Altered neuronal gene expression in brain regions differentially affected by Alzheimer's disease: a reference data set

miRNAs in cerebrospinal fluid associated with Alzheimer's disease: A systematic review and pathway analysis using a data mining and machine learning approach

Alzheimer's disease (AD) is the most common type and accounts for 60%-70% of the reported cases of dementia. MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in gene expression regulation. Although the diagnosis of AD is primarily clinical, several miRNAs have been associated with AD and considered as potential markers for diagnosis and progression of AD. We sought to match AD-related miRNAs in cerebrospinal fluid (CSF) found in the GeoDataSets, evaluated by machine learning, with miRNAs listed in a systematic review, and a pathway analysis. Using machine learning approaches, we identified most differentially expressed miRNAs in Gene Expression Omnibus (GEO), which were validated by the systematic review, using the acronym PECO-Population (P): Patients with AD, Exposure (E): expression of miRNAs, Comparison (C): Healthy individuals, and Objective (O): miRNAs differentially expressed in CSF. Additionally, pathway enrichment analysis was performed to identify the main pathways involving at least four miRNAs selected. Four miRNAs were identified for differentiating between patients with and without AD in machine learning combined to systematic review, and followed the pathways analysis: miRNA-30a-3p, miRNA-193a-5p, miRNA-143-3p, miRNA-145-5p. The pathways epidermal growth factor, MAPK, TGF-beta and ATM-dependent DNA damage response, were regulated by these miRNAs, but only the MAPK pathway presented higher relevance after a randomic pathway analysis. These findings have the potential to assist in the development of diagnostic tests for AD using miRNAs as biomarkers, as well as provide understanding of the relationship between different pathophysiological mechanisms of AD.

ZCCHC17 knockdown phenocopies Alzheimer's disease-related loss of synaptic proteins and hyperexcitability

ZCCHC17 is a master regulator of synaptic gene expression and has recently been shown to play a role in splicing of neuronal mRNA. We previously showed that ZCCHC17 protein declines in Alzheimer's disease (AD) brain tissue before there is significant gliosis and neuronal loss, that ZCCHC17 loss partially replicates observed splicing abnormalities in AD brain tissue, and that maintenance of ZCCHC17 levels is predicted to support cognitive resilience in AD. Here, we assessed the functional consequences of reduced ZCCHC17 expression in primary cortical neuronal cultures using siRNA knockdown. Consistent with its previously identified role in synaptic gene expression, loss of ZCCHC17 led to loss of synaptic protein expression. Patch recording of neurons shows that ZCCHC17 loss significantly disrupted the excitation/inhibition balance of neurotransmission, and favored excitatory-dominant synaptic activity as measured by an increase in spontaneous excitatory post synaptic currents and action potential firing rate, and a decrease in spontaneous inhibitory post synaptic currents. These findings are consistent with the hyperexcitable phenotype seen in AD animal models and in patients. We are the first to assess the functional consequences of ZCCHC17 knockdown in neurons and conclude that ZCCHC17 loss partially phenocopies AD-related loss of synaptic proteins and hyperexcitability.

Transcriptomic analysis reveals sex-specific patterns in the hippocampus in Alzheimer's disease

Background

The hippocampus, vital for memory and learning, is among the first brain regions affected in Alzheimer's Disease (AD) and exhibits adult neurogenesis. Women face twice the risk of developing AD compare to men, making it crucial to understand sex differences in hippocampal function for comprehending AD susceptibility.

Methods

We conducted a comprehensive analysis of bulk mRNA postmortem samples from the whole hippocampus (GSE48350, GSE5281) and its CA1 and CA3 subfields (GSE29378). Our aim was to perform a comparative molecular signatures analysis, investigating sex-specific differences and similarities in the hippocampus and its subfields in AD. This involved comparing the gene expression profiles among: (a) male controls (M-controls) vs. female controls (F-controls), (b) females with AD (F-AD) vs. F-controls, (c) males with AD (M-AD) vs. M-controls, and (d) M-AD vs. F-AD. Furthermore, we identified AD susceptibility genes interacting with key targets of menopause hormone replacement drugs, specifically the ESR1 and ESR2 genes, along with GPER1.

Results

The hippocampal analysis revealed contrasting patterns between M-AD vs. M-controls and F-AD vs. F-controls, as well as M-controls vs. F-controls. Notably, BACE1, a key enzyme linked to amyloid-beta production in AD pathology, was found to be upregulated in M-controls compared to F-controls in both CA1 and CA3 hippocampal subfields. In M-AD vs. M-controls, the GABAergic synapse was downregulated, and the Estrogen signaling pathway was upregulated in both subfields, unlike in F-AD vs. F-controls. Analysis of the whole hippocampus also revealed upregulation of the GABAergic synapse in F-AD vs. F-controls. While direct comparison of M-AD vs. F-AD, revealed a small upregulation of the ESR1 gene in the CA1 subfield of males. Conversely, F-AD vs. F-controls exhibited downregulation of the Dopaminergic synapse in both subfields, while the Calcium signaling pathway showed mixed regulation, being upregulated in CA1 but downregulated in CA3, unlike in M-AD vs. M-controls. The upregulated Estrogen signaling pathway in M-AD, suggests a compensatory response to neurodegenerative specifically in males with AD. Our results also identified potential susceptibility genes interacting with ESR1 and ESR2, including MAPK1, IGF1, AKT1, TP53 and CD44.

Conclusion

These findings underscore the importance of sex-specific disease mechanisms in AD pathogenesis. Region-specific analysis offers a more detailed examination of localized changes in the hippocampus, enabling to capture sex-specific molecular patterns in AD susceptibility and progression.

Novel insights into immune-related genes associated with type 2 diabetes mellitus-related cognitive impairment

BACKGROUND

The cognitive impairment in type 2 diabetes mellitus (T2DM) is a multifaceted and advancing state that requires further exploration to fully comprehend. Neuroinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease.

AIM

To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment.

METHODS

To identify differentially expressed genes (DEGs) between T2DM and controls, we used data from the Gene Expression Omnibus database GSE125387. To identify T2DM module genes, we used Weighted Gene Co-Expression Network Analysis. All the genes were subject to Gene Set Enrichment Analysis. Protein-protein interaction network construction and machine learning were utilized to identify three hub genes. Immune cell infiltration analysis was performed. The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis. Validation experiments including reverse transcription quantitative real-time PCR, Western blotting and immunohistochemistry were conducted both in vivo and in vitro. To identify potential drugs associated with hub genes, we used the Comparative Toxicogenomics Database (CTD).

RESULTS

A total of 576 DEGs were identified using GSE125387. By taking the intersection of DEGs, T2DM module genes, and immune-related genes, a total of 59 genes associated with the immune system were identified. Afterward, machine learning was utilized to identify three hub genes (H2-T24, Rac3, and Tfrc). The hub genes were associated with a variety of immune cells. The three hub genes were validated in GSE152539. Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro, consistent with the bioinformatics analysis. Additionally, 11 potential drugs associated with RAC3 and TFRC were identified based on the CTD.

CONCLUSION

Immune-related genes that differ in expression in the hippocampus are closely linked to microglia. We validated the expression of three hub genes both in vivo and in vitro, consistent with our bioinformatics results. We discovered 11 compounds associated with RAC3 and TFRC. These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.

Innovative target mining stratagems to navigate drug repurposing endeavours

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Dysregulated AEBP1 and COLEC12 Genes in Late-Onset Alzheimer's Disease: Insights from Brain Cortex and Peripheral Blood Analysis

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive impairment, often accompanied by alterations in mood, confusion, and, ultimately, a state of acute mental disturbance. The cerebral cortex is considered a promising area for investigating the underlying causes of AD by analyzing transcriptional patterns, which could be complemented by investigating blood samples obtained from patients. We analyzed the RNA expression profiles of three distinct areas of the brain cortex, including the frontal cortex (FC), temporal cortex (TC), and entorhinal cortex (EC) in patients with AD. Functional enrichment analysis was performed on the differentially expressed genes (DEGs) across the three regions. The two genes with the most significant expression changes in the EC region were selected for assessing mRNA expression levels in the peripheral blood of late-onset AD patients using quantitative PCR (qPCR). We identified eight shared DEGs in these regions, including AEBP1 and COLEC12, which exhibited prominent changes in expression. Functional enrichment analysis uncovered a significant association of these DEGs with the transforming growth factor-β (TGF-β) signaling pathway and processes related to angiogenesis. Importantly, we established a robust connection between the up-regulation of AEBP1 and COLEC12 in both the brain and peripheral blood. Furthermore, we have demonstrated the potential of AEBP1 and COLEC12 genes as effective diagnostic tools for distinguishing between late-onset AD patients and healthy controls. This study unveils the intricate interplay between AEBP1 and COLEC12 in AD and underscores their potential as markers for disease detection and monitoring.

Updates on mouse models of Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease in the United States (US). Animal models, specifically mouse models have been developed to better elucidate disease mechanisms and test therapeutic strategies for AD. A large portion of effort in the field was focused on developing transgenic (Tg) mouse models through over-expression of genetic mutations associated with familial AD (FAD) patients. Newer generations of mouse models through knock-in (KI)/knock-out (KO) or CRISPR gene editing technologies, have been developed for both familial and sporadic AD risk genes with the hope to more accurately model proteinopathies without over-expression of human AD genes in mouse brains. In this review, we summarized the phenotypes of a few commonly used as well as newly developed mouse models in translational research laboratories including the presence or absence of key pathological features of AD such as amyloid and tau pathology, synaptic and neuronal degeneration as well as cognitive and behavior deficits. In addition, advantages and limitations of these AD mouse models have been elaborated along with discussions of any sex-specific features. More importantly, the omics data from available AD mouse models have been analyzed to categorize molecular signatures of each model reminiscent of human AD brain changes, with the hope to guide future selection of most suitable models for specific research questions to be addressed in the AD field.

Trends in the application of "omics" to Alzheimer's disease: a bibliometric and visualized study

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disease with an insidious onset. The widespread application of omics techniques in AD has attracted considerable attention. We aimed to make a comprehensive analysis of published omics articles on AD in order to determine the research profile and application trends of omics techniques in AD.

METHODS

This study utilizes bibliometric and visual methods including a map collaboration map, co-citations, and keywords to identify knowledge structures, hot topics, and research trends based on 6,828 publications from the Web of Science Core Collection (WoSCC) database.

RESULTS

The results of this study showed that 5654 institutions from 91 countries published articles in this field. The USA, China, and the UK played a leading role in publishing numerous articles in relevant journals as well as prolific institutions and authors, respectively. This paper collects a large number of literatures on the application of AD omics technology from the WoSCC database and found the omics technology applied to AD is mainly based on genomics technology. The application of transcriptomics technology has shown an increasing trend in recent years, and the application of multi-omics technology will be the general trend in the future.

CONCLUSION

The development status, frontier hotspots, and general trends of omics application technologies are reviewed. This article will provide intelligence support to researchers and institutions in the field of Alzheimer's omics research and applications from a practical perspective.

Large-scale gene expression changes in APP/PSEN1 and GFAP mutation models exhibit high congruence with Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder with both genetic and non-genetic causes. Animal research models are available for a multitude of diseases and conditions affecting the central nervous system (CNS), and large-scale CNS gene expression data exist for many of these. Although there are several models specifically for AD, each recapitulates different aspects of the human disease. In this study we evaluate over 500 animal models to identify those with CNS gene expression patterns matching human AD datasets. Approaches included a hypergeometric based scoring system that rewards congruent gene expression patterns but penalizes discordant gene expression patterns. The top two models identified were APP/PS1 transgenic mice expressing mutant APP and PSEN1, and mice carrying a GFAP mutation that is causative of Alexander disease, a primary disorder of astrocytes in the CNS. The APP/PS1 and GFAP models both matched over 500 genes moving in the same direction as in human AD, and both had elevated GFAP expression and were highly congruent with one another. Also scoring highly were the 5XFAD model (with five mutations in APP and PSEN1) and mice carrying CK-p25, APP, and MAPT mutations. Animals with the APOE3 and 4 mutations combined with traumatic brain injury ranked highly. Bulbectomized rats scored high, suggesting anosmia could be causative of AD-like gene expression. Other matching models included the SOD1G93A strain and knockouts for SNORD116 (Prader-Willi mutation), GRID2, INSM1, XBP1, and CSTB. Many top models demonstrated increased expression of GFAP, and results were similar across multiple human AD datasets. Heatmap and Uniform Manifold Approximation Plot results were consistent with hypergeometric ranking. Finally, some gene manipulation models, including for TYROBP and ATG7, were identified with reversed AD patterns, suggesting possible neuroprotective effects. This study provides insight for the pathobiology of AD and the potential utility of available animal models.

ZCCHC17 Modulates Neuronal RNA Splicing and Supports Cognitive Resilience in Alzheimer's Disease

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis using data from human autopsy tissue (consisting of males and females) and female human cell lines. Co-immunoprecipitation (co-IP) of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA-splicing proteins. ZCCHC17 knockdown results in widespread RNA-splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4-dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find a significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that the maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

Navigating the Gene Co-Expression Network and Drug Repurposing Opportunities for Brain Disorders Associated with Neurocognitive Impairment

Neurocognitive impairment refers to a spectrum of disorders characterized by a decline in cognitive functions such as memory, attention, and problem-solving, which are often linked to structural or functional abnormalities in the brain. While its exact etiology remains elusive, genetic factors play a pivotal role in disease onset and progression. This study aimed to identify highly correlated gene clusters (modules) and key hub genes shared across neurocognition-impairing diseases, including Alzheimer's disease (AD), Parkinson's disease with dementia (PDD), HIV-associated neurocognitive disorders (HAND), and glioma. Herein, the microarray datasets AD (GSE5281), HAND (GSE35864), glioma (GSE15824), and PD (GSE7621) were used to perform Weighted Gene Co-expression Network Analysis (WGCNA) to identify highly preserved modules across the studied brain diseases. Through gene set enrichment analysis, the shared modules were found to point towards processes including neuronal transcriptional dysregulation, neuroinflammation, protein aggregation, and mitochondrial dysfunction, hallmarks of many neurocognitive disorders. These modules were used in constructing protein-protein interaction networks to identify hub genes shared across the diseases of interest. These hub genes were found to play pivotal roles in processes including protein homeostasis, cell cycle regulation, energy metabolism, and signaling, all associated with brain and CNS diseases, and were explored for their drug repurposing experiments. Drug repurposing based on gene signatures highlighted drugs including Dorzolamide and Oxybuprocaine, which were found to modulate the expression of the hub genes in play and may have therapeutic implications in neurocognitive disorders. While both drugs have traditionally been used for other medical purposes, our study underscores the potential of a combined WGCNA and drug repurposing strategy for searching for new avenues in the simultaneous treatment of different diseases that have similarities in gene co-expression networks.

Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network

Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimer's disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

Endotype Characterization Reveals Mechanistic Differences Across Brain Regions in Sporadic Alzheimer's Disease

Background

While Alzheimer's disease (AD) pathology is associated with altered brain structure, it is not clear whether gene expression changes mirror the onset and evolution of pathology in distinct brain regions. Deciphering the mechanisms which cause the differential manifestation of the disease across different regions has the potential to help early diagnosis.

Objective

We aimed to identify common and unique endotypes and their regulation in tangle-free neurons in sporadic AD (SAD) across six brain regions: entorhinal cortex (EC), hippocampus (HC), medial temporal gyrus (MTG), posterior cingulate (PC), superior frontal gyrus (SFG), and visual cortex (VCX).

Methods

To decipher the states of tangle-free neurons across different brain regions in human subjects afflicted with AD, we performed analysis of the neural transcriptome. We explored changes in differential gene expression, functional and transcription factor target enrichment, and co-expression gene module detection analysis to discern disease-state transcriptomic variances and characterize endotypes. Additionally, we compared our results to tangled AD neuron microarray-based study and the Allen Brain Atlas.

Results

We identified impaired neuron function in EC, MTG, PC, and VCX resulting from REST activation and reversal of mature neurons to a precursor-like state in EC, MTG, and SFG linked to SOX2 activation. Additionally, decreased neuron function and increased dedifferentiation were linked to the activation of SUZ12. Energetic deficit connected to NRF1 inactivation was found in HC, PC, and VCX.

Conclusions

Our findings suggest that SAD manifestation varies in scale and severity in different brain regions. We identify endotypes, such as energetic shortfalls, impaired neuronal function, and dedifferentiation.

Reduced PIN1 gene expression in neocortical and limbic brain regions in female Alzheimer's patients correlates with cognitive and neuropathological phenotypes

Women have a higher incidence of Alzheimer's disease (AD), even after adjusting for increased longevity. Thus, there is an urgent need to identify the molecular networks that underpin the sex-associated risk of AD. Recent efforts have identified PIN1 as a key regulator of tau phosphorylation signaling pathway. Pin1 is the only gene, to date, that when deleted can cause both tau and Aβ-related pathologies in an age-dependent manner. We analyzed multiple brain transcriptomic datasets focusing on sex differences in PIN1 mRNA levels, in an aging and AD cohort, which revealed reduced PIN1 levels driven by females. Then, we validated this observation in an independent dataset (ROS/MAP) which also revealed that PIN1 is negatively correlated with multiregional neurofibrillary tangle density and global cognitive function, in females only. Additional analysis revealed a decrease in PIN1 in subjects with mild cognitive impairment (MCI) compared with aged individuals, again, driven predominantly by female subjects. Our results show that while both male and female AD patients show decreased PIN1 expression, changes occur before the onset of clinical symptoms of AD in females and correlate to early events associated with AD risk (e.g., synaptic dysfunction). These changes are specific to neurons, and may be a potential prognostic marker to assess AD risk in the aging population and even more so in AD females with increased risk of AD.

Longitudinal APOE4- and amyloid-dependent changes in the blood transcriptome in cognitively intact older adults

BACKGROUND

Gene expression is dysregulated in Alzheimer's disease (AD) patients, both in peripheral blood and post mortem brain. We investigated peripheral whole-blood gene (co)expression to determine molecular changes prior to symptom onset.

METHODS

RNA was extracted and sequenced for 65 cognitively healthy F-PACK participants (65 (56-80) years, 34 APOE4 non-carriers, 31 APOE4 carriers), at baseline and follow-up (interval: 5.0 (3.4-8.6) years). Participants received amyloid PET at both time points and amyloid rate of change derived. Accumulators were defined with rate of change ≥ 2.19 Centiloids. We performed differential gene expression and weighted gene co-expression network analysis to identify differentially expressed genes and networks of co-expressed genes, respectively, with respect to traits of interest (APOE4 status, amyloid accumulation (binary/continuous)), and amyloid positivity status, followed by Gene Ontology annotation.

RESULTS

There were 166 significant differentially expressed genes at follow-up compared to baseline in APOE4 carriers only, whereas 12 significant differentially expressed genes were found only in APOE4 non-carriers, over time. Among the significant genes in APOE4 carriers, several had strong evidence for a pathogenic role in AD based on direct association scores generated from the DISQOVER platform: NGRN, IGF2, GMPR, CLDN5, SMIM24. Top enrichment terms showed upregulated mitochondrial and metabolic pathways, and an exacerbated upregulation of ribosomal pathways in APOE4 carriers compared to non-carriers. Similarly, there were 33 unique significant differentially expressed genes at follow-up compared to baseline in individuals classified as amyloid negative at baseline and positive at follow-up or amyloid positive at both time points and 32 unique significant differentially expressed genes over time in individuals amyloid negative at both time points. Among the significant genes in the first group, the top five with the highest direct association scores were as follows: RPL17-C18orf32, HSP90AA1, MBP, SIRPB1, and GRINA. Top enrichment terms included upregulated metabolism and focal adhesion pathways. Baseline and follow-up gene co-expression networks were separately built. Seventeen baseline co-expression modules were derived, with one significantly negatively associated with amyloid accumulator status (r² =  - 0.25, p = 0.046). This was enriched for proteasomal protein catabolic process and myeloid cell development. Thirty-two follow-up modules were derived, with two significantly associated with APOE4 status: one downregulated (r² =  - 0.27, p = 0.035) and one upregulated (r² = 0.26, p = 0.039) module. Top enrichment processes for the downregulated module included proteasomal protein catabolic process and myeloid cell homeostasis. Top enrichment processes for the upregulated module included cytoplasmic translation and rRNA processing.

CONCLUSIONS

We show that there are longitudinal gene expression changes that implicate a disrupted immune system, protein removal, and metabolism in cognitively intact individuals who carry APOE4 or who accumulate in cortical amyloid. This provides insight into the pathophysiology of AD, whilst providing novel targets for drug and therapeutic development.

ZCCHC17 modulates neuronal RNA splicing and supports cognitive resilience in Alzheimer's disease

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's Disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis. Co-immunoprecipitation of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA splicing proteins. ZCCHC17 knockdown results in widespread RNA splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4 dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

Identification of TAC1 Associated with Alzheimer's Disease Using a Robust Rank Aggregation Approach

BACKGROUND

Alzheimer's disease (AD) brings heavy burden to society and family. There is an urgent need to find effective methods for disease diagnosis and treatment. The robust rank aggregation (RRA) approach that could aggregate the resulting gene lists has been widely utilized in genomic data analysis.

OBJECTIVE

To identify hub genes using RRA approach in AD.

METHODS

Seven microarray datasets in frontal cortex from GEO database were used to identify differential expressed genes (DEGs) in AD patients using RRA approach. STRING was performed to explore the protein-to-protein interaction (PPI). Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were utilized for enrichment analysis. Human Gene Connectome and Gene Set Enrichment Analysis were used for functional annotation. Finally, the expression levels of hub genes were validated in the cortex of 5xFAD mice by quantitative real-time polymerase chain reaction.

RESULTS

After RRA analysis, 473 DEGs (216 upregulated and 257 downregulated) were identified in AD samples. PPI showed that DEGs had a total of 416 nodes and 2750 edges. These genes were divided into 17 clusters, each of which contains at least three genes. After functional annotation and enrichment analysis, TAC1 is identified as the hub gene and may be related to synaptic function and inflammation. In addition, Tac1 was found downregulated in cortices of 5xFAD mice.

CONCLUSION

In the current study, TAC1 is identified as a key gene in the frontal cortex of AD, providing insight into the possible pathogenesis and potential therapeutic targets for this disease.

Cancer and Alzheimer's Inverse Correlation: an Immunogenetic Analysis

Numerous studies have demonstrated an inverse link between cancer and Alzheimer's disease (AD), with data suggesting that people with Alzheimer's have a decreased risk of cancer and vice versa. Although other studies have investigated mechanisms to explain this relationship, the connection between these two diseases remains largely unexplained. Processes seen in cancer, such as decreased apoptosis and increased cell proliferation, seem to be reversed in AD. Given the need for effective therapeutic strategies for AD, comparisons with cancer could yield valuable insights into the disease process and perhaps result in new treatments. Here, through a review of existing literature, we compared the expressions of genes involved in cell proliferation and apoptosis to establish a genetic basis for the reciprocal association between AD and cancer. We discuss an array of genes involved in the aforementioned processes, their relevance to both diseases, and how changes in those genes produce varying effects in either disease.

Exploring Shared Biomarkers of Myocardial Infarction and Alzheimer's Disease via Single-Cell/Nucleus Sequencing and Bioinformatics Analysis

BACKGROUND

Patients are at increased risk of dementia, including Alzheimer's disease (AD), after myocardial infarction (MI), but the biological link between MI and AD is unclear.

OBJECTIVE

To understand the association between the pathogenesis of MI and AD and identify common biomarkers of both diseases.

METHODS

Using public databases, we identified common biomarkers of MI and AD. Least absolute shrinkage and selection operator (LASSO) regression and protein-protein interaction (PPI) network were performed to further screen hub biomarkers. Functional enrichment analyses were performed on the hub biomarkers. Single-cell/nucleus analysis was utilized to further analyze the hub biomarkers at the cellular level in carotid atherosclerosis and AD datasets. Motif enrichment analysis was used to screen key transcription factors.

RESULTS

26 common differentially expressed genes were screened between MI and AD. Function enrichment analyses showed that these differentially expressed genes were mainly associated with inflammatory pathways. A key gene, Regulator of G-protein Signaling 1 (RGS1), was obtained by LASSO regression and PPI network. RGS1 was confirmed to mainly express in macrophages and microglia according to single-cell/nucleus analysis. The difference in expression of RGS1 in macrophages and microglia between disease groups and controls was statistically significant (p < 0.0001). The expression of RGS1 in the disease groups was upregulated with the differentiation of macrophages and microglia. RelA was a key transcription factor regulating RGS1.

CONCLUSION

Macrophages and microglia are involved in the inflammatory response of MI and AD. RGS1 may be a key biomarker in this process.

Alzheimer's disease large-scale gene expression portrait identifies exercise as the top theoretical treatment

Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects multiple brain regions and is difficult to treat. In this study we used 22 AD large-scale gene expression datasets to identify a consistent underlying portrait of AD gene expression across multiple brain regions. Then we used the portrait as a platform for identifying treatments that could reverse AD dysregulated expression patterns. Enrichment of dysregulated AD genes included multiple processes, ranging from cell adhesion to CNS development. The three most dysregulated genes in the AD portrait were the inositol trisphosphate kinase, ITPKB (upregulated), the astrocyte specific intermediate filament protein, GFAP (upregulated), and the rho GTPase, RHOQ (upregulated). 41 of the top AD dysregulated genes were also identified in a recent human AD GWAS study, including PNOC, C4B, and BCL11A. 42 transcription factors were identified that were both dysregulated in AD and that in turn affect expression of other AD dysregulated genes. Male and female AD portraits were highly congruent. Out of over 250 treatments, three datasets for exercise or activity were identified as the top three theoretical treatments for AD via reversal of large-scale gene expression patterns. Exercise reversed expression patterns of hundreds of AD genes across multiple categories, including cytoskeleton, blood vessel development, mitochondrion, and interferon-stimulated related genes. Exercise also ranked as the best treatment across a majority of individual region-specific AD datasets and meta-analysis AD datasets. Fluoxetine also scored well and a theoretical combination of fluoxetine and exercise reversed 549 AD genes. Other positive treatments included curcumin. Comparisons of the AD portrait to a recent depression portrait revealed a high congruence of downregulated genes in both. Together, the AD portrait provides a new platform for understanding AD and identifying potential treatments for AD.

The Role of Clusterin Transporter in the Pathogenesis of Alzheimer’s Disease at the Blood–Brain Barrier Interface: A Systematic Review

Alzheimer’s disease (AD) is considered a chronic and debilitating neurological illness that is increasingly impacting older-age populations. Some proteins, including clusterin (CLU or apolipoprotein J) transporter, can be linked to AD, causing oxidative stress. Therefore, its activity can affect various functions involving complement system inactivation, lipid transport, chaperone activity, neuronal transmission, and cellular survival pathways. This transporter is known to bind to the amyloid beta (Aβ) peptide, which is the major pathogenic factor of AD. On the other hand, this transporter is also active at the blood–brain barrier (BBB), a barrier that prevents harmful substances from entering and exiting the brain. Therefore, in this review, we discuss and emphasize the role of the CLU transporter and CLU-linked molecular mechanisms at the BBB interface in the pathogenesis of AD.

Alzheimer's disease: insights from a network medicine perspective

Alzheimer’s disease (AD) is the most common neurodegenerative disease that currently lacks available effective therapy. Thus, identifying novel molecular biomarkers for diagnosis and treatment of AD is urgently demanded. In this study, we exploited tools and concepts of the emerging research area of Network Medicine to unveil a novel putative disease gene signature associated with AD. We proposed a new pipeline, which combines the strengths of two consolidated algorithms of the Network Medicine: DIseAse MOdule Detection (DIAMOnD), designed to predict new disease-associated genes within the human interactome network; and SWItch Miner (SWIM), designed to predict important (switch) genes within the co-expression network. Our integrated computational analysis allowed us to enlarge the set of the known disease genes associated to AD with additional 14 genes that may be proposed as new potential diagnostic biomarkers and therapeutic targets for AD phenotype.

A statistical network pre-processing method to improve relevance and significance of gene lists in microarray gene expression studies

Background

Microarrays can perform large scale studies of differential expressed gene (DEGs) and even single nucleotide polymorphisms (SNPs), thereby screening thousands of genes for single experiment simultaneously. However, DEGs and SNPs are still just as enigmatic as the first sequence of the genome. Because they are independent from the affected biological context. Pathway enrichment analysis (PEA) can overcome this obstacle by linking both DEGs and SNPs to the affected biological pathways and consequently to the underlying biological functions and processes.

Results

To improve the enrichment analysis results, we present a new statistical network pre-processing method by mapping DEGs and SNPs on a biological network that can improve the relevance and significance of the DEGs or SNPs of interest to incorporate pathway topology information into the PEA. The proposed methodology improves the statistical significance of the PEA analysis in terms of computed p value for each enriched pathways and limit the number of enriched pathways. This helps reduce the number of relevant biological pathways with respect to a non-specific list of genes.

Conclusion

The proposed method provides two-fold enhancements. Network analysis reveals fewer DEGs, by selecting only relevant DEGs and the detected DEGs improve the enriched pathways’ statistical significance, rather than simply using a general list of genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04936-z.

Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease

Introduction

The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co-expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD.

Methods

We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers.

Results

WGCNA identified five modules associated with biological clocks, with the module designated as "purple" showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers.

Conclusion

Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD.

Highlights

Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes.Weighted gene co-expression network analysis (WGCNA) found five modules related to biological aging.Among the hub genes of the module, CX3CR1 was downregulated in AD.The CX3CR1 expression level was associated with cognitive performance and brain atrophy.

Identification of the molecular subgroups in Alzheimer's disease by transcriptomic data

Background

Alzheimer's disease (AD) is a heterogeneous pathological disease with genetic background accompanied by aging. This inconsistency is present among molecular subtypes, which has led to diagnostic ambiguity and failure in drug development. We precisely distinguished patients of AD at the transcriptome level.

Methods

We collected 1,240 AD brain tissue samples collected from the GEO dataset. Consensus clustering was used to identify molecular subtypes, and the clinical characteristics were focused on. To reveal transcriptome differences among subgroups, we certificated specific upregulated genes and annotated the biological function. According to RANK METRIC SCORE in GSEA, TOP10 was defined as the hub gene. In addition, the systematic correlation between the hub gene and “A/T/N” was analyzed. Finally, we used external data sets to verify the diagnostic value of hub genes.

Results

We identified three molecular subtypes of AD from 743 AD samples, among which subtypes I and III had high-risk factors, and subtype II had protective factors. All three subgroups had higher neuritis plaque density, and subgroups I and III had higher clinical dementia scores and neurofibrillary tangles than subgroup II. Our results confirmed a positive association between neurofibrillary tangles and dementia, but not neuritis plaques. Subgroup I genes clustered in viral infection, hypoxia injury, and angiogenesis. Subgroup II showed heterogeneity in synaptic pathology, and we found several essential beneficial synaptic proteins. Due to presenilin one amplification, Subgroup III was a risk subgroup suspected of familial AD, involving abnormal neurogenic signals, glial cell differentiation, and proliferation. Among the three subgroups, the highest combined diagnostic value of the hub genes were 0.95, 0.92, and 0.83, respectively, indicating that the hub genes had sound typing and diagnostic ability.

Conclusion

The transcriptome classification of AD cases played out the pathological heterogeneity of different subgroups. It throws daylight on the personalized diagnosis and treatment of AD.

Integrated analysis and identification of hub genes as novel biomarkers for Alzheimer’s disease

Alzheimer’s disease (AD) is an intractable and progressive neurodegenerative disorder that can lead to severe cognitive decline, impaired speech, short-term memory loss, and finally an inability to function in daily life. For patients, their families, and even all of society, AD can impart great emotional pressure and economic costs. Therefore, this study aimed to investigate potential diagnostic biomarkers of AD. Using the Gene Expression Omnibus (GEO) database, the expression profiles of genes were extracted from the GSE5281, GSE28146, and GSE48350 microarray datasets. Then, immune-related genes were identified by the intersections of differentially expressed genes (DEGs). Functional enrichment analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA), were performed. Subsequently, random forest models and least absolute shrinkage and selection operator regression were used to further screen hub genes, which were then validated using receiver operating characteristic (ROC) curve analysis. Finally, 153 total immune-related DEGs were identified in relation to AD. DO analysis of these immune-related DEGs showed that they were enriched in “lung disease,” “reproductive system disease,” and “atherosclerosis.” Single GSEA of hub genes showed that they were particularly enriched in “oxidative phosphorylation.” ROC analysis of AGAP3 yielded an area under the ROC curve of 0.878 for GSE5281, 0.727 for GSE28146, and 0.635 for GSE48350. Moreover, immune infiltration analysis demonstrated that AGAP3 was related to follicular helper T cells, naïve CD4 T cells, naïve B cells, memory B cells, macrophages M0, macrophages M1, macrophages M2, resting natural killer (NK) cells, activated NK cells, monocytes, neutrophils, eosinophils, and activated mast cells. These results indicate that identifying immune-related DEGs might enhance the current understanding of the development and prognosis of AD. Furthermore, AGAP3 not only plays a vital role in AD progression and diagnosis but could also serve as a valuable target for further research on AD.

Analysis of ROQUIN, Tristetraprolin (TTP), and BDNF/miR-16/TTP regulatory axis in late onset Alzheimer’s disease

Alzheimer’s disease (AD) is a heterogeneous degenerative disorder of the brain that is on the rise worldwide. One of the critical processes that might be disturbed in AD is gene expression regulation. Tristetraprolin (TTP) and RC3H1 gene (ROQUIN) are two RNA-binding proteins (RBPs) that target AU-rich elements (AREs) and constitutive decay elements (CDEs), respectively. TTP and ROQUIN, members of the CCCH zinc-finger protein family, have been demonstrated to fine-tune numerous inflammatory factors. In addition, miR-16 has distinct characteristics and may influence the target mRNA through the ARE site. Interestingly, BDNF mRNA has ARE sites in the 3’ untranslated region (UTR) and can be targeted by regulatory factors, such as TTP and miR-16 on MRE sequences, forming BDNF/miR-16/TTP regulatory axis. A number of two microarray datasets were downloaded, including information on mRNAs (GSE106241) and miRNAs (GSE157239) from individuals with AD and corresponding controls. R software was used to identify BDNF, TTP, ROQUIN, and miR-16 expression levels in temporal cortex (TC) tissue datasets. Q-PCR was also used to evaluate the expression of these regulatory factors and the expression of BDNF in the blood of 50 patients with AD and 50 controls. Bioinformatic evaluation showed that TTP and miR-16 overexpression might act as post-transcriptional regulatory factors to control BDNF expression in AD in TC samples. Instead, this expression pattern was not found in peripheral blood samples from patients with AD compared to normal controls. ROQUIN expression was increased in the peripheral blood of patients with AD. Hsa-miR-16-5p levels did not show significant differences in peripheral blood samples. Finally, it was shown that TTP and BDNF, based on evaluating the receiver operating characteristic (ROC), effectively identify patients with AD from healthy controls. This study could provide a new perspective on the molecular regulatory processes associated with AD pathogenic mechanisms linked to the BDNF growth factor, although further research is needed on the possible roles of these factors in AD.

The Hidden Notes of Redox Balance in Neurodegenerative Diseases

Reactive oxygen species (ROS) are versatile molecules that, even if produced in the background of many biological processes and responses, possess pleiotropic roles categorized in two interactive yet opposite domains. In particular, ROS can either function as signaling molecules that shape physiological cell functions, or act as deleterious end products of unbalanced redox reactions. Indeed, cellular redox status needs to be tightly regulated to ensure proper cellular functioning, and either excessive ROS accumulation or the dysfunction of antioxidant systems can perturb the redox homeostasis, leading to supraphysiological concentrations of ROS and potentially harmful outcomes. Therefore, whether ROS would act as signaling molecules or as detrimental factors strictly relies on a dynamic equilibrium between free radical production and scavenging resources. Of notice, the mammalian brain is particularly vulnerable to ROS-mediated toxicity, because it possesses relatively poor antioxidant defenses to cope with the redox burden imposed by the elevated oxygen consumption rate and metabolic activity. Many features of neurodegenerative diseases can in fact be traced back to causes of oxidative stress, which may influence both the onset and progression of brain demise. This review focuses on the description of the dual roles of ROS as double-edge sword in both physiological and pathological settings, with reference to Alzheimer's and Parkinson's diseases.

Altered mitochondrial microenvironment at the spotlight of musculoskeletal aging and Alzheimer's disease

Emerging evidence has linked Alzheimer's disease (AD) onset with musculoskeletal aging via a muscle-brain crosstalk mediated by dysregulation of the mitochondrial microenvironment. This study investigated gene expression profiles from skeletal muscle tissues of older healthy adults to identify potential gene biomarkers whose dysregulated expression and protein interactome were involved in AD. Screening of the literature resulted in 12 relevant microarray datasets (GSE25941, GSE28392, GSE28422, GSE47881, GSE47969, GSE59880) in musculoskeletal aging and (GSE4757, GSE5281, GSE16759, GSE28146, GSE48350, GSE84422) in AD. Retrieved differentially expressed genes (DEGs) were used to construct two unique protein-protein interaction networks and clustering gene modules were identified. Overlapping module DEGs in the musculoskeletal aging and AD networks were ranked based on 11 topological algorithms and the five highest-ranked ones were considered as hub genes. The analysis revealed that the dysregulated expression of the mitochondrial microenvironment genes, NDUFAB1, UQCRC1, UQCRFS1, NDUFS3, and MRPL15, overlapped between both musculoskeletal aging and AD networks. Thus, these genes may have a potential role as markers of AD occurrence in musculoskeletal aging. Human studies are warranted to evaluate the functional role and prognostic value of these genes in aging populations with sarcopenia and AD.

Articulating target-mining techniques to disinter Alzheimer's specific targets for drug repurposing

BACKGROUND AND OBJECTIVES

Alzheimer's Disease (AD), an extremely progressive neurodegenerative disorder is an amalgamation of numerous intricate pathological networks. This century old disease is still an unmet medical condition owing to the modest efficacy of existing therapeutic agents in antagonizing the multi-targeted pathological pathways underlying AD. Given the paucity in AD specific drugs, fabricating comprehensive research strategies to envision disease specific targets to channelize and expedite drug discovery are mandated. However, the dwindling approval rates and stringent regulatory constraints concerning the approval of a new chemical entity is daunting the pharmaceutical industries from effectuating de novo research. To bridge the existing gaps in AD drug research, a promising contemporary way out could be drug repurposing. This drug repurposing investigation is intended to envisage AD specific targets and create drug libraries pertinent to the shortlisted targets via a series of avant-garde bioinformatics and computational strategies.

METHODS

Transcriptomic analysis of three AD specific datasets viz., GSE122063, GSE15222 and GSE5281 revealed significant Differentially Expressed Genes (DEGs) and subsequent Protein-Protein Interactions (PPI) network analysis captured crucial AD targets. Later, homology model was constructed through I-TASSER for a shortlisted target protein which lacked X-ray crystallographic structure and the built protein model was validated by molecular dynamic simulations. Further, drug library was created for the shortlisted target based on structural and side effect similarity with respective standard drugs. Finally, molecular docking, binding energy calculations and molecular dynamics studies were carried out to unravel the interactions exhibited by drugs from the created library with amino acids in active binding pocket of RGS4.

RESULTS

SST and RGS4 were shortlisted as potentially significant AD specific targets, however, the less explored target RGS4 was considered for further sequential analysis. Homology model constructed for RGS4 displayed best quality when validated through Ramachandran plot and ERRAT plot. Subsequent docking and molecular dynamics studies showcased substantial affinity demonstrated by three drugs viz., Ziprasidone, Melfoquine and Metaxalone from the created drug libraries, towards RGS4.

CONCLUSION

This virtual analysis forecasted the repurposable potential of Ziprasidone, Melfoquine and Metaxalone against AD based on their affinity towards RGS4, a key AD-specific target.

Transcriptional Profiling of Hippocampus Identifies Network Alterations in Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by rapid brain cell degeneration affecting different areas of the brain. Hippocampus is one of the earliest involved brain regions in the disease. Modern technologies based on high-throughput data have identified transcriptional profiling of several neurological diseases, including AD, for a better comprehension of genetic mechanisms of the disease. In this study, we investigated differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets of hippocampus of AD patients. The identified DEGs were submitted to Weighted correlation network analysis (WGCNA) and ClueGo to explore genes with a higher degree centrality and to comprehend their biological role. Subsequently, MCODE was used to identify subnetworks of interconnected DEGs. Our study found 40 down-regulated genes and 36 up-regulated genes as consensus DEGs. Analysis of the co-expression network revealed ACOT7, ATP8A2, CDC42, GAD1, GOT1, INA, NCALD, and WWTR1 to be genes with a higher degree centrality. ClueGO revealed the pathways that were mainly enriched, such as clathrin coat assembly, synaptic vesicle endocytosis, and DNA damage response signal transduction by p53 class mediator. In addition, we found a subnetwork of 12 interconnected genes (AMPH, CA10, CALY, NEFL, SNAP25, SNAP91, SNCB, STMN2, SV2B, SYN2, SYT1, and SYT13). Only CA10 and CALY are targets of known drugs while the others could be potential novel drug targets.

Exploring common genetic contributors to neuroprotection from amyloid pathology

Preclinical Alzheimer's disease describes some individuals who harbour Alzheimer's pathologies but are asymptomatic. For this study, we hypothesized that genetic variation may help protect some individuals from Alzheimer's-related neurodegeneration. We therefore conducted a genome-wide association study using 5 891 064 common variants to assess whether genetic variation modifies the association between baseline beta-amyloid, as measured by both cerebrospinal fluid and positron emission tomography, and neurodegeneration defined using MRI measures of hippocampal volume. We combined and jointly analysed genotype, biomarker and neuroimaging data from non-Hispanic white individuals who were enrolled in four longitudinal ageing studies (n = 1065). Using regression models, we examined the interaction between common genetic variants (Minor Allele Frequency >0.01), including APOE-ɛ4 and APOE-ɛ2, and baseline cerebrospinal levels of amyloid (CSF Aβ42) on baseline hippocampal volume and the longitudinal rate of hippocampal atrophy. For targeted replication of top findings, we analysed an independent dataset (n = 808) where amyloid burden was assessed by Pittsburgh Compound B ([11C]-PiB) positron emission tomography. In this study, we found that APOE-ɛ4 modified the association between baseline CSF Aβ42 and hippocampal volume such that APOE-ɛ4 carriers showed more rapid atrophy, particularly in the presence of enhanced amyloidosis. We also identified a novel locus on chromosome 3 that interacted with baseline CSF Aβ42. Minor allele carriers of rs62263260, an expression quantitative trait locus for the SEMA5B gene (P = 1.46 × 10-8; 3:122675327) had more rapid neurodegeneration when amyloid burden was high and slower neurodegeneration when amyloid was low. The rs62263260 × amyloid interaction on longitudinal change in hippocampal volume was replicated in an independent dataset (P = 0.0112) where amyloid burden was assessed by positron emission tomography. In addition to supporting the established interaction between APOE and amyloid on neurodegeneration, our study identifies a novel locus that modifies the association between beta-amyloid and hippocampal atrophy. Annotation results may implicate SEMA5B, a gene involved in synaptic pruning and axonal guidance, as a high-quality candidate for functional confirmation and future mechanistic analysis.

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Alzheimer’s disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.

Characterizing the role of the dark kinome in neurodegenerative disease - A mini review

BACKGROUND

Drugs that modulate previously unexplored targets could potentially slow or halt the progression of neurodegenerative diseases. Several candidate proteins lie within the dark kinome, those human kinases that have not been well characterized. Much of the kinome (~80%) remains poorly studied, and these targets likely harbor untapped biological potential.

SCOPE OF REVIEW

This review highlights the significance of kinases as mediators of aberrant pathways in neurodegeneration and provides examples of published high-quality small molecules that modulate some of these kinases.

MAJOR CONCLUSIONS

There is a need for continued efforts to develop high-quality chemical tools to illuminate the function of understudied kinases in the brain. Potent and selective small molecules enable accurate pairing of an observed phenotype with a protein target.

GENERAL SIGNIFICANCE

The examples discussed herein support the premise that validation of therapeutic hypotheses surrounding kinase targets can be accomplished via small molecules and they can serve as the basis for disease-focused drug development campaigns.

Single-cell Transcriptional Changes in Neurodegenerative Diseases

In recent decades, our understanding of the molecular changes involved in neurodegenerative diseases has been transformed. Single-cell RNA sequencing and single-nucleus RNA sequencing technologies have been applied to provide cellular and molecular details of the brain at the single-cell level. This has expanded our knowledge of the central nervous system and provided insights into the molecular vulnerability of brain cell types and underlying mechanisms in neurodegenerative diseases. In this review, we highlight the recent advances and findings related to neurodegenerative diseases using these cutting-edge technologies.

Revelation of Pivotal Genes Pertinent to Alzheimer's Pathogenesis: A Methodical Evaluation of 32 GEO Datasets

Alzheimer’s disease (AD), a dreadful neurodegenerative disorder that affects cognitive and behavioral function in geriatric populations, is characterized by the presence of amyloid deposits and neurofibrillary tangles in brain regions. The International D World Alzheimer Report2018 noted a global prevalence of 50 million AD cases and forecasted a threefold rise to 139 million by 2050. Although there exist numerous genetic association studies pertinent to AD in different ethnicities, critical genetic factors and signaling pathways underlying its pathogenesis remain ambiguous. This study was aimed to analyze the genetic data retrieved from 32 Gene Expression Omnibus datasets belonging to diverse ethnic cohorts in order to identify overlapping differentially expressed genes (DEGs). Stringent selection criteria were framed to shortlist appropriate datasets based on false discovery rate (FDR) p-value and log FC, and relevant details of upregulated and downregulated DEGs were retrieved. Among the 32 datasets, only six satisfied the selection criteria. The GEO2R tool was employed to retrieve significant DEGs. Nine common DEGs, i.e., SLC5A3, BDNF, SST, SERPINA3, RTN3, RGS4, NPTX, ENC1 and CRYM were found in more than 60% of the selected datasets. These DEGs were later subjected to protein–protein interaction analysis with 18 AD-specific literature-derived genes. Among the nine common DEGs, BDNF, SST, SERPINA3, RTN3 and RGS4 exhibited significant interactions with crucial proteins including BACE1, GRIN2B, APP, APOE, COMT, PSEN1, INS, NEP and MAPT. Functional enrichment analysis revealed involvement of these genes in trans-synaptic signaling, chemical transmission, PI3K pathway signaling, receptor–ligand activity and G protein signaling. These processes are interlinked with AD pathways.

Multiomics Identification of Potential Targets for Alzheimer Disease and Antrocin as a Therapeutic Candidate

Alzheimer’s disease (AD) is the most frequent cause of neurodegenerative dementia and affects nearly 50 million people worldwide. Early stage diagnosis of AD is challenging, and there is presently no effective treatment for AD. The specific genetic alterations and pathological mechanisms of the development and progression of dementia remain poorly understood. Therefore, identifying essential genes and molecular pathways that are associated with this disease’s pathogenesis will help uncover potential treatments. In an attempt to achieve a more comprehensive understanding of the molecular pathogenesis of AD, we integrated the differentially expressed genes (DEGs) from six microarray datasets of AD patients and controls. We identified ATPase H+ transporting V1 subunit A (ATP6V1A), BCL2 interacting protein 3 (BNIP3), calmodulin-dependent protein kinase IV (CAMK4), TOR signaling pathway regulator-like (TIPRL), and the translocase of outer mitochondrial membrane 70 (TOMM70) as upregulated DEGs common to the five datasets. Our analyses revealed that these genes exhibited brain-specific gene co-expression clustering with OPA1, ITFG1, OXCT1, ATP2A2, MAPK1, CDK14, MAP2K4, YWHAB, PARK2, CMAS, HSPA12A, and RGS17. Taking the mean relative expression levels of this geneset in different brain regions into account, we found that the frontal cortex (BA9) exhibited significantly (p < 0.05) higher expression levels of these DEGs, while the hippocampus exhibited the lowest levels. These DEGs are associated with mitochondrial dysfunction, inflammation processes, and various pathways involved in the pathogenesis of AD. Finally, our blood–brain barrier (BBB) predictions using the support vector machine (SVM) and LiCABEDS algorithm and molecular docking analysis suggested that antrocin is permeable to the BBB and exhibits robust ligand–receptor interactions with high binding affinities to CAMK4, TOMM70, and T1PRL. Our results also revealed good predictions for ADMET properties, drug-likeness, adherence to Lipinskís rules, and no alerts for pan-assay interference compounds (PAINS) Conclusions: These results suggest a new molecular signature for AD parthenogenesis and antrocin as a potential therapeutic agent. Further investigation is warranted.

BMSCs-exosomes containing GDF-15 alleviated SH-SY5Y cell injury model of Alzheimer's disease via AKT/GSK-3β/β-catenin

BACKGROUND

Mesenchymal stem cells (MSCs) therapy has great potential for Alzheimer's disease (AD) treatment. Here, we investigated the roles of BMSCs-exosomes containing growth differentiation factor-15 (GDF-15) in regulating SH-SY5Y cell injury in AD.

METHODS

The SH-SY5Y cell injury model was constructed by treating SH-SY5Y cells with 10 μM Aβ₄₂. GDF-15 expression was assessed using qRT-PCR and western blot. CCK8 assay and flow cytometry assay were employed to elevate cell proliferation and apoptosis, respectively. The expression levels of inflammatory factors (IL-6, IL-1β, TNFα and IL-8) and Aβ₄₂ were detected using ELISA. Besides, the levels of apoptosis-related proteins and AKT pathway-related proteins were determined using western blot.

RESULTS

Our results displayed that BMSCs-EVs treatment elevated cell viability, while suppressed cell apoptosis and inflammation in Aβ₄₂-treated SH-SY5Y cells. Exosomes secreted by BMSCs after GDF-15 silence lost the ability to restore Aβ₄₂-induced SH-SY5Y cell damage. GDF-15 treatment restored Aβ₄₂-induced SH-SY5Y cell damage, while it was eliminated by AKT pathway inhibition. BMSCs-exosomes containing GDF-15 upregulated NEP and IDE via activation of AKT/GSK-3β/β-catenin pathway, thereby degrading Aβ₄₂ protein to relieve SH-SY5Y cell damage.

CONCLUSION

BMSCs-exosomes containing GDF-15 alleviated SH-SY5Y cell damage via AKT/GSK-3β/β-catenin. Our work confers a promising therapeutic strategy for AD.

Identification of retinoblastoma binding protein 7 (Rbbp7) as a mediator against tau acetylation and subsequent neuronal loss in Alzheimer's disease and related tauopathies

Evidence indicates that tau hyper-phosphorylation and subsequent neurofibrillary tangle formation contribute to the extensive neuronal death in Alzheimer's disease (AD) and related tauopathies. Recent work has identified that increased tau acetylation can promote tau phosphorylation. Tau acetylation occurs at lysine 280 resulting from increased expression of the lysine acetyltransferase p300. The exact upstream mechanisms mediating p300 expression remain elusive. Additional work highlights the role of the epigenome in tau pathogenesis, suggesting that dysregulation of epigenetic proteins may contribute to acetylation and hyper-phosphorylation of tau. Here, we identify and focus on the histone-binding subunit of the Nucleosome Remodeling and Deacetylase (NuRD) complex: Retinoblastoma-Binding Protein 7 (Rbbp7). Rbbp7 chaperones chromatin remodeling proteins to their nuclear histone substrates, including histone acetylases and deacetylases. Notably, Rbbp7 binds to p300, suggesting that it may play a role in modulating tau acetylation. We interrogated Rbbp7 in post-mortem brain tissue, cell lines and mouse models of AD. We found reduced Rbbp7 mRNA expression in AD cases, a significant negative correlation with CERAD (neuritic plaque density) and Braak Staging (pathogenic tau inclusions) and a significant positive correlation with post-mortem brain weight. We also found a neuron-specific downregulation of Rbbp7 mRNA in AD patients. Rbbp7 protein levels were significantly decreased in 3xTg-AD and PS19 mice compared to NonTg, but no decreases were found in APP/PS1 mice that lack tau pathology. In vitro, Rbbp7 overexpression rescued TauP301L-induced cytotoxicity in immortalized hippocampal cells and primary cortical neurons. In vivo, hippocampal Rbbp7 overexpression rescued neuronal death in the CA1 of PS19 mice. Mechanistically, we found that increased Rbbp7 reduced p300 levels, tau acetylation at lysine 280 and tau phosphorylation at AT8 and AT100 sites. Collectively, these data identify a novel role of Rbbp7, protecting against tau-related pathologies, and highlight its potential as a therapeutic target in AD and related tauopathies.

Mapping Post-Translational Modifications in Brain Regions in Alzheimer's Disease Using Proteomics Data Mining

Alzheimer's disease (AD) is a leading cause of dementia and a neurodegenerative disease. Proteomics and post-translational modification (PTM) analyses offer new opportunities for a comprehensive understanding of pathophysiology of brain in AD. We report here multiple PTMs in patients with AD, harnessing publicly available proteomics data from nine brain regions and at three different Braak stages of disease progression. Specifically, we identified 7190 peptides with PTMs, corresponding to 2545 proteins from brain regions with intermediate tangles, and 6864 peptides with PTMs corresponding to 2465 proteins from brain regions with severe tangles. A total of 103 proteins with PTMs were expressed uniquely to intermediate tangles and severe tangles compared to no tangles. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis suggested the association of these proteins in AD progression through platelet activation. These modified proteins were also found to be enriched for the tricarboxylic acid (TCA) cycle, respiratory electron cycle, and detoxification of reactive oxygen species. The multi-PTM data reported here contribute to our understanding of the neurobiology of AD and highlight the prospects of omics systems science research in neurodegenerative diseases. The present study provides a region-wise classification for the proteins with PTMs along with their differential expression patterns, providing insights into the localization of these proteins upon modification. The catalog of multi-PTMs identified in the context of AD from different brain regions provides a unique platform for generating newer hypotheses in understanding the putative role of specific PTMs in AD pathogenesis.

Disruption of a RAC1-centred network is associated with Alzheimer's disease pathology and causes age-dependent neurodegeneration

The molecular biological mechanisms of Alzheimer’s disease (AD) involve disease-associated crosstalk through many genes and include a loss of normal as well as a gain of abnormal interactions among genes. A protein domain network (PDN) is a collection of physical bindings that occur between protein domains, and the states of the PDNs in patients with AD are likely to be perturbed compared to those in normal healthy individuals. To identify PDN changes that cause neurodegeneration, we analysed the PDNs that occur among genes co-expressed in each of three brain regions at each stage of AD. Our analysis revealed that the PDNs collapsed with the progression of AD stage and identified five hub genes, including Rac1, as key players in PDN collapse. Using publicly available as well as our own gene expression data, we confirmed that the mRNA expression level of the RAC1 gene was downregulated in the entorhinal cortex (EC) of AD brains. To test the causality of these changes in neurodegeneration, we utilized Drosophila as a genetic model and found that modest knockdown of Rac1 in neurons was sufficient to cause age-dependent behavioural deficits and neurodegeneration. Finally, we identified a microRNA, hsa-miR-101-3p, as a potential regulator of RAC1 in AD brains. As the Braak neurofibrillary tangle (NFT) stage progressed, the expression levels of hsa-miR-101-3p were increased specifically in the EC. Furthermore, overexpression of hsa-miR-101-3p in the human neuronal cell line SH-SY5Y caused RAC1 downregulation. These results highlight the utility of our integrated network approach for identifying causal changes leading to neurodegeneration in AD.

Reassessment of Pioglitazone for Alzheimer's Disease

Alzheimer's disease is a quintessential 'unmet medical need', accounting for ∼65% of progressive cognitive impairment among the elderly, and 700,000 deaths in the United States in 2020. In 2019, the cost of caring for Alzheimer's sufferers was $244B, not including the emotional and physical toll on caregivers. In spite of this dismal reality, no treatments are available that reduce the risk of developing AD or that offer prolonged mitiagation of its most devestating symptoms. This review summarizes key aspects of the biology and genetics of Alzheimer's disease, and we describe how pioglitazone improves many of the patholophysiological determinants of AD. We also summarize the results of pre-clinical experiments, longitudinal observational studies, and clinical trials. The results of animal testing suggest that pioglitazone can be corrective as well as protective, and that its efficacy is enhanced in a time- and dose-dependent manner, but the dose-effect relations are not monotonic or sigmoid. Longitudinal cohort studies suggests that it delays the onset of dementia in individuals with pre-existing type 2 diabetes mellitus, which small scale, unblinded pilot studies seem to confirm. However, the results of placebo-controlled, blinded clinical trials have not borne this out, and we discuss possible explanations for these discrepancies.

PINK1 Activation Attenuates Impaired Neuronal-Like Differentiation and Synaptogenesis and Mitochondrial Dysfunction in Alzheimer's Disease Trans-Mitochondrial Cybrid Cells

BACKGROUND

Mitochondrial dysfunction, bioenergetic deficit, and extensive oxidative stress underlie neuronal perturbation during the early stage of Alzheimer's disease (AD). Previously, we demonstrated that decreased PTEN-induced putative kinase 1 (PINK1) expression is associated with AD pathology in AD-affected human brains and AD mice.

OBJECTIVE

In the present study, we highlight the essential role of PINK1 in AD-relevant mitochondrial perturbation and neuronal malfunction.

METHODS

Using trans-mitochondrial "cybrid" (cytoplasmic hybrid) neuronal cells, whose mitochondria are transferred from platelets of patients with sporadic AD, we observed the effect of PINK1 in neuronal-like differentiation and synaptogenesis and mitochondrial functions.

RESULTS

In AD cybrid cells, the downregulation of PINK1 is correlated to the alterations in mitochondrial morphology and function and deficit in neuronal-like differentiation. Restoring/increasing PINK1 by lentivirus transduction of PINK1 robustly attenuates mitochondrial defects and rescues neurite-like outgrowth. Importantly, defective PINK1 kinase activity fails to reverse these detrimental effects. Mechanistically, AD cybrid cells reveal a significant decrease in PINK1-dependent phosphorylated mitofusin (Mfn) 2, a key mitochondrial membrane protein that participates in mitochondrial fusion, and an insufficient autophagic activity for the clearance of dysfunctional mitochondria. Overexpression of PINK1, but not mutant PINK1 elevates phosphorylation of Mfn2 and autophagy signaling LC3-II. Accordingly, PINK1-overexpressed AD cybrids exhibit increases in mitochondrial length and density and suppressed reactive oxygen species. These results imply that activation of PINK1 protects against AD-affected mitochondrial dysfunction and impairment in neuronal maturation and differentiation.

CONCLUSION

PINK1-mediated mitophagy is important for maintaining mitochondrial health by clearance of dysfunctional mitochondria and therefore, improves energy homeostasis in AD.

DHCR24 Knock-Down Induced Tau Hyperphosphorylation at Thr181, Ser199, Thr231, Ser262, Ser396 Epitopes and Inhibition of Autophagy by Overactivation of GSK3β/mTOR Signaling

Accumulating evidences supported that knock-down of DHCR24 is linked to the pathological risk factors of AD, suggesting a potential role of DHCR24 in AD pathogenesis. However, the molecular mechanism link between DHCR24 and tauopathy remains unknown. Here, in order to elucidate the relationship between DHCR24 and tauopathy, we will focus on the effect of DHCR24 on the tau hyperphosphorylation at some toxic sites. In present study, we found that DHCR24 knock-down significantly lead to the hyperphosphorylation of tau sites at Thr181, Ser199, Thr231, Ser262, Ser396. Moreover, DHCR24 knock-down also increase the accumulation of p62 protein, simultaneously decreased the ratio of LC3-II/LC3-I and the number of autophagosome compared to the control groups, suggesting the inhibition of autophagy activity. In contrast, DHCR24 knock-in obviously abolished the effect of DHCR24 knock-down on tau hyperphosphrylation and autophagy. In addition, to elucidate the association between DHCR24 and tauopathy, we further showed that the level of plasma membrane cholesterol, lipid raft-anchored protein caveolin-1, and concomitantly total I class PI3-K (p110α), phospho-Akt (Thr308 and Ser473) were significantly decreased, resulting in the disruption of lipid raft/caveola and inhibition of PI3-K/Akt signaling in silencing DHCR24 SH-SY5Y cells compared to control groups. At the same time, DHCR24 knock-down simultaneously decreased the level of phosphorylated GSK3β at Ser9 (inactive form) and increased the level of phosphorylated mTOR at Ser2448 (active form), leading to overactivation of GSK3β and mTOR signaling. On the contrary, DHCR24 knock-in largely increased the level of membrane cholesterol and caveolin-1, suggesting the enhancement of lipid raft/caveola. And synchronously DHCR24 knock-in also abolished the effect of DHCR24 knock-down on the inhibition of PI3-K/Akt signaling as well as the overactivation of GSK3β and mTOR signaling. Collectively, our data strongly supported DHCR24 knock-down lead to tau hyperphosphorylation and the inhibition of autophagy by a lipid raft-dependent PI3-K/Akt-mediated GSK3β and mTOR signaling. Taking together, our results firstly demonstrated that the decrease of plasma membrane cholesterol mediated by DHCR24 deficiency might contribute to the tauopathy in AD and other tauopathies.

Chronic Treatment with 50 mg/kg Cannabidiol Improves Cognition and Moderately Reduces Aβ40 Levels in 12-Month-Old Male AβPPswe/PS1ΔE9 Transgenic Mice

Alzheimer's disease (AD) is characterized by progressive cognitive decline and pathologically by the accumulation of amyloid-β (Aβ) and tau hyperphosphorylation causing neurodegeneration and neuroinflammation. Current AD treatments do not stop or reverse the disease progression, highlighting the need for more effective therapeutics. The phytocannabinoid cannabidiol (CBD) has demonstrated antioxidant, anti-inflammatory, and neuroprotective properties. Furthermore, chronic CBD treatment (20 mg/kg) reverses social and object recognition memory deficits in the AβPPxPS1 transgenic mouse model with only limited effects on AD-relevant brain pathology. Importantly, studies have indicated that CBD works in a dose-dependent manner. Thus, this study determined the chronic effects of 50 mg/kg CBD in male AβPPxPS1 mice. 12-month-old mice were treated with 50 mg/kg CBD or vehicle via daily intraperitoneal injections for 3 weeks prior to behavioral testing. A variety of cognitive domains including object and social recognition, spatial and fear-associated memory were evaluated. Pathological brain analyses for AD-relevant markers were conducted using ELISA and western blot. Vehicle-treated male AβPPxPS1 mice demonstrated impaired social recognition memory and reversal spatial learning. These deficits were restored after CBD treatment. Chronic CBD tended to reduce insoluble Aβ40 levels in the hippocampus of AβPPxPS1 mice but had no effect on neuroinflammation, neurodegeneration, or PPARγ markers in the cortex. This study demonstrates that therapeutic-like effects of 50 mg/kg CBD on social recognition memory and spatial learning deficits in AβPPxPS1 mice are accompanied by moderate brain region-specific reductions in insoluble Aβ40 levels. The findings emphasize the clinical relevance of CBD treatment in AD; however, the underlying mechanisms involved require further investigation.

Defining early changes in Alzheimer's disease from RNA sequencing of brain regions differentially affected by pathology

Tau pathology in Alzheimer’s disease (AD) spreads in a predictable pattern that corresponds with disease symptoms and severity. At post-mortem there are cortical regions that range from mildly to severely affected by tau pathology and neuronal loss. A comparison of the molecular signatures of these differentially affected areas within cases and between cases and controls may allow the temporal modelling of disease progression. Here we used RNA sequencing to explore differential gene expression in the mildly affected primary visual cortex and moderately affected precuneus of ten age-, gender- and RNA quality-matched post-mortem brains from AD patients and healthy controls. The two regions in AD cases had similar transcriptomic signatures but there were broader abnormalities in the precuneus consistent with the greater tau load. Both regions were characterised by upregulation of immune-related genes such as those encoding triggering receptor expressed on myeloid cells 2 and membrane spanning 4-domains A6A and milder changes in insulin/IGF1 signalling. The precuneus in AD was also characterised by changes in vesicle secretion and downregulation of the interneuronal subtype marker, somatostatin. The ‘early’ AD transcriptome is characterised by perturbations in synaptic vesicle secretion on a background of neuroimmune dysfunction. In particular, the synaptic deficits that characterise AD may begin with the somatostatin division of inhibitory neurotransmission.

fISHing with immunohistochemistry for housekeeping gene changes in Alzheimer's disease using an automated quantitative analysis workflow

In situ hybridization (ISH) is a powerful tool that can be used to localize mRNA expression in tissue samples. Combining ISH with immunohistochemistry (IHC) to determine cell type provides cellular context of mRNA expression, which cannot be achieved with gene microarray or polymerase chain reaction. To study mRNA and protein expression on the same section we investigated the use of RNAscope® ISH in combination with fluorescent IHC on paraffin-embedded human brain tissue. We first developed a high-throughput, automated image analysis workflow for quantifying RNA puncta across the total cell population and within neurons identified by NeuN⁺ immunoreactivity. We then applied this automated analysis to tissue microarray (TMA) sections of middle temporal gyrus tissue (MTG) from neurologically normal and Alzheimer's Disease (AD) cases to determine the suitability of three commonly used housekeeping genes: ubiquitin C (UBC), peptidyl-prolyl cis-trans isomerase B (PPIB) and DNA-directed RNA polymerase II subunit RPB1 (POLR2A). Overall, we saw a significant decrease in total and neuronal UBC expression in AD cases compared to normal cases. Total expression results were validated with RT-qPCR using fresh frozen tissue from 5 normal and 5 AD cases. We conclude that this technique combined with our novel automated analysis pipeline provides a suitable platform to study changes in gene expression in diseased human brain tissue with cellular and anatomical context. Furthermore, our results suggest that UBC is not a suitable housekeeping gene in the study of post-mortem AD brain tissue.

Molecular characterization of selectively vulnerable neurons in Alzheimer's disease

Alzheimer's disease (AD) is characterized by the selective vulnerability of specific neuronal populations, the molecular signatures of which are largely unknown. To identify and characterize selectively vulnerable neuronal populations, we used single-nucleus RNA sequencing to profile the caudal entorhinal cortex and the superior frontal gyrus-brain regions where neurofibrillary inclusions and neuronal loss occur early and late in AD, respectively-from postmortem brains spanning the progression of AD-type tau neurofibrillary pathology. We identified RORB as a marker of selectively vulnerable excitatory neurons in the entorhinal cortex and subsequently validated their depletion and selective susceptibility to neurofibrillary inclusions during disease progression using quantitative neuropathological methods. We also discovered an astrocyte subpopulation, likely representing reactive astrocytes, characterized by decreased expression of genes involved in homeostatic functions. Our characterization of selectively vulnerable neurons in AD paves the way for future mechanistic studies of selective vulnerability and potential therapeutic strategies for enhancing neuronal resilience.