Evidence map›Paper›PMID 37600517›Full record

ArticleFrontiers in aging neuroscience2023

Identification of disulfidptosis-related genes and subgroups in Alzheimer's disease.

Shijia Ma, Dan Wang, Daojun Xie

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
8.2field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 47 citations in OpenAlex.

  1. The emerging roles of disulfidptosis in cancer.Apoptosis : an international journal on programmed cell death · 2026
    Review
  2. Review
  3. Disulfidptosis: molecular mechanisms and therapeutic targets.Signal transduction and targeted therapy · 2026
    Review
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  7. Programmed cell death: a promising management for Alzheimer's disease.Apoptosis : an international journal on programmed cell death · 2026
    Review
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  15. Disulfidptosis-related genes RPN1 inhibits the progression of hepatocellular carcinoma by regulating cell cycle, may be a new therapeutic targets.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 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

3 authors at 1 institution in 1 country.

Shijia MaThe First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China.
Dan WangEncephalopathy Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China.
Daojun XieEncephalopathy Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China.
Anhui University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alzheimer's disease (AD), a common neurological disorder, has no effective treatment due to its complex pathogenesis. Disulfidptosis, a newly discovered type of cell death, seems to be closely related to the occurrence of various diseases. In this study, through bioinformatics analysis, the expression and function of disulfidptosis-related genes (DRGs) in Alzheimer's disease were explored. Methods: Differential analysis was performed on the gene expression matrix of AD, and the intersection of differentially expressed genes and disulfidptosis-related genes in AD was obtained. Hub genes were further screened using multiple machine learning methods, and a predictive model was constructed. Finally, 97 AD samples were divided into two subgroups based on hub genes. Results: In this study, a total of 22 overlapping genes were identified, and 7 hub genes were further obtained through machine learning, including MYH9, IQGAP1, ACTN4, DSTN, ACTB, MYL6, and GYS1. Furthermore, the diagnostic capability was validated using external datasets and clinical samples. Based on these genes, a predictive model was constructed, with a large area under the curve (AUC = 0.8847), and the AUCs of the two external validation datasets were also higher than 0.7, indicating the high accuracy of the predictive model. Using unsupervised clustering based on hub genes, 97 AD samples were divided into Cluster1 ( Conclusion: A close association between disulfidptosis and Alzheimer's disease was discovered in this study, and a predictive model was established to assess the risk of disulfidptosis subtype in AD patients. This study provides new perspectives for exploring biomarkers and potential therapeutic targets for Alzheimer's disease.

Indexed as

Alzheimer’s diseasedisulfidptosismachine learningmolecular clustersprediction model

Identifiers

PMID37600517
PMCPMC10436325
OpenAlexW4385580962

What OpenQuestion 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 OpenQuestion graph.