Boosting the power of rare variant association studies by imputation using large-scale sequencing population

Rare variants can explain part of the heritability of complex traits that are ignored by conventional GWASs. The emergence of large-scale population sequencing data provides opportunities to study rare variants. However, few studies systematically evaluate the extent to which imputation using sequencing data can improve the power of rare variant association studies. Using whole genome sequencing (WGS) data (n = 150,119) as the ground truth, we described the landscape and evaluated the consistency of rare variants in SNP array (n = 488,377) imputed from TOPMed or HRC+UK10K in the UK Biobank, respectively. The TOPMed imputation covered more rare variants, and its imputation quality could reach 0.5 for even extremely rare variants. TOPMed-imputed data was closer to WGS in all MAC intervals for three ethnicities (average Cramer’s V>0.75). Furthermore, association tests were performed on 30 quantitative and 15 binary traits. Compared to WGS data, the identified rare variants in TOPMed-imputed data increased 27.71% for quantitative traits, while it could be improved by ∼10-fold for binary traits. In gene-based analysis, the signals in TOPMed-imputed data increased 111.45% for quantitative traits, and it identified 15 genes in total, while WGS only found 6 genes for binary traits. Finally, we harmonized SNP array and WGS data for lung cancer and epithelial ovarian cancer. More variants and genes could be identified than from WGS data alone, such as BRCA1 , BRCA2 , and CHRNA5 . Our findings highlighted that incorporating rare variants imputed from large-scale sequencing populations could greatly boost the power of GWAS. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement National Natural Science Foundation of China (82373685 and 82373685 to S.S., 82220108002 to F.C., 82103946 and 82173620 to Y.Z.), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (21KJB330004 to S.S.), and US NIH (NCI) grant #U01CA209414 to DCC. ### 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: UK Biobank data, ILCCO-Oncoarray data, TRICL data, PLCO data, FOCI-Exome Chip data, FOCI-OncoArray Chip, CIMBA, gnomAD, dnSNP 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