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Sample records for identifying disease genes

  1. Identifying Mendelian disease genes with the Variant Effect Scoring Tool

    PubMed Central

    2013-01-01

    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

  2. Gene-based rare allele analysis identified a risk gene of Alzheimer's disease.

    PubMed

    Kim, Jong Hun; Song, Pamela; Lim, Hyunsun; Lee, Jae-Hyung; Lee, Jun Hong; Park, Sun Ah

    2014-01-01

    Alzheimer's disease (AD) has a strong propensity to run in families. However, the known risk genes excluding APOE are not clinically useful. In various complex diseases, gene studies have targeted rare alleles for unsolved heritability. Our study aims to elucidate previously unknown risk genes for AD by targeting rare alleles. We used data from five publicly available genetic studies from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the database of Genotypes and Phenotypes (dbGaP). A total of 4,171 cases and 9,358 controls were included. The genotype information of rare alleles was imputed using 1,000 genomes. We performed gene-based analysis of rare alleles (minor allele frequency≤3%). The genome-wide significance level was defined as meta P<1.8×10(-6) (0.05/number of genes in human genome = 0.05/28,517). ZNF628, which is located at chromosome 19q13.42, showed a genome-wide significant association with AD. The association of ZNF628 with AD was not dependent on APOE ε4. APOE and TREM2 were also significantly associated with AD, although not at genome-wide significance levels. Other genes identified by targeting common alleles could not be replicated in our gene-based rare allele analysis. We identified that rare variants in ZNF628 are associated with AD. The protein encoded by ZNF628 is known as a transcription factor. Furthermore, the associations of APOE and TREM2 with AD were highly significant, even in gene-based rare allele analysis, which implies that further deep sequencing of these genes is required in AD heritability studies.

  3. LGscore: A method to identify disease-related genes using biological literature and Google data.

    PubMed

    Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

    2015-04-01

    Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods.

  4. GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases

    PubMed Central

    2012-01-01

    Background Although many diseases have been well characterized at the molecular level, the underlying mechanisms are often unknown. Nearly half of all human genes remain poorly studied, yet these genes may contribute to a number of disease processes. Genes involved in common biological processes and diseases are often co-expressed. Using known disease-associated genes in a co-expression analysis may help identify and prioritize novel candidate genes for further study. Results We have created an online tool, called GeneFriends, which identifies co-expressed genes in over 1,000 mouse microarray datasets. GeneFriends can be used to assign putative functions to poorly studied genes. Using a seed list of disease-associated genes and a guilt-by-association method, GeneFriends allows users to quickly identify novel genes and transcription factors associated with a disease or process. We tested GeneFriends using seed lists for aging, cancer, and mitochondrial complex I disease. We identified several candidate genes that have previously been predicted as relevant targets. Some of the genes identified are already being tested in clinical trials, indicating the effectiveness of this approach. Co-expressed transcription factors were investigated, identifying C/ebp genes as candidate regulators of aging. Furthermore, several novel candidate genes, that may be suitable for experimental or clinical follow-up, were identified. Two of the novel candidates of unknown function that were co-expressed with cancer-associated genes were selected for experimental validation. Knock-down of their human homologs (C1ORF112 and C12ORF48) in HeLa cells slowed growth, indicating that these genes of unknown function, identified by GeneFriends, may be involved in cancer. Conclusions GeneFriends is a resource for biologists to identify and prioritize novel candidate genes involved in biological processes and complex diseases. It is an intuitive online resource that will help drive experimentation

  5. Using the BITOLA system to identify candidate genes for Parkinson’s disease

    PubMed Central

    Karić, Amela; Karić, Alen

    2011-01-01

    Complexity of multifactorial diseases as Parkinson’s disease (PD) often complicate identifying causal genetic factors by traditional approaches such as positional cloning and candidate gene analyses. PD is etiologically and genetically complex disease and second most common neurodegenerative disorder after Alzheimer’s disease. The most cases of PD are idiopathic and small growing subset of individuals have single gene defect as the cause. The main goal of this research was to identify the potential candidate genes for idiopathic PD by using biomedical discovery support system (BITOLA). For detecting the potential candidate genes for PD was used opened system of bioinformatics tool BITOLA. Data of chromosome location, tissue specific expression of potential candidate genes and their potential association with PD were obtained from Medline, Locus Link, Gene Cards and OMIM. By using BITOLA system is identified 17 genes as potential candidate genes for PD. The role of three genes (MAPT, PARK2, UCHL1) in PD were confirmed earlier. Discovering the novel candidate genes for multifactiorial diseases by using specially mentioned bioinformatics tool BITOLA could offer the new opportunity for researching genetics base of PD without using tissue samples of patients. PMID:21875422

  6. Applying the Fisher score to identify Alzheimer's disease-related genes.

    PubMed

    Yang, J; Liu, Y L; Feng, C S; Zhu, G Q

    2016-01-01

    Biologists and scientists can use the data from Alzheimer's disease (AD) gene expression microarrays to mine AD disease-related genes. Because of disadvantages such as small sample sizes, high dimensionality, and a high level of noise, it is difficult to obtain accurate and meaningful biological information from gene expression profiles. In this paper, we present a novel approach for utilizing AD microarray data to identify the morbigenous genes. The Fisher score, a classical feature selection method, is utilized to evaluate the importance of each gene. Genes with a large between-classes variance and small within-class variance are selected as candidate morbigenous genes. The results using an AD dataset show that the proposed approach is effective for gene selection. Satisfactory accuracy can be achieved by using only a small number of selected genes. PMID:27420981

  7. Identifying and prioritizing disease-related genes based on the network topological features.

    PubMed

    Li, Zhan-Chao; Lai, Yan-Hua; Chen, Li-Li; Xie, Yun; Dai, Zong; Zou, Xiao-Yong

    2014-12-01

    Identifying and prioritizing disease-related genes are the most important steps for understanding the pathogenesis and discovering the therapeutic targets. The experimental examination of these genes is very expensive and laborious, and usually has a higher false positive rate. Therefore, it is highly desirable to develop computational methods for the identification and prioritization of disease-related genes. In this study, we develop a powerful method to identify and prioritize candidate disease genes. The novel network topological features with local and global information are proposed and adopted to characterize genes. The performance of these novel features is verified based on the 10-fold cross-validation test and leave-one-out cross-validation test. The proposed features are compared with the published features, and fused strategy is investigated by combining the current features with the published features. And, these combination features are also utilized to identify and prioritize Parkinson's disease-related genes. The results indicate that identified genes are highly related to some molecular process and biological function, which provides new clues for researching pathogenesis of Parkinson's disease. The source code of Matlab is freely available on request from the authors. PMID:25183318

  8. A fast and high performance multiple data integration algorithm for identifying human disease genes

    PubMed Central

    2015-01-01

    Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620

  9. De Novo Transcriptome Sequencing of Oryza officinalis Wall ex Watt to Identify Disease-Resistance Genes.

    PubMed

    He, Bin; Gu, Yinghong; Tao, Xiang; Cheng, Xiaojie; Wei, Changhe; Fu, Jian; Cheng, Zaiquan; Zhang, Yizheng

    2015-12-10

    Oryza officinalis Wall ex Watt is one of the most important wild relatives of cultivated rice and exhibits high resistance to many diseases. It has been used as a source of genes for introgression into cultivated rice. However, there are limited genomic resources and little genetic information publicly reported for this species. To better understand the pathways and factors involved in disease resistance and accelerating the process of rice breeding, we carried out a de novo transcriptome sequencing of O. officinalis. In this research, 137,229 contigs were obtained ranging from 200 to 19,214 bp with an N50 of 2331 bp through de novo assembly of leaves, stems and roots in O. officinalis using an Illumina HiSeq 2000 platform. Based on sequence similarity searches against a non-redundant protein database, a total of 88,249 contigs were annotated with gene descriptions and 75,589 transcripts were further assigned to GO terms. Candidate genes for plant-pathogen interaction and plant hormones regulation pathways involved in disease-resistance were identified. Further analyses of gene expression profiles showed that the majority of genes related to disease resistance were all expressed in the three tissues. In addition, there are two kinds of rice bacterial blight-resistant genes in O. officinalis, including two Xa1 genes and three Xa26 genes. All 2 Xa1 genes showed the highest expression level in stem, whereas one of Xa26 was expressed dominantly in leaf and other 2 Xa26 genes displayed low expression level in all three tissues. This transcriptomic database provides an opportunity for identifying the genes involved in disease-resistance and will provide a basis for studying functional genomics of O. officinalis and genetic improvement of cultivated rice in the future.

  10. De Novo Transcriptome Sequencing of Oryza officinalis Wall ex Watt to Identify Disease-Resistance Genes

    PubMed Central

    He, Bin; Gu, Yinghong; Tao, Xiang; Cheng, Xiaojie; Wei, Changhe; Fu, Jian; Cheng, Zaiquan; Zhang, Yizheng

    2015-01-01

    Oryza officinalis Wall ex Watt is one of the most important wild relatives of cultivated rice and exhibits high resistance to many diseases. It has been used as a source of genes for introgression into cultivated rice. However, there are limited genomic resources and little genetic information publicly reported for this species. To better understand the pathways and factors involved in disease resistance and accelerating the process of rice breeding, we carried out a de novo transcriptome sequencing of O. officinalis. In this research, 137,229 contigs were obtained ranging from 200 to 19,214 bp with an N50 of 2331 bp through de novo assembly of leaves, stems and roots in O. officinalis using an Illumina HiSeq 2000 platform. Based on sequence similarity searches against a non-redundant protein database, a total of 88,249 contigs were annotated with gene descriptions and 75,589 transcripts were further assigned to GO terms. Candidate genes for plant–pathogen interaction and plant hormones regulation pathways involved in disease-resistance were identified. Further analyses of gene expression profiles showed that the majority of genes related to disease resistance were all expressed in the three tissues. In addition, there are two kinds of rice bacterial blight-resistant genes in O. officinalis, including two Xa1 genes and three Xa26 genes. All 2 Xa1 genes showed the highest expression level in stem, whereas one of Xa26 was expressed dominantly in leaf and other 2 Xa26 genes displayed low expression level in all three tissues. This transcriptomic database provides an opportunity for identifying the genes involved in disease-resistance and will provide a basis for studying functional genomics of O. officinalis and genetic improvement of cultivated rice in the future. PMID:26690414

  11. A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases.

    PubMed

    Gustafsson, Mika; Gawel, Danuta R; Alfredsson, Lars; Baranzini, Sergio; Björkander, Janne; Blomgran, Robert; Hellberg, Sandra; Eklund, Daniel; Ernerudh, Jan; Kockum, Ingrid; Konstantinell, Aelita; Lahesmaa, Riita; Lentini, Antonio; Liljenström, H Robert I; Mattson, Lina; Matussek, Andreas; Mellergård, Johan; Mendez, Melissa; Olsson, Tomas; Pujana, Miguel A; Rasool, Omid; Serra-Musach, Jordi; Stenmarker, Margaretha; Tripathi, Subhash; Viitala, Miro; Wang, Hui; Zhang, Huan; Nestor, Colm E; Benson, Mikael

    2015-11-11

    Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development. PMID:26560356

  12. Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

    PubMed Central

    Song, Min

    2016-01-01

    In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

  13. Gene Expression-Based Screen for Parkinson's Disease Identifies GW8510 as a Neuroprotective Agent.

    PubMed

    Wimalasena, Nivanthika K; Le, Viet Q; Wimalasena, Kandatege; Schreiber, Stuart L; Karmacharya, Rakesh

    2016-07-20

    We carried out a gene expression-based in silico screen in order to identify small molecules with gene-expression profiles that are anticorrelated with a gene-expression profile for Parkinson's disease (PD). We identified the cyclin-dependent kinase 2/5 (CDK2/5) inhibitor GW8510 as our most significant hit and characterized its effects in rodent MN9D cells and in human neuronal cells derived from induced pluripotent stem cells. GW8510 demonstrated neuroprotective ability in MN9D cells in the presence of 1-methyl-4-phenylpyridium (MPP(+)), a widely used neurotoxin model for Parkinson's disease. In order to delineate the nature and extent of GW8510's neuroprotective properties, we studied GW8510 in human neuronal cells in the context of various mechanisms of cellular stress. We found that GW8510 was protective against small-molecule mitochondrial and endoplasmic reticulum stressors. Our findings illustrate an approach to using small-molecule gene expression libraries to identify compounds with therapeutic potential in human diseases. PMID:27270122

  14. Variance of gene expression identifies altered network constraints in neurological disease.

    PubMed

    Mar, Jessica C; Matigian, Nicholas A; Mackay-Sim, Alan; Mellick, George D; Sue, Carolyn M; Silburn, Peter A; McGrath, John J; Quackenbush, John; Wells, Christine A

    2011-08-01

    Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinson's disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.

  15. A Special Local Clustering Algorithm for Identifying the Genes Associated With Alzheimer’s Disease

    PubMed Central

    Pang, Chao-Yang; Hu, Wei; Hu, Ben-Qiong; Shi, Ying; Vanderburg, Charles R.; Rogers, Jack T.

    2010-01-01

    Clustering is the grouping of similar objects into a class. Local clustering feature refers to the phenomenon whereby one group of data is separated from another, and the data from these different groups are clustered locally. A compact class is defined as one cluster in which all similar elements cluster tightly within the cluster. Herein, the essence of the local clustering feature, revealed by mathematical manipulation, results in a novel clustering algorithm termed as the special local clustering (SLC) algorithm that was used to process gene microarray data related to Alzheimer’s disease (AD). SLC algorithm was able to group together genes with similar expression patterns and identify significantly varied gene expression values as isolated points. If a gene belongs to a compact class in control data and appears as an isolated point in incipient, moderate and/or severe AD gene microarray data, this gene is possibly associated with AD. Application of a clustering algorithm in disease-associated gene identification such as in AD is rarely reported. PMID:20089478

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

    PubMed

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

    2014-07-04

    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.

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

    PubMed

    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

    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.

  18. Molecular profiling of experimental endometriosis identified gene expression patterns in common with human disease

    PubMed Central

    Flores, Idhaliz; Rivera, Elizabeth; Ruiz, Lynnette A.; Santiago, Olga I.; Vernon, Michael W.; Appleyard, Caroline B.

    2007-01-01

    OBJECTIVE To validate a rat model of endometriosis using cDNA microarrays by identifying common gene expression patterns beween experimental and natural disease. DESIGN Autotransplantation rat model. SETTING Medical school department. ANIMALS Female Sprague-Dawley rats. INTERVENTIONS Endometriosis was surgically-induced by suturing uterine horn implants next to the small intestine’s mesentery. Control rats received sutures with no implants. After 60 days, endometriotic implants and uterine horn were obtained. MAIN OUTCOME MEASURES Gene expression levels determined by cDNA microarrays and QRT-PCR. METHODS Cy5-labeled cDNA was synthesized from total RNA obtained from endometriotic implants. Cy3-labeled cDNA was synthesized using uterine RNA from a control rat. Gene expression levels were analyzed after hybridizing experimental and control labeled cDNA to PIQOR™ Toxicology Rat Microarrays (Miltenyi Biotec) containing 1,252 known genes. Cy5/Cy3 ratios were determined and genes with >2-fold higher or <0.5-fold lower expression levels were selected. Microarray results were validated by QRT-PCR. RESULTS We observed differential expression of genes previously shown to be upregulated in patients, including growth factors, inflammatory cytokines/receptors, tumor invasion/metastasis factors, adhesion molecules, and anti-apoptotic factors. CONCLUSIONS This study presents evidence in support of using this rat model to study the natural history of endometriosis and test novel therapeutics for this incurable disease. PMID:17478174

  19. Integromic Analysis of Genetic Variation and Gene Expression Identifies Networks for Cardiovascular Disease Phenotypes

    PubMed Central

    Yao, Chen; Chen, Brian H.; Joehanes, Roby; Otlu, Burcak; Zhang, Xiaoling; Liu, Chunyu; Huan, Tianxiao; Tastan, Oznur; Cupples, L. Adrienne; Meigs, James B.; Fox, Caroline S.; Freedman, Jane E.; Courchesne, Paul; O’Donnell, Christopher J.; Munson, Peter J.; Keles, Sunduz; Levy, Daniel

    2015-01-01

    Background Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies have reported numerous single nucleotide polymorphisms (SNPs) to be associated with CVD, the role of most of these variants in disease processes remains unknown. Methods and Results We built a CVD network using 1512 SNPs associated with 21 CVD traits in genome-wide association studies (at P≤5×10−8) and cross-linked different traits by virtue of their shared SNP associations. We then explored whole blood gene expression in relation to these SNPs in 5257 participants in the Framingham Heart Study. At a false discovery rate <0.05, we identified 370 cis-expression quantitative trait loci (eQTLs; SNPs associated with altered expression of nearby genes) and 44 trans-eQTLs (SNPs associated with altered expression of remote genes). The eQTL network revealed 13 CVD-related modules. Searching for association of eQTL genes with CVD risk factors (lipids, blood pressure, fasting blood glucose, and body mass index) in the same individuals, we found examples in which the expression of eQTL genes was significantly associated with these CVD phenotypes. In addition, mediation tests suggested that a subset of SNPs previously associated with CVD phenotypes in genome-wide association studies may exert their function by altering expression of eQTL genes (eg, LDLR and PCSK7), which in turn may promote interindividual variation in phenotypes. Conclusions Using a network approach to analyze CVD traits, we identified complex networks of SNP-phenotype and SNP-transcript connections. Integrating the CVD network with phenotypic data, we identified biological pathways that may provide insights into potential drug targets for treatment or prevention of CVD. PMID:25533967

  20. Identifying driving gene clusters in complex diseases through critical transition theory

    NASA Astrophysics Data System (ADS)

    Wolanyk, Nathaniel; Wang, Xujing; Hessner, Martin; Gao, Shouguo; Chen, Ye; Jia, Shuang

    A novel approach of looking at the human body using critical transition theory has yielded positive results: clusters of genes that act in tandem to drive complex disease progression. This cluster of genes can be thought of as the first part of a large genetic force that pushes the body from a curable, but sick, point to an incurable diseased point through a catastrophic bifurcation. The data analyzed is time course microarray blood assay data of 7 high risk individuals for Type 1 Diabetes who progressed into a clinical onset, with an additional larger study requested to be presented at the conference. The normalized data is 25,000 genes strong, which were narrowed down based on statistical metrics, and finally a machine learning algorithm using critical transition metrics found the driving network. This approach was created to be repeatable across multiple complex diseases with only progression time course data needed so that it would be applicable to identifying when an individual is at risk of developing a complex disease. Thusly, preventative measures can be enacted, and in the longer term, offers a possible solution to prevent all Type 1 Diabetes.

  1. Exome sequencing identified FGF12 as a novel candidate gene for Kashin-Beck disease.

    PubMed

    Zhang, Feng; Dai, Lanlan; Lin, Weimin; Wang, Wenyu; Liu, Xuanzhu; Zhang, Jianguo; Yang, Tielin; Liu, Xiaogang; Shen, Hui; Chen, Xiangding; Tan, Lijun; Tian, Qing; Deng, Hong-Wen; Xu, Xun; Guo, Xiong

    2016-01-01

    The objective of this study was to identify novel causal genes involved in the pathogenesis of Kashin-Beck disease (KBD). A representative grade III KBD sib pair with serious skeletal growth and development failure was subjected to exome sequencing using the Illumina Hiseq2000 platform. The detected gene mutations were then filtered against the data of 1000 Genome Project, dbSNP database, and BGI inhouse database, and replicated by a genome-wide association study (GWAS) of KBD. Ninety grade II or III KBD patients with extreme KBD phenotypes and 1627 healthy controls were enrolled in the GWAS. Affymetrix Genome-Wide Human SNP Array 6.0 was applied for genotyping. PLINK software was used for association analysis. We identified a novel 106T>C at the 3'UTR of the FGF12 gene, which has not been reported by now. Sequence alignment observed high conversation at the mutated 3'UTR+106T>C locus across various vertebrates. In the GWAS of KBD, we detected nine SNPs of the FGF12 gene showing association evidence (P value < 0.05) with KBD. The most significant association signal was observed at rs1847340 (P value = 1.90 × 10(-5)). This study suggests that FGF12 was a susceptibility gene of KBD. Our results provide novel clues for revealing the pathogenesis of KBD and the biological function of FGF12. PMID:26290467

  2. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

    PubMed Central

    Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

    2016-01-01

    The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

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

    PubMed Central

    2011-01-01

    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

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

    PubMed Central

    2013-01-01

    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

  5. Can modular analysis identify disease-associated candidate genes for therapeutics?

    PubMed

    Tegnér, Jesper

    2009-01-01

    Complex diseases such as allergy change gene expression in several cell types and tissues. Benson and colleagues have now shown, in a paper in BMC Systems Biology, that this complexity can be studied effectively using an integrated experimental and computational modular analysis. Their strategy revealed a core of allergy-associated genes of potential therapeutic value.

  6. Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease.

    PubMed

    Johnson, Michael R; Shkura, Kirill; Langley, Sarah R; Delahaye-Duriez, Andree; Srivastava, Prashant; Hill, W David; Rackham, Owen J L; Davies, Gail; Harris, Sarah E; Moreno-Moral, Aida; Rotival, Maxime; Speed, Doug; Petrovski, Slavé; Katz, Anaïs; Hayward, Caroline; Porteous, David J; Smith, Blair H; Padmanabhan, Sandosh; Hocking, Lynne J; Starr, John M; Liewald, David C; Visconti, Alessia; Falchi, Mario; Bottolo, Leonardo; Rossetti, Tiziana; Danis, Bénédicte; Mazzuferi, Manuela; Foerch, Patrik; Grote, Alexander; Helmstaedter, Christoph; Becker, Albert J; Kaminski, Rafal M; Deary, Ian J; Petretto, Enrico

    2016-02-01

    Genetic determinants of cognition are poorly characterized, and their relationship to genes that confer risk for neurodevelopmental disease is unclear. Here we performed a systems-level analysis of genome-wide gene expression data to infer gene-regulatory networks conserved across species and brain regions. Two of these networks, M1 and M3, showed replicable enrichment for common genetic variants underlying healthy human cognitive abilities, including memory. Using exome sequence data from 6,871 trios, we found that M3 genes were also enriched for mutations ascertained from patients with neurodevelopmental disease generally, and intellectual disability and epileptic encephalopathy in particular. M3 consists of 150 genes whose expression is tightly developmentally regulated, but which are collectively poorly annotated for known functional pathways. These results illustrate how systems-level analyses can reveal previously unappreciated relationships between neurodevelopmental disease-associated genes in the developed human brain, and provide empirical support for a convergent gene-regulatory network influencing cognition and neurodevelopmental disease. PMID:26691832

  7. Sensitized phenotypic screening identifies gene dosage sensitive region on chromosome 11 that predisposes to disease in mice

    PubMed Central

    Ermakova, Olga; Piszczek, Lukasz; Luciani, Luisa; Cavalli, Florence M G; Ferreira, Tiago; Farley, Dominika; Rizzo, Stefania; Paolicelli, Rosa Chiara; Al-Banchaabouchi, Mumna; Nerlov, Claus; Moriggl, Richard; Luscombe, Nicholas M; Gross, Cornelius

    2011-01-01

    The identification of susceptibility genes for human disease is a major goal of current biomedical research. Both sequence and structural variation have emerged as major genetic sources of phenotypic variability and growing evidence points to copy number variation as a particularly important source of susceptibility for disease. Here we propose and validate a strategy to identify genes in which changes in dosage alter susceptibility to disease-relevant phenotypes in the mouse. Our approach relies on sensitized phenotypic screening of megabase-sized chromosomal deletion and deficiency lines carrying altered copy numbers of ∼30 linked genes. This approach offers several advantages as a method to systematically identify genes involved in disease susceptibility. To examine the feasibility of such a screen, we performed sensitized phenotyping in five therapeutic areas (metabolic syndrome, immune dysfunction, atherosclerosis, cancer and behaviour) of a 0.8 Mb reciprocal chromosomal duplication and deficiency on chromosome 11 containing 27 genes. Gene dosage in the region significantly affected risk for high-fat diet-induced metabolic syndrome, antigen-induced immune hypersensitivity, ApoE-induced atherosclerosis, and home cage activity. Follow up studies on individual gene knockouts for two candidates in the region showed that copy number variation in Stat5 was responsible for the phenotypic variation in antigen-induced immune hypersensitivity and metabolic syndrome. These data demonstrate the power of sensitized phenotypic screening of segmental aneuploidy lines to identify disease susceptibility genes. PMID:21204268

  8. Using gene expression data to identify certain gastro-intestinal diseases

    PubMed Central

    2012-01-01

    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. PMID:23171526

  9. 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

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

    2013-01-01

    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.

  10. Next generation exome sequencing of paediatric inflammatory bowel disease patients identifies rare and novel variants in candidate genes

    PubMed Central

    Christodoulou, Katja; Wiskin, Anthony E; Gibson, Jane; Tapper, William; Willis, Claire; Afzal, Nadeem A; Upstill-Goddard, Rosanna; Holloway, John W; Simpson, Michael A; Beattie, R Mark; Collins, Andrew

    2013-01-01

    Background Multiple genes have been implicated by association studies in altering inflammatory bowel disease (IBD) predisposition. Paediatric patients often manifest more extensive disease and a particularly severe disease course. It is likely that genetic predisposition plays a more substantial role in this group. Objective To identify the spectrum of rare and novel variation in known IBD susceptibility genes using exome sequencing analysis in eight individual cases of childhood onset severe disease. Design DNA samples from the eight patients underwent targeted exome capture and sequencing. Data were processed through an analytical pipeline to align sequence reads, conduct quality checks, and identify and annotate variants where patient sequence differed from the reference sequence. For each patient, the entire complement of rare variation within strongly associated candidate genes was catalogued. Results Across the panel of 169 known IBD susceptibility genes, approximately 300 variants in 104 genes were found. Excluding splicing and HLA-class variants, 58 variants across 39 of these genes were classified as rare, with an alternative allele frequency of <5%, of which 17 were novel. Only two patients with early onset Crohn's disease exhibited rare deleterious variations within NOD2: the previously described R702W variant was the sole NOD2 variant in one patient, while the second patient also carried the L1007 frameshift insertion. Both patients harboured other potentially damaging mutations in the GSDMB, ERAP2 and SEC16A genes. The two patients severely affected with ulcerative colitis exhibited a distinct profile: both carried potentially detrimental variation in the BACH2 and IL10 genes not seen in other patients. Conclusion For each of the eight individuals studied, all non-synonymous, truncating and frameshift mutations across all known IBD genes were identified. A unique profile of rare and potentially damaging variants was evident for each patient with this

  11. Real-Time qPCR Identifies Suitable Reference Genes for Borna Disease Virus-Infected Rat Cortical Neurons

    PubMed Central

    Zhang, Lujun; Liu, Siwen; Zhang, Liang; You, Hongmin; Huang, Rongzhong; Sun, Lin; He, Peng; Chen, Shigang; Zhang, Hong; Xie, Peng

    2014-01-01

    Quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) is the most commonly-used technique to identify gene expression profiles. The selection of stably expressed reference genes is a prerequisite to properly evaluating gene expression. Here, the suitability of commonly-used reference genes in normalizing RT-qPCR assays of mRNA expression in cultured rat cortical neurons infected with Borna disease virus (BDV) was assessed. The expressions of eight commonly-used reference genes were comparatively analyzed in BDV-infected rat cortical neurons and non-infected control neurons mainly across 9 and 12 days post-infection. These reference genes were validated by RT-qPCR and separately ranked by four statistical algorithms: geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. Then, the RankAggreg package was used to construct consensus rankings. ARBP was found to be the most stable internal control gene at Day 9, and ACTB at Day 12. As the assessment of the validity of the selected reference genes confirms the suitability of applying a combination of the two most stable references genes, combining the two most stable genes for normalization of RT-qPCR studies in BDV-infected rat cortical neurons is recommended at each time point. This study can contribute to improving BDV research by providing the means by which to obtain more reliable and accurate gene expression measurements. PMID:25431926

  12. Genome-wide transcriptional analysis of flagellar regeneration in Chlamydomonas reinhardtii identifies orthologs of ciliary disease genes

    NASA Technical Reports Server (NTRS)

    Stolc, Viktor; Samanta, Manoj Pratim; Tongprasit, Waraporn; Marshall, Wallace F.

    2005-01-01

    The important role that cilia and flagella play in human disease creates an urgent need to identify genes involved in ciliary assembly and function. The strong and specific induction of flagellar-coding genes during flagellar regeneration in Chlamydomonas reinhardtii suggests that transcriptional profiling of such cells would reveal new flagella-related genes. We have conducted a genome-wide analysis of RNA transcript levels during flagellar regeneration in Chlamydomonas by using maskless photolithography method-produced DNA oligonucleotide microarrays with unique probe sequences for all exons of the 19,803 predicted genes. This analysis represents previously uncharacterized whole-genome transcriptional activity profiling study in this important model organism. Analysis of strongly induced genes reveals a large set of known flagellar components and also identifies a number of important disease-related proteins as being involved with cilia and flagella, including the zebrafish polycystic kidney genes Qilin, Reptin, and Pontin, as well as the testis-expressed tubby-like protein TULP2.

  13. Chicks and SNPs--an entree into identifying genes conferring disease resistance in chicken

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With high-density chicken rearing, control of infectious diseases are critical for economic viability and maintaining public confidence in poultry products. Among poultry diseases, Marek’s disease (MD), a lymphoproliferative disease caused by the highly oncogenic herpesvirus Marek's disease virus (M...

  14. Identify potential drugs for cardiovascular diseases caused by stress-induced genes in vascular smooth muscle cells

    PubMed Central

    Ciou, Jin-Shuei; Chen, Shun-Tsung; Chung, Yi; Tsai, Jeffrey J. P.; Kurubanjerdjit, Nilubon

    2016-01-01

    Background Abnormal proliferation of vascular smooth muscle cells (VSMC) is a major cause of cardiovascular diseases (CVDs). Many studies suggest that vascular injury triggers VSMC dedifferentiation, which results in VSMC changes from a contractile to a synthetic phenotype; however, the underlying molecular mechanisms are still unclear. Methods In this study, we examined how VSMC responds under mechanical stress by using time-course microarray data. A three-phase study was proposed to investigate the stress-induced differentially expressed genes (DEGs) in VSMC. First, DEGs were identified by using the moderated t-statistics test. Second, more DEGs were inferred by using the Gaussian Graphical Model (GGM). Finally, the topological parameters-based method and cluster analysis approach were employed to predict the last batch of DEGs. To identify the potential drugs for vascular diseases involve VSMC proliferation, the drug-gene interaction database, Connectivity Map (cMap) was employed. Success of the predictions were determined using in-vitro data, i.e. MTT and clonogenic assay. Results Based on the differential expression calculation, at least 23 DEGs were found, and the findings were qualified by previous studies on VSMC. The results of gene set enrichment analysis indicated that the most often found enriched biological processes are cell-cycle-related processes. Furthermore, more stress-induced genes, well supported by literature, were found by applying graph theory to the gene association network (GAN). Finally, we showed that by processing the cMap input queries with a cluster algorithm, we achieved a substantial increase in the number of potential drugs with experimental IC50 measurements. With this novel approach, we have not only successfully identified the DEGs, but also improved the DEGs prediction by performing the topological and cluster analysis. Moreover, the findings are remarkably validated and in line with the literature. Furthermore, the cMap and

  15. Diagnostic Exome Sequencing Identifies a Novel Gene, EMILIN1, Associated with Autosomal‐Dominant Hereditary Connective Tissue Disease

    PubMed Central

    Capuano, Alessandra; Bucciotti, Francesco; Farwell, Kelly D.; Tippin Davis, Brigette; Mroske, Cameron; Hulick, Peter J.; Weissman, Scott M.; Gao, Qingshen; Spessotto, Paola; Doliana, Roberto

    2015-01-01

    ABSTRACT Heritable connective tissue diseases are a highly heterogeneous family of over 200 disorders that affect the extracellular matrix. While the genetic basis of several disorders is established, the etiology has not been discovered for a large portion of patients, likely due to rare yet undiscovered disease genes. By performing trio‐exome sequencing of a 55‐year‐old male proband presenting with multiple symptoms indicative of a connective disorder, we identified a heterozygous missense alteration in exon 1 of the Elastin Microfibril Interfacer 1 (EMILIN1) gene, c.64G>A (p.A22T). The proband presented with ascending and descending aortic aneurysms, bilateral lower leg and foot sensorimotor peripheral neuropathy, arthropathy, and increased skin elasticity. Sanger sequencing confirmed that the EMILIN1 alteration, which maps around the signal peptide cleavage site, segregated with disease in the affected proband, mother, and son. The impaired secretion of EMILIN‐1 in cells transfected with the mutant p.A22T coincided with abnormal protein accumulation within the endoplasmic reticulum. In skin biopsy of the proband, we detected less EMILIN‐1 with disorganized and abnormal coarse fibrils, aggregated deposits underneath the epidermis basal lamina, and dermal cells apoptosis. These findings collectively suggest that EMILIN1 may represent a new disease gene associated with an autosomal‐dominant connective tissue disorder. PMID:26462740

  16. Diagnostic Exome Sequencing Identifies a Novel Gene, EMILIN1, Associated with Autosomal-Dominant Hereditary Connective Tissue Disease.

    PubMed

    Capuano, Alessandra; Bucciotti, Francesco; Farwell, Kelly D; Tippin Davis, Brigette; Mroske, Cameron; Hulick, Peter J; Weissman, Scott M; Gao, Qingshen; Spessotto, Paola; Colombatti, Alfonso; Doliana, Roberto

    2016-01-01

    Heritable connective tissue diseases are a highly heterogeneous family of over 200 disorders that affect the extracellular matrix. While the genetic basis of several disorders is established, the etiology has not been discovered for a large portion of patients, likely due to rare yet undiscovered disease genes. By performing trio-exome sequencing of a 55-year-old male proband presenting with multiple symptoms indicative of a connective disorder, we identified a heterozygous missense alteration in exon 1 of the Elastin Microfibril Interfacer 1 (EMILIN1) gene, c.64G>A (p.A22T). The proband presented with ascending and descending aortic aneurysms, bilateral lower leg and foot sensorimotor peripheral neuropathy, arthropathy, and increased skin elasticity. Sanger sequencing confirmed that the EMILIN1 alteration, which maps around the signal peptide cleavage site, segregated with disease in the affected proband, mother, and son. The impaired secretion of EMILIN-1 in cells transfected with the mutant p.A22T coincided with abnormal protein accumulation within the endoplasmic reticulum. In skin biopsy of the proband, we detected less EMILIN-1 with disorganized and abnormal coarse fibrils, aggregated deposits underneath the epidermis basal lamina, and dermal cells apoptosis. These findings collectively suggest that EMILIN1 may represent a new disease gene associated with an autosomal-dominant connective tissue disorder.

  17. Combined NGS Approaches Identify Mutations in the Intraflagellar Transport Gene IFT140 in Skeletal Ciliopathies with Early Progressive Kidney Disease

    PubMed Central

    Schmidts, Miriam; Frank, Valeska; Eisenberger, Tobias; al Turki, Saeed; Bizet, Albane A.; Antony, Dinu; Rix, Suzanne; Decker, Christian; Bachmann, Nadine; Bald, Martin; Vinke, Tobias; Toenshoff, Burkhard; Donato, Natalia Di; Neuhann, Theresa; Hartley, Jane L.; Maher, Eamonn R.; Bogdanović, Radovan; Peco-Antić, Amira; Mache, Christoph; Hurles, Matthew E.; Joksić, Ivana; Guć-Šćekić, Marija; Dobricic, Jelena; Brankovic-Magic, Mirjana; Bolz, Hanno J.; Pazour, Gregory J.; Beales, Philip L.; Scambler, Peter J.; Saunier, Sophie; Mitchison, Hannah M.; Bergmann, Carsten

    2014-01-01

    Ciliopathies are genetically heterogeneous disorders characterized by variable expressivity and overlaps between different disease entities. This is exemplified by the short rib-polydactyly syndromes, Jeune, Sensenbrenner, and Mainzer-Saldino chondrodysplasia syndromes. These three syndromes are frequently caused by mutations in intraflagellar transport (IFT) genes affecting the primary cilia, which play a crucial role in skeletal and chondral development. Here, we identified mutations in IFT140, an IFT complex A gene, in five Jeune asphyxiating thoracic dystrophy (JATD) and two Mainzer-Saldino syndrome (MSS) families, by screening a cohort of 66 JATD/MSS patients using whole exome sequencing and targeted resequencing of a customized ciliopathy gene panel. We also found an enrichment of rare IFT140 alleles in JATD compared with nonciliopathy diseases, implying putative modifier effects for certain alleles. IFT140 patients presented with mild chest narrowing, but all had end-stage renal failure under 13 years of age and retinal dystrophy when examined for ocular dysfunction. This is consistent with the severe cystic phenotype of Ift140 conditional knockout mice, and the higher level of Ift140 expression in kidney and retina compared with the skeleton at E15.5 in the mouse. IFT140 is therefore a major cause of cono-renal syndromes (JATD and MSS). The present study strengthens the rationale for IFT140 screening in skeletal ciliopathy spectrum patients that have kidney disease and/or retinal dystrophy. PMID:23418020

  18. Saccharomyces Fungemia Associated with Esophageal Disease Identified by D1/D2 Ribosomal RNA Gene Sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Disseminated Saccharomyces infection has been reported in immunosuppressed patients treated with probiotics, but disseminated Saccharomyces cerevisiae infection associated with underlying esophageal disease is not previously described. Saccharomyces cerevisiae (which occasionally colonizes the gast...

  19. Genome-wide association study for acute otitis media in children identifies FNDC1 as disease contributing gene

    PubMed Central

    van Ingen, Gijs; Li, Jin; Goedegebure, André; Pandey, Rahul; Li, Yun Rose; March, Michael E.; Jaddoe, Vincent W. V.; Bakay, Marina; Mentch, Frank D.; Thomas, Kelly; Wei, Zhi; Chang, Xiao; Hain, Heather S.; Uitterlinden, André G.; Moll, Henriette A.; van Duijn, Cornelia M.; Rivadeneira, Fernando; Raat, Hein; Baatenburg de Jong, Robert J.; Sleiman, Patrick M.; van der Schroeff, Marc P.; Hakonarson, Hakon

    2016-01-01

    Acute otitis media (AOM) is among the most common pediatric diseases, and the most frequent reason for antibiotic treatment in children. Risk of AOM is dependent on environmental and host factors, as well as a significant genetic component. We identify genome-wide significance at a locus on 6q25.3 (rs2932989, Pmeta=2.15 × 10−09), and show that the associated variants are correlated with the methylation status of the FNDC1 gene (cg05678571, P=1.43 × 10−06), and further show it is an eQTL for FNDC1 (P=9.3 × 10−05). The mouse homologue, Fndc1, is expressed in middle ear tissue and its expression is upregulated upon lipopolysaccharide treatment. In this first GWAS of AOM and the largest OM genetic study to date, we identify the first genome-wide significant locus associated with AOM. PMID:27677580

  20. Genome-Wide Association Study Identifies Novel Susceptibility Genes Associated with Coronary Artery Aneurysm Formation in Kawasaki Disease.

    PubMed

    Kuo, Ho-Chang; Li, Sung-Chou; Guo, Mindy Ming-Huey; Huang, Ying-Hsien; Yu, Hong-Ren; Huang, Fu-Chen; Jiao, Fuyong; Kuo, Hsing-Chun; Andrade, Jorge; Chan, Wen-Ching

    2016-01-01

    Kawasaki disease (KD) or Kawasaki syndrome is known as a vasculitis of small to medium-sized vessels, and coronary arteries are predominantly involved in childhood. Generally, 20-25% of untreated with IVIG and 3-5% of treated KD patients have been developed coronary artery lesions (CALs), such as dilatation and aneurysm. Understanding how coronary artery aneurysms (CAAs) are established and maintained in KD patients is therefore of great importance. Upon our previous genotyping data of 157 valid KD subjects, a genome-wide association study (GWAS) has been conducted among 11 (7%) CAA-developed KD patients to reveal five significant genetic variants passed pre-defined thresholds and resulted in two novel susceptibility protein-coding genes, which are NEBL (rs16921209 (P = 7.44 × 10-9; OR = 32.22) and rs7922552 (P = 8.43 × 10-9; OR = 32.0)) and TUBA3C (rs17076896 (P = 8.04 × 10-9; OR = 21.03)). Their known functions have been reported to associate with cardiac muscle and tubulin, respectively. As a result, this might imply their putative roles of establishing CAAs during KD progression. Additionally, various model analyses have been utilized to determine dominant and recessive inheritance patterns of identified susceptibility mutations. Finally, all susceptibility genes hit by significant genetic variants were further investigated and the top three representative gene-ontology (GO) clusters were regulation of cell projection organization, neuron recognition, and peptidyl-threonine phosphorylation. Our results help to depict the potential routes of the pathogenesis of CAAs in KD patients and will facilitate researchers to improve the diagnosis and prognosis of KD in personalized medicine. PMID:27171184

  1. Genome-Wide Association Study Identifies Novel Susceptibility Genes Associated with Coronary Artery Aneurysm Formation in Kawasaki Disease

    PubMed Central

    Guo, Mindy Ming-Huey; Huang, Ying-Hsien; Yu, Hong-Ren; Huang, Fu-Chen; Jiao, Fuyong; Kuo, Hsing-Chun; Andrade, Jorge

    2016-01-01

    Kawasaki disease (KD) or Kawasaki syndrome is known as a vasculitis of small to medium-sized vessels, and coronary arteries are predominantly involved in childhood. Generally, 20–25% of untreated with IVIG and 3–5% of treated KD patients have been developed coronary artery lesions (CALs), such as dilatation and aneurysm. Understanding how coronary artery aneurysms (CAAs) are established and maintained in KD patients is therefore of great importance. Upon our previous genotyping data of 157 valid KD subjects, a genome-wide association study (GWAS) has been conducted among 11 (7%) CAA-developed KD patients to reveal five significant genetic variants passed pre-defined thresholds and resulted in two novel susceptibility protein-coding genes, which are NEBL (rs16921209 (P = 7.44 × 10−9; OR = 32.22) and rs7922552 (P = 8.43 × 10−9; OR = 32.0)) and TUBA3C (rs17076896 (P = 8.04 × 10−9; OR = 21.03)). Their known functions have been reported to associate with cardiac muscle and tubulin, respectively. As a result, this might imply their putative roles of establishing CAAs during KD progression. Additionally, various model analyses have been utilized to determine dominant and recessive inheritance patterns of identified susceptibility mutations. Finally, all susceptibility genes hit by significant genetic variants were further investigated and the top three representative gene-ontology (GO) clusters were regulation of cell projection organization, neuron recognition, and peptidyl-threonine phosphorylation. Our results help to depict the potential routes of the pathogenesis of CAAs in KD patients and will facilitate researchers to improve the diagnosis and prognosis of KD in personalized medicine. PMID:27171184

  2. Genome-Wide Analysis Identifies IL-18 and FUCA2 as Novel Genes Associated with Diastolic Function in African Americans with Sickle Cell Disease

    PubMed Central

    Sysol, Justin R.; Abbasi, Taimur; Patel, Amit R.; Lang, Roberto M.; Gupta, Akash; Garcia, Joe G. N.; Gordeuk, Victor R.; Machado, Roberto F.

    2016-01-01

    Background Diastolic dysfunction is common in sickle cell disease (SCD), and is associated with an increased risk of mortality. However, the molecular pathogenesis underlying this development is poorly understood. The aim of this study was to identify a gene expression profile that is associated with diastolic function in SCD, potentially elucidating molecular mechanisms behind diastolic dysfunction development. Methods Diastolic function was measured via echocardiography in 65 patients with SCD from two independent study populations. Gene expression microarray data was compared with diastolic function in both study cohorts. Candidate genes that associated in both analyses were tested for validation in a murine SCD model. Lastly, genotyping array data from the replication cohort was used to derive cis-expression quantitative trait loci (cis-eQTLs) and genetic associations within the candidate gene regions. Results Transcriptome data from both patient cohorts implicated 7 genes associated with diastolic function, and mouse SCD myocardial expression validated 3 of these genes. Genetic associations and eQTLs were detected in 2 of the 3 genes, FUCA2 and IL18. Conclusions FUCA2 and IL18 are associated with diastolic function in SCD patients, and may be involved in the pathogenesis of the disease. Genetic polymorphisms within the FUCA2 and IL18 gene regions are also associated with diastolic function in SCD, likely by affecting expression levels of the genes. PMID:27636371

  3. Susceptibility to thyroid autoimmune disease: molecular analysis of HLA-D region genes identifies new markers for goitrous Hashimoto's thyroiditis.

    PubMed

    Badenhoop, K; Schwarz, G; Walfish, P G; Drummond, V; Usadel, K H; Bottazzo, G F

    1990-11-01

    Hashimoto's thyroiditis has been shown to be associated with the HLA-specificities DR4 and DR5. Since former association studies yielded variable results, we used novel molecular typing methods to assess predisposing immunogenetic factors. Gene analysis of the HLA-DR-DQ and tumor necrosis factor region was performed in a group of Hashimoto's thyroiditis patients and randomly chosen controls using standards and nomenclature of the 10th International Histocompatibility Workshop. Genomic DNA of patients and controls was analyzed using a cDNA probe of the DQB1 gene. The resulting restriction fragment patterns allowed the determination of newly defined DQw-types 1-9. We find the strongest relative risk conferred by DQw7 (RR = 4.7), that is observed in 36 of 64 patients (56%) and only 21 of 98 controls (21%) (P corr less than 0.002). Comparison of DNA sequence variation in the DQB1 gene, that is found predominantly in Hashimoto's thyroiditis patients, indicates that codons 45 and 57 are critical features in DQw7 which distinguish it from other DQw specificities. The adjacent DQA1 genes also display a significant association with Hashimoto's thyroiditis (DQA1*0201/*0301 heterozygotes were found in 37% of patients and 15% controls, P less than 0.03). No significant association could be found with polymorphisms of the tumor necrosis factor gene. These results provide a new basis for the concept of genetic susceptibility in Hashimoto's thyroiditis and will help to elucidate the underlying autoimmune mechanisms that lead to disease at the functional level. PMID:1977755

  4. A bivariate genome-wide association study identifies ADAM12 as a novel susceptibility gene for Kashin-Beck disease

    PubMed Central

    Hao, Jingcan; Wang, Wenyu; Wen, Yan; Xiao, Xiao; He, Awen; Guo, Xiong; Yang, Tielin; Liu, Xiaogang; Shen, Hui; Chen, Xiangding; Tian, Qing; Deng, Hong-Wen; Zhang, Feng

    2016-01-01

    Kashin-Beck disease (KBD) is a chronic osteoarthropathy, which manifests as joint deformities and growth retardation. Only a few genetic studies of growth retardation associated with the KBD have been carried out by now. In this study, we conducted a two-stage bivariate genome-wide association study (BGWAS) of the KBD using joint deformities and body height as study phenotypes, totally involving 2,417 study subjects. Articular cartilage specimens from 8 subjects were collected for immunohistochemistry. In the BGWAS, ADAM12 gene achieved the most significant association (rs1278300 p-value = 9.25 × 10−9) with the KBD. Replication study observed significant association signal at rs1278300 (p-value = 0.007) and rs1710287 (p-value = 0.002) of ADAM12 after Bonferroni correction. Immunohistochemistry revealed significantly decreased expression level of ADAM12 protein in the KBD articular cartilage (average positive chondrocyte rate = 47.59 ± 7.79%) compared to healthy articular cartilage (average positive chondrocyte rate = 64.73 ± 5.05%). Our results suggest that ADAM12 gene is a novel susceptibility gene underlying both joint destruction and growth retardation of the KBD. PMID:27545300

  5. Whole-genome conditional two-locus analysis identifies novel candidate genes for late-onset Parkinson's disease.

    PubMed

    González-Pérez, A; Gayán, J; Marín, J; Galán, J J; Sáez, M E; Real, L M; Antúnez, C; Ruiz, A

    2009-07-01

    Whole-genome epistasis analysis may add a new layer of knowledge to whole-genome association studies, permitting the identification of new candidate genes which are completely transparent during conventional single-locus analysis. We present the first whole-genome conditional two-locus analysis in Parkinson's disease (PD). We scanned the entire genome and selected markers that interacted with a set of well-known loci previously associated to PD (SNCA, Parkin, LRRK2, UCHL1, DJ-1, PINK and MAPT). Our work describes several loci potentially related to PD risk which interact with SNCA, PARK1 and LRRK2 markers. We propose conditional whole-genome two-locus association analysis as a valuable method that might be helpful in re-analysing and re-interpreting data from whole-genome association studies.

  6. Twelve novel HGD gene variants identified in 99 alkaptonuria patients: focus on 'black bone disease' in Italy.

    PubMed

    Nemethova, Martina; Radvanszky, Jan; Kadasi, Ludevit; Ascher, David B; Pires, Douglas E V; Blundell, Tom L; Porfirio, Berardino; Mannoni, Alessandro; Santucci, Annalisa; Milucci, Lia; Sestini, Silvia; Biolcati, Gianfranco; Sorge, Fiammetta; Aurizi, Caterina; Aquaron, Robert; Alsbou, Mohammed; Lourenço, Charles Marques; Ramadevi, Kanakasabapathi; Ranganath, Lakshminarayan R; Gallagher, James A; van Kan, Christa; Hall, Anthony K; Olsson, Birgitta; Sireau, Nicolas; Ayoob, Hana; Timmis, Oliver G; Sang, Kim-Hanh Le Quan; Genovese, Federica; Imrich, Richard; Rovensky, Jozef; Srinivasaraghavan, Rangan; Bharadwaj, Shruthi K; Spiegel, Ronen; Zatkova, Andrea

    2016-01-01

    Alkaptonuria (AKU) is an autosomal recessive disorder caused by mutations in homogentisate-1,2-dioxygenase (HGD) gene leading to the deficiency of HGD enzyme activity. The DevelopAKUre project is underway to test nitisinone as a specific treatment to counteract this derangement of the phenylalanine-tyrosine catabolic pathway. We analysed DNA of 40 AKU patients enrolled for SONIA1, the first study in DevelopAKUre, and of 59 other AKU patients sent to our laboratory for molecular diagnostics. We identified 12 novel DNA variants: one was identified in patients from Brazil (c.557T>A), Slovakia (c.500C>T) and France (c.440T>C), three in patients from India (c.469+6T>C, c.650-85A>G, c.158G>A), and six in patients from Italy (c.742A>G, c.614G>A, c.1057A>C, c.752G>A, c.119A>C, c.926G>T). Thus, the total number of potential AKU-causing variants found in 380 patients reported in the HGD mutation database is now 129. Using mCSM and DUET, computational approaches based on the protein 3D structure, the novel missense variants are predicted to affect the activity of the enzyme by three mechanisms: decrease of stability of individual protomers, disruption of protomer-protomer interactions or modification of residues in the region of the active site. We also present an overview of AKU in Italy, where so far about 60 AKU cases are known and DNA analysis has been reported for 34 of them. In this rather small group, 26 different HGD variants affecting function were described, indicating rather high heterogeneity. Twelve of these variants seem to be specific for Italy.

  7. Human disease genes.

    PubMed

    Jimenez-Sanchez, G; Childs, B; Valle, D

    2001-02-15

    The complete human genome sequence will facilitate the identification of all genes that contribute to disease. We propose that the functional classification of disease genes and their products will reveal general principles of human disease. We have determined functional categories for nearly 1,000 documented disease genes, and found striking correlations between the function of the gene product and features of disease, such as age of onset and mode of inheritance. As knowledge of disease genes grows, including those contributing to complex traits, more sophisticated analyses will be possible; their results will yield a deeper understanding of disease and an enhanced integration of medicine with biology.

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

    PubMed Central

    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; Bossù, 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; Buée, L; Campion, D; Soininen, H; Breteler, M; Riemenschneider, M; Van Broeckhoven, C; Alpérovitch, A; Lathrop, M; Trégouët, D-A; Williams, J; Amouyel, P

    2013-01-01

    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 Aβ plasma concentrations in three independent non-demented populations (n=2579). We reported that polymorphisms were associated with plasma Aβ42/Aβ40 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. PMID:22430674

  9. A module-based analytical strategy to identify novel disease-associated genes shows an inhibitory role for interleukin 7 Receptor in allergic inflammation

    PubMed Central

    Mobini, Reza; Andersson, Bengt A; Erjefält, Jonas; Hahn-Zoric, Mirjana; Langston, Michael A; Perkins, Andy D; Cardell, Lars Olaf; Benson, Mikael

    2009-01-01

    Background The identification of novel genes by high-throughput studies of complex diseases is complicated by the large number of potential genes. However, since disease-associated genes tend to interact, one solution is to arrange them in modules based on co-expression data and known gene interactions. The hypothesis of this study was that such a module could be a) found and validated in allergic disease and b) used to find and validate one ore more novel disease-associated genes. Results To test these hypotheses integrated analysis of a large number of gene expression microarray experiments from different forms of allergy was performed. This led to the identification of an experimentally validated reference gene that was used to construct a module of co-expressed and interacting genes. This module was validated in an independent material, by replicating the expression changes in allergen-challenged CD4+ cells. Moreover, the changes were reversed following treatment with corticosteroids. The module contained several novel disease-associated genes, of which the one with the highest number of interactions with known disease genes, IL7R, was selected for further validation. The expression levels of IL7R in allergen challenged CD4+ cells decreased following challenge but increased after treatment. This suggested an inhibitory role, which was confirmed by functional studies. Conclusion We propose that a module-based analytical strategy is generally applicable to find novel genes in complex diseases. PMID:19216740

  10. 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- ...

  11. A Parkinson's disease gene regulatory network identifies the signaling protein RGS2 as a modulator of LRRK2 activity and neuronal toxicity

    PubMed Central

    Dusonchet, Julien; Li, Hu; Guillily, Maria; Liu, Min; Stafa, Klodjan; Derada Troletti, Claudio; Boon, Joon Y.; Saha, Shamol; Glauser, Liliane; Mamais, Adamantios; Citro, Allison; Youmans, Katherine L.; Liu, LiQun; Schneider, Bernard L.; Aebischer, Patrick; Yue, Zhenyu; Bandopadhyay, Rina; Glicksman, Marcie A.; Moore, Darren J.; Collins, James J.; Wolozin, Benjamin

    2014-01-01

    Mutations in LRRK2 are one of the primary genetic causes of Parkinson's disease (PD). LRRK2 contains a kinase and a GTPase domain, and familial PD mutations affect both enzymatic activities. However, the signaling mechanisms regulating LRRK2 and the pathogenic effects of familial mutations remain unknown. Identifying the signaling proteins that regulate LRRK2 function and toxicity remains a critical goal for the development of effective therapeutic strategies. In this study, we apply systems biology tools to human PD brain and blood transcriptomes to reverse-engineer a LRRK2-centered gene regulatory network. This network identifies several putative master regulators of LRRK2 function. In particular, the signaling gene RGS2, which encodes for a GTPase-activating protein (GAP), is a key regulatory hub connecting the familial PD-associated genes DJ-1 and PINK1 with LRRK2 in the network. RGS2 expression levels are reduced in the striata of LRRK2 and sporadic PD patients. We identify RGS2 as a novel interacting partner of LRRK2 in vivo. RGS2 regulates both the GTPase and kinase activities of LRRK2. We show in mammalian neurons that RGS2 regulates LRRK2 function in the control of neuronal process length. RGS2 is also protective against neuronal toxicity of the most prevalent mutation in LRRK2, G2019S. We find that RGS2 regulates LRRK2 function and neuronal toxicity through its effects on kinase activity and independently of GTPase activity, which reveals a novel mode of action for GAP proteins. This work identifies RGS2 as a promising target for interfering with neurodegeneration due to LRRK2 mutations in PD patients. PMID:24794857

  12. Experimental approaches for identifying schizophrenia risk genes.

    PubMed

    Mantripragada, Kiran K; Carroll, Liam S; Williams, Nigel M

    2010-01-01

    Schizophrenia is a severe, debilitating and common psychiatric disorder, which directly affects approximately 1% of the population worldwide. Although previous studies have unequivocally shown that schizophrenia has a strong genetic component, our understanding of its pathophysiology remains limited. The precise genetic architecture of schizophrenia remains elusive and is likely to be complex. It is believed that multiple genetic variants, with each contributing a modest effect on disease risk, interact with environmental factors resulting in the phenotype. In this chapter, we summarise the main molecular genetic approaches that have been utilised in identifying susceptibility genes for schizophrenia and discuss the advantages and disadvantages of each approach. First, we detail the findings of linkage mapping in pedigrees (affected families), which analyse the co-segregation of polymorphic genetic markers with disease phenotype. Second, the contribution of targeted and genome-wide association studies, which compare differential allelic frequencies in schizophrenia cases and matched controls, is presented. Third, we discuss about the identification of susceptibility genes through analysis of chromosomal structural variation (gains and losses of genetic material). Lastly, we introduce the concept of re-sequencing, where the entire genome/exome is sequenced both in affected and unaffected individuals. This approach has the potential to provide a clarified picture of the majority of the genetic variation underlying disease pathogenesis. PMID:21312414

  13. Caenorhabditis elegans expressing the Saccharomyces cerevisiae NADH alternative dehydrogenase Ndi1p, as a tool to identify new genes involved in complex I related diseases

    PubMed Central

    Cossard, Raynald; Esposito, Michela; Sellem, Carole H.; Pitayu, Laras; Vasnier, Christelle; Delahodde, Agnès; Dassa, Emmanuel P.

    2015-01-01

    Isolated complex I deficiencies are one of the most commonly observed biochemical features in patients suffering from mitochondrial disorders. In the majority of these clinical cases the molecular bases of the diseases remain unknown suggesting the involvement of unidentified factors that are critical for complex I function. The Saccharomyces cerevisiae NDI1 gene, encoding the mitochondrial internal NADH dehydrogenase was previously shown to complement a complex I deficient strain in Caenorhabditis elegans with notable improvements in reproduction and whole organism respiration. These features indicate that Ndi1p can functionally integrate the respiratory chain, allowing complex I deficiency complementation. Taking into account the Ndi1p ability to bypass complex I, we evaluate the possibility to extend the range of defects/mutations causing complex I deficiencies that can be alleviated by NDI1 expression. We report here that NDI1 expressing animals unexpectedly exhibit a slightly shortened lifespan, a reduction in the progeny, and a depletion of the mitochondrial genome. However, Ndi1p is expressed and targeted to the mitochondria as a functional protein that confers rotenone resistance to those animals without affecting their respiration rate and ATP content. We show that the severe embryonic lethality level caused by the RNAi knockdowns of complex I structural subunit encoding genes (e.g., NDUFV1, NDUFS1, NDUFS6, NDUFS8, or GRIM-19 human orthologs) in wild type animals is significantly reduced in the Ndi1p expressing worm. All together these results open up the perspective to identify new genes involved in complex I function, assembly, or regulation by screening an RNAi library of genes leading to embryonic lethality that should be rescued by NDI1 expression. PMID:26124772

  14. Expression of individual mutations and haplotypes in the galactocerebrosidase gene identified by the newborn screening program in New York State and in confirmed cases of Krabbe's disease.

    PubMed

    Saavedra-Matiz, Carlos A; Luzi, Paola; Nichols, Matthew; Orsini, Joseph J; Caggana, Michele; Wenger, David A

    2016-11-01

    Newborn screening (NBS) for Krabbe's disease (KD) has been instituted in several states, and New York State has had the longest experience. After an initial screening of dried blood spots, samples from individuals with galactocerebrosidase (GALC) values below a given cutoff level were subjected to additional testing, including sequencing of the GALC gene. This resulted in the identification of mutations that had previously been found in confirmed KD patients and of variants that had never previously been reported. Some individuals had variants considered to be polymorphisms, alone or on the same allele as another mutation. To help with counseling of families on the risk for a newborn to develop KD, expression studies were conducted with these variants identified by NBS. GALC activity was measured in COS1 cells for 140 constructs and compared with mutations that had previously been seen in confirmed cases of KD. When a polymorphism was present on the same allele as the variant, expressed activity was measured with and without the polymorphism. In some cases the presence of the polymorphism greatly lowered the measured GALC activity, possibly making it disease causing. Although it is not possible to predict conclusively whether a variant is severe and will result in infantile KD if two such variants are present or whether a variant is mild and will result in late-onset disease, some variants clearly are not disease causing. This is the largest expression study of GALC variants/mutations found in NBS and confirmed KD cases. This work will be helpful for counseling families of screen-positive newborns found to have low GALC activity. © 2016 Wiley Periodicals, Inc. PMID:27638593

  15. Midbrain Gene Screening Identifies a New Mesoaccumbal Glutamatergic Pathway and a Marker for Dopamine Cells Neuroprotected in Parkinson’s Disease

    PubMed Central

    Viereckel, Thomas; Dumas, Sylvie; Smith-Anttila, Casey J. A.; Vlcek, Bianca; Bimpisidis, Zisis; Lagerström, Malin C.; Konradsson-Geuken, Åsa; Wallén-Mackenzie, Åsa

    2016-01-01

    The ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) of the midbrain are associated with Parkinson’s disease (PD), schizophrenia, mood disorders and addiction. Based on the recently unraveled heterogeneity within the VTA and SNc, where glutamate, GABA and co-releasing neurons have been found to co-exist with the classical dopamine neurons, there is a compelling need for identification of gene expression patterns that represent this heterogeneity and that are of value for development of human therapies. Here, several unique gene expression patterns were identified in the mouse midbrain of which NeuroD6 and Grp were expressed within different dopaminergic subpopulations of the VTA, and TrpV1 within a small heterogeneous population. Optogenetics-coupled in vivo amperometry revealed a previously unknown glutamatergic mesoaccumbal pathway characterized by TrpV1-Cre-expression. Human GRP was strongly detected in non-melanized dopaminergic neurons within the SNc of both control and PD brains, suggesting GRP as a marker for neuroprotected neurons in PD. This study thus unravels markers for distinct subpopulations of neurons within the mouse and human midbrain, defines unique anatomical subregions within the VTA and exposes an entirely new glutamatergic pathway. Finally, both TRPV1 and GRP are implied in midbrain physiology of importance to neurological and neuropsychiatric disorders. PMID:27762319

  16. Huntington's disease gene located.

    PubMed

    Kolata, G

    1983-11-25

    Investigators have found a restriction enzyme marker, a piece of DNA that can be located with recombinant DNA techniques, that is so close to the Huntington's disease gene that its presence can be used as an indicator for that gene. If this marker is used as a diagnostic test for Huntington's disease, people at risk for getting the disease will be able to learn whether or not they will in fact develop the disease. The ability to predict the inevitable onset of this progressive, degenerative disease raises ethical questions about counseling, screening, and disclosure of risk status to patients and family members.

  17. Identifying potential cancer driver genes by genomic data integration

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  18. Identifying potential cancer driver genes by genomic data integration

    PubMed Central

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

    2013-01-01

    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

  19. Expression profiling identifies genes involved in emphysema severity.

    PubMed

    Francis, Santiyagu M Savarimuthu; Larsen, Jill E; Pavey, Sandra J; Bowman, Rayleen V; Hayward, Nicholas K; Fong, Kwun M; Yang, Ian A

    2009-01-01

    Chronic obstructive pulmonary disease (COPD) is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients.Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR) if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples.Class comparison identified 98 differentially expressed genes (p < 0.01). Fifty-one of those genes had been previously evaluated in differentiation between normal and severe emphysema lung. qRT-PCR confirmed the direction of change in expression in 29 of the 51 genes and 11 of those validated, remaining significant at p < 0.05. Biological replication in an independent cohort confirmed the altered expression of eight genes, with seven genes differentially expressed by greater than 1.3 fold, identifying these as candidate determinants of emphysema severity.Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3. PMID:19723343

  20. Expression profiling identifies genes involved in emphysema severity

    PubMed Central

    2009-01-01

    Chronic obstructive pulmonary disease (COPD) is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR) if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p < 0.01). Fifty-one of those genes had been previously evaluated in differentiation between normal and severe emphysema lung. qRT-PCR confirmed the direction of change in expression in 29 of the 51 genes and 11 of those validated, remaining significant at p < 0.05. Biological replication in an independent cohort confirmed the altered expression of eight genes, with seven genes differentially expressed by greater than 1.3 fold, identifying these as candidate determinants of emphysema severity. Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3. PMID:19723343

  1. Study Identifies Genetic Subtypes of Crohn's Disease

    MedlinePlus

    ... medlineplus.gov/news/fullstory_161499.html Study Identifies Genetic Subtypes of Crohn's Disease Findings may help explain ... disease appears to have at least two distinct genetic subtypes, which could explain why the condition is ...

  2. Researchers Identify Genes Linked to Hot Flashes

    MedlinePlus

    ... fullstory_161579.html Researchers Identify Genes Linked to Hot Flashes Mutations found in women of all races, ... Some women may be genetically predisposed to suffer hot flashes before or during menopause, a new study ...

  3. 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

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

    2013-01-01

    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. PMID:23740999

  4. High-resolution melting (HRM) of the cytochrome B gene: a powerful approach to identify blood-meal sources in Chagas disease Vectors.

    PubMed

    Peña, Victor H; Fernández, Geysson J; Gómez-Palacio, Andrés M; Mejía-Jaramillo, Ana M; Cantillo, Omar; Triana-Chávez, Omar

    2012-01-01

    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.

  5. Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytren’s Disease

    PubMed Central

    Becker, Kerstin; Siegert, Sabine; Toliat, Mohammad Reza; Du, Juanjiangmeng; Casper, Ramona; Dolmans, Guido H.; Werker, Paul M.; Tinschert, Sigrid; Franke, Andre; Gieger, Christian; Strauch, Konstantin; Nothnagel, Michael; Nürnberg, Peter; Hennies, Hans Christian

    2016-01-01

    Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value < 5x10-8). In addition, we identified 14 new suggestive loci (p-value < 10−5). Intriguingly, several of these new loci contain genes associated with Wnt signalling and therefore represent excellent candidates for replication. Next, we compared whole-transcriptome data between patient- and control-derived tissue samples and found the Wnt/β-catenin pathway to be the top deregulated pathway in patient samples. We then conducted network and pathway analyses in order to identify protein networks that are enriched for genes highlighted in the GWAS meta-analysis and expression data sets. We found further evidence that the Wnt signalling pathways in conjunction with other pathways may play a critical role in Dupuytren´s disease. PMID:27467239

  6. A survey of FLS2 genes from multiple citrus species identifies candidates for enhancing disease resistance to Xanthomonas citri ssp. citri.

    PubMed

    Shi, Qingchun; Febres, Vicente J; Jones, Jeffrey B; Moore, Gloria A

    2016-01-01

    Pathogen-associated molecular patterns (PAMPs)-triggered immunity (PTI) is an important component of plant innate immunity. In a previous study, we showed that the PAMP flg22 from Xanthomonas citri ssp. citri (Xflg22), the causal agent of citrus canker, induced PTI in citrus, which correlated with the observed levels of canker resistance. Here, we identified and sequenced two bacterial flagellin/flg22 receptors (FLS2-1 and FLS2-2) from 'Duncan' grapefruit (Citrus paradisi, CpFLS2-1 and CpFLS2-2) and 'Sun Chu Sha' mandarin (C. reticulata, CrFLS2-1 and CrFLS2-2). We were able to isolate only one FLS2 from 'Nagami' kumquat (Fortunella margarita, FmFLS2-1) and gene flanking sequences suggest a rearrangement event that resulted in the deletion of FLS2-2 from the genome. Phylogenetic analysis, gene structure and presence of critical amino acid domains all indicate we identified the true FLS2 genes in citrus. FLS2-2 was more transcriptionally responsive to Xflg22 than FLS2-1, with induced expression levels higher in canker-resistant citrus than in susceptible ones. Interestingly, 'Nagami' kumquat showed the highest FLS2-1 steady-state expression levels, although it was not induced by Xflg22. We selected FmFLS2-1, CrFLS2-2 and CpFLS2-2 to further evaluate their capacity to enhance bacterial resistance using Agrobacterium-mediated transient expression assays. Both FmFLS2-1 and CrFLS2-2, the two proteins from canker-resistant species, conferred stronger Xflg22 responses and reduced canker symptoms in leaves of the susceptible grapefruit genotype. These two citrus genes will be useful resources to enhance PTI and achieve resistance against canker and possibly other bacterial pathogens in susceptible citrus types. PMID:27222722

  7. From SNPs to Genes: Disease Association at the Gene Level

    PubMed Central

    Lehne, Benjamin; Lewis, Cathryn M.; Schlitt, Thomas

    2011-01-01

    Interpreting Genome-Wide Association Studies (GWAS) at a gene level is an important step towards understanding the molecular processes that lead to disease. In order to incorporate prior biological knowledge such as pathways and protein interactions in the analysis of GWAS data it is necessary to derive one measure of association for each gene. We compare three different methods to obtain gene-wide test statistics from Single Nucleotide Polymorphism (SNP) based association data: choosing the test statistic from the most significant SNP; the mean test statistics of all SNPs; and the mean of the top quartile of all test statistics. We demonstrate that the gene-wide test statistics can be controlled for the number of SNPs within each gene and show that all three methods perform considerably better than expected by chance at identifying genes with confirmed associations. By applying each method to GWAS data for Crohn's Disease and Type 1 Diabetes we identified new potential disease genes. PMID:21738570

  8. Gene mutations in Cushing's disease

    PubMed Central

    Xiong, Qi; Ge, Wei

    2016-01-01

    Cushing's disease (CD) is a severe (and potentially fatal) disease caused by adrenocorticotropic hormone (ACTH)-secreting adenomas of the pituitary gland (often termed pituitary adenomas). The majority of ACTH-secreting corticotroph tumors are sporadic and CD rarely appears as a familial disorder, thus, the genetic mechanisms underlying CD are poorly understood. Studies have reported that various mutated genes are associated with CD, such as those in menin 1, aryl hydrocarbon receptor-interacting protein and the nuclear receptor subfamily 3 group C member 1. Recently it was identified that ubiquitin-specific protease 8 mutations contribute to CD, which was significant towards elucidating the genetic mechanisms of CD. The present study reviews the associated gene mutations in CD patients. PMID:27588171

  9. Pyrosequencing-based profiling of archaeal and bacterial 16S rRNA genes identifies a novel archaeon associated with black band disease in corals.

    PubMed

    Sato, Yui; Willis, Bette L; Bourne, David G

    2013-11-01

    Black band disease (BBD) is a microbial consortium that creates anoxic, sulfide-rich microenvironments and kills underlying coral tissues as it rapidly migrates across colonies. Although bacterial communities associated with BBD have been studied extensively, the presence and roles of archaea are unexplored. Using amplicon-pyrosequencing of 16S ribosomal RNA genes, we investigated the community structure of both archaea and bacteria within microbial lesions of BBD and the less-virulent precursor stage, 'cyanobacterial patches' (CP), affecting the coral Montipora hispida. We detected characteristic shifts in microbial communities during the development of BBD from CP, reflecting microenvironmental changes within lesions. Archaeal profiles in CP suggested a diverse assemblage affiliated with the Thaumarchaeota and Euryarchaeota, similar to communities described for oxic marine environments. In contrast, a novel ribotype, distantly affiliated to the Euryarchaeota, dominated up to 94% of archaeal sequences retrieved from BBD. The physiological characteristics of this dominant archaeal ribotype are unknown because of the novelty of its 16S ribosomal RNA gene sequences; however, their prominent associations with BBD lesions suggest the ability to thrive in the organic- and sulfide-rich anoxic microenvironment characteristic of BBD lesions. Discovery of this novel archaeal ribotype provides new insights into the microbial ecology and aetiology of BBD. PMID:24112537

  10. Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes.

    PubMed

    Edmunds, Richard C; Su, Baofeng; Balhoff, James P; Eames, B Frank; Dahdul, Wasila M; Lapp, Hilmar; Lundberg, John G; Vision, Todd J; Dunham, Rex A; Mabee, Paula M; Westerfield, Monte

    2016-01-01

    Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

  11. Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

    PubMed Central

    Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

    2016-01-01

    Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

  12. A survey of FLS2 genes from multiple citrus species identifies candidates for enhancing disease resistance to Xanthomonas citri ssp. citri.

    PubMed Central

    Shi, Qingchun; Febres, Vicente J; Jones, Jeffrey B; Moore, Gloria A

    2016-01-01

    Pathogen-associated molecular patterns (PAMPs)-triggered immunity (PTI) is an important component of plant innate immunity. In a previous study, we showed that the PAMP flg22 from Xanthomonas citri ssp. citri (Xflg22), the causal agent of citrus canker, induced PTI in citrus, which correlated with the observed levels of canker resistance. Here, we identified and sequenced two bacterial flagellin/flg22 receptors (FLS2-1 and FLS2-2) from ‘Duncan’ grapefruit (Citrus paradisi, CpFLS2-1 and CpFLS2-2) and ‘Sun Chu Sha’ mandarin (C. reticulata, CrFLS2-1 and CrFLS2-2). We were able to isolate only one FLS2 from ‘Nagami’ kumquat (Fortunella margarita, FmFLS2-1) and gene flanking sequences suggest a rearrangement event that resulted in the deletion of FLS2-2 from the genome. Phylogenetic analysis, gene structure and presence of critical amino acid domains all indicate we identified the true FLS2 genes in citrus. FLS2-2 was more transcriptionally responsive to Xflg22 than FLS2-1, with induced expression levels higher in canker-resistant citrus than in susceptible ones. Interestingly, ‘Nagami’ kumquat showed the highest FLS2-1 steady-state expression levels, although it was not induced by Xflg22. We selected FmFLS2-1, CrFLS2-2 and CpFLS2-2 to further evaluate their capacity to enhance bacterial resistance using Agrobacterium-mediated transient expression assays. Both FmFLS2-1 and CrFLS2-2, the two proteins from canker-resistant species, conferred stronger Xflg22 responses and reduced canker symptoms in leaves of the susceptible grapefruit genotype. These two citrus genes will be useful resources to enhance PTI and achieve resistance against canker and possibly other bacterial pathogens in susceptible citrus types. PMID:27222722

  13. Analysis of gene expression profile identifies potential biomarkers for atherosclerosis.

    PubMed

    Liu, Luran; Liu, Yan; Liu, Chang; Zhang, Zhuobo; Du, Yaojun; Zhao, Hao

    2016-10-01

    The present study aimed to identify potential biomarkers for atherosclerosis via analysis of gene expression profiles. The microarray dataset no. GSE20129 was downloaded from the Gene Expression Omnibus database. A total of 118 samples from the peripheral blood of female patients was used, including 47 atherosclerotic and 71 non‑atherosclerotic patients. The differentially expressed genes (DEGs) in the atherosclerosis samples were identified using the Limma package. Gene ontology term and Kyoto Encyclopedia of Genes and Genomes pathway analyses for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. The recursive feature elimination (RFE) algorithm was applied for feature selection via iterative classification, and support vector machine classifier was used for the validation of prediction accuracy. A total of 430 DEGs in the atherosclerosis samples were identified, including 149 up‑ and 281 downregulated genes. Subsequently, the RFE algorithm was used to identify 11 biomarkers, whose receiver operating characteristic curves had an area under curve of 0.92, indicating that the identified 11 biomarkers were representative. The present study indicated that APH1B, JAM3, FBLN2, CSAD and PSTPIP2 may have important roles in the progression of atherosclerosis in females and may be potential biomarkers for early diagnosis and prognosis as well as treatment targets for this disease. PMID:27573188

  14. Analysis of gene expression profile identifies potential biomarkers for atherosclerosis

    PubMed Central

    Liu, Luran; Liu, Yan; Liu, Chang; Zhang, Zhuobo; Du, Yaojun; Zhao, Hao

    2016-01-01

    The present study aimed to identify potential biomarkers for atherosclerosis via analysis of gene expression profiles. The microarray dataset no. GSE20129 was downloaded from the Gene Expression Omnibus database. A total of 118 samples from the peripheral blood of female patients was used, including 47 atherosclerotic and 71 non-atherosclerotic patients. The differentially expressed genes (DEGs) in the atherosclerosis samples were identified using the Limma package. Gene ontology term and Kyoto Encyclopedia of Genes and Genomes pathway analyses for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. The recursive feature elimination (RFE) algorithm was applied for feature selection via iterative classification, and support vector machine classifier was used for the validation of prediction accuracy. A total of 430 DEGs in the atherosclerosis samples were identified, including 149 up- and 281 downregulated genes. Subsequently, the RFE algorithm was used to identify 11 biomarkers, whose receiver operating characteristic curves had an area under curve of 0.92, indicating that the identified 11 biomarkers were representative. The present study indicated that APH1B, JAM3, FBLN2, CSAD and PSTPIP2 may have important roles in the progression of atherosclerosis in females and may be potential biomarkers for early diagnosis and prognosis as well as treatment targets for this disease. PMID:27573188

  15. Genotype analysis identifies the cause of the "royal disease".

    PubMed

    Rogaev, Evgeny I; Grigorenko, Anastasia P; Faskhutdinova, Gulnaz; Kittler, Ellen L W; Moliaka, Yuri K

    2009-11-01

    The "royal disease," a blood disorder transmitted from Queen Victoria to European royal families, is a striking example of X-linked recessive inheritance. Although the disease is widely recognized to be a form of the blood clotting disorder hemophilia, its molecular basis has never been identified, and the royal disease is now likely extinct. We identified the likely disease-causing mutation by applying genomic methodologies (multiplex target amplification and massively parallel sequencing) to historical specimens from the Romanov branch of the royal family. The mutation occurs in F9, a gene on the X chromosome that encodes blood coagulation factor IX, and is predicted to alter RNA splicing and to lead to production of a truncated form of factor IX. Thus, the royal disease is the severe form of hemophilia, also known as hemophilia B or Christmas disease.

  16. Chapter 15: Disease Gene Prioritization

    PubMed Central

    Bromberg, Yana

    2013-01-01

    Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases. PMID:23633938

  17. Network Topology Reveals Key Cardiovascular Disease Genes

    PubMed Central

    Stojković, Neda; Radak, Djordje; Pržulj, Nataša

    2013-01-01

    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

  18. Network motif-based method for identifying coronary artery disease

    PubMed Central

    LI, YIN; CONG, YAN; ZHAO, YUN

    2016-01-01

    The present study aimed to develop a more efficient method for identifying coronary artery disease (CAD) than the conventional method using individual differentially expressed genes (DEGs). GSE42148 gene microarray data were downloaded, preprocessed and screened for DEGs. Additionally, based on transcriptional regulation data obtained from ENCODE database and protein-protein interaction data from the HPRD, the common genes were downloaded and compared with genes annotated from gene microarrays to screen additional common genes in order to construct an integrated regulation network. FANMOD was then used to detect significant three-gene network motifs. Subsequently, GlobalAncova was used to screen differential three-gene network motifs between the CAD group and the normal control data from GSE42148. Genes involved in the differential network motifs were then subjected to functional annotation and pathway enrichment analysis. Finally, clustering analysis of the CAD and control samples was performed based on individual DEGs and the top 20 network motifs identified. In total, 9,008 significant three-node network motifs were detected from the integrated regulation network; these were categorized into 22 interaction modes, each containing a minimum of one transcription factor. Subsequently, 1,132 differential network motifs involving 697 genes were screened between the CAD and control group. The 697 genes were enriched in 154 gene ontology terms, including 119 biological processes, and 14 KEGG pathways. Identifying patients with CAD based on the top 20 network motifs provided increased accuracy compared with the conventional method based on individual DEGs. The results of the present study indicate that the network motif-based method is more efficient and accurate for identifying CAD patients than the conventional method based on individual DEGs. PMID:27347046

  19. Integrative Genomics Identifies Gene Signature Associated with Melanoma Ulceration

    PubMed Central

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

    2013-01-01

    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

  20. Computational approaches for human disease gene prediction and ranking.

    PubMed

    Zhu, Cheng; Wu, Chao; Aronow, Bruce J; Jegga, Anil G

    2014-01-01

    While candidate gene association studies continue to be the most practical and frequently employed approach in disease gene investigation for complex disorders, selecting suitable genes to test is a challenge. There are several computational approaches available for selecting and prioritizing disease candidate genes. A majority of these tools are based on guilt-by-association principle where novel disease candidate genes are identified and prioritized based on either functional or topological similarity to known disease genes. In this chapter we review the prioritization criteria and the algorithms along with some use cases that demonstrate how these tools can be used for identifying and ranking human disease candidate genes.

  1. Functional Analysis of Avr9/Cf-9 Rapidly Elicited Genes Identifies a Protein Kinase, ACIK1, That Is Essential for Full Cf-9–Dependent Disease Resistance in TomatoW⃞

    PubMed Central

    Rowland, Owen; Ludwig, Andrea A.; Merrick, Catherine J.; Baillieul, Fabienne; Tracy, Frances E.; Durrant, Wendy E.; Fritz-Laylin, Lillian; Nekrasov, Vladimir; Sjölander, Kimmen; Yoshioka, Hirofumi; Jones, Jonathan D.G.

    2005-01-01

    Tomato (Lycopersicon esculentum) Cf genes confer resistance to the fungal pathogen Cladosporium fulvum through recognition of secreted avirulence (Avr) peptides. Plant defense responses, including rapid alterations in gene expression, are immediately activated upon perception of the pathogen. Previously, we identified a collection of Avr9/Cf-9 rapidly (15 to 30 min) elicited (ACRE) genes from tobacco (Nicotiana tabacum). Many of the ACRE genes encode putative signaling components and thus may play pivotal roles in the initial development of the defense response. To assess the requirement of 42 of these genes in the hypersensitive response (HR) induced by Cf-9/Avr9 or by Cf-4/Avr4, we used virus-induced gene silencing (VIGS) in N. benthamiana. Three genes were identified that when silenced compromised the Cf-mediated HR. We further characterized one of these genes, which encodes a Ser/Thr protein kinase called Avr9/Cf-9 induced kinase 1 (ACIK1). ACIK1 mRNA was rapidly upregulated in tobacco and tomato upon elicitation by Avr9 and by wounding. Silencing of ACIK1 in tobacco resulted in a reduced HR that correlated with loss of ACIK1 transcript. Importantly, ACIK1 was found to be required for Cf-9/Avr9- and Cf-4/Avr4-mediated HRs but not for the HR or resistance mediated by other resistance/Avr systems, such as Pto/AvrPto, Rx/Potato virus X, or N/Tobacco mosaic virus. Moreover, VIGS of LeACIK1 in tomato decreased Cf-9–mediated resistance to C. fulvum, showing the importance of ACIK1 in disease resistance. PMID:15598806

  2. Advances in identifying beryllium sensitization and disease.

    PubMed

    Middleton, Dan; Kowalski, Peter

    2010-01-01

    Beryllium is a lightweight metal with unique qualities related to stiffness, corrosion resistance, and conductivity. While there are many useful applications, researchers in the 1930s and 1940s linked beryllium exposure to a progressive occupational lung disease. Acute beryllium disease is a pulmonary irritant response to high exposure levels, whereas chronic beryllium disease (CBD) typically results from a hypersensitivity response to lower exposure levels. A blood test, the beryllium lymphocyte proliferation test (BeLPT), was an important advance in identifying individuals who are sensitized to beryllium (BeS) and thus at risk for developing CBD. While there is no true "gold standard" for BeS, basic epidemiologic concepts have been used to advance our understanding of the different screening algorithms.

  3. Advances in Identifying Beryllium Sensitization and Disease

    PubMed Central

    Middleton, Dan; Kowalski, Peter

    2010-01-01

    Beryllium is a lightweight metal with unique qualities related to stiffness, corrosion resistance, and conductivity. While there are many useful applications, researchers in the 1930s and l940s linked beryllium exposure to a progressive occupational lung disease. Acute beryllium disease is a pulmonary irritant response to high exposure levels, whereas chronic beryllium disease (CBD) typically results from a hypersensitivity response to lower exposure levels. A blood test, the beryllium lymphocyte proliferation test (BeLPT), was an important advance in identifying individuals who are sensitized to beryllium (BeS) and thus at risk for developing CBD. While there is no true “gold standard” for BeS, basic epidemiologic concepts have been used to advance our understanding of the different screening algorithms. PMID:20195436

  4. Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer’s Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease

    PubMed Central

    Chandrasekaran, Sreedevi; Bonchev, Danail

    2016-01-01

    Network-based approaches are powerful and beneficial tools to study complex systems in their entirety, elucidating the essential factors that turn the multitude of individual elements into a functional system. In this study we used critical network topology descriptors and guilt-by-association rule to explore and understand the significant molecular players, drug targets and underlying biological mechanisms of Alzheimer’s disease. Analyzing two post-mortem brain gene microarrays (GSE4757 and GSE28146) with Pathway Studio software package we constructed and analyzed a set of protein-protein interaction, as well as miRNA-target networks. In a 4-step procedure the expression datasets were normalized using Robust Multi-array Average approach, while the modulation of gene expression by the disease was statistically evaluated by the empirical Bayes method from the limma Bioconductor package. Representative set of 214 seed-genes (p<0.01) common for the three brain sections of the two microarrays was thus created. The Pathway Studio analysis of the networks built identified 15 new potential AD-related genes and 17 novel AD-involved microRNAs. Using KEGG pathways relevant in Alzheimer’s disease we built an integrated mechanistic network from the interactions between the overlapping genes in these pathways. Routes of possible disease initiation process were thus revealed through the CD4, DCN, and IL8 extracellular ligands. DAVID and IPA enrichment analysis uncovered a number of deregulated biological processes and pathways including neuron projection/differentiation, aging, oxidative stress, chemokine/ neurotrophin signaling, long-term potentiation and others. The findings in this study offer information of interest for subsequent experimental studies. PMID:26784894

  5. Integrated analyses of genome-wide DNA occupancy and expression profiling identify key genes and pathways involved in cellular transformation by the Marek's disease virus oncoprotein Meq

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek’s disease (MD) is an economically significant disease in chickens 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 largely attributed for viral o...

  6. Gene therapy for CNS diseases - Krabbe disease.

    PubMed

    Rafi, Mohammad A

    2016-01-01

    This is a brief report of the 19th Annual Meeting of the American Society of Gene and Cell Therapy that took place from May 4th through May 7th, 2016 in Washington, DC, USA. While the meeting provided many symposiums, lectures, and scientific sessions this report mainly focuses on one of the sessions on the "Gene Therapy for central nervous system (CNS) Diseases" and specifically on the "Gene Therapy for the globoid cell leukodystrophy or Krabbe disease. Two presentations focused on this subject utilizing two animal models of this disease: mice and dog models. Different serotypes of adeno-associate viral vectors (AAV) alone or in combination with bone marrow transplantations were used in these research projects. The Meeting of the ASGCT reflected continuous growth in the fields of gene and cell therapy and brighter forecast for efficient treatment options for variety of human diseases. PMID:27525222

  7. 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

    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

    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-γ 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-γ 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-γ 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

  8. A penalized robust method for identifying gene-environment interactions.

    PubMed

    Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

    2014-04-01

    In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model misspecification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example, with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications.

  9. Differences in Pathogenesis for Salmonella enterica serovar Typhimurium in the Mouse Versus the Swine Model Identify Bacterial Gene Products Required for Systemic but not Gastrointestinal Disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the last several decades, the mouse model of Typhoid fever has been an extremely productive model to investigate Salmonella enterica serovar Typhimurium pathogenesis. The mouse is the paradigm for investigating systemic disease due to infection by Salmonella; however, the swine model of gastro...

  10. Mining biological databases for candidate disease genes

    NASA Astrophysics Data System (ADS)

    Braun, Terry A.; Scheetz, Todd; Webster, Gregg L.; Casavant, Thomas L.

    2001-07-01

    The publicly-funded effort to sequence the complete nucleotide sequence of the human genome, the Human Genome Project (HGP), has currently produced more than 93% of the 3 billion nucleotides of the human genome into a preliminary `draft' format. In addition, several valuable sources of information have been developed as direct and indirect results of the HGP. These include the sequencing of model organisms (rat, mouse, fly, and others), gene discovery projects (ESTs and full-length), and new technologies such as expression analysis and resources (micro-arrays or gene chips). These resources are invaluable for the researchers identifying the functional genes of the genome that transcribe and translate into the transcriptome and proteome, both of which potentially contain orders of magnitude more complexity than the genome itself. Preliminary analyses of this data identified approximately 30,000 - 40,000 human `genes.' However, the bulk of the effort still remains -- to identify the functional and structural elements contained within the transcriptome and proteome, and to associate function in the transcriptome and proteome to genes. A fortuitous consequence of the HGP is the existence of hundreds of databases containing biological information that may contain relevant data pertaining to the identification of disease-causing genes. The task of mining these databases for information on candidate genes is a commercial application of enormous potential. We are developing a system to acquire and mine data from specific databases to aid our efforts to identify disease genes. A high speed cluster of Linux of workstations is used to analyze sequence and perform distributed sequence alignments as part of our data mining and processing. This system has been used to mine GeneMap99 sequences within specific genomic intervals to identify potential candidate disease genes associated with Bardet-Biedle Syndrome (BBS).

  11. Gene Therapy for Retinal Diseases

    PubMed Central

    Samiy, Nasrollah

    2014-01-01

    Gene therapy has a growing research potential particularly in the field of ophthalmic and retinal diseases owing to three main characteristics of the eye; accessibility in terms of injections and surgical interventions, its immune-privileged status facilitating the accommodation to the antigenicity of a viral vector, and tight blood-ocular barriers which save other organs from unwanted contamination. Gene therapy has tremendous potential for different ocular diseases. In fact, the perspective of gene therapy in the field of eye research does not confine to exclusive monogenic ophthalmic problems and it has the potential to include gene based pharmacotherapies for non-monogenic problems such as age related macular disease and diabetic retinopathy. The present article has focused on how gene transfer into the eye has been developed and used to treat retinal disorders with no available therapy at present. PMID:25709778

  12. Gene therapy for lung disease.

    PubMed

    Ennist, D L

    1999-06-01

    Gene therapy is a new field of medical research that has great potential to influence the course of treatment of human disease. The lung has been a particularly attractive target organ for gene therapy due to its accessibility and the identification of genetic deficits for a number of lung diseases. Several clinical trials have shown evidence of low levels of gene transfer and expression, but without any benefit to the patients involved. Thus, current studies are focusing on further research and technological improvements to the vectors. Gene therapy is now beginning to benefit from a shift in emphasis from clinical trials to the development of better tools and procedures to deliver gene therapy to the bedside.

  13. Comparison of melanoblast expression patterns identifies distinct classes of genes

    PubMed Central

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

    2010-01-01

    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. PMID:19493314

  14. Identifying driver genes in cancer by triangulating gene expression, gene location, and survival data.

    PubMed

    Rouam, Sigrid; Miller, Lance D; Karuturi, R Krishna Murthy

    2014-01-01

    Driver genes are directly responsible for oncogenesis and identifying them is essential in order to fully understand the mechanisms of cancer. However, it is difficult to delineate them from the larger pool of genes that are deregulated in cancer (ie, passenger genes). In order to address this problem, we developed an approach called TRIAngulating Gene Expression (TRIAGE through clinico-genomic intersects). Here, we present a refinement of this approach incorporating a new scoring methodology to identify putative driver genes that are deregulated in cancer. TRIAGE triangulates - or integrates - three levels of information: gene expression, gene location, and patient survival. First, TRIAGE identifies regions of deregulated expression (ie, expression footprints) by deriving a newly established measure called the Local Singular Value Decomposition (LSVD) score for each locus. Driver genes are then distinguished from passenger genes using dual survival analyses. Incorporating measurements of gene expression and weighting them according to the LSVD weight of each tumor, these analyses are performed using the genes located in significant expression footprints. Here, we first use simulated data to characterize the newly established LSVD score. We then present the results of our application of this refined version of TRIAGE to gene expression data from five cancer types. This refined version of TRIAGE not only allowed us to identify known prominent driver genes, such as MMP1, IL8, and COL1A2, but it also led us to identify several novel ones. These results illustrate that TRIAGE complements existing tools, allows for the identification of genes that drive cancer and could perhaps elucidate potential future targets of novel anticancer therapeutics.

  15. Disease Resistance Gene Analogs (RGAs) in Plants

    PubMed Central

    Sekhwal, Manoj Kumar; Li, Pingchuan; Lam, Irene; Wang, Xiue; Cloutier, Sylvie; You, Frank M.

    2015-01-01

    Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens’ resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed. PMID:26287177

  16. Disease Resistance Gene Analogs (RGAs) in Plants.

    PubMed

    Sekhwal, Manoj Kumar; Li, Pingchuan; Lam, Irene; Wang, Xiue; Cloutier, Sylvie; You, Frank M

    2015-01-01

    Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens' resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

  17. Patching genes to fight disease

    SciTech Connect

    Holzman, D.

    1990-09-03

    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.

  18. Disease gene prioritization using network and feature.

    PubMed

    Xie, Bingqing; Agam, Gady; Balasubramanian, Sandhya; Xu, Jinbo; Gilliam, T Conrad; Maltsev, Natalia; Börnigen, Daniela

    2015-04-01

    Identifying high-confidence candidate genes that are causative for disease phenotypes, from the large lists of variations produced by high-throughput genomics, can be both time-consuming and costly. The development of novel computational approaches, utilizing existing biological knowledge for the prioritization of such candidate genes, can improve the efficiency and accuracy of the biomedical data analysis. It can also reduce the cost of such studies by avoiding experimental validations of irrelevant candidates. In this study, we address this challenge by proposing a novel gene prioritization approach that ranks promising candidate genes that are likely to be involved in a disease or phenotype under study. This algorithm is based on the modified conditional random field (CRF) model that simultaneously makes use of both gene annotations and gene interactions, while preserving their original representation. We validated our approach on two independent disease benchmark studies by ranking candidate genes using network and feature information. Our results showed both high area under the curve (AUC) value (0.86), and more importantly high partial AUC (pAUC) value (0.1296), and revealed higher accuracy and precision at the top predictions as compared with other well-performed gene prioritization tools, such as Endeavour (AUC-0.82, pAUC-0.083) and PINTA (AUC-0.76, pAUC-0.066). We were able to detect more target genes (9/18/19/27) on top positions (1/5/10/20) compared to Endeavour (3/11/14/23) and PINTA (6/10/13/18). To demonstrate its usability, we applied our method to a case study for the prediction of molecular mechanisms contributing to intellectual disability and autism. Our approach was able to correctly recover genes related to both disorders and provide suggestions for possible additional candidates based on their rankings and functional annotations. PMID:25844670

  19. Feline polycystic kidney disease mutation identified in PKD1.

    PubMed

    Lyons, Leslie A; Biller, David S; Erdman, Carolyn A; Lipinski, Monika J; Young, Amy E; Roe, Bruce A; Qin, Baifang; Grahn, Robert A

    2004-10-01

    Autosomal dominant polycystic kidney disease (ADPKD) is a commonly inherited disorder in humans that causes the formation of fluid-filled renal cysts, often leading to renal failure. PKD1 mutations cause 85% of ADPKD. Feline PKD is autosomal dominant and has clinical presentations similar to humans. PKD affects approximately 38% of Persian cats worldwide, which is approximately 6% of cats, making it the most prominent inherited feline disease. Previous analyses have shown significant linkage between the PKD phenotype and microsatellite markers linked to the feline homolog for PKD1. In this report, the feline PKD1 gene was scanned for causative mutations and a C>A transversion was identified at c.10063 (human ref NM_000296) in exon 29, resulting in a stop mutation at position 3284, which suggests a loss of approximately 25% of the C-terminus of the protein. The same mutation has not been identified in humans, although similar regions of the protein are truncated. The C>A transversion has been identified in the heterozygous state in 48 affected cats examined, including 41 Persians, a Siamese, and several other breeds that have been known to outcross with Persians. In addition, the mutation is segregating concordantly in all available PKD families. No unaffected cats have been identified with the mutation. No homozygous cats have been identified, supporting the suggestion that the mutation is embryonic lethal. These data suggest that the stop mutation causes feline PKD, providing a test to identify cats that will develop PKD and demonstrating that the domestic cat is an ideal model for human PKD. PMID:15466259

  20. YGA: identifying distinct biological features between yeast gene sets.

    PubMed

    Chang, Darby Tien-Hao; Li, Wen-Si; Bai, Yi-Han; Wu, Wei-Sheng

    2013-04-10

    The advance of high-throughput experimental technologies generates many gene sets with different biological meanings, where many important insights can only be extracted by identifying the biological (regulatory/functional) features that are distinct between different gene sets (e.g. essential vs. non-essential genes, TATA box-containing vs. TATA box-less genes, induced vs. repressed genes under certain biological conditions). Although many servers have been developed to identify enriched features in a gene set, most of them were designed to analyze one gene set at a time but cannot compare two gene sets. Moreover, the features used in existing servers were mainly focused on functional annotations (GO terms), pathways, transcription factor binding sites (TFBSs) and/or protein-protein interactions (PPIs). In yeast, various important regulatory features, including promoter bendability, nucleosome occupancy, 5'-UTR length, and TF-gene regulation evidence, are available but have not been used in any enrichment analysis servers. This motivates us to develop the Yeast Genes Analyzer (YGA), a web server that simultaneously analyzes various biological (regulatory/functional) features of two gene sets and performs statistical tests to identify the distinct features between them. Many well-studied gene sets such as essential, stress-response, TATA box-containing and cell cycle genes were pre-compiled in YGA for users, if they have only one gene set, to compare with. In comparison with the existing enrichment analysis servers, YGA tests more comprehensive regulatory features (e.g. promoter bendability, nucleosome occupancy, 5'-UTR length, experimental evidence of TF-gene binding and TF-gene regulation) and functional features (e.g. PPI, GO terms, pathways and functional groups of genes, including essential/non-essential genes, stress-induced/-repressed genes, TATA box-containing/-less genes, occupied/depleted proximal-nucleosome genes and cell cycle genes). Furthermore, YGA

  1. BLAT2DOLite: An Online System for Identifying Significant Relationships between Genetic Sequences and Diseases.

    PubMed

    Cheng, Liang; Zhang, Shuo; Hu, Yang

    2016-01-01

    The significantly related diseases of sequences could play an important role in understanding the functions of these sequences. In this paper, we introduced BLAT2DOLite, an online system for annotating human genes and diseases and identifying the significant relationships between sequences and diseases. Currently, BLAT2DOLite integrates Entrez Gene database and Disease Ontology Lite (DOLite), which contain loci of gene and relationships between genes and diseases. It utilizes hypergeometric test to calculate P-values between genes and diseases of DOLite. The system can be accessed from: http://123.59.132.21:8080/BLAT2DOLite. The corresponding web service is described in: http://123.59.132.21:8080/BLAT2DOLite/BLAT2DOLiteIDMappingPort?wsdl. PMID:27315278

  2. BLAT2DOLite: An Online System for Identifying Significant Relationships between Genetic Sequences and Diseases

    PubMed Central

    Cheng, Liang; Zhang, Shuo; Hu, Yang

    2016-01-01

    The significantly related diseases of sequences could play an important role in understanding the functions of these sequences. In this paper, we introduced BLAT2DOLite, an online system for annotating human genes and diseases and identifying the significant relationships between sequences and diseases. Currently, BLAT2DOLite integrates Entrez Gene database and Disease Ontology Lite (DOLite), which contain loci of gene and relationships between genes and diseases. It utilizes hypergeometric test to calculate P-values between genes and diseases of DOLite. The system can be accessed from: http://123.59.132.21:8080/BLAT2DOLite. The corresponding web service is described in: http://123.59.132.21:8080/BLAT2DOLite/BLAT2DOLiteIDMappingPort?wsdl. PMID:27315278

  3. Blood Pressure Loci Identified with a Gene-Centric Array

    PubMed Central

    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, 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.

    2011-01-01

    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. PMID:22100073

  4. Genes and Disease: Prader-Willi Syndrome

    MedlinePlus

    ... Medicine, National Institutes of Health. National Center for Biotechnology Information (US). Genes and Disease [Internet]. Bethesda (MD): National Center for Biotechnology Information (US); 1998-. Genes and Disease [Internet]. Show ...

  5. Identifying gene expression modules that define human cell fates.

    PubMed

    Germanguz, I; Listgarten, J; Cinkornpumin, J; Solomon, A; Gaeta, X; Lowry, W E

    2016-05-01

    Using a compendium of cell-state-specific gene expression data, we identified genes that uniquely define cell states, including those thought to represent various developmental stages. Our analysis sheds light on human cell fate through the identification of core genes that are altered over several developmental milestones, and across regional specification. Here we present cell-type specific gene expression data for 17 distinct cell states and demonstrate that these modules of genes can in fact define cell fate. Lastly, we introduce a web-based database to disseminate the results.

  6. Rice transcriptome analysis to identify possible herbicide quinclorac detoxification genes

    PubMed Central

    Xu, Wenying; Di, Chao; Zhou, Shaoxia; Liu, Jia; Li, Li; Liu, Fengxia; Yang, Xinling; Ling, Yun; Su, Zhen

    2015-01-01

    Quinclorac is a highly selective auxin-type herbicide and is widely used in the effective control of barnyard grass in paddy rice fields, improving the world's rice yield. The herbicide mode of action of quinclorac has been proposed, and hormone interactions affecting quinclorac signaling has been identified. Because of widespread use, quinclorac may be transported outside rice fields with the drainage waters, leading to soil and water pollution and other environmental health problems. In this study, we used 57K Affymetrix rice whole-genome array to identify quinclorac signaling response genes to study the molecular mechanisms of action and detoxification of quinclorac in rice plants. Overall, 637 probe sets were identified with differential expression levels under either 6 or 24 h of quinclorac treatment. Auxin-related genes such as GH3 and OsIAAs responded to quinclorac treatment. Gene Ontology analysis showed that genes of detoxification-related family genes were significantly enriched, including cytochrome P450, GST, UGT, and ABC and drug transporter genes. Moreover, real-time RT-PCR analysis showed that top candidate genes of P450 families such as CYP81, CYP709C, and CYP72A were universally induced by different herbicides. Some Arabidopsis genes of the same P450 family were up-regulated under quinclorac treatment. We conducted rice whole-genome GeneChip analysis and the first global identification of quinclorac response genes. This work may provide potential markers for detoxification of quinclorac and biomonitors of environmental chemical pollution. PMID:26483837

  7. Identifying significant associations of orthologous simple sequence repeats with gene ontologies.

    PubMed

    Chen, Chien-Ming; Pai, Tun-Wen; Chuang, Chia-Sheng; Huang, Jhen-Li; Tzou, Wen-Shyong; Hu, Chin-Hua

    2014-01-01

    Simple Sequence Repeats (SSRs), also known as microsatellites, regulate gene functions. SSR mutations in a disease gene may cause various genetic disorders. To identify putative functional SSRs, a web-based system, Gene Ontology SSR Hierarchy (GOSH), was developed to facilitate discovery of significant associations between SSRs and Gene Ontology (GO) terms. Using the GO hierarchy term structure, GOSH assists users with selecting functional or biological gene subsets. Significant SSR patterns are retrieved and identified via comprehensive overrepresentation analysis within a target gene subset and by comparing results with orthologous genes. Pattern relationships between different biological subsets or supersets can be observed by using the GO hierarchy structure directly. GOSH also supports GO searching through identified significant SSR patterns and all GO terms possessing such patterns are listed for consultation. GOSH is the first comprehensive and efficient online mining tool for discovering significant orthologous SSR patterns in GO terms and is available at http://gosh.cs.ntou.edu.tw/.

  8. 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...

  9. Genes conserved for arbuscular mycorrhizal symbiosis identified through phylogenomics.

    PubMed

    Bravo, Armando; York, Thomas; Pumplin, Nathan; Mueller, Lukas A; Harrison, Maria J

    2016-01-01

    Arbuscular mycorrhizal symbiosis (AMS), a widespread mutualistic association of land plants and fungi(1), is predicted to have arisen once, early in the evolution of land plants(2-4). Consistent with this notion, several genes required for AMS have been conserved throughout evolution(5) and their symbiotic functions preserved, at least between monocot and dicot plants(6,7). Despite its significance, knowledge of the plants' genetic programme for AMS is limited. To date, most genes required for AMS have been found through commonalities with the evolutionarily younger nitrogen-fixing Rhizobium legume symbiosis (RLS)(8) or by reverse genetic analyses of differentially expressed candidate genes(9). Large sequence-indexed insertion mutant collections and recent genome editing technologies have vastly increased the power of reverse genetics but selection of candidate genes, from the thousands of genes that change expression during AMS, remains an arbitrary process. Here, we describe a phylogenomics approach to identify genes whose evolutionary history predicts conservation for AMS and we demonstrate the accuracy of the predictions through reverse genetics analysis. Phylogenomics analysis of 50 plant genomes resulted in 138 genes from Medicago truncatula predicted to function in AMS. This includes 15 genes with known roles in AMS. Additionally, we demonstrate that mutants in six previously uncharacterized AMS-conserved genes are all impaired in AMS. Our results demonstrate that phylogenomics is an effective strategy to identify a set of evolutionarily conserved genes required for AMS. PMID:27249190

  10. How to identify essential genes from molecular networks?

    PubMed Central

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

    2009-01-01

    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. PMID:19822021

  11. Evolutionary Signatures amongst Disease Genes Permit Novel Methods for Gene Prioritization and Construction of Informative Gene-Based Networks

    PubMed Central

    Priedigkeit, Nolan; Wolfe, Nicholas; Clark, Nathan L.

    2015-01-01

    Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC), is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting “disease map” network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks. PMID:25679399

  12. Gene therapy for peripheral nervous system diseases.

    PubMed

    Federici, Thais; Boulis, Nicholas

    2007-08-01

    Peripheral nerve diseases, also known as peripheral neuropathies, affect 15-20 million of Americans and diabetic neuropathy is the most common condition. Currently, the treatment of peripheral neuropathies is more focused on managing pain rather than providing permissive conditions for regeneration. Despite advances in microsurgical techniques, including nerve grafting and reanastomosis, axonal regeneration after peripheral nerve injury remains suboptimal. Also, no satisfactory treatments are available at this time for peripheral neurodegeneration occurring in motor neuron diseases (MND), including amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). Peripheral nerves have the inherent capacity of regeneration. Gene therapy strategies focused on neuroprotection may help optimizing axonal regrowth. A better understanding of the cellular and molecular events involved in axonal degeneration and regeneration have helped researchers to identify targets for intervention. This review summarizes the current state on the clinical experience as well as gene therapy strategies for peripheral neuropathies, including MND, peripheral nerve injury, neuropathic pain, and diabetic neuropathy.

  13. A Novel Prioritization Method in Identifying Recurrent Venous Thromboembolism-Related Genes

    PubMed Central

    Xie, Ruiqiang; Chen, Binbin; Huang, Hao; Li, Yiran; He, Yuehan; Lv, Junjie; He, Weiming; Chen, Lina

    2016-01-01

    Identifying the genes involved in venous thromboembolism (VTE) recurrence is important not only for understanding the pathogenesis but also for discovering the therapeutic targets. We proposed a novel prioritization method called Function-Interaction-Pearson (FIP) by creating gene-disease similarity scores to prioritize candidate genes underling VTE. The scores were calculated by integrating and optimizing three types of resources including gene expression, gene ontology and protein-protein interaction. As a result, 124 out of top 200 prioritized candidate genes had been confirmed in literature, among which there were 34 antithrombotic drug targets. Compared with two well-known gene prioritization tools Endeavour and ToppNet, FIP was shown to have better performance. The approach provides a valuable alternative for drug targets discovery and disease therapy. PMID:27050193

  14. A genomic approach to identify hybrid incompatibility genes

    PubMed Central

    Cooper, Jacob C.; Phadnis, Nitin

    2016-01-01

    ABSTRACT Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids. PMID:27230814

  15. Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

    DOE PAGES

    Xia, Jing; Rocke, David M.; Perry, George; Ray, Monika

    2014-01-01

    In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

  16. A novel approach for identifying causal models of complex diseases from family data.

    PubMed

    Park, Leeyoung; Kim, Ju H

    2015-04-01

    Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal-normal, normal-disease, and disease-disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene-environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene-environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases. PMID:25701286

  17. Renal disease: environment, race, or genes?

    PubMed

    Adler, Sharon

    2006-01-01

    Diabetic nephropathy is over-represented in people of color. This reflects both environmental and genetic factors. Numerous studies assess the effects of access to care and patient adherence in the development of kidney diseases. After correcting for these factors, genetic influences remain. Genetic approaches to discerning genes that predispose to diabetic nephropathy include candidate gene approaches, linkage analysis, mapping by admixture linkage disequilibrium, and transmission disequilibrium testing. Numerous candidate genes have been identified, although few have been confirmed apart from those representing genes in the renin-angiotensin system. The results of linkage analysis studies have similarly resulted in genomic regions purported to show linkage in a variety of ethnic groups that have most often not been confirmed in other ethnic groups, and sometimes in other groups of similar ethnicity but different phenotype definitions. The chromosomal regions determining glomerular filtration rate do not appear to be localized to the same chromosome as those related to proteinuria. Large cohorts of subjects have now been amassed by numerous research groups, and genome-wide scanning results involving much larger cohorts are anticipated to be published in the next few years. It is hoped that these strategies will ultimately identify chromosomsal regions and/ or genes that confer risk for diabetic nephropathy, and in so doing, provide clues to new therapies.

  18. The Wilson disease gene: Haplotypes and mutations

    SciTech Connect

    Thomas, G.R.; Roberts, E.A.; Cox, D.W.; Walshe, J.M.

    1994-09-01

    Wilson disease (WND) is an autosomal recessive defect of copper transport. The gene involved in WND, located on chromosome 13, has recently been shown to be a putative copper transporting P-type ATPase, designated ATP7B. The gene is highly similar to ATP7A, located on the X chromosome, which is defective in Menkes disease, another disorder of copper transport. We have available for study WND families from Canada (34 families), the United Kingdom (32 families), Japan (4 families), Iceland (3 families) and Hong Kong (2 families). We have utilized four highly polymorphic CA repeat markers (D13S296, D13S301, D13S314 and D13S316) surrounding the ATP7B locus to construct haplotypes in these families. Analysis indicates that there are many unique WND haplotypes not present on normal chromosomes and that there may be a large number of different WND mutations. We have screened the WND patients for mutations in the ATP7B gene. Fifty six patients, representing all of the identified haplotypes, have been screened using single strand conformational polymorphism (SSCP), followed by selective sequencing. To date, 19 mutations and 12 polymorphisms have been identified. All of the changes are nucleotide substitutions or small insertions/deletions and there is no evidence for larger deletions as seen in the similar gene on the X chromosome, ATP7A. Haplotypes of close markers and the ability to detect some of the mutations present in the gene allow for more reliable molecular diagnosis of presymptomatic sibs of WND patients. A reassessment of individuals previously diagnosed in the presymptomatic phase is now required, as we have have identified some heterozygotes who are biochemically indistinguishable from affected homozygotes. The identification of specific mutations will soon allow direct diagnosis of WND patients with a high level of certainty.

  19. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases

    PubMed Central

    Lin, Peng-Lin; Yu, Ya-Wen

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn’s disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn’s disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  20. Pathway Analysis Incorporating Protein-Protein Interaction Networks Identified Candidate Pathways for the Seven Common Diseases.

    PubMed

    Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

    2016-01-01

    Pathway analysis has become popular as a secondary analysis strategy for genome-wide association studies (GWAS). Most of the current pathway analysis methods aggregate signals from the main effects of single nucleotide polymorphisms (SNPs) in genes within a pathway without considering the effects of gene-gene interactions. However, gene-gene interactions can also have critical effects on complex diseases. Protein-protein interaction (PPI) networks have been used to define gene pairs for the gene-gene interaction tests. Incorporating the PPI information to define gene pairs for interaction tests within pathways can increase the power for pathway-based association tests. We propose a pathway association test, which aggregates the interaction signals in PPI networks within a pathway, for GWAS with case-control samples. Gene size is properly considered in the test so that genes do not contribute more to the test statistic simply due to their size. Simulation studies were performed to verify that the method is a valid test and can have more power than other pathway association tests in the presence of gene-gene interactions within a pathway under different scenarios. We applied the test to the Wellcome Trust Case Control Consortium GWAS datasets for seven common diseases. The most significant pathway is the chaperones modulate interferon signaling pathway for Crohn's disease (p-value = 0.0003). The pathway modulates interferon gamma, which induces the JAK/STAT pathway that is involved in Crohn's disease. Several other pathways that have functional implications for the seven diseases were also identified. The proposed test based on gene-gene interaction signals in PPI networks can be used as a complementary tool to the current existing pathway analysis methods focusing on main effects of genes. An efficient software implementing the method is freely available at http://puppi.sourceforge.net. PMID:27622767

  1. Sleeping Beauty mouse models identify candidate genes involved in gliomagenesis.

    PubMed

    Vyazunova, Irina; Maklakova, Vilena I; Berman, Samuel; De, Ishani; Steffen, Megan D; Hong, Won; Lincoln, Hayley; Morrissy, A Sorana; Taylor, Michael D; Akagi, Keiko; Brennan, Cameron W; Rodriguez, Fausto J; Collier, Lara S

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma.

  2. Gene Expression in Relation to Exhaled Nitric Oxide Identifies Novel Asthma Phenotypes with Unique Biomolecular Pathways

    PubMed Central

    Modena, Brian D.; Tedrow, John R.; Milosevic, Jadranka; Bleecker, Eugene R.; Meyers, Deborah A.; Wu, Wei; Bar-Joseph, Ziv; Erzurum, Serpil C.; Gaston, Benjamin M.; Busse, William W.; Jarjour, Nizar N.; Kaminski, Naftali

    2014-01-01

    Rationale Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies. Objectives To link gene expression patterns to clinical asthma phenotypes. Methods We used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP). Measurements and Main Results We first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics—termed “subject clusters” (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10−6. Hierarchical clustering of these 1,384 genes identified nine gene clusters or “biclusters,” whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted. Conclusions These findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes. PMID:25338189

  3. Identifying gene regulatory network rewiring using latent differential graphical models.

    PubMed

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-09-30

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions.

  4. Identifying gene regulatory network rewiring using latent differential graphical models

    PubMed Central

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-01-01

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions. PMID:27378774

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

    PubMed

    Edenberg, Howard J; Foroud, Tatiana

    2006-09-01

    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.

  6. Disease Risk Factors Identified through Shared Genetic Architecture and Electronic Medical Records

    PubMed Central

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

    2015-01-01

    Genome-Wide Association Studies (GWAS) have identified genetic variants for thousands of diseases and traits. In this study, 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-SNP association database (VARIMED), analyzing the findings from 8,962 published association studies. Similarity between traits and diseases was statistically evaluated based on 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 (EMR) from 3 independent medical centers for evidence of the trait appearing in patients within one year of first diagnosis of the disease. We validated that 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 prostate specific antigen and serum magnesium levels were altered before the diagnosis of lung cancer and gastric cancer, respectively. Disease-trait associations identifies traits that can potentially serve a prognostic function clinically; validating disease-trait associations through EMR can whether these candidates are risk factors for complex diseases. PMID:24786325

  7. The Implicitome: A Resource for Rationalizing Gene-Disease Associations

    PubMed Central

    van der Horst, Eelke; Kaliyaperumal, Rajaram; Mina, Eleni; Tatum, Zuotian; Laros, Jeroen F. J.; van Mulligen, Erik M.; Schuemie, Martijn; Aten, Emmelien; Li, Tong Shu; Bruskiewich, Richard; Good, Benjamin M.; Su, Andrew I.; Kors, Jan A.; den Dunnen, Johan; van Ommen, Gert-Jan B.; Roos, Marco; ‘t Hoen, Peter A.C.; Mons, Barend; Schultes, Erik A.

    2016-01-01

    High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations. PMID:26919047

  8. The Implicitome: A Resource for Rationalizing Gene-Disease Associations.

    PubMed

    Hettne, Kristina M; Thompson, Mark; van Haagen, Herman H H B M; van der Horst, Eelke; Kaliyaperumal, Rajaram; Mina, Eleni; Tatum, Zuotian; Laros, Jeroen F J; van Mulligen, Erik M; Schuemie, Martijn; Aten, Emmelien; Li, Tong Shu; Bruskiewich, Richard; Good, Benjamin M; Su, Andrew I; Kors, Jan A; den Dunnen, Johan; van Ommen, Gert-Jan B; Roos, Marco; 't Hoen, Peter A C; Mons, Barend; Schultes, Erik A

    2016-01-01

    High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations. PMID:26919047

  9. Effect of gene polymorphisms on periodontal diseases

    PubMed Central

    Tarannum, Fouzia; Faizuddin, Mohamed

    2012-01-01

    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. PMID:22754216

  10. Conceptual thinking for in silico prioritization of candidate disease genes.

    PubMed

    Tiffin, Nicki

    2011-01-01

    Prioritization of most likely etiological genes entails predicting and defining a set of characteristics that are most likely to fit the underlying disease gene and scoring candidates according to their fit to this "perfect disease gene" profile. This requires a full understanding of the disease phenotype, characteristics, and any available data on the underlying genetics of the disease. Public databases provide enormous and ever-growing amounts of information that can be relevant to the prioritization of etiological genes. Computational approaches allow this information to be retrieved in an automated and exhaustive way and can therefore facilitate the comprehensive mining of this information, including its combination with sets of empirically generated data, in the process of identifying most likely candidate disease genes.

  11. Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype.

    PubMed

    Kanth, Priyanka; Bronner, Mary P; Boucher, Kenneth M; Burt, Randall W; Neklason, Deborah W; Hagedorn, Curt H; Delker, Don A

    2016-06-01

    Sessile serrated colon adenoma/polyps (SSA/P) are found during routine screening colonoscopy and may account for 20% to 30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. In addition, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing (RNA-Seq) was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon, and 20 control colon specimens. Differential expression and leave-one-out cross-validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1,422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n = 12) and sporadic SSA/Ps (n = 9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability. A smaller 7-gene panel showed high sensitivity and specificity in identifying BRAF-mutant, CpG island methylator phenotype high, and MLH1-silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. Cancer Prev Res; 9(6); 456-65. ©2016 AACR.

  12. Immunogenetic mechanisms leading to thyroid autoimmunity: recent advances in identifying susceptibility genes and regions.

    PubMed

    Brand, Oliver J; Gough, Stephen C L

    2011-12-01

    The autoimmune thyroid diseases (AITD) include Graves' disease (GD) and Hashimoto's thyroiditis (HT), which are characterised by a breakdown in immune tolerance to thyroid antigens. Unravelling the genetic architecture of AITD is vital to better understanding of AITD pathogenesis, required to advance therapeutic options in both disease management and prevention. The early whole-genome linkage and candidate gene association studies provided the first evidence that the HLA region and CTLA-4 represented AITD risk loci. Recent improvements in; high throughput genotyping technologies, collection of larger disease cohorts and cataloguing of genome-scale variation have facilitated genome-wide association studies and more thorough screening of candidate gene regions. This has allowed identification of many novel AITD risk genes and more detailed association mapping. The growing number of confirmed AITD susceptibility loci, implicates a number of putative disease mechanisms most of which are tightly linked with aspects of immune system function. The unprecedented advances in genetic study will allow future studies to identify further novel disease risk genes and to identify aetiological variants within specific gene regions, which will undoubtedly lead to a better understanding of AITD patho-physiology.

  13. A survey of disease connections for CD4+ T cell master genes and their directly linked genes.

    PubMed

    Li, Wentian; Espinal-Enríquez, Jesús; Simpfendorfer, Kim R; Hernández-Lemus, Enrique

    2015-12-01

    Genome-wide association studies and other genetic analyses have identified a large number of genes and variants implicating a variety of disease etiological mechanisms. It is imperative for the study of human diseases to put these genetic findings into a coherent functional context. Here we use system biology tools to examine disease connections of five master genes for CD4+ T cell subtypes (TBX21, GATA3, RORC, BCL6, and FOXP3). We compiled a list of genes functionally interacting (protein-protein interaction, or by acting in the same pathway) with the master genes, then we surveyed the disease connections, either by experimental evidence or by genetic association. Embryonic lethal genes (also known as essential genes) are over-represented in master genes and their interacting genes (55% versus 40% in other genes). Transcription factors are significantly enriched among genes interacting with the master genes (63% versus 10% in other genes). Predicted haploinsufficiency is a feature of most these genes. Disease-connected genes are enriched in this list of genes: 42% of these genes have a disease connection according to Online Mendelian Inheritance in Man (OMIM) (versus 23% in other genes), and 74% are associated with some diseases or phenotype in a Genome Wide Association Study (GWAS) (versus 43% in other genes). Seemingly, not all of the diseases connected to genes surveyed were immune related, which may indicate pleiotropic functions of the master regulator genes and associated genes.

  14. 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...

  15. OrthoDisease: tracking disease gene orthologs across 100 species.

    PubMed

    Forslund, Kristoffer; Schreiber, Fabian; Thanintorn, Nattaphon; Sonnhammer, Erik L L

    2011-09-01

    Orthology is one of the most important tools available to modern biology, as it allows making inferences from easily studied model systems to much less tractable systems of interest, such as ourselves. This becomes important not least in the study of genetic diseases. We here review work on the orthology of disease-associated genes and also present an updated version of the InParanoid-based disease orthology database and web site OrthoDisease, with 14-fold increased species coverage since the previous version. Using this resource, we survey the taxonomic distribution of orthologs of human genes involved in different disease categories. The hypothesis that paralogs can mask the effect of deleterious mutations predicts that known heritable disease genes should have fewer close paralogs. We found large-scale support for this hypothesis as significantly fewer duplications were observed for disease genes in the OrthoDisease ortholog groups.

  16. Gene Regulatory Networks Elucidating Huanglongbing Disease Mechanisms

    PubMed Central

    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

    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

  17. Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes

    PubMed Central

    Hirbo, Jibril; Eidem, Haley; Rokas, Antonis; Abbot, Patrick

    2015-01-01

    Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB), a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23–34%) are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB. PMID:26641094

  18. Gene linked to Lou Gehrig's disease

    SciTech Connect

    Marx, J.

    1993-03-05

    Scientists have just taken a big step toward understanding the cause of Lou Gehrig's disease, one of the most devastating nerve degenerative diseases. A large team of researchers, led by Robert Brown Jr. of Harvards's Massachusetts General Hospital and Robert Horvitz, a Howard Hughes Medical Institute investigator at the Massachusetts Institute of Technology, report in the 4 March Nature that they've identified the gene that causes a hereditary form of the condition, which also goes by the name amyothophic lateral sclerosis (ALS). While most ALS cases - approximately 90% - are apparently sporadic' and not caused by an inherited gene defect, all the patients have such similar symptons that researchers are hopeful that what they learn about hereditary ALS will also apply to the sporadic form, possibly leading to new therapeutic strategies that will help both. It's a very important finding,' says neurobiologist Donald Harter of the Howard Hughes Medical Institute. It's one of the first handles we've had on the genetic basis of ALS.' The gene encodes Cu/Zn-binding superoxide dismutase and maps to the long arm of human chromosome 21.

  19. Identification of PAHX, a Refsum disease gene.

    PubMed

    Mihalik, S J; Morrell, J C; Kim, D; Sacksteder, K A; Watkins, P A; Gould, S J

    1997-10-01

    Refsum disease is an autosomal recessive disorder characterized by retinitis pigmentosa, peripheral polyneuropathy, cerebellar ataxia and increased cerebrospinal fluid protein. Biochemically, the disorder is defined by two related properties: pronounced accumulation of phytanic acid and selective loss of the peroxisomal dioxygenase required for alpha-hydroxylation of phytanoyl-CoA2. Decreased phytanic-acid oxidation is also observed in human cells lacking PEX7, the receptor for the type-2 peroxisomal targetting signal (PTS2; refs 3,4), suggesting that the enzyme defective in Refsum disease is targetted to peroxisomes by a PTS2. We initially identified the human PAHX and mouse Pahx genes as expressed sequence tags (ESTs) capable of encoding PTS2 proteins. Human PAHX is targetted to peroxisomes, requires the PTS2 receptor for peroxisomal localization, interacts with the PTS2 receptor in the yeast two-hybrid assay and has intrinsic phytanoyl-CoA alpha-hydroxylase activity that requires the dioxygenase cofactor iron and cosubstrate 2-oxoglutarate. Radiation hybrid data place PAHX on chromosome 10 between the markers D10S249 and D10S466, a region previously implicated in Refsum disease by homozygosity mapping. We find that both Refsum disease patients examined are homozygous for inactivating mutations in PAHX, demonstrating that mutations in PAHX can cause Refsum disease.

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

    PubMed Central

    Wang, Lan; Zhang, Yong-Hong; Lei, Shu-Feng; Deng, Fei-Yan

    2016-01-01

    Objective Systemic lupus erythematosus (SLE) is a complex auto-immune disease. Gene expression studies have been conducted to identify SLE-related genes in various types of samples. It is unknown whether there are common marker genes significant for SLE but independent of sample types, which may have potentials for follow-up translational research. The aim of this study is to identify common marker genes across various sample types for SLE. Methods Based on four public microarray gene expression datasets for SLE covering three representative types of blood-born samples (monocyte; peripheral blood mononuclear cell, PBMC; whole blood), we utilized three statistics (fold-change, FC; t-test p value; false discovery rate adjusted p value) to scrutinize genes simultaneously regulated with SLE across various sample types. For common marker genes, we conducted the Gene Ontology enrichment analysis and Protein-Protein Interaction analysis to gain insights into their functions. Results We identified 10 common marker genes associated with SLE (IFI6, IFI27, IFI44L, OAS1, OAS2, EIF2AK2, PLSCR1, STAT1, RNASE2, and GSTO1). Significant up-regulation of IFI6, IFI27, and IFI44L with SLE was observed in all the studied sample types, though the FC was most striking in monocyte, compared with PBMC and whole blood (8.82–251.66 vs. 3.73–74.05 vs. 1.19–1.87). Eight of the above 10 genes, except RNASE2 and GSTO1, interact with each other and with known SLE susceptibility genes, participate in immune response, RNA and protein catabolism, and cell death. Conclusion Our data suggest that there exist common marker genes across various sample types for SLE. The 10 common marker genes, identified herein, deserve follow-up studies to dissert their potentials as diagnostic or therapeutic markers to predict SLE or treatment response. PMID:27257790

  1. Gene-environment interactions in human disease: nuisance or opportunity?

    PubMed

    Ober, Carole; Vercelli, Donata

    2011-03-01

    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 could 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, although more tractable, might not be sufficient to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene-environment interactions.

  2. Using SCOPE to identify potential regulatory motifs in coregulated genes.

    PubMed

    Martyanov, Viktor; Gross, Robert H

    2011-05-31

    SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data. In this article, we utilize a web version of SCOPE to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs and has been used in other studies. The three algorithms that comprise SCOPE are BEAM, which finds non-degenerate motifs (ACCGGT), PRISM, which finds degenerate motifs (ASCGWT), and SPACER, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from

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

    PubMed Central

    2014-01-01

    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. PMID:24602502

  4. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations

    PubMed Central

    Gligorijevic, Djordje; Stojanovic, Jelena; Djuric, Nemanja; Radosavljevic, Vladan; Grbovic, Mihajlo; Kulathinal, Rob J.; Obradovic, Zoran

    2016-01-01

    Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies. PMID:27578529

  5. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations.

    PubMed

    Gligorijevic, Djordje; Stojanovic, Jelena; Djuric, Nemanja; Radosavljevic, Vladan; Grbovic, Mihajlo; Kulathinal, Rob J; Obradovic, Zoran

    2016-01-01

    Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies. PMID:27578529

  6. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations.

    PubMed

    Gligorijevic, Djordje; Stojanovic, Jelena; Djuric, Nemanja; Radosavljevic, Vladan; Grbovic, Mihajlo; Kulathinal, Rob J; Obradovic, Zoran

    2016-01-01

    Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies.

  7. Phage cluster relationships identified through single gene analysis

    PubMed Central

    2013-01-01

    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. PMID:23777341

  8. Genes Necessary for Bacterial Magnetite Biomineralization Identified by Transposon Mutagenesis

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

    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

  9. Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases

    PubMed Central

    Ruau, David; Dudley, Joel T.; Chen, Rong; Phillips, Nicholas G.; Swan, Gary E.; Lazzeroni, Laura C.; Clark, J. David

    2012-01-01

    Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10−10) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10−4, 1.8×10−4, and 2.2×10−4 respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates. PMID:22685391

  10. Sleeping Beauty Mouse Models Identify Candidate Genes Involved in Gliomagenesis

    PubMed Central

    Vyazunova, Irina; Maklakova, Vilena I.; Berman, Samuel; De, Ishani; Steffen, Megan D.; Hong, Won; Lincoln, Hayley; Morrissy, A. Sorana; Taylor, Michael D.; Akagi, Keiko; Brennan, Cameron W.; Rodriguez, Fausto J.; Collier, Lara S.

    2014-01-01

    Genomic studies of human high-grade gliomas have discovered known and candidate tumor drivers. Studies in both cell culture and mouse models have complemented these approaches and have identified additional genes and processes important for gliomagenesis. Previously, we found that mobilization of Sleeping Beauty transposons in mice ubiquitously throughout the body from the Rosa26 locus led to gliomagenesis with low penetrance. Here we report the characterization of mice in which transposons are mobilized in the Glial Fibrillary Acidic Protein (GFAP) compartment. Glioma formation in these mice did not occur on an otherwise wild-type genetic background, but rare gliomas were observed when mobilization occurred in a p19Arf heterozygous background. Through cloning insertions from additional gliomas generated by transposon mobilization in the Rosa26 compartment, several candidate glioma genes were identified. Comparisons to genetic, epigenetic and mRNA expression data from human gliomas implicates several of these genes as tumor suppressor genes and oncogenes in human glioblastoma. PMID:25423036

  11. Axon Regeneration Genes Identified by RNAi Screening in C. elegans

    PubMed Central

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

    2014-01-01

    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/β-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 β-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

  12. Methods for identifying an essential gene in a prokaryotic microorganism

    DOEpatents

    Shizuya, Hiroaki

    2006-01-31

    Methods are provided for the rapid identification of essential or conditionally essential DNA segments in any species of haploid cell (one copy chromosome per cell) that is capable of being transformed by artificial means and is capable of undergoing DNA recombination. This system offers an enhanced means of identifying essential function genes in diploid pathogens, such as gram-negative and gram-positive bacteria.

  13. Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes

    PubMed Central

    Lieberman, Tami D.; Michel, Jean-Baptiste; Aingaran, Mythili; Potter-Bynoe, Gail; Roux, Damien; Davis, Michael R.; Skurnik, David; Leiby, Nicholas; LiPuma, John J.; Goldberg, Joanna B.; McAdam, Alexander J.; Priebe, Gregory P.; Kishony, Roy

    2011-01-01

    Bacterial pathogens evolve during the infection of their human hosts1-8, but separating adaptive and neutral mutations remains challenging9-11. Here, we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple patients. We conducted a retrospective study of a Burkholderia dolosa outbreak among people with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired non-synonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes illuminate the genetic basis of important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition, and implicate oxygen-dependent gene regulation as paramount in lung infections. Several genes have not been previously implicated in pathogenesis, suggesting new therapeutic targets. The identification of parallel molecular evolution suggests key selection forces acting on pathogens within humans and can help predict and prepare for their future evolutionary course. PMID:22081229

  14. Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics.

    PubMed

    Harper, Andrea L; McKinney, Lea Vig; Nielsen, Lene Rostgaard; Havlickova, Lenka; Li, Yi; Trick, Martin; Fraser, Fiona; Wang, Lihong; Fellgett, Alison; Sollars, Elizabeth S A; Janacek, Sophie H; Downie, J Allan; Buggs, Richard J A; Kjær, Erik Dahl; Bancroft, Ian

    2016-01-01

    Tree disease epidemics are a global problem, impacting food security, biodiversity and national economies. The potential for conservation and breeding in trees is hampered by complex genomes and long lifecycles, with most species lacking genomic resources. The European Ash tree Fraxinus excelsior is being devastated by the fungal pathogen Hymenoscyphus fraxineus, which causes ash dieback disease. Taking this system as an example and utilizing Associative Transcriptomics for the first time in a plant pathology study, we discovered gene sequence and gene expression variants across a genetic diversity panel scored for disease symptoms and identified markers strongly associated with canopy damage in infected trees. Using these markers we predicted phenotypes in a test panel of unrelated trees, successfully identifying individuals with a low level of susceptibility to the disease. Co-expression analysis suggested that pre-priming of defence responses may underlie reduced susceptibility to ash dieback. PMID:26757823

  15. An extended set of yeast-based functional assays accurately identifies human disease mutations

    PubMed Central

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L.; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E.; Vidal, Marc; Andrews, Brenda J.; Boone, Charles; Dolinski, Kara; Roth, Frederick P.

    2016-01-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods. PMID:26975778

  16. An extended set of yeast-based functional assays accurately identifies human disease mutations.

    PubMed

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E; Vidal, Marc; Andrews, Brenda J; Boone, Charles; Dolinski, Kara; Roth, Frederick P

    2016-05-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods. PMID:26975778

  17. An extended set of yeast-based functional assays accurately identifies human disease mutations.

    PubMed

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E; Vidal, Marc; Andrews, Brenda J; Boone, Charles; Dolinski, Kara; Roth, Frederick P

    2016-05-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods.

  18. Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics

    PubMed Central

    Harper, Andrea L.; McKinney, Lea Vig; Nielsen, Lene Rostgaard; Havlickova, Lenka; Li, Yi; Trick, Martin; Fraser, Fiona; Wang, Lihong; Fellgett, Alison; Sollars, Elizabeth S. A.; Janacek, Sophie H.; Downie, J. Allan; Buggs, Richard. J. A.; Kjær, Erik Dahl; Bancroft, Ian

    2016-01-01

    Tree disease epidemics are a global problem, impacting food security, biodiversity and national economies. The potential for conservation and breeding in trees is hampered by complex genomes and long lifecycles, with most species lacking genomic resources. The European Ash tree Fraxinus excelsior is being devastated by the fungal pathogen Hymenoscyphus fraxineus, which causes ash dieback disease. Taking this system as an example and utilizing Associative Transcriptomics for the first time in a plant pathology study, we discovered gene sequence and gene expression variants across a genetic diversity panel scored for disease symptoms and identified markers strongly associated with canopy damage in infected trees. Using these markers we predicted phenotypes in a test panel of unrelated trees, successfully identifying individuals with a low level of susceptibility to the disease. Co-expression analysis suggested that pre-priming of defence responses may underlie reduced susceptibility to ash dieback. PMID:26757823

  19. DDA: A Novel Network-Based Scoring Method to Identify Disease–Disease Associations

    PubMed Central

    Suratanee, Apichat; Plaimas, Kitiporn

    2015-01-01

    Categorizing human diseases provides higher efficiency and accuracy for disease diagnosis, prognosis, and treatment. Disease–disease association (DDA) is a precious information that indicates the large-scale structure of complex relationships of diseases. However, the number of known and reliable associations is very small. Therefore, identification of DDAs is a challenging task in systems biology and medicine. Here, we developed a novel network-based scoring algorithm called DDA to identify the relationships between diseases in a large-scale study. Our method is developed based on a random walk prioritization in a protein–protein interaction network. This approach considers not only whether two diseases directly share associated genes but also the statistical relationships between two different diseases using known disease-related genes. Predicted associations were validated by known DDAs from a database and literature supports. The method yielded a good performance with an area under the curve of 71% and outperformed other standard association indices. Furthermore, novel DDAs and relationships among diseases from the clusters analysis were reported. This method is efficient to identify disease–disease relationships on an interaction network and can also be generalized to other association studies to further enhance knowledge in medical studies. PMID:26673408

  20. AKAP2 identified as a novel gene mutated in a Chinese family with adolescent idiopathic scoliosis

    PubMed Central

    Li, Wei; Li, YaWei; Zhang, Lusi; Guo, Hui; Tian, Di; Li, Ying; Peng, Yu; Zheng, Yu; Dai, Yuliang; Xia, Kun; Lan, Xinqiang; Wang, Bing; Hu, Zhengmao

    2016-01-01

    Background Adolescent idiopathic scoliosis exhibits high heritability and is one of the most common spinal deformities found in adolescent populations. However, little is known about the disease-causing genes in families with adolescent idiopathic scoliosis exhibiting Mendelian inheritance. Objective The aim of this study was to identify the causative gene in a family with adolescent idiopathic scoliosis. Methods Whole-exome sequencing was performed on this family to identify the candidate gene. Sanger sequencing was conducted to validate the candidate mutations and familial segregation. Real-time QPCR was used to measure the expression level of the possible causative gene. Results We identified the mutation c.2645A>C (p.E882A) within the AKAP2 gene, which cosegregated with the adolescent idiopathic scoliosis phenotypes. AKAP2 is located in a previously reported linkage locus (IS4) on chromosome 9q31.2–q34.2 and has been implicated in skeletal development. The mutation was absent in dbSNP144, ESP6500 and 503 ethnicity-matched controls. Real-time QPCR revealed that the mRNA expression level in the patients was increased significantly compared with the family controls (p<0.0001). Conclusions AKAP2 was therefore implicated as a novel gene mutated in a Chinese family with adolescent idiopathic scoliosis. Further studies should be conducted to validate the results from the perspective of both the genetics and pathogenesis of this disease. PMID:26989089

  1. Transposon tagging of disease resistance genes

    SciTech Connect

    Michelmore, R.W. . Dept. of Physics)

    1989-01-01

    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.

  2. Using Drosophila melanogaster to identify chemotherapy toxicity genes.

    PubMed

    King, Elizabeth G; Kislukhin, Galina; Walters, Kelli N; Long, Anthony D

    2014-09-01

    The severity of the toxic side effects of chemotherapy shows a great deal of interindividual variability, and much of this variation is likely genetically based. Simple DNA tests predictive of toxic side effects could revolutionize the way chemotherapy is carried out. Due to the challenges in identifying polymorphisms that affect toxicity in humans, we use Drosophila fecundity following oral exposure to carboplatin, gemcitabine and mitomycin C as a model system to identify naturally occurring DNA variants predictive of toxicity. We use the Drosophila Synthetic Population Resource (DSPR), a panel of recombinant inbred lines derived from a multiparent advanced intercross, to map quantitative trait loci affecting chemotoxicity. We identify two QTL each for carboplatin and gemcitabine toxicity and none for mitomycin. One QTL is associated with fly orthologs of a priori human carboplatin candidate genes ABCC2 and MSH2, and a second QTL is associated with fly orthologs of human gemcitabine candidate genes RRM2 and RRM2B. The third, a carboplatin QTL, is associated with a posteriori human orthologs from solute carrier family 7A, INPP4A&B, and NALCN. The fourth, a gemcitabine QTL that also affects methotrexate toxicity, is associated with human ortholog GPx4. Mapped QTL each explain a significant fraction of variation in toxicity, yet individual SNPs and transposable elements in the candidate gene regions fail to singly explain QTL peaks. Furthermore, estimates of founder haplotype effects are consistent with genes harboring several segregating functional alleles. We find little evidence for nonsynonymous SNPs explaining mapped QTL; thus it seems likely that standing variation in toxicity is due to regulatory alleles.

  3. Comprehensive annotation of bidirectional promoters identifies co-regulation among breast and ovarian cancer genes.

    PubMed

    Yang, Mary Q; Koehly, Laura M; Elnitski, Laura L

    2007-04-20

    A "bidirectional gene pair" comprises two adjacent genes whose transcription start sites are neighboring and directed away from each other. The intervening regulatory region is called a "bidirectional promoter." These promoters are often associated with genes that function in DNA repair, with the potential to participate in the development of cancer. No connection between these gene pairs and cancer has been previously investigated. Using the database of spliced-expressed sequence tags (ESTs), we identified the most complete collection of human transcripts under the control of bidirectional promoters. A rigorous screen of the spliced EST data identified new bidirectional promoters, many of which functioned as alternative promoters or regulated novel transcripts. Additionally, we show a highly significant enrichment of bidirectional promoters in genes implicated in somatic cancer, including a substantial number of genes implicated in breast and ovarian cancers. The repeated use of this promoter structure in the human genome suggests it could regulate co-expression patterns among groups of genes. Using microarray expression data from 79 human tissues, we verify regulatory networks among genes controlled by bidirectional promoters. Subsets of these promoters contain similar combinations of transcription factor binding sites, including evolutionarily conserved ETS factor binding sites in ERBB2, FANCD2, and BRCA2. Interpreting the regulation of genes involved in co-expression networks, especially those involved in cancer, will be an important step toward defining molecular events that may contribute to disease.

  4. Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease

    PubMed Central

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

    2004-01-01

    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. PMID:15385455

  5. Disease-specific classification using deconvoluted whole blood gene expression.

    PubMed

    Wang, Li; Oh, William K; Zhu, Jun

    2016-01-01

    Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets. PMID:27596246

  6. Disease-specific classification using deconvoluted whole blood gene expression

    PubMed Central

    Wang, Li; Oh, William K.; Zhu, Jun

    2016-01-01

    Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets. PMID:27596246

  7. A recellularized human colon model identifies cancer driver genes.

    PubMed

    Chen, Huanhuan Joyce; Wei, Zhubo; Sun, Jian; Bhattacharya, Asmita; Savage, David J; Serda, Rita; Mackeyev, Yuri; Curley, Steven A; Bu, Pengcheng; Wang, Lihua; Chen, Shuibing; Cohen-Gould, Leona; Huang, Emina; Shen, Xiling; Lipkin, Steven M; Copeland, Neal G; Jenkins, Nancy A; Shuler, Michael L

    2016-08-01

    Refined cancer models are needed to bridge the gaps between cell line, animal and clinical research. Here we describe the engineering of an organotypic colon cancer model by recellularization of a native human matrix that contains cell-populated mucosa and an intact muscularis mucosa layer. This ex vivo system recapitulates the pathophysiological progression from APC-mutant neoplasia to submucosal invasive tumor. We used it to perform a Sleeping Beauty transposon mutagenesis screen to identify genes that cooperate with mutant APC in driving invasive neoplasia. We identified 38 candidate invasion-driver genes, 17 of which, including TCF7L2, TWIST2, MSH2, DCC, EPHB1 and EPHB2 have been previously implicated in colorectal cancer progression. Six invasion-driver genes that have not, to our knowledge, been previously described were validated in vitro using cell proliferation, migration and invasion assays and ex vivo using recellularized human colon. These results demonstrate the utility of our organoid model for studying cancer biology. PMID:27398792

  8. Identifying sleep regulatory genes using a Drosophila model of insomnia

    PubMed Central

    Seugnet, Laurent; Suzuki, Yasuko; Thimgan, Matthew; Donlea, Jeff; Gimbel, Sarah I.; Gottschalk, Laura; Duntley, Steve P.; Shaw, Paul J.

    2009-01-01

    Although it is widely accepted that sleep must serve an essential biological function, little is known about molecules that underlie sleep regulation. Given that insomnia is a common sleep disorder that disrupts the ability to initiate and maintain restorative sleep, a better understanding of its molecular underpinning may provide crucial insights into sleep regulatory processes. Thus, we created a line of flies using laboratory selection that share traits with human insomnia. After 60 generations insomnia-like (ins-l) flies sleep 60 min a day, exhibit difficulty initiating sleep, difficulty maintaining sleep, and show evidence of daytime cognitive impairment. ins-l flies are also hyperactive and hyper responsive to environmental perturbations. In addition they have difficulty maintaining their balance, have elevated levels of dopamine, are short-lived and show increased levels of triglycerides, cholesterol, and free fatty acids. While their core molecular clock remains intact, ins-l flies lose their ability to sleep when placed into constant darkness. Whole genome profiling identified genes that are modified in ins-l flies. Among those differentially expressed transcripts genes involved in metabolism, neuronal activity, and sensory perception constituted over-represented categories. We demonstrate that two of these genes are upregulated in human subjects following acute sleep deprivation. Together these data indicate that the ins-l flies are a useful tool that can be used to identify molecules important for sleep regulation and may provide insights into both the causes and long-term consequences of insomnia. PMID:19494137

  9. Anaerobically expressed Escherichia coli genes identified by operon fusion techniques.

    PubMed Central

    Choe, M; Reznikoff, W S

    1991-01-01

    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. PMID:1917846

  10. Genome-wide association study for Crohn's disease in the Quebec Founder Population identifies multiple validated disease loci

    PubMed Central

    Raelson, John V.; Little, Randall D.; Ruether, Andreas; Fournier, Hélène; Paquin, Bruno; Van Eerdewegh, Paul; Bradley, W. E. C.; Croteau, Pascal; Nguyen-Huu, Quynh; Segal, Jonathan; Debrus, Sophie; Allard, René; Rosenstiel, Philip; Franke, Andre; Jacobs, Gunnar; Nikolaus, Susanna; Vidal, Jean-Michel; Szego, Peter; Laplante, Nathalie; Clark, Hilary F.; Paulussen, René J.; Hooper, John W.; Keith, Tim P.; Belouchi, Abdelmajid; Schreiber, Stefan

    2007-01-01

    Genome-wide association (GWA) studies offer a powerful unbiased method for the identification of multiple susceptibility genes for complex diseases. Here we report the results of a GWA study for Crohn's disease (CD) using family trios from the Quebec Founder Population (QFP). Haplotype-based association analyses identified multiple regions associated with the disease that met the criteria for genome-wide significance, with many containing a gene whose function appears relevant to CD. A proportion of these were replicated in two independent German Caucasian samples, including the established CD loci NOD2 and IBD5. The recently described IL23R locus was also identified and replicated. For this region, multiple individuals with all major haplotypes in the QFP were sequenced and extensive fine mapping performed to identify risk and protective alleles. Several additional loci, including a region on 3p21 containing several plausible candidate genes, a region near JAKMIP1 on 4p16.1, and two larger regions on chromosome 17 were replicated. Together with previously published loci, the spectrum of CD genes identified to date involves biochemical networks that affect epithelial defense mechanisms, innate and adaptive immune response, and the repair or remodeling of tissue. PMID:17804789

  11. Patient Identified Disease Burden in Facioscapulohumeral Muscular Dystrophy

    PubMed Central

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

    2013-01-01

    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. PMID:23225386

  12. Assessment of gene order computing methods for Alzheimer's disease

    PubMed Central

    2013-01-01

    Background Computational genomics of Alzheimer disease (AD), the most common form of senile dementia, is a nascent field in AD research. The field includes AD gene clustering by computing gene order which generates higher quality gene clustering patterns than most other clustering methods. However, there are few available gene order computing methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Further, their performance in gene order computation using AD microarray data is not known. We thus set forth to evaluate the performances of current gene order computing methods with different distance formulas, and to identify additional features associated with gene order computation. Methods Using different distance formulas- Pearson distance and Euclidean distance, the squared Euclidean distance, and other conditions, gene orders were calculated by ACO and GA (including standard GA and improved GA) methods, respectively. The qualities of the gene orders were compared, and new features from the calculated gene orders were identified. Results Compared to the GA methods tested in this study, ACO fits the AD microarray data the best when calculating gene order. In addition, the following features were revealed: different distance formulas generated a different quality of gene order, and the commonly used Pearson distance was not the best distance formula when used with both GA and ACO methods for AD microarray data. Conclusion Compared with Pearson distance and Euclidean distance, the squared Euclidean distance generated the best quality gene order computed by GA and ACO methods. PMID:23369541

  13. Identifying genes that mediate anthracyline toxicity in immune cells.

    PubMed

    Frick, Amber; Suzuki, Oscar T; Benton, Cristina; Parks, Bethany; Fedoriw, Yuri; Richards, Kristy L; Thomas, Russell S; Wiltshire, Tim

    2015-01-01

    The role of the immune system in response to chemotherapeutic agents remains elusive. The interpatient variability observed in immune and chemotherapeutic cytotoxic responses is likely, at least in part, due to complex genetic differences. Through the use of a panel of genetically diverse mouse inbred strains, we developed a drug screening platform aimed at identifying genes underlying these chemotherapeutic cytotoxic effects on immune cells. Using genome-wide association studies (GWAS), we identified four genome-wide significant quantitative trait loci (QTL) that contributed to the sensitivity of doxorubicin and idarubicin in immune cells. Of particular interest, a locus on chromosome 16 was significantly associated with cell viability following idarubicin administration (p = 5.01 × 10(-8)). Within this QTL lies App, which encodes amyloid beta precursor protein. Comparison of dose-response curves verified that T-cells in App knockout mice were more sensitive to idarubicin than those of C57BL/6J control mice (p < 0.05). In conclusion, the cellular screening approach coupled with GWAS led to the identification and subsequent validation of a gene involved in T-cell viability after idarubicin treatment. Previous studies have suggested a role for App in in vitro and in vivo cytotoxicity to anticancer agents; the overexpression of App enhances resistance, while the knockdown of this gene is deleterious to cell viability. Further investigations should include performing mechanistic studies, validating additional genes from the GWAS, including Ppfia1 and Ppfibp1, and ultimately translating the findings to in vivo and human studies.

  14. Enrichment Analysis Identifies Functional MicroRNA-Disease Associations in Humans.

    PubMed

    Yuan, Dandan; Cui, Xiaomeng; Wang, Yang; Zhao, Yilei; Li, Huiying; Hu, Suangjiu; Chu, Xiaodan; Li, Yan; Li, Qiang; Liu, Qian; Zhu, Wenliang

    2015-01-01

    Substantial evidence has shown that microRNAs (miRNAs) may be causally linked to the occurrence and progression of human diseases. Herein, we conducted an enrichment analysis to identify potential functional miRNA-disease associations (MDAs) in humans by integrating currently known biological data: miRNA-target interactions (MTIs), protein-protein interactions, and gene-disease associations. Two contributing factors to functional miRNA-disease associations were quantitatively considered: the direct effects of miRNA that target disease-related genes, and indirect effects triggered by protein-protein interactions. Ninety-nine miRNAs were scanned for possible functional association with 2223 MeSH-defined human diseases. Each miRNA was experimentally validated to target ≥ 10 mRNA genes. Putative MDAs were identified when at least one MTI was confidently validated for a disease. Overall, 19648 putative MDAs were found, of which 10.0% was experimentally validated. Further results suggest that filtering for miRNAs that target a greater number of disease-related genes (n ≥ 8) can significantly enrich for true MDAs from the set of putative associations (enrichment rate = 60.7%, adjusted hypergeometric p = 2.41×10-91). Considering the indirect effects of miRNAs further elevated the enrichment rate to 72.6%. By using this method, a novel MDA between miR-24 and ovarian cancer was found. Compared with scramble miRNA overexpression of miR-24 was validated to remarkably induce ovarian cancer cells apoptosis. Our study provides novel insight into factors contributing to functional MDAs by integrating large quantities of previously generated biological data, and establishes a feasible method to identify plausible associations with high confidence. PMID:26296081

  15. Gene therapy for CNS diseases – Krabbe disease

    PubMed Central

    Rafi, Mohammad A.

    2016-01-01

    Summary This is a brief report of the 19th Annual Meeting of the American Society of Gene and Cell Therapy that took place from May 4th through May 7th, 2016 in Washington, DC, USA. While the meeting provided many symposiums, lectures, and scientific sessions this report mainly focuses on one of the sessions on the "Gene Therapy for central nervous system (CNS) Diseases" and specifically on the "Gene Therapy for the globoid cell leukodystrophy or Krabbe disease. Two presentations focused on this subject utilizing two animal models of this disease: mice and dog models. Different serotypes of adeno-associate viral vectors (AAV) alone or in combination with bone marrow transplantations were used in these research projects. The Meeting of the ASGCT reflected continuous growth in the fields of gene and cell therapy and brighter forecast for efficient treatment options for variety of human diseases. PMID:27525222

  16. 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- ... in preclinical animal models of this disease. Other genetic disorders After many years of laboratory and preclinical ...

  17. Gene drive systems for insect disease vectors.

    PubMed

    Sinkins, Steven P; Gould, Fred

    2006-06-01

    The elegant mechanisms by which naturally occurring selfish genetic elements, such as transposable elements, meiotic drive genes, homing endonuclease genes and Wolbachia, spread at the expense of their hosts provide some of the most fascinating and remarkable subjects in evolutionary genetics. These elements also have enormous untapped potential to be used in the control of some of the world's most devastating diseases. Effective gene drive systems for spreading genes that can block the transmission of insect-borne pathogens are much needed. Here we explore the potential of natural gene drive systems and discuss the artificial constructs that could be envisaged for this purpose.

  18. Gene Conversion in Human Genetic Disease

    PubMed Central

    Chen, Jian-Min; Férec, Claude; Cooper, David N.

    2010-01-01

    Gene conversion is a specific type of homologous recombination that involves the unidirectional transfer of genetic material from a ‘donor’ sequence to a highly homologous ‘acceptor’. We have recently reviewed the molecular mechanisms underlying gene conversion, explored the key part that this process has played in fashioning extant human genes, and performed a meta-analysis of gene-conversion events known to have caused human genetic disease. Here we shall briefly summarize some of the latest developments in the study of pathogenic gene conversion events, including (i) the emerging idea of minimal efficient sequence homology (MESH) for homologous recombination, (ii) the local DNA sequence features that appear to predispose to gene conversion, (iii) a mechanistic comparison of gene conversion and transient hypermutability, and (iv) recently reported examples of pathogenic gene conversion events. PMID:24710102

  19. Isolated populations and complex disease gene identification

    PubMed Central

    Kristiansson, Kati; Naukkarinen, Jussi; Peltonen, Leena

    2008-01-01

    The utility of genetically isolated populations (population isolates) in the mapping and identification of genes is not only limited to the study of rare diseases; isolated populations also provide a useful resource for studies aimed at improved understanding of the biology underlying common diseases and their component traits. Well characterized human populations provide excellent study samples for many different genetic investigations, ranging from genome-wide association studies to the characterization of interactions between genes and the environment. PMID:18771588

  20. Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

    PubMed Central

    McDonald, Megan C.; McGinness, Lachlan; Hane, James K.; Williams, Angela H.; Milgate, Andrew; Solomon, Peter S.

    2016-01-01

    Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene. PMID:26837952

  1. Diseases originate and terminate by genes: unraveling nonviral gene delivery.

    PubMed

    Swami, Rajan; Singh, Indu; Khan, Wahid; Ramakrishna, Sistla

    2013-12-01

    The world is driving in to the era of transformation of chemical therapeutic molecules to biological genetic material therapeutics, and that is where the biological drugs especially "genes" come into existence. These genes worked as "magical bullets" to specifically silence faulty genes responsible for progression of diseases. Viral gene delivery research is far ahead of nonviral gene delivery technique. However, with more advancement in polymer science, new ways are opening for better and efficient nonviral gene delivery. But efficient delivery method is always considered as a bottleneck for gene delivery as success of which will decide the fate of gene in cells. During the past decade, it became evident that extracellular as well as intracellular barriers compromise the transfection efficiency of nonviral vectors. The challenge for gene therapy research is to pinpoint the rate-limiting steps in this complex process and implement strategies to overcome the biological physiochemical and metabolic barriers encountered during targeting. The synergy between studies that investigate the mechanism of breaking in and breaking out of nonviral gene delivery carrier through various extracellular and intracellular barriers with desired characteristics will enable the rational design of vehicles and revolutionize the treatment of various diseases.

  2. NDRC: A Disease-Causing Genes Prioritized Method Based on Network Diffusion and Rank Concordance.

    PubMed

    Fang, Minghong; Hu, Xiaohua; Wang, Yan; Zhao, Junmin; Shen, Xianjun; He, Tingting

    2015-07-01

    Disease-causing genes prioritization is very important to understand disease mechanisms and biomedical applications, such as design of drugs. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease genes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively prioritized. These approaches tend to prioritize those genes that are highly connected in the PPI network while perform poorly when they are applied to loosely connected disease genes. To address these problems, we propose a new disease-causing genes prioritization method that based on network diffusion and rank concordance (NDRC). The method is evaluated by leave-one-out cross validation on 1931 diseases in which at least one gene is known to be involved, and it is able to rank the true causal gene first in 849 of all 2542 cases. The experimental results suggest that NDRC significantly outperforms other existing methods such as RWR, VAVIEN, DADA and PRINCE on identifying loosely connected disease genes and successfully put dangling genes as potential candidate disease genes. Furthermore, we apply NDRC method to study three representative diseases, Meckel syndrome 1, Protein C deficiency and Peroxisome biogenesis disorder 1A (Zellweger). Our study has also found that certain complex disease-causing genes can be divided into several modules that are closely associated with different disease phenotype.

  3. A probabilistic disease-gene finder for personal genomes.

    PubMed

    Yandell, Mark; Huff, Chad; Hu, Hao; Singleton, Marc; Moore, Barry; Xing, Jinchuan; Jorde, Lynn B; Reese, Martin G

    2011-09-01

    VAAST (the Variant Annotation, Analysis & Search Tool) is a probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST builds on existing amino acid substitution (AAS) and aggregative approaches to variant prioritization, combining elements of both into a single unified likelihood framework that allows users to identify damaged genes and deleterious variants with greater accuracy, and in an easy-to-use fashion. VAAST can score both coding and noncoding variants, evaluating the cumulative impact of both types of variants simultaneously. VAAST can identify rare variants causing rare genetic diseases, and it can also use both rare and common variants to identify genes responsible for common diseases. VAAST thus has a much greater scope of use than any existing methodology. Here we demonstrate its ability to identify damaged genes using small cohorts (n = 3) of unrelated individuals, wherein no two share the same deleterious variants, and for common, multigenic diseases using as few as 150 cases.

  4. GeneValidator: identify problems with protein-coding gene predictions

    PubMed Central

    Drăgan, Monica-Andreea; Moghul, Ismail; Priyam, Anurag; Bustos, Claudio; Wurm, Yannick

    2016-01-01

    Summary: Genomes of emerging model organisms are now being sequenced at very low cost. However, obtaining accurate gene predictions remains challenging: even the best gene prediction algorithms make substantial errors and can jeopardize subsequent analyses. Therefore, many predicted genes must be time-consumingly visually inspected and manually curated. We developed GeneValidator (GV) to automatically identify problematic gene predictions and to aid manual curation. For each gene, GV performs multiple analyses based on comparisons to gene sequences from large databases. The resulting report identifies problematic gene predictions and includes extensive statistics and graphs for each prediction to guide manual curation efforts. GV thus accelerates and enhances the work of biocurators and researchers who need accurate gene predictions from newly sequenced genomes. Availability and implementation: GV can be used through a web interface or in the command-line. GV is open-source (AGPL), available at https://wurmlab.github.io/tools/genevalidator. Contact: y.wurm@qmul.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26787666

  5. Identifying Genes Involved in Cyclic Processes by Combining Gene Expression Analysis and Prior Knowledge

    PubMed Central

    2009-01-01

    Based on time series gene expressions, cyclic genes can be recognized via spectral analysis and statistical periodicity detection tests. These cyclic genes are usually associated with cyclic biological processes, for example, cell cycle and circadian rhythm. The power of a scheme is practically measured by comparing the detected periodically expressed genes with experimentally verified genes participating in a cyclic process. However, in the above mentioned procedure the valuable prior knowledge only serves as an evaluation benchmark, and it is not fully exploited in the implementation of the algorithm. In addition, partial data sets are also disregarded due to their nonstationarity. This paper proposes a novel algorithm to identify cyclic-process-involved genes by integrating the prior knowledge with the gene expression analysis. The proposed algorithm is applied on data sets corresponding to Saccharomyces cerevisiae and Drosophila melanogaster, respectively. Biological evidences are found to validate the roles of the discovered genes in cell cycle and circadian rhythm. Dendrograms are presented to cluster the identified genes and to reveal expression patterns. It is corroborated that the proposed novel identification scheme provides a valuable technique for unveiling pathways related to cyclic processes. PMID:19390635

  6. Linking Genes to Cardiovascular Diseases: Gene Action and Gene-Environment Interactions.

    PubMed

    Pasipoularides, Ares

    2015-12-01

    A unique myocardial characteristic is its ability to grow/remodel in order to adapt; this is determined partly by genes and partly by the environment and the milieu intérieur. In the "post-genomic" era, a need is emerging to elucidate the physiologic functions of myocardial genes, as well as potential adaptive and maladaptive modulations induced by environmental/epigenetic factors. Genome sequencing and analysis advances have become exponential lately, with escalation of our knowledge concerning sometimes controversial genetic underpinnings of cardiovascular diseases. Current technologies can identify candidate genes variously involved in diverse normal/abnormal morphomechanical phenotypes, and offer insights into multiple genetic factors implicated in complex cardiovascular syndromes. The expression profiles of thousands of genes are regularly ascertained under diverse conditions. Global analyses of gene expression levels are useful for cataloging genes and correlated phenotypes, and for elucidating the role of genes in maladies. Comparative expression of gene networks coupled to complex disorders can contribute insights as to how "modifier genes" influence the expressed phenotypes. Increasingly, a more comprehensive and detailed systematic understanding of genetic abnormalities underlying, for example, various genetic cardiomyopathies is emerging. Implementing genomic findings in cardiology practice may well lead directly to better diagnosing and therapeutics. There is currently evolving a strong appreciation for the value of studying gene anomalies, and doing so in a non-disjointed, cohesive manner. However, it is challenging for many-practitioners and investigators-to comprehend, interpret, and utilize the clinically increasingly accessible and affordable cardiovascular genomics studies. This survey addresses the need for fundamental understanding in this vital area.

  7. Candidate gene discovery and prioritization in rare diseases.

    PubMed

    Jegga, Anil G

    2014-01-01

    A rare or orphan disorder is any disease that affects a small percentage of the population. Most genes and pathways underlying these disorders remain unknown. High-throughput techniques are frequently applied to detect disease candidate genes. The speed and affordability of sequencing following recent technological advances while advantageous are accompanied by the problem of data deluge. Furthermore, experimental validation of disease candidate genes is both time-consuming and expensive. Therefore, several computational approaches have been developed to identify the most promising candidates for follow-up studies. Based on the guilt by association principle, most of these approaches use prior knowledge about a disease of interest to discover and rank novel candidate genes. In this chapter, a brief overview of some of the in silico strategies for candidate gene prioritization is provided. To demonstrate their utility in rare disease research, a Web-based computational suite of tools that use integrated heterogeneous data sources for ranking disease candidate genes is used to demonstrate how to run typical queries using this system.

  8. Copy number variation analysis identifies novel CAKUT candidate genes in children with a solitary functioning kidney

    PubMed Central

    Westland, Rik; Verbitsky, Miguel; Vukojevic, Katarina; Perry, Brittany J.; Fasel, David A.; Zwijnenburg, Petra J.G.; Bökenkamp, Arend; Gille, Johan J.P.; Saraga-Babic, Mirna; Ghiggeri, Gian Marco; D’Agati, Vivette D.; Schreuder, Michiel F.; Gharavi, Ali G.; van Wijk, Joanna A.E.; Sanna-Cherchi, Simone

    2016-01-01

    Copy number variations associate with different developmental phenotypes and represent a major cause of congenital anomalies of the kidney and urinary tract (CAKUT). Because rare pathogenic copy number variations are often large and contain multiple genes, identification of the underlying genetic drivers has proven to be difficult. Here we studied the role of rare copy number variations in 80 patients from the KIMONO-study cohort for which pathogenic mutations in three genes commonly implicated in CAKUT were excluded. In total, 13 known or novel genomic imbalances in 11 of 80 patients were absent or extremely rare in 23,362 population controls. To identify the most likely genetic drivers for the CAKUT phenotype underlying these rare copy number variations, we used a systematic in silico approach based on frequency in a large dataset of controls, annotation with publicly available databases for developmental diseases, tolerance and haploinsufficiency scores, and gene expression profile in the developing kidney and urinary tract. Five novel candidate genes for CAKUT were identified that showed specific expression in the human and mouse developing urinary tract. Among these genes, DLG1 and KIF12 are likely novel susceptibility genes for CAKUT in humans. Thus, there is a significant role of genomic imbalance in the determination of kidney developmental phenotypes. Additionally, we defined a systematic strategy to identify genetic drivers underlying rare copy number variations. PMID:26352300

  9. Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways

    PubMed Central

    Cirulli, Elizabeth T.; Lasseigne, Brittany N.; Petrovski, Slavé; Sapp, Peter C.; Dion, Patrick A.; Leblond, Claire S.; Couthouis, Julien; Lu, Yi-Fan; Wang, Quanli; Krueger, Brian J.; Ren, Zhong; Keebler, Jonathan; Han, Yujun; Levy, Shawn E.; Boone, Braden E.; Wimbish, Jack R.; Waite, Lindsay L.; Jones, Angela L.; Carulli, John P.; Day-Williams, Aaron G.; Staropoli, John F.; Xin, Winnie W.; Chesi, Alessandra; Raphael, Alya R.; McKenna-Yasek, Diane; Cady, Janet; de Jong, J.M.B. Vianney; Kenna, Kevin P.; Smith, Bradley N.; Topp, Simon; Miller, Jack; Gkazi, Athina; Al-Chalabi, Ammar; van den Berg, Leonard H.; Veldink, Jan; Silani, Vincenzo; Ticozzi, Nicola; Shaw, Christopher E.; Baloh, Robert H.; Appel, Stanley; Simpson, Ericka; Lagier-Tourenne, Clotilde; Pulst, Stefan M.; Gibson, Summer; Trojanowski, John Q.; Elman, Lauren; McCluskey, Leo; Grossman, Murray; Shneider, Neil A.; Chung, Wendy K.; Ravits, John M.; Glass, Jonathan D.; Sims, Katherine B.; Van Deerlin, Vivianna M.; Maniatis, Tom; Hayes, Sebastian D.; Ordureau, Alban; Swarup, Sharan; Landers, John; Baas, Frank; Allen, Andrew S.; Bedlack, Richard S.; Harper, J. Wade; Gitler, Aaron D.; Rouleau, Guy A.; Brown, Robert; Harms, Matthew B.; Cooper, Gregory M.; Harris, Tim; Myers, Richard M.; Goldstein, David B.

    2015-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. Here we report the results of a moderate-scale sequencing study aimed at identifying new genes contributing to predisposition for ALS. We performed whole exome sequencing of 2,874 ALS patients and compared them to 6,405 controls. Several known ALS genes were found to be associated, and the non-canonical IκB kinase family TANK-Binding Kinase 1 (TBK1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention. PMID:25700176

  10. Gene Therapy For Ischemic Heart Disease

    PubMed Central

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

    2010-01-01

    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. PMID:20600100

  11. Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways.

    PubMed

    Cirulli, Elizabeth T; Lasseigne, Brittany N; Petrovski, Slavé; Sapp, Peter C; Dion, Patrick A; Leblond, Claire S; Couthouis, Julien; Lu, Yi-Fan; Wang, Quanli; Krueger, Brian J; Ren, Zhong; Keebler, Jonathan; Han, Yujun; Levy, Shawn E; Boone, Braden E; Wimbish, Jack R; Waite, Lindsay L; Jones, Angela L; Carulli, John P; Day-Williams, Aaron G; Staropoli, John F; Xin, Winnie W; Chesi, Alessandra; Raphael, Alya R; McKenna-Yasek, Diane; Cady, Janet; Vianney de Jong, J M B; Kenna, Kevin P; Smith, Bradley N; Topp, Simon; Miller, Jack; Gkazi, Athina; Al-Chalabi, Ammar; van den Berg, Leonard H; Veldink, Jan; Silani, Vincenzo; Ticozzi, Nicola; Shaw, Christopher E; Baloh, Robert H; Appel, Stanley; Simpson, Ericka; Lagier-Tourenne, Clotilde; Pulst, Stefan M; Gibson, Summer; Trojanowski, John Q; Elman, Lauren; McCluskey, Leo; Grossman, Murray; Shneider, Neil A; Chung, Wendy K; Ravits, John M; Glass, Jonathan D; Sims, Katherine B; Van Deerlin, Vivianna M; Maniatis, Tom; Hayes, Sebastian D; Ordureau, Alban; Swarup, Sharan; Landers, John; Baas, Frank; Allen, Andrew S; Bedlack, Richard S; Harper, J Wade; Gitler, Aaron D; Rouleau, Guy A; Brown, Robert; Harms, Matthew B; Cooper, Gregory M; Harris, Tim; Myers, Richard M; Goldstein, David B

    2015-03-27

    Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. We report the results of a moderate-scale sequencing study aimed at increasing the number of genes known to contribute to predisposition for ALS. We performed whole-exome sequencing of 2869 ALS patients and 6405 controls. Several known ALS genes were found to be associated, and TBK1 (the gene encoding TANK-binding kinase 1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention.

  12. Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

    PubMed Central

    SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

    2016-01-01

    Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

  13. Exome Sequencing Identifies Three Novel Candidate Genes Implicated in Intellectual Disability

    PubMed Central

    Azam, Maleeha; Ayub, Humaira; Vissers, Lisenka E. L. M.; Gilissen, Christian; Ali, Syeda Hafiza Benish; Riaz, Moeen; Veltman, Joris A.; Pfundt, Rolph; van Bokhoven, Hans; Qamar, Raheel

    2014-01-01

    Intellectual disability (ID) is a major health problem mostly with an unknown etiology. Recently exome sequencing of individuals with ID identified novel genes implicated in the disease. Therefore the purpose of the present study was to identify the genetic cause of ID in one syndromic and two non-syndromic Pakistani families. Whole exome of three ID probands was sequenced. Missense variations in two plausible novel genes implicated in autosomal recessive ID were identified: lysine (K)-specific methyltransferase 2B (KMT2B), zinc finger protein 589 (ZNF589), as well as hedgehog acyltransferase (HHAT) with a de novo mutation with autosomal dominant mode of inheritance. The KMT2B recessive variant is the first report of recessive Kleefstra syndrome-like phenotype. Identification of plausible causative mutations for two recessive and a dominant type of ID, in genes not previously implicated in disease, underscores the large genetic heterogeneity of ID. These results also support the viewpoint that large number of ID genes converge on limited number of common networks i.e. ZNF589 belongs to KRAB-domain zinc-finger proteins previously implicated in ID, HHAT is predicted to affect sonic hedgehog, which is involved in several disorders with ID, KMT2B associated with syndromic ID fits the epigenetic module underlying the Kleefstra syndromic spectrum. The association of these novel genes in three different Pakistani ID families highlights the importance of screening these genes in more families with similar phenotypes from different populations to confirm the involvement of these genes in pathogenesis of ID. PMID:25405613

  14. Enhancing Plant Disease Resistance without R Genes.

    PubMed

    Sarma, Birinchi Kumar; Singh, Harikesh Bahadur; Fernando, Dilantha; Silva, Roberto Nascimento; Gupta, Vijai Kumar

    2016-07-01

    Crop plants encounter constant biotic challenges, and these challenges have historically been best managed with resistance (R) genes. However, the rapid evolution of new pathogenic strains along with the nonavailability or nonidentification of R genes in cultivated crop species against a large number of plant pathogens have led researchers to think beyond R genes. Biotechnological tools have shown promise in dealing with such challenges. Technologies such as transgenerational plant immunity, interspecies transfer of pattern recognition receptors (PRRs), pathogen-derived resistance (PDR), gene regulation, and expression of antimicrobial peptides (AMPs) in host plants from other plant species have led to enhanced disease resistance and increased food security. PMID:27113633

  15. Analysis of pan-genome to identify the core genes and essential genes of Brucella spp.

    PubMed

    Yang, Xiaowen; Li, Yajie; Zang, Juan; Li, Yexia; Bie, Pengfei; Lu, Yanli; Wu, Qingmin

    2016-04-01

    Brucella spp. are facultative intracellular pathogens, that cause a contagious zoonotic disease, that can result in such outcomes as abortion or sterility in susceptible animal hosts and grave, debilitating illness in humans. For deciphering the survival mechanism of Brucella spp. in vivo, 42 Brucella complete genomes from NCBI were analyzed for the pan-genome and core genome by identification of their composition and function of Brucella genomes. The results showed that the total 132,143 protein-coding genes in these genomes were divided into 5369 clusters. Among these, 1710 clusters were associated with the core genome, 1182 clusters with strain-specific genes and 2477 clusters with dispensable genomes. COG analysis indicated that 44 % of the core genes were devoted to metabolism, which were mainly responsible for energy production and conversion (COG category C), and amino acid transport and metabolism (COG category E). Meanwhile, approximately 35 % of the core genes were in positive selection. In addition, 1252 potential essential genes were predicted in the core genome by comparison with a prokaryote database of essential genes. The results suggested that the core genes in Brucella genomes are relatively conservation, and the energy and amino acid metabolism play a more important role in the process of growth and reproduction in Brucella spp. This study might help us to better understand the mechanisms of Brucella persistent infection and provide some clues for further exploring the gene modules of the intracellular survival in Brucella spp.

  16. Transcriptome analysis reveals mucin 4 to be highly associated with periodontitis and identifies pleckstrin as a link to systemic diseases

    PubMed Central

    Lundmark, Anna; Davanian, Haleh; Båge, Tove; Johannsen, Gunnar; Koro, Catalin; Lundeberg, Joakim; Yucel-Lindberg, Tülay

    2015-01-01

    The multifactorial chronic inflammatory disease periodontitis, which is characterized by destruction of tooth-supporting tissues, has also been implicated as a risk factor for various systemic diseases. Although periodontitis has been studied extensively, neither disease-specific biomarkers nor therapeutic targets have been identified, nor its link with systemic diseases. Here, we analyzed the global transcriptome of periodontitis and compared its gene expression profile with those of other inflammatory conditions, including cardiovascular disease (CVD), rheumatoid arthritis (RA), and ulcerative colitis (UC). Gingival biopsies from 62 patients with periodontitis and 62 healthy subjects were subjected to RNA sequencing. The up-regulated genes in periodontitis were related to inflammation, wounding and defense response, and apoptosis, whereas down-regulated genes were related to extracellular matrix organization and structural support. The most highly up-regulated gene was mucin 4 (MUC4), and its protein product was confirmed to be over-expressed in periodontitis. When comparing the expression profile of periodontitis with other inflammatory diseases, several gene ontology categories, including inflammatory response, cell death, cell motion, and homeostatic processes, were identified as common to all diseases. Only one gene, pleckstrin (PLEK), was significantly overexpressed in periodontitis, CVD, RA, and UC, implicating this gene as an important networking link between these chronic inflammatory diseases. PMID:26686060

  17. Transcriptome analysis reveals mucin 4 to be highly associated with periodontitis and identifies pleckstrin as a link to systemic diseases.

    PubMed

    Lundmark, Anna; Davanian, Haleh; Båge, Tove; Johannsen, Gunnar; Koro, Catalin; Lundeberg, Joakim; Yucel-Lindberg, Tülay

    2015-01-01

    The multifactorial chronic inflammatory disease periodontitis, which is characterized by destruction of tooth-supporting tissues, has also been implicated as a risk factor for various systemic diseases. Although periodontitis has been studied extensively, neither disease-specific biomarkers nor therapeutic targets have been identified, nor its link with systemic diseases. Here, we analyzed the global transcriptome of periodontitis and compared its gene expression profile with those of other inflammatory conditions, including cardiovascular disease (CVD), rheumatoid arthritis (RA), and ulcerative colitis (UC). Gingival biopsies from 62 patients with periodontitis and 62 healthy subjects were subjected to RNA sequencing. The up-regulated genes in periodontitis were related to inflammation, wounding and defense response, and apoptosis, whereas down-regulated genes were related to extracellular matrix organization and structural support. The most highly up-regulated gene was mucin 4 (MUC4), and its protein product was confirmed to be over-expressed in periodontitis. When comparing the expression profile of periodontitis with other inflammatory diseases, several gene ontology categories, including inflammatory response, cell death, cell motion, and homeostatic processes, were identified as common to all diseases. Only one gene, pleckstrin (PLEK), was significantly overexpressed in periodontitis, CVD, RA, and UC, implicating this gene as an important networking link between these chronic inflammatory diseases. PMID:26686060

  18. DRUMS: a human disease related unique gene mutation search engine.

    PubMed

    Li, Zuofeng; Liu, Xingnan; Wen, Jingran; Xu, Ye; Zhao, Xin; Li, Xuan; Liu, Lei; Zhang, Xiaoyan

    2011-10-01

    With the completion of the human genome project and the development of new methods for gene variant detection, the integration of mutation data and its phenotypic consequences has become more important than ever. Among all available resources, locus-specific databases (LSDBs) curate one or more specific genes' mutation data along with high-quality phenotypes. Although some genotype-phenotype data from LSDB have been integrated into central databases little effort has been made to integrate all these data by a search engine approach. In this work, we have developed disease related unique gene mutation search engine (DRUMS), a search engine for human disease related unique gene mutation as a convenient tool for biologists or physicians to retrieve gene variant and related phenotype information. Gene variant and phenotype information were stored in a gene-centred relational database. Moreover, the relationships between mutations and diseases were indexed by the uniform resource identifier from LSDB, or another central database. By querying DRUMS, users can access the most popular mutation databases under one interface. DRUMS could be treated as a domain specific search engine. By using web crawling, indexing, and searching technologies, it provides a competitively efficient interface for searching and retrieving mutation data and their relationships to diseases. The present system is freely accessible at http://www.scbit.org/glif/new/drums/index.html.

  19. Prediction of causal candidate genes in coronary artery disease loci

    PubMed Central

    Brænne, Ingrid; Civelek, Mete; Vilne, Baiba; Di Narzo, Antonio; Johnson, Andrew D.; Zhao, Yuqi; Reiz, Benedikt; Codoni, Veronica; Webb, Thomas R.; Asl, Hassan Foroughi; Hamby, Stephen E.; Zeng, Lingyao; Trégouët, David-Alexandre; Hao, Ke; Topol, Eric J.; Schadt, Eric E.; Yang, Xia; Samani, Nilesh J.; Björkegren, Johan L.M.; Erdmann, Jeanette; Schunkert, Heribert; Lusis, Aldons J.

    2015-01-01

    Objective Genome-wide association studies (GWAS) have so far identified 159 significant and suggestive loci for coronary artery disease (CAD). We now report comprehensive bioinformatics analyses of sequence variation in these loci to predict candidate causal genes. Approach and Results All annotated genes in the loci were evaluated with respect to protein coding SNPs and gene expression parameters. The latter included expression quantitative trait loci, tissue specificity, and miRNA binding. High priority candidate genes were further identified based on literature searches and our experimental data. We conclude that the great majority of causal variations affecting CAD risk occur in non-coding regions, with 41 % affecting gene expression robustly versus 6% leading to amino acid changes. Many of these genes differed from the traditionally annotated genes, which was usually based on proximity to the lead SNP. Indeed, we obtained evidence that genetic variants at CAD loci affect 98 genes which had not been linked to CAD previously. Conclusions Our results substantially revise the list of likely candidates for CAD and suggest that GWAS efforts in other diseases may benefit from similar bioinformatics analyses. PMID:26293461

  20. Gene Therapy Techniques for Peripheral Arterial Disease

    SciTech Connect

    Manninen, Hannu I.; Maekinen, Kimmo

    2002-03-15

    Somatic gene therapy is the introduction of new genetic material into selective somatic cells with resulting therapeutic benefits. Vascular wall and, subsequently, cardiovascular diseases have become an interesting target for gene therapy studies.Arteries are an attractive target for gene therapy since vascular interventions, both open surgical and endovascular, are well suited for minimally invasive, easily monitored gene delivery. Promising therapeutic effects have been obtained in animal models in preventing post-angioplasty restenosis and vein graft thickening, as well as increasing blood flow and collateral development in ischemic limbs.First clinical trials suggest a beneficial effect of vascular endothelial growth factor in achieving therapeutic angiogenesis in chronic limb ischemia and the efficacy of decoy oligonucleotides to prevent infrainguinal vein graft stenosis. However, further studies are mandatory to clarify the safety issues, to develop better gene delivery vectors and delivery catheters, to improve transgene expression, as well as to find the most effective and safe treatment genes.

  1. A computational framework for the prioritization of disease-gene candidates

    PubMed Central

    2015-01-01

    Background The identification of genes and uncovering the role they play in diseases is an important and complex challenge. Genome-wide linkage and association studies have made advancements in identifying genetic variants that underpin human disease. An important challenge now is to identify meaningful disease-associated genes from a long list of candidate genes implicated by these analyses. The application of gene prioritization can enhance our understanding of disease mechanisms and aid in the discovery of drug targets. The integration of protein-protein interaction networks along with disease datasets and contextual information is an important tool in unraveling the molecular basis of diseases. Results In this paper we propose a computational pipeline for the prioritization of disease-gene candidates. Diverse heterogeneous data including: gene-expression, protein-protein interaction network, ontology-based similarity and topological measures and tissue-specific are integrated. The pipeline was applied to prioritize Alzheimer's Disease (AD) genes, whereby a list of 32 prioritized genes was generated. This approach correctly identified key AD susceptible genes: PSEN1 and TRAF1. Biological process enrichment analysis revealed the prioritized genes are modulated in AD pathogenesis including: regulation of neurogenesis and generation of neurons. Relatively high predictive performance (AUC: 0.70) was observed when classifying AD and normal gene expression profiles from individuals using leave-one-out cross validation. Conclusions This work provides a foundation for future investigation of diverse heterogeneous data integration for disease-gene prioritization. PMID:26330267

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

    PubMed Central

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

    2012-01-01

    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. PMID:22735708

  3. Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases.

    PubMed

    Chen, Rong; Shi, Lisong; Hakenberg, Jörg; Naughton, Brian; Sklar, Pamela; Zhang, Jianguo; Zhou, Hanlin; Tian, Lifeng; Prakash, Om; Lemire, Mathieu; Sleiman, Patrick; Cheng, Wei-Yi; Chen, Wanting; Shah, Hardik; Shen, Yulan; Fromer, Menachem; Omberg, Larsson; Deardorff, Matthew A; Zackai, Elaine; Bobe, Jason R; Levin, Elissa; Hudson, Thomas J; Groop, Leif; Wang, Jun; Hakonarson, Hakon; Wojcicki, Anne; Diaz, George A; Edelmann, Lisa; Schadt, Eric E; Friend, Stephen H

    2016-05-01

    Genetic studies of human disease have traditionally focused on the detection of disease-causing mutations in afflicted individuals. Here we describe a complementary approach that seeks to identify healthy individuals resilient to highly penetrant forms of genetic childhood disorders. A comprehensive screen of 874 genes in 589,306 genomes led to the identification of 13 adults harboring mutations for 8 severe Mendelian conditions, with no reported clinical manifestation of the indicated disease. Our findings demonstrate the promise of broadening genetic studies to systematically search for well individuals who are buffering the effects of rare, highly penetrant, deleterious mutations. They also indicate that incomplete penetrance for Mendelian diseases is likely more common than previously believed. The identification of resilient individuals may provide a first step toward uncovering protective genetic variants that could help elucidate the mechanisms of Mendelian diseases and new therapeutic strategies. PMID:27065010

  4. Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes.

    PubMed

    Saunders, Colleen J; Jalali Sefid Dashti, Mahjoubeh; Gamieldien, Junaid

    2016-01-25

    Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening, and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (COL11A2, ELN, ITGB3, LOX) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge, and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies.

  5. Semantic interrogation of a multi knowledge domain ontological model of tendinopathy identifies four strong candidate risk genes

    PubMed Central

    Saunders, Colleen J.; Jalali Sefid Dashti, Mahjoubeh; Gamieldien, Junaid

    2016-01-01

    Tendinopathy is a multifactorial syndrome characterised by tendon pain and thickening, and impaired performance during activity. Candidate gene association studies have identified genetic factors that contribute to intrinsic risk of developing tendinopathy upon exposure to extrinsic factors. Bioinformatics approaches that data-mine existing knowledge for biological relationships may assist with the identification of candidate genes. The aim of this study was to data-mine functional annotation of human genes and identify candidate genes by ontology-seeded queries capturing the features of tendinopathy. Our BioOntological Relationship Graph database (BORG) integrates multiple sources of genomic and biomedical knowledge into an on-disk semantic network where human genes and their orthologs in mouse and rat are central concepts mapped to ontology terms. The BORG was used to screen all human genes for potential links to tendinopathy. Following further prioritisation, four strong candidate genes (COL11A2, ELN, ITGB3, LOX) were identified. These genes are differentially expressed in tendinopathy, functionally linked to features of tendinopathy and previously implicated in other connective tissue diseases. In conclusion, cross-domain semantic integration of multiple sources of biomedical knowledge, and interrogation of phenotypes and gene functions associated with disease, may significantly increase the probability of identifying strong and unobvious candidate genes in genetic association studies. PMID:26804977

  6. A gene-trap strategy identifies quiescence-induced genes in synchronized myoblasts.

    PubMed

    Sambasivan, Ramkumar; Pavlath, Grace K; Dhawan, Jyotsna

    2008-03-01

    Cellular quiescence is characterized not only by reduced mitotic and metabolic activity but also by altered gene expression. Growing evidence suggests that quiescence is not merely a basal state but is regulated by active mechanisms. To understand the molecular programme that governs reversible cell cycle exit, we focused on quiescence-related gene expression in a culture model of myogenic cell arrest and activation. Here we report the identification of quiescence-induced genes using a gene-trap strategy. Using a retroviral vector, we generated a library of gene traps in C2C12 myoblasts that were screened for arrest-induced insertions by live cell sorting (FACS-gal). Several independent gene- trap lines revealed arrest-dependent induction of betagal activity, confirming the efficacy of the FACS screen. The locus of integration was identified in 15 lines. In three lines,insertion occurred in genes previously implicated in the control of quiescence, i.e. EMSY - a BRCA2--interacting protein, p8/com1 - a p300HAT -- binding protein and MLL5 - a SET domain protein. Our results demonstrate that expression of chromatin modulatory genes is induced in G0, providing support to the notion that this reversibly arrested state is actively regulated.

  7. Multiple gene mutations identified in patients infected with influenza A (H7N9) virus.

    PubMed

    Chen, Cuicui; Wang, Mingbang; Zhu, Zhaoqin; Qu, Jieming; Xi, Xiuhong; Tang, Xinjun; Lao, Xiangda; Seeley, Eric; Li, Tao; Fan, Xiaomei; Du, Chunling; Wang, Qin; Yang, Lin; Hu, Yunwen; Bai, Chunxue; Zhang, Zhiyong; Lu, Shuihua; Song, Yuanlin; Zhou, Wenhao

    2016-01-01

    Influenza A (H7N9) virus induced high mortality since 2013. It is important to elucidate the potential genetic variations that contribute to virus infection susceptibilities. In order to identify genetic mutations that might increase host susceptibility to infection, we performed exon sequencing and validated the SNPS by Sanger sequencing on 18 H7N9 patients. Blood samples were collected from 18 confirmed H7N9 patients. The genomic DNA was captured with the Agilent SureSelect Human All Exon kit, sequenced on the Illumina Hiseq 2000, and the resulting data processed and annotated with Genome analysis Tool. SNPs were verified by independent Sanger sequencing. The DAVID database and the DAPPLE database were used to do bioinformatics analysis. Through exon sequencing and Sanger sequencing, we identified 21 genes that were highly associated with H7N9 influenza infection. Protein-protein interaction analysis showed that direct interactions among genetic products were significantly higher than expected (p = 0.004), and DAVID analysis confirmed the defense-related functions of these genes. Gene mutation profiles of survived and non-survived patients were similar, suggesting some of genes identified in this study may be associated with H7N9 influenza susceptibility. Host specific genetic determinants of disease severity identified by this approach may provide new targets for the treatment of H7N9 influenza.

  8. Multiple gene mutations identified in patients infected with influenza A (H7N9) virus.

    PubMed

    Chen, Cuicui; Wang, Mingbang; Zhu, Zhaoqin; Qu, Jieming; Xi, Xiuhong; Tang, Xinjun; Lao, Xiangda; Seeley, Eric; Li, Tao; Fan, Xiaomei; Du, Chunling; Wang, Qin; Yang, Lin; Hu, Yunwen; Bai, Chunxue; Zhang, Zhiyong; Lu, Shuihua; Song, Yuanlin; Zhou, Wenhao

    2016-01-01

    Influenza A (H7N9) virus induced high mortality since 2013. It is important to elucidate the potential genetic variations that contribute to virus infection susceptibilities. In order to identify genetic mutations that might increase host susceptibility to infection, we performed exon sequencing and validated the SNPS by Sanger sequencing on 18 H7N9 patients. Blood samples were collected from 18 confirmed H7N9 patients. The genomic DNA was captured with the Agilent SureSelect Human All Exon kit, sequenced on the Illumina Hiseq 2000, and the resulting data processed and annotated with Genome analysis Tool. SNPs were verified by independent Sanger sequencing. The DAVID database and the DAPPLE database were used to do bioinformatics analysis. Through exon sequencing and Sanger sequencing, we identified 21 genes that were highly associated with H7N9 influenza infection. Protein-protein interaction analysis showed that direct interactions among genetic products were significantly higher than expected (p = 0.004), and DAVID analysis confirmed the defense-related functions of these genes. Gene mutation profiles of survived and non-survived patients were similar, suggesting some of genes identified in this study may be associated with H7N9 influenza susceptibility. Host specific genetic determinants of disease severity identified by this approach may provide new targets for the treatment of H7N9 influenza. PMID:27156515

  9. MICA∗078: A novel allele identified in a Moroccan individual affected by celiac disease.

    PubMed

    Piancatelli, Daniela; Oumhani, Khadija; Benelbarhdadi, Imane; Del Beato, Tiziana; Colanardi, Alessia; Sebastiani, Pierluigi; Tessitore, Alessandra; El Aouad, Rajae; Essaid, Abdellah

    2015-06-01

    A novel MICA allele, MICA(∗)078, has been identified during HLA/MICA high resolution typing of Moroccan patients with celiac disease. MICA(∗)078 shows an uncommon variation at a highly conserved nucleotide position (nt 493, G → A), resulting in one amino acid change at codon 142 (V → I) of MICA gene (compared to MICA(∗)002:01), located in the α2-domain, in which V142 is the common residue.

  10. Identifying Symptom Patterns in People Living With HIV Disease.

    PubMed

    Wilson, Natalie L; Azuero, Andres; Vance, David E; Richman, Joshua S; Moneyham, Linda D; Raper, James L; Heath, Sonya L; Kempf, Mirjam-Colette

    2016-01-01

    Symptoms guide disease management, and patients frequently report HIV-related symptoms, but HIV symptom patterns reported by patients have not been described in the era of improved antiretroviral treatment. The objectives of our study were to investigate the prevalence and burden of symptoms in people living with HIV and attending an outpatient clinic. The prevalence, burden, and bothersomeness of symptoms reported by patients in routine clinic visits during 2011 were assessed using the 20-item HIV Symptom Index. Principal component analysis was used to identify symptom clusters and relationships between groups using appropriate statistic techniques. Two main clusters were identified. The most prevalent and bothersome symptoms were muscle aches/joint pain, fatigue, and poor sleep. A third of patients had seven or more symptoms, including the most burdensome symptoms. Even with improved antiretroviral drug side-effect profiles, symptom prevalence and burden, independent of HIV viral load and CD4+ T cell count, are high.

  11. Identifying Symptom Patterns in People Living With HIV Disease

    PubMed Central

    Wilson, Natalie L.; Azuero, Andres; Vance, David E.; Richman, Joshua S.; Moneyham, Linda D.; Raper, James L.; Heath, Sonya L.; Kempf, Mirjam-Colette

    2016-01-01

    Symptoms guide disease management, and patients frequently report HIV-related symptoms, but HIV symptom patterns reported by patients have not been described in the era of improved antiretroviral treatment. The objectives of our study were to investigate the prevalence and burden of symptoms in people living with HIV and attending an outpatient clinic. The prevalence, burden, and bothersomeness of symptoms reported by patients in routine clinic visits during 2011 were assessed using the 20-item HIV Symptom Index. Principal component analysis was used to identify symptom clusters and relationships between groups using appropriate statistic techniques. Two main clusters were identified. The most prevalent and bothersome symptoms were muscle aches/joint pain, fatigue, and poor sleep. A third of patients had seven or more symptoms, including the most burdensome symptoms. Even with improved antiretroviral drug side-effect profiles, symptom prevalence and burden, independent of HIV viral load and CD4+ T cell count, are high. PMID:26790340

  12. Identifying concerted evolution and gene conversion in mammalian gene pairs lasting over 100 million years

    PubMed Central

    Carson, Andrew R; Scherer, Stephen W

    2009-01-01

    Background Concerted evolution occurs in multigene families and is characterized by stretches of homogeneity and higher sequence similarity between paralogues than between orthologues. Here we identify human gene pairs that have undergone concerted evolution, caused by ongoing gene conversion, since at least the human-mouse divergence. Our strategy involved the identification of duplicated genes with greater similarity within a species than between species. These genes were required to be present in multiple mammalian genomes, suggesting duplication early in mammalian divergence. To eliminate genes that have been conserved due to strong purifying selection, our analysis also required at least one intron to have retained high sequence similarity between paralogues. Results We identified three human gene pairs undergoing concerted evolution (BMP8A/B, DDX19A/B, and TUBG1/2). Phylogenetic investigations reveal that in each case the duplication appears to have occurred prior to eutherian mammalian radiation, with exactly two paralogues present in all examined species. This indicates that all three gene duplication events were established over 100 million years ago. Conclusion The extended duration of concerted evolution in multiple distant lineages suggests that there has been prolonged homogenization of specific segments within these gene pairs. Although we speculate that selection for homogenization could have been utilized in order to maintain crucial homo- or hetero- binding domains, it remains unclear why gene conversion has persisted for such extended periods of time. Through these analyses, our results demonstrate additional examples of a process that plays a definite, although unspecified, role in molecular evolution. PMID:19583854

  13. Curing genetic disease with gene therapy.

    PubMed

    Williams, David A

    2014-01-01

    Development of viral vectors that allow high efficiency gene transfer into mammalian cells in the early 1980s foresaw the treatment of severe monogenic diseases in humans. The application of gene transfer using viral vectors has been successful in diseases of the blood and immune systems, albeit with several curative studies also showing serious adverse events (SAEs). In children with X-linked severe combined immunodeficiency (SCID-X1), chronic granulomatous disease, and Wiskott-Aldrich syndrome, these SAEs were caused by inappropriate activation of oncogenes. Subsequent studies have defined the vector sequences responsible for these transforming events. Members of the Transatlantic Gene Therapy Consortium [TAGTC] have collaboratively developed new vectors that have proven safer in preclinical studies and used these vectors in new clinical trials in SCID-X1. These trials have shown evidence of early efficacy and preliminary integration analysis data from the SCID-X1 trial suggest an improved safety profile.

  14. [Huntington's disease--advances in gene mapping].

    PubMed

    Nakamura, S

    1993-09-01

    Huntington's disease (HD) is a progressive neurodegenerative disorder characterized by motor disturbance, cognitive loss, and psychiatric manifestations. It is inherited in an autosomal dominant fashion. The genetic defect causing HD was assigned to chromosome 4 in 1983 using polymorphic DNA markers in humans. Thereafter, a location cloning approach was pursued to isolate and characterize the HD gene. Recently, the Huntington's disease collaborative research group has isolated a new gene, IT 15, in 4p 16.3. IT 15 contains a polymorphic trinucleotide repeat that is expanded and unstable on HD chromosomes. A (CAG)n repeat longer than the normal range was observed on HD chromosomes from disease families. The (CAG)n repeat appears to be located within the coding sequence of a predicted 348 kd protein that is unrelated to any known gene.

  15. On the Identifiability of Transmission Dynamic Models for Infectious Diseases.

    PubMed

    Lintusaari, Jarno; Gutmann, Michael U; Kaski, Samuel; Corander, Jukka

    2016-03-01

    Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models presents two challenges: (1) the likelihood function of the models is generally not computable, and computationally intensive simulation-based inference methods need to be employed, and (2) the model may not be fully identifiable from the available data. While the first difficulty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identifiability issues may lead to inferences that are driven more by prior assumptions than by the data themselves. We consider a popular and relatively simple yet analytically intractable model for the spread of tuberculosis based on classical IS6110 fingerprinting data. We report on the identifiability of the model, also presenting some methodological advances regarding the inference. Using likelihood approximations, we show that the reproductive value cannot be identified from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are influenced by the assumed infectious population size, which generally has been kept fixed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with sufficient precision.

  16. On the Identifiability of Transmission Dynamic Models for Infectious Diseases.

    PubMed

    Lintusaari, Jarno; Gutmann, Michael U; Kaski, Samuel; Corander, Jukka

    2016-03-01

    Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models presents two challenges: (1) the likelihood function of the models is generally not computable, and computationally intensive simulation-based inference methods need to be employed, and (2) the model may not be fully identifiable from the available data. While the first difficulty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identifiability issues may lead to inferences that are driven more by prior assumptions than by the data themselves. We consider a popular and relatively simple yet analytically intractable model for the spread of tuberculosis based on classical IS6110 fingerprinting data. We report on the identifiability of the model, also presenting some methodological advances regarding the inference. Using likelihood approximations, we show that the reproductive value cannot be identified from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are influenced by the assumed infectious population size, which generally has been kept fixed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with sufficient precision. PMID:26739450

  17. Parkinson's disease candidate gene prioritization based on expression profile of midbrain dopaminergic neurons

    PubMed Central

    2010-01-01

    Background Parkinson's disease is the second most common neurodegenerative disorder. The pathological hallmark of the disease is degeneration of midbrain dopaminergic neurons. Genetic association studies have linked 13 human chromosomal loci to Parkinson's disease. Identification of gene(s), as part of the etiology of Parkinson's disease, within the large number of genes residing in these loci can be achieved through several approaches, including screening methods, and considering appropriate criteria. Since several of the indentified Parkinson's disease genes are expressed in substantia nigra pars compact of the midbrain, expression within the neurons of this area could be a suitable criterion to limit the number of candidates and identify PD genes. Methods In this work we have used the combination of findings from six rodent transcriptome analysis studies on the gene expression profile of midbrain dopaminergic neurons and the PARK loci in OMIM (Online Mendelian Inheritance in Man) database, to identify new candidate genes for Parkinson's disease. Results Merging the two datasets, we identified 20 genes within PARK loci, 7 of which are located in an orphan Parkinson's disease locus and one, which had been identified as a disease gene. In addition to identifying a set of candidates for further genetic association studies, these results show that the criteria of expression in midbrain dopaminergic neurons may be used to narrow down the number of genes in PARK loci for such studies. PMID:20716345

  18. Gene therapy in Alzheimer's disease - potential for disease modification.

    PubMed

    Nilsson, Per; Iwata, Nobuhisa; Muramatsu, Shin-ichi; Tjernberg, Lars O; Winblad, Bengt; Saido, Takaomi C

    2010-04-01

    Alzheimer's disease (AD) is the major cause of dementia in the elderly, leading to memory loss and cognitive decline. The mechanism underlying onset of the disease has not been fully elucidated. However, characteristic pathological manifestations include extracellular accumulation and aggregation of the amyloid beta-peptide (Abeta) into plaques and intracellular accumulation and aggregation of hyperphosphorylated tau, forming neurofibrillary tangles. Despite extensive research worldwide, no disease modifying treatment is yet available. In this review, we focus on gene therapy as a potential treatment for AD, and summarize recent work in the field, ranging from proof-of-concept studies in animal models to clinical trials. The multifactorial causes of AD offer a variety of possible targets for gene therapy, including two neurotrophic growth factors, nerve growth factor and brain-derived neurotrophic factor, Abeta-degrading enzymes, such as neprilysin, endothelin-converting enzyme and cathepsin B, and AD associated apolipoprotein E. This review also discusses advantages and drawbacks of various rapidly developing virus-mediated gene delivery techniques for gene therapy. Finally, approaches aiming at down-regulating amyloid precursor protein (APP) and beta-site APP cleaving enzyme 1 levels by means of siRNA-mediated knockdown are briefly summarized. Overall, the prospects appear hopeful that gene therapy has the potential to be a disease modifying treatment for AD.

  19. Mitigating false-positive associations in rare disease gene discovery.

    PubMed

    Akle, Sebastian; Chun, Sung; Jordan, Daniel M; Cassa, Christopher A

    2015-10-01

    Clinical sequencing is expanding, but causal variants are still not identified in the majority of cases. These unsolved cases can aid in gene discovery when individuals with similar phenotypes are identified in systems such as the Matchmaker Exchange. We describe risks for gene discovery in this growing set of unsolved cases. In a set of rare disease cases with the same phenotype, it is not difficult to find two individuals with the same phenotype that carry variants in the same gene. We quantify the risk of false-positive association in a cohort of individuals with the same phenotype, using the prior probability of observing a variant in each gene from over 60,000 individuals (Exome Aggregation Consortium). Based on the number of individuals with a genic variant, cohort size, specific gene, and mode of inheritance, we calculate a P value that the match represents a true association. A match in two of 10 patients in MECP2 is statistically significant (P = 0.0014), whereas a match in TTN would not reach significance, as expected (P > 0.999). Finally, we analyze the probability of matching in clinical exome cases to estimate the number of cases needed to identify genes related to different disorders. We offer Rare Disease Match, an online tool to mitigate the uncertainty of false-positive associations. PMID:26378430

  20. Mitigating false-positive associations in rare disease gene discovery.

    PubMed

    Akle, Sebastian; Chun, Sung; Jordan, Daniel M; Cassa, Christopher A

    2015-10-01

    Clinical sequencing is expanding, but causal variants are still not identified in the majority of cases. These unsolved cases can aid in gene discovery when individuals with similar phenotypes are identified in systems such as the Matchmaker Exchange. We describe risks for gene discovery in this growing set of unsolved cases. In a set of rare disease cases with the same phenotype, it is not difficult to find two individuals with the same phenotype that carry variants in the same gene. We quantify the risk of false-positive association in a cohort of individuals with the same phenotype, using the prior probability of observing a variant in each gene from over 60,000 individuals (Exome Aggregation Consortium). Based on the number of individuals with a genic variant, cohort size, specific gene, and mode of inheritance, we calculate a P value that the match represents a true association. A match in two of 10 patients in MECP2 is statistically significant (P = 0.0014), whereas a match in TTN would not reach significance, as expected (P > 0.999). Finally, we analyze the probability of matching in clinical exome cases to estimate the number of cases needed to identify genes related to different disorders. We offer Rare Disease Match, an online tool to mitigate the uncertainty of false-positive associations.

  1. Gene therapy for human genetic disease?

    PubMed

    Friedmann, T; Roblin, R

    1972-03-01

    In our view, gene therapy may ameliorate some human genetic diseases in the future. For this reason, we believe that research directed at the development of techniques for gene therapy should continue. For the foreseeable future, however, we oppose any further attempts at gene therapy in human patients because (i) our understanding of such basic processes as gene regulation and genetic recombination in human cells is inadequate; (ii) our understanding of the details of the relation between the molecular defect and the disease state is rudimentary for essentially all genetic diseases; and (iii) we have no information on the short-range and long-term side effects of gene therapy. We therefore propose that a sustained effort be made to formulate a complete set of ethicoscientific criteria to guide the development and clinical application of gene therapy techniques. Such an endeavor could go a long way toward ensuring that gene therapy is used in humans only in those instances where it will prove beneficial, and toward preventing its misuse through premature application. Two recent papers have provided new demonstrations of directed genetic modification of mammalian cells. Munyon et al. (44) restored the ability to synthesize the enzyme thymidine kinase to thymidine kinase-deficient mouse cells by infection with ultraviolet-irradiated herpes simplex virus. In their experiments the DNA from herpes simplex virus, which contains a gene coding for thymidine kinase, may have formed a hereditable association with the mouse cells. Merril et al. (45) reported that treatment of fibroblasts from patients with galactosemia with exogenous DNA caused increased activity of a missing enzyme, alpha-D-galactose-l-phosphate uridyltransferase. They also provided some evidence that the change persisted after subculturing the treated cells. If this latter report can be confirmed, the feasibility of directed genetic modification of human cells would be clearly demonstrated, considerably

  2. Gene-Trap Mutagenesis Identifies Mammalian Genes Contributing to Intoxication by Clostridium perfringens ε-Toxin

    PubMed Central

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

    2011-01-01

    The Clostridium perfringens ε-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 ε-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 ε-toxin, was used to select clones of cells resistant to ε-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 ε-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 ε-toxin-induced cytotoxicity. Additionally, ε-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 ε-toxin induces cell death and new targets for potential therapeutic intervention. PMID:21412435

  3. Identifying Unstable Regions of Proteins Involved in Misfolding Diseases

    NASA Astrophysics Data System (ADS)

    Guest, Will; Cashman, Neil; Plotkin, Steven

    2009-05-01

    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 regions of a protein using three methods to parameterize energy changes: a modified G=o model, changes in solvent-accessible surface area, and all-atoms molecular dynamics. The entropic effects of disulfide bonds and post-translational modifications are treated analytically. It incorporates a novel method for finding local dielectric constants inside a protein to accurately handle charge effects. We have predicted the unstable parts of prion protein and superoxide dismutase 1, the proteins involved in CJD and fALS respectively, and have used these regions as epitopes to prepare antibodies that are specific to the misfolded conformation and show promise as therapeutic agents.

  4. A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

    PubMed

    Jiang, Peng; Scarpa, Joseph R; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D; Hao, Ke; Summa, Keith C; Yang, He S; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

    2015-05-01

    Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders.

  5. Combining gene expression and genetic analyses to identify candidate genes involved in cold responses in pea.

    PubMed

    Legrand, Sylvain; Marque, Gilles; Blassiau, Christelle; Bluteau, Aurélie; Canoy, Anne-Sophie; Fontaine, Véronique; Jaminon, Odile; Bahrman, Nasser; Mautord, Julie; Morin, Julie; Petit, Aurélie; Baranger, Alain; Rivière, Nathalie; Wilmer, Jeroen; Delbreil, Bruno; Lejeune-Hénaut, Isabelle

    2013-09-01

    Cold stress affects plant growth and development. In order to better understand the responses to cold (chilling or freezing tolerance), we used two contrasted pea lines. Following a chilling period, the Champagne line becomes tolerant to frost whereas the Terese line remains sensitive. Four suppression subtractive hybridisation libraries were obtained using mRNAs isolated from pea genotypes Champagne and Terese. Using quantitative polymerase chain reaction (qPCR) performed on 159 genes, 43 and 54 genes were identified as differentially expressed at the initial time point and during the time course study, respectively. Molecular markers were developed from the differentially expressed genes and were genotyped on a population of 164 RILs derived from a cross between Champagne and Terese. We identified 5 candidate genes colocalizing with 3 different frost damage quantitative trait loci (QTL) intervals and a protein quantity locus (PQL) rich region previously reported. This investigation revealed the role of constitutive differences between both genotypes in the cold responses, in particular with genes related to glycine degradation pathway that could confer to Champagne a better frost tolerance. We showed that freezing tolerance involves a decrease of expression of genes related to photosynthesis and the expression of a gene involved in the production of cysteine and methionine that could act as cryoprotectant molecules. Although it remains to be confirmed, this study could also reveal the involvement of the jasmonate pathway in the cold responses, since we observed that two genes related to this pathway were mapped in a frost damage QTL interval and in a PQL rich region interval, respectively.

  6. Identifying glycoside hydrolase family 18 genes in the mycoparasitic fungal species Clonostachys rosea.

    PubMed

    Tzelepis, Georgios; Dubey, Mukesh; Jensen, Dan Funck; Karlsson, Magnus

    2015-07-01

    Clonostachysrosea is a mycoparasitic fungal species that is an efficient biocontrol agent against many plant diseases. During mycoparasitic interactions, one of the most crucial steps is the hydrolysis of the prey's fungal cell wall, which mainly consists of glucans, glycoproteins and chitin. Chitinases are hydrolytic enzymes responsible for chitin degradation and it is suggested that they play an important role in fungal-fungal interactions. Fungal chitinases belong exclusively to the glycoside hydrolase (GH) family 18.These GH18 proteins are categorized into three distinct phylogenetic groups (A, B and C), subdivided into several subgroups. In this study, we identified 14 GH18 genes in the C. rosea genome, which is remarkably low compared with the high numbers found in mycoparasitic Trichoderma species. Phylogenetic analysis revealed that C. rosea contains eight genes in group A, two genes in group B, two genes in group C, one gene encoding a putative ENGase (endo-β-N-acetylglucosaminidase) and the ech37 gene, which is of bacterial origin. Gene expression analysis showed that only two genes had higher transcription levels during fungal-fungal interactions, while eight out of 14 GH18 genes were triggered by chitin. Furthermore, deletion of the C group chiC2 gene decreased the growth inhibitory activity of C. rosea culture filtrates against Botrytis cinerea and Rhizoctonia solani, although the biocontrol ability of C. rosea against B. cinerea was not affected. In addition, a potential role of the CHIC2 chitinase in the sporulation process was revealed. These results provide new information about the role of GH18 proteins in mycoparasitic interactions.

  7. Age-associated bidirectional modulation of gene expression in single identified R15 neuron of Aplysia

    PubMed Central

    2013-01-01

    Background Despite the advances in our understanding of aging-associated behavioral decline, relatively little is known about how aging affects neural circuits that regulate specific behaviors, particularly the expression of genes in specific neural circuits during aging. We have addressed this by exploring a peptidergic neuron R15, an identified neuron of the marine snail Aplysia californica. R15 is implicated in reproduction and osmoregulation and responds to neurotransmitters such as acetylcholine, serotonin and glutamate and is characterized by its action potential bursts. Results We examined changes in gene expression in R15 neurons during aging by microarray analyses of RNAs from two different age groups, mature and old animals. Specifically we find that 1083 ESTs are differentially regulated in mature and old R15 neurons. Bioinformatics analyses of these genes have identified specific biological pathways that are up or downregulated in mature and old neurons. Comparison with human signaling networks using pathway analyses have identified three major networks [(1) cell signaling, cell morphology, and skeletal muscular system development (2) cell death and survival, cellular function maintenance and embryonic development and (3) neurological diseases, developmental and hereditary disorders] altered in old R15 neurons. Furthermore, qPCR analysis of single R15 neurons to quantify expression levels of candidate regulators involved in transcription (CREB1) and translation (S6K) showed that aging is associated with a decrease in expression of these regulators, and similar analysis in three other neurons (L7, L11 and R2) showed that gene expression change during aging could be bidirectional. Conclusions We find that aging is associated with bidirectional changes in gene expression. Detailed bioinformatics analyses and human homolog searches have identified specific biological processes and human-relevant signaling pathways in R15 that are affected during aging

  8. Clinical Markers for Identifying Cholinergic Deficits in Parkinson's Disease

    PubMed Central

    Müller, Martijn L.T.M.; Bohnen, Nicolaas I.; Kotagal, Vikas; Scott, Peter J.H.; Koeppe, Robert A.; Frey, Kirk A.; Albin, Roger L.

    2014-01-01

    Background Cholinergic projection systems degeneration is associated with dopamine non-responsive features of Parkinson's disease (PD). Cholinergic deficits are variable in non-demented PD. Identification of cholinergic deficits in PD may help with selection of suitable patients for targeted cholinergic drug treatment in PD. The objective of this retrospective multivariate predictor analysis study was to identify clinical markers indicative of cholinergic deficits in PD patients, as assessed by acetylcholinesterase ([11C]PMP) positron emission tomography. Methods One hundred thirty-seven PD patients (34 female) participated; median modified Hoehn and Yahr score was 2.5 (range 1–4), average age of 65.6 ± 7.4 years, and average duration of motor disease symptoms of 6.0 ± 4.2 years. Subjects were dichotomized as “normocholinergic” or “hypocholinergic” based on a 5th percentile cutoff from normal for the basal forebrain-cortical and pedunculopontine nucleus-thalamic cholinergic projection systems. Previously identified clinical indices of cholinergic denervation were used for statistical prediction of cholinergic deficits. Logistic regression determined which risk factors predicted cholinergic deficits. Sensitivity, specificity, and accuracy were determined for the (combinations of) significant predictor variables. Results There were 49 (35.8%) hypocholinergic PD subjects. The combination of RBD symptoms and fall history showed highest diagnostic accuracy (81.1%) for predicting combined thalamic and cortical cholinergic deficits. A combined assessment of 8.5 meter walk time and lower score on the Montreal cognitive assessment scale provided diagnostic accuracy of 80.7 % for predicting isolated cortical cholinergic denervation. Conclusion Assessment of clinical indices of cholinergic denervation may be useful for identifying suitable subjects for trials of targeted cholinergic drug treatments in PD. PMID:25393613

  9. Next-Generation Sequencing Identifies Transportin 3 as the Causative Gene for LGMD1F

    PubMed Central

    Mutarelli, Margherita; Peterle, Enrico; Del Vecchio Blanco, Francesca; Rispoli, Rossella; Savarese, Marco; Garofalo, Arcomaria; Piluso, Giulio; Morandi, Lucia; Ricci, Giulia; Siciliano, Gabriele; Angelini, Corrado; Nigro, Vincenzo

    2013-01-01

    Limb-girdle muscular dystrophies (LGMD) are genetically and clinically heterogeneous conditions. We investigated a large family with autosomal dominant transmission pattern, previously classified as LGMD1F and mapped to chromosome 7q32. Affected members are characterized by muscle weakness affecting earlier the pelvic girdle and the ileopsoas muscles. We sequenced the whole exome of four family members and identified a shared heterozygous frame-shift variant in the Transportin 3 (TNPO3) gene, encoding a member of the importin-β super-family. The TNPO3 gene is mapped within the LGMD1F critical interval and its 923-amino acid human gene product is also expressed in skeletal muscle. In addition, we identified an isolated case of LGMD with a new missense mutation in the same gene. We localized the mutant TNPO3 around the nucleus, but not inside. The involvement of gene related to the nuclear transport suggests a novel disease mechanism leading to muscular dystrophy. PMID:23667635

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

    PubMed

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

    2014-06-01

    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

  11. A Genome-Wide Methylation Approach Identifies a New Hypermethylated Gene Panel in Ulcerative Colitis

    PubMed Central

    Kang, Keunsoo; Bae, Jin-Han; Han, Kyudong; Kim, Eun Soo; Kim, Tae-Oh; Yi, Joo Mi

    2016-01-01

    The cause of inflammatory bowel disease (IBD) is still unknown, but there is growing evidence that environmental factors such as epigenetic changes can contribute to the disease etiology. The aim of this study was to identify newly hypermethylated genes in ulcerative colitis (UC) using a genome-wide DNA methylation approach. Using an Infinium HumanMethylation450 BeadChip array, we screened the DNA methylation changes in three normal colon controls and eight UC patients. Using these methylation profiles, 48 probes associated with CpG promoter methylation showed differential hypermethylation between UC patients and normal controls. Technical validations for methylation analyses in a larger series of UC patients (n = 79) were performed by methylation-specific PCR (MSP) and bisulfite sequencing analysis. We finally found that three genes (FAM217B, KIAA1614 and RIBC2) that were significantly elevating the promoter methylation levels in UC compared to normal controls. Interestingly, we confirmed that three genes were transcriptionally silenced in UC patient samples by qRT-PCR, suggesting that their silencing is correlated with the promoter hypermethylation. Pathway analyses were performed using GO and KEGG databases with differentially hypermethylated genes in UC. Our results highlight that aberrant hypermethylation was identified in UC patients which can be a potential biomarker for detecting UC. Moreover, pathway-enriched hypermethylated genes are possibly implicating important cellular function in the pathogenesis of UC. Overall, this study describes a newly hypermethylated gene panel in UC patients and provides new clinical information that can be used for the diagnosis and therapeutic treatment of IBD. PMID:27517910

  12. A Genome-Wide Methylation Approach Identifies a New Hypermethylated Gene Panel in Ulcerative Colitis.

    PubMed

    Kang, Keunsoo; Bae, Jin-Han; Han, Kyudong; Kim, Eun Soo; Kim, Tae-Oh; Yi, Joo Mi

    2016-01-01

    The cause of inflammatory bowel disease (IBD) is still unknown, but there is growing evidence that environmental factors such as epigenetic changes can contribute to the disease etiology. The aim of this study was to identify newly hypermethylated genes in ulcerative colitis (UC) using a genome-wide DNA methylation approach. Using an Infinium HumanMethylation450 BeadChip array, we screened the DNA methylation changes in three normal colon controls and eight UC patients. Using these methylation profiles, 48 probes associated with CpG promoter methylation showed differential hypermethylation between UC patients and normal controls. Technical validations for methylation analyses in a larger series of UC patients (n = 79) were performed by methylation-specific PCR (MSP) and bisulfite sequencing analysis. We finally found that three genes (FAM217B, KIAA1614 and RIBC2) that were significantly elevating the promoter methylation levels in UC compared to normal controls. Interestingly, we confirmed that three genes were transcriptionally silenced in UC patient samples by qRT-PCR, suggesting that their silencing is correlated with the promoter hypermethylation. Pathway analyses were performed using GO and KEGG databases with differentially hypermethylated genes in UC. Our results highlight that aberrant hypermethylation was identified in UC patients which can be a potential biomarker for detecting UC. Moreover, pathway-enriched hypermethylated genes are possibly implicating important cellular function in the pathogenesis of UC. Overall, this study describes a newly hypermethylated gene panel in UC patients and provides new clinical information that can be used for the diagnosis and therapeutic treatment of IBD. PMID:27517910

  13. Progressive retinal atrophy in Schapendoes dogs: mutation of the newly identified CCDC66 gene.

    PubMed

    Dekomien, Gabriele; Vollrath, Conni; Petrasch-Parwez, Elisabeth; Boevé, Michael H; Akkad, Denis A; Gerding, Wanda M; Epplen, Jörg T

    2010-05-01

    Canine generalized progressive retinal atrophy (gPRA) is characterized by continuous degeneration of photoreceptor cells leading to night blindness and progressive vision loss. Until now, mutations in 11 genes have been described that account for gPRA in dogs, mostly following an autosomal recessive inheritance mode. Here, we describe a gPRA locus comprising the newly identified gene coiled-coil domain containing 66 (CCDC66) on canine chromosome 20, as identified via linkage analysis in the Schapendoes breed. Mutation screening of the CCDC66 gene revealed a 1-bp insertion in exon 6 leading to a stop codon as the underlying cause of disease. The insertion is present in all affected dogs in the homozygous state as well as in all obligatory mutation carriers in the heterozygous state. The CCDC66 gene is evolutionarily conserved in different vertebrate species and exhibits a complex pattern of differential RNA splicing resulting in various isoforms in the retina. Immunohistochemically, CCDC66 protein is detected mainly in the inner segments of photoreceptors in mouse, dog, and man. The affected Schapendoes retina lacks CCDC66 protein. Thus this natural canine model for gPRA yields superior potential to understand functional implications of this newly identified protein including its physiology, and it opens new perspectives for analyzing different aspects of the general pathophysiology of gPRA. PMID:19777273

  14. Alexander disease: a review and the gene.

    PubMed

    Johnson, Anne B

    2002-01-01

    This review presents historical and clinical information on the rare human brain disorder known as Alexander disease (ALX), and reports on the recent discovery of the gene that appears to be causative. The disease is a fatal, white matter disorder (leukodystrophy) of childhood. Adult onset cases also have been described, but it has not been clear whether they represent the same disease. Until recently the diagnosis was made by the pathological examination of brain tissue, in which abundant Rosenthal fibers were found. These abnormal structures occurred within astrocytes, but their composition was unclear. In 1985, a child underwent a diagnostic brain biopsy at this institution, which established the diagnosis of ALX. Ultrastructural immunocytochemistry revealed that the Rosenthal fibers contained abundant amounts of glial fibrillary acidic protein (GFAP), a normal component of astocytic intermediate filaments. Thus, the gene for this filament protein was considered a candidate gene for the cause of ALX, and DNA samples from children presumed or proven to have this disorder were banked for future study. Other work on the same brain biopsy showed that Rosenthal fibers also contained abundant alphaB-crystallin, a heat shock protein, but no defect was found in its gene. A decade after the biopsy, a transgenic mouse with an extra copy of the gene for GFAP was produced. These mice died early and their brains contained Rosenthal fibers. Although not an exact model for ALX, this also suggested that the gene for GFAP should be considered a candidate gene for ALX. Subsequent research has demonstrated that the great majority of childhood ALX cases contain mutations in the gene for GFAP. This work is now being extended as a diagnostic test, as well as to seek understanding of the pathogenesis of ALX and possible approaches for treatment.

  15. Prediction of disease-gene-drug relationships following a differential network analysis.

    PubMed

    Zickenrott, S; Angarica, V E; Upadhyaya, B B; del Sol, A

    2016-01-01

    Great efforts are being devoted to get a deeper understanding of disease-related dysregulations, which is central for introducing novel and more effective therapeutics in the clinics. However, most human diseases are highly multifactorial at the molecular level, involving dysregulation of multiple genes and interactions in gene regulatory networks. This issue hinders the elucidation of disease mechanism, including the identification of disease-causing genes and regulatory interactions. Most of current network-based approaches for the study of disease mechanisms do not take into account significant differences in gene regulatory network topology between healthy and disease phenotypes. Moreover, these approaches are not able to efficiently guide database search for connections between drugs, genes and diseases. We propose a differential network-based methodology for identifying candidate target genes and chemical compounds for reverting disease phenotypes. Our method relies on transcriptomics data to reconstruct gene regulatory networks corresponding to healthy and disease states separately. Further, it identifies candidate genes essential for triggering the reversion of the disease phenotype based on network stability determinants underlying differential gene expression. In addition, our method selects and ranks chemical compounds targeting these genes, which could be used as therapeutic interventions for complex diseases.

  16. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

    PubMed Central

    Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation. PMID:27559342

  17. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

    PubMed

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

  18. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

    PubMed

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation. PMID:27559342

  19. Identifying Dysregulated Genes Induced by Kaposi's Sarcoma-associated Herpesvirus (KSHV)

    PubMed Central

    Alcendor, Donald; Knobel, Susan

    2010-01-01

    Currently KS is the most predominant HIV/AIDS related malignancy in Southern Africa and hence the world.1,2 It is characterized as an angioproliferative tumor of vascular endothelial cells and produces rare B cell lymphoproliferative diseases in the form of pleural effusion lymphomas (PEL) and some forms of multicentric Castleman's disease.3-5 Only 1-5% of cells in KS lesions actively support lytic replication of Kaposi's sarcoma-associated herpesvirus (KSHV), the etiological agent associated with KS, and it is clear that cellular factors must interact with viral factors in the process of oncogenesis and tumor progression.6,7 Identifying novel host-factor determinants which contribute to KS pathology is essential for developing prognostic markers for tumor progression and metastasis as well as for developing novel therapeutics for the treatment of KS.8 The accompanying video details the methods we use to identify host cell gene expression programs altered in dermal microvascular endothelial cells (DMVEC) after KSHV infection and in KS tumor tissue.9 Once dysregulated genes are identified by microarray analysis, changes in protein expression are confirmed by immunoblot and dual labeled immunofluorescence. Changes in transcriptional expression of dysregulated genes are confirmed in vitro by quantitative real-time polymerase chain reaction (qRT-PCR). Validation of in vitro findings using archival KS tumor tissue is also performed by dual labeled immunochemistry and tissue microarrays.8,10 Our approach to identifying dysregulated genes in the KS tumor tissue microenvironment will allow the development of in vitro and subsequently in vivo model systems for discovery and evaluation of potential novel therapeutic for the treatment of KS. PMID:20864930

  20. Syndrome to gene (S2G): in-silico identification of candidate genes for human diseases.

    PubMed

    Gefen, Avitan; Cohen, Raphael; Birk, Ohad S

    2010-03-01

    The identification of genomic loci associated with human genetic syndromes has been significantly facilitated through the generation of high density SNP arrays. However, optimal selection of candidate genes from within such loci is still a tedious labor-intensive bottleneck. Syndrome to Gene (S2G) is based on novel algorithms which allow an efficient search for candidate genes in a genomic locus, using known genes whose defects cause phenotypically similar syndromes. S2G (http://fohs.bgu.ac.il/s2g/index.html) includes two components: a phenotype Online Mendelian Inheritance in Man (OMIM)-based search engine that alleviates many of the problems in the existing OMIM search engine (negation phrases, overlapping terms, etc.). The second component is a gene prioritizing engine that uses a novel algorithm to integrate information from 18 databases. When the detailed phenotype of a syndrome is inserted to the web-based software, S2G offers a complete improved search of the OMIM database for similar syndromes. The software then prioritizes a list of genes from within a genomic locus, based on their association with genes whose defects are known to underlie similar clinical syndromes. We demonstrate that in all 30 cases of novel disease genes identified in the past year, the disease gene was within the top 20% of candidate genes predicted by S2G, and in most cases--within the top 10%. Thus, S2G provides clinicians with an efficient tool for diagnosis and researchers with a candidate gene prediction tool based on phenotypic data and a wide range of gene data resources. S2G can also serve in studies of polygenic diseases, and in finding interacting molecules for any gene of choice.

  1. Gene Therapy for "Bubble Boy" Disease.

    PubMed

    Hoggatt, Jonathan

    2016-07-14

    Adenosine deaminase (ADA) deficiency results in the accumulation of toxic metabolites that destroy the immune system, causing severe combined immunodeficiency (ADA-SCID), often referred to as the "bubble boy" disease. Strimvelis is a European Medicines Agency approved gene therapy for ADA-SCID patients without a suitable bone marrow donor.

  2. Murine candidate bleomycin induced pulmonary fibrosis susceptibility genes identified by gene expression and sequence analysis of linkage regions

    PubMed Central

    Haston, C; Tomko, T; Godin, N; Kerckhoff, L; Hallett, M

    2005-01-01

    Background: Pulmonary fibrosis is a complex disease for which the predisposing genetic variants remain unknown. In a prior study, susceptibility to bleomycin induced pulmonary fibrosis was mapped to loci Blmpf1 and Blmpf2 on chromosomes 17 and 11, respectively, in a C57BL/6J (B6, susceptible) and C3Hf/KAM (C3H, resistant) mouse cross. Methods: Herein, the genetic basis of bleomycin induced pulmonary fibrosis was investigated in an approach combining gene expression and sequencing data with previously mapped linkage intervals. Results: In this study, gene expression analysis with microarrays revealed 1892 genes or ESTs (expressed sequence tags) to be differentially expressed between bleomycin treated B6 and C3H mice and 67 of these genetic elements map to Blmpf1 or Blmpf2. This group included genes involved in an oxidative stress response, in apoptosis, and in immune regulation. A comparison of the B6 and C3H sequence, for Blmpf1 and Blmpf2, made using the NCBI database and available C3H sequence, revealed approximately 35% of the genes in these regions contain non-synonymous coding sequence changes. An assessment of genotype/phenotype correlation among other inbred strains revealed 36% of these B6/C3H sequence variations predict for the known bleomycin induced fibrosis susceptibility of the DBA (susceptible) and A/J (resistant) mouse strains. Conclusions: Combining genomics approaches of differential gene expression and sequence variation potentially identifies approximately 5% the linked genes as fibrosis susceptibility candidate genes in this mouse cross. PMID:15937080

  3. MMTV insertional mutagenesis identifies genes, gene families and pathways involved in mammary cancer.

    PubMed

    Theodorou, Vassiliki; Kimm, Melanie A; Boer, Mandy; Wessels, Lodewyk; Theelen, Wendy; Jonkers, Jos; Hilkens, John

    2007-06-01

    We performed a high-throughput retroviral insertional mutagenesis screen in mouse mammary tumor virus (MMTV)-induced mammary tumors and identified 33 common insertion sites, of which 17 genes were previously not known to be associated with mammary cancer and 13 had not previously been linked to cancer in general. Although members of the Wnt and fibroblast growth factors (Fgf) families were frequently tagged, our exhaustive screening for MMTV insertion sites uncovered a new repertoire of candidate breast cancer oncogenes. We validated one of these genes, Rspo3, as an oncogene by overexpression in a p53-deficient mammary epithelial cell line. The human orthologs of the candidate oncogenes were frequently deregulated in human breast cancers and associated with several tumor parameters. Computational analysis of all MMTV-tagged genes uncovered specific gene families not previously associated with cancer and showed a significant overrepresentation of protein domains and signaling pathways mainly associated with development and growth factor signaling. Comparison of all tagged genes in MMTV and Moloney murine leukemia virus-induced malignancies showed that both viruses target mostly different genes that act predominantly in distinct pathways.

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

    PubMed

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

    2014-07-01

    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.

  5. Whole-exome sequencing identifies rare pathogenic variants in new predisposition genes for familial colorectal cancer

    PubMed Central

    Esteban-Jurado, Clara; Vila-Casadesús, Maria; Garre, Pilar; Lozano, Juan José; Pristoupilova, Anna; Beltran, Sergi; Muñoz, Jenifer; Ocaña, Teresa; Balaguer, Francesc; López-Cerón, Maria; Cuatrecasas, Miriam; Franch-Expósito, Sebastià; Piqué, Josep M.; Castells, Antoni; Carracedo, Angel; Ruiz-Ponte, Clara; Abulí, Anna; Bessa, Xavier; Andreu, Montserrat; Bujanda, Luis; Caldés, Trinidad; Castellví-Bel, Sergi

    2015-01-01

    Purpose: Colorectal cancer is an important cause of mortality in the developed world. Hereditary forms are due to germ-line mutations in APC, MUTYH, and the mismatch repair genes, but many cases present familial aggregation but an unknown inherited cause. The hypothesis of rare high-penetrance mutations in new genes is a likely explanation for the underlying predisposition in some of these familial cases. Methods: Exome sequencing was performed in 43 patients with colorectal cancer from 29 families with strong disease aggregation without mutations in known hereditary colorectal cancer genes. Data analysis selected only very rare variants (0–0.1%), producing a putative loss of function and located in genes with a role compatible with cancer. Variants in genes previously involved in hereditary colorectal cancer or nearby previous colorectal cancer genome-wide association study hits were also chosen. Results: Twenty-eight final candidate variants were selected and validated by Sanger sequencing. Correct family segregation and somatic studies were used to categorize the most interesting variants in CDKN1B, XRCC4, EPHX1, NFKBIZ, SMARCA4, and BARD1. Conclusion: We identified new potential colorectal cancer predisposition variants in genes that have a role in cancer predisposition and are involved in DNA repair and the cell cycle, which supports their putative involvement in germ-line predisposition to this neoplasm. PMID:25058500

  6. Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

    PubMed Central

    2015-01-01

    Background While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease. Results We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations. PMID:26356760

  7. Relationship between TBX20 gene polymorphism and congenital heart disease.

    PubMed

    Yang, X F; Zhang, Y F; Zhao, C F; Liu, M M; Si, J P; Fang, Y F; Xing, W W; Wang, F L

    2016-01-01

    Congenital heart disease in children is a type of birth defect. Previous studies have suggested that the transcription factor, TBX20, is involved in the occurrence and development of congenital heart disease in children; however, the specific regulatory mechanisms are yet to be evaluated. Hence, this study aimed to evaluate the relationship between the TBX20 polymorphism and the occurrence and development of congenital heart disease. The TBX20 gene sequence was obtained from the NCBI database and the polymorphic locus candidate was predicted. Thereafter, the specific gene primers were designed for the restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR) of DNA extracted from the blood of 80 patients with congenital heart disease and 80 controls. The results of the PCR were subjected to correlation analysis to identify the differences between the amplicons and to determine the relationship between the TBX20 gene polymorphism and congenital heart disease. One of the single nucleotide polymorphic locus was found to be rs3999950: c.774T>C (Ala265Ala). The TC genotype frequency in the patients was higher than that in the controls, similar to that for the C locus. The odds ratio of the TC genotypes was above 1, indicating that the presence of the TC genotype increases the incidence of congenital heart diseases. Thus, rs3999950 may be associated with congenital heart disease, and TBX20 may predispose children to the defect. PMID:27323105

  8. Integrating nutrigenomics data to identify cardiometabolic gene-environment interactions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nutrition is a key factor in health and in many age-related diseases. This is particularly the case for cardiometabolic diseases such as cardiovascular disease, type 2 diabetes and hypertension, and is often precluded by obesity, glucose impairment and metabolic syndrome. Our research objectives are...

  9. Preselective gene therapy for Fabry disease

    PubMed Central

    Qin, Gangjian; Takenaka, Toshihiro; Telsch, Kimberly; Kelley, Leslie; Howard, Tazuko; Levade, Thierry; Deans, Robert; Howard, Bruce H.; Malech, Harry L.; Brady, Roscoe O.; Medin, Jeffrey A.

    2001-01-01

    Fabry disease is a lipid storage disorder resulting from mutations in the gene encoding the enzyme α-galactosidase A (α-gal A; EC 3.2.1.22). We previously have demonstrated long-term α-gal A enzyme correction and lipid reduction mediated by therapeutic ex vivo transduction and transplantation of hematopoietic cells in a mouse model of Fabry disease. We now report marked improvement in the efficiency of this gene-therapy approach. For this study we used a novel bicistronic retroviral vector that engineers expression of both the therapeutic α-gal A gene and the human IL-2Rα chain (huCD25) gene as a selectable marker. Coexpression of huCD25 allowed selective immunoenrichment (preselection) of a variety of transduced human and murine cells, resulting in enhanced intracellular and secreted α-gal A enzyme activities. Of particular significance for clinical applicability, mobilized CD34+ peripheral blood hematopoietic stem/progenitor cells from Fabry patients have low-background huCD25 expression and could be enriched effectively after ex vivo transduction, resulting in increased α-gal A activity. We evaluated effects of preselection in the mouse model of Fabry disease. Preselection of transduced Fabry mouse bone marrow cells elevated the level of multilineage gene-corrected hematopoietic cells in the circulation of transplanted animals and improved in vivo enzymatic activity levels in plasma and organs for more than 6 months after both primary and secondary transplantation. These studies demonstrate the potential of using a huCD25-based preselection strategy to enhance the clinical utility of ex vivo hematopoietic stem/progenitor cell gene therapy of Fabry disease and other disorders. PMID:11248095

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

    PubMed Central

    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

    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. PMID:22279524

  11. Approaches for recognizing disease genes based on network.

    PubMed

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

    2014-01-01

    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.

  12. Gene expression profiling identifies distinct molecular subgroups of leiomyosarcoma with clinical relevance

    PubMed Central

    Lee, Yin-Fai; Roe, Toby; Mangham, D Chas; Fisher, Cyril; Grimer, Robert J; Judson, Ian

    2016-01-01

    Background: Soft tissue sarcomas are heterogeneous and a major complication in their management is that the existing classification scheme is not definitive and is still evolving. Leiomyosarcomas, a major histologic category of soft tissue sarcomas, are malignant tumours displaying smooth muscle differentiation. Although defined as a single group, they exhibit a wide range of clinical behaviour. We aimed to carry out molecular classification to identify new molecular subgroups with clinical relevance. Methods: We used gene expression profiling on 20 extra-uterine leiomyosarcomas and cross-study analyses for molecular classification of leiomyosarcomas. Clinical significance of the subgroupings was investigated. Results: We have identified two distinct molecular subgroups of leiomyosarcomas. One group was characterised by high expression of 26 genes that included many genes from the sub-classification gene cluster proposed by Nielsen et al. These sub-classification genes include genes that have importance structurally, as well as in cell signalling. Notably, we found a statistically significant association of the subgroupings with tumour grade. Further refinement led to a group of 15 genes that could recapitulate the tumour subgroupings in our data set and in a second independent sarcoma set. Remarkably, cross-study analyses suggested that these molecular subgroups could be found in four independent data sets, providing strong support for their existence. Conclusions: Our study strongly supported the existence of distinct leiomyosarcoma molecular subgroups, which have clinical association with tumour grade. Our findings will aid in advancing the classification of leiomyosarcomas and lead to more individualised and better management of the disease. PMID:27607470

  13. Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

    PubMed Central

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple

  14. Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

    PubMed

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR-essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR-essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR-essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR-essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR-induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led

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

    PubMed Central

    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-Thérèse; 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; Hernández, Isabel; Rubinsztein, David C.; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M.; Fiévet, 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; Bossù, 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-García, 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, Mercè; Hiltunen, Mikko; Martin, Eden R.; Schmidt, Reinhold; Rujescu, Dan; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, 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

    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. PMID:24922517

  16. Integrated Genomics Identifies Convergence of Ankylosing Spondylitis with Global Immune Mediated Disease Pathways

    PubMed Central

    Uddin, Mohammed; Codner, Dianne; Mahmud Hasan, S M; Scherer, Stephen W; O’Rielly, Darren D; Rahman, Proton

    2015-01-01

    Ankylosing spondylitis(AS), a highly heritable complex inflammatory arthritis. Although, a handful of non-HLA risk loci have been identified, capturing the unexplained genetic contribution to AS pathogenesis remains a challenge attributed to additive, pleiotropic and epistatic-interactions at the molecular level. Here, we developed multiple integrated genomic approaches to quantify molecular convergence of non-HLA loci with global immune mediated diseases. We show that non-HLA genes are significantly sensitive to deleterious mutation accumulation in the general population compared with tolerant genes. Human developmental proteomics (prenatal to adult) analysis revealed that proteins encoded by non-HLA AS risk loci are 2-fold more expressed in adult hematopoietic cells.Enrichment analysis revealed AS risk genes overlap with a significant number of immune related pathways (p < 0.0001 to 9.8 × 10-12). Protein-protein interaction analysis revealed non-shared AS risk genes are highly clustered seeds that significantly converge (empirical; p < 0.01 to 1.6 × 10-4) into networks of global immune mediated disease risk loci. We have also provided initial evidence for the involvement of STAT2/3 in AS pathogenesis. Collectively, these findings highlight molecular insight on non-HLA AS risk loci that are not exclusively connected with overlapping immune mediated diseases; rather a component of common pathophysiological pathways with other immune mediated diseases. This information will be pivotal to fully explain AS pathogenesis and identify new therapeutic targets. PMID:25980808

  17. [Expression of bioinformatically identified genes in skin of psoriasis patients].

    PubMed

    2013-10-01

    Gene expression analysis for EPHA2 (EPH receptor A2), EPHB2 (EPH receptor B2), S100A9 (S100 calcium binding protein A9), PBEF(nicotinamide phosphoribosyltransferase), LILRB2 (leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 2), PLAUR (plasminogen activator, urokinase receptor), LTB (lymphotoxin beta (TNF superfamily, member 3)), WNT5A (wingless-type MMTV integration site family, member 5A) has been conducted using real-time polymerase chain reaction in specimens affected by psoriasis versus visually intact skin in 18 patients. It was revealed that the expression of the nine examined genes was upregulated in the affected by psoriasis compared to visually intact skin specimens. The highest expression was observed for S100A9, S100AS, PBEF, WNT5A2, and EPHB2 genes. S100A9 and S100A8 gene expression in the affected by psoriasis skin was 100-fold higher versus visually intact skin while PBEF, WNT5A, and EPHB2 gene expression was upregulated more than five-fold. We suggested that the high expression of these genes might be associated with the state of the pathological process in psoriasis. Moreover, the transcriptional activity of these genes might serve a molecular indicator of the efficacy of treatment in psoriasis. PMID:25508677

  18. [Expression of bioinformatically identified genes in skin of psoriasis patients].

    PubMed

    Sobolev, V V; Nikol'skaia, T A; Zolotarenko, A D; Piruzian, E S; Bruskin, S A

    2013-10-01

    Gene expression analysis for EPHA2 (EPH receptor A2), EPHB2 (EPH receptor B2), S100A9 (S100 calcium binding protein A9), PBEF(nicotinamide phosphoribosyltransferase), LILRB2 (leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 2), PLAUR (plasminogen activator, urokinase receptor), LTB (lymphotoxin beta (TNF superfamily, member 3)), WNT5A (wingless-type MMTV integration site family, member 5A) has been conducted using real-time polymerase chain reaction in specimens affected by psoriasis versus visually intact skin in 18 patients. It was revealed that the expression of the nine examined genes was upregulated in the affected by psoriasis compared to visually intact skin specimens. The highest expression was observed for S100A9, S100AS, PBEF, WNT5A2, and EPHB2 genes. S100A9 and S100A8 gene expression in the affected by psoriasis skin was 100-fold higher versus visually intact skin while PBEF, WNT5A, and EPHB2 gene expression was upregulated more than five-fold. We suggested that the high expression of these genes might be associated with the state of the pathological process in psoriasis. Moreover, the transcriptional activity of these genes might serve a molecular indicator of the efficacy of treatment in psoriasis. PMID:25474898

  19. Epidermal growth factor gene is a newly identified candidate gene for gout

    PubMed Central

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

  20. Epidermal growth factor gene is a newly identified candidate gene for gout.

    PubMed

    Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

    2016-01-01

    Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67-0.88, Padjusted = 6.42 × 10(-3)). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

  1. Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases.

    PubMed

    Arakelyan, Arsen; Nersisyan, Lilit; Petrek, Martin; Löffler-Wirth, Henry; Binder, Hans

    2016-01-01

    Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent.

  2. Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases

    PubMed Central

    Arakelyan, Arsen; Nersisyan, Lilit; Petrek, Martin; Löffler-Wirth, Henry; Binder, Hans

    2016-01-01

    Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent. PMID:27200087

  3. Comparative transcriptome analysis of atrial septal defect identifies dysregulated genes during heart septum morphogenesis.

    PubMed

    Wang, Wenju; Niu, Zhaoyi; Wang, Yi; Li, Yaxiong; Zou, Honglin; Yang, Li; Meng, Mingyao; Wei, Chuanyu; Li, Qinrui; Duan, Le; Xie, Yanhua; Zhang, Yayong; Cao, Yu; Han, Shen; Hou, Zongliu; Jiang, Lihong

    2016-01-10

    Congenital heart disease (CHD) is one of most common birth defects, causing fetal loss and death in newborn all over the world. Atrial and ventricular septal defects were the most common CHD subtypes in most districts. During the past decades, several genes were identified to control atrial septum formation, and mutations of these genes can cause cardiac septation defects. However, the pathogenic mechanism of ASD on transcriptional levels has not been well elucidated yet. Herein, we performed comparative transcriptome analysis between normal and atrial septal defect (ASD) patients by Illumina RNA sequencing (RNA-seq). Advanced bioinformatic analyses were employed to identify dysregulated genes in ASD. The results indicated that cardiac specific transcriptional factors (GATA4 and NKX2-5), extracellular signal molecules (VEGFA and BMP10) and cardiac sarcomeric proteins (MYL2, MYL3, MYH7, TNNT1 and TNNT3) were downregulated in ASD which may affect heart atrial septum formation, cardiomyocyte proliferation and cardiac muscle development. Importantly, cell cycle was dominant pathway among downregulated genes, and decreased expression of the proteins included in cell cycle may disturb cardiomyocyte growth and differentiation during atrial septum formation. Our study provided evidences of understanding pathogenic mechanism of ASD and resource for validation of CHD genomic studies.

  4. Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci.

    PubMed

    Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun

    2016-01-01

    Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo.

  5. Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci

    PubMed Central

    Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun

    2016-01-01

    Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo. PMID:26870082

  6. A modifier screen identifies DNAJB6 as a cardiomyopathy susceptibility gene

    PubMed Central

    Ding, Yonghe; Long, Pamela A.; Bos, J. Martijn; Shih, Yu-Huan; Ma, Xiao; Sundsbak, Rhianna S.; Chen, Jianhua; Jiang, Yiwen; Zhao, Liqun; Hu, Xinyang; Wang, Jianan; Shi, Yongyong; Ackerman, Michael J.; Lin, Xueying; Ekker, Stephen C.; Redfield, Margaret M.; Olson, Timothy M.; Xu, Xiaolei

    2016-01-01

    Mutagenesis screening is a powerful forward genetic approach that has been successfully applied in lower-model organisms to discover genetic factors for biological processes. This phenotype-based approach has yet to be established in vertebrates for probing major human diseases, largely because of the complexity of colony management. Herein, we report a rapid strategy for identifying genetic modifiers of cardiomyopathy (CM). Based on the application of doxorubicin stress to zebrafish insertional cardiac (ZIC) mutants, we identified 4 candidate CM-modifying genes, of which 3 have been linked previously to CM. The long isoform of DnaJ (Hsp40) homolog, subfamily B, member 6b (dnajb6b(L)) was identified as a CM susceptibility gene, supported by identification of rare variants in its human ortholog DNAJB6 from CM patients. Mechanistic studies indicated that the deleterious, loss-of-function modifying effects of dnajb6b(L) can be ameliorated by inhibition of ER stress. In contrast, overexpression of dnajb6(L) exerts cardioprotective effects on both fish and mouse CM models. Together, our findings establish a mutagenesis screening strategy that is scalable for systematic identification of genetic modifiers of CM, feasible to suggest therapeutic targets, and expandable to other major human diseases.

  7. A modifier screen identifies DNAJB6 as a cardiomyopathy susceptibility gene

    PubMed Central

    Ding, Yonghe; Long, Pamela A.; Bos, J. Martijn; Shih, Yu-Huan; Ma, Xiao; Sundsbak, Rhianna S.; Chen, Jianhua; Zhao, Liqun; Hu, Xinyang; Wang, Jianan; Shi, Yongyong; Ackerman, Michael J.; Lin, Xueying; Ekker, Stephen C.; Redfield, Margaret M.; Olson, Timothy M.

    2016-01-01

    Mutagenesis screening is a powerful forward genetic approach that has been successfully applied in lower-model organisms to discover genetic factors for biological processes. This phenotype-based approach has yet to be established in vertebrates for probing major human diseases, largely because of the complexity of colony management. Herein, we report a rapid strategy for identifying genetic modifiers of cardiomyopathy (CM). Based on the application of doxorubicin stress to zebrafish insertional cardiac (ZIC) mutants, we identified 4 candidate CM-modifying genes, of which 3 have been linked previously to CM. The long isoform of DnaJ (Hsp40) homolog, subfamily B, member 6b (dnajb6b(L)) was identified as a CM susceptibility gene, supported by identification of rare variants in its human ortholog DNAJB6 from CM patients. Mechanistic studies indicated that the deleterious, loss-of-function modifying effects of dnajb6b(L) can be ameliorated by inhibition of ER stress. In contrast, overexpression of dnajb6(L) exerts cardioprotective effects on both fish and mouse CM models. Together, our findings establish a mutagenesis screening strategy that is scalable for systematic identification of genetic modifiers of CM, feasible to suggest therapeutic targets, and expandable to other major human diseases. PMID:27642634

  8. Identifying Autism Loci and Genes by Tracing Recent Shared Ancestry

    PubMed Central

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

    2008-01-01

    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, or c3orf58), whose level of expression changes in response to neuronal activity, a marker of genes involved in synaptic changes that underlie learning. A subset of genes, including NHE9 (Na+/H+ exchanger 9), showed additional potential mutations in patients with unrelated parents. Our findings highlight the utility of “homozygosity mapping” in heterogeneous disorders like autism but also suggest that defective regulation of gene expression after neural activity may be a mechanism common to seemingly diverse autism mutations. PMID:18621663

  9. Systems Approaches to Identifying Gene Regulatory Networks in Plants

    PubMed Central

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

    2009-01-01

    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. PMID:18616425

  10. Development and Utilization of InDel Markers to Identify Peanut (Arachis hypogaea) Disease Resistance.

    PubMed

    Liu, Lifeng; Dang, Phat M; Chen, Charles Y

    2015-01-01

    Peanut diseases, such as leaf spot and spotted wilt caused by Tomato Spotted Wilt Virus, can significantly reduce yield and quality. Application of marker assisted plant breeding requires the development and validation of different types of DNA molecular markers. Nearly 10,000 SSR-based molecular markers have been identified by various research groups around the world, but less than 14.5% showed polymorphism in peanut and only 6.4% have been mapped. Low levels of polymorphism limit the application of marker assisted selection (MAS) in peanut breeding programs. Insertion/deletion (InDel) markers have been reported to be more polymorphic than SSRs in some crops. The goals of this study were to identify novel InDel markers and to evaluate the potential use in peanut breeding. Forty-eight InDel markers were developed from conserved sequences of functional genes and tested in a diverse panel of 118 accessions covering six botanical types of cultivated peanut, of which 104 were from the U.S. mini-core. Results showed that 16 InDel markers were polymorphic with polymorphic information content (PIC) among InDels ranged from 0.017 to 0.660. With respect to botanical types, PICs varied from 0.176 for fastigiata var., 0.181 for hypogaea var., 0.306 for vulgaris var., 0.534 for aequatoriana var., 0.556 for peruviana var., to 0.660 for hirsuta var., implying that aequatoriana var., peruviana var., and hirsuta var. have higher genetic diversity than the other types and provide a basis for gene functional studies. Single marker analysis was conducted to associate specific marker to disease resistant traits. Five InDels from functional genes were identified to be significantly correlated to tomato spotted wilt virus (TSWV) infection and leaf spot, and these novel markers will be utilized to identify disease resistant genotype in breeding populations.

  11. Development and Utilization of InDel Markers to Identify Peanut (Arachis hypogaea) Disease Resistance

    PubMed Central

    Liu, Lifeng; Dang, Phat M.; Chen, Charles Y.

    2015-01-01

    Peanut diseases, such as leaf spot and spotted wilt caused by Tomato Spotted Wilt Virus, can significantly reduce yield and quality. Application of marker assisted plant breeding requires the development and validation of different types of DNA molecular markers. Nearly 10,000 SSR-based molecular markers have been identified by various research groups around the world, but less than 14.5% showed polymorphism in peanut and only 6.4% have been mapped. Low levels of polymorphism limit the application of marker assisted selection (MAS) in peanut breeding programs. Insertion/deletion (InDel) markers have been reported to be more polymorphic than SSRs in some crops. The goals of this study were to identify novel InDel markers and to evaluate the potential use in peanut breeding. Forty-eight InDel markers were developed from conserved sequences of functional genes and tested in a diverse panel of 118 accessions covering six botanical types of cultivated peanut, of which 104 were from the U.S. mini-core. Results showed that 16 InDel markers were polymorphic with polymorphic information content (PIC) among InDels ranged from 0.017 to 0.660. With respect to botanical types, PICs varied from 0.176 for fastigiata var., 0.181 for hypogaea var., 0.306 for vulgaris var., 0.534 for aequatoriana var., 0.556 for peruviana var., to 0.660 for hirsuta var., implying that aequatoriana var., peruviana var., and hirsuta var. have higher genetic diversity than the other types and provide a basis for gene functional studies. Single marker analysis was conducted to associate specific marker to disease resistant traits. Five InDels from functional genes were identified to be significantly correlated to tomato spotted wilt virus (TSWV) infection and leaf spot, and these novel markers will be utilized to identify disease resistant genotype in breeding populations. PMID:26617627

  12. Integrated sequence analysis pipeline provides one-stop solution for identifying disease-causing mutations.

    PubMed

    Hu, Hao; Wienker, Thomas F; Musante, Luciana; Kalscheuer, Vera M; Kahrizi, Kimia; Najmabadi, Hossein; Ropers, H Hilger

    2014-12-01

    Next-generation sequencing has greatly accelerated the search for disease-causing defects, but even for experts the data analysis can be a major challenge. To facilitate the data processing in a clinical setting, we have developed a novel medical resequencing analysis pipeline (MERAP). MERAP assesses the quality of sequencing, and has optimized capacity for calling variants, including single-nucleotide variants, insertions and deletions, copy-number variation, and other structural variants. MERAP identifies polymorphic and known causal variants by filtering against public domain databases, and flags nonsynonymous and splice-site changes. MERAP uses a logistic model to estimate the causal likelihood of a given missense variant. MERAP considers the relevant information such as phenotype and interaction with known disease-causing genes. MERAP compares favorably with GATK, one of the widely used tools, because of its higher sensitivity for detecting indels, its easy installation, and its economical use of computational resources. Upon testing more than 1,200 individuals with mutations in known and novel disease genes, MERAP proved highly reliable, as illustrated here for five families with disease-causing variants. We believe that the clinical implementation of MERAP will expedite the diagnostic process of many disease-causing defects.

  13. Identifying novel resistance genes in rice wild relatives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rice blast and sheath blight are major fungal diseases of cultivated rice (Oryza sativa L. ) that limit Arkansas rough rice yields and market potential. Resistance to these diseases has been found in rice wild relatives (Oryza spp.) A collection of these wild relatives originating from outside the U...

  14. Aberrant splicing of the PTPRD gene mimics microdeletions identified at this locus in neuroblastomas.

    PubMed

    Nair, Prakash; De Preter, Katleen; DePreter, Katleen; Vandesompele, Jo; Speleman, Frank; Stallings, Raymond L

    2008-03-01

    Neuroblastoma (NBL), a pediatric tumor arising from precursor cells of the sympathetic nervous system, is characterized by numerous recurrent large-scale chromosomal imbalances. High resolution oligonucleotide array CGH analysis of NBL has previously identified microdeletions that are confined to the 5' UTR of the protein tyrosine phosphatase receptor D (PTPRD) gene, implicating this gene in the pathogenesis of these tumors. Here, we demonstrate that the 5' UTR of this gene, consisting of 11 noncoding exons, is also aberrantly spliced in >50% of NBL primary tumors and cell lines. The loss of exons from the 5' UTR region through aberrant splicing results in aberrant mRNA isoforms that are similar to those generated through microdeletions. The aberrant splicing or microdeletion of 5' UTR exons in such a high proportion of tumors indicates that loss of these exons dys-regulates the mRNA sequence. To further validate the role of PTPRD in NBL, we have examined the expression of this gene in normal fetal adrenal neuroblasts (the cell of origin of NBL) and in tumors from patients with either low stage or high stage disease. This gene is expressed at lower levels in high stage NBL tumors, particularly those with amplification of MYCN, relative to low stage tumors or normal fetal adrenal neuroblasts, consistent with the possibility that loss of the 5' UTR exons have destabilized the mRNA.

  15. Genome-Wide Expression Profiles Identify Potential Targets for Gene by Environment Interactions in Asthma Severity

    PubMed Central

    Sordillo, Joanne E; Kelly, Roxanne; Bunyavanich, Supinda; McGeachie, Michael; Qiu, Weiliang; Croteau-Chonka, Damien C.; Soto-Quiros, Manuel; Avila, Lydiana; Celedón, Juan C.; Brehm, John M.; Weiss, Scott T; Gold, Diane R; Litonjua, Augusto A

    2015-01-01

    Background Gene by environment interaction (G × E) studies utilizing GWAS data are often underpowered after adjustment for multiple comparisons. Differential gene expression, in response to the exposure of interest, may capture the most biologically relevant genes at the genome-wide level. Methods We used differential genome-wide expression profiles from the Home Allergens and Asthma Birth cohort in response to Der f 1 allergen (sensitized vs. non-sensitized) to inform a G × E study of dust mite exposure and asthma severity. Polymorphisms in differentially expressed genes were identified in GWAS data from CAMP, a clinical trial in childhood asthmatics. Home dust mite allergen (< or ≥ 10µg/g dust) was assessed at baseline, and (≥ 1) severe asthma exacerbation (emergency room (ER) visit or hospitalization for asthma in the first trial year) served as the disease severity outcome. The Genetics of Asthma in Costa Rica (GACRS) study, and a Puerto Rico/Connecticut asthma cohortwere used for replication. Results IL-9, IL-5 and PRG2 expression was up-regulated in Der f 1 stimulated PBMCs from dust mite sensitized individuals (adj. p value <0.04). IL-9 polymorphisms (rs11741137, rs2069885, rs1859430) showed evidence for interaction with dust mite in CAMP (p=0.02 to 0.03), with replication in GACRS (p=0.04). Subjects with the dominant genotype for these IL-9 polymorphisms were more likely to report a severe asthma exacerbation if exposed to elevated dust mite. Conclusions Genome-wide differential gene expression in response to dust mite allergen identified IL-9, a biologically plausible gene target that may interact with environmental dust mite to increase severe asthma exacerbations in children. PMID:25913104

  16. Gene trapping identifies transiently induced survival genes during programmed cell death

    PubMed Central

    Wempe, Frank; Yang, Ji-Yeon; Hammann, Joanna; Melchner, Harald von

    2001-01-01

    Background The existence of a constitutively expressed machinery for death in individual cells has led to the notion that survival factors repress this machinery and, if such factors are unavailable, cells die by default. In many cells, however, mRNA and protein synthesis inhibitors induce apoptosis, suggesting that in some cases transcriptional activity might actually impede cell death. To identify transcriptional mechanisms that interfere with cell death and survival, we combined gene trap mutagenesis with site-specific recombination (Cre/loxP system) to isolate genes from cells undergoing apoptosis by growth factor deprivation. Results From an integration library consisting of approximately 2 × 106 unique proviral integrations obtained by infecting the interleukin-3 (IL-3)-dependent hematopoietic cell line - FLOXIL3 - with U3Cre gene trap virus, we have isolated 125 individual clones that converted to factor independence upon IL-3 withdrawal. Of 102 cellular sequences adjacent to U3Cre integration sites, 17% belonged to known genes, 11% matched single expressed sequence tags (ESTs) or full cDNAs with unknown function and 72% had no match within the public databases. Most of the known genes recovered in this analysis encoded proteins with survival functions. Conclusions We have shown that hematopoietic cells undergoing apoptosis after withdrawal of IL-3 activate survival genes that impede cell death. This results in reduced apoptosis and improved survival of cells treated with a transient apoptotic stimulus. Thus, apoptosis in hematopoietic cells is the end result of a conflict between death and survival signals, rather than a simple death by default. PMID:11516336

  17. Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis.

    PubMed

    Méheust, Raphaël; Zelzion, Ehud; Bhattacharya, Debashish; Lopez, Philippe; Bapteste, Eric

    2016-03-29

    The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the "recycling" of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance. PMID:26976593

  18. Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis

    PubMed Central

    Méheust, Raphaël; Zelzion, Ehud; Bhattacharya, Debashish; Lopez, Philippe; Bapteste, Eric

    2016-01-01

    The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the “recycling” of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance. PMID:26976593

  19. Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis.

    PubMed

    Méheust, Raphaël; Zelzion, Ehud; Bhattacharya, Debashish; Lopez, Philippe; Bapteste, Eric

    2016-03-29

    The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the "recycling" of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance.

  20. Identification of susceptibility genes and genetic modifiers of human diseases

    NASA Astrophysics Data System (ADS)

    Abel, Kenneth; Kammerer, Stefan; Hoyal, Carolyn; Reneland, Rikard; Marnellos, George; Nelson, Matthew R.; Braun, Andreas

    2005-03-01

    The completion of the human genome sequence enables the discovery of genes involved in common human disorders. The successful identification of these genes is dependent on the availability of informative sample sets, validated marker panels, a high-throughput scoring technology, and a strategy for combining these resources. We have developed a universal platform technology based on mass spectrometry (MassARRAY) for analyzing nucleic acids with high precision and accuracy. To fuel this technology, we generated more than 100,000 validated assays for single nucleotide polymorphisms (SNPs) covering virtually all known and predicted human genes. We also established a large DNA sample bank comprised of more than 50,000 consented healthy and diseased individuals. This combination of reagents and technology allows the execution of large-scale genome-wide association studies. Taking advantage of MassARRAY"s capability for quantitative analysis of nucleic acids, allele frequencies are estimated in sample pools containing large numbers of individual DNAs. To compare pools as a first-pass "filtering" step is a tremendous advantage in throughput and cost over individual genotyping. We employed this approach in numerous genome-wide, hypothesis-free searches to identify genes associated with common complex diseases, such as breast cancer, osteoporosis, and osteoarthritis, and genes involved in quantitative traits like high density lipoproteins cholesterol (HDL-c) levels and central fat. Access to additional well-characterized patient samples through collaborations allows us to conduct replication studies that validate true disease genes. These discoveries will expand our understanding of genetic disease predisposition, and our ability for early diagnosis and determination of specific disease subtype or progression stage.

  1. Human Disease Insight: An integrated knowledge-based platform for disease-gene-drug information.

    PubMed

    Tasleem, Munazzah; Ishrat, Romana; Islam, Asimul; Ahmad, Faizan; Hassan, Md Imtaiyaz

    2016-01-01

    The scope of the Human Disease Insight (HDI) database is not limited to researchers or physicians as it also provides basic information to non-professionals and creates disease awareness, thereby reducing the chances of patient suffering due to ignorance. HDI is a knowledge-based resource providing information on human diseases to both scientists and the general public. Here, our mission is to provide a comprehensive human disease database containing most of the available useful information, with extensive cross-referencing. HDI is a knowledge management system that acts as a central hub to access information about human diseases and associated drugs and genes. In addition, HDI contains well-classified bioinformatics tools with helpful descriptions. These integrated bioinformatics tools enable researchers to annotate disease-specific genes and perform protein analysis, search for biomarkers and identify potential vaccine candidates. Eventually, these tools will facilitate the analysis of disease-associated data. The HDI provides two types of search capabilities and includes provisions for downloading, uploading and searching disease/gene/drug-related information. The logistical design of the HDI allows for regular updating. The database is designed to work best with Mozilla Firefox and Google Chrome and is freely accessible at http://humandiseaseinsight.com.

  2. Human Disease Insight: An integrated knowledge-based platform for disease-gene-drug information.

    PubMed

    Tasleem, Munazzah; Ishrat, Romana; Islam, Asimul; Ahmad, Faizan; Hassan, Md Imtaiyaz

    2016-01-01

    The scope of the Human Disease Insight (HDI) database is not limited to researchers or physicians as it also provides basic information to non-professionals and creates disease awareness, thereby reducing the chances of patient suffering due to ignorance. HDI is a knowledge-based resource providing information on human diseases to both scientists and the general public. Here, our mission is to provide a comprehensive human disease database containing most of the available useful information, with extensive cross-referencing. HDI is a knowledge management system that acts as a central hub to access information about human diseases and associated drugs and genes. In addition, HDI contains well-classified bioinformatics tools with helpful descriptions. These integrated bioinformatics tools enable researchers to annotate disease-specific genes and perform protein analysis, search for biomarkers and identify potential vaccine candidates. Eventually, these tools will facilitate the analysis of disease-associated data. The HDI provides two types of search capabilities and includes provisions for downloading, uploading and searching disease/gene/drug-related information. The logistical design of the HDI allows for regular updating. The database is designed to work best with Mozilla Firefox and Google Chrome and is freely accessible at http://humandiseaseinsight.com. PMID:26631432

  3. EST mining of the UniGene dataset to identify retina-specific genes.

    PubMed

    Stöhr, H; Mah, N; Schulz, H L; Gehrig, A; Fröhlich, S; Weber, B H

    2000-01-01

    Age-related macular degeneration (AMD) is a multifactorial disorder affecting the visual system with a high prevalence among the elderly population but with no effective therapy available at present. To better understand the pathogenesis of this disorder, the identification of the genetic factors and the determination of their contribution to AMD is needed. Towards this goal, we are pursuing a strategy that makes use of the EST data processed in the UniGene database and aims at the generation of a comprehensive catalogue of genes preferentially active in the human retina. Subsequently, these genes will be systematically assessed in AMD. We performed a retina EST sampling and obtained a total of 673 clusters containing only retina ESTs as well as 568 clusters with at least 30% of the ESTs in each cluster originating from retina cDNA libraries. Of these, 180 representative EST clusters with varying retina and non-retina EST contents were analyzed for their in vitro expression. This approach identified 39 transcripts with retina-specific expression. One of these genes (C18orf2) mapping to chromosome 18 was further characterized. Multiple C18orf2 transcripts display a complex pattern of differential splicing in the human retina. The various isoforms encode hypothetical polypeptides with no homologies to known proteins or protein motifs.

  4. Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

    PubMed

    Davis, Allan Peter; Wiegers, Thomas C; King, Benjamin L; Wiegers, Jolene; Grondin, Cynthia J; Sciaky, Daniela; Johnson, Robin J; Mattingly, Carolyn J

    2016-01-01

    Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD's gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug makers

  5. Fluid Mechanics, Arterial Disease, and Gene Expression

    NASA Astrophysics Data System (ADS)

    Tarbell, John M.; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow-induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid mechanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs.

  6. Fluid Mechanics, Arterial Disease, and Gene Expression

    PubMed Central

    Tarbell, John M.; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow–induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs. PMID:25360054

  7. Fluid Mechanics, Arterial Disease, and Gene Expression.

    PubMed

    Tarbell, John M; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow-induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs.

  8. Expression Quantitative Trait Loci Analysis Identifies Associations Between Genotype and Gene Expression in Human Intestine

    PubMed Central

    KABAKCHIEV, BOYKO; SILVERBERG, MARK S.

    2013-01-01

    BACKGROUND & AIMS Genome-wide association studies have greatly increased our understanding of intestinal disease. However, little is known about how genetic variations result in phenotypic changes. Some polymorphisms have been shown to modulate quantifiable phenotypic traits; these are called quantitative trait loci. Quantitative trait loci that affect levels of gene expression are called expression quantitative trait loci (eQTL), which can provide insight into the biological relevance of data from genome-wide association studies. We performed a comprehensive eQTL scan of intestinal tissue. METHODS Total RNA was extracted from ileal biopsy specimens and genomic DNA was obtained from whole-blood samples from the same cohort of individuals. Cis- and trans-eQTL analyses were performed using a custom software pipeline for samples from 173 subjects. The analyses determined the expression levels of 19,047 unique autosomal genes listed in the US National Center for Biotechnology Information database and more than 580,000 variants from the Single Nucleotide Polymorphism database. RESULTS The presence of more than 15,000 cis- and trans-eQTL was detected with statistical significance. eQTL associated with the same expression trait were in high linkage disequilibrium. Comparative analysis with previous eQTL studies showed that 30% to 40% of genes identified as eQTL in monocytes, liver tissue, lymphoblastoid cell lines, T cells, and fibroblasts are also eQTL in ileal tissue. Conversely, most of the significant eQTL have not been previously identified and could be tissue specific. These are involved in many cell functions, including division and antigen processing and presentation. Our analysis confirmed that previously published cis-eQTL are single nucleotide polymorphisms associated with inflammatory bowel disease: rs2298428/UBE2L3, rs1050152/SLC22A4, and SLC22A5. We identified many new associations between inflammatory bowel disease susceptibility loci and gene expression

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

    PubMed Central

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

    2013-01-01

    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. PMID:24223098

  10. A Genetic Screen Identifies Interferon-α Effector Genes Required to Suppress Hepatitis C Virus Replication

    PubMed Central

    Fusco, Dahlene N.; Brisac, Cynthia; John, Sinu P.; Huang, Yi-Wen; Chin, Christopher R.; Xie, Tiao; Zhao, Hong; Zhang, Leiliang; Chevalier, Stephane; Wambua, Daniel; Lin, Wenyu; Peng, Lee; Chung, Raymond T.; Brass, Abraham L.

    2013-01-01

    Background & Aims Hepatitis C virus (HCV) infection is a leading cause of end-stage liver disease. Interferon (IFN)-α is an important component of anti-HCV therapy; it upregulates transcription of IFN-stimulated genes (ISGs)—many of which have been investigated for their anti-viral effects. However, all the genes required for the anti-viral function of IFN-α (IFN effector genes, IEGs) are not known. IEGs include not only ISGs, but other non-transcriptionally induced genes that are required for the anti-viral effect of IFN-α. In contrast to candidate approaches based on analyses mRNA expression, identification of IEGs requires a broad functional approach. Methods We performed an unbiased genome-wide small-interfering (si)RNA screen to identify IEGs that inhibit HCV. Huh7.5.1 hepatoma cells were transfected with siRNAs, incubated with IFN-α, and then infected with JFH1 HCV. Cells were stained using HCV core antibody, imaged, and analyzed to determine the percent infection. Candidate IEGs detected in the screen were validated and analyzed further. Results The screen identified 120 previously unreported IEGs. From these, we more fully evaluated 9 (ALG10, BCHE, DPP4, GCKR, GUCY1B3, MYST1, PPP3CB, PDIP1, SLC27A2) and demonstrated that they enabled IFN-α–mediated suppression of HCV at multiple steps of its lifecycle. Expression of these genes had more potent effects against flaviviridae, because a subset were required for IFN-α to suppress dengue virus but not influenza A virus. Furthermore, many of the host genes detected in this screen (92%) were not transcriptionally stimulated by IFN-α; these genes represent a heretofore unknown class of non-ISG IEGs. Conclusion We performed a whole-genome loss-of-function screen to identify genes that mediate the effects of IFN-α against human pathogenic viruses. We found that IFN-α restricts HCV via actions of general and specific IEGs. PMID:23462180

  11. Cell-type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy

    PubMed Central

    Inkeles, Megan S.; Teles, Rosane M.B.; Pouldar, Delila; Andrade, Priscila R.; Madigan, Cressida A.; Ambrose, Mike; Sarno, Euzenir N.; Rea, Thomas H.; Ochoa, Maria T.; Iruela-Arispe, M. Luisa; Swindell, William R.; Ottenhoff, Tom H.M.; Geluk, Annemieke; Bloom, Barry R.

    2016-01-01

    Transcriptome profiles derived from the site of human disease have led to the identification of genes that contribute to pathogenesis, yet the complex mixture of cell types in these lesions has been an obstacle for defining specific mechanisms. Leprosy provides an outstanding model to study host defense and pathogenesis in a human infectious disease, given its clinical spectrum, which interrelates with the host immunologic and pathologic responses. Here, we investigated gene expression profiles derived from skin lesions for each clinical subtype of leprosy, analyzing gene coexpression modules by cell-type deconvolution. In lesions from tuberculoid leprosy patients, those with the self-limited form of the disease, dendritic cells were linked with MMP12 as part of a tissue remodeling network that contributes to granuloma formation. In lesions from lepromatous leprosy patients, those with disseminated disease, macrophages were linked with a gene network that programs phagocytosis. In erythema nodosum leprosum, neutrophil and endothelial cell gene networks were identified as part of the vasculitis that results in tissue injury. The present integrated computational approach provides a systems approach toward identifying cell-defined functional networks that contribute to host defense and immunopathology at the site of human infectious disease. PMID:27699251

  12. Cell-type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy

    PubMed Central

    Inkeles, Megan S.; Teles, Rosane M.B.; Pouldar, Delila; Andrade, Priscila R.; Madigan, Cressida A.; Ambrose, Mike; Sarno, Euzenir N.; Rea, Thomas H.; Ochoa, Maria T.; Iruela-Arispe, M. Luisa; Swindell, William R.; Ottenhoff, Tom H.M.; Geluk, Annemieke; Bloom, Barry R.

    2016-01-01

    Transcriptome profiles derived from the site of human disease have led to the identification of genes that contribute to pathogenesis, yet the complex mixture of cell types in these lesions has been an obstacle for defining specific mechanisms. Leprosy provides an outstanding model to study host defense and pathogenesis in a human infectious disease, given its clinical spectrum, which interrelates with the host immunologic and pathologic responses. Here, we investigated gene expression profiles derived from skin lesions for each clinical subtype of leprosy, analyzing gene coexpression modules by cell-type deconvolution. In lesions from tuberculoid leprosy patients, those with the self-limited form of the disease, dendritic cells were linked with MMP12 as part of a tissue remodeling network that contributes to granuloma formation. In lesions from lepromatous leprosy patients, those with disseminated disease, macrophages were linked with a gene network that programs phagocytosis. In erythema nodosum leprosum, neutrophil and endothelial cell gene networks were identified as part of the vasculitis that results in tissue injury. The present integrated computational approach provides a systems approach toward identifying cell-defined functional networks that contribute to host defense and immunopathology at the site of human infectious disease.

  13. Transcriptome Sequencing Identified Genes and Gene Ontologies Associated with Early Freezing Tolerance in Maize

    PubMed Central

    Li, Zhao; Hu, Guanghui; Liu, Xiangfeng; Zhou, Yao; Li, Yu; Zhang, Xu; Yuan, Xiaohui; Zhang, Qian; Yang, Deguang; Wang, Tianyu; Zhang, Zhiwu

    2016-01-01

    Originating in a tropical climate, maize has faced great challenges as cultivation has expanded to the majority of the world's temperate zones. In these zones, frost and cold temperatures are major factors that prevent maize from reaching its full yield potential. Among 30 elite maize inbred lines adapted to northern China, we identified two lines of extreme, but opposite, freezing tolerance levels—highly tolerant and highly sensitive. During the seedling stage of these two lines, we used RNA-seq to measure changes in maize whole genome transcriptome before and after freezing treatment. In total, 19,794 genes were expressed, of which 4550 exhibited differential expression due to either treatment (before or after freezing) or line type (tolerant or sensitive). Of the 4550 differently expressed genes, 948 exhibited differential expression due to treatment within line or lines under freezing condition. Analysis of gene ontology found that these 948 genes were significantly enriched for binding functions (DNA binding, ATP binding, and metal ion binding), protein kinase activity, and peptidase activity. Based on their enrichment, literature support, and significant levels of differential expression, 30 of these 948 genes were selected for quantitative real-time PCR (qRT-PCR) validation. The validation confirmed our RNA-Seq-based findings, with squared correlation coefficients of 80% and 50% in the tolerance and sensitive lines, respectively. This study provided valuable resources for further studies to enhance understanding of the molecular mechanisms underlying maize early freezing response and enable targeted breeding strategies for developing varieties with superior frost resistance to achieve yield potential. PMID:27774095

  14. Elevating crop disease resistance with cloned genes.

    PubMed

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

    2014-04-01

    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. PMID:24535396

  15. Elevating crop disease resistance with cloned genes

    PubMed Central

    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

    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. PMID:24535396

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

    PubMed Central

    Maiti, Amit K.; Nath, Swapan K.

    2012-01-01

    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. PMID:23000205

  17. Genome-wide association studies identify new targets in cardiovascular disease.

    PubMed

    Calkin, Anna C; Tontonoz, Peter

    2010-09-01

    The prevalence of cardiovascular disease (CVD) continues to increase worldwide, highlighting the need for new therapeutic strategies. A recent meta-analysis of genome-wide association studies (GWASs) of over 100,000 individuals published in Nature identified 59 new loci associated with lipid traits; of these, a locus on chromosome 1p13 was most strongly associated with low-density lipoprotein cholesterol (LDL-C) levels. An accompanying study in Nature identified SORT1 as the causal gene at the 1p13 locus and showed that increased expression of sortilin-1 protein in liver was associated with lower LDL-C levels and a reduced risk of myocardial infarction. Together, these studies provide strong validation of the utility of GWASs in identifying biological pathways relevant to CVD pathogenesis and perhaps treatment.

  18. Inflammatory bowel disease gene discovery. CRADA final report

    SciTech Connect

    1997-09-09

    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.

  19. Biomedical Information Extraction: Mining Disease Associated Genes from Literature

    ERIC Educational Resources Information Center

    Huang, Zhong

    2014-01-01

    Disease associated gene discovery is a critical step to realize the future of personalized medicine. However empirical and clinical validation of disease associated genes are time consuming and expensive. In silico discovery of disease associated genes from literature is therefore becoming the first essential step for biomarker discovery to…

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

    PubMed Central

    2014-01-01

    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. PMID:24995881

  1. Identifying mechanistic indicators of childhood asthma from blood gene expression

    EPA Science Inventory

    Asthmatic individuals have been identified as a susceptible subpopulation for air pollutants. However, asthma represents a syndrome with multiple probable etiologies, and the identification of these asthma endotypes is critical to accurately define the most susceptible subpopula...

  2. Analysis of genomic aberrations and gene expression profiling identifies novel lesions and pathways in myeloproliferative neoplasms

    PubMed Central

    Rice, K L; Lin, X; Wolniak, K; Ebert, B L; Berkofsky-Fessler, W; Buzzai, M; Sun, Y; Xi, C; Elkin, P; Levine, R; Golub, T; Gilliland, D G; Crispino, J D; Licht, J D; Zhang, W

    2011-01-01

    Polycythemia vera (PV), essential thrombocythemia and primary myelofibrosis, are myeloproliferative neoplasms (MPNs) with distinct clinical features and are associated with the JAK2V617F mutation. To identify genomic anomalies involved in the pathogenesis of these disorders, we profiled 87 MPN patients using Affymetrix 250K single-nucleotide polymorphism (SNP) arrays. Aberrations affecting chr9 were the most frequently observed and included 9pLOH (n=16), trisomy 9 (n=6) and amplifications of 9p13.3–23.3 (n=1), 9q33.1–34.13 (n=1) and 9q34.13 (n=6). Patients with trisomy 9 were associated with elevated JAK2V617F mutant allele burden, suggesting that gain of chr9 represents an alternative mechanism for increasing JAK2V617F dosage. Gene expression profiling of patients with and without chr9 abnormalities (+9, 9pLOH), identified genes potentially involved in disease pathogenesis including JAK2, STAT5B and MAPK14. We also observed recurrent gains of 1p36.31–36.33 (n=6), 17q21.2–q21.31 (n=5) and 17q25.1–25.3 (n=5) and deletions affecting 18p11.31–11.32 (n=8). Combined SNP and gene expression analysis identified aberrations affecting components of a non-canonical PRC2 complex (EZH1, SUZ12 and JARID2) and genes comprising a ‘HSC signature' (MLLT3, SMARCA2 and PBX1). We show that NFIB, which is amplified in 7/87 MPN patients and upregulated in PV CD34+ cells, protects cells from apoptosis induced by cytokine withdrawal. PMID:22829077

  3. Analysis of genomic aberrations and gene expression profiling identifies novel lesions and pathways in myeloproliferative neoplasms.

    PubMed

    Rice, K L; Lin, X; Wolniak, K; Ebert, B L; Berkofsky-Fessler, W; Buzzai, M; Sun, Y; Xi, C; Elkin, P; Levine, R; Golub, T; Gilliland, D G; Crispino, J D; Licht, J D; Zhang, W

    2011-11-01

    Polycythemia vera (PV), essential thrombocythemia and primary myelofibrosis, are myeloproliferative neoplasms (MPNs) with distinct clinical features and are associated with the JAK2V617F mutation. To identify genomic anomalies involved in the pathogenesis of these disorders, we profiled 87 MPN patients using Affymetrix 250K single-nucleotide polymorphism (SNP) arrays. Aberrations affecting chr9 were the most frequently observed and included 9pLOH (n=16), trisomy 9 (n=6) and amplifications of 9p13.3-23.3 (n=1), 9q33.1-34.13 (n=1) and 9q34.13 (n=6). Patients with trisomy 9 were associated with elevated JAK2V617F mutant allele burden, suggesting that gain of chr9 represents an alternative mechanism for increasing JAK2V617F dosage. Gene expression profiling of patients with and without chr9 abnormalities (+9, 9pLOH), identified genes potentially involved in disease pathogenesis including JAK2, STAT5B and MAPK14. We also observed recurrent gains of 1p36.31-36.33 (n=6), 17q21.2-q21.31 (n=5) and 17q25.1-25.3 (n=5) and deletions affecting 18p11.31-11.32 (n=8). Combined SNP and gene expression analysis identified aberrations affecting components of a non-canonical PRC2 complex (EZH1, SUZ12 and JARID2) and genes comprising a 'HSC signature' (MLLT3, SMARCA2 and PBX1). We show that NFIB, which is amplified in 7/87 MPN patients and upregulated in PV CD34+ cells, protects cells from apoptosis induced by cytokine withdrawal.

  4. A Genome-wide CRISPR Screen in Toxoplasma Identifies Essential Apicomplexan Genes.

    PubMed

    Sidik, Saima M; Huet, Diego; Ganesan, Suresh M; Huynh, My-Hang; Wang, Tim; Nasamu, Armiyaw S; Thiru, Prathapan; Saeij, Jeroen P J; Carruthers, Vern B; Niles, Jacquin C; Lourido, Sebastian

    2016-09-01

    Apicomplexan parasites are leading causes of human and livestock diseases such as malaria and toxoplasmosis, yet most of their genes remain uncharacterized. Here, we present the first genome-wide genetic screen of an apicomplexan. We adapted CRISPR/Cas9 to assess the contribution of each gene from the parasite Toxoplasma gondii during infection of human fibroblasts. Our analysis defines ∼200 previously uncharacterized, fitness-conferring genes unique to the phylum, from which 16 were investigated, revealing essential functions during infection of human cells. Secondary screens identify as an invasion factor the claudin-like apicomplexan microneme protein (CLAMP), which resembles mammalian tight-junction proteins and localizes to secretory organelles, making it critical to the initiation of infection. CLAMP is present throughout sequenced apicomplexan genomes and is essential during the asexual stages of the malaria parasite Plasmodium falciparum. These results provide broad-based functional information on T. gondii genes and will facilitate future approaches to expand the horizon of antiparasitic interventions. PMID:27594426

  5. Mutational analysis of PKD1 gene in a Chinese family with autosomal dominant polycystic kidney disease.

    PubMed

    Liu, Jingyan; Li, Lanrong; Liu, Qingmin

    2015-01-01

    Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary disease and common renal disease. Mutations of PKD genes are responsible for this disease. We analyzed a large Chinese family with ADPKD using Sanger sequencing to identify the mutation responsible for this disease. The family comprised 27 individuals including 10 ADPKD patients. These ADPKD patients had severe renal disease and most of them died very young. We analyzed 6 survival patients gene and found they all had C10529T mutation in exon 35 of PKD1 gene. We did not found gene mutation in any unaffected relatives or 300 unrelated controls. These findings suggested that the C10529T mutation in PKD1 gene might be the pathogenic mutation responsible for the disease in this family. PMID:26722532

  6. Mutational analysis of PKD1 gene in a Chinese family with autosomal dominant polycystic kidney disease

    PubMed Central

    Liu, Jingyan; Li, Lanrong; Liu, Qingmin

    2015-01-01

    Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary disease and common renal disease. Mutations of PKD genes are responsible for this disease. We analyzed a large Chinese family with ADPKD using Sanger sequencing to identify the mutation responsible for this disease. The family comprised 27 individuals including 10 ADPKD patients. These ADPKD patients had severe renal disease and most of them died very young. We analyzed 6 survival patients gene and found they all had C10529T mutation in exon 35 of PKD1 gene. We did not found gene mutation in any unaffected relatives or 300 unrelated controls. These findings suggested that the C10529T mutation in PKD1 gene might be the pathogenic mutation responsible for the disease in this family. PMID:26722532

  7. Dorothy Hodgkin Lecture 2014. Understanding genes identified by genome-wide association studies for type 2 diabetes.

    PubMed

    Rutter, G A

    2014-12-01

    Whilst the heritable nature of Type 2 diabetes has been recognized for many years, only in the past two decades have linkage analyses in families and genome-wide association studies in large populations begun to reveal the genetic landscape of the disease in detail. Whilst the former have provided a powerful means of identifying the genes responsible for monogenic forms of the disease, the latter highlight relatively large genomic regions. These often harbour multiple genes, whose relative contribution to exaggerated disease risk is uncertain. In the present study, the approaches that have been used to dissect the role of just a few (TCF7L2, SLC30A8, ADCY5, MTNR1B and CDKAL1) of the ~ 500 genes identified at dozens of implicated loci are described. These are usually selected based on the strength of their effect on disease risk, and predictions as to their likely biological role. Direct determination of the effects of identified polymorphisms on gene expression in disease-relevant tissues, notably the pancreatic islet, are then performed to identify genes whose expression is affected by a particular polymorphism. Subsequent functional analyses then involve perturbing gene expression in vitro in β-cell lines or isolated islets and in vivo in animal models. Although the majority of polymorphisms affect insulin production rather than action, and mainly affect the β cell, effects via other tissues may also contribute, requiring careful consideration in the design and interpretation of experiments in model systems. These considerations illustrate the scale of the task needed to exploit genome-wide association study data for the development of new therapeutic strategies.

  8. A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

    PubMed

    Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

    2015-01-01

    In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

  9. Transcriptome profiling to identify genes involved in peroxisome assembly and function.

    PubMed

    Smith, Jennifer J; Marelli, Marcello; Christmas, Rowan H; Vizeacoumar, Franco J; Dilworth, David J; Ideker, Trey; Galitski, Timothy; Dimitrov, Krassen; Rachubinski, Richard A; Aitchison, John D

    2002-07-22

    Yeast cells were induced to proliferate peroxisomes, and microarray transcriptional profiling was used to identify PEX genes encoding peroxins involved in peroxisome assembly and genes involved in peroxisome function. Clustering algorithms identified 224 genes with expression profiles similar to those of genes encoding peroxisomal proteins and genes involved in peroxisome biogenesis. Several previously uncharacterized genes were identified, two of which, YPL112c and YOR084w, encode proteins of the peroxisomal membrane and matrix, respectively. Ypl112p, renamed Pex25p, is a novel peroxin required for the regulation of peroxisome size and maintenance. These studies demonstrate the utility of comparative gene profiling as an alternative to functional assays to identify genes with roles in peroxisome biogenesis.

  10. Gene expression profiling of CD34+ cells identifies a molecular signature of chronic myeloid leukemia blast crisis.

    PubMed

    Zheng, C; Li, L; Haak, M; Brors, B; Frank, O; Giehl, M; Fabarius, A; Schatz, M; Weisser, A; Lorentz, C; Gretz, N; Hehlmann, R; Hochhaus, A; Seifarth, W

    2006-06-01

    Despite recent success in the treatment of early-stage disease, blastic phase (BP) of chronic myeloid leukemia (CML) that is characterized by rapid expansion of therapy-refractory and differentiation-arrested blasts, remains a therapeutic challenge. The development of resistance upon continuous administration of imatinib mesylate is associated with poor prognosis pointing to the need for alternative therapeutic strategies and a better understanding of the molecular mechanisms underlying disease progression. To identify transcriptional signatures that may explain pathological characteristics and aggressive behavior of BP blasts, we performed comparative gene expression profiling on CD34+ Ph+ cells purified from patients with untreated newly diagnosed chronic phase CML (CP, n=11) and from patients in BP (n=9) using Affymetrix oligonucleotide arrays. Supervised microarray data analysis revealed 114 differentially expressed genes (P<10(-4)), 34 genes displaying more than two-fold transcriptional changes when comparing CP and BP groups. While 24 of these genes were downregulated, 10 genes, especially suppressor of cytokine signalling 2 (SOCS2), CAMPATH-1 antigen (CD52), and four human leukocyte antigen-related genes were strongly overexpressed in BP. Expression of selected genes was validated by real-time-polymerase chain reaction and flow cytometry. Our data suggest the existence of a common gene expression profile of CML-BP and provide new insight into the molecular phenotype of blasts associated with disease progression and high malignancy. PMID:16617318

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

    PubMed Central

    2013-01-01

    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

  12. Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas.

    PubMed

    Zhou, Ruigang; Man, Yigang

    2016-04-01

    The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed genes (DEGs) and differentially methylated regions (DMRs), respectively, integrated analysis of the DEGs and DMRs was performed to detect their correlation. Subsequently, the WGCNA algorithm was applied to identify the significant modules and construct the co‑expression network associated with PAs. Furthermore, Gene Ontology enrichment analysis of the associated genes was performed using the Database for Annotation, Visualization and Integrated Discovery. A total number of 2,259 DEGs and 235 DMRs were screened out. Integrated analysis revealed that 30 DEGs were DMRs with prominent negative correlation (cor=‑0.82; P=0.02). Based on the DEGs, the gene co‑expression network was constructed, and nine network modules associated with PAs were identified. The functional analysis results showed that genes relevant to PAs were closely associated with cell differentiation modulation. The screened PA-associated genes were significantly different at the expression and methylation levels. These genes may be used as reliable candidate target genes for the treatment of PAs.

  13. Identifying Stress Transcription Factors Using Gene Expression and TF-Gene Association Data.

    PubMed

    Wu, Wei-Sheng; Chen, Bor-Sen

    2009-11-24

    Unicellular organisms such as yeasts have evolved to survive environmental stresses by rapidly reorganizing the genomic expression program to meet the challenges of harsh environments. The complex adaptation mechanisms to stress remain to be elucidated. In this study, we developed Stress Transcription Factor Identification Algorithm (STFIA), which integrates gene expression and TF-gene association data to identify the stress transcription factors (TFs) of six kinds of stresses. We identified some general stress TFs that are in response to various stresses, and some specific stress TFs that are in response to one specific stress. The biological significance of our findings is validated by the literature. We found that a small number of TFs may be sufficient to control a wide variety of expression patterns in yeast under different stresses. Two implications can be inferred from this observation. First, the adaptation mechanisms to different stresses may have a bow-tie structure. Second, there may exist extensive regulatory cross-talk among different stress responses. In conclusion, this study proposes a network of the regulators of stress responses and their mechanism of action.

  14. Personalized gene silencing therapeutics for Huntington disease.

    PubMed

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

    2014-07-01

    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.

  15. Detecting gene-gene interactions that underlie human diseases

    PubMed Central

    Cordell, Heather J.

    2010-01-01

    Following the identification of several disease-associated polymorphisms by whole genome association analysis, interest is now focussing on the detection of effects that, due to their interaction with other genetic (or environmental) factors, may not be identified by using standard single-locus tests. In addition to increasing power to detect association, there is also a hope detecting interactions between loci will allow us to elucidate the biological and biochemical pathways underpinning disease. Here I provide a critical survey of the current methodological approaches (and related software packages) used to detect interactions between genetic loci that contribute to human genetic disease. I also discuss the difficulties in determining the biologcal relevance of statistical interactions. PMID:19434077

  16. A yeast functional screen predicts new candidate ALS disease genes

    PubMed Central

    Couthouis, Julien; Hart, Michael P.; Shorter, James; DeJesus-Hernandez, Mariely; Erion, Renske; Oristano, Rachel; Liu, Annie X.; Ramos, Daniel; Jethava, Niti; Hosangadi, Divya; Epstein, James; Chiang, Ashley; Diaz, Zamia; Nakaya, Tadashi; Ibrahim, Fadia; Kim, Hyung-Jun; Solski, Jennifer A.; Williams, Kelly L.; Mojsilovic-Petrovic, Jelena; Ingre, Caroline; Boylan, Kevin; Graff-Radford, Neill R.; Dickson, Dennis W.; Clay-Falcone, Dana; Elman, Lauren; McCluskey, Leo; Greene, Robert; Kalb, Robert G.; Lee, Virginia M.-Y.; Trojanowski, John Q.; Ludolph, Albert; Robberecht, Wim; Andersen, Peter M.; Nicholson, Garth A.; Blair, Ian P.; King, Oliver D.; Bonini, Nancy M.; Van Deerlin, Vivianna; Rademakers, Rosa; Mourelatos, Zissimos; Gitler, Aaron D.

    2011-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating and universally fatal neurodegenerative disease. Mutations in two related RNA-binding proteins, TDP-43 and FUS, that harbor prion-like domains, cause some forms of ALS. There are at least 213 human proteins harboring RNA recognition motifs, including FUS and TDP-43, raising the possibility that additional RNA-binding proteins might contribute to ALS pathogenesis. We performed a systematic survey of these proteins to find additional candidates similar to TDP-43 and FUS, followed by bioinformatics to predict prion-like domains in a subset of them. We sequenced one of these genes, TAF15, in patients with ALS and identified missense variants, which were absent in a large number of healthy controls. These disease-associated variants of TAF15 caused formation of cytoplasmic foci when expressed in primary cultures of spinal cord neurons. Very similar to TDP-43 and FUS, TAF15 aggregated in vitro and conferred neurodegeneration in Drosophila, with the ALS-linked variants having a more severe effect than wild type. Immunohistochemistry of postmortem spinal cord tissue revealed mislocalization of TAF15 in motor neurons of patients with ALS. We propose that aggregation-prone RNA-binding proteins might contribute very broadly to ALS pathogenesis and the genes identified in our yeast functional screen, coupled with prion-like domain prediction analysis, now provide a powerful resource to facilitate ALS disease gene discovery. PMID:22065782

  17. Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes

    PubMed Central

    Scharfe, Curt; Lu, Henry Horng-Shing; Neuenburg, Jutta K.; Allen, Edward A.; Li, Guan-Cheng; Klopstock, Thomas; Cowan, Tina M.; Enns, Gregory M.; Davis, Ronald W.

    2009-01-01

    Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the

  18. Prioritization of Disease Susceptibility Genes Using LSM/SVD.

    PubMed

    Gong, Lejun; Yang, Ronggen; Yan, Qin; Sun, Xiao

    2013-12-01

    Understanding the role of genetics in diseases is one of the most important tasks in the postgenome era. It is generally too expensive and time consuming to perform experimental validation for all candidate genes related to disease. Computational methods play important roles for prioritizing these candidates. Herein, we propose an approach to prioritize disease genes using latent semantic mapping based on singular value decomposition. Our hypothesis is that similar functional genes are likely to cause similar diseases. Measuring the functional similarity between known disease susceptibility genes and unknown genes is to predict new disease susceptibility genes. Taking autism as an instance, the analysis results of the top ten genes prioritized demonstrate they might be autism susceptibility genes, which also indicates our approach could discover new disease susceptibility genes. The novel approach of disease gene prioritization could discover new disease susceptibility genes, and latent disease-gene relations. The prioritized results could also support the interpretive diversity and experimental views as computational evidence for disease researchers.

  19. Seven newly identified loci for autoimmune thyroid disease.

    PubMed

    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

    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

  20. Seven newly identified loci for autoimmune thyroid disease.

    PubMed

    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

    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.

  1. Novel Association Strategy with Copy Number Variation for Identifying New Risk Loci of Human Diseases

    PubMed Central

    Chen, Xianfeng; Li, Xinlei; Wang, Ping; Liu, Yang; Zhang, Zhenguo; Zhao, Guoping; Xu, Haiming; Zhu, Jun; Qin, Xueying; Chen, Suchao; Hu, Landian; Kong, Xiangyin

    2010-01-01

    Background Copy number variations (CNV) are important causal genetic variations for human disease; however, the lack of a statistical model has impeded the systematic testing of CNVs associated with disease in large-scale cohort. Methodology/Principal Findings Here, we developed a novel integrated strategy to test CNV-association in genome-wide case-control studies. We converted the single-nucleotide polymorphism (SNP) signal to copy number states using a well-trained hidden Markov model. We mapped the susceptible CNV-loci through SNP site-specific testing to cope with the physiological complexity of CNVs. We also ensured the credibility of the associated CNVs through further window-based CNV-pattern clustering. Genome-wide data with seven diseases were used to test our strategy and, in total, we identified 36 new susceptible loci that are associated with CNVs for the seven diseases: 5 with bipolar disorder, 4 with coronary artery disease, 1 with Crohn's disease, 7 with hypertension, 9 with rheumatoid arthritis, 7 with type 1 diabetes and 3 with type 2 diabetes. Fifteen of these identified loci were validated through genotype-association and physiological function from previous studies, which provide further confidence for our results. Notably, the genes associated with bipolar disorder converged in the phosphoinositide/calcium signaling, a well-known affected pathway in bipolar disorder, which further supports that CNVs have impact on bipolar disorder. Conclusions/Significance Our results demonstrated the effectiveness and robustness of our CNV-association analysis and provided an alternative avenue for discovering new associated loci of human diseases. PMID:20808825

  2. Candidate genes for limiting cholestatic intestinal injury identified by gene expression profiling

    PubMed Central

    Alaish, Samuel M; Timmons, Jennifer; Smith, Alexis; Buzza, Marguerite S; Murphy, Ebony; Zhao, Aiping; Sun, Yezhou; Turner, Douglas J; Shea-Donahue, Terez; Antalis, Toni M; Cross, Alan; Dorsey, Susan G

    2013-01-01

    The lack of bile flow from the liver into the intestine can have devastating complications including hepatic failure, sepsis, and even death. This pathologic condition known as cholestasis can result from etiologies as diverse as total parenteral nutrition (TPN), hepatitis, and pancreatic cancer. The intestinal injury associated with cholestasis has been shown to result in decreased intestinal resistance, increased bacterial translocation, and increased endotoxemia. Anecdotal clinical evidence suggests a genetic predisposition to exaggerated injury. Recent animal research on two different strains of inbred mice demonstrating different rates of bacterial translocation with different mortality rates supports this premise. In this study, a microarray analysis of intestinal tissue following common bile duct ligation (CBDL) performed under general anesthesia on these same two strains of inbred mice was done with the goal of identifying the potential molecular mechanistic pathways responsible. Over 500 genes were increased more than 2.0-fold following CBDL. The most promising candidate genes included major urinary proteins (MUPs), serine protease-1-inhibitor (Serpina1a), and lipocalin-2 (LCN-2). Quantitative polymerase chain reaction (qPCR) validated the microarray results for these candidate genes. In an in vitro experiment using differentiated intestinal epithelial cells, inhibition of MUP-1 by siRNA resulted in increased intestinal epithelial cell permeability. Diverse novel mechanisms involving the growth hormone pathway, the acute phase response, and the innate immune response are thus potential avenues for limiting cholestatic intestinal injury. Changes in gene expression were at times found to be not only due to the CBDL but also due to the murine strain. Should further studies in cholestatic patients demonstrate interindividual variability similar to what we have shown in mice, then a “personalized medicine” approach to cholestatic patients may become

  3. Genome Wide Association Study Identifies L3MBTL4 as a Novel Susceptibility Gene for Hypertension

    PubMed Central

    Liu, Xin; Hu, Cheng; Bao, Minghui; Li, Jing; Liu, Xiaoyan; Tan, Xuerui; Zhou, Yong; Chen, Yequn; Wu, Shouling; Chen, Shuohua; Zhang, Rong; Jiang, Feng; Jia, Weiping; Wang, Xingyu; Yang, Xinchun; Cai, Jun

    2016-01-01

    Hypertension is a major global health burden and a leading risk factor for cardiovascular diseases. Although its heritability has been documented previously, contributing loci identified to date account for only a small fraction of blood pressure (BP) variation, which strongly suggests the existence of undiscovered variants. To identify novel variants, we conducted a three staged genetic study in 21,990 hypertensive cases and normotensive controls. Four single nucleotide polymorphisms (SNPs) at three new genes (L3MBTL4 rs403814, Pmeta = 6.128 × 10−9; LOC729251, and TCEANC) and seven SNPs at five previously reported genes were identified as being significantly associated with hypertension. Through functional analysis, we found that L3MBTL4 is predominantly expressed in vascular smooth muscle cells and up-regulated in spontaneously hypertensive rats. Rats with ubiquitous over-expression of L3MBTL4 exhibited significantly elevated BP, increased thickness of the vascular media layer and cardiac hypertrophy. Mechanistically, L3MBTL4 over-expression could lead to down-regulation of latent transforming growth factor-β binding protein 1 (LTBP1), and phosphorylation activation of the mitogen-activated protein kinases (MAPK) signaling pathway, which is known to trigger the pathological progression of vascular remodeling and BP elevation. These findings pinpointed L3MBTL4 as a critical contributor to the development and progression of hypertension and uncovers a novel target for therapeutic intervention. PMID:27480026

  4. CFTR gene mutations in isolated chronic obstructive pulmonary disease

    SciTech Connect

    Pignatti, P.F.; Bombien, C.; Marigo, C.

    1994-09-01

    In order to identify a possible hereditary predisposition to the development of chronic obstructive pulmonary disease (COPD), we have looked for the presence of cystic fibrosis transmembrane regulator (CFTR) gene DNA sequence modifications in 28 unrelated patients with no signs of cystic fibrosis. The known mutations in Italian CF patients, as well as the most frequent worldwide CF mutations, were investigated. In addition, a denaturing gradient gel electrophoresis analysis of about half of the coding sequence of the gene in 56 chromosomes from the patients and in 102 chromosomes from control individuals affected by other pulmonary diseases and from normal controls was performed. Nine different CFTR gene mutations and polymorphisms were found in seven patients, a highly significant increase over controls. Two of the patients were compound heterozygotes. Two frequent CF mutations were detected: deletion F508 and R117H; two rare CF mutations: R1066C and 3667ins4; and five CF sequence variants: R75Q (which was also described as a disease-causing mutation in male sterility cases due to the absence of the vasa deferentia), G576A, 2736 A{r_arrow}G, L997F, and 3271+18C{r_arrow}T. Seven (78%) of the mutations are localized in transmembrane domains. Six (86%) of the patients with defined mutations and polymorphisms had bronchiectasis. These results indicate that CFTR gene mutations and sequence alterations may be involved in the etiopathogenesis of some cases of COPD.

  5. The impact of self-identified race on epidemiologic studies of gene expression.

    PubMed

    Sharma, Sunita; Murphy, Amy; Howrylak, Judie; Himes, Blanca; Cho, Michael H; Chu, Jen-Hwa; Hunninghake, Gary M; Fuhlbrigge, Anne; Klanderman, Barbara; Ziniti, John; Senter-Sylvia, Jody; Liu, Andy; Szefler, Stanley J; Strunk, Robert; Castro, Mario; Hansel, Nadia N; Diette, Gregory B; Vonakis, Becky M; Adkinson, N Franklin; Carey, Vincent J; Raby, Benjamin A

    2011-02-01

    Although population differences in gene expression have been established, the impact on differential gene expression studies in large populations is not well understood. We describe the effect of self-reported race on a gene expression study of lung function in asthma. We generated gene expression profiles for 254 young adults (205 non-Hispanic whites and 49 African Americans) with asthma on whom concurrent total RNA derived from peripheral blood CD4(+) lymphocytes and lung function measurements were obtained. We identified four principal components that explained 62% of the variance in gene expression. The dominant principal component, which explained 29% of the total variance in gene expression, was strongly associated with self-identified race (P<10(-16)). The impact of these racial differences was observed when we performed differential gene expression analysis of lung function. Using multivariate linear models, we tested whether gene expression was associated with a quantitative measure of lung function: pre-bronchodilator forced expiratory volume in one second (FEV(1)). Though unadjusted linear models of FEV(1) identified several genes strongly correlated with lung function, these correlations were due to racial differences in the distribution of both FEV(1) and gene expression, and were no longer statistically significant following adjustment for self-identified race. These results suggest that self-identified race is a critical confounding covariate in epidemiologic studies of gene expression and that, similar to genetic studies, careful consideration of self-identified race in gene expression profiling studies is needed to avoid spurious association.

  6. HLA and other gene associations with dengue disease severity.

    PubMed

    Stephens, H A F

    2010-01-01

    Large case control gene association studies have been performed on cohorts of dengue virus (DENV) infected patients identified in mainland Southeast Asia, South Asia and the Caribbean. Candidate genes that have shown statistically significant associations with DENV disease severity encode HLA molecules, cell receptors for IgG (FcGII), vitamin D and ICAM3 (DCSIGN or CD209), pathogen recognition molecules such as mannose binding lectin (MBL), blood related antigens including ABO and human platelet antigens (HPA1 and HPA2). In ethnic Thais with secondary infections a variety of HLA class I alleles (HLA-A 0203, 0207, A11, B 15, B 44, B 46, B 48, B 51, B 52), DCSIGN promoter polymorphisms and the AB blood group, independently associate with either susceptibility or resistance to dengue fever (DF) and the more severe dengue hemorrhagic fever (DHF). There is also evidence that some HLA associations with disease severity correlate with the DENV serotype inducing secondary infections. Taken together, there is now evidence that allelic variants of multiple gene loci involved in both acquired and innate immune responses contribute significantly to DENV disease outcome and severity. Further analysis of the genetic basis of severe DENV disease in different at risk populations may contribute to the development of new preventative and therapeutic interventions.

  7. A genomewide screen for chronic rhinosinusitis genes identifies a locus on chromosome 7q

    PubMed Central

    Pinto, Jayant M.; Hayes, M. Geoffrey; Schneider, Daniel; Naclerio, Robert M.; Ober, Carole

    2014-01-01

    Background Chronic rhinosinusitis is an important public health problem with substantial impact on patient quality of life and health care costs. We hypothesized that genetic variation may be one factor that affects this disease. Objective To identify genetic variation underlying susceptibility to chronic rhinosinusitis using a genome-wide approach. Methods We studied a religious isolate that practices a communal lifestyle and shares common environmental exposures. Using physical examination, medical interviews, and a review of medical records, we identified 8 individuals with chronic rhinosinusitis out of 291 screened. These 8 individuals were related to each other in a single 60 member, 9 generation pedigree. A genome-wide screen for loci influencing susceptibility to chronic rhinosinusitis using 1123 genome-wide markers was conducted. Results The largest linkage peak (P = 0.0023; 127.15 cM, equivalent to LOD=2.01) was on chromosome 7q31.1-7q32.1, 7q31 (127.15 cM; 1-LOD support region: 115cM to 135cM) and included the CFTR locus. Genotyping of 38 mutations in the CFTR gene did not reveal variation accounting for this linkage signal. Conclusion Understanding the genes involved in chronic rhinosinusitis may lead to improvements in its diagnosis and treatment. Our results represent the first genome-wide screen for chronic rhinosinusitis and suggest that a locus on 7q31.1-7q32.1 influences disease susceptibility. This may be the CFTR gene or another nearby locus. PMID:18622306

  8. Gene expression profiles in the rat streptococcal cell wall-induced arthritis model identified using microarray analysis.

    PubMed

    Rioja, Inmaculada; Clayton, Chris L; Graham, Simon J; Life, Paul F; Dickson, Marion C

    2005-01-01

    Experimental arthritis models are considered valuable tools for delineating mechanisms of inflammation and autoimmune phenomena. Use of microarray-based methods represents a new and challenging approach that allows molecular dissection of complex autoimmune diseases such as arthritis. In order to characterize the temporal gene expression profile in joints from the reactivation model of streptococcal cell wall (SCW)-induced arthritis in Lewis (LEW/N) rats, total RNA was extracted from ankle joints from naive, SCW injected, or phosphate buffered saline injected animals (time course study) and gene expression was analyzed using Affymetrix oligonucleotide microarray technology (RAE230A). After normalization and statistical analysis of data, 631 differentially expressed genes were sorted into clusters based on their levels and kinetics of expression using Spotfire profile search and K-mean cluster analysis. Microarray-based data for a subset of genes were validated using real-time PCR TaqMan analysis. Analysis of the microarray data identified 631 genes (441 upregulated and 190 downregulated) that were differentially expressed (Delta > 1.8, P < 0.01), showing specific levels and patterns of gene expression. The genes exhibiting the highest fold increase in expression on days -13.8, -13, or 3 were involved in chemotaxis, inflammatory response, cell adhesion and extracellular matrix remodelling. Transcriptome analysis identified 10 upregulated genes (Delta > 5), which have not previously been associated with arthritis pathology and are located in genomic regions associated with autoimmune disease. The majority of the downregulated genes were associated with metabolism, transport and regulation of muscle development. In conclusion, the present study describes the temporal expression of multiple disease-associated genes with potential pathophysiological roles in the reactivation model of SCW-induced arthritis in Lewis (LEW/N) rat. These findings improve our understanding of

  9. Shared Genetic Etiology between Type 2 Diabetes and Alzheimer's Disease Identified by Bioinformatics Analysis.

    PubMed

    Gao, Lei; Cui, Zhen; Shen, Liang; Ji, Hong-Fang

    2015-01-01

    Type 2 diabetes (T2D) and Alzheimer's disease (AD) are two major health issues, and increasing evidence in recent years supports the close connection between these two diseases. The present study aimed to explore the shared genetic etiology underlying T2D and AD based on the available genome wide association studies (GWAS) data collected through August 2014. We performed bioinformatics analyses based on GWAS data of T2D and AD on single nucleotide polymorphisms (SNPs), gene, and pathway levels, respectively. Six SNPs (rs111789331, rs12721046, rs12721051, rs4420638, rs56131196, and rs66626994) were identified for the first time to be shared genetic factors between T2D and AD. Further functional enrichment analysis found lipid metabolism related pathways to be common between these two disorders. The findings may have important implications for future mechanistic and interventional studies for T2D and AD. PMID:26639962

  10. Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach

    PubMed Central

    Yuan, Fei; Zhou, You; Wang, Meng; Yang, Jing; Wu, Kai; Lu, Changhong; Kong, Xiangyin; Cai, Yu-Dong

    2015-01-01

    Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486

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

    PubMed Central

    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; Lagacé, Caroline; Neale, Benjamin; Lo, Ken Sin; Schumm, Phil; Törkvist, 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

    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. PMID:21983784

  12. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

    PubMed

    Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

    2016-04-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

  13. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development

    PubMed Central

    Takeda, Haruna; Rust, Alistair G.; Ward, Jerrold M.; Yew, Christopher Chin Kuan; Jenkins, Nancy A.; Copeland, Neal G.

    2016-01-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4+/− mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

  14. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

    PubMed

    Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

    2016-04-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

  15. A new method for identifying causal genes of schizophrenia and anti-tuberculosis drug-induced hepatotoxicity

    PubMed Central

    Huang, Tao; Liu, Cheng-Lin; Li, Lin-Lin; Cai, Mei-Hong; Chen, Wen-Zhong; Xu, Yi-Feng; O’Reilly, Paul F.; Cai, Lei; He, Lin

    2016-01-01

    Schizophrenia (SCZ) may cause tuberculosis, the treatments for which can induce anti-tuberculosis drug-induced hepatotoxicity (ATDH) and SCZ-like disorders. To date, the causal genes of both SCZ and ATDH are unknown. To identify them, we proposed a new network-based method by integrating network random walk with restart algorithm, gene set enrichment analysis, and hypergeometric test; using this method, we identified 500 common causal genes. For gene validation, we created a regularly updated online database ATDH-SCZgenes and conducted a systematic meta-analysis of the association of each gene with either disease. Till now, only GSTM1 and GSTT1 have been well studied with respect to both diseases; and a total of 23 high-quality association studies were collected for the current meta-analysis validation. Finally, the GSTM1 present genotype was confirmed to be significantly associated with both ATDH [Odds Ratio (OR): 0.71, 95% confidence interval (CI): 0.56–0.90, P = 0.005] and SCZ (OR: 0.78, 95% CI: 0.66–0.92, P = 0.004) according to the random-effect model. Furthermore, these significant results were supported by “moderate” evidence according to the Venice criteria. Our findings indicate that GSTM1 may be a causal gene of both ATDH and SCZ, although further validation pertaining to other genes, such as CYP2E1 or DRD2, is necessary. PMID:27580934

  16. A new method for identifying causal genes of schizophrenia and anti-tuberculosis drug-induced hepatotoxicity.

    PubMed

    Huang, Tao; Liu, Cheng-Lin; Li, Lin-Lin; Cai, Mei-Hong; Chen, Wen-Zhong; Xu, Yi-Feng; O'Reilly, Paul F; Cai, Lei; He, Lin

    2016-01-01

    Schizophrenia (SCZ) may cause tuberculosis, the treatments for which can induce anti-tuberculosis drug-induced hepatotoxicity (ATDH) and SCZ-like disorders. To date, the causal genes of both SCZ and ATDH are unknown. To identify them, we proposed a new network-based method by integrating network random walk with restart algorithm, gene set enrichment analysis, and hypergeometric test; using this method, we identified 500 common causal genes. For gene validation, we created a regularly updated online database ATDH-SCZgenes and conducted a systematic meta-analysis of the association of each gene with either disease. Till now, only GSTM1 and GSTT1 have been well studied with respect to both diseases; and a total of 23 high-quality association studies were collected for the current meta-analysis validation. Finally, the GSTM1 present genotype was confirmed to be significantly associated with both ATDH [Odds Ratio (OR): 0.71, 95% confidence interval (CI): 0.56-0.90, P = 0.005] and SCZ (OR: 0.78, 95% CI: 0.66-0.92, P = 0.004) according to the random-effect model. Furthermore, these significant results were supported by "moderate" evidence according to the Venice criteria. Our findings indicate that GSTM1 may be a causal gene of both ATDH and SCZ, although further validation pertaining to other genes, such as CYP2E1 or DRD2, is necessary. PMID:27580934

  17. Gene-environment interactions in ocular diseases.

    PubMed

    Sacca, S C; Bolognesi, C; Battistella, A; Bagnis, A; Izzotti, A

    2009-07-10

    Degenerative ocular diseases are widespread in the population and represent a major cause of reversible and irreversible blindness. Scientific evidences have been accumulating supporting the role of genotoxic damage and gene environment interactions in the pathogenesis of these diseases mainly including glaucoma, age-related macular degeneration, and cataract. Glaucoma, in its degenerative form, is characterized by the degeneration of the trabecular meshwork, the tissue of the anterior chamber of the eye devoted to aqueous-humour outflow. Such a degenerative process results in intra-ocular pressure increase and progressive damage of optic nerve head. Oxidative stress and DNA damage play an important role in inducing the degeneration of these well differentiated target tissues in which DNA damage results in a progressive cell loss. Macular degeneration is a common age-related disease affecting the central regions of the retina inducing progressive accumulation of oxidized lipoproteins and neovascularization. Environmental genotoxic risk factors include diet, light, and cigarette smoke paralleled by individual susceptibility as determined by adverse genetic assets. Cataract is a progressive opacity of the crystalline lens resulting from molecular damages induced by various risk factors including UV-containing light. This disease has been related to a failure in antioxidant defences. Experimental study provides evidence that cataract patients possess higher basal level of DNA damage, as evaluated by Comet test, in lymphocytes than controls. This finding is paralleled by the higher susceptibility to oxidative stress observed in the same patients. These novel experimental data further support the role of DNA damage as a main factor contributing to cataract onset. In conclusion, the examined degenerative ocular diseases recognise environmental risk factors often displaying genotoxic attitudes. Whenever these factors target individuals who are susceptible due their

  18. Identifying host genetic risk factors in the context of public health surveillance for invasive pneumococcal disease.

    PubMed

    Lingappa, Jairam R; Dumitrescu, Logan; Zimmer, Shanta M; Lynfield, Ruth; McNicholl, Janet M; Messonnier, Nancy E; Whitney, Cynthia G; Crawford, Dana C

    2011-01-01

    Host genetic factors that modify risk of pneumococcal disease may help target future public health interventions to individuals at highest risk of disease. We linked data from population-based surveillance for invasive pneumococcal disease (IPD) with state-based newborn dried bloodspot repositories to identify biological samples from individuals who developed invasive pneumococcal disease. Genomic DNA was extracted from 366 case and 732 anonymous control samples. TagSNPs were selected in 34 candidate genes thought to be associated with host response to invasive pneumococcal disease, and a total of 326 variants were successfully genotyped. Among 543 European Americans (EA) (182 cases and 361 controls), and 166 African Americans (AA) (53 cases and 113 controls), common variants in surfactant protein D (SFTPD) are consistently underrepresented in IPD. SFTPD variants with the strongest association for IPD are intronic rs17886286 (allelic OR 0.45, 95% confidence interval (CI) [0.25, 0.82], with p = 0.007) in EA and 5' flanking rs12219080 (allelic OR 0.32, 95%CI [0.13, 0.78], with p = 0.009) in AA. Variants in CD46 and IL1R1 are also associated with IPD in both EA and AA, but with effects in different directions; FAS, IL1B, IL4, IL10, IL12B, SFTPA1, SFTPB, and PTAFR variants are associated (p≤0.05) with IPD in EA or AA. We conclude that variants in SFTPD may protect against IPD in EA and AA and genetic variation in other host response pathways may also contribute to risk of IPD. While our associations are not corrected for multiple comparisons and therefore must be replicated in additional cohorts, this pilot study underscores the feasibility of integrating public health surveillance with existing, prospectively collected, newborn dried blood spot repositories to identify host genetic factors associated with infectious diseases.

  19. Gene expression profiling of dengue infected human primary cells identifies secreted mediators in vivo

    PubMed Central

    Becerra, Aniuska; Warke, Rajas V.; Martin, Katherine; Xhaja, Kris; de Bosch, Norma; Rothman, Alan L.; Bosch, Irene

    2009-01-01

    We used gene expression profiling of human primary cells infected in vitro with dengue virus (DENV) as a tool to identify secreted mediators induced in response to the acute infection. Affymetrix Genechip analysis of human primary monocytes, B cells and dendritic cells infected with DENV in vitro revealed a strong induction of monocyte chemotactic protein 2 (MCP-2/CCL8), interferon gamma-induced protein 10 (IP-10/CXCL10) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL/TNFSF10). The expression of these genes was confirmed in dendritic cells infected with DENV in vitro at mRNA and protein levels. A prospectively enrolled cohort of DENV-infected Venezuelan patients was used to measure the levels of these proteins in serum during three different periods of the disease. Results showed significant increase of MCP-2, IP-10 and TRAIL levels in DENV-infected patients during the febrile period, when compared to healthy donors and patients with other febrile illnesses. MCP-2 and IP-10 levels were still elevated during the post-febrile period while TRAIL levels dropped close to normal after defervescense. Patients with primary infections had higher TRAIL levels than patients with secondary infections during the febrile period of the disease. Increased levels of IP-10, TRAIL and MCP-2 in acute DENV infections suggest a role for these mediators in the immune response to the infection. PMID:19551822

  20. Validating GWAS-Identified Risk Loci for Alzheimer's Disease in Han Chinese Populations.

    PubMed

    Wang, Hui-Zhen; Bi, Rui; Hu, Qiu-Xiang; Xiang, Qun; Zhang, Chen; Zhang, Deng-Feng; Zhang, Wen; Ma, Xiaohong; Guo, Wanjun; Deng, Wei; Zhao, Liansheng; Ni, Peiyan; Li, Mingli; Fang, Yiru; Li, Tao; Yao, Yong-Gang

    2016-01-01

    In recent years, genome-wide association studies (GWASs) have identified many novel susceptible genes/loci for Alzheimer's disease (AD). However, most of these studies were conducted in European and populations of European origin, and limited studies have been performed in Han Chinese. In this study, we genotyped 14 single-nucleotide polymorphisms (SNPs) in eight GWAS-reported AD risk genes in 1509 individuals comprising two independent Han Chinese case-control cohorts. Four SNPs (rs11234495, rs592297, rs676733, and rs3851179) in the PICALM gene were significantly associated with late-onset (LO)-AD in populations from Southwest China, whereas SNPs rs744373 (BIN1), rs9331942 (CLU), and rs670139 (MS4A4E) were linked to LO-AD in populations from East China. In the combined Han Chinese population, positive associations were observed between PICALM, CLU, MS4A4E genes, and LO-AD. The association between rs3851179 (PICALM), rs744373 (BIN1), and AD was further confirmed by meta-analysis of Asian populations. Our study verified the association between PICALM, BIN1, CLU, and MS4A4E variants and AD susceptibility in Han Chinese populations. We also discerned some regional differences concerning AD susceptibility SNPs.

  1. Identifying Multimodal Intermediate Phenotypes Between Genetic Risk Factors and Disease Status in Alzheimer's Disease.

    PubMed

    Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Saykin, Andrew J; Zhang, Daoqiang; Shen, Li

    2016-10-01

    Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer's disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

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

    PubMed Central

    2010-01-01

    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. PMID:20459635

  3. A Multi-Layered Screening Method to Identify Plant Regulatory Genes.

    PubMed

    Kim, Chang-Kug; Kim, Jin-A; Choi, Ji-Weon; Jeong, In-Seon; Moon, Yi-Seul; Park, Dong-Suk; Seol, Young-Joo; Kim, Yong-Kab; Kim, Yong-Hwan; Kim, Yeon-Ki

    2014-01-01

    We used a seven-step process to identify genes involved in glucosinolate biosynthesis and metabolism in the Chinese cabbage (Brassica rapa). We constructed an annotated data set with 34,570 unigenes from B. rapa and predicted 11,526 glucosinolate-related candidate genes using expression profiles generated across nine stages of development on a 47k-gene microarray. Using our multi-layered screening method, we screened 392 transcription factors, 843 pathway genes, and 4,162 ortholog genes associated with glucosinolate-related biosynthesis. Finally, we identified five genes by comparison of the pathway-network genes including the transcription-factor genes and the ortholog-ontology genes. The five genes were anchored to the chromosomes of B. rapa to characterize their genetic-map positions, and phylogenetic reconstruction with homologous genes was performed. These anchored genes were verified by reverse-transcription polymerase chain reaction. While the five genes identified by our multi-layered screen require further characterization and validation, our study demonstrates the power of multi-layered screening after initial identification of genes on microarrays.

  4. DGEM--a microarray gene expression database for primary human disease tissues.

    PubMed

    Xia, Yuni; Campen, Andrew; Rigsby, Dan; Guo, Ying; Feng, Xingdong; Su, Eric W; Palakal, Mathew; Li, Shuyu

    2007-01-01

    Gene expression patterns can reflect gene regulations in human tissues under normal or pathologic conditions. Gene expression profiling data from studies of primary human disease samples are particularly valuable since these studies often span many years in order to collect patient clinical information and achieve a large sample size. Disease-to-Gene Expression Mapper (DGEM) provides a beneficial community resource to access and analyze these data; it currently includes Affymetrix oligonucleotide array datasets for more than 40 human diseases and 1400 samples. The data are normalized to the same scale and stored in a relational database. A statistical-analysis pipeline was implemented to identify genes abnormally expressed in disease tissues or genes whose expressions are associated with clinical parameters such as cancer patient survival. Data-mining results can be queried through a web-based interface at http://dgem.dhcp.iupui.edu/. The query tool enables dynamic generation of graphs and tables that are further linked to major gene and pathway resources that connect the data to relevant biology, including Entrez Gene and Kyoto Encyclopedia of Genes and Genomes (KEGG). In summary, DGEM provides scientists and physicians a valuable tool to study disease mechanisms, to discover potential disease biomarkers for diagnosis and prognosis, and to identify novel gene targets for drug discovery. The source code is freely available for non-profit use, on request to the authors. PMID:17570735

  5. Identification of candidates for human disease genes using large-scale PCR mapping of gene-based STSs

    SciTech Connect

    Berry, R.; Stevens, T.J.; Wilcox, A.S.

    1994-09-01

    We have developed a strategy for the rapid identification of possible human disease/syndrome genes. Using this procedure we found candidates for 45 human disease/syndrome genes from the first 200 genes mapped. New human genes are identified through automated single-pass sequencing into the 3{prime} untranslated (3{prime}UT) regions of human cDNAs. Primers derived from the 3{prime}UT region sequences, representing gene-based STSs, are used for PCR analyses of the CEPH megabase YAC DNA pools. With this approach {approximately}18,000 megabase YACs can be screened and a single YAC identified using only 52 PCR reactions. The YAC localization in conjunction with other mapping approaches, such as PCR mapping to chromosomes by means of somatic hybrids, allows mapping to chromosomal band locations. In this manner, each gene can be associated with its own STS which in turn specifies both a corresponding genomic clone and a specific location in the genome. These locations can be compared to purported locations of disease genes listed in Online Mendelian Inheritance in Man. Using our current collection of >3,000 human brain cDNA sequences as a resource, we have carried out a proof of principle study in which {approximately}200 cDNAs were mapped to YACs within a few months. Appropriate scale up of this strategy could permit mapping of most human genes and identification of many candidate disease genes over the next few years.

  6. Aging syndrome genes and premature coronary artery disease

    PubMed Central

    Low, Adrian F; O'Donnell, Christopher J; Kathiresan, Sekar; Everett, Brendan; Chae, Claudia U; Shaw, Stanley Y; Ellinor, Patrick T; MacRae, Calum A

    2005-01-01

    Background Vascular disease is a feature of aging, and coronary vascular events are a major source of morbidity and mortality in rare premature aging syndromes. One such syndrome is caused by mutations in the lamin A/C (LMNA) gene, which also has been implicated in familial insulin resistance. A second gene related to premature aging in man and in murine models is the KLOTHO gene, a hypomorphic variant of which (KL-VS) is significantly more common in the first-degree relatives of patients with premature coronary artery disease (CAD). We evaluated whether common variants at the LMNA or KLOTHO genes are associated with rigorously defined premature CAD. Methods We identified 295 patients presenting with premature acute coronary syndromes confirmed by angiography. A control group of 145 patients with no evidence of CAD was recruited from outpatient referral clinics. Comprehensive haplotyping of the entire LMNA gene, including the promoter and untranslated regions, was performed using a combination of TaqMan® probes and direct sequencing of 14 haplotype-tagging single nucleotide polymorphisms (SNPs). The KL-VS variant of the KLOTHO gene was typed using restriction digest of a PCR amplicon. Results Two SNPs that were not in Hardy Weinberg equilibrium were excluded from analysis. We observed no significant differences in allele, genotype or haplotype frequencies at the LMNA or KLOTHO loci between the two groups. In addition, there was no evidence of excess homozygosity at the LMNA locus. Conclusion Our data do not support the hypothesis that premature CAD is associated with common variants in the progeroid syndrome genes LMNA and KLOTHO. PMID:16262891

  7. A Systems Genetics Approach Identifies CXCL14, ITGAX, and LPCAT2 as Novel Aggressive Prostate Cancer Susceptibility Genes

    PubMed Central

    Andreas, Jonathan; Patel, Shashank J.; Zhang, Suiyuan; Chines, Peter; Elkahloun, Abdel; Chandrasekharappa, Settara; Gutkind, J. Silvio; Molinolo, Alfredo A.; Crawford, Nigel P. S.

    2014-01-01

    Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL) mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ) F2 intercross males (n = 228), which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ) F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322) were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A) were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2) harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such approaches will

  8. Metabolic disruption identified in the Huntington's disease transgenic sheep model.

    PubMed

    Handley, Renee R; Reid, Suzanne J; Patassini, Stefano; Rudiger, Skye R; Obolonkin, Vladimir; McLaughlan, Clive J; Jacobsen, Jessie C; Gusella, James F; MacDonald, Marcy E; Waldvogel, Henry J; Bawden, C Simon; Faull, Richard L M; Snell, Russell G

    2016-02-11

    Huntington's disease (HD) is a dominantly inherited, progressive neurodegenerative disorder caused by a CAG repeat expansion within exon 1 of HTT, encoding huntingtin. There are no therapies that can delay the progression of this devastating disease. One feature of HD that may play a critical role in its pathogenesis is metabolic disruption. Consequently, we undertook a comparative study of metabolites in our transgenic sheep model of HD (OVT73). This model does not display overt symptoms of HD but has circadian rhythm alterations and molecular changes characteristic of the early phase disease. Quantitative metabolite profiles were generated from the motor cortex, hippocampus, cerebellum and liver tissue of 5 year old transgenic sheep and matched controls by gas chromatography-mass spectrometry. Differentially abundant metabolites were evident in the cerebellum and liver. There was striking tissue-specificity, with predominantly amino acids affected in the transgenic cerebellum and fatty acids in the transgenic liver, which together may indicate a hyper-metabolic state. Furthermore, there were more strong pair-wise correlations of metabolite abundance in transgenic than in wild-type cerebellum and liver, suggesting altered metabolic constraints. Together these differences indicate a metabolic disruption in the sheep model of HD and could provide insight into the presymptomatic human disease.

  9. 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...

  10. Metabolic disruption identified in the Huntington's disease transgenic sheep model.

    PubMed

    Handley, Renee R; Reid, Suzanne J; Patassini, Stefano; Rudiger, Skye R; Obolonkin, Vladimir; McLaughlan, Clive J; Jacobsen, Jessie C; Gusella, James F; MacDonald, Marcy E; Waldvogel, Henry J; Bawden, C Simon; Faull, Richard L M; Snell, Russell G

    2016-01-01

    Huntington's disease (HD) is a dominantly inherited, progressive neurodegenerative disorder caused by a CAG repeat expansion within exon 1 of HTT, encoding huntingtin. There are no therapies that can delay the progression of this devastating disease. One feature of HD that may play a critical role in its pathogenesis is metabolic disruption. Consequently, we undertook a comparative study of metabolites in our transgenic sheep model of HD (OVT73). This model does not display overt symptoms of HD but has circadian rhythm alterations and molecular changes characteristic of the early phase disease. Quantitative metabolite profiles were generated from the motor cortex, hippocampus, cerebellum and liver tissue of 5 year old transgenic sheep and matched controls by gas chromatography-mass spectrometry. Differentially abundant metabolites were evident in the cerebellum and liver. There was striking tissue-specificity, with predominantly amino acids affected in the transgenic cerebellum and fatty acids in the transgenic liver, which together may indicate a hyper-metabolic state. Furthermore, there were more strong pair-wise correlations of metabolite abundance in transgenic than in wild-type cerebellum and liver, suggesting altered metabolic constraints. Together these differences indicate a metabolic disruption in the sheep model of HD and could provide insight into the presymptomatic human disease. PMID:26864449

  11. Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network

    PubMed Central

    Shi, Ying; Li, Li-Peng; Ren, Hui

    2014-01-01

    Gastric cancer, as one of the leading causes of cancer related deaths worldwide, causes about 800,000 deaths per year. Up to now, the mechanism underlying this disease is still not totally uncovered. Identification of related genes of this disease is an important step which can help to understand the mechanism underlying this disease, thereby designing effective treatments. In this study, some novel gastric cancer related genes were discovered based on the knowledge of known gastric cancer related ones. These genes were searched by applying the shortest path algorithm in protein-protein interaction network. The analysis results suggest that some of them are indeed involved in the biological process of gastric cancer, which indicates that they are the actual gastric cancer related genes with high probability. It is hopeful that the findings in this study may help promote the study of this disease and the methods can provide new insights to study various diseases. PMID:24729971

  12. Characterization of candidate genes in inflammatory bowel disease-associated risk loci.

    PubMed

    Peloquin, Joanna M; Goel, Gautam; Kong, Lingjia; Huang, Hailiang; Haritunians, Talin; Sartor, R Balfour; Daly, Mark J; Newberry, Rodney D; McGovern, Dermot P; Yajnik, Vijay; Lira, Sergio A; Xavier, Ramnik J

    2016-01-01

    GWAS have linked SNPs to risk of inflammatory bowel disease (IBD), but a systematic characterization of disease-associated genes has been lacking. Prior studies utilized microarrays that did not capture many genes encoded within risk loci or defined expression quantitative trait loci (eQTLs) using peripheral blood, which is not the target tissue in IBD. To address these gaps, we sought to characterize the expression of IBD-associated risk genes in disease-relevant tissues and in the setting of active IBD. Terminal ileal (TI) and colonic mucosal tissues were obtained from patients with Crohn's disease or ulcerative colitis and from healthy controls. We developed a NanoString code set to profile 678 genes within IBD risk loci. A subset of patients and controls were genotyped for IBD-associated risk SNPs. Analyses included differential expression and variance analysis, weighted gene coexpression network analysis, and eQTL analysis. We identified 116 genes that discriminate between healthy TI and colon samples and uncovered patterns in variance of gene expression that highlight heterogeneity of disease. We identified 107 coexpressed gene pairs for which transcriptional regulation is either conserved or reversed in an inflammation-independent or -dependent manner. We demonstrate that on average approximately 60% of disease-associated genes are differentially expressed in inflamed tissue. Last, we identified eQTLs with either genotype-only effects on expression or an interaction effect between genotype and inflammation. Our data reinforce tissue specificity of expression in disease-associated candidate genes, highlight genes and gene pairs that are regulated in disease-relevant tissue and inflammation, and provide a foundation to advance the understanding of IBD pathogenesis. PMID:27668286

  13. Effective Boolean dynamics analysis to identify functionally important genes in large-scale signaling networks.

    PubMed

    Trinh, Hung-Cuong; Kwon, Yung-Keun

    2015-11-01

    Efficiently identifying functionally important genes in order to understand the minimal requirements of normal cellular development is challenging. To this end, a variety of structural measures have been proposed and their effectiveness has been investigated in recent literature; however, few studies have shown the effectiveness of dynamics-based measures. This led us to investigate a dynamic measure to identify functionally important genes, and the effectiveness of which was verified through application on two large-scale human signaling networks. We specifically consider Boolean sensitivity-based dynamics against an update-rule perturbation (BSU) as a dynamic measure. Through investigations on two large-scale human signaling networks, we found that genes with relatively high BSU values show slower evolutionary rate and higher proportions of essential genes and drug targets than other genes. Gene-ontology analysis showed clear differences between the former and latter groups of genes. Furthermore, we compare the identification accuracies of essential genes and drug targets via BSU and five well-known structural measures. Although BSU did not always show the best performance, it effectively identified the putative set of genes, which is significantly different from the results obtained via the structural measures. Most interestingly, BSU showed the highest synergy effect in identifying the functionally important genes in conjunction with other measures. Our results imply that Boolean-sensitive dynamics can be used as a measure to effectively identify functionally important genes in signaling networks.

  14. Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis.

    PubMed

    Kazmi, Nabila; Gaunt, Tom R

    2016-01-01

    Cardiovascular disease (including coronary artery disease and myocardial infarction) is one of the leading causes of death in Europe, and is influenced by both environmental and genetic factors. With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. We analyzed gene expression data from blood samples taken from normal people (n = 21), non-significant coronary artery disease (n = 93), patients with unstable angina (n = 16), stable coronary artery disease (n = 14) and myocardial infarction (MI; n = 207). We used a feature selection approach to identify a set of gene expression variables which successfully differentiate different cardiovascular diseases. The initial features were discovered by fitting a linear model for each probe set across all arrays of normal individuals and patients with myocardial infarction. Three different feature optimisation algorithms were devised which identified two discriminating sets of genes, one using MI and normal controls (total genes = 6) and another one using MI and unstable angina patients (total genes = 7). In all our classification approaches we used a non-parametric k-nearest neighbour (KNN) classification method (k = 3). The results proved the diagnostic robustness of the final feature sets in discriminating patients with myocardial infarction from healthy controls. Interestingly it also showed efficacy in discriminating myocardial infarction patients from patients with clinical symptoms of cardiac ischemia but no myocardial necrosis or stable coronary artery disease, despite the influence of batch effects and different microarray gene chips and platforms.

  15. Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis

    PubMed Central

    Kazmi, Nabila; Gaunt, Tom R.

    2016-01-01

    Cardiovascular disease (including coronary artery disease and myocardial infarction) is one of the leading causes of death in Europe, and is influenced by both environmental and genetic factors. With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. We analyzed gene expression data from blood samples taken from normal people (n = 21), non-significant coronary artery disease (n = 93), patients with unstable angina (n = 16), stable coronary artery disease (n = 14) and myocardial infarction (MI; n = 207). We used a feature selection approach to identify a set of gene expression variables which successfully differentiate different cardiovascular diseases. The initial features were discovered by fitting a linear model for each probe set across all arrays of normal individuals and patients with myocardial infarction. Three different feature optimisation algorithms were devised which identified two discriminating sets of genes, one using MI and normal controls (total genes = 6) and another one using MI and unstable angina patients (total genes = 7). In all our classification approaches we used a non-parametric k-nearest neighbour (KNN) classification method (k = 3). The results proved the diagnostic robustness of the final feature sets in discriminating patients with myocardial infarction from healthy controls. Interestingly it also showed efficacy in discriminating myocardial infarction patients from patients with clinical symptoms of cardiac ischemia but no myocardial necrosis or stable coronary artery disease, despite the influence of batch effects and different microarray gene chips and platforms. PMID:26930047

  16. A network-based method for identifying prognostic gene modules in lung squamous carcinoma

    PubMed Central

    Zhang, Kaitai; Wang, Guiqi; Zhang, Lei; An, Ning; Cheng, Shujun

    2016-01-01

    Similarities in gene expression between both developing embryonic and precancerous tissues and cancer tissues may help identify much-needed biomarkers and therapeutic targets in lung squamous carcinoma. In this study, human lung samples representing ten successive time points, from embryonic development to carcinogenesis, were used to construct global gene expression profiles. Differentially expressed genes with similar expression in precancerous and cancer samples were identified. Using a network-based greedy searching algorithm to analyze the training cohort (n = 69) and three independent testing cohorts, we successfully identified a significant 22-gene module in which expression levels were correlated with overall survival in lung squamous carcinoma patients. PMID:26919109

  17. Rapid-Throughput Skeletal Phenotyping of 100 Knockout Mice Identifies 9 New Genes That Determine Bone Strength

    PubMed Central

    Gogakos, Apostolos; White, Jacqueline K.; Evans, Holly; Jacques, Richard M.; van der Spek, Anne H.; Ramirez-Solis, Ramiro; Ryder, Edward; Sunter, David; Boyde, Alan; Campbell, Michael J.

    2012-01-01

    Osteoporosis is a common polygenic disease and global healthcare priority but its genetic basis remains largely unknown. We report a high-throughput multi-parameter phenotype screen to identify functionally significant skeletal phenotypes in mice generated by the Wellcome Trust Sanger Institute Mouse Genetics Project and discover novel genes that may be involved in the pathogenesis of osteoporosis. The integrated use of primary phenotype data with quantitative x-ray microradiography, micro-computed tomography, statistical approaches and biomechanical testing in 100 unselected knockout mouse strains identified nine new genetic determinants of bone mass and strength. These nine new genes include five whose deletion results in low bone mass and four whose deletion results in high bone mass. None of the nine genes have been implicated previously in skeletal disorders and detailed analysis of the biomechanical consequences of their deletion revealed a novel functional classification of bone structure and strength. The organ-specific and disease-focused strategy described in this study can be applied to any biological system or tractable polygenic disease, thus providing a general basis to define gene function in a system-specific manner. Application of the approach to diseases affecting other physiological systems will help to realize the full potential of the International Mouse Phenotyping Consortium. PMID:22876197

  18. The ANKH gene and familial calcium pyrophosphate dihydrate deposition disease.

    PubMed

    Netter, Patrick; Bardin, Thomas; Bianchi, Arnaud; Richette, Pascal; Loeuille, Damien

    2004-09-01

    Familial calcium pyrophosphate dihydrate deposition (CPPD) disease is a chronic condition in which CPPD microcrystals deposit in the joint fluid, cartilage, and periarticular tissues. Two forms of familial CPPD disease have been identified: CCAL1 and CCAL2. The CCAL1 locus is located on the long arm of chromosome 8 and is associated with CPPD and severe osteoarthritis. The CCAL2 locus has been mapped to the short arm of chromosome 5 and identified in families from the Alsace region of France and the United Kingdom. The ANKH protein is involved in pyrophosphate metabolism and, more specifically, in pyrophosphate transport from the intracellular to the extracellular compartment. Numerous ANKH gene mutations cause familial CCAL2; they enhance ANKH protein activity, thereby elevating extracellular pyrophosphate levels and promoting the formation of pyrophosphate crystals, which produce the manifestations of the disease. Recent studies show that growth factors and cytokines can modify the expression of the normal ANKH protein. These results suggest a role for ANKH in sporadic CPPD disease and in CPPD associated with degenerative disease.

  19. Using Registries to Identify Adverse Events in Rheumatic Diseases

    PubMed Central

    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.

    2013-01-01

    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

  20. Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases.

    PubMed

    Greene, Daniel; Richardson, Sylvia; Turro, Ernest

    2016-03-01

    Rare genetic disorders, which can now be studied systematically with affordable genome sequencing, are often caused by high-penetrance rare variants. Such disorders are often heterogeneous and characterized by abnormalities spanning multiple organ systems ascertained with variable clinical precision. Existing methods for identifying genes with variants responsible for rare diseases summarize phenotypes with unstructured binary or quantitative variables. The Human Phenotype Ontology (HPO) allows composite phenotypes to be represented systematically but association methods accounting for the ontological relationship between HPO terms do not exist. We present a Bayesian method to model the association between an HPO-coded patient phenotype and genotype. Our method estimates the probability of an association together with an HPO-coded phenotype characteristic of the disease. We thus formalize a clinical approach to phenotyping that is lacking in standard regression techniques for rare disease research. We demonstrate the power of our method by uncovering a number of true associations in a large collection of genome-sequenced and HPO-coded cases with rare diseases. PMID:26924528

  1. Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases

    PubMed Central

    Greene, Daniel; Richardson, Sylvia; Turro, Ernest

    2016-01-01

    Rare genetic disorders, which can now be studied systematically with affordable genome sequencing, are often caused by high-penetrance rare variants. Such disorders are often heterogeneous and characterized by abnormalities spanning multiple organ systems ascertained with variable clinical precision. Existing methods for identifying genes with variants responsible for rare diseases summarize phenotypes with unstructured binary or quantitative variables. The Human Phenotype Ontology (HPO) allows composite phenotypes to be represented systematically but association methods accounting for the ontological relationship between HPO terms do not exist. We present a Bayesian method to model the association between an HPO-coded patient phenotype and genotype. Our method estimates the probability of an association together with an HPO-coded phenotype characteristic of the disease. We thus formalize a clinical approach to phenotyping that is lacking in standard regression techniques for rare disease research. We demonstrate the power of our method by uncovering a number of true associations in a large collection of genome-sequenced and HPO-coded cases with rare diseases. PMID:26924528

  2. Inferring novel gene-disease associations using Medical Subject Heading Over-representation Profiles

    PubMed Central

    2012-01-01

    Background MEDLINE®/PubMed® currently indexes over 18 million biomedical articles, providing unprecedented opportunities and challenges for text analysis. Using Medical Subject Heading Over-representation Profiles (MeSHOPs), an entity of interest can be robustly summarized, quantitatively identifying associated biomedical terms and predicting novel indirect associations. Methods A procedure is introduced for quantitative comparison of MeSHOPs derived from a group of MEDLINE® articles for a biomedical topic (for example, articles for a specific gene or disease). Similarity scores are computed to compare MeSHOPs of genes and diseases. Results Similarity scores successfully infer novel associations between diseases and genes. The number of papers addressing a gene or disease has a strong influence on predicted associations, revealing an important bias for gene-disease relationship prediction. Predictions derived from comparisons of MeSHOPs achieves a mean 8% AUC improvement in the identification of gene-disease relationships compared to gene-independent baseline properties. Conclusions MeSHOP comparisons are demonstrated to provide predictive capacity for novel relationships between genes and human diseases. We demonstrate the impact of literature bias on the performance of gene-disease prediction methods. MeSHOPs provide a rich source of annotation to facilitate relationship discovery in biomedical informatics. PMID:23021552

  3. Loci influencing blood pressure identified using a cardiovascular gene-centric array

    PubMed Central

    Ganesh, Santhi K.; Tragante, Vinicius; Guo, Wei; Guo, Yiran; Lanktree, Matthew B.; Smith, Erin N.; Johnson, Toby; Castillo, Berta Almoguera; Barnard, John; Baumert, Jens; Chang, Yen-Pei Christy; Elbers, Clara C.; Farrall, Martin; Fischer, Mary E.; Franceschini, Nora; Gaunt, Tom R.; Gho, Johannes M.I.H.; Gieger, Christian; Gong, Yan; Isaacs, Aaron; Kleber, Marcus E.; Leach, Irene Mateo; McDonough, Caitrin W.; Meijs, Matthijs F.L.; Mellander, Olle; Molony, Cliona M.; Nolte, Ilja M.; Padmanabhan, Sandosh; Price, Tom S.; Rajagopalan, Ramakrishnan; Shaffer, Jonathan; Shah, Sonia; Shen, Haiqing; Soranzo, Nicole; van der Most, Peter J.; Van Iperen, Erik P.A.; Van Setten, Jessic A.; Vonk, Judith M.; Zhang, Li; Beitelshees, Amber L.; Berenson, Gerald S.; Bhatt, Deepak L.; Boer, Jolanda M.A.; Boerwinkle, Eric; Burkley, Ben; Burt, Amber; Chakravarti, Aravinda; Chen, Wei; Cooper-DeHoff, Rhonda M.; Curtis, Sean P.; Dreisbach, Albert; Duggan, David; Ehret, Georg B.; Fabsitz, Richard R.; Fornage, Myriam; Fox, Ervin; Furlong, Clement E.; Gansevoort, Ron T.; Hofker, Marten H.; Hovingh, G. Kees; Kirkland, Susan A.; Kottke-Marchant, Kandice; Kutlar, Abdullah; LaCroix, Andrea Z.; Langaee, Taimour Y.; Li, Yun R.; Lin, Honghuang; Liu, Kiang; Maiwald, Steffi; Malik, Rainer; Murugesan, Gurunathan; Newton-Cheh, Christopher; O'Connell, Jeffery R.; Onland-Moret, N. Charlotte; Ouwehand, Willem H.; Palmas, Walter; Penninx, Brenda W.; Pepine, Carl J.; Pettinger, Mary; Polak, Joseph F.; Ramachandran, Vasan S.; Ranchalis, Jane; Redline, Susan; Ridker, Paul M.; Rose, Lynda M.; Scharnag, Hubert; Schork, Nicholas J.; Shimbo, Daichi; Shuldiner, Alan R.; Srinivasan, Sathanur R.; Stolk, Ronald P.; Taylor, Herman A.; Thorand, Barbara; Trip, Mieke D.; van Duijn, Cornelia M.; Verschuren, W. Monique; Wijmenga, Cisca; Winkelmann, Bernhard R.; Wyatt, Sharon; Young, J. Hunter; Boehm, Bernhard O.; Caulfield, Mark J.; Chasman, Daniel I.; Davidson, Karina W.; Doevendans, Pieter A.; FitzGerald, Garret A.; Gums, John G.; Hakonarson, Hakon; Hillege, Hans L.; Illig, Thomas; Jarvik, Gail P.; Johnson, Julie A.; Kastelein, John J.P.; Koenig, Wolfgang; März, Winfried; Mitchell, Braxton D.; Murray, Sarah S.; Oldehinkel, Albertine J.; Rader, Daniel J.; Reilly, Muredach P.; Reiner, Alex P.; Schadt, Eric E.; Silverstein, Roy L.; Snieder, Harold; Stanton, Alice V.; Uitterlinden, André G.; van der Harst, Pim; van der Schouw, Yvonne T.; Samani, Nilesh J.; Johnson, Andrew D.; Munroe, Patricia B.; de Bakker, Paul I.W.; Zhu, Xiaofeng; Levy, Daniel; Keating, Brendan J.; Asselbergs, Folkert W.

    2013-01-01

    Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10−6). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention. PMID:23303523

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

    PubMed Central

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

    2013-01-01

    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. PMID:23527177

  5. Identifying Early Changes in Myocardial Microstructure in Hypertensive Heart Disease

    PubMed Central

    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

    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. PMID:24831515

  6. Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

    PubMed

    Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

    2016-02-01

    Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis.

  7. Reference genes identified in SH-SY5Y cells using custom-made gene arrays with validation by quantitative polymerase chain reaction.

    PubMed

    Hoerndli, Frédéric J; Toigo, Marco; Schild, Andreas; Götz, Jürgen; Day, Philip J

    2004-12-01

    Transcriptomic methods are widely used as an initial approach to gain a mechanistic insight into physiological and pathological processes. Because differences in gene regulation to be assessed by RNA screening methods (e.g., SAGE, Affymetrix GeneChips) can be very subtle, these techniques require stable reference genes for accurate normalization. It is widely known that housekeeping genes, which are routinely used for normalization, can vary significantly depending on the tissue, and experimental test. In this study, we aimed at identifying stable reference genes for a fibrillar Abeta(42) peptide-treated, human tau-expressing SH-SY5Y neuroblastoma cell line derived to model aspects of Alzheimer's disease in tissue culture. We selected genes exhibiting potential normalization characteristics from public databases to create a custom-made microarray allowing the identification of reference genes for low, intermediate, and abundant mRNAs. A subset of these candidates was subjected to quantitative real-time polymerase chain reaction and was analyzed with geNorm software. By doing so, we were able to identify GAPD, M-RIP, and POLR2F as stable and usable reference genes irrespective of differentiation status and Abeta(42) treatment. PMID:15519568

  8. Whole-genome sequencing of individuals from a founder population identifies candidate genes for asthma.

    PubMed

    Campbell, Catarina D; Mohajeri, Kiana; Malig, Maika; Hormozdiari, Fereydoun; Nelson, Benjamin; Du, Gaixin; Patterson, Kristen M; Eng, Celeste; Torgerson, Dara G; Hu, Donglei; Herman, Catherine; Chong, Jessica X; Ko, Arthur; O'Roak, Brian J; Krumm, Niklas; Vives, Laura; Lee, Choli; Roth, Lindsey A; Rodriguez-Cintron, William; Rodriguez-Santana, Jose; Brigino-Buenaventura, Emerita; Davis, Adam; Meade, Kelley; LeNoir, Michael A; Thyne, Shannon; Jackson, Daniel J; Gern, James E; Lemanske, Robert F; Shendure, Jay; Abney, Mark; Burchard, Esteban G; Ober, Carole; Eichler, Evan E

    2014-01-01

    Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS. PMID:25116239

  9. Whole-genome sequencing of individuals from a founder population identifies candidate genes for asthma.

    PubMed

    Campbell, Catarina D; Mohajeri, Kiana; Malig, Maika; Hormozdiari, Fereydoun; Nelson, Benjamin; Du, Gaixin; Patterson, Kristen M; Eng, Celeste; Torgerson, Dara G; Hu, Donglei; Herman, Catherine; Chong, Jessica X; Ko, Arthur; O'Roak, Brian J; Krumm, Niklas; Vives, Laura; Lee, Choli; Roth, Lindsey A; Rodriguez-Cintron, William; Rodriguez-Santana, Jose; Brigino-Buenaventura, Emerita; Davis, Adam; Meade, Kelley; LeNoir, Michael A; Thyne, Shannon; Jackson, Daniel J; Gern, James E; Lemanske, Robert F; Shendure, Jay; Abney, Mark; Burchard, Esteban G; Ober, Carole; Eichler, Evan E

    2014-01-01

    Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.

  10. Whole-Genome Sequencing of Individuals from a Founder Population Identifies Candidate Genes for Asthma

    PubMed Central

    Campbell, Catarina D.; Mohajeri, Kiana; Malig, Maika; Hormozdiari, Fereydoun; Nelson, Benjamin; Du, Gaixin; Patterson, Kristen M.; Eng, Celeste; Torgerson, Dara G.; Hu, Donglei; Herman, Catherine; Chong, Jessica X.; Ko, Arthur; O'Roak, Brian J.; Krumm, Niklas; Vives, Laura; Lee, Choli; Roth, Lindsey A.; Rodriguez-Cintron, William; Rodriguez-Santana, Jose; Brigino-Buenaventura, Emerita; Davis, Adam; Meade, Kelley; LeNoir, Michael A.; Thyne, Shannon; Jackson, Daniel J.; Gern, James E.; Lemanske, Robert F.; Shendure, Jay; Abney, Mark; Burchard, Esteban G.; Ober, Carole; Eichler, Evan E.

    2014-01-01

    Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS. PMID:25116239

  11. Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

    PubMed

    Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

    2016-09-01

    Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

  12. Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

    PubMed

    Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

    2016-09-01

    Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics. PMID:27632082

  13. Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis

    PubMed Central

    Zhao, Junfei; Sheng, Jinsong; Rubin, Donald H.

    2016-01-01

    Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics. PMID:27632082

  14. Genetics, environment, and gene-environment interactions in the development of systemic rheumatic diseases.

    PubMed

    Sparks, Jeffrey A; Costenbader, Karen H

    2014-11-01

    Rheumatic diseases offer distinct challenges to researchers because of heterogeneity in disease phenotypes, low disease incidence, and geographic variation in genetic and environmental factors. Emerging research areas, including epigenetics, metabolomics, and the microbiome, may provide additional links between genetic and environmental risk factors in the pathogenesis of rheumatic disease. This article reviews the methods used to establish genetic and environmental risk factors and studies gene-environment interactions in rheumatic diseases, and provides specific examples of successes and challenges in identifying gene-environment interactions in rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Emerging research strategies and future challenges are discussed.

  15. Identifying Neisseria species by use of the 50S ribosomal protein L6 (rplF) gene.

    PubMed

    Bennett, Julia S; Watkins, Eleanor R; Jolley, Keith A; Harrison, Odile B; Maiden, Martin C J

    2014-05-01

    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.

  16. Gene expression profiling and candidate gene resequencing identifies pathways and mutations important for malignant transformation caused by leukemogenic fusion genes.

    PubMed

    Novak, Rachel L; Harper, David P; Caudell, David; Slape, Christopher; Beachy, Sarah H; Aplan, Peter D

    2012-12-01

    NUP98-HOXD13 (NHD13) and CALM-AF10 (CA10) are oncogenic fusion proteins produced by recurrent chromosomal translocations in patients with acute myeloid leukemia (AML). Transgenic mice that express these fusions develop AML with a long latency and incomplete penetrance, suggesting that collaborating genetic events are required for leukemic transformation. We employed genetic techniques to identify both preleukemic abnormalities in healthy transgenic mice as well as collaborating events leading to leukemic transformation. Candidate gene resequencing revealed that 6 of 27 (22%) CA10 AMLs spontaneously acquired a Ras pathway mutation and 8 of 27 (30%) acquired an Flt3 mutation. Two CA10 AMLs acquired an Flt3 internal-tandem duplication, demonstrating that these mutations can be acquired in murine as well as human AML. Gene expression profiles revealed a marked upregulation of Hox genes, particularly Hoxa5, Hoxa9, and Hoxa10 in both NHD13 and CA10 mice. Furthermore, mir196b, which is embedded within the Hoxa locus, was overexpressed in both CA10 and NHD13 samples. In contrast, the Hox cofactors Meis1 and Pbx3 were differentially expressed; Meis1 was increased in CA10 AMLs but not NHD13 AMLs, whereas Pbx3 was consistently increased in NHD13 but not CA10 AMLs. Silencing of Pbx3 in NHD13 cells led to decreased proliferation, increased apoptosis, and decreased colony formation in vitro, suggesting a previously unexpected role for Pbx3 in leukemic transformation.

  17. A candidate plasma protein classifier to identify Alzheimer's disease.

    PubMed

    Zhao, Xuemei; Lejnine, Serguei; Spond, Jeffrey; Zhang, Chunsheng; Ramaraj, T C; Holder, Daniel J; Dai, Hongyue; Weiner, Russell; Laterza, Omar F

    2015-01-01

    Biomarkers currently used in the aid for the diagnosis of Alzheimer's disease (AD) are cerebrospinal fluid (CSF) protein markers and brain neuroimaging markers. These biomarkers, however, either involve semi-invasive procedures or are costly to measure. Thus, AD biomarkers from more easily accessible body fluids, such as plasma, are very enticing. Using an aptamer-based proteomic technology, we profiled 1,129 plasma proteins of AD patients and non-demented control individuals. A 5-protein classifier for AD identification was constructed in the discovery study with excellent 10-fold cross-validation performance (90.1% sensitivity, 84.2% specificity, 87.9% accuracy, and AUC as 0.94). In an independent validation study, the classifier was applied and correctly predicted AD with 100.0% sensitivity, 80.0% specificity, and 90.0% accuracy, matching or outperforming the CSF Aβ42 and tau biomarkers whose performance were assessed in individual-matched CSF samples obtained at the same visit as plasma sample collection. Moreover, the classifier also correctly predicted mild cognitive impairment, an early pre-dementia state of the disease, with 96.7% sensitivity, 80.0% specificity, and 92.5% accuracy. These studies demonstrate that plasma proteins could be used effectively and accurately to contribute to the clinical diagnosis of AD. Although additional and more diverse cohorts are needed for further validation of the robustness, including the support of postmortem diagnosis, the 5-protein classifier appears to be a promising blood test to contribute diagnosis of AD. PMID:25114072

  18. A candidate plasma protein classifier to identify Alzheimer's disease.

    PubMed

    Zhao, Xuemei; Lejnine, Serguei; Spond, Jeffrey; Zhang, Chunsheng; Ramaraj, T C; Holder, Daniel J; Dai, Hongyue; Weiner, Russell; Laterza, Omar F

    2015-01-01

    Biomarkers currently used in the aid for the diagnosis of Alzheimer's disease (AD) are cerebrospinal fluid (CSF) protein markers and brain neuroimaging markers. These biomarkers, however, either involve semi-invasive procedures or are costly to measure. Thus, AD biomarkers from more easily accessible body fluids, such as plasma, are very enticing. Using an aptamer-based proteomic technology, we profiled 1,129 plasma proteins of AD patients and non-demented control individuals. A 5-protein classifier for AD identification was constructed in the discovery study with excellent 10-fold cross-validation performance (90.1% sensitivity, 84.2% specificity, 87.9% accuracy, and AUC as 0.94). In an independent validation study, the classifier was applied and correctly predicted AD with 100.0% sensitivity, 80.0% specificity, and 90.0% accuracy, matching or outperforming the CSF Aβ42 and tau biomarkers whose performance were assessed in individual-matched CSF samples obtained at the same visit as plasma sample collection. Moreover, the classifier also correctly predicted mild cognitive impairment, an early pre-dementia state of the disease, with 96.7% sensitivity, 80.0% specificity, and 92.5% accuracy. These studies demonstrate that plasma proteins could be used effectively and accurately to contribute to the clinical diagnosis of AD. Although additional and more diverse cohorts are needed for further validation of the robustness, including the support of postmortem diagnosis, the 5-protein classifier appears to be a promising blood test to contribute diagnosis of AD.

  19. With current gene markers, presymptomatic diagnosis of heritable disease is still a family affair

    SciTech Connect

    Not Available

    1987-09-04

    In the last four years, genes or genetic markers have been identified for a host of disorders including Huntington's disease, cystic fibrosis, Duchenne muscular dystrophy, polycystic kidney disease, bipolar depressive disorder, retinoblastoma, Alzheimer's disease, and schizophrenia. Such discoveries have made it possible to diagnose in utero some 30 genetic diseases during the first trimester of pregnancy. Yet, while these newly discovered gene markers may be revolutionizing prenatal and presymptomatic diagnosis, they are in many respects halfway technology. Such was the opinion of several speakers at a conference sponsored by the American Medical Association in Washington, DC. At the conference, entitled DNA Probes in the Practice of Medicine, geneticists emphasized that gene markers - stretches of DNA that are usually inherited in tandem with a disease gene - are usually not sufficient for presymptomatic diagnosis of genetic disease in an individual.

  20. Whole-exome sequencing identifies MST1R as a genetic susceptibility gene in nasopharyngeal carcinoma

    PubMed Central

    Dai, Wei; Zheng, Hong; Cheung, Arthur Kwok Leung; Tang, Clara Sze-man; Ko, Josephine Mun Yee; Wong, Bonnie Wing Yan; Leong, Merrin Man Long; Sham, Pak Chung; Cheung, Florence; Kwong, Dora Lai-Wan; Ngan, Roger Kai Cheong; Ng, Wai Tong; Yau, Chun Chung; Pan, Jianji; Peng, Xun; Tung, Stewart; Zhang, Zengfeng; Ji, Mingfang; Chiang, Alan Kwok-Shing; Lee, Anne Wing-Mui; Lee, Victor Ho-fun; Lam, Ka-On; Au, Kwok Hung; Cheng, Hoi Ching; Yiu, Harry Ho-Yin; Lung, Maria Li

    2016-01-01

    Multiple factors, including host genetics, environmental factors, and Epstein–Barr virus (EBV) infection, contribute to nasopharyngeal carcinoma (NPC) development. To identify genetic susceptibility genes for NPC, a whole-exome sequencing (WES) study was performed in 161 NPC cases and 895 controls of Southern Chinese descent. The gene-based burden test discovered an association between macrophage-stimulating 1 receptor (MST1R) and NPC. We identified 13 independent cases carrying the MST1R pathogenic heterozygous germ-line variants, and 53.8% of these cases were diagnosed with NPC aged at or even younger than 20 y, indicating that MST1R germ-line variants are relevant to disease early-age onset (EAO) (age of ≤20 y). In total, five MST1R missense variants were found in EAO cases but were rare in controls (EAO vs. control, 17.9% vs. 1.2%, P = 7.94 × 10−12). The validation study, including 2,160 cases and 2,433 controls, showed that the MST1R variant c.G917A:p.R306H is highly associated with NPC (odds ratio of 9.0). MST1R is predominantly expressed in the tissue-resident macrophages and is critical for innate immunity that protects organs from tissue damage and inflammation. Importantly, MST1R expression is detected in the ciliated epithelial cells in normal nasopharyngeal mucosa and plays a role in the cilia motility important for host defense. Although no somatic mutation of MST1R was identified in the sporadic NPC tumors, copy number alterations and promoter hypermethylation at MST1R were often observed. Our findings provide new insights into the pathogenesis of NPC by highlighting the involvement of the MST1R-mediated signaling pathways. PMID:26951679

  1. Phenotypic Variability and Newly Identified Mutations of the IVD Gene in Japanese Patients with Isovaleric Acidemia.

    PubMed

    Sakamoto, Osamu; Arai-Ichinoi, Natsuko; Mitsubuchi, Hiroshi; Chinen, Yasutsugu; Haruna, Hidenori; Maruyama, Hidehiko; Sugawara, Hidenori; Kure, Shigeo

    2015-01-01

    Isovaleric acidemia (IVA) is an autosomal recessive inborn error affecting leucine metabolism. It is caused by a deficiency in isovaleryl-CoA dehydrogenase (IVD), a mitochondrial matrix enzyme that catalyzes the oxidation of isovaleryl-CoA to 3-methylcrotonyl-CoA. IVD is a FAD-containing enzyme, consisting of four identical subunits. Clinical features of IVA include poor feeding, vomiting, lethargy, developmental delay, metabolic acidosis, and a characteristic "sweaty foot" odor. IVA is one of the target disorders for newborn screening by tandem mass spectrometry (MS/MS). The human IVD gene is located on chromosome 15q. To date, over 50 disease-causing mutations have been reported worldwide. In this study, we searched for IVD mutations in five Japanese patients with IVA (neonatal type, two patients; chronic intermittent type, two patients; and mild biochemical type, one patient). The diagnosis of IVA was confirmed by urinary organic acid analysis using gas chromatography and mass spectrometry. All coding exons and the flanking introns in the IVD gene were amplified by PCR and were directly sequenced. We thus identified six hitherto unknown mutations (p.G94D, p.E116K, p.M167T, p.L243P, p.L246P, and c.696+1G>T) and four previously reported (p.R53P, p.R395C, p.Y403C, and p.E411K) pathogenic mutations. All patients were compound heterozygotes, and each mutation was identified in a single patient. Pathogenicity of newly identified mutations was validated using computational programs. Among them, the p.M167T is believed to influence FAD binding, as the position 167 is present in one of the FAD-binding sites. Our results have illustrated the heterogeneous mutation spectrum and clinical presentation of IVA in the Japanese patients.

  2. Expression of coordinately regulated defense response genes and analysis of their role in disease resistance in Medicago truncatula

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarray technology was used to identify genes associated with disease defense responses in the model legume Medicago truncatula. Transcript profiles from leaves inoculated with Colletotrichum trifolii and Erysiphe pisi and roots infected with Phytophthora medicaginis were compared to identify gen...

  3. An Integrative Transcriptomic Analysis for Identifying Novel Target Genes Corresponding to Severity Spectrum in Spinal Muscular Atrophy

    PubMed Central

    Yang, Chung-Wei; Chen, Chien-Lin; Chou, Wei-Chun; Lin, Ho-Chen; Jong, Yuh-Jyh; Tsai, Li-Kai; Chuang, Chun-Yu

    2016-01-01

    Spinal muscular atrophy (SMA) is an inherited neuromuscular disease resulting from a recessive mutation in the SMN1 gene. This disease affects multiple organ systems with varying degrees of severity. Exploration of the molecular pathological changes occurring in different cell types in SMA is crucial for developing new therapies. This study collected 39 human microarray datasets from ArrayExpress and GEO databases to build an integrative transcriptomic analysis for recognizing novel SMA targets. The transcriptomic analysis was conducted through combining weighted correlation network analysis (WGCNA) for gene module detection, gene set enrichment analysis (GSEA) for functional categorization and filtration, and Cytoscape (visual interaction gene network analysis) for target gene identification. Seven novel target genes (Bmp4, Serpine1, Gata6, Ptgs2, Bcl2, IL6 and Cntn1) of SMA were revealed, and are all known in the regulation of TNFα for controlling neural, cardiac and bone development. Sequentially, the differentially expressed patterns of these 7 target genes in mouse tissues (e.g., spinal cord, heart, muscles and bone) were validated in SMA mice of different severities (pre-symptomatic, mildly symptomatic, and severely symptomatic). In severely symptomatic SMA mice, TNFα was up-regulated with attenuation of Bmp4 and increase of Serpine1 and Gata6 (a pathway in neural and cardiac development), but not in pre-symptomatic and mildly symptomatic SMA mice. The severely symptomatic SMA mice also had the elevated levels of Ptgs2 and Bcl2 (a pathway in skeletal development) as well as IL6 and Cntn1 (a pathway in nervous system development). Thus, the 7 genes identified in this study might serve as potential target genes for future investigations of disease pathogenesis and SMA therapy. PMID:27331400

  4. Differences in Gene-Gene Interactions in Graves’ Disease Patients Stratified by Age of Onset

    PubMed Central

    Jurecka-Lubieniecka, Beata; Bednarczuk, Tomasz; Ploski, Rafal; Krajewska, Jolanta; Kula, Dorota; Kowalska, Malgorzata; Tukiendorf, Andrzej; Kolosza, Zofia; Jarzab, Barbara

    2016-01-01

    Background Graves’ disease (GD) is a complex disease in which genetic predisposition is modified by environmental factors. Each gene exerts limited effects on the development of autoimmune disease (OR = 1.2–1.5). An epidemiological study revealed that nearly 70% of the risk of developing inherited autoimmunological thyroid diseases (AITD) is the result of gene interactions. In the present study, we analyzed the effects of the interactions of multiple loci on the genetic predisposition to GD. The aim of our analyses was to identify pairs of genes that exhibit a multiplicative interaction effect. Material and Methods A total of 709 patients with GD were included in the study. The patients were stratified into more homogeneous groups depending on the age at time of GD onset: younger patients less than 30 years of age and older patients greater than 30 years of age. Association analyses were performed for genes that influence the development of GD: HLADRB1, PTPN22, CTLA4 and TSHR. The interactions among polymorphisms were analyzed using the multiple logistic regression and multifactor dimensionality reduction (MDR) methods. Results GD patients stratified by the age of onset differed in the allele frequencies of the HLADRB1*03 and 1858T polymorphisms of the PTPN22 gene (OR = 1.7, p = 0.003; OR = 1.49, p = 0.01, respectively). We evaluated the genetic interactions of four SNPs in a pairwise fashion with regard to disease risk. The coexistence of HLADRB1 with CTLA4 or HLADRB1 with PTPN22 exhibited interactions on more than additive levels (OR = 3.64, p = 0.002; OR = 4.20, p < 0.001, respectively). These results suggest that interactions between these pairs of genes contribute to the development of GD. MDR analysis confirmed these interactions. Conclusion In contrast to a single gene effect, we observed that interactions between the HLADRB1/PTPN22 and HLADRB1/CTLA4 genes more closely predicted the risk of GD onset in young patients. PMID:26943356

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

    PubMed

    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

    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.

  6. Ultra-deep targeted sequencing of advanced oral squamous cell carcinoma identifies a mutation-based prognostic gene signature

    PubMed Central

    Huang, Po-Jung; Huang, Yi; Hsu, An; Tang, Petrus; Chang, Yu-Sun; Chen, Hua-Chien; Yen, Tzu-Chen

    2015-01-01

    Background Patients with advanced oral squamous cell carcinoma (OSCC) have heterogeneous outcomes that limit the implementation of tailored treatment options. Genetic markers for improved prognostic stratification are eagerly awaited. Methods Herein, next-generation sequencing (NGS) was performed in 345 formalin-fixed paraffin-embedded (FFPE) samples obtained from advanced OSCC patients. Genetic mutations on the hotspot regions of 45 cancer-related genes were detected using an ultra-deep (>1000×) sequencing approach. Kaplan-Meier plots and Cox regression analyses were used to investigate the associations between the mutation status and disease-free survival (DFS). Results We identified 1269 non-synonymous mutations in 276 OSCC samples. TP53, PIK3CA, CDKN2A, HRAS and BRAF were the most frequently mutated genes. Mutations in 14 genes were found to predict DFS. A mutation-based signature affecting ten genes (HRAS, BRAF, FGFR3, SMAD4, KIT, PTEN, NOTCH1, AKT1, CTNNB1, and PTPN11) was devised to predict DFS. Two different resampling methods were used to validate the prognostic value of the identified gene signature. Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005). Conclusions Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients. PMID:25980437

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

    PubMed

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

    2014-08-01

    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.

  8. Rhesus monkey model of liver disease reflecting clinical disease progression and hepatic gene expression analysis.

    PubMed

    Wang, Hong; Tan, Tao; Wang, Junfeng; Niu, Yuyu; Yan, Yaping; Guo, Xiangyu; Kang, Yu; Duan, Yanchao; Chang, Shaohui; Liao, Jianpeng; Si, Chenyang; Ji, Weizhi; Si, Wei

    2015-10-07

    Alcoholic liver disease (ALD) is a significant public health issue with heavy medical and economic burdens. The aetiology of ALD is not yet completely understood. The development of drugs and therapies for ALD is hampered by a lack of suitable animal models that replicate both the histological and metabolic features of human ALD. Here, we characterize a rhesus monkey model of alcohol-induced liver steatosis and hepatic fibrosis that is compatible with the clinical progression of the biochemistry and pathology in humans with ALD. Microarray analysis of hepatic gene expression was conducted to identify potential molecular signatures of ALD progression. The up-regulation of expression of hepatic genes related to liver steatosis (CPT1A, FASN, LEPR, RXRA, IGFBP1, PPARGC1A and SLC2A4) was detected in our rhesus model, as was the down-regulation of such genes (CYP7A1, HMGCR, GCK and PNPLA3) and the up-regulation of expression of hepatic genes related to liver cancer (E2F1, OPCML, FZD7, IGFBP1 and LEF1). Our results demonstrate that this ALD model reflects the clinical disease progression and hepatic gene expression observed in humans. These findings will be useful for increasing the understanding of ALD pathogenesis and will benefit the development of new therapeutic procedures and pharmacological reagents for treating ALD.

  9. Rhesus monkey model of liver disease reflecting clinical disease progression and hepatic gene expression analysis

    PubMed Central

    Wang, Hong; Tan, Tao; Wang, Junfeng; Niu, Yuyu; Yan, Yaping; Guo, Xiangyu; Kang, Yu; Duan, Yanchao; Chang, Shaohui; Liao, Jianpeng; Si, Chenyang; Ji, Weizhi; Si, Wei

    2015-01-01

    Alcoholic liver disease (ALD) is a significant public health issue with heavy medical and economic burdens. The aetiology of ALD is not yet completely understood. The development of drugs and therapies for ALD is hampered by a lack of suitable animal models that replicate both the histological and metabolic features of human ALD. Here, we characterize a rhesus monkey model of alcohol-induced liver steatosis and hepatic fibrosis that is compatible with the clinical progression of the biochemistry and pathology in humans with ALD. Microarray analysis of hepatic gene expression was conducted to identify potential molecular signatures of ALD progression. The up-regulation of expression of hepatic genes related to liver steatosis (CPT1A, FASN, LEPR, RXRA, IGFBP1, PPARGC1A and SLC2A4) was detected in our rhesus model, as was the down-regulation of such genes (CYP7A1, HMGCR, GCK and PNPLA3) and the up-regulation of expression of hepatic genes related to liver cancer (E2F1, OPCML, FZD7, IGFBP1 and LEF1). Our results demonstrate that this ALD model reflects the clinical disease progression and hepatic gene expression observed in humans. These findings will be useful for increasing the understanding of ALD pathogenesis and will benefit the development of new therapeutic procedures and pharmacological reagents for treating ALD. PMID:26442469

  10.  Bile salt export pump deficiency disease: two novel, late onset, ABCB11 mutations identified by next generation sequencing.

    PubMed

    Vitale, Giovanni; Pirillo, Martina; Mantovani, Vilma; Marasco, Elena; Aquilano, Adelia; Gamal, Nesrine; Francalanci, Paola; Conti, Fabio; Andreone, Pietro

    2016-01-01

     Progressive familial intrahepatic cholestasis (PFIC) is a heterogeneous group of autosomal recessive cholestatic diseases of childhood and represents the main indication for liver transplantation at this age; PFIC2 involves ABCB11 gene, that encodes the ATPdependent canalicular bile salt export pump (BSEP). Benign intrahepatic cholestasis (BRIC) identifies a group of diseases involving the same genes and characterized by intermittent attacks of cholestasis with no progression to liver cirrhosis. Diagnosis with standard sequencing techniques is expensive and available only at a few tertiary centers. We report the application of next generation sequencing (NGS) in the diagnosis of the familial intrahepatic cholestasis with a parallel sequencing of three causative genes. We identified the molecular defects in ABCB11 gene in two different probands who developed a severe cholestatic disease of unknown origin. In the first patient a compound heterozygosity for the novel frameshift mutation p.Ser1100GlnfsX38 and the missense variant p.Glu135Lys was detected. In the second patient, triggered by contraceptive therapy, we identified homozygosity for a novel missense variant p.Ala523Gly. In conclusion, these mutations seem to have a late onset and a less aggressive clinical impact, acting as an intermediate form between BRIC and PFIC. PMID:27493120

  11. Identification of genes conferring genetic resistance to Marek’s disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic resistance to Marek’s disease (MD) is complex and controlled by many genes with the majority having small effect making them difficult to detect. Thus, to identify specific genes, we have been employing and integrating a variety of genomic and functional genomic approaches that capitalize on...

  12. AN MHC class I immune evasion gene of Marek's disease virus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek's disease virus (MDV) is a widespread a-herpesvirus of chickens that causes T cell tumors. Acute, but not latent, MDV infection has previously been shown to lead to downregulation of cell-surface MHC class I (Virology 282:198–205 (2001)), but the gene(s) involved have not been identified. Here...

  13. Cell-based Assays to Identify Inhibitors of Viral Disease

    PubMed Central

    Green, Neil; Ott, Robert D.; Isaacs, Richard J.; Fang, Hong

    2009-01-01

    Background Antagonizing the production of infectious virus inside cells requires drugs that can cross the cell membrane without harming host cells. Objective It is therefore advantageous to establish intracellular potency of anti-viral drug candidates early in the drug-discovery pipeline. Methods To this end, cell-based assays are being developed and employed in high-throughput drug screening, ranging from assays that monitor replication of intact viruses to those that monitor activity of specific viral proteins. While numerous cell-based assays have been developed and investigated, rapid counter screens are also needed to define the specific viral targets of identified inhibitors and to eliminate nonspecific screening hits. Results/Conclusions Here, we describe the types of cell-based assays being used in antiviral drug screens and evaluate the equally important counter screens that are being employed to reach the full potential of cell-based high-throughput screening. PMID:19750206

  14. A comparative transcriptome analysis identifying FGF23 regulated genes in the kidney of a mouse CKD model.

    PubMed

    Dai, Bing; David, Valentin; Martin, Aline; Huang, Jinsong; Li, Hua; Jiao, Yan; Gu, Weikuan; Quarles, L Darryl

    2012-01-01

    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)/α-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 α-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-β) and tumor necrosis factor-alpha (TNF-α) 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.

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

    PubMed Central

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

    2014-01-01

    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

  16. Challenges associated with identifying the environmental determinants of the inflammatory bowel diseases.

    PubMed

    Molodecky, Natalie A; Panaccione, Remo; Ghosh, Subrata; Barkema, Herman W; Kaplan, Gilaad G

    2011-08-01

    In the last several years there has been an explosion in the discovery of inflammatory bowel disease (IBD) susceptibility genes; however, similar advances in identifying and defining environmental risk factors associated with IBD have lagged behind. Moreover, many studies that have explored the same or similar environmental risk factors of IBD have demonstrated disparate results and come to conflicting conclusions. In order for the field to move forward, it is important to understand and resolve why these differences exist. This significant heterogeneity has blurred the identification of the fundamental environmental determinants of IBD. The purpose of this review article is to explore the factors that have likely contributed to the heterogeneity among observational studies of environmental risk factors in IBD. In doing so, it is hoped that methodological standardization may lead to consistent environmental associations.

  17. Differentiating disease subtypes by using pathway patterns constructed from gene expressions and protein networks.

    PubMed

    Hung, Fei-Hung; Chiu, Hung-Wen

    2015-01-01

    Gene expression profiles differ in different diseases. Even if diseases are at the same stage, such diseases exhibit different gene expressions, not to mention the different subtypes at a single lesion site. Distinguishing different disease subtypes at a single lesion site is difficult. In early cases, subtypes were initially distinguished by doctors. Subsequently, further differences were found through pathological experiments. For example, a brain tumor can be classified according to its origin, its cell-type origin, or the tumor site. Because of the advancements in bioinformatics and the techniques for accumulating gene expressions, researchers can use gene expression data to classify disease subtypes. Because the operation of a biopathway is closely related to the disease mechanism, the application of gene expression profiles for clustering disease subtypes is insufficient. In this study, we collected gene expression data of healthy and four myelodysplastic syndrome subtypes and applied a method that integrated protein-protein interaction and gene expression data to identify different patterns of disease subtypes. We hope it is efficient for the classification of disease subtypes in adventure.

  18. Gene expression analysis approach to establish possible links between Parkinson's disease, cancer and cardiovascular diseases.

    PubMed

    Karim, Sajjad; Mirza, Zeenat; Kamal, Mohammad A; Abuzenadah, Adel M; Al-Qahtani, Mohammed H

    2014-01-01

    Non-communicable chronic diseases have been apparently established as threat to human health, and are currently the world's main killer. Cardiovascular diseases (CVD), cancer, diabetes and neurodegenerative diseases are collectively amounting to more than 60% of non-communicable disease burden across world. Tremendous advancements in healthcare enabled us to fight several health problems primarily infectious diseases. However, this increased longevity where in many cases an individual suffers from several such chronic diseases simultaneously, making treatment complex. Finding whether diseases can coexist in an individual by chance or there exists a possible association between them is vital. Our goal is to establish possible existing link among CVD, cancer and Parkinson's disease (PD) for better understanding of the associated molecular network. In this study, we integrated multiple dataset retrieved from the National Centre for Biotechnology Information's Gene Expression Omnibus database, and took a systems-biology approach to compare and distinguish the molecular network associated with PD, cancer and CVD. We identified 230, 308 and 1619 differentially expressed genes for CVD, cancer and PD dataset respectively using cut off p value<0.5 and fold change>2. We integrated these data with known pathways using Ingenuity Pathway Analysis tool and found following common pathways associated with all three diseases to be most affected; epithelial adherens junction signaling, remodelling of epithelial adherens junctions, role of BRCA1 in DNA damage response, sphingomyelin metabolism, 3- phosphoinositide biosynthesis, acute myeloid leukemia signaling, type I diabetes mellitus signaling, agrin interactions at neuromuscular junction, role of IL-17A in arthritis, and antigen presentation pathways. In conclusion, CVD, cancer and PD appear tightly associated at molecular level.

  19. Evolutionary conservation and disease gene association of the human genes composing pseudogenes.

    PubMed

    Sen, Kamalika; Ghosh, Tapash Chandra

    2012-06-15

    Pseudogenes, the 'genomic fossils' present portrayal of evolutionary history of human genome. The human genes configuring pseudogenes are also now coming forth as important resources in the study of human protein evolution. In this communication, we explored evolutionary conservation of the genes forming pseudogenes over the genes lacking any pseudogene and delving deeper, we probed an evolutionary rate difference between the disease genes in the two groups. We illustrated this differential evolutionary pattern by gene expressivity, number of regulatory miRNA targeting per gene, abundance of protein complex forming genes and lesser percentage of protein intrinsic disorderness. Furthermore, pseudogenes are observed to harbor sequence variations, over their entirety, those become degenerative disease-causing mutations though the disease involvement of their progenitors is still unexplored. Here, we unveiled an immense association of disease genes in the genes casting pseudogenes in human. We interpreted the issue by disease associated miRNA targeting, genes containing polymorphisms in miRNA target sites, abundance of genes having disease causing non-synonymous mutations, disease gene specific network properties, presence of genes having repeat regions, affluence of dosage sensitive genes and the presence of intrinsically unstructured protein regions.

  20. Role of the MHC2TA gene in autoimmune diseases

    PubMed Central

    Martínez, Alfonso; Sánchez‐Lopez, Marta; Varadé, Jezabel; Mas, Ana; Martín, M Carmen; de las Heras, Virginia; Arroyo, Rafael; Mendoza, Juan Luis; Díaz‐Rubio, Manuel; Fernández‐Gutiérrez, Benjamín; de la Concha, Emilio G; Urcelay, Elena

    2007-01-01

    Objectives Expression of major histocompatibility complex (MHC) class II genes is almost exclusively regulated by the class II transactivator. A promoter polymorphism (−168A/G, rs3087456) in the MHC2TA gene was associated with increased susceptibility to rheumatoid arthritis, multiple sclerosis and myocardial infarction in a northern European population. However, no evidence of association of this MHC2TA variant with the two autoimmune diseases could be subsequently detected in independent cohorts. Aim To test the aforementioned single nucleotide polymorphism and another G→C change (nt1614 from coding sequence, rs4774) to analyse the haplotype pattern in this MHC2TA gene. Methods A case–control study was performed with 350 patients with rheumatoid arthritis, 396 patients with multiple sclerosis, 663 patients with inflammatory bowel disease (IBD) and 519 healthy controls from Madrid. Genotyping was ascertained by using TaqMan assays‐on‐demand on a 7900HT analyser, following the manufacturer's suggestions (Applied Biosystems, Foster City, California, USA). Haplotypes were inferred with the expectation–maximisation algorithm implemented by the Arlequin software. Results No independent association with these autoimmune diseases was found for either polymorphism in the Spanish cohorts tested. However, when haplotypes were compared between patients with rheumatoid arthritis and controls, a significant difference in their overall frequency distribution was observed, evidencing a protective haplotype (−168A/1614C, p = 0.006; odds ratio (OR) 0.7) and a risk haplotype (−168G/1614C, p = 0.019; OR 1.6). Patients with multiple sclerosis mirrored these results, but no effect on IBD was identified. Conclusions The MHC2TA gene influences predisposition to rheumatoid arthritis and multiple sclerosis, but not to IBD. The −168G allele is not an aetiological variant in itself, but a genetic marker of susceptibility/protection haplotypes. PMID:17012290

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

    PubMed

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

    2014-01-01

    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.

  2. A Drosophila Model Identifies a Critical Role for Zinc in Mineralization for Kidney Stone Disease

    PubMed Central

    Lang, Sven; Bose, Neelanjan; Kahn, Arnold; Flechner, Lawrence; Blaschko, Sarah D.; Zee, Tiffany; Muteliefu, Gulinuer; Bond, Nichole; Kolipinski, Marysia; Fakra, Sirine C.; Mandel, Neil; Miller, Joe; Ramanathan, Arvind; Killilea, David W.; Brückner, Katja; Kapahi, Pankaj; Stoller, Marshall L.

    2015-01-01

    Ectopic calcification is a driving force for a variety of diseases, including kidney stones and atherosclerosis, but initiating factors remain largely unknown. Given its importance in seemingly divergent disease processes, identifying fundamental principal actors for ectopic calcification may have broad translational significance. Here we establish a Drosophila melanogaster model for ectopic calcification by inhibiting xanthine dehydrogenase whose deficiency leads to kidney stones in humans and dogs. Micro X-ray absorption near edge spectroscopy (μXANES) synchrotron analyses revealed high enrichment of zinc in the Drosophila equivalent of kidney stones, which was also observed in human kidney stones and Randall’s plaques (early calcifications seen in human kidneys thought to be the precursor for renal stones). To further test the role of zinc in driving mineralization, we inhibited zinc transporter genes in the ZnT family and observed suppression of Drosophila stone formation. Taken together, genetic, dietary, and pharmacologic interventions to lower zinc confirm a critical role for zinc in driving the process of heterogeneous nucleation that eventually leads to stone formation. Our findings open a novel perspective on the etiology of urinary stones and related diseases, which may lead to the identification of new preventive and therapeutic approaches. PMID:25970330

  3. A Drosophila model identifies a critical role for zinc in mineralization for kidney stone disease.

    PubMed

    Chi, Thomas; Kim, Man Su; Lang, Sven; Bose, Neelanjan; Kahn, Arnold; Flechner, Lawrence; Blaschko, Sarah D; Zee, Tiffany; Muteliefu, Gulinuer; Bond, Nichole; Kolipinski, Marysia; Fakra, Sirine C; Mandel, Neil; Miller, Joe; Ramanathan, Arvind; Killilea, David W; Brückner, Katja; Kapahi, Pankaj; Stoller, Marshall L

    2015-01-01

    Ectopic calcification is a driving force for a variety of diseases, including kidney stones and atherosclerosis, but initiating factors remain largely unknown. Given its importance in seemingly divergent disease processes, identifying fundamental principal actors for ectopic calcification may have broad translational significance. Here we establish a Drosophila melanogaster model for ectopic calcification by inhibiting xanthine dehydrogenase whose deficiency leads to kidney stones in humans and dogs. Micro X-ray absorption near edge spectroscopy (μXANES) synchrotron analyses revealed high enrichment of zinc in the Drosophila equivalent of kidney stones, which was also observed in human kidney stones and Randall's plaques (early calcifications seen in human kidneys thought to be the precursor for renal stones). To further test the role of zinc in driving mineralization, we inhibited zinc transporter genes in the ZnT family and observed suppression of Drosophila stone formation. Taken together, genetic, dietary, and pharmacologic interventions to lower zinc confirm a critical role for zinc in driving the process of heterogeneous nucleation that eventually leads to stone formation. Our findings open a novel perspective on the etiology of urinary stones and related diseases, which may lead to the identification of new preventive and therapeutic approaches.

  4. Candidate gene associated with a mutation causing recessive polycystic kidney disease in mice

    SciTech Connect

    Moyer, J.H.; Lee-Tischler, M.J.; Kwon, H.Y.; Schrick, J.J. ); Avner, E.D.; Sweeney, W.E. ); Godfrey, V.L.; Cacheiro, N.L.A.; Woychik, R.P. ); Wilkinson, J.E. )

    1994-05-27

    A line of transgenic mice was generated that contains an insertional mutation causing a phenotype similar to human autosomal recessive polycystic kidney disease. Homozygotes displayed a complex phenotype that included bilateral polycystic kidneys and an unusual liver lesion. The mutant locus was cloned and characterized through use of the transgene as a molecular marker. Additionally, a candidate polycystic kidney disease (PKD) gene was identified whose structure and expression are directly associated with the mutant locus. A complementary DNA derived from this gene predicted a peptide containing a motif that was originally identified in several genes involved in cell cycle control.

  5. A GABBR2 gene variant modifies pathophysiology in Huntington's disease.

    PubMed

    Philpott, April L; Fitzgerald, Paul B; Bailey, Neil W; Churchyard, Andrew; Georgiou-Karistianis, Nellie; Cummins, Tarrant D R

    2016-05-01

    Striatal degeneration in Huntington's disease (HD) causes changes in cortico-subcortical pathways. Transcranial magnetic stimulation (TMS) is a valuable tool for assessing pathophysiology within these pathways, yet has had limited application in HD. As cortico-subcortical pathways are largely mediated by GABA and dopamine receptor genes, understanding how these genes modulate neurophysiology in HD may provide new insights into how underlying pathology maps onto clinical phenotype. Twenty-nine participants with HD underwent motor cortex stimulation, while corticospinal excitability, cortical inhibition and intracortical facilitation were indexed via peripheral electromyography. Single-nucleotide polymorphism mapping was performed across six genes that are known to modulate cortico-subcortical pathways (GABRA2, GABBR1, GABBR2, DRD1, DRD2, DRD4). Genetic associations with six TMS measures and age at onset were investigated. Our hierarchical multiple regression analysis, controlling for CAG and age, revealed that a GABBR2 variant, predicted to be disease-causative, was significantly associated with corticospinal excitability at corrected levels. A subsequent uncorrected exploratory analysis revealed associations between GABBR2, GABRA2 and DRD2 variants with TMS measures of corticospinal excitability and cortical inhibition in HD, as well as with age at onset. Our findings support the notion that uncovering genetic associations with pathophysiological measures and age at onset is an important way forward in terms of generating meaningful biomarkers with diagnostic and prognostic sensitivity, and identifying novel human-validated targets for future clinical trials.

  6. Large Scale Association Analysis Identifies Three Susceptibility Loci for Coronary Artery Disease

    PubMed Central

    Youhanna, Sonia; Badro, Danielle A.; Kamatani, Yoichiro; Hager, Jörg; Yeretzian, Joumana S.; El-Khazen, Georges; Haber, Marc; Salloum, Angelique K.; Douaihy, Bouchra; Othman, Raed; Shasha, Nabil; Kabbani, Samer; Bayeh, Hamid El; Chammas, Elie; Farrall, Martin; Gauguier, Dominique; Platt, Daniel E.; Zalloua, Pierre A.

    2011-01-01

    Genome wide association studies (GWAS) and their replications that have associated DNA variants with myocardial infarction (MI) and/or coronary artery disease (CAD) are predominantly based on populations of European or Eastern Asian descent. Replication of the most significantly associated polymorphisms in multiple populations with distinctive genetic backgrounds and lifestyles is crucial to the understanding of the pathophysiology of a multifactorial disease like CAD. We have used our Lebanese cohort to perform a replication study of nine previously identified CAD/MI susceptibility loci (LTA, CDKN2A-CDKN2B, CELSR2-PSRC1-SORT1, CXCL12, MTHFD1L, WDR12, PCSK9, SH2B3, and SLC22A3), and 88 genes in related phenotypes. The study was conducted on 2,002 patients with detailed demographic, clinical characteristics, and cardiac catheterization results. One marker, rs6922269, in MTHFD1L was significantly protective against MI (OR = 0.68, p = 0.0035), while the variant rs4977574 in CDKN2A-CDKN2B was significantly associated with MI (OR = 1.33, p = 0.0086). Associations were detected after adjustment for family history of CAD, gender, hypertension, hyperlipidemia, diabetes, and smoking. The parallel study of 88 previously published genes in related phenotypes encompassed 20,225 markers, three quarters of which with imputed genotypes The study was based on our genome-wide genotype data set, with imputation across the whole genome to HapMap II release 22 using HapMap CEU population as a reference. Analysis was conducted on both the genotyped and imputed variants in the 88 regions covering selected genes. This approach replicated HNRNPA3P1-CXCL12 association with CAD and identified new significant associations of CDKAL1, ST6GAL1, and PTPRD with CAD. Our study provides evidence for the importance of the multifactorial aspect of CAD/MI and describes genes predisposing to their etiology. PMID:22216278

  7. Rare disease relations through common genes and protein interactions.

    PubMed

    Fernandez-Novo, Sara; Pazos, Florencio; Chagoyen, Monica

    2016-06-01

    ODCs (Orphan Disease Connections), available at http://csbg.cnb.csic.es/odcs, is a novel resource to explore potential molecular relations between rare diseases. These molecular relations have been established through the integration of disease susceptibility genes and human protein-protein interactions. The database currently contains 54,941 relations between 3032 diseases.

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

    PubMed

    Schnable, James C; Freeling, Michael

    2011-01-01

    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.

  9. Non-MHC genes linked to autoimmune disease.

    PubMed

    Deitiker, Philip; Atassi, M Zouhair

    2012-01-01

    The genetic traits that result in autoimmune diseases represent complicating factors in explicating the molecular and cellular elements of autoimmune responses and how these responses can be overcome or manipulated. This article focuses on the major non-major histocompatibility complex genes that have been found to be linked to autoimmune diseases. A given gene may associate with a number of autoimmune diseases and, conversely, a given disease may link to a number of common autoimmune disease (AD) genes. Collaboration and interaction among genes and the number of diseases that develop and the extensive risk factors shared among ADs further complicate the outcome. This article describes the various relationships between gene regions associated with multiple ADs and the complexity of those relationships.

  10. Affected kindred analysis of human X chromosome exomes to identify novel X-linked intellectual disability genes.

    PubMed

    Niranjan, Tejasvi S; Skinner, Cindy; May, Melanie; Turner, Tychele; Rose, Rebecca; Stevenson, Roger; Schwartz, Charles E; Wang, Tao

    2015-01-01

    X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders.

  11. Affected Kindred Analysis of Human X Chromosome Exomes to Identify Novel X-Linked Intellectual Disability Genes

    PubMed Central

    Niranjan, Tejasvi S.; Skinner, Cindy; May, Melanie; Turner, Tychele; Rose, Rebecca; Stevenson, Roger; Schwartz, Charles E.; Wang, Tao

    2015-01-01

    X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders. PMID:25679214

  12. Gene therapy for cardiovascular disease mediated by ultrasound and microbubbles

    PubMed Central

    2013-01-01

    Gene therapy provides an efficient approach for treatment of cardiovascular disease. To realize the therapeutic effect, both efficient delivery to the target cells and sustained expression of transgenes are required. Ultrasound targeted microbubble destruction (UTMD) technique has become a potential strategy for target-specific gene and drug delivery. When gene-loaded microbubble is injected, the ultrasound-mediated microbubble destruction may spew the transported gene to the targeted cells or organ. Meanwhile, high amplitude oscillations of microbubbles increase the permeability of capillary and cell membrane, facilitating uptake of the released gene into tissue and cell. Therefore, efficiency of gene therapy can be significantly improved. To date, UTMD has been successfully investigated in many diseases, and it has achieved outstanding progress in the last two decades. Herein, we discuss the current status of gene therapy of cardiovascular diseases, and reviewed the progress of the delivery of genes to cardiovascular system by UTMD. PMID:23594865

  13. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    PubMed Central

    Lascorz, Jesús; Hemminki, Kari; Försti, Asta

    2011-01-01

    Background: A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9%) had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO) categories or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation. PMID:21483658

  14. Thiamine responsive megaloblastic anemia syndrome: a novel homozygous SLC19A2 gene mutation identified.

    PubMed

    Mikstiene, Violeta; Songailiene, Jurgita; Byckova, Jekaterina; Rutkauskiene, Giedre; Jasinskiene, Edita; Verkauskiene, Rasa; Lesinskas, Eugenijus; Utkus, Algirdas

    2015-07-01

    Thiamine responsive megaloblastic anemia syndrome (TRMAS) is a rare autosomal recessive disorder especially in countries where consanguinity is uncommon. Three main features are characteristic of the disease - megaloblastic anemia, early onset deafness, and non-type I diabetes. TRMAS is a Mendelian disorder; a gene SLC19A2 coding high affinity thiamine transporter mediating vitamin B1 uptake through cell membrane has been identified. We present the first patient with TRMAS in Lithuania - a 3-year-old boy born to a non-consanguineous family with a novel homozygous SLC19A2 gene mutation. The patient had insulin dependent diabetes (onset 11 months), respiratory illness (onset 11 months), bilateral profound hearing loss (onset at 7 months, verified at 20 months), refractory anemia (onset 2 years), and decreased vision acuity and photophobia (onset 2.5 years). The psychomotor abilities developed according to age. Phenotypic evaluation did not reveal any dysmorphic features. The clinical diagnosis of TRMAS was suspected and daily supplementation with thiamine 100 mg was started. The condition of the patient markedly improved several days after the initiation of treatment. The results of SLC19A2 gene molecular testing confirmed the clinical diagnosis - novel homozygous c.[205G>T], p.[(Val69Phe)] mutation changing conserved amino acid residue or even interfering the mRNA splicing. Clinical heterogeneity, diverse dynamics, and wide spectrum of symptoms are aggravating factors in the diagnosis. The possibility of treatment demands early recognition of disorder to facilitate the improvement of the patient's condition. PMID:25707023

  15. Thiamine responsive megaloblastic anemia syndrome: a novel homozygous SLC19A2 gene mutation identified.

    PubMed

    Mikstiene, Violeta; Songailiene, Jurgita; Byckova, Jekaterina; Rutkauskiene, Giedre; Jasinskiene, Edita; Verkauskiene, Rasa; Lesinskas, Eugenijus; Utkus, Algirdas

    2015-07-01

    Thiamine responsive megaloblastic anemia syndrome (TRMAS) is a rare autosomal recessive disorder especially in countries where consanguinity is uncommon. Three main features are characteristic of the disease - megaloblastic anemia, early onset deafness, and non-type I diabetes. TRMAS is a Mendelian disorder; a gene SLC19A2 coding high affinity thiamine transporter mediating vitamin B1 uptake through cell membrane has been identified. We present the first patient with TRMAS in Lithuania - a 3-year-old boy born to a non-consanguineous family with a novel homozygous SLC19A2 gene mutation. The patient had insulin dependent diabetes (onset 11 months), respiratory illness (onset 11 months), bilateral profound hearing loss (onset at 7 months, verified at 20 months), refractory anemia (onset 2 years), and decreased vision acuity and photophobia (onset 2.5 years). The psychomotor abilities developed according to age. Phenotypic evaluation did not reveal any dysmorphic features. The clinical diagnosis of TRMAS was suspected and daily supplementation with thiamine 100 mg was started. The condition of the patient markedly improved several days after the initiation of treatment. The results of SLC19A2 gene molecular testing confirmed the clinical diagnosis - novel homozygous c.[205G>T], p.[(Val69Phe)] mutation changing conserved amino acid residue or even interfering the mRNA splicing. Clinical heterogeneity, diverse dynamics, and wide spectrum of symptoms are aggravating factors in the diagnosis. The possibility of treatment demands early recognition of disorder to facilitate the improvement of the patient's condition.

  16. Identifying the Genetic Variation of Gene Expression Using Gene Sets: Application of Novel Gene Set eQTL Approach to PharmGKB and KEGG

    PubMed Central

    Abo, Ryan; Jenkins, Gregory D.; Wang, Liewei; Fridley, Brooke L.

    2012-01-01

    Genetic variation underlying the regulation of mRNA gene expression in humans may provide key insights into the molecular mechanisms of human traits and complex diseases. Current statistical methods to map genetic variation associated with mRNA gene expression have typically applied standard linkage and/or association methods; however, when genome-wide SNP and mRNA expression data are available performing all pair wise comparisons is computationally burdensome and may not provide optimal power to detect associations. Consideration of different approaches to account for the high dimensionality and multiple testing issues may provide increased efficiency and statistical power. Here we present a novel approach to model and test the association between genetic variation and mRNA gene expression levels in the context of gene sets (GSs) and pathways, referred to as gene set – expression quantitative trait loci analysis (GS-eQTL). The method uses GSs to initially group SNPs and mRNA expression, followed by the application of principal components analysis (PCA) to collapse the variation and reduce the dimensionality within the GSs. We applied GS-eQTL to assess the association between SNP and mRNA expression level data collected from a cell-based model system using PharmGKB and KEGG defined GSs. We observed a large number of significant GS-eQTL associations, in which the most significant associations arose between genetic variation and mRNA expression from the same GS. However, a number of associations involving genetic variation and mRNA expression from different GSs were also identified. Our proposed GS-eQTL method effectively addresses the multiple testing limitations in eQTL studies and provides biological context for SNP-expression associations. PMID:22905253

  17. THE ETIOLOGY OF AUTOIMMUNE THYROID DISEASE: A STORY OF GENES AND ENVIRONMENT

    PubMed Central

    Tomer, Yaron; Huber, Amanda

    2013-01-01

    Autoimmune thyroid diseases (AITD), including Graves’ disease (GD) and Hashimoto’s thyroiditis (HT) are prevalent autoimmune diseases, affecting up to 5% of the general population. Autoimmune thyroid diseases arise due to complex interactions between environmental and genetic factors. Significant progress has been made in our understanding of the genetic and environmental triggers contributing to AITD. However, the interactions between genes and environment are yet to be defined. Among the major AITD susceptibility genes that have been identified and characterized is the HLADR gene locus, as well as non-MHC genes including the CTLA-4, CD40, PTPN22, thyroglobulin, and TSH receptor genes. The major environmental triggers of AITD include iodine, medications, infection, smoking, and possibly stress. Recent data on the genetic predisposition to AITD lead to novel putative mechanisms by which the genetic-environmental interactions may lead to the development of thyroid autoimmunity. PMID:19307103

  18. P21 gene knock down does not identify genetic effectors seen with gene knock out.

    PubMed

    Karakas, Bedri; Weeraratna, Ashani T; Abukhdeir, Abde M; Konishi, Hiroyuki; Gustin, John P; Vitolo, Michele I; Bachman, Kurtis E; Park, Ben Ho

    2007-07-01

    RNA interference (RNAi) has become a popular tool for analyzing gene function in cancer research. The feasibility of using RNAi in cellular and animal models as an alternative to conventional gene knock out approaches has been demonstrated. Although these studies show that RNAi can recapitulate phenotypes seen in knock out animals and their derived cell lines, a systematic study rigorously comparing downstream effector genes between RNAi and gene knock out has not been performed. Here we present data contrasting the phenotypic and genotypic changes that occur with either stable knock down via RNAi of the cyclin dependent kinase inhibitor p21 versus its somatic cell knock out counterpart in the human mammary epithelial cell line MCF-10A. Our results demonstrate that p21 knock down clones display a growth proliferative response upon exposure to Transforming Growth Factor-Beta Type 1 (TGFbeta) similar to p21 knock out clones. However, gene expression profiles were significantly different in p21 knock down cells versus p21 knock out clones. Importantly p21 knock down clones did not display increased gene expression of interleukin-1alpha (IL-1alpha), a critical effector of this growth response previously validated in p21 knock out cells. We conclude that gene knock out can yield additional vital information that may be missed with gene knock down strategies.

  19. A functional siRNA screen identifies genes modulating angiotensin II-mediated EGFR transactivation.

    PubMed

    George, Amee J; Purdue, Brooke W; Gould, Cathryn M; Thomas, Daniel W; Handoko, Yanny; Qian, Hongwei; Quaife-Ryan, Gregory A; Morgan, Kylie A; Simpson, Kaylene J; Thomas, Walter G; Hannan, Ross D

    2013-12-01

    The angiotensin type 1 receptor (AT1R) transactivates the epidermal growth factor receptor (EGFR) to mediate cellular growth, however, the molecular mechanisms involved have not yet been resolved. To address this, we performed a functional siRNA screen of the human kinome in human mammary epithelial cells that demonstrate a robust AT1R-EGFR transactivation. We identified a suite of genes encoding proteins that both positively and negatively regulate AT1R-EGFR transactivation. Many candidates are components of EGFR signalling networks, whereas others, including TRIO, BMX and CHKA, have not been previously linked to EGFR transactivation. Individual knockdown of TRIO, BMX or CHKA attenuated tyrosine phosphorylation of the EGFR by angiotensin II stimulation, but this did not occur following direct stimulation of the EGFR with EGF, indicating that these proteins function between the activated AT1R and the EGFR. Further investigation of TRIO and CHKA revealed that their activity is likely to be required for AT1R-EGFR transactivation. CHKA also mediated EGFR transactivation in response to another G protein-coupled receptor (GPCR) ligand, thrombin, indicating a pervasive role for CHKA in GPCR-EGFR crosstalk. Our study reveals the power of unbiased, functional genomic screens to identify new signalling mediators important for tissue remodelling in cardiovascular disease and cancer. PMID:24046455

  20. Gene Deletion Screen for Cardiomyopathy in Adult Drosophila Identifies a New Notch Ligand

    PubMed Central

    Kim, Il-Man; Wolf, Matthew J.; Rockman, Howard A.

    2010-01-01

    Rationale Drosophila has been recognized as a model to study human cardiac diseases. Objective Despite these findings, and the wealth of tools that are available to the fly community, forward genetic screens for adult heart phenotypes have been rarely performed due to the difficulty in accurately measuring cardiac function in adult Drosophila. Methods and Results Using optical coherence tomography to obtain real-time analysis of cardiac function in awake Drosophila, we performed a genomic deficiency screen in adult flies. Based on multiple complementary approaches, we identified CG31665 as a novel gene causing dilated cardiomyopathy. CG31665, which we name weary (wry), has structural similarities to members of the Notch family. Using cell aggregation assays and γ-secretase inhibitors we show that Wry is a novel Notch ligand that can mediate cellular adhesion with Notch expressing cells and transactivates Notch to promote signaling and nuclear transcription. Importantly, Wry lacks a DSL (Delta-Serrate-Lag) domain that is common feature to the other Drosophila Notch ligands. We further show that Notch signaling is critically important for the maintenance of normal heart function of the adult fly. Conclusions In conclusion, we identify a previously unknown Notch ligand in Drosophila that when deleted causes cardiomyopathy. Our study suggests that Notch signaling components may be a therapeutic target for dilated cardiomyopathy. PMID:20203305

  1. Genome-Wide RNAi Screens in C. elegans to Identify Genes Influencing Lifespan and Innate Immunity.

    PubMed

    Sinha, Amit; Rae, Robbie

    2016-01-01

    RNA interference is a rapid, inexpensive, and highly effective tool used to inhibit gene function. In C. elegans, whole genome screens have been used to identify genes involved with numerous traits including aging and innate immunity. RNAi in C. elegans can be carried out via feeding, soaking, or injection. Here we outline protocols used to maintain, grow, and carry out RNAi via feeding in C. elegans and determine whether the inhibited genes are essential for lifespan or innate immunity. PMID:27581293

  2. The compact Selaginella genome identifies changes in gene content associated with the evolution of vascular plants

    SciTech Connect

    Grigoriev, Igor V.; Banks, Jo Ann; Nishiyama, Tomoaki; Hasebe, Mitsuyasu; Bowman, John L.; Gribskov, Michael; dePamphilis, Claude; Albert, Victor A.; Aono, Naoki; Aoyama, Tsuyoshi; Ambrose, Barbara A.; Ashton, Neil W.; Axtell, Michael J.; Barker, Elizabeth; Barker, Michael S.; Bennetzen, Jeffrey L.; Bonawitz, Nicholas D.; Chapple, Clint; Cheng, Chaoyang; Correa, Luiz Gustavo Guedes; Dacre, Michael; DeBarry, Jeremy; Dreyer, Ingo; Elias, Marek; Engstrom, Eric M.; Estelle, Mark; Feng, Liang; Finet, Cedric; Floyd, Sandra K.; Frommer, Wolf B.; Fujita, Tomomichi; Gramzow, Lydia; Gutensohn, Michael; Harholt, Jesper; Hattori, Mitsuru; Heyl, Alexander; Hirai, Tadayoshi; Hiwatashi, Yuji; Ishikawa, Masaki; Iwata, Mineko; Karol, Kenneth G.; Koehler, Barbara; Kolukisaoglu, Uener; Kubo, Minoru; Kurata, Tetsuya; Lalonde, Sylvie; Li, Kejie; Li, Ying; Litt, Amy; Lyons, Eric; Manning, Gerard; Maruyama, Takeshi; Michael, Todd P.; Mikami, Koji; Miyazaki, Saori; Morinaga, Shin-ichi; Murata, Takashi; Mueller-Roeber, Bernd; Nelson, David R.; Obara, Mari; Oguri, Yasuko; Olmstead, Richard G.; Onodera, Naoko; Petersen, Bent Larsen; Pils, Birgit; Prigge, Michael; Rensing, Stefan A.; Riano-Pachon, Diego Mauricio; Roberts, Alison W.; Sato, Yoshikatsu; Scheller, Henrik Vibe; Schulz, Burkhard; Schulz, Christian; Shakirov, Eugene V.; Shibagaki, Nakako; Shinohara, Naoki; Shippen, Dorothy E.; Sorensen, Iben; Sotooka, Ryo; Sugimoto, Nagisa; Sugita, Mamoru; Sumikawa, Naomi; Tanurdzic, Milos; Theilsen, Gunter; Ulvskov, Peter; Wakazuki, Sachiko; Weng, Jing-Ke; Willats, William W.G.T.; Wipf, Daniel; Wolf, Paul G.; Yang, Lixing; Zimmer, Andreas D.; Zhu, Qihui; Mitros, Therese; Hellsten, Uffe; Loque, Dominique; Otillar, Robert; Salamov, Asaf; Schmutz, Jeremy; Shapiro, Harris; Lindquist, Erika; Lucas, Susan; Rokhsar, Daniel

    2011-04-28

    We report the genome sequence of the nonseed vascular plant, Selaginella moellendorffii, and by comparative genomics identify genes that likely played important roles in the early evolution of vascular plants and their subsequent evolution

  3. Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.

    PubMed

    Wang, Jiguang; Zhang, Shihua; Wang, Yong; Chen, Luonan; Zhang, Xiang-Sun

    2009-09-01

    One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system-based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases.

  4. A Comprehensive Evaluation of Disease Phenotype Networks for Gene Prioritization

    PubMed Central

    Li, Jianhua; Lin, Xiaoyan; Teng, Yueyang; Qi, Shouliang; Xiao, Dayu; Zhang, Jianying; Kang, Yan

    2016-01-01

    Identification of disease-causing genes is a fundamental challenge for human health studies. The phenotypic similarity among diseases may reflect the interactions at the molecular level, and phenotype comparison can be used to predict disease candidate genes. Online Mendelian Inheritance in Man (OMIM) is a database of human genetic diseases and related genes that has become an authoritative source of disease phenotypes. However, disease phenotypes have been described by free text; thus, standardization of phenotypic descriptions is needed before diseases can be compared. Several disease phenotype networks have been established in OMIM using different standardization methods. Two of these networks are important for phenotypic similarity analysis: the first and most commonly used network (mimMiner) is standardized by medical subject heading, and the other network (resnikHPO) is the first to be standardized by human phenotype ontology. This paper comprehensively evaluates for the first time the accuracy of these two networks in gene prioritization based on protein–protein interactions using large-scale, leave-one-out cross-validation experiments. The results show that both networks can effectively prioritize disease-causing genes, and the approach that relates two diseases using a logistic function improves prioritization performance. Tanimoto, one of four methods for normalizing resnikHPO, generates a symmetric network and it performs similarly to mimMiner. Furthermore, an integration of these two networks outperforms either network alone in gene prioritization, indicating that these two disease networks are complementary. PMID:27415759

  5. Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database

    PubMed Central

    Davis, Allan Peter; Wiegers, Thomas C.; King, Benjamin L.; Wiegers, Jolene; Grondin, Cynthia J.; Sciaky, Daniela; Johnson, Robin J.; Mattingly, Carolyn J.

    2016-01-01

    Strategies for discovering common molecular events among disparate diseases hold promise for improving understanding of disease etiology and expanding treatment options. One technique is to leverage curated datasets found in the public domain. The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) manually curates chemical-gene, chemical-disease, and gene-disease interactions from the scientific literature. The use of official gene symbols in CTD interactions enables this information to be combined with the Gene Ontology (GO) file from NCBI Gene. By integrating these GO-gene annotations with CTD’s gene-disease dataset, we produce 753,000 inferences between 15,700 GO terms and 4,200 diseases, providing opportunities to explore presumptive molecular underpinnings of diseases and identify biological similarities. Through a variety of applications, we demonstrate the utility of this novel resource. As a proof-of-concept, we first analyze known repositioned drugs (e.g., raloxifene and sildenafil) and see that their target diseases have a greater degree of similarity when comparing GO terms vs. genes. Next, a computational analysis predicts seemingly non-intuitive diseases (e.g., stomach ulcers and atherosclerosis) as being similar to bipolar disorder, and these are validated in the literature as reported co-diseases. Additionally, we leverage other CTD content to develop testable hypotheses about thalidomide-gene networks to treat seemingly disparate diseases. Finally, we illustrate how CTD tools can rank a series of drugs as potential candidates for repositioning against B-cell chronic lymphocytic leukemia and predict cisplatin and the small molecule inhibitor JQ1 as lead compounds. The CTD dataset is freely available for users to navigate pathologies within the context of extensive biological processes, molecular functions, and cellular components conferred by GO. This inference set should aid researchers, bioinformaticists, and pharmaceutical drug

  6. A genetic screen in zebrafish identifies the mutants vps18, nf2 and foie gras as models of liver disease.

    PubMed

    Sadler, Kirsten C; Amsterdam, Adam; Soroka, Carol; Boyer, James; Hopkins, Nancy

    2005-08-01

    Hepatomegaly is a sign of many liver disorders. To identify zebrafish mutants to serve as models for hepatic pathologies, we screened for hepatomegaly at day 5 of embryogenesis in 297 zebrafish lines bearing mutations in genes that are essential for embryonic development. Seven mutants were identified, and three have phenotypes resembling different liver diseases. Mutation of the class C vacuolar protein sorting gene vps18 results in hepatomegaly associated with large, vesicle-filled hepatocytes, which we attribute to the failure of endosomal-lysosomal trafficking. Additionally, these mutants develop defects in the bile canaliculi and have marked biliary paucity, suggesting that vps18 also functions to traffic vesicles to the hepatocyte apical membrane and may play a role in the development of the intrahepatic biliary tree. Similar findings have been reported for individuals with arthrogryposis-renal dysfunction-cholestasis (ARC) syndrome, which is due to mutation of another class C vps gene. A second mutant, resulting from disruption of the tumor suppressor gene nf2, develops extrahepatic choledochal cysts in the common bile duct, suggesting that this gene regulates division of biliary cells during development and that nf2 may play a role in the hyperplastic tendencies observed in biliary cells in individuals with choledochal cysts. The third mutant is in the novel gene foie gras, which develops large, lipid-filled hepatocytes, resembling those in individuals with fatty liver disease. These mutants illustrate the utility of zebrafish as a model for studying liver development and disease, and provide valuable tools for investigating the molecular pathogenesis of congenital biliary disorders and fatty liver disease.