Evidence map›Paper›PMID 39439987›Full record

ArticleFrontiers in molecular neuroscience2024

Exploring shared biomarkers and shared pathways in insomnia and atherosclerosis using integrated bioinformatics analysis.

Qichong Yang, Juncheng Liu, Tingting Zhang, Tingting Zhu, Siyu Yao, Rongzi Wang, Wenjuan Wang, Haliminai Dilimulati, Junbo Ge, Songtao An

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in molecular neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

10 authors.

Qichong YangCentral China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.
Juncheng LiuKey Laboratory of Cardiac Regenerative Medicine, National Health Commission, Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Zhengzhou, Henan, China.
Tingting ZhangCenter for Clinical Single-Cell Biomedicine, Henan Province People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Tingting ZhuDepartment of Cardiopulmonary Functions Test, Henan Province People's Hospital, People's Hospital of Henan University, Zhengzhou, Henan, China.
Siyu YaoCentral China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.
Rongzi WangCentral China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.
Wenjuan WangCentral China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.
Haliminai DilimulatiCentral China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.
Junbo GeDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China.
Songtao AnCentral China Fuwai Hospital of Zhengzhou University, Fuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Insomnia (ISM) is one of the non-traditional drivers of atherosclerosis (AS) and an important risk factor for AS-related cardiovascular disease. Our study aimed to explore the shared pathways and diagnostic biomarkers of ISM-related AS using integrated bioinformatics analysis. Methods: We download the datasets from the Gene Expression Omnibus database and the GeneCards database. Weighted gene co-expression network analysis and gene differential expression analysis were applied to screen the AS-related gene set. The shared genes of ISM and AS were obtained by intersecting with ISM-related genes. Subsequently, candidate diagnostic biomarkers were identified by constructing protein-protein interaction networks and machine learning algorithms, and a nomogram was constructed. Moreover, to explore potential mechanisms, a comprehensive analysis of shared genes was carried out, including enrichment analysis, protein interactions, immune cell infiltration, and single-cell sequencing analysis. Results: We successfully screened 61 genes shared by ISM and AS, of which 3 genes ( Conclusion: We constructed a diagnostic nomogram based on

Indexed as

atherosclerosisbiomarkersimmune cell infiltrationinflammatory responseinsomniasingle-cell sequencing analysis

Identifiers

PMID39439987
PMCPMC11493776

What OpenQuestion 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 OpenQuestion graph.