Evidence map›Paper›PMID 41221472›Full record

ArticlePulmonary circulation2025

Identification and Validation of Potential Diagnostic Biomarkers for Pulmonary Arterial Hypertension Based on Gene Expression Profiling.

Huan Liu, Mengyu Wu, Guanming Qi, Feifei Ma, Yunshan Cao

Abstract read
In one paragraph

Article in Pulmonary circulation, 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. Article
  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

5 authors.

Huan LiuThe First Clinical Medical College Gansu University of Chinese Medicine (Gansu Provincial Hospital) Lanzhou Gansu China.ORCID https://orcid.org/0009-0006-9521-2533
Mengyu WuThe First Clinical Medical College Gansu University of Chinese Medicine (Gansu Provincial Hospital) Lanzhou Gansu China.ORCID https://orcid.org/0009-0008-2362-308X
Guanming QiInternal Medicine, Guthrie Lourdes Hospital Binghamton New York USA.
Feifei MaDepartment of Biochemistry and Immunology, Capital Center for Children's Health, Capital Medical University Capital Institute of Pediatrics Beijing China.ORCID https://orcid.org/0009-0000-9279-4263
Yunshan CaoHeart, Lung and Vessels Center, Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu Sichuan China.ORCID https://orcid.org/0000-0001-8463-1093

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary arterial hypertension (PAH) is a life-threatening condition characterized by elevated pulmonary vascular resistance. Despite recent advances, early diagnosis remains challenging due to nonspecific symptoms. By utilizing RNA sequencing (RNA-seq) data from the GEO database, we conducted bioinformatics analyses to identify potential diagnostic biomarkers. Differentially expressed genes (DEGs) were screened in blood from PAH patients, followed by functional enrichment and protein-protein interaction (PPI) network analyses. Thirteen overlapping DEGs were identified, which were enriched in erythrocyte development, heme biosynthesis, and chloride transport. Five hub genes (SLC4A1, AHSP, ALAS2, FECH, and CA1), exhibited strong diagnostic potential, with an area under the curve (AUC) ≥ 0.7 in training datasets (GSE38267, GSE22356). External validation using datasets GSE33463 and GSE117261 confirmed their efficacy in blood samples, although AHSP showed reduced performance in lung tissue. Experimental validation in hypoxic human pulmonary artery smooth muscle cells (hPASMCs) supported the bioinformatics findings. These results underscore SLC4A1, AHSP, ALAS2, FECH, and CA1 as promising noninvasive diagnostic biomarkers for PAH, linking transcriptional dysregulation to clinical application.

Indexed as

GEOPAHRNA seqROC curvesRT‐qPCR

Identifiers

PMID41221472
PMCPMC12598573

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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.