The DNA Damage Response and HIV-Associated Pulmonary Arterial Hypertension.
Ari SimenauerEva Nozik-GrayckAdela Cota-GomezPublished in: International journal of molecular sciences (2020)
The HIV-infected population is at a dramatically increased risk of developing pulmonary arterial hypertension (PAH), a devastating and fatal cardiopulmonary disease that is rare amongst the general population. It is increasingly apparent that PAH is a disease with complex and heterogeneous cellular and molecular pathologies, and options for therapeutic intervention are limited, resulting in poor clinical outcomes for affected patients. A number of soluble HIV factors have been implicated in driving the cellular pathologies associated with PAH through perturbations of various signaling and regulatory networks of uninfected bystander cells in the pulmonary vasculature. While these mechanisms are likely numerous and multifaceted, the overlapping features of PAH cellular pathologies and the effects of viral factors on related cell types provide clues as to the potential mechanisms driving HIV-PAH etiology and progression. In this review, we discuss the link between the DNA damage response (DDR) signaling network, chronic HIV infection, and potential contributions to the development of pulmonary arterial hypertension in chronically HIV-infected individuals.
Keyphrases
- pulmonary arterial hypertension
- hiv infected
- antiretroviral therapy
- dna damage response
- pulmonary hypertension
- human immunodeficiency virus
- pulmonary artery
- hiv positive
- polycyclic aromatic hydrocarbons
- hiv aids
- dna repair
- end stage renal disease
- randomized controlled trial
- induced apoptosis
- newly diagnosed
- chronic kidney disease
- sars cov
- transcription factor
- single cell
- hepatitis c virus
- patient reported outcomes
- peritoneal dialysis
- computed tomography
- endoplasmic reticulum stress
- magnetic resonance
- mesenchymal stem cells
- human health
- dna damage
- drug induced
- signaling pathway
- climate change
- single molecule
- network analysis
- bone marrow