Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease

Kevin Huynh(Baker Heart and Diabetes Institute), Wei Ling Florence Lim(Edith Cowan University), Corey Giles(Baker Heart and Diabetes Institute), Kaushala S. Jayawardana(Baker Heart and Diabetes Institute), Agus Salim(Baker Heart and Diabetes Institute), Natalie A. Mellett(Baker Heart and Diabetes Institute), Alexander Smith(Baker Heart and Diabetes Institute), Gavriel Olshansky(Baker Heart and Diabetes Institute), Brian G. Drew(Baker Heart and Diabetes Institute), Pratishtha Chatterjee(Edith Cowan University), Ian Martins(Edith Cowan University), Simon M. Laws(Edith Cowan University), Ashley I. Bush(The University of Melbourne), Christopher C. Rowe(The University of Melbourne), Victor L. Villemagne(The University of Melbourne), David Ames(National Ageing Research Institute), Colin L. Masters(The University of Melbourne), Matthias Arnold(Duke University), Kwangsik Nho(Indiana University School of Medicine), Andrew J. Saykin(Indiana University School of Medicine), Rebecca Baillie(Rosa (United States)), Xianlin Han(The University of Texas at San Antonio Health Science Center), Rima Kaddurah‐Daouk(Duke University), Ralph N. Martins(Edith Cowan University), Peter J. Meikle(Baker Heart and Diabetes Institute)
Nature Communications
November 10, 2020
Cited by 163Open Access
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Abstract

Abstract Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM 3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation.


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