fluid stem cells (AFSCs) into rat brain ventricles has shown improvement in symptoms of Parkinson's disease and also highlighted the minimal immune rejection risk of AFSCs, even between species. Although AFSCs appeared to be a promising resource for cell-based regenerative therapy, AFSCs contain a heterogeneous pool of distinct cell types, rendering each preparation of AFSCs unique. Identification of predictive markers for neuron-prone AFSCs is necessary before such stem cell-based therapeutics can become a reality. In an attempt to identify markers of AFSCs to predict their ability for neurogenesis, we performed a two-phase study. In the discovery phase of 23 AFSCs, we tested ZNF521/Zfp521, OCT6, SOX1, SOX2, SOX3, and SOX9 as predictive markers of AFSCs for neural differentiation. In the validation phase, the efficacy of these predictive markers was tested in independent sets of 18 AFSCs and 14 dental pulp stem cells (DPSCs). We found that high expression of SOX9 in AFSCs is associated with good neurogenetic ability, and these positive correlations were confirmed in independent sets of AFSCs and DPSCs. Furthermore, knockdown of SOX9 in AFSCs inhibited their neuronal differentiation. In conclusion, the discovery of SOX9 as a predictive marker for neuron-prone AFSCs could expedite the selection of useful clones for regenerative medicine, in particular, in neurological diseases and injuries. PMID:25154783

Successful prediction of genetic richness at wild potato collection sites in southeastern Arizona

USDA-ARS?s Scientific Manuscript database

Much time, money, and effort is needed to collect even a fraction of the potential geographic range of wild potato species, so there is efficiency to gain if one could predict and prioritize spots particularly rich in unique alleles for collecting. A previous experiment that used AFLP markers to com...

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed Central

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-01-01

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-09-28

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

Algorithms for selecting informative marker panels for population assignment.

PubMed

Rosenberg, Noah A

2005-11-01

Given a set of potential source populations, genotypes of an individual of unknown origin at a collection of markers can be used to predict the correct source population of the individual. For improved efficiency, informative markers can be chosen from a larger set of markers to maximize the accuracy of this prediction. However, selecting the loci that are individually most informative does not necessarily produce the optimal panel. Here, using genotypes from eight species--carp, cat, chicken, dog, fly, grayling, human, and maize--this univariate accumulation procedure is compared to new multivariate "greedy" and "maximin" algorithms for choosing marker panels. The procedures generally suggest similar panels, although the greedy method often recommends inclusion of loci that are not chosen by the other algorithms. In seven of the eight species, when applied to five or more markers, all methods achieve at least 94% assignment accuracy on simulated individuals, with one species--dog--producing this level of accuracy with only three markers, and the eighth species--human--requiring approximately 13-16 markers. The new algorithms produce substantial improvements over use of randomly selected markers; where differences among the methods are noticeable, the greedy algorithm leads to slightly higher probabilities of correct assignment. Although none of the approaches necessarily chooses the panel with optimal performance, the algorithms all likely select panels with performance near enough to the maximum that they all are suitable for practical use.

The role of toxicology to characterize biomarkers for agrochemicals with potential endocrine activities.

PubMed

Mantovani, Alberto; Maranghi, Francesca; La Rocca, Cinzia; Tiboni, Gian Mario; Clementi, Maurizio

2008-09-01

The paper discusses current knowledge and possible research priorities on biomarkers of exposure, effect and susceptibility for potential endocrine activities of agrochemicals (dicarboximides, ethylene bisdithiocarbammates, triazoles, etc.). Possible widespread, multiple-pathway exposure to agrochemicals highlights the need to assess internal exposure of animals or humans, which is the most relevant exposure measure for hazard and risk estimation; however, exposure data should be integrated by early indicators predictive of possible health effects, particularly for vulnerable groups such as mother-child pairs. Research need include: non-invasive biomarkers for children biomonitoring; novel biomarkers of total exposure to measure whole endocrine disrupter-related burden; characterization of biomarkers of susceptibility, including the role of markers of nutritional status; anchoring early molecular markers to established toxicological endpoints to support their predictivity; integrating "omics"-based approaches in a system-toxicology framework. As biomonitoring becomes increasingly important in the environment-and-health scenario, toxicologists can substantially contribute both to the characterization of new biomarkers and to the predictivity assessment and improvement of the existing ones.

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

PubMed Central

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments.

PubMed

Windhausen, Vanessa S; Atlin, Gary N; Hickey, John M; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E; Raman, Babu; Cairns, Jill E; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E

2012-11-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F(2)-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F(2)-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set.

Omnibus Risk Assessment via Accelerated Failure Time Kernel Machine Modeling

PubMed Central

Sinnott, Jennifer A.; Cai, Tianxi

2013-01-01

Summary Integrating genomic information with traditional clinical risk factors to improve the prediction of disease outcomes could profoundly change the practice of medicine. However, the large number of potential markers and possible complexity of the relationship between markers and disease make it difficult to construct accurate risk prediction models. Standard approaches for identifying important markers often rely on marginal associations or linearity assumptions and may not capture non-linear or interactive effects. In recent years, much work has been done to group genes into pathways and networks. Integrating such biological knowledge into statistical learning could potentially improve model interpretability and reliability. One effective approach is to employ a kernel machine (KM) framework, which can capture nonlinear effects if nonlinear kernels are used (Scholkopf and Smola, 2002; Liu et al., 2007, 2008). For survival outcomes, KM regression modeling and testing procedures have been derived under a proportional hazards (PH) assumption (Li and Luan, 2003; Cai et al., 2011). In this paper, we derive testing and prediction methods for KM regression under the accelerated failure time model, a useful alternative to the PH model. We approximate the null distribution of our test statistic using resampling procedures. When multiple kernels are of potential interest, it may be unclear in advance which kernel to use for testing and estimation. We propose a robust Omnibus Test that combines information across kernels, and an approach for selecting the best kernel for estimation. The methods are illustrated with an application in breast cancer. PMID:24328713

Combinatorial markers of mild cognitive impairment conversion to Alzheimer's disease--cytokines and MRI measures together predict disease progression.

PubMed

Furney, Simon J; Kronenberg, Deborah; Simmons, Andrew; Güntert, Andreas; Dobson, Richard J; Proitsi, Petroula; Wahlund, Lars Olof; Kloszewska, Iwona; Mecocci, Patrizia; Soininen, Hilkka; Tsolaki, Magda; Vellas, Bruno; Spenger, Christian; Lovestone, Simon

2011-01-01

Progression of people presenting with Mild Cognitive Impairment (MCI) to dementia is not certain and it is not possible for clinicians to predict which people are most likely to convert. The inability of clinicians to predict progression limits the use of MCI as a syndrome for treatment in prevention trials and, as more people present with this syndrome in memory clinics, and as earlier diagnosis is a major goal of health services, this presents an important clinical problem. Some data suggest that CSF biomarkers and functional imaging using PET might act as markers to facilitate prediction of conversion. However, both techniques are costly and not universally available. The objective of our study was to investigate the potential added benefit of combining biomarkers that are more easily obtained in routine clinical practice to predict conversion from MCI to Alzheimer's disease. To explore this we combined automated regional analysis of structural MRI with analysis of plasma cytokines and chemokines and compared these to measures of APOE genotype and clinical assessment to assess which best predict progression. In a total of 205 people with MCI, 77 of whom subsequently converted to Alzheimer's disease, we find biochemical markers of inflammation to be better predictors of conversion than APOE genotype or clinical measures (Area under the curve (AUC) 0.65, 0.62, 0.59 respectively). In a subset of subjects who also had MRI scans the combination of serum markers of inflammation and MRI automated imaging analysis provided the best predictor of conversion (AUC 0.78). These results show that the combination of imaging and cytokine biomarkers provides an improvement in prediction of MCI to AD conversion compared to either datatype alone, APOE genotype or clinical data and an accuracy of prediction that would have clinical utility.

Technical aspects of real time positron emission tracking for gated radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chamberland, Marc; Xu, Tong, E-mail: txu@physics.carleton.ca; McEwen, Malcolm R.

2016-02-15

Purpose: Respiratory motion can lead to treatment errors in the delivery of radiotherapy treatments. Respiratory gating can assist in better conforming the beam delivery to the target volume. We present a study of the technical aspects of a real time positron emission tracking system for potential use in gated radiotherapy. Methods: The tracking system, called PeTrack, uses implanted positron emission markers and position sensitive gamma ray detectors to track breathing motion in real time. PeTrack uses an expectation–maximization algorithm to track the motion of fiducial markers. A normalized least mean squares adaptive filter predicts the location of the markers amore » short time ahead to account for system response latency. The precision and data collection efficiency of a prototype PeTrack system were measured under conditions simulating gated radiotherapy. The lung insert of a thorax phantom was translated in the inferior–superior direction with regular sinusoidal motion and simulated patient breathing motion (maximum amplitude of motion ±10 mm, period 4 s). The system tracked the motion of a {sup 22}Na fiducial marker (0.34 MBq) embedded in the lung insert every 0.2 s. The position of the was marker was predicted 0.2 s ahead. For sinusoidal motion, the equation used to model the motion was fitted to the data. The precision of the tracking was estimated as the standard deviation of the residuals. Software was also developed to communicate with a Linac and toggle beam delivery. In a separate experiment involving a Linac, 500 monitor units of radiation were delivered to the phantom with a 3 × 3 cm photon beam and with 6 and 10 MV accelerating potential. Radiochromic films were inserted in the phantom to measure spatial dose distribution. In this experiment, the period of motion was set to 60 s to account for beam turn-on latency. The beam was turned off when the marker moved outside of a 5-mm gating window. Results: The precision of the tracking in the IS direction was 0.53 mm for a sinusoidally moving target, with an average count rate ∼250 cps. The average prediction error was 1.1 ± 0.6 mm when the marker moved according to irregular patient breathing motion. Across all beam deliveries during the radiochromic film measurements, the average prediction error was 0.8 ± 0.5 mm. The maximum error was 2.5 mm and the 95th percentile error was 1.5 mm. Clear improvement of the dose distribution was observed between gated and nongated deliveries. The full-width at halfmaximum of the dose profiles of gated deliveries differed by 3 mm or less than the static reference dose distribution. Monitoring of the beam on/off times showed synchronization with the location of the marker within the latency of the system. Conclusions: PeTrack can track the motion of internal fiducial positron emission markers with submillimeter precision. The system can be used to gate the delivery of a Linac beam based on the position of a moving fiducial marker. This highlights the potential of the system for use in respiratory-gated radiotherapy.« less

Molecular markers in bladder cancer: Novel research frontiers.

PubMed

Sanguedolce, Francesca; Cormio, Antonella; Bufo, Pantaleo; Carrieri, Giuseppe; Cormio, Luigi

2015-01-01

Bladder cancer (BC) is a heterogeneous disease encompassing distinct biologic features that lead to extremely different clinical behaviors. In the last 20 years, great efforts have been made to predict disease outcome and response to treatment by developing risk assessment calculators based on multiple standard clinical-pathological factors, as well as by testing several molecular markers. Unfortunately, risk assessment calculators alone fail to accurately assess a single patient's prognosis and response to different treatment options. Several molecular markers easily assessable by routine immunohistochemical techniques hold promise for becoming widely available and cost-effective tools for a more reliable risk assessment, but none have yet entered routine clinical practice. Current research is therefore moving towards (i) identifying novel molecular markers; (ii) testing old and new markers in homogeneous patients' populations receiving homogeneous treatments; (iii) generating a multimarker panel that could be easily, and thus routinely, used in clinical practice; (iv) developing novel risk assessment tools, possibly combining standard clinical-pathological factors with molecular markers. This review analyses the emerging body of literature concerning novel biomarkers, ranging from genetic changes to altered expression of a huge variety of molecules, potentially involved in BC outcome and response to treatment. Findings suggest that some of these indicators, such as serum circulating tumor cells and tissue mitochondrial DNA, seem to be easily assessable and provide reliable information. Other markers, such as the phosphoinositide-3-kinase (PI3K)/AKT (serine-threonine kinase)/mTOR (mammalian target of rapamycin) pathway and epigenetic changes in DNA methylation seem to not only have prognostic/predictive value but also, most importantly, represent valuable therapeutic targets. Finally, there is increasing evidence that the development of novel risk assessment tools combining standard clinical-pathological factors with molecular markers represents a major quest in managing this poorly predictable disease.

Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato.

PubMed

Stich, Benjamin; Van Inghelandt, Delphine

2018-01-01

Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

PubMed Central

Stich, Benjamin; Van Inghelandt, Delphine

2018-01-01

Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs. PMID:29563919

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound

PubMed Central

Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J.; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T.; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J.

2017-01-01

Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival. PMID:28401902

A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound.

PubMed

Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J

2017-04-12

Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival.

Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

PubMed

Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

2011-01-01

Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

A water marker monitored by satellites to predict seasonal endemic cholera.

PubMed

Jutla, Antarpreet; Akanda, Ali Shafqat; Huq, Anwar; Faruque, Abu Syed Golam; Colwell, Rita; Islam, Shafiqul

2013-01-01

The ability to predict an occurrence of cholera, a water-related disease, offers a significant public health advantage. Satellite based estimates of chlorophyll, a surrogate for plankton abundance, have been linked to cholera incidence. However, cholera bacteria can survive under a variety of coastal ecological conditions, thus constraining the predictive ability of the chlorophyll, since it provides only an estimate of greenness of seawater. Here, a new remote sensing based index is proposed: Satellite Water Marker (SWM), which estimates condition of coastal water, based on observed variability in the difference between blue (412 nm) and green (555 nm) wavelengths that can be related to seasonal cholera incidence. The index is bounded between physically separable wavelengths for relatively clear (blue) and turbid (green) water. Using SWM, prediction of cholera with reasonable accuracy, with at least two month in advance, can potentially be achieved in the endemic coastal regions.

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer

PubMed Central

WANG, HAIYING; MOLINA, JULIAN; JIANG, JOHN; FERBER, MATTHEW; PRUTHI, SANDHYA; JATKOE, TIMOTHY; DERECHO, CARLO; RAJPUROHIT, YASHODA; ZHENG, JIAN; WANG, YIXIN

2013-01-01

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and response to treatment. PMID:24649289

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer.

PubMed

Wang, Haiying; Molina, Julian; Jiang, John; Ferber, Matthew; Pruthi, Sandhya; Jatkoe, Timothy; Derecho, Carlo; Rajpurohit, Yashoda; Zheng, Jian; Wang, Yixin

2013-11-01

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and response to treatment.

Clinical utility of endocrine markers predicting myocardial siderosis in transfusion dependent thalassemia major.

PubMed

Ehsan, Lubaina; Rashid, Mariam; Alvi, Najveen; Awais, Khadija; Nadeem, Omair; Asghar, Aleezay; Sajjad, Fatimah; Fatima, Malika; Qidwai, Asim; Hussain, Shabneez; Hasan, Erum; Brown, Nick; Altaf, Sadaf; Hasan, Babar; Kirmani, Salman

2018-06-12

Endocrinopathy due to iron overload is the most common morbidity whereas myocardial siderosis causing toxic cardiomyopathy is the leading cause of mortality among patients with transfusion dependent thalassemia major (TDTM). If detected early, this can be treated with aggressive chelation. T2* cardiac magnetic resonance imaging (CMR) guided chelation protocols are now the gold standard but have limited availability in low and middle-income countries. We hypothesized that markers of endocrine dysfunction would correlate with T2* CMR and can be used to predict the severity of myocardial siderosis and guide chelation therapy. We undertook a multicenter retrospective study of 280 patients with TDTM to assess the prevalence of endocrinopathies and the predictive value of a number of individual and composite markers of endocrinopathy with T2* CMR. The prevalence of hypogonadism, stunting, hypoparathyroidism, and hypothyroidism was 82%, 69%, 40%, and 30%, respectively. The sensitivity of hypogonadism and stunting predicting severe myocardial siderosis was 90% and 80%, respectively. We conclude that clinical markers of endocrine dysfunction, especially hypogonadism (positive likelihood ratio [LR+] = 1.4, 95% confidence interval [CI] = 1.0-1.9; positive predictive value [PPV] = 77%, 95% CI = 70-82; negative predictive value [NPV] = 57%, 95% CI = 34-77] and stunting (LR+ = 1.3, 95% CI = 1.1-1.6; PPV = 64%, 95% CI = 60-69; NPV = 55%, 95% CI = 45-64) in TDTM can predict severe myocardial siderosis and can potentially guide chelation therapy, especially where access to T2* CMR is limited. © 2018 Wiley Periodicals, Inc.

Genomic Prediction of Testcross Performance in Canola (Brassica napus)

PubMed Central

Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

2016-01-01

Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years. PMID:26824924

Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

PubMed Central

Windhausen, Vanessa S.; Atlin, Gary N.; Hickey, John M.; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E.; Raman, Babu; Cairns, Jill E.; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E.

2012-01-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F2-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F2-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set. PMID:23173094

Prognostic markers of pediatric meningococcal sepsis.

PubMed

Briassoulis, George; Galani, Angeliki

2014-09-01

Having available tools to determine the prognosis of pediatric meningococcal sepsis at admission to the Intensive Care Unit or during the course of the disease constitutes a clinical necessity. Recently, new readily measurable circulating biomarkers have been described as an additional tool for severity classification and prediction of mortality in meningococcal disease. These biomarkers have been associated with increased risk of mortality scores and a number of organ failures in heterogeneous samples of critically ill children. In future, genetic markers may be used for identification of high-risk patients by creating prediction rules for clinical course and sequelae, and potentially provide more insight in the complex immune response in meningococcal sepsis. We briefly summarize the data pointing at the emerging genome-wide expression profiling studies and review the prognostic value of the main markers investigated in pediatric meningococcal sepsis putting them in the current frame of sepsis in general.

Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification

PubMed Central

Korolev, Igor O.; Symonds, Laura L.; Bozoki, Andrea C.

2016-01-01

Background Individuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level. Methods Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework. Results Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions. Conclusions We developed an accurate prognostic model for predicting MCI-to-dementia progression over a three-year period. The model utilizes widely available, cost-effective, non-invasive markers and can be used to improve patient selection in clinical trials and identify high-risk MCI patients for early treatment. PMID:26901338

Omnibus risk assessment via accelerated failure time kernel machine modeling.

PubMed

Sinnott, Jennifer A; Cai, Tianxi

2013-12-01

Integrating genomic information with traditional clinical risk factors to improve the prediction of disease outcomes could profoundly change the practice of medicine. However, the large number of potential markers and possible complexity of the relationship between markers and disease make it difficult to construct accurate risk prediction models. Standard approaches for identifying important markers often rely on marginal associations or linearity assumptions and may not capture non-linear or interactive effects. In recent years, much work has been done to group genes into pathways and networks. Integrating such biological knowledge into statistical learning could potentially improve model interpretability and reliability. One effective approach is to employ a kernel machine (KM) framework, which can capture nonlinear effects if nonlinear kernels are used (Scholkopf and Smola, 2002; Liu et al., 2007, 2008). For survival outcomes, KM regression modeling and testing procedures have been derived under a proportional hazards (PH) assumption (Li and Luan, 2003; Cai, Tonini, and Lin, 2011). In this article, we derive testing and prediction methods for KM regression under the accelerated failure time (AFT) model, a useful alternative to the PH model. We approximate the null distribution of our test statistic using resampling procedures. When multiple kernels are of potential interest, it may be unclear in advance which kernel to use for testing and estimation. We propose a robust Omnibus Test that combines information across kernels, and an approach for selecting the best kernel for estimation. The methods are illustrated with an application in breast cancer. © 2013, The International Biometric Society.

Inflammatory Markers and Preeclampsia: A Systematic Review.

PubMed

Black, Kathleen Darrah; Horowitz, June Andrews

Preeclampsia (PE), a serious and variable pregnancy complication affecting 5%-10% of the obstetric population, has an undetermined etiology, yet inflammation is concomitant with its development, particularly in relation to endothelial dysfunction. The purpose of this systematic review was to examine the published evidence concerning an association between PE and inflammatory markers for their usefulness in the prediction or early identification of women with PE in antepartum clinical settings. In this systematic review, we used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Cumulative Index for Nursing and Allied Health and MEDLINE/OVID were the electronic databases used for identifying published articles. We placed no time limit on the publication year. The search generated 798 articles. After removing duplicates, screening abstracts, and conducting full-text reviews, we retained 73 articles and examined 57 unique markers. This review shows that C-reactive protein and the cytokines, specifically the proinflammatory markers IL-6, IL-8, and tumor necrosis factor alpha, garner the most support as potential inflammatory markers for clinical surveillance of PE, particularly during the second and third trimesters. Based on this review, we cannot recommend any single inflammatory marker for routine clinical use to predict/identify PE onset or progression. Research is recommended to examine a combination panel of these four inflammatory markers both with and without clinical risk factors toward the goal of translation to practice.

Early prognostication markers in cardiac arrest patients treated with hypothermia.

PubMed

Karapetkova, M; Koenig, M A; Jia, X

2016-03-01

Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA. © 2015 EAN.

The Promise of Novel Molecular Markers in Bladder Cancer

PubMed Central

Miremami, Jahan; Kyprianou, Natasha

2014-01-01

Bladder cancer is the fourth most common malignancy in the US and is associated with the highest cost per patient. A high likelihood of recurrence, mandating stringent surveillance protocols, has made the development of urinary markers a focus of intense pursuit with the hope of decreasing the burden this disease places on patients and the healthcare system. To date, routine use of markers is not recommended for screening or diagnosis. Interests include the development of a single urinary marker that can be used in place of or as an adjunct to current screening and surveillance techniques, as well identifying a molecular signature for an individual’s disease that can help predict progression, prognosis, and potential therapeutic response. Markers have shown potential value in improving diagnostic accuracy when used as an adjunct to current modalities, risk-stratification of patients that could aid the clinician in determining aggressiveness of surveillance, and allowing for a decrease in invasive surveillance procedures. This review discusses the current understanding of emerging biomarkers, including miRNAs, gene signatures and detection of circulating tumor cells in the blood, and their potential clinical value in bladder cancer diagnosis, as prognostic indicators, and surveillance tools, as well as limitations to their incorporation into medical practice. PMID:25535079

Anti-A2 and anti-A1 domain antibodies are potential predictors of immune tolerance induction outcome in children with hemophilia A.

PubMed

Lapalud, P; Rothschild, C; Mathieu-Dupas, E; Balicchi, J; Gruel, Y; Laune, D; Molina, F; Schved, J F; Granier, C; Lavigne-Lissalde, G

2015-04-01

Hemophilia A (HA) is a congenital bleeding disorder resulting from factor VIII deficiency. The most serious complication of HA management is the appearance of inhibitory antibodies (Abs) against injected FVIII concentrates. To eradicate inhibitors, immune tolerance induction (ITI) is usually attempted, but it fails in up to 30% of cases. Currently, no undisputed predictive marker of ITI outcome is available to facilitate the clinical decision. To identify predictive markers of ITI efficacy. The isotypic and epitopic repertoires of inhibitory Abs were analyzed in plasma samples collected before ITI initiation from 15 children with severe HA and high-titer inhibitors, and their levels were compared in the two outcome groups (ITI success [n = 7] and ITI failure [n = 8]). The predictive value of these candidate biomarkers and of the currently used indicators (inhibitor titer and age at ITI initiation, highest inhibitor titer before ITI, and interval between inhibitor diagnosis and ITI initiation) was then compared by statistical analysis (Wilcoxon test and receiver receiver operating characteristic [ROC] curve analysis). Whereas current indicators seemed to fail in discriminating patients in the two outcome groups (ITI success or failure), anti-A1 and anti-A2 Ab levels before ITI initiation appeared to be good potential predictive markers of ITI outcome (P < 0.018). ROC analysis showed that anti-A1 and anti-A2 Abs were the best at discriminating between outcome groups (area under the ROC curve of > 0.875). Anti-A1 and anti-A2 Abs could represent new promising tools for the development of ITI outcome prediction tests for children with severe HA. © 2015 International Society on Thrombosis and Haemostasis.

Modified aging of elite athletes revealed by analysis of epigenetic age markers

PubMed Central

Spólnicka, Magdalena; Pośpiech, Ewelina; Adamczyk, Jakub Grzegorz; Freire-Aradas, Ana; Pepłońska, Beata; Zbieć-Piekarska, Renata; Makowska, Żanetta; Pięta, Anna; Lareu, Maria Victoria; Phillips, Christopher; Płoski, Rafał; Żekanowski, Cezary

2018-01-01

Recent progress in epigenomics has led to the development of prediction systems that enable accurate age estimation from DNA methylation data. Our objective was to track responses to intense physical exercise of individual age-correlated DNA methylation markers and to infer their potential impact on the aging processes. The study showed accelerated DNA hypermethylation for two CpG sites in TRIM59 and KLF14. Both markers predicted the investigated elite athletes to be several years older than controls and this effect was more substantial in subjects involved in power sports. Accordingly, the complete 5-CpG model revealed age acceleration of elite athletes (P=1.503x10-7) and the result was more significant amongst power athletes (P=1.051x10-9). The modified methylation of TRIM59 and KLF14 in top athletes may be accounted for by the biological roles played by these genes. Their known anti-tumour and anti-inflammatory activities suggests that intense physical training has a complex influence on aging and potentially launches signalling networks that contribute to the observed lower risk of elite athletes to develop cardiovascular disease and cancer. PMID:29466246

Modified aging of elite athletes revealed by analysis of epigenetic age markers.

PubMed

Spólnicka, Magdalena; Pośpiech, Ewelina; Adamczyk, Jakub Grzegorz; Freire-Aradas, Ana; Pepłońska, Beata; Zbieć-Piekarska, Renata; Makowska, Żanetta; Pięta, Anna; Lareu, Maria Victoria; Phillips, Christopher; Płoski, Rafał; Żekanowski, Cezary; Branicki, Wojciech

2018-02-15

Recent progress in epigenomics has led to the development of prediction systems that enable accurate age estimation from DNA methylation data. Our objective was to track responses to intense physical exercise of individual age-correlated DNA methylation markers and to infer their potential impact on the aging processes. The study showed accelerated DNA hypermethylation for two CpG sites in TRIM59 and KLF14 . Both markers predicted the investigated elite athletes to be several years older than controls and this effect was more substantial in subjects involved in power sports. Accordingly, the complete 5-CpG model revealed age acceleration of elite athletes ( P =1.503x10 -7 ) and the result was more significant amongst power athletes (P=1.051x10 -9 ). The modified methylation of TRIM59 and KLF14 in top athletes may be accounted for by the biological roles played by these genes. Their known anti-tumour and anti-inflammatory activities suggests that intense physical training has a complex influence on aging and potentially launches signalling networks that contribute to the observed lower risk of elite athletes to develop cardiovascular disease and cancer.

Risk Classification with an Adaptive Naive Bayes Kernel Machine Model.

PubMed

Minnier, Jessica; Yuan, Ming; Liu, Jun S; Cai, Tianxi

2015-04-22

Genetic studies of complex traits have uncovered only a small number of risk markers explaining a small fraction of heritability and adding little improvement to disease risk prediction. Standard single marker methods may lack power in selecting informative markers or estimating effects. Most existing methods also typically do not account for non-linearity. Identifying markers with weak signals and estimating their joint effects among many non-informative markers remains challenging. One potential approach is to group markers based on biological knowledge such as gene structure. If markers in a group tend to have similar effects, proper usage of the group structure could improve power and efficiency in estimation. We propose a two-stage method relating markers to disease risk by taking advantage of known gene-set structures. Imposing a naive bayes kernel machine (KM) model, we estimate gene-set specific risk models that relate each gene-set to the outcome in stage I. The KM framework efficiently models potentially non-linear effects of predictors without requiring explicit specification of functional forms. In stage II, we aggregate information across gene-sets via a regularization procedure. Estimation and computational efficiency is further improved with kernel principle component analysis. Asymptotic results for model estimation and gene set selection are derived and numerical studies suggest that the proposed procedure could outperform existing procedures for constructing genetic risk models.

Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers

PubMed Central

2014-01-01

Background Although the X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. In this study, we presented a method for computing genomic relationships using X chromosome markers, investigated the accuracy of imputation from a low density (7K) to the 54K SNP (single nucleotide polymorphism) panel, and compared the accuracy of genomic prediction with and without using X chromosome markers. Methods The impact of considering X chromosome markers on prediction accuracy was assessed using data from Nordic Holstein bulls and different sets of SNPs: (a) the 54K SNPs for reference and test animals, (b) SNPs imputed from the 7K to the 54K SNP panel for test animals, (c) SNPs imputed from the 7K to the 54K panel for half of the reference animals, and (d) the 7K SNP panel for all animals. Beagle and Findhap were used for imputation. GBLUP (genomic best linear unbiased prediction) models with or without X chromosome markers and with or without a residual polygenic effect were used to predict genomic breeding values for 15 traits. Results Averaged over the two imputation datasets, correlation coefficients between imputed and true genotypes for autosomal markers, pseudo-autosomal markers, and X-specific markers were 0.971, 0.831 and 0.935 when using Findhap, and 0.983, 0.856 and 0.937 when using Beagle. Estimated reliabilities of genomic predictions based on the imputed datasets using Findhap or Beagle were very close to those using the real 54K data. Genomic prediction using all markers gave slightly higher reliabilities than predictions without X chromosome markers. Based on our data which included only bulls, using a G matrix that accounted for sex-linked relationships did not improve prediction, compared with a G matrix that did not account for sex-linked relationships. A model that included a polygenic effect did not recover the loss of prediction accuracy from exclusion of X chromosome markers. Conclusions The results from this study suggest that markers on the X chromosome contribute to accuracy of genomic predictions and should be used for routine genomic evaluation. PMID:25080199

A two step Bayesian approach for genomic prediction of breeding values.

PubMed

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.

PubMed

Baker, Stuart G; Kramer, Barnett S

2015-08-01

A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. We organized our discussion around a different theme for each topic. "Fundamentally an extrapolation" refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. "Decision analysis to the rescue" refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. "The appeal of simplicity" refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. © The Author(s) 2014.

Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection.

PubMed

McElroy, Michel S; Navarro, Alberto J R; Mustiga, Guiliana; Stack, Conrad; Gezan, Salvador; Peña, Geover; Sarabia, Widem; Saquicela, Diego; Sotomayor, Ignacio; Douglas, Gavin M; Migicovsky, Zoë; Amores, Freddy; Tarqui, Omar; Myles, Sean; Motamayor, Juan C

2018-01-01

Cacao ( Theobroma cacao ) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches' broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri , respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS) and genomic selection (GS) provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS) and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP) microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod), one of FPRD (monilia pod) and two productivity traits (total fresh weight of pods and % healthy pods produced). GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families), varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom) to 0.15 (monilia pod), and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds substantial promise in accelerating disease-resistance in cacao.

Predicting Violent Behavior: What Can Neuroscience Add?

PubMed

Poldrack, Russell A; Monahan, John; Imrey, Peter B; Reyna, Valerie; Raichle, Marcus E; Faigman, David; Buckholtz, Joshua W

2018-02-01

The ability to accurately predict violence and other forms of serious antisocial behavior would provide important societal benefits, and there is substantial enthusiasm for the potential predictive accuracy of neuroimaging techniques. Here, we review the current status of violence prediction using actuarial and clinical methods, and assess the current state of neuroprediction. We then outline several questions that need to be addressed by future studies of neuroprediction if neuroimaging and other neuroscientific markers are to be successfully translated into public policy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combined panel of serum human tissue kallikreins and CA-125 for the detection of epithelial ovarian cancer.

PubMed

Koh, Stephen Chee Liang; Huak, Chan Yiong; Lutan, Delfi; Marpuang, Johny; Ketut, Suwiyoga; Budiana, Nyoma Gede; Saleh, Agustria Zainu; Aziz, Mohamad Farid; Winarto, Hariyono; Pradjatmo, Heru; Hoan, Nguyen Khac Han; Thanh, Pham Viet; Choolani, Mahesh

2012-07-01

To determine the predictive accuracy of the combined panels of serum human tissue kallikreins (hKs) and CA-125 for the detection of epithelial ovarian cancer. Serum specimens collected from 5 Indonesian centers and 1 Vietnamese center were analyzed for CA-125, hK6, and hK10 levels. A total of 375 specimens from patients presenting with ovarian tumors, which include 156 benign cysts, 172 epithelial ovarian cancers (stage I/II, n=72; stage III/IV, n=100), 36 germ cell tumors and 11 borderline tumors, were included in the study analysis. Receiver operating characteristic analysis were performed to determine the cutoffs for age, CA-125, hK6, and hK10. Sensitivity, specificity, negative, and positive predictive values were determined for various combinations of the biomarkers. The levels of hK6 and hK10 were significantly elevated in ovarian cancer cases compared to benign cysts. Combination of 3 markers, age/CA-125/hk6 or CA-125/hk6/hk10, showed improved specificity (100%) and positive predictive value (100%) for prediction of ovarian cancer, when compared to the performance of single markers having 80-92% specificity and 74-87% positive predictive value. Four-marker combination, age/CA-125/hK6/hK10 also showed 100% specificity and 100% positive predictive value, although it demonstrated low sensitivity (11.9%) and negative predictive value (52.8%). The combination of human tissue kallikreins and CA-125 showed potential for improving prediction of epithelial ovarian cancer in patients presenting with ovarian tumors.

Evaluating surrogate endpoints, prognostic markers, and predictive markers — some simple themes

PubMed Central

Baker, Stuart G.; Kramer, Barnett S.

2014-01-01

Background A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. Methods We organized our discussion around a different theme for each topic. Results “Fundamentally an extrapolation” refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. “Decision analysis to the rescue” refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. “The appeal of simplicity” refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. Conclusion The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. PMID:25385934

Development of EST Intron-Targeting SNP Markers for Panax ginseng and Their Application to Cultivar Authentication.

PubMed

Wang, Hongtao; Li, Guisheng; Kwon, Woo-Saeng; Yang, Deok-Chun

2016-06-04

Panax ginseng is one of the most valuable medicinal plants in the Orient. The low level of genetic variation has limited the application of molecular markers for cultivar authentication and marker-assisted selection in cultivated ginseng. To exploit DNA polymorphism within ginseng cultivars, ginseng expressed sequence tags (ESTs) were searched against the potential intron polymorphism (PIP) database to predict the positions of introns. Intron-flanking primers were then designed in conserved exon regions and used to amplify across the more variable introns. Sequencing results showed that single nucleotide polymorphisms (SNPs), as well as indels, were detected in four EST-derived introns, and SNP markers specific to "Gopoong" and "K-1" were first reported in this study. Based on cultivar-specific SNP sites, allele-specific polymerase chain reaction (PCR) was conducted and proved to be effective for the authentication of ginseng cultivars. Additionally, the combination of a simple NaOH-Tris DNA isolation method and real-time allele-specific PCR assay enabled the high throughput selection of cultivars from ginseng fields. The established real-time allele-specific PCR assay should be applied to molecular authentication and marker assisted selection of P. ginseng cultivars, and the EST intron-targeting strategy will provide a potential approach for marker development in species without whole genomic DNA sequence information.

Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

PubMed Central

2015-01-01

Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610

An evaluation of the genetic-matched pair study design using genome-wide SNP data from the European population.

PubMed

Lu, Timothy Tehua; Lao, Oscar; Nothnagel, Michael; Junge, Olaf; Freitag-Wolf, Sandra; Caliebe, Amke; Balascakova, Miroslava; Bertranpetit, Jaume; Bindoff, Laurence Albert; Comas, David; Holmlund, Gunilla; Kouvatsi, Anastasia; Macek, Milan; Mollet, Isabelle; Nielsen, Finn; Parson, Walther; Palo, Jukka; Ploski, Rafal; Sajantila, Antti; Tagliabracci, Adriano; Gether, Ulrik; Werge, Thomas; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, André Gerardus; Gieger, Christian; Wichmann, Heinz-Erich; Ruether, Andreas; Schreiber, Stefan; Becker, Christian; Nürnberg, Peter; Nelson, Matthew Roberts; Kayser, Manfred; Krawczak, Michael

2009-07-01

Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309,790 markers; Affymetrix GeneChip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given individual, based on the IBS status for the subset alone. However, our results suggest that, by following this approach, the prediction accuracy is only notably improved by the first 20 markers selected, and increases proportionally to the marker number thereafter. Furthermore, in a considerable proportion of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable of predicting the BOM than randomly chosen subsets. This leads us to conclude that, at least in Europe, the utility of the genetic-matched pair study design depends critically on the availability of comprehensive genotype information for both cases and controls.

Can Nucleoli Be Markers of Developmental Potential in Human Zygotes?

PubMed

Fulka, Helena; Kyogoku, Hirohisa; Zatsepina, Olga; Langerova, Alena; Fulka, Josef

2015-11-01

In 1999, Tesarik and Greco reported that they could predict the developmental potential of human zygotes from a single static evaluation of their pronuclei. This was based on the distribution and number of specific nuclear organelles - the nucleoli. Recent studies in mice show that nucleoli play a key role in parental genome restructuring after fertilization, and that interfering with this process may lead to developmental failure. These studies thus support the Tesarik-Greco evaluation as a potentially useful method for selecting high-quality embryos in human assisted reproductive technologies. In this opinion article we discuss recent evidence linking nucleoli to parental genome reprogramming, and ask whether nucleoli can mirror or be used as representative markers of embryonic parameters such as chromosome content or DNA fragmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting strain using forward modelling of restored cross-sections: Application to rollover anticlines over listric normal faults

NASA Astrophysics Data System (ADS)

Poblet, Josep; Bulnes, Mayte

2007-12-01

A strategy to predict strain across geological structures, based on previous techniques, is modified and evaluated, and a practical application is shown. The technique, which employs cross-section restoration combined with kinematic forward modelling, consists of restoring a section, placing circular strain markers on different domains of the restoration, and forward modelling the restored section with strain markers until the present-day stage is reached. The restoration algorithm employed must be also used to forward model the structure. The ellipses in the forward modelled section allow determining the strain state of the structure and may indirectly predict orientation and distribution of minor structures such as small-scale fractures. The forward model may be frozen at different time steps (different growth stages) allowing prediction of both spatial and temporal variation of strain. The method is evaluated through its application to two stages of a clay experiment, that includes strain markers, and its geometry and deformation history are well documented, providing a strong control on the results. To demonstrate the method's potential, it is successfully applied to a depth-converted seismic profile in the Central Sumatra Basin, Indonesia. This allowed us to gain insight into the deformation undergone by rollover anticlines over listric normal faults.

Evaluation of 7 serum biomarkers and uterine artery Doppler ultrasound for first-trimester prediction of preeclampsia: a systematic review.

PubMed

Kuc, Sylwia; Wortelboer, Esther J; van Rijn, Bas B; Franx, Arie; Visser, Gerard H A; Schielen, Peter C J I

2011-04-01

Preeclampsia (PE) affects 1% to 2% of pregnant women and is a leading cause of maternal and perinatal morbidity and mortality worldwide. The clinical syndrome of PE arises in the second half of pregnancy. However, many underlying factors including defective placentation may already be apparent in the first and early second trimester in many patients. In clinical practice, there is currently no reliable screening method in the first trimester of pregnancy with sufficient accuracy to identify women at high risk to develop PE. Early identification of high-risk pregnancy may facilitate the development of new strategies for antenatal surveillance or prevention and thus improve maternal and perinatal outcome. The aim of this systematic review was to study the literature on the predictive potential of first-trimester serum markers and of uterine artery Doppler velocity waveform assessment (Ut-A Doppler). Literature on the 7 most studied serum markers (ADAM12, fβ-hCG, Inhibin A, Activin A, PP13, PlGF, and PAPP-A) and Ut-A Doppler was primarily selected. In the selected literature, a combination of these markers was analyzed, and where relevant, the value of maternal characteristics was added. Measurements of serum markers and Ut-A Doppler were performed between week 8 + 0 and 14 + 0 GA. Low levels of PP13, PlGF, and PAPP-A and elevated level of Inhibin A have been found to be significantly associated with the development of PE later in pregnancy. The detection rates of single markers, fixed at 10% false-positive rate, in the prediction of early-onset PE were relatively low, and ranged from 22% to 83%. Detection rates for combinations of multiple markers varied between 38% and 100%. Therefore, a combination of multiple markers yields high detection rates and is promising to identify patients at high risk of developing PE. However, large scale prospective studies are required to evaluate the power of this integrated approach in clinical practice. Obstetricians and Gynecologists, Family physicians Learning Objectives: After completion of this article, the reader should be better able to appraise the recent literature on the development of preeclampsia in the first-trimester, evaluate the predictive value of first-trimester markers and use first-trimester markers, either individually or in combination, to assess the risk of preeclampsia.

Predictive factors of response to mTOR inhibitors in neuroendocrine tumours.

PubMed

Zatelli, Maria Chiara; Fanciulli, Giuseppe; Malandrino, Pasqualino; Ramundo, Valeria; Faggiano, Antongiulio; Colao, Annamaria

2016-03-01

Medical treatment of neuroendocrine tumours (NETs) has drawn a lot of attention due to the recent demonstration of efficacy of several drugs on progression-free survival, including somatostatin analogs, small tyrosine kinase inhibitors and mTOR inhibitors (or rapalogs). The latter are approved as therapeutic agents in advanced pancreatic NETs and have been demonstrated to be effective in different types of NETs, with variable efficacy due to the development of resistance to treatment. Early detection of patients that may benefit from rapalogs treatment is of paramount importance in order to select the better treatment and avoid ineffective and expensive treatments. Predictive markers for therapeutic response are under intensive investigation, aiming at a tailored patient management and more appropriate resource utilization. This review summarizes the available data on the tissue, circulating and imaging markers that are potentially predictive of rapalog efficacy in NETs. © 2016 Society for Endocrinology.

Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

PubMed Central

Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

2016-01-01

Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

CYR61 and TAZ Upregulation and Focal Epithelial to Mesenchymal Transition May Be Early Predictors of Barrett's Esophagus Malignant Progression.

PubMed

Cardoso, Joana; Mesquita, Marta; Dias Pereira, António; Bettencourt-Dias, Mónica; Chaves, Paula; Pereira-Leal, José B

2016-01-01

Barrett's esophagus is the major risk factor for esophageal adenocarcinoma. It has a low but non-neglectable risk, high surveillance costs and no reliable risk stratification markers. We sought to identify early biomarkers, predictive of Barrett's malignant progression, using a meta-analysis approach on gene expression data. This in silico strategy was followed by experimental validation in a cohort of patients with extended follow up from the Instituto Português de Oncologia de Lisboa de Francisco Gentil EPE (Portugal). Bioinformatics and systems biology approaches singled out two candidate predictive markers for Barrett's progression, CYR61 and TAZ. Although previously implicated in other malignancies and in epithelial-to-mesenchymal transition phenotypes, our experimental validation shows for the first time that CYR61 and TAZ have the potential to be predictive biomarkers for cancer progression. Experimental validation by reverse transcriptase quantitative PCR and immunohistochemistry confirmed the up-regulation of both genes in Barrett's samples associated with high-grade dysplasia/adenocarcinoma. In our cohort CYR61 and TAZ up-regulation ranged from one to ten years prior to progression to adenocarcinoma in Barrett's esophagus index samples. Finally, we found that CYR61 and TAZ over-expression is correlated with early focal signs of epithelial to mesenchymal transition. Our results highlight both CYR61 and TAZ genes as potential predictive biomarkers for stratification of the risk for development of adenocarcinoma and suggest a potential mechanistic route for Barrett's esophagus neoplastic progression.

Pathobiologic Markers of the Ewing Sarcoma Family of Tumors: State of the Art and Prediction of Behaviour

PubMed Central

Pinto, Alfredo; Dickman, Paul; Parham, David

2011-01-01

Over the past three decades, the outcome of Ewing sarcoma family tumor (ESFT) patients who are nonmetastatic at presentation has improved considerably. The prognosis of patients with metastatic disease at the time of diagnosis and recurrence after therapy remains dismal. Drug-resistant disease at diagnosis or at relapse remains a major cause of mortality among patients diagnosed with ESFT. In order to improve the outcome for patients with potential relapse, there is an urgent need to find reliable markers that either predict tumor behaviour at diagnosis or identify therapeutic molecular targets at the time of recurrence. An improved understanding of the cell of origin and the molecular pathways that regulate tumorigenicity in ESFT should aid us in the search for novel therapies for ESFT. The purpose of this paper is thus to outline current concepts of sarcomagenesis in ESFT and to discuss ESFT patterns of differentiation and molecular markers that might affect prognosis or direct future therapeutic development. PMID:20981347

Prognostic Value of Molecular Markers and Implication for Molecular Targeted Therapies in Nasopharyngeal Carcinoma: An Update in an Era of New Targeted Molecules Development.

PubMed

Liu, Mu-Tai; Chen, Mu-Kuan; Huang, Chia-Chun; Huang, Chao-Yuan

2015-02-01

The aim of the study was to evaluate the prognostic significance of molecular biomarkers which could provide information for more accurate prognostication and development of novel therapeutic strategies for nasopharyngeal carcinoma (NPC). NPC is a unique malignant epithelial carcinoma of head and neck region, with an intimate association with the Epstein-Barr virus (EBV). Currently, the prediction of NPC prognosis is mainly based on the clinical TNM staging; however, NPC patients with the same clinical stage often present different clinical outcomes, suggesting that the TNM stage is insufficient to precisely predict the prognosis of this disease. In this review, we give an overview of the prognostic value of molecular markers in NPC and discuss potential strategies of targeted therapies for treatment of NPC. Molecular biomarkers, which play roles in abnormal proliferation signaling pathways (such as Wnt/β-catenin pathway), intracellular mitogenic signal aberration (such as hypoxia-inducible factor (HIF)-1α), receptor-mediated aberrations (such as vascular endothelial growth factor (VEGF)), tumor suppressors (such as p16 and p27 activity), cell cycle aberrations (such as cyclin D1 and cyclin E), cell adhesion aberrations (such as E-cadherin), apoptosis dysregualtion (such as survivin) and centromere aberration (centromere protein H), are prognostic markers for NPC. Plasma EBV DNA concentrations and EBV-encoded latent membrane proteins are also prognostic markers for NPC. Implication of molecular targeted therapies in NPC was discussed. Such therapies could have potential in combination with different cytotoxic agents to combat and eradicate tumor cells. In order to further improve overall survival for patients with loco-regionally advanced NPC, the development of innovative strategies, including prognostic molecular markers and molecular targeted agents is needed.

Development of Raman spectral markers to assess metastatic bone in breast cancer

PubMed Central

Ding, Hao; Nyman, Jeffry S.; Sterling, Julie A.; Perrien, Daniel S.; Mahadevan-Jansen, Anita; Bi, Xiaohong

2014-01-01

Abstract. Bone is the most common site for breast cancer metastases. One of the major complications of bone metastasis is pathological bone fracture caused by chronic bone loss and degeneration. Current guidelines for the prediction of pathological fracture mainly rely on radiographs or computed tomography, which are limited in their ability to predict fracture risk. The present study explored the feasibility of using Raman spectroscopy to estimate pathological fracture risk by characterizing the alterations in the compositional properties of metastatic bones. Tibiae with evident bone destruction were investigated using Raman spectroscopy. The carbonation level calculated by the ratio of carbonate/phosphate ν1 significantly increased in the tumor-bearing bone at all the sampling regions at the proximal metaphysis and diaphysis, while tumor-induced elevation in mineralization and crystallinity was more pronounced in the metaphysis. Furthermore, the increased carbonation level is positively correlated to bone lesion size, indicating that this parameter could serve as a unique spectral marker for tumor progression and bone loss. With the promising advances in the development of spatially offset Raman spectroscopy for deep tissue measurement, this spectral marker can potentially be used for future noninvasive evaluation of metastatic bone and prediction of pathological fracture risk. PMID:24933683

Development of Raman spectral markers to assess metastatic bone in breast cancer

NASA Astrophysics Data System (ADS)

Ding, Hao; Nyman, Jeffry S.; Sterling, Julie A.; Perrien, Daniel S.; Mahadevan-Jansen, Anita; Bi, Xiaohong

2014-11-01

Bone is the most common site for breast cancer metastases. One of the major complications of bone metastasis is pathological bone fracture caused by chronic bone loss and degeneration. Current guidelines for the prediction of pathological fracture mainly rely on radiographs or computed tomography, which are limited in their ability to predict fracture risk. The present study explored the feasibility of using Raman spectroscopy to estimate pathological fracture risk by characterizing the alterations in the compositional properties of metastatic bones. Tibiae with evident bone destruction were investigated using Raman spectroscopy. The carbonation level calculated by the ratio of carbonate/phosphate ν1 significantly increased in the tumor-bearing bone at all the sampling regions at the proximal metaphysis and diaphysis, while tumor-induced elevation in mineralization and crystallinity was more pronounced in the metaphysis. Furthermore, the increased carbonation level is positively correlated to bone lesion size, indicating that this parameter could serve as a unique spectral marker for tumor progression and bone loss. With the promising advances in the development of spatially offset Raman spectroscopy for deep tissue measurement, this spectral marker can potentially be used for future noninvasive evaluation of metastatic bone and prediction of pathological fracture risk.

Predicting bone mineral acquisition during puberty: data from a 3-year follow-up study in Hamamatsu, Japan.

PubMed

Kouda, Katsuyasu; Ohara, Kumiko; Nakamura, Harunobu; Fujita, Yuki; Iki, Masayuki

2017-03-01

Although most adult bone mass is acquired before adolescence, only a few studies have assessed bone turnover markers in children. Thus, the utility of bone markers to evaluate and predict bone mineral accrual in children is unclear. The present study assessed the association between serum bone markers at 11 years of age and subsequent changes in bone gain. Information on bone minerals and bone markers at baseline and at the 3-year follow-up were obtained from 121 children who registered as fifth-grade students in 2010, in Hamamatsu, Japan. Whole-body bone mineral content (WBBMC) and whole-body bone mineral density (WBBMD) were measured using dual-energy X-ray absorptiometry. Boys showed significant (P < 0.05) positive relationships between intact osteocalcin at baseline and WBBMC at follow-up (β = 0.24), between tartrate-resistant acid phosphatase isoenzyme 5b (TRAP5b) and WBBMC (β = 0.34), and between TRAP5b and WBBMD (β = 0.34), after adjusting for potential confounding factors. In girls, adjusted means of 3-year gain in both WBBMC and WBBMD significantly increased from the lowest to highest quartiles of type 1 collagen cross-linked C-terminal telopeptide. In boys, adjusted means of 3-year gain in both WBBMC and WBBMD significantly increased from the lowest to highest quartiles of TRAP5b. Children with a high concentration of bone turnover markers tended to exhibit substantial accrual of bone minerals. These results suggest that serum levels of circulating biomarkers at age 11 predict subsequent bone mineral accrual.

Molecular markers for urothelial bladder cancer prognosis: toward implementation in clinical practice.

PubMed

van Rhijn, Bas W G; Catto, James W; Goebell, Peter J; Knüchel, Ruth; Shariat, Shahrokh F; van der Poel, Henk G; Sanchez-Carbayo, Marta; Thalmann, George N; Schmitz-Dräger, Bernd J; Kiemeney, Lambertus A

2014-10-01

To summarize the current status of clinicopathological and molecular markers for the prediction of recurrence or progression or both in non-muscle-invasive and survival in muscle-invasive urothelial bladder cancer, to address the reproducibility of pathology and molecular markers, and to provide directions toward implementation of molecular markers in future clinical decision making. Immunohistochemistry, gene signatures, and FGFR3-based molecular grading were used as molecular examples focussing on prognostics and issues related to robustness of pathological and molecular assays. The role of molecular markers to predict recurrence is limited, as clinical variables are currently more important. The prediction of progression and survival using molecular markers holds considerable promise. Despite a plethora of prognostic (clinical and molecular) marker studies, reproducibility of pathology and molecular assays has been understudied, and lack of reproducibility is probably the main reason that individual prediction of disease outcome is currently not reliable. Molecular markers are promising to predict progression and survival, but not recurrence. However, none of these are used in the daily clinical routine because of reproducibility issues. Future studies should focus on reproducibility of marker assessment and consistency of study results by incorporating scoring systems to reduce heterogeneity of reporting. This may ultimately lead to incorporation of molecular markers in clinical practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP effects (SNP-BLUP model). When reducing marker density from WGS data to 30 K, SNP-BLUP tended to yield the highest accuracies, at least in the short term. Based on SVD of the genotype matrix, we developed a direct method for the calculation of BayesC estimates of marker effects. Although SVD- and MCMC-based marker effects differed slightly, their prediction accuracies were similar. Assuming that the SVD of the marker genotype matrix is already performed for other reasons (e.g. for SNP-BLUP), computation times for the BayesC predictions were comparable to those of SNP-BLUP.

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Short communication: Improving the accuracy of genomic prediction of body conformation traits in Chinese Holsteins using markers derived from high-density marker panels.

PubMed

Song, H; Li, L; Ma, P; Zhang, S; Su, G; Lund, M S; Zhang, Q; Ding, X

2018-06-01

This study investigated the efficiency of genomic prediction with adding the markers identified by genome-wide association study (GWAS) using a data set of imputed high-density (HD) markers from 54K markers in Chinese Holsteins. Among 3,056 Chinese Holsteins with imputed HD data, 2,401 individuals born before October 1, 2009, were used for GWAS and a reference population for genomic prediction, and the 220 younger cows were used as a validation population. In total, 1,403, 1,536, and 1,383 significant single nucleotide polymorphisms (SNP; false discovery rate at 0.05) associated with conformation final score, mammary system, and feet and legs were identified, respectively. About 2 to 3% genetic variance of 3 traits was explained by these significant SNP. Only a very small proportion of significant SNP identified by GWAS was included in the 54K marker panel. Three new marker sets (54K+) were herein produced by adding significant SNP obtained by linear mixed model for each trait into the 54K marker panel. Genomic breeding values were predicted using a Bayesian variable selection (BVS) model. The accuracies of genomic breeding value by BVS based on the 54K+ data were 2.0 to 5.2% higher than those based on the 54K data. The imputed HD markers yielded 1.4% higher accuracy on average (BVS) than the 54K data. Both the 54K+ and HD data generated lower bias of genomic prediction, and the 54K+ data yielded the lowest bias in all situations. Our results show that the imputed HD data were not very useful for improving the accuracy of genomic prediction and that adding the significant markers derived from the imputed HD marker panel could improve the accuracy of genomic prediction and decrease the bias of genomic prediction. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy

NASA Astrophysics Data System (ADS)

Qiu, Peng; D'Souza, Warren D.; McAvoy, Thomas J.; Liu, K. J. Ray

2007-09-01

Tumor motion induced by respiration presents a challenge to the reliable delivery of conformal radiation treatments. Real-time motion compensation represents the technologically most challenging clinical solution but has the potential to overcome the limitations of existing methods. The performance of a real-time couch-based motion compensation system is mainly dependent on two aspects: the ability to infer the internal anatomical position and the performance of the feedback control system. In this paper, we propose two novel methods for the two aspects respectively, and then combine the proposed methods into one system. To accurately estimate the internal tumor position, we present partial-least squares (PLS) regression to predict the position of the diaphragm using skin-based motion surrogates. Four radio-opaque markers were placed on the abdomen of patients who underwent fluoroscopic imaging of the diaphragm. The coordinates of the markers served as input variables and the position of the diaphragm served as the output variable. PLS resulted in lower prediction errors compared with standard multiple linear regression (MLR). The performance of the feedback control system depends on the system dynamics and dead time (delay between the initiation and execution of the control action). While the dynamics of the system can be inverted in a feedback control system, the dead time cannot be inverted. To overcome the dead time of the system, we propose a predictive feedback control system by incorporating forward prediction using least-mean-square (LMS) and recursive least square (RLS) filtering into the couch-based control system. Motion data were obtained using a skin-based marker. The proposed predictive feedback control system was benchmarked against pure feedback control (no forward prediction) and resulted in a significant performance gain. Finally, we combined the PLS inference model and the predictive feedback control to evaluate the overall performance of the feedback control system. Our results show that, with the tumor motion unknown but inferred by skin-based markers through the PLS model, the predictive feedback control system was able to effectively compensate intra-fraction motion.

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers

PubMed Central

Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.

2018-01-01

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

PubMed

Jiang, Yong; Schmidt, Renate H; Reif, Jochen C

2018-05-04

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.

Some ethylene biosynthesis and AP2/ERF genes reveal a specific pattern of expression during somatic embryogenesis in Hevea brasiliensis

PubMed Central

2012-01-01

Background Ethylene production and signalling play an important role in somatic embryogenesis, especially for species that are recalcitrant in in vitro culture. The AP2/ERF superfamily has been identified and classified in Hevea brasiliensis. This superfamily includes the ERFs involved in response to ethylene. The relative transcript abundance of ethylene biosynthesis genes and of AP2/ERF genes was analysed during somatic embryogenesis for callus lines with different regeneration potential, in order to identify genes regulated during that process. Results The analysis of relative transcript abundance was carried out by real-time RT-PCR for 142 genes. The transcripts of ERFs from group I, VII and VIII were abundant at all stages of the somatic embryogenesis process. Forty genetic expression markers for callus regeneration capacity were identified. Fourteen markers were found for proliferating calli and 35 markers for calli at the end of the embryogenesis induction phase. Sixteen markers discriminated between normal and abnormal embryos and, lastly, there were 36 markers of conversion into plantlets. A phylogenetic analysis comparing the sequences of the AP2 domains of Hevea and Arabidopsis genes enabled us to predict the function of 13 expression marker genes. Conclusions This first characterization of the AP2/ERF superfamily in Hevea revealed dramatic regulation of the expression of AP2/ERF genes during the somatic embryogenesis process. The gene expression markers of proliferating callus capacity to regenerate plants by somatic embryogenesis should make it possible to predict callus lines suitable to be used for multiplication. Further functional characterization of these markers opens up prospects for discovering specific AP2/ERF functions in the Hevea species for which somatic embryogenesis is difficult. PMID:23268714

Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia

PubMed Central

Iwata, Hiroyoshi; Hayashi, Takeshi; Terakami, Shingo; Takada, Norio; Sawamura, Yutaka; Yamamoto, Toshiya

2013-01-01

Although the potential of marker-assisted selection (MAS) in fruit tree breeding has been reported, bi-parental QTL mapping before MAS has hindered the introduction of MAS to fruit tree breeding programs. Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. Selection based on genomic predictions of breeding values (genomic selection: GS) is another alternative for MAS. This study examined the potential of GWAS and GS in pear breeding with 76 Japanese pear cultivars to detect significant associations of 162 markers with nine agronomic traits. We applied multilocus Bayesian models accounting for ordinal categorical phenotypes for GWAS and GS model training. Significant associations were detected at harvest time, black spot resistance and the number of spurs and two of the associations were closely linked to known loci. Genome-wide predictions for GS were accurate at the highest level (0.75) in harvest time, at medium levels (0.38–0.61) in resistance to black spot, firmness of flesh, fruit shape in longitudinal section, fruit size, acid content and number of spurs and at low levels (<0.2) in all soluble solid content and vigor of tree. Results suggest the potential of GWAS and GS for use in future breeding programs in Japanese pear. PMID:23641189

Development of EST Intron-Targeting SNP Markers for Panax ginseng and Their Application to Cultivar Authentication

PubMed Central

Wang, Hongtao; Li, Guisheng; Kwon, Woo-Saeng; Yang, Deok-Chun

2016-01-01

Panax ginseng is one of the most valuable medicinal plants in the Orient. The low level of genetic variation has limited the application of molecular markers for cultivar authentication and marker-assisted selection in cultivated ginseng. To exploit DNA polymorphism within ginseng cultivars, ginseng expressed sequence tags (ESTs) were searched against the potential intron polymorphism (PIP) database to predict the positions of introns. Intron-flanking primers were then designed in conserved exon regions and used to amplify across the more variable introns. Sequencing results showed that single nucleotide polymorphisms (SNPs), as well as indels, were detected in four EST-derived introns, and SNP markers specific to “Gopoong” and “K-1” were first reported in this study. Based on cultivar-specific SNP sites, allele-specific polymerase chain reaction (PCR) was conducted and proved to be effective for the authentication of ginseng cultivars. Additionally, the combination of a simple NaOH-Tris DNA isolation method and real-time allele-specific PCR assay enabled the high throughput selection of cultivars from ginseng fields. The established real-time allele-specific PCR assay should be applied to molecular authentication and marker assisted selection of P. ginseng cultivars, and the EST intron-targeting strategy will provide a potential approach for marker development in species without whole genomic DNA sequence information. PMID:27271615

BJ-TSA-9, a novel human tumor-specific gene, has potential as a biomarker of lung cancer.

PubMed

Li, Yunyan; Dong, Xueyuan; Yin, Yanhui; Su, Yanrong; Xu, Qingwen; Zhang, Yuxia; Pang, Xuewen; Zhang, Yu; Chen, Weifeng

2005-12-01

Using bioinformatics, we have identified a novel tumor-specific gene BJ-TSA-9, which has been validated by Northern blot analysis and reverse transcription-polymerase chain reaction (RT-PCR). BJ-TSA-9 mRNA was expressed in 52.5% (21 of 40) of human lung cancer tissues and was especially higher in lung adenocarcinoma (68.8%). To explore the potential application of BJ-TSA-9 for the detection of circulating cancer cells in lung cancer patients, nested RT-PCR was performed. The overall positive detection rate was 34.3% (24 of 70) in peripheral blood mononuclear cells (PBMCs) of patients with various types of lung cancers and was 53.6% (15 of 28) in PBMCs of lung adenocarcinoma patients. In combination with the detection of two known marker genes SCC and LUNX, the detection rate was increased to 81.4%. A follow-up study was performed in 37 patients after surgical removal of tumor mass. Among nine patients with persistent detection of two to three tumor marker transcripts in PBMCs, six patients had recurrence/metastasis. In contrast, 28 patients with transient detection of one tumor marker or without detection of any tumor marker were all in remission. Thus, BJ-TSA-9 may serve as a marker for lung cancer diagnosis and as a marker, in combination with two other tumor markers, for the prediction of the recurrence and prognosis of lung cancer patients.

[Neuroimaging and Blood Biomarkers in Functional Prognosis after Stroke].

PubMed

Branco, João Paulo; Costa, Joana Santos; Sargento-Freitas, João; Oliveira, Sandra; Mendes, Bruno; Laíns, Jorge; Pinheiro, João

2016-11-01

Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke. Review of the literature published between 2005 and 2015, in English, using the terms "ischemic stroke", "neuroimaging" e "blood biomarkers". We included nine studies, based on abstract reading. Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke's volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide. Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional prognosis after ischemic stroke.

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias.

PubMed

Clarke, Laurence J; Soubrier, Julien; Weyrich, Laura S; Cooper, Alan

2014-11-01

Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR-amplified the blend using five primer sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers. © 2014 John Wiley & Sons Ltd.

Ratio of mean platelet volume to platelet count is a potential surrogate marker predicting liver cirrhosis.

PubMed

Iida, Hiroya; Kaibori, Masaki; Matsui, Kosuke; Ishizaki, Morihiko; Kon, Masanori

2018-01-27

To provide a simple surrogate marker predictive of liver cirrhosis (LC). Specimens from 302 patients who underwent resection for hepatocellular carcinoma between January 2006 and December 2012 were retrospectively analyzed. Based on pathologic findings, patients were divided into groups based on whether or not they had LC. Parameters associated with hepatic functional reserve were compared in these two groups using Mann-Whitney U -test for univariate analysis. Factors differing significantly in univariate analyses were entered into multivariate logistic regression analysis. There were significant differences between the LC group ( n = 100) and non-LC group ( n = 202) in prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin, albumin, cholinesterase, type IV collagen, hyaluronic acid, indocyanine green retention rate at 15 min, maximal removal rate of technitium-99m diethylene triamine penta-acetic acid-galactosyl human serum albumin and ratio of mean platelet volume to platelet count (MPV/PLT). Multivariate analysis showed that prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin and hyaluronic acid, and MPV/PLT ratio were factors independently predictive of LC. The area under the curve value for MPV/PLT was 0.78, with a 0.8 cutoff value having a sensitivity of 65% and a specificity of 78%. The MPV/PLT ratio, which can be determined simply from the complete blood count, may be a simple surrogate marker predicting LC.

Biochemical markers for prediction of preclampsia: review of the literature

PubMed Central

Monte, Santo

2011-01-01

Preeclampsia (PE) is one of the most common diseases worldwide, complicating ~5% of all pregnancies. Although no major progress has been achieved in the treatment of PE, our ability to identify women at highrisk has increased considerably during the past decade. The early identification of patients with an increased risk for preeclampsia is therefore one of the most important goals in obstetrics. Today, several markers may offer the potential to be used, most likely in a combinatory analysis, as predictors or diagnostic tools. We present here the current knowledge on the biology of preeclampsia and review several biochemical markers which may be used to monitor preeclampsia in a future, that, we hope, is not to distant from today. PMID:22439080

Biochemical markers for prediction of preclampsia: review of the literature.

PubMed

Monte, Santo

2011-07-01

Preeclampsia (PE) is one of the most common diseases worldwide, complicating ~5% of all pregnancies.Although no major progress has been achieved in the treatment of PE, our ability to identify women at highrisk has increased considerably during the past decade.The early identification of patients with an increased risk for preeclampsia is therefore one of the most important goals in obstetrics. Today, several markers may offer the potential to be used, most likely in a combinatory analysis, as predictors or diagnostic tools. We present here the current knowledge on the biology of preeclampsia and review several biochemical markers which may be used to monitor preeclampsia in a future, that, we hope, is not to distant from today.

CYR61 and TAZ Upregulation and Focal Epithelial to Mesenchymal Transition May Be Early Predictors of Barrett’s Esophagus Malignant Progression

PubMed Central

Mesquita, Marta; Dias Pereira, António; Bettencourt-Dias, Mónica; Chaves, Paula; Pereira-Leal, José B.

2016-01-01

Barrett’s esophagus is the major risk factor for esophageal adenocarcinoma. It has a low but non-neglectable risk, high surveillance costs and no reliable risk stratification markers. We sought to identify early biomarkers, predictive of Barrett’s malignant progression, using a meta-analysis approach on gene expression data. This in silico strategy was followed by experimental validation in a cohort of patients with extended follow up from the Instituto Português de Oncologia de Lisboa de Francisco Gentil EPE (Portugal). Bioinformatics and systems biology approaches singled out two candidate predictive markers for Barrett’s progression, CYR61 and TAZ. Although previously implicated in other malignancies and in epithelial-to-mesenchymal transition phenotypes, our experimental validation shows for the first time that CYR61 and TAZ have the potential to be predictive biomarkers for cancer progression. Experimental validation by reverse transcriptase quantitative PCR and immunohistochemistry confirmed the up-regulation of both genes in Barrett’s samples associated with high-grade dysplasia/adenocarcinoma. In our cohort CYR61 and TAZ up-regulation ranged from one to ten years prior to progression to adenocarcinoma in Barrett’s esophagus index samples. Finally, we found that CYR61 and TAZ over-expression is correlated with early focal signs of epithelial to mesenchymal transition. Our results highlight both CYR61 and TAZ genes as potential predictive biomarkers for stratification of the risk for development of adenocarcinoma and suggest a potential mechanistic route for Barrett’s esophagus neoplastic progression. PMID:27583562

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

PubMed Central

2013-01-01

Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

Improving lung cancer prognosis assessment by incorporating synthetic minority oversampling technique and score fusion method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Shiju; Qian, Wei; Guan, Yubao

2016-06-15

Purpose: This study aims to investigate the potential to improve lung cancer recurrence risk prediction performance for stage I NSCLS patients by integrating oversampling, feature selection, and score fusion techniques and develop an optimal prediction model. Methods: A dataset involving 94 early stage lung cancer patients was retrospectively assembled, which includes CT images, nine clinical and biological (CB) markers, and outcome of 3-yr disease-free survival (DFS) after surgery. Among the 94 patients, 74 remained DFS and 20 had cancer recurrence. Applying a computer-aided detection scheme, tumors were segmented from the CT images and 35 quantitative image (QI) features were initiallymore » computed. Two normalized Gaussian radial basis function network (RBFN) based classifiers were built based on QI features and CB markers separately. To improve prediction performance, the authors applied a synthetic minority oversampling technique (SMOTE) and a BestFirst based feature selection method to optimize the classifiers and also tested fusion methods to combine QI and CB based prediction results. Results: Using a leave-one-case-out cross-validation (K-fold cross-validation) method, the computed areas under a receiver operating characteristic curve (AUCs) were 0.716 ± 0.071 and 0.642 ± 0.061, when using the QI and CB based classifiers, respectively. By fusion of the scores generated by the two classifiers, AUC significantly increased to 0.859 ± 0.052 (p < 0.05) with an overall prediction accuracy of 89.4%. Conclusions: This study demonstrated the feasibility of improving prediction performance by integrating SMOTE, feature selection, and score fusion techniques. Combining QI features and CB markers and performing SMOTE prior to feature selection in classifier training enabled RBFN based classifier to yield improved prediction accuracy.« less

Chemoreception of hunger levels alters the following behaviour of a freshwater snail.

PubMed

Larcher, Marie; Crane, Adam L

2015-12-01

Chemically-mediated orientation is essential for many animals that must locate sites containing resources such as mates or food. One way to find these areas is by using publically-available information from other individuals. We tested a freshwater snail, Physa gyrina, for chemoreception of conspecific cues and predicted they could discriminate between cues based on information regarding hunger levels. We placed 'tracker' snails into a 2-arm arena where they could either follow or avoid an area previously used by a 'marker' snail. The hunger levels of both trackers and markers was manipulated, being either starved or fed. Starved and fed trackers did not differ in their following response when markers were hungry, but starved trackers were significantly more likely to follow fed markers, compared to fed trackers that tended to avoid areas used by fed markers. This outcome suggests that P. gyrina uses conspecific chemical cues to find food and potentially in some situations to avoid intra-specific food competition. Copyright © 2015 Elsevier B.V. All rights reserved.

Additive Genetic Variability and the Bayesian Alphabet

PubMed Central

Gianola, Daniel; de los Campos, Gustavo; Hill, William G.; Manfredi, Eduardo; Fernando, Rohan

2009-01-01

The use of all available molecular markers in statistical models for prediction of quantitative traits has led to what could be termed a genomic-assisted selection paradigm in animal and plant breeding. This article provides a critical review of some theoretical and statistical concepts in the context of genomic-assisted genetic evaluation of animals and crops. First, relationships between the (Bayesian) variance of marker effects in some regression models and additive genetic variance are examined under standard assumptions. Second, the connection between marker genotypes and resemblance between relatives is explored, and linkages between a marker-based model and the infinitesimal model are reviewed. Third, issues associated with the use of Bayesian models for marker-assisted selection, with a focus on the role of the priors, are examined from a theoretical angle. The sensitivity of a Bayesian specification that has been proposed (called “Bayes A”) with respect to priors is illustrated with a simulation. Methods that can solve potential shortcomings of some of these Bayesian regression procedures are discussed briefly. PMID:19620397

Accuracy of Genomic Prediction in Switchgrass (Panicum virgatum L.) Improved by Accounting for Linkage Disequilibrium

PubMed Central

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.; Mitchell, Robert B.; Vogel, Kenneth P.; Buell, C. Robin; Casler, Michael D.

2016-01-01

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height, and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs. PMID:26869619

Long-term culture and cryopreservation does not affect the stability and functionality of human embryonic stem cell-derived hepatocyte-like cells.

PubMed

Mandal, Arundhati; Raju, Sheena; Viswanathan, Chandra

2016-02-01

Human embryonic stem cells (hESCs) are predicted to be an unlimited source of hepatocytes which can pave the way for applications such as cell replacement therapies or as a model of human development or even to predict the hepatotoxicity of drug compounds. We have optimized a 23-d differentiation protocol to generate hepatocyte-like cells (HLCs) from hESCs, obtaining a relatively pure population which expresses the major hepatic markers and is functional and mature. The stability of the HLCs in terms of hepato-specific marker expression and functionality was found to be intact even after an extended period of in vitro culture and cryopreservation. The hESC-derived HLCs have shown the capability to display sensitivity and an alteration in the level of CYP enzyme upon drug induction. This illustrates the potential of such assays in predicting the hepatotoxicity of a drug compound leading to advancement of pharmacology.

Unlocking Diversity in Germplasm Collections via Genomic Selection: A Case Study Based on Quantitative Adult Plant Resistance to Stripe Rust in Spring Wheat.

PubMed

Muleta, Kebede T; Bulli, Peter; Zhang, Zhiwu; Chen, Xianming; Pumphrey, Michael

2017-11-01

Harnessing diversity from germplasm collections is more feasible today because of the development of lower-cost and higher-throughput genotyping methods. However, the cost of phenotyping is still generally high, so efficient methods of sampling and exploiting useful diversity are needed. Genomic selection (GS) has the potential to enhance the use of desirable genetic variation in germplasm collections through predicting the genomic estimated breeding values (GEBVs) for all traits that have been measured. Here, we evaluated the effects of various scenarios of population genetic properties and marker density on the accuracy of GEBVs in the context of applying GS for wheat ( L.) germplasm use. Empirical data for adult plant resistance to stripe rust ( f. sp. ) collected on 1163 spring wheat accessions and genotypic data based on the wheat 9K single nucleotide polymorphism (SNP) iSelect assay were used for various genomic prediction tests. Unsurprisingly, the results of the cross-validation tests demonstrated that prediction accuracy increased with an increase in training population size and marker density. It was evident that using all the available markers (5619) was unnecessary for capturing the trait variation in the germplasm collection, with no further gain in prediction accuracy beyond 1 SNP per 3.2 cM (∼1850 markers), which is close to the linkage disequilibrium decay rate in this population. Collectively, our results suggest that larger germplasm collections may be efficiently sampled via lower-density genotyping methods, whereas genetic relationships between the training and validation populations remain critical when exploiting GS to select from germplasm collections. Copyright © 2017 Crop Science Society of America.

Genomic selection in sugar beet breeding populations.

PubMed

Würschum, Tobias; Reif, Jochen C; Kraft, Thomas; Janssen, Geert; Zhao, Yusheng

2013-09-18

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.

Circulating microRNA are predictive of aging and acute adaptive response to resistance exercise in men

USDA-ARS?s Scientific Manuscript database

Circulating microRNA (c-miRNA) have the potential to function as novel noninvasive markers of the underlying physiological state of skeletal muscle. This investigation sought to determine the influence of aging on c-miRNA expression at rest and following resistance exercise in male volunteers (Young...

Prognostic and predictive factors in colorectal cancer.

PubMed

Bolocan, A; Ion, D; Ciocan, D N; Paduraru, D N

2012-01-01

Colorectal cancer (CRC) is an important public health problem; it is a leading cause of cancer mortality in the industrialized world, second to lung cancer: each year there are nearly one million new cases of CRC diagnosed worldwide and half a million deaths (1). This review aims to summarise the most important currently available markers for CRC that provide prognostic or predictive information. Amongst others, it covers serum markers such as CEA and CA19-9, markers expressed by tumour tissues, such as thymidylate synthase, and also the expression/loss of expression of certain oncogenes and tumour suppressor genes such as K-ras and p53. The prognostic value of genomic instability, angiogenesis and proliferative indices, such as the apoptotic index, are discussed. The advent of new therapies created the pathway for a personalized approach of the patient. This will take into consideration the complex genetic mechanisms involved in tumorigenesis, besides the classical clinical and pathological stagings. The growing number of therapeutic agents and known molecular targets in oncology lead to a compulsory study of the clinical use of biomarkers with role in improving response and survival, as well as in reducing toxicity and establishing economic stability. The potential predictive and prognostic biomarkers which have arisen from the study of the genetic basis of colorectal cancer and their therapeutical significance are discussed. RevistaChirurgia.

Why humans deviate from rational choice.

PubMed

Hewig, Johannes; Kretschmer, Nora; Trippe, Ralf H; Hecht, Holger; Coles, Michael G H; Holroyd, Clay B; Miltner, Wolfgang H R

2011-04-01

Rational choice theory predicts that humans always optimize the expected utility of options when making decisions. However, in decision-making games, humans often punish their opponents even when doing so reduces their own reward. We used the Ultimatum and Dictator games to examine the affective correlates of decision-making. We show that the feedback negativity, an event-related brain potential that originates in the anterior cingulate cortex that has been related to reinforcement learning, predicts the decision to reject unfair offers in the Ultimatum game. Furthermore, the decision to reject is positively related to more negative emotional reactions and to increased autonomic nervous system activity. These findings support the idea that subjective emotional markers guide decision-making and that the anterior cingulate cortex integrates instances of reinforcement and punishment to provide such affective markers. Copyright © 2010 Society for Psychophysiological Research.

MAP3K8/TPL-2/COT is a potential predictive marker for MEK inhibitor treatment in high-grade serous ovarian carcinomas.

PubMed

Gruosso, Tina; Garnier, Camille; Abelanet, Sophie; Kieffer, Yann; Lemesre, Vincent; Bellanger, Dorine; Bieche, Ivan; Marangoni, Elisabetta; Sastre-Garau, Xavier; Mieulet, Virginie; Mechta-Grigoriou, Fatima

2015-10-12

Ovarian cancer is a silent disease with a poor prognosis that urgently requires new therapeutic strategies. In low-grade ovarian tumours, mutations in the MAP3K BRAF gene constitutively activate the downstream kinase MEK. Here we demonstrate that an additional MAP3K, MAP3K8 (TPL-2/COT), accumulates in high-grade serous ovarian carcinomas (HGSCs) and is a potential prognostic marker for these tumours. By combining analyses on HGSC patient cohorts, ovarian cancer cells and patient-derived xenografts, we demonstrate that MAP3K8 controls cancer cell proliferation and migration by regulating key players in G1/S transition and adhesion dynamics. In addition, we show that the MEK pathway is the main pathway involved in mediating MAP3K8 function, and that MAP3K8 exhibits a reliable predictive value for the effectiveness of MEK inhibitor treatment. Our data highlight key roles for MAP3K8 in HGSC and indicate that MEK inhibitors could be a useful treatment strategy, in combination with conventional chemotherapy, for this disease.

A potential germ cell-specific marker in Japanese flounder, Paralichthys olivaceus: identification and characterization of lymphocyte antigen 75 (Ly75/CD205)

NASA Astrophysics Data System (ADS)

Yang, Yang; Liu, Qinghua; Ma, Daoyuan; Song, Zongchen; Li, Jun

2018-04-01

Some germ cell marker genes, such as vasa, nanos, and dead end (dnd), have been identified in fish. Recently, lymphocyte antigen 75 (Ly75/CD205) has been identified as a mitotic germ cell-specific cell-surface marker in several fish species. In this study, the Japanese flounder ly75 homolog (ly75) was cloned and its expression pattern in gonads was analyzed. The full-length cDNA of ly75 was 7 346 bp, with an open reading frame (ORF) of 5 229 bp. The ORF encoded a protein containing 1 742 amino acids with a predicted molecular mass of 196.89 kDa. In adult tissues, ly75 transcripts were detected in all analyzed tissues but abundantly in the testis. In in-situ hybridization analyses, ly75 mRNA was predominantly localized in oocytes in the ovary and spermatogonia in the testis, but ly75 mRNA was not detected in oogonia, spermatocytes, spermatids, or spermatozoa. These results indicated that ly75 could be a potential germ cell-specific marker in P. olivaceus, as in other fishes.

A 4-gene panel as a marker at chromosome 8q in Asian gastric cancer patients.

PubMed

Cheng, Lei; Zhang, Qing; Yang, Sheng; Yang, Yanqing; Zhang, Wen; Gao, Hengjun; Deng, Xiaxing; Zhang, Qinghua

2013-10-01

A widely held viewpoint is that the use of multiple markers, combined in some type of algorithm, will be necessary to provide high enough discrimination between diseased cases and non-diseased. We applied stepwise logistic regression analysis to identify the best combination of the 32 biomarkers at chromosome 8q on an independent public microarray test set of 80 paired gastric samples. A combination of SULF1, INTS8, ATP6V1C1, and GPR172A was identified with a prediction accuracy of 98.0% for discriminating carcinomas from adjacent noncancerous tissues in our previous 25 paired samples. Interestingly, the overexpression of SULF1 was associated with tumor invasion and metastasis. Function prediction analysis revealed that the 4-marker panel was mainly associated with acidification of intracellular compartments. Taken together, we found a 4-gene panel that accurately discriminated gastric carcinomas from adjacent noncancerous tissues and these results had potential clinical significance in the early diagnosis and targeted treatment of gastric cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

Inferring biomarkers for Mycobacterium avium subsp. paratuberculosis infection and disease progression in cattle using experimental data

NASA Astrophysics Data System (ADS)

Magombedze, Gesham; Shiri, Tinevimbo; Eda, Shigetoshi; Stabel, Judy R.

2017-03-01

Available diagnostic assays for Mycobacterium avium subsp. paratuberculosis (MAP) have poor sensitivities and cannot detect early stages of infection, therefore, there is need to find new diagnostic markers for early infection detection and disease stages. We analyzed longitudinal IFN-γ, ELISA-antibody and fecal shedding experimental sensitivity scores for MAP infection detection and disease progression. We used both statistical methods and dynamic mathematical models to (i) evaluate the empirical assays (ii) infer and explain biological mechanisms that affect the time evolution of the biomarkers, and (iii) predict disease stages of 57 animals that were naturally infected with MAP. This analysis confirms that the fecal test is the best marker for disease progression and illustrates that Th1/Th2 (IFN-γ/ELISA antibodies) assays are important for infection detection, but cannot reliably predict persistent infections. Our results show that the theoretical simulated macrophage-based assay is a potential good diagnostic marker for MAP persistent infections and predictor of disease specific stages. We therefore recommend specifically designed experiments to test the use of a based assay in the diagnosis of MAP infections.

Activin in acute pancreatitis: Potential risk-stratifying marker and novel therapeutic target.

PubMed

Staudacher, Jonas J; Yazici, Cemal; Carroll, Timothy; Bauer, Jessica; Pang, Jingbo; Krett, Nancy; Xia, Yinglin; Wilson, Annette; Papachristou, Georgios; Dirmeier, Andrea; Kunst, Claudia; Whitcomb, David C; Fantuzzi, Giamila; Jung, Barbara

2017-10-06

Acute Pancreatitis is a substantial health care challenge with increasing incidence. Patients who develop severe disease have considerable mortality. Currently, no reliable predictive marker to identify patients at risk for severe disease exists. Treatment is limited to rehydration and supporting care suggesting an urgent need to develop novel approaches to improve standard care. Activin is a critical modulator of inflammatory responses, but has not been assessed in pancreatitis. Here, we demonstrate that serum activin is elevated and strongly correlates with disease severity in two established murine models of acute pancreatitis induced by either cerulein or IL-12 + IL-18. Furthermore, in mice, inhibition of activin conveys survival benefits in pancreatitis. In addition, serum activin levels were measured from a retrospective clinical cohort of pancreatitis patients and high activin levels in patients at admission are predictive of worse outcomes, indicated by longer overall hospital and intensive care unit stays. Taken together, activin is a novel candidate as a clinical marker to identify those acute pancreatitis patients with severe disease who would benefit from aggressive treatment and activin may be a therapeutic target in severe acute pancreatitis.

Tryptophan Predicts the Risk for Future Type 2 Diabetes

PubMed Central

Chen, Tianlu; Zheng, Xiaojiao; Ma, Xiaojing; Bao, Yuqian; Ni, Yan; Hu, Cheng; Rajani, Cynthia; Huang, Fengjie; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recently, 5 amino acids were identified and verified as important metabolites highly associated with type 2 diabetes (T2D) development. This report aims to assess the association of tryptophan with the development of T2D and to evaluate its performance with existing amino acid markers. A total of 213 participants selected from a ten-year longitudinal Shanghai Diabetes Study (SHDS) were examined in two ways: 1) 51 subjects who developed diabetes and 162 individuals who remained metabolically healthy in 10 years; 2) the same 51 future diabetes and 23 strictly matched ones selected from the 162 healthy individuals. Baseline fasting serum tryptophan concentrations were quantitatively measured using ultra-performance liquid chromatography triple quadruple mass spectrometry. First, serum tryptophan level was found significantly higher in future T2D and was positively and independently associated with diabetes onset risk. Patients with higher tryptophan level tended to present higher degree of insulin resistance and secretion, triglyceride and blood pressure. Second, the prediction potential of tryptophan is non-inferior to the 5 existing amino acids. The predictive performance of the combined score improved after taking tryptophan into account. Our findings unveiled the potential of tryptophan as a new marker associated with diabetes risk in Chinese populations. The addition of tryptophan provided complementary value to the existing amino acid predictors. PMID:27598004

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.

PubMed

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-06-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat

PubMed Central

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-01-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection. PMID:24518889

Epigenetic Biomarkers of Breast Cancer Risk: Across the Breast Cancer Prevention Continuum.

PubMed

Terry, Mary Beth; McDonald, Jasmine A; Wu, Hui Chen; Eng, Sybil; Santella, Regina M

2016-01-01

Epigenetic biomarkers, such as DNA methylation, can increase cancer risk through altering gene expression. The Cancer Genome Atlas (TCGA) Network has demonstrated breast cancer-specific DNA methylation signatures. DNA methylation signatures measured at the time of diagnosis may prove important for treatment options and in predicting disease-free and overall survival (tertiary prevention). DNA methylation measurement in cell free DNA may also be useful in improving early detection by measuring tumor DNA released into the blood (secondary prevention). Most evidence evaluating the use of DNA methylation markers in tertiary and secondary prevention efforts for breast cancer comes from studies that are cross-sectional or retrospective with limited corresponding epidemiologic data, raising concerns about temporality. Few prospective studies exist that are large enough to address whether DNA methylation markers add to the prediction of tertiary and secondary outcomes over and beyond standard clinical measures. Determining the role of epigenetic biomarkers in primary prevention can help in identifying modifiable pathways for targeting interventions and reducing disease incidence. The potential is great for DNA methylation markers to improve cancer outcomes across the prevention continuum. Large, prospective epidemiological studies will provide essential evidence of the overall utility of adding these markers to primary prevention efforts, screening, and clinical care.

Emerging biomarkers in anaplastic oligodendroglioma: implications for clinical investigation and patient management.

PubMed

Sahebjam, Solmaz; McNamara, Mairéad G; Mason, Warren P

2013-07-01

Oligodendrogliomas are heterogeneous tumors with a variable response to treatment. This clinical variability underlines the urgent need for markers that can reliably aid diagnosis and guide clinical decision-making. Long-term follow-up data from the EORTC 26951 and RTOG 9402 clinical trials in newly diagnosed anaplastic oligodendroglioma have established chromosome 1p19q codeletion as a predictive marker of response to procarbazine, lomustine and vincristine chemotherapy in anaplastic oligodendrogliomas. In addition, MGMT promoter hypermethylation has been strongly associated with glioma CpG island hypermethylation phenotype (G-CIMP+) status, this has been suggested as an epiphenomenon of genome-wide methylation, conferring a more favorable prognosis. Molecular profiling of these tumors has identified several other markers with potential clinical significance: mutations of IDH, CIC, FUBP1 and CDKN2A require further validation before they can be implemented as clinical decision-making tools. Additionally, recent data on the clinical significance of intrinsic glioma subtyping appears promising. Indeed, existing evidence suggests that comprehensive analyses such as intrinsic glioma subtyping or G-CIMP status are superior to single molecular markers. Clearly, with evolving treatment strategies and in the era of individualized therapy, broader omics-based molecular evaluations are required to improve outcome prediction and to identify patients who will benefit from specific treatment strategies.

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

DOE PAGES

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.; ...

2016-02-11

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height,more » and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.« less

Accuracy of genomic prediction in switchgrass ( Panicum virgatum L.) improved by accounting for linkage disequilibrium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramstein, Guillaume P.; Evans, Joseph; Kaeppler, Shawn M.

Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS) is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height,more » and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Furthermore, some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.« less

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Genomic selection in plant breeding.

PubMed

Newell, Mark A; Jannink, Jean-Luc

2014-01-01

Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor and major marker effects. Thus, the GEBV may capture more of the genetic variation for the particular trait under selection.

Genomic selection in plant breeding

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor ...

Genomic Predictions and Genome-Wide Association Study of Resistance Against Piscirickettsia salmonis in Coho Salmon (Oncorhynchus kisutch) Using ddRAD Sequencing

PubMed Central

Barría, Agustín; Christensen, Kris A.; Yoshida, Grazyella M.; Correa, Katharina; Jedlicki, Ana; Lhorente, Jean P.; Davidson, William S.; Yáñez, José M.

2018-01-01

Piscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming, and current treatments have been ineffective for the control of this disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping of hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and to identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. A total of 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) were experimentally challenged against P. salmonis and their genotypes were assayed using ddRAD sequencing. A total of 9,389 SNPs markers were identified in the population. These markers were used to test genomic selection models and compare different GWAS methodologies for resistance measured as day of death (DD) and binary survival (BIN). Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN. The models showed an improvement of up to 95% and 155% respectively over PBLUP. One SNP related with B-cell development was identified as a potential functional candidate associated with resistance to P. salmonis defined as DD. PMID:29440129

Measured glomerular filtration rate does not improve prediction of mortality by cystatin C and creatinine.

PubMed

Sundin, Per-Ola; Sjöström, Per; Jones, Ian; Olsson, Lovisa A; Udumyan, Ruzan; Grubb, Anders; Lindström, Veronica; Montgomery, Scott

2017-04-01

Cystatin C may add explanatory power for associations with mortality in combination with other filtration markers, possibly indicating pathways other than glomerular filtration rate (GFR). However, this has not been firmly established since interpretation of associations independent of measured GFR (mGFR) is limited by potential multicollinearity between markers of GFR. The primary aim of this study was to assess associations between cystatin C and mortality, independent of mGFR. A secondary aim was to evaluate the utility of combining cystatin C and creatinine to predict mortality risk. Cox regression was used to assess the associations of cystatin C and creatinine with mortality in 1157 individuals referred for assessment of plasma clearance of iohexol. Since cystatin C and creatinine are inversely related to mGFR, cystatin C - 1 and creatinine - 1 were used. After adjustment for mGFR, lower cystatin C - 1 (higher cystatin C concentration) and higher creatinine - 1 (lower creatinine concentration) were independently associated with increased mortality. When nested models were compared, avoiding the potential influence of multicollinearity, the independence of the associations was supported. Among models combining the markers of GFR, adjusted for demographic factors and comorbidity, cystatin C - 1 and creatinine - 1 combined explained the largest proportion of variance in associations with mortality risk ( R 2  = 0.61). Addition of mGFR did not improve the model. Our results suggest that both creatinine and cystatin C have independent associations with mortality not explained entirely by mGFR and that mGFR does not offer a more precise mortality risk assessment than these endogenous filtration markers combined. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Beyond an AFLP genome scan towards the identification of immune genes involved in plague resistance in Rattus rattus from Madagascar.

PubMed

Tollenaere, C; Jacquet, S; Ivanova, S; Loiseau, A; Duplantier, J-M; Streiff, R; Brouat, C

2013-01-01

Genome scans using amplified fragment length polymorphism (AFLP) markers became popular in nonmodel species within the last 10 years, but few studies have tried to characterize the anonymous outliers identified. This study follows on from an AFLP genome scan in the black rat (Rattus rattus), the reservoir of plague (Yersinia pestis infection) in Madagascar. We successfully sequenced 17 of the 22 markers previously shown to be potentially affected by plague-mediated selection and associated with a plague resistance phenotype. Searching these sequences in the genome of the closely related species Rattus norvegicus assigned them to 14 genomic regions, revealing a random distribution of outliers in the genome (no clustering). We compared these results with those of an in silico AFLP study of the R. norvegicus genome, which showed that outlier sequences could not have been inferred by this method in R. rattus (only four of the 15 sequences were predicted). However, in silico analysis allowed the prediction of AFLP markers distribution and the estimation of homoplasy rates, confirming its potential utility for designing AFLP studies in nonmodel species. The 14 genomic regions surrounding AFLP outliers (less than 300 kb from the marker) contained 75 genes encoding proteins of known function, including nine involved in immune function and pathogen defence. We identified the two interleukin 1 genes (Il1a and Il1b) that share homology with an antigen of Y. pestis, as the best candidates for genes subject to plague-mediated natural selection. At least six other genes known to be involved in proinflammatory pathways may also be affected by plague-mediated selection. © 2012 Blackwell Publishing Ltd.

Molecular markers associated with development and progression of potentially premalignant oral epithelial lesions: Current knowledge and future implications.

PubMed

Nikitakis, Nikolaos G; Pentenero, Monica; Georgaki, Maria; Poh, Catherine F; Peterson, Douglas E; Edwards, Paul; Lingen, Mark; Sauk, John J

2018-06-01

Identification and management of potentially premalignant oral epithelial lesions (PPOELs) at highest risk of malignant transformation holds great promise for successful secondary prevention of oral squamous cell carcinoma, potentially reducing oral cancer morbidity and mortality. However, to date, neither clinical nor histopathologic validated risk predictors that can reliably predict which PPOELs will definitively progress to malignancy have been identified. In addition, the management of PPOELs remains a major challenge. Arguably, progress in the prevention and treatment of oral premalignancy and cancer will require improved understanding of the underlying molecular mechanisms, facilitating the discovery of diagnostic, prognostic, and predictive markers, as well as the identification of novel targeted therapeutics. This review provides a synopsis of the molecular biomarkers that have been studied in PPOELs and have been correlated with the presence and grade of dysplasia and/or their propensity to undergo malignant transformation to oral squamous cell carcinoma. The emphasis is on highlighting new emerging research fields, particularly epigenetic events, including methylation and micro-RNA regulation. Several promising biomarkers are highlighted. Current limitations and challenges are discussed. Recommendations for future focused research areas, to validate and promote clinically useful applications, are offered. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of Bioelectrical Impedance Analysis in Critically Ill Patients: Results of a Multicenter Prospective Study.

PubMed

Kuchnia, Adam; Earthman, Carrie; Teigen, Levi; Cole, Abigail; Mourtzakis, Marina; Paris, Michael; Looijaard, Willem; Weijs, Peter; Oudemans-van Straaten, Heleen; Beilman, Gregory; Day, Andrew; Leung, Roger; Compher, Charlene; Dhaliwal, Rupinder; Peterson, Sarah; Roosevelt, Hannah; Heyland, Daren K

2017-09-01

In critically ill patients, muscle loss is associated with adverse outcomes. Raw bioelectrical impedance analysis (BIA) parameters (eg, phase angle [PA] and impedance ratio [IR]) have received attention as potential markers of muscularity, nutrition status, and clinical outcomes. Our objective was to test whether PA and IR could be used to assess low muscularity and predict clinical outcomes. Patients (≥18 years) having an abdominal computed tomography (CT) scan and admitted to intensive care underwent multifrequency BIA within 72 hours of scan. CT scans were landmarked at the third lumbar vertebra and analyzed for skeletal muscle cross-sectional area (CSA). CSA ≤170 cm 2 for males and ≤110 cm 2 for females defined low muscularity. The relationship between PA (and IR) and CT muscle CSA was evaluated using multivariate regression and included adjustments for age, sex, body mass index, Charlson Comorbidity Index, and admission type. PA and IR were also evaluated for predicting discharge status using dual-energy x-ray absorptiometry-derived cut-points for low fat-free mass index. Of 171 potentially eligible patients, 71 had BIA and CT scans within 72 hours. Area under the receiver operating characteristic (c-index) curve to predict CT-defined low muscularity was 0.67 ( P ≤ .05) for both PA and IR. With covariates added to logistic regression models, PA and IR c-indexes were 0.78 and 0.76 ( P < .05), respectively. Low PA and high IR predicted time to live ICU discharge. Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention.

Predicting the female flight capability of gypsy moths by using DNA markers

Treesearch

Melody A. Keena; Marie-José Côté; Phyllis S. Grinberg; William E. Wallner

2011-01-01

Gypsy moths (Lymantria dispar L.) from different geographic origins have different biological and behavioral traits that can affect the risk of establishment and spread in new areas. One behavioral trait of major concern is the capacity of females from some geographic origins to fly, thus increasing the potential rate of spread and making detection...

Factors predicting labor induction success: a critical analysis.

PubMed

Crane, Joan M G

2006-09-01

Because of the risk of failed induction of labor, a variety of maternal and fetal factors as well as screening tests have been suggested to predict labor induction success. Certain characteristics of the woman (including parity, age, weight, height and body mass index), and of the fetus (including birth weight and gestational age) are associated with the success of labor induction; with parous, young women who are taller and lower weight having a higher rate of induction success. Fetuses with a lower birth weight or increased gestational age are also associated with increased induction success. The condition of the cervix at the start of induction is an important predictor, with the modified Bishop score being a widely used scoring system. The most important element of the Bishop score is dilatation. Other predictors, including transvaginal ultrasound (TVUS) and biochemical markers [including fetal fibronectin (fFN)] have been suggested. Meta-analyses of studies identified from MEDLINE, PubMed, and EMBASE and published from 1990 to October 2005 were performed evaluating the use of TVUS and fFN in predicting labor induction success in women at term with singleton gestations. Both TVUS and Bishop score predicted successful induction [likelihood ratio (LR)=1.82, 95% confidence interval (CI)=1.51-2.20 and LR=2.10, 95%CI=1.67-2.64, respectively]. As well, fFN and Bishop score predicted successful induction (LR=1.49, 95%CI=1.20-1.85, and LR=2.62, 95%CI=1.88-3.64, respectively). Although TVUS and fFN predicted successful labor induction, neither has been shown to be superior to Bishop score. Further research is needed to evaluate these potential predictors and insulin-like growth factor binding protein-1 (IGFBP-1), another potential biochemical marker.

Clinical trials with velnacrine: (PROPP) the physician reference of predicted probabilities--a statistical model for the estimation of hepatotoxicity risk with velnacrine maleate.

PubMed

Hardiman, S; Miller, K; Murphy, M

1993-01-01

Safety observations during the clinical development of Mentane (velnacrine maleate) have included the occurrence of generally asymptomatic liver enzyme elevations confined to patients with Alzheimer's disease (AD). The clinical presentation of this reversible hepatocellular injury is analogous to that reported for tetrahydroaminoacridine (THA). Direct liver injury, possibly associated with the production of a toxic metabolite, would be consistent with reports of aberrant xenobiotic metabolism in Alzheimer's disease patients. Since a patient related aberration in drug metabolism was suspected, a biostatistical strategy was developed with the objective of predicting hepatotoxicity in individual patients prior to exposure to velnacrine maleate. The method used logistic regression techniques with variable selection restricted to those items which could be routinely and inexpensively accessed at screen evaluation for potential candidates for treatment. The model was to be predictive (a marker for eventual hepatotoxicity) rather than a causative model, and techniques employed "goodness of fit", percentage correct, and positive and negative predictive values. On the basis of demographic and baseline laboratory data from 942 patients, the PROPP statistic was developed (the Physician Reference Of Predicted Probabilities). Main effect variables included age, gender, and nine hematological and serum chemistry variables. The sensitivity of the current model is approximately 49%, specificity approximately 88%. Using prior probability estimates, however, in which the patient's likelihood of liver toxicity is presumed to be at least 30%, the positive predictive value ranged between 64-77%. Although the clinical utility of this statistic will require refinements and additional prospective confirmation, its potential existence speaks to the possibility of markers for idiosyncratic drug metabolism in patients with Alzheimer's disease.

Mucin expression in pleomorphic adenoma of salivary gland: a potential role for MUC1 as a marker to predict recurrence.

PubMed

Hamada, T; Matsukita, S; Goto, M; Kitajima, S; Batra, S K; Irimura, T; Sueyoshi, K; Sugihara, K; Yonezawa, S

2004-08-01

Pleomorphic adenoma of the salivary gland (PA) is essentially a benign neoplasm. However, patients with recurrent PA are difficult to manage. There are rare reports on useful immunohistochemical markers to detect a high risk of recurrence when the primary lesions are resected. To find a new marker to predict the recurrence of PA. Primary lesions of PA were collected from nine patients showing subsequent recurrence and from 40 patients without recurrence during at least 10 years of follow up of the disease. Paraffin wax embedded tumour samples of the two groups were examined for the expression profiles of MUC1 (differentially glycosylated forms), MUC2, MUC4, MUC5AC, and MUC6 using immunohistochemistry. Several clinicopathological factors were also examined. In univariate analysis of the factors examined, MUC1/DF3 high expression (more than 30% of the neoplastic cells stained) in the primary lesions was seen more frequently in patients with recurrence (four of nine) than in those without recurrence (three of 40; p = 0.011). Larger tumour size (more than 3.0 cm) of the primary PA was also a significant (p = 0.035) risk factor for the recurrence of PA. In multivariate analysis, only high expression of MUC1/DF3 was found to be a significant independent risk factor for the recurrence of PA (p = 0.021). Expression of MUC1/DF3 in PA is a useful marker to predict its recurrence. Those patients with PA showing positive MUC1/DF3 expression should be followed up carefully.

[Non-small cell lung cancer. Subtyping and predictive molecular marker investigations in cytology].

PubMed

Savic, S; Bihl, M P; Bubendorf, L

2012-07-01

The diagnosis and treatment of non-small cell lung cancer (NSCLC) have been revolutionized over the last few years. Requirements for cytopathologists in lung cancer diagnosis have therefore changed. The general diagnostic category of NSLC is no longer sufficient. In addition cytological specimens need to be evaluated for adequacy regarding predictive marker analyses. Accurate NSCLC subtyping with a distinction of adenocarcinoma from squamous cell carcinoma is crucial for treatment decisions as the subtype will decide on the chemotherapy regimen and the choice of predictive marker analyses for targeted treatment. In the majority of cases, the subtype can be diagnosed by morphology alone. Cytology is equally well suited as biopsy specimens for the assessment of molecular predictive markers. The best results are achieved when both cytology and biopsy specimens are compared to choose the most appropriate specimen for morphological subtyping and molecular testing. In this paper, we discuss special issues of NSCLC subtyping and currently recommended predictive molecular marker analyses.

Systematic considerations for a multicomponent pharmacokinetic study of Epimedii wushanensis herba: From method establishment to pharmacokinetic marker selection.

PubMed

Wang, Caihong; Wu, Caisheng; Zhang, Jinlan; Jin, Ying

2015-04-15

Prenylflavonoids are major active components of Epimedii wushanensis herba (EWH). The global pharmacokinetics of prenylflavonoids are unclear, as these compounds yield multiple, often unidentified metabolites. This study successfully elucidated the pharmacokinetic profiles of EWH extract and five EWH-derived prenylflavonoid monomers in rats. The study was a comprehensive analysis of metabolic pathways and pharmacokinetic markers. Major plasma compounds identified after oral administration of EWH-derived prototypes or extract included: (1) prenylflavonoid prototypes, (2) deglycosylated products, and (3) glucuronide conjugates. To select appropriate EWH-derived pharmacokinetic markers, a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method was established to simultaneously monitor 14 major compounds in unhydrolyzed plasma and 10 potential pharmacokinetic markers in hydrolyzed plasma. The pharmacokinetic profiles indicated that the glucuronide conjugates of icaritin were the principle circulating metabolites and that total icaritin accounted for ∼99% of prenylflavonoid exposure after administration of EWH-derived materials to rats. To further investigate icaritin as a prospective pharmacokinetic marker, correlation analysis was performed between total icaritin and its glucuronide conjugates, and a strong correlation (r > 0.5) was found, indicating that total icaritin content accurately reflected changes in the exposure levels of the glucuronide conjugates over time. Therefore, icaritin is a sufficient pharmacokinetic marker for evaluating dynamic prenylflavonoid exposure levels. Next, a mathematical model was developed based on the prenylflavonoid content of EWH and the exposure levels in rats, using icaritin as the pharmacokinetic marker. This model accurately predicted exposure levels in vivo, with similar predicted vs. experimental area under the curve (AUC)(0-96 h) values for total icaritin (24.1 vs. 32.0 mg/L h). Icaritin in hydrolyzed plasma can be used as a pharmacokinetic marker to reflect prenylflavonoid exposure levels, as well as the changes over time of its glucuronide conjugates. Crown Copyright © 2015. Published by Elsevier GmbH. All rights reserved.

Molecular alterations and biomarkers in colorectal cancer

PubMed Central

Grady, William M.; Pritchard, Colin C.

2013-01-01

The promise of precision medicine is now a clinical reality. Advances in our understanding of the molecular genetics of colorectal cancer genetics is leading to the development of a variety of biomarkers that are being used as early detection markers, prognostic markers, and markers for predicting treatment responses. This is no more evident than in the recent advances in testing colorectal cancers for specific molecular alterations in order to guide treatment with the monoclonal antibody therapies cetuximab and panitumumab, which target the epidermal growth factor receptor (EGFR). In this review, we update a prior review published in 2010 and describe our current understanding of the molecular pathogenesis of colorectal cancer and how these alterations relate to emerging biomarkers for early detection and risk stratification (diagnostic markers), prognosis (prognostic markers), and the prediction of treatment responses (predictive markers). PMID:24178577

[Studies of marker screening efficiency and corresponding influencing factors in QTL composite interval mapping].

PubMed

Gao, Yong-Ming; Wan, Ping

2002-06-01

Screening markers efficiently is the foundation of mapping QTLs by composite interval mapping. Main and interaction markers distinguished, besides using background control for genetic variation, could also be used to construct intervals of two-way searching for mapping QTLs with epistasis, which can save a lot of calculation time. Therefore, the efficiency of marker screening would affect power and precision of QTL mapping. A doubled haploid population with 200 individuals and 5 chromosomes was constructed, with 50 markers evenly distributed at 10 cM space. Among a total of 6 QTLs, one was placed on chromosome I, two linked on chromosome II, and the other three linked on chromosome IV. QTL setting included additive effects and epistatic effects of additive x additive, the corresponding QTL interaction effects were set if data were collected under multiple environments. The heritability was assumed to be 0.5 if no special declaration. The power of marker screening by stepwise regression, forward regression, and three methods for random effect prediction, e.g. best linear unbiased prediction (BLUP), linear unbiased prediction (LUP) and adjusted unbiased prediction (AUP), was studied and compared through 100 Monte Carlo simulations. The results indicated that the marker screening power by stepwise regression at 0.1, 0.05 and 0.01 significant level changed from 2% to 68%, the power changed from 2% to 72% by forward regression. The larger the QTL effects, the higher the marker screening power. While the power of marker screening by three random effect prediction was very low, the maximum was only 13%. That suggested that regression methods were much better than those by using the approaches of random effect prediction to identify efficient markers flanking QTLs, and forward selection method was more simple and efficient. The results of simulation study on heritability showed that heightening of both general heritability and interaction heritability of genotype x environments could enhance marker screening power, the former had a greater influence on QTLs with larger main and/or epistatic effects, while the later on QTLs with small main and/or epistatic effects. The simulation of 100 times was also conducted to study the influence of different marker number and density on marker screening power. It is indicated that the marker screening power would decrease if there were too many markers, especially with high density in a mapping population, which suggested that a mapping population with definite individuals could only hold limited markers. According to the simulation study, the reasonable number of markers should not be more than individuals. The simulation study of marker screening under multiple environments showed high total power of marker screening. In order to relieve the problem that marker screening power restricted the efficiency of QTL mapping, markers identified in multiple environments could be used to construct two search intervals.

Sex specific differences in the predictive value of cholesterol homeostasis markers and 10-Year CVD event rate in Framingham Offspring Study participants

USDA-ARS?s Scientific Manuscript database

Available data are inconsistent on factors influencing plasma cholesterol homeostasis marker concentrations and their value in predicting subsequent cardiovascular disease (CVD) events. To address this issue the relationship between markers of cholesterol absorption (campesterol, sitosterol, cholest...

Relapse prediction in Graves´ disease: Towards mathematical modeling of clinical, immune and genetic markers.

PubMed

Langenstein, Christoph; Schork, Diana; Badenhoop, Klaus; Herrmann, Eva

2016-12-01

Graves' disease (GD) is an important and prevalent thyroid autoimmune disorder. Standard therapy for GD consists of antithyroid drugs (ATD) with treatment periods of around 12 months but relapse is frequent. Since predictors for relapse are difficult to identify the individual decision making for optimal treatment is often arbitrary. After reviewing the literature on this topic we summarize important factors involved in GD and with respect to their potential for relapse prediction from markers before and after treatment. This information was used to design a mathematical model integrating thyroid hormone parameters, thyroid size, antibody titers and a complex algorithm encompassing genetic predisposition, environmental exposures and current immune activity in order to arrive at a prognostic index for relapse risk after treatment. In the search for a tool to analyze and predict relapse in GD mathematical modeling is a promising approach. In analogy to mathematical modeling approaches in other diseases such as viral infections, we developed a differential equation model on the basis of published clinical trials in patients with GD. Although our model needs further evaluation to be applicable in a clinical context, it provides a perspective for an important contribution to a final statistical prediction model.

Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree

PubMed Central

de los Campos, Gustavo; Naya, Hugo; Gianola, Daniel; Crossa, José; Legarra, Andrés; Manfredi, Eduardo; Weigel, Kent; Cotes, José Miguel

2009-01-01

The availability of genomewide dense markers brings opportunities and challenges to breeding programs. An important question concerns the ways in which dense markers and pedigrees, together with phenotypic records, should be used to arrive at predictions of genetic values for complex traits. If a large number of markers are included in a regression model, marker-specific shrinkage of regression coefficients may be needed. For this reason, the Bayesian least absolute shrinkage and selection operator (LASSO) (BL) appears to be an interesting approach for fitting marker effects in a regression model. This article adapts the BL to arrive at a regression model where markers, pedigrees, and covariates other than markers are considered jointly. Connections between BL and other marker-based regression models are discussed, and the sensitivity of BL with respect to the choice of prior distributions assigned to key parameters is evaluated using simulation. The proposed model was fitted to two data sets from wheat and mouse populations, and evaluated using cross-validation methods. Results indicate that inclusion of markers in the regression further improved the predictive ability of models. An R program that implements the proposed model is freely available. PMID:19293140

Usefulness of cardiac biomarkers to predict cardiac recovery in patients on extracorporeal membrane oxygenation support for refractory cardiogenic shock.

PubMed

Luyt, Charles-Edouard; Landivier, Antoine; Leprince, Pascal; Bernard, Maguy; Pavie, Alain; Chastre, Jean; Combes, Alain

2012-10-01

No prognostic markers of myocardial recovery in patients with refractory cardiogenic shock requiring circulatory support are known, but early identification of patients who will not recover might provide an opportunity to change the treatment strategy to improve outcome. Because N-terminal fragment of the B-type natriuretic peptide, troponin Ic, midregional fragment of the proatrial natriuretic peptide, proadrenomedullin, and copeptin are prognostic markers in patients with cardiac failure, we hypothesized that, among patients with refractory cardiogenic shock of potentially reversible cause supported with extracorporeal membrane oxygenation (ECMO), the kinetics of these markers might help identify patients who would recover. This was a prospective, observational, single-center study in a medical-surgical intensive care unit. Among 41 consecutive patients with refractory cardiogenic shock of potentially reversible cause receiving ECMO support, 18 recovered and were successfully weaned off the machine. Blood N-terminal fragment of the B-type natriuretic peptide, troponin Ic, midregional fragment of the proatrial natriuretic peptide, proadrenomedullin, and copeptin concentrations were determined on days 1, 3, and 7 post-ECMO. Neither the absolute values of those biomarkers at days 1, 3, or 7 nor their kinetics during the first week differed between patients weaned or not. Areas under the receiver operating characteristic curves (95% confidence interval) of the day 1-to-day 3 biomarker changes for predicting cardiac recovery were 0.54 (0.36-0.71), 0.61 (0.43-0.78), 0.61 (0.42-0.77), 0.56 (0.38-0.73), and 0.61 (0.43-0.78), respectively. In patients with refractory cardiogenic shock of potentially reversible cause receiving ECMO support, early measurements of cardiac biomarkers are not useful for identifying those who would recover. Copyright © 2012 Elsevier Inc. All rights reserved.

Neutrophil-to-lymphocyte ratio as a novel-potential marker for predicting prognosis of Bell palsy.

PubMed

Bucak, Abdulkadir; Ulu, Sahin; Oruc, Serdar; Yucedag, Fatih; Tekin, Mustafa Said; Karakaya, Fatıma; Aycicek, Abdullah

2014-07-01

Bell palsy can be defined as an idiopathic, acute, facial nerve palsy. Although the pathogenesis of Bell palsy is not fully understood, inflammation seems to play important role. Neutrophil-to-lymphocyte (NLR) ratio was defined as a novel potential marker to determine inflammation and it is routinely measured in peripheral blood. Our goal was to investigate the relationship between Bell palsy and inflammation by using NLR. Retrospective study. The 54 patients who were followed up for Bell palsy for a period of 1 to 3 years, along with 45 age- and sex-matched controls, were included in the study. An automated blood cell counter was used for NLR measurements. All patients were treated with prednisone, 1 mg/kg per day with a progressive dose reduction. Patients were classified according to the House-Brackmann grading system at posttreatment period. Those with House-Brackmann grade I and grade II were regarded as satisfactory recovery; and those with House-Brackmann grade III to grade VI were regarded as nonsatisfactory recovery. The mean NLR and neutrophil values in patients with Bell palsy were significantly higher than in the control group (P=0.001 and P<0.001, respectively). In addition, NLR levels were higher in nonsatisfactory recovered patients compared with satisfactory recovered ones (P<0.001). This is the first study investigating the relationship between NLR levels and Bell palsy and its prognosis. Our result suggest that while evaluating Bell palsy patients, NLR might be taken into account as a novel potential marker to predict the patients' prognosis. 3b. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

Metaphylogenomic and potential functionality of the limpet Patella pellucida's gastrointestinal tract microbiome.

PubMed

Dudek, Magda; Adams, Jessica; Swain, Martin; Hegarty, Matthew; Huws, Sharon; Gallagher, Joe

2014-10-20

This study investigated the microbial diversity associated with the digestive tract of the seaweed grazing marine limpet Patella pellucida. Using a modified indirect DNA extraction protocol and performing metagenomic profiling based on specific prokaryotic marker genes, the abundance of bacterial groups was identified from the analyzed metagenome. The members of three significantly abundant phyla of Proteobacteria, Firmicutes and Bacteroidetes were characterized through the literature and their predicted functions towards the host, as well as potential applications in the industrial environment assessed.

Evaluation and Integration of Genetic Signature for Prediction Risk of Nasopharyngeal Carcinoma in Southern China

PubMed Central

Winkler, Cheryl A.; Li, Ji; Guan, Li; Tang, Minzhong; Liao, Jian; Deng, Hong; de Thé, Guy; Zeng, Yi; O'Brien, Stephen J.

2014-01-01

Genetic factors, as well as environmental factors, play a role in development of nasopharyngeal carcinoma (NPC). A number of single nucleotide polymorphisms (SNPs) have been reported to be associated with NPC. To confirm these genetic associations with NPC, two independent case-control studies from Southern China comprising 1166 NPC cases and 2340 controls were conducted. Seven SNPs in ITGA9 at 3p21.3 and 9 SNPs within the 6p21.3 HLA region were genotyped. To explore the potential clinical application of these genetic markers in NPC, we further evaluate the predictive/diagnostic role of significant SNPs by calculating the area under the curve (AUC). Results. The reported associations between ITGA9 variants and NPC were not replicated. Multiple loci of GABBR1, HLA-F, HLA-A, and HCG9 were statistically significant in both cohorts (P combined range from 5.96 × 10−17 to 0.02). We show for the first time that these factors influence NPC development independent of environmental risk factors. This study also indicated that the SNP alone cannot serve as a predictive/diagnostic marker for NPC. Integrating the most significant SNP with IgA antibodies status to EBV, which is presently used as screening/diagnostic marker for NPC in Chinese populations, did not improve the AUC estimate for diagnosis of NPC. PMID:25180181

Evaluation and integration of genetic signature for prediction risk of nasopharyngeal carcinoma in Southern China.

PubMed

Guo, Xiuchan; Winkler, Cheryl A; Li, Ji; Guan, Li; Tang, Minzhong; Liao, Jian; Deng, Hong; de Thé, Guy; Zeng, Yi; O'Brien, Stephen J

2014-01-01

Genetic factors, as well as environmental factors, play a role in development of nasopharyngeal carcinoma (NPC). A number of single nucleotide polymorphisms (SNPs) have been reported to be associated with NPC. To confirm these genetic associations with NPC, two independent case-control studies from Southern China comprising 1166 NPC cases and 2340 controls were conducted. Seven SNPs in ITGA9 at 3p21.3 and 9 SNPs within the 6p21.3 HLA region were genotyped. To explore the potential clinical application of these genetic markers in NPC, we further evaluate the predictive/diagnostic role of significant SNPs by calculating the area under the curve (AUC). The reported associations between ITGA9 variants and NPC were not replicated. Multiple loci of GABBR1, HLA-F, HLA-A, and HCG9 were statistically significant in both cohorts (P(combined) range from 5.96 × 10(-17) to 0.02). We show for the first time that these factors influence NPC development independent of environmental risk factors. This study also indicated that the SNP alone cannot serve as a predictive/diagnostic marker for NPC. Integrating the most significant SNP with IgA antibodies status to EBV, which is presently used as screening/diagnostic marker for NPC in Chinese populations, did not improve the AUC estimate for diagnosis of NPC.

Potential role of liver enzymes levels as predictor markers of glucose metabolism disorders in Tunisian population.

PubMed

Bouhajja, Houda; Abdelhedi, Rania; Amouri, Ali; Hadj Kacem, Faten; Marrakchi, Rim; Safi, Wajdi; Mrabet, Houcem; Chtourou, Lassaad; Charfi, Nadia; Fourati, Mouna; Bensassi, Salwa; Jamoussi, Kamel; Abid, Mohamed; Ayadi, Hammadi; Feki, Mouna Mnif; Elleuch, Noura Bougacha

2018-03-10

The relationship between liver enzymes and type 2 diabetes (T2D) risk is inconclusive. We aimed to evaluate the association between liver markers and risk of carbohydrate metabolism disorders and their discriminatory power for T2D prediction. This cross-sectional study enrolled 216 participants classified as normoglycemic, prediabetes, newly-diagnosed diabetes and diagnosed diabetes. All participants underwent anthropometric and biochemical measurements. The relationship between hepatic enzymes and glucose metabolism markers was evaluated by ANCOVA analyses. The associations between liver enzymes and incident carbohydrate metabolism disorders were analyzed through logistic regression and their discriminatory capacity for T2D by receiver operating characteristic (ROC) analysis. High alkaline phosphatase (AP), alanine aminotransferase (ALT), γ-glutamyltransferase (γGT) and aspartate aminotrasferase (AST) levels were independently related to decreased insulin sensitivity. Interestingly, higher AP level was significantly associated with increased risk of prediabetes (p=0.017), newly-diagnosed diabetes (p=0.004) and T2D (p=0.007). Elevated γGT level was an independent risk factor for T2D (p=0.032) and undiagnosed-T2D (p=0.010) in prediabetic and normoglycemic subjects, respectively. In ROC analysis, AP was a powerful predictor of incident diabetes and significantly improved T2D prediction. Liver enzymes within normal range, specifically AP levels, are associated with increased risk of carbohydrate metabolism disorders and significantly improved T2D prediction.

Correlates of tuberculosis risk: predictive biomarkers for progression to active tuberculosis

PubMed Central

Petruccioli, Elisa; Scriba, Thomas J.; Petrone, Linda; Hatherill, Mark; Cirillo, Daniela M.; Joosten, Simone A.; Ottenhoff, Tom H.; Denkinger, Claudia M.; Goletti, Delia

2016-01-01

New approaches to control the spread of tuberculosis (TB) are needed, including tools to predict development of active TB from latent TB infection (LTBI). Recent studies have described potential correlates of risk, in order to inform the development of prognostic tests for TB disease progression. These efforts have included unbiased approaches employing “omics” technologies, as well as more directed, hypothesis-driven approaches assessing a small set or even individual selected markers as candidate correlates of TB risk. Unbiased high-throughput screening of blood RNAseq profiles identified signatures of active TB risk in individuals with LTBI, ≥1 year before diagnosis. A recent infant vaccination study identified enhanced expression of T-cell activation markers as a correlate of risk prior to developing TB; conversely, high levels of Ag85A antibodies and high frequencies of interferon (IFN)-γ specific T-cells were associated with reduced risk of disease. Others have described CD27−IFN-γ+CD4+ T-cells as possibly predictive markers of TB disease. T-cell responses to TB latency antigens, including heparin-binding haemagglutinin and DosR-regulon-encoded antigens have also been correlated with protection. Further studies are needed to determine whether correlates of risk can be used to prevent active TB through targeted prophylactic treatment, or to allow targeted enrolment into efficacy trials of new TB vaccines and therapeutic drugs. PMID:27836953

Genomic selection in sugar beet breeding populations

PubMed Central

2013-01-01

Background Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. Results We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. Conclusions The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding. PMID:24047500

Prognostic markers in localized prostate cancer: from microscopes to molecules.

PubMed

Harding, M A; Theodorescu, D

Management of patients diagnosed with localized prostate cancer is complicated by the diverse natural history of the disease and variable response to treatment. Prognostic criteria currently in use cannot fully predict tumor behavior and thus limit the ability to recommend treatment regimens with the assurance that they are the best course of action for each individual patient. The search for better prognostic markers is now focussed on the molecular mechanisms which underlay tumor behavior, such as altered cell cycle progression, apoptosis, neuroendocrine differentiation, and angiogenesis. As the number of potential molecular markers increases, it is becoming evident that no single marker will provide the prognostic information necessary to make a significant improvement in patient care. In addition, it seems likely that traditional methods of assessing the prognostic value of this multitude of new markers will prove inadequate. In this review, we briefly examine the current state of prognostication in localized prostate cancer and some of the promising new molecular markers. Next, we examine how new technologies may allow the multiplex analysis of vast numbers of markers and how computational methods such as artificial neural networks will provide meaningful interpretation of the data. In the near future, such an integrated approach may provide a comprehensive prognostic tool for localized prostate cancer.

Impact of in-Sewer Degradation of Pharmaceutical and Personal Care Products (PPCPs) Population Markers on a Population Model.

PubMed

O'Brien, Jake William; Banks, Andrew Phillip William; Novic, Andrew Joseph; Mueller, Jochen F; Jiang, Guangming; Ort, Christoph; Eaglesham, Geoff; Yuan, Zhiguo; Thai, Phong K

2017-04-04

A key uncertainty of wastewater-based epidemiology is the size of the population which contributed to a given wastewater sample. We previously developed and validated a Bayesian inference model to estimate population size based on 14 population markers which: (1) are easily measured and (2) have mass loads which correlate with population size. However, the potential uncertainty of the model prediction due to in-sewer degradation of these markers was not evaluated. In this study, we addressed this gap by testing their stability under sewer conditions and assessed whether degradation impacts the model estimates. Five markers, which formed the core of our model, were stable in the sewers while the others were not. Our evaluation showed that the presence of unstable population markers in the model did not decrease the precision of the population estimates providing that stable markers such as acesulfame remained in the model. However, to achieve the minimum uncertainty in population estimates, we propose that the core markers to be included in population models for other sites should meet two additional criteria: (3) negligible degradation in wastewater to ensure the stability of chemicals during collection; and (4) < 10% in-sewer degradation could occur during the mean residence time of the sewer network.

Diagnosing Appendicitis: Evidence-Based Review of the Diagnostic Approach in 2014

PubMed Central

Shogilev, Daniel J.; Duus, Nicolaj; Odom, Stephen R.; Shapiro, Nathan I.

2014-01-01

Introduction Acute appendicitis is the most common abdominal emergency requiring emergency surgery. However, the diagnosis is often challenging and the decision to operate, observe or further work-up a patient is often unclear. The utility of clinical scoring systems (namely the Alvarado score), laboratory markers, and the development of novel markers in the diagnosis of appendicitis remains controversial. This article presents an update on the diagnostic approach to appendicitis through an evidence-based review. Methods We performed a broad Medline search of radiological imaging, the Alvarado score, common laboratory markers, and novel markers in patients with suspected appendicitis. Results Computed tomography (CT) is the most accurate mode of imaging for suspected cases of appendicitis, but the associated increase in radiation exposure is problematic. The Alvarado score is a clinical scoring system that is used to predict the likelihood of appendicitis based on signs, symptoms and laboratory data. It can help risk stratify patients with suspected appendicitis and potentially decrease the use of CT imaging in patients with certain Alvarado scores. White blood cell (WBC), C-reactive protein (CRP), granulocyte count and proportion of polymorphonuclear (PMN) cells are frequently elevated in patients with appendicitis, but are insufficient on their own as a diagnostic modality. When multiple markers are used in combination their diagnostic utility is greatly increased. Several novel markers have been proposed to aid in the diagnosis of appendicitis; however, while promising, most are only in the preliminary stages of being studied. Conclusion While CT is the most accurate mode of imaging in suspected appendicitis, the accompanying radiation is a concern. Ultrasound may help in the diagnosis while decreasing the need for CT in certain circumstances. The Alvarado Score has good diagnostic utility at specific cutoff points. Laboratory markers have very limited diagnostic utility on their own but show promise when used in combination. Further studies are warranted for laboratory markers in combination and to validate potential novel markers. PMID:25493136

Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.

PubMed

Tiezzi, Francesco; Maltecca, Christian

2015-04-02

Genomic BLUP (GBLUP) can predict breeding values for non-phenotyped individuals based on the identity-by-state genomic relationship matrix (G). The G matrix can be constructed from thousands of markers spread across the genome. The strongest assumption of G and consequently of GBLUP is that all markers contribute equally to the genetic variance of a trait. This assumption is violated for traits that are controlled by a small number of quantitative trait loci (QTL) or individual QTL with large effects. In this paper, we investigate the performance of using a weighted genomic relationship matrix (wG) that takes into consideration the genetic architecture of the trait in order to improve predictive ability for a wide range of traits. Multiple methods were used to calculate weights for several economically relevant traits in US Holstein dairy cattle. Predictive performance was tested by k-means cross-validation. Relaxing the GBLUP assumption of equal marker contribution by increasing the weight that is given to a specific marker in the construction of the trait-specific G resulted in increased predictive performance. The increase was strongest for traits that are controlled by a small number of QTL (e.g. fat and protein percentage). Furthermore, bias in prediction estimates was reduced compared to that resulting from the use of regular G. Even for traits with low heritability and lower general predictive performance (e.g. calving ease traits), weighted G still yielded a gain in accuracy. Genomic relationship matrices weighted by marker realized variance yielded more accurate and less biased predictions for traits regulated by few QTL. Genome-wide association analyses were used to derive marker weights for creating weighted genomic relationship matrices. However, this can be cumbersome and prone to low stability over generations because of erosion of linkage disequilibrium between markers and QTL. Future studies may include other sources of information, such as functional annotation and gene networks, to better exploit the genetic architecture of traits and produce more stable predictions.

Early Prognostication Markers in Cardiac Arrest Patients Treated with Hypothermia

PubMed Central

Karapetkova, Maria; Koenig, Matthew A.; Jia, Xiaofeng

2015-01-01

Background and purpose Established prognostication markers, such as clinical findings, electroencephalography (EEG), and biochemical markers, used by clinicians to predict neurologic outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. Methods MEDLINE and EMBASE were searched for evidence on the current standards for neurologic outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers, and multimodal approaches for prognostication were included and reviewed. Results While the prognostic accuracy of various tests has been questioned after TH, pupillary light reflexes and somatosensory evoked potentials (SSEP) are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 hours after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as MRI and CT, can identify functional and structural brain injury, but are not readily available at the patient’s bedside because of limited availability and high costs. Conclusions A multimodal algorithm composed of neurological examination, EEG-based quantitative testing, and SSEP, in conjunction with newer MRI sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed later than 72 hours after CA. PMID:26228521

Heart rate variability predicts alcohol craving in alcohol dependent outpatients: further evidence for HRV as a psychophysiological marker of self-regulation.

PubMed

Quintana, Daniel S; Guastella, Adam J; McGregor, Iain S; Hickie, Ian B; Kemp, Andrew H

2013-09-01

Past research has highlighted an important role of the autonomic nervous system in alcohol dependence and capacity for self-regulation. While previous studies have examined alcohol dependent inpatients, it remains unclear whether resting-state HRV, a potential psychophysiological marker of ones capacity for self-regulation, is related to craving in patients who currently consume alcohol. Thus, the aim of the present study was to determine whether HRV predicts alcohol craving in dependent individuals in the community. Resting-state HRV and alcohol craving, as indexed by the obsessive compulsive drinking scale, were assessed in 26 alcohol dependent outpatients. Results supported hypotheses indicating that HRV accounts for an additional 12.1% of the variance in craving after controlling for age, anxiety and levels of alcohol consumption. Here we show for the first time that resting-state HRV predicts craving in alcohol dependent outpatients. Results provide important new evidence for a role of the autonomic nervous system in the maintenance of dependence disorders. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

PubMed

Baker, Stuart G; Schuit, Ewoud; Steyerberg, Ewout W; Pencina, Michael J; Vickers, Andrew; Vickers, Andew; Moons, Karel G M; Mol, Ben W J; Lindeman, Karen S

2014-09-28

An important question in the evaluation of an additional risk prediction marker is how to interpret a small increase in the area under the receiver operating characteristic curve (AUC). Many researchers believe that a change in AUC is a poor metric because it increases only slightly with the addition of a marker with a large odds ratio. Because it is not possible on purely statistical grounds to choose between the odds ratio and AUC, we invoke decision analysis, which incorporates costs and benefits. For example, a timely estimate of the risk of later non-elective operative delivery can help a woman in labor decide if she wants an early elective cesarean section to avoid greater complications from possible later non-elective operative delivery. A basic risk prediction model for later non-elective operative delivery involves only antepartum markers. Because adding intrapartum markers to this risk prediction model increases AUC by 0.02, we questioned whether this small improvement is worthwhile. A key decision-analytic quantity is the risk threshold, here the risk of later non-elective operative delivery at which a patient would be indifferent between an early elective cesarean section and usual care. For a range of risk thresholds, we found that an increase in the net benefit of risk prediction requires collecting intrapartum marker data on 68 to 124 women for every correct prediction of later non-elective operative delivery. Because data collection is non-invasive, this test tradeoff of 68 to 124 is clinically acceptable, indicating the value of adding intrapartum markers to the risk prediction model. Copyright © 2014 John Wiley & Sons, Ltd.

Endometrial immune markers are potential predictors of normal fertility and pregnancy after in vitro fertilization.

PubMed

Kofod, Louise; Lindhard, Anette; Bzorek, Michael; Eriksen, Jens Ole; Larsen, Lise Grupe; Hviid, Thomas Vauvert F

2017-09-01

Elucidating immune mechanisms in the endometrium, which lead to the success of implantation and pregnancy, is important in reproductive medicine. Studies of immune cell abundance have shown conflicting results, and the expression and importance of HLA class Ib proteins in pre-implantation endometrium have not yet been investigated. The study population consisted of four subgroups: a hydrosalpinx, a salpingectomy, an unexplained infertility, and a fertile control group. Endometrial samples were collected during the implantation window. Immune markers (CD56 + and CD16 + cells, FoxP3 + Tregs, HLA-G, HLA-F) were quantified in the samples. The outcome of the subsequent IVF treatment was recorded. Increased CD56 + uNK cells and high HLA-G expression served as predictor for successful pregnancy outcome. HLA-F expression was positively correlated with uNK cells, being indirectly predictive for achieving pregnancy. Endometrial uNK cell abundance in the pre-implantation endometrium seems to be important for normal fertility and pregnancy success, and they may be used as clinical markers to predict implantation success in IVF. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations.

PubMed

Chen, Tianlu; Ni, Yan; Ma, Xiaojing; Bao, Yuqian; Liu, Jiajian; Huang, Fengjie; Hu, Cheng; Xie, Guoxiang; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-02-05

Recent studies revealed strong evidence that branched-chain and aromatic amino acids (BCAAs and AAAs) are closely associated with the risk of developing type 2 diabetes in several Western countries. The aim of this study was to evaluate the potential role of BCAAs and AAAs in predicting the diabetes development in Chinese populations. The serum levels of valine, leucine, isoleucine, tyrosine, and phenylalanine were measured in a longitudinal and a cross sectional studies with a total of 429 Chinese participants at different stages of diabetes development, using an ultra-performance liquid chromatography triple quadruple mass spectrometry platform. The alterations of the five AAs in Chinese populations are well in accordance with previous reports. Early elevation of the five AAs and their combined score was closely associated with future development of diabetes, suggesting an important role of these metabolites as early markers of diabetes. On the other hand, the five AAs were not as good as existing clinical markers in differentiating diabetic patients from their healthy counterparts. Our findings verified the close correlation of BCAAs and AAAs with insulin resistance and future development of diabetes in Chinese populations and highlighted the predictive value of these markers for future development of diabetes.

Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations

PubMed Central

Chen, Tianlu; Ni, Yan; Ma, Xiaojing; Bao, Yuqian; Liu, Jiajian; Huang, Fengjie; Hu, Cheng; Xie, Guoxiang; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recent studies revealed strong evidence that branched-chain and aromatic amino acids (BCAAs and AAAs) are closely associated with the risk of developing type 2 diabetes in several Western countries. The aim of this study was to evaluate the potential role of BCAAs and AAAs in predicting the diabetes development in Chinese populations. The serum levels of valine, leucine, isoleucine, tyrosine, and phenylalanine were measured in a longitudinal and a cross sectional studies with a total of 429 Chinese participants at different stages of diabetes development, using an ultra-performance liquid chromatography triple quadruple mass spectrometry platform. The alterations of the five AAs in Chinese populations are well in accordance with previous reports. Early elevation of the five AAs and their combined score was closely associated with future development of diabetes, suggesting an important role of these metabolites as early markers of diabetes. On the other hand, the five AAs were not as good as existing clinical markers in differentiating diabetic patients from their healthy counterparts. Our findings verified the close correlation of BCAAs and AAAs with insulin resistance and future development of diabetes in Chinese populations and highlighted the predictive value of these markers for future development of diabetes. PMID:26846565

Biochemical markers of acute limb ischemia, rhabdomyolysis, and impact on limb salvage.

PubMed

Watson, J Devin B; Gifford, Shaun M; Clouse, W Darrin

2014-12-01

Biochemical markers of ischemia reperfusion injury have been of interest to vascular surgeons and researchers for many years. Acute limb ischemia is the quintessential clinical scenario where these markers would seem relevant. The use of biomarkers to preoperatively or perioperatively predict which patients will not tolerate limb-salvage efforts or who will have poor functional outcomes after salvage is of immense interest. Creatinine phosphokinase, myoglobin, lactate, lactate dehydrogenase, potassium, bicarbonate, and neutrophil/leukocyte ratios are a few of the studied biomarkers available. Currently, the most well-studied aspect of ischemia reperfusion injury is rhabdomyolysis leading to acute kidney injury. The last 10 years have seen significant progression and improvement in the treatment of rhabdomyolysis, from minor supportive care to use of continuous renal replacement therapy. Identification of specific biomarkers with predictive outcome characteristics in the setting of ischemia reperfusion injury will help guide therapeutic development and potentially mitigate pathophysiologic changes in acute limb ischemia, including rhabdomyolysis. These may further lead to improvements in short- and long-term surgical outcomes and limb salvage, as well as a better understanding of the timing and selection of intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

USDA-ARS?s Scientific Manuscript database

Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

Survivin expression in head and neck squamous cell carcinomas is frequent and correlates with clinical parameters and treatment outcomes.

PubMed

Münscher, Adrian; Prochnow, Sebastian; Gulati, Amit; Sauter, Guido; Lörincz, Balazs; Blessmann, Marco; Hanken, Henning; Böttcher, Arne; Clauditz, Till Sebastian

2018-04-18

Strong expression of survivin is associated with worse survival in many different tumours, and in cell culture, a correlation between radiation resistance and survivin expression can be seen. The potential of survivin expression as a prognostic/predictive marker or therapeutic target has not been examined in head and neck squamous cell carcinomas (HNSCC) yet. Retrospective study of 452 tissue samples and clinical data from patients with squamous cell carcinomas of the larynx/hypopharynx (LSCC), oral cavity (OSCC) and oropharynx (OPSCC) treated in the University Medical Centre Hamburg-Eppendorf between 2002 and 2006. The expression patterns were detected by tissue microarray technique and correlated with clinical parameters (sex, age, tumour location, TNM 7th edition, grading, recurrence-free and overall survival). 222 OSCC, 126 OPSCC and 105 LSCC tumours of 118 females and 335 males with a mean follow-up of 41.3 months were examined. Survivin expression correlates with pN, cM, pT and overall survival. The potential of survivin as a prognostic/predictive marker is very high. The findings have to be confirmed in a larger cohort of HNSCC esp. in those tumours treated primarily with radio/radiochemotherapy.

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

C-reactive protein and other markers of inflammation in hemodialysis patients

PubMed Central

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies. PMID:24009946

C-reactive protein and other markers of inflammation in hemodialysis patients.

PubMed

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies.

Identification of Single-Copy Orthologous Genes between Physalis and Solanum lycopersicum and Analysis of Genetic Diversity in Physalis Using Molecular Markers

PubMed Central

Wei, Jingli; Hu, Xiaorong; Yang, Jingjing; Yang, Wencai

2012-01-01

The genus Physalis includes a number of commercially important edible and ornamental species. Its high nutritional value and potential medicinal properties leads to the increased commercial interest in the products of this genus worldwide. However, lack of molecular markers prevents the detailed study of genetics and phylogeny in Physalis, which limits the progress of breeding. In the present study, we compared the DNA sequences between Physalis and tomato, and attempted to analyze genetic diversity in Physalis using tomato markers. Blasting 23180 DNA sequences derived from Physalis against the International Tomato Annotation Group (ITAG) Release2.3 Predicted CDS (SL2.40) discovered 3356 single-copy orthologous genes between them. A total of 38 accessions from at least six species of Physalis were subjected to genetic diversity analysis using 97 tomato markers and 25 SSR markers derived from P. peruviana. Majority (73.2%) of tomato markers could amplify DNA fragments from at least one accession of Physalis. Diversity in Physalis at molecular level was also detected. The average Nei’s genetic distance between accessions was 0.3806 with a range of 0.2865 to 0.7091. These results indicated Physalis and tomato had similarity at both molecular marker and DNA sequence levels. Therefore, the molecular markers developed in tomato can be used in genetic study in Physalis. PMID:23166835

Identification of single-copy orthologous genes between Physalis and Solanum lycopersicum and analysis of genetic diversity in Physalis using molecular markers.

PubMed

Wei, Jingli; Hu, Xiaorong; Yang, Jingjing; Yang, Wencai

2012-01-01

The genus Physalis includes a number of commercially important edible and ornamental species. Its high nutritional value and potential medicinal properties leads to the increased commercial interest in the products of this genus worldwide. However, lack of molecular markers prevents the detailed study of genetics and phylogeny in Physalis, which limits the progress of breeding. In the present study, we compared the DNA sequences between Physalis and tomato, and attempted to analyze genetic diversity in Physalis using tomato markers. Blasting 23180 DNA sequences derived from Physalis against the International Tomato Annotation Group (ITAG) Release2.3 Predicted CDS (SL2.40) discovered 3356 single-copy orthologous genes between them. A total of 38 accessions from at least six species of Physalis were subjected to genetic diversity analysis using 97 tomato markers and 25 SSR markers derived from P. peruviana. Majority (73.2%) of tomato markers could amplify DNA fragments from at least one accession of Physalis. Diversity in Physalis at molecular level was also detected. The average Nei's genetic distance between accessions was 0.3806 with a range of 0.2865 to 0.7091. These results indicated Physalis and tomato had similarity at both molecular marker and DNA sequence levels. Therefore, the molecular markers developed in tomato can be used in genetic study in Physalis.

Multi-parametric spinal cord MRI as potential progression marker in amyotrophic lateral sclerosis.

PubMed

El Mendili, Mohamed-Mounir; Cohen-Adad, Julien; Pelegrini-Issac, Mélanie; Rossignol, Serge; Morizot-Koutlidis, Régine; Marchand-Pauvert, Véronique; Iglesias, Caroline; Sangari, Sina; Katz, Rose; Lehericy, Stéphane; Benali, Habib; Pradat, Pierre-François

2014-01-01

To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs.

Genomic Selection in Multi-environment Crop Trials.

PubMed

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

Histopathology of aortic complications in bicuspid aortic valve versus Marfan syndrome: relevance for therapy?

PubMed

Grewal, Nimrat; Franken, Romy; Mulder, Barbara J M; Goumans, Marie-José; Lindeman, Johannes H N; Jongbloed, Monique R M; DeRuiter, Marco C; Klautz, Robert J M; Bogers, Ad J J C; Poelmann, Robert E; Groot, Adriana C Gittenberger-de

2016-05-01

Patients with bicuspid aortic valve (BAV) and patients with Marfan syndrome (MFS) are more prone to develop aortic dilation and dissection compared to persons with a tricuspid aortic valve (TAV). To elucidate potential common and distinct pathways of clinical relevance, we compared the histopathological substrates of aortopathy. Ascending aortic wall biopsies were divided in five groups: BAV (n = 36) and TAV (n = 23) without and with dilation and non-dilated MFS (n = 8). General histologic features, apoptosis, the expression of markers for vascular smooth muscle cell (VSMC) maturation, markers predictive for ascending aortic dilation in BAV, and expression of fibrillin-1 were investigated. Both MFS and BAV showed an altered distribution and decreased fibrillin-1 expression in the aorta and a significantly lower level of differentiated VSMC markers. Interestingly, markers predictive for aortic dilation in BAV were not expressed in the MFS aorta. The aorta in MFS was similar to the aorta in dilated TAV with regard to the presence of medial degeneration and apoptosis, while other markers for degeneration and aging like inflammation and progerin expression were low in MFS, comparable to BAV. Both MFS and BAV aortas have immature VSMCs, while MFS and TAV patients have a similar increased rate of medial degeneration. However, the mechanism leading to apoptosis is expected to be different, being fibrillin-1 mutation induced increased angiotensin-receptor-pathway signaling in MFS and cardiovascular aging and increased progerin in TAV. Our findings could explain why angiotensin inhibition is successful in MFS and less effective in TAV and BAV patients.

Using Optical Markers of Non-dysplastic Rectal Epithelial Cells to Identify Patients With Ulcerative Colitis (UC) - Associated Neoplasia

PubMed Central

Bista, Rajan K.; Brentnall, Teresa A.; Bronner, Mary P.; Langmead, Christopher J.; Brand, Randall E.; Liu, Yang

2011-01-01

BACKGROUND Current surveillance guidelines for patients with long-standing ulcerative colitis (UC) recommend repeated colonoscopy with random biopsies, which is time-consuming, discomforting and expensive. A less invasive strategy is to identify neoplasia by analyzing biomarkers from the more accessible rectum to predict the need for a full colonoscopy. The goal of this pilot study is to evaluate whether optical markers of rectal mucosa derived from a novel optical technique – partial-wave spectroscopic microscopy (PWS) could identify UC patients with high-grade dysplasia (HGD) or cancer (CA) present anywhere in their colon. METHODS Banked frozen non-dysplastic mucosal rectal biopsies were used from 28 UC patients (15 without dysplasia and 13 with concurrent HGD or CA). The specimen slides were made using a touch prep method and underwent PWS analysis. We divided the patients into two groups: 13 as a training set and an independent 15 as a validation set. RESULTS We identified six optical markers, ranked by measuring the information gain with respect to the outcome of cancer. The most effective markers were selected by maximizing the cross validated training accuracy of a Naive Bayes classifier. The optimal classifier was applied to the validation data yielding 100% sensitivity and 75% specificity. CONCLUSIONS Our results indicate that the PWS-derived optical markers can accurately predict UC patients with HGD/CA through assessment of rectal epithelial cells. By aiming for a high sensitivity, our approach could potentially simplify the surveillance of UC patients and improve overall resource utilization by identifying patients with HGD/CA who should proceed with colonoscopy. PMID:21351200

Using optical markers of nondysplastic rectal epithelial cells to identify patients with ulcerative colitis-associated neoplasia.

PubMed

Bista, Rajan K; Brentnall, Teresa A; Bronner, Mary P; Langmead, Christopher J; Brand, Randall E; Liu, Yang

2011-12-01

Current surveillance guidelines for patients with long-standing ulcerative colitis (UC) recommend repeated colonoscopy with random biopsies, which is time-consuming, discomforting, and expensive. A less invasive strategy is to identify neoplasia by analyzing biomarkers from the more accessible rectum to predict the need for a full colonoscopy. The goal of this pilot study was to evaluate whether optical markers of rectal mucosa derived from a novel optical technique, partial-wave spectroscopic microscopy (PWS), could identify UC patients with high-grade dysplasia (HGD) or cancer (CA) present anywhere in their colon. Banked frozen nondysplastic mucosal rectal biopsies were used from 28 UC patients (15 without dysplasia and 13 with concurrent HGD or CA). The specimen slides were made using a touch prep method and underwent PWS analysis. We divided the patients into two groups: 13 as a training set and an independent 15 as a validation set. We identified six optical markers, ranked by measuring the information gain with respect to the outcome of cancer. The most effective markers were selected by maximizing the cross-validated training accuracy of a Naive Bayes classifier. The optimal classifier was applied to the validation data yielding 100% sensitivity and 75% specificity. Our results indicate that the PWS-derived optical markers can accurately predict UC patients with HGD/CA through assessment of rectal epithelial cells. By aiming for high sensitivity, our approach could potentially simplify the surveillance of UC patients and improve overall resource utilization by identifying patients with HGD/CA who should proceed with colonoscopy. Copyright © 2011 Crohn's & Colitis Foundation of America, Inc.

The Promise of Biological Markers for Treatment Response in First-Episode Psychosis: A Systematic Review

PubMed Central

Fond, Guillaume; d’Albis, Marc-Antoine; Jamain, Stéphane; Tamouza, Ryad; Arango, Celso; Fleischhacker, W. Wolfgang; Glenthøj, Birte; Leweke, Markus; Lewis, Shôn; McGuire, Phillip; Meyer-Lindenberg, Andreas; Sommer, Iris E.; Winter-van Rossum, Inge; Kapur, Shitij; Kahn, René S.; Rujescu, Dan; Leboyer, Marion

2015-01-01

Successful treatment of first-episode psychosis is one of the major factors that impacts long-term prognosis. Currently, there are no satisfactory biological markers (biomarkers) to predict which patients with a first-episode psychosis will respond to which treatment. In addition, a non-negligible rate of patients does not respond to any treatment or may develop side effects that affect adherence to the treatments as well as negatively impact physical health. Thus, there clearly is a pressing need for defining biomarkers that may be helpful to predict response to treatment and sensitivity to side effects in first-episode psychosis. The present systematic review provides (1) trials that assessed biological markers associated with antipsychotic response or side effects in first-episode psychosis and (2) potential biomarkers associated with biological disturbances that may guide the choice of conventional treatments or the prescription of innovative treatments. Trials including first-episode psychoses are few in number. Most of the available data focused on pharmacogenetics markers with so far only preliminary results. To date, these studies yielded—beside markers for metabolism of antipsychotics—no or only a few biomarkers for response or side effects, none of which have been implemented in daily clinical practice. Other biomarkers exploring immunoinflammatory, oxidative, and hormonal disturbances emerged as biomarkers of first-episode psychoses in the last decades, and some of them have been associated with treatment response. In addition to pharmacogenetics, further efforts should focus on the association of emergent biomarkers with conventional treatments or with innovative therapies efficacy, where some preliminary data suggest promising results. PMID:25759473

Multiple reaction monitoring targeted LC-MS analysis of potential cell death marker proteins for increased bioprocess control.

PubMed

Albrecht, Simone; Kaisermayer, Christian; Reinhart, David; Ambrose, Monica; Kunert, Renate; Lindeberg, Anna; Bones, Jonathan

2018-05-01

The monitoring of protein biomarkers for the early prediction of cell stress and death is a valuable tool for process characterization and efficient biomanufacturing control. A representative set of six proteins, namely GPDH, PRDX1, LGALS1, CFL1, TAGLN2 and MDH, which were identified in a previous CHO-K1 cell death model using discovery LC-MS E was translated into a targeted liquid chromatography multiple reaction monitoring mass spectrometry (LC-MRM-MS) platform and verified. The universality of the markers was confirmed in a cell growth model for which three Chinese hamster ovary host cell lines (CHO-K1, CHO-S, CHO-DG44) were grown in batch culture in two different types of basal media. LC-MRM-MS was also applied to spent media (n = 39) from four perfusion biomanufacturing series. Stable isotope-labelled peptide analogues and a stable isotope-labelled monoclonal antibody were used for improved protein quantitation and simultaneous monitoring of the workflow reproducibility. Significant increases in protein concentrations were observed for all viability marker proteins upon increased dead cell numbers and allowed for discrimination of spent media with dead cell densities below and above 1 × 10 6  dead cells/mL which highlights the potential of the selected viability marker proteins in bioprocess control. Graphical abstract Overview of the LC-MRM-MS workflow for the determination of proteomic markers in conditioned media from the bioreactor that correlate with CHO cell death.

Predicting refeeding hypophosphataemia: insulin growth factor 1 (IGF-1) as a diagnostic biochemical marker for clinical practice.

PubMed

Goyale, Atul; Ashley, Sarah L; Taylor, David R; Elnenaei, Manal O; Alaghband-Zadeh, Jamshid; Sherwood, Roy A; le Roux, Carel W; Vincent, Royce P

2015-01-01

Refeeding syndrome (RS) is a potentially fatal condition that can occur following the re-introduction of nutrition after a period of starvation. Hypophosphataemia following the reintroduction of nutrition is often the only reliable biochemical marker of RS. Refeeding index (RI) generated from baseline insulin-like growth factor-1 (IGF-1) and leptin has been proposed as a useful biochemical marker for the identification of patients at risk of developing refeeding hypophosphataemia (RH). A prospective study included 52 patients referred for parenteral nutrition (PN). The sensitivity and specificity of IGF-1 measured using a sensitive assay was compared to the RI in predicting the development of RH (a ≥ 30% drop in PO4 during the first 36-h of PN administration). Leptin and IGF-1 were analysed on baseline samples using a quantitative enzyme-linked immunoassay. Daily blood samples were collected from all patients for routine biochemistry for the full duration of PN administration. High sensitivity IGF-1 measurement alone was comparable with the RI, using receiver-operating characteristic (ROC) curve analysis, with areas under the curve being 0.79 and 0.80, respectively, and superior to leptin alone (0.72) for predicting ≥ 30% drop in PO4. The cut-off value for IGF-1 that gave best sensitivity (91% [95% CI 75-98%]) and specificity (65% [95% CI 41-85%]) was 63.7 µg/L, with a likelihood ratio of 2.59. Baseline IGF-1 is an objective, sensitive and specific biochemical marker in identifying patients who are at high risk of developing RH prior to PN administration and therefore may have a role in clinical practice. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Which hemostatic markers add to the predictive value of conventional risk factors for coronary heart disease and ischemic stroke? The Caerphilly Study.

PubMed

Smith, Ann; Patterson, Chris; Yarnell, John; Rumley, Ann; Ben-Shlomo, Yoav; Lowe, Gordon

2005-11-15

Few studies have examined whether hemostatic markers contribute to risk of coronary disease and ischemic stroke independently of conventional risk factors. This study examines 11 hemostatic markers that reflect different aspects of the coagulation process to determine which have prognostic value after accounting for conventional risk factors. A total of 2398 men aged 49 to 65 years were examined in 1984 to 1988, and the majority gave a fasting blood sample for assay of lipids and hemostatic markers. Men were followed up for a median of 13 years, and cardiovascular disease (CVD) events were recorded. There were 486 CVD events in total, 353 with prospective coronary disease and 133 with prospective ischemic stroke. On univariable analysis, fibrinogen, low activated protein C ratio, D-dimer, tissue plasminogen activator (tPA), and plasminogen activator inhibitor-1 (PAI-1) were associated significantly with risk of CVD. On multivariable analyses with conventional risk factors forced into the proportional hazards model, fibrinogen, D-dimer, and PAI-1 were significantly associated with risk of CVD, whereas factor VIIc showed an inverse association (P=0.001). In a model that contained the conventional risk factors, the hazard ratio for subsequent CVD in the top third of the distribution of predicted risk relative to the bottom third was 2.7 for subjects without preexisting CVD. This ratio increased to 3.7 for the model that also contained the 4 hemostatic factors. Fibrinogen, D-dimer, PAI-1 activity, and factor VIIc each has potential to increase the prediction of coronary disease/ischemic stroke in middle-aged men, in addition to conventional risk factors.

Relationship between family history of type 2 diabetes and serum FGF21.

PubMed

Davis, Greggory R; Deville, Tiffany; Guillory, Joshua; Bellar, David; Nelson, Arnold G

2017-11-01

Determining predictive markers for the development of type 2 diabetes (T2D), particularly in young individuals, offers immense potential benefits in preventative medicine. Previous research examining serum fibroblast growth factor 21 (FGF21) in humans has revealed equivocal relationships with clinical markers of metabolic dysfunction. However, it is unknown to what extent, if any, first-degree family history of T2D (mother or father of the participant diagnosed with T2D) level affects serum FGF21 levels. The aim of this study was to determine whether in healthy individuals with FH+ (n = 18) and without FH- (n = 17) a family history of T2D affects serum FGF21. Fasting serum and clinical, metabolic and anthropometric measures were determined using a cross-sectional design. Differences between groups for FGF21 were not significant (FH+ = 266 pg/mL ± 51·4, FH = 180 pg/mL ± 29; Z = 0·97, P = 0·33). Adiponectin values were lower in FH+ (8·81 μg/mL ± 2·14) compared to FH- (10·65 μg/mL ± 1·44; F = 8·83, P = 0·01). Resistin was negatively correlated with FGF21 for all participants (r = -0·38, P = 0·03), but no other clinical, metabolic, or serum markers were predictive for serum FGF21 in FH+ or FH-. Serum FGF21 is not significantly different between FH+ and FH- in young, healthy individuals. Based upon the data of this pilot study, it is unclear whether serum FGF21 can be used as a stand-alone predictive marker for T2D in healthy subjects. © 2017 Stichting European Society for Clinical Investigation Journal Foundation.

Extension and refinement of the predictive value of different classes of markers in ADNI: Four year follow-up data

PubMed Central

Gomar, Jesus J; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

2014-01-01

Background This study examined the predictive value of different classes of markers in the progression from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD) over an extended 4 year follow-up in ADNI. Methods MCI patients assessed on clinical, cognitive, MRI, PET-FDG, and CSF markers at baseline, and followed on a yearly basis for four years to ascertain progression to AD. Logistic regression models were fitted in clusters including demographics, APOE genotype, cognitive markers, and biomarkers (morphometric, PET-FDG, CSF Abeta and tau). Results The predictive model at four years revealed that two cognitive measures, an episodic memory measure and a clock drawing screening test, were the best predictors of conversion (AUC= 0.78). Conclusions This model of prediction is consistent to the previous model at two years, thus highlighting the importance of cognitive measures in progression from MCI to AD. Cognitive markers were more robust predictors than biomarkers. PMID:24613706

Individualization of controlled ovarian stimulation in IVF using ovarian reserve markers: from theory to practice.

PubMed

La Marca, Antonio; Sunkara, Sesh Kamal

2014-01-01

The main objective of individualization of treatment in IVF is to offer every single woman the best treatment tailored to her own unique characteristics, thus maximizing the chances of pregnancy and eliminating the iatrogenic and avoidable risks resulting from ovarian stimulation. Personalization of treatment in IVF should be based on the prediction of ovarian response for every individual. The starting point is to identify if a woman is likely to have a normal, poor or a hyper response and choose the ideal treatment protocol tailored to this prediction. The objective of this review is to summarize the predictive ability of ovarian reserve markers, such as antral follicle count (AFC) and anti-Mullerian hormone (AMH), and the therapeutic strategies that have been proposed in IVF after this prediction. A systematic review of the existing literature was performed by searching Medline, EMBASE, Cochrane library and Web of Science for publications in the English language related to AFC, AMH and their incorporation into controlled ovarian stimulation (COS) protocols in IVF. Literature available to May 2013 was included. The search generated 305 citations of which 41 and 25 studies, respectively, reporting the ability of AMH and AFC to predict response to COS were included in this review. The literature review demonstrated that AFC and AMH, the most sensitive markers of ovarian reserve identified to date, are ideal in planning personalized COS protocols. These sensitive markers permit prediction of the whole spectrum of ovarian response with reliable accuracy and clinicians may use either of the two markers as they can be considered interchangeable. Following the categorization of expected ovarian response to stimulation clinicians can adopt tailored therapeutic strategies for each patient. Current scientific trend suggests the elective use of the GnRH antagonist based regimen for hyper-responders, and probably also poor responders, as likely to be beneficial. The selection of the appropriate and individualized gonadotrophin dose is also of paramount importance for effective COS and subsequent IVF outcomes. Personalized IVF offers several benefits; it enables clinicians to give women more accurate information on their prognosis thus facilitating counselling especially in cases of extremes of ovarian response. The deployment of therapeutic strategies based on selective use of GnRH analogues and the fine tuning of the gonadotrophin dose on the basis of potential ovarian response in every single woman can allow for a safer and more effective IVF practice.

Concise Review: Multifaceted Characterization of Human Mesenchymal Stem Cells for Use in Regenerative Medicine

PubMed Central

Samsonraj, Rebekah M.; Raghunath, Michael; Nurcombe, Victor; Hui, James H.

2017-01-01

Abstract Mesenchymal stem cells (MSC) hold great potential for regenerative medicine because of their ability for self‐renewal and differentiation into tissue‐specific cells such as osteoblasts, chondrocytes, and adipocytes. MSCs orchestrate tissue development, maintenance and repair, and are useful for musculoskeletal regenerative therapies to treat age‐related orthopedic degenerative diseases and other clinical conditions. Importantly, MSCs produce secretory factors that play critical roles in tissue repair that support both engraftment and trophic functions (autocrine and paracrine). The development of uniform protocols for both preparation and characterization of MSCs, including standardized functional assays for evaluation of their biological potential, are critical factors contributing to their clinical utility. Quality control and release criteria for MSCs should include cell surface markers, differentiation potential, and other essential cell parameters. For example, cell surface marker profiles (surfactome), bone‐forming capacities in ectopic and orthotopic models, as well as cell size and granularity, telomere length, senescence status, trophic factor secretion (secretome), and immunomodulation, should be thoroughly assessed to predict MSC utility for regenerative medicine. We propose that these and other functionalities of MSCs should be characterized prior to use in clinical applications as part of comprehensive and uniform guidelines and release criteria for their clinical‐grade production to achieve predictably favorable treatment outcomes for stem cell therapy. Stem Cells Translational Medicine 2017;6:2173–2185 PMID:29076267

Comparison of Models and Whole-Genome Profiling Approaches for Genomic-Enabled Prediction of Septoria Tritici Blotch, Stagonospora Nodorum Blotch, and Tan Spot Resistance in Wheat.

PubMed

Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

2017-07-01

The leaf spotting diseases in wheat that include Septoria tritici blotch (STB) caused by , Stagonospora nodorum blotch (SNB) caused by , and tan spot (TS) caused by pose challenges to breeding programs in selecting for resistance. A promising approach that could enable selection prior to phenotyping is genomic selection that uses genome-wide markers to estimate breeding values (BVs) for quantitative traits. To evaluate this approach for seedling and/or adult plant resistance (APR) to STB, SNB, and TS, we compared the predictive ability of least-squares (LS) approach with genomic-enabled prediction models including genomic best linear unbiased predictor (GBLUP), Bayesian ridge regression (BRR), Bayes A (BA), Bayes B (BB), Bayes Cπ (BC), Bayesian least absolute shrinkage and selection operator (BL), and reproducing kernel Hilbert spaces markers (RKHS-M), a pedigree-based model (RKHS-P) and RKHS markers and pedigree (RKHS-MP). We observed that LS gave the lowest prediction accuracies and RKHS-MP, the highest. The genomic-enabled prediction models and RKHS-P gave similar accuracies. The increase in accuracy using genomic prediction models over LS was 48%. The mean genomic prediction accuracies were 0.45 for STB (APR), 0.55 for SNB (seedling), 0.66 for TS (seedling) and 0.48 for TS (APR). We also compared markers from two whole-genome profiling approaches: genotyping by sequencing (GBS) and diversity arrays technology sequencing (DArTseq) for prediction. While, GBS markers performed slightly better than DArTseq, combining markers from the two approaches did not improve accuracies. We conclude that implementing GS in breeding for these diseases would help to achieve higher accuracies and rapid gains from selection. Copyright © 2017 Crop Science Society of America.

Genomewide predictions from maize single-cross data.

PubMed

Massman, Jon M; Gordillo, Andres; Lorenzana, Robenzon E; Bernardo, Rex

2013-01-01

Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r(MG)) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r(MG) values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r(MG) values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r(2) between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (cofmpared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.

Petri net-based prediction of therapeutic targets that recover abnormally phosphorylated proteins in muscle atrophy.

PubMed

Jung, Jinmyung; Kwon, Mijin; Bae, Sunghwa; Yim, Soorin; Lee, Doheon

2018-03-05

Muscle atrophy, an involuntary loss of muscle mass, is involved in various diseases and sometimes leads to mortality. However, therapeutics for muscle atrophy thus far have had limited effects. Here, we present a new approach for therapeutic target prediction using Petri net simulation of the status of phosphorylation, with a reasonable assumption that the recovery of abnormally phosphorylated proteins can be a treatment for muscle atrophy. The Petri net model was employed to simulate phosphorylation status in three states, i.e. reference, atrophic and each gene-inhibited state based on the myocyte-specific phosphorylation network. Here, we newly devised a phosphorylation specific Petri net that involves two types of transitions (phosphorylation or de-phosphorylation) and two types of places (activation with or without phosphorylation). Before predicting therapeutic targets, the simulation results in reference and atrophic states were validated by Western blotting experiments detecting five marker proteins, i.e. RELA, SMAD2, SMAD3, FOXO1 and FOXO3. Finally, we determined 37 potential therapeutic targets whose inhibition recovers the phosphorylation status from an atrophic state as indicated by the five validated marker proteins. In the evaluation, we confirmed that the 37 potential targets were enriched for muscle atrophy-related terms such as actin and muscle contraction processes, and they were also significantly overlapping with the genes associated with muscle atrophy reported in the Comparative Toxicogenomics Database (p-value < 0.05). Furthermore, we noticed that they included several proteins that could not be characterized by the shortest path analysis. The three potential targets, i.e. BMPR1B, ROCK, and LEPR, were manually validated with the literature. In this study, we suggest a new approach to predict potential therapeutic targets of muscle atrophy with an analysis of phosphorylation status simulated by Petri net. We generated a list of the potential therapeutic targets whose inhibition recovers abnormally phosphorylated proteins in an atrophic state. They were evaluated by various approaches, such as Western blotting, GO terms, literature, known muscle atrophy-related genes and shortest path analysis. We expect the new proposed strategy to provide an understanding of phosphorylation status in muscle atrophy and to provide assistance towards identifying new therapies.

Management of hepatocellular carcinoma: Predictive value of immunohistochemical markers for postoperative survival

PubMed Central

Niu, Zhao-Shan; Niu, Xiao-Jun; Wang, Mei

2015-01-01

Hepatocellular carcinoma (HCC) accounts for over 90% of all primary liver cancers. With an ever increasing incidence trend year by year, it has become the third most common cause of death from cancer worldwide. Hepatic resection is generally considered to be one of the most effective therapies for HCC patients, however, there is a high risk of recurrence in postoperative HCC. In clinical practice, there exists an urgent need for valid prognostic markers to identify patients with prognosis, hence the importance of studies on prognostic markers in improving the prediction of HCC prognosis. This review focuses on the most promising immunohistochemical prognostic markers in predicting the postoperative survival of HCC patients. PMID:25624992

Common Marker Genes Identified from Various Sample Types for Systemic Lupus Erythematosus.

PubMed

Bing, Peng-Fei; Xia, Wei; Wang, Lan; Zhang, Yong-Hong; Lei, Shu-Feng; Deng, Fei-Yan

2016-01-01

Systemic lupus erythematosus (SLE) is a complex auto-immune disease. Gene expression studies have been conducted to identify SLE-related genes in various types of samples. It is unknown whether there are common marker genes significant for SLE but independent of sample types, which may have potentials for follow-up translational research. The aim of this study is to identify common marker genes across various sample types for SLE. Based on four public microarray gene expression datasets for SLE covering three representative types of blood-born samples (monocyte; peripheral blood mononuclear cell, PBMC; whole blood), we utilized three statistics (fold-change, FC; t-test p value; false discovery rate adjusted p value) to scrutinize genes simultaneously regulated with SLE across various sample types. For common marker genes, we conducted the Gene Ontology enrichment analysis and Protein-Protein Interaction analysis to gain insights into their functions. We identified 10 common marker genes associated with SLE (IFI6, IFI27, IFI44L, OAS1, OAS2, EIF2AK2, PLSCR1, STAT1, RNASE2, and GSTO1). Significant up-regulation of IFI6, IFI27, and IFI44L with SLE was observed in all the studied sample types, though the FC was most striking in monocyte, compared with PBMC and whole blood (8.82-251.66 vs. 3.73-74.05 vs. 1.19-1.87). Eight of the above 10 genes, except RNASE2 and GSTO1, interact with each other and with known SLE susceptibility genes, participate in immune response, RNA and protein catabolism, and cell death. Our data suggest that there exist common marker genes across various sample types for SLE. The 10 common marker genes, identified herein, deserve follow-up studies to dissert their potentials as diagnostic or therapeutic markers to predict SLE or treatment response.

Salivary Cortisol: A Psychophysiological Marker for PTSD

DTIC Science & Technology

2011-04-01

potential to develop PTSD or PTSD symptoms. Stress is often known as the negative consequence of the failure to respond appropriately to the emotional or...is capable of PTG, not everyone necessarily will exhibit PTG. 4 The Brain & Stress In addition to understanding the emotional and...going to happen they begin to anticipate it. This primary anticipation precipitates an anticipatory emotional response, and this response predicts the

Biomarkers Associated with Cognitive Impairment in Treated Cancer Patients: Potential Predisposition and Risk Factors

PubMed Central

Castel, Hélène; Denouel, Angeline; Lange, Marie; Tonon, Marie-Christine; Dubois, Martine; Joly, Florence

2017-01-01

Purpose: Cognitive impairment in cancer patients induced, at least in part, by treatment are frequently observed and likely have negative impacts on patient quality of life. Such cognitive dysfunctions can affect attention, executive functions, and memory and processing speed, can persist after treatment, and their exact causes remain unclear. The aim of this review was to create an inventory and analysis of clinical studies evaluating biological markers and risk factors for cognitive decline in cancer patients before, during, or after therapy. The ultimate objectives were to identify robust markers and to determine what further research is required to develop original biological markers to enable prevention or adapted treatment management of patients at risk. Method: This review was guided by the PRISMA statement and included a search strategy focused on three components: “cognition disorders,” “predictive factors”/“biological markers,” and “neoplasms,” searched in PubMed since 2005, with exclusion criteria concerning brain tumors, brain therapy, and imaging or animal studies. Results: Twenty-three studies meeting the criteria were analyzed. Potential associations/correlations were identified between cognitive impairments and specific circulating factors, cerebral spinal fluid constituents, and genetic polymorphisms at baseline, during, and at the end of treatment in cancer populations. The most significant results were associations between cognitive dysfunctions and genetic polymorphisms, including APOE-4 and COMT-Val; increased plasma levels of the pro-inflammatory cytokine, IL-6; anemia; and hemoglobin levels during chemotherapy. Plasma levels of specific hormones of the hypothalamo-pituitary-adrenal axis are also modified by treatment. Discussion: It is recognized in the field of cancer cognition that cancer and comorbidities, as well as chemotherapy and hormone therapy, can cause persistent cognitive dysfunction. A number of biological circulating factors and genetic polymorphisms, can predispose to the development of cognitive disorders. However, many predictive factors remain unproven and discordant findings are frequently reported, warranting additional clinical and preclinical longitudinal cohort studies, with goals of better characterization of potential biomarkers and identification of patient populations at risk and/or particularly deleterious treatments. Research should focus on prevention and personalized cancer management, to improve the daily lives, autonomy, and return to work of patients. PMID:28377717

Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

PubMed

Savolainen, Otto; Fagerberg, Björn; Vendelbo Lind, Mads; Sandberg, Ann-Sofie; Ross, Alastair B; Bergström, Göran

2017-01-01

The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA), smoking, serum adiponectin)) alone, and in combination with metabolomics had the largest areas under the curve (AUC) (0.794 (95% confidence interval [0.738-0.850]) and 0.808 [0.749-0.867] respectively), with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577-0.736]). Prediction based on non-blood based measures was 0.638 [0.565-0.711]). Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model.

Biomarkers for predicting type 2 diabetes development—Can metabolomics improve on existing biomarkers?

PubMed Central

Savolainen, Otto; Fagerberg, Björn; Vendelbo Lind, Mads; Sandberg, Ann-Sofie; Ross, Alastair B.; Bergström, Göran

2017-01-01

Aim The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Methods Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Results Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA), smoking, serum adiponectin)) alone, and in combination with metabolomics had the largest areas under the curve (AUC) (0.794 (95% confidence interval [0.738–0.850]) and 0.808 [0.749–0.867] respectively), with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577–0.736]). Prediction based on non-blood based measures was 0.638 [0.565–0.711]). Conclusions Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model. PMID:28692646

A practical guide to epidemiological practice and standards in the identification and validation of diagnostic markers using a bladder cancer example.

PubMed

Behrens, T; Bonberg, N; Casjens, S; Pesch, B; Brüning, T

2014-01-01

Technical advances to analyze biological markers have generated a plethora of promising new marker candidates for early detection of cancer. However, in subsequent analyses only few could be successfully validated as being predictive, clinically useful, or effective. This failure is partially due to rapid publication of results that were detected in early stages of biomarker research. Methodological considerations are a major concern when carrying out molecular epidemiological studies of diagnostic markers to avoid errors that increase the potential for bias. Although guidelines for conducting studies and reporting of results have been published to improve the quality of marker studies, their planning and execution still need to be improved. We will discuss different sources of bias in study design, handling of specimens, and statistical analysis to illustrate possible pitfalls associated with marker research, and present legal, ethical, and technical considerations associated with storage and handling of specimens. This article presents a guide to epidemiological standards in marker research using bladder cancer as an example. Because of the possibility to detect early cancer stages due to leakage of molecular markers from the target organ or exfoliation of tumor cells into the urine, bladder cancer is particularly useful to study diagnostic markers. To improve the overall quality of marker research, future developments should focus on networks of studies and tissue banks according to uniform legal, ethical, methodological, and technical standards. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. © 2013.

Frequency of serum tumour marker monitoring in patients with non-seminomatous germ cell tumours.

PubMed Central

Seckl, M. J.; Rustin, G. J.; Bagshawe, K. D.

1990-01-01

In patients relapsing on surveillance following orchidectomy for stage 1 non-seminomatous germ cell tumours, it is essential that treatment is initiated before they develop advanced disease with a poor prognosis. Patients who start chemotherapy with levels of human chorionic gonadotrophin (HCG) greater than 1,000 i.u. l-1 and/or alpha-fetoprotein (AFP) level greater than 500 ku l-1 have been shown to have a worse prognosis than patients with lower marker levels. We studied 64 patients between 1968 and 1987 with rising serial tumour markers. The potential time in which markers could rise to poor prognostic levels was calculated assuming an exponential rate of increase. Adverse levels were predicted in one patient (1.6%) within 7 days, in two patients (3.1%) within 14 days, in eight patients (12.5%) within 4 weeks and in 16 patients (25%) within 6 weeks. This suggests that, initially, weekly marker estimations should be performed on stage 1 surveillance patients. The extra cost to a specialist follow-up laboratory of weekly as opposed to the usual monthly marker measurements will be less than 33,600 pounds for every 400 patients on surveillance. One extra patient is likely to be cured for this sum. PMID:1695522

Dressed to kill? Visible markers of coalitional affiliation enhance conceptualized formidability.

PubMed

Fessler, Daniel M T; Holbrook, Colin; Dashoff, David

2016-01-01

Displaying markers of coalitional affiliation is a common feature of contemporary life. In situations in which interaction with members of rival coalitions is likely, signaling coalitional affiliation may simultaneously constitute an implicit challenge to opponents and an objective commitment device, binding signalers to their coalitions. Individuals who invite conflict, and who cannot readily back out of conflict, constitute a greater threat than those who avoid conflict and preserve the option of feigning neutrality. As a consequence, the former should be viewed as more formidable than the latter. Recent research indicates that relative formidability is summarized using the envisioned physical size and strength of a potential antagonist. Thus, individuals who display markers of coalitional affiliation should be conceptualized as more physically imposing than those who do not. We tested this prediction in two experiments. In Study 1, conducted with U.S. university students, participants inspected images of sports fans' faces. In Study 2, conducted with U.S. Mechanical Turk workers, participants read vignettes depicting political partisans. In both studies, participants estimated the physical formidability of the target individuals and reported their own ability to defend themselves; in Study 2, participants estimated the target's aggressiveness. Consonant with predictions, targets depicted as signaling coalitional affiliation in situations of potential conflict were envisioned to be more physically formidable and more aggressive than were those not depicted as signaling thusly. Underscoring that the calculations at issue concern the possibility of violent conflict, participants' estimates of the protagonist's features were inversely correlated with their ability to defend themselves. © 2016 Wiley Periodicals, Inc.

Exploring the Q-marker of "sweat soaking method" processed radix Wikstroemia indica: Based on the "effect-toxicity-chemicals" study.

PubMed

Feng, Guo; Chen, Yun-Long; Li, Wei; Li, Lai-Lai; Wu, Zeng-Guang; Wu, Zi-Jun; Hai, Yue; Zhang, Si-Chao; Zheng, Chuan-Qi; Liu, Chang-Xiao; He, Xin

2018-06-01

Radix Wikstroemia indica (RWI), named "Liao Ge Wang" in Chinese, is a kind of toxic Chinese herbal medicine (CHM) commonly used in Miao nationality of South China. "Sweat soaking method" processed RWI could effectively decrease its toxicity and preserve therapeutic effect. However, the underlying mechanism of processing is still not clear, and the Q-markers database for processed RWI has not been established. Our study is to investigate and establish the quality evaluation system and potential Q-markers based on "effect-toxicity-chemicals" relationship of RWI for quality/safety assessment of "sweat soaking method" processing. The variation of RWI in efficacy and toxicity before and after processing was investigated by pharmacological and toxicological studies. Cytotoxicity test was used to screen the cytotoxicity of components in RWI. The material basis in ethanol extract of raw and processed RWI was studied by UPLC-Q-TOF/MS. And the potential Q-markers were analyzed and predicted according to "effect-toxicity-chemical" relationship. RWI was processed by "sweat soaking method", which could preserve efficacy and reduce toxicity. Raw RWI and processed RWI did not show significant difference on the antinociceptive and anti-inflammatory effect, however, the injury of liver and kidney by processed RWI was much weaker than that by raw RWI. The 20 compounds were identified from the ethanol extract of raw product and processed product of RWI using UPLC-Q-TOF/MS, including daphnoretin, emodin, triumbelletin, dibutyl phthalate, Methyl Paraben, YH-10 + OH and matairesinol, arctigenin, kaempferol and physcion. Furthermore, 3 diterpenoids (YH-10, YH-12 and YH-15) were proved to possess the high toxicity and decreased by 48%, 44% and 65%, respectively, which could be regarded as the potential Q-markers for quality/safety assessment of "sweat soaking method" processed RWI. A Q-marker database of processed RWI by "sweat soaking method" was established according to the results and relationship of "effect-toxicity-chemicals", which provided a scientific evidence for processing methods, mechanism and the clinical application of RWI, also provided experimental results to explore the application of Q-marker in CHM. Copyright © 2018 Elsevier GmbH. All rights reserved.

Markers predicting response to bacillus Calmette-Guérin immunotherapy in high-risk bladder cancer patients: a systematic review.

PubMed

Zuiverloon, Tahlita C M; Nieuweboer, Annemieke J M; Vékony, Hedvig; Kirkels, Wim J; Bangma, Chris H; Zwarthoff, Ellen C

2012-01-01

Currently, bacillus Calmette-Guérin (BCG) intravesical instillations are standard treatment for patients with high-grade non-muscle-invasive bladder cancer; however, no markers are available to predict BCG response. To review the contemporary literature on markers predicting BCG response, to discuss the key issues concerning the identification of predictive markers, and to provide recommendations for further research studies. We performed a systematic review of the literature using PubMed and Embase databases in the period 1996-2010. The free-text search was extended by adding the following keywords: recurrence, progression, survival, molecular marker, prognosis, TP53, Ki-67, RB, fibronectin, immunotherapy, cytokine, interleukin, natural killer, macrophage, PMN, polymorphism, SNP, single nucleotide polymorphism, and gene signature. If thresholds for the detection of urinary interleukin (IL)-8, IL-18, and tumour necrosis factor apoptosis-inducing ligand levels are standardised, measurement of these cytokines holds promise in the assessment of BCG therapy outcome. Studies on immunohistochemical markers (ie, TP53, Ki-67, and retinoblastoma) display contradictory results, probably because of the small patient groups that were used and seem unsuitable to predict BCG response. Exploring combinations of protein levels might prove to be more helpful to establish the effect of BCG therapy. Single nucleotide polymorphisms, either in cytokines or in genes involved in DNA repair, need to be investigated in different ethnicities before their clinical relevance can be determined. Measurement of urinary IL-2 levels seems to be the most potent marker of all the clinical parameters reviewed. IL-2 levels are currently the most promising predictive markers of BCG response. For future studies focusing on new biomarkers, it is essential to make more use of new biomedical techniques such as microRNA profiling and genomewide sequencing. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Metaphylogenomic and Potential Functionality of the Limpet Patella pellucida’s Gastrointestinal Tract Microbiome

PubMed Central

Dudek, Magda; Adams, Jessica; Swain, Martin; Hegarty, Matthew; Huws, Sharon; Gallagher, Joe

2014-01-01

This study investigated the microbial diversity associated with the digestive tract of the seaweed grazing marine limpet Patella pellucida. Using a modified indirect DNA extraction protocol and performing metagenomic profiling based on specific prokaryotic marker genes, the abundance of bacterial groups was identified from the analyzed metagenome. The members of three significantly abundant phyla of Proteobacteria, Firmicutes and Bacteroidetes were characterized through the literature and their predicted functions towards the host, as well as potential applications in the industrial environment assessed. PMID:25334059

Novel Applications of Multi-task Learning and Multiple Output Regression to Multiple Genetic Trait Prediction

USDA-ARS?s Scientific Manuscript database

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait predicti...

Intestinal Fatty Acid Binding Protein as a Marker of Necrosis and Severity in Acute Pancreatitis.

PubMed

Kupčinskas, Juozas; Gedgaudas, Rolandas; Hartman, Hannes; Sippola, Tomi; Lindström, Outi; Johnson, Colin D; Regnér, Sara

2018-07-01

The aim of this study was to study intestinal fatty acid binding protein (i-FABP) as a potential biomarker in predicting severity of acute pancreatitis (AP). In a prospective multicenter cohort study, plasma levels of i-FABP were measured in 402 patients with AP. Severity of AP was determined based on the 1992 Atlanta Classification. Admission levels of plasma i-FABP were significantly higher in patients with pancreatic necrosis, in patients having systemic complications, in patients treated invasively, in patients treated in the intensive care unit, in patients with severe AP, and in deceased patients. Plasma i-FABP levels on admission yielded an area under curve (AUC) of 0.732 in discriminating patients with or without pancreatic necrosis and AUC of 0.669 in predicting severe AP. Combination of levels of i-FABP and venous lactate on the day of admission showed higher discriminative power in severe AP-AUC of 0.808. Higher i-FABP levels on admission were associated with pancreatic necrosis, systemic complications, and severe AP. Low levels of i-FABP had a high negative predictive value for pancreatic necrosis and severe AP. Combination of levels of i-FABP and venous lactates on admission were superior to either of markers used alone in predicting severe AP.

Key Clinical Factors Predicting Adipokine and Oxidative Stress Marker Concentrations among Normal, Overweight and Obese Pregnant Women Using Artificial Neural Networks.

PubMed

Solis-Paredes, Mario; Estrada-Gutierrez, Guadalupe; Perichart-Perera, Otilia; Montoya-Estrada, Araceli; Guzmán-Huerta, Mario; Borboa-Olivares, Héctor; Bravo-Flores, Eyerahi; Cardona-Pérez, Arturo; Zaga-Clavellina, Veronica; Garcia-Latorre, Ethel; Gonzalez-Perez, Gabriela; Hernández-Pérez, José Alfredo; Irles, Claudine

2017-12-28

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2'-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2'-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care.

Social networks and inflammatory markers in the Framingham Heart Study.

PubMed

Loucks, Eric B; Sullivan, Lisa M; D'Agostino, Ralph B; Larson, Martin G; Berkman, Lisa F; Benjamin, Emelia J

2006-11-01

Lack of social integration predicts coronary heart disease mortality in prospective studies; however, the biological pathways that may be responsible are poorly understood. The specific aims of this study were to examine whether social networks are associated with serum concentrations of the inflammatory markers interleukin-6 (IL-6), C-reactive protein (CRP), soluble intercellular adhesion molecule-1 (sICAM-1) and monocyte chemoattractant protein-1 (MCP-1). Participants in the Framingham Study attending examinations from 1998 to 2001 (n=3267) were eligible for inclusion in the study. Social networks were assessed using the Berkman-Syme Social Network Index (SNI). Concentrations of IL-6, CRP, sICAM-1 and MCP-1 were measured in fasting serum samples. Multivariable linear regression analyses were used to assess the association of social networks with inflammatory markers adjusting for potential confounders including age, smoking, blood pressure, total:HDL cholesterol ratio, body mass index, lipid-lowering and antihypertensive medication, diabetes, cardiovascular disease, depression and socioeconomic status. Results found that the SNI was significantly inversely associated with IL-6 in men (p=0.03) after adjusting for potential confounders. In age-adjusted analyses, social networks also were significantly inversely associated with IL-6 for women (p=0.03) and were marginally to modestly associated with CRP and sICAM-1 for men (p=0.08 and 0.02, respectively), but these associations were not significant in the multivariate analyses. In conclusion, social networks were found to be inversely associated with interleukin-6 levels in men. The possibility that inflammatory markers may be potential mediators between social integration and coronary heart disease merits further investigation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ausborn, Natalie L.; Le, Quynh Thu; Bradley, Jeffrey D.

Therapeutic decisions in non-small cell lung cancer (NSCLC) have been mainly based on disease stage, performance status, and co-morbidities, and rarely on histological or molecular classification. Rather than applying broad treatments to unselected patients that may result in survival increase of only weeks to months, research efforts should be, and are being, focused on identifying predictive markers for molecularly targeted therapy and determining genomic signatures that predict survival and response to specific therapies. The availability of such targeted biologics requires their use to be matched to tumors of corresponding molecular vulnerability for maximum efficacy. Molecular markers such as epidermal growthmore » factor receptor (EGFR), K-ras, vascular endothelial growth factor (VEGF), mammalian target of rapamycin (mTOR), and anaplastic lymphoma kinase (ALK) represent potential parameters guide treatment decisions. Ultimately, identifying patients who will respond to specific therapies will allow optimal efficacy with minimal toxicity, which will result in more judicious and effective application of expensive targeted therapy as the new paradigm of personalized medicine develops.« less

Serum-circulating miRNAs predict neuroblastoma progression in mouse model of high-risk metastatic disease.

PubMed

Ramraj, Satish Kumar; Aravindan, Sheeja; Somasundaram, Dinesh Babu; Herman, Terence S; Natarajan, Mohan; Aravindan, Natarajan

2016-04-05

Circulating miRNAs have momentous clinical relevance as prognostic biomarkers and in the progression of solid tumors. Recognizing novel candidates of neuroblastoma-specific circulating miRNAs would allow us to identify potential prognostic biomarkers that could predict the switch from favorable to high-risk metastatic neuroblastoma (HR-NB). Utilizing mouse models of favorable and HR-NB and whole miRnome profiling, we identified high serum levels of 34 and low levels of 46 miRNAs in animals with HR-NB. Preferential sequence homology exclusion of mouse miRNAs identified 25 (11 increased; 14 decreased) human-specific prognostic marker candidates, of which, 21 were unique to HR-NB. miRNA QPCR validated miRnome profile. Target analysis defined the candidate miRNAs' signal transduction flow-through and demonstrated their converged roles in tumor progression. miRNA silencing studies verified the function of select miRNAs on the translation of at least 14 target proteins. Expressions of critical targets that correlate tumor progression in tissue of multifarious organs identify the orchestration of HR-NB. Significant (>10 fold) increase in serum levels of miR-381, miR-548h, and miR-580 identify them as potential prognostic markers for neuroblastoma progression. For the first time, we identified serum-circulating miRNAs that predict the switch from favorable to HR-NB and, further imply that these miRNAs could play a functional role in tumor progression.

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

PubMed Central

Beaulieu, J; Doerksen, T; Clément, S; MacKay, J; Bousquet, J

2014-01-01

Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach. PMID:24781808

Procalcitonin as a potential predicting factor for prognosis in bacterial meningitis.

PubMed

Park, Bong Soo; Kim, Si Eun; Park, Si Hyung; Kim, Jinseung; Shin, Kyong Jin; Ha, Sam Yeol; Park, JinSe; Kim, Sung Eun; Lee, Byung In; Park, Kang Min

2017-02-01

We investigated the potential role of serum procalcitonin in differentiating bacterial meningitis from viral meningitis, and in predicting the prognosis in patients with bacterial meningitis. This was a retrospective study of 80 patients with bacterial meningitis (13 patients died). In addition, 58 patients with viral meningitis were included as the disease control groups for comparison. The serum procalcitonin level was measured in all patients at admission. Differences in demographic and laboratory data, including the procalcitonin level, were analyzed between the groups. We used the mortality rate during hospitalization as a marker of prognosis in patients with bacterial meningitis. Multiple logistic regression analysis showed that high serum levels of procalcitonin (>0.12ng/mL) were an independently significant variable for differentiating bacterial meningitis from viral meningitis. The risk of having bacterial meningitis with high serum levels of procalcitonin was at least 6 times higher than the risk of having viral meningitis (OR=6.76, 95% CI: 1.84-24.90, p=0.004). In addition, we found that high levels of procalcitonin (>7.26ng/mL) in the blood were an independently significant predictor for death in patients with bacterial meningitis. The risk of death in patients with bacterial meningitis with high serum levels of procalcitonin may be at least 9 times higher than those without death (OR=9.09, 95% CI: 1.74-47.12, p=0.016). We found that serum procalcitonin is a useful marker for differentiating bacterial meningitis from viral meningitis, and it is also a potential predicting factor for prognosis in patients with bacterial meningitis. Copyright © 2016 Elsevier Ltd. All rights reserved.

DNA methylation-based age prediction from various tissues and body fluids

PubMed Central

Jung, Sang-Eun; Shin, Kyoung-Jin; Lee, Hwan Young

2017-01-01

Aging is a natural and gradual process in human life. It is influenced by heredity, environment, lifestyle, and disease. DNA methylation varies with age, and the ability to predict the age of donor using DNA from evidence materials at a crime scene is of considerable value in forensic investigations. Recently, many studies have reported age prediction models based on DNA methylation from various tissues and body fluids. Those models seem to be very promising because of their high prediction accuracies. In this review, the changes of age-associated DNA methylation and the age prediction models for various tissues and body fluids were examined, and then the applicability of the DNA methylation-based age prediction method to the forensic investigations was discussed. This will improve the understandings about DNA methylation markers and their potential to be used as biomarkers in the forensic field, as well as the clinical field. PMID:28946940

Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

PubMed

Crossa, José; Campos, Gustavo de Los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

2010-10-01

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

Screening for type 2 diabetes and prediabetes in obese youth: evaluating alternate markers of glycemia - 1,5-anhydroglucitol, fructosamine, and glycated albumin.

PubMed

Chan, Christine L; Pyle, Laura; Kelsey, Megan; Newnes, Lindsey; Zeitler, Philip S; Nadeau, Kristen J

2016-05-01

Hemoglobin A1c (HbA1c) is increasingly performed over the oral glucose tolerance test (OGTT) as the initial screening test for type 2 diabetes in youth. However, the optimal strategy for identifying type 2 diabetes in youth remains controversial. Alternate glycemic markers have been proposed as potentially useful tools for diabetes screening. We examined the relationships among fructosamine (FA), glycated albumin (GA), and 1,5-anhydroglucitol (1,5-AG) with traditional screening tests, HbA1c and OGTT. Youth 10-18 yrs, BMI ≥85th‰, and HbA1c <7.5% had a single visit with measurement of HbA1c, 1,5-AG, FA, GA, and a standard OGTT. Distributions of FA, GA, and 1,5-AG by HbA1c and 2-hour glucose (2hG) categories were compared. Receiver operating characteristic (ROC)-curves were generated to determine the cut points at which alternate markers maximized sensitivity and specificity for predicting prediabetes and diabetes. One hundred and seventeen, 62% female, 59% Hispanic, 22% White, 17% black, median 14.1 yr, and body mass index (BMI) z-score 2.3 participated. Median values of each alternate marker differed significantly between prediabetes and diabetes HbA1c and 2hG categories (p < 0.017). Only GA medians differed (p = 0.006) between normal and prediabetes HbA1c. Area under the receiver operating characteristic curves (ROC-AUCs) for alternate markers as predictors of prediabetes (0.5-0.66) were low; however, alternate marker ROC-AUCs for identifying diabetes (0.82-0.98) were excellent. Although the alternate markers were poor predictors of prediabetes, they all performed well predicting diabetes by 2hG and HbA1c. Whereas the usefulness of these markers for identifying prediabetes is limited, they may be useful in certain scenarios as second line screening tools for diabetes in overweight/obese youth. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multi-Parametric Spinal Cord MRI as Potential Progression Marker in Amyotrophic Lateral Sclerosis

PubMed Central

El Mendili, Mohamed-Mounir; Cohen-Adad, Julien; Pelegrini-Issac, Mélanie; Rossignol, Serge; Morizot-Koutlidis, Régine; Marchand-Pauvert, Véronique; Iglesias, Caroline; Sangari, Sina; Katz, Rose; Lehericy, Stéphane; Benali, Habib; Pradat, Pierre-François

2014-01-01

Objective To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. Materials and Methods After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. Results At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. Conclusion Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs. PMID:24755826

Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection.

PubMed

Kuroda, Daisuke; Sawayama, Hiroshi; Kurashige, Junji; Iwatsuki, Masaaki; Eto, Tsugio; Tokunaga, Ryuma; Kitano, Yuki; Yamamura, Kensuke; Ouchi, Mayuko; Nakamura, Kenichi; Baba, Yoshifumi; Sakamoto, Yasuo; Yamashita, Yoichi; Yoshida, Naoya; Chikamoto, Akira; Baba, Hideo

2018-03-01

Controlling Nutritional Status (CONUT), as calculated from serum albumin, total cholesterol concentration, and total lymphocyte count, was previously shown to be useful for nutritional assessment. The current study investigated the potential use of CONUT as a prognostic marker in gastric cancer patients after curative resection. Preoperative CONUT was retrospectively calculated in 416 gastric cancer patients who underwent curative resection at Kumamoto University Hospital from 2005 to 2014. The patients were divided into two groups: CONUT-high (≥4) and CONUT-low (≤3), according to time-dependent receiver operating characteristic (ROC) analysis. The associations of CONUT with clinicopathological factors and survival were evaluated. CONUT-high patients were significantly older (p < 0.001) and had a lower body mass index (p = 0.019), deeper invasion (p < 0.001), higher serum carcinoembryonic antigen (p = 0.037), and higher serum carbohydrate antigen 19-9 (p = 0.007) compared with CONUT-low patients. CONUT-high patients had significantly poorer overall survival (OS) compared with CONUT-low patients according to univariate and multivariate analyses (hazard ratio: 5.09, 95% confidence interval 3.12-8.30, p < 0.001). In time-dependent ROC analysis, CONUT had a higher area under the ROC curve (AUC) for the prediction of 5-year OS than the neutrophil lymphocyte ratio, the Modified Glasgow Prognostic Score, or pStage. When the time-dependent AUC curve was used to predict OS, CONUT tended to maintain its predictive accuracy for long-term survival at a significantly higher level for an extended period after surgery when compared with the other markers tested. CONUT is useful for not only estimating nutritional status but also for predicting long-term OS in gastric cancer patients after curative resection.

Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification.

PubMed

Schmedes, Sarah E; Woerner, August E; Novroski, Nicole M M; Wendt, Frank R; King, Jonathan L; Stephens, Kathryn M; Budowle, Bruce

2018-01-01

The human skin microbiome is comprised of diverse communities of bacterial, eukaryotic, and viral taxa and contributes millions of additional genes to the repertoire of human genes, affecting human metabolism and immune response. Numerous genetic and environmental factors influence the microbiome composition and as such contribute to individual-specific microbial signatures which may be exploited for forensic applications. Previous studies have demonstrated the potential to associate skin microbial profiles collected from touched items to their individual owner, mainly using unsupervised methods from samples collected over short time intervals. Those studies utilize either targeted 16S rRNA or shotgun metagenomic sequencing to characterize skin microbiomes; however, these approaches have limited species and strain resolution and susceptibility to stochastic effects, respectively. Clade-specific markers from the skin microbiome, using supervised learning, can predict individual identity using skin microbiomes from their respective donors with high accuracy. In this study the hidSkinPlex is presented, a novel targeted sequencing method using skin microbiome markers developed for human identification. The hidSkinPlex (comprised of 286 bacterial (and phage) family-, genus-, species-, and subspecies-level markers), initially was evaluated on three bacterial control samples represented in the panel (i.e., Propionibacterium acnes, Propionibacterium granulosum, and Rothia dentocariosa) to assess the performance of the multiplex. The hidSkinPlex was further evaluated for prediction purposes. The hidSkinPlex markers were used to attribute skin microbiomes collected from eight individuals from three body sites (i.e., foot (Fb), hand (Hp) and manubrium (Mb)) to their host donor. Supervised learning, specifically regularized multinomial logistic regression and 1-nearest-neighbor classification were used to classify skin microbiomes to their hosts with up to 92% (Fb), 96% (Mb), and 100% (Hp) accuracy. All samples (n=72) regardless of body site origin were correctly classified with up to 94% accuracy, and body site origin could be predicted with up to 86% accuracy. Finally, human short tandem repeat and single-nucleotide polymorphism profiles were generated from skin swab extracts from a single subject to highlight the potential to use microbiome profiling in conjunction with low-biomass samples. The hidSkinPlex is a novel targeted enrichment approach to profile skin microbiomes for human forensic identification purposes and provides a method to further characterize the utility of skin microflora for human identification in future studies, such as the stability and diversity of the personal skin microbiome. Copyright © 2017 Elsevier B.V. All rights reserved.

Contemporary biological markers of exposure to fluoride.

PubMed

Rugg-Gunn, Andrew John; Villa, Alberto Enrique; Buzalaf, Marília Rabelo Afonso

2011-01-01

Contemporary biological markers assess present, or very recent, exposure to fluoride: fluoride concentrations in blood, bone surface, saliva, milk, sweat and urine have been considered. A number of studies relating fluoride concentration in plasma to fluoride dose have been published, but at present there are insufficient data on plasma fluoride concentrations across various age groups to determine the 'usual' concentrations. Although bone contains 99% of the body burden of fluoride, attention has focused on the bone surface as a potential marker of contemporary fluoride exposure. From rather limited data, the ratio surface-to-interior concentration of fluoride may be preferred to whole bone fluoride concentration. Fluoride concentrations in the parotid and submandibular/sublingual ductal saliva follow the plasma fluoride concentration, although at a lower concentration. At present, there are insufficient data to establish a normal range of fluoride concentrations in ductal saliva as a basis for recommending saliva as a marker of fluoride exposure. Sweat and human milk are unsuitable as markers of fluoride exposure. A proportion of ingested fluoride is excreted in urine. Plots of daily urinary fluoride excretion against total daily fluoride intake suggest that daily urinary fluoride excretion is suitable for predicting fluoride intake for groups of people, but not for individuals. While fluoride concentrations in plasma, saliva and urine have some ability to predict fluoride exposure, present data are insufficient to recommend utilizing fluoride concentrations in these body fluids as biomarkers of contemporary fluoride exposure for individuals. Daily fluoride excretion in urine can be considered a useful biomarker of contemporary fluoride exposure for groups of people, and normal values have been published. Copyright © 2011 S. Karger AG, Basel.

A Novel Predictive Equation for Potential Diagnosis of Cholangiocarcinoma

PubMed Central

Kraiklang, Ratthaphol; Pairojkul, Chawalit; Khuntikeo, Narong; Imtawil, Kanokwan; Wongkham, Sopit; Wongkham, Chaisiri

2014-01-01

Cholangiocarcinoma (CCA) is the second most common-primary liver cancer. The difficulties in diagnosis limit successful treatment of CCA. At present, histological investigation is the standard diagnosis for CCA. However, there are some poor-defined tumor tissues which cannot be definitively diagnosed by general histopathology. As molecular signatures can define molecular phenotypes related to diagnosis, prognosis, or treatment outcome, and CCA is the second most common cancer found after hepatocellularcarcinoma (HCC), the aim of this study was to develop a predictive model which differentiates CCA from HCC and normal liver tissues. An in-house PCR array containing 176 putative CCA marker genes was tested with the training set tissues of 20 CCA and 10 HCC cases. The molecular signature of CCA revealed the prominent expression of genes involved in cell adhesion and cell movement, whereas HCC showed elevated expression of genes related to cell proliferation/differentiation and metabolisms. A total of 69 genes differentially expressed in CCA and HCC were optimized statistically to formulate a diagnostic equation which distinguished CCA cases from HCC cases. Finally, a four-gene diagnostic equation (CLDN4, HOXB7, TMSB4 and TTR) was formulated and then successfully validated using real-time PCR in an independent testing set of 68 CCA samples and 77 non-CCA controls. Discrimination analysis showed that a combination of these genes could be used as a diagnostic marker for CCA with better diagnostic parameters with high sensitivity and specificity than using a single gene marker or the usual serum markers (CA19-9 and CEA). This new combination marker may help physicians to identify CCA in liver tissues when the histopathology is uncertain. PMID:24586698

Atypical preference for infant-directed speech as an early marker of autism spectrum disorders? A literature review and directions for further research.

PubMed

Filipe, Marisa G; Watson, Linda; Vicente, Selene G; Frota, Sónia

2018-01-01

Autism spectrum disorders (ASD) refer to a complex group of neurodevelopmental disorders causing difficulties with communication and interpersonal relationships, as well as restricted and repetitive behaviours and interests. As early identification, diagnosis, and intervention provide better long-term outcomes, early markers of ASD have gained increased research attention. This review examines evidence that auditory processing enhanced by social interest, in particular auditory preference of speech directed towards infants and young children (i.e. infant-directed speech - IDS), may be an early marker of risk for ASD. Although this review provides evidence for IDS preference as, indeed, a potential early marker of ASD, the explanation for differences in IDS processing among children with ASD versus other children remains unclear, as are the implications of these impairments for later social-communicative development. Therefore, it is crucial to explore atypicalities in IDS processing early on development and to understand whether preferential listening to specific types of speech sounds in the first years of life may help to predict the impairments in social and language development.

Skin autofluorescence as a measure of advanced glycation endproduct deposition: a novel risk marker in chronic kidney disease.

PubMed

Smit, Andries J; Gerrits, Esther G

2010-11-01

Skin autofluorescence (SAF) is a new method to noninvasively assess accumulation of advanced glycation endproducts (AGEs) in a tissue with low turnover. Recent progress in the clinical application of SAF as a risk marker for diabetic nephropathy as well as cardiovascular disease in nondiabetic end-stage kidney disease, less advanced chronic kidney disease, and renal transplant recipients is reviewed. Experimental studies highlight the fundamental role of the interaction of AGEs with the receptor for AGEs (RAGEs), also called the AGE-RAGE axis, in the pathogenesis of vascular and chronic kidney disease. SAF predicts (cardiovascular) mortality in renal failure and also chronic renal transplant dysfunction. Long-term follow-up results from the Diabetes Control and Complications Trial and UK Prospective Diabetes Study suggest that AGE accumulation is a key carrier of metabolic memory and oxidative stress. Short-term intervention studies in diabetic nephropathy with thiamine, benfotiamine and angiotensin-receptor blockers aimed at reducing AGE formation have reported mixed results. SAF is a noninvasive marker of AGE accumulation in a tissue with low turnover, and thereby of metabolic memory and oxidative stress. SAF independently predicts cardiovascular and renal risk in diabetes, as well as in chronic kidney disease. Further long-term studies are required to assess the potential benefits of interventions to reduce AGE accumulation.

Linking empathy to visuospatial perspective-taking in gambling addiction.

PubMed

Tomei, Alexander; Besson, Jacques; Grivel, Jeremy

2017-04-01

It has been demonstrated that people suffering from substance-related addictions are less empathic than their non-addicted counterparts. Our first aim was to verify if this is also true for behavioral addictions. We hypothesized that problem gamblers are less empathic than healthy controls. Our second aim was to identify a cognitive marker of empathy that could be targeted in cognitive rehabilitation strategies. We propose that a potential cognitive marker of empathy could be visuospatial perspective-taking. Specifically, we hypothesized that visuospatial perspective-taking performances are lower in problem gamblers compared to healthy controls and that these visuospatial performances predict empathy. Thirty-one non-gamblers, 24 healthy gamblers, and 21 problem gamblers performed a visuospatial perspective-taking task before completing the Interpersonal Reactivity Index (IRI; Davis, 1980; Davis, 1983). Problem gamblers had decreased empathy and lower performance at the visuospatial perspective-taking task than non-gamblers and healthy gamblers. Furthermore, we confirmed that visuospatial perspective-taking abilities predict empathy on the IRI dimensions of interpersonal perspective-taking and personal distress. The present study provides new evidence that reduced empathy is not limited to subjects with substance-related addictions; rather, it extends to behavioral addictions. Visuospatial perspective-taking may be a viable cognitive marker for use as a rehabilitation target of empathy. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

High-throughput chinmedomics-based prediction of effective components and targets from herbal medicine AS1350

PubMed Central

Liu, Qi; Zhang, Aihua; Wang, Liang; Yan, Guangli; Zhao, Hongwei; Sun, Hui; Zou, Shiyu; Han, Jinwei; Ma, Chung Wah; Kong, Ling; Zhou, Xiaohang; Nan, Yang; Wang, Xijun

2016-01-01

This work was designed to explore the effective components and targets of herbal medicine AS1350 and its effect on “Kidney-Yang Deficiency Syndrome” (KYDS) based on a chinmedomics strategy which is capable of directly discovering and predicting the effective components, and potential targets, of herbal medicine. Serum samples were analysed by UPLC-MS combined with pattern recognition analysis to identify the biomarkers related to the therapeutic effects. Interestingly, the effectiveness of AS1350 against KYDS was proved by the chinmedomics method and regulated the biomarkers and targeting of metabolic disorders. Some 48 marker metabolites associated with alpha-linolenic acid metabolism, fatty acid metabolism, sphingolipids metabolism, phospholipid metabolism, steroid hormone biosynthesis, and amino acid metabolism were identified. The correlation coefficient between the constituents in vivo and the changes of marker metabolites were calculated by PCMS software and the potential effective constituents of AS1350 were also confirmed. By using chinmedomics technology, the components in AS1350 protecting against KYDS by re-balancing metabolic disorders of fatty acid metabolism, lipid metabolism, steroid hormone biosynthesis, etc. were deduced. These data indicated that the phenotypic characterisations of AS1350 altering the metabolic signatures of KYDS were multi-component, multi-pathway, multi-target, and overall regulation in nature. PMID:27910928

Privacy-preserving genomic testing in the clinic: a model using HIV treatment.

PubMed

McLaren, Paul J; Raisaro, Jean Louis; Aouri, Manel; Rotger, Margalida; Ayday, Erman; Bartha, István; Delgado, Maria B; Vallet, Yannick; Günthard, Huldrych F; Cavassini, Matthias; Furrer, Hansjakob; Doco-Lecompte, Thanh; Marzolini, Catia; Schmid, Patrick; Di Benedetto, Caroline; Decosterd, Laurent A; Fellay, Jacques; Hubaux, Jean-Pierre; Telenti, Amalio

2016-08-01

The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.Genet Med 18 8, 814-822.

Isolation and characterization of new highly polymorphic DNA markers from the Huntington disease region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weber, B.; Hedrick, A.; Andrew, S.

1992-02-01

The defect causing Huntington disease (HD) has been mapped to 4p16.3, distal to the DNA marker D4S10. Subsequently, additional polymorphic markers closer to the HD gene have been isolated, which has led to the establishment of predictive testing programs for individuals at risk for HD. Approximately 17% of persons presenting to the Canadian collaborative study for predictive testing for HD have not received any modification of risk, in part because of limited informativeness of currently available DNA markers. Therefore, more highly polymorphic DNA markers are needed, which well further increase the accuracy and availability of predictive testing, specifically for familiesmore » with complex or incomplete pedigree structures. In addition, new markers are urgently needed in order to refine the breakpoints in the few known recombinant HD chromosomes, which could allow a more accurate localization of the HD gene within 4p16.3 and, therefore, accelerate the cloning of the disease gene. In this study, the authors present the identification and characterization of nine new polymorphic DNA markers, including three markers which detect highly informative multiallelic VNTR-like polymorphisms with PIC values of up to .84. These markers have been isolated from a cloned region of DNA which has been previously mapped approximately 1,000 kb from the 4p telomere.« less

A comparative analysis of gene-expression data of multiple cancer types.

PubMed

Xu, Kun; Cui, Juan; Olman, Victor; Yang, Qing; Puett, David; Xu, Ying

2010-10-27

A comparative study of public gene-expression data of seven types of cancers (breast, colon, kidney, lung, pancreatic, prostate and stomach cancers) was conducted with the aim of deriving marker genes, along with associated pathways, that are either common to multiple types of cancers or specific to individual cancers. The analysis results indicate that (a) each of the seven cancer types can be distinguished from its corresponding control tissue based on the expression patterns of a small number of genes, e.g., 2, 3 or 4; (b) the expression patterns of some genes can distinguish multiple cancer types from their corresponding control tissues, potentially serving as general markers for all or some groups of cancers; (c) the proteins encoded by some of these genes are predicted to be blood secretory, thus providing potential cancer markers in blood; (d) the numbers of differentially expressed genes across different cancer types in comparison with their control tissues correlate well with the five-year survival rates associated with the individual cancers; and (e) some metabolic and signaling pathways are abnormally activated or deactivated across all cancer types, while other pathways are more specific to certain cancers or groups of cancers. The novel findings of this study offer considerable insight into these seven cancer types and have the potential to provide exciting new directions for diagnostic and therapeutic development.

Progastrin: a potential predictive marker of liver metastasis in colorectal cancer.

PubMed

Westwood, David A; Patel, Oneel; Christophi, Christopher; Shulkes, Arthur; Baldwin, Graham S

2017-07-01

Staging of colorectal cancer often fails to discriminate outcomes of patients with morphologically similar tumours that exhibit different clinical behaviours. Data from several studies suggest that the gastrin family of growth factors potentiates colorectal cancer tumourigenesis. The aim of this study was to investigate whether progastrin expression may predict clinical outcome in colorectal cancer. Patients with colorectal adenocarcinoma of identical depth of invasion who had not received neoadjuvant therapy were included. The patients either had stage IIa disease with greater than 3-year disease-free survival without adjuvant therapy or stage IV disease with liver metastases on staging CT. Progastrin expression in tumour sections was scored with reference to the intensity and area of immunohistochemical staining. Progastrin expression by stage IV tumours was significantly greater than stage IIa tumours with mean progastrin immunopositivity scores of 2.1 ± 0.2 versus 0.5 ± 0.2, respectively (P < 0.001). This is the first study to show that progastrin expression may be predictive of aggressive tumour behaviour in patients with colorectal cancer and supports its clinical relevance and potential use as a biomarker.

A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

PubMed

Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

2017-07-01

Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

The effect of using genealogy-based haplotypes for genomic prediction

PubMed Central

2013-01-01

Background Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Conclusions Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy. PMID:23496971

The effect of using genealogy-based haplotypes for genomic prediction.

PubMed

Edriss, Vahid; Fernando, Rohan L; Su, Guosheng; Lund, Mogens S; Guldbrandtsen, Bernt

2013-03-06

Genomic prediction uses two sources of information: linkage disequilibrium between markers and quantitative trait loci, and additive genetic relationships between individuals. One way to increase the accuracy of genomic prediction is to capture more linkage disequilibrium by regression on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (π) of the haplotype covariates had zero effect, i.e. a Bayesian mixture method. About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some cases, decreased the bias of prediction. With the Bayesian method, accuracy of prediction was less sensitive to parameter π when fitting haplotypes compared to fitting markers. Use of haplotypes based on genealogy can slightly increase the accuracy of genomic prediction. Improved methods to cluster the haplotypes constructed from local genealogy could lead to additional gains in accuracy.

Genomic selection for slaughter age in pigs using the Cox frailty model.

PubMed

Santos, V S; Martins Filho, S; Resende, M D V; Azevedo, C F; Lopes, P S; Guimarães, S E F; Glória, L S; Silva, F F

2015-10-19

The aim of this study was to compare genomic selection methodologies using a linear mixed model and the Cox survival model. We used data from an F2 population of pigs, in which the response variable was the time in days from birth to the culling of the animal and the covariates were 238 markers [237 single nucleotide polymorphism (SNP) plus the halothane gene]. The data were corrected for fixed effects, and the accuracy of the method was determined based on the correlation of the ranks of predicted genomic breeding values (GBVs) in both models with the corrected phenotypic values. The analysis was repeated with a subset of SNP markers with largest absolute effects. The results were in agreement with the GBV prediction and the estimation of marker effects for both models for uncensored data and for normality. However, when considering censored data, the Cox model with a normal random effect (S1) was more appropriate. Since there was no agreement between the linear mixed model and the imputed data (L2) for the prediction of genomic values and the estimation of marker effects, the model S1 was considered superior as it took into account the latent variable and the censored data. Marker selection increased correlations between the ranks of predicted GBVs by the linear and Cox frailty models and the corrected phenotypic values, and 120 markers were required to increase the predictive ability for the characteristic analyzed.

OS090. Performance of candidate clinical and biochemical markers in screening early in pregnancy to detect women at high risk to develop preeclampsia.

PubMed

Forest, J-C; Massé, J; Bujold, E; Rousseau, F; Charland, M; Thériault, S; Lafond, J; Giguère, Y

2012-07-01

The advent of early preventive measures, such as low-dose aspirin targeting women at high risk of preeclampsia (PE), emphasizes the need for better detection. Despite the emergence of promising biochemical markers linked to the pathophysiological processes, systematic reviews have shown that, until now, no single tests fulfill the criteria set by WHO for biomarkers to screen for a disease. However, recent literature reveals that by combining various clinical, biophysical and biochemical markers into multivariate algorithms, one can envisage to estimate the risk of PE with a performance that would reach clinical utility and cost-effectiveness, but this remains to be demonstrated in various environments and health care settings. To investigate, in a prospective study, the clinical utility of candidate biomarkers and clinical data to detect, early in pregnancy, women at risk to develop PE and to propose a multivariate prediction algorithm combining clinical parameters to biochemical markers. 7929 pregnant women prospectively recruited at the first prenatal visit, provided blood samples, clinical and sociodemographic information. 214 pregnant women developed hypertensive disorders of pregnancy (HDP) of which 88 had PE (1.2%), including 44 with severe PE (0.6%). A nested case-control study was performed including for each case of HDP two normal pregnancies matched for maternal age, gestational age at recruitment, ethnicity, parity, and smoking status. Based on the literature we selected the most promising markers in a multivariate logistic regression model: mean arterial pressure (MAP), BMI, placental growth factor (PlGF), soluble Flt-1, inhibin A and PAPP-A. Biomarker results measured between 10-18 weeks gestation were expressed as multiples of the median. Medians were determined for each gestational week. When combined with MAP at the time of blood sampling and BMI at the beginning of pregnancy, the four biochemical markers discriminate normal pregnancies from those with HDP. At a 5% false positive rate, 37% of the affected pregnancies would have been detected. However, considering the prevalence of HDP in our population, the positive predictive value would have been only 15%. If all the predicted positive women would have been proposed a preventive intervention, only one out 6.7 women could have potentially benefited. In the case of severe PE, performance was not improved, sensitivity was the same, but the positive predictive value decreased to 3% (lower prevalence of severe PE). In our low-risk Caucasian population, neither individual candidate markers nor multivariate risk algorithm using an a priori combination of selected markers reached a performance justifying implementation. This also emphasizes the necessity to take into consideration characteristics of the population and environment influencing prevalence before promoting wide implementation of such screening strategies. In a perspective of personalized medicine, it appears more than ever mandatory to tailor recommendations for HDP screening according not only to individual but also to population characteristics. Copyright © 2012. Published by Elsevier B.V.

Promoter Hypermethylation of Tumour Suppressor Genes as Potential Biomarkers in Colorectal Cancer

PubMed Central

Ng, Jennifer Mun-Kar; Yu, Jun

2015-01-01

Colorectal cancer (CRC) is a common malignancy and the fourth leading cause of cancer deaths worldwide. It results from the accumulation of multiple genetic and epigenetic changes leading to the transformation of colon epithelial cells into invasive adenocarcinomas. In CRC, epigenetic changes, in particular promoter CpG island methylation, occur more frequently than genetic mutations. Hypermethylation contributes to carcinogenesis by inducing transcriptional silencing or downregulation of tumour suppressor genes and currently, over 600 candidate hypermethylated genes have been identified. Over the past decade, a deeper understanding of epigenetics coupled with technological advances have hinted at the potential of translating benchtop research into biomarkers for clinical use. DNA methylation represents one of the largest bodies of literature in epigenetics, and hence has the highest potential for minimally invasive biomarker development. Most progress has been made in the development of diagnostic markers and there are currently two, one stool-based and one blood-based, biomarkers that are commercially available for diagnostics. Prognostic and predictive methylation markers are still at their infantile stages. PMID:25622259

Protein markers of malignant potential in penile and vulvar lichen sclerosus.

PubMed

Carlson, Bayard C; Hofer, Matthias D; Ballek, Nathaniel; Yang, Ximing J; Meeks, Joshua J; Gonzalez, Chris M

2013-08-01

Lichen sclerosus is an inflammatory skin disorder affecting anogenital areas in males and females that is associated with squamous cell carcinoma. However, there is a lack of data on the role of biomarkers for predicting lichen sclerosus progression to squamous cell carcinoma. We focused on early protein markers of squamous cell carcinoma and their expression in lichen sclerosus to improve the mechanistic and diagnostic understanding of lichen sclerosus. We performed an extensive PubMed® and MEDLINE® search for protein markers found in early stages of vulvar and penile squamous cell carcinoma, and their prevalence in associated lichen sclerosus lesions. In recent years several markers have been implicated as precursor markers for malignant transformation of lichen sclerosus into squamous cell carcinoma, including p53, Ki-67, γ-H2AX, MCM3 and cyclin D1. These proteins are up-regulated in lichen sclerosus of the vulva/penis and squamous cell carcinoma. Various levels of evidence show an association between lichen sclerosus and squamous cell carcinoma. p16 is over expressed in penile and vulvar squamous cell carcinoma associated with human papillomavirus infection but conflicting reports exist about its expression in lichen sclerosus. The angiogenesis markers vascular endothelial growth factor and cyclooxygenase-2 are expressed at higher levels, and microvessel density is increased in vulvar lichen sclerosus and squamous cell carcinoma, indicating a possible similar association in penile lichen sclerosus. Only a minority of lichen sclerosus cases are associated with squamous cell carcinoma. However, the therapeutic implications of a squamous cell carcinoma diagnosis are severe. Clinically, we lack an understanding of how to separate indolent lichen sclerosus cases from those in danger of progression to squamous cell carcinoma. Several protein markers show promise for further delineating the pathobiology of lichen sclerosus and the potential malignant transformation into squamous cell carcinoma. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Spiked GBS: A unified, open platform for single marker genotyping and whole-genome profiling

USDA-ARS?s Scientific Manuscript database

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of t...

Identify super quality markers from prototype-based pharmacokinetic markers of Tangzhiqing tablet (TZQ) based on in vitro dissolution/ permeation and in vivo absorption correlations.

PubMed

Li, Ziqiang; Liu, Jia; Li, Yazhuo; Du, Xi; Li, Yanfen; Wang, Ruihua; Lv, Chunxiao; He, Xin; Wang, Baohe; Huang, Yuhong; Zhang, Deqin

2018-06-01

A quality marker (Q-marker) is defined as an inherent chemical compound that is used for the quality control of a drug. Its biological activities are closely related to safety and therapeutic effects. Generally, a multiple-component herbal medicine may have many Q-markers. We therefore proposed a concept of "super Q-marker" satisfying both the criterion of Q-markers and PK-markers to be used in more effective quality control of herbal medicine. The first aim was to find suitable prototype-based PK-markers from Tangzhiqing tablets (TZQ), a Chinese patent medicine. Then super Q-markers were expected to be identified from the prototype-based PK-markers based on an in vitro-in vivo correlation study. Potentially eligible prototype-based PK-markers were identified in a single- and multiple-dose pharmacokinetic study on TZQ in 30 healthy volunteers. The in vitro dissolution and permeation profiles of the prototype-based PK-markers of TZQ were evaluated by the physiologically-based drug dissolution/absorption simulating system (DDASS). An in vitro-in vivo correlation analysis was conducted between the dissolution/permeation behaviors in DDASS and the actual absorption profiles in human to test the transferability and traceability of the promising super Q-markers for TZQ. In human, plasma paeoniflorin and nuciferine as prototype-based PK-markers exhibited the appropriate pharmacokinetic properties, including dose-dependent systemic exposure (AUC, C max ) and a proper elimination half-life (1∼3h). In DDASS, it was predicted that paeoniflorin and nuciferine are highly permeable but the absorption rates are primarily limited by the dissolution rates. Moreover, the established in vitro-in vivo correlations of paeoniflorin and nuciferine were in support of the super Q-markers features. Paeoniflorin and nuciferine are identified as the super Q-markers from the prototype-based PK-markers of TZQ based on findings from a combination of in vitro, in vivo, and in vitro-in vivo correlation studies. This method is practical for optimal identification of qualified Q-markers, thus helping improve the quality control of herbal medicines. Copyright © 2018 Elsevier GmbH. All rights reserved.

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results. PMID:27499890

Prediction of preservative sensitization potential using surface marker CD86 and/or CD54 expression on human cell line, THP-1.

PubMed

Sakaguchi, Hitoshi; Miyazawa, Masaaki; Yoshida, Yukiko; Ito, Yuichi; Suzuki, Hiroyuki

2007-02-01

Preservatives are important components in many products, but have a history of purported allergy. Several assays [e.g., guinea pig maximization test (GPMT), local lymph node assay (LLNA)] are used to evaluate allergy potential of preservatives. We recently developed the human Cell Line Activation Test (h-CLAT), an in vitro skin sensitization test using human THP-1 cells. This test evaluates the augmentation of CD86 and CD54 expression, which are key events in the sensitization process, as an indicator of allergy following treatment with test chemical. Earlier, we found that a sub-toxic concentration was needed for the up-regulation of surface marker expression. In this study, we further evaluate the capability of h-CLAT to predict allergy potential using eight preservatives. Cytotoxicity was determined using propidium iodide with flow cytometry analysis and five doses that produce a 95, 85, 75, 65, and 50% cell viability were selected. If a material did not have any cytotoxicity at the highest technical dose (HTD), five doses are set using serial 1.3 dilutions of the HTD. The test materials used were six known allergic preservatives (e.g., methylchloroisothiazolinone/methylisothiazolinone, formaldehyde), and two non-allergic preservatives (methylparaben and 4-hydroxybenzoic acid). All allergic preservatives augmented CD86 and/or CD54 expression, indicating h-CLAT correctly identified the allergens. No augmentation was observed with the non-allergic preservatives; also correctly identified by h-CLAT. In addition, we report two threshold concentrations that may be used to categorize skin sensitization potency like the LLNA estimated concentration that yield a three-fold stimulation (EC3) value. These corresponding values are the estimated concentration which gives a relative fluorescence intensity (RFI) = 150 for CD86 and an RFI = 200 for CD54. These data suggest that h-CLAT, using THP-1 cells, may be able to predict the allergy potential of preservatives and possibility classify the potency of an allergen.

Concise Review: Multifaceted Characterization of Human Mesenchymal Stem Cells for Use in Regenerative Medicine.

PubMed

Samsonraj, Rebekah M; Raghunath, Michael; Nurcombe, Victor; Hui, James H; van Wijnen, Andre J; Cool, Simon M

2017-12-01

Mesenchymal stem cells (MSC) hold great potential for regenerative medicine because of their ability for self-renewal and differentiation into tissue-specific cells such as osteoblasts, chondrocytes, and adipocytes. MSCs orchestrate tissue development, maintenance and repair, and are useful for musculoskeletal regenerative therapies to treat age-related orthopedic degenerative diseases and other clinical conditions. Importantly, MSCs produce secretory factors that play critical roles in tissue repair that support both engraftment and trophic functions (autocrine and paracrine). The development of uniform protocols for both preparation and characterization of MSCs, including standardized functional assays for evaluation of their biological potential, are critical factors contributing to their clinical utility. Quality control and release criteria for MSCs should include cell surface markers, differentiation potential, and other essential cell parameters. For example, cell surface marker profiles (surfactome), bone-forming capacities in ectopic and orthotopic models, as well as cell size and granularity, telomere length, senescence status, trophic factor secretion (secretome), and immunomodulation, should be thoroughly assessed to predict MSC utility for regenerative medicine. We propose that these and other functionalities of MSCs should be characterized prior to use in clinical applications as part of comprehensive and uniform guidelines and release criteria for their clinical-grade production to achieve predictably favorable treatment outcomes for stem cell therapy. Stem Cells Translational Medicine 2017;6:2173-2185. © 2017 The Authors Stem Cells Translational Medicine published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

Prediction of miscarriage in women with viable intrauterine pregnancy-A systematic review and diagnostic accuracy meta-analysis.

PubMed

Pillai, Rekha N; Konje, Justin C; Richardson, Matthew; Tincello, Douglas G; Potdar, Neelam

2018-01-01

Both ultrasound and biochemical markers either alone or in combination have been described in the literature for the prediction of miscarriage. We performed this systematic review and meta-analysis to determine the best combination of biochemical, ultrasound and demographic markers to predict miscarriage in women with viable intrauterine pregnancy. The electronic database search included Medline (1946-June 2017), Embase (1980-June 2017), CINAHL (1981-June 2017) and Cochrane library. Key MESH and Boolean terms were used for the search. Data extraction and collection was performed based on the eligibility criteria by two authors independently. Quality assessment of the individual studies was done using QUADAS 2 (Quality Assessment for Diagnostic Accuracy Studies-2: A Revised Tool) and statistical analysis performed using the Cochrane systematic review manager 5.3 and STATA vs.13.0. Due to the diversity of the combinations used for prediction in the included papers it was not possible to perform a meta-analysis on combination markers. Therefore, we proceeded to perform a meta-analysis on ultrasound markers alone to determine the best marker that can help to improve the diagnostic accuracy of predicting miscarriage in women with viable intrauterine pregnancy. The systematic review identified 18 eligible studies for the quantitative meta-analysis with a total of 5584 women. Among the ultrasound scan markers, fetal bradycardia (n=10 studies, n=1762 women) on hierarchical summary receiver operating characteristic showed sensitivity of 68.41%, specificity of 97.84%, positive likelihood ratio of 31.73 (indicating a large effect on increasing the probability of predicting miscarriage) and negative likelihood ratio of 0.32. In studies for women with threatened miscarriage (n=5 studies, n=771 women) fetal bradycardia showed further increase in sensitivity (84.18%) for miscarriage prediction. Although there is gestational age dependent variation in the fetal heart rate, a plot of fetal heart rate cut off level versus log diagnostic odds ratio showed that at ≤110 beat per minutes the diagnostic power to predict miscarriage is higher. Other markers of intra uterine hematoma, crown rump length and yolk sac had significantly decreased predictive value. Therefore in women with threatened miscarriage and presence of fetal bradycardia on ultrasound scan, there is a role for offering repeat ultrasound scan in a week to ten days interval. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lan, Yemin; Rosen, Gail; Hershberg, Ruth

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that themore » percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. In conclusion, our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.« less

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

DOE PAGES

Lan, Yemin; Rosen, Gail; Hershberg, Ruth

2016-05-03

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that themore » percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. In conclusion, our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.« less

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

The microRNAs as potential biomarkers for predicting the onset of aflatoxin exposure in human beings: a review.

PubMed

Valencia-Quintana, Rafael; Sánchez-Alarcón, Juana; Tenorio-Arvide, María G; Deng, Youjun; Montiel-González, José M R; Gómez-Arroyo, Sandra; Villalobos-Pietrini, Rafael; Cortés-Eslava, Josefina; Flores-Márquez, Ana R; Arenas-Huertero, Francisco

2014-01-01

The identification of aflatoxins as human carcinogens has stimulated extensive research efforts, which continue to the present, to assess potential health hazards resulting from contamination of the human food supply and to minimize exposure. The use of biomarkers that are mechanistically supported by toxicological studies will be important tools for identifying stages in the progression of development of the health effects of environmental agents. miRNAs are small non-coding mRNAs that regulate post-transcriptional gene expression. Also, they are molecular markers of cellular responses to various chemical agents. Growing evidence has demonstrated that environmental chemicals can induce changes in miRNA expression. miRNAs are good biomarkers because they are well defined, chemically uniform, restricted to a manageable number of species, and stable in cells and in the circulation. miRNAs have been used as serological markers of HCC and other tumors. The expression patterns of different miRNAs can distinguish among HCC-hepatitis viruses related, HCC cirrhosis-derivate, and HCC unrelated to either of them. The main objective of this review is to find unreported miRNAs in HCC related to other causes, so that they can be used as specific molecular biomarkers in populations exposed to aflatoxins and as early markers of exposure, damage/presence of HCC. Until today specific miRNAs as markers for aflatoxins-exposure and their reliability are currently lacking. Based on their elucidated mechanisms of action, potential miRNAs that could serve as possible markers of HCC by exposure to aflatoxins are miR-27a, miR-27b, miR-122, miR-148, miR-155, miR-192, miR-214, miR-221, miR-429, and miR-500. Future validation for all of these miRNAs will be needed to assess their prognostic significance and confirm their relationship with the induction of HCC due to aflatoxin exposure.

S100 B: A new concept in neurocritical care

PubMed Central

Rezaei, Omidvar; Pakdaman, Hossein; Gharehgozli, Kurosh; Simani, Leila; Vahedian-Azimi, Amir; Asaadi, Sina; Sahraei, Zahra; Hajiesmaeili, Mohammadreza

2017-01-01

After brain injuries, concentrations of some brain markers such as S100B protein in serum and cerebrospinal fluid (CSF) are correlated with the severity and outcome of brain damage. To perform an updated review of S100B roles in human neurocritical care domain, an electronic literature search was carried among articles published in English prior to March 2017. They were retrieved from PubMed, Scopus, EMBSCO, CINAHL, ISC and the Cochrane Library using keywords including “brain”, “neurobiochemical marker”, “neurocritical care”, and “S100B protein”. The integrative review included 48 studies until March 2017. S100B protein can be considered as a marker for blood brain barrier damage. The marker has an important role in the development and recovery of normal central nervous system (CNS) after injury. In addition to extra cerebral sources of S100B, the marker is principally built in the astroglial and Schwann cells. The neurobiochemical marker, S100B, has a pathognomonic role in the diagnosis of a broad spectrum of brain damage including traumatic brain injury (TBI), brain tumor, and stroke. Moreover, a potential predicting role for the neurobiochemical marker has been presumed in the efficiency of brain damage treatment and prognosis. However further animal and human studies are required before widespread routine clinical introduction of S100 protein. PMID:28761630

Development of a gene-centered ssr atlas as a resource for papaya (Carica papaya) marker-assisted selection and population genetic studies.

PubMed

Vidal, Newton Medeiros; Grazziotin, Ana Laura; Ramos, Helaine Christine Cancela; Pereira, Messias Gonzaga; Venancio, Thiago Motta

2014-01-01

Carica papaya (papaya) is an economically important tropical fruit. Molecular marker-assisted selection is an inexpensive and reliable tool that has been widely used to improve fruit quality traits and resistance against diseases. In the present study we report the development and validation of an atlas of papaya simple sequence repeat (SSR) markers. We integrated gene predictions and functional annotations to provide a gene-centered perspective for marker-assisted selection studies. Our atlas comprises 160,318 SSRs, from which 21,231 were located in genic regions (i.e. inside exons, exon-intron junctions or introns). A total of 116,453 (72.6%) of all identified repeats were successfully mapped to one of the nine papaya linkage groups. Primer pairs were designed for markers from 9,594 genes (34.5% of the papaya gene complement). Using papaya-tomato orthology assessments, we assembled a list of 300 genes (comprising 785 SSRs) potentially involved in fruit ripening. We validated our atlas by screening 73 SSR markers (including 25 fruit ripening genes), achieving 100% amplification rate and uncovering 26% polymorphism rate between the parental genotypes (Sekati and JS12). The SSR atlas presented here is the first comprehensive gene-centered collection of annotated and genome positioned papaya SSRs. These features combined with thousands of high-quality primer pairs make the atlas an important resource for the papaya research community.

Probability genotype imputation method and integrated weighted lasso for QTL identification.

PubMed

Demetrashvili, Nino; Van den Heuvel, Edwin R; Wit, Ernst C

2013-12-30

Many QTL studies have two common features: (1) often there is missing marker information, (2) among many markers involved in the biological process only a few are causal. In statistics, the second issue falls under the headings "sparsity" and "causal inference". The goal of this work is to develop a two-step statistical methodology for QTL mapping for markers with binary genotypes. The first step introduces a novel imputation method for missing genotypes. Outcomes of the proposed imputation method are probabilities which serve as weights to the second step, namely in weighted lasso. The sparse phenotype inference is employed to select a set of predictive markers for the trait of interest. Simulation studies validate the proposed methodology under a wide range of realistic settings. Furthermore, the methodology outperforms alternative imputation and variable selection methods in such studies. The methodology was applied to an Arabidopsis experiment, containing 69 markers for 165 recombinant inbred lines of a F8 generation. The results confirm previously identified regions, however several new markers are also found. On the basis of the inferred ROC behavior these markers show good potential for being real, especially for the germination trait Gmax. Our imputation method shows higher accuracy in terms of sensitivity and specificity compared to alternative imputation method. Also, the proposed weighted lasso outperforms commonly practiced multiple regression as well as the traditional lasso and adaptive lasso with three weighting schemes. This means that under realistic missing data settings this methodology can be used for QTL identification.

Psychosis prediction and clinical utility in familial high-risk studies: Selective review, synthesis, and implications for early detection and intervention

PubMed Central

Shah, Jai L.; Tandon, Neeraj; Keshavan, Matcheri S.

2016-01-01

Aim Accurate prediction of which individuals will go on to develop psychosis would assist early intervention and prevention paradigms. We sought to review investigations of prospective psychosis prediction based on markers and variables examined in longitudinal familial high-risk (FHR) studies. Methods We performed literature searches in MedLine, PubMed and PsycINFO for articles assessing performance characteristics of predictive clinical tests in FHR studies of psychosis. Studies were included if they reported one or more predictive variables in subjects at FHR for psychosis. We complemented this search strategy with references drawn from articles, reviews, book chapters and monographs. Results Across generations of familial high-risk projects, predictive studies have investigated behavioral, cognitive, psychometric, clinical, neuroimaging, and other markers. Recent analyses have incorporated multivariate and multi-domain approaches to risk ascertainment, although with still generally modest results. Conclusions While a broad range of risk factors has been identified, no individual marker or combination of markers can at this time enable accurate prospective prediction of emerging psychosis for individuals at FHR. We outline the complex and multi-level nature of psychotic illness, the myriad of factors influencing its development, and methodological hurdles to accurate and reliable prediction. Prospects and challenges for future generations of FHR studies are discussed in the context of early detection and intervention strategies. PMID:23693118

Genome-enabled prediction models for yield related traits in chickpea

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

A proof-of-principle simulation for closed-loop control based on preexisting experimental thalamic DBS-enhanced instrumental learning.

PubMed

Wang, Ching-Fu; Yang, Shih-Hung; Lin, Sheng-Huang; Chen, Po-Chuan; Lo, Yu-Chun; Pan, Han-Chi; Lai, Hsin-Yi; Liao, Lun-De; Lin, Hui-Ching; Chen, Hsu-Yan; Huang, Wei-Chen; Huang, Wun-Jhu; Chen, You-Yin

Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption. However, when the association between the biomarkers of the model and stimulation is unclear, it is difficult to develop an optimal control scheme for other DBS applications, i.e., DBS-enhanced instrumental learning. Furthermore, few studies have investigated the effect of closed-loop DBS control for cognition function, such as instrumental skill learning, and have been implemented in simulation environments. In this paper, we proposed a proof-of-principle design for a closed-loop DBS system, cognitive-enhancing DBS (ceDBS), which enhanced skill learning based on in vivo experimental data. The ceDBS acquired local field potential (LFP) signal from the thalamic central lateral (CL) nuclei of animals through a neural signal processing system. A strong coupling of the theta oscillation (4-7 Hz) and the learning period was found in the water reward-related lever-pressing learning task. Therefore, the theta-band power ratio, which was the averaged theta band to averaged total band (1-55 Hz) power ratio, could be used as a physiological marker for enhancement of instrumental skill learning. The on-line extraction of the theta-band power ratio was implemented on a field-programmable gate array (FPGA). An autoregressive with exogenous inputs (ARX)-based predictor was designed to construct a CL-thalamic DBS model and forecast the future physiological marker according to the past physiological marker and applied DBS. The prediction could further assist the design of a closed-loop DBS controller. A DBS controller based on a fuzzy expert system was devised to automatically control DBS according to the predicted physiological marker via a set of rules. The simulated experimental results demonstrate that the ceDBS based on the closed-loop control architecture not only reduced power consumption using the predictive physiological marker, but also achieved a desired level of physiological marker through the DBS controller. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat

PubMed Central

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-01-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

PubMed

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Malignant perivascular epithelioid cell tumor in children: description of a case and review of the literature.

PubMed

Alaggio, Rita; Cecchetto, Giovanni; Martignoni, Guido; Bisogno, Gianni; Cheng, Liang; Sperlì, Domenico; d'Amore, Emauele S G; Dall'Igna, Patrizia

2012-06-01

Perivascular epithelioid cell tumors (PEComas) include different morphological entities originating from perivascular epithelioid cells. Their clinical behavior is not predictable, and there are no strict histologic criteria for malignancy, although larger tumors with infiltrative growth, hypercellularity, cellular atypia, atypical mitoses, and necrosis generally have a malignant course. Pediatric PEComas are rare, with less than 40 cases reported, mostly in children older than 5 years. We describe a case of malignant PEComa of the ligamentum teres in a 2-year-old girl, characterized by the occurrence of local relapse after primary treatment with chemotherapy and surgery and poor response to imatinib mesilate and temsirolimus used after further analyses confirmed p70S6K expression involved in the mTOR pathway. The girl was eventually treated with a debulking surgical procedure and is now alive with disease 6 years after diagnosis. Literature data of children affected by PEComas were also analyzed, trying to identify pathologic characteristics that could predict their course and therapeutic options. Histologically, they may be differentiated in 3 prognostic categories: (1) benign, lacking unfavorable morphological markers; (2) with uncertain malignant potential, carrying 1 unfavorable marker; and (3) malignant, with at least 2 unfavorable markers. In the literature, 9% of cases occurred as a second malignancy probably because of genomic instability related to treatment. Their different biology and the potential value of targeted therapies remain to be explored. The indolent evolution in our patient was similar to that reported in some other cases in the literature. In terms of treatment, the present case suggests a minor response to temsirolimus compared with the adult population. Copyright © 2012 Elsevier Inc. All rights reserved.

Short and long term prognosis in perinatal asphyxia: An update.

PubMed

Ahearne, Caroline E; Boylan, Geraldine B; Murray, Deirdre M

2016-02-08

Interruption of blood flow and gas exchange to the fetus in the perinatal period, known as perinatal asphyxia, can, if significant, trigger a cascade of neuronal injury, leading on to neonatal encephalopathy (NE) and resultant long-term damage. While the majority of infants who are exposed to perinatal hypoxia-ischaemia will recover quickly and go on to have a completely normal survival, a proportion will suffer from an evolving clinical encephalopathy termed hypoxic-ischaemic encephalopathy (HIE) or NE if the diagnosis is unclear. Resultant complications of HIE/NE are wide-ranging and may affect the motor, sensory, cognitive and behavioural outcome of the child. The advent of therapeutic hypothermia as a neuroprotective treatment for those with moderate and severe encephalopathy has improved prognosis. Outcome prediction in these infants has changed, but is more important than ever, as hypothermia is a time sensitive intervention, with a very narrow therapeutic window. To identify those who will benefit from current and emerging neuroprotective therapies we must be able to establish the severity of their injury soon after birth. Currently available indicators such as blood biochemistry, clinical examination and electrophysiology are limited. Emerging biological and physiological markers have the potential to improve our ability to select those infants who will benefit most from intervention. Biomarkers identified from work in proteomics, metabolomics and transcriptomics as well as physiological markers such as heart rate variability, EEG analysis and radiological imaging when combined with neuroprotective measures have the potential to improve outcome in HIE/NE. The aim of this review is to give an overview of the literature in regards to short and long-term outcome following perinatal asphyxia, and to discuss the prediction of this outcome in the early hours after birth when intervention is most crucial; looking at both currently available tools and introducing novel markers.

The significance and predictive value of free light chains in the urine of patients with chronic inflammatory rheumatic disease.

PubMed

Bramlage, Carsten Paul; Froelich, Britta; Wallbach, Manuel; Minguet, Joan; Grupp, Clemens; Deutsch, Cornelia; Bramlage, Peter; Koziolek, Michael; Müller, Gerhard Anton

2016-12-01

In patients with rheumatic diseases, reliable markers for determining disease activity are scarce. One potential parameter is the level of immunoglobulin free light chains (FLCs), which is known to be elevated in the blood of patients with certain rheumatic diseases. Few studies have quantified FLCs in urine, a convenient source of test sample, in patients with different rheumatic diseases. We carried out a retrospective analysis of patients with rheumatic disease attending the University hospital of Goettingen, Germany. Subjects were included if they had urine levels of both κ and λ FLCs available and did not have myeloma. Data regarding systemic inflammation and kidney function were recorded, and FLC levels were correlated with inflammatory markers. Of the 382 patients with rheumatic disease, 40.1 % had chronic polyarthritis, 21.2 % connective tissue disease, 18.6 % spondyloarthritis and 15.7 % vasculitis. Elevated levels of κ FLCs were found for 84 % of patients and elevated λ for 52.7 %. For the patients with rheumatoid arthritis, FLCs correlated with C-reactive protein (κ, r = 0.368, p < 0.001; λ, r = 0.398, p < 0.001) and erythrocyte sedimentation rate (κ, r = 0.692, p < 0.001; λ, r = 0.612, p < 0.001). Patients being treated with rituximab displayed FLC levels similar to those of the reference group. There were clear elevations in both κ and λ FLCs in patients with rheumatic disease, but not in κ/λ ratio. The correlation between FLCs and inflammatory markers in patients with rheumatoid arthritis demonstrates their potential for predicting disease activity.

Nonparametric method for genomics-based prediction of performance of quantitative traits involving epistasis in plant breeding.

PubMed

Sun, Xiaochun; Ma, Ping; Mumm, Rita H

2012-01-01

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.

Nonparametric Method for Genomics-Based Prediction of Performance of Quantitative Traits Involving Epistasis in Plant Breeding

PubMed Central

Sun, Xiaochun; Ma, Ping; Mumm, Rita H.

2012-01-01

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression. PMID:23226325

Mutation at embB Codon 306, a Potential Marker for the Identification of Multidrug Resistance Associated with Ethambutol in Mycobacterium tuberculosis

PubMed Central

Cuevas-Córdoba, Betzaida; Juárez-Eusebio, Dulce María; Almaraz-Velasco, Raquel; Muñiz-Salazar, Raquel; Laniado-Laborin, Rafael

2015-01-01

Ethambutol inhibits arabinogalactan and lipoarabinomannan biosynthesis in mycobacteria. The occurrence of mutations in embB codon 306 in ethambutol-susceptible isolates and their absence in resistant isolates has raised questions regarding the utility of this codon as a potential marker for resistance against ethambutol. The characterization of mutations on embB 306 will contribute to a better understanding of the mechanisms of resistance to this drug; therefore, the purpose of this study was to investigate the association between embB 306 mutations and first-line drug resistance profiles in tuberculosis isolates. We sequenced the region surrounding the embB 306 codon in 175 tuberculosis clinical isolates, divided according to drug sensitivity, in three groups: 110 were resistant to at least one first-line drug, of which 61 were resistant to ethambutol (EMBr), 49 were sensitive to ethambutol (EMBs) but were resistant to another drug, and 65 were pansensitive isolates (Ps). The associations between embB 306 mutations and phenotypic resistance to all first-line drugs were determined, and their validity and safety as a diagnostic marker were assessed. One of the Ps isolates (1/65), one of the EMBs isolates (1/49), and 20 of the EMBr isolates (20/61) presented with an embB 306 mutation. Four different single-nucleotide polymorphisms (SNPs) at embB 306 were associated with simultaneous resistance to ethambutol, isoniazid, and rifampin (odds ratio [OR], 17.7; confidence interval [CI], 5.6 to 56.1) and showed a positive predictive value of 82%, with a specificity of 97% for diagnosing multidrug resistance associated with ethambutol, indicating its potential as a molecular marker for several drugs. PMID:26124153

Neural Markers of Attention to Aversive Pictures Predict Response to Cognitive Behavioral Therapy in Anxiety and Depression

PubMed Central

Stange, Jonathan P.; MacNamara, Annmarie; Barnas, Olga; Kennedy, Amy E.; Hajcak, Greg; Phan, K Luan; Klumpp, Heide

2016-01-01

Excessive attention toward aversive information may be a core mechanism underlying emotional disorders, but little is known about whether this is predictive of response to treatments. We evaluated whether enhanced attention toward aversive stimuli, as indexed by an event-related potential component, the late positive potential (LPP), would predict response to cognitive behavioral therapy (CBT) in patients with social anxiety disorder and/or major depressive disorder. Thirty-two patients receiving 12 weeks of CBT responded to briefly-presented pairs of aversive and neutral pictures that served as targets or distracters while electroencephaolography was recorded. Patients with larger pre-treatment LPPs to aversive relative to neutral distracters (when targets were aversive) were more likely to respond to CBT, and demonstrated larger reductions in symptoms of depression and anxiety following treatment. Increased attention toward irrelevant aversive stimuli may signal attenuated top-down control, so treatments like CBT that improve this control could be beneficial for these individuals. PMID:27784617

Emotion and hypervigilance: negative affect predicts increased P1 responses to non-negative pictorial stimuli.

PubMed

Schomberg, Jessica; Schöne, Benjamin; Gruber, Thomas; Quirin, Markus

2016-06-01

Previous research has demonstrated that negative affect influences attentional processes. Here, we investigate whether pre-experimental negative affect predicts a hypervigilant neural response as indicated by increased event-related potential amplitudes in response to neutral and positive visual stimuli. In our study, seventeen male participants filled out the German version of the positive and negative affect schedule (Watson et al. in J Pers Soc Psychol 54:1063-1070, 1988; Krohne et al. in Diagnostica 42:139-156, 1996) and subsequently watched positive (erotica, extreme sports, beautiful women) and neutral (daily activities) photographs while electroencephalogram was recorded. In line with our hypothesis, low state negative affect but not (reduced) positive affect predicted an increase in the first positive event-related potential amplitude P1 as a typical marker of increased selective attention. As this effect occurred in response to non-threatening picture conditions, negative affect may foster an individual's general hypervigilance, a state that has formerly been associated with psychopathology only.

Neural markers of attention to aversive pictures predict response to cognitive behavioral therapy in anxiety and depression.

PubMed

Stange, Jonathan P; MacNamara, Annmarie; Barnas, Olga; Kennedy, Amy E; Hajcak, Greg; Phan, K Luan; Klumpp, Heide

2017-02-01

Excessive attention toward aversive information may be a core mechanism underlying emotional disorders, but little is known about whether this is predictive of response to treatments. We evaluated whether enhanced attention toward aversive stimuli, as indexed by an event-related potential component, the late positive potential (LPP), would predict response to cognitive behavioral therapy (CBT) in patients with social anxiety disorder and/or major depressive disorder. Thirty-two patients receiving 12 weeks of CBT responded to briefly-presented pairs of aversive and neutral pictures that served as targets or distracters while electroencephaolography was recorded. Patients with larger pre-treatment LPPs to aversive relative to neutral distracters (when targets were aversive) were more likely to respond to CBT, and demonstrated larger reductions in symptoms of depression and anxiety following treatment. Increased attention toward irrelevant aversive stimuli may signal attenuated top-down control, so treatments like CBT that improve this control could be beneficial for these individuals. Copyright © 2016 Elsevier B.V. All rights reserved.

Structure-Based Design of Inhibitors to the Cytotoxin Ricin

DTIC Science & Technology

2006-07-01

markers for the receptor may be predicted by these programs. To follow up on this experiment, we began to screen a large commercial data base, the...of the Huisgen thermal [3+2] cycloaddition reaction (Table 1). The advantages of this click chemistry approach include the potential for favorable...41, 2113-2116. Hartmuth C. Kolb, M. G. F. K. B. S. (2001). Click Chemistry: Diverse Chemical Function from a Few Good Reactions . Angewandte

Circulating metabolomic profile can predict dyslipidemia in HIV patients undergoing antiretroviral therapy.

PubMed

Rodríguez-Gallego, Esther; Gómez, Josep; Domingo, Pere; Ferrando-Martínez, Sara; Peraire, Joaquim; Viladés, Consuelo; Veloso, Sergi; López-Dupla, Miguel; Beltrán-Debón, Raúl; Alba, Verónica; Vargas, Montserrat; Castellano, Alfonso J; Leal, Manuel; Pacheco, Yolanda María; Ruiz-Mateos, Ezequiel; Gutiérrez, Félix; Vidal, Francesc; Rull, Anna

2018-06-01

Dyslipidemia in HIV-infected patients is unique and pathophysiologically associated with host factors, HIV itself and the use of antiretroviral therapy (ART). The use of nuclear magnetic resonance spectroscopy (NMR) provides additional data to conventional lipid measurements concerning the number of lipoprotein subclasses and particle sizes. To investigate the ability of lipoprotein profile, we used a circulating metabolomic approach in a cohort of 103 ART-naive HIV-infected patients, who were initiating non-nucleoside analogue transcriptase inhibitor (NNRTI)-based ART, and we subsequently followed up these patients for 36 months. Univariate and multivariate analyses were performed to evaluate the predictive power of NMR spectroscopy. VLDL-metabolism (including VLDL lipid concentrations, sizes, and particle numbers), total triglycerides and lactate levels resulted in good classifiers of dyslipidemia (AUC 0.903). Total particles/HDL-P ratio was significantly higher in ART-associated dyslipidemia compared to ART-normolipidemia (p = 0.001). Large VLDL-Ps were positively associated with both LDL-triglycerides (ρ 0.682, p < 0.001) and lactate concentrations (ρ 0.416, p < 0.001), the last one a marker of mitochondrial low oxidative capacity. Our data suggest that circulating metabolites have better predictive values for HIV/ART-related dyslipidemia onset than do the biochemical markers associated with conventional lipid measurements. NMR identifies changes in VLDL-P, lactate and LDL-TG as potential clinical markers of baseline HIV-dyslipidemia predisposition. Differences in circulating metabolomics, especially differences in particle size, are indicators of important derangements of mitochondrial function that are linked to ART-related dyslipidemia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Inflamm-aging does not simply reflect increases in pro-inflammatory markers.

PubMed

Morrisette-Thomas, Vincent; Cohen, Alan A; Fülöp, Tamàs; Riesco, Éléonor; Legault, Véronique; Li, Qing; Milot, Emmanuel; Dusseault-Bélanger, Françis; Ferrucci, Luigi

2014-07-01

Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions among the markers. A multidimensional approach allows a more robust interpretation of the various relationships between the markers. We applied principal component analysis (PCA) to 19 inflammatory biomarkers from the InCHIANTI study. We identified a clear, stable structure among the markers, with the first axis explaining inflammatory activation (both pro- and anti-inflammatory markers loaded strongly and positively) and the second axis innate immune response. The first but not the second axis was strongly correlated with age (r=0.56, p<0.0001, r=0.08 p=0.053), and both were strongly predictive of mortality (hazard ratios per PCA unit (95% CI): 1.33 (1.16-1.53) and 0.87 (0.76-0.98) respectively) and multiple chronic diseases, but in opposite directions. Both axes were more predictive than any individual markers for baseline chronic diseases and mortality. These results show that PCA can uncover a novel biological structure in the relationships among inflammatory markers, and that key axes of this structure play important roles in chronic disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Proteomic Signatures of the Zebrafish (Danio rerio) Embryo: Sensitivity and Specificity in Toxicity Assessment of Chemicals.

PubMed

Hanisch, Karen; Küster, Eberhard; Altenburger, Rolf; Gündel, Ulrike

2010-01-01

Studies using embryos of the zebrafish Danio rerio (DarT) instead of adult fish for characterising the (eco-) toxic potential of chemicals have been proposed as animal replacing methods. Effect analysis at the molecular level might enhance sensitivity, specificity, and predictive value of the embryonal studies. The present paper aimed to test the potential of toxicoproteomics with zebrafish eleutheroembryos for sensitive and specific toxicity assessment. 2-DE-based toxicoproteomics was performed applying low-dose (EC(10)) exposure for 48 h with three-model substances Rotenone, 4,6-dinitro-o-cresol (DNOC) and Diclofenac. By multivariate "pattern-only" PCA and univariate statistical analyses, alterations in the embryonal proteome were detectable in nonetheless visibly intact organisms and treatment with the three substances was distinguishable at the molecular level. Toxicoproteomics enabled the enhancement of sensitivity and specificity of the embryonal toxicity assay and bear the potency to identify protein markers serving as general stress markers and early diagnosis of toxic stress.

Proteomic Signatures of the Zebrafish (Danio rerio) Embryo: Sensitivity and Specificity in Toxicity Assessment of Chemicals

PubMed Central

Hanisch, Karen; Küster, Eberhard; Altenburger, Rolf; Gündel, Ulrike

2010-01-01

Studies using embryos of the zebrafish Danio rerio (DarT) instead of adult fish for characterising the (eco-) toxic potential of chemicals have been proposed as animal replacing methods. Effect analysis at the molecular level might enhance sensitivity, specificity, and predictive value of the embryonal studies. The present paper aimed to test the potential of toxicoproteomics with zebrafish eleutheroembryos for sensitive and specific toxicity assessment. 2-DE-based toxicoproteomics was performed applying low-dose (EC10) exposure for 48 h with three-model substances Rotenone, 4,6-dinitro-o-cresol (DNOC) and Diclofenac. By multivariate “pattern-only” PCA and univariate statistical analyses, alterations in the embryonal proteome were detectable in nonetheless visibly intact organisms and treatment with the three substances was distinguishable at the molecular level. Toxicoproteomics enabled the enhancement of sensitivity and specificity of the embryonal toxicity assay and bear the potency to identify protein markers serving as general stress markers and early diagnosis of toxic stress. PMID:22084678

Molecular epidemiology, cancer-related symptoms, and cytokines pathway

PubMed Central

Reyes-Gibby, Cielito C; Wu, Xifeng; Spitz, Margaret; Kurzrock, Razelle; Fisch, Michael; Bruera, Eduardo; Shete, Sanjay

2012-01-01

The Human Genome Project and HapMap have led to a better appreciation of the importance of common genetic variation in determining cancer risk, created potential for predicting response to therapy, and made possible the development of targeted prevention and therapeutic interventions. Advances in molecular epidemiology can be used to explore the role of genetic variation in modulating the risk for severe and persistent symptoms, such as pain, depression, and fatigue, in patients with cancer. The same genes that are implicated in cancer risk might also be involved in the modulation of therapeutic outcomes. For example, polymorphisms in several cytokine genes are potential markers for genetic susceptibility both for cancer risk and for cancer-related symptoms. These genetic polymorphisms are stable markers and easily and reliably assayed to explore the extent to which genetic variation might prove useful in identifying patients with cancer at high-risk of symptom development. Likewise, they could identify subgroups who might benefit most from symptom intervention, and contribute to developing personalised and more effective therapies for persistent symptoms. PMID:18672213

Molecular Pathology: Predictive, Prognostic, and Diagnostic Markers in Uterine Tumors.

PubMed

Ritterhouse, Lauren L; Howitt, Brooke E

2016-09-01

This article focuses on the diagnostic, prognostic, and predictive molecular biomarkers in uterine malignancies, in the context of morphologic diagnoses. The histologic classification of endometrial carcinomas is reviewed first, followed by the description and molecular classification of endometrial epithelial malignancies in the context of histologic classification. Taken together, the molecular and histologic classifications help clinicians to approach troublesome areas encountered in clinical practice and evaluate the utility of molecular alterations in the diagnosis and subclassification of endometrial carcinomas. Putative prognostic markers are reviewed. The use of molecular alterations and surrogate immunohistochemistry as prognostic and predictive markers is also discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving the quality of biomarker discovery research: the right samples and enough of them.

PubMed

Pepe, Margaret S; Li, Christopher I; Feng, Ziding

2015-06-01

Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients.

PubMed

Bernchou, Uffe; Hansen, Olfred; Schytte, Tine; Bertelsen, Anders; Hope, Andrew; Moseley, Douglas; Brink, Carsten

2015-10-01

This study investigates the ability of pre-treatment factors and response markers extracted from standard cone-beam computed tomography (CBCT) images to predict the lung density changes induced by radiotherapy for non-small cell lung cancer (NSCLC) patients. Density changes in follow-up computed tomography scans were evaluated for 135 NSCLC patients treated with radiotherapy. Early response markers were obtained by analysing changes in lung density in CBCT images acquired during the treatment course. The ability of pre-treatment factors and CBCT markers to predict lung density changes induced by radiotherapy was investigated. Age and CBCT markers extracted at 10th, 20th, and 30th treatment fraction significantly predicted lung density changes in a multivariable analysis, and a set of response models based on these parameters were established. The correlation coefficient for the models was 0.35, 0.35, and 0.39, when based on the markers obtained at the 10th, 20th, and 30th fraction, respectively. The study indicates that younger patients without lung tissue reactions early into their treatment course may have minimal radiation induced lung density increase at follow-up. Further investigations are needed to examine the ability of the models to identify patients with low risk of symptomatic toxicity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Transcriptome analysis of cattle muscle identifies potential markers for skeletal muscle growth rate and major cell types.

PubMed

Guo, Bing; Greenwood, Paul L; Cafe, Linda M; Zhou, Guanghong; Zhang, Wangang; Dalrymple, Brian P

2015-03-13

This study aimed to identify markers for muscle growth rate and the different cellular contributors to cattle muscle and to link the muscle growth rate markers to specific cell types. The expression of two groups of genes in the longissimus muscle (LM) of 48 Brahman steers of similar age, significantly enriched for "cell cycle" and "ECM (extracellular matrix) organization" Gene Ontology (GO) terms was correlated with average daily gain/kg liveweight (ADG/kg) of the animals. However, expression of the same genes was only partly related to growth rate across a time course of postnatal LM development in two cattle genotypes, Piedmontese x Hereford (high muscling) and Wagyu x Hereford (high marbling). The deposition of intramuscular fat (IMF) altered the relationship between the expression of these genes and growth rate. K-means clustering across the development time course with a large set of genes (5,596) with similar expression profiles to the ECM genes was undertaken. The locations in the clusters of published markers of different cell types in muscle were identified and used to link clusters of genes to the cell type most likely to be expressing them. Overall correspondence between published cell type expression of markers and predicted major cell types of expression in cattle LM was high. However, some exceptions were identified: expression of SOX8 previously attributed to muscle satellite cells was correlated with angiogenesis. Analysis of the clusters and cell types suggested that the "cell cycle" and "ECM" signals were from the fibro/adipogenic lineage. Significant contributions to these signals from the muscle satellite cells, angiogenic cells and adipocytes themselves were not as strongly supported. Based on the clusters and cell type markers, sets of five genes predicted to be representative of fibro/adipogenic precursors (FAPs) and endothelial cells, and/or ECM remodelling and angiogenesis were identified. Gene sets and gene markers for the analysis of many of the major processes/cell populations contributing to muscle composition and growth have been proposed, enabling a consistent interpretation of gene expression datasets from cattle LM. The same gene sets are likely to be applicable in other cattle muscles and in other species.

Socioeconomic status, psychological resources, and inflammatory markers: Results from the MIDUS Study

PubMed Central

Elliot, Ari J.; Chapman, Benjamin P.

2016-01-01

Objective To investigate interactions of psychological resources and socioeconomic status in predicting markers of systemic inflammation, as well as potential gender differences and the explanatory role of childhood and adult stress exposures, health behaviors, and negative and positive affect. Method We utilized a sample of adults from the Midlife in the United States Survey (MIDUS) who provided biomarker data (N=1,152). SES was operationalized as a composite of education, income, and occupational prestige, and psychological resources as a latent factor measured with optimism, perceived control, and self-esteem. Linear regression models examined these two factors and their interaction in predicting interleukin-6 (IL-6) and C-reactive protein (CRP) measured on average 2 years later, as well as three-way interactions involving gender and the impact of covariate adjustment. Results Psychological resources interacted with SES in men (for IL-6: p<.001; for CRP: p=.04) but not in women. In men, greater psychological resources were associated with lower concentrations of IL-6 at lower levels of SES, but higher concentrations of both markers at higher levels of SES. The inverse association between resources and IL-6 at low SES was moderately attenuated upon adjustment for negative affect. Conclusion Socioeconomic status might modulate the linkage between psychological resources and systemic inflammation in men. At lower levels of SES, resources may be related to lower inflammation in part through lower negative affect. Associations with higher inflammation at higher SES add to growing evidence suggesting that adaptive psychological characteristics may be associated with markers of poorer physiological function under certain conditions. PMID:27280368

Inferring Geographic Coordinates of Origin for Europeans Using Small Panels of Ancestry Informative Markers

PubMed Central

Paschou, Peristera

2010-01-01

Recent large-scale studies of European populations have demonstrated the existence of population genetic structure within Europe and the potential to accurately infer individual ancestry when information from hundreds of thousands of genetic markers is used. In fact, when genomewide genetic variation of European populations is projected down to a two-dimensional Principal Components Analysis plot, a surprising correlation with actual geographic coordinates of self-reported ancestry has been reported. This substructure can hamper the search of susceptibility genes for common complex disorders leading to spurious correlations. The identification of genetic markers that can correct for population stratification becomes therefore of paramount importance. Analyzing 1,200 individuals from 11 populations genotyped for more than 500,000 SNPs (Population Reference Sample), we present a systematic exploration of the extent to which geographic coordinates of origin within Europe can be predicted, with small panels of SNPs. Markers are selected to correlate with the top principal components of the dataset, as we have previously demonstrated. Performing thorough cross-validation experiments we show that it is indeed possible to predict individual ancestry within Europe down to a few hundred kilometers from actual individual origin, using information from carefully selected panels of 500 or 1,000 SNPs. Furthermore, we show that these panels can be used to correctly assign the HapMap Phase 3 European populations to their geographic origin. The SNPs that we propose can prove extremely useful in a variety of different settings, such as stratification correction or genetic ancestry testing, and the study of the history of European populations. PMID:20805874

Serum biomarkers of bone metabolism in castration-resistant prostate cancer patients with skeletal metastases: results from SWOG 0421.

PubMed

Lara, Primo N; Ely, Benjamin; Quinn, David I; Mack, Philip C; Tangen, Catherine; Gertz, Erik; Twardowski, Przemyslaw W; Goldkorn, Amir; Hussain, Maha; Vogelzang, Nicholas J; Thompson, Ian M; Van Loan, Marta D

2014-04-01

Prior studies suggest that elevated markers of bone turnover are prognostic for poor survival in castration-resistant prostate cancer (CRPC). The predictive role of these markers relative to bone-targeted therapy is unknown. We prospectively evaluated the prognostic and predictive value of bone biomarkers in sera from CRPC patients treated on a placebo-controlled phase III trial of docetaxel with or without the bone targeted endothelin-A receptor antagonist atrasentan (SWOG S0421). Markers for bone resorption (N-telopeptide and pyridinoline) and formation (C-terminal collagen propeptide and bone alkaline phosphatase) were assayed in pretreatment and serial sera. Cox proportional hazards regression models were fit for overall survival. Models were fit with main effects for marker levels and with/without terms for marker-treatment interaction, adjusted for clinical variables, to assess the prognostic and predictive value of atrasentan. Analysis was adjusted for multiple comparisons. Two-sided P values were calculated using the Wald test. Sera from 778 patients were analyzed. Elevated baseline levels of each of the markers were associated with worse survival (P < .001). Increasing marker levels by week nine of therapy were also associated with subsequent poor survival (P < .001). Patients with the highest marker levels (upper 25th percentile for all markers) not only had a poor prognosis (hazard ratio [HR] = 4.3; 95% confidence interval [CI] = 2.41 to 7.65; P < .001) but also had a survival benefit from atrasentan (HR = 0.33; 95% CI = 0.15 to 0.71; median survival = 13 [atrasentan] vs 5 months [placebo]; P interaction = .005). Serum bone metabolism markers have statistically significant independent prognostic value in CRPC. Importantly, a small group of patients (6%) with highly elevated markers of bone turnover appear to preferentially benefit from atrasentan therapy.

A practical review of prognostic correlations of molecular biomarkers in glioblastoma.

PubMed

Karsy, Michael; Neil, Jayson A; Guan, Jian; Mahan, Mark A; Mark, Mahan A; Colman, Howard; Jensen, Randy L

2015-03-01

Despite extensive efforts in research and therapeutics, achieving longer survival for patients with glioblastoma (GBM) remains a formidable challenge. Furthermore, because of rapid advances in the scientific understanding of GBM, communication with patients regarding the explanations and implications of genetic and molecular markers can be difficult. Understanding the important biomarkers that play a role in GBM pathogenesis may also help clinicians in educating patients about prognosis, potential clinical trials, and monitoring response to treatments. This article aims to provide an up-to-date review that can be discussed with patients regarding common molecular markers, namely O-6-methylguanine-DNA methyltransferase (MGMT), isocitrate dehydrogenase 1 and 2 (IDH1/2), p53, epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), phosphatase and tensin homolog (PTEN), phosphoinositide 3-kinase (PI3K), and 1p/19q. The importance of the distinction between a prognostic and a predictive biomarker as well as clinical trials regarding these markers and their relevance to clinical practice are discussed.

Systems immunology reveals markers of susceptibility to West Nile virus infection.

PubMed

Qian, Feng; Goel, Gautam; Meng, Hailong; Wang, Xiaomei; You, Fuping; Devine, Lesley; Raddassi, Khadir; Garcia, Melissa N; Murray, Kristy O; Bolen, Christopher R; Gaujoux, Renaud; Shen-Orr, Shai S; Hafler, David; Fikrig, Erol; Xavier, Ramnik; Kleinstein, Steven H; Montgomery, Ruth R

2015-01-01

West Nile virus (WNV) infection is usually asymptomatic but can cause severe neurological disease and death, particularly in older patients, and how individual variations in immunity contribute to disease severity is not yet defined. Animal studies identified a role for several immunity-related genes that determine the severity of infection. We have integrated systems-level transcriptional and functional data sets from stratified cohorts of subjects with a history of WNV infection to define whether these markers can distinguish susceptibility in a human population. Transcriptional profiles combined with immunophenotyping of primary cells identified a predictive signature of susceptibility that was detectable years after acute infection (67% accuracy), with the most prominent alteration being decreased IL1B induction following ex vivo infection of macrophages with WNV. Deconvolution analysis also determined a significant role for CXCL10 expression in myeloid dendritic cells. This systems analysis identified markers of pathogenic mechanisms and offers insights into potential therapeutic strategies. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways

PubMed Central

Shao, Zhuo; Huo, Diwei; Zhang, Denan; Xie, Hongbo; Yang, Jingbo; Liu, Qiuqi; Chen, Xiujie

2018-01-01

Hepatocellular carcinoma (HCC) is the most frequent type of liver cancer with poor survival rate and high mortality. Despite efforts on the mechanism of HCC, new molecular markers are needed for exact diagnosis, evaluation and treatment. Here, we combined transcriptome of HCC with networks and pathways to identify reliable molecular markers. Through integrating 249 differentially expressed genes with syncretic protein interaction networks, we constructed a HCC-specific network, from which we further extracted 480 pivotal genes. Based on the cross-talk between the enriched pathways of the pivotal genes, we finally identified a HCC signature of 45 genes, which could accurately distinguish HCC patients with normal individuals and reveal the prognosis of HCC patients. Among these 45 genes, 15 showed dysregulated expression patterns and a part have been reported to be associated with HCC and/or other cancers. These findings suggested that our identified 45 gene signature could be potential and valuable molecular markers for diagnosis and evaluation of HCC. PMID:29765536

Expression of Epithelial Mesenchymal Transition and Cancer Stem Cell Markers in Circulating Tumor Cells.

PubMed

Werner, Stefan; Stenzl, Arnulf; Pantel, Klaus; Todenhöfer, Tilman

2017-01-01

The characterization of circulating tumor cells (CTC) has the potential not only to provide important insights into molecular alterations of advanced tumor disease but also to facilitate risk prediction. Epithelial mesenchymal transition (EMT) has been discovered as important process for the development of metastases and the dissemination of tumor cells into the blood stream. In different tumor types, CTC with a mesenchymal phenotype have been reported that have presumably underwent EMT. Moreover, CTC with stem-cell like characteristics have been postulated as important drivers of tumor progression. Different platforms have been introduced to allow CTC enrichment independent of expression of epithelial antigens, as these may be downregulated in EMT- or stem-cell-like CTC. Both for CTCs with EMT- or stem-cell features different markers have been proposed. However, there is still a lack of evidence on the association of these markers with functional features and characteristics for stem cells and cells undergoing EMT.

Analysis of molecular markers as predictive factors of lymph node involvement in breast carcinoma.

PubMed

Paula, Luciana Marques; De Moraes, Luis Henrique Ferreira; Do Canto, Abaeté Leite; Dos Santos, Laurita; Martin, Airton Abrahão; Rogatto, Silvia Regina; De Azevedo Canevari, Renata

2017-01-01

Nodal status is the most significant independent prognostic factor in breast cancer. Identification of molecular markers would allow stratification of patients who require surgical assessment of lymph nodes from the large numbers of patients for whom this surgical procedure is unnecessary, thus leading to a more accurate prognosis. However, up to now, the reported studies are preliminary and controversial, and although hundreds of markers have been assessed, few of them have been used in clinical practice for treatment or prognosis in breast cancer. The purpose of the present study was to determine whether protein phosphatase Mg2+/Mn2+ dependent 1D, β-1,3-N-acetylglucosaminyltransferase, neural precursor cell expressed, developmentally down-regulated 9, prohibitin, phosphoinositide-3-kinase regulatory subunit 5 (PIK3R5), phosphatidylinositol-5-phosphate 4-kinase type IIα, TRF1-interacting ankyrin-related ADP-ribose polymerase 2, BCL2 associated agonist of cell death, G2 and S-phase expressed 1 and PAX interacting protein 1 genes, described as prognostic markers in breast cancer in a previous microarray study, are also predictors of lymph node involvement in breast carcinoma Reverse transcription-quantitative polymerase chain reaction analysis was performed on primary breast tumor tissues from women with negative lymph node involvement (n=27) compared with primary tumor tissues from women with positive lymph node involvement (n=23), and was also performed on primary tumors and paired lymph node metastases (n=11). For all genes analyzed, only the PIK3R5 gene exhibited differential expression in samples of primary tumors with positive lymph node involvement compared with primary tumors with negative lymph node involvement (P=0.0347). These results demonstrate that the PIK3R5 gene may be considered predictive of lymph node involvement in breast carcinoma. Although the other genes evaluated in the present study have been previously characterized to be involved with the development of distant metastases, they did not have predictive potential.

Integration of DNA marker information into breeding value predictions

USDA-ARS?s Scientific Manuscript database

Calves from seven breeds including 20 herds were genotyped with a reduced DNA marker panel for weaning weight. The marker panel used was derived using USMARC Cycle VII animals. The results from the current study suggest marker effects are not robust across breeds and that methodology exists to integ...

Potential application of non-small cell lung cancer-associated autoantibodies to early cancer diagnosis

PubMed Central

Yao, Yibing; Fan, Yu; Wu, Jun; Wan, Haisu; Wang, Jing; Lam, Stephen; Lam, Wan L.; Girard, Luc; Gazdar, Adi F.; Wu, Zhihao; Zhou, Qinghua

2015-01-01

To identify a panel of tumor associated autoantibodies which can potentially be used as biomarkers for the early diagnosis of non-small cell lung cancer (NSCLC). Thirty-five unique and in-frame expressed phage proteins were isolated. Based on the gene expression profiling, four proteins were selected for further study. Both receiver operating characteristic curve analysis and leave-one-out method revealed that combined measurements of four antibodies produced have better predictive accuracies than any single marker alone. Leave-one-out validation also showed significant relevance with all stages of NSCLC patients. The panel of autoantibodies has a high potential for detecting early stage NSCLC. PMID:22713465

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction.

PubMed

Brøndum, R F; Su, G; Janss, L; Sahana, G; Guldbrandtsen, B; Boichard, D; Lund, M S

2015-06-01

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Serial urinary IL-2, IL-6, IL-8, TNFalpha, UBC, CYFRA 21-1 and NMP22 during follow-up of patients with bladder cancer receiving intravesical BCG.

PubMed

Sanchez-Carbayo, M; Urrutia, M; Romani, R; Herrero, M; Gonzalez de Buitrago, J M; Navajo, J A

2001-01-01

We evaluated the potential role of serial preinstillation levels of several interleukins, TNFalpha and urinary tumor markers to monitor patients with bladder cancer receiving intravesical BCG. 121 urine samples were collected from: patients with bladder cancer treated with BCG (group 1); patients with bladder cancer receiving other intravesical treatment (group 2) and patients with urinary tract infections (group 3). Cytokines [IL-2, IL6 and [L8] and TNFalpha and urinary tumor markers [UBC, CYFRA 21-1 and NMP22] were measured by immunoassays. In 3 out of 15 BCG non-responders that recurred over the period of the study, no cytokine peak for IL-2, IL-6 or TNFa were detected. Urinary tumor markers increased in 2 out of 3 of these patients earlier than scheduled cystoscopies. Cytokine measurement was heterogeneous among 12 out of 15 BCG-responding patients: there were low levels of IL-6 and TNFalpha and peaks of IL-2 and IL-8 in 10 out of 12 and 4 out of 12 patients, respectively. During responding patients' follow-up we observed false-positive results in 7 out of 65 urine samples for UBC, 8 out of 65 for CYFRA 21-1 and 20 out of 65 for NMP22. Urinary tract infections were the main factor associated with non-specific elevations of IL-6 and IL-8 and urinary tumor markers in all groups of patients. Although larger series are required to confirn our preliminary observations, our data argue for a potential predictive role for IL-2 of favourable response to BCG therapy. Monitoring BCG with urinary tumor markers could early detect recurrence in non-responding patients.

Biochemical bone turnover markers in diabetes mellitus - A systematic review.

PubMed

Starup-Linde, Jakob; Vestergaard, Peter

2016-01-01

Diabetes mellitus is associated with an increased risk of fractures, which is not explained by bone mineral density. Other markers as bone turnover markers (BTMs) may be useful. To assess the relationship between BTMs, diabetes, and fractures. A systematic literature search was conducted in August 2014. The databases searched were Medline at Pubmed and Embase. Medline at Pubmed was searched by "Diabetes Mellitus" (MESH) and "bone turnover markers" and Embase was searched using the Emtree by "Diabetes Mellitus" and "bone turnover", resulting in 611 studies. The eligibility criteria for the studies were to assess BTM in either type 1 diabetes (T1D) or type 2 diabetes (T2D) patients. Of the 611 eligible studies, removal of duplicates and screening by title and abstract lead to 114 potential studies for full-text review. All these studies were full-text screened for eligibility and 45 studies were included. Two additional studies were added from other sources. Among the 47 studies included there were 1 meta-analysis, 29 cross-sectional studies, 13 randomized controlled trials, and 4 longitudinal studies. Both T1D and T2D were studied. Most studies reported fasting BTM and excluded renal disease. Markers of bone resorption and formation seem to be lower in diabetes patients. Bone specific alkaline phosphatase is normal or increased, which suggests that the matrix becomes hypermineralized in diabetes patients. The BTMs: C-terminal cross-link of collagen, insulin-like growth factor-1, and sclerostin may potentially predict fractures, but longitudinal trials are needed. This article is part of a Special Issue entitled Bone and diabetes. Copyright © 2015 Elsevier Inc. All rights reserved.

Predictive markers in calpastatin for tenderness in commercial pig populations

USDA-ARS?s Scientific Manuscript database

The identification of predictive DNA markers for pork quality would allow U.S. pork producers and breeders to more quickly and efficiently select genetically superior animals for production of consistent, high quality meat. Genome scans have identified QTL for tenderness on pig chromosome 2 which ha...

Molecular marker genes for ectomycorrhizal symbiosis

Treesearch

Shiv Hiremath; Carolyn McQuattie; Gopi Podila; Jenise Bauman

2013-01-01

Mycorrhizal symbiosis is a mutually beneficial association very commonly found among most vascular plants. Formation of mycorrhiza happens only between compatible partners and predicting this is often accomplished through a trial and error process. We investigated the possibility of using expression of symbiosis specific genes as markers to predict the formation of...

Serum biomarkers of bone metabolism in castration resistant prostate cancer patients with skeletal metastases

USDA-ARS?s Scientific Manuscript database

Background. Prior studies suggest that elevated markers of bone turnover are prognostic for poor survival in castration resistant prostate cancer (CRPC). The predictive role of these markers relative to bone-targeted therapy is unknown. We prospectively evaluated the prognostic and predictive value ...

Dread of uncertain pain: An event-related potential study

PubMed Central

Huang, Yujing; Shang, Qian; Dai, Shenyi; Ma, Qingguo

2017-01-01

Humans experience more stress about uncertain situations than certain situations. However, the neural mechanism underlying the uncertainty of a negative stimulus has not been determined. In the present study, event-related potential was recorded to examine neural responses during the dread of unpredictable pain. We used a cueing paradigm in which predictable cues were always followed by electric shocks, unpredictable cues by electric shocks at a 50/50 ratio and safe cues by no electric shock. Visual analogue scales following electric shocks were presented to quantify subjective anxiety levels. The behavioral results showed that unpredictable cues evoked high-level anxiety compared with predictable cues in both painful and unpainful stimulation conditions. More importantly, the ERPs results revealed that unpredictable cues elicited a larger P200 at parietal sites than predictable cues. In addition, unpredictable cues evoked larger P200 compared with safe cues at frontal electrodes and compared with predictable cues at parietal electrodes. In addition, larger P3b and LPP were observed during perception of safe cues compared with predictable cues at frontal and central electrodes. The similar P3b effect was also revealed in the left sites. The present study underlined that the uncertain dread of pain was associated with threat appraisal process in pain system. These findings on early event-related potentials were significant for a neural marker and development of therapeutic interventions. PMID:28832607

Predicting the influence of liposomal lipid composition on liposome size, zeta potential and liposome-induced dendritic cell maturation using a design of experiments approach.

PubMed

Soema, Peter C; Willems, Geert-Jan; Jiskoot, Wim; Amorij, Jean-Pierre; Kersten, Gideon F

2015-08-01

In this study, the effect of liposomal lipid composition on the physicochemical characteristics and adjuvanticity of liposomes was investigated. Using a design of experiments (DoE) approach, peptide-containing liposomes containing various lipids (EPC, DOPE, DOTAP and DC-Chol) and peptide concentrations were formulated. Liposome size and zeta potential were determined for each formulation. Moreover, the adjuvanticity of the liposomes was assessed in an in vitro dendritic cell (DC) model, by quantifying the expression of DC maturation markers CD40, CD80, CD83 and CD86. The acquired data of these liposome characteristics were successfully fitted with regression models, and response contour plots were generated for each response factor. These models were applied to predict a lipid composition that resulted in a liposome with a target zeta potential. Subsequently, the expression of the DC maturation factors for this lipid composition was predicted and tested in vitro; the acquired maturation responses corresponded well with the predicted ones. These results show that a DoE approach can be used to screen various lipids and lipid compositions, and to predict their impact on liposome size, charge and adjuvanticity. Using such an approach may accelerate the formulation development of liposomal vaccine adjuvants. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

PubMed

Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Molecular markers of neuropsychological functioning and Alzheimer's disease.

PubMed

Edwards, Melissa; Balldin, Valerie Hobson; Hall, James; O'Bryant, Sid

2015-03-01

The current project sought to examine molecular markers of neuropsychological functioning among elders with and without Alzheimer's disease (AD) and determine the predictive ability of combined molecular markers and select neuropsychological tests in detecting disease presence. Data were analyzed from 300 participants (n = 150, AD and n = 150, controls) enrolled in the Texas Alzheimer's Research and Care Consortium. Linear regression models were created to examine the link between the top five molecular markers from our AD blood profile and neuropsychological test scores. Logistical regressions were used to predict AD presence using serum biomarkers in combination with select neuropsychological measures. Using the neuropsychological test with the least amount of variance overlap with the molecular markers, the combined neuropsychological test and molecular markers was highly accurate in detecting AD presence. This work provides the foundation for the generation of a point-of-care device that can be used to screen for AD.

Genetic Nature of Elemental Contents in Wheat Grains and Its Genomic Prediction: Toward the Effective Use of Wheat Landraces from Afghanistan

PubMed Central

Yamaoka, Shuhei; Yoshimura, Kazusa; Kondou, Youichi; Onogi, Akio; Matsui, Minami; Iwata, Hiroyoshi; Ban, Tomohiro

2017-01-01

Profiling elemental contents in wheat grains and clarifying the underlying genetic systems are important for the breeding of biofortified crops. Our objective was to evaluate the genetic potential of 269 Afghan wheat landraces for increasing elemental contents in wheat cultivars. The contents of three major (Mg, K, and P) and three minor (Mn, Fe, and Zn) elements in wheat grains were measured by energy dispersive X-ray fluorescence spectrometry. Large variations in elemental contents were observed among landraces. Marker-based heritability estimates were low to moderate, suggesting that the elemental contents are complex quantitative traits. Genetic correlations between two locations (Japan and Afghanistan) and among the six elements were estimated using a multi-response Bayesian linear mixed model. Low-to-moderate genetic correlations were observed among major elements and among minor elements respectively, but not between major and minor elements. A single-response genome-wide association study detected only one significant marker, which was associated with Zn, suggesting it will be difficult to increase the elemental contents of wheat by conventional marker-assisted selection. Genomic predictions for major elemental contents were moderately or highly accurate, whereas those for minor elements were mostly low or moderate. Our results indicate genomic selection may be useful for the genetic improvement of elemental contents in wheat. PMID:28072876

Immunophenotyping does not improve predictivity of the local lymph node assay in mice.

PubMed

Strauss, Volker; Kolle, Susanne N; Honarvar, Naveed; Dammann, Martina; Groeters, Sibylle; Faulhammer, Frank; Landsiedel, Robert; van Ravenzwaay, Bennard

2015-04-01

The local lymph node assay (LLNA) is a regulatory accepted test for the identification of skin sensitizing substances by measuring radioactive thymidine incorporation into the lymph node. However, there is evidence that LLNA is overestimating the sensitization potential of certain substance classes in particular those exerting skin irritation. Some reports describe the additional use of flow cytometry-based immunophenotyping to better discriminate irritants from sensitizing irritants in LLNA. In the present study, the 22 performance standards plus 8 surfactants were assessed using the radioactive LLNA method. In addition, lymph node cells were immunophenotyped to evaluate the specificity of the lymph node response using cell surface markers such as B220 or CD19, CD3, CD4, CD8, I-A(κ) and CD69 with the aim to allow a better discrimination above all between irritants and sensitizers, but also non-irritating sensitizers and non-sensitizers. However, the markers assessed in this study do not sufficiently differentiate between irritants and irritant sensitizers and therefore did not improve the predictive capacity of the LLNA. Copyright © 2014 John Wiley & Sons, Ltd.

Psychosis prediction in secondary mental health services. A broad, comprehensive approach to the "at risk mental state" syndrome.

PubMed

Francesconi, M; Minichino, A; Carrión, R E; Delle Chiaie, R; Bevilacqua, A; Parisi, M; Rullo, S; Bersani, F Saverio; Biondi, M; Cadenhead, K

2017-02-01

Accuracy of risk algorithms for psychosis prediction in "at risk mental state" (ARMS) samples may differ according to the recruitment setting. Standardized criteria used to detect ARMS individuals may lack specificity if the recruitment setting is a secondary mental health service. The authors tested a modified strategy to predict psychosis conversion in this setting by using a systematic selection of trait-markers of the psychosis prodrome in a sample with a heterogeneous ARMS status. 138 non-psychotic outpatients (aged 17-31) were consecutively recruited in secondary mental health services and followed-up for up to 3 years (mean follow-up time, 2.2 years; SD=0.9). Baseline ARMS status, clinical, demographic, cognitive, and neurological soft signs measures were collected. Cox regression was used to derive a risk index. 48% individuals met ARMS criteria (ARMS-Positive, ARMS+). Conversion rate to psychosis was 21% for the overall sample, 34% for ARMS+, and 9% for ARMS-Negative (ARMS-). The final predictor model with a positive predictive validity of 80% consisted of four variables: Disorder of Thought Content, visuospatial/constructional deficits, sensory-integration, and theory-of-mind abnormalities. Removing Disorder of Thought Content from the model only slightly modified the predictive accuracy (-6.2%), but increased the sensitivity (+9.5%). These results suggest that in a secondary mental health setting the use of trait-markers of the psychosis prodrome may predict psychosis conversion with great accuracy despite the heterogeneity of the ARMS status. The use of the proposed predictive algorithm may enable a selective recruitment, potentially reducing duration of untreated psychosis and improving prognostic outcomes. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Molecular epidemiology of malaria in Cameroon. XXX. sequence analysis of Plasmodium falciparum ATPase 6, dihydrofolate reductase, and dihydropteroate synthase resistance markers in clinical isolates from children treated with an artesunate-sulfadoxine-pyrimethamine combination.

PubMed

Menemedengue, Virginie; Sahnouni, Khalifa; Basco, Leonardo; Tahar, Rachida

2011-07-01

Plasmodium falciparum dihydrofolate reductase (dhfr) and dihydropteroate synthase (dhps) genes are reliable molecular markers for antifolate resistance. The P. falciparum ATPase 6 (pfatp6) gene has been proposed to be a potential marker for artemisinin resistance. In our previous clinical study, we showed that artesunate-sulfadoxine-pyrimethamine is highly effective against uncomplicated malaria in Yaoundé, Cameroon. In the present study, dhfr, dhps, and pfatp6 mutations in P. falciparum isolates obtained from children treated with artesunate-sulfadoxine-pyrimethamine were determined. All 61 isolates had wild-type Pfatp6 263, 623, and 769 alleles, and 11 (18%) had a single E431K substitution. Three additional mutations, E643Q, E432K, and E641Q, were detected. The results did not indicate any warning signal of serious concern (i.e., no parasites were seen with quintuple dhfr-dhps, DHFR Ile164Leu, or pfatp6 mutations), as confirmed by the high clinical efficacy of artesunate-sulfadoxine-pyrimethamine. Further studies are required to identify a molecular marker that reliably predicts artemisinin resistance.

Molecular Epidemiology of Malaria in Cameroon. XXX. Sequence Analysis of Plasmodium falciparum ATPase 6, Dihydrofolate Reductase, and Dihydropteroate Synthase Resistance Markers in Clinical Isolates from Children Treated with an Artesunate-Sulfadoxine-Pyrimethamine Combination

PubMed Central

Menemedengue, Virginie; Sahnouni, Khalifa; Basco, Leonardo; Tahar, Rachida

2011-01-01

Plasmodium falciparum dihydrofolate reductase (dhfr) and dihydropteroate synthase (dhps) genes are reliable molecular markers for antifolate resistance. The P. falciparum ATPase 6 (pfatp6) gene has been proposed to be a potential marker for artemisinin resistance. In our previous clinical study, we showed that artesunate-sulfadoxine-pyrimethamine is highly effective against uncomplicated malaria in Yaoundé, Cameroon. In the present study, dhfr, dhps, and pfatp6 mutations in P. falciparum isolates obtained from children treated with artesunate-sulfadoxine-pyrimethamine were determined. All 61 isolates had wild-type Pfatp6 263, 623, and 769 alleles, and 11 (18%) had a single E431K substitution. Three additional mutations, E643Q, E432K, and E641Q, were detected. The results did not indicate any warning signal of serious concern (i.e., no parasites were seen with quintuple dhfr-dhps, DHFR Ile164Leu, or pfatp6 mutations), as confirmed by the high clinical efficacy of artesunate-sulfadoxine-pyrimethamine. Further studies are required to identify a molecular marker that reliably predicts artemisinin resistance. PMID:21734119

Stable isotope-labelled feed nutrients to assess nutrient-specific feed passage kinetics in ruminants.

PubMed

Warner, Daniel; Dijkstra, Jan; Hendriks, Wouter H; Pellikaan, Wilbert F

2014-03-30

Knowledge of digesta passage kinetics in ruminants is essential to predict nutrient supply to the animal in relation to optimal animal performance, environmental pollution and animal health. Fractional passage rates (FPR) of feed are widely used in modern feed evaluation systems and mechanistic rumen models, but data on nutrient-specific FPR are scarce. Such models generally rely on conventional external marker techniques, which do not always describe digesta passage kinetics in a satisfactory manner. Here the use of stable isotope-labelled dietary nutrients as a promising novel tool to assess nutrient-specific passage kinetics is discussed. Some major limitations of this technique include a potential marker migration, a poor isotope distribution in the labelled feed and a differential disappearance rate of isotopes upon microbial fermentation in non-steady state conditions. Such limitations can often be circumvented by using intrinsically stable isotope-labelled plant material. Data are limited but indicate that external particulate markers overestimate rumen FPR of plant fibre compared with the internal stable isotope markers. Stable isotopes undergo the same digestive mechanism as the labelled feed components and are thus of particular interest to specifically measure passage kinetics of digestible dietary nutrients. © 2013 Society of Chemical Industry.

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

Prognostic value of HMGB1 and oxidative stress markers in multiple trauma patients: A single-centre prospective study.

PubMed

Polito, Francesca; Cicciu', Marco; Aguennouz, Mohammed; Cucinotta, Maria; Cristani, Mariateresa; Lauritano, Floriana; Sindoni, Alessandro; Gioffre'-Florio, Maria; Fama, Fausto

2016-09-01

Serious multiple traumatic injuries may rapidly become fatal or be complicated by a life-threatening sequelae leading to a significant increase of the mortality rate. Trauma scoring systems are used to evaluate the critical status of the patient and recently many different biomarkers have been taken into account to better estimate the potential clinical outcome. The aim of the present study is to analyse the expression pattern of high-mobility group box-1 (HMGB1), oxidative stress markers and nuclear factor erythroid 2-related (Nrf2) in critically ill traumatic patients (at hospital admittance and after 6 and 24 h), in order to find out their potential role as early post-traumatic predictors markers. Forty-seven patients admitted for multiple trauma and 15 healthy participants were prospectively recruited. Eight patients (17%) died within 92 h of admission; this subgroup of patients presented the highest severity scores and their HMGB1 expression levels were significantly correlated with ISS, whereas patients with higher ISS exhibited higher levels of HMGB1 (P <0.001). Our study suggests the role of HMGB1 as a predictive biomarker of outcome in injured patients and hypothesizes the protective role of Nrf2 in bringing down the oxidative stress and HMGB1 release; measuring HMGB1 in combination with Nrf2 might represent a potentially useful tool in the early detection of post-trauma complications. © The Author(s) 2016.

Early life adversity and inflammation in African Americans and whites in the midlife in the United States survey.

PubMed

Slopen, Natalie; Lewis, Tené T; Gruenewald, Tara L; Mujahid, Mahasin S; Ryff, Carol D; Albert, Michelle A; Williams, David R

2010-09-01

To determine whether early life adversity (ELA) was predictive of inflammatory markers and to determine the consistency of these associations across racial groups. We analyzed data from 177 African Americans and 822 whites aged 35 to 86 years from two preliminary subsamples of the Midlife in the United States biomarker study. ELA was measured via retrospective self-report. We used multivariate linear regression models to examine the associations between ELA and C-reactive protein, interleukin-6, fibrinogen, endothelial leukocyte adhesion molecule-1, and soluble intercellular adhesion molecule-1, independent of age, gender, and medications. We extended race-stratified models to test three potential mechanisms for the observed associations. Significant interactions between ELA and race were observed for all five biomarkers. Models stratified by race revealed that ELA predicted higher levels of log interleukin-6, fibrinogen, endothelial leukocyte adhesion molecule-1, and soluble intercellular adhesion molecule-1 among African Americans (p < .05), but not among whites. Some, but not all, of these associations were attenuated after adjustment for health behaviors and body mass index, adult stressors, and depressive symptoms. ELA was predictive of high concentrations of inflammatory markers at midlife for African Americans, but not whites. This pattern may be explained by an accelerated course of age-related disease development for African Americans.

Activation of cellular immune response in acute pancreatitis.

PubMed Central

Mora, A; Pérez-Mateo, M; Viedma, J A; Carballo, F; Sánchez-Payá, J; Liras, G

1997-01-01

BACKGROUND: Inflammatory mediators have recently been implicated as potential markers of severity in acute pancreatitis. AIMS: To determine the value of neopterin and polymorphonuclear (PMN) elastase as markers of activation of cellular immunity and as early predictors of disease severity. PATIENTS: Fifty two non-consecutive patients classified according to their clinical outcome into mild (n = 26) and severe pancreatitis (n = 26). METHODS: Neopterin in serum and the PMN elastase/A1PI complex in plasma were measured during the first three days of hospital stay. RESULTS: Within three days after the onset of acute pancreatitis, PMN elastase was significantly higher in the severe pancreatitis group. Patients with severe disease also showed significantly higher values of neopterin on days 1 and 2 but not on day 3 compared with patients with mild disease. There was a significant correlation between PMN elastase and neopterin values on days 1 and 2. PMN elastase on day 1 predicted disease severity with a sensitivity of 76.7% and a specificity of 91.6%. Neopterin did not surpass PMN elastase in the probability of predicting disease severity. CONCLUSIONS: These data show that activation of cellular immunity is implicated in the pathogenesis of acute pancreatitis and may be a main contributory factor to disease severity. Neopterin was not superior to PMN elastase in the prediction of severity. PMID:9245935

Identification and Validation of SNP Markers Linked to Dwarf Traits Using SLAF-Seq Technology in Lagerstroemia

PubMed Central

Ju, Yiqian; Jiao, Yao; Feng, Lu; Pan, Huitang; Cheng, Tangren; Zhang, Qixiang

2016-01-01

The genetic control of plant architecture is a promising approach to breed desirable cultivars, particularly in ornamental flowers. In this study, the F1 population (142 seedlings) derived from Lagerstroemia fauriei (non-dwarf) × L. indica ‘Pocomoke’ (dwarf) was phenotyped for six traits (plant height (PH), internode length (IL), internode number, primary lateral branch height (PLBH), secondary lateral branch height and primary branch number), and the IL and PLBH traits were positively correlated with the PH trait and considered representative indexes of PH. Fifty non-dwarf and dwarf seedlings were pooled and subjected to a specific-locus amplified fragment sequencing (SLAF-seq) method, which screened 1221 polymorphic markers. A total of 3 markers segregating between bulks were validated in the F1 population, with the M16337 and M38412 markers highly correlated with the IL trait and the M25207 marker highly correlated with the PLBH trait. These markers provide a predictability of approximately 80% using a single marker (M25207) and a predictability of 90% using marker combinations (M16337 + M25207) in the F1 population, which revealed that the IL and the PLBH traits, especially the PLBH, were the decisive elements for PH in terms of molecular regulation. Further validation was performed in the BC1 population and a set of 28 Lagerstroemia stocks using allele-specific PCR (AS-PCR) technology, and the results showed the stability and reliability of the SNP markers and the co-determination of PH by multiple genes. Our findings provide an important theoretical and practical basis for the early prediction and indirect selection of PH using the IL and the PLBH, and the detected SNPs may be useful for marker-assisted selection (MAS) in crape myrtle. PMID:27404662

Varying strength of cognitive markers and biomarkers to predict conversion and cognitive decline in an early-stage-enriched mild cognitive impairment sample.

PubMed

Egli, Simone C; Hirni, Daniela I; Taylor, Kirsten I; Berres, Manfred; Regeniter, Axel; Gass, Achim; Monsch, Andreas U; Sollberger, Marc

2015-01-01

Several cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. However, predictors might be more or less powerful depending on the characteristics of the MCI sample. To investigate which cognitive markers and biomarkers predict conversion to AD dementia and course of cognitive functioning in a MCI sample with a high proportion of early-stage MCI patients. Variables known to predict progression in MCI patients and hypothesized to predict progression in early-stage MCI patients were selected. Cognitive (long-delay free recall, regional primacy score), imaging (hippocampal and entorhinal cortex volumes, fornix fractional anisotropy), and CSF (Aβ1-42/t-tau, Aβ1-42) variables from 36 MCI patients were analyzed with Cox regression and mixed-effect models to determine their individual and combined abilities to predict time to conversion to AD dementia and course of global cognitive functioning, respectively. Those variables hypothesized to predict the course of early-stage MCI patients were most predictive for MCI progression. Specifically, regional primacy score (a measure of word-list position learning) most consistently predicted conversion to AD dementia and course of cognitive functioning. Both the prediction of conversion and course of cognitive functioning were maximized by including CSF Aβ1-42 and fornix integrity biomarkers, respectively, indicating the complementary information carried by cognitive variables and biomarkers. Predictors of MCI progression need to be interpreted in light of the characteristics of the respective MCI sample. Future studies should aim to compare predictive strengths of markers between early-stage and late-stage MCI patients.

Immunohistochemical Expression Of Ezrin In Oral Potentially Malignant Disorders-A Descriptive Study.

PubMed

Mohanraj, Raghini; Ramani, Pratibha; Premkumar, Priya; Natesan, Anuja; Sherlin, Herald J; Sukumaran, Gheena

2017-11-01

Ezrin, also known as cytovillin, is a member of the ERM family of protein. Ezrin cross-links actin filament with the plasma membrane. They are involved in the formation of microvilli, cell-cell adhesion, maintenance of cell shape, cell motility, and membrane trafficking. Recent analysis reveals their involvement in signaling pathways. Ezrin is highly expressed in several types of human cancers, and correlation between its immunoreactivity and histopathological data as well as the patient outcome has previously been studied. The objective of the study was to analyze the immunohistochemical expression pattern of ezrin in oral potentially malignant disorders (OPMDs), namely, oral submucous fibrosis (OSMF) with different grades and clinically leucoplakia (hyperkeratosis with various degree of dysplasia) and its use as a predictive marker for malignant transformation. Sample size n = 43, histopathologically confirmed cases of OPMDs (13 cases of OSMF with different grades and 30 cases of clinically leukoplakia) were retrieved from the Department of Oral and Maxillofacial Pathology. Immunohistochemistry was done using anti-ezrin antibody, and the expression was graded in terms of proportion and intensity. There was a significant expression of ezrin in OPMDs, and its cytoplasmic shift can be used as a predictive marker for malignant transformation. The findings of the current study revealed that the expression of ezrin in OPMDs may be related to the progression of the disease.

MicroRNA, Proteins, and Metabolites as Novel Biomarkers for Prediabetes, Diabetes, and Related Complications

PubMed Central

Vaishya, Suniti; Sarwade, Rucha D.; Seshadri, Vasudevan

2018-01-01

Type 2 diabetes mellitus (T2DM) is no more a lifestyle disease of developed countries. It has emerged as a major health problem worldwide including developing countries. However, how diabetes could be detected at an early stage (prediabetes) to prevent the progression of disease is still unclear. Currently used biomarkers like glycated hemoglobin and assessment of blood glucose level have their own limitations. These classical markers can be detected when the disease is already established. Prognosis of disease at early stages and prediction of population at a higher risk require identification of specific markers that are sensitive enough to be detected at early stages of disease. Biomarkers which could predict the risk of disease in people will be useful for developing preventive/proactive therapies to those individuals who are at a higher risk of developing the disease. Recent studies suggested that the expression of biomolecules including microRNAs, proteins, and metabolites specifically change during the progression of T2DM and related complications, suggestive of disease pathology. Owing to their omnipresence in body fluids and their association with onset, progression, and pathogenesis of T2DM, these biomolecules can be potential biomarker for prognosis, diagnosis, and management of disease. In this article, we summarize biomolecules that could be potential biomarkers and their signature changes associated with T2DM and related complications during disease pathogenesis. PMID:29740397

Only White Matter Hyperintensities Predicts Post-Stroke Cognitive Performances Among Cerebral Small Vessel Disease Markers: Results from the TABASCO Study.

PubMed

Molad, Jeremy; Kliper, Efrat; Korczyn, Amos D; Ben Assayag, Einor; Ben Bashat, Dafna; Shenhar-Tsarfaty, Shani; Aizenstein, Orna; Shopin, Ludmila; Bornstein, Natan M; Auriel, Eitan

2017-01-01

White matter hyperintensities (WMH) were shown to predict cognitive decline following stroke or transient ischemic attack (TIA). However, WMH are only one among other radiological markers of cerebral small vessel disease (SVD). The aim of this study was to determine whether adding other SVD markers to WMH improves prediction of post-stroke cognitive performances. Consecutive first-ever stroke or TIA patients (n = 266) from the Tel Aviv Acute Brain Stroke Cohort (TABASCO) study were enrolled. MRI scans were performed within seven days of stroke onset. We evaluated the relationship between cognitive performances one year following stroke, and previously suggested total SVD burden score including WMH, lacunes, cerebral microbleeds (CMB), and perivascular spaces (PVS). Significant negative associations were found between WMH and cognition (p < 0.05). Adding other SVD markers (lacunes, CMB, PVS) to WMH did not improve predication of post-stroke cognitive performances. Negative correlations between SVD burden score and cognitive scores were observed for global cognitive, memory, and visual spatial scores (all p < 0.05). However, following an adjustment for confounders, no associations remained significant. WMH score was associated with poor post-stroke cognitive performance. Adding other SVD markers or SVD burden score, however, did not improve prediction.

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

PubMed Central

Roy, Janine; Aust, Daniela; Knösel, Thomas; Rümmele, Petra; Jahnke, Beatrix; Hentrich, Vera; Rückert, Felix; Niedergethmann, Marco; Weichert, Wilko; Bahra, Marcus; Schlitt, Hans J.; Settmacher, Utz; Friess, Helmut; Büchler, Markus; Saeger, Hans-Detlev; Schroeder, Michael; Pilarsky, Christian; Grützmann, Robert

2012-01-01

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice. PMID:22615549

Derivation of genetic biomarkers for cancer risk stratification in Barrett's oesophagus: a prospective cohort study

PubMed Central

Timmer, Margriet R.; Martinez, Pierre; Lau, Chiu T.; Westra, Wytske M.; Calpe, Silvia; Rygiel, Agnieszka M.; Rosmolen, Wilda D.; Meijer, Sybren L.; ten Kate, Fiebo J.W.; Dijkgraaf, Marcel G.W.; Mallant-Hent, Rosalie C.; Naber, Anton H.J.; van Oijen, Arnoud H.A.M.; Baak, Lubbertus C.; Scholten, Pieter; Böhmer, Clarisse J.M.; Fockens, Paul; Maley, Carlo C.; Graham, Trevor A.; Bergman, Jacques J.G.H.M.; Krishnadath, Kausilia K.

2016-01-01

Objective The risk of developing adenocarcinoma in non-dysplastic Barrett's oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers. Methods In a prospective cohort of patients with non-dysplastic Barrett's oesophagus, we evaluated six molecular markers: p16, p53, Her-2/neu, 20q, MYC, and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional-hazards models, receiver-operating-characteristic curves and a leave-one-out analysis. Results A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett's length, and the markers, p16 loss, MYC gain, and aneusomy, were significantly associated with progression on univariate analysis. We defined an ‘Abnormal Marker Count’ that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett's length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI, 2.6 to 29.8) increased hazard ratio compared with the low-risk group, with an area under the curve of 0.76 (95% CI, 0.66 to 0.86). Conclusion A prediction model based on age, Barrett's length, and the markers p16, MYC, and aneusomy determines progression risk in non-dysplastic Barrett's oesophagus. PMID:26104750

Prediction of the contact sensitizing potential of chemicals using analysis of gene expression changes in human THP-1 monocytes.

PubMed

Arkusz, Joanna; Stępnik, Maciej; Sobala, Wojciech; Dastych, Jarosław

2010-11-10

The aim of this study was to find differentially regulated genes in THP-1 monocytic cells exposed to sensitizers and nonsensitizers and to investigate if such genes could be reliable markers for an in vitro predictive method for the identification of skin sensitizing chemicals. Changes in expression of 35 genes in the THP-1 cell line following treatment with chemicals of different sensitizing potential (from nonsensitizers to extreme sensitizers) were assessed using real-time PCR. Verification of 13 candidate genes by testing a large number of chemicals (an additional 22 sensitizers and 8 nonsensitizers) revealed that prediction of contact sensitization potential was possible based on evaluation of changes in three genes: IL8, HMOX1 and PAIMP1. In total, changes in expression of these genes allowed correct detection of sensitization potential of 21 out of 27 (78%) test sensitizers. The gene expression levels inside potency groups varied and did not allow estimation of sensitization potency of test chemicals. Results of this study indicate that evaluation of changes in expression of proposed biomarkers in THP-1 cells could be a valuable model for preliminary screening of chemicals to discriminate an appreciable majority of sensitizers from nonsensitizers. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Predictive markers of honey bee colony collapse.

PubMed

Dainat, Benjamin; Evans, Jay D; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

2012-01-01

Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies.

Predictive Markers of Honey Bee Colony Collapse

PubMed Central

Dainat, Benjamin; Evans, Jay D.; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

2012-01-01

Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies. PMID:22384162

Identification of ganglioside GM2 activator playing a role in cancer cell migration through proteomic analysis of breast cancer secretomes.

PubMed

Shin, Jihye; Kim, Gamin; Lee, Jong Won; Lee, Ji Eun; Kim, Yoo Seok; Yu, Jong-Han; Lee, Seung-Taek; Ahn, Sei Hyun; Kim, Hoguen; Lee, Cheolju

2016-06-01

Cancer cell secretomes are considered a potential source for the discovery of cancer markers. In this study, the secretomes of four breast cancer (BC) cell lines (Hs578T, MCF-7, MDA-MB-231, and SK-BR-3) were profiled with liquid chromatography-tandem mass spectrometry analysis. A total of 1410 proteins were identified with less than 1% false discovery rate, of which approximately 55% (796 proteins) were predicted to be secreted from cells. To find BC-specific proteins among the secreted proteins, data of immunohistochemical staining compiled in the Human Protein Atlas were investigated by comparing the data of BC tissues with those of normal tissues. By applying various criteria, including higher expression level in BC tissues, higher predicted potential of secretion, and sufficient number of tandem mass spectra, 12 biomarker candidate proteins including ganglioside GM2 activator (GM2A) were selected for confirmation. Western blot analysis and ELISA for plasma samples of healthy controls and BC patients revealed elevation of GM2A in BC patients, especially those who were estrogen receptor-negative. Additionally, siRNA-mediated knockdown of GM2A in BC cells decreased migration in vitro, whereas the overexpression of GM2A led to an increase in cell migration. Although GM2A as a diagnostic and prognostic marker in BC should be carefully verified further, this study has established the potential role of GM2A in BC progression. © 2016 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Air pollution and blood lipid markers levels: Estimating short and long-term effects on elderly hypertension inpatients complicated with or without type 2 diabetes.

PubMed

Xiao, Sanhua; Liu, Ranran; Wei, Youxiu; Feng, Lin; Lv, Xuemin; Tang, Fei

2016-08-01

With the development of society and the economy, many Chinese cities are shrouded in pollution haze for much of the year. Scientific studies have identified various adverse effects of air pollutants on human beings. However, the relationships between air pollution and blood lipid levels are still unclear. The objective of this study is to explore the short and long-term effects of air pollution on eight blood lipid markers among elderly hypertension inpatients complicated with or without type 2 diabetes (T2D). Blood lipid markers which met the pre-established inclusion criteria were exported from the medical record system. Air pollution data were acquired from the official environmental protection website. Associations between the air quality index and the blood lipid indexes were analyzed by one-way ANOVA and further Bonferroni correction. In an exposure time of 7 days or longer, blood lipid markers were somewhat affected by poor air quality. However, the results could not predict whether atherosclerosis would be promoted or inhibited by poorer air condition. Changes of blood lipid markers of hypertension inpatients with or without T2D were not completely the same, but no blood lipid markers had an opposite trend between the two populations. The air quality index was associated with changes to blood lipid markers to some extent in a population of hypertension inpatients with or without T2D. Further studies are needed to investigate the potential mechanism by which air pollutants induce blood lipids changes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genomic selection of agronomic traits in hybrid rice using an NCII population.

PubMed

Xu, Yang; Wang, Xin; Ding, Xiaowen; Zheng, Xingfei; Yang, Zefeng; Xu, Chenwu; Hu, Zhongli

2018-05-10

Hybrid breeding is an effective tool to improve yield in rice, while parental selection remains the key and difficult issue. Genomic selection (GS) provides opportunities to predict the performance of hybrids before phenotypes are measured. However, the application of GS is influenced by several genetic and statistical factors. Here, we used a rice North Carolina II (NC II) population constructed by crossing 115 rice varieties with five male sterile lines as a model to evaluate effects of statistical methods, heritability, marker density and training population size on prediction for hybrid performance. From the comparison of six GS methods, we found that predictabilities for different methods are significantly different, with genomic best linear unbiased prediction (GBLUP) and least absolute shrinkage and selection operation (LASSO) being the best, support vector machine (SVM) and partial least square (PLS) being the worst. The marker density has lower influence on predicting rice hybrid performance compared with the size of training population. Additionally, we used the 575 (115 × 5) hybrid rice as a training population to predict eight agronomic traits of all hybrids derived from 120 (115 + 5) rice varieties each mating with 3023 rice accessions from the 3000 rice genomes project (3 K RGP). Of the 362,760 potential hybrids, selection of the top 100 predicted hybrids would lead to 35.5%, 23.25%, 30.21%, 42.87%, 61.80%, 75.83%, 19.24% and 36.12% increase in grain yield per plant, thousand-grain weight, panicle number per plant, plant height, secondary branch number, grain number per panicle, panicle length and primary branch number, respectively. This study evaluated the factors affecting predictabilities for hybrid prediction and demonstrated the implementation of GS to predict hybrid performance of rice. Our results suggest that GS could enable the rapid selection of superior hybrids, thus increasing the efficiency of rice hybrid breeding.

Predictive factors in the evaluation of treatment response to neoadjuvant chemoradiotherapy in patients with advanced esophageal squamous cell cancer

PubMed Central

Wong, Claudia

2017-01-01

Neoadjuvant therapy before esophagectomy is evidence-based, and is a standard-of-care for locally advanced and operable esophageal cancer. However response to such treatment varies in individual patients, from no clinical response to pathological complete response. It has been consistently shown that a good pathological responses is of prognostic value, but perhaps in the expense of those who do not. It is important to identify suitable predictive factors for response, so that patients are not exposed to potentially harmful chemotherapy and/or radiotherapy without benefits. Alternative management strategies can be devised. Various clinical, radiological, serological and potential molecular markers have been studied. None has been shown to be sufficiently reliable to be used in daily practice. Certainly more understanding of the molecular basis for response to chemotherapy/radiotherapy is needed, so that patient treatment can be tailored and individualized. PMID:28815073

Recent advances in development of marker-free transgenic plants: regulation and biosafety concern.

PubMed

Tuteja, Narendra; Verma, Shiv; Sahoo, Ranjan Kumar; Raveendar, Sebastian; Reddy, I N Bheema Lingeshwara

2012-03-01

During the efficient genetic transformation of plants with the gene of interest, some selectable marker genes are also used in order to identify the transgenic plant cells or tissues. Usually, antibiotic- or herbicide-selective agents and their corresponding resistance genes are used to introduce economically valuable genes into crop plants. From the biosafety authority and consumer viewpoints, the presence of selectable marker genes in released transgenic crops may be transferred to weeds or pathogenic microorganisms in the gastrointestinal tract or soil, making them resistant to treatment with herbicides or antibiotics, respectively. Sexual crossing also raises the problem of transgene expression because redundancy of transgenes in the genome may trigger homology-dependent gene silencing. The future potential of transgenic technologies for crop improvement depends greatly on our abilities to engineer stable expression of multiple transgenic traits in a predictable fashion and to prevent the transfer of undesirable transgenic material to non-transgenic crops and related species. Therefore, it is now essential to develop an efficient marker-free transgenic system. These considerations underline the development of various approaches designed to facilitate timely elimination of transgenes when their function is no longer needed. Due to the limiting number of available selectable marker genes, in future the stacking of transgenes will be increasingly desirable. The production of marker-free transgenic plants is now a critical requisite for their commercial deployment and also for engineering multiple and complex trait. Here we describe the current technologies to eliminate the selectable marker genes (SMG) in order to develop marker-free transgenic plants and also discuss the regulation and biosafety concern of genetically modified (GM) crops.

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review.

PubMed

Weymann, Alexander; Sabashnikov, Anton; Ali-Hasan-Al-Saegh, Sadeq; Popov, Aron-Frederik; Jalil Mirhosseini, Seyed; Baker, William L; Lotfaliani, Mohammadreza; Liu, Tong; Dehghan, Hamidreza; Yavuz, Senol; de Oliveira Sá, Michel Pompeu Barros; Jang, Jae-Sik; Zeriouh, Mohamed; Meng, Lei; D'Ascenzo, Fabrizio; Deshmukh, Abhishek J; Biondi-Zoccai, Guiseppe; Dohmen, Pascal M; Calkins, Hugh; Cardiac Surgery And Cardiology-Group Imcsc-Group, Integrated Meta-Analysis Of Cardiac

2017-03-31

BACKGROUND The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. MATERIAL AND METHODS We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. RESULTS A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD) =197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1-2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004));  fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and  endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. CONCLUSIONS The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients.

Development of a Gene-Centered SSR Atlas as a Resource for Papaya (Carica papaya) Marker-Assisted Selection and Population Genetic Studies

PubMed Central

Vidal, Newton Medeiros; Grazziotin, Ana Laura; Ramos, Helaine Christine Cancela; Pereira, Messias Gonzaga; Venancio, Thiago Motta

2014-01-01

Carica papaya (papaya) is an economically important tropical fruit. Molecular marker-assisted selection is an inexpensive and reliable tool that has been widely used to improve fruit quality traits and resistance against diseases. In the present study we report the development and validation of an atlas of papaya simple sequence repeat (SSR) markers. We integrated gene predictions and functional annotations to provide a gene-centered perspective for marker-assisted selection studies. Our atlas comprises 160,318 SSRs, from which 21,231 were located in genic regions (i.e. inside exons, exon-intron junctions or introns). A total of 116,453 (72.6%) of all identified repeats were successfully mapped to one of the nine papaya linkage groups. Primer pairs were designed for markers from 9,594 genes (34.5% of the papaya gene complement). Using papaya-tomato orthology assessments, we assembled a list of 300 genes (comprising 785 SSRs) potentially involved in fruit ripening. We validated our atlas by screening 73 SSR markers (including 25 fruit ripening genes), achieving 100% amplification rate and uncovering 26% polymorphism rate between the parental genotypes (Sekati and JS12). The SSR atlas presented here is the first comprehensive gene-centered collection of annotated and genome positioned papaya SSRs. These features combined with thousands of high-quality primer pairs make the atlas an important resource for the papaya research community. PMID:25393538

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review

PubMed Central

Weymann, Alexander; Sabashnikov, Anton; Ali-Hasan-Al-Saegh, Sadeq; Popov, Aron-Frederik; Mirhosseini, Seyed Jalil; Baker, William L.; Lotfaliani, Mohammadreza; Liu, Tong; Dehghan, Hamidreza; Yavuz, Senol; de Oliveira Sá, Michel Pompeu Barros; Jang, Jae-Sik; Zeriouh, Mohamed; Meng, Lei; D’Ascenzo, Fabrizio; Deshmukh, Abhishek J.; Biondi-Zoccai, Giuseppe; Dohmen, Pascal M.; Calkins, Hugh

2017-01-01

Background The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. Material/Methods We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. Results A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD)=197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1–2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004)); fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. Conclusions The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients. PMID:28360407

Ancestry prediction in Singapore population samples using the Illumina ForenSeq kit.

PubMed

Ramani, Anantharaman; Wong, Yongxun; Tan, Si Zhen; Shue, Bing Hong; Syn, Christopher

2017-11-01

The ability to predict bio-geographic ancestry can be valuable to generate investigative leads towards solving crimes. Ancestry informative marker (AIM) sets include large numbers of SNPs to predict an ancestral population. Massively parallel sequencing has enabled forensic laboratories to genotype a large number of such markers in a single assay. Illumina's ForenSeq DNA Signature Kit includes the ancestry informative SNPs reported by Kidd et al. In this study, the ancestry prediction capabilities of the ForenSeq kit through sequencing on the MiSeq FGx were evaluated in 1030 unrelated Singapore population samples of Chinese, Malay and Indian origin. A total of 59 ancestry SNPs and phenotypic SNPs with AIM properties were selected. The bio-geographic ancestry of the 1030 samples, as predicted by Illumina's ForenSeq Universal Analysis Software (UAS), was determined. 712 of the genotyped samples were used as a training sample set for the generation of an ancestry prediction model using STRUCTURE and Snipper. The performance of the prediction model was tested by both methods with the remaining 318 samples. Ancestry prediction in UAS was able to correctly classify the Singapore Chinese as part of the East Asian cluster, while Indians clustered with Ad-mixed Americans and Malays clustered in-between these two reference populations. Principal component analyses showed that the 59 SNPs were only able to account for 26% of the variation between the Singapore sub-populations. Their discriminatory potential was also found to be lower (G ST =0.085) than that reported in ALFRED (F ST =0.357). The Snipper algorithm was able to correctly predict bio-geographic ancestry in 91% of Chinese and Indian, and 88% of Malay individuals, while the success rates for the STRUCTURE algorithm were 94% in Chinese, 80% in Malay, and 91% in Indian individuals. Both these algorithms were able to provide admixture proportions when present. Ancestry prediction accuracy (in terms of likelihood ratio) was generally high in the absence of admixture. Misclassification occurred in admixed individuals, who were likely offspring of inter-ethnic marriages, and hence whose self-reported bio-geographic ancestries were dependent on that of their fathers, and in individuals of minority sub-populations with inter-ethnic beliefs. The ancestry prediction capabilities of the 59 SNPs on the ForenSeq kit were reasonably effective in differentiating the Singapore Chinese, Malay and Indian sub-populations, and will be of use for investigative purposes. However, there is potential for more accurate prediction through the evaluation of other AIM sets. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of acid-detergent lignin, alkaline-peroxide lignin, and acid-detergent insoluble ash as internal markers for predicting fecal output and digestibility by cattle offered bermudagrass hays of varying nutrient composition.

PubMed

Kanani, Juvenal; Philipp, Dirk; Coffey, Kenneth P; Kegley, Elizabeth B; West, Charles P; Gadberry, Shane; Jennings, John; Young, Ashley N; Rhein, Robert T

2014-01-13

The potential for acid-detergent insoluble ash (ADIA), alkaline-peroxide lignin (APL), and acid-detergent lignin (ADL) to predict fecal output (FO) and dry matter digestibility (DMD) by cattle offered bermudagrass [Cynodon dactylon (L.) Pers.] hays of different qualities was evaluated. Eight ruminally cannulated cows (594 ± 35.5 kg) were allocated randomly to 4 hay diets: low (L), medium low (ML), medium high (MH), and high (H) crude protein (CP) concentration (79, 111, 131, and 164 g CP/kg on a DM basis, respectively). Diets were offered in 3 periods with 2 diet replicates per period and were rotated across cows between periods. Cows were individually fed 20 g DM/kg of body weight in equal feedings at 08:00 and 16:00 h for a 10-d adaptation followed by a 5-d total fecal collection. Actual DM intake (DMI), DMD, and FO were determined based on hay offered, ort, and feces excreted. These components were then analyzed for ADL, APL, and ADIA concentration to determine marker recovery and marker-based estimates of FO and DMD. Forage DMI was affected by diet (P = 0.02), and DMI from MH and H was greater (P < 0.05) than from L. Apparent DMD tended (P = 0.08) to differ among diets while FO (P = 0.20) was not affected by diet treatments. Average ADL recovery (1.16) was greater (P < 0.05) than that of ADIA (1.03) and APL (1.06), but ADIA and APL did not differ (P = 0.42). Estimates of FO and DMD derived using APL and ADIA were not different (P ≥ 0.05) from total fecal collection while those using ADL differed (P < 0.05). There was no diet by marker interaction (P ≥ 0.22) for either FO or DMD. Acid-detergent insoluble ash and APL accurately predicted FO and DMD of cattle fed bermudagrass hay of varying nutrient composition. These internal markers may facilitate studies involving large numbers of animals and forages. Results from such studies may be used to develop improved equations to predict energy values of forages based on the relationship of dietary components to digestibility across a wide range of forages.

Bleomycin-Induced Pulmonary Changes on Restaging Computed Tomography Scans in Two Thirds of Testicular Cancer Patients Show No Correlation With Fibrosis Markers.

PubMed

den Hollander, Martha W; Westerink, Nico-Derk L; Lubberts, Sjoukje; Bongaerts, Alfons H H; Wolf, Rienhart F E; Altena, Renska; Nuver, Janine; Oosting, Sjoukje F; de Vries, Elisabeth G E; Walenkamp, Anna M E; Meijer, Coby; Gietema, Jourik A

2016-08-01

In metastatic testicular cancer patients treated with bleomycin, etoposide, and cisplatin (BEP) chemotherapy, bleomycin-induced pneumonitis is a well-known and potentially fatal side effect. We sought to determine the prevalence of lesions as signs of bleomycin-induced pulmonary changes on restaging computed tomography (CT) scans after treatment and to ascertain whether fibrosis markers were predictive of these changes. This prospective nonrandomized cohort study included metastatic testicular cancer patients, 18-50 years of age, treated with BEP chemotherapy. Restaging CT scans were examined for lesions as signs of bleomycin-induced pulmonary changes by two independent radiologists and graded as minor, moderate, or severe. Plasma samples were collected before, during, and after treatment and were quantified for transforming growth factor-β1 (TGF-β1), growth differentiation factor-15 (GDF-15), and high-sensitivity C-reactive protein (hs-CRP). In total, 66 patients were included: forty-five (68%) showed signs of bleomycin-induced pulmonary changes on the restaging CT scan, 37 of which were classified as minor and 8 as moderate. No differences in TGF-β1, GDF-15, or hs-CRP plasma levels were found between these groups. Bleomycin-induced pulmonary changes are common on restaging CT scans after BEP chemotherapy for metastatic testicular cancer. Changes in TGF-β1, GDF-15, and hs-CRP plasma levels do not differ between patients with and without radiological lesions as signs of bleomycin-induced pulmonary changes and are therefore not helpful as predictive biomarkers. Bleomycin-induced pneumonitis (BIP) is a well-known and potentially fatal side effect in metastatic testicular cancer patients treated with bleomycin, etoposide, and cisplatin chemotherapy. Currently, the decision to discontinue bleomycin administration is made during treatment and is based on clinical signs. An upfront or early marker or biomarker that identifies patients likely to develop BIP would be preferable. This study found that bleomycin-induced pulmonary changes are common on restaging computed tomography scans and mostly resolve. No correlation was seen between these changes and fibrosis or inflammation markers (transforming growth factor-β1, growth differentiation factor-15, and high-sensitivity C-reactive protein). ©AlphaMed Press.

MicroRNAs in prostate cancer: Functional role as biomarkers.

PubMed

Kanwal, Rajnee; Plaga, Alexis R; Liu, Xiaoqi; Shukla, Girish C; Gupta, Sanjay

2017-10-28

MicroRNAs (miRNAs) are small endogenous non-coding molecules that alters gene expression through post-transcriptional regulation of messenger RNA. Compelling evidence suggest the role of miRNA in cancer biology having potential as diagnostic, prognostic and predictive biomarkers. This review summarizes the current knowledge on miRNA deregulated in prostate cancer and their role as oncogene, tumor suppressor and metastasis regulators. The emerging information elucidating the biological function of miRNA is promising and may lead to their potential usefulness as diagnostic/prognostic markers and development as effective therapeutic tools for management of prostate cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Applying a CAD-generated imaging marker to assess short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Zarafshani, Ali; Heidari, Morteza; Wang, Yunzhi; Aghaei, Faranak; Zheng, Bin

2018-02-01

Although whether using computer-aided detection (CAD) helps improve radiologists' performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all "prior" negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65+/-0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (p<0.01). Thus, the study showed that CAD-generated false-positives might provide a new quantitative imaging marker to help assess short-term breast cancer risk.

Predictive value of [-2]propsa (p2psa) and its derivatives for the prostate cancer detection in the 2.0 to 10.0ng/mL PSA range.

PubMed

Vukovic, I; Djordjevic, D; Bojanic, N; Babic, U; Soldatovic, I

2017-01-01

To assess predictive value of new tumor markers, precursor of prostate specific antigen (p2PSA) and its derivates-%p2PSA and prostate health index (PHI) in detection of patients with indolent and aggressive prostate cancer (PC) in a subcohort of man whose total PSA ranged from 2 to 10ng/mL. This cross-sectional study included 129 consecutive male patients aged over 50 years, with no previous history of PC and with normal digital rectal examination findings, but with serum PSA in interval between 2 and 10ng/mL. All patients underwent standard transrectal ultrasonography guided prostate biopsy for the first time. For all patients, serum PSA, free PSA (fPSA) and p2PSA were measured and PHI and %p2PSA were calculated. PHI and %p2PSA levels were significanlty higher in patients with PC compared to those without this malignancy. The same findings have been observed in group of patients with Gleason score ≥7 compared to those with Gleason score <7. ROC analysis reveled the highest area under the curve with these two markers. Multivariate logistic regression showed significant improvement in PC detection and its agressive form (assumed as Gleason score ≥7). New markers, derivates of p2PSA (especially %p2PSA and PHI), represente potentially very important clinical tool for predicting presence of PC, and even more important, to discriminate patients with Gleason score <7 from those with Gleason score ≥7 with total PSA in range from 2 to 10ng/mL. Copyright® by the International Brazilian Journal of Urology.

Exhaled Breath Temperature as a Novel Marker of Future Development of COPD: Results of a Follow-Up Study in Smokers.

PubMed

Labor, Marina; Vrbica, Žarko; Gudelj, Ivan; Labor, Slavica; Jurić, Iva; Plavec, Davor

2016-12-01

Although only less than one-third of smokers develop COPD, early marker(s) of COPD development are lacking. The aim of this research was to assess the ability of an average equilibrium exhaled breath temperature (EBT) in identifying susceptibility to cigarette smoke so as to predict COPD development in smokers at risk. The study was a part of a multicenter prospective cohort study in current smokers (N = 140, both sexes, 40-65 years, ≥20 pack-years) with no prior diagnosis of COPD. Diagnostic workup includes history, physical, quality of life, hematology and highly sensitive CRP, EBT before and after smoking a cigarette, lung function with bronchodilator test, and 6-minute walk test. Patients without a diagnosis of COPD and in GOLD 1 stage at initial assessment were reassessed after 2 years. COPD was additionally diagnosed based on lower level of normal (LLN) lung function criteria. Utility of EBT for disease progression was analyzed using receiver operator curve (ROC) and logistic regression analyses. Change in EBT after smoking a cigarette at initial visit (ΔEBT) was significantly predictive for disease progression (newly diagnosed COPD; newly diagnosed COPD + severity progression) after 2 years (p < 0.05 for both). ΔEBT had an AUC of 0.859 (p = 0.011) with sensitivity of 66.7% and specificity of 98.1% for newly diagnosed COPD using LLN criteria. We conclude that EBT shows potential for predicting the future development of COPD in current smokers. This was best seen using LLN to diagnose COPD, adding further evidence to question the use of GOLD criteria for diagnosing COPD.

Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

PubMed Central

2010-01-01

Background The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating this and other important prior information into modelling. However a full Bayesian analysis is often not feasible due to the large computational time involved. Results This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. Conclusions emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time. PMID:20969788

Profiling Coping Strategies in Male and Female Rats: Potential neurobehavioral markers of increased resilience to depressive symptoms

PubMed Central

Kent, Molly; Bardi, Massimo; Hazelgrove, Ashley; Sewell, Kaitlyn; Kirk, Emily; Thompson, Brooke; Trexler, Kristen; Terhune-Cotter, Brennan; Lambert, Kelly

2018-01-01

Coping strategies have been associated with differential stress responsivity, perhaps providing a valuable neurobiological marker for susceptibility to the emergence of depressogenic symptoms or vulnerability to other anxiety-related disorders. Rats profiled with a flexible coping phenotype, for example, exhibit increased neurobiological markers of emotional regulation compared to active and passive copers (Bardi et al., 2012; Lambert et al., 2014). In the current study, responses of male and female rats to prediction errors in a spatial foraging task (dry land maze; DLM) were examined after animals were exposed to chronic unpredictable stress (CUS). Brains were processed following the DLM training/assessment for fos-activation patterns and several measures of neuroplasticity in relevant areas. Behavioral responses observed during both the CUS and DLM phases of testing suggested that males and females employ different means of gathering information such as increased ambulatory exploration in males and rear responses in females. Fecal samples collected during baseline and following CUS swim exposure revealed higher corticosterone (CORT) in active copers, whereas flexible copers had higher dehydroepiandrosterone (DHEA) and DHEA/CORT ratios, both indications of enhanced emotional regulation. Focusing on the neural analysis, flexible copers exhibited fewer fos-immunoreactive cells in the basolateral amygdala and a trend toward lower activation in the insula while encountering the prediction error associated with the DLM probe trial. Coping profiles also differentially influenced markers of neuroplasticity; specifically, flexible copers exhibited higher levels nestin-immunoreactivity (ir). Further, less hippocampal glucocorticoid receptor-ir was observed in the flexible copers than the active and passive copers. In sum, flexible coping rats exhibited evidence of emotional resilience as indicated by several neurobiological measures; however, despite increased rates of depression and related symptoms reported in human females, sex effects weren’t as pervasive as coping strategy profiles in the analysis of neurobiological markers employed in the current study. PMID:28755980

Exploring a new quantitative image marker to assess benefit of chemotherapy to ovarian cancer patients

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Patil, Omkar; Aghaei, Faranak; Wang, Yunzhi; Zheng, Bin

2017-03-01

Accurately assessing the potential benefit of chemotherapy to cancer patients is an important prerequisite to developing precision medicine in cancer treatment. The previous study has shown that total psoas area (TPA) measured on preoperative cross-section CT image might be a good image marker to predict long-term outcome of pancreatic cancer patients after surgery. However, accurate and automated segmentation of TPA from the CT image is difficult due to the fuzzy boundary or connection of TPA to other muscle areas. In this study, we developed a new interactive computer-aided detection (ICAD) scheme aiming to segment TPA from the abdominal CT images more accurately and assess the feasibility of using this new quantitative image marker to predict the benefit of ovarian cancer patients receiving Bevacizumab-based chemotherapy. ICAD scheme was applied to identify a CT image slice of interest, which is located at the level of L3 (vertebral spines). The cross-sections of the right and left TPA are segmented using a set of adaptively adjusted boundary conditions. TPA is then quantitatively measured. In addition, recent studies have investigated that muscle radiation attenuation which reflects fat deposition in the tissue might be a good image feature for predicting the survival rate of cancer patients. The scheme and TPA measurement task were applied to a large national clinical trial database involving 1,247 ovarian cancer patients. By comparing with manual segmentation results, we found that ICAD scheme could yield higher accuracy and consistency for this task. Using a new ICAD scheme can provide clinical researchers a useful tool to more efficiently and accurately extract TPA as well as muscle radiation attenuation as new image makers, and allow them to investigate the discriminatory power of it to predict progression-free survival and/or overall survival of the cancer patients before and after taking chemotherapy.

Economic and developmental considerations for pharmacogenomic technology.

PubMed

Vernon, John A; Johnson, Scott J; Hughen, W Keener; Trujillo, Antonio

2006-01-01

The pharmaceutical industry's core business is the innovation, development and marketing of new drugs. Pharmacogenetic (PG) testing and technology has the potential to increase a drug's value in many ways. A critical issue for the industry is whether products in development should be teamed with genetic tests that could segment the total population into responders and non-responders. In this paper we use a cost-effectiveness framework to model the strategic decision-making considerations by pharmaceutical manufacturers as they relate to drug development and the new technology of PG (the science of using genetic markers to predict drug response). In a simple, static, one-period model we consider three drug development strategies: a drug is exclusively developed and marketed to patients with a particular genetic marker; no distinguishing among patients based on the expression of a genetic marker is made (traditional approach); and a strategy whereby a drug is marketed to patients both with and without the genetic marker but there is price discrimination between the two subpopulations. We developed three main principles: revenues under a strategy targeting only the responder subpopulation will never generate more revenue than that which could have been obtained under a traditional approach; total revenues under a targeted PG strategy will be less than that under a traditional approach but higher than a naive [corrected] view would believe them to be; and a traditional [corrected] approach will earn the same total revenues as a price discrimination strategy, assuming no intermarket arbitrage. While these principles relate to the singular (and quite narrow) consideration of drug revenues, they may nevertheless partially explain why PG is not being used as widely as was predicted several years ago when the technology first became available, especially in terms of pharmaceutical manufacturer-developed tests.

Polymorphism rs2073618 of the osteoprotegerin gene as a potential marker of subclinical carotid atherosclerosis in Caucasians with type 2 diabetes mellitus.

PubMed

Pleskovič, Aleš; Ramuš, Sara Mankoč; Pražnikar, Zala Jenko; Šantl Letonja, Marija; Cokan Vujkovac, Andreja; Gazdikova, Katarina; Caprnda, Martin; Gaspar, Ludovit; Kruzliak, Peter; Petrovič, Daniel

2017-08-01

The OPG/RANKL/RANK (osteoprotegerin/receptor-activator of nuclear factor κB ligand/receptor-activator of nuclear factor κB) axis has been recently linked to the development of atherosclerosis and plaque destabilization. We have investigated whether polymorphism rs2073618 of the OPG gene is associated with subclinical markers of carotid atherosclerosis in subjects with type 2 diabetes mellitus (T2DM). 595 subjects with T2DM were enrolled in the cross-sectional study. Subclinical markers of carotid atherosclerosis (carotid intima media thickness, plaque thickness, and plaques presence) were assessed with ultrasound at the time of recruitment. Genotyping for rs2073618 (a missense variant located in exon I of the OPG gene) was performed, and OPG serum levels were determined by ELISA. Compared to the GG genotype, the CC genotype of the rs2073618 polymorphism had a significantly increased risk for the presence of carotid plaque (OR = 2.54, 95 % CI = 1.22-5.28, p = 0.01). No statistically significant difference could be detected (p = 0.68) upon comparing median values of serum OPG levels among studied genotype groups in subjects with T2DM. Multivariable linear regression analyses in T2DM subjects demonstrated that GC and CC genotypes (p = 0.03 and p = 0.003), together with statin therapy (p = 0.009), were independent predictors of the number of carotid segments with plaques. Despite the fact that OPG rs2073618 genotypes failed to predict the serum OPG levels as there was no statistical difference among compared genotypes, our results demonstrate that the rs2073618 polymorphism could be a possible genetic marker for the prediction of increased risk for carotid plaque burden as a measure of advanced subclinical atherosclerosis in T2DM subjects.

IGF-1 levels across the spectrum of normal to elevated in acromegaly: relationship to insulin sensitivity, markers of cardiovascular risk and body composition.

PubMed

Reid, Tirissa J; Jin, Zhezhen; Shen, Wei; Reyes-Vidal, Carlos M; Fernandez, Jean Carlos; Bruce, Jeffrey N; Kostadinov, Jane; Post, Kalmon D; Freda, Pamela U

2015-12-01

Activity of acromegaly is gauged by levels of GH and IGF-1 and epidemiological studies demonstrate that their normalization reduces acromegaly's excess mortality rate. However, few data are available linking IGF-1 levels to features of the disease that may relate to cardiovascular (CV) risk. Therefore, we tested the hypothesis that serum IGF-1 levels relative to the upper normal limit relate to insulin sensitivity, serum CV risk markers and body composition in acromegaly. In this prospective, cross-sectional study conducted at a pituitary tumor referral center we studied 138 adult acromegaly patients, newly diagnosed and previously treated surgically, with fasting and post-oral glucose levels of endocrine and CV risk markers and body composition assessed by DXA. Active acromegaly is associated with lower insulin sensitivity, body fat and CRP levels than acromegaly in remission. %ULN IGF-1 strongly predicts insulin sensitivity, better than GH and this persists after adjustment for body fat and lean tissue mass. %ULN IGF-1 also relates inversely to CRP levels and fat mass, positively to lean tissue and skeletal muscle estimated (SM(E)) by DXA, but not to blood pressure, lipids, BMI or waist circumference. Gender interacts with the IGF-1-lean tissue mass relationship. Active acromegaly presents a unique combination of features associated with CV risk, reduced insulin sensitivity yet lower body fat and lower levels of some serum CV risk markers, a pattern that is reversed in remission. %ULN IGF-1 levels strongly predict these features. Given the known increased CV risk of active acromegaly, these findings suggest that of these factors insulin resistance is most strongly related to disease activity and potentially to the increased CV risk of active acromegaly.

Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

PubMed

Benson, M

2016-03-01

Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide a brief introduction to systems medicine and discuss how it may contribute to the clinical implementation of individualized treatment, using clinically relevant examples. © 2015 The Association for the Publication of the Journal of Internal Medicine.

Prognostic factors, predictive markers and cancer biology: the triad for successful oral cancer chemoprevention.

PubMed

Monteiro de Oliveira Novaes, Jose Augusto; William, William N

2016-10-01

Oral squamous cell carcinomas represent a significant cancer burden worldwide. Unfortunately, chemoprevention strategies investigated to date have failed to produce an agent considered standard of care to prevent oral cancers. Nonetheless, recent advances in clinical trial design may streamline drug development in this setting. In this manuscript, we review some of these improvements, including risk prediction tools based on molecular markers that help select patients most suitable for chemoprevention. We also discuss the opportunities that novel preclinical models and modern molecular profiling techniques will bring to the prevention field in the near future, and propose a clinical trials framework that incorporates molecular prognostic factors, predictive markers and cancer biology as a roadmap to improve chemoprevention strategies for oral cancers.

Optimum location of external markers using feature selection algorithms for real‐time tumor tracking in external‐beam radiotherapy: a virtual phantom study

PubMed Central

Nankali, Saber; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-01

In external‐beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation‐based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two “Genetic” and “Ranker” searching procedures. The performance of these algorithms has been evaluated using four‐dimensional extended cardiac‐torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro‐fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F‐test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation‐based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers. PACS numbers: 87.55.km, 87.56.Fc PMID:26894358

Optimum location of external markers using feature selection algorithms for real-time tumor tracking in external-beam radiotherapy: a virtual phantom study.

PubMed

Nankali, Saber; Torshabi, Ahmad Esmaili; Miandoab, Payam Samadi; Baghizadeh, Amin

2016-01-08

In external-beam radiotherapy, using external markers is one of the most reliable tools to predict tumor position, in clinical applications. The main challenge in this approach is tumor motion tracking with highest accuracy that depends heavily on external markers location, and this issue is the objective of this study. Four commercially available feature selection algorithms entitled 1) Correlation-based Feature Selection, 2) Classifier, 3) Principal Components, and 4) Relief were proposed to find optimum location of external markers in combination with two "Genetic" and "Ranker" searching procedures. The performance of these algorithms has been evaluated using four-dimensional extended cardiac-torso anthropomorphic phantom. Six tumors in lung, three tumors in liver, and 49 points on the thorax surface were taken into account to simulate internal and external motions, respectively. The root mean square error of an adaptive neuro-fuzzy inference system (ANFIS) as prediction model was considered as metric for quantitatively evaluating the performance of proposed feature selection algorithms. To do this, the thorax surface region was divided into nine smaller segments and predefined tumors motion was predicted by ANFIS using external motion data of given markers at each small segment, separately. Our comparative results showed that all feature selection algorithms can reasonably select specific external markers from those segments where the root mean square error of the ANFIS model is minimum. Moreover, the performance accuracy of proposed feature selection algorithms was compared, separately. For this, each tumor motion was predicted using motion data of those external markers selected by each feature selection algorithm. Duncan statistical test, followed by F-test, on final results reflected that all proposed feature selection algorithms have the same performance accuracy for lung tumors. But for liver tumors, a correlation-based feature selection algorithm, in combination with a genetic search algorithm, proved to yield best performance accuracy for selecting optimum markers.

Expression of surface markers on the human monocytic leukaemia cell line, THP-1, as indicators for the sensitizing potential of chemicals.

PubMed

An, Susun; Kim, Seoyoung; Huh, Yong; Lee, Tae Ryong; Kim, Han-Kon; Park, Kui-Lea; Eun, Hee Chul

2009-04-01

Evaluation of skin sensitization potential is an important part of the safety assessment of cosmetic ingredients and topical drugs. Recently, evaluation of changes in surface marker expression induced in dendritic cells (DC) or DC surrogate cell lines following exposure to chemicals represents one approach for in vitro test methods. The study aimed to test the change of expression patterns of surface markers on THP-1 cells by chemicals as a predictive in vitro method for contact sensitization. We investigated the expression of CD54, CD86, CD83, CD80, and CD40 after a 1-day exposure to sensitizers (1-chloro-2,4-dinitrobenzene; 2,4-dinitrofluorobenzene; benzocaine; 5-chloro-2-methyl-4-isothiazolin-3-one; hexyl cinnamic aldehyde; eugenol; nickel sulfate hexahydrate; potassium dichromate; cobalt sulfate; 2-mercaptobenzothiazole; and ammonium tetrachloroplatinate) and non-sensitizers (sodium lauryl sulfate, benzalkonium chloride, lactic acid, salicylic acid, isopropanol, and dimethyl sulphoxide). The test concentrations were 0.1x, 0.5x, and 1x of the 50% inhibitory concentration, and the relative fluorescence intensity was used as an expression indicator. By evaluating the expression patterns of CD54, CD86, and CD40, we could classify the chemicals as sensitizers or non-sensitizers, but CD80 and CD83 showed non-specific patterns of expression. These data suggest that the THP-1 cells are good model for screening contact sensitizers and CD40 could be a useful marker complementary to CD54 and CD86.

Tumor Endothelial Marker Imaging in Melanomas Using Dual-Tracer Fluorescence Molecular Imaging

PubMed Central

Tichauer, Kenneth M.; Deharvengt, Sophie J.; Samkoe, Kimberley S.; Gunn, Jason R.; Bosenberg, Marcus W.; Turk, Mary-Jo; Hasan, Tayyaba; Stan, Radu V.; Pogue, Brian W.

2014-01-01

Purpose Cancer-specific endothelial markers available for intravascular binding are promising targets for new molecular therapies. In this study, a molecular imaging approach of quantifying endothelial marker concentrations (EMCI) is developed and tested in highly light-absorbing melanomas. The approach involves injection of targeted imaging tracer in conjunction with an untargeted tracer, which is used to account for nonspecific uptake and tissue optical property effects on measured targeted tracer concentrations. Procedures Theoretical simulations and a mouse melanoma model experiment were used to test out the EMCI approach. The tracers used in the melanoma experiments were fluorescently labeled anti-Plvap/PV1 antibody (plasmalemma vesicle associated protein Plvap/PV1 is a transmembrane protein marker exposed on the luminal surface of endothelial cells in tumor vasculature) and a fluorescent isotype control antibody, the uptakes of which were measured on a planar fluorescence imaging system. Results The EMCI model was found to be robust to experimental noise under reversible and irreversible binding conditions and was capable of predicting expected overexpression of PV1 in melanomas compared to healthy skin despite a 5-time higher measured fluorescence in healthy skin compared to melanoma: attributable to substantial light attenuation from melanin in the tumors. Conclusions This study demonstrates the potential of EMCI to quantify endothelial marker concentrations in vivo, an accomplishment that is currently unavailable through any other methods, either in vivo or ex vivo. PMID:24217944

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

2016-01-01

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

Altered expression of HER-2 and the mismatch repair genes MLH1 and MSH2 predicts the outcome of T1 high-grade bladder cancer.

PubMed

Sanguedolce, Francesca; Cormio, Antonella; Massenio, Paolo; Pedicillo, Maria C; Cagiano, Simona; Fortunato, Francesca; Calò, Beppe; Di Fino, Giuseppe; Carrieri, Giuseppe; Bufo, Pantaleo; Cormio, Luigi

2018-04-01

The identification of factors predicting the outcome of stage T1 high-grade bladder cancer (BC) is a major clinical issue. We performed immunohistochemistry to assess the role of human epidermal growth factor receptor-2 (HER-2) and microsatellite instability (MSI) factors MutL homologue 1 (MLH1) and MutS homologue 2 (MSH2) in predicting recurrence and progression of T1 high-grade BCs having undergone transurethral resection of bladder tumor (TURBT) alone or TURBT + intravesical instillations of bacillus Calmette-Guerin (BCG). HER-2 overexpression was a significant predictor of disease-free survival (DFS) in the overall as well as in the two patients' population; as for progression-free survival (PFS), it was significant in the overall but not in the two patients' population. MLH1 was an independent predictor of PFS only in patients treated with BCG and MSH2 failed to predict DFS and PFS in all populations. Most importantly, the higher the number of altered markers the lowers the DFS and PFS. In multivariate Cox proportional-hazards regression analysis, the number of altered molecular markers and BCG treatment were significant predictors (p = 0.0004 and 0.0283, respectively) of DFS, whereas the number of altered molecular markers was the only significant predictor (p = 0.0054) of PFS. Altered expression of the proto-oncogene HER-2 and the two molecular markers of genetic instability MLH1 and MSH2 predicted T1 high-grade BC outcome with the higher the number of altered markers the lower the DFS and PFS. These findings provide grounds for further testing them in predicting the outcome of this challenging disease.

[Comparison of various noninvasive serum markers of liver fibrosis in chronic viral liver disease].

PubMed

Kim, Sun Min; Sohn, Joo Hyun; Kim, Tae Yeob; Roh, Young Wook; Eun, Chang Soo; Jeon, Yong Cheol; Han, Dong Soo; Oh, Young Ha

2009-12-01

The aim of this study was to determine the clinical performances of noninvasive serum markers for the prediction of liver fibrosis in chronic viral liver diseases. We analyzed a total of 225 patients with chronic viral liver diseases (180 with hepatitis B virus, 43 with hepatitis C virus, and 2 with hepatitis B+C virus) who underwent a liver biopsy procedure at the Hanyang University Guri Hospital between March 2002 and February 2007. Serum was also obtained at the time of liver biopsy. Liver fibrosis was staged according to the scoring system proposed by the Korean Study Group for the Pathology of Digestive Diseases. Various noninvasive serum markers were evaluated, including the aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (AAR), age-platelet (AP) index, AST/platelet ratio index (APRI), cirrhosis discriminant score (CDS), platelet count, hyaluronic acid (HA), and type IV collagen. There were 17, 40, 61, 74, and 33 patients at stages F0, F1, F2, F3, and F4, respectively. The overall diagnostic accuracies of each marker, as determined by the area under receiver operating characteristics curves, were APRI=0.822, CDS=0.776, platelet count=0.773, AP index=0.756, HA=0.749, type IV collagen=0.718, and AAR=0.642 for predicting significant fibrosis (> or =F2); and CDS=0.835, platelet count=0.795, AP index=0.794, HA=0.766, AAR=0.711, type IV collagen=0.697, and APRI=0.691 for predicting extensive fibrosis (> or =F3). All noninvasive serum markers evaluated in this study were useful for predicting significant or extensive liver fibrosis in chronic viral liver diseases. In particular, APRI was most useful for the prediction of significant fibrosis, and CDS was most useful for the prediction of extensive fibrosis.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress

PubMed Central

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C.

2014-01-01

Background and Aims Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Methods Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. Key Results To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait ‘total crop nitrogen uptake’ (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10–36 % more yield than those based on markers for yield per se. Conclusions This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. PMID:24984712

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.

PubMed

Kraus, Virginia Byers; Feng, Sheng; Wang, ShengChu; White, Scott; Ainslie, Maureen; Brett, Alan; Holmes, Anthony; Charles, H Cecil

2009-12-01

To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3-year period. A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius. Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52-0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79). We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.

Targeted Sequencing for Discovery and Validation of DNA Methylation Markers of Colon Cancer Metastasis — EDRN Public Portal

Cancer.gov

Colon cancer is the second leading cause of cancer death in the United States. A key issue in treating colon cancer patients is inability to accurately predict tumors that have metastatic potential and require adjuvant chemotherapy. This project will test the model that tumor metastases arise from intra-tumor heterogeneity generated by DNA methylation events, and that detecting these events can provide a predictve signature of tumors with poor outcome

Epigenetic Therapy in Lung Cancer - Role of microRNAs.

PubMed

Rothschild, Sacha I

2013-01-01

Lung cancer is the leading cause of cancer deaths worldwide. microRNAs (miRNAs) are a class of small non-coding RNA species that have been implicated in the control of many fundamental cellular and physiological processes such as cellular differentiation, proliferation, apoptosis, and stem cell maintenance. Some miRNAs have been categorized as "oncomiRs" as opposed to "tumor suppressor miRs." This review focuses on the role of miRNAs in the lung cancer carcinogenesis and their potential as diagnostic, prognostic, or predictive markers.

Further evidence for population specific differences in the effect of DNA markers and gender on eye colour prediction in forensics.

PubMed

Pośpiech, Ewelina; Karłowska-Pik, Joanna; Ziemkiewicz, Bartosz; Kukla, Magdalena; Skowron, Małgorzata; Wojas-Pelc, Anna; Branicki, Wojciech

2016-07-01

The genetics of eye colour has been extensively studied over the past few years, and the identified polymorphisms have been applied with marked success in the field of Forensic DNA Phenotyping. A picture that arises from evaluation of the currently available eye colour prediction markers shows that only the analysis of HERC2-OCA2 complex has similar effectiveness in different populations, while the predictive potential of other loci may vary significantly. Moreover, the role of gender in the explanation of human eye colour variation should not be neglected in some populations. In the present study, we re-investigated the data for 1020 Polish individuals and using neural networks and logistic regression methods explored predictive capacity of IrisPlex SNPs and gender in this population sample. In general, neural networks provided higher prediction accuracy comparing to logistic regression (AUC increase by 0.02-0.06). Four out of six IrisPlex SNPs were associated with eye colour in the studied population. HERC2 rs12913832, OCA2 rs1800407 and SLC24A4 rs12896399 were found to be the most important eye colour predictors (p < 0.007) while the effect of rs16891982 in SLC45A2 was less significant. Gender was found to be significantly associated with eye colour with males having ~1.5 higher odds for blue eye colour comparing to females (p = 0.002) and was ranked as the third most important factor in blue/non-blue eye colour determination. However, the implementation of gender into the developed prediction models had marginal and ambiguous impact on the overall accuracy of prediction confirming that the effect of gender on eye colour in this population is small. Our study indicated the advantage of neural networks in prediction modeling in forensics and provided additional evidence for population specific differences in the predictive importance of the IrisPlex SNPs and gender.

Early Cord Metabolite Index and Outcome in Perinatal Asphyxia and Hypoxic-Ischaemic Encephalopathy.

PubMed

Ahearne, C E; Denihan, N M; Walsh, B H; Reinke, S N; Kenny, L C; Boylan, G B; Broadhurst, D I; Murray, D M

2016-01-01

A 1H-NMR-derived metabolomic index based on early umbilical cord blood alterations of succinate, glycerol, 3-hydroxybutyrate and O-phosphocholine has shown potential for the prediction of hypoxic-ischaemic encephalopathy (HIE) severity. To evaluate whether this metabolite score can predict 3-year neurodevelopmental outcome in infants with perinatal asphyxia and HIE, compared with current standard biochemical and clinical markers. From September 2009 to June 2011, infants at risk of perinatal asphyxia were recruited from a single maternity hospital. Cord blood was drawn and biobanked at delivery. Neonates were monitored for development of encephalopathy both clinically and electrographically. Neurodevelopmental outcome was assessed at 36-42 months using the Bayley Scales of Infant and Toddler Development, ed. III (BSID-III). Death and cerebral palsy were also considered as abnormal end points. Thirty-one infants had both metabolomic analysis and neurodevelopmental outcome at 36-42 months. No child had a severely abnormal BSID-III result. The metabolite index significantly correlated with outcome (ρ2 = 0.30, p < 0.01), which is robust to predict both severe outcome (area under the receiver operating characteristic curve: 0.92, p < 0.01) and intact survival (0.80, p = 0.01). There was no correlation between the index score and performance in the individual BSID-III subscales (cognitive, language, motor). The metabolite index outperformed other standard biochemical markers at birth for prediction of outcome at 3 years, but was not superior to EEG or the Sarnat score. © 2016 S. Karger AG, Basel.

Presymptomatic electrophysiological tests predict clinical onset and survival in SOD1(G93A) ALS mice.

PubMed

Mancuso, Renzo; Osta, Rosario; Navarro, Xavier

2014-12-01

We assessed the predictive value of electrophysiological tests as a marker of clinical disease onset and survival in superoxide-dismutase 1 (SOD1)(G93A) mice. We evaluated the accuracy of electrophysiological tests in differentiating transgenic versus wild-type mice. We made a correlation analysis of electrophysiological parameters and the onset of symptoms, survival, and number of spinal motoneurons. Presymptomatic electrophysiological tests show great accuracy in differentiating transgenic versus wild-type mice, with the most sensitive parameter being the tibialis anterior compound muscle action potential (CMAP) amplitude. The CMAP amplitude at age 10 weeks correlated significantly with clinical disease onset and survival. Electrophysiological tests increased their survival prediction accuracy when evaluated at later stages of the disease and also predicted the amount of lumbar spinal motoneuron preservation. Electrophysiological tests predict clinical disease onset, survival, and spinal motoneuron preservation in SOD1(G93A) mice. This is a methodological improvement for preclinical studies. © 2014 Wiley Periodicals, Inc.

Novel prognostic tissue markers in congestive heart failure.

PubMed

Stone, James R

2015-01-01

Heart failure is a relatively common disorder associated with high morbidity, mortality, and economic burden. Better tools to predict outcomes for patients with heart failure could allow for better decision making concerning patient treatment and management and better utilization of health care resources. Endomyocardial biopsy offers a mechanism to pathologically diagnose specific diseases in patients with heart failure, but such biopsies can often be negative, with no specific diagnostic information. Novel tissue markers in endomyocardial biopsies have been identified that may be useful in assessing prognosis in heart failure patients. Such tissue markers include ubiquitin, Gremlin-1, cyclophilin A, and heterogeneous nuclear ribonucleoprotein C. In some cases, tissue markers have been found to be independent of and even superior to clinical indices and serum markers in predicting prognosis for heart failure patients. In some cases, these novel tissue markers appear to offer prognostic information even in the setting of an otherwise negative endomyocardial biopsy. Copyright © 2014 Elsevier Inc. All rights reserved.

The impact of sport related stressors on immunity and illness risk in team-sport athletes.

PubMed

Keaney, Lauren C; Kilding, Andrew E; Merien, Fabrice; Dulson, Deborah K

2018-06-19

Elite team-sport athletes are frequently exposed to stressors that have the potential to depress immunity and increase infection risk. Therefore, the purpose of this review is to describe how team-sport stressors impact upon immune responses, along with exploring whether alterations in these markers have the potential to predict upper respiratory tract illness symptoms. Narrative review. Salivary secretory immunoglobulin A (SIgA) and T-cell markers have been shown to predict infection risk in individual endurance athletes. Papers discussing the impact of team-sport stressors on SIgA and T-cells were discussed in the review, studies discussing other aspects of immunity were excluded. Journal articles were sourced from PubMed, Web of science and Scopus. Key search terms included team-sport athletes, stressors, immunity, T-cells, cytokines, SIgA and upper respiratory illness. Most team-sport stressors appear to increase risk for illness. An association between reduced SIgA and increased illness incidence has been demonstrated. Intensive training and competition periods have been shown to reduce SIgA, however, it is less clear how additional stressors including extreme environmental conditions, travel, psychological stress, sleep disturbance and poor nutrition affect immune responses. Monitoring SIgA may provide an assessment of a team-sport athletes risk status for developing upper respiratory tract symptoms, however there is currently not enough evidence to suggest SIgA alone can predict illness. Team-sport stressors challenge immunity and it is possible that the combination of stressors could have a compounding effect on immunodepression and infection risk. Given that illness can disrupt training and performance, further research is required to better elucidate how stressors individually and collectively influence immunity and illness. Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

On prediction of genetic values in marker-assisted selection.

PubMed Central

Lange, C; Whittaker, J C

2001-01-01

We suggest a new approximation for the prediction of genetic values in marker-assisted selection. The new approximation is compared to the standard approach. It is shown that the new approach will often provide substantially better prediction of genetic values; furthermore the new approximation avoids some of the known statistical problems of the standard approach. The advantages of the new approach are illustrated by a simulation study in which the new approximation outperforms both the standard approach and phenotypic selection. PMID:11729177

DNA Adducts from Anticancer Drugs as Candidate Predictive Markers for Precision Medicine

PubMed Central

2016-01-01

Biomarker-driven drug selection plays a central role in cancer drug discovery and development, and in diagnostic strategies to improve the use of traditional chemotherapeutic drugs. DNA-modifying anticancer drugs are still used as first line medication, but drawbacks such as resistance and side effects remain an issue. Monitoring the formation and level of DNA modifications induced by anticancer drugs is a potential strategy for stratifying patients and predicting drug efficacy. In this perspective, preclinical and clinical data concerning the relationship between drug-induced DNA adducts and biological response for platinum drugs and combination therapies, nitrogen mustards and half-mustards, hypoxia-activated drugs, reductase-activated drugs, and minor groove binding agents are presented and discussed. Aspects including measurement strategies, identification of adducts, and biological factors that influence the predictive relationship between DNA modification and biological response are addressed. A positive correlation between DNA adduct levels and response was observed for the majority of the studies, demonstrating the high potential of using DNA adducts from anticancer drugs as mechanism-based biomarkers of susceptibility, especially as bioanalysis approaches with higher sensitivity and throughput emerge. PMID:27936622

Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacobs, John M.; Rhodes, M.; Brown, C. W.

The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity aremore » capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.« less

Predicting risk in patients with acetaminophen overdose

PubMed Central

James, Laura P.; Gill, Prit; Simpson, Pippa

2014-01-01

Acetaminophen (APAP) overdose is a very common cause of drug overdose and acute liver failure in the US and Europe. Mechanism-based biomarkers of APAP toxicity have the potential to improve the clinical management of patients with large dose ingestions of APAP. The current approach to the management of APAP toxicity is limited by imprecise and time-constrained risk assessments and late-stage markers of liver injury. A recent study of “low-risk” APAP overdose patients who all received treatment with N-acetylcysteine, found that cell-death biomarkers were more sensitive than alanine aminotransferase (ALT) and APAP concentrations in predicting the development of acute liver injury. The data suggest a potential role for new biomarkers to identify “low risk” patients following APAP overdose. However, a practical and ethical consideration that complicates predictive biomarker research in this area is the clinical need to deliver antidote treatment within 10 hours of APAP overdose. The treatment effect and time-dependent nature of N-acetylcysteine treatment must be considered in future “predictive” toxicology studies of APAP-induced liver injury. PMID:23984999

The Prognostic Role of Cancer Stem Cell Markers for Long-term Outcome After Resection of Colonic Liver Metastases.

PubMed

Spelt, Lidewij; Sasor, Agata; Ansari, Daniel; Hilmersson, Katarzyna Said; Andersson, Roland

2018-01-01

To assess the expression of cancer stem cell (CSC) markers CD44, CD133 and CD24 in colon cancer liver metastases and analyse their predictive value for overall survival (OS) and disease-free survival (DFS) after liver resection. Patients operated on for colon cancer liver metastases were included. CSC marker expression was determined through immunohistochemistry analysis. OS and DFS were compared between marker-positive and marker-negative patients. Multivariate analysis was performed to select predictive variables for OS and DFS. CD133-positive patients had a worse DFS than CD133-negative patients, with a median DFS of 12 and 25 months (p=0.051). Multivariate analysis selected CD133 expression as a significant predictor for DFS. CD44 and CD24 were not found to predict OS or DFS. CD133 expression in colonic liver metastases is a negative prognostic factor for DFS after liver resection. In the future, CD133 could be used as a biomarker for risk stratification, and possibly for developing novel targeted therapy. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Genetic markers on BTA14 predictive for residual feed intake in beef steers and their effects on carcass and meat quality traits

USDA-ARS?s Scientific Manuscript database

With the high cost of feed for animal production, genetic selection for animals that metabolize feed more efficiently could result in substantial cost savings for cattle producers. The purpose of this study was to identify DNA markers predictive for differences among cattle for traits associated wit...

Dysfunctional information processing in individuals with acute exposure to sexual abuse: An ERP study.

PubMed

Han, Changwoo; Park, Minkyung; Lee, Jun-Young; Jung, Hee Yeon; Park, Su Mi; Choi, Jung-Seok

2018-06-01

Acute stress disorder (ASD) and posttraumatic stress disorder (PTSD) may occur after traumatic event and also cause significant life time impairment. P300 event-related potential (ERP) is a potential biological marker for PTSD and can reflect cognitive impairment in information processing and attention. Despite the usefulness of ERP, there are few attempts to reveal relationships between ASD and P300. In the present study, we aimed to determine if the P300 of the patients who were the victims of sexual abuse reflected the quantitative trait of ASD or if P300 is applicable as a state marker for predicting the risk of PTSD.Fifteen female victims of sexual abuse diagnosed with ASD and 18 healthy controls (HCs) without trauma exposure participated in this study. We investigated the P300 ERPs in patients with ASD to compare them with those of HCs. ERPs were acquired from female adults during an auditory oddball task. Between-group differences in amplitudes or latencies of P300 were investigated using repeated-measures analysis of variance.The ASD groups showed reduced P300 amplitudes at the midline centroparietal site as well as reduced accuracy rates during an auditory oddball task compared with the HCs.These results indicate that ASD have abnormalities in the P300 compared to those in HCs. Moreover, the reduction in P300 could be considered a candidate neurophysiological marker for ASD.

A Secreted Form of the Asialoglycoprotein Receptor, sH2a, as a Novel Potential Noninvasive Marker for Liver Fibrosis

PubMed Central

Lurie, Yoav; Ron, Efrat; Santo, Moshe; Reif, Shimon; Elashvili, Irma; Bar, Lana; Lederkremer, Gerardo Z.

2011-01-01

Background and Aim The human asialoglycoprotein receptor is a membrane heterooligomer expressed exclusively in hepatocytes. A soluble secreted form, sH2a, arises, not by shedding at the cell surface, but by intracellular cleavage of its membrane-bound precursor, which is encoded by an alternatively spliced form of the receptor H2 subunit. Here we determined and report that sH2a, present at constant levels in serum from healthy individuals is altered upon liver fibrosis, reflecting the status of hepatocyte function. Methods We measured sH2a levels in serum using a monoclonal antibody and an ELISA assay that we developed, comparing with routine liver function markers. We compared blindly pretreatment serum samples from a cohort of 44 hepatitis C patients, which had METAVIR-scored biopsies, with 28 healthy individuals. Results sH2a levels varied minimally for the healthy individuals (150±21 ng/ml), whereas the levels deviated from this normal range increasingly in correlation with fibrosis stage. A simple algorithm combining sH2a levels with those of alanine aminotransferase allowed prediction of fibrosis stage, with a very high area under the ROC curve of 0.86. Conclusions sH2a has the potential to be a uniquely sensitive and specific novel marker for liver fibrosis and function. PMID:22096539

Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers.

PubMed

Ortigosa, Nuria; Pérez-Roselló, Víctor; Donoso, Víctor; Osca, Joaquín; Martínez-Dolz, Luis; Fernández, Carmen; Galbis, Antonio

2018-04-01

Cardiac resynchronization therapy (CRT) is an effective treatment for those patients with severe heart failure. Regrettably, there are about one third of CRT "non-responders", i.e. patients who have undergone this form of device therapy but do not respond to it, which adversely affects the utility and cost-effectiveness of CRT. In this paper, we assess the ability of a novel surface ECG marker to predict CRT response. We performed a retrospective exploratory study of the ECG previous to CRT implantation in 43 consecutive patients with ischemic (17) or non-ischemic (26) cardiomyopathy. We extracted the QRST complexes (consisting of the QRS complex, the S-T segment, and the T wave) and obtained a measure of their energy by means of spectral analysis. This ECG marker showed statistically significant lower values for non-responder patients and, joint with the duration of QRS complexes (the current gold-standard to predict CRT response), the following performances: 86% accuracy, 88% sensitivity, and 80% specificity. In this manner, the proposed ECG marker may help clinicians to predict positive response to CRT in a non-invasive way, in order to minimize unsuccessful procedures.

Tumor-infiltrating lymphocytes and ductal carcinoma in situ of the breast: friends or foes?

PubMed

Agahozo, Marie Colombe; Hammerl, Dora; Debets, Reno; Kok, Marleen; van Deurzen, Carolien H M

2018-02-20

In the past three decades, the detection rate of ductal carcinoma in situ of the breast has dramatically increased due to breast screening programs. As a consequence, about 20% of all breast cancer cases are detected in this early in situ stage. Some ductal carcinoma in situ cases will progress to invasive breast cancer, while other cases are likely to have an indolent biological behavior. The presence of tumor-infiltrating lymphocytes is seen as a promising prognostic and predictive marker in invasive breast cancer, mainly in HER2-positive and triple-negative subtypes. Here, we summarize the current understanding regarding immune infiltrates in invasive breast cancer and highlight recent observations regarding the presence and potential clinical significance of such immune infiltrates in patients with ductal carcinoma in situ. The presence of tumor-infiltrating lymphocytes, their numbers, composition, and potential relationship with genomic status will be discussed. Finally, we propose that a combination of genetic and immune markers may better stratify ductal carcinoma in situ subtypes with respect to tumor evolution.

The epigenetics of prostate cancer diagnosis and prognosis: update on clinical applications.

PubMed

Blute, Michael L; Damaschke, Nathan A; Jarrard, David F

2015-01-01

There is a major deficit in our ability to detect and predict the clinical behavior of prostate cancer (PCa). Epigenetic changes are associated with PCa development and progression. This review will focus on recent results in the clinical application of diagnostic and prognostic epigenetic markers. The development of high throughput technology has seen an enormous increase in the discovery of new markers that encompass epigenetic changes including those in DNA methylation and histone modifications. Application of these findings to urine and other biofluids, but also cancer and noncancerous prostate tissue, has resulted in new biomarkers. There has been a recent commercial development of a DNA methylation-based assay for identifying PCa risk from normal biopsy tissue. Other biomarkers are currently in the validation phase and encompass combinations of multiple genes. Epigenetic changes improve the specificity and sensitivity of PCa diagnosis and have the potential to help determine clinical prognosis. Additional studies will not only provide new and better biomarker candidates, but also have the potential to inform new therapeutic strategies given the reversibility of these processes.

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat.

PubMed

Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Huerta-Espino, Julio; Lan, Caixia; Bhavani, Sridhar; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

2017-07-01

Genomic prediction for seedling and adult plant resistance to wheat rusts was compared to prediction using few markers as fixed effects in a least-squares approach and pedigree-based prediction. The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies for effective evaluation and exploitation of quantitative rust resistance. One promising approach that could accelerate gain from selection for rust resistance is 'genomic selection' which utilizes dense genome-wide markers to estimate the breeding values (BVs) for quantitative traits. Our objective was to compare three genomic prediction models including genomic best linear unbiased prediction (GBLUP), GBLUP A that was GBLUP with selected loci as fixed effects and reproducing kernel Hilbert spaces-markers (RKHS-M) with least-squares (LS) approach, RKHS-pedigree (RKHS-P), and RKHS markers and pedigree (RKHS-MP) to determine the BVs for seedling and/or adult plant resistance (APR) to leaf rust (LR), stem rust (SR), and stripe rust (YR). The 333 lines in the 45th IBWSN and the 313 lines in the 46th IBWSN were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. The mean prediction accuracies ranged from 0.31-0.74 for LR seedling, 0.12-0.56 for LR APR, 0.31-0.65 for SR APR, 0.70-0.78 for YR seedling, and 0.34-0.71 for YR APR. For most datasets, the RKHS-MP model gave the highest accuracies, while LS gave the lowest. GBLUP, GBLUP A, RKHS-M, and RKHS-P models gave similar accuracies. Using genome-wide marker-based models resulted in an average of 42% increase in accuracy over LS. We conclude that GS is a promising approach for improvement of quantitative rust resistance and can be implemented in the breeding pipeline.

The Lack of Utility of Circulating Biomarkers of Inflammation and Endothelial Dysfunction for Type 2 Diabetes Risk Prediction Among Postmenopausal Women

PubMed Central

Chao, Chun; Song, Yiqing; Cook, Nancy; Tseng, Chi-Hong; Manson, JoAnn E.; Eaton, Charles; Margolis, Karen L.; Rodriguez, Beatriz; Phillips, Lawrence S.; Tinker, Lesley F.; Liu, Simin

2011-01-01

Background Recent studies have linked plasma markers of inflammation and endothelial dysfunction to type 2 diabetes mellitus (DM) development. However, the utility of these novel biomarkers for type 2 DM risk prediction remains uncertain. Methods The Women’s Health Initiative Observational Study (WHIOS), a prospective cohort, and a nested case-control study within the WHIOS of 1584 incident type 2 DM cases and 2198 matched controls were used to evaluate the utility of plasma markers of inflammation and endothelial dysfunction for type 2 DM risk prediction. Between September 1994 and December 1998, 93 676 women aged 50 to 79 years were enrolled in the WHIOS. Fasting plasma levels of glucose, insulin, white blood cells, tumor necrosis factor receptor 2, interleukin 6, high-sensitivity C-reactive protein, E-selectin, soluble intercellular adhesion molecule 1, and vascular cell adhesion molecule 1 were measured using blood samples collected at baseline. A series of prediction models including traditional risk factors and novel plasma markers were evaluated on the basis of global model fit, model discrimination, net reclassification improvement, and positive and negative predictive values. Results Although white blood cell count and levels of interleukin 6, high-sensitivity C-reactive protein, and soluble intercellular adhesion molecule 1 significantly enhanced model fit, none of the inflammatory and endothelial dysfunction markers improved the ability of model discrimination (area under the receiver operating characteristic curve, 0.93 vs 0.93), net reclassification, or predictive values (positive, 0.22 vs 0.24; negative, 0.99 vs 0.99 [using 15% 6-year type 2 DM risk as the cutoff]) compared with traditional risk factors. Similar results were obtained in ethnic-specific analyses. Conclusion Beyond traditional risk factors, measurement of plasma markers of systemic inflammation and endothelial dysfunction contribute relatively little additional value in clinical type 2 DM risk prediction in a multiethnic cohort of postmenopausal women. PMID:20876407

A Joint Model for the Kinetics of CTC Count and PSA Concentration During Treatment in Metastatic Castration-Resistant Prostate Cancer*

PubMed Central

Wilbaux, M; Tod, M; De Bono, J; Lorente, D; Mateo, J; Freyer, G; You, B; Hénin, E

2015-01-01

Assessment of treatment efficacy in metastatic castration-resistant prostate cancer (mCRPC) is limited by frequent nonmeasurable bone metastases. The count of circulating tumor cells (CTCs) is a promising surrogate marker that may replace the widely used prostate-specific antigen (PSA). The purpose of this study was to quantify the dynamic relationships between the longitudinal kinetics of these markers during treatment in patients with mCRPC. Data from 223 patients with mCRPC treated by chemotherapy and/or hormonotherapy were analyzed for up to 6 months of treatment. A semimechanistic model was built, combining the following several pharmacometric advanced features: (1) Kinetic-Pharmacodynamic (K-PD) compartments for treatments (chemotherapy and hormonotherapy); (2) a latent variable linking both marker kinetics; (3) modeling of CTC kinetics with a cell lifespan model; and (4) a negative binomial distribution for the CTC random sampling. Linked with survival, this model would potentially be useful for predicting treatment efficacy during drug development or for therapeutic adjustment in treated patients. PMID:26225253

The Late Positive Potential: A Neurophysiological Marker for Emotion Regulation in Children

ERIC Educational Resources Information Center

Dennis, Tracy A.; Hajcak, Greg

2009-01-01

Background: The ability to modulate emotional responses, or emotion regulation, is a key mechanism in the development of mood disruptions. Detection of a neural marker for emotion regulation thus has the potential to inform early detection and intervention for mood problems. One such neural marker may be the late positive potential (LPP), which is…

The role of steroid receptor coactivator-3 (SRC-3) in human malignant disease.

PubMed

Gojis, O; Rudraraju, B; Alifrangis, C; Krell, J; Libalova, P; Palmieri, C

2010-03-01

The p160 steroid receptor coactivator (SRC) family is critical to the transcriptional activation function of nuclear hormone receptors. A key member of this family is SRC-3, initially found to be amplified and expressed in breast cancer it has subsequent been shown to be expressed in malignant disease arising from a wide range of other organs. An understanding of the potential role of SRC-3 in the pathogenesis and its possible prognostic role in a broad range of tumours will improve our general understanding of carcinogenesis as well as potentially leading to a new prognostic marker as well as new therapeutic targets. Relevant papers were identified by searching the PubMed and MEDLINE databases for article published until 28th February 2009. Only articles published in English were considered. The search terms included "SRC-3", "AIB1" in association with the following terms: "human", "cancer" and "malignant disease". The search focused on malignant disease arising outside of the mammary gland. Full articles were obtained and references were checked for additional material when appropriate. SRC-3 is amplified and expressed in a wide spectrum of human malignant diseases and appears to be a potential prognostic marker in a number of different tumours. SRC-3 appears to be implicated in the possible risk of developing prostate and ovarian cancer. Its presence appears to be a marker of aggressive disease. Further research is required to determine its predictive and prognostic utility given the relative paucity of studies for each specific malignant disease. Copyright (c) 2009. Published by Elsevier Ltd.

The Alcohol Dehydrogenase Isoenzyme as a Potential Marker of Pancreatitis.

PubMed

Jelski, Wojciech; Piechota, Joanna; Orywal, Karolina; Szmitkowski, Maciej

2018-05-01

Human pancreas parenchyma contains various alcohol dehydrogenase (ADH) isoenzymes and also possesses aldehyde dehydrogenase (ALDH) activity. The altered activities of ADH and ALDH in damaged pancreatic tissue in the course of pancreatitis are reflected in the human serum. The aim of this study was to investigate a potential role of ADH and ALDH as markers for acute (AP) and chronic pancreatitis (CP). Serum samples were collected for routine biochemical investigations from 75 patients suffering from acute pancreatitis and 70 patients with chronic pancreatitis. Fluorometric methods were used to measure the activity of class I and II ADH and ALDH activity. The total ADH activity and activity of class III and IV isoenzymes were measured by a photometric method. There was a significant increase in the activity of ADH III isoenzyme (15.06 mU/l and 14.62 mU/l vs. 11.82 mU/l; p<0.001) and total ADH activity (764 mU/l and 735 mU/l vs. 568 mU/l) in the sera of patients with acute pancreatitis or chronic pancreatitis compared to the control. The diagnostic sensitivity for ADH III was about 84%, specificity was 92 %, positive and negative predictive values were 93% and 87% respectively in acute pancreatitis. Area under the Receiver Operating Curve (ROC) curve for ADH III in AP and CP was 0.88 and 0.86 respectively. ADH III has a potential role as a marker of acute and chronic pancreatitis. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Financial Exploitation Is Associated With Structural and Functional Brain Differences in Healthy Older Adults

PubMed Central

Spreng, R. Nathan; Cassidy, Benjamin N; Darboh, Bri S; DuPre, Elizabeth; Lockrow, Amber W; Setton, Roni; Turner, Gary R

2017-01-01

Abstract Background Age-related brain changes leading to altered socioemotional functioning may increase vulnerability to financial exploitation. If confirmed, this would suggest a novel mechanism leading to heightened financial exploitation risk in older adults. Development of predictive neural markers could facilitate increased vigilance and prevention. In this preliminary study, we sought to identify structural and functional brain differences associated with financial exploitation in older adults. Methods Financially exploited older adults (n = 13, 7 female) and a matched cohort of older adults who had been exposed to, but avoided, a potentially exploitative situation (n = 13, 7 female) were evaluated. Using magnetic resonance imaging, we examined cortical thickness and resting state functional connectivity. Behavioral data were collected using standardized cognitive assessments, self-report measures of mood and social functioning. Results The exploited group showed cortical thinning in anterior insula and posterior superior temporal cortices, regions associated with processing affective and social information, respectively. Functional connectivity encompassing these regions, within default and salience networks, was reduced, while between network connectivity was increased. Self-reported anger and hostility was higher for the exploited group. Conclusions We observed financial exploitation associated with brain differences in regions involved in socioemotional functioning. These exploratory and preliminary findings suggest that alterations in brain regions implicated in socioemotional functioning may be a marker of financial exploitation risk. Large-scale, prospective studies are necessary to validate this neural mechanism, and develop predictive markers for use in clinical practice. PMID:28369260

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Bo, E-mail: luboufl@gmail.com; Park, Justin C.; Fan, Qiyong

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparsemore » optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.« less

Intraovarian markers of follicular and oocyte maturation.

PubMed

Pellicer, A; Diamond, M P; DeCherney, A H; Naftolin, F

1987-08-01

The use of ovulation induction for multiple follicular growth in in vitro fertilization (IVF) has introduced the problem of follicular asynchrony. As a consequence of the asynchrony, the parameters most commonly used by IVF groups to assess follicular and oocyte quality within those follicles are not sufficiently sensitive or specific. Thus, each follicle must be considered separately, and specific markers of follicular and/or oocyte maturation must be sought from within the follicle. In this review we analyze previous reports of potential markers of follicular and oocyte maturation. In regards to the follicular fluid constituents, the level of estradiol in follicular fluid correlates with fertilization and pregnancy in stimulated cycles. Other steroids are only helpful when specific stimulation protocols are used. The level of some follicular proteins such as alpha-1-antitrypsin and fibrinogen also correlates with fertilization and pregnancy outcome. Cyclic AMP levels in follicular fluid are significantly reduced in follicles leading to conception. Regulators of oocyte maturation, such as the Oocyte Maturation Inhibitor (OMI) or the Meiosis Inducing Substance (MIS) have also been correlated with IVF outcome, but their exact structure remains still unknown. In addition, other sophisticated parameters, such as chemotactic activity of human leukocytes, or simple methods, such as the presence of intrafollicular echoes, have also been used as successful markers in predicting IVF outcome.

Characterizing relationships among fecal indicator bacteria ...

EPA Pesticide Factsheets

Bed sediments of streams and rivers may store high concentrations of fecal indicator bacteria (FIB) and pathogens. Due to resuspension events, these contaminants can be mobilized into the water column and affect overall water quality. Other bacterial indicators such as microbial source tracking (MST) markers, developed to determine potential sources of fecal contamination, can also be resuspended from bed sediments. The primary objective of this study was to predict occurrence of waterborne pathogens in water and streambed sediments using a simple statistical model that includes traditionally measured FIB, environmental parameters and source allocation, using MST markers as predictor variables. Synoptic sampling events were conducted during baseflow conditions downstream from agricultural (AG), forested (FORS), and wastewater pollution control plant (WPCP) land uses. Concentrations of FIB and MST markers were measured in water and sediments, along with occurrences of the enteric pathogens Campylobacter, Listeria and Salmonella, and the virulence gene that carries Shiga toxin, stx2. Pathogens were detected in water more often than in underlying sediments. Shiga toxin was significantly related to land use, with concentrations of the ruminant marker selected as an independent variable that could correctly classify 76% and 64% of observed Shiga toxin occurrences in water and sediment, respectively. FIB concentrations and water quality parameters were also selected a

Patient-specific evolution of renal function in chronic heart failure patients dynamically predicts clinical outcome in the Bio-SHiFT study.

PubMed

Brankovic, Milos; Akkerhuis, K Martijn; van Boven, Nick; Anroedh, Sharda; Constantinescu, Alina; Caliskan, Kadir; Manintveld, Olivier; Cornel, Jan Hein; Baart, Sara; Rizopoulos, Dimitris; Hillege, Hans; Boersma, Eric; Umans, Victor; Kardys, Isabella

2018-04-01

Renal dysfunction is an important component of chronic heart failure (CHF), but its single assessment does not sufficiently reflect clinically silent progression of CHF prior to adverse clinical outcome. Therefore, we aimed to investigate temporal evolutions of glomerular and tubular markers in 263 stable patients with CHF, and to determine if their patient-specific evolutions during this clinically silent period can dynamically predict clinical outcome. We determined the risk of clinical outcome (composite endpoint of Heart Failure hospitalization, cardiac death, Left Ventricular Assist Device placement, and heart transplantation) in relation to marker levels, slopes and areas under their trajectories. In each patient, the trajectories were estimated using repeatedly measured glomerular markers: creatinine/estimated glomerular filtration rate (eGFR), cystatin C (CysC), and tubular markers: urinary N-acetyl-beta-D-glucosaminidase (NAG) and kidney injury molecule (KIM)-1, plasma and urinary neutrophil gelatinase-associated lipocalin (NGAL). During 2.2 years of follow-up, we collected on average 8 urine and 9 plasma samples per patient. All glomerular markers predicted the endpoint (univariable hazard ratio [95% confidence interval] per 20% increase: creatinine: 1.18[1.07-1.31], CysC: 2.41[1.81-3.41], and per 20% eGFR decrease: 1.13[1.05-1.23]). Tubular markers, NAG, and KIM-1 also predicted the endpoint (NAG: 1.06[1.01-1.11] and KIM-1: 1.08[1.04-1.11]). Larger slopes were the strongest predictors (creatinine: 1.57[1.39-1.84], CysC: 1.76[1.52-2.09], eGFR: 1.59[1.37-1.90], NAG: 1.26[1.11-1.44], and KIM-1: 1.64[1.38-2.05]). Associations persisted after multivariable adjustment for clinical characteristics. Thus, during clinically silent progression of CHF, glomerular and tubular functions deteriorate, but not simultaneously. Hence, patient-specific evolutions of these renal markers dynamically predict clinical outcome in patients with CHF. Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

How learning analytics can early predict under-achieving students in a blended medical education course.

PubMed

Saqr, Mohammed; Fors, Uno; Tedre, Matti

2017-07-01

Learning analytics (LA) is an emerging discipline that aims at analyzing students' online data in order to improve the learning process and optimize learning environments. It has yet un-explored potential in the field of medical education, which can be particularly helpful in the early prediction and identification of under-achieving students. The aim of this study was to identify quantitative markers collected from students' online activities that may correlate with students' final performance and to investigate the possibility of predicting the potential risk of a student failing or dropping out of a course. This study included 133 students enrolled in a blended medical course where they were free to use the learning management system at their will. We extracted their online activity data using database queries and Moodle plugins. Data included logins, views, forums, time, formative assessment, and communications at different points of time. Five engagement indicators were also calculated which would reflect self-regulation and engagement. Students who scored below 5% over the passing mark were considered to be potentially at risk of under-achieving. At the end of the course, we were able to predict the final grade with 63.5% accuracy, and identify 53.9% of at-risk students. Using a binary logistic model improved prediction to 80.8%. Using data recorded until the mid-course, prediction accuracy was 42.3%. The most important predictors were factors reflecting engagement of the students and the consistency of using the online resources. The analysis of students' online activities in a blended medical education course by means of LA techniques can help early predict underachieving students, and can be used as an early warning sign for timely intervention.

Drug-gene modeling in pediatric T-cell acute lymphoblastic leukemia highlights importance of 6-mercaptopurine for outcome.

PubMed

Beesley, Alex H; Firth, Martin J; Anderson, Denise; Samuels, Amy L; Ford, Jette; Kees, Ursula R

2013-05-01

Patients relapsing with T-cell acute lymphoblastic leukemia (T-ALL) face a dismal outcome. The aim of this study was to identify new markers of drug resistance and clinical response in T-ALL. We measured gene expression and drug sensitivity in 15 pediatric T-ALL cell lines to find signatures predictive of resistance to 10 agents used in therapy. These were used to generate a model for outcome prediction in patient cohorts using microarray data from diagnosis specimens. In three independent T-ALL cohorts, the 10-drug model was able to accurately identify patient outcome, indicating that the in vitro-derived drug-gene profiles were clinically relevant. Importantly, predictions of outcome within each cohort were linked to distinct drugs, suggesting that different mechanisms contribute to relapse. Sulfite oxidase (SUOX) expression and the drug-transporter ABCC1 (MRP1) were linked to thiopurine sensitivity, suggesting novel pathways for targeting resistance. This study advances our understanding of drug resistance in T-ALL and provides new markers for patient stratification. The results suggest potential benefit from the earlier use of 6-mercaptopurine in T-ALL therapy or the development of adjuvants that may sensitize blasts to this drug. The methodology developed in this study could be applied to other cancers to achieve patient stratification at the time of diagnosis.

A systematic review of first trimester biochemical and molecular predictive tests for preeclampsia.

PubMed

Abdi, Fatemeh; Aghaie, Zohreh; Rahnemaie, Fatemeh Sadat; Alimoradi, Zainab

2018-04-16

Preeclampsia is a multisystem disorder affecting 5%-8% of pregnant women. Considering the ongoing debate over the predicting value of some commercial first trimester tests, the aim of this study was to compare the existing first trimester screening tests for preeclampsia. In this systematic review, relevant articles published during 2000-2017 were extracted from PubMed, Science Direct, Scopus, Cochrane Library, ISI Web of Science, and ProQuest databases. After thorough evaluation of the 412 potentially eligible papers, only 26 papers were selected based on the inclusion criteria. From a total of 412 retrieved studies, 28 papers were found eligible. Most studies had case-control or nested case-control designs. A total of 15164 pregnant women were evaluated in the reviewed studies. Various tests were applied in the first trimester of pregnancy to predict the development of preeclampsia. The most commonly used biomarkers were uterine artery pulsatility index, pregnancy-associated plasma protein A (PAPP-A), adiponectin, human chorionic gonadotropin (hCG) hormone and inhibin-A. Other tests were used in only one or two studies. Based on this review, a combination of markers should be evaluated for the identification of high risk women. Novel methods measuring multiple markers will hopefully facilitate the development of clinically effective screening programs in the future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Sensitivity to structure in action sequences: An infant event-related potential study.

PubMed

Monroy, Claire D; Gerson, Sarah A; Domínguez-Martínez, Estefanía; Kaduk, Katharina; Hunnius, Sabine; Reid, Vincent

2017-05-06

Infants are sensitive to structure and patterns within continuous streams of sensory input. This sensitivity relies on statistical learning, the ability to detect predictable regularities in spatial and temporal sequences. Recent evidence has shown that infants can detect statistical regularities in action sequences they observe, but little is known about the neural process that give rise to this ability. In the current experiment, we combined electroencephalography (EEG) with eye-tracking to identify electrophysiological markers that indicate whether 8-11-month-old infants detect violations to learned regularities in action sequences, and to relate these markers to behavioral measures of anticipation during learning. In a learning phase, infants observed an actor performing a sequence featuring two deterministic pairs embedded within an otherwise random sequence. Thus, the first action of each pair was predictive of what would occur next. One of the pairs caused an action-effect, whereas the second did not. In a subsequent test phase, infants observed another sequence that included deviant pairs, violating the previously observed action pairs. Event-related potential (ERP) responses were analyzed and compared between the deviant and the original action pairs. Findings reveal that infants demonstrated a greater Negative central (Nc) ERP response to the deviant actions for the pair that caused the action-effect, which was consistent with their visual anticipations during the learning phase. Findings are discussed in terms of the neural and behavioral processes underlying perception and learning of structured action sequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Privacy-preserving genomic testing in the clinic: a model using HIV treatment

PubMed Central

McLaren, Paul J.; Raisaro, Jean Louis; Aouri, Manel; Rotger, Margalida; Ayday, Erman; Bartha, István; Delgado, Maria B.; Vallet, Yannick; Günthard, Huldrych F.; Cavassini, Matthias; Furrer, Hansjakob; Doco-Lecompte, Thanh; Marzolini, Catia; Schmid, Patrick; Di Benedetto, Caroline; Decosterd, Laurent A.; Fellay, Jacques; Hubaux, Jean-Pierre; Telenti, Amalio

2016-01-01

Purpose: The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. Genet Med 18 8, 814–822. Methods: We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. Genet Med 18 8, 814–822. Results: A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. Genet Med 18 8, 814–822. Conclusions: The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine. Genet Med 18 8, 814–822. PMID:26765343

Molecular biomarkers for chronological age in animal ecology.

PubMed

Jarman, Simon N; Polanowski, Andrea M; Faux, Cassandra E; Robbins, Jooke; De Paoli-Iseppi, Ricardo; Bravington, Mark; Deagle, Bruce E

2015-10-01

The chronological age of an individual animal predicts many of its biological characteristics, and these in turn influence population-level ecological processes. Animal age information can therefore be valuable in ecological research, but many species have no external features that allow age to be reliably determined. Molecular age biomarkers provide a potential solution to this problem. Research in this area of molecular ecology has so far focused on a limited range of age biomarkers. The most commonly tested molecular age biomarker is change in average telomere length, which predicts age well in a small number of species and tissues, but performs poorly in many other situations. Epigenetic regulation of gene expression has recently been shown to cause age-related modifications to DNA and to cause changes in abundance of several RNA types throughout animal lifespans. Age biomarkers based on these epigenetic changes, and other new DNA-based assays, have already been applied to model organisms, humans and a limited number of wild animals. There is clear potential to apply these marker types more widely in ecological studies. For many species, these new approaches will produce age estimates where this was previously impractical. They will also enable age information to be gathered in cross-sectional studies and expand the range of demographic characteristics that can be quantified with molecular methods. We describe the range of molecular age biomarkers that have been investigated to date and suggest approaches for developing the newer marker types as age assays in nonmodel animal species. © 2015 John Wiley & Sons Ltd.

Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's disease neuroimaging initiative.

PubMed

Gomar, Jesus J; Bobes-Bascaran, Maria T; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

2011-09-01

Biomarkers have become increasingly important in understanding neurodegenerative processes associated with Alzheimer disease. Markers include regional brain volumes, cerebrospinal fluid measures of pathological Aβ1-42 and total tau, cognitive measures, and individual risk factors. To determine the discriminative utility of different classes of biomarkers and cognitive markers by examining their ability to predict a change in diagnostic status from mild cognitive impairment to Alzheimer disease. Longitudinal study. We analyzed the Alzheimer's Disease Neuroimaging Initiative database to study patients with mild cognitive impairment who converted to Alzheimer disease (n = 116) and those who did not convert (n = 204) within a 2-year period. We determined the predictive utility of 25 variables from all classes of markers, biomarkers, and risk factors in a series of logistic regression models and effect size analyses. The Alzheimer's Disease Neuroimaging Initiative public database. Primary outcome measures were odds ratios, pseudo- R(2)s, and effect sizes. In comprehensive stepwise logistic regression models that thus included variables from all classes of markers, the following baseline variables predicted conversion within a 2-year period: 2 measures of delayed verbal memory and middle temporal lobe cortical thickness. In an effect size analysis that examined rates of decline, change scores for biomarkers were modest for 2 years, but a change in an everyday functional activities measure (Functional Assessment Questionnaire) was considerably larger. Decline in scores on the Functional Assessment Questionnaire and Trail Making Test, part B, accounted for approximately 50% of the predictive variance in conversion from mild cognitive impairment to Alzheimer disease. Cognitive markers at baseline were more robust predictors of conversion than most biomarkers. Longitudinal analyses suggested that conversion appeared to be driven less by changes in the neurobiologic trajectory of the disease than by a sharp decline in functional ability and, to a lesser extent, by declines in executive function.

Derivation of genetic biomarkers for cancer risk stratification in Barrett's oesophagus: a prospective cohort study.

PubMed

Timmer, Margriet R; Martinez, Pierre; Lau, Chiu T; Westra, Wytske M; Calpe, Silvia; Rygiel, Agnieszka M; Rosmolen, Wilda D; Meijer, Sybren L; Ten Kate, Fiebo J W; Dijkgraaf, Marcel G W; Mallant-Hent, Rosalie C; Naber, Anton H J; van Oijen, Arnoud H A M; Baak, Lubbertus C; Scholten, Pieter; Böhmer, Clarisse J M; Fockens, Paul; Maley, Carlo C; Graham, Trevor A; Bergman, Jacques J G H M; Krishnadath, Kausilia K

2016-10-01

The risk of developing adenocarcinoma in non-dysplastic Barrett's oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers. In a prospective cohort of patients with non-dysplastic Barrett's oesophagus, we evaluated six molecular markers: p16, p53, Her-2/neu, 20q, MYC and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional-hazards models, receiver operating characteristic curves and a leave-one-out analysis. A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett's length, and the markers, p16 loss, MYC gain and aneusomy, were significantly associated with progression on univariate analysis. We defined an 'Abnormal Marker Count' that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett's length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI 2.6 to 29.8) increased HR when compared with the low-risk group, with an area under the curve of 0.76 (95% CI 0.66 to 0.86). A prediction model based on age, Barrett's length and the markers p16, MYC and aneusomy determines progression risk in non-dysplastic Barrett's oesophagus. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

PubMed

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

PubMed Central

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

New molecular markers and cytogenetic probes enable chromosome identification of wheat-Thinopyrum intermedium introgression lines for improving protein and gluten contents.

PubMed

Li, Guangrong; Wang, Hongjin; Lang, Tao; Li, Jianbo; La, Shixiao; Yang, Ennian; Yang, Zujun

2016-10-01

New molecular markers were developed for targeting Thinopyrum intermedium 1St#2 chromosome, and novel FISH probe representing the terminal repeats was produced for identification of Thinopyrum chromosomes. Thinopyrum intermedium has been used as a valuable resource for improving the disease resistance and yield potential of wheat. A wheat-Th. intermedium ssp. trichophorum chromosome 1St#2 substitution and translocation has displayed superior grain protein and wet gluten content. With the aim to develop a number of chromosome 1St#2 specific molecular and cytogenetic markers, a high throughput, low-cost specific-locus amplified fragment sequencing (SLAF-seq) technology was used to compare the sequences between a wheat-Thinopyrum 1St#2 (1D) substitution and the related species Pseudoroegneria spicata (St genome, 2n = 14). A total of 5142 polymorphic fragments were analyzed and 359 different SLAF markers for 1St#2 were predicted. Thirty-seven specific molecular markers were validated by PCR from 50 randomly selected SLAFs. Meanwhile, the distribution of transposable elements (TEs) at the family level between wheat and St genomes was compared using the SLAFs. A new oligo-nucleotide probe named Oligo-pSt122 from high SLAF reads was produced for fluorescence in situ hybridization (FISH), and was observed to hybridize to the terminal region of 1St#L and also onto the terminal heterochromatic region of Th. intermedium genomes. The genome-wide markers and repetitive based probe Oligo-pSt122 will be valuable for identifying Thinopyrum chromosome segments in wheat backgrounds.

Developing Rice with High Yield under Phosphorus Deficiency: Pup1 Sequence to Application1[W][OA

PubMed Central

Chin, Joong Hyoun; Gamuyao, Rico; Dalid, Cheryl; Bustamam, Masdiar; Prasetiyono, Joko; Moeljopawiro, Sugiono; Wissuwa, Matthias; Heuer, Sigrid

2011-01-01

The major quantitative trait locus (QTL) Phosphorus uptake1 (Pup1) confers tolerance of phosphorus deficiency in soil and is currently one of the most promising QTLs for the development of tolerant rice (Oryza sativa) varieties. To facilitate targeted introgression of Pup1 into intolerant varieties, the gene models predicted in the Pup1 region in the donor variety Kasalath were used to develop gene-based molecular markers that are evenly distributed over the fine-mapped 278-kb QTL region. To validate the gene models and optimize the markers, gene expression analyses and partial allelic sequencing were conducted. The markers were tested in more than 80 diverse rice accessions revealing three main groups with different Pup1 allele constitution. Accessions with tolerant (group I) and intolerant (group III) Pup1 alleles were distinguished from genotypes with Kasalath alleles at some of the analyzed loci (partial Pup1; group II). A germplasm survey additionally confirmed earlier data showing that Pup1 is largely absent from irrigated rice varieties but conserved in varieties and breeding lines adapted to drought-prone environments. A core set of Pup1 markers has been defined, and sequence polymorphisms suitable for single-nucleotide polymorphism marker development for high-throughput genotyping were identified. Following a marker-assisted backcrossing approach, Pup1 was introgressed into two irrigated rice varieties and three Indonesian upland varieties. First phenotypic evaluations of the introgression lines suggest that Pup1 is effective in different genetic backgrounds and environments and that it has the potential to significantly enhance grain yield under field conditions. PMID:21602323

SNPs selection using support vector regression and genetic algorithms in GWAS

PubMed Central

2014-01-01

Introduction This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. Results The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. Conclusions The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels. PMID:25573332

Biomarkers of oxidative status: missing tools in conservation physiology.

PubMed

Beaulieu, Michaël; Costantini, David

2014-01-01

Recent ecological studies have shown that oxidative status could have a significant impact on fitness components in wild animals. Not only can oxidative status reflect the environmental conditions that animals experience, but it can also predict their chances of reproduction and survival in the future in their natural habitat. Such important characteristics make markers of oxidative status informative tools to evaluate a priori individual perspectives of reproduction and survival as well as to assess a posteriori the effect of human activities on the fitness of species of conservation concern and wildlife in general. Markers of oxidative status may therefore help conservation practitioners to identify conservation threats to animal populations and to maximize the success of wildlife management. Despite these potential benefits for animal conservation programmes, up to now markers of oxidative status have only been reported anecdotally in conservation studies. The aim of this review is therefore to raise awareness by conservation practitioners of the use of markers of oxidative status. Towards this end, we first describe how environmental disruptions due to human activities can translate into variation in oxidative status. Second, we show how individual and population variation in oxidative status may contribute to the success or the failure of reintroduction or translocation programmes. Finally, we emphasize the technical features specific to the measurement of markers of oxidative status in conservation programmes, which may help investigators with the interpretation of their results. Such prior knowledge about markers of oxidative status may encourage conservation physiologists to use them in order to enhance the success of conservation programmes and wildlife management.

Biomarkers of oxidative status: missing tools in conservation physiology

PubMed Central

Beaulieu, Michaël; Costantini, David

2014-01-01

Recent ecological studies have shown that oxidative status could have a significant impact on fitness components in wild animals. Not only can oxidative status reflect the environmental conditions that animals experience, but it can also predict their chances of reproduction and survival in the future in their natural habitat. Such important characteristics make markers of oxidative status informative tools to evaluate a priori individual perspectives of reproduction and survival as well as to assess a posteriori the effect of human activities on the fitness of species of conservation concern and wildlife in general. Markers of oxidative status may therefore help conservation practitioners to identify conservation threats to animal populations and to maximize the success of wildlife management. Despite these potential benefits for animal conservation programmes, up to now markers of oxidative status have only been reported anecdotally in conservation studies. The aim of this review is therefore to raise awareness by conservation practitioners of the use of markers of oxidative status. Towards this end, we first describe how environmental disruptions due to human activities can translate into variation in oxidative status. Second, we show how individual and population variation in oxidative status may contribute to the success or the failure of reintroduction or translocation programmes. Finally, we emphasize the technical features specific to the measurement of markers of oxidative status in conservation programmes, which may help investigators with the interpretation of their results. Such prior knowledge about markers of oxidative status may encourage conservation physiologists to use them in order to enhance the success of conservation programmes and wildlife management. PMID:27293635

Combination of long noncoding RNA MALAT1 and carcinoembryonic antigen for the diagnosis of malignant pleural effusion caused by lung cancer.

PubMed

Wang, Wan-Wei; Zhou, Xi-Lei; Song, Ying-Jian; Yu, Chang-Hua; Zhu, Wei-Guo; Tong, Yu-Suo

2018-01-01

Long noncoding RNAs (lncRNAs) are present in body fluids, but their potential as tumor biomarkers has never been investigated in malignant pleural effusion (MPE) caused by lung cancer. The aim of this study was to assess the clinical significance of lncRNAs in pleural effusion, which could potentially serve as diagnostic and predictive markers for lung cancer-associated MPE (LC-MPE). RNAs from pleural effusion were extracted in 217 cases of LC-MPE and 132 cases of benign pleural effusion (BPE). Thirty-one lung cancer-associated lncRNAs were measured using quantitative real-time polymerase chain reaction (qRT-PCR). The level of carcinoembryonic antigen (CEA) was also determined. The receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were established to evaluate the sensitivity and specificity of the identified lncRNAs and other biomarkers. The correlations between baseline pleural effusion lncRNAs expression and response to chemotherapy were also analyzed. Three lncRNAs ( MALAT1 , H19 , and CUDR ) were found to have potential as diagnostic markers in LC-MPE. The AUCs for MALAT1 , H19 , CUDR , and CEA were 0.891, 0.783, 0.824, and 0.826, respectively. Using a logistic model, the combination of MALAT1 and CEA (AUC, 0.924) provided higher sensitivity and accuracy in predicting LC-MPE than CEA (AUC, 0.826) alone. Moreover, baseline MALAT1 expression in pleural fluid was inversely correlated with chemotherapy response in patients with LC-MPE. Pleural effusion lncRNAs were effective in differentiating LC-MPE from BPE. The combination of MALAT1 and CEA was more effective for LC-MPE diagnosis.

Oxidative stress and neurobehavioral problems in pediatric acute lymphoblastic leukemia patients undergoing chemotherapy.

PubMed

Stenzel, Stephanie L; Krull, Kevin R; Hockenberry, Marilyn; Jain, Neelam; Kaemingk, Kris; Miketova, Petra; Moore, Ida M

2010-03-01

Neurobehavioral problems after chemotherapy treatment for pediatric acute lymphoblastic leukemia (ALL) have been a recent focus of investigation. This study extended previous research that suggested oxidative stress as a potential mechanism for chemotherapy-induced central nervous system injury by examining early markers of oxidative stress in relation to subsequent neurobehavioral problems. Oxidized and unoxidized components of phosphatidylcholine (PC) were measured in the cerebrospinal fluid of 87 children with ALL at diagnosis, induction, and consolidation. Behavioral assessments were conducted postconsolidation and at the end of chemotherapy. Results revealed a significant association between physiologic reactivity (high vs. low PC changes from diagnosis) and behavioral outcomes (high vs. low pathology). Elevated oxidized PC fraction change was predictive of increased problems with aggression at the end of therapy as well as postconsolidation adaptability. Furthermore, symptoms of hyperactivity systematically changed over time in relation to both unoxidized PC and oxidized PC fraction reactivity. These findings suggest that symptoms of behavioral problems occur early in the course of chemotherapy and that increases in the cerebrospinal fluid PC markers of oxidative stress during induction and consolidation may help to predict certain future behavioral problems.

Brucella melitensis VirB12 recombinant protein is a potential marker for serodiagnosis of human brucellosis.

PubMed

Mirkalantari, Shiva; Zarnani, Amir-Hassan; Nazari, Mahboobeh; Irajian, Gholam Reza; Amirmozafari, Nour

2017-03-03

The numerous drawbacks of current serological tests for diagnosis of brucellosis which mainly results from cross reactivity with LPS from other gram-negative bacteria have generated an increasing interest to find more specific non-LPS antigens. Previous studies had indicated that Brucella VirB12 protein, a cell surface protein and component of type IV secretion system, induces antibody response during animal infection. However, this protein has not yet been tested as a serological diagnostic marker in human brucellosis. Recombinant VirB12 protein was prepared and evaluated the efficacy of it in an indirect enzyme-linked immunosorbent assay (ELISA) for brucellosis with sera collected from different region of Iran and the results were compared with a commercial ELISA kit. Sera from human brucellosis patients strongly reacted to the purified recombinant VirB12. The sensitivity, specificity, accuracy, negative predictive value and positive predictive value of recombinant VirB12-based ELISA related to the commercial-ELISA method were 87.8, 94, 90, 80 and 96.6% respectively. We concluded that antigenic VirB12 have a property value that can be considered as a candidate for using in serodiagnostic tests for human brucellosis.

Peptide selection and antibody generation for the prospective immunorecognition of Cry1Ab16 protein of transgenic maize.

PubMed

Costa, Joana; Marani, Mariela M; Grazina, Liliana; Villa, Caterina; Meira, Liliana; Oliveira, M Beatriz P P; Leite, José R S A; Mafra, Isabel

2017-09-15

The introduction of genes isolated from different Bacillus thuringiensis strains to express Cry-type toxins in transgenic crops is a common strategy to confer insect resistance traits. This work intended to extensively in silico analyse Cry1A(b)16 protein for the identification of peptide markers for the biorecognition of transgenic crops. By combining two different strategies based on several bioinformatic tools for linear epitope prediction, a set of seven peptides was successfully selected as potential Cry1A(b)16 immunogens. For the prediction of conformational epitopes, Cry1A(b)16 models were built on the basis of three independent templates of homologue proteins of Cry1A(a) and Cry1A(c) using an integrated approach. PcH_736-746 and PcH_876-886 peptides were selected as the best candidates, being synthesised and used for the production of polyclonal antibodies. To the best of our knowledge, this is the first attempt of selecting and defining linear peptides as immunogenic markers of Cry1A(b)-type toxins in transgenic maize. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Breed Composition Using Breed Frequencies of 50,000 Markers from the U.S. Meat Animal Research Center 2,000 Bull Project

USDA-ARS?s Scientific Manuscript database

Our objective was to evaluate whether breed composition of crossbred cattle could be predicted using reference breed frequencies of SNP markers on the BovineSNP50 array. Semen DNA samples of over 2,000 bulls from 16 common commercial beef breeds were genotyped using the array and used to estimate cu...

Short and long term prognosis in perinatal asphyxia: An update

PubMed Central

Ahearne, Caroline E; Boylan, Geraldine B; Murray, Deirdre M

2016-01-01

Interruption of blood flow and gas exchange to the fetus in the perinatal period, known as perinatal asphyxia, can, if significant, trigger a cascade of neuronal injury, leading on to neonatal encephalopathy (NE) and resultant long-term damage. While the majority of infants who are exposed to perinatal hypoxia-ischaemia will recover quickly and go on to have a completely normal survival, a proportion will suffer from an evolving clinical encephalopathy termed hypoxic-ischaemic encephalopathy (HIE) or NE if the diagnosis is unclear. Resultant complications of HIE/NE are wide-ranging and may affect the motor, sensory, cognitive and behavioural outcome of the child. The advent of therapeutic hypothermia as a neuroprotective treatment for those with moderate and severe encephalopathy has improved prognosis. Outcome prediction in these infants has changed, but is more important than ever, as hypothermia is a time sensitive intervention, with a very narrow therapeutic window. To identify those who will benefit from current and emerging neuroprotective therapies we must be able to establish the severity of their injury soon after birth. Currently available indicators such as blood biochemistry, clinical examination and electrophysiology are limited. Emerging biological and physiological markers have the potential to improve our ability to select those infants who will benefit most from intervention. Biomarkers identified from work in proteomics, metabolomics and transcriptomics as well as physiological markers such as heart rate variability, EEG analysis and radiological imaging when combined with neuroprotective measures have the potential to improve outcome in HIE/NE. The aim of this review is to give an overview of the literature in regards to short and long-term outcome following perinatal asphyxia, and to discuss the prediction of this outcome in the early hours after birth when intervention is most crucial; looking at both currently available tools and introducing novel markers. PMID:26862504

Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis

PubMed Central

Craig-Schapiro, Rebecca; Kuhn, Max; Xiong, Chengjie; Pickering, Eve H.; Liu, Jingxia; Misko, Thomas P.; Perrin, Richard J.; Bales, Kelly R.; Soares, Holly; Fagan, Anne M.; Holtzman, David M.

2011-01-01

Background Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10–15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181). Methods and Findings Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age. Conclusions/Significance Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best current CSF biomarkers for distinguishing very mildly/mildly demented from cognitively normal individuals. Additionally, we identified a novel biomarker (calbindin) with significant prognostic potential. PMID:21526197

Interruption or deferral of antiretroviral therapy reduces markers of bone turnover compared with continuous therapy: the SMART Body Composition Substudy

PubMed Central

Hoy, Jennifer; Grund, Birgit; Roediger, Mollie; Ensrud, Kristine E.; Brar, Indira; Colebunders, Robert; De Castro, Nathalie; Johnson, Margaret; Sharma, Anjali; Carr, Andrew

2013-01-01

Bone mineral density (BMD) declines significantly in HIV patients on antiretroviral therapy (ART). We compared the effects of intermittent versus continuous ART on markers of bone turnover in the Body Composition substudy of the Strategies for Management of AntiRetroviral Therapy (SMART) trial and determined whether early changes in markers predicted subsequent change in BMD. For 202 participants (median age 44 years, 17% female, 74% on ART) randomised to continuous or intermittent ART, plasma markers of inflammation and bone turnover were evaluated at baseline, months 4 and 12; BMD at the spine (dual X-ray absorptiometry [DXA] and computed tomography) and hip (DXA) was evaluated annually. Compared to the continuous ART group, mean bone-specific alkaline phosphatase (bALP), osteocalcin, procollagen type 1 N-terminal propeptide (P1NP), N-terminal cross-linking telopeptide of type 1 collagen (NTX), and C-terminal cross-linking telopeptide of type 1 collagen (βCTX) decreased significantly in the intermittent ART group, whereas RANKL and the RANKL:osteoprotegerin (OPG) ratio increased (all p≤0.002 at month 4 and month 12). Increases in bALP, osteocalcin, P1NP, NTX, and βCTX at month 4 predicted decrease in hip BMD at month 12, while increases in RANKL and the RANKL:OPG ratio at month 4 predicted increase in hip and spine BMD at month 12. This study has shown that compared with continuous ART, interruption of ART results in a reduction in markers of bone turnover and increase in BMD at hip and spine, and that early changes in markers of bone turnover predict BMD changes at 12 months. PMID:23299909

KRAS oncogene in non-small cell lung cancer: clinical perspectives on the treatment of an old target.

PubMed

Román, Marta; Baraibar, Iosune; López, Inés; Nadal, Ernest; Rolfo, Christian; Vicent, Silvestre; Gil-Bazo, Ignacio

2018-02-19

Lung neoplasms are the leading cause of death by cancer worldwide. Non-small cell lung cancer (NSCLC) constitutes more than 80% of all lung malignancies and the majority of patients present advanced disease at onset. However, in the last decade, multiple oncogenic driver alterations have been discovered and each of them represents a potential therapeutic target. Although KRAS mutations are the most frequently oncogene aberrations in lung adenocarcinoma patients, effective therapies targeting KRAS have yet to be developed. Moreover, the role of KRAS oncogene in NSCLC remains unclear and its predictive and prognostic impact remains controversial. The study of the underlying biology of KRAS in NSCLC patients could help to determine potential candidates to evaluate novel targeted agents and combinations that may allow a tailored treatment for these patients. The aim of this review is to update the current knowledge about KRAS-mutated lung adenocarcinoma, including a historical overview, the biology of the molecular pathways involved, the clinical relevance of KRAS mutations as a prognostic and predictive marker and the potential therapeutic approaches for a personalized treatment of KRAS-mutated NSCLC patients.

Emotional Intelligence as a Predictor of Academic and/or Professional Success

PubMed Central

Cain, Jeff; Smith, Kelly M.

2006-01-01

The concept of “emotional intelligence” has been extensively popularized in the lay press and corporate world as individuals purport the potential ability of emotional intelligence to predict various markers of success. Emotional intelligence (EI) most commonly incorporates concepts of emotional expression and regulation, self-awareness, and empathy. The concept has been criticized by some for its loose definition and parallels to personality traits. Additionally, several limitations to the instruments used to measure emotional intelligence have been identified. This review examines the foundations of the definitions of emotional intelligence as well as existing educational research involving emotional intelligence, both within the health professions and externally. Recommendations for future research and research potential are discussed. PMID:17136189

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

A Biodosimeter for Multiparametric Determination of Radiation Dose, Radiation Quality, and Radiation Risk

NASA Technical Reports Server (NTRS)

Richmond, Robert; Cruz, Angela; Jansen, Heather; Bors, Karen

2003-01-01

Predicting risk of human cancer following exposure of an individual or a population to ionizing radiation is challenging. To an approximation, this is because uncertainties of uniform absorption of dose and the uniform processing of dose-related damage at the cellular level within a complex set of biological variables degrade the confidence of predicting the delayed expression of cancer as a relatively rare event. Cellular biodosimeters that simultaneously report: 1) the quantity of absorbed dose after exposure to ionizing radiation, 2) the quality of radiation delivering that dose, and 3) the risk of developing cancer by the cells absorbing that dose would therefore be useful. An approach to such a multiparametric biodosimeter will be reported. This is the demonstration of a dose responsive field effect of enhanced expression of keratin 18 (K18) in cultures of human mammary epithelial cells irradiated with cesium-1 37 gamma-rays. Dose response of enhanced K18 expression was experimentally extended over a range of 30 to 90 cGy for cells evaluated at mid-log phase. K18 has been reported to be a marker for tumor staging and for apoptosis, and thereby serves as an example of a potential marker for cancer risk, where the reality of such predictive value would require additional experimental development. Since observed radiogenic increase in expression of K18 is a field effect, ie., chronically present in all cells of the irradiated population, it may be hypothesized that K18 expression in specific cells absorbing particulate irradiation, such as the high-LET-producing atomic nuclei of space radiation, will report on both the single-cell distributions of those particles amongst cells within the exposed population, and that the relatively high dose per cell delivered by densely ionizing tracks of those intersecting particles will lead to cell-specific high-expression levels of K18, thereby providing analytical end points that may be used to resolve both the quantity and the quality of the radiation dose absorbed by individual cells. The principal value of this reported potential multiparametric cellular biodosimeter is suggested to be that it justifies a search for similar but more robust radiogenic assays. That is, K18 is only one radiation dose-sensitive expressed protein, whereas analytical techniques of genomics and proteomics can be used to simultaneously analyze multiple gene and protein expressions resulting from radiation-dose absorption. The potential usefulness of multiparametric cellular biodosimeters will be best realized from quantitatively profiling these multiple markers using these modern techniques.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

PubMed

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

СD44+/CD24- markers of cancer stem cells in patients with breast cancer of different molecular subtypes.

PubMed

Chekhun, S V; Zadvorny, T V; Tymovska, Yu O; Anikusko, M F; Novak, O E; Polishchuk, L Z

2015-03-01

To determine frequency of tumors with immunohistochemical markers of cancer stem cells (CSC) CD44+/CD24- in patients with breast cancer (BC) of different molecular subtype and to evaluate their prognostic value. Surgical material of 132 patients with BC stage I-II, age from 23 to 75 years, mean age - 50.2 ± 3.1 years was studied. Clinical, immunohistochemical (expression CD44+/CD24-), morphological, statistical. BC is characterized by heterogeneity of molecular subtypes and expression of markers (CD44+/CD24-). Immunohistochemical study of expression of CSC markers in surgical material has detected their expression in 34 (25.4%) patients with BC of different molecular subtypes. The highest frequency of cells with expression of CSC marker was observed in patients with basal molecular subtype (44.8% patients). Most of BC patients with phenotype CD44+/CD24 had stage I of tumor process (34.3%). Statistical processing of data has showen that Yule colligation coefficient equaled 0.28 (р > 0.05) that argues poor correlation between stage of tumor process and number of tumors with positive expression of CSC markers. Statistical processing of data has showen high correlation between presence of cells with expression of CSC markers and metastases of BC in regional lymph nodes (Yule colligation coefficient equals 0.943; р < 0.5). Difference in overall survival of patients with BC of basal molecular subtype depending on expression of CSC CD44+/CD24- markers was detected. Survival of patients with basal BC was reliably higher at lack in tumors of cells with CSC markers CD44+/CD24- and, correspondingly, lower at presence of such cells (р < 0.05). In patients with BC of luminal (A and B), HER-2-positive subtypes, significant change in survival of patients depending on expression of CSC markers was not determined (р > 0.05). Significance of tumor cells with markers CD44+/CD24- within the limits of molecular subtype of BC may be additional criterion for advanced biological characteristic of BC, and in patients with BC of basal molecular subtype - for predictive evaluation of individual potential of tumor to aggressive clinical course.

Early predicted time to normalization of tumor markers predicts outcome in poor-prognosis nonseminomatous germ cell tumors.

PubMed

Fizazi, Karim; Culine, Stéphane; Kramar, Andrew; Amato, Robert J; Bouzy, Jeannine; Chen, Isan; Droz, Jean-Pierre; Logothetis, Christopher J

2004-10-01

The prognostic relevance of the rate of decline of serum alpha-fetoprotein (AFP) and human chorionic gonadotropin (HCG) during the first 3 weeks of chemotherapy for nonseminomatous germ cell tumors (NSGCT) was studied in the context of the International Germ Cell Cancer Collaborative Group (IGCCCG) classification. Data from 653 patients prospectively recruited in clinical trials were studied. Tumor markers were obtained before chemotherapy and 3 weeks later. Decline rates were calculated using a logarithmic formula and expressed as a predicted time to normalization (TTN). A favorable TTN was defined when both AFP and HCG had a favorable decline rate, including cases with normal values. The median follow-up was 50 months (range, 2 to 151 months). Tumor decline rate expressed as a predicted TTN was associated with both progression-free survival (PFS; P <.0001) and overall survival (OS; P <.0001). The 4-year PFS rates were 64% and 38% in patients from the poor-prognosis group who had a favorable and an unfavorable TTN, respectively. The 4-year OS rates were 83% and 58%, respectively. This effect was independent from the initial tumor marker values, the primary tumor site, and the presence of nonpulmonary visceral metastases: tumor marker decline rate remained a strong predictor for both PFS (hazard ratio = 2.5; P =.01) and OS (hazard ratio = 4.6; P =.002) in patients from the IGCCCG poor-prognosis group in multivariate analysis. Early predicted time to tumor marker normalization is an independent prognostic factor in patients with poor-prognosis NSGCT and may be a useful tool in the therapeutic management of these patients.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malinowski, Kathleen T.; Fischell Department of Bioengineering, University of Maryland, College Park, MD; McAvoy, Thomas J.

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precisionmore » in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.« less

Reliability increases from combining 50,000- and 777,000-marker genotypes from four countries

USDA-ARS?s Scientific Manuscript database

Genomic predictions were compared on U.S. scale after combining 50,000 (50K) and 777,000 (HD) marker genotypes across countries. The genotyped Holsteins included 161,341 animals with five marker densities including 1,510 with HD. Imputation was more accurate with FImpute than with findhap across the...

The Predictive Value of Coefficient of PCT × BG for Anastomotic Leak in Esophageal Carcinoma Patients With ARDS After Esophagectomy.

PubMed

Li, Huan; Wang, Daofeng; Wei, Wenxiao; Ouyang, Lamei; Lou, Ning

2017-01-01

Anastomotic leak was a potentially severe life-threatening complication of esophagectomy, which drew attention in consequence of progressive dyspnea until acute respiratory distress syndrome (ARDS) due to the early asymptomatic presentation. Respiratory failure, caused by ARDS as the severe presentation of anastomotic leak, is the most common organ failure. CRP (C-reactive protein), procalcitonin (PCT), and Blood G (BG) test are the sensitivity markers for inflammatory, sepsis, and fungemia, respectively. Early recognition and intervention treatment of anastomotic leak may alleviate complication and improve outcome. We retrospectively analyzed 71 patients, accepting mechanical ventilation support because of ARDS as the complication after radical resection of esophagus cancer. Clinical data were collected from the patients' electronic medical records, including their clinically hematological examination, drainage fluid cultures, and sputum culture. Accord to appearance of anastomotic leak or not, all patients were divided into 2 groups, leak group and no-leak group. Inflammatory markers, such as CRP, PCT, and the coefficient of BG and PCT, were significantly different between the 2 groups. Respiratory index, white blood cell, hemoglobin (HBG), platelet (PLT), and other clinical factors were not significantly different between the 2 groups. Receiver operating characteristic curves were constructed to calculate the sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve for various cutoff levels of several factors. Blood G tests presented the better predicting value for anastomotic leak. Blood G tests and PCT should be tested after esophagectomy. The coefficient of PCT and BG (>260) is of great significance, and clinical value to predict anastomotic leak for patients with postesophagectomy ARDS, early PCT and BG test, and especially, dynamic variation may alleviate complication and improve outcome.

HumanMethylation450K Array–Identified Biomarkers Predict Tumour Recurrence/Progression at Initial Diagnosis of High-risk Non-muscle Invasive Bladder Cancer

PubMed Central

Kitchen, Mark O; Bryan, Richard T; Emes, Richard D; Luscombe, Christopher J; Cheng, KK; Zeegers, Maurice P; James, Nicholas D; Gommersall, Lyndon M; Fryer, Anthony A

2018-01-01

Background: High-risk non-muscle invasive bladder cancer (HR-NMIBC) is a clinically unpredictable disease. Despite clinical risk estimation tools, many patients are undertreated with intra-vesical therapies alone, whereas others may be over-treated with early radical surgery. Molecular biomarkers, particularly DNA methylation, have been reported as predictive of tumour/patient outcomes in numerous solid organ and haematologic malignancies; however, there are few reports in HR-NMIBC and none using genome-wide array assessment. We therefore sought to identify novel DNA methylation markers of HR-NMIBC clinical outcomes that might predict tumour behaviour at initial diagnosis and help guide patient management. Patients and methods: A total of 21 primary initial diagnosis HR-NMIBC tumours were analysed by Illumina HumanMethylation450 BeadChip arrays and subsequently bisulphite Pyrosequencing. In all, 7 had not recurred at 1 year after resection and 14 had recurred and/or progressed despite intra-vesical BCG. A further independent cohort of 32 HR-NMIBC tumours (17 no recurrence and 15 recurrence and/or progression despite BCG) were also assessed by bisulphite Pyrosequencing. Results: Array analyses identified 206 CpG loci that segregated non-recurrent HR-NMIBC tumours from clinically more aggressive recurrence/progression tumours. Hypermethylation of CpG cg11850659 and hypomethylation of CpG cg01149192 in combination predicted HR-NMIBC recurrence and/or progression within 1 year of diagnosis with 83% sensitivity, 79% specificity, and 83% positive and 79% negative predictive values. Conclusions: This is the first genome-wide DNA methylation analysis of a unique HR-NMIBC tumour cohort encompassing known 1-year clinical outcomes. Our analyses identified potential novel epigenetic markers that could help guide individual patient management in this clinically unpredictable disease. PMID:29343995

Fibroblast growth factor-2 (FGF2) and syndecan-1 (SDC1) are potential biomarkers for putative circulating CD15+/CD30+ cells in poor outcome Hodgkin lymphoma patients

PubMed Central

2013-01-01

Background High risk, unfavorable classical Hodgkin lymphoma (cHL) includes those patients with primary refractory or early relapse, and progressive disease. To improve the availability of biomarkers for this group of patients, we investigated both tumor biopsies and peripheral blood leukocytes (PBL) of untreated (chemo-naïve, CN) Nodular Sclerosis Classic Hodgkin Lymphoma (NS-cHL) patients for consistent biomarkers that can predict the outcome prior to frontline treatment. Methods and materials Bioinformatics data mining was used to generate 151 candidate biomarkers, which were screened against a library of 10 HL cell lines. Expression of FGF2 and SDC1 by CD30+ cells from HL patient samples representing good and poor outcomes were analyzed by qRT-PCR, immunohistochemical (IHC), and immunofluorescence analyses. Results To identify predictive HL-specific biomarkers, potential marker genes selected using bioinformatics approaches were screened against HL cell lines and HL patient samples. Fibroblast Growth Factor-2 (FGF2) and Syndecan-1 (SDC1) were overexpressed in all HL cell lines, and the overexpression was HL-specific when compared to 116 non-Hodgkin lymphoma tissues. In the analysis of stratified NS-cHL patient samples, expression of FGF2 and SDC1 were 245 fold and 91 fold higher, respectively, in the poor outcome (PO) group than in the good outcome (GO) group. The PO group exhibited higher expression of the HL marker CD30, the macrophage marker CD68, and metastatic markers TGFβ1 and MMP9 compared to the GO group. This expression signature was confirmed by qualitative immunohistochemical and immunofluorescent data. A Kaplan-Meier analysis indicated that samples in which the CD30+ cells carried an FGF2+/SDC1+ immunophenotype showed shortened survival. Analysis of chemo-naive HL blood samples suggested that in the PO group a subset of CD30+ HL cells had entered the circulation. These cells significantly overexpressed FGF2 and SDC1 compared to the GO group. The PO group showed significant down-regulation of markers for monocytes, T-cells, and B-cells. These expression signatures were eliminated in heavily pretreated patients. Conclusion The results suggest that small subsets of circulating CD30+/CD15+ cells expressing FGF2 and SDC1 represent biomarkers that identify NS-cHL patients who will experience a poor outcome (primary refractory and early relapsing). PMID:23988031

Assessment Effects of Resveratrol on Human Telomerase Reverse Transcriptase Messenger Ribonucleic Acid Transcript in Human Glioblastoma.

PubMed

Mirzazadeh, Azin; Kheirollahi, Majid; Farashahi, Ehsan; Sadeghian-Nodoushan, Fatemeh; Sheikhha, Mohammad Hasan; Aflatoonian, Behrouz

2017-01-01

Glioblastoma (GBM) is the most common and aggressive brain tumor, which has a poor prognosis despite the advent of different therapeutic strategies. There are numerous molecular biomarkers to contribute diagnosis, prognosis, and prediction of response to the current therapy in GBM. One of the most important markers that are potentially valuable is immortalization-specific or immortalization-associated marker named "hTERT messenger ribonucleic acid (mRNA)" the key subunit of telomerase enzyme, which is expressed in more than 85% of cancer cells, in spite of the majority of normal somatic cells. In this study, we investigated the effects of resveratrol (RSV) on this mRNA marker level, leading to cancer progression. U-87MG cell line was obtained from Pasteur Institute of Iran and treated with various concentrations of 0-160 μg/mL of RSV and at different time points (24, 48, and 72 h). To evaluate viability of U-87MG cells, standard 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay was performed. Real-time polymerase chain reaction (RT-PCR) was used for comparative and quantitative assessment of human telomerase reverse transcriptase (hTERT) mRNA copy number versus control-untreated group. The results of our investigation suggested that RSV effectively inhibited cell growth and caused cell death in dose-dependent ( P < 0.05) and not in time-dependent manner ( P > 0.05), in vitro . Interestingly, quantitative RT-PCR analysis demonstrated that at half inhibition concentration, RSV dramatically decreased mRNA expression of hTERT, the catalytic subunit of telomerase enzyme, which leads to prevention of cell division and tumor progression. With regard to downregulation of this immortalization-associated marker, RSV may potentially be used as a therapeutic agent against GBM.

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

NASA Astrophysics Data System (ADS)

Daye, Dania; Bobo, Ezra; Baumann, Bethany; Ioannou, Antonios; Conant, Emily F.; Maidment, Andrew D. A.; Kontos, Despina

2011-03-01

Mammographic parenchymal texture patterns have been shown to be related to breast cancer risk. Yet, little is known about the biological basis underlying this association. Here, we investigate the potential of mammographic parenchymal texture patterns as an inherent phenotypic imaging marker of endogenous hormonal exposure of the breast tissue. Digital mammographic (DM) images in the cranio-caudal (CC) view of the unaffected breast from 138 women diagnosed with unilateral breast cancer were retrospectively analyzed. Menopause status was used as a surrogate marker of endogenous hormonal activity. Retroareolar 2.5cm2 ROIs were segmented from the post-processed DM images using an automated algorithm. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, grey-level spatial correlation, and fractal dimension were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance in distinguishing between 72 pre- and 66 post-menopausal women. Logistic regression was performed to assess the independent effect of each texture feature in predicting menopause status. ROC analysis showed that texture features have inherent capacity to distinguish between pre- and post-menopausal statuses (AUC>0.5, p<0.05). Logistic regression including all texture features yielded an ROC curve with an AUC of 0.76. Addition of age at menarche, ethnicity, contraception use and hormonal replacement therapy (HRT) use lead to a modest model improvement (AUC=0.78) while texture features maintained significant contribution (p<0.05). The observed differences in parenchymal texture features between pre- and post- menopausal women suggest that mammographic texture can potentially serve as a surrogate imaging marker of endogenous hormonal activity.

Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

PubMed Central

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers. PMID:24371830

Multiple biomarker panels for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

Serglycin as a potential biomarker for glioma: association of serglycin expression, extent of mast cell recruitment and glioblastoma progression

PubMed Central

Roy, Ananya; Attarha, Sanaz; Weishaupt, Holger; Edqvist, Per-Henrik; Swartling, Fredrik J.; Bergqvist, Michael; Siebzehnrubl, Florian A.; Smits, Anja; Pontén, Fredrik; Tchougounova, Elena

2017-01-01

Serglycin is an intracellular proteoglycan with a unique ability to adopt highly divergent structures by glycosylation with variable types of glycosaminoglycans (GAGs) when expressed by different cell types. Serglycin is overexpressed in aggressive cancers suggesting its protumorigenic role. In this study, we explored the expression of serglycin in human glioma and its correlation with survival and immune cell infiltration. We demonstrate that serglycin is expressed in glioma and that increased expression predicts poor survival of patients. Analysis of serglycin expression in a large cohort of low- and high-grade human glioma samples reveals that its expression is grade dependent and is positively correlated with mast cell (MC) infiltration. Moreover, serglycin expression in patient-derived glioma cells is significantly increased upon MC co-culture. This is also accompanied by increased expression of CXCL12, CXCL10, as well as markers of cancer progression, including CD44, ZEB1 and vimentin. In conclusion, these findings indicate the importance of infiltrating MCs in glioma by modulating signaling cascades involving serglycin, CD44 and ZEB1. The present investigation reveals serglycin as a potential prognostic marker for glioma and demonstrates an association with the extent of MC recruitment and glioma progression, uncovering potential future therapeutic opportunities for patients. PMID:28445977

Risk factors and seroprevalence of markers for hepatitis A, B and C in persons subject to homelessness in inner Sydney.

PubMed

Poulos, Roslyn; Ferson, Mark; Orr, Karen; Lucy, Adrienne; Botham, Susan; McCarthy, Michele; Stern, Jerome; Dixon, Julie; Murray, Carolyn; Polis, Suzanne

2007-06-01

To determine the seroprevalence of hepatitis A, B and C and the prevalence of risk factors for blood-borne infections in persons subject to homelessness attending a medical clinic in inner Sydney. During 2003-05, 201 clients were enrolled in a prospective study to determine the acceptance, completion rates and immunogenicity of the standard vaccination schedule for hepatitis A and B. On enrolment, clients completed a risk factor assessment questionnaire and undertook pre-vaccination serological screening for hepatitis A, B and C. Forty-five per cent (85/188) of clients were positive for anti-HCV antibodies; 32% (60/189) showed evidence of past infection with HBV (anti-HBc); and 48% (89/189) were positive for anti-HAV antibodies. It was not uncommon for clients to have multiple markers of hepatitis. A past history of injecting drug use was significantly associated with markers for hepatitis B and C; age predicted presence of anti-HAV. A verbal history of infection appeared more reliable for hepatitis C, but considerably less so for hepatitis A and B. Persons subject to homelessness are at risk of blood-borne infection. The seroprevalence of markers for hepatitis B and C are higher than in the general population. Despite the high proportion of clients with serological markers for hepatitis A and B, at least 69% of clients could potentially benefit from hepatitis A and/or B vaccination.

Biomarker in Cisplatin-Based Chemotherapy for Urinary Bladder Cancer.

PubMed

Ecke, Thorsten H

2015-01-01

The treatment of metastasized bladder cancer has been evolving during recent years. Cisplatin based chemotherapy combinations are still gold standard in the treatment of advanced and metastasized bladder cancer. But new therapies are approaching. Based to this fact biological markers will become more important for decisions in bladder cancer treatment. A systematic MEDLINE search of the key words "cisplatin", "bladder cancer", "DNA marker", "protein marker", "methylation biomarker", "predictive marker", "prognostic marker" has been made. This review aims to highlight the most relevant clinical and experimental studies investigating markers for metastasized transitional carcinoma of the urothelium treated by cisplatin based regimens.

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows

PubMed Central

Huber, K.; Dänicke, S.; Rehage, J.; Sauerwein, H.; Otto, W.; Rolle-Kampczyk, U.; von Bergen, M.

2016-01-01

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life. PMID:27089826

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows.

PubMed

Huber, K; Dänicke, S; Rehage, J; Sauerwein, H; Otto, W; Rolle-Kampczyk, U; von Bergen, M

2016-04-19

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life.

Prognostic and predictive biomarkers post curative intent therapy

PubMed Central

Feldman, Rebecca

2017-01-01

Large-scale screening trials have demonstrated that early diagnosis of lung cancer results in a significant reduction in lung cancer mortality. Despite improvements in detecting more lung cancers at early stages, the 5-year survival rates of lung cancers diagnosed before widespread disease is only 30–50%. High rates of recurrence, despite early diagnosis, suggest the need to improve treatment strategies based on the likelihood of recurrence in patient subsets, as well as explore the role of predictive markers for therapy selection in the adjuvant setting. In the era of personalized medicine, there have been a wide array of molecular alterations and signatures studied for their potential prognostic and predictive utility, however most have failed to translate into clinical tools. This review will discuss progress made in clinical management of lung cancer, and recent progress in the development of patient selection tools for the refinement of early stage lung cancers. PMID:29057234

Autism as a disorder of prediction

PubMed Central

Sinha, Pawan; Kjelgaard, Margaret M.; Gandhi, Tapan K.; Tsourides, Kleovoulos; Cardinaux, Annie L.; Pantazis, Dimitrios; Diamond, Sidney P.; Held, Richard M.

2014-01-01

A rich collection of empirical findings accumulated over the past three decades attests to the diversity of traits that constitute the autism phenotypes. It is unclear whether subsets of these traits share any underlying causality. This lack of a cohesive conceptualization of the disorder has complicated the search for broadly effective therapies, diagnostic markers, and neural/genetic correlates. In this paper, we describe how theoretical considerations and a review of empirical data lead to the hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities. With compromised prediction skills, an individual with autism inhabits a seemingly “magical” world wherein events occur unexpectedly and without cause. Immersion in such a capricious environment can prove overwhelming and compromise one’s ability to effectively interact with it. If validated, this hypothesis has the potential of providing unifying insights into multiple aspects of autism, with attendant benefits for improving diagnosis and therapy. PMID:25288765

Efficient SNP Discovery by Combining Microarray and Lab-on-a-Chip Data for Animal Breeding and Selection

PubMed Central

Huang, Chao-Wei; Lin, Yu-Tsung; Ding, Shih-Torng; Lo, Ling-Ling; Wang, Pei-Hwa; Lin, En-Chung; Liu, Fang-Wei; Lu, Yen-Wen

2015-01-01

The genetic markers associated with economic traits have been widely explored for animal breeding. Among these markers, single-nucleotide polymorphism (SNPs) are gradually becoming a prevalent and effective evaluation tool. Since SNPs only focus on the genetic sequences of interest, it thereby reduces the evaluation time and cost. Compared to traditional approaches, SNP genotyping techniques incorporate informative genetic background, improve the breeding prediction accuracy and acquiesce breeding quality on the farm. This article therefore reviews the typical procedures of animal breeding using SNPs and the current status of related techniques. The associated SNP information and genotyping techniques, including microarray and Lab-on-a-Chip based platforms, along with their potential are highlighted. Examples in pig and poultry with different SNP loci linked to high economic trait values are given. The recommendations for utilizing SNP genotyping in nimal breeding are summarized. PMID:27600241

[Social dysfunction in schizotypy].

PubMed

de Wachter, O; De La Asuncion, J; Sabbe, B; Morrens, M

2016-01-01

Schizotypy is a personality organisation that is closely related to schizotypal personality disorder and schizophrenia and is characterised by deficits in social functioning. Although the dimensions of social dysfunction have not yet been fully explored certain aspects of social dysfunction are promising predictive markers for schizophrenia. To describe schizotypy and its influence on social functioning. We reviewed the literature systematically using the online databases PubMed and PsycINFO. The disorder known as schizotypy lies at the basis of schizotypal personality disorder. Both disorders are characterised by an increased risk for schizophrenia. The social dysfunctioning seen in schizotypy corresponds to the social dysfunction seen in schizophrenia. Impairments in social cognition are causal factors of this social dysfunction. Both the negative and the positive dimension of schizotypy influence social cognition. More focused, objective and interactive research to the various aspects of social functioning in schizotypy is needed in order to discover potential premorbid markers for schizophrenia.

New Martian climate constraints from radar reflectivity within the north polar layered deposits

NASA Astrophysics Data System (ADS)

Lalich, D. E.; Holt, J. W.

2017-01-01

The north polar layered deposits (NPLD) of Mars represent a global climate record reaching back millions of years, potentially recorded in visible layers and radar reflectors. However, little is known of the specific link between those layers, reflectors, and the global climate. To test the hypothesis that reflectors are caused by thick and indurated layers known as "marker beds," the reflectivity of three reflectors was measured, mapped, and compared to a reflectivity model. The measured reflectivities match the model and show a strong sensitivity to layer thickness, implying that radar reflectivity may be used as a proxy for short-term accumulation patterns and that regional climate plays a strong role in layer thickness variations. Comparisons to an orbitally forced NPLD accumulation model show a strong correlation with predicted marker bed formation, but dust content is higher than expected, implying a stronger role for dust in Mars polar climate than previously thought.

Fiber-Optic Array Scanning Technology (FAST) for Detection and Molecular Characterization of Circulating Tumor Cells.

PubMed

Ao, Zheng; Liu, Xiaohe

2017-01-01

Circulating tumor cell (CTC) as an important component in "liquid biopsy" holds crucial clinical relevance in cancer prognosis, treatment efficiency evaluation, prediction and potentially early detection. Here, we present a Fiber-optic Array Scanning Technology (FAST) that enables antigen-agnostic, size-agnostic detection of CTC. By immunofluorescence staining detection of a combination of a panel of markers, FAST technology can be applied to detect rare CTC in non-small cell lung cancer (NSCLC) setting with high sensitivity and specificity. In combination with Automated Digital Microscopy (ADM) platform, companion markers on CTC such as Vimentin and Programmed death-ligand 1 (PD-L1) can also be analyzed to further characterize these CTCs. FAST data output is also compatible with downstream single cell picking platforms. Single cell can be isolated post ADM confirmation and used for "actionable" genetic mutations analysis.

Biological markers in animals can provide information on exposure and bioavailability of environmental contaminants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shugart, L.R.; Adams, S.M.; Jimenez, B.D.

1987-01-01

Epidemiologic studies of agents present in the environment seek to identify the extent to which they contribute to the causation of a specific toxic, clinical, or pathological endpoint. The multifactorial nature of disease etiology, long latency periods and the complexity of exposure, all contribute to the difficulty of establishing associations and casual relationships between a specific exposure and an adverse outcome. These barriers to studies of exposures and subsequent risk assessment cannot generally be changed. However, the appropriate use of biological markers in animal species living in a contaminated habitat can provide a measure of potential damage from that exposuremore » and, in some instances, act as a surrogate for human environmental exposures. Quantitative predictivity of the effect of exposure to environmental pollutants is being approached by employing an appropriate array of biological end points. 34 refs., 1 fig., 6 tabs.« less

Predictive Validity of Explicit and Implicit Threat Overestimation in Contamination Fear

PubMed Central

Green, Jennifer S.; Teachman, Bethany A.

2012-01-01

We examined the predictive validity of explicit and implicit measures of threat overestimation in relation to contamination-fear outcomes using structural equation modeling. Undergraduate students high in contamination fear (N = 56) completed explicit measures of contamination threat likelihood and severity, as well as looming vulnerability cognitions, in addition to an implicit measure of danger associations with potential contaminants. Participants also completed measures of contamination-fear symptoms, as well as subjective distress and avoidance during a behavioral avoidance task, and state looming vulnerability cognitions during an exposure task. The latent explicit (but not implicit) threat overestimation variable was a significant and unique predictor of contamination fear symptoms and self-reported affective and cognitive facets of contamination fear. On the contrary, the implicit (but not explicit) latent measure predicted behavioral avoidance (at the level of a trend). Results are discussed in terms of differential predictive validity of implicit versus explicit markers of threat processing and multiple fear response systems. PMID:24073390

A Population Genetics Model of Marker-Assisted Selection

PubMed Central

Luo, Z. W.; Thompson, R.; Woolliams, J. A.

1997-01-01

A deterministic two-loci model was developed to predict genetic response to marker-assisted selection (MAS) in one generation and in multiple generations. Formulas were derived to relate linkage disequilibrium in a population to the proportion of additive genetic variance used by MAS, and in turn to an extra improvement in genetic response over phenotypic selection. Predictions of the response were compared to those predicted by using an infinite-loci model and the factors affecting efficiency of MAS were examined. Theoretical analyses of the present study revealed the nonlinearity between the selection intensity and genetic response in MAS. In addition to the heritability of the trait and the proportion of the marker-associated genetic variance, the frequencies of the selectively favorable alleles at the two loci, one marker and one quantitative trait locus, were found to play an important role in determining both the short- and long-term efficiencies of MAS. The evolution of linkage disequilibrium and thus the genetic response over several generations were predicted theoretically and examined by simulation. MAS dissipated the disequilibrium more quickly than drift alone. In some cases studied, the rate of dissipation was as large as that to be expected in the circumstance where the true recombination fraction was increased by three times and selection was absent. PMID:9215918

Accuracy of Genomic Prediction for Foliar Terpene Traits in Eucalyptus polybractea.

PubMed

Kainer, David; Stone, Eric A; Padovan, Amanda; Foley, William J; Külheim, Carsten

2018-06-11

Unlike agricultural crops, most forest species have not had millennia of improvement through phenotypic selection, but can contribute energy and material resources and possibly help alleviate climate change. Yield gains similar to those achieved in agricultural crops over millennia could be made in forestry species with the use of genomic methods in a much shorter time frame. Here we compare various methods of genomic prediction for eight traits related to foliar terpene yield in Eucalyptus polybractea , a tree grown predominantly for the production of Eucalyptus oil. The genomic markers used in this study are derived from shallow whole genome sequencing of a population of 480 trees. We compare the traditional pedigree-based additive best linear unbiased predictors (ABLUP), genomic BLUP (GBLUP), BayesB genomic prediction model, and a form of GBLUP based on weighting markers according to their influence on traits (BLUP|GA). Predictive ability is assessed under varying marker densities of 10,000, 100,000 and 500,000 SNPs. Our results show that BayesB and BLUP|GA perform best across the eight traits. Predictive ability was higher for individual terpene traits, such as foliar α-pinene and 1,8-cineole concentration (0.59 and 0.73, respectively), than aggregate traits such as total foliar oil concentration (0.38). This is likely a function of the trait architecture and markers used. BLUP|GA was the best model for the two biomass related traits, height and 1 year change in height (0.25 and 0.19, respectively). Predictive ability increased with marker density for most traits, but with diminishing returns. The results of this study are a solid foundation for yield improvement of essential oil producing eucalypts. New markets such as biopolymers and terpene-derived biofuels could benefit from rapid yield increases in undomesticated oil-producing species. Copyright © 2018, G3: Genes, Genomes, Genetics.

Graphical assessment of incremental value of novel markers in prediction models: From statistical to decision analytical perspectives.

PubMed

Steyerberg, Ewout W; Vedder, Moniek M; Leening, Maarten J G; Postmus, Douwe; D'Agostino, Ralph B; Van Calster, Ben; Pencina, Michael J

2015-07-01

New markers may improve prediction of diagnostic and prognostic outcomes. We aimed to review options for graphical display and summary measures to assess the predictive value of markers over standard, readily available predictors. We illustrated various approaches using previously published data on 3264 participants from the Framingham Heart Study, where 183 developed coronary heart disease (10-year risk 5.6%). We considered performance measures for the incremental value of adding HDL cholesterol to a prediction model. An initial assessment may consider statistical significance (HR = 0.65, 95% confidence interval 0.53 to 0.80; likelihood ratio p < 0.001), and distributions of predicted risks (densities or box plots) with various summary measures. A range of decision thresholds is considered in predictiveness and receiver operating characteristic curves, where the area under the curve (AUC) increased from 0.762 to 0.774 by adding HDL. We can furthermore focus on reclassification of participants with and without an event in a reclassification graph, with the continuous net reclassification improvement (NRI) as a summary measure. When we focus on one particular decision threshold, the changes in sensitivity and specificity are central. We propose a net reclassification risk graph, which allows us to focus on the number of reclassified persons and their event rates. Summary measures include the binary AUC, the two-category NRI, and decision analytic variants such as the net benefit (NB). Various graphs and summary measures can be used to assess the incremental predictive value of a marker. Important insights for impact on decision making are provided by a simple graph for the net reclassification risk. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neural correlates of endogenous attention, exogenous attention and inhibition of return in touch.

PubMed

Jones, Alexander; Forster, Bettina

2014-07-01

Selective attention helps process the myriad of information constantly touching our body. Both endogenous and exogenous mechanisms are relied upon to effectively process this information; however, it is unclear how they relate in the sense of touch. In three tasks we contrasted endogenous and exogenous event-related potential (ERP) and behavioural effects. Unilateral tactile cues were followed by a tactile target at the same or opposite hand. Clear behavioural effects showed facilitation of expected targets both when the cue predicted targets at the same (endogenous predictive task) and opposite hand (endogenous counter-predictive task), and these effects also correlated with ERP effects of endogenous attention. In an exogenous task, where the cue was non-informative, inhibition of return (IOR) was observed. The electrophysiological results demonstrated early effects of exogenous attention followed by later endogenous attention modulations. These effects were independent in both the endogenous predictive and exogenous tasks. However, voluntarily directing attention away from a cued body part influenced the early exogenous marker (N80). This suggests that the two mechanisms are interdependent, at least when the task requires more demanding shifts of attention. The early marker of exogenous tactile attention, the N80, was not directly related to IOR, which may suggest that exogenous attention and IOR are not necessarily two sides of the same coin. This study adds valuable new insight into how we process and select information presented to our body, showing both independent and interdependent effects of endogenous and exogenous attention in touch. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Neurofilament light chain in cerebrospinal fluid and prediction of disease activity in clinically isolated syndrome and relapsing-remitting multiple sclerosis.

PubMed

Håkansson, I; Tisell, A; Cassel, P; Blennow, K; Zetterberg, H; Lundberg, P; Dahle, C; Vrethem, M; Ernerudh, J

2017-05-01

Improved biomarkers are needed to facilitate clinical decision-making and as surrogate endpoints in clinical trials in multiple sclerosis (MS). We assessed whether neurodegenerative and neuroinflammatory markers in cerebrospinal fluid (CSF) at initial sampling could predict disease activity during 2 years of follow-up in patients with clinically isolated syndrome (CIS) and relapsing-remitting MS. Using multiplex bead array and enzyme-linked immunosorbent assay, CXCL1, CXCL8, CXCL10, CXCL13, CCL20, CCL22, neurofilament light chain (NFL), neurofilament heavy chain, glial fibrillary acidic protein, chitinase-3-like-1, matrix metalloproteinase-9 and osteopontin were analysed in CSF from 41 patients with CIS or relapsing-remitting MS and 22 healthy controls. Disease activity (relapses, magnetic resonance imaging activity or disability worsening) in patients was recorded during 2 years of follow-up in this prospective longitudinal cohort study. In a logistic regression analysis model, NFL in CSF at baseline emerged as the best predictive marker, correctly classifying 93% of patients who showed evidence of disease activity during 2 years of follow-up and 67% of patients who did not, with an overall proportion of 85% (33 of 39 patients) correctly classified. Combining NFL with either neurofilament heavy chain or osteopontin resulted in 87% overall correctly classified patients, whereas combining NFL with a chemokine did not improve results. This study demonstrates the potential prognostic value of NFL in baseline CSF in CIS and relapsing-remitting MS and supports its use as a predictive biomarker of disease activity. © 2017 EAN.

How to predict clinical relapse in inflammatory bowel disease patients

PubMed Central

Liverani, Elisa; Scaioli, Eleonora; Digby, Richard John; Bellanova, Matteo; Belluzzi, Andrea

2016-01-01

Inflammatory bowel diseases have a natural course characterized by alternating periods of remission and relapse. Disease flares occur in a random way and are currently unpredictable for the most part. Predictors of benign or unfavourable clinical course are required to facilitate treatment decisions and to avoid overtreatment. The present article provides a literature review of the current evidence on the main clinical, genetic, endoscopic, histologic, serologic and fecal markers to predict aggressiveness of inflammatory bowel disease and discuss their prognostic role, both in Crohn’s disease and ulcerative colitis. No single marker seems to be reliable alone as a flare predictor, even in light of promising evidence regarding the role of fecal markers, in particular fecal calprotectin, which has reported good results recently. In order to improve our daily clinical practice, validated prognostic scores should be elaborated, integrating clinical and biological markers of prognosis. Finally, we propose an algorithm considering clinical history and biological markers to intercept patients with high risk of clinical relapse. PMID:26811644

EGFR Gene Amplification and KRAS Mutation Predict Response to Combination Targeted Therapy in Metastatic Colorectal Cancer.

PubMed

Khan, Sajid A; Zeng, Zhaoshi; Shia, Jinru; Paty, Philip B

2017-07-01

Genetic variability in KRAS and EGFR predicts response to cetuximab in irinotecan refractory colorectal cancer. Whether these markers or others remain predictive in combination biologic therapies including bevacizumab is unknown. We identified predictive biomarkers from patients with irinotecan refractory metastatic colorectal cancer treated with cetuximab plus bevacizumab. Patients who received cetuximab plus bevacizumab for irinotecan refractory colorectal cancer in either of two Phase II trials conducted were identified. Tumor tissue was available for 33 patients. Genomic DNA was extracted and used for mutational analysis of KRAS, BRAF, and p53 genes. Fluorescence in situ hybridization was performed to assess EGFR copy number. The status of single genes and various combinations were tested for association with response. Seven of 33 patients responded to treatment. KRAS mutations were found in 14/33 cases, and 0 responded to treatment (p = 0.01). EGFR gene amplification was seen in 3/33 of tumors and in every case was associated with response to treatment (p < 0.001). TP53 and BRAF mutations were found in 18/33 and 0/33 tumors, respectively, and there were no associations with response to either gene. EGFR gene amplification and KRAS mutations are predictive markers for patients receiving combination biologic therapy of cetuximab plus bevacizumab for metastatic colorectal cancer. One marker or the other is present in the tumor of half of all patients allowing treatment response to be predicted with a high degree of certainty. The role for molecular markers in combination biologic therapy seems promising.

Molecular imaging to track Parkinson's disease and atypical parkinsonisms: New imaging frontiers.

PubMed

Strafella, Antonio P; Bohnen, Nicolaas I; Perlmutter, Joel S; Eidelberg, David; Pavese, Nicola; Van Eimeren, Thilo; Piccini, Paola; Politis, Marios; Thobois, Stephane; Ceravolo, Roberto; Higuchi, Makoto; Kaasinen, Valtteri; Masellis, Mario; Peralta, M Cecilia; Obeso, Ignacio; Pineda-Pardo, Jose Ángel; Cilia, Roberto; Ballanger, Benedicte; Niethammer, Martin; Stoessl, Jon A

2017-02-01

Molecular imaging has proven to be a powerful tool for investigation of parkinsonian disorders. One current challenge is to identify biomarkers of early changes that may predict the clinical trajectory of parkinsonian disorders. Exciting new tracer developments hold the potential for in vivo markers of underlying pathology. Herein, we provide an overview of molecular imaging advances and how these approaches help us to understand PD and atypical parkinsonisms. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Epigenetic Therapy in Lung Cancer – Role of microRNAs

PubMed Central

Rothschild, Sacha I.

2013-01-01

Lung cancer is the leading cause of cancer deaths worldwide. microRNAs (miRNAs) are a class of small non-coding RNA species that have been implicated in the control of many fundamental cellular and physiological processes such as cellular differentiation, proliferation, apoptosis, and stem cell maintenance. Some miRNAs have been categorized as “oncomiRs” as opposed to “tumor suppressor miRs.” This review focuses on the role of miRNAs in the lung cancer carcinogenesis and their potential as diagnostic, prognostic, or predictive markers. PMID:23802096

Sequencing consolidates molecular markers with plant breeding practice.

PubMed

Yang, Huaan; Li, Chengdao; Lam, Hon-Ming; Clements, Jonathan; Yan, Guijun; Zhao, Shancen

2015-05-01

Plenty of molecular markers have been developed by contemporary sequencing technologies, whereas few of them are successfully applied in breeding, thus we present a review on how sequencing can facilitate marker-assisted selection in plant breeding. The growing global population and shrinking arable land area require efficient plant breeding. Novel strategies assisted by certain markers have proven effective for genetic gains. Fortunately, cutting-edge sequencing technologies bring us a deluge of genomes and genetic variations, enlightening the potential of marker development. However, a large gap still exists between the potential of molecular markers and actual plant breeding practices. In this review, we discuss marker-assisted breeding from a historical perspective, describe the road from crop sequencing to breeding, and highlight how sequencing facilitates the application of markers in breeding practice.

Baseline series fragrance markers fail to predict contact allergy.

PubMed

Mann, Jack; McFadden, John P; White, Jonathan M L; White, Ian R; Banerjee, Piu

2014-05-01

Negative patch test results with fragrance allergy markers in the European baseline series do not always predict a negative reaction to individual fragrance substances. To determine the frequencies of positive test reactions to the 26 fragrance substances for which labelling is mandatory in the EU, and how effectively reactions to fragrance markers in the baseline series predict positive reactions to the fragrance substances that are labelled. The records of 1951 eczema patients, routinely tested with the labelled fragrance substances and with an extended European baseline series in 2011 and 2012, were retrospectively reviewed. Two hundred and eighty-one (14.4%) (71.2% females) reacted to one or more allergens from the labelled-fragrance substance series and/or a fragrance marker from the European baseline series. The allergens that were positive with the greatest frequencies were cinnamyl alcohol (48; 2.46%), Evernia furfuracea (44; 2.26%), and isoeugenol (40; 2.05%). Of the 203 patients who reacted to any of the 26 fragrances in the labelled-fragrance substance series, only 117 (57.6%) also reacted to a fragrance marker in the baseline series. One hundred and seven (52.7%) reacted to either fragrance mix I or fragrance mix II, 28 (13.8%) reacted to Myroxylon pereirae, and 13 (6.4%) reacted to hydroxyisohexyl 3-cyclohexene carboxaldehyde. These findings confirm that the standard fragrance markers fail to identify patients with contact allergies to the 26 fragrances. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.

PubMed

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C

2014-09-01

Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait 'total crop nitrogen uptake' (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10-36 % more yield than those based on markers for yield per se. This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Discovery of markers of exposure specific to bites of Lutzomyia longipalpis, the vector of Leishmania infantum chagasi in Latin America.

PubMed

Teixeira, Clarissa; Gomes, Regis; Collin, Nicolas; Reynoso, David; Jochim, Ryan; Oliveira, Fabiano; Seitz, Amy; Elnaiem, Dia-Eldin; Caldas, Arlene; de Souza, Ana Paula; Brodskyn, Cláudia I; de Oliveira, Camila Indiani; Mendonca, Ivete; Costa, Carlos H N; Volf, Petr; Barral, Aldina; Kamhawi, Shaden; Valenzuela, Jesus G

2010-03-23

Sand flies deliver Leishmania parasites to a host alongside salivary molecules that affect infection outcomes. Though some proteins are immunogenic and have potential as markers of vector exposure, their identity and vector specificity remain elusive. We screened human, dog, and fox sera from endemic areas of visceral leishmaniasis to identify potential markers of specific exposure to saliva of Lutzomyia longipalpis. Human and dog sera were further tested against additional sand fly species. Recombinant proteins of nine transcripts encoding secreted salivary molecules of Lu. longipalpis were produced, purified, and tested for antigenicity and specificity. Use of recombinant proteins corresponding to immunogenic molecules in Lu. longipalpis saliva identified LJM17 and LJM11 as potential markers of exposure. LJM17 was recognized by human, dog, and fox sera; LJM11 by humans and dogs. Notably, LJM17 and LJM11 were specifically recognized by humans exposed to Lu. longipalpis but not by individuals exposed to Lu. intermedia. Salivary recombinant proteins are of value as markers of vector exposure. In humans, LJM17 and LJM11 emerged as potential markers of specific exposure to Lu. longipalpis, the vector of Leishmania infantum chagasi in Latin America. In dogs, LJM17, LJM11, LJL13, LJL23, and LJL143 emerged as potential markers of sand fly exposure. Testing these recombinant proteins in large scale studies will validate their usefulness as specific markers of Lu. longipalpis exposure in humans and of sand fly exposure in dogs.

Correlates of a single cortical action potential in the epidural EEG

PubMed Central

Teleńczuk, Bartosz; Baker, Stuart N; Kempter, Richard; Curio, Gabriel

2015-01-01

To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes. PMID:25554430

Importance of Multimodal MRI in Characterizing Brain Tissue and Its Potential Application for Individual Age Prediction.

PubMed

Cherubini, Andrea; Caligiuri, Maria Eugenia; Peran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2016-09-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2(*) relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. The results of the linear model were used to predict apparent age in different regions of individual brain. This approach pointed to a number of novel applications that could potentially help highlighting areas particularly vulnerable to disease.

Evaluating the physiological reserves of older patients with cancer: the value of potential biomarkers of aging?

PubMed

Pallis, Athanasios G; Hatse, Sigrid; Brouwers, Barbara; Pawelec, Graham; Falandry, Claire; Wedding, Ulrich; Lago, Lissandra Dal; Repetto, Lazzaro; Ring, Alistair; Wildiers, Hans

2014-04-01

Aging of an individual entails a progressive decline of functional reserves and loss of homeostasis that eventually lead to mortality. This process is highly individualized and is influenced by multiple genetic, epigenetic and environmental factors. This individualization and the diversity of factors influencing aging result in a significant heterogeneity among people with the same chronological age, representing a major challenge in daily oncology practice. Thus, many factors other than mere chronological age will contribute to treatment tolerance and outcome in the older patients with cancer. Clinical/comprehensive geriatric assessment can provide information on the general health status of individuals, but is far from perfect as a prognostic/predictive tool for individual patients. On the other hand, aging can also be assessed in terms of biological changes in certain tissues like the blood compartment which result from adaptive alterations due to past history of exposures, as well as intrinsic aging processes. There are major signs of 'aging' in lymphocytes (e.g. lymphocyte subset distribution, telomere length, p16INK4A expression), and also in (inflammatory) cytokine expression and gene expression patterns. These result from a combination of the above two processes, overlaying genetic predispositions which contribute significantly to the aging phenotype. These potential "aging biomarkers" might provide additional prognostic/predictive information supplementing clinical evaluation. The purpose of the current paper is to describe the most relevant potential "aging biomarkers" (markers that indicate the biological functional age of patients) which focus on the biological background, the (limited) available clinical data, and technical challenges. Despite their great potential interest, there is a need for much more (validated) clinical data before these biomarkers could be used in a routine clinical setting. This manuscript tries to provide a guideline on how these markers can be integrated in future research aimed at providing such data. © 2013.

Candidate Markers Associated with the Probability of Future Pulmonary Exacerbations in Cystic Fibrosis Patients

PubMed Central

Wojewodka, Gabriella; De Sanctis, Juan B.; Bernier, Joanie; Bérubé, Julie; Ahlgren, Heather G.; Gruber, Jim; Landry, Jennifer; Lands, Larry C.; Nguyen, Dao; Rousseau, Simon; Benedetti, Andrea; Matouk, Elias; Radzioch, Danuta

2014-01-01

Introduction Pulmonary exacerbations (PEs) cause significant morbidity and can severely impact disease progression in cystic fibrosis (CF) lung disease, especially in patients who suffer from recurrent PEs. The assessments able to predict a future PE or a recurrent PE are limited. We hypothesized that combining clinical, molecular and patient reported data could identify patients who are at risk of PE. Methods We prospectively followed a cohort of 53 adult CF patients for 24 months. Baseline values for spirometry, clinical status using the Matouk Disease Score, quality of life (QOL), inflammatory markers (C-reactive protein (CRP), interleukins (IL)-1β, -6, -8, -10, macrophage inflammatory protein (MIP)-1β, tumor necrosis factor (TNF) and vascular endothelial growth factor (VEGF)), polyunsaturated fatty acids and lipid peroxidation in blood plasma were collected for all patients during periods of stable disease, and patients were monitored for PE requiring PO/IV antibiotic treatment. Additionally, we closely followed 13 patients during PEs collecting longitudinal data on changes in markers from baseline values. We assessed whether any markers were predictors of future PE at baseline and after antibiotic treatment. Results Out of 53 patients, 37 experienced PEs during our study period. At baseline, we found that low lung function, clinical scoring and QOL values were associated with increased risk of PE events. PEs were associated with increased inflammatory markers at Day 1, and these biomarkers improved with treatment. The imbalance in arachidonic acid and docosahexaenoic acid levels improved with treatment which coincided with reductions in lipid peroxidation. High levels of inflammatory markers CRP and IL-8 were associated with an early re-exacerbation. Conclusion Our results demonstrate that worse clinical and QOL assessments during stable disease are potential markers associated with a higher risk of future PEs, while higher levels of inflammatory markers at the end of antibiotic treatment may be associated with early re-exacerbation. PMID:24533110

Prediction of clinical response based on pharmacokinetic/pharmacodynamic models of 5-hydroxytryptamine reuptake inhibitors in mice

PubMed Central

Kreilgaard, M; Smith, D G; Brennum, L T; Sánchez, C

2008-01-01

Background and purpose: Bridging the gap between preclinical research and clinical trials is vital for drug development. Predicting clinically relevant steady-state drug concentrations (Css) in serum from preclinical animal models may facilitate this transition. Here we used a pharmacokinetic/pharmacodynamic (PK/PD) modelling approach to evaluate the predictive validity of 5-hydroxytryptamine (5-HT; serotonin) transporter (SERT) occupancy and 5-hydroxytryptophan (5-HTP)-potentiated behavioral syndrome induced by 5-HT reuptake inhibitor (SRI) antidepressants in mice. Experimental approach: Serum and whole brain drug concentrations, cortical SERT occupancy and 5-HTP-potentiated behavioral syndrome were measured over 6 h after a single subcutaneous injection of escitalopram, paroxetine or sertraline. [3H]2-(2-dimethylaminomethylphenylsulphanyl)-5-methyl-phenylamine ([3H]MADAM) was used to assess SERT occupancy. For PK/PD modelling, an effect-compartment model was applied to collapse the hysteresis and predict the steady-state relationship between drug exposure and PD response. Key results: The predicted Css for escitalopram, paroxetine and sertraline at 80% SERT occupancy in mice are 18 ng mL−1, 18 ng mL−1 and 24 ng mL−1, respectively, with corresponding responses in the 5-HTP behavioral model being between 20–40% of the maximum. Conclusions and implications: Therapeutically effective SERT occupancy for SRIs in depressed patients is approximately 80%, and the corresponding plasma Css are 6–21 ng mL−1, 21-95 ng mL−1 and 20–48 ng mL−1 for escitalopram, paroxetine and sertraline, respectively. Thus, PK/PD modelling using SERT occupancy and 5-HTP-potentiated behavioral syndrome as response markers in mice may be a useful tool to predict clinically relevant plasma Css values. PMID:18552871

Ferritin levels predict severe dengue.

PubMed

Soundravally, R; Agieshkumar, B; Daisy, M; Sherin, J; Cleetus, C C

2015-02-01

Currently, no tests are available to monitor and predict severity and outcome of dengue. To find potential markers that predict dengue severity, the present study validated the serum level of three acute-phase proteins α-1 antitrypsin, ceruloplasmin and ferritin in a pool of severe dengue cases compared to non-severe forms and other febrile illness controls. A total of 96 patients were divided into two equal groups with group 'A' comprising dengue-infected cases and group 'B' with other febrile illness cases negative for dengue. Out of 48 dengue-infected cases, 13 had severe dengue and the remaining 35 were classified as non-severe dengue. Immunoassays were performed to evaluate the serum levels of acute-phase proteins both on the day of admission and on the day of defervescence. The efficiency of individual proteins in predicting the disease severity was assessed using receiver operating characteristic curve. The study did not find any significant difference in the levels of α-1 antitrypsin between the clinical groups. A significant increase in the levels of ceruloplasmin around defervescence in severe cases compared to non-severe and other febrile controls was observed and this is the first report describing the potential association of ceruloplasmin and dengue severity. Interestingly, a steady increase in the level of serum ferritin was recorded throughout the course of illness. Among all the three proteins, the elevated ferritin level could predict the disease severity with highest sensitivity and specificity of 76.9 and 83.3 %, respectively, on the day of admission and the same was found to be 90 and 91.6 % around defervescence. On the basis of this diagnostic efficiency, we propose that ferritin may serve as a potential biomarker for an early prediction of disease severity.

Combined Screening for Early Detection of Pre-Eclampsia

PubMed Central

Park, Hee Jin; Shim, Sung Shin; Cha, Dong Hyun

2015-01-01

Although the precise pathophysiology of pre-eclampsia remains unknown, this condition continues to be a major cause of maternal and fetal mortality. Early prediction of pre-eclampsia would allow for timely initiation of preventive therapy. A combination of biophysical and biochemical markers are superior to other tests for early prediction of the development of pre-eclampsia. Apart from the use of parameters in first-trimester aneuploidy screening, cell-free fetal DNA quantification is emerging as a promising marker for prediction of pre-eclampsia. This article reviews the current research of the most important strategies for prediction of pre-eclampsia, including the use of maternal risk factors, mean maternal arterial pressure, ultrasound parameters, and biomarkers. PMID:26247944

Improved age determination of blood and teeth samples using a selected set of DNA methylation markers

PubMed Central

Kamalandua, Aubeline

2015-01-01

Age estimation from DNA methylation markers has seen an exponential growth of interest, not in the least from forensic scientists. The current published assays, however, can still be improved by lowering the number of markers in the assay and by providing more accurate models to predict chronological age. From the published literature we selected 4 age-associated genes (ASPA, PDE4C, ELOVL2, and EDARADD) and determined CpG methylation levels from 206 blood samples of both deceased and living individuals (age range: 0–91 years). This data was subsequently used to compare prediction accuracy with both linear and non-linear regression models. A quadratic regression model in which the methylation levels of ELOVL2 were squared showed the highest accuracy with a Mean Absolute Deviation (MAD) between chronological age and predicted age of 3.75 years and an adjusted R2 of 0.95. No difference in accuracy was observed for samples obtained either from living and deceased individuals or between the 2 genders. In addition, 29 teeth from different individuals (age range: 19–70 years) were analyzed using the same set of markers resulting in a MAD of 4.86 years and an adjusted R2 of 0.74. Cross validation of the results obtained from blood samples demonstrated the robustness and reproducibility of the assay. In conclusion, the set of 4 CpG DNA methylation markers is capable of producing highly accurate age predictions for blood samples from deceased and living individuals PMID:26280308

Mapping QTL for popping expansion volume in popcorn with simple sequence repeat markers.

PubMed

Lu, H-J; Bernardo, R; Ohm, H W

2003-02-01

Popping expansion volume is the most important quality trait in popcorn ( Zea mays L.), but its genetics is not well understood. The objectives of this study were to map quantitative trait loci (QTLs) responsible for popping expansion volume in a popcorn x dent corn cross, and to compare the predicted efficiencies of phenotypic selection, marker-based selection, and marker-assisted selection for popping expansion volume. Of 259 simple sequence repeat (SSR) primer pairs screened, 83 pairs were polymorphic between the H123 (dent corn) and AG19 (popcorn) parental inbreds. Popping test data were obtained for 160 S(1) families developed from the [AG19(H123 x AG19)] BC(1) population. The heritability ( h(2)) for popping expansion volume on an S(1) family mean basis was 0.73. The presence of the gametophyte factor Ga1(s) in popcorn complicates the analysis of popcorn x dent corn crosses. But, from a practical perspective, the linkage between a favorable QTL allele and Ga1(s) in popcorn will lead to selection for the favorable QTL allele. Four QTLs, on chromosomes 1S, 3S, 5S and 5L, jointly explained 45% of the phenotypic variation. Marker-based selection for popping expansion volume would require less time and work than phenotypic selection. But due to the high h(2) of popping expansion volume, marker-based selection was predicted to be only 92% as efficient as phenotypic selection. Marker-assisted selection, which comprises index selection on phenotypic and marker scores, was predicted to be 106% as efficient as phenotypic selection. Overall, our results suggest that phenotypic selection will remain the preferred method for selection in popcorn x dent corn crosses.

Quantification of plasma exosome is a potential prognostic marker for esophageal squamous cell carcinoma.

PubMed

Matsumoto, Yasunori; Kano, Masayuki; Akutsu, Yasunori; Hanari, Naoyuki; Hoshino, Isamu; Murakami, Kentaro; Usui, Akihiro; Suito, Hiroshi; Takahashi, Masahiko; Otsuka, Ryota; Xin, Hu; Komatsu, Aki; Iida, Keiko; Matsubara, Hisahiro

2016-11-01

Exosomes play important roles in cancer progression. Although its contents (e.g., proteins and microRNAs) have been focused on in cancer research, particularly as potential diagnostic markers, the exosome behavior and methods for exosome quantification remain unclear. In the present study, we analyzed the tumor-derived exosome behavior and assessed the quantification of exosomes in patient plasma as a biomarker for esophageal squamous cell carcinoma (ESCC). A CD63-GFP expressing human ESCC cell line (TE2-CD63-GFP) was made by transfection, and mouse subcutaneous tumor models were established. Fluorescence imaging was performed on tumors and plasma exosomes harvested from mice. GFP-positive small vesicles were confirmed in the plasma obtained from TE2-CD63-GFP tumor-bearing mice. Patient plasma was collected in Chiba University Hospital (n=86). Exosomes were extracted from 100 µl of the plasma and quantified by acetylcholinesterase (AChE) activity. The relationship between exosome quantification and the patient clinical characteristics was assessed. The quantification of exosomes isolated from the patient plasma revealed that esophageal cancer patients (n=66) expressed higher exosome levels than non-malignant patients (n=20) (P=0.0002). Although there was no correlation between the tumor progression and the exosome levels, exosome number was the independent prognostic marker and low levels of exosome predicted a poor prognosis (P=0.03). In conclusion, exosome levels may be useful as an independent prognostic factor for ESCC patients.

Serum markers for prostate cancer: a rational approach to the literature.

PubMed

Steuber, Thomas; O'Brien, Matthew Frank; Lilja, Hans

2008-07-01

Due to its universal applicability for early detection and prediction of cancer stage and disease recurrence, widespread implementation of serum-based prostate-specific antigen (PSA) measurements has a significant influence on current treatment strategies for men with prostate cancer (PCa). However, over-detection and the resultant over-treatment of indolent cancers have been strongly implicated to occur. Using current recommended guidelines, the PSA test suffers from both limited sensitivity and specificity to enable efficacious population-based cancer detection. Therefore, novel biomarkers are much needed to complement PSA by enhancing its diagnostic and prognostic performance. The present literature on serum markers for PCa was reviewed. PSA derivatives, molecular PSA isoforms, and novel molecular targets in blood were summarized and weighted against their potential to improve decision-making of men with PCa. Current evidence suggests that no single analyte is likely to achieve the desired level of diagnostic and prognostic accuracy for PCa. However, the combination of biomarkers with clinical and demographic data, for example, using established standard nomograms, has produced progress toward the goal of both optimal screening and risk assessment. Furthermore, potential candidate molecular markers for PCa can be derived from high-throughput technologies. Current studies demonstrate that understanding dynamic PSA changes over time may offer diagnostic and prognostic information. Bridging the gap between basic science and clinical practice represents the main goal in the near future to enable physicians to tailor risk-adjusted screening and treatment strategies for current patients with PCa.

Accuracy of Predicted Genomic Breeding Values in Purebred and Crossbred Pigs.

PubMed

Hidalgo, André M; Bastiaansen, John W M; Lopes, Marcos S; Harlizius, Barbara; Groenen, Martien A M; de Koning, Dirk-Jan

2015-05-26

Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent. Copyright © 2015 Hidalgo et al.

Self-injury, aggression and destruction in children with severe intellectual disability: Incidence, persistence and novel, predictive behavioural risk markers.

PubMed

Davies, L E; Oliver, C

2016-01-01

A risk informed, early intervention strategy for self-injurious, aggressive and destructive behaviours in children with severe intellectual disability is gaining support. The aims of this study were to establish the cumulative incidence and persistence of self-injury, aggression and destruction and the relationship between these behaviours and two potentially predictive behavioural risk markers (repetitive behaviour, and impulsivity and overactivity) in children at high risk. In a longitudinal design self-injury, aggression and destruction were assessed by teachers of 417 children with severe intellectual disability on two occasions separated by 15-18 months. Aggression, destruction and self-injury were persistent (69%, 57% and 58% respectively). Repetitive and restricted behaviours and interests (RRBI) and overactivity/impulsivity (O/I) were significantly associated with aggression (O/I OR=1.291, p<.001), destruction (RRBI OR 1.201, p=.013; O/I OR 1.278, p<.001) and/or self-injury (RRBI, OR 1.25, p=.004; O/I OR=1.117, p<.001). The relative risk of the cumulative incidence of self-injury, aggression and destruction was significantly increased by repetitive and restricted behaviours and interests (self-injury 2.66, destruction 2.16) and/or overactivity/impulsivity (aggression 2.42, destruction 2.07). The results provide evidence that repetitive and restricted behaviours and interests, and overactivity/impulsivity, are risk markers for the onset of self-injury, aggression and destruction within the already high risk group of children with severe intellectual disability. Copyright © 2015 Elsevier Ltd. All rights reserved.

Financial Exploitation Is Associated With Structural and Functional Brain Differences in Healthy Older Adults.

PubMed

Spreng, R Nathan; Cassidy, Benjamin N; Darboh, Bri S; DuPre, Elizabeth; Lockrow, Amber W; Setton, Roni; Turner, Gary R

2017-10-01

Age-related brain changes leading to altered socioemotional functioning may increase vulnerability to financial exploitation. If confirmed, this would suggest a novel mechanism leading to heightened financial exploitation risk in older adults. Development of predictive neural markers could facilitate increased vigilance and prevention. In this preliminary study, we sought to identify structural and functional brain differences associated with financial exploitation in older adults. Financially exploited older adults (n = 13, 7 female) and a matched cohort of older adults who had been exposed to, but avoided, a potentially exploitative situation (n = 13, 7 female) were evaluated. Using magnetic resonance imaging, we examined cortical thickness and resting state functional connectivity. Behavioral data were collected using standardized cognitive assessments, self-report measures of mood and social functioning. The exploited group showed cortical thinning in anterior insula and posterior superior temporal cortices, regions associated with processing affective and social information, respectively. Functional connectivity encompassing these regions, within default and salience networks, was reduced, while between network connectivity was increased. Self-reported anger and hostility was higher for the exploited group. We observed financial exploitation associated with brain differences in regions involved in socioemotional functioning. These exploratory and preliminary findings suggest that alterations in brain regions implicated in socioemotional functioning may be a marker of financial exploitation risk. Large-scale, prospective studies are necessary to validate this neural mechanism, and develop predictive markers for use in clinical practice. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.

Platelet density per monocyte predicts adverse events in patients after percutaneous coronary intervention.

PubMed

Rutten, Bert; Roest, Mark; McClellan, Elizabeth A; Sels, Jan W; Stubbs, Andrew; Jukema, J Wouter; Doevendans, Pieter A; Waltenberger, Johannes; van Zonneveld, Anton-Jan; Pasterkamp, Gerard; De Groot, Philip G; Hoefer, Imo E

2016-01-01

Monocyte recruitment to damaged endothelium is enhanced by platelet binding to monocytes and contributes to vascular repair. Therefore, we studied whether the number of platelets per monocyte affects the recurrence of adverse events in patients after percutaneous coronary intervention (PCI). Platelet-monocytes complexes with high and low median fluorescence intensities (MFI) of the platelet marker CD42b were isolated using cell sorting. Microscopic analysis revealed that a high platelet marker MFI on monocytes corresponded with a high platelet density per monocyte while a low platelet marker MFI corresponded with a low platelet density per monocyte (3.4 ± 0.7 vs 1.4 ± 0.1 platelets per monocyte, P=0.01). Using real-time video microscopy, we observed increased recruitment of high platelet density monocytes to endothelial cells as compared with low platelet density monocytes (P=0.01). Next, we classified PCI scheduled patients (N=263) into groups with high, medium and low platelet densities per monocyte and assessed the recurrence of adverse events. After multivariate adjustment for potential confounders, we observed a 2.5-fold reduction in the recurrence of adverse events in patients with a high platelet density per monocyte as compared with a low platelet density per monocyte [hazard ratio=0.4 (95% confidence interval, 0.2-0.8), P=0.01]. We show that a high platelet density per monocyte increases monocyte recruitment to endothelial cells and predicts a reduction in the recurrence of adverse events in patients after PCI. These findings may imply that a high platelet density per monocyte protects against recurrence of adverse events.

Heterogeneity in Immune Marker Expression after Acquisition of Resistance to EGFR Kinase Inhibitors: Analysis of a Case with Small Cell Lung Cancer Transformation.

PubMed

Suda, Kenichi; Murakami, Isao; Yu, Hui; Kim, Jihye; Ellison, Kim; Rivard, Christopher J; Mitsudomi, Tetsuya; Hirsch, Fred R

2017-06-01

Expression of immune markers is of scientific interest because of their potential roles as predictive biomarkers for immunotherapy. Although the microenvironment of metastatic tumors and/or therapy-inducible histological transformation may affect the expression of these immune markers, there are few data regarding this context. A 76-year-old never-smoking female with EGFR-mutated lung adenocarcinoma (AC) acquired resistance to gefitinib. After her death, an autopsy revealed SCLC transformation and EGFR T790M secondary mutation (T790M) as mutually exclusive resistance mechanisms occurring differently in different metastases; two liver metastases (SCLC versus AC with T790M) and two lymph node metastases (SCLC versus AC with T790M) were analyzed to compare the expression status of immune markers by immunohistochemistry and by an immune oncology gene expression panel. Programmed death ligand 1 (PD-L1) protein was partially expressed in tumor cells with AC lesions (T790M) but not in tumor cells with SCLC transformation. The liver metastasis with SCLC transformation showed no stromal PD-L1 expression and scant tumor-infiltrating lymphocytes, whereas the other lesions demonstrated stromal PD-L1 staining and infiltration of CD8-positive T cells. Data generated using an immuno-oncology gene expression panel indicated a higher level of T-cell costimulatory molecules and lower expression of type I interferon-regulated genes in lesions with SCLC transformation. These data highlight the heterogeneity of expression of immune markers depending on the metastatic sites and histological transformation and indicate that the biopsy specimen from one lesion may not be representative of immune marker status for all lesions. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Tools for outcome prediction in patients with community acquired pneumonia.

PubMed

Khan, Faheem; Owens, Mark B; Restrepo, Marcos; Povoa, Pedro; Martin-Loeches, Ignacio

2017-02-01

Community-acquired pneumonia (CAP) is one of the most common causes of mortality world-wide. The mortality rate of patients with CAP is influenced by the severity of the disease, treatment failure and the requirement for hospitalization and/or intensive care unit (ICU) management, all of which may be predicted by biomarkers and clinical scoring systems. Areas covered: We review the recent literature examining the efficacy of established and newly-developed clinical scores, biological and inflammatory markers such as C-Reactive protein (CRP), procalcitonin (PCT) and Interleukin-6 (IL-6), whether used alone or in conjunction with clinical severity scores to assess the severity of CAP, predict treatment failure, guide acute in-hospital or ICU admission and predict mortality. Expert commentary: The early prediction of treatment failure using clinical scores and biomarkers plays a developing role in improving survival of patients with CAP by identifying high-risk patients requiring hospitalization or ICU admission; and may enable more efficient allocation of resources. However, it is likely that combinations of scoring systems and biomarkers will be of greater use than individual markers. Further larger studies are needed to corroborate the additive value of these markers to clinical prediction scores to provide a safer and more effective assessment tool for clinicians.

Short-term effects of air pollution, markers of endothelial activation, and coagulation to predict major adverse cardiovascular events in patients with acute coronary syndrome: insights from AIRACOS study.

PubMed

Dominguez-Rodriguez, Alberto; Abreu-Gonzalez, Pedro; Rodríguez, Sergio; Avanzas, Pablo; Juarez-Prera, Ruben A

2017-07-01

The aim of this study was to determine whether markers of inflammation and coagulation are associated with short-term particulate matter exposure and predict major adverse cardiovascular events at 360 d in patients with acute coronary syndrome (ACS). We included 307 consecutive patients, and assessed the average concentrations of data on atmospheric pollution in ambient air and meteorological variables from 1 d up to 7 d prior to admission. In patients with ACS, the markers of endothelial activation and coagulation, but not black carbon exposure, are associated with major adverse cardiovascular events at one-year follow-up.

Neuroanatomy of the vmPFC and dlPFC predicts individual differences in cognitive regulation during dietary self-control across regulation strategies.

PubMed

Schmidt, Liane; Tusche, Anita; Manoharan, Nicolas; Hutcherson, Cendri; Hare, Todd; Plassmann, Hilke

2018-06-04

Making healthy food choices is challenging for many people. Individuals differ greatly in their ability to follow health goals in the face of temptation, but it is unclear what underlies such differences. Using voxel-based morphometry (VBM), we investigated in healthy humans (i.e., men and women) links between structural variation in gray matter volume and individuals' level of success in shifting toward healthier food choices. We combined MRI and choice data into a joint dataset by pooling across three independent studies that employed a task prompting participants to explicitly focus on the healthiness of food items before making their food choices. Within this dataset, we found that individual differences in gray matter volume in the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) predicted regulatory success. We extended and confirmed these initial findings by predicting regulatory success out of sample and across tasks in a second dataset requiring participants to apply a different regulation strategy that entailed distancing from cravings for unhealthy, appetitive foods. Our findings suggest that neuroanatomical markers in the vmPFC and dlPFC generalized to different forms of dietary regulation strategies across participant groups. They provide novel evidence that structural differences in neuroanatomy of two key regions for valuation and its control, the vmPFC and dlPFC, predict an individual's ability to exert control in dietary choices. SIGNIFICANCE STATEMENT Dieting involves regulating food choices in order to eat healthier foods and fewer unhealthy foods. People differ dramatically in their ability to achieve or maintain this regulation, but it is unclear why. Here, we show that individuals with more gray matter volume in the dorsolateral and ventromedial prefrontal cortex are better at exercising dietary self-control. This relationship was observed across four different studies examining two different forms of dietary self-regulation, suggesting that neuroanatomical differences in the vmPFC and dlPFC may represent a general marker for self-control abilities. These results identify candidate neuroanatomical markers for dieting success and failure, and suggest potential targets for therapies aimed at preventing or treating obesity and related eating disorders. Copyright © 2018 the authors.

Early Markers of Autism Spectrum Disorders in Infants and Toddlers Prospectively Identified in the Social Attention and Communication Study

ERIC Educational Resources Information Center

Barbaro, Josephine; Dissanayake, Cheryl

2013-01-01

The Social Attention and Communication Study involved the successful implementation of developmental surveillance of the early markers of autism spectrum disorders in a community-based setting. The objective in the current study was to determine the most discriminating and predictive markers of autism spectrum disorders used in the Social…

BBD Reference Set Application: Jeffery Marks-Duke (2015) — EDRN Public Portal

Cancer.gov

We propose a pre-validation study for markers that could predict the likelihood of invasive breast cancer following a tissue diagnosis of benign breast pathology (any diagnosis that is less severe than carcinoma in situ). The study is designed to test the utility of a series of markers that were shown to have some predictive value by immunohistochemical staining in other cohorts. These markers include the proliferation associated antigen KI-67, EZH2, PTGS2 (COX2), ALDH1, CDKN2A (p16), HYAL1, MMP1, CEACAM6, and TP53. In addition, we propose analyzing two markers that comprise part of the DCIS Oncotype panel, GSTM1 and progesterone receptor (PR). The study will occur in two EDRN clinical validation center (CVC) laboratories, namely Duke and University of Kansas, and utilize specimens from Northwestern University and Geisinger Health System that have been identified and are either already sectioned or waiting to be sectioned. Results will be scored and returned to the DMCC to determine whether any of the markers or combinations of these markers may have sufficient value to proceed to a second stage validation with large numbers of samples from Geisenger Health Systems and the Henry Ford Hospital.

Symptom Severity Predicts Degree of T Cell Activation In Adult Women Following Childhood Maltreatment

PubMed Central

Lemieux, Andrine; Coe, Christopher L.; Carnes, Molly

2008-01-01

Although depression is often associated with a reduction in cellular immune responses, other types of emotional disturbance and psychopathology can activate certain aspects of immunity. Activation markers on T cells, in particular, have been found to be elevated in post-traumatic stress states. However, little is known about the relationship between the severity of PTSD symptoms and the degree of change in T cell phenotypes, or about the potential role of neuroendocrine factors in mediating the association. Twenty-four women with a history of sexual trauma during childhood, including 11 who met diagnostic criteria for PTSD, were compared to 12 age-matched, healthy women without a history of maltreatment. The women provided fasted blood samples for enumeration of cell subsets by immunofluorescence and 24-hour urine samples for analysis of catecholamine and cortisol levels. The percent of T cells expressing CD45RA, an early activation marker, was higher in the PTSD diagnosed women, and the levels correlated positively with intrusive symptoms and negatively with avoidant symptoms. These alterations in cell surface markers did not appear to be mediated by norepinephrine (NE) or cortisol, making them a distinctive and independent biomarker of arousal and disturbance in PTSD. PMID:18396007

The expression ratio of Map7/B2M is prognostic for survival in patients with stage II colon cancer.

PubMed

Blum, Craig; Graham, Amanda; Yousefzadeh, Matt; Shrout, Jessica; Benjamin, Katie; Krishna, Murli; Hoda, Raza; Hoda, Rana; Cole, David J; Garrett-Mayer, Elizabeth; Reed, Carolyn; Wallace, Michael; Mitas, Michael

2008-09-01

Colorectal cancer (CRC) is the second most frequent cause of cancer-related death in the United States. To determine whether certain molecular markers might be prognostic for survival, we measured by quantitative real-time RT-PCR the expression levels of 15 previously studied genes that are known to be up-regulated or down-regulated in the progression of epithelial cancers. The tumor samples were extracted from formalin-fixed paraffin-embedded primary tissues derived from patients with Stage II CRC who developed disease recurrence within two years (n=10), or were disease-free for at least 4 years (n=12). We were able to determine, by AUC curve analysis, that the ratio of microtubule associated protein 7 (Map7)/B2M was predictive of outcome in our sample set. Further, using Kaplan-Meier survival analysis, we observed significantly different curves as a function of marker positivity for the Map7/B2M (p=0.0001; HR=11) expression ratio. This suggests that the expression ratio of Map7/B2M may serve as a valuable prognostic marker in patients with Stage II colon cancer, and potentially guide therapeutic decision making.

The expression ratio of Map7/B2M is prognostic for survival in patients with stage II colon cancer

PubMed Central

BLUM, CRAIG; GRAHAM, AMANDA; YOUSEFZADEH, MATT; SHROUT, JESSICA; BENJAMIN, KATIE; KRISHNA, MURLI; HODA, RAZA; HODA, RANA; COLE, DAVID J.; GARRETT-MAYER, ELIZABETH; REED, CAROLYN; WALLACE, MICHAEL; MITAS, MICHAEL

2012-01-01

Colorectal cancer (CRC) is the second most frequent cause of cancer-related death in the United States. To determine whether certain molecular markers might be prognostic for survival, we measured by quantitative real-time RT-PCR the expression levels of 15 previously studied genes that are known to be up-regulated or down-regulated in the progression of epithelial cancers. The tumor samples were extracted from formalin-fixed paraffin-embedded primary tissues derived from patients with Stage II CRC who developed disease recurrence within two years (n=10), or were disease-free for at least 4 years (n=12). We were able to determine, by AUC curve analysis, that the ratio of microtubule associated protein 7 (Map7)/B2M was predictive of outcome in our sample set. Further, using Kaplan-Meier survival analysis, we observed significantly different curves as a function of marker positivity for the Map7/B2M (p=0.0001; HR=11) expression ratio. This suggests that the expression ratio of Map7/B2M may serve as a valuable prognostic marker in patients with Stage II colon cancer, and potentially guide therapeutic decision making. PMID:18695889

Theranostic Biomarkers for Schizophrenia

PubMed Central

Nikolac Perkovic, Matea; Nedic Erjavec, Gordana; Svob Strac, Dubravka; Uzun, Suzana; Kozumplik, Oliver; Pivac, Nela

2017-01-01

Schizophrenia is a highly heritable, chronic, severe, disabling neurodevelopmental brain disorder with a heterogeneous genetic and neurobiological background, which is still poorly understood. To allow better diagnostic procedures and therapeutic strategies in schizophrenia patients, use of easy accessible biomarkers is suggested. The most frequently used biomarkers in schizophrenia are those associated with the neuroimmune and neuroendocrine system, metabolism, different neurotransmitter systems and neurotrophic factors. However, there are still no validated and reliable biomarkers in clinical use for schizophrenia. This review will address potential biomarkers in schizophrenia. It will discuss biomarkers in schizophrenia and propose the use of specific blood-based panels that will include a set of markers associated with immune processes, metabolic disorders, and neuroendocrine/neurotrophin/neurotransmitter alterations. The combination of different markers, or complex multi-marker panels, might help in the discrimination of patients with different underlying pathologies and in the better classification of the more homogenous groups. Therefore, the development of the diagnostic, prognostic and theranostic biomarkers is an urgent and an unmet need in psychiatry, with the aim of improving diagnosis, therapy monitoring, prediction of treatment outcome and focus on the personal medicine approach in order to improve the quality of life in patients with schizophrenia and decrease health costs worldwide. PMID:28358316

Genomic Selection in Commercial Perennial Crops: Applicability and Improvement in Oil Palm (Elaeis guineensis Jacq.).

PubMed

Kwong, Qi Bin; Ong, Ai Ling; Teh, Chee Keng; Chew, Fook Tim; Tammi, Martti; Mayes, Sean; Kulaveerasingam, Harikrishna; Yeoh, Suat Hui; Harikrishna, Jennifer Ann; Appleton, David Ross

2017-06-06

Genomic selection (GS) uses genome-wide markers to select individuals with the desired overall combination of breeding traits. A total of 1,218 individuals from a commercial population of Ulu Remis x AVROS (UR x AVROS) were genotyped using the OP200K array. The traits of interest included: shell-to-fruit ratio (S/F, %), mesocarp-to-fruit ratio (M/F, %), kernel-to-fruit ratio (K/F, %), fruit per bunch (F/B, %), oil per bunch (O/B, %) and oil per palm (O/P, kg/palm/year). Genomic heritabilities of these traits were estimated to be in the range of 0.40 to 0.80. GS methods assessed were RR-BLUP, Bayes A (BA), Cπ (BC), Lasso (BL) and Ridge Regression (BRR). All methods resulted in almost equal prediction accuracy. The accuracy achieved ranged from 0.40 to 0.70, correlating with the heritability of traits. By selecting the most important markers, RR-BLUP B has the potential to outperform other methods. The marker density for certain traits can be further reduced based on the linkage disequilibrium (LD). Together with in silico breeding, GS is now being used in oil palm breeding programs to hasten parental palm selection.

Evaluating Chagas disease progression and cure through blood-derived biomarkers: a systematic review.

PubMed

Requena-Méndez, Ana; López, Manuel Carlos; Angheben, Andrea; Izquierdo, Luis; Ribeiro, Isabela; Pinazo, Maria-Jesús; Gascon, Joaquim; Muñoz, José

2013-09-01

This article reviews the usefulness of various types of blood-derived biomarkers that are currently being studied to predict the progression of Chagas disease in patients with the indeterminate form, to assess the efficacy of antiparasitic drugs and to identify early cardiac and gastrointestinal damage. The authors used a search strategy based on MEDLINE, Cochrane Library Register for systematic review, EmBase, Global Health and LILACS databases. Out of 1716 screened articles, only 166 articles were eligible for final inclusion. The authors classified the biomarkers according to their biochemical structure and primary biological activity in four groups: i) markers of inflammation and cellular injury, ii) metabolic biomakers, iii) prothrombotic biomarkers and iv) markers derived from specific antigens of the parasite. Several potential biomarkers might have clinical potential for the detection of early cardiopathy. Such capacity is imperative in order to detect high-risk patients who require intensive monitoring and earlier therapy. Prospective studies with longer follow-ups are needed for the appraisal of biomarkers assessing clinical or microbiological cure after therapy. At the same time, studies evaluating more than one biomarker are useful to compare the efficacy among them given the lack of a recognized gold standard.

Insulin-like growth factor II mRNA-binding protein 3 (IMP3) is a marker that predicts presence of invasion in papillary biliary tumors.

PubMed

Sasaki, Motoko; Sato, Yasunori

2017-04-01

Biliary tumors showing intraductal papillary growth (Pap-BTs) include intraductal papillary neoplasm of the bile duct (IPNB) and papillary cholangiocarcinoma (CC). A differential diagnosis between IPNB and papillary CC currently remains challenging. The aim of the present study is to identify histological features and immunohistochemical markers of malignant potential such as tumor invasion in Pap-BTs. Subjects comprised 37 patients with Pap-BT (intrahepatic and perihilar [proximal], 27: 17 noninvasive and 10 invasive; distal, 10: all invasive). We examined histological features and the expression of p53, enhancer of zeste homolog 2, insulin-like growth factor II mRNA-binding protein 3 (IMP3), and DNA methyltransferase-1 in the intraductal area in Pap-BTs. Noninvasive Pap-BT was characterized by the presence of a low-grade dysplastic area, edematous stroma, and the absence of necrosis. The expression of p53, enhancer of zeste homolog 2, IMP3, and DNA methyltransferase-1 was significantly weaker in noninvasive Pap-BTs than in invasive Pap-BTs (P<.01). Diffuse cytoplasmic IMP3 expression was absent in noninvasive Pap-BTs. IMP3 showed the greatest specificity to predict a presence of invasion. A heatmap demonstrated that proximal noninvasive Pap-BTs and distal Pap-BTs may be completely different. In bile duct biopsies, the expression of IMP3 was the most precise predictor of invasion in Pap-BTs. In conclusion, Pap-BTs may be separated into 3 subgroups: (1) proximal noninvasive Pap-BT, corresponding to IPNB; (2) distal invasive Pap-BT, corresponding to papillary CC; and (3) the remaining Pap-BT including IPNB with associated adenocarcinomas, based on histological and immunohistochemical features. IMP3 may be a useful marker for predicting invasion in Pap-BT. Copyright © 2017 Elsevier Inc. All rights reserved.

Plasma cell-free DNA and qSOFA score predict 7-day mortality in 481 emergency department bacteraemia patients.

PubMed

Rannikko, Juha; Seiskari, Tapio; Huttunen, Reetta; Tarkiainen, Iina; Jylhävä, Juulia; Hurme, Mikko; Syrjänen, Jaana; Aittoniemi, Janne

2018-04-24

A few studies have shown that both quick Sequential Organ Failure Assessment (qSOFA) score and cell-free DNA (cfDNA) have potential use as a prognostic marker in patients with infection. We studied these two markers alone and in combination to identify those emergency department (ED) patients with the highest risk of death. Plasma cfDNA level was studied on days 0 to 4 after admittance to the ED from 481 culture-positive bloodstream infection cases. The qSOFA score was evaluated retrospectively according to Sepsis-3 definitions. The primary outcome was death by day 7. CfDNA on day 0 was significantly higher in non-survivors than in survivors (2.02 μg/ml vs. 1.35 μg/ml, p<0.001). CfDNA level was high (>1.69 μg/ml) in 134 (28%) out of 481 cases and the qSOFA score was ≥2 in 128 (28%) out of 458 cases. High cfDNA and qSOFA score ≥2 had 70% and 77% sensitivity and 76% and 76% specificity in predicting death by day 7, respectively. High cfDNA alone had odds ratio (OR) of 7.7 (95% CI 3.9-15.3) and qSOFA score ≥2 OR of 11.6 (5.5-24.3), but their combination had OR of 20.3 (10.0-41.4) in predicting death by day 7 when compared with those with low cfDNA and qSOFA score <2. Among the five cases with the highest cfDNA levels, there were three patients with severe disseminated intravascular coagulation. CfDNA and qSOFA score can be used independently to identify those bacteraemia patients at high risk of death, and combining these two markers gives additional advantage. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Feasibility of event-related potential (ERP) biomarker use to study effects of mother's voice exposure on speech sound differentiation of preterm infants.

PubMed

D Chorna, Olena; L Hamm, Ellyn; Shrivastava, Hemang; Maitre, Nathalie L

2018-01-01

Atypical maturation of auditory neural processing contributes to preterm-born infants' language delays. Event-related potential (ERP) measurement of speech-sound differentiation might fill a gap in treatment-response biomarkers to auditory interventions. We evaluated whether these markers could measure treatment effects in a quasi-randomized prospective study. Hospitalized preterm infants in passive or active, suck-contingent mother's voice exposure groups were not different at baseline. Post-intervention, the active group had greater increases in/du/-/gu/differentiation in left frontal and temporal regions. Infants with brain injury had lower baseline/ba/-/ga/and/du/-/gu/differentiation than those without. ERP provides valid discriminative, responsive, and predictive biomarkers of infant speech-sound differentiation.

Predictive biological markers of systemic lupus erythematosus flares: a systematic literature review.

PubMed

Gensous, Noémie; Marti, Aurélie; Barnetche, Thomas; Blanco, Patrick; Lazaro, Estibaliz; Seneschal, Julien; Truchetet, Marie-Elise; Duffau, Pierre; Richez, Christophe

2017-10-24

The aim of this study was to identify the most reliable biomarkers in the literature that could be used as flare predictors in systemic lupus erythematosus (SLE). A systematic review of the literature was performed using two databases (MEDLINE and EMBASE) through April 2015 and congress abstracts from the American College of Rheumatology and the European League Against Rheumatism were reviewed from 2010 to 2014. Two independent reviewers screened titles and abstracts and analysed selected papers in detail, using a specific questionnaire. Reports addressing the relationships between one or more defined biological test(s) and the occurrence of disease exacerbation were included in the systematic review. From all of the databases, 4668 records were retrieved, of which 69 studies or congress abstracts were selected for the systematic review. The performance of seven types of biomarkers performed routinely in clinical practice and nine types of novel biological markers was evaluated. Despite some encouraging results for anti-double-stranded DNA antibodies, anti-C1q antibodies, B-lymphocyte stimulator and tumour necrosis factor-like weak inducer of apoptosis, none of the biomarkers stood out from the others as a potential gold standard for flare prediction. The results were heterogeneous, and a lack of standardized data prevented us from identifying a powerful biomarker. No powerful conclusions could be drawn from this systematic review due to a lack of standardized data. Efforts should be undertaken to optimize future research on potential SLE biomarkers to develop validated candidates. Thus, we propose a standardized pattern for future studies.

Value of 18F-FDG PET/CT Combined With Tumor Markers in the Evaluation of Ascites.

PubMed

Han, Na; Sun, Xun; Qin, Chunxia; Hassan Bakari, Khamis; Wu, Zhijian; Zhang, Yongxue; Lan, Xiaoli

2018-05-01

The purpose of this study is to investigate the value of 18 F-FDG PET/CT combined with assessment of tumor markers in serum or ascites for the diagnosing and determining the prognosis of benign and malignant ascites. Patients with ascites of unknown cause who underwent evaluation with FDG PET/CT were included in this retrospective study. The maximum standardized uptake value (SUV max ) and levels of the tumor markers carbohydrate antigen-125 (CA-125) and carcinoembryonic antigen (CEA) in serum and ascites were recorded. The diagnostic values of FDG PET/CT, CEA and CA-125 levels in serum or ascites, and the combination of imaging plus tumor marker assessment were evaluated. Factors that were predictive of survival were also analyzed. A total of 177 patients were included. Malignant ascites was eventually diagnosed in 104 patients, and benign ascites was diagnosed in the remaining 73 patients. With the use of FDG PET/CT, 44 patients (42.3%) were found to have primary tumors. The sensitivity, specificity, and accuracy of FDG PET/CT were 92.3%, 83.6%, and 88.7%, respectively. CA-125 levels in serum and ascites showed much better sensitivity than did CEA levels, but they showed significantly lower specificity. If the combination of tumor markers and FDG PET/CT was analyzed, the sensitivity, specificity, and accuracy of tumor markers in serum were 96.6%, 78.1%, and 88.7%, and those of tumor markers in ascites were 97.7%, 80.0%, and 90.4%, respectively. Sex may be an important factor affecting survival time (hazard ratio, 0.471; p = 0.004), but age, CEA level, and FDG PET/CT findings could not predict survival. FDG PET/CT combined with assessment of tumor markers, especially CEA, increased the efficacy of diagnosis of ascites of unknown causes. Male sex conferred a poorer prognosis, whereas age, CEA level, and FDG uptake had no predictive significance in patients with malignant ascites.

Clinical Value of miR-101-3p and Biological Analysis of its Prospective Targets in Breast Cancer: A Study Based on The Cancer Genome Atlas (TCGA) and Bioinformatics.

PubMed

Li, Chun-Yao; Xiong, Dan-Dan; Huang, Chun-Qin; He, Rong-Quan; Liang, Hai-Wei; Pan, Deng-Hua; Wang, Han-Lin; Wang, Yi-Wen; Zhu, Hua-Wei; Chen, Gang

2017-04-18

BACKGROUND MiR-101-3p can promote apoptosis and inhibit proliferation, invasion, and metastasis in breast cancer (BC) cells. However, its mechanisms in BC are not fully understood. Therefore, a comprehensive analysis of the target genes, pathways, and networks of miR-101-3p in BC is necessary. MATERIAL AND METHODS The miR-101 profiles for 781 patients with BC from The Cancer Genome Atlas (TCGA) were analyzed. Gene expression profiling of GSE31397 with miR-101-3p transfected MCF-7 cells and scramble control cells was downloaded from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified. The potential genes targeted by miR-101-3p were also predicted. Gene Ontology (GO) and pathway and network analyses were constructed for the DEGs and predicted genes. RESULTS In the TCGA data, a low level of miR-101-2 expression might represent a diagnostic (AUC: 0.63) marker, and the miR-101-1 was a prognostic (HR=1.79) marker. MiR-101-1 was linked to the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), and miR-101-2 was associated with the tumor (T), lymph node (N), and metastasis (M) stages of BC. Moreover, 427 genes were selected from the 921 DEGs in GEO and the 7924 potential target genes from the prediction databases. These genes were related to transcription, metabolism, biosynthesis, and proliferation. The results were also significantly enriched in the VEGF, mTOR, focal adhesion, Wnt, and chemokine signaling pathways. CONCLUSIONS MiR-101-1 and miR-101-2 may be prospective biomarkers for the prognosis and diagnosis of BC, respectively, and are associated with diverse clinical parameters. The target genes of miR-101-3p regulate the development and progression of BC. These results provide insight into the pathogenic mechanism and potential therapies for BC.

Gene expression analysis in zebrafish embryos: a potential approach to predict effect concentrations in the fish early life stage test.

PubMed

Weil, Mirco; Scholz, Stefan; Zimmer, Michaela; Sacher, Frank; Duis, Karen

2009-09-01

Based on the hypothesis that analysis of gene expression could be used to predict chronic fish toxicity, the zebrafish (Danio rerio) embryo test (DarT), developed as a replacement method for the acute fish test, was expanded to a gene expression D. rerio embryo test (Gene-DarT). The effects of 14 substances on lethal and sublethal endpoints of the DarT and on expression of potential marker genes were investigated: the aryl hydrocarbon receptor 2, cytochrome P450 1A (cypla), heat shock protein 70, fizzy-related protein 1, the transcription factors v-maf musculoaponeurotic fibrosarcoma oncogene family protein g (avian) 1 and NF-E2-p45-related factor, and heme oxygenase 1 (hmox1). After exposure of zebrafish embryos for 48 h, differential gene expression was evaluated using reverse transcriptase-polymerase chain reaction, gel electrophoresis, and densitometric analysis of the gels. All tested compounds significantly affected the expression of at least one potential marker gene, with cyp1a and hmox1 being most sensitive. Lowest-observed-effect concentrations (LOECs) for gene expression were below concentrations resulting in 10% lethal effects in the DarT. For 10 (3,4- and 3,5-dichloroaniline, 1,4-dichlorobenzene, 2,4-dinitrophenol, atrazine, parathion-ethyl, chlorotoluron, genistein, 4-nitroquinoline-1-oxide, and cadmium) out of the 14 tested substances, LOEC values derived with the Gene-DarT differ by a factor of less than 10 from LOEC values of fish early life stage tests with zebrafish. For pentachloroaniline and pentachlorobenzene, the Gene-DarT showed a 23- and 153-fold higher sensitivity, respectively, while for lindane, it showed a 13-fold lower sensitivity. For ivermectin, the Gene-DarT was by a factor of more than 1,000 less sensitive than the acute fish test. The results of the present study indicate that gene expression analysis in zebrafish embryos could principally be used to predict effect concentrations in the fish early life stage test.

Myeloid derived suppressor cells in cancer: therapeutic, predictive, and prognostic implications

PubMed Central

Diaz-Montero, C. Marcela; Finke, Jim; Montero, Alberto J.

2014-01-01

Immune evasion is a hallmark of cancer. While, there are multiple different mechanisms that cancer cells employ, myeloid deriver suppressor cells (MDSCs) are one of the key drivers of tumor mediated immune evasion. MDSCs begin as myeloid cells recruited to the tumor microenvironment where they are transformed into potent immunosuppressive cells. Our understanding of the clinical relevance of MDSCs in cancer patients, however has significantly lagged behind the preclinical literature in part due to the absence of a cognate molecule present in mice, as well as the considerable heterogeneity of MDSCs. However, if one evaluates the clinical literature through the filter of clinically robust endpoints, such as overall survival, three important phenotypes have emerged: promyelocytic, monocytic, and granulocytic. Based on these studies, MDSCs have clear prognostic importance in multiple solid tumors, and emerging data supports the utility of circulating MDSCs as a predictive marker for cancer immunotherapy, and even as an early leading marker for predicting clinical response to systemic chemotherapy in patients with advanced solid tumors. More recent preclinical data in immunosuppressed murine models suggest that MDSCs play an important role in tumor progression and the metastatic process that is independent of their immunosuppressive properties. Consequently, targeting MDSCs either in combination with cancer immunotherapy or independently as part of an approach to inhibit the metastatic process, appears to be a very clinically promising strategy. We review different approaches to target MDSCs that could potentially be tested in future clinical trials in cancer patients. PMID:24787291

Genetic diversity and distribution of Senegalia senegal (L.) Britton under climate change scenarios in West Africa.

PubMed

Lyam, Paul Terwase; Duque-Lazo, Joaquín; Durka, Walter; Hauenschild, Frank; Schnitzler, Jan; Michalak, Ingo; Ogundipe, Oluwatoyin Temitayo; Muellner-Riehl, Alexandra Nora

2018-01-01

Climate change is predicted to impact species' genetic diversity and distribution. We used Senegalia senegal (L.) Britton, an economically important species distributed in the Sudano-Sahelian savannah belt of West Africa, to investigate the impact of climate change on intraspecific genetic diversity and distribution. We used ten nuclear and two plastid microsatellite markers to assess genetic variation, population structure and differentiation across thirteen sites in West Africa. We projected suitable range, and potential impact of climate change on genetic diversity using a maximum entropy approach, under four different climate change scenarios. We found higher genetic and haplotype diversity at both nuclear and plastid markers than previously reported. Genetic differentiation was strong for chloroplast and moderate for the nuclear genome. Both genomes indicated three spatially structured genetic groups. The distribution of Senegalia senegal is strongly correlated with extractable nitrogen, coarse fragments, soil organic carbon stock, precipitation of warmest and coldest quarter and mean temperature of driest quarter. We predicted 40.96 to 6.34 per cent of the current distribution to favourably support the species' ecological requirements under future climate scenarios. Our results suggest that climate change is going to affect the population genetic structure of Senegalia senegal, and that patterns of genetic diversity are going to influence the species' adaptive response to climate change. Our study contributes to the growing evidence predicting the loss of economically relevant plants in West Africa in the next decades due to climate change.

Genetic diversity and distribution of Senegalia senegal (L.) Britton under climate change scenarios in West Africa

PubMed Central

Duque-Lazo, Joaquín; Durka, Walter; Hauenschild, Frank; Schnitzler, Jan; Michalak, Ingo; Ogundipe, Oluwatoyin Temitayo; Muellner-Riehl, Alexandra Nora

2018-01-01

Climate change is predicted to impact species’ genetic diversity and distribution. We used Senegalia senegal (L.) Britton, an economically important species distributed in the Sudano-Sahelian savannah belt of West Africa, to investigate the impact of climate change on intraspecific genetic diversity and distribution. We used ten nuclear and two plastid microsatellite markers to assess genetic variation, population structure and differentiation across thirteen sites in West Africa. We projected suitable range, and potential impact of climate change on genetic diversity using a maximum entropy approach, under four different climate change scenarios. We found higher genetic and haplotype diversity at both nuclear and plastid markers than previously reported. Genetic differentiation was strong for chloroplast and moderate for the nuclear genome. Both genomes indicated three spatially structured genetic groups. The distribution of Senegalia senegal is strongly correlated with extractable nitrogen, coarse fragments, soil organic carbon stock, precipitation of warmest and coldest quarter and mean temperature of driest quarter. We predicted 40.96 to 6.34 per cent of the current distribution to favourably support the species’ ecological requirements under future climate scenarios. Our results suggest that climate change is going to affect the population genetic structure of Senegalia senegal, and that patterns of genetic diversity are going to influence the species’ adaptive response to climate change. Our study contributes to the growing evidence predicting the loss of economically relevant plants in West Africa in the next decades due to climate change. PMID:29659603

Non-invasive oxidative stress markers for liver fibrosis development in the evolution of toxic hepatitis.

PubMed

Clichici, Simona; Catoi, C; Mocan, T; Filip, A; Login, C; Nagy, A; Daicoviciu, D; Decea, N; Gherman, C; Moldovan, R; Muresan, Adriana

2011-06-01

Oxidative stress is related to the liver fibrosis, anticipating the hepatic stellate cells' (HSC) activation. Our aim was to correlate oxidative stress markers with the histological liver alterations in order to identify predictive, noninvasive parameters of fibrosis progression in the evolution of toxic hepatitis.CCl4 in sunflower oil was administered to rats intragastrically, twice a week. After 2, 3, 4 and 8 weeks of treatment, plasma levels of malondialdehyde (MDA), protein carbonyls (PC), hydrogen donor capacity (HD), sulfhydryl groups (SH), and glutathione (GSH) were measured and histological examination of the liver slides was performed. Dynamics of histological disorders was assessed by The Knodell score. Significant elevation of inflammation grade was obtained after the second week of the experiment only (p=0.001), while fibrosis started to become significant (p=0.001) after 1 month of CCl4 administration. Between plasma MDA and liver fibrosis development a good correlation was obtained (r=0.877, p=0.05). Correlation between PC dynamics and liver alterations was marginally significant for inflammation grade (r=0.756, p=0.138). HD evolution revealed a marginally inverse correlation with inflammation grade (r=-0.794, p=0.108). No correlations could be established for other parameters with either inflammation grade or fibrosis stage.Our study shows that MDA elevation offers the best prediction potential for fibrosis, while marginal prediction fiability could be attributed to high levels of plasma PC and low levels of HD.

Mechanistic biomarkers provide early and sensitive detection of acetaminophen-induced acute liver injury at first presentation to hospital

PubMed Central

Antoine, Daniel J; Dear, James W; Lewis, Philip Starkey; Platt, Vivien; Coyle, Judy; Masson, Moyra; Thanacoody, Ruben H; Gray, Alasdair J; Webb, David J; Moggs, Jonathan G; Bateman, D Nicholas; Goldring, Christopher E; Park, B Kevin

2013-01-01

Acetaminophen overdose is a common reason for hospital admission and the most frequent cause of hepatotoxicity in the Western world. Early identification would facilitate patient-individualized treatment strategies. We investigated the potential of a panel of novel biomarkers (with enhanced liver expression or linked to the mechanisms of toxicity) to identify patients with acetaminophen-induced acute liver injury (ALI) at first presentation to the hospital when currently used markers are within the normal range. In the first hospital presentation plasma sample from patients (n = 129), we measured microRNA-122 (miR-122; high liver specificity), high mobility group box-1 (HMGB1; marker of necrosis), full-length and caspase-cleaved keratin-18 (K18; markers of necrosis and apoptosis), and glutamate dehydrogenase (GLDH; marker of mitochondrial dysfunction). Receiver operator characteristic curve analysis and positive/negative predictive values were used to compare sensitivity to report liver injury versus alanine transaminase (ALT) and International Normalized Ratio (INR). In all patients, biomarkers at first presentation significantly correlated with peak ALT or INR. In patients presenting with normal ALT or INR, miR-122, HMGB1, and necrosis K18 identified the development of liver injury (n = 15) or not (n = 84) with a high degree of accuracy and significantly outperformed ALT, INR, and plasma acetaminophen concentration for the prediction of subsequent ALI (n = 11) compared with no ALI (n = 52) in patients presenting within 8 hours of overdose. Conclusion: Elevations in plasma miR-122, HMGB1, and necrosis K18 identified subsequent ALI development in patients on admission to the hospital, soon after acetaminophen overdose, and in patients with ALTs in the normal range. The application of such a biomarker panel could improve the speed of clinical decision-making, both in the treatment of ALI and the design/execution of patient-individualized treatment strategies. PMID:23390034

Combining the audit questionnaire and biochemical markers to assess alcohol use and risk of alcohol withdrawal in medical inpatients.

PubMed

Dolman, Jonathan M; Hawkes, Neil D

2005-01-01

Alcohol consumption is often under-reported in patients admitted to general hospitals with acute illness. For alcohol-dependent individuals hospital admission results in an enforced period of abstinence with potential alcohol withdrawal symptoms, and possible life threatening complications. Early detection of alcohol use is therefore beneficial to patients and health services. The purpose of this study was to investigate the performance of the alcohol use disorders identification test (AUDIT) questionnaire in the acute medical setting, and the effect of combining routine biological markers-glutamyltransferase, alanine aminotransferase, aspartate aminotransferase, and mean corpuscular volume (MCV) on its performance in the early identification of in-patients with alcohol use disorders and at risk of developing symptoms of alcohol withdrawal. Prospective study in consecutive patients admitted to an acute medical admissions ward. All patients were screened using the AUDIT questionnaire and routine blood tests. Patients were then monitored for symptoms of withdrawal using clinical institute withdrawal assessment for alcohol (CIWA-Ar). Of the 874 patients screened using the AUDIT, 98 (11%) screened positive of whom 17 (2% of the 874) experienced clinically significant alcohol withdrawal symptoms, when using serial CIWA-Ar. The AUDIT and serial CIWA-Ar detected all patients who went on to manifest acute withdrawal symptoms. There was no loss of sensitivity at an AUDIT cut-off of 13 or more compared with the lower cut-off of 8 or more. A positive predictive value of 17.3% for an AUDIT score of 8 or more in the detection of withdrawal, increased to 47.1% when found in combination with at least two abnormal biological markers whilst maintaining a sensitivity of 94.1% and specificity of 97.9%. These findings confirm that AUDIT is a useful alcohol screen in general medical settings and that its ability to correctly predict which patients will experience alcohol withdrawal is increased when used in combination with biological markers.

"Anti-Mullerian Hormone: Marker for Ovarian Response in Controlled Ovarian Stimulation for IVF Patients": A First Pilot Study in the Indian Population.

PubMed

Singh, Neeta; Malik, Ekta; Banerjee, Ayan; Chosdol, Kunzang; Sreenivas, V; Mittal, Suneeta

2013-08-01

To measure the levels of early follicular phase Anti-Mullerian hormone (AMH) in Indian patients of IVF and to evaluate the AMH as a predictive marker of ovarian response in assisted reproductive technology outcome. Sixty women (age 25-40 years) selected for in vitro fertilization treatment were included in this study. Analysis of day-2 serum samples was done for the AMH, FSH, Inhibin B, and LH by ELISA kit methods. USG was done for the antral follicle count (AFC) and oocytes' retrieval. Hormone parameters were compared and correlated with the oocytes' retrieval count and the AFC. The discriminant analysis was done to compare relevance of different parameters for predicting ovarian response. The Anti-Mullerian hormone showed a significant correlation with the oocytes' retrieval after ovulation induction for IVF (r = 0.648, p < 0.0001) and no correlation was seen with serum FSH, LH, and Inhibin. Serum AMH levels show 80 % sensitivity and 80 % specificity in predicting poor ovarian response. There is a significant correlation between day-2 serum AMH levels and the oocytes' retrieval count in women undergoing ovulation induction for IVF, and the AMH is a good marker as the negative predictive values for the success of ART. There is no correlation found between other hormonal ovarian reserve markers and the oocytes' retrieval count.

Predicting impending death: inconsistency in speed is a selective and early marker.

PubMed

Macdonald, Stuart W S; Hultsch, David F; Dixon, Roger A

2008-09-01

Among older adults, deficits in both level and variability of speeded performance are linked to neurological impairment. This study examined whether and when speed (rate), speed (inconsistency), and traditional accuracy-based markers of cognitive performance foreshadow terminal decline and impending death. Victoria Longitudinal Study data spanning 12 years (5 waves) of measurement were assembled for 707 adults aged 59 to 95 years. Whereas 442 survivors completed all waves and relevant measures, 265 decedents participated on at least 1 occasion and subsequently died. Four main results were observed. First, Cox regressions evaluating the 3 cognitive predictors of mortality replicated previous results for cognitive accuracy predictors. Second, level (rate) of speeded performance predicted survival independent of demographic indicators, cardiovascular health, and cognitive performance level. Third, inconsistency in speed predicted survival independent of all influences combined. Fourth, follow-up random-effects models revealed increases in inconsistency in speed per year closer to death, with advancing age further moderating the accelerated growth. Hierarchical prediction patterns support the view that inconsistency in speed is an early behavioral marker of neurological dysfunction associated with impending death. (c) 2008 APA, all rights reserved

Predicting Impending Death: Inconsistency in Speed is a Selective and Early Marker

PubMed Central

MacDonald, Stuart W.S.; Hultsch, David F.; Dixon, Roger A.

2008-01-01

Among older adults, deficits in both level and variability of speeded performance are linked to neurological impairment. This study examined whether and when speed (rate), speed (inconsistency), and traditional accuracy-based markers of cognitive performance foreshadow terminal decline and impending death. Victoria Longitudinal Study data spanning 12 years (5 waves) of measurement were assembled for 707 adults aged 59 to 95 years. Whereas 442 survivors completed all waves and relevant measures, 265 decedents participated on at least one occasion and subsequently died. Four main results were observed. First, Cox regressions evaluating the three cognitive predictors of mortality replicated previous results for cognitive accuracy predictors. Second, level (rate) of speeded performance predicted survival independent of demographic indicators, cardiovascular health, and cognitive performance level. Third, inconsistency in speed predicted survival independent of all influences combined. Fourth, follow-up random-effects models revealed increases in inconsistency in speed per year closer to death, with advancing age further moderating the accelerated growth. Hierarchical prediction patterns support the view that inconsistency in speed is an early behavioral marker of neurological dysfunction associated with impending death. PMID:18808249

Individualization of controlled ovarian stimulation in vitro fertilization using ovarian reserve markers.

PubMed

Grisendi, Valentina; La Marca, Antonio

2017-06-01

In assisted reproduction technologies (ART) the controlled ovarian stimulation (COS) therapy is the starting point from which a good oocytes retrieval depends. Treatment individualization is based on ovarian response prediction, which largely depends on a woman's ovarian reserve. Anti-Müllerian hormone (AMH) and antral follicle count (AFC) are considered the most accurate and reliable markers of ovarian reserve. A literature search was carried out for studies that addressed the ability of AMH and AFC to predict poor and/or excessive ovarian response in IVF cycles. According to the predicted response to ovarian stimulation (poor- normal- or high-response) is today possible not only to personalize pre-treatment counseling with the couple, but also to individualize the ovarian stimulation protocol, choosing among GnRH-agonists or antagonists for endogenous follicle-stimulating hormone (FSH) suppression and formulating the FSH starting dose most adequate for the single patients. In this review we discuss how to choose the best COS therapy for the single patient, on the basis of the markers-guided ovarian response prediction.

Performance of prognostic markers in the prediction of wound healing or amputation among patients with foot ulcers in diabetes: a systematic review.

PubMed

Brownrigg, J R W; Hinchliffe, R J; Apelqvist, J; Boyko, E J; Fitridge, R; Mills, J L; Reekers, J; Shearman, C P; Zierler, R E; Schaper, N C

2016-01-01

Prediction of wound healing and major amputation in patients with diabetic foot ulceration is clinically important to stratify risk and target interventions for limb salvage. No consensus exists as to which measure of peripheral artery disease (PAD) can best predict outcomes. To evaluate the prognostic utility of index PAD measures for the prediction of healing and/or major amputation among patients with active diabetic foot ulceration, two reviewers independently screened potential studies for inclusion. Two further reviewers independently extracted study data and performed an assessment of methodological quality using the Quality in Prognostic Studies instrument. Of 9476 citations reviewed, 11 studies reporting on 9 markers of PAD met the inclusion criteria. Annualized healing rates varied from 18% to 61%; corresponding major amputation rates varied from 3% to 19%. Among 10 studies, skin perfusion pressure ≥ 40 mmHg, toe pressure ≥ 30 mmHg (and ≥ 45 mmHg) and transcutaneous pressure of oxygen (TcPO2 ) ≥ 25 mmHg were associated with at least a 25% higher chance of healing. Four studies evaluated PAD measures for predicting major amputation. Ankle pressure < 70 mmHg and fluorescein toe slope < 18 units each increased the likelihood of major amputation by around 25%. The combined test of ankle pressure < 50 mmHg or an ankle brachial index (ABI) < 0.5 increased the likelihood of major amputation by approximately 40%. Among patients with diabetic foot ulceration, the measurement of skin perfusion pressures, toe pressures and TcPO2 appear to be more useful in predicting ulcer healing than ankle pressures or the ABI. Conversely, an ankle pressure of < 50 mmHg or an ABI < 0.5 is associated with a significant increase in the incidence of major amputation. Copyright © 2015 John Wiley & Sons, Ltd.

Network pharmacology analysis of the anti-cancer pharmacological mechanisms of Ganoderma lucidum extract with experimental support using Hepa1-6-bearing C57 BL/6 mice.

PubMed

Zhao, Ruo-Lin; He, Yu-Min

2018-01-10

Ganoderma lucidum (GL) is an oriental medical fungus, which was used to prevent and treat many diseases. Previously, the effective compounds of Ganoderma lucidum extract (GLE) were extracted from two kinds of GL, [Ganoderma lucidum (Leyss. Ex Fr.) Karst.] and [Ganoderma sinense Zhao, Xu et Zhang], which have been used for adjuvant anti-cancer clinical therapy for more than 20 years. However, its concrete active compounds and its regulation mechanisms on tumor are unclear. In this study, we aimed to identify the main active compounds from GLE and to investigate its anti-cancer mechanisms via drug-target biological network construction and prediction. The main active compounds of GLE were identified by HPLC, EI-MS and NMR, and the compounds related targets were predicted using docking program. To investigate the functions of GL holistically, the active compounds of GL and related targets were predicted based on four public databases. Subsequently, the Identified-Compound-Target network and Predicted-Compound-Target network were constructed respectively, and they were overlapped to detect the hub potential targets in both networks. Furthermore, the qRT-PCR and western-blot assays were used to validate the expression levels of target genes in GLE treated Hepa1-6-bearing C57 BL/6 mice. In our work, 12 active compounds of GLE were identified, including Ganoderic acid A, Ganoderenic acid A, Ganoderic acid B, Ganoderic acid H, Ganoderic acid C2, Ganoderenic acid D, Ganoderic acid D, Ganoderenic acid G, Ganoderic acid Y, Kaemferol, Genistein and Ergosterol. Using the docking program, 20 targets were mapped to 12 compounds of GLE. Furthermore, 122 effective active compounds of GL and 116 targets were holistically predicted using public databases. Compare with the Identified-Compound-Target network and Predicted-Compound-Target network, 6 hub targets were screened, including AR, CHRM2, ESR1, NR3C1, NR3C2 and PGR, which was considered as potential markers and might play important roles in the process of GLE treatment. GLE effectively inhibited tumor growth in Hepa1-6-bearing C57 BL/6 mice. Finally, consistent with the results of qRT-PCR data, the results of western-blot assay demonstrated the expression levels of PGR and ESR1 were up-regulated, as well as the expression levels of NR3C2 and AR were down-regulated, while the change of NR3C1 and CHRM2 had no statistical significance. The results indicated that these 4 hub target genes, including NR3C2, AR, ESR1 and PGR, might act as potential markers to evaluate the curative effect of GLE treatment in tumor. And, the combined data provide preliminary study of the pharmacological mechanisms of GLE, which may be a promising potential therapeutic and chemopreventative candidate for anti-cancer. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Recommendations for research priorities in breast cancer by the Coalition of Cancer Cooperative Groups Scientific Leadership Council: systemic therapy and therapeutic individualization.

PubMed

Sparano, Joseph A; Hortobagyi, Gabriel N; Gralow, Julie R; Perez, Edith A; Comis, Robert L

2010-02-01

Over 9,000 women with breast cancer are enrolled annually on clinical trials sponsored by the National Cancer Institute (NCI), accounting for about one-third of all patients enrolled on NCI-sponsored trials. Thousands are also enrolled on pharmaceutical-sponsored studies. Although breast cancer mortality rates have recently declined for the first time in part due to systemic therapeutic advances, coordinated efforts will be necessary to maintain this trend. The Coalition of Cancer Cooperative Groups convened the Scientific Leadership Council in breast cancer (BC), an expert panel, to identify priorities for future research and current trials with greatest practice-changing potential. Panelists formed a consensus on research priorities for chemoprevention, development and application of molecular markers for predicting therapeutic benefit and toxicity, intermediate markers predictive of therapeutic effect, pathogenesis-based therapeutic approaches, utilization of adaptive designs requiring fewer patients to achieve objectives, special and minority populations, and effects of BC and treatment on patients and families. Panelists identified 13 ongoing studies as High Priority and identified gaps in the current trial portfolio. We propose priorities for current and future clinical breast cancer research evaluating systemic therapies that may serve to improve the efficiency of clinical trials, identify individuals most likely to derive therapeutic benefit, and prioritize therapeutic strategies.

Taxane-mediated radiosensitization derives from chromosomal missegregation on tripolar mitotic spindles orchestrated by AURKA and TPX2.

PubMed

Orth, M; Unger, K; Schoetz, U; Belka, C; Lauber, K

2018-01-04

Taxane-based radiochemotherapy is a central treatment option for various cancer entities in locally advanced stages. The therapeutic synergism of this combined modality approach due to taxane-mediated radiosensitization of cancer cells is well-known. However, the underlying molecular mechanisms remain largely elusive, and mechanism-derived predictive markers of taxane-based radiochemotherapy are currently not available. Here, we show that clinically relevant doses of Paclitaxel, the prototype taxane, stimulate a tripolar mode of mitosis leading to chromosomal missegregation and aneuploidization rather than interfering with cell cycle progression. This distinct mitotic phenotype was interlinked with Paclitaxel-mediated radiosensitization via overexpression of mitotic Aurora kinase A (AURKA) and its cofactor TPX2 whose knockdown rescued the bipolar mode of cell division and largely attenuated the radiosensitizing effects of Paclitaxel. In the cancer genome atlas (TCGA) lung adenocarcinoma cohort, high expression levels of AURKA and TPX2 were associated with specifically improved overall survival upon taxane-based radiochemotherapy, but not in case of non-taxane-based radiochemotherapy, chemo- or radiotherapy only. Thus, our data provide insights into Paclitaxel-mediated radiosensitization on a mechanistic and molecular level and identify AURKA and TPX2 as the first potential mechanism-based, predictive markers of taxane-based radiochemotherapy.

Two markers in predicting the cardiovascular events in patients with polycystic ovary syndrome: increased P-wave and QT dispersion.

PubMed

Akdag, S; Cim, N; Yildizhan, R; Akyol, A; Ozturk, F; Babat, N

2015-09-01

Polycystic ovary syndrome (PCOS) is a prevalent disease with many potential long-term cardiovascular risks. P-wave dispersion (Pdis) and QT dispersion (QTdis) have been shown to be noninvasive electrocardiographic predictors for development of cardiac arrhythmias. In this study we aimed to search Pdis and QTdis parameters in patients with PCOS. The study included 82 patients with PCOS and 74 age- and sex-matched healthy controls. Baseline 12-lead electrocardiographic and transthoracic echocardiographic measurements were evaluated. P-wave maximum duration (Pmax), P-wave minimum duration (Pmin), Pdis, QT interval, heart rate-corrected QT dispersion and QTdis were calculated by two cardiologists. Patients wirh PCOS had significantly higher QT dispersion (49.5 ± 14.1 vs. 37.9 ± 12.6 ms, p < 0.001), and P wave dispersion (54.2 ± 11.4 vs. 45.9 ± 10.1 ms, p < 0.001) than the controls. Serum testosterone and estradiol levels was correlated with the Pdis (r = 0.677, p < 0.001 and r = 0.415, p < 0.001 respectively) and QTdis (r = 0.326, p < 0.001 and r = 0.321, p < 0.001 respectively). Pdis and QTdis are simple and useful electrocardiographic markers which may be used in the prediction of the risk of adverse cardiovascular events in PCOS patients.

Clinical manifestation, serology marker & microscopic agglutination test (MAT) to mortality in human leptospirosis

NASA Astrophysics Data System (ADS)

Perdhana, S. A. P.; Susilo, R. S. B.; Arifin; Redhono, D.; Sumandjar, T.

2018-03-01

Leptospirosis is a potentially fatal zoonosis that is endemic in many tropical regions and causes large epidemics after heavy rainfall and flooding. Severe disease is estimated 5–15% of all human infections. Its mortality rate is 5-40%. MAT, isolation of the organism, or leptospiral DNA in PCR are used to confirm Leptospirosis. This cross-sectional analytic study recruited 26 hospitalized leptospirosis patients admitted to Dr. Moewardi Hospital Surakarta. The diagnosis was based on clinical, laboratory and epidemiological findings. The onset of the disease was the date when the first symptom started, and the end of the analysis was the date when the patient died or discharged. Modified Faine’s score ≥ 25 tend to die (45.5%) while modified Faine’s score 20 – 24 tend to heal (60%) (OR 1.250; CI 0.259-6.029; p=1.0). Seropositive IgM predicts mortality 7.8 times higher than seronegative IgM (OR 7.800; CI 1.162-52.353; p=0.038). MAT positive predict mortality 10.667 times higher than MAT negative (OR 10.667; CI 1.705-66.720; p=0.015). Clinical manifestation, MAT, and serologic marker are all correlated with mortality in Leptospirosis. However, statistically, clinical manifestation has an insignificant correlation.

Exploring the role of molecular biomarkers as a potential weapon against gastric cancer: A review of the literature.

PubMed

Matboli, Marwa; El-Nakeep, Sarah; Hossam, Nourhan; Habieb, Alaa; Azazy, Ahmed E M; Ebrahim, Ali E; Nagy, Ziad; Abdel-Rahman, Omar

2016-07-14

Gastric cancer (GC) is a global health problem and a major cause of cancer-related death with high recurrence rates ranging from 25% to 40% for GC patients staging II-IV. Unfortunately, while the majority of GC patients usually present with advanced tumor stage; there is still limited evidence-based therapeutic options. Current approach to GC management consists mainly of; endoscopy followed by, gastrectomy and chemotherapy or chemo-radiotherapy. Recent studies in GC have confirmed that it is a heterogeneous disease. Many molecular characterization studies have been performed in GC. Recent discoveries of the molecular pathways underlying the disease have opened the door to more personalized treatment and better predictable outcome. The identification of molecular markers is a useful tool for clinical managementin GC patients, assisting in diagnosis, evaluation of response to treatment and development of novel therapeutic modalities. While chemotherapeutic agents have certain physiological effects on the tumor cells, the prediction of the response is different from one type of tumor to the other. The specificity of molecular biomarkers is a principal feature driving their application in anticancer therapies. Here we are trying to focus on the role of molecular pathways of GC and well-established molecular markers that can guide the therapeutic management.

Epileptiform abnormalities predict delayed cerebral ischemia in subarachnoid hemorrhage.

PubMed

Kim, J A; Rosenthal, E S; Biswal, S; Zafar, S; Shenoy, A V; O'Connor, K L; Bechek, S C; Valdery Moura, J; Shafi, M M; Patel, A B; Cash, S S; Westover, M B

2017-06-01

To identify whether abnormal neural activity, in the form of epileptiform discharges and rhythmic or periodic activity, which we term here ictal-interictal continuum abnormalities (IICAs), are associated with delayed cerebral ischemia (DCI). Retrospective analysis of continuous electroencephalography (cEEG) reports and medical records from 124 patients with moderate to severe grade subarachnoid hemorrhage (SAH). We identified daily occurrence of seizures and IICAs. Using survival analysis methods, we estimated the cumulative probability of IICA onset time for patients with and without delayed cerebral ischemia (DCI). Our data suggest the presence of IICAs indeed increases the risk of developing DCI, especially when they begin several days after the onset of SAH. We found that all IICA types except generalized rhythmic delta activity occur more commonly in patients who develop DCI. In particular, IICAs that begin later in hospitalization correlate with increased risk of DCI. IICAs represent a new marker for identifying early patients at increased risk for DCI. Moreover, IICAs might contribute mechanistically to DCI and therefore represent a new potential target for intervention to prevent secondary cerebral injury following SAH. These findings imply that IICAs may be a novel marker for predicting those at higher risk for DCI development. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Molecular Markers for Breast Cancer: Prediction on Tumor Behavior

PubMed Central

Banin Hirata, Bruna Karina; Oda, Julie Massayo Maeda; Losi Guembarovski, Roberta; Ariza, Carolina Batista; de Oliveira, Carlos Eduardo Coral; Watanabe, Maria Angelica Ehara

2014-01-01

Breast cancer is one of the most common cancers with greater than 1,300,000 cases and 450,000 deaths each year worldwide. The development of breast cancer involves a progression through intermediate stages until the invasive carcinoma and finally into metastatic disease. Given the variability in clinical progression, the identification of markers that could predict the tumor behavior is particularly important in breast cancer. The determination of tumor markers is a useful tool for clinical management in cancer patients, assisting in diagnostic, staging, evaluation of therapeutic response, detection of recurrence and metastasis, and development of new treatment modalities. In this context, this review aims to discuss the main tumor markers in breast carcinogenesis. The most well-established breast molecular markers with prognostic and/or therapeutic value like hormone receptors, HER-2 oncogene, Ki-67, and p53 proteins, and the genes for hereditary breast cancer will be presented. Furthermore, this review shows the new molecular targets in breast cancer: CXCR4, caveolin, miRNA, and FOXP3, as promising candidates for future development of effective and targeted therapies, also with lower toxicity. PMID:24591761

Bidirectional Prospective Associations Between Cardiac Autonomic Activity and Inflammatory Markers.

PubMed

Hu, Mandy Xian; Lamers, Femke; Neijts, Melanie; Willemsen, Gonneke; de Geus, Eco J C; Penninx, Brenda W J H

2018-06-01

Autonomic nervous system (ANS) imbalance has been cross-sectionally associated with inflammatory processes. Longitudinal studies are needed to shed light on the nature of this relationship. We examined cross-sectional and bidirectional prospective associations between cardiac autonomic measures and inflammatory markers. Analyses were conducted with baseline (n = 2823), 2-year (n = 2099), and 6-year (n = 1774) data from the Netherlands Study of Depression and Anxiety. To compare the pattern of results, prospective analyses with ANS (during sleep, leisure time, and work) and inflammation were conducted in two data sets from the Netherlands Twin Register measured for 4.9 years (n = 356) and 5.4 years (n = 472). Autonomic nervous system measures were heart rate (HR) and respiratory sinus arrhythmia (RSA). Inflammatory markers were C-reactive protein (CRP) and interleukin (IL)-6. The Netherlands Study of Depression and Anxiety results showed that higher HR and lower RSA were cross-sectionally significantly associated with higher inflammatory levels. Higher HR predicted higher levels of CRP (B = .065, p < .001) and IL-6 (B = .036, p = .014) at follow-up. Higher CRP levels predicted lower RSA (B = -.024, p = .048) at follow-up. The Netherlands Twin Register results confirmed that higher HR was associated with higher CRP and IL-6 levels 4.9 years later. Higher IL-6 levels predicted higher HR and lower RSA at follow-up. Autonomic imbalance is associated with higher levels of inflammation. Independent data from two studies converge in evidence that higher HR predicts subsequent higher levels of CRP and IL-6. Inflammatory markers may also predict future ANS activity, but evidence for this was less consistent.

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

Exosomal microRNAs in seminal plasma are markers of the origin of azoospermia and can predict the presence of sperm in testicular tissue.

PubMed

Barceló, Maria; Mata, Ana; Bassas, Lluís; Larriba, Sara

2018-06-01

Are exosomal microRNAs (miRNAs) in seminal plasma (SP) useful as markers of the origin of azoospermia and the presence of sperm in the testis? Our study demonstrated the potential of several miRNAs contained in small extracellular vesicles (sEVs) of seminal fluid as sensitive and specific biomarkers for selecting those azoospermic individuals with real chances of obtaining spermatozoa from the testicular biopsy. There are no precise non-invasive diagnostic methods for classifying the origin of the sperm defects in semen and the spermatogenic reserve of the testis in those infertile men with a total absence of sperm in the ejaculate (azoospermia). The diagnosis of such individuals is often based on the practice of biopsies. In this context it is reasonable to study the presence of organ-specific markers in human semen that contains fluid from the testis and the male reproductive glands, which could help in the diagnosis and prognosis of male infertility. Additionally, seminal fluid contains high concentrations of sEVs that are morphologically and molecularly consistent with exosomes, which originate from multiple cellular sources in the male reproductive tract. A case and control prospective study was performed. This study compares the miRNA content of exosomes in semen samples obtained from nine normozoospermic fertile individuals (control group), 14 infertile men diagnosed with azoospermia due to spermatogenic failure, and 13 individuals with obstructive azoospermia and conserved spermatogenesis. Additionally, three severe oligozoospermic individuals (<5 × 106 sperm/ml) were included in the study. A differential high-throughput miRNA profiling analysis using miRNA quantitative PCR panels was performed in SP exosomes from azoospermic patients and fertile individuals. A total of 623 miRNAs were included in the miRNA profiling stage of the study. A total of 397 miRNAs (63.7%) were consistently detected in samples from all groups and statistically analysed, which revealed altered patterns of miRNA expression in infertile patients. We focused on the miRNAs that were differentially expressed between azoospermia as a result of an obstruction in the genital tract (i.e. having conserved spermatogenesis) and azoospermia caused by spermatogenic failure, and described, in a miRNA validation stage of the study, the expression values of one miRNA (miR-31-5p) in exosomes from semen as a predictive biomarker test for the origin of azoospermia with high sensitivity and specificity (>90%). The efficacy of the predictive test was even better when the blood FSH values were included in the analysis. Furthermore a model that included miR-539-5p and miR-941 expression values is also described as being useful for predicting the presence of residual spermatogenesis in individuals with severe spermatogenic disorders with diagnostic accuracy. Further studies, with an independent second population involving a larger number of samples, are needed to confirm our findings. Our findings contribute to the search for the most valuable genetic markers that are potentially useful as tools for predicting the presence of testicular sperm in azoospermic individuals. This work was financially supported by grants from the Fondo de Investigaciones Sanitarias/Fondo Europeo de Desarrollo Regional "Una manera de hacer Europa" (FIS/FEDER) [Grant number PI15/00153], the Generalitat de Catalunya [Grant number 2014SGR5412]. S.L. is sponsored by the Researchers Stabilization Program (ISCIII/Generalitat de Catalunya) from the Spanish National Health System [CES09/020].

Identification of contact and respiratory sensitizers according to IL-4 receptor α expression and IL-2 production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goutet, Michèle, E-mail: michele.goutet@inrs.fr; Pépin, Elsa; Langonné, Isabelle

2012-04-15

Identification of allergenic chemicals is an important occupational safety issue. While several methods exist to identify contact sensitizers, there is currently no validated model to predict the potential of chemicals to act as respiratory sensitizers. Previously, we reported that cytometry analysis of the local immune responses induced in mice dermally exposed to the respiratory sensitizer trimellitic anhydride (TMA 10%) and contact sensitizer dinitrochlorobenzene (DNCB 1%) could identify divergent expression of several immune parameters. The present study confirms, first, that IgE-positive B cells, MHC class II molecules, interleukin (IL)-2, IL-4 and IL-4Rα can differentiate the allergic reactions caused by high dosesmore » of strong respiratory (TMA, phthalic anhydride and toluene diisocyanate) and contact sensitizers (DNCB, dinitrofluorobenzene and oxazolone). The second part of the study was designed to test the robustness of these markers when classing the weakly immunogenic chemicals most often encountered. Six respiratory allergens, including TMA (2.5%), five contact allergens, including DNCB (0.25%), and two irritants were compared at doses of equivalent immunogenicity. The results indicated that IL-4Rα and IL-2 can be reliably used to discriminate sensitizers. Respiratory sensitizers induced markedly higher IL-4Rα levels than contact allergens, while irritants had no effect on this parameter. Inversely, contact allergens tended to induce higher percentages of IL-2{sup +}CD8{sup +} cells than respiratory allergens. In contrast, the markers MHC-II, IgE and IL-4 were not able to classify chemicals with low immunogenic potential. In conclusion, IL-4Rα and IL-2 have the potential to be used in classifying a variety of chemical allergens. -- Highlights: ► Identification of chemical allergens is an important occupational safety issue. ► There is currently no model to predict the potential of chemicals to induce asthma. ► We analyze immune responses induced in mice by a variety of chemical sensitizers. ► IL-2 and IL-4R alpha show potential to discriminate between both types of allergens. ► This method could be applied to highly and weakly immunogenic chemicals.« less

CCL3L1-CCR5 genotype improves the assessment of AIDS Risk in HIV-1-infected individuals.

PubMed

Kulkarni, Hemant; Agan, Brian K; Marconi, Vincent C; O'Connell, Robert J; Camargo, Jose F; He, Weijing; Delmar, Judith; Phelps, Kenneth R; Crawford, George; Clark, Robert A; Dolan, Matthew J; Ahuja, Sunil K

2008-09-08

Whether vexing clinical decision-making dilemmas can be partly addressed by recent advances in genomics is unclear. For example, when to initiate highly active antiretroviral therapy (HAART) during HIV-1 infection remains a clinical dilemma. This decision relies heavily on assessing AIDS risk based on the CD4+ T cell count and plasma viral load. However, the trajectories of these two laboratory markers are influenced, in part, by polymorphisms in CCR5, the major HIV coreceptor, and the gene copy number of CCL3L1, a potent CCR5 ligand and HIV-suppressive chemokine. Therefore, we determined whether accounting for both genetic and laboratory markers provided an improved means of assessing AIDS risk. In a prospective, single-site, ethnically-mixed cohort of 1,132 HIV-positive subjects, we determined the AIDS risk conveyed by the laboratory and genetic markers separately and in combination. Subjects were assigned to a low, moderate or high genetic risk group (GRG) based on variations in CCL3L1 and CCR5. The predictive value of the CCL3L1-CCR5 GRGs, as estimated by likelihood ratios, was equivalent to that of the laboratory markers. GRG status also predicted AIDS development when the laboratory markers conveyed a contrary risk. Additionally, in two separate and large groups of HIV+ subjects from a natural history cohort, the results from additive risk-scoring systems and classification and regression tree (CART) analysis revealed that the laboratory and CCL3L1-CCR5 genetic markers together provided more prognostic information than either marker alone. Furthermore, GRGs independently predicted the time interval from seroconversion to CD4+ cell count thresholds used to guide HAART initiation. The combination of the laboratory and genetic markers captures a broader spectrum of AIDS risk than either marker alone. By tracking a unique aspect of AIDS risk distinct from that captured by the laboratory parameters, CCL3L1-CCR5 genotypes may have utility in HIV clinical management. These findings illustrate how genomic information might be applied to achieve practical benefits of personalized medicine.

Prediction of Response to Sorafenib in Hepatocellular Carcinoma: A Putative Marker Panel by Multiple Reaction Monitoring-Mass Spectrometry (MRM-MS).

PubMed

Kim, Hyunsoo; Yu, Su Jong; Yeo, Injun; Cho, Young Youn; Lee, Dong Hyeon; Cho, Yuri; Cho, Eun Ju; Lee, Jeong-Hoon; Kim, Yoon Jun; Lee, Sungyoung; Jun, Jongsoo; Park, Taesung; Yoon, Jung-Hwan; Kim, Youngsoo

2017-07-01

Sorafenib is the only standard treatment for unresectable hepatocellular carcinoma (HCC), but it provides modest survival benefits over placebo, necessitating predictive biomarkers of the response to sorafenib. Serum samples were obtained from 115 consecutive patients with HCC before sorafenib treatment and analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) and ELISA to quantify candidate biomarkers. We verified a triple-marker panel to be predictive of the response to sorafenib by MRM-MS, comprising CD5 antigen-like (CD5L), immunoglobulin J (IGJ), and galectin-3-binding protein (LGALS3BP), in HCC patients. This panel was a significant predictor (AUROC > 0.950) of the response to sorafenib treatment, having the best cut-off value (0.4) by multivariate analysis. In the training set, patients who exceeded this cut-off value had significantly better overall survival (median, 21.4 months) than those with lower values (median, 8.6 months; p = 0.001). Further, a value that was lower than this cutoff was an independent predictor of poor overall survival [hazard ratio (HR), 2.728; 95% confidence interval (CI), 1.312-5.672; p = 0.007] and remained an independent predictive factor of rapid progression (HR, 2.631; 95% CI, 1.448-4.780; p = 0.002). When applied to the independent validation set, levels of the cut-off value for triple-marker panel maintained their prognostic value for poor clinical outcomes. On the contrast, the triple-marker panel was not a prognostic factor for patients who were treated with transarterial chemoembolization (TACE). The discriminatory signature of a triple-marker panel provides new insights into targeted proteomic biomarkers for individualized sorafenib therapy. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Evaluation of the Value of d-Dimer, P-Selectin, and Platelet Count for Prediction of Portal Vein Thrombosis After Devascularization.

PubMed

Fei, Yang; Zong, Guang-Quan; Chen, Jian; Liu, Ren-Min

2016-07-01

To evaluate the value of d-dimer, P-selectin, and platelet count in patients with cirrhotic portal hypertension (PHT) for prediction of portal vein thrombosis (PVT) after devascularization. A total of 137 patients with cirrhotic PHT who undergone devascularization from January 2012 to April 2014 were retrospectively reviewed, all of them were divided into 2 groups (PVT group and non-PVT group) by Doppler ultrasonography (DU) examination. The level of d-dimer, P-selectin, and platelet count was tested during the perioperative period. In all, 38 (27.7%) patients were found to have PVT by DU examination postoperatively. In contrast to the non-PVT group, the level of d-dimer, P-selectin, and platelet count in the PVT group was much higher significantly at 1, 3, and 7 days after devascularization. (P < .05). However, in the 15 days after surgery, the difference in P-selectin between the 2 groups was not significant (P = .260). It was shown that the highest sensitivity of the 3 markers for PVT was d-dimer, the highest specificity belonged to P-selectin. The area under receiver-operating characteristic (ROC) curve of P-selectin was the biggest of the 3 markers. When the 3 markers were combined to be used to diagnose PVT, the sensitivity was increased to 0.907, with a slight drop of specificity to 0.693, the area under the ROC curve was 0.927. The level of d-dimer, P-selectin, and platelet count might be good candidate predictive markers for PVT in patients with cirrhotic PHT after devascularization. The combined test of the 3 markers can increase the value of prediction. © The Author(s) 2015.

Correlation between lower balance of Th2 helper T-cells and expression of PD-L1/PD-1 axis genes enables prognostic prediction in patients with glioblastoma.

PubMed

Takashima, Yasuo; Kawaguchi, Atsushi; Kanayama, Tomohiko; Hayano, Azusa; Yamanaka, Ryuya

2018-04-10

Common cancer treatments include radiation therapy, chemotherapy including molecular targeted drugs and anticancer drugs, and surgical treatment. Recent studies have focused on investigating the mechanisms by which immune cells attack cancer cells and produce immune tolerance-suppressing cytokines, as well as on their potential application in cancer immunotherapy. We conducted expression profiling of CD274 ( PD-L1 ), GATA3, IFNG, IL12R, IL12RB2, IL4, PDCD1 ( PD-1 ), PDCD1LG2 ( PD-L2 ), and TBX21 ( T-bet ) using data of 158 glioblastoma multiforme (GBM) patients with clinical information available at The Cancer Genome Atlas. Principal component analysis of the expression profiling data was used to derive an equation for evaluating the status of Th1 and Th2 cells. GBM specimens were divided based on the median of the Th scores. The results revealed that Th1 High Th2 Low and Th1 Low Th2 Low statuses indicated better prognosis than Th1 High Th2 High , and were evaluated based on the downregulation of PD-L1, PD-L2, and PD-1. Furthermore, Th2 Low divided based on the threshold, as well as CD274 Low and PDCD1 Low , were associated with good prognosis. In the Th2 Low subgroup, 14 genes were identified as potential prognostic markers. Of these, SLC11A1 Low , TNFRSF1B Low , and LTBR Low also indicated good prognosis. These results suggest that low Th2 balance and low activity of the PD-L1/PD-1 axis predict good prognosis in GBM. The set of genes identified in the present study could reliably predict survival in GBM patients and serve as useful molecular markers. Furthermore, this set of genes could prove to be novel targets for cancer immunotherapy.

Prognostic Cell Biological Markers in Cervical Cancer Patients Primarily Treated With (Chemo)radiation: A Systematic Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noordhuis, Maartje G.; Eijsink, Jasper J.H.; Roossink, Frank

2011-02-01

The aim of this study was to systematically review the prognostic and predictive significance of cell biological markers in cervical cancer patients primarily treated with (chemo)radiation. A PubMed, Embase, and Cochrane literature search was performed. Studies describing a relation between a cell biological marker and survival in {>=}50 cervical cancer patients primarily treated with (chemo)radiation were selected. Study quality was assessed, and studies with a quality score of 4 or lower were excluded. Cell biological markers were clustered on biological function, and the prognostic and predictive significance of these markers was described. In total, 42 studies concerning 82 cell biologicalmore » markers were included in this systematic review. In addition to cyclooxygenase-2 (COX-2) and serum squamous cell carcinoma antigen (SCC-ag) levels, markers associated with poor prognosis were involved in epidermal growth factor receptor (EGFR) signaling (EGFR and C-erbB-2) and in angiogenesis and hypoxia (carbonic anhydrase 9 and hypoxia-inducible factor-1{alpha}). Epidermal growth factor receptor and C-erbB-2 were also associated with poor response to (chemo)radiation. In conclusion, EGFR signaling is associated with poor prognosis and response to therapy in cervical cancer patients primarily treated with (chemo)radiation, whereas markers involved in angiogenesis and hypoxia, COX-2, and serum SCC-ag levels are associated with a poor prognosis. Therefore, targeting these pathways in combination with chemoradiation may improve survival in advanced-stage cervical cancer patients.« less

Genomic prediction using phenotypes from pedigreed lines with no marker data

USDA-ARS?s Scientific Manuscript database

Until now genomic prediction in plant breeding has only used information from individuals that have been genotyped. In practice, information from non-genotyped relatives of genotyped individuals can be used to improve the genomic prediction accuracy. Single-step genomic prediction integrates all the...

Molecular markers of carcinogenesis for risk stratification of individuals with colorectal polyps: a case-control study.

PubMed

Gupta, Samir; Sun, Han; Yi, Sang; Storm, Joy; Xiao, Guanghua; Balasubramanian, Bijal A; Zhang, Song; Ashfaq, Raheela; Rockey, Don C

2014-10-01

Risk stratification using number, size, and histology of colorectal adenomas is currently suboptimal for identifying patients at increased risk for future colorectal cancer. We hypothesized that molecular markers of carcinogenesis in adenomas, measured via immunohistochemistry, may help identify high-risk patients. To test this hypothesis, we conducted a retrospective, 1:1 matched case-control study (n = 216; 46% female) in which cases were patients with colorectal cancer and synchronous adenoma and controls were patients with adenoma but no colorectal cancer at baseline or within 5 years of follow-up. In phase I of analyses, we compared expression of molecular markers of carcinogenesis in case and control adenomas, blind to case status. In phase II of analyses, patients were randomly divided into independent training and validation groups to develop a model for predicting case status. We found that seven markers [p53, p21, Cox-2, β-catenin (BCAT), DNA-dependent protein kinase (DNApkcs), survivin, and O6-methylguanine-DNA methyltransferase (MGMT)] were significantly associated with case status on unadjusted analyses, as well as analyses adjusted for age and advanced adenoma status (P < 0.01 for at least one marker component). When applied to the validation set, a predictive model using these seven markers showed substantial accuracy for identifying cases [area under the receiver operation characteristic curve (AUC), 0.83; 95% confidence interval (CI), 0.74-0.92]. A parsimonious model using three markers performed similarly to the seven-marker model (AUC, 0.84). In summary, we found that molecular markers of carcinogenesis distinguished adenomas from patients with and without colorectal cancer. Furthermore, we speculate that prospective studies using molecular markers to identify individuals with polyps at risk for future neoplasia are warranted. ©2014 American Association for Cancer Research.