Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases. Issue 6 (20th December 2021)

• Record Type: Journal Article
• Authors: Jiang, Lin; Jiang, Hui; Dai, Sheng; Chen, Ying; Song, Youqiang; Tang, Clara Sze-Man; Pang, Shirley Yin-Yu; Ho, Shu-Leong; Wang, Binbin; Garcia-Barcelo, Maria-Mercedes; Tam, Paul Kwong-Hang; Cherny, Stacey S; Li, Mulin Jun; Sham, Pak Chung; Li, Miaoxin
• Is Part Of: Nucleic acids research. Volume 50:Issue 6(2022)
• Page Start: e34
• Page End: e34
• Publication Date: 2021-12-20
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkab1234
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Identifying rare variants that contribute to complex diseases is challenging because of the low statistical power in current tests comparing cases with controls. Here, we propose a novel and powerful rare variants association test based on the deviation of the observed mutation burden of a gene in cases from a baseline predicted by a weighted recursive truncated negative-binomial regression (RUNNER) on genomic features available from public data. Simulation studies show that RUNNER is substantially more powerful than state-of-the-art rare variant association tests and has reasonable type 1 error rates even for stratified populations or in small samples. Applied to real case-control data, RUNNER recapitulates known genes of Hirschsprung disease and Alzheimer's disease missed by current methods and detects promising new candidate genes for both disorders. In a case-only study, RUNNER successfully detected a known causal gene of amyotrophic lateral sclerosis. The present study provides a powerful and robust method to identify susceptibility genes with rare risk variants for complex diseases.