Age- and sex-specific lipoprotein profiles in general and cardiometabolic population cohorts

Ricardo Conde; Rubén Gil-Redondo; Maider Bizkarguenaga; Samantha Lodge; Phillip Nitschke; Ángela de Diego; Beatriz González-Valle; Jennie Hui; Michael L Hunter; Bu B Yeap; Ana Cenarro; Virginia Lope; Hansjörg Habisch; Christoph Haudum; Nicolas Verheyen; Barbara Obermayer-Pietsch; María José Zaro Bastanzuri; María Reyes González Fernández; Daniel Fernández-Bergés; Ane Miren Salazar; Maria Pilar Sorando-Fernandez; Susana Meijide; Gonzalo Hernandez; Eunate Arana; Maria Luisa Seco; Adriana Sousa; Nádia Oliveira; Ignacio Verde; Tobias Madl; Miguel Unda-Urzaiz; Arkaitz Carracedo; Tammo Diercks; Adela Castelló; Hartmut Schäfer; Manfred Spraul; Claire Cannet; Nieves Embade; Luca Valenti; Fernando Civeira; Shelly C Lu; Elaine Holmes; Julien Wist; Jeremy K Nicholson; José M Mato; Oscar Millet

doi:10.1016/j.ebiom.2025.106021

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Age- and sex-specific lipoprotein profiles in general and cardiometabolic population cohorts

Journal article

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Age- and sex-specific lipoprotein profiles in general and cardiometabolic population cohorts

Ricardo Conde, Rubén Gil-Redondo, Maider Bizkarguenaga, Samantha Lodge, Phillip Nitschke, Ángela de Diego, Beatriz González-Valle, Jennie Hui, Michael L Hunter, Bu B Yeap, …

EBioMedicine, Vol.122, 106021

2025

DOI: https://doi.org/10.1016/j.ebiom.2025.106021

PMID: 41207221

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Abstract

Lipids

Lipoproteins

NMR spectroscopy

Ageing

Cardiovascular disease risk

SCORE2

Background Nuclear magnetic resonance (NMR) spectroscopy enables the characterisation of lipoprotein sub-particles, providing a more detailed lipid profile than the conventional lipid measurements, with potential clinical relevance, particularly in cardiovascular disease (CVD), which remains the leading cause of mortality worldwide. Nonetheless, for clinical implementation, it is essential to first determine the normal variation of lipoprotein parameters by age and sex. Methods This cross-sectional study analysed a large dataset of 31,275 serum or plasma samples from five different countries using the B.I.LISA™ NMR-based platform, quantifying 112 lipoprotein parameters, including subclass size and concentration. Lipoprotein parameters from specific cohorts were fitted to a Quantile Generalised Additive Model (QGAM) to calculate the different percentiles as a function of age and sex. Findings A sub-cohort of individuals belonging to non-oriented cohorts (27,470 individuals) showed that lipoprotein parameters exhibit distinct sex- and age-dependent patterns, with inflection points observed around 44 and 60 years in women and around 60 years in men, aligning with known ageing acceleration models. The sub-cohort of 3021 individuals showing cardiometabolic risk factors was used to evaluate the effect of obesity, hypertension and diabetes in the lipoprotein distribution. Finally, we analysed the lipoprotein parameters that align with SCORE2 (a well-known CVD risk predictor) in an age- and sex-dependent manner. Many NMR-derived parameters effectively distinguish between low and high/very high CVD risk profiles, with very low-density (VLDL)-associated parameters demonstrating the highest sensitivity across a broad age range. Interpretation Our findings provide reference values for NMR-derived lipoprotein parameters by age and sex, enabling their accurate interpretation in the context of cardiovascular disease risk stratification. Funding The specific funding of this article is provided in the acknowledgements section.

Details

Title: Age- and sex-specific lipoprotein profiles in general and cardiometabolic population cohorts
Authors/Creators: Ricardo Conde - CIC bioGUNE
Rubén Gil-Redondo - CIC bioGUNE
Maider Bizkarguenaga - CIC bioGUNE
Samantha Lodge - Murdoch University
Phillip Nitschke - Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA, 6150, Australia
Ángela de Diego - CIC bioGUNE
Beatriz González-Valle - CIC bioGUNE
Jennie Hui - Pathwest Laboratory Medicine
Michael L Hunter - The University of Western Australia
Bu B Yeap - Fiona Stanley Hospital
Ana Cenarro - Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Virginia Lope - Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Hansjörg Habisch - Medical University of Graz
Christoph Haudum - University of Graz
Nicolas Verheyen - Medical University of Graz
Barbara Obermayer-Pietsch - University of Graz
María José Zaro Bastanzuri - Hospital Don Benito Villanueva, Badajoz, Spain
María Reyes González Fernández - Hospital Universitario de Badajoz, Badajoz, Spain
Daniel Fernández-Bergés - SES
Ane Miren Salazar - Planta
Maria Pilar Sorando-Fernandez - Osakidetza
Susana Meijide - BioCruces Health research Institute
Gonzalo Hernandez - Planta
Eunate Arana - Osakidetza
Maria Luisa Seco - OSARTEN Kooperativa Elkartea, Arrasate-Mondragón, 20500, Spain
Adriana Sousa - University of Beira Interior
Nádia Oliveira - University of Beira Interior
Ignacio Verde - University of Beira Interior
Tobias Madl - BioTechMed-Graz
Miguel Unda-Urzaiz
Arkaitz Carracedo - CIC bioGUNE
Tammo Diercks - CIC bioGUNE
Adela Castelló - Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Hartmut Schäfer - Bruker
Manfred Spraul - Bruker
Claire Cannet - Bruker
Nieves Embade - CIC bioGUNE
Luca Valenti - Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico
Fernando Civeira - Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Shelly C Lu - Cedars-Sinai Medical Center
Elaine Holmes - Imperial College London
Julien Wist - Murdoch University
Jeremy K Nicholson - Imperial College London
José M Mato - CIC bioGUNE
Oscar Millet - CIC bioGUNE
Publication Details: EBioMedicine, Vol.122, 106021
Publisher: Elsevier Ltd.
Identifiers: 991005829375707891
Murdoch Affiliation: Health Futures Institute; Centre for Computational and Systems Medicine
Language: English
Resource Type: Journal article

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