Systems-based proteomics to resolve the biology of Alzheimer's disease beyond amyloid and tau

DECIPHERING THE ROLE OF miRNAs IN ALZHEIMER'S DISEASE: PREDICTIVE TARGETING AND PATHWAY MODULATION - A SYSTEMATIC REVIEW

Alzheimer's Disease (AD), a multifaceted neurodegenerative disorder, is increasingly understood through the regulatory lens of microRNAs (miRNAs). This review comprehensively examines the pivotal roles of miRNAs in AD pathogenesis, shedding light on their influence across various pathways. We delve into the biogenesis and mechanisms of miRNAs, emphasizing their significant roles in brain function and regulation. The review then navigates the complex landscape of AD pathogenesis, identifying key genetic, environmental, and molecular factors, with a focus on hallmark pathological features like amyloid-beta accumulation and tau protein hyperphosphorylation. Central to our discussion is the intricate involvement of miRNAs in these processes, highlighting their altered expression patterns in AD and subsequent functional implications, from amyloid-beta metabolism to tau pathology, neuroinflammation, oxidative stress, and synaptic dysfunction. The predictive analysis of miRNA targets using computational methods, complemented by experimental validations, forms a crucial part of our discourse, unraveling the contributions of specific miRNAs to AD. Moreover, we explore the therapeutic potential of miRNAs as biomarkers and in miRNA-based interventions, while addressing the challenges in translating these findings into clinical practice. This review aims to enhance understanding of miRNAs in AD, offering a foundation for future research directions and novel therapeutic strategies.

Plasma proteomics and lipidomics facilitate elucidation of the link between Alzheimer's disease development and vessel wall fragility

Proximity Extension Assay (PEA) and mass spectrometry (MS) methodologies were utilized for the proteomic and lipidomic characterization of plasma specimens from patients who developed Alzheimer's disease. Proteomics was performed by both PEA and Liquid Chromatography (LC)/MS in this study, but all the more because LC/MS generally tends to be biased towards proteins with high expression and high variability, generating hypotheses proved challenging. Consequently, attempt was made to interpret the results from the PEA data. There were 150 significantly variable proteins and 68 lipids among 1000 proteins and 400 lipids. Pathway analysis was performed for both total and variable proteins measured to reduce bias, and it appeared that vascular fragility was related to AD. Furthermore, a multitude of lipid-associated proteins exhibited statistical changes. In certain instances, the function of individual proteins affected the factors associated with them, whereas others demonstrated trends contrary to anticipated outcomes. These trends seem indicative of diverse feedback mechanisms that provide homeostatic equilibrium. The degree of unsaturation of fatty acids, correlated with cardiovascular risk, warrants specific attention. Certain bile acids exhibited the potential to cause vascular endothelial damage. Contemplating these discoveries in tandem with previously documented phenomena, subtle shifts in homeostatic functions seem to be linked to the fragility of vascular endothelial cells. This is evidenced by the slow and chronic evolution of Alzheimer's disease from preclinical stages to its manifestation.

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.

Network proteomics of the Lewy body dementia brain reveals presynaptic signatures distinct from Alzheimer's disease

Lewy body dementia (LBD), a class of disorders comprising Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer's disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson's disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or "modules" of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Identification of deregulated lncRNAs in Alzheimer's disease: an integrated gene co-expression network analysis of hippocampus and fusiform gyrus RNA-seq datasets

Introduction

The deregulation of lncRNAs expression has been associated with neuronal damage in Alzheimer's disease (AD), but how or whether they can influence its onset is still unknown. We investigated 2 RNA-seq datasets consisting, respectively, of the hippocampal and fusiform gyrus transcriptomic profile of AD patients, matched with non-demented controls.

Methods

We performed a differential expression analysis, a gene correlation network analysis (WGCNA) and a pathway enrichment analysis of two RNA-seq datasets.

Results

We found deregulated lncRNAs in common between hippocampus and fusiform gyrus and deregulated gene groups associated to functional pathways related to neurotransmission and memory consolidation. lncRNAs, co-expressed with known AD-related coding genes, were identified from the prioritized modules of both brain regions.

Discussion

We found common deregulated lncRNAs in the AD hippocampus and fusiform gyrus, that could be considered common signatures of AD pathogenesis, providing an important source of information for understanding the molecular changes of AD.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

INTRODUCTION

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

METHODS

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

RESULTS

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

DISCUSSION

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

HIGHLIGHTS

A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, suggesting that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, suggesting that DEGs exert more impact on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we observe an overall downregulation of astrocyte and microglia modules across all brain regions in AD, indicating a prevailing trend of functional repression in glial cells across these regions. Notable genes from the CALM and HSP90 families emerged as hub genes across neuronal modules in all brain regions, suggesting conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis to comprehensively understand the cell-type-specific roles of genes in AD-related biological processes.

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.

Potential prognostic value of CSF-targeted proteomics across the Alzheimer's disease continuum

BACKGROUND

Core biomarkers for Alzheimer's disease (AD), such as Aβ42 and tau, have demonstrated high prognostic accuracy but do not fully capture the complex pathophysiology of AD. In this study, our objective was to identify novel cerebrospinal fluid (CSF) biomarkers using proteomics across the entire AD continuum to predict conversion to AD and explore their involvement in AD pathogenesis.

METHODS

A cohort of 186 cognitively normal (CN), 127 subjective memory complaint (SMC), 79 early mild cognitive impairment (EMCI), 249 late MCI (LMCI), and 132 AD individuals was analyzed, with a follow-up period of over 3 years for non-AD participants. CSF 65 peptides, as well as hippocampal and entorhinal volumes were analyzed, and cognitive function was evaluated using the 13-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog 13). Cox proportional hazards models and mediation analysis were performed to investigate associations and causal relationships.

RESULTS

During the follow-up, approximately one-fourth (146/580) of the non-AD participants progressed to AD. After adjusting for baseline diagnosis (CN to LMCI) and other variables, multivariable Cox regression analysis identified three peptides (VAELEDEK, VSFELFADK, and VVSSIEQK) as significant predictors of conversion to AD. Incorporating these three peptides into the initial model significantly improved the C-statistic from 0.82 to 0.85 for predicting AD conversion, surpassing the predictive ability of Aβ42 and P-tau. Moreover, hippocampal and entorhinal volumes mediated 30.3-53.8% of the association between the three peptides and ADAS-Cog 13 scores.

CONCLUSIONS

These findings underscore the potential of these three peptides as robust prognostic biomarker candidates for AD conversion across the entire AD continuum, with a mechanism involving the mediation of hippocampal and entorhinal volumes.

Molecular mechanisms implicated in protein changes in the Alzheimer's disease human hippocampus

This study aimed to elucidate the specific biochemical pathways linked to changes in proteins in the Alzheimer's disease (AD) human hippocampus. Our data demonstrate a constant rise in the expression of four proteins (VGF, GFAP, HSPB1, and APP) across all eleven studies. Notably, UBC was the most centrally involved and had increased expression in the hippocampus tissue of individuals with AD. Modified proteins in the hippocampal tissue were found to activate the innate immune system and disrupt communication across chemical synapses. Four hub proteins (CD44, APP, ITGB2, and APOE) are connected to amyloid plaques, whereas two hub proteins (RPL24 and RPS23) are related to neurofibrillary tangles (NFTs). The presence of modified proteins was discovered to trigger the activation of microglia and decrease the functioning of ribosomes and mitochondria in the hippocampus. Three significant microRNAs (hsa-miR-106b-5p, hsa-miR-17-5p, and hsa-miR-16-5p) and transcription factors (MYT1L, PIN1, and CSRNP3) have been discovered to improve our understanding of the alterations in proteins within the hippocampal tissues that lead to the progression of AD. These findings establish a path for possible treatments for AD to employ therapeutic strategies that specifically focus on the proteins or processes linked to the illness.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Subcellular proteomics insights into Alzheimer's disease development

Alzheimer's disease (AD), one of the most common dementias, is a neurodegenerative disease characterized by cognitive impairment and decreased judgment function. The expected number of AD patient is increasing in the context of the world's advancing medical care and increasing human life expectancy. Since current molecular mechanism studies on AD pathogenesis are incomplete, there is no specific and effective therapeutic agent. Mass spectrometry (MS)-based unbiased proteomics studies provide an effective and comprehensive approach. Many advances have been made in the study of the mechanism, diagnostic markers, and drug targets of AD using proteomics. This paper focus on subcellular level studies, reviews studies using proteomics to study AD-associated mitochondrial dysfunction, synaptic, and myelin damage, the protein composition of amyloid plaques (APs) and neurofibrillary tangles (NFTs), changes in tissue extracellular vehicles (EVs) and exosome proteome, and the protein changes in ribosomes and lysosomes. The methods of sample separation and preparation and proteomic analysis as well as the main findings of these studies are involved. The results of these proteomics studies provide insights into the pathogenesis of AD and provide theoretical resource and direction for future research in AD, helping to identify new biomarkers and drugs targets for AD.

Paradigm shift required for translational research on the brain

Biomedical research on the brain has led to many discoveries and developments, such as understanding human consciousness and the mind and overcoming brain diseases. However, historical biomedical research on the brain has unique characteristics that differ from those of conventional biomedical research. For example, there are different scientific interpretations due to the high complexity of the brain and insufficient intercommunication between researchers of different disciplines owing to the limited conceptual and technical overlap of distinct backgrounds. Therefore, the development of biomedical research on the brain has been slower than that in other areas. Brain biomedical research has recently undergone a paradigm shift, and conducting patient-centered, large-scale brain biomedical research has become possible using emerging high-throughput analysis tools. Neuroimaging, multiomics, and artificial intelligence technology are the main drivers of this new approach, foreshadowing dramatic advances in translational research. In addition, emerging interdisciplinary cooperative studies provide insights into how unresolved questions in biomedicine can be addressed. This review presents the in-depth aspects of conventional biomedical research and discusses the future of biomedical research on the brain.

Large-scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

Introduction

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups.

Methods

Dorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS).

Results

As a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals.

Discussion

This comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer's pathology

Dysfunction in fast-spiking parvalbumin interneurons (PV-INs) may represent an early pathophysiological perturbation in Alzheimer's Disease (AD). Defining early proteomic alterations in PV-INs can provide key biological and translationally-relevant insights. We used cell-type-specific in-vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state PV-IN proteomes. PV-IN proteomic signatures include high metabolic and translational activity, with over-representation of AD-risk and cognitive resilience-related proteins. In bulk proteomes, PV-IN proteins were associated with cognitive decline in humans, and with progressive neuropathology in humans and the 5xFAD mouse model of Aβ pathology. PV-IN CIBOP in early stages of Aβ pathology revealed signatures of increased mitochondria and metabolism, synaptic and cytoskeletal disruption and decreased mTOR signaling, not apparent in whole-brain proteomes. Furthermore, we demonstrated pre-synaptic defects in PV-to-excitatory neurotransmission, validating our proteomic findings. Overall, in this study we present native-state proteomes of PV-INs, revealing molecular insights into their unique roles in cognitive resiliency and AD pathogenesis.

Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration

The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.

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.

Cerebral organoids with chromosome 21 trisomy secrete Alzheimer's disease-related soluble aggregates detectable by single-molecule-fluorescence and super-resolution microscopy

Understanding the role of small, soluble aggregates of beta-amyloid (Aβ) and tau in Alzheimer's disease (AD) is of great importance for the rational design of preventative therapies. Here we report a set of methods for the detection, quantification, and characterisation of soluble aggregates in conditioned media of cerebral organoids derived from human iPSCs with trisomy 21, thus containing an extra copy of the amyloid precursor protein (APP) gene. We detected soluble beta-amyloid (Aβ) and tau aggregates secreted by cerebral organoids from both control and the isogenic trisomy 21 (T21) genotype. We developed a novel method to normalise measurements to the number of live neurons within organoid-conditioned media based on glucose consumption. Thus normalised, T21 organoids produced 2.5-fold more Aβ aggregates with a higher proportion of larger (300-2000 nm2) and more fibrillary-shaped aggregates than controls, along with 1.3-fold more soluble phosphorylated tau (pTau) aggregates, increased inflammasome ASC-specks, and a higher level of oxidative stress inducing thioredoxin-interacting protein (TXNIP). Importantly, all this was detectable prior to the appearance of histological amyloid plaques or intraneuronal tau-pathology in organoid slices, demonstrating the feasibility to model the initial pathogenic mechanisms for AD in-vitro using cells from live genetically pre-disposed donors before the onset of clinical disease. Then, using different iPSC clones generated from the same donor at different times in two independent experiments, we tested the reproducibility of findings in organoids. While there were differences in rates of disease progression between the experiments, the disease mechanisms were conserved. Overall, our results show that it is possible to non-invasively follow the development of pathology in organoid models of AD over time, by monitoring changes in the aggregates and proteins in the conditioned media, and open possibilities to study the time-course of the key pathogenic processes taking place.

Cholesterol metabolism: physiological regulation and diseases

Cholesterol homeostasis is crucial for cellular and systemic function. The disorder of cholesterol metabolism not only accelerates the onset of cardiovascular disease (CVD) but is also the fundamental cause of other ailments. The regulation of cholesterol metabolism in the human is an extremely complex process. Due to the dynamic balance between cholesterol synthesis, intake, efflux and storage, cholesterol metabolism generally remains secure. Disruption of any of these links is likely to have adverse effects on the body. At present, increasing evidence suggests that abnormal cholesterol metabolism is closely related to various systemic diseases. However, the exact mechanism by which cholesterol metabolism contributes to disease pathogenesis remains unclear, and there are still unknown factors. In this review, we outline the metabolic process of cholesterol in the human body, especially reverse cholesterol transport (RCT). Then, we discuss separately the impact of abnormal cholesterol metabolism on common diseases and potential therapeutic targets for each disease, including CVD, tumors, neurological diseases, and immune system diseases. At the end of this review, we focus on the effect of cholesterol metabolism on eye diseases. In short, we hope to provide more new ideas for the pathogenesis and treatment of diseases from the perspective of cholesterol.

Network Proteomics of the Lewy Body Dementia Brain Reveals Presynaptic Signatures Distinct from Alzheimer's Disease

Lewy body dementia (LBD), a class of disorders comprising Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer's disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson's disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or "modules" of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Uncovering the Oxidative Stress Mechanisms and Targets in Alzheimer's Disease by Integrating Phenotypic Screening Data and Polypharmacology Networks

Background

The oxidative stress hypothesis is challenging the dominant position of amyloid-β (Aβ) in the field of understanding the mechanisms of Alzheimer's disease (AD), a complicated and untreatable neurodegenerative disease.

Objective

The goal of the present study was to uncover the oxidative stress mechanisms causing AD, as well as the potential therapeutic targets and neuroprotective drugs against oxidative stress mechanisms.

Methods

In this study, a systematic workflow combining pharmacological experiments and computational prediction was proposed. 222 drugs and natural products were collected first and then tested on SH-SY5Y cells to obtain phenotypic screening data on neuroprotection. The preliminary screening data were integrated with drug-target interactions (DTIs) and multi-scale biomedical data, which were analyzed with statistical tests and gene set enrichment analysis. A polypharmacology network was further constructed for investigation.

Results

340 DTIs were matched in multiple databases, and 222 cell viability ratios were calculated for experimental compounds. We identified significant potential therapeutic targets based on oxidative stress mechanisms for AD, including NR3C1, SHBG, ESR1, PGR, and AVPR1A, which might be closely related to neuroprotective effects and pathogenesis. 50% of the top 14 enriched pathways were found to correlate with AD, such as arachidonic acid metabolism and neuroactive ligand-receptor interaction. Several approved drugs in this research were also found to exert neuroprotective effects against oxidative stress mechanisms, including beclometasone, methylprednisolone, and conivaptan.

Conclusion

Our results indicated that NR3C1, SHBG, ESR1, PGR, and AVPR1A were promising therapeutic targets and several drugs may be repurposed from the perspective of oxidative stress and AD.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

Introduction

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

Methods

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

Results

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

Discussion

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

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.

Measures of Aging Biology in Saliva and Blood as Novel Biomarkers for Stroke and Heart Disease in Older Adults

BACKGROUND AND OBJECTIVES

The role of aging biology as a novel risk factor and biomarker for vascular outcomes in different accessible body tissues such as saliva and blood remain unclear. We aimed to (1) assess the role of aging biology as a risk factor of stroke and heart disease among individuals of same chronologic age and sex and (2) compare aging biology biomarkers measured in different accessible body tissues as novel biomarkers for stroke and heart disease in older adults.

METHODS

This study included individuals who consented for blood and saliva draw in the Venous Blood Substudy and Telomere Length Study of the Health and Retirement Study (HRS). The HRS is a population-based, nationally representative longitudinal survey of individuals aged 50 years and older in the United States. Saliva-based measures included telomere length. Blood-based measures included DNA methylation and physiology biomarkers. Propensity scores-matched analyses and Cox regression models were conducted.

RESULTS

This study included individuals aged 50 years and older, who consented for blood (N = 9,934) and saliva (N = 5,808) draw in the HRS. Blood-based biomarkers of aging biology showed strong associations with incident stroke as follows: compared with the lowest tertile of blood-based biomarkers of aging, biologically older individuals had significantly higher risk of stroke based on DNA methylation Grim Age clock (adjusted hazard ratio [aHR] = 2.64, 95% CI 1.90-3.66, p < 0.001) and Physiology-based Phenotypic Age clock (aHR = 1.75, 95% CI 1.27-2.42, p < 0.001). In secondary analysis, biologically older individuals had increased risk of heart disease as follows: DNA methylation Grim Age clock (aHR = 1.77, 95% CI 1.49-2.11, p < 0.001) and Physiology-based Phenotypic Age clock (aHR = 1.61, 95% CI 1.36-1.90, p < 0.001).

DISCUSSION

Compared with saliva-based telomere length, blood-based aging physiology and some DNA methylation biomarkers are strongly associated with vascular disorders including stroke and are more precise and sensitive biomarkers of aging. Saliva-based telomere length and blood-based DNA methylation and physiology biomarkers likely represent different aspects of biological aging and accordingly vary in their precision as novel biomarkers for optimal vascular health.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Mechanistic Intimate Insights into the Role of Hydrogen Sulfide in Alzheimer's Disease: A Recent Systematic Review

In the rapidly evolving field of Alzheimer's Disease (AD) research, the intricate role of Hydrogen Sulfide (H2S) has garnered critical attention for its diverse involvement in both pathological substrates and prospective therapeutic paradigms. While conventional pathophysiological models of AD have primarily emphasized the significance of amyloid-beta (Aβ) deposition and tau protein hyperphosphorylation, this targeted systematic review meticulously aggregates and rigorously appraises seminal contributions from the past year elucidating the complex mechanisms of H2S in AD pathogenesis. Current scholarly literature accentuates H2S's dual role, delineating its regulatory functions in critical cellular processes-such as neurotransmission, inflammation, and oxidative stress homeostasis-while concurrently highlighting its disruptive impact on quintessential AD biomarkers. Moreover, this review illuminates the nuanced mechanistic intimate interactions of H2S in cerebrovascular and cardiovascular pathology associated with AD, thereby exploring avant-garde therapeutic modalities, including sulfurous mineral water inhalations and mud therapy. By emphasizing the potential for therapeutic modulation of H2S via both donors and inhibitors, this review accentuates the imperative for future research endeavors to deepen our understanding, thereby potentially advancing novel diagnostic and therapeutic strategies in AD.

Genetic background influences the 5XFAD Alzheimer's disease mouse model brain proteome

There is an urgent need to improve the translational validity of Alzheimer's disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable the discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. In this study, we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in the hippocampus and cortex (n = 3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across the hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress responses and neuronal synapse/signaling. The modules with the strongest relationship to human disease-neuronal synapse/signaling and lysosome/stress response-were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated with AD genotype in the hippocampus compared with the cortex. Our findings suggest that the genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.

Neurobiochemical characteristics of arginine-rich peptides explain their potential therapeutic efficacy in neurodegenerative diseases

Neurodegenerative diseases, including Alzheimer̕ s disease (AD), Parkinson̕ s disease (PD), Huntington̕ s disease (HD), and Amyotrophic Lateral Sclerosis (ALS) require special attention to find new potential treatment methods. This review aims to summarize the current knowledge of the relationship between the biochemical properties of arginine-rich peptides (ARPs) and their neuroprotective effects to deal with the harmful effects of risk factors. It seems that ARPs have portrayed a promising and fantastic landscape for treating neurodegeneration-associated disorders. With multimodal mechanisms of action, ARPs play various unprecedented roles, including as the novel delivery platforms for entering the central nervous system (CNS), the potent antagonists for calcium influx, the invader molecules for targeting mitochondria, and the protein stabilizers. Interestingly, these peptides inhibit the proteolytic enzymes and block protein aggregation to induce pro-survival signaling pathways. ARPs also serve as the scavengers of toxic molecules and the reducers of oxidative stress agents. They also have anti-inflammatory, antimicrobial, and anti-cancer properties. Moreover, by providing an efficient nucleic acid delivery system, ARPs can play an essential role in developing various fields, including gene vaccines, gene therapy, gene editing, and imaging. ARP agents and ARP/cargo therapeutics can be raised as an emergent class of neurotherapeutics for neurodegeneration. Part of the aim of this review is to present recent advances in treating neurodegenerative diseases using ARPs as an emerging and powerful therapeutic tool. The applications and progress of ARPs-based nucleic acid delivery systems have also been discussed to highlight their usefulness as a broad-acting class of drugs.

Unbiased classification of the elderly human brain proteome resolves distinct clinical and pathophysiological subtypes of cognitive impairment

Cognitive impairment in the elderly features complex molecular pathophysiology extending beyond the hallmark pathologies of traditional disease classification. Molecular subtyping using large-scale -omic strategies can help resolve this biological heterogeneity. Using quantitative mass spectrometry, we measured ∼8000 proteins across >600 dorsolateral prefrontal cortex tissues with clinical diagnoses of no cognitive impairment (NCI), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia. Unbiased classification of MCI and AD cases based on individual proteomic profiles resolved three classes with expression differences across numerous cell types and biological ontologies. Two classes displayed molecular signatures atypical of AD neurodegeneration, such as elevated synaptic and decreased inflammatory markers. In one class, these atypical proteomic features were associated with clinical and pathological hallmarks of cognitive resilience. We were able to replicate these classes and their clinicopathological phenotypes across two additional tissue cohorts. These results promise to better define the molecular heterogeneity of cognitive impairment and meaningfully impact its diagnostic and therapeutic precision.

Mitochondrial hypermetabolism precedes impaired autophagy and synaptic disorganization in App knock-in Alzheimer mouse models

Accumulation of amyloid β-peptide (Aβ) is a driver of Alzheimer's disease (AD). Amyloid precursor protein (App) knock-in mouse models recapitulate AD-associated Aβ pathology, allowing elucidation of downstream effects of Aβ accumulation and their temporal appearance upon disease progression. Here we have investigated the sequential onset of AD-like pathologies in AppNL-F and AppNL-G-F knock-in mice by time-course transcriptome analysis of hippocampus, a region severely affected in AD. Strikingly, energy metabolism emerged as one of the most significantly altered pathways already at an early stage of pathology. Functional experiments in isolated mitochondria from hippocampus of both AppNL-F and AppNL-G-F mice confirmed an upregulation of oxidative phosphorylation driven by the activity of mitochondrial complexes I, IV and V, associated with higher susceptibility to oxidative damage and Ca2+-overload. Upon increasing pathologies, the brain shifts to a state of hypometabolism with reduced abundancy of mitochondria in presynaptic terminals. These late-stage mice also displayed enlarged presynaptic areas associated with abnormal accumulation of synaptic vesicles and autophagosomes, the latter ultimately leading to local autophagy impairment in the synapses. In summary, we report that Aβ-induced pathways in App knock-in mouse models recapitulate key pathologies observed in AD brain, and our data herein adds a comprehensive understanding of the pathologies including dysregulated metabolism and synapses and their timewise appearance to find new therapeutic approaches for AD.

Compilation of reported protein changes in the brain in Alzheimer's disease

Proteomic studies of human Alzheimer's disease brain tissue have potential to identify protein changes that drive disease, and to identify new drug targets. Here, we analyse 38 published Alzheimer's disease proteomic studies, generating a map of protein changes in human brain tissue across thirteen brain regions, three disease stages (preclinical Alzheimer's disease, mild cognitive impairment, advanced Alzheimer's disease), and proteins enriched in amyloid plaques, neurofibrillary tangles, and cerebral amyloid angiopathy. Our dataset is compiled into a searchable database (NeuroPro). We found 848 proteins were consistently altered in 5 or more studies. Comparison of protein changes in early-stage and advanced Alzheimer's disease revealed proteins associated with synapse, vesicle, and lysosomal pathways show change early in disease, but widespread changes in mitochondrial associated protein expression change are only seen in advanced Alzheimer's disease. Protein changes were similar for brain regions considered vulnerable and regions considered resistant. This resource provides insight into Alzheimer's disease brain protein changes and highlights proteins of interest for further study.

How Many Alzheimer-Perusini's Atypical Forms Do We Still Have to Discover?

Alzheimer-Perusini's (AD) disease represents the most spread dementia around the world and constitutes a serious problem for public health. It was first described by the two physicians from whom it took its name. Nowadays, we have extensively expanded our knowledge about this disease. Starting from a merely clinical and histopathologic description, we have now reached better molecular comprehension. For instance, we passed from an old conceptualization of the disease based on plaques and tangles to a more modern vision of mixed proteinopathy in a one-to-one relationship with an alteration of specific glial and neuronal phenotypes. However, no disease-modifying therapies are yet available. It is likely that the only way to find a few "magic bullets" is to deepen this aspect more and more until we are able to draw up specific molecular profiles for single AD cases. This review reports the most recent classifications of AD atypical variants in order to summarize all the clinical evidence using several discrimina (for example, post mortem neurofibrillary tangle density, cerebral atrophy, or FDG-PET studies). The better defined four atypical forms are posterior cortical atrophy (PCA), logopenic variant of primary progressive aphasia (LvPPA), behavioral/dysexecutive variant and AD with corticobasal degeneration (CBS). Moreover, we discuss the usefulness of such classifications before outlining the molecular-genetic aspects focusing on microglial activity or, more generally, immune system control of neuroinflammation and neurodegeneration.

Advances in proteomic phenotyping of microglia in neurodegeneration

Microglia are dynamic resident immune cells of the central nervous system (CNS) that sense, survey, and respond to changes in their environment. In disease states, microglia transform from homeostatic to diverse molecular phenotypic states that play complex and causal roles in neurologic disease pathogenesis, as evidenced by the identification of microglial genes as genetic risk factors for neurodegenerative disease. While advances in transcriptomic profiling of microglia from the CNS of humans and animal models have provided transformative insights, the transcriptome is only modestly reflective of the proteome. Proteomic profiling of microglia is therefore more likely to provide functionally and therapeutically relevant targets. In this review, we discuss molecular insights gained from transcriptomic studies of microglia in the context of Alzheimer's disease as a prototypic neurodegenerative disease, and highlight existing and emerging approaches for proteomic profiling of microglia derived from in vivo model systems and human brain.

Analyzing the glial proteome in Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, memory loss, and changes in behavior. Accumulating evidence indicates that dysfunction of glial cells, including astrocytes, microglia, and oligodendrocytes, may contribute to the development and progression of AD. Large-scale analysis of glial proteins sheds light on their roles in cellular processes and diseases. In AD, glial proteomics has been utilized to understand glia-based pathophysiology and identify potential biomarkers and therapeutic targets.

AREA COVERED

In this review, we provide an updated overview of proteomic analysis of glia in the context of AD. Additionally, we discuss current challenges in the field, involving glial complexity and heterogeneity, and describe some cutting-edge proteomic technologies to address them.

EXPERT OPINION

Unbiased comprehensive analysis of glial proteomes aids our understanding of the molecular and cellular mechanisms of AD pathogenesis. These investigations highlight the crucial role of glial cells and provide novel insights into the mechanisms of AD pathology. A deeper understanding of the AD-related glial proteome could offer a repertoire of potential biomarkers and therapeutics. Further technical advancement of glial proteomics will enable us to identify proteins within individual cells and specific cell types, thus significantly enhancing our comprehension of AD pathogenesis.

DHCR24 reverses Alzheimer's disease-related pathology and cognitive impairment via increasing hippocampal cholesterol levels in 5xFAD mice

Accumulating evidences reveal that cellular cholesterol deficiency could trigger the onset of Alzheimer's disease (AD). As a key regulator, 24-dehydrocholesterol reductase (DHCR24) controls cellular cholesterol homeostasis, which was found to be downregulated in AD vulnerable regions and involved in AD-related pathological activities. However, DHCR24 as a potential therapeutic target for AD remains to be identified. In present study, we demonstrated the role of DHCR24 in AD by employing delivery of adeno-associated virus carrying DHCR24 gene into the hippocampus of 5xFAD mice. Here, we found that 5xFAD mice had lower levels of cholesterol and DHCR24 expression, and the cholesterol loss was alleviated by DHCR24 overexpression. Surprisingly, the cognitive impairment of 5xFAD mice was significantly reversed after DHCR24-based gene therapy. Moreover, we revealed that DHCR24 knock-in successfully prevented or reversed AD-related pathology in 5xFAD mice, including amyloid-β deposition, synaptic injuries, autophagy, reactive astrocytosis, microglial phagocytosis and apoptosis. In conclusion, our results firstly demonstrated that the potential value of DHCR24-mediated regulation of cellular cholesterol level as a promising treatment for AD.

Genetic background influences the 5XFAD Alzheimer's disease mouse model brain proteome

There is a pressing need to improve the translational validity of Alzheimer's disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. Here we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in hippocampus and cortex (n=3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress response and neuronal synapse/signaling. The modules with the strongest relationship to human disease-neuronal synapse/signaling and lysosome/stress response-were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated to AD genotype in hippocampus compared to cortex. Our findings suggest that genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.

Native-state proteomics of Parvalbumin interneurons identifies novel molecular signatures and metabolic vulnerabilities to early Alzheimer's disease pathology

One of the earliest pathophysiological perturbations in Alzheimer's Disease (AD) may arise from dysfunction of fast-spiking parvalbumin (PV) interneurons (PV-INs). Defining early protein-level (proteomic) alterations in PV-INs can provide key biological and translationally relevant insights. Here, we use cell-type-specific in vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state proteomes of PV interneurons. PV-INs exhibited proteomic signatures of high metabolic, mitochondrial, and translational activity, with over-representation of causally linked AD genetic risk factors. Analyses of bulk brain proteomes indicated strong correlations between PV-IN proteins with cognitive decline in humans, and with progressive neuropathology in humans and mouse models of Aβ pathology. Furthermore, PV-IN-specific proteomes revealed unique signatures of increased mitochondrial and metabolic proteins, but decreased synaptic and mTOR signaling proteins in response to early Aβ pathology. PV-specific changes were not apparent in whole-brain proteomes. These findings showcase the first native state PV-IN proteomes in mammalian brain, revealing a molecular basis for their unique vulnerabilities in AD.

Quantitative Mass Spectrometry Analysis of Cerebrospinal Fluid Protein Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT-) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT-), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT- individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.

Proteomics analysis of prefrontal cortex of Alzheimer's disease patients revealed dysregulated proteins in the disease and novel proteins associated with amyloid-β pathology

BACKGROUND

Alzheimer's disease (AD) is a progressive, chronic, and neurodegenerative disease, and the most common cause of dementia worldwide. Currently, the mechanisms underlying the disease are far from being elucidated. Thus, the study of proteins involved in its pathogenesis would allow getting further insights into the disease and identifying new markers for AD diagnosis.

METHODS

We aimed here to analyze protein dysregulation in AD brain by quantitative proteomics to identify novel proteins associated with the disease. 10-plex TMT (tandem mass tags)-based quantitative proteomics experiments were performed using frozen tissue samples from the left prefrontal cortex of AD patients and healthy individuals and vascular dementia (VD) and frontotemporal dementia (FTD) patients as controls (CT). LC-MS/MS analyses were performed using a Q Exactive mass spectrometer.

RESULTS

In total, 3281 proteins were identified and quantified using MaxQuant. Among them, after statistical analysis with Perseus (p value < 0.05), 16 and 155 proteins were defined as upregulated and downregulated, respectively, in AD compared to CT (Healthy, FTD and VD) with an expression ratio ≥ 1.5 (upregulated) or ≤ 0.67 (downregulated). After bioinformatics analysis, ten dysregulated proteins were selected as more prone to be associated with AD, and their dysregulation in the disease was verified by qPCR, WB, immunohistochemistry (IHC), immunofluorescence (IF), pull-down, and/or ELISA, using tissue and plasma samples of AD patients, patients with other dementias, and healthy individuals.

CONCLUSIONS

We identified and validated novel AD-associated proteins in brain tissue that should be of further interest for the study of the disease. Remarkably, PMP2 and SCRN3 were found to bind to amyloid-β (Aβ) fibers in vitro, and PMP2 to associate with Aβ plaques by IF, whereas HECTD1 and SLC12A5 were identified as new potential blood-based biomarkers of the disease.

Structural Proteomic Profiling of Cerebrospinal Fluids to Reveal Novel Conformational Biomarkers for Alzheimer's Disease

Alzheimer's disease (AD) is the most common representation of dementia, with brain pathological hallmarks of protein abnormal aggregation, such as with amyloid beta and tau protein. It is well established that posttranslational modifications on tau protein, particularly phosphorylation, increase the likelihood of its aggregation and subsequent formation of neurofibrillary tangles, another hallmark of AD. As additional misfolded proteins presumably exist distinctly in AD disease states, which would serve as potential source of AD biomarkers, we used limited proteolysis-coupled with mass spectrometry (LiP-MS) to probe protein structural changes. After optimizing the LiP-MS conditions, we further applied this method to human cerebrospinal fluid specimens collected from healthy control, mild cognitive impairment (MCI), and AD subject groups to characterize proteome-wide misfolding tendencies as a result of disease progression. The fully tryptic peptides embedding LiP sites were compared with the half-tryptic peptides generated from internal cleavage of the same region to determine any structural unfolding or misfolding. We discovered hundreds of significantly up- and down-regulated peptides associated with MCI and AD indicating their potential structural changes in AD progression. Moreover, we detected 53 structurally changed regions in 12 proteins with high confidence between the healthy control and disease groups, illustrating the functional relevance of these proteins with AD progression. These newly discovered conformational biomarker candidates establish valuable future directions for exploring the molecular mechanism of designing therapeutic targets for AD.

The Case for a Novel Therapeutic Approach to Dementia: Small Molecule Hepatocyte Growth Factor (HGF/MET) Positive Modulators

An estimated 6.5 million Americans aged 65 years or older have Alzheimer's disease (AD), which will grow to 13.8 million Americans by 2060. Despite the growing burden of dementia, no fundamental change in drug development for AD has been seen in > 20 years. Currently approved drugs for AD produce only modest symptomatic improvements in cognition with small effect sizes. A growing mismatch exists between the urgent need to develop effective drugs for symptomatic AD and the largely failed search for disease modification. The failure rate of clinical trials in AD is high overall, and in particular for disease-modifying therapies. Research efforts in AD have focused predominantly on amyloid-β and tau pathologies, but limiting clinical research to these "classical hallmarks" of the disease does not address the most urgent patient, caregiver, or societal needs. Rather, clinical research should consider the complex pathophysiology of AD. Innovative approaches are needed that provide outside-the-box thinking, and re-imagine trial design, interventions, and outcomes as well as progress in proteomics and fluid biomarker analytics for both diagnostics and disease monitoring. A new approach offering a highly specific, yet multi-pronged intervention that exerts positive modulation on the HGF/MET neurotrophic system is currently being tested in mid-to-late-stage clinical trials in mild to moderate AD. Findings from such trials may provide data to support novel approaches for development of innovative drugs for treating AD at various disease stages, including among patients already symptomatic, and may offer benefits for other neurodegenerative diseases.

Mediation Analysis and Mixed-Effects Models for the Identification of Stage-specific Imaging Genetics Patterns in Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common and severe forms of Senile Dementia. Genome-wide association studies (GWAS) have identified dozens of AD susceptible loci. To better understand potential mechanism-of-action for AD, quantitative brain imaging features have been studied as mediators linking genetic variants to AD outcomes. In this study, Mediation analysis, Chow test and Mixed-effects Models are used to investigate the biological pathways by which genetic variants affect both brain structures/functions and disease diagnosis. We analyzed the imaging and genetics data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project, including a Polygenic Hazard Score (PHS) and 13 imaging quantitative traits (QTs) extracted from the AV45 PET scans quantifying the amyloid deposition in different brain regions of subjects from four separate diagnostic groups. Mediation analysis assessed the mediating effects of image QTs between PHS and diagnosis, whereas Chow test and Linear Mixed-Effects models were used to characterize intra-group differences in the associations between genetic scores and imaging QTs for different disease stages. Results show that promising stage-specific imaging QTs that mediate the genetic effect of the studied PHS on disease status have been identified, providing novel insights into the predictive power of the PHS and the mediating power of amyloid imaging QTs with respect to multiple stages over the AD progression.

The Brain Protein Atlas: A conglomerate of proteomics datasets of human neural tissue

The human brain represents one of the most complex biological structures with significant spatiotemporal molecular plasticity occurring through early development, learning, aging, and disease. While much progress has been made in mapping its transcriptional architecture, more downstream phenotypic readouts are relatively scarce due to limitations with tissue heterogeneity and accessibility, as well as an inability to amplify protein species prior to global -OMICS analysis. To address some of these barriers, our group has recently focused on using mass-spectrometry workflows compatible with small amounts of formalin-fixed paraffin-embedded tissue samples. This has enabled exploration into spatiotemporal proteomic signatures of the brain and disease across otherwise inaccessible neurodevelopmental timepoints and anatomical niches. Given the similar theme and approaches, we introduce an integrated online portal, "The Brain Protein Atlas (BPA)" (www.brainproteinatlas.org), representing a public resource that allows users to access and explore these amalgamated datasets. Specifically, this portal contains a growing set of peer-reviewed mass-spectrometry-based proteomic datasets, including spatiotemporal profiles of human cerebral development, diffuse gliomas, clinically aggressive meningiomas, and a detailed anatomic atlas of glioblastoma. One barrier to entry in mass spectrometry-based proteomics data analysis is the steep learning curve required to extract biologically relevant data. BPA, therefore, includes several built-in analytical tools to generate relevant plots (e.g., volcano plots, heatmaps, boxplots, and scatter plots) and evaluate the spatiotemporal patterns of proteins of interest. Future iterations aim to expand available datasets, including those generated by the community at large, and analytical tools for exploration. Ultimately, BPA aims to improve knowledge dissemination of proteomic information across the neuroscience community in hopes of accelerating the biological understanding of the brain and various maladies.

M1 muscarinic receptor activation reduces the molecular pathology and slows the progression of prion-mediated neurodegenerative disease

Many dementias are propagated through the spread of "prion-like" misfolded proteins. This includes prion diseases themselves (such as Creutzfeldt-Jakob disease) and Alzheimer's disease (AD), for which no treatments are available to slow or stop progression. The M1 acetylcholine muscarinic receptor (M1 receptor) is abundant in the brain, and its activity promotes cognitive function in preclinical models and in patients with AD. Here, we investigated whether activation of the M1 receptor might slow the progression of neurodegeneration associated with prion-like misfolded protein in a mouse model of prion disease. Proteomic and transcriptomic analysis of the hippocampus revealed that this model had a molecular profile that was similar to that of human neurodegenerative diseases, including AD. Chronic enhancement of the activity of the M1 receptor with the positive allosteric modulator (PAM) VU0486846 reduced the abundance of prion-induced molecular markers of neuroinflammation and mitochondrial dysregulation in the hippocampus and normalized the abundance of those associated with neurotransmission, including synaptic and postsynaptic signaling components. PAM treatment of prion-infected mice prolonged survival and maintained cognitive function. Thus, allosteric activation of M1 receptors may reduce the severity of neurodegenerative diseases caused by the prion-like propagation of misfolded protein.

Dynamin-like Protein 1 (DNML1) as a Molecular Target for Antibody-Based Immunotherapy to Treat Glaucoma

Slow and progressive loss of retinal ganglion cells (RGCs) is the main characteristic of glaucoma, the second leading cause of blindness worldwide. Previous studies have shown that impaired mitochondrial dynamics could facilitate retinal neurodegeneration. Mitochondrial dynamics are regulated directly (fission) or more indirectly (fusion) by dynamin-like protein 1 (DNML1). Therefore, DNM1L might be a promising target for an antibody-based approach to treat glaucoma. The consequences of targeting endogenous DNM1L by antibodies in a glaucoma animal model have not been investigated yet. Here, we show that the intravitreal application of an anti-DNM1L antibody showed protective effects regarding the survival of RGCs and their axons in the retinal nerve fiber layer (RNFL). Antibody treatment also improved retinal functionality, as observed by electroretinography (Ganzfeld ERG). Western blot analysis revealed altered DNM1L phosphorylation and altered expression of proteins related to apoptosis suggesting a decreased apoptosis rate. Mass spectrometry analysis revealed 28 up-regulated and 21 down-regulated proteins (p < 0.05) in both experimental groups. Protein pathway analysis showed that many proteins interacted directly with the target protein DNM1L and could be classified into three main protein clusters: Vesicle traffic-associated (NSF, SNCA, ARF1), mitochondrion-associated (HSP9A, SLC25A5/ANT2, GLUD1) and cytoskeleton-associated (MAP1A) signaling pathway. Our results demonstrate that DNM1L is a promising target for an antibody-based approach to glaucoma therapy.

Plasma proteome profiling identifies changes associated to AD but not to FTD

BACKGROUND

Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process.

METHODS

Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis.

RESULTS

Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified.

CONCLUSIONS

We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.

Insulin and serine metabolism as sex-specific hallmarks of Alzheimer's disease in the human hippocampus

Healthy aging is an ambitious aspiration for humans, but neurodegenerative disorders, such as Alzheimer's disease (AD), strongly affect quality of life. Using an integrated omics approach, we investigate alterations in the molecular composition of postmortem hippocampus samples of healthy persons and individuals with AD. Profound differences are apparent between control and AD male and female cohorts in terms of up- and downregulated metabolic pathways. A decrease in the insulin response is evident in AD when comparing the female with the male group. The serine metabolism (linked to the glycolytic pathway and generating the N-methyl-D-aspartate [NMDA] receptor coagonist D-serine) is also significantly modulated: the D-Ser/total serine ratio represents a way to counteract age-related cognitive decline in healthy men and during AD onset in women. These results show how AD changes and, in certain respects, almost reverses sex-specific proteomic and metabolomic profiles, highlighting how different pathophysiological mechanisms are active in men and women.