کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8634261 | 1569094 | 2018 | 39 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Interactions among the variants of insulin-related genes and nutrients increase the risk of type 2 diabetes
ترجمه فارسی عنوان
تعاملات بین انواع ژن ها و مواد غذایی مرتبط با انسولین خطر ابتلا به دیابت نوع 2 را افزایش می دهد
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کلمات کلیدی
OGTTGLIS3cross-validation consistencydeleted in liver cancer 1TEBADLC1GMDRGSISHOMA-BKARET2DMCDC42HbA1cCVCORSHOMA-IRAUC - AUCanalysis of variance - تحلیل واریانسANOVA - تحلیل واریانس Analysis of varianceoral glucose tolerance - تحمل گلوکز خوراکیInsulin secretion - ترشح انسولینGlucose-stimulated insulin secretion - ترشح انسولین تحریک شده توسط گلوکزGene-gene interaction - تعامل ژن-ژنKoGES - جوشType 2 diabetes - دیابت نوع 2body mass index - شاخص توده بدنBMI - شاخص توده بدنیconfidence intervals - فاصله اطمینانEnergy intake - مصرف انرژی GWAS - مطالعهٔ همخوانی سراسر ژنومarea under the curve - منطقه تحت منحنیodds ratios - نسبت شانسHemoglobin A1c - هموگلوبین A1ccell division control protein 42 - پروتئین کنترل تقسیم سلولی 42Single nucleotide polymorphism - پلیمورفیسم تک نوکلئوتیدیSNP - چندریختی تک-نوکلئوتیدGeneralized Multifactor Dimensionality Reduction - کاهش ضریب مولتی فاکتور کلی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
علوم غدد
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nutrition Research - Volume 51, March 2018, Pages 82-92
Journal: Nutrition Research - Volume 51, March 2018, Pages 82-92
نویسندگان
Kyung-Won Hong, Sung Hoon Kim, Xin Zhang, Sunmin Park,