<i>P</i>‐value based analysis for shared controls design in genome‐wide association studies

Zaykin, Dmitri V.; Kozbur, Damian

doi:10.1002/gepi.20536

Cited by 41 publications

(48 citation statements)

References 26 publications

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“…There was no evidence of genomic inflation. To identify shared pAID-association loci, we performed an inverse χ 2 meta-analysis, accounting for sample-size variation and the use of a shared control across the ten pAIDs 25 . We identified 27 linkage disequilibrium (LD)-independent loci, consisting of associated SNPs with r 2 > 0.05 within a 1-Mb window where at least one lead SNP reached a conventionally defined GWS threshold ( P < 5 × 10 −8 ; Fig.…”

Section: Resultsmentioning

confidence: 99%

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Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Zhao

et al. 2015

Nat Med

243

180

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Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ2 meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico–replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases.

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Section: Resultsmentioning

confidence: 99%

“…To adjust for confounding due to the use of a shared or pooled control population, we applied a previously published method to perform an inverse weighted χ 2 meta-analysis 80 .…”

Section: Methodsmentioning

confidence: 99%

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Zhao

et al. 2015

Nat Med

243

180

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“…Second, we used the method of Zaykin and Kozbur 21 , which is similar to the method by Lin and Sullivan 22 to account for overlap of an estimated ~38,000 controls between the CARDIoGRAM and METASTROKE samples from the KORA, WTCCC2, CHARGE and deCODE studies (the exact number of overlapping controls could not be determined in the absence of individualized data) which may lead to the inflation of meta-analysis p-values. This program compensates for this lack of independence in test statistics created by the use of the same controls by computing the correlation between studies and using this measure for correction of p-values obtained from a standard meta-analysis.…”

Section: Methodsmentioning

confidence: 99%

Shared Genetic Susceptibility to Ischemic Stroke and Coronary Artery Disease

Dichgans

Malik

König

et al. 2014

Stroke

309

224

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Summary Background and Purpose Ischemic stroke (IS) and coronary artery disease (CAD) share several risk factors and each have a substantial heritability. We conducted a genome-wide analysis to evaluate the extent of shared genetic determination of the two diseases. Methods Genome-wide association data were obtained from the METASTROKE, CARDIoGRAM, and C4D consortia. We first analyzed common variants reaching a nominal threshold of significance (p<0.01) for CAD for their association with IS and vice versa. We then examined specific overlap across phenotypes for variants that reached a high threshold of significance. Finally, we conducted a joint meta-analysis on the combined phenotype of IS or CAD. Corresponding analyses were performed restricted to the 2,167 individuals with the ischemic large artery stroke (LAS) subtype. Results Common variants associated with CAD at p<0.01 were associated with a significant excess risk for IS and for LAS and vice versa. Among the 42 known genome-wide significant loci for CAD, three and five loci were significantly associated with IS and LAS, respectively. In the joint meta-analyses, 15 loci passed genome-wide significance (p<5×10-8) for the combined phenotype of IS or CAD and 17 loci passed genome-wide significance for LAS or CAD. Since these loci had prior evidence for genome-wide significance for CAD we specifically analyzed the respective signals for IS and LAS and found evidence for association at chr12q24/SH2B3 (pIS=1.62×10-07) and ABO (pIS =2.6×10-4) as well as at HDAC9 (pLAS=2.32×10-12), 9p21 (pLAS =3.70×10-6), RAI1-PEMT-RASD1 (pLAS =2.69×10-5), EDNRA (pLAS =7.29×10-4), and CYP17A1-CNNM2-NT5C2 (pLAS =4.9×10-4). Conclusions Our results demonstrate substantial overlap in the genetic risk of ischemic stroke and particularly the large artery stroke subtype with coronary artery disease.

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“…For example, a common assumption in a meta-analysis is the independence of samples in the studies to be combined. If this assumption is violated, for example, because of overlap of a subset of individuals across studies, this may result in spurious associations (Lin and Sullivan, 2009;Zaykin and Kozbur, 2010). Similarly, in a comparative study, differences in sample size between data sets can have an adverse effect in an intersection analysis.…”

Section: Discussionmentioning

confidence: 99%

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies

et al. 2016

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The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana, using flowering and growth-related traits.

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P‐value based analysis for shared controls design in genome‐wide association studies

Cited by 41 publications

References 26 publications

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Shared Genetic Susceptibility to Ischemic Stroke and Coronary Artery Disease

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies

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