PROTEIN-CODING VARIANTS IMPLICATE NOVEL GENES RELATED TO LIPID HOMEOSTASIS CONTRIBUTING TO BODY FAT DISTRIBUTION
Anne E. JusticeiD, Tugce KaraderiiD, Heather M. HighlandiD, Kristin L. YoungiD, Mariaelisa GraffiD, Yingchang LuiD, Valérie TurcotiD, Paul Livermore AueriD, Rebecca S. FineiD, Xiuqing GuoiD, Claudia SchurmanniD, Adelheid M. LempradliD, Eirini MarouliiD, Anubha MahajaniD, Thomas W. WinkleriD, Adam E. LockeiD, Carolina Medina‐GómeziD, Tõnu EskoiD, Sailaja VedantamiD, Ayush GiriiD, Ken Sin LoiD, Tamuno Alfred, Poorva Mudgal, Maggie C.Y. NgiD, Nancy L. Heard‐CostaiD, , Andrew Tym HattersleyiD
Abstract
Body fat distribution is a heritable risk factor for a range of adverse health consequences, including hyperlipidemia and type 2 diabetes. To identify protein-coding variants associated with body fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, we analyzed 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries for discovery and 132,177 independent European-ancestry individuals for validation. We identified 15 common (minor allele frequency, MAF[≥]5%) and 9 low frequency or rare (MAF<5%) coding variants that have not been reported previously. Pathway/gene set enrichment analyses of all associated variants highlight lipid particle, adiponectin level, abnormal white adipose tissue physiology, and bone development and morphology as processes affecting fat distribution and body shape. Furthermore, the cross-trait associations and the analyses of variant and gene function highlight a strong connection to lipids, cardiovascular traits, and type 2 diabetes. In functional follow-up analyses, specifically in Drosophila RNAi-knockdown crosses, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). By examining variants often poorly tagged or entirely missed by genome-wide association studies, we implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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