| Literature DB >> 33459256 |
Reza K Hammond1,2, Matthew C Pahl1,2, Chun Su1,2, Diana L Cousminer1,2, Michelle E Leonard1,2, Sumei Lu1,2, Claudia A Doege3,4,5, Yadav Wagley6, Kenyaita M Hodge1,2, Chiara Lasconi1,2, Matthew E Johnson1,2, James A Pippin1,2, Kurt D Hankenson6, Rudolph L Leibel7, Alessandra Chesi1,2, Andrew D Wells1,8,9, Struan Fa Grant1,2,10,11,12.
Abstract
To uncover novel significant association signals (p<5×10-8), genome-wide association studies (GWAS) requires increasingly larger sample sizes to overcome statistical correction for multiple testing. As an alternative, we aimed to identify associations among suggestive signals (5 × 10-8≤p<5×10-4) in increasingly powered GWAS efforts using chromatin accessibility and direct contact with gene promoters as biological constraints. We conducted retrospective analyses of three GIANT BMI GWAS efforts using ATAC-seq and promoter-focused Capture C data from human adipocytes and embryonic stem cell (ESC)-derived hypothalamic-like neurons. This approach, with its extremely low false-positive rate, identified 15 loci at p<5×10-5 in the 2010 GWAS, of which 13 achieved genome-wide significance by 2018, including at NAV1, MTIF3, and ADCY3. Eighty percent of constrained 2015 loci achieved genome-wide significance in 2018. We observed similar results in waist-to-hip ratio analyses. In conclusion, biological constraints on sub-significant GWAS signals can reveal potentially true-positive loci for further investigation in existing data sets without increasing sample size.Entities:
Keywords: Capture C; GWAS; bioinformatics; body mass index; computational biology; functional genomics; genetics; genomics; human; systems biology; waist-hip ratio
Mesh:
Year: 2021 PMID: 33459256 PMCID: PMC7815306 DOI: 10.7554/eLife.62206
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140