Exploratory Evidence of a Gene–Smoking Interaction Involving MTR rs1805087 in Type 2 Diabetes Mellitus

ABSTRACT Type 2 diabetes mellitus (T2DM) is the most common form of diabetes worldwide. In Brazil, diabetes affects 7.7% of adults and represents a substantial public health and economic burden. Variants in the MTR gene may disrupt one‐carbon metabolism, potentially contributing to hyperhomocysteinemia and increased susceptibility to T2DM. A case–control study involving 219 age‐ and sex‐matched individuals was conducted to evaluate the association between the MTR rs1805087 variant and susceptibility to T2DM. Associations under different genetic inheritance models were examined using χ 2 tests and odds ratios (95% confidence interval [CI]). In parallel, machine‐learning (ML) algorithms were applied, with predictive performance assessed using accuracy, precision, sensitivity, and receiver operating characteristic–area under the curve (ROC–AUC). The variant was not independently associated with T2DM. However, among individuals with T2DM, genotype distributions differed according to smoking status, with significant associations under the codominant and recessive genetic models. Exploratory ML analyses showed limited discriminative ability in the independent test set, with ROC–AUC values of 0.555 for K ‐nearest neighbors ( K NN), 0.524 for support vector machine (SVM), and 0.503 for random forest (RF). All models exhibited substantial declines in performance compared with cross‐validation results obtained in the training set. MTR rs1805087 was not independently associated with T2DM in this studied population. However, differences in genotype distributions according to smoking status among individuals with T2DM may reflect context‐dependent genetic effects. Exploratory ML analyses showed limited predictive performance but identified smoking as one of the most influential predictors across all evaluated algorithms.