Gender, Contraceptives and Individual Metabolic Predisposition Shape a Healthy Plasma Lipidome

Susanne Sales(Max Planck Institute of Molecular Cell Biology and Genetics), J. Graessler(University Hospital Carl Gustav Carus), Sara Ciucci(Genotype (Germany)), Rania Al-Atrib(University Hospital Carl Gustav Carus), Terhi Vihervaara(Zora Biosciences (Finland)), Kai Schuhmann(Max Planck Institute of Molecular Cell Biology and Genetics), Dimple Kauhanen(Zora Biosciences (Finland)), Marko Sysi‐Aho(Zora Biosciences (Finland)), Stefan R. Bornstein(King's College Hospital NHS Foundation Trust), Marc Bickle(Max Planck Institute of Molecular Cell Biology and Genetics), Carlo Vittorio Cannistraci(Technische Universität Dresden), Kim Ekroos(Zora Biosciences (Finland)), Andrej Shevchenko(Max Planck Institute of Molecular Cell Biology and Genetics)
Scientific Reports
June 14, 2016
Cited by 109Open Access
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Abstract

Lipidomics of human blood plasma is an emerging biomarker discovery approach that compares lipid profiles under pathological and physiologically normal conditions, but how a healthy lipidome varies within the population is poorly understood. By quantifying 281 molecular species from 27 major lipid classes in the plasma of 71 healthy young Caucasians whose 35 clinical blood test and anthropometric indices matched the medical norm, we provided a comprehensive, expandable and clinically relevant resource of reference molar concentrations of individual lipids. We established that gender is a major lipidomic factor, whose impact is strongly enhanced by hormonal contraceptives and mediated by sex hormone-binding globulin. In lipidomics epidemiological studies should avoid mixed-gender cohorts and females taking hormonal contraceptives should be considered as a separate sub-cohort. Within a gender-restricted cohort lipidomics revealed a compositional signature that indicates the predisposition towards an early development of metabolic syndrome in ca. 25% of healthy male individuals suggesting a healthy plasma lipidome as resource for early biomarker discovery.


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