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SHR Neuro Cancer Cardio Lipid Metab Microb
Conde, R; Gil-Redondo, R; Bizkarguenaga, M; Lodge, S; Nitschke, P; de, Diego, Á; González-Valle, B; Hui, J; Hunter, ML; Yeap, BB; Cenarro, A; Lope, V; Habisch, H; Haudum, C; Verheyen, N; Obermayer-Pietsch, B; Zaro, Bastanzuri, MJ; González, Fernández, MR; Fernández-Bergés, D; Salazar, AM; Sorando-Fernandez, MP; Meijide, S; Hernandez, G; Arana, E; Seco, ML; Sousa, A; Oliveira, N; Verde, I; Madl, T; Unda-Urzaiz, M; Carracedo, A; Diercks, T; Castelló, A; Schäfer, H; Spraul, M; Cannet, C; Embade, N; Valenti, L; Civeira, F; Lu, SC; Holmes, E; Wist, J; Nicholson, JK; Mato, JM; Millet, O.
Age- and sex-specific lipoprotein profiles in general and cardiometabolic population cohorts.
EBioMedicine. 2025; 122:106021
Doi: 10.1016/j.ebiom.2025.106021
PubMed
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FullText_MUG
- Co-authors Med Uni Graz
- Habisch Hansjörg
- Haudum Christoph
- Madl Tobias
- Obermayer-Pietsch Barbara
- Verheyen Nicolas Dominik
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- Abstract:
- 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.