CSF and plasma proteomic insights into the pathophysiology of cerebral small vessel disease and cerebrovascular event risk prediction
Bibliographic record
Abstract
BACKGROUND: Cerebral small vessel disease (cSVD) is the leading vascular contributor to dementia and stroke, with white matter lesions (WML) as the most common manifestation. Despite its prevalence, the underlying pathophysiology remains poorly understood, and reliable plasma biomarkers are lacking. Leveraging multi-omics approach, we aimed to: 1) explore the mechanisms underlying WML progression and cognitive decline, and 2) validate CSF-identified biomarkers in plasma across cSVD manifestations and assess their potential to predict future cerebrovascular events. METHOD: We analyzed 1,388 CSF proteins using Olink in the Swedish BioFINDER-2 cohort (n = 1,670). Differential protein abundance for cSVD manifestations (WML, microbleeds and infarcts) was evaluated using linear models, adjusting for age, sex, average protein levels and intracranial volume, if applicable. We used linear mixed-effects models to identify proteins associated with WML progression and mediation analysis to determine WML-associated DAP contributing to cognitive decline over six years. Plasma proteomics was assessed using SOMAscan7k (n = 1,599) and Olink (n = 694) in BioFINDER-2, with DAP analysis, as previously described, focusing on cSVD-associated proteins identified from CSF. In UK Biobank, we assessed cSVD-associated plasma proteins identified in BioFINDER-2 by examining their association with 5-year risk of cerebrovascular outcomes using Cox proportional hazards models and evaluated their predictive utility with a Random Forest classifier (n = 51,606). RESULT: While many proteins were associated with baseline and WML progression, we identified a subset uniquely associated with WML progression, enriched in microglial and macrophage populations (Figure 1). The link between WML and cognitive decline was partly mediated by neuronal and OPC-associated proteins (Figure 2). Key cSVD-associated proteins in CSF, including MMP7, MMP12, TNFRSF11B and GDF15, were validated in plasma (Figure 3A). Using UK Biobank as a population-based setting (Figure 3B), we identified a subset of cSVD-associated plasma proteins related to the risk of cerebrovascular events (Figure 3C), which significantly improved 5-year risk stratification (Figure 3D), surpassing models based on age, sex, and stroke risk score. CONCLUSION: Our findings reveal proteins linked to WML progression and cognitive decline, advancing the understanding of cSVD pathophysiology. Validation of key proteomic markers in plasma and demonstration of their predictive value for cerebrovascular outcomes highlight their potential for early risk stratification and personalized prevention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".