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

PLoS One. 2022 Sep 15;17(9):e0274701. doi: 10.1371/journal.pone.0274701. eCollection 2022.

Abstract

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-Malmö, 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acids
  • Carbohydrates
  • Cardiovascular Diseases*
  • Ceramides
  • Cholesterol, HDL
  • Cluster Analysis
  • Fatty Acids
  • Glucose
  • Glycerophospholipids
  • Heart Disease Risk Factors
  • Humans
  • Insulin Resistance*
  • Metabolic Syndrome*
  • Risk Factors
  • Sulfates
  • Triglycerides
  • Vitamins

Substances

  • Amino Acids
  • Carbohydrates
  • Ceramides
  • Cholesterol, HDL
  • Fatty Acids
  • Glycerophospholipids
  • Sulfates
  • Triglycerides
  • Vitamins
  • Glucose

Grants and funding

JGS was supported by grants from the Swedish Heart-Lung Foundation (2019-0526), the Swedish Research Council (2017-02554), the European Research Council (ERC-STG-2015-679242), Skåne University Hospital, governmental funding of clinical research within the Swedish National Health Service, a generous donation from the Knut and Alice Wallenberg foundation to the Wallenberg Center for Molecular Medicine in Lund, and funding from the Swedish Research Council (Linnaeus grant Dnr 349-2006-237, Strategic Research Area Exodiab Dnr 2009-1039) and Swedish Foundation for Strategic Research (Dnr IRC15-0067) to the Lund University Diabetes Center. GE was supported by grants from the Swedish Heart-Lung Foundation (20200173), Swedish Research Council (2019-01236) TF was supported by grants from Swedish Research Council (2019-01471), the Swedish Heart-Lung Foundation (2019-0505), and the European Research Council (ERC-2018-STG 801965). JÄ was supported by grants from Swedish research council (2019-01015 and 2020-00243) and the Swedish Heart Lung foundation (20180343). The main funding body of The Swedish CArdioPulmonary bioImage Study (SCAPIS) is the Swedish Heart-Lung Foundation. The study is also funded by the Knut and Alice Wallenberg Foundation, the Swedish Research Council, and VINNOVA (Sweden’s Innovation agency), the University of Gothenburg and Sahlgrenska University Hospital, Karolinska Institutet and Stockholm county council, Linköping University and University Hospital, Lund University and Skåne University Hospital, Umeå University and University Hospital, Uppsala University and University Hospital. The EpiHealth study is funded as a strategic research area (SFO) by the Swedish government. The data handling were enabled by resources in project sens2019512 provided by the Swedish National Infrastructure for Computing (SNIC) at Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.