Cerebrospinal fluid transcripts may predict shunt surgery responses in normal pressure hydrocephalus

Author:

Levin Zachary12,Leary Owen P3,Mora Victor12,Kant Shawn3,Brown Sarah3,Svokos Konstantina3,Akbar Umer4,Serre Thomas25,Klinge Petra3,Fleischmann Alexander12ORCID,Ruocco Maria Grazia25

Affiliation:

1. Department of Neuroscience, Brown University , Providence, RI 02912 , USA

2. Carney Institute for Brain Science, Brown University , Providence, RI 02912 , USA

3. Department of Neurosurgery, Rhode Island Hospital, Warren Alpert Medical School, Brown University , Providence, RI 02903 , USA

4. Department of Neurology, Rhode Island Hospital, Warren Alpert Medical School, Brown University , Providence, RI 02903 , USA

5. Department of Cognitive Linguistic and Psychological Sciences, Brown University , Providence, RI 02912 , USA

Abstract

Abstract Molecular biomarkers for neurodegenerative diseases are critical for advancing diagnosis and therapy. Normal pressure hydrocephalus (NPH) is a neurological disorder characterized by progressive neurodegeneration, gait impairment, urinary incontinence and cognitive decline. In contrast to most other neurodegenerative disorders, NPH symptoms can be improved by the placement of a ventricular shunt that drains excess CSF. A major challenge in NPH management is the identification of patients who benefit from shunt surgery. Here, we perform genome-wide RNA sequencing of extracellular vesicles in CSF of 42 NPH patients, and we identify genes and pathways whose expression levels correlate with gait, urinary or cognitive symptom improvement after shunt surgery. We describe a machine learning algorithm trained on these gene expression profiles to predict shunt surgery response with high accuracy. The transcriptomic signatures we identified may have important implications for improving NPH diagnosis and treatment and for understanding disease aetiology.

Funder

Zimmerman Innovation

Carney Institute for Brain Science

Brown University OVPR

Publisher

Oxford University Press (OUP)

Subject

Neurology (clinical)

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