Type 2 diabetes mellitus (T2D) represents an indirect cause of mortality and a key factor in reduced quality of life due to its progressive impact on cardiometabolic health. Genetic predisposition is estimated to account for more than 50% of the risk of developing T2D, although most genetic variants remain unidentified. Identifying heterogeneous biomarkers, including genetic variants and their interaction with non-genetic factors, is crucial for advancing the understanding of T2D aetiology. This study aimed to identify genetic variants (SNPs) associated with T2D through Next-Generation Sequencing (NGS) and to investigate their interaction with environmental, clinical, and anthropometric factors in a cohort of the Spanish general population (DI@BET.ES dataset).
An exploratory analysis was conducted to evaluate the effect of prevalent genetic variants on T2D predisposition, as well as their interaction with environmental and clinical variables. To prioritize the identified variants, the SEQENS algorithm was employed to generate relevance rankings in stratified populations. Three different models were developed for the analysis: a genetic model, an environmental model, and a combined model. The performance of the prioritization models was evaluated using the concordance index of machine learning models predicting the risk of developing T2D as a function of age with the identified risk factors.
The combined model outperformed the individual models in variant prioritization and interaction analysis. The most relevant variables selected included fasting glucose, BMI, waist circumference, basal insulin, HDL and LDL cholesterol, triglycerides, consanguinity with first-degree relatives with T2D, body weight, WHR, monthly beer intake, nickel in particulate matter, and a specific genetic variant, rs78416608. This variant, located in the SCARA5 gene, is linked to immunity, apoptotic cell clearance, and lipid metabolism regulation, processes associated with T2D pathophysiology. These findings highlight the importance of an integrative approach to understanding T2D.
