Meta-analysis Of Genome-wide Association Scans Research Articles

Neuroimaging genetic analyses of novel candidate genes associated with reading and language

Neuroimaging measures provide useful endophenotypes for tracing genetic effects on reading and language. A recent Genome-Wide Association Scan Meta-Analysis (GWASMA) of reading and language skills (N=1862) identified strongest associations with the genes CCDC136/FLNC and RBFOX2. Here, we follow up the top findings from this GWASMA, through neuroimaging genetics in an independent sample of 1275 healthy adults. To minimize multiple-testing, we used a multivariate approach, focusing on cortical regions consistently implicated in prior literature on developmental dyslexia and language impairment. Specifically, we investigated grey matter surface area and thickness of five regions selected a priori: middle temporal gyrus (MTG); pars opercularis and pars triangularis in the inferior frontal gyrus (IFG-PO and IFG-PT); postcentral parietal gyrus (PPG) and superior temporal gyrus (STG). First, we analysed the top associated polymorphisms from the reading/language GWASMA: rs59197085 (CCDC136/FLNC) and rs5995177 (RBFOX2). There was significant multivariate association of rs5995177 with cortical thickness, driven by effects on left PPG, right MTG, right IFG (both PO and PT), and STG bilaterally. The minor allele, previously associated with reduced reading-language performance, showed negative effects on grey matter thickness. Next, we performed exploratory gene-wide analysis of CCDC136/FLNC and RBFOX2; no other associations surpassed significance thresholds. RBFOX2 encodes an important neuronal regulator of alternative splicing. Thus, the prior reported association of rs5995177 with reading/language performance could potentially be mediated by reduced thickness in associated cortical regions. In future, this hypothesis could be tested using sufficiently large samples containing both neuroimaging data and quantitative reading/language scores from the same individuals.

Genome-Wide Association Study to Identify Common Variants Associated with Brachial Circumference: A Meta-Analysis of 14 Cohorts

Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.

Genomic risk profiling of ischemic stroke: results of an international genome-wide association meta-analysis.

IntroductionFamilial aggregation of ischemic stroke derives from shared genetic and environmental factors. We present a meta-analysis of genome-wide association scans (GWAS) from 3 cohorts to identify the contribution of common variants to ischemic stroke risk.MethodsThis study involved 1464 ischemic stroke cases and 1932 controls. Cases were genotyped using the Illumina 610 or 660 genotyping arrays; controls, with Illumina HumanHap 550Kv1 or 550Kv3 genotyping arrays. Imputation was performed with the 1000 Genomes European ancestry haplotypes (August 2010 release) as a reference. A total of 5,156,597 single-nucleotide polymorphisms (SNPs) were incorporated into the fixed effects meta-analysis. All SNPs associated with ischemic stroke (P<1×10−5) were incorporated into a multivariate risk profile model.ResultsNo SNP reached genome-wide significance for ischemic stroke (P<5×10−8). Secondary analysis identified a significant cumulative effect for age at onset of stroke (first versus fifth quintile of cumulative profiles based on SNPs associated with late onset, ß = 14.77 [10.85,18.68], P = 5.5×10−12), as well as a strong effect showing increased risk across samples with a high propensity for stroke among samples with enriched counts of suggestive risk alleles (P<5×10−6). Risk profile scores based only on genomic information offered little incremental prediction.DiscussionThere is little evidence of a common genetic variant contributing to moderate risk of ischemic stroke. Quintiles based on genetic loading of alleles associated with a younger age at onset of ischemic stroke revealed a significant difference in age at onset between those in the upper and lower quintiles. Using common variants from GWAS and imputation, genomic profiling remains inferior to family history of stroke for defining risk. Inclusion of genomic (rare variant) information may be required to improve clinical risk profiling.

A meta-analysis of genome-wide association scans identifies IL18RAP, PTPN2, TAGAP, and PUS10 as shared risk loci for Crohn's disease and celiac disease.

Crohn's disease (CD) and celiac disease (CelD) are chronic intestinal inflammatory diseases, involving genetic and environmental factors in their pathogenesis. The two diseases can co-occur within families, and studies suggest that CelD patients have a higher risk to develop CD than the general population. These observations suggest that CD and CelD may share common genetic risk loci. Two such shared loci, IL18RAP and PTPN2, have already been identified independently in these two diseases. The aim of our study was to explicitly identify shared risk loci for these diseases by combining results from genome-wide association study (GWAS) datasets of CD and CelD. Specifically, GWAS results from CelD (768 cases, 1,422 controls) and CD (3,230 cases, 4,829 controls) were combined in a meta-analysis. Nine independent regions had nominal association p-value <1.0×10−5 in this meta-analysis and showed evidence of association to the individual diseases in the original scans (p-value <1×10−2 in CelD and <1×10−3 in CD). These include the two previously reported shared loci, IL18RAP and PTPN2, with p-values of 3.37×10−8 and 6.39×10−9, respectively, in the meta-analysis. The other seven had not been reported as shared loci and thus were tested in additional CelD (3,149 cases and 4,714 controls) and CD (1,835 cases and 1,669 controls) cohorts. Two of these loci, TAGAP and PUS10, showed significant evidence of replication (Bonferroni corrected p-values <0.0071) in the combined CelD and CD replication cohorts and were firmly established as shared risk loci of genome-wide significance, with overall combined p-values of 1.55×10−10 and 1.38×10−11 respectively. Through a meta-analysis of GWAS data from CD and CelD, we have identified four shared risk loci: PTPN2, IL18RAP, TAGAP, and PUS10. The combined analysis of the two datasets provided the power, lacking in the individual GWAS for single diseases, to detect shared loci with a relatively small effect.

The association between BANK1 and TNFAIP3 gene polymorphisms and systemic lupus erythematosus: a meta-analysis

The past decade has witnessed hundreds of reports declaring or not being able to replicable genetic association with systemic lupus erythematosus (SLE) susceptibility. BANK1 is a gene that encodes a B-cell-specific scaffold protein and its activation can affect B-cell-receptor-induced calcium mobilization from intracellular calcium stores. TNFAIP3 encodes the ubiquitin-modifying enzyme, also known as A20, which is a cytoplasmic zinc finger protein that inhibits nuclear factor kappa-B (NFKB) activity and tumour necrosis factor (TNF)-mediated programmed cell death. The association of BANK1 and TNFAIP3 polymorphism with SLE has been reported in several studies. The aim of this study was to assess whether combined evidence shows the association between BANK1 and TNFAIP3 polymorphism and SLE. We report the results of a meta-analysis of genome-wide association scans and replication in independent sets for BANK1 and TNFAIP3 polymorphism and SLE that includes 12,416 subjects with SLE and 19,113 control subjects. Meta-odds ratios (ORs) and 95% confidence intervals (CIs) based on random effects models. Both of BANK1 and TNFAIP3 harbour several controversial single nucleotide polymorphisms (SNPs). We selected and identified three SNPs of BANK1 associated with SLE (rs17266594, P = 1.949e-10; OR = 1.380; 95% CI: 1.250-1.525; rs10516487, P = 2.642e-13; OR = 1.317; 95% CI: 1.223-1.417; rs3733197, P = 3.452e-06; OR = 1.193; 95% CI: 1.107-1.286); one SNP of TNFAIP3 associated with SLE (rs2230926, P = 1.502e-12; OR = 1.826; 95% CI: 1.545-2.157). This meta-analysis demonstrates a significant association between BANK1 and TNFAIP3 gene polymorphism and SLE in multiple ethnic populations. These findings reinforce the value of large sample series for discovery and follow-up of genetic variants contributing to the aetiology of SLE.

Meta-analysis of gene-environment interaction: joint estimation of SNP and SNP × environment regression coefficients.

Genetic discoveries are validated through the meta-analysis of genome-wide association scans in large international consortia. Because environmental variables may interact with genetic factors, investigation of differing genetic effects for distinct levels of an environmental exposure in these large consortia may yield additional susceptibility loci undetected by main effects analysis. We describe a method of joint meta-analysis (JMA) of SNP and SNP by Environment (SNP × E) regression coefficients for use in gene-environment interaction studies. In testing SNP × E interactions, one approach uses a two degree of freedom test to identify genetic variants that influence the trait of interest. This approach detects both main and interaction effects between the trait and the SNP. We propose a method to jointly meta-analyze the SNP and SNP × E coefficients using multivariate generalized least squares. This approach provides confidence intervals of the two estimates, a joint significance test for SNP and SNP × E terms, and a test of homogeneity across samples. We present a simulation study comparing this method to four other methods of meta-analysis and demonstrate that the JMA performs better than the others when both main and interaction effects are present. Additionally, we implemented our methods in a meta-analysis of the association between SNPs from the type 2 diabetes-associated gene PPARG and log-transformed fasting insulin levels and interaction by body mass index in a combined sample of 19,466 individuals from five cohorts.

Meta-analysis of genome-wide association scans for genetic susceptibility to endometriosis in Japanese population

To identify susceptibility genes for endometriosis in Japanese women, genome-wide association (GWA) analysis was performed using two case-control cohorts genotyped with the Affymetrix Mapping 500K Array or Genome-Wide Human SNP Array 6.0. In each of the two array cohorts, stringent quality control (QC) filters were applied to newly obtained genotype data, together with previously analyzed data from the Japanese Integrated Database Project. After QC-based filtering of samples and single nucleotide polymorphisms (SNPs) in each cohort, 282 838 SNPs in both genotyping platforms were tested for association with endometriosis using a meta-analysis of the two GWA studies with 696 patients with endometriosis and 825 controls. The meta-analysis revealed that a common susceptibility locus conferring a large effect on the disease risk was unlikely. On the other hand, an excess of SNPs with P-values <10(-4) (36 vs 28 SNPs expected by chance) was observed in the meta-analysis. Of note, four of the top five SNPs with P-values <10(-5) were located in and around IL1A (interleukin 1α), which might be a functional candidate gene for endometriosis. Further studies with larger case-control cohorts will be necessary to elucidate the genetic risk factors.

METAL: fast and efficient meta-analysis of genomewide association scans

Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats.Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/Contact: goncalo@umich.edu

METAL: fast and efficient meta-analysis of genomewide association scans

METAL: fast and efficient meta-analysis of genomewide association scans

METAL: Fast and efficient meta-analysis of genomewide association scans

METAL: Fast and efficient meta-analysis of genomewide association scans

Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci

We report the results of a meta-analysis of genome-wide association scans for multiple sclerosis (MS) susceptibility that includes 2,624 subjects with MS and 7,220 control subjects. Replication in an independent set of 2,215 subjects with MS and 2,116 control subjects validates new MS susceptibility loci at TNFRSF1A (combined P = 1.59 x 10(-11)), IRF8 (P = 3.73 x 10(-9)) and CD6 (P = 3.79 x 10(-9)). TNFRSF1A harbors two independent susceptibility alleles: rs1800693 is a common variant with modest effect (odds ratio = 1.2), whereas rs4149584 is a nonsynonymous coding polymorphism of low frequency but with stronger effect (allele frequency = 0.02; odds ratio = 1.6). We also report that the susceptibility allele near IRF8, which encodes a transcription factor known to function in type I interferon signaling, is associated with higher mRNA expression of interferon-response pathway genes in subjects with MS.

Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.