Unbiased CSF Proteomics in Patients With Idiopathic Normal Pressure Hydrocephalus to Identify Molecular Signatures and Candidate Biomarkers.

Abstract

Background and objectives: Idiopathic normal pressure hydrocephalus (iNPH) is a reversible neurologic disorder that remains poorly understood. Accurate differential diagnosis of iNPH and Alzheimer disease (AD) is complicated by overlapping clinical manifestations. Beyond neuroimaging, there are currently no biomarkers available for iNPH leading to frequent misdiagnosis, and proteomic studies into iNPH have been limited by low sample sizes and inadequate analytical depth. In this study, we report the results of a large-scale proteomic analysis of CSF from patients with iNPH to elucidate pathogenesis and identify potential disease biomarkers.

Methods: CSF samples were collected through lumbar puncture during diagnostic visits to the Mass General Brigham neurology clinic. Samples were analyzed using mass spectrometry. Differential expression of proteins was studied using linear regression models. Results were integrated with publicly available single-nucleus transcriptomic data to explore potential cellular origins. Biological process enrichment was analyzed using gene-set enrichment analyses. To identify potential diagnostic biomarkers, decision tree-based machine learning algorithms were applied.

Results: Participants were classified as cognitively unimpaired (N = 53, mean age: 66.5 years, 58.5% female), AD (N = 124, mean age: 71.2 years, 46.0% female), or iNPH (N = 44, mean age: 74.6 years, 34.1% female) based on clinical diagnosis and AD biomarker status. Gene Ontology analyses indicated upregulation of the immune system and coagulation processes and downregulation of neuronal signaling processes in iNPH. Differential expression analysis showed a general downregulation of proteins in iNPH. Integration of differentially expressed proteins with transcriptomic data indicated that changes likely originated from neuronal, endothelial, and glial origins. Using machine learning algorithms, a panel of 12 markers with high diagnostic potential for iNPH were identified, which were not all detected using univariate linear regression models. These markers spanned the various molecular processes found to be affected in iNPH, such as LTBP2, neuronal pentraxin receptor (NPTXR), and coagulation factor 5.

Discussion: Leveraging the etiologic insights from a typical neurologic clinical cohort, our results indicate that processes of immune response, coagulation, and neuronal signaling are affected in iNPH. We highlight specific markers of potential diagnostic interest. Together, our findings provide novel insights into the pathophysiology of iNPH and may facilitate improved diagnosis of this poorly understood disorder.