Dairy Product Intake and Risk of Type 2 Diabetes in EPIC-InterAct: A Mendelian Randomization Study
Publication: Diabetes Care
Vissers LET, Sluijs I, van der Schouw YT, Forouhi NG, Imamura F, Burgess S, et al.
6 February 2019
Eating healthily on a daily basis is a major step to prevent development of type 2 diabetes. Higher intake of dairy products has been associated with a lower risk of diabetes in a meta-analysis of observational studies. Yogurt and cheese intake particularly were associated with lower diabetes risk, whereas milk intake was not, with substantial heterogeneity for most dairy products.
However, potential confounding and reverse causation cannot be excluded. Owing to these limitations, the causal role of dairy products in diabetes prevention remains debatable.
The relationship between dairy products and risk of diabetes could be investigated by applying a Mendelian randomization (MR) approach, using genetic variability in the MCM6 gene associated with lactase persistence (LP) in adults as an instrumental variable (IV).
Lactase is necessary to break down the sugars that are found in dairy products, i.e., lactose. Single nucleotide polymorphisms (SNPs) in the MCM6 region have been associated with LP (6). rs4988235 (LCT-12910C>T) has been associated with LP in European populations and has been associated with a higher intake of milk in European cohorts, albeit not in all.
Previous MR studies reported no association between LP-associated milk intake and diabetes. However, variation in the MCM6 gene is likely to lead to population stratification, which would introduce bias to an MR analysis, and previous MR studies did not sufficiently adjust for population substructure. Also, previous studies did not investigate whether rs4988235 was specifically associated with dairy product intake after adjusting for population substructure.
We therefore investigated whether rs4988235 associated with intake of dairy products and other foods in a pan-European study in eight countries with different dietary habits. We adjusted for genetic principal components (PCs) and study center to adjust for population substructure (16). Next, we used rs4988235 in an IV analysis to investigate whether there is a causal relationship between the LP-associated exposure and risk of diabetes.