# Serum proteomics reveals biomarkers for diagnosis, stratification, and mechanistic insights into cerebral microbleeds

## TL;DR

This study identifies blood protein biomarkers for detecting and understanding cerebral microbleeds, offering a non-invasive diagnostic tool and insights into their causes.

## Contribution

The study is the first to provide a comprehensive serum proteomic profile of CMBs and identifies novel biomarkers for diagnosis and subtype differentiation.

## Key findings

- 151 serum proteins were found to differ between CMB patients and healthy controls.
- Five proteins (MMP3, EFEMP1, TIMP1, UMOD, UBA52) were identified as candidate biomarkers with strong validation performance.
- Subtype-specific biomarkers (RCN1, NEO1, APLP1) effectively distinguished lobar from deep CMBs with high diagnostic accuracy.

## Abstract

Cerebral microbleeds (CMBs) are small vascular lesions detectable on MRI and are associated with increased stroke risk and cognitive decline. However, imaging-based diagnosis is limited by cost and accessibility. This study aimed to identify serum protein biomarkers for early CMB diagnosis and to elucidate molecular mechanisms underlying CMB subtypes.

We enrolled 43 patients with MRI confirmed CMBs and 38 healthy controls. Serum proteomic profiling used high performance liquid chromatography coupled with tandem mass spectrometry. Differential protein expression and pathway enrichment analyses were performed. Biomarkers were selected using LASSO, support vector machine recursive feature elimination, and random forest algorithms. Validation employed enzyme linked immunosorbent assay (n = 60) and Western blotting (n = 8).

We identified 151 proteins that differed between CMB and control groups. Altered pathways involved inflammation, extracellular matrix remodeling, and lipid metabolism. Five proteins emerged as candidate biomarkers: MMP3, EFEMP1, TIMP1, UMOD, and UBA52. MMP3, EFEMP1, TIMP1, and UMOD showed robust validation performance with AUC values > 0.7, and EFEMP1 positively correlated with CMB burden. Subtype analysis distinguished lobar from deep CMBs, with RCN1, NEO1, and APLP1 effectively discriminating subtypes with AUC values > 0.8. Pathway analysis highlighted MAPK, RAF, and ERK signaling in deep CMBs and IGF signaling in lobar CMBs.

This study presents the first comprehensive serum proteomic landscape of CMBs and identifies novel biomarkers with potential for noninvasive early diagnosis and subtype differentiation, supporting precision medicine approaches for CMB management. IGF and MAPK pathway signatures suggest mechanistic links between CMB subtypes and neurovascular aging.