Obesity is a public health problem that is well suited to risk assessment using a GRS. It is highly prevalent 11; it is a significant source of health-care costs, morbidity, and mortality 12–14; it is under strong genetic influence 15; and GWAS are beginning to elucidate its molecular genetic roots 16. Therefore, translational research in obesity genomics may ultimately help to address a public-health priority. A key challenge is that obesity’s genetic roots are diffuse, multifactorial, and non-deterministic; many variants scattered across the genome each contribute small risks for obesity 17. In other words, information from multiple genetic variants is needed to characterize genetic susceptibility to obesity. Thus, a GRS may be useful. A further challenge is uncertainty about the specific genetic variants to be included in an obesity GRS. Different GWAS identify different genomic loci and, when loci are replicated across GWAS, the specific SNPs identified may be different 18. To address this challenge, we developed a 3-stage approach to review GWAS results and select specific SNPs to include in a GRS. We devised our approach to be systematic
