Rashid Mamoon, Al Qarni Ali, Al Mahri Saeed, Mohammad Sameer, Khan Altaf, Abdullah Mashan L, Lehe Cynthia, Al Amoudi Reem, Aldibasi Omar, Bouchama Abderrezak
Department of AI and Bioinformatics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh 11426, Saudi Arabia.
Endocrinology and Metabolism, Department of Medicine, King Abdulaziz Hospital, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Al Ahsa 31982, Saudi Arabia.
J Endocr Soc. 2023 Dec 20;8(1):bvad159. doi: 10.1210/jendso/bvad159. eCollection 2023 Dec 1.
Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery.
We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome.
We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction.
Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (, , and superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery.
The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.
减肥手术已被证明对诱导肥胖成年人的2型糖尿病完全缓解有效。然而，其实现糖尿病完全缓解的疗效仍然存在差异，且术前难以预测。
我们旨在描述减肥手术诱导的与糖尿病缓解相关的转录组变化以及基线转录组的预测作用。
我们对26例肥胖和2型糖尿病成年患者的前瞻性队列进行了全基因组微阵列分析，在基线（手术前）、减肥手术后2个月和12个月时检测外周血单个核细胞。我们将机器学习应用于基线转录组，以识别预测代谢结果的基因。我们使用实时聚合酶链反应验证微阵列表达谱。
16例患者在12个月时进入糖尿病缓解期，10例未缓解。基因表达分析显示缓解者和未缓解者之间存在异同。差异包括关键基因（、和超家族）、代谢和信号通路（Hippo、Sirtuin、ARE介导的信使RNA降解、MSP-RON和亨廷顿）的表达，以及预测的生物学功能（β细胞生长和增殖、胰岛素和葡萄糖代谢、能量平衡、炎症和神经退行性变）。对基线转录组进行建模确定了10个基因，这些基因可能在减肥手术前预测代谢结果。
减肥手术后转录组的变化区分了糖尿病完全缓解的患者和未缓解的患者。基线转录组有助于术前预测减肥手术诱导的糖尿病缓解。
