ArticleTranslational stroke research2025
Proteome Profiling of Serum Reveals Pathological Mechanisms and Biomarker Candidates for Cerebral Small Vessel Disease.
Article in Translational stroke research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Cerebral Infarction: Epidemiology, Classification, Mechanisms, Diagnosis, and Management.MedComm · 2026Review
- Vascular and Neural Transcriptomics Reveal Stage-Dependent Pathways to Inflammation and Cognitive Dysfunction in a Rat Model of Hypertension.Journal of the American Heart Association · 2026Article
- Identification of distinct and shared biomarker panels in different manifestations of cerebral small-vessel disease through proteomic profiling.Nature aging · 2026Article
- Serum proteomics reveals biomarkers for diagnosis, stratification, and mechanistic insights into cerebral microbleeds.Frontiers in aging neuroscience · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Cerebral small vessel disease (CSVD) is a global brain disorder that is characterized by a series of clinical, neuroimaging, and neuropathological manifestations. However, the molecular pathophysiological mechanisms of CSVD have not been thoroughly investigated. Liquid chromatography-tandem mass spectrometry-based proteomics has broad application prospects in biomedicine. It is used to elucidate disease-related molecular processes and pathophysiological pathways, thus providing an important opportunity to explore the pathophysiological mechanisms of CSVD. Serum samples were obtained from 96 participants (58 with CSVD and 38 controls) consecutively recruited from The First Affiliated Hospital of Zhengzhou University. After removing high-abundance proteins, the serum samples were analyzed using high-resolution mass spectrometry. Bioinformatics methods were used for in-depth analysis of the obtained proteomic data, and the results were verified experimentally. Compared with the control group, 52 proteins were differentially expressed in the sera of the CSVD group. Furthermore, analyses indicated the involvement of these differentially expressed proteins in CSVD through participation in the overactivation of complement and coagulation cascades and dysregulation of insulin-like growth factor-binding proteins. The proteomic biomarker panel identified by the machine learning model combined with clinical features is expected to facilitate the diagnosis of CSVD (AUC = 0.947, 95% CI = 0.895-0.978). The study is the most in-depth study on CSVD proteomics to date and suggests that the overactivation of the complement cascade and the dysregulation of IGFBP on- IGF may be closely correlated with the occurrence and progression of CSVD, offering the potential to develop peripheral blood biomarkers and providing new insights into the biological basis of CSVD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.