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Lipid-derived Compounds in the Human Body

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Related Experiment Video

Updated: May 9, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

Plasma lipid profiling in a large population-based cohort.

Jacquelyn M Weir1, Gerard Wong, Christopher K Barlow

  • 1Baker IDI Heart and Diabetes Institute, Melbourne, Australia.

Journal of Lipid Research
|July 23, 2013
PubMed
Summary

This study profiled 312 plasma lipids in over 1,000 individuals, revealing associations between lipid subclasses like ceramides and lysophospholipids with age, sex, and body mass index (BMI). These findings may link obesity and metabolic health to chronic disease risk.

Keywords:
cardiovascular diseasedisease risklipidomicsmass spectrometryobesity

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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
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Published on: September 30, 2025

Area of Science:

  • Metabolomics
  • Biochemistry
  • Population Health

Background:

  • Plasma lipid profiles are crucial for understanding metabolic health.
  • Previous studies have linked certain lipids to chronic diseases.
  • The interplay between lipids, anthropometrics, and physiology requires further investigation.

Purpose of the Study:

  • To perform comprehensive plasma lipid profiling in a large population cohort.
  • To identify associations between specific lipid classes, subclasses, and individual species with anthropometric and physiological measures.
  • To explore the potential role of lipids in mediating the effects of age, sex, and obesity on disease risk.

Main Methods:

  • Plasma lipid profiling of 312 lipids across 23 classes using liquid chromatography electrospray ionization tandem mass spectrometry.
  • Analysis of a population cohort exceeding 1,000 individuals.
  • Application of linear and logistic regression to identify significant associations.

Main Results:

  • Identified significant associations between lipid subclasses (ceramides, sphingomyelins, lysophospholipids) and anthropometric/physiological measures (age, sex, BMI).
  • Ceramides were higher in males and associated with age and BMI.
  • Lysophospholipids showed age association, were higher in males, and negatively associated with BMI.
  • Cholesterol esters and triacylglycerols showed expected associations with age, sex, and BMI.

Conclusions:

  • Plasma lipid profiling can reveal significant associations with demographic and physiological factors.
  • Specific lipid subclasses demonstrate distinct relationships with age, sex, and BMI.
  • These lipid-phenotype associations may elucidate mechanisms underlying chronic disease risk in diverse populations.