961 resultados para Genome-wide linkage
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Introduction: Les études GVvA (Genome-wide association ,-studies) ont identifié et confirmé plus de 20 gènes de susceptibilité au DT2 et ont contribué à mieux comprendre sa physiopathologie. L'hyperglycémie à jeun (GJ), et 2 heures après une HGPO (G2h) sont les deux mesures cliniques du diagnostic du DT2. Nous avons identifié récemment la G6P du pancréas (G6PC2) comme déterminant de la variabilité physiologique de la GJ puis Ie récepteur à la mélatonine (MTNRIB) qui de plus lie la régulation du rythme circadien au DT2. Dans ce travail nous avons étudié la génétique de la G2h à l'aide de l'approche GWA. Résultats: Nous avons réalisé une méta-analyse GWA dans le cadre de MAGIC (Meta-Analysis of Glucose and Insulin related traits Consortium) qui a inclus 9 études GWA (N=15'234). La réplication de 29 loci (N=6958-30 121, P < 10-5 ) a confirmé 5 nouveaux loci; 2 étant connus comme associés avec Ie DT2 (TCF7L2, P = 1,6 X 10-10 ) et la GJ (GCKR, p = 5,6 X 10-10 ); alors que GIPR (p= 5,2 X 10-12), VSP13C (p= 3,9 X 10-8) et ADCY5 (p = 1,11 X 10-15 ) sont inédits. GIPR code Ie récepteur au GIP (gastric inhibitory polypeptide) qui est sécrété par les ceIlules intestinales pour stimuler la sécrétion de l'insuline en réponse au glucose (l'effet incrétine). Les porteurs du variant GIPR qui augmente la G2h ont également un indice insulinogénique plus bas, (p= 1,0 X 10-17) mais ils ne présentent aucune modification de leur glycémie suite à une hyperglycémie provoquée par voie veineuse (p= 0,21). Ces résultats soutiennent un effet incrétine du locus GIPR qui expliquerait ~9,6 % de la variance total de ce trait. La biologie de ADCY5 et VPS13C et son lien avec l'homéostasie du glucose restent à élucider. GIPR n'est pas associé avec le risque de DT2 indiquant qu'il influence la variabilité physiologique de la G2h alors que le locus ADCY5 est associé avec le DT2 (OR = 1,11, P = 1,5 X 10-15). Conclusion: Notre étude démontre que l'étude de la G2h est une approche efficace d'une part pour la compréhension de la base génétique de la physiologie de ce trait clinique important et d'autre part pour identifier de nouveaux gènes de susceptibilité au DT2.
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Background: Amino acid tandem repeats are found in nearly one-fifth of human proteins. Abnormal expansion of these regions is associated with several human disorders. To gain further insight into the mutational mechanisms that operate in this type of sequence, we have analyzed a large number of mutation variants derived from human expressed sequence tags (ESTs).Results: We identified 137 polymorphic variants in 115 different amino acid tandem repeats. Of these, 77 contained amino acid substitutions and 60 contained gaps (expansions or contractions of the repeat unit). The analysis showed that at least about 21% of the repeats might be polymorphic in humans. We compared the mutations found in different types of amino acid repeats and in adjacent regions. Overall, repeats showed a five-fold increase in the number of gap mutations compared to adjacent regions, reflecting the action of slippage within the repetitive structures. Gap and substitution mutations were very differently distributed between different amino acid repeat types. Among repeats containing gap variants we identified several disease and candidate disease genes.Conclusion: This is the first report at a genome-wide scale of the types of mutations occurring in the amino acid repeat component of the human proteome. We show that the mutational dynamics of different amino acid repeat types are very diverse. We provide a list of loci with highly variable repeat structures, some of which may be potentially involved in disease.
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Amino acid tandem repeats, also called homopolymeric tracts, are extremely abundant in eukaryotic proteins. To gain insight into the genome-wide evolution of these regions in mammals, we analyzed the repeat content in a large data set of rat-mouse-human orthologs. Our results show that human proteins contain more amino acid repeats than rodent proteins and that trinucleotide repeats are also more abundant in human coding sequences. Using the human species as an outgroup, we were able to address differences in repeat loss and repeat gain in the rat and mouse lineages. In this data set, mouse proteins contain substantially more repeats than rat proteins, which can be at least partly attributed to a higher repeat loss in the rat lineage. The data are consistent with a role for trinucleotide slippage in the generation of novel amino acid repeats. We confirm the previously observed functional bias of proteins with repeats, with overrepresentation of transcription factors and DNA-binding proteins. We show that genes encoding amino acid repeats tend to have an unusually high GC content, and that differences in coding GC content among orthologs are directly related to the presence/absence of repeats. We propose that the different GC content isochore structure in rodents and humans may result in an increased amino acid repeat prevalence in the human lineage.
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Cells are subjected to dramatic changes of gene expression upon environmental changes. Stresscauses a general down-regulation of gene expression together with the induction of a set of stress-responsivegenes. The p38-related stress-activated protein kinase Hog1 is an important regulator of transcription uponosmostress in yeast. Genome-wide localization studies of RNA polymerase II (RNA Pol II) and Hog1 showed that stress induced major changes in RNA Pol II localization, with a shift toward stress-responsive genes relative to housekeeping genes. RNA Pol II relocalization required Hog1, which was also localized to stress-responsive loci. In addition to RNA Pol II-bound genes, Hog1 also localized to RNA polymerase III-bound genes, pointing to a wider role for Hog1 in transcriptional control than initially expected. Interestingly, an increasing association of Hog1 with stressresponsive genes was strongly correlated with chromatin remodeling and increased gene expression. Remarkably, MNase-Seq analysis showed that although chromatin structure was not significantly altered at a genome-wide level in response to stress, there was pronounced chromatin remodeling for those genes that displayed Hog1 association. Hog1 serves to bypass the general down-regulation of gene expression that occurs in response to osmostress, and does so both by targeting RNA Pol II machinery and by inducing chromatin remodeling at stressresponsive loci.
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Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.
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High systemic levels of IP-10 at onset of combination therapy for chronic hepatitis C mirror intrahepatic mRNA levels and predict a slower first phase decline in HCV RNA as well as poor outcome. Recently several genome wide association studies have revealed that single nucleotide polymorphisms (SNPs) on chromosome19 within proximity of IL28B predict spontaneous clearance of HCV infection and as therapeutic outcome among patients infected with HCV genotype 1, with three such SNPs being highly predictive: rs12979860, rs12980275, and rs8099917. In the present study, we correlated genetic variations in these SNPs from 253 Caucasian patients with pretreatment plasma levels of IP-10 and HCV RNA throughout therapy within a phase III treatment trial (HCV-DITTO). The favorable genetic variations in all three SNPs (CC, AA, and TT respectively) was significantly associated with lower baseline IP-10 (CC vs. CT/TT at rs12979860: median 189 vs. 258 pg/mL, P=0.02, AA vs. AG/GG at rs12980275: median 189 vs. 258 pg/mL, P=0.01, TT vs. TG/GG at rs8099917: median 224 vs. 288 pg/mL, P=0.04), were significantly less common among HCV genotype 1 infected patients than genotype 2/3 (P<0.0001, P<0.0001, and P=0.01 respectively) and had significantly higher baseline viral load than carriers of the SNP genotypes (6.3 vs. 5.9 log 10 IU/mL, P=0.0012, 6.3 vs. 6.0 log 10 IU/mL, P=0.026, and 6.3 vs. 5.8 log 10 IU/mL, P=0.0003 respectively). Among HCV genotype 1 infected homozygous or heterogeneous carriers of the favorable C, A, and T genotypes, lower baseline IP-10 was significantly associated with greater decline in HCV-RNA day 0-4, which translated into increased rates of achieving SVR among homozygous patients with baseline IP-10 below 150 pg/mL (85%, 75%, and 75% respectively). In a multivariate analysis among genotype 1 infected patients, both baseline IP-10 and the SNPs were significant independent predictors of SVR. Conclusion: Baseline plasma IP-10 is significantly associated with IL28B variations, and augments the predictiveness of the first phase decline in HCV RNA and final treatment outcome.
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Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P < 5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P = 0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder. © 2012 Wiley Periodicals, Inc.
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Extensive population-based genome-wide association studies have identified an association between the FTO gene and BMI; however, the mechanism of action is still unknown. To determine whether FTO may influence weight regulation through psychological and behavioral factors, seven single-nucleotide polymorphisms (SNPs) of the FTO gene were genotyped in 1,085 individuals with anorexia nervosa (AN) and 677 healthy weight controls from the international Price Foundation Genetic Studies of Eating Disorders. Each SNP was tested in association with eating disorder phenotypes and measures that have previously been associated with eating behavior pathology: trait anxiety, harm-avoidance, novelty seeking, impulsivity, obsessionality, compulsivity, and concern over mistakes. After appropriate correction for multiple comparisons, no significant associations between individual FTO gene SNPs and eating disorder phenotypes or related eating behavior pathology were identified in cases or controls. Thus, this study found no evidence that FTO gene variants associated with weight regulation in the general population are associated with eating disorder phenotypes in AN participants or matched controls. © 2011 Wiley-Liss, Inc.
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Structural variation, whether it is caused by copy number variants or present in a balanced form, such as reciprocal translocations and inversions, can have a profound and dramatic effect on the expression of genes mapping within and close to the rearrangement, as well as affecting others genome wide. These effects can be caused by altering the copy number of one or more genes or regulatory elements (dosage effect) or from physical disruption of links between regulatory elements and their associated gene or genes, resulting in perturbation of expression. Similarly, large-scale structural variants can result in genome-wide expression changes by altering the positions that chromosomes occupy within the nucleus, potentially disrupting not only local cis interactions, but also trans interactions that occur throughout the genome. Structural variation is, therefore, a significant factor in the study of gene expression and is discussed here in more detail.
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We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.
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Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.
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Candidate gene and genome-wide association studies have not identified common variants, which are reliably associated with depression. The recent identification of obesity predisposing genes that are highly expressed in the brain raises the possibility of their genetic contribution to depression. As variation in the intron 1 of the fat mass- and obesity-associated (FTO) gene contributes to polygenic obesity, we assessed the possibility that FTO gene may contribute to depression in a cross-sectional multi-ethnic sample of 6561 depression cases and 21 932 controls selected from the EpiDREAM, INTERHEART, DeCC (depression case-control study) and Cohorte Lausannoise (CoLaus) studies. Major depression was defined according to DSM IV diagnostic criteria. Association analyses were performed under the additive genetic model. A meta-analysis of the four studies showed a significant inverse association between the obesity risk FTO rs9939609 A variant and depression (odds ratio=0.92 (0.89, 0.97), P=3 × 10(-4)) adjusted for age, sex, ethnicity/population structure and body-mass index (BMI) with no significant between-study heterogeneity (I(2)=0%, P=0.63). The FTO rs9939609 A variant was also associated with increased BMI in the four studies (β 0.30 (0.08, 0.51), P=0.0064) adjusted for age, sex and ethnicity/population structure. In conclusion, we provide the first evidence that the FTO rs9939609 A variant may be associated with a lower risk of depression independently of its effect on BMI. This study highlights the potential importance of obesity predisposing genes on depression.
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Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation likely to play a role in phenotypic diversity and evolution. Much effort has been put into the identification and mapping of regions that vary in copy number among seemingly normal individuals in humans and a number of model organisms, using bioinformatics or hybridization-based methods. These have allowed uncovering associations between copy number changes and complex diseases in whole-genome association studies, as well as identify new genomic disorders. At the genome-wide scale, however, the functional impact of CNV remains poorly studied. Here we review the current catalogs of CNVs, their association with diseases and how they link genotype and phenotype. We describe initial evidence which revealed that genes in CNV regions are expressed at lower and more variable levels than genes mapping elsewhere, and also that CNV not only affects the expression of genes varying in copy number, but also have a global influence on the transcriptome. Further studies are warranted for complete cataloguing and fine mapping of CNVs, as well as to elucidate the different mechanisms by which they influence gene expression.
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BACKGROUND: There is an ever-increasing volume of data on host genes that are modulated during HIV infection, influence disease susceptibility or carry genetic variants that impact HIV infection. We created GuavaH (Genomic Utility for Association and Viral Analyses in HIV, http://www.GuavaH.org), a public resource that supports multipurpose analysis of genome-wide genetic variation and gene expression profile across multiple phenotypes relevant to HIV biology. FINDINGS: We included original data from 8 genome and transcriptome studies addressing viral and host responses in and ex vivo. These studies cover phenotypes such as HIV acquisition, plasma viral load, disease progression, viral replication cycle, latency and viral-host genome interaction. This represents genome-wide association data from more than 4,000 individuals, exome sequencing data from 392 individuals, in vivo transcriptome microarray data from 127 patients/conditions, and 60 sets of RNA-seq data. Additionally, GuavaH allows visualization of protein variation in ~8,000 individuals from the general population. The publicly available GuavaH framework supports queries on (i) unique single nucleotide polymorphism across different HIV related phenotypes, (ii) gene structure and variation, (iii) in vivo gene expression in the setting of human infection (CD4+ T cells), and (iv) in vitro gene expression data in models of permissive infection, latency and reactivation. CONCLUSIONS: The complexity of the analysis of host genetic influences on HIV biology and pathogenesis calls for comprehensive motors of research on curated data. The tool developed here allows queries and supports validation of the rapidly growing body of host genomic information pertinent to HIV research.
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PURPOSE: A homozygous mutation in the H6 family homeobox 1 (HMX1) gene is responsible for a new oculoauricular defect leading to eye and auricular developmental abnormalities as well as early retinal degeneration (MIM 612109). However, the HMX1 pathway remains poorly understood, and in the first approach to better understand the pathway's function, we sought to identify the target genes. METHODS: We developed a predictive promoter model (PPM) approach using a comparative transcriptomic analysis in the retina at P15 of a mouse model lacking functional Hmx1 (dmbo mouse) and its respective wild-type. This PPM was based on the hypothesis that HMX1 binding site (HMX1-BS) clusters should be more represented in promoters of HMX1 target genes. The most differentially expressed genes in the microarray experiment that contained HMX1-BS clusters were used to generate the PPM, which was then statistically validated. Finally, we developed two genome-wide target prediction methods: one that focused on conserving PPM features in human and mouse and one that was based on the co-occurrence of HMX1-BS pairs fitting the PPM, in human or in mouse, independently. RESULTS: The PPM construction revealed that sarcoglycan, gamma (35kDa dystrophin-associated glycoprotein) (Sgcg), teashirt zinc finger homeobox 2 (Tshz2), and solute carrier family 6 (neurotransmitter transporter, glycine) (Slc6a9) genes represented Hmx1 targets in the mouse retina at P15. Moreover, the genome-wide target prediction revealed that mouse genes belonging to the retinal axon guidance pathway were targeted by Hmx1. Expression of these three genes was experimentally validated using a quantitative reverse transcription PCR approach. The inhibitory activity of Hmx1 on Sgcg, as well as protein tyrosine phosphatase, receptor type, O (Ptpro) and Sema3f, two targets identified by the PPM, were validated with luciferase assay. CONCLUSIONS: Gene expression analysis between wild-type and dmbo mice allowed us to develop a PPM that identified the first target genes of Hmx1.