171 research outputs found
Analysis of GWAS top hits in ADHD suggests association to two polymorphisms located in genes expressed in the cerebellum
No full textAttention deficit/hyperactivity disorder (ADHD) is a common psychiatric disorder influenced by genetic factors. Several chromosomal regions with potential linkage and candidate genes associations have been reported, but findings are often inconsistent and non-replicated. The few genome-wide association studies (GWAS) carried out so far differ for study design and phenotypes analyzed, and did not detect any association significant at the genome-wide level. In the present study we examined the top SNPs reported in the GWAS by Neale et al. [2008] in an independent cohort. Although our sample size is smaller (415 trios vs. 909), the power was sufficient to confirm the role of candidate markers in ADHD if a true association exists. Two out of 36 top SNPs were significant at alpha = 0.05 in our sample, although none was still significant after correction for multiple tests. These two SNPs are both located in genes coding for as yet uncharacterized proteins expressed in the cerebellum, XKR4 in 8q12.1, and FAM190A in 4q22.1. Three other FAM190A SNPs have TDT P-values of <10(-5) in our sample, a level of significance only reached by a total of five SNPs in our genome-wide data. While these findings could be due to chance, we cannot exclude that these markers are indeed associated to disease risk. Remarkably, brain imaging studies have shown reduction of the posterior inferior cerebellar lobules volume of ADHD boys and girls compared to controls, persistent with age and not present in unaffected siblings, suggesting that the cerebellum may be directly related to pathophysiology of ADHD. (C) 2010 Wiley-Liss, Inc
Biological role and disease impact of copy number variation in complex disease
No full textIn the human genome, DNA variants give rise to a variety of complex phenotypes. Ranging from single base mutations to copy number variations (CNVs), many of these variants are neutral in selection and disease etiology, making difficult the detection of true common or rare frequency disease-causing mutations. However, allele frequency comparisons in cases, controls, and families may reveal disease associations. Single nucleotide polymorphism (SNP) arrays and exome sequencing are popular assays for genome-wide variant identification. To limit bias between samples, uniform testing is crucial, including standardized platform versions and sample processing. Bases occupy single points while copy variants occupy segments. Bases are bi-allelic while copies are multi-allelic. One genome also encodes many different cell types. In this study, we investigate how CNV impacts different cell types, including heart, brain and blood cells, all of which serve as models of complex disease. Here, we describe ParseCNV, a systematic algorithm specifically developed as a part of this project to perform more accurate disease associations using SNP arrays or exome sequencing-generated CNV calls with quality tracking of variants, contributing to each significant overlap signal. Red flags of variant quality, genomic region, and overlap profile are assessed in a continuous score and shown to correlate over 90% with independent verification methods. We compared these data with our large internal cohort of 68,000 subjects, with carefully mapped CNVs, which gave a robust rare variant frequency in unaffected populations. In these investigations, we uncovered a number of loci in which CNVs are significantly enriched in non-coding RNA (ncRNA), Online Mendelian Inheritance in Man (OMIM), and genome-wide association study (GWAS) regions, impacting complex disease. By evaluating thoroughly the variant frequencies in pediatric individuals, we subsequently compared these frequencies in geriatric individuals to gain insight of these variants\u27 impact on lifespan. Longevity-associated CNVs enriched in pediatric patients were found to aggregate in alternative splicing genes. Congenital heart disease is the most common birth defect and cause of infant mortality. When comparing congenital heart disease families, with cases and controls genotyped both on SNP arrays and exome sequencing, we uncovered significant and confident loci that provide insight into the molecular basis of disease. Neurodevelopmental disease affects the quality of life and cognitive potential of many children. In the neurodevelopmental and psychiatric diseases, CACNA, GRM, CNTN, and SLIT gene families show multiple significant signals impacting a large number of developmental and psychiatric disease traits, with the potential of informing therapeutic decision-making. Through new tool development and analysis of large disease cohorts genotyped on a variety of assays, I have uncovered an important biological role and disease impact of CNV in complex disease
Evidence from human and zebrafish that GPC1 is a biliary atresia susceptibility gene.
No full textBackground & Aims: Biliary atresia (BA) is a progressive fibroinflammatory disorder of infants involving the extrahepatic and intrahepatic biliary tree. Its etiology is unclear but is believed to involve exposure of a genetically susceptible individual to certain environmental factors. BA occurs exclusively in the neonatal liver, so variants of genes expressed during hepatobiliary development could affect susceptibility. Genome-wide association studies previously identified a potential region of interest at 2q37. We continued these studies to narrow the region and identify BA susceptibility genes. Methods: We searched for copy number variants that were increased among patients with BA (n = 61) compared with healthy individuals (controls; n = 5088). After identifying a candidate gene, we investigated expression patterns of orthologues in zebrafish liver and the effects of reducing expression, with morpholino antisense oligonucleotides, on biliary development, gene expression, and signal transduction. Results: We observed a statistically significant increase in deletions at 2q37.3 in patients with BA that resulted in deletion of one copy of GPC1, which encodes glypican 1, a heparan sulfate proteoglycan that regulates Hedgehog signaling and inflammation. Knockdown of gpc1 in zebrafish led to developmental biliary defects. Exposure of the gpc1 morphants to cyclopamine, a Hedgehog antagonist, partially rescued the gpc1-knockdown phenotype. Injection of zebrafish with recombinant Sonic Hedgehog led to biliary defects similar to those of the gpc1 morphants. Liver samples from patients with BA had reduced levels of apical GPC1 in cholangiocytes compared with samples from controls. Conclusions: Based on genetic analysis of patients with BA and zebrafish, GPC1 appears to be a BA susceptibility gene. These findings also support a role for Hedgehog signaling in the pathogenesis of BA. © 2013 AGA Institute
Genome-wide Association: From Confounded to Confident
No full text Genome-wide association studies (GWAS) allow for a large number of samples to be assayed simultaneously, using a genome-wide tagging single nucleotide polymorphism (SNP) approach. The initial boon of success from disease studies such as macular degeneration and inflammatory bowel disease has been mitigated by lack of genome-wide significance for psychiatric disorders and related traits, despite evaluations of large populations. In addition to SNP genotypes, which are common variants typically attributing small or modest relative risk, copy number variations can be detected based on the same data set. Several rare recurrent copy number variations have been associated with psychiatric diseases in genome-wide analyses. Proper and responsible study design, followed by rigorous data quality assessment of genomic matching of cases and controls, is most likely to uncover regions of significant association that replicate in independent cohorts, thereby maximizing the chance of significant and confident association. </jats:p
Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps.
No full textWhere causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways.We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our "pathways group lasso with adaptive weights" (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets.In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small
Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
No full textMultiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis
Data-informed insights into sex differences in peripheral blood mononuclear cells from single-cell transcriptomics
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A genome-wide scan for common alleles affecting risk for autism
No full textAlthough autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C
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