Evidence map›Paper›PMID 39027505›Full record

ArticleHeliyon2024

Identification and experimental validation of m7G-related molecular subtypes, immune signature, and feature genes in Alzheimer's disease.

Piaopiao Lian, Xing Cai, Cailin Wang, Heng Zhai, Ke Liu, Xiaoman Yang, Yi Wu, Zhuoran Ma, Xuebing Cao, Yan Xu

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Piaopiao LianDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xing CaiDepartment of Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Cailin WangDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Heng ZhaiDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ke LiuDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiaoman YangDepartment of Neurology, Renmin Hospital of Wuhan University, Wuhan, China.
Yi WuDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhuoran MaDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xuebing CaoDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yan XuDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored. Methods: The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses. Results: Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes ( Conclusion: To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.

Indexed as

Alzheimer's diseaseBioinformatic analysisCharacteristic genesN7-methylguanosine

Identifiers

PMID39027505
PMCPMC11255592

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.