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Novel clusters of type 2 Diabetes: A tailored therapeutic approach

2021; CIG Media Group; Issue: 2 Linguagem: Inglês

10.26497/ao200037

2341-0736

Vitória Duarte, Catarina Ivo, David Veríssimo, João Pedro Mendonça, Luís Lopes, Dolores Passos, João Jácome de Castro, Mafalda Marcelino,

Computational Drug Discovery Methods

Introduction:Type 2 diabetes is a heterogeneous disease for which etiological mechanisms are incompletely understood and subclassification may improve patient care.In this paper, we aimed to stratify a cohort of Portuguese patients with adult-onset diabetes followed at our Diabetic clinic into subgroups and assess the impact of the clusters on outcomes and therapy.Methods: We performed a cluster analysis on 1280 patients followed at our Diabetic clinic.Clusters were based on three variables: presence of glutamic acid decarboxylase antibodies, age at diagnosis and body mass index.Clinical data was retrieved from patient records.Statistical analysis was performed using SPSS v.25.0.Results: We identified four replicable clusters of adult-onset diabetes, with significantly different patient characteristics and risk of diabetic complications.Clusters 1 and 2 were characterized by early-onset disease, higher HbA1c and insulin treatment.More than half of patients were included in cluster 3, requiring combined therapy.Cluster 4 was characterized by late-onset disease, low HbA1c and monotherapy.Cluster 1 had the highest risk of retinopathy. Conclusion:The recently proposed cluster analysis is easily replicable in real-world clinical practice and applicable to different populations, including other Portuguese settings.This new subclassification may contribute patient tailored therapy, therefore representing a first step towards precision medicine in type 2 diabetes.