CROI 2019 Abstract eBook
of U=U on dismantling HIV related stigma; importance of ‘language matters’ when communicating the U=U science; and the impact of U=U on the sexual and reproductive lives of PLHIV. Community concerns discussed include the continued resistance to sharing the message, limited updates to existing resources to reflect the U=U science; questions about breastfeeding and syringe sharing; concerns with unequal access to testing, treatment and care; and concerns with stigmatizing and criminalizing people living with HIV who are not virally suppressed. Personal stories of PLHIV and examples of the campaign are shared to illustrate the main points. 119 MORE THAN U: MAXIMIZING POPULATION-LEVEL EFFECTS OF U=U Andrew E. Grulich , University of New South Wales, Sydney, NSW, Australia At the population level, U=U is part of HIV treatment as prevention. HIV treatment as prevention explicitly includes the goals of increasing HIV testing, HIV treatment, and undetectable viral load. In 2014, UNAIDS released its 90/90/90 goals with the dual aims of improving the health of people living with HIV and reducing HIV transmission to lead to the end of the AIDS epidemic. The 90/90/90 goals are based in part on modelling of the preventive effects of HIV treatment as prevention in an African heterosexual epidemic. Several pragmatic population-based trials of HIV treatment as prevention are underway in sub-Saharan Africa, and observational evidence provide strong evidence that treatment roll-out has been associated with reduced HIV transmission in some settings. In epidemics where transmission among men who have sex with men (MSM) predominates, transmission dynamics are substantially different, and it is likely that achieving the 90/90/90 goals may not be enough, on its own, to end the HIV epidemic. U=U is a vital part of combination prevention, and effects are maximised where it is combined with ensuring early HIV diagnosis. The treatment as prevention. 120 THE CHALLENGES OF HIV TREATMENT IN AN ERA OF POLYPHARMACY David Back , University of Liverpool, Liverpool, UK The prevalence of HIV-infected people aged 50 years or older is increasing rapidly and this population often exhibits a higher number of comorbidities and other age-related conditions at a younger age than in the general population. Numerous cohort studies (eg NA-Accord, EuroSIDA, DatAIDS, GEPPO, PODIVM, MACS, US Veterans Affairs, POPPY; SHCS) have highlighted the increasing burden of co-morbidities in older PLWH with some studies describing the prevalence of polypharmacy (most often described as more than 5 co-medications) to be >40%. With polypharmacy comes the inevitable consideration of drug-drug interactions (DDIs). So we need to understand i) the mechanisms of DDIs (which are not always CYP-mediated!), ii) the difference in DDI potential of the currently recommended antiretroviral agents and iii) the clinical relevance of DDIs. We always need to be aware of the unexpected! The prescribing information or label of a drug is often the primary source of DDI awareness. But the labels cover a limited number of specific DDIs and not infrequently there are differences between the US Prescribing Information and the European SmPC or country specific information which may confuse. Therefore health care professionals often rely on other sources (websites, apps) for their daily management of DDIs. With commonly used co-medications it may be necessary to: change or modify the dose of a co-medication, change the ARV, modify the dose of the ARV or take care with the timing of administration. However it is also important to take care that co-meds are not under dosed. As we look to the future, we need research programs to determine the impact of eliminating medications not essential for quality of life and survival for those aging with HIV (ie de-prescribing). We also need to face the challenge of DDI studies with long acting ARVs – currently injectable and implants. However there are other emerging technologies and with all long acting medicines there will be an important role for PBPK modelling in generating DDI data in virtual patients. Ronald Swanstrom , University of North Carolina at Chapel Hill, Chapel Hill, NC, USA HIV-1 can be detected in the brain/CNS, and more conveniently in cerebral spinal fluid (CSF), at all times after infection. Its presence reflects a number of processes ranging from the trafficking of infected T cells through the establishment of an independently replicating population (compartmentalization) where the virus has evolved to infect a host cell with a low density of CD4 (CD4 low phenotype). A deeper understanding of these multiple processes has come from a clearer definition of viral entry phenotypes. 121 NEUROHIV: WHAT THE VIRUS TELLS US
A common misconception in the HIV-1 field is that all viruses that use CCR5 (R5 viruses) are macrophage-tropic. In fact, macrophage-tropic/ viruses, with their ability to enter cells with a low density of CD4 (as seen on macrophages), are rarely found in the blood and have not been detected among transmitted/ founder viruses. The main form of HIV-1 found in the blood, and the form that enters the CNS by trafficking in infected T cells, uses CCR5 but requires a high density of CD4 (as is seen on CD4+ T cells) for efficient entry; this predominant form of HIV-1 is more appropriately called R5 T cell-tropic. This clearer understanding of HIV-1 entry phenotypes has allowed a reassessment of when and where macrophage-tropic/CD4 low viruses evolve and their role in pathogenesis. Earlier studies highlighted the detection of CD4 low viruses in the CNS and their link to severe CNS disease at late stages prior to death, such as HIV-associated dementia (HAD). The evolution of macrophage-tropic viruses can be viewed as an evolutionary path the virus follows when its target CD4+ T cells become limiting, a situation that is especially common behind the blood-brain barrier in the CNS. Persistent viral infection in the brain is likely to be very different from infection of CD4+ T cells in tissues such as lymph nodes, spleen, and GALT. The question of viral escape in the CNS during suppressive therapy, either transient or persistent, can now be addressed in the context of viruses that are adapted to replication in this environment. Similarly, rebound virus in the CSF after treatment interruption may provide insight into the presence of compartmentalized reservoirs. 122 BRAIN CONNECTIVITY IN NEUROLOGICALLY ASYMPTOMATIC PEOPLE WITH HIV SWITCHING ART Jaime H. Vera 1 , Sofia Toniolo 1 , Mara Cercignani 1 , Borja Mora-Peris 2 , Jasmini Alagaratnam 2 , Jonathan Underwood 2 , Marta Boffito 3 , Mark Nelson 3 , Alan Winston 2 1 Brighton and Sussex Medical School, Brighton, UK, 2 Imperial College London, London, UK, 3 Chelsea and Westminster Hospital, London, UK Background: Central nervous system (CNS) toxicities of antiretroviral therapies are well described. Functional MRI (fMRI) can assess brain activity and functional connectivity (FC) non-invasively, providing insights into pathogenic mechanisms. We assessed changes in fMRI patterns in neurologically asymptomatic people with HIV (PWH) participating in two studies assessing CNS parameters when switching antiretroviral therapy. Methods: Virologically suppressed PWH switching from tenofovir-DF/ emtricitabine (TDF/F) with efavirenz to rilpivirine (n=10) and TDF/F with raltegravir to dolutegravir (n=12) were included. Changes in CNS parameters included patient-reported outcome measures (PROM) of sleep (PSQI) and depression (HADS). fMRI imaging was assessed at baseline and at least 120 days after switching therapy and included resting-state fMRI (RS-fMRI) and behavioral stop signal reaction times (SSRT) task fMRI. Resting state and SSRT fMRI were examined by independent component analyses (ICA) using the FSL’s MELODIC tool. Results: Of 22 participants, all were male, median age (range) was 49 (33-71) years, median CD4+count (range) was 700 (339-1164) cells/uL and HIV RNA was less than <20 copies/mL in all. Switching from efavirenz to rilpivirine was associated with enhanced connectivity of the Dorsal Attention Network (DAN) most pronounced in the right superior parietal lobule and a reduction in stop SSRTs (response inhibition, p=0.025, see figure) which was positively correlated with the duration of time previously on efavirenz (median 5 (range 1-10) years, p=0.02). Switching from raltegravir to dolutegravir was associated with increased connectivity in the DAN, sensory-motor (SM), and associative visual (VISAS) networks. There was a 4.8% decline in anxiety scores on HADS and a 2% decline in sleep symptoms on PSQI, with scores of 19 and 14, and 22 and 20 at baseline and follow-up, respectively, after switching from efavirenz to rilpivirine (p<0.005) and no significant changes in PROMS when switching from raltegravir to dolutegravir. No association between changes in fMRI and PROMs were observed. Conclusion: In PWH switching antiretroviral therapy, changes in fMRI are evident. This was most pronounced in PWH switching from efavirenz to rilpivirine where improved attention and response inhibition on fMRI was evident. Whilst changes were evident on fMRI when switching integrase inhibitor, any clinical implications of these findings require further validation.
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