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    Low-abundance drug resistant variant patterns among HIV-1 patients with virological failure in Uganda

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    Master's Dissertation (6.483Mb)
    Date
    2022-03
    Author
    Namaganda, Maria Magdalene
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    Abstract
    Background: The emergence and spread of antiretroviral drug resistant HIV-1 variants is one of the major factors responsible for therapeutic failure in persons living with HIV (PLWH) as it jeopardizes the efforts to reduce the progression of AIDS. While Sanger sequencing is the conventional method for HIV drug resistance testing, it is unable to detect low-abundance variants. This study aimed to detect as well as study the mutation burden of the HIV-1 variants conferring resistance to first line antiretroviral drugs among HIV-1 patients with virological failure in Uganda. Methods: Blood samples were collected from 60 PLWH on first- line ART to detect for the presence of low-abundance drug resistance variants using NGS of HIV protease and reverse transcriptase genes. Sanger sequencing was performed for all the samples for validation purpose. We used the HyDRA bioinformatics pipeline to analyze for the drug resistance mutations and Stanford HIV drug resistance database for interpretations of the variants. Results: Out of the 60 samples, 58 passed the quality check and were considered for analysis. Low-abundance HIV drug resistance variants were identified in 38 out of the 58 samples (65.5%). Overall, we found 757 variants from the NGS data and 90 variants from the Sanger sequencing data sets. The most prevalent low-abundance variants present in the samples were K65R (65.5%), K14R, K45R, L63P and I64V identified in 63.79% of the samples and I15V, K70R, V77I and L283I identified in 60.3% of the samples. Conclusion: Findings from the study revealed that 65.5% of the sampled population harbored low-abundance HIV-1 variants, most of which were previously reported to cause virological failure and consequently antiviral drug resistance. Key words: HIV, Drug resistance testing, Low-abundance (minority) variants, Sanger sequencing, Next-generation sequencing
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    http://hdl.handle.net/10570/10737
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