학술논문

Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity
Document Type
article
Source
Diabetes. 63(6)
Subject
Biomedical and Clinical Sciences
Genetics
Diabetes
Autoimmune Disease
Clinical Research
Prevention
Aetiology
2.1 Biological and endogenous factors
Metabolic and endocrine
Alleles
Cluster Analysis
Diabetes Mellitus
Type 2
Female
Gene Frequency
Genetic Predisposition to Disease
Genetic Variation
Genome-Wide Association Study
Humans
Insulin
Insulin Resistance
Insulin Secretion
Insulin-Secreting Cells
Male
Polymorphism
Single Nucleotide
Quantitative Trait Loci
Risk Factors
Transcription Factors
MAGIC Investigators
Medical and Health Sciences
Endocrinology & Metabolism
Biomedical and clinical sciences
Language
Abstract
Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.