Deep proteomic network analysis of Alzheimer's disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease

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 enrich HBPs from plasma obtained from AD (n = 62) and control (n = 47) samples. These profiles were then correlated to Aβ, tau and phosphorylated tau (pTau) CSF biomarkers and plasma pTau181 from the same individuals, as well as a consensus brain proteome network to assess the overlap with AD brain pathophysiology.

RESULTS

Heparin enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundant proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude in abundance, were measured across 109 samples. Compared to the consensus AD brain protein co-expression network, we observed that specific plasma proteins exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes, highlighting the complex interplay between the two compartments. Elevated proteins in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate with Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and the APOE4 proteoform. Additionally, heparin-enriched proteins in plasma demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau181. A panel of five plasma proteins classified AD from control individuals with an area under the curve (AUC) of 0.85. When combined with plasma pTau181, the panel significantly improved the classification performance of pTau181 alone, increasing the AUC from 0.93 to 0.98. This suggests that the heparin-enriched plasma proteome captures additional variance in cognitive dementia beyond what is explained by pTau181.

CONCLUSION

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

Hypothalamic and hippocampal transcriptome changes in AppNL-G-F mice as a function of metabolic and inflammatory dysfunction

The progression of Alzheimer's disease (AD) has a silent phase that predates characteristic cognitive decline and eventually leads to active cognitive deficits. Metabolism, diet, and obesity have been correlated to the development of AD but is poorly understood. The hypothalamus is a brain region that exerts homeostatic control on food intake and metabolism and has been noted to be impacted during the active phase of Alzheimer's disease. This study, in using an amyloid overexpression AppNL-G-F mouse model under normal metabolic conditions, examines blood markers in young and old male AppNL-G-F mice (n = 5) that corresponds to the silent and active phases of AD, and bulk gene expression changes in the hypothalamus and the hippocampus. The results show a large panel of inflammatory mediators, leptin, and other proteins that may be involved in weakening the blood brain barrier, to be increased in the young AppNL-G-F mice but not in the old AppNL-G-F mice. There were also several differentially expressed genes in both the hypothalamus and the hippocampus in the young AppNL-G-F mice prior to amyloid plaque formation and cognitive decline that persisted in the old AppNL-G-F mice, including GABRa2 receptor, Wdfy1, and several pseudogenes with unknown function. These results suggests that a larger panel of inflammatory mediators may be used as blood markers to detect silent AD, and that a change in leptin and gene expression in the hypothalamus exist prior to cognitive effects, suggesting a coupling of metabolism with amyloid plaque induced cognitive decline.

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.

Tau, RNA, and RNA-Binding Proteins: Complex Interactions in Health and Neurodegenerative Diseases

The tau protein is a key contributor to multiple neurodegenerative diseases. The pathology of tau is thought to be related to tau's propensity to form self-templating fibrillar structures that allow tau fibers to propagate in the brain by prion-like mechanisms. Unresolved issues with respect to tau pathology are how the normal function of tau and its misregulation contribute to disease, how cofactors and cellular organelles influence the initiation and propagation of tau fibers, and determining the mechanism of tau toxicity. Herein, we review the connection between tau and degenerative diseases, the basis for tau fibrilization, and how that process interacts with cellular molecules and organelles. One emerging theme is that tau interacts with RNA and RNA-binding proteins, normally and in pathologic aggregates, which may provide insight into alterations in RNA regulation observed in disease.

A neurotherapeutic approach with Lacticaseibacillus rhamnosus E9 on gut microbiota and intestinal barrier in MPTP-induced mouse model of Parkinson's disease

The gut microbiota plays a crucial role in neural development and progression of neural disorders like Parkinson's disease (PD). Probiotics have been suggested to impact neurodegenerative diseases via gut-brain axis. This study aims to investigate the therapeutic potential of Lacticaseibacillus rhamnosus E9, a high exopolysaccharide producer, on 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-induced mouse model of PD. C57BL/6 mice subjected to MPTP were fed L. rhamnosus E9 for fifteen days and sacrificed after the last administration. Motor functions were determined by open-field, catalepsy, and wire-hanging tests. The ileum and the brain tissues were collected for ELISA, qPCR, and immunohistochemistry analyses. The cecum content was obtained for microbiota analysis. E9 supplementation alleviated MPTP-induced motor dysfunctions accompanied by decreased levels of striatal TH and dopamine. E9 also reduced the level of ROS in the striatum and decreased the DAT expression while increasing the DR1. Furthermore, E9 improved intestinal integrity by enhancing ZO-1 and Occludin levels and reversed the dysbiosis of the gut microbiota induced by MPTP. In conclusion, E9 supplementation improved the MPTP-induced motor deficits and neural damage as well as intestinal barrier by modulating the gut microbiota in PD mice. These findings suggest that E9 supplementation holds therapeutic potential in managing PD through the gut-brain axis.

Psychosocial experiences are associated with human brain mitochondrial biology

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these "mind-mitochondria" associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

STAU1 exhibits a dual function by promoting amyloidogenesis and tau phosphorylation in cultured cells

Staufen-1 (STAU1) is a double-stranded RNA-binding protein (RBP) involved in a variety of pathological conditions. In this study, we investigated the potential role of STAU1 in Alzheimer's disease (AD), in which two hallmarks are well-established as cerebral β-amyloid protein (Aβ) deposition and Tau-centered neurofibrillary tangles. We found that STAU1 protein level was significantly increased in cells that stably express full-length APP and the brain of APP/PS1 mice, an animal model of AD. STAU1 knockdown, as opposed to overexpression, significantly decreased the protein levels of β-amyloid converting enzyme 1 (BACE1) and Aβ. We further found that STAU1 extended the half-life of the BACE1 mRNA through binding to the 3' untranslated region (3'UTR). Transcriptome analysis revealed that STAU1 enhanced the expression of growth arrest and DNA damage 45 β (GADD45B) upstream of P38 MAPK signaling, which contributed to STAU1-induced regulation of Tau phosphorylation at Ser396 and Thr181. Together, STAU1 promoted amyloidogenesis by inhibiting BACE1 mRNA decay, and augmented Tau phosphorylation through activating GADD45B in relation to P38 MAPK. Targeting STAU1 that acts on both amyloidogenesis and tauopathy may serve as an optimistic approach for AD treatment.

Broad proteomics analysis of seeding-induced aggregation of α-synuclein in M83 neurons reveals remodeling of proteostasis mechanisms that might contribute to Parkinson's disease pathogenesis

Aggregation of misfolded α-synuclein (α-syn) is a key characteristic feature of Parkinson's disease (PD) and related synucleinopathies. The nature of these aggregates and their contribution to cellular dysfunction is still not clearly elucidated. We employed mass spectrometry-based total and phospho-proteomics to characterize the underlying molecular and biological changes due to α-syn aggregation using the M83 mouse primary neuronal model of PD. We identified gross changes in the proteome that coincided with the formation of large Lewy body-like α-syn aggregates in these neurons. We used protein-protein interaction (PPI)-based network analysis to identify key protein clusters modulating specific biological pathways that may be dysregulated and identified several mechanisms that regulate protein homeostasis (proteostasis). The observed changes in the proteome may include both homeostatic compensation and dysregulation due to α-syn aggregation and a greater understanding of both processes and their role in α-syn-related proteostasis may lead to improved therapeutic options for patients with PD and related disorders.

Familial Alzheimer's Disease Neurons Bearing Mutations in PSEN1 Display Increased Calcium Responses to AMPA as an Early Calcium Dysregulation Phenotype

Familial Alzheimer's disease (FAD) can be caused by mutations in PSEN1 that encode presenilin-1, a component of the gamma-secretase complex that cleaves amyloid precursor protein. Alterations in calcium (Ca2+) homeostasis and glutamate signaling are implicated in the pathogenesis of FAD; however, it has been difficult to assess in humans whether or not these phenotypes are the result of amyloid or tau pathology. This study aimed to assess the early calcium and glutamate phenotypes of FAD by measuring the Ca2+ response of induced pluripotent stem cell (iPSC)-derived neurons bearing PSEN1 mutations to glutamate and the ionotropic glutamate receptor agonists NMDA, AMPA, and kainate compared to isogenic control and healthy lines. The data show that in early neurons, even in the absence of amyloid and tau phenotypes, FAD neurons exhibit increased Ca2+ responses to glutamate and AMPA, but not NMDA or kainate. Together, this suggests that PSEN1 mutations alter Ca2+ and glutamate signaling as an early phenotype of FAD.

Neuritic Plaques - Gateways to Understanding Alzheimer's Disease

Extracellular deposits of amyloid-β (Aβ) in the form of plaques are one of the main pathological hallmarks of Alzheimer's disease (AD). Over the years, many different Aβ plaque morphologies such as neuritic plaques, dense cored plaques, cotton wool plaques, coarse-grain plaques, and diffuse plaques have been described in AD postmortem brain tissues, but correlation of a given plaque type with AD progression or AD symptoms is not clear. Furthermore, the exact trigger causing the development of one Aβ plaque morphological subtype over the other is still unknown. Here, we review the current knowledge about neuritic plaques, a subset of Aβ plaques surrounded by swollen or dystrophic neurites, which represent the most detrimental and consequential Aβ plaque morphology. Neuritic plaques have been associated with local immune activation, neuronal network dysfunction, and cognitive decline. Given that neuritic plaques are at the interface of Aβ deposition, tau aggregation, and local immune activation, we argue that understanding the exact mechanism of neuritic plaque formation is crucial to develop targeted therapies for AD.

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.

A novel multi-omics mendelian randomization method for gene set enrichment and its application to psychiatric disorders

Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often do not implicate specific genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS) that integrate xQTL and GWAS information, can link GWAS signals to effects on specific genes. To further increase detection power, gene signals are aggregated within relevant gene sets (GS) by performing gene set enrichment (GSE) analyses. Often GSE methods test for enrichment of "signal" genes in curated GS while overlooking their linkage disequilibrium (LD) structure, allowing for the possibility of increased false positive rates. Moreover, no GSE tool uses xQTL information to perform mendelian randomization (MR) analysis. To make causal inference on association between PD and GS, we develop a novel MR GSE (MR-GSE) procedure. First, we generate a "synthetic" GWAS for each MSigDB GS by aggregating summary statistics for x-level (mRNA, protein or DNA methylation (DNAm) levels) from the largest xQTL studies available) of genes in a GS. Second, we use synthetic GS GWAS as exposure in a generalized summary-data-based-MR analysis of complex trait outcomes. We applied MR-GSE to GWAS of nine important PD. When applied to the underpowered opioid use disorder GWAS, none of the four analyses yielded any signals, which suggests a good control of false positive rates. For other PD, MR-GSE greatly increased the detection of GO terms signals (2,594) when compared to the commonly used (non-MR) GSE method (286). Some of the findings might be easier to adapt for treatment, e.g., our analyses suggest modest positive effects for supplementation with certain vitamins and/or omega-3 for schizophrenia, bipolar and major depression disorder patients. Similar to other MR methods, when applying MR-GSE researchers should be mindful of the confounding effects of horizontal pleiotropy on statistical inference.

Gene knockout of RNA binding motif 5 in the brain alters RIMS2 protein homeostasis in the cerebellum and Hippocampus and exacerbates behavioral deficits after a TBI in mice

RNA binding motif 5 (RBM5) is a tumor suppressor in cancer but its role in the brain is unclear. We used conditional gene knockout (KO) mice to test if RBM5 inhibition in the brain affects chronic cortical brain tissue survival or function after a controlled cortical impact (CCI) traumatic brain injury (TBI). RBM5 KO decreased baseline contralateral hemispheric volume (p < 0.0001) and exacerbated ipsilateral tissue loss at 21 d after CCI in male mice vs. wild type (WT) (p = 0.0019). CCI injury, but not RBM5 KO, impaired beam balance performance (0-5d post-injury) and swim speed on the Morris Water Maze (MWM) (19-20d) (p < 0.0001). RBM5 KO was associated with mild learning impairment in female mice (p = 0.0426), reflected as a modest increase in escape latency early in training (14-18d post-injury). However, KO did not affect spatial memory at 19d post-injury in male or in female mice but it was impaired by CCI in females (p = 0.0061). RBM5 KO was associated with impaired visual function in male mice on the visible platform test at 20d post-injury (p = 0.0256). To explore signaling disturbances in KOs related to behavior, we first cross-referenced known brain-specific RBM5-regulated gene targets with genes in the curated RetNet database that impact vision. We then performed a secondary literature search on RBM5-regulated genes with a putative role in hippocampal function. Regulating synaptic membrane exocytosis 2 (RIMS) 2 was identified as a gene of interest because it regulates both vision and hippocampal function. Immunoprecipitation and western blot confirmed protein expression of a novel ~170 kDa RIMS2 variant in the cerebellum, and in the hippocampus, it was significantly increased in KO vs WT (p < 0.0001), and in a sex-dependent manner (p = 0.0390). Furthermore, male KOs had decreased total canonical RIMS2 levels in the cerebellum (p = 0.0027) and hippocampus (p < 0.0001), whereas female KOs had increased total RIMS1 levels in the cerebellum (p = 0.0389). In summary, RBM5 modulates brain function in mammals. Future work is needed to test if RBM5 dependent regulation of RIMS2 splicing effects vision and cognition, and to verify potential sex differences on behavior in a larger cohort of mice.

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.

RNA-binding proteins potentially regulate the alternative splicing of apoptotic genes during knee osteoarthritis progression

BACKGROUND

Alternative splicing (AS) is a principal mode of genetic regulation and one of the most widely used mechanisms to generate structurally and functionally distinct mRNA and protein variants. Dysregulation of AS may result in aberrant transcription and protein products, leading to the emergence of human diseases. Although considered important for regulating gene expression, genome-wide AS dysregulation, underlying mechanisms, and clinical relevance in knee osteoarthritis (OA) remain unelucidated. Therefore, in this study, we elucidated and validated AS events and their regulatory mechanisms during OA progression.

RESULTS

In this study, we identified differentially expressed genes between human OA and healthy meniscus samples. Among them, the OA-associated genes were primarily enriched in biological pathways such as extracellular matrix organization and ossification. The predominant OA-associated regulated AS (RAS) events were found to be involved in apoptosis during OA development. The expression of the apoptosis-related gene BCL2L13, XAF1, and NF2 were significantly different between OA and healthy meniscus samples. The construction of a covariation network of RNA-binding proteins (RBPs) and RAS genes revealed that differentially expressed RBP genes LAMA2 and CUL4B may regulate the apoptotic genes XAF1 and BCL2L13 to undergo AS events during OA progression. Finally, RT-qPCR revealed that CUL4B expression was significantly higher in OA meniscus samples than in normal controls and that the AS ratio of XAF1 was significantly different between control and OA samples; these findings were consistent with their expected expression and regulatory relationships.

CONCLUSIONS

Differentially expressed RBPs may regulate the AS of apoptotic genes during knee OA progression. XAF1 and its regulator, CUL4B, may serve as novel biomarkers and potential therapeutic targets for this disease.

Post-translational modifications linked to preclinical Alzheimer's disease-related pathological and cognitive changes

INTRODUCTION

In this study, we leverage proteomic techniques to identify communities of proteins underlying Alzheimer's disease (AD) risk among clinically unimpaired (CU) older adults.

METHODS

We constructed a protein co-expression network using 3869 cerebrospinal fluid (CSF) proteins quantified by SomaLogic, Inc., in a cohort of participants along the AD clinical spectrum. We then replicated this network in an independent cohort of CU older adults and related these modules to clinically-relevant outcomes.

RESULTS

We discovered modules enriched for phosphorylation and ubiquitination that were associated with abnormal amyloid status, as well as p-tau181 (M4: β = 2.44, p < 0.001, M7: β = 2.57, p < 0.001) and executive function performance (M4: β = -2.00, p = 0.005, M7: β = -2.39, p < 0.001).

DISCUSSION

In leveraging CSF proteomic data from individuals spanning the clinical spectrum of AD, we highlight the importance of post-translational modifications for early cognitive and pathological changes.

CXCL10/IgG1 Axis in Multiple Sclerosis as a Potential Predictive Biomarker of Disease Activity

BACKGROUND AND OBJECTIVES

Multiple sclerosis (MS) is a heterogeneous disease, and its course is difficult to predict. Prediction models can be established by measuring intrathecally synthesized proteins involved in inflammation, glial activation, and CNS injury.

METHODS

To determine how these intrathecal proteins relate to the short-term, i.e., 12 months, disease activity in relapsing-remitting MS (RRMS), we measured the intrathecal synthesis of 46 inflammatory mediators and 14 CNS injury or glial activation markers in matched serum and CSF samples from 47 patients with MS (pwMS), i.e., 23 RRMS and 24 clinically isolated syndrome (CIS), undergoing diagnostic lumbar puncture. Subsequently, all pwMS were followed for ≥12 months in a retrospective follow-up study and ultimately classified into "active", i.e., developing clinical and/or radiologic disease activity, n = 18) or "nonactive", i.e., not having disease activity, n = 29. Disease activity in patients with CIS corresponded to conversion to RRMS. Thus, patients with CIS were subclassified as "converters" or "nonconverters" based on their conversion status at the end of a 12-month follow-up. Twenty-seven patients with noninflammatory neurologic diseases were included as negative controls. Data were subjected to differential expression analysis and modeling techniques to define the connectivity arrangement (network) between neuroinflammation and CNS injury relevant to short-term disease activity in RRMS.

RESULTS

Lower age and/or higher CXCL13 levels positively distinguished active/converting vs nonactive/nonconverting patients. Network analysis significantly improved the prediction of short-term disease activity because active/converting patients featured a stronger positive connection between IgG1 and CXCL10. Accordingly, analysis of disease activity-free survival demonstrated that pwMS, both RRMS and CIS, with a lower or negative IgG1-CXCL10 correlation, have a higher probability of activity-free survival than the patients with a significant correlation (p < 0.0001, HR ≥ 2.87).

DISCUSSION

Findings indicate that a significant IgG1-CXCL10 positive correlation predicts the risk of short-term disease activity in patients with RRMS and CIS. Thus, the present results can be used to develop a predictive model for MS activity and conversion to RRMS.

SHMT2 Mediates Small-Molecule-Induced Alleviation of Alzheimer Pathology Via the 5'UTR-dependent ADAM10 Translation Initiation

It is long been suggested that one-carbon metabolism (OCM) is associated with Alzheimer's disease (AD), whereas the potential mechanisms remain poorly understood. Taking advantage of chemical biology, that mitochondrial serine hydroxymethyltransferase (SHMT2) directly regulated the translation of ADAM metallopeptidase domain 10 (ADAM10), a therapeutic target for AD is reported. That the small-molecule kenpaullone (KEN) promoted ADAM10 translation via the 5' untranslated region (5'UTR) and improved cognitive functions in APP/PS1 mice is found. SHMT2, which is identified as a target gene of KEN and the 5'UTR-interacting RNA binding protein (RBP), mediated KEN-induced ADAM10 translation in vitro and in vivo. SHMT2 controls AD signaling pathways through binding to a large number of RNAs and enhances the 5'UTR activity of ADAM10 by direct interaction with GAGGG motif, whereas this motif affected ribosomal scanning of eukaryotic initiation factor 2 (eIF2) in the 5'UTR. Together, KEN exhibits therapeutic potential for AD by linking OCM with RNA processing, in which the metabolic enzyme SHMT2 "moonlighted" as RBP by binding to GAGGG motif and promoting the 5'UTR-dependent ADAM10 translation initiation.

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.

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.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

Meta-analysis of age-related cognitive decline reveals a novel locus for the attention domain and implicates a COVID-19-related gene for global cognitive function

INTRODUCTION

Cognitive abilities have substantial heritability throughout life, as shown by twin- and population-based studies. However, there is limited understanding of the genetic factors related to cognitive decline in aging across neurocognitive domains.

METHODS

We conducted a meta-analysis on 3045 individuals aged ≥65, derived from three population-based cohorts, to identify genetic variants associated with the decline of five neurocognitive domains (attention, memory, executive function, language, visuospatial function) and global cognitive decline. We also conducted gene-based and functional bioinformatics analyses.

RESULTS

Apolipoprotein E (APOE)4 was significantly associated with decline of memory (p = 5.58E-09) and global cognitive function (p = 1.84E-08). We identified a novel association with attention decline on chromosome 9, rs6559700 (p = 2.69E-08), near RASEF. Gene-based analysis also identified a novel gene, TMPRSS11D, involved in the activation of SARS-CoV-2, to be associated with the decline in global cognitive function (p = 4.28E-07).

DISCUSSION

Domain-specific genetic studies can aid in the identification of novel genes and pathways associated with decline across neurocognitive domains.

HIGHLIGHTS

rs6559700 was associated with decline of attention. APOE4 was associated with decline of memory and global cognitive decline. TMPRSS11D, a gene involved in the activation of SARS-CoV-2, was implicated in global cognitive decline. Cognitive domain abilities had both unique and shared molecular pathways across the domains.

Unveiling the Molecular Footprint: Proteome-Based Biomarkers for Alzheimer's Disease

Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Early and accurate diagnosis of AD is crucial for implementing timely interventions and developing effective therapeutic strategies. Proteome-based biomarkers have emerged as promising tools for AD diagnosis and prognosis due to their ability to reflect disease-specific molecular alterations. There is of great significance for biomarkers in AD diagnosis and management. It emphasizes the limitations of existing diagnostic approaches and the need for reliable and accessible biomarkers. Proteomics, a field that comprehensively analyzes the entire protein complement of cells, tissues, or bio fluids, is presented as a powerful tool for identifying AD biomarkers. There is a diverse range of proteomic approaches employed in AD research, including mass spectrometry, two-dimensional gel electrophoresis, and protein microarrays. The challenges associated with identifying reliable biomarkers, such as sample heterogeneity and the dynamic nature of the disease. There are well-known proteins implicated in AD pathogenesis, such as amyloid-beta peptides, tau protein, Apo lipoprotein E, and clusterin, as well as inflammatory markers and complement proteins. Validation and clinical utility of proteome-based biomarkers are addressing the challenges involved in validation studies and the diagnostic accuracy of these biomarkers. There is great potential in monitoring disease progression and response to treatment, thereby aiding in personalized medicine approaches for AD patients. There is a great role for bioinformatics and data analysis in proteomics for AD biomarker research and the importance of data preprocessing, statistical analysis, pathway analysis, and integration of multi-omics data for a comprehensive understanding of AD pathophysiology. In conclusion, proteome-based biomarkers hold great promise in the field of AD research. They provide valuable insights into disease mechanisms, aid in early diagnosis, and facilitate personalized treatment strategies. However, further research and validation studies are necessary to harness the full potential of proteome-based biomarkers in clinical practice.

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.

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.

Quantitative proteomics of cerebrospinal fluid from African Americans and Caucasians reveals shared and divergent changes in Alzheimer's disease

BACKGROUND

Despite being twice as likely to get Alzheimer's disease (AD), African Americans have been grossly underrepresented in AD research. While emerging evidence indicates that African Americans with AD have lower cerebrospinal fluid (CSF) levels of Tau compared to Caucasians, other differences in AD CSF biomarkers have not been fully elucidated. Here, we performed unbiased proteomic profiling of CSF from African Americans and Caucasians with and without AD to identify both common and divergent AD CSF biomarkers.

METHODS

Multiplex tandem mass tag-based mass spectrometry (TMT-MS) quantified 1,840 proteins from 105 control and 98 AD patients of which 100 identified as Caucasian while 103 identified as African American. We used differential protein expression and co-expression approaches to assess how changes in the CSF proteome are related to race and AD. Co-expression network analysis organized the CSF proteome into 14 modules associated with brain cell-types and biological pathways. A targeted mass spectrometry method, selected reaction monitoring (SRM), with heavy labeled internal standards was used to measure a panel of CSF module proteins across a subset of African Americans and Caucasians with or without AD. A receiver operating characteristic (ROC) curve analysis assessed the performance of each protein biomarker in differentiating controls and AD by race.

RESULTS

Consistent with previous findings, the increase of Tau levels in AD was greater in Caucasians than in African Americans by both immunoassay and TMT-MS measurements. CSF modules which included 14-3-3 proteins (YWHAZ and YWHAG) demonstrated equivalent disease-related elevations in both African Americans and Caucasians with AD, whereas other modules demonstrated more profound disease changes within race. Modules enriched with proteins involved with glycolysis and neuronal/cytoskeletal proteins, including Tau, were more increased in Caucasians than in African Americans with AD. In contrast, a module enriched with synaptic proteins including VGF, SCG2, and NPTX2 was significantly lower in African Americans than Caucasians with AD. Following SRM and ROC analysis, VGF, SCG2, and NPTX2 were significantly better at classifying African Americans than Caucasians with AD.

CONCLUSIONS

Our findings provide insight into additional protein biomarkers and pathways reflecting underlying brain pathology that are shared or differ by race.

Localized proteomic differences in the choroid plexus of Alzheimer's disease and epilepsy patients

Introduction

Alzheimer's disease (AD) and epilepsy are reciprocally related. Among sporadic AD patients, clinical seizures occur in 10-22% and subclinical epileptiform abnormalities occur in 22-54%. Cognitive deficits, especially short-term memory impairments, occur in most epilepsy patients. Common neurophysiological and molecular mechanisms occur in AD and epilepsy. The choroid plexus undergoes pathological changes in aging, AD, and epilepsy, including decreased CSF turnover, amyloid beta (Aβ), and tau accumulation due to impaired clearance and disrupted CSF amino acid homeostasis. This pathology may contribute to synaptic dysfunction in AD and epilepsy.

Methods

We evaluated control (n = 8), severe AD (n = 8; A3, B3, C3 neuropathology), and epilepsy autopsy cases (n = 12) using laser capture microdissection (LCM) followed by label-free quantitative mass spectrometry on the choroid plexus adjacent to the hippocampus at the lateral geniculate nucleus level.

Results

Proteomics identified 2,459 proteins in the choroid plexus. At a 5% false discovery rate (FDR), 616 proteins were differentially expressed in AD vs. control, 1 protein in epilepsy vs. control, and 438 proteins in AD vs. epilepsy. There was more variability in the epilepsy group across syndromes. The top 20 signaling pathways associated with differentially expressed proteins in AD vs. control included cell metabolism pathways; activated fatty acid beta-oxidation (p = 2.00 x 10^-7, z = 3.00), and inhibited glycolysis (p = 1.00 x 10^-12, z = -3.46). For AD vs. epilepsy, the altered pathways included cell metabolism pathways, activated complement system (p = 5.62 x 10^-5, z = 2.00), and pathogen-induced cytokine storm (p = 2.19 x 10^-2, z = 3.61). Of the 617 altered proteins in AD and epilepsy vs. controls, 497 (81%) were positively correlated (p < 0.0001, R² = 0.27).

Discussion

We found altered signaling pathways in the choroid plexus of severe AD cases and many correlated changes in the protein expression of cell metabolism pathways in AD and epilepsy cases. The shared molecular mechanisms should be investigated further to distinguish primary pathogenic changes from the secondary ones. These mechanisms could inform novel therapeutic strategies to prevent disease progression or restore normal function. A focus on dual-diagnosed AD/epilepsy cases, specific epilepsy syndromes, such as temporal lobe epilepsy, and changes across different severity levels in AD and epilepsy would add to our understanding.

Alzheimer's Disease Protein Relevance Analysis Using Human and Mouse Model Proteomics Data

The principles governing genotype-phenotype relationships are still emerging(1-3), and detailed translational as well as transcriptomic information is required to understand complex phenotypes, such as the pathogenesis of Alzheimer's disease. For this reason, the proteomics of Alzheimer disease (AD) continues to be studied extensively. Although comparisons between data obtained from humans and mouse models have been reported, approaches that specifically address the between-species statistical comparisons are understudied. Our study investigated the performance of two statistical methods for identification of proteins and biological pathways associated with Alzheimer's disease for cross-species comparisons, taking specific data analysis challenges into account, including collinearity, dimensionality reduction and cross-species protein matching. We used a human dataset from a well-characterized cohort followed for over 22 years with proteomic data available. For the mouse model, we generated proteomic data from whole brains of CVN-AD and matching control mouse models. We used these analyses to determine the reliability of a mouse model to forecast significant proteomic-based pathological changes in the brain that may mimic pathology in human Alzheimer's disease. Compared with LASSO regression, partial least squares discriminant analysis provided better statistical performance for the proteomics analysis. The major biological finding of the study was that extracellular matrix proteins and integrin-related pathways were dysregulated in both the human and mouse data. This approach may help inform the development of mouse models that are more relevant to the study of human late-onset Alzheimer's disease.

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

INTRODUCTION

Clinical proteomics studies of Alzheimer's disease (AD) research aim to identify biomarkers useful for clinical research, diagnostics, and improve our understanding of the pathological processes involved in the disease. The rapidly increasing performance of proteomics technologies is likely to have great impact on AD research.

AREAS COVERED

We review recent proteomics approaches that have advanced the field of clinical AD research. Specifically, we discuss the application of targeted mass spectrometry (MS), labeling-based and label-free MS-based as well as affinity-based proteomics to AD biomarker development, underpinning their importance with the latest impactful clinical studies. We evaluate how proteomics technologies have been adapted to meet current challenges. Finally, we discuss the limitations and potential of proteomics techniques and whether their scope might extend beyond current research-based applications.

EXPERT OPINION

To date, proteomics technologies in the AD field have been largely limited to AD biomarker discovery. The recent development of the first successful disease-modifying treatments of AD will further increase the need for blood biomarkers for early, accurate diagnosis, and CSF biomarkers that reflect specific pathological processes. Proteomics has the potential to meet these requirements and to progress into clinical routine practice, provided that current limitations are overcome.

Targeting the post-synaptic proteome has therapeutic potential for psychosis in Alzheimer Disease

Individuals with Alzheimer Disease who develop psychotic symptoms (AD + P) experience more rapid cognitive decline and have reduced indices of synaptic integrity relative to those without psychosis (AD-P). We sought to determine whether the postsynaptic density (PSD) proteome is altered in AD + P relative to AD-P, analyzing PSDs from dorsolateral prefrontal cortex of AD + P, AD-P, and a reference group of cognitively normal elderly subjects. The PSD proteome of AD + P showed a global shift towards lower levels of all proteins relative to AD-P, enriched for kinases, proteins regulating Rho GTPases, and other regulators of the actin cytoskeleton. We computationally identified potential novel therapies predicted to reverse the PSD protein signature of AD + P. Five days of administration of one of these drugs, the C-C Motif Chemokine Receptor 5 inhibitor, maraviroc, led to a net reversal of the PSD protein signature in adult mice, nominating it as a novel potential treatment for AD + P.

Moving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer's disease

Alzheimer's disease (AD) manifests along a spectrum of cognitive deficits and levels of neuropathology. Genetic studies support a heterogeneous disease mechanism, with around 70 associated loci to date, implicating several biological processes that mediate risk for AD. Despite this heterogeneity, most experimental systems for testing new therapeutics are not designed to capture the genetically complex drivers of AD risk. In this review, we first provide an overview of those aspects of AD that are largely stereotyped and those that are heterogeneous, and we review the evidence supporting the concept that different subtypes of AD are important to consider in the design of agents for the prevention and treatment of the disease. We then dive into the multifaceted biological domains implicated to date in AD risk, highlighting studies of the diverse genetic drivers of disease. Finally, we explore recent efforts to identify biological subtypes of AD, with an emphasis on the experimental systems and data sets available to support progress in this area.

Stress granules sequester Alzheimer's disease-associated gene transcripts and regulate disease-related neuronal proteostasis

Environmental and physiological stresses can accelerate Alzheimer's disease (AD) pathogenesis. Under stress, a cytoplasmic membraneless structure termed a stress granule (SG) is formed and is associated with various neurodegenerative disorders, including AD. SGs contain translationally arrested mRNAs, suggesting that impaired RNA metabolism in neurons causes AD progression; however, the underlying mechanism remains unclear. Here, we identified numerous mRNAs and long non-coding RNAs that are directly targeted by the SG core proteins G3BP1 and G3BP2. They redundantly target RNAs before and after stress conditions. We further identified RNAs within SGs, wherein AD-associated gene transcripts accumulated, suggesting that SGs can directly regulate AD development. Furthermore, gene-network analysis revealed a possible link between the sequestration of RNAs by SGs and the impairment of protein neurohomeostasis in AD brains. Together, our study provides a comprehensive RNA regulatory mechanism involving SGs, which could be targeted therapeutically to slow AD progression mediated by SGs.

Cross-Platform Synaptic Network Analysis of Human Entorhinal Cortex Identifies TWF2 as a Modulator of Dendritic Spine Length

Proteomic studies using postmortem human brain tissue samples have yielded robust assessments of the aging and neurodegenerative disease(s) proteomes. While these analyses provide lists of molecular alterations in human conditions, like Alzheimer's disease (AD), identifying individual proteins that affect biological processes remains a challenge. To complicate matters, protein targets may be highly understudied and have limited information on their function. To address these hurdles, we sought to establish a blueprint to aid selection and functional validation of targets from proteomic datasets. A cross-platform pipeline was engineered to focus on synaptic processes in the entorhinal cortex (EC) of human patients, including controls, preclinical AD, and AD cases. Label-free quantification mass spectrometry (MS) data (n = 2260 proteins) was generated on synaptosome fractionated tissue from Brodmann area 28 (BA28; n = 58 samples). In parallel, dendritic spine density and morphology was measured in the same individuals. Weighted gene co-expression network analysis was used to construct a network of protein co-expression modules that were correlated with dendritic spine metrics. Module-trait correlations were used to guide unbiased selection of Twinfilin-2 (TWF2), which was the top hub protein of a module that positively correlated with thin spine length. Using CRISPR-dCas9 activation strategies, we demonstrated that boosting endogenous TWF2 protein levels in primary hippocampal neurons increased thin spine length, thus providing experimental validation for the human network analysis. Collectively, this study describes alterations in dendritic spine density and morphology as well as synaptic proteins and phosphorylated tau from the entorhinal cortex of preclinical and advanced stage AD patients.SIGNIFICANCE STATEMENT Proteomic studies can yield vast lists of molecules that are altered under various experimental or disease conditions. Here, we provide a blueprint to facilitate mechanistic validation of protein targets from human brain proteomic datasets. We conducted a proteomic analysis of human entorhinal cortex (EC) samples spanning cognitively normal and Alzheimer's disease (AD) cases with a comparison of dendritic spine morphology in the same samples. Network integration of proteomics with dendritic spine measurements allowed for unbiased discovery of Twinfilin-2 (TWF2) as a regulator of dendritic spine length. A proof-of-concept experiment in cultured neurons demonstrated that altering Twinfilin-2 protein level induced corresponding changes in dendritic spine length, thus providing experimental validation for the computational framework.

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.

mRNA isoform balance in neuronal development and disease

Balanced mRNA isoform diversity and abundance are spatially and temporally regulated throughout cellular differentiation. The proportion of expressed isoforms contributes to cell type specification and determines key properties of the differentiated cells. Neurons are unique cell types with intricate developmental programs, characteristic cellular morphologies, and electrophysiological potential. Neuron-specific gene expression programs establish these distinctive cellular characteristics and drive diversity among neuronal subtypes. Genes with neuron-specific alternative processing are enriched in key neuronal functions, including synaptic proteins, adhesion molecules, and scaffold proteins. Despite the similarity of neuronal gene expression programs, each neuronal subclass can be distinguished by unique alternative mRNA processing events. Alternative processing of developmentally important transcripts alters coding and regulatory information, including interaction domains, transcript stability, subcellular localization, and targeting by RNA binding proteins. Fine-tuning of mRNA processing is essential for neuronal activity and maintenance. Thus, the focus of neuronal RNA biology research is to dissect the transcriptomic mechanisms that underlie neuronal homeostasis, and consequently, predispose neuronal subtypes to disease. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Integrated Proteomics to Understand the Role of Neuritin (NRN1) as a Mediator of Cognitive Resilience to Alzheimer's Disease

The molecular mechanisms and pathways enabling certain individuals to remain cognitively normal despite high levels of Alzheimer's disease (AD) pathology remain incompletely understood. These cognitively normal people with AD pathology are described as preclinical or asymptomatic AD (AsymAD) and appear to exhibit cognitive resilience to the clinical manifestations of AD dementia. Here we present a comprehensive network-based approach from cases clinically and pathologically defined as asymptomatic AD to map resilience-associated pathways and extend mechanistic validation. Multiplex tandem mass tag MS (TMT-MS) proteomic data (n = 7787 proteins) was generated on brain tissue from Brodmann area 6 and Brodmann area 37 (n = 109 cases, n = 218 total samples) and evaluated by consensus weighted gene correlation network analysis. Notably, neuritin (NRN1), a neurotrophic factor previously linked to cognitive resilience, was identified as a hub protein in a module associated with synaptic biology. To validate the function of NRN1 with regard to the neurobiology of AD, we conducted microscopy and physiology experiments in a cellular model of AD. NRN1 provided dendritic spine resilience against amyloid-β (Aβ) and blocked Aβ-induced neuronal hyperexcitability in cultured neurons. To better understand the molecular mechanisms of resilience to Aβ provided by NRN1, we assessed how exogenous NRN1 alters the proteome by TMT-MS (n = 8238 proteins) of cultured neurons and integrated the results with the AD brain network. This revealed overlapping synapse-related biology that linked NRN1-induced changes in cultured neurons with human pathways associated with cognitive resilience. Collectively, this highlights the utility of integrating the proteome from the human brain and model systems to advance our understanding of resilience-promoting mechanisms and prioritize therapeutic targets that mediate resilience to AD.

DEAD-Box Helicase 17 Promotes Amyloidogenesis by Regulating BACE1 Translation

Amyloidogenesis is one of the key pathophysiological changes in Alzheimer's disease (AD). Accumulation of the toxic Aβ results from the catalytic processing of β-amyloid precursor protein (APP) associated β-amyloid converting enzyme 1 (BACE1) activity. It is reported that dead-box helicase 17 (DDX17) controls RNA metabolism and is involved in the development of multiple diseases. However, whether DDX17 might play a role in amyloidogenesis has not been documented. In the present study, we found that DDX17 protein level was significantly increased in HEK and SH-SY5Y cells that stably express full-length APP (HEK-APP and Y5Y-APP) and in the brain of APP/PS1 mice, an animal model of AD. DDX17 knockdown, as opposed to DDX17 overexpression, markedly reduced the protein levels of BACE1 and the β-amyloid peptide (Aβ) in Y5Y-APP cells. We further found that DDX17-mediated enhancement of BACE1 was selectively attenuated by translation inhibitors. Specifically, DDX17 selectively interacted with the 5' untranslated region (5'UTR) of BACE1 mRNA, and deletion of the 5'UTR abolished the effect of DDX17 on luciferase activity or protein level of BACE1. Here, we show that the enhanced expression of DDX17 in AD was associated with amyloidogenesis; through the 5'UTR-dependent BACE1 translation, DDX17 might serve as an important mediator contributing to the progression of AD.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

Differential splicing of neuronal genes in a Trem2*R47H mouse model mimics alterations associated with Alzheimer's disease

BACKGROUND

Molecular characterization of late-onset Alzheimer's disease (LOAD), the leading cause of age-related dementia, has revealed transcripts, proteins, and pathway alterations associated with disease. Assessing these postmortem signatures of LOAD in experimental model systems can further elucidate their relevance to disease origins and progression. Model organisms engineered with human genetic factors further link these signatures to disease-associated variants, especially when studies are designed to leverage homology across species. Here we assess differential gene splicing patterns in aging mouse models carrying humanized APOE4 and/or the Trem2*R47H variant on a C57BL/6J background. We performed a differential expression of gene (DEG) and differential splicing analyses on whole brain transcriptomes at multiple ages. To better understand the difference between differentially expressed and differentially spliced genes, we evaluated enrichment of KEGG pathways and cell-type specific gene signatures of the adult brain from each alteration type. To determine LOAD relevance, we compared differential splicing results from mouse models with multiple human AD splicing studies.

RESULTS

We found that differentially expressed genes in Trem2*R47H mice were significantly enriched in multiple AD-related pathways, including immune response, osteoclast differentiation, and metabolism, whereas differentially spliced genes were enriched for neuronal related functions, including GABAergic synapse and glutamatergic synapse. These results were reinforced by the enrichment of microglial genes in DEGs and neuronal genes in differentially spliced genes in Trem2*R47H mice. We observed significant overlap between differentially spliced genes in Trem2*R47H mice and brains from human AD subjects. These effects were absent in APOE4 mice and suppressed in APOE4.Trem2*R47H double mutant mice relative to Trem2*R47H mice.

CONCLUSIONS

The cross-species observation that alternative splicing observed in LOAD are present in Trem2*R47H mouse models suggests a novel link between this candidate risk gene and molecular signatures of LOAD in neurons and demonstrates how deep molecular analysis of new genetic models links molecular disease outcomes to a human candidate gene.

Programmable macromolecule-based RNA-targeting therapies to treat human neurological disorders

Disruptions in RNA processing play critical roles in the pathogenesis of neurological diseases. In this Perspective, we discuss recent progress in the development of RNA-targeting therapeutic modalities. We focus on progress, limitations, and opportunities in a new generation of therapies engineered from RNA binding proteins and other endogenous RNA regulatory macromolecules to treat human neurological disorders.

Proteomic profile of nuclei containing p62-positive inclusions in a patient with neuronal intranuclear inclusion disease

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disease characterized by eosinophilic hyaline intranuclear inclusions in the neurons, glial cells, and other somatic cells. Although CGG repeat expansions in NOTCH2NLC have been identified in most East Asian patients with NIID, the pathophysiology of NIID remains unclear. Ubiquitin- and p62-positive intranuclear inclusions are the pathological hallmark of NIID. Targeted immunostaining studies have identified several other proteins present in these inclusions. However, the global molecular changes within nuclei with these inclusions remained unclear. Herein, we analyzed the proteomic profile of nuclei with p62-positive inclusions in a NIID patient with CGG repeat expansion in NOTCH2NLC to discover candidate proteins involved in the NIID pathophysiology. We used fluorescence-activated cell sorting and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify each protein identified in the nuclei with p62-positive inclusions. The distribution of increased proteins was confirmed via immunofluorescence in autopsy brain samples from three patients with genetically confirmed NIID. Overall, 526 proteins were identified, of which 243 were consistently quantified using MS. A 1.4-fold increase was consistently observed for 20 proteins in nuclei with p62-positive inclusions compared to those without. Fifteen proteins identified with medium or high confidence in the LC-MS/MS analysis were further evaluated. Gene ontology enrichment analysis showed enrichment of several terms, including poly(A) RNA binding, nucleosomal DNA binding, and protein binding. Immunofluorescence studies confirmed that the fluorescent intensities of increased RNA-binding proteins identified by proteomic analysis, namely hnRNP A2/B1, hnRNP A3, and hnRNP C1/C2, were higher in the nuclei with p62-positive inclusions than in those without, which were not confined to the intranuclear inclusions. We identified several increased proteins in nuclei with p62-positive inclusions. Although larger studies are needed to validate our results, these proteomic data may form the basis for understanding the pathophysiology of NIID.

Comprehensive Characterization of RNA-Binding Proteins in Colon Adenocarcinoma Identifies a Novel Prognostic Signature for Predicting Clinical Outcomes and Immunotherapy Responses Based on Machine Learning

BACKGROUND

RNA-binding proteins (RBPs) are crucial factors that function in the posttranscriptional modification process and are significant in cancer.

OBJECTIVE

This research aimed for a multigene signature to predict the prognosis and immunotherapy response of patients with colon adenocarcinoma (COAD) based on the expression profile of RNA-binding proteins (RBPs).

METHODS

COAD samples retrieved from the TCGA and GEO datasets were utilized for a training dataset and a validation dataset. Totally, 14 shared RBP genes with prognostic significance were identified. Non-negative matrix factorization clusters defined by these RBPs could stratify COAD patients into two molecular subtypes. Cox regression analysis and identification of 8-gene signature categorized COAD patients into high- and low-risk populations with significantly different prognosis and immunotherapy responses.

RESULTS

Our prediction signature was superior to another five well-established prediction models. A nomogram was generated to quantificationally predict the overall survival (OS) rate, validated by calibration curves. Our findings also indicated that high-risk populations possessed an enhanced immune evasion capacity and low-risk populations might benefit immunotherapy, especially for the joint combination of PD-1 and CTLA4 immunosuppressants. DHX15 and LARS2 were detected with significantly different expressions in both datasets, which were further confirmed by qRTPCR and immunohistochemical staining.

CONCLUSION

Our observations supported an eight-RBP-related signature that could be applied for survival prediction and immunotherapy response of patients with COAD.

Proteome Network Analysis Identifies Potential Biomarkers for Brain Aging

BACKGROUND

Alzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults.

OBJECTIVE

To identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome.

METHODS

Weighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up).

RESULTS

Two proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities.

CONCLUSIONS

Proteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.

Multi-platform proteomic analysis of Alzheimer's disease cerebrospinal fluid and plasma reveals network biomarkers associated with proteostasis and the matrisome

Robust and accessible biomarkers that can capture the heterogeneity of Alzheimer's disease and its diverse pathological processes are urgently needed. Here, we undertook an investigation of Alzheimer's disease cerebrospinal fluid (CSF) and plasma from the same subjects (n=18 control, n=18 AD) using three different proteomic platforms-SomaLogic SomaScan, Olink proximity extension assay, and tandem mass tag-based mass spectrometry-to assess which protein markers in these two biofluids may serve as reliable biomarkers of AD pathophysiology observed from unbiased brain proteomics studies. Median correlation of overlapping protein measurements across platforms in CSF (r~0.7) and plasma (r~0.6) was good, with more variability in plasma. The SomaScan technology provided the most measurements in plasma. Surprisingly, many proteins altered in AD CSF were found to be altered in the opposite direction in plasma, including important members of AD brain co-expression modules. An exception was SMOC1, a key member of the brain matrisome module associated with amyloid-β deposition in AD, which was found to be elevated in both CSF and plasma. Protein co-expression analysis on greater than 7000 protein measurements in CSF and 9500 protein measurements in plasma across all proteomic platforms revealed strong changes in modules related to autophagy, ubiquitination, and sugar metabolism in CSF, and endocytosis and the matrisome in plasma. Cross-platform and cross-biofluid proteomics represents a promising approach for AD biomarker development.

Comprehensive landscape of the functions and prognostic value of RNA binding proteins in uterine corpus endometrial carcinoma

Background: The dysregulation of RNA binding proteins (RBPs) is involved in tumorigenesis and progression. However, information on the overall function of RNA binding proteins in Uterine Corpus Endometrial Carcinoma (UCEC) remains to be studied. This study aimed to explore Uterine Corpus Endometrial Carcinoma-associated molecular mechanisms and develop an RNA-binding protein-associated prognostic model.

Methods: Differently expressed RNA binding proteins were identified between Uterine Corpus Endometrial Carcinoma tumor tissues and normal tissues by R packages (DESeq2, edgeR) from The Cancer Genome Atlas (TCGA) database. Hub RBPs were subsequently identified by univariate and multivariate Cox regression analyses. The cBioPortal platform, R packages (ggplot2), Human Protein Atlas (HPA), and TIMER online database were used to explore the molecular mechanisms of Uterine Corpus Endometrial Carcinoma. Kaplan-Meier (K-M), Area Under Curve (AUC), and the consistency index (c-index) were used to test the performance of our model.

Results: We identified 128 differently expressed RNA binding proteins between Uterine Corpus Endometrial Carcinoma tumor tissues and normal tissues. Seven RNA binding proteins genes (NOP10, RBPMS, ATXN1, SBDS, POP5, CD3EAP, ZC3H12C) were screened as prognostic hub genes and used to construct a prognostic model. Such a model may be able to predict patient prognosis and acquire the best possible treatment. Further analysis indicated that, based on our model, the patients in the high-risk subgroup had poor overall survival (OS) compared to those in the low-risk subgroup. We also established a nomogram based on seven RNA binding proteins. This nomogram could inform individualized diagnostic and therapeutic strategies for Uterine Corpus Endometrial Carcinoma.

Conclusion: Our work focused on systematically analyzing a large cohort of Uterine Corpus Endometrial Carcinoma patients in the The Cancer Genome Atlas database. We subsequently constructed a robust prognostic model based on seven RNA binding proteins that may soon inform individualized diagnosis and treatment.

Alzheimer's disease-associated U1 snRNP splicing dysfunction causes neuronal hyperexcitability and cognitive impairment

Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.

Shared mechanisms across the major psychiatric and neurodegenerative diseases

Several common psychiatric and neurodegenerative diseases share epidemiologic risk; however, whether they share pathophysiology is unclear and is the focus of our investigation. Using 25 GWAS results and LD score regression, we find eight significant genetic correlations between psychiatric and neurodegenerative diseases. We integrate the GWAS results with human brain transcriptomes (n = 888) and proteomes (n = 722) to identify cis- and trans- transcripts and proteins that are consistent with a pleiotropic or causal role in each disease, referred to as causal proteins for brevity. Within each disease group, we find many distinct and shared causal proteins. Remarkably, 30% (13 of 42) of the neurodegenerative disease causal proteins are shared with psychiatric disorders. Furthermore, we find 2.6-fold more protein-protein interactions among the psychiatric and neurodegenerative causal proteins than expected by chance. Together, our findings suggest these psychiatric and neurodegenerative diseases have shared genetic and molecular pathophysiology, which has important ramifications for early treatment and therapeutic development.

Raphe and ventrolateral medulla proteomics in epilepsy and sudden unexpected death in epilepsy

Brainstem nuclei dysfunction is implicated in sudden unexpected death in epilepsy. In animal models, deficient serotonergic activity is associated with seizure-induced respiratory arrest. In humans, glia are decreased in the ventrolateral medullary pre-Botzinger complex that modulate respiratory rhythm, as well as in the medial medullary raphe that modulate respiration and arousal. Finally, sudden unexpected death in epilepsy cases have decreased midbrain volume. To understand the potential role of brainstem nuclei in sudden unexpected death in epilepsy, we evaluated molecular signalling pathways using localized proteomics in microdissected midbrain dorsal raphe and medial medullary raphe serotonergic nuclei, as well as the ventrolateral medulla in brain tissue from epilepsy patients who died of sudden unexpected death in epilepsy and other causes in diverse epilepsy syndromes and non-epilepsy control cases (n = 15-16 cases per group/region). Compared with the dorsal raphe of non-epilepsy controls, we identified 89 proteins in non-sudden unexpected death in epilepsy and 219 proteins in sudden unexpected death in epilepsy that were differentially expressed. These proteins were associated with inhibition of EIF2 signalling (P-value of overlap = 1.29 × 10-8, z = -2.00) in non-sudden unexpected death in epilepsy. In sudden unexpected death in epilepsy, there were 10 activated pathways (top pathway: gluconeogenesis I, P-value of overlap = 3.02 × 10-6, z = 2.24) and 1 inhibited pathway (fatty acid beta-oxidation, P-value of overlap = 2.69 × 10-4, z = -2.00). Comparing sudden unexpected death in epilepsy and non-sudden unexpected death in epilepsy, 10 proteins were differentially expressed, but there were no associated signalling pathways. In both medullary regions, few proteins showed significant differences in pairwise comparisons. We identified altered proteins in the raphe and ventrolateral medulla of epilepsy patients, including some differentially expressed in sudden unexpected death in epilepsy cases. Altered signalling pathways in the dorsal raphe of sudden unexpected death in epilepsy indicate a shift in cellular energy production and activation of G-protein signalling, inflammatory response, stress response and neuronal migration/outgrowth. Future studies should assess the brain proteome in relation to additional clinical variables (e.g. recent tonic-clonic seizures) and in more of the reciprocally connected cortical and subcortical regions to better understand the pathophysiology of epilepsy and sudden unexpected death in epilepsy.

A Dichotomous Role for FABP7 in Sleep and Alzheimer's Disease Pathogenesis: A Hypothesis

Fatty acid binding proteins (FABPs) are a family of intracellular lipid chaperone proteins known to play critical roles in the regulation of fatty acid uptake and transport as well as gene expression. Brain-type fatty acid binding protein (FABP7) is enriched in astrocytes and has been implicated in sleep/wake regulation and neurodegenerative diseases; however, the precise mechanisms underlying the role of FABP7 in these biological processes remain unclear. FABP7 binds to both arachidonic acid (AA) and docosahexaenoic acid (DHA), resulting in discrete physiological responses. Here, we propose a dichotomous role for FABP7 in which ligand type determines the subcellular translocation of fatty acids, either promoting wakefulness aligned with Alzheimer's pathogenesis or promoting sleep with concomitant activation of anti-inflammatory pathways and neuroprotection. We hypothesize that FABP7-mediated translocation of AA to the endoplasmic reticulum of astrocytes increases astrogliosis, impedes glutamatergic uptake, and enhances wakefulness and inflammatory pathways via COX-2 dependent generation of pro-inflammatory prostaglandins. Conversely, we propose that FABP7-mediated translocation of DHA to the nucleus stabilizes astrocyte-neuron lactate shuttle dynamics, preserves glutamatergic uptake, and promotes sleep by activating anti-inflammatory pathways through the peroxisome proliferator-activated receptor-γ transcriptional cascade. Importantly, this model generates several testable hypotheses applicable to other neurodegenerative diseases, including amyotrophic lateral sclerosis and Parkinson's disease.

Brain Cell Type-Specific Nuclear Proteomics Is Imperative to Resolve Neurodegenerative Disease Mechanisms

Neurodegenerative diseases (NDs) involve complex cellular mechanisms that are incompletely understood. Emerging findings have revealed that disruption of nuclear processes play key roles in ND pathogenesis. The nucleus is a nexus for gene regulation and cellular processes that together, may underlie pathomechanisms of NDs. Furthermore, many genetic risk factors for NDs encode proteins that are either present in the nucleus or are involved in nuclear processes (for example, RNA binding proteins, epigenetic regulators, or nuclear-cytoplasmic transport proteins). While recent advances in nuclear transcriptomics have been significant, studies of the nuclear proteome in brain have been relatively limited. We propose that a comprehensive analysis of nuclear proteomic alterations of various brain cell types in NDs may provide novel biological and therapeutic insights. This may be feasible because emerging technical advances allow isolation and investigation of intact nuclei from post-mortem frozen human brain tissue with cell type-specific and single-cell resolution. Accordingly, nuclei of various brain cell types harbor unique protein markers which can be used to isolate cell-type specific nuclei followed by down-stream proteomics by mass spectrometry. Here we review the literature providing a rationale for investigating proteomic changes occurring in nuclei in NDs and then highlight the potential for brain cell type-specific nuclear proteomics to enhance our understanding of distinct cellular mechanisms that drive ND pathogenesis.