Mendelian randomization study of maternal influences on birthweight and future cardiometabolic risk in the HUNT cohort
Year: 2020
Type: article
Study design: Observational Study
Abstract: Introduction There is a robust and well-documented observational relationship between lower birthweight and higher risk of cardiometabolic disease in later life. The Developmental Origins of Health and Disease (DOHaD) hypothesis posits that adverse environmental factors in utero or in the early years of life result in increased future risk of cardiometabolic disease. Our aim was to investigate whether there was evidence for causal effects of the intrauterine environment, as proxied by maternal single nucleotide polymorphisms (SNPs) that influence offspring birthweight independent of offspring genotype, on offspring cardiometabolic risk factors such as blood pressure, non-fasting glucose, body mass index (BMI), and lipid levels. Methods We investigated whether a genetic risk score of maternal SNPs associated with offspring birthweight was also associated with offspring cardiometabolic risk factors, after controlling for offspring genotypes at the same loci, in up to 26,057 mother-offspring pairs from the Nord-Trøndelag Health (HUNT) Study. We also conducted similar analyses in 19,792 father-offspring pairs from the same study to investigate whether there was evidence that any such causal effects operated through the postnatal, rather than the intrauterine environment. To take account of the considerable cryptic relatedness in HUNT, we implemented a computationally efficient genetic linear mixed model using the OpenMx software package to perform our analyses. Results We found little evidence for a maternal genetic effect of birthweight associated variants on offspring cardiometabolic risk factors after adjusting for offspring genotypes at the same loci. Likewise, we found little evidence for paternal genetic effects on offspring cardiometabolic risk factors performing similar analyses in father-offspring pairs. In contrast, offspring genetic risk scores of birthweight associated variants were strongly related to many cardiometabolic risk factors, even after conditioning on maternal genotypes at the same loci. Conclusion Our results suggest that the maternal intrauterine environment, as proxied by maternal SNPs that influence offspring birthweight, is unlikely to be a major determinant of adverse cardiometabolic outcomes in population based samples of individuals. In contrast, genetic pleiotropy appears to explain some of the observational relationship between offspring birthweight and future cardiometabolic risk.
Source: Nature Communications
Institutions: The University of Queensland, University of Oslo, Norwegian University of Science and Technology, University of Bristol, St Olav's University Hospital, MRC Integrative Epidemiology Unit, University of Michigan, Virginia Commonwealth University, Virginia Commonwealth University Medical Center, University of Exeter, NIHR Bristol Biomedical Research Centre
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $5,380
Funders: Norges Teknisk-Naturvitenskapelige Universitet, Wellcome Trust, Australian Government, National Institute for Health and Care Research, British Heart Foundation, University of Bristol, Helse Midt-Norge, Norges Forskningsråd, Diabetesforbundet, St. Olavs Hospital Universitetssykehuset i Trondheim, National Institutes of Health, Fakultet for medisin og helsevitenskap, Norges Teknisk-Naturvitenskapelige Universitet, Medical Research Council, National Health and Medical Research Council, Faculty of Medicine and Health, University of Sydney, Norwegian Institute of Public Health, National Institute on Drug Abuse, National Institute of Diabetes and Digestive and Kidney Diseases, H2020 European Research Council
Awards: Reproductive and cardio-metabolic health, G1653514516, Investigating the Genetic Correlation Underlying the Developmental Origins of Health and Disease, G2538597952, G2786058305, G2891268083, Developing and Applying Statistical Genetics Methods to Elucidate the Developmental Origins of Health and Disease, G3601192221, Using genetics to understand how the maternal intrauterine environment influences fetal growth., G4089438869, G4257455355, Development and application of a Mendelian randomization framework aimed at dissecting the biological basis of ankylosing spondylitis and other complex diseases, G4344264865, Developing and applying statistical genetics methods to identify genes, molecular biomarkers and environmental agents that causally affect risk of complex musculoskeletal diseases, G5260012927, G5321324157, G5607908600, NIHR Senior Investigator Award, Mendelian randomization to hypothesis-free causal inference, Using genetics to understand how the maternal intrauterine environment influences fetal growth., Effects of maternal gestational adiposity on fetal development and perinatal, postnatal and next generation health., G7194418384, Metabolomic and Epigenomic Mechanisms in Developmental Overnutrition., Psychometric and Genetic Assessments of Substance Use, Psychometric and Genetic Assessments of Substance Use, G7990456425, G8340598841, G8473540729, G8502142660, Identifying maternal and fetal genetic determinants of infant birthweight and their relationship to offspring cardiometabolic risk, G9000063344
OpenAlex ID: W3094110148