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Abstract
Lipidomics research could provide insights of pathobiological mechanisms in Alzheimer’s disease. This study explores a battery of plasma lipids that can differentiate Alzheimer’s disease (AD) patients from healthy controls and determines whether lipid profiles correlate with genetic risk for AD. AD plasma samples were collected from the Sydney Memory and Ageing Study (MAS) Sydney, Australia (aged range 75–97 years; 51.2% male). Untargeted lipidomics analysis was performed by liquid chromatography coupled–mass spectrometry (LC–MS/MS). We found that several lipid species from nine lipid classes, particularly sphingomyelins (SMs), cholesterol esters (ChEs), phosphatidylcholines (PCs), phosphatidylethanolamines (PIs), phosphatidylinositols (PIs), and triglycerides (TGs) are dysregulated in AD patients and may help discriminate them from healthy controls. However, when the lipid species were grouped together into lipid subgroups, only the DG group was significantly higher in AD. ChEs, SMs, and TGs resulted in good classification accuracy using the Glmnet algorithm (elastic net penalization for the generalized linear model [glm]) with more than 80% AUC. In general, group lipids and the lipid subclasses LPC and PE had less classification accuracy compared to the other subclasses. We also found significant increases in SMs, PIs, and the LPE/PE ratio in human U251 astroglioma cell lines exposed to pathophysiological concentrations of oligomeric Aβ42. This suggests that oligomeric Aβ42 plays a contributory, if not causal role, in mediating changes in lipid profiles in AD that can be detected in the periphery. In addition, we evaluated the association of plasma lipid profiles with AD-related single nucleotide polymorphisms (SNPs) and polygenic risk scores (PRS) of AD. We found that FERMT2 and MS4A6A showed a significantly differential association with lipids in all lipid classes across disease and control groups. ABCA7 had a differential association with more than half of the DG lipids (52.63%) and PI lipids (57.14%), respectively. Additionally, 43.4% of lipids in the SM class were differentially associated with CLU. More than 30% of lipids in ChE, PE, and TG classes had differential associations with separate genes (ChE-PICALM, SLC24A4, and SORL1; PE-CLU and CR1; TG-BINI) between AD and control group. These data may provide renewed insights into the pathobiology of AD and the feasibility of identifying individuals with greater AD risk.
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1 University of New South Wales, Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432); Guangdong Academy of Medical Sciences, Guangdong Mental Health Center, Guangdong Provincial People’s Hospital, Guangzhou, China (GRID:grid.410643.4)
2 University of New South Wales, Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432)
3 University of New South Wales, Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432); Neuroscience Research Australia, Randwick, Australia (GRID:grid.250407.4) (ISNI:0000 0000 8900 8842)
4 University of New South Wales, Mark Wainwright Analytical Centre, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432)
5 University of New South Wales, Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432); Prince of Wales Hospital, Neuropsychiatric Institute, Euroa Centre, Sydney, Australia (GRID:grid.415193.b)
6 University of New South Wales, Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, Sydney, Australia (GRID:grid.1005.4) (ISNI:0000 0004 4902 0432); Huzhou Central Hospital Huzhou, School of Medicine, Huzhou University, Huzhou, China (GRID:grid.413679.e) (ISNI:0000 0004 0517 0981)