AD-related Pathways Research Articles

Multi-tissue Methylation Analysis of Alzheimer's Disease: Insights into Pathways, Modules, and Key Genes.

DNA methylation plays a crucial role in the onset and progression of Alzheimer's disease (AD). Genome-wide methylation analysis of multi-tissue data can provide insights into the pathology and diagnostic biomarkers of AD. Computational tools were employed to identify pathways associated with AD and to develop a poly-methylation score (PMS). Key genes within the identified pathways were determined through module analysis and protein-protein interaction networks followed by validation in β-amyloid 42-induced cellular models. Linear mixed-effects model was used to investigate the longitudinal relationship between PMS and changes in AD phenotypes. AD-related pathways exhibited tissue specificity. The key genes in blood, frontal cortex, neurons, and glial cells were THBS1, TGFB1, HIF1A, and KLF4, respectively. Furthermore, the expression alterations of these genes were validated in three cellular models (SH-SY5Y, HMC3, and THP-1). Notably, higher PMS was significantly correlated with accelerated declines in cerebral metabolic rate and cognitive function. Using machine learning to analyze methylation data and identify key genes in AD patients enhanced our understanding of AD pathogenesis. Further research is needed to validate the potential of these key genes as intervention targets for AD.

Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes.

Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes.

Dynamics and role of covalently-closed circular RNAs in Alzheimer's disease: A review of experimental and bioinformatics studies.

Dynamics and role of covalently-closed circular RNAs in Alzheimer's disease: A review of experimental and bioinformatics studies.

Spatial profiling of chromatin accessibility reveals alteration of glial cells in Alzheimer's disease mouse brain.

Abnormal epigenetic modifications, including altered chromatin accessibility, have been implicated in the development and progression of Alzheimer's disease (AD). In this study, we applied spatially resolved chromatin accessibility profiling by performing spatial assay for transposase-accessible chromatin using sequencing (ATAC-seq) to analyze brain tissues from 5xFAD AD model and C57BL/6J control mice. Our analysis identified seven major cell types across 11 brain regions and further characterized glial subtypes microglia and astrocytes revealing subtype-specific chromatin accessibility changes in 5xFAD mice relative to controls. These alterations were associated with AD-related pathways, including neuroinflammation and immune dysregulation, and synaptic dysfunction and neuronal signaling in microglia, as well as lysosomal and proteasomal activity, lipoprotein metabolism, and mitochondrial dysfunction in astrocytes. We also characterized cell-type-specific enrichments of motifs and transcription factors, including enrichment of Bcl11a in microglia. Furthermore, we linked chromatin accessibility changes in 5xFAD mice to human AD risk genes, highlighting altered epigenetic signatures in genes such as Trem2. Supporting the spatial ATAC-seq findings, flow cytometry validated a selective increase in VISTA (encoded by Vsir) protein expression in 5xFAD microglia, supporting the spatial ATAC-seq findings and indicating a shift toward a pro-inflammatory, disease-associated microglial (DAM-like) phenotype. These findings underscore the utility of spatial chromatin accessibility profiling for uncovering brain-region specific cell identities and epigenetic mechanisms underlying AD pathogenesis.

Investigating the effects of 40 Hz sound stimulation on Alzheimer's disease pathways: Modulation of amyloid-β42 secretion, tau phosphorylation, phagocytosis, and autophagy.

BackgroundAlzheimer's disease (AD) is the main cause of dementia in an aging society. Previous studies have demonstrated that non-invasive light flicker and sound with gamma frequency oscillations can modulate AD-related pathology in AD mice, potentially improving patient outcomes. However, the molecular mechanism by which sound with gamma frequency oscillations inhibits the expression of amyloid-β1-42 (Aβ42) and the phosphorylation of tau, and modulating cell autophagy in nerve cells are still unclear.ObjectiveThis study aimed to explore the molecular effects of 40 Hz sound stimulation on AD-related pathways in a cellular model.MethodsWe designed a 40 Hz stimulating sound (H+ multi-frequency audio) for this study, and cells were exposed to H+ multi-frequency audio. The concentration of Aβ42 was quantified by enzyme-linked immunosorbent assay. Protein levels were examined by western blotting. Phagocytosis was examined by confocal microscopy and phagocytic analysis.ResultsFirst, we found that exposure to the 40 Hz stimulating sound inhibited the secretion of Aβ42 by activating the AβPP/ADAM10 pathway and suppressing the AβPP/BACE1 pathway. Second, 40 Hz stimulating sound inhibited tau phosphorylation at Thr181 through the inactivation of the Akt/mTOR pathway. Third, 40 Hz stimulating sound enhanced the phagocytosis and autophagy of Aβ42 through the AMPK/ULK/LC3B pathway in cells.ConclusionsOur study showed that 40 Hz stimulating sound is involved in the inhibition of Aβ42 secretion, p-Tau protein expression, and the promotion of phagocytosis and Aβ42 autophagy in cells. We suggest that 40 Hz stimulating sound could be a potential intervention to attenuate AD progression in the future.

Alzheimer's disease patient brain extracts induce multiple pathologies in novel vascularized neuroimmune organoids for disease modeling and drug discovery.

Alzheimer's Disease (AD) is the most common cause of dementia, afflicting 55 million individuals worldwide, with limited treatment available. Current AD models mainly focus on familial AD (fAD), which is due to genetic mutations. However, models for studying sporadic AD (sAD), which represents over 95% of AD cases without specific genetic mutations, are severely limited. Moreover, the fundamental species differences between humans and animals might significantly contribute to clinical failures for AD therapeutics that have shown success in animal models, highlighting the urgency to develop more translational human models for studying AD, particularly sAD. In this study, we developed a complex human pluripotent stem cell (hPSC)-based vascularized neuroimmune organoid model, which contains multiple cell types affected in human AD brains, including human neurons, microglia, astrocytes, and blood vessels. Importantly, we demonstrated that brain extracts from individuals with sAD can effectively induce multiple AD pathologies in organoids four weeks post-exposure, including amyloid beta (Aβ) plaque-like aggregates, tau tangle-like aggregates, neuroinflammation, elevated microglial synaptic pruning, synapse/neuronal loss, and impaired neural network activity. Proteomics analysis also revealed disrupted AD-related pathways in our vascularized AD neuroimmune organoids. Furthermore, after treatment with Lecanemab, an FDA-approved antibodydrug targeting Aβ, AD brain extracts exposed organoids showed a significant reduction of amyloid burden, along with an elevated vascular inflammation response. Thus, the vascularized neuroimmune organoid model provides a unique opportunity to study AD, particularly sAD, under a pathophysiological relevant three-dimensional (3D) human cell environment. It also holds great promise to facilitate AD drug development, particularly for immunotherapies.

Ferroptosis and Alzheimer's: unveiling new avenues for the treatment and prevention.

Alzheimer's disease (AD), one of the most prevalent neurodegenerative illnesses worldwide, has a devastating effect on individual, families and society. Despite the extensive research and effort, various clinical trials aimed against amyloid-β, which is suspected to have a causative role in the illness, have not yet shown any clinically significant success to date. Emerging evidence suggests that ferroptosis, a kind of programmed cell death triggered by lipid peroxidation and dependent on iron, plays a role in AD. There is a complex relationship between AD and ferroptosis. In both the processes iron dysregulation, altered anti-oxidant mechanisms and lipid peroxidation is involved. Ferroptotic processes contributes to the neuro-inflammation, oxidative stress and damage to the neurons as observed in AD. Additionally, amyloid-β, a hallmark of AD, may influence the ferroptosis, further linked the two pathways. Numerous signalling pathways such as Phospho inositide 3-kinase, Glycogen synthase kinase-3β, 5'-AMP-activated protein kinase, nuclear factor erythroid 2-related factor-2 and Sirtuin pathway plays a part in the pathophysiology of AD. Through a comprehensive review of current research and experimentation, this investigation elucidates the interactions between novel pharmacological agents (ferroptotic inhibitors) and AD-related pathways. Furthermore, this review highlights the various ferroptotic inhibitors as the therapeutic agents for the slowing down the progression of AD. The crosstalk between these processes could unveil the potential therapeutic targets for the AD treatment.

Pathway-based network medicine identifies novel natural products for Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is the leading cause of dementia, characterized by a complex pathogenesis that complicates the development of effective treatments. Natural products are promising multitarget agents because of their ability to interact with multiple molecular targets. Network-based medicine presents a robust strategy for discovering such agents, which can address the intricate mechanisms underlying AD.MethodsIn this study, we constructed an AD-related pathway-gene network via text mining and pathway database construction. This network facilitated the identification of natural products that target multiple pathways and genes associated with AD. We evaluated the safety profiles of two selected natural products in C57BL/6J mice through assessments of general behavior, body weight changes, vital organ weight and morphology, and hematological and biochemical parameters. APP/PS1 transgenic mice were subsequently treated with these natural products—either individually or in combination—to assess their therapeutic effects. Cognitive function was evaluated via behavioral tests, such as novel object recognition, Y-maze, and Morris water maze tests. Additionally, immunohistochemical staining and enzyme-linked immunosorbent assays were performed to examine Aβ-associated pathological changes. Transcriptomic analysis and quantitative real-time polymerase chain reaction (qRT-PCR) were employed to elucidate the mechanisms underlying the effects of the natural products.ResultsThe constructed AD-related pathway-gene network encompassed three perspectives: (i) Most Studied Pathways (21 pathways with 5325 genes), (ii) Gene-Associated Pathways (26 pathways with 2557 genes), and (iii) Popular Pathways (24 pathways with 3435 genes). Two natural products, (-)-Vestitol and Salviolone, were selected for further validation. Their safety was confirmed in C57BL/6J mice. Notably, the combination of (-)-Vestitol and Salviolone synergistically affected cognitive function in APP/PS1 transgenic mice by reducing Aβ deposition and lowering toxic soluble Aβ levels in the brain. Transcriptomic analysis and qRT-PCR experiments revealed that their combination regulated AD-related pathways and genes more comprehensively, particularly affecting the Neuroactive ligand-receptor interaction and Calcium signaling pathway.ConclusionsOur findings demonstrate that screening potential natural products through an AD-related pathway-gene network is a promising strategy for discovering novel therapeutics for AD. The therapeutic potential of (-)-Vestitol and Salviolone as novel candidates for AD treatment is underscored by their synergistic effects, attributed to their comprehensive regulation of AD-associated pathways and genes.

RA-PR058, a novel ramalin derivative, reduces BACE1 expression and phosphorylation of tau in Alzheimer’s disease mouse models

ABSTRACT Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterized by cognitive decline, anxiety-like behavior, β-amyloid (Aβ) accumulation, and tau hyperphosphorylation. BACE1, the enzyme critical for Aβ production, has been a major therapeutic target; however, direct BACE1 inhibition has been associated with adverse side effects. This study investigates the therapeutic potential of RA-PR058, a novel ramalin derivative, as a multi-targeted modulator of AD-related pathologies. The effects of RA-PR058 were evaluated in vitro and in vivo. In vitro studies used SH-SY5Y cells under oxidative stress conditions to assess BACE1 expression, while in vivo effects were studied in 3xTg-AD mice following one month of oral RA-PR058 treatment. Behavioral assessments, biochemical analyses, transcriptomic profiling, and pharmacokinetic evaluations were performed to determine the efficacy of RA-PR058. RA-PR058 significantly reduced oxidative stress-induced BACE1 expression in vitro and decreased cortical BACE1 expression in 3xTg-AD mice. In vivo treatment alleviated anxiety-like behavior and reduced tau phosphorylation at disease-relevant sites (Ser202/Thr205, Thr231, and Ser396). Transcriptomic analysis revealed RA-PR058-mediated gene expression changes related to central nervous system development, response to hypoxia, and neuroactive ligand–receptor interactions, suggesting broader regulatory effects on AD-related pathways. Pharmacokinetic analysis demonstrated that RA-PR058 exhibits high metabolic stability, minimal cytochrome P450 interactions, and moderate blood–brain barrier penetration. RA-PR058 demonstrates potential as a multi-target AD therapeutic by reducing BACE1 expression, tau hyperphosphorylation, and anxiety-like behavior, coupled with favorable pharmacokinetics. Additional studies are needed to assess cognitive effects and clarify molecular mechanisms, but RA-PR058 may represent a promising advancement in addressing AD’s complex pathology.

Identification of Therapeutic Potential of Hydroxychavicol Against Alzheimer's Disease: An Integrated Network Pharmacology, Molecular Docking, and Dynamic Simulation Study.

Alzheimer's disease (AD) is a commonly occurring neurodegenerative disease in elderly and it is a leading cause of dementia worldwide. Hydroxychavicol (HC), a major phenolic component of Piper betle, has prominent anti-inflammatory and antioxidant properties, and studies have found its role in cognition improvement. Here is a systematic approach to deciphering the potential protein targets of HC in AD through network pharmacology and validation from molecular docking and dynamics simulation study. First, the druglikeliness of HC was predicted using the SwissADME analysis, which showed significant druglikeliness. A total of 88 possible target genes between HC and AD were obtained from the Swiss Target Prediction, HIT Version 2, DisGeNET, and GeneCards database. The pathway analysis was carried out using the STRING database which showed several genes including COMT, HSP90AA1, and GAPDH as the top hub genes on the basis of degree. GO and KEGG analyses demonstrated that the core targets were mainly involved in cAMP, PI3K/AkT, HIF1, Rap1, and Calcium signaling pathways. The molecular docking of HC with top hub genes resulted in the highest binding of HC with COMT (-8.9 kcal/mol), GAPDH (-6.7 kcal/mol), and HSP90AA1 (-6.5 kcal/mol) that showed stable binding in the molecular dynamics simulation study. COMT regulates the dopamine levels in the prefrontal cortex and impairment of the COMT is associated with the rapid progression of AD. HSP90, a ubiquitous molecular chaperone, is involved in regulating tau metabolism and Aβ processing and found to be downregulated in AD. GAPDH has been reported as the disease-susceptible gene in AD and its interaction with amyloid precursor protein and NFTs has also been reported. These findings suggest that HC is a promising therapeutic candidate, targeting multiple AD-related pathways, warranting further investigation into its molecular mechanisms and potential for clinical application.

Network pharmacology and artificial intelligence in traditional Chinesemedicine for Alzheimer’s disease:Acomprehensive review

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, characterized by the accumulation of amyloid-beta, tau hyperphosphorylation, neuroinflammation, and oxidative stress. With current pharmacological treatments providing symptomatic relief, the need for other therapeutic approaches becomes evident. Traditional Chinese Medicine, with its multi-component and multi-target approach, offers promising potential for the management of AD, but the complex formulations have proved challenging to discern precise mechanisms of therapy. Network pharmacology, a systems biology approach, has emerged as a powerful tool in understanding the mechanisms of action of TCM by mapping bioactive compounds to AD-related pathways. This method enables the identification of synergistic interactions and key molecular targets, facilitating drug discovery and optimization. Furthermore, AI, particularly machine learning and deep learning algorithms, has revolutionized TCM research by analyzing large datasets, predicting compound-target interactions, and enabling personalized treatment approaches. AI-driven virtual screening and computational modeling have rapidly accelerated the identification of potential neuroprotective compounds, such as curcumin, ginsenosides, and huperzine A, which modulate multiple AD-associated pathways. The integration of network pharmacology and AI offers a systematic framework for validating TCM formulations and optimizing their therapeutic potential. This review highlights recent advancements in AI-assisted TCM research, discusses key bioactive compounds, and explores their mechanisms in AD treatment. While standardization and regulatory approval continue to be challenging, the synthesis of ancient knowledge with contemporary computing technologies holds enormous promise for effective, multi-target interventions for AD, thereby ushering in a new wave of innovative therapeutic approaches.

Epigenetics in Neurodegenerative Diseases.

Healthy brain functioning requires a continuous fine-tuning of gene expression, involving changes in the epigenetic landscape and 3D chromatin organization. Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD) are three multifactorial neurodegenerative diseases (NDDs) that are partially explained by genetics (gene mutations and genetic risk factors) and influenced by non-genetic factors (i.e., aging, lifestyle, and environmental conditions). Examining comprehensive studies of global and locus-specific (epi)genomic and transcriptomic alterations in human and mouse brain samples at the cell-type resolution has uncovered important phenomena associated with AD. First, DNA methylation and histone marks at promoters contribute to transcriptional dysregulation of genes that are directly implicated in AD pathogenesis (i.e., APP), neuroplasticity and cognition (i.e., PSD95), and microglial activation (i.e., TREM2). Second, the presence of AD genetic risk variants in cell-type-specific distal enhancers (i.e., BIN1 in microglia) alters transcription, presumably by disrupting associated enhancer-promoter interactions and chromatin looping. Third, epigenomic erosion is associated with widespread transcriptional disruption and cell identity loss. And fourth, aging, high cholesterol, air pollution, and pesticides have emerged as potential drivers of AD by inducing locus-specific and global epigenetic modifications that impact key AD-related pathways. Epigenetic studies in ALS/FTD also provide evidence that genetic and non-genetic factors alter gene expression profiles in neurons and astrocytes through aberrant epigenetic mechanisms. We additionally overview the recent development of potential new therapeutic strategies involving (epi)genetic editing and the use of small chromatin-modifying molecules (epidrugs).

DJ-1-mediated repression of the RNA-binding protein FMRP is predicted to impact known Alzheimer's disease-related protein networks.

RNA-binding proteins (RBPs) modulate the synaptic proteome and are instrumental in maintaining synaptic homeostasis. Moreover, aberrant expression of an RBP in a disease state would have deleterious downstream effects on synaptic function. While many underlying mechanisms of synaptic dysfunction in Alzheimer's disease (AD) have been proposed, the contribution of RBPs has been relatively unexplored. To investigate alterations in RBP-messenger RNA (mRNA) interactions in AD, and its overall impact on the disease-related proteome. We first utilized RNA-immunoprecipitation to investigate interactions between RBP, DJ-1 (Parkinson's Disease protein 7) and target mRNAs in controls and AD. Surface Sensing of Translation - Proximity Ligation Assay (SUnSET-PLA) and western blotting additionally quantified alterations in mRNA translation and protein expression of DJ-1 targets. Finally, we utilized an unbiased bioinformatic approach that connects AD-related pathways to two RBPs, DJ-1 and FMRP (Fragile X messenger ribonucleoprotein 1). We find that oligomeric DJ-1 in AD donor synapses were less dynamic in their ability to bind and unbind mRNA compared to synapses from cognitively unimpaired, neuropathologically-verified controls. Furthermore, we find that DJ-1 associates with the mRNA coding for FMRP, Fmr1, leading to its reduced synaptic expression in AD. Through the construction of protein-protein interaction networks, aberrant expression of DJ-1 and FMRP are predicted to lead to the upregulation of key AD-related pathways, such as thyroid hormone stimulating pathway, autophagy, and ubiquitin mediated proteolysis. DJ-1 and FMRP are novel targets that may restore established neurobiological mechanisms underlying AD.

Investigating gene expression datasets of hippocampus tissue to discover Alzheimer's disease-associated molecular markers.

Alzheimer's disease (AD) is an advancing neurodegenerative disorder distinguished by the formation of amyloid plaques and neurofibrillary tangles in the human brain. Nevertheless, the lack of peripheral biomarkers that can detect the development of AD remains a significant limitation. The main aim of this work was to discover the molecular markers associated with AD. We conducted a comprehensive microarray analysis of gene expression data from hippocampus tissue in AD patients and control samples using three microarray datasets (GSE1297, GSE28146, and GSE29378) collected from Gene Expression Omnibus (GEO). The datasets were pre-processed and normalized, revealing 346 significant genes, 103 of which were upregulated and 243 downregulated. The PPI network of significant genes was constructed to detect the top 50 hub genes, which were then further analyzed using Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes pathway (KEGG), and GSEA, revealing 47 key genes involved in AD-related pathways. These key genes were then subjected to feed forward loop (FFL) motif analysis for the prediction of transcriptional factors (TFs) and microRNAs (miRNAs) mediated gene regulatory networks. The interaction of AD-associated TFs HNF4A, SPI1, EGR1, STAT3, and MYC and miRNAs hsa-miR-155-5p and hsa-miR-16-5p in the transcriptional and post-transcriptional events of 3 upregulated and 10 downregulated genes: H2AFZ, MCM3, MYO1C, AXIN1, CCND1, ETS2, MYH9, RELA, RHEB, SOCS3, TBL1X, TBP, TXNIP, and YWHAZ, respectively, has been identified. The miRNA/TF-mediated three types of the FFL motifs, i.e., miRNA-FFL, TF-FFL, and composite-FFL, were constructed, and seven common genes among these FFL were identified: CCND1, MYH9, SOCS3, RHEB, MYO1C, TXNIP, AXIN1, and TXNIP. These findings may provide insights into the development of potential molecular markers for therapeutic management of AD.

Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes.

Spatial transcriptomics ( ST ) data provide spatially-informed gene expression for studying complex diseases such as Alzheimer's disease ( AD ). Existing studies using ST data to identify genes with spatially-informed differential gene expression ( DGE ) of complex diseases have limited power due to small sample sizes. Conversely, single-nucleus RNA sequencing ( snRNA-seq ) data offer larger sample sizes for studying cell-type specific ( CTS ) DGE but lack spatial information. In this study, we integrated ST and snRNA-seq data to enhance the power of spatially-informed CTS DGE analysis of AD-related phenotypes. First, we utilized the recently developed deep learning tool CelEry to infer the spatial location of ∼1.5M cells from snRNA-seq data profiled from dorsolateral prefrontal cortex ( DLPFC ) tissue of 436 postmortem brains in the ROS/MAP cohorts. Spatial locations of six cortical layers that have distinct anatomical structures and biological functions were inferred. Second, we conducted cortical-layer specific ( CLS ) and CTS DGE analyses for three quantitative AD-related phenotypes -- β-amyloid, tangle density, and cognitive decline. CLS-CTS DGE analyses were conducted based on linear mixed regression models with pseudo-bulk scRNA-seq data and inferred cortical layer locations. We identified 450 potential CLS-CTS significant genes with nominal p-values<10 -4 , including 258 for β-amyloid, 122 for tangle density, and 127 for cognitive decline. Majority of these identified genes, including the ones having known associations with AD (e.g., APOE , KCNIP3 , and CTSD ), cannot be detected by traditional CTS DGE analyses without considering spatial information. We also identified 8 genes shared across all three phenotypes, 21 between β-amyloid and tangle density, 10 between cognitive decline and tangle density, and 10 between β-amyloid and cognitive density. Particularly, Gene Set Enrichment Analyses with the CLS-CTS DGE results of microglia in cortical layer-6 of β-amyloid identified 12 significant AD-related pathways. Incorporating spatial information with snRNA-seq data detected significant genes and pathways for AD-related phenotypes that would not be identified by traditional CTS DGE analyses. These identified CLS-CTS significant genes not only help illustrate the pathogenesis of AD, but also provide potential CLS-CTS targets for developing therapeutics of AD.

Haploinsufficiency and Alzheimer's Disease: The Possible Pathogenic and Protective Genetic Factors.

Alzheimer's disease (AD) is a complex neurodegenerative disorder influenced by various genetic factors. In addition to the well-established amyloid precursor protein (APP), Presenilin-1 (PSEN1), Presenilin-2 (PSEN2), and apolipoprotein E (APOE), several other genes such as Sortilin-related receptor 1 (SORL1), Phospholipid-transporting ATPase ABCA7 (ABCA7), Triggering Receptor Expressed on Myeloid Cells 2 (TREM2), Phosphatidylinositol-binding clathrin assembly protein (PICALM), and clusterin (CLU) were implicated. These genes contribute to neurodegeneration through both gain-of-function and loss-of-function mechanisms. While it was traditionally thought that heterozygosity in autosomal recessive mutations does not lead to disease, haploinsufficiency was linked to several conditions, including cancer, autism, and intellectual disabilities, indicating that a single functional gene copy may be insufficient for normal cellular functions. In AD, the haploinsufficiency of genes such as ABCA7 and SORL1 may play significant yet under-explored roles. Paradoxically, heterozygous knockouts of PSEN1 or PSEN2 can impair synaptic plasticity and alter the expression of genes involved in oxidative phosphorylation and cell adhesion. Animal studies examining haploinsufficient AD risk genes, such as vacuolar protein sorting-associated protein 35 (VPS35), sirtuin-3 (SIRT3), and PICALM, have shown that their knockout can exacerbate neurodegenerative processes by promoting amyloid production, accumulation, and inflammation. Conversely, haploinsufficiency in APOE, beta-secretase 1 (BACE1), and transmembrane protein 59 (TMEM59) was reported to confer neuroprotection by potentially slowing amyloid deposition and reducing microglial activation. Given its implications for other neurodegenerative diseases, the role of haploinsufficiency in AD requires further exploration. Modeling the mechanisms of gene knockout and monitoring their expression patterns is a promising approach to uncover AD-related pathways. However, challenges such as identifying susceptible genes, gene-environment interactions, phenotypic variability, and biomarker analysis must be addressed. Enhancing model systems through humanized animal or cell models, utilizing advanced research technologies, and integrating multi-omics data will be crucial for understanding disease pathways and developing new therapeutic strategies.

Unveiling disulfidptosis-related biomarkers and predicting drugs in Alzheimer’s disease

Alzheimer's disease is the predominant form of dementia, and disulfidptosis is the latest reported mode of cell death that impacts various disease processes. This study used bioinformatics to analyze genes associated with disulfidptosis in Alzheimer's disease comprehensively. Based on the public datasets, the differentially expressed genes associated with disulfidptosis were identified, and immune cell infiltration was investigated through correlation analysis. Subsequently, hub genes were determined by a randomforest model. A prediction model was constructed using logistic regression. In addition, the drug-target affinity was predicted by a graph neural network model, and the results were validated by molecular docking. Five hub genes (PPEF1, NEUROD6, VIP, NUPR1, and GEM) were identified. The gene set showed significant enrichment for AD-related pathways. The logistic regression model demonstrated an AUC of 0.952, with AUC values of 0.916 and 0.864 in validated datasets. The immune infiltration analysis revealed significant heterogeneity between the Alzheimer's disease and control groups. High-affinity drugs for hub genes were identified. Through our study, a disease prediction model was constructed using potential biomarkers, and drugs targeting the genes were predicted. These results contribute to further understanding of the molecular mechanisms underlying Alzheimer's disease.

Neuroprotective Effects of Sulforaphane in a rat model of Alzheimer's Disease induced by Aβ (1–42) peptides

Neuroprotective Effects of Sulforaphane in a rat model of Alzheimer's Disease induced by Aβ (1–42) peptides

Developmental neurotoxicity of PFOA exposure on hiPSC-derived cortical neurons

Developmental neurotoxicity of PFOA exposure on hiPSC-derived cortical neurons

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases.

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases. We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ). For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method. We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.