Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci.
Reza K HammondMatthew C PahlChun SuDiana L CousminerMichelle E LeonardSumei LuClaudia A DoegeYadav WagleyKenyaita M HodgeChiara LasconiMatthew E JohnsonJames A PippinKurt D HankensonRudolph L LeibelAlessandra ChesiAndrew D WellsStruan F A GrantPublished in: eLife (2021)
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.
Keyphrases
- genome wide
- dna methylation
- copy number
- genome wide association
- body mass index
- genome wide association study
- stem cells
- gene expression
- big data
- endothelial cells
- electronic health record
- transcription factor
- spinal cord
- dna damage
- type diabetes
- adipose tissue
- metabolic syndrome
- weight gain
- machine learning
- quality improvement
- cell therapy
- artificial intelligence
- total hip arthroplasty
- pluripotent stem cells