Cerebrospinal Fluid and Brain Proteoforms of the Granin Neuropeptide Family in Alzheimer's Disease

A compilation of reported alterations in the cerebrospinal fluid proteome in Alzheimer's disease

Alzheimer's disease is a multifaceted neurodegenerative disorder, with diverse underlying pathophysiological processes extending beyond amyloid-β and tau accumulation. The heterogeneity of Alzheimer's disease necessitates the identification of a broad array of biomarkers that capture the diverse mechanisms contributing to disease onset and progression. In this study, we systematically compiled and analysed cerebrospinal fluid proteomics data from omics studies utilizing mass spectrometry, Olink, or SomaScan platforms. Systematic literature searches for each platform revealed a total of 264 studies. From this, a set of 18 studies were selected based on sample size, number of markers analysed, and open data availability. We found a total of 1,448 differentially expressed proteins between Alzheimer's disease and amyloid negative controls across these datasets, with 635 being found in more than one study. A 'top' set of 61 differentially expressed proteins were consistently reported in at least six studies. Clustering and functional enrichment analysis of the top differentially expressed proteins indicated involvement in metabolic regulation, glutathione metabolism and proteins of the 14-3-3 family, reflecting importance of reactive oxygen species (ROS) response. Synaptic signalling processes were found to generally be downregulated. We further integrated the top differentially expressed proteins with results from a study on familial Alzheimer's disease cerebrospinal fluid to assess at which stage of disease progression these proteins change, highlighting markers shared between sporadic and familial Alzheimer's disease datasets. Lastly, we examine the overlap of the top differentially expressed proteins between cerebrospinal fluid and brain tissue using a publicly available database. This analysis provides a comprehensive overview of the Alzheimer's disease cerebrospinal fluid proteomic landscape, indicating changes in key pathways and cellular processes associated with Alzheimer's disease pathology. By integrating data from different platforms, we highlight reproducible protein changes that may serve as promising candidates for further biomarker research aimed at improving patient stratification, tracking disease progression, and assessing therapeutic interventions.

VGF and Its Derived Peptides in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by a progressive degeneration in the neurons of the frontal cortex, spinal cord, and brainstem, altering the correct release of neurotransmitters. The disease affects every muscle in the body and could cause death three to five years after symptoms first occur. There is currently no efficient treatment to stop the disease's progression. The lack of identification of potential therapeutic strategies is a consequence of the delayed diagnosis due to the absence of accurate ALS early biomarkers. Indeed, neurotransmitters altered in ALS are not measurable in body fluids at quantities that allow for testing, making their use as diagnostic tools a challenge. Contrarily, neuroproteins and neuropeptides are chemical messengers produced and released by neurons, and most of them have the potential to enter bodily fluids. To find out new possible ALS biomarkers, the research of neuropeptides and proteins is intensified using mass spectrometry and biochemical-based assays. Neuropeptides derived from the proVGF precursor protein act as signaling molecules within neurons. ProVGF and its derived peptides are expressed in the nervous and endocrine systems but are also widely distributed in body fluids such as blood, urine, and cerebrospinal fluid, making them viable options as disease biomarkers. To highlight the proVGF and its derived peptides' major roles as ALS diagnostic biomarkers, this review provides an overview of the VGF peptide alterations in spinal cord and body fluids and outlines the limitations of the reported investigations.

Brain Proteome Profiling Reveals Common and Divergent Signatures in Parkinson's Disease, Multiple System Atrophy, and Progressive Supranuclear Palsy

The molecular pathogenesis of degenerative parkinsonisms, including Parkinson's disease (PD), progressive supranuclear palsy (PSP), and Multiple system atrophy (MSA), remains largely unknown. To gain novel insight into molecular processes associated with these diseases, we conducted a proteome-wide expression study in prefrontal cortex tissue from a cohort of 181 individuals, comprising PD (N = 73), PSP (N = 18), MSA (N = 17) and healthy control (N = 73). Using marker gene profiles, we first assess the cellular composition of the samples and, subsequently, identify distinct protein signatures for each disease, while correcting for cell composition. Our findings indicate that all three diseases are characterized by a structural and/or functional loss of deep cortical neurons, while PD exhibits an additional decrease in somatostatin-expressing interneurons, as well as in endothelial cells. Differential protein expression analysis identified multiple proteins and pathways with disease-specific expression, some of which have previously been associated with parkinsonism or neurodegeneration in general. Notably, we observed a strong mitochondrial signature which was present in both PD and PSP, albeit of a different composition and most pronounced in PSP, but not in MSA where immunological/inflammation-related pathways dominated. Additionally, we identified protein signatures associated with the severity of α-synuclein pathology in PD and showed that these are highly enriched in an upregulation of mitochondrial processes, specifically related to oxidative phosphorylation and in particular respiratory complexes I and IV. We identify multiple novel signatures of protein expression, associated with PD, PSP, and MSA, as well as with the severity of α-synuclein pathology in the PD brain.

Recent Advances in Human Cerebrospinal Fluid Proteomics

Cerebrospinal fluid (CSF) proteomics has become an alternative that allows zooming-in where pathophysiological alterations are taking place, detecting protein mediators that might eventually be considered as potential biomarkers in neurological or psychiatric diseases. From a technological point of view, mass-spectrometry-based-proteomics as well as antibody/aptamer-based platforms allow the simultaneous monitoring of secreted and circulating proteins in a broad concentration range in a robust manner, generating innovative facets in biomarker validation. This chapter highlights recent discoveries in the field of CSF protein analysis, covering sample preparation methods for proteomic workflows, shotgun proteomics, subproteomics, and other omics applied to CSF.

Heterogeneity of cerebral atrophic rate in mild cognitive impairment and its interactive association with proteins related to microglia activity on longitudinal cognitive changes

BACKGROUND

Heterogeneity of cerebral atrophic rate commonly exists in mild cognitive impairment (MCI), which may be associated with microglia-involved neuropathology and have an influence on cognitive outcomes.

OBJECTIVE

We aim to explore the heterogeneity of cerebral atrophic rate among MCI and its association with plasma proteins related to microglia activity, with further investigation of their interaction effects on long-term cognition.

SUBJECTS

A total of 630 MCI subjects in the ADNI database were included, of which 260 subjects were available with baseline data on plasma proteins.

METHODS

Group-based multi-trajectory modeling (GBMT) was used to identify the latent classes with heterogeneous cerebral atrophic rates. Associations between latent classes and plasma proteins related to microglia activity were investigated with generalized linear models. Linear mixed effect models (LME) were implemented to explore the interaction effects between proteins related to microglia activity and identified latent classes on longitudinal cognitive changes.

RESULTS

Two latent classes were identified and labeled as the slow-atrophy class and the fast-atrophy class. Associations were found between such heterogeneity of atrophic rates and plasma proteins related to microglia activity, especially AXL receptor tyrosine kinase (AXL), CD40 antigen (CD40), and tumor necrosis factor receptor-like 2 (TNF-R2). Interaction effects on longitudinal cognitive changes showed that higher CD40 was associated with faster cognitive decline in the slow-atrophy class and higher AXL or TNF-R2 was associated with slower cognitive decline in the fast-atrophy class.

CONCLUSIONS

Heterogeneity of atrophic rates at the MCI stage is associated with several plasma proteins related to microglia activity, which show either protective or adverse effects on long-term cognition depending on the variability of atrophic rates.

Multifaceted Role of Specialized Neuropeptide-Intensive Neurons on the Selective Vulnerability to Alzheimer's Disease in the Human Brain

Regarding Alzheimer's disease (AD), specific neuronal populations and brain regions exhibit selective vulnerability. Understanding the basis of this selective neuronal and regional vulnerability is essential to elucidate the molecular mechanisms underlying AD pathology. However, progress in this area is currently hindered by the incomplete understanding of the intricate functional and spatial diversity of neuronal subtypes in the human brain. Previous studies have demonstrated that neuronal subpopulations with high neuropeptide (NP) co-expression are disproportionately absent in the entorhinal cortex of AD brains at the single-cell level, and there is a significant decline in hippocampal NP expression in naturally aging human brains. Given the role of NPs in neuroprotection and the maintenance of microenvironments, we hypothesize that neurons expressing higher levels of NPs (HNP neurons) possess unique functional characteristics that predispose them to cellular abnormalities, which can manifest as degeneration in AD with aging. To test this hypothesis, multiscale and spatiotemporal transcriptome data from ~1900 human brain samples were analyzed using publicly available datasets. The results indicate that HNP neurons experienced greater metabolic burden and were more prone to protein misfolding. The observed decrease in neuronal abundance during stages associated with a higher risk of AD, coupled with the age-related decline in the expression of AD-associated neuropeptides (ADNPs), provides temporal evidence supporting the role of NPs in the progression of AD. Additionally, the localization of ADNP-producing HNP neurons in AD-associated brain regions provides neuroanatomical support for the concept that cellular/neuronal composition is a key factor in regional AD vulnerability. This study offers novel insights into the molecular and cellular basis of selective neuronal and regional vulnerability to AD in human brains.

Transcriptome Signatures for Cognitive Resilience Among Individuals with Pathologically Confirmed Alzheimer Disease

INTRODUCTION

Limited success to date in development of drugs that target hallmark Alzheimer disease (AD) proteins as a means to slow AD-related cognitive decline has sparked interest in approaches focused on cognitive resilience. We sought to identify transcriptome signatures among brain donors with neuropathologically confirmed AD that distinguish those with cognitive impairment from those that were cognitively intact.

METHODS

We compared gene expression patterns in brain tissue from donors in four cohorts who were cognitively and pathologically normal (controls), met clinical and pathological criteria for AD (SymAD), or were cognitively normal prior to death despite pathological evidence of AD (cognitively resilient or AsymAD). Differentially expressed genes (DEGs) at the transcriptome-wide significance (TWS) level (P<10 -6 ) in the total sample and nominally significant (P<0.05) in at least two datasets were further evaluated in analyses testing association of gene expression with co-calibrated and harmonized cognitive domain scores and AD-related neuropathological traits.

RESULTS

We identified 52 TWS DEGs, including 14 that surpassed a significance threshold of P<5×10 -8 . The three most significant DEGs, ADAMTS2 (Log2 fold change [Log2FC]=0.46, P=2.94×10 -14 ), S100A4 (Log2FC=0.61, P=3.98×10 -11 ) and NRIP2 (Log2FC=0.32, P=9.52×10 -11 ) were up-regulated in SymAD compared to AsymAD brains. ADAMTS2 and SLC6A9 were also significantly and nominally differentially expressed between AsymAD cases and controls (FDR P=0.45 and FDR P=0.57, respectively). Significant associations (P<0.0038) were identified for executive function with expression of ADAMTS2 (P=4.15×10 -8 ) and ARSG (P=1.09×10 -3 ), and for memory with PRELP (P=3.92×10 -5 ) and EMP3 (P=7.75×10 -4 ), and for language with SLC38A2 (P=6.76×10 -5 ) and SLC6A9 (P=2.13 ×10 -3 ). Expression of ARSG and FHIP1B were associated with measures of Tau pathology (AT8: P=1.5×10 -3 , and pTau181: P=3.64×10 -3 , respectively), and SLC6A9 expression was associated with multiple pTau isoforms including pTau181 (P=1.5×10 -3 ) and pTau396 (P=2.05×10 -3 ). PRELP expression was associated with synaptic density (PSD.95: P=6.18 ×10 -6 ). DEGs were significantly enriched in pathways involving E2F targets, cholesterol homeostasis, and oxidative phosphorylation.

CONCLUSION

We identified multiple DEGs that differentiate neuropathologically confirmed AD cases with and without cognitive impairment prior to death. Expression of several of these genes was also associated with measures of cognitive performance and AD-related neuropathological traits, thus providing important insights into cognitive resilience mechanisms and strategies for delaying clinical symptoms of AD.

Novel plasma protein biomarkers: A time-dependent predictive model for Alzheimer's disease

BACKGROUND

The accurate prediction of Alzheimer's disease (AD) is crucial for the efficient management of its progression. The objective of this research was to construct a new risk predictive model utilizing novel plasma protein biomarkers for predicting AD incidence in the future and analyze their potential biological correlation with AD incidence.

METHODS

A cohort of 440 participants aged 60 years and older from the Alzheimer's Disease Neuroimaging Initiative (ADNI) longitudinal cohort was utilized. The baseline plasma proteomics data was employed to conduct Cox regression, LASSO regression, and cross-validation to identify plasma protein signatures predictive of AD risk. Subsequently, a multivariable Cox proportional hazards model based on these signatures was constructed. The performance of the risk prediction model was evaluated using time-dependent receiver operating characteristic (t-ROC) curves and Kaplan-Meier curves. Additionally, we analyzed the correlations between protein signature expression in plasma and predicted AD risk, the time of AD onset, the expression of protein signatures in cerebrospinal fluid (CSF), the expression of CSF and plasma biomarkers, and APOE ε4 genotypes. Colocalization and Mendelian randomization analyses was conducted to investigate the association between protein features and AD risk. GEO database was utilized to analyze the differential expression of protein features in the blood and brain of AD patients.

RESULTS

We identified seven protein signatures (APOE, CGA, CRP, CCL26, CCL20, NRCAM, and PYY) that independently predicted AD incidence in the future. The risk prediction model demonstrated area under the ROC curve (AUC) values of 0.77, 0.76, and 0.77 for predicting AD incidence at 4, 6, and 8 years, respectively. Furthermore, the model remained stable in the range of the 3rd to the 12th year (ROC ≥ 0.74). The low-risk group, as defined by the model, exhibited a significantly later AD onset compared to the high-risk group (P < 0.0001). Moreover, all protein signatures exhibited significant correlations with AD risk (P < 0.001) and the time of AD onset (P < 0.01). There was no strong correlation between the protein expression levels in plasma and CSF, as well as AD CSF biomarkers. APOE, CGA, and CRP exhibited significantly lower expression levels in APOE ε4 positive individuals (P < 0.05). Additionally, colocalization analysis reveals a significant association between AD and SNP loci in APOE. Mendelian randomization analysis shows a negative correlation between NRCAM and AD risk. Transcriptomic analysis indicates a significant downregulation of NRCAM and PYY in the peripheral blood of AD patients (P < 0.01), while APOE, CGA, and NRCAM are significantly downregulated in the brains of AD patients (P < 0.0001).

CONCLUSION

Our research has successfully identified protein signatures in plasma as potential risk biomarkers that can independently predict AD onset in the future. Notably, this risk prediction model has demonstrated commendable predictive performance and stability over time. These findings underscore the promising utility of plasma protein signatures in dynamically predicting the risk of AD, thereby facilitating early screening and intervention strategies.

Lower Plasma Levels of Selective VGF (Non-Acronymic) Peptides in Bipolar Disorder: Comparative Analysis Reveals Distinct Patterns across Mood Disorders and Healthy Controls

INTRODUCTION

Discriminating bipolar disorder (BD) from major depressive disorder (MDD) remains a challenging clinical task. Identifying specific peripheral biosignatures that can differentiate between BD and MDD would significantly increase diagnostic accuracy. Dysregulated neuroplasticity is implicated in BD and MDD, and psychotropic medications restore specific disrupted processes by increasing neurotrophic signalling. The nerve growth factor inducible vgf gene (non-acronymic) encodes a precursor protein named proVGF, which undergoes proteolytic processing to produce several VGF peptides, some of which were suggested to be implicated in mood disorders and have antidepressant effects. Since the presence of VGF peptides in humans has been exclusively investigated in brain and cerebrospinal fluid, we aimed to identify which VGF peptides are present in the plasma and to investigate whether their levels could differentiate BD from MDD as well as responders from non-responders to pharmacological interventions.

METHODS

VGF peptides were investigated in plasma from patients diagnosed with MDD (n = 37) or BD (n = 40 under lithium plus n = 29 never exposed to lithium), as well as healthy controls (HC; n = 36).

RESULTS

Three VGF peptides (TLQP-11, AQEE-14, and NAPP-19) were identified using spectrometry analysis of plasma from HC. These peptides were then measured in the entire sample using ELISA, which showed significantly lower levels of AQEE and NAPP in BD than in HC and MDD (p = 5.0 × 10-5, p = 0.001, respectively).

CONCLUSION

Our findings suggest that lower plasma levels of NAPP and AQEE are specifically associated with BD, thus possibly representing a diagnostic biomarker in mood disorders.

Dysregulated Cerebrospinal Fluid Proteome of Spinocerebellar Ataxia Type 2 and its Clinical Implications

BACKGROUND

Abnormalities in ataxin-2 associated with spinocerebellar ataxia type 2 (SCA2) may lead to widespread disruptions in the proteome. This study was performed to identify dysregulated proteome in SCA2 and to explore its clinical-radiological correlations.

METHODS

Cerebrospinal fluid (CSF) samples from 21 genetically confirmed SCA2 were subjected to shotgun proteome analysis using mass spectrometry (MS) and tandem mass tag (TMT)-based multiplexing. Proteins with at least 1.5-fold change in abundance were identified. Their relative abundance was measured using parallel reaction monitoring (PRM) and correlated against disease-related factors.

RESULTS

Eleven proteins were significantly upregulated in SCA2. They belonged to the family of cell adhesion molecules and granins. Their fold changes showed significant clinical, genetic, and radiological correlations.

CONCLUSIONS

Significant dysregulation of CSF proteome is seen in SCA2. The dysregulated protein may have potential use in clinical evaluation of patients with SCA2.

Interrogation of the human cortical peptidome uncovers cell-type specific signatures of cognitive resilience against Alzheimer's disease

Alzheimer's disease (AD) is characterised by age-related cognitive decline. Brain accumulation of amyloid-β plaques and tau tangles is required for a neuropathological AD diagnosis, yet up to one-third of AD-pathology positive community-dwelling elderly adults experience no symptoms of cognitive decline during life. Conversely, some exhibit chronic cognitive impairment in absence of measurable neuropathology, prompting interest into cognitive resilience-retained cognition despite significant neuropathology-and cognitive frailty-impaired cognition despite low neuropathology. Synapse loss is widespread within the AD-dementia, but not AD-resilient, brain. Recent evidence points towards critical roles for synaptic proteins, such as neurosecretory VGF, in cognitive resilience. However, VGF and related proteins often signal as peptide derivatives. Here, nontryptic peptidomic mass spectrometry was performed on 102 post-mortem cortical samples from individuals across cognitive and neuropathological spectra. Neuropeptide signalling proteoforms derived from VGF, somatostatin (SST) and protachykinin-1 (TAC1) showed higher abundance in AD-resilient than AD-dementia brain, whereas signalling proteoforms of cholecystokinin (CCK) and chromogranin (CHG) A/B and multiple cytoskeletal molecules were enriched in frail vs control brain. Integrating our data with publicly available single nuclear RNA sequencing (snRNA-seq) showed enrichment of cognition-related genes in defined cell-types with established links to cognitive resilience, including SST interneurons and excitatory intratelencephalic cells.

Diagnostic value of CSF chromogranin A to discriminate between Alzheimer's disease and dementia with Lewy bodies

BACKGROUND

Chromogranin A (CgA) seems to be involved in the pathophysiology of different neurodegenerative pathologies such as Alzheimer's disease (AD) and dementia with Lewy Bodies (DLB). CgA is present in the aggregates of amyloid plaques and in Lewy bodies but CgA also has a function in neuroinflammatory processes via microglia. Our objective was to determine if there is a difference in the CgA concentration in the cerebrospinal fluid (CSF) of AD and DLB patients and whether the CgA concentration can discriminate between the two diseases.

METHODS

Using the previously described AlphaLewyMA cohort, we included 117 patients with a CSF CgA assay: 15 control subjects (CS group), 64 DLB patients, 17 AD patients and 21 patients with both AD and probable DLB criteria (AD/DLB group). CgA concentration was assessed using the MSD platform.

RESULTS

CSF CgA was increased in the AD and AD/DLB groups compared with the DLB group (p = 0.0006 between AD and DLB, p = 0.0013 between AD/DLB and DLB). No significant difference in CgA concentration was found between DLB and CS. ROC curve analysis showed an area under the curve of 0.791 between AD and DLB. CgA concentrations were correlated with t-Tau and P-Tau regardless of the pathology (for Tau: p = 0.022 for AD; p < 0.0001 for DLB; p = 0.004 for AD/DLB; for P-Tau: p = 0.032 for AD; p < 0.0001 for DLB; p = 0.0009 for AD/DLB). Aβ42 was positively correlated with CgA in the DLB group but not in the AD and AD/DLB groups (for DLB: p < 0.0001; for AD: p = 0.57; for AD/DLB: p = 0.58).

CONCLUSIONS

CSF CgA concentrations are increased in AD but not in DLB and correlate with P-Tau and Tau whatever the disease. These results suggest a link between tauopathy/neurodegeneration and CgA.

Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics

Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.

Cerebrospinal fluid shotgun proteomics identifies distinct proteomic patterns in cerebral amyloid angiopathy rodent models and human patients

Cerebral amyloid angiopathy (CAA) is a form of small vessel disease characterised by the progressive deposition of amyloid β protein in the cerebral vasculature, inducing symptoms including cognitive impairment and cerebral haemorrhages. Due to their accessibility and homogeneous disease phenotypes, animal models are advantageous platforms to study diseases like CAA. Untargeted proteomics studies of CAA rat models (e.g. rTg-DI) and CAA patients provide opportunities for the identification of novel biomarkers of CAA. We performed untargeted, data-independent acquisition proteomic shotgun analyses on the cerebrospinal fluid of rTg-DI rats and wild-type (WT) littermates. Rodents were analysed at 3 months (n = 6/10), 6 months (n = 8/8), and 12 months (n = 10/10) for rTg-DI and WT respectively. For humans, proteomic analyses were performed on CSF of sporadic CAA patients (sCAA) and control participants (n = 39/28). We show recurring patterns of differentially expressed (mostly increased) proteins in the rTg-DI rats compared to wild type rats, especially of proteases of the cathepsin protein family (CTSB, CTSD, CTSS), and their main inhibitor (CST3). In sCAA patients, decreased levels of synaptic proteins (e.g. including VGF, NPTX1, NRXN2) and several members of the granin family (SCG1, SCG2, SCG3, SCG5) compared to controls were discovered. Additionally, several serine protease inhibitors of the SERPIN protein family (including SERPINA3, SERPINC1 and SERPING1) were differentially expressed compared to controls. Fifteen proteins were significantly altered in both rTg-DI rats and sCAA patients, including (amongst others) SCG5 and SERPING1. These results identify specific groups of proteins likely involved in, or affected by, pathophysiological processes involved in CAA pathology such as protease and synapse function of rTg-DI rat models and sCAA patients, and may serve as candidate biomarkers for sCAA.