Using Genetics to Investigate the Developmental Origins of Health and Disease

Identification: Evans, David


Using Genetics to Investigate the Developmental Origins of Health and Disease
David M. Evans on behalf of the Early Growth Genetics (EGG) Consortium
University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland
Low birth weight is observationally associated with poor perinatal outcomes and increased future risk of a range of cardio-metabolic diseases, in both first world and developing countries. However, it remains unclear which maternal exposures during pregnancy cause low birthweight (i.e. via intrauterine mechanisms) and whether low birthweight itself causes increased risk of cardio-metabolic disease in later life (the so-called Developmental Origins of Health and Disease “DOHaD”).
In this talk, I outline a method called Mendelian randomization which leverages results from genome-wide association studies to estimate the causal effect of environmental exposures on medically relevant outcomes. Because Mendelian randomization can be performed using publically available summary results data from genome-wide association studies, the method represents a cost-effective complement to randomized controlled trials in investigating causality, which in contrast may be expensive, impractical or unethical to implement.
In this talk I show how we have used Mendelian randomization to investigate whether the observational correlation between offspring birthweight and a range of maternal environmental exposures, and between low offspring birthweight and future risk of cardio-metabolic disease reflect causal relationships. I utilize results from a large trans-ethnic genome-wide association analysis of birthweight (N > 300,000) that we have performed in the UK Biobank and Early Growth Genetics Consortium, where we have used advanced statistical genetics methods to decompose genetic effects on birthweight into maternal and fetal-mediated components. I discuss how Mendelian randomization approaches can be used to inform health policy and how the approach can be used to translate findings from genome-wide association studies into clinical practice.


Credits: None available.

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