Serum proteome profiling reveals HGFA as a candidate biomarker for pulmonary arterial hypertension

Abstract

Background: Identification and validation of potential biomarkers could facilitate the identification of pulmonary arterial hypertension (PAH) and thus aid to study their roles in the disease process.

Methods: We used the isobaric tag for relative and absolute quantitation approaches to compare the protein profiles between the serum of PAH patients and the controls. Bioinformatics analyses and enzyme-linked immunosorbent assay (ELISA) identification of PAH patients and the controls were performed to identify the potential biomarkers. The receiver operating characteristic curve (ROC) analysis was used to evaluate the diagnostic performance of these potential biomarkers. Mendelian randomization (MR) analysis further clarified the relationship between the potential biomarkers and PAH. Additionally, the expression levels of the potential biomarkers were further validated in two PAH animal models (monocrotaline-PH and Sugen5416 plus hypoxia-PH) using ELISA and reverse transcription-quantitative PCR (RT-qPCR).

Results: We identified significant changes in three proteins including heparanase (HPSE), gelsolin (GSN), and hepatocyte growth factor activator (HGFA) in PAH patients. The ROC analysis showed that the areas under the curve of HPSE, GSN, and HGFA in differentiating PAH patients from controls were 0.769, 0.777, and 0.964, respectively. HGFA was correlated with multiple parameters of right ventricular functions in PAH patients. Besides proteomic analysis, we also used MR method to demonstrate the causal link between genetically reduced HGFA levels and an increased risk of PAH. In subsequent validation study in PAH animal models, the mRNA expression levels of HGFA in the lung tissues were significantly lower in PAH rat models than in controls. In the rat models, serum levels of HGFA were lower compared to the control group and showed a negative correlation with right ventricular systolic pressure.

Conclusion: The study demonstrated that HGFA might be a promising biomarker for noninvasive detection of PAH.

Keywords: Biomarkers; Isobaric tag for relative and absolute quantitation; Proteomics; Pulmonary arterial hypertension (PAH).

Fig. 1

Proteomics analysis revealed differential protein expression in the serum of PAH patients. A Flow chart. B Total number of identified (green bar) and quantified (red bar) proteins in the iTRAQ experiment. C Volcano plots for the expression of differentially expressed proteins. D A total of 41 upregulated proteins and 44 downregulated proteins were identified

Fig. 2

Functional enrichment analyses of differentially expressed proteins. A The top 10 enrichment GO Biological Process (BP) pathways ranked by enrichment score. B The top 10 enrichment GO Cellular Component (CC) pathways ranked by enrichment score. C The top 10 enrichment GO Molecular Function (MF) pathways ranked by enrichment score. D The top 9 enrichment KEGG pathways ranked by enrichment score

Fig. 3

PPI network for differentially expressed proteins and key module analysis

Fig. 4

Verification of differentially expressed proteins by ELISA in validation cohort. A GSN, B HFGA, C HPSE, D SAA1, and E ECM1 in pulmonary arterial hypertension patients and healthy controls. F Receiver operating characteristic (ROC) results of different proteins between the PAHs and healthy controls. As the result of significance test, *P value < 0.05; **P value < 0.01; ***P value < 0.001; ****P value < 0.0001; ns P value > 0.05

Fig. 5

Correlation network of three biomarkers and clinical indicators in pulmonary arterial hypertension patients. Correlations are indicated in red for positive correlations and in blue for negative correlations. As the result of significance test, *P value < 0.05

Fig. 6

Two-sample Mendelian randomization reveals causal evidence for HGFA on pulmonary arterial hypertension. A The forest plots illustrate the standardized beta (95% confidence interval) for each two-sample Mendelian randomization method; B Scatter plot to visualize the causal effect of HGFA on the risk of pulmonary arterial hypertension. The slope of the straight line indicates the magnitude of the causal association. IVW inverse-variance weighted

Fig. 7

Validation of HGFA expression. A Gene expression of HGFA in GSE113439 datasets; B receiver operating characteristic (ROC) results of HGFA between the PAHs and healthy controls in GSE113439 datasets; C Hgfa mRNA expression via RT-qPCR in lung tissues from SuHx-PH rat models or control; D Hgfa mRNA expression via RT-qPCR in lung tissues from MCT-PH rat models or control; E HGFA expression via ELISA in serum from SuHx-PH rat models or control; F HGFA expression via ELISA in serum from MCT-PH rat models or control; G relationship between HGFA expression and RVSP in SuHx-PH rat models or control; H relationship between HGFA expression and RVSP in MCT-PH rat models or control. **P value < 0.01. ***P value < 0.001. ****P value < 0.0001