Neurodegeneration and astrogliosis in the entorhinal cortex in Alzheimer's disease: Stereological layer-specific assessment and proteomic analysis

Mining Alzheimer's disease clinical data: reducing effects of natural aging for predicting progression and identifying subtypes

Introduction

Because Alzheimer's disease (AD) has significant heterogeneity in encephalatrophy and clinical manifestations, AD research faces two critical challenges: eliminating the impact of natural aging and extracting valuable clinical data for patients with AD.

Methods

This study attempted to address these challenges by developing a novel machine-learning model called tensorized contrastive principal component analysis (T-cPCA). The objectives of this study were to predict AD progression and identify clinical subtypes while minimizing the influence of natural aging.

Results

We leveraged a clinical variable space of 872 features, including almost all AD clinical examinations, which is the most comprehensive AD feature description in current research. T-cPCA yielded the highest accuracy in predicting AD progression by effectively minimizing the confounding effects of natural aging.

Discussion

The representative features and pathogenic circuits of the four primary AD clinical subtypes were discovered. Confirmed by clinical doctors in Tangdu Hospital, the plaques (18F-AV45) distribution of typical patients in the four clinical subtypes are consistent with representative brain regions found in four AD subtypes, which further offers novel insights into the underlying mechanisms of AD pathogenesis.

Integrative Multi-omics Analysis to Characterize Herpes Virus Infection Increases the Risk of Alzheimer's Disease

Evidence suggests that herpes virus infection is associated with an increased risk of Alzheimer's disease (AD), and innate and adaptive immunity plays an important role in the association. Although there have been many studies, the mechanism of the association is still unclear. This study aims to reveal the underlying molecular and immune regulatory network through multi-omics data and provide support for the study of the mechanism of infection and AD in the future. Here, we found that the herpes virus infection significantly increased the risk of AD. Genes associated with the occurrence and development of AD and genetically regulated by herpes virus infection are mainly enrichment in immune-related pathways. The 22 key regulatory genes identified by machine learning are mainly immune genes. They are also significantly related to the infiltration changes of 3 immune cell in AD. Furthermore, many of these genes have previously been reported to be linked, or potentially linked, to the pathological mechanisms of both herpes virus infection and AD. In conclusion, this study contributes to the study of the mechanisms related to herpes virus infection and AD, and indicates that the regulation of innate and adaptive immunity may be an effective strategy for preventing and treating herpes virus infection and AD. Additionally, the identified key regulatory genes, whether previously studied or newly discovered, may serve as valuable targets for prevention and treatment strategies.

Neuropathological stage-dependent proteome mapping of the olfactory tract in Alzheimer's disease: From early olfactory-related omics signatures to computational repurposing of drug candidates

Alzheimer's disease (AD) is the most common form of dementia, characterized by an early olfactory dysfunction, progressive memory loss, and behavioral deterioration. Albeit substantial progress has been made in characterizing AD-associated molecular and cellular events, there is an unmet clinical need for new therapies. In this study, olfactory tract proteotyping performed in controls and AD subjects (n = 17/group) showed a Braak stage-dependent proteostatic impairment accompanied by the progressive modulation of amyloid precursor protein and tau functional interactomes. To implement a computational repurposing of drug candidates with the capacity to reverse early AD-related olfactory omics signatures (OMSs), we generated a consensual OMSs database compiling differential omics datasets obtained by mass-spectrometry or RNA-sequencing derived from initial AD across the olfactory axis. Using the Connectivity Map-based drug repurposing approach, PKC, EGFR, Aurora kinase, Glycogen synthase kinase, and CDK inhibitors were the top pharmacologic classes capable to restore multiple OMSs, whereas compounds with targeted activity to inhibit PI3K, Insulin-like growth factor 1 (IGF-1), microtubules, and Polo-like kinase (PLK) represented a family of drugs with detrimental potential to induce olfactory AD-associated gene expression changes. To validate the potential therapeutic effects of the proposed drugs, in vitro assays were performed. These validation experiments revealed that pretreatment of human neuron-like SH-SY5Y cells with the EGFR inhibitor AG-1478 showed a neuroprotective effect against hydrogen peroxide-induced damage while the pretreatment with the Aurora kinase inhibitor Reversine reduced amyloid-beta (Aβ)-induced neurotoxicity. Taken together, our data pointed out that OMSs may be useful as substrates for drug repurposing to propose novel neuroprotective treatments against AD.

Proteomic analysis identifies HSP90AA1, PTK2B, and ANXA2 in the human entorhinal cortex in Alzheimer's disease: Potential role in synaptic homeostasis and Aβ pathology through microglial and astroglial cells

Alzheimer's disease (AD), the most prevalent neurodegenerative disorder worldwide, is clinically characterized by cognitive deficits. Neuropathologically, AD brains accumulate deposits of amyloid-β (Aβ) and tau proteins. Furthermore, these misfolded proteins can propagate from cell to cell in a prion-like manner and induce native proteins to become pathological. The entorhinal cortex (EC) is among the earliest areas affected by tau accumulation along with volume reduction and neurodegeneration. Neuron-glia interactions have recently come into focus; however, the role of microglia and astroglia in the pathogenesis of AD remains unclear. Proteomic approaches allow the determination of changes in the proteome to better understand the pathology underlying AD. Bioinformatic analysis of proteomic data was performed to compare ECs from AD and non-AD human brain tissue. To validate the proteomic results, western blot, immunofluorescence, and confocal studies were carried out. The findings revealed that the most disturbed signaling pathway was synaptogenesis. Because of their involvement in synapse function, relationship with Aβ and tau proteins and interactions in the pathway analysis, three proteins were selected for in-depth study: HSP90AA1, PTK2B, and ANXA2. All these proteins showed colocalization with neurons and/or astroglia and microglia and with pathological Aβ and tau proteins. In particular, ANXA2, which is overexpressed in AD, colocalized with amoeboid microglial cells and Aβ plaques surrounded by astrocytes. Taken together, the evidence suggests that unbalanced expression of HSP90AA1, PTK2B, and ANXA2 may play a significant role in synaptic homeostasis and Aβ pathology through microglial and astroglial cells in the human EC in AD.

Shared Manifold Regularized Joint Feature Selection for Joint Classification and Regression in Alzheimer's Disease Diagnosis

In Alzheimer's disease (AD) diagnosis, joint feature selection for predicting disease labels (classification) and estimating cognitive scores (regression) with neuroimaging data has received increasing attention. In this paper, we propose a model named Shared Manifold regularized Joint Feature Selection (SMJFS) that performs classification and regression in a unified framework for AD diagnosis. For classification, unlike the existing works that build least squares regression models which are insufficient in the ability of extracting discriminative information for classification, we design an objective function that integrates linear discriminant analysis and subspace sparsity regularization for acquiring an informative feature subset. Furthermore, the local data relationships are learned according to the samples' transformed distances to exploit the local data structure adaptively. For regression, in contrast to previous works that overlook the correlations among cognitive scores, we learn a latent score space to capture the correlations and employ the latent space to design a regression model with l2,1 -norm regularization, facilitating the feature selection in regression task. Moreover, the missing cognitive scores can be recovered in the latent space for increasing the number of available training samples. Meanwhile, to capture the correlations between the two tasks and describe the local relationships between samples, we construct an adaptive shared graph to guide the subspace learning in classification and the latent cognitive score learning in regression simultaneously. An efficient iterative optimization algorithm is proposed to solve the optimization problem. Extensive experiments on three datasets validate the discriminability of the features selected by SMJFS.

Human brain glycoform coregulation network and glycan modification alterations in Alzheimer's disease

Despite the importance of protein glycosylation to brain health, current knowledge of glycosylated proteoforms or glycoforms in human brain and their alterations in Alzheimer's disease (AD) is limited. Here, we report a proteome-wide glycoform profiling study of human AD and control brains using intact glycopeptide-based quantitative glycoproteomics coupled with systems biology. Our study identified more than 10,000 human brain N-glycoforms from nearly 1200 glycoproteins and uncovered disease signatures of altered glycoforms and glycan modifications, including reduced sialylation and N-glycan branching and elongation as well as elevated mannosylation and N-glycan truncation in AD. Network analyses revealed a higher-order organization of brain glycoproteome into networks of coregulated glycoforms and glycans and discovered glycoform and glycan modules associated with AD clinical phenotype, amyloid-β accumulation, and tau pathology. Our findings provide valuable insights into disease pathogenesis and a rich resource of glycoform and glycan changes in AD and pave the way forward for developing glycosylation-based therapies and biomarkers for AD.

Therapeutic effects of long-term HBOT on Alzheimer's disease neuropathologies and cognitive impairment in APPswe/PS1dE9 mice

Alzheimer's disease (AD) is the most common neurodegenerative disorder with the pathological hallmarks of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs) in the brain. Although there is a hope that anti-amyloid monoclonal antibodies may emerge as a new therapy for AD, the high cost and side effect is a big concern. Non-drug therapy is attracting more attention and may provide a better resolution for the treatment of AD. Given the fact that hypoxia contributes to the pathogenesis of AD, hyperbaric oxygen therapy (HBOT) may be an effective intervention that can alleviate hypoxia and improve AD. However, it remains unclear whether long-term HBOT intervention in the early stage of AD can slow AD progression and ultimately prevent cognitive impairment in this disease. In this study we applied consecutive 3-month HBOT interventions on 3-month-old APPswe/PS1dE9 AD mice which represent the early stage of AD. When the APPswe/PS1dE9 mice at 9-month-old which represent the disease stage we measured cognitive function, 24-h blood oxygen saturation, Aβ and tau pathologies, vascular structure and function, and neuroinflammation in APPswe/PS1dE9 mice. Our results showed that long-term HBOT can attenuate the impairments in cognitive function observed in 9-month-old APPswe/PS1dE9 mice. Most importantly, HBOT effectively reduced the progression of Aβ plaques deposition, hyperphosphorylated tau protein aggregation, and neuronal and synaptic degeneration in the AD mice. Further, long-term HBOT was able to enhance blood oxygen saturation level. Besides, long-term HBOT can improve vascular structure and function, and reduce neuroinflammation in AD mice. This study is the first to demonstrate that long-term HBOT intervention in the early stage of AD can attenuate cognitive impairment and AD-like pathologies. Overall, these findings highlight the potential of long-term HBOT as a disease-modifying approach for AD treatment.

Proteoform Analysis of the Human Olfactory System: A Window into Neurodegenerative Diseases

Background: Very little is known about the proteome of the human olfactory system and how diseases associated with olfactory dysfunctions can affect it. With this review, we try to summarize the existing literature on the use of this technique for a better understanding of the neurodegenerative disease process. Methods: We used the PubMed database and found different articles which were then selected independently by three authors. Results: We found 157 articles, of which, after careful selection, only 30 were analyzed in this review. We presented all the associations identified between the protein/pathway alterations neurodegenerative diseases and SARS-CoV-2 infection. Conclusions: We think that the proteome of the olfactory system through blood, saliva, and mucus analysis could be a new way to better understand, diagnose, and finally treat neurodegenerative diseases.

Similar brain proteomic signatures in Alzheimer's disease and epilepsy

The prevalence of epilepsy is increased among Alzheimer's Disease (AD) patients and cognitive impairment is common among people with epilepsy. Epilepsy and AD are linked but the shared pathophysiological changes remain poorly defined. We aim to identify protein differences associated with epilepsy and AD using published proteomics datasets. We observed a highly significant overlap in protein differences in epilepsy and AD: 89% (689/777) of proteins altered in the hippocampus of epilepsy patients were significantly altered in advanced AD. Of the proteins altered in both epilepsy and AD, 340 were altered in the same direction, while 216 proteins were altered in the opposite direction. Synapse and mitochondrial proteins were markedly decreased in epilepsy and AD, suggesting common disease mechanisms. In contrast, ribosome proteins were increased in epilepsy but decreased in AD. Notably, many of the proteins altered in epilepsy interact with tau or are regulated by tau expression. This suggests that tau likely mediates common protein changes in epilepsy and AD. Immunohistochemistry for Aβ and multiple phosphorylated tau species (pTau396/404, pTau217, pTau231) showed a trend for increased intraneuronal pTau217 and pTau231 but no phosphorylated tau aggregates or amyloid plaques in epilepsy hippocampal sections. Our results provide insights into common mechanisms in epilepsy and AD and highlights the potential role of tau in mediating common pathological protein changes in epilepsy and AD.

Gene Expression at the Tripartite Synapse: Bridging the Gap Between Neurons and Astrocytes

Astrocytes, a major class of glial cells, are an important element at the synapse where they engage in bidirectional crosstalk with neurons to regulate numerous aspects of neurotransmission, circuit function, and behavior. Mutations in synapse-related genes expressed in both neurons and astrocytes are central factors in a vast number of neurological disorders, making the proteins that they encode prominent targets for therapeutic intervention. Yet, while the roles of many of these synaptic proteins in neurons are well established, the functions of the same proteins in astrocytes are largely unknown. This gap in knowledge must be addressed to refine therapeutic approaches. In this chapter, we integrate multiomic meta-analysis and a comprehensive overview of current literature to show that astrocytes express an astounding number of genes that overlap with the neuronal and synaptic transcriptomes. Further, we highlight recent reports that characterize the expression patterns and potential novel roles of these genes in astrocytes in both physiological and pathological conditions, underscoring the importance of considering both cell types when investigating the function and regulation of synaptic proteins.

Synaptic Involvement of the Human Amygdala in Parkinson's Disease

α-Synuclein, a protein mostly present in presynaptic terminals, accumulates neuropathologically in Parkinson's disease in a 6-stage sequence and propagates in the nervous system in a prion-like manner through neurons and glia. In stage 3, the substantia nigra are affected, provoking motor symptoms and the amygdaloid complex, leading to different nonmotor symptoms; from here, synucleinopathy spreads to the temporal cortex and beyond. The expected increase in Parkinson's disease incidence accelerates the need for detection biomarkers; however, the heterogeneity of this disease, including pathological aggregates and pathophysiological pathways, poses a challenge in the search for new therapeutic targets and biomarkers. Proteomic analyses are lacking, and the literature regarding synucleinopathy, neural and glial involvement, and volume of the human amygdaloid complex is controversial. Therefore, the present study combines both proteomic and stereological probes. Data-independent acquisition-parallel accumulation of serial fragmentation proteomic analysis revealed a remarkable proteomic impact, especially at the synaptic level in the human amygdaloid complex in Parkinson's disease. Among the 199 differentially expressed proteins, guanine nucleotide-binding protein G(i) subunit alpha-1 (GNAI1), elongation factor 1-alpha 1 (EEF1A1), myelin proteolipid protein (PLP1), neuroplastin (NPTN), 14-3-3 protein eta (YWHAH), gene associated with retinoic and interferon-induced mortality 19 protein (GRIM19), and orosomucoid-2 (ORM2) stand out as potential biomarkers in Parkinson's disease. Stereological analysis, however, did not reveal alterations regarding synucleinopathy, neural or glial populations, or volume changes. To our knowledge, this is the first proteomic study of the human amygdaloid complex in Parkinson's disease, and it identified possible biomarkers of the disease. Lewy pathology could not be sufficient to cause neurodegeneration or alteration of microglial and astroglial populations in the human amygdaloid complex in Parkinson's disease. Nevertheless, damage at the proteomic level is manifest, showing up significant synaptic involvement.

Lysosomal proteomics reveals mechanisms of neuronal apoE4associated lysosomal dysfunction

ApoE4 is the primary risk factor for Alzheimer's Disease. While apoE is primarily expressed by astrocytes, AD pathology including endosomal abnormalities and mitochondrial dysfunction first occurs in neurons. Lysosomes are poised at the convergence point between these features. We find that apoE4-expressing cells exhibit lysosomal alkalinization, reduced lysosomal proteolysis, and impaired mitophagy. To identify driving factors for this lysosomal dysfunction, we performed quantitative lysosomal proteome profiling. This revealed that apoE4 expression results in lysosomal depletion of Lgals3bp and accumulation of Tmed5 in both Neuro-2a cells and postmitotic human neurons. Modulating the expression of both proteins affected lysosomal function, with Tmed5 knockdown rescuing lysosomal alkalinization in apoE4 cells, and Lgals3bp knockdown causing lysosomal alkalinization and reduced lysosomal density in apoE3 cells. Taken together, our work reveals that apoE4 exerts gain-of-toxicity by alkalinizing the lysosomal lumen, pinpointing lysosomal Tmed5 accumulation and Lgals3bp depletion as apoE4-associated drivers for this phenotype.

A Nanodisc-Paved Biobridge Facilitates Stem Cell Membrane Fusogenicity for Intracerebral Shuttling and Bystander Effects

Mesenchymal stem cell (MSC) therapies experience steadfast clinical advances but are still hindered by inefficient site-specific migration. An adaptable MSC membrane fusogenicity technology is conceptualized for lipid raft-mediated targeting ligand embedding by using toolkits of discoidal high-density lipoprotein (HDL)-containing biomimicking 4F peptides. According to the pathological clues of brain diseases, the vascular cell adhesion molecule 1 specialized VBP peptide is fused with 4F to assemble 4F-VBP (HDL), which acts as a biobridge and transfers VBP onto the living cell membrane via lipid rafts for surface engineering of MSCs in suspension. When compared with the membrane-modifying strategies of PEGylated phospholipids, 4F-VBP (HDL) provides a 3.86 higher linkage efficiency to obtain MSCs4F-VBP(HDL) , which can recognize and adhere to the inflammatory endothelium for efficient blood-brain barrier crossing and brain accumulation. In APPswe/PSEN1dE9 mice with Alzheimer's disease (AD), the transcriptomic analysis reveals that systemic administration of MSCs4F-VBP(HDL) can activate pathways associated with neuronal activity and diminish neuroinflammation for rewiring AD brains. This customizable HDL-mediated membrane fusogenicity platform primes MSC inflammatory brain delivery, which can be expanded to other disease treatments by simply fusing 4F with relevant ligands for living cell engineering.

Human amygdala involvement in Alzheimer's disease revealed by stereological and dia-PASEF analysis

Alzheimer's disease (AD) is characterized by the accumulation of pathological amyloid-β (Aβ) and Tau proteins. According to the prion-like hypothesis, both proteins can seed and disseminate through brain regions through neural connections and glial cells. The amygdaloid complex (AC) is involved early in the disease, and its widespread connections with other brain regions indicate that it is a hub for propagating pathology. To characterize changes in the AC as well as the involvement of neuronal and glial cells in AD, a combined stereological and proteomic analysis was performed in non-Alzheimer's disease and AD human samples. The synaptic alterations identified by proteomic data analysis could be related to the volume reduction observed in AD by the Cavalieri probe without neuronal loss. The pathological markers appeared in a gradient pattern with the medial region (cortical nucleus, Co) being more affected than lateral regions, suggesting the relevance of connections in the distribution of the pathology among different brain regions. Generalized astrogliosis was observed in every AC nucleus, likely related to deposits of pathological proteins. Astrocytes might mediate phagocytic microglial activation, whereas microglia might play a dual role since protective and toxic phenotypes have been described. These results highlight the potential participation of the amygdala in the disease spreading from/to olfactory areas, the temporal lobe and beyond. Proteomic data are available via ProteomeXchange with identifier PXD038322.

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.

Not every estimate counts - evaluation of cell composition estimation approaches in brain bulk tissue data

BACKGROUND

Variation in cell composition can dramatically impact analyses in bulk tissue samples. A commonly employed approach to mitigate this issue is to adjust statistical models using estimates of cell abundance derived directly from omics data. While an arsenal of estimation methods exists, the applicability of these methods to brain tissue data and whether or not cell estimates can sufficiently account for confounding cellular composition has not been adequately assessed.

METHODS

We assessed the correspondence between different estimation methods based on transcriptomic (RNA sequencing, RNA-seq) and epigenomic (DNA methylation and histone acetylation) data from brain tissue samples of 49 individuals. We further evaluated the impact of different estimation approaches on the analysis of H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-seq) data from entorhinal cortex of individuals with Alzheimer's disease and controls.

RESULTS

We show that even closely adjacent tissue samples from the same Brodmann area vary greatly in their cell composition. Comparison across different estimation methods indicates that while different estimation methods applied to the same data produce highly similar outcomes, there is a surprisingly low concordance between estimates based on different omics data modalities. Alarmingly, we show that cell type estimates may not always sufficiently account for confounding variation in cell composition.

CONCLUSIONS

Our work indicates that cell composition estimation or direct quantification in one tissue sample should not be used as a proxy to the cellular composition of another tissue sample from the same brain region of an individual-even if the samples are directly adjacent. The highly similar outcomes observed among vastly different estimation methods, highlight the need for brain benchmark datasets and better validation approaches. Finally, unless validated through complementary experiments, the interpretation of analyses outcomes based on data confounded by cell composition should be done with great caution, and ideally avoided all together.

Orthogonal latent space learning with feature weighting and graph learning for multimodal Alzheimer's disease diagnosis

Recent studies have shown that multimodal neuroimaging data provide complementary information of the brain and latent space-based methods have achieved promising results in fusing multimodal data for Alzheimer's disease (AD) diagnosis. However, most existing methods treat all features equally and adopt nonorthogonal projections to learn the latent space, which cannot retain enough discriminative information in the latent space. Besides, they usually preserve the relationships among subjects in the latent space based on the similarity graph constructed on original features for performance boosting. However, the noises and redundant features significantly corrupt the graph. To address these limitations, we propose an Orthogonal Latent space learning with Feature weighting and Graph learning (OLFG) model for multimodal AD diagnosis. Specifically, we map multiple modalities into a common latent space by orthogonal constrained projection to capture the discriminative information for AD diagnosis. Then, a feature weighting matrix is utilized to sort the importance of features in AD diagnosis adaptively. Besides, we devise a regularization term with learned graph to preserve the local structure of the data in the latent space and integrate the graph construction into the learning processing for accurately encoding the relationships among samples. Instead of constructing a similarity graph for each modality, we learn a joint graph for multiple modalities to capture the correlations among modalities. Finally, the representations in the latent space are projected into the target space to perform AD diagnosis. An alternating optimization algorithm with proved convergence is developed to solve the optimization objective. Extensive experimental results show the effectiveness of the proposed method.

Molecular Mechanisms Underlying Neuroinflammation Elicited by Occupational Injuries and Toxicants

Occupational injuries and toxicant exposures lead to the development of neuroinflammation by activating distinct mechanistic signaling cascades that ultimately culminate in the disruption of neuronal function leading to neurological and neurodegenerative disorders. The entry of toxicants into the brain causes the subsequent activation of glial cells, a response known as 'reactive gliosis'. Reactive glial cells secrete a wide variety of signaling molecules in response to neuronal perturbations and thus play a crucial role in the progression and regulation of central nervous system (CNS) injury. In parallel, the roles of protein phosphorylation and cell signaling in eliciting neuroinflammation are evolving. However, there is limited understanding of the molecular underpinnings associated with toxicant- or occupational injury-mediated neuroinflammation, gliosis, and neurological outcomes. The activation of signaling molecules has biological significance, including the promotion or inhibition of disease mechanisms. Nevertheless, the regulatory mechanisms of synergism or antagonism among intracellular signaling pathways remain elusive. This review highlights the research focusing on the direct interaction between the immune system and the toxicant- or occupational injury-induced gliosis. Specifically, the role of occupational injuries, e.g., trips, slips, and falls resulting in traumatic brain injury, and occupational toxicants, e.g., volatile organic compounds, metals, and nanoparticles/nanomaterials in the development of neuroinflammation and neurological or neurodegenerative diseases are highlighted. Further, this review recapitulates the recent advancement related to the characterization of the molecular mechanisms comprising protein phosphorylation and cell signaling, culminating in neuroinflammation.

S100A6 Protein-Expression and Function in Norm and Pathology

S100A6, also known as calcyclin, is a calcium-binding protein belonging to the S100 protein family. It was first identified and purified more than 30 years ago. Initial structural studies, focused mostly on the mode and affinity of Ca²⁺ binding and resolution of the resultant conformational changes, were soon complemented by research on its expression, localization and identification of binding partners. With time, the use of biophysical methods helped to resolve the structure and versatility of S100A6 complexes with some of its ligands. Meanwhile, it became clear that S100A6 expression was altered in various pathological states and correlated with the stage/progression of many diseases, including cancers, indicative of its important, and possibly causative, role in some of these diseases. This, in turn, prompted researchers to look for the mechanism of S100A6 action and to identify the intermediary signaling pathways and effectors. After all these years, our knowledge on various aspects of S100A6 biology is robust but still incomplete. The list of S100A6 ligands is growing all the time, as is our understanding of the physiological importance of these interactions. The present review summarizes available data concerning S100A6 expression/localization, interaction with intracellular and extracellular targets, involvement in Ca²⁺-dependent cellular processes and association with various pathologies.

Quantitative optical coherence microscopy of neuron morphology in human entorhinal cortex

Introduction

The size and shape of neurons are important features indicating aging and the pathology of neurodegenerative diseases. Despite the significant advances of optical microscopy, quantitative analysis of the neuronal features in the human brain remains largely incomplete. Traditional histology on thin slices bears tremendous distortions in three-dimensional reconstruction, the magnitude of which are often greater than the structure of interest. Recently development of tissue clearing techniques enable the whole brain to be analyzed in small animals; however, the application in the human remains challenging.

Methods

In this study, we present a label-free quantitative optical coherence microscopy (OCM) technique to obtain the morphological parameters of neurons in human entorhinal cortex (EC). OCM uses the intrinsic back-scattering property of tissue to identify individual neurons in 3D. The area, length, width, and orientation of individual neurons are quantified and compared between layer II and III in EC.

Results

The high-resolution mapping of neuron size, shape, and orientation shows significant differences between layer II and III neurons in EC. The results are validated by standard Nissl staining of the same samples.

Discussion

The quantitative OCM technique in our study offers a new solution to analyze variety of neurons and their organizations in the human brain, which opens new insights in advancing our understanding of neurodegenerative diseases.

Synapsin 1 Ameliorates Cognitive Impairment and Neuroinflammation in Rats with Alzheimer's Disease: An Experimental and Bioinformatics Study

BACKGROUND

Alzheimer's disease (AD) is a persistent neuropathological injury that manifests via neuronal/synaptic death, age spot development, tau hyperphosphorylation, neuroinflammation, and apoptosis. Synapsin 1 (SYN1), a neuronal phosphoprotein, is believed to be responsible for the pathology of AD.

OBJECTIVE

This study aimed to elucidate the exact role of SYN1 in ameliorating AD and its potential regulatory mechanisms.

METHODS

The AD dataset GSE48350 was downloaded from the GEO database, and SYN1 was focused on differential expression analysis and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. After establishing an AD rat model, they were treated with RNAi lentivirus to trigger SYN1 overexpression. The amelioration of SYN1 in AD-associated behavior was validated using multiple experiments (water maze test and object recognition test). SYN1's repairing effect on the important factors in AD was confirmed by detecting the concentration of inflammatory factors (interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α), neurotransmitters (acetylcholine (ACh), dopamine (DA), and 5-hydroxytryptophan (5-HT)) and markers of oxidative stress (glutathione (GSH), malondialdehyde (MDA), reactive oxygen species (ROS)). Molecular biology experiments (qRT-PCR and western blot) were performed to examine AD-related signaling pathways after SYN1 overexpression.

RESULTS

Differential expression analysis yielded a total of 545 differentially expressed genes, of which four were upregulated and 541 were downregulated. The enriched pathways were basically focused on synaptic functions, and the analysis of the protein- protein interaction network focused on the key genes in SYN1. SYN1 significantly improved the spatial learning and memory abilities of AD rats. This enhancement was reflected in the reduced escape latency of the rats in the water maze, the significantly extended dwell time in the third quadrant, and the increased number of crossings. Furthermore, the results of the object recognition test revealed reduced time for rats to explore familiar and new objects. After SYN1 overexpression, the cAMP signaling pathway was activated, the phosphorylation levels of the CREB and PKA proteins were elevated, and the secretion of neurotransmitters such as ACh, DA, and 5-HT was promoted. Furthermore, oxidative stress was suppressed, as supported by decreased levels of MDA and ROS. Regarding inflammatory factors, the levels of IL-6, IL-1β, and TNF-α were significantly reduced in AD rats with SYN1 overexpression.

CONCLUSION

SYN1 overexpression improves cognitive function and promotes the release of various neurotransmitters in AD rats by inhibiting oxidative stress and inflammatory responses through cAMP signaling pathway activation. These findings may provide a theoretical basis for the targeted diagnosis and treatment of AD.