上海交通大学学报（医学版）

上海交通大学学报（医学版） >

2022 , Vol. 42 >Issue 3: 259 - 266

DOI: https://doi.org/10.3969/j.issn.1674-8115.2022.03.001

心脑血管慢病协防共管专题

基于人群大队列探索心脑血管疾病相关血浆代谢组学特征

  • 张梦吉 ,
  • 黄琳 ,
  • 李峥 ,
  • 马卓然 ,
  • 魏霖 ,
  • 袁安彩 ,
  • 胡刘华 ,
  • 张薇 ,
  • 钱昆 ,
  • 卜军
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  • 1.上海交通大学医学院附属仁济医院心内科，上海 200127
    2.上海交通大学生物医学工程学院，上海 200030
    3.上海交通大学医疗机器人研究院，上海 200240
    4.上海市胸科医院/上海交通大学医学院附属胸科医院检验科，上海 200030
张梦吉（1996—），女，博士生；电子信箱：zmj_xy@sjtu.edu.cn
黄 琳（1988—），女，副研究员，博士；电子信箱：linhuang@shsmu.edu.cn。第一联系人：（张梦吉、黄 琳并列第一作者）
卜军，电子信箱：pujun310@hotmail.com。

收稿日期: 2022-01-22

  网络出版日期: 2022-05-09

基金资助

国家重点研发计划(2018YFC1312800);国家自然科学基金(82001985);上海市自然科学基金(20ZR1440000);浦东新区卫生健康委员会联合攻关项目(PW2019D-11)

收起

Plasma metabolic signature of cardiovascular and cerebrovascular diseases from a large cohort study

  • Mengji ZHANG ,
  • Lin HUANG ,
  • Zheng LI ,
  • Zhuoran MA ,
  • Lin WEI ,
  • Ancai YUAN ,
  • Liuhua HU ,
  • Wei ZHANG ,
  • Kun QIAN ,
  • Jun PU
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  • 1.Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
    2.School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
    3.Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
    4.Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
PU Jun, E-mail: pujun310@hotmail.com.

Received date: 2022-01-22

  Online published: 2022-05-09

Supported by

National Key R&D Program of China(2018YFC1312800);National Natural Science Foundation of China(82001985);Natural Science Foundation of Shanghai(20ZR1440000);Joint Project of Health Committee of Pudong New Area(PW2019D-11)

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摘要

目的·采用纳米增强激光解吸电离质谱技术采集大队列人群的血浆代谢指纹图谱，为心脑血管疾病的发生发展提供代谢组学差异解释。方法·所有样本来源于上海市浦东新区自然人群队列。于2019年2—8月期间纳入符合标准的14 419例队列成员，分别为冠心病单患组1 608例，脑卒中单患组461例，心脑血管疾病共患组（冠心病+脑卒中）145例和对照组12 205例，并进行前瞻性血浆样本采集。采用课题组开发的纳米材料增强激光解吸电离质谱技术对血浆样品进行代谢指纹图谱采集，基于统计分析确认心脑血管疾病单患人群（冠心病单患组、脑卒中单患组）或心脑血管共患人群的典型代谢特征。结果·研究共提取到345个代谢信号峰作为血浆代谢指纹图谱。再经过质谱数据分析，鉴定出具有差异性变化的6种代谢生物标志物（以下简称标志物）与心脑血管疾病高度相关。进一步地，6个代谢标志物可以归为“酮体代谢因子”“脂肪酸代谢因子”2个集群。“酮体代谢因子”集群中，冠心病单患组血浆中氨基磺酸、乙酰乙酸、甲基丙二酸的强度显著增加，而在脑卒中单患组、心脑血管共患组中显著下降。“脂肪酸代谢因子”集群中，心脑血管共患组血浆中葡萄糖、半乳糖醛酸、α-亚麻酸的强度显著降低，而在脑卒中单患组中显著增加。根据以上6种代谢标志物，在“酮体代谢因子”集群中，鉴定出3种相关代谢通路；在“脂肪酸代谢因子”集群中，鉴定出2种相关代谢通路。结论·研究采用的新型固相质谱技术实现了大队列人群的高效血浆代谢指纹图谱采集，确定了6个与心脑血管疾病差异调控相关的血浆代谢标志物，进一步从代谢角度揭示心脑血管疾病的分子病理机制，为心脑血管疾病发病机制提供代谢层面线索。

关键词： 心脑血管疾病; 冠心病; 脑卒中; 血浆代谢指纹图谱; 代谢组学; 生物标志物

本文引用格式

张梦吉 , 黄琳 , 李峥 , 马卓然 , 魏霖 , 袁安彩 , 胡刘华 , 张薇 , 钱昆 , 卜军 . 基于人群大队列探索心脑血管疾病相关血浆代谢组学特征[J]. 上海交通大学学报（医学版）, 2022 , 42(3) : 259 -266 . DOI: 10.3969/j.issn.1674-8115.2022.03.001

Abstract

Objective

·To explore the metabolic differences for the occurrence and development of cardiovascular and cerebrovascular diseases, the study performed the plasma metabolic analysis by nano-enhanced laser desorption ionization-mass spectrometry (NELDI-MS) on a large cohort.

Methods

·People were enrolled from general population establishment and follow-up cohort in Pudong New Area, Shanghai. Plasma samples were prospectively collected from 14 419 cohort people who met the criteria from February to August 2019. All the cohort people were divided into coronary heart disease (CHD) group (n=1 608), stroke group (n=461), cardiovascular and cerebrovascular diseases (CHD+stroke) group (n=145) and the control group (n=12 205). The plasma metabolic fingerprints (PMFs) of the enrolled samples were collected by NELDI-MS and then analyzed by statistical analysis for identifying the typical metabolic biomakers in patients with stroke, patients with CHD, and patients with both CHD and stroke.

Results

·Three hundred and forty-five metabolic signal peaks were extracted as PMFs. Six metabolic biomarkers with differential regulations were identified as the potential risk factor for cardiovascular and cerebrovascular diseases respectively by mass spectrometry data analysis. Further, the six metabolic biomarkers were mapped into the altered ketone body and fatty acid metabolism clusters. In the cluster of ketone body metabolism, the intensities of amidosulfonic acid, acetoacetic acid and methylmalonic acid were significantly increased in patients with CHD, but significantly decreased in patients with stroke and cardiovascular cerebrovascular diseases. In the cluster of fatty acid metabolism, the intensities of glucose, galacturonic acid and α-linolenic acid were significantly decreased in patients with cardiovascular and cerebrovascular diseases, but significantly increased in patients with stroke. According to the above six metabolic biomakers, three related metabolic pathways were identified in the cluster of ketone body metabolism, and two related metabolic pathways were identified in the cluster of fatty acid metabolism.

Conclusion

·The novel solid-phase MS approach used in this study has realized the high-efficiency collection of PMFs in a large cohort of people. Six plasma metabolic biomarkers with differential regulation are identified in cohort people with cardiovascular and cerebrovascular diseases, shedding light on the molecular pathological mechanisms of cardiovascular and cerebrovascular diseases from metabolic perspectives. It is expected to provide metabolic clues for the pathogenesis of cardiovascular and cerebrovascular diseases.

Key words： cardiovascular and cerebrovascular disease; coronary heart disease (CHD); stroke; plasma metabolic fingerprint (PMF); metabolomics; biomaker

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