Lipids, lipoproteins, and metabolites and risk of myocardial infarction and stroke
Holmes, Michael V.; Millwood, Iona Y.; Kartsonaki, Christiana; Hill, Michael R.; Bennett, Derrick A.; Boxall, Ruth; Guo, Yu; Xu, Xin; Bian, Zheng; Hu, Ruying; Walters, Robin G.; Chen, Junshi; Ala-Korpela, Mika; Parish, Sarah; Clarke, Robert J.; Peto, Richard; Collins, Rory; Li, Liming; Chen, Zhengming (2018-02-06)
Michael V. Holmes, Iona Y. Millwood, Christiana Kartsonaki, Michael R. Hill, Derrick A. Bennett, Ruth Boxall, Yu Guo, Xin Xu, Zheng Bian, Ruying Hu, Robin G. Walters, Junshi Chen, Mika Ala-Korpela, Sarah Parish, Robert J. Clarke, Richard Peto, Rory Collins, Liming Li, Zhengming Chen, Lipids, Lipoproteins, and Metabolites and Risk of Myocardial Infarction and Stroke, Journal of the American College of Cardiology, Volume 71, Issue 6, 2018, Pages 620-632, ISSN 0735-1097, https://doi.org/10.1016/j.jacc.2017.12.006.
© 2018 The Authors. Published by Elsevier on behalf of the American College of CardiologyFoundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe2019070222617
Tiivistelmä
Abstract
Background: Blood lipids are established risk factors for myocardial infarction (MI), but uncertainty persists about the relevance of lipids, lipoprotein particles, and circulating metabolites for MI and stroke subtypes.
Objectives: This study sought to investigate the associations of plasma metabolic markers with risks of incident MI, ischemic stroke (IS), and intracerebral hemorrhage (ICH).
Methods: In a nested case-control study (912 MI, 1,146 IS, and 1,138 ICH cases, and 1,466 common control subjects) 30 to 79 years of age in China Kadoorie Biobank, nuclear magnetic resonance spectroscopy measured 225 metabolic markers in baseline plasma samples. Logistic regression was used to estimate adjusted odds ratios (ORs) for a 1-SD higher metabolic marker.
Results: Very low-, intermediate-, and low-density lipoprotein particles were positively associated with MI and IS. High-density lipoprotein (HDL) particles were inversely associated with MI apart from small HDL. In contrast, no lipoprotein particles were associated with ICH. Cholesterol in large HDL was inversely associated with MI and IS (OR: 0.79 and 0.88, respectively), whereas cholesterol in small HDL was not (OR: 0.99 and 1.06, respectively). Triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI, with a similar pattern for IS. Glycoprotein acetyls, ketone bodies, glucose, and docosahexaenoic acid were associated with all 3 diseases. The 225 metabolic markers showed concordant associations between MI and IS, but not with ICH.
Conclusions: Lipoproteins and lipids showed similar associations with MI and IS, but not with ICH. Within HDL particles, cholesterol concentrations were inversely associated, whereas triglyceride concentrations were positively associated with MI. Glycoprotein acetyls and several non–lipid-related metabolites associated with all 3 diseases.
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