Genetic Risk Score for Prediction of Newborn Adiposity and Large-for-Gestational-Age Birth

Abstract

Context: Macrosomic infants are at increased risk for adverse metabolic outcomes. Improving prediction of large-for-gestational-age (LGA) birth may help prevent these outcomes. Objective: This study sought to determine whether genes associated with obesity-related traits in adults are associated with newborn size, and whether a genetic risk score (GRS) predicts LGA birth. Setting and Design: Single nucleotide polymorphisms (SNPs) in 40 regions associated with adult obesity-related traits were tested for association with newborn size. GRS's for birth weight and sum of skinfolds (SSF) specific to ancestry were calculated using the most highly associated SNP for each ancestry in genomic regions with one or more SNPs associated with birth weight and/or SSF in at least one ancestry group or meta-analyses. Participants: Newborns from the Hyperglycemia Adverse Pregnancy Outcomes Study were studied (942 Afro-Caribbean, 1294 Northern European, 573 Mexican-American, and 1182 Thai). Outcome Measures: Birth weight >90th percentile (LGA) and newborn SSF >90th percentile were primary outcomes. Results: After adjustment for ancestry, sex, gestational age at delivery, parity, maternal genotype, maternal smoking/alcohol intake, age, body mass index, height, blood pressure and glucose, 25 and 23 SNPs were associated (P < .001) with birth weight and newborn SSF, respectively. The GRS was highly associated with both phenotypes as continuous variables across all ancestries (P ≤ 1.6 × 10−19) and improved prediction of birth weight and SSF >90th percentile when added to a baseline model incorporating the covariates listed above. Conclusions: A GRS comprised of SNPs associated with adult obesity-related traits may provide an approach for predicting LGA birth and newborn adiposity beyond established risk factors.