Multi-Omics Exploration of Obesity Biomarkers in Sedentary and Weight Loss Cohorts.

IF 6.2 Q2 GENETICS & HEREDITY
Phenomics (Cham, Switzerland) Pub Date : 2024-10-28 eCollection Date: 2025-04-01 DOI:10.1007/s43657-024-00165-x
Hui Wang, Yixiao Zhuang, Rong Hua, Ting Yao, Kaiqing Lin, Yitao Zhang, Rui Huang, Ruwen Wang, Shanshan Guo, Qiwei Shen, Yikai Shao, Wei Wu, Linling Fan, Yonghao Feng, Qiyuan Yao, Hongying Ye, Xingxing Kong, Qiongyue Zhang, Ru Wang, Tiemin Liu
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Abstract

Sedentary behavior for two years during the coronavirus disease 2019 (COVID-19) pandemic contributes to weight gain. Gut microbiota and blood metabolome are related to body mass index (BMI) and indicate individual metabolic changes. Surgery and exercise are effective weight-loss methods. The precise plasma metabolites and gut microbiota biomarkers involved and the underlying mechanisms are still largely unclear. To address this issue, we analyzed weight gain and weight loss cohorts to identify biomarkers associated with obesity. In the sedentary cohort, 49 subjects were recruited in year 2019. After two years of sedentary behavior during the COVID-19 pandemic, the BMI of 24 subjects significantly increased (Weight gain group), while that of the remnant 25 subjects remained constant (Maintaining weight group). At baseline and two years post baseline, the gut microbiota and blood metabolome, as well as body composition and clinical indicators, were all collected. In weight loss studies, we analyze the plasma metabolome of the two cohorts, including individuals who underwent laparoscopic sleeve gastrectomy (LSG) surgery and exercise intervention. Weight gain through sedentary behavior contributed to the variation of the gut microbiota and plasma metabolites composition. Creatine, phenylalanine and tyrosine exhibited significant positive associations with BMI and fat mass. We further confirmed the association between BMI and plasma metabolites in two weight loss cohorts. By utilizing a linear regression model, we found that 10 metabolites including creatine were correlated with BMI in weight loss individuals. Based on receiver operating characteristic (ROC) curves, creatine exhibited a satisfactory classification performance in regard to predicting weight reduction (AUCLSG = 0.890, AUCS ports = 0.840). Moreover, some gut microbiota, including Bifidobacterium angulatum DSM 20098 = JCM 7096 and Rothia dentocariosa M567I could affect BMI through the mediating factor of creatine.

Graphical abstract:

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-024-00165-x.

久坐和减肥人群中肥胖生物标志物的多组学研究。
在2019冠状病毒病(COVID-19)大流行期间,久坐两年会导致体重增加。肠道微生物群和血液代谢组与身体质量指数(BMI)有关,表明个体代谢变化。手术和运动是有效的减肥方法。确切的血浆代谢物和肠道微生物群生物标志物及其潜在机制仍不清楚。为了解决这个问题,我们分析了体重增加和体重减少的队列,以确定与肥胖相关的生物标志物。在久坐队列中,2019年招募了49名受试者。在COVID-19大流行期间,经过两年的久坐行为,24名受试者的BMI显著增加(增重组),而剩余25名受试者的BMI保持不变(维持体重组)。在基线和基线后2年,收集肠道微生物群和血液代谢组,以及身体组成和临床指标。在减肥研究中,我们分析了两个队列的血浆代谢组,包括接受腹腔镜袖胃切除术(LSG)手术和运动干预的个体。久坐行为导致的体重增加会导致肠道微生物群和血浆代谢物组成的变化。肌酸、苯丙氨酸和酪氨酸与BMI和脂肪量呈显著正相关。我们进一步证实了两个减肥队列中BMI和血浆代谢物之间的关联。通过线性回归模型,我们发现包括肌酸在内的10种代谢物与减肥个体的BMI相关。根据受试者工作特征(ROC)曲线,肌酸在预测体重减轻方面表现出令人满意的分类性能(AUCLSG = 0.890, AUCS ports = 0.840)。此外,角双歧杆菌DSM 20098 = JCM 7096、牙齿罗氏菌M567I等肠道菌群可通过肌酸的介导因子影响BMI。图片摘要:补充资料:在线版本包含补充资料,下载地址为10.1007/s43657-024-00165-x。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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