Mika Ala-Korpela, Siyu Zhao, Marjo-Riitta Järvelin, Ville-Petteri Mäkinen, Pauli Ohukainen, Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology: disclosure of fundamental structural and metabolic relationships, International Journal of Epidemiology, 2021;, dyab156, https://doi.org/10.1093/ije/dyab156
Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology : disclosure of fundamental structural and metabolic relationships
|Author:||Ala-Korpela, Mika1,2,3,4; Zhao, Siyu1,2,3; Järvelin, Marjo-Riitta2,3,5,6,7;|
1Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
2Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
3Biocenter Oulu, University of Oulu, Oulu, Finland
4NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
5Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
6Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
7Department of Life Sciences, College of Health and Life Sciences, Brunel University London, UK
8Australian Centre for Precision Health, University of South Australia, Adelaide, Australia
9Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, Australia
|Online Access:||PDF Full Text (PDF, 2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022020217345
Oxford University Press,
|Publish Date:|| 2022-02-02
Background: Quantitative lipoprotein analytics using nuclear magnetic resonance (NMR) spectroscopy is currently commonplace in large-scale studies. One methodology has become widespread and is currently being utilized also in large biobanks. It allows the comprehensive characterization of 14 lipoprotein subclasses, clinical lipids, apolipoprotein A-I and B. The details of these data are conceptualized here in relation to lipoprotein metabolism with particular attention on the fundamental characteristics of subclass particle numbers, lipid concentrations and compositional measures.
Methods and results: The NMR methodology was applied to fasting serum samples from Northern Finland Birth Cohorts 1966 and 1986 with 5651 and 5605 participants, respectively. All results were highly consistent between the cohorts. Circulating lipid concentrations in a particular lipoprotein subclass arise predominantly as the result of the circulating number of those subclass particles. The spherical lipoprotein particle shape, with a radially oriented surface monolayer, imposes size-dependent biophysical constraints for the lipid composition of individual subclass particles and inherently restricts the accommodation of metabolic changes via compositional modifications. The new finding that the relationship between lipoprotein subclass particle concentrations and the particle size is log-linear reveals that circulating lipoprotein particles are also under rather strict metabolic constraints for both their absolute and relative concentrations.
Conclusions: The fundamental structural and metabolic relationships between lipoprotein subclasses elucidated in this study empower detailed interpretation of lipoprotein metabolism. Understanding the intricate details of these extensive data is important for the precise interpretation of novel therapeutic opportunities and for fully utilizing the potential of forthcoming analyses of genetic and metabolic data in large biobanks.
International journal of epidemiology
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
3141 Health care science
M.A.K. is supported by a research grant from the Sigrid Juselius Foundation, Finland. P.O. is supported by the Emil Aaltonen Foundation. The Northern Finland Birth Cohorts have received funding from the Academy of Finland, Novo Nordisk Foundation and EU.
The NFBC data sets are available through an application process for researchers who meet the criteria for access to confidential data. Please contact the project centre (NFBCprojectcenter@oulu.fi) and visit the website (www.oulu.fi/nfbc) for more information.
© The Author(s) 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.