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Genome-Wide Mendelian Randomization Identifies Ferroptosis-Related Drug Targets for Alzheimer's Disease.
Wang, Ying; Song, Xinhua; Wang, Rui; Xu, Xinzi; Du, Yaming; Chen, Guohua; Mei, Junhua.
Afiliación
  • Wang Y; Department of Neurology, Traditional Chinese and Western Medicine Hospital of Wuhan/Wuhan First Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Song X; Department of Neurology, Wuhan First Hospital, Hubei University of Chinese Medicine, Wuhan, China.
  • Wang R; Department of Neurology, Wuhan First Hospital, Hubei University of Chinese Medicine, Wuhan, China.
  • Xu X; Department of Neurology, Wuhan First Hospital, Hubei University of Chinese Medicine, Wuhan, China.
  • Du Y; Department of Neurology, Wuhan First Hospital, Hubei University of Chinese Medicine, Wuhan, China.
  • Chen G; Department of Neurology, Traditional Chinese and Western Medicine Hospital of Wuhan, Hubei University of Chinese Medicine, Wuhan, China.
  • Mei J; Department of Neurology, Traditional Chinese and Western Medicine Hospital of Wuhan, Hubei University of Chinese Medicine, Wuhan, China.
J Alzheimers Dis Rep ; 8(1): 1185-1197, 2024.
Article en En | MEDLINE | ID: mdl-39247875
ABSTRACT

Background:

Alzheimer's disease (AD) currently lacks effective disease-modifying treatments. Recent research suggests that ferroptosis could be a potential therapeutic target. Mendelian randomization (MR) is a widely used method for identifying novel therapeutic targets.

Objective:

Employ genetic information to evaluate the causal impact of ferroptosis-related genes on the risk of AD.

Methods:

564 ferroptosis-related genes were obtained from FerrDb. We derived genetic instrumental variables for these genes using four brain quantitative trait loci (QTL) and two blood QTL datasets. Summary-data-based Mendelian randomization (SMR) and two-sample MR methods were applied to estimate the causal effects of ferroptosis-related genes on AD. Using extern transcriptomic datasets and triple-transgenic mouse model of AD (3xTg-AD) to further validate the gene targets identified by the MR analysis.

Results:

We identified 17 potential AD risk gene targets from GTEx, 13 from PsychENCODE, and 22 from BrainMeta (SMR p < 0.05 and HEIDI test p > 0.05). Six overlapping ferroptosis-related genes associated with AD were identified, which could serve as potential therapeutic targets (PEX10, CDC25A, EGFR, DLD, LIG3, and TRIB3). Additionally, we further pinpointed risk genes or proteins at the blood tissue and pQTL levels. Notably, EGFR demonstrated significant dysregulation in the extern transcriptomic datasets and 3xTg-AD models.

Conclusions:

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the six druggable genes for AD treatment, especially for EGFR (validated by transcriptome and 3xTg-AD), which could be useful for prioritizing AD drug development in the field of ferroptosis.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: J Alzheimers Dis Rep Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: J Alzheimers Dis Rep Año: 2024 Tipo del documento: Article País de afiliación: China