Mendelian randomization study on the association between cheese intake and diabetes

Objective To explore whether there is a causal relationship between cheese intake and diabetes through Mendel randomization (MR). Methods Two samples of MR were used to verify the causal effect of cheese intake on diabetes. The analysis was conducted using inverse variance weighted (IVW), weighted median, and MR-Egger regression methods. We used a meta-analysis of publicly available genome-wide association studies (GWAS) to compile statistical datasets, and cheese intake data as exposure factors were sourced from individuals of European ancestry in the UK biobank (n=451486). At the same time, GWAS’s public summary statistical data set is also used for self reporting non cancer disease codes: diabetes data included in the Finnish database (total n=184404; case=1219, control=183185) ( http://www.finngen.fi/en )as a result. Result We selected 108 single nucleotide polymorphisms (SNPs) with genome-wide significance as instrumental variables from the GWAS intake of cheese. IVW method results show a causal relationship between cheese intake and diabetes (β=- 1.196, SE=0.3817, P=0.001729). MR Egger regression results show that directed pleiotropy is unlikely to bias the results (intercept=0.015; P=0.58), but there is no causal relationship between cheese intake and diabetes (β=- 2.073, SE=1.621, P=0.206). The results of weighted median method also showed that there was no causal relationship between cheese intake and diabetes (β=- 0.7828, SE=0.5701, P=0.1698). Cochran’s Q-test and funnel plot indicate no evidence of heterogeneity and asymmetry, indicating the absence of directed pleiotropy. Conclusion The results of MR analysis support that cheese intake may have a causal relationship with the reduced risk of diabetes.