Predicting and understanding the response to short-term intensive insulin therapy in people with early type 2 diabetes
Predicting and understanding the response to short-term intensive insulin therapy in people with early type 2 diabetes
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DOI：
10.1016/j.molmet.2018.11.003
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发表时间：
2019-02-01
影响因子：
8.1
通讯作者：
Seyhan, Attila A.
中科院分区：
文献类型：
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作者：
Lopez, Yury O. Nunez;Retnakaran, Ravi;Seyhan, Attila A.
目的：在 2 型糖尿病病程早期进行短期强化胰岛素治疗 (IIT) 可显着改善 β 细胞功能，并对血糖控制产生持久影响。然而，传统方法无法确定哪些患者更适合 IIT，并且对于决定反应的分子机制知之甚少。因此，本研究旨在开发一种模型，能够准确预测对 IIT 的反应，并深入了解驱动人类这种反应的分子机制。 方法：对 24 名早期 2 型糖尿病患者在基线和 IIT 后 4 周进行评估，包括基础地特胰岛素和餐前门冬胰岛素。 12 人对 IIT 产生了有益的 β 细胞反应（应答者），12 人则没有（无应答者）。 β 细胞功能通过多种方法评估，包括胰岛素分泌敏感性指数 2。在 IIT 之前和之后对血浆样本中的 MicroRNA (miRNA) 进行了分析。使用机器学习算法对 IIT 的反应进行建模，并通过差异表达、相关性和功能网络分析 (FNA) 评估潜在的 miRNA 介导的调节机制。结果：循环 miR-145-5p、miR-29c-3p 和 HbA1c 的基线水平准确地 (91.7%) 预测对 IIT 的反应 (OR = 121 [95% CI: 6.7, 2188.3])。从机制上讲，先前描述的 miR-145-5p 和 miR-483-3p/5p 之间控制 TP53 介导的细胞凋亡的调节环路似乎也出现在我们的早期 2 型糖尿病人类研究人群中。此外，由于 IIT 导致 miR-138-5p、miR-192-5p、miR-195-5p、miR-320b 和 let-7a-5p 循环水平显着（倍数变化 > 2，P < 0.05）纵向变化进一步表征了应答者组的特征，并与 β 细胞功能和 β 细胞功能测量的变化显着相关（垂直条 r 垂直条 > 0.4，P < 0.05）。胰岛素敏感性。 FNA 确定了一个协调/合作调节 miRNA 靶向基因的网络，该网络可能通过对导致 β 细胞功能障碍的细胞凋亡过程的负调节以及随之而来的增殖的正调节来驱动 IIT 反应。结论：早期 2 型糖尿病患者对 IIT 的反应与特征性 miRNA 特征相关。这项研究代表了识别 IIT（该领域目前的局限性）潜在反应者的第一步，并为 β 细胞功能障碍可逆性的病理生理学决定因素提供了重要的见解。 (C) 2018 作者。由爱思唯尔有限公司出版。
Objective: Short-term intensive insulin therapy (IIT) early in the course of type 2 diabetes acutely improves beta-cell function with long-lasting effects on glycemic control. However, conventional measures cannot determine which patients are better suited for IIT, and little is known about the molecular mechanisms determining response. Therefore, this study aimed to develop a model that could accurately predict the response to IIT and provide insight into molecular mechanisms driving such response in humans.Methods: Twenty-four patients with early type 2 diabetes were assessed at baseline and four weeks after IIT, consisting of basal detemir and premeal insulin aspart. Twelve individuals had a beneficial beta-cell response to IIT (responders) and 12 did not (nonresponders). Beta-cell function was assessed by multiple methods, including Insulin Secretion-Sensitivity Index-2. MicroRNAs (miRNAs) were profiled in plasma samples before and after IIT. The response to IIT was modeled using a machine learning algorithm and potential miRNA-mediated regulatory mechanisms assessed by differential expression, correlation, and functional network analyses (FNA).Results: Baseline levels of circulating miR-145-5p, miR-29c-3p, and HbA1c accurately (91.7%) predicted the response to IIT (OR = 121 [95% CI: 6.7, 2188.3]). Mechanistically, a previously described regulatory loop between miR-145-5p and miR-483-3p/5p, which controls TP53-mediated apoptosis, appears to also occur in our study population of humans with early type 2 diabetes. In addition, significant (fold change > 2, P < 0.05) longitudinal changes due to IIT in the circulating levels of miR-138-5p, miR-192-5p, miR-195-5p, miR-320b, and let-7a-5p further characterized the responder group and significantly correlated (vertical bar r vertical bar > 0.4, P < 0.05) with the changes in measures of beta-cell function and insulin sensitivity. FNA identified a network of coordinately/cooperatively regulated miRNA-targeted genes that potentially drives the IIT response through negative regulation of apoptotic processes that underlie beta cell dysfunction and concomitant positive regulation of proliferation.Conclusions: Responses to IIT in people with early type 2 diabetes are associated with characteristic miRNA signatures. This study represents a first step to identify potential responders to IIT (a current limitation in the field) and provides important insight into the pathophysiologic determinants of the reversibility of beta-cell dysfunction. (C) 2018 The Authors. Published by Elsevier GmbH.