中国成年人血浆代谢物与死亡风险的前瞻性关联研究  

Associations of plasma metabolites with mortality in Chinese adults:a prospective study

作　　者：巫婷 宋树摇 庞元捷[1,2,3] 余灿清 孙点剑一[1,2,3] 裴培 杜怀东 陈君石 陈铮鸣[4] 潘安 吕筠[1,2,3,7] 李立明 中国慢性病前瞻性研究项目协作组[8] Wu Ting;Song Shuyao;Pang Yuanjie;Yu Canqing;Sun Dianjianyi;Pei Pei;Du Huaidong;Chen Junshi;Chen Zhengming;Pan An;Lyu Jun;Li Liming;the China Kadoorie Biobank Collaborative Group(Department of Epidemiology and Biostatistics,School of Public Health,Peking University,Beijing 100191,China;Peking University Center for Public Health and Epidemic Preparedness&Response,Beijing 100191,China;Key Laboratory of Epidemiology of Major Diseases(Peking University),Ministry of Education,Beijing 100191,China;Clinical Trial Service Unit and Epidemiological Studies Unit,Nuffield Department of Population Health,University of Oxford,Oxford OX37LF,United Kingdom;China National Center for Food Safety Risk Assessment,Beijing 100022,China;Department of Epidemiology and Biostatistics,School of Public Health,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China;State Key Laboratory of Vascular Homeostasis and Remodeling,Peking University,Beijing 100191,China;不详)

机构地区：[1]北京大学公共卫生学院流行病与卫生统计学系,北京100191 [2]北京大学公众健康与重大疫情防控战略研究中心,北京100191 [3]重大疾病流行病学教育部重点实验室(北京大学),北京100191 [4]牛津大学临床与流行病学研究中心纳菲尔德人群健康系,牛津OX37LF [5]国家食品安全风险评估中心,北京100022 [6]华中科技大学同济医学院公共卫生学院流行病与卫生统计学系,武汉430030 [7]北京大学血管稳态与重构全国重点实验室,北京100191 [8]不详

出　　处：《中华流行病学杂志》2025年第4期557-565,共9页Chinese Journal of Epidemiology

基　　金：国家自然科学基金(82304223,82192902,82192904,82192900,81973125);国家重点研发计划(2023YFC3606302);中国香港Kadoorie Charitable基金。

摘　　要：目的探究中国成年人血浆代谢物水平与全因死亡及各死因别死亡风险间的前瞻性关联。方法基于中国慢性病前瞻性研究(CKB)中2183名健康成年人的血浆代谢组学数据,采用靶向质谱技术检测代谢物水平。使用Cox比例风险回归模型分析630种血浆代谢物与全因死亡风险间的关联,同时通过特定原因的风险回归模型,评估血浆代谢物与心血管疾病(CVD)、癌症及其他原因死亡风险的关系。通过逐步回归筛选出与全因死亡独立相关的关键代谢物,并采用受试者工作特征曲线下面积(AUC)评估这些血浆代谢物对传统预测因子在全因死亡预测能力上的提升。结果研究对象年龄为(53.2±9.8)岁,65.1%为女性,中位随访14.5年,共发生231名死亡。共有44种血浆代谢物与全因死亡风险显著相关[错误发现率(FDR)校正后均P<0.05],主要包括TG、神经酰胺和氨基酸类物质。同时,分别发现29、15种与癌症死亡、其他原因死亡相关的血浆代谢物,但FDR校正后未观察到与CVD死亡显著相关的血浆代谢物。将14种与全因死亡独立相关的血浆代谢物纳入传统预测模型后,显著提升了模型的预测性能。其中,在包含实验室检测指标的传统预测模型中加入血浆代谢物,模型AUC达到0.798(95%CI:0.755~0.843),相对于传统预测模型提升了0.088(P<0.001)。结论多种血浆代谢物与死亡风险相关,并能显著提升死亡风险预测模型的准确性,本研究为理解衰老的生理机制及开展个体化健康风险评估提供了新的线索。Objective To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods This study analyzed plasma metabolomics data from 2183 healthy adults in the China Kadoorie Biobank(CKB),measured using targeted mass spectrometry.Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality.Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease(CVD)risks,cancer,and other-cause mortality.Stepwise regression was used to identify key metabolites independently associated with all-cause mortality,and the area under the receiver operating characteristic curve(AUC)was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results The mean age of the participants was(53.2±9.8)years,65.1%of whom were female.During a median follow-up of 14.5 years,231 deaths occurred.A total of 44 metabolites were significantly associated with the risk of all-cause mortality[false discovery rate(FDR)-adjusted P<0.05],primarily including triglycerides,ceramides,and amino acids.Additionally,29 and 15 metabolites were found to be associated with cancer and other-cause mortality,respectively,but no metabolites were significantly associated with CVD mortality after FDR corrections.Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance.Specifically,incorporating metabolites into the traditional model,which already included laboratory biomarkers,increased the AUC to 0.798(95%CI:0.755-0.843),an improvement of 0.088 compared to the traditional model(P<0.001).Conclusions Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models.These findings provide new insigh

关 键 词：代谢标志物 死亡 前瞻性队列研究 

分 类 号：R54[医药卫生—心血管疾病]