The synthetic opioid fentanyl increases HIV replication and chemokine co-receptor expression in vitro.
Ling KongMohamed Tarek M ShataJennifer L BrownMichael S LyonsKenneth E ShermanJason Tory BlackardPublished in: Journal of neurovirology (2022)
The US is experiencing a major public health crisis that is fueled by the illicit use of synthetic opioids including fentanyl. While several drugs of abuse can enhance viral replication and/or antagonize immune responses, the impact of specific synthetic opioids on HIV pathogenesis is poorly understood. Thus, we evaluated the effects of fentanyl on HIV replication in vitro. HIV-susceptible or HIV-expressing cell lines were incubated with fentanyl. HIV p24 synthesis and chemokine receptor levels were quantified by ELISA in culture supernatants and cell lysates, respectively. Addition of fentanyl resulted in a dose-dependent increase in HIV replication. Fentanyl enhanced expression of the HIV chemokine co-receptors CXCR4 and CCR5 and caused a dose-dependent decrease in cell viability. The opioid antagonist naltrexone blocked the effect of fentanyl on HIV replication and CCR5 receptor levels but not CXCR4 receptor levels. TLR9 expression was induced by HIV; however, fentanyl inhibited TLR9 expression in a dose-dependent manner. These data demonstrate that the synthetic opioid fentanyl can promote HIV replication in vitro. As increased HIV levels are associated with accelerated disease progression and higher likelihood of transmission, additional research is required to enhance the understanding of opioid-virus interactions and to develop new and/or optimized treatment strategies for persons with HIV and opioid use disorder.
Keyphrases
- antiretroviral therapy
- hiv positive
- hiv infected
- hiv testing
- human immunodeficiency virus
- hepatitis c virus
- hiv aids
- men who have sex with men
- public health
- immune response
- chronic pain
- pain management
- south africa
- toll like receptor
- inflammatory response
- bone marrow
- single cell
- mesenchymal stem cells
- binding protein
- artificial intelligence
- deep learning