Identification of biomarkers related to copper metabolism in patients with pulmonary arterial hypertension

BMC Pulmonary Medicine

Research

Wei Zhang¹  Xin Chen²  Lei Wang³  Cong Li³  Jing Huang⁴ 

[1] Department of Emergency, The First Affiliated Hospital Xi’an Jiaotong University, 710061, Xi’an, Shaanxi, China;Department of Radiology, The Second Affiliated Hospital of Xi’an Jiaotong University (Xibei Hospital), 710004, Xi’an, Shaanxi, China;Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xi’an Jiaotong University (Xibei Hospital), 710004, Xi’an, Shaanxi, China;Department of Rheumatism and Immunology, The First Affiliated Hospital Xi’an Jiaotong University, 710061, Xi’an, Shaanxi, China;

关键词: Pulmonary arterial hypertension;    Copper metabolism-related genes;    Biomarkers;   

DOI  :  10.1186/s12890-023-02326-6

 received in 2022-09-09, accepted in 2023-01-13,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThe pathogenesis of pulmonary arterial hypertension (PAH) and associated biomarkers remain to be studied. Copper metabolism is an emerging metabolic research direction in many diseases, but its role in PAH is still unclear.MethodsPAH-related datasets were downloaded from the Gene Expression Omnibus database, and 2067 copper metabolism-related genes (CMGs) were obtained from the GeneCards database. Differential expression analysis and the Venn algorithm were used to acquire the differentially expressed CMGs (DE-CMGs). DE-CMGs were then used for the coexpression network construction to screen candidate key genes associated with PAH. Furthermore, the predictive performance of the model was verified by receiver operating characteristic (ROC) analysis, and genes with area under the curve (AUC) values greater than 0.8 were selected as diagnostic genes. Then support vector machine, least absolute shrinkage and selection operator regression, and Venn diagrams were applied to detect biomarkers. Moreover, gene set enrichment analysis was performed to explore the function of the biomarkers, and immune-related analyses were utilized to study the infiltration of immune cells. The drug-gene interaction database was used to predict potential therapeutic drugs for PAH using the biomarkers. Biomarkers expression in clinical samples was verified by real-time quantitative PCR.ResultsFour biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) were screened. The ROC analysis showed that the 4 biomarkers performed well (AUCs > 0.7). The high expression groups for the 4 biomarkers were enriched in protein activity-related pathways including protein export, spliceosome and proteasome. Furthermore, 8 immune cell types were significantly different between the two groups, including naive B cells, memory B cells, and resting memory CD4 T cells. Afterward, a gene-drug network was constructed. This network illustrated that STREPTOZOCIN, IBUPROFEN, and CELECOXIB were shared by the PTGER4 and DDIT3. Finally, the results of RT-qPCR in clinical samples further confirmed the results of the public database for the expression of NFKBIA and OSM.ConclusionIn conclusion, four biomarkers (DDIT3, NFKBIA, OSM, and PTGER4) with considerable diagnostic values were identified, and a gene-drug network was further constructed. The results of this study may have significant implications for the development of new diagnostic biomarkers and actionable targets to expand treatment options for PAH patients.

【 授权许可】

CC BY   
© The Author(s) 2023

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