BackgroundNormal Pressure Hydrocephalus (NPH) is a neurological condition where there is enlarged ventricular size with normal opening pressure at lumbar puncture. Etiology is uncertain but it is presumed to occur from an imbalance in the production and/or absorption of cerebrospinal fluid (CSF) leading to expansion of the ventricles. Clinical features include gait dysfunction, cognitive impairments, bladder incontinence. Diagnosis is challenging, given a large overlap in clinical and neuroradiological features and co‐morbidity with other more common diseases of aging, especially Alzheimer’s disease (AD) and Lewy body diseases. CSF amyloid and tau biomarkers can be helpful to identify AD pathology but do not exclude concurrent NPH. Currently, there are no biofluid biomarkers to assist in diagnosis of NPH. Here we describe a proteomic discovery pilot to identify candidate protein biomarkers associated with NPH.Method176 banked CSF samples from the MassGeneral Institute for Neurodegenerative Disease biorepository were separated into three groups: NPH (n=30), AD (n=65), and cognitively unimpaired neurological controls (CU‐N; n=81). Diagnoses were established based on comprehensive chart review and CSF AD biomarkers. For proteomic analysis, samples were prepared in batches and analyzed by LC‐MS/MS on an Orbitrap Fusion using a data‐independent acquisition method with non‐overlapping windows from 400‐1000 m/z. Batches were run sequentially, and raw files were searched per batch using Scaffold‐DIA and a custom data‐dependent generated library.ResultFive proteins present in hemoglobulin (HBD and HBB), immunoglobulins (LV39 and KV105), and fibrinogen (FIBA) were increased in NPH compared to AD (Benjamini‐Hochberg adjusted p‐value pAdj <0.05). CSF erythrocyte counts were undetectable in all but one NPH subjects suggesting that a traumatic LP was not the cause of the increased levels. Two neuron associated proteins (VGF and NPTXR) were detected at lower levels in NPH compared to CU‐N subjects (pAdj<0.0001). Alpha‐1‐antichymotrypsin (AACT), was detected at high concentrations both in NPH and AD compared to CU‐N subjects (pAdj<0.02).ConclusionProteomic analysis in NPH may identify novel pathological processes involved in the disease process and aid in the development of biomarkers in NPH.

BackgroundDiagnosis of Alzheimer’s disease (AD) primarily relies on cognitive assessments combined with imaging and limited fluid biomarkers. These biomarkers do not correlate with cognitive prognosis. Analysis of larger sets of biomarkers could improve diagnosis and prognosis of AD and differentiate between comorbid pathophysiologies, and measure treatment efficacy. Here, we report analysis of a Data‐independent Acquisition (DIA) mass‐spectrometry method used to simultaneously quantify hundreds of proteins in a large‐scale patient cohort. We aim to define markers that are able to stratify and diagnose AD in this clinically complex cohort.MethodSamples from 408 patients spanning various dementia diagnoses were collected from the Massachusetts General Hospital Lumbar Puncture clinic. The patient cohort consisted of ATN‐verified cognitively‐unimpaired (n = 81), mild‐cognitive impairment from AD (n = 116), mild‐cognitive impairment from other causes (n = 78), dementia from AD (n = 65) and dementia from other causes (n = 31). Samples were analyzed on an Orbitrap Fusion using a DIA method and raw files were searched using Scaffold‐DIA.ResultAnalyses of the method’s technical performance showed a median intrabatch CV of 24.7% which decreased to 17.5% after filtering for peptides expressed in 95% of all samples. The mean interbatch CV was 73.7% which reduced to 28.8% after ComBat batch‐correction. After filtering for missing values and selecting only the peptides with a mean intrabatch CV below 25%, our dataset consists of 1761 unique peptide sequences belonging to 516 proteins.To determine the differential abundance of peptides we fit a linear regression model to the data. 572 peptides were found to be differentially abundant across all diagnoses compared to AD (padj < 0.05). 11 of these peptides belonging to 5 proteins (PKM, ALDOA, GUAD, BASP1 and CH3L1) were differentially abundant between AD and all non‐AD diagnoses, suggesting specificity for AD. PKM and ALDOA, are involved in regulation of balance between glycolysis and oxidative phosphorylation, potentially indicating a shift in brain metabolism in AD.ConclusionTechnically robust unbiased mass‐spectrometry can highlight novel AD specific biomarkers which may reflect pathophysiological processes key to AD progression.

Background Alzheimer’s disease (AD) is a complex heterogenous neurodegenerative disorder, characterized by multiple pathophysiologies, including disruptions in brain metabolism. Defining markers for patient stratification across these pathophysiologies is an important step towards personalized treatment of AD. Efficient brain glucose metabolism is essential to sustain neuronal activity, but hypometabolism is consistently observed in AD. The molecular changes underlying these observations remain unclear. Recent studies have indicated dysregulation of several glycolysis markers in AD cerebrospinal fluid and tissue.Methods In this study, unbiased mass spectrometry was used to perform a deep proteomic survey of cerebrospinal fluid (CSF) from a large-scale clinically complex cohort to uncover changes related to impaired glucose metabolism.Results Two glycolytic enzymes, Pyruvate kinase (PKM) and Aldolase A (ALDOA) were found to be specifically upregulated in AD CSF compared to other non-AD groups. Presence of full-length protein of these enzymes in CSF was confirmed through immunoblotting. Levels of tryptic peptides of these enzymes correlated significantly with CSF glucose and CSF lactate in matching CSF samples.Conclusions The results presented here indicate a general dysregulation of glucose metabolism in the brain in AD. We highlight two markers ALDOA and PKM that may act as potential functionally-relevant biomarkers of glucose metabolism dysregulation in AD.