Genetic risk sum score comprised of common polygenic variation is associated with body mass index

Abstract

Genome-wide association studies (GWAS) of body mass index (BMI) using large samples have yielded approximately a dozen robustly associated variants and implicated additional loci. Individually these variants have small effects and in aggregate explain a small proportion of the variance. As a result, replication attempts have limited power to achieve genome-wide significance, even with several thousand subjects. Since there is strong prior evidence for genetic influence on BMI for specific variants, alternative approaches to replication can be applied. Instead of testing individual loci sequentially, a genetic risk sum score (GRSS) summarizing the total number of risk alleles can be tested. In the current study, GRSS comprising 56 top variants catalogued from two large meta-analyses was tested for association with BMI in the Molecular Genetics of Schizophrenia controls (2,653 European-Americans, 973 African-Americans). After accounting for covariates known to influence BMI (ancestry, sex, age), GRSS was highly associated with BMI (p value = 3.19E−06) although explained a limited amount of the variance (0.66%). However, area under receiver operator criteria curve (AUC) estimates indicated that the GRSS and covariates significantly predicted overweight and obesity classification with maximum discriminative ability for predicting class III obesity (AUC = 0.697). The relative contributions of the individual loci to GRSS were examined post hoc and the results were not due to a few highly significant variants, but rather the result of numerous variants of small effect. This study provides evidence of the utility of a GRSS as an alternative approach to replication of common polygenic variation in complex traits.

Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At‐Risk Individuals

“…Many genomic variants together contribute to overall risk (termed polygenic risk) for a number of complex traits [Peterson et al, 2011; Hamshere et al, 2013; Meyers et al, 2013], and this genetic architecture is evident in a number of psychiatric conditions—including BP [Purcell et al, 2009; Lee et al, 2012, 2013; Smoller et al, 2013; Bramon et al, 2014]. While the elucidation of the genetic causes for BP has been challenging, the field is progressing in understanding the genetic architecture of this complex disorder (reviewed in [Craddock and Sklar, 2013]) and in identifying specific genes which increase risk [Sklar et al, 2011].…”

Obesity polymorphisms identified in genome-wide association studies interact with n-3 polyunsaturated fatty acid intake and modify the genetic association with adiposity phenotypes in Yup’ik people

“…Li et al (2010) included 12 SNPs that explained 0.9 % of BMI variation in Europeans, Takeuchi et al (2011) calculated a GRS with 14 SNPs that explained 0.65 % among Japanese, and Peterson et al (2011) included 56 SNPs explained 0.66 % of the variation in BMI among a mixed sample of European-and African-Americans. We calculated a GRS in this study using 5 obesity GWAS SNPs that overlap with Li et al (2010), 7 obesity GWAS SNPs that overlap with Takeuchi et al (2011), and 9 obesity GWAS SNPs that overlap with Peterson et al (2011). Taken together, these results suggest that while considerable progress has been made in gene discovery, obesity SNPs highly replicated in GWAS do not yet predict a significant proportion of the heritability attributed to adiposity phenotypes.…”

Interactions of genetic and environmental risk factors with respect to body fat mass in children: Results from the ALSPAC study

“…Evidence comes originally from adoption and twin studies (1,2) and has been confirmed in recent genome-wide association (GWA) studies, in which a number of risk alleles for overweight / obesity have been identified (3)(4)(5)(6)(7). Combining such genetic variants in a risk score appears to be an appropriate measurement of an individual's genetic predisposition for overweight (8,9). In a previous study, we found that such a genetic risk score was associated with differential effect sizes depending on children's body composition, with greatest effects on higher body mass index (BMI) percentiles (10).…”