The metabolomic profile associated with clustering of cardiovascular risk factors -A multi-sample evaluation

被引:6
|
作者
Lind, Lars [1 ]
Sundstrom, Johan [1 ]
Elmstahl, Solve [2 ]
Dekkers, Koen F. [1 ]
Smith, J. Gustav [3 ,4 ,5 ,6 ,7 ,8 ]
Engstrom, Gunnar [2 ]
Fall, Tove [1 ]
Arnlov, Johan [9 ,10 ]
机构
[1] Uppsala Univ, Dept Med Sci, Uppsala, Sweden
[2] Lund Univ, Dept Clin Sci, Malmo, Sweden
[3] Lund Univ, Dept Cardiol, Clin Sci, Lund, Sweden
[4] Skane Univ Hosp, Lund, Sweden
[5] Gothenburg Univ, Inst Med, Dept Mol & Clin Med, Wallenberg Lab, Gothenburg, Sweden
[6] Sahlgrens Univ Hosp, Dept Cardiol, Gothenburg, Sweden
[7] Lund Univ, Wallenberg Ctr Mol Med, Lund, Sweden
[8] Lund Univ, Lund Univ Diabet Ctr, Lund, Sweden
[9] Karolinska Inst, Dept Neurobiol Care Sci & Soc, Div Family Med & Primary Care, Huddinge, Sweden
[10] Dalarna Univ, Sch Hlth & Social Studies, Falun, Sweden
来源
PLOS ONE | 2022年 / 17卷 / 09期
基金
瑞典研究理事会; 欧洲研究理事会;
关键词
SERUM-CHOLESTEROL ESTER; FATTY-ACID-COMPOSITION; INFARCTION;
D O I
10.1371/journal.pone.0274701
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background A clustering of cardiovascular risk factors is denoted the metabolic syndrome (MetS), but the mechanistic underpinnings of this clustering is not clear. Using large-scale metabolomics, we aimed to find a metabolic profile common for all five components of MetS. Methods and findings 791 annotated non-xenobiotic metabolites were measured by ultra-performance liquid chromatography tandem mass spectrometry in five different population-based samples (Discovery samples: EpiHealth, n = 2342 and SCAPIS-Uppsala, n = 4985. Replication sample: SCAPIS-Malmo, n = 3978, Characterization samples: PIVUS, n = 604 and POEM, n = 501). MetS was defined by the NCEP/consensus criteria. Fifteen metabolites were related to all five components of MetS (blood pressure, waist circumference, glucose, HDL-cholesterol and triglycerides) at a false discovery rate of <0.05 with adjustments for BMI and several life-style factors. They represented different metabolic classes, such as amino acids, simple carbohydrates, androgenic steroids, corticosteroids, co-factors and vitamins, ceramides, carnitines, fatty acids, phospholipids and metabolonic lactone sulfate. All 15 metabolites were related to insulin sensitivity (Matsuda index) in POEM, but only Palmitoyl-oleoyl-GPE (16:0/18:1), a glycerophospholipid, was related to incident cardiovascular disease over 8.6 years follow-up in the EpiHealth sample following adjustment for cardiovascular risk factors (HR 1.32 for a SD change, 95%CI 1.07-1.63). Conclusion A complex metabolic profile was related to all cardiovascular risk factors included in MetS independently of BMI. This profile was also related to insulin sensitivity, which provide further support for the importance of insulin sensitivity as an important underlying mechanism in the clustering of cardiovascular risk factors.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors
    Marrachelli, Vannina G.
    Rentero, Pilar
    Mansego, Maria L.
    Manuel Morales, Jose
    Galan, Inma
    Pardo-Tendero, Mercedes
    Martinez, Fernando
    Carlos Martin-Escudero, Juan
    Briongos, Laisa
    Javier Chaves, Felipe
    Redon, Josep
    Monleon, Daniel
    PLOS ONE, 2016, 11 (09):
  • [2] Multi-sample test-based clustering for fuzzy random variables
    Gonzalez-Rodriguez, Gil
    Colubi, Ana
    D'Urso, Pierpaolo
    Montenegro, Manuel
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2009, 50 (05) : 721 - 731
  • [3] BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data
    Guo, Yanghong
    Zhu, Bencong
    Tang, Chen
    Rong, Ruichen
    Ma, Ying
    Xiao, Guanghua
    Xu, Lin
    Li, Qiwei
    BRIEFINGS IN BIOINFORMATICS, 2024, 25 (06)
  • [4] Psychosocial factors in retirement intentions and adjustment: a multi-sample study
    Topa, Gabriela
    Alcover, Carlos-Maria
    CAREER DEVELOPMENT INTERNATIONAL, 2015, 20 (04) : 384 - 408
  • [5] Clustering of cardiovascular risk factors
    Haffner, SM
    MULTIPLE RISK FACTORS IN CARDIOVASCULAR DISEASE: STRATEGIES OF PREVENTION OF CORONARY HEART DISEASE, CARDIAC FAILURE, AND STROKE, 1998, 12 : 233 - 237
  • [6] A Multi-Sample and Multi-Channel Technique for Electrochemical Testing and Corrosion Evaluation
    Ashida, Yugo
    Nishizawa, Shinichi
    JOURNAL OF TESTING AND EVALUATION, 2020, 48 (02) : 1769 - 1775
  • [7] Hypovolaemia was associated with clustering of major cardiovascular risk factors in general population
    Kong, Xianglei
    Ma, Xiaojing
    Yao, Jing
    Zheng, Shuting
    Cui, Meiyu
    Xu, Dongmei
    BMC CARDIOVASCULAR DISORDERS, 2014, 14
  • [8] Clustering of major cardiovascular risk factors is associated with arterial stiffness in adults
    Xiang-Lei Kong
    Xiao-Jing Ma
    Cheng-Yin Zhang
    Dong-Mei Xu
    慢性疾病与转化医学(英文), 2018, 4 (04) : 254 - 259
  • [9] Low insulin sensitivity is associated with clustering of cardiovascular disease risk factors
    Mykkanen, L
    Haffner, SM
    Ronnemaa, T
    Bergman, RN
    Laakso, M
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 1997, 146 (04) : 315 - 321
  • [10] LOW INSULIN SENSITIVITY IS ASSOCIATED WITH A CLUSTERING OF CARDIOVASCULAR RISK-FACTORS
    MYKKANEN, L
    RONNEMAA, T
    LAAKSO, M
    DIABETES, 1994, 43 : A150 - A150