Evidence map›Paper›PMID 40419934›Full record

ArticleMedicine2025

Identification of key genes and diagnostic biomarkers for peripheral atherosclerosis: A multi-omics approach.

Luofei Huang, Han Li, Quanzhi Lin

Abstract read
In one paragraph

Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

Luofei HuangLiuzhou Municipal Liutie Central Hospital, Liuzhou, Guangxi, China.
Han LiDepartment of Internal Medicine, Liuzhou People's Hospital, Liuzhou, Guangxi, China.
Quanzhi LinDepartment of Internal Medicine, The First Affiliated Hospital of Guangxi University of Science and Technology, Liuzhou, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral atherosclerosis (PAS), characterized by lipid plaque accumulation in arterial walls, significantly increases cardiovascular risk. This study aimed to identify molecular biomarkers and elucidate underlying mechanisms of PAS progression. We analyzed 2 gene expression omnibus datasets (GSE28829, GSE100927) to identify differentially expressed genes (P < .05, |log2FC| ≥ 0.585). Functional enrichment (Gene Ontology/Kyoto Encyclopedia of Genes and Genomes) and Mendelian randomization analyses were performed using genome-wide association study and expression quantitative trait loci data. Six hub genes were validated through single-cell RNA sequencing and independent datasets. A diagnostic nomogram was developed and evaluated using calibration curves, decision curve analysis, and receiver operating characteristic metrics. Integrated analysis revealed 6 key PAS-associated genes (leukocyte immunoglobulin-like receptor B1, hematopoietic cell-specific lyn substrate 1, plasminogen activator urokinase, C-type lectin domain family 2 member B, phosphatidylinositol-4-phosphate 5-kinase type 1 beta, cofilin 2). The diagnostic model demonstrated exceptional accuracy, achieving area under the receiver operating characteristic curves of 1.0 (training) and 0.975 (validation). Mendelian randomization confirmed causal relationships, with cofilin 2 and phosphatidylinositol-4-phosphate 5-kinase type 1 beta showing protective effects (odds ratio 0.74-0.90), while C-type lectin domain family 2 member B, hematopoietic cell-specific lyn substrate 1, leukocyte immunoglobulin-like receptor B1, and plasminogen activator urokinase emerged as risk factors. This multi-omics study identifies novel molecular signatures of PAS and establishes a robust diagnostic tool. The findings advance our understanding of PAS pathogenesis and pave the way for personalized therapeutic strategies.

Indexed as

AtherosclerosisBiomarkersGene Expression ProfilingGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisMultiomicsNomogramsQuantitative Trait LociROC CurveBiomarkersdiagnostic biomarkerseQTLMendelian randomizationperipheral atherosclerosistranscriptomics

Identifiers

PMID40419934
PMCPMC12114065

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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.