Cerebrospinal fluid inflammatory cytokines as prognostic indicators for cognitive decline across Alzheimer's disease spectrum
Year: 2025
Type: article
Abstract: Background Neuroinflammation actively contributes to the pathophysiology of Alzheimer's disease (AD); however, the value of neuroinflammatory biomarkers for disease-staging or predicting disease progression remains unclear. Objective To investigate diagnostic and prognostic utility of inflammatory biomarkers in combination with conventional AD biomarkers. Methods Data from 258 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) with cerebrospinal fluid (CSF) biomarkers of amyloid-β (Aβ), tau, and inflammation were analyzed. Clinically meaningful cognitive decline (CMCD) was defined as a ≥ 4-point increase on the Alzheimer's Disease Assessment Scale Cognitive Subscore 11. Predictor variables included demographics (D: age, sex, education), APOE4 status (A), inflammatory biomarkers (I), and classic AD biomarkers of Aβ and p-tau181 (C). Models incorporating inflammatory biomarkers assessed their contribution to improving baseline diagnostic classification and 1-year CMCD prediction. Results At 1-year follow-up, 27.1% of participants experienced CMCD. Adding inflammatory biomarkers to models with D and A variables (DA model) improved classification of cognitively normal (CN) versus mild cognitive impairment (MCI) and CN versus Dementia ( p < 0.001). Similarly, inflammatory markers enhanced classification in models including C (DAC model), for CN versus MCI ( p < 0.01) and CN versus Dementia ( p < 0.001). Predictive performance for CMCD was improved in individuals with MCI and dementia in both models (all p < 0.05). In addition, the DAI model outperformed the DAC model in predicting CMCD for MCI and Dementia groups (both p < 0.05). Conclusions Addition of CSF inflammatory biomarkers to biomarkers of AD improves diagnostic accuracy of clinical disease stage at baseline and add incremental value to AD biomarkers for prediction of cognitive decline.
Source: Journal of Alzheimer s Disease
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G104586243, G1363224498, G1568214416, G1690084658, G2183984161, G2227922493, G2936261991, Predictive analytics for cognitive decline and Alzheimer's disease, Early Phase Pain Investigation Clinical Network: Greater New York Clinical Center, Einstein Aging Study, G4144334948, Feasibility and Acceptability of Telephone-delivered MBCT for Migraine and Depression (FATE-MD), Alzheimer's Disease Neuroimaging Initiative, G5781168786, G5810807418, G5812660874, G6030962204, G646921540, G6857393522, G6979286903
OpenAlex ID: W4409674404