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靶向胆汁酸和溶血磷脂酰胆碱谱分析鉴定肥胖非糖尿病人群血糖结局的脂质特征。

Untargeted Profiling of Bile Acids and Lysophospholipids Identifies the Lipid Signature Associated with Glycemic Outcome in an Obese Non-Diabetic Clinical Cohort.

机构信息

Nestlé Research, Nestlé Institute of Health Sciences, 1015 Lausanne, Switzerland.

Institute of Clinical Chemistry, Inselspital, Bern University Hospital, 3010 Bern, Switzerland.

出版信息

Biomolecules. 2020 Jul 15;10(7):1049. doi: 10.3390/biom10071049.

Abstract

The development of high throughput assays for assessing lipid metabolism in metabolic disorders, especially in diabetes research, nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH), provides a reliable tool for identifying and characterizing potential biomarkers in human plasma for early diagnosis or prognosis of the disease and/or responses to a specific treatment. Predicting the outcome of weight loss or weight management programs is a challenging yet important aspect of such a program's success. The characterization of potential biomarkers of metabolic disorders, such as lysophospholipids and bile acids, in large human clinical cohorts could provide a useful tool for successful predictions. In this study, we validated an LC-MS method combining the targeted and untargeted detection of these lipid species. Its potential for biomarker discovery was demonstrated in a well-characterized overweight/obese cohort subjected to a low-caloric diet intervention, followed by a weight maintenance phase. Relevant markers predicting successful responses to the low-caloric diet intervention for both weight loss and glycemic control improvements were identified. The response to a controlled weight loss intervention could be best predicted using the baseline concentration of three lysophospholipids (PC(22:4/0:0), PE(17:1/0:0), and PC(22:5/0:0)). Insulin resistance on the other hand could be best predicted using clinical parameters and levels of circulating lysophospholipids and bile acids. Our approach provides a robust tool not only for research purposes, but also for clinical practice, as well as designing new clinical interventions or assessing responses to specific treatment. Considering this, it presents a step toward personalized medicine.

摘要

高通量测定法在代谢紊乱(特别是糖尿病研究、非酒精性脂肪肝疾病 [NAFLD] 和非酒精性脂肪性肝炎 [NASH])中的脂质代谢评估中的发展,为鉴定和描述人类血浆中潜在的生物标志物提供了一种可靠的工具,可用于疾病的早期诊断或预后以及(或)对特定治疗的反应。预测减肥或体重管理方案的结果是此类方案成功的一个具有挑战性但很重要的方面。代谢紊乱潜在生物标志物(如溶血磷脂和胆汁酸)的特征,在大型人类临床队列中可以提供成功预测的有用工具。在这项研究中,我们验证了一种 LC-MS 方法,该方法结合了这些脂质种类的靶向和非靶向检测。在经过低热量饮食干预和随后的体重维持阶段的情况下,在特征明确的超重/肥胖队列中,该方法展示了其在生物标志物发现方面的潜力。确定了预测低热量饮食干预对体重减轻和血糖控制改善的成功反应的相关标志物。使用三种溶血磷脂(PC(22:4/0:0)、PE(17:1/0:0)和 PC(22:5/0:0))的基线浓度可以最好地预测对受控体重减轻干预的反应。另一方面,胰岛素抵抗可以使用临床参数以及循环溶血磷脂和胆汁酸的水平来最佳预测。我们的方法不仅为研究目的,而且为临床实践以及设计新的临床干预或评估对特定治疗的反应提供了一种强大的工具。考虑到这一点,它为个性化医疗迈出了一步。

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