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  • The extreme genetic diversity between HIV subtypes has

    2018-10-23

    The extreme genetic trpv1 between HIV-1 subtypes has phenotypic consequences in vitro including differential HIV-1 mRNA transcriptional control (Montano et al., 2000; van et al., 2004), protease activity (Velazquez-Campoy et al., 2001), integration site selection (Demeulemeester et al., 2014), MHC class I downregulation (Mann et al., 2014), and entry efficiency (Marozsan et al., 2005). Overall, subtype C HIV-1 isolates have lower replicative fitness in tissue culture relative to HIV-1 isolates of any other subtype (Abraha et al., 2009; Ball et al., 2003; Arien et al., 2005). Relevance of these in vitro HIV studies to virulence would require comprehensive analyses on the natural history of infections with different HIV-1 subtypes, which could then in turn guide treatment and prevention strategies in the majority of people currently living with HIV-1. Longitudinal and cross-sectional studies in sub-Saharan Africa have suggested different disease courses and treatment outcomes in individuals infected with subtype A, B, C, D and URFs/CRFs (Amornkul et al., 2013; Rainwater et al., 2005; Baeten et al., 2007; Kaleebu et al., 2002; Palm et al., 2014; Kanki et al., 1999; Kiwanuka et al., 2009), the most significant being the faster disease progression and higher rates of treatment failures in subtype D versus subtype A infections (Baeten et al., 2007; Kaleebu et al., 2002; Kyeyune et al., 2013). From 1999 to 2003, over 4400 HIV-negative women in Uganda and Zimbabwe were enrolled in the Hormonal Contraception and the Risk of HIV Acquisition (HC-HIV) Study (Morrison et al., 2007), during which 303 women were identified with incident HIV infection and participated in the Hormonal Contraception and HIV-1 Genital Shedding and Disease Progression among Women with Primary HIV Infection (GS) Study (Morrison et al., 2010; Morrison et al., 2011; Lemonovich et al., 2015). The 76 subtype A, 177 subtype C, 31 subtype D and two URF HIV infected women (286 of 303 women) were followed for an average of 5years, currently the largest natural history cohort of non-subtype B infections. Consistent with WHO recommendations at the time of the study, treatment was provided when HIV-infected participants reached CD4 cell counts below 200/ml on two consecutive tests or were diagnosed with stage IV or advanced III disease (WHO Classification). It should be noted that anti-retroviral therapy (ART) was not yet routinely available in these countries at the start of this study period. This study was designed to monitor immune and viral parameters and to compare these biomarkers of disease progression to country of origin, contraceptive use, infecting subtype, and phenotypic properties of the virus.
    Materials and Methods
    Results
    Discussion By the 1980s, all the HIV-1 subtypes had emerged, were circulating and recombining in the Congo basin as well as spreading to neighboring countries/regions (Tebit and Arts, 2011). Various HIV-1 subtypes were introduced in multiple geographic regions (South Africa, Zimbabwe, Brazil, India, etc) (Arien et al., 2007) by the late 1990s and yet, subtype C HIV-1 rose in prevalence faster than any other subtype in the heterosexual population (<10% in early 1990s to >50% today) (Arien et al., 2007) (Fig. 1). We have previously reported that HIV-1 subtype C isolates had lower replicative fitness in human T-cells and macrophages than other group M subtypes (Abraha et al., 2009; Ball et al., 2003; Arien et al., 2005) but could only speculate that HIV-1 subtype C may cause slower disease progression (Arien et al., 2007). Aside from regions in Brazil, Tanzania, and Kenya, HIV-1 subtype C typically dominates in regional pandemics and does not co-circulate at high frequencies with other HIV-1 subtypes in human populations (Arien et al., 2007). As a consequence, comparing disease progression related to different HIV-1 subtype infections in a single country or region is very difficult. Thus, we screened for and recruited 300 AHI in Ugandan and Zimbabwean women and then followed the natural history of these HIV infections for 5–9years in the absence of treatment. With this cohort in Uganda and Zimbabwe, we have a population of only women, all of Bantu origin, all recruited within AHI (following heterosexual transmission), and finally, representing the subtype A, C and D HIV cohorts for sufficient statistical power to measure differences in disease progression. Independent statisticians at two different institutions (FHI 360 and Case Western Reserve University) analyzed the cohort data presented herein. The 2-fold difference in disease progression between these two countries was not attributable to diet, secondary/opportunistic infections, sexual habits, or age (Lemonovich et al., 2015). Of course, we could not screen for presence or absence of all pathogens, sociodemographic or tribal/population differences but the questionnaires administered by medical officers at each patient visit was trpv1 extensive as was the tests for various clinical chemistries and other health indicators. Examples of the questionnaire and acquired laboratory data is available upon request. We are currently interest in screening the microbiota in the vaginal tract of these women to assess possible difference which may be associated with disease progression but again, we do anticipate differences that segregate by country given the similar diet and diverse human genetics. Of all the parameters tested, only HIV-1 subtypes could clearly delineate differences in the rate of CD4 cell decline in blood. Infection with subtype C HIV-1 resulted in the slowest declines in CD4 T-cell counts (0.489 cells/week) as compared to subtype A (0.781cells/week) and then subtype D HIV-1 infection with the most rapid declines in CD4 T-cell counts (1.231cells/week).