Open Access

Identification and immunological characterization of genes associated with ferroptosis in Alzheimer's disease and experimental demonstration

  • Authors:
    • Zhen Xiao
    • Rui Hu
    • Wan-Lu Liu
    • Xiao-Xuan He
    • Ming-You Dong
    • Zhong-Shi Huang
  • View Affiliations

  • Published online on: July 3, 2024     https://doi.org/10.3892/mmr.2024.13279
  • Article Number: 155
  • Copyright: © Xiao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

 The incidence of Alzheimer's disease (AD) is rising globally, yet its treatment and prediction of this condition remain challenging due to the complex pathophysiological mechanisms associated with it. Consequently, the objective of the present study was to analyze and characterize the molecular mechanisms underlying ferroptosis‑related genes (FEGs) in the pathogenesis of AD, as well as to construct a prognostic model. The findings will provide new insights for the future diagnosis and treatment of AD. First, the AD dataset GSE33000 from the Gene Expression Omnibus database and the FEGs from FerrDB were obtained. Next, unsupervised cluster analysis was used to obtain the FEGs that were most relevant to AD. Subsequently, enrichment analyses were performed on the FEGs to explore biological functions. Subsequently, the role of these genes in the immune microenvironment was elucidated through CIBERSORT. Then, the optimal machine learning was selected by comparing the performance of different machine learning models. To validate the prediction efficiency, the models were validated using nomograms, calibration curves, decision curve analysis and external datasets. Furthermore, the expression of FEGs between different groups was verified using reverse transcription quantitative PCR and western blot analysis. In AD, alterations in the expression of FEGs affect the aggregation and infiltration of certain immune cells. This indicated that the occurrence of AD is strongly associated with immune infiltration. Finally, the most appropriate machine learning models were selected, and AD diagnostic models and nomograms were built. The present study provided novel insights that enhance understanding with regard to the molecular mechanism of action of FEGs in AD. Moreover, the present study provided biomarkers that may facilitate the diagnosis of AD.
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September-2024
Volume 30 Issue 3

Print ISSN: 1791-2997
Online ISSN:1791-3004

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Spandidos Publications style
Xiao Z, Hu R, Liu W, He X, Dong M and Huang Z: Identification and immunological characterization of genes associated with ferroptosis in Alzheimer's disease and experimental demonstration. Mol Med Rep 30: 155, 2024.
APA
Xiao, Z., Hu, R., Liu, W., He, X., Dong, M., & Huang, Z. (2024). Identification and immunological characterization of genes associated with ferroptosis in Alzheimer's disease and experimental demonstration. Molecular Medicine Reports, 30, 155. https://doi.org/10.3892/mmr.2024.13279
MLA
Xiao, Z., Hu, R., Liu, W., He, X., Dong, M., Huang, Z."Identification and immunological characterization of genes associated with ferroptosis in Alzheimer's disease and experimental demonstration". Molecular Medicine Reports 30.3 (2024): 155.
Chicago
Xiao, Z., Hu, R., Liu, W., He, X., Dong, M., Huang, Z."Identification and immunological characterization of genes associated with ferroptosis in Alzheimer's disease and experimental demonstration". Molecular Medicine Reports 30, no. 3 (2024): 155. https://doi.org/10.3892/mmr.2024.13279