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Sample records for identifying disease genes

  1. Identifying disease genes by integrating multiple data sources

    PubMed Central

    2014-01-01

    Background Now multiple types of data are available for identifying disease genes. Those data include gene-disease associations, disease phenotype similarities, protein-protein interactions, pathways, gene expression profiles, etc.. It is believed that integrating different kinds of biological data is an effective method to identify disease genes. Results In this paper, we propose a multiple data integration method based on the theory of Markov random field (MRF) and the method of Bayesian analysis for identifying human disease genes. The proposed method is not only flexible in easily incorporating different kinds of data, but also reliable in predicting candidate disease genes. Conclusions Numerical experiments are carried out by integrating known gene-disease associations, protein complexes, protein-protein interactions, pathways and gene expression profiles. Predictions are evaluated by the leave-one-out method. The proposed method achieves an AUC score of 0.743 when integrating all those biological data in our experiments. PMID:25350511

  2. Identifying Causal Genes and Dysregulated Pathways in Complex Diseases

    PubMed Central

    Kim, Yoo-Ah; Wuchty, Stefan; Przytycka, Teresa M.

    2011-01-01

    In complex diseases, various combinations of genomic perturbations often lead to the same phenotype. On a molecular level, combinations of genomic perturbations are assumed to dys-regulate the same cellular pathways. Such a pathway-centric perspective is fundamental to understanding the mechanisms of complex diseases and the identification of potential drug targets. In order to provide an integrated perspective on complex disease mechanisms, we developed a novel computational method to simultaneously identify causal genes and dys-regulated pathways. First, we identified a representative set of genes that are differentially expressed in cancer compared to non-tumor control cases. Assuming that disease-associated gene expression changes are caused by genomic alterations, we determined potential paths from such genomic causes to target genes through a network of molecular interactions. Applying our method to sets of genomic alterations and gene expression profiles of 158 Glioblastoma multiforme (GBM) patients we uncovered candidate causal genes and causal paths that are potentially responsible for the altered expression of disease genes. We discovered a set of putative causal genes that potentially play a role in the disease. Combining an expression Quantitative Trait Loci (eQTL) analysis with pathway information, our approach allowed us not only to identify potential causal genes but also to find intermediate nodes and pathways mediating the information flow between causal and target genes. Our results indicate that different genomic perturbations indeed dys-regulate the same functional pathways, supporting a pathway-centric perspective of cancer. While copy number alterations and gene expression data of glioblastoma patients provided opportunities to test our approach, our method can be applied to any disease system where genetic variations play a fundamental causal role. PMID:21390271

  3. 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 available as a stand-alone software package at http://wiki.chasmsoftware.org and is hosted by the CRAVAT web server at http://www.cravat.us PMID:23819870

  4. 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. PMID:25617670

  5. Genes to diseases (G2D) computational method to identify asthma candidate genes.

    PubMed

    Tremblay, Karine; Lemire, Mathieu; Potvin, Camille; Tremblay, Alexandre; Hunninghake, Gary M; Raby, Benjamin A; Hudson, Thomas J; Perez-Iratxeta, Carolina; Andrade-Navarro, Miguel A; Laprise, Catherine

    2008-01-01

    Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay-Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait. PMID:18682798

  6. Genes to Diseases (G2D) Computational Method to Identify Asthma Candidate Genes

    PubMed Central

    Tremblay, Karine; Lemire, Mathieu; Potvin, Camille; Tremblay, Alexandre; Hunninghake, Gary M.; Raby, Benjamin A.; Hudson, Thomas J.; Perez-Iratxeta, Carolina; Andrade-Navarro, Miguel A.; Laprise, Catherine

    2008-01-01

    Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay?Lac-St-Jean (SLSJ) asthmatic familial collection (n?=?609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n?=?1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n?=?91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p?=?0.000463; corrected p?=?0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait. PMID:18682798

  7. Bioinformatic Tools for Identifying Disease Gene and SNP Candidates

    PubMed Central

    Mooney, Sean D.; Krishnan, Vidhya G.; Evani, Uday S.

    2013-01-01

    As databases of genome data continue to grow, our understanding of the functional elements of the genome grows as well. Many genetic changes in the genome have now been discovered and characterized, including both disease-causing mutations and neutral polymorphisms. In addition to experimental approaches to characterize specific variants, over the past decade, there has been intense bioinformatic research to understand the molecular effects of these genetic changes. In addition to genomic experimental assays, the bioinformatic efforts have focused on two general areas. First, researchers have annotated genetic variation data with molecular features that are likely to affect function. Second, statistical methods have been developed to predict mutations that are likely to have a molecular effect. In this protocol manuscript, methods for understanding the molecular functions of single nucleotide polymorphisms (SNPs) and mutations are reviewed and described. The intent of this chapter is to provide an introduction to the online tools that are both easy to use and useful. PMID:20238089

  8. Using the BITOLA system to identify candidate genes for Parkinsons disease

    PubMed Central

    Kari?, Amela; Kari?, Alen

    2011-01-01

    Complexity of multifactorial diseases as Parkinsons 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 Alzheimers 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

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

    PubMed Central

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

    2009-01-01

    Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regionsthat likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/). PMID:19557189

  10. 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

    2014-08-23

    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

  11. IDENTIFYING DISEASE RESISTANCE GENES AND PATHWAYS THROUGH HOST-PATHOGEN PROTEIN INTERACTIONS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A major objective of both animal and plant genomics research is to identify disease resistance genes and pathways. Popular approaches to achieve this goal include candidate gene testing, genome-wide QTL screens, and DNA microarrays. We argue that the two-hybrid assay, which detects protein-protein...

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

    PubMed

    Muto, Taro

    2011-01-01

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

  13. 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

  14. 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

  15. 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

    2015-01-01

    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

  16. A network-based approach to identify disease-associated gene modules through integrating DNA methylation and gene expression.

    PubMed

    Zhang, Yuanyuan; Zhang, Junying; Liu, Zhaowen; Liu, Yajun; Tuo, Shouheng

    2015-09-25

    Formation and progression of complex diseases are generally the joint effect of genetic and epigenetic disorders, thus an integrative analysis of epigenetic and genetic data is essential for understanding mechanism of the diseases. In this study, we integrate Illuminate 450k DNA methylation and gene expression data to calculate the weights of gene network using Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA). The approach considers all methylation values of CpG sites in a gene, rather than averaging them which was used in other studies ignoring the variability of the methylation sites. Through comparing topological features of control network with those of case network, including global and local features, candidate disease-associated genes and gene modules are identified. We apply the approach to real data, breast invasive carcinoma (BRCA). It successfully identifies susceptibility breast cancer-related genes, such as TP53, BRCA1, EP300, CDK2, MCM7 and so forth, within which most are previously known to breast cancer. Also, GO and pathway enrichment analysis indicate that these genes enrich in cell apoptosis and regulation of cell death which are cancer-related biological processes. Importantly, through analyzing the functions and comparing expression and methylation values of these genes between cases and controls, we find some genes, such as VASN, SNRPD3, and gene modules, targeted by POLR2C, CHMP1B and TAF9, which might be novel breast cancer-related biomarkers. PMID:26282201

  17. 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

  18. Genes that Affect Brain Structure and Function Identified by Rare Variant Analyses of Mendelian Neurologic Disease.

    PubMed

    Karaca, Ender; Harel, Tamar; Pehlivan, Davut; Jhangiani, Shalini N; Gambin, Tomasz; Coban Akdemir, Zeynep; Gonzaga-Jauregui, Claudia; Erdin, Serkan; Bayram, Yavuz; Campbell, Ian M; Hunter, Jill V; Atik, Mehmed M; Van Esch, Hilde; Yuan, Bo; Wiszniewski, Wojciech; Isikay, Sedat; Yesil, Gozde; Yuregir, Ozge O; Tug Bozdogan, Sevcan; Aslan, Huseyin; Aydin, Hatip; Tos, Tulay; Aksoy, Ayse; De Vivo, Darryl C; Jain, Preti; Geckinli, B Bilge; Sezer, Ozlem; Gul, Davut; Durmaz, Burak; Cogulu, Ozgur; Ozkinay, Ferda; Topcu, Vehap; Candan, Sukru; Cebi, Alper Han; Ikbal, Mevlit; Yilmaz Gulec, Elif; Gezdirici, Alper; Koparir, Erkan; Ekici, Fatma; Coskun, Salih; Cicek, Salih; Karaer, Kadri; Koparir, Asuman; Duz, Mehmet Bugrahan; Kirat, Emre; Fenercioglu, Elif; Ulucan, Hakan; Seven, Mehmet; Guran, Tulay; Elcioglu, Nursel; Yildirim, Mahmut Selman; Aktas, Dilek; Alika?ifo?lu, Mehmet; Ture, Mehmet; Yakut, Tahsin; Overton, John D; Yuksel, Adnan; Ozen, Mustafa; Muzny, Donna M; Adams, David R; Boerwinkle, Eric; Chung, Wendy K; Gibbs, Richard A; Lupski, James R

    2015-11-01

    Development of the human nervous system involves complex interactions among fundamental cellular processes and requires a multitude of genes, many of which remain to be associated with human disease. We applied whole exome sequencing to 128 mostly consanguineous families with neurogenetic disorders that often included brain malformations. Rare variant analyses for both single nucleotide variant (SNV) and copy number variant (CNV) alleles allowed for identification of 45 novel variants in 43 known disease genes, 41 candidate genes, and CNVs in 10 families, with an overall potential molecular cause identified in >85% of families studied. Among the candidate genes identified, we found PRUNE, VARS, and DHX37 in multiple families and homozygous loss-of-function variants in AGBL2, SLC18A2, SMARCA1, UBQLN1, and CPLX1. Neuroimaging and insilico analysis of functional and expression proximity between candidate and known disease genes allowed for further understanding of genetic networks underlying specific types of brain malformations. VIDEO ABSTRACT. PMID:26539891

  19. Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

    PubMed Central

    Halappanavar, Sabina

    2015-01-01

    Summary Background: The presence of diverse types of nanomaterials (NMs) in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2), carbon black (CB) or carbon nanotubes (CNTs) to determine the disease significance of these data-driven gene sets. Results: Biclusters representing inflammation (chemokine activity), DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS) and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032). The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles. Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several previously defined, functionally relevant gene sets, the present study also identified two novel genes sets: a gene set associated with pulmonary fibrosis and a gene set associated with ROS, underlining the advantage of using a data-driven approach to identify novel, functionally related gene sets. The results can be used in future gene set enrichment analysis studies involving NMs or as features for clustering and classifying NMs of diverse properties. PMID:26885455

  20. DNA methylation map of mouse and human brain identifies target genes in Alzheimers disease

    PubMed Central

    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

    2013-01-01

    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 Alzheimers 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 Alzheimers disease. We were able to translate these findings to patients with Alzheimers disease, identifying DNA methylation-associated silencing of three targets genes: thromboxane A2 receptor (TBXA2R), sorbin and SH3 domain containing 3 (SORBS3) and spectrin beta 4 (SPTBN4). These hypermethylation targets indicate that the cyclic AMP response element-binding protein (CREB) activation pathway and the axon initial segment could contribute to the disease. PMID:24030951

  1. 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

  2. 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; ODonnell, 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?510?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

  3. Genetic similarity between cancers and comorbid Mendelian diseases identifies candidate driver genes

    PubMed Central

    Melamed, Rachel D.; Emmett, Kevin J.; Madubata, Chioma; Rzhetsky, Andrey; Rabadan, Raul

    2015-01-01

    Despite large-scale cancer genomics studies, key somatic mutations driving cancer, and their functional roles, remain elusive. Here we propose that analysis of comorbidities of Mendelian diseases with cancers provides a novel, systematic way to discover new cancer genes. If germline genetic variation in Mendelian loci predisposes bearers to common cancers, the same loci may harbor cancer-associated somatic variation. Compilations of clinical records spanning over 100 million patients provide an unprecedented opportunity to assess clinical associations between Mendelian diseases and cancers. We systematically compare these comorbidities against recurrent somatic mutations from more than five thousand patients across many cancers. Using multiple measures of genetic similarity, we show that a Mendelian disease and comorbid cancer indeed have genetic alterations of significant functional similarity. This result provides a basis to identify candidate drivers in cancers including melanoma and glioblastoma. Some Mendelian diseases demonstrate pan-cancer comorbidity and shared genetics across cancers. PMID:25926297

  4. 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?gene of KBD. Our results provide novel clues for revealing the pathogenesis of KBD and the biological function of FGF12. PMID:26290467

  5. Comparative gene expression analysis in mouse models for multiple sclerosis, Alzheimers disease and stroke for identifying commonly regulated and disease-specific gene changes

    PubMed Central

    Tseveleki, Vivian; Rubio, Renee; Vamvakas, Sotiris-Spyros; White, Joseph; Taoufik, Era; Petit, Edwige; Quackenbush, John; Probert, Lesley

    2014-01-01

    The brain responds to injury and infection by activating innate defense and tissue repair mechanisms. Working upon the hypothesis that the brain defense response involves common genes and pathways across diverse pathologies, we analysed global gene expression in brain from mouse models representing three major central nervous system disorders, cerebral stroke, multiple sclerosis and Alzheimers disease compared to normal brain using DNA microarray expression profiling. A comparison of dysregulated genes across disease models revealed common genes and pathways including key components of estrogen and TGF-? signaling pathways that have been associated with neuroprotection as well as a neurodegeneration mediator, TRPM7. Further, for each disease model, we discovered collections of differentially expressed genes that provide novel insight into the individual pathology and its associated mechanisms. Our data provide a resource for exploring the complex molecular mechanisms that underlie brain neurodegeneration and a new approach for identifying generic and disease-specific targets for therapy. PMID:20435134

  6. Integrated analysis of differential gene expression profiles in hippocampi to identify candidate genes involved in Alzheimer's disease

    PubMed Central

    HU, WANHUA; LIN, XIAODONG; CHEN, KELONG

    2015-01-01

    Alzheimer's disease (AD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. Identifying altered neuronal gene expression in AD may provide diagnostic or therapeutic targets for AD. The present study aimed to identify differentially expressed genes (DEGs) and their further association with other biological processes that regulate causative factors for AD. The present study performed an integrated analysis of publicly available gene expression omnibus datasets of AD hippocampi. Gene ontology (GO) enrichment analyses, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein-Protein interaction (PPI) network analysis were performed. The present study detected 295 DEGs (109 upregulated and 186 downregulated genes) in hippocampi between AD and control samples by integrating four datasets of gene expression profiles of hippocampi of patients with AD. Respiratory electron transport chain (GO: 0022904; P=1.6410?11) was the most significantly enriched GO term among biological processes, while for molecular functions, the most significantly enriched GO term was that of protein binding (GO: 0005515; P=3.0310?29), and for cellular components, the most significantly enriched GO term was that of the cytoplasm (GO: 0005737; P=8.6710?33). The most significant pathway in the KEGG analysis was oxidative phosphorylation (P=1.6110?13). PPI network analysis showed that the significant hub proteins contained ?-actin (degree, 268), hepatoma-derived growth factor (degree, 218) and WD repeat-containing protein 82 (degree, 87). The integrated analysis performed in the present study serves as a basis for identifying novel drug targets to develop improved therapies and interventions for common and devastating neurological diseases such as AD. PMID:26324066

  7. Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene.

    PubMed

    Davison, Lucy J; Wallace, Chris; Cooper, Jason D; Cope, Nathan F; Wilson, Nicola K; Smyth, Deborah J; Howson, Joanna M M; Saleh, Nada; Al-Jeffery, Abdullah; Angus, Karen L; Stevens, Helen E; Nutland, Sarah; Duley, Simon; Coulson, Richard M R; Walker, Neil M; Burren, Oliver S; Rice, Catherine M; Cambien, Francois; Zeller, Tanja; Munzel, Thomas; Lackner, Karl; Blakenberg, Stefan; Fraser, Peter; Gottgens, Berthold; Todd, John A; Attwood, Tony; Belz, Stephanie; Braund, Peter; Cambien, François; Cooper, Jason; Crisp-Hihn, Abi; Diemert, Patrick; Deloukas, Panos; Foad, Nicola; Erdmann, Jeanette; Goodall, Alison H; Gracey, Jay; Gray, Emma; Williams, Rhian G; Heimerl, Susanne; Hengstenberg, Christian; Jolley, Jennifer; Krishnan, Unni; Lloyd-Jones, Heather; Lugauer, Ingrid; Lundmark, Per; Maouche, Seraya; Moore, Jasbir S; Muir, David; Murray, Elizabeth; Nelson, Chris P; Neudert, Jessica; Niblett, David; O'Leary, Karen; Ouwehand, Willem H; Pollard, Helen; Rankin, Angela; Rice, Catherine M; Sager, Hendrik; Samani, Nilesh J; Sambrook, Jennifer; Schmitz, Gerd; Scholz, Michael; Schroeder, Laura; Schunkert, Heribert; Syvannen, Ann-Christine; Tennstedt, Stefanie; Wallace, Chris

    2012-01-15

    The chromosome 16p13 region has been associated with several autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). CLEC16A has been reported as the most likely candidate gene in the region, since it contains the most disease-associated single-nucleotide polymorphisms (SNPs), as well as an imunoreceptor tyrosine-based activation motif. However, here we report that intron 19 of CLEC16A, containing the most autoimmune disease-associated SNPs, appears to behave as a regulatory sequence, affecting the expression of a neighbouring gene, DEXI. The CLEC16A alleles that are protective from T1D and MS are associated with increased expression of DEXI, and no other genes in the region, in two independent monocyte gene expression data sets. Critically, using chromosome conformation capture (3C), we identified physical proximity between the DEXI promoter region and intron 19 of CLEC16A, separated by a loop of >150 kb. In reciprocal experiments, a 20 kb fragment of intron 19 of CLEC16A, containing SNPs associated with T1D and MS, as well as with DEXI expression, interacted with the promotor region of DEXI but not with candidate DNA fragments containing other potential causal genes in the region, including CLEC16A. Intron 19 of CLEC16A is highly enriched for transcription-factor-binding events and markers associated with enhancer activity. Taken together, these data indicate that although the causal variants in the 16p13 region lie within CLEC16A, DEXI is an unappreciated autoimmune disease candidate gene, and illustrate the power of the 3C approach in progressing from genome-wide association studies results to candidate causal genes. PMID:21989056

  8. 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<510?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 1.061.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ?4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity?=?0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes. PMID:21966275

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

    PubMed

    2011-09-01

    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<510(-7)). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ?4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity?=?0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes. PMID:21966275

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Resistance to infection takes place at many levels, and involves both non-specific and specific immune mechanisms. The chicken has a different repertoire of immune genes, molecules, cells and organs compared to mammals. To understand the role of any disease resistance gene(s), it is therefore impo...

  11. 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, Slav; Katz, Anas; 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, Bndicte; 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

  12. Peripheral blood gene expression patterns discriminate among chronic inflammatory diseases and healthy controls and identify novel targets

    PubMed Central

    2010-01-01

    Background Chronic inflammatory diseases including inflammatory bowel disease (IBD; Crohn's disease and ulcerative colitis), psoriasis and rheumatoid arthritis (RA) afflict millions of people worldwide, but their pathogenesis is still not well understood. It is also not well known if distinct changes in gene expression characterize these diseases and if these patterns can discriminate between diseased and control patients and/or stratify the disease. The main focus of our work was the identification of novel markers that overlap among the 3 diseases or discriminate them from each other. Methods Diseased (n = 13, n = 15 and n = 12 in IBD, psoriasis and RA respectively) and healthy patients (n = 18) were recruited based on strict inclusion and exclusion criteria; peripheral blood samples were collected by clinicians (30 ml) in Venous Blood Vacuum Collection Tubes containing EDTA and peripheral blood mononuclear cells were separated by Ficoll gradient centrifugation. RNA was extracted using Trizol reagent. Gene expression data was obtained using TaqMan Low Density Array (TLDA) containing 96 genes that were selected by an algorithm and the statistical analyses were performed in Prism by using non-parametric Mann-Whitney U test (P-values < 0.05). Results Here we show that using a panel of 96 disease associated genes and measuring mRNA expression levels in peripheral blood derived mononuclear cells; we could identify disease-specific gene panels that separate each disease from healthy controls. In addition, a panel of five genes such as ADM, AQP9, CXCL2, IL10 and NAMPT discriminates between all samples from patients with chronic inflammation and healthy controls. We also found genes that stratify the diseases and separate different subtypes or different states of prognosis in each condition. Conclusions These findings and the identification of five universal markers of chronic inflammation suggest that these diseases have a common background in pathomechanism, but still can be separated by peripheral blood gene expression. Importantly, the identified genes can be associated with overlapping biological processes including changed inflammatory response. Gene panels based on such markers can play a major role in the development of personalized medicine, in monitoring disease progression and can lead to the identification of new potential drug targets in chronic inflammation. PMID:20444268

  13. 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

  14. Real-time qPCR identifies suitable reference genes for Borna disease virus-infected rat cortical neurons.

    PubMed

    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

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

    PubMed Central

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

    2011-01-01

    Sex-differences in human liver gene expression were characterized on a genome-wide scale using a large liver sample collection, allowing for detection of small expression differences with high statistical power. 1,249 sex-biased genes were identified, 70% showing higher expression in females. Chromosomal bias was apparent, with female-biased genes enriched on chrX and male-biased genes enriched on chrY and chr19, where 11 male-biased zinc-finger KRAB-repressor domain genes are distributed in six clusters. Top biological functions and diseases significantly enriched in sex-biased genes include transcription, chromatin organization and modification, sexual reproduction, lipid metabolism and cardiovascular disease. Notably, sex-biased genes are enriched at loci associated with polygenic dyslipidemia and coronary artery disease in genome-wide association studies. Moreover, of the 8 sex-biased genes at these loci, 4 have been directly linked to monogenic disorders of lipid metabolism and show an expression profile in females (elevated expression of ABCA1, APOA5 and LDLR; reduced expression of LIPC) that is consistent with the lower female risk of coronary artery disease. Female-biased expression was also observed for CYP7A1, which is activated by drugs used to treat hypercholesterolemia. Several sex-biased drug-metabolizing enzyme genes were identified, including members of the CYP, UGT, GPX and ALDH families. Half of 879 mouse orthologs, including many genes of lipid metabolism and homeostasis, show growth hormone-regulated sex-biased expression in mouse liver, suggesting growth hormone might play a similar regulatory role in human liver. Finally, the evolutionary rate of protein coding regions for human-mouse orthologs, revealed by dN/dS ratio, is significantly higher for genes showing the same sex-bias in both species than for non-sex-biased genes. These findings establish that human hepatic sex differences are widespread and affect diverse cell metabolic processes, and may help explain sex differences in lipid profiles associated with sex differential risk of coronary artery disease. PMID:21858147

  16. 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.

  17. Rare copy number variations in congenital heart disease patients identify unique genes in left-right patterning

    PubMed Central

    Fakhro, Khalid A.; Choi, Murim; Ware, Stephanie M.; Belmont, John W.; Towbin, Jeffrey A.; Lifton, Richard P.; Khokha, Mustafa K.; Brueckner, Martina

    2011-01-01

    Dominant human genetic diseases that impair reproductive fitness and have high locus heterogeneity constitute a problem for gene discovery because the usual criterion of finding more mutations in specific genes than expected by chance may require extremely large populations. Heterotaxy (Htx), a congenital heart disease resulting from abnormalities in left-right (LR) body patterning, has features suggesting that many cases fall into this category. In this setting, appropriate model systems may provide a means to support implication of specific genes. By high-resolution genotyping of 262 Htx subjects and 991 controls, we identify a twofold excess of subjects with rare genic copy number variations in Htx (14.5% vs. 7.4%, P = 1.5 × 10−4). Although 7 of 45 Htx copy number variations were large chromosomal abnormalities, 38 smaller copy number variations altered a total of 61 genes, 22 of which had Xenopus orthologs. In situ hybridization identified 7 of these 22 genes with expression in the ciliated LR organizer (gastrocoel roof plate), a marked enrichment compared with 40 of 845 previously studied genes (sevenfold enrichment, P < 10−6). Morpholino knockdown in Xenopus of Htx candidates demonstrated that five (NEK2, ROCK2, TGFBR2, GALNT11, and NUP188) strongly disrupted both morphological LR development and expression of pitx2, a molecular marker of LR patterning. These effects were specific, because 0 of 13 control genes from rare Htx or control copy number variations produced significant LR abnormalities (P = 0.001). These findings identify genes not previously implicated in LR patterning. PMID:21282601

  18. Integrated whole transcriptome and DNA methylation analysis identifies gene networks specific to late-onset Alzheimer's disease.

    PubMed

    Humphries, Crystal E; Kohli, Martin A; Nathanson, Lubov; Whitehead, Patrice; Beecham, Gary; Martin, Eden; Mash, Deborah C; Pericak-Vance, Margaret A; Gilbert, John

    2015-01-01

    Previous transcriptome studies observed disrupted cellular processes in late-onset Alzheimer's disease (LOAD), yet it is unclear whether these changes are specific to LOAD, or are common to general neurodegeneration. In this study, we address this question by examining transcription in LOAD and comparing it to cognitively normal controls and a cohort of "disease controls." Differential transcription was examined using RNA-seq, which allows for the examination of protein coding genes, non-coding RNAs, and splicing. Significant transcription differences specific to LOAD were observed in five genes: C10orf105, DIO2, a lincRNA, RARRES3, and WIF1. These findings were replicated in two independent publicly available microarray data sets. Network analyses, performed on 2,504 genes with moderate transcription differences in LOAD, reveal that these genes aggregate into seven networks. Two networks involved in myelination and innate immune response specifically correlated to LOAD. FRMD4B and ST18, hub genes within the myelination network, were previously implicated in LOAD. Of the five significant genes, WIF1 and RARRES3 are directly implicated in the myelination process; the other three genes are located within the network. LOAD specific changes in DNA methylation were located throughout the genome and substantial changes in methylation were identified within the myelination network. Splicing differences specific to LOAD were observed across the genome and were decreased in all seven networks. DNA methylation had reduced influence on transcription within LOAD in the myelination network when compared to both controls. These results hint at the molecular underpinnings of LOAD and indicate several key processes, genes, and networks specific to the disease. PMID:25380588

  19. 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, Mareks disease (MD), a lymphoproliferative disease caused by the highly oncogenic herpesvirus Marek's disease virus (M...

  20. 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

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

    PubMed Central

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

    2014-01-01

    Background Genetic variants make some contributions to inflammatory bowel disease (IBD), including Crohns disease (CD) and ulcerative colitis (UC). More than 100 susceptibility loci were identified in Western IBD studies, but susceptibility gene has not been found in Chinese IBD patients till now. Sequencing of individuals with an IBD family history is a powerful approach toward our understanding of the genetics and pathogenesis of IBD. The aim of this study, which focuses on a Han Chinese CD family, is to identify high-risk variants and potentially novel loci using whole exome sequencing technique. Methods Exome sequence data from 4 individuals belonging to a same family were analyzed using bioinformatics methods to narrow down the variants associated with CD. The potential risk genes were further analyzed by genotyping and Sanger sequencing in family members, additional 401 healthy controls (HC), 278 sporadic CD patients, 123 UC cases, a pair of monozygotic CD twins and another Chinese CD family. Results From the CD family in which the father and daughter were affected, we identified a novel single nucleotide variant (SNV) c.374T>C (p.I125T) in exon 4 of discs large homolog 1 (DLG1), a gene has been reported to play mutiple roles in cell proliferation, T cell polarity and T cell receptor signaling. After genotyping among case and controls, a PLINK analysis showed the variant was of significance (P<0.05). 4 CD patients of the other Chinese family bore another non-synonymous variant c.833G>A (p.R278Q) in exon 9 of DLG1. Conclusions We have discovered novel genetic variants in the coding regions of DLG1 gene, the results support that DLG1 is a novel potential susceptibility gene for CD in Chinese patients. PMID:24937328

  2. Whole-Exome Sequencing to Identify a Novel LMNA Gene Mutation Associated with Inherited Cardiac Conduction Disease

    PubMed Central

    Hsieh, Wen-Ping; Kuo, Chi-Tai; Wang, Wen-Ching; Chu, Chia-Han; Hung, Chiu-Lien; Cheng, Chia-Yang; Tsai, Hsin-Yi; Lee, Jia-Lin; Tang, Chuan-Yi; Hsu, Lung-An

    2013-01-01

    Background Inherited cardiac conduction diseases (CCD) are rare but are caused by mutations in a myriad of genes. Recently, whole-exome sequencing has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases. Objective To investigate the genetic background of a family affected by inherited CCD. Methods and Results We used whole-exome sequencing to study a Chinese family with multiple family members affected by CCD. Using the pedigree information, we proposed a heterozygous missense mutation (c.G695T, Gly232Val) in the lamin A/C (LMNA) gene as a candidate mutation for susceptibility to CCD in this family. The mutation is novel and is expected to affect the conformation of the coiled-coil rod domain of LMNA according to a structural model prediction. Its pathogenicity in lamina instability was further verified by expressing the mutation in a cellular model. Conclusions Our results suggest that whole-exome sequencing is a feasible approach to identifying the candidate genes underlying inherited conduction diseases. PMID:24349489

  3. 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

  4. Chicks and single-nucleotide polymorphisms: an entree into identifying genes conferring disease resistance in chicken

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek's disease (MD) is one of the most serious chronic infectious disease threats to the U.S. poultry industry. Selecting for increased genetic resistance to MD is a control strategy that can augment current vaccinal control measures. Although our previous efforts integrating various genomic scre...

  5. 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...

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

    PubMed Central

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

    2011-01-01

    Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2df<5×10−8 in GWAIS, and OR = 0.41, P = 3×10−8 in heavy coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that are missed in GWAS. Both adenosine antagonists (caffeine-like) and glutamate antagonists (GRIN2A-related) are being tested in clinical trials for treatment of PD. GRIN2A may be a useful pharmacogenetic marker for subdividing individuals in clinical trials to determine which medications might work best for which patients. PMID:21876681

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

    PubMed Central

    2011-01-01

    Introduction A number of genetic-association studies have identified genes contributing to ankylosing spondylitis (AS) susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a 'snapshot' of the sampled cells' activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort. Methods A total of 18 active AS patients, classified according to the New York criteria, and 18 gender- and age-matched controls were profiled using Illumina HT-12 whole-genome expression BeadChips which carry cDNAs for 48,000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan low density arrays (TLDAs). Results A total of 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a P-value <0.0005 (80% confidence level of false discovery rate). Forty-seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 downregulated 1.3- to 2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300, which modulate cartilage and bone metabolism. Conclusions We have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease. PMID:21470430

  8. Identifying Gene Interaction Networks

    PubMed Central

    Bebek, Gurkan

    2016-01-01

    In this chapter, we introduce interaction networks by describing how they are generated, where they are stored, and how they are shared. We focus on publicly available interaction networks and describe a simple way of utilizing these resources. As a case study, we used Cytoscape, an open source and easy-to-use network visualization and analysis tool to first gather and visualize a small network. We have analyzed this network’s topological features and have looked at functional enrichment of the network nodes by integrating the gene ontology database. The methods described are applicable to larger networks that can be collected from various resources. PMID:22307715

  9. Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

    PubMed Central

    Emmanuel, Catherine; Gava, Natalie; Kennedy, Catherine; Balleine, Rosemary L.; Sharma, Raghwa; Wain, Gerard; Brand, Alison; Hogg, Russell; Etemadmoghadam, Dariush; George, Joshy; Birrer, Michael J.; Clarke, Christine L.; Chenevix-Trench, Georgia; Bowtell, David D. L.; Harnett, Paul R.; deFazio, Anna

    2011-01-01

    Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute to the development of ovarian cancer. PMID:21423607

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

    PubMed Central

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

    2011-01-01

    Marek's disease virus (MDV) is a highly contagious oncogenic alphaherpesvirus that causes disease that is both a cancer model and a continuing threat to the world's poultry industry. This comprehensive gene expression study analyzes the host response to infection in both resistant and susceptible lines of chickens and inherent expression differences between the two lines following the infection of the host. A novel pathogenicity mechanism, involving the downregulation of genes containing HIC1 transcription factor binding sites as early as 4 days postinfection, was suggested from this analysis. HIC1 drives antitumor mechanisms, suggesting that MDV infection switches off genes involved in antitumor regulation several days before the expression of the MDV oncogene meq. The comparison of the gene expression data to previous QTL data identified several genes as candidates for involvement in resistance to MD. One of these genes, IRG1, was confirmed by single nucleotide polymorphism analysis to be involved in susceptibility. Its precise mechanism remains to be elucidated, although the analysis of gene expression data suggests it has a role in apoptosis. Understanding which genes are involved in susceptibility/resistance to MD and defining the pathological mechanisms of the disease gives us a much greater ability to try to reduce the incidence of this virus, which is costly to the poultry industry in terms of both animal welfare and economics. PMID:21865384

  11. Positively Selected Disease Response Orthologous Gene Sets in the Cereals Identified Using Sorghum bicolor L. Moench Expression Profiles and Comparative Genomics

    PubMed Central

    Zamora, Alejandro; Sun, Qi; Hamblin, Martha T.; Aquadro, Charles F.; Kresovich, Stephen

    2009-01-01

    Disease response genes (DRGs) diverge under recurrent positive selection as a result of a molecular arms race between hosts and pathogens. Most of these studies were conducted in animals, and few defense genes have been shown to evolve adaptively in plants. To test for adaptation in the molecules mediating disease resistance in the cereals, we first combined information from the expression pattern of Sorghum bicolor genes and from divergence to the full genome of rice to identify candidate DRGs. We then used evolutionary analyses of orthologous gene sets from several grass species, to determine whether the DRGs show signals of positive selection and the residues targeted. We found 140 divergent genes upregulated under biotic stress in S. bicolor by evaluating the relative abundance of expressed sequence tags in different libraries and comparing them with rice genes. For 10 of these genes, we found sets of orthologs including sequences from rice and three other cereals; six genes showed a pattern of substitution that was consistent with positive selection. Three of these genes, a thaumatin, a peroxidase, and a barley mlo homolog, are known antifungal proteins. The other three genes with evidence of positive selection were a MCM-1 agamous deficiens SRF- (MADS) box transcription factor, an eIF5 translation initiation factor, and a gene of unknown function but with evidence of expression during stress. Permutation analyses, using different ortholog and paralog sequences, consistently identified five positively selected codons in the peroxidase, a member of a cluster of genes and a large gene family. We mapped the positively selected residues onto the structure of the peroxidase and thaumatin and found that all sites are on the surface of these proteins and several are close to biochemically determined active sites. Identifying new positively selected plant disease resistance genes and the critical amino acid sites provides a basis for functional studies that may increase our understanding of their underlying molecular mechanisms of action. Additionally, it may lead to the identification of individuals having variation at functionally important sites, as well as eventually using this information in the rational design and engineering of proteins involved in plant disease resistance. PMID:19506000

  12. Genome-wide haplotype association study identify TNFRSF1A, CASP7, LRP1B, CDH1 and TG genes associated with Alzheimer's disease in Caribbean Hispanic individuals.

    PubMed

    Shang, Zhenwei; Lv, Hongchao; Zhang, Mingming; Duan, Lian; Wang, Situo; Li, Jin; Liu, Guiyou; Ruijie, Zhang; Jiang, Yongshuai

    2015-12-15

    Alzheimer's disease (AD) is an acquired disorder of cognitive and behavioral impairment. It is considered to be caused by variety of factors, such as age, environment and genetic factors. In order to identify the genetic affect factors of AD, we carried out a bioinformatic approach which combined genome-wide haplotype-based association study with gene prioritization. The raw SNP genotypes data was downloaded from GEO database (GSE33528). It contains 615 AD patients and 560 controls of Caribbean Hispanic individuals. Firstly, we identified the linkage disequilibrium (LD) haplotype blocks and performed genome-wide haplotype association study to screen significant haplotypes that were associated with AD. Then we mapped these significant haplotypes to genes and obtained candidate genes set for AD. At last, we prioritized AD candidate genes based on their similarity with 36 known AD genes, so as to identify AD related genes. The results showed that 141 haplotypes on 134 LD blocks were significantly associated with AD (P<1E-4), and these significant haplotypes were mapped to 132 AD candidate genes. After prioritizing these candidate genes, we found seven AD related genes: APOE, APOC1, TNFRSF1A, LRP1B, CDH1, TG and CASP7. Among these genes, APOE and APOC1 are known AD risk genes. For the other five genes TNFRSF1A, CDH1, CASP7, LRP1B and TG, this is the first genetic association study which showed the significant association between these five genes and AD susceptibility in Caribbean Hispanic individuals. We believe that our findings can provide a new perspective to understand the genetic affect factors of AD. PMID:26621834

  13. Genome-wide haplotype association study identify TNFRSF1A, CASP7, LRP1B, CDH1 and TG genes associated with Alzheimer's disease in Caribbean Hispanic individuals

    PubMed Central

    Shang, Zhenwei; Lv, Hongchao; Zhang, Mingming; Duan, Lian; Wang, Situo; Li, Jin; Liu, Guiyou; Ruijie, Zhang; Jiang, Yongshuai

    2015-01-01

    Alzheimer's disease (AD) is an acquired disorder of cognitive and behavioral impairment. It is considered to be caused by variety of factors, such as age, environment and genetic factors. In order to identify the genetic affect factors of AD, we carried out a bioinformatic approach which combined genome-wide haplotype-based association study with gene prioritization. The raw SNP genotypes data was downloaded from GEO database (GSE33528). It contains 615 AD patients and 560 controls of Caribbean Hispanic individuals. Firstly, we identified the linkage disequilibrium (LD) haplotype blocks and performed genome-wide haplotype association study to screen significant haplotypes that were associated with AD. Then we mapped these significant haplotypes to genes and obtained candidate genes set for AD. At last, we prioritized AD candidate genes based on their similarity with 36 known AD genes, so as to identify AD related genes. The results showed that 141 haplotypes on 134 LD blocks were significantly associated with AD (P<1E-4), and these significant haplotypes were mapped to 132 AD candidate genes. After prioritizing these candidate genes, we found seven AD related genes: APOE, APOC1, TNFRSF1A, LRP1B, CDH1, TG and CASP7. Among these genes, APOE and APOC1 are known AD risk genes. For the other five genes TNFRSF1A, CDH1, CASP7, LRP1B and TG, this is the first genetic association study which showed the significant association between these five genes and AD susceptibility in Caribbean Hispanic individuals. We believe that our findings can provide a new perspective to understand the genetic affect factors of AD. PMID:26621834

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

    PubMed Central

    2014-01-01

    Background An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity. PMID:25032995

  15. CSGene: a literature-based database for cell senescence genes and its application to identify critical cell aging pathways and associated diseases.

    PubMed

    Zhao, M; Chen, L; Qu, H

    2016-01-01

    Cell senescence is a cellular process in which normal diploid cells cease to replicate and is a major driving force for human cancers and aging-associated diseases. Recent studies on cell senescence have identified many new genetic components and pathways that control cell aging. However, there is no comprehensive resource for cell senescence that integrates various genetic studies and relationships with cell senescence, and the risk associated with complex diseases such as cancer is still unexplored. We have developed the first literature-based gene resource for exploring cell senescence genes, CSGene. We complied 504 experimentally verified genes from public data resources and published literature. Pathway analyses highlighted the prominent roles of cell senescence genes in the control of rRNA gene transcription and unusual rDNA repeat that constitute a center for the stability of the whole genome. We also found a strong association of cell senescence with HIV-1 infection and viral carcinogenesis that are mainly related to promoter/enhancer binding and chromatin modification processes. Moreover, pan-cancer mutation and network analysis also identified common cell aging mechanisms in cancers and uncovered a highly modular network structure. These results highlight the utility of CSGene for elucidating the complex cellular events of cell senescence. PMID:26775705

  16. Identifying gene regulatory networks in schizophrenia.

    PubMed

    Potkin, Steven G; Macciardi, Fabio; Guffanti, Guia; Fallon, James H; Wang, Qi; Turner, Jessica A; Lakatos, Anita; Miles, Michael F; Lander, Arthur; Vawter, Marquis P; Xie, Xiaohui

    2010-11-15

    The imaging genetics approach to studying the genetic basis of disease leverages the individual strengths of both neuroimaging and genetic studies by visualizing and quantifying the brain activation patterns in the context of genetic background. Brain imaging as an intermediate phenotype can help clarify the functional link among genes, the molecular networks in which they participate, and brain circuitry and function. Integrating genetic data from a genome-wide association study (GWAS) with brain imaging as a quantitative trait (QT) phenotype can increase the statistical power to identify risk genes. A QT analysis using brain imaging (DLPFC activation during a working memory task) as a quantitative trait has identified unanticipated risk genes for schizophrenia. Several of these genes (RSRC1, ARHGAP18, ROBO1-ROBO2, GPC1, TNIK, and CTXN3-SLC12A2) have functions related to progenitor cell proliferation, migration, and differentiation, cytoskeleton reorganization, axonal connectivity, and development of forebrain structures. These genes, however, do not function in isolation but rather through gene regulatory networks. To obtain a deeper understanding how the GWAS-identified genes participate in larger gene regulatory networks, we measured correlations among transcript levels in the mouse and human postmortem tissue and performed a gene set enrichment analysis (GSEA) that identified several microRNA associated with schizophrenia (448, 218, 137). The results of such computational approaches can be further validated in animal experiments in which the networks are experimentally studied and perturbed with specific compounds. Glypican 1 and FGF17 mouse models for example, can be used to study such gene regulatory networks. The model demonstrates epistatic interactions between FGF and glypican on brain development and may be a useful model of negative symptom schizophrenia. PMID:20600988

  17. 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; Marques Loureno, Charles; Ramadevi, Kanakasabapathi; Ranganath, Lakshminarayan R; Gallagher, James A; van Kan, Christa; Hall, Anthony K; Olsson, Birgitta; Sireau, Nicolas; Ayoob, Hana; Timmis, Oliver G; Le Quan Sang, Kim-Hanh; 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. PMID:25804398

  18. 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

    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

  19. 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; Boss, 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; Bue, L; Campion, D; Soininen, H; Breteler, M; Riemenschneider, M; Van Broeckhoven, C; Alprovitch, A; Lathrop, M; Trgout, 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 casecontrol 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: (1.431.96); P=1.1 10?10). We finally searched for association between SNPs within the FRMD4A locus and A? plasma concentrations in three independent non-demented populations (n=2579). We reported that polymorphisms were associated with plasma A?42/A?40 ratio (best signal, P=5.4 10?7). In conclusion, combining both GWHA study and a conservative three-stage replication approach, we characterised FRMD4A as a new genetic risk factor of AD. PMID:22430674

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

    PubMed

    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; Boss, P; Annoni, G; Nacmias, B; Bosco, P; Panza, F; Sanchez-Garcia, F; Del Zompo, M; Coto, E; Owen, M; O'Donovan, M; Valdivieso, F; Caffarra, P; Caffara, P; Scarpini, E; Combarros, O; Bue, L; Campion, D; Soininen, H; Breteler, M; Riemenschneider, M; Van Broeckhoven, C; Alprovitch, A; Lathrop, M; Trgout, D-A; Williams, J; Amouyel, P

    2013-04-01

    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 A? plasma concentrations in three independent non-demented populations (n=2579). We reported that polymorphisms were associated with plasma A?42/A?40 ratio (best signal, P=5.4 10(-7)). In conclusion, combining both GWHA study and a conservative three-stage replication approach, we characterised FRMD4A as a new genetic risk factor of AD. PMID:22430674

  1. A severe recessive and a mild dominant form of Charcot-Marie-Tooth disease associated with a newly identified Glu222Lys GDAP1 gene mutation.

    PubMed

    Kabzi?ska, Dagmara; Kotruchow, Katarzyna; Cegielska, Joanna; Hausmanowa-Petrusewicz, Irena; Kocha?ski, Andrzej

    2014-01-01

    Charcot-Marie-Tooth (CMT) disease caused by mutations in the GDAP1 gene has been shown to be inherited via traits that may be either autosomal recessive (in the majority of cases) [CMT4A] or autosomal dominant [CMT2K]. CMT4A disease is characterized by an early onset, and a severe clinical course often leading to a loss of ambulation, whereas CMT2K is characterized by a mild clinical course of benign axonal neuropathy beginning even in the 6th decade of life. Clinical data from a GDAP1 mutated patient suggests that the presence of a particular mutation is associated with a certain trait of inheritance. The association of a particular GDAP1 gene mutation and a dominant or recessive trait of inheritance is of special importance for genetic counseling and the prenatal diagnostics as regards severe forms of CMT. In the present study we report on two CMT families in which a newly identified Glu222Lys mutation within the GDAP1 gene segregates both in autosomal dominant and recessive traits. Our study shows that at least some GDAP1 gene mutations may segregate with the CMT phenotype as both dominant and recessive traits. Thus, genetic counseling for CMT4A/CMT2K families requires more extensive data on GDAP1 phenotype-genotype correlations. PMID:25337607

  2. Broker Genes in Human Disease

    PubMed Central

    Cai, James J.; Borenstein, Elhanan; Petrov, Dmitri A.

    2010-01-01

    Genes that underlie human disease are important subjects of systems biology research. In the present study, we demonstrate that Mendelian and complex disease genes have distinct and consistent proteinprotein interaction (PPI) properties. We show that five different network properties can be reduced to two independent metrics when applied to the human PPI network. These two metrics largely coincide with the degree (number of connections) and the clustering coefficient (the number of connections among the neighbors of a particular protein). We demonstrate that disease genes have simultaneously unusually high degree and unusually low clustering coefficient. Such genes can be described as brokers in that they connect many proteins that would not be connected otherwise. We show that these results are robust to the effect of gene age and inspection bias variation. Notably, genes identified in genome-wide association study (GWAS) have network patterns that are almost indistinguishable from the network patterns of nondisease genes and significantly different from the network patterns of complex disease genes identified through non-GWAS means. This suggests either that GWAS focused on a distinct set of diseases associated with an unusual set of genes or that mapping of GWAS-identified single nucleotide polymorphisms onto the causally affected neighboring genes is error prone. PMID:20937604

  3. 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

  4. Identifying proteins controlling key disease signaling pathways

    PubMed Central

    Gitter, Anthony; Bar-Joseph, Ziv

    2013-01-01

    Motivation: Several types of studies, including genome-wide association studies and RNA interference screens, strive to link genes to diseases. Although these approaches have had some success, genetic variants are often only present in a small subset of the population, and screens are noisy with low overlap between experiments in different labs. Neither provides a mechanistic model explaining how identified genes impact the disease of interest or the dynamics of the pathways those genes regulate. Such mechanistic models could be used to accurately predict downstream effects of knocking down pathway members and allow comprehensive exploration of the effects of targeting pairs or higher-order combinations of genes. Results: We developed methods to model the activation of signaling and dynamic regulatory networks involved in disease progression. Our model, SDREM, integrates static and time series data to link proteins and the pathways they regulate in these networks. SDREM uses prior information about proteins likelihood of involvement in a disease (e.g. from screens) to improve the quality of the predicted signaling pathways. We used our algorithms to study the human immune response to H1N1 influenza infection. The resulting networks correctly identified many of the known pathways and transcriptional regulators of this disease. Furthermore, they accurately predict RNA interference effects and can be used to infer genetic interactions, greatly improving over other methods suggested for this task. Applying our method to the more pathogenic H5N1 influenza allowed us to identify several strain-specific targets of this infection. Availability: SDREM is available from http://sb.cs.cmu.edu/sdrem Contact: zivbj@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23812988

  5. New Genes Tied to Alzheimer's Disease

    MedlinePLUS

    ... Matters November 4, 2013 New Genes Tied to Alzheimer’s Disease Researchers identified 11 new genes that affect the risk for Alzheimer’s disease. The findings point to novel targets for preventing ...

  6. Human genes and diseases

    SciTech Connect

    Blasi, F.

    1986-01-01

    This book consists of 16 chapters. Some of the chapter titles are: Towards a complete linkage map of he X-chromosome; The role of HPRT genes in human disease; Human plasminogen activators. Genes and proteins structure; Metallothionein gene regulation in Menke's Disease; Molecular genetics of human B cell neoplasia, The erb-B related growth factors receptors, and Aldolase gene and protein families: structure, expression and molecular pathophysiology.

  7. 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

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

    PubMed Central

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

    2014-01-01

    Between 10 and 25% of individuals with non-alcoholic fatty liver disease (NAFLD) develop hepatic fibrosis leading to cirrhosis and hepatocellular carcinoma (HCC). To investigate the molecular basis of disease progression, we performed a genome-wide analysis of copy number variation (CNV) in a total of 49 patients with NAFLD [10 simple steatosis and 39 non-alcoholic steatohepatitis (NASH)] and 49 matched controls using high-density comparative genomic hybridization (CGH) microarrays. A total of 11 CNVs were found to be unique to individuals with simple steatosis, whilst 22 were common between simple steatosis and NASH, and 224 were unique to NASH. We postulated that these CNVs could be involved in the pathogenesis of NAFLD progression. After stringent filtering, we identified four rare and/or novel CNVs that may influence the pathogenesis of NASH. Two of these CNVs, located at 13q12.11 and 12q13.2 respectively, harbour the exportin 4 (XPO4) and phosphodiesterase 1B (PDE1B) genes which are already known to be involved in the etiology of liver cirrhosis and HCC. Cross-comparison of the genes located at these four CNV loci with genes already known to be associated with NAFLD yielded a set of genes associated with shared biological processes including cell death, the key process involved in ‘second hit’ hepatic injury. To our knowledge, this pilot study is the first to provide CNV information of potential relevance to the NAFLD spectrum. These data could prove invaluable in predicting patients at risk of developing NAFLD and more importantly, those who will subsequently progress to NASH. PMID:24743702

  9. Candidate genes for panhypopituitarism identified by gene expression profiling

    PubMed Central

    Mortensen, Amanda H.; MacDonald, James W.; Ghosh, Debashis

    2011-01-01

    Mutations in the transcription factors PROP1 and PIT1 (POU1F1) lead to pituitary hormone deficiency and hypopituitarism in mice and humans. The dysmorphology of developing Prop1 mutant pituitaries readily distinguishes them from those of Pit1 mutants and normal mice. This and other features suggest that Prop1 controls the expression of genes besides Pit1 that are important for pituitary cell migration, survival, and differentiation. To identify genes involved in these processes we used microarray analysis of gene expression to compare pituitary RNA from newborn Prop1 and Pit1 mutants and wild-type littermates. Significant differences in gene expression were noted between each mutant and their normal littermates, as well as between Prop1 and Pit1 mutants. Otx2, a gene critical for normal eye and pituitary development in humans and mice, exhibited elevated expression specifically in Prop1 mutant pituitaries. We report the spatial and temporal regulation of Otx2 in normal mice and Prop1 mutants, and the results suggest Otx2 could influence pituitary development by affecting signaling from the ventral diencephalon and regulation of gene expression in Rathke's pouch. The discovery that Otx2 expression is affected by Prop1 deficiency provides support for our hypothesis that identifying molecular differences in mutants will contribute to understanding the molecular mechanisms that control pituitary organogenesis and lead to human pituitary disease. PMID:21828248

  10. 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

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

    PubMed

    Cossard, Raynald; Esposito, Michela; Sellem, Carole H; Pitayu, Laras; Vasnier, Christelle; Delahodde, Agns; 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

  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. NIH Researchers Identify OCD Risk Gene

    MedlinePLUS

    ... Issues Research News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of ... gene variant that doubles an individual's risk for obsessive-compulsive disorder (OCD). The new functional variant, or allele, is ...

  14. Identifying Common Genes and Networks in Multi-Organ Fibrosis

    PubMed Central

    Wenzke, Kevin E.; Cantemir-Stone, Carmen; Zhang, Jie; Marsh, Clay B.; Huang, Kun

    2012-01-01

    Fibroproliferative diseases of organs are poorly understood and generally lack effective anti-fibrotic treatments. Our goal was to identify the key regulatory factors in pathologic fibrosis, common between organ-based fibrotic disease. We analyzed 9 microarray datasets publicly available in the GEO datasets from lung, heart, liver and kidney fibrotic disease tissue (489 microarrays total, disease and control). We identified a set of 90 genes differentially expressed in at least five microarray datasets. We used IPA and DAVID analysis to identify gene networks and their molecular functions. A mutual information based network work activity analysis showed that a connective tissue disorders network was the most active for all types of fibrosis included in this analysis. Conclusion: Our analysis indicates that despite different disease manifestation, organ fibrosis share a specific set of genes suggesting the potential for a common origin. PMID:22779061

  15. A vector space model approach to identify genetically related diseases

    PubMed Central

    2012-01-01

    Objective The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models. Materials and Methods A vector space model approach was developed that bridges gene disease knowledge inferred across three knowledge bases: Online Mendelian Inheritance in Man, GenBank, and Medline. The approach was then used to identify potentially related diseases for two target diseases: Alzheimer disease and Prader-Willi Syndrome. Results In the case of both Alzheimer Disease and Prader-Willi Syndrome, a set of plausible diseases were identified that may warrant further exploration. Discussion This study furthers seminal work by Swanson, et al. that demonstrated the potential for mining literature for putative correlations. Using a vector space modeling approach, information from both biomedical literature and genomic resources (like GenBank) can be combined towards identification of putative correlations of interest. To this end, the relevance of the predicted diseases of interest in this study using the vector space modeling approach were validated based on supporting literature. Conclusion The results of this study suggest that a vector space model approach may be a useful means to identify potential relationships between complex diseases, and thereby enable the coordination of gene-based findings across multiple complex diseases. PMID:22227640

  16. 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

  17. Identifying potential cancer driver genes by genomic data integration.

    PubMed

    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

  18. 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.

  19. 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

  20. [Syntropic genes of allergic diseases].

    PubMed

    Fre?din, M B; Puzyrev, V P

    2010-02-01

    Common (syntropic) genes of allergic diseases (ADs) HLA-DQB1, HLA-DRB1, IL4, IL4RA, MS4A2, HLA-DQA1, LTC4S, IL13, IL10, and TGFBL have been identified on the basis of information from the HuGENet internet database. The functional sphere of competence of these genes is associated mainly with the initiation and regulation of an immune response and inflammation. Importance of these processes in the development of ADs is underlined. The results of cluster analysis of allergic diseases obtained using the data on common genes predisposing to their development are presented. Genetic clusterization ofADs confirms their accepted clinical classification. PMID:20297660

  1. Integrating Gene Regulatory Networks to identify cancer-specific genes.

    PubMed

    Bo, Valeria; Tucker, Allan

    2015-01-01

    Consensus approaches have been widely used to identify Gene Regulatory Networks (GRNs) that are common to multiple studies. However, in this research we develop an application that semi-automatically identifies key mechanisms that are specific to a particular set of conditions. We analyse four different types of cancer to identify gene pathways unique to each of them. To support the results reliability we calculate the prediction accuracy of each gene for the specified conditions and compare to predictions on other conditions. The most predictive are validated using the GeneCards encyclopaedia1 coupled with a statistical test for validating clusters. Finally, we implement an interface that allows the user to identify unique subnetworks of any selected combination of studies using AND & NOT logic operators. Results show that unique genes and sub-networks can be reliably identified and that they reflect key mechanisms that are fundamental to the cancer types under study. PMID:26306224

  2. Systematic characterisation of disease associated balanced chromosome rearrangements by FISH: cytogenetically and genetically anchored YACs identify microdeletions and candidate regions for mental retardation genes.

    PubMed

    Wirth, J; Nothwang, H G; van der Maarel, S; Menzel, C; Borck, G; Lopez-Pajares, I; Brndum-Nielsen, K; Tommerup, N; Bugge, M; Ropers, H H; Haaf, T

    1999-04-01

    Disease associated balanced chromosome rearrangements (DBCRs) have been instrumental in the isolation of many disease genes. To facilitate the molecular cytogenetic characterisation of DBCRs, we have generated a set of >1200 non-chimeric, cytogenetically and genetically anchored CEPH YACs, on average one per 3 cM, spaced over the entire human genome. By fluorescence in situ hybridisation (FISH), we have performed a systematic search for YACs spanning translocation breakpoints. Patients with DBCRs and either syndromic or non-syndromic mental retardation (MR) were ascertained through the Mendelian Cytogenetics Network (MCN), a collaborative effort of, at present, 270 cytogenetic laboratories throughout the world. In this pilot study, we have characterised 10 different MR associated chromosome regions delineating candidate regions for MR. Five of these regions are narrowed to breakpoint spanning YACs, three of which are located on chromosomes 13q21, 13q22, and 13q32, respectively, one on chromosome 4p14, and one on 6q25. In two out of six DBCRs, we found cytogenetically cryptic deletions of 3-5 Mb on one or both translocation chromosomes. Thus, cryptic deletions may be an important cause of disease in seemingly balanced chromosome rearrangements that are associated with a disease phenotype. Our region specific FISH probes, which are available to MCN members, can be a powerful tool in clinical cytogenetics and positional cloning. PMID:10227392

  3. Identifying genes related with rheumatoid arthritis via system biology analysis.

    PubMed

    Liu, Tao; Lin, Xinmei; Yu, Hongjian

    2015-10-15

    Rheumatoid arthritis (RA) is a chronic, inflammatory joint disease that mainly attacks synovial joints. However, the underlying systematic relationship among different genes and biological processes involved in the pathogenesis are still unclear. By analyzing and comparing the transcriptional profiles from RA, OA (osteoarthritis) patients as well as ND (normal donors) with bioinformatics methods, we tend to uncover the potential molecular networks and critical genes which play important roles in RA and OA development. Initially, hierarchical clustering was performed to classify the overall transcriptional profiles. Differentially expressed genes (DEGs) between ND and RA and OA patients were identified. Furthermore, PPI networks were constructed, functional modules were extracted, and functional annotation was also applied. Our functional analysis identifies 22 biological processes and 2 KEGG pathways enriched in the commonly-regulated gene set. However, we found that number of set of genes differentially expressed genes only between RA and ND reaches up to 244, indicating this gene set may specifically accounts for processing to disease of RA. Additionally, 142 biological processes and 19 KEGG pathways are over-represented by these 244 genes. Meanwhile, although another 21 genes were differentially expressed only in OA and ND, no biological process nor pathway is over-represented by them. PMID:26117171

  4. 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

  5. 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

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

    PubMed Central

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

    2010-01-01

    We undertook a two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the APOE locus (most significant SNP: rs2075650, p= 1.810?157) and observed genome-wide significant association with SNPs at two novel loci: rs11136000 in the CLU or APOJ gene (p= 1.410?9) and rs3851179, a SNP 5? to the PICALM gene (p= 1.910?8). Both novel associations were supported in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with AD in the combined dataset (rs11136000: p= 8.510?10, odds ratio= 0.86; rs3851179: p= 1.310?9, odds ratio= 0.86). We also observed more variants associated at p< 110?5 than expected by chance (p=7.510?6), including polymorphisms at the BIN1, DAB1 and CR1 loci. PMID:19734902

  7. 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

  8. 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

  9. 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

  10. [Gene therapy of hereditary diseases].

    PubMed

    Ginter, E K

    2000-01-01

    In the review the main advantages in development of the approaches to gene therapy of hereditary diseases are presented. Now more than 1000 genes of hereditary diseases are mapped and some hundreds are cloned which is prerequisite for gene therapy. The transfer of the recombinant gene into the cell and the subsequent expression of the transgene product are the rate-limiting steps for successful gene therapy. A variety of methods, including the use of physical methods, modified viruses and synthetic vectors, are currently being used in experiments and clinical trials. Since the approval and initiation of the first human gene therapy trial to treat ADA deficiency, there have been several dozen approved gene therapy trials but clear clinical result was stated for ADA deficiency only. Cystic Fibrosis, CF was among several hereditary diseases which were considered as a target for gene therapy. Experiments on development of recombinant gene constructions, gene delivery by adenovirus vectors and liposomes as well as by other constructions into epithelial lung cells, gene expression and on the safety of gene therapy procedures were relatively successful. Phase 1 gene therapy clinical trials of CF showed that some unaccounted physiological peculiarities of lung tissue of the patients diminished effectiveness of gene transfer, longevity of CFTR gene expression and in some cases unexpected immunological complications arises during clinical trials. Now an intensive attempt to overcome these problems in gene therapy of CF are undertaken. PMID:11033886

  11. Characterizing the Molecular Basis of Attenuation of Marek's Disease Virus via In Vitro Serial Passage Identifies De Novo Mutations in the Helicase-Primase Subunit Gene UL5 and Other Candidates Associated with Reduced Virulence

    PubMed Central

    Hildebrandt, Evin; Dunn, John R.; Perumbakkam, Sudeep; Niikura, Masahiro

    2014-01-01

    ABSTRACT Marek's disease (MD) is a lymphoproliferative disease of chickens caused by the oncogenic Gallid herpesvirus 2, commonly known as Marek's disease virus (MDV). MD vaccines, the primary control method, are often generated by repeated in vitro serial passage of this highly cell-associated virus to attenuate virulent MDV strains. To understand the genetic basis of attenuation, we used experimental evolution by serially passing three virulent MDV replicates generated from an infectious bacterial artificial chromosome (BAC) clone. All replicates became completely or highly attenuated, indicating that de novo mutation, and not selection among quasispecies existing in a strain, is the primary driving force for the reduction in virulence. Sequence analysis of the attenuated replicates revealed 41 to 95 single-nucleotide variants (SNVs) at 2% or higher frequency in each population and several candidate genes containing high-frequency, nonsynonymous mutations. Five candidate mutations were incorporated into recombinant viruses to determine their in vivo effect. SNVs within UL42 (DNA polymerase auxiliary subunit) and UL46 (tegument) had no measurable influence, while two independent mutations in LORF2 (a gene of unknown function) improved survival time of birds but did not alter disease incidence. A fifth SNV located within UL5 (helicase-primase subunit) greatly reduced in vivo viral replication, increased survival time of birds, and resulted in only 0 to 11% disease incidence. This study shows that multiple genes, often within pathways involving DNA replication and transcriptional regulation, are involved in de novo attenuation of MDV and provides targets for the rational design of future MD vaccines. IMPORTANCE Marek's disease virus (MDV) is a very important pathogen in chickens that costs the worldwide poultry industry $1 billion to $2 billion annually. Marek's disease (MD) vaccines, the primary control method, are often produced by passing virulent strains in cell culture until attenuated. To understand this process, we identified all the changes in the viral genome that occurred during repeated cell passage. We find that a single mutation in the UL5 gene, which encodes a viral protein necessary for DNA replication, reduces disease incidence by 90% or more. In addition, other candidate genes were identified. This information should lead to the development of more effective and rationally designed MD vaccines leading to improved animal health and welfare and lower costs to consumers. PMID:24648463

  12. Gene Therapy for Skin Diseases

    PubMed Central

    Gorell, Emily; Nguyen, Ngon; Lane, Alfred; Siprashvili, Zurab

    2014-01-01

    The skin possesses qualities that make it desirable for gene therapy, and studies have focused on gene therapy for multiple cutaneous diseases. Gene therapy uses a vector to introduce genetic material into cells to alter gene expression, negating a pathological process. This can be accomplished with a variety of viral vectors or nonviral administrations. Although results are promising, there are several potential pitfalls that must be addressed to improve the safety profile to make gene therapy widely available clinically. PMID:24692191

  13. 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

  14. The Search for Autism Disease Genes

    ERIC Educational Resources Information Center

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

    2004-01-01

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

  15. Differential network analyses of Alzheimer's disease identify early events in Alzheimer's disease pathology.

    PubMed

    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 low 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. PMID:25147748

  16. Differential Network Analyses of Alzheimer's Disease Identify Early Events in Alzheimer's Disease Pathology

    PubMed Central

    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 low 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. PMID:25147748

  17. Susceptibility Genes for Multiple Sclerosis Identified in a Gene-Based Genome-Wide Association Study

    PubMed Central

    Lin, Xiang; Deng, Fei-Yan; Lu, Xin

    2015-01-01

    Background and Purpose Multiple sclerosis (MS) is a demyelinating and inflammatory disease of the central nervous system. The aim of this study was to identify more genes associated with MS. Methods Based on the publicly available data of the single-nucleotide polymorphism-based genome-wide association study (GWAS) from the database of Genotypes and Phenotypes, we conducted a powerful gene-based GWAS in an initial sample with 931 family trios, and a replication study sample with 978 cases and 883 controls. For interesting genes, gene expression in MS-related cells between MS cases and controls was examined by using publicly available datasets. Results A total of 58 genes was identified, including 20 "novel" genes significantly associated with MS (p<1.40×10-4). In the replication study, 44 of the 58 identified genes had been genotyped and 35 replicated the association. In the gene-expression study, 21 of the 58 identified genes exhibited differential expressions in MS-related cells. Thus, 15 novel genes were supported by replicated association and/or differential expression. In particular, four of the novel genes, those encoding myelin oligodendrocyte glycoprotein (MOG), coiled-coil alpha-helical rod protein 1 (CCHCR1), human leukocyte antigen complex group 22 (HCG22), and major histocompatibility complex, class II, DM alpha (HLA-DMA), were supported by the evidence of both. Conclusions The results of this study emphasize the high power of gene-based GWAS in detecting the susceptibility genes of MS. The novel genes identified herein may provide new insights into the molecular genetic mechanisms underlying MS. PMID:26320842

  18. Gene therapy for neurodegenerative diseases.

    PubMed

    O'Connor, Deirdre M; Boulis, Nicholas M

    2015-08-01

    Gene therapy is, potentially, a powerful tool for treating neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy, Parkinson's disease (PD) and Alzheimer's disease (AD). To date, clinical trials have failed to show any improvement in outcome beyond the placebo effect. Efforts to improve outcomes are focusing on three main areas: vector design and the identification of new vector serotypes, mode of delivery of gene therapies, and identification of new therapeutic targets. These advances are being tested both individually and together to improve efficacy. These improvements may finally make gene therapy successful for these disorders. PMID:26122838

  19. 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).

  20. 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...

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

    PubMed Central

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

    2006-01-01

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

  2. Searching for the autoimmune thyroid disease susceptibility genes: from gene mapping to gene function.

    PubMed

    Tomer, Yaron; Davies, Terry F

    2003-10-01

    The autoimmune thyroid diseases (AITD) are complex diseases that are caused by an interaction between susceptibility genes and environmental triggers. Genetic susceptibility, in combination with external factors (e.g., dietary iodine), is believed to initiate the autoimmune response to thyroid antigens. Abundant epidemiological data, including family and twin studies, point to a strong genetic influence on the development of AITD. Various techniques have been used to identify the genes contributing to the etiology of AITD, including candidate gene analysis and whole genome screening. These studies have enabled the identification of several loci (genetic regions) that are linked with AITD, and in some of these loci putative AITD susceptibility genes have been identified. Some of these genes/loci are unique to Graves' disease (GD) and Hashimoto's thyroiditis (HT), and some are common to both diseases, indicating that there is a shared genetic susceptibility to GD and HT. The putative GD and HT susceptibility genes include both immune modifying genes (e.g., human leukocyte antigen, cytotoxic T lymphocyte antigen-4) and thyroid-specific genes (e.g., TSH receptor, thyroglobulin). Most likely these loci interact, and their interactions may influence disease phenotype and severity. It is hoped that in the near future additional AITD susceptibility genes will be identified and the mechanisms by which they induce AITD will be unraveled. PMID:14570752

  3. 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. PMID:26287177

  4. 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

  5. Identifying and characterizing barley genes that protect against trichothecenes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Our overall goal is to identify genes that play a role in resistance to Fusarium Head Blight (FHB) and to develop and test transgenic wheat carrying these genes. In particular, we are interested in identifying genes that protect barley and wheat from the effects of trichothecenes. Previously, we con...

  6. 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. PMID:25949096

  7. Identifying Driver Genes in Cancer by Triangulating Gene Expression, Gene Location, and Survival Data

    PubMed Central

    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. PMID:25949096

  8. 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.

  9. [Gene therapy and Alzheimer's disease].

    PubMed

    Li, Jian; Li, Wenwen; Zhou, Jun

    2015-04-01

    Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the presence of extracellular β-amyloid in the senile plaques, intracellular aggregates of abnormal phosphorylation of tau protein in the neurofibrillary tangles, neuronal loss and cerebrovascular amyloidosis. The manifestations of clinical symptoms include memory impairment, cognitive decline, altered behavior and language deficit. Currently available drugs in AD therapy consist of acetylcholinesterase inhibitors, NMDA receptor antagonists, non-steroidal anti-inflammatory drugs, etc. These drugs can only alleviate the symptoms of AD. Gene therapy is achieved by vector-mediated gene transfer technology, which can delivery DNA or RNA into target cells to promote the expression of a protective or therapeutic protein and silence certain virulence genes. PMID:25931222

  10. Identifying Constraints to Potato System Sustainability: Diseases

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Four different potato cropping systems, designed to address specific management goals of soil conservation (SC), soil improvement (SI), disease suppression (DS), and a status quo (standard rotation) control (SQ), were evaluated for their effects on soilborne and foliar diseases of potato, as well as...

  11. Multiplex PCR for identifying DMD gene deletions.

    PubMed

    den Dunnen, Johan T; Beggs, Alan H

    2006-05-01

    The identification of dystrophin as the defective protein in patients with Duchenne and Becker muscular dystrophies (DMD and BMD) has allowed the development of sensitive and specific tests to establish a diagnosis and to aid in genetic counseling and prenatal diagnosis. The Basic Protocol describes three complementary multiplex PCR assays that detect 26 dystrophin gene exons. The multiplex nature of these assays allows the detection of up to ten different exons in a single reaction. At least one of these exons is missing in >95% of deletions. The Support Protocol describes preparation and storage of stock PCR reaction mixes with primers for each of the three diagnostic assays. The Alternate Protocol is a modification of the Basic Protocol for radioactive detection of duplications in males and deletions in carrier females. PMID:18428400

  12. Classification of Missense Mutations of Disease Genes

    PubMed Central

    Zhou, Xi; Iversen, Edwin S.; Parmigiani, Giovanni

    2008-01-01

    Clinical management of individuals found to harbor a mutation at a known disease-susceptibility gene depends on accurate assessment of mutation-specific disease risk. For missense mutations (MMs)mutations that lead to a single amino acid change in the protein coded by the genethis poses a particularly challenging problem. Because it is not possible to predict the structural and functional changes to the protein product for a given amino acid substitution, and because functional assays are often not available, disease association must be inferred from data on individuals with the mutation. Inference is complicated by small sample sizes and by sampling mechanisms that bias toward individuals at high familial risk of disease. We propose a Bayesian hierarchical model to classify the disease association of MMs given pedigree data collected in the high-risk setting. The models structure allows simultaneous characterization of multiple MMs. It uses a group of pedigrees identified through probands tested positive for known disease associated mutations and a group of test-negative pedigrees, both obtained from the same clinic, to calibrate classification and control for potential ascertainment bias. We apply this model to study MMs of breast-ovarian susceptibility genes BRCA1 and BRCA2, using data collected at the Duke University Medical Center in Durham, North Carolina. PMID:18418466

  13. Activation tag screening to identify novel genes for trichothecene resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The goal of our research is to identify plant genes which enhance trichothecene resistance and, ultimately, Fusarium Head Blight resistance in wheat and barley. We are taking a two pronged approach using Arabidopsis to identify plant genes which confer resistance to trichothecenes. The first approac...

  14. 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 ...

  15. Gene Therapy for Diseases and Genetic Disorders

    MedlinePLUS

    ... Submit Your Press Release Donate Home ASGCT Gene Therapy for Diseases Gene Therapy has made important medical ... the most notable advancements are the following: Gene Therapy for Genetic Disorders Severe Combined Immune Deficiency (ADA- ...

  16. Bioinformatics analysis to identify the differentially expressed genes of glaucoma

    PubMed Central

    YAN, XIANG; YUAN, FEI; CHEN, XIUPING; DONG, CHUNQIONG

    2015-01-01

    The aim of the present study was to screen the differentially expressed genes (DEGs) associated with glaucoma and investigate the changing patterns of the expression of these genes. The GSE2378 gene microarray data of glaucoma was downloaded from the Gene Expression Omnibus database, which included seven normal samples and eight glaucoma astrocyte samples. Taking into account the corresponding associations between the probe ID and gene symbols, the DEGs were identified prior to and subsequent to the summation of probe level values using the Limma package in R language, followed by Gene Ontology (GO) and pathway enrichment analyses. Interaction networks of the DEGs were constructed using the Biomolecular Interaction Network Database, and cluster analysis of the genes in the networks was performed using ClusterONE. Subsequent to the summation of probe value, a total of 223 genes were identified as DEGs between the normal and glaucoma samples, including 74 downregulated and 149 upregulated genes. In addition, the DEGs were found to be associated with several functions, including response to wounding, extracellular region part and calcium ion binding. The most significantly enriched pathways were complement and coagulation cascades, arrhythmogenic right ventricular cardiomyopathy and extracellular matrix (ECM)-receptor interaction. Furthermore, interaction networks were constructed of the DEGs prior to and subsequent to the summation of probe values, and HNF4A and CEBPD were identified as hub genes. Additionally, 37 and 31 GO terms were identified to be enriched in the two DEGs of the networks prior to and subsequent to summation, respectively. The results indicated the identified genes associated with ECM as important, and the CEBPD gene was considered to be a critical gene in glaucoma. The findings of the present study offer a potential reference value in further investigations of glaucoma at the gene level. PMID:26135629

  17. Gene Expression Signatures of Coronary Heart Disease

    PubMed Central

    Joehanes, Roby; Ying, Saixia; Huan, Tianxiao; Johnson, Andrew D.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Woodhouse, Kimberly A.; Sen, Shurjo K.; Tanriverdi, Kahraman; Courchesne, Paul; Freedman, Jane E.; O'Donnell, Christopher J.; Levy, Daniel; Munson, Peter J.

    2013-01-01

    Objective To identify transcriptomic biomarkers of coronary heart disease (CHD) in 188 CHD cases and 188 age- and sex-matched controls who were participants in the Framingham Heart Study. Approach and results A total of 35 genes were differentially expressed in CHD cases vs. controls at FDR<0.5 including GZMB, TMEM56 and GUK1. Cluster analysis revealed three gene clusters associated with CHD, two linked to increased erythrocyte production and a third to reduced natural killer (NK) and T cell activity in CHD cases. Exon-level results corroborated and extended the gene-level results. Alternative splicing analysis suggested that GUK1 and 38 other genes were differentially spliced in CHD cases vs. controls. Gene ontology analysis linked ubiquitination and T-cell-related pathways with CHD. Conclusion Two bioinformatically defined groups of genes show consistent associations with CHD. Our findings are consistent with the hypotheses that hematopoesis is up-regulated in CHD, possibly reflecting a compensatory mechanism, and that innate immune activity is disrupted in CHD or altered by its treatment. Transcriptomic signatures may be useful in identifying pathways associated with CHD and point toward novel therapeutic targets for its treatment and prevention. PMID:23539218

  18. Identifying multiple causative genes at a single GWAS locus.

    PubMed

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

    2013-12-01

    Genome-wide association studies (GWAS) are useful for nominating candidate genes, but typically are unable to establish disease causality or differentiate between the effects of variants in linkage disequilibrium (LD). Additionally, some GWAS loci might contain multiple causative variants or genes that contribute to the overall disease susceptibility at a single locus. However, the majority of current GWAS lack the statistical power to test whether multiple causative genes underlie the same locus, prompting us to adopt an alternative approach to testing multiple GWAS genes empirically. We used gene targeting in a disease-susceptible rat model of genetic hypertension to test all six genes at the Agtrap-Plod1 locus (Agtrap, Mthfr, Clcn6, Nppa, Nppb, and Plod1) for blood pressure (BP) and renal phenotypes. This revealed that the majority of genes at this locus (five out of six) can impact hypertension by modifying BP and renal phenotypes. Mutations of Nppa, Plod1, and Mthfr increased disease susceptibility, whereas Agtrap and Clcn6 mutations decreased hypertension risk. Reanalysis of the human AGTRAP-PLOD1 locus also implied that disease-associated haplotype blocks with polygenic effects were not only possible, but rather were highly plausible. Combined, these data demonstrate for the first time that multiple modifiers of hypertension can cosegregate at a single GWAS locus. PMID:24006081

  19. A predictive approach to identify genes differentially expressed

    NASA Astrophysics Data System (ADS)

    Saraiva, Erlandson F.; Louzada, Francisco; Milan, Lus A.; Meira, Silvana; Cobre, Juliana

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria.

  20. Blood pressure loci identified with a gene-centric array.

    PubMed

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

    2011-12-01

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

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

    PubMed Central

    Johnson, Toby; Gaunt, TomR.; Newhouse, StephenJ.; Padmanabhan, Sandosh; Tomaszewski, Maciej; Kumari, Meena; Morris, RichardW.; Tzoulaki, Ioanna; O'Brien, EoinT.; Poulter, NeilR.; Sever, Peter; Shields, DenisC.; Thom, Simon; Wannamethee, SasiwarangG.; Whincup, PeterH.; Brown, MorrisJ.; Connell, JohnM.; Dobson, RichardJ.; Howard, PhilipJ.; Mein, CharlesA.; Onipinla, Abiodun; Shaw-Hawkins, Sue; Zhang, Yun; Smith, GeorgeDavey; Day, IanN.M.; Lawlor, DebbieA.; Goodall, AlisonH.; Fowkes, F.Gerald; Abecasis, GonaloR.; Elliott, Paul; Gateva, Vesela; Braund, PeterS.; Burton, PaulR.; Nelson, ChristopherP.; Tobin, MartinD.; vanderHarst, Pim; Glorioso, Nicola; Neuvrith, Hani; Salvi, Erika; Staessen, JanA.; Stucchi, Andrea; Devos, Nabila; Jeunemaitre, Xavier; Plouin, Pierre-Franois; Tichet, Jean; Juhanson, Peeter; Org, Elin; Putku, Margus; Sber, Siim; Veldre, Gudrun; Viigimaa, Margus; Levinsson, Anna; Rosengren, Annika; Thelle, DagS.; Hastie, ClaireE.; Hedner, Thomas; Lee, WaiK.; Melander, Olle; Wahlstrand, Bjrn; Hardy, Rebecca; Wong, Andrew; Cooper, JackieA.; Palmen, Jutta; Chen, Li; Stewart, AlexandreF.R.; Wells, GeorgeA.; Westra, Harm-Jan; Wolfs, MarcelG.M.; Clarke, Robert; Franzosi, MariaGrazia; Goel, Anuj; Hamsten, Anders; Lathrop, Mark; Peden, JohnF.; Seedorf, Udo; Watkins, Hugh; Ouwehand, WillemH.; Sambrook, Jennifer; Stephens, Jonathan; Casas, Juan-Pablo; Drenos, Fotios; Holmes, MichaelV.; Kivimaki, Mika; Shah, Sonia; Shah, Tina; Talmud, PhilippaJ.; Whittaker, John; Wallace, Chris; Delles, Christian; Laan, Maris; Kuh, Diana; Humphries, SteveE.; Nyberg, Fredrik; Cusi, Daniele; Roberts, Robert; Newton-Cheh, Christopher; Franke, Lude; Stanton, AliceV.; Dominiczak, AnnaF.; Farrall, Martin; Hingorani, AroonD.; Samani, NileshJ.; Caulfield, MarkJ.; Munroe, PatriciaB.

    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

  2. Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

  3. Proteomics Approach to Identify Biomarkers in Neurodegenerative Diseases.

    PubMed

    Nayak, Annapurna; Salt, Gregory; Verma, Sunil K; Kishore, Uday

    2015-01-01

    This chapter examines the use of proteomics in understanding pathogenesis and identifying possible biomarkers in a range of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, and prion diseases. We have attempted to look at the neuroproteomic approach from a biomarker discovery point of view. Novel biomarkers can pave the way for new therapeutic targets and lead us to a better understanding of the pathogenesis involved in the neurodegenerative diseases. PMID:26315762

  4. Huntington's disease biomarker progression profile identified by transcriptome sequencing in peripheral blood

    PubMed Central

    Mastrokolias, Anastasios; Ariyurek, Yavuz; Goeman, Jelle J; van Duijn, Erik; Roos, Raymund AC; van der Mast, Roos C; van Ommen, GertJan B; den Dunnen, Johan T; 't Hoen, Peter AC; van Roon-Mom, Willeke MC

    2015-01-01

    With several therapeutic approaches in development for Huntington's disease, there is a need for easily accessible biomarkers to monitor disease progression and therapy response. We performed next-generation sequencing-based transcriptome analysis of total RNA from peripheral blood of 91 mutation carriers (27 presymptomatic and, 64 symptomatic) and 33 controls. Transcriptome analysis by DeepSAGE identified 167 genes significantly associated with clinical total motor score in Huntington's disease patients. Relative to previous studies, this yielded novel genes and confirmed previously identified genes, such as H2AFY, an overlap in results that has proven difficult in the past. Pathway analysis showed enrichment of genes of the immune system and target genes of miRNAs, which are downregulated in Huntington's disease models. Using a highly parallelized microfluidics array chip (Fluidigm), we validated 12 of the top 20 significant genes in our discovery cohort and 7 in a second independent cohort. The five genes (PROK2, ZNF238, AQP9, CYSTM1 and ANXA3) that were validated independently in both cohorts present a candidate biomarker panel for stage determination and therapeutic readout in Huntington's disease. Finally we suggest a first empiric formula predicting total motor score from the expression levels of our biomarker panel. Our data support the view that peripheral blood is a useful source to identify biomarkers for Huntington's disease and monitor disease progression in future clinical trials. PMID:25626709

  5. Huntington's disease biomarker progression profile identified by transcriptome sequencing in peripheral blood.

    PubMed

    Mastrokolias, Anastasios; Ariyurek, Yavuz; Goeman, Jelle J; van Duijn, Erik; Roos, Raymund A C; van der Mast, Roos C; van Ommen, GertJan B; den Dunnen, Johan T; 't Hoen, Peter A C; van Roon-Mom, Willeke M C

    2015-10-01

    With several therapeutic approaches in development for Huntington's disease, there is a need for easily accessible biomarkers to monitor disease progression and therapy response. We performed next-generation sequencing-based transcriptome analysis of total RNA from peripheral blood of 91 mutation carriers (27 presymptomatic and, 64 symptomatic) and 33 controls. Transcriptome analysis by DeepSAGE identified 167 genes significantly associated with clinical total motor score in Huntington's disease patients. Relative to previous studies, this yielded novel genes and confirmed previously identified genes, such as H2AFY, an overlap in results that has proven difficult in the past. Pathway analysis showed enrichment of genes of the immune system and target genes of miRNAs, which are downregulated in Huntington's disease models. Using a highly parallelized microfluidics array chip (Fluidigm), we validated 12 of the top 20 significant genes in our discovery cohort and 7 in a second independent cohort. The five genes (PROK2, ZNF238, AQP9, CYSTM1 and ANXA3) that were validated independently in both cohorts present a candidate biomarker panel for stage determination and therapeutic readout in Huntington's disease. Finally we suggest a first empiric formula predicting total motor score from the expression levels of our biomarker panel. Our data support the view that peripheral blood is a useful source to identify biomarkers for Huntington's disease and monitor disease progression in future clinical trials. PMID:25626709

  6. 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

  7. Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

    PubMed

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

    2015-02-01

    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

  8. 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

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

    PubMed

    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

  10. Early Warning Sign for Kidney Disease Identified in Study

    MedlinePLUS

    ... news/fullstory_155546.html Early Warning Sign for Kidney Disease Identified in Study Researchers say blood test ... ve discovered an early warning sign of chronic kidney disease. They found that levels of a common ...

  11. Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network

    PubMed Central

    Wang, Baoman; Yuan, Fei; Kong, Xiangyin; Hu, Lan-Dian; Cai, Yu-Dong

    2015-01-01

    Apoptosis is the process of programmed cell death (PCD) that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature. PMID:26543496

  12. 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.

  13. 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...

  14. A gene recommender algorithm to identify coexpressed genes in C. elegans.

    PubMed

    Owen, Art B; Stuart, Josh; Mach, Kathy; Villeneuve, Anne M; Kim, Stuart

    2003-08-01

    One of the most important uses of whole-genome expression data is for the discovery of new genes with similar function to a given list of genes (the query) already known to have closely related function. We have developed an algorithm, called the gene recommender, that ranks genes according to how strongly they correlate with a set of query genes in those experiments for which the query genes are most strongly coregulated. We used the gene recommender to find other genes coexpressed with several sets of query genes, including genes known to function in the retinoblastoma complex. Genetic experiments confirmed that one gene (JC8.6) identified by the gene recommender acts with lin-35 Rb to regulate vulval cell fates, and that another gene (wrm-1) acts antagonistically. We find that the gene recommender returns lists of genes with better precision, for fixed levels of recall, than lists generated using the C. elegans expression topomap. PMID:12902378

  15. Can We Identify Genes with Increased Phylogenetic Reliability?

    PubMed

    Doyle, Vinson P; Young, Randee E; Naylor, Gavin J P; Brown, Jeremy M

    2015-09-01

    Topological heterogeneity among gene trees is widely observed in phylogenomic analyses and some of this variation is likely caused by systematic error in gene tree estimation. Systematic error can be mitigated by improving models of sequence evolution to account for all evolutionary processes relevant to each gene or identifying those genes whose evolution best conforms to existing models. However, the best method for identifying such genes is not well established. Here, we ask if filtering genes according to their clock-likeness or posterior predictive effect size (PPES, an inference-based measure of model violation) improves phylogenetic reliability and congruence. We compared these approaches to each other, and to the common practice of filtering based on rate of evolution, using two different metrics. First, we compared gene-tree topologies to accepted reference topologies. Second, we examined topological similarity among gene trees in filtered sets. Our results suggest that filtering genes based on clock-likeness and PPES can yield a collection of genes with more reliable phylogenetic signal. For the two exemplar data sets we explored, from yeast and amniotes, clock-likeness and PPES outperformed rate-based filtering in both congruence and reliability. PMID:26099258

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

    DOE PAGESBeta

    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

  17. Genetic risk factors for the development of allergic disease identified by genome-wide association

    PubMed Central

    Portelli, M A; Hodge, E; Sayers, I

    2015-01-01

    An increasing proportion of the worldwide population is affected by allergic diseases such as allergic rhinitis (AR), atopic dermatitis (AD) and allergic asthma and improved treatment options are needed particularly for severe, refractory disease. Allergic diseases are complex and development involves both environmental and genetic factors. Although the existence of a genetic component for allergy was first described almost 100years ago, progress in gene identification has been hindered by lack of high throughput technologies to investigate genetic variation in large numbers of subjects. The development of Genome-Wide Association Studies (GWAS), a hypothesis-free method of interrogating large numbers of common variants spanning the entire genome in disease and non-disease subjects has revolutionised our understanding of the genetics of allergic disease. Susceptibility genes for asthma, AR and AD have now been identified with confidence, suggesting there are common and distinct genetic loci associated with these diseases, providing novel insights into potential disease pathways and mechanisms. Genes involved in both adaptive and innate immune mechanisms have been identified, notably including multiple genes involved in epithelial function/secretion, suggesting that the airway epithelium may be particularly important in asthma. Interestingly, concordance/discordance between the genetic factors driving allergic traits such as IgE levels and disease states such as asthma have further supported the accumulating evidence for heterogeneity in these diseases. While GWAS have been useful and continue to identify novel genes for allergic diseases through increased sample sizes and phenotype refinement, future approaches will integrate analyses of rare variants, epigenetic mechanisms and eQTL approaches, leading to greater insight into the genetic basis of these diseases. Gene identification will improve our understanding of disease mechanisms and generate potential therapeutic opportunities. PMID:24766371

  18. Gene therapy of benign gynecological diseases?

    PubMed Central

    Hassan, Memy H.; Othman, Essam E.; Hornung, Daniela; Al-Hendy, Ayman

    2015-01-01

    Gene therapy is the introduction of genetic material into patients cells to achieve therapeutic benefit. Advances in molecular biology techniques and better understanding of disease pathogenesis have validated the use of a variety of genes as potential molecular targets for gene therapy based approaches. Gene therapy strategies include: mutation compensation of dysregulated genes; replacement of defective tumor-suppressor genes; inactivation of oncogenes; introduction of suicide genes; immunogenic therapy and antiangiogenesis based approaches. Preclinical studies of gene therapy for various gynecological disorders have not only shown to be feasible, but also showed promising results in diseases such as uterine leiomyomas and endometriosis. In recent years, significant improvement in gene transfer technology has led to the development of targetable vectors, which have fewer side-effects without compromising their efficacy. This review provides an update on developing gene therapy approaches to treat common gynecological diseases such as uterine leiomyoma and endometriosis. PMID:19446586

  19. The study of psychiatric disease genes and drugs in zebrafish

    PubMed Central

    Haesemeyer, Martin; Schier, Alexander F.

    2014-01-01

    Mutations associated with psychiatric disease are being identified, but it remains unclear how the affected genes contribute to disease. Zebrafish is an emerging model to study psychiatric disease genes with a rich repertoire of phenotyping tools. Recent zebrafish research has uncovered potential developmental phenotypes for genes associated with psychiatric disorders, while drug screens have behaviorally characterized small molecules and identified new classes of drugs. Behavioral studies have led to promising models for endophenotypes of psychiatric diseases. While further research is needed to firmly link these models to psychiatric disorders, they are valuable tools for phenotyping genetic mutations and drugs. Recently developed tools in genome editing and in vivo imaging promise additional insights into the processes disrupted by mutations in psychiatric disease genes. PMID:25523356

  20. 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

  1. 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

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

    PubMed

    Li, Wentian; Espinal-Enrquez, Jess; Simpfendorfer, Kim R; Hernndez-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. PMID:26411796

  3. Deletions of recessive disease genes: CNV contribution to carrier states and disease-causing alleles

    PubMed Central

    Boone, Philip M.; Campbell, Ian M.; Baggett, Brett C.; Soens, Zachry T.; Rao, Mitchell M.; Hixson, Patricia M.; Patel, Ankita; Bi, Weimin; Cheung, Sau Wai; Lalani, Seema R.; Beaudet, Arthur L.; Stankiewicz, Pawel; Shaw, Chad A.; Lupski, James R.

    2013-01-01

    Over 1200 recessive disease genes have been described in humans. The prevalence, allelic architecture, and per-genome load of pathogenic alleles in these genes remain to be fully elucidated, as does the contribution of DNA copy-number variants (CNVs) to carrier status and recessive disease. We mined CNV data from 21,470 individuals obtained by array-comparative genomic hybridization in a clinical diagnostic setting to identify deletions encompassing or disrupting recessive disease genes. We identified 3212 heterozygous potential carrier deletions affecting 419 unique recessive disease genes. Deletion frequency of these genes ranged from one occurrence to 1.5%. When compared with recessive disease genes never deleted in our cohort, the 419 recessive disease genes affected by at least one carrier deletion were longer and located farther from known dominant disease genes, suggesting that the formation and/or prevalence of carrier CNVs may be affected by both local and adjacent genomic features and by selection. Some subjects had multiple carrier CNVs (307 subjects) and/or carrier deletions encompassing more than one recessive disease gene (206 deletions). Heterozygous deletions spanning multiple recessive disease genes may confer carrier status for multiple single-gene disorders, for complex syndromes resulting from the combination of two or more recessive conditions, or may potentially cause clinical phenotypes due to a multiply heterozygous state. In addition to carrier mutations, we identified homozygous and hemizygous deletions potentially causative for recessive disease. We provide further evidence that CNVs contribute to the allelic architecture of both carrier and recessive disease-causing mutations. Thus, a complete recessive carrier screening method or diagnostic test should detect CNV alleles. PMID:23685542

  4. 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 characteristicstermed 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?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

  5. 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

  6. 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

  7. Using next-generation RNA sequencing to identify imprinted genes

    PubMed Central

    Wang, X; Clark, A G

    2014-01-01

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

  8. Immunogenetic Mechanisms Leading to Thyroid Autoimmunity: Recent Advances in Identifying Susceptibility Genes and Regions

    PubMed Central

    Brand, Oliver J; Gough, Stephen C.L

    2011-01-01

    The autoimmune thyroid diseases (AITD) include Graves disease (GD) and Hashimotos 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. PMID:22654554

  9. 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. PMID:22654554

  10. Integrating Autoimmune Risk Loci with Gene-Expression Data Identifies Specific Pathogenic Immune Cell Subsets

    PubMed Central

    Hu, Xinli; Kim, Hyun; Stahl, Eli; Plenge, Robert; Daly, Mark; Raychaudhuri, Soumya

    2011-01-01

    Although genome-wide association studies have implicated many individual loci in complex diseases, identifying the exact causal alleles and the cell types within which they act remains greatly challenging. To ultimately understand disease mechanism, researchers mustcarefully conceive functional studies in relevant pathogenic cell types to demonstrate the cellular impact of disease-associated genetic variants. This challenge is highlighted in autoimmune diseases, such as rheumatoid arthritis, where any of a broad range of immunological cell types might potentially be impacted by genetic variation to cause disease. To this end, we developed a statistical approach to identify potentially pathogenic cell types in autoimmune diseases by using a gene-expression data set of 223 murine-sorted immune cells from the Immunological Genome Consortium. We found enrichment of transitional B cell genes in systemic lupus erythematosus (p = 5.9 10?6) and epithelial-associated stimulated dendritic cell genes in Crohn disease (p = 1.6 10?5). Finally, we demonstrated enrichment of CD4+ effector memory Tcell genes within rheumatoid arthritis loci (p < 10?6). To further validate the role of CD4+ effector memory Tcells within rheumatoid arthritis, we identified 436 loci that were not yet known to be associated with the disease but that had a statistically suggestive association in a recent genome-wide association study (GWAS) meta-analysis (pGWAS < 0.001). Even among these putative loci, we noted a significant enrichment for genes specifically expressed in CD4+ effector memory Tcells (p = 1.25 10?4). These cell types are primary candidates for future functional studies to reveal the role of risk alleles in autoimmunity. Our approach has application in other phenotypes, outside of autoimmunity, where many loci have been discovered and high-quality cell-type-specific gene expression is available. PMID:21963258

  11. Candidate DNA repair susceptibility genes identified by exome sequencing in high-risk pancreatic cancer.

    PubMed

    Smith, Alyssa L; Alirezaie, Najmeh; Connor, Ashton; Chan-Seng-Yue, Michelle; Grant, Robert; Selander, Iris; Bascuñana, Claire; Borgida, Ayelet; Hall, Anita; Whelan, Thomas; Holter, Spring; McPherson, Treasa; Cleary, Sean; Petersen, Gloria M; Omeroglu, Atilla; Saloustros, Emmanouil; McPherson, John; Stein, Lincoln D; Foulkes, William D; Majewski, Jacek; Gallinger, Steven; Zogopoulos, George

    2016-01-28

    The genetic basis underlying the majority of hereditary pancreatic adenocarcinoma (PC) is unknown. Since DNA repair genes are widely implicated in gastrointestinal malignancies, including PC, we hypothesized that there are novel DNA repair PC susceptibility genes. As germline DNA repair gene mutations may lead to PC subtypes with selective therapeutic responses, we also hypothesized that there is an overall survival (OS) difference in mutation carriers versus non-carriers. We therefore interrogated the germline exomes of 109 high-risk PC cases for rare protein-truncating variants (PTVs) in 513 putative DNA repair genes. We identified PTVs in 41 novel genes among 36 kindred. Additional genetic evidence for causality was obtained for 17 genes, with FAN1, NEK1 and RHNO1 emerging as the strongest candidates. An OS difference was observed for carriers versus non-carriers of PTVs with early stage (≤IIB) disease. This adverse survival trend in carriers with early stage disease was also observed in an independent series of 130 PC cases. We identified candidate DNA repair PC susceptibility genes and suggest that carriers of a germline PTV in a DNA repair gene with early stage disease have worse survival. PMID:26546047

  12. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

    PubMed Central

    Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

    2015-01-01

    The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures. PMID:26199946

  13. CNL Disease Resistance Genes in Soybean and Their Evolutionary Divergence

    PubMed Central

    Nepal, Madhav P; Benson, Benjamin V

    2015-01-01

    Disease resistance genes (R-genes) encode proteins involved in detecting pathogen attack and activating downstream defense molecules. Recent availability of soybean genome sequences makes it possible to examine the diversity of gene families including disease-resistant genes. The objectives of this study were to identify coiled-coil NBS-LRR (= CNL) R-genes in soybean, infer their evolutionary relationships, and assess structural as well as functional divergence of the R-genes. Profile hidden Markov models were used for sequence identification and model-based maximum likelihood was used for phylogenetic analysis, and variation in chromosomal positioning, gene clustering, and functional divergence were assessed. We identified 188 soybean CNL genes nested into four clades consistent to their orthologs in Arabidopsis. Gene clustering analysis revealed the presence of 41 gene clusters located on 13 different chromosomes. Analyses of the Ks-values and chromosomal positioning suggest duplication events occurring at varying timescales, and an extrapericentromeric positioning may have facilitated their rapid evolution. Each of the four CNL clades exhibited distinct patterns of gene expression. Phylogenetic analysis further supported the extrapericentromeric positioning effect on the divergence and retention of the CNL genes. The results are important for understanding the diversity and divergence of CNL genes in soybean, which would have implication in soybean crop improvement in future. PMID:25922568

  14. Finding Genetic Overlaps Among Diseases Based on Ranked Gene Lists

    PubMed Central

    Chen, Quan; Zhou, Xianghong J.

    2015-01-01

    Abstract To understand disease relationships in terms of their genetic mechanisms, it is important to study the common genetic basis among different diseases. Although discoveries on pleiotropic genes related to multiple diseases abound, methods flexibly applicable to various types of datasets generated from different studies or experiments are needed to gain big pictures on the genetic relationships among a large number of diseases. We develop a set of genetic similarity measures to gauge the genetic overlap between diseases, as well as several estimators of the number of overlapping disease genes between diseases. These methods are based on ranked gene lists so that they could be flexibly applied to different types of data. We first investigate the performance of the genetic similarity measure for evaluating the similarity between human diseases in simulation studies. Then we apply the method to diseases in the OMIM database. We show that our proposed genetic measure achieves superior performance in explaining phenotype similarities between diseases compared to simpler methods. Furthermore, we identified common genes underlying the genetic overlap between disease pairs. With an example of five vision-related diseases, we demonstrate how our methods can provide insights into the relationships among diseases based on their shared genetic mechanisms. PMID:25684200

  15. The impact of sample imbalance on identifying differentially expressed genes

    PubMed Central

    Yang, Kun; Li, Jianzhong; Gao, Hong

    2006-01-01

    Background Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the problem of sample imbalance and there is no study to investigate the impact of sample imbalance on identifying differential expression genes. In addition, it is not clear which method is more suitable for the unbalanced data. Results Based on random sampling, two evaluation models are proposed to investigate the impact of sample imbalance on identifying differential expression genes. Using the proposed evaluation models, the performances of six famous methods are compared on the unbalanced data. The experimental results indicate that the sample imbalance has a great influence on selecting differential expression genes. Furthermore, different methods have very different performances on the unbalanced data. Among the six methods, the welch t-test appears to perform best when the size of samples in the large variance group is larger than that in the small one, while the Regularized t-test and SAM outperform others on the unbalanced data in other cases. Conclusion Two proposed evaluation models are effective and sample imbalance should be taken into account in microarray experiment design and gene expression data analysis. The results and two proposed evaluation models can provide some help in selecting suitable method to process the unbalanced data. PMID:17217526

  16. Integrative genomics identifies APOE ε4 effectors in Alzheimer's disease.

    PubMed

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

    2013-08-01

    Late-onset Alzheimer's disease (LOAD) risk is strongly influenced by genetic factors such as the presence of the apolipoprotein E ε4 allele (referred to here as APOE4), as well as non-genetic determinants including ageing. To pursue mechanisms by which these affect human brain physiology and modify LOAD risk, we initially analysed whole-transcriptome cerebral cortex gene expression data in unaffected APOE4 carriers and LOAD patients. APOE4 carrier status was associated with a consistent transcriptomic shift that broadly resembled the LOAD profile. Differential co-expression correlation network analysis of the APOE4 and LOAD transcriptomic changes identified a set of candidate core regulatory mediators. Several of these--including APBA2, FYN, RNF219 and SV2A--encode known or novel modulators of LOAD associated amyloid beta A4 precursor protein (APP) endocytosis and metabolism. Furthermore, a genetic variant within RNF219 was found to affect amyloid deposition in human brain and LOAD age-of-onset. These data implicate an APOE4 associated molecular pathway that promotes LOAD. PMID:23883936

  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 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...

  19. Quantifying cellular capacity identifies gene expression designs with reduced burden.

    PubMed

    Ceroni, Francesca; Algar, Rhys; Stan, Guy-Bart; Ellis, Tom

    2015-05-01

    Heterologous gene expression can be a significant burden for cells. Here we describe an in vivo monitor that tracks changes in the capacity of Escherichia coli in real time and can be used to assay the burden imposed by synthetic constructs and their parts. We identify construct designs with reduced burden that predictably outperformed less efficient designs, despite having equivalent output. PMID:25849635

  20. Identifying candidate genes for blood pressure quantitative trait loci using differential gene expression and a panel of congenic strains.

    PubMed

    Cicila, G T; Lee, S J

    1998-12-01

    The most difficult step in dissecting the molecular basis of a quantitative trait is proceeding from chromosomal locations associated with this trait (i.e., quantitative trait locus, QTL) to determining what gene(s) in the QTL region is causative. Using standard positional cloning methodology to identify candidate genes for a particular QTL has three drawbacks: 1) it is labor intensive; 2) defining variants in genes causing quantitative variation from sequence information alone is difficult or impossible; and 3) many (or most) genes in a particular chromosomal interval will not be relevant for a specific disease/trait because they are not expressed in critical candidate organs. Instead of positional cloning, we propose using a panel of congenic strains, where each carries an allele for a different QTL on a similar genetic background, in conjunction with identification of differentially-expressed genes in target organs of inbred strains of contrasting phenotype. This will identify genes having altered expression in organs critical to regulating blood pressure and the development of hypertension. Radiation hybrid mapping of such genes will result in a transcription map of differentially-expressed genes in a target organ of a rat model of genetic hypertension. This approach could rapidly identify genes mapping to genomic regions near QTL, which will be strong candidates to explain, in part, the observed strain differences in blood pressure. This novel approach, which uses a panel of congenic strains to facilitate the mapping and subsequent identification of differentially-expressed and QTL-associated genes, should be applicable to any genetic model for identifying candidate genes located near QTL, given the availability of a panel of congenic strains. PMID:9877523

  1. Identifying lipid metabolism genes in pig liver after clenbuterol administration.

    PubMed

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

    2012-01-01

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

  2. Adipose Co-expression networks across Finns and Mexicans identify novel triglyceride-associated genes

    PubMed Central

    2012-01-01

    Background High serum triglyceride (TG) levels is an established risk factor for coronary heart disease (CHD). Fat is stored in the form of TGs in human adipose tissue. We hypothesized that gene co-expression networks in human adipose tissue may be correlated with serum TG levels and help reveal novel genes involved in TG regulation. Methods Gene co-expression networks were constructed from two Finnish and one Mexican study sample using the blockwiseModules R function in Weighted Gene Co-expression Network Analysis (WGCNA). Overlap between TG-associated networks from each of the three study samples were calculated using a Fishers Exact test. Gene ontology was used to determine known pathways enriched in each TG-associated network. Results We measured gene expression in adipose samples from two Finnish and one Mexican study sample. In each study sample, we observed a gene co-expression network that was significantly associated with serum TG levels. The TG modules observed in Finns and Mexicans significantly overlapped and shared 34 genes. Seven of the 34 genes (ARHGAP30, CCR1, CXCL16, FERMT3, HCST, RNASET2, SELPG) were identified as the key hub genes of all three TG modules. Furthermore, two of the 34 genes (ARHGAP9, LST1) reside in previous TG GWAS regions, suggesting them as the regional candidates underlying the GWAS signals. Conclusions This study presents a novel adipose gene co-expression network with 34 genes significantly correlated with serum TG across populations. PMID:23217153

  3. A systematic screening to identify de novo mutations causing sporadic early-onset Parkinson's disease.

    PubMed

    Kun-Rodrigues, Celia; Ganos, Christos; Guerreiro, Rita; Schneider, Susanne A; Schulte, Claudia; Lesage, Suzanne; Darwent, Lee; Holmans, Peter; Singleton, Andrew; Bhatia, Kailash; Bras, Jose

    2015-12-01

    Despite the many advances in our understanding of the genetic basis of Mendelian forms of Parkinson's disease (PD), a large number of early-onset cases still remain to be explained. Many of these cases, present with a form of disease that is identical to that underlined by genetic causes, but do not have mutations in any of the currently known disease-causing genes. Here, we hypothesized that de novo mutations may account for a proportion of these early-onset, sporadic cases. We performed exome sequencing in full parent-child trios where the proband presents with typical PD to unequivocally identify de novo mutations. This approach allows us to test all genes in the genome in an unbiased manner. We have identified and confirmed 20 coding de novo mutations in 21 trios. We have used publicly available population genetic data to compare variant frequencies and our independent in-house dataset of exome sequencing in PD (with over 1200 cases) to identify additional variants in the same genes. Of the genes identified to carry de novo mutations, PTEN, VAPB and ASNA1 are supported by various sources of data to be involved in PD. We show that these genes are reported to be within a protein-protein interaction network with PD genes and that they contain additional rare, case-specific, mutations in our independent cohort of PD cases. Our results support the involvement of these three genes in PD and suggest that testing for de novo mutations in sporadic disease may aid in the identification of novel disease-causing genes. PMID:26362251

  4. A systematic screening to identify de novo mutations causing sporadic early-onset Parkinson's disease

    PubMed Central

    Kun-Rodrigues, Celia; Ganos, Christos; Guerreiro, Rita; Schneider, Susanne A.; Schulte, Claudia; Lesage, Suzanne; Darwent, Lee; Holmans, Peter; Singleton, Andrew; Bhatia, Kailash; Bras, Jose

    2015-01-01

    Despite the many advances in our understanding of the genetic basis of Mendelian forms of Parkinson's disease (PD), a large number of early-onset cases still remain to be explained. Many of these cases, present with a form of disease that is identical to that underlined by genetic causes, but do not have mutations in any of the currently known disease-causing genes. Here, we hypothesized that de novo mutations may account for a proportion of these early-onset, sporadic cases. We performed exome sequencing in full parent–child trios where the proband presents with typical PD to unequivocally identify de novo mutations. This approach allows us to test all genes in the genome in an unbiased manner. We have identified and confirmed 20 coding de novo mutations in 21 trios. We have used publicly available population genetic data to compare variant frequencies and our independent in-house dataset of exome sequencing in PD (with over 1200 cases) to identify additional variants in the same genes. Of the genes identified to carry de novo mutations, PTEN, VAPB and ASNA1 are supported by various sources of data to be involved in PD. We show that these genes are reported to be within a protein–protein interaction network with PD genes and that they contain additional rare, case-specific, mutations in our independent cohort of PD cases. Our results support the involvement of these three genes in PD and suggest that testing for de novo mutations in sporadic disease may aid in the identification of novel disease-causing genes. PMID:26362251

  5. An in vivo screen to identify candidate neurogenic genes in the developing Xenopus visual system.

    PubMed

    Bestman, Jennifer E; Huang, Lin-Chien; Lee-Osbourne, Jane; Cheung, Phillip; Cline, Hollis T

    2015-12-15

    Neurogenesis in the brain of Xenopus laevis continues throughout larval stages of development. We developed a 2-tier screen to identify candidate genes controlling neurogenesis in Xenopus optic tectum in vivo. First, microarray and NanoString analyses were used to identify candidate genes that were differentially expressed in Sox2-expressing neural progenitor cells or their neuronal progeny. Then an in vivo, time-lapse imaging-based screen was used to test whether morpholinos against 34 candidate genes altered neural progenitor cell proliferation or neuronal differentiation over 3 days in the optic tectum of intact Xenopus tadpoles. We co-electroporated antisense morpholino oligonucleotides against each of the candidate genes with a plasmid that drives GFP expression in Sox2-expressing neural progenitor cells and quantified the effects of morpholinos on neurogenesis. Of the 34 morpholinos tested, 24 altered neural progenitor cell proliferation or neuronal differentiation. The candidates which were tagged as differentially expressed and validated by the in vivo imaging screen include: actn1, arl9, eif3a, elk4, ephb1, fmr1-a, fxr1-1, fbxw7, fgf2, gstp1, hat1, hspa5, lsm6, mecp2, mmp9, and prkaca. Several of these candidates, including fgf2 and elk4, have known or proposed neurogenic functions, thereby validating our strategy to identify candidates. Genes with no previously demonstrated neurogenic functions, gstp1, hspa5 and lsm6, were identified from the morpholino experiments, suggesting that our screen successfully revealed unknown candidates. Genes that are associated with human disease, such as such as mecp2 and fmr1-a, were identified by our screen, providing the groundwork for using Xenopus as an experimental system to probe conserved disease mechanisms. Together the data identify candidate neurogenic regulatory genes and demonstrate that Xenopus is an effective experimental animal to identify and characterize genes that regulate neural progenitor cell proliferation and differentiation in vivo. PMID:25818835

  6. Recent gene therapy advancements for neurological diseases.

    PubMed

    Nagabhushan Kalburgi, Sahana; Khan, Nadia N; Gray, Steven J

    2013-02-01

    The past few years have seen rapid advancements in vector-mediated gene transfer to the nervous system and modest successes in human gene therapy trials. The purpose of this review is to describe commonly-used viral gene transfer vectors and recent advancements towards producing meaningful gene-based treatments for central nervous system (CNS) disorders. Gene therapy trials for Canavan disease, Batten disease, adrenoleukodystrophy, and Parkinson's disease are discussed to illustrate the current state of clinical gene transfer to the CNS. Preclinical studies are under way for a number of diseases, primarily lysosomal storage disorders, using a newer generation of vectors and delivery strategies. Relevant studies in animal models are highlighted for Mucopolysaccharidosis IIIB and Krabbe disease to provide a prelude for what can be expected in the coming years for human gene transfer trials, using recent advancements in gene transfer technology. In conclusion, recent improvements in CNS gene transfer technology are expected to significantly increase the degree of disease rescue in future CNS-directed clinical trials, exceeding the modest clinical successes that have been observed so far. PMID:23449113

  7. 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-? 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

  8. Systematic Analysis of New Drug Indications by Drug-Gene-Disease Coherent Subnetworks

    PubMed Central

    Wang, L; Wang, Y; Hu, Q; Li, S

    2014-01-01

    Drug targets and disease genes may work as driver factors at the transcriptional level, which propagate signals through gene regulatory network and cause the downstream genes' differential expression. How to analyze transcriptional response data to identify meaningful gene modules shared by both drugs and diseases is still a critical issue for drug-disease associations and molecular mechanism. In this article, we propose the drug-gene-disease coherent subnetwork concept to group the biological function related drugs, diseases, and genes. It was defined as the subnetwork with drug, gene, and disease as nodes and their interactions coherently crossing three data layers as edges. Integrating differential expression profiles of 418 drugs and 84 diseases, we develop a computational framework and identify 13 coherent subnetworks such as inflammatory bowel disease and melanoma relevant subnetwork. The results demonstrate that our coherent subnetwork approach is able to identify novel drug indications and highlight their molecular basis. PMID:25390685

  9. Homophila: human disease gene cognates in Drosophila.

    PubMed

    Chien, Samson; Reiter, Lawrence T; Bier, Ethan; Gribskov, Michael

    2002-01-01

    Although many human genes have been associated with genetic diseases, knowing which mutations result in disease phenotypes often does not explain the etiology of a specific disease. Drosophila melanogaster provides a powerful system in which to use genetic and molecular approaches to investigate human genetic diseases. Homophila is an intergenomic resource linking the human and fly genomes in order to stimulate functional genomic investigations in Drosophila that address questions about genetic disease in humans. Homophila provides a comprehensive linkage between the disease genes compiled in Online Mendelian Inheritance in Man (OMIM) and the complete Drosophila genomic sequence. Homophila is a relational database that allows searching based on human disease descriptions, OMIM number, human or fly gene names, and sequence similarity, and can be accessed at http://homophila.sdsc.edu. PMID:11752278

  10. 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

  11. 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.

  12. 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?=?1.310?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?=?1.710?4, 1.810?4, and 2.210?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

  13. 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

  14. 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

  15. An Effective Method to Identify Shared Pathways and Common Factors among Neurodegenerative Diseases

    PubMed Central

    Li, Ping; Nie, Yaling; Yu, Jingkai

    2015-01-01

    Groups of distinct but related diseases often share common symptoms, which suggest likely overlaps in underlying pathogenic mechanisms. Identifying the shared pathways and common factors among those disorders can be expected to deepen our understanding for them and help designing new treatment strategies effected on those diseases. Neurodegeneration diseases, including Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD), were taken as a case study in this research. Reported susceptibility genes for AD, PD and HD were collected and human protein-protein interaction network (hPPIN) was used to identify biological pathways related to neurodegeneration. 81 KEGG pathways were found to be correlated with neurodegenerative disorders. 36 out of the 81 are human disease pathways, and the remaining ones are involved in miscellaneous human functional pathways. Cancers and infectious diseases are two major subclasses within the disease group. Apoptosis is one of the most significant functional pathways. Most of those pathways found here are actually consistent with prior knowledge of neurodegenerative diseases except two cell communication pathways: adherens and tight junctions. Gene expression analysis showed a high probability that the two pathways were related to neurodegenerative diseases. A combination of common susceptibility genes and hPPIN is an effective method to study shared pathways involved in a group of closely related disorders. Common modules, which might play a bridging role in linking neurodegenerative disorders and the enriched pathways, were identified by clustering analysis. The identified shared pathways and common modules can be expected to yield clues for effective target discovery efforts on neurodegeneration. PMID:26575483

  16. Flavobacterium johnsoniae Gliding Motility Genes Identified by mariner Mutagenesis

    PubMed Central

    Braun, Timothy F.; Khubbar, Manjeet K.; Saffarini, Daad A.; McBride, Mark J.

    2005-01-01

    Cells of Flavobacterium johnsoniae glide rapidly over surfaces. The mechanism of F. johnsoniae gliding motility is not known. Eight gld genes required for gliding motility have been described. Disruption of any of these genes results in complete loss of gliding motility, deficiency in chitin utilization, and resistance to bacteriophages that infect wild-type cells. Two modified mariner transposons, HimarEm1 and HimarEm2, were constructed to allow the identification of additional motility genes. HimarEm1 and HimarEm2 each transposed in F. johnsoniae, and nonmotile mutants were identified and analyzed. Four novel motility genes, gldK, gldL, gldM, and gldN, were identified. GldK is similar in sequence to the lipoprotein GldJ, which is required for gliding. GldL, GldM, and GldN are not similar in sequence to proteins of known function. Cells with mutations in gldK, gldL, gldM, and gldN were defective in motility and chitin utilization and were resistant to bacteriophages that infect wild-type cells. Introduction of gldA, gldB, gldD, gldFG, gldH, gldI, and gldJ and the region spanning gldK, gldL, gldM, and gldN individually into 50 spontaneous and chemically induced nonmotile mutants restored motility to each of them, suggesting that few additional F. johnsoniae gld genes remain to be identified. PMID:16199564

  17. 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 are undertaking a complementation strategy to demonstrate the necessity of these novel genes in BCMM as well as characterizing the phenotypes of the mutants. 1. S. B. R. Chang, J. F. Stolz, J. L. Kirschvink, S. M. Awramik, Precambrian Res. 43, 305-315 (1989). 2. K. Grünberg, C. Wawer, B. M. Tebo, D. Schüler, Appl. Environ. Microbiol. 67, 4573-4582 (2001). 3. A. T. Wahyudi, H. Takeyama, T. Matsunaga, Appl. Biochem. Biotechnol. 91-3, 147-154 (2001). 4. T. Matsunaga, C. Nakamura, J. G. Burgess, K. Sode, J. Bacteriol. 174, 2748-2753 (1992).

  18. Analysis of Gene Order Conservation in Eukaryotes Identifies Transcriptionally and Functionally Linked Genes

    PubMed Central

    Dvila Lpez, Marcela; Martnez Guerra, Juan Jos; Samuelsson, Tore

    2010-01-01

    The order of genes in eukaryotes is not entirely random. Studies of gene order conservation are important to understand genome evolution and to reveal mechanisms why certain neighboring genes are more difficult to separate during evolution. Here, genome-wide gene order information was compiled for 64 species, representing a wide variety of eukaryotic phyla. This information is presented in a browser where gene order may be displayed and compared between species. Factors related to non-random gene order in eukaryotes were examined by considering pairs of neighboring genes. The evolutionary conservation of gene pairs was studied with respect to relative transcriptional direction, intergenic distance and functional relationship as inferred by gene ontology. The results show that among gene pairs that are conserved the divergently and co-directionally transcribed genes are much more common than those that are convergently transcribed. Furthermore, highly conserved pairs, in particular those of fungi, are characterized by a short intergenic distance. Finally, gene pairs of metazoa and fungi that are evolutionary conserved and that are divergently transcribed are much more likely to be related by function as compared to poorly conserved gene pairs. One example is the ribosomal protein gene pair L13/S16, which is unusual as it occurs both in fungi and alveolates. A specific functional relationship between these two proteins is also suggested by the fact that they are part of the same operon in both eubacteria and archaea. In conclusion, factors associated with non-random gene order in eukaryotes include relative gene orientation, intergenic distance and functional relationships. It seems likely that certain pairs of genes are conserved because the genes involved have a transcriptional and/or functional relationship. The results also indicate that studies of gene order conservation aid in identifying genes that are related in terms of transcriptional control. PMID:20498846

  19. 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

  20. 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

  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. PMID:25423036

  2. 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

  3. 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

  4. 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.

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

    PubMed

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

    2013-07-11

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

  6. 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

  7. Heterozygous Screen in Saccharomyces cerevisiae Identifies Dosage-Sensitive Genes That Affect Chromosome Stability

    PubMed Central

    Strome, Erin D.; Wu, Xiaowei; Kimmel, Marek; Plon, Sharon E.

    2008-01-01

    Current techniques for identifying mutations that convey a small increased cancer risk or those that modify cancer risk in carriers of highly penetrant mutations are limited by the statistical power of epidemiologic studies, which require screening of large populations and candidate genes. To identify dosage-sensitive genes that mediate genomic stability, we performed a genomewide screen in Saccharomyces cerevisiae for heterozygous mutations that increase chromosome instability in a checkpoint-deficient diploid strain. We used two genome stability assays sensitive enough to detect the impact of heterozygous mutations and identified 172 heterozygous gene disruptions that affected chromosome fragment (CF) loss, 45% of which also conferred modest but statistically significant instability of endogenous chromosomes. Analysis of heterozygous deletion of 65 of these genes demonstrated that the majority increased genomic instability in both checkpoint-deficient and wild-type backgrounds. Strains heterozygous for COMA kinetochore complex genes were particularly unstable. Over 50% of the genes identified in this screen have putative human homologs, including CHEK2, ERCC4, and TOPBP1, which are already associated with inherited cancer susceptibility. These findings encourage the incorporation of this orthologous gene list into cancer epidemiology studies and suggest further analysis of heterozygous phenotypes in yeast as models of human disease resulting from haplo-insufficiency. PMID:18245329

  8. Sheath blight disease screening methods to identify resistant Oryza spp. accessions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Oryza species, wild relatives of cultivated rice (O. sativa), may contain novel resistance genes to sheath blight, caused by Rhizoctonia solani Kühn, that could be used to enhance resistance to this important disease in commercial rice. Suitable greenhouse screening methods are needed to identify re...

  9. A Genome-wide screen identifies frequently methylated genes in haematological and epithelial cancers

    PubMed Central

    2010-01-01

    Background Genetic as well as epigenetic alterations are a hallmark of both epithelial and haematological malignancies. High throughput screens are required to identify epigenetic markers that can be useful for diagnostic and prognostic purposes across malignancies. Results Here we report for the first time the use of the MIRA assay (methylated CpG island recovery assay) in combination with genome-wide CpG island arrays to identify epigenetic molecular markers in childhood acute lymphoblastic leukemia (ALL) on a genome-wide scale. We identified 30 genes demonstrating methylation frequencies of ≥25% in childhood ALL, nine genes showed significantly different methylation frequencies in B vs T-ALL. For majority of the genes expression could be restored in methylated leukemia lines after treatment with 5-azaDC. Forty-four percent of the genes represent targets of the polycomb complex. In chronic myeloid leukemia (CML) two of the genes, (TFAP2A and EBF2), demonstrated increased methylation in blast crisis compared to chronic phase (P < 0.05). Furthermore hypermethylation of an autophagy related gene ATG16L2 was associated with poorer prognosis in terms of molecular response to Imatinib treatment. Lastly we demonstrated that ten of these genes were also frequently methylated in common epithelial cancers. Conclusion In summary we have identified a large number of genes showing frequent methylation in childhood ALL, methylation status of two of these genes is associated with advanced disease in CML and methylation status of another gene is associated with prognosis. In addition a subset of these genes may act as epigenetic markers across hematological malignancies as well as common epithelial cancers. PMID:20184741

  10. Researchers Pinpoint Genes Linked to Height, Heart Disease

    MedlinePLUS

    ... rights reserved. More Health News on: Genes and Gene Therapy Heart Diseases Recent Health News Related MedlinePlus Health Topics Genes and Gene Therapy Heart Diseases About MedlinePlus Site Map FAQs Contact ...

  11. [Fecal lactoferrin in identifying and management of inflammatory bowel disease].

    PubMed

    Pac-Kozuchowska, Elzbieta; Krawiec, Paulina; Mroczkowska-Juchkiewicz, Agnieszka

    2014-07-01

    Inflammatory bowel disease is a group of chronic inflammatory conditions of gastrointestinal tract, including ulcerative colitis and Crohn's disease. Diagnosis of inflammatory bowel disease is based on clinical symptoms, lower and/or upper gastrointestinal tract endoscopy with biopsies and histological results. These procedures are invasive for patients and highly expensive. Thus, efforts are underway to establish new noninvasive tests appropriate to diagnosis and management of inflammatory bowel disease. Commonly used, blood markers of inflammation or scales of inflammatory bowel disease activity has been demonstrated to be insufficient. Recently, there has been increasing interest in identifying biomarkers, i.e. calprotectin, lactoferrin, mieloperoxidasis or S100A12 protein in faeces. These proteins are produced by neutrophil granulocytes and clearly reflect inflammation directly in bowel. It should be highlighted that these tests are noninvasive and may be perform repetitiously. PMID:25154203

  12. A Pilot Study of Gene/Gene and Gene/Environment Interactions in Alzheimer Disease

    PubMed Central

    Ghebranious, Nader; Mukesh, Bickol; Giampietro, Philip F.; Glurich, Ingrid; Mickel, Susan F.; Waring, Stephen C.; McCarty, Catherine A.

    2011-01-01

    Background: Although some genes associated with increased risk of Alzheimer Disease (AD) have been identified, few data exist related to gene/gene and gene/environment risk of AD. The purpose of this pilot study was to explore gene/gene and gene/environment associations in AD and to obtain data for sample size estimates for larger, more definitive studies of AD. Methods: The effect of gene/gene and gene/environment interaction related to late onset Alzheimer Disease (LOAD) was investigated in 153 subjects with LOAD and 302 gender matched controls enrolled in the Personalized Medicine Research Project, a population-based bio-repository. Genetic risk factors examined included APOE, ACE, OLR1,and CYP46 genes, and environmental factors included smoking, total cholesterol, LDL, HDL, triglycerides, C-reactive protein, blood pressure, statin use, and body mass index. Results: The mean age of the cases was 78.2 years and the mean age of the controls was 87.2 years. APOE4 was significantly associated with LOAD (OR=3.55, 95%CL=1.70, 7.45). Cases were significantly more likely to have ever smoked cigarettes during their life (49.3% versus 38.4%, p=0.03). The highest recorded blood pressure and pulse pressure measurements were significantly higher in the controls than the cases (all P<0.005). Although not statistically significant in this pilot study, the relationship of the following factors was associated in opposite directions with LOAD based on the presence of an APOE4 allele: obesity at the age of 50, ACE, OLR1, and CYP46. Conclusions: These pilot data suggest that gene/gene and gene/environment interactions may be important in LOAD, with APOE, a known risk factor for LOAD, affecting the relationship of ACE and OLR1 to LOAD. Replication with a larger sample size and in other racial/ethnic groups is warranted and the allele and risk factor frequencies will assist in choosing an appropriate sample size for a definitive study. PMID:20682755

  13. Gene therapy for childhood immunological diseases.

    PubMed

    Kohn, D B

    2008-01-01

    Gene therapy using autologous hematopoietic stem cells (HSC) that are corrected with the normal gene may have a beneficial effect on blood cell production or function, without the immunologic complications of allogeneic HSC transplantation. Childhood immunological diseases are highly favorable candidates for responses to gene therapy using HSC. Hemoglobinopathies, lysosomal and metabolic disorders and defects of hematopoietic stem and progenitor cells should also be ameliorated by gene therapy using autologous HSC. At present, gene therapy has been beneficial for patients with XSCID, ADA-deficient SCID and chronic granulomatous disease. The principle that partial marrow conditioning increases engraftment of gene-corrected HSC has been demonstrated. Clinical trials are being developed in Europe and the United States to treat several other genetic blood cell disorders. This progress is tempered by the serious complication observed in XSCID patients developing T lymphoproliferative disease. New methods for gene transfer (lentiviral and foamy viral vectors, semi-viral systems and gene correction) may retain or further increase the efficacy and decrease the risks from gene therapy using HSC. Ultimately, the relative benefits and risks of autologous gene therapy will be weighed against other available options (for example, allogeneic HSCT) to determine the treatment of choice. PMID:17994122

  14. Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2

    PubMed Central

    2012-01-01

    Background The analysis of complex diseases is an important problem in human genetics. Because multifactoriality is expected to play a pivotal role, many studies are currently focused on collecting information on the genetic and environmental factors that potentially influence these diseases. However, there is still a lack of efficient and thoroughly tested statistical models that can be used to identify implicated features and their interactions. Simulations using large biologically realistic data sets with known gene-gene and gene-environment interactions that influence the risk of a complex disease are a convenient and useful way to assess the performance of statistical methods. Results The Gene-Environment iNteraction Simulator 2 (GENS2) simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. GENS2 is based on data with realistic patterns of linkage disequilibrium, and imposes no limitations either on the number of individuals to be simulated or on number of non-predisposing genetic/environmental factors to be considered. The GENS2 tool is able to simulate gene-environment and gene-gene interactions. To make the Simulator more intuitive, the input parameters are expressed as standard epidemiological quantities. GENS2 is written in Python language and takes advantage of operators and modules provided by the simuPOP simulation environment. It can be used through a graphical or a command-line interface and is freely available from http://sourceforge.net/projects/gensim. The software is released under the GNU General Public License version 3.0. Conclusions Data produced by GENS2 can be used as a benchmark for evaluating statistical tools designed for the identification of gene-gene and gene-environment interactions. PMID:22698142

  15. 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. PMID:25236447

  16. Using Drosophila melanogaster To Identify Chemotherapy Toxicity Genes

    PubMed Central

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

    2014-01-01

    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. PMID:25236447

  17. 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

  18. Multiplexed Component Analysis to Identify Genes Contributing to the Immune Response during Acute SIV Infection.

    PubMed

    Hosseini, Iraj; Gama, Lucio; Mac Gabhann, Feilim

    2015-01-01

    Immune response genes play an important role during acute HIV and SIV infection. Using an SIV macaque model of AIDS and CNS disease, our overall goal was to assess how the expression of genes associated with immune and inflammatory responses are longitudinally changed in different organs or cells during SIV infection. To compare RNA expression of a panel of 88 immune-related genes across time points and among three tissues - spleen, mesenteric lymph nodes (MLN) and peripheral blood mononuclear cells (PBMC) - we designed a set of Nanostring probes. To identify significant genes during acute SIV infection and to investigate whether these genes are tissue-specific or have global roles, we introduce a novel multiplexed component analysis (MCA) method. This combines multivariate analysis methods with multiple preprocessing methods to create a set of 12 "judges"; each judge emphasizes particular types of change in gene expression to which cells could respond, for example, the absolute or relative size of expression change from baseline. Compared to bivariate analysis methods, our MCA method improved classification rates. This analysis allows us to identify three categories of genes: (a) consensus genes likely to contribute highly to the immune response; (b) genes that would contribute highly to the immune response only if certain assumptions are met - e.g. that the cell responds to relative expression change rather than absolute expression change; and (c) genes whose contribution to immune response appears to be modest. We then compared the results across the three tissues of interest; some genes are consistently highly-contributing in all tissues, while others are specific for certain tissues. Our analysis identified CCL8, CXCL10, CXCL11, MxA, OAS2, and OAS1 as top contributing genes, all of which are stimulated by type I interferon. This suggests that the cytokine storm during acute SIV infection is a systemic innate immune response against viral replication. Furthermore, these genes have approximately equal contributions to all tissues, making them possible candidates to be used as non-invasive biomarkers in studying PBMCs instead of MLN and spleen during acute SIV infection experiments. We identified clusters of genes that co-vary together and studied their correlation with regard to other gene clusters. We also developed novel methods to faithfully visualize multi-gene correlations on two-dimensional polar plots, and to visualize tissue specificity of gene expression responses. PMID:25984721

  19. 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. PMID:26080386

  20. Comparison of Molecular Signatures from Multiple Skin Diseases Identifies Mechanisms of Immunopathogenesis

    PubMed Central

    Inkeles, Megan S.; Scumpia, Philip O.; Swindell, William R.; Lopez, David; Teles, Rosane M.B.; Graeber, Thomas G.; Meller, Stephan; Homey, Bernhard; Elder, James T.; Gilliet, Michel; Modlin, Robert L.; Pellegrini, Matteo

    2014-01-01

    The ability to obtain gene expression profiles from human disease specimens provides an opportunity to identify relevant gene pathways, but is limited by the absence of data sets spanning a broad range of conditions. Here, we analyzed publicly available microarray data from 16 diverse skin conditions in order to gain insight into disease pathogenesis. Unsupervised hierarchical clustering separated samples by disease and common cellular and molecular pathways. Disease specific signatures were leveraged to build a multi-disease classifier which predicted the diagnosis of publicly and prospectively collected expression profiles with 93% accuracy. In one sample, the molecular classifier differed from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinical presentation evolved. Finally, integration of interferon (IFN) regulated gene programs with the skin database revealed a significant inverse correlation between IFN? and IFN? programs across all conditions. Our study provides an integrative approach to the study of gene signatures from multiple skin conditions, elucidating mechanisms of disease pathogenesis. Additionally, these studies provide a framework for developing tools for personalized medicine towards the precise prediction, prevention, and treatment of disease on an individual level. PMID:25111617

  1. Identifying Francisella tularensis genes required for growth in host cells.

    PubMed

    Brunton, J; Steele, S; Miller, C; Lovullo, E; Taft-Benz, S; Kawula, T

    2015-08-01

    Francisella tularensis is a highly virulent Gram-negative intracellular pathogen capable of infecting a vast diversity of hosts, ranging from amoebae to humans. A hallmark of F. tularensis virulence is its ability to quickly grow to high densities within a diverse set of host cells, including, but not limited to, macrophages and epithelial cells. We developed a luminescence reporter system to facilitate a large-scale transposon mutagenesis screen to identify genes required for growth in macrophage and epithelial cell lines. We screened 7,454 individual mutants, 269 of which exhibited reduced intracellular growth. Transposon insertions in the 269 growth-defective strains mapped to 68 different genes. FTT_0924, a gene of unknown function but highly conserved among Francisella species, was identified in this screen to be defective for intracellular growth within both macrophage and epithelial cell lines. FTT_0924 was required for full Schu S4 virulence in a murine pulmonary infection model. The ?FTT_0924 mutant bacterial membrane is permeable when replicating in hypotonic solution and within macrophages, resulting in strongly reduced viability. The permeability and reduced viability were rescued when the mutant was grown in a hypertonic solution, indicating that FTT_0924 is required for resisting osmotic stress. The ?FTT_0924 mutant was also significantly more sensitive to ?-lactam antibiotics than Schu S4. Taken together, the data strongly suggest that FTT_0924 is required for maintaining peptidoglycan integrity and virulence. PMID:25987704

  2. Immunoglobulin A coating identifies colitogenic bacteria in inflammatory bowel disease.

    PubMed

    Palm, Noah W; de Zoete, Marcel R; Cullen, Thomas W; Barry, Natasha A; Stefanowski, Jonathan; Hao, Liming; Degnan, Patrick H; Hu, Jianzhong; Peter, Inga; Zhang, Wei; Ruggiero, Elizabeth; Cho, Judy H; Goodman, Andrew L; Flavell, Richard A

    2014-08-28

    Specific members of the intestinal microbiota dramatically affect inflammatory bowel disease (IBD) in mice. In humans, however, identifying bacteria that preferentially affect disease susceptibility and severity remains a major challenge. Here, we used flow-cytometry-based bacterial cell sorting and 16S sequencing to characterize taxa-specific coating of the intestinal microbiota with immunoglobulin A (IgA-SEQ) and show that high IgA coating uniquely identifies colitogenic intestinal bacteria in a mouse model of microbiota-driven colitis. We then used IgA-SEQ and extensive anaerobic culturing of fecal bacteria from IBD patients to create personalized disease-associated gut microbiota culture collections with predefined levels of IgA coating. Using these collections, we found that intestinal bacteria selected on the basis of high coating with IgA conferred dramatic susceptibility to colitis in germ-free mice. Thus, our studies suggest that IgA coating identifies inflammatory commensals that preferentially drive intestinal disease. Targeted elimination of such bacteria may reduce, reverse, or even prevent disease development. PMID:25171403

  3. New Viruses Identified in Fig Trees Exhibiting Fig Mosaic Disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fig mosaic disease has been known for decades, but the causal agent has been elusive. Here we present data on the incidence of at least four new viruses isolated from fig trees exhibiting mosaic symptoms. One of the viruses is closely related to the recently identified European mountain ash ringspo...

  4. 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 intrieur. 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. PMID:26545598

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

    PubMed Central

    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

  6. Variability of Gene Expression Identifies Transcriptional Regulators of Early Human Embryonic Development

    PubMed Central

    Hasegawa, Yu; Taylor, Deanne; Ovchinnikov, Dmitry A.; Wolvetang, Ernst J.; de Torrenté, Laurence; Mar, Jessica C.

    2015-01-01

    An analysis of gene expression variability can provide an insightful window into how regulatory control is distributed across the transcriptome. In a single cell analysis, the inter-cellular variability of gene expression measures the consistency of transcript copy numbers observed between cells in the same population. Application of these ideas to the study of early human embryonic development may reveal important insights into the transcriptional programs controlling this process, based on which components are most tightly regulated. Using a published single cell RNA-seq data set of human embryos collected at four-cell, eight-cell, morula and blastocyst stages, we identified genes with the most stable, invariant expression across all four developmental stages. Stably-expressed genes were found to be enriched for those sharing indispensable features, including essentiality, haploinsufficiency, and ubiquitous expression. The stable genes were less likely to be associated with loss-of-function variant genes or human recessive disease genes affected by a DNA copy number variant deletion, suggesting that stable genes have a functional impact on the regulation of some of the basic cellular processes. Genes with low expression variability at early stages of development are involved in regulation of DNA methylation, responses to hypoxia and telomerase activity, whereas by the blastocyst stage, low-variability genes are enriched for metabolic processes as well as telomerase signaling. Based on changes in expression variability, we identified a putative set of gene expression markers of morulae and blastocyst stages. Experimental validation of a blastocyst-expressed variability marker demonstrated that HDDC2 plays a role in the maintenance of pluripotency in human ES and iPS cells. Collectively our analyses identified new regulators involved in human embryonic development that would have otherwise been missed using methods that focus on assessment of the average expression levels; in doing so, we highlight the value of studying expression variability for single cell RNA-seq data. PMID:26288249

  7. Refining analyses of copy number variation identifies specific genes associated with developmental delay.

    PubMed

    Coe, Bradley P; Witherspoon, Kali; Rosenfeld, Jill A; van Bon, Bregje W M; Vulto-van Silfhout, Anneke T; Bosco, Paolo; Friend, Kathryn L; Baker, Carl; Buono, Serafino; Vissers, Lisenka E L M; Schuurs-Hoeijmakers, Janneke H; Hoischen, Alex; Pfundt, Rolph; Krumm, Nik; Carvill, Gemma L; Li, Deana; Amaral, David; Brown, Natasha; Lockhart, Paul J; Scheffer, Ingrid E; Alberti, Antonino; Shaw, Marie; Pettinato, Rosa; Tervo, Raymond; de Leeuw, Nicole; Reijnders, Margot R F; Torchia, Beth S; Peeters, Hilde; O'Roak, Brian J; Fichera, Marco; Hehir-Kwa, Jayne Y; Shendure, Jay; Mefford, Heather C; Haan, Eric; Gcz, Jozef; de Vries, Bert B A; Romano, Corrado; Eichler, Evan E

    2014-10-01

    Copy number variants (CNVs) are associated with many neurocognitive disorders; however, these events are typically large, and the underlying causative genes are unclear. We created an expanded CNV morbidity map from 29,085 children with developmental delay in comparison to 19,584 healthy controls, identifying 70 significant CNVs. We resequenced 26 candidate genes in 4,716 additional cases with developmental delay or autism and 2,193 controls. An integrated analysis of CNV and single-nucleotide variant (SNV) data pinpointed 10 genes enriched for putative loss of function. Follow-up of a subset of affected individuals identified new clinical subtypes of pediatric disease and the genes responsible for disease-associated CNVs. These genetic changes include haploinsufficiency of SETBP1 associated with intellectual disability and loss of expressive language and truncations of ZMYND11 in individuals with autism, aggression and complex neuropsychiatric features. This combined CNV and SNV approach facilitates the rapid discovery of new syndromes and genes involved in neuropsychiatric disease despite extensive genetic heterogeneity. PMID:25217958

  8. Screening for noise in gene expression identifies drug synergies.

    PubMed

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

    2014-06-20

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

  9. Screening for Noise in Gene Expression Identifies Drug Synergies

    PubMed Central

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

    2014-01-01

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

  10. Identifying the genes regulated by IDH1 via gene-chip in glioma cell U87

    PubMed Central

    Ren, Jie; Lou, Meiqing; Shi, Jinlong; Xue, Yajun; Cui, Daming

    2015-01-01

    Glioma is the most common form of primary brain tumor. Increasing evidence show that IDH1 gene mutation is implicated in glioma. However, the mechanism involved in the progression of glioma remains unclear until now. In the study reported here, we used gene chip to identifying the genes regulated with IDH mutanted at R132. The results showed that IDH1-mutant leads to 1255 up-regulated genes and 1862 down-regulated genes in U87 cell lines. Meanwhile, GO and gene-network was performed and shown IDH1-mutant mainly affect small molecule metabolic process, mitotic cell cycle and apoptosis. This result will lay a foundation for further study of IDH1 gene function in the future. PMID:26770405

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

    PubMed

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

    2009-03-01

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

  12. Identifying genes that mediate anthracyline toxicity in immune cells

    PubMed Central

    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. PMID:25926793

  13. Identifying critical transitions and their leading biomolecular networks in complex diseases

    NASA Astrophysics Data System (ADS)

    Liu, Rui; Li, Meiyi; Liu, Zhi-Ping; Wu, Jiarui; Chen, Luonan; Aihara, Kazuyuki

    2012-12-01

    Identifying a critical transition and its leading biomolecular network during the initiation and progression of a complex disease is a challenging task, but holds the key to early diagnosis and further elucidation of the essential mechanisms of disease deterioration at the network level. In this study, we developed a novel computational method for identifying early-warning signals of the critical transition and its leading network during a disease progression, based on high-throughput data using a small number of samples. The leading network makes the first move from the normal state toward the disease state during a transition, and thus is causally related with disease-driving genes or networks. Specifically, we first define a state-transition-based local network entropy (SNE), and prove that SNE can serve as a general early-warning indicator of any imminent transitions, regardless of specific differences among systems. The effectiveness of this method was validated by functional analysis and experimental data.

  14. An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis.

    PubMed

    Sweet-Cordero, Alejandro; Mukherjee, Sayan; Subramanian, Aravind; You, Han; Roix, Jeffrey J; Ladd-Acosta, Christine; Mesirov, Jill; Golub, Todd R; Jacks, Tyler

    2005-01-01

    Using advanced gene targeting methods, generating mouse models of cancer that accurately reproduce the genetic alterations present in human tumors is now relatively straightforward. The challenge is to determine to what extent such models faithfully mimic human disease with respect to the underlying molecular mechanisms that accompany tumor progression. Here we describe a method for comparing mouse models of cancer with human tumors using gene-expression profiling. We applied this method to the analysis of a model of Kras2-mediated lung cancer and found a good relationship to human lung adenocarcinoma, thereby validating the model. Furthermore, we found that whereas a gene-expression signature of KRAS2 activation was not identifiable when analyzing human tumors with known KRAS2 mutation status alone, integrating mouse and human data uncovered a gene-expression signature of KRAS2 mutation in human lung cancer. We confirmed the importance of this signature by gene-expression analysis of short hairpin RNA-mediated inhibition of oncogenic Kras2. These experiments identified both a pattern of gene expression indicative of KRAS2 mutation and potential effectors of oncogenic KRAS2 activity in human cancer. This approach provides a strategy for using genomic analysis of animal models to probe human disease. PMID:15608639

  15. Viruses, autophagy genes, and Crohn's disease.

    PubMed

    Hubbard, Vanessa M; Cadwell, Ken

    2011-07-01

    The etiology of the intestinal disease Crohn's disease involves genetic factors as well as ill-defined environmental agents. Several genetic variants linked to this disease are associated with autophagy, a process that is critical for proper responses to viral infections. While a role for viruses in this disease remains speculative, accumulating evidence indicate that this possibility requires serious consideration. In this review, we will examine the three-way relationship between viruses, autophagy genes, and Crohn's disease and discuss how host-pathogen interactions can mediate complex inflammatory disorders. PMID:21994779

  16. Genetics of sputum gene expression in chronic obstructive pulmonary disease.

    PubMed

    Qiu, Weiliang; Cho, Michael H; Riley, John H; Anderson, Wayne H; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A; Lomas, David A; Crapo, James D; Beaty, Terri H; Celli, Bartolome R; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M; Silverman, Edwin K; Hersh, Craig P

    2011-01-01

    Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

  17. Genetics of Sputum Gene Expression in Chronic Obstructive Pulmonary Disease

    PubMed Central

    Qiu, Weiliang; Cho, Michael H.; Riley, John H.; Anderson, Wayne H.; Singh, Dave; Bakke, Per; Gulsvik, Amund; Litonjua, Augusto A.; Lomas, David A.; Crapo, James D.; Beaty, Terri H.; Celli, Bartolome R.; Rennard, Stephen; Tal-Singer, Ruth; Fox, Steven M.; Silverman, Edwin K.; Hersh, Craig P.

    2011-01-01

    Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

  18. 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

  19. Gene expression profiling as a window into idiopathic pulmonary fibrosis pathogenesis: can we identify the right target genes?

    PubMed

    Kaminski, Naftali; Rosas, Ivan O

    2006-06-01

    Expression microarrays that provide genome-level, transcriptional, high-resolution profiles have been applied successfully to multiple diseases. Although microarrays provide information regarding thousands of genes, many investigators prefer to focus on a single gene and validate its role, an approach often supported by grant and journal reviewers. Only a minority of investigators focus on global changes in gene expression. Here, we describe and contrast two general approaches to the use of microarray data: the reductionist "cherry picking" approach and the more global, quantitative "systems" approach. We describe microarray analysis experiments relevant to idiopathic pulmonary fibrosis (IPF) in the context of these two approaches. Although it seems that the cherry-picking approaches have been successful in identifying new relevant genes in IPF, we suggest that to fulfill the discovery potential of microarrays in IPF and to create a working model of IPF, unbiased integrative systems approaches are required. PMID:16738198

  20. Genomics meets proteomics: identifying the culprits in disease.

    PubMed

    Stunnenberg, Hendrik G; Hubner, Nina C

    2014-06-01

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

  1. Beryllium Lymphocyte Proliferation Test Surveillance Identifies Clinically Significant Beryllium Disease

    PubMed Central

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

    2011-01-01

    Background Workplace surveillance identifies chronic beryllium disease (CBD) but it remains unknown over what time frame mild CBD will progress to a more severe form. Methods We examined physiology and treatment in 229 beryllium sensitization (BeS) and 171 CBD surveillance-identified cases diagnosed from 1982 to 2002. Never smoking CBD cases (81) were compared to never smoking BeS patients (83) to assess disease progression. We compared CBD machinists to non-machinists to examine effects of exposure. Results At baseline, CBD and BeS cases did not differ significantly in exposure time or physiology. CBD patients were more likely to have machined beryllium. Of CBD cases, 19.3% went on to require oral immunosuppressive therapy. At 30 years from first exposure, measures of gas exchange were significantly worse and total lung capacity was lower for CBD subjects. Machinists had faster disease progression as measured by pulmonary function testing and gas exchange. Conclusions Medical surveillance for CBD identifies individuals at significant risk of disease progression and impairment with sufficient time since first exposure. PMID:19681064

  2. An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

    PubMed Central

    Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

    2009-01-01

    Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

  3. Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD.

    PubMed

    Yoo, Seungyeul; Takikawa, Sachiko; Geraghty, Patrick; Argmann, Carmen; Campbell, Joshua; Lin, Luan; Huang, Tao; Tu, Zhidong; Foronjy, Robert F; Feronjy, Robert; Spira, Avrum; Schadt, Eric E; Powell, Charles A; Zhu, Jun

    2015-01-01

    Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a 'causal' role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology. PMID:25569234

  4. Integrative Analysis of DNA Methylation and Gene Expression Data Identifies EPAS1 as a Key Regulator of COPD

    PubMed Central

    Yoo, Seungyeul; Takikawa, Sachiko; Geraghty, Patrick; Argmann, Carmen; Campbell, Joshua; Lin, Luan; Huang, Tao; Tu, Zhidong; Feronjy, Robert; Spira, Avrum; Schadt, Eric E.; Powell, Charles A.; Zhu, Jun

    2015-01-01

    Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology. PMID:25569234

  5. The Centre for Modeling Human Disease Gene Trap resource.

    PubMed

    To, Christine; Epp, Trevor; Reid, Tammy; Lan, Qing; Yu, Mei; Li, Carol Y J; Ohishi, Minako; Hant, Paula; Tsao, Nora; Casallo, Guillermo; Rossant, Janet; Osborne, Lucy R; Stanford, William L

    2004-01-01

    Gene trap mutagenesis of mouse embryonic stem cells generates random loss-of-function mutations, which can be identified by a sequence tag and can often report the endogenous expression of the mutated gene. The Centre for Modeling Human Disease is performing expression- and sequence-based screens of gene trap insertions to generate new mouse mutations as a resource for the scientific community. The gene trap insertions are screened using multiplexed in vitro differentiation and induction assays, and sequence tags are generated to complement expression profiles. Researchers may search for insertions in genes expressed in target cell lineages, under specific in vitro conditions, or based upon sequence identity via an online searchable database (http://www.cmhd.ca/sub/genetrap.asp). The clones are available as a resource to researchers worldwide to help to functionally annotate the mammalian genome and will serve as a source to test candidate loci identified by phenotype-driven mutagenesis screens. PMID:14681480

  6. 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. PMID:21913285

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

    PubMed Central

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

    2010-01-01

    Purpose. To identify genes and molecular mechanisms associated with photoreceptor degeneration in a canine model of XLRP caused by an RPGR exon ORF15 microdeletion. Methods. Expression profiles of mutant and normal retinas were compared by using canine retinal custom cDNA microarrays. qRT-PCR, Western blot analysis, and immunohistochemistry (IHC) were applied to selected genes, to confirm and expand the microarray results. Results. At 7 and 16 weeks, respectively, 56 and 18 transcripts were downregulated in the mutant retinas, but none were differentially expressed (DE) at both ages, suggesting the involvement of temporally distinct pathways. Downregulated genes included the known retina-relevant genes PAX6, CHML, and RDH11 at 7 weeks and CRX and SAG at 16 weeks. Genes directly or indirectly active in apoptotic processes were altered at 7 weeks (CAMK2G, NTRK2, PRKCB, RALA, RBBP6, RNF41, SMYD3, SPP1, and TUBB2C) and 16 weeks (SLC25A5 and NKAP). Furthermore, the DE genes at 7 weeks (ELOVL6, GLOD4, NDUFS4, and REEP1) and 16 weeks (SLC25A5 and TARS2) are related to mitochondrial functions. qRT-PCR of 18 genes confirmed the microarray results and showed DE of additional genes not on the array. Only GFAP was DE at 3 weeks of age. Western blot and IHC analyses also confirmed the high reliability of the transcriptomic data. Conclusions. Several DE genes were identified in mutant retinas. At 7 weeks, a combination of nonclassic anti- and proapoptosis genes appear to be involved in photoreceptor degeneration, whereas at both 7 and 16 weeks, the expression of mitochondria-related genes indicates that they may play a relevant role in the disease process. PMID:20574030

  8. 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.

  9. Integrated genomics identifies convergence of ankylosing spondylitis with global immune mediated disease pathways.

    PubMed

    Uddin, Mohammed; Codner, Dianne; Hasan, S M Mahmud; 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 × 0(-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

  10. Identifying gene clusters by discovering common intervals in indeterminate strings

    PubMed Central

    2014-01-01

    Background Comparative analyses of chromosomal gene orders are successfully used to predict gene clusters in bacterial and fungal genomes. Present models for detecting sets of co-localized genes in chromosomal sequences require prior knowledge of gene family assignments of genes in the dataset of interest. These families are often computationally predicted on the basis of sequence similarity or higher order features of gene products. Errors introduced in this process amplify in subsequent gene order analyses and thus may deteriorate gene cluster prediction. Results In this work, we present a new dynamic model and efficient computational approaches for gene cluster prediction suitable in scenarios ranging from traditional gene family-based gene cluster prediction, via multiple conflicting gene family annotations, to gene family-free analysis, in which gene clusters are predicted solely on the basis of a pairwise similarity measure of the genes of different genomes. We evaluate our gene family-free model against a gene family-based model on a dataset of 93 bacterial genomes. Conclusions Our model is able to detect gene clusters that would be also detected with well-established gene family-based approaches. Moreover, we show that it is able to detect conserved regions which are missed by gene family-based methods due to wrong or deficient gene family assignments. PMID:25571793

  11. Statistical Challenges in Identifying Risk Factors for Aortic Disease

    PubMed Central

    Rizzo, John A.; Chen, Jie; Fang, Hai; Ziganshin, Bulat A.; Elefteriades, John A.

    2014-01-01

    Being largely asymptomatic, thoracic aortic aneurysms pose a challenge for the physician to identify and intervene in time to prevent death or a major complication. Knowing how to accurately analyze the available clinical data is vital to informing the proper management of these patients. This paper seeks to provide an overview of the statistical methods most commonly used to analyze clinical outcomes with a special focus on research related to aortic disease.

  12. Exome resequencing identifies potential tumor-suppressor genes that predispose to colorectal cancer.

    PubMed

    Smith, Christopher G; Naven, Marc; Harris, Rebecca; Colley, James; West, Hannah; Li, Ning; Liu, Yuan; Adams, Richard; Maughan, Timothy S; Nichols, Laura; Kaplan, Richard; Wagner, Michael J; McLeod, Howard L; Cheadle, Jeremy P

    2013-07-01

    Inherited factors account for around one third of all colorectal cancers (CRCs) and include rare high penetrance mutations in APC, MSH2, MSH6, and POLE. Here, we sought novel tumor-suppressor genes that predispose to CRC by exome resequencing 50 sporadic patients with advanced CRC (18 diagnosed ?35 years of age) at a mean coverage of 30. To help identify potentially pathogenic alleles, we initially sought rare or novel germline truncating mutations in 1,138 genes that were likely to play a role in colorectal tumorigenesis. In total, 32 such mutations were identified and confirmed, and included an insertion in APC and a deletion in POLE, thereby validating our approach for identifying disease alleles. We sought somatic mutations in the corresponding genes in the CRCs of the patients harboring the germline lesions and found biallelic inactivation of FANCM, LAMB4, PTCHD3, LAMC3, and TREX2, potentially implicating these genes as tumor suppressors. We also identified a patient who carried a germline truncating mutation in NOTCH3, part of the Notch signaling cascade that maintains intestinal homeostasis. Our whole exome analyses provided further gene lists to facilitate the identification of potential predisposition alleles. PMID:23585368

  13. Comparative oncogenomics identifies PSMB4 and SHMT2 as potential cancer driver genes.

    PubMed

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

    2014-06-01

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

  14. 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

  15. A polymorphic gene nested within an intron of the tau gene: Implications for Alzheimer's disease

    PubMed Central

    Conrad, Chris; Vianna, Cintia; Freeman, Melissa; Davies, Peter

    2002-01-01

    A previously undescribed gene, Saitohin (STH), has been discovered in the intron between exons 9 and 10 of the human tau gene. STH is an intronless gene that encodes a 128-aa protein with no clear homologs. The tissue expression of STH is similar to tau, a gene that is implicated in many neurodegenerative disorders. In humans, a single nucleotide polymorphism that results in an amino acid change (Q7R) has been identified in STH and was used in a case control study. The Q7R polymorphism appears to be over-represented in the homozygous state in late onset Alzheimer's disease subjects. PMID:12032355

  16. Co-clustering phenomegenome 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 phenotypegene 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 phenotypegene association matrix under the prior knowledge from phenotype similarity network and proteinprotein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotypegene 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 proteinprotein 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

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

    PubMed Central

    Cirulli, Elizabeth T.; Lasseigne, Brittany N.; Petrovski, Slav; 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 I?B 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

  18. 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. PMID:25700176

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

    PubMed Central

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

    2012-01-01

    Rationale Peripheral blood biomarkers are needed to identify and determine the extent of idiopathic pulmonary fibrosis (IPF). Current physiologic and radiographic prognostic indicators diagnose IPF too late in the course of disease. We hypothesize that peripheral blood biomarkers will identify disease in its early stages, and facilitate monitoring for disease progression. Methods Gene expression profiles of peripheral blood RNA from 130 IPF patients were collected on Agilent microarrays. Significance analysis of microarrays (SAM) with a false discovery rate (FDR) of 1% was utilized to identify genes that were differentially-expressed in samples categorized based on percent predicted DLCO and FVC. Main Measurements and Results At 1% FDR, 1428 genes were differentially-expressed in mild IPF (DLCO >65%) compared to controls and 2790 transcripts were differentially- expressed in severe IPF (DLCO >35%) compared to controls. When categorized by percent predicted DLCO, SAM demonstrated 13 differentially-expressed transcripts between mild and severe IPF (< 5% FDR). These include CAMP, CEACAM6, CTSG, DEFA3 and A4, OLFM4, HLTF, PACSIN1, GABBR1, IGHM, and 3 unknown genes. Principal component analysis (PCA) was performed to determine outliers based on severity of disease, and demonstrated 1 mild case to be clinically misclassified as a severe case of IPF. No differentially-expressed transcripts were identified between mild and severe IPF when categorized by percent predicted FVC. Conclusions These results demonstrate that the peripheral blood transcriptome has the potential to distinguish normal individuals from patients with IPF, as well as extent of disease when samples were classified by percent predicted DLCO, but not FVC. PMID:22761659

  20. 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

  1. Identifying Sarcomere Gene Mutations in HCM: A Personal History

    PubMed Central

    Seidman, Christine E.; Seidman, J.G.

    2011-01-01

    This article provides an historical and personal perspective on the discovery of genetic causes for hypertrophic cardiomyopathy (HCM). Extraordinary insights of physicians who initially detailed remarkable and varied manifestations of the disorder, collaboration among multidisciplinary teams with skills in clinical diagnostics and molecular genetics, and hard work by scores of trainees, solved the etiologic riddle of HCM, and unexpectedly demonstrated mutations in sarcomere protein genes as the cause of disease. In addition to celebrating 20 years of genetic research in HCM, this article serves as an introductory overview to a thematic review series that will present contemporary advances in the field of hypertrophic heart disease. Through the continued application of advances in genetic methodologies, combined with biochemical and biophysical analyses of the consequences of human mutations, fundamental knowledge about HCM and sarcomere biology has emerged. Expanding research to elucidate the mechanisms by which subtle genetic variation in contractile proteins remodel the human heart remains an exciting opportunity, one with considerable promise to provide new strategies to limit or even prevent HCM pathogenesis. PMID:21415408

  2. Identifying sarcomere gene mutations in hypertrophic cardiomyopathy: a personal history.

    PubMed

    Seidman, Christine E; Seidman, J G

    2011-03-18

    This review provides an historical and personal perspective on the discovery of genetic causes for hypertrophic cardiomyopathy (HCM). Extraordinary insights by physicians who initially detailed remarkable and varied manifestations of the disorder, collaboration among multidisciplinary teams with skills in clinical diagnostics and molecular genetics, and hard work by scores of trainees solved the etiologic riddle of HCM and unexpectedly demonstrated mutations in sarcomere protein genes as the cause of disease. In addition to celebrating 20 years of genetic research in HCM, this article serves as an introductory overview to a thematic review series that will present contemporary advances in the field of hypertrophic heart disease. Through the continued application of advances in genetic methodologies, combined with biochemical and biophysical analyses of the consequences of human mutations, fundamental knowledge about HCM and sarcomere biology has emerged. Expanding research to elucidate the mechanisms by which subtle genetic variation in contractile proteins remodel the human heart remains an exciting opportunity, one with considerable promise to provide new strategies to limit or even prevent HCM pathogenesis. PMID:21415408

  3. Gene and splicing therapies for neuromuscular diseases.

    PubMed

    Benchaouir, Rachid; Robin, Valerie; Goyenvalle, Aurelie

    2015-01-01

    Neuromuscular disorders (NMD) are heterogeneous group of genetic diseases characterized by muscle weakness and wasting. Duchenne Muscular dystrophy (DMD) and Spinal muscular atrophy (SMA) are two of the most common and severe forms in humans and although the molecular mechanisms of these diseases have been extensively investigated, there is currently no effective treatment. However, new gene-based therapies have recently emerged with particular noted advances in using conventional gene replacement strategies and RNA-based technology. Whilst proof of principle have been demonstrated in animal models, several clinical trials have recently been undertaken to investigate the feasibility of these strategies in patients. In particular, antisense mediated exon skipping has shown encouraging results and hold promise for the treatment of dystrophic muscle. In this review, we summarize the recent progress of therapeutic approaches to neuromuscular diseases, with an emphasis on gene therapy and splicing modulation for DMD and SMA, focusing on the advantages offered by these technologies but also their challenges. PMID:25961553

  4. 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

  5. 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; Bge, Tove; Johannsen, Gunnar; Koro, Catalin; Lundeberg, Joakim; Yucel-Lindberg, Tlay

    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

  6. 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. PMID:26724943

  7. Neuronal gene expression profiling: uncovering the molecular biology of neurodegenerative disease.

    PubMed

    Mufson, Elliott J; Counts, Scott E; Che, Shaoli; Ginsberg, Stephen D

    2006-01-01

    The development of gene array techniques to quantify expression levels of dozens to thousands of genes simultaneously within selected tissue samples from control and diseased brain has enabled researchers to generate expression profiles of vulnerable neuronal populations in several neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, schizophrenia, multiple sclerosis, and Creutzfeld-Jakob disease. Intriguingly, gene expression analysis reveals that vulnerable brain regions in many of these diseases share putative pathogenetic alterations in common classes of genes, including decrements in synaptic transcript levels and increments in immune response transcripts. Thus, gene expression profiles of diseased neuronal populations may reveal mechanistic clues to the molecular pathogenesis underlying various neurological diseases and aid in identifying potential therapeutic targets. This chapter will review how regional and single cell gene array technologies have advanced our understanding of the genetics of human neurological disease. PMID:17027698

  8. Thick and Thin Filament Gene Mutations in Striated Muscle Diseases

    PubMed Central

    Tajsharghi, Homa

    2008-01-01

    The sarcomere is the fundamental unit of cardiac and skeletal muscle contraction. During the last ten years, there has been growing awareness of the etiology of skeletal and cardiac muscle diseases originating in the sarcomere, an important evolving field. Many sarcomeric diseases affect newborn children, i. e. are congenital myopathies. The discovery and characterization of several myopathies caused by mutations in myosin heavy chain genes, coding for the major component of skeletal muscle thick filaments, has led to the introduction of a new entity in the field of neuromuscular disorders: myosin myopathies. Recently, mutations in genes coding for skeletal muscle thin filaments, associated with various clinical features, have been identified. These mutations evoke distinct structural changes within the sarcomeric thin filament. Current knowledge regarding contractile protein dysfunction as it relates to disease pathogenesis has failed to decipher the mechanistic links between mutations identified in sarcomeric proteins and skeletal myopathies, which will no doubt require an integrated physiological approach. The discovery of additional genes associated with myopathies and the elucidation of the molecular mechanisms of pathogenesis will lead to improved and more accurate diagnosis, including prenatally, and to enhanced potential for prognosis, genetic counseling and developing possible treatments for these diseases. The goal of this review is to present recent progress in the identification of gene mutations from each of the major structural components of the sarcomere, the thick and thin filaments, related to skeletal muscle disease. The genetics and clinical manifestations of these disorders will be discussed. PMID:19325803

  9. Thick and thin filament gene mutations in striated muscle diseases.

    PubMed

    Tajsharghi, Homa

    2008-06-01

    The sarcomere is the fundamental unit of cardiac and skeletal muscle contraction. During the last ten years, there has been growing awareness of the etiology of skeletal and cardiac muscle diseases originating in the sarcomere, an important evolving field. Many sarcomeric diseases affect newborn children, i. e. are congenital myopathies. The discovery and characterization of several myopathies caused by mutations in myosin heavy chain genes, coding for the major component of skeletal muscle thick filaments, has led to the introduction of a new entity in the field of neuromuscular disorders: myosin myopathies. Recently, mutations in genes coding for skeletal muscle thin filaments, associated with various clinical features, have been identified. These mutations evoke distinct structural changes within the sarcomeric thin filament. Current knowledge regarding contractile protein dysfunction as it relates to disease pathogenesis has failed to decipher the mechanistic links between mutations identified in sarcomeric proteins and skeletal myopathies, which will no doubt require an integrated physiological approach. The discovery of additional genes associated with myopathies and the elucidation of the molecular mechanisms of pathogenesis will lead to improved and more accurate diagnosis, including prenatally, and to enhanced potential for prognosis, genetic counseling and developing possible treatments for these diseases. The goal of this review is to present recent progress in the identification of gene mutations from each of the major structural components of the sarcomere, the thick and thin filaments, related to skeletal muscle disease. The genetics and clinical manifestations of these disorders will be discussed. PMID:19325803

  10. TimeXNet: Identifying active gene sub-networks using time-course gene expression profiles

    PubMed Central

    2014-01-01

    Background Time-course gene expression profiles are frequently used to provide insight into the changes in cellular state over time and to infer the molecular pathways involved. When combined with large-scale molecular interaction networks, such data can provide information about the dynamics of cellular response to stimulus. However, few tools are currently available to predict a single active gene sub-network from time-course gene expression profiles. Results We introduce a tool, TimeXNet, which identifies active gene sub-networks with temporal paths using time-course gene expression profiles in the context of a weighted gene regulatory and protein-protein interaction network. TimeXNet uses a specialized form of the network flow optimization approach to identify the most probable paths connecting the genes with significant changes in expression at consecutive time intervals. TimeXNet has been extensively evaluated for its ability to predict novel regulators and their associated pathways within active gene sub-networks in the mouse innate immune response and the yeast osmotic stress response. Compared to other similar methods, TimeXNet identified up to 50% more novel regulators from independent experimental datasets. It predicted paths within a greater number of known pathways with longer overlaps (up to 7 consecutive edges) within these pathways. TimeXNet was also shown to be robust in the presence of varying amounts of noise in the molecular interaction network. Conclusions TimeXNet is a reliable tool that can be used to study cellular response to stimuli through the identification of time-dependent active gene sub-networks in diverse biological systems. It is significantly better than other similar tools. TimeXNet is implemented in Java as a stand-alone application and supported on Linux, MS Windows and Macintosh. The output of TimeXNet can be directly viewed in Cytoscape. TimeXNet is freely available for non-commercial users. PMID:25522063

  11. Genome-Wide Architecture of Disease Resistance Genes in Lettuce

    PubMed Central

    Christopoulou, Marilena; Wo, Sebastian Reyes-Chin; Kozik, Alex; McHale, Leah K.; Truco, Maria-Jose; Wroblewski, Tadeusz; Michelmore, Richard W.

    2015-01-01

    Genome-wide motif searches identified 1134 genes in the lettuce reference genome of cv. Salinas that are potentially involved in pathogen recognition, of which 385 were predicted to encode nucleotide binding-leucine rich repeat receptor (NLR) proteins. Using a maximum-likelihood approach, we grouped the NLRs into 25 multigene families and 17 singletons. Forty-one percent of these NLR-encoding genes belong to three families, the largest being RGC16 with 62 genes in cv. Salinas. The majority of NLR-encoding genes are located in five major resistance clusters (MRCs) on chromosomes 1, 2, 3, 4, and 8 and cosegregate with multiple disease resistance phenotypes. Most MRCs contain primarily members of a single NLR gene family but a few are more complex. MRC2 spans 73 Mb and contains 61 NLRs of six different gene families that cosegregate with nine disease resistance phenotypes. MRC3, which is 25 Mb, contains 22 RGC21 genes and colocates with Dm13. A library of 33 transgenic RNA interference tester stocks was generated for functional analysis of NLR-encoding genes that cosegregated with disease resistance phenotypes in each of the MRCs. Members of four NLR-encoding families, RGC1, RGC2, RGC21, and RGC12 were shown to be required for 16 disease resistance phenotypes in lettuce. The general composition of MRCs is conserved across different genotypes; however, the specific repertoire of NLR-encoding genes varied particularly of the rapidly evolving Type I genes. These tester stocks are valuable resources for future analyses of additional resistance phenotypes. PMID:26449254

  12. Identifying Diagnostic Peptides for Lyme Disease through Epitope Discovery

    PubMed Central

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

    2001-01-01

    Serum antibodies from patients with Lyme disease (LD) were used to affinity select peptide epitopes from 12 large random peptide libraries in phage display format. The selected peptides were surveyed for reactivity with a panel of positive sera (from LD patients) and negative sera (from subjects without LD), thus identifying 17 peptides with a diagnostically useful binding pattern: reactivity with at least three positive sera and no reactivity with any of the negative sera. The peptides define eight sequence motifs, none of which can be matched convincingly with segments of proteins from Borrelia burgdorferi, the LD pathogen; evidently, then, they are mimotopes, mimicking natural pathogen epitopes without matching contiguous amino acids of pathogen proteins. Peptides like these could be the basis of a new diagnostic enzyme-linked immunosorbent assay for LD, with sufficient specificity and sensitivity to replace expensive immunoblotting tests that are currently required for definitive serological diagnosis. Moreover, the method used to discover these peptides did not require any knowledge of the pathogen and involved generic procedures that are applicable to almost any infectious disease, including emerging diseases for which no pathogen has yet been identified. PMID:11139210

  13. Mislocalization-related disease gene discovery using gene expression based computational protein localization prediction.

    PubMed

    Liu, Zhonghao; Hu, Jianjun

    2016-01-15

    Protein sorting is an important mechanism for transporting proteins to their target subcellular locations after their synthesis. Mutations on genes may disrupt the well regulated protein sorting process, leading to a variety of mislocation related diseases. This paper proposes a methodology to discover such disease genes based on gene expression data and computational protein localization prediction. A kernel logistic regression based algorithm is used to successfully identify several candidate cancer genes which may cause cancers due to their mislocation within the cell. Our results also showed that compared to the gene co-expression network defined on Pearson correlation coefficients, the nonlinear Maximum Correlation Coefficients (MIC) based co-expression network give better results for subcellular localization prediction. PMID:26416496

  14. 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

  15. 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

    2016-01-01

    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

  16. Gene expression analyses identify Narp contribution in the development of L-DOPA-induced dyskinesia.

    PubMed

    Charbonnier-Beaupel, Fanny; Malerbi, Marion; Alcacer, Cristina; Tahiri, Khadija; Carpentier, Wassila; Wang, Chuansong; During, Matthew; Xu, Desheng; Worley, Paul F; Girault, Jean-Antoine; Herv, Denis; Corvol, Jean-Christophe

    2015-01-01

    In Parkinson's disease, long-term dopamine replacement therapy is complicated by the appearance of L-DOPA-induced dyskinesia (LID). One major hypothesis is that LID results from an aberrant transcriptional program in striatal neurons induced by L-DOPA and triggered by the activation of ERK. To identify these genes, we performed transcriptome analyses in the striatum in 6-hydroxydopamine-lesioned mice. A time course analysis (0-6 h after treatment with L-DOPA) identified an acute signature of 709 genes, among which genes involved in protein phosphatase activity were overrepresented, suggesting a negative feedback on ERK activation by l-DOPA. l-DOPA-dependent deregulation of 28 genes was blocked by pretreatment with SL327, an inhibitor of ERK activation, and 26 genes were found differentially expressed between highly and weakly dyskinetic animals after treatment with L-DOPA. The intersection list identified five genes: FosB, Th, Nptx2, Nedd4l, and Ccrn4l. Nptx2 encodes neuronal pentraxin II (or neuronal activity-regulated pentraxin, Narp), which is involved in the clustering of glutamate receptors. We confirmed increased Nptx2 expression after L-DOPA and its blockade by SL327 using quantitative RT-PCR in independent experiments. Using an escalating L-DOPA dose protocol, LID severity was decreased in Narp knock-out mice compared with their wild-type littermates or after overexpression of a dominant-negative form of Narp in the striatum. In conclusion, we have identified a molecular signature induced by L-DOPA in the dopamine-denervated striatum that is dependent on ERK and associated with LID. Here, we demonstrate the implication of one of these genes, Nptx2, in the development of LID. PMID:25568106

  17. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

    PubMed Central

    He, Xin; Sanders, Stephan J.; Liu, Li; De Rubeis, Silvia; Lim, Elaine T.; Sutcliffe, James S.; Schellenberg, Gerard D.; Gibbs, Richard A.; Daly, Mark J.; Buxbaum, Joseph D.; State, Matthew W.; Devlin, Bernie; Roeder, Kathryn

    2013-01-01

    De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support. PMID:23966865

  18. 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

  19. 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. PMID:26775695

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

    PubMed Central

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

    2013-01-01

    Alzheimer disease (AD) is a devastating neurodegenerative disease affecting more than five million Americans. In this study, we have used updated genetic linkage data from chromosome 10 in combination with expression data from serial analysis of gene expression to choose a new set of thirteen candidate genes for genetic analysis in late onset Alzheimer disease (LOAD). Results in this study identify the KIAA1462 locus as a candidate locus for LOAD in APOE4 carriers. Two genes exist at this locus, KIAA1462, a gene associated with coronary artery disease, and rokimi, encoding an untranslated spliced RNA The genetic architecture at this locus suggests that the gene product important in this association is either rokimi, or a different isoform of KIAA1462 than the isoform that is important in cardiovascular disease. Expression data suggests that isoform f of KIAA1462 is a more attractive candidate for association with LOAD in APOE4 carriers than rokimi which had no detectable expression in brain. PMID:24349219

  1. Molecular Characterization of Potato Disease Resistance Genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A key long-term management strategy for combating potato diseases is to develop cultivars with high levels of resistance through identification and integration of major resistance (R) genes. This talk will summarize our results of cloning and characterizing major late blight and Verticillium wilt R...

  2. 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+ Tcell count, are high. PMID:26790340

  3. COPD subtypes identified by network-based clustering of blood gene expression.

    PubMed

    Chang, Yale; Glass, Kimberly; Liu, Yang-Yu; Silverman, Edwin K; Crapo, James D; Tal-Singer, Ruth; Bowler, Russ; Dy, Jennifer; Cho, Michael; Castaldi, Peter

    2016-03-01

    One of the most common smoking-related diseases, chronic obstructive pulmonary disease (COPD), results from a dysregulated, multi-tissue inflammatory response to cigarette smoke. We hypothesized that systemic inflammatory signals in genome-wide blood gene expression can identify clinically important COPD-related disease subtypes, and we leveraged pre-existing gene interaction networks to guide unsupervised clustering of blood microarray expression data. Using network-informed non-negative matrix factorization, we analyzed genome-wide blood gene expression from 229 former smokers in the ECLIPSE Study, and we identified novel, clinically relevant molecular subtypes of COPD. These network-informed clusters were more stable and more strongly associated with measures of lung structure and function than clusters derived from a network-naïve approach, and they were associated with subtype-specific enrichment for inflammatory and protein catabolic pathways. These clusters were successfully reproduced in an independent sample of 135 smokers from the COPDGene Study. PMID:26773458

  4. The VPS35 gene and Parkinson's disease.

    PubMed

    Deng, Hao; Gao, Kai; Jankovic, Joseph

    2013-05-01

    Parkinson's disease (PD), the second most common age-related neurodegenerative disease, is characterized by loss of dopaminergic and nondopaminergic neurons, leading to a variety of motor and nonmotor symptoms. In addition to environmental factors, genetic predisposition and specific gene mutations have been shown to play an important role in the pathogenesis of this disorder. Recently, the identification of the vacuolar protein sorting 35 homolog gene (VPS35), linked to autosomal dominant late-onset PD, has provided new clues to the pathogenesis of PD. Here we discuss the VPS35 gene, its protein function, and various pathways involved in Wnt/?-catenin signaling and in the role of DMT1 mediating the uptake of iron and iron translocation from endosomes to the cytoplasm. Further understanding of these mechanisms will undoubtedly provide new insights into the pathogenic mechanisms of PD and may lead to prevention and better treatment of the disorder. PMID:23536430

  5. 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

  6. Analyse multiple disease subtypes and build associated gene networks using genome-wide expression profiles

    PubMed Central

    2015-01-01

    Background Despite the large increase of transcriptomic studies that look for gene signatures on diseases, there is still a need for integrative approaches that obtain separation of multiple pathological states providing robust selection of gene markers for each disease subtype and information about the possible links or relations between those genes. Results We present a network-oriented and data-driven bioinformatic approach that searches for association of genes and diseases based on the analysis of genome-wide expression data derived from microarrays or RNA-Seq studies. The approach aims to (i) identify gene sets associated to different pathological states analysed together; (ii) identify a minimum subset within these genes that unequivocally differentiates and classifies the compared disease subtypes; (iii) provide a measurement of the discriminant power of these genes and (iv) identify links between the genes that characterise each of the disease subtypes. This bioinformatic approach is implemented in an R package, named geNetClassifier, available as an open access tool in Bioconductor. To illustrate the performance of the tool, we applied it to two independent datasets: 250 samples from patients with four major leukemia subtypes analysed using expression arrays; another leukemia dataset analysed with RNA-Seq that includes a subtype also present in the previous set. The results show the selection of key deregulated genes recently reported in the literature and assigned to the leukemia subtypes studied. We also show, using these independent datasets, the selection of similar genes in a network built for the same disease subtype. Conclusions The construction of gene networks related to specific disease subtypes that include parameters such as gene-to-gene association, gene disease specificity and gene discriminant power can be very useful to draw gene-disease maps and to unravel the molecular features that characterize specific pathological states. The application of the bioinformatic tool here presented shows a neat way to achieve such molecular characterization of the diseases using genome-wide expression data. PMID:26040557

  7. A Systems Approach Identifies Networks and Genes Linking Sleep and Stress: Implications for Neuropsychiatric Disorders

    PubMed Central

    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

    2016-01-01

    SUMMARY Sleep dysfunction and stress susceptibility are co-morbid complex traits, which often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multi-level 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 the interplay between sleep, stress, and neuropathology emerge from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework to interrogate the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. PMID:25921536

  8. 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-?-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. PMID:25881898

  9. Genome-Wide Scan Informed by Age-Related Disease Identifies Loci for Exceptional Human Longevity

    PubMed Central

    Fortney, Kristen; Dobriban, Edgar; Garagnani, Paolo; Pirazzini, Chiara; Monti, Daniela; Mari, Daniela; Atzmon, Gil; Barzilai, Nir; Franceschi, Claudio; Owen, Art B.; Kim, Stuart K.

    2015-01-01

    We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related disease in order to narrow the search for SNPs associated with longevity. To gain support for our approach, we first show there is an overlap between loci involved in disease and loci associated with extreme longevity. These results indicate that several disease variants may be depleted in centenarians versus the general population. Next, we used iGWAS to harness information from 14 meta-analyses of disease and trait GWAS to identify longevity loci in two studies of long-lived humans. In a standard GWAS analysis, only one locus in these studies is significant (APOE/TOMM40) when controlling the false discovery rate (FDR) at 10%. With iGWAS, we identify eight genetic loci to associate significantly with exceptional human longevity at FDR < 10%. We followed up the eight lead SNPs in independent cohorts, and found replication evidence of four loci and suggestive evidence for one more with exceptional longevity. The loci that replicated (FDR < 5%) included APOE/TOMM40 (associated with Alzheimer’s disease), CDKN2B/ANRIL (implicated in the regulation of cellular senescence), ABO (tags the O blood group), and SH2B3/ATXN2 (a signaling gene that extends lifespan in Drosophila and a gene involved in neurological disease). Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits, including coronary artery disease and Alzheimer’s disease. iGWAS provides a new analytical strategy for uncovering SNPs that influence extreme longevity, and can be applied more broadly to boost power in other studies of complex phenotypes. PMID:26677855

  10. Genome-Wide Scan Informed by Age-Related Disease Identifies Loci for Exceptional Human Longevity.

    PubMed

    Fortney, Kristen; Dobriban, Edgar; Garagnani, Paolo; Pirazzini, Chiara; Monti, Daniela; Mari, Daniela; Atzmon, Gil; Barzilai, Nir; Franceschi, Claudio; Owen, Art B; Kim, Stuart K

    2015-12-01

    We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related disease in order to narrow the search for SNPs associated with longevity. To gain support for our approach, we first show there is an overlap between loci involved in disease and loci associated with extreme longevity. These results indicate that several disease variants may be depleted in centenarians versus the general population. Next, we used iGWAS to harness information from 14 meta-analyses of disease and trait GWAS to identify longevity loci in two studies of long-lived humans. In a standard GWAS analysis, only one locus in these studies is significant (APOE/TOMM40) when controlling the false discovery rate (FDR) at 10%. With iGWAS, we identify eight genetic loci to associate significantly with exceptional human longevity at FDR < 10%. We followed up the eight lead SNPs in independent cohorts, and found replication evidence of four loci and suggestive evidence for one more with exceptional longevity. The loci that replicated (FDR < 5%) included APOE/TOMM40 (associated with Alzheimer's disease), CDKN2B/ANRIL (implicated in the regulation of cellular senescence), ABO (tags the O blood group), and SH2B3/ATXN2 (a signaling gene that extends lifespan in Drosophila and a gene involved in neurological disease). Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits, including coronary artery disease and Alzheimer's disease. iGWAS provides a new analytical strategy for uncovering SNPs that influence extreme longevity, and can be applied more broadly to boost power in other studies of complex phenotypes. PMID:26677855

  11. Whole USH2A Gene Sequencing Identifies Several New Deep Intronic Mutations.

    PubMed

    Liquori, Alessandro; Vach, Christel; Baux, David; Blanchet, Catherine; Hamel, Christian; Malcolm, Sue; Koenig, Michel; Claustres, Mireille; Roux, Anne-Franoise

    2016-02-01

    Deep intronic mutations leading to pseudoexon (PE) insertions are underestimated and most of these splicing alterations have been identified by transcript analysis, for instance, the first deep intronic mutation in USH2A, the gene most frequently involved in Usher syndrome type II (USH2). Unfortunately, analyzing USH2A transcripts is challenging and for 1.8%-19% of USH2 individuals carrying a single USH2A recessive mutation, a second mutation is yet to be identified. We have developed and validated a DNA next-generation sequencing approach to identify deep intronic variants in USH2A and evaluated their consequences on splicing. Three distinct novel deep intronic mutations have been identified. All were predicted to affect splicing and resulted in the insertion of PEs, as shown by minigene assays. We present a new and attractive strategy to identify deep intronic mutations, when RNA analyses are not possible. Moreover, the bioinformatics pipeline developed is independent of the gene size, implying the possible application of this approach to any disease-linked gene. Finally, an antisense morpholino oligonucleotide tested in vitro for its ability to restore splicing caused by the c.9959-4159A>G mutation provided high inhibition rates, which are indicative of its potential for molecular therapy. PMID:26629787

  12. 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.

  13. Identifying biological themes within lists of genes with EASE

    PubMed Central

    Hosack, Douglas A; Dennis, Glynn; Sherman, Brad T; Lane, H Clifford; Lempicki, Richard A

    2003-01-01

    EASE is a customizable software application for rapid biological interpretation of gene lists that result from the analysis of microarray, proteomics, SAGE and other high-throughput genomic data. The biological themes returned by EASE recapitulate manually determined themes in previously published gene lists and are robust to varying methods of normalization, intensity calculation and statistical selection of genes. EASE is a powerful tool for rapidly converting the results of functional genomics studies from 'genes' to 'themes'. PMID:14519205

  14. Species-wide genetic incompatibility analysis identifies immune genes as hot spots of deleterious epistasis.

    PubMed

    Chae, Eunyoung; Bomblies, Kirsten; Kim, Sang-Tae; Karelina, Darya; Zaidem, Maricris; Ossowski, Stephan; Martn-Pizarro, Carmen; Laitinen, Roosa A E; Rowan, Beth A; Tenenboim, Hezi; Lechner, Sarah; Demar, Monika; Habring-Mller, Anette; Lanz, Christa; Rtsch, Gunnar; Weigel, Detlef

    2014-12-01

    Intraspecific genetic incompatibilities prevent the assembly of specific alleles into single genotypes and influence genome- and species-wide patterns of sequence variation. A common incompatibility in plants is hybrid necrosis, characterized by autoimmune responses due to epistatic interactions between natural genetic variants. By systematically testing thousands of F1 hybrids of Arabidopsis thaliana strains, we identified a small number of incompatibility hot spots in the genome, often in regions densely populated by nucleotide-binding domain and leucine-rich repeat (NLR) immune receptor genes. In several cases, these immune receptor loci interact with each other, suggestive of conflict within the immune system. A particularly dangerous locus is a highly variable cluster of NLR genes, DM2, which causes multiple independent incompatibilities with genes that encode a range of biochemical functions, including NLRs. Our findings suggest that deleterious interactions of immune receptors limit the combinations of favorable disease resistance alleles accessible to plant genomes. PMID:25467443

  15. Species-wide Genetic Incompatibility Analysis Identifies Immune Genes as Hotspots of Deleterious Epistasis

    PubMed Central

    Chae, Eunyoung; Bomblies, Kirsten; Kim, Sang-Tae; Karelina, Darya; Zaidem, Maricris; Ossowski, Stephan; Martn-Pizarro, Carmen; Laitinen, Roosa A. E.; Rowan, Beth A.; Tenenboim, Hezi; Lechner, Sarah; Demar, Monika; Habring-Mller, Anette; Lanz, Christa; Rtsch, Gunnar; Weigel, Detlef

    2014-01-01

    Summary Intraspecific genetic incompatibilities prevent the assembly of specific alleles into single genotypes and influence genome- and species-wide patterns of sequence variation. A common incompatibility in plants is hybrid necrosis, characterized by autoimmune responses due to epistatic interactions between natural genetic variants. By systematically testing thousands of F1 hybrids of Arabidopsis thaliana strains, we identified a small number of incompatibility hotspots in the genome, often in regions densely populated by NLR immune receptor genes. In several cases, these immune receptor loci interact with each other, suggestive of conflict within the immune system. A particularly dangerous locus is a highly variable cluster of NLR genes, DANGEROUS MIX2 (DM2), which causes multiple, independent incompatibilities with genes that encode a range of biochemical functions, including NLRs. Our findings suggest that deleterious interactions of immune receptors at the front lines of host-pathogen co-evolution limit the combinations of favorable disease resistance alleles accessible to plant genomes. PMID:25467443

  16. A New Strategy to Identify and Annotate Human RPE-Specific Gene Expression

    PubMed Central

    Booij, Judith C.; ten Brink, Jacoline B.; Swagemakers, Sigrid M. A.; Verkerk, Annemieke J. M. H.; Essing, Anke H. W.; van der Spek, Peter J.; Bergen, Arthur A. B.

    2010-01-01

    Background To identify and functionally annotate cell type-specific gene expression in the human retinal pigment epithelium (RPE), a key tissue involved in age-related macular degeneration and retinitis pigmentosa. Methodology RPE, photoreceptor and choroidal cells were isolated from selected freshly frozen healthy human donor eyes using laser microdissection. RNA isolation, amplification and hybridization to 44 k microarrays was carried out according to Agilent specifications. Bioinformatics was carried out using Rosetta Resolver, David and Ingenuity software. Principal Findings Our previous 22 k analysis of the RPE transcriptome showed that the RPE has high levels of protein synthesis, strong energy demands, is exposed to high levels of oxidative stress and a variable degree of inflammation. We currently use a complementary new strategy aimed at the identification and functional annotation of RPE-specific expressed transcripts. This strategy takes advantage of the multilayered cellular structure of the retina and overcomes a number of limitations of previous studies. In triplicate, we compared the transcriptomes of RPE, photoreceptor and choroidal cells and we deduced RPE specific expression. We identified at least 114 entries with RPE-specific gene expression. Thirty-nine of these 114 genes also show high expression in the RPE, comparison with the literature showed that 85% of these 39 were previously identified to be expressed in the RPE. In the group of 114 RPE specific genes there was an overrepresentation of genes involved in (membrane) transport, vision and ophthalmic disease. More fundamentally, we found RPE-specific involvement in the RAR-activation, retinol metabolism and GABA receptor signaling pathways. Conclusions In this study we provide a further specification and understanding of the RPE transcriptome by identifying and analyzing genes that are specifically expressed in the RPE. PMID:20479888

  17. 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. Evaluation of gene expression changes in different neurons suggests specific transcriptomic signature of single neurons during aging. PMID:24330282

  18. A systematic analysis of human disease-associated gene sequences in Drosophila melanogaster.

    PubMed

    Reiter, L T; Potocki, L; Chien, S; Gribskov, M; Bier, E

    2001-06-01

    We performed a systematic analysis of 929 human disease gene entries associated with at least one mutant allele in the Online Mendelian Inheritance in Man (OMIM) database against the recently completed genome sequence of Drosophila melanogaster. The results of this search have been formatted as an updateable and searchable on-line database called Homophila. Our analysis identified 714 distinct human disease genes (77% of disease genes searched) matching 548 unique Drosophila sequences, which we have summarized by disease category. This breakdown into disease classes creates a picture of disease genes that are amenable to study using Drosophila as the model organism. Of the 548 Drosophila genes related to human disease genes, 153 are associated with known mutant alleles and 56 more are tagged by P-element insertions in or near the gene. Examples of how to use the database to identify Drosophila genes related to human disease genes are presented. We anticipate that cross-genomic analysis of human disease genes using the power of Drosophila second-site modifier screens will promote interaction between human and Drosophila research groups, accelerating the understanding of the pathogenesis of human genetic disease. The Homophila database is available at http://homophila.sdsc.edu. PMID:11381037

  19. 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

  20. Gene Profiling of Mta1 Identifies Novel Gene Targets and Functions

    PubMed Central

    Eswaran, Jeyanthy; Kumar, Rakesh

    2011-01-01

    Background Metastasis-associated protein 1 (MTA1), a master dual co-regulatory protein is found to be an integral part of NuRD (Nucleosome Remodeling and Histone Deacetylation) complex, which has indispensable transcriptional regulatory functions via histone deacetylation and chromatin remodeling. Emerging literature establishes MTA1 to be a valid DNA-damage responsive protein with a significant role in maintaining the optimum DNA-repair activity in mammalian cells exposed to genotoxic stress. This DNA-damage responsive function of MTA1 was reported to be a P53-dependent and independent function. Here, we investigate the influence of P53 on gene regulation function of Mta1 to identify novel gene targets and functions of Mta1. Methods Gene expression analysis was performed on five different mouse embryonic fibroblasts (MEFs) samples (i) the Mta1 wild type, (ii) Mta1 knock out (iii) Mta1 knock out in which Mta1 was reintroduced (iv) P53 knock out (v) P53 knock out in which Mta1 was over expressed using Affymetrix Mouse Exon 1.0 ST arrays. Further Hierarchical Clustering, Gene Ontology analysis with GO terms satisfying corrected p-value<0.1, and the Ingenuity Pathway Analysis were performed. Finally, RT-qPCR was carried out on selective candidate genes. Significance/Conclusion This study represents a complete genome wide screen for possible target genes of a coregulator, Mta1. The comparative gene profiling of Mta1 wild type, Mta1 knockout and Mta1 re-expression in the Mta1 knockout conditions define “bona fide” Mta1 target genes. Further extensive analyses of the data highlights the influence of P53 on Mta1 gene regulation. In the presence of P53 majority of the genes regulated by Mta1 are related to inflammatory and anti-microbial responses whereas in the absence of P53 the predominant target genes are involved in cancer signaling. Thus, the presented data emphasizes the known functions of Mta1 and serves as a rich resource which could help us identify novel Mta1 functions. PMID:21364872

  1. 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

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

    PubMed Central

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

    2012-01-01

    Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n = 197, temporal cortex n = 202) and with other brain pathologies (non–AD, cerebellar n = 177, temporal cortex n = 197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ±100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non–ADs (q<0.05, p = 7.70×10−5–1.67×10−82). Of these, 2,089 were also significant in the temporal cortex (p = 1.85×10−5–1.70×10−141). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10−6). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinson's disease (PD) MMRN1/rs6532197, Paget's disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9–3.3 fold enrichment (p<10−6) of significant cisSNPs with suggestive AD–risk association (p<10−3) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non–CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics. PMID:22685416

  3. Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants.

    PubMed

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

    2012-01-01

    Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n=197, temporal cortex n=202) and with other brain pathologies (non-AD, cerebellar n=177, temporal cortex n=197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ± 100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non-ADs (q<0.05, p=7.70 × 10(-5)-1.67 × 10(-82)). Of these, 2,089 were also significant in the temporal cortex (p=1.85 × 10(-5)-1.70 × 10(-141)). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10(-6)). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinson's disease (PD) MMRN1/rs6532197, Paget's disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9-3.3 fold enrichment (p<10(-6)) of significant cisSNPs with suggestive AD-risk association (p<10(-3)) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non-CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics. PMID:22685416

  4. Integrating genomic and epigenomic information: a promising strategy for identifying functional DNA variants of human disease.

    PubMed

    Zaina, S; Lund, G

    2012-04-01

    In a clinical setting diagnosis, heritability, risk and outcome of human disease rely heavily on the use of markers present in specific tissues. In the past decade, the development of genome-wide, non-hypothesis driven methods to identify molecular markers associated with disease have led to the discovery of numerous genetic variations associated with specific human diseases, the majority of which map within non-coding regions of the genome. In parallel, whole-genome studies focused on the role of gene regulatory epigenetic modifications such as DNA methylation and histone modifications are providing a conceptual framework for understanding the functional significance of sequence variation in human disease. This review highlights selected recent development in epigenetics and discusses their implications with respect to the identification of functional or novel single nucleotide polymorphisms. PMID:22292420

  5. 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

  6. 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. PMID:24747070

  7. 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

  8. GWAS identifies novel SLE susceptibility genes and explains the association of the HLA region.

    PubMed

    Armstrong, D L; Zidovetzki, R; Alarcón-Riquelme, M E; Tsao, B P; Criswell, L A; Kimberly, R P; Harley, J B; Sivils, K L; Vyse, T J; Gaffney, P M; Langefeld, C D; Jacob, C O

    2014-09-01

    In a genome-wide association study (GWAS) of individuals of European ancestry afflicted with systemic lupus erythematosus (SLE) the extensive utilization of imputation, step-wise multiple regression, lasso regularization and increasing study power by utilizing false discovery rate instead of a Bonferroni multiple test correction enabled us to identify 13 novel non-human leukocyte antigen (HLA) genes and confirmed the association of four genes previously reported to be associated. Novel genes associated with SLE susceptibility included two transcription factors (EHF and MED1), two components of the NF-κB pathway (RASSF2 and RNF114), one gene involved in adhesion and endothelial migration (CNTN6) and two genes involved in antigen presentation (BIN1 and SEC61G). In addition, the strongly significant association of multiple single-nucleotide polymorphisms (SNPs) in the HLA region was assigned to HLA alleles and serotypes and deconvoluted into four primary signals. The novel SLE-associated genes point to new directions for both the diagnosis and treatment of this debilitating autoimmune disease. PMID:24871463

  9. Analysis of the retinal gene expression profile after hypoxic preconditioning identifies candidate genes for neuroprotection

    PubMed Central

    Thiersch, Markus; Raffelsberger, Wolfgang; Frigg, Rico; Samardzija, Marijana; Wenzel, Andreas; Poch, Olivier; Grimm, Christian

    2008-01-01

    Background Retinal degeneration is a main cause of blindness in humans. Neuroprotective therapies may be used to rescue retinal cells and preserve vision. Hypoxic preconditioning stabilizes the transcription factor HIF-1? in the retina and strongly protects photoreceptors in an animal model of light-induced retinal degeneration. To address the molecular mechanisms of the protection, we analyzed the transcriptome of the hypoxic retina using microarrays and real-time PCR. Results Hypoxic exposure induced a marked alteration in the retinal transcriptome with significantly different expression levels of 431 genes immediately after hypoxic exposure. The normal expression profile was restored within 16 hours of reoxygenation. Among the differentially regulated genes, several candidates for neuroprotection were identified like metallothionein-1 and -2, the HIF-1 target gene adrenomedullin and the gene encoding the antioxidative and cytoprotective enzyme paraoxonase 1 which was previously not known to be a hypoxia responsive gene in the retina. The strongly upregulated cyclin dependent kinase inhibitor p21 was excluded from being essential for neuroprotection. Conclusion Our data suggest that neuroprotection after hypoxic preconditioning is the result of the differential expression of a multitude of genes which may act in concert to protect visual cells against a toxic insult. PMID:18261226

  10. Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs

    PubMed Central

    2011-01-01

    Background Differential coexpression analysis (DCEA) is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links). Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D) expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum. PMID:21806838

  11. Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci

    PubMed Central

    Miller, Clint; Pjanic, Milos; Castano, Victor G.; Kim, Juyong B.; Salfati, Elias L.; Kundaje, Anshul B.; Bejerano, Gill; Assimes, Themistocles; Yang, Xia; Quertermous, Thomas

    2015-01-01

    To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including “growth factor binding,” “matrix interaction,” and “smooth muscle contraction.” We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology. PMID:26020271

  12. Analysis of the Robustness of Network-Based Disease-Gene Prioritization Methods Reveals Redundancy in the Human Interactome and Functional Diversity of Disease-Genes

    PubMed Central

    Guney, Emre; Oliva, Baldo

    2014-01-01

    Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO) analysis highlighted the role of functional diversity for such diseases. PMID:24733074

  13. 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

  14. Network-based prediction and knowledge mining of disease genes

    PubMed Central

    2015-01-01

    Background In recent years, high-throughput protein interaction identification methods have generated a large amount of data. When combined with the results from other in vivo and in vitro experiments, a complex set of relationships between biological molecules emerges. The growing popularity of network analysis and data mining has allowed researchers to recognize indirect connections between these molecules. Due to the interdependent nature of network entities, evaluating proteins in this context can reveal relationships that may not otherwise be evident. Methods We examined the human protein interaction network as it relates to human illness using the Disease Ontology. After calculating several topological metrics, we trained an alternating decision tree (ADTree) classifier to identify disease-associated proteins. Using a bootstrapping method, we created a tree to highlight conserved characteristics shared by many of these proteins. Subsequently, we reviewed a set of non-disease-associated proteins that were misclassified by the algorithm with high confidence and searched for evidence of a disease relationship. Results Our classifier was able to predict disease-related genes with 79% area under the receiver operating characteristic (ROC) curve (AUC), which indicates the tradeoff between sensitivity and specificity and is a good predictor of how a classifier will perform on future data sets. We found that a combination of several network characteristics including degree centrality, disease neighbor ratio, eccentricity, and neighborhood connectivity help to distinguish between disease- and non-disease-related proteins. Furthermore, the ADTree allowed us to understand which combinations of strongly predictive attributes contributed most to protein-disease classification. In our post-processing evaluation, we found several examples of potential novel disease-related proteins and corresponding literature evidence. In addition, we showed that first- and second-order neighbors in the PPI network could be used to identify likely disease associations. Conclusions We analyzed the human protein interaction network and its relationship to disease and found that both the number of interactions with other proteins and the disease relationship of neighboring proteins helped to determine whether a protein had a relationship to disease. Our classifier predicted many proteins with no annotated disease association to be disease-related, which indicated that these proteins have network characteristics that are similar to disease-related proteins and may therefore have disease associations not previously identified. By performing a post-processing step after the prediction, we were able to identify evidence in literature supporting this possibility. This method could provide a useful filter for experimentalists searching for new candidate protein targets for drug repositioning and could also be extended to include other network and data types in order to refine these predictions. PMID:26043920

  15. Hyperoxia-induced neurodegeneration as a tool to identify neuroprotective genes in Drosophila melanogaster.

    PubMed

    Gruenewald, Christoph; Botella, Jose A; Bayersdorfer, Florian; Navarro, Juan A; Schneuwly, Stephan

    2009-06-15

    Oxidative stress has been reported to be a common underlying mechanism in the pathogenesis of many neurodegenerative disorders such as Alzheimer, Huntington, Creutzfeld-Jakob, and Parkinson disease. Despite the increasing number of articles showing a correlation between oxidative damage and neurodegeneration little is known about the genetic elements that confer protection against the deleterious effects of an oxidative imbalance in neurons. We show that oxygen-induced damage is a direct cause of brain degeneration in Drosophila and establish an experimental setup measuring dopaminergic neuron survival to model oxidative stress-induced neurodegeneration in flies. The overexpression of superoxide dismutase but not catalase was able to protect dopaminergic neurons against oxidative imbalance under hyperoxia treatment. In an effort to identify new genes involved in the process of oxidative stress-induced neurodegeneration, we have carried out a genome-wide expression analysis to identify genes whose expression is upregulated in fly heads under hyperoxia. Among them, a number of mitochondrial and cytoplasmic chaperones could be identified and were shown to protect dopaminergic neurons when overexpressed, thus validating our approach to identifying new genes involved in the neuronal defense mechanism against oxidative stress. PMID:19345730

  16. A Genome-Wide Association Study Identifies Novel and Functionally Related Susceptibility Loci for Kawasaki Disease

    PubMed Central

    Breunis, Willemijn B.; Ng, Sarah B.; Li, Yi; Bonnard, Carine; Ling, Ling; Wright, Victoria J.; Thalamuthu, Anbupalam; Odam, Miranda; Shimizu, Chisato; Burns, Jane C.; Levin, Michael; Kuijpers, Taco W.; Hibberd, Martin L.

    2009-01-01

    Kawasaki disease (KD) is a pediatric vasculitis that damages the coronary arteries in 25% of untreated and approximately 5% of treated children. Epidemiologic data suggest that KD is triggered by unidentified infection(s) in genetically susceptible children. To investigate genetic determinants of KD susceptibility, we performed a genome-wide association study (GWAS) in 119 Caucasian KD cases and 135 matched controls with stringent correction for possible admixture, followed by replication in an independent cohort and subsequent fine-mapping, for a total of 893 KD cases plus population and family controls. Significant associations of 40 SNPs and six haplotypes, identifying 31 genes, were replicated in an independent cohort of 583 predominantly Caucasian KD families, with NAALADL2 (rs17531088, pcombined?=?1.1310?6) and ZFHX3 (rs7199343, pcombined?=?2.3710?6) most significantly associated. Sixteen associated variants with a minor allele frequency of >0.05 that lay within or close to known genes were fine-mapped with HapMap tagging SNPs in 781 KD cases, including 590 from the discovery and replication stages. Original or tagging SNPs in eight of these genes replicated the original findings, with seven genes having further significant markers in adjacent regions. In four genes (ZFHX3, NAALADL2, PPP1R14C, and TCP1), the neighboring markers were more significantly associated than the originally associated variants. Investigation of functional relationships between the eight fine-mapped genes using Ingenuity Pathway Analysis identified a single functional network (p?=?10?13) containing five fine-mapped genesLNX1, CAMK2D, ZFHX3, CSMD1, and TCP1with functional relationships potentially related to inflammation, apoptosis, and cardiovascular pathology. Pair-wise blood transcript levels were measured during acute and convalescent KD for all fine-mapped genes, revealing a consistent trend of significantly reduced transcript levels prior to treatment. This is one of the first GWAS in an infectious disease. We have identified novel, plausible, and functionally related variants associated with KD susceptibility that may also be relevant to other cardiovascular diseases. PMID:19132087

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

    PubMed Central

    2014-01-01

    Background Copper is essential for the survival of aerobic organisms. If copper is not properly regulated in the body however, it can be extremely cytotoxic and genetic mutations that compromise copper homeostasis result in severe clinical phenotypes. Understanding how cells maintain optimal copper levels is therefore highly relevant to human health. Results We found that addition of copper (Cu) to culture medium leads to increased respiratory growth of yeast, a phenotype which we then systematically and quantitatively measured in 5050 homozygous diploid deletion strains. Cus positive effect on respiratory growth was quantitatively reduced in deletion strains representing 73 different genes, the function of which identify increased iron uptake as a cause of the increase in growth rate. Conversely, these effects were enhanced in strains representing 93 genes. Many of these strains exhibited respiratory defects that were specifically rescued by supplementing the growth medium with Cu. Among the genes identified are known and direct regulators of copper homeostasis, genes required to maintain low vacuolar pH, and genes where evidence supporting a functional link with Cu has been heretofore lacking. Roughly half of the genes are conserved in man, and several of these are associated with Mendelian disorders, including the Cu-imbalance syndromes Menkes and Wilsons disease. We additionally demonstrate that pharmacological agents, including the approved drug disulfiram, can rescue Cu-deficiencies of both environmental and genetic origin. Conclusions A functional screen in yeast has expanded the list of genes required for Cu-dependent fitness, revealing a complex cellular system with implications for human health. Respiratory fitness defects arising from perturbations in this system can be corrected with pharmacological agents that increase intracellular copper concentrations. PMID:24708151

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

    PubMed Central

    Szsz, Andrs; Tubak, Vilmos; Kemny, Lajos; Kondorosi, va; Nagy, Istvn

    2013-01-01

    Activation of dendritic cells by different pathogens induces the secretion of proinflammatory mediators resulting in local inflammation. Importantly, innate immunity must be properly controlled, as its continuous activation leads to the development of chronic inflammatory diseases such as psoriasis. Lipopolysaccharide (LPS) or peptidoglycan (PGN) induced tolerance, a phenomenon of transient unresponsiveness of cells to repeated or prolonged stimulation, proved valuable model for the study of chronic inflammation. Thus, the aim of this study was the identification of the transcriptional diversity of primary human immature dendritic cells (iDCs) upon PGN induced tolerance. Using SAGE-Seq approach, a tag-based transcriptome sequencing method, we investigated gene expression changes of primary human iDCs upon stimulation or restimulation with Staphylococcus aureus derived PGN, a widely used TLR2 ligand. Based on the expression pattern of the altered genes, we identified non-tolerizeable and tolerizeable genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (Kegg) analysis showed marked enrichment of immune-, cell cycle- and apoptosis related genes. In parallel to the marked induction of proinflammatory mediators, negative feedback regulators of innate immunity, such as TNFAIP3, TNFAIP8, Tyro3 and Mer are markedly downregulated in tolerant cells. We also demonstrate, that the expression pattern of TNFAIP3 and TNFAIP8 is altered in both lesional, and non-lesional skin of psoriatic patients. Finally, we show that pretreatment of immature dendritic cells with anti-TNF-? inhibits the expression of IL-6 and CCL1 in tolerant iDCs and partially releases the suppression of TNFAIP8. Our findings suggest that after PGN stimulation/restimulation the host cell utilizes different mechanisms in order to maintain critical balance between inflammation and tolerance. Importantly, the transcriptome sequencing of stimulated/restimulated iDCs identified numerous genes with altered expression to date not associated with role in chronic inflammation, underlying the relevance of our in vitro model for further characterization of IFN-primed iDCs. PMID:24039940

  19. 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...

  20. Gene Expression in Human Hippocampus from Cocaine Abusers Identifies Genes which Regulate Extracellular Matrix Remodeling

    PubMed Central

    Mash, Deborah C.; ffrench-Mullen, Jarlath; Adi, Nikhil; Qin, Yujing; Buck, Andrew; Pablo, John

    2007-01-01

    The chronic effects of cocaine abuse on brain structure and function are blamed for the inability of most addicts to remain abstinent. Part of the difficulty in preventing relapse is the persisting memory of the intense euphoria or cocaine “rush”. Most abused drugs and alcohol induce neuroplastic changes in brain pathways subserving emotion and cognition. Such changes may account for the consolidation and structural reconfiguration of synaptic connections with exposure to cocaine. Adaptive hippocampal plasticity could be related to specific patterns of gene expression with chronic cocaine abuse. Here, we compare gene expression profiles in the human hippocampus from cocaine addicts and age-matched drug-free control subjects. Cocaine abusers had 151 gene transcripts upregulated, while 91 gene transcripts were downregulated. Topping the list of cocaine-regulated transcripts was RECK in the human hippocampus (FC = 2.0; p<0.05). RECK is a membrane-anchored MMP inhibitor that is implicated in the coordinated regulation of extracellular matrix integrity and angiogenesis. In keeping with elevated RECK expression, active MMP9 protein levels were decreased in the hippocampus from cocaine abusers. Pathway analysis identified other genes regulated by cocaine that code for proteins involved in the remodeling of the cytomatrix and synaptic connections and the inhibition of blood vessel proliferation (PCDH8, LAMB1, ITGB6, CTGF and EphB4). The observed microarray phenotype in the human hippocampus identified RECK and other region-specific genes that may promote long-lasting structural changes with repeated cocaine abuse. Extracellular matrix remodeling in the hippocampus may be a persisting effect of chronic abuse that contributes to the compulsive and relapsing nature of cocaine addiction. PMID:18000554

  1. 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.

  2. 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

  3. Comparative and Functional Genomics in Identifying Aflatoxin Biosynthetic Genes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Identification of genes involved in aflatoxin biosynthesis through Aspergillus flavus genomics has been actively pursued. A. flavus Expressed Sequence Tags (ESTs) and whole genome sequencing have been completed. Groups of genes that are potentially involved in aflatoxin production have been profi...

  4. 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

  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. Mutation skew in genes identified by genome-wide association study of hypertriglyceridemia

    PubMed Central

    Johansen, Christopher T.; Wang, Jian; Lanktree, Matthew B.; Cao, Henian; McIntyre, Adam D.; Ban, Matthew R.; Martins, Rebecca A.; Kennedy, Brooke A.; Hassell, Reina G.; Visser, Maartje E.; Schwartz, Stephen M.; Voight, Benjamin F.; Elosua, Roberto; Salomaa, Veikko; O'Donnell, Christopher J.; Dallinga-Thie, Geesje M.; Anand, Sonia S.; Yusuf, Salim; Huff, Murray W.; Kathiresan, Sekar; Hegele, Robert A.

    2010-01-01

    Genome-wide association studies (GWAS) have replicably identified multiple loci associated with population-based plasma lipid concentrations1-5. Common genetic variants at these loci together explain <10% of the total variation of each lipid trait4,5. Rare variants of individually large effect may contribute additionally to the missing heritability of lipid traits6,7, however it remains to be shown to what extent rare variants will affect lipid phenotypes. Here, we demonstrate a significant accumulation of rare variants in GWAS-identified genes in patients with an extreme phenotype of abnormal plasma triglyceride (TG) metabolism. A GWAS of hypertriglyceridemia (HTG) patients revealed that common variants in APOA5, GCKR, LPL and APOB genes were associated with the HTG phenotype at genome-wide significance. We subsequently resequenced protein coding regions of these genes and found a significant burden of 154 rare missense or nonsense variants in 438 HTG patients, in contrast to 53 variants in 327 controls (P=6.2X10-8); this corresponds to a carrier frequency of 28.1% of HTG patients and 15.3% of controls (P=2.6X10-5). Many rare variants were predicted in silico to have compromised function; additionally some had previously demonstrated dysfunctionality in vitro. Rare variants in these 4 genes explained 1.1% of total variation in HTG diagnoses. Our study demonstrates a marked mutation skew that likely contributes to disease pathophysiology in patients with HTG. PMID:20657596

  7. 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. PMID:26870082

  8. 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. PMID:26375510

  9. 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

  10. Identifying A?-specific pathogenic mechanisms using a nematode model of Alzheimer's disease.

    PubMed

    Hassan, Wail M; Dostal, Vishantie; Huemann, Brady N; Yerg, John E; Link, Christopher D

    2015-02-01

    Multiple gene expression alterations have been linked to Alzheimer's disease (AD), implicating multiple metabolic pathways in its pathogenesis. However, a clear distinction between AD-specific gene expression changes and those resulting from nonspecific responses to toxic aggregating proteins has not been made. We investigated alterations in gene expression induced by human beta-amyloid peptide (A?) in a Caenorhabditis elegans AD model. A?-induced gene expression alterations were compared with those caused by a synthetic aggregating protein to identify A?-specific effects. Both A?-specific and nonspecific alterations were observed. Among A?-specific genes were those involved in aging, proteasome function, and mitochondrial function. An intriguing observation was the significant overlap between gene expression changes induced by A? and those induced by Cry5B, a bacterial pore-forming toxin. This led us to hypothesize that A? exerts its toxic effect, at least in part, by causing damage to biological membranes. We provide in vivo evidence consistent with this hypothesis. This study distinguishes between A?-specific and nonspecific mechanisms and provides potential targets for therapeutics discovery. PMID:25457027

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

    PubMed Central

    2012-01-01

    Background High throughput experiments resulted in many genomic datasets and hundreds of candidate disease genes. To discover the real disease genes from a set of candidate genes, computational methods have been proposed and worked on various types of genomic data sources. As a single source of genomic data is prone of bias, incompleteness and noise, integration of different genomic data sources is highly demanded to accomplish reliable disease gene identification. Results In contrast to the commonly adapted data integration approach which integrates separate lists of candidate genes derived from the each single data sources, we merge various genomic networks into a multigraph which is capable of connecting multiple edges between a pair of nodes. This novel approach provides a data platform with strong noise tolerance to prioritize the disease genes. A new idea of random walk is then developed to work on multigraphs using a modified step to calculate the transition matrix. Our method is further enhanced to deal with heterogeneous data types by allowing cross-walk between phenotype and gene networks. Compared on benchmark datasets, our method is shown to be more accurate than the state-of-the-art methods in disease gene identification. We also conducted a case study to identify disease genes for Insulin-Dependent Diabetes Mellitus. Some of the newly identified disease genes are supported by recently published literature. Conclusions The proposed RWRM (Random Walk with Restart on Multigraphs) model and CHN (Complex Heterogeneous Network) model are effective in data integration for candidate gene prioritization. PMID:23282070

  12. 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 CO? 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

  13. 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

  14. Methods to identify and analyze gene products involved in neuronal intracellular transport using Drosophila.

    PubMed

    Neisch, Amanda L; Avery, Adam W; Machamer, James B; Li, Min-Gang; Hays, Thomas S

    2016-01-01

    Proper neuronal function critically depends on efficient intracellular transport and disruption of transport leads to neurodegeneration. Molecular pathways that support or regulate neuronal transport are not fully understood. A greater understanding of these pathways will help reveal the pathological mechanisms underlying disease. Drosophila melanogaster is the premier model system for performing large-scale genetic functional screens. Here we describe methods to carry out primary and secondary genetic screens in Drosophila aimed at identifying novel gene products and pathways that impact neuronal intracellular transport. These screens are performed using whole animal or live cell imaging of intact neural tissue to ensure integrity of neurons and their cellular environment. The primary screen is used to identify gross defects in neuronal function indicative of a disruption in microtubule-based transport. The secondary screens, conducted in both motoneurons and dendritic arborization neurons, will confirm the function of candidate gene products in intracellular transport. Together, the methodologies described here will support labs interested in identifying and characterizing gene products that alter intracellular transport in Drosophila. PMID:26794520

  15. Identifying autism loci and genes by tracing recent shared ancestry.

    PubMed

    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

    2008-07-11

    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

  16. 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

  17. Antioxidant Enzyme Gene Transfer for Ischemic Diseases

    PubMed Central

    Wu, Jian; Hecker, James G.; Chiamvimonvat, Nipavan

    2009-01-01

    The balance of redox is pivotal for normal function and integrity of tissues. Ischemic insults occur as results of a variety of conditions, leading to an accumulation of reactive oxygen species (ROS) and an imbalanced redox status in the tissues. The oxidant stress may activate signaling mechanisms provoking more toxic events, and eventually cause tissue damage. Therefore, treatments with antioxidants, free radical scavengers and their mimetics, as well as gene transfer approaches to overexpress antioxidant genes represent potential therapeutic options to correct the redox imbalance. Among them, antioxidant gene transfer may enhance the production of antioxidant scavengers, and has been employed to experimentally prevent or treat ischemic injury in cardiovascular, pulmonary, hepatic, intestinal, central nervous or other systems in animal models. With improvements in vector systems and delivery approaches, innovative antioxidant gene therapy has conferred better outcomes for myocardial infarction, reduced restenosis after coronary angioplasty, improved the quality and function of liver grafts, as well as outcome of intestinal and cerebral ischemic attacks. However, it is crucial to be mindful that like other therapeutic armentarium, the efficacy of antioxidant gene transfer requires extensive preclinical investigation before it can be used in patients, and that it may have unanticipated short- or long-term adverse effects. Thus, it is critical to balance between the therapeutic benefits and potential risks, to develop disease-specific antioxidant gene transfer strategies, to deliver the therapy with an optimal time window and in a safe manner. This review attempts to provide the rationale, the most effective approaches and the potential hurdles of available antioxidant gene transfer approaches for ischemic injury in various organs, as well as the possible directions of future preclinical and clinical investigations of this highly promising therapeutic modality. PMID:19233238

  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. Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

    PubMed

    Clarke, Luka A; Botelho, Hugo M; Sousa, Lisete; Falcao, Andre O; Amaral, Margarida D

    2015-11-01

    A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease. PMID:26225835

  20. 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; Celedn, 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 ? 10g/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

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

    PubMed Central

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

    2014-01-01

    Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets. Here we introduce our Yeast Augmented Network Analysis (YANA) approach and test it with the X-linked spinal muscular atrophy (SMA) disease gene UBA1.First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish) SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases. PMID:25075304

  2. 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...

  3. Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimers 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 Alzheimers disease. The integrated analysis of this gene signature allowed us to identify the protein traffic vesicles as prominent players in the pathogenesis of Alzheimers. Considering the distances and complexity of protein trafficking in neurons, it is plausible that spontaneous protein misfolding along with a shortage of growth stimulation result in neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis have been discussed, with an emphasis on the protective effects of AT-1 mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Alignment with emerging literature confirmed many predictions derived from early-stage Alzheimers disease CDM. Conclusions A flexible approach for high-throughput data analysis, the Compact Disease Model generation, allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses. PMID:24196233

  4. 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

  5. Evaluation of an efficient approach for identifying genetic disease loci

    SciTech Connect

    Sheffield, V.C.; Kwitek-Black, A.E.; Rokhlina, T.

    1994-09-01

    Identification of disease loci by genetic linkage analysis has been enhanced by the availability of highly polymorphic short tandem repeat polymorphic markers (STRPs). The development of high quality tri- and tetranucleotide STRPs allows new strategies to increase the efficiency of genotyping resulting in streamlined linkage studies. We have tested a strategy using pooled DNA samples from affected individuals from large Bedouin pedigrees segregating recessive disorders. Equal molar amounts of DNA from affected individuals are pooled and used as a template for PCR of STRPs. Pooled DNA from unaffected siblings are used as controls. STRPS linked to the disorder show a shift in allele frequency in the affected compared to the control pool, whereas unlinked markers show an identical allele distribution in affected and control pools. We have demonstrated the sensitivity of this approach for identifying STRPs giving positive lod scores in recessive kindreds. We have also modelled this approach with dominant pedigrees. Application of this approach to polygenic disorders should be possible by using methods to quantitate allele frequencies in pooled samples. The high quality tri- and tetranucleotide repeat markers developed by the Cooperative Human Linkage Center (CHLC) facilitate the use of this method.

  6. 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 mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes. PMID:19390613

  7. 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; Rodrguez, Mara A.; Corbera, Joan; Muntoni, Francesco; Feng, Lucy; Rivas, Eloy; Torner, Ferran; Gualandi, Francesca; Gomez-Foix, Anna M.; Ferrer, Anna; Ortez, Carlos; Nascimento, Andrs; 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

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

    PubMed

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

    2013-01-01

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

  9. An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

    PubMed Central

    Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

    2013-01-01

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

  10. Gene expression profiling identifies molecular pathways associated with collagen VI deficiency and provides novel therapeutic targets.

    PubMed

    Paco, Sonia; Kalko, Susana G; Jou, Cristina; Rodrguez, Mara A; Corbera, Joan; Muntoni, Francesco; Feng, Lucy; Rivas, Eloy; Torner, Ferran; Gualandi, Francesca; Gomez-Foix, Anna M; Ferrer, Anna; Ortez, Carlos; Nascimento, Andrs; 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

  11. Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies

    PubMed Central

    Ortutay, Csaba; Vihinen, Mauno

    2009-01-01

    Disease gene identification is still a challenge despite modern high-throughput methods. Many diseases are very rare or lethal and thus cannot be investigated with traditional methods. Several in silico methods have been developed but they have some limitations. We introduce a new method that combines information about protein-interaction network properties and Gene Ontology terms. Genes with high-calculated network scores and statistically significant gene ontology terms based on known diseases are prioritized as candidate genes. The method was applied to identify novel primary immunodeficiency-related genes, 26 of which were found. The investigation uses the protein-interaction network for all essential immunome human genes available in the Immunome Knowledge Base and an analysis of their enriched gene ontology annotations. The identified disease gene candidates are mainly involved in cellular signaling including receptors, protein kinases and adaptor and binding proteins as well as enzymes. The method can be generalized for any disease group with sufficient information. PMID:19073697

  12. Identifying genetic determinants of host resistance to Marek's disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek's disease (MD) is a contagious disease of poultry induced by an alpha-herpesvirus known as Marek's disease virus (MDV). MD has been controlled by vaccination since the 1970s but it remains a serious potential threat to the world poultry industry since: 1) commercial poultry populations at larg...

  13. Chromatin Signature Identifies Monoallelic Gene Expression Across Mammalian Cell Types

    PubMed Central

    Nag, Anwesha; Vigneau, Sbastien; Savova, Virginia; Zwemer, Lillian M.; Gimelbrant, Alexander A.

    2015-01-01

    Monoallelic expression of autosomal genes (MAE) is a widespread epigenetic phenomenon which is poorly understood, due in part to current limitations of genome-wide approaches for assessing it. Recently, we reported that a specific histone modification signature is strongly associated with MAE and demonstrated that it can serve as a proxy of MAE in human lymphoblastoid cells. Here, we use murine cells to establish that this chromatin signature is conserved between mouse and human and is associated with MAE in multiple cell types. Our analyses reveal extensive conservation in the identity of MAE genes between the two species. By analyzing MAE chromatin signature in a large number of cell and tissue types, we show that it remains consistent during terminal cell differentiation and is predominant among cell-type specific genes, suggesting a link between MAE and specification of cell identity. PMID:26092837

  14. 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.

  15. Gene therapy for degenerative disc disease.

    PubMed

    Sobajima, S; Kim, J S; Gilbertson, L G; Kang, J D

    2004-02-01

    Degenerative disc disease (DDD) is a chronic process that can become clinically manifest in multiple disorders such as idiopathic low back pain, disc herniation, radiculopathy, myelopathy, and spinal stenosis. The limited available technology for the treatment of these and other pathologic and disabling conditions arising from DDD is highly invasive (eg, surgical discectomy and fusion), manifesting a certain degree of complications and unsatisfactory clinical outcomes. Although the precise pathophysiology of DDD remains to be clearly delineated, the progressive decline in aggrecan, the primary proteoglycan of the nucleus pulposus, appears to be a final common pathway. It has been hypothesized that imbalance in the synthesis and catabolism of certain critical extracellular matrix components can be mitigated by the transfer of genes to intervertebral disc cells encoding factors that modulate synthesis and catabolism of these components. The successful in vivo transfer of therapeutic genes to target cells within the intervertebral disc in clinically relevant animal models of DDD is one example of the rapid progress that is being made towards the development of gene therapy approaches for the treatment of DDD. This chapter reviews the ability of gene therapy to alter biologic processes in the degenerated intervertebral disc and outlines the work needed to be done before human clinical trials can be contemplated. PMID:14724681

  16. Gene expression profiling in autoimmune non-infectious uveitis disease

    PubMed Central

    Li, Zhuqing; Liu, Baoying; Arvydas, Maminishkis; Mahesh, Sankaranarayana P.; Yeh, Steven; Lew, Julie; Lim, Wee Kiak; Sen, H. Nida; Clarke, Grace; Buggage, Ronald; Miller, Sheldon S.; Nussenblatt., Robert B.

    2008-01-01

    Non-infectious uveitis is a predominantly T cell mediated autoimmune, intraocular inflammatory disease. To characterize the gene expression profile from patients with non-infectious uveitis, peripheral blood mononuclear cells (PBMCs) were isolated from 50 patients with clinically characterized non-infectious uveitis syndrome. A pathway-specific cDNA microarray was used for gene expression profiling and real time PCR array for further confirmation. Sixty-seven inflammation and autoimmune associated genes were found differentially expressed in uveitis patients with twenty-eight of those genes being validated by real-time PCR. Several genes previously unknown for autoimmune uveitis, including IL-22, IL-19, IL-20 and IL-25/IL-17E, were found to be highly expressed among uveitis patients compared to the normal subjects with IL-22 expression highly variable among the patients. Furthermore, we show that IL-22 can affect primary human retinal pigment epithelial cells by decreasing total tissue resistance and inducing apoptosis possibly by decreasing phospho-Bad level. In addition, the microarray data identified a possible uveitis-associated gene expression pattern, showed distinct gene expression profiles in patients during periods of clinical activity and quiescence, and demonstrated similar expression patterns in related patients with similar clinical phenotypes. Our data provides the first evidence that a sub-set of IL-10 family genes are implicated in non-infectious uveitis and that IL-22 can affect human retinal pigment epithelial cells. The results may facilitate further understanding of the molecular mechanisms of autoimmune uveitis and other autoimmune originated inflammatory diseases. PMID:18802119

  17. Discovering New Genes in the Pathways of Common Sporadic Neurodegenerative Diseases: A Bioinformatics Approach.

    PubMed

    Kim, Yong Hwan; Beak, Seung Han; Charidimou, Andreas; Song, Min

    2016-01-13

    Late onset Alzheimer's disease (AD) and Parkinson's disease (PD) are mostly "sporadic" age-related neurodegenerative disorders, but with a clear genetic component. However, their genetic architecture is complex and heterogeneous, largely remaining a conundrum, with only a handful of well-established genetic risk factors consistently associated with these diseases. It is possible that numerous, yet undiscovered, AD and PD related genes might exist. We focused on the 'gene' as a mediator to find new potential genes that might have a relationship with both disorders using bio-literature mining techniques. Based on Entrez Gene, we extracted the genes and directional gene-gene relation in the entire MEDLINE records and then constructed a directional gene-gene network. We identified common genes associated with two different but related diseases by performing shortest path analysis on the network. With our approach, we were able to identify and map already known genes that have a direct relationship with PD and AD. In addition, we identified 7 genes previously unknown to be a bridge between these two disorders. We confirmed 4 genes, ROS1, FMN1, ATP8A2, and SNORD12C, by biomedical literature and further checked 3 genes, ERVK-10, PRS, and C7orf49, that might have a high possibility to be related with both diseases. Additional experiments were performed to demonstrate the effectiveness of our proposed method. Comparing to the co-occurrence approach, our approach detected 25% more candidate genes and verified 10% more genes that have the relationship between both diseases than the co-occurrence approach did. PMID:26836166

  18. Genes and non-mendelian diseases: dealing with complexity.

    PubMed

    Jordan, Bertrand

    2014-01-01

    The first decades of the new medical genetics (1980 to 2000) were marked by resounding successes, with the identification of the genes responsible (when defective) for muscular dystrophy, cystic fibrosis, or Huntington's disease, to name justa few of the several thousand Mendelian genetic conditions whose causes are now known. In contrast, the search for genes involved in common disorders such as diabetes,hypertension, schizophrenia, or autism failed miserably in the 1990s, with inconsistent and conflicting results--although the strong genetic component of these diseases (that also involve environmental factors) was (and still is) beyond doubt. From 2000 on,thanks to huge progress in genomic knowledge, technology, and analytical methods, it became possible to reliably identify genes influencing the risk of complex conditions,using the so-called GWAS (Genome-Wide Association Study) approach. Yet many problems remain, such as the vexing question of the "missing heritability," or the difficulty of translating these scientific results into genetic tests with real clinical validity and utility. Autism is one of the cases in which a strong genetic component has been demonstrated, but where the search for causative genes remains difficult and attempts at developing valid genetic tests have failed, because of the many genes involved and possibly of the heterogeneity of the condition. PMID:25345706

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

    PubMed

    Rivas, Manuel A; Beaudoin, Mlissa; 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; Lagac, Caroline; Neale, Benjamin; Lo, Ken Sin; Schumm, Phil; Trkvist, Leif; Dubinsky, Marla C; Brant, Steven R; Silverberg, Mark S; 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

    2011-11-01

    More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 10(-16), odds ratio ? 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models. PMID:21983784

  20. Mutation screening of patients with Alzheimer disease identifies APP locus duplication in a Swedish patient

    PubMed Central

    2011-01-01

    Background Missense mutations in three different genes encoding amyloid-? precursor protein, presenilin 1 and presenilin 2 are recognized to cause familial early-onset Alzheimer disease. Also duplications of the amyloid precursor protein gene have been shown to cause the disease. At the Dept. of Geriatric Medicine, Karolinska University Hospital, Sweden, patients are referred for mutation screening for the identification of nucleotide variations and for determining copy-number of the APP locus. Methods We combined the method of microsatellite marker genotyping with a quantitative real-time PCR analysis to detect duplications in patients with Alzheimer disease. Results In 22 DNA samples from individuals diagnosed with clinical Alzheimer disease, we identified one patient carrying a duplication on chromosome 21 which included the APP locus. Further mapping of the chromosomal region by array-comparative genome hybridization showed that the duplication spanned a maximal region of 1.09 Mb. Conclusions This is the first report of an APP duplication in a Swedish Alzheimer patient and describes the use of quantitative real-time PCR as a tool for determining copy-number of the APP locus. PMID:22044463

  1. Identifying a species tree subject to random lateral gene transfer.

    PubMed

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

    2013-04-01

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

  2. Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimers disease

    PubMed Central

    Li, Xinzhong; Long, Jintao; He, Taigang; Belshaw, Robert; Scott, James

    2015-01-01

    Previous studies have evaluated gene expression in Alzheimers disease (AD) brains to identify mechanistic processes, but have been limited by the size of the datasets studied. Here we have implemented a novel meta-analysis approach to identify differentially expressed genes (DEGs) in published datasets comprising 450 late onset AD (LOAD) brains and 212 controls. We found 3124 DEGs, many of which were highly correlated with Braak stage and cerebral atrophy. Pathway Analysis revealed the most perturbed pathways to be (a) nitric oxide and reactive oxygen species in macrophages (NOROS), (b) NFkB and (c) mitochondrial dysfunction. NOROS was also up-regulated, and mitochondrial dysfunction down-regulated, in healthy ageing subjects. Upstream regulator analysis predicted the TLR4 ligands, STAT3 and NFKBIA, for activated pathways and RICTOR for mitochondrial genes. Protein-protein interaction network analysis emphasised the role of NFKB; identified a key interaction of CLU with complement; and linked TYROBP, TREM2 and DOK3 to modulation of LPS signalling through TLR4 and to phosphatidylinositol metabolism. We suggest that NEUROD6, ZCCHC17, PPEF1 and MANBAL are potentially implicated in LOAD, with predicted links to calcium signalling and protein mannosylation. Our study demonstrates a highly injurious combination of TLR4-mediated NFKB signalling, NOROS inflammatory pathway activation, and mitochondrial dysfunction in LOAD. PMID:26202100

  3. Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimer's disease.

    PubMed

    Li, Xinzhong; Long, Jintao; He, Taigang; Belshaw, Robert; Scott, James

    2015-01-01

    Previous studies have evaluated gene expression in Alzheimer's disease (AD) brains to identify mechanistic processes, but have been limited by the size of the datasets studied. Here we have implemented a novel meta-analysis approach to identify differentially expressed genes (DEGs) in published datasets comprising 450 late onset AD (LOAD) brains and 212 controls. We found 3124 DEGs, many of which were highly correlated with Braak stage and cerebral atrophy. Pathway Analysis revealed the most perturbed pathways to be (a) nitric oxide and reactive oxygen species in macrophages (NOROS), (b) NFkB and (c) mitochondrial dysfunction. NOROS was also up-regulated, and mitochondrial dysfunction down-regulated, in healthy ageing subjects. Upstream regulator analysis predicted the TLR4 ligands, STAT3 and NFKBIA, for activated pathways and RICTOR for mitochondrial genes. Protein-protein interaction network analysis emphasised the role of NFKB; identified a key interaction of CLU with complement; and linked TYROBP, TREM2 and DOK3 to modulation of LPS signalling through TLR4 and to phosphatidylinositol metabolism. We suggest that NEUROD6, ZCCHC17, PPEF1 and MANBAL are potentially implicated in LOAD, with predicted links to calcium signalling and protein mannosylation. Our study demonstrates a highly injurious combination of TLR4-mediated NFKB signalling, NOROS inflammatory pathway activation, and mitochondrial dysfunction in LOAD. PMID:26202100

  4. Bioinformatic Screening of Autoimmune Disease Genes and Protein Structure Prediction with FAMS for Drug Discovery

    PubMed Central

    Ishida, Shigeharu; Umeyama, Hideaki; Iwadate, Mitsuo; Y-h, Taguchi

    2014-01-01

    Autoimmune diseases are often intractable because their causes are unknown. Identifying which genes contribute to these diseases may allow us to understand the pathogenesis, but it is difficult to determine which genes contribute to disease. Recently, epigenetic information has been considered to activate/deactivate disease-related genes. Thus, it may also be useful to study epigenetic information that differs between healthy controls and patients with autoimmune disease. Among several types of epigenetic information, promoter methylation is believed to be one of the most important factors. Here, we propose that principal component analysis is useful to identify specific gene promoters that are differently methylated between the normal healthy controls and patients with autoimmune disease. Full Automatic Modeling System (FAMS) was used to predict the three-dimensional structures of selected proteins and successfully inferred relatively confident structures. Several possibilities of the application to the drug discovery based on obtained structures are discussed. PMID:23855671

  5. 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

  6. Inherited neuropathies: from gene to disease.

    PubMed

    Keller, M P; Chance, P F

    1999-04-01

    Inherited disorders of peripheral nerves represent a common group of neurologic diseases. Charcot-Marie-Tooth neuropathy type 1 (CMT1) is a genetically heterogeneous group of chronic demyelinating polyneuropathies with loci mapping to chromosome 17 (CMT1A), chromosome 1 (CMT1B) and to another unknown autosome (CMT1C). CMT1A is most often associated with a tandem 1.5-megabase (Mb) duplication in chromosome 17p11.2-12, or in rare patients may result from a point mutation in the peripheral myelin protein-22 (PMP22) gene. CMT1B is associated with point mutations in the myelin protein zero (P0 or MPZ) gene. The molecular defect in CMT1C is unknown. X-linked Charcot-Marie-Tooth neuropathy (CMTX), which has clinical features similar to CMT1, is associated with mutations in the connexin32 gene. Charcot-Marie-Tooth neuropathy type 2 (CMT2) is an axonal neuropathy, also of undetermined cause. One form of CMT2 maps to chromosome 1p36 (CMT2A), another to chromosome 3p (CMT2B) and another to 7p (CMT2D). Dejerine-Sottas disease (DSD), also called hereditary motor and sensory neuropathy type III (HMSNIII), is a severe, infantile-onset demyelinating polyneuropathy syndrome that may be associated with point mutations in either the PMP22 gene or the P0 gene and shares considerable clinical and pathological features with CMT1. Hereditary neuropathy with liability to pressure palsies (HNPP) is an autosomal dominant disorder that results in a recurrent, episodic demyelinating neuropathy. HNPP is associated with a 1.5-Mb deletion in chromosome 17p11.2-12 and results from reduced expression of the PMP22 gene. CMT1A and HNPP are reciprocal duplication/deletion syndromes originating from unequal crossover during germ cell meiosis. Other rare forms of demyelinating peripheral neuropathies map to chromosome 8q, 10q and 11q. Hereditary neuralgic amyotrophy (familial brachial plexus neuropathy) is an autosomal dominant disorder causing painful, recurrent brachial plexopathies and maps to chromosome 17q25. PMID:10219749

  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 ?-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 ? 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. PMID:25186316

  8. A set-based association test identifies sex-specific gene sets associated with type 2 diabetes

    PubMed Central

    He, Tao; Zhong, Ping-Shou; Cui, Yuehua

    2014-01-01

    Single variant analysis in genome-wide association studies (GWAS) has been proven to be successful in identifying thousands of genetic variants associated with hundreds of complex diseases. However, these identified variants only explain a small fraction of inheritable variability in many diseases, suggesting that other resources, such as multilevel genetic variations, may contribute to disease susceptibility. In this work, we proposed to combine genetic variants that belong to a gene set, such as at gene- and pathway-level to form an integrated signal aimed to identify major players that function in a coordinated manner conferring disease risk. The integrated analysis provides novel insight into disease etiology while individual signals could be easily missed by single variant analysis. We applied our approach to a genome-wide association study of type 2 diabetes (T2D) with male and female data analyzed separately. Novel sex-specific genes and pathways were identified to increase the risk of T2D. We also demonstrated the performance of signal integration through simulation studies. PMID:25429300

  9. Hashimoto's Thyroiditis: From Genes to the Disease

    PubMed Central

    Zaletel, Katja; Gaber?ek, Simona

    2011-01-01

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

  10. 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. PMID:22829077

  11. 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 9p13.323.3 (n=1), 9q33.134.13 (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 1p36.3136.33 (n=6), 17q21.2q21.31 (n=5) and 17q25.125.3 (n=5) and deletions affecting 18p11.3111.32 (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

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

    PubMed Central

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

    2012-01-01

    INTRODUCTION Neural tube defects (NTDs) are congenital anomalies caused by a combination of genetic and environmental influences. A defect below the head region resulting in protuberance of meninges and nervous tissue is termed myelomeningocele (MM). MM, the most common NTD compatible with survival, occurs in approximately 1 in 1,000 births worldwide. Maternal pre- and periconceptional folate supplementation reduces the risk of NTDs by up to 70%. A key enzyme in folate metabolism is 5, 10-methylene-tetrahydrofolate reductase (MTHFR). OBJECTIVES Sequence the 12 exons of the MTHFR gene among 96 subjects with MM to identify variants potentially contributing to the disease trait. METHODS Exons were amplified by polymerase chain reaction and the products were sequenced by Sanger method to reveal sequence variants compared to MTHFR reference sequences. Association of variants was examined by Fishers test. RESULTS A novel variant c.171+3G>T was identified in intron 1 in one affected subject. The variant was not found in the subjects unaffected mothers DNA and the unaffected fathers DNA was unavailable. We found significant differences in allele frequencies for seven SNPs in MM subjects compared to ethnically matched reference populations reported in the single nucleotide polymorphism (SNP) database (dbSNP). CONCLUSION We identified a novel variant c.171+3G>T in the MTHFR gene that potentially affects splicing in an affected subject. Also, we observed five SNPs (rs13306561, rs2274976, rs2066462, rs12121543, and rs1476413) in the MTHFR gene not previously shown to associate with MM. The current study provides additional evidence that multiple variations in the MTHFR gene are associated with MM. PMID:22241680

  13. Gene expression reveals overlap between normal aging and Alzheimer’s disease genes

    PubMed Central

    Avramopoulos, Dimitrios; Szymanski, Megan; Wang, Ruihua; Bassett, Susan

    2010-01-01

    Alzheimer’s disease (AD) is a common cause of dementia with a strong genetic component and risk sharply increasing with age. We performed two parallel microarray experiments to independently identify genes involved in normal aging and genes involved in AD using RNA extracted from the temporal lobe of 22 late onset AD and 23 control brain donors. We found that AD is accompanied by significant changes in the expression of many genes with up-regulation of genes involved in inflammation and in transcription regulation and down-regulation of genes involved in neuronal functions. The changes with healthy aging involved multiple genes but were not as strong. Replicating and strengthening previous reports we find a highly significant overlap between genes changing expression with age and those changing in AD and we observe that those changes are most often in the same direction. This result supports an overlap between the biological processes of normal aging and susceptibility to AD and suggests that age related genes expression changes might increase the risk to develop AD. PMID:20570407

  14. 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

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

    PubMed Central

    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

  16. Using context-specific effect of miRNAs to identify functional associations between miRNAs and gene signatures

    PubMed Central

    2013-01-01

    Background MicroRNAs are a class of short regulatory RNAs that act as post-transcriptional fine-tune regulators of a large host of genes that play key roles in many cellular processes and signaling pathways. A useful step for understanding their functional role is characterizing their influence on the protein context of the targets. Using miRNA context-specific influence as a functional signature is promising to identify functional associations between miRNAs and other gene signatures, and thus advance our understanding of miRNA mode of action. Results In the current study we utilized the power of regularized regression models to construct functional associations between gene signatures. Genes that are influenced by miRNAs directly(computational miRNA target prediction) or indirectly (protein partners of direct targets) are defined as functional miRNA gene signature. The combined direct and indirect miRNA influence is defined as context-specific effects of miRNAs, and is used to identify regulatory effects of miRNAs on curated gene signatures. Elastic-net regression was used to build functional associations between context-specific effect of miRNAs and other gene signatures (disease, pathway signatures) by identifying miRNAs whose targets are enriched in gene lists. As a proof of concept, elastic-net regression was applied on lists of genes downregulated upon pre-miRNA transfection, and successfully identified the treated miRNA. This model was then extended to construct functional relationships between miRNAs and disease and pathway gene lists. Integrating context-specific effects of miRNAs on a protein network reveals more significant miRNA enrichment in prostate gene signatures compared to miRNA direct targets. The model identified novel list of miRNAs that are associated with prostate clinical variables. Conclusions Elastic-net regression is used as a model to construct functional associations between miRNA signatures and other gene signatures. Defining miRNA context-specific functional gene signature by integrating the downstream effect of miRNAs demonstrates better performance compared to the miRNA signature alone (direct targets). miRNA functional signatures can greatly facilitate miRNA research to uncover new functional associations between miRNAs and diseases, drugs or pathways. PMID:24267745

  17. 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...

  18. Identifying and characterizing barley genes that protect against trichothecene mycotoxins

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fusarium head blight of wheat and barley, caused by the fungal pathogen Fusarium graminearum, is a major disease problem around the world. During infection, trichothecene mycotoxins are produced and act as virulence factors, resulting in reduced grain yield and quality. There are two types of tricho...

  19. Identifying the genetic basis of attenuation in Marek's disease virus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Marek’s disease virus (MDV) is an oncogenic alphaherpesvirus of chickens that induces lymphoid tumors in susceptible birds. This agronomically-important disease is controlled primarily through vaccines that prevent tumor formation but are non-sterilizing. Currently most efficacious vaccines consist ...

  20. Synthetic lethal screening in the mammalian central nervous system identifies Gpx6 as a modulator of Huntingtons disease

    PubMed Central

    Shema, Reut; Kulicke, Ruth; Cowley, Glenn S.; Stein, Rachael; Root, David E.; Heiman, Myriam

    2015-01-01

    Huntingtons disease, the most common inherited neurodegenerative disease, is characterized by a dramatic loss of deep-layer cortical and striatal neurons, as well as morbidity in midlife. Human genetic studies led to the identification of the causative gene, huntingtin. Recent genomic advances have also led to the identification of hundreds of potential interacting partners for huntingtin protein and many hypotheses as to the molecular mechanisms whereby mutant huntingtin leads to cellular dysfunction and death. However, the multitude of possible interacting partners and cellular pathways affected by mutant huntingtin has complicated efforts to understand the etiology of this disease, and to date no curative therapeutic exists. To address the general problem of identifying the disease-phenotype contributing genes from a large number of correlative studies, here we develop a synthetic lethal screening methodology for the mammalian central nervous system, called SLIC, for synthetic lethal in the central nervous system. Applying SLIC to the study of Huntingtons disease, we identify the age-regulated glutathione peroxidase 6 (Gpx6) gene as a modulator of mutant huntingtin toxicity and show that overexpression of Gpx6 can dramatically alleviate both behavioral and molecular phenotypes associated with a mouse model of Huntingtons disease. SLIC can, in principle, be used in the study of any neurodegenerative disease for which a mouse model exists, promising to reveal modulators of neurodegenerative disease in an unbiased fashion, akin to screens in simpler model organisms. PMID:25535386

  1. Synthetic lethal screening in the mammalian central nervous system identifies Gpx6 as a modulator of Huntington's disease.

    PubMed

    Shema, Reut; Kulicke, Ruth; Cowley, Glenn S; Stein, Rachael; Root, David E; Heiman, Myriam

    2015-01-01

    Huntington's disease, the most common inherited neurodegenerative disease, is characterized by a dramatic loss of deep-layer cortical and striatal neurons, as well as morbidity in midlife. Human genetic studies led to the identification of the causative gene, huntingtin. Recent genomic advances have also led to the identification of hundreds of potential interacting partners for huntingtin protein and many hypotheses as to the molecular mechanisms whereby mutant huntingtin leads to cellular dysfunction and death. However, the multitude of possible interacting partners and cellular pathways affected by mutant huntingtin has complicated efforts to understand the etiology of this disease, and to date no curative therapeutic exists. To address the general problem of identifying the disease-phenotype contributing genes from a large number of correlative studies, here we develop a synthetic lethal screening methodology for the mammalian central nervous system, called SLIC, for synthetic lethal in the central nervous system. Applying SLIC to the study of Huntington's disease, we identify the age-regulated glutathione peroxidase 6 (Gpx6) gene as a modulator of mutant huntingtin toxicity and show that overexpression of Gpx6 can dramatically alleviate both behavioral and molecular phenotypes associated with a mouse model of Huntington's disease. SLIC can, in principle, be used in the study of any neurodegenerative disease for which a mouse model exists, promising to reveal modulators of neurodegenerative disease in an unbiased fashion, akin to screens in simpler model organisms. PMID:25535386

  2. Seven newly identified loci for autoimmune thyroid disease

    PubMed Central

    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.

    2012-01-01

    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

  3. 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

  4. 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

  5. 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 possible. PMID:24179676

  6. DIFFERENTIALLY EXPRESSED GENES IN RESPONSES TO LATE LEAF SPOT DISEASE CAUSED BY CERCOSPORIDIUM PERSONATUM IN PEANUT USING MICROARRAY ANALYSIS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Late leaf spot disease caused by Cercosporidium personatum is one of the most destructive foliar diseases of peanut worldwide. This research was to identify resistance genes in response to leaf spot disease using miccroarray and real-time PCR. To identify transcripts involved in disease resistance, ...

  7. 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.

  8. Gene Prospector: An evidence gateway for evaluating potential susceptibility genes and interacting risk factors for human diseases

    PubMed Central

    Yu, Wei; Wulf, Anja; Liu, Tiebin; Khoury, Muin J; Gwinn, Marta

    2008-01-01

    Background Millions of single nucleotide polymorphisms have been identified as a result of the human genome project and the rapid advance of high throughput genotyping technology. Genetic association studies, such as recent genome-wide association studies (GWAS), have provided a springboard for exploring the contribution of inherited genetic variation and gene/environment interactions in relation to disease. Given the capacity of such studies to produce a plethora of information that may then be described in a number of publications, selecting possible disease susceptibility genes and identifying related modifiable risk factors is a major challenge. A Web-based application for finding evidence of such relationships is key to the development of follow-up studies and evidence for translational research. We developed a Web-based application that selects and prioritizes potential disease-related genes by using a highly curated and updated literature database of genetic association studies. The application, called Gene Prospector, also provides a comprehensive set of links to additional data sources. Results We compared Gene Prospector results for the query "Parkinson" with a list of 13 leading candidate genes (Top Results) from a curated, specialty database for genetic associations with Parkinson disease (PDGene). Nine of the thirteen leading candidate genes from PDGene were in the top 10th percentile of the ranked list from Gene Prospector. In fact, Gene Prospector included more published genetic association studies for the 13 leading candidate genes than PDGene did. Conclusion Gene Prospector provides an online gateway for searching for evidence about human genes in relation to diseases, other phenotypes, and risk factors, and provides links to published literature and other online data sources. Gene Prospector can be accessed via . PMID:19063745

  9. Exome Sequencing Identifies a Novel Gene, WNK1, for Susceptibility to Pelvic Organ Prolapse (POP)

    PubMed Central

    Rao, Shuquan; Lang, Jinghe; Zhu, Lan; Chen, Juan

    2015-01-01

    Pelvic organ prolapse (POP) is a common gynecological disorder; however, the genetic components remain largely unidentified. Exome sequencing has been widely used to identify pathogenic gene mutations of several diseases because of its high chromosomal coverage and accuracy. In this study, we performed whole exome sequencing (WES), for the first time, on 8 peripheral blood DNA samples from representative POP cases. After filtering the sequencing data from the dbSNP database (build 138) and the 1000 Genomes Project, 2 missense variants in WNK1, c.2668G > A (p.G890R) and c.6761C> T (p.P2254L), were identified and further validated via Sanger sequencing. In validation stage, the c.2668G > A (p.G890R) variant and 8 additional variants were detected in 11 out of 161 POP patients. All these variants were absent in 231 healthy controls. Functional experiments showed that fibroblasts from the utero-sacral ligaments of POP with WNK1 mutations exhibited loose and irregular alignment compared with fibroblasts from healthy controls. In sum, our study identified a novel gene, WNK1, for POP susceptibility, expanded the causal mutation spectrums of POP, and provided evidence for the genetic diagnosis and medical management of POP in the future. PMID:25739019

  10. Large Scale Association Analysis Identifies Three Susceptibility Loci for Coronary Artery Disease

    PubMed Central

    Youhanna, Sonia; Badro, Danielle A.; Kamatani, Yoichiro; Hager, Jrg; 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

  11. 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 the molecular events that underlie the pathology in this animal model, which is potentially a valuable comparator to human rheumatoid arthritis (RA). PMID:15642130

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

    PubMed Central

    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 nave, 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 the molecular events that underlie the pathology in this animal model, which is potentially a valuable comparator to human rheumatoid arthritis (RA). PMID:15642130

  13. Identifying microRNA targets in different gene regions

    PubMed Central

    2014-01-01

    Background Currently available microRNA (miRNA) target prediction algorithms require the presence of a conserved seed match to the 5' end of the miRNA and limit the target sites to the 3' untranslated regions of mRNAs. However, it has been noted that these requirements may be too stringent, leading to a substantial number of missing targets. Results We have developed TargetS, a novel computational approach for predicting miRNA targets with the target sites located along entire gene sequences, which permits finding additional targets that are not located in the 3' un-translated regions. Our model is based on both canonical seed matching and non-canonical seed pairing, which discovers targets that allow one bit GU wobble. It does not rely on evolutionary conservation, so it allows the detection of species-specific miRNA-mRNA interactions and makes it suitable for analyzing un-conserved gene sequences. To test the performance of our approach, we have imported the widely used benchmark dataset revealing fold-changes in protein production corresponding to each of the five selected microRNAs. Compared to well-known miRNA target prediction tools, including TargetScanS, PicTar and MicroT_CDS, our method yields the highest sensitivity, while achieving a comparable level of accuracy. Human miRNA target predictions using our computational approach are available online at http://liubioinfolab.org/targetS/mirna.html Conclusions A simple but powerful computational miRNA target prediction method is developed that is solely based on canonical and non-canonical seed matches without requiring evolutionary conservation of the target sites. Our method also expands the target search space to different gene regions, rather than limiting to 3'UTR only. This improves the sensitivity of miRNA target identification, while achieving a comparable accuracy with existing methods. PMID:25077573

  14. Analysis of antigen receptor genes in Hodgkin's disease.

    PubMed Central

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

    1993-01-01

    AIM--To analyse the configuration of the antigen receptor genes in Hodgkin's disease. METHODS--DNA extracted from 45 samples of Hodgkin's disease was analysed using Southern blotting and DNA hybridisation, using probes to the joining region of the immunoglobulin heavy chain gene, the constant region of kappa immunoglobulin light chain gene, and the constant region of the beta chain of the T cell receptor gene. RESULTS--A single case of nodular sclerosing disease showed clonal rearrangement of the immunoglobulin heavy and light chain genes, all other samples having germline immunoglobulin genes. The nature of the clonal population in the diseased tissue is uncertain, because the intensity of the rearranged bands did not correlate with the percentage of Reed-Sternberg cells present. The T cell receptor genes were in germline configuration in all the samples. CONCLUSIONS--Antigen receptor gene rearrangement is a rare finding in unselected cases of Hodgkin's disease. Images PMID:8388407

  15. Using Epidemiological Models and Genetic Selection to Identify Theoretical Opportunities to Reduce Disease Impact

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Selection for disease resistance is a contemporary topic with developing approaches for genetic improvement. Merging the sciences of genetic selection and epidemiology is essential to identify selection schemes to enhance disease resistance. Epidemiological models can identify theoretical opportuni...

  16. 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

    2015-11-28

    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

  17. 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

  18. Identifying genes affectng stress response in rainbow trout

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such set of traits are the respon...

  19. A two-stage meta-analysis identifies several new loci for Parkinson's disease.

    PubMed

    2011-06-01

    A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson's Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson's disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p<510(-10), PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n?=?399) and methylation (n?=?292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loci. PMID:21738488

  20. 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

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

    PubMed Central

    2011-01-01

    A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson's Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson's disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p<510?10, PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n?=?399) and methylation (n?=?292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loci. PMID:21738488

  2. Can Raman spectroscopy identify the origin of Paget disease?

    NASA Astrophysics Data System (ADS)

    Martin, A. A.; Marcelo, Moreno; Bitar, R.; Martinho, H., .; Santos, E. A. P.; Arisawa, E. A. L.

    2008-02-01

    The histogenesis of the breast Paget's disease was investigated by the optical diagnosis technique using Raman spectroscopy. A total of 15 spectra of the associated breast lesion, 21 spectra of the eczematoid skin lesion and 396 spectra of invasive breast cancer not otherwise specified were compared by clustering the spectral data between 800 - 1800 cm -1 at level of similarity of 95%, using a correlation distance measurement by computing the covariance matrix. The Raman spectral-biochemical characterization of invasive breast cancer and breast Paget's disease with eczematoid skin lesion associated with underlying invasive breast lesion tissues enabled one concludes that the parenchymal disease had similar characteristics to the skin's Paget lesion. This could indicate a similar histogenesis for both. Thus, the findings of the present work adds a relevant experimental evidence that agrees with the epidermotropic theory of Paget's disease, that states that the cells originate in the breast ducts and migrate to the nipple's skin.

  3. 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

  4. 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. PMID:26930047

  5. EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization

    PubMed Central

    Rackham, Owen J. L.; Shihab, Hashem A.; Johnson, Michael R.; Petretto, Enrico

    2015-01-01

    Methods to interpret personal genome sequences are increasingly required. Here, we report a novel framework (EvoTol) to identify disease-causing genes using patient sequence data from within protein coding-regions. EvoTol quantifies a gene's intolerance to mutation using evolutionary conservation of protein sequences and can incorporate tissue-specific gene expression data. We apply this framework to the analysis of whole-exome sequence data in epilepsy and congenital heart disease, and demonstrate EvoTol's ability to identify known disease-causing genes is unmatched by competing methods. Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation, informing novel polygenic contributions to human disease. PMID:25550428

  6. Genetic association of sirtuin genes and Parkinson's disease.

    PubMed

    Jesús, Silvia; Gómez-Garre, Pilar; Carrillo, Fátima; Cáceres-Redondo, María T; Huertas-Fernández, Ismael; Bernal-Bernal, Inmaculada; Bonilla-Toribio, Marta; Vargas-González, Laura; Carballo, Manuel; Mir, Pablo

    2013-09-01

    Parkinson's disease (PD) is a neurodegenerative disease caused by both genetic and environmental factors. Sirtuins are highly-conserved, NAD-dependent class III deacetylases that regulate a variety of cellular functions. Most of the known sirtuins have been involved in animal models of neurodegenerative disorders, such as PD. Although seven sirtuin family members have been identified (SIRT1-SIRT7) the relationship between sirtuins and PD in humans has not been established. Our aim was to investigate the association between sirtuin genes and risk of PD. We included 326 PD patients and 371 controls from southern Spain. Forty-one single nucleotide polymorphisms (SNPs) in sirtuin genes were genotyped in order to determine whether they were related to the risk of PD. These SNPs included Tag-SNPs, coding non-synonymous SNPs and SNPs affecting activity of microRNA binding sites. No relationship was found between these SNPs in sirtuin genes and PD. Our data indicate that variations in sirtuin genes do not affect the risk for PD, at least in our population. PMID:23719790

  7. Identifying Host Genetic Risk Factors in the Context of Public Health Surveillance for Invasive Pneumococcal Disease

    PubMed Central

    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. PMID:21858107

  8. Identifying rhesus macaque gene orthologs using heterospecific human CNV probes.

    PubMed

    Ng, Jillian; Fass, Joseph N; Durbin-Johnson, Blythe; Smith, David Glenn; Kanthaswamy, Sree

    2015-12-01

    We used the Affymetrix() Genome-Wide Human SNP Array 6.0 to identify heterospecific markers and compare copy number and structural genomic variation between humans and rhesus macaques. Over 200,000 human copy number variation (CNV) probes were mapped to a Chinese and an Indian rhesus macaque sample. Observed genomic rearrangements and synteny were in agreement with the results of a previously published genomic comparison between humans and rhesus macaques. Comparisons between each of the two rhesus macaques and humans yielded 206 regions with copy numbers that differed by at least two fold in the Indian rhesus macaque and human, 32 in the Chinese rhesus macaque and human, and 147 in both rhesus macaques. The detailed genomic map and preliminary CNV data are useful for better understanding genetic variation in rhesus macaques, identifying derived changes in human CNVs that may have evolved by selection, and determining the suitability of rhesus macaques as human models for particular biomedical studies. PMID:26697375

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

    PubMed

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

    2014-01-01

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

  10. Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

    PubMed Central

    Wang, Lan; Wu, Long-Fei; Lu, Xin; Mo, Xing-Bo; Tang, Zai-Xiang; Lei, Shu-Feng; Deng, Fei-Yan

    2015-01-01

    Objective Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested. Methods We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis. Results We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation. Conclusion The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases. PMID:26352601

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

    PubMed Central

    Ringman, John M.; Coppola, Giovanni

    2013-01-01

    Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets. PMID:23558482

  12. 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 facilitate the identification of novel germline factors driving aggressive disease susceptibility and allow for new insights into these deadly forms of prostate cancer. PMID:25411967

  13. 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. PMID:26355777

  14. A Novel Mutation in Aspartoacylase Gene; Canavan Disease.

    PubMed

    Ashrafi, Mahmoudreza; Tavasoli, Alireza; Katibeh, Pegah; Aryani, Omid; Vafaee-Shahi, Mohammad

    2015-01-01

    Objective Canavan disease (CD) is a type of vacuolating leukodystrophy with autosomal recessive inheritance. Aspartoacylase deficiency results in decrease of myelin biosynthesis, dysmyelination and brain edema. Although CD is a very common in Ashkenazi Jews patients, several cases have been reported from non-Jewish population. This report is based on a homozygous C.202G>A mutation in the ASPA gene identified from an Iranian patient. To our knowledge, this type of mutation has not been reported in non-Jewish population in the literature. PMID:26664442

  15. Identifying the Association Between Alzheimer's Disease and Parkinson's Disease Using Genome-Wide Association Studies and Protein-Protein Interaction Network.

    PubMed

    Liu, Guiyou; Bao, Xinjie; Jiang, Yongshuai; Liao, Mingzhi; Jiang, Qinghua; Feng, Rennan; Zhang, Liangcai; Ma, Guoda; Chen, Zugen; Wang, Guangyu; Wang, Renzhi; Zhao, Bin; Li, Keshen

    2015-12-01

    Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most common neurodegenerative diseases in the elderly. Shared clinical and pathological features have been reported. Recent large-scale genome-wide association studies (GWAS) have been conducted and reported a number of AD and PD variants. Until now, the underlying genetic mechanisms for all these newly identified PD variants as well as the association between AD and PD are still unclear exactly. We think that PD variants may contribute to AD and PD by influence on brain gene expression. Here, we conducted a systems analysis using (1) AD and PD variants (P?identified by the published GWAS; (2) four brain expression GWAS datasets using expression quantitative trait loci from the cerebellum and temporal cortex; (3) large-scale AD GWAS from the Alzheimer Disease Genetics Consortium (ADGC); (4) a protein-protein interaction network. Our results indicated that PD variants around the 17q21 were associated with gene expression and suggestive AD risk. We also identified significant interaction among AD and PD susceptibility genes. We believe that our findings may explain the underlying genetic mechanisms for newly identified PD variants in PD and AD, as well as the association between AD and PD, which may be very useful for future genetic studies for both diseases. PMID:25370933

  16. 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. PMID:26827652

  17. Identifying rhesus macaque gene orthologs using heterospecific human CNV probes

    PubMed Central

    Ng, Jillian; Fass, Joseph N.; Durbin-Johnson, Blythe; Smith, David Glenn; Kanthaswamy, Sree

    2015-01-01

    We used the Affymetrix® Genome-Wide Human SNP Array 6.0 to identify heterospecific markers and compare copy number and structural genomic variation between humans and rhesus macaques. Over 200,000 human copy number variation (CNV) probes were mapped to a Chinese and an Indian rhesus macaque sample. Observed genomic rearrangements and synteny were in agreement with the results of a previously published genomic comparison between humans and rhesus macaques. Comparisons between each of the two rhesus macaques and humans yielded 206 regions with copy numbers that differed by at least two fold in the Indian rhesus macaque and human, 32 in the Chinese rhesus macaque and human, and 147 in both rhesus macaques. The detailed genomic map and preliminary CNV data are useful for better understanding genetic variation in rhesus macaques, identifying derived changes in human CNVs that may have evolved by selection, and determining the suitability of rhesus macaques as human models for particular biomedical studies. PMID:26697375

  18. 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...

  19. 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

  20. The Use of Random Homozygous Gene Perturbation to Identify Novel Host-Oriented Targets for Influenza

    PubMed Central

    Sui, Baoquan; Bamba, Douty; Weng, Ke; Ung, Huong; Van Dyke, Jessica; Goldblatt, Michael; Duan, Roxanne; Kinch, Michael S.; Li, Wu-Bo

    2009-01-01

    Conventional approaches for therapeutic targeting of viral pathogens have consistently faced obstacles arising from the development of resistant strains and a lack of broad-spectrum application. Influenza represents a particularly problematic therapeutic challenge since high viral mutation rates have often confounded many conventional antivirals. Newly emerging or engineered strains of influenza represent an even greater threat as typified by recent interest in avian subtypes of influenza. Based on the limitations associated with targeting virally-encoded molecules, we have taken an orthogonal approach of targeting host pathways in a manner that prevents viral propagation or spares the host from virus-mediated pathogenicity. To this end, we report herein the application of an improved technology for target discovery, Random Homozygous Gene Perturbation (RHGP), to identify host-oriented targets that are well-tolerated in normal cells but that prevent influenza-mediated killing of host cells. Improvements in RHGP facilitated a thorough screening of the entire genome, both for overexpression or loss of expression, to identify targets that render host cells resistant to influenza infection. We identify a set of host-oriented targets that prevent influenza killing of host cells and validate these targets using multiple approaches. These studies provide further support for a new paradigm to combat viral disease and demonstrate the power of RHGP to identify novel targets and mechanisms. PMID:19327807

  1. 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

  2. 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.

  3. 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

  4. Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis

    PubMed Central

    Shi, Kai; Bing, Zhi-Tong; Cao, Gui-Qun; Guo, Ling; Cao, Ya-Na; Jiang, Hai-Ou; Zhang, Mei-Xia

    2015-01-01

    AIM To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis (WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study. METHODS Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus (GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes. The function of the genes were annotated by gene ontology (GO). RESULTS In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location (sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter (LTD). Additionally, we identified the hug gene (top connectivity with other genes) in each module. The hub gene RPS15A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma. CONCLUSION From WGCNA analysis and hub gene calculation, we identified RPS15A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma. PMID:25938039

  5. 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

  6. 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

  7. 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

    2015-01-01

    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

  8. A Classifier-based approach to identify genetic similarities between diseases

    PubMed Central

    Schaub, Marc A.; Kaplow, Irene M.; Sirota, Marina; Do, Chuong B.; Butte, Atul J.; Batzoglou, Serafim

    2009-01-01

    Motivation: Genome-wide association studies are commonly used to identify possible associations between genetic variations and diseases. These studies mainly focus on identifying individual single nucleotide polymorphisms (SNPs) potentially linked with one disease of interest. In this work, we introduce a novel methodology that identifies similarities between diseases using information from a large number of SNPs. We separate the diseases for which we have individual genotype data into one reference disease and several query diseases. We train a classifier that distinguishes between individuals that have the reference disease and a set of control individuals. This classifier is then used to classify the individuals that have the query diseases. We can then rank query diseases according to the average classification of the individuals in each disease set, and identify which of the query diseases are more similar to the reference disease. We repeat these classification and comparison steps so that each disease is used once as reference disease. Results: We apply this approach using a decision tree classifier to the genotype data of seven common diseases and two shared control sets provided by the Wellcome Trust Case Control Consortium. We show that this approach identifies the known genetic similarity between type 1 diabetes and rheumatoid arthritis, and identifies a new putative similarity between bipolar disease and hypertension. Contact: serafim@cs.stanford.edu PMID:19477990

  9. 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-OConnell, 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

  10. 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...

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

    PubMed

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

    2014-04-01

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

  12. Quantifying dominance and deleterious effect on human disease genes

    PubMed Central

    Osada, Naoki; Mano, Shuhei; Gojobori, Jun

    2009-01-01

    Human genes responsible for inherited diseases are important for the understanding of human disease. We investigated the degree of polymorphism and divergence in the human disease genes to elucidate the effect of natural selection on human disease genes. In particular, the effect of disease dominance was incorporated into the analysis. Both dominant disease genes (DDG) and recessive disease genes (RDG) had a higher mutation rate per site and encoded longer proteins than the nondisease genes, which exposed the disease genes to a faster flux of new mutations. Using an unbiased polymorphism dataset, we found that, proportionally, RDG harbor more nonsynonymous polymorphisms compared with DDG. We estimated the selection intensity on the disease genes using polymorphism and divergence data and determined whether the different patterns of polymorphism and divergence between DDG and RDG could be explained by the difference in only dominance. Even after the dominance effect was considered, the selection intensity on RDG was significantly different from DDG, suggesting that the deleterious effect of the dominant and recessive disease mutations are fundamentally different. PMID:19139396

  13. Gene therapy for cardiovascular manifestations of lysosomal storage diseases

    PubMed Central

    Sleeper, Meg M.; Haskins, Mark E.; Ponder, Katherine P.

    2012-01-01

    Cardiac disease causes morbidity in several lysosomal storage diseases, which are the result of deficient activity of lysosomal enzymes. Mucopolysaccharidosis (MPS) causes aortic and valvular disease, Pompe disease causes cardiac muscle weakness, and Fabry disease causes left ventricular hypertrophy. Enzyme replacement therapy involves intravenous injection of enzyme modified with mannose 6-phosphate, which can be taken up by cells, and is currently approved for some lysosomal storage diseases. Gene therapy can result in secretion of mannose 6-phosphate-modified enzyme into blood, from where it can; similarly, be taken up by cells. Gene therapy has been effective in animal models of lysosomal storage disease, and holds great promise. PMID:26937225

  14. 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 282:198205 (2001)), but the gene(s) involved have not been identified. Here...

  15. Identification of Candidate Genes in Rice for Resistance to Sheath Blight Disease by Whole Genome Sequencing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent advances in whole genome sequencing have allowed identification of genes for disease susceptibility in humans. The objective of our research was to exploit whole genome sequences of 13 rice (Oryza sativa L.) inbred lines to identify non-synonymous SNPs (nsSNPs) and candidate genes for resista...

  16. Identification of genes conferring genetic resistance to Mareks disease

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic resistance to Mareks 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...

  17. 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; Mrz, 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, Andr 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

  18. Clustering gene expression regulators: new approach to disease subtyping.

    PubMed

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

    2014-01-01

    One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. PMID:24416320

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

    PubMed Central

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

    2010-01-01

    Dilated cardiomyopathy (DCM) is a structural heart disease with strong genetic background. Monogenic forms of DCM are observed in families with mutations located mostly in genes encoding structural and sarcomeric proteins. However, strong evidence suggests that genetic factors also affect the susceptibility to idiopathic DCM. To identify risk alleles for non-familial forms of DCM, we carried out a case-control association study, genotyping 664 DCM cases and 1,874 population-based healthy controls from Germany using a 50K human cardiovascular disease bead chip covering more than 2,000 genes pre-selected for cardiovascular relevance. After quality control, 30,920 single nucleotide polymorphisms (SNP) were tested for association with the disease by logistic regression adjusted for gender, and results were genomic-control corrected. The analysis revealed a significant association between a SNP in HSPB7 gene (rs1739843, minor allele frequency 39%) and idiopathic DCM (p = 1.06×10−6, OR = 0.67 [95% CI 0.57–0.79] for the minor allele T). Three more SNPs showed p < 2.21×10−5. De novo genotyping of these four SNPs was done in three independent case-control studies of idiopathic DCM. Association between SNP rs1739843 and DCM was significant in all replication samples: Germany (n = 564, n = 981 controls, p = 2.07×10−3, OR = 0.79 [95% CI 0.67–0.92]), France 1 (n = 433 cases, n = 395 controls, p = 3.73×10−3, OR = 0.74 [95% CI 0.60–0.91]), and France 2 (n = 249 cases, n = 380 controls, p = 2.26×10−4, OR = 0.63 [95% CI 0.50–0.81]). The combined analysis of all four studies including a total of n = 1,910 cases and n = 3,630 controls showed highly significant evidence for association between rs1739843 and idiopathic DCM (p = 5.28×10−13, OR = 0.72 [95% CI 0.65–0.78]). None of the other three SNPs showed significant results in the replication stage. This finding of the HSPB7 gene from a genetic search for idiopathic DCM using a large SNP panel underscores the influence of common polymorphisms on DCM susceptibility. PMID:20975947

  20. 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.