Interactions among the variants of insulin-related genes and nutrients increase the risk of type 2 diabetes

• Published in: Nutrition research (New York, N.Y.) Vol. 51; pp. 82 - 92
• Main Authors: Hong, Kyung-Won, Kim, Sung Hoon, Zhang, Xin, Park, Sunmin
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.03.2018
• Subjects: Adult; Aged; Asian Continental Ancestry Group - genetics; Calcium, Dietary - administration & dosage; Calcium, Dietary - pharmacology; Cohort Studies; Diabetes Mellitus, Type 2 - etiology; Diabetes Mellitus, Type 2 - genetics; Energy Intake; Epigenesis, Genetic; Epistasis, Genetic; Female; gene-gene interaction; generalized multifactor dimensionality reduction; Genotype; Humans; Insulin - genetics; Insulin - metabolism; Insulin Resistance; insulin secretion; Logistic Models; Male; Middle Aged; Odds Ratio; Polymorphism, Single Nucleotide; Republic of Korea; Risk Factors; Type 2 diabetes; Republic of Korea; Type 2 diabetes; T2DM; GWAS; SQFFQ; GLIS3; HOMA-B; FNBP1L; AUC; SNP; GMDR; ANOVA; TEBA; TRBA; GRSBM; gene-gene interaction; HbA1c; Cdc42; BMI; generalized multifactor dimensionality reduction; energy intake; KoGES; CI; KARE; insulin secretion; HOMA-IR; ORs; CVC; DLC1; GSIS; OGTT
• ISSN: 0271-5317; 1879-0739
• DOI: 10.1016/j.nutres.2017.12.012

Asians easily develops type 2 diabetes (T2DM) since they have insufficient glucose-stimulated insulin secretion (GSIS) in insulin resistant states. Since this may be associated with genetic background, the hypothesis of this study was that inter-genetic and gene-nutrient interactions may explain the low insulin secretory capacity of Asians. Accordingly, we identified the best gene-gene and gene-nutrient interactions using generalized multifactor dimensionality reduction (GMDR) in a large Korean cohort (n=8,842). Initially, we used 105 genetic variants associated with GSIS to identify the best gene-gene interaction model using the GMDR method. The best model included six SNPs, FNBP1L-rs4847428, FNBP1L-rs23766, GLIS3-rs2027393, GLIS3-rs3892354, GLIS3-rs486163 and DLC1-rs17093957. For each individual, we obtained the genetic risk scores based on the best model (GRSBM) to predict the GSIS levels. The GRSBM were divided into low, medium and high groups, and the association between T2DM and the GRSBM was measured using logistic regression. We analyzed the interaction between the GRSBM and the nutrition intakes. The adjusted odds ratios for T2DM risk increased by 1.701 fold in the high-score group compared to the low-score group. HOMA-B, an index of insulin secretion capacity, but not insulin resistance index was much lower in the high-score group than the low-score group. The association between the GRSBM and T2DM risk was greater in subjects with high energy intakes and low Ca intake, than those with low energy intake and high Ca intake. The high-score group was susceptible to T2DM incidence due to lower GSIS than the low-score group especially in subjects with high energy intake. In conclusion, the hypothesis of the study was accepted. These findings suggested that individuals with high GRSBM of the 6 genes in the model should avoid diets in high energy and low in calcium (<500 mg/day) to protect against T2DM.