Assessing genetic causal relationship between milk fat content and chronic kidney disease: a two-sample Mendelian randomization study

This study investigates the genetic causal relationship between milk fat content and chronic kidney disease (CKD) using publicly available genome-wide association study (GWAS) data. Single nucleotide polymorphisms (SNPs) significantly associated with milk fat content were identified following rigorous quality control procedures. A two-sample Mendelian randomization (MR) approach was used to analyze the relationship between three milk fat levels and CKD risk. The inverse variance weighting (IVW) method with random effects served as the primary analysis, supported by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analyses, including Cochran's Q tests and MR-Egger intercepts, were conducted to assess heterogeneity and pleiotropy. A leave-one-out analysis tested the influence of individual SNPs on the causal estimates. Additional validation using maximum likelihood, penalized weighted median, and IVW with fixed effects further supported result consistency. The IVW results revealed no clear evidence of a causal link between milk fat content and CKD risk, a finding echoed by the other MR methods. Minimal heterogeneity was observed. Overall, the study suggests no significant genetic causal association between milk fat intake and CKD, offering valuable insights into the genetic epidemiology of CKD. Notably, genetic instruments derived from self-reported "milk type" may reflect broader dietary habits or cultural factors-such as lactose tolerance-rather than precise fat consumption levels, which may influence interpretations of causality.