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. 2025 Jan 31;17(1):31.
doi: 10.1186/s13195-024-01612-7.

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

Natalia Cullell  1   2 , Giovanni Caruana  3 , Andrea Elias-Mas  3   4   5 , Ariane Delgado-Sanchez  6 , Cristina Artero  7 , Maria Teresa Buongiorno  7 , Marta Almería  7 , Nicola J Ray  6 , Sonia A L Correa  8 , Jerzy Krupinski  9   10
Affiliations

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

Natalia Cullell et al. Alzheimers Res Ther. .

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.

Keywords: Alzheimer’s disease; Glymphatic system; Inflammation; MRI; Mild cognitive impairment; Proteomics.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was approved by the Ethical Committee of the Hospital Universitari MútuaTerrassa, Terrassa (Barcelona), Spain, and was conducted in accordance with both local regulations and international ethical standards, such as the Declaration of Helsinki. All participants were included after signing an informed consent form, having received comprehensive information regarding the study’s purpose, procedures, potential risks, and benefits. Confidentiality and anonymity of participants were strictly maintained throughout the study, and participants were informed of their right to withdraw at any point without consequence. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Description of the study workflow and cohorts. aMCI: amnestic mild cognitive impairment; GS: Glymphatic system. aMCI/AD( +): Participants with aMCI and positive CSF AD biomarkers. AMCI/AD( +) was considered when participants had Aβ1-42/Aβ1-40 < 0.068 plus at least two other positive biomarkers from Aβ1-42 < 638 pg/mL; total-tau > 404 pg/mL; p-tau 181 > 52.1 pg/mL; total-tau/ Aβ42 > 0.784
Fig. 2
Fig. 2
Volcano plot for the “composite” GS clearance efficiency study. The X-axis represents the log2FoldChange (FC) and the Y-axis the -log(p-value). Red dots are proteins with significant (p-value < 0.05) upregulation (log2FC > 1 standard deviation of the mean) and blue dots are proteins with significant downregulation upregulation (log2FC < 1 standard deviation of the mean)
Fig. 3
Fig. 3
Protein set enrichment analysis from the “single analysis”. The figure shows the significant FDR-corrected pathways associated with GS clearance in some ROI. The number of ROIs in which the pathway is significant is shown in parenthesis after the pathway name
Fig. 4
Fig. 4
Protein set enrichment analysis with Panther from the “composite analysis”. Pathways with positive (in blue) or negative (in orange) enrichment score in the GS clearance efficiency proteomic dataset
Fig. 5
Fig. 5
ROC curves for the proteomic ROI-specific (black lines) and demographic (red lines) models. A ROC curves for the aMCI prediction and B ROC curves for the aMCI/AD( +) prediction
See this image and copyright information in PMC

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