SynthesisEmerging microbes & infections2025
Deep sequencing reveals underestimated burden of integrase inhibitor resistance mutations in people living with HIV: a global individual patient data meta-analysis.
Synthesis in Emerging microbes & infections, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Genetic Subtypes, Pretreatment Drug Resistance, and Associated Factors Among Individuals Newly Diagnosed With HIV-1 in Zhejiang Province From 2022 to 2024: Cross-Sectional Study.JMIR public health and surveillance · 2026Article
- Two cases of possible transmitted HIV drug resistance to all currently available integrase inhibitors, the Netherlands, 2025.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026Article
- Machine learning quantifies immuno-virological interactions: a TRIPOD+AI compliant prediction model for HIV-1 salvage therapy outcomes.Frontiers in immunology · 2026Article
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Authors and funding
9 authors.
Funding
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Abstract
Integrase strand transfer inhibitors (INSTIs) have emerged as cornerstone agents in global antiretroviral therapy, though growing drug resistance presents clinical challenges. Conventional Sanger sequencing may underestimate the burden of low-frequency variants. This global meta-analysis systematically assesses the actual INSTI resistance burden among people living with HIV (PLWH) through deep sequencing technology. Our comprehensive search across Web of Science, PubMed, Cochrane Library, Embase, and Scopus (PROSPERO ID: CRD42023495535) identified studies utilizing deep sequencing for HIV integrase resistance detection. Through meta-analysis and individual participant data (IPD) analysis using HIVdb (v9.8), we differentiated pretreatment (PDR) and acquired (ADR) drug resistance, quantifying mutation rates, resistance rates, and missed detection across thresholds (above-threshold, high-frequency, low-frequency). The analysis incorporated 40 studies with 46 datapoints involving 10,778 patients. Treatment-naïve PLWH demonstrated above-threshold, high-frequency, and low-frequency mutation rates of 9.92%, 7.29%, and 5.88%, respectively, corresponding to resistance rates of 2.60%, 0.09%, and 3.90%. Treated patients showed elevated mutation rates of 19.02%, 16.64%, and 10.23%, with resistance rates reaching 16.10%, 8.67%, and 6.95%. IPD analysis of 394 mutation-positive individuals revealed 8.52% low-frequency resistance to dolutegravir and bictegravir in treatment-naïve populations, while treated patients exhibited significantly increased intermediate/high-level resistance to first-generation INSTIs, including raltegravir and elvitegravir. Conventional sequencing thresholds missed 3.61% pretreatment and 2.46% acquired drug resistance. These findings demonstrate that deep sequencing reveals substantially underestimated INSTI resistance burdens in PLWH. Although second-generation INSTIs maintain lower resistance rates, cross-resistance risks necessitate clinical vigilance. Optimized resistance surveillance strategies incorporating low-frequency mutation detection offer critical evidence for advancing global HIV control efforts.
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