Evidence map›Paper›PMID 41516150›Full record

ArticleInternational journal of molecular sciences2025

A Combined Bioinformatics and Clinical Validation Study Identifies

Innokenty A Savin, Aleksandra V Sen'kova, Andrey V Markov, Olga S Kotova, Ilya S Shpagin, Lyubov A Shpagina, Valentin V Vlassov, Marina A Zenkova

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2025. 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

8 authors.

Innokenty A SavinInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, Lavrent'ev Avenue 8, 630090 Novosibirsk, Russia.ORCID 0000-0002-3032-858X
Aleksandra V Sen'kovaInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, Lavrent'ev Avenue 8, 630090 Novosibirsk, Russia.ORCID 0000-0001-5729-9910
Andrey V MarkovInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, Lavrent'ev Avenue 8, 630090 Novosibirsk, Russia.ORCID 0000-0001-7569-9555
Olga S KotovaDepartment of Hospital Therapy and Medical Rehabilitation, Novosibirsk State Medical University, Krasny Prospect 52, 630091 Novosibirsk, Russia.ORCID 0000-0003-0724-1539
Ilya S ShpaginDepartment of Hospital Therapy and Medical Rehabilitation, Novosibirsk State Medical University, Krasny Prospect 52, 630091 Novosibirsk, Russia.ORCID 0000-0002-3109-9811
Lyubov A ShpaginaDepartment of Hospital Therapy and Medical Rehabilitation, Novosibirsk State Medical University, Krasny Prospect 52, 630091 Novosibirsk, Russia.ORCID 0000-0003-0871-7551
Valentin V VlassovInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, Lavrent'ev Avenue 8, 630090 Novosibirsk, Russia.ORCID 0000-0003-2845-2992
Marina A ZenkovaInstitute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, Lavrent'ev Avenue 8, 630090 Novosibirsk, Russia.ORCID 0000-0003-4044-1049

Funding

Russian Science Foundation 19-74-30011the Russian state-funded project for ICBFM SB RAS 125012300659-6
6 · The paper itself

Abstract

Chronic obstructive pulmonary disease (COPD) is often diagnosed after significant lung damage has already occurred, highlighting a need for minimally invasive biomarkers for early detection of COPD development. This study aims to identify transcriptional biomarkers in peripheral blood mononuclear cells (PBMCs). A Weighted Gene Co-Expression Network Analysis (WGCNA) was performed on the GSE146560 transcriptomic dataset. Hub genes were cross-validated using independent transcriptomic data (GSE94916), topology analysis of a COPD-related protein-protein interaction (PPI) network, and a text-mining approach. The top candidate genes were validated using RT-qPCR in a clinical cohort, consisting of 28 COPD patients and 13 healthy volunteers, and their diagnostic value was evaluated using receiver operating characteristic (ROC) analysis. WGCNA identified four gene modules significantly correlated with COPD, the functional annotation of which revealed their enrichment in immune and tissue remodeling pathways. Further analysis of the PPI network topology structure and gene expression revealed a hub gene signature that was significantly upregulated in PBMCs of COPD patients, including

Indexed as

Computational BiologyLeukocytes, MononuclearProto-Oncogene Proteins c-mdm2Pulmonary Disease, Chronic ObstructiveTacrolimus Binding ProteinsAgedBiomarkersFemaleGene Expression ProfilingGene Regulatory NetworksHumansMaleMiddle AgedProtein Interaction MapsROC CurveTacrolimus Binding Protein 5BiomarkersMDM2 protein, humanProto-Oncogene Proteins c-mdm2Tacrolimus Binding Protein 5Tacrolimus Binding Proteinsbioinformaticsbiomarkerschronic obstructive pulmonary diseasedifferentially expressed genes

Identifiers

PMID41516150
PMCPMC12785598

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.