Single-cell RNA sequencing reveals B cell-related molecular biomarkers for Alzheimer's disease

Peripheral blood immune cell phenotypes and Alzheimer's disease: A mediation Mendelian randomization study

BackgroundAlzheimer's disease (AD) is a debilitating neurodegenerative disorder. Although peripheral immune cells have been implicated in the pathology of AD, the causal relationship between peripheral blood immune cells and AD remains to be fully elucidated.ObjectiveTo examine the association between peripheral blood immune cell phenotypes and AD, mediated by peripheral blood metabolite, a two-step Mendelian randomization (MR) analysis was performed.MethodsSummary statistics were obtained from the two largest independent cohorts. We explored bidirectional univariable MR analysis to explore causal associations and assessed the mediated proportion of peripheral blood metabolite phenotypes.ResultsThe proportion of IgD + CD38- B cells (Bm1) were found to increase the risk of AD in both the FinnGen database (p = 0.033) and the UK Biobank (p = 0.034). Conversely, hematopoietic stem cells were associated with a decreased risk of AD in the FinnGen database (p = 0.045) and the UK Biobank (p = 0.017). Mediation analysis revealed indirect effects of the proportion of Bm1 on AD through cysteine levels (β = 5 × 10-3), Acetylcarnitine (C2) to propionylcarnitine (C3) ratio (β = 4.5 × 10-3), and Gamma-glutamyl-alpha-lysine levels (β = 2.6 × 10-3), with mediated proportion of 19.4%, 16.9% and 9.6% of the total effect, respectively. Additionally, hematopoietic stem cells influenced AD through Glycolithocholate sulfate levels (β = 1.5 × 10-3), with a mediated proportion of 3.5%.ConclusionsOur findings demonstrate that two peripheral blood immune cell phenotypes impact the risk of AD. These immune cells may influence AD through various peripheral blood metabolite, identifying potential intervention targets for individuals at risk.

Fingolimod ameliorates amyloid deposition and neurodegeneration in APP/PS1 mouse model of Alzheimer's disease

INTRODUCTION

The immune system plays a critical role in regulating amyloid-beta (Aβ) metabolism in Alzheimer's Disease (AD). Both T and B lymphocytes are involved in the pathogenesis of AD. The sphingosine-1-phosphate (S1P) receptor modulator fingolimod used in the treatment of multiple sclerosis, can promote lymphocyte homing, potentially reducing the infiltration of peripheral lymphocytes into the brain.

METHODS

In this study, 8-month-old APP/PS1 mice were orally administered fingolimod at a dose of 1 mg/kg/day or saline as a control for 2 months. After treatment, the mice were subjected to behavioral tests, pathological examinations, and biochemical analyses to evaluate behavioral deficits and AD-type pathologies.

RESULTS

Fingolimod inhibits the infiltration of peripheral lymphocytes into the brain and reduces neuroinflammation. Fingolimod enhances cognitive function and alleviates brain Aβ deposition. Additionally, fingolimod treatment mitigates other AD-related pathologies, including Tau hyperphosphorylation, neuroinflammation, and neurodegeneration. Proteomic analysis further confirms the therapeutic effects of fingolimod in AD, reflected by the downregulation of proteins involved in multiple AD-associated pathways.

DISCUSSION

This study illustrates that fingolimod effectively ameliorates multiple pathological features of AD, highlighting its potential as a promising therapeutic candidate for the disease.

Bone marrow mesenchymal stem cells alleviate neurological dysfunction by reducing autophagy damage via downregulation of SYNPO2 in neonatal hypoxic-ischemic encephalopathy rats

Neonatal hypoxic-ischemic encephalopathy (HIE) is worsened by autophagy-induced neuronal damage, with SYNPO2 playing a key role in this process. This study investigates the involvement of SYNPO2 in neuronal autophagy and explores the potential of bone marrow mesenchymal stem cells (BMSCs) to alleviate HIE-induced dysfunction by inhibiting SYNPO2-mediated autophagy. Using in vitro and in vivo neonatal HIE models, we observed an upregulation of SYNPO2 expression, accompanied by increased neuronal injury and aggregation of autophagy-related proteins. Intervention with BMSCs effectively reduced SYNPO2 expression, and SYNPO2 depression mitigated neuroautophagic damage and improved neurological dysfunctions. Moreover, SYNPO2 overexpression exacerbated neuroautophagy despite BMSC treatment, while SYNPO2 depletion notably reduced neuroautophagic damage and alleviated cognitive impairments, retaining the neuroprotective efficacy of BMSC treatment. These findings confirm the role of BMSCs in attenuating HIE injury by suppressing neuroautophagy and provide insights into the mechanistic involvement of SYNPO2. Ultimately, this study identifies SYNPO2 as a novel therapeutic target for neonatal HIE and supports the clinical potential of BMSCs in HIE management.

A single-cell atlas to map sex-specific gene-expression changes in blood upon neurodegeneration

The clinical course and treatment of neurodegenerative disease are complicated by immune-system interference and chronic inflammatory processes, which remain incompletely understood. Mapping immune signatures in larger human cohorts through single-cell gene expression profiling supports our understanding of observed peripheral changes in neurodegeneration. Here, we employ single-cell gene expression profiling of over 909k peripheral blood mononuclear cells (PBMCs) from 121 healthy individuals, 48 patients with mild cognitive impairment (MCI), 46 with Parkinson's disease (PD), 27 with Alzheimer's disease (AD), and 15 with both PD and MCI. The dataset is interactively accessible through a freely available website ( https://www.ccb.uni-saarland.de/adrcsc ). In this work, we identify disease-associated changes in blood cell type composition and the gene expression in a sex-specific manner, offering insights into peripheral and solid tissue signatures in AD and PD.

Peripheral and central neuroimmune mechanisms in Alzheimer's disease pathogenesis

Alzheimer's disease (AD) poses a growing global health challenge as populations age. Recent research highlights the crucial role of peripheral immunity in AD pathogenesis. This review explores how blood-brain barrier disruption allows peripheral immune cells to infiltrate the central nervous system (CNS), worsening neuroinflammation and disease progression. We examine recent findings on interactions between peripheral immune cells and CNS-resident microglia, forming a self-perpetuating inflammatory cycle leading to neuronal dysfunction. Moreover, this review emphasizes recent developments in the dysregulation of immune factors from both the periphery and CNS, and their impact on AD progression. With ongoing research and development of new therapeutic strategies, this review underscores the importance of modulating interactions between the peripheral immune system and CNS in AD therapy.

Biomarker Identification for Alzheimer's Disease Using a Multi-Filter Gene Selection Approach

There is still a lack of effective therapies for Alzheimer's disease (AD), the leading cause of dementia and cognitive decline. Identifying reliable biomarkers and therapeutic targets is crucial for advancing AD research. In this study, we developed an aggregative multi-filter gene selection approach to identify AD biomarkers. This method integrates hub gene ranking techniques, such as degree and bottleneck, with feature selection algorithms, including Random Forest and Double Input Symmetrical Relevance, and applies ranking aggregation to improve accuracy and robustness. Five publicly available AD-related microarray datasets (GSE48350, GSE36980, GSE132903, GSE118553, and GSE5281), covering diverse brain regions like the hippocampus and frontal cortex, were analyzed, yielding 803 overlapping differentially expressed genes from 464 AD and 492 normal cases. An independent dataset (GSE109887) was used for external validation. The approach identified 50 prioritized genes, achieving an AUC of 86.8 in logistic regression on the validation dataset, highlighting their predictive value. Pathway analysis revealed involvement in critical biological processes such as synaptic vesicle cycles, neurodegeneration, and cognitive function. These findings provide insights into potential therapeutic targets for AD.

Integrating Bulk and Single-Cell Transcriptomic Data to Identify Ferroptosis-Associated Inflammatory Gene in Alzheimer's Disease

Background

Ferroptosis is a form of programmed cell death triggered by iron-dependent lipid peroxidation, characterized by iron accumulation and elevated reactive oxygen species (ROS), leading to cell membrane damage. It is associated with a variety of diseases. However, the cellular and molecular links between ferroptosis, immune inflammation, and the brain-peripheral blood axis in Alzheimer's disease (AD) remain unclear.

Methods

We integrated bulk RNA-seq data from AD brain tissue and peripheral blood and refined the screening of AD candidate genes through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and other approaches. Additionally, we analyzed single-cell RNA-seq (scRNA-seq) data from AD patients' brain tissue and peripheral blood, combined with scRNA-seq data from experimental autoimmune encephalomyelitis (EAE) mouse brain tissue. This enabled us to explore AD-related molecular mechanisms from a cell-type-specific perspective. Finally, candidate genes were validated in ferroptosis models using reverse transcription quantitative PCR (RT-qPCR) and immunofluorescence methods.

Results

Bulk RNA-seq analysis identified SLC11A1, an inflammatory gene associated with AD. Single-cell RNA-seq analysis further revealed that SLC11A1 expression was significantly elevated in the pro-inflammatory (M1-type) microglia and peripheral blood monocytes in AD. Moreover, we identified a microglial subpopulation in AD M1-type microglia that was highly associated with ferroptosis. This subpopulation simultaneously expressed characteristic markers of peripheral blood monocytes, suggesting that these cells may originate from peripheral blood monocytes, thereby triggering neuroinflammation through the ferroptosis pathway. Cell experiments confirmed that SLC11A1 was significantly upregulated in inflammatory microglia induced by ferroptosis.

Conclusion

This study reveals the key role of SLC11A1 in AD, particularly in the context of ferroptosis and immune inflammation. It provides a novel molecular mechanistic perspective and offers potential targets for future therapeutic strategies.

Bioinformatics insights into mitochondrial and immune gene regulation in Alzheimer's disease

BACKGROUND

There is growing evidence that the pathogenesis of Alzheimer's disease is closely linked to the resident innate immune cells of the central nervous system, including microglia and astrocytes. Mitochondrial dysfunction in microglia has also been reported to play an essential role in the pathogenesis of AD and other neurological diseases. Therefore, finding the mitochondrial and immune-related gene (MIRG) signatures in AD can be significant in diagnosing and treating AD.

METHODS

In this study, the intersection of the differentially expressed genes (DEGs) from the GSE109887 cohort, immune-related genes (IRGs) obtained from WGCNA analysis, and mitochondria-related genes (MRGs) was taken to identify mitochondria-immune-related genes (MIRGs). Then, using machine learning algorithms, biomarkers with good diagnostic value were selected, and a nomogram was constructed. Subsequently, we further analyzed the signaling pathways and potential biological mechanisms of the biomarkers through gene set enrichment analysis, prediction of transcription factors (TFs), miRNAs, and drug prediction.

RESULTS

Using machine learning algorithms, five biomarkers (TSPO, HIGD1A, NDUFAB1, NT5DC3, and MRPS30) were successfully identified, and a nomogram model with strong diagnostic ability and accuracy (AUC > 0.9) was constructed. In addition, single-gene enrichment analysis revealed that NDUFAB1 was significantly enriched in pathways associated with diseases, such as Alzheimer's and Parkinson's, providing valuable insights for future clinical research on Alzheimer's in the context of mitochondrial-immune interactions. Interestingly, brain tissue pathology showed neuronal atrophy and demyelination in AD mice, along with a reduction in Nissl bodies. Furthermore, the escape latency of AD mice was significantly longer than that of the control group. After platform removal, there was a notable increase in the path complexity and time required to reach the target quadrant, suggesting a reduction in spatial memory capacity in AD mice. Moreover, qRT-PCR validation confirmed that the mRNA expression of the five biomarkers was consistent with bioinformatics results. In AD mice, TSPO expression was increased, while HIGD1A, NDUFAB1, NT5DC3, and MRPS30 expressions were decreased. However, peripheral blood samples did not show expression of HIGD1A or MRPS30. These findings provide new insights for research on Alzheimer's disease in the context of mitochondrial-immune interactions, further exploring the pathogenesis of Alzheimer's disease and offering new perspectives for the clinical development of novel drugs.

CONCLUSIONS

Five mitochondrial and immune biomarkers, i.e., TSPO, HIGD1A, NDUFAB1, NT5DC3, and MRPS30, with diagnostic value in Alzheimer's disease, were screened by machine-learning algorithmic models, which will be a guide for future clinical research of Alzheimer's disease in the mitochondria-immunity-related direction.

Emerging role of adaptive immunity in diabetes-induced cognitive impairment: from the periphery to the brain

Diabetic cognitive impairment (DCI) is a central nervous system complication induced by peripheral metabolic dysfunction of diabetes mellitus. Cumulative studies have shown that neuro-immune crosstalk is involved in the pathological progression of DCI. However, current studies mostly focus on the interaction between innate immunity cells and neurons, while ignoring the role of adaptive immunity cells in DCI. Notably, recent studies have revealed adaptive immune cells are involved in cognitive development and the progression of neurodegenerative diseases. Equally important, accumulated past studies have also shown that diabetic patients experience imbalanced peripheral adaptive immune homeostasis and disrupted transmission of adaptive immune cells to the central system. Therefore, this review first updated the cognitive mechanism of adaptive immune regulation, and then summarized the contribution of adaptive immunity to DCI from the aspects of peripheral adaptive immune homeostasis, transmission pathways, and brain tissue infiltration. Furthermore, we also summarized the potential of anti-diabetic drugs to regulate adaptive immunity, and looked forward to the potential value of regulatory adaptive immunity in the prevention and treatment of DCI, to provide a new strategy for the prevention and treatment of DCI.

Transcriptomic predictors of rapid progression from mild cognitive impairment to Alzheimer's disease

BACKGROUND

Effective treatment for Alzheimer's disease (AD) remains an unmet need. Thus, identifying patients with mild cognitive impairment (MCI) who are at high-risk of progressing to AD is crucial for early intervention.

METHODS

Blood-based transcriptomics analyses were performed using a longitudinal study cohort to compare progressive MCI (P-MCI, n = 28), stable MCI (S-MCI, n = 39), and AD patients (n = 49). Statistical DESeq2 analysis and machine learning methods were employed to identify differentially expressed genes (DEGs) and develop prediction models.

RESULTS

We discovered a remarkable gender-specific difference in DEGs that distinguish P-MCI from S-MCI. Machine learning models achieved high accuracy in distinguishing P-MCI from S-MCI (AUC 0.93), AD from S-MCI (AUC 0.94), and AD from P-MCI (AUC 0.92). An 8-gene signature was identified for distinguishing P-MCI from S-MCI.

CONCLUSIONS

Blood-based transcriptomic biomarker signatures show great utility in identifying high-risk MCI patients, with mitochondrial processes emerging as a crucial contributor to AD progression.

Diagnostic and Therapeutic Advances of RNAs in Precision Medicine of Gastrointestinal Tumors

Gastrointestinal tumors present a significant challenge for precision medicine due to their complexity, necessitating the development of more specific diagnostic tools and therapeutic agents. Recent advances have positioned coding and non-coding RNAs as emerging biomarkers for these malignancies, detectable by liquid biopsies, and as innovative therapeutic agents. Many RNA-based therapeutics, such as small interfering RNA (siRNA) and antisense oligonucleotides (ASO), have entered clinical trials or are available on the market. This review provides a narrative examination of the diagnostic and therapeutic potential of RNA in gastrointestinal cancers, with an emphasis on its application in precision medicine. This review discusses the current challenges, such as drug resistance and tumor metastasis, and highlights how RNA molecules can be leveraged for targeted detection and treatment. Additionally, this review categorizes specific diagnostic biomarkers and RNA therapeutic targets based on tissue type, offering a comprehensive analysis of their role in advancing precision medicine for gastrointestinal tumors.

A mini review of leveraging biobanking in the identification of novel biomarkers in neurological disorders: insights from a rapid single-cell sequencing pipeline

Recent successes in the identification of biomarkers and therapeutic targets for diagnosing and managing neurological diseases underscore the critical need for cutting-edge biobanks in the conduct of high-caliber translational neuroscience research. Biobanks dedicated to neurological disorders are particularly timely, given the increasing prevalence of neurological disability among the rising aging population. Translational research focusing on disorders of the central nervous system (CNS) poses distinct challenges due to the limited accessibility of CNS tissue pre-mortem. Nevertheless, technological breakthroughs, including single-cell and single-nucleus methodologies, offer unprecedented insights into CNS pathophysiology using minimal input such as cerebrospinal fluid (CSF) cells and brain biopsies. Moreover, assays designed to detect factors that are released by CNS resident cells and diffuse into the CSF and/or bloodstream (such as neurofilament light chain [NfL], glial fibrillar acidic protein [GFAP] and amyloid beta peptides), and systemic factors that cross the blood-brain barrier to target CNS-specific molecules (e.g., autoantibodies that bind either the NMDA receptor [NMDAR] or myelin oligodendrocyte glycoprotein [MOG]), are increasingly deployed in clinical research and practice. This review provides an overview of current biobanking practices in neurological disorders and discusses ongoing challenges to biomarker discovery. Additionally, it outlines a rapid consenting and processing pipeline ensuring fresh paired blood and CSF specimens for single-cell sequencing that might more accurately reflect in vivo pathways. In summary, augmenting biobank rigor and establishing innovative research pipelines using patient samples will undoubtedly accelerate biomarker discovery in neurological disorders.

Identification of key neutrophil extracellular trap genes in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder that is associated with neuroinflammation. Neutrophil extracellular traps (NETs) are web-like structures that cause inflammation, but its involvement in AD pathogenesis is unclear.

OBJECTIVE

This study aimed to identify key NETs related genes associated with AD.

METHODS

A total of 180 samples from the GSE122063 and GSE36980 dataset were obtained from the GEO repository. The representative genes were obtained, and its diagnostic performance was evaluated by analyzing operating characteristic curves. Consensus clustering and principal component analysis were performed to cluster AD samples. Gene ontology, KEGG pathway enrichment, and protein interaction network were analyzed. Peripheral blood samples were collected from 5 AD patients and 5 healthy donors to determine the expression of representative proteins or genes using WB, ELISA, and RT-qPCR.

RESULTS

A total of 297 differentially expressed genes (DEGs) were associated with AD, 18 NETs genes showed potential diagnostic value. NETs genes expression effectively distinguished AD patients into 2 subgroups. The AD1 cluster showed higher abundance of activated dendritic cells, monocytes, and neutrophils, the AD2 cluster showed higher levels of naive B cells, eosinophils, and activated NK cells. We randomly selected and measured the levels representative genes in AD patients. The levels of NETs and CCL2, TLR2 expressions were significantly increased, whereas the level of BDNF was significantly decreased in AD patients comparing with healthy controls.

CONCLUSIONS

This study identified key NET genes including BDNF, CCL2, and TLR2 to be associated with AD pathogenesis and classification.

Identification of altered immune cell types and molecular mechanisms in Alzheimer's disease progression by single-cell RNA sequencing

Introduction

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by gradual loss of cognitive function. Understanding the molecular mechanisms is crucial for developing effective therapies.

Methods

Data from single-cell RNA sequencing (scRNA-seq) in the GSE181279 dataset and gene chips in the GSE63060 and GSE63061 datasets were collected and analyzed to identify immune cell types and differentially expressed genes. Cell communication, pseudotime trajectory, enrichment analysis, co- expression network, and short time-series expression miner were analyzed to identify disease-specific molecular and cellular mechanisms.

Results

We identified eight cell types (B cells, monocytes, natural killer cells, gamma-delta T cells, CD8+ T cells, Tem/Temra cytotoxic T cells, Tem/Trm cytotoxic T cells, and mucosal-associated invariant T cells) using scRNA-seq. AD samples were enriched in monocytes, CD8+ T cells, Tem/Temra cytotoxic T cells, and Tem/Trm cytotoxic T cells, whereas samples from healthy controls were enriched in natural killer and mucosal-associated invariant T cells. Five co-expression modules that were identified through weighted gene correlation network analysis were enriched in immune- inflammatory pathways. Candidate genes with higher area under the receiver operating characteristic curve values were screened, and the expression trend of Ubiquitin-Fold Modifier Conjugating Enzyme 1 (UFC1) gradually decreased from healthy controls to mild cognitive impairment and then to AD.

Conclusion

Our study suggests that peripheral immune cells may be a potential therapeutic target for AD. Candidate genes, particularly UFC1, may serve as potential biomarkers for progression of AD.

Advancements in Single-Cell RNA Sequencing Research for Neurological Diseases

Neurological diseases are a major cause of the global burden of disease. Although the mechanisms of the occurrence and development of neurological diseases are not fully clear, most of them are associated with cells mediating neuroinflammation. Yet medications and other therapeutic options to improve treatment are still very limited. Single-cell RNA sequencing (scRNA-seq), as a delightfully potent breakthrough technology, not only identifies various cell types and response states but also uncovers cell-specific gene expression changes, gene regulatory networks, intercellular communication, and cellular movement trajectories, among others, in different cell types. In this review, we describe the technology of scRNA-seq in detail and discuss and summarize the application of scRNA-seq in exploring neurological diseases, elaborating the corresponding specific mechanisms of the diseases as well as providing a reliable basis for new therapeutic approaches. Finally, we affirm that scRNA-seq promotes the development of the neuroscience field and enables us to have a deeper cellular understanding of neurological diseases in the future, which provides strong support for the treatment of neurological diseases and the improvement of patients' prognosis.

Single-cell analysis of nasal epithelial cell development in domestic pigs

The nasal mucosa forms a critical barrier against the invasion of respiratory pathogens. Composed of a heterogeneous assortment of cell types, the nasal mucosa relies on the unique characteristics and complex intercellular dynamics of these cells to maintain their structural integrity and functional efficacy. In this study, single-cell RNA sequencing (scRNA-seq) of porcine nasal mucosa was performed, and nineteen distinct nasal cell types, including nine epithelial cell types, five stromal cell types, and five immune cell types, were identified. The distribution patterns of three representative types of epithelial cells (basal cells, goblet cells, and ciliated cells) were subsequently detected by immunofluorescence. We conducted a comparative analysis of these data with published human single-cell data, revealing consistent differentiation trajectories among porcine and human nasal epithelial cells. Specifically, basal cells serve as the initial stage in the differentiation process of nasal epithelial cells, which then epithelial cells. This research not only enhances our understanding of the composition and transcriptional signature of porcine nasal mucosal cells but also offers a theoretical foundation for developing alternative models for human respiratory diseases.

Single-cell RNA sequencing reveals peripheral immunological features in Parkinson's Disease

Although many researchers of Parkinson's disease (PD) have shifted their focus from the central nervous system (CNS) to the peripheral blood, a significant knowledge gap remains between PD severity and the peripheral immune response. In the current study, we aimed to map the peripheral immunity atlas in peripheral blood mononuclear cells (PBMCs) from PD patients and healthy controls using single-cell RNA sequencing (scRNA-seq). Our study employed scRNA-seq analysis to map the peripheral immunity atlas in PD by profiling PBMCs from PD-Early, PD-Late patients and matched controls. By enlarging the blood sample size, we validated the roles of NK cells in numerous immune-related biological processes. We also detected the infiltration of NK cells into the cerebral motor cortex as the disease progressed, using human brain sections, and elucidated the communication between the periphery and CNS and its implications for PD. As a result, cell subpopulation atlases in PBMCs from PD patients and healthy controls along with differentially expressed genes in NK cells were identified by scRNA-seq analysis, representing 6 major immune cell subsets among which NK cells declined in the progression of PD. We further validated NK cell reduction in increasing samples and found that they participated in numerous immune-related biological processes and infiltration into the cerebral motor cortex as the disease proceeded, evidencingd the close communication between the peripheral immune response and CNS. Strikingly, XCL2 positively correlated with PD severity, with good predictive performance of PD and specific expression in subclusters C2 and C5 of NK cells. All these findings delineated the critical role of peripheral immune response mediated by NK cells in the pathogenesis of PD. NK cell-specific XCL2 could be used as a diagnostic marker for treating PD. The indispensable function of NK cells and NK cell-specific molecular biomarkers highlighted the implication of the peripheral immune response in PD progression. Trial registration: ChiCTR, ChiCTR1900023975. Registered 20 June 2019 - Retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=31035 .

The changes of peripheral blood hub genes in 24-week-old APP/PS1/Tau triple transgenic mouse model based on weighted gene co-expression network analysis

Peripheral regulation emerges as a promising intervention in the early stages of Alzheimer's disease (AD). The hub genes in the peripheral blood of MCI patients from GEO database (GSE63060, GSE63061) were screened using weighted gene co-expression analysis (WGCNA). Meanwhile, behavioral tests, HE staining and Nissl staining were used to detect the memory impairment and histopathological changes in 24-week-old male 3×Tg-AD mice. Thioflavin-S and immunohistochemical staining were used to determine the Aβ deposition in both intracellular and extracellular neurons. Subsequently, the MCI-hub genes were verified by quantitative real-time PCR (qRT-PCR) in the peripheral blood of 3×Tg-AD mice. The research revealed ten hub genes associated with MCI were identified WGCNA. Short-term memory loss, intracellular Aβ deposition and limited of extracellular amyloid plaques in 3×Tg-AD mice. The qRT-PCR analysis of peripheral blood from these mice revealed significantly down-regulation in the expression levels of ATP5C1, ITGB2, EFTUD2 and RPS27A genes; whereas the expression level of VCP gene was significantly up-regulated. These findings confirmed that 24-week-old male 3×Tg-AD mice were a valuable animal model for simulating the early symptomatic stages of AD. Additionally, the peripheral blood MCI-hub genes related to immune response, energy metabolism and ribosomal coding efficiency provide potential biomarkers for this stage.

Exploring resveratrol against Alzheimer's disease and Parkinson's disease through integrating network pharmacology, bioinformatics, and experimental validation strategy in vitro

Background

The study aims to investigate the pharmacological basis and molecular mechanisms of resveratrol in the treatment of Alzheimer's disease (AD) and Parkinson's disease (PD) through the approach of treating different diseases with the same method, guided by traditional Chinese medicine theory. Utilizing network pharmacology and bioinformatics methods, this research aims to provide modern medical evidence for the theory of treating different diseases with the same method in traditional Chinese medicine.

Methods

Omnibus from Swiss Target Prediction, TCMSP, SuperPred, SEA, HIT, CTD, TCMIP and Gene Expression Disease datasets for resveratrol related genes, Alzheimer's disease, and Parkinson's disease were obtained from the GEO database. Core targets were identified by weighted gene coexpression network analysis (WGCNA) and minimum absolute contraction and selection operator (LASSO). The expression of core targets was verified in AD and PD cell models. The immune characteristics of AD and PD were analyzed by CIBERSORT algorithm. Finally, the potential mechanism of resveratrol intervention on the core target was studied by molecular docking technique.

Results

The results of network pharmacological analysis showed that resveratrol acted on 85 common targets such as STAT3 and CASP3, affected AGE-RAGE signaling pathway and PI3K-Akt signaling pathway, and showed the effect of "same disease and different treatment" for AD and PD. Three core targets associated with AD and PD (PLK4, FCGRT, and PRKAR2A) were finally identified through comprehensive transcriptome analysis, and experimentally verified in cell models of AD and PD. At the same time, the analysis of immune cell infiltration suggested that AD and PD had dysregulation of inflammation, and the core target was significantly related to M2 macrophages.

Conclusion

Resveratrol may play a potential mechanism of "treating the same disease with different diseases" and target three core targets (PLK4, FCGRT and PRKAR2A) to improve the disease process of AD and PD by participating in the regulation of immune and inflammatory pathways. These findings have potential implications for clinical practice and future research.

EBF1 is a potential biomarker for predicting progression from mild cognitive impairment to Alzheimer's disease: an in silico study

Introduction

The prediction of progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is an important clinical challenge. This study aimed to identify the independent risk factors and develop a nomogram model that can predict progression from MCI to AD.

Methods

Data of 141 patients with MCI were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We set a follow-up time of 72 months and defined patients as stable MCI (sMCI) or progressive MCI (pMCI) according to whether or not the progression of MCI to AD occurred. We identified and screened independent risk factors by utilizing weighted gene co-expression network analysis (WGCNA), where we obtained 14,893 genes after data preprocessing and selected the soft threshold β = 7 at an R 2 of 0.85 to achieve a scale-free network. A total of 14 modules were discovered, with the midnightblue module having a strong association with the prognosis of MCI. Using machine learning strategies, which included the least absolute selection and shrinkage operator and support vector machine-recursive feature elimination; and the Cox proportional-hazards model, which included univariate and multivariable analyses, we identified and screened independent risk factors. Subsequently, we developed a nomogram model for predicting the progression from MCI to AD. The performance of our nomogram was evaluated by the C-index, calibration curve, and decision curve analysis (DCA). Bioinformatics analysis and immune infiltration analysis were conducted to clarify the function of early B cell factor 1 (EBF1).

Results

First, the results showed that 40 differentially expressed genes (DEGs) related to the prognosis of MCI were generated by weighted gene co-expression network analysis. Second, five hub variables were obtained through the abovementioned machine learning strategies. Third, a low Montreal Cognitive Assessment (MoCA) score [hazard ratio (HR): 4.258, 95% confidence interval (CI): 1.994-9.091] and low EBF1 expression (hazard ratio: 3.454, 95% confidence interval: 1.813-6.579) were identified as the independent risk factors through the Cox proportional-hazards regression analysis. Finally, we developed a nomogram model including the MoCA score, EBF1, and potential confounders (age and gender). By evaluating our nomogram model and validating it in both internal and external validation sets, we demonstrated that our nomogram model exhibits excellent predictive performance. Through the Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes Genomes (KEGG) functional enrichment analysis, and immune infiltration analysis, we found that the role of EBF1 in MCI was closely related to B cells.

Conclusion

EBF1, as a B cell-specific transcription factor, may be a key target for predicting progression from MCI to AD. Our nomogram model was able to provide personalized risk factors for the progression from MCI to AD after evaluation and validation.

Comprehensive review on single-cell RNA sequencing: A new frontier in Alzheimer's disease research

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition marked by gradual cognitive deterioration and the loss of neurons. While conventional bulk RNA sequencing techniques have shed light on AD pathology, they frequently obscure the cellular diversity within brain tissues. The advent of single-cell RNA sequencing (scRNA-seq) has transformed our capability to analyze the cellular composition of AD, allowing for the detection of unique cell populations, rare cell types, and gene expression alterations at an individual cell level. This review examines the use of scRNA-seq in AD research, focusing on its contributions to understanding cellular diversity, disease progression, and potential therapeutic targets. We discuss key technological innovations, data analysis techniques, and challenges associated with scRNA-seq in studying AD. Furthermore, we highlight recent studies that have utilized scRNA-seq to identify novel biomarkers, uncover disease-associated pathways, and elucidate the role of non-neuronal cells, such as microglia and astrocytes, in AD pathogenesis. By providing a comprehensive overview of advancements in scRNA-seq for unraveling cellular heterogeneity in AD, this review highlights the transformative impact of scRNA-seq on our comprehension of disease mechanisms and the creation of targeted treatments.

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.

Alterations of mRNAs and Non-coding RNAs Associated with Neuroinflammation in Alzheimer's Disease

Alzheimer's disease is a neurodegenerative pathology whose pathognomonic hallmarks are increased generation of β-amyloid (Aβ) peptide, production of hyperphosphorylated (pTau), and neuroinflammation. The last is an alteration closely related to the progression of AD and although it is present in multiple neurodegenerative diseases, the pathophysiological events that characterize neuroinflammatory processes vary depending on the disease. In this article, we focus on mRNA and non-coding RNA alterations as part of the pathophysiological events characteristic of neuroinflammation in AD and the influence of these alterations on the course of the disease through interaction with multiple RNAs related to the generation of Aβ, pTau, and neuroinflammation itself.

The role of m6A modification in the risk prediction and Notch1 pathway of Alzheimer's disease

N6-methyladenosine (m6A) methylation and abnormal immune responses are implicated in neurodegenerative diseases, yet their relationship in Alzheimer's disease (AD) remains unclear. We obtained AD datasets from GEO databases and used AD mouse and cell models, observing abnormal expression of m6A genes in the AD group, alongside disruptions in the immune microenvironment. Key m6A genes (YTHDF2, LRPPRC, and FTO) selected by machine learning were associated with the Notch pathway, with FTO and Notch1 displaying the strongest correlation. Specifically, FTO expression decreased and m6A methylation of Notch1 increased in AD mouse and cell models. We further silenced FTO expression in HT22 cells, resulting in upregulation of the Notch1 signaling pathway. Additionally, increased Notch1 expression in dendritic cells heightened inflammatory cytokine secretion in vitro. These results suggest that reduced FTO expression may contribute to the pathogenesis of AD by activating the Notch1 pathway to interfere with the immune response.

The role of Immune cells in Alzheimer's disease: a bidirectional Mendelian randomization study

BACKGROUND

Alzheimer's disease (AD) is a leading cause of dementia, characterized by the accumulation of amyloid-beta (Aβ) and hyperphosphorylated tau proteins, leading to neuroinflammation and neuronal damage. The role of the immune system in AD pathogenesis is increasingly recognized, prompting an exploration of the causal relationship between immune cells and AD by using Mendelian randomization (MR) approaches.

METHODS

Utilizing genome-wide association study (GWAS) data from European cohorts, we conducted an MR study to investigate the causal links between immune cell phenotypes and AD. We selected single nucleotide polymorphisms (SNPs) associated with immune cell traits at a genome-wide significance threshold and applied various MR methods, including MR Egger, Weighted median, and inverse variance weighted analysis, to assess the causality between 731 immune phenotypes and AD.

RESULTS

Our MR analysis identified 15 immune cell types with significant causal relationships to AD pathogenesis. Notably, the absolute count of CD28-CD4-CD8- T cells and the expression of HLA DR on B cells were linked to a protective effect against AD, while 13 other immune phenotypes were identified as contributing to the risk factors for the disease. The causal effects of AD on immunophenotypic traits are predominantly negative, implying that AD may impair the functionality of immune cells. Validation through independent datasets, such as FinnGen and GCST90027158, confirmed the causal association between six specific immune cells and AD.

CONCLUSION

This comprehensive MR study elucidates the intricate network of causal relationships between diverse immunophenotypic traits and AD, providing novel insights into the immunopathogenesis of AD. The findings suggest potential immunological targets that could be leveraged for early diagnosis, disease monitoring, and therapeutic intervention.

Causal relationships between peripheral immune cells and Alzheimer's disease: a two-sample Mendelian randomization study

OBJECTIVE

Previous research suggests that peripheral immune cells may play a role in the development of Alzheimer's disease (AD). Our study aims to determine if the composition of peripheral immune cells directly contributes to the occurrence of AD.

METHODS

We utilized a two-sample Mendelian randomization (MR) approach to examine the association between peripheral immune cells and AD.The primary analysis method used was the inverse variance weighted (IVW) method, and we also conducted analyses using MR Egger, weighted median, simple mode, and weighted mode methods to ensure the accuracy of the results.Heterogeneity and horizontal pleiotropy were evaluated using Cochran's Q statistics and the MR Egger intercept, respectively.

RESULTS

The study found a significant correlation between increased IgD + CD24- AC cells (Odds Ratio [OR] = 1.03, 95% Confidence Interval [CI] = 1.01-1.06, P = 0.0172), increased CD4 + %leukocyte (OR = 1.08, 95% CI = 1.02-1.14, P = 0.0086), and increased CD4 + CD8dim AC cells (OR = 1.06, 95% CI = 1.01-1.11, P = 0.0218), with an increased susceptibility to AD. Conversely, an increase in EM DN (CD4-CD8-) %T cells (OR = 0.95, 95% CI = 0.92-0.99, P = 0.0164) and an increase in DN (CD4-CD8-) AC cells (OR = 0.93, 95% CI = 0.88-0.99, P = 0.0145) were associated with a protective effect against AD.

CONCLUSION

Our findings establish a causal link between peripheral immune cells and AD. This study is the first to examine the relationship between peripheral immune cells and AD using MR, offering valuable insights for early diagnosis and treatment decisions.

Traumatic brain injury alters the effects of class II invariant peptide (CLIP) antagonism on chronic meningeal CLIP + B cells, neuropathology, and neurobehavioral impairment in 5xFAD mice

BACKGROUND

Traumatic brain injury (TBI) is a significant risk factor for Alzheimer's disease (AD), and accumulating evidence supports a role for adaptive immune B and T cells in both TBI and AD pathogenesis. We previously identified B cell and major histocompatibility complex class II (MHCII)-associated invariant chain peptide (CLIP)-positive B cell expansion after TBI. We also showed that antagonizing CLIP binding to the antigen presenting groove of MHCII after TBI acutely reduced CLIP + splenic B cells and was neuroprotective. The current study investigated the chronic effects of antagonizing CLIP in the 5xFAD Alzheimer's mouse model, with and without TBI.

METHODS

12-week-old male wild type (WT) and 5xFAD mice were administered either CLIP antagonist peptide (CAP) or vehicle, once at 30 min after either sham or a lateral fluid percussion injury (FPI). Analyses included flow cytometric analysis of immune cells in dural meninges and spleen, histopathological analysis of the brain, magnetic resonance diffusion tensor imaging, cerebrovascular analysis, and assessment of motor and neurobehavioral function over the ensuing 6 months.

RESULTS

9-month-old 5xFAD mice had significantly more CLIP + B cells in the meninges compared to age-matched WT mice. A one-time treatment with CAP significantly reduced this population in 5xFAD mice. Importantly, CAP also improved some of the immune, histopathological, and neurobehavioral impairments in 5xFAD mice over the ensuing six months. Although FPI did not further elevate meningeal CLIP + B cells, it did negate the ability of CAP to reduce meningeal CLIP + B cells in the 5xFAD mice. FPI at 3 months of age exacerbated some aspects of AD pathology in 5xFAD mice, including further reducing hippocampal neurogenesis, increasing plaque deposition in CA3, altering microgliosis, and disrupting the cerebrovascular structure. CAP treatment after injury ameliorated some but not all of these FPI effects.

Neuroinflammation in Alzheimer's disease: insights from peripheral immune cells

Alzheimer's disease (AD) is a serious brain disorder characterized by the presence of beta-amyloid plaques, tau pathology, inflammation, neurodegeneration, and cerebrovascular dysfunction. The presence of chronic neuroinflammation, breaches in the blood-brain barrier (BBB), and increased levels of inflammatory mediators are central to the pathogenesis of AD. These factors promote the penetration of immune cells into the brain, potentially exacerbating clinical symptoms and neuronal death in AD patients. While microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in AD, recent evidence suggests the infiltration of cerebral vessels and parenchyma by peripheral immune cells, including neutrophils, T lymphocytes, B lymphocytes, NK cells, and monocytes in AD. These cells participate in the regulation of immunity and inflammation, which is expected to play a huge role in future immunotherapy. Given the crucial role of peripheral immune cells in AD, this article seeks to offer a comprehensive overview of their contributions to neuroinflammation in the disease. Understanding the role of these cells in the neuroinflammatory response is vital for developing new diagnostic markers and therapeutic targets to enhance the diagnosis and treatment of AD patients.

Enrichment of liver MAIT cells in a mouse model of Alzheimer's disease

Emerging evidence has supported a role for the immune system and liver in Alzheimer's disease (AD). However, our understanding of how hepatic immune cells are altered in AD is limited. We previously found that brain mucosal-associated invariant T (MAIT) cell numbers are increased in AD. Furthermore, loss of MAIT cells and their antigen-presenting molecule, MR1, reduced amyloid-β accumulation in the brain. MAIT cells are also significantly present in the liver. Therefore, we sought to analyze MAIT and other immune cells in the AD liver. Increased frequency of activated MAIT cells (but not conventional T cells) were found in 8-month-old 5XFAD mouse livers. Therefore, these data raise the possibility that there is a role for peripheral MAIT cells in AD pathology.

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics

Unlocking the full dimensionality of single-cell RNA sequencing data (scRNAseq) is the next frontier to a richer, fuller understanding of cell biology. We introduce q-diffusion, a framework for capturing the coexpression structure of an entire library of genes, improving on state-of-the-art analysis tools. The method is demonstrated via three case studies. In the first, q-diffusion helps gain statistical significance for differential effects on patient outcomes when analyzing the CALGB/SWOG 80405 randomized phase III clinical trial, suggesting precision guidance for the treatment of metastatic colorectal cancer. Secondly, q-diffusion is benchmarked against existing scRNAseq classification methods using an in vitro PBMC dataset, in which the proposed method discriminates IFN-γ stimulation more accurately. The same case study demonstrates improvements in unsupervised cell clustering with the recent Tabula Sapiens human atlas. Finally, a local distributional segmentation approach for spatial scRNAseq, driven by q-diffusion, yields interpretable structures of human cortical tissue.

Unraveling the mechanisms of NK cell dysfunction in aging and Alzheimer's disease: insights from GWAS and single-cell transcriptomics

BACKGROUND

Aging is an important factor in the development of Alzheimer's disease (AD). The senescent cells can be recognized and removed by NK cells. However, NK cell function is gradually inactivated with age. Therefore, this study used senescence as an entry point to investigate how NK cells affect AD.

METHODS

The study validated the correlation between cognition and aging through a prospective cohort of the National Health and Nutrition Examination Survey database. A cellular trajectory analysis of the aging population was performed using single-cell nuclear transcriptome sequencing data from patients with AD and different ages. The genome-wide association study (GWAS) cohort of AD patients was used as the outcome event, and the expression quantitative trait locus was used as an instrumental variable. Causal associations between genes and AD were analyzed by bidirectional Mendelian randomization (MR) and co-localization. Finally, clinical cohorts were constructed to validate the expression of key genes.

RESULTS

A correlation between cognition and aging was demonstrated using 2,171 older adults over 60 years of age. Gene regulation analysis revealed that most of the highly active transcription factors were concentrated in the NK cell subpopulation of AD. NK cell trajectories were constructed for different age populations. MR and co-localization analyses revealed that CHD6 may be one of the factors influencing AD.

CONCLUSION

We explored different levels of AD and aging from population cohorts, single-cell data, and GWAS cohorts and found that there may be some correlations of NK cells between aging and AD. It also provides some basis for potential causation.

Association of peripheral B cells and delirium: combined single-cell sequencing and Mendelian randomization analysis

Background

Delirium seriously affects the prognosis of patients and greatly reduces the ability to work and live. Peripheral inflammatory events may contribute to the development of delirium, the mechanism of which is still unclear. There is a lack of effective diagnostic and treatments for delirium in clinical practice. The study aims to investigate alterations in peripheral immune cell subsets under inflammatory stress and to explore causal associations with delirium.

Methods

Single-cell transcriptional sequencing data of human peripheral blood mononuclear cells (PBMC) before and after lipopolysaccharide (LPS) intervention were processed by the Seurat package in R software. PBMC subsets and cellular markers were defined after downscaling and clustering by the Harmony algorithm to identify characteristic subsets in the context of inflammatory stress. Subsequently, a two-sample Mendelian randomization (MR) study was used to explore the causal associations of these inflammation-related PBMC subsets and their molecular phenotypes with delirium. Based on publicly available genetic data, the study incorporated 70 PBMC-associated immune traits, including 8 types of circulating immune cells, 33 B cell subsets and molecular phenotypes, 13 T cell subsets, and 16 B cell-associated cytokines. The results were also validated for robustness, heterogeneity, and horizontal pleiotropy.

Results

Under LPS-induced inflammatory stress, B cells, T cells, monocytes, and dendritic cells in human PBMC showed significant activation and quantitative changes. Of these, only lymphocyte and B cell counts were causally associated with delirium risk. This risk link is also seen in the TNF pathway. Further studies of B cells and their subsets revealed that this association may be related to unswitched memory B cells and CD27 expressed on memory B cells. Annotation of the screened SNPs revealed significant polymorphisms in CD27 and CD40 annotated by rs25680 and rs9883798, respectively. The functions of the key annotated genes may be related to the regulation of immune responses, cell differentiation, proliferation, and intercellular interactions.

Conclusion

The present study revealed the potential possibility that B cell, memory B cell subset, and TNF-related molecules may be involved in the development of delirium due to peripheral inflammation, which can provide clues for further investigation of delirium prevention and treatment strategies.

Single-cell transcriptomics analysis of cellular heterogeneity and immune mechanisms in neurodegenerative diseases

Single-cell transcriptomics analysis is an advanced technology that can describe the intracellular transcriptome in complex tissues. It profiles and analyses datasets by single-cell RNA sequencing. Neurodegenerative diseases are identified by the abnormal apoptosis of neurons in the brain with few or no effective therapy strategies at present, which has been a growing healthcare concern and brought a great burden to society. The transcriptome of individual cells provides deep insights into previously unforeseen cellular heterogeneity and gene expression differences in neurodegenerative disorders. It detects multiple cell subsets and functional changes during pathological progression, which deepens the understanding of the molecular underpinnings and cellular basis of neurodegenerative diseases. Furthermore, the transcriptome analysis of immune cells shows the regulation of immune response. Different subtypes of immune cells and their interaction are found to contribute to disease progression. This finding enables the discovery of novel targets and biomarkers for early diagnosis. In this review, we emphasize the principles of the technology, and its recent progress in the study of cellular heterogeneity and immune mechanisms in neurodegenerative diseases. The application of single-cell transcriptomics analysis in neurodegenerative disorders would help explore the pathogenesis of these diseases and develop novel therapeutic methods.

scHybridBERT: integrating gene regulation and cell graph for spatiotemporal dynamics in single-cell clustering

Graph learning models have received increasing attention in the computational analysis of single-cell RNA sequencing (scRNA-seq) data. Compared with conventional deep neural networks, graph neural networks and language models have exhibited superior performance by extracting graph-structured data from raw gene count matrices. Established deep neural network-based clustering approaches generally focus on temporal expression patterns while ignoring inherent interactions at gene-level as well as cell-level, which could be regarded as spatial dynamics in single-cell data. Both gene-gene and cell-cell interactions are able to boost the performance of cell type detection, under the framework of multi-view modeling. In this study, spatiotemporal embedding and cell graphs are extracted to capture spatial dynamics at the molecular level. In order to enhance the accuracy of cell type detection, this study proposes the scHybridBERT architecture to conduct multi-view modeling of scRNA-seq data using extracted spatiotemporal patterns. In this scHybridBERT method, graph learning models are employed to deal with cell graphs and the Performer model employs spatiotemporal embeddings. Experimental outcomes about benchmark scRNA-seq datasets indicate that the proposed scHybridBERT method is able to enhance the accuracy of single-cell clustering tasks by integrating spatiotemporal embeddings and cell graphs.

Migration Inhibition Factor Secreted by Peripheral Blood Memory B Cells Binding to CD74-CD44 Receptor Complex Drives Macrophage Behavior in Alzheimer's Disease

Dysregulation of the peripheral immune system is be involved in the neuroinflammation in Alzheimer disease (AD) and accelerate the disease progression. The contribution of immune cells, particularly B cells, to AD pathogenesis has gained attention in recent research. In this study, we investigated the role of Peripheral Blood Memory B cells (PBMBs) and their secreted Migration Inhibition Factor (MIF) in driving macrophage behavior in AD based on the scRNA-seq technique, immunofluorescence and flow cytometry. We discovered that MIF binds to the CD74-CD44 receptor complex on macrophages, influencing their behavior. The dysregulated macrophage response hampers the clearance of amyloid-beta (Aβ) plaques, exacerbating AD pathology. Targeting the MIF-CD74-CD44 signal pathway may hold therapeutic potential in modulating macrophage activity and mitigating neuroinflammation in AD. This study provides a further understanding of peripheral immune cells dysregulated in AD.

Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies

Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation.

Single-Cell Sequencing in Neurodegenerative Disorders

Neurodegenerative disorders are typically characterized by late onset progressive damage to specific (sub)populations of cells of the nervous system that are essential for mobility, coordination, strength, sensation, and cognition. Addressing this selective cellular vulnerability has become feasible with the emergence of single-cell-omics technologies, which now represent the state-of-the-art approach to profile heterogeneity of complex tissues including human post-mortem brain at unprecedented resolution. In this review, we briefly recapitulate the experimental workflow of single-cell RNA sequencing and summarize the recent knowledge acquired with it in the most common neurodegenerative diseases: Parkinson's, Alzheimer's, Huntington's disease, and multiple sclerosis. We also discuss the possibility of applying single-cell approaches in the diagnostics and therapy of neurodegenerative disorders, as well as the limitations. While we are currently at the point of deeply exploring the transcriptomic changes in the affected cells, further technological developments hold a promise of manipulating the affected pathways once we understand them better.

Blood tau-PT217 contributes to the anesthesia/surgery-induced delirium-like behavior in aged mice

INTRODUCTION

Blood phosphorylated tau at threonine 217 (tau-PT217) is a newly established biomarker for Alzheimer's disease and postoperative delirium in patients. However, the mechanisms and consequences of acute changes in blood tau-PT217 remain largely unknown.

METHODS

We investigated the effects of anesthesia/surgery on blood tau-PT217 in aged mice, and evaluated the associated changes in B cell populations, neuronal excitability in anterior cingulate cortex, and delirium-like behavior using positron emission tomography imaging, nanoneedle technology, flow cytometry, electrophysiology, and behavioral tests.

RESULTS

Anesthesia/surgery induced acute increases in blood tau-PT217 via enhanced generation in the lungs and release from B cells. Tau-PT217 might cross the blood-brain barrier, increasing neuronal excitability and inducing delirium-like behavior. B cell transfer and WS635, a mitochondrial function enhancer, mitigated the anesthesia/surgery-induced changes.

DISCUSSION

Acute increases in blood tau-PT217 may contribute to brain dysfunction and postoperative delirium. Targeting B cells or mitochondrial function may have therapeutic potential for preventing or treating these conditions.

[Identification of Peripheral Blood GZMK + CD8 + T Cells As Biomarkers of Alzheimer's Disease Based on Single-Cell Transcriptome]

Objective

Based on single-cell RNA sequencing (scRNA-seq) to explore immune characteristics in the peripheral blood of patients with Alzheimer's disease (AD) as biomarkers.

Methods

GSE168522, the scRNA-seq dataset of AD peripheral blood immune cells, was downloaded from the Gene Expression Omnibus (GEO) database and was analyzed in the RAD-Blood web server (http://www.bioinform.cn/RAD-Blood/). The changes in blood cell composition in AD patients were analyzed. The abnormal communications between different types of cells in AD patients were investigated by the CellChat R package.

Results

There were two kinds of CD8 + T cells in the blood of AD patients and healthy individuals, one of which highly expressed granzyme K ( GZMK) (false discovery rate [FDR]<0.05), and the other highly expressed GZMA, GZMB, and GZMH (FDR<0.05). In the blood of AD patients, the content of GZMK + CD8 + T cells was increased by 32.9% ( P=5.15E-21), their interactions with other cell types were increased, and they might be associated with AD through the abnormal signal transduction of major histocompatibility complex class Ⅰ (MHC-Ⅰ). Erythrocyte provided the main ligands, that are, human leukocyte antigen (HLA) class Ⅰ molecules, including HLA- A, HLA- B, HLA- C, and HLA- E, for the abnormal MHC-Ⅰ signaling pathway of GZMK + CD8 + T cells. The RESISTIN signaling pathway was specifically enriched in the blood of AD patients.

Conclusion

The increased content of peripheral blood GZMK + CD8 + T cells, the increased interaction between GZMK + CD8 + T cells and erythrocytes, and the enhanced RESISTIN pathway are potential blood biomarkers of AD.

Underlying Mechanisms of Brain Aging and Neurodegenerative Diseases as Potential Targets for Preventive or Therapeutic Strategies Using Phytochemicals

During aging, several tissues and biological systems undergo a progressive decline in function, leading to age-associated diseases such as neurodegenerative, inflammatory, metabolic, and cardiovascular diseases and cancer. In this review, we focus on the molecular underpinning of senescence and neurodegeneration related to age-associated brain diseases, in particular, Alzheimer's and Parkinson's diseases, along with introducing nutrients or phytochemicals that modulate age-associated molecular dysfunctions, potentially offering preventive or therapeutic benefits. Based on current knowledge, the dysregulation of microglia genes and neuroinflammation, telomere attrition, neuronal stem cell degradation, vascular system dysfunction, reactive oxygen species, loss of chromosome X inactivation in females, and gut microbiome dysbiosis have been seen to play pivotal roles in neurodegeneration in an interactive manner. There are several phytochemicals (e.g., curcumin, EGCG, fucoidan, galangin, astin C, apigenin, resveratrol, phytic acid, acacetin, daucosterol, silibinin, sulforaphane, withaferin A, and betulinic acid) that modulate the dysfunction of one or several key genes (e.g., TREM2, C3, C3aR1, TNFA, NF-kb, TGFB1&2, SIRT1&6, HMGB1, and STING) affected in the aged brain. Although phytochemicals have shown promise in slowing down the progression of age-related brain diseases, more studies to identify their efficacy, alone or in combinations, in preclinical systems can help to design novel nutritional strategies for the management of neurodegenerative diseases in humans.

Serotonin/5-HT7 receptor provides an adaptive signal to enhance pigmentation response to environmental stressors through cAMP-PKA-MAPK, Rab27a/RhoA, and PI3K/AKT signaling pathways

Serotonin (5-HT), a neurotransmitter, is essential for normal and pathological pigmentation processing, and its receptors may be therapeutical targets. The effect and behavior of the 5-HT7 receptor (5-HT7R) in melanogenesis in high vertebrates remain unknown. Herein, we examine the role and molecular mechanism of 5-HT7R in the pigmentation of human skin cells, human tissue, mice, and zebrafish models. Firstly, 5-HT7R protein expression decreased significantly in stress-induced depigmentation skin and vitiligo epidermis. Stressed mice received transdermal serotonin 5-HT7R selective agonists (LP-12, 0.01%) for 12 or 60 days. Mice might recover from persistent stress-induced depigmentation. The downregulation of tyrosinase (Tyr), microphthalmia-associated transcription factor (Mitf) expression, and 5-HT7R was consistently restored in stressed skin. High-throughput RNA sequencing showed that structural organization (dendrite growth and migration) and associated pathways were activated in the dorsal skin of LP-12-treated animals. 5-HT7R selective agonist, LP-12, had been demonstrated to enhance melanin production, dendrite growth, and chemotactic motility in B16F10 cells, normal human melanocytes (NHMCs), and zebrafish. Mechanistically, the melanogenic, dendritic, and migratory functions of 5-HT7R were dependent on the downstream signaling of cAMP-PKA-ERK1/2, JNK MAPK, RhoA/Rab27a, and PI3K/AKT pathway activation. Importantly, pharmacological inhibition and genetic siRNA of 5-HT7R by antagonist SB269970 partially/completely abolished these functional properties and the related activated pathways in both NHMCs and B16F10 cells. Consistently, htr7a/7b genetic knockdown in zebrafish could blockade melanogenic effects and abrogate 5-HT-induced melanin accumulation. Collectively, we have first identified that 5-HT7R regulates melanogenesis, which may be a targeted therapy for pigmentation disorders, especially those worsened by stress.

Integrated single-cell multiomics reveals novel immune candidate markers for post-traumatic coagulopathy

Introduction

Post-traumatic coagulopathy (PTC) is a critical pathology in traumatic brain injury (TBI), however, its potential mechanism is not clear. To explore this in peripheral samples, we integrated single cell RNA-sequencing and T cell repertoire (TCR)-sequencing across a cohort of patients with TBI.

Methods

Clinical samples from patients with more brain severity demonstrated overexpression of T cell receptor-encoding genes and less TCR diversity.

Results

By mapping TCR clonality, we found patients with PTC have less TCR clones, and the TCR clones are mainly distributed in cytotoxic effector CD8+T cell. In addition, the counts of CD8+ T cell and natural killer (NK) cells are associated with the coagulation parameter by WGCNA, and the granzyme and lectin-like receptor profiles are also decreased in the peripheral blood from TBI patients, suggesting that reduced peripheral CD8+ clonality and cytotoxic profiles may be involved in PTC after TBI.

Conclusion

Our work systematically revealed the critical immune status in PTC patients at the single-cell level.

B lymphocytes ameliorate Alzheimer's disease-like neuropathology via interleukin-35

Increasing evidence supports the involvement of the peripheral immune system in the pathogenesis of Alzheimer's disease (AD). In the present study, we found that B lymphocytes could mitigate beta-Amyloid (Aβ) pathology and memory impairments in a transgenic AD mouse model. Specifically, in young 5 × FAD mice, we evidenced increased B cells in the frontal cortex and meningeal tissues; depletion of mature B cells aggravated these mice's Aβ load and memory deficits. The increased B cells produced more interleukin-35 (IL-35) in the front cortex. We further found IL-35 neutralization exacerbated Aβ pathology, while injecting IL-35 mitigated Aβ load and cognitive dysfunction in 5 × FAD mice with or without mature B cell deficiency. Mechanistically, IL-35 inhibited neuronal BACE1 transcription through modulating the SOCS1/STAT1 pathway, and reduced Aβ production accordingly. Reanalysis of the single-cell RNA sequencing data from blood samples of AD patients suggested an increased population of IL-35-producing B cells. Together, the present study revealed a novel effect of B lymphocyte-derived IL-35 on inhibiting Aβ production in the frontal cortex, which may serve as a potential target for future AD treatment.

Neuroimmune mechanisms underlying Alzheimer's disease: Insights into central and peripheral immune cell crosstalk

Alzheimer's disease (AD) is a highly life-threatening neurodegenerative disease. Dysregulation of the immune system plays a critical role in promoting AD, which has attracted extensive attention recently. Central and peripheral immune responses are involved in the pathogenesis of AD. Immune changes precede Aβ-associated senile plaque formation and tau-related neurofibrillary tangles, which are the recognised pathological features of AD. Therefore, elucidating immune-related mechanisms underlying the development of AD can help to prevent and treat AD at the source by blocking its progression before the development of pathological changes. To understand the specific pathogenesis of AD, it is important to examine the role of central and peripheral immunity in AD. This review summarises immune-related mechanisms underlying the pathogenesis of AD, focusing on the effect of various central and peripheral immune cells, and describes the possible crosstalk between central and peripheral immunity during the development of AD. This review provides novel insights into the treatment of AD and offers a new direction for immune-related research on AD in the future.

Acquired immunity and Alzheimer's disease

Alzheimer's disease (AD) is an age-related neurodegenerative disease characterized by progressive cognitive defects. The role of the central immune system dominated by microglia in the progression of AD has been extensively investigated. However, little is known about the peripheral immune system in AD pathogenesis. Recently, with the discovery of the meningeal lymphatic vessels and glymphatic system, the roles of the acquired immunity in the maintenance of central homeostasis and neurodegenerative diseases have attracted an increasing attention. The T cells not only regulate the function of neurons, astrocytes, microglia, oligodendrocytes and brain microvascular endothelial cells, but also participate in the clearance of β-amyloid (Aβ) plaques. Apart from producing antibodies to bind Aβ peptides, the B cells affect Aβ-related cascades via a variety of antibody-independent mechanisms. This review systemically summarizes the recent progress in understanding pathophysiological roles of the T cells and B cells in AD.

Glia as antigen-presenting cells in the central nervous system

The contribution of the cells within the central nervous system (CNS) toward adaptive immune responses is emerging and incompletely understood. Recent findings indicate important functional interactions between T-cells and glial cells within the CNS that may contribute to disease and neuropathology through antigen presentation. Although glia are not classically considered antigen-presenting cell (APC) types, there is growing evidence indicating that glial antigen presentation plays an important role in several neurological diseases. This review discusses these findings which incriminate microglia, astrocytes, and oligodendrocyte lineage cells as CNS-resident APC types with implications for understanding disease.

Identification of diagnostic genes for both Alzheimer's disease and Metabolic syndrome by the machine learning algorithm

BACKGROUND

Alzheimer's disease is the most common neurodegenerative disease worldwide. Metabolic syndrome is the most common metabolic and endocrine disease in the elderly. Some studies have suggested a possible association between MetS and AD, but few studied genes that have a co-diagnostic role in both diseases.

METHODS

The microarray data of AD (GSE63060 and GSE63061 were merged after the batch effect was removed) and MetS (GSE98895) in the GEO database were downloaded. The WGCNA was used to identify the co-expression modules related to AD and MetS. RF and LASSO were used to identify the candidate genes. Machine learning XGBoost improves the diagnostic effect of hub gene in AD and MetS. The CIBERSORT algorithm was performed to assess immune cell infiltration MetS and AD samples and to investigate the relationship between biomarkers and infiltrating immune cells. The peripheral blood mononuclear cells (PBMCs) single-cell RNA (scRNA) sequencing data from patients with AD and normal individuals were visualized with the Seurat standard flow dimension reduction clustering the metabolic pathway activity changes each cell with ssGSEA.

RESULTS

The brown module was identified as the significant module with AD and MetS. GO analysis of shared genes showed that intracellular transport and establishment of localization in cell and organelle organization were enriched in the pathophysiology of AD and MetS. By using RF and Lasso learning methods, we finally obtained eight diagnostic genes, namely ARHGAP4, SNRPG, UQCRB, PSMA3, DPM1, MED6, RPL36AL and RPS27A. Their AUC were all greater than 0.7. Higher immune cell infiltrations expressions were found in the two diseases and were positively linked to the characteristic genes. The scRNA-seq datasets finally obtained seven cell clusters. Seven major cell types including CD8 T cell, monocytes, T cells, NK cell, B cells, dendritic cells and macrophages were clustered according to immune cell markers. The ssGSEA revealed that immune-related gene (SNRPG) was significantly regulated in the glycolysis-metabolic pathway.

CONCLUSION

We identified genes with common diagnostic effects on both MetS and AD, and found genes involved in multiple metabolic pathways associated with various immune cells.

Association of B cell profile and receptor repertoire with the progression of Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent type of dementia. Reports have revealed that the peripheral immune system is linked to neuropathology; however, little is known about the contribution of B lymphocytes in AD. For this longitudinal study, 133 participants are included at baseline and second-year follow-up. Also, we analyze B cell receptor (BCR) repertoire data generated from a public dataset of three normal and 10 AD samples and perform BCR repertoire profiling and pairwise sharing analysis. As a result, longitudinal increase in B lymphocytes is associated with increased cerebral amyloid deposition and hyperactivates induced pluripotent stem cell-derived microglia with loss-of-function for beta-amyloid clearance. Patients with AD share similar class-switched BCR sequences with identical isotypes, despite the high somatic hypermutation rate. Thus, BCR repertoire profiling can lead to the development of individualized immune-based therapeutics and treatment. We provide evidence of both quantitative and qualitative changes in B lymphocytes during AD pathogenesis.