Analysis of human brain RNA-seq data reveals combined effects of 4 types of RNA modifications and 18 types of programmed cell death on Alzheimer's disease

被引:0
|
作者
Ye, Ke [1 ]
Han, Xinyu [1 ]
Tian, Mengjie [1 ]
Liu, Lulu [1 ]
Gao, Xu [1 ,2 ,3 ,5 ]
Xia, Qing [4 ]
Wang, Dayong [1 ,2 ,3 ,5 ]
机构
[1] Harbin Med Univ, Sch Basic Med Sci, Dept Biochem & Mol Biol, Harbin 150081, Heilongjiang, Peoples R China
[2] Harbin Med Univ, Key Lab Heilongjiang Prov Genet Modified Anim, Harbin 150081, Heilongjiang, Peoples R China
[3] Heilongjiang Acad Med Sci, Translat Med Res & Cooperat Ctr Northern China, Harbin 150081, Heilongjiang, Peoples R China
[4] Beijing Univ Chinese Med, Dongzhimen Hosp, Beijing 100700, Peoples R China
[5] Harbin Med Univ, Key Lab Preservat Human Genet Resources & Dis Cont, Minist Educ, Harbin 150081, Heilongjiang, Peoples R China
基金
黑龙江省自然科学基金;
关键词
Alzheimer's disease; RNA modification; Programmed cell death; Synapse; Parahippocampal gyrus; Machine learning; A-BETA; AUTOSIS; HIPPOCAMPAL; MECHANISMS; MICROGLIA; DEMENTIA; NEURONS; ANOIKIS; TAU;
D O I
10.1186/s12967-025-06324-6
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
BackgroundRNA modification plays a critical role in Alzheimer's disease (AD) by modulating the expression and function of AD-related genes, thereby affecting AD occurrence and progression. Programmed cell death is closely related to neuronal death and associated with neuronal loss and cognitive function changes in AD. However, the mechanism of their joint action on AD remains unknown and requires further exploration.MethodsWe used the MSBB RNA-seq dataset to analyze the correlation between RNA modification, programmed cell death, and AD. We used combined studies of RNA modification and programmed cell death to distinguish subgroups of patients, and the results highlight the strong correlation between RNA modification-related programmed cell death and AD. A weighted gene co-expression network was constructed, and the pivotal roles of programmed cell death genes in key modules were identified. Finally, by combining unsupervised consensus clustering, gene co-expression networks, and machine learning algorithms, an RNA modification-related programmed cell death network was constructed, and the pivotal roles of programmed cell death genes in key modules were identified. An RNA modification-related programmed cell death risk score was calculated to predict the occurrence of AD.ResultsRPCD-related genes classified patients into subgroups with distinct clinical characteristics. Nineteen key genes were identified and an RPCD risk score was constructed based on the key genes. This score can be used for the diagnosis of AD and the assessment of disease progression in patients. The diagnostic efficacy of the RPCD risk score and the key genes was validated in the ROSMAP, GEO, and ADNI datasets.ConclusionThis study uncovered that RNA modification-related PCD is of significance for AD progression and early prediction, providing insights from a new perspective for the study of disease mechanisms in AD.
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页数:24
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