Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort

Network Pharmacology Reveals Key Targets and Pathways of Madhuca longifolia for Potential Alzheimer's Disease Treatment

Madhuca longifolia, commonly known as the mahua tree, has been traditionally used in medicine due to its anti-inflammatory, anti-diabetic, and antimicrobial properties. Its active compounds help in managing diabetes, alleviating cognitive impairment associated with Alzheimer's disease. Nonetheless, the exact neuroprotective mechanism of Madhuca longifolia against Alzheimer's disease remains unclear. This study looked into possible methods by which Madhuca longifolia protects against Alzheimer's disease using network pharmacology, molecular docking and molecular dynamic simulations studies. By applying pre-screening of active constituents, target prediction, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis, our study found that Madhuca longifolia is related to eight active ingredients (Ascorbic acid, Riboflavin, Pantothenic acid, (4 R)-2beta,3beta,23-trihydroxy-oleana-5,12-dien-28-oic acid, Quercetin, Nicotinic acid, Bassiaic acid Thiamine) and 272 common gene targets, with significant involvement in pathways such as PI3K-Akt signaling and neuroactive ligand-receptor interaction. Network analysis demonstrated how Madhuca longifolia can prevent AD by modifying important signalling networks, which may be one of the molecular mechanisms driving the plant's effectiveness against the disease. Molecular docking studies revealed that there were robust binding abilities of Quercetin, Riboflavin and Pantothenic acid to key target proteins AKT1, JUN, and STAT3. Later, molecular dynamic simulations was done to examine the successful activity of the active compounds against potential targets, and it was found that AKT1 and AKT1-Quercetin complex became stable at 260 ps. It may be seen through the study that quercetin may act as a good inhibitor for treatment. This thorough investigation provides a strong basis for future research and development efforts by advancing our understanding of Madhuca longifolia medicinal potential in Alzheimer's disease.

Reversal of synapse loss in Alzheimer mouse models by targeting mGluR5 to prevent synaptic tagging by C1Q

Microglia-mediated synaptic loss contributes to the development of cognitive impairments in Alzheimer's disease (AD). However, the basis for this immune-mediated attack on synapses remains to be elucidated. Treatment with the metabotropic glutamate receptor 5 (mGluR5) silent allosteric modulator (SAM), BMS-984923, prevents β-amyloid oligomer-induced aberrant synaptic signaling while preserving physiological glutamate response. Here, we show that oral BMS-984923 effectively occupies brain mGluR5 sites visualized by [¹⁸F]FPEB positron emission tomography (PET) at doses shown to be safe in rodents and nonhuman primates. In aged mouse models of AD (APPswe/PS1ΔE9 overexpressing transgenic and App^NL-G-F/hMapt double knock-in), SAM treatment fully restored synaptic density as measured by [¹⁸F]SynVesT-1 PET for SV2A and by histology, and the therapeutic benefit persisted after drug washout. Phospho-TAU accumulation in double knock-in mice was also reduced by SAM treatment. Single-nuclei transcriptomics demonstrated that SAM treatment in both models normalized expression patterns to a far greater extent in neurons than glia. Last, treatment prevented synaptic localization of the complement component C1Q and synaptic engulfment in AD mice. Thus, selective modulation of mGluR5 reversed neuronal gene expression changes to protect synapses from damage by microglial mediators in rodents.

Identification of Immune Hub Genes Associated With Braak Stages in Alzheimer’s Disease and Their Correlation of Immune Infiltration

Background

Alzheimer’s disease (AD) is the most common type of neurodegenerative disease. Tau pathology is one of the pathological features of AD, and its progression is closely related to the progress of AD. Immune system dysfunction is an important mediator of Tau pathological progression, but the specific molecular mechanism is still unclear. The purpose of this study is to determine the immune hub genes and peripheral immune cell infiltration associated with the Braak stages, and the molecular mechanisms between them.

Methods

In this study, 60 samples with different Braak stages in the GSE106241 dataset were used to screen Braak stages-related immune hub genes by using the WGCNA package in R and cytoHubba plugin. The temporal lobe expression data in the Alzdata database were used to verify the results. The correlation between the expression level of immune core genes and the pathological features of AD was analyzed to evaluate the abundance of peripheral immune cell infiltration and screened Braak stages-related cells. Finally, we used correlation analysis of immune hub genes and immune cells and Gene Set Enrichment Analysis (GSEA) of them.

Results

Seven genes (GRB2, HSP90AA1, HSPA4, IGF1, KRAS, PIK3R1, and PTPN11) were identified as immune core genes after the screening of the test datasets and validation of independent data. Among them, Kirsten rat sarcoma viral oncogene homolog (KRAS) and Phosphoinositide-3-Kinase Regulatory Subunit 1 (PIK3R1) were the most closely related to Tau and Aβ pathology in AD. In addition, the ImmuneScore increased gradually with the increase of Braak stages. Five types of immune cells (plasma cells, T follicular helper cells, M2 macrophage, activated NK cells, and eosinophils) were correlated with Braak stages. KRAS and PIK3R1 were the immune core genes most related to the abnormal infiltration of peripheral immune cells. They participated in the regulation of the pathological process of AD through axon guidance, long-term potentiation, cytokine–cytokine receptor interaction, RNA polymerase, etc.

Conclusion

The KRAS and PIK3R1 genes were identified as the immune hub genes most associated with Tau pathological progress in AD. The abnormal infiltration of peripheral immune cells mediated by these cells was involved in the Tau pathological process. This provides new insights for AD.

Gene co-expression changes underlying the functional connectomic alterations in Alzheimer's disease

BACKGROUND

There is growing evidence indicating that a number of functional connectivity networks are disrupted at each stage of the full clinical Alzheimer's disease spectrum. Such differences are also detectable in cognitive normal (CN) carrying mutations of AD risk genes, suggesting a substantial relationship between genetics and AD-altered functional brain networks. However, direct genetic effect on functional connectivity networks has not been measured.

METHODS

Leveraging existing AD functional connectivity studies collected in NeuroSynth, we performed a meta-analysis to identify two sets of brain regions: ones with altered functional connectivity in resting state network and ones without. Then with the brain-wide gene expression data in the Allen Human Brain Atlas, we applied a new biclustering method to identify a set of genes with differential co-expression patterns between these two set of brain regions.

RESULTS

Differential co-expression analysis using biclustering method led to a subset of 38 genes which showed distinctive co-expression patterns between AD-related and non AD-related brain regions in default mode network. More specifically, we observed 4 sub-clusters with noticeable co-expression difference, where the difference in correlations is above 0.5 on average.

CONCLUSIONS

This work applies a new biclustering method to search for a subset of genes with altered co-expression patterns in AD-related default mode network regions. Compared with traditional differential expression analysis, differential co-expression analysis yielded many more significant hits with extra insights into the wiring mechanism between genes. Particularly, the differential co-expression pattern was observed between two sets of genes, suggesting potential upstream genetic regulators in AD development.

Co-sparse reduced-rank regression for association analysis between imaging phenotypes and genetic variants

MOTIVATION

The association analysis between genetic variants and imaging phenotypes must be carried out to understand the inherited neuropsychiatric disorders via imaging genetic studies. Given the high dimensionality in imaging and genetic data, traditional methods based on massive univariate regression entail large computational cost and disregard many-to-many correlations between phenotypes and genetic variants. Several multivariate imaging genetic methods have been proposed to alleviate the above problems. However, most of these methods are based on the l1 penalty, which might cause the over-selection of variables and thus mislead scientists in analyzing data from the field of neuroimaging genetics.

RESULTS

To address these challenges in both statistics and computation, we propose a novel co-sparse reduced-rank regression model that identifies complex correlations in a dimensional reduction manner. We developed an iterative algorithm based on a group primal dual-active set formulation to detect simultaneously important genetic variants and imaging phenotypes efficiently and precisely via non-convex penalty. The simulation studies showed that our method achieved accurate and stable performance in parameter estimation and variable selection. In real application, the proposed approach successfully detected several novel Alzheimer's disease-related genetic variants and regions of interest, which indicate that our method may be a valuable statistical toolbox for imaging genetic studies.

AVAILABILITY AND IMPLEMENTATION

The R package csrrr, and the code for experiments in this article is available in Github: https://github.com/hailongba/csrrr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Gene network and biological pathways associated with susceptibility to differentiated thyroid carcinoma

Variants identified in earlier genome-wide association studies (GWAS) on differentiated thyroid carcinoma (DTC) explain about 10% of the overall estimated genetic contribution and could not provide complete insights into biological mechanisms involved in DTC susceptibility. Integrating systems biology information from model organisms, genome-wide expression data from tumor and matched normal tissue and GWAS data could help identifying DTC-associated genes, and pathways or functional networks in which they are involved. We performed data mining of GWAS data of the EPITHYR consortium (1551 cases and 1957 controls) using various pathways and protein-protein interaction (PPI) annotation databases and gene expression data from The Cancer Genome Atlas. We identified eight DTC-associated genes at known loci 2q35 (DIRC3), 8p12 (NRG1), 9q22 (FOXE1, TRMO, HEMGN, ANP32B, NANS) and 14q13 (MBIP). Using the EW_dmGWAS approach we found that gene networks related to glycogenolysis, glycogen metabolism, insulin metabolism and signal transduction pathways associated with muscle contraction were overrepresented with association signals (false discovery rate adjusted p-value < 0.05). Additionally, suggestive association of 21 KEGG and 75 REACTOME pathways with DTC indicate a link between DTC susceptibility and functions related to metabolism of cholesterol, amino sugar and nucleotide sugar metabolism, steroid biosynthesis, and downregulation of ERBB2 signaling pathways. Together, our results provide novel insights into biological mechanisms contributing to DTC risk.

Genome-Wide Association Identifies Risk Pathways for SAPHO Syndrome

SAPHO syndrome is a rare chronic inflammatory disease which is characterized by the comprehensive manifestations of bone, joint, and skin. However, little is known about the pathogenesis of SAPHO syndrome. A genome-wide association study (GWAS) of 49 patients and 121 control subjects have primarily focused on identification of common genetic variants associated with SAPHO, the data were analyzed by classical multiple logistic regression. Later, GWAS findings were further validated using whole exome sequencing (WES) in 16 patients and 15 controls to identify potentially functional pathways involved in SAPHO pathogenesis. In general, 40588 SNPs in genomic regions were associated with P < 0.05 after filter process, only 9 SNPs meet the expected cut-off P-value, however, none of them had association with SAPHO syndrome based on published literatures. And then, 15 pathways were found involved in SAPHO pathogenesis, of them, 6 pathways including osteoclast differentiation, bacterial invasion of epithelial cells, et al., had strong association with skin, osteoarticular manifestations of SAPHO or inflammatory reaction based published research. This study identified aberrant osteoclast differentiation and other pathways were involved in SAPHO syndrome. This finding may give insight into the understanding of pathogenic genes of SAPHO and provide the basis for SAPHO research and treatment.

Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

BACKGROUND

Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism.

RESULTS

In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse.

CONCLUSIONS

The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies.

Small molecule modulation of the p75 neurotrophin receptor inhibits multiple amyloid beta-induced tau pathologies

Longitudinal preclinical and clinical studies suggest that Aβ drives neurite and synapse degeneration through an array of tau-dependent and independent mechanisms. The intracellular signaling networks regulated by the p75 neurotrophin receptor (p75NTR) substantially overlap with those linked to Aβ and to tau. Here we examine the hypothesis that modulation of p75NTR will suppress the generation of multiple potentially pathogenic tau species and related signaling to protect dendritic spines and processes from Aβ-induced injury. In neurons exposed to oligomeric Aβ in vitro and APP mutant mouse models, modulation of p75NTR signaling using the small-molecule LM11A-31 was found to inhibit Aβ-associated degeneration of neurites and spines; and tau phosphorylation, cleavage, oligomerization and missorting. In line with these effects on tau, LM11A-31 inhibited excess activation of Fyn kinase and its targets, tau and NMDA-NR2B, and decreased Rho kinase signaling changes and downstream aberrant cofilin phosphorylation. In vitro studies with pseudohyperphosphorylated tau and constitutively active RhoA revealed that LM11A-31 likely acts principally upstream of tau phosphorylation, and has effects preventing spine loss both up and downstream of RhoA activation. These findings support the hypothesis that modulation of p75NTR signaling inhibits a broad spectrum of Aβ-triggered, tau-related molecular pathology thereby contributing to synaptic resilience.

Identification of novel candidate autoantibodies in Alzheimer's disease

BACKGROUND AND PURPOSE

Accumulated failures in Alzheimer's disease (AD) clinical trials have highlighted an urgent need to identify additional biomarkers involved in AD. Recently, mounting evidence reported that autoantibodies are ubiquitous in human sera. However, it is unknown whether autoantibodies are upregulated in amyloid-tau biomarker-confirmed AD.

METHODS

A total of 40 subjects with mild dementia (Clinical Dementia Rating = 1) were stratified into AD (n = 16) and non-AD (n = 24) groups according to their cerebrospinal fluid levels of tau and Aβ₄₂ . Their sera were collected and analyzed using a microarray containing > 1600 potential human autoantigens. Autoantibodies that were present exclusively in the AD group were identified and selected using the penetrance-based fold change method with the following criteria: penetrance fold change_(AD)  ≥ 2, frequency_(AD)  ≥ 15% and frequency_(non-AD)  = 0%.

RESULTS

All controls and samples passed the quality control criteria and were further used for biomarker analysis. Six autoantibodies with elevated responses to the following autoantigens were found exclusively in the AD group: nucleosome assembly protein 1-like 3 (31.3%, 5/16 subjects) and microtubule-associated protein 4, pantothenic acid kinase 3, phosphoinositide-3-kinase regulatory subunit 1, protein tyrosine phosphatase type IVA member 1 and SRY (sex-determining region Y)-box 15 (all 18.8%, 3/16 subjects).

CONCLUSIONS

Although some identified autoantigens are linked to AD and cognitive dysfunction, the increased autoantibody levels have not been reported in AD. Autoantibodies may provide deeper insights into the pathogenesis of AD and serve as diagnostic biomarkers; their corresponding antigens can be further studied to assess their potential as therapeutic targets.

Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative

INTRODUCTION

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials.

METHODS

We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/).

RESULTS

(1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies.

DISCUSSION

ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

Mechanotransduction signaling in podocytes from fluid flow shear stress

Recently, we and others have found that hyperfiltration-associated increase in biomechanical forces, namely, tensile stress and fluid flow shear stress (FFSS), can directly and distinctly alter podocyte structure and function. The ultrafiltrate flow over the major processes and cell body generates FFSS to podocytes. Our previous work suggests that the cyclooxygenase-2 (COX-2)-PGE2-PGE2 receptor 2 (EP2) axis plays an important role in mechanoperception of FFSS in podocytes. To address mechanotransduction of the perceived stimulus through EP2, cultured podocytes were exposed to FFSS (2 dyn/cm2) for 2 h. Total RNA from cells at the end of FFSS treatment, 2-h post-FFSS, and 24-h post-FFSS was used for whole exon array analysis. Differentially regulated genes ( P < 0.01) were analyzed using bioinformatics tools Enrichr and Ingenuity Pathway Analysis to predict pathways/molecules. Candidate pathways were validated using Western blot analysis and then further confirmed to be resulting from a direct effect of PGE2 on podocytes. Results show that FFSS-induced mechanotransduction as well as exogenous PGE2 activate the Akt-GSK3β-β-catenin (Ser552) and MAPK/ERK but not the cAMP-PKA signal transduction cascades. These pathways are reportedly associated with FFSS-induced and EP2-mediated signaling in other epithelial cells as well. The current regimen for treating hyperfiltration-mediated injury largely depends on targeting the renin-angiotensin-aldosterone system. The present study identifies specific transduction mechanisms and provides novel information on the direct effect of FFSS on podocytes. These results suggest that targeting EP2-mediated signaling pathways holds therapeutic significance for delaying progression of chronic kidney disease secondary to hyperfiltration.