Integration of transcriptomics, proteomics, phosphoproteomics analysis for characterization of pulmonary arterial hypertension in Chinese people

Integration of transcriptomics, proteomics, phosphoproteomics analysis for characterization of pulmonary arterial hypertension in Chinese people | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integration of transcriptomics, proteomics, phosphoproteomics analysis for characterization of pulmonary arterial hypertension in Chinese people tianya liu, Siqi Zhou, Rui Wang, Xiaomei Xu, Fang Gao, Zu Jie, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3929686/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Pulmonary arterial hypertension (PAH), a fatal disease, is characterized by pulmonary vascular remodeling and vascular resistance. However, the molecular mechanisms underlying the pathogenesis of PAH remained to be incompletely understood. Methods RNA-seq, 4D Lable-free proteomics and phosphoproteomics were used to detect the levels of mRNA, proteins, and phosphoproteins in lung tissues from PAH patients, respectively. Parallel reaction monitoring (PRM) was carried out to verify the expression of the differentially expressed proteins. Results Totally, 967 differentially expressed genes (|log2FoldChange|>1 and p 1 and p < 0.05) in lung tissues of PAH patients as compared with the control group. Integrated analysis of the three omic measures revealed that the biological processes involving inflammation, ion channel and metabolism were closely associated with PAH. Several signaling pathways, such as ferroptosis, HIF-1, PI3K-AKT, and Rap1 might be related to the development of PAH. Conclusions This study combined multi-omics characteristic profiling to find out the changed genes or proteins that contributed to a detailed pathogenic of PAH. It would have the benefit of looking for the novel and effective treatment targets and therapeutic drugs to PAH patients. Pulmonary arterial hypertension RNA-seq proteomic phosphoproteomic pulmonary vascular remodeling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background PAH, is a progressive and cureless disease, characterized with elevated pulmonary arterial pressure and vascular resistance, with subsequent ventricular dilatation and heart failures[ 1 ]. The incidence of PAH is about 15 to 50 persons per million worldwide according to the data of the multiple international regions[ 2 ]. Many factors, such as germline mutation, inflammation, dysfunction of pulmonary arterial endothelial cells and metabolic derangements contribute to the pathogenesis of the disease [ 3 ]. Once the biological disturbances occur, progressive vasoconstriction and remodeling of the pulmonary arteries ensues, causing abnormal proliferation and apoptosis of the smooth muscle cells. Currently, there are urgent needs for the development of novel therapeutic targets and effective therapeutic agents of PAH [ 4 ]. The current clinical drugs treating PAH include: calcium channel blockers, anti-coagulants, diuretics and oxygen. These drugs are limited to the symptomatic treatment improvement and could not solve the fundamental problems [ 5 ]. The classical drugs such as endothelin receptor antagonist, soluble guanylate cyclase agonist, phosphodiesterase type 5 inhibitor, prostaglandin agonists or analogs, could alleviated the clinical symptoms and improved the prognosis. Due to the complicated pathogenesis of PAH, it is unsatisfactory for the effect of those drugs in reversing the pulmonary vascular remodeling [ 6 ]. The patient survival of advanced PAH remains poor at five years despite the treatment advances, and the expensive operation of lung transplantation is an important option for those patients [ 7 ]. Thus, in-depth understanding of the underlying mechanisms are extremely urgent for PAH. Omics are a new approach for whole gene analysis in a specific cell type or tissue. Transcriptomics focuses on the gene expression at the RNA level and offers the genome-wide information, while proteomics is the large-scale analysis of the entire protein, and phosphoproteomics analysis is to detect the phosphorylation of proteins in complex biological process [ 8 – 10 ]. Multi-omics techniques integrating these individual omics are very useful in detecting various biological processes. In this study, RNA-seq or 4D Lable-free approach for proteomics and phosphoproteomics was performed in lung tissues of PAH patients to determine the molecular characteristics of PAH. Dysregulated levels of genes, proteins and protein phosphorylation were identified. We further combined the results from these omics analyses to unveil the pathogenesis of PAH. Materials and methods Tissue samples Lung tissues were obtained from the Wuxi People's Hospital and the Affiliated Hospital of Xuzhou Medical University, and all patients provided their written informed consent. The study was approved by the institutional research ethics committee and the experimental methods were performed in accordance with the relevant guidelines and regulations. Lung tissues of PAH group were isolated from the lungs of patients receiving lung transoplantation, while the control group were undergoing chest surgery. PAH diagnosis has been diagnosed in every patient by clinical method, and the isolated tissue samples were frozen in liquid nitrogen for subsequent experiment. RNA isolation and RNA-seq Transcriptome sequencing was performed at Genechem Biotechnology Co., Ltd. (Shanghai, China) following the standard experimental procedures as described [ 11 ]. RNA was extracted from tissues using NEBNext® Ultra II Directional RNA Library Prep Kit (NEB, USA) and the total amount of 1 µg RNA per sample was used for the RNA sample preparations. Then RNA was fragmented and purified to construct libraries. PCR products were purified and library quality was assessed on the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA) according to the manufacturer’s instructions. RNA-seq based transcriptome profiling was performed by high-throughput Illumina NovaSeq 6000 sequencing platform (Illumina Technologies, CA, USA) and 150 bp paired-end reads were generated. RNA-seq analyses Reference genome and gene model annotation files were downloaded from genome website directly. FeatureCounts was used to count the reads numbers mapped to each gene and for quantification of gene expression level. Differential expression analysis between the two groups was performed using the DESeq2 software which provided statistical routines in digital gene expression data based on the negative binomial distribution. The resulting p-values were adjusted by the Benjamini and Hochberg’s approach for controlling the false discovery rate. Genes with an adjusted p-value < 0.05 found by DESeq2 were assigned as differentially expressed. The corrected p-value of 0.05 and | log2 (fold change) |were set as the threshold for significantly differential expression and cluster Profiler R package used for the enrichment analysis. Protein extraction and preparation SDT buffer was added to the tissues and the lysate was homogenized by MP Automated Homogenizer (6.0M/S, 30s, twice). The homogenate was sonicated and boiled for 10 min. After centrifuged at 14000g for 15 min, the supernatant was filtered with 0.22 µm filters. The protein was quantified by the BCA Protein Assay Kit (P0012, Beyotime, China) and using SDS-PAGE electrophoresis for quality control. Filter-aided sample preparation (FASP) is a universal method for peptide segment and the peptide was desalted by C18 column [ 12 ]. Similarly, the labeled peptides were combined and desalted using C18 Cartridge and the mixture was subjected to High-Select™ Fe-NTA Phosphopeptide Enrichment Kit (Thermo Fisher scientific, A32992). The eluent were dried down via vacuum centrifugation at 45℃ and then dissolved in 0.1% formic acid buffer. 4D Label‑free quantitative proteomics and phosphorylation proteomics 4D Label-free quantitative proteomics and phosphorylation proteomics were performed by Genechem Biotechnology Co., Ltd. (Shanghai, China). 4D Label-free technology could quantitatively determine protein levels without complex labeling or processing of samples [ 13 ]. Before mass spectrometry (MS) identification, the samples were separated using the NanoElute system (Bruker, Bremen, Germany) with a nanoscale flow rate. Then the samples were analyzed by the timsTOF Pro (Bruker, Bremen, Germany) with PASEF mode. The duration of analysis was 90 min (for phosphorylation analysis was 120 min) and the detection method was positive ion. The mass range of mother ion was 100 to 1700m/z, and the ion mobility was start from 0.75 V to 1.4 V⋅s/cm 2 . The ion ramp time was 100ms, and the tilization rate was 100%. In addition, the capillary voltage was 1500V and the drying gas speed was 3L/min, the temperature was 180°C. The mass charge ratio of peptides and peptide fragments were collected according to the following methods: 10 MS/MS scans (total cycle time 1.16sec), the charge range was 0 to 5, the active exclusion was 0.5 min, the scheduling target intensity was10000, intensity threshold was 2500, and the Normalized Collision Energy was 20 to 59eV. Protein identification and quantification analysis Raw files were processed by MaxQuant 1.6.17.0 using the standard settings against Human protein database (Uniprot_HomoSapiens_20337_20220308_swissprot). An initial search was set at 10 ppm and searched followed an enzymatic cleavage rule of Trypsin/P, which allowed maximal two missed cleavage sites and the mass tolerance of 40ppm for fragment ions. Carbamidomethylation of cysteines was defined as fixed modification, and oxidation of methionines as well as N-terminal acetylation was defined as variable modification for searching. The cutoff of global false discovery rate (FDR) for peptide or protein identification was set at 0.01. Protein aboundance was calculated on the basis of the normalized spectral protein intensity (LFQ intensity). The significant differentially expressed proteins up-regulated more than 2 fold or down-regulated less than 0.5 fold and p-value < 0.05 were screened by UniProt database ( https://www.uniprot.org/ ) for bioinformatics analysis. As previously reported, we only analyzed the protein phosphorylation changes that were higher or lower than the fold change of itself in proteomics [ 14 ]. Gene Ontology (GO) annotation To determine the biological and functional properties of the identified proteins, we employed the hypergeometric test to perform GO enrichment analysis. Firstly, the target protein sequences were aligned to the database using NCBI BLAST+ (ncbi-blast-2.3.0+) on the Linux server and kept the top ten sequences (E-value was less than or equal to 0.001). Using Blast2GO to select the GO term (database version: go_20190701.obo) of the sequence with the top Bit-Score and complete the elementary annotation from GO terms for target protein by Blast2GO Command Line. In order to improve the efficiency of annotation, InterProScan were used to search EBI database for conserved motif matching the protein and added the functional information [ 15 ]. ANNEX was performed for the further annotation information and established the connections between different GO categories to improve the accuracy of annotation. Fisher’s exact test was used to enrich GO terms by comparing the number of differentially expressed proteins and total proteins correlated to GO terms. Kyoto encyclopedia of genes and genomes (KEGG) pathway annotation Using KEGG Orthology And Links Annotation software (version number: V2.2) for KEGG pathway annotation on the target protein and classified the sequence by KEGG Orthology (KO) with the information about the pathways automatically. Fisher’s exact test was used to enrich KEGG terms by comparing the number of differentially expressed proteins and total proteins correlated to KEGG terms. Protein validation by PRM PRM was performed to determine the levels of those differentially expressed proteins to verify the proteomic analysis based on the 4D label-free LC-MS/MS. The total protein extraction, enzyme digestion, and desalination were the same as described in the previous sample preparation. Two micrograms of peptide mixture were loaded onto the C18-reversed phase analytical column (Thermo Fisher Scientific, Acclaim PepMap RSLC 50um × 15cm, nano viper, P/N164943, USA) in buffer A (0.1% Formic acid) and separated with a linear gradient of buffer B (80% acetonitrile and 0.1% formic acid) at a flow rate of 300 nl/min. The liquid gradient was as follows: 1 ~ 3% B liquid for 0 min ~ 5 min;, 3%~28% B liquid for 6 min ~ 45min, 28% ~ 38% B liquid for 46 min ~ 50min, 38%~100% B liquid for 51min ~ 55min, 100% B liquid for 56 min ~ 60min. Peptide fragmentation and targeted PRM MS were performed using a Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, USA) that was coupled to Easy nLC (Thermo Fisher Scientific, USA) for 60 min in the positive ion mode. Data were acquired using the most abundant precursor ions setting the survey scan ranging from 350 to 1800 m/z for high-energy collisional dissociation (HCD). Survey scans were obtained at a resolution of 60000 m/z with AGC target of 3E6 and maximum injection time of 50 ms. MS2 scans were at a resolution of 30000 m/z for HCD spectra with AGC target of 2E5 and maximum injection time of 50 ms, isolation width was 1.6 m/z. Only the ions with the charge state between 2 ~ 6 and a minimum intensity of 8E3 were selected for fragmentation. Dynamic exclusion for selected ions was 30s and normalized collision energy was 27 eV. The MS RAW file were analyzed by SpectroDive software and database version was uniprot_homo_20230312_20423_9606_swiss_prot. Statistical analysis was processed with SPSS software and all the results were analyzed using Student’s t test with expressed as means ± standard error. Significant differences were judged by the p-value < 0.05. Results Screening the differential charateristics in PAH The samples from the lung tissues of PAH (n = 8) or control patients (n = 8) were subjected to high-throughput sequencing, including RNAseq, 4D Label-free technology to identify changes of mRNA, protein and phosphoprotein, respectively. Differentially expressed genes (DEGs) analysis revealed the mRNA levels of 967 genes were significantly different (|log2FoldChange|>1 and p < 0.05), 424 genes was downregulated and 543 genes was upregulated at least twofold change (Fig. 1 A and Table S1 ). Because proteins represent the actual functional molecules, 4D Label‑free technology was conducted to investigate the differences of proteomic levels between the two groups. 4049 proteins were identified and 764 differentially expressed proteins (DEPs) were observed after data filtering (|log2FoldChange|>1 and p < 0.05). Among those proteins, 467 proteins were increased in PAH, while 297 proteins were reduced above twofold change (Fig. 1 B and Table S2 ). In addition, the top-10 upregulated and downregulated proteins of each group were exhibited in detailed heatmaps (Fig. S1 ). Those DEPs indicated the dysregulated proteins expression in the progression of PAH. Meanwhile, we subsequently identified 2197 proteins in phosphoproteome analysis, including 314 downregulated phosphoproteins and 97 upregulated phosphoproteins, respectively (Fig. 1 C and Table S3 ). The top-10 most altered phosphorylated protein and phosphorylation site were displayed in supplementary materials (Fig. S2 ). Then we integrated the analysis between transcriptome and proteomics. There were 54 genes with overlapped alterations at both mRNA and proteins levels, including 48 proteins with the similar trend with mRNA expression, and 6 proteins with the opposite tendency (Fig. 1 D). Overall, different characteristics could be observed through multi-omics analysis between the two groups. Enolase 1 (ENO1), a protein necessary for pulmonary artery smooth muscle cells (PASMC) proliferation and de-differentiation, were significantly higher compared to the controls as reported [ 16 ]. In addition, we confirmed the altered expression of several other proteins implicated in PAH pathobiology, such as caveolin-1(CAV1) and chloride intracellular channel protein 1(CLIC1) according to the previous study [ 17 – 19 ]. All the marked changes indicated successful materials establishment from PAH patients. Furthermore, the alterations of some proteins like alkaline phosphatase, tissue-nonspecific isozyme (ALPL), membrane metalloendopeptidase (MME), versican (VCAN) have not been reported in PAH previously. Transcriptome profiling between PAH and control patients Transcriptomes is one of the most important regulation modes in cell. To identify the possible novel molecular factors or pathways associated with PAH, GO and KEGG enrichment were performed to analyze DEGs using twofold chang. It was determined three sub parts in GO enrichment analysis: biological process (BP), molecular function (MF), and cellular component (CC). The DEGs were mainly enriched in endocrine process, acute inflammatory response, regulation of chemokine production, electron transport chain, tissue remodeling, and NADH dehydrogenase activity (Fig. 2 A). KEGG pathway analyses revealed that DEGs were highly enriched in oxidative phosphorylation, HIF-1 signaling pathway, ferroptosis, and p53 signaling pathway in PAH (Fig. 2 B). In particular, the most enriched BP of the DEGs was related to the energy and metabolism, including electron transport chain, oxidative phosphorylation, and purine ribonucleoside triphosphate metabolic process. For the downregulated DEGs, the enriched BP included cell-cell adhesion via plasma-membrane adhesion molecules, and neutrophil activation involved in immune response. For MF, the most significantly enriched GO terms for upregulated and downregulated DEGs were extracellular matrix (ECM) structural constituent and cytokine receptor activity, respectively. In CC, extracellular matrix and secretory granule membrane were the most significantly enriched GO terms in the up- and downregulated DEGs, respectively (Fig. S3 A-C). The top three most KEGG pathways among the upregulated DEGs were oxidative phosphorylation, p53 signaling pathway and cell cycle, and the downregulated DEGs were cytokine-cytokine receptor interaction, cAMP signaling pathway and cell adhesion molecules, respectively (Fig. S3 D). To gain insight into the function of the detected genes, Gene Set Enrichment Analysis (GSEA) was conducted. Based on the absolute values of normalized enrichment score (NES) > 1, nominal p value < 0.05 and FDR < 0.25, the signaling pathways of electron transfer activity (GO: 0009055, NES = 1.95, p = 0.008, FDR = 0.24), oxidative phosphorylation (GO: 000619, NES = 1.80, p = 0.018, FDR = 0.18) were significantly enriched (Fig. 2 C & 2 D). The detailed information of genes contributed to the enrichment items were revealed in the supplementary materials (Table S4 ). In summary, the DEGs were primarily enriched in inflammation, oxidative stress, metabolism and several other important signaling pathways. Proteomic profiling between PAH and control patients To understand the proteomic profiling or pathways affected during the progression of PAH, 764 DEPs were subjected to GO and KEGG. Proteins with |log2FoldChange|>1 were subjected to the analysis. BP terms enrichment analysis revealed the dysfunction in extracellular matrix organization, angiogenesis, electron transport chain and metabolism disorder, like glutamine, fructose and other substance metabolism. It was noticed that the term of electron transport chain was found both in the results of transcriptomics and proteomics, which mean this biological process were important in the progression of PAH. For MF, the most significantly enriched GO terms for DEPs were “binding” and extracellular matrix structural constituent and CC terms revealed thatlysosomal lumen, adherens junction were enriched (Fig. 3 A). Similarly, the top 20 of KEGG pathways analyses suggested the involvement of ECM-receptor interaction, lysosome, PI3K-AKT signaling pathway and Rap1 signaling pathway in the advancing of diseases (Fig. 3 B). More significantly changed terms were enriched in metabolic pathways, including metabolisms of amino acids, purine, glutathione and glycolysis. Some key proteins were involved in regulation disease development via differently pathways. The detailed information of protein contributing to each enrichment items was exhibited in the supplementary materials (Table S5). In summary, DEPs alterations of signaling pathways, metabolism and dysfunctional cellular processes might be involved in the pathogenesis of PAH. Functional analysis of phosphorylated DEPs between PAH and control patients Protein phosphorylation plays a central role in regulating protein structure, function and closely connects with human health. Next, GO and KEGG analysis were performed to analyze the 411 differentially phosphorylated proteins depending on the significance of p-values and |log2FoldChange|>1. The proteins of which the fold changes of phosphorylated form less than the total change of its total form were excluded. GO enrichment analysis showed that the differentially phosphorylated proteins were most enriched in three reference sets (Fig. 4 A). Those phosphorylated proteins participated in various cellular process, such as epithelial cell proliferation involved in lung morphogenesis, negative regulation of potassium ion transmembrane transporter activity, cellular response to cytokine stimulus, response to calcium ion, notch signaling pathway in BP. For MF, the top significantly enriched GO terms were “binding” and structural constituent of cytoskeleton, voltage-gated ion channel activity and potassium channel activity. Cell-cell junction, stress fiber were the enriched CC terms for phosphoproteins. Meanwhile, KEGG enrichment analysis revealed that most significant enriched terms were autophagy, HIF-1 signaling pathway, tight junction and leukocyte transendothelial migration (Fig. 4 B). Descriptions of the enriched proteins entry were available in the supplementary materials (Table S6). Among these pathways, HIF-1 signaling pathway was observed both in the KEGG analysis of transcriptomics and proteomics, which implicated that this pathway might play a critical role in pathogenic progress of PAH. In summary, phosphorylated DEPs were involved in the regulation of several cellular processes, such as ion channel and metabolism, which were tightly associated with PAH. Verification of the key proteins To further verify that the results from the proteomics data, PRM was carried out to determine the expression of the selected DEPs, including the proteins from the significantly enriched GO term or KEGG pathways and the proteins with significant alterations. Similar to proteomics studies previously, there were some discrepancies between the two approaches [ 20 , 21 ]. The relative quantitative expression of each selected protein showed that 25 proteins had not significant difference as observed in the 4D Lable-free approach and PRM analyses, while five proteins did not demonstrate significant changes (Fig. 5 ). As shown in Fig. 5 , the fold change of VCAN, MME, CLIC1 and other proteins were verified to be significant in the two methods (Table S7). Discussion Current drug therapy could only alleviated the clinical symptoms, while could prevent the progression of PAH, thus lung transplantation would be needed for patients with advanced PAH. Currently, we identified the novel dysregulated genes or proteins in the lung tissues of PAH using RNA-seq analyses and 4D Label‑free technology. The mRNA, protein and phosphorylated proteins profiles of lung tissues were established to investigate the complex pathogenesis of PAH. Furthermore, we integrated multi-omics characteristics to establish the PAH gene expression PAH profiles, and observed some novel alterations of proteins or signaling pathways that have not been found previously for the further pathophysiology and potential therapeutics in PAH. Based on differential expression genes analysis, we totally identified 543 upregulated and 424 downregulated genes, and those DEGs revealed some key genes involved in PAH. Some genes exhibited similar changes consistent with previous research [ 16 , 22 ]. GO analyses of DEGs in PAH showed that most of the enriched genes were related to inflammatory response and oxidative stress, tissue remodeling, for example, cell chemotaxis, acute inflammatory response, and positive regulation of cell motility. Oxidative phosphorylation and HIF-1 signaling pathway were the top significantly regulated KEGG pathway identified in PAH group. Enrichment analyse of GSEA showed that oxidative phosphorylation were involved in PAH, those results was consistent with evidence that oxidative stress was critical in the pathophysiology of PAH, antioxidant treatment might be the potential therapeutic target for the treatment of PAH [ 23 , 24 ]. Of note, many similarities to human cancers in the pulmonary vasculature, up-regulated or down-regulated gene group also be of interest for PAH, including neutrophil activation involved in immune response, chemokine receptor activity, and calcium ion homeostasis had been implicated as the cause or consequence of PAH [ 25 , 26 ]. Ferroptosis was a newly identified iron-dependent form of regulated cell death, playing critical roles in various organ injuries [ 27 ]. Our data indicated that DEGs in ferroptosis and p53 signaling were correlated with PAH. Oxidative phosphorylation and other factors might influence pulmonary vascular remodeling from RNA-seq analysis of PAH. We further performed 4D label-free quantitative proteomics method to screen proteins expression in PAH. It was well known that proteins, which were expressed by genes after transcription, were the executors and deterministic players in life process, so the changes of protein urgently need to know. Our proteomics results revealed a total of 764 proteins were significantly changed more than two-fold change, of which 467 upregulated proteins and 297 downregulated proteins. Most of the altered proteins were enriched in the regulation of autophagy, angiogenesis, metabolic process, ion channel, and acute inflammatory response. GO analysis suggested a pronounced contributory role of angiogenesis, electron transport chain, ion channel and metabolism. KEGG pathway analysis showed the significant enrichment in apoptosis, PI3K-Akt and Rap1 signaling pathway, metabolic pathways and secondary metabolities biosynthesis pathway. According to previous study, inhibition of PI3K-Akt pathways could attenuate the development of PAH, as potential therapeutic target for PAH [ 28 ]. However, the roles of some altered pathways like Rap1 signaling in PAH were still unveiled. In addition, we pay attention to that the relevant representative protein, such as caveolin-2 (CAV2), chloride intracellular channel 5 (CLIC5), were enriched in many vital pathways. CAV2 belongs to caveolin gene family and widely expressed in most cell types, regulates many key processes, such as cell migration and metastasis, angiogenesis, and drug resistance [ 29 , 30 ]. It have been reported that loss-of-function of CAV1 could affect pulmonary artery endothelial cells proliferation and migration, as well as reduce cytoskeletal stress fibers, leading to neointima formation and aggravated PAH [ 31 , 32 ]. The results of proteomics and PRM showed CAV2 were significantly changed, but there are still a lot of unknown field for its role in PAH. Chloride channel, CLIC1, CLIC4 are excessively expressed in PAH and contribute to mitochondrial dysfunction and energy metabolism in endothelium [ 33 , 34 ]. CLIC5 encodes actin-based cytoskeletal protein, and has been thought to play significant roles in human cancers [ 35 ]. Enrichment result suggested that CLIC5 might participate in obsolete peroxidase reaction and was associated with PAH. In order to acquire in-depth study of the pathogenesis of PAH, we integrated the results of transcriptomics and proteomic and found 54 genes with overlapped alterations. Transcriptomics could clarify the mechanism of functional disorders; proteomics could be used to predict relevant target genes [ 36 ]. Integrated analysis of the results of transcriptomics and proteomics provides a new vision for the pathogenesis of PAH. We noted that the representative protein desmin (DES) and MME had the same tendency in mRNA and protein level. DES is a muscle-specific protein and a primary subunit of the intermediate filament in cardiac, skeletal and smooth muscles [ 37 ]. DES abnormal expression might break the balance in preserving the homeostasis of pulmonary artery smooth muscle cell [ 38 ]. Illustrating the role of those proteins would help to elucidate the pathogenesis of PAH. Besides the proteomic analysis, we conducted phosphoproteomic profiling in the lung tissues of PAH, and observed 97 upregulated phosphoproteins and 314 downregluated phosphoproteins. The observe in proteins’ phosphorylation suggested a direct involvement of protein phosphorylation in the development of PAH. Results from the selected GO terms contained epithelial cell proliferation, potassium ion transmembrane transporter activity, notch signaling pathway, including DES, epidermal growth factor receptor (EGFR), VCAN, and NEDD4L. Those proteins were associated with cellular proliferation or progression and the regulation of a range of pulmonary disease [ 39 , 40 ]. The enrichment analysis consistent with the development of PAH characterized by dysregulated proliferation of all vascular cell types, including endothelial, smooth muscle, and fibroblasts [ 41 ]. Meanwhile, KEGG pathways analysis of phosphoproteins also uncovered an intriguing finding: autophagy, apoptosis, and HIF-1 signaling pathway. The representative proteins included mammalian target of rapamycin (mTOR), ENO1, DES, EGFR, and integrin Subunit Beta 4 (ITGB4). mTOR is a highly important protein kinase that responds to the cellular and extracellular signals, and its phosphorylation has been reported to contribute to the proliferation, migration, and gene regulation of pulmonary artery smooth muscle and endothelial cells, thus involved in pulmonary vascular remodeling and continuous vasoconstriction [ 42 , 43 ]. However, the relationship between ENO1 and PAH is poorly understand, thus exploring the potential role of ENO1 might be of great interest. Overall, the altered phosphoproteins were generally directly correlated with the development of PAH. There are some limitations in this study. The samples from the PAH patients probably have taken clinical drugs that may influence the expression of some proteins. Nevertheless, precious studies on human samples are difficult to acquire. Our results had shown a great deal of consistency with the changed proteins consistent with the previous study, demonstrating that our samples have clinical significance [ 44 , 45 ]. However, the alterations of some key PAH-related proteins, such as bone morphogenetic protein receptor type II (BMPR2), STAT3 and phosphor-STAT3, were not observed [ 46 ]. It may be due to their lower expression or high standard of fold change compared for the identified proteins in our study. Additionally, an integrated analysis of mRNA and protein level could provide more complicated and comprehensive information to better understand protein regulation [ 47 ]. Moreover, phosphoproteomic integrated the information of protein modifications to obtain a deep understanding in the pathogenesis of PAH. In future, multi-omics and biological method might help us to identify detailed origins of key proteins and pathways in PAH. Conclusion In summary, we performed a comprehensive analysis of the molecular mechanism of PAH through the integrated analysis with transcriptomics, proteomic, phosphoproteomic analysis of lung tissues in PAH patients. Our multi-omics analyses provided an overview of dysregulated genes expression in lung tissues of PAH patients, thus contributed to a better understanding of the molecular pathogenesis. Further studies in the changes in the mRNA, proteins, and phosphoproteins in future studies might benefit in searching the potential therapeutic targets and interventional strategies for PAH. Abbreviations PAH: Pulmonary arterial hypertension GO: Gene Ontology KEGG: Kyoto encyclopedia of genes and genomes PRM: Parallel reaction monitoring ENO1: Enolase 1 PASMC: Pulmonary artery smooth muscle cells CAV1: Caveolin-1 CLIC1: Chloride intracellular channel protein 1 MME: Membrane metalloendopeptidase VCAN: Versican DES: Desmin TAGLN: Transgelin CHI3L1: Chitinase-3-like protein 1 Declarations Acknowledgements We thank all the participants in this study. We would lie to thank the anonymous reviewers for their valuable comments and suggestions, which helped improve the quality of our mamuscirpt. Authors’ contributions LTY, WZP conceived and designed the overall study. ZSQ and WR conducted the bioinformatics analysis. ZSQ analyzed data for the key proteins screening. LTY, WR, XXM and DF recruited patients. LTY drafted the manuscript. WZP was the guarantor of the study. All authors approved the fnal draft for publication Funding This work was supported by the National Natural Science Foundation of China (Grant No. 82270059 and 81703493), The Natural Science Foundation of Jiangsu Province (Grant No. BK20221222 and BK20170258), The China Postdoctoral Science Foundation‑funded projects (Grant No. 2019M661943), The Foundation of Xuzhou Science and Technology Department (Grant No. KC21154). Availability of data and materials The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request. Ethics approval and consent to participate The study was approved by the Medical Institutional Ethics Committee of the Affiliated Hospital of Xuzhou Medical University and Wuxi People's Hospital. Patients all signed the written informed consents before taking part into our study. 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Paulin D, Li Z: Desmin: a major intermediate filament protein essential for the structural integrity and function of muscle. Exp Cell Res 2004, 301:1-7. Agnetti G, Herrmann H, Cohen S: New roles for desmin in the maintenance of muscle homeostasis. FEBS J 2022, 289:2755-2770. Shan CG, Wang H, Lin T, Liu D, Wen L, Chen ZJ, Zhen JJ, Lai MY, Zhang L, Zou X, et al: A non-small cell lung cancer (NSCLC) patient with leptomeningeal metastasis harboring rare epidermal growth factor receptor (EGFR) mutations G719S and L861Q benefited from doubling dosage of osimertinib: a case report. Ann Palliat Med 2021, 10:5897-5901. Li M, Sun G, Wang P, Wang W, Cao K, Song C, Sun Y, Zhang Y, Zhang N: Research progress of Nedd4L in cardiovascular diseases. Cell Death Discov 2022, 8:206. Rafikova O, Al Ghouleh I, Rafikov R: Focus on Early Events: Pathogenesis of Pulmonary Arterial Hypertension Development. Antioxid Redox Signal 2019, 31:933-953. 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Additional Declarations No competing interests reported. Supplementary Files Fig.S1proteintop10.tif Fig.S2phosphorylatedproteinstop10.tif Fig.S3.tif SupplementaryInformationandTbaleS7.docx TableS1.967differentiallyexpressedgenesinPAHcomparedwithcontrolgroup.xls TableS2.764differentialexpressedproteinsinPAHcomparedwithcontrolgroup.xlsx TableS3.411differentialexpressedphosphorylatedproteinscomparedwithcontrolgroup.xlsx TableS4.ThedetailedinformationofthesignificantGOandKEGGpathwaysofdifferentialexpressedgenesinPAH1.xlsx TableS4.ThedetailedinformationofthesignificantGOandKEGGpathwaysofdifferentialexpressedgenesinPAH.xlsx TableS5.BiologicalfunctionsofproteinsdifferentiallyexpressedinPAH.xlsx TableS6.BiologicalfunctionsofphosphorylatedproteinsdifferentiallyexpressedinPAH.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3929686","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271421493,"identity":"88816de6-36e6-42c7-ab87-311665886bd6","order_by":0,"name":"tianya liu","email":"","orcid":"","institution":"the Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"tianya","middleName":"","lastName":"liu","suffix":""},{"id":271421494,"identity":"6a259fa2-a729-4135-9302-198d4d0fbe8c","order_by":1,"name":"Siqi Zhou","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Siqi","middleName":"","lastName":"Zhou","suffix":""},{"id":271421495,"identity":"957ab7cb-52c3-4406-a085-14b12ebff1a1","order_by":2,"name":"Rui Wang","email":"","orcid":"","institution":"the Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Wang","suffix":""},{"id":271421496,"identity":"978205aa-cef5-46cc-92eb-ea1eed174356","order_by":3,"name":"Xiaomei Xu","email":"","orcid":"","institution":"the Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaomei","middleName":"","lastName":"Xu","suffix":""},{"id":271421497,"identity":"5d350a4b-23e7-42ba-99a0-d94ff34d7a63","order_by":4,"name":"Fang Gao","email":"","orcid":"","institution":"the Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Gao","suffix":""},{"id":271421498,"identity":"04247ba8-0a82-4002-a1bc-d12abfd387f7","order_by":5,"name":"Zu Jie","email":"","orcid":"","institution":"the Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zu","middleName":"","lastName":"Jie","suffix":""},{"id":271421499,"identity":"da3513f7-389e-4a6a-bd88-018b97cf5033","order_by":6,"name":"Zhiping Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYDACCQglx8befIAkLQbGfDzHEkjTkjhPIkeBOB3ys3sPf3jb9ie9jSGHgeFHxTbCWhjnnEuTnHPGILeN4ewBxp4ztwlrYZbIMWPmqQBqYexLYGZsI0ILm0SO8WceA4N0NmYeA+K08EjkGEgDbUlgYyNWi4REHsgvxoZtPGwJB4nyi/yMXFCIycnLz3988MGPCiK0AJ0GRmBwgBj1qFpGwSgYBaNgFGAFAGi4NKjmb1h6AAAAAElFTkSuQmCC","orcid":"","institution":"the Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhiping","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-02-05 03:14:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3929686/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3929686/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50924770,"identity":"15d5ab8e-d7ac-420c-9617-9c01885d0729","added_by":"auto","created_at":"2024-02-09 17:05:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":169454,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical analysis of the differentially expressed genes, proteins andphosphoproteins. (A) Volcano plot of all differentially expressed genes in the group of control (n=8) or the group of pulmonary hypertension (n=8). The x-axis displays the log2 fold change value, and y-axis corresponds to the mean expression of log10 (p value). Each gene is represented by a single dot, the red dots represent upregulated expressed genes (p \u0026lt; 0.05, log2FoldChange \u0026gt; 1), whereas green dots represent downregulated genes (p \u0026lt; 0.05, log2FoldChange \u0026lt; -1). (B) Volcano plot of differentially expressed proteins quantified by proteomic analysis in the group of control or the group of PAH. The red dots or green dots represent differentially expressed proteins (p \u0026lt; 0.05, |log2FoldChange| \u0026gt; 1). (C) Volcano plot of differentially expressed phosphoproteins quantified by phosphoproteomic analysis in the group of control or the group of PAH. The red dots or green dots represent differentially expressed phosphoproteins (p \u0026lt; 0.05, |log2FoldChange| \u0026gt; 1). (D) Clustering map of the intersection of changed genes or proteins in the group of control or the group of PAH. The red and blue boxes represent the upregulated and downregulated proteins, respectively.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/485040c3005d452400b03f84.png"},{"id":50924783,"identity":"52145e69-d0b2-4dbe-bcf6-da21375d95b3","added_by":"auto","created_at":"2024-02-09 17:05:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":466138,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional classification based on pathway enrichment analysis of differently genes in lung tissues of patients with pulmonary hypertension as compared with that of control. (A) Go functional classification of DEGs using Fisher’s exact test for biological process (BP), molecular function (MF), and cellular component (CC) categories (|log2FoldChange|\u0026gt; 1, p\u0026lt;0.01). (B) The KEGG pathway classification of DEGs using Fisher’s exact test (|log2FoldChange|\u0026gt; 1, p\u0026lt;0.05). The vertical axis represents KEGG pathways in each category, and the numbers beside the bars are enrichment factors, which represent the significance and reliability of proteins enriched in this item. The reliability of the proteins in an item was enhanced when the value increased. The horizontal axis shows the -log10 (p-value) of each item. (C) GSEA showed the enrichment in electron transfer activity (NES=1.95, p=0.008, FDR=0.24). (D) GSEA showed enrichment in oxidative phosphorylation (GO: 000619, NES=1.80, p=0.018, FDR=0.18). Comparison of samples, NES, nominal p-value, and FDR were determined by the GSEA software, and were indicated within each enrichment plot.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/8243befcdadb7867caa5cacd.png"},{"id":50924781,"identity":"750643f4-1698-4122-a7ee-632e5bc44b04","added_by":"auto","created_at":"2024-02-09 17:05:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":339606,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional classification based on the pathway enrichment analysis of differently proteins in the pulmonary hypertension group compared with the control group. (A) The respective enriched GO terms in the biological process, molecular function and cellular compartment (p\u0026lt;0.01). (B) KEGG pathways enrichment analysis for significantly altered proteins (p\u0026lt;0.05). The horizontal axis shows the significance of each pathway in the form of -log10 (p-value). Numbers beside the bars are enrichment factors of each enriched pathway.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/7edfe4d0c8fad5ef13a2e4a3.png"},{"id":50924780,"identity":"401e40f7-7d40-4497-906b-a15d1d6345c5","added_by":"auto","created_at":"2024-02-09 17:05:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":368964,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional classification based on the pathway enrichment analysis of differently phosphoproteins in pulmonary hypertension group compared with the control group. (A) GO functional classification in differentially expressed phosphoproteins (p\u0026lt;0.01). (B) Rich factor of significant KEGG pathways (p\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/3fcf8059363f985c6f57280f.png"},{"id":50924778,"identity":"48a02939-7965-4cd5-ab0b-9526568fb126","added_by":"auto","created_at":"2024-02-09 17:05:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":278768,"visible":true,"origin":"","legend":"\u003cp\u003eValidation of candidate protein expression with Parallel reaction monitoring analysis in pulmonary hypertension group relative to the control (Con). VACN, CFL1, MME, TAGLN, DES, CLIC5, PRKAR1A, PLEC, DMTN, TAGLN2, ALPL, ENO1, CHI3L1, CLIC1, HSP90AA1, EIF2A, PDLIM2, SCN7A, AHNAK, LAMB3, SORBS3, ITGB4, HDAC1, EGFR, CAV2 were detected in the lung tissues from PAH patients. N=8, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/c1a9d781940bc628885db272.png"},{"id":51338046,"identity":"4d160242-d445-4423-9529-099200f8cf16","added_by":"auto","created_at":"2024-02-19 20:25:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1317120,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/86dba8be-bb90-4934-a340-8f3fce40eb9c.pdf"},{"id":50924771,"identity":"13f8cc6e-dfb9-4f83-8038-b8c0cac85ac6","added_by":"auto","created_at":"2024-02-09 17:05:34","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1564984,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S1proteintop10.tif","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/6334b8f51ea4613c70c87589.tif"},{"id":50924773,"identity":"1515197f-bc7d-44d4-9980-d28eb629095d","added_by":"auto","created_at":"2024-02-09 17:05:34","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1966004,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S2phosphorylatedproteinstop10.tif","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/5902f16edc632972c89ab0ec.tif"},{"id":50924772,"identity":"f0e4e3d7-d9e8-4608-9c7b-1a2d1f1361e8","added_by":"auto","created_at":"2024-02-09 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17:05:34","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":24843,"visible":true,"origin":"","legend":"","description":"","filename":"TableS6.BiologicalfunctionsofphosphorylatedproteinsdifferentiallyexpressedinPAH.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3929686/v1/ec4f69b2472448dd9155bd4f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integration of transcriptomics, proteomics, phosphoproteomics analysis for characterization of pulmonary arterial hypertension in Chinese people","fulltext":[{"header":"Background","content":"\u003cp\u003ePAH, is a progressive and cureless disease, characterized with elevated pulmonary arterial pressure and vascular resistance, with subsequent ventricular dilatation and heart failures[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The incidence of PAH is about 15 to 50 persons per million worldwide according to the data of the multiple international regions[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Many factors, such as germline mutation, inflammation, dysfunction of pulmonary arterial endothelial cells and metabolic derangements contribute to the pathogenesis of the disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Once the biological disturbances occur, progressive vasoconstriction and remodeling of the pulmonary arteries ensues, causing abnormal proliferation and apoptosis of the smooth muscle cells. Currently, there are urgent needs for the development of novel therapeutic targets and effective therapeutic agents of PAH [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current clinical drugs treating PAH include: calcium channel blockers, anti-coagulants, diuretics and oxygen. These drugs are limited to the symptomatic treatment improvement and could not solve the fundamental problems [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The classical drugs such as endothelin receptor antagonist, soluble guanylate cyclase agonist, phosphodiesterase type 5 inhibitor, prostaglandin agonists or analogs, could alleviated the clinical symptoms and improved the prognosis. Due to the complicated pathogenesis of PAH, it is unsatisfactory for the effect of those drugs in reversing the pulmonary vascular remodeling [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The patient survival of advanced PAH remains poor at five years despite the treatment advances, and the expensive operation of lung transplantation is an important option for those patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, in-depth understanding of the underlying mechanisms are extremely urgent for PAH.\u003c/p\u003e \u003cp\u003eOmics are a new approach for whole gene analysis in a specific cell type or tissue. Transcriptomics focuses on the gene expression at the RNA level and offers the genome-wide information, while proteomics is the large-scale analysis of the entire protein, and phosphoproteomics analysis is to detect the phosphorylation of proteins in complex biological process [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Multi-omics techniques integrating these individual omics are very useful in detecting various biological processes. In this study, RNA-seq or 4D Lable-free approach for proteomics and phosphoproteomics was performed in lung tissues of PAH patients to determine the molecular characteristics of PAH. Dysregulated levels of genes, proteins and protein phosphorylation were identified. We further combined the results from these omics analyses to unveil the pathogenesis of PAH.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eTissue samples\u003c/p\u003e \u003cp\u003e Lung tissues were obtained from the Wuxi People's Hospital and the Affiliated Hospital of Xuzhou Medical University, and all patients provided their written informed consent. The study was approved by the institutional research ethics committee and the experimental methods were performed in accordance with the relevant guidelines and regulations. Lung tissues of PAH group were isolated from the lungs of patients receiving lung transoplantation, while the control group were undergoing chest surgery. PAH diagnosis has been diagnosed in every patient by clinical method, and the isolated tissue samples were frozen in liquid nitrogen for subsequent experiment.\u003c/p\u003e \u003cp\u003eRNA isolation and RNA-seq\u003c/p\u003e \u003cp\u003eTranscriptome sequencing was performed at Genechem Biotechnology Co., Ltd. (Shanghai, China) following the standard experimental procedures as described [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. RNA was extracted from tissues using NEBNext\u0026reg; Ultra II Directional RNA Library Prep Kit (NEB, USA) and the total amount of 1 \u0026micro;g RNA per sample was used for the RNA sample preparations. Then RNA was fragmented and purified to construct libraries. PCR products were purified and library quality was assessed on the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA) according to the manufacturer\u0026rsquo;s instructions. RNA-seq based transcriptome profiling was performed by high-throughput Illumina NovaSeq 6000 sequencing platform (Illumina Technologies, CA, USA) and 150 bp paired-end reads were generated.\u003c/p\u003e \u003cp\u003eRNA-seq analyses\u003c/p\u003e \u003cp\u003eReference genome and gene model annotation files were downloaded from genome website directly. FeatureCounts was used to count the reads numbers mapped to each gene and for quantification of gene expression level. Differential expression analysis between the two groups was performed using the DESeq2 software which provided statistical routines in digital gene expression data based on the negative binomial distribution. The resulting p-values were adjusted by the Benjamini and Hochberg\u0026rsquo;s approach for controlling the false discovery rate. Genes with an adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 found by DESeq2 were assigned as differentially expressed. The corrected p-value of 0.05 and | log2 (fold change) |were set as the threshold for significantly differential expression and cluster Profiler R package used for the enrichment analysis.\u003c/p\u003e \u003cp\u003eProtein extraction and preparation\u003c/p\u003e \u003cp\u003eSDT buffer was added to the tissues and the lysate was homogenized by MP Automated Homogenizer (6.0M/S, 30s, twice). The homogenate was sonicated and boiled for 10 min. After centrifuged at 14000g for 15 min, the supernatant was filtered with 0.22 \u0026micro;m filters. The protein was quantified by the BCA Protein Assay Kit (P0012, Beyotime, China) and using SDS-PAGE electrophoresis for quality control. Filter-aided sample preparation (FASP) is a universal method for peptide segment and the peptide was desalted by C18 column [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Similarly, the labeled peptides were combined and desalted using C18 Cartridge and the mixture was subjected to High-Select\u0026trade; Fe-NTA Phosphopeptide Enrichment Kit (Thermo Fisher scientific, A32992). The eluent were dried down via vacuum centrifugation at 45℃ and then dissolved in 0.1% formic acid buffer.\u003c/p\u003e \u003cp\u003e4D Label‑free quantitative proteomics and phosphorylation proteomics\u003c/p\u003e \u003cp\u003e4D Label-free quantitative proteomics and phosphorylation proteomics were performed by Genechem Biotechnology Co., Ltd. (Shanghai, China). 4D Label-free technology could quantitatively determine protein levels without complex labeling or processing of samples [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Before mass spectrometry (MS) identification, the samples were separated using the NanoElute system (Bruker, Bremen, Germany) with a nanoscale flow rate. Then the samples were analyzed by the timsTOF Pro (Bruker, Bremen, Germany) with PASEF mode. The duration of analysis was 90 min (for phosphorylation analysis was 120 min) and the detection method was positive ion. The mass range of mother ion was 100 to 1700m/z, and the ion mobility was start from 0.75 V to 1.4 V\u0026sdot;s/cm\u003csup\u003e2\u003c/sup\u003e. The ion ramp time was 100ms, and the tilization rate was 100%. In addition, the capillary voltage was 1500V and the drying gas speed was 3L/min, the temperature was 180\u0026deg;C. The mass charge ratio of peptides and peptide fragments were collected according to the following methods: 10 MS/MS scans (total cycle time 1.16sec), the charge range was 0 to 5, the active exclusion was 0.5 min, the scheduling target intensity was10000, intensity threshold was 2500, and the Normalized Collision Energy was 20 to 59eV.\u003c/p\u003e \u003cp\u003eProtein identification and quantification analysis\u003c/p\u003e \u003cp\u003eRaw files were processed by MaxQuant 1.6.17.0 using the standard settings against Human protein database (Uniprot_HomoSapiens_20337_20220308_swissprot). An initial search was set at 10 ppm and searched followed an enzymatic cleavage rule of Trypsin/P, which allowed maximal two missed cleavage sites and the mass tolerance of 40ppm for fragment ions. Carbamidomethylation of cysteines was defined as fixed modification, and oxidation of methionines as well as N-terminal acetylation was defined as variable modification for searching. The cutoff of global false discovery rate (FDR) for peptide or protein identification was set at 0.01. Protein aboundance was calculated on the basis of the normalized spectral protein intensity (LFQ intensity). The significant differentially expressed proteins up-regulated more than 2 fold or down-regulated less than 0.5 fold and p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were screened by UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for bioinformatics analysis. As previously reported, we only analyzed the protein phosphorylation changes that were higher or lower than the fold change of itself in proteomics [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGene Ontology (GO) annotation\u003c/p\u003e \u003cp\u003eTo determine the biological and functional properties of the identified proteins, we employed the hypergeometric test to perform GO enrichment analysis. Firstly, the target protein sequences were aligned to the database using NCBI BLAST+ (ncbi-blast-2.3.0+) on the Linux server and kept the top ten sequences (E-value was less than or equal to 0.001). Using Blast2GO to select the GO term (database version: go_20190701.obo) of the sequence with the top Bit-Score and complete the elementary annotation from GO terms for target protein by Blast2GO Command Line. In order to improve the efficiency of annotation, InterProScan were used to search EBI database for conserved motif matching the protein and added the functional information [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. ANNEX was performed for the further annotation information and established the connections between different GO categories to improve the accuracy of annotation. Fisher\u0026rsquo;s exact test was used to enrich GO terms by comparing the number of differentially expressed proteins and total proteins correlated to GO terms.\u003c/p\u003e \u003cp\u003eKyoto encyclopedia of genes and genomes (KEGG) pathway annotation\u003c/p\u003e \u003cp\u003eUsing KEGG Orthology And Links Annotation software (version number: V2.2) for KEGG pathway annotation on the target protein and classified the sequence by KEGG Orthology (KO) with the information about the pathways automatically. Fisher\u0026rsquo;s exact test was used to enrich KEGG terms by comparing the number of differentially expressed proteins and total proteins correlated to KEGG terms.\u003c/p\u003e \u003cp\u003eProtein validation by PRM\u003c/p\u003e \u003cp\u003ePRM was performed to determine the levels of those differentially expressed proteins to verify the proteomic analysis based on the 4D label-free LC-MS/MS. The total protein extraction, enzyme digestion, and desalination were the same as described in the previous sample preparation. Two micrograms of peptide mixture were loaded onto the C18-reversed phase analytical column (Thermo Fisher Scientific, Acclaim PepMap RSLC 50um \u0026times; 15cm, nano viper, P/N164943, USA) in buffer A (0.1% Formic acid) and separated with a linear gradient of buffer B (80% acetonitrile and 0.1% formic acid) at a flow rate of 300 nl/min. The liquid gradient was as follows: 1\u0026thinsp;~\u0026thinsp;3% B liquid for 0 min\u0026thinsp;~\u0026thinsp;5 min;, 3%~28% B liquid for 6 min\u0026thinsp;~\u0026thinsp;45min, 28% ~ 38% B liquid for 46 min\u0026thinsp;~\u0026thinsp;50min, 38%~100% B liquid for 51min\u0026thinsp;~\u0026thinsp;55min, 100% B liquid for 56 min\u0026thinsp;~\u0026thinsp;60min.\u003c/p\u003e \u003cp\u003ePeptide fragmentation and targeted PRM MS were performed using a Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, USA) that was coupled to Easy nLC (Thermo Fisher Scientific, USA) for 60 min in the positive ion mode. Data were acquired using the most abundant precursor ions setting the survey scan ranging from 350 to 1800 m/z for high-energy collisional dissociation (HCD). Survey scans were obtained at a resolution of 60000 m/z with AGC target of 3E6 and maximum injection time of 50 ms. MS2 scans were at a resolution of 30000 m/z for HCD spectra with AGC target of 2E5 and maximum injection time of 50 ms, isolation width was 1.6 m/z. Only the ions with the charge state between 2\u0026thinsp;~\u0026thinsp;6 and a minimum intensity of 8E3 were selected for fragmentation. Dynamic exclusion for selected ions was 30s and normalized collision energy was 27 eV.\u003c/p\u003e \u003cp\u003eThe MS RAW file were analyzed by SpectroDive software and database version was uniprot_homo_20230312_20423_9606_swiss_prot. Statistical analysis was processed with SPSS software and all the results were analyzed using Student\u0026rsquo;s t test with expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error. Significant differences were judged by the p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eScreening the differential charateristics in PAH\u003c/p\u003e \u003cp\u003eThe samples from the lung tissues of PAH (n\u0026thinsp;=\u0026thinsp;8) or control patients (n\u0026thinsp;=\u0026thinsp;8) were subjected to high-throughput sequencing, including RNAseq, 4D Label-free technology to identify changes of mRNA, protein and phosphoprotein, respectively. Differentially expressed genes (DEGs) analysis revealed the mRNA levels of 967 genes were significantly different (|log2FoldChange|\u0026gt;1 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), 424 genes was downregulated and 543 genes was upregulated at least twofold change (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Because proteins represent the actual functional molecules, 4D Label‑free technology was conducted to investigate the differences of proteomic levels between the two groups. 4049 proteins were identified and 764 differentially expressed proteins (DEPs) were observed after data filtering (|log2FoldChange|\u0026gt;1 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among those proteins, 467 proteins were increased in PAH, while 297 proteins were reduced above twofold change (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). In addition, the top-10 upregulated and downregulated proteins of each group were exhibited in detailed heatmaps (Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Those DEPs indicated the dysregulated proteins expression in the progression of PAH. Meanwhile, we subsequently identified 2197 proteins in phosphoproteome analysis, including 314 downregulated phosphoproteins and 97 upregulated phosphoproteins, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). The top-10 most altered phosphorylated protein and phosphorylation site were displayed in supplementary materials (Fig.\u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Then we integrated the analysis between transcriptome and proteomics. There were 54 genes with overlapped alterations at both mRNA and proteins levels, including 48 proteins with the similar trend with mRNA expression, and 6 proteins with the opposite tendency (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Overall, different characteristics could be observed through multi-omics analysis between the two groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEnolase 1 (ENO1), a protein necessary for pulmonary artery smooth muscle cells (PASMC) proliferation and de-differentiation, were significantly higher compared to the controls as reported [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In addition, we confirmed the altered expression of several other proteins implicated in PAH pathobiology, such as caveolin-1(CAV1) and chloride intracellular channel protein 1(CLIC1) according to the previous study [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. All the marked changes indicated successful materials establishment from PAH patients. Furthermore, the alterations of some proteins like alkaline phosphatase, tissue-nonspecific isozyme (ALPL), membrane metalloendopeptidase (MME), versican (VCAN) have not been reported in PAH previously.\u003c/p\u003e \u003cp\u003eTranscriptome profiling between PAH and control patients\u003c/p\u003e \u003cp\u003eTranscriptomes is one of the most important regulation modes in cell. To identify the possible novel molecular factors or pathways associated with PAH, GO and KEGG enrichment were performed to analyze DEGs using twofold chang. It was determined three sub parts in GO enrichment analysis: biological process (BP), molecular function (MF), and cellular component (CC). The DEGs were mainly enriched in endocrine process, acute inflammatory response, regulation of chemokine production, electron transport chain, tissue remodeling, and NADH dehydrogenase activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). KEGG pathway analyses revealed that DEGs were highly enriched in oxidative phosphorylation, HIF-1 signaling pathway, ferroptosis, and p53 signaling pathway in PAH (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn particular, the most enriched BP of the DEGs was related to the energy and metabolism, including electron transport chain, oxidative phosphorylation, and purine ribonucleoside triphosphate metabolic process. For the downregulated DEGs, the enriched BP included cell-cell adhesion via plasma-membrane adhesion molecules, and neutrophil activation involved in immune response. For MF, the most significantly enriched GO terms for upregulated and downregulated DEGs were extracellular matrix (ECM) structural constituent and cytokine receptor activity, respectively. In CC, extracellular matrix and secretory granule membrane were the most significantly enriched GO terms in the up- and downregulated DEGs, respectively (Fig.\u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA-C). The top three most KEGG pathways among the upregulated DEGs were oxidative phosphorylation, p53 signaling pathway and cell cycle, and the downregulated DEGs were cytokine-cytokine receptor interaction, cAMP signaling pathway and cell adhesion molecules, respectively (Fig.\u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eD). To gain insight into the function of the detected genes, Gene Set Enrichment Analysis (GSEA) was conducted. Based on the absolute values of normalized enrichment score (NES)\u0026thinsp;\u0026gt;\u0026thinsp;1, nominal p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.25, the signaling pathways of electron transfer activity (GO: 0009055, NES\u0026thinsp;=\u0026thinsp;1.95, p\u0026thinsp;=\u0026thinsp;0.008, FDR\u0026thinsp;=\u0026thinsp;0.24), oxidative phosphorylation (GO: 000619, NES\u0026thinsp;=\u0026thinsp;1.80, p\u0026thinsp;=\u0026thinsp;0.018, FDR\u0026thinsp;=\u0026thinsp;0.18) were significantly enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC \u0026amp; \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The detailed information of genes contributed to the enrichment items were revealed in the supplementary materials (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). In summary, the DEGs were primarily enriched in inflammation, oxidative stress, metabolism and several other important signaling pathways.\u003c/p\u003e \u003cp\u003eProteomic profiling between PAH and control patients\u003c/p\u003e \u003cp\u003eTo understand the proteomic profiling or pathways affected during the progression of PAH, 764 DEPs were subjected to GO and KEGG. Proteins with |log2FoldChange|\u0026gt;1 were subjected to the analysis.\u003c/p\u003e \u003cp\u003eBP terms enrichment analysis revealed the dysfunction in extracellular matrix organization, angiogenesis, electron transport chain and metabolism disorder, like glutamine, fructose and other substance metabolism. It was noticed that the term of electron transport chain was found both in the results of transcriptomics and proteomics, which mean this biological process were important in the progression of PAH. For MF, the most significantly enriched GO terms for DEPs were \u0026ldquo;binding\u0026rdquo; and extracellular matrix structural constituent and CC terms revealed thatlysosomal lumen, adherens junction were enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Similarly, the top 20 of KEGG pathways analyses suggested the involvement of ECM-receptor interaction, lysosome, PI3K-AKT signaling pathway and Rap1 signaling pathway in the advancing of diseases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). More significantly changed terms were enriched in metabolic pathways, including metabolisms of amino acids, purine, glutathione and glycolysis. Some key proteins were involved in regulation disease development via differently pathways. The detailed information of protein contributing to each enrichment items was exhibited in the supplementary materials (Table S5). In summary, DEPs alterations of signaling pathways, metabolism and dysfunctional cellular processes might be involved in the pathogenesis of PAH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFunctional analysis of phosphorylated DEPs between PAH and control patients\u003c/p\u003e \u003cp\u003eProtein phosphorylation plays a central role in regulating protein structure, function and closely connects with human health. Next, GO and KEGG analysis were performed to analyze the 411 differentially phosphorylated proteins depending on the significance of p-values and |log2FoldChange|\u0026gt;1. The proteins of which the fold changes of phosphorylated form less than the total change of its total form were excluded. GO enrichment analysis showed that the differentially phosphorylated proteins were most enriched in three reference sets (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Those phosphorylated proteins participated in various cellular process, such as epithelial cell proliferation involved in lung morphogenesis, negative regulation of potassium ion transmembrane transporter activity, cellular response to cytokine stimulus, response to calcium ion, notch signaling pathway in BP. For MF, the top significantly enriched GO terms were \u0026ldquo;binding\u0026rdquo; and structural constituent of cytoskeleton, voltage-gated ion channel activity and potassium channel activity. Cell-cell junction, stress fiber were the enriched CC terms for phosphoproteins. Meanwhile, KEGG enrichment analysis revealed that most significant enriched terms were autophagy, HIF-1 signaling pathway, tight junction and leukocyte transendothelial migration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Descriptions of the enriched proteins entry were available in the supplementary materials (Table S6). Among these pathways, HIF-1 signaling pathway was observed both in the KEGG analysis of transcriptomics and proteomics, which implicated that this pathway might play a critical role in pathogenic progress of PAH. In summary, phosphorylated DEPs were involved in the regulation of several cellular processes, such as ion channel and metabolism, which were tightly associated with PAH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eVerification of the key proteins\u003c/p\u003e \u003cp\u003eTo further verify that the results from the proteomics data, PRM was carried out to determine the expression of the selected DEPs, including the proteins from the significantly enriched GO term or KEGG pathways and the proteins with significant alterations. Similar to proteomics studies previously, there were some discrepancies between the two approaches [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The relative quantitative expression of each selected protein showed that 25 proteins had not significant difference as observed in the 4D Lable-free approach and PRM analyses, while five proteins did not demonstrate significant changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the fold change of VCAN, MME, CLIC1 and other proteins were verified to be significant in the two methods (Table S7).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCurrent drug therapy could only alleviated the clinical symptoms, while could prevent the progression of PAH, thus lung transplantation would be needed for patients with advanced PAH. Currently, we identified the novel dysregulated genes or proteins in the lung tissues of PAH using RNA-seq analyses and 4D Label‑free technology. The mRNA, protein and phosphorylated proteins profiles of lung tissues were established to investigate the complex pathogenesis of PAH. Furthermore, we integrated multi-omics characteristics to establish the PAH gene expression PAH profiles, and observed some novel alterations of proteins or signaling pathways that have not been found previously for the further pathophysiology and potential therapeutics in PAH.\u003c/p\u003e \u003cp\u003eBased on differential expression genes analysis, we totally identified 543 upregulated and 424 downregulated genes, and those DEGs revealed some key genes involved in PAH. Some genes exhibited similar changes consistent with previous research [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. GO analyses of DEGs in PAH showed that most of the enriched genes were related to inflammatory response and oxidative stress, tissue remodeling, for example, cell chemotaxis, acute inflammatory response, and positive regulation of cell motility. Oxidative phosphorylation and HIF-1 signaling pathway were the top significantly regulated KEGG pathway identified in PAH group. Enrichment analyse of GSEA showed that oxidative phosphorylation were involved in PAH, those results was consistent with evidence that oxidative stress was critical in the pathophysiology of PAH, antioxidant treatment might be the potential therapeutic target for the treatment of PAH [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Of note, many similarities to human cancers in the pulmonary vasculature, up-regulated or down-regulated gene group also be of interest for PAH, including neutrophil activation involved in immune response, chemokine receptor activity, and calcium ion homeostasis had been implicated as the cause or consequence of PAH [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Ferroptosis was a newly identified iron-dependent form of regulated cell death, playing critical roles in various organ injuries [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Our data indicated that DEGs in ferroptosis and p53 signaling were correlated with PAH. Oxidative phosphorylation and other factors might influence pulmonary vascular remodeling from RNA-seq analysis of PAH. We further performed 4D label-free quantitative proteomics method to screen proteins expression in PAH.\u003c/p\u003e \u003cp\u003eIt was well known that proteins, which were expressed by genes after transcription, were the executors and deterministic players in life process, so the changes of protein urgently need to know. Our proteomics results revealed a total of 764 proteins were significantly changed more than two-fold change, of which 467 upregulated proteins and 297 downregulated proteins. Most of the altered proteins were enriched in the regulation of autophagy, angiogenesis, metabolic process, ion channel, and acute inflammatory response. GO analysis suggested a pronounced contributory role of angiogenesis, electron transport chain, ion channel and metabolism. KEGG pathway analysis showed the significant enrichment in apoptosis, PI3K-Akt and Rap1 signaling pathway, metabolic pathways and secondary metabolities biosynthesis pathway. According to previous study, inhibition of PI3K-Akt pathways could attenuate the development of PAH, as potential therapeutic target for PAH [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, the roles of some altered pathways like Rap1 signaling in PAH were still unveiled. In addition, we pay attention to that the relevant representative protein, such as caveolin-2 (CAV2), chloride intracellular channel 5 (CLIC5), were enriched in many vital pathways. CAV2 belongs to caveolin gene family and widely expressed in most cell types, regulates many key processes, such as cell migration and metastasis, angiogenesis, and drug resistance [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It have been reported that loss-of-function of CAV1 could affect pulmonary artery endothelial cells proliferation and migration, as well as reduce cytoskeletal stress fibers, leading to neointima formation and aggravated PAH [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The results of proteomics and PRM showed CAV2 were significantly changed, but there are still a lot of unknown field for its role in PAH. Chloride channel, CLIC1, CLIC4 are excessively expressed in PAH and contribute to mitochondrial dysfunction and energy metabolism in endothelium [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. CLIC5 encodes actin-based cytoskeletal protein, and has been thought to play significant roles in human cancers [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Enrichment result suggested that CLIC5 might participate in obsolete peroxidase reaction and was associated with PAH.\u003c/p\u003e \u003cp\u003eIn order to acquire in-depth study of the pathogenesis of PAH, we integrated the results of transcriptomics and proteomic and found 54 genes with overlapped alterations. Transcriptomics could clarify the mechanism of functional disorders; proteomics could be used to predict relevant target genes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Integrated analysis of the results of transcriptomics and proteomics provides a new vision for the pathogenesis of PAH. We noted that the representative protein desmin (DES) and MME had the same tendency in mRNA and protein level. DES is a muscle-specific protein and a primary subunit of the intermediate filament in cardiac, skeletal and smooth muscles [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. DES abnormal expression might break the balance in preserving the homeostasis of pulmonary artery smooth muscle cell [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Illustrating the role of those proteins would help to elucidate the pathogenesis of PAH.\u003c/p\u003e \u003cp\u003eBesides the proteomic analysis, we conducted phosphoproteomic profiling in the lung tissues of PAH, and observed 97 upregulated phosphoproteins and 314 downregluated phosphoproteins. The observe in proteins\u0026rsquo; phosphorylation suggested a direct involvement of protein phosphorylation in the development of PAH. Results from the selected GO terms contained epithelial cell proliferation, potassium ion transmembrane transporter activity, notch signaling pathway, including DES, epidermal growth factor receptor (EGFR), VCAN, and NEDD4L. Those proteins were associated with cellular proliferation or progression and the regulation of a range of pulmonary disease [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The enrichment analysis consistent with the development of PAH characterized by dysregulated proliferation of all vascular cell types, including endothelial, smooth muscle, and fibroblasts [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Meanwhile, KEGG pathways analysis of phosphoproteins also uncovered an intriguing finding: autophagy, apoptosis, and HIF-1 signaling pathway. The representative proteins included mammalian target of rapamycin (mTOR), ENO1, DES, EGFR, and integrin Subunit Beta 4 (ITGB4). mTOR is a highly important protein kinase that responds to the cellular and extracellular signals, and its phosphorylation has been reported to contribute to the proliferation, migration, and gene regulation of pulmonary artery smooth muscle and endothelial cells, thus involved in pulmonary vascular remodeling and continuous vasoconstriction [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, the relationship between ENO1 and PAH is poorly understand, thus exploring the potential role of ENO1 might be of great interest. Overall, the altered phosphoproteins were generally directly correlated with the development of PAH.\u003c/p\u003e \u003cp\u003eThere are some limitations in this study. The samples from the PAH patients probably have taken clinical drugs that may influence the expression of some proteins. Nevertheless, precious studies on human samples are difficult to acquire. Our results had shown a great deal of consistency with the changed proteins consistent with the previous study, demonstrating that our samples have clinical significance [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. However, the alterations of some key PAH-related proteins, such as bone morphogenetic protein receptor type II (BMPR2), STAT3 and phosphor-STAT3, were not observed [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. It may be due to their lower expression or high standard of fold change compared for the identified proteins in our study. Additionally, an integrated analysis of mRNA and protein level could provide more complicated and comprehensive information to better understand protein regulation [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Moreover, phosphoproteomic integrated the information of protein modifications to obtain a deep understanding in the pathogenesis of PAH. In future, multi-omics and biological method might help us to identify detailed origins of key proteins and pathways in PAH.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, we performed a comprehensive analysis of the molecular mechanism of PAH through the integrated analysis with transcriptomics, proteomic, phosphoproteomic analysis of lung tissues in PAH patients. Our multi-omics analyses provided an overview of dysregulated genes expression in lung tissues of PAH patients, thus contributed to a better understanding of the molecular pathogenesis. Further studies in the changes in the mRNA, proteins, and phosphoproteins in future studies might benefit in searching the potential therapeutic targets and interventional strategies for PAH.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePAH: Pulmonary arterial hypertension\u003c/p\u003e\n\u003cp\u003eGO: Gene Ontology \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKEGG: Kyoto encyclopedia of genes and genomes\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePRM: Parallel reaction monitoring\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eENO1: Enolase 1\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePASMC: Pulmonary artery smooth muscle cells\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCAV1: Caveolin-1\u003c/p\u003e\n\u003cp\u003eCLIC1: Chloride intracellular channel protein 1\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMME: Membrane metalloendopeptidase\u003c/p\u003e\n\u003cp\u003eVCAN: Versican\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDES: Desmin\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTAGLN: Transgelin\u003c/p\u003e\n\u003cp\u003eCHI3L1: Chitinase-3-like protein 1\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the participants in this study. We would lie to thank the anonymous reviewers for their valuable comments and suggestions, which helped improve the quality of our mamuscirpt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLTY, WZP conceived and designed the overall study. ZSQ and WR conducted the bioinformatics analysis. ZSQ analyzed data for the key proteins screening. LTY, WR, XXM and DF recruited patients. LTY drafted the manuscript. WZP was the guarantor of the study. All authors approved the fnal draft for publication\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 82270059 and 81703493), The Natural Science Foundation of Jiangsu Province (Grant No. BK20221222 and BK20170258), The China Postdoctoral Science Foundation‑funded projects (Grant No. \u0026nbsp;2019M661943), The Foundation of Xuzhou Science and Technology Department (Grant No. KC21154).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Medical Institutional Ethics Committee of the Affiliated Hospital of Xuzhou Medical University and Wuxi People\u0026apos;s Hospital. Patients all signed the written informed consents before taking part into our study. The study project conforms to the ethical guidelines of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll of the authors listed for this paper consent to the publication of this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHassoun PM: Pulmonary Arterial Hypertension. \u003cem\u003eN Engl J Med \u003c/em\u003e2021, 385:2361-2376.\u003c/li\u003e\n\u003cli\u003eLevine DJ: Pulmonary arterial hypertension: updates in epidemiology and evaluation of patients. \u003cem\u003eAm J Manag Care \u003c/em\u003e2021, 27:S35-S41.\u003c/li\u003e\n\u003cli\u003eHoeper MM, Ghofrani HA, Gr\u0026uuml;nig E, Klose H, Olschewski H, Rosenkranz S: Pulmonary Hypertension. \u003cem\u003eDtsch Arztebl Int \u003c/em\u003e2017, 114:73-84.\u003c/li\u003e\n\u003cli\u003eMcGee M, Whitehead N, Martin J, Collins N: Drug-associated pulmonary arterial hypertension. \u003cem\u003eClin Toxicol (Phila) \u003c/em\u003e2018, 56:801-809.\u003c/li\u003e\n\u003cli\u003eVazquez ZGS, Klinger JR: Guidelines for the Treatment of Pulmonary Arterial Hypertension. \u003cem\u003eLung \u003c/em\u003e2020, 198:581-596.\u003c/li\u003e\n\u003cli\u003eCondon DF, Agarwal S, Chakraborty A, Auer N, Vazquez R, Patel H, Zamanian RT, de Jesus Perez VA: Novel Mechanisms Targeted by Drug Trials in Pulmonary Arterial Hypertension. \u003cem\u003eChest \u003c/em\u003e2022, 161:1060-1072.\u003c/li\u003e\n\u003cli\u003eFarber HW, Miller DP, Poms AD, Badesch DB, Frost AE, Muros-Le Rouzic E, Romero AJ, Benton WW, Elliott CG, McGoon MD, Benza RL: Five-Year outcomes of patients enrolled in the REVEAL Registry. \u003cem\u003eChest \u003c/em\u003e2015, 148:1043-1054.\u003c/li\u003e\n\u003cli\u003eDong Z, Chen Y: Transcriptomics: advances and approaches. \u003cem\u003eSci China Life Sci \u003c/em\u003e2013, 56:960-967.\u003c/li\u003e\n\u003cli\u003eMendes ML, Dittmar G: Targeted proteomics on its way to discovery. \u003cem\u003eProteomics \u003c/em\u003e2022, 22:e2100330.\u003c/li\u003e\n\u003cli\u003eUrban J: A review on recent trends in the phosphoproteomics workflow. 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potential therapeutic targets for idiopathic pulmonary arterial hypertension. \u003cem\u003eBr J Pharmacol \u003c/em\u003e2020, 177:3505-3518.\u003c/li\u003e\n\u003cli\u003eBalistrieri A, Makino A, Yuan JX: Pathophysiology and pathogenic mechanisms of pulmonary hypertension: role of membrane receptors, ion channels, and Ca(2+) signaling. \u003cem\u003ePhysiol Rev \u003c/em\u003e2023, 103:1827-1897.\u003c/li\u003e\n\u003cli\u003eBuccitelli C, Selbach M: mRNAs, proteins and the emerging principles of gene expression control. \u003cem\u003eNat Rev Genet \u003c/em\u003e2020, 21:630-644.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pulmonary arterial hypertension, RNA-seq, proteomic, phosphoproteomic, pulmonary vascular remodeling","lastPublishedDoi":"10.21203/rs.3.rs-3929686/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3929686/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePulmonary arterial hypertension (PAH), a fatal disease, is characterized by pulmonary vascular remodeling and vascular resistance. However, the molecular mechanisms underlying the pathogenesis of PAH remained to be incompletely understood.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRNA-seq, 4D Lable-free proteomics and phosphoproteomics were used to detect the levels of mRNA, proteins, and phosphoproteins in lung tissues from PAH patients, respectively. Parallel reaction monitoring (PRM) was carried out to verify the expression of the differentially expressed proteins.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTotally, 967 differentially expressed genes (|log2FoldChange|\u0026gt;1 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), 764 differentially expressed proteins and 411 phosphoproteins were observed after data filtering (|log2FoldChange|\u0026gt;1 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in lung tissues of PAH patients as compared with the control group. Integrated analysis of the three omic measures revealed that the biological processes involving inflammation, ion channel and metabolism were closely associated with PAH. Several signaling pathways, such as ferroptosis, HIF-1, PI3K-AKT, and Rap1 might be related to the development of PAH.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study combined multi-omics characteristic profiling to find out the changed genes or proteins that contributed to a detailed pathogenic of PAH. It would have the benefit of looking for the novel and effective treatment targets and therapeutic drugs to PAH patients.\u003c/p\u003e","manuscriptTitle":"Integration of transcriptomics, proteomics, phosphoproteomics analysis for characterization of pulmonary arterial hypertension in Chinese people","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-09 17:05:29","doi":"10.21203/rs.3.rs-3929686/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"be28580f-4a80-443c-8b29-35c6ac098045","owner":[],"postedDate":"February 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-19T20:17:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-09 17:05:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3929686","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3929686","identity":"rs-3929686","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}