Identification of feature genes and pathways for Alzheimer's disease via WGCNA and LASSO regression

Characteristics and Transcriptomic Analysis of Cholinergic Neurons Derived from Induced Pluripotent Stem Cells with APP Mutation in Alzheimer's Disease

Background

The cholinergic hypothesis is one of the main theories that describe the pathogenesis of Alzheimer's disease (AD). Cholinergic neurons degenerate early and are severely damaged in AD. Despite extensive research, the causes of cholinergic neuron damage and the underlying molecular changes remain unclear.

Objective

This study aimed to explore the characteristics and transcriptomic changes in cholinergic neurons derived from human induced pluripotent stem cells (iPSCs) with APP mutation.

Methods

Peripheral blood mononuclear cells from patients with AD and healthy individuals were reprogrammed into iPSCs. The iPSCs were differentiated into cholinergic neurons. Cholinergic neurons were stained, neurotoxically tested, and electrophysiologically and transcriptomically analyzed.

Results

The iPSCs-derived cholinergic neurons from a patient with AD carrying a mutation in APP displayed enhanced susceptibility to Aβ1-42-induced neurotoxicity, characterized by severe neurotoxic effects, such as cell body coagulation and neurite fragmentation. Cholinergic neurons exhibited electrophysiological impairments and neuronal death after 21 days of culture in the AD group. Transcriptome analysis disclosed 883 differentially expressed genes (DEGs, 420 upregulated and 463 downregulated) participating in several signaling pathways implicated in AD pathogenesis. To assess the reliability of RNA sequencing, the expression of 16 target DEGs was validated using qPCR. Finally, the expression of the 8 core genes in different cell types of brain was analyzed by the AlzData database.

Conclusions

In this study, iPSCs-derived cholinergic neurons from AD patients with APP mutations exhibit characteristics reminiscent of neurodegenerative disease. Transcriptome analysis revealed the corresponding DEGs and pathways, providing potential biomarkers and therapeutic targets for advancing AD research.

Dissecting gene expression networks in the developing hippocampus through the lens of NEIL3 depletion

Gene regulation in the hippocampus is fundamental for its development, synaptic plasticity, memory formation, and adaptability. Comparisons of gene expression among different developmental stages, distinct cell types, and specific experimental conditions have identified differentially expressed genes contributing to the organization and functionality of hippocampal circuits. The NEIL3 DNA glycosylase, one of the DNA repair enzymes, plays an important role in hippocampal maturation and neuron functionality by shaping transcription. While differential gene expression (DGE) analysis has identified key genes involved, broader gene expression patterns crucial for high-order hippocampal functions remain uncharted. By utilizing the weighted gene co-expression network analysis (WGCNA), we mapped gene expression networks in immature (p8-neonatal) and mature (3 m-adult) hippocampal circuits in wild-type and NEIL3-deficient mice. Our study unveiled intricate gene network structures underlying hippocampal maturation, delineated modules of co-expressed genes, and pinpointed highly interconnected hub genes specific to the maturity of hippocampal subregions. We investigated variations within distinct gene network modules following NEIL3 depletion, uncovering NEIL3-targeted hub genes that influence module connectivity and specificity. By integrating WGCNA with DGE, we delve deeper into the NEIL3-dependent molecular intricacies of hippocampal maturation. This study provides a comprehensive systems-level analysis for assessing the potential correlation between gene connectivity and functional connectivity within the hippocampal network, thus shaping hippocampal function throughout development.

Study of molecular patterns associated with ferroptosis in Parkinson's disease and its immune signature

Parkinson's disease is the second most common neurodegenerative disease in the world. We downloaded data on Parkinson's disease and Ferroptosis-related genes from the GEO and FerrDb databases. We used WCGAN and Random Forest algorithm to screen out five Parkinson's disease ferroptosis-related hub genes. Two genes were identified for the first time as possibly playing a role in Braak staging progression. Unsupervised clustering analysis based on hub genes yielded ferroptosis isoforms, and immune infiltration analysis indicated that these isoforms are associated with immune cells and may represent different immune patterns. FRHGs scores were obtained to quantify the level of ferroptosis modifications in each individual. In addition, differences in interleukin expression were found between the two ferroptosis subtypes. The biological functions involved in the hub gene are analyzed. The ceRNA regulatory network of hub genes was mapped. The disease classification diagnosis model and risk prediction model were also constructed by applying hub genes based on logistic regression. Multiple external datasets validated the hub gene and classification diagnostic model with some accuracy. This study explored hub genes associated with ferroptosis in Parkinson's disease and their molecular patterns and immune signatures to provide new ideas for finding new targets for intervention and predictive biomarkers.

Identification and validation of key genes associated with atrial fibrillation in the elderly

Background

Atrial fibrillation (AF) is the most common cardiac arrhythmia and significantly increases the risk of stroke and heart failure (HF), contributing to a higher mortality rate. Increasing age is a major risk factor for AF; however, the mechanisms of how aging contributes to the occurrence and progression of AF remain unclear. This study conducted weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes and determine their potential associations with aging-related AF.

Materials and methods

WGCNA was performed using the AF dataset GSE2240 obtained from the Gene Expression Omnibus, which contained data from atrial myocardium in cardiac patients with permanent AF or sinus rhythm (SR). Hub genes were identified in clinical samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were also performed.

Results

Green and pink were the most critical modules associated with AF, from which nine hub genes, PTGDS, COLQ, ASTN2, VASH1, RCAN1, AMIGO2, RBP1, MFAP4, and ALDH1A1, were hypothesized to play key roles in the AF pathophysiology in elderly and seven of them have high diagnostic value. Functional enrichment analysis demonstrated that the green module was associated with the calcium, cyclic adenosine monophosphate (cAMP), and peroxisome proliferator-activated receptors (PPAR) signaling pathways, and the pink module may be associated with the transforming growth factor beta (TGF-β) signaling pathway in myocardial fibrosis.

Conclusion

We identified nine genes that may play crucial roles in the pathophysiological mechanism of aging-related AF, among which six genes were associated with AF for the first time. This study provided novel insights into the impact of aging on the occurrence and progression of AF, and identified biomarkers and potential therapeutic targets for AF.