Next-generation proteomics technologies in Alzheimer's disease: from clinical research to routine diagnostics.

INTRODUCTION: Clinical proteomics studies of Alzheimer's disease (AD) research aim to identify biomarkers useful for clinical research, diagnostics, and improve our understanding of the pathological processes involved in the disease. The rapidly increasing performance of proteomics technologies is likely to have great impact on AD research. AREAS COVERED: We review recent proteomics approaches that have advanced the field of clinical AD research. Specifically, we discuss the application of targeted mass spectrometry (MS), labeling-based and label-free MS-based as well as affinity-based proteomics to AD biomarker development, underpinning their importance with the latest impactful clinical studies. We evaluate how proteomics technologies have been adapted to meet current challenges. Finally, we discuss the limitations and potential of proteomics techniques and whether their scope might extend beyond current research-based applications. EXPERT OPINION: To date, proteomics technologies in the AD field have been largely limited to AD biomarker discovery. The recent development of the first successful disease-modifying treatments of AD will further increase the need for blood biomarkers for early, accurate diagnosis, and CSF biomarkers that reflect specific pathological processes. Proteomics has the potential to meet these requirements and to progress into clinical routine practice, provided that current limitations are overcome.

Novel cerebrospinal fluid biomarkers correlating with shunt responsiveness in patients with idiopathic normal pressure hydrocephalus.

BACKGROUND: Idiopathic Normal pressure hydrocephalus (iNPH) is a form of adult hydrocephalus that is clinically characterized by progressive gait impairment, cognitive dysfunction, and urinary incontinence. The current standard method of treatment involves surgical installation of a CSF diversion shunt. However, only a fraction of patients shows an alleviation of symptoms from shunt surgery. Thus, the purpose of this prospective explorative proteomic study was to identify prognostic CSF biomarkers to predict shunt responsiveness in iNPH patients. Further, we evaluated the ability of the core Alzheimer's disease (AD) CSF biomarkers phosphorylated (p)-tau, total (t)-tau, and amyloid-ß 1-42 (Aß1-42) to serve as predictors of shunt response. METHODS: We conducted a tandem mass tag (TMT) proteomic analysis of lumbar CSF from 68 iNPH patients, sampled pre-shunt surgery. Tryptic digests of CSF samples were labelled with TMTpro reagents. The TMT multiplex samples were fractionated in 24 concatenated fractions by reversed-phase chromatography at basic pH and analysed by liquid chromatography coupled to mass spectrometry (LC-MS) on an Orbitrap Lumos mass spectrometer. The relative abundances of the identified proteins were correlated with (i) iNPH grading scale (iNPHGS) and (ii) gait speed change 1 year after surgery from baseline to identify predictors of shunt responsiveness. RESULTS: We identified four CSF biomarker candidates which correlated most strongly with clinical improvement on the iNPHGS and were significantly changed in shunt-responsive compared to shunt-unresponsive iNPH patients 1 year post-surgery: FABP3 (R = - 0.46, log2(fold change (FC)) = - 0.25, p < 0.001), ANXA4 (R = 0.46, log2(FC) = 0.32, p < 0.001), MIF (R = -0.49, log2(FC) = - 0.20, p < 0.001) and B3GAT2 (R = 0.54, log2(FC) = 0.20, p < 0.001). In addition, five biomarker candidates were selected based on their strong correlation with gait speed change 1 year after shunt installation: ITGB1 (R = - 0.48, p < 0.001), YWHAG (R = - 0.41, p < 0.01), OLFM2 (R = 0.39, p < 0.01), TGFBI (R = - 0.38, p < 0.01), and DSG2 (R = 0.37, p < 0.01). Concentrations of the CSF AD core biomarkers did not differ significantly with shunt responsiveness. CONCLUSION: FABP3, MIF, ANXA4, B3GAT2, ITGB1, YWHAG, OLFM2, TGFBI and DSG2 in CSF are promising prognostic biomarker candidates to predict shunt responsiveness in iNPH patients.

SCRN1: A cerebrospinal fluid biomarker correlating with tau in Alzheimer's disease.

INTRODUCTION: Secernin-1 (SCRN1) is a neuronal protein that co-localizes with neurofibrillary tangles in Alzheimer's disease (AD), but not with tau inclusions in corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), or Pick's disease. METHODS: We measured SCRN1 concentration in cerebrospinal fluid (CSF) using a novel mass spectrometric parallel reaction monitoring method in three clinical cohorts comprising patients with neurochemically characterized AD (n = 25) and controls (n = 28), clinically diagnosed Parkinson's disease (PD; n = 38), multiple system atrophy (MSA; n = 31), PSP (n = 20), CBD (n = 8), healthy controls (n = 37), and neuropathology-confirmed AD (n = 47). RESULTS: CSF SCRN1 was significantly increased in AD (P < 0.01, fold change = 1.4) compared to controls (receiver operating characteristic area under the curve = 0.78) but not in CBD, PSP, PD, or MSA. CSF SCRN1 positively correlated with CSF total tau (R = 0.78, P = 1.1 × 10-13 ), phosphorylated tau181 (R = 0.64, P = 3.2 × 10-8 ), and Braak stage and negatively correlated with Mini-Mental State Examination score. DISCUSSION: CSF SCRN1 is a candidate biomarker of AD, reflecting tau pathology. HIGHLIGHTS: We developed a parallel reaction monitoring assay to measure secernin-1 (SCRN1) in cerebrospinal fluid (CSF). CSF SCRN1 was increased in Alzheimer's disease compared to healthy controls. CSF SCRN1 remained unchanged in Parkinson's disease, multiple system atrophy, progressive supranuclear palsy, or corticobasal degeneration compared to controls. CSF SCRN1 correlated strongly with CSF phosphorylated tau and total tau. CSF SCRN1 increased across Braak stages and negatively correlated with Mini-Mental State Examination score.

Optimized sample preparation and data analysis for TMT proteomic analysis of cerebrospinal fluid applied to the identification of Alzheimer's disease biomarkers.

BACKGROUND: Cerebrospinal fluid (CSF) is an important biofluid for biomarkers of neurodegenerative diseases such as Alzheimer's disease (AD). By employing tandem mass tag (TMT) proteomics, thousands of proteins can be quantified simultaneously in large cohorts, making it a powerful tool for biomarker discovery. However, TMT proteomics in CSF is associated with analytical challenges regarding sample preparation and data processing. In this study we address those challenges ranging from data normalization over sample preparation to sample analysis. METHOD: Using liquid chromatography coupled to mass-spectrometry (LC-MS), we analyzed TMT multiplex samples consisting of either identical or individual CSF samples, evaluated quantification accuracy and tested the performance of different data normalization approaches. We examined MS2 and MS3 acquisition strategies regarding accuracy of quantification and performed a comparative evaluation of filter-assisted sample preparation (FASP) and an in-solution protocol. Finally, four normalization approaches (median, quantile, Total Peptide Amount, TAMPOR) were applied to the previously published European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) dataset. RESULTS: The correlation of measured TMT reporter ratios with spiked-in standard peptide amounts was significantly lower for TMT multiplexes composed of individual CSF samples compared with those composed of aliquots of a single CSF pool, demonstrating that the heterogeneous CSF sample composition influences TMT quantitation. Comparison of TMT reporter normalization methods showed that the correlation could be improved by applying median- and quantile-based normalization. The slope was improved by acquiring data in MS3 mode, albeit at the expense of a 29% decrease in the number of identified proteins. FASP and in-solution sample preparation of CSF samples showed a 73% overlap in identified proteins. Finally, using optimized data normalization, we present a list of 64 biomarker candidates (clinical AD vs. controls, p < 0.01) identified in the EMIF-AD cohort. CONCLUSION: We have evaluated several analytical aspects of TMT proteomics in CSF. The results of our study provide practical guidelines to improve the accuracy of quantification and aid in the design of sample preparation and analytical protocol. The AD biomarker list extracted from the EMIF-AD cohort can provide a valuable basis for future biomarker studies and help elucidate pathogenic mechanisms in AD.