Intra- and inter-individual variation of the human lipidome

  • Anh Hoang Nguyen
  • , Habtamu B. Beyene
  • , Gabriele Mocciaro
  • , Lisa Hahnefeld
  • , Santosh Lamichhane
  • , Mikael Fabritius
  • , Henri Avela
  • , Yuqin Wang
  • , Alex M. Dickens
  • , Robert Gurke
  • , Baoru Yang
  • , William J. Griffiths
  • , Tuulia Hyötyläinen
  • , Peter J. Meikle
  • , Matej Orešič*
  • *Corresponding author for this work

Research output: Contribution to journalReview Article or Literature Reviewpeer-review

1 Citation (Scopus)

Abstract

Lipids play essential roles in cellular functions such as membrane structure, signaling, and energy storage. Lipidomics—global study of lipids in cells and tissues—seeks to identify biomarkers and uncover underlying metabolic pathways. Human lipid concentrations in cells and biofluids can fluctuate at multiple temporal scales, reflecting normal biochemical and physiological variation, or responses to various internal and external stimuli. Understanding both intra- and inter-individual lipid variability is crucial for accurate lipidomics study design and interpretation. This knowledge also supports personalized healthcare, moving beyond static reference ranges. Here, we review key drivers of intra-individual variation, including diet, circadian rhythms, sleep, environmental exposures, and physiological states. We also examine inter-individual factors such as genetics, age, sex, microbiome composition, and medications. Finally, we discuss how these variables interact and influence lipidomics outcomes, aiming to enhance reproducibility and guide future research.

Original languageEnglish
Article number118368
JournalTrAC - Trends in Analytical Chemistry
Volume191
DOIs
Publication statusPublished - Oct 2025
MoE publication typeA2 Review article in a scientific journal

Funding

This publication is based upon work from COST Action EpiLipidNET, Pan-European Network in Lipidomics and Epilipidomics (CA19105; https://www.epilipid.net), supported by COST (European Cooperation in Science and Technology). We would like to thank Samuel Rischke for creating Fig. 1. Figures were also created with Biorender.

Keywords

  • Human lipidome
  • Inter-individual variation
  • Intra-individual variation
  • Lipidomics
  • Mass spectrometry

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