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Predicting and understanding the response to short-term intensive insulin therapy in people with early type 2 diabetes

机译:预测和了解早期2型糖尿病患者对短期强化胰岛素治疗的反应

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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 (|r|??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. ClinicalTrial.gov identifier: NCT01270789 .
机译:目的在2型糖尿病的早期进行短期强化胰岛素治疗(IIT)可以显着改善β细胞功能,并对血糖控制产生长期影响。但是,常规措施无法确定哪些患者更适合于IIT,而对于确定反应的分子机制知之甚少。因此,本研究旨在建立一个模型,该模型可以准确地预测对IIT的反应,并深入了解驱动人类反应的分子机制。方法对24例2型早期糖尿病患者进行基线和IIT治疗后4周的评估,包括基础地米尔和餐前胰岛素。十二个人对IIT产生了有益的β细胞应答(应答者),而十二个人没有应答(无应答)。通过多种方法评估β细胞功能,包括胰岛素分泌敏感性指数2。在IIT之前和之后在血浆样品中分析MicroRNA(miRNA)。使用机器学习算法对潜在的IIT响应进行建模,并通过差异表达,相关性和功能网络分析(FNA)评估潜在的miRNA介导的调控机制。结果循环miR-​​145-5p,miR-29c-3p和HbA1c的基线水平准确地(91.7%)预测了对IIT的反应(OR?=?121 [95%CI:6.7,2188.3])。从机制上讲,先前描述的控制TP53介导的细胞凋亡的miR-145-5p和miR-483-3p / 5p之间的调节环似乎也出现在我们患有早期2型糖尿病的人群中。此外,由于IIT,miR-138-5p,miR-192-5p,miR-195-5p,miR-320b,循环中的水平显着(倍数变化≥2,P≤0.05)纵向变化。并且let-7a-5p进一步表征了应答者组,并且与β细胞功能和胰岛素敏感性的测定值显着相关(| r |≥0.4,P≤0.05)。 FNA确定了一个协调/协同调控的miRNA靶向基因网络,该网络可能通过负调控凋亡过程(可能是β细胞功能障碍和增殖的积极调控)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特征有关。这项研究代表了确定对IIT(本领域当前的局限性)的潜在反应者的第一步,并为了解β细胞功能障碍可逆性的病理生理决定因素提供了重要的见识。 ClinicalTrial.gov标识符:NCT01270789。

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