A Novel Test to Diagnose Normal Pressure Hydrocephalus (NPH) and Predict Shunt Surgery
Overview
Normal pressure hydrocephalus (NPH) is a progressive neurological disorder characterized by the accumulation of cerebrospinal fluid (CSF) in the brain. NPH has devasting impacts on patient quality of life, including progressive neurodegeneration, locomotor dysfunction, urinary incontinence and cognitive decline. Unlike other neurodegenerative diseases, NPH can be effectively treated through surgical intervention in which a shunt is placed in the brain to drain excess CSF. Because this surgery is associated with serious postoperative risks such as shunt infection, there is an urgent need to accurately diagnose NPH cases among other neurological disorders and identify patients whose symptoms will improve with surgery. The disclosed method outlines the identification of novel RNA biomarkers for NPH and their application in predicting gait, urinary and cognitive symptom improvement after surgery.
Market Opportunity
Reliable diagnoses and effective therapies for neurodegenerative disease remain largely unavailable. NPH is a type of neurodegenerative disorder which impacts 20 million people worldwide. Further, it is estimated that NPH accounts for 5-10% of all dementia cases. The ability to accurately differentiate NPH from other diseases, however, remains challenging as NPH symptoms overlap with other neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease. Moreover, core biomarkers associated with neurodegeneration and inflammation, such as amyloid-b, tau proteins, IL-6, IL-8 and TNFa have limited predictive value for shunt surgery outcomes. Current diagnostic tests that have been developed to inform NPH surgical intervention are focused on stimulating CSF drainage (i.e. high volume CSF tap testing or lumbar drainage) and monitoring patient symptoms. Thus, there is a critical need for an objective, quantitative diagnostic test which will identify NPH in patients and predict benefit from shunt surgery.
Innovation and Meaningful Advantages
The disclosed technology has been developed by combining robust scientific methods in neurosurgery, molecular biology and machine learning while driven to translatable discovery using patient samples and advanced analyses. In this work, CSF fluid, which has been robustly shown to fluctuate its composition based on neurogenerative pathological state, was collected from NPH patients during the placement of a ventriculoperitoneal shunt. Transcriptomic profiling was performed on these samples to identify genes and pathways that are differentially expressed in NPH patients with urinary incontinence and cognitive impairment prior to surgery as well has changes in the transcriptomic landscape that occur in patients with improved symptoms after shunt surgery. From this, a machine learning model was developed which can be used to determine if a patient would benefit from surgical intervention based on their baseline transcriptomic profile. In this way, the technology not only provides novel biomarkers for NPH diagnosis but also improves patient care through informing clinical decision making and identifies novel therapeutic targets for neurological disorders beyond NPH. The multi-disciplinary research team working on this technology was formed from a successful Zimmerman Innovation Award in Brain Science and the project is now further supported by the Carney Institute of Brain Science at Brown University.
Collaboration Opportunity
We are interested in exploring research collaborations
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