Combining two large clinical cohorts (AIBL and ADNI) to identify multiple lipid metabolic pathways in prevalent and incident Alzheimer’s disease
Year: 2020
Type: preprint
Abstract: ABSTRACT Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising of many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 lipid species across 32 lipid (sub)classes) allows for detailed isomeric and isobaric lipid separation. We applied the methodology to examine plasma samples from the Australian Imaging, Biomarkers and Lifestyle flagship study of aging (AIBL, n = 1112) and serum from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n = 800) studies. Cross sectional analysis using both cohorts identified concordant unique peripheral signatures associated with AD. Specific pathways include; sphingolipids, including G M3 gangliosides, where their acyl composition drove the major associations, and lipids previously associated with dysfunctional lipid metabolism in cardiometabolic disease including the phosphatidylethanolamine and triglyceride classes. Infomation derived from improved isomeric seperation highlighted pathway-specific changes with ether lipids including plasmalogens implicating perixosmal dysfunction in disease pathology. Longitudinal analysis revealed similar lipid signitures in both AIBL and ADNI cohorts with future disease onset. We utilised the two independent studies to train and validate multivariate lipid models that significantly improved disease classification and prediction. Together our results provide a holistic view of the lipidome and its relationship with AD using a comprehensive lipidomics approach, providing targets for further mechanistic investigation.
Source: medRxiv
Authors: Kevin Huynh, Wei Ling Florence Lim, Corey Giles, Kaushala S Jayawardana, Agus Salim, Natalie A Mellett, Alex Smith, Gavriel Olshansky, Brian G Drew, Pratishtha Chatterjee, Ian Martins, Simon M Laws, Ashley I Bush, Christopher C Rowe, Victor L Villemagne, David Ames, Colin L Masters, Matthias Arnold, Kwangsik Nho, Andrew J Saykin, Rebecca Baillie, Xianlin Han, Rima Kaddurah-Daouk, Ralph N Martins, Peter J Meikle
Institutions: Baker Heart and Diabetes Institute, Monash University, Edith Cowan University, Cooperative Research Centre for Mental Health, La Trobe University, KaRaMinds, Macquarie University, Curtin University, The University of Melbourne, Florey Institute of Neuroscience and Mental Health, Austin Hospital, Austin Health, National Ageing Research Institute, Duke University, Helmholtz Munich, Institute of Computational Biology, Indiana University Indianapolis, Indiana University School of Medicine, Rosa (United States), The University of Texas at San Antonio Health Science Center, The University of Western Australia
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: Science and Industry Endowment Fund, Australian Government, Commonwealth Scientific and Industrial Research Organisation, Dementia Collaborative Research Centres, Australia, Dementia Australia, Medical Research Council, National Health and Medical Research Council, National Institute on Aging
OpenAlex ID: W3032328632