Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics

Rationale and design of the ABOARD project (A Personalized Medicine Approach for Alzheimer's Disease)

The key to stopping Alzheimer's disease (AD) lies in the pre-dementia stages, with the goal to stop AD before dementia has started. We present the rationale and design of the ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) project, which aims to invest in personalized medicine for AD. ABOARD is a Dutch public-private partnership of 32 partners, connecting stakeholders from a scientific, clinical, and societal perspective. The 5-year project is structured into five work packages on (1) diagnosis, (2) prediction, (3) prevention, (4) patient-orchestrated care, and (5) communication and dissemination. ABOARD functions as a network organization in which professionals interact cross-sectorally. ABOARD has a strong junior training program "Juniors On Board." Project results are shared with society through multiple communication resources. By including relevant partners and involving citizens at risk, patients, and their care partners, ABOARD builds toward a future with personalized medicine for AD.

Highlights

ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) is a public-private research project executed by 32 partners that functions as a network organization.Together, the project partners build toward a future with personalized medicine for Alzheimer's disease.Although ABOARD is a Dutch consortium, it has international relevance.ABOARD improves diagnosis, prediction, prevention, and patient-orchestrated care.

TMT proteomics analysis of cerebrospinal fluid from patients with cerebral venous sinus thrombosis

CVST is a type of venous stroke that mainly affects young adults with no reliable diagnostic markers and effective treatment strategies for secondary pathologies. However, the underlying pathological molecular mechanisms remain unclear. Here, we systematically analyzed the molecule profiling of the cerebrospinal fluid (CSF) in CVST patients via tandem mass tag (TMT)-based proteomics for the first time, aiming to reveal the pathogenesis and provide evidence for the diagnosis and treatment of CVST. Five CVST patients and five control patients were selected, and CSF samples were analyzed by TMT proteomics. Differentially expressed proteins (DEPs) were acquired and bioinformatics analysis was performed. Besides, parallel reaction monitoring (PRM) was utilized to validate the DEPs. 468 differentially expressed proteins were screened, 185 of which were up-regulated and 283 were down-regulated (fold change >1.2, P < 0.05). Bioinformatics analysis displayed that these proteins were significantly enriched in multiple pathways related to a variety of pathophysiological processes. PRM verification showed that apolipoprotein E, MMP-2, neuroserpin, clusterin, and several other molecules were down-regulated. These identified proteins reveal unique pathophysiological characteristics secondary to CVST. Further characterization of these proteins in future research could enable their application as potential therapeutic targets and biomarkers in CVST therapy. SIGNIFICANCE: Cerebral venous sinus thrombosis (CVST) is an underrated and potentially fatal cause of stroke with a reported mortality of 5-10% worldwide. Currently, in addition to anticoagulant and thrombolytic therapy, effective treatments targeting the injured brain parenchyma after CVST remain limited. Besides, accurate diagnostic markers are still sorely lacking. In the present study, we will detect the alterations of the CSF protein spectrum of CVST patients by TMT technique, screen differentially expressed proteins, analyze the functions of these signals through bioinformatics methods, and finally validate the key molecules through parallel reaction monitoring (PRM) technique. Collectively, the study aimed to offer a reference for the discovery of specific protein/pathway alterations in the CSF of CVST patients and further reveal the underlying pathogenesis, thereby providing evidence for the diagnosis and treatment of CVST.

Transferability of Alzheimer's disease progression subtypes to an independent population cohort

In the past, methods to subtype or biotype patients using brain imaging data have been developed. However, it is unclear whether and how these trained machine learning models can be successfully applied to population cohorts to study the genetic and lifestyle factors underpinning these subtypes. This work, using the Subtype and Stage Inference (SuStaIn) algorithm, examines the generalisability of data-driven Alzheimer's disease (AD) progression models. We first compared SuStaIn models trained separately on Alzheimer's disease neuroimaging initiative (ADNI) data and an AD-at-risk population constructed from the UK Biobank dataset. We further applied data harmonization techniques to remove cohort effects. Next, we built SuStaIn models on the harmonized datasets, which were then used to subtype and stage subjects in the other harmonized dataset. The first key finding is that three consistent atrophy subtypes were found in both datasets, which match the previously identified subtype progression patterns in AD: 'typical', 'cortical' and 'subcortical'. Next, the subtype agreement was further supported by high consistency in individuals' subtypes and stage assignment based on the different models: more than 92% of the subjects, with reliable subtype assignment in both ADNI and UK Biobank dataset, were assigned to an identical subtype under the model built on the different datasets. The successful transferability of AD atrophy progression subtypes across cohorts capturing different phases of disease development enabled further investigations of associations between AD atrophy subtypes and risk factors. Our study showed that (1) the average age is highest in the typical subtype and lowest in the subcortical subtype; (2) the typical subtype is associated with statistically more-AD-like cerebrospinal fluid biomarkers values in comparison to the other two subtypes; and (3) in comparison to the subcortical subtype, the cortical subtype subjects are more likely to associate with prescription of cholesterol and high blood pressure medications. In summary, we presented cross-cohort consistent recovery of AD atrophy subtypes, showing how the same subtypes arise even in cohorts capturing substantially different disease phases. Our study opened opportunities for future detailed investigations of atrophy subtypes with a broad range of early risk factors, which will potentially lead to a better understanding of the disease aetiology and the role of lifestyle and behaviour on AD.

Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies

Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.

Sixteen-Year Longitudinal Evaluation of Blood-Based DNA Methylation Biomarkers for Early Prediction of Alzheimer's Disease

BACKGROUND

DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, has shown promise for Alzheimer's disease (AD) prediction.

OBJECTIVE

Testing long-term predictive ability (>15 years) of existing DNAm-based epigenetic age acceleration (EAA) measures and identifying novel early blood-based DNAm AD-prediction biomarkers.

METHODS

EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models (LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16 years before clinical onset, and post-onset follow-up. Novel DNAm biomarkers were generated with epigenome-wide LMMs, and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10-16 years), and post-AD-onset time-points.

RESULTS

EAA did not differentiate cases from controls during the follow-up time (p > 0.05). Three new DNA biomarkers showed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions (p-values: 0.022-<0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146 cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOEɛ4-carriership (OR = 1.38 per 1 SD DNAm score increase versus OR = 13.58 for ɛ4-allele carriage; AUCs = 77.2% versus 87.0%). Literature review showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with our identified CpGs.

Treatment of Alzheimer's disease by combination of acupuncture and Chinese medicine based on pathophysiological mechanism: A review

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by neurodegeneration, nerve loss, neurofibrillary tangles, and Aβ plaques. In modern medical science, there has been a serious obstacle to the effective treatment of AD. At present, there is no clinically proven and effective western medicine treatment for AD. The reason is that the etiology of AD is not yet fully understood. In 2018, the international community put forward a purely biological definition of AD, but soon this view of biomarkers was widely questioned, because the so-called AD biomarkers are shared with other neurological diseases, the diagnostic accuracy is low, and they face various challenges in the process of clinical diagnosis and treatment. Nowadays, scholars increasingly regard AD as the result of multimechanism and multicenter interaction. Because there is no exact Western medicine treatment for AD, the times call for the comprehensive treatment of AD in traditional Chinese medicine (TCM). AD belongs to the category of "dull disease" in TCM. For thousands of years, TCM has accumulated a lot of relevant treatment experience in the process of diagnosis and treatment. TCM, acupuncture, and the combination of acupuncture and medicine all play an important role in the treatment of AD. Based on the research progress of modern medicine on the pathophysiology of AD, this paper discusses the treatment of this disease with the combination of acupuncture and medicine.

Data and sample sharing as an enabler for large-scale biomarker research and development: The EPND perspective

Biomarker discovery, development, and validation are reliant on large-scale analyses of high-quality samples and data. Currently, significant quantities of data and samples have been generated by European studies on Alzheimer's disease (AD) and other neurodegenerative diseases (NDD), representing a valuable resource for developing biomarkers to support early detection of disease, treatment monitoring, and patient stratification. However, discovery of, access to, and sharing of data and samples from AD and NDD research are hindered both by silos that limit collaboration, and by the array of complex requirements for secure, legal, and ethical sharing. In this Perspective article, we examine key challenges currently hampering large-scale biomarker research, and outline how the European Platform for Neurodegenerative Diseases (EPND) plans to address them. The first such challenge is a fragmented landscape filled with technical barriers that make it difficult to discover and access high-quality samples and data in one location. A second challenge is related to the complex array of legal and ethical requirements that must be navigated by researchers when sharing data and samples, to ensure compliance with data protection regulations and research ethics. Another challenge is the lack of broad-scale collaboration and opportunities to facilitate partnerships between data and sample contributors and researchers, in addition to a lack of regulatory engagement early in the research process to enable validation of potential biomarkers. A further challenge facing projects is the need to remain sustainable beyond initial funding periods, ensuring data and samples are shared and reused, thereby driving further research and innovation. In addressing these challenges, EPND will enable an environment of faster and more disruptive research on diagnostics and disease-modifying therapies for Alzheimer's disease and other neurodegenerative diseases.

β-Synuclein as a candidate blood biomarker for synaptic degeneration in Alzheimer's disease

Synaptic degeneration is an early event closely associated with the course of Alzheimer's disease (AD). The identification of synaptic blood biomarkers is, therefore, of great interest and clinical relevance. The levels of most synaptic proteins are increased in the cerebrospinal fluid (CSF) of patients with AD, but their detection in blood is hitherto either unavailable or not very informative. This paradigm is related to their low concentration, their peripheral origin, or the presence of highly abundant blood proteins that hinder detection. In recent years, significant progress has been made in detecting the presynaptic protein β-synuclein. This mini-review summarizes the results that highlight the role of β-synuclein as a candidate blood marker for synaptic degeneration in AD.

Omics-based biomarkers discovery for Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorders presenting with the pathological hallmarks of amyloid plaques and tau tangles. Over the past few years, great efforts have been made to explore reliable biomarkers of AD. High-throughput omics are a technology driven by multiple levels of unbiased data to detect the complex etiology of AD, and it provides us with new opportunities to better understand the pathophysiology of AD and thereby identify potential biomarkers. Through revealing the interaction networks between different molecular levels, the ultimate goal of multi-omics is to improve the diagnosis and treatment of AD. In this review, based on the current AD pathology and the current status of AD diagnostic biomarkers, we summarize how genomics, transcriptomics, proteomics and metabolomics are all conducing to the discovery of reliable AD biomarkers that could be developed and used in clinical AD management.

The Innovative Medicines Initiative neurodegeneration portfolio: From individual projects to collaborative networks

The IMI public-private partnership between the European Commission and the European Federation of Pharmaceutical Industries and Associations (EFPIA) was launched in 2008 with an initial budget of €2 billion. Aiming to accelerate the development of innovative medicines for areas of unmet clinical need, the IMI has committed over €380 million to projects on neurodegenerative disorders (NDD), catalyzing public-private collaborations at scale and at all stages of the R&D pipeline. Because of this vast investment, research on neurodegenerative diseases has made enormous strides in recent decades. The challenge for the future however remains to utilize this newly found knowledge and generated assets to develop better tools and novel therapeutic strategies. Here, we report the results of an integrated programme analysis of the IMI NDD portfolio, performed by the Neuronet Coordination and Support Action. Neuronet was launched by the IMI in 2019 to boost synergies and collaboration between projects in the IMI NDD portfolio, to increase the impact and visibility of research, and to facilitate interactions with related initiatives worldwide. Our analysis assessed the characteristics, structure and assets of the project portfolio and identifies lessons from projects spanning preclinical research to applied clinical studies and beyond. Evaluation of project parameters and network analyses of project partners revealed a complex web of 236 partnering organizations, with EFPIA partners often acting as connecting nodes across projects, and with a great diversity of academic institutions. Organizations in the UK, Germany, France and the Netherlands were highly represented in the portfolio, which has a strong focus on clinical research in Alzheimer's and Parkinson's disease in particular. Based on surveys and unstructured interviews with NDD research leaders, we identified actions to enhance collaboration between project partners, by improving the structure and definition of in-kind contributions; reducing administrative burdens; and enhancing the exploitation of outcomes from research investments by EU taxpayers and EFPIA. These recommendations could help increase the efficiency and impact of future public-private partnerships on neurodegeneration.

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers

Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.

Differential impairment of cerebrospinal fluid synaptic biomarkers in the genetic forms of frontotemporal dementia

BACKGROUND

Approximately a third of frontotemporal dementia (FTD) is genetic with mutations in three genes accounting for most of the inheritance: C9orf72, GRN, and MAPT. Impaired synaptic health is a common mechanism in all three genetic variants, so developing fluid biomarkers of this process could be useful as a readout of cellular dysfunction within therapeutic trials.

METHODS

A total of 193 cerebrospinal fluid (CSF) samples from the GENetic FTD Initiative including 77 presymptomatic (31 C9orf72, 23 GRN, 23 MAPT) and 55 symptomatic (26 C9orf72, 17 GRN, 12 MAPT) mutation carriers as well as 61 mutation-negative controls were measured using a microflow LC PRM-MS set-up targeting 15 synaptic proteins: AP-2 complex subunit beta, complexin-2, beta-synuclein, gamma-synuclein, 14-3-3 proteins (eta, epsilon, zeta/delta), neurogranin, Rab GDP dissociation inhibitor alpha (Rab GDI alpha), syntaxin-1B, syntaxin-7, phosphatidylethanolamine-binding protein 1 (PEBP-1), neuronal pentraxin receptor (NPTXR), neuronal pentraxin 1 (NPTX1), and neuronal pentraxin 2 (NPTX2). Mutation carrier groups were compared to each other and to controls using a bootstrapped linear regression model, adjusting for age and sex.

RESULTS

CSF levels of eight proteins were increased only in symptomatic MAPT mutation carriers (compared with controls) and not in symptomatic C9orf72 or GRN mutation carriers: beta-synuclein, gamma-synuclein, 14-3-3-eta, neurogranin, Rab GDI alpha, syntaxin-1B, syntaxin-7, and PEBP-1, with three other proteins increased in MAPT mutation carriers compared with the other genetic groups (AP-2 complex subunit beta, complexin-2, and 14-3-3 zeta/delta). In contrast, CSF NPTX1 and NPTX2 levels were affected in all three genetic groups (decreased compared with controls), with NPTXR concentrations being affected in C9orf72 and GRN mutation carriers only (decreased compared with controls). No changes were seen in the CSF levels of these proteins in presymptomatic mutation carriers. Concentrations of the neuronal pentraxins were correlated with brain volumes in the presymptomatic period for the C9orf72 and GRN groups, suggesting that they become abnormal in proximity to symptom onset.

CONCLUSIONS

Differential synaptic impairment is seen in the genetic forms of FTD, with abnormalities in multiple measures in those with MAPT mutations, but only changes in neuronal pentraxins within the GRN and C9orf72 mutation groups. Such markers may be useful in future trials as measures of synaptic dysfunction, but further work is needed to understand how these markers change throughout the course of the disease.

Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer's disease

Understanding Alzheimer's disease (AD) heterogeneity is important for understanding the underlying pathophysiological mechanisms of AD. However, AD atrophy subtypes may reflect different disease stages or biologically distinct subtypes. Here we use longitudinal magnetic resonance imaging data (891 participants with AD dementia, 305 healthy control participants) from four international cohorts, and longitudinal clustering to estimate differential atrophy trajectories from the age of clinical disease onset. Our findings (in amyloid-β positive AD patients) show five distinct longitudinal patterns of atrophy with different demographical and cognitive characteristics. Some previously reported atrophy subtypes may reflect disease stages rather than distinct subtypes. The heterogeneity in atrophy rates and cognitive decline within the five longitudinal atrophy patterns, potentially expresses a complex combination of protective/risk factors and concomitant non-AD pathologies. By alternating between the cross-sectional and longitudinal understanding of AD subtypes these analyses may allow better understanding of disease heterogeneity.

Increased CSF-decorin predicts brain pathological changes driven by Alzheimer's Aβ amyloidosis

Cerebrospinal fluid (CSF) biomarkers play an important role in diagnosing Alzheimer's disease (AD) which is characterized by amyloid-β (Aβ) amyloidosis. Here, we used two App knock-in mouse models, App^NL-F/NL-F and App^{NL-G-F/NL-G-F}, exhibiting AD-like Aβ pathology to analyze how the brain pathologies translate to CSF proteomes by label-free mass spectrometry (MS). This identified several extracellular matrix (ECM) proteins as significantly altered in App knock-in mice. Next, we compared mouse CSF proteomes with previously reported human CSF MS results acquired from patients across the AD spectrum. Intriguingly, the ECM protein decorin was similarly and significantly increased in both App^NL-F/NL-F and App^{NL-G-F/NL-G-F} mice, strikingly already at three months of age in the App^NL-F/NL-F mice and preclinical AD subjects having abnormal CSF-Aβ42 but normal cognition. Notably, in this group of subjects, CSF-decorin levels positively correlated with CSF-Aβ42 levels indicating that the change in CSF-decorin is associated with early Aβ amyloidosis. Importantly, receiver operating characteristic analysis revealed that CSF-decorin can predict a specific AD subtype having innate immune activation and potential choroid plexus dysfunction in the brain. Consistently, in App^NL-F/NL-F mice, increased CSF-decorin correlated with both Aβ plaque load and with decorin levels in choroid plexus. In addition, a low concentration of human Aβ42 induces decorin secretion from mouse primary neurons. Interestingly, we finally identify decorin to activate neuronal autophagy through enhancing lysosomal function. Altogether, the increased CSF-decorin levels occurring at an early stage of Aβ amyloidosis in the brain may reflect pathological changes in choroid plexus, present in a subtype of AD subjects.

Four Distinct Subtypes of Alzheimer's Disease Based on Resting-State Connectivity Biomarkers

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder with significant heterogeneity. Different AD phenotypes may be associated with specific brain network changes. Uncovering disease heterogeneity by using functional networks could provide insights into precise diagnoses.

METHODS

We investigated the subtypes of AD using nonnegative matrix factorization clustering on the previously identified 216 resting-state functional connectivities that differed between AD and normal control subjects. We conducted the analysis using a discovery dataset (n = 809) and a validated dataset (n = 291). Next, we grouped individuals with mild cognitive impairment according to the model obtained in the AD groups. Finally, the clinical measures and brain structural characteristics were compared among the subtypes to assess their relationship with differences in the functional network.

RESULTS

Individuals with AD were clustered into 4 subtypes reproducibly, which included those with 1) diffuse and mild functional connectivity disruption (subtype 1), 2) predominantly decreased connectivity in the default mode network accompanied by an increase in the prefrontal circuit (subtype 2), 3) predominantly decreased connectivity in the anterior cingulate cortex accompanied by an increase in prefrontal cortex connectivity (subtype 3), and 4) predominantly decreased connectivity in the basal ganglia accompanied by an increase in prefrontal cortex connectivity (subtype 4). In addition to these differences in functional connectivity, differences between the AD subtypes were found in cognition, structural measures, and cognitive decline patterns.

CONCLUSIONS

These comprehensive results offer new insights that may advance precision medicine for AD and facilitate strategies for future clinical trials.

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.

Signatures of glial activity can be detected in the CSF proteome

SignificanceSingle-cell transcriptomics has revealed specific glial activation states associated with the pathogenesis of neurodegenerative diseases, such as Alzheimer's and Parkinson's disease (AD and PD). What is still needed are clinically relevant biomarkers for deciphering such glial states in AD and PD patients. To this end, we applied proteome analysis in cerebrospinal fluid (CSF) of mouse models of AD and PD pathology. This allowed us to identify a panel of glial CSF proteins that largely match the transcriptomic changes. The identified proteins can also be quantified in human CSF and show changes in AD patients, supporting their relevance as biomarker candidates to stage glial activation in patients with neurodegenerative diseases.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09354-0.

Effects of age, amyloid, sex, and APOE ε4 on the CSF proteome in normal cognition

Introduction

It is important to understand which biological processes change with aging, and how such changes are associated with increased Alzheimer's disease (AD) risk. We studied how cerebrospinal fluid (CSF) proteomics changed with age and tested if associations depended on amyloid status, sex, and apolipoprotein E Ɛ4 genotype.

Methods

We included 277 cognitively intact individuals aged 46 to 89 years from Alzheimer's Disease Neuroimaging Initiative, European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery, and Metabolic Syndrome in Men. In total, 1149 proteins were measured with liquid chromatography mass spectrometry with multiple reaction monitoring/Rules-Based Medicine, tandem mass tag mass spectrometry, and SOMAscan. We tested associations between age and protein levels in linear models and tested enrichment for Reactome pathways.

Results

Levels of 252 proteins increased with age independently of amyloid status. These proteins were associated with immune and signaling processes. Levels of 21 proteins decreased with older age exclusively in amyloid abnormal participants and these were enriched for extracellular matrix organization.

Discussion

We found amyloid-independent and -dependent CSF proteome changes with older age, perhaps representing physiological aging and early AD pathology.

Biomarker A+T-: is this Alzheimer's disease or not? A combined CSF and pathology study

The biological definition of Alzheimer's disease using CSF biomarkers requires abnormal levels of both amyloid (A) and tau (T). However, biomarkers and corresponding cutoffs may not always reflect the presence or absence of pathology. Previous studies suggest that up to 32% of individuals with autopsy-confirmed Alzheimer's disease show normal CSF p-tau levels in vivo, but these studies are sparse and had small sample sizes. Therefore, in three independent autopsy cohorts, we studied whether or not CSF A+T- excluded Alzheimer's disease based on autopsy. We included 215 individuals, for whom ante-mortem CSF collection and autopsy had been performed, from three cohorts: (i) the Amsterdam Dementia Cohort (ADC) [n = 80, 37 (46%) Alzheimer's disease at autopsy, time between CSF collection and death 4.5 ± 2.9 years]; (ii) the Antwerp Dementia Cohort (DEM) [n = 92, 84 (91%) Alzheimer's disease at autopsy, time CSF collection to death 1.7 ± 2.3 years]; and (iii) the Alzheimer's Disease Neuroimaging Initiative (ADNI) [n = 43, 31 (72%) Alzheimer's disease at autopsy, time CSF collection to death 5.1 ± 2.5 years]. Biomarker profiles were based on dichotomized CSF Aβ1-42 and p-tau levels. The accuracy of CSF AT profiles to detect autopsy-confirmed Alzheimer's disease was assessed. Lastly, we investigated whether the concordance of AT profiles with autopsy diagnosis improved when CSF was collected closer to death in 9 (10%) DEM and 30 (70%) ADNI individuals with repeated CSF measurements available. In total, 50-73% of A+T- individuals and 100% of A+T+ individuals had Alzheimer's disease at autopsy. Amyloid status showed the highest accuracy to detect autopsy-confirmed Alzheimer's disease (accuracy, sensitivity and specificity in the ADC: 88%, 92% and 84%; in the DEM: 87%, 94% and 12%; and in the ADNI cohort: 86%, 90% and 75%, respectively). The addition of CSF p-tau did not further improve these estimates. We observed no differences in demographics or degree of Alzheimer's disease neuropathology between A+T- and A+T+ individuals with autopsy-confirmed Alzheimer's disease. All individuals with repeated CSF measurements remained stable in Aβ1-42 status during follow-up. None of the Alzheimer's disease individuals with a normal p-tau status changed to abnormal; however, four (44%) DEM individuals and two (7%) ADNI individuals changed from abnormal to normal p-tau status over time, and all had Alzheimer's disease at autopsy. In summary, we found that up to 73% of A+T- individuals had Alzheimer's disease at autopsy. This should be taken into account in both research and clinical settings.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

Tauopathies: new perspectives and challenges

BACKGROUND

Tauopathies are a class of neurodegenerative disorders characterized by neuronal and/or glial tau-positive inclusions.

MAIN BODY

Clinically, tauopathies can present with a range of phenotypes that include cognitive/behavioral-disorders, movement disorders, language disorders and non-specific amnestic symptoms in advanced age. Pathologically, tauopathies can be classified based on the predominant tau isoforms that are present in the inclusion bodies (i.e., 3R, 4R or equal 3R:4R ratio). Imaging, cerebrospinal fluid (CSF) and blood-based tau biomarkers have the potential to be used as a routine diagnostic strategy and in the evaluation of patients with tauopathies. As tauopathies are strongly linked neuropathologically and genetically to tau protein abnormalities, there is a growing interest in pursuing of tau-directed therapeutics for the disorders. Here we synthesize emerging lessons on tauopathies from clinical, pathological, genetic, and experimental studies toward a unified concept of these disorders that may accelerate the therapeutics.

CONCLUSIONS

Since tauopathies are still untreatable diseases, efforts have been made to depict clinical and pathological characteristics, identify biomarkers, elucidate underlying pathogenesis to achieve early diagnosis and develop disease-modifying therapies.

Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.

METHODS

We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.

RESULTS

Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.

DISCUSSION

ADNI has had a profound impact in improving clinical trials for AD.

Cerebrospinal fluid tau levels are associated with abnormal neuronal plasticity markers in Alzheimer's disease

Background

Increased total tau (t-tau) in cerebrospinal fluid (CSF) is a key characteristic of Alzheimer’s disease (AD) and is considered to result from neurodegeneration. T-tau levels, however, can be increased in very early disease stages, when neurodegeneration is limited, and can be normal in advanced disease stages. This suggests that t-tau levels may be driven by other mechanisms as well. Because tau pathophysiology is emerging as treatment target for AD, we aimed to clarify molecular processes associated with CSF t-tau levels.

Methods

We performed a proteomic, genomic, and imaging study in 1380 individuals with AD, in the preclinical, prodromal, and mild dementia stage, and 380 controls from the Alzheimer’s Disease Neuroimaging Initiative and EMIF-AD Multimodality Biomarker Discovery study.

Results

We found that, relative to controls, AD individuals with increased t-tau had increased CSF concentrations of over 400 proteins enriched for neuronal plasticity processes. In contrast, AD individuals with normal t-tau had decreased levels of these plasticity proteins and showed increased concentrations of proteins indicative of blood–brain barrier and blood-CSF barrier dysfunction, relative to controls. The distinct proteomic profiles were already present in the preclinical AD stage and persisted in prodromal and dementia stages implying that they reflect disease traits rather than disease states. Dysregulated plasticity proteins were associated with SUZ12 and REST signaling, suggesting aberrant gene repression. GWAS analyses contrasting AD individuals with and without increased t-tau highlighted several genes involved in the regulation of gene expression. Targeted analyses of SNP rs9877502 in GMNC, associated with t-tau levels previously, correlated in individuals with AD with CSF concentrations of 591 plasticity associated proteins. The number of APOE-e4 alleles, however, was not associated with the concentration of plasticity related proteins.

Conclusions

CSF t-tau levels in AD are associated with altered levels of proteins involved in neuronal plasticity and blood–brain and blood-CSF barrier dysfunction. Future trials may need to stratify on CSF t-tau status, as AD individuals with increased t-tau and normal t-tau are likely to respond differently to treatment, given their opposite CSF proteomic profiles.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13024-022-00521-3.

Advances in Proteomic and Metabolomic Profiling of Neurodegenerative Diseases

Proteomics and metabolomics are two emerging fields that hold promise to shine light on the molecular mechanisms causing neurodegenerative diseases. Research in this area may reveal and quantify specific metabolites and proteins that can be targeted by therapeutic interventions intended at halting or reversing the neurodegenerative process. This review aims at providing a general overview on the current status of proteomic and metabolomic profiling in neurodegenerative diseases. We focus on the most common neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. We discuss the relevance of state-of-the-art metabolomics and proteomics approaches and their potential for biomarker discovery. We critically review advancements made so far, highlighting how metabolomics and proteomics may have a significant impact in future therapeutic and biomarker development. Finally, we further outline technologies used so far as well as challenges and limitations, placing the current information in a future-facing context.

Temporal Subtyping of Alzheimer's Disease Using Medical Conditions Preceding Alzheimer's Disease Onset in Electronic Health Records

Subtyping of Alzheimer's disease (AD) can facilitate diagnosis, treatment, prognosis and disease management. It can also support the testing of new prevention and treatment strategies through clinical trials. In this study, we employed spectral clustering to cluster 29,922 AD patients in the OneFlorida Data Trust using their longitudinal EHR data of diagnosis and conditions into four subtypes. These subtypes exhibit different patterns of progression of other conditions prior to the first AD diagnosis. In addition, according to the results of various statistical tests, these subtypes are also significantly different with respect to demographics, mortality, and prescription medications after the AD diagnosis. This study could potentially facilitate early detection and personalized treatment of AD as well as data-driven generalizability assessment of clinical trials for AD.

Microglia in Alzheimer's Disease: a Key Player in the Transition Between Homeostasis and Pathogenesis

Immune activation accompanies the development of proteinopathy in the brains of Alzheimer's dementia patients. Evolving from the long-held viewpoint that immune activation triggers the pathological trajectory in Alzheimer's disease, there is accumulating evidence now that microglial activation is neither pro-amyloidogenic nor just a simple reactive process to the proteinopathy. Preclinical studies highlight an interesting aspect of immunity, i.e., spurring immune system activity may be beneficial under certain circumstances. Indeed, a dynamic evolving relationship between different activation states of the immune system and its neuronal neighbors is thought to regulate overall brain organ health in both healthy aging and progression of Alzheimer's dementia. A new premise evolving from genome, transcriptome, and proteome data is that there might be at least two major phases of immune activation that accompany the pathological trajectory in Alzheimer's disease. Though activation on a chronic scale will certainly lead to neurodegeneration, this emerging knowledge of a potential beneficial aspect of immune activation allows us to form holistic insights into when, where, and how much immune system activity would need to be tuned to impact the Alzheimer's neurodegenerative cascade. Even with the trove of recently emerging -omics data from patients and preclinical models, how microglial phenotypes are functionally related to the transition of a healthy aging brain towards progressive degenerative state remains unknown. A deeper understanding of the synergism between microglial functional states and brain organ health could help us discover newer interventions and therapies that enable us to address the current paucity of disease-modifying therapies in Alzheimer's disease.

Dense core vesicle markers in CSF and cortical tissues of patients with Alzheimer's disease

Background

New fluid biomarkers for Alzheimer's disease (AD) that reveal synaptic and neural network dysfunctions are needed for clinical practice and therapeutic trial design. Dense core vesicle (DCV) cargos are promising cerebrospinal fluid (CSF) indicators of synaptic failure in AD patients. However, their value as biomarkers has not yet been determined.

Methods

Immunoassays were performed to analyze the secretory proteins prohormone convertases PC1/3 and PC2, carboxypeptidase E (CPE), secretogranins SgIII and SgII, and Cystatin C in the cerebral cortex (n = 45, provided by Bellvitge University Hospital) and CSF samples (n = 66, provided by The Sant Pau Initiative on Neurodegeneration cohort) from AD patients (n = 56) and age-matched controls (n = 55).

Results

In AD tissues, most DCV proteins were aberrantly accumulated in dystrophic neurites and activated astrocytes, whereas PC1/3, PC2 and CPE were also specifically accumulated in hippocampal granulovacuolar degeneration bodies. AD individuals displayed an overall decline of secretory proteins in the CSF. Interestingly, in AD patients, the CSF levels of prohormone convertases strongly correlated inversely with those of neurodegeneration markers and directly with cognitive impairment status.

Conclusions

These results demonstrate marked alterations of neuronal-specific prohormone convertases in CSF and cortical tissues of AD patients. The neuronal DCV cargos are biomarker candidates for synaptic dysfunction and neurodegeneration in AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40035-021-00263-0.

Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer's disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in "amyloidome" (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

CSF Proteomic Alzheimer's Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals

We recently discovered three distinct pathophysiological subtypes in Alzheimer’s disease (AD) using cerebrospinal fluid (CSF) proteomics: one with neuronal hyperplasticity, a second with innate immune system activation, and a third subtype with blood–brain barrier dysfunction. It remains unclear whether AD proteomic subtype profiles are a consequence of amyloid aggregation, or might exist upstream from aggregated amyloid. We studied this question in 127 older individuals with intact cognition and normal AD biomarkers in two independent cohorts (EMIF-AD MBD and ADNI). We clustered 705 proteins measured in CSF that were previously related to AD. We identified in these cognitively intact individuals without AD pathology three subtypes: two subtypes were seen in both cohorts (n = 49 with neuronal hyperplasticity and n = 44 with blood–brain barrier dysfunction), and one only in ADNI (n = 12 with innate immune activation). The proteins specific for these subtypes strongly overlapped with AD subtype protein profiles (overlap coefficients 92%–71%). Longitudinal p₁₈₁-tau and amyloid β 1–42 (Aβ42) CSF analysis showed that in the hyperplasticity subtype p₁₈₁-tau increased (β = 2.6 pg/mL per year, p = 0.01) and Aβ42 decreased over time (β = −4.4 pg/mL per year, p = 0.03), in the innate immune activation subtype p₁₈₁-tau increased (β = 3.1 pg/mL per year, p = 0.01) while in the blood–brain barrier dysfunction subtype Aβ42 decreased (β = −3.7 pg/mL per year, p = 0.009). These findings suggest that AD proteomic subtypes might already manifest in cognitively normal individuals and may predispose for AD before amyloid has reached abnormal levels.

Proteomic correlates of cortical thickness in cognitively normal individuals with normal and abnormal cerebrospinal fluid beta-amyloid1-42

Cortical atrophy is an early feature of Alzheimer´s disease (AD). The biological processes associated with variability in cortical thickness remain largely unknown. We studied 220 cerebrospinal fluid (CSF) proteins to evaluate biological pathways associated with cortical thickness in 34 brain regions in 79 cognitively normal older individuals with normal (>192 ng/L, n = 47), and abnormal (≤192 ng/L, n = 32) CSF beta-amyloid_1-42 (Aβ₄₂). Interactions for Aβ₄₂ status were tested. Panther GeneOntology and Cytoscape ClueGO analyses were used to evaluate biological processes associated with regional cortical thickness. 170 (77.3 %) proteins related with cortical thickness in at least 1 brain region across the total group, and 171 (77.7 %) proteins showed Aβ₄₂ specific associations. Higher levels of proteins related to axonal and synaptic integrity, amyloid accumulation, and inflammation were associated with thinner cortex in lateral temporal regions, the rostral anterior cingulum, the lateral occipital cortex and the pars opercularis only in the abnormal Aβ₄₂ group. Alterations in CSF proteomics are associated with a regional cortical atrophy in the earliest stages of AD.

Bayes analysis supports null hypothesis of anti-amyloid beta therapy in Alzheimer's disease

Numerous clinical trials of anti-amyloid beta (Aβ) immunotherapy in Alzheimer's disease have been performed. None of these have provided convincing evidence for beneficial effects. Using traditional frequentist meta-analysis, the conclusion is that there is absence of evidence for a therapeutic effect, with a point estimate effect size of 0.05 (95% confidence interval -0.00 to 0.10, P = .055). In addition, this non-significant effect equates to 0.4 points per year on the cognitive subscale of the Alzheimer's Disease Assessment Scale. This is well below the minimally clinically important difference. Bayesian meta-analysis of these trial data provides strong evidence of absence of a therapeutic effect, with a Bayes factor of 11.27 in favor of the null hypothesis, opposed to a Bayes factor of 0.09 in favor of a treatment effect. Bayesian analysis is particularly valuable in this context of repeatedly reported small, non-significant effect sizes in individual trials. Mechanisms other than removal of Aβ from the brain may be probed to slow progression of Alzheimer's disease.

Cerebrospinal fluid biomarker panel for synaptic dysfunction in Alzheimer's disease

INTRODUCTION

Synaptic dysfunction and degeneration is one of the earliest events in Alzheimer's disease (AD) and the best correlate of cognitive decline. Thus, identification and validation of biomarkers reflecting synaptic degeneration to be used as prognostic biomarkers are greatly needed.

METHOD

Solid-phase extraction and parallel reaction monitoring mass spectrometry were used to quantify 17 synaptic proteins in CSF, in two cross-sectional studies including AD (n = 52) and controls (n = 37).

RESULTS

Increased concentrations of beta-synuclein, gamma-synuclein, neurogranin, phosphatidylethanolamine-binding protein 1, and 14-3-3 proteins were observed in AD patients compared to controls, while neuronal pentraxin-2 and neuronal pentraxin receptor were decreased.

DISCUSSION

We have established a method with a novel panel of synaptic proteins as biomarkers of synaptic dysfunction. The results indicate that several of the proteins included in the panel may serve as synaptic biomarkers for AD.