Evidence map›Paper›PMID 39013959›Full record

ArticleScientific reports2024

CXCL9, IL2RB, and SPP1, potential diagnostic biomarkers in the co-morbidity pattern of atherosclerosis and non-alcoholic steatohepatitis.

Xize Wu, Changbin Yuan, Jiaxiang Pan, Yi Zhou, Xue Pan, Jian Kang, Lihong Ren, Lihong Gong, Yue Li

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  5. [SingleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
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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

9 authors.

Xize Wu *Liaoning University of Traditional Chinese Medicine, No. 79 Chongshan East Road, Huanggu District, Shenyang, 110847, Liaoning, China.
Changbin Yuan *Liaoning University of Traditional Chinese Medicine, No. 79 Chongshan East Road, Huanggu District, Shenyang, 110847, Liaoning, China.
Jiaxiang Pan *The Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, Liaoning, China.
Yi ZhouLiaoning University of Traditional Chinese Medicine, No. 79 Chongshan East Road, Huanggu District, Shenyang, 110847, Liaoning, China.
Xue PanLiaoning University of Traditional Chinese Medicine, No. 79 Chongshan East Road, Huanggu District, Shenyang, 110847, Liaoning, China.
Jian KangLiaoning University of Traditional Chinese Medicine, No. 79 Chongshan East Road, Huanggu District, Shenyang, 110847, Liaoning, China.
Lihong RenNantong Hospital of Traditional Chinese Medicine, Nantong Hospital Affiliated to Nanjing University of Chinese Medicine, Nantong, 226000, Jiangsu, China. 317791181@qq.com.
Lihong GongLiaoning University of Traditional Chinese Medicine, No. 79 Chongshan East Road, Huanggu District, Shenyang, 110847, Liaoning, China. Linda1795@sina.com.
Yue LiThe Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, 110032, Liaoning, China. med_liyue@163.com.

Funding

Science and Technology Research Project of Education Department of Liaoning Province No. L202048Youth Project of Basic Scientific Research Project of Education Department of Liaoning Province No. LJKQZ2021064
6 · The paper itself

Abstract

Non-alcoholic steatohepatitis (NASH) is a hepatocyte inflammation based on hepatocellular steatosis, yet there is no effective drug treatment. Atherosclerosis (AS) is caused by lipid deposition in the endothelium, which can lead to various cardiovascular diseases. NASH and AS share common risk factors, and NASH can also elevate the risk of AS, causing a higher morbidity and mortality rate for atherosclerotic heart disease. Therefore, timely detection and diagnosis of NASH and AS are particularly important. In this study, differential gene expression analysis and weighted gene co-expression network analysis were performed on the AS (GSE100927) and NASH (GSE89632) datasets to obtain common crosstalk genes, respectively. Then, candidate Hub genes were screened using four topological algorithms and externally validated in the GSE43292 and GSE63067 datasets to obtain Hub genes. Furthermore, immune infiltration analysis and gene set variation analysis were performed on the Hub genes to explore the underlying mechanisms. The DGIbd database was used to screen candidate drugs for AS and NASH. Finally, a NASH model was constructed using free fatty acid-induced human L02 cells, an AS model was constructed using lipopolysaccharide-induced HUVECs, and a co-morbidity model was constructed using L02 cells and HUVECs to verify Hub gene expression. The result showed that a total of 113 genes common to both AS and NASH were identified as crosstalk genes, and enrichment analysis indicated that these genes were mainly involved in the regulation of immune and metabolism-related pathways. 28 candidate Hub genes were screened according to four topological algorithms, and CXCL9, IL2RB, and SPP1 were identified as Hub genes after in vitro experiments and external dataset validation. The ROC curves and SVM modeling demonstrated the good diagnostic efficacy of these three Hub genes. In addition, the Hub genes are strongly associated with immune cell infiltration, especially macrophages and γ-δ T cell infiltration. Finally, five potential therapeutic drugs were identified. has-miR-185 and hsa-miR-335 were closely related to AS and NASH. This study demonstrates that CXCL9, IL2RB, and SPP1 may serve as potential biomarkers for the diagnosis of the co-morbidity patterns of AS and NASH and as potential targets for drug therapy.

Indexed as

AtherosclerosisBiomarkersChemokine CXCL9Non-alcoholic Fatty Liver DiseaseComorbidityGene Expression ProfilingGene Regulatory NetworksHumansHuman Umbilical Vein Endothelial CellsBiomarkersChemokine CXCL9BioinformaticsDifferentially expressed genesImmune infiltration microenvironmentWeighted gene co-expression network analysis

Identifiers

PMID39013959
PMCPMC11252365

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Registered trials

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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.