Exploiting pleiotropy to enhance variant discovery with functional false discovery rates

Abstract

The cost of acquiring participants for genome-wide association studies (GWAS) can limit sample sizes and inhibit discovery of genetic variants. We introduce the surrogate functional false discovery rate (sfFDR) framework which integrates summary statistics of related traits to increase power. The sfFDR framework provides estimates of FDR quantities such as the functional local FDR and q-value, and uses these estimates to derive a functional p-value for type I error rate control and a functional local Bayes’ factor for post-GWAS analyses (e.g., fine mapping and colocalization). Compared to a standard analysis, sfFDR substantially increased power (equivalent to a 60% increase in sample size) in a study of obesity-related traits from the UK Biobank, and discovered eight additional lead SNPs near genes linked to immune-related responses in a rare disease GWAS of eosinophilic granulomatosis with polyangiitis. Collectively, these results highlight the utility of exploiting related traits in both small and large studies.

Competing Interest Statement

C.W. has received funding from GSK and MSD and is a part time employee of GSK. These companies had no input into this work.

Funding Statement

This work was supported by the Wellcome Trust (WT220788, WT219506) and the MRC (MC_UU_00002/4, MC_UU_00040/01).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study used publicly available data that were originally located at https://www.ebi.ac.uk/gwas and https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

sfFDR is publicly available in the R package {\tt sffdr} and can be downloaded at https://github.com/ajbass/sffdr. The code to reproduce the results in this work can be found at https://github.com/ajbass/sffdr_manuscript and the GWAS summary statistics used in the EGPA analysis are publicly available to download at https://www.ebi.ac.uk/gwas. Access to the UK Biobank data can be requested at https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access.

https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access

https://www.ebi.ac.uk/gwas

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