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Adult-onset diabetes mellitus (here: aDM) is not a uniform disease entity. In European populations, five diabetes subgroups have been identified by cluster analysis using simple clinical variables; these may elucidate diabetes aetiology and disease prognosis. We aimed at reproducing these subgroups among Ghanaians with aDM, and establishing their importance for diabetic complications in different health system contexts. We used data of 541 Ghanaians with aDM (age: 25-70 years; male sex: 44%) from the multi-center, cross-sectional Research on Obesity and Diabetes among African Migrants (RODAM) Study. Adult-onset DM was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L, documented use of glucose-lowering medication or self-reported diabetes, and age of onset ≥ 18 years. We derived subgroups by cluster analysis using (i) a previously published set of variables: age at diabetes onset, HbA1c, body mass index, HOMA-beta, HOMA-IR, positivity of glutamic acid decarboxylase autoantibodies (GAD65Ab), and (ii) Ghana-specific variables: age at onset, waist circumference, FPG, and fasting insulin. For each subgroup, we calculated the clinical, treatment-related and morphometric characteristics, and the proportions of objectively measured and self-reported diabetic complications. We reproduced the five subgroups: cluster 1 (obesity-related, 73%) and cluster 5 (insulin-resistant, 5%) with no dominant diabetic complication patterns; cluster 2 (age-related, 10%) characterized by the highest proportions of coronary artery disease (CAD, 18%) and stroke (13%); cluster 3 (autoimmune-related, 5%) showing the highest proportions of kidney dysfunction (40%) and peripheral artery disease (PAD, 14%); and cluster 4 (insulin-deficient, 7%) characterized by the highest proportion of retinopathy (14%). The second approach yielded four subgroups: obesity- and age-related (68%) characterized by the highest proportion of CAD (9%); body fat-related and insulin-resistant (18%) showing the highest proportions of PAD (6%) and stroke (5%); malnutrition-related (8%) exhibiting the lowest mean waist circumference and the highest proportion of retinopathy (20%); and ketosis-prone (6%) with the highest proportion of kidney dysfunction (30%) and urinary ketones (6%). With the same set of clinical variables, the previously published aDM subgroups can largely be reproduced by cluster analysis in this Ghanaian population. This method may generate in-depth understanding of the aetiology and prognosis of aDM, particularly when choosing variables that are clinically relevant for the target population., (© 2023. The Author(s).)

Introduction: Beta-cell autoantibodies are established markers of autoimmunity, which we compared between Ghanaian adults with or without diabetes, living in rural and urban Ghana and in three European cities., Methods: In the multicenter cross-sectional Research on Obesity and Diabetes among African Migrants (RODAM) study (N = 5898), we quantified autoantibodies against glutamic acid decarboxylase (GAD65Ab) by radioligand binding assay (RBA) and established cut-offs for positivity by displacement analysis. In a subsample, we performed RBA for zinc transporter-8 autoantibodies (ZnT8Ab). Associations of environmental, sociodemographic, and clinical factors with GAD65Ab were calculated., Results: In this study population (age: 46.1 ± 11.9 years; female: 62%; Ghana-rural: 1111; Ghana-urban: 1455; Europe: 3332), 9.2% had diabetes with adult-onset. GAD65Ab concentrations were the highest in Ghana-rural (32.4; 10.8-71.3 U/mL), followed by Ghana-urban (26.0; 12.3-49.1 U/mL) and Europe (11.9; 3.0-22.8 U/mL) with no differences between European cities. These distributions were similar for ZnT8Ab. Current fever, history of fever, and higher concentrations of liver enzymes marginally explained site-specific GAD65Ab concentrations. GAD65Ab positivity was as frequent in diabetes as in nondiabetes (5.4% vs 6.1%; P = .25). This was also true for ZnT8Ab positivity., Conclusion: Geographic location determines the occurrence of GAD65Ab and ZnT8Ab more than the diabetes status. Beta-cell autoimmunity may not be feasible to differentiate diabetes subgroups in this population., (© 2020 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)