Browsing by Author "Nankya, Immaculate"

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    CCR5 promoter variants among Ugandan HIV-1 elite and viremic controllers: a laboratory ฀ based cross ฀ sectional study
    (Research Square, 2020) Nyiro, Brian; Amanya, Sharon B.; Nabatanzi, Rose; Bayiyana, Alice; Kalazane, Linda I.; Waswa, Francis; Nabulime, Eva; Karara, Daniel; Kabali, Joel; Mboowa, Gerald; Kayongo, Alex; Kateete, David P.; Nankya, Immaculate
    Mechanisms for HIV control among HIV-1 elite and viremic-controllers are not fully understood. In Uganda, Studies have reported individuals who without Antiretroviral therapy have the inherent ability to control HIV progression to AIDS for a period of greater than 5 years. However, reasons for this phenotype are not understood. The study objective was to determine the distribution of CCR5 co-receptor on CD4+ T-cells and its associated promoter variants among HIV-1 elite and viremic-controllers. Methods We isolated CD4+T-cells from PBMCs using EasySep CD4+ T-cell negative selection kit, and stimulated them with anti-CD3 and anti-CD28 for 48 hours. To quantify CCR5 expression, we performed immune-phenotyping using flow cytometry. CCR5 promoter polymorphisms were determined through sanger sequencing. The Kruskal–Wallis and the Mann-Whitney test were used to compare differences in the percentages of CCR5+ CD4+ T-cells and the differences in CCR5 densities on CD4+ T-cells respectively. p values < 0.05 were considered significant. Results The percentage of CCR5+CD4+ T-cells was higher among the non-controllers compared to the controllers although, the difference was not statistically significant; elite and viremic-controllers (p=0.9173), viremic and non-controllers (0.0702), elite and non-controllers (0.6010). Of significance was the CCR5 densities on CD4+ T-cells, which were significantly higher among non-controllers relative to the controllers; elite and viremic-controllers (p=3048), viremic and non43 controllers (P=0.0312), elite and non-controllers (P=0.0210)
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    The Challenge of HIV-1 Antiretroviral Resistance in Africa in the Era of HAART
    (AIDS reviews, 2009) Sendagire, Hakim; Easterbrook, Philippa J.; Nankya, Immaculate; Arts, Eric; Thomas, David; Reynolds, Steven J.
    Antiretroviral therapy programs in Africa are currently providing treatment for almost two million people. The long-term success of large scale antiretroviral therapy programs in sub-Saharan Africa remains uncertain because of the limited information currently available on rates of virologic failure and selection for drug-resistant variants in the different HIV subtypes. This article provides a comprehensive review of the published literature on the prevalence of primary and secondary HIV drug resistance with different subtypes and in various settings across sub-Saharan Africa.
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    Nucleoside Reverse-Transcriptase Inhibitor Cross-Resistance And Outcomes from Second-Line Antiretroviral Therapy in the Public Health Approach: An Observational Analysis within the Randomised, Open-Label, EARNEST trial
    (The lancet HIV, 2017) Paton, Nicholas I.; Kityo, Cissy; Thompson, Jennifer; Nankya, Immaculate; Bagenda, Leonard; Kambugu, Andrew; Kiconco, Mary; Mugyenyi, Peter
    Cross-resistance after first-line antiretroviral therapy (ART) failure is expected to impair activity of nucleoside reverse-transcriptase inhibitors (NRTIs) in second-line therapy for patients with HIV, but evidence for the effect of cross-resistance on virological outcomes is limited. We aimed to assess the association between the activity, predicted by resistance testing, of the NRTIs used in second-line therapy and treatment outcomes for patients infected with HIV. We did an observational analysis of additional data from a published open-label, randomised trial of second-line ART (EARNEST) in sub-Saharan Africa. 1277 adults or adolescents infected with HIV in whom first-line ART had failed (assessed by WHO criteria with virological confirmation) were randomly assigned to a boosted protease inhibitor (standardised to ritonavir-boosted lopinavir) with two to three NRTIs (clinician-selected, without resistance testing); or with raltegravir; or alone as protease inhibitor monotherapy (discontinued after week 96). We tested genotypic resistance on stored baseline samples in patients in the protease inhibitor and NRTI group and calculated the predicted activity of prescribed second-line NRTIs. We measured viral load in stored samples for all patients obtained every 12–16 weeks. This trial is registered with Controlled-Trials.com (number ISRCTN 37737787) and ClinicalTrials.gov (number NCT00988039). Baseline genotypes were available in 391 (92%) of 426 patients in the protease inhibitor and NRTI group. 176 (89%) of 198 patients prescribed a protease inhibitor with no predicted-active NRTIs had viral suppression (viral load <400 copies per mL) at week 144, compared with 312 (81%) of 383 patients in the protease inhibitor and raltegravir group at week 144 (p=0·02) and 233 (61%) of 280 patients in the protease inhibitor monotherapy group at week 96 (p<0·0001). Compared with results with no active NRTIs, 95 (85%) of 112 patients with one predicted-active NRTI had viral suppression (p=0·3) and 20 (77%) of 26 patients with two or three active NRTIs had viral suppression (p=0·08). Over all follow-up, greater predicted NRTI activity was associated with worse viral load suppression (global p=0·0004). Genotypic resistance testing might not accurately predict NRTI activity in protease inhibitor-based second-line ART. Our results do not support the introduction of routine resistance testing in ART programmes in low-income settings for the purpose of selecting second-line NRTIs.
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    Virologic versus immunologic monitoring and the rate of accumulated genotypic resistance to first-line antiretroviral drugs in Uganda
    (BMC infectious diseases, 2012) Reynolds, Steven J; Sendagire, Hakim; Newell, Kevin; Castelnuovo, Barbara; Nankya, Immaculate; Kamya, Moses; Quinn, Thomas C.; Manabe, Yukari C.; Kambugu, Andrew
    Viral load monitoring (VLM) to identify individuals failing antiretroviral therapy (ART) is not widely available in resource-limited settings. We compared the genotypic resistance patterns between clients with VLM versus immunological monitoring (IM).Between 2004–2008, 559 ART naïve clients were enrolled in a prospective cohort, initiated on ART, and monitored with viral load (VL) and CD4+ cell counts every 6 months (VLM group). From February 2008 through June 2009, 998 clients on ART for 36–40 months (corresponding to the follow-up time of the VLM group) at the same clinic and monitored with CD4+ cell counts every 6 months were recruited into a cross sectional study (IM group). Samples from VLM clients at 12, 24 and 36 months and IM clients at 36–40 months with VL > 2000 copies/ml underwent genotypic drug resistance testing.Baseline characteristics were similar. Virologic failure (VL > 400 copies/ml) at 12, 24 and 36 months in the VLM group were 12%, 6% and 8% respectively, and in the IM group 10% at 36–40 months. Samples from 39 VLM and 70 IM clients were genotyped. 23/39 (59%) clients in the VLM group (at 12, 24 or 36 months) compared to 63/70 (90%) in the IM group, (P < 0.0001) had at least 1 non-nucleoside reverse transcriptase mutation. 19/39 (49%) of VLM clients had an M184V mutation compared to 61/70 (87%) in the IM group (P < 0.0001). Only 2/39 (5%) of VLM clients developed thymidine analogue mutations compared to 34/70 (49%) of IM clients (P < 0.0001).Routine VL monitoring reduced the rate of accumulated genotypic resistance to commonly used ART in Uganda.