Trajectory of plasma lipidomes associated with the risk of late-onset Alzheimer’s disease pathogenesis: a longitudinal study in the ADNI cohort
Year: 2023
Type: preprint
Abstract: Comprehensive lipidomic studies have demonstrated strong cross-sectional associations between the blood lipidome and late-onset Alzheimer’s disease (AD) and its risk factors. However, the longitudinal relationship between the lipidomic variations and progression of AD remains unknown. Here, we employed longitudinal lipidomic profiling on 4,730 plasma samples from 1,517 participants of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort to investigate the temporal evolution of lipidomes among diagnostic groups. At baseline, there were 1,393 participants including 437 cognitively normal (CN), 713 with mild cognitive impairment (MCI), and 243 AD cases. During follow up, 329 individuals (29 CN and 300 MCI) developed clinical AD (AD converters). We developed an AD-CN classification model to stratify the non-converting MCI group into AD-like and non AD-like MCI based on their lipidomics profiles at baseline. Longitudinal analysis identified associations between the change in ether lipid species (including alkylphosphatidylcholine, alkenylphosphatidylcholine, lysoalkylphosphatidylcholine, and lysoalkenylphosphatidylcholine) in converters relative to non-converting CN and MCI groups. Further, the AD-CN model efficiently classified MCI into low AD risk and high AD risk, with the high AD risk group having two times higher risk of conversion to AD than the low risk group. These findings suggest that the lipidomic profile can serve as a potential biomarker to identify individuals at higher risk for progressing to AD.
Source: medRxiv
Authors: Tingting Wang, Matthias Arnold, Kevin Huynh, Patrick Weinisch, Corey Giles, Natalie A Mellett, Thy Duong, Bharadwaj Marella, Kwangsik Nho, Alysha De Livera, Xianlin Han, Colette Blach, Andrew J Saykin, Gabi Kastenmüller, Peter J Meikle, Rima Kaddurah-Daouk, the Alzheimer’s Disease Neuroimaging Initiative
Institutions: Baker Heart and Diabetes Institute, The University of Melbourne, Duke University, Helmholtz Munich, Institute of Computational Biology, La Trobe University, Indiana University Indianapolis, Indiana University School of Medicine, The University of Texas at San Antonio Health Science Center
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4380318448
