Data-driven multivariate population subgrouping via lipoprotein phenotypes <em>versus</em> apolipoprotein B in the risk assessment of coronary heart disease
Ohukainen, Pauli; Kuusisto, Sanna; Kettunen, Johannes; Perola, Markus; Järvelin, Marjo-Riitta; Mäkinen, Ville-Petteri; Ala-Korpela, Mika (2019-12-13)
Pauli Ohukainen, Sanna Kuusisto, Johannes Kettunen, Markus Perola, Marjo-Riitta Järvelin, Ville-Petteri Mäkinen, Mika Ala-Korpela, Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease, Atherosclerosis, Volume 294, 2020, Pages 10-15, ISSN 0021-9150, https://doi.org/10.1016/j.atherosclerosis.2019.12.009
© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe2020042722683
Tiivistelmä
Abstract
Background and aims: Population subgrouping has been suggested as means to improve coronary heart disease (CHD) risk assessment. We explored here how unsupervised data-driven metabolic subgrouping, based on comprehensive lipoprotein subclass data, would work in large-scale population cohorts.
Methods: We applied a self-organizing map (SOM) artificial intelligence methodology to define subgroups based on detailed lipoprotein profiles in a population-based cohort (n = 5789) and utilised the trained SOM in an independent cohort (n = 7607). We identified four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk and compared those to univariate subgrouping by apolipoprotein B quartiles.
Results: The SOM-based subgroup with highest concentrations for non-HDL measures had the highest, and the subgroup with lowest concentrations, the lowest risk for CHD. However, apolipoprotein B quartiles produced better resolution of risk than the SOM-based subgroups and also striking dose-response behaviour.
Conclusions: These results suggest that the majority of lipoprotein-mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles. Therefore, even advanced multivariate subgrouping, with comprehensive data on lipoprotein metabolism, may not advance CHD risk assessment.
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