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Identification of Potential Risk Genes and the Immune Landscape Of G C A T T A C G G C A T genes Article Identification of Potential Risk Genes and the Immune Landscape of Idiopathic Pulmonary Arterial Hypertension via Microarray Gene Expression Dataset Reanalysis Jing Xu 1,†, Yicheng Yang 2,†, Yuejin Yang 1,* and Changming Xiong 2,* 1 Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China; [email protected] 2 Pulmonary Vascular Disease Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China; [email protected] * Correspondence: [email protected] (Y.Y.); [email protected] (C.X.) † These authors contributed equally to the work. Abstract: Gene dysfunction and immune cell infiltration play an essential role in the pathogenesis of idiopathic pulmonary arterial hypertension (IPAH). We aimed to investigate the immune landscape and novel differentially expressed genes (DEGs) of IPAH. In addition, potential druggable molecular targets for IPAH were also explored. In this study, the GSE117261 dataset was reanalyzed to explore the immune landscape and hub DEGs of IPAH. Lasso Cox regression analysis and receiver operating characteristic curve analysis were performed to detect the predictive value of IPAH. Additionally, the underlying drug targets for IPAH treatment were determined by drug–gene analysis. IPAH was significantly associated with the transforming growth factor-β (TGF-β) signaling pathway and Wnt signaling pathway as well as energetic metabolism dysfunction. We identified 31 upregulated and 39 Citation: Xu, J.; Yang, Y.; Yang, Y.; downregulated DEGs in IPAH patients. Six hub genes, namely, SAA1, CCL5, CXCR1, CXCR2, CCR1, Xiong, C. Identification of Potential and ADORA3, were related to IPAH pathogenesis regardless of sex differences. Prediction model Risk Genes and the Immune analysis showed that the area under the curve values of the hub DEGs except CXCR2 were all above Landscape of Idiopathic Pulmonary 0.9 for distinguishing IPAH patients. In addition, the relative proportions of 5 subtypes of immune Arterial Hypertension via Microarray + + cells, namely, CD8 T cells, CD4 memory resting T cells, γ delta T cells, M1 macrophages, and Gene Expression Dataset Reanalysis. resting mast cells, were significantly upregulated in the IPAH samples, while 6 subtypes of immune Genes 2021, 12, 125. https://doi.org/ + cells, namely, CD4 naive T cells, resting NK cells, monocytes, M0 macrophages, activated mast cells, 10.3390/genes12010125 and neutrophils, were downregulated. Additionally, a total of 17 intersecting drugs targeting 5 genes, Received: 20 November 2020 CCL5, CXCR1, CXCR2, CCR1, and ADORA3, were generated as potential druggable molecular targets Accepted: 14 January 2021 for IPAH. Our study revealed the underlying correlations between genes and immune cells in IPAH Published: 19 January 2021 and demonstrated for the first time that SAA1, CCL5, CXCR1, CCR1, and ADORA3 may be novel genetic targets for IPAH. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in Keywords: idiopathic pulmonary arterial hypertension; differentially expressed genes; immune cell published maps and institutional affil- infiltration; drug–gene interaction; bioinformatic iations. 1. Introduction Copyright: © 2021 by the authors. Pulmonary arterial hypertension (PAH), defined as a mean pulmonary artery pres- Licensee MDPI, Basel, Switzerland. sure ≥ 25 mmHg and pulmonary capillary wedge pressure ≤ 15 mmHg on resting right This article is an open access article heart catheterization, is a progressive disease that may lead to right heart failure and distributed under the terms and hemodynamic disorder [1]. Despite the use of targeted drugs in the clinic, PAH remains a conditions of the Creative Commons life-limiting disease. High pressure in the pulmonary artery is attributed to vasoconstric- Attribution (CC BY) license (https:// tion, pulmonary vascular remodeling and vascular inflammation, and current research creativecommons.org/licenses/by/ focuses on exploring more novel pathogenic mechanisms to reverse PAH; however, this 4.0/). Genes 2021, 12, 125. https://doi.org/10.3390/genes12010125 https://www.mdpi.com/journal/genes Genes 2021, 12, x FOR PEER REVIEW 2 of 17 heart catheterization, is a progressive disease that may lead to right heart failure and he- Genes 2021, 12, 125 2 of 16 modynamic disorder [1]. Despite the use of targeted drugs in the clinic, PAH remains a life-limiting disease. High pressure in the pulmonary artery is attributed to vasocon- striction, pulmonary vascular remodeling and vascular inflammation, and current re- researchsearch stillfocuses far fromon exploring clinical more practice novel [2 ].pathogenic Several genetic mechanisms targets to and reverse immune PAH; patternshow- of PAHever, have this beenresearch revealed still far [3 from–5]. Theclinical gene practice spectrum [2]. Several and immune genetic targets landscape and immune have gained greatpatterns attention of PAH for theirhave valuebeen revealed in reversing [3–5].PAH. The gene spectrum and immune landscape have gained great attention for their value in reversing PAH. PAH without a cause or associated condition is called idiopathic PAH (IPAH). Al- PAH without a cause or associated condition is called idiopathic PAH (IPAH). Alt- though genetic dysfunction is commonly regarded as the basic pathogenesis of IPAH, hough genetic dysfunction is commonly regarded as the basic pathogenesis of IPAH, sev- severaleral known known targeted targeted genes genes explain explain only 15 only–30% 15–30% of IPAH of case IPAHs. Moreover, cases. Moreover, although recent although recentstudies studies have havedemonstrated demonstrated that both that bone both morphogenetic bone morphogenetic protein (BMP) protein 9 [2] (BMP) and pros- 9 [2] and prostacyclintacyclin synthase synthase [6] genetic [6] genetic variants variants may also may be alsoinvolve bed involved in the pathogenesis in the pathogenesis of IPAH, of IPAH,they theystill fail still to fail fully to explain fully explain the cause the of cause IPAH of in IPAH patients, in patients, indicating indicating that the genetic that the basis genetic basisof IPAH of IPAH needs needs further further investigation. investigation. In addition, In addition, immune immune and inflammatory and inflammatory cells play cells playessential essential roles roles in the in thepathology pathology of IPAH of IPAH [2], and [2], studies and studies of the immune of the immune landscape landscape may be may bevaluable valuable for for developing developing novel novel approaches approaches to treat to treatIPAH. IPAH. BioinformaticBioinformatic research research has been been used used to to investigate investigate the the potential potential pathogenic pathogenic mecha- mecha- nismsnisms of of cardiovascular cardiovascular diseases diseases [ 7[7]]. In. In this this study, study, the the GSE117261 GSE117261dataset dataset profilesprofiles producedpro- byduced Stearman by Stearman et al. [8] et were al. [8] acquired were ac fromquired the from Gene the Expression Gene Expression Omnibus Omnib (GEO)us (GEO) database ( https://www.ncbi.nlm.nih.gov/geo/database (https://www.ncbi.nlm.nih.gov/geo/).). GSE117261 GSE117261 contains contains gene expressiongene expression data data from the completefrom the transcriptomics complete transcriptomics analysis analysis of IPAH of and IPAH control and control lung biopsy lung biopsy tissues. tissues To date,. To few date, few data-based studies have been performed to analyze the potential genes and im- data-based studies have been performed to analyze the potential genes and immune cell mune cell infiltration of IPAH. We analyzed the transcriptome differences and immune infiltrationlandscape of of IPAH. IPAH Wepatients analyzed as well the as transcriptome potential druggable differences molecular and immunetargets for landscape IPAH of IPAHtreatment, patients which as well may as pr potentialovide novel druggable insights for molecular disease development. targets for IPAH Figure treatment, 1 shows the which mayflowchart provide of novel the analysis insights procedure. for disease development. Figure1 shows the flowchart of the analysis procedure. Figure 1. The overview of the analysis procedure. GSE117261 dataset profiles were downloaded from the Gene Expression Omnibus database, and Gene Set Enrichment Analysis (GSEA) was conducted to investigate the potential biological pathways using the entire gene set. Thirty-one common upregulated differentially expressed genes (DEGs) and 39 common downregulated DEGs were identified. The DAVID database, ClueGo and Clupedia were used to perform GO and pathway enrichment of the DEGs, and STRING was used to construct the PPI network. The hub genes were detected by Cytoscape software. The immune landscape in the dataset samples was determined by the CIBERSORT algorithm. Lasso Cox regression analysis and ROC analysis were performed to build the IPAH prediction model. Additionally, drug–gene analysis was conducted to explore underlying drug targets for IPAH treatment. GSEA: Gene set enrichment analysis; DEGs: Differentially expressed genes; GO: Gene ontology; PPI: Protein–protein interaction; ROC: Receiver operating characteristic. Genes 2021, 12, 125 3 of 16 2. Materials and
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