Pulmonary Arterial Hypertension Complicated with COVID-19

Attapon  Cheepsattayakorn^1,2,3,4*, Ruangrong  Cheepsattayakorn⁵, Porntep  Siriwanarangsun²

1. Faculty  of  Medicine  Vajira  Hospital, Navamindradhiraj  University, Bangkok, Thailand.

2. Faculty  of  Medicine, Western  University, Pathumtani  Province, Thailand.

3. 10th  Zonal  Tuberculosis  and  Chest  Disease  Center, Chiang  Mai, Thailand.

4. Department  of  Disease  Control, Ministry  of  Public  Health, Thailand.

5. Department  of  Pathology, Faculty  of  Medicine, Chiang  Mai  University, Chiang  Mai, Thailand.

                                             
Correspondence to: Attapon  Cheepsattayakorn, 10th  Zonal  Tuberculosis  and  Chest  Disease  Center, 143  Sridornchai  Road  Changklan  Muang  Chiang  Mai  50100  Thailand.

Copyright

© 2024 Attapon  Cheepsattayakorn. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: 01 Nov 2024

Published: 01 Dec 2024

Identification  of  the respiratory and cardiovascular systems, particularly, pulmonary  arterial  hypertension (PAH), acute  cardiac  injury, and  venous  thromboembolism (VTE)  can  be  identified  in  long-term  effects  of  COVID-19, but the virus also affects the neurological system, bones, endocrine glands, include  acute respiratory distress syndrome (ARDS) [1, 2].

With  a  novel, and  severe  novel  coronavirus  infections, PAH  has been reported to complicate the course of illness for 13.4% and 21% of patients, respectively. PAH  is a serious complication of new coronavirus infection, increasing the likelihood of requiring mechanical ventilation, extracorporeal membrane oxygenation (ECMO), intensive  care  unit (ICU) care and even death.     Enhancing the long-term prognosis of patients and minimize the hospitalization rate and death due to such complications therefore, by  early  detecting high pulmonary artery pressure in patients  with  SARS-CoV-2 [3-6].  As  revealed  by  previous  studies  and  reasons  described  by  the processes of immunological dysfunction, endothelial dysfunction, vascular leakage, and thrombotic microangiopathy that are comparable to those that cause pulmonary vascular disease, such  as  PAH  may be responsible for the effects of SARS-CoV-2 on pulmonary hemodynamics. On the other hand, reports of the study mechanism's depth and specificity are uncommon [3-7].

A  recent  study  in  2024  conducted  by  Hou  et  al  using a functional enrichment analysis on the GEO database to identify common differentially expressed genes (C-DEGs) across the  PAH  and  COVID-19  datasets. The results of a screening of the key genes using three machine algorithms: LASSO, RF, and SVM-RFE-based  were  confirmed  by  the  validation  queue. The role of prioritized core genes  was  examined  by  using  the  gene  set  enrichment  analysis (GSEA). The regulatory networks including these DEGs, including TF-gene connections and TF-microRNA co-regulation  were  next  mapped  out. Molecular docking simulations, drug-protein  interaction  networks, and molecular dynamics simulations were employed to screen for possible therapeutic medicines. The  study findings are expected to offer a novel approach to elucidating the genetic connection between the aforementioned disorders (Figures  1-5) [8].  

  Additionally, CCL20 and  SELE  were found to be indicators of PAH  and  COVID-19 co-pathogenesis by various bioinformatics analyze and machine learning algorithms. Adaptive immune response, leukocyte, lymphocyte mediated immune responses, and proinflammatory response mediated by cytokines like IL-12, TNF-α were functionally enriched in these two hub genes. These two hub genes were selected for nomogram construction and their diagnostic value evaluated by machine learning. The nomogram was found to have high diagnostic value. Dendritic cells had the strongest connection with CCL20  and  SELE, followed by activated CD4 T cells, active dendritic cells, natural killer T cells, neutrophils, and plasmacytoid dendritic cells. Using only 2 reference genes, they were able to isolate 12 shared TFs and 25 shared TF-miRNAs.by FFL tool, This FFL among CCL20, miR-1256 and PPARG may be a novel regulatory module in PAH  complicated  with  COVID-19. It was hypothesized that AFLATOXIN  B1, 1-NITROPYRENR, and  FENRETINIDE  would be useful in treating PAH  complicated  with  COVID-19. Further molecular  dynamics  and  molecular docking simulations demonstrated that 1-nitropyrene had the most stable binding with CCL20  and  SELE (Figures 1-5) [8]. 

In  conclusion, by  understanding the comorbidity of PAH  and  COVID-19 may be assisted by these angiogenesis  and  biomarkers connection between PAH  and  COVID-19.

Figure  1  Demonstrating  identification and functional enrichment analysis of common DEGs. (A) Venn diagram revealing 47 Up-regulated common DEGs in PAH  and  COVID-19. (B) Venn diagram revealing 17 Down-regulated common DEGs in PAH  and  COVID-19. (C) KEGG pathway analysis was performed on common DEGs. (D) GO-BP terms of common genes. (E) GO-CC terms of common genes. (F) GO-MF terms of common genes. DEG Differentially expressed genes. COVID coronavirus disease. PAH pulmonary hypertension. KEGG Kyoto Encyclopedia of Genes and Genomes. GO-BP, GO-CC, GO-MF Gene Ontology terms in biological process, cellular component, and molecular function [8].

Figure 2  Demonstrating  the  selection of candidate diagnostic biomarkers of COVID-19 progression with machine learning approaches. (A,B) LASSO regression analysis was applied to screen diagnostic biomarkers. (C) The diagnostic error relating to control,COVID-19 and total groups was visualized from the random forest. (D) The column showing 30 DEGs ranked based on the importance score calculated from the random forest. (E,F) The number of DEGs with the lowest error and highest accuracy after 100 folds were considered the most suitable candidates via the SVM-RFE algorithm. (G) The intersection of 3 machine learning algorithms was obtained with a Venn diagram tool. LASSO least absolute shrinkage and selection operator, SVM-RFE support vector machine recursive feature elimination, DEGs Differentially expressed genes [8].

Figure  3  Demonstrating  the  association between the hub genes and immune infiltration. (A) In GSE147507cohort, CCL20, SELE were revealed to positively correlate with most cell types. Except for CD56dim natural killer cells, CD56bright natural killer cells, memory B cells, and Type 2 T helper cells. (B) In GSE113439 cohort, CCL20, SELE were shown to positively correlate with many cell types. Including: type 1 T helper cell, regulatory T cell, plasmacytoid dendritic cell, neutrophil, natural killer T cell, mast cell, central memory CD4 T cell, activated dendritic cell, and activated CD4 T cell. Red: positive correlation; Blue: negative correlation. (C) According to a Pearson correlation study, plasmacytoid dendritic cells had the highest level of association with CCL20,while Activated dendritic cells had the highest level of linkage with SELE [8]. 

Figure  4  Demonstrating  the  network for TF-gene and TF-miRNA interaction with Common DEGs. (A) They predicted 25 miRNAs and 11 TF-genes interacting with SELE and CCL20 through the Network analyst website. Red nodes: hub genes; blue nodes: miRNA. Green nodes:TF-genes. (B) They showed that among CCL20, miR-1256 and PPARG may be a novel regulatory module in PAH  complicated  with  COVID-19 through the FFL tool [8].

Figure  5  Demonstrating  3D and 2D molecular docking patterns for (A) FENRETINIDE, (B) 1-NITROPYRENE, (C) AFLATOXIN B1 with CCL20 respectively. (D) FENRETINIDE, (E) 1-NITROPYRENE, (F) AFLATOXIN B1 with SELE, respectively [8].

References  

1. The Lancet. Understanding long COVID: A modern medical challenge. Lancet. 398, 725.

DOI : https://doi.org/10.1016/S0140-6736(21)01900-0 (2021).

2. Zeng, H. et al. A new coronavirus estimation global score for predicting mortality during hospitalization in patients with COVID-19. Cardiol. Discov. 2, 69–76.

DOI : https://doi.org/10.1097/CD9.0000000000000052 (2022).

3. Kobusiak-Prokopowicz, M. et al. Cardiovascular, pulmonary, and neuropsychiatric short- and long-term complications of COVID-19. Cells. 11, 3882.

DOI : https://doi.org/10.3390/cells11233882 (2022).

4. Castiglione, L. & Droppa, M. Pulmonary hypertension and COVID-19. Hamostaseologie. 42, 230–238.

DOI : https://doi.org/10.1055/a-1661-0240 (2022).

5. Pagnesi, M. et al. Pulmonary hypertension and right ventricular involvement in hospitalised patients with COVID-19. Heart. 106, 1324–1331.

DOI : https://doi.org/10.1136/heartjnl-2020-317355 (2022).

6. Wesley Milks, M. et al. Risk assessment in patients with pulmonary arterial hypertension in the era of COVID 19 pandemic and the telehealth revolution: State of the art review. J. Heart Lung Transplant. 40(3), 172–182.

DOI : https://doi.org/10.1016/j.healun.2020.12.005 (2021).

7. Farha, S. & Heresi, G. A. COVID-19 and pulmonary arterial hypertension: Early data and many questions. Ann. Am. Thorac. Soc. 17, 1528–1530.

DOI : https://doi.org/10.1513/AnnalsATS.202008-1014ED (2020).

8. Hou, Q., Jiang, J., Na, K. et al. Potential therapeutic targets for COVID-19 complicated with pulmonary hypertension: a bioinformatics and early validation study. Sci Rep 14, 9294 (2024).

DOI : https://doi.org/10.1038/s41598-024-60113-7.