CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease

INTRODUCTION: We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS: Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N− based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS: Only a few individuals were A+T+Ng−. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng− and A+T+NfL−, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV−, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION: Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. Highlights: In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau

Involvement of the choroid plexus in Alzheimer’s disease pathophysiology: findings from mouse and human proteomic studies

Background: Structural and functional changes of the choroid plexus (ChP) have been reported in Alzheimer’s disease (AD). Nonetheless, the role of the ChP in the pathogenesis of AD remains largely unknown. We aim to unravel the relation between ChP functioning and core AD pathogenesis using a unique proteomic approach in mice and humans. Methods: We used an APP knock-in mouse model, APPNL-G-F, exhibiting amyloid pathology, to study the association between AD brain pathology and protein changes in mouse ChP tissue and CSF using liquid chromatography mass spectrometry. Mouse proteomes were investigated at the age of 7 weeks (n = 5) and 40 weeks (n = 5). Results were compared with previously published human AD CSF proteomic data (n = 496) to identify key proteins and pathways associated with ChP changes in AD. Results: ChP tissue proteome was dysregulated in APPNL-G-F mice relative to wild-type mice at both 7 and 40 weeks. At both ages, ChP tissue proteomic changes were associated with epithelial cells, mitochondria, protein modification, extracellular matrix and lipids. Nonetheless, some ChP tissue proteomic changes were different across the disease trajectory; pathways related to lysosomal function, endocytosis, protein formation, actin and complement were uniquely dysregulated at 7 weeks, while pathways associated with nervous system, immune system, protein degradation and vascular system were uniquely dysregulated at 40 weeks. CSF proteomics in both mice and humans showed similar ChP-related dysregulated pathways. Conclusions: Together, our findings support the hypothesis of ChP dysfunction in AD. These ChP changes were related to amyloid pathology. Therefore, the ChP could become a novel promising therapeutic target for AD

Diagnostic value of cerebrospinal fluid A beta ratios in preclinical Alzheimer's disease

Introduction: In this study of preclinical Alzheimer's disease (AD) we assessed the added diagnostic value of using cerebrospinal fluid (CSF) A beta ratios rather than A beta 42 in isolation for detecting individuals who are positive on amyloid positron emission tomography (PET). Methods: Thirty-eight community-recruited cognitively intact older adults (mean age 73, range 65-80 years) underwent F-18-flutemetamol PET and CSF measurement of A beta 1-42, A beta 1-40, A beta 1-38, and total tau (ttau). F-18-flutemetamol retention was quantified using standardized uptake value ratios in a composite cortical region (SUVRcomp) with reference to cerebellar grey matter. Based on a prior autopsy validation study, the SUVRcomp cut-off was 1.57. Sensitivities, specificities and cut-offs were defined based on receiver operating characteristic analysis with CSF analytes as variables of interest and F-18-flutemetamol positivity as the classifier. We also determined sensitivities and CSF cut-off values at fixed specificities of 90 % and 95 %. Results: Seven out of 38 subjects (18 %) were positive on amyloid PET. A beta 42/ttau, A beta 42/A beta 40, A beta 42/A beta 38, and A beta 42 had the highest accuracy to identify amyloid-positive subjects (area under the curve (AUC) >= 0.908). A beta 40 and A beta 38 had significantly lower discriminative power (AUC = 0.571). When specificity was fixed at 90 % and 95 %, A beta 42/ttau had the highest sensitivity among the different CSF markers (85.71 % and 71.43 %, respectively). Sensitivity of A beta 42 alone was significantly lower under these conditions (57.14 % and 42.86 %, respectively). Conclusion: For the CSF-based definition of preclinical AD, if a high specificity is required, our data support the use of A beta 42/ttau rather than using A beta 42 in isolation

Pyroptosis in Alzheimer's disease: cell type-specific activation in microglia, astrocytes and neurons

The major neuropathological hallmarks of Alzheimer's disease (AD) are amyloid β (Aβ) plaques and neurofibrillary tangles (NFT), accompanied by neuroinflammation and neuronal loss. Increasing evidence is emerging for the activation of the canonical NOD-, LRR- and pyrin domain-containing 3 (NLRP3) inflammasome in AD. However, the mechanisms leading to neuronal loss in AD and the involvement of glial cells in these processes are still not clear. The aim of this study was to investigate the contribution of pyroptosis, a pro-inflammatory mechanism of cell death downstream of the inflammasome, to neurodegeneration in AD. Immunohistochemistry and biochemical analysis of protein levels were performed on human post-mortem brain tissue. We investigated the presence of cleaved gasdermin D (GSDMD), the pyroptosis effector protein, as well as the NLRP3 inflammasome-forming proteins, in the medial temporal lobe of 23 symptomatic AD, 25 pathologically defined preclinical AD (p-preAD) and 21 non-demented control cases. Cleaved GSDMD was detected in microglia, but also in astrocytes and in few pyramidal neurons in the first sector of the cornu ammonis (CA1) of the hippocampus and the temporal cortex of Brodmann area 36. Only microglia expressed all NLRP3 inflammasome-forming proteins (i.e., ASC, NLRP3, caspase-1). Cleaved GSDMD-positive astrocytes and neurons exhibited caspase-8 and non-canonical inflammasome protein caspase-4, respectively, potentially indicating alternative pathways for GSDMD cleavage. Brains of AD patients exhibited increased numbers of cleaved GSDMD-positive cells. Cleaved GSDMD-positive microglia and astrocytes were found in close proximity to Aβ plaques, while cleaved GSDMD-positive neurons were devoid of NFTs. In CA1, NLRP3-positive microglia and cleaved GSDMD-positive neurons were associated with local neuronal loss, indicating a possible contribution of NLRP3 inflammasome and pyroptosis activation to AD-related neurodegeneration. Taken together, our results suggest cell type-specific activation of pyroptosis in AD and extend the current knowledge about the contribution of neuroinflammation to the neurodegenerative process in AD via a direct link to neuron death by pyroptosis

Comparison of ELISA- and SIMOA-based quantification of plasma Aβ ratios for early detection of cerebral amyloidosis

Background: Blood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages. Methods: In this prospective cross-sectional study, we quantified plasma Aβ 1–42/Aβ 1–40 ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ 1–42/Aβ 1–40 to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer’s disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms. Results: ELISA and SIMOA plasma Aβ 1–42/Aβ 1–40 detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72–0.84; SIMOA: AUC 0.79, 95% CI 0.73–0.85), and both increased the performance of a basic demographic model including only age and APOE-ε4 genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ 1–42/Aβ 1–40 correlated similarly with amyloid-PET for both platforms (Spearman ρ = − 0.32, p < 0.0001), yet correlations with CSF Aβ 1–42/t-tau were stronger for ELISA (ρ = 0.41, p = 0.002) than for SIMOA (ρ = 0.29, p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ 1–42 and Aβ 1–40 measured by SIMOA consistently underestimating those measured by ELISA. Conclusions: ELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ 1–42/Aβ 1–40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment. Trial registration: EudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014, https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE)

Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology

BACKGROUND: Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics. METHODS: Individuals were classified based on CSF amyloid beta (Aβ)1-42 (A) and phosphorylated tau (T), as cognitively normal A—T– (CN), MCI A–T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed. RESULTS: A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus. CONCLUSION: The pathophysiology of MCI-SNAP (A–T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD

Cerebrospinal fluid proteomic profiling of individuals with mild cognitive impairment and suspected non-Alzheimer's disease pathophysiology

Background: Suspected non-Alzheimer's disease pathophysiology (SNAP) is a biomarker concept that encompasses individuals with neuronal injury but without amyloidosis. We aim to investigate the pathophysiology of SNAP, defined as abnormal tau without amyloidosis, in individuals with mild cognitive impairment (MCI) by cerebrospinal fluid (CSF) proteomics. Methods: Individuals were classified based on CSF amyloid beta (Aβ)1-42 (A) and phosphorylated tau (T), as cognitively normal A—T– (CN), MCI A–T+ (MCI-SNAP), and MCI A+T+ (MCI-AD). Proteomics analyses, Gene Ontology (GO), brain cell expression, and gene expression analyses in brain regions of interest were performed. Results: A total of 96 proteins were decreased in MCI-SNAP compared to CN and MCI-AD. These proteins were enriched for extracellular matrix (ECM), hemostasis, immune system, protein processing/degradation, lipids, and synapse. Fifty-one percent were enriched for expression in the choroid plexus. Conclusion: The pathophysiology of MCI-SNAP (A–T+) is distinct from that of MCI-AD. Our findings highlight the need for a different treatment in MCI-SNAP compared to MCI-AD