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1

Primer: strategies for identifying genes involved in renal disease  

Microsoft Academic Search

The globally increasing number of patients with end-stage renal disease urges the identification of molecular pathways involved in renal pathophysiology, to serve as targets for intervention. Moreover, the identification of genetic risk factors or protective genes can aid tailored therapy. Tools that can be used to identify genes involved in renal disease include gene expression arrays, linkage analysis and association

Ariela Benigni; Giuseppe Remuzzi; Martin H de Borst

2008-01-01

2

Identifying disease genes and module biomarkers by differential interactions  

PubMed Central

Objective A complex disease is generally caused by the mutation of multiple genes or by the dysfunction of multiple biological processes. Systematic identification of causal disease genes and module biomarkers can provide insights into the mechanisms underlying complex diseases, and help develop efficient therapies or effective drugs. Materials and Methods In this paper, we present a novel approach to predict disease genes and identify dysfunctional networks or modules, based on the analysis of differential interactions between disease and control samples, in contrast to the analysis of differential gene or protein expressions widely adopted in existing methods. Results and Discussion As an example, we applied our method to the study of three-stage microarray data for gastric cancer. We identified network modules or module biomarkers that include a set of genes related to gastric cancer, implying the predictive power of our method. The results on holdout validation data sets show that our identified module can serve as an effective module biomarker for accurately detecting or diagnosing gastric cancer, thereby validating the efficiency of our method. Conclusion We proposed a new approach to detect module biomarkers for diseases, and the results on gastric cancer demonstrated that the differential interactions are useful to detect dysfunctional modules in the molecular interaction network, which in turn can be used as robust module biomarkers.

Liu, Zhi-Ping; Zhao, Xing-Ming; Chen, Luonan

2011-01-01

3

Identifying Mendelian disease genes with the Variant Effect Scoring Tool  

PubMed Central

Background Whole exome sequencing studies identify hundreds to thousands of rare protein coding variants of ambiguous significance for human health. Computational tools are needed to accelerate the identification of specific variants and genes that contribute to human disease. Results We have developed the Variant Effect Scoring Tool (VEST), a supervised machine learning-based classifier, to prioritize rare missense variants with likely involvement in human disease. The VEST classifier training set comprised ~ 45,000 disease mutations from the latest Human Gene Mutation Database release and another ~45,000 high frequency (allele frequency >1%) putatively neutral missense variants from the Exome Sequencing Project. VEST outperforms some of the most popular methods for prioritizing missense variants in carefully designed holdout benchmarking experiments (VEST ROC AUC = 0.91, PolyPhen2 ROC AUC = 0.86, SIFT4.0 ROC AUC = 0.84). VEST estimates variant score p-values against a null distribution of VEST scores for neutral variants not included in the VEST training set. These p-values can be aggregated at the gene level across multiple disease exomes to rank genes for probable disease involvement. We tested the ability of an aggregate VEST gene score to identify candidate Mendelian disease genes, based on whole-exome sequencing of a small number of disease cases. We used whole-exome data for two Mendelian disorders for which the causal gene is known. Considering only genes that contained variants in all cases, the VEST gene score ranked dihydroorotate dehydrogenase (DHODH) number 2 of 2253 genes in four cases of Miller syndrome, and myosin-3 (MYH3) number 2 of 2313 genes in three cases of Freeman Sheldon syndrome. Conclusions Our results demonstrate the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bioinformatics in assisting the search for disease genes in large-scale exome sequencing studies. VEST is available as a stand-alone software package at http://wiki.chasmsoftware.org and is hosted by the CRAVAT web server at http://www.cravat.us

2013-01-01

4

Identifying disease feature genes based on cellular localized gene functional modules and regulation networks  

Microsoft Academic Search

Identifying disease-relevant genes and functional modules, based on gene expression profiles and gene functional knowledge,\\u000a is of high importance for studying disease mechanisms and subtyping disease phenotypes. Using gene categories of biological\\u000a process and cellular component in Gene Ontology, we propose an approach to selecting functional modules enriched with differentially\\u000a expressed genes, and identifying the feature functional modules of high

Min Zhang; Jing Zhu; Zheng Guo; Xia Li; Da Yang; Lei Wang; Shaoqi Rao

2006-01-01

5

Transcriptomic and genetic studies identify IL33 as a candidate gene for Alzheimer's disease  

Microsoft Academic Search

The only recognized genetic determinant of the common forms of Alzheimer's disease (AD) is the ?4 allele of the apolipoprotein E gene (APOE). To identify new candidate genes, we recently performed transcriptomic analysis of 2741 genes in chromosomal regions of interest using brain tissue of AD cases and controls. From 82 differentially expressed genes, 1156 polymorphisms were genotyped in two

J Chapuis; D Hot; F Hansmannel; O Kerdraon; S Ferreira; C Hubans; C A Maurage; L Huot; F Bensemain; G Laumet; A M Ayral; N Fievet; J J Hauw; S T DeKosky; Y Lemoine; T Iwatsubo; F Wavrant-Devrièze; J F Dartigues; C Tzourio; L Buée; F Pasquier; C Berr; D Mann; C Lendon; A Alpérovitch; M I Kamboh; P Amouyel; J C Lambert

2009-01-01

6

MIClique: An Algorithm to Identify Differentially Coexpressed Disease Gene Subset from Microarray Data  

PubMed Central

Computational analysis of microarray data has provided an effective way to identify disease-related genes. Traditional disease gene selection methods from microarray data such as statistical test always focus on differentially expressed genes in different samples by individual gene prioritization. These traditional methods might miss differentially coexpressed (DCE) gene subsets because they ignore the interaction between genes. In this paper, MIClique algorithm is proposed to identify DEC gene subsets based on mutual information and clique analysis. Mutual information is used to measure the coexpression relationship between each pair of genes in two different kinds of samples. Clique analysis is a commonly used method in biological network, which generally represents biological module of similar function. By applying the MIClique algorithm to real gene expression data, some DEC gene subsets which correlated under one experimental condition but uncorrelated under another condition are detected from the graph of colon dataset and leukemia dataset.

Zhang, Huanping; Song, Xiaofeng; Wang, Huinan; Zhang, Xiaobai

2009-01-01

7

Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions  

PubMed Central

Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions—that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/).

Raychaudhuri, Soumya; Plenge, Robert M.; Rossin, Elizabeth J.; Ng, Aylwin C. Y.; Purcell, Shaun M.; Sklar, Pamela; Scolnick, Edward M.; Xavier, Ramnik J.; Altshuler, David; Daly, Mark J.

2009-01-01

8

Identifying gene-disease associations using centrality on a literature mined gene-interaction network  

PubMed Central

Motivation: Understanding the role of genetics in diseases is one of the most important aims of the biological sciences. The completion of the Human Genome Project has led to a rapid increase in the number of publications in this area. However, the coverage of curated databases that provide information manually extracted from the literature is limited. Another challenge is that determining disease-related genes requires laborious experiments. Therefore, predicting good candidate genes before experimental analysis will save time and effort. We introduce an automatic approach based on text mining and network analysis to predict gene-disease associations. We collected an initial set of known disease-related genes and built an interaction network by automatic literature mining based on dependency parsing and support vector machines. Our hypothesis is that the central genes in this disease-specific network are likely to be related to the disease. We used the degree, eigenvector, betweenness and closeness centrality metrics to rank the genes in the network. Results: The proposed approach can be used to extract known and to infer unknown gene-disease associations. We evaluated the approach for prostate cancer. Eigenvector and degree centrality achieved high accuracy. A total of 95% of the top 20 genes ranked by these methods are confirmed to be related to prostate cancer. On the other hand, betweenness and closeness centrality predicted more genes whose relation to the disease is currently unknown and are candidates for experimental study. Availability: A web-based system for browsing the disease-specific gene-interaction networks is available at: http://gin.ncibi.org Contact: radev@umich.edu

Ozgur, Arzucan; Vu, Thuy; Erkan, Gunes; Radev, Dragomir R.

2008-01-01

9

A proposal of a novel experimental procedure to genetically identify disease gene loci in humans.  

PubMed

Forward genetics in humans is beneficial in terms of diagnosis and treatment of genetic diseases, and discovery of gene functions. However, experimental mating is not possible among humans. In order to overcome this problem, I propose a novel experimental procedure to genetically identify human disease gene loci. To accomplish this, somatic cells from patients or their parents are reprogrammed to the pluripotent state, oogenesis is induced, the oocytes are parthenogenetically activated in the presence of cytochalasin, and embryonic stem cells are established from the parthenogenetic blastocysts. This protocol produces a set of diploid pluripotent stem cell clones having maternal and paternal chromosomes in different manners to each other. The genetic loci for the disease genes are determined through the conventional processes of positional cloning. Thus, taking advantage of the strategy proposed here, if the abnormality is reproducible using patient-derived pluripotent stem cells, a single carrier of the genetic mutations would be adequate to identify the disease gene loci. PMID:21422742

Muto, Taro

2011-01-01

10

Integrated immunogenomics in the chicken: deciphering the immune response to identify disease resistance genes.  

PubMed

Resistance to infection takes place at many levels, and involves both non-specific and specific immune mechanisms. The chicken has a different repertoire of immune genes, molecules, cells and organs compared to mammals. To understand the role of any disease resistance gene(s), it is therefore important to understand these different repertoires, and the bird's response to a particular pathogen. Our studies focus on the innate immune response, as responses of macrophages from inbred lines of chickens, and heterophils from commercial birds, correlate with resistance or susceptibility to Salmonella infection with a variety of Salmonella serovars and infection models. To map disease resistance genes, we are using a combination of expression quantitative trait loci (eQTLs) from microarray studies, allied with whole genome SNP arrays (WGA) and a candidate gene approach. There are over 500 human genes with the Gene Ontology term "innate immunity". We have identified over 400 of these genes in the chicken genome, and are actively identifying informative SNPs in them. The segregation of 6000 WGA SNPs across all of our inbred lines was also assessed, which should yield approximately 900 informative SNPs for a cross between any two lines. The initial focus of these studies is on mapping resistance genes in our inbred lines, but the studies will be extended to commercial flocks. PMID:18817286

Kaiser, P; Howell, J; Fife, M; Sadeyen, J R; Salmon, N; Rothwell, L; Young, J; van Diemen, P; Stevens, M; Poh, T Y; Jones, M; Barrow, P; Swaggerty, C; Kogut, M; Smith, J; Burt, D

2008-01-01

11

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.  

PubMed

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

12

Mini Review Identifying human disease genes: advances in molecular genetics and computational approaches.  

PubMed

The human genome project is one of the significant achievements that have provided detailed insight into our genetic legacy. During the last two decades, biomedical investigations have gathered a considerable body of evidence by detecting more than 2000 disease genes. Despite the imperative advances in the genetic understanding of various diseases, the pathogenesis of many others remains obscure. With recent advances, the laborious methodologies used to identify DNA variations are replaced by direct sequencing of genomic DNA to detect genetic changes. The ability to perform such studies depends equally on the development of high-throughput and economical genotyping methods. Currently, basically for every disease whose origen is still unknown, genetic approaches are available which could be pedigree-dependent or -independent with the capacity to elucidate fundamental disease mechanisms. Computer algorithms and programs for linkage analysis have formed the foundation for many disease gene detection projects, similarly databases of clinical findings have been widely used to support diagnostic decisions in dysmorphology and general human disease. For every disease type, genome sequence variations, particularly single nucleotide polymorphisms are mapped by comparing the genetic makeup of case and control groups. Methods that predict the effects of polymorphisms on protein stability are useful for the identification of possible disease associations, whereas structural effects can be assessed using methods to predict stability changes in proteins using sequence and/or structural information. PMID:25061732

Bakhtiar, S M; Ali, A; Baig, S M; Barh, D; Miyoshi, A; Azevedo, V

2014-01-01

13

DNA methylation map of mouse and human brain identifies target genes in Alzheimer's disease.  

PubMed

The central nervous system has a pattern of gene expression that is closely regulated with respect to functional and anatomical regions. DNA methylation is a major regulator of transcriptional activity, and aberrations in the distribution of this epigenetic mark may be involved in many neurological disorders, such as Alzheimer's disease. Herein, we have analysed 12 distinct mouse brain regions according to their CpG 5'-end gene methylation patterns and observed their unique epigenetic landscapes. The DNA methylomes obtained from the cerebral cortex were used to identify aberrant DNA methylation changes that occurred in two mouse models of Alzheimer's disease. We were able to translate these findings to patients with Alzheimer's disease, identifying DNA methylation-associated silencing of three targets genes: thromboxane A2 receptor (TBXA2R), sorbin and SH3 domain containing 3 (SORBS3) and spectrin beta 4 (SPTBN4). These hypermethylation targets indicate that the cyclic AMP response element-binding protein (CREB) activation pathway and the axon initial segment could contribute to the disease. PMID:24030951

Sanchez-Mut, Jose V; Aso, Ester; Panayotis, Nicolas; Lott, Ira; Dierssen, Mara; Rabano, Alberto; Urdinguio, Rocio G; Fernandez, Agustin F; Astudillo, Aurora; Martin-Subero, Jose I; Balint, Balazs; Fraga, Mario F; Gomez, Antonio; Gurnot, Cecile; Roux, Jean-Christophe; Avila, Jesus; Hensch, Takao K; Ferrer, Isidre; Esteller, Manel

2013-10-01

14

Functional screening in Drosophila identifies Alzheimer's disease susceptibility genes and implicates Tau-mediated mechanisms.  

PubMed

Using a Drosophila model of Alzheimer's disease (AD), we systematically evaluated 67 candidate genes based on AD-associated genomic loci (P < 10(-4)) from published human genome-wide association studies (GWAS). Genetic manipulation of 87 homologous fly genes was tested for modulation of neurotoxicity caused by human Tau, which forms neurofibrillary tangle pathology in AD. RNA interference (RNAi) targeting 9 genes enhanced Tau neurotoxicity, and in most cases reciprocal activation of gene expression suppressed Tau toxicity. Our screen implicates cindr, the fly ortholog of the human CD2AP AD susceptibility gene, as a modulator of Tau-mediated disease mechanisms. Importantly, we also identify the fly orthologs of FERMT2 and CELF1 as Tau modifiers, and these loci have been independently validated as AD susceptibility loci in the latest GWAS meta-analysis. Both CD2AP and FERMT2 have been previously implicated with roles in cell adhesion, and our screen additionally identifies a fly homolog of the human integrin adhesion receptors, ITGAM and ITGA9, as a modifier of Tau neurotoxicity. Our results highlight cell adhesion pathways as important in Tau toxicity and AD susceptibility and demonstrate the power of model organism genetic screens for the functional follow-up of human GWAS. PMID:24067533

Shulman, Joshua M; Imboywa, Selina; Giagtzoglou, Nikolaos; Powers, Martin P; Hu, Yanhui; Devenport, Danelle; Chipendo, Portia; Chibnik, Lori B; Diamond, Allison; Perrimon, Norbert; Brown, Nicholas H; De Jager, Philip L; Feany, Mel B

2014-02-15

15

Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease  

PubMed Central

Background Alzheimer’s disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling. Results Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (SR) based method followed by prioritization using clusters derived from PPI network. SR for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes. Conclusions With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD.

2014-01-01

16

Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10  

PubMed Central

A broad region of chromosome 10 (chr10) has engendered continued interest in the etiology of late-onset Alzheimer Disease (LOAD) from both linkage and candidate gene studies. However, there is a very extensive heterogeneity on chr10. We converged linkage analysis and gene expression data using the concept of genomic convergence that suggests that genes showing positive results across multiple different data types are more likely to be involved in AD. We identified and examined 28 genes on chr10 for association with AD in a Caucasian case-control dataset of 506 cases and 558 controls with substantial clinical information. The cases were all LOAD (minimum age at onset ? 60 years). Both single marker and haplotypic associations were tested in the overall dataset and 8 subsets defined by age, gender, ApoE and clinical status. PTPLA showed allelic, genotypic and haplotypic association in the overall dataset. SORCS1 was significant in the overall data sets (p=0.0025) and most significant in the female subset (allelic association p=0.00002, a 3-locus haplotype had p=0.0005). Odds Ratio of SORCS1 in the female subset was 1.7 (p<0.0001). SORCS1 is an interesting candidate gene involved in the A? pathway. Therefore, genetic variations in PTPLA and SORCS1 may be associated and have modest effect to the risk of AD by affecting A? pathway. The replication of the effect of these genes in different study populations and search for susceptible variants and functional studies of these genes are necessary to get a better understanding of the roles of the genes in Alzheimer disease.

Liang, Xueying; Slifer, Michael; Martin, Eden R.; Schnetz-Boutaud, Nathalie; Bartlett, Jackie; Anderson, Brent; Zuchner, Stephan; Gwirtsman, Harry; Gilbert, John R.; Pericak-Vance, Margaret A.; Haines, Jonathan L.

2009-01-01

17

Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10.  

PubMed

A broad region of chromosome 10 (chr10) has engendered continued interest in the etiology of late-onset Alzheimer Disease (LOAD) from both linkage and candidate gene studies. However, there is a very extensive heterogeneity on chr10. We converged linkage analysis and gene expression data using the concept of genomic convergence that suggests that genes showing positive results across multiple different data types are more likely to be involved in AD. We identified and examined 28 genes on chr10 for association with AD in a Caucasian case-control dataset of 506 cases and 558 controls with substantial clinical information. The cases were all LOAD (minimum age at onset > or = 60 years). Both single marker and haplotypic associations were tested in the overall dataset and 8 subsets defined by age, gender, ApoE and clinical status. PTPLA showed allelic, genotypic and haplotypic association in the overall dataset. SORCS1 was significant in the overall data sets (p=0.0025) and most significant in the female subset (allelic association p=0.00002, a 3-locus haplotype had p=0.0005). Odds Ratio of SORCS1 in the female subset was 1.7 (p<0.0001). SORCS1 is an interesting candidate gene involved in the Abeta pathway. Therefore, genetic variations in PTPLA and SORCS1 may be associated and have modest effect to the risk of AD by affecting Abeta pathway. The replication of the effect of these genes in different study populations and search for susceptible variants and functional studies of these genes are necessary to get a better understanding of the roles of the genes in Alzheimer disease. PMID:19241460

Liang, Xueying; Slifer, Michael; Martin, Eden R; Schnetz-Boutaud, Nathalie; Bartlett, Jackie; Anderson, Brent; Züchner, Stephan; Gwirtsman, Harry; Gilbert, John R; Pericak-Vance, Margaret A; Haines, Jonathan L

2009-03-01

18

Identifying genes for coronary artery disease: An idea whose time has come  

PubMed Central

BACKGROUND: Coronary artery disease (CAD) remains the number one killer in the western world. Genetics accounts for greater than 50% of the risk for CAD. Genetic screening and early prevention in individuals identified as being at increased risk could dramatically reduce the prevalence of CAD, thus necessitating the identification of genes predisposing to CAD. Studies of genes identified by the candidate gene approach have not been replicated due, in part, to inadequate sample size. Genome-wide scan association studies have been limited by the use of thousands of markers rather than the hundreds of thousands required, and by the use of hundreds of individuals rather than the thousands required. Replication of positive findings in an independent population is essential. To detect a minor allele frequency of 5% or greater with an odds ratio for risk of 1.3 or greater and 90% power, an estimated 14,000 (9000 affected and 5000 control) subjects are required. METHODS: The Affymetrix GeneChip Human Mapping 500K Array Set (Affymetrix Inc, USA) provides a marker every 6000 base pairs as required, and is being used to genotype 1000 cases of premature CAD and 1000 normal subjects, followed by replication in 8000 affected individuals and 4000 control subjects. The phenotype is confirmed or excluded by coronary arteriograms by catheterization or multislice computed tomography. RESULTS: Since 2005, more than 800 million genotypes have been performed and analyses performed on 500 control subjects and 500 affected individuals. Several thousand significant single nucleotide polymorphisms and 130 clusters associated with CAD have been identified. CONCLUSIONS: This is the first genome-wide scan using the 500,000 marker set in a case-control association study for CAD genes. Several genes associated with CAD appear promising.

Roberts, Robert; Stewart, Alexandre FR; Wells, George A; Williams, Kathryn A; Kavaslar, Nihan; McPherson, Ruth

2007-01-01

19

[Analysis of disease-pathway by identifying susceptible genes to primary biliary cirrhosis].  

PubMed

High concordance rate in monozygotic twins and familial clustering of patients with primary biliary cirrhosis (PBC) indicate the involvement of strong genetic factors in the development of PBC. Recent genome-wide association studies (GWASs) and subsequent meta-analyses in European descent have identified HLA and 21 non-HLA susceptibility loci which are involved in IL12/IL12R signaling, TNF/TLR-NFKB signaling and B cell differentiation in the development of PBC. To identify susceptibility loci for PBC in Japanese population, a GWAS and subsequent replication study was performed in a total of 1327 PBC cases and 1120 healthy controls. In addition to the most significant susceptibility region at HLA, two significant (p<5×10(-8)) susceptibility loci (TNFSF15 and POU2AF1) were identified. Although these susceptibility loci are different from those identified in European descent (IL12A, IL12RB2, SPIB), these loci are involved in the same signaling pathways, differentiation of T lymphocyte to Th1 cells and differentiation of B lymphocyte to plasma cells. Among 21 non-HLA susceptibility loci for PBC identified in GWASs of European descent, 10 loci (CD80, IKZF3, IL7R, NFKB1, STAT4, TNFAIP2, CXCR5, MAP3K7IP1, rs6974491, DENND1B) showed significant associations in the Japanese population. The comparative analysis of disease-susceptibility genes in multiple ethnicities may provide an important clue for the dissection of disease-pathogenesis. PMID:23291485

Nakamura, Minoru; Makamura, Minoru

2012-01-01

20

Genome Screen to Identify Susceptibility Genes for Parkinson Disease in a Sample without parkin Mutations  

PubMed Central

Parkinson disease (PD) is a common neurodegenerative disorder characterized by bradykinesia, resting tremor, muscular rigidity, and postural instability, as well as by a clinically significant response to treatment with levodopa. Mutations in the ?-synuclein gene have been found to result in autosomal dominant PD, and mutations in the parkin gene produce autosomal recessive juvenile-onset PD. We have studied 203 sibling pairs with PD who were evaluated by a rigorous neurological assessment based on (a) inclusion criteria consisting of clinical features highly associated with autopsy-confirmed PD and (b) exclusion criteria highly associated with other, non-PD pathological diagnoses. Families with positive LOD scores for a marker in an intron of the parkin gene were prioritized for parkin-gene testing, and mutations in the parkin gene were identified in 22 families. To reduce genetic heterogeneity, these families were not included in subsequent genome-screen analysis. Thus, a total of 160 multiplex families without evidence of a parkin mutation were used in multipoint nonparametric linkage analysis to identify PD-susceptibility genes. Two models of PD affection status were considered: model I included only those individuals with a more stringent diagnosis of verified PD (96 sibling pairs from 90 families), whereas model II included all examined individuals as affected, regardless of their final diagnostic classification (170 sibling pairs from 160 families). Under model I, the highest LOD scores were observed on chromosome X (LOD score 2.1) and on chromosome 2 (LOD score 1.9). Analyses performed with all available sibling pairs (model II) found even greater evidence of linkage to chromosome X (LOD score 2.7) and to chromosome 2 (LOD score 2.5). Evidence of linkage was also found to chromosomes 4, 5, and 13 (LOD scores >1.5). Our findings are consistent with those of other linkage studies that have reported linkage to chromosomes 5 and X.

Pankratz, Nathan; Nichols, William C.; Uniacke, Sean K.; Halter, Cheryl; Rudolph, Alice; Shults, Cliff; Conneally, P. Michael; Foroud, Tatiana

2002-01-01

21

GSEA-SNP identifies genes associated with Johne’s disease in cattle  

Microsoft Academic Search

SNP-based gene-set enrichment analysis from single nucleotide polymorphisms, or GSEA-SNP, is a tool to identify candidate\\u000a genes based on enrichment analysis of sets of genes rather than single SNP associations. The objective of this study was to\\u000a identify modest-effect genes associated with Mycobacterium avium subsp. paratuberculosis (Map) tissue infection or fecal shedding using GSEA-SNP applied to KEGG pathways or Gene

Holly L. Neibergs; Matthew L. Settles; Robert H. Whitlock; Jeremy F. Taylor

2010-01-01

22

Large-Scale Gene-Centric Analysis Identifies Novel Variants for Coronary Artery Disease  

PubMed Central

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ?2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10?33; LPA:p<10?19; 1p13.3:p<10?17) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10?7). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06–1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ?4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity?=?0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes.

2011-01-01

23

Large-scale gene-centric analysis identifies novel variants for coronary artery disease.  

PubMed

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ?2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10(-33); LPA:p<10(-19); 1p13.3:p<10(-17)) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10(-7)). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ?4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity?=?0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes. PMID:21966275

2011-09-01

24

A Genome-wide Association Study Identifies LIPA as a Susceptibility Gene for Coronary Artery Disease  

PubMed Central

Background eQTL analyses are important to improve the understanding of genetic association results. Here, we performed a genome-wide association and global gene expression study to identify functionally relevant variants affecting the risk of coronary artery disease (CAD). Methods and Results In a genome-wide association analysis of 2,078 CAD cases and 2,953 controls, we identified 950 single nucleotide polymorphisms (SNPs) that were associated with CAD at P<10-3. Subsequent in silico and wet-lab replication stages and a final meta-analysis of 21,428 CAD cases and 38,361 controls revealed a novel association signal at chromosome 10q23.31 within the LIPA (Lysosomal Acid Lipase A) gene (P=3.7×10-8; OR 1.1; 95% CI: 1.07-1.14). The association of this locus with global gene expression was assessed by genome-wide expression analyses in the monocyte transcriptome of 1,494 individuals. The results showed a strong association of this locus with expression of the LIPA transcript (P=1.3×10-96). An assessment of LIPA SNPs and transcript with cardiovascular phenotypes revealed an association of LIPA transcript levels with impaired endothelial function (P=4.4×10-3). Conclusions The use of data on genetic variants and the addition of data on global monocytic gene expression led to the identification of the novel functional CAD susceptibility locus LIPA, located on chromosome 10q23.31. The respective eSNPs associated with CAD strongly affect LIPA gene expression level, which itself was related to endothelial dysfunction, a precursor of CAD.

Wild, Philipp S; Zeller, Tanja; Schillert, Arne; Szymczak, Silke; Sinning, Christoph R; Deiseroth, Arne; Schnabel, Renate B; Lubos, Edith; Keller, Till; Eleftheriadis, Medea S; Bickel, Christoph; Rupprecht, Hans J; Wilde, Sandra; Rossmann, Heidi; Diemert, Patrick; Cupples, L Adrienne; Perret, Claire; Erdmann, Jeanette; Stark, Klaus; Kleber, Marcus E; Epstein, Stephen E; Voight, Benjamin F; Kuulasmaa, Kari; Li, Mingyao; Schafer, Arne S; Klopp, Norman; Braund, Peter S; Sager, Hendrik B; Demissie, Serkalem; Proust, Carole; Konig, Inke R; Wichmann, Heinz-Erich; Reinhard, Wibke; Hoffmann, Michael M; Virtamo, Jarmo; Burnett, Mary Susan; Siscovick, David; Wiklund, Per Gunnar; Qu, Liming; El Mokthari, Nour Eddine; Thompson, John R; Peters, Annette; Smith, Albert V; Yon, Emmanuelle; Baumert, Jens; Hengstenberg, Christian; Marz, Winfried; Amouyel, Philippe; Devaney, Joseph; Schwartz, Stephen M; Saarela, Olli; Mehta, Nehal N; Rubin, Diana; Silander, Kaisa; Hall, Alistair S; Ferrieres, Jean; Harris, Tamara B; Melander, Olle; Kee, Frank; Hakonarson, Hakon; Schrezenmeir, Juergen; Gudnason, Vilmundur; Elosua, Roberto; Arveiler, Dominique; Evans, Alun; Rader, Daniel J; Illig, Thomas; Schreiber, Stefan; Bis, Joshua C; Altshuler, David; Kavousi, Maryam; Witteman, Jaqueline CM; Uitterlinden, Andre G; Hofman, Albert; Folsom, Aaron R; Barbalic, Maja; Boerwinkle, Eric; Kathiresan, Sekar; Reilly, Muredach P; O'Donnell, Christopher J; Samani, Nilesh J; Schunkert, Heribert; Cambien, Francois; Lackner, Karl J; Tiret, Laurence; Salomaa, Veikko; Munzel, Thomas; Ziegler, Andreas; Blankenberg, Stefan

2011-01-01

25

Systematic Association Mapping Identifies NELL1 as a Novel IBD Disease Gene  

PubMed Central

Crohn disease (CD), a sub-entity of inflammatory bowel disease (IBD), is a complex polygenic disorder. Although recent studies have successfully identified CD-associated genetic variants, these susceptibility loci explain only a fraction of the heritability of the disease. Here, we report on a multi-stage genome-wide scan of 393 German CD cases and 399 controls. Among the 116,161 single-nucleotide polymorphisms tested, an association with the known CD susceptibility gene NOD2, the 5q31 haplotype, and the recently reported CD locus at 5p13.1 was confirmed. In addition, SNP rs1793004 in the gene encoding nel-like 1 precursor (NELL1, chromosome 11p15.1) showed a consistent disease-association in independent German population- and family-based samples (942 cases, 1082 controls, 375 trios). Subsequent fine mapping and replication in an independent sample of 454 French/Canadian CD trios supported the authenticity of the NELL1 association. Further confirmation in a large German ulcerative colitis (UC) sample indicated that NELL1 is a ubiquitous IBD susceptibility locus (combined p<10?6; OR?=?1.66, 95% CI: 1.30–2.11). The novel 5p13.1 locus was also replicated in the French/Canadian sample and in an independent UK CD patient panel (453 cases, 521 controls, combined p<10?6 for SNP rs1992660). Several associations were replicated in at least one independent sample, point to an involvement of ITGB6 (upstream), GRM8 (downstream), OR5V1 (downstream), PPP3R2 (downstream), NM_152575 (upstream) and HNF4G (intron).

Franke, Andre; Hampe, Jochen; Rosenstiel, Philip; Becker, Christian; Wagner, Florian; Hasler, Robert; Little, Randall D.; Huse, Klaus; Ruether, Andreas; Balschun, Tobias; Wittig, Michael; ElSharawy, Abdou; Mayr, Gabriele; Albrecht, Mario; Prescott, Natalie J.; Onnie, Clive M.; Fournier, Helene; Keith, Tim; Radelof, Uwe; Platzer, Matthias; Mathew, Christopher G.; Stoll, Monika; Krawczak, Michael; Nurnberg, Peter; Schreiber, Stefan

2007-01-01

26

Novel applications of motif-directed profiling to identify disease resistance genes in plants  

PubMed Central

Background Molecular profiling of gene families is a versatile tool to study diversity between individual genomes in sexual crosses and germplasm. Nucleotide binding site (NBS) profiling, in particular, targets conserved nucleotide binding site-encoding sequences of resistance gene analogs (RGAs), and is widely used to identify molecular markers for disease resistance (R) genes. Results In this study, we used NBS profiling to identify genome-wide locations of RGA clusters in the genome of potato clone RH. Positions of RGAs in the potato RH and DM genomes that were generated using profiling and genome sequencing, respectively, were compared. Largely overlapping results, but also interesting discrepancies, were found. Due to the clustering of RGAs, several parts of the genome are overexposed while others remain underexposed using NBS profiling. It is shown how the profiling of other gene families, i.e. protein kinases and different protein domain-coding sequences (i.e., TIR), can be used to achieve a better marker distribution. The power of profiling techniques is further illustrated using RGA cluster-directed profiling in a population of Solanum berthaultii. Multiple different paralogous RGAs within the Rpi-ber cluster could be genetically distinguished. Finally, an adaptation of the profiling protocol was made that allowed the parallel sequencing of profiling fragments using next generation sequencing. The types of RGAs that were tagged in this next-generation profiling approach largely overlapped with classical gel-based profiling. As a potential application of next-generation profiling, we showed how the R gene family associated with late blight resistance in the SH*RH population could be identified using a bulked segregant approach. Conclusions In this study, we provide a comprehensive overview of previously described and novel profiling primers and their genomic targets in potato through genetic mapping and comparative genomics. Furthermore, it is shown how genome-wide or fine mapping can be pursued by choosing different sets of profiling primers. A protocol for next-generation profiling is provided and will form the basis for novel applications. Using the current overview of genomic targets, a rational choice can be made for profiling primers to be employed.

2013-01-01

27

Genome-wide Association Study Identifies Genes for Biomarkers of Cardiovascular Disease: Serum Urate and Dyslipidemia  

PubMed Central

Summary Many common diseases are accompanied by disturbances in biochemical traits. Identifying the genetic determinants could provide novel insights into disease mechanisms and reveal avenues for developing new therapies. Here, we report a genome-wide association analysis for commonly measured serum and urine biochemical traits. As part of the WTCCC, 500,000 SNPs genome wide were genotyped in 1955 hypertensive individuals characterized for 25 serum and urine biochemical traits. For each trait, we assessed association with individual SNPs, adjusting for age, sex, and BMI. Lipid measurements were further examined in a meta-analysis of genome-wide data from a type 2 diabetes scan. The most promising associations were examined in two epidemiological cohorts. We discovered association between serum urate and SLC2A9, a glucose transporter (p = 2 × 10?15) and confirmed this in two independent cohorts, GRAPHIC study (p = 9 × 10?15) and TwinsUK (p = 8 × 10?19). The odds ratio for hyperuricaemia (defined as urate >0.4 mMol/l) is 1.89 (95% CI = 1.36–2.61) per copy of common allele. We also replicated many genes previously associated with serum lipids and found previously recognized association between LDL levels and SNPs close to genes encoding PSRC1 and CELSR2 (p = 1 × 10?7). The common allele was associated with a 6% increase in nonfasting serum LDL. This region showed increased association in the meta-analysis (p = 4 × 10?14). This finding provides a potential biological mechanism for the recent association of this same allele of the same SNP with increased risk of coronary disease.

Wallace, Chris; Newhouse, Stephen J.; Braund, Peter; Zhang, Feng; Tobin, Martin; Falchi, Mario; Ahmadi, Kourosh; Dobson, Richard J.; Marcano, Ana Carolina B.; Hajat, Cother; Burton, Paul; Deloukas, Panagiotis; Brown, Morris; Connell, John M.; Dominiczak, Anna; Lathrop, G. Mark; Webster, John; Farrall, Martin; Spector, Tim; Samani, Nilesh J.; Caulfield, Mark J.; Munroe, Patricia B.

2008-01-01

28

Identifying candidate disease genes using a trace norm constrained bipartite raking model.  

PubMed

Computational prediction of genes that play roles in human diseases remains an important but challenging task. In this work, we formulate candidate gene prediction as a bipartite ranking problem combining a task-wise ordered observation model with a latent multitask regression function using the matrix-variate Gaussian process (MV-GP). We then use a trace-norm constrained variational inference approach to obtain the bipartite ranking model variables and the parameters of the underlying multitask regression model. We use this model to predict candidate genes from two gene-disease association data sets and show that our model outperforms current state-of-the-art methods. Finally, we demonstrate the practical utility of our method by successfully recovering well characterized gene-disease associations hidden in our training data. PMID:24110473

Lee, Cheng H; Koyejo, Oluwasanmi; Ghosh, Joydeep

2013-01-01

29

Large-scale gene-centric analysis identifies novel variants for coronary artery disease  

Microsoft Academic Search

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in approximately 2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases

A. S. Butterworth; P. S. Braund; R. J. Hardwick; D. Saleheen; J. F. Peden; N. Soranzo; J. C. Chambers; M. E. Kleber; B. Keating; A. Qasim; N. Klopp; J. Erdmann; H. Basart; J. H. Baumert; C. R. Bezzina; B. O. Boehm; J. Brocheton; P. Bugert; F. Cambien; R. Collins; D. Couper; J. S. de Jong; P. Diemert; K. Ejebe; C. C. Elbers; P. Elliott; M. Fornage; P. Frossard; S. Garner; S. E. Hunt; J. J. Kastelein; O. H. Klungel; H. Kluter; K. Koch; I. R. Konig; A. S. Kooner; K. Liu; R. McPherson; M. D. Musameh; S. Musani; G. Papanicolaou; A. Peters; B. J. Peters; S. Potter; B. M. Psaty; A. Rasheed; J. Scott; U. Seedorf; J. S. Sehmi; N. Sotoodehnia; K. Stark; J. Stephens; C. E. van der Schoot; Y. T. van der Schouw; P. van der Harst; R. S. Vasan; A. A. Wilde; C. Willenborg; B. R. Winkelmann; M. Zaidi; W. Zhang; A. Ziegler; W. Koenig; W. Matz; M. D. Trip; M. P. Reilly; S. Kathiresan; H. Schunkert; A. Hamsten; A. S. Hall; J. S. Kooner; S. G. Thompson; J. R. Thompson; H. Watkins; J. Danesh; T. Barnes; S. Rafelt; V. Codd; N. Bruinsma; L. R. Dekker; J. P. Henriques; R. J. de Winter; M. Alings; C. F. Allaart; A. P. Gorgels; F. W. A. Verheugt; M. Mueller; C. Meisinger; S. DerOhannessian; N. N. Mehta; J. Ferguson; H. Hakonarson; W. Matthai; R. Wilensky; J. C. Hopewell; S. Parish; P. Linksted; J. Notman; H. Gonzalez; A. Young; T. Ostley; A. Munday; N. Goodwin; V. Verdon; S. Shah; C. Edwards; C. Mathews; R. Gunter; J. Benham; C. Davies; M. Cobb; L. Cobb; J. Crowther; A. Richards; M. Silver; S. Tochlin; S. Mozley; S. Clark; M. Radley; K. Kourellias; P. Olsson; S. Barlera; G. Tognoni; S. Rust; G. Assmann; S. Heath; D. Zelenika; I. Gut; F. Green; M. Farrall; A. Goel; H. Ongen; M. G. Franzosi; M. Lathrop; R. Clarke; A. Aly; K. Anner; K. Bjorklund; G. Blomgren; B. Cederschiold; K. Danell-Toverud; P. Eriksson; U. Grundstedt; M. Heinonen; M. L. Hellenius; F. van't Hooft; K. Husman; J. Lagercrantz; A. Larsson; M. Larsson; M. Mossfeldt; A. Malarstig; G. Olsson; M. Sabater-Lleal; B. Sennblad; A. Silveira; R. Strawbridge; B. Soderholm; J. Ohrvik; K. S. Zaman; N. H. Mallick; M. Azhar; A. Samad; M. Ishaq; N. Shah; M. Samuel; T. L. Assimes; H. Holm; M. Preuss; A. F. Stewart; M. Barbalic; C. Gieger; D. Absher; Z. Aherrahrou; H. Allayee; D. Altshuler; S. Anand; K. Andersen; J. L. Anderson; D. Ardissino; S. G. Ball; A. J. Balmforth; L. C. Becker; D. M. Becker; K. Berger; J. C. Bis; S. M. Boekholdt; E. Boerwinkle; M. J. Brown; M. S. Burnett; I. Buysschaert; J. F. Carlquist; L. Chen; R. W. Davies; G. Dedoussis; A. Dehghan; S. Demissie; J. Devaney; A. Doering; N. E. El Mokhtari; S. G. Ellis; R. Elosua; J. C. Engert; S. Epstein; U. de Faire; M. Fischer; A. R. Folsom; J. Freyer; B. Gigante; D. Girelli; S. Gretarsdottir; V. Gudnason; J. R. Gulcher; S. Tennstedt; E. Halperin; N. Hammond; S. L. Hazen; A. Hofman; B. D. Horne; T. Illig; C. Iribarren; G. T. Jones; J. W. Jukema; M. A. Kaiser; L. M. Kaplan; K. T. Khaw; J. W. Knowles; G. Kolovou; A. Kong; R. Laaksonen; D. Lambrechts; K. Leander; M. Li; W. Lieb; G. Lettre; C. Loley; A. J. Lotery; P. M. Mannucci; N. Martinelli; P. P. McKeown; T. Meitinger; O. Melander; P. A. Merlini; V. Mooser; T. Morgan; Muhleisen T. W; J. B. Muhlestein; K. Musunuru; J. Nahrstaedt; M. M. Nothen; O. Olivieri; F. Peyvandi; R. S. Patel; C. C. Patterson; L. Qu; A. A. Quyyumi; D. J. Rader; L. S. Rallidis; C. Rice; F. R. Roosendaal; D. Rubin; V. Salomaa; M. L. Sampietro; M. S. Sandhu; E. Schadt; A. Schafer; A. Schillert; S. Schreiber; J. Schrezenmeir; S. M. Schwartz; D. S. Siscovick; M. Sivananthan; S. Sivapalaratnam; A. V. Smith; T. B. Smith; J. D. Snoep; J. A. Spertus; K. Stefansson; K. Stirrups; M. Stoll; W. H. Tang; G. Thorgeirsson; G. Thorleifsson; M. Tomaszewski; A. G. Uitterlinden; A. M. van Rij; B. F. Voight; N. J. Wareham; G. AWells; H. E. Wichmann; J. C. Witteman; B. J. Wright; S. Ye; L. A. Cupples; T. Quertermous; W. Marz; S. Blankenberg; U. Thorsteinsdottir; R. Roberts; C. J. O'Donnell; N. C. Onland-Moret; J. van Setten; P. I. de Bakker; W. M. Verschuren; J. M. Boer; C. Wijmenga; M. H. Hofker; A. H. Maitland-van der Zee; A. de Boer; D. E. Grobbee; T. Attwood; S. Belz; J. Cooper; A. Crisp-Hihn; P. Deloukas; N. Foad; A. H. Goodall; J. Gracey; E. Gray; R. Gwilliams; S. Heimerl; C. Hengstenberg; J. Jolley; U. Krishnan; H. Lloyd-Jones; I. Lugauer; P. Lundmark; S. Maouche; J. S. Moore; D. Muir; E. Murray; C. P. Nelson; J. Neudert; D. Niblett; K. O'Leary; W. H. Ouwehand; H. Pollard; A. Rankin; H. Sager; N. J. Samani; J. Sambrook; G. Schmitz; M. Scholz; L. Schroeder; A. C. Syvannen; C. Wallace

2011-01-01

30

Using gene expression data to identify certain gastro-intestinal diseases  

PubMed Central

Background Inflammatory bowel diseases, ulcerative colitis and Crohn’s disease are considered to be of autoimmune origin, but the etiology of irritable bowel syndrome remains elusive. Furthermore, classifying patients into irritable bowel syndrome and inflammatory bowel diseases can be difficult without invasive testing and holds important treatment implications. Our aim was to assess the ability of gene expression profiling in blood to differentiate among these subject groups. Methods Transcript levels of a total of 45 genes in blood were determined by quantitative real-time polymerase chain reaction (RT-PCR). We applied three separate analytic approaches; one utilized a scoring system derived from combinations of ratios of expression levels of two genes and two different support vector machines. Results All methods discriminated different subject cohorts, irritable bowel syndrome from control, inflammatory bowel disease from control, irritable bowel syndrome from inflammatory bowel disease, and ulcerative colitis from Crohn’s disease, with high degrees of sensitivity and specificity. Conclusions These results suggest these approaches may provide clinically useful prediction of the presence of these gastro-intestinal diseases and syndromes.

2012-01-01

31

ToP: a trend-of-disease-progression procedure works well for identifying cancer genes from multi-state cohort gene expression data for human colorectal cancer.  

PubMed

Significantly expressed genes extracted from microarray gene expression data have proved very useful for identifying genetic biomarkers of diseases, including cancer. However, deriving a disease related inference from a list of differentially expressed genes has proven less than straightforward. In a systems disease such as cancer, how genes interact with each other should matter just as much as the level of gene expression. Here, in a novel approach, we used the network and disease progression properties of individual genes in state-specific gene-gene interaction networks (GGINs) to select cancer genes for human colorectal cancer (CRC) and obtain a much higher hit rate of known cancer genes when compared with methods not based on network theory. We constructed GGINs by integrating gene expression microarray data from multiple states--healthy control (Nor), adenoma (Ade), inflammatory bowel disease (IBD) and CRC--with protein-protein interaction database and Gene Ontology. We tracked changes in the network degrees and clustering coefficients of individual genes in the GGINs as the disease state changed from one to another. From these we inferred the state sequences Nor-Ade-CRC and Nor-IBD-CRC both exhibited a trend of (disease) progression (ToP) toward CRC, and devised a ToP procedure for selecting cancer genes for CRC. Of the 141 candidates selected using ToP, ?50% had literature support as cancer genes, compared to hit rates of 20% to 30% for standard methods using only gene expression data. Among the 16 candidate cancer genes that encoded transcription factors, 13 were known to be tumorigenic and three were novel: CDK1, SNRPF, and ILF2. We identified 13 of the 141 predicted cancer genes as candidate markers for early detection of CRC, 11 and 2 at the Ade and IBD states, respectively. PMID:23799036

Chung, Feng-Hsiang; Lee, Henry Hsin-Chung; Lee, Hoong-Chien

2013-01-01

32

Whole-Genome Sequencing of a Single Proband Together with Linkage Analysis Identifies a Mendelian Disease Gene  

PubMed Central

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders.

Wohler, Elizabeth; Oswald, Gretchen L.; Stevens, Eric L.; Ge, Dongliang; Shianna, Kevin V.; Smith, Jason P.; Maia, Jessica M.; Gumbs, Curtis E.; Pevsner, Jonathan; Thomas, George; Valle, David; Hoover-Fong, Julie E.; Goldstein, David B.

2010-01-01

33

Expression profiling of cervical cancers in Indian women at different stages to identify gene signatures during progression of the disease  

PubMed Central

Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from Indian women, spanning International Federation of Gynaecology and Obstetrics (FIGO) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA–B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine–cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP1, proliferating cell nuclear antigen (PCNA), STK17A, and DUSP1 among others that were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression.

Thomas, Asha; Mahantshetty, Umesh; Kannan, Sadhana; Deodhar, Kedar; Shrivastava, Shyam K; Kumar-Sinha, Chandan; Mulherkar, Rita

2013-01-01

34

TM4SF10 gene sequencing in XLMR patients identifies common polymorphisms but no disease-associated mutation  

PubMed Central

Background The TM4SF10 gene encodes a putative four-transmembrane domains protein of unknown function termed Brain Cell Membrane Protein 1 (BCMP1), and is abundantly expressed in the brain. This gene is located on the short arm of human chromosome X at p21.1. The hypothesis that mutations in the TM4SF10 gene are associated with impaired brain function was investigated by sequencing the gene in individuals with hereditary X-linked mental retardation (XLMR). Methods The coding region (543 bp) of TM4SF10, including intronic junctions, and the long 3' untranslated region (3 233 bp), that has been conserved during evolution, were sequenced in 16 male XLMR patients from 14 unrelated families with definite, or suggestive, linkage to the TM4SF10 gene locus, and in 5 normal males. Results Five sequence changes were identified but none was found to be associated with the disease. Two of these changes correspond to previously known SNPs, while three other were novel SNPs in the TM4SF10 gene. Conclusion We have investigated the majority of the known MRX families linked to the TM4SF10 gene region. In the absence of mutations detected, our study indicates that alterations of TM4SF10 are not a frequent cause of XLMR.

Christophe-Hobertus, Christiane; Kooy, Frank; Gecz, Jozef; Abramowicz, Marc J; Holinski-Feder, Elke; Schwartz, Charles; Christophe, Daniel

2004-01-01

35

Exome Sequencing Identifies DLG1 as a Novel Gene for Potential Susceptibility to Crohn's Disease in a Chinese Family Study  

PubMed Central

Background Genetic variants make some contributions to inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC). More than 100 susceptibility loci were identified in Western IBD studies, but susceptibility gene has not been found in Chinese IBD patients till now. Sequencing of individuals with an IBD family history is a powerful approach toward our understanding of the genetics and pathogenesis of IBD. The aim of this study, which focuses on a Han Chinese CD family, is to identify high-risk variants and potentially novel loci using whole exome sequencing technique. Methods Exome sequence data from 4 individuals belonging to a same family were analyzed using bioinformatics methods to narrow down the variants associated with CD. The potential risk genes were further analyzed by genotyping and Sanger sequencing in family members, additional 401 healthy controls (HC), 278 sporadic CD patients, 123 UC cases, a pair of monozygotic CD twins and another Chinese CD family. Results From the CD family in which the father and daughter were affected, we identified a novel single nucleotide variant (SNV) c.374T>C (p.I125T) in exon 4 of discs large homolog 1 (DLG1), a gene has been reported to play mutiple roles in cell proliferation, T cell polarity and T cell receptor signaling. After genotyping among case and controls, a PLINK analysis showed the variant was of significance (P<0.05). 4 CD patients of the other Chinese family bore another non-synonymous variant c.833G>A (p.R278Q) in exon 9 of DLG1. Conclusions We have discovered novel genetic variants in the coding regions of DLG1 gene, the results support that DLG1 is a novel potential susceptibility gene for CD in Chinese patients.

Song, Lu; NG, Siew Chien; Wang, Xiaobing; Chen, Liping; Yi, Fengming; Ran, Zhihua; Zhou, Rui; Xia, Bing

2014-01-01

36

Single-Cell Expression Profiling of Dopaminergic Neurons Combined with Association Analysis Identifies Pyridoxal Kinase as Parkinson's Disease Gene  

PubMed Central

Objective The etiology of Parkinson disease (PD) is complex and multifactorial, with hereditary and environmental factors contributing. Monogenic forms have provided molecular clues to disease mechanisms but genetic modifiers of idiopathic PD are still to be determined. Methods We carried out whole-genome expression profiling of isolated human substantia nigra (SN) neurons from patients with PD vs. controls followed by association analysis of tagging single-nucleotide polymorphisms (SNPs) in differentially regulated genes. Association was investigated in a German PD sample and confirmed in Italian and British cohorts. Results We identified four differentially expressed genes located in PD candidate pathways, ie, MTND2 (mitochondrial, p = 7.14 × 10?7), PDXK (vitamin B6/dopamine metabolism, p = 3.27 × 10?6), SRGAP3 (axon guidance, p = 5.65 × 10?6), and TRAPPC4 (vesicle transport, p = 5.81 × 10?6). We identified a DNA variant (rs2010795) in PDXK associated with an increased risk of PD in the German cohort (p = 0.00032). This association was confirmed in the British (p = 0.028) and Italian (p = 0.0025) cohorts individually and reached a combined value of p = 1.2 × 10?7 (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.18–1.44). Interpretation We provide an example of how microgenomic genome-wide expression studies in combination with association analysis can aid to identify genetic modifiers in neurodegenerative disorders. The detection of a genetic variant in PDXK, together with evidence accumulating from clinical studies, emphasize the impact of vitamin B6 status and metabolism on disease risk and therapy in PD.

Elstner, Matthias; Morris, Christopher M.; Heim, Katharina; Lichtner, Peter; Bender, Andreas; Mehta, Divya; Schulte, Claudia; Sharma, Manu; Hudson, Gavin; Goldwurm, Stefano; Giovanetti, Alessandro; Zeviani, Massimo; Burn, David J.; McKeith, Ian G.; Perry, Robert H.; Jaros, E.; Kruger, Rejko; Wichmann, H.-Erich; Schreiber, Stefan; Campbell, Harry; Wilson, James F.; Wright, Alan F.; Dunlop, Malcolm; Pistis, Giorgio; Toniolo, Daniela; Chinnery, Patrick F.; Gasser, Thomas; Klopstock, Thomas; Meitinger, Thomas; Prokisch, Holger; Turnbull, Douglass M.

2014-01-01

37

Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5  

PubMed Central

Background Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas). Results We identified four genes with SNPs that showed the strongest and most consistent associations with LDL-C and CAD: EBF1, PPP2R2B, SPOCK1, and PRELID2. The most significant results for association of SNPs with LDL-C were: EBF1, rs6865969, p = 0.01; PPP2R2B, rs2125443, p = 0.005; SPOCK1, rs17600115, p = 0.003; and PRELID2, rs10074645, p = 0.0002). The most significant results for CAD were EBF1, rs6865969, p = 0.007; PPP2R2B, rs7736604, p = 0.0003; SPOCK1, rs17170899, p = 0.004; and PRELID2, rs7713855, p = 0.003. Conclusion Using an intermediate disease-related quantitative trait of LDL-C we have identified four novel CAD genes, EBF1, PRELID2, SPOCK1, and PPP2R2B. These four genes should be further examined in future functional studies as candidate susceptibility loci for cardiovascular disease mediated through LDL-cholesterol pathways.

2012-01-01

38

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee  

PubMed Central

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df?=?10?6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR?=?0.43; P?=?6×10?7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication?=?0.59, PReplication?=?10?3; ORPooled?=?0.51, PPooled?=?7×10?8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P?=?3×10?3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P?=?6×10?13). Imputation revealed a block of SNPs that achieved P2df<5×10?8 in GWAIS, and OR?=?0.41, P?=?3×10?8 in heavy coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that are missed in GWAS. Both adenosine antagonists (caffeine-like) and glutamate antagonists (GRIN2A-related) are being tested in clinical trials for treatment of PD. GRIN2A may be a useful pharmacogenetic marker for subdividing individuals in clinical trials to determine which medications might work best for which patients.

Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh

2011-01-01

39

Transcriptional Profiling of Human Liver Identifies Sex-Biased Genes Associated with Polygenic Dyslipidemia and Coronary Artery Disease  

Microsoft Academic Search

Sex-differences in human liver gene expression were characterized on a genome-wide scale using a large liver sample collection, allowing for detection of small expression differences with high statistical power. 1,249 sex-biased genes were identified, 70% showing higher expression in females. Chromosomal bias was apparent, with female-biased genes enriched on chrX and male-biased genes enriched on chrY and chr19, where 11

Yijing Zhang; Kathrin Klein; Aarathi Sugathan; Najlla Nassery; Alan Dombkowski; Ulrich M. Zanger; David J. Waxman

2011-01-01

40

Genome-wide copy number variation study and gene expression analysis identify ABI3BP as a susceptibility gene for Kashin-Beck disease.  

PubMed

Kashin-Beck disease (KBD) is a chronic osteochondropathy. In this study, we conducted the first genome-wide copy number variation study (GCNVS) of KBD totally involving 2,743 Chinese Han adults. GCNVS was first performed using Affymetrix Human SNP6.0 Arrays. The identified copy number variations (CNVs) were then replicated in an independent Chinese Han sample containing 1,026 subjects. SNP genotyping, CNV identification and quality control were implemented by Birdsuite. STRUCTURE and EIGENSTRAT were applied for controlling potential population stratification in the GCNVS. Association analysis was conducted using PLINK. Microarray and qRT-PCR were also conducted to compare the expression levels of the genes overlapping with identified CNVs between KBD patients and healthy controls. GCNVS found that CNV452 (P value = 7.78 × 10(-5)) overlapping with ABI3BP gene was significantly associated with KBD. Replication association study observed that rs9850273 (P value = 0.008) and rs7613610 (P value = 0.021) in ABI3BP gene were significantly associated with KBD. Gene expression analysis also found that ABI3BP was up-regulated in KBD patients compared to healthy controls. Our results suggest that ABI3BP was a novel susceptibility gene for KBD. PMID:24442417

Zhang, Feng; Guo, Xiong; Zhang, Yinping; Wen, Yan; Wang, Weizhuo; Wang, Sen; Yang, Tielin; Shen, Hui; Chen, Xiangding; Tian, Qing; Tan, Lijun; Deng, Hong-Wen

2014-06-01

41

Whole blood transcriptional profiling in ankylosing spondylitis identifies novel candidate genes that might contribute to the inflammatory and tissue-destructive disease aspects  

PubMed Central

Introduction A number of genetic-association studies have identified genes contributing to ankylosing spondylitis (AS) susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a 'snapshot' of the sampled cells' activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort. Methods A total of 18 active AS patients, classified according to the New York criteria, and 18 gender- and age-matched controls were profiled using Illumina HT-12 whole-genome expression BeadChips which carry cDNAs for 48,000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan low density arrays (TLDAs). Results A total of 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a P-value <0.0005 (80% confidence level of false discovery rate). Forty-seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 downregulated 1.3- to 2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300, which modulate cartilage and bone metabolism. Conclusions We have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease.

2011-01-01

42

Power and Pitfalls of the Genome-Wide Association Study Approach to Identify Genes for Alzheimer’s Disease  

Microsoft Academic Search

Until recently, the search for genes contributing to Alzheimer’s disease (AD) had been slow and disappointing, with the notable\\u000a exception of the APOE ?4 allele, which increases risk and reduces the age at onset of AD in a dose-dependent fashion. Findings from genome-wide\\u000a association studies (GWAS) made up of fewer than several thousand cases and controls each have not been

Richard Sherva; Lindsay A. Farrer

2011-01-01

43

Suppressors of the arabidopsis lsd5 cell death mutation identify genes involved in regulating disease resistance responses.  

PubMed Central

Cell death is associated with the development of the plant disease resistance hypersensitive reaction (HR). Arabidopsis lsd mutants that spontaneously exhibit cell death reminiscent of the HR were identified previously. To study further the regulatory context in which cell death acts during disease resistance, one of these mutants, lsd5, was used to isolate new mutations that suppress its cell death phenotype. Using a simple lethal screen, nine lsd5 cell death suppressors, designated phx (for the mythological bird Phoenix that rises from its ashes), were isolated. These mutants were characterized with respect to their response to a bacterial pathogen and oomycete parasite. The strongest suppressors-phx2, 3, 6, and 11-1-showed complex, differential patterns of disease resistance modifications. These suppressors attenuated disease resistance to avirulent isolates of the biotrophic Peronospora parasitica pathogen, but only phx2 and phx3 altered disease resistance to avirulent strains of Pseudomonas syringae pv tomato. Therefore, some of these phx mutants define common regulators of cell death and disease resistance. In addition, phx2 and phx3 exhibited enhanced disease susceptibility to different virulent pathogens, confirming probable links between the disease resistance and susceptibility pathways.

Morel, J B; Dangl, J L

1999-01-01

44

A Network Analysis of the Human T-Cell Activation Gene Network Identifies Jagged1 as a Therapeutic Target for Autoimmune Diseases  

PubMed Central

Understanding complex diseases will benefit the recognition of the properties of the gene networks that control biological functions. Here, we set out to model the gene network that controls T-cell activation in humans, which is critical for the development of autoimmune diseases such as Multiple Sclerosis (MS). The network was established on the basis of the quantitative expression from 104 individuals of 20 genes of the immune system, as well as on biological information from the Ingenuity database and Bayesian inference. Of the 31 links (gene interactions) identified in the network, 18 were identified in the Ingenuity database and 13 were new and we validated 7 of 8 interactions experimentally. In the MS patients network, we found an increase in the weight of gene interactions related to Th1 function and a decrease in those related to Treg and Th2 function. Indeed, we found that IFN-ß therapy induces changes in gene interactions related to T cell proliferation and adhesion, although these gene interactions were not restored to levels similar to controls. Finally, we identify JAG1 as a new therapeutic target whose differential behaviour in the MS network was not modified by immunomodulatory therapy. In vitro treatment with a Jagged1 agonist peptide modulated the T-cell activation network in PBMCs from patients with MS. Moreover, treatment of mice with experimental autoimmune encephalomyelitis with the Jagged1 agonist ameliorated the disease course, and modulated Th2, Th1 and Treg function. This study illustrates how network analysis can predict therapeutic targets for immune intervention and identified the immunomodulatory properties of Jagged1 making it a new therapeutic target for MS and other autoimmune diseases.

Palacios, Ricardo; Goni, Joaquin; Martinez-Forero, Ivan; Iranzo, Jaime; Sepulcre, Jorge; Melero, Ignacio; Villoslada, Pablo

2007-01-01

45

Gene expression profiling to identify potentially relevant disease outcomes and support human health risk assessment for carbon black nanoparticle exposure.  

PubMed

New approaches are urgently needed to evaluate potential hazards posed by exposure to nanomaterials. Gene expression profiling provides information on potential modes of action and human relevance, and tools have recently become available for pathway-based quantitative risk assessment. The objective of this study was to use toxicogenomics in the context of human health risk assessment. We explore the utility of toxicogenomics in risk assessment, using published gene expression data from C57BL/6 mice exposed to 18, 54 and 162 ?g Printex 90 carbon black nanoparticles (CBNP). Analysis of CBNP-perturbed pathways, networks and transcription factors revealed concomitant changes in predicted phenotypes (e.g., pulmonary inflammation and genotoxicity), that correlated with dose and time. Benchmark doses (BMDs) for apical endpoints were comparable to minimum BMDs for relevant pathway-specific expression changes. Comparison to inflammatory lung disease models (i.e., allergic airway inflammation, bacterial infection and tissue injury and fibrosis) and human disease profiles revealed that induced gene expression changes in Printex 90 exposed mice were similar to those typical for pulmonary injury and fibrosis. Very similar fibrotic pathways were perturbed in CBNP-exposed mice and human fibrosis disease models. Our synthesis demonstrates how toxicogenomic profiles may be used in human health risk assessment of nanoparticles and constitutes an important step forward in the ultimate recognition of toxicogenomic endpoints in human health risk. As our knowledge of molecular pathways, dose-response characteristics and relevance to human disease continues to grow, we anticipate that toxicogenomics will become increasingly useful in assessing chemical toxicities and in human health risk assessment. PMID:23146762

Bourdon, Julie A; Williams, Andrew; Kuo, Byron; Moffat, Ivy; White, Paul A; Halappanavar, Sabina; Vogel, Ulla; Wallin, Håkan; Yauk, Carole L

2013-01-01

46

Systems Analysis of Immune Responses in Marek's Disease Virus-Infected Chickens Identifies a Gene Involved in Susceptibility and Highlights a Possible Novel Pathogenicity Mechanism?†  

PubMed Central

Marek's disease virus (MDV) is a highly contagious oncogenic alphaherpesvirus that causes disease that is both a cancer model and a continuing threat to the world's poultry industry. This comprehensive gene expression study analyzes the host response to infection in both resistant and susceptible lines of chickens and inherent expression differences between the two lines following the infection of the host. A novel pathogenicity mechanism, involving the downregulation of genes containing HIC1 transcription factor binding sites as early as 4 days postinfection, was suggested from this analysis. HIC1 drives antitumor mechanisms, suggesting that MDV infection switches off genes involved in antitumor regulation several days before the expression of the MDV oncogene meq. The comparison of the gene expression data to previous QTL data identified several genes as candidates for involvement in resistance to MD. One of these genes, IRG1, was confirmed by single nucleotide polymorphism analysis to be involved in susceptibility. Its precise mechanism remains to be elucidated, although the analysis of gene expression data suggests it has a role in apoptosis. Understanding which genes are involved in susceptibility/resistance to MD and defining the pathological mechanisms of the disease gives us a much greater ability to try to reduce the incidence of this virus, which is costly to the poultry industry in terms of both animal welfare and economics.

Smith, Jacqueline; Sadeyen, Jean-Remy; Paton, Ian R.; Hocking, Paul M.; Salmon, Nigel; Fife, Mark; Nair, Venugopal; Burt, David W.; Kaiser, Pete

2011-01-01

47

A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease  

PubMed Central

Background An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity.

2014-01-01

48

New mutation of the desmin gene identified in an extended Indian pedigree presenting with distal myopathy and cardiac disease.  

PubMed

In this report, we describe a new mutation located in the coiled 1B domain of desmin and associated with a predominant cardiac involvement and a high degree of cardiac sudden death in a large Indian pedigree with 12 affected members. The index cases was 38-year-old man who presented with progressive difficulty in gripping footwear of 5 years duration with the onset in the left lower limb followed by right lower limb in 6 months. 3 years from onset, he developed lower limb proximal and truncal muscle weakness. There was mild atrophy of the shoulder girdle muscles with grade 3 weakness, moderate wasting of thigh and anterior leg muscles with proximal muscle weakness and foot drop. At 40 years, he had a pacemaker implanted. The 9 exons and intronic boundaries of the desmin gene were sequenced and a heterozygous nucleotide change c. 734A > G in exon 3 was identified. PMID:24441330

Nalini, Atchayaram; Gayathri, Narayanappa; Richard, Pascale; Cobo, Ana-Maria; Urtizberea, J Andoni

2013-01-01

49

Repressor- and activator-type ethylene response factors functioning in jasmonate signaling and disease resistance identified via a genome-wide screen of Arabidopsis transcription factor gene expression.  

PubMed

To identify transcription factors (TFs) involved in jasmonate (JA) signaling and plant defense, we screened 1,534 Arabidopsis (Arabidopsis thaliana) TFs by real-time quantitative reverse transcription-PCR for their altered transcript at 6 h following either methyl JA treatment or inoculation with the incompatible pathogen Alternaria brassicicola. We identified 134 TFs that showed a significant change in expression, including many APETALA2/ethylene response factor (AP2/ERF), MYB, WRKY, and NAC TF genes with unknown functions. Twenty TF genes were induced by both the pathogen and methyl JA and these included 10 members of the AP2/ERF TF family, primarily from the B1a and B3 subclusters. Functional analysis of the B1a TF AtERF4 revealed that AtERF4 acts as a novel negative regulator of JA-responsive defense gene expression and resistance to the necrotrophic fungal pathogen Fusarium oxysporum and antagonizes JA inhibition of root elongation. In contrast, functional analysis of the B3 TF AtERF2 showed that AtERF2 is a positive regulator of JA-responsive defense genes and resistance to F. oxysporum and enhances JA inhibition of root elongation. Our results suggest that plants coordinately express multiple repressor- and activator-type AP2/ERFs during pathogen challenge to modulate defense gene expression and disease resistance. PMID:16183832

McGrath, Ken C; Dombrecht, Bruno; Manners, John M; Schenk, Peer M; Edgar, Cameron I; Maclean, Donald J; Scheible, Wolf-Rüdiger; Udvardi, Michael K; Kazan, Kemal

2005-10-01

50

Regulatory gene networks and signaling pathways from primary osteoarthritis and Kashin-Beck disease, an endemic osteoarthritis, identified by three analysis software.  

PubMed

Three new software systems, Ingenuity pathway analysis(IPA, TranscriptomeBrowser and MetaCore, were compared by analyzing chondrocyte microarray data of Kashin-Beck disease (KBD) and primary knee osteoarthritis(OA) to understand the pathway or network analysis software which has a superior function to identify target genes with easy operation and effective for differential diagnosis and treatment of KBD and OA. RNA was isolated from cartilage samples taken from KBD patients and OA ones. Agilent 44K human whole genome oligonucleotide microarrays were used to detect differentially expressed genes. From IPA, we identified one significant canonical pathway and two significant networks. From GeneHub analysis, we got three networks. One significant canonical pathway and one significant network were obtained from TranscriptomeBrowser analysis. POSTN and LEF1 which were got from IPA, RAC2 which was identified by both of the IPA and TranscriptomeBrowser may be most closely related to the etiopathogenesis of KBD. According to our data analysis, IPA and TranscriptomeBrowser are suitable for pathway analysis, while, TranscriptomeBrowser is suitable for network analysis. The significant genes obtained from IPA and TranscriptomeBrowser analysis may thus provide a better understanding of the molecular details in the pathogenesis of KBD and also provide useful pathways and network maps for future research in osteochondrosis. PMID:23069848

Wang, Sen; Duan, Chen; Zhang, Feng; Ma, Weijuan; Guo, Xiong

2013-01-01

51

Identifying proteins controlling key disease signaling pathways  

PubMed Central

Motivation: Several types of studies, including genome-wide association studies and RNA interference screens, strive to link genes to diseases. Although these approaches have had some success, genetic variants are often only present in a small subset of the population, and screens are noisy with low overlap between experiments in different labs. Neither provides a mechanistic model explaining how identified genes impact the disease of interest or the dynamics of the pathways those genes regulate. Such mechanistic models could be used to accurately predict downstream effects of knocking down pathway members and allow comprehensive exploration of the effects of targeting pairs or higher-order combinations of genes. Results: We developed methods to model the activation of signaling and dynamic regulatory networks involved in disease progression. Our model, SDREM, integrates static and time series data to link proteins and the pathways they regulate in these networks. SDREM uses prior information about proteins’ likelihood of involvement in a disease (e.g. from screens) to improve the quality of the predicted signaling pathways. We used our algorithms to study the human immune response to H1N1 influenza infection. The resulting networks correctly identified many of the known pathways and transcriptional regulators of this disease. Furthermore, they accurately predict RNA interference effects and can be used to infer genetic interactions, greatly improving over other methods suggested for this task. Applying our method to the more pathogenic H5N1 influenza allowed us to identify several strain-specific targets of this infection. Availability: SDREM is available from http://sb.cs.cmu.edu/sdrem Contact: zivbj@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Gitter, Anthony; Bar-Joseph, Ziv

2013-01-01

52

Genome-wide haplotype association study identifies the FRMD4A gene as a risk locus for Alzheimer's disease  

PubMed Central

Recently, several genome-wide association studies (GWASs) have led to the discovery of nine new loci of genetic susceptibility in Alzheimer's disease (AD). However, the landscape of the AD genetic susceptibility is far away to be complete and in addition to single-SNP (single-nucleotide polymorphism) analyses as performed in conventional GWAS, complementary strategies need to be applied to overcome limitations inherent to this type of approaches. We performed a genome-wide haplotype association (GWHA) study in the EADI1 study (n=2025 AD cases and 5328 controls) by applying a sliding-windows approach. After exclusion of loci already known to be involved in AD (APOE, BIN1 and CR1), 91 regions with suggestive haplotype effects were identified. In a second step, we attempted to replicate the best suggestive haplotype associations in the GERAD1 consortium (2820 AD cases and 6356 controls) and observed that 9 of them showed nominal association. In a third step, we tested relevant haplotype associations in a combined analysis of five additional case–control studies (5093 AD cases and 4061 controls). We consistently replicated the association of a haplotype within FRMD4A on Chr.10p13 in all the data set analyzed (OR: 1.68; 95% CI: (1.43–1.96); P=1.1 × 10?10). We finally searched for association between SNPs within the FRMD4A locus and A? plasma concentrations in three independent non-demented populations (n=2579). We reported that polymorphisms were associated with plasma A?42/A?40 ratio (best signal, P=5.4 × 10?7). In conclusion, combining both GWHA study and a conservative three-stage replication approach, we characterised FRMD4A as a new genetic risk factor of AD.

Lambert, J-C; Grenier-Boley, B; Harold, D; Zelenika, D; Chouraki, V; Kamatani, Y; Sleegers, K; Ikram, M A; Hiltunen, M; Reitz, C; Mateo, I; Feulner, T; Bullido, M; Galimberti, D; Concari, L; Alvarez, V; Sims, R; Gerrish, A; Chapman, J; Deniz-Naranjo, C; Solfrizzi, V; Sorbi, S; Arosio, B; Spalletta, G; Siciliano, G; Epelbaum, J; Hannequin, D; Dartigues, J-F; Tzourio, C; Berr, C; Schrijvers, E M C; Rogers, R; Tosto, G; Pasquier, F; Bettens, K; Van Cauwenberghe, C; Fratiglioni, L; Graff, C; Delepine, M; Ferri, R; Reynolds, C A; Lannfelt, L; Ingelsson, M; Prince, J A; Chillotti, C; Pilotto, A; Seripa, D; Boland, A; Mancuso, M; Bossu, P; Annoni, G; Nacmias, B; Bosco, P; Panza, F; Sanchez-Garcia, F; Del Zompo, M; Coto, E; Owen, M; O'Donovan, M; Valdivieso, F; Caffara, P; Scarpini, E; Combarros, O; Buee, L; Campion, D; Soininen, H; Breteler, M; Riemenschneider, M; Van Broeckhoven, C; Alperovitch, A; Lathrop, M; Tregouet, D-A; Williams, J; Amouyel, P

2013-01-01

53

A Network Analysis of the Human T-Cell Activation Gene Network Identifies Jagged1 as a Therapeutic Target for Autoimmune Diseases  

Microsoft Academic Search

Understanding complex diseases will benefit the recognition of the properties of the gene networks that control biological functions. Here, we set out to model the gene network that controls T-cell activation in humans, which is critical for the development of autoimmune diseases such as Multiple Sclerosis (MS). The network was established on the basis of the quantitative expression from 104

Ricardo Palacios; Joaquin Goni; Ivan Martinez-Forero; Jaime Iranzo; Jorge Sepulcre; Ignacio Melero; Pablo Villoslada

2007-01-01

54

NIH Researchers Identify OCD Risk Gene  

MedlinePLUS

... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...

55

Genome-Wide Analysis of Copy Number Variation Identifies Candidate Gene Loci Associated with the Progression of Non-Alcoholic Fatty Liver Disease  

PubMed Central

Between 10 and 25% of individuals with non-alcoholic fatty liver disease (NAFLD) develop hepatic fibrosis leading to cirrhosis and hepatocellular carcinoma (HCC). To investigate the molecular basis of disease progression, we performed a genome-wide analysis of copy number variation (CNV) in a total of 49 patients with NAFLD [10 simple steatosis and 39 non-alcoholic steatohepatitis (NASH)] and 49 matched controls using high-density comparative genomic hybridization (CGH) microarrays. A total of 11 CNVs were found to be unique to individuals with simple steatosis, whilst 22 were common between simple steatosis and NASH, and 224 were unique to NASH. We postulated that these CNVs could be involved in the pathogenesis of NAFLD progression. After stringent filtering, we identified four rare and/or novel CNVs that may influence the pathogenesis of NASH. Two of these CNVs, located at 13q12.11 and 12q13.2 respectively, harbour the exportin 4 (XPO4) and phosphodiesterase 1B (PDE1B) genes which are already known to be involved in the etiology of liver cirrhosis and HCC. Cross-comparison of the genes located at these four CNV loci with genes already known to be associated with NAFLD yielded a set of genes associated with shared biological processes including cell death, the key process involved in ‘second hit’ hepatic injury. To our knowledge, this pilot study is the first to provide CNV information of potential relevance to the NAFLD spectrum. These data could prove invaluable in predicting patients at risk of developing NAFLD and more importantly, those who will subsequently progress to NASH.

Zain, Shamsul Mohd; Mohamed, Rosmawati; Cooper, David N.; Razali, Rozaimi; Rampal, Sanjay; Mahadeva, Sanjiv; Chan, Wah-Kheong; Anwar, Arif; Rosli, Nurul Shielawati Mohamed; Mahfudz, Anis Shafina; Cheah, Phaik-Leng; Basu, Roma Choudhury; Mohamed, Zahurin

2014-01-01

56

Polymorphisms in recent GWA identified asthma genes CA10, SGK493, and CTNNA3 are associated with disease severity and treatment response in childhood asthma.  

PubMed

Recent genome-wide association studies (GWAs) have identified several new genetic risk factors for asthma; however, their influence on disease behavior and treatment response is still unclear. The aim of our study was the association analysis of the most significant single nucleotide polymorphisms (SNPs) recently reported by GWAs in different phenotypes of childhood asthma and analysis of correlation between these SNPs and clinical parameters. We have genotyped 288 children with asthma and 276 healthy controls. We provided here first replication of bivariate associations between CA10 (p?=?0.001) and SGK493 (p?=?0.011) with asthma. In addition, we have identified new correlation between SNPs in CA10, SGK493, and CTNNA3 with asthma behavior and glucocorticoid treatment response. Asthma patients who carried G allele in SNP rs967676 in gene CA10 were associated with more pronounced airway obstruction, higher bronchial hyper-reactivity, and increased inflammation. Higher bronchial hyper-reactivity was also associated with C allele in SNP rs1440095 in gene SGK493 but only in nonatopic asthmatics. In addition, we found that patients who carried at least one T allele in SNP rs1786929 in CTNNA3 (p?=?0.022) and atopic patients who carried at least one G allele in SNP rs967676 in gene CA10 (p?=?0.034) had higher increase in pulmonary function after glucocorticoid therapy. Our results suggest genetic heterogeneity between atopic and nonatopic asthma. We provided further evidence that treatment response in childhood asthma is genetically predisposed, and we report here two novel SNPs in genes CA10 and CTNNA3 as potential pharmacogenetic biomarkers that could be used in personalized treatment in childhood asthma. PMID:24407380

Perin, Petra; Poto?nik, Uroš

2014-03-01

57

Parkinson's Disease: Gene Therapies  

PubMed Central

With the recent development of effective gene delivery systems, gene therapy for the central nervous system is finding novel applications. Here, we review existing viral vectors and discuss gene therapy strategies that have been proposed for Parkinson’s disease. To date, most of the clinical trials were based on viral vectors to deliver therapeutic transgenes to neurons within the basal ganglia. Initial trials used genes to relieve the major motor symptoms caused by nigrostriatal degeneration. Although these new genetic approaches still need to prove more effective than existing symptomatic treatments, there is a need for disease-modifying strategies. The investigation of the genetic factors implicated in Parkinson’s disease is providing precious insights in disease pathology that, combined with innovative gene delivery systems, will hopefully offer novel opportunities for gene therapy interventions to slow down, or even halt disease progression.

Coune, Philippe G.; Schneider, Bernard L.; Aebischer, Patrick

2012-01-01

58

Identifying potential cancer driver genes by genomic data integration  

NASA Astrophysics Data System (ADS)

Cancer is a genomic disease associated with a plethora of gene mutations resulting in a loss of control over vital cellular functions. Among these mutated genes, driver genes are defined as being causally linked to oncogenesis, while passenger genes are thought to be irrelevant for cancer development. With increasing numbers of large-scale genomic datasets available, integrating these genomic data to identify driver genes from aberration regions of cancer genomes becomes an important goal of cancer genome analysis and investigations into mechanisms responsible for cancer development. A computational method, MAXDRIVER, is proposed here to identify potential driver genes on the basis of copy number aberration (CNA) regions of cancer genomes, by integrating publicly available human genomic data. MAXDRIVER employs several optimization strategies to construct a heterogeneous network, by means of combining a fused gene functional similarity network, gene-disease associations and a disease phenotypic similarity network. MAXDRIVER was validated to effectively recall known associations among genes and cancers. Previously identified as well as novel driver genes were detected by scanning CNAs of breast cancer, melanoma and liver carcinoma. Three predicted driver genes (CDKN2A, AKT1, RNF139) were found common in these three cancers by comparative analysis.

Chen, Yong; Hao, Jingjing; Jiang, Wei; He, Tong; Zhang, Xuegong; Jiang, Tao; Jiang, Rui

2013-12-01

59

Identifying potential cancer driver genes by genomic data integration.  

PubMed

Cancer is a genomic disease associated with a plethora of gene mutations resulting in a loss of control over vital cellular functions. Among these mutated genes, driver genes are defined as being causally linked to oncogenesis, while passenger genes are thought to be irrelevant for cancer development. With increasing numbers of large-scale genomic datasets available, integrating these genomic data to identify driver genes from aberration regions of cancer genomes becomes an important goal of cancer genome analysis and investigations into mechanisms responsible for cancer development. A computational method, MAXDRIVER, is proposed here to identify potential driver genes on the basis of copy number aberration (CNA) regions of cancer genomes, by integrating publicly available human genomic data. MAXDRIVER employs several optimization strategies to construct a heterogeneous network, by means of combining a fused gene functional similarity network, gene-disease associations and a disease phenotypic similarity network. MAXDRIVER was validated to effectively recall known associations among genes and cancers. Previously identified as well as novel driver genes were detected by scanning CNAs of breast cancer, melanoma and liver carcinoma. Three predicted driver genes (CDKN2A, AKT1, RNF139) were found common in these three cancers by comparative analysis. PMID:24346768

Chen, Yong; Hao, Jingjing; Jiang, Wei; He, Tong; Zhang, Xuegong; Jiang, Tao; Jiang, Rui

2013-01-01

60

Identifying Gene Networks Underlying the Neurobiology of Ethanol and Alcoholism  

PubMed Central

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

Wolen, Aaron R.; Miles, Michael F.

2012-01-01

61

Disease Resistance Mechanism Identified in Plants  

NSF Publications Database

... plants is triggered by the interaction of proteins produced by both a resistance gene in the plant ... how a plant recognizes one pathogen, we should begin to understand how plants identify many ...

62

Integrated Analyses of Genome-Wide DNA Occupancy and Expression Profiling Identify Key Genes and Pathways Involved in Cellular Transformation by a Marek's Disease Virus Oncoprotein, Meq  

PubMed Central

Marek's disease (MD) is an economically significant disease in chickens that is caused by the highly oncogenic Marek's disease virus (MDV). A major unanswered question is the mechanism of MDV-induced tumor formation. Meq, a bZIP transcription factor discovered in the 1990s, is critically involved in viral oncogenicity, but only a few of its host target genes have been described, impeding our understanding of MDV-induced tumorigenesis. Using chromatin immunoprecipitation-sequencing (ChIP-seq) and microarray analysis, a high-confidence list of Meq binding sites in the chicken genome and a global transcriptome of Meq-responsive genes were generated. Meq binding sites were found to be enriched in the promoter regions of upregulated genes but not in those of downregulated genes. ChIP-seq was also performed for c-Jun, a known heterodimeric partner of Meq. The close location of binding sites of Meq and c-Jun was noted, suggesting cooperativity between these two factors in modulating transcription. Pathway analysis indicated that Meq transcriptionally regulates many genes that are part of several signaling pathways including the extracellular signal-regulated kinase /mitogen-activated protein kinase (ERK/MAPK), Jak-STAT, and ErbB pathways, which are critical for oncogenesis and/or include signaling mediators involved in apoptosis. Meq activates oncogenic signaling cascades by transcriptionally activating major kinases in the ERK/MAPK pathway and simultaneously repressing phosphatases, as verified using inhibitors of MEK and ERK1/2 in a cell proliferation assay. This study provides significant insights into the mechanistic basis of Meq-dependent cell transformation.

Subramaniam, Sugalesini; Johnston, John; Preeyanon, Likit; Brown, C. Titus; Kung, Hsing-Jien

2013-01-01

63

PCR and restriction fragment length polymorphism of a pel gene as a tool to identify Erwinia carotovora in relation to potato diseases.  

PubMed Central

Using a sequenced pectate lyase-encoding gene (pel gene), we developed a PCR test for Erwinia carotovora. A set of primers allowed the amplification of a 434-bp fragment in E. carotovora strains. Among the 89 E. carotovora strains tested, only the Erwinia carotovora subsp. betavasculorum strains were not detected. A restriction fragment length polymorphism (RFLP) study was undertaken on the amplified fragment with seven endonucleases. The Sau3AI digestion pattern specifically identified the Erwinia carotovora subsp. atroseptica strains, and the whole set of data identified the Erwinia carotovora subsp. wasabiae strains. However, Erwinia carotovora subsp. carotovora and Erwinia carotovora subsp. odorifera could not be separated. Phenetic and phylogenic analyses of RFLP results showed E. carotovora subsp. atroseptica as a homogeneous group while E. carotovora subsp. carotovora and E. carotovora subsp. odorifera strains exhibited a genetic diversity that may result from a nonmonophyletic origin. The use of RFLP on amplified fragments in epidemiology and for diagnosis is discussed. Images

Darrasse, A; Priou, S; Kotoujansky, A; Bertheau, Y

1994-01-01

64

High-Resolution Melting (HRM) of the Cytochrome B Gene: A Powerful Approach to Identify Blood-Meal Sources in Chagas Disease Vectors  

PubMed Central

Methods to determine blood-meal sources of hematophagous Triatominae bugs (Chagas disease vectors) are serological or based on PCR employing species-specific primers or heteroduplex analysis, but these are expensive, inaccurate, or problematic when the insect has fed on more than one species. To solve those problems, we developed a technique based on HRM analysis of the mitochondrial gene cytochrome B (Cyt b). This technique recognized 14 species involved in several ecoepidemiological cycles of the transmission of Trypanosoma cruzi and it was suitable with DNA extracted from intestinal content and feces 30 days after feeding, revealing a resolution power that can display mixed feedings. Field samples were analyzed showing blood meal sources corresponding to domestic, peridomiciliary and sylvatic cycles. The technique only requires a single pair of primers that amplify the Cyt b gene in vertebrates and no other standardization, making it quick, easy, relatively inexpensive, and highly accurate.

Pena, Victor H.; Fernandez, Geysson J.; Gomez-Palacio, Andres M.; Mejia-Jaramillo, Ana M.; Cantillo, Omar; Triana-Chavez, Omar

2012-01-01

65

Novel Mutation Identified in the PAH Gene  

Microsoft Academic Search

The investigation of a DNA-amplified fragment of a phenylketonuria (PKU) patient by sequencing reveals a novel mutation in the PAH gene. This mutation represents the deletion of a single base (guanine) localized at the intron 11\\/exon 12 junction. This newly described mutation may be a frameshift or a splicing mutation. The identified mutation expresses phenotypically as the severe form of

E. V. Charikova

1996-01-01

66

Identifying clusters in Bayesian disease mapping.  

PubMed

Disease mapping is the field of spatial epidemiology interested in estimating the spatial pattern in disease risk across [Formula: see text] areal units. One aim is to identify units exhibiting elevated disease risks, so that public health interventions can be made. Bayesian hierarchical models with a spatially smooth conditional autoregressive prior are used for this purpose, but they cannot identify the spatial extent of high-risk clusters. Therefore, we propose a two-stage solution to this problem, with the first stage being a spatially adjusted hierarchical agglomerative clustering algorithm. This algorithm is applied to data prior to the study period, and produces [Formula: see text] potential cluster structures for the disease data. The second stage fits a separate Poisson log-linear model to the study data for each cluster structure, which allows for step-changes in risk where two clusters meet. The most appropriate cluster structure is chosen by model comparison techniques, specifically by minimizing the Deviance Information Criterion. The efficacy of the methodology is established by a simulation study, and is illustrated by a study of respiratory disease risk in Glasgow, Scotland. PMID:24622038

Anderson, Craig; Lee, Duncan; Dean, Nema

2014-07-01

67

Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease, and shows evidence for additional susceptibility genes  

PubMed Central

We undertook a two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the APOE locus (most significant SNP: rs2075650, p= 1.8×10?157) and observed genome-wide significant association with SNPs at two novel loci: rs11136000 in the CLU or APOJ gene (p= 1.4×10?9) and rs3851179, a SNP 5? to the PICALM gene (p= 1.9×10?8). Both novel associations were supported in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with AD in the combined dataset (rs11136000: p= 8.5×10?10, odds ratio= 0.86; rs3851179: p= 1.3×10?9, odds ratio= 0.86). We also observed more variants associated at p< 1×10?5 than expected by chance (p=7.5×10?6), including polymorphisms at the BIN1, DAB1 and CR1 loci.

Harold, Denise; Abraham, Richard; Hollingworth, Paul; Sims, Rebecca; Gerrish, Amy; Hamshere, Marian; Singh Pahwa, Jaspreet; Moskvina, Valentina; Dowzell, Kimberley; Williams, Amy; Jones, Nicola; Thomas, Charlene; Stretton, Alexandra; Morgan, Angharad; Lovestone, Simon; Powell, John; Proitsi, Petroula; Lupton, Michelle K; Brayne, Carol; Rubinsztein, David C.; Gill, Michael; Lawlor, Brian; Lynch, Aoibhinn; Morgan, Kevin; Brown, Kristelle; Passmore, Peter; Craig, David; McGuinness, Bernadette; Todd, Stephen; Holmes, Clive; Mann, David; Smith, A. David; Love, Seth; Kehoe, Patrick G.; Hardy, John; Mead, Simon; Fox, Nick; Rossor, Martin; Collinge, John; Maier, Wolfgang; Jessen, Frank; Schurmann, Britta; van den Bussche, Hendrik; Heuser, Isabella; Kornhuber, Johannes; Wiltfang, Jens; Dichgans, Martin; Frolich, Lutz; Hampel, Harald; Hull, Michael; Rujescu, Dan; Goate, Alison; Kauwe, John S.K.; Cruchaga, Carlos; Nowotny, Petra; Morris, John C.; Mayo, Kevin; Sleegers, Kristel; Bettens, Karolien; Engelborghs, Sebastiaan; De Deyn, Peter; van Broeckhoven, Christine; Livingston, Gill; Bass, Nicholas J.; Gurling, Hugh; McQuillin, Andrew; Gwilliam, Rhian; Deloukas, Panagiotis; Al-Chalabi, Ammar; Shaw, Christopher E.; Tsolaki, Magda; Singleton, Andrew; Guerreiro, Rita; Muhleisen, Thomas W.; Nothen, Markus M.; Moebus, Susanne; Jockel, Karl-Heinz; Klopp, Norman; Wichmann, H-Erich; Carrasquillo, Minerva M.; Pankratz, V. Shane; Younkin, Steven G.; Holmans, Peter; O'Donovan, Michael; Owen, Michael J.; Williams, Julie

2010-01-01

68

Integrative Genomics Identifies Gene Signature Associated with Melanoma Ulceration  

PubMed Central

Background Despite the extensive research approaches applied to characterise malignant melanoma, no specific molecular markers are available that are clearly related to the progression of this disease. In this study, our aims were to define a gene expression signature associated with the clinical outcome of melanoma patients and to provide an integrative interpretation of the gene expression -, copy number alterations -, and promoter methylation patterns that contribute to clinically relevant molecular functional alterations. Methods Gene expression profiles were determined using the Affymetrix U133 Plus2.0 array. The NimbleGen Human CGH Whole-Genome Tiling array was used to define CNAs, and the Illumina GoldenGate Methylation platform was applied to characterise the methylation patterns of overlapping genes. Results We identified two subclasses of primary melanoma: one representing patients with better prognoses and the other being characteristic of patients with unfavourable outcomes. We assigned 1,080 genes as being significantly correlated with ulceration, 987 genes were downregulated and significantly enriched in the p53, Nf-kappaB, and WNT/beta-catenin pathways. Through integrated genome analysis, we defined 150 downregulated genes whose expression correlated with copy number losses in ulcerated samples. These genes were significantly enriched on chromosome 6q and 10q, which contained a total of 36 genes. Ten of these genes were downregulated and involved in cell-cell and cell-matrix adhesion or apoptosis. The expression and methylation patterns of additional genes exhibited an inverse correlation, suggesting that transcriptional silencing of these genes is driven by epigenetic events. Conclusion Using an integrative genomic approach, we were able to identify functionally relevant molecular hotspots characterised by copy number losses and promoter hypermethylation in distinct molecular subtypes of melanoma that contribute to specific transcriptomic silencing and might indicate a poor clinical outcome of melanoma.

Toth, Reka; Vizkeleti, Laura; Herandez-Vargas, Hector; Lazar, Viktoria; Emri, Gabriella; Szatmari, Istvan; Herceg, Zdenko; Adany, Roza; Balazs, Margit

2013-01-01

69

Disease gene identification strategies for exome sequencing  

PubMed Central

Next generation sequencing can be used to search for Mendelian disease genes in an unbiased manner by sequencing the entire protein-coding sequence, known as the exome, or even the entire human genome. Identifying the pathogenic mutation amongst thousands to millions of genomic variants is a major challenge, and novel variant prioritization strategies are required. The choice of these strategies depends on the availability of well-phenotyped patients and family members, the mode of inheritance, the severity of the disease and its population frequency. In this review, we discuss the current strategies for Mendelian disease gene identification by exome resequencing. We conclude that exome strategies are successful and identify new Mendelian disease genes in approximately 60% of the projects. Improvements in bioinformatics as well as in sequencing technology will likely increase the success rate even further. Exome sequencing is likely to become the most commonly used tool for Mendelian disease gene identification for the coming years.

Gilissen, Christian; Hoischen, Alexander; Brunner, Han G; Veltman, Joris A

2012-01-01

70

Network topology reveals key cardiovascular disease genes.  

PubMed

The structure of protein-protein interaction (PPI) networks has already been successfully used as a source of new biological information. Even though cardiovascular diseases (CVDs) are a major global cause of death, many CVD genes still await discovery. We explore ways to utilize the structure of the human PPI network to find important genes for CVDs that should be targeted by drugs. The hope is to use the properties of such important genes to predict new ones, which would in turn improve a choice of therapy. We propose a methodology that examines the PPI network wiring around genes involved in CVDs. We use the methodology to identify a subset of CVD-related genes that are statistically significantly enriched in drug targets and "driver genes." We seek such genes, since driver genes have been proposed to drive onset and progression of a disease. Our identified subset of CVD genes has a large overlap with the Core Diseasome, which has been postulated to be the key to disease formation and hence should be the primary object of therapeutic intervention. This indicates that our methodology identifies "key" genes responsible for CVDs. Thus, we use it to predict new CVD genes and we validate over 70% of our predictions in the literature. Finally, we show that our predicted genes are functionally similar to currently known CVD drug targets, which confirms a potential utility of our methodology towards improving therapy for CVDs. PMID:23977067

Sarajli?, Anida; Janji?, Vuk; Stojkovi?, Neda; Radak, Djordje; Pržulj, Nataša

2013-01-01

71

Network Topology Reveals Key Cardiovascular Disease Genes  

PubMed Central

The structure of protein-protein interaction (PPI) networks has already been successfully used as a source of new biological information. Even though cardiovascular diseases (CVDs) are a major global cause of death, many CVD genes still await discovery. We explore ways to utilize the structure of the human PPI network to find important genes for CVDs that should be targeted by drugs. The hope is to use the properties of such important genes to predict new ones, which would in turn improve a choice of therapy. We propose a methodology that examines the PPI network wiring around genes involved in CVDs. We use the methodology to identify a subset of CVD-related genes that are statistically significantly enriched in drug targets and “driver genes.” We seek such genes, since driver genes have been proposed to drive onset and progression of a disease. Our identified subset of CVD genes has a large overlap with the Core Diseasome, which has been postulated to be the key to disease formation and hence should be the primary object of therapeutic intervention. This indicates that our methodology identifies “key” genes responsible for CVDs. Thus, we use it to predict new CVD genes and we validate over 70% of our predictions in the literature. Finally, we show that our predicted genes are functionally similar to currently known CVD drug targets, which confirms a potential utility of our methodology towards improving therapy for CVDs.

Stojkovic, Neda; Radak, Djordje; Przulj, Natasa

2013-01-01

72

Basal Gene Expression by Lung CD4+ T Cells in Chronic Obstructive Pulmonary Disease Identifies Independent Molecular Correlates of Airflow Obstruction and Emphysema Extent  

PubMed Central

Lung CD4+ T cells accumulate as chronic obstructive pulmonary disease (COPD) progresses, but their role in pathogenesis remains controversial. To address this controversy, we studied lung tissue from 53 subjects undergoing clinically-indicated resections, lung volume reduction, or transplant. Viable single-cell suspensions were analyzed by flow cytometry or underwent CD4+ T cell isolation, followed either by stimulation with anti-CD3 and cytokine/chemokine measurement, or by real-time PCR analysis. In lung CD4+ T cells of most COPD subjects, relative to lung CD4+ T cells in smokers with normal spirometry: (a) stimulation induced minimal IFN-? or other inflammatory mediators, but many subjects produced more CCL2; (b) the T effector memory subset was less uniformly predominant, without correlation with decreased IFN-? production. Analysis of unstimulated lung CD4+ T cells of all subjects identified a molecular phenotype, mainly in COPD, characterized by markedly reduced mRNA transcripts for the transcription factors controlling TH1, TH2, TH17 and FOXP3+ T regulatory subsets and their signature cytokines. This mRNA-defined CD4+ T cell phenotype did not result from global inability to elaborate mRNA; increased transcripts for inhibitory CD28 family members or markers of anergy; or reduced telomerase length. As a group, these subjects had significantly worse spirometry, but not DLCO, relative to subjects whose lung CD4+ T cells expressed a variety of transcripts. Analysis of mRNA transcripts of unstimulated lung CD4+ T cell among all subjects identified two distinct molecular correlates of classical COPD clinical phenotypes: basal IL-10 transcripts correlated independently and inversely with emphysema extent (but not spirometry); by contrast, unstimulated IFN-? transcripts correlated independently and inversely with reduced spirometry (but not reduced DLCO or emphysema extent). Aberrant lung CD4+ T cells polarization appears to be common in advanced COPD, but also exists in some smokers with normal spirometry, and may contribute to development and progression of specific COPD phenotypes. Trial Registration ClinicalTrials.gov as NCT00281229

Freeman, Christine M.; McCubbrey, Alexandra L.; Crudgington, Sean; Nelson, Joshua; Martinez, Fernando J.; Han, MeiLan K.; Washko, George R.; Chensue, Stephen W.; Arenberg, Douglas A.; Meldrum, Catherine A.; McCloskey, Lisa; Curtis, Jeffrey L.

2014-01-01

73

A molecular signature in blood identifies early Parkinson's disease  

PubMed Central

Background The search for biomarkers in Parkinson’s disease (PD) is crucial to identify the disease early and monitor the effectiveness of neuroprotective therapies. We aim to assess whether a gene signature could be detected in blood from early/mild PD patients that could support the diagnosis of early PD, focusing on genes found particularly altered in the substantia nigra of sporadic PD. Results The transcriptional expression of seven selected genes was examined in blood samples from 62 early stage PD patients and 64 healthy age-matched controls. Stepwise multivariate logistic regression analysis identified five genes as optimal predictors of PD: p19 S-phase kinase-associated protein 1A (odds ratio [OR] 0.73; 95% confidence interval [CI] 0.60–0.90), huntingtin interacting protein-2 (OR 1.32; CI 1.08–1.61), aldehyde dehydrogenase family 1 subfamily A1 (OR 0.86; 95% CI 0.75–0.99), 19?S proteasomal protein PSMC4 (OR 0.73; 95% CI 0.60–0.89) and heat shock 70-kDa protein 8 (OR 1.39; 95% CI 1.14–1.70). At a 0.5 cut-off the gene panel yielded a sensitivity and specificity in detecting PD of 90.3 and 89.1 respectively and the area under the receiving operating curve (ROC AUC) was 0.96. The performance of the five-gene classifier on the de novo PD individuals alone composing the early PD cohort (n?=?38), resulted in a similar ROC with an AUC of 0.95, indicating the stability of the model and also, that patient medication had no significant effect on the predictive probability (PP) of the classifier for PD risk. The predictive ability of the model was validated in an independent cohort of 30 patients at advanced stage of PD, classifying correctly all cases as PD (100% sensitivity). Notably, the nominal average value of the PP for PD (0.95 (SD?=?0.09)) in this cohort was higher than that of the early PD group (0.83 (SD?=?0.22)), suggesting a potential for the model to assess disease severity. Lastly, the gene panel fully discriminated between PD and Alzheimer’s disease (n?=?29). Conclusions The findings provide evidence on the ability of a five-gene panel to diagnose early/mild PD, with a possible diagnostic value for detection of asymptomatic PD before overt expression of the disorder.

2012-01-01

74

The Search for Autism Disease Genes  

ERIC Educational Resources Information Center

Autism is a heritable disorder characterized by phenotypic and genetic complexity. This review begins by surveying current linkage, gene association, and cytogenetic studies performed with the goal of identifying autism disease susceptibility variants. Though numerous linkages and associations have been identified, they tend to diminish upon…

Wassink, Thomas H.; Brzustowicz, Linda M.; Bartlett, Christopher W.; Szatmari, Peter

2004-01-01

75

Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism  

PubMed Central

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD.

Poot, Martin; Hochstenbach, Ron; Spierenburg, Henk A.; Vorstman, Jacob A. S.; van Daalen, Emma; de Jonge, Maretha V.; Verbeek, Nienke E.; Brilstra, Eva H.; van 't Slot, Ruben; Ophoff, Roel A.; van Es, Michael A.; Blauw, Hylke M.; Veldink, Jan H.; Buizer-Voskamp, Jacobine E.; Beemer, Frits A.; van den Berg, Leonard H.; Wijmenga, Cisca; van Amstel, Hans Kristian Ploos; van Engeland, Herman; Burbach, J. Peter H.; Staal, Wouter G.

2009-01-01

76

Identifying Antimicrobial Resistance Genes with DNA Microarrays  

Microsoft Academic Search

We developed and tested a glass-based microarray suitable for detecting multiple tetracycline (tet) resistance genes. Microarray probes for 17 tet genes, the -lactamase blaTEM-1 gene, and a 16S ribosomal DNA gene (Escherichia coli) were generated from known controls by PCR. The resulting products (ca. 550 bp) were applied as spots onto epoxy-silane-derivatized, Teflon-masked slides by using a robotic spotter. DNA

Douglas R. Call; Marlene K. Bakko; Melissa J. Krug; Marilyn C. Roberts

2003-01-01

77

Gene Therapy for Parkinson's Disease  

PubMed Central

Current pharmacological and surgical treatments for Parkinson's disease offer symptomatic improvements to those suffering from this incurable degenerative neurological disorder, but none of these has convincingly shown effects on disease progression. Novel approaches based on gene therapy have several potential advantages over conventional treatment modalities. These could be used to provide more consistent dopamine supplementation, potentially providing superior symptomatic relief with fewer side effects. More radically, gene therapy could be used to correct the imbalances in basal ganglia circuitry associated with the symptoms of Parkinson's disease, or to preserve or restore dopaminergic neurons lost during the disease process itself. The latter neuroprotective approach is the most exciting, as it could theoretically be disease modifying rather than simply symptom alleviating. Gene therapy agents using these approaches are currently making the transition from the laboratory to the bedside. This paper summarises the theoretical approaches to gene therapy for Parkinson's disease and the findings of clinical trials in this rapidly changing field.

Denyer, Rachel; Douglas, Michael R.

2012-01-01

78

Gene therapy for ocular diseases  

PubMed Central

The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

2011-01-01

79

Gene therapy in Parkinson's disease.  

PubMed

Gene therapy in Parkinson's disease appears to be at the brink of the clinical study phase. Future gene therapy protocols will be based on a substantial amount of preclinical data regarding the use of ex vivo and in vivo genetic modifications with the help of viral or non-viral vectors. To date, the supplementation of neurotrophic factors and substitution for the dopaminergic deficit have formed the focus of trials to achieve relief in animal models of Parkinson's disease. Newer approaches include attempts to influence detrimental cell signalling pathways and to inhibit overactive basal ganglia structures. Nevertheless, current models of Parkinson's disease do not mirror all aspects of the human disease, and important issues with respect to long-term protein expression, choice of target structures and transgenes and safety remain to be solved. Here, we thoroughly review available animal data of gene transfer in models of Parkinson's disease. PMID:15322915

Eberhardt, O; Schulz, J B

2004-10-01

80

Gene Therapy for Liver Disease  

Microsoft Academic Search

With major advances in biomedical science over the last 2 decades, the possibility of treating human disease at a genetic level has become a tantalizing possibility. As a result, a growing number of investigators are focusing on the development of techniques to deliver therapeutic genes into cells. The liver has been a model organ in the development of this gene

Timothy J. Davern II; Bruce F. Scharschmidt

1998-01-01

81

Cancer genomics identifies disrupted epigenetic genes.  

PubMed

Latest advances in genome technologies have greatly advanced the discovery of epigenetic genes altered in cancer. The initial single candidate gene approaches have been coupled with newly developed epigenomic platforms to hasten the convergence of scientific discoveries and translational applications. Here, we present an overview of the evolution of cancer epigenomics and an updated catalog of disruptions in epigenetic pathways, whose misregulation can culminate in cancer. The creation of these basic mutational catalogs in cell lines and primary tumors will provide us with enough knowledge to move diagnostics and therapy from the laboratory bench to the bedside. PMID:24104525

Simó-Riudalbas, Laia; Esteller, Manel

2014-06-01

82

Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.  

PubMed

Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases. PMID:16757574

Tiffin, Nicki; Adie, Euan; Turner, Frances; Brunner, Han G; van Driel, Marc A; Oti, Martin; Lopez-Bigas, Nuria; Ouzounis, Christos; Perez-Iratxeta, Carolina; Andrade-Navarro, Miguel A; Adeyemo, Adebowale; Patti, Mary Elizabeth; Semple, Colin A M; Hide, Winston

2006-01-01

83

Comparison of melanoblast expression patterns identifies distinct classes of genes  

PubMed Central

Summary A full understanding of transcriptional regulation requires integration of information obtained from multiple experimental datasets. These include datasets annotating gene expression within the context of an entire organism under normal and genetically perturbed conditions. Here we describe an expression dataset annotating pigment cell-expressed genes of the developing melanocyte and RPE lineages. Expression images are annotated and available at http://research.nhgri.nih.gov/manuscripts/Loftus/March2009/. Data is also summarized in a standardized manner using a universal melanoblast scoring scale that accounts for the embryonic location of cells and regional cell density. This approach allowed us to classify 14 pigment genes into 4 groupings classified by cell lineage expression, temporal-spatial context, and differential alteration in response to altered MITF and SOX10 status. Significant differences in regional populations were also observed across inbred strain backgrounds highlighting the value of this approach to identify modifier allele influences on melanoblast number and distributions. This analysis revealed novel features of in vivo expression patterns that are not measurable by in vitro-based assays, providing data that in combination with genomic analyses will allow modeling of pigment cell gene expression in development and disease.

Loftus, Stacie K.; Baxter, Laura L.; Buac, Kristina; Watkins-Chow, Dawn E.; Larson, Denise M.; Pavan, William J.

2010-01-01

84

Single Gene Disease Risk  

Microsoft Academic Search

\\u000a The diagnosis of a child with a single gene disorder can take on different meanings for different families. It is not uncommon\\u000a for some families to arrive at a pediatric genetics clinic after months or years of searching for an underlying reason for\\u000a their child’s symptoms. The fact that, through genetic testing, clinicians can put a name to the collection

Tricia See; Cynthia J. Tifft

85

[Gene therapy for Parkinson's disease].  

PubMed

Parkinson's disease is a chronic and progressive disorder whose treatment does not prevent middle term appearance of invalidating motor and psychic complications. Gene therapy techniques which are increasingly applied in the field of neurodegenerative diseases are added to the possibility of treatment of this disease. Among the existing modalities, the in vivo strategies that use potent viral vectors are those which have obtained the best results in the different existing models of the disease. This article aims to review the information regarding the use of these latter techniques, the therapeutic trials that have been conducted and the advantages and disadvantages that the use of the different vectors have. PMID:17315100

Gómez Gallego, M; Fernández Barreiro, A

2007-01-01

86

Differential Gene Repertoire in Mycobacterium ulcerans Identifies Candidate Genes for Patho-Adaptation  

PubMed Central

Background Based on large genomic sequence polymorphisms, several haplotypes belonging to two major lineages of the human pathogen Mycobacterium ulcerans could be distinguished among patient isolates from various geographic origins. However, the biological relevance of insertional/deletional diversity is not understood. Methodology Using comparative genomics, we have investigated the genes located in regions of difference recently identified by DNA microarray based hybridisation analysis. The analysed regions of difference comprise ?7% of the entire M. ulcerans genome. Principal Findings Several different mechanisms leading to loss of functional genes were identified, ranging from pseudogenization, caused by frame shift mutations or mobile genetic element interspersing, to large sequence polymorphisms. Four hot spot regions for genetic instability were unveiled. Altogether, 229 coding sequences were found to be differentially inactivated, constituting a repertoire of coding sequence variation in the rather monomorphic M. ulcerans. Conclusions/Significance The differential gene inactivation patterns associated with the M. ulcerans haplotypes identified candidate genes that may confer enhanced adaptation upon ablation of expression. A number of gene conversions confined to the classical lineage may contribute to particular virulence of this group comprising isolates from Africa and Australia. Identification of this spectrum of anti-virulence gene candidates expands our understanding of the pathogenicity and ecology of the emerging infectious disease Buruli ulcer.

Kaser, Michael; Pluschke, Gerd

2008-01-01

87

Linking genes to diseases: it's all in the data  

PubMed Central

Genome-wide association analyses on large patient cohorts are generating large sets of candidate disease genes. This is coupled with the availability of ever-increasing genomic databases and a rapidly expanding repository of biomedical literature. Computational approaches to disease-gene association attempt to harness these data sources to identify the most likely disease gene candidates for further empirical analysis by translational researchers, resulting in efficient identification of genes of diagnostic, prognostic and therapeutic value. Existing computational methods analyze gene structure and sequence, functional annotation of candidate genes, characteristics of known disease genes, gene regulatory networks, protein-protein interactions, data from animal models and disease phenotype. To date, a few studies have successfully applied computational analysis of clinical phenotype data for specific diseases and shown genetic associations. In the near future, computational strategies will be facilitated by improved integration of clinical and computational research, and by increased availability of clinical phenotype data in a format accessible to computational approaches.

2009-01-01

88

Computationally Identifying Novel NF-kappa B-Regulated Immune Genes in the Human Genome  

Microsoft Academic Search

Identifying novel NF-B-regulated immune genes in the human genome is important to our understanding of immune mechanisms and immune diseases. We fit logistic regression models to the promoters of 62known NF-B-regulated immune genes, to find patterns of transcription factor binding in the promoters of genes with known immune function. Using these patterns, we scanned the promoters of additional genes to

Rongxiang Liu; Richard C. McEachin; David J. States

2003-01-01

89

Patching genes to fight disease  

SciTech Connect

The National Institutes of Health has approved the first gene therapy experiments, one of which will try to cure cancer by bolstering the immune system. The applications of such therapy are limited, but the potential aid to people with genetic diseases is great.

Holzman, D.

1990-09-03

90

Blood Pressure Loci Identified with a Gene-Centric Array  

PubMed Central

Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10?7 study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r2 = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10?7 at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

Johnson, Toby; Gaunt, Tom R.; Newhouse, Stephen J.; Padmanabhan, Sandosh; Tomaszewski, Maciej; Kumari, Meena; Morris, Richard W.; Tzoulaki, Ioanna; O'Brien, Eoin T.; Poulter, Neil R.; Sever, Peter; Shields, Denis C.; Thom, Simon; Wannamethee, Sasiwarang G.; Whincup, Peter H.; Brown, Morris J.; Connell, John M.; Dobson, Richard J.; Howard, Philip J.; Mein, Charles A.; Onipinla, Abiodun; Shaw-Hawkins, Sue; Zhang, Yun; Smith, George Davey; Day, Ian N.M.; Lawlor, Debbie A.; Goodall, Alison H.; Fowkes, F. Gerald; Abecasis, Goncalo R.; Elliott, Paul; Gateva, Vesela; Braund, Peter S.; Burton, Paul R.; Nelson, Christopher P.; Tobin, Martin D.; van der Harst, Pim; Glorioso, Nicola; Neuvrith, Hani; Salvi, Erika; Staessen, Jan A.; Stucchi, Andrea; Devos, Nabila; Jeunemaitre, Xavier; Plouin, Pierre-Francois; Tichet, Jean; Juhanson, Peeter; Org, Elin; Putku, Margus; Sober, Siim; Veldre, Gudrun; Viigimaa, Margus; Levinsson, Anna; Rosengren, Annika; Thelle, Dag S.; Hastie, Claire E.; Hedner, Thomas; Lee, Wai K.; Melander, Olle; Wahlstrand, Bjorn; Hardy, Rebecca; Wong, Andrew; Cooper, Jackie A.; Palmen, Jutta; Chen, Li; Stewart, Alexandre F.R.; Wells, George A.; Westra, Harm-Jan; Wolfs, Marcel G.M.; Clarke, Robert; Franzosi, Maria Grazia; Goel, Anuj; Hamsten, Anders; Lathrop, Mark; Peden, John F.; Seedorf, Udo; Watkins, Hugh; Ouwehand, Willem H.; Sambrook, Jennifer; Stephens, Jonathan; Casas, Juan-Pablo; Drenos, Fotios; Holmes, Michael V.; Kivimaki, Mika; Shah, Sonia; Shah, Tina; Talmud, Philippa J.; Whittaker, John; Wallace, Chris; Delles, Christian; Laan, Maris; Kuh, Diana; Humphries, Steve E.; Nyberg, Fredrik; Cusi, Daniele; Roberts, Robert; Newton-Cheh, Christopher; Franke, Lude; Stanton, Alice V.; Dominiczak, Anna F.; Farrall, Martin; Hingorani, Aroon D.; Samani, Nilesh J.; Caulfield, Mark J.; Munroe, Patricia B.

2011-01-01

91

Blood pressure loci identified with a gene-centric array.  

PubMed

Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies. PMID:22100073

Johnson, Toby; Gaunt, Tom R; Newhouse, Stephen J; Padmanabhan, Sandosh; Tomaszewski, Maciej; Kumari, Meena; Morris, Richard W; Tzoulaki, Ioanna; O'Brien, Eoin T; Poulter, Neil R; Sever, Peter; Shields, Denis C; Thom, Simon; Wannamethee, Sasiwarang G; Whincup, Peter H; Brown, Morris J; Connell, John M; Dobson, Richard J; Howard, Philip J; Mein, Charles A; Onipinla, Abiodun; Shaw-Hawkins, Sue; Zhang, Yun; Davey Smith, George; Day, Ian N M; Lawlor, Debbie A; Goodall, Alison H; Fowkes, F Gerald; Abecasis, Gonçalo R; Elliott, Paul; Gateva, Vesela; Braund, Peter S; Burton, Paul R; Nelson, Christopher P; Tobin, Martin D; van der Harst, Pim; Glorioso, Nicola; Neuvrith, Hani; Salvi, Erika; Staessen, Jan A; Stucchi, Andrea; Devos, Nabila; Jeunemaitre, Xavier; Plouin, Pierre-François; Tichet, Jean; Juhanson, Peeter; Org, Elin; Putku, Margus; Sõber, Siim; Veldre, Gudrun; Viigimaa, Margus; Levinsson, Anna; Rosengren, Annika; Thelle, Dag S; Hastie, Claire E; Hedner, Thomas; Lee, Wai K; Melander, Olle; Wahlstrand, Björn; Hardy, Rebecca; Wong, Andrew; Cooper, Jackie A; Palmen, Jutta; Chen, Li; Stewart, Alexandre F R; Wells, George A; Westra, Harm-Jan; Wolfs, Marcel G M; Clarke, Robert; Franzosi, Maria Grazia; Goel, Anuj; Hamsten, Anders; Lathrop, Mark; Peden, John F; Seedorf, Udo; Watkins, Hugh; Ouwehand, Willem H; Sambrook, Jennifer; Stephens, Jonathan; Casas, Juan-Pablo; Drenos, Fotios; Holmes, Michael V; Kivimaki, Mika; Shah, Sonia; Shah, Tina; Talmud, Philippa J; Whittaker, John; Wallace, Chris; Delles, Christian; Laan, Maris; Kuh, Diana; Humphries, Steve E; Nyberg, Fredrik; Cusi, Daniele; Roberts, Robert; Newton-Cheh, Christopher; Franke, Lude; Stanton, Alice V; Dominiczak, Anna F; Farrall, Martin; Hingorani, Aroon D; Samani, Nilesh J; Caulfield, Mark J; Munroe, Patricia B

2011-12-01

92

Improved human disease candidate gene prioritization using mouse phenotype  

PubMed Central

Background The majority of common diseases are multi-factorial and modified by genetically and mechanistically complex polygenic interactions and environmental factors. High-throughput genome-wide studies like linkage analysis and gene expression profiling, tend to be most useful for classification and characterization but do not provide sufficient information to identify or prioritize specific disease causal genes. Results Extending on an earlier hypothesis that the majority of genes that impact or cause disease share membership in any of several functional relationships we, for the first time, show the utility of mouse phenotype data in human disease gene prioritization. We study the effect of different data integration methods, and based on the validation studies, we show that our approach, ToppGene , outperforms two of the existing candidate gene prioritization methods, SUSPECTS and ENDEAVOUR. Conclusion The incorporation of phenotype information for mouse orthologs of human genes greatly improves the human disease candidate gene analysis and prioritization.

Chen, Jing; Xu, Huan; Aronow, Bruce J; Jegga, Anil G

2007-01-01

93

Identifying multiple causative genes at a single GWAS locus  

PubMed Central

Genome-wide association studies (GWAS) are useful for nominating candidate genes, but typically are unable to establish disease causality or differentiate between the effects of variants in linkage disequilibrium (LD). Additionally, some GWAS loci might contain multiple causative variants or genes that contribute to the overall disease susceptibility at a single locus. However, the majority of current GWAS lack the statistical power to test whether multiple causative genes underlie the same locus, prompting us to adopt an alternative approach to testing multiple GWAS genes empirically. We used gene targeting in a disease-susceptible rat model of genetic hypertension to test all six genes at the Agtrap-Plod1 locus (Agtrap, Mthfr, Clcn6, Nppa, Nppb, and Plod1) for blood pressure (BP) and renal phenotypes. This revealed that the majority of genes at this locus (five out of six) can impact hypertension by modifying BP and renal phenotypes. Mutations of Nppa, Plod1, and Mthfr increased disease susceptibility, whereas Agtrap and Clcn6 mutations decreased hypertension risk. Reanalysis of the human AGTRAP-PLOD1 locus also implied that disease-associated haplotype blocks with polygenic effects were not only possible, but rather were highly plausible. Combined, these data demonstrate for the first time that multiple modifiers of hypertension can cosegregate at a single GWAS locus.

Flister, Michael J.; Tsaih, Shirng-Wern; O'Meara, Caitlin C.; Endres, Bradley; Hoffman, Matthew J.; Geurts, Aron M.; Dwinell, Melinda R.; Lazar, Jozef; Jacob, Howard J.; Moreno, Carol

2013-01-01

94

Gene expression profiling identifies clinically relevant subtypes of prostate cancer  

Microsoft Academic Search

Prostate cancer, a leading cause of cancer death, displays a broad range of clinical behavior from relatively indolent to aggressive metastatic disease. To explore potential molecular variation underlying this clinical heterogeneity, we profiled gene expression in 62 primary prostate tumors, as well as 41 normal prostate specimens and nine lymph node metastases, using cDNA microarrays containing 26,000 genes. Unsupervised hierarchical

Jacques Lapointe; Chunde Li; John P. Higgins; Matt van de Rijn; Eric Bair; Kelli Montgomery; Michelle Ferrari; Lars Egevad; Walter Rayford; Ulf Bergerheim; Peter Ekman; Angelo M. Demarzo; Robert Tibshirani; David Botstein; Patrick O. Brown; James D. Brooks; Jonathan R. Pollack

2004-01-01

95

Gene Expression Profiling Identifies Molecular Subtypes of Inflammatory Breast Cancer  

Microsoft Academic Search

Breast cancer is a heterogeneous disease. Comprehensive gene expression profiles obtained using DNA microarrays have revealed previously indistinguishable subtypes of noninflam- matory breast cancer (NIBC) related to different features of mammary epithelial biology and significantly associated with survival. Inflammatory breast cancer (IBC) is a rare, partic- ular, and aggressive form of disease. Here we have investigated whether the five molecular

Francois Bertucci; Pascal Finetti; Jacques Rougemont; Emmanuelle Charafe-Jauffret; Nathalie Cervera; Carole Tarpin; Catherine Nguyen; Luc Xerri; Remi Houlgatte; Jocelyne Jacquemier; Patrice Viens; Daniel Birnbaum

2005-01-01

96

GENE EXPRESSION PROFILING TO IDENTIFY MECHANISMS OF MALE REPRODUCTIVE TOXICITY  

EPA Science Inventory

Gene Expression Profiling to Identify Mechanisms of Male Reproductive Toxicity David J. Dix National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA. Ab...

97

GENE EXPRESSION PROFILING TO IDENTIFY BIOMARKERS OF REPRODUCTIVE TOXICITY  

EPA Science Inventory

SOT 2005 SESSION ABSTRACT GENE EXPRESSION PROFILING TO IDENTIFY BIOMARKERS OF REPRODUCTIVE TOXICITY David J. Dix. National Health and Environmental Effects Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle...

98

Scientists Identify Four Candidate Obesity Genes in Mice  

NSDL National Science Digital Library

Press release on a recent study where researchers developed a strain of mice more likely to be obese and then, using this strain, identified four genes in mouse chromosome 7 that may relate to obesity. This study, ÃÂFour Out of Eight Genes in a Mouse Chromosome 7 Congenic Donor Region are Candidate Obesity Genes,ÃÂ was conducted by Craig H. Warden, Kari A. Sarahan, and Janis S. Fisler of the University of California, Davis. The study is published in Physiologic Genomics.

APS Communications Office (American Physiological Society Communications Office)

2011-09-06

99

How to identify essential genes from molecular networks?  

PubMed Central

Background The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion. Results By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for Saccharomyces cerevisiae, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined. Conclusion The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.

del Rio, Gabriel; Koschutzki, Dirk; Coello, Gerardo

2009-01-01

100

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease  

PubMed Central

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

101

Identifying Unstable Regions of Proteins Involved in Misfolding Diseases  

Microsoft Academic Search

Protein misfolding is a necessary step in the pathogenesis of many diseases, including Creutzfeldt-Jakob disease (CJD) and familial amyotrophic lateral sclerosis (fALS). Identifying unstable structural elements in their causative proteins elucidates the early events of misfolding and presents targets for inhibition of the disease process. An algorithm was developed to calculate the Gibbs free energy of unfolding for all sequence-contiguous

Will Guest; Neil Cashman; Steven Plotkin

2009-01-01

102

RNA interference based gene therapy for neurological disease  

Microsoft Academic Search

Neurodegenerative disorders represent a major class of disorders for which thus far any effective small molecule drug therapy has failed to emerge. RNA interference (RNAi), by which disease genes such as those identified for spino-cerebellar ataxia and Huntington's disease can be specifically silenced, has great potential in becoming a successful therapeutic strategy for these diseases. RNAi has shown therapeutic value

Aarti Jagannath; Matthew Wood

2007-01-01

103

ENU Mutagenesis in Mice Identifies Candidate Genes For Hypogonadism  

PubMed Central

Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low density genome-wide SNP arrays. Ten of the fifteen lines were pursued further using higher resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility.

Weiss, Jeffrey; Hurley, Lisa A.; Harris, Rebecca M.; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A.; Moran, Jennifer L.; Beier, David R.; Mason, Christopher; Jameson, J. Larry

2012-01-01

104

Integrative genomics identifies APOE ?4 effectors in Alzheimer's disease.  

PubMed

Late-onset Alzheimer's disease (LOAD) risk is strongly influenced by genetic factors such as the presence of the apolipoprotein E ?4 allele (referred to here as APOE4), as well as non-genetic determinants including ageing. To pursue mechanisms by which these affect human brain physiology and modify LOAD risk, we initially analysed whole-transcriptome cerebral cortex gene expression data in unaffected APOE4 carriers and LOAD patients. APOE4 carrier status was associated with a consistent transcriptomic shift that broadly resembled the LOAD profile. Differential co-expression correlation network analysis of the APOE4 and LOAD transcriptomic changes identified a set of candidate core regulatory mediators. Several of these--including APBA2, FYN, RNF219 and SV2A--encode known or novel modulators of LOAD associated amyloid beta A4 precursor protein (APP) endocytosis and metabolism. Furthermore, a genetic variant within RNF219 was found to affect amyloid deposition in human brain and LOAD age-of-onset. These data implicate an APOE4 associated molecular pathway that promotes LOAD. PMID:23883936

Rhinn, Herve; Fujita, Ryousuke; Qiang, Liang; Cheng, Rong; Lee, Joseph H; Abeliovich, Asa

2013-08-01

105

Inferring gene family histories in yeast identifies lineage specific expansions.  

PubMed

The complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes. PMID:24921666

Ames, Ryan M; Money, Daniel; Lovell, Simon C

2014-01-01

106

Functional epigenetic approach identifies frequently methylated genes in Ewing sarcoma.  

PubMed

Using a candidate gene approach we recently identified frequent methylation of the RASSF2 gene associated with poor overall survival in Ewing sarcoma (ES). To identify effective biomarkers in ES on a genome-wide scale, we used a functionally proven epigenetic approach, in which gene expression was induced in ES cell lines by treatment with a demethylating agent followed by hybridization onto high density gene expression microarrays. After following a strict selection criterion, 34 genes were selected for expression and methylation analysis in ES cell lines and primary ES. Eight genes (CTHRC1, DNAJA4, ECHDC2, NEFH, NPTX2, PHF11, RARRES2, TSGA14) showed methylation frequencies of>20% in ES tumors (range 24-71%), these genes were expressed in human bone marrow derived mesenchymal stem cells (hBMSC) and hypermethylation was associated with transcriptional silencing. Methylation of NPTX2 or PHF11 was associated with poorer prognosis in ES. In addition, six of the above genes also showed methylation frequency of>20% (range 36-50%) in osteosarcomas. Identification of these genes may provide insights into bone cancer tumorigenesis and development of epigenetic biomarkers for prognosis and detection of these rare tumor types. PMID:24005033

Alholle, Abdullah; Brini, Anna T; Gharanei, Seley; Vaiyapuri, Sumathi; Arrigoni, Elena; Dallol, Ashraf; Gentle, Dean; Kishida, Takeshi; Hiruma, Toru; Avigad, Smadar; Grimer, Robert; Maher, Eamonn R; Latif, Farida

2013-11-01

107

Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions  

PubMed Central

The complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes.

Ames, Ryan M.; Money, Daniel; Lovell, Simon C.

2014-01-01

108

Gene Duplication Identified in an Uncommon Form of Bone Cancer  

Cancer.gov

Scientists have discovered that a familial form of a rare bone cancer called chordoma is explained not by typical types of changes or mutations in the sequence of DNA in a gene, but rather by the presence of a second copy of an entire gene. Inherited large structural changes, known as copy number variations (CNVs), have been implicated in some hereditary diseases but have seldom been reported as the underlying basis for a familial cancer.

109

The evolution of disease resistance genes  

Microsoft Academic Search

Several common themes have shaped the evolution of plant disease resistance genes. These include duplication events of progenitor resistance genes and further expansion to create clustered gene families. Variation can arise from both intragenic and intergenic recombination and gene conversion. Recombination has also been implicated in the generation of novel resistance specificities. Resistance gene clusters appear to evolve more rapidly

Todd E. Richter; Pamela C. Ronald

2000-01-01

110

Disease risk factors identified through shared genetic architecture and electronic medical records.  

PubMed

Genome-wide association studies have identified genetic variants for thousands of diseases and traits. We evaluated the relationships between specific risk factors (for example, blood cholesterol level) and diseases on the basis of their shared genetic architecture in a comprehensive human disease-single-nucleotide polymorphism association database (VARIMED), analyzing the findings from 8962 published association studies. Similarity between traits and diseases was statistically evaluated on the basis of their association with shared gene variants. We identified 120 disease-trait pairs that were statistically similar, and of these, we tested and validated five previously unknown disease-trait associations by searching electronic medical records (EMRs) from three independent medical centers for evidence of the trait appearing in patients within 1 year of first diagnosis of the disease. We validated that the mean corpuscular volume is elevated before diagnosis of acute lymphoblastic leukemia; both have associated variants in the gene IKZF1. Platelet count is decreased before diagnosis of alcohol dependence; both are associated with variants in the gene C12orf51. Alkaline phosphatase level is elevated in patients with venous thromboembolism; both share variants in ABO. Similarly, we found that prostate-specific antigen and serum magnesium levels were altered before the diagnosis of lung cancer and gastric cancer, respectively. Disease-trait associations identify traits that could serve as future prognostics, if validated through EMR and subsequent prospective trials. PMID:24786325

Li, Li; Ruau, David J; Patel, Chirag J; Weber, Susan C; Chen, Rong; Tatonetti, Nicholas P; Dudley, Joel T; Butte, Atul J

2014-04-30

111

Axon regeneration genes identified by RNAi screening in C. elegans.  

PubMed

Axons of the mammalian CNS lose the ability to regenerate soon after development due to both an inhibitory CNS environment and the loss of cell-intrinsic factors necessary for regeneration. The complex molecular events required for robust regeneration of mature neurons are not fully understood, particularly in vivo. To identify genes affecting axon regeneration in Caenorhabditis elegans, we performed both an RNAi-based screen for defective motor axon regeneration in unc-70/?-spectrin mutants and a candidate gene screen. From these screens, we identified at least 50 conserved genes with growth-promoting or growth-inhibiting functions. Through our analysis of mutants, we shed new light on certain aspects of regeneration, including the role of ?-spectrin and membrane dynamics, the antagonistic activity of MAP kinase signaling pathways, and the role of stress in promoting axon regeneration. Many gene candidates had not previously been associated with axon regeneration and implicate new pathways of interest for therapeutic intervention. PMID:24403161

Nix, Paola; Hammarlund, Marc; Hauth, Linda; Lachnit, Martina; Jorgensen, Erik M; Bastiani, Michael

2014-01-01

112

Axon Regeneration Genes Identified by RNAi Screening in C. elegans  

PubMed Central

Axons of the mammalian CNS lose the ability to regenerate soon after development due to both an inhibitory CNS environment and the loss of cell-intrinsic factors necessary for regeneration. The complex molecular events required for robust regeneration of mature neurons are not fully understood, particularly in vivo. To identify genes affecting axon regeneration in Caenorhabditis elegans, we performed both an RNAi-based screen for defective motor axon regeneration in unc-70/?-spectrin mutants and a candidate gene screen. From these screens, we identified at least 50 conserved genes with growth-promoting or growth-inhibiting functions. Through our analysis of mutants, we shed new light on certain aspects of regeneration, including the role of ?-spectrin and membrane dynamics, the antagonistic activity of MAP kinase signaling pathways, and the role of stress in promoting axon regeneration. Many gene candidates had not previously been associated with axon regeneration and implicate new pathways of interest for therapeutic intervention.

Nix, Paola; Hammarlund, Marc; Hauth, Linda; Lachnit, Martina; Jorgensen, Erik M.

2014-01-01

113

DCEG Scientists Identify New Gene Mutation Related to Familial Melanoma  

Cancer.gov

Scientists have identified a rare inherited mutation in a gene that can increase the risk of familial melanoma, according to a study that appeared online in Nature Genetics on March 30, 2014. Although the finding does not offer immediate benefit to patients, variation in the Protection of Telomeres-1 (POT1) gene provides additional clues as to the origins of melanoma and may open new avenues in prevention and treatment research. Read the full NCI Benchmarks blog post about this study.

114

The genetics of alcoholism: identifying specific genes through family studies.  

PubMed

Alcoholism is a complex disorder with both genetic and environmental risk factors. Studies in humans have begun to elucidate the genetic underpinnings of the risk for alcoholism. Here we briefly review strategies for identifying individual genes in which variations affect the risk for alcoholism and related phenotypes, in the context of one large study that has successfully identified such genes. The Collaborative Study on the Genetics of Alcoholism (COGA) is a family-based study that has collected detailed phenotypic data on individuals in families with multiple alcoholic members. A genome-wide linkage approach led to the identification of chromosomal regions containing genes that influenced alcoholism risk and related phenotypes. Subsequently, single nucleotide polymorphisms (SNPs) were genotyped in positional candidate genes located within the linked chromosomal regions, and analyzed for association with these phenotypes. Using this sequential approach, COGA has detected association with GABRA2, CHRM2 and ADH4; these associations have all been replicated by other researchers. COGA has detected association to additional genes including GABRG3, TAS2R16, SNCA, OPRK1 and PDYN, results that are awaiting confirmation. These successes demonstrate that genes contributing to the risk for alcoholism can be reliably identified using human subjects. PMID:16961766

Edenberg, Howard J; Foroud, Tatiana

2006-09-01

115

Using next-generation RNA sequencing to identify imprinted genes.  

PubMed

Genomic imprinting is manifested as differential allelic expression (DAE) depending on the parent-of-origin. The most direct way to identify imprinted genes is to directly score the DAE in a context where one can identify which parent transmitted each allele. Because many genes display DAE, simply scoring DAE in an individual is not sufficient to identify imprinted genes. In this paper, we outline many technical aspects of a scheme for identification of imprinted genes that makes use of RNA sequencing (RNA-seq) from tissues isolated from F1 offspring derived from the pair of reciprocal crosses. Ideally, the parental lines are from two inbred strains that are not closely related to each other. Aspects of tissue purity, RNA extraction, library preparation and bioinformatic inference of imprinting are all covered. These methods have already been applied in a number of organisms, and one of the most striking results is the evolutionary fluidity with which novel imprinted genes are gained and lost within genomes. The general methodology is also applicable to a wide range of other biological problems that require quantification of allele-specific expression using RNA-seq, such as cis-regulation of gene expression, X chromosome inactivation and random monoallelic expression. PMID:24619182

Wang, X; Clark, A G

2014-08-01

116

A two step method to identify clinical outcome relevant genes with microarray data.  

PubMed

With advances in microarray technology, many biomarkers selection approaches have been proposed for cancer diagnosis. Marker sets are selected by scoring genes for how well they can discriminate between different classes of diseases [1-4] or are ranked by significance analysis without reference to classification tasks. However there is a pressing need for methods integrating biological priori knowledge in the gene selection process. In this study, we proposed to identify genes primarily in terms of diagnostic outcome relevance. As gene expression is a combination effect, with the help of SVD, the microarray data is decomposed, the eigenvectors correspond to the biological effect of clinical outcomes are identified. Genes which play important roles in determining this biological effect are detected. Therefore, genes are essentially identified in terms of the strength of association with clinical outcomes and the relationship of genes and clinical outcomes is analyzed. Monte Carlo simulations are then used to fine tune the selected gene set in terms of classification accuracy. The approach was tested on four public data sets. Comparative studies show that the selected genes achieved higher classification accuracies. Graphical analysis visualizes that they have close relationship with the cancer class. Statistical simulation shows that the gene set found by the proposed method is also less variable and comparatively invariant to external influences. The biological relevance of the selected genes is further discussed and validated with the literature study and analysis of biological databases. PMID:21130182

Han, Bin; Li, Lihua; Chen, Yan; Zhu, Lei; Dai, Qi

2011-04-01

117

Novel methods to identify biologically relevant genes for leukemia and prostate cancer from gene expression profiles  

PubMed Central

Background High-throughput microarray experiments now permit researchers to screen thousands of genes simultaneously and determine the different expression levels of genes in normal or cancerous tissues. In this paper, we address the challenge of selecting a relevant and manageable subset of genes from a large microarray dataset. Currently, most gene selection methods focus on identifying a set of genes that can further improve classification accuracy. Few or none of these small sets of genes, however, are biologically relevant (i.e. supported by medical evidence). To deal with this critical issue, we propose two novel methods that can identify biologically relevant genes concerning cancers. Results In this paper, we propose two novel techniques, entitled random forest gene selection (RFGS) and support vector sampling technique (SVST). Compared with results from six other methods developed in this paper, we demonstrate experimentally that RFGS and SVST can identify more biologically relevant genes in patients with leukemia or prostate cancer. Among the top 25 genes selected using SVST method, 15 genes were biologically relevant genes in patients with leukemia and 13 genes were biologically relevant genes in patients with prostate cancer. Meanwhile, the RFGS method, while less effective than SVST, still identified an average of 9 biologically relevant genes in both leukemia and prostate cancers. In contrast to traditional statistical methods, which only identify less than 8 genes in patients with leukemia and less than 8 genes in patients with prostate cancer, our methods yield significantly better results. Conclusions Our proposed SVST and RFGS methods are novel approaches that can identify a greater number of biologically relevant genes. These methods have been successfully applied to both leukemia and prostate cancers. Research in the fields of biology and medicine should benefit from the identification of biologically relevant genes by confirming recent discoveries in cancer research or suggesting new avenues for exploration.

2010-01-01

118

Effect of gene polymorphisms on periodontal diseases  

PubMed Central

Periodontal diseases are inflammatory diseases of supporting structures of the tooth. It results in the destruction of the supporting structures and most of the destructive processes involved are host derived. The processes leading to destruction and regeneration of the destroyed tissues are of great interest to both researchers and clinicians. The selective susceptibility of subjects for periodontitis has remained an enigma and wide varieties of risk factors have been implicated for the manifestation and progression of periodontitis. Genetic factors have been a new addition to the list of risk factors for periodontal diseases. With the availability of human genome sequence and the knowledge of the complement of the genes, it should be possible to identify the metabolic pathways involved in periodontal destruction and regeneration. Most forms of periodontitis represent a life-long account of interactions between the genome, behaviour, and environment. The current practical utility of genetic knowledge in periodontitis is limited. The information contained within the human genome can potentially lead to a better understanding of the control mechanisms modulating the production of inflammatory mediators as well as provides potential therapeutic targets for periodontal disease. Allelic variants at multiple gene loci probably influence periodontitis susceptibility.

Tarannum, Fouzia; Faizuddin, Mohamed

2012-01-01

119

Gene therapy for neurodegenerative diseases based on lentiviral vectors.  

PubMed

Gene therapy approaches to treat inherited and acquired disorders offer many unique advantages over conventional therapeutic approaches. For neurodegenerative diseases, gene therapy is particularly attractive due to the restricted bioavailability of conventional therapeutic substances to the affected structures of the brain and progressive nature of these diseases. With the development of lentiviral vector systems, many issues have been addressed and new delivery routes to the nervous system have been identified. Lentiviral vectors can efficiently deliver genes to postmitotic neuronal cell types offering long-term expression, can be generated in high titers, and do not give immunological complications. Various animal studies have demonstrated the effectiveness of these vectors to deliver therapeutic genes into the nervous system, as well as to model human diseases. This chapter will describe the basic features of lentiviral vectors, the progress, and their applications as a therapeutic strategy to treat diseases such as amyotrophic lateral sclerosis, spinal muscular atrophy, Parkinson's disease, and Huntington's disease. PMID:19660657

Nanou, Aikaterini; Azzouz, Mimoun

2009-01-01

120

International team identifies critical genes mutated in stomach cancer  

Cancer.gov

An international team of scientists, led by researchers from the Duke-NUS Graduate Medical School in Singapore and National Cancer Centre of Singapore, has identified hundreds of novel genes that are mutated in stomach cancer, the second-most lethal cancer worldwide.

121

Gene identified that sensitizes cancer cells to chemotherapy drugs  

Cancer.gov

NCI scientists have found that a gene, Schlafen-11 (SLFN11), sensitizes cells to substances known to cause irreparable damage to DNA.  As part of their study, the researchers used a repository of 60 cell types to identify predictors of cancer cell response to classes of DNA damaging agents, widely used as chemotherapy treatments for many cancers.

122

Candidate Olfaction Genes Identified within the Helicoverpa armigera Antennal Transcriptome  

PubMed Central

Antennal olfaction is extremely important for insect survival, mediating key behaviors such as host preference, mate choice, and oviposition site selection. Multiple antennal proteins are involved in olfactory signal transduction pathways. Of these, odorant receptors (ORs) and ionotropic receptors (IRs) confer specificity on olfactory sensory neuron responses. In this study, we identified the olfactory gene repertoire of the economically important agricultural pest moth, Helicoverpa armigera, by assembling the adult male and female antennal transcriptomes. Within the male and female antennal transcriptomes we identified a total of 47 OR candidate genes containing 6 pheromone receptor candidates. Additionally, 12 IR genes as well as 26 odorant-binding proteins and 12 chemosensory proteins were annotated. Our results allow a systematic functional analysis across much of conventional ORs repertoire and newly reported IRs mediating the key olfaction-mediated behaviors of H. armigera.

Liu, Yang; Gu, Shaohua; Zhang, Yongjun; Guo, Yuyuan; Wang, Guirong

2012-01-01

123

Time course analysis of gene expression identifies multiple genes with differential expression in patients with in-stent restenosis  

PubMed Central

Background The vascular disease in-stent restenosis (ISR) is characterized by formation of neointima and adverse inward remodeling of the artery after injury by coronary stent implantation. We hypothesized that the analysis of gene expression in peripheral blood mononuclear cells (PBMCs) would demonstrate differences in transcript expression between individuals who develop ISR and those who do not. Methods and Results We determined and investigated PBMC gene expression of 358 patients undergoing an index procedure to treat in de novo coronary artery lesions with bare metallic stents, using a novel time-varying intercept model to optimally assess the time course of gene expression across a time course of blood samples. Validation analyses were conducted in an independent sample of 97 patients with similar time-course blood sampling and gene expression data. We identified 47 probesets with differential expression, of which 36 were validated upon independent replication testing. The genes identified have varied functions, including some related to cellular growth and metabolism, such as the NAB2 and LAMP genes. Conclusions In a study of patients undergoing bare metallic stent implantation, we have identified and replicated differential gene expression in peripheral blood mononuclear cells, studied across a time series of blood samples. The genes identified suggest alterations in cellular growth and metabolism pathways, and these results provide the basis for further specific functional hypothesis generation and testing of the mechanisms of ISR.

2011-01-01

124

KIAA1462, A Coronary Artery Disease Associated Gene, Is a Candidate Gene for Late Onset Alzheimer Disease in APOE Carriers  

PubMed Central

Alzheimer disease (AD) is a devastating neurodegenerative disease affecting more than five million Americans. In this study, we have used updated genetic linkage data from chromosome 10 in combination with expression data from serial analysis of gene expression to choose a new set of thirteen candidate genes for genetic analysis in late onset Alzheimer disease (LOAD). Results in this study identify the KIAA1462 locus as a candidate locus for LOAD in APOE4 carriers. Two genes exist at this locus, KIAA1462, a gene associated with coronary artery disease, and “rokimi”, encoding an untranslated spliced RNA The genetic architecture at this locus suggests that the gene product important in this association is either “rokimi”, or a different isoform of KIAA1462 than the isoform that is important in cardiovascular disease. Expression data suggests that isoform f of KIAA1462 is a more attractive candidate for association with LOAD in APOE4 carriers than “rokimi” which had no detectable expression in brain.

Murdock, Deborah G.; Bradford, Yuki; Schnetz-Boutaud, Nathalie; Mayo, Ping; Allen, Melissa J.; D'Aoust, Laura N.; Liang, Xueying; Mitchell, Sabrina L.; Zuchner, Stephan; Small, Gary W.; Gilbert, John R.; Pericak-Vance, Margaret A.; Haines, Jonathan L.

2013-01-01

125

Identifying lipid metabolism genes in pig liver after clenbuterol administration.  

PubMed

Clenbuterol is a repartition agent (beta 2-adrenoceptor agonist) that can decrease fat deposition and increase skeletal muscle growth at manageable dose. To better understand the molecular mechanism of Clenbuterol's action, GeneChips and real-time PCR were used to compare the gene expression profiles of liver tissue in pigs with/without administration of Clenbuterol. Metabolism effects and the global gene expression profiles of liver tissue from Clenbuterol-treated and untreated pigs were conducted. Function enrichment tests showed that the differentially expressed genes are enriched in glycoprotein protein, plasma membrane, fatty acid and amino acid metabolic process, and cell differentiation and signal transduction groups. Pathway mining analysis revealed that physiological pathways such as MAPK, cell adhesion molecules, and the insulin signaling pathway, were remarkably regulated when Clenbuterol was administered. Gene prioritization algorithm was used to associate a number of important differentially expressed genes with lipid metabolism in response to Clenbuterol. Genes identified as differentially expressed in this study will be candidates for further investigation of the molecular mechanisms involved in Clenbuterol's effects on adipose and skeletal muscle tissue. PMID:22652664

Liu, Qiuyue; Zhang, Jin; Guo, Wei; Zhao, Yiqiang; Hu, Xiaoxiang; Li, Ning

2012-01-01

126

Patient Identified Disease Burden in Facioscapulohumeral Muscular Dystrophy  

PubMed Central

Introduction The multitude of symptoms associated with facioscapulohumeral muscular dystrophy (FSHD) disease burden are of varying importance. The extent of these symptoms and their cumulative effect on the FSHD population is unknown. Methods We conducted interviews with adult FSHD patients to identify which symptoms have the greatest effect on their lives. Each interview was recorded, transcribed, coded, and analyzed using a qualitative framework technique, triangulation, and 3-investigator consensus approach. Results 1375 quotes were obtained through 20 patient interviews. 251 symptoms of importance were identified representing 14 themes of FSHD disease burden. Symptoms associated with mobility impairment, activity limitation, and social role limitation were most frequently mentioned by participants. Conclusions There are multiple themes and symptoms, some previously under-recognized, that play a key role in FSHD disease burden.

Johnson, Nicholas E; Quinn, Christine; Eastwood, Eileen; Tawil, Rabi; Heatwole, Chad R

2013-01-01

127

Polycystic kidney disease - where gene dosage counts  

PubMed Central

Gene dosage effects have emerged as playing a central role in the pathogenesis of polycystic kidney disease. Yet, how gene dosage can ultimately have an impact on the formation of kidney cysts remains unknown. In this commentary we review the evidence for the role of gene dosage effects versus the “2-hit” mutation model in polycystic kidney disease (PKD), and also discuss how gene networks may potentially make intertwined contributions to PKD.

Stayner, Cherie A.

2014-01-01

128

Prioritizing genes of potential relevance to diseases affected by sex hormones: an example of Myasthenia Gravis  

Microsoft Academic Search

BACKGROUND: About 5% of western populations are afflicted by autoimmune diseases many of which are affected by sex hormones. Autoimmune diseases are complex and involve many genes. Identifying these disease-associated genes contributes to development of more effective therapies. Also, association studies frequently imply genomic regions that contain disease-associated genes but fall short of pinpointing these genes. The identification of disease-associated

Mandeep Kaur; Sebastian Schmeier; Cameron R MacPherson; Oliver Hofmann; Winston A Hide; Stephen Taylor; Nick Willcox; Vladimir B Bajic

2008-01-01

129

Genes, Environment, Health, and Disease: Facing up to Complexity  

Microsoft Academic Search

The deciphering of the human genome sequence, the DNA instruction book that makes us not only uniquely human but also unique as individuals, has provided unparalleled opportunities for identifying the relationship of genetic variation to health and disease. Yet as we move from single-gene diseases, in which a single misspelled base-pair can lead to such devastating conditions as sickle cell

Teri A. Manolio; Francis S. Collins

2007-01-01

130

Gene Regulatory Networks Elucidating Huanglongbing Disease Mechanisms  

PubMed Central

Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas), especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young and mature leaves. Four categories of orchard trees were studied: symptomatic, asymptomatic, apparently healthy, and healthy. Principal component analysis found distinct expression patterns between immature and mature fruits and leaf samples for all four categories of trees. A predicted protein – protein interaction network identified HLB-regulated genes for sugar transporters playing key roles in the overall plant responses. Gene set and pathway enrichment analyses highlight the role of sucrose and starch metabolism in disease symptom development in all tissues. HLB-regulated genes (glucose-phosphate-transporter, invertase, starch-related genes) would likely determine the source-sink relationship disruption. In infected leaves, transcriptomic changes were observed for light reactions genes (downregulation), sucrose metabolism (upregulation), and starch biosynthesis (upregulation). In parallel, symptomatic fruits over-expressed genes involved in photosynthesis, sucrose and raffinose metabolism, and downregulated starch biosynthesis. We visualized gene networks between tissues inducing a source-sink shift. CaLas alters the hormone crosstalk, resulting in weak and ineffective tissue-specific plant immune responses necessary for bacterial clearance. Accordingly, expression of WRKYs (including WRKY70) was higher in fruits than in leaves. Systemic acquired responses were inadequately activated in young leaves, generally considered the sites where most new infections occur.

Martinelli, Federico; Reagan, Russell L.; Uratsu, Sandra L.; Phu, My L.; Albrecht, Ute; Zhao, Weixiang; Davis, Cristina E.; Bowman, Kim D.; Dandekar, Abhaya M.

2013-01-01

131

Gene regulatory networks elucidating huanglongbing disease mechanisms.  

PubMed

Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas), especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young and mature leaves. Four categories of orchard trees were studied: symptomatic, asymptomatic, apparently healthy, and healthy. Principal component analysis found distinct expression patterns between immature and mature fruits and leaf samples for all four categories of trees. A predicted protein - protein interaction network identified HLB-regulated genes for sugar transporters playing key roles in the overall plant responses. Gene set and pathway enrichment analyses highlight the role of sucrose and starch metabolism in disease symptom development in all tissues. HLB-regulated genes (glucose-phosphate-transporter, invertase, starch-related genes) would likely determine the source-sink relationship disruption. In infected leaves, transcriptomic changes were observed for light reactions genes (downregulation), sucrose metabolism (upregulation), and starch biosynthesis (upregulation). In parallel, symptomatic fruits over-expressed genes involved in photosynthesis, sucrose and raffinose metabolism, and downregulated starch biosynthesis. We visualized gene networks between tissues inducing a source-sink shift. CaLas alters the hormone crosstalk, resulting in weak and ineffective tissue-specific plant immune responses necessary for bacterial clearance. Accordingly, expression of WRKYs (including WRKY70) was higher in fruits than in leaves. Systemic acquired responses were inadequately activated in young leaves, generally considered the sites where most new infections occur. PMID:24086326

Martinelli, Federico; Reagan, Russell L; Uratsu, Sandra L; Phu, My L; Albrecht, Ute; Zhao, Weixiang; Davis, Cristina E; Bowman, Kim D; Dandekar, Abhaya M

2013-01-01

132

[Gene therapy of neurological diseases].  

PubMed

In hereditary neurological diseases, gene transfer into neurons is made difficult by: the nature of the cells (postmitotic cells, that cannot be cultured, genetically modified ex vivo, then retransplanted), sometimes, their widespread localization, the blood-brain barrier. However, three viral vectors derived from adenovirus, Herpes simplex virus and adeno-associated virus have been shown to be very efficient in transferring DNA into brain cells. All of these vectors can infect resting cells, especially neurons, and are efficient in vivo. Retroviral vectors which can infect dividing cells only are mainly used for ex vivo genetic modification of cells (neural progenitor cells, myoblasts, fibroblasts) followed by intracerebral transplantation. Alternatively, genetically modified cells can be transplanted in a peripheral site if the transgene product is able to cross the blood-brain barrier or to be transported retrogradely from the nerve terminals. We have especially investigated the potential interest of adenoviral vectors to transfer foreign genes into brain cells and to treat animal models of neurological diseases. These vectors allowed us to transfer the lacZ gene into any neural cell type, including neurons, glia, photoreceptors and olfactory receptors, ex vivo, in cell culture, and in vivo, by stereotactic administration. In addition, axonal transport of adenoviral vectors has been demonstrated, e.g. in the substantia nigra after injection into the striatum, in the olfactory bulb after intranasal instillation and in spinal motor neurons after intramuscular injection. After intracerebroventricular injection, ependymal cells are massively infected and express the transgene for several months, as this is also observed in neurons. Through the spinal canal and cerebrospinal fluid, the vector can diffuse to a considerable distance from the injection point, e.g. to the lumbar spinal cord after injection in the suboccipital region. To test the biological function of transgenes transferred through adenoviral vectors, we have constructed vectors with cDNAs or genes for various neutrophic factors: CNTF, NT3, BDNF and GDNF. These vectors were biologically active on target cells, ex vivo and in vivo. In the pmn mouse model of progressive motor neuronal degeneration, some of these vectors, alone or combined, allowed for prolongation of life of homozygous animals by more than two fold, and for decrease in the demyelination of phrenic nerve axons. Finally, we have also constructed an adenoviral vector carrying the alpha-hexosaminidase cDNA, encoding the enzyme subunit deficient in Tay Sachs patients. This vector permitted to normalize ganglioside metabolism in Tay Sachs fibroblasts and is currently tested in knock out mice deficient in hexosaminidase A. In spite of all these encouraging results, we are nevertheless aware that progress in vector design and delivery strategies will be needed before gene therapy can become a realistic therapeutical strategy in humans. PMID:8881264

Kahn, A; Haase, G; Akli, S; Guidotti, J E

1996-01-01

133

Gene-Environment Interactions in Human Disease: Nuisance or Opportunity?  

PubMed Central

Many environmental risk factors for common, complex human diseases have been revealed by epidemiologic studies, but how genotypes at specific loci modulate individual responses to environmental risk factors is largely unknown. Gene-environment interactions will be missed in genome-wide association studies and may account for some of the ‘missing heritability’ for these diseases. In this review, we focus on asthma as a model disease for studying gene-environment interactions because of relatively large numbers of candidate gene-environment interactions with asthma risk in the literature. Identifying these interactions using genome-wide approaches poses formidable methodological problems and elucidating molecular mechanisms for these interactions has been challenging. We suggest that studying gene-environment interactions in animal models, while more tractable, is not likely to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene-environment interactions.

Ober, Carole; Vercelli, Donata

2010-01-01

134

Beryllium Lymphocyte Proliferation Test Surveillance Identifies Clinically Significant Beryllium Disease  

PubMed Central

Background Workplace surveillance identifies chronic beryllium disease (CBD) but it remains unknown over what time frame mild CBD will progress to a more severe form. Methods We examined physiology and treatment in 229 beryllium sensitization (BeS) and 171 CBD surveillance-identified cases diagnosed from 1982 to 2002. Never smoking CBD cases (81) were compared to never smoking BeS patients (83) to assess disease progression. We compared CBD machinists to non-machinists to examine effects of exposure. Results At baseline, CBD and BeS cases did not differ significantly in exposure time or physiology. CBD patients were more likely to have machined beryllium. Of CBD cases, 19.3% went on to require oral immunosuppressive therapy. At 30 years from first exposure, measures of gas exchange were significantly worse and total lung capacity was lower for CBD subjects. Machinists had faster disease progression as measured by pulmonary function testing and gas exchange. Conclusions Medical surveillance for CBD identifies individuals at significant risk of disease progression and impairment with sufficient time since first exposure.

Mroz, Margaret M.; Maier, Lisa A.; Strand, Matthew; Silviera, Lori; Newman, Lee S.

2011-01-01

135

Positive-unlabeled learning for disease gene identification  

PubMed Central

Background: Identifying disease genes from human genome is an important but challenging task in biomedical research. Machine learning methods can be applied to discover new disease genes based on the known ones. Existing machine learning methods typically use the known disease genes as the positive training set P and the unknown genes as the negative training set N (non-disease gene set does not exist) to build classifiers to identify new disease genes from the unknown genes. However, such kind of classifiers is actually built from a noisy negative set N as there can be unknown disease genes in N itself. As a result, the classifiers do not perform as well as they could be. Result: Instead of treating the unknown genes as negative examples in N, we treat them as an unlabeled set U. We design a novel positive-unlabeled (PU) learning algorithm PUDI (PU learning for disease gene identification) to build a classifier using P and U. We first partition U into four sets, namely, reliable negative set RN, likely positive set LP, likely negative set LN and weak negative set WN. The weighted support vector machines are then used to build a multi-level classifier based on the four training sets and positive training set P to identify disease genes. Our experimental results demonstrate that our proposed PUDI algorithm outperformed the existing methods significantly. Conclusion: The proposed PUDI algorithm is able to identify disease genes more accurately by treating the unknown data more appropriately as unlabeled set U instead of negative set N. Given that many machine learning problems in biomedical research do involve positive and unlabeled data instead of negative data, it is possible that the machine learning methods for these problems can be further improved by adopting PU learning methods, as we have done here for disease gene identification. Availability and implementation: The executable program and data are available at http://www1.i2r.a-star.edu.sg/?xlli/PUDI/PUDI.html. Contact: xlli@i2r.a-star.edu.sg or yang0293@e.ntu.edu.sg Supplementary information: Supplementary Data are available at Bioinformatics online.

Yang, Peng; Li, Xiao-Li; Mei, Jian-Ping; Kwoh, Chee-Keong; Ng, See-Kiong

2012-01-01

136

Identifying a series of candidate genes for mania and psychosis: a convergent functional genomics approach.  

PubMed

We have used methamphetamine treatment of rats as an animal model for psychotic mania. Specific brain regions were analyzed comprehensively for changes in gene expression using oligonucleotide GeneChip microarrays. The data was cross-matched against human genomic loci associated with either bipolar disorder or schizophrenia. Using this convergent approach, we have identified several novel candidate genes (e.g., signal transduction molecules, transcription factors, metabolic enzymes) that may be involved in the pathogenesis of mood disorders and psychosis. Furthermore, for one of these genes, G protein-coupled receptor kinase 3 (GRK3), we found by Western blot analysis evidence for decreased protein levels in a subset of patient lymphoblastoid cell lines that correlated with disease severity. Finally, the classification of these candidate genes into two prototypical categories, psychogenes and psychosis-suppressor genes, is described. PMID:11074017

Niculescu, A B; Segal, D S; Kuczenski, R; Barrett, T; Hauger, R L; Kelsoe, J R

2000-11-01

137

Phage cluster relationships identified through single gene analysis  

PubMed Central

Background Phylogenetic comparison of bacteriophages requires whole genome approaches such as dotplot analysis, genome pairwise maps, and gene content analysis. Currently mycobacteriophages, a highly studied phage group, are categorized into related clusters based on the comparative analysis of whole genome sequences. With the recent explosion of phage isolation, a simple method for phage cluster prediction would facilitate analysis of crude or complex samples without whole genome isolation and sequencing. The hypothesis of this study was that mycobacteriophage-cluster prediction is possible using comparison of a single, ubiquitous, semi-conserved gene. Tape Measure Protein (TMP) was selected to test the hypothesis because it is typically the longest gene in mycobacteriophage genomes and because regions within the TMP gene are conserved. Results A single gene, TMP, identified the known Mycobacteriophage clusters and subclusters using a Gepard dotplot comparison or a phylogenetic tree constructed from global alignment and maximum likelihood comparisons. Gepard analysis of 247 mycobacteriophage TMP sequences appropriately recovered 98.8% of the subcluster assignments that were made by whole-genome comparison. Subcluster-specific primers within TMP allow for PCR determination of the mycobacteriophage subcluster from DNA samples. Using the single-gene comparison approach for siphovirus coliphages, phage groupings by TMP comparison reflected relationships observed in a whole genome dotplot comparison and confirm the potential utility of this approach to another widely studied group of phages. Conclusions TMP sequence comparison and PCR results support the hypothesis that a single gene can be used for distinguishing phage cluster and subcluster assignments. TMP single-gene analysis can quickly and accurately aid in mycobacteriophage classification.

2013-01-01

138

Network biology approach for identifying key regulatory genes by expression based study of breast cancer  

PubMed Central

The use of high-throughput array technology is omnipresent in diverse areas specifically, early diagnosis of disease, discovery of infectious agents, search for biological markers and screening of potential drug candidates. Here, we integrated gene expression data with the network-based approach to identify novel genes that were playing central role in the network through interconnecting to a number of differentially expressed breast cancer genes. The 62 cancerous genes retrieved from the Breast Cancer Gene Database (BCGD) were mapped in the normalized data accessed from Stanford Microarray Database (SMD) to analyze their pattern. Interaction networks for each gene were constructed to understand the biology of the metastasis at systems level. The individual networks were fused together for the detection of interacting hubs, 38 novel genes were found to be deeply intermingled with the central hub node. Gene Ontology studies were made to depict the biology of the hub nodes not alone through gene ranking but by applying the Hyper geometric test with the Benjamini Hochberg False Discovery Rate (FDR) correction method at a significance level of 0.05. Analyzing p-values from the statistical test indicated that most of the novel genes were involved in the same biological function as the disordered genes like signal transducer, transcription regulator, enzyme binding, molecular transducer and receptor signaling protein activity and same pathway as MAPK signaling, Apoptosis, Wnt Signaling, ErbB signaling and Cell Cycle. Lastly, we identified 3 novel genes CHUK, INSR and CREBBP showing high connections with the 12 novel genes reported in literatures as well with the perturbed genes. As a result, these genes can be considered as significant finding in revealing the basis and pathways responsible for breast cancer.

Chand, Yamini; Alam, Md Afroz

2012-01-01

139

Genomics meets proteomics: identifying the culprits in disease.  

PubMed

Genome-wide association studies (GWAS) revealed genomic risk loci that potentially have an impact on disease and phenotypic traits. This extensive resource holds great promise in providing novel directions for personalized medicine, including disease risk prediction, prevention and targeted medication. One of the major challenges that researchers face on the path between the initial identification of an association and precision treatment of patients is the comprehension of the biological mechanisms that underlie these associations. Currently, the focus to solve these questions lies on the integrative analysis of system-wide data on global genome variation, gene expression, transcription factor binding, epigenetic profiles and chromatin conformation. The generation of this data mainly relies on next-generation sequencing. However, due to multiple recent developments, mass spectrometry-based proteomics now offers additional, by the GWAS field so far hardly recognized possibilities for the identification of functional genome variants and, in particular, for the identification and characterization of (differentially) bound protein complexes as well as physiological target genes. In this review, we introduce these proteomics advances and suggest how they might be integrated in post-GWAS workflows. We argue that the combination of highly complementary techniques is powerful and can provide an unbiased, detailed picture of GWAS loci and their mechanistic involvement in disease. PMID:24135908

Stunnenberg, Hendrik G; Hubner, Nina C

2014-06-01

140

Animal Models of GWAS-Identified Type 2 Diabetes Genes  

PubMed Central

More than 65 loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D). Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notably TCF7L2 and ZnT8/SLC30A8, have to date been examined in mouse models. We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics.

da Silva Xavier, Gabriela; Bellomo, Elisa A.; McGinty, James A.; French, Paul M.; Rutter, Guy A.

2013-01-01

141

Genes Necessary for Bacterial Magnetite Biomineralization Identified by Transposon Mutagenesis  

NASA Astrophysics Data System (ADS)

Magnetic bacteria synthesize nanoscale crystals of magnetite in intracellular, membrane-bounded organelles (magnetosomes). These crystals are preserved in the fossil record at least as far back as the late Neoproterozoic and have been tentatively identified in much older rocks (1). This fossil record may provide deep time calibration points for molecular evolution studies once the genes involved in biologically controlled magnetic mineralization (BCMM) are known. Further, a genetic and biochemical understanding of BCMM will give insight into the depositional environment and biogeochemical cycles in which magnetic bacteria play a role. The BCMM process is not well understood, though proteins have been identified from the magnetosome membrane and genetic manipulation and biochemical characterization of these proteins are underway. Most of the proteins currently thought to be involved are encoded within the mam cluster, a large cluster of genes whose products localize to the magnetosome membrane and are conserved among magnetic bacteria (2). In an effort to identify all of the genes necessary for bacterial BCMM, we undertook a transposon mutagenesis of Magnetospirillum magneticum AMB-1. Non-magnetic mutants (MNMs) were identified by growth in liquid culture followed by a magnetic assay. The insertion site of the transposon was identified two ways. First MNMs were screened with a PCR assay to determine if the transposon had inserted into the mam cluster. Second, the transposon was rescued from the mutant DNA and cloned for sequencing. The majority insertion sites are located within the mam cluster. Insertion sites also occur in operons which have not previously been suspected to be involved in magnetite biomineralization. None of the insertion sites have occurred within genes reported from previous transposon mutagenesis studies of AMB-1 (3, 4). Two of the non-mam cluster insertion sites occur in operons containing genes conserved particularly between MS-1 and MC-1. We are undertaking a complementation strategy to demonstrate the necessity of these novel genes in BCMM as well as characterizing the phenotypes of the mutants. 1. S. B. R. Chang, J. F. Stolz, J. L. Kirschvink, S. M. Awramik, Precambrian Res. 43, 305-315 (1989). 2. K. Grünberg, C. Wawer, B. M. Tebo, D. Schüler, Appl. Environ. Microbiol. 67, 4573-4582 (2001). 3. A. T. Wahyudi, H. Takeyama, T. Matsunaga, Appl. Biochem. Biotechnol. 91-3, 147-154 (2001). 4. T. Matsunaga, C. Nakamura, J. G. Burgess, K. Sode, J. Bacteriol. 174, 2748-2753 (1992).

Nash, C. Z.; Komeili, A.; Newman, D. K.; Kirschvink, J. L.

2004-12-01

142

Candidate Gene for the Chromosome 1 Familial Alzheimer's Disease Locus  

Microsoft Academic Search

A candidate gene for the chromosome 1 Alzheimer's disease (AD) locus was identified (STM2). The predicted amino acid sequence for STM2 is homologous to that of the recently cloned chromosome 14 AD gene (S182). A point mutation in STM2, resulting in the substitution of an isoleucine for an asparagine (N141l), was identified in affected people from Volga German AD kindreds.

Ephrat Levy-Lahad; Wilma Wasco; Parvoneh Poorkaj; Donna M. Romano; Junko Oshima; Warren H. Pettingell; Chang-En Yu; Paul D. Jondro; Stephen D. Schmidt; Kai Wang; Annette C. Crowley; Ying-Hui Fu; Suzanne Y. Guenette; David Galas; Ellen Nemens; Ellen M. Wijsman; Thomas D. Bird; Gerard D. Schellenberg; Rudolph E. Tanzi

1995-01-01

143

DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics  

PubMed Central

Background De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes. Methods To accelerate the search for ASD genes, we developed a novel algorithm, DAWN, to model two kinds of data: rare variations from exome sequencing and gene co-expression in the mid-fetal prefrontal and motor-somatosensory neocortex, a critical nexus for risk. The algorithm casts the ensemble data as a hidden Markov random field in which the graph structure is determined by gene co-expression and it combines these interrelationships with node-specific observations, namely gene identity, expression, genetic data and the estimated effect on risk. Results Using currently available genetic data and a specific developmental time period for gene co-expression, DAWN identified 127 genes that plausibly affect risk, and a set of likely ASD subnetworks. Validation experiments making use of published targeted resequencing results demonstrate its efficacy in reliably predicting ASD genes. DAWN also successfully predicts known ASD genes, not included in the genetic data used to create the model. Conclusions Validation studies demonstrate that DAWN is effective in predicting ASD genes and subnetworks by leveraging genetic and gene expression data. The findings reported here implicate neurite extension and neuronal arborization as risks for ASD. Using DAWN on emerging ASD sequence data and gene expression data from other brain regions and tissues would likely identify novel ASD genes. DAWN can also be used for other complex disorders to identify genes and subnetworks in those disorders.

2014-01-01

144

Identifying genes underlying skin pigmentation differences among human populations  

Microsoft Academic Search

Skin pigmentation is a human phenotype that varies greatly among human populations and it has long been speculated that this\\u000a variation is adaptive. We therefore expect the genes that contribute to these large differences in phenotype to show large\\u000a allele frequency differences among populations and to possibly harbor signatures of positive selection. To identify the loci\\u000a that likely contribute to

Sean Myles; Mehmet Somel; Kun Tang; Janet Kelso; Mark Stoneking

2007-01-01

145

Harnessing genomics to identify environmental determinants of heritable disease  

PubMed Central

Next-generation sequencing technologies can now be used to directly measure heritable de novo DNA sequence mutations in humans. However, these techniques have not been used to examine environmental factors that induce such mutations and their associated diseases. To address this issue, a working group on environmentally induced germline mutation analysis (ENIGMA) met in October 2011 to propose the necessary foundational studies, which include sequencing of parent–offspring trios from highly exposed human populations, and controlled dose–response experiments in animals. These studies will establish background levels of variability in germline mutation rates and identify environmental agents that influence these rates and heritable disease. Guidance for the types of exposures to examine come from rodent studies that have identified agents such as cancer chemotherapeutic drugs, ionizing radiation, cigarette smoke, and air pollution as germ-cell mutagens. Research is urgently needed to establish the health consequences of parental exposures on subsequent generations.

Yauk, Carole Lyn; Argueso, J. Lucas; Auerbach, Scott S.; Awadalla, Philip; Davis, Sean R.; DeMarini, David M.; Douglas, George R.; Dubrova, Yuri E.; Elespuru, Rosalie K.; Glover, Thomas W.; Hales, Barbara F.; Hurles, Matthew E.; Klein, Catherine B.; Lupski, James R.; Manchester, David K.; Marchetti, Francesco; Montpetit, Alexandre; Mulvihill, John J.; Robaire, Bernard; Robbins, Wendie A.; Rouleau, Guy A.; Shaughnessy, Daniel T.; Somers, Christopher M.; Taylor, James G.; Trasler, Jacquetta; Waters, Michael D.; Wilson, Thomas E.; Witt, Kristine L.; Bishop, Jack B.

2012-01-01

146

Computational disease gene prioritization: an appraisal.  

PubMed

Abstract Bioinformatics aids in the understanding of the biological processes of living beings and the genetic architecture of human diseases. The discovery of disease-related genes improves the diagnosis and therapy design for the disease. To save the cost and time involved in the experimental verification of the candidate genes, computational methods are employed for ranking the genes according to their likelihood of being associated with the disease. Only top-ranked genes are then verified experimentally. A variety of methods have been conceived by the researchers for the prioritization of the disease candidate genes, which differ in the data source being used or the scoring function used for ranking the genes. A review of various aspects of computational disease gene prioritization and its research issues is presented in this article. The aspects covered are gene prioritization process, data sources used, types of prioritization methods, and performance assessment methods. This article provides a brief overview and acts as a quick guide for disease gene prioritization. PMID:24665902

Gill, Nivit; Singh, Shailendra; Aseri, Trilok C

2014-06-01

147

Whole Exome Sequencing Identifies Novel Recurrently Mutated Genes in Patients with Splenic Marginal Zone Lymphoma  

PubMed Central

The pathogenesis of splenic marginal zone lymphoma (SMZL) remains largely unknown. Recent high-throughput sequencing studies have identified recurrent mutations in key pathways, most notably NOTCH2 mutations in >25% of patients. These studies are based on small, heterogeneous discovery cohorts, and therefore only captured a fraction of the lesions present in the SMZL genome. To identify further novel pathogenic mutations within related biochemical pathways, we applied whole exome sequencing (WES) and copy number (CN) analysis to a biologically and clinically homogeneous cohort of seven SMZL patients with 7q abnormalities and IGHV1-2*04 gene usage. We identified 173 somatic non-silent variants, affecting 160 distinct genes. In additional to providing independent validation of the presence of mutation in several previously reported genes (NOTCH2, TNFAIP3, MAP3K14, MLL2 and SPEN), our study defined eight additional recurrently mutated genes in SMZL; these genes are CREBBP, CBFA2T3, AMOTL1, FAT4, FBXO11, PLA2G4D, TRRAP and USH2A. By integrating our WES and CN data we identified three mutated putative candidate genes targeted by 7q deletions (CUL1, EZH2 and FLNC), with FLNC positioned within the well-characterized 7q minimally deleted region. Taken together, this work expands the reported directory of recurrently mutated cancer genes in this disease, thereby expanding our understanding of SMZL pathogenesis. Ultimately, this work will help to establish a stratified approach to care including the possibility of targeted therapy.

Ennis, Sarah; Walewska, Renata; Forster, Jade; Parker, Helen; Davis, Zadie; Gardiner, Anne; Collins, Andrew; Oscier, David G.; Strefford, Jonathan C.

2013-01-01

148

Global methylation analysis identifies prognostically important epigenetically inactivated tumor suppressor genes in multiple myeloma  

PubMed Central

Outcome in multiple myeloma is highly variable and a better understanding of the factors that influence disease biology is essential to understand and predict behavior in individual patients. In the present study, we analyzed combined genomewide DNA methylation and gene expression data of patients treated in the Medical Research Council Myeloma IX trial. We used these data to identify epigenetically repressed tumor suppressor genes with prognostic relevance in myeloma. We identified 195 genes with changes in methylation status that were significantly associated with prognosis. Combining DNA methylation and gene expression data led to the identification of the epigenetically regulated tumor modulating genes GPX3, RBP1, SPARC, and TGFBI. Hypermethylation of these genes was associated with significantly shorter overall survival, independent of age, International Staging System score, and adverse cytogenetics. The 4 differentially methylated and expressed genes are known to mediate important tumor suppressive functions including response to chemotherapy (TGFBI), interaction with the microenvironment (SPARC), retinoic acid signaling (RBP1), and the response to oxidative stress (GPX3), which could explain the prognostic impact of their differential methylation. Assessment of the DNA methylation status of the identified genes could contribute to the molecular characterization of myeloma, which is prerequisite for an individualized treatment approach.

Kaiser, Martin F.; Johnson, David C.; Wu, Ping; Walker, Brian A.; Brioli, Annamaria; Mirabella, Fabio; Wardell, Christopher P.; Melchor, Lorenzo; Davies, Faith E.

2013-01-01

149

Global methylation analysis identifies prognostically important epigenetically inactivated tumor suppressor genes in multiple myeloma.  

PubMed

Outcome in multiple myeloma is highly variable and a better understanding of the factors that influence disease biology is essential to understand and predict behavior in individual patients. In the present study, we analyzed combined genomewide DNA methylation and gene expression data of patients treated in the Medical Research Council Myeloma IX trial. We used these data to identify epigenetically repressed tumor suppressor genes with prognostic relevance in myeloma. We identified 195 genes with changes in methylation status that were significantly associated with prognosis. Combining DNA methylation and gene expression data led to the identification of the epigenetically regulated tumor modulating genes GPX3, RBP1, SPARC, and TGFBI. Hypermethylation of these genes was associated with significantly shorter overall survival, independent of age, International Staging System score, and adverse cytogenetics. The 4 differentially methylated and expressed genes are known to mediate important tumor suppressive functions including response to chemotherapy (TGFBI), interaction with the microenvironment (SPARC), retinoic acid signaling (RBP1), and the response to oxidative stress (GPX3), which could explain the prognostic impact of their differential methylation. Assessment of the DNA methylation status of the identified genes could contribute to the molecular characterization of myeloma, which is prerequisite for an individualized treatment approach. PMID:23699600

Kaiser, Martin F; Johnson, David C; Wu, Ping; Walker, Brian A; Brioli, Annamaria; Mirabella, Fabio; Wardell, Christopher P; Melchor, Lorenzo; Davies, Faith E; Morgan, Gareth J

2013-07-11

150

Translatome analysis of CHO cells to identify key growth genes.  

PubMed

We report the first investigation of translational efficiency on a global scale, also known as translatome, of a Chinese hamster ovary (CHO) DG44 cell line producing monoclonal antibodies (mAb). The translatome data was generated via combined use of high resolution and streamlined polysome profiling technology and proprietary Nimblegen microarrays probing for more than 13K annotated CHO-specific genes. The distribution of ribosome loading during the exponential growth phase revealed the translational activity corresponding to the maximal growth rate, thus allowing us to identify stably and highly translated genes encoding heterogeneous nuclear ribonucleoproteins (Hnrnpc and Hnrnpa2b1), protein regulator of cytokinesis 1 (Prc1), glucose-6-phosphate dehydrogenase (G6pdh), UTP6 small subunit processome (Utp6) and RuvB-like protein 1 (Ruvbl1) as potential key players for cellular growth. Moreover, correlation analysis between transcriptome and translatome data sets showed that transcript level and translation efficiency were uncoupled for 95% of investigated genes, suggesting the implication of translational control mechanisms such as the mTOR pathway. Thus, the current translatome analysis platform offers new insights into gene expression in CHO cell cultures by bridging the gap between transcriptome and proteome data, which will enable researchers of the bioprocessing field to prioritize in high-potential candidate genes and to devise optimal strategies for cell engineering toward improving culture performance. PMID:23876478

Courtes, Franck C; Lin, Joyce; Lim, Hsueh Lee; Ng, Sze Wai; Wong, Niki S C; Koh, Geoffrey; Vardy, Leah; Yap, Miranda G S; Loo, Bernard; Lee, Dong-Yup

2013-09-10

151

How to identify the genetic basis of gastrointestinal and liver diseases?  

PubMed Central

New insights into the genetic basis of disease are being generated at an ever increasing rate. This explosion of information was ignited by technological advances, such as the polymerase chain reaction and automated DNA sequencing. Although its promise is great, the integration of genetics into the everyday practice of medicine remains challenging. This review discusses the application of molecular genetics in general with a specific focus on hereditary diseases of the digestive organs. The application of molecular genetics in everyday clinical routine is hampered by the difficult interpretation of test results. These difficulties include the prediction of disease penetrance, the presence of multiple mutations of a particular gene with varying functional consequences, and the importance of exogenous factors modulating disease expression. To date, the most significant impact of genetics has been to increase our understanding of disease aetiology and pathogenesis and to reliably identify siblings of affected patients with the risk to develop symptomatic disease.

Ferenci, P

2003-01-01

152

Integration of text- and data-mining using ontologies successfully selects disease gene candidates  

Microsoft Academic Search

Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause dis- eases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant

Nicki Tiffin; Janet F. Kelso; Alan R. Powell; Hong Pan; Vladimir B. Bajic; Winston A. Hide

2005-01-01

153

Gene Therapy for Chronic Granulomatous Disease  

Microsoft Academic Search

Identification of gene mutations responsible for leukocyte dysfunction along with the application of gene transfer technology has made genetic correction of such disorders possible. Much of the research into molecular therapy for inherited disorders of phagocytes has been focused on chronic granulomatous disease (CGD). CGD results from mutations in any one of the four genes encoding essential subunits of respiratory

W. Scott Goebel; Mary C. Dinauer

2003-01-01

154

Gene therapy for childhood immunological diseases  

Microsoft Academic Search

Gene therapy using autologous hematopoietic stem cells (HSC) that are corrected with the normal gene may have a beneficial effect on blood cell production or function, without the immunologic complications of allogeneic HSC transplantation. Childhood immunological diseases are highly favorable candidates for responses to gene therapy using HSC. Hemoglobinopathies, lysosomal and metabolic disorders and defects of hematopoietic stem and progenitor

D B Kohn

2008-01-01

155

Identifying gene expression profile of spinal cord injury in rat by bioinformatics strategy.  

PubMed

Spinal cord injury (SCI) leads to the loss of sensory, motor, and autonomic function. We aimed to identify the therapeutic targets of-SCI by bioinformatics analysis. The gene expression profile of GSE20907 was downloaded from gene expression omnibus database. By comparing gene expression profiles with control samples, we screened out several differentially expressed genes (DEGs) in 3 days, 2 weeks and 1 month post-SCI. The pathway enrichment and protein-protein interaction (PPI) network analysis for the identified DEGs were performed. Then, transcription factors and microRNAs for DEGs were predicted. We found that up-regulated DEGs mainly participated in cell cycle, oxidative phosphorylation and immune-related pathways; while down-regulated DEGs were mainly involved in oxidative phosphorylation and central nervous system disease signaling pathways. In the constructed PPI network, Bub1, Vascular endothelial growth factor, Topoisomerase II? (TOP2a) and Cdc20 showed better correspondence with cell cycle, repair system and nerve system. Furthermore, the up-regulated genes (Arpc1b, CD74 and Brd2) significantly mapped to the target genes of transcription factors. The down-regulated genes of 3 days post-injury and the up-regulated genes of 2 weeks post-injury were significantly enriched as the target genes of microRNAs (miR-129 and miR-124). In conclusion, our results may provide guidelines to discuss the collaboration of PPI network in carcinogenesis of SCI. PMID:24595446

Jin, Lingjing; Wu, Zhourui; Xu, Wei; Hu, Xiao; Zhang, Jin; Xue, Zhigang; Cheng, Liming

2014-05-01

156

Identification of gene interactions associated with disease from gene expression data using synergy networks  

PubMed Central

Background Analysis of microarray data has been used for the inference of gene-gene interactions. If, however, the aim is the discovery of disease-related biological mechanisms, then the criterion for defining such interactions must be specifically linked to disease. Results Here we present a computational methodology that jointly analyzes two sets of microarray data, one in the presence and one in the absence of a disease, identifying gene pairs whose correlation with disease is due to cooperative, rather than independent, contributions of genes, using the recently developed information theoretic measure of synergy. High levels of synergy in gene pairs indicates possible membership of the two genes in a shared pathway and leads to a graphical representation of inferred gene-gene interactions associated with disease, in the form of a "synergy network." We apply this technique on a set of publicly available prostate cancer expression data and successfully validate our results, confirming that they cannot be due to pure chance and providing a biological explanation for gene pairs with exceptionally high synergy. Conclusion Thus, synergy networks provide a computational methodology helpful for deriving "disease interactomes" from biological data. When coupled with additional biological knowledge, they can also be helpful for deciphering biological mechanisms responsible for disease.

Watkinson, John; Wang, Xiaodong; Zheng, Tian; Anastassiou, Dimitris

2008-01-01

157

Republished review: Gene therapy for ocular diseases  

PubMed Central

The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

2011-01-01

158

Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease  

PubMed Central

Streptococcus pneumoniae is a leading cause of invasive bacterial disease. This is the first study to examine the expression of S. pneumoniae genes in vivo by using whole-genome microarrays available from The Institute for Genomic Research. Total RNA was collected from pneumococci isolated from infected blood, infected cerebrospinal fluid, and bacteria attached to a pharyngeal epithelial cell line in vitro. Microarray analysis of pneumococcal genes expressed in these models identified body site-specific patterns of expression for virulence factors, transporters, transcription factors, translation-associated proteins, metabolism, and genes with unknown function. Contributions to virulence predicted for several unknown genes with enhanced expression in vivo were confirmed by insertion duplication mutagenesis and challenge of mice with the mutants. Finally, we cross-referenced our results with previous studies that used signature-tagged mutagenesis and differential fluorescence induction to identify genes that are potentially required by a broad range of pneumococcal strains for invasive disease.

Orihuela, Carlos J.; Radin, Jana N.; Sublett, Jack E.; Gao, Geli; Kaushal, Deepak; Tuomanen, Elaine I.

2004-01-01

159

The Peripheral Blood Transcriptome Identifies the Presence and Extent of Disease in Idiopathic Pulmonary Fibrosis  

PubMed Central

Rationale Peripheral blood biomarkers are needed to identify and determine the extent of idiopathic pulmonary fibrosis (IPF). Current physiologic and radiographic prognostic indicators diagnose IPF too late in the course of disease. We hypothesize that peripheral blood biomarkers will identify disease in its early stages, and facilitate monitoring for disease progression. Methods Gene expression profiles of peripheral blood RNA from 130 IPF patients were collected on Agilent microarrays. Significance analysis of microarrays (SAM) with a false discovery rate (FDR) of 1% was utilized to identify genes that were differentially-expressed in samples categorized based on percent predicted DLCO and FVC. Main Measurements and Results At 1% FDR, 1428 genes were differentially-expressed in mild IPF (DLCO >65%) compared to controls and 2790 transcripts were differentially- expressed in severe IPF (DLCO >35%) compared to controls. When categorized by percent predicted DLCO, SAM demonstrated 13 differentially-expressed transcripts between mild and severe IPF (< 5% FDR). These include CAMP, CEACAM6, CTSG, DEFA3 and A4, OLFM4, HLTF, PACSIN1, GABBR1, IGHM, and 3 unknown genes. Principal component analysis (PCA) was performed to determine outliers based on severity of disease, and demonstrated 1 mild case to be clinically misclassified as a severe case of IPF. No differentially-expressed transcripts were identified between mild and severe IPF when categorized by percent predicted FVC. Conclusions These results demonstrate that the peripheral blood transcriptome has the potential to distinguish normal individuals from patients with IPF, as well as extent of disease when samples were classified by percent predicted DLCO, but not FVC.

Yang, Ivana V.; Luna, Leah G.; Cotter, Jennifer; Talbert, Janet; Leach, Sonia M.; Kidd, Raven; Turner, Julia; Kummer, Nathan; Kervitsky, Dolly; Brown, Kevin K.; Boon, Kathy; Schwarz, Marvin I.; Schwartz, David A.; Steele, Mark P.

2012-01-01

160

A sequence-based approach to identify reference genes for gene expression analysis  

PubMed Central

Background An important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer) may not be suitable in another (e.g. breast cancer). Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate. Methods Serial analysis of gene expression (SAGE) profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR), and their impact on differential expression analysis of microarray data was evaluated. Results We show that (i) conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii) reference genes identified for lung cancer do not perform well for other cancer types (breast and brain), (iii) reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv) normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung cancer exhibit higher statistical significance using a dataset normalized with our reference genes relative to normalization without using our reference genes. Conclusions Our analyses found NDUFA1, RPL19, RAB5C, and RPS18 to occupy the top ranking positions among 15 suitable reference genes optimal for normalization of lung tissue expression data. Significantly, the approach used in this study can be applied to data generated using new generation sequencing platforms for the identification of reference genes optimal within diverse contexts.

2010-01-01

161

Anaerobically expressed Escherichia coli genes identified by operon fusion techniques.  

PubMed Central

Genes that are expressed under anaerobic conditions were identified by operon fusion techniques with a hybrid bacteriophage of lambda and Mu, lambda placMu53, which creates transcriptional fusions to lacZY. Cells were screened for anaerobic expression on XG medium. Nine strains were selected, and the insertion point of the hybrid phage in each strain was mapped on the Escherichia coli chromosome linkage map. The anaerobic and aerobic expression levels of these genes were measured by beta-galactosidase assays in different medium conditions and in the presence of three regulatory mutations (fnr, narL, and rpoN). The anaerobically expressed genes (aeg) located at minute 99 (aeg-99) and 75 (aeg-75) appeared to be partially regulated by fnr, and aeg-93 is tightly regulated by fnr. aeg-60 requires a functional rpoN gene for its anaerobic expression. aeg-46.5 is repressed by narL. aeg-65A and aeg-65C are partially controlled by fnr but only in media containing nitrate or fumarate. aeg-47.5 and aeg-48.5 were found to be anaerobically induced only in rich media. The effects of a narL mutation on aeg-46.5 expression were observed in all medium conditions regardless of the presence or absence of nitrate. This suggests that narL has a regulatory function in the absence of exogenously added nitrate.

Choe, M; Reznikoff, W S

1991-01-01

162

Transposon tagging of disease resistance genes  

SciTech Connect

We are developing a transposon mutagenesis system for lettuce to clone genes for resistance to the fungal pathogen, Bremia lactucae. Activity of heterologous transposons is being studied in transgenic plants. Southern analysis of T{sub 1} and T{sub 2} plants containing Tam3 from Antirrhinum provided ambiguous results. Multiple endonuclease digests indicated that transposition had occurred; however, in no plant were all endonuclease digests consistent with a simple excision event. Southern or PCR analysis of over 50 plans containing Ac from maize have also failed to reveal clear evidence of transposition; this is contrast to experiments by others with the same constructs who have observed high rates of Ac excision in other plant species. Nearly all of 65 T{sub 2} families containing Ac interrupting a chimeric streptomycin resistance gene (Courtesy J. Jones, Sainsbury Lab., UK) clearly segregated for streptomycin resistance. Southern analyses, however, showed no evidence of transposition, indicating restoration of a functional message by other mechanisms, possibly mRNA processing. Transgenic plants have also been generated containing CaMV 35S or hsp70 promoters fused to transposase coding sequences or a Ds element interrupting a chimeric GUS gene (Courtesy M. Lassner, UC Davis). F{sub 1} plants containing both constructs were analyzed for transposition. Only two plants containing both constructs were obtained from 48 progeny, far fewer than expected, and neither showed evidence of transposition in Southerns and GUS assays. We are currently constructing further chimeric transposase fusions. To test for the stability of the targeted disease resistance genes, 50,000 F{sub 1} plants heterozygous for three resistance genes were generated; no mutants have been identified in the 5000 so far screened.

Michelmore, R.W. (California Univ., Davis, CA (USA). Dept. of Physics)

1989-01-01

163

Identifying Diagnostic Peptides for Lyme Disease through Epitope Discovery  

PubMed Central

Serum antibodies from patients with Lyme disease (LD) were used to affinity select peptide epitopes from 12 large random peptide libraries in phage display format. The selected peptides were surveyed for reactivity with a panel of positive sera (from LD patients) and negative sera (from subjects without LD), thus identifying 17 peptides with a diagnostically useful binding pattern: reactivity with at least three positive sera and no reactivity with any of the negative sera. The peptides define eight sequence motifs, none of which can be matched convincingly with segments of proteins from Borrelia burgdorferi, the LD pathogen; evidently, then, they are “mimotopes,” mimicking natural pathogen epitopes without matching contiguous amino acids of pathogen proteins. Peptides like these could be the basis of a new diagnostic enzyme-linked immunosorbent assay for LD, with sufficient specificity and sensitivity to replace expensive immunoblotting tests that are currently required for definitive serological diagnosis. Moreover, the method used to discover these peptides did not require any knowledge of the pathogen and involved generic procedures that are applicable to almost any infectious disease, including emerging diseases for which no pathogen has yet been identified.

Kouzmitcheva, Galina A.; Petrenko, Valery A.; Smith, George P.

2001-01-01

164

Proteomic analysis of age-dependent changes in protein solubility identifies genes that modulate lifespan  

PubMed Central

While it is generally recognized that misfolding of specific proteins can cause late-onset disease, the contribution of protein aggregation to the normal aging process is less well understood. To address this issue, a mass spectrometry-based proteomic analysis was performed to identify proteins that adopt sodium dodecyl sulfate (SDS)-insoluble conformations during aging in Caenorhabditis elegans. SDS-insoluble proteins extracted from young and aged C. elegans were chemically labeled by isobaric tagging for relative and absolute quantification (iTRAQ) and identified by liquid chromatography and mass spectrometry. Two hundred and three proteins were identified as being significantly enriched in an SDS-insoluble fraction in aged nematodes and were largely absent from a similar protein fraction in young nematodes. The SDS-insoluble fraction in aged animals contains a diverse range of proteins including a large number of ribosomal proteins. Gene ontology analysis revealed highly significant enrichments for energy production and translation functions. Expression of genes encoding insoluble proteins observed in aged nematodes was knocked down using RNAi, and effects on lifespan were measured. 41% of genes tested were shown to extend lifespan after RNAi treatment, compared with 18% in a control group of genes. These data indicate that genes encoding proteins that become insoluble with age are enriched for modifiers of lifespan. This demonstrates that proteomic approaches can be used to identify genes that modify lifespan. Finally, these observations indicate that the accumulation of insoluble proteins with diverse functions may be a general feature of aging.

Reis-Rodrigues, Pedro; Czerwieniec, Gregg; Peters, Theodore W; Evani, Uday S; Alavez, Silvestre; Gaman, Emily A; Vantipalli, Maithili; Mooney, Sean D; Gibson, Bradford W; Lithgow, Gordon J; Hughes, Robert E

2012-01-01

165

Identifying novel genes involved in both deer physiological and human pathological osteoporosis.  

PubMed

Osteoporosis attacks 10% of the population worldwide. Humans or even the model animals of the disease cannot recover from porous bone. Regeneration in skeletal elements is the unique feature of our newly investigated osteoporosis model, the red deer (Cervus elaphus) stag. Cyclic physiological osteoporosis is a consequence of the annual antler cycle. This phenomenon raises the possibility to identify genes involved in the regulation of bone mineral density on the basis of comparative genomics between deer and human. We compare gene expression activity of osteoporotic and regenerating rib bone samples versus autumn dwell control in red deer by microarray hybridization. Identified genes were tested on human femoral bone tissue from non-osteoporotic controls and patients affected with age-related osteoporosis. Expression data were evaluated by Principal Components Analysis and Canonical Variates Analysis. Separation of patients into a normal and an affected group based on ten formerly known osteoporosis reference genes was significantly improved by expanding the data with newly identified genes. These genes include IGSF4, FABP3, FABP4, FKBP2, TIMP2, TMSB4X, TRIB, and members of the Wnt signaling. This study supports that extensive comparative genomic analyses, here deer and human, provide a novel approach to identify new targets for human diagnostics and therapy. PMID:19107525

Borsy, Adrienn; Podani, János; Stéger, Viktor; Balla, Bernadett; Horváth, Arnold; Kósa, János P; Gyurján, István; Molnár, Andrea; Szabolcsi, Zoltán; Szabó, László; Jakó, Eéna; Zomborszky, Zoltán; Nagy, János; Semsey, Szabolcs; Vellai, Tibor; Lakatos, Péter; Orosz, László

2009-03-01

166

Screening for noise in gene expression identifies drug synergies.  

PubMed

Stochastic fluctuations are inherent to gene expression and can drive cell-fate specification. We used such fluctuations to modulate reactivation of HIV from latency-a quiescent state that is a major barrier to an HIV cure. By screening a diverse library of bioactive small molecules, we identified more than 80 compounds that modulated HIV gene-expression fluctuations (i.e., "noise"), without changing mean expression. These noise-modulating compounds would be neglected in conventional screens, and yet, they synergized with conventional transcriptional activators. Noise enhancers reactivated latent cells significantly better than existing best-in-class reactivation drug combinations (and with reduced off-target cytotoxicity), whereas noise suppressors stabilized latency. Noise-modulating chemicals may provide novel probes for the physiological consequences of noise and an unexplored axis for drug discovery, allowing enhanced control over diverse cell-fate decisions. PMID:24903562

Dar, Roy D; Hosmane, Nina N; Arkin, Michelle R; Siliciano, Robert F; Weinberger, Leor S

2014-06-20

167

Identifying highly mutated IGHD genes in the junctions of rearranged human immunoglobulin heavy chain genes  

Microsoft Academic Search

The reliable identification of IGHD genes within human immunoglobulin heavy chains is challenging with up to one third of rearrangements having no identifiable IGHD gene. The short, mutated IGHD genes are generally assumed to be indistinguishable from the N-REGIONS of non-template encoded nucleotides that surround them. In this study we have characterised N-REGIONS, demonstrating the importance of nucleotide composition biases

Katherine J. L. Jackson; Bruno A. Gaëta; Andrew M. Collins

2007-01-01

168

A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression  

PubMed Central

Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method). This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS) and Progression Score (PS) in progression analysis, True Positive Rate (TPR) in gene pair analysis, and Pathway Enrichment Score (PES) in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From this research, several gene interaction networks inferred could provide clues for the mechanism of prostate cancer progression. Conclusion The SIG method reliably identifies cancer progression correlated gene pairs, and performs well both in gene pair ontology analysis and in pathway enrichment analysis. This method provides an effective means of understanding the molecular mechanism of carcinogenesis by appropriately tracking down the process of cancer progression.

Mo, Wen Juan; Fu, Xu Ping; Han, Xiao Tian; Yang, Guang Yuan; Zhang, Ji Gang; Guo, Feng Hua; Huang, Yan; Mao, Yu Min; Li, Yao; Xie, Yi

2009-01-01

169

A Comparison of Logistic Regression, Logic Regression, Classification Tree, and Random Forests to Identify Effective Gene-Gene and Gene-Environmental Interactions  

PubMed Central

Genome wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with a variety of common human diseases. Due to the weak marginal effect of most disease-associated SNPs, attention has recently turned to evaluating the combined effect of multiple disease-associated SNPs on the risk of disease. Several recent multigenic studies show potential evidence of applying multigenic approaches in association studies of various diseases including lung cancer. But the question remains as to the best methodology to analyze single nucleotide polymorphisms in multiple genes. In this work, we consider four methods—logistic regression, logic regression, classification tree, and random forests—to compare results for identifying important genes or gene-gene and gene-environmental interactions. To evaluate the performance of four methods, the cross-validation misclassification error and areas under the curves are provided. We performed a simulation study and applied them to the data from a large-scale, population-based, case-control study.

Yoo, Wonsuk; Ference, Brian A.; Cote, Michele L; Schwartz, Ann

2013-01-01

170

A novel approach to identify driver genes involved in androgen-independent prostate cancer  

PubMed Central

Background Insertional mutagenesis screens have been used with great success to identify oncogenes and tumor suppressor genes. Typically, these screens use gammaretroviruses (?RV) or transposons as insertional mutagens. However, insertional mutations from replication-competent ?RVs or transposons that occur later during oncogenesis can produce passenger mutations that do not drive cancer progression. Here, we utilized a replication-incompetent lentiviral vector (LV) to perform an insertional mutagenesis screen to identify genes in the progression to androgen-independent prostate cancer (AIPC). Methods Prostate cancer cells were mutagenized with a LV to enrich for clones with a selective advantage in an androgen-deficient environment provided by a dysregulated gene(s) near the vector integration site. We performed our screen using an in vitro AIPC model and also an in vivo xenotransplant model for AIPC. Our approach identified proviral integration sites utilizing a shuttle vector that allows for rapid rescue of plasmids in E. coli that contain LV long terminal repeat (LTR)-chromosome junctions. This shuttle vector approach does not require PCR amplification and has several advantages over PCR-based techniques. Results Proviral integrations were enriched near prostate cancer susceptibility loci in cells grown in androgen-deficient medium (p?genes that influence AIPC were identified; ATPAF1, GCOM1, MEX3D, PTRF, and TRPM4. Additionally, we showed that RNAi knockdown of ATPAF1 significantly reduces growth (p?identifying a known prostate cancer gene, PTRF, and also several genes not previously associated with prostate cancer. The replication-incompetent shuttle vector approach has broad potential applications for cancer gene discovery, and for interrogating diverse biological and disease processes.

2014-01-01

171

Gene Therapy for Allergic Airway Diseases  

Microsoft Academic Search

Airway diseases such as allergic asthma and rhinitis are characterized by a T-helper type 2 (Th2) response. Treatment of allergic\\u000a airway diseases is currently limited to drugs that relieve disease symptoms and inflammation. In the search for new therapeutics,\\u000a efforts have been made to treat allergic airway disease with gene therapy, and many preclinical studies have demonstrated\\u000a its impressive potential.

Tania Maes; Kurt G. Tournoy; Guy F. Joos

2011-01-01

172

A gain-of-function screen to identify genes that reduce lifespan in the adult of Drosophila melanogaster  

PubMed Central

Background Several lines of evidence associate misregulated genetic expression with risk factors for diabetes, Alzheimer’s, and other diseases that sporadically develop in healthy adults with no background of hereditary disorders. Thus, we are interested in genes that may be expressed normally through parts of an individual’s life, but can cause physiological defects and disease when misexpressed in adulthood. Results We attempted to identify these genes in a model organism by arbitrarily misexpressing specific genes in adult Drosophila melanogaster, using 14,133 Gene Search lines. We identified 39 “reduced-lifespan genes” that, when misexpressed in adulthood, shortened the flies’ lifespan to less than 30% of that of control flies. About half of these genes have human orthologs that are known to be involved in human diseases. For about one-fourth of the reduced-lifespan genes, suppressing apoptosis restored the lifespan shortened by their misexpression. We determined the organs responsible for reduced lifespan when these genes were misexpressed specifically in adulthood, and found that while some genes induced reduced lifespan only when misexpressed in specific adult organs, others could induce reduced lifespan when misexpressed in various organs. This finding suggests that tissue-specific dysfunction may be involved in reduced lifespan related to gene misexpression. Gene ontology analysis showed that reduced-lifespan genes are biased toward genes related to development. Conclusions We identified 39 genes that, when misexpressed in adulthood, shortened the lifespan of adult flies. Suppressing apoptosis rescued this shortened lifespan for only a subset of the reduced-lifespan genes. The adult tissues in which gene misexpression caused early death differed among the reduced-lifespan genes. These results suggest that the cause of reduced lifespan upon misexpression differed among the genes.

2014-01-01

173

[Construction of SW480 cell model identifying Shigella virulent genes].  

PubMed

Signature-tagged mutagenesis (STM) is a novel technology with high throughput screening ability to identify virulent genes of pathogen in vivo. An appropriate animal or cell line model is one of prerequisites by exploiting this technique. In order to apply STM to Shigella flexneri, RC426 was constructed as an attenuated mutant with chloramphenicol resistance and aroA and virG genes inactivated by homologous recombination; another attenuated strain T32 was used as an oral S. flexneri 2a vaccine due to a spontaneous deletion in three loci (ipaBCDA, invA and virG) on the virulence plasmid. The wild type strain 2457T had the invasion ability into host cells. The three strains, RC426, T32 and 2457T, were mixed together to invade colon cancer cell line SW480, and the distinct strains were recovered and counted from cell lysates of invaded SW480 in different time. The results showed that there were statistically significant differences between the amounts of two attenuated strains recovered and that of virulent strain within 12h invasion, indicating SW480 was a suitable cell model for applying STM to screen virulent genes of Shigella flexneri. PMID:15640048

Yao, Xiao; Wang, Heng-Liang; Shi, Zhao-Xing; Yan, Xiao-Yu; Feng, Er-Ling; Liu, Quan-Hong; Su, Guo-Fu; Huang, Liu-Yu

2004-07-01

174

Candidate genes affecting Drosophila life span identified by integrating microarray gene expression analysis and QTL mapping.  

PubMed

The current increase in life expectancy observed in industrialized societies underscores the need to achieve a better understanding of the aging process that could help the development of effective strategies to achieve healthy aging. This will require not only identifying genes involved in the aging process, but also understanding how their effects are modulated by environmental factors, such as dietary intake and life style. Although the human genome has been sequenced, it may be impractical to study humans or other long-lived organisms to gain a mechanistic understanding about the aging process. Thus, short-lived animal models are essential to identifying the mechanisms and genes that affect the rate and quality of aging as a first step towards identifying genetic variants in humans. In this study, we investigated gene expression changes between two strains of Drosophila (Oregon and 2b) for which quantitative trait loci (QTLs) affecting life span were identified previously. We collected males and females from both strains at young and old ages, and assessed whole genome variation in transcript abundance using Affymetrix GeneChips. We observed 8217 probe sets with detectable transcripts. A total of 2371 probe sets, representing 2220 genes, exhibited significant changes in transcript abundance with age; and 839 probe sets were differentially expressed between Oregon and 2b. We focused on the 359 probe sets (representing 354 genes) that exhibited significant changes in gene expression both with age and between strains. We used these genes to integrate the analysis of microarray gene expression data, bioinformatics, and the results of genetic mapping studies reported previously, to identify 49 candidate genes and four pathways that could potentially be responsible for regulating life span and involved in the process of aging in Drosophila and humans. PMID:17196240

Lai, Chao-Qiang; Parnell, Laurence D; Lyman, Richard F; Ordovas, Jose M; Mackay, Trudy F C

2007-03-01

175

Novel radiation response genes identified in gene-trapped MCF10A mammary epithelial cells.  

PubMed

We have used a gene-trapping strategy to screen human mammary epithelial cells for radiation response genes. Relative mRNA expression levels of five candidate genes in MCF10A cells were analyzed, both with and without exposure to radiation. In all five cases, the trapped genes were significantly down-regulated after radiation treatment. Sequence analysis of the fusion transcripts identified the trapped genes: (1) the human androgen receptor, (2) the uncharacterized DREV1 gene, which has known homology to DNA methyltransferases, (3) the human creatine kinase gene, (4) the human eukaryotic translation elongation factor 1 beta 2, and (5) the human ribosomal protein L27. All five genes were down-regulated significantly after treatment with varying doses of ionizing radiation (0.10 to 4.0 Gy) and at varying times (2-30 h after treatment). The genes were also analyzed in human fibroblast and lymphoblastoid cell lines to determine whether the radiation response being observed was cell-type specific. The results verified that the observed radiation response was not a cell-type-specific phenomenon, suggesting that the genes play essential roles in the radiation damage control pathways. This study demonstrates the potential of the gene-trap approach for the identification and functional analysis of novel radiation response genes. PMID:17390725

Malone, Jennifer; Ullrich, Robert

2007-02-01

176

Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes  

PubMed Central

Background Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. Methods We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. Results In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Conclusion Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome.

Warnat, Patrick; Oberthuer, Andre; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt

2007-01-01

177

Comparative Oncogenomics Identifies PSMB4 and SHMT2 as Potential Cancer Driver Genes.  

PubMed

Cancer genomes maintain a complex array of somatic alterations required for maintenance and progression of the disease, posing a challenge to identify driver genes among this genetic disorder. Toward this end, we mapped regions of recurrent amplification in a large collection (n = 392) of primary human cancers and selected 620 genes whose expression is elevated in tumors. An RNAi loss-of-function screen targeting these genes across a panel of 32 cancer cell lines identified potential driver genes. Subsequent functional assays identified SHMT2, a key enzyme in the serine/glycine synthesis pathway, as necessary for tumor cell survival but insufficient for transformation. The 26S proteasomal subunit, PSMB4, was identified as the first proteasomal subunit with oncogenic properties promoting cancer cell survival and tumor growth in vivo. Elevated expression of SHMT2 and PSMB4 was found to be associated with poor prognosis in human cancer, supporting the development of molecular therapies targeting these genes or components of their pathways. Cancer Res; 74(11); 3114-26. ©2014 AACR. PMID:24755469

Lee, Genee Y; Haverty, Peter M; Li, Li; Kljavin, Noelyn M; Bourgon, Richard; Lee, James; Stern, Howard; Modrusan, Zora; Seshagiri, Somasekar; Zhang, Zemin; Davis, David; Stokoe, David; Settleman, Jeffrey; de Sauvage, Frederic J; Neve, Richard M

2014-06-01

178

Transcriptional Profile Analysis of RPGRORF15 Frameshift Mutation Identifies Novel Genes Associated with Retinal Degeneration  

PubMed Central

Purpose. To identify genes and molecular mechanisms associated with photoreceptor degeneration in a canine model of XLRP caused by an RPGR exon ORF15 microdeletion. Methods. Expression profiles of mutant and normal retinas were compared by using canine retinal custom cDNA microarrays. qRT-PCR, Western blot analysis, and immunohistochemistry (IHC) were applied to selected genes, to confirm and expand the microarray results. Results. At 7 and 16 weeks, respectively, 56 and 18 transcripts were downregulated in the mutant retinas, but none were differentially expressed (DE) at both ages, suggesting the involvement of temporally distinct pathways. Downregulated genes included the known retina-relevant genes PAX6, CHML, and RDH11 at 7 weeks and CRX and SAG at 16 weeks. Genes directly or indirectly active in apoptotic processes were altered at 7 weeks (CAMK2G, NTRK2, PRKCB, RALA, RBBP6, RNF41, SMYD3, SPP1, and TUBB2C) and 16 weeks (SLC25A5 and NKAP). Furthermore, the DE genes at 7 weeks (ELOVL6, GLOD4, NDUFS4, and REEP1) and 16 weeks (SLC25A5 and TARS2) are related to mitochondrial functions. qRT-PCR of 18 genes confirmed the microarray results and showed DE of additional genes not on the array. Only GFAP was DE at 3 weeks of age. Western blot and IHC analyses also confirmed the high reliability of the transcriptomic data. Conclusions. Several DE genes were identified in mutant retinas. At 7 weeks, a combination of nonclassic anti- and proapoptosis genes appear to be involved in photoreceptor degeneration, whereas at both 7 and 16 weeks, the expression of mitochondria-related genes indicates that they may play a relevant role in the disease process.

Genini, Sem; Zangerl, Barbara; Slavik, Julianna; Acland, Gregory M.; Beltran, William A.

2010-01-01

179

Gene Therapy for Diseases and Genetic Disorders  

MedlinePLUS

... notable advancements are the following: Gene Therapy for Genetic Disorders Severe Combined Immune Deficiency (ADA-SCID) ADA-SCID ... in preclinical animal models of this disease. Other genetic disorders After many years of laboratory and preclinical research ...

180

Salmonella enterica Highly Expressed Genes Are Disease Specific  

PubMed Central

During in vitro broth culture, bacterial gene expression is typically dominated by highly expressed factors involved in protein biosynthesis, maturation, and folding, but it is unclear if this also applies to conditions in natural environments. Here, we used a promoter trap strategy with an unstable green fluorescent protein reporter that can be detected in infected mouse tissues to identify 21 Salmonella enterica promoters with high levels of activity in a mouse enteritis model. We then measured the activities of these and 31 previously identified Salmonella promoters in both the enteritis and a murine typhoid fever model. Surprisingly, the data reveal that instead of protein biosynthesis genes, disease-specific genes such as Salmonella pathogenicity island 1 (SPI-1)-associated genes and genes involved in anaerobic respiration (enteritis) or SPI-2-associated genes and genes of the PhoP regulon (typhoid fever), respectively, dominate Salmonella in vivo gene expression. The overall functional profile of highly expressed genes suggests a marked shift in major transcriptional activities to nutrient utilization during enteritis or to fighting against the host during typhoid fever. The large proportion of known and novel essential virulence factors among the identified genes suggests that high expression levels during infection may correlate with functional relevance.

Rollenhagen, Claudia; Bumann, Dirk

2006-01-01

181

Diametrical clustering for identifying anti-correlated gene clusters  

Microsoft Academic Search

Motivation: Clustering genes based upon their expres- sion patterns allows us to predict gene function. Most existing clus- tering algorithms cluster genes together when their expression pat- terns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive ó genes responding to the

Inderjit S. Dhillon; Edward M. Marcotte; Usman Roshan

2003-01-01

182

Brain Expression Genome-Wide Association Study (eGWAS) Identifies Human Disease-Associated Variants  

PubMed Central

Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n?=?197, temporal cortex n?=?202) and with other brain pathologies (non–AD, cerebellar n?=?177, temporal cortex n?=?197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ±100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non–ADs (q<0.05, p?=?7.70×10?5–1.67×10?82). Of these, 2,089 were also significant in the temporal cortex (p?=?1.85×10?5–1.70×10?141). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10?6). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinson's disease (PD) MMRN1/rs6532197, Paget's disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9–3.3 fold enrichment (p<10?6) of significant cisSNPs with suggestive AD–risk association (p<10?3) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non–CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics.

Crook, Julia; Pankratz, V. Shane; Carrasquillo, Minerva M.; Rowley, Christopher N.; Nair, Asha A.; Middha, Sumit; Maharjan, Sooraj; Nguyen, Thuy; Ma, Li; Malphrus, Kimberly G.; Palusak, Ryan; Lincoln, Sarah; Bisceglio, Gina; Georgescu, Constantin; Kouri, Naomi; Kolbert, Christopher P.; Jen, Jin; Haines, Jonathan L.; Mayeux, Richard; Pericak-Vance, Margaret A.; Farrer, Lindsay A.; Schellenberg, Gerard D.; Petersen, Ronald C.; Graff-Radford, Neill R.; Dickson, Dennis W.; Younkin, Steven G.; Ertekin-Taner, Nilufer

2012-01-01

183

Gene Transfer Approaches for Gynecological Diseases  

Microsoft Academic Search

Gene transfer presents a potentially useful approach for the treatment of diseases refractory to conventional therapies. Various preclinical and clinical strategies have been explored for treatment of gynecological diseases. Given the direst need for novel treatments, much of the work has been performed with gynecological cancers and ovarian cancer in particular. Although the safety of many approaches has been demonstrated

Mari Raki; Daniel T. Rein; Anna Kanerva; Akseli Hemminki

2006-01-01

184

Metabolomics tools for identifying biomarkers for neuropsychiatric diseases.  

PubMed

The repertoire of biochemicals (or small molecules) present in cells, tissue, and body fluids is known as the metabolome. Today, clinicians utilize only a very small part of the information contained in the metabolome, as revealed by the quantification of a limited set of analytes to gain information on human health. Examples include measuring glucose or cholesterol to monitor diabetes and cardiovascular health, respectively. With a focus on comprehensively studying the metabolome, the rapidly growing field of metabolomics captures the metabolic state of organisms at the global or "-omics" level. Given that the overall health status of an individual is captured by his or her metabolic state, which is a reflection of what has been encoded by the genome and modified by environmental factors, metabolomics has the potential to have a great impact upon medical practice by providing a wealth of relevant biochemical data. Metabolomics promises to improve current, single metabolites-based clinical assessments by identifying metabolic signatures (biomarkers) that embody global biochemical changes in disease, predict responses to treatment or medication side effects (pharmachometabolomics). State of the art metabolomic analytical platforms and informatics tools are being used to map potential biomarkers for a multitude of disorders including those of the central nervous system (CNS). Indeed, CNS disorders are linked to disturbances in metabolic pathways related to neurotransmitter systems (dopamine, serotonin, GABA and glutamate); fatty acids such as arachidonic acid-cascade; oxidative stress and mitochondrial function. Metabolomics tools are enabling us to map in greater detail perturbations in many biochemical pathways and links among these pathways this information is key for development of biomarkers that are disease-specific. In this review, we elaborate on some of the concepts and technologies used in metabolomics and its promise for biomarker discovery. We also highlight early findings from metabolomic studies in CNS disorders such as schizophrenia, Major Depressive Disorder (MDD), Bipolar Disorder (BD), Amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD). PMID:19303440

Quinones, Marlon P; Kaddurah-Daouk, Rima

2009-08-01

185

Comprehensive analysis of the LRRK2 gene in sixty families with Parkinson's disease  

Microsoft Academic Search

Mutations in the gene leucine-rich repeat kinase 2 (LRRK2) have been recently identified in families with Parkinson's disease (PD). However, the prevalence and nature of LRRK2 mutations, the polymorphism content of the gene, and the associated phenotypes remain poorly understood. We performed a comprehensive study of this gene in a large sample of families with Parkinson's disease compatible with autosomal

Alessio Di Fonzo; Cristina Tassorelli; Michele De Mari; Hsin F Chien; Joaquim Ferreira; Christan F Rohé; Giulio Riboldazzi; Angelo Antonini; Gianni Albani; Alessandro Mauro; Roberto Marconi; Giovanni Abbruzzese; Leonardo Lopiano; Emiliana Fincati; Marco Guidi; Paolo Marini; Fabrizio Stocchi; Marco Onofrj; Vincenzo Toni; Michele Tinazzi; Giovanni Fabbrini; Paolo Lamberti; Nicola Vanacore; Giuseppe Meco; Petra Leitner; Ryan J Uitti; Zbigniew K Wszolek; Thomas Gasser; Erik J Simons; Guido J Breedveld; Stefano Goldwurm; Gianni Pezzoli; Cristina Sampaio; Egberto Barbosa; Emilia Martignoni; Ben A Oostra; Vincenzo Bonifati

2006-01-01

186

a Novel Measure for Finding Disease-Specific Genes from the Biomedical Literature  

NASA Astrophysics Data System (ADS)

We present a novel measure that identifies disease-associated genes from the biomedical literature in terms of causing less side-effects. Our aim is to extract genes that not only have strong associations with a given disease, but also have no or weak associations with other diseases. This enables identification of specific disease-associated genes, the decreased expression of which would result in a lower probability of side-effects, thus contributing to efficient drug development. Our proposed method incorporates transitive associations between the disease and genes based on the frequency of co-occurrence of gene terms.

Kwon, Yeondae; Sugawara, Hideaki; Shimizu, Shogo; Miyazaki, Satoru

2013-01-01

187

Lung disease modifier genes in cystic fibrosis.  

PubMed

Cystic fibrosis (CF) is recognized as a single gene disorder. However, a considerable diversity in its clinical phenotype has been documented since the description of the disease. Identification of additional gene alleles, so called "modifier genes" that directly influence the phenotype of CF disease became a challenge in the late '90ies, not only for the insight it provides into the CF pathophysiology, but also for the development of new potential therapeutic targets. One of the most studied phenotype has been the lung disease severity as lung dysfunction is the major cause of morbidity and mortality in CF. This review details the results of two main genetic approaches that have mainly been explored so far: (1) an "a priori" approach, i.e. the candidate gene approach; (2) a "without a priori" approach, analyzing the whole genome by linkage and genome-wide association studies (GWAS), or the whole exome by exome sequencing. PMID:24569122

Guillot, Loic; Beucher, Julie; Tabary, Olivier; Le Rouzic, Philippe; Clement, Annick; Corvol, Harriet

2014-07-01

188

Gene Therapy For Ischemic Heart Disease  

PubMed Central

Current pharmacologic therapy for ischemic heart disease suffers multiple limitations such as compliance issues and side effects of medications. Revascularization procedures often end with need for repeat procedures. Patients remain symptomatic despite maximal medical therapy. Gene therapy offers an attractive alternative to current pharmacologic therapies and may be beneficial in refractory disease. Gene therapy with isoforms of growth factors such as VEGF, FGF and HGF induces angiogenesis, decreases apoptosis and leads to protection in the ischemic heart. Stem cell therapy augmented with gene therapy used for myogenesis has proven to be beneficial in numerous animal models of myocardial ischemia. Gene therapy coding for antioxidants, eNOS, HSP, mitogen-activated protein kinase and numerous other anti apoptotic proteins have demonstrated significant cardioprotection in animal models. Clinical trials have demonstrated safety in humans apart from symptomatic and objective improvements in cardiac function. Current research efforts are aimed at refining various gene transfection techniques and regulation of gene expression in vivo in the heart and circulation to improve clinical outcomes in patients that suffer from ischemic heart disease. In this review article we will attempt to summarize the current state of both preclinical and clinical studies of gene therapy to combat myocardial ischemic disease.

Lavu, Madhav; Gundewar, Susheel; Lefer, David J.

2010-01-01

189

Fox Chase researchers identify a gene that predicts recurrence in squamous cell carcinoma of the head and neck  

Cancer.gov

Fox Chase Cancer Center researchers have identified a gene that predicts disease recurrence in individuals with squamous cell carcinoma of the head and neck. The new findings, presented at the American Association for Cancer Research Annual Meeting 2012 on Monday, April 2, show that patients with one common variant of a gene which encodes the cytochrome P450 (CYP1B1) protein are likely to have a longer time-to-recurrence than those with the more typical form of the gene.

190

Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases  

PubMed Central

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean?=?4.4 Mb) that contain many genes (mean?=?79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data.

Puffenberger, Erik G.; Jinks, Robert N.; Sougnez, Carrie; Cibulskis, Kristian; Willert, Rebecca A.; Achilly, Nathan P.; Cassidy, Ryan P.; Fiorentini, Christopher J.; Heiken, Kory F.; Lawrence, Johnny J.; Mahoney, Molly H.; Miller, Christopher J.; Nair, Devika T.; Politi, Kristin A.; Worcester, Kimberly N.; Setton, Roni A.; DiPiazza, Rosa; Sherman, Eric A.; Eastman, James T.; Francklyn, Christopher; Robey-Bond, Susan; Rider, Nicholas L.; Gabriel, Stacey; Morton, D. Holmes; Strauss, Kevin A.

2012-01-01

191

Co-clustering phenome-genome for phenotype classification and disease gene discovery  

PubMed Central

Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways.

Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

2012-01-01

192

Prioritization of retinal disease genes: an integrative approach.  

PubMed

The discovery of novel disease-associated variations in genes is often a daunting task in highly heterogeneous disease classes. We seek a generalizable algorithm that integrates multiple publicly available genomic data sources in a machine-learning model for the prioritization of candidates identified in patients with retinal disease. To approach this problem, we generate a set of feature vectors from publicly available microarray, RNA-seq, and ChIP-seq datasets of biological relevance to retinal disease, to observe patterns in gene expression specificity among tissues of the body and the eye, in addition to photoreceptor-specific signals by the CRX transcription factor. Using these features, we describe a novel algorithm, positive and unlabeled learning for prioritization (PULP). This article compares several popular supervised learning techniques as the regression function for PULP. The results demonstrate a highly significant enrichment for previously characterized disease genes using a logistic regression method. Finally, a comparison of PULP with the popular gene prioritization tool ENDEAVOUR shows superior prioritization of retinal disease genes from previous studies. The java source code, compiled binary, assembled feature vectors, and instructions are available online at https://github.com/ahwagner/PULP. PMID:23508994

Wagner, Alex H; Taylor, Kyle R; DeLuca, Adam P; Casavant, Thomas L; Mullins, Robert F; Stone, Edwin M; Scheetz, Todd E; Braun, Terry A

2013-06-01

193

Discovering disease-genes by topological features in human protein-protein interaction network  

Microsoft Academic Search

Motivation: Mining the hereditary disease-genes from human genome is one of the most important tasks in bioinformatics research. A variety of sequence features and functional similarities between known human hereditary disease-genes and those not known to be involved in disease have been systematically examined and efficient classifiers have been constructed based on the identified common patterns. The availability of human

Jianzhen Xu; Yongjin Li

2006-01-01

194

Fourteen-Genome Comparison Identifies DNA Markers for Severe-Disease-Associated Strains of Clostridium difficile?†  

PubMed Central

Clostridium difficile is a common cause of infectious diarrhea in hospitalized patients. A severe and increased incidence of C. difficile infection (CDI) is associated predominantly with the NAP1 strain; however, the existence of other severe-disease-associated (SDA) strains and the extensive genetic diversity across C. difficile complicate reliable detection and diagnosis. Comparative genome analysis of 14 sequenced genomes, including those of a subset of NAP1 isolates, allowed the assessment of genetic diversity within and between strain types to identify DNA markers that are associated with severe disease. Comparative genome analysis of 14 isolates, including five publicly available strains, revealed that C. difficile has a core genome of 3.4 Mb, comprising ?3,000 genes. Analysis of the core genome identified candidate DNA markers that were subsequently evaluated using a multistrain panel of 177 isolates, representing more than 50 pulsovars and 8 toxinotypes. A subset of 117 isolates from the panel had associated patient data that allowed assessment of an association between the DNA markers and severe CDI. We identified 20 candidate DNA markers for species-wide detection and 10,683 single nucleotide polymorphisms (SNPs) associated with the predominant SDA strain (NAP1). A species-wide detection candidate marker, the sspA gene, was found to be the same across 177 sequenced isolates and lacked significant similarity to those of other species. Candidate SNPs in genes CD1269 and CD1265 were found to associate more closely with disease severity than currently used diagnostic markers, as they were also present in the toxin A-negative and B-positive (A-B+) strain types. The genetic markers identified illustrate the potential of comparative genomics for the discovery of diagnostic DNA-based targets that are species specific or associated with multiple SDA strains.

Forgetta, Vincenzo; Oughton, Matthew T.; Marquis, Pascale; Brukner, Ivan; Blanchette, Ruth; Haub, Kevin; Magrini, Vince; Mardis, Elaine R.; Gerding, Dale N.; Loo, Vivian G.; Miller, Mark A.; Mulvey, Michael R.; Rupnik, Maja; Dascal, Andre; Dewar, Ken

2011-01-01

195

Gene-expression profiling in rheumatic disease: tools and therapeutic potential  

Microsoft Academic Search

Gene-expression profiling is a powerful tool for the discovery of molecular fingerprints that underlie human disease. Microarray technologies allow the analysis of messenger RNA transcript levels for every gene in the genome. However, gene-expression profiling is best viewed as part of a pipeline that extends from sample collection through clinical application. Key genes and pathways identified by microarray profiling should

Jason W. Bauer; Hatice Bilgic; Emily C. Baechler

2009-01-01

196

Identifying the Viral Genes Encoding Envelope Glycoproteins for Differentiation of Cyprinid herpesvirus 3 Isolates  

PubMed Central

Cyprinid herpes virus 3 (CyHV-3) diseases have been reported around the world and are associated with high mortalities of koi (Cyprinus carpio). Although little work has been conducted on the molecular analysis of this virus, glycoprotein genes identified in the present study seem to be valuable targets for genetic comparison of this virus. Three envelope glycoprotein genes (ORF25, 65 and 116) of the CyHV-3 isolates from the USA, Israel, Japan and Korea were compared, and interestingly, sequence insertions or deletions were observed in these target regions. In addition, polymorphisms were presented in microsatellite zones from two glycoprotein genes (ORF65 and 116). In phylogenetic tree analysis, the Korean isolate was remarkably distinguished from USA, Israel, Japan isolates. These findings may be suitable for many applications including isolates differentiation and phylogeny studies.

Han, Jee Eun; Kim, Ji Hyung; Renault, Tristan; Choresca, Casiano; Shin, Sang Phil; Jun, Jin Woo; Park, Se Chang

2013-01-01

197

Exploring matrix factorization techniques for significant genes identification of Alzheimer's disease microarray gene expression data  

PubMed Central

Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA) and nonnegative matrix factorization (NMF) are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and the biological analysis of the identified significant genes and their related pathways demonstrated that these genes play a prominent role in AD and relate the activation patterns to AD phenotypes. It is validated that the combination of these two methods is efficient. Conclusions Unsupervised matrix factorization methods provide efficient tools to analyze high-throughput microarray dataset. According to the facts that different unsupervised approaches explore correlations in the high-dimensional data space and identify relevant subspace base on different hypotheses, integrating these methods to explore the underlying biological information from microarray dataset is an efficient approach. By combining the significant genes identified by both ICA and NMF, the biological analysis shows great efficient for elucidating the molecular taxonomy of Alzheimer’s disease and enable better experimental design to further identify potential pathways and therapeutic targets of AD.

2011-01-01

198

Exome sequencing identifies MPL as a causative gene in familial aplastic anemia.  

PubMed

The primary cause of aplastic anemia remains unknown in many patients. The aim of this study was to clarify the genetic cause of familial aplastic anemia. Genomic DNA of an affected individual from a multiplex consanguineous family was hybridized to a Nimblegen exome library before being sequenced on a GAIIx genome analyzer. Once the disease causing homozygous mutation had been confirmed in the consanguineous family, this gene was then analyzed for mutation in 33 uncharacterized index cases of aplastic anemia (<13 years) using denaturing HPLC. Abnormal traces were confirmed by direct sequencing. Exome sequencing identified a novel homozygous nonsense mutation in the thrombopoietin receptor gene MPL. An additional novel homozygous MPL mutation was identified in the screen of 33 aplastic anemia patients. This study shows for the first time a link between homozygous MPL mutations and familial aplastic anemia. It also highlights the important role of MPL in trilineage hematopoiesis. PMID:22180433

Walne, Amanda J; Dokal, Arran; Plagnol, Vincent; Beswick, Richard; Kirwan, Michael; de la Fuente, Josu; Vulliamy, Tom; Dokal, Inderjeet

2012-04-01

199

A computational bioinformatics analysis of gene expression identifies candidate agents for prostate cancer.  

PubMed

Prostate cancer is the second most frequently diagnosed cancer and the sixth leading cause of cancer death in males worldwide. Although great progress has been made, the molecular mechanisms of prostate cancer are far from being fully understood and treatment of this disease remains palliative. In this study, we sought to explore the molecular mechanism of prostate cancer and then identify biologically active small molecules capable of targeting prostate cancer using a computational bioinformatics analysis of gene expression. A total of 3068 genes, involved in cell communication, development, localisation and cell proliferation, were differentially expressed in prostate cancer samples compared with normal controls. Pathways associated with signal transduction, immune response and tumorigenesis were dysfunctional. Further, we identified a group of small molecules capable of reversing prostate cancer. These candidate agents may provide the groundwork for a combination therapy approach for prostate cancer. However, further evaluation for their potential use in the treatment of prostate cancer is still needed. PMID:23790256

Wen, D; Geng, J; Li, W; Guo, C; Zheng, J

2014-08-01

200

Identifying biological themes within lists of genes with EASE  

PubMed Central

EASE is a customizable software application for rapid biological interpretation of gene lists that result from the analysis of microarray, proteomics, SAGE, and other high-throughput genomic data. The biological themes returned by EASE recapitulate manually determined themes in previously published gene lists and are robust to varying methods of normalization, intensity calculation and statistical selection of genes. EASE is a powerful tool for rapidly converting the results of functional genomics studies from "genes to themes."

2003-01-01

201

Expressed sequences tags of the anther smut fungus, Microbotryum violaceum, identify mating and pathogenicity genes  

PubMed Central

Background The basidiomycete fungus Microbotryum violaceum is responsible for the anther-smut disease in many plants of the Caryophyllaceae family and is a model in genetics and evolutionary biology. Infection is initiated by dikaryotic hyphae produced after the conjugation of two haploid sporidia of opposite mating type. This study describes M. violaceum ESTs corresponding to nuclear genes expressed during conjugation and early hyphal production. Results A normalized cDNA library generated 24,128 sequences, which were assembled into 7,765 unique genes; 25.2% of them displayed significant similarity to annotated proteins from other organisms, 74.3% a weak similarity to the same set of known proteins, and 0.5% were orphans. We identified putative pheromone receptors and genes that in other fungi are involved in the mating process. We also identified many sequences similar to genes known to be involved in pathogenicity in other fungi. The M. violaceum EST database, MICROBASE, is available on the Web and provides access to the sequences, assembled contigs, annotations and programs to compare similarities against MICROBASE. Conclusion This study provides a basis for cloning the mating type locus, for further investigation of pathogenicity genes in the anther smut fungi, and for comparative genomics.

Yockteng, Roxana; Marthey, Sylvain; Chiapello, Helene; Gendrault, Annie; Hood, Michael E; Rodolphe, Francois; Devier, Benjamin; Wincker, Patrick; Dossat, Carole; Giraud, Tatiana

2007-01-01

202

Candidate genes affecting Drosophila life span identified by integrating microarray gene expression analysis and QTL mapping  

Microsoft Academic Search

The current increase in life expectancy observed in industrialized societies underscores the need to achieve a better understanding of the aging process that could help the development of effective strategies to achieve healthy aging. This will require not only identifying genes involved in the aging process, but also understanding how their effects are modulated by environmental factors, such as dietary

Chao-Qiang Lai; Laurence D. Parnell; Richard F. Lyman; Jose M. Ordovas; Trudy F. C. Mackay

2007-01-01

203

Prospects for gene therapy in Parkinson's disease.  

PubMed

Numerous advances in in vivo and ex vivo gene-therapy approaches to Parkinson's disease offer promise for direct clinical trials in patients in the next several years. These systems are predicated on introducing gene that encode enzymes responsible for dopamine biosynthesis or neurotrophic factors that may delay nigrostriatal degeneration or facilitate regeneration. We review the current status of experimental approaches to gene therapy for Parkinson's disease. Comparative advantages and disadvantages of each system are enumerated, and preclinical trials of some of the systems are evaluated. Although the specific in vivo or ex vivo methods used for gene transfer into the brain are likely to be supplanted by newer technology over the next decade, the principles and approaches developed in current studies likely will remain the same. PMID:8866488

Freese, A; Stern, M; Kaplitt, M G; O'Connor, W M; Abbey, M V; O'Connor, M J; During, M J

1996-09-01

204

Yeast Augmented Network Analysis (YANA): a new systems approach to identify therapeutic targets for human genetic diseases  

PubMed Central

Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets. Here we introduce our Yeast Augmented Network Analysis (YANA) approach and test it with the X-linked spinal muscular atrophy (SMA) disease gene UBA1. First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish) SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases.

Wiley, David J.; Juan, Ilona; Le, Hao; Cai, Xiaodong; Baumbach, Lisa; Beattie, Christine; D'Urso, Gennaro

2014-01-01

205

Gene-trap mutagenesis identifies mammalian genes contributing to intoxication by Clostridium perfringens ?-toxin.  

PubMed

The Clostridium perfringens ?-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ?-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ?-toxin, was used to select clones of cells resistant to ?-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ?-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ?-toxin-induced cytotoxicity. Additionally, ?-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ?-toxin induces cell death and new targets for potential therapeutic intervention. PMID:21412435

Ivie, Susan E; Fennessey, Christine M; Sheng, Jinsong; Rubin, Donald H; McClain, Mark S

2011-01-01

206

Gene-Trap Mutagenesis Identifies Mammalian Genes Contributing to Intoxication by Clostridium perfringens ?-Toxin  

PubMed Central

The Clostridium perfringens ?-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ?-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ?-toxin, was used to select clones of cells resistant to ?-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ?-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ?-toxin-induced cytotoxicity. Additionally, ?-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ?-toxin induces cell death and new targets for potential therapeutic intervention.

Ivie, Susan E.; Fennessey, Christine M.; Sheng, Jinsong; Rubin, Donald H.; McClain, Mark S.

2011-01-01

207

Progress in gene therapy of dystrophic heart disease  

PubMed Central

The heart is frequently afflicted in muscular dystrophy. In severe cases, cardiac lesion may directly result in death. Over the years, pharmacological and/or surgical interventions have been the mainstay to alleviate cardiac symptoms in muscular dystrophy patients. Although these traditional modalities remain useful, the emerging field of gene therapy has now provided an unprecedented opportunity to transform our thinking/approach in the treatment of dystrophic heart disease. In fact, the premise is already in place for genetic correction. Gene mutations have been identified and animal models are available for several types of muscular dystrophy. Most importantly, innovative strategies have been developed to effectively deliver therapeutic genes to the heart. Dystrophin-deficient Duchenne cardiomyopathy is associated with Duchenne muscular dystrophy (DMD), the most common lethal muscular dystrophy. Considering its high incidence, there has been a considerable interest and significant input in the development of Duchenne cardiomyopathy gene therapy. Using Duchenne cardiomyopathy as an example, here we illustrate the struggles and successes experienced in the burgeoning field of dystrophic heart disease gene therapy. In light of abundant and highly promising data with the adeno-associated virus (AAV) vector, we have specially emphasized on AAV-mediated gene therapy. Besides DMD, we have also discussed gene therapy for treating cardiac diseases in other muscular dystrophies such as limb-girdle muscular dystrophy.

Lai, Y; Duan, D

2013-01-01

208

Recessive Mutation Identifies Auxin-Repressed Protein ARP1, Which Regulates Growth and Disease Resistance in Tobacco.  

PubMed

To study the molecular mechanism that underpins crosstalk between plant growth and disease resistance, we performed a mutant screening on tobacco and created a recessive mutation that caused the phenotype of growth enhancement and resistance impairment (geri1). In the geri1 mutant, growth enhancement accompanies promoted expression of growth-promoting genes, whereas repressed expression of defense response genes is consistent with impaired resistance to diseases caused by viral, bacterial, and oomycete pathogens. The geri1 allele identifies a single genetic locus hypothetically containing the tagged GERI1 gene. The isolated GERI1 gene was predicted to encode auxin-repressed protein ARP1, which was determined to be 13.5 kDa in size. The ARP1/GERI1 gene was further characterized as a repressor of plant growth and an activator of disease resistance based on genetic complementation, gene silencing, and overexpression analyses. ARP1/GERI1 resembles pathogen-associated molecular patterns and is required for them to repress plant growth and activate plant immunity responses. ARP1/GERI1 represses growth by inhibiting the expression of AUXIN RESPONSE FACTOR gene ARF8, and ARP1/GERI1 recruits the NPR1 gene, which is essential for the salicylic-acid-mediated defense, to coregulate disease resistance. In conclusion, ARP1/GERI1 is an integral regulator for crosstalk between growth and disease resistance in the plant. PMID:24875793

Zhao, Yanying; Li, Cheng; Ge, Jun; Xu, Manyu; Zhu, Qian; Wu, Tingquan; Guo, An; Xie, Junyi; Dong, Hansong

2014-07-01

209

Transcriptome profiling to identify genes involved in pathogenicity of Valsa mali on apple tree.  

PubMed

Apple Valsa canker, caused by the fungus Valsa mali (Vm), is one of the most destructive diseases of apple in China. A better understanding of this host-pathogen interaction is urgently needed to improve management strategies. In the current study we sequenced the transcriptomes of Vm during infection of apple bark and mycelium grown in axenic culture using Illumina RNA-Seq technology. We identified 437 genes that were differentially expressed during fungal infection compared to fungal mycelium grown in axenic culture. One hundred and thirty nine of these 437 genes showed more than two fold higher transcript abundance during infection. GO and KEGG enrichment analyses of the up-regulated genes suggest prevalence of genes associated with pectin catabolic, hydrolase activity and secondary metabolite biosynthesis during fungal infection. Some of the up-regulated genes associated with loss of pathogenicity and reduced virulence annotated by host-pathogen interaction databases may also be involved in cell wall hydrolysis and secondary metabolite transport, including a glycoside hydrolase family 28 protein, a peptidase and two major facilitator superfamily proteins. This highlights the importance of secondary metabolites and cell wall hydrolases during establishment of apple Valsa canker. Functional verification of the genes involved in pathogenicity of Vm will allow us to better understand how the fungus interferes with the host machinery and assists in apple canker establishment. PMID:24747070

Ke, Xiwang; Yin, Zhiyuan; Song, Na; Dai, Qingqing; Voegele, Ralf T; Liu, Yangyang; Wang, Haiying; Gao, Xiaoning; Kang, Zhensheng; Huang, Lili

2014-07-01

210

Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimer's disease  

PubMed Central

Background High-throughput profiling of human tissues typically yield as results the gene lists comprised of a mix of relevant molecular entities with multiple false positives that obstruct the translation of such results into mechanistic hypotheses. From general probabilistic considerations, gene lists distilled for the mechanistically relevant components can be far more useful for subsequent experimental design or data interpretation. Results The input candidate gene lists were processed into different tiers of evidence consistency established by enrichment analysis across subsets of the same experiments and across different experiments and platforms. The cut-offs were established empirically through ontological and semantic enrichment; resultant shortened gene list was re-expanded by Ingenuity Pathway Assistant tool. The resulting sub-networks provided the basis for generating mechanistic hypotheses that were partially validated by literature search. This approach differs from previous consistency-based studies in that the cut-off on the Receiver Operating Characteristic of the true-false separation process is optimized by flexible selection of the consistency building procedure. The gene list distilled by this analytic technique and its network representation were termed Compact Disease Model (CDM). Here we present the CDM signature for the study of early-stage Alzheimer’s disease. The integrated analysis of this gene signature allowed us to identify the protein traffic vesicles as prominent players in the pathogenesis of Alzheimer’s. Considering the distances and complexity of protein trafficking in neurons, it is plausible that spontaneous protein misfolding along with a shortage of growth stimulation result in neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis have been discussed, with an emphasis on the protective effects of AT-1 mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Alignment with emerging literature confirmed many predictions derived from early-stage Alzheimer’s disease’ CDM. Conclusions A flexible approach for high-throughput data analysis, the Compact Disease Model generation, allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses.

2013-01-01

211

Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.  

PubMed

The identification of disease genes is very important not only to provide greater understanding of gene function and cellular mechanisms which drive human disease, but also to enhance human disease diagnosis and treatment. Recently, high-throughput techniques have been applied to detect dozens or even hundreds of candidate genes. However, experimental approaches to validate the many candidates are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Therefore, numerous theoretical and computational methods (e.g. network-based approaches) have been developed to prioritize candidate disease genes. Many network-based approaches implicitly utilize the observation that genes causing the same or similar diseases tend to correlate with each other in gene-protein relationship networks. Of these network approaches, the random walk with restart algorithm (RWR) is considered to be a state-of-the-art approach. To further improve the performance of RWR, we propose a novel method named ESFSC to identify disease-related genes, by enlarging the seed set according to the centrality of disease genes in a network and fusing information of the protein-protein interaction (PPI) network topological similarity and the gene expression correlation. The ESFSC algorithm restarts at all of the nodes in the seed set consisting of the known disease genes and their k-nearest neighbor nodes, then walks in the global network separately guided by the similarity transition matrix constructed with PPI network topological similarity properties and the correlational transition matrix constructed with the gene expression profiles. As a result, all the genes in the network are ranked by weighted fusing the above results of the RWR guided by two types of transition matrices. Comprehensive simulation results of the 10 diseases with 97 known disease genes collected from the Online Mendelian Inheritance in Man (OMIM) database show that ESFSC outperforms existing methods for prioritizing candidate disease genes. The top prediction results of Alzheimer's disease are consistent with previous literature reports. PMID:24695957

Zhang, Shao-Wu; Shao, Dong-Dong; Zhang, Song-Yao; Wang, Yi-Bin

2014-06-01

212

A large-scale analysis of tissue-specific pathology and gene expression of human disease genes and complexes  

PubMed Central

Heritable diseases are caused by germ-line mutations that, despite tissuewide presence, often lead to tissue-specific pathology. Here, we make a systematic analysis of the link between tissue-specific gene expression and pathological manifestations in many human diseases and cancers. Diseases were systematically mapped to tissues they affect from disease-relevant literature in PubMed to create a disease–tissue covariation matrix of high-confidence associations of >1,000 diseases to 73 tissues. By retrieving >2,000 known disease genes, and generating 1,500 disease-associated protein complexes, we analyzed the differential expression of a gene or complex involved in a particular disease in the tissues affected by the disease, compared with nonaffected tissues. When this analysis is scaled to all diseases in our dataset, there is a significant tendency for disease genes and complexes to be overexpressed in the normal tissues where defects cause pathology. In contrast, cancer genes and complexes were not overexpressed in the tissues from which the tumors emanate. We specifically identified a complex involved in XY sex reversal that is testis-specific and down-regulated in ovaries. We also identified complexes in Parkinson disease, cardiomyopathies, and muscular dystrophy syndromes that are similarly tissue specific. Our method represents a conceptual scaffold for organism-spanning analyses and reveals an extensive list of tissue-specific draft molecular pathways, both known and unexpected, that might be disrupted in disease.

Lage, Kasper; Hansen, Niclas Tue; Karlberg, E. Olof; Eklund, Aron C.; Roque, Francisco S.; Donahoe, Patricia K.; Szallasi, Zoltan; Jensen, Thomas Sk?t; Brunak, S?ren

2008-01-01

213

Gene Network Analysis in a Pediatric Cohort Identifies Novel Lung Function Genes  

PubMed Central

Lung function is a heritable trait and serves as an important clinical predictor of morbidity and mortality for pulmonary conditions in adults, however, despite its importance, no studies have focused on uncovering pediatric-specific loci influencing lung function. To identify novel genetic determinants of pediatric lung function, we conducted a genome-wide association study (GWAS) of four pulmonary function traits, including FVC, FEV1, FEV1/FVC and FEF25–75% in 1556 children. Further, we carried out gene network analyses for each trait including all SNPs with a P-value of <1.0×10?3 from the individual GWAS. The GWAS identified SNPs with notable trends towards association with the pulmonary function measures, including the previously described INTS12 locus association with FEV1 (pmeta?=?1.41×10?7). The gene network analyses identified 34 networks of genes associated with pulmonary function variables in Caucasians. Of those, the glycoprotein gene network reached genome-wide significance for all four variables. P-value range pmeta?=?6.29×10?4 - 2.80×10?8 on meta-analysis. In this study, we report on specific pathways that are significantly associated with pediatric lung function at genome-wide significance. In addition, we report the first loci associated with lung function in both pediatric Caucasian and African American populations.

McDonough, Joseph M.; Wei, Zhi; Kim, Cecilia; Chiavacci, Rosetta; Mentch, Frank; Caboot, Jason B.; Spergel, Jonathan; Allen, Julian L.; Sleiman, Patrick M. A.; Hakonarson, Hakon

2013-01-01

214

Gene Profiling of Mta1 Identifies Novel Gene Targets and Functions  

PubMed Central

Background Metastasis-associated protein 1 (MTA1), a master dual co-regulatory protein is found to be an integral part of NuRD (Nucleosome Remodeling and Histone Deacetylation) complex, which has indispensable transcriptional regulatory functions via histone deacetylation and chromatin remodeling. Emerging literature establishes MTA1 to be a valid DNA-damage responsive protein with a significant role in maintaining the optimum DNA-repair activity in mammalian cells exposed to genotoxic stress. This DNA-damage responsive function of MTA1 was reported to be a P53-dependent and independent function. Here, we investigate the influence of P53 on gene regulation function of Mta1 to identify novel gene targets and functions of Mta1. Methods Gene expression analysis was performed on five different mouse embryonic fibroblasts (MEFs) samples (i) the Mta1 wild type, (ii) Mta1 knock out (iii) Mta1 knock out in which Mta1 was reintroduced (iv) P53 knock out (v) P53 knock out in which Mta1 was over expressed using Affymetrix Mouse Exon 1.0 ST arrays. Further Hierarchical Clustering, Gene Ontology analysis with GO terms satisfying corrected p-value<0.1, and the Ingenuity Pathway Analysis were performed. Finally, RT-qPCR was carried out on selective candidate genes. Significance/Conclusion This study represents a complete genome wide screen for possible target genes of a coregulator, Mta1. The comparative gene profiling of Mta1 wild type, Mta1 knockout and Mta1 re-expression in the Mta1 knockout conditions define “bona fide” Mta1 target genes. Further extensive analyses of the data highlights the influence of P53 on Mta1 gene regulation. In the presence of P53 majority of the genes regulated by Mta1 are related to inflammatory and anti-microbial responses whereas in the absence of P53 the predominant target genes are involved in cancer signaling. Thus, the presented data emphasizes the known functions of Mta1 and serves as a rich resource which could help us identify novel Mta1 functions.

Eswaran, Jeyanthy; Kumar, Rakesh

2011-01-01

215

Genomic analysis of primordial dwarfism reveals novel disease genes.  

PubMed

Primordial dwarfism (PD) is a disease in which severely impaired fetal growth persists throughout postnatal development and results in stunted adult size. The condition is highly heterogeneous clinically, but the use of certain phenotypic aspects such as head circumference and facial appearance has proven helpful in defining clinical subgroups. In this study, we present the results of clinical and genomic characterization of 16 new patients in whom a broad definition of PD was used (e.g., 3M syndrome was included). We report a novel PD syndrome with distinct facies in two unrelated patients, each with a different homozygous truncating mutation in CRIPT. Our analysis also reveals, in addition to mutations in known PD disease genes, the first instance of biallelic truncating BRCA2 mutation causing PD with normal bone marrow analysis. In addition, we have identified a novel locus for Seckel syndrome based on a consanguineous multiplex family and identified a homozygous truncating mutation in DNA2 as the likely cause. An additional novel PD disease candidate gene XRCC4 was identified by autozygome/exome analysis, and the knockout mouse phenotype is highly compatible with PD. Thus, we add a number of novel genes to the growing list of PD-linked genes, including one which we show to be linked to a novel PD syndrome with a distinct facial appearance. PD is extremely heterogeneous genetically and clinically, and genomic tools are often required to reach a molecular diagnosis. PMID:24389050

Shaheen, Ranad; Faqeih, Eissa; Ansari, Shinu; Abdel-Salam, Ghada; Al-Hassnan, Zuhair N; Al-Shidi, Tarfa; Alomar, Rana; Sogaty, Sameera; Alkuraya, Fowzan S

2014-02-01

216

A cross-species transcriptomics approach to identify genes involved in leaf development  

Microsoft Academic Search

BACKGROUND: We have made use of publicly available gene expression data to identify transcription factors and transcriptional modules (regulons) associated with leaf development in Populus. Different tissue types were compared to identify genes informative in the discrimination of leaf and non-leaf tissues. Transcriptional modules within this set of genes were identified in a much wider set of microarray data collected

Nathaniel Robert Street; Max Bylesjö; Petter Gustafsson; Johan Trygg; Stefan Jansson

2008-01-01

217

Genome Wide Transcriptome Analysis of Dendritic Cells Identifies Genes with Altered Expression in Psoriasis  

PubMed Central

Activation of dendritic cells by different pathogens induces the secretion of proinflammatory mediators resulting in local inflammation. Importantly, innate immunity must be properly controlled, as its continuous activation leads to the development of chronic inflammatory diseases such as psoriasis. Lipopolysaccharide (LPS) or peptidoglycan (PGN) induced tolerance, a phenomenon of transient unresponsiveness of cells to repeated or prolonged stimulation, proved valuable model for the study of chronic inflammation. Thus, the aim of this study was the identification of the transcriptional diversity of primary human immature dendritic cells (iDCs) upon PGN induced tolerance. Using SAGE-Seq approach, a tag-based transcriptome sequencing method, we investigated gene expression changes of primary human iDCs upon stimulation or restimulation with Staphylococcus aureus derived PGN, a widely used TLR2 ligand. Based on the expression pattern of the altered genes, we identified non-tolerizeable and tolerizeable genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (Kegg) analysis showed marked enrichment of immune-, cell cycle- and apoptosis related genes. In parallel to the marked induction of proinflammatory mediators, negative feedback regulators of innate immunity, such as TNFAIP3, TNFAIP8, Tyro3 and Mer are markedly downregulated in tolerant cells. We also demonstrate, that the expression pattern of TNFAIP3 and TNFAIP8 is altered in both lesional, and non-lesional skin of psoriatic patients. Finally, we show that pretreatment of immature dendritic cells with anti-TNF-? inhibits the expression of IL-6 and CCL1 in tolerant iDCs and partially releases the suppression of TNFAIP8. Our findings suggest that after PGN stimulation/restimulation the host cell utilizes different mechanisms in order to maintain critical balance between inflammation and tolerance. Importantly, the transcriptome sequencing of stimulated/restimulated iDCs identified numerous genes with altered expression to date not associated with role in chronic inflammation, underlying the relevance of our in vitro model for further characterization of IFN-primed iDCs.

Szasz, Andras; Tubak, Vilmos; Kemeny, Lajos; Kondorosi, Eva; Nagy, Istvan

2013-01-01

218

A functional screen for copper homeostasis genes identifies a pharmacologically tractable cellular system  

PubMed Central

Background Copper is essential for the survival of aerobic organisms. If copper is not properly regulated in the body however, it can be extremely cytotoxic and genetic mutations that compromise copper homeostasis result in severe clinical phenotypes. Understanding how cells maintain optimal copper levels is therefore highly relevant to human health. Results We found that addition of copper (Cu) to culture medium leads to increased respiratory growth of yeast, a phenotype which we then systematically and quantitatively measured in 5050 homozygous diploid deletion strains. Cu’s positive effect on respiratory growth was quantitatively reduced in deletion strains representing 73 different genes, the function of which identify increased iron uptake as a cause of the increase in growth rate. Conversely, these effects were enhanced in strains representing 93 genes. Many of these strains exhibited respiratory defects that were specifically rescued by supplementing the growth medium with Cu. Among the genes identified are known and direct regulators of copper homeostasis, genes required to maintain low vacuolar pH, and genes where evidence supporting a functional link with Cu has been heretofore lacking. Roughly half of the genes are conserved in man, and several of these are associated with Mendelian disorders, including the Cu-imbalance syndromes Menkes and Wilson’s disease. We additionally demonstrate that pharmacological agents, including the approved drug disulfiram, can rescue Cu-deficiencies of both environmental and genetic origin. Conclusions A functional screen in yeast has expanded the list of genes required for Cu-dependent fitness, revealing a complex cellular system with implications for human health. Respiratory fitness defects arising from perturbations in this system can be corrected with pharmacological agents that increase intracellular copper concentrations.

2014-01-01

219

Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease  

PubMed Central

We densely genotyped, using 1000 Genomes Project pilot CEU and additional re-sequencing study variants, 183 reported immune-mediated disease non-HLA risk loci in 12,041 celiac disease cases and 12,228 controls. We identified 13 new celiac disease risk loci at genome wide significance, bringing the total number of known loci (including HLA) to 40. Multiple independent association signals are found at over a third of these loci, attributable to a combination of common, low frequency, and rare genetic variants. In comparison with previously available data such as HapMap3, our dense genotyping in a large sample size provided increased resolution of the pattern of linkage disequilibrium, and suggested localization of many signals to finer scale regions. In particular, 29 of 54 fine-mapped signals appeared localized to specific single genes - and in some instances to gene regulatory elements. We define a complex genetic architecture of risk regions, and refine risk signals, providing a next step towards elucidating causal disease mechanisms.

Trynka, Gosia; Hunt, Karen A; Bockett, Nicholas A; Romanos, Jihane; Mistry, Vanisha; Szperl, Agata; Bakker, Sjoerd F; Bardella, Maria Teresa; Bhaw-Rosun, Leena; Castillejo, Gemma; de la Concha, Emilio G.; de Almeida, Rodrigo Coutinho; Dias, Kerith-Rae M; van Diemen, Cleo C.; Dubois, Patrick CA; Duerr, Richard H.; Edkins, Sarah; Franke, Lude; Fransen, Karin; Gutierrez, Javier; Heap, Graham AR; Hrdlickova, Barbara; Hunt, Sarah; Izurieta, Leticia Plaza; Izzo, Valentina; Joosten, Leo AB; Langford, Cordelia; Mazzilli, Maria Cristina; Mein, Charles A; Midah, Vandana; Mitrovic, Mitja; Mora, Barbara; Morelli, Marinita; Nutland, Sarah; Nunez, Concepcion; Onengut-Gumuscu, Suna; Pearce, Kerra; Platteel, Mathieu; Polanco, Isabel; Potter, Simon; Ribes-Koninckx, Carmen; Ricano-Ponce, Isis; Rich, Stephen S.; Rybak, Anna; Santiago, Jose Luis; Senapati, Sabyasachi; Sood, Ajit; Szajewska, Hania; Troncone, Riccardo; Varade, Jezabel; Wallace, Chris; Wolters, Victorien M; Zhernakova, Alexandra; Thelma, B.K.; Cukrowska, Bozena; Urcelay, Elena; Bilbao, Jose Ramon; Mearin, M Luisa; Barisani, Donatella; Barrett, Jeffrey C; Plagnol, Vincent; Deloukas, Panos; Wijmenga, Cisca; van Heel, David A

2011-01-01

220

Prion disease induced alterations in gene expression in spleen and brain prior to clinical symptoms  

Microsoft Academic Search

Prion diseases are fatal neurodegenerative disorders that affect animals and humans. There is a need to gain understanding of prion disease pathogenesis and to develop diagnostic assays to detect prion diseases prior to the onset of clinical symptoms. The goal of this study was to identify genes that show altered expression early in the disease process in the spleen and

Hyeon O Kim; Greg P Snyder; Tyler M Blazey; Richard E Race; Bruce Chesebro; Pamela J Skinner

221

Bacteroides fragilis enterotoxin gene sequences in patients with inflammatory bowel disease.  

PubMed Central

We identified enterotoxigenic Bacteroides fragilis in stool specimens of patients with inflammatory bowel disease and other gastrointestinal disorders. The organism was detected in 11 (13.2%) of 83 patients with inflammatory bowel disease. Of 57 patients with active disease, 19.3% were toxin positive; none of those with inactive disease had specimens positive for enterotoxigenic Bacteroides fragilis gene sequences.

Prindiville, T. P.; Sheikh, R. A.; Cohen, S. H.; Tang, Y. J.; Cantrell, M. C.; Silva, J.

2000-01-01

222

Functional gene group analysis identifies synaptic gene groups as risk factor for schizophrenia.  

PubMed

Schizophrenia is a highly heritable disorder with a polygenic pattern of inheritance and a population prevalence of ~1%. Previous studies have implicated synaptic dysfunction in schizophrenia. We tested the accumulated association of genetic variants in expert-curated synaptic gene groups with schizophrenia in 4673 cases and 4965 healthy controls, using functional gene group analysis. Identifying groups of genes with similar cellular function rather than genes in isolation may have clinical implications for finding additional drug targets. We found that a group of 1026 synaptic genes was significantly associated with the risk of schizophrenia (P=7.6 × 10(-11)) and more strongly associated than 100 randomly drawn, matched control groups of genetic variants (P<0.01). Subsequent analysis of synaptic subgroups suggested that the strongest association signals are derived from three synaptic gene groups: intracellular signal transduction (P=2.0 × 10(-4)), excitability (P=9.0 × 10(-4)) and cell adhesion and trans-synaptic signaling (P=2.4 × 10(-3)). These results are consistent with a role of synaptic dysfunction in schizophrenia and imply that impaired intracellular signal transduction in synapses, synaptic excitability and cell adhesion and trans-synaptic signaling play a role in the pathology of schizophrenia. PMID:21931320

Lips, E S; Cornelisse, L N; Toonen, R F; Min, J L; Hultman, C M; Holmans, P A; O'Donovan, M C; Purcell, S M; Smit, A B; Verhage, M; Sullivan, P F; Visscher, P M; Posthuma, D

2012-10-01

223

Two major genes, linked to HLA and Gm, control susceptibility to Graves' disease  

Microsoft Academic Search

Graves' disease is a multifactorial disease in which immunogenetic as well as environmental factors have important roles. Recently, cumulative evidence has shown that genes controlling immune responses are linked to the MHC (major histocompatibility complex)1 and\\/or immunoglobulin allotype genes2,3. To identify the genes governing susceptibility to Graves' disease, we have studied 30 Japanese families where more than two first degree

Hisamitsu Uno; Takehiko Sasazuki; Hajime Tamai; Hideo Matsumoto

1981-01-01

224

Sleeping Beauty Plays a Significant Role in Identifying Cancer Genes  

Cancer.gov

Researchers at the University of Minnesota Cancer Center and the National Cancer Institute (NCI), part of the National Institutes of Health, have discovered a new method that could accelerate the way cancer-causing genes are found and could lead to a more accurate identification of the genes

225

Identification of Sequence Variants in Genetic Disease-Causing Genes Using Targeted Next-Generation Sequencing  

Microsoft Academic Search

BackgroundIdentification of gene variants plays an important role in research on and diagnosis of genetic diseases. A combination of enrichment of targeted genes and next-generation sequencing (targeted DNA-HiSeq) results in both high efficiency and low cost for targeted sequencing of genes of interest.Methodology\\/Principal FindingsTo identify mutations associated with genetic diseases, we designed an array-based gene chip to capture all of

Xiaoming Wei; Xiangchun Ju; Xin Yi; Qian Zhu; Ning Qu; Tengfei Liu; Yang Chen; Hui Jiang; Guanghui Yang; Ruan Zhen; Zhangzhang Lan; Ming Qi; Jinming Wang; Yi Yang; Yuxing Chu; Xiaoyan Li; Yanfang Guang; Jian Huang

2011-01-01

226

Weighted gene co-expression network analysis identifies biomarkers in glycerol kinase deficient mice.  

PubMed

Symptomatic glycerol kinase deficiency (GKD) is associated with episodic metabolic and central nervous system deterioration. We report here the first application of weighted gene co-expression network analysis (WGCNA) to investigate a knockout (KO) murine model of a human genetic disease. WGCNA identified networks and key hub transcripts from liver mRNA of glycerol kinase (Gyk) KO and wild-type (WT) mice. Day of life 1 (dol1) samples from KO mice contained a network module enriched for organic acid metabolism before Gyk KO mice develop organic acidemia and die on dol3-4. Furthermore, the module containing Gyk was enriched with apoptotic genes. We used causal testing to elucidate the causal relationships between intramodular hub genes Acot, Psat and Plk3. Important causal relationships are confirmed in cell cultures. We provide evidence that GK may have an apoptotic moonlighting role that is lost in GKD. This first application of WGCNA to mouse knockout data provides insights into the molecular mechanisms of GKD pathogenesis. The resulting systems-genetic gene screening method identifies candidate biomarkers for GKD. PMID:19546021

MacLennan, Nicole K; Dong, Jun; Aten, Jason E; Horvath, Steve; Rahib, Lola; Ornelas, Loren; Dipple, Katrina M; McCabe, Edward R B

2009-01-01

227

Seven newly identified loci for autoimmune thyroid disease.  

PubMed

Autoimmune thyroid disease (AITD), including Graves' disease (GD) and Hashimoto's thyroiditis (HT), is one of the most common of the immune-mediated diseases. To further investigate the genetic determinants of AITD, we conducted an association study using a custom-made single-nucleotide polymorphism (SNP) array, the ImmunoChip. The SNP array contains all known and genotype-able SNPs across 186 distinct susceptibility loci associated with one or more immune-mediated diseases. After stringent quality control, we analysed 103 875 common SNPs (minor allele frequency >0.05) in 2285 GD and 462 HT patients and 9364 controls. We found evidence for seven new AITD risk loci (P < 1.12 × 10(-6); a permutation test derived significance threshold), five at locations previously associated and two at locations awaiting confirmation, with other immune-mediated diseases. PMID:22922229

Cooper, Jason D; Simmonds, Matthew J; Walker, Neil M; Burren, Oliver; Brand, Oliver J; Guo, Hui; Wallace, Chris; Stevens, Helen; Coleman, Gillian; Franklyn, Jayne A; Todd, John A; Gough, Stephen C L

2012-12-01

228

Approaches for Recognizing Disease Genes Based on Network  

PubMed Central

Diseases are closely related to genes, thus indicating that genetic abnormalities may lead to certain diseases. The recognition of disease genes has long been a goal in biology, which may contribute to the improvement of health care and understanding gene functions, pathways, and interactions. However, few large-scale gene-gene association datasets, disease-disease association datasets, and gene-disease association datasets are available. A number of machine learning methods have been used to recognize disease genes based on networks. This paper states the relationship between disease and gene, summarizes the approaches used to recognize disease genes based on network, analyzes the core problems and challenges of the methods, and outlooks future research direction.

Zou, Quan; Li, Jinjin; Wang, Chunyu; Zeng, Xiangxiang

2014-01-01

229

Microarray analysis of hepatic gene expression identifies new genes involved in steatotic liver.  

PubMed

Trans-10, cis-12-conjugated linoleic acid (CLA)-enriched diets promote fatty liver in mice, while cis-9, trans-11-CLA ameliorates this effect, suggesting regulation of multiple genes. To test this hypothesis, apoE-deficient mice were fed a Western-type diet enriched with linoleic acid isomers, and their hepatic gene expression was analyzed with DNA microarrays. To provide an initial screening of candidate genes, only 12 with remarkably modified expression between both CLA isomers were considered and confirmed by quantitative RT-PCR. Additionally mRNA expression of 15 genes involved in lipid metabolism was also studied. Ten genes (Fsp27, Aqp4, Cd36, Ly6d, Scd1, Hsd3b5, Syt1, Cyp7b1, and Tff3) showed significant associations among their expressions and the degree of hepatic steatosis. Their involvement was also analyzed in other models of steatosis. In hyperhomocysteinemic mice lacking Cbs gene, only Fsp27, Cd36, Scd1, Syt1, and Hsd3b5 hepatic expressions were associated with steatosis. In apoE-deficient mice consuming olive-enriched diet displaying reduction of the fatty liver, only Fsp27 and Syt1 expressions were found associated. Using this strategy, we have shown that expression of these genes is highly associated with hepatic steatosis in a genetic disease such as Cbs deficiency and in two common situations such as Western diets containing CLA isomers or a Mediterranean-type diet. Conclusion: The results highlight new processes involved in lipid handling in liver and will help to understand the complex human pathology providing new proteins and new strategies to cope with hepatic steatosis. PMID:19258494

Guillén, Natalia; Navarro, María A; Arnal, Carmen; Noone, Enda; Arbonés-Mainar, José M; Acín, Sergio; Surra, Joaquín C; Muniesa, Pedro; Roche, Helen M; Osada, Jesús

2009-05-13

230

New VMD2 gene mutations identified in patients affected by Best vitelliform macular dystrophy  

PubMed Central

Purpose The mutations responsible for Best vitelliform macular dystrophy (BVMD) are found in a gene called VMD2. The VMD2 gene encodes a transmembrane protein named bestrophin?1 (hBest1) which is a Ca2+?sensitive chloride channel. This study was performed to identify disease?specific mutations in 27 patients with BVMD. Because this disease is characterised by an alteration in Cl? channel function, patch clamp analysis was used to test the hypothesis that one of the VMD2 mutated variants causes the disease. Methods Direct sequencing analysis of the 11 VMD2 exons was performed to detect new abnormal sequences. The mutant of hBest1 was expressed in HEK?293 cells and the associated Cl? current was examined using whole?cell patch clamp analysis. Results Six new VMD2 mutations were identified, located exclusively in exons four, six and eight. One of these mutations (Q293H) was particularly severe. Patch clamp analysis of human embryonic kidney cells expressing the Q293H mutant showed that this mutant channel is non?functional. Furthermore, the Q293H mutant inhibited the function of wild?type bestrophin?1 channels in a dominant negative manner. Conclusions This study provides further support for the idea that mutations in VMD2 are a necessary factor for Best disease. However, because variable expressivity of VMD2 was observed in a family with the Q293H mutation, it is also clear that a disease?linked mutation in VMD2 is not sufficient to produce BVMD. The finding that the Q293H mutant does not form functional channels in the membrane could be explained either by disruption of channel conductance or gating mechanisms or by improper trafficking of the protein to the plasma membrane.

Marchant, D; Yu, K; Bigot, K; Roche, O; Germain, A; Bonneau, D; Drouin-Garraud, V; Schorderet, D F; Munier, F; Schmidt, D; Neindre, P Le; Marsac, C; Menasche, M; Dufier, J L; Fischmeister, R; Hartzell, C; Abitbol, M

2007-01-01

231

B.E.A.R. GeneInfo: A tool for identifying gene-related biomedical publications through user modifiable queries  

PubMed Central

Background Once specific genes are identified through high throughput genomics technologies there is a need to sort the final gene list to a manageable size for validation studies. The triaging and sorting of genes often relies on the use of supplemental information related to gene structure, metabolic pathways, and chromosomal location. Yet in disease states where the genes may not have identifiable structural elements, poorly defined metabolic pathways, or limited chromosomal data, flexible systems for obtaining additional data are necessary. In these situations having a tool for searching the biomedical literature using the list of identified genes while simultaneously defining additional search terms would be useful. Results We have built a tool, BEAR GeneInfo, that allows flexible searches based on the investigators knowledge of the biological process, thus allowing for data mining that is specific to the scientist's strengths and interests. This tool allows a user to upload a series of GenBank accession numbers, Unigene Ids, Locuslink Ids, or gene names. BEAR GeneInfo takes these IDs and identifies the associated gene names, and uses the lists of gene names to query PubMed. The investigator can add additional modifying search terms to the query. The subsequent output provides a list of publications, along with the associated reference hyperlinks, for reviewing the identified articles for relevance and interest. An example of the use of this tool in the study of human prostate cancer cells treated with Selenium is presented. Conclusions This tool can be used to further define a list of genes that have been identified through genomic or genetic studies. Through the use of targeted searches with additional search terms the investigator can limit the list to genes that match their specific research interests or needs. The tool is freely available on the web at [1], and the authors will provide scripts and database components if requested mdatta@mcw.edu

Zhou, Guohui; Wen, Xinyu; Liu, Hang; Schlicht, Michael J; Hessner, Martin J; Tonellato, Peter J; Datta, Milton W

2004-01-01

232

A novel homozygous mutation in SUCLA2 gene identified by exome sequencing  

PubMed Central

Mitochondrial disorders with multiple mitochondrial respiratory chain (MRC) enzyme deficiency and depletion of mitochondrial DNA (mtDNA) are autosomal recessive conditions due to mutations in several nuclear genes necessary for proper mtDNA maintenance. In this report, we describe two Italian siblings presenting with encephalomyopathy and mtDNA depletion in muscle. By whole exome-sequencing and prioritization of candidate genes, we identified a novel homozygous missense mutation in the SUCLA2 gene in a highly conserved aminoacid residue. Although a recurrent mutation in the SUCLA2 gene is relatively frequent in the Faroe Islands, mutations in other populations are extremely rare. In contrast with what has been reported in other patients, methyl-malonic aciduria, a biomarker for this genetic defect, was absent in our proband and very mildly elevated in her affected sister. This report demonstrates that next-generation technologies, particularly exome-sequencing, are user friendly, powerful means for the identification of disease genes in genetically and clinically heterogeneous inherited conditions, such as mitochondrial disorders.

Lamperti, Costanza; Fang, Mingyan; Invernizzi, Federica; Liu, Xuanzhu; Wang, Hairong; Zhang, Qing; Carrara, Franco; Moroni, Isabella; Zeviani, Massimo; Zhang, Jianguo; Ghezzi, Daniele

2012-01-01

233

Functional genomics in rat models of hypertension: using differential expression and congenic strains to identify and evaluate candidate genes.  

PubMed

Hypertension is a leading contributor to cardiovascular diseases such as heart attack and stroke. Genetic and environmental factors contribute to the development of hypertension. Animal models have been developed to study the genetic contributions to blood pressure (BP) regulation and to identify chromosomal regions harboring candidate genes causative of differences in BP regulation (i.e., BP quantitative trait loci [QTL]). Advances in both mammalian genome projects and global gene expression analysis present opportunities to study functional genomics in these animal models. In this article, novel approaches for designing experiments and interpreting global gene expression data using the Dahl salt-sensitive hypertension rat model are presented. We describe two-step screening protocols that can be used to identify BP QTL candidate genes. Genetically determined expression differences are identified in the target organs of inbred strains of contrasting phenotype in the first screen. Expression patterns in a panel of congenic strains or expression differences stemming from gene x environment interactions are examined in the second screen. Chromosomal locations of these genes can then be examined to determine whether they map to BP QTL-containing regions. Another approach is to study the expression of genes identified from public databases to be located within BP QTL-containing congenic regions. Several candidate genes have been identified using these strategies. PMID:12641397

Lee, Soon Jin; Cicila, George T

2002-01-01

234

Identification of human disease genes from interactome network using graphlet interaction.  

PubMed

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Wang, Xiao-Dong; Huang, Jia-Liang; Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

235

Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease  

PubMed Central

Background Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p?=?1.4×10?6) and 14 (IGHV1-67 p?=?7.9×10?8) which indexed novel susceptibility loci. Significance The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

Harold, Denise; Jones, Lesley; Holmans, Peter; Gerrish, Amy; Vedernikov, Alexey; Richards, Alexander; DeStefano, Anita L.; Lambert, Jean-Charles; Ibrahim-Verbaas, Carla A.; Naj, Adam C.; Sims, Rebecca; Jun, Gyungah; Bis, Joshua C.; Beecham, Gary W.; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A.; Denning, Nicola; Smith, Albert V.; Chouraki, Vincent; Thomas, Charlene; Ikram, M. Arfan; Zelenika, Diana; Vardarajan, Badri N.; Kamatani, Yoichiro; Lin, Chiao-Feng; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L.; Vronskaya, Maria; Johnson, Andrew D.; Ruiz, Agustin; Bihoreau, Marie-Therese; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Hanon, Olivier; Fitzpatrick, Annette L.; Buxbaum, Joseph D.; Campion, Dominique; Crane, Paul K.; Baldwin, Clinton; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L.; De Jager, Philip L.; Deramecourt, Vincent; Johnston, Janet A.; Evans, Denis; Lovestone, Simon; Letenneur, Luc; Hernandez, Isabel; Rubinsztein, David C.; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M.; Fievet, Nathalie; Huentelman, Matthew J.; Gill, Michael; Brown, Kristelle; Kamboh, M. Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B.; Myers, Amanda J.; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Rogaeva, Ekaterina; Gallacher, John; George-Hyslop, Peter St; Clarimon, Jordi; Lleo, Alberto; Bayer, Anthony; Tsuang, Debby W.; Yu, Lei; Tsolaki, Magda; Bossu, Paola; Spalletta, Gianfranco; Proitsi, Petra; Collinge, John; Sorbi, Sandro; Garcia, Florentino Sanchez; Fox, Nick C.; Hardy, John; Naranjo, Maria Candida Deniz; Bosco, Paolo; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Scarpini, Elio; Bonuccelli, Ubaldo; Mancuso, Michelangelo; Siciliano, Gabriele; Moebus, Susanne; Mecocci, Patrizia; Zompo, Maria Del; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Frank-Garcia, Ana; Panza, Francesco; Solfrizzi, Vincenzo; Caffarra, Paolo; Nacmias, Benedetta; Perry, William; Mayhaus, Manuel; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M.; Ingelsson, Martin; Beekly, Duane; Alvarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G.; Coto, Eliecer; Hamilton-Nelson, Kara L.; Gu, Wei; Razquin, Cristina; Pastor, Pau; Mateo, Ignacio; Owen, Michael J.; Faber, Kelley M.; Jonsson, Palmi V.; Combarros, Onofre; O'Donovan, Michael C.; Cantwell, Laura B.; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H.; Bennett, David A.; Harris, Tamara B.; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee F. A. G.; Passmore, Peter; Montine, Thomas J.; Bettens, Karolien; Rotter, Jerome I.; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M.; Kukull, Walter A.; Hannequin, Didier; Powell, John F.; Nalls, Michael A.; Ritchie, Karen; Lunetta, Kathryn L.; Kauwe, John S. K.; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Merce; Hiltunen, Mikko; Martin, Eden R.; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-Francois; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nothen, Markus M.; Graff, Caroline; Psaty, Bruce M.; Haines, Jonathan L.; Lathrop, Mark; Pericak-Vance, Margaret A.; Launer, Lenore J.; Van Broeckhoven, Christine; Farrer, Lindsay A.; van Duijn, Cornelia M.; Ramirez, Alfredo

2014-01-01

236

Systems Approaches to Identifying Gene Regulatory Networks in Plants  

PubMed Central

Complex gene regulatory networks are composed of genes, noncoding RNAs, proteins, metabolites, and signaling components. The availability of genome-wide mutagenesis libraries; large-scale transcriptome, proteome, and metabalome data sets; and new high-throughput methods that uncover protein interactions underscores the need for mathematical modeling techniques that better enable scientists to synthesize these large amounts of information and to understand the properties of these biological systems. Systems biology approaches can allow researchers to move beyond a reductionist approach and to both integrate and comprehend the interactions of multiple components within these systems. Descriptive and mathematical models for gene regulatory networks can reveal emergent properties of these plant systems. This review highlights methods that researchers are using to obtain large-scale data sets, and examples of gene regulatory networks modeled with these data. Emergent properties revealed by the use of these network models and perspectives on the future of systems biology are discussed.

Long, Terri A.; Brady, Siobhan M.; Benfey, Philip N.

2009-01-01

237

Three clinical variants of gastroesophageal reflux disease form two distinct gene expression signatures  

Microsoft Academic Search

It has been proposed recently that gastroesophageal reflux disease (GERD) patients may be categorized into three distinct groups exhibiting non-erosive reflux disease (NERD), erosive reflux disease (ERD), and Barrett’s esophagus (BE). Measurement of relative gene expression levels was undertaken to identify distinct molecular subclasses in different variants of gastroesophageal disease. The measurements were made with Affymetrix U133A 2.0 GeneChips and

Jerzy Ostrowski; Tymon Rubel; Lucjan S. Wyrwicz; Michal Mikula; Andrzej Bielasik; Eugeniusz Butruk; Jaroslaw Regula

2006-01-01

238

FROM GENES TO PHENOTYPE IN A FLY: A DEFICIENCY SCREEN TO IDENTIFY GENE REGIONS AFFECTING FEMALE FERTILITY IN DROSOPHILA MELANOGASTER  

NSDL National Science Digital Library

This series of laboratory exercises engages students in the scholarship of discovery by having them conduct a deficiency screen to identify genes affecting Drosophila female fertility. Students are also introduced to bioinformatics as they use FlyBase to identify genes within a deficiency region and develop hypotheses regarding specific gene effects on female sperm storage.

PhD Margaret C Bloch-Qazi (Gustavus Adolphus College Biology)

2009-01-28

239

Systems analysis of inflammatory bowel disease based on comprehensive gene information  

PubMed Central

Background The rise of systems biology and availability of highly curated gene and molecular information resources has promoted a comprehensive approach to study disease as the cumulative deleterious function of a collection of individual genes and networks of molecules acting in concert. These "human disease networks" (HDN) have revealed novel candidate genes and pharmaceutical targets for many diseases and identified fundamental HDN features conserved across diseases. A network-based analysis is particularly vital for a study on polygenic diseases where many interactions between molecules should be simultaneously examined and elucidated. We employ a new knowledge driven HDN gene and molecular database systems approach to analyze Inflammatory Bowel Disease (IBD), whose pathogenesis remains largely unknown. Methods and Results Based on drug indications for IBD, we determined sibling diseases of mild and severe states of IBD. Approximately 1,000 genes associated with the sibling diseases were retrieved from four databases. After ranking the genes by the frequency of records in the databases, we obtained 250 and 253 genes highly associated with the mild and severe IBD states, respectively. We then calculated functional similarities of these genes with known drug targets and examined and presented their interactions as PPI networks. Conclusions The results demonstrate that this knowledge-based systems approach, predicated on functionally similar genes important to sibling diseases is an effective method to identify important components of the IBD human disease network. Our approach elucidates a previously unknown biological distinction between mild and severe IBD states.

2012-01-01

240

Genome-wide association study and mouse model identify interaction between RET and EDNRB pathways in Hirschsprung disease  

Microsoft Academic Search

Genetic studies of Hirschsprung disease, a common congenital malformation, have identified eight genes with mutations that can be associated with this condition. Mutations at individual loci are, however, neither necessary nor sufficient to cause clinical disease. We conducted a genome-wide association study in 43 Mennonite family trios using 2,083 microsatellites and single-nucleotide polymorphisms and a new multipoint linkage disequilibrium method

Minerva M. Carrasquillo; Andrew S. McCallion; Erik G. Puffenberger; Carl S. Kashuk; Nassim Nouri; Aravinda Chakravarti

2002-01-01

241

A Two-Stage Meta-Analysis Identifies Several New Loci for Parkinson's Disease  

PubMed Central

A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson's Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson's disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p<5×10?10, PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n?=?399) and methylation (n?=?292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loci.

2011-01-01

242

Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease  

PubMed Central

More than a thousand disease susceptibility loci have been identified via genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings generally remain to be defined. We utilize pooled next-generation sequencing to study 56 genes in regions associated to Crohn’s Disease in 350 cases and 350 controls. Follow up genotyping of 70 rare and low-frequency protein-altering variants (MAF ~ .001-.05) in nine independent case-control series (16054 CD patients, 12153 UC patients, 17575 healthy controls) identifies four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association to a novel, protective splice variant in CARD9 (p < 1e-16, OR ~ 0.29), as well as additional associations to coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by providing novel, rare, and likely functional variants that will empower functional experiments and predictive models.

Rivas, Manuel A.; Beaudoin, Melissa; Gardet, Agnes; Stevens, Christine; Sharma, Yashoda; Zhang, Clarence K.; Boucher, Gabrielle; Ripke, Stephan; Ellinghaus, David; Burtt, Noel; Fennell, Tim; Kirby, Andrew; Latiano, Anna; Goyette, Philippe; Green, Todd; Halfvarson, Jonas; Haritunians, Talin; Korn, Joshua M.; Kuruvilla, Finny; Lagace, Caroline; Neale, Benjamin; Lo, Ken Sin; Schumm, Phil; Torkvist, Leif; Dubinsky, Marla; Brant, Steven R.; Silverberg, Mark; Duerr, Richard H.; Altshuler, David; Gabriel, Stacey; Lettre, Guillaume; Franke, Andre; D'Amato, Mauro; McGovern, Dermot P.B.; Cho, Judy H.; Rioux, John D.; Xavier, Ramnik J.; Daly, Mark J.

2012-01-01

243

Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease  

Microsoft Academic Search

Genes and mechanisms involved in common complex diseases, such as the autoimmune disorders that affect approximately 5% of the population, remain obscure. Here we identify polymorphisms of the cytotoxic T lymphocyte antigen 4 gene (CTLA4)-which encodes a vital negative regulatory molecule of the immune system-as candidates for primary determinants of risk of the common autoimmune disorders Graves' disease, autoimmune hypothyroidism

Hironori Ueda; Joanna M. M. Howson; Laura Esposito; Joanne Heward; Hywel Snook; Giselle Chamberlain; Daniel B. Rainbow; Kara M. D. Hunter; Annabel N. Smith; Gianfranco Di Genova; Mathias H. Herr; Ingrid Dahlman; Felicity Payne; Deborah Smyth; Christopher Lowe; Rebecca C. J. Twells; Sarah Howlett; Barry Healy; Sarah Nutland; Helen E. Rance; Vin Everett; Luc J. Smink; Alex C. Lam; Heather J. Cordell; Neil M. Walker; Cristina Bordin; John Hulme; Costantino Motzo; Francesco Cucca; J. Fred Hess; Michael L. Metzker; Jane Rogers; Simon Gregory; Amit Allahabadia; Ratnasingam Nithiyananthan; Eva Tuomilehto-Wolf; Jaakko Tuomilehto; Polly Bingley; Kathleen M. Gillespie; Dag E. Undlien; Kjersti S. Rønningen; Cristian Guja; Constantin Ionescu-Tîrgoviste; David A. Savage; A. Peter Maxwell; Dennis J. Carson; Chris C. Patterson; Jayne A. Franklyn; David G. Clayton; Laurence B. Peterson; Linda S. Wicker; John A. Todd; Stephen C. L. Gough

2003-01-01

244

Gene Expression Profiling Identifies Molecular Pathways Associated with Collagen VI Deficiency and Provides Novel Therapeutic Targets  

PubMed Central

Ullrich congenital muscular dystrophy (UCMD), caused by collagen VI deficiency, is a common congenital muscular dystrophy. At present, the role of collagen VI in muscle and the mechanism of disease are not fully understood. To address this we have applied microarrays to analyse the transcriptome of UCMD muscle and compare it to healthy muscle and other muscular dystrophies. We identified 389 genes which are differentially regulated in UCMD relative to controls. In addition, there were 718 genes differentially expressed between UCMD and dystrophin deficient muscle. In contrast, only 29 genes were altered relative to other congenital muscular dystrophies. Changes in gene expression were confirmed by real-time PCR. The set of regulated genes was analysed by Gene Ontology, KEGG pathways and Ingenuity Pathway analysis to reveal the molecular functions and gene networks associated with collagen VI defects. The most significantly regulated pathways were those involved in muscle regeneration, extracellular matrix remodelling and inflammation. We characterised the immune response in UCMD biopsies as being mainly mediated via M2 macrophages and the complement pathway indicating that anti-inflammatory treatment may be beneficial to UCMD as for other dystrophies. We studied the immunolocalisation of ECM components and found that biglycan, a collagen VI interacting proteoglycan, was reduced in the basal lamina of UCMD patients. We propose that biglycan reduction is secondary to collagen VI loss and that it may be contributing towards UCMD pathophysiology. Consequently, strategies aimed at over-expressing biglycan and restore the link between the muscle cell surface and the extracellular matrix should be considered.

Paco, Sonia; Kalko, Susana G.; Jou, Cristina; Rodriguez, Maria A.; Corbera, Joan; Muntoni, Francesco; Feng, Lucy; Rivas, Eloy; Torner, Ferran; Gualandi, Francesca; Gomez-Foix, Anna M.; Ferrer, Anna; Ortez, Carlos; Nascimento, Andres; Colomer, Jaume; Jimenez-Mallebrera, Cecilia

2013-01-01

245

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.  

PubMed

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

246

Prioritizing genes of potential relevance to diseases affected by sex hormones: an example of Myasthenia Gravis  

PubMed Central

Background About 5% of western populations are afflicted by autoimmune diseases many of which are affected by sex hormones. Autoimmune diseases are complex and involve many genes. Identifying these disease-associated genes contributes to development of more effective therapies. Also, association studies frequently imply genomic regions that contain disease-associated genes but fall short of pinpointing these genes. The identification of disease-associated genes has always been challenging and to date there is no universal and effective method developed. Results We have developed a method to prioritize disease-associated genes for diseases affected strongly by sex hormones. Our method uses various types of information available for the genes, but no information that directly links genes with the disease. It generates a score for each of the considered genes and ranks genes based on that score. We illustrate our method on early-onset myasthenia gravis (MG) using genes potentially controlled by estrogen and localized in a genomic segment (which contains the MHC and surrounding region) strongly associated with MG. Based on the considered genomic segment 283 genes are ranked for their relevance to MG and responsiveness to estrogen. The top three ranked genes, HLA-G, TAP2 and HLA-DRB1, are implicated in autoimmune diseases, while TAP2 is associated with SNPs characteristic for MG. Within the top 35 prioritized genes our method identifies 90% of the 10 already known MG-associated genes from the considered region without using any information that directly links genes to MG. Among the top eight genes we identified HLA-G and TUBB as new candidates. We show that our ab-initio approach outperforms the other methods for prioritizing disease-associated genes. Conclusion We have developed a method to prioritize disease-associated genes under the potential control of sex hormones. We demonstrate the success of this method by prioritizing the genes localized in the MHC and surrounding region and evaluating the role of these genes as potential candidates for estrogen control as well as MG. We show that our method outperforms the other methods. The method has a potential to be adapted to prioritize genes relevant to other diseases.

Kaur, Mandeep; Schmeier, Sebastian; MacPherson, Cameron R; Hofmann, Oliver; Hide, Winston A; Taylor, Stephen; Willcox, Nick; Bajic, Vladimir B

2008-01-01

247

NMD inhibition fails to identify tumour suppressor genes in microsatellite stable gastric cancer cell lines  

Microsoft Academic Search

BACKGROUND: Gastric cancers frequently show chromosomal alterations which can cause activation of oncogenes, and\\/or inactivation of tumour suppressor genes. In gastric cancer several chromosomal regions are described to be frequently lost, but for most of the regions, no tumour suppressor genes have been identified yet. The present study aimed to identify tumour suppressor genes inactivated by nonsense mutation and deletion

Tineke E Buffart; Marianne Tijssen; Jamila El-Bchiri; Alex Duval; Mark Wiel; Bauke Ylstra; Gerrit A Meijer; Beatriz Carvalho

2009-01-01

248

Inclusion of Gene-Gene and Gene-Environment Interactions Unlikely to Dramatically Improve Risk Prediction for Complex Diseases  

PubMed Central

Genome-wide association studies have identified hundreds of common genetic variants associated with the risk of multifactorial diseases. However, their impact on discrimination and risk prediction is limited. It has been suggested that the identification of gene-gene (G-G) and gene-environment (G-E) interactions would improve disease prediction and facilitate prevention. We conducted a simulation study to explore the potential improvement in discrimination if G-G and G-E interactions exist and are known. We used three diseases (breast cancer, type 2 diabetes, and rheumatoid arthritis) as motivating examples. We show that the inclusion of G-G and G-E interaction effects in risk-prediction models is unlikely to dramatically improve the discrimination ability of these models.

Aschard, Hugues; Chen, Jinbo; Cornelis, Marilyn C.; Chibnik, Lori B.; Karlson, Elizabeth W.; Kraft, Peter

2012-01-01

249

Identifying genetic diversity of avirulence genes in Leptosphaeria maculans using whole genome sequencing.  

PubMed

Next generation sequencing technology allows rapid re-sequencing of individuals, as well as the discovery of single nucleotide polymorphisms (SNPs), for genomic diversity and evolutionary analyses. By sequencing two isolates of the fungal plant pathogen Leptosphaeria maculans, the causal agent of blackleg disease in Brassica crops, we have generated a resource of over 76 million sequence reads aligned to the reference genome. We identified over 21,000 SNPs with an overall SNP frequency of one SNP every 2,065 bp. Sequence validation of a selection of these SNPs in additional isolates collected throughout Australia indicates a high degree of polymorphism in the Australian population. In preliminary phylogenetic analysis, isolates from Western Australia clustered together and those collected from Brassica juncea stubble were identical. These SNPs provide a novel marker resource to study the genetic diversity of this pathogen. We demonstrate that re-sequencing provides a method of validating previously characterised SNPs and analysing differences in important genes, such as the disease related avirulence genes of L. maculans. Understanding the genetic characteristics of this devastating pathogen is vital in developing long-term solutions to managing blackleg disease in Brassica crops. PMID:23793572

Zander, Manuel; Patel, Dhwani A; Van de Wouw, Angela; Lai, Kaitao; Lorenc, Michal T; Campbell, Emma; Hayward, Alice; Edwards, David; Raman, Harsh; Batley, Jacqueline

2013-08-01

250

Gene-expression profiling of microdissected breast cancer microvasculature identifies distinct tumor vascular subtypes  

PubMed Central

Introduction Angiogenesis represents a potential therapeutic target in breast cancer. However, responses to targeted antiangiogenic therapies have been reported to vary among patients. This suggests that the tumor vasculature may be heterogeneous and that an appropriate choice of treatment would require an understanding of these differences. Methods To investigate whether and how the breast tumor vasculature varies between individuals, we isolated tumor-associated and matched normal vasculature from 17 breast carcinomas by laser-capture microdissection, and generated gene-expression profiles. Because microvessel density has previously been associated with disease course, tumors with low (n = 9) or high (n = 8) microvessel density were selected for analysis to maximize heterogeneity for this feature. Results We identified differences between tumor and normal vasculature, and we describe two subtypes present within tumor vasculature. These subtypes exhibit distinct gene-expression signatures that reflect features including hallmarks of vessel maturity. Potential therapeutic targets (MET, ITGAV, and PDGFR?) are differentially expressed between subtypes. Taking these subtypes into account has allowed us to derive a vascular signature associated with disease outcome. Conclusions Our results further support a role for tumor microvasculature in determining disease progression. Overall, this study provides a deeper molecular understanding of the heterogeneity existing within the breast tumor vasculature and opens new avenues toward the improved design and targeting of antiangiogenic therapies.

2012-01-01

251

Obstacles to identifying viruses that cause autoimmune disease  

Microsoft Academic Search

In addition to a clear genetic disposition, environmental factors and viral infections are thought to play a role in the pathogenesis of autoimmune diseases such as type I diabetes or multiple sclerosis (MS). This article will explore, by use of paradigms developed in a transgenic mouse model, why it has been so difficult to prove a causative association between viral

Matthias G. von Herrath

2000-01-01

252

Clinical Evaluation of Global Change in Alzheimer's Disease: Identifying Consensus  

Microsoft Academic Search

It is important that clinicians who rate global change as part of Alzheimer's disease (AD) clinical drug trials agree on a relevant set of behaviors and information to be considered in formulating their rating. Yet, consensus among raters has been difficult to establish, and inter-rater reliability of clinical global impression of change (CGIC) ratings has been low. In preparation for

Jason T. Olin; Lon S. Schneider; Rachelle S. Doody; Christopher M. Clark; Steven H. Ferris; John C. Morris; Barry Reisberg; Frederick A. Schmitt

1996-01-01

253

Harnessing genomics to identify environmental determinants of heritable disease  

EPA Science Inventory

De novo mutation is increasingly being recognized as the cause for a range of human genetic diseases and disorders. Important examples of this include inherited genetic disorders such as autism, schizophrenia, mental retardation, epilepsy, and a broad range of adverse reproductiv...

254

A framework to identify gene expression profiles in a model of inflammation induced by lipopolysaccharide after treatment with thalidomide  

PubMed Central

Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS) stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis.

2012-01-01

255

Identifying new human oocyte marker genes: a microarray approach  

Microsoft Academic Search

The efficacy of classical IVF techniques is still impaired by poor implantation and pregnancy rates after embryo transfer. This is mainly due to a lack of reliable criteria for the selection of embryos with sufficient development potential. Several studies have provided evidence that some gene expression levels could be used as objective markers of oocyte and embryo competence and capacity

Stéphan Gasca; Franck Pellestor; Saïd Assou; Vanessa Loup; Tal Anahory; Hervé Dechaud; John De Vos; Samir Hamamah

2007-01-01

256

Identifying a species tree subject to random lateral gene transfer.  

PubMed

A major problem for inferring species trees from gene trees is that evolutionary processes can sometimes favor gene tree topologies that conflict with an underlying species tree. In the case of incomplete lineage sorting, this phenomenon has recently been well-studied, and some elegant solutions for species tree reconstruction have been proposed. One particularly simple and statistically consistent estimator of the species tree under incomplete lineage sorting is to combine three-taxon analyses, which are phylogenetically robust to incomplete lineage sorting. In this paper, we consider whether such an approach will also work under lateral gene transfer (LGT). By providing an exact analysis of some cases of this model, we show that there is a zone of inconsistency when majority-rule three-taxon gene trees are used to reconstruct species trees under LGT. However, a triplet-based approach will consistently reconstruct a species tree under models of LGT, provided that the expected number of LGT transfers is not too high. Our analysis involves a novel connection between the LGT problem and random walks on cyclic graphs. We have implemented a procedure for reconstructing trees subject to LGT or lineage sorting in settings where taxon coverage may be patchy and illustrate its use on two sample data sets. PMID:23340439

Steel, Mike; Linz, Simone; Huson, Daniel H; Sanderson, Michael J

2013-04-01

257

An integrative genomics approach to infer causal associations between gene expression and disease  

Microsoft Academic Search

A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations. Ordering gene expression traits relative to one another

John Lamb; Xia Yang; Jun Zhu; Steve Edwards; Debraj GuhaThakurta; Solveig K Sieberts; Stephanie Monks; Marc Reitman; Chunsheng Zhang; Pek Yee Lum; Amy Leonardson; Rolf Thieringer; Joseph M Metzger; Liming Yang; John Castle; Haoyuan Zhu; Shera F Kash; Thomas A Drake; Alan Sachs; Aldons J Lusis; Eric E Schadt

2005-01-01

258

Disease gene identification by random walk on multigraphs merging heterogeneous genomic and phenotype data  

PubMed Central

Background High throughput experiments resulted in many genomic datasets and hundreds of candidate disease genes. To discover the real disease genes from a set of candidate genes, computational methods have been proposed and worked on various types of genomic data sources. As a single source of genomic data is prone of bias, incompleteness and noise, integration of different genomic data sources is highly demanded to accomplish reliable disease gene identification. Results In contrast to the commonly adapted data integration approach which integrates separate lists of candidate genes derived from the each single data sources, we merge various genomic networks into a multigraph which is capable of connecting multiple edges between a pair of nodes. This novel approach provides a data platform with strong noise tolerance to prioritize the disease genes. A new idea of random walk is then developed to work on multigraphs using a modified step to calculate the transition matrix. Our method is further enhanced to deal with heterogeneous data types by allowing cross-walk between phenotype and gene networks. Compared on benchmark datasets, our method is shown to be more accurate than the state-of-the-art methods in disease gene identification. We also conducted a case study to identify disease genes for Insulin-Dependent Diabetes Mellitus. Some of the newly identified disease genes are supported by recently published literature. Conclusions The proposed RWRM (Random Walk with Restart on Multigraphs) model and CHN (Complex Heterogeneous Network) model are effective in data integration for candidate gene prioritization.

2012-01-01

259

Clustering Approaches To Identifying Gene Expression Patterns from DNA Microarray Data  

Microsoft Academic Search

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological ration- ale for this approach is the fact that many co- expressed genes are co-regulated, and identifying co- expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites

Jin Hwan Do; Dong-Kug Choi

2007-01-01

260

Candidate genes and functional noncoding variants identified in a canine model of obsessive-compulsive disorder  

PubMed Central

Background Obsessive-compulsive disorder (OCD), a severe mental disease manifested in time-consuming repetition of behaviors, affects 1 to 3% of the human population. While highly heritable, complex genetics has hampered attempts to elucidate OCD etiology. Dogs suffer from naturally occurring compulsive disorders that closely model human OCD, manifested as an excessive repetition of normal canine behaviors that only partially responds to drug therapy. The limited diversity within dog breeds makes identifying underlying genetic factors easier. Results We use genome-wide association of 87 Doberman Pinscher cases and 63 controls to identify genomic loci associated with OCD and sequence these regions in 8 affected dogs from high-risk breeds and 8 breed-matched controls. We find 119 variants in evolutionarily conserved sites that are specific to dogs with OCD. These case-only variants are significantly more common in high OCD risk breeds compared to breeds with no known psychiatric problems. Four genes, all with synaptic function, have the most case-only variation: neuronal cadherin (CDH2), catenin alpha2 (CTNNA2), ataxin-1 (ATXN1), and plasma glutamate carboxypeptidase (PGCP). In the 2 Mb gene desert between the cadherin genes CDH2 and DSC3, we find two different variants found only in dogs with OCD that disrupt the same highly conserved regulatory element. These variants cause significant changes in gene expression in a human neuroblastoma cell line, likely due to disrupted transcription factor binding. Conclusions The limited genetic diversity of dog breeds facilitates identification of genes, functional variants and regulatory pathways underlying complex psychiatric disorders that are mechanistically similar in dogs and humans.

2014-01-01

261

Deep Sequencing Study of the MTHFR Gene to Identify Variants Associated with Myelomeningocele  

PubMed Central

INTRODUCTION Neural tube defects (NTDs) are congenital anomalies caused by a combination of genetic and environmental influences. A defect below the head region resulting in protuberance of meninges and nervous tissue is termed myelomeningocele (MM). MM, the most common NTD compatible with survival, occurs in approximately 1 in 1,000 births worldwide. Maternal pre- and periconceptional folate supplementation reduces the risk of NTDs by up to 70%. A key enzyme in folate metabolism is 5, 10-methylene-tetrahydrofolate reductase (MTHFR). OBJECTIVES Sequence the 12 exons of the MTHFR gene among 96 subjects with MM to identify variants potentially contributing to the disease trait. METHODS Exons were amplified by polymerase chain reaction and the products were sequenced by Sanger method to reveal sequence variants compared to MTHFR reference sequences. Association of variants was examined by Fisher’s test. RESULTS A novel variant c.171+3G>T was identified in intron 1 in one affected subject. The variant was not found in the subject’s unaffected mother’s DNA and the unaffected father’s DNA was unavailable. We found significant differences in allele frequencies for seven SNPs in MM subjects compared to ethnically matched reference populations reported in the single nucleotide polymorphism (SNP) database (dbSNP). CONCLUSION We identified a novel variant c.171+3G>T in the MTHFR gene that potentially affects splicing in an affected subject. Also, we observed five SNPs (rs13306561, rs2274976, rs2066462, rs12121543, and rs1476413) in the MTHFR gene not previously shown to associate with MM. The current study provides additional evidence that multiple variations in the MTHFR gene are associated with MM.

Aneji, Chiamaka U; Northrup, Hope; Au, Kit Sing

2012-01-01

262

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.  

PubMed

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression. PMID:22203922

B?l?cescu, Loredana; B?l?cescu, O; Cri?an, N; Fetica, B; Petru?, B; Bung?rdean, C?t?lina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Drago?, N; Berindan-Neagoe, Ioana

2011-01-01

263

A computational study identifies HIV progression-related genes using mRMR and shortest path tracing.  

PubMed

Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression. PMID:24244287

Ma, Chengcheng; Dong, Xiao; Li, Rudong; Liu, Lei

2013-01-01

264

A Computational Study Identifies HIV Progression-Related Genes Using mRMR and Shortest Path Tracing  

PubMed Central

Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression.

Liu, Lei

2013-01-01

265

Using registries to identify adverse events in rheumatic diseases.  

PubMed

The proven effectiveness of biologics and other immunomodulatory products in inflammatory rheumatic diseases has resulted in their widespread use as well as reports of potential short- and long-term complications such as infection and malignancy. These complications are especially worrisome in children who often have serial exposures to multiple immunomodulatory products. Post-marketing surveillance of immunomodulatory products in juvenile idiopathic arthritis (JIA) and pediatric systemic lupus erythematosus is currently based on product-specific registries and passive surveillance, which may not accurately reflect the safety risks for children owing to low numbers, poor long-term retention, and inadequate comparators. In collaboration with the US Food and Drug Administration (FDA), patient and family advocacy groups, biopharmaceutical industry representatives and other stakeholders, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) and the Duke Clinical Research Institute (DCRI) have developed a novel pharmacosurveillance model (CARRA Consolidated Safety Registry [CoRe]) based on a multicenter longitudinal pediatric rheumatic diseases registry with over 8000 participants. The existing CARRA infrastructure provides access to much larger numbers of subjects than is feasible in single-product registries. Enrollment regardless of medication exposure allows more accurate detection and evaluation of safety signals. Flexibility built into the model allows the addition of specific data elements and safety outcomes, and designation of appropriate disease comparator groups relevant to each product, fulfilling post-marketing requirements and commitments. The proposed model can be applied to other pediatric and adult diseases, potentially transforming the paradigm of pharmacosurveillance in response to the growing public mandate for rigorous post-marketing safety monitoring. PMID:24144710

Lionetti, Geraldina; Kimura, Yukiko; Schanberg, Laura E; Beukelman, Timothy; Wallace, Carol A; Ilowite, Norman T; Winsor, Jane; Fox, Kathleen; Natter, Marc; Sundy, John S; Brodsky, Eric; Curtis, Jeffrey R; Del Gaizo, Vincent; Iyasu, Solomon; Jahreis, Angelika; Meeker-O'Connell, Ann; Mittleman, Barbara B; Murphy, Bernard M; Peterson, Eric D; Raymond, Sandra C; Setoguchi, Soko; Siegel, Jeffrey N; Sobel, Rachel E; Solomon, Daniel; Southwood, Taunton R; Vesely, Richard; White, Patience H; Wulffraat, Nico M; Sandborg, Christy I

2013-11-01

266

Gene expression profiling identifies genes predictive of oral squamous cell carcinoma  

PubMed Central

Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity. To identify potential biomarkers for early detection of invasive OSCC, we compared gene expression of incident primary OSCC, oral dysplasia, and clinically normal oral tissue from surgical patients without head and neck cancer or pre-neoplastic oral lesions (controls), using Affymetrix U133 2.0 Plus arrays. We identified 131 differentially expressed probe sets using a training set of 119 OSCC patients and 35 controls. Forward and stepwise logistic regression analyses identified 10 successive combinations of genes which expression differentiated OSCC from controls. The best model included LAMC2, encoding laminin gamma 2 chain, and COL4A1, encoding collagen, type IV, alpha 1 chain. Subsequent modeling without these two markers showed that COL1A1, encoding collagen, type I, alpha 1 chain, and PADI1, encoding peptidyl arginine deiminase, type 1, also can distinguish OSCC from controls. We validated these two models using an internal independent testing set of 48 invasive OSCC and 10 controls and an external testing set of 42 head and neck squamous cell carcinoma (HNSCC) cases and 14 controls (GEO GSE6791), with sensitivity and specificity above 95%. These two models were also able to distinguish dysplasia (n=17) from control (n=35) tissue. Differential expression of these four genes was confirmed by qRT-PCR. If confirmed in larger studies, the proposed models may hold promise for monitoring local recurrence at surgical margins and the development of second primary oral cancer in OSCC patients.

Chen, Chu; Mendez, Eduardo; Houck, John; Fan, Wenhong; Lohavanichbutr, Pawadee; Doody, Dave; Yueh, Bevan; Futran, Neal D.; Upton, Melissa; Farwell, D. Gregory; Schwartz, Stephen M.; Zhao, Lue Ping

2008-01-01

267

Inflammatory bowel disease gene discovery. CRADA final report  

SciTech Connect

The ultimate goal of this project is to identify the human gene(s) responsible for the disorder known as IBD. The work was planned in two phases. The desired products resulting from Phase 1 were BAC clone(s) containing the genetic marker(s) identified by gene/Networks, Inc. as potentially linked to IBD, plasmid subclones of those BAC(s), and new genetic markers developed from these plasmid subclones. The newly developed markers would be genotyped by gene/Networks, Inc. to ascertain evidence for linkage or non-linkage of IBD to this region. If non-linkage was indicated, the project would move to investigation of other candidate chromosomal regions. Where linkage was indicated, the project would move to Phase 2, in which a physical map of the candidate region(s) would be developed. The products of this phase would be contig(s) of BAC clones in the region exhibiting linkage to IBD, as well as plasmic subclones of the BACs and further genetic marker development. There would also be continued genotyping with new polymorphic markers during this phase. It was anticipated that clones identified and developed during these two phases would provide the physical resources for eventual disease gene discovery.

NONE

1997-09-09

268

Identifying Autism Loci and Genes by Tracing Recent Shared Ancestry  

Microsoft Academic Search

To find inherited causes of autism-spectrum disorders, we studied families in which parents share ancestors, enhancing the role of inherited factors. We mapped several loci, some containing large, inherited, homozygous deletions that are likely mutations. The largest deletions implicated genes, including PCDH10 (protocadherin 10) and DIA1 (deleted in autism1, orc3orf58), whose level of expression changes in response to neuronal activity,

Eric M. Morrow; Seung-Yun Yoo; Steven W. Flavell; Tae-Kyung Kim; Yingxi Lin; Robert Sean Hill; Nahit M. Mukaddes; Soher Balkhy; Generoso Gascon; Asif Hashmi; Samira Al-Saad; Janice Ware; Robert M. Joseph; Rachel Greenblatt; Danielle Gleason; Julia A. Ertelt; Kira A. Apse; Adria Bodell; Jennifer N. Partlow; Brenda Barry; Hui Yao; Kyriacos Markianos; Russell J. Ferland; Michael E. Greenberg; Christopher A. Walsh

2008-01-01

269

Gene Network Analysis of Small Molecules with Autoimmune Disease Associated Genes Predicts a Novel Strategy for Drug Efficacy  

PubMed Central

Numerous genes/SNPs in autoimmune diseases (ADs) are identified through genome-wide association studies (GWAS) and likely to contribute in developing autoimmune phenotypes. Constructions of biologically meaningful pathways are necessary to determine how these genes interact each other and with other small molecules to develop various complex ADs phenotypes prior to beginning time-consuming rigorous experimentation. We have constructed biological pathways with genetically identified genes leading to shared ADs phenotypes. Various environmental and endogenous factors interact with these ADs associated genes suggesting their critical role in developing diseases and further association studies could be designed for assessing the role of these factors with risk allele in a specific gene. Additionally, existing drugs that have been used long before the identification of these genetically associated genes also interact with these newly associated genes. Thus advanced therapeutic strategies could be designed by grouping patients with risk allele(s) in particular genes that directly or closely interact with the specified drugs. This drug-susceptible gene network will not only increase our understanding about the additional molecular basis for effectiveness against these diseases but also which drug could be more effective for those patients carrying risk allele(s) in that gene. Additionally, we have also identified several interlinking genes in the pathways that could be used for designing future association studies.

Maiti, Amit K.; Nath, Swapan K.

2012-01-01

270

Elevating crop disease resistance with cloned genes  

PubMed Central

Essentially all plant species exhibit heritable genetic variation for resistance to a variety of plant diseases caused by fungi, bacteria, oomycetes or viruses. Disease losses in crop monocultures are already significant, and would be greater but for applications of disease-controlling agrichemicals. For sustainable intensification of crop production, we argue that disease control should as far as possible be achieved using genetics rather than using costly recurrent chemical sprays. The latter imply CO2 emissions from diesel fuel and potential soil compaction from tractor journeys. Great progress has been made in the past 25 years in our understanding of the molecular basis of plant disease resistance mechanisms, and of how pathogens circumvent them. These insights can inform more sophisticated approaches to elevating disease resistance in crops that help us tip the evolutionary balance in favour of the crop and away from the pathogen. We illustrate this theme with an account of a genetically modified (GM) blight-resistant potato trial in Norwich, using the Rpi-vnt1.1 gene isolated from a wild relative of potato, Solanum venturii, and introduced by GM methods into the potato variety Desiree.

Jones, Jonathan D. G.; Witek, Kamil; Verweij, Walter; Jupe, Florian; Cooke, David; Dorling, Stephen; Tomlinson, Laurence; Smoker, Matthew; Perkins, Sara; Foster, Simon

2014-01-01

271

Identifying Early Changes in Myocardial Microstructure in Hypertensive Heart Disease  

PubMed Central

The transition from healthy myocardium to hypertensive heart disease is characterized by a series of poorly understood changes in myocardial tissue microstructure. Incremental alterations in the orientation and integrity of myocardial fibers can be assessed using advanced ultrasonic image analysis. We used a modified algorithm to investigate left ventricular myocardial microstructure based on analysis of the reflection intensity at the myocardial-pericardial interface on B-mode echocardiographic images. We evaluated the extent to which the novel algorithm can differentiate between normal myocardium and hypertensive heart disease in humans as well as in a mouse model of afterload resistance. The algorithm significantly differentiated between individuals with uncomplicated essential hypertension (N?=?30) and healthy controls (N?=?28), even after adjusting for age and sex (P?=?0.025). There was a trend in higher relative wall thickness in hypertensive individuals compared to controls (P?=?0.08), but no difference between groups in left ventricular mass (P?=?0.98) or total wall thickness (P?=?0.37). In mice, algorithm measurements (P?=?0.026) compared with left ventricular mass (P?=?0.053) more clearly differentiated between animal groups that underwent fixed aortic banding, temporary aortic banding, or sham procedure, on echocardiography at 7 weeks after surgery. Based on sonographic signal intensity analysis, a novel imaging algorithm provides an accessible, non-invasive measure that appears to differentiate normal left ventricular microstructure from myocardium exposed to chronic afterload stress. The algorithm may represent a particularly sensitive measure of the myocardial changes that occur early in the course of disease progression.

Hiremath, Pranoti; Bauer, Michael; Aguirre, Aaron D.; Cheng, Hui-Wen; Unno, Kazumasa; Patel, Ravi B.; Harvey, Bethany W.; Chang, Wei-Ting; Groarke, John D.; Liao, Ronglih; Cheng, Susan

2014-01-01

272

Evaluation of suitable reference genes for gene expression studies in bronchoalveolar lavage cells from horses with inflammatory airway disease  

Microsoft Academic Search

BACKGROUND: The stability of reference genes has a tremendous effect on the results of relative quantification of genes expression by quantitative polymerase chain reaction. Equine Inflammatory Airway Disease (IAD) is a common condition often treated with corticosteroids. The diagnosis of IAD is based on clinical signs and bronchoalveolar lavage (BAL) fluid cytology. The aim of this study was to identify

Laura Beekman; Triin Tohver; Rkia Dardari; Renaud Léguillette

2011-01-01

273

Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana  

Microsoft Academic Search

A major challenge in evolutionary biology and plant breeding is to identify the genetic basis of complex quantitative traits, including those that contribute to adaptive variation. Here we review the development of new methods and resources to fine-map intraspecific genetic variation that underlies natural phenotypic variation in plants. In particular, the analysis of 107 quantitative traits reported in the first

Fabrice Roux; Joy Bergelson

2010-01-01

274

Functional Connectivity Measured with Magnetoencephalography Identifies Persons with HIV Disease  

PubMed Central

There is need for a valid and reliable biomarker for HIV Associated Neurocognitive Disorder (HAND). The purpose of the present study was to provide preliminary evidence of the potential utility of neuronal functional connectivity measures obtained using magnetoencephalography (MEG) to identify HIV-associated changes in brain function. Resting state, eyes closed, MEG data from 10 HIV-infected individuals and 8 seronegative controls were analyzed using mutual information (MI) between all pairs of MEG sensors to determine whether there were functional brain networks that distinguished between subject groups based on cognition (global and learning) or on serostatus. Three networks were identified across all subjects, but after permutation testing (at ? < .005) only the one related to HIV serostatus was significant. The network included MEG sensors (planar gradiometers) above the right anterior region connecting to sensors above the left posterior region. A mean MI value was calculated across all connections from the anterior to the posterior groupings; that score distinguished between the serostatus groups with only one error (sensitivity = 1.00, specificity = .88 (X2 = 15.4, df = 1, p < .01, Relative Risk = .11). There were no significant associations between the MI value and the neuropsychological Global Impairment rating, substance abuse, mood disorder, age, education, CD4+ cell counts or HIV viral load. We conclude that using a measure of functional connectivity, it may be possible to distinguish between HIV-infected and uninfected individuals, suggesting that MEG may have the potential to serve as a sensitive, non-invasive biomarker for HAND.

Becker, James T.; Bajo, Ricardo; Fabrizio, Melissa; Sudre, Gustavo; Cuesta, Pablo; Aizenstein, Howard J.; Lopez, Oscar L.; Wolk, David; Parkkonen, Lauri; Maestu, Fernando; Bagic, Anto

2012-01-01

275

Genome-wide association analyses identify SPOCK as a key novel gene underlying age at menarche.  

PubMed

For females, menarche is a most significant physiological event. Age at menarche (AAM) is a trait with high genetic determination and is associated with major complex diseases in women. However, specific genes for AAM variation are largely unknown. To identify genetic factors underlying AAM variation, a genome-wide association study (GWAS) examining about 380,000 SNPs was conducted in 477 Caucasian women. A follow-up replication study was performed to validate our major GWAS findings using two independent Caucasian cohorts with 854 siblings and 762 unrelated subjects, respectively, and one Chinese cohort of 1,387 unrelated subjects--all females. Our GWAS identified a novel gene, SPOCK (Sparc/Osteonectin, CWCV, and Kazal-like domains proteoglycan), which had seven SNPs associated with AAM with genome-wide false discovery rate (FDR) q<0.05. Six most significant SNPs of the gene were selected for validation in three independent replication cohorts. All of the six SNPs were replicated in at least one cohort. In particular, SNPs rs13357391 and rs1859345 were replicated both within and across different ethnic groups in all three cohorts, with p values of 5.09 x 10(-3) and 4.37 x 10(-3), respectively, in the Chinese cohort and combined p values (obtained by Fisher's method) of 5.19 x 10(-5) and 1.02 x 10(-4), respectively, in all three replication cohorts. Interestingly, SPOCK can inhibit activation of MMP-2 (matrix metalloproteinase-2), a key factor promoting endometrial menstrual breakdown and onset of menstrual bleeding. Our findings, together with the functional relevance, strongly supported that the SPOCK gene underlies variation of AAM. PMID:19282985

Liu, Yao-Zhong; Guo, Yan-Fang; Wang, Liang; Tan, Li-Jun; Liu, Xiao-Gang; Pei, Yu-Fang; Yan, Han; Xiong, Dong-Hai; Deng, Fei-Yan; Yu, Na; Zhang, Yin-Ping; Zhang, Lei; Lei, Shu-Feng; Chen, Xiang-Ding; Liu, Hong-Bin; Zhu, Xue-Zhen; Levy, Shawn; Papasian, Christopher J; Drees, Betty M; Hamilton, James J; Recker, Robert R; Deng, Hong-Wen

2009-03-01

276

Genome-Wide Association Analyses Identify SPOCK as a Key Novel Gene Underlying Age at Menarche  

PubMed Central

For females, menarche is a most significant physiological event. Age at menarche (AAM) is a trait with high genetic determination and is associated with major complex diseases in women. However, specific genes for AAM variation are largely unknown. To identify genetic factors underlying AAM variation, a genome-wide association study (GWAS) examining about 380,000 SNPs was conducted in 477 Caucasian women. A follow-up replication study was performed to validate our major GWAS findings using two independent Caucasian cohorts with 854 siblings and 762 unrelated subjects, respectively, and one Chinese cohort of 1,387 unrelated subjects—all females. Our GWAS identified a novel gene, SPOCK (Sparc/Osteonectin, CWCV, and Kazal-like domains proteoglycan), which had seven SNPs associated with AAM with genome-wide false discovery rate (FDR) q<0.05. Six most significant SNPs of the gene were selected for validation in three independent replication cohorts. All of the six SNPs were replicated in at least one cohort. In particular, SNPs rs13357391 and rs1859345 were replicated both within and across different ethnic groups in all three cohorts, with p values of 5.09×10?3 and 4.37×10?3, respectively, in the Chinese cohort and combined p values (obtained by Fisher's method) of 5.19×10?5 and 1.02×10?4, respectively, in all three replication cohorts. Interestingly, SPOCK can inhibit activation of MMP-2 (matrix metalloproteinase-2), a key factor promoting endometrial menstrual breakdown and onset of menstrual bleeding. Our findings, together with the functional relevance, strongly supported that the SPOCK gene underlies variation of AAM.

Liu, Yao-Zhong; Guo, Yan-Fang; Wang, Liang; Tan, Li-Jun; Liu, Xiao-Gang; Pei, Yu-Fang; Yan, Han; Xiong, Dong-Hai; Deng, Fei-Yan; Yu, Na; Zhang, Yin-Ping; Zhang, Lei; Lei, Shu-Feng; Chen, Xiang-Ding; Liu, Hong-Bin; Zhu, Xue-Zhen; Levy, Shawn; Papasian, Christopher J.; Drees, Betty M.; Hamilton, James J.; Recker, Robert R.; Deng, Hong-Wen

2009-01-01

277

Personalized gene silencing therapeutics for Huntington disease.  

PubMed

Gene silencing offers a novel therapeutic strategy for dominant genetic disorders. In specific diseases, selective silencing of only one copy of a gene may be advantageous over non-selective silencing of both copies. Huntington disease (HD) is an autosomal dominant disorder caused by an expanded CAG trinucleotide repeat in the Huntingtin gene (HTT). Silencing both expanded and normal copies of HTT may be therapeutically beneficial, but preservation of normal HTT expression is preferred. Allele-specific methods can selectively silence the mutant HTT transcript by targeting either the expanded CAG repeat or single nucleotide polymorphisms (SNPs) in linkage disequilibrium with the expansion. Both approaches require personalized treatment strategies based on patient genotypes. We compare the prospect of safe treatment of HD by CAG- and SNP-specific silencing approaches and review HD population genetics used to guide target identification in the patient population. Clinical implementation of allele-specific HTT silencing faces challenges common to personalized genetic medicine, requiring novel solutions from clinical scientists and regulatory authorities. PMID:24646433

Kay, C; Skotte, N H; Southwell, A L; Hayden, M R

2014-07-01

278

Large-scale association analysis identifies new risk loci for coronary artery disease  

PubMed Central

Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r2 < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.

2013-01-01

279

Large-scale association analysis identifies new risk loci for coronary artery disease.  

PubMed

Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways. PMID:23202125

Deloukas, Panos; Kanoni, Stavroula; Willenborg, Christina; Farrall, Martin; Assimes, Themistocles L; Thompson, John R; Ingelsson, Erik; Saleheen, Danish; Erdmann, Jeanette; Goldstein, Benjamin A; Stirrups, Kathleen; König, Inke R; Cazier, Jean-Baptiste; Johansson, Asa; Hall, Alistair S; Lee, Jong-Young; Willer, Cristen J; Chambers, John C; Esko, Tõnu; Folkersen, Lasse; Goel, Anuj; Grundberg, Elin; Havulinna, Aki S; Ho, Weang K; Hopewell, Jemma C; Eriksson, Niclas; Kleber, Marcus E; Kristiansson, Kati; Lundmark, Per; Lyytikäinen, Leo-Pekka; Rafelt, Suzanne; Shungin, Dmitry; Strawbridge, Rona J; Thorleifsson, Gudmar; Tikkanen, Emmi; Van Zuydam, Natalie; Voight, Benjamin F; Waite, Lindsay L; Zhang, Weihua; Ziegler, Andreas; Absher, Devin; Altshuler, David; Balmforth, Anthony J; Barroso, Inês; Braund, Peter S; Burgdorf, Christof; Claudi-Boehm, Simone; Cox, David; Dimitriou, Maria; Do, Ron; Doney, Alex S F; El Mokhtari, NourEddine; Eriksson, Per; Fischer, Krista; Fontanillas, Pierre; Franco-Cereceda, Anders; Gigante, Bruna; Groop, Leif; Gustafsson, Stefan; Hager, Jörg; Hallmans, Göran; Han, Bok-Ghee; Hunt, Sarah E; Kang, Hyun M; Illig, Thomas; Kessler, Thorsten; Knowles, Joshua W; Kolovou, Genovefa; Kuusisto, Johanna; Langenberg, Claudia; Langford, Cordelia; Leander, Karin; Lokki, Marja-Liisa; Lundmark, Anders; McCarthy, Mark I; Meisinger, Christa; Melander, Olle; Mihailov, Evelin; Maouche, Seraya; Morris, Andrew D; Müller-Nurasyid, Martina; Nikus, Kjell; Peden, John F; Rayner, N William; Rasheed, Asif; Rosinger, Silke; Rubin, Diana; Rumpf, Moritz P; Schäfer, Arne; Sivananthan, Mohan; Song, Ci; Stewart, Alexandre F R; Tan, Sian-Tsung; Thorgeirsson, Gudmundur; van der Schoot, C Ellen; Wagner, Peter J; Wells, George A; Wild, Philipp S; Yang, Tsun-Po; Amouyel, Philippe; Arveiler, Dominique; Basart, Hanneke; Boehnke, Michael; Boerwinkle, Eric; Brambilla, Paolo; Cambien, Francois; Cupples, Adrienne L; de Faire, Ulf; Dehghan, Abbas; Diemert, Patrick; Epstein, Stephen E; Evans, Alun; Ferrario, Marco M; Ferrières, Jean; Gauguier, Dominique; Go, Alan S; Goodall, Alison H; Gudnason, Villi; Hazen, Stanley L; Holm, Hilma; Iribarren, Carlos; Jang, Yangsoo; Kähönen, Mika; Kee, Frank; Kim, Hyo-Soo; Klopp, Norman; Koenig, Wolfgang; Kratzer, Wolfgang; Kuulasmaa, Kari; Laakso, Markku; Laaksonen, Reijo; Lee, Ji-Young; Lind, Lars; Ouwehand, Willem H; Parish, Sarah; Park, Jeong E; Pedersen, Nancy L; Peters, Annette; Quertermous, Thomas; Rader, Daniel J; Salomaa, Veikko; Schadt, Eric; Shah, Svati H; Sinisalo, Juha; Stark, Klaus; Stefansson, Kari; Trégouët, David-Alexandre; Virtamo, Jarmo; Wallentin, Lars; Wareham, Nicholas; Zimmermann, Martina E; Nieminen, Markku S; Hengstenberg, Christian; Sandhu, Manjinder S; Pastinen, Tomi; Syvänen, Ann-Christine; Hovingh, G Kees; Dedoussis, George; Franks, Paul W; Lehtimäki, Terho; Metspalu, Andres; Zalloua, Pierre A; Siegbahn, Agneta; Schreiber, Stefan; Ripatti, Samuli; Blankenberg, Stefan S; Perola, Markus; Clarke, Robert; Boehm, Bernhard O; O'Donnell, Christopher; Reilly, Muredach P; März, Winfried; Collins, Rory; Kathiresan, Sekar; Hamsten, Anders; Kooner, Jaspal S; Thorsteinsdottir, Unnur; Danesh, John; Palmer, Colin N A; Roberts, Robert; Watkins, Hugh; Schunkert, Heribert; Samani, Nilesh J

2013-01-01

280

Genome-wide Linkage and Association Analyses to Identify Genes Influencing Adiponectin Levels: The GEMS Study  

PubMed Central

Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10?7). These two SNPs were in high linkage disequilibrium (r2 = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 × 10?5) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.

Ling, Hua; Waterworth, Dawn M.; Stirnadel, Heide A.; Pollin, Toni I.; Barter, Philip J.; Kesaniemi, Y. Antero; Mahley, Robert W.; McPherson, Ruth; Waeber, Gerard; Bersot, Thomas P.; Cohen, Jonathan C.; Grundy, Scott M.; Mooser, Vincent E.; Mitchell, Braxton D.

2014-01-01

281

Detecting gene–gene interactions that underlie human diseases  

Microsoft Academic Search

Following the identification of several disease-associated polymorphisms by genome-wide association (GWA) analysis, interest is now focusing on the detection of effects that, owing to their interaction with other genetic or environmental factors, might not be identified by using standard single-locus tests. In addition to increasing the power to detect associations, it is hoped that detecting interactions between loci will allow

Heather J Cordell

2009-01-01

282

A Multistep Screening Method to Identify Genes Using Evolutionary Transcriptome of Plants  

PubMed Central

We introduced a multistep screening method to identify the genes in plants using microarrays and ribonucleic acid (RNA)-seq transcriptome data. Our method describes the process for identifying genes using the salt-tolerance response pathways of the potato (Solanum tuberosum) plant. Gene expression was analyzed using microarrays and RNA-seq experiments that examined three potato lines (high, intermediate, and low salt tolerance) under conditions of salt stress. We screened the orthologous genes and pathway genes involved in salinity-related biosynthetic pathways, and identified nine potato genes that were candidates for salinity-tolerance pathways. The nine genes were selected to characterize their phylogenetic reconstruction with homologous genes of Arabidopsis thaliana, and a Circos diagram was generated to understand the relationships among the selected genes. The involvement of the selected genes in salt-tolerance pathways was verified by reverse transcription polymerase chain reaction analysis. One candidate potato gene was selected for physiological validation by generating dehydration-responsive element-binding 1 (DREB1)-overexpressing transgenic potato plants. The DREB1 overexpression lines exhibited increased salt tolerance and plant growth when compared to that of the control. Although the nine genes identified by our multistep screening method require further characterization and validation, this study demonstrates the power of our screening strategy after the initial identification of genes using microarrays and RNA-seq experiments.

Kim, Chang-Kug; Lim, Hye-Min; Na, Jong-Kuk; Choi, Ji-Weon; Sohn, Seong-Han; Park, Soo-Chul; Kim, Young-Hwan; Kim, Yong-Kab; Kim, Dool-Yi

2014-01-01

283

A multistep screening method to identify genes using evolutionary transcriptome of plants.  

PubMed

We introduced a multistep screening method to identify the genes in plants using microarrays and ribonucleic acid (RNA)-seq transcriptome data. Our method describes the process for identifying genes using the salt-tolerance response pathways of the potato (Solanum tuberosum) plant. Gene expression was analyzed using microarrays and RNA-seq experiments that examined three potato lines (high, intermediate, and low salt tolerance) under conditions of salt stress. We screened the orthologous genes and pathway genes involved in salinity-related biosynthetic pathways, and identified nine potato genes that were candidates for salinity-tolerance pathways. The nine genes were selected to characterize their phylogenetic reconstruction with homologous genes of Arabidopsis thaliana, and a Circos diagram was generated to understand the relationships among the selected genes. The involvement of the selected genes in salt-tolerance pathways was verified by reverse transcription polymerase chain reaction analysis. One candidate potato gene was selected for physiological validation by generating dehydration-responsive element-binding 1 (DREB1)-overexpressing transgenic potato plants. The DREB1 overexpression lines exhibited increased salt tolerance and plant growth when compared to that of the control. Although the nine genes identified by our multistep screening method require further characterization and validation, this study demonstrates the power of our screening strategy after the initial identification of genes using microarrays and RNA-seq experiments. PMID:24812480

Kim, Chang-Kug; Lim, Hye-Min; Na, Jong-Kuk; Choi, Ji-Weon; Sohn, Seong-Han; Park, Soo-Chul; Kim, Young-Hwan; Kim, Yong-Kab; Kim, Dool-Yi

2014-01-01

284

Whole exome sequencing identifies three recessive FIG4 mutations in an apparently dominant pedigree with Charcot-Marie-Tooth disease.  

PubMed

Charcot-Marie-Tooth disease (CMT) is genetically heterogeneous and classification based on motor nerve conduction velocity and inheritance is used to direct genetic testing. With the less common genetic forms of CMT, identifying the causative genetic mutation by Sanger sequencing of individual genes can be time-consuming and costly. Next-generation sequencing technologies show promise for clinical testing in diseases where a similar phenotype is caused by different genes. We report the unusual occurrence of CMT4J, caused by mutations in FIG4, in a apparently dominant pedigree. The affected proband and her mother exhibit different disease severities associated with different combinations of compound heterozygous FIG4 mutations, identified by whole exome sequencing. The proband was also shown to carry a de novo nonsense mutation in the dystrophin gene, which may contribute to her more severe phenotype. This study is a cautionary reminder that in families with two generations affected, explanations other than dominant inheritance are possible, such as recessive inheritance due to three mutations segregating in the family. It also emphasises the advantages of next-generation sequencing approaches that screen multiple CMT genes at once for patients in whom the common genes have been excluded. PMID:24878229

Menezes, Manoj P; Waddell, Leigh; Lenk, Guy M; Kaur, Simranpreet; MacArthur, Daniel G; Meisler, Miriam H; Clarke, Nigel F

2014-08-01

285

From gene expression analysis to tissue microarrays: a rational approach to identify therapeutic and diagnostic targets in lymphoid malignancies.  

PubMed

Mantle cell lymphoma (MCL) is an aggressive lymphoid malignancy for which better treatment strategies are needed. To identify potential diagnostic and therapeutic targets, a signature consisting of MCL-associated genes was selected based on a comprehensive gene expression analysis of malignant and normal B cells. The corresponding protein epitope signature tags were identified and used to raise monospecific, polyclonal antibodies, which were subsequently analyzed on paraffin-embedded sections of malignant and normal tissue. In this study, we demonstrate that the initial selection strategy of MCL-associated genes successfully allows identification of protein antigens either uniquely expressed or overexpressed in MCL compared with normal lymphoid tissues. We propose that genome-based, affinity proteomics, using protein epitope signature tag-induced antibodies, is an efficient way to rapidly identify a number of disease-associated protein candidates of both previously known and unknown identities. PMID:16524965

Ek, Sara; Andréasson, Ulrika; Hober, Sophia; Kampf, Caroline; Pontén, Fredrik; Uhlén, Mathias; Merz, Hartmut; Borrebaeck, Carl A K

2006-06-01

286

Predicting environmental chemical factors associated with disease-related gene expression data  

PubMed Central

Background Many common diseases arise from an interaction between environmental and genetic factors. Our knowledge regarding environment and gene interactions is growing, but frameworks to build an association between gene-environment interactions and disease using preexisting, publicly available data has been lacking. Integrating freely-available environment-gene interaction and disease phenotype data would allow hypothesis generation for potential environmental associations to disease. Methods We integrated publicly available disease-specific gene expression microarray data and curated chemical-gene interaction data to systematically predict environmental chemicals associated with disease. We derived chemical-gene signatures for 1,338 chemical/environmental chemicals from the Comparative Toxicogenomics Database (CTD). We associated these chemical-gene signatures with differentially expressed genes from datasets found in the Gene Expression Omnibus (GEO) through an enrichment test. Results We were able to verify our analytic method by accurately identifying chemicals applied to samples and cell lines. Furthermore, we were able to predict known and novel environmental associations with prostate, lung, and breast cancers, such as estradiol and bisphenol A. Conclusions We have developed a scalable and statistical method to identify possible environmental associations with disease using publicly available data and have validated some of the associations in the literature.

2010-01-01

287

Comparative Genomic Analysis Identifies an ADP-Ribosylation Factor-like Gene as the Cause of Bardet-Biedl Syndrome (BBS3)  

PubMed Central

Bardet-Biedl syndrome (BBS) is a genetically heterogeneous, pleiotropic human disorder characterized by obesity, retinopathy, polydactyly, renal and cardiac malformations, learning disabilities, and hypogenitalism. Eight BBS loci have been mapped, and seven genes have been identified. BBS3 was previously mapped to chromosome 3 by linkage analysis in a large Israeli Bedouin kindred. The rarity of other families mapping to the BBS3 locus has made it difficult to narrow the disease interval sufficiently to identify the gene by positional cloning. We hypothesized that the genomes of model organisms that contained the orthologues to known BBS genes would also likely contain a BBS3 orthologue. Therefore, comparative genomic analysis was performed to prioritize BBS candidate genes for mutation screening. Known BBS proteins were compared with the translated genomes of model organisms to identify a subset of organisms in which these proteins were conserved. By including multiple organisms that have relatively small genome sizes in the analysis, the number of candidate genes was reduced, and a few genes mapping to the BBS3 interval emerged as the best candidates for this disorder. One of these genes, ADP-ribosylation factor-like 6 (ARL6), contains a homozygous stop mutation that segregates completely with the disease in the Bedouin kindred originally used to map the BBS3 locus, identifying this gene as the BBS3 gene. These data illustrate the power of comparative genomic analysis for the study of human disease and identifies a novel BBS gene.

Chiang, Annie P.; Nishimura, Darryl; Searby, Charles; Elbedour, Khalil; Carmi, Rivka; Ferguson, Amanda L.; Secrist, Jenifer; Braun, Terry; Casavant, Thomas; Stone, Edwin M.; Sheffield, Val C.

2004-01-01

288

A vertex similarity-based framework to discover and rank orphan disease-related genes  

PubMed Central

Background A rare or orphan disease (OD) is any disease that affects a small percentage of the population. While opportunities now exist to accelerate progress toward understanding the basis for many more ODs, the prioritization of candidate genes is still a critical step for disease-gene identification. Several network-based frameworks have been developed to address this problem with varied results. Result We have developed a novel vertex similarity (VS) based parameter-free prioritizing framework to identify and rank orphan disease candidate genes. We validate our approach by using 1598 known orphan disease-causing genes (ODGs) representing 172 orphan diseases (ODs). We compare our approach with a state-of-art parameter-based approach (PageRank with Priors or PRP) and with another parameter-free method (Interconnectedness or ICN). Our results show that VS-based approach outperforms ICN and is comparable to PRP. We further apply VS-based ranking to identify and rank potential novel candidate genes for several ODs. Conclusion We demonstrate that VS-based parameter-free ranking approach can be successfully used for disease candidate gene prioritization and can complement other network-based methods for candidate disease gene ranking. Importantly, our VS-ranked top candidate genes for the ODs match the known literature, suggesting several novel causal relationships for further investigation.

2012-01-01

289

Hashimoto's Thyroiditis: From Genes to the Disease.  

PubMed

Hashimoto's thyroiditis (HT) is the most prevalent autoimmune thyroid disorder. Intrathyroidal lymphocytic infiltration is followed by a gradual destruction of the thyroid gland which may lead to subclinical or overt hypothyroidism. Biochemical markers of the disease are thyroid peroxidase and/or thyroglobulin autoantibodies in the serum which are present with a higher prevalence in females than in males and increase with age. Although exact mechanisms of aetiology and pathogenesis of the disorder are not completely understood, a strong genetic susceptibility to the disease has been confirmed predominantly by family and twin studies. Several genes were shown to be associated with the disease occurrence, progression, and severity. Genes for human leukocyte antigen, cytotoxic T lymphocyte antigen-4, protein tyrosine phosphatase nonreceptor-type 22, thyroglobulin, vitamin D receptor, and cytokines are considered to be of utmost importance. Amongst endogenous factors for the disease development, the attention is focused predominantly on female sex, pregnancy with postpartum period and fetal microchimerism. Environmental factors influencing HT development are iodine intake, drugs, infections and different chemicals. Disturbed self-tolerance accompanied by the increased antigen presentation is a prerequisite for the HT occurrence, whereas proper interaction of thyroid cells, antigen presenting cells, and T cells are necessary for the initiation of thyroid autoimmunity. Secreted cytokines lead predominantly to T-helper type 1 (Th1) response as well as to Th 17 response which has only recently been implicated. Final outcome of HT is thyroid destruction which is mostly a consequence of the apoptotic processes combined with T-cell mediated cytotoxicity. PMID:22654557

Zaletel, Katja; Gaberš?ek, Simona

2011-12-01

290

Using BLAST for identifying gene and protein names in journal articles  

Microsoft Academic Search

We describe a system which automatically identifies gene and protein names in journal articles, an important and non-trivial first step in knowledge extraction of protein and gene actions. Our system uses a database of gene and protein names and is based on BLAST [Altschul et al., Nucleic Acids Res. 25 (1997) 3389–3402], a popular tool for DNA and protein sequence

Michael Krauthammer; Andrey Rzhetsky; Pavel Morozov; Carol Friedman

2000-01-01

291

A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data  

Microsoft Academic Search

BACKGROUND: The previous studies of genome-wide expression patterns show that a certain percentage of genes are cell cycle regulated. The expression data has been analyzed in a number of different ways to identify cell cycle dependent genes. In this study, we pose the hypothesis that cell cycle dependent genes are considered as oscillating systems with a rhythm, i.e. systems producing

Chang Sik Kim; Cheol Soo Bae; Hong Joon Tcha

2008-01-01

292

A General Approach for Identifying Distant Regulatory Elements Applied to the Gdf6 Gene  

Microsoft Academic Search

Regulatory sequences in higher genomes can map large distances from gene coding regions, and cannot yet be identified by simple inspection of primary DNA sequence information. Here we describe an efficient method of surveying large genomic regions for gene regulatory information, and subdividing complex sets of distant regulatory elements into smaller intervals for detailed study. The mouse Gdf6 gene is

Douglas P. Mortlock; Catherine Guenther; David M. Kingsley

2003-01-01

293

Leber congenital amaurosis: genes, proteins and disease mechanisms.  

PubMed

Leber congenital amaurosis (LCA) is the most severe retinal dystrophy causing blindness or severe visual impairment before the age of 1 year. Linkage analysis, homozygosity mapping and candidate gene analysis facilitated the identification of 14 genes mutated in patients with LCA and juvenile retinal degeneration, which together explain approximately 70% of the cases. Several of these genes have also been implicated in other non-syndromic or syndromic retinal diseases, such as retinitis pigmentosa and Joubert syndrome, respectively. CEP290 (15%), GUCY2D (12%), and CRB1 (10%) are the most frequently mutated LCA genes; one intronic CEP290 mutation (p.Cys998X) is found in approximately 20% of all LCA patients from north-western Europe, although this frequency is lower in other populations. Despite the large degree of genetic and allelic heterogeneity, it is possible to identify the causative mutations in approximately 55% of LCA patients by employing a microarray-based, allele-specific primer extension analysis of all known DNA variants. The LCA genes encode proteins with a wide variety of retinal functions, such as photoreceptor morphogenesis (CRB1, CRX), phototransduction (AIPL1, GUCY2D), vitamin A cycling (LRAT, RDH12, RPE65), guanine synthesis (IMPDH1), and outer segment phagocytosis (MERTK). Recently, several defects were identified that are likely to affect intra-photoreceptor ciliary transport processes (CEP290, LCA5, RPGRIP1, TULP1). As the eye represents an accessible and immune-privileged organ, it appears to be uniquely suitable for human gene replacement therapy. Rodent (Crb1, Lrat, Mertk, Rpe65, Rpgrip1), avian (Gucy2D) and canine (Rpe65) models for LCA and profound visual impairment have been successfully corrected employing adeno-associated virus or lentivirus-based gene therapy. Moreover, phase 1 clinical trials have been carried out in humans with RPE65 deficiencies. Apart from ethical considerations inherently linked to treating children, major obstacles for the treatment of LCA could be the putative developmental deficiencies in the visual cortex in persons blind from birth (amblyopia), the absence of sufficient numbers of viable photoreceptor or RPE cells in LCA patients, and the unknown and possibly toxic effects of overexpression of transduced genes. Future LCA research will focus on the identification of the remaining causal genes, the elucidation of the molecular mechanisms of disease in the retina, and the development of gene therapy approaches for different genetic subtypes of LCA. PMID:18632300

den Hollander, Anneke I; Roepman, Ronald; Koenekoop, Robert K; Cremers, Frans P M

2008-07-01

294

Family-based analysis identified CD2 as a susceptibility gene for primary open angle glaucoma in Chinese Han population.  

PubMed

Primary open angle glaucoma (POAG) is characterized by optic disc cupping and irreversible loss of retinal ganglion cells. Few genes have been detected that influence POAG susceptibility and little is known about its genetic architecture. In this study, we employed exome sequencing on three members from a high frequency POAG family to identify the risk factors of POAG in Chinese population. Text-mining method was applied to identify genes associated with glaucoma in literature, and protein-protein interaction networks were constructed. Furthermore, reverse transcription PCR and Western blot were performed to confirm the differential gene expression. Six genes, baculoviral inhibitors of apoptosis protein repeat containing 6 (BIRC6), CD2, luteinizing hormone/choriogonadotropin receptor (LHCGR), polycystic kidney and hepatic disease gene 1 (PKHD1), phenylalanine hydroxylase (PAH) and fucosyltransferase 7 (FUT7), which might be associated with POAG, were identified. Both the mRNA expression levels and protein expression levels of HSP27 were increased in astrocytes from POAG patients compared with those from normal control, suggesting that mutation in CD2 might pose a risk for POAG in Chinese population. In conclusion, novel rare variants detected by exome sequencing may hold the key to unravelling the remaining contribution of genetics to complex diseases such as POAG. PMID:24597656

Liu, Ting; Xie, Lin; Ye, Jian; He, Xiangge

2014-04-01

295

A WIDE TOMATO DISEASE GENES SCANNING FOR R GENE MARKERS DEVELOPMENT  

Microsoft Academic Search

in silico analysis resistance gene, tomato genome, SNPs, multiplex Plant disease resistance genes (R-Genes) are an important class of genes from which a subset are well characterized at the molecular level. These genes play a key role in the recognition of the products of avirulence (Avr) genes from pathogens and in the activation of plant defence responses. In the Solanaceae

296

A genome-wide association study of psoriasis and psoriatic arthritis identifies new disease loci.  

PubMed

A genome-wide association study was performed to identify genetic factors involved in susceptibility to psoriasis (PS) and psoriatic arthritis (PSA), inflammatory diseases of the skin and joints in humans. 223 PS cases (including 91 with PSA) were genotyped with 311,398 single nucleotide polymorphisms (SNPs), and results were compared with those from 519 Northern European controls. Replications were performed with an independent cohort of 577 PS cases and 737 controls from the U.S., and 576 PSA patients and 480 controls from the U.K.. Strongest associations were with the class I region of the major histocompatibility complex (MHC). The most highly associated SNP was rs10484554, which lies 34.7 kb upstream from HLA-C (P = 7.8x10(-11), GWA scan; P = 1.8x10(-30), replication; P = 1.8x10(-39), combined; U.K. PSA: P = 6.9x10(-11)). However, rs2395029 encoding the G2V polymorphism within the class I gene HCP5 (combined P = 2.13x10(-26) in U.S. cases) yielded the highest ORs with both PS and PSA (4.1 and 3.2 respectively). This variant is associated with low viral set point following HIV infection and its effect is independent of rs10484554. We replicated the previously reported association with interleukin 23 receptor and interleukin 12B (IL12B) polymorphisms in PS and PSA cohorts (IL23R: rs11209026, U.S. PS, P = 1.4x10(-4); U.K. PSA: P = 8.0x10(-4); IL12B:rs6887695, U.S. PS, P = 5x10(-5) and U.K. PSA, P = 1.3x10(-3)) and detected an independent association in the IL23R region with a SNP 4 kb upstream from IL12RB2 (P = 0.001). Novel associations replicated in the U.S. PS cohort included the region harboring lipoma HMGIC fusion partner (LHFP) and conserved oligomeric golgi complex component 6 (COG6) genes on chromosome 13q13 (combined P = 2x10(-6) for rs7993214; OR = 0.71), the late cornified envelope gene cluster (LCE) from the Epidermal Differentiation Complex (PSORS4) (combined P = 6.2x10(-5) for rs6701216; OR 1.45) and a region of LD at 15q21 (combined P = 2.9x10(-5) for rs3803369; OR = 1.43). This region is of interest because it harbors ubiquitin-specific protease-8 whose processed pseudogene lies upstream from HLA-C. This region of 15q21 also harbors the gene for SPPL2A (signal peptide peptidase like 2a) which activates tumor necrosis factor alpha by cleavage, triggering the expression of IL12 in human dendritic cells. We also identified a novel PSA (and potentially PS) locus on chromosome 4q27. This region harbors the interleukin 2 (IL2) and interleukin 21 (IL21) genes and was recently shown to be associated with four autoimmune diseases (Celiac disease, Type 1 diabetes, Grave's disease and Rheumatoid Arthritis). PMID:18369459

Liu, Ying; Helms, Cynthia; Liao, Wilson; Zaba, Lisa C; Duan, Shenghui; Gardner, Jennifer; Wise, Carol; Miner, Andrew; Malloy, M J; Pullinger, Clive R; Kane, John P; Saccone, Scott; Worthington, Jane; Bruce, Ian; Kwok, Pui-Yan; Menter, Alan; Krueger, James; Barton, Anne; Saccone, Nancy L; Bowcock, Anne M

2008-03-01

297

Analysis of antigen receptor genes in Hodgkin's disease.  

PubMed Central

AIM--To analyse the configuration of the antigen receptor genes in Hodgkin's disease. METHODS--DNA extracted from 45 samples of Hodgkin's disease was analysed using Southern blotting and DNA hybridisation, using probes to the joining region of the immunoglobulin heavy chain gene, the constant region of kappa immunoglobulin light chain gene, and the constant region of the beta chain of the T cell receptor gene. RESULTS--A single case of nodular sclerosing disease showed clonal rearrangement of the immunoglobulin heavy and light chain genes, all other samples having germline immunoglobulin genes. The nature of the clonal population in the diseased tissue is uncertain, because the intensity of the rearranged bands did not correlate with the percentage of Reed-Sternberg cells present. The T cell receptor genes were in germline configuration in all the samples. CONCLUSIONS--Antigen receptor gene rearrangement is a rare finding in unselected cases of Hodgkin's disease. Images

Angel, C A; Pringle, J H; Naylor, J; West, K P; Lauder, I

1993-01-01

298

Genetic Association Study Identifies HSPB7 as a Risk Gene for Idiopathic Dilated Cardiomyopathy  

PubMed Central

Dilated cardiomyopathy (DCM) is a structural heart disease with strong genetic background. Monogenic forms of DCM are observed in families with mutations located mostly in genes encoding structural and sarcomeric proteins. However, strong evidence suggests that genetic factors also affect the susceptibility to idiopathic DCM. To identify risk alleles for non-familial forms of DCM, we carried out a case-control association study, genotyping 664 DCM cases and 1,874 population-based healthy controls from Germany using a 50K human cardiovascular disease bead chip covering more than 2,000 genes pre-selected for cardiovascular relevance. After quality control, 30,920 single nucleotide polymorphisms (SNP) were tested for association with the disease by logistic regression adjusted for gender, and results were genomic-control corrected. The analysis revealed a significant association between a SNP in HSPB7 gene (rs1739843, minor allele frequency 39%) and idiopathic DCM (p?=?1.06×10?6, OR?=?0.67 [95% CI 0.57–0.79] for the minor allele T). Three more SNPs showed p < 2.21×10?5. De novo genotyping of these four SNPs was done in three independent case-control studies of idiopathic DCM. Association between SNP rs1739843 and DCM was significant in all replication samples: Germany (n?=?564, n?=?981 controls, p?=?2.07×10?3, OR?=?0.79 [95% CI 0.67–0.92]), France 1 (n?=?433 cases, n?=?395 controls, p?=?3.73×10?3, OR?=?0.74 [95% CI 0.60–0.91]), and France 2 (n?=?249 cases, n?=?380 controls, p?=?2.26×10?4, OR?=?0.63 [95% CI 0.50–0.81]). The combined analysis of all four studies including a total of n?=?1,910 cases and n?=?3,630 controls showed highly significant evidence for association between rs1739843 and idiopathic DCM (p?=?5.28×10?13, OR?=?0.72 [95% CI 0.65–0.78]). None of the other three SNPs showed significant results in the replication stage. This finding of the HSPB7 gene from a genetic search for idiopathic DCM using a large SNP panel underscores the influence of common polymorphisms on DCM susceptibility.

Stark, Klaus; Esslinger, Ulrike B.; Reinhard, Wibke; Petrov, George; Winkler, Thomas; Komajda, Michel; Isnard, Richard; Charron, Philippe; Villard, Eric; Cambien, Francois; Tiret, Laurence; Aumont, Marie-Claude; Dubourg, Olivier; Trochu, Jean-Noel; Fauchier, Laurent; DeGroote, Pascal; Richter, Anette; Maisch, Bernhard; Wichter, Thomas; Zollbrecht, Christa; Grassl, Martina; Schunkert, Heribert; Linsel-Nitschke, Patrick; Erdmann, Jeanette; Baumert, Jens; Illig, Thomas; Klopp, Norman; Wichmann, H.-Erich; Meisinger, Christa; Koenig, Wolfgang; Lichtner, Peter; Meitinger, Thomas; Schillert, Arne; Konig, Inke R.; Hetzer, Roland; Heid, Iris M.; Regitz-Zagrosek, Vera; Hengstenberg, Christian

2010-01-01

299

Identifying Subspace Gene Clusters from Microarray Data Using Low-Rank Representation  

PubMed Central

Identifying subspace gene clusters from the gene expression data is useful for discovering novel functional gene interactions. In this paper, we propose to use low-rank representation (LRR) to identify the subspace gene clusters from microarray data. LRR seeks the lowest-rank representation among all the candidates that can represent the genes as linear combinations of the bases in the dataset. The clusters can be extracted based on the block diagonal representation matrix obtained using LRR, and they can well capture the intrinsic patterns of genes with similar functions. Meanwhile, the parameter of LRR can balance the effect of noise so that the method is capable of extracting useful information from the data with high level of background noise. Compared with traditional methods, our approach can identify genes with similar functions yet without similar expression profiles. Also, it could assign one gene into different clusters. Moreover, our method is robust to the noise and can identify more biologically relevant gene clusters. When applied to three public datasets, the results show that the LRR based method is superior to existing methods for identifying subspace gene clusters.

Cui, Yan; Zheng, Chun-Hou; Yang, Jian

2013-01-01

300

Mechanistic phenotypes: an aggregative phenotyping strategy to identify disease mechanisms using GWAS data.  

PubMed

A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with "mechanistic phenotypes", comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p?=?0.0001, FDR p?=?0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p?=?2×10-5, FDR p?=?0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p?=?4×10-6, FDR p?=?0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms. PMID:24349080

Mosley, Jonathan D; Van Driest, Sara L; Larkin, Emma K; Weeke, Peter E; Witte, John S; Wells, Quinn S; Karnes, Jason H; Guo, Yan; Bastarache, Lisa; Olson, Lana M; McCarty, Catherine A; Pacheco, Jennifer A; Jarvik, Gail P; Carrell, David S; Larson, Eric B; Crosslin, David R; Kullo, Iftikhar J; Tromp, Gerard; Kuivaniemi, Helena; Carey, David J; Ritchie, Marylyn D; Denny, Josh C; Roden, Dan M

2013-01-01

301

Mechanistic Phenotypes: An Aggregative Phenotyping Strategy to Identify Disease Mechanisms Using GWAS Data  

PubMed Central

A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1) non-synonymous SNPs (nsSNPs) associated with “mechanistic phenotypes”, comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1) thrombosis, evaluated in a population of 1,655 African Americans; and (2) four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs), and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p?=?0.0001, FDR p?=?0.03), driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p?=?2×10?5, FDR p?=?0.03) (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L) while the additive model showed enrichment related to chromatid segregation (p?=?4×10?6, FDR p?=?0.005) (KIF25, PINX1). We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.

Mosley, Jonathan D.; Van Driest, Sara L.; Larkin, Emma K.; Weeke, Peter E.; Witte, John S.; Wells, Quinn S.; Karnes, Jason H.; Guo, Yan; Bastarache, Lisa; Olson, Lana M.; McCarty, Catherine A.; Pacheco, Jennifer A.; Jarvik, Gail P.; Carrell, David S.; Larson, Eric B.; Crosslin, David R.; Kullo, Iftikhar J.; Tromp, Gerard; Kuivaniemi, Helena; Carey, David J.; Ritchie, Marylyn D.; Denny, Josh C.; Roden, Dan M.

2013-01-01

302

Global analysis of the human pathophenotypic similarity gene network merges disease module components.  

PubMed

The molecular complexity of genetic diseases requires novel approaches to break it down into coherent biological modules. For this purpose, many disease network models have been created and analyzed. We highlight two of them, "the human diseases networks" (HDN) and "the orphan disease networks" (ODN). However, in these models, each single node represents one disease or an ambiguous group of diseases. In these cases, the notion of diseases as unique entities reduces the usefulness of network-based methods. We hypothesize that using the clinical features (pathophenotypes) to define pathophenotypic connections between disease-causing genes improve our understanding of the molecular events originated by genetic disturbances. For this, we have built a pathophenotypic similarity gene network (PSGN) and compared it with the unipartite projections (based on gene-to-gene edges) similar to those used in previous network models (HDN and ODN). Unlike these disease network models, the PSGN uses semantic similarities. This pathophenotypic similarity has been calculated by comparing pathophenotypic annotations of genes (human abnormalities of HPO terms) in the "Human Phenotype Ontology". The resulting network contains 1075 genes (nodes) and 26197 significant pathophenotypic similarities (edges). A global analysis of this network reveals: unnoticed pairs of genes showing significant pathophenotypic similarity, a biological meaningful re-arrangement of the pathological relationships between genes, correlations of biochemical interactions with higher similarity scores and functional biases in metabolic and essential genes toward the pathophenotypic specificity and the pleiotropy, respectively. Additionally, pathophenotypic similarities and metabolic interactions of genes associated with maple syrup urine disease (MSUD) have been used to merge into a coherent pathological module.Our results indicate that pathophenotypes contribute to identify underlying co-dependencies among disease-causing genes that are useful to describe disease modularity. PMID:23437198

Reyes-Palomares, Armando; Rodríguez-López, Rocío; Ranea, Juan A G; Sánchez Jiménez, Francisca; Medina, Miguel Angel

2013-01-01

303

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits.  

PubMed

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations. PMID:24314549

Benton, Miles C; Lea, Rod A; Macartney-Coxson, Donia; Carless, Melanie A; Göring, Harald H; Bellis, Claire; Hanna, Michelle; Eccles, David; Chambers, Geoffrey K; Curran, Joanne E; Harper, Jacquie L; Blangero, John; Griffiths, Lyn R

2013-12-01

304

Mapping eQTLs in the Norfolk Island Genetic Isolate Identifies Candidate Genes for CVD Risk Traits  

PubMed Central

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10?7) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

Benton, Miles C.; Lea, Rod A.; Macartney-Coxson, Donia; Carless, Melanie A.; Goring, Harald H.; Bellis, Claire; Hanna, Michelle; Eccles, David; Chambers, Geoffrey K.; Curran, Joanne E.; Harper, Jacquie L.; Blangero, John; Griffiths, Lyn R.

2013-01-01

305

An integrated approach to infer causal associations among gene expression, genotype variation, and disease.  

PubMed

Gene expression data and genotype variation data are now capable of providing genome-wide patterns across many different clinical conditions. However, the separate analysis of these data has limitations in elucidating the complex network of gene interactions underlying complex traits, such as common human diseases. More information about the identity of key driver genes of common diseases comes from integrating these two heterogeneous types of data. We developed a two-step procedure to characterize complex diseases by integrating genotype variation data and gene expression data. The first step elucidates the causal relationship among genetic variation, gene expression level, and disease. Based on the causal relationship determined at the first step, the second step identifies significant gene expression traits whose effects on disease status or whose responses to disease status are modified by the specific genotype variation. For the selected significant genes, a pathway enrichment analysis can be performed to identify the genetic mechanism of a complex disease. The proposed two-step procedure was shown to be an effective method for integrating three different levels of data, i.e., genotype variation, gene expression and disease status. By applying the proposed procedure to a chronic fatigue syndrome (CFS) dataset, we identified a list of potential causal genes for CFS, and found an evidence for difference in genetic mechanisms of the etiology between CFS without 'a major depressive disorder with melancholic features' (CFS) and CFS with 'a major depressive disorder with melancholic features' (CFS-MDD/m). Especially, the SNPs within NR3C1 gene were shown to differently influence the susceptibility of developing CFS and CFS-MDD/m through integrative action with gene expression levels. PMID:19540336

Lee, Eunjee; Cho, Seoae; Kim, Kyunga; Park, Taesung

2009-10-01

306

De Novo Copy Number Variants Identify New Genes and Loci in Isolated, Sporadic Tetralogy of Fallot  

PubMed Central

Tetralogy of Fallot (TOF), the most common severe congenital heart malformation, occurs sporadically, without other anomaly, and from unknown cause in 70% of cases. A genome-wide survey of 114 TOF patients and their unaffected parents identified 11 de novo copy number variants (CNVs) that were absent or extremely rare (<0.1%) in 2,265 controls. A second, independent TOF cohort (n = 398) was then examined for additional CNVs at these loci. In 1% (5/512, p = 0.0002, OR = 22.3) of non-syndromic sporadic TOF cases we identified CNVs at chromosome 1q21.1. Recurrent CNVs were also identified at 3p25.1, 7p21.3 and 22q11.2. CNVs in a single TOF case occurred at six loci, two that encode known (NOTCH1, JAG1) disease genes. Our data predicts that at least 10% (4.5–15.5, 95% CI) of sporadic, non-syndromic TOF reflects de novo CNVs and implicates mutations within these loci as etiologic in other cases of TOF.

Greenway, Steven C; Pereira, Alexandre C; Lin, Jennifer C; DePalma, Steven R; Israel, Samuel J; Mesquita, Sonia M; Ergul, Emel; Conta, Jessie R; Korn, Joshua M; McCarroll, Steven A; Gorham, Joshua M; Gabriel, Stacey; Altshuler, David A; de Lourdes Quintanilla-Dieck, Maria; Artunduaga, Maria Alexandra; Eavey, Roland D; Plenge, Robert M; Shadick, Nancy A; Weinblatt, Michael E; De Jager, Philip L; Hafler, David A; Breitbart, Roger E; Seidman, J G; Seidman, Christine E

2009-01-01

307

Identifying Neisseria Species by Use of the 50S Ribosomal Protein L6 (rplF) Gene  

PubMed Central

The comparison of 16S rRNA gene sequences is widely used to differentiate bacteria; however, this gene can lack resolution among closely related but distinct members of the same genus. This is a problem in clinical situations in those genera, such as Neisseria, where some species are associated with disease while others are not. Here, we identified and validated an alternative genetic target common to all Neisseria species which can be readily sequenced to provide an assay that rapidly and accurately discriminates among members of the genus. Ribosomal multilocus sequence typing (rMLST) using ribosomal protein genes has been shown to unambiguously identify these bacteria. The PubMLST Neisseria database (http://pubmlst.org/neisseria/) was queried to extract the 53 ribosomal protein gene sequences from 44 genomes from diverse species. Phylogenies reconstructed from these genes were examined, and a single 413-bp fragment of the 50S ribosomal protein L6 (rplF) gene was identified which produced a phylogeny that was congruent with the phylogeny reconstructed from concatenated ribosomal protein genes. Primers that enabled the amplification and direct sequencing of the rplF gene fragment were designed to validate the assay in vitro and in silico. Allele sequences were defined for the gene fragment, associated with particular species names, and stored on the PubMLST Neisseria database, providing a curated electronic resource. This approach provides an alternative to 16S rRNA gene sequencing, which can be readily replicated for other organisms for which more resolution is required, and it has potential applications in high-resolution metagenomic studies.

Bennett, Julia S.; Watkins, Eleanor R.; Jolley, Keith A.; Harrison, Odile B.

2014-01-01

308

Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data  

PubMed Central

Background Interactions among genomic loci (also known as epistasis) have been suggested as one of the potential sources of missing heritability in single locus analysis of genome-wide association studies (GWAS). The computational burden of searching for interactions is compounded by the extremely low threshold for identifying significant p-values due to multiple hypothesis testing corrections. Utilizing prior biological knowledge to restrict the set of candidate SNP pairs to be tested can alleviate this problem, but systematic studies that investigate the relative merits of integrating different biological frameworks and GWAS data have not been conducted. Results We developed four biologically based frameworks to identify pairwise interactions among candidate SNP pairs as follows: (1) for each human protein-coding gene, a set of SNPs associated with that gene was constructed providing a gene-based interaction model, (2) for each known biological pathway, a set of SNPs associated with the genes in the pathway was constructed providing a pathway-based interaction model, (3) a set of SNPs associated with genes in a disease-related subnetwork provides a network-based interaction model, and (4) a framework is based on the function of SNPs. The last approach uses expression SNPs (eSNPs or eQTLs), which are SNPs or loci that have defined effects on the abundance of transcripts of other genes. We constructed pairs of eSNPs and SNPs located in the target genes whose expression is regulated by eSNPs. For all four frameworks the SNP sets were exhaustively tested for pairwise interactions within the sets using a traditional logistic regression model after excluding genes that were previously identified to associate with the trait. Using previously published GWAS data for type 2 diabetes (T2D) and the biologically based pair-wise interaction modeling, we identify twelve genes not seen in the previous single locus analysis. Conclusion We present four approaches to detect interactions associated with complex diseases. The results show our approaches outperform the traditional single locus approaches in detecting genes that previously did not reach significance; the results also provide novel drug targets and biomarkers relevant to the underlying mechanisms of disease.

2012-01-01

309

Allelic Variants of Complement Genes Associated with Dense Deposit Disease  

PubMed Central

The alternative pathway of the complement cascade plays a role in the pathogenesis of dense deposit disease (DDD). Deficiency of complement factor H and mutations in CFH associate with the development of DDD, but it is unknown whether allelic variants in other complement genes also associate with this disease. We studied patients with DDD and identified previously unreported sequence alterations in several genes in addition to allelic variants and haplotypes common to patients with DDD. We found that the likelihood of developing DDD increases with the presence of two or more risk alleles in CFH and C3. To determine the functional consequence of this finding, we measured the activity of the alternative pathway in serum samples from phenotypically normal controls genotyped for variants in CFH and C3. Alternative pathway activity was higher in the presence of variants associated with DDD. Taken together, these data confirm that DDD is a complex genetic disease and may provide targets for the development of disease-specific therapies.

Abrera-Abeleda, Maria Asuncion; Nishimura, Carla; Frees, Kathy; Jones, Michael; Maga, Tara; Katz, Louis M.; Zhang, Yuzhou

2011-01-01

310

The KM-Algorithm Identifies Regulated Genes in Time Series Expression Data  

PubMed Central

We present a statistical method to rank observed genes in gene expression time series experiments according to their degree of regulation in a biological process. The ranking may be used to focus on specific genes or to select meaningful subsets of genes from which gene regulatory networks can be built. Our approach is based on a state space model that incorporates hidden regulators of gene expression. Kalman (K) smoothing and maximum (M) likelihood estimation techniques are used to derive optimal estimates of the model parameters upon which a proposed regulation criterion is based. The statistical power of the proposed algorithm is investigated, and a real data set is analyzed for the purpose of identifying regulated genes in time dependent gene expression data. This statistical approach supports the concept that meaningful biological conclusions can be drawn from gene expression time series experiments by focusing on strong regulation rather than large expression values.

Bremer, Martina; Doerge, R. W.

2009-01-01

311

New Genes and New Insights from Old Genes: Update on Alzheimer Disease  

PubMed Central

Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets.

Ringman, John M.; Coppola, Giovanni

2013-01-01

312

PCR-Based Strategy To Detect and Identify Species of Phaeoacremonium Causing Grapevine Diseases  

Microsoft Academic Search

Species of Phaeoacremonium (especially Phaeoacremonium aleophilum) are associated with two severe diseases in grapevines, Petri disease in young plants and Esca disease in adult plants. Phaeoacremonium species grow slowly on culture medium, and it is difficult to identify these species on the basis of morphological characteristics. Primers Pm1 and Pm2 were designed in the ribosomal DNA internal transcribed spacer (ITS)

Angeles Aroca; Rosa Raposo

2007-01-01

313

Novel Biomarkers Distinguishing Active Tuberculosis from Latent Infection Identified by Gene Expression Profile of Peripheral Blood Mononuclear Cells  

PubMed Central

Background Humans infected with Mycobacterium tuberculosis (MTB) can delete the pathogen or otherwise become latent infection or active disease. However, the factors influencing the pathogen clearance and disease progression from latent infection are poorly understood. This study attempted to use a genome-wide transcriptome approach to identify immune factors associated with MTB infection and novel biomarkers that can distinguish active disease from latent infection. Methodology/Principal Findings Using microarray analysis, we comprehensively determined the transcriptional difference in purified protein derivative (PPD) stimulated peripheral blood mononuclear cells (PBMCs) in 12 individuals divided into three groups: TB patients (TB), latent TB infection individuals (LTBI) and healthy controls (HC) (n?=?4 per group). A transcriptional profiling of 506 differentially expressed genes could correctly group study individuals into three clusters. Moreover, 55- and 229-transcript signatures for tuberculosis infection (TB<BI) and active disease (TB) were identified, respectively. The validation study by quantitative real-time PCR (qPCR) performed in 83 individuals confirmed the expression patterns of 81% of the microarray identified genes. Decision tree analysis indicated that three genes of CXCL10, ATP10A and TLR6 could differentiate TB from LTBI subjects. Additional validation was performed to assess the diagnostic ability of the three biomarkers within 36 subjects, which yielded a sensitivity of 71% and specificity of 89%. Conclusions/Significance The transcription profiles of PBMCs induced by PPD identified distinctive gene expression patterns associated with different infectious status and provided new insights into human immune responses to MTB. Furthermore, this study indicated that a combination of CXCL10, ATP10A and TLR6 could be used as novel biomarkers for the discrimination of TB from LTBI.

Lu, Chanyi; Wu, Jing; Wang, Honghai; Wang, Sen; Diao, Ni; Wang, Feifei; Gao, Yan; Chen, Jiazhen; Shao, Lingyun; Weng, Xinhua; Zhang, Ying; Zhang, Wenhong

2011-01-01

314

A Comparative Transcriptome Analysis Identifying FGF23 Regulated Genes in the Kidney of a Mouse CKD Model  

PubMed Central

Elevations of circulating Fibroblast growth factor 23 (FGF23) are associated with adverse cardiovascular outcomes and progression of renal failure in chronic kidney disease (CKD). Efforts to identify gene products whose transcription is directly regulated by FGF23 stimulation of fibroblast growth factor receptors (FGFR)/?-Klotho complexes in the kidney is confounded by both systemic alterations in calcium, phosphorus and vitamin D metabolism and intrinsic alterations caused by the underlying renal pathology in CKD. To identify FGF23 responsive genes in the kidney that might explain the association between FGF23 and adverse outcomes in CKD, we performed comparative genome wide analysis of gene expression profiles in the kidney of the Collagen 4 alpha 3 null mice (Col4a3?/?) model of progressive kidney disease with kidney expression profiles of Hypophosphatemic (Hyp) and FGF23 transgenic mouse models of elevated FGF23. The different complement of potentially confounding factors in these models allowed us to identify genes that are directly targeted by FGF23. This analysis found that ?-Klotho, an anti-aging hormone and FGF23 co-receptor, was decreased by FGF23. We also identified additional FGF23-responsive transcripts and activation of networks associated with renal damage and chronic inflammation, including lipocalin 2 (Lcn2), transforming growth factor beta (TGF-?) and tumor necrosis factor-alpha (TNF-?) signaling pathways. Finally, we found that FGF23 suppresses angiotensin-converting enzyme 2 (ACE2) expression in the kidney, thereby providing a pathway for FGF23 regulation of the renin-angiotensin system. These gene products provide a possible mechanistic links between elevated FGF23 and pathways responsible for renal failure progression and cardiovascular diseases.

Martin, Aline; Huang, Jinsong; Li, Hua; Jiao, Yan; Gu, Weikuan; Quarles, L. Darryl

2012-01-01

315

A Microarray-Based Gene Expression Analysis to Identify Diagnostic Biomarkers for Unknown Primary Cancer  

PubMed Central

Background The biological basis for cancer of unknown primary (CUP) at the molecular level remains largely unknown, with no evidence of whether a common biological entity exists. Here, we assessed the possibility of identifying a common diagnostic biomarker for CUP using a microarray gene expression analysis. Methods Tumor mRNA samples from 60 patients with CUP were analyzed using the Affymetrix U133A Plus 2.0 GeneChip and were normalized by asinh (hyperbolic arc sine) transformation to construct a mean gene-expression profile specific to CUP. A gene-expression profile specific to non-CUP group was constructed using publicly available raw microarray datasets. The t-tests were performed to compare the CUP with non-CUP groups and the top 59 CUP specific genes with the highest fold change were selected (p-value<0.001). Results Among the 44 genes that were up-regulated in the CUP group, 6 genes for ribosomal proteins were identified. Two of these genes (RPS7 and RPL11) are known to be involved in the Mdm2–p53 pathway. We also identified several genes related to metastasis and apoptosis, suggesting a biological attribute of CUP. Conclusions The protein products of the up-regulated and down-regulated genes identified in this study may be clinically useful as unique biomarkers for CUP.

Kurahashi, Issei; Fujita, Yoshihiko; Arao, Tokuzo; Kurata, Takayasu; Koh, Yasuhiro; Sakai, Kazuko; Matsumoto, Koji; Tanioka, Maki; Takeda, Koji; Takiguchi, Yuichi; Yamamoto, Nobuyuki; Tsuya, Asuka; Matsubara, Nobuaki; Mukai, Hirofumi; Minami, Hironobu; Chayahara, Naoko; Yamanaka, Yasuhiro; Miwa, Keisuke; Takahashi, Shin; Takahashi, Shunji; Nakagawa, Kazuhiko; Nishio, Kazuto

2013-01-01

316

Exploiting Protein-Protein Interaction Networks for Genome-Wide Disease-Gene Prioritization  

PubMed Central

Complex genetic disorders often involve products of multiple genes acting cooperatively. Hence, the pathophenotype is the outcome of the perturbations in the underlying pathways, where gene products cooperate through various mechanisms such as protein-protein interactions. Pinpointing the decisive elements of such disease pathways is still challenging. Over the last years, computational approaches exploiting interaction network topology have been successfully applied to prioritize individual genes involved in diseases. Although linkage intervals provide a list of disease-gene candidates, recent genome-wide studies demonstrate that genes not associated with any known linkage interval may also contribute to the disease phenotype. Network based prioritization methods help highlighting such associations. Still, there is a need for robust methods that capture the interplay among disease-associated genes mediated by the topology of the network. Here, we propose a genome-wide network-based prioritization framework named GUILD. This framework implements four network-based disease-gene prioritization algorithms. We analyze the performance of these algorithms in dozens of disease phenotypes. The algorithms in GUILD are compared to state-of-the-art network topology based algorithms for prioritization of genes. As a proof of principle, we investigate top-ranking genes in Alzheimer's disease (AD), diabetes and AIDS using disease-gene associations from various sources. We show that GUILD is able to significantly highlight disease-gene associations that are not used a priori. Our findings suggest that GUILD helps to identify genes implicated in the pathology of human disorders independent of the loci associated with the disorders.

Guney, Emre; Oliva, Baldo

2012-01-01

317

Exploiting protein-protein interaction networks for genome-wide disease-gene prioritization.  

PubMed

Complex genetic disorders often involve products of multiple genes acting cooperatively. Hence, the pathophenotype is the outcome of the perturbations in the underlying pathways, where gene products cooperate through various mechanisms such as protein-protein interactions. Pinpointing the decisive elements of such disease pathways is still challenging. Over the last years, computational approaches exploiting interaction network topology have been successfully applied to prioritize individual genes involved in diseases. Although linkage intervals provide a list of disease-gene candidates, recent genome-wide studies demonstrate that genes not associated with any known linkage interval may also contribute to the disease phenotype. Network based prioritization methods help highlighting such associations. Still, there is a need for robust methods that capture the interplay among disease-associated genes mediated by the topology of the network. Here, we propose a genome-wide network-based prioritization framework named GUILD. This framework implements four network-based disease-gene prioritization algorithms. We analyze the performance of these algorithms in dozens of disease phenotypes. The algorithms in GUILD are compared to state-of-the-art network topology based algorithms for prioritization of genes. As a proof of principle, we investigate top-ranking genes in Alzheimer's disease (AD), diabetes and AIDS using disease-gene associations from various sources. We show that GUILD is able to significantly highlight disease-gene associations that are not used a priori. Our findings suggest that GUILD helps to identify genes implicated in the pathology of human disorders independent of the loci associated with the disorders. PMID:23028459

Guney, Emre; Oliva, Baldo

2012-01-01

318

Gene expression profiling of murine T-cell lymphoblastic lymphoma identifies deregulation of S-phase initiating genes?  

PubMed Central

In a search for genes and pathways implicated in T-cell lymphoblastic lymphoma (T-LBL) development, we used a murine lymphoma model, where mice of the NMRI-inbred strain were inoculated with murine leukemia virus mutants. The resulting tumors were analyzed by integration analysis and global gene expression profiling to determine the effect of the retroviral integrations on the nearby genes, and the deregulated pathways in the tumors. Gene expression profiling identified increased expression of genes involved in the minichromosome maintenance and origin of recognition pathway as well as downregulation in negative regulators of G1/S transition, indicating increased S-phase initiation in murine T-LBLs.

Dabrowska, Magdalena Julia; Ejegod, Ditte; Lassen, Louise Berkhoudt; Johnsen, Hans Erik; Wabl, Matthias; Pedersen, Finn Skou; Dybkaer, Karen

2014-01-01

319

Systematic 16S rRNA Gene Sequencing of Atypical Clinical Isolates Identified 27 New Bacterial Species Associated with Humans  

PubMed Central

Clinical microorganisms isolated during a 5-year study in our hospital that could not be identified by conventional criteria were studied by 16S rRNA gene sequence analysis. Each isolate yielded a ?1,400-bp sequence containing <5 ambiguities which was compared with the GenBank 16S rRNA gene library; 1,404 such isolates were tested, and 120 were considered unique (27 isolates) or rare (?10 cases reported in the literature) human pathogens. Eleven new species, “Actinobaculum massiliae,” “Candidatus Actinobaculum timonae,” Paenibacillus sanguinis, “Candidatus Bacteroides massiliae,” Chryseobacterium massiliae, “Candidatus Chryseobacterium timonae,” Paenibacillus massiliensis, “Candidatus Peptostreptococcus massiliae,” “Candidatus Prevotella massiliensis,” Rhodobacter massiliensis, and “Candidatus Veillonella atypica” were identified. Sixteen species were obtained from humans for the first time. Our results show the important role that 16S rRNA gene sequence-based bacterial identification currently plays in recognizing unusual and emerging bacterial diseases.

Drancourt, M.; Berger, P.; Raoult, D.

2004-01-01

320

Gene expression profiling of human adrenocortical tumors using complementary deoxyribonucleic Acid microarrays identifies several candidate genes as markers of malignancy.  

PubMed

The aim of this study was to identify predictor sets of genes whose over- or underexpression in human sporadic adrenocortical tumors would help to identify malignant vs. benign tumors and to predict postsurgical metastatic recurrence. For this, we analyzed the expression of 230 candidate genes using cDNA microarrays in a series of 57 well-characterized human sporadic adrenocortical tumors (33 adenomas and 24 carcinomas). We identified two clusters of genes (the IGF-II cluster containing eight genes, including IGF-II, and the steroidogenesis cluster containing six genes encoding steroidogenic enzymes plus eight other genes) whose combined levels of expression appeared to be good predictors of malignancy. This predictive value was as strong as that of the pathological score of Weiss. The analysis of the population of carcinomas (13 tumors) for genes whose expression would be strongly different between recurring and nonrecurring tumors allowed identification of 14 genes meeting these criteria. Among these genes, there are probably new markers of tumor evolution that will deserve additional validation on a larger scale. Taken together, these results show that the parallel analysis of the expression levels of a selected group of genes on microgram quantities of tumor RNA (a quantity that can be obtained from fine needle aspirations) appears as a complementary method to histopathology for the diagnosis and prognosis of evolution of adrenocortical carcinomas. PMID:15613424

de Fraipont, Florence; El Atifi, Michelle; Cherradi, Nadia; Le Moigne, Gwennaelle; Defaye, Geneviève; Houlgatte, Rémi; Bertherat, Jérôme; Bertagna, Xavier; Plouin, Pierre-François; Baudin, Eric; Berger, François; Gicquel, Christine; Chabre, Olivier; Feige, Jean-Jacques

2005-03-01

321

Comparison of gene expression between left atria and left ventricles from non-diseased humans.  

PubMed

We examine the reliability and accuracy of gene array technology in analyzing differences in gene expression between human non-diseased left atrium and left ventricle. We have used cDNA gene arrays and validated those data by carefully designed quantitative real-time polymerase chain reaction (PCR). We have identified pitfalls using cDNA gene array technology based on comparisons with other gene array studies and with changes reported for the levels of expression of the genes corresponding to these cDNAs. The high error rate reported here underscores the cautionary comments reported by others in this field. PMID:14730688

Tsubakihara, Masako; Williams, Neal K; Keogh, Anne; dos Remedios, Cristobal G

2004-01-01

322

Rapid in vivo forward genetic approach for identifying axon death genes in Drosophila.  

PubMed

Axons damaged by acute injury, toxic insults, or neurodegenerative diseases execute a poorly defined autodestruction signaling pathway leading to widespread fragmentation and functional loss. Here, we describe an approach to study Wallerian degeneration in the Drosophila L1 wing vein that allows for analysis of axon degenerative phenotypes with single-axon resolution in vivo. This method allows for the axotomy of specific subsets of axons followed by examination of progressive axonal degeneration and debris clearance alongside uninjured control axons. We developed new Flippase (FLP) reagents using proneural gene promoters to drive FLP expression very early in neural lineages. These tools allow for the production of mosaic clone populations with high efficiency in sensory neurons in the wing. We describe a collection of lines optimized for forward genetic mosaic screens using MARCM (mosaic analysis with a repressible cell marker; i.e., GFP-labeled, homozygous mutant) on all major autosomal arms (?95% of the fly genome). Finally, as a proof of principle we screened the X chromosome and identified a collection eight recessive and two dominant alleles of highwire, a ubiquitin E3 ligase required for axon degeneration. Similar unbiased forward genetic screens should help rapidly delineate axon death genes, thereby providing novel potential drug targets for therapeutic intervention to prevent axonal and synaptic loss. PMID:24958874

Neukomm, Lukas J; Burdett, Thomas C; Gonzalez, Michael A; Züchner, Stephan; Freeman, Marc R

2014-07-01

323

A strategy to find gene combinations that identify children who progress rapidly to type 1 diabetes after islet autoantibody seroconversion.  

PubMed

We recently developed a novel approach capable of identifying gene combinations to obtain maximal disease risk stratification. Type 1 diabetes has a preclinical phase including seroconversion to autoimmunity and subsequent progression to diabetes. Here, we applied our gene combination approach to identify combinations that contribute either to islet autoimmunity or to the progression from islet autoantibodies to diabetes onset. We examined 12 type 1 diabetes susceptibility genes (INS, ERBB3, PTPN2, IFIH1, PTPN22, KIAA0350, CD25, CTLA4, SH2B3, IL2, IL18RAP, IL10) in a cohort of children of parents with type 1 diabetes and prospectively followed from birth. The most predictive combination was subsequently applied to a smaller validation cohort. The combinations of genes only marginally contributed to the risk of developing islet autoimmunity, but could substantially modify risk of progression to diabetes in islet autoantibody-positive children. The greatest discrimination was provided by risk allele scores of five genes, INS, IFIH1, IL18RAP, CD25, and IL2 genes, which could identify 80 % of islet autoantibody-positive children who progressed to diabetes within 6 years of seroconversion and discriminate high risk (63 % within 6 years; 95 % CI 45-81 %) and low risk (11 % within 6 years; 95 % CI 0.1-22 %; p = 4 × 10(-5)) antibody-positive children. Risk stratification by these five genes was confirmed in a second cohort of islet autoantibody children. These findings highlight genes that may affect the rate of the beta-cell destruction process once autoimmunity has initiated and may help to identify islet autoantibody-positive subjects with rapid progression to diabetes. PMID:24249616

Bonifacio, Ezio; Krumsiek, Jan; Winkler, Christiane; Theis, Fabian J; Ziegler, Anette-Gabriele

2014-06-01

324

Gene Expression Signature-Based Screening Identifies New Broadly Effective Influenza A Antivirals  

PubMed Central

Classical antiviral therapies target viral proteins and are consequently subject to resistance. To counteract this limitation, alternative strategies have been developed that target cellular factors. We hypothesized that such an approach could also be useful to identify broad-spectrum antivirals. The influenza A virus was used as a model for its viral diversity and because of the need to develop therapies against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection by different influenza A virus subtypes which would allow the identification of potential antiviral drugs with a broad anti-influenza spectrum of activity. We analyzed the cellular gene expression response to infection with five different human and avian influenza A virus strains and identified 300 genes as differentially expressed between infected and non-infected samples. The most 20 dysregulated genes were used to screen the connectivity map, a database of drug-associated gene expression profiles. Candidate antivirals were then identified by their inverse correlation to the query signature. We hypothesized that such molecules would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified and their effects were tested in vitro on five influenza A strains. Six of the molecules inhibited influenza viral growth. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five out of the eight identified molecules, demonstrating that this strategy could contribute to identifying new broad anti-influenza agents acting on cellular gene expression. The identified infection signature genes, the expression of which are modified upon infection, could encode cellular proteins involved in the viral life cycle. This is the first study showing that gene expression-based screening can be used to identify antivirals. Such an approach could accelerate drug discovery and be extended to other pathogens.

Josset, Laurence; Textoris, Julien; Loriod, Beatrice; Ferraris, Olivier; Moules, Vincent; Lina, Bruno; N'Guyen, Catherine; Diaz, Jean-Jacques; Rosa-Calatrava, Manuel

2010-01-01

325

Polymorphisms of insulin degrading enzyme gene are not associated with Alzheimer's disease  

Microsoft Academic Search

To date, allele 4 of the apolipoprotein E gene is the only risk factor that has been robustly associated with Alzheimer's disease (AD). Identification and molecular characterization of other risk factors is of great interest. The insulin degrading enzyme (IDE) is an attractive candidate gene since: (i), previous studies have identified a possible role that IDE plays in the degradation

Mekki Boussaha; Didier Hannequin; Patrice Verpillat; Alexis Brice; Thierry Frebourg; Dominique Campion

2002-01-01

326

Heterogeneity of linkage disequilibrium in human genes has implications for association studies of common diseases  

Microsoft Academic Search

Linkage disequilibrium (LD) is the central concept of genetic association studies. Although LD has been shown not to be uniformly distributed across the genome, limited information is available about the character- istics of LD within candidate genes at large. We screened coding and regulatory regions of 50 candidate genes for cardiovascular diseases and identified 228 polymorphisms. The overall sequence diversity

Laurence Tiret; Odette Poirier; Viviane Nicaud; Sandrine Barbaux; Stefan-Martin Herrmann; Claire Perret; Ségolène Raoux; Carole Francomme; Géraud Lebard; David Trégouët; François Cambien

2002-01-01

327

Identification of a Common Gene Expression Response in Different Lung Inflammatory Diseases in Rodents and Macaques  

Microsoft Academic Search

To identify gene expression responses common to multiple pulmonary diseases we collected microarray data for acute lung inflammation models from 12 studies and used these in a meta-analysis. The data used include exposures to air pollutants; bacterial, viral, and parasitic infections; and allergic asthma models. Hierarchical clustering revealed a cluster of 383 up-regulated genes with a common response. This cluster

Jeroen L. A. Pennings; Tjeerd G. Kimman; Riny Janssen; Nina Papavasiliou

2008-01-01

328

A strategy for disease gene identification through nonsense-mediated mRNA decay inhibition  

Microsoft Academic Search

Premature termination codons (PTCs) have been shown to initiate degradation of mutant transcripts through the nonsense-mediated messenger RNA (mRNA) decay (NMD) pathway. We report a strategy, termed gene identification by NMD inhibition (GINI), to identify genes harboring nonsense codons that underlie human diseases. In this strategy, the NMD pathway is pharmacologically inhibited in cultured patient cells, resulting in stabilization of

Erick N. Noensie; Harry C. Dietz

2001-01-01

329

Large-scale functional RNAi screen in C. elegans identifies genes that regulate the dysfunction of mutant polyglutamine neurons  

PubMed Central

Background A central goal in Huntington's disease (HD) research is to identify and prioritize candidate targets for neuroprotective intervention, which requires genome-scale information on the modifiers of early-stage neuron injury in HD. Results Here, we performed a large-scale RNA interference screen in C. elegans strains that express N-terminal huntingtin (htt) in touch receptor neurons. These neurons control the response to light touch. Their function is strongly impaired by expanded polyglutamines (128Q) as shown by the nearly complete loss of touch response in adult animals, providing an in vivo model in which to manipulate the early phases of expanded-polyQ neurotoxicity. In total, 6034 genes were examined, revealing 662 gene inactivations that either reduce or aggravate defective touch response in 128Q animals. Several genes were previously implicated in HD or neurodegenerative disease, suggesting that this screen has effectively identified candidate targets for HD. Network-based analysis emphasized a subset of high-confidence modifier genes in pathways of interest in HD including metabolic, neurodevelopmental and pro-survival pathways. Finally, 49 modifiers of 128Q-neuron dysfunction that are dysregulated in the striatum of either R/2 or CHL2 HD mice, or both, were identified. Conclusions Collectively, these results highlight the relevance to HD pathogenesis, providing novel information on the potential therapeutic targets for neuroprotection in HD.

2012-01-01

330

A Scan of Chromosome 10 Identifies a Novel Locus Showing Strong Association with Late-Onset Alzheimer Disease  

PubMed Central

Strong evidence of linkage to late-onset Alzheimer disease (LOAD) has been observed on chromosome 10, which implicates a wide region and at least one disease-susceptibility locus. Although significant associations with several biological candidate genes on chromosome 10 have been reported, these findings have not been consistently replicated, and they remain controversial. We performed a chromosome 10–specific association study with 1,412 gene-based single-nucleotide polymorphisms (SNPs), to identify susceptibility genes for developing LOAD. The scan included SNPs in 677 of 1,270 known or predicted genes; each gene contained one or more markers, about half (48%) of which represented putative functional mutations. In general, the initial testing was performed in a white case-control sample from the St. Louis area, with 419 LOAD cases and 377 age-matched controls. Markers that showed significant association in the exploratory analysis were followed up in several other white case-control sample sets to confirm the initial association. Of the 1,397 markers tested in the exploratory sample, 69 reached significance (P<.05). Five of these markers replicated at P<.05 in the validation sample sets. One marker, rs498055, located in a gene homologous to RPS3A (LOC439999), was significantly associated with Alzheimer disease in four of six case-control series, with an allelic P value of .0001 for a meta-analysis of all six samples. One of the case-control samples with significant association to rs498055 was derived from the linkage sample (P=.0165). These results indicate that variants in the RPS3A homologue are associated with LOAD and implicate this gene, adjacent genes, or other functional variants (e.g., noncoding RNAs) in the pathogenesis of this disorder.

Grupe, Andrew; Li, Yonghong; Rowland, Charles; Nowotny, Petra; Hinrichs, Anthony L.; Smemo, Scott; Kauwe, John S. K.; Maxwell, Taylor J.; Cherny, Sara; Doil, Lisa; Tacey, Kristina; van Luchene, Ryan; Myers, Amanda; Wavrant-De Vrieze, Fabienne; Kaleem, Mona; Hollingworth, Paul; Jehu, Luke; Foy, Catherine; Archer, Nicola; Hamilton, Gillian; Holmans, Peter; Morris, Chris M.; Catanese, Joseph; Sninsky, John; White, Thomas J.; Powell, John; Hardy, John; O'Donovan, Michael; Lovestone, Simon; Jones, Lesley; Morris, John C.; Thal, Leon; Owen, Michael; Williams, Julie; Goate, Alison

2006-01-01

331

Genes Involved in the Osteoarthritis Process Identified through Genome Wide Expression Analysis in Articular Cartilage; the RAAK Study  

PubMed Central

Objective Identify gene expression profiles associated with OA processes in articular cartilage and determine pathways changing during the disease process. Methods Genome wide gene expression was determined in paired samples of OA affected and preserved cartilage of the same joint using microarray analysis for 33 patients of the RAAK study. Results were replicated in independent samples by RT-qPCR and immunohistochemistry. Profiles were analyzed with the online analysis tools DAVID and STRING to identify enrichment for specific pathways and protein-protein interactions. Results Among the 1717 genes that were significantly differently expressed between OA affected and preserved cartilage we found significant enrichment for genes involved in skeletal development (e.g. TNFRSF11B and FRZB). Also several inflammatory genes such as CD55, PTGES and TNFAIP6, previously identified in within-joint analyses as well as in analyses comparing preserved cartilage from OA affected joints versus healthy cartilage were among the top genes. Of note was the high up-regulation of NGF in OA cartilage. RT-qPCR confirmed differential expression for 18 out of 19 genes with expression changes of 2-fold or higher, and immunohistochemistry of selected genes showed a concordant change in protein expression. Most of these changes associated with OA severity (Mankin score) but were independent of joint-site or sex. Conclusion We provide further insights into the ongoing OA pathophysiological processes in cartilage, in particular into differences in macroscopically intact cartilage compared to OA affected cartilage, which seem relatively consistent and independent of sex or joint. We advocate that development of treatment could benefit by focusing on these similarities in gene expression changes and/or pathways.

Bovee, Judith V. M. G.; Bomer, Nils; van der Breggen, Ruud; Lakenberg, Nico; Keurentjes, J. Christiaan; Goeman, Jelle J.; Slagboom, P. Eline; Nelissen, Rob G. H. H.; Bos, Steffan D.; Meulenbelt, Ingrid

2014-01-01

332

GenDrux: A biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer  

PubMed Central

Background This paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications. Results GenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated. Conclusions The successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future.

2011-01-01

333

A network-based method for predicting disease-causing genes.  

PubMed

A fundamental problem in human health is the inference of disease-causing genes, with important applications to diagnosis and treatment. Previous work in this direction relied on knowledge of multiple loci associated with the disease, or causal genes for similar diseases, which limited its applicability. Here we present a new approach to causal gene prediction that is based on integrating protein-protein interaction network data with gene expression data under a condition of interest. The latter are used to derive a set of disease-related genes which is assumed to be in close proximity in the network to the causal genes. Our method applies a set-cover-like heuristic to identify a small set of genes that best "cover" the disease-related genes. We perform comprehensive simulations to validate our method and test its robustness to noise. In addition, we validate our method on real gene expression data and on gene specific knockouts. Finally, we apply it to suggest possible genes that are involved in myasthenia gravis. PMID:19193144

Karni, Shaul; Soreq, Hermona; Sharan, Roded

2009-02-01

334

Genome wide association study of SNP-, gene-, and pathway-based approaches to identify genes influencing susceptibility to Staphylococcus aureus infections.  

PubMed

Background: We conducted a genome-wide association study (GWAS) to identify specific genetic variants that underlie susceptibility to diseases caused by Staphylococcus aureus in humans. Methods: Cases (n = 309) and controls (n = 2925) were genotyped at 508,921 single nucleotide polymorphisms (SNPs). Cases had at least one laboratory and clinician confirmed disease caused by S. aureus whereas controls did not. R-package (for SNP association), EIGENSOFT (to estimate and adjust for population stratification) and gene- (VEGAS) and pathway-based (DAVID, PANTHER, and Ingenuity Pathway Analysis) analyses were performed. Results: No SNP reached genome-wide significance. Four SNPs exceeded the p < 10(-5) threshold including two (rs2455012 and rs7152530) reaching a p-value < 10(-7). The nearby genes were PDE4B (rs2455012), TXNRD2 (rs3804047), VRK1 and BCL11B (rs7152530), and PNPLA5 (rs470093). The top two findings from the gene-based analysis were NMRK2 (p gene = 1.20E-05), which codes an integrin binding molecule (focal adhesion), and DAPK3 (p gene = 5.10E-05), a serine/threonine kinase (apoptosis and cytokinesis). The pathway analyses identified epithelial cell responses to mechanical and non-mechanical stress. Conclusion: We identified potential susceptibility genes for S. aureus diseases in this preliminary study but confirmation by other studies is needed. The observed associations could be relevant given the complexity of S. aureus as a pathogen and its ability to exploit multiple biological pathways to cause infections in humans. PMID:24847357

Ye, Zhan; Vasco, Daniel A; Carter, Tonia C; Brilliant, Murray H; Schrodi, Steven J; Shukla, Sanjay K

2014-01-01

335

Clustering Gene Expression Regulators: New Approach to Disease Subtyping  

PubMed Central

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

336

Automated Ontological Gene Annotation for Computing Disease Similarity  

PubMed Central

The annotation of gene/gene products with information on associated diseases is useful as an aid to clinical diagnosis and drug discovery. Several supervised and unsupervised methods exist that automate the association of genes with diseases, but relatively little work has been done to map protein sequence data to disease terminologies. This paper augments an existing open-disease terminology, the Disease Ontology (DO), and uses it for automated annotation of Swissprot records. In addition to the inherent benefits of mapping data to a rich ontology, we demonstrate a gain of 36.1% in gene-disease associations compared to that in DO. Further, we measure disease similarity by exploiting the co-occurrence of annotation among proteins and the hierarchical structure of DO. This makes it possible to find related diseases or signs, with the potential to find previously unknown relationships.

Mathur, Sachin; Dinakarpandian, Deendayal

2010-01-01

337

Using phylogenomic patterns and gene ontology to identify proteins of importance in plant evolution.  

PubMed

We use measures of congruence on a combined expressed sequenced tag genome phylogeny to identify proteins that have potential significance in the evolution of seed plants. Relevant proteins are identified based on the direction of partitioned branch and hidden support on the hypothesis obtained on a 16-species tree, constructed from 2,557 concatenated orthologous genes. We provide a general method for detecting genes or groups of genes that may be under selection in directions that are in agreement with the phylogenetic pattern. Gene partitioning methods and estimates of the degree and direction of support of individual gene partitions to the overall data set are used. Using this approach, we correlate positive branch support of specific genes for key branches in the seed plant phylogeny. In addition to basic metabolic functions, such as photosynthesis or hormones, genes involved in posttranscriptional regulation by small RNAs were significantly overrepresented in key nodes of the phylogeny of seed plants. Two genes in our matrix are of critical importance as they are involved in RNA-dependent regulation, essential during embryo and leaf development. These are Argonaute and the RNA-dependent RNA polymerase 6 found to be overrepresented in the angiosperm clade. We use these genes as examples of our phylogenomics approach and show that identifying partitions or genes in this way provides a platform to explain some of the more interesting organismal differences among species, and in particular, in the evolution of plants. PMID:20624728

Cibrián-Jaramillo, Angélica; De la Torre-Bárcena, Jose E; Lee, Ernest K; Katari, Manpreet S; Little, Damon P; Stevenson, Dennis W; Martienssen, Rob; Coruzzi, Gloria M; DeSalle, Rob

2010-01-01

338

Genes identified by visible mutant phenotypes show increased bias toward one of two subgenomes of maize.  

PubMed

Not all genes are created equal. Despite being supported by sequence conservation and expression data, knockout homozygotes of many genes show no visible effects, at least under laboratory conditions. We have identified a set of maize (Zea mays L.) genes which have been the subject of a disproportionate share of publications recorded at MaizeGDB. We manually anchored these "classical" maize genes to gene models in the B73 reference genome, and identified syntenic orthologs in other grass genomes. In addition to proofing the most recent version 2 maize gene models, we show that a subset of these genes, those that were identified by morphological phenotype prior to cloning, are retained at syntenic locations throughout the grasses at much higher levels than the average expressed maize gene, and are preferentially found on the maize1 subgenome even with a duplicate copy is still retained on the opposite subgenome. Maize1 is the subgenome that experienced less gene loss following the whole genome duplication in maize lineage 5-12 million years ago and genes located on this subgenome tend to be expressed at higher levels in modern maize. Links to the web based software that supported our syntenic analyses in the grasses should empower further research and support teaching involving the history of maize genetic research. Our findings exemplify the concept of "grasses as a single genetic system," where what is learned in one grass may be applied to another. PMID:21423772

Schnable, James C; Freeling, Michael

2011-01-01

339

Quantifying dominance and deleterious effect on human disease genes  

PubMed Central

Human genes responsible for inherited diseases are important for the understanding of human disease. We investigated the degree of polymorphism and divergence in the human disease genes to elucidate the effect of natural selection on human disease genes. In particular, the effect of disease dominance was incorporated into the analysis. Both dominant disease genes (DDG) and recessive disease genes (RDG) had a higher mutation rate per site and encoded longer proteins than the nondisease genes, which exposed the disease genes to a faster flux of new mutations. Using an unbiased polymorphism dataset, we found that, proportionally, RDG harbor more nonsynonymous polymorphisms compared with DDG. We estimated the selection intensity on the disease genes using polymorphism and divergence data and determined whether the different patterns of polymorphism and divergence between DDG and RDG could be explained by the difference in only dominance. Even after the dominance effect was considered, the selection intensity on RDG was significantly different from DDG, suggesting that the deleterious effect of the dominant and recessive disease mutations are fundamentally different.

Osada, Naoki; Mano, Shuhei; Gojobori, Jun

2009-01-01

340

Whole-blood transcriptional profiling of interferon-inducible genes identifies highly upregulated IFI27 in primary myelofibrosis.  

PubMed

Gene expression profiling studies have unraveled deregulation of several genes that might be of pathogenetic importance for the development and phenotype of the Philadelphia-negative chronic myeloproliferative neoplasms. In the context of interferon-alpha2 as a promising therapeutic agent, we focused upon the transcriptional profiling of interferon-associated genes in patients with essential thrombocythemia (ET) (n = 19), polycythemia vera (PV) (n = 41), and primary myelofibrosis (PMF) (n = 9). Using whole-blood transcriptional profiling and accordingly obtaining an integrated signature of genes expressed in several immune cells (granulocytes, monocytes, B cells, T cells, platelets), we have identified a number of interferon-associated genes to be significantly deregulated but with a highly significant deregulation of interferon-inducible gene 27 (IFI27) (ET, PV, and PMF, fold change 8, 16, and 30, respectively). The striking deregulation of IFI genes may reflect a hyperstimulated but insufficient immune system being most enhanced in patients with advanced myelofibrosis, in whom the IFI27 gene displayed an exceedingly high expression. The interferon signature may reflect primary myelofibrosis as the burn-out phase of chronic inflammation which ultimately elicits clonal evolution and expansion owing to an exaggerated but incompetent antitumor immune response. Finally, IFI27 may be a novel biomarker of disease activity and tumor burden in patients with CMPNs. PMID:21447007

Skov, Vibe; Larsen, Thomas Stauffer; Thomassen, Mads; Riley, Caroline Hasselbalch; Jensen, Morten K; Bjerrum, Ole Weis; Kruse, Torben A; Hasselbalch, Hans Carl

2011-07-01

341

A Look to Future Directions in Gene Therapy Research for Monogenic Diseases  

PubMed Central

The concept of gene therapy has long appealed to biomedical researchers and clinicians because it promised to treat certain diseases at their origins. In the last several years, there have been several trials in which patients have benefited from gene therapy protocols. This progress, however, has revealed important problems, including the problem of insertional oncogenesis. In this review, which focuses on monogenic diseases, we discuss the problem of insertional oncogenesis and identify areas for future research, such as developing more quantitative assays for risk and efficacy, and ways of minimizing the genotoxic effects of gene therapy protocols, which will be important if gene therapy is to fulfill its conceptual promise.

Porteus, Matthew H; Connelly, Jon P; Pruett, Shondra M

2006-01-01

342

The gene mutated in autosomal recessive polycystic kidney disease encodes a large, receptor-like protein  

Microsoft Academic Search

Autosomal recessive polycystic kidney disease (ARPKD) is characterized by dilation of collecting ducts and by biliary dysgenesis and is an important cause of renal- and liver-related morbidity and mortality. Genetic analysis of a rat with recessive polycystic kidney disease revealed an orthologous relationship between the rat locus and the ARPKD region in humans; a candidate gene was identified. A mutation

Christopher J. Ward; Marie C. Hogan; Sandro Rossetti; Denise Walker; Tam Sneddon; Xiaofang Wang; Vicky Kubly; Julie M. Cunningham; Robert Bacallao; Masahiko Ishibashi; Dawn S. Milliner; Vicente E. Torres; Peter C. Harris

2002-01-01

343

Gene expression profiling in the lungs of pigs with different susceptibilities to Glässer's disease  

Microsoft Academic Search

BACKGROUND: Haemophilus parasuis is the causative agent of Glässer's disease in pigs. Currently, little is known about the molecular mechanisms that contribute to disease susceptibility. This study used a porcine oligonucleotide microarray to identify genes that were differentially expressed (DE) in the lungs of colostrum-deprived animals previously characterized as being either 'Fully Resistant' (FR) or 'Susceptible' to infection by H.

Jamie M Wilkinson; Carole A Sargent; Lucina Galina-Pantoja; Alexander W Tucker

2010-01-01

344

A Novel Dataset for Identifying Sex-Biased Genes in Drosophila  

PubMed Central

Phenotypic differences between males and females of sexually dimorphic species are caused in large part by differences in gene expression between the sexes, most of which occurs in the gonads. To accurately identify genes differentially expressed between males and females in Drosophila, we sequenced the testis and ovary transcriptomes of D. yakuba, D. pseudoobscura, and D. ananassae and used them to identify sex-biased genes in the latter two species. We highlight the increased sensitivity and improved power of sex-biased gene detection methods when using our testis/ovary data versus male and female whole body transcriptome data. We thus provide a resource specifically designed to accurately identify and characterize sex-biased genes across Drosophila. This dataset is available through NCBI GEO accession GSE52058.

VanKuren, Nicholas W.; Vibranovski, Maria D.

2014-01-01

345

Disease Gene Characterization through Large-Scale Co-Expression Analysis  

PubMed Central

Background In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET). Results Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2) and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders. Discussion UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

Funari, Vincent A.; Harry, Bret; Strom, Samuel P.; Cohn, Dan H.; Nelson, Stanley F.

2009-01-01

346

Differential Expression of Vitamin E and Selenium-Responsive Genes by Disease Severity in Chronic Obstructive Pulmonary Disease  

PubMed Central

Antioxidant nutritional status is hypothesized to influence chronic obstructive pulmonary disease (COPD) susceptibility and progression. Although past studies relate antioxidants to gene expression, there are no data in patients with COPD. This study investigated the hypothesis that antioxidant status is compromised in patients with COPD, and antioxidant-responsive genes differentially express in a similar pattern. Lung tissue samples from patients with COPD were assayed for vitamin E and gene expression. Selenium and vitamin E were assayed in corresponding plasma samples. Discovery based genome-wide expression analysis compared moderate, severe, and very severe COPD (GOLD II-IV) patients to mild and at-risk/normal (GOLD 0-I). Hypotheses-driven analyses assessed differential gene expression by disease severity for vitamin E-responsive and selenium-responsive genes. GOLD II-IV COPD patients had 30% lower lung tissue vitamin E levels compared to GOLD 0-I participants (p = 0.0082). No statistically significant genome-wide differences in expression by disease severity were identified. Hypothesis-driven analyses of 109 genes found 16 genes differentially expressed (padjusted<0.05) by disease severity including 6 selenium-responsive genes (range in fold-change -1.39 to 2.25), 6 vitamin E-responsive genes (fold-change -2.30 to 1.51), and 4 COPD-associated genes. Lung tissue vitamin E in patients with COPD was associated with disease severity and vitamin E-responsive genes were differentially expressed by disease severity. While nutritional status is hypothesized to contribute to COPD risk, and is of therapeutic interest, evidence to date is mainly observational. The findings reported herein are novel, and support a role of vitamin E in COPD progression.

Agler, AH; Crystal, RG; Mezey, JG; Fuller, J; Gao, C; Hansen, JG; Cassano, PA

2014-01-01

347

Large-scale identification of disease genes involved in acute myeloid leukemia  

Microsoft Academic Search

Acute myeloid leukemia (AML) is a heterogeneous group of diseases in which\\u000a chromosomal aberrations, small insertions or deletions, or point mutations\\u000a in certain genes have profound consequences for prognosis. However, the\\u000a majority of AML patients present without currently known genetic defects.\\u000a Retroviral insertion mutagenesis in mice has become a powerful tool for\\u000a identifying new disease genes involved in the pathogenesis

Stefan J. Erkeland; Marijke Valkhof; Claudia Heijmans-Antonissen; Antoinette van Hoven-Beijen; H. R. Delwel; Mirjam H. A. Hermans; Ivo P. Touw

2004-01-01

348

Genomewide association study for susceptibility genes contributing to familial Parkinson disease  

Microsoft Academic Search

Five genes have been identified that contribute to Mendelian forms of Parkinson disease (PD); however, mutations have been\\u000a found in fewer than 5% of patients, suggesting that additional genes contribute to disease risk. Unlike previous studies that\\u000a focused primarily on sporadic PD, we have performed the first genomewide association study (GWAS) in familial PD. Genotyping\\u000a was performed with the Illumina

Nathan Pankratz; Jemma B. Wilk; Jeanne C. Latourelle; Anita L. DeStefano; Cheryl Halter; Elizabeth W. Pugh; Kimberly F. Doheny; James F. Gusella; William C. Nichols; Tatiana Foroud; Richard H. Myers

2009-01-01