Naja Khaled, Anwardeen Najeha, Bashraheel Sara S, Elrayess Mohamed A
Biomedical Research Center, Qatar University, Doha, Qatar.
College of Medicine, QU Health, Qatar University, Doha, Qatar.
J Pharm Pharm Sci. 2024 Sep 17;27:13305. doi: 10.3389/jpps.2024.13305. eCollection 2024.
Sulfonylureas have been a longstanding pharmacotherapy in the management of type 2 diabetes, with potential benefits beyond glycemic control. Although sulfonylureas are effective, interindividual variability exists in drug response. Pharmacometabolomics is a potent method for elucidating variations in individual drug response. Identifying unique metabolites associated with treatment response can improve our ability to predict outcomes and optimize treatment strategies for individual patients. Our objective is to identify metabolic signatures associated with good and poor response to sulfonylureas, which could enhance our capability to anticipate treatment outcome.
In this cross-sectional study, clinical and metabolomics data for 137 patients with type 2 diabetes who are taking sulfonylurea as a monotherapy or a combination therapy were obtained from Qatar Biobank. Patients were empirically categorized according to their glycosylated hemoglobin levels into poor and good responders to sulfonylureas. To examine variations in metabolic signatures between the two distinct groups, we have employed orthogonal partial least squares discriminant analysis and linear models while correcting for demographic confounders and metformin usage.
Good responders showed increased levels of acylcholines, gamma glutamyl amino acids, sphingomyelins, methionine, and a novel metabolite 6-bromotryptophan. Conversely, poor responders showed increased levels of metabolites of glucose metabolism and branched chain amino acid metabolites.
The results of this study have the potential to empower our knowledge of variability in patient response to sulfonylureas, and carry significant implications for advancing precision medicine in type 2 diabetes management.
磺脲类药物一直是治疗2型糖尿病的常用药物疗法，其潜在益处不仅限于血糖控制。尽管磺脲类药物有效，但药物反应存在个体差异。药物代谢组学是阐明个体药物反应差异的有效方法。识别与治疗反应相关的独特代谢物可以提高我们预测结果的能力，并为个体患者优化治疗策略。我们的目标是识别与磺脲类药物反应良好和反应不佳相关的代谢特征，这可以增强我们预测治疗结果的能力。
在这项横断面研究中，从卡塔尔生物样本库获得了137例接受磺脲类单药治疗或联合治疗的2型糖尿病患者的临床和代谢组学数据。根据糖化血红蛋白水平，将患者经验性地分为磺脲类药物反应不佳和反应良好的两组。为了研究这两个不同组之间代谢特征的差异，我们采用了正交偏最小二乘判别分析和线性模型，同时校正了人口统计学混杂因素和二甲双胍的使用情况。
反应良好者的酰基胆碱、γ-谷氨酰氨基酸、鞘磷脂、蛋氨酸和一种新型代谢物6-溴色氨酸水平升高。相反，反应不佳者的葡萄糖代谢产物和支链氨基酸代谢产物水平升高。
本研究结果有可能增强我们对患者对磺脲类药物反应变异性的认识，并对推进2型糖尿病管理中的精准医学具有重要意义。
