Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution

Arkan Abadi; Akram Alyass; Sebastien Robiou du Pont; Ben Bolker; Pardeep Singh; Viswanathan Mohan; Rafael Diaz; James C Engert; Salim Yusuf; Hertzel C Gerstein; Sonia S Anand; David Meyre

doi:10.1016/j.ajhg.2017.10.007

Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution

Am J Hum Genet. 2017 Dec 7;101(6):925-938. doi: 10.1016/j.ajhg.2017.10.007.

Authors

Affiliations

¹ Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada.
² Department of Mathematics and Statistics, McMaster University, Hamilton, ON L8S 4L8, Canada.
³ Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.
⁴ Madras Diabetes Research Foundation, Gopalapuram, Chennai 600086, India.
⁵ Estudios Clínicos Latino America, Paraguay 160, S2000CVD Rosario, Santa Fe, Argentina.
⁶ McGill University, Montreal, QC H3A 0G4, Canada.
⁷ Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.
⁸ Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada. Electronic address: meyred@mcmaster.ca.

Abstract

A growing number of single-nucleotide polymorphisms (SNPs) have been associated with body mass index (BMI) and obesity, but whether the effects of these obesity-susceptibility loci are uniform across the BMI distribution remains unclear. We studied the effects of 37 BMI-associated SNPs in 75,230 adults of European ancestry across BMI percentiles by using conditional quantile regression (CQR) and meta-regression (MR) models. The effects of nine SNPs (24%)-rs1421085 (FTO; p = 8.69 × 10^-15), rs6235 (PCSK1; p = 7.11 × 10^-6), rs7903146 (TCF7L2; p = 9.60 × 10^-6), rs11873305 (MC4R; p = 5.08 × 10^-5), rs12617233 (FANCL; p = 5.30 × 10^-5), rs11672660 (GIPR; p = 1.64 × 10^-4), rs997295 (MAP2K5; p = 3.25 × 10^-4), rs6499653 (FTO; p = 6.23 × 10^-4), and rs3824755 (NT5C2; p = 7.90 × 10^-4)-increased significantly across the sample BMI distribution. We showed that such increases stemmed from unadjusted gene interactions that enhanced the effects of SNPs in persons with a high BMI. When 125 height-associated SNPs were analyzed for comparison, only one (<1%), rs6219 (IGF1, p = 1.80 × 10^-4), showed effects that varied significantly across height percentiles. Cumulative gene scores of these SNPs (GS-BMI and GS-height) showed that only GS-BMI had effects that increased significantly across the sample distribution (BMI: p = 7.03 × 10^-37; height: p = 0.499). Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method for detecting such interactions by using only the sample outcome distribution.

Keywords: body mass index; conditional quantile regression; epistasis; gene score; gene-environment interactions; height; missing heritability; polygenic inheritance; quantitative trait distribution; variable allele penetrance.

MeSH terms

Adult
Aged
Aged, 80 and over
Body Height / genetics*
Body Mass Index*
Gene Frequency
Gene-Environment Interaction
Genetic Predisposition to Disease / genetics
Humans
Middle Aged
Multifactorial Inheritance / genetics*
Obesity / genetics*
Penetrance*
Polymorphism, Single Nucleotide / genetics
Quantitative Trait Loci / genetics
White People / genetics
Young Adult