Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 May 31:13:908783.
doi: 10.3389/fphar.2022.908783. eCollection 2022.

Regulatory T Cell-Related Gene Indicators in Pulmonary Hypertension

Yan Liu  1 , Jun-Zhuo Shi  2   3 , Rong Jiang  4 , Shao-Fei Liu  5   6 , Yang-Yang He  2   3 , Emiel P C van der Vorst  7   8   9   10   11 , Christian Weber  7   8   12   13 , Yvonne Döring  7   8   14 , Yi Yan  7
Affiliations

Regulatory T Cell-Related Gene Indicators in Pulmonary Hypertension

Yan Liu et al. Front Pharmacol. .

Abstract

Objective: Regulatory T cells (Tregs) are critical immune modulators to maintain immune homeostasis and limit pulmonary hypertension (PH). This study was aimed to identify Treg-related genes (TRGs) in PH. Methods: The gene expression profile from lungs of PH patients was retrieved from the Gene Expression Omnibus (GEO) database. The abundance of Tregs was estimated by the xCell algorithm, the correlation of which with differentially expressed genes (DEGs) was performed. DEGs with a |Pearson correlation coefficient| >0.4 were identified as TRGs. Functional annotation and the protein-protein interaction (PPI) network were analyzed. A gene signature for 25 hub TRGs (TRGscore) was generated by a single sample scoring method to determine its accuracy to distinguish PH from control subjects. TRGs were validated in datasets of transcriptional profiling of PH cohorts and in lung tissues of experimental PH mice. Results: A total of 819 DEGs were identified in lungs of 58 PAH patients compared to that of 25 control subjects of dataset GSE117261. In total, 165 of all these DEGs were correlated with the abundance of Tregs and identified as TRGs, with 90 upregulated genes and 75 downregulated genes compared to that of control subjects. The upregulated TRGs were enriched in negative regulation of multiple pathways, such as cAMP-mediated signaling and I-kappaB kinase/NF-kappaB signaling, and regulated by multiple genes encoding transcriptional factors including HIF1A. Furthermore, 25 hub genes categorized into three clusters out of 165 TRGs were derived, and we identified 27 potential drugs targeting 10 hub TRGs. The TRGscore based on 25 hub TRGs was higher in PH patients and could distinguish PH from control subjects (all AUC >0.7). Among them, 10 genes including NCF2, MNDA/Ifi211, HCK, FGR, CSF3R, AQP9, S100A8, G6PD/G6pdx, PGD, and TXNRD1 were significantly reduced in lungs of severe PH patients of dataset GSE24988 as well as in lungs of hypoxic PH mice compared to corresponding controls. Conclusion: Our finding will shed some light on the Treg-associated therapeutic targets in the progression of PH and emphasize on TRGscore as a novel indicator for PH.

Keywords: Treg-related genes; gene indicators; immune; pulmonary hypertension; regulatory T cells; transcriptomics.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Differentially expressed genes (DEGs) and top five DEGs positively and negatively correlated with the abundance of Tregs. (A) DEGs between 58 PAH patients and 25 control subjects of the GSE117261 dataset were visualized in volcano plots (fold change >1.5 or <0.67 and p < 0.05). Red dot represents upregulated DEGs, and dark blue dot represents downregulated DEGs in PAH patients compared to control subjects. (B–F) RGS1 (B); SLC4A7 (C); SYTL3 (D); CXCR4 (E); and ITK (F) were DEGs most positively correlated with the abundance of Tregs as analyzed by Pearson correlation analysis. (G–K) TALDO1 (G); MNDA (H); PROK2 (I); NT5DC2 (J); and CXCR2 (K) were DEGs most negatively correlated with the abundance of Tregs as analyzed by Pearson correlation analysis.
FIGURE 2
FIGURE 2
Functional annotation of TRGs. (A,B) Gene Ontology—biological pathways for 90 upregulated TRGs (A) and 75 downregulated TRGs (B) of the aforementioned dataset were identified by the functional annotation web tool DAVID and visualized in the barplot. (C,D) Genes encoding transcriptional factors in regulation of the gene profiling of upregulated TRGs (C) and downregulated TRGs (D) were explored and identified by the TRRUST category from the functional annotation tool Metascape.
FIGURE 3
FIGURE 3
Construction of the protein–protein interaction (PPI) network and identification of hub TRGs. (A) PPI network was constructed by the STRING database, and each blue filled circle represents a TRG. (B) Hub genes were screened out by the MCODE plugin in Cytoscape and categorized into three clusters. Hub TRGs in the left (first) and middle (second) clusters were downregulated in lungs of PAH patients compared to those of controls of the GSE117261 dataset. The hub TRGs in the right (third) cluster were upregulated in lungs of PAH patients compared to those of controls in the same dataset.
FIGURE 4
FIGURE 4
Validation of hub TRGs in a dataset of an independent PH cohort. (A–C) Gene expression of hub TRGs in the first (left) cluster (A), hub TRGs in the second (middle) cluster (B), and hub TRGs in the third (right) cluster (C) of Figure 3B were examined in lungs of 17 severe PH patients and 22 controls of the GSE24988 dataset. Data represent mean ± SEM. *p < 0.05; **p < 0.01 compared to control subjects, as analyzed by the unpaired t-test or Mann–Whitney test as appropriate.
FIGURE 5
FIGURE 5
Diagnostic performance of TRGscore for the patients with PH. (A–C) TRGscore between patients with PAH (group 1 PH) from the GSE117261 dataset (A), severe PH from the GSE24988 dataset (B), and PH from the GSE113439 dataset (C) were compared with the corresponding controls, respectively. (D–F) Receiver operation characteristic curves of TRGscore to distinguish PH from controls in GSE117261 (D), GSE24988 (E), and GSE113439 datasets (F), respectively. Data represent mean ± SEM. **p < 0.01; ***p < 0.001 compared to control subjects, as analyzed by the unpaired t-test.
FIGURE 6
FIGURE 6
Validation of hub TRGs in mouse lung tissues of hypoxic PH. (A–B) Right ventricular systolic pressure (RVSP) (A) and right ventricular hypertrophy (B) were assessed in hypoxia (Hx)-induced PH mice or mice under normoxia (Nor) at day 28 (n = 8/group). (C–D) Representative images of H&E staining (C) and quantification of vascular medial thickness (D) of lung tissues from mice under hypoxic or normoxic conditions at day 28 (n = 8/group). (E–G) Gene expression of hub TRGs in the first (left) cluster (E), in the second (middle) cluster (F), and in the third (right) cluster (G) of Figure 3B were examined in lungs of hypoxic PH mice and control mice at day 28 (n = 8/group). Data represent mean ± SEM. *p < 0.05; **p < 0.01; ***p < 0.001 compared to mice under normoxia, as analyzed by the unpaired t-test or Mann–Whitney test as appropriate.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Aran D., Hu Z., Butte A. J. (2017). xCell: Digitally Portraying the Tissue Cellular Heterogeneity Landscape. Genome Biol. 18 (1), 220. 10.1186/s13059-017-1349-1 - DOI - PMC - PubMed
    1. Benza R. L., Miller D. P., Barst R. J., Badesch D. B., Frost A. E., McGoon M. D. (2012). An Evaluation of Long-Term Survival from Time of Diagnosis in Pulmonary Arterial Hypertension from the REVEAL Registry. Chest 142 (2), 448–456. 10.1378/chest.11-1460 - DOI - PubMed
    1. Bodor J., Feigenbaum L., Bodorova J., Bare C., Reitz M. S., Jr., Gress R. E. (2001). Suppression of T-Cell Responsiveness by Inducible cAMP Early Repressor (ICER). J. Leukoc. Biol. 69 (6), 1053–1059. - PubMed
    1. Bonnet S., Michelakis E. D., Porter C. J., Andrade-Navarro M. A., Thébaud B., Bonnet S., et al. (2006). An Abnormal Mitochondrial-Hypoxia Inducible Factor-1alpha-Kv Channel Pathway Disrupts Oxygen Sensing and Triggers Pulmonary Arterial Hypertension in Fawn Hooded Rats: Similarities to Human Pulmonary Arterial Hypertension. Circulation 113 (22), 2630–2641. 10.1161/CIRCULATIONAHA.105.609008 - DOI - PubMed
    1. Bopp T., Becker C., Klein M., Klein-Hessling S., Palmetshofer A., Serfling E., et al. (2007). Cyclic Adenosine Monophosphate Is a Key Component of Regulatory T Cell-Mediated Suppression. J. Exp. Med. 204 (6), 1303–1310. 10.1084/jem.20062129 - DOI - PMC - PubMed