ArticleAmerican journal of epidemiology2025
Understanding lipidomics associations and the lipoprotein-related caveats in population epidemiology.
Article in American journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Uncovering the similarities of lipidome-wide markers of carotid artery plaque and metabolic dysfunction-associated fatty liver disease: the Young Finns study.Scientific reports · 2026Article
- Multi-Omics Reveals Mechanisms of Metabolic Rejuvenation in Aged Mice and Pre-Frail Older Men by Losartan.Aging cell · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Mass spectrometry lipidomics is becoming customary to analyze serum/plasma samples in epidemiology. The measurables are molecular constituents of lipoprotein particles, but very little is known about the consequences of adjusting lipidomics data with lipoprotein measures. We studied 2 population cohorts with 5657 and 2036 participants. Liquid chromatography/tandem mass spectrometry lipidomics was applied to analyze 24 molecular lipid classes and nuclear magnetic resonance spectroscopy to quantify 7 lipoprotein lipids plus apolipoprotein A-I and B. The associations of these measures were analyzed via partial Spearman's correlations. The effects of 9 different lipoprotein adjustments on these interrelationships were assessed. Multivariable regression modeling with these adjustments was also performed for the associations between the lipidomics data and body mass index. These novel large-scale lipidomics data and their associations between the lipoprotein measures were coherent in both population cohorts, confirming the compatibility of the analytical approaches. Simulated data were generated to corroborate the mediation effects. The lipoprotein-related lipid transport and metabolism inherently mediate the lipidomics associations, as evident from the striking effects of the lipoprotein adjustments. These effects and their relevance to the interpretations of lipidomics data are presented and discussed in detail for the first time. The combined lipoprotein lipid adjustments appear prone to overadjustment and arbitrary biases.
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