Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer's disease

CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease

In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers.

Bridging the gap: Multi-omics profiling of brain tissue in Alzheimer's disease and older controls in multi-ethnic populations

INTRODUCTION

Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD.

METHODS

To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors.

RESULTS

We generated multi-omics data and curated and harmonized phenotypic data from BA (n = 306), LA (n = 326), or BA and LA (n = 4) brain donors plus non-Hispanic White (n = 252) and other (n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures.

DISCUSSION

The inclusion of traditionally underrepresented groups in multi-omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.

HIGHLIGHTS

Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi-ethnic populations. Brain multi-omics data is generated from Black American, Latin American, and non-Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.

Proteomic changes in Alzheimer's disease associated with progressive Aβ plaque and tau tangle pathologies

Proteomics can shed light on the dynamic and multifaceted alterations in neurodegenerative disorders like Alzheimer's disease (AD). Combining radioligands measuring β-amyloid (Aβ) plaques and tau tangles with cerebrospinal fluid proteomics, we uncover molecular events mirroring different stages of AD pathology in living humans. We found 127 differentially abundant proteins (DAPs) across the AD spectrum. The strongest Aβ-related proteins were mainly expressed in glial cells and included SMOC1 and ITGAM. A dozen proteins linked to ATP metabolism and preferentially expressed in neurons were independently associated with tau tangle load and tau accumulation. Only 20% of the DAPs were also altered in other neurodegenerative diseases, underscoring AD's distinct proteome. Two co-expression modules related, respectively, to protein metabolism and microglial immune response encompassed most DAPs, with opposing, staggered trajectories along the AD continuum. We unveil protein signatures associated with Aβ and tau proteinopathy in vivo, offering insights into complex neural responses and potential biomarkers and therapeutics targeting different disease stages.

Integrative proteomics identifies a conserved Aβ amyloid responsome, novel plaque proteins, and pathology modifiers in Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder that develops over decades. AD brain proteomics reveals vast alterations in protein levels and numerous altered biologic pathways. Here, we compare AD brain proteome and network changes with the brain proteomes of amyloid β (Aβ)-depositing mice to identify conserved and divergent protein networks with the conserved networks identifying an Aβ amyloid responsome. Proteins in the most conserved network (M42) accumulate in plaques, cerebrovascular amyloid (CAA), and/or dystrophic neuronal processes, and overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), increases the accumulation of Aβ in plaques and CAA. M42 proteins bind amyloid fibrils in vitro, and MDK and PTN co-accumulate with cardiac transthyretin amyloid. M42 proteins appear intimately linked to amyloid deposition and can regulate amyloid deposition, suggesting that they are pathology modifiers and thus putative therapeutic targets. We posit that amyloid-scaffolded accumulation of numerous M42+ proteins is a central mechanism mediating downstream pathophysiology in AD.

15 Years of Longitudinal Genetic, Clinical, Cognitive, Imaging, and Biochemical Measures in DIAN

This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimer's disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.

Modeling late-onset Alzheimer's disease neuropathology via direct neuronal reprogramming

Late-onset Alzheimer's disease (LOAD) is the most common form of Alzheimer's disease (AD). However, modeling sporadic LOAD that endogenously captures hallmark neuronal pathologies such as amyloid-β (Aβ) deposition, tau tangles, and neuronal loss remains an unmet need. We demonstrate that neurons generated by microRNA (miRNA)-based direct reprogramming of fibroblasts from individuals affected by autosomal dominant AD (ADAD) and LOAD in a three-dimensional environment effectively recapitulate key neuropathological features of AD. Reprogrammed LOAD neurons exhibit Aβ-dependent neurodegeneration, and treatment with β- or γ-secretase inhibitors before (but not subsequent to) Aβ deposit formation mitigated neuronal death. Moreover inhibiting age-associated retrotransposable elements in LOAD neurons reduced both Aβ deposition and neurodegeneration. Our study underscores the efficacy of modeling late-onset neuropathology of LOAD through high-efficiency miRNA-based neuronal reprogramming.

Ubiquitin-Proteasome System in the Different Stages of Dominantly Inherited Alzheimer's Disease

This study explored the role of the ubiquitin-proteasome system (UPS) in dominantly inherited Alzheimer's disease (DIAD) by examining changes in cerebrospinal fluid (CSF) levels of UPS proteins along with disease progression, AD imaging biomarkers (PiB PET, tau PET), neurodegeneration imaging measures (MRI, FDG PET), and Clinical Dementia Rating® (CDR®). Using the SOMAscan assay, we detected subtle increases in specific ubiquitin enzymes associated with proteostasis in mutation carriers (MCs) up to two decades before the estimated symptom onset. This was followed by more pronounced elevations of UPS-activating enzymes, including E2 and E3 proteins, and ubiquitin-related modifiers. Our findings also demonstrated consistent correlations between UPS proteins and CSF biomarkers such as Aβ42/40 ratio, total tau, various phosphorylated tau species to total tau ratios (ptau181/T181, ptauT205/T205, ptauS202/S202, ptauT217/T217), and MTBR-tau243, alongside Neurofilament light chain (NfL) and the CDR®. Notably, a positive association was observed with imaging markers (PiB PET, tau PET) and a negative correlation with markers of neurodegeneration (FDG PET, MRI), highlighting a significant link between UPS dysregulation and neurodegenerative processes. The correlations suggest that the increase in multiple UPS proteins with rising tau levels and tau-tangle associated markers, indicating a potential role for the UPS in relation to misfolded tau/neurofibrillary tangles (NFTs) and symptom onset. These findings indicate that elevated CSF UPS proteins in DIAD MCs could serve as early indicators of disease progression and suggest a link between UPS dysregulation and amyloid plaque, tau tangles formation, implicating the UPS as a potential therapeutic target in AD pathogenesis.

Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center

The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

Blood-Based Proteomics for Adult-Onset Focal Dystonias

OBJECTIVES

The adult-onset focal dystonias are characterized by over-active muscles leading to abnormal movements. For most cases, the etiology and pathogenesis remain unknown. In the current study, unbiased proteomics methods were used to identify potential changes in blood plasma proteins.

METHODS

A large-scale unbiased proteomics screen was used to compare proteins (N = 6,345) in blood plasma of normal healthy controls (N = 49) with adult-onset focal dystonia (N = 143) consisting of specific subpopulations of cervical dystonia (N = 45), laryngeal dystonia (N = 49), and blepharospasm (N = 49). Pathway analyses were conducted to identify relevant biological pathways. Finally, protein changes were used to build a prediction model for dystonia.

RESULTS

After correction for multiple comparisons, 15 proteins were associated with adult-onset focal dystonia. Subgroup analyses revealed some proteins were shared across the dystonia subgroups while others were unique to 1 subgroup. The top biological pathways involved changes in the immune system, metal ion transport, and reactive oxygen species. A 4-protein model showed high accuracy in discriminating control individuals from dystonia cases [average area under the curve (AUC) = 0.89].

INTERPRETATION

These studies provide novel insights into the etiopathogenesis of dystonia, as well as novel potential biomarkers. ANN NEUROL 2024;96:110-120.

Proteomic analysis of Alzheimer's disease cerebrospinal fluid reveals alterations associated with APOE ε4 and atomoxetine treatment

Alzheimer's disease (AD) is currently defined by the aggregation of amyloid-β (Aβ) and tau proteins in the brain. Although biofluid biomarkers are available to measure Aβ and tau pathology, few markers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here, we characterized the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals using two different proteomic technologies-tandem mass tag mass spectrometry and SomaScan. Integration of both data types allowed for generation of a robust protein coexpression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen-associated protein kinase signaling, neddylation, and mitochondrial biology and overlapped with a previously described lipoprotein module in serum. Alterations of all three modules in blood were associated with dementia more than 20 years before diagnosis. Analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Clustering of individuals based on their CSF proteomic profiles revealed heterogeneity of pathological changes not fully reflected by Aβ and tau.

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Bridging the Gap: Multi-Omics Profiling of Brain Tissue in Alzheimer's Disease and Older Controls in Multi-Ethnic Populations

INTRODUCTION

Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD.

METHODS

To bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors.

RESULTS

We generated multi-omics data and curated and harmonized phenotypic data from AA (n=306), LA (n=326), or AA and LA (n=4) brain donors plus Non-Hispanic White (n=252) and other (n=20) ethnic groups, to establish a foundational dataset enriched for AA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures.

DISCUSSION

Inclusion of traditionally underrepresented groups in multi-omics studies is essential to discover the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.

The selfish network: how the brain preserves behavioral function through shifts in neuronal network state

Neuronal networks possess the ability to regulate their activity states in response to disruptions. How and when neuronal networks turn from physiological into pathological states, leading to the manifestation of neuropsychiatric disorders, remains largely unknown. Here, we propose that neuronal networks intrinsically maintain network stability even at the cost of neuronal loss. Despite the new stable state being potentially maladaptive, neural networks may not reverse back to states associated with better long-term outcomes. These maladaptive states are often associated with hyperactive neurons, marking the starting point for activity-dependent neurodegeneration. Transitions between network states may occur rapidly, and in discrete steps rather than continuously, particularly in neurodegenerative disorders. The self-stabilizing, metastable, and noncontinuous characteristics of these network states can be mathematically described as attractors. Maladaptive attractors may represent a distinct pathophysiological entity that could serve as a target for new therapies and for fostering resilience.

Heparin-enriched plasma proteome is significantly altered in Alzheimer's Disease

Introduction

Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to β-amyloid (Aβ) and tau pathology in Alzheimer's disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches.

Methods

We employed heparin affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to capture and enrich HBPs in plasma obtained from AD (n=62) and control (n=47) samples. These profiles were then correlated to a consensus AD brain proteome, as well as with Aβ, tau and phosphorylated tau (pTau) CSF biomarkers from the same individuals. We then leveraged published human postmortem brain proteome datasets to assess the overlap with the heparin-enriched plasma proteome.

Results

Heparin-enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundance proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude were detectable. Utilizing a consensus AD brain protein co-expression network, we observed that specific plasma HBPs exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes highlighting the complex interplay between the two compartments. Elevated HBPs in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate within Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and APOE. Additionally, heparin enriched plasma proteins demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau from the same individuals.

Conclusion

These findings support the utility of a heparin-affinity approach for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease

Changes in Amyloid-β (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).

Diagnostic and progression biomarkers in cerebrospinal fluid of Alzheimer's disease patients

In this commentary, we address a paper published by Johnson et al. by assessing the robustness of their method to discover diagnostic biomarkers in Alzheimer's disease (AD). In addition, we examine how these newly discovered and previously discovered biomarkers, can play a role in assisting patients with AD and those at risk for developing AD, with an emphasis on the translational hurdles that accompany such discoveries.

Alzheimer's polygenic risk scores are associated with cognitive phenotypes in Down syndrome

INTRODUCTION

This study aimed to investigate the influence of the overall Alzheimer's disease (AD) genetic architecture on Down syndrome (DS) status, cognitive measures, and cerebrospinal fluid (CSF) biomarkers.

METHODS

AD polygenic risk scores (PRS) were tested for association with DS-related traits.

RESULTS

The AD risk PRS was associated with disease status in several cohorts of sporadic late- and early-onset and familial late-onset AD, but not in familial early-onset AD or DS. On the other hand, lower DS Mental Status Examination memory scores were associated with higher PRS, independent of intellectual disability and APOE (PRS including APOE, PRSAPOE , p = 2.84 × 10-4 ; PRS excluding APOE, PRSnonAPOE , p = 1.60 × 10-2 ). PRSAPOE exhibited significant associations with Aβ42, tTau, pTau, and Aβ42/40 ratio in DS.

DISCUSSION

These data indicate that the AD genetic architecture influences cognitive and CSF phenotypes in DS adults, supporting common pathways that influence memory decline in both traits.

HIGHLIGHTS

Examination of the polygenic risk of AD in DS presented here is the first of its kind. AD PRS influences memory aspects in DS individuals, independently of APOE genotype. These results point to an overlap between the genes and pathways that leads to AD and those that influence dementia and memory decline in the DS population. APOE ε4 is linked to DS cognitive decline, expanding cognitive insights in adults.

Clonal CD8 T Cells Accumulate in the Leptomeninges and Communicate with Microglia in Human Neurodegeneration

Murine studies have highlighted a crucial role for immune cells in the meninges in surveilling the central nervous system (CNS) and influencing neuroinflammation. However, how meningeal immunity is altered in human neurodegeneration and its effects on CNS inflammation is understudied. We performed the first single-cell analysis of the transcriptomes and T cell receptor (TCR) repertoire of 104,635 immune cells from 55 postmortem human brain and leptomeningeal tissues from donors with neurodegenerative diseases including amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease. RNA and TCR sequencing from paired leptomeninges and brain allowed us to perform lineage tracing to identify the spatial trajectory of clonal T cells in the CNS and its borders. We propose that T cells activated in the brain emigrate to and establish residency in the leptomeninges where they likely contribute to impairments in lymphatic drainage and remotely to CNS inflammation by producing IFNγ and other cytokines. We identified regulatory networks local to the meninges including NK cell-mediated CD8 T cell killing which likely help to control meningeal inflammation. Collectively, these findings provide not only a foundation for future studies into brain border immune surveillance but also highlight important intercellular dynamics that could be leveraged to modulate neuroinflammation.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways

Background

To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies.

Methods

We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models.

Findings

We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89).

Interpretation

Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs.

Funding

Proteomic data generation was supported by NIH: RF1AG044546.

Aβ Amyloid Scaffolds the Accumulation of Matrisome and Additional Proteins in Alzheimer's Disease

We report a highly significant correlation in brain proteome changes between Alzheimers disease (AD) and CRND8 APP695NL/F transgenic mice. However, integrating protein changes observed in the CRND8 mice with co-expression networks derived from human AD, reveals both conserved and divergent module changes. For the most highly conserved module (M42, matrisome) we find many proteins accumulate in plaques, cerebrovascular amyloid (CAA), dystrophic processes, or a combination thereof. Overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), in CRND8 mice brains leads to increased accumulation of A β ; in plaques and in CAA; further, recombinant MDK and PTN enhance A β ; aggregation into amyloid. Multiple M42 proteins, annotated as heparan sulfate binding proteins, bind to fibrillar A β 42 and a non-human amyloid fibril in vitro. Supporting this binding data, MDK and PTN co-accumulate with transthyretin (TTR) amyloid in the heart and islet amyloid polypeptide (IAPP) amyloid in the pancreas. Our findings establish several critical insights. Proteomic changes in modules observed in human AD brains define an A β ; amyloid responsome that is well conserved from mouse model to human. Further, distinct amyloid structures may serve as scaffolds, facilitating the co-accumulation of proteins with signaling functions. We hypothesize that this co-accumulation may contribute to downstream pathological sequalae. Overall, this contextualized understanding of proteomic changes and their interplay with amyloid deposition provides valuable insights into the complexity of AD pathogenesis and potential biomarkers and therapeutic targets.

Proteomic Network Analysis of Alzheimer's Disease Cerebrospinal Fluid Reveals Alterations Associated with APOE ε4 Genotype and Atomoxetine Treatment

Alzheimer's disease (AD) is currently defined at the research level by the aggregation of amyloid-β (Aβ) and tau proteins in brain. While biofluid biomarkers are available to measure Aβ and tau pathology, few biomarkers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here we describe the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals as assessed by two different proteomic technologies-tandem mass tag (TMT) mass spectrometry and SomaScan. Harmonization and integration of both data types allowed for generation of a robust protein co-expression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen associated protein kinase (MAPK) signaling, neddylation, and mitochondrial biology, and overlapped with a previously described lipoprotein module in serum. Neddylation and oxidant detoxification/MAPK signaling modules had a negative association with APOE ε4 whereas the mitochondrion module had a positive association with APOE ε4. The directions of association were consistent between CSF and blood in two independent longitudinal cohorts, and altered levels of all three modules in blood were associated with dementia over 20 years prior to diagnosis. Dual-proteomic platform analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Individuals who had more severe glycolytic changes at baseline responded better to ATX. Clustering of individuals based on their CSF proteomic network profiles revealed ten groups that did not cleanly stratify by Aβ and tau status, underscoring the heterogeneity of pathological changes not fully reflected by Aβ and tau. AD biofluid proteomics holds promise for the development of biomarkers that reflect diverse pathologies for use in clinical trials and precision medicine.

Clonal CD8 T cells in the leptomeninges are locally controlled and influence microglia in human neurodegeneration

Recent murine studies have highlighted a crucial role for the meninges in surveilling the central nervous system (CNS) and influencing CNS inflammation. However, how meningeal immunity is altered in human neurodegeneration and its potential effects on neuroinflammation is understudied. In the present study, we performed single-cell analysis of the transcriptomes and T cell receptor repertoire of 72,576 immune cells from 36 postmortem human brain and leptomeninges tissues from donors with neurodegenerative diseases including amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease. We identified the meninges as an important site of antigen presentation and CD8 T cell activation and clonal expansion and found that T cell activation in the meninges is a requirement for infiltration into the CNS. We further found that natural killer cells have the potential to negatively regulate T cell activation locally in the meninges through direct killing and are one of many regulatory mechanisms that work to control excessive neuroinflammation.