ArticleJournal of advanced research2026
Proteomic profiling in cerebrospinal fluid reveal biomarkers for shunt outcome in idiopathic normal-pressure hydrocephalus.
Article in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Decoding the CSF Proteomic Signature of Idiopathic Normal Pressure Hydrocephalus: A Systematic Review.Molecules (Basel, Switzerland) · 2026Pooled it
- Multi-omics and high-spatial-resolution omics: deciphering complexity in neurological disorders.GigaScience · 2025Pooled it
- Cerebrospinal fluid and plasma biomarkers in idiopathic normal pressure hydrocephalus: comparison with Alzheimer's and Parkinson's diseases.Frontiers in aging neuroscience · 2026Article
- Cerebrospinal fluid proteomics identifies calcyphosine and follistatin-like 1 as exploratory candidate proteins of interest in hydrocephalus.Frontiers in neurologyArticle
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Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe pathophysiology of idiopathic normal pressure hydrocephalus (iNPH) remains unclear, and the treatment strategy remains suboptimal. This study aims to identify biomarkers for shunt prognosis by cerebrospinal fluid (CSF) proteomic profiling.
methodsCSF samples collected from 37 iNPH patients from the discovery cohort and 12 iNPH patients from an independent validation cohort (71.9 ± 6.1 years (mean ± SD)), and 16 age-balanced controls (69.9 ± 7.6 years (mean ± SD)) were collected from September 2020 to December 2023. 53 CSF samples were analyzed using a mass spectrometry-based proteomic workflow. Clinical evaluations were performed on all iNPH patients, and 44 patients underwent ventriculoperitoneal shunting. Postoperative CSF were also collected from 10 iNPH patients who underwent shunting surgery. Bioinformatics, machine learning, and enzyme-linked immunosorbent assay (ELISA) were performed to identify CSF proteome changes related to pathophysiology in iNPH, and screen for biomarkers associated with shunt response.
results39 and 285 proteins significantly increased and decreased in iNPH CSF compared to the control group. Gene ontology analysis revealed that the noticeably increased proteins were mainly associated with myeloid leukocyte migration and extracellular matrix organization, and significantly decreased proteins were primarily associated with axon development and synapse organization. Machine learning identified 6 candidate biomarkers that potentially predicted the response to shunt surgery. Among these, QPCT levels were found to be elevated in non-responders, while RBP4 levels were decreased, and both of these changes were validated through ELISA.
conclusionsOur findings provide support for the hypothesis that the pathophysiology of iNPH is characterized by a state of neuroinflammation, extracellular matrix remodeling, and neurodegeneration, and CSF shunting can reverse such pathological state. Machine learning using preoperative proteomic profiles satisfactorily predicted the clinical outcome of the shunt procedure in iNPH. Future research targeting specific proteins in iNPH may be warranted to better comprehend the disease mechanism and design patient-tailored treatments.
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