Evaluating the Predictive Value of Oxylipins for Cognitive Measures And White Matter Hyperintensities in Alzheimer’S Disease Continuum Compared to Conventional Beta‑Amyloid and Tau Protein Biomarkers Publisher



A Shaabanpoor Haghighi ALIREZA ; M Mayeli MAHSA ; E Ramezannezhad ELHAM ; N Pouroushaninia NEGIN ; R Barzegar Parizi REZVAN ; M Nourollahifoumeshi MAHTAB ; N Idelkhani NASIM ; Z Dadjou ZAHRA ; N Saeedipour NILOOFAR ; N Safaee NEGAR
Source: Molecular Neurobiology Published:2025

Abstract

Oxylipins are signaling molecules that result from the oxidation of long-chain polyunsaturated fatty acids, and they have been attracting attention due to their potential use as biomarkers for the early detection of Alzheimer’s disease (AD) and other disorders. In contrast to beta-amyloid and tau protein biomarkers, we aimed to investigate the potential of oxylipins as an AD biomarker to predict cognitive measures. This study analyzed data from 703 participants (mean age 60 years) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We included 150 cognitively normal (CN) participants, 240 patients with early mild cognitive impairment (EMCI), 145 with late mild cognitive impairment (LMCI), 59 with subjetive memory complaints (SMC), and 109 with AD. Cognitive assessments were conducted using the clinical dementia rating scale (CDR), and cerebrospinal fluid (CSF) biomarkers (Aβ1-42 and p-tau181) were measured via the Luminex platform. Metabolite associations with CSF biomarkers were evaluated using random forest regression and linear regression models, with adjustments for age and sex and normalization for total intracranial volume (tICV). In the random forest regression model, Aβ42 was the most significant predictor for EMCI, while BSH_Sphingosine1P18.2 and BSL_GCDCA were significant for LMCI and MCI, respectively. Aβ42 appeared in SMC and CN but with lower significance than in EMCI. In CN, ASL_ResolvinE2 was most important. BSL_12_HETE was the strongest predictor for AD (R-squared = 0.199, metabolite-CSF R-squared = 0.024). Additionally, BSH_FA20.4_w6 (R-squared = 0.1772) outperformed CSF metabolites in EMCI detection, and BSH_Sphingosine1P16.1 (R-squared = 0.19) outperformed CSF metabolites in LMCI detection. Our findings suggest that select oxylipins may serve as predictive biomarkers of cognitive performance, although conventional CSF biomarkers remain superior for predicting the cognitive findings in the early stages. © 2025 Elsevier B.V., All rights reserved.