Combining two large clinical cohorts (AIBL and ADNI) to identify multiple lipid metabolic pathways in prevalent and incident Alzheimer's disease.
By
Kevin Huynh,
Florence Lim,
Corey Giles,
Kaushala S Jayawardana,
Agus Salim,
Natalie A Mellett,
Alexander 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
Posted 28 May 2020
medRxiv DOI: 10.1101/2020.05.26.20114215
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 GM3 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.
Download data
- Downloaded 383 times
- Download rankings, all-time:
- Site-wide: 69,160
- In neurology: 147
- Year to date:
- Site-wide: 32,860
- Since beginning of last month:
- Site-wide: 35,780
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!