Department of Diabetes, Endocrinology and Metabolism, School of Medicine, Fukushima Medical University, Fukushima 960-1295, Japan.
Division of Endocrinology, Diabetes and Metabolism, Hematology, Rheumatology (Second Department of Internal Medicine), University of the Ryukyus, Okinawa 903-0215, Japan.
Diabetes Res Clin Pract. 2021 Oct;180:109067. doi: 10.1016/j.diabres.2021.109067. Epub 2021 Sep 23.
Diabetes mellitus results from an interplay between insulin resistance and β-cell dysfunction. Since their relative contributions to its pathogenesis are difficult to quantify, therapeutic strategies for glycaemic control are determined primarily based on two limited metrics: plasma glucose and haemoglobin A1c. Recent attempts have been made to subclassify diabetes mellitus to better predict its associated pathology and plan appropriate therapeutic strategies. These classifications are based on data-driven cluster analysis using autoimmunity, age, obesity (metabolically unhealthy and healthy phenotypes), insulin secretory capacity and resistance, and ethnicity. This review addresses potential therapeutic strategies for the cluster-based classifications of adult-onset diabetes mellitus to achieve better glycaemic control and prevent or at least delay the concomitant complications.
糖尿病是由胰岛素抵抗和β细胞功能障碍相互作用引起的。由于它们对发病机制的相对贡献难以量化，因此血糖控制的治疗策略主要基于两个有限的指标：血浆葡萄糖和糖化血红蛋白。最近，人们试图对糖尿病进行细分，以更好地预测其相关病理，并制定适当的治疗策略。这些分类是基于使用自身免疫、年龄、肥胖（代谢不健康和健康表型）、胰岛素分泌能力和抵抗以及种族的基于数据的聚类分析。这篇综述探讨了基于聚类的成人发病糖尿病的潜在治疗策略，以实现更好的血糖控制，预防或至少延迟伴随的并发症。
