Wednesday, April 8, 2020 at 11.00-12.00
Nele Taba (University of Tartu)
Detecting causal effects of diet on health using the method of Mendelian randomization
It has been long known that nutrition plays an important role in the development and progress of several diseases, which in turn create high burden for individuals, society and health-care. Nevertheless, in many cases the mechanism by which food acts on health is still unclear. One of the candidates for filling this gap are blood metabolites. Thus detecting causal relationships between dietary choices and biomarkers might reveal more insight into the mechanism by which food affects health.
We use the method of Mendelian Randomization (MR) to tackle this issue. This is possible by virtue of the recently detected 302 (289 novel) single nucleotide polymorphisms (SNP) associated with 39 dietary items (Pirastu et al., under review) and a genome wide association study conducted on 123 blood metabolites measured by nuclear magnetic resonance spectroscopy (Kettunen et al., 2016).
We detected 48 potentially causal links between food and metabolites that help us better understand the pathways by which food affects health. The probably most clinically relevant findings include the pathways regarding Apolipoprotein B, total cholesterol in intermediate density lipoproteins, and omega-6 and omega-3 fatty acids. In the seminar I will introduce how a method that was widely used in econometrics (instrumental variable estimation) found its use in genetics and health-sciences (Mendelian randomization) and discuss what is the potential benefit of MR in regard to saving various resources. Furthermore, I will discuss the potential use of the detected relationships.
Kettunen, J., Demirkan, A., Würtz, P., Draisma, H.H., Haller, T., Rawal, R., Vaarhorst, A., Kangas, A.J., Lyytikäinen, L.P., Pirinen, M. and Pool, R., 2016. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nature communications, 7, p.11122.
Pirastu, N., McDonnell, C., Grzeszkowiak, E.J., Mounier, N., Imamura, F., Day, F.R., Zheng, J., Taba, N., Concas, M.P., Repetto, L., Kentistou, K.A., Robino, A., Esko, T., Joshi, P.K., Fischer, K., Ong, K.K., Gaunt, T.R., Kutalik, Z., Perry, J., Wilson, J.F., 2019. Using genetics to disentangle the complex relationship between food choices and health status, bioRxiv 829952; doi: https://doi.org/10.1101/829952