Atherogenic lipidomics profile in healthy individuals with low cardiorespiratory fitness: The HUNT3 fitness study.


Journal

Atherosclerosis
ISSN: 1879-1484
Titre abrégé: Atherosclerosis
Pays: Ireland
ID NLM: 0242543

Informations de publication

Date de publication:
02 2022
Historique:
received: 20 08 2021
revised: 26 12 2021
accepted: 11 01 2022
pubmed: 2 2 2022
medline: 22 3 2022
entrez: 1 2 2022
Statut: ppublish

Résumé

Low cardiorespiratory fitness is a strong and independent risk factor for cardiovascular disease (CVD). Serum profiling of healthy individuals with large differences in cardiorespiratory fitness may therefore reveal early biomarkers of CVD development. Thus, we aimed to identify circulating lipoprotein subfractions differentially expressed between groups of individuals with large differences in cardiorespiratory fitness, measured as maximal oxygen uptake (VO Healthy subjects (40-59 years) were selected from the third wave of the Trøndelag health study (HUNT3) based on having an age-dependent high VO 99 lipoprotein subfractions were quantified in serum samples using nuclear magnetic resonance (NMR) lipidomics. Standard clinical analyses showed similar levels of total cholesterol, low-density lipoprotein (LDL)-cholesterol and high-density lipoprotein (HDL)-cholesterol between the groups, and slightly higher levels of triglycerides in participants with low VO Low VO

Sections du résumé

BACKGROUND AND AIMS
Low cardiorespiratory fitness is a strong and independent risk factor for cardiovascular disease (CVD). Serum profiling of healthy individuals with large differences in cardiorespiratory fitness may therefore reveal early biomarkers of CVD development. Thus, we aimed to identify circulating lipoprotein subfractions differentially expressed between groups of individuals with large differences in cardiorespiratory fitness, measured as maximal oxygen uptake (VO
METHODS
Healthy subjects (40-59 years) were selected from the third wave of the Trøndelag health study (HUNT3) based on having an age-dependent high VO
RESULTS
99 lipoprotein subfractions were quantified in serum samples using nuclear magnetic resonance (NMR) lipidomics. Standard clinical analyses showed similar levels of total cholesterol, low-density lipoprotein (LDL)-cholesterol and high-density lipoprotein (HDL)-cholesterol between the groups, and slightly higher levels of triglycerides in participants with low VO
CONCLUSIONS
Low VO

Identifiants

pubmed: 35101845
pii: S0021-9150(22)00015-6
doi: 10.1016/j.atherosclerosis.2022.01.001
pii:
doi:

Substances chimiques

Cholesterol, HDL 0
Triglycerides 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

51-57

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Auteurs

Markus Nodeland (M)

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.

Marie Klevjer (M)

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; Department of Cardiology, St. Olavs Hospital, Trondheim, Norway.

Julie Sæther (J)

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; Department of Cardiology, St. Olavs Hospital, Trondheim, Norway; Norwegian Health Association, Oslo, Norway.

Guro Giskeødegård (G)

Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.

Tone Frost Bathen (TF)

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.

Ulrik Wisløff (U)

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; Department of Cardiology, St. Olavs Hospital, Trondheim, Norway.

Anja Bye (A)

Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; Department of Cardiology, St. Olavs Hospital, Trondheim, Norway. Electronic address: anja.bye@ntnu.no.

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Classifications MeSH