ETD Collection
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Item In vitro HIV-1 drug resistance phenotyping, genotyping and novel virological failure detection tools for clinical patient management.(2014-03-28) Bronze, Michelle SaltaoOf the 22.5 million individuals infected with the human immunodeficiency virus (HIV) in sub-Saharan Africa, 62% of patients requiring treatment had access to highly active antiretroviral therapy (HAART) in 2011. The delivery of HAART and the appropriate laboratory monitoring of HIV positive individuals in sub-Saharan African countries has become a public health priority, an intervention which has and will continue to dramatically reduce HIV-related morbidity and mortality. Routine laboratory monitoring of HIV infected individuals should ideally include CD4+ T cell testing to assess when to start ART, viral load monitoring to assess virological failure on ART and when indicated, HIVDR genotyping.However, this is often not implemented in resource limited settings due to challenges such as inadequate infrastructure and laboratory capacity, amongst others. Thus the Affordable Resistance Testing for Africa (ART-A) initiative was established to develop an affordable HIV drug resistance testing (HIVDR) algorithm applicable to Africa. The objective of this study was to evaluate the role of in vitro HIVDR phenotyping in the context of HIV-1 subtype C (the most prevalent circulating subtype in sub-Saharan Africa), genotyping and genotypic interpretation tools using existing algorithms, as well as novel virological failure detection tools for clinical patient management. Current gold standard HIVDR phenotyping technologies use an HIV-1 subtype B backbone to create recombinant viruses with patient-derived polymerase (protease and partial reverse transcriptase). This backbone could impact on the in vitro phenotyping results of non-B subtypes, and therefore it was deemed necessary to establish the applicability of HIVDR phenotypic testing of subtype C polymerase when a commercially available subtype B backbone is used. One hundred and fourteen HIV-1 subtype C samples were HIVDR phenotyped against 17 antiretroviral drugs using both subtype B and C backbones and showed a high level of concordance between the two backbone phenotypic resistance profiles (95.8%; 1590 of 1660 fold change comparisons). Natural assay variability was largely responsible for discordant results. Results confirmed that HIV-1 phenotypic reverse transcriptase inhibitor drug resistance test interpretation is independent of the virus backbone subtype. No conclusions could be made for protease inhibitor resistance since limited samples from 2nd line failure were available. Subsequently, the HIVDR genotypic and phenotypic results of the 114 patient samples were compared to determine whether genotyping is a viable alternative to phenotyping. Results showed a 92.3% concordance between genotyping and phenotyping of individual drug comparisons for a number of HIVDR profiles. Discrepancies were attributed to phenotypic assay variability in addition to the role of mutation mixtures, which impacted genotypic interpretations. Overall, HIVDR genotyping is a reliable tool to detect and interpret antiretroviral drug resistance in HIV-1 subtype C infected patients, and can thus be used for clinical patient management. Once the accuracy of HIVDR genotyping was established, the development, validation and evaluation of a potential virological failure assay (ARTA-VFA) and a simplified HIVDR (ARTA-HIVDRultralight) assay was undertaken. A simplified and conceptually novel approach using a qualitative viral load assay with a pre-determined cut-off that gives a threshold above which virological failure (VF) could be confirmed and below which treatment success was likely, was tested. A real-time PCR (ARTA-VFA) assay was developed which involved the amplification of a short sequence of the HIV-1 LTR region from RNA extracted either from plasma and/or dried blood spots (DBS). The ARTA-VFA was tested on 409 patient samples,and successfully amplified samples from all major HIV-1 group M subtypes with equal specificity. The VF was qualitatively classified as a viral load >1000 RNA copies/ml in plasma samples, and >5000 RNA copies/ml in DBS samples. Comparative testing yielded accurate VF determination for therapy-switching in approximately 93% of clinical cases tested, compared to current gold standard quantitative viral load assays. A simplified HIVDR genotyping assay (ARTA-HIVDRultralight) targeting the region of RT harboring all major RT inhibitor resistance mutation positions, thus providing all relevant susceptibility data for first-line regimen failures was developed and assessed. The ARTAHIVDRultralight assay was designed to be practical, faster, and more affordable, show flexibility with respect to equipment (open platform), use DBS or plasma as starting material and amplify and sequence a smaller amplicon (RT). The assay performed well when compared to the in-house assay used in the laboratory at the time for both 212 plasma and 25 DBS samples, yielding identical mutations and subsequent resistant profiles. Furthermore, a theoretical in silico exercise to investigate the consequences of using 125,329 shortened RT genotype (ARTA-HIVDRultralight) as compared to full-length RT sequences showed >95% and >90% concordance when using the Stanford HIVdb algorithm and the virco®TYPE tool, respectively. Differences noted were minor and unlikely to have any impact on clinical decision-making. Overall, this study illustrated that the short RT sequences can be reliably used to generate HIVDR genotypes using the Stanford HIVdb and virco®TYPE algorithms and reduce sequencing costs substantially. A field evaluation using the ARTA-VFA and ARTA-HIVDRultralight on 288 clinical samples was conducted, showing that the accuracy and precision of both assays (using 248 plasma or 40 DBS sampling methods) compared well to the reference methodology, thereby extending access of testing to more remote settings.These assays were designed to either be used as a testing strategy of initially assessing VF,and once confirmed performing an HIVDR assay, or alternatively to be used separately as stand-alone, or within different laboratory tiers in resource limited settings. It is envisaged that the ARTA-VFA could be used in the middle laboratory tier, and if confirmatory, patient samples can be referred to a reference laboratory with the available infrastructure for HIVDR testing using the ARTA-HIVDRultralight. Lastly, an automated sequence analysis and editing software for use in correct base calling of nucleotide/mutation mixtures in HIVDR genotyping was validated on 1624 sequences. Compared to reference software, where interpretation is often operator dependent, this software performed extremely well, with minor discrepancies noted. The automated software can be used to reduce subjectivity, time taken for analysis which is often the rate-limiting step and thus improving the turn-around time and clinical relevance of HIVDR genotyping. Overall, the results obtained describe the validation of using HIVDR genotyping as an alternative tool to phenotyping, and the subsequent development and validation of simple, affordable, "open-platform" alternatives to currently used methods for virological failure monitoring, and accommodate a centralized approach to HIVDR with DBS testing in resource limited settings.Item Predictors of weight loss in HIV-infected women on antiretroviral therapy in Rwanda.(2014-03-28) Kimenyi, Jean PaulBackground: Highly Active Antiretroviral Treatment (HAART) has reduced the frequency of weight loss/wasting associated with HIV infection. However, weight loss remains a problem, even in the HAART era. Objectives: This study was carried out to assess weight change in a cohort of HIV-infected women on HAART in Rwanda, from 2005 to 2008, and to identify factors that predict weight loss in this cohort. Methods: Data from a cohort of 449 HIV-positive women on HAART enrolled in the Rwanda Women’s Inter-association Study and Assessment (RWISA), starting in May 2005, and followed at six monthly intervals until December 2008, were analysed. The outcome assessed in this study was change in weight, measured in kilograms at 6, 12 and 24 months after HAART initiation. Nutritional status was recorded and laboratory measurements (weight, height and CD4 cell count) were taken prior and after HAART initiation. All covariates were time dependent, except for the history of weight loss which was recorded at baseline only. Generalized Estimating Equation (GEE) using the linear link (Gaussian [normal]), exchangeable covariance structure and robust standard error was used to assess the factors associated with changes in weight (weight loss or weight gain) and to control for potential confounders. Results: Prior to HAART initiation, the mean weight of the study participants was 53.1 kg (SD 9.5). The mean BMI was 21.3 kg/m2 (SD 3.6) and the mean CD4 cell count was 222.9 cells/μL (SD 120.6) [47.6% had CD4 cell counts <200 cells/μL, 52.2% had CD4 cell counts ≥200 cells/μL]. Overall, the participants gained weight from baseline to 12 months after HAART initiation. The mean weight change was 1.9 kg (SD 7.8) (p<0.001) 6 months after HAART initiation, 2.9 kg (SD 5.9) (p <0.001) 12 months after HAART initiation, and 2.4 kg (SD 6.5) (p <0.001) 24 months after HAART initiation. Six months after HAART initiation, 48.3% of participants had gained weight, and 21.0% had lost weight. Twelve months after HAART initiation, 56.9% had gained weight, and 18.3% had lost weight, Twenty-four months after HAART initiation, 56.6% had gained weight, and 22.6% had lost weight. Participants with CD4 cell counts ≤ 200 cells/μL at baseline gained more weight than those with CD4 cell counts > 200 cells/μL at 6, 12 and 24 months after HAART initiation. Participants who were underweight (BMI <18.5 kg/m2) at baseline gained more weight than other participants three months after HAART initiation. Time-dependent diarrhoea for more than two weeks and a CD4 cell count of 200 - 350 cells/μL were significantly associated with weight loss (p≤ 0.05). Others factors, such as time-dependent education level (completion of secondary school), marital status (married legally and status other than married legally or widowed), and increases in CD4 cell counts, were associated with weight gain (p≤ 0.05). Conclusion: Although the majority of participants gained weight during the first 12 months of being on HAART, a significant proportion of participants lost weight while on HAART. The findings on the predictors of weight change in HIV-positive women on HAART can be used to promote weight gain in women who start HAART. Clinicians who take care of HIV-infected patients on HAART should pay attention to those who lose weight, and those who present with diarrhoea or with CD4 cell counts of <350 cells/μL at follow-up visits, since these factors are associated with weight loss in the HAART era.