Evidence map›Paper›PMID 40370624›Full record

ArticleCardiology research2025

Dissecting Autophagy Gene Expression in Endothelial Cells of Pulmonary Arterial Hypertension at Single-Cell Resolution.

Chang Zhi Zhang, Qian Yu, Wei Jia Liu, Jing Han

Abstract read
In one paragraph

Article in Cardiology research, 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

4 authors.

Chang Zhi ZhangDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang 550001, China.
Qian YuDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang 550001, China.
Wei Jia LiuDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang 550001, China.
Jing HanDepartment of Respiratory and Critical Care Medicine, Guizhou Provincial People's Hospital, Guiyang 550001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Endothelial cell (EC) dysfunction is one of the pathogeneses of pulmonary arterial hypertension (PAH); autophagy is an important conserved mechanism for maintaining cellular homeostasis. However, to date, transcriptional signatures of autophagy-related genes during PAH are not well characterized. Methods: We analyzed the single-cell RNA sequencing (scRNA-seq) data and revealed the relationship between autophagy and PAH in EC from the perspective of differential expression, transcriptional signature typing, comparative analysis, pseudo-temporal changes of autophagy genes, and high dimensional weighted gene co-expression network analysis (hdWGCNA) networks of autophagy genes. Moreover, we established an Results: Single-cell data showed that ECs had three different subgroups, namely Endo-Nor (normal state), Endo-Mid (transition state), and Endo-PAH (PAH disease group). Functional enrichment analysis of differentially expressed genes between Endo-PAH and Endo-Nor showed that autophagy and phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathways were abnormal. Pseudo-temporal trajectory analysis showed that eight autophagy-related genes were involved in regulating PAH progression. Furthermore, the hdWGCNA network revealed six autophagy-related PAH progression genes. By comprehensively comparing different analysis methods, we identified Conclusion: This study dissected the expression signature of autophagy genes in PAH at single-cell resolution and identified DDIT4 as a potential biomarker.

Indexed as

AutophagyDdit4Endothelial cellhdWGCNAPAH

Identifiers

PMID40370624
PMCPMC12074683

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.