{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Burdorf RM"],"funding":["National Institute of Allergy and Infectious Diseases","UNC Lineberger Comprehensive Cancer Center","NIAID NIH HHS","NCI NIH HHS","National Institutes of Health","NIH HHS"],"pagination":["86-94"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11272071"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["230(1)"],"pubmed_abstract":["<h4>Background</h4>The association between low-frequency human immunodeficiency virus type 1 (HIV-1) drug resistance mutations (DRMs) and treatment failure (TF) is controversial. We explore this association using next-generation sequencing (NGS) methods that accurately sample low-frequency DRMs.<h4>Methods</h4>We enrolled women with HIV-1 in Malawi who were either antiretroviral therapy (ART) naive (cohort A), had ART failure (cohort B), or had discontinued ART (cohort C). At entry, cohorts A and C began a nonnucleoside reverse transcriptase inhibitor-based regimen and cohort B started a protease inhibitor-based regimen. We used Primer ID MiSeq to identify regimen-relevant DRMs in entry and TF plasma samples, and a Cox proportional hazards model to calculate hazard ratios (HRs) for entry DRMs. Low-frequency DRMs were defined as ≤20%.<h4>Results</h4>We sequenced 360 participants. Cohort B and C participants were more likely to have TF than cohort A participants. The presence of K103N at entry significantly increased TF risk among A and C participants at both high and low frequency, with HRs of 3.12 (95% confidence interval [CI], 1.58-6.18) and 2.38 (95% CI, 1.00-5.67), respectively. At TF, 45% of participants showed selection of DRMs while in the remaining participants there was an apparent lack of selective pressure from ART.<h4>Conclusions</h4>Using accurate NGS for DRM detection may benefit an additional 10% of patients by identifying low-frequency K103N mutations."],"journal":["The Journal of infectious diseases"],"pubmed_title":["Impact of Low-Frequency Human Immunodeficiency Virus Type 1 Drug Resistance Mutations on Antiretroviral Therapy Outcomes."],"pmcid":["PMC11272071"],"funding_grant_id":["R01-HD080485","P30 AI050410","R01 AI140970","P30 CA016086","R01-AI40970","P30-AI050410","P30-CA016086"],"pubmed_authors":["Maliwichi M","Swanstrom R","Chagomerana MB","Jumbe A","Zhou S","Wallie S","Long N","Amon C","Li Y","Adams L","Burdorf RM","Tegha G","Hosseinipour MC","Hill CS"],"additional_accession":[]},"is_claimable":false,"name":"Impact of Low-Frequency Human Immunodeficiency Virus Type 1 Drug Resistance Mutations on Antiretroviral Therapy Outcomes.","description":"<h4>Background</h4>The association between low-frequency human immunodeficiency virus type 1 (HIV-1) drug resistance mutations (DRMs) and treatment failure (TF) is controversial. We explore this association using next-generation sequencing (NGS) methods that accurately sample low-frequency DRMs.<h4>Methods</h4>We enrolled women with HIV-1 in Malawi who were either antiretroviral therapy (ART) naive (cohort A), had ART failure (cohort B), or had discontinued ART (cohort C). At entry, cohorts A and C began a nonnucleoside reverse transcriptase inhibitor-based regimen and cohort B started a protease inhibitor-based regimen. We used Primer ID MiSeq to identify regimen-relevant DRMs in entry and TF plasma samples, and a Cox proportional hazards model to calculate hazard ratios (HRs) for entry DRMs. Low-frequency DRMs were defined as ≤20%.<h4>Results</h4>We sequenced 360 participants. Cohort B and C participants were more likely to have TF than cohort A participants. The presence of K103N at entry significantly increased TF risk among A and C participants at both high and low frequency, with HRs of 3.12 (95% confidence interval [CI], 1.58-6.18) and 2.38 (95% CI, 1.00-5.67), respectively. At TF, 45% of participants showed selection of DRMs while in the remaining participants there was an apparent lack of selective pressure from ART.<h4>Conclusions</h4>Using accurate NGS for DRM detection may benefit an additional 10% of patients by identifying low-frequency K103N mutations.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jul","modification":"2025-04-04T02:21:54.981Z","creation":"2025-04-04T02:21:54.981Z"},"accession":"S-EPMC11272071","cross_references":{"pubmed":["39052733"],"doi":["10.1093/infdis/jiae131"]}}