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  5. Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology – disclosure of fundamental structural and metabolic relationships

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Preprint
en
2021

Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology – disclosure of fundamental structural and metabolic relationships

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0 Files

en
2021
DOI: 10.1101/2021.03.08.21253123

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Paul M Ridker
Paul M Ridker

Harvard University

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Mika Ala‐Korpela
Siyu Zhao
Paul M Ridker
+2 more

Abstract

Abstract Aims Quantitative lipoprotein analytics by NMR spectroscopy is currently commonplace in large-scale studies. One methodology has become widespread and is currently being utilised also in large biobanks. It allows comprehensive characterisation of 14 lipoprotein subclasses, clinical lipids, apolipoprotein A-I and B. The details of these data are conceptualised here in relation to lipoprotein metabolism with particular attention to 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 Cohort 1966 and 1986 with 5,651 and 5,605 participants, respectively. All results were highly coherent 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 reveal that circulating lipoprotein particles are also under rather strict metabolic constraints for both their absolute and relative concentrations. Conclusion 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 consequential for the precise interpretation of novel therapeutic opportunities and for fully utilising the potential of forthcoming analyses of genetic and metabolic data in extensive biobanks. One-sentence Summary NMR spectroscopy facilitates comprehensive characterisation of lipoprotein subclass metabolism and offers additional value to epidemiology, genetics and pharmacology in large-scale studies and biobanks. Key Messages The circulating particle number of a lipoprotein subclass is the defining measure for its lipid concentrations; the particle lipid composition is only in a minor role. The relationship between circulating lipoprotein subclass particle concentrations and the particle size is log-linear. The overall structure of lipoprotein subclass particles with a spherical shape and an oriented surface monolayer poses strong size-dependent biomolecular constraints for their lipid composition. The circulating lipoprotein subclass particle concentrations in humans are metabolically constraint for both elemental absolute and relative concentration ranges. The smallest HDL particle concentrations are negatively associated with those of large HDL and generally the associations of the smallest HDL particles are similar to those of apolipoprotein B-containing particles. The apolipoprotein B-containing particles constitute less than 10% of all lipoprotein particles but carry around two thirds of circulating lipoprotein lipids. LDL and IDL particles amount to almost 90% of all apolipoprotein B-containing particles. The supplemental role of lipoprotein subclass data in cardiometabolic risk assessment is slight. In the current era of biobanks and big data, the combination of lipoprotein subclass data with drug-target Mendelian randomization analyses provides great scientific synergy, intricate details and potential cost savings in drug development. Graphical abstract / key messages

How to cite this publication

Mika Ala‐Korpela, Siyu Zhao, Paul M Ridker, Ville‐Petteri Mäkinen, Pauli Ohukainen (2021). Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology – disclosure of fundamental structural and metabolic relationships. , DOI: https://doi.org/10.1101/2021.03.08.21253123.

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Publication Details

Type

Preprint

Year

2021

Authors

5

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1101/2021.03.08.21253123

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