Evidence map›Paper›PMID 40074694›Full record

ArticleJournal of cellular and molecular medicine2025

Decoding Alzheimer's Disease With Depression: Molecular Insights and Therapeutic Target.

Zekun Li, Hongmin Guo, Yihao Ge, Xiaohan Li, Fang Dong, Feng Zhang

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

6 authors.

Zekun LiDepartment of Rehabilitation Medicine, The Third Hospital of Hebei Medical University, Shijiazhuang, P. R. China.
Hongmin GuoDepartment of Rehabilitation Medicine, The Third Hospital of Hebei Medical University, Shijiazhuang, P. R. China.
Yihao GeDepartment of Rehabilitation Medicine, The Third Hospital of Hebei Medical University, Shijiazhuang, P. R. China.
Xiaohan LiDepartment of Rehabilitation Medicine, The Third Hospital of Hebei Medical University, Shijiazhuang, P. R. China.
Fang DongDepartment of Clinical Laboratory Medicine, The Third Hospital of Hebei Medical University, Shijiazhuang, P. R. China.
Feng ZhangDepartment of Rehabilitation Medicine, The Third Hospital of Hebei Medical University, Shijiazhuang, P. R. China.ORCID 0000-0002-7845-7970

Funding

National Natural Science Foundation of China 82072531
6 · The paper itself

Abstract

The purpose of this study was to recognise predictive biomarkers and explore the promising therapeutic targets of AD with depression. We confirmed a positive correlation between AD and depression through MR Analysis. Through WGCNA analysis, we identified 1569 genes containing two modules, which were most related to AD. In addition, 1629 depressive DEGs were also identified. In these genes, 84 genes were shared by both AD and depression, which were screened by the Degree algorithm, MCC algorithm, and four machine learning algorithms. Two genes (ITGB5 and SPCS1) were confirmed as predictive biomarkers with AUC > 0.7. Furthermore, the nomogram indicated that ITGB5 and SPCS1 are good biomarkers in diagnosing AD with depression. Four drugs targeted at ITGB5 were determined by the DGIdb website. In conclusion, we identified two predictive biomarkers for AD with depression, thus providing promising therapeutic targets for AD with depression.

Indexed as

Alzheimer DiseaseDepressionAlgorithmsBiomarkersComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansMachine LearningMolecular Targeted TherapyBiomarkersAlzheimer's diseasedepressionimmune cell infiltration analysismachine learning algorithmsmendelian randomizationpredictive biomarkers

Identifiers

PMID40074694
PMCPMC11903198

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.