Genetic control of human brain transcript expression in Alzheimer disease

An integrated approach to identifying sex-specific genes, transcription factors, and pathways relevant to Alzheimer's disease

BACKGROUND

Age represents a significant risk factor for the development of Alzheimer's disease (AD); however, recent research has documented an influencing role of sex in several features of AD. Understanding the impact of sex on specific molecular mechanisms associated with AD remains a critical challenge to creating tailored therapeutic interventions.

METHODS

The exploration of the sex-based differential impact on disease (SDID) in AD used a systematic review to first select transcriptomic studies of AD with data regarding sex in the period covering 2002 to 2021 with a focus on the primary brain regions affected by AD - the cortex (CT) and the hippocampus (HP). A differential expression analysis for each study and two tissue-specific meta-analyses were then performed. Focusing on the CT due to the presence of significant SDID-related alterations, a comprehensive functional characterization was conducted: protein-protein network interaction and over-representation analyses to explore biological processes and pathways and a VIPER analysis to estimate transcription factor activity.

RESULTS

We selected 8 CT and 5 HP studies from the Gene Expression Omnibus (GEO) repository for tissue-specific meta-analyses. We detected 389 significantly altered genes in the SDID comparison in the CT. Generally, female AD patients displayed more affected genes than males; we grouped said genes into six subsets according to their expression profile in female and male AD patients. Only subset I (repressed genes in female AD patients) displayed significant results during functional profiling. Female AD patients demonstrated more significant impairments in biological processes related to the regulation and organization of synapsis and pathways linked to neurotransmitters (glutamate and GABA) and protein folding, Aβ aggregation, and accumulation compared to male AD patients. These findings could partly explain why we observe more pronounced cognitive decline in female AD patients. Finally, we detected 23 transcription factors with different activation patterns according to sex, with some associated with AD for the first time. All results generated during this study are readily available through an open web resource Metafun-AD (https://bioinfo.cipf.es/metafun-ad/).

CONCLUSION

Our meta-analyses indicate the existence of differences in AD-related mechanisms in female and male patients. These sex-based differences will represent the basis for new hypotheses and could significantly impact precision medicine and improve diagnosis and clinical outcomes in AD patients.

Changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease

While there are currently over 40 replicated genes with mapped risk alleles for Late Onset Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest driver of risk, with odds ratios for neuropathologically confirmed E44 carriers exceeding 30 (95% confidence interval 16.59-58.75). We sought to address whether the APOE E4 haplotype modifies expression globally through networks of expression to increase LOAD risk. We have used the Human Brainome data to build expression networks comparing APOE E4 carriers to non-carriers using scalable mixed-datatypes Bayesian network (BN) modeling. We have found that VGF had the greatest explanatory weight. High expression of VGF is a protective signal, even on the background of APOE E4 alleles. LOAD risk signals, considering an APOE background, include high levels of SPECC1L, HLA-DRA and RANBP3L. Our findings nominate several new transcripts, taking a combined approach to network building including known LOAD risk loci.

Impact of knockout of dual-specificity protein phosphatase 5 on structural and mechanical properties of rat middle cerebral arteries: implications for vascular aging

Vascular aging influences hemodynamics, elevating risks for vascular diseases and dementia. We recently demonstrated that knockout (KO) of Dusp5 enhances cerebral and renal hemodynamics and cognitive function. This improvement correlates with elevated pPKC and pERK1/2 levels in the brain and kidneys. Additionally, we observed that Dusp5 KO modulates the passive mechanical properties of cerebral and renal arterioles, associated with increased myogenic tone at low pressure, enhanced distensibility, greater compliance, and reduced stiffness. The present study evaluates the structural and mechanical properties of the middle cerebral artery (MCA) in Dusp5 KO rats. We found that vascular smooth muscle cell layers and the collagen content in the MCA wall are comparable between Dusp5 KO and control rats. The internal elastic lamina in the MCA of Dusp5 KO rats exhibits increased thickness, higher autofluorescence intensity, smaller fenestrae areas, and fewer fenestrations. Despite an enhanced myogenic response and tone of the MCA in Dusp5 KO rats, other passive mechanical properties, such as wall thickness, cross-sectional area, wall-to-lumen ratio, distensibility, incremental elasticity, circumferential wall stress, and elastic modulus, do not significantly differ between strains. These findings suggest that while Dusp5 KO has a limited impact on altering the structural and mechanical properties of MCA, its primary role in ameliorating hemodynamics and cognitive functions is likely attributable to its enzymatic activity on cerebral arterioles. Further research is needed to elucidate the specific enzymatic mechanisms and explore potential clinical applications in the context of vascular aging.

Exploration of interaction interface of TRKβ/BDNF through fingerprint analysis to disinter potential agonists

Tyrosine Kinase beta (TRKβ), is a type I membrane receptor which plays a major role in various signalling pathways. TRKβ was found to be upregulated in various cancers and contrastingly downregulated in various neurodegenerative disorders. Hitherto, contemporary drug research is oriented towards discovery of TRKβ inhibitors, thus neglecting the development of TRKβ agonists. This research is aimed at identifying FDA approved drugs exhibiting repurposable potential as TRKβ agonists by mapping them with fingerprints of the BDNF/TRKβ interaction interface. Initially, crucial interacting residues were retrieved and a receptor grid was generated around it. TRKβ agonists were retrieved from literature search and a drug library was created for each agonist based on its structural and side effect similarities. Subsequently, molecular docking and dynamics were performed for each library to identify the drugs possessing affinity towards the binding pocket of TRKβ. The study revealed molecular interactions of Perospirone, Droperidol, Urapidil, and Clobenzorex with the crucial amino acids lining the active binding pocket of TRKβ. Subsequent network pharmacological analysis of the above drugs revealed their interactions with key proteins involved in neurotransmitter signalling pathways. Clobenzorex displayed high stability in dynamics simulation and therefore this drug is recommended for further experimental evaluations to attain better mechanistic insights and predict its implications in correcting neuropathological aberrations. This study's focus on the interaction interface between TRKβ and BDNF, combined with the utilization of fingerprint analysis for drug repurposing, contributes to our understanding of neurotrophic signalling and holds potential for identifying new therapeutic options for neurological disorders.

Seipin deficiency-induced lipid dysregulation leads to hypomyelination-associated cognitive deficits via compromising oligodendrocyte precursor cell differentiation

Seipin is one key mediator of lipid metabolism that is highly expressed in adipose tissues as well as in the brain. Lack of Seipin gene, Bscl2, leads to not only severe lipid metabolic disorders but also cognitive impairments and motor disabilities. Myelin, composed mainly of lipids, facilitates nerve transmission and is important for motor coordination and learning. Whether Seipin deficiency-leaded defects in learning and motor coordination is underlined by lipid dysregulation and its consequent myelin abnormalities remains to be elucidated. In the present study, we verified the expression of Seipin in oligodendrocytes (OLs) and their precursors, oligodendrocyte precursor cells (OPCs), and demonstrated that Seipin deficiency compromised OPC differentiation, which led to decreased OL numbers, myelin protein, myelinated fiber proportion and thickness of myelin. Deficiency of Seipin resulted in impaired spatial cognition and motor coordination in mice. Mechanistically, Seipin deficiency suppressed sphingolipid metabolism-related genes in OPCs and caused morphological abnormalities in lipid droplets (LDs), which markedly impeded OPC differentiation. Importantly, rosiglitazone, one agonist of PPAR-gamma, substantially restored phenotypes resulting from Seipin deficiency, such as aberrant LDs, reduced sphingolipids, obstructed OPC differentiation, and neurobehavioral defects. Collectively, the present study elucidated how Seipin deficiency-induced lipid dysregulation leads to neurobehavioral deficits via impairing myelination, which may pave the way for developing novel intervention strategy for treating metabolism-involved neurological disorders.

Sex differences in luteinizing hormone aggravates Aβ deposition in APP/PS1 and Aβ1-42-induced mouse models of Alzheimer's disease

Alzheimer's disease (AD) exhibits a higher incidence rate among older women, and dysregulation of the hypothalamic-pituitary-gonadal (HPG) axis during aging is associated with cognitive impairments and the development of dementia. luteinizing hormone (LH) has an important role in CNS function, such as mediating neuronal pregnenolone production, and modulating neuronal plasticity and cognition. The sex differences in LH and its impact on Aβ deposition in AD individuals remain unclear, with no reported specific mechanisms. Here, we show through data mining that LH-related pathways are significantly enriched in female AD patients. Additionally, LH levels are elevated in female AD patients and exhibit a negative correlation with cognitive levels but a positive correlation with AD pathology levels, and females exhibit a greater extent of AD pathology, such as Aβ deposition. In vivo, we observed that the exogenous injection of LH exacerbated behavioral impairments induced by Aβ1-42 in mice. LH injection resulted in worsened neuronal damage and increased Aβ deposition. In SH-SY5Y cells, co-administration of LH with Aβ further exacerbated Aβ-induced neuronal damage. Furthermore, LH can dose-dependently decrease the levels of NEP and LHR proteins while increasing the expression of GFAP and IBA1 in vivo and in vitro. Taken together, these results indicate that LH can exacerbate cognitive impairment and neuronal damage in mice by increasing Aβ deposition. The potential mechanism may involve the reduction of NEP and LHR expression, along with the exacerbation of Aβ-induced inflammation.

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.

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.

Investigating the Potential Shared Molecular Mechanisms between COVID-19 and Alzheimer's Disease via Transcriptomic Analysis

SARS-CoV-2 caused the COVID-19 pandemic. COVID-19 may elevate the risk of cognitive impairment and even cause dementia in infected individuals; it may accelerate cognitive decline in elderly patients with dementia, possibly in Alzheimer's disease (AD) patients. However, the mechanisms underlying the interplay between AD and COVID-19 are still unclear. To investigate the underlying mechanisms and associations between AD progression and SARS-CoV-2 infection, we conducted a series of bioinformatics research into SARS-CoV-2-infected cells, COVID-19 patients, AD patients, and SARS-CoV-2-infected AD patients. We identified the common differentially expressed genes (DEGs) in COVID-19 patients, AD patients, and SARS-CoV-2-infected cells, and these DEGs are enriched in certain pathways, such as immune responses and cytokine storms. We constructed the gene interaction network with the signaling transduction module in the center and identified IRF7, STAT1, STAT2, and OAS1 as the hub genes. We also checked the correlations between several key transcription factors and the SARS-CoV-2 and COVID-19 pathway-related genes. We observed that ACE2 expression is positively correlated with IRF7 expression in AD and coronavirus infections, and interestingly, IRF7 is significantly upregulated in response to different RNA virus infections. Further snRNA-seq analysis indicates that NRGN neurons or endothelial cells may be responsible for the increase in ACE2 and IRF7 expression after SARS-CoV-2 infection. The positive correlation between ACE2 and IRF7 expressions is confirmed in the hippocampal formation (HF) of SARS-CoV-2-infected AD patients. Our findings could contribute to the investigation of the molecular mechanisms underlying the interplay between AD and COVID-19 and to the development of effective therapeutic strategies for AD patients with COVID-19.

The Human Brainome: changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease

While there are currently over 40 replicated genes with mapped risk alleles for Late Onset Alzheimer's disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest driver of risk, with odds ratios for neuropathologically confirmed E44 carriers exceeding 30 (95% confidence interval 16.59-58.75). We sought to address whether the APOE E4 haplotype modifies expression globally through networks of expression to increase LOAD risk. We have used the Human Brainome data to build expression networks comparing APOE E4 carriers to non-carriers using scalable mixed-datatypes Bayesian network (BN) modeling. We have found that VGF had the greatest explanatory weight. High expression of VGF is a protective signal, even on the background of APOE E4 alleles. LOAD risk signals, considering an APOE background, include high levels of SPECC1L, HLA-DRA and RANBP3L. Our findings nominate several new transcripts, taking a combined approach to network building including known LOAD risk loci.

Role of Dusp5 KO on Vascular Properties of Middle Cerebral Artery in Rats

Vascular aging influences hemodynamics, elevating risks for vascular diseases and dementia. We recently demonstrated that knockout (KO) of Dusp5 enhances cerebral and renal hemodynamics and cognitive function. This improvement correlates with elevated pPKC and pERK1/2 levels in the brain and kidneys. Additionally, we observed that Dusp5 KO modulates the passive mechanical properties of cerebral and renal arterioles, associated with increased myogenic tone at low pressure, enhanced distensibility, greater compliance, and reduced stiffness. The present study evaluates the structural and mechanical properties of the middle cerebral artery (MCA) in Dusp5 KO rats. We found that vascular smooth muscle cell layers and the collagen content in the MCA wall are comparable between Dusp5 KO and control rats. The internal elastic lamina in the MCA of Dusp5 KO rats exhibits increased thickness, higher autofluorescence intensity, smaller fenestrae areas, and fewer fenestrations. Despite an enhanced myogenic response and tone of the MCA in Dusp5 KO rats, other passive mechanical properties, such as wall thickness, cross-sectional area, wall-to-lumen ratio, distensibility, incremental elasticity, circumferential wall stress, and elastic modulus, do not significantly differ between strains. These findings suggest that while Dusp5 KO has a limited impact on altering the structural and mechanical properties of MCA, its primary role in ameliorating hemodynamics and cognitive functions is likely attributable to its enzymatic activity on cerebral arterioles. Further research is needed to elucidate the specific enzymatic mechanisms and explore potential clinical applications in the context of vascular aging.

An Alzheimer's disease risk variant in TTC3 modifies the actin cytoskeleton organization and the PI3K-Akt signaling pathway in iPSC-derived forebrain neurons

A missense variant in the tetratricopeptide repeat domain 3 (TTC3) gene (rs377155188, p.S1038C, NM_003316.4:c 0.3113C>G) was found to segregate with disease in a multigenerational family with late-onset Alzheimer's disease. This variant was introduced into induced pluripotent stem cells (iPSCs) derived from a cognitively intact individual using CRISPR genome editing, and the resulting isogenic pair of iPSC lines was differentiated into cortical neurons. Transcriptome analysis showed an enrichment for genes involved in axon guidance, regulation of actin cytoskeleton, and GABAergic synapse. Functional analysis showed that the TTC3 p.S1038C iPSC-derived neuronal progenitor cells had altered 3-dimensional morphology and increased migration, while the corresponding neurons had longer neurites, increased branch points, and altered expression levels of synaptic proteins. Pharmacological treatment with small molecules that target the actin cytoskeleton could revert many of these cellular phenotypes, suggesting a central role for actin in mediating the cellular phenotypes associated with the TTC3 p.S1038C variant.

Transfer Learning for Classification of Alzheimer's Disease Based on Genome Wide Data

Alzheimer's disease (AD) is a type of brain disorder that is regarded as a degenerative disease because the corresponding symptoms aggravate with the time progression. Single nucleotide polymorphisms (SNPs) have been identified as relevant biomarkers for this condition. This study aims to identify SNPs biomarkers associated with the AD in order to perform a reliable classification of AD. In contrast to existing related works, we utilize deep transfer learning with varying experimental analysis for reliable classification of AD. For this purpose, the convolutional neural networks (CNN) are firstly trained over the genome-wide association studies (GWAS) dataset requested from the AD neuroimaging initiative. We then employ the deep transfer learning for further training of our CNN (as base model) over a different AD GWAS dataset, to extract the final set of features. The extracted features are then fed into Support Vector Machine for classification of AD. Detailed experiments are performed using multiple datasets and varying experimental configurations. The statistical outcomes indicate an accuracy of 89% which is a significant improvement when benchmarked with existing related works.

Neurodegenerative Disease Associated Pathways in the Brains of Triple Transgenic Alzheimer's Model Mice Are Reversed Following Two Weeks of Peripheral Administration of Fasudil

The pan Rho-associated coiled-coil-containing protein kinase (ROCK) inhibitor fasudil acts as a vasodilator and has been used as a medication for post-cerebral stroke for the past 29 years in Japan and China. More recently, based on the involvement of ROCK inhibition in synaptic function, neuronal survival, and processes associated with neuroinflammation, it has been suggested that the drug may be repurposed for neurodegenerative diseases. Indeed, fasudil has demonstrated preclinical efficacy in many neurodegenerative disease models. To facilitate an understanding of the wider biological processes at play due to ROCK inhibition in the context of neurodegeneration, we performed a global gene expression analysis on the brains of Alzheimer's disease model mice treated with fasudil via peripheral IP injection. We then performed a comparative analysis of the fasudil-driven transcriptional profile with profiles generated from a meta-analysis of multiple neurodegenerative diseases. Our results show that fasudil tends to drive gene expression in a reverse sense to that seen in brains with post-mortem neurodegenerative disease. The results are most striking in terms of pathway enrichment analysis, where pathways perturbed in Alzheimer's and Parkinson's diseases are overwhelmingly driven in the opposite direction by fasudil treatment. Thus, our results bolster the repurposing potential of fasudil by demonstrating an anti-neurodegenerative phenotype in a disease context and highlight the potential of in vivo transcriptional profiling of drug activity.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

An Alzheimer's disease risk variant in TTC3 modifies the actin cytoskeleton organization and the PI3K-Akt signaling pathway in iPSC-derived forebrain neurons

A missense variant in the tetratricopeptide repeat domain 3 ( TTC3 ) gene (rs377155188, p.S1038C, NM_003316.4:c.3113C>G) was found to segregate with disease in a multigenerational family with late onset Alzheimer's disease. This variant was introduced into induced pluripotent stem cells (iPSCs) derived from a cognitively intact individual using CRISPR genome editing and the resulting isogenic pair of iPSC lines were differentiated into cortical neurons. Transcriptome analysis showed an enrichment for genes involved in axon guidance, regulation of actin cytoskeleton, and GABAergic synapse. Functional analysis showed that the TTC3 p.S1038C iPSC-derived neuronal progenitor cells had altered 3D morphology and increased migration, while the corresponding neurons had longer neurites, increased branch points, and altered expression levels of synaptic proteins. Pharmacological treatment with small molecules that target the actin cytoskeleton could revert many of these cellular phenotypes, suggesting a central role for actin in mediating the cellular phenotypes associated with the TTC3 p.S1038C variant.

Highlights

The AD risk variant TTC3 p.S1038C reduces the expression levels of TTC3 The variant modifies the expression of AD specific genes BACE1 , INPP5F , and UNC5C Neurons with the variant are enriched for genes in the PI3K-Akt pathwayiPSC-derived neurons with the alteration have increased neurite length and branchingThe variant interferes with actin cytoskeleton and is ameliorated by Cytochalasin D.

Molecular differences in brain regional vulnerability to aging between males and females

Background

Aging-related cognitive decline is associated with brain structural changes and synaptic loss. However, the molecular mechanisms of cognitive decline during normal aging remain elusive.

Results

Using the GTEx transcriptomic data from 13 brain regions, we identified aging-associated molecular alterations and cell-type compositions in males and females. We further constructed gene co-expression networks and identified aging-associated modules and key regulators shared by both sexes or specific to males or females. A few brain regions such as the hippocampus and the hypothalamus show specific vulnerability in males, while the cerebellar hemisphere and the anterior cingulate cortex regions manifest greater vulnerability in females than in males. Immune response genes are positively correlated with age, whereas those involved in neurogenesis are negatively correlated with age. Aging-associated genes identified in the hippocampus and the frontal cortex are significantly enriched for gene signatures implicated in Alzheimer's disease (AD) pathogenesis. In the hippocampus, a male-specific co-expression module is driven by key synaptic signaling regulators including VSNL1, INA, CHN1 and KCNH1; while in the cortex, a female-specific module is associated with neuron projection morphogenesis, which is driven by key regulators including SRPK2, REPS2 and FXYD1. In the cerebellar hemisphere, a myelination-associated module shared by males and females is driven by key regulators such as MOG, ENPP2, MYRF, ANLN, MAG and PLP1, which have been implicated in the development of AD and other neurodegenerative diseases.

Conclusions

This integrative network biology study systematically identifies molecular signatures and networks underlying brain regional vulnerability to aging in males and females. The findings pave the way for understanding the molecular mechanisms of gender differences in developing neurodegenerative diseases such as AD.

Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease

Despite decades of genetic studies on late-onset Alzheimer's disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer's pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer's-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer's disease.

Enhanced Cerebral Hemodynamics and Cognitive Function Via Knockout of Dual-Specificity Protein Phosphatase 5

Alzheimer's Disease (AD) and Alzheimer's Disease-Related Dementias (ADRD) are neurodegenerative disorders. Recent studies suggest that cerebral hypoperfusion is an early symptom of AD/ADRD. Dual-specificity protein phosphatase 5 (DUSP5) has been implicated in several pathological conditions, including pulmonary hypertension and cancer, but its role in AD/ADRD remains unclear. The present study builds on our previous findings, demonstrating that inhibition of ERK and PKC leads to a dose-dependent dilation of the middle cerebral artery and penetrating arteriole, with a more pronounced effect in Dusp5 KO rats. Both ERK and PKC inhibitors resulted in a significant reduction of myogenic tone in vessels from Dusp5 KO rats. Dusp5 KO rats exhibited stronger autoregulation of the surface but not deep cortical cerebral blood flow. Inhibition of ERK and PKC significantly enhanced the contractile capacity of vascular smooth muscle cells from both strains. Finally, a significant improvement in learning and memory was observed in Dusp5 KO rats 24 hours after initial training. Our results suggest that altered vascular reactivity in Dusp5 KO rats may involve distinct mechanisms for different vascular beds, and DUSP5 deletion could be a potential therapeutic target for AD/ADRD. Further investigations are necessary to determine the effects of DUSP5 inhibition on capillary stalling, blood-brain barrier permeability, and neurodegeneration in aging and disease models.

Exploring the interaction between T-cell antigen receptor-related genes and MAPT or ACHE using integrated bioinformatics analysis

Alzheimer's disease (AD) is a neurodegenerative disease that primarily occurs in elderly individuals with cognitive impairment. Although extracellular β-amyloid (Aβ) accumulation and tau protein hyperphosphorylation are considered to be leading causes of AD, the molecular mechanism of AD remains unknown. Therefore, in this study, we aimed to explore potential biomarkers of AD. Next-generation sequencing (NGS) datasets, GSE173955 and GSE203206, were collected from the Gene Expression Omnibus (GEO) database. Analysis of differentially expressed genes (DEGs), gene ontology (GO) functional enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein networks were performed to identify genes that are potentially associated with AD. Analysis of the DEG based protein-protein interaction (PPI) network using Cytoscape indicated that neuroinflammation and T-cell antigen receptor (TCR)-associated genes (LCK, ZAP70, and CD44) were the top three hub genes. Next, we validated these three hub genes in the AD database and utilized two machine learning models from different AD datasets (GSE15222) to observe their general relationship with AD. Analysis using the random forest classifier indicated that accuracy (78%) observed using the top three genes as inputs differed only slightly from that (84%) observed using all genes as inputs. Furthermore, another data set, GSE97760, which was analyzed using our novel eigenvalue decomposition method, indicated that the top three hub genes may be involved in tauopathies associated with AD, rather than Aβ pathology. In addition, protein-protein docking simulation revealed that the top hub genes could form stable binding sites with acetylcholinesterase (ACHE). This suggests a potential interaction between hub genes and ACHE, which plays an essential role in the development of anti-AD drug design. Overall, the findings of this study, which systematically analyzed several AD datasets, illustrated that LCK, ZAP70, and CD44 may be used as AD biomarkers. We also established a robust prediction model for classifying patients with AD.

Identification of gene networks mediating regional resistance to tauopathy in late-onset Alzheimer’s disease

Neurofibrillary lesions composed of tau protein aggregates are defining hallmarks of Alzheimer’s Disease. Despite tau filaments appearing to spread between networked brain regions in a prion-like manner, certain areas including cerebellum resist trans-synaptic spread of tauopathy and degeneration of their constituent neuronal cell bodies. To identify molecular correlates of resistance, we derived and implemented a ratio of ratios approach for disaggregating gene expression data on the basis of regional vulnerability to tauopathic neurodegeneration. When applied to vulnerable pre-frontal cortex as an internal reference for resistant cerebellum, the approach segregated adaptive changes in expression into two components. The first was enriched for neuron-derived transcripts associated with proteostasis including specific members of the molecular chaperone family and was unique to resistant cerebellum. When produced as purified proteins, each of the identified chaperones depressed aggregation of 2N4R tau in vitro at sub-stoichiometric concentrations, consistent with the expression polarity deduced from ratio of ratios testing. In contrast, the second component enriched for glia- and microglia-derived transcripts associated with neuroinflammation, segregating these pathways from susceptibility to tauopathy. These data support the utility of ratio of ratios testing for establishing the polarity of gene expression changes with respect to selective vulnerability. The approach has the potential to identify new targets for drug discovery predicated on their ability to promote resistance to disease in vulnerable neuron populations.

CREB3L2-ATF4 heterodimerization defines a transcriptional hub of Alzheimer's disease gene expression linked to neuropathology

Gene expression is changed by disease, but how these molecular responses arise and contribute to pathophysiology remains less understood. We discover that β-amyloid, a trigger of Alzheimer's disease (AD), promotes the formation of pathological CREB3L2-ATF4 transcription factor heterodimers in neurons. Through a multilevel approach based on AD datasets and a novel chemogenetic method that resolves the genomic binding profile of dimeric transcription factors (ChIPmera), we find that CREB3L2-ATF4 activates a transcription network that interacts with roughly half of the genes differentially expressed in AD, including subsets associated with β-amyloid and tau neuropathologies. CREB3L2-ATF4 activation drives tau hyperphosphorylation and secretion in neurons, in addition to misregulating the retromer, an endosomal complex linked to AD pathogenesis. We further provide evidence for increased heterodimer signaling in AD brain and identify dovitinib as a candidate molecule for normalizing β-amyloid-mediated transcriptional responses. The findings overall reveal differential transcription factor dimerization as a mechanism linking disease stimuli to the development of pathogenic cellular states.

Combined metabolic activators improve metabolic functions in the animal models of neurodegenerative diseases

BACKGROUND

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are associated with metabolic abnormalities. Integrative analysis of human clinical data and animal studies have contributed to a better understanding of the molecular and cellular pathways involved in the progression of NDDs. Previously, we have reported that the combined metabolic activators (CMA), which include the precursors of nicotinamide adenine dinucleotide and glutathione can be utilized to alleviate metabolic disorders by activating mitochondrial metabolism.

METHODS

We first analysed the brain transcriptomics data from AD patients and controls using a brain-specific genome-scale metabolic model (GEM). Then, we investigated the effect of CMA administration in animal models of AD and PD. We evaluated pathological and immunohistochemical findings of brain and liver tissues. Moreover, PD rats were tested for locomotor activity and apomorphine-induced rotation.

FINDINGS

Analysis of transcriptomics data with GEM revealed that mitochondrial dysfunction is involved in the underlying molecular pathways of AD. In animal models of AD and PD, we showed significant damage in the high-fat diet groups' brain and liver tissues compared to the chow diet. The histological analyses revealed that hyperemia, degeneration and necrosis in neurons were improved by CMA administration in both AD and PD animal models. These findings were supported by immunohistochemical evidence of decreased immunoreactivity in neurons. In parallel to the improvement in the brain, we also observed dramatic metabolic improvement in the liver tissue. CMA administration also showed a beneficial effect on behavioural functions in PD rats.

INTERPRETATION

Overall, we showed that CMA administration significantly improved behavioural scores in parallel with the neurohistological outcomes in the AD and PD animal models and is a promising treatment for improving the metabolic parameters and brain functions in NDDs.

What does heritability of Alzheimer's disease represent?

INTRODUCTION

Both late-onset Alzheimer's disease (AD) and ageing have a strong genetic component. In each case, many associated variants have been discovered, but how much missing heritability remains to be discovered is debated. Variability in the estimation of SNP-based heritability could explain the differences in reported heritability.

METHODS

We compute heritability in five large independent cohorts (N = 7,396, 1,566, 803, 12,528 and 3,963) to determine whether a consensus for the AD heritability estimate can be reached. These cohorts vary by sample size, age of cases and controls and phenotype definition. We compute heritability a) for all SNPs, b) excluding APOE region, c) excluding both APOE and genome-wide association study hit regions, and d) SNPs overlapping a microglia gene-set.

RESULTS

SNP-based heritability of late onset Alzheimer's disease is between 38 and 66% when age and genetic disease architecture are correctly accounted for. The heritability estimates decrease by 12% [SD = 8%] on average when the APOE region is excluded and an additional 1% [SD = 3%] when genome-wide significant regions were removed. A microglia gene-set explains 69-84% of our estimates of SNP-based heritability using only 3% of total SNPs in all cohorts.

CONCLUSION

The heritability of neurodegenerative disorders cannot be represented as a single number, because it is dependent on the ages of cases and controls. Genome-wide association studies pick up a large proportion of total AD heritability when age and genetic architecture are correctly accounted for. Around 13% of SNP-based heritability can be explained by known genetic loci and the remaining heritability likely resides around microglial related genes.

Altered gene expression in excitatory neurons is associated with Alzheimer's disease and its higher incidence in women

Introduction

Alzheimer's disease (AD) is a neurodegenerative disorder involving interactions between different cell types in the brain. Previous single-cell and bulk expression Alzheimer's studies have reported conflicting findings about the key cell types and cellular pathways whose expression is primarily altered in this disease. We re-analyzed these data in a uniform, coherent manner aiming to resolve and extend past findings. Our analysis sheds light on the observation that females have higher AD incidence than males.

Methods

We re-analyzed three single-cell transcriptomics datasets. We used the software Model-based Analysis of Single-cell Transcriptomics (MAST) to seek differentially expressed genes comparing AD cases to matched controls for both sexes together and each sex separately. We used the GOrilla software to search for enriched pathways among the differentially expressed genes. Motivated by the male/female difference in incidence, we studied genes on the X-chromosome, focusing on genes in the pseudoautosomal region (PAR) and on genes that are heterogeneous across individuals or tissues for X-inactivation. We validated findings by analyzing bulk AD datasets from the cortex in the Gene Expression Omnibus.

Results

Our results resolve a contradiction in the literature, showing that by comparing AD patients to unaffected controls, excitatory neurons have more differentially expressed genes than do other cell types. Synaptic transmission and related pathways are altered in a sex-specific analysis of excitatory neurons. PAR genes and X-chromosome heterogeneous genes, including, for example, BEX1 and ELK1, may contribute to the difference in sex incidence of Alzheimer's disease. GRIN1, stood out as an overexpressed autosomal gene in cases versus controls in all three single-cell datasets and as a functional candidate gene contributing to pathways upregulated in cases.

Discussion

Taken together, these results point to a potential linkage between two longstanding questions concerning AD pathogenesis, involving which cell type is the most important and why females have a higher incidence than males.

Highlights

By reanalyzing three, published, single-cell RNAseq datasets, we resolved a contradiction in the literature and showed that when comparing AD patients to unaffected controls, excitatory neurons have more differentially expressed genes than do other cell types.Further analysis of the published single-cell datasets showed that synaptic transmission and related pathways are altered in a sex-specific analysis of excitatory neurons.Combining analysis of single-cell datasets and publicly available bulk transcriptomics datasets revealed that X-chromosome genes, such as BEX1, ELK1, and USP11, whose X-inactivation status is heterogeneous may contribute to the higher incidence in females of Alzheimer's disease.

Cerebrospinal fluid immune dysregulation during healthy brain aging and cognitive impairment

Cerebrospinal fluid (CSF) contains a tightly regulated immune system. However, knowledge is lacking about how CSF immunity is altered with aging or neurodegenerative disease. Here, we performed single-cell RNA sequencing on CSF from 45 cognitively normal subjects ranging from 54 to 82 years old. We uncovered an upregulation of lipid transport genes in monocytes with age. We then compared this cohort with 14 cognitively impaired subjects. In cognitively impaired subjects, downregulation of lipid transport genes in monocytes occurred concomitantly with altered cytokine signaling to CD8 T cells. Clonal CD8 T effector memory cells upregulated C-X-C motif chemokine receptor 6 (CXCR6) in cognitively impaired subjects. The CXCR6 ligand, C-X-C motif chemokine ligand 16 (CXCL16), was elevated in the CSF of cognitively impaired subjects, suggesting CXCL16-CXCR6 signaling as a mechanism for antigen-specific T cell entry into the brain. Cumulatively, these results reveal cerebrospinal fluid immune dysregulation during healthy brain aging and cognitive impairment.

Identification and Prioritization of PET Neuroimaging Targets for Microglial Phenotypes Associated with Microglial Activity in Alzheimer's Disease

Activation of microglial cells accompanies the progression of many neurodegenerative disorders, including Alzheimer's disease (AD). Development of molecular imaging tools specific to microglia can help elucidate the mechanism through which microglia contribute to the pathogenesis and progression of neurodegenerative disorders. Through analysis of published genetic, transcriptomic, and proteomic data sets, we identified 19 genes with microglia-specific expression that we then ranked based on association with the AD characteristics, change in expression, and potential druggability of the target. We believe that the process we used to identify and rank microglia-specific genes is broadly applicable to the identification and evaluation of targets in other disease areas and for applications beyond molecular imaging.

SIRT7 Deficiency Protects against Aβ42-Induced Apoptosis through the Regulation of NOX4-Derived Reactive Oxygen Species Production in SH-SY5Y Cells

Alzheimer's disease (AD) is an age-related neurodegenerative disease that is characterized by irreversible memory loss and cognitive decline. The deposition of amyloid-β (Aβ), especially aggregation-prone Aβ₄₂, is considered to be an early event preceding neurodegeneration in AD. Sirtuins (SIRT1-7 in mammals) are nicotinamide adenine dinucleotide-dependent lysine deacetylases/deacylases, and several sirtuins play important roles in AD. However, the involvement of SIRT7 in AD pathogenesis is not known. Here, we demonstrate that SIRT7 mRNA expression is increased in the cortex, entorhinal cortex, and prefrontal cortex of AD patients. We also found that Aβ₄₂ treatment rapidly increased NADPH oxidase 4 (NOX4) expression at the post-transcriptional level, and induced reactive oxygen species (ROS) production and apoptosis in neuronal SH-SY5Y cells. In contrast, SIRT7 knockdown inhibited Aβ₄₂-induced ROS production and apoptosis by suppressing the upregulation of NOX4. Collectively, these findings suggest that the inhibition of SIRT7 may play a beneficial role in AD pathogenesis through the regulation of ROS production.

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.

Somatostatin-evoked Aβ catabolism in the brain: Mechanistic involvement of α-endosulfine-KATP channel pathway

Alzheimer's disease (AD) is characterized by the deposition of amyloid β peptide (Aβ) in the brain. The neuropeptide somatostatin (SST) regulates Aβ catabolism by enhancing neprilysin (NEP)-catalyzed proteolytic degradation. However, the mechanism by which SST regulates NEP activity remains unclear. Here, we identified α-endosulfine (ENSA), an endogenous ligand of the ATP-sensitive potassium (K_ATP) channel, as a negative regulator of NEP downstream of SST signaling. The expression of ENSA is significantly increased in AD mouse models and in patients with AD. In addition, NEP directly contributes to the degradation of ENSA, suggesting a substrate-dependent feedback loop regulating NEP activity. We also discovered the specific K_ATP channel subtype that modulates NEP activity, resulting in the Aβ levels altered in the brain. Pharmacological intervention targeting the particular K_ATP channel attenuated Aβ deposition, with impaired memory function rescued via the NEP activation in our AD mouse model. Our findings provide a mechanism explaining the molecular link between K_ATP channel and NEP activation, and give new insights into alternative strategies to prevent AD.

Parkinson's Disease rs117896735 Variant Regulates INPP5F Expression in Brain Tissues and Increases Risk of Alzheimer's Disease

BACKGROUND

Both INPP5D and INPP5F are members of INPP5 family. INPP5F rs117896735 variant was associated with Parkinson's disease (PD) risk, and INPP5D was an Alzheimer's disease (AD) risk gene. However, it remains unclear about the roles of INPP5F rs117896735 variant in AD.

OBJECTIVE

We aim to investigate the roles of rs117896735 in AD.

METHODS

First, we conducted a candidate variant study to evaluate the association of rs117896735 variant with AD risk using the large-scale AD GWAS dataset. Second, we conducted a gene expression analysis of INPP5F to investigate the expression difference of INPP5F in different human tissues using two large-scale gene expression datasets. Third, we conducted an expression quantitative trait loci analysis to evaluate whether rs117896735 variant regulate the expression of INPP5F. Fourth, we explore the potentially differential expression of INPP5F in AD and control using multiple AD-control gene expression datasets in human brain tissues and whole blood.

RESULTS

We found that 1) rs117896735 A allele was associated with the increased risk of AD with OR = 1.15, 95% CI 1.005-1.315, p = 0.042; 2) rs117896735 A allele could increase INPP5F expression in multiple human tissues; 3) INPP5F showed different expression in different human tissues, especially in brain tissues; 4) INPP5F showed significant expression dysregulation in AD compared with controls in human brain tissues.

CONCLUSION

Conclusion: We demonstrate that PD rs117896735 variant could regulate INPP5F expression in brain tissues and increase the risk of AD. These finding may provide important information about the role of rs117896735 in AD.

Connecting the dots: The boons and banes of network modeling

Network modeling transforms data into a structure of nodes and edges such that edges represent relationships between pairs of objects, then extracts clusters of densely connected nodes in order to capture high-dimensional relationships hidden in the data. This efficient and flexible strategy holds potential for unveiling complex patterns concealed within massive datasets, but standard implementations overlook several key issues that can undermine research efforts. These issues range from data imputation and discretization to correlation metrics, clustering methods, and validation of results. Here, we enumerate these pitfalls and provide practical strategies for alleviating their negative effects. These guidelines increase prospects for future research endeavors as they reduce type I and type II (false-positive and false-negative) errors and are generally applicable for network modeling applications across diverse domains.

Integrated Genomic, Transcriptomic and Proteomic Analysis for Identifying Markers of Alzheimer's Disease

There is an urgent need to identify biomarkers for Alzheimer’s disease (AD), but the identification of reliable blood-based biomarkers has proven to be much more difficult than initially expected. The current availability of high-throughput multi-omics data opens new possibilities in this titanic task. Candidate Single Nucleotide Polymorphisms (SNPs) from large, genome-wide association studies (GWAS), meta-analyses exploring AD (case-control design), and quantitative measures for cortical structure and general cognitive performance were selected. The Genotype-Tissue Expression (GTEx) database was used for identifying expression quantitative trait loci (eQTls) among candidate SNPs. Genes significantly regulated by candidate SNPs were investigated for differential expression in AD cases versus controls in the brain and plasma, both at the mRNA and protein level. This approach allowed us to identify candidate susceptibility factors and biomarkers of AD, facing experimental validation with more evidence than with genetics alone.

Identifying correlations driven by influential observations in large datasets

Although high-throughput data allow researchers to interrogate thousands of variables simultaneously, it can also introduce a significant number of spurious results. Here we demonstrate that correlation analysis of large datasets can yield numerous false positives due to the presence of outliers that canonical methods fail to identify. We present Correlations Under The InfluencE (CUTIE), an open-source jackknifing-based method to detect such cases with both parametric and non-parametric correlation measures, and which can also uniquely rescue correlations not originally deemed significant or with incorrect sign. Our approach can additionally be used to identify variables or samples that induce these false correlations in high proportion. A meta-analysis of various omics datasets using CUTIE reveals that this issue is pervasive across different domains, although microbiome data are particularly susceptible to it. Although the significance of a correlation eventually depends on the thresholds used, our approach provides an efficient way to automatically identify those that warrant closer examination in very large datasets.

Systems biology approaches to unravel the molecular and genetic architecture of Alzheimer's disease and related tauopathies

Over the years, genetic studies have identified multiple genetic risk variants associated with neurodegenerative disorders and helped reveal new biological pathways and genes of interest. However, genetic risk variants commonly reside in non-coding regions and may regulate distant genes rather than the nearest gene, as well as a gene's interaction partners in biological networks. Systems biology and functional genomics approaches provide the framework to unravel the functional significance of genetic risk variants in disease. In this review, we summarize the genetic and transcriptomic studies of Alzheimer's disease and related tauopathies and focus on the advantages of performing systems-level analyses to interrogate the biological pathways underlying neurodegeneration. Finally, we highlight new avenues of multi-omics analysis with single-cell approaches, which provide unparalleled opportunities to systematically explore cellular heterogeneity, and present an example of how to integrate publicly available single-cell datasets. Systems-level analysis has illuminated the function of many disease risk genes, but much work remains to study tauopathies and to understand spatiotemporal gene expression changes of specific cell types.

Amyloid-β toxicity modulates tau phosphorylation through the PAX6 signalling pathway

The molecular link between amyloid-β plaques and neurofibrillary tangles, the two pathological hallmarks of Alzheimer's disease, is still unclear. Increasing evidence suggests that amyloid-β peptide activates multiple regulators of cell cycle pathways, including transcription factors CDKs and E2F1, leading to hyperphosphorylation of tau protein. However, the exact pathways downstream of amyloid-β-induced cell cycle imbalance are unknown. Here, we show that PAX6, a transcription factor essential for eye and brain development which is quiescent in adults, is increased in the brains of patients with Alzheimer's disease and in APP transgenic mice, and plays a key role between amyloid-β and tau hyperphosphorylation. Downregulation of PAX6 protects against amyloid-β peptide-induced neuronal death, suggesting that PAX6 is a key executor of the amyloid-β toxicity pathway. Mechanistically, amyloid-β upregulates E2F1, followed by the induction of PAX6 and c-Myb, while Pax6 is a direct target for both E2F1 and its downstream target c-Myb. Furthermore, PAX6 directly regulates transcription of GSK-3β, a kinase involved in tau hyperphosphorylation and neurofibrillary tangles formation, and its phosphorylation of tau at Ser356, Ser396 and Ser404. In conclusion, we show that signalling pathways that include CDK/pRB/E2F1 modulate neuronal death signals by activating downstream transcription factors c-Myb and PAX6, leading to GSK-3β activation and tau pathology, providing novel potential targets for pharmaceutical intervention.

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.

Experimental and real-world evidence supporting the computational repurposing of bumetanide for APOE4-related Alzheimer's disease

The evident genetic, pathological, and clinical heterogeneity of Alzheimer's disease (AD) poses challenges for traditional drug development. We conducted a computational drug repurposing screen for drugs to treat apolipoprotein (apo) E4-related AD. We first established apoE-genotype-dependent transcriptomic signatures of AD by analyzing publicly-available human brain database. We then queried these signatures against the Connectivity Map database containing transcriptomic perturbations of >1300 drugs to identify those that best reverse apoE-genotype-specific AD signatures. Bumetanide was identified as a top drug for apoE4 AD. Bumetanide treatment of apoE4 mice without or with Aβ accumulation rescued electrophysiological, pathological, or cognitive deficits. Single-nucleus RNA-sequencing revealed transcriptomic reversal of AD signatures in specific cell types in these mice, a finding confirmed in apoE4-iPSC-derived neurons. In humans, bumetanide exposure was associated with a significantly lower AD prevalence in individuals over the age of 65 in two electronic health record databases, suggesting effectiveness of bumetanide in preventing AD.

Systems Analysis Reveals Ageing-Related Perturbations in Retinoids and Sex Hormones in Alzheimer's and Parkinson's Diseases

Neurodegenerative diseases, including Alzheimer's (AD) and Parkinson's diseases (PD), are complex heterogeneous diseases with highly variable patient responses to treatment. Due to the growing evidence for ageing-related clinical and pathological commonalities between AD and PD, these diseases have recently been studied in tandem. In this study, we analysed transcriptomic data from AD and PD patients, and stratified these patients into three subclasses with distinct gene expression and metabolic profiles. Through integrating transcriptomic data with a genome-scale metabolic model and validating our findings by network exploration and co-analysis using a zebrafish ageing model, we identified retinoids as a key ageing-related feature in all subclasses of AD and PD. We also demonstrated that the dysregulation of androgen metabolism by three different independent mechanisms is a source of heterogeneity in AD and PD. Taken together, our work highlights the need for stratification of AD/PD patients and development of personalised and precision medicine approaches based on the detailed characterisation of these subclasses.

Pairwise interactions in gene expression determine a hierarchical transcriptional profile in the human brain

The orchestrated expression of thousands of genes gives rise to the complexity of the human brain. However, the structures governing these myriad gene-gene interactions remain unclear. By analyzing transcription data from more than 2000 sites in six human brains, we found that pairwise interactions between genes, without considering any higher-order interactions, are sufficient to predict the transcriptional pattern of the genome for individual brain regions and the transcriptional profile of the entire brain consisting of more than 200 areas. These findings suggest a quadratic complexity of transcriptional patterns in the human brain, which is much simpler than expected. In addition, using a pairwise interaction model, we revealed that the strength of gene-gene interactions in the human brain gives rise to the nearly maximal number of transcriptional clusters, which may account for the functional and structural richness of the brain.

Integration of peripheral transcriptomics, genomics, and interactomics following trauma identifies causal genes for symptoms of post-traumatic stress and major depression

Posttraumatic stress disorder (PTSD) is a debilitating syndrome with substantial morbidity and mortality that occurs in the aftermath of trauma. Symptoms of major depressive disorder (MDD) are also a frequent consequence of trauma exposure. Identifying novel risk markers in the immediate aftermath of trauma is a critical step for the identification of novel biological targets to understand mechanisms of pathophysiology and prevention, as well as the determination of patients most at risk who may benefit from immediate intervention. Our study utilizes a novel approach to computationally integrate blood-based transcriptomics, genomics, and interactomics to understand the development of risk vs. resilience in the months following trauma exposure. In a two-site longitudinal, observational prospective study, we assessed over 10,000 individuals and enrolled >700 subjects in the immediate aftermath of trauma (average 5.3 h post-trauma (range 0.5-12 h)) in the Grady Memorial Hospital (Atlanta) and Jackson Memorial Hospital (Miami) emergency departments. RNA expression data and 6-month follow-up data were available for 366 individuals, while genotype, transcriptome, and phenotype data were available for 297 patients. To maximize our power and understanding of genes and pathways that predict risk vs. resilience, we utilized a set-cover approach to capture fluctuations of gene expression of PTSD or depression-converting patients and non-converting trauma-exposed controls to find representative sets of disease-relevant dysregulated genes. We annotated such genes with their corresponding expression quantitative trait loci and applied a variant of a current flow algorithm to identify genes that potentially were causal for the observed dysregulation of disease genes involved in the development of depression and PTSD symptoms after trauma exposure. We obtained a final list of 11 driver causal genes related to MDD symptoms, 13 genes for PTSD symptoms, and 22 genes in PTSD and/or MDD. We observed that these individual or combined disorders shared ESR1, RUNX1, PPARA, and WWOX as driver causal genes, while other genes appeared to be causal driver in the PTSD only or MDD only cases. A number of these identified causal pathways have been previously implicated in the biology or genetics of PTSD and MDD, as well as in preclinical models of amygdala function and fear regulation. Our work provides a promising set of initial pathways that may underlie causal mechanisms in the development of PTSD or MDD in the aftermath of trauma.

Rheb-mTOR activation rescues Aβ-induced cognitive impairment and memory function by restoring miR-146 activity in glial cells

Deposition of amyloid beta plaques in adult rat or human brain is associated with increased production of proinflammatory cytokines by associated glial cells that are responsible for degeneration of the diseased tissue. The expression of these cytokines is usually under check and is controlled at the post-transcriptional level via several microRNAs. Computational analysis of gene expression profiles of cortical regions of Alzheimer’s disease patients’ brain suggests ineffective target cytokine mRNA suppression by existing micro-ribonucleoproteins (miRNPs) in diseased brain. Exploring the mechanism of amyloid beta-induced cytokine expression, we have identified how the inactivation of the repressive miR-146 miRNPs causes increased production of cytokines in amyloid beta-exposed glial cells. In exploration of the cause of miRNP inactivation, we have noted amyloid beta oligomer-induced sequestration of the mTORC1 complex to early endosomes that results in decreased Ago2 phosphorylation, limited Ago2-miRNA uncoupling, and retarded Ago2-cytokine mRNA interaction in rat astrocytes. Interestingly, constitutive activation of mTORC1 by Rheb activator restricts proinflammatory cytokine production by reactivating miR-146 miRNPs in amyloid beta-exposed glial cells to rescue the disease phenotype in the in vivo rat model of Alzheimer’s disease.

Multiomics integrative analysis identifies APOE allele-specific blood biomarkers associated to Alzheimer's disease etiopathogenesis

Alzheimer's disease (AD) is the most common form of dementia, currently affecting 35 million people worldwide. Apolipoprotein E (APOE) ε4 allele is the major risk factor for sporadic, late-onset AD (LOAD), which comprises over 95% of AD cases, increasing the risk of AD 4-12 fold. Despite this, the role of APOE in AD pathogenesis is still a mystery. Aiming for a better understanding of APOE-specific effects, the ADAPTED consortium analysed and integrated publicly available data of multiple OMICS technologies from both plasma and brain stratified by APOE haplotype (APOE2, APOE3 and APOE4). Combining genome-wide association studies (GWAS) with differential mRNA and protein expression analyses and single-nuclei transcriptomics, we identified genes and pathways contributing to AD in both APOE dependent and independent fashion. Interestingly, we characterised a set of biomarkers showing plasma and brain consistent protein profiles and opposite trends in APOE2 and APOE4 AD cases that could constitute screening tools for a disease that lacks specific blood biomarkers. Beside the identification of APOE-specific signatures, our findings advocate that this novel approach, based on the concordance across OMIC layers and tissues, is an effective strategy for overcoming the limitations of often underpowered single-OMICS studies.

Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer's Disease

To identify the molecular mechanisms and novel therapeutic targets of late-onset Alzheimer's Disease (LOAD), we performed an integrative network analysis of multi-omics profiling of four cortical areas across 364 donors with varying cognitive and neuropathological phenotypes. Our analyses revealed thousands of molecular changes and uncovered neuronal gene subnetworks as the most dysregulated in LOAD. ATP6V1A was identified as a key regulator of a top-ranked neuronal subnetwork, and its role in disease-related processes was evaluated through CRISPR-based manipulation in human induced pluripotent stem cell-derived neurons and RNAi-based knockdown in Drosophila models. Neuronal impairment and neurodegeneration caused by ATP6V1A deficit were improved by a repositioned compound, NCH-51. This study provides not only a global landscape but also detailed signaling circuits of complex molecular interactions in key brain regions affected by LOAD, and the resulting network models will serve as a blueprint for developing next-generation therapeutic agents against LOAD.

Danger-Sensing/Patten Recognition Receptors and Neuroinflammation in Alzheimer's Disease

Fibrillar aggregates and soluble oligomers of both Amyloid-β peptides (Aβs) and hyperphosphorylated Tau proteins (p-Tau-es), as well as a chronic neuroinflammation are the main drivers causing progressive neuronal losses and dementia in Alzheimer’s disease (AD). However, the underlying pathogenetic mechanisms are still much disputed. Several endogenous neurotoxic ligands, including Aβs, and/or p-Tau-es activate innate immunity-related danger-sensing/pattern recognition receptors (PPRs) thereby advancing AD’s neuroinflammation and progression. The major PRR families involved include scavenger, Toll-like, NOD-like, AIM2-like, RIG-like, and CLEC-2 receptors, plus the calcium-sensing receptor (CaSR). This quite intricate picture stresses the need to identify the pathogenetically topmost Aβ-activated PRR, whose signaling would trigger AD’s three main drivers and their intra-brain spread. In theory, the candidate might belong to any PRR family. However, results of preclinical studies using in vitro nontumorigenic human cortical neurons and astrocytes and in vivo AD-model animals have started converging on the CaSR as the pathogenetically upmost PRR candidate. In fact, the CaSR binds both Ca²⁺ and Aβs and promotes the spread of both Ca²⁺ dyshomeostasis and AD’s three main drivers, causing a progressive neurons’ death. Since CaSR’s negative allosteric modulators block all these effects, CaSR’s candidacy for topmost pathogenetic PRR has assumed a growing therapeutic potential worth clinical testing.

Reconstruction of a directed acyclic graph with intervention

Identification of causal relations among variables is central to many scientific investigations, as in regulatory network analysis of gene interactions and brain network analysis of effective connectivity of causal relations between regions of interest. Statistically, causal relations are often modeled by a directed acyclic graph (DAG), and hence that reconstruction of a DAG's structure leads to the discovery of causal relations. Yet, reconstruction of a DAG's structure from observational data is impossible because a DAG Gaussian model is usually not identifiable with unequal error variances. In this article, we reconstruct a DAG's structure with the help of interventional data. Particularly, we construct a constrained likelihood to regularize intervention in addition to adjacency matrices to identify a DAG's structure, subject to an error variance constraint to further reinforce the model identifiability. Theoretically, we show that the proposed constrained likelihood leads to identifiable models, thus correct reconstruction of a DAG's structure through parameter estimation even with unequal error variances. Computationally, we design efficient algorithms for the proposed method. In simulations, we show that the proposed method enables to produce a higher accuracy of reconstruction with the help of interventional observations.

Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia but has no effective treatment. A comprehensive investigation of cell type-specific responses and cellular heterogeneity in AD is required to provide precise molecular and cellular targets for therapeutic development. Accordingly, we perform single-nucleus transcriptome analysis of 169,496 nuclei from the prefrontal cortical samples of AD patients and normal control (NC) subjects. Differential analysis shows that the cell type-specific transcriptomic changes in AD are associated with the disruption of biological processes including angiogenesis, immune activation, synaptic signaling, and myelination. Subcluster analysis reveals that compared to NC brains, AD brains contain fewer neuroprotective astrocytes and oligodendrocytes. Importantly, our findings show that a subpopulation of angiogenic endothelial cells is induced in the brain in patients with AD. These angiogenic endothelial cells exhibit increased expression of angiogenic growth factors and their receptors (i.e., EGFL7, FLT1, and VWF) and antigen-presentation machinery (i.e., B2M and HLA-E). This suggests that these endothelial cells contribute to angiogenesis and immune response in AD pathogenesis. Thus, our comprehensive molecular profiling of brain samples from patients with AD reveals previously unknown molecular changes as well as cellular targets that potentially underlie the functional dysregulation of endothelial cells, astrocytes, and oligodendrocytes in AD, providing important insights for therapeutic development.

Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer's disease

Alzheimer's disease (AD) is a devastating neurological disorder characterized by changes in cell-type proportions and consequently marked alterations of the transcriptome. Here we use a data-driven systems biology meta-analytical approach across three human AD cohorts, encompassing six cortical brain regions, and integrate with multi-scale datasets comprising of DNA methylation, histone acetylation, transcriptome- and genome-wide association studies and quantitative trait loci to further characterize the genetic architecture of AD. We perform co-expression network analysis across more than 1200 human brain samples, identifying robust AD-associated dysregulation of the transcriptome, unaltered in normal human aging. We assess the cell-type specificity of AD gene co-expression changes and estimate cell-type proportion changes in human AD by integrating co-expression modules with single-cell transcriptome data generated from 27 321 nuclei from human postmortem prefrontal cortical tissue. We also show that genetic variants of AD are enriched in a microglial AD-associated module and identify key transcription factors regulating co-expressed modules. Additionally, we validate our results in multiple published human AD gene expression datasets, which can be easily accessed using our online resource (https://swaruplab.bio.uci.edu/consensusAD).

A second X chromosome contributes to resilience in a mouse model of Alzheimer's disease

A major sex difference in Alzheimer's disease (AD) is that men with the disease die earlier than do women. In aging and preclinical AD, men also show more cognitive deficits. Here, we show that the X chromosome affects AD-related vulnerability in mice expressing the human amyloid precursor protein (hAPP), a model of AD. XY-hAPP mice genetically modified to develop testicles or ovaries showed worse mortality and deficits than did XX-hAPP mice with either gonad, indicating a sex chromosome effect. To dissect whether the absence of a second X chromosome or the presence of a Y chromosome conferred a disadvantage on male mice, we varied sex chromosome dosage. With or without a Y chromosome, hAPP mice with one X chromosome showed worse mortality and deficits than did those with two X chromosomes. Thus, adding a second X chromosome conferred resilience to XY males and XO females. In addition, the Y chromosome, its sex-determining region Y gene (Sry), or testicular development modified mortality in hAPP mice with one X chromosome such that XY males with testicles survived longer than did XY or XO females with ovaries. Furthermore, a second X chromosome conferred resilience potentially through the candidate gene Kdm6a, which does not undergo X-linked inactivation. In humans, genetic variation in KDM6A was linked to higher brain expression and associated with less cognitive decline in aging and preclinical AD, suggesting its relevance to human brain health. Our study suggests a potential role for sex chromosomes in modulating disease vulnerability related to AD.