Assessing Whether Genetic Scores Explain Extra Variation in Birthweight, when Added to Clinical and Anthropometric Measures

Background Human birthweight is a complex, multifactorial trait. Maternal characteristics contribute to birthweight variation by influencing the intrauterine environment. Variation explained by genetic effects is also important, but their contributions have not been assessed alongside other key determinants. We aimed to investigate variance in birthweight explained by genetic scores in addition to easily-measurable clinical and anthropometric variables. Methods We analysed 549 European-ancestry parent-offspring trios from a UK community-based birth cohort. We investigated variance explained in birthweight (adjusted for sex and gestational age) in multivariable linear regression models including genetic scores, routinely-measured maternal characteristics, and parental anthropometric variables. We used R-Squared ( R 2 ) to estimate variance explained, adjusted R-squared (Adj- R 2 ) to assess improvement in model fit from added predictors, and F-tests to compare nested models. Results Maternal and fetal genetic scores together explained 6.0% variance in birthweight. A model containing maternal age, weight, smoking, parity and 28-week fasting glucose explained 21.7% variance. Maternal genetic score explained additional variance when added to maternal characteristics (Adj- R 2 = 0.233 vs Adj- R 2 = 0.210, p < 0.001). Fetal genetic score improved variance explained (Adj- R 2 = 0.264 vs 0.248, p < 0.001) when added to maternal characteristics and parental heights. Conclusions Genetic scores account for variance explained in birthweight in addition to easily measurable clinical variables. Parental heights partially capture fetal genotype and its contribution to birthweight, but genetic scores explain additional variance. While the genetic contribution is modest, it is comparable to that of individual clinical characteristics such as parity, which suggests that genetics could be included in tools aiming to predict risk of high or low birthweights.