A Bioinformatics Perspective on the Dysregulation of Ferroptosis and Ferroptosis-related Immune Cell Infiltration in Alzheimer's Disease

A review and analysis of key biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

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.

Ferroptosis Signaling Pathways: Alzheimer's Disease

The involvements of iron metabolism, lipid peroxidation, and oxidative stress in Alzheimer's disease (AD) development have recently received a lot of attention. We also observe that these pathogenic occurrences play a key role in regulating ferroptosis, a unique regulatory cell death that is iron-dependent, oxidative, and non-apoptotic. Iron is a crucial component that makes up a subunit of the oxidase responsible for lipid peroxidation. A family of non-heme iron enzymes known as lipoxygenases (LOXs) can cause ferroptosis by oxidising polyunsaturated fatty acids in cellular membranes (PUFAs). Toxic lipid hydroperoxides are produced in large part by the iron in LOX active sites. Deferoxamine and deferiprone, two iron chelators, could also treat ferroptosis by eliminating the crucial catalytic iron from LOXs. Phospholipids containing polyunsaturated fatty acids are the main substrates of lipid peroxidation in ferroptosis, which is favourably controlled by enzymes like ACSL4, LPCAT3, ALOXs, or POR. Selective stimulation of autophagic degradation pathways leads to an increase in iron accumulation and lipid peroxidation, which promotes ferroptosis. We highlighted recent advancements in our understanding of ferroptosis signaling routes in this study. One form of regulated necrotic cell death known as ferroptosis has been linked to a number of diseases, including cancer, neurological disorders, and ischemia/reperfusion injury. Cerebrospinal fluid (CSF) ferritin may be a good indicator of the amount of iron in the brain because it is the main protein that stores iron.

Research on ferroptosis as a therapeutic target for the treatment of neurodegenerative diseases

Ferroptosis is an iron- and lipid peroxidation (LPO)-mediated programmed cell death type. Recently, mounting evidence has indicated the involvement of ferroptosis in neurodegenerative diseases, especially in Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and so on. Treating ferroptosis presents opportunities as well as challenges for neurodegenerative diseases. This review provides a comprehensive overview of typical features of ferroptosis and the underlying mechanisms that contribute to its occurrence, as well as their implications in the pathogenesis and advancement of major neurodegenerative disorders. Meanwhile, we summarize the utilization of ferroptosis inhibition in both experimental and clinical approaches for the treatment of major neurodegenerative disorders. In addition, we specifically summarize recent advances in developing therapeutic means targeting ferroptosis in these diseases, which may guide future approaches for the effective management of these devastating medical conditions.

The inhibition of ORMDL3 prevents Alzheimer's disease through ferroptosis by PERK/ATF4/HSPA5 pathway

Alzheimer's disease (AD) is a neurodegenerative disease with high incidence and widespread attention. There is currently no clear clarification of the pathogenesis. However, ORMDL3 causes ferroptosis in AD, and the potential mechanisms remain unclear. So, this study explore the function of ORMDL3 on ferroptosis in AD and its potential regulatory mechanisms. APPswe/PS1dE9 mice and C57BL/6 mice were induced into the mice model. The murine microglial BV-2 cells also were induced into the vitro model. In serum samples of AD patients, ORMDL3 mRNA expression levels were upregulated. The serum ORMDL3 levels expression was positively related to the ADL score or MoCA score in AD patients. The serum ORMDL3 expression level was positively related to MMSE score or Hcy levels in AD patients. The mRNA expression of ORMDL3 in the hippocampal tissue of the mice model of AD was upregulated at one, four and eight months. The protein expression of ORMDL3 was upregulated in the mice model of AD. ORMDL3 promoted Alzheimer's disease, and increased oxidative response and ferroptosis in a model of AD. PERK/ATF4/HSPA5 pathway is one important signal pathway for the effects of ORMDL3 in a model of AD. Collectively, these data suggested that ORMDL3 promoted oxidative response and ferroptosis in a model of AD by the PERK/ATF4/HSPA5 pathway, which might be a novel target spot mechanism of ferroptosis in AD and may serve as a regulator of AD-induced ferroptosis.

Uncovering the Impact of Aggrephagy in the Development of Alzheimer's Disease: Insights Into Diagnostic and Therapeutic Approaches from Machine Learning Analysis

BACKGROUND

Alzheimer's disease (AD) stands as a widespread neurodegenerative disorder marked by the gradual onset of memory impairment, predominantly impacting the elderly. With projections indicating a substantial surge in AD diagnoses, exceeding 13.8 million individuals by 2050, there arises an urgent imperative to discern novel biomarkers for AD.

METHODS

To accomplish these objectives, we explored immune cell infiltration and the expression patterns of immune cells and immune function-related genes of AD patients. Furthermore, we utilized the consensus clustering method combined with aggrephagy-related genes (ARGs) for typing AD patients and categorized AD specimens into distinct clusters (C1, C2). A total of 272 candidate genes were meticulously identified through a combination of differential analysis and Weighted Gene Co-Expression Network Analysis (WGCNA). Subsequently, we applied three machine learning algorithms-namely random forest (RF), support vector machine (SVM), and generalized linear model (GLM)-to pinpoint a pathogenic signature comprising five genes associated with AD. To validate the predictive accuracy of these identified genes in discerning AD progression, we constructed nomograms.

RESULTS

Our analyses uncovered that cluster C2 exhibits a higher immune expression than C1. Based on the ROC(0.956). We identified five characteristic genes (PFKFB4, PDK3, KIAA0319L, CEBPD, and PHC2T) associated with AD immune cells and function. The nomograms constructed on the basis of these five diagnostic genes demonstrated effectiveness. In the validation group, the ROC values were found to be 0.760 and 0.838, respectively. These results validate the robustness and reliability of the diagnostic model, affirming its potential for accurate identification of AD.

CONCLUSION

Our findings not only contribute to a deeper understanding of the molecular mechanisms underlying AD but also offer valuable insights for drug development and clinical analysis. The limitation of our study is the limited sample size, and although AD-related genes were identified and some of the mechanisms elucidated, further experiments are needed to elucidate the more in-depth mechanisms of these characterized genes in the disease.