Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness–Death Model

Abstract

Type 2 diabetes (T2D) is a prevalent chronic disease in the Korean population, influenced by lifestyle, dietary habits, and genetics. This study aimed to identify the effects of food intake and genetic factors on T2D progression in Korean adults using a multi-state illness-death model. We analyzed three transition models: normal glucose tolerance (NGT) to prediabetes (PD), NGT to T2D, and PD to T2D. We first identified dietary patterns significantly associated with each transition, using multivariate Cox proportional hazards models. Then, we assessed the impact of single-nucleotide polymorphisms (SNPs) on each transition, incorporating these dietary patterns as covariates. Our analysis revealed significant associations between the identified dietary patterns and the risk of PD and T2D incidence among individuals with NGT. We also identified novel genetic variants associated with disease progression: two SNPs (rs4607517 in Glucokinase [GCK] and rs758982 in Calcium/Calmodulin-Dependent Protein Kinase II Beta [CAMK2B]) in the NGT to PD model, and eight SNPs in the NGT to T2D model, including variants in the Zinc Finger Protein 106 (ZNF106), PTOV1 Extended AT-Hook Containing Adaptor Protein (PTOV1), Proprotein Convertase Subtilisin/Kexin Type 2 (PCSK2), Forkhead Box D2 (FOXD2), Solute Carrier Family 38 Member 7 (SLC38A7), and Neuronal Growth Regulator 1 (NEGR1)genes. Functional annotation analysis using ANNOVAR revealed that rs4607517 (GCK) and rs59595912 (PTOV1) exhibited high Combined Annotation-Dependent Depletion (CADD) and Deleterious Annotation of Genetic Variants using Neural Networks (DANN) scores, suggesting potential pathogenicity and providing a functional basis for their association with T2D progression. Integrating dietary and genetic factors with a multi-state model, this comprehensive approach offers valuable insights into T2D development and highlights potential targets for prevention and personalized interventions.