The Prevalence of Polyneuropathy in Type 2 Diabetes Subgroups Based on HOMA2 Indices of β-Cell Function and Insulin Sensitivity

OBJECTIVE Metabolic syndrome components may cumulatively increase the risk of diabetic polyneuropathy (DPN) in type 2 diabetes mellitus (T2DM) patients, driven by insulin resistance and hyperinsulinemia. We investigated the prevalence of DPN in three T2DM subgroups based on indices of b-cell function and insulin sensitivity. RESEARCH DESIGN AND METHODS We estimated b-cell function (HOMA2-B) and insulin sensitivity (HOMA2-S) in 4,388 Danish patients with newly diagnosed T2DM. Patients were categorized into subgroups of hyperinsulinemic (high HOMA2-B, low HOMA2-S), classical (low HOMA2-B, low HOMA2-S), and insulinopenic (low HOMA2-B, high HOMA2-S) T2DM. After a median follow-up of 3 years, patients filled the Michigan Neuropathy Screening Instrument questionnaire (MNSIq) to identify DPN (score ‡ 4). We used Poisson regression to calculate adjusted prevalence ratios (PRs) for DPN, and spline models to examine the association with HOMA2-B and HOMA2-S. RESULTS A total of 3,397 (77%) patients filled in the MNSIq. The prevalence of DPN was 23% among hyperinsulinemic, 16% among classical, and 14% among insulinopenic pa-tients. After adjusting for demographics, diabetes duration and therapy, lifestyle behaviors, and metabolic syndrome components (waist circumference, triglycer-ides, HDL cholesterol, hypertension, and HbA1c), the PR of DPN was 1.35 (95% CI 1.15–1.57) for the hyperinsulinemic compared with the classical patients. In spline analyses, we observed a linear relation of higher DPN prevalence with increasing HOMA2-B, independent of both metabolic syndrome components and HOMA2-S. CONCLUSIONS Hyperinsulinemia marked by high HOMA2-B is likely an important risk factor for DPN beyond metabolic syndrome components and insulin resistance. This should be considered when developing interventions to prevent DPN

Type 2 diabetes classification : a data-driven cluster study of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) cohort

Introduction A Swedish data-driven cluster study identified four distinct type 2 diabetes (T2D) clusters, based on age at diagnosis, body mass index (BMI), hemoglobin A1c (HbA1c) level, and homeostatic model assessment 2 (HOMA2) estimates of insulin resistance and beta-cell function. A Danish study proposed three T2D phenotypes (insulinopenic, hyperinsulinemic, and classical) based on HOMA2 measures only. We examined these two new T2D classifications using the Danish Centre for Strategic Research in Type 2 Diabetes cohort. Research design and methods In 3529 individuals, we first performed a k-means cluster analysis with a forced k-value of four to replicate the Swedish clusters: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild age-related (MARD), and mild obesity-related (MOD) diabetes. Next, we did an analysis open to alternative k-values (ie, data determined the optimal number of clusters). Finally, we compared the data-driven clusters with the three Danish phenotypes. Results Compared with the Swedish findings, the replicated Danish SIDD cluster included patients with lower mean HbA1c (86 mmol/mol vs 101 mmol/mol), and the Danish MOD cluster patients were less obese (mean BMI 32 kg/m 2 vs 36 kg/m 2). Our data-driven alternative k-value analysis suggested the optimal number of T2D clusters in our data to be three, rather than four. When comparing the four replicated Swedish clusters with the three proposed Danish phenotypes, 81%, 79%, and 69% of the SIDD, MOD, and MARD patients, respectively, fitted the classical T2D phenotype, whereas 70% of SIRD patients fitted the hyperinsulinemic phenotype. Among the three alternative data-driven clusters, 60% of patients in the most insulin-resistant cluster constituted 76% of patients with a hyperinsulinemic phenotype. Conclusion Different HOMA2-based approaches did not classify patients with T2D in a consistent manner. The T2D classes characterized by high insulin resistance/hyperinsulinemia appeared most distinct