Evidence map›Paper›PMID 35875800›Full record

ArticleFrontiers in aging neuroscience2022

Hub Genes, Diagnostic Model, and Predicted Drugs Related to Iron Metabolism in Alzheimer's Disease.

Xuefeng Gu, Donglin Lai, Shuang Liu, Kaijie Chen, Peng Zhang, Bing Chen, Gang Huang, Xiaoqin Cheng, Changlian Lu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.4field-weighted citation impact, top 4% of its field
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

28 citing papers in PubMed, 37 citations in OpenAlex.

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  9. [Bioinformatics analysis of oxidative stress and immune infiltration in rheumatoid arthritis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025
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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

9 authors at 4 institutions in 1 country.

Xuefeng GuShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Donglin LaiShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Shuang LiuShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Kaijie ChenShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Peng ZhangShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Bing ChenDepartment of Neurosurgery, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Gang HuangShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Xiaoqin ChengDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China.
Changlian LuShanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China.
University of Shanghai for Science and Technology · CNShanghai University of Medicine and Health Sciences · CNGuangdong Medical College · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD), the most common neurodegenerative disease, remains unclear in terms of its underlying causative genes and effective therapeutic approaches. Meanwhile, abnormalities in iron metabolism have been demonstrated in patients and mouse models with AD. Therefore, this study sought to find hub genes based on iron metabolism that can influence the diagnosis and treatment of AD. First, gene expression profiles were downloaded from the GEO database, including non-demented (ND) controls and AD samples. Fourteen iron metabolism-related gene sets were downloaded from the MSigDB database, yielding 520 iron metabolism-related genes. The final nine hub genes associated with iron metabolism and AD were obtained by differential analysis and WGCNA in brain tissue samples from GSE132903. GO analysis revealed that these genes were mainly involved in two major biological processes, autophagy and iron metabolism. Through stepwise regression and logistic regression analyses, we selected four of these genes to construct a diagnostic model of AD. The model was validated in blood samples from GSE63061 and GSE85426, and the AUC values showed that the model had a relatively good diagnostic performance. In addition, the immune cell infiltration of the samples and the correlation of different immune factors with these hub genes were further explored. The results suggested that these genes may also play an important role in immunity to AD. Finally, eight drugs targeting these nine hub genes were retrieved from the DrugBank database, some of which were shown to be useful for the treatment of AD or other concomitant conditions, such as insomnia and agitation. In conclusion, this model is expected to guide the diagnosis of patients with AD by detecting the expression of several genes in the blood. These hub genes may also assist in understanding the development and drug treatment of AD.

Indexed as

Alzheimer's diseasediagnosticdrughub geneimmuneiron metabolism

Identifiers

PMID35875800
PMCPMC9300955
OpenAlexW4284880523

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.