Evidence mapPaperPMID 42332537Full record

ArticleMedicine2026

Study on diagnostic genes and immune microenvironment disorder in comorbid atherosclerosis and Alzheimer disease.

Pengyun Ni, Bingbing Zhao, Hao Xv

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Pengyun NiDepartment of Science and Education, Baoji Traditional Chinese Medicine Hospital, Baoji, China.ORCID 0000-0001-7334-1162
Bingbing ZhaoEmergency Department, Baoji Traditional Chinese Medicine Hospital, Baoji, China.
Hao XvDepartment of Neurology, 987 Hospital PLA Joint Logistic Support Force, Baoji, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerosis (AS) and Alzheimer disease (AD) are globally prevalent chronic diseases with challenges of difficult early diagnosis and a lack of effective combined therapies. This study explored their shared molecular mechanisms, potential diagnostic biomarkers, and immune microenvironment disorders. Using AS dataset GSE100927 and AD dataset GSE97760, key differentially expressed genes (key DEGs) were identified via bioinformatics (differential expression analysis, protein-protein interaction network, machine learning). A risk prediction model was built and validated with receiver operating characteristic/area under the curve. Immune infiltration was compared between patient and control groups; miRNA-transcription factor-mRNA and key DEGs-chemical networks were predicted, and key DEGs-AS/AD causal relationships verified by Mendelian randomization. Venn analysis found 89 common DEGs (enriched in lipid metabolism, Wnt pathway, etc). Four key DEGs (early growth response 2 [EGR2], leukocyte-specific transcript 1 [LST1], membrane-spanning 4-domains subfamily A member 7 [MS4A7], and 2'-5'-oligoadenylate synthetase like [OASL]) were confirmed. The model had high accuracy (C-index = 0.982, area under the curve > 0.9). Mendelian randomization showed EGR2 was an AS risk/AD protective factor; LST1 an AS risk factor; MS4A7 an AD risk factor; no clear OASL-AD causality. EGR2, LST1, MS4A7, and OASL are novel diagnostic biomarkers and potential therapeutic targets for comorbid AS and AD.

Indexed as

Alzheimer DiseaseAtherosclerosisBiomarkersComputational BiologyEarly Growth Response Protein 2Gene Expression ProfilingHumansMachine LearningMembrane ProteinsMendelian Randomization AnalysisMicroRNAsProtein Interaction MapsBiomarkersEarly Growth Response Protein 2EGR2 protein, humanMembrane ProteinsMicroRNAsAlzheimer diseaseatherosclerosisdiagnostic genesimmune microenvironmentmachine learningMendelian randomization

Identifiers

PMID42332537
PMCPMC13286548

What Socratic holds

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Registered trials

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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 Socratic graph.