Dataset Information

Clinical and genetic determinants of progression of type 2 diabetes: a DIRECT study.

ABSTRACT: To identify the clinical and genetic factors that explain why the rate of diabetes progression is highly variable between individuals following diagnosis of type 2 diabetes.We studied 5,250 patients with type 2 diabetes using comprehensive electronic medical records in Tayside, Scotland, from 1992 onward. We investigated the association of clinical, biochemical, and genetic factors with the risk of progression of type 2 diabetes from diagnosis to the requirement of insulin treatment (defined as insulin treatment or HbA1c ?8.5% [69 mmol/mol] treated with two or more noninsulin therapies).Risk of progression was associated with both low and high BMI. In an analysis stratified by BMI and HbA1c at diagnosis, faster progression was independently associated with younger age at diagnosis, higher log triacylglyceride (TG) concentrations (hazard ratio [HR] 1.28 per mmol/L [95% CI 1.15-1.42]) and lower HDL concentrations (HR 0.70 per mmol/L [95% CI 0.55-0.87]). A high Genetic Risk Score derived from 61 diabetes risk variants was associated with a younger age at diagnosis and a younger age when starting insulin but was not associated with the progression rate from diabetes to the requirement of insulin treatment.Increased TG and low HDL levels are independently associated with increased rate of progression of diabetes. The genetic factors that predispose to diabetes are different from those that cause rapid progression of diabetes, suggesting a difference in biological process that needs further investigation.

SUBMITTER: Zhou K

PROVIDER: S-EPMC4038744 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Clinical and genetic determinants of progression of type 2 diabetes: a DIRECT study.

Zhou Kaixin K Donnelly Louise A LA Morris Andrew D AD Franks Paul W PW Jennison Chris C Palmer Colin Na CN Pearson Ewan R ER

Diabetes care 20131101 3

<h4>Objective</h4>To identify the clinical and genetic factors that explain why the rate of diabetes progression is highly variable between individuals following diagnosis of type 2 diabetes.<h4>Research design and methods</h4>We studied 5,250 patients with type 2 diabetes using comprehensive electronic medical records in Tayside, Scotland, from 1992 onward. We investigated the association of clinical, biochemical, and genetic factors with the risk of progression of type 2 diabetes from diagnosi ...[more]

PMID: 24186880

Similar Datasets

Project description:BACKGROUND:Type 2 diabetes (T2D) is a progressive disease whereby there is often deterioration in glucose control despite escalation in treatment. There is significant heterogeneity to this progression of glycemia after onset of diabetes, yet the factors that influence glycemic progression are not well understood. Given the tremendous burden of diabetes in the Chinese population, and limited knowledge on factors that influence glycemia, we aim to identify the clinical and genetic predictors for glycemic progression in Chinese patients with T2D. METHODS AND FINDINGS:In 1995-2007, 7,091 insulin-naïve Chinese patients (mean age 56.8 ± 13.3 [SD] years; mean age of T2D onset 51.1 ± 12.7 years; 47% men; 28.4% current or ex-smokers; median duration of diabetes 4 [IQR: 1-9] years; mean HbA1c 7.4% ± 1.7%; mean body mass index [BMI] 25.3 ± 4.0 kg/m2) were followed prospectively in the Hong Kong Diabetes Register. We examined associations of BMI and other clinical and genetic factors with glycemic progression defined as requirement of continuous insulin treatment, or 2 consecutive HbA1c ?8.5% while on ?2 oral glucose-lowering drugs (OGLDs), with validation in another multicenter cohort of Hong Kong Diabetes Biobank. During a median follow-up period of 8.8 (IQR: 4.8-13.3) years, incidence of glycemic progression was 48.0 (95% confidence interval [CI] 46.3-49.8) per 1,000 person-years with 2,519 patients started on insulin. Among the latter, 33.2% had a lag period of 1.3 years before insulin was initiated. Risk of progression was associated with extremes of BMI and high HbA1c. On multivariate Cox analysis, early age at diagnosis, microvascular complications, high triglyceride levels, and tobacco use were additional independent predictors for glycemic progression. A polygenic risk score (PRS) including 123 known risk variants for T2D also predicted rapid progression to insulin therapy (hazard ratio [HR]: 1.07 [95% CI 1.03-1.12] per SD; P = 0.001), with validation in the replication cohort (HR: 1.24 [95% CI 1.06-1.46] per SD; P = 0.008). A PRS using 63 BMI-related variants predicted BMI (beta [SE] = 0.312 [0.057] per SD; P = 5.84 × 10-8) but not glycemic progression (HR: 1.01 [95% CI 0.96-1.05] per SD; P = 0.747). Limitations of this study include potential misdiagnosis of T2D and lack of detailed data of drug use during follow-up in the replication cohort. CONCLUSIONS:Our results show that approximately 5% of patients with T2D failed OGLDs annually in this clinic-based cohort. The independent associations of modifiable and genetic risk factors allow more precise identification of high-risk patients for early intensive control of multiple risk factors to prevent glycemic progression.

Project description:BACKGROUND:Type 2 diabetes is a major healthcare problem. Glucose-, lipid-, and blood pressure-lowering strategies decrease the risk of micro- and macrovascular complications. However, a substantial residual risk remains. To unravel the etiology of type 2 diabetes and its complications, large-scale, well-phenotyped studies with prospective follow-up are needed. This is the goal of the DiaGene study. In this manuscript, we describe the design and baseline characteristics of the study. METHODS:The DiaGene study is a multi-centre, prospective, extensively phenotyped type 2 diabetes cohort study with concurrent inclusion of diabetes-free individuals at baseline as controls in the city of Eindhoven, The Netherlands. We collected anthropometry, laboratory measurements, DNA material, and detailed information on medication usage, family history, lifestyle and past medical history. Furthermore, we assessed the prevalence and incidence of retinopathy, nephropathy, neuropathy, and diabetic feet in cases. Using logistic regression models, we analyzed the association of 11 well known genetic risk variants with type 2 diabetes in our study. RESULTS:In total, 1886 patients with type 2 diabetes and 854 controls were included. Cases had worse anthropometric and metabolic profiles than controls. Patients in outpatient clinics had higher prevalence of macrovascular (41.9% vs. 34.8%; P = 0.002) and microvascular disease (63.8% vs. 20.7%) compared to patients from primary care. With the exception of the genetic variant in KCNJ11, all type 2 diabetes susceptibility variants had higher allele frequencies in subjects with type 2 diabetes than in controls. CONCLUSIONS:In our study population, considerable rates of macrovascular and microvascular complications are present despite treatment. These prevalence rates are comparable to other type 2 diabetes populations. While planning genomics, we describe that 11 well-known type 2 diabetes genetic risk variants (in TCF7L2, PPARG-P12A, KCNJ11, FTO, IGF2BP2, DUSP9, CENTD2, THADA, HHEX, CDKAL1, KCNQ1) showed similar associations compared to literature. This study is well-suited for multiple omics analyses to further elucidate disease pathophysiology. Our overall goal is to increase the understanding of the underlying mechanisms of type 2 diabetes and its complications for developing new prediction, prevention, and treatment strategies.

Dataset Information

Clinical and genetic determinants of progression of type 2 diabetes: a DIRECT study.

Publications

Clinical and genetic determinants of progression of type 2 diabetes: a DIRECT study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure