Glymphatic system clearance and Alzheimer’s disease risk: a CSF proteome-wide study

Cullell, Natalia, Caruana, Giovanni, Elias-Mas, Andrea, Delgado-Sanchez, Ariane, Artero, Cristina, Buongiorno, Maria Teresa, Almería, Marta, Ray, Nicola J ORCID: https://orcid.org/0000-0001-9645-0812, Correa, Sonia A L ORCID: https://orcid.org/0000-0002-7434-1073 and Krupinski, Jerzy ORCID: https://orcid.org/0000-0002-5136-8898 (2025) Glymphatic system clearance and Alzheimer’s disease risk: a CSF proteome-wide study. Alzheimer's Research & Therapy, 17 (1). 31. ISSN 1758-9193

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Abstract

Background: The emerging evidence of the role of the glymphatic system (GS) in Alzheimer’s disease (AD) provides new opportunities for intervention from the earliest stages of the disease. The aim of the study is to evaluate the efficacy of GS in AD to identify new disease biomarkers. Methods: We performed a two-stage proteomic study to evaluate the GS health using intravenous gadolinium-based contrast agent (GBCA) with serial T1 3T magnetic resonance imaging (MRI) in individuals with amnestic mild cognitive impairment (aMCI). In Stage 1 (evaluated in the Cohort 1 of aMCI participants (n = 11)), we correlated the levels of 7K cerebrospinal fluid (CSF) proteins (estimated by SOMAscan) with GS health in 78 Freesurfer-segmented brain regions of interest (ROIs). Results: A total of seven different proteins were significantly associated with GS health (p-value < 6.4 × 10–4). The stronger correlations were identified for NSUN6, GRAAK, OLFML3, ACTN2, RUXF, SHPS1 and TIM-4. A pathway enrichment analysis revealed that the proteins associated with GS health were mainly implicated in neurodegenerative processes, immunity and inflammation. In Stage 2, we validated these proteomic results in a new cohort of aMCI participants (with and without evidence of AD pathology in CSF (aMCI(-) and aMCI/AD( +); n = 22 and 7, respectively) and healthy controls (n = 10). Proteomic prediction models were generated in each ROI. These were compared with demographic-only models for identifying participants with aMCI(-) and aMCI/AD( +) vs controls. This analysis was repeated to determine if the models could identify those with aMCI/AD( +) from both aMCI(-) and controls. The proteomic models were found to outperform the demographic-only models. Conclusions: Our study identifies proteins linked with GS health and involved the immune system in aMCI participants.