Archives

  • 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-07
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • 2024-04
  • 2024-05

    • trpv1 antagonist Like other natural history cohorts rapid di

    2018-10-23

    Like other natural history cohorts, rapid disease progression was observed at a 7–9% frequency regardless of HIV-1 subtype but slow progressors/controllers appeared only in subtype A and C infections. The differential rates of CD4 T-cell declines (D>A>C) was still significant when rapid progressors and controllers were removed from the analyses. We have proposed that a combination of “good” host genetics (e.g. HLA B27 or B57) and infection with HIV of low replicative fitness may result in “elite” HIV control (Lobritz et al., 2011), i.e. a rare condition in Africa but closely approximated by the 13 subtype C infections with no declines in CD4 cell counts and <103copies/ml of virus for >5years of infection (Fig. 3a & f). Based on previous human genetic studies across Africa (Cao et al., 2004; Paximadis et al., 2012; Kijak et al., 2009; McLaren and Fellay, 2015; McLaren and Carrington, 2015) (www.allelefrequencies.net/), we now know that the Bantu population has the greatest genetic trpv1 antagonist of Homo sapiens. Low prevalence of “HIV protective” polymorphisms/alleles in the Shona and Buganda tribes (both Bantu) (e.g. <5% of CCR5Δ32, CCR2a 64I, HLA-B57 and B27) could not explain the dramatic differences in disease progression. Interestingly, there were no significant differences between countries or HIV-1 subtypes in the viral RNA levels at set point or over the course of infection. In our previous report using 188 patients for this cohort and with minimal analyses of follow up (<3years), we observed a slightly higher viral loads at set point in subtype C and D versus A infections (p<0.04, ANOVA) that has not held significance when expanding to the 286 patients in this study (Morrison et al., 2010). Instead, expansion of the cohort size now showed a trend for lower viral load set points in subtype C infections versus A or D (Suppl Fig. 3c). Regardless, it is again important to stress that we did not observe any significant differences in viral load during disease based on infection by specific HIV-1 subtype. Most studies examining disease progression in natural history cohorts are now impossible and unethical based on WHO guidelines for the initiation of cART in all HIV positive patients regardless of CD4 T-cells counts (http://www.who.int/hiv/pub/guidelines/earlyrelease-arv/en/). With the start of this study in 2000, we followed WHO/UNAIDS guidelines to treat with CD4 cell counts ≤200/ml which was controversial because few charities, governments, and international organizations (e.g. WHO, PEPFAR) had rolled out their treatment programs in Africa. During this ten year cohort study, 33% of the participants received treatment at an average of 1500days post-infection. Subtype D infected women were ~1.7-fold more likely to receive treatment than subtype A or C infected women. By modelling the rates of CD4 declines in this natural history cohort, the projected time to reach ≤200/ml or AIDS in these women was 1.3 fold longer with subtype C (estimated mean of 12.3years) than A (9.5years) and 2.0 fold longer with C than subtype D (6.2years). Historical data of subtype B infections in North America and Europe suggest 6–8years as an approximate time to reach AIDS (CD4 T-cells <200/ml) (Munoz et al., 1995; Mellors et al., 1996) but there are no natural history cohorts from diagnosis (prior to treatment) to establish accurate estimates. Interestingly, despite (i) different geographical regions, (ii) different human populations, and (iii) higher rates of parasitic and other co-morbities in Uganda, infections with subtype B in North America and D in Uganda may have similar rates of CD4 T-cell declines and time to AIDS. Subtype B and D HIV-1 share the most sequence homology of all subtypes and several studies suggest that subtype B was a sub-branch and “member” of subtype D super-cluster. Earlier reports have also described faster disease progression and reduced response to treatment in East Africans infected with HIV-1 subtype D than subtype A (Baeten et al., 2007; Kaleebu et al., 2002; Kyeyune et al., 2013).