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Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Original publication

DOI

10.1038/nature19806

Type

Journal article

Journal

Nature

Publication Date

10/2016

Volume

538

Pages

248 - 252

Addresses

Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

Keywords

CHARGE Consortium Hematology Working Group, Early Growth Genetics (EGG) Consortium, Fetus, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Birth Weight, Glycogen, Insulin, Glucose, Anthropometry, Cohort Studies, Signal Transduction, Chromatin Assembly and Disassembly, Genomic Imprinting, Aging, Blood Pressure, Genotype, Phenotype, Adult, Female, Male, Coronary Artery Disease, Genetic Variation, Genome-Wide Association Study, Genetic Loci, Datasets as Topic