Genetic networks in Parkinson's and Alzheimer's disease

Normative aging results in degradation of gene networks in a zebra finch basal ganglia nucleus dedicated to vocal behavior

Aging increases brain susceptibility to neurodegenerative diseases, but the mechanisms are not clear. Vocal behavior provides an accessible, reliable, and sensitive biomarker to address this because voice changes in middle age can be early indicators of neurodegenerative diseases. The adult male zebra finch is an excellent model organism for these studies due to well-characterized vocal brain circuitry and strong homology to human brain centers. We performed RNA sequencing of song-dedicated basal ganglia nucleus Area X followed by weighted gene co-expression network analyses to examine changes in gene patterns across younger adult, middle, and older ages. Song-correlated gene networks degrade with age, with modules losing their coherence and migrating to different sets of genes, and changes in connection strength particularly for hub genes including those associated with human speech, Parkinson's, and Alzheimer's diseases. Gene pathway enrichment analyses reveal a lack of ongoing metabolic and biogenic processes in older finches. Our findings provide a robust platform for targeting network hubs in the treatment of neurologically driven human vocal disorders.

Sex-specific transcriptome similarity networks elucidate comorbidity relationships

Humans present sex-driven biological differences. Consequently, the prevalence of analyzing specific diseases and comorbidities differs between the sexes, directly impacting patients' management and treatment. Despite its relevance and the growing evidence of said differences across numerous diseases (with 4,370 PubMed results published within the past year), knowledge at the comorbidity level remains limited. In fact, to date, no study has attempted to identify the biological processes altered differently in women and men, promoting differences in comorbidities. To shed light on this problem, we analyze expression data for more than 100 diseases from public repositories, analyzing each sex independently. We calculate similarities between differential expression profiles by disease pairs and find that 13-16% of transcriptomically similar disease pairs are sex-specific. By comparing these results with epidemiological evidence, we recapitulate 53-60% of known comorbidities distinctly described for men and women, finding sex-specific transcriptomic similarities between sex-specific comorbid diseases. The analysis of shared underlying pathways shows that diseases can co-occur in men and women by altering alternative biological processes. Finally, we identify different drugs differentially associated with comorbid diseases depending on patients' sex, highlighting the need to consider this relevant variable in the administration of drugs due to their possible influence on comorbidities.

Maackiain: A comprehensive review of its pharmacology, synthesis, pharmacokinetics and toxicity

Maackiain is an important component of some herbs in traditional Chinese medicine (TCM), such as Sophora flavescens Aiton, Spatholobus suberectus Dunn and Paeonia lactiflora Pall. Maackiain belongs to the second largest group of isoflavonoids the pterocarpans that is widespread in several plant genera, for example Maackia, Sophora, Caragana, Trifolium and Millettia. Recently, maackiain has attracting more attention because of its numerous pharmacological properties. This review offers the first extensive overview of maackiain natural isolation sources, pharmacological activities, synthesis, toxicity, and pharmacokinetic properties. The literature search published between 1962 and 2023 were reported by collecting the data from Google Scholar, Science Direct, SpringerLink, Web of Science, PubMed, Wiley Online, China National Knowledge Infrastructure, Scopus and structure search in SciFinder. Finding reveals the broad range of pharmacological activities of maackiain, such as anti-inflammatory, sepsis prevention, anti-cancer, anti-allergic, anti-osteolytic, anti-obesity, nephroprotective, antifungal, neuroprotective, anti-leukemic, antimalarial and inflammasome activation. Based on findings of pharmacokinetic studies, it is observed that maackiain possesses a low level of bioavailability and absorption and a rapid rate of elimination, but maackiain absorption rates in the extract were comparatively much higher than pure forms because of higher solubility and may reduce the metabolism by other ingredients present in the extract. Toxicity investigations revealed that maackiain is non-toxic to the majority of cells and selectively cytotoxic. After witnessing the beneficial pharmacological properties of maackiain, it is believed to be an emerging drug candidate for the treatment of inflammation, allergic, nephroprotection in T2D, depression, or Alzheimer's disease and obesity. However, future research topics should likely to include that elucidates its mechanism of toxicity and in vivo proper tracking of its conducts in drug delivery system. Integrating toxicity and efficiency, as well as structure modification, are critical approaches to enhancing its pharmacological properties and oral bioavailability.

Phlorizin ameliorates cognitive and behavioral impairments via the microbiota-gut-brain axis in high-fat and high-fructose diet-induced obese male mice

The long-term high-fat, high-sugar diet exacerbates type 2 diabetes mellitus (T2DM)-related cognitive impairments. Phlorizin, a well-studied natural compound found in apples and other plants, is recognized for its bioactive properties, including modulation of glucose and lipid metabolism. Despite its established role in mitigating metabolic disorders, the neuroprotective effects of phlorizin, particularly against diabetes-related cognitive dysfunction, have not been fully elucidated. Therefore, the present study aimed to investigate the effect of dietary supplementation of phlorizin on high-fat and high-fructose diet (HFFD)-induced cognitive dysfunction and evaluate the crucial role of the microbiota-gut-brain axis. We found that dietary supplementation of phlorizin for 14 weeks effectively prevented glucolipid metabolism disorder, spatial learning impairment, and memory impairment in HFFD mice. In addition, phlorizin improved the HFFD-induced decrease in synaptic plasticity, neuroinflammation, and excessive activation of microglia in the hippocampus. Transcriptomics analysis shows that the protective effect of phlorizin on cognitive impairment was associated with increased expression of neurotransmitters and synapse-related genes in the hippocampus. Phlorizin treatment alleviated colon microbiota disturbance, mainly manifested by an increase in gut microbiota diversity and the abundance of short-chain fatty acid (SCFA)-producing bacteria. The level of microbial metabolites, including SCFA, inosine 5'-monophosphate (IMP), and D (-)-beta-hydroxybutyric acid (BHB) were also significantly increased after phlorizin treatment. Integrating multiomics analysis observed tight connections between phlorizin-regulated genes, microbiota, and metabolites. Furthermore, removal of the gut microbiota via antibiotics treatment diminished the protective effect of phlorizin against HFFD-induced cognitive impairment, underscoring the critical role of the gut microbiota in mediating cognitive behavior. Importantly, supplementation with SCFA and BHB alone mimicked the regulatory effects of phlorizin on cognitive function. Therefore, phlorizin shows promise as a potential nutritional therapy for addressing cognitive impairment associated with metabolic disorders. Further research is needed to explore its effectiveness in preventing and alleviating neurodegenerative diseases.

Understanding the (epi)genetic dysregulation in Parkinson's disease through an integrative brain competitive endogenous RNA network

Parkinson's disease (PD) is a rapidly growing neurodegenerative disorder characterized by dopaminergic neuron loss in the substantia nigra pars compacta (SN) and aggregation of α-synuclein. Its aetiology involves a multifaceted interplay among genetic, environmental, and epigenetic factors. We integrated brain gene expression data from PD patients to construct a comprehensive regulatory network encompassing messenger RNAs (mRNAs), microRNAs (miRNAs), circular RNAs (circRNAs) and, for the first time, RNA binding proteins (RBPs). Expression data from the SN of PD patients and controls were systematically selected from public databases to identify combined differentially expressed genes (DEGs). Brain co-expression analysis revealed modules comprising significant DEGs that function cooperatively. The relationships among co-expressed DEGs, miRNAs, circRNAs, and RBPs revealed an intricate competitive endogenous RNA (ceRNA) network responsible for post-transcriptional dysregulation in PD. Many genes in the ceRNA network, including the TOMM20 and HMGCR genes, overlap with the most relevant genes in our previous Alzheimer's disease-associated ceRNA network, suggesting common underlying mechanisms between both conditions. Moreover, in the ceRNA subnetwork, the RBP Aly/REF export factor (ALYREF), which acts as an RNA 5-methylcytosine(m5C)-binding protein, stood out. Our data sheds new light on the potential role of brain ceRNA networks in PD pathogenesis.

Cerebral Artery Overexpression of the NMUR1 Gene Is Associated with Moyamoya Disease: A Weighted Gene Co-Expression Network Analysis

INTRODUCTION

This study aimed to elucidate mechanisms underlying moyamoya disease (MMD) pathogenesis and to identify potential novel biomarkers. We utilized gene co-expression networks to identify hub genes associated with the disease.

METHODS

Twenty-one middle cerebral artery (MCA) samples from MMD patients and 11 MCA control samples were obtained from the Gene Expression Omnibus (GEO) dataset, GSE189993. To discover functional pathways and potential biomarkers, weighted gene co-expression network analysis (WGCNA) was employed. The hub genes identified were re-assessed through differential gene expression analysis (DGEA) via DESeq2 for further reliability verification. Additional 4 samples from the superficial temporal arteries (STAs) from MMD patients were obtained from GSE141025, and a subgroup analysis stratified by arterial type (MCA vs. STA) DGEA was performed to assess if the hub genes associated with MMD are expressed significantly greater on the affected arteries compared to healthy ones in MMD.

RESULTS

WGCNA revealed a predominant module encompassing 139 hub genes, predominantly associated with the neuroactive ligand-receptor interaction (NLRI) pathway. Of those, 17 genes were validated as significantly differentially expressed. Neuromedin U receptor 1 (NMUR1) and thyrotropin-releasing hormone were 2 out of the 17 hub genes involved in the NLRI pathway (log fold change [logFC]: 1.150, p = 0.00028; logFC: 1.146, p = 0.00115, respectively). MMD-only subgroup analysis stratified by location showed that NMUR1 is significantly overexpressed in the MCA compared to the STA (logFC: 1.962; p = 0.00053) which further suggests its possible localized involvement in the progressive stenosis seen in the cerebral arteries in MMD.

CONCLUSION

This is the first study to have performed WGCNA on samples directly affected by MMD. NMUR1 expression is well known to induce localized arterial smooth muscle constriction and, recently, type 2 inflammation which can predispose to arterial stenosis potentially advancing the symptoms and progression of MMD. Further validation and functional studies are necessary to understand the precise role of NMUR1 upregulation in MMD and its potential implications.

A review and analysis of key biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

Blood biomarker-based classification study for neurodegenerative diseases

As the population ages, neurodegenerative diseases are becoming more prevalent, making it crucial to comprehend the underlying disease mechanisms and identify biomarkers to allow for early diagnosis and effective screening for clinical trials. Thanks to advancements in gene expression profiling, it is now possible to search for disease biomarkers on an unprecedented scale.Here we applied a selection of five machine learning (ML) approaches to identify blood-based biomarkers for Alzheimer's (AD) and Parkinson's disease (PD) with the application of multiple feature selection methods. Based on ROC AUC performance, one optimal random forest (RF) model was discovered for AD with 159 gene markers (ROC-AUC = 0.886), while one optimal RF model was discovered for PD (ROC-AUC = 0.743). Additionally, in comparison to traditional ML approaches, deep learning approaches were applied to evaluate their potential applications in future works. We demonstrated that convolutional neural networks perform consistently well across both the Alzheimer's (ROC AUC = 0.810) and Parkinson's (ROC AUC = 0.715) datasets, suggesting its potential in gene expression biomarker detection with increased tuning of their architecture.

Orchestration of a blood-derived and ADARB1-centred network in Alzheimer's and Parkinson's disease

The peripheral immune system is thought to influence the pathogenesis of the central nervous system in Alzheimer's disease (AD) and Parkinson's disease (PD). This study aimed to investigate the characteristics of peripheral leukocytes in AD and PD by comprehensively analyzing the transcriptomic and metabolic features in the blood (NCONTROL = 15; NAD = 11; NPD = 13). The study found an ADARB1-centered module that was associated with diagnosis, phenethylamine, and glutamate. The module consisted of ADARB1, a vital RNA-editing enzyme, LINC02960, and 109 miRNAs. The study also predicted that the ADARB1 and involved regulators were targeted by miRNAs in the ADARB1 module. The integrated analysis of transcriptome and metabolic panel revealed a central role of ADARB1, miR-199b-5p, miR-26a, miR-450b-5p, miR-34c-5p, glutamate and phenethylamine in the regulatory relationships. The study highlights a set of synergetic non-coding RNA related to ADARB1 in the blood ecosystem of AD and PD with dynamic glutamate and phenethylamine, providing new insights into the pathogenesis of these diseases.

Investigation of Anti-Alzheimer's Mechanisms of Sarsasapogenin Derivatives by Network-Based Combining Structure-Based Methods

Alzheimer's disease (AD), a neurodegenerative disease with no cure, affects millions of people worldwide and has become one of the biggest healthcare challenges. Some investigated compounds play anti-AD roles at the cellular or the animal level, but their molecular mechanisms remain unclear. In this study, we designed a strategy combining network-based and structure-based methods together to identify targets for anti-AD sarsasapogenin derivatives (AAs). First, we collected drug-target interactions (DTIs) data from public databases, constructed a global DTI network, and generated drug-substructure associations. After network construction, network-based models were built for DTI prediction. The best bSDTNBI-FCFP_4 model was further used to predict DTIs for AAs. Second, a structure-based molecular docking method was employed for rescreening the prediction results to obtain more credible target proteins. Finally, in vitro experiments were conducted for validation of the predicted targets, and Nrf2 showed significant evidence as the target of anti-AD compound AA13. Moreover, we analyzed the potential mechanisms of AA13 for the treatment of AD. Generally, our combined strategy could be applied to other novel drugs or compounds and become a useful tool in identification of new targets and elucidation of disease mechanisms. Our model was deployed on our NetInfer web server (http://lmmd.ecust.edu.cn/netinfer/).

Genetic correlation and gene-based pleiotropy analysis for four major neurodegenerative diseases with summary statistics

Recent genome-wide association studies suggested shared genetic components between neurodegenerative diseases. However, pleiotropic association patterns among them remain poorly understood. We here analyzed 4 major neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), and found suggestively positive genetic correlation. We next implemented a gene-centric pleiotropy analysis with a powerful method called PLACO and detected 280 pleiotropic associations (226 unique genes) with these diseases. Functional analyses demonstrated that these genes were enriched in the pancreas, liver, heart, blood, brain, and muscle tissues; and that 42 pleiotropic genes exhibited drug-gene interactions with 341 drugs. Using Mendelian randomization, we discovered that AD and PD can increase the risk of developing ALS, and that AD and ALS can also increase the risk of developing FTD, respectively. Overall, this study provides in-depth insights into shared genetic components and causal relationship among the 4 major neurodegenerative diseases, indicating genetic overlap and causality commonly drive their co-occurrence. It also has important implications on the etiology understanding, drug development and therapeutic targets for neurodegenerative diseases.

Alzheimer's Disease and Alzheimer's Disease-Related Dementias in African Americans: Focus on Caregivers

Alzheimer's disease (AD) and Alzheimer's Disease-Related Dementias (ADRD) are chronic illnesses that are highly prevalent in African Americans (AA). AD and ADRD are caused by multiple factors, such as genetic mutations, modifiable and non-modifiable risk factors, and lifestyle. Histopathological, morphological, and cellular studies revealed how multiple cellular changes are implicated in AD and ADRD, including synaptic damage, inflammatory responses, hormonal imbalance, mitochondrial abnormalities, and neuronal loss, in addition to the accumulation of amyloid beta and phosphorylated tau in the brain. The contributions of race, ethnicity, location and socioeconomic status all have a significant impact on the care and support services available to dementia patients. Furthermore, disparities in health care are entangled with social, economic, and environmental variables that perpetuate disadvantages among different groups, particularly African Americans. As such, it remains important to understand how various racial and ethnic groups perceive, access, and experience health care. Considering that the mounting data shows AA may be more susceptible to AD than white people, the demographic transition creates significant hurdles in providing adequate care from family caregivers. Furthermore, there is growing recognition that AD and ADRD pose a significant stress on AA caregivers compared to white people. In this review, we examine the current literature on racial disparities in AD and ADRD, particularly concerning AA caregivers.

Mechanism of action deconvolution of the small-molecule pathological tau aggregation inhibitor Anle138b

BACKGROUND

A key histopathological hallmark of Alzheimer's disease (AD) is the presence of neurofibrillary tangles of aggregated microtubule-associated protein tau in neurons. Anle138b is a small molecule which has previously shown efficacy in mice in reducing tau aggregates and rescuing AD disease phenotypes.

METHODS

In this work, we employed bioinformatics analysis-including pathway enrichment and causal reasoning-of an in vitro tauopathy model. The model consisted of cultured rat cortical neurons either unseeded or seeded with tau aggregates derived from human AD patients, both of which were treated with Anle138b to generate hypotheses for its mode of action. In parallel, we used a collection of human target prediction models to predict direct targets of Anle138b based on its chemical structure.

RESULTS

Combining the different approaches, we found evidence supporting the hypothesis that the action of Anle138b involves several processes which are key to AD progression, including cholesterol homeostasis and neuroinflammation. On the pathway level, we found significantly enriched pathways related to these two processes including those entitled "Superpathway of cholesterol biosynthesis" and "Granulocyte adhesion and diapedesis". With causal reasoning, we inferred differential activity of SREBF1/2 (involved in cholesterol regulation) and mediators of the inflammatory response such as NFKB1 and RELA. Notably, our findings were also observed in Anle138b-treated unseeded neurons, meaning that the inferred processes are independent of tau pathology and thus represent the direct action of the compound in the cellular system. Through structure-based ligand-target prediction, we predicted the intracellular cholesterol carrier NPC1 as well as NF-κB subunits as potential targets of Anle138b, with structurally similar compounds in the model training set known to target the same proteins.

CONCLUSIONS

This study has generated feasible hypotheses for the potential mechanism of action of Anle138b, which will enable the development of future molecular interventions aiming to reduce tau pathology in AD patients.

GRK5 Deficiency in the Hippocampus Leads to Cognitive Impairment via Abnormal Microglial Alterations

GRK5 is a member of the G protein-coupled receptor (GPCR) kinase family and is closely associated with heart and nervous system disease. It has been reported that GRK5 is closely related to cerebral nerve function and neurodegenerative diseases. However, the biological function of GRK5 in the brain and the influence of GRK5 deficiency on cognitive dysfunction associated with neurodegenerative diseases are unknown. Here, we reported that mice with reduced GRK5 in the hippocampus exhibit cognitive impairment and some Alzheimer's disease (AD)-related molecular pathologies, such as significant neuronal damage and loss, enhanced tau protein phosphorylation, and increased levels of Aβ peptides in the hippocampus. Mechanistically, we observed that GRK5 is located in microglia and plays an essential role in maintaining the morphology and function of microglia. GRK5 deficiency elicits microglial morphology changes and proinflammatory-associated gene increases. In addition, transcriptional analysis of hippocampal tissues revealed striking changes in neuroactive ligand‒receptor interactions and TNF signaling in GRK5-deficient mice. In conclusion, our results further confirm the vital role of GRK5 in maintaining normal cognitive function in mice. This finding suggests a possible mechanism by which GRK5 maintains microglial homeostasis, and its loss may induce microglial function deficits and cause some AD-related molecular pathogenesis.

Functionally Validating Evolutionary Conserved Risk Genes for Parkinson's Disease in Drosophila melanogaster

Parkinson's disease (PD) is a heterogeneous and complex neurodegenerative disorder and large-scale genetic studies have identified >130 genes associated with PD. Although genomic studies have been decisive for our understanding of the genetic contributions underlying PD, these associations remain as statistical associations. Lack of functional validation limits the biological interpretation; however, it is labour extensive, expensive, and time consuming. Therefore, the ideal biological system for functionally validating genetic findings must be simple. The study aim was to assess systematically evolutionary conserved PD-associated genes using Drosophila melanogaster. From a literature review, a total of 136 genes have found to be associated with PD in GWAS studies, of which 11 are strongly evolutionary conserved between Homo sapiens and D. melanogaster. By ubiquitous gene expression knockdown of the PD-genes in D. melanogaster, the flies' escape response was investigated by assessing their negative geotaxis response, a phenotype that has previously been used to investigate PD in D. melanogaster. Gene expression knockdown was successful in 9/11 lines, and phenotypic consequences were observed in 8/9 lines. The results provide evidence that genetically modifying expression levels of PD genes in D. melanogaster caused reduced climbing ability of the flies, potentially supporting their role in dysfunctional locomotion, a hallmark of PD.

Polygenic Liability to Alzheimer's Disease Is Associated with a Wide Range of Chronic Diseases: A Cohort Study of 312,305 Participants

BACKGROUND

Alzheimer's disease (AD) patients rank among the highest levels of comorbidities compared to persons with other diseases. However, it is unclear whether the conditions are caused by shared pathophysiology due to the genetic pleiotropy for AD risk genes.

OBJECTIVE

To figure out the genetic pleiotropy for AD risk genes in a wide range of diseases.

METHODS

We estimated the polygenic risk score (PRS) for AD and tested the association between PRS and 16 ICD10 main chapters, 136 ICD10 level-1 chapters, and 377 diseases with cases more than 1,000 in 312,305 individuals without AD diagnosis from the UK Biobank.

RESULTS

After correction for multiple testing, AD PRS was associated with two main ICD10 chapters: Chapter IV (endocrine, nutritional and metabolic diseases) and Chapter VII (eye and adnexa disorders). When narrowing the definition of the phenotypes, positive associations were observed between AD PRS and other types of dementia (OR = 1.39, 95% CI [1.34, 1.45], p = 1.96E-59) and other degenerative diseases of the nervous system (OR = 1.18, 95% CI [1.13, 1.24], p = 7.74E-10). In contrast, we detected negative associations between AD PRS and diabetes mellitus, obesity, chronic bronchitis, other retinal disorders, pancreas diseases, and cholecystitis without cholelithiasis (ORs range from 0.94 to 0.97, FDR < 0.05).

CONCLUSION

Our study confirms several associations reported previously and finds some novel results, which extends the knowledge of genetic pleiotropy for AD in a range of diseases. Further mechanistic studies are necessary to illustrate the molecular mechanisms behind these associations.

Multi-omics analysis reveals GABAergic dysfunction after traumatic brainstem injury in rats

Background

Traumatic brainstem injury (TBSI) is one of the forms of brain injury and has a very high mortality rate. Understanding the molecular mechanism of injury can provide additional information for clinical treatment.

Materials and methods

In this study, we detected transcriptome, proteomics, and metabolome expression changes in the brainstem of TBSI rats, and comprehensively analyzed the underlying mechanisms of TBSI.

Results

After TBSI, there was significant diffuse axonal injury (DAI) in the brainstem of rats. A total of 579 genes, 70 proteins, and 183 metabolites showed significant changes in brainstem tissue. Through molecular function and pathway analysis, the differentially expressed genes, proteins, and metabolites of TBSI were mainly attributed to neural signal regulation, inflammation, neuroprotection, and immune system. In addition, a comprehensive analysis of transcripts, proteins, and metabolites showed that the genes, proteins, and metabolic pathways regulated in the brainstem after TBSI were involved in neuroactive ligand-receptor interaction. A variety of GCPR-regulated pathways were affected, especially GAGA's corresponding receptors GABA_A, GABA_B, GABA_C, and transporter GAT that were inhibited to varying degrees.

Conclusion

This study provides insights into the development of a rapid diagnostic kit and making treatment strategies for TBSI.

Single-cell network biology characterizes cell type gene regulation for drug repurposing and phenotype prediction in Alzheimer's disease

Dysregulation of gene expression in Alzheimer's disease (AD) remains elusive, especially at the cell type level. Gene regulatory network, a key molecular mechanism linking transcription factors (TFs) and regulatory elements to govern gene expression, can change across cell types in the human brain and thus serve as a model for studying gene dysregulation in AD. However, AD-induced regulatory changes across brain cell types remains uncharted. To address this, we integrated single-cell multi-omics datasets to predict the gene regulatory networks of four major cell types, excitatory and inhibitory neurons, microglia and oligodendrocytes, in control and AD brains. Importantly, we analyzed and compared the structural and topological features of networks across cell types and examined changes in AD. Our analysis shows that hub TFs are largely common across cell types and AD-related changes are relatively more prominent in some cell types (e.g., microglia). The regulatory logics of enriched network motifs (e.g., feed-forward loops) further uncover cell type-specific TF-TF cooperativities in gene regulation. The cell type networks are also highly modular and several network modules with cell-type-specific expression changes in AD pathology are enriched with AD-risk genes. The further disease-module-drug association analysis suggests cell-type candidate drugs and their potential target genes. Finally, our network-based machine learning analysis systematically prioritized cell type risk genes likely involved in AD. Our strategy is validated using an independent dataset which showed that top ranked genes can predict clinical phenotypes (e.g., cognitive impairment) of AD with reasonable accuracy. Overall, this single-cell network biology analysis provides a comprehensive map linking genes, regulatory networks, cell types and drug targets and reveals cell-type gene dysregulation in AD.

Associations of ARHGAP26 Polymorphisms with Alzheimer's Disease and Cardiovascular Disease

The Rho GTPase activating protein 26 (ARHGAP26) gene has been reported to be associated with neuropsychiatric diseases and neurodegenerative diseases including Parkinson's disease. We examined whether the ARHGAP26 gene is associated with Alzheimer's disease (AD) and/or cardiovascular disease (CVD). Multivariable logistic regression model was used to examine the associations of 154 single nucleotide polymorphisms (SNPs) within the ARHGAP26 gene with AD and CVD using the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) cohort. Fourteen SNPs were associated with AD (top SNP rs3776362 with p = 3.43 × 10^-3), while 37 SNPs revealed associations with CVD (top SNP rs415235 with p = 2.06 × 10^-4). Interestingly, 13 SNPs were associated with both AD and CVD. SNP rs3776362 was associated with CVD, Functional Activities Questionnaire (FAQ), and Clinical Dementia Rating Sum of Boxes (CDR-SB). A replication study using a Caribbean Hispanics sample showed that 17 SNPs revealed associations with AD, and 12 SNPs were associated with CVD. The third sample using a family-based study design showed that 9 SNPs were associated with AD, and 3 SNPs were associated with CVD. SNP rs6836509 within the ARHGAP10 gene (an important paralogon of ARHGAP26) was associated with AD and cerebrospinal fluid total tau (t-tau) level in the ADNI sample. Several SNPs were functionally important using the RegulomeDB, while a number of SNPs were associated with significant expression quantitative trait loci (eQTLs) using Genotype-Tissue Expression (GTEx) databases. In conclusion, genetic variants within ARHGAP26 were associated with AD and CVD. These findings add important new insights into the potentially shared pathogenesis of AD and CVD.

Preservation Analysis on Spatiotemporal Specific Co-expression Networks Suggests the Immunopathogenesis of Alzheimer's Disease

The occurrence and development of Alzheimer’s disease (AD) is a continuous clinical and pathophysiological process, molecular biological, and brain functional change often appear before clinical symptoms, but the detailed underlying mechanism is still unclear. The expression profiling of postmortem brain tissue from AD patients and controls provides evidence about AD etiopathogenesis. In the current study, we used published AD expression profiling data to construct spatiotemporal specific coexpression networks in AD and analyzed the network preservation features of each brain region in different disease stages to identify the most dramatically changed coexpression modules and obtained AD-related biological pathways, brain regions and circuits, cell types and key genes based on these modules. As result, we constructed 57 spatiotemporal specific networks (19 brain regions by three disease stages) in AD and observed universal expression changes in all 19 brain regions. The eight most dramatically changed coexpression modules were identified in seven brain regions. Genes in these modules are mostly involved in immune response-related pathways and non-neuron cells, and this supports the immune pathology of AD and suggests the role of blood brain barrier (BBB) injuries. Differentially expressed genes (DEGs) meta-analysis and protein–protein interaction (PPI) network analysis suggested potential key genes involved in AD development that might be therapeutic targets. In conclusion, our systematical network analysis on published AD expression profiling data suggests the immunopathogenesis of AD and identifies key brain regions and genes.

N6-methyladenosine (m6A) modification and its clinical relevance in cognitive dysfunctions

BACKGROUND

N6 adenosine methylation (m6A) is the most abundant internal RNA modification in eukaryotic cells. Dysregulation of m6A has been associated with the perturbations of cell proliferation and cell death in different diseases. However, the roles of m6A in the neurodegenerative process and cognitive dysfunction are unclear.

METHODS

We systematically investigated the molecular alterations of m6A regulators and their clinical relevance with cognitive dysfunctions using published datasets of Alzheimer's Disease (AD), vascular dementia, and mild cognitive impairment (MCI).

FINDINGS

The expressions of m6A regulators vary in different tissues and closely correlate with neurodegenerative pathways. We identified co-expressive m6A regulators SNRPG and SNRPD2 as potential biomarkers to predict transformation from MCI to AD. Moreover, we explored correlations between Apolipoprotein E4 and m6A methylations.

INTERPRETATION

Collectively, these findings suggest that m6A methylations as potential biomarkers and therapeutic targets for cognitive dysfunction.

FUNDING

This work was supported by the National Natural Science Foundation of China (81871040) and the Shanghai Health System Talent Training Program (2018BR29).

Revealing the Modular Similarities and Differences Among Alzheimer's Disease, Vascular Dementia, and Parkinson's Disease in Genomic Networks

Alzheimer's disease (AD), vascular dementia (VD), and Parkinson's disease (PD) exert increasingly lethal or disabling effects on humans, but the associations among these diseases at the molecular level remain unclear. In our research, lists of genes related to these three diseases were acquired from public databases. We constructed gene-gene networks of the lists of disease-related genes using the STRING database and selected the plug-in MCODE as the most suitable method to divide the three disease-associated networks into modules through an entropy calculation. Notably, 1173 AD-related, 203 VD-related, and 722 PD-related genes as well as 72 overlapping genes were observed among the three diseases. By dividing the modules from the gene network, we divided the AD-related gene network into 27 modules, the VD-related gene network into 8 modules, and the PD-related gene network into 17 modules. After the enrichment analysis of each disease-related gene, 146 overlapping biological processes and 32 overlapping pathways were identified. Ultimately, through similarity analysis of the genes, biological processes, and pathways, we found that AD and VD were the most closely related at the biological process and pathway levels, with similarity coefficients of 0.2784 and 0.3626, respectively. After analyzing the overlapping gene network, we found that INS might play an important role in the network and that insulin and its signaling pathways may play a key role in these neurodegenerative diseases. Our research illustrates a new method for in-depth research on the three diseases, which may accelerate the progress of developing new therapeutics and may be applied to prevent neurodegenerative diseases.

Identifying molecular targets for reverse aging using integrated network analysis of transcriptomic and epigenomic changes during aging

Aging is associated with widespread physiological changes, including skeletal muscle weakening, neuron system degeneration, hair loss, and skin wrinkling. Previous studies have identified numerous molecular biomarkers involved in these changes, but their regulatory mechanisms and functional repercussions remain elusive. In this study, we conducted next-generation sequencing of DNA methylation and RNA sequencing of blood samples from 51 healthy adults between 20 and 74 years of age and identified aging-related epigenetic and transcriptomic biomarkers. We also identified candidate molecular targets that can reversely regulate the transcriptomic biomarkers of aging by reconstructing a gene regulatory network model and performing signal flow analysis. For validation, we screened public experimental data including gene expression profiles in response to thousands of chemical perturbagens. Despite insufficient data on the binding targets of perturbagens and their modes of action, curcumin, which reversely regulated the biomarkers in the experimental dataset, was found to bind and inhibit JUN, which was identified as a candidate target via signal flow analysis. Collectively, our results demonstrate the utility of a network model for integrative analysis of omics data, which can help elucidate inter-omics regulatory mechanisms and develop therapeutic strategies against aging.

Real-Time and Sensitive Immunosensor for Label-Free Detection of Specific Antigen with a Comb of Microchannel Long-Period Fiber Grating

This study aimed to develop a comb of microchannel and immunosensor based on long-period fiber grating using the process of Lithographie Galvanoformung Abformung-like micro-electromechanical systems (LIGA-like MEMS) for real-time and label-free detection of specific antigen. The coupling between propagating core and cladding modes was conducted from the comb of microchannel long-period fiber grating (CM-LPFG). The CM-LPFG-based immunosensor consisted of a microchannel structure through photoresist stacking processes and was sandwiched with an optical fiber to obtain a long-period structure. Specific immunoglobulin against protein antigen was immobilized onto an optical fiber surface and produced a real-time resonance effect on sensing specific protein antigen from the extracted protein mixtures of the cancer cell lines. The variable transmission loss was -14.07 dB, and the resonant wavelength shift was 11.239 nm. The low limit of detection for total protein concentration was 1.363 ng/μL. Our results revealed that the CM-LPFG-based immnosensor for real-time detection of label-free protein antigen is feasible and sensitive based on the diversification of a transmission loss and achieves specific immunosensing purposes for lab-on-fiber technology.