CROI 2019 Abstract eBook

Abstract eBook

Poster Abstracts

542 COMPARISON OF NEXT-GENERATION SEQUENCING ANALYSIS PIPELINES FOR HIV-1 DRUG RESISTANCE Emma R. Lee 1 , Eric Enns 1 , Neil Parkin 2 , Chanson J. Brumme 3 , Mark Howison 4 , Santiago Avila-Rios 5 , Cheryl Jennings 6 , Gary Van Domselaar 1 , Marc Noguera- Julian 7 , P. Richard Harrigan 8 , Miguel E. Quinones-Mateu 9 , Roger Paredes 7 , Rami Kantor 4 , Paul Sandstrom 1 , Hezhao Ji 1 1 Public Health Agency of Canada, Winnipeg, MB, Canada, 2 Data First Consulting, Belmont, CA, USA, 3 British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada, 4 Brown University, Providence, RI, USA, 5 National Institute of Respiratory Diseases, Mexico City, Mexico, 6 Rush University Medical Center, Chicago, IL, USA, 7 IrsiCaixa Institute for AIDS Research, Badalona, Spain, 8 University of British Columbia, Vancouver, BC, Canada, 9 Case Western Reserve University, Cleveland, OH, USA Background: NGS is a potentially useful tool for HIV-1 drug resistance (HIVDR) testing because of its sensitivity for detecting low abundance drug resistant variants. Many NGS HIVDR data analysis pipelines have been independently developed, with variable outputs and potential discrepancies. Standardization of analytic methods and comparison of pipelines are lacking, yet may impact interpretation and be significant in downstream applications. Methods: We compared the performance of five NGS pipelines using samples from the Sanger-based genotyping proficiency testing administered by the NIAID Virology Quality Assurance (VQA) program. Ten VQA panel specimens were genotyped (protease and reverse transcriptase) by each of six laboratories using their in-house NGS assays. Raw NGS data were processed in each laboratory using one of five different pipelines: HyDRA, MiCall, PASeq, Hivmmer and DEEPGEN (Table 1). All laboratories uploaded their raw NGS and analytic comparisons were performed centrally, including: linear range for AAV frequency (linear regression analysis), analytical sensitivity and specificity, and variation of detected AAV frequencies. Amino acid variants (AAV) detected by at least four of the five pipelines at median frequency ≥1%were considered for subsequent performance assessment. Results: A total of 657 AAVs were detected; median 67 per sample. All pipelines demonstrated good linearity in AAV frequency measurements between 1% and 100%. The pipelines showed an average sensitivity of 99.3% (range: 98.8- 99.8%) and specificity of 94.1% (85.7-99.7%). The majority (473 of 657, 72%) of AAVs were present at frequencies ≥20% and these frequency measurements contained fewer discrepancies as compared to AAVs with median frequencies ≤ 20% (Table 1). Conclusion: Comparison of five different NGS-based HIVDR genotyping analysis pipelines in detection of AAVs present at frequencies ≥20% using VQA panel specimens demonstrated good correlation across pipelines. Specificity was decreased at AAV frequencies ≤20% and more outliers were observed, which may be due to differences in quality control criteria among the pipelines. Findings from this study highlight the need for well-defined quality assurance strategies for NGS HIVDR data processing, especially for low abundance variant reporting.

Monogram BioSciences, San Francisco, CA, USA Background: HIV DNA sequencing was developed to provide HIV antiretroviral resistance information when viral loads are insufficient to permit standard RNA-based sequencing assays, especially when historical resistance tests are unavailable or incomplete. Here we evaluated the results from a large set of specimens submitted for routine HIV DNA resistance testing. Methods: HIV DNA sequencing was performed using an assay that evaluates all of protease and integrase and amino acids 1 – 400 of reverse transcriptase from HIV-1 DNA extracted fromwhole blood. Briefly, target sequences are amplified from genomic DNA using triplicate nested PCR followed by sequencing on the Illumina MiSeq platform. A Bayesian model is applied to assign a probability that individual reads have been modified by APOBEC-induced hypermutation and flagged for removal from the analysis. Variants are reported at a sensitivity level that is equivalent to Sanger sequencing. The list of resistance associated mutations (RAMs) was derived frommultiple sources, avoiding polymorphic positions and low-impact or secondary RAMs. HIV DNA sequence results from >64,000 patient samples submitted for routine testing in the US were included in the analysis. The data were evaluated to assess frequency of RAMS, temporal trends from 2015 to 2018 and associations with gender, age and geography. Results: At least one RAM was identified in 58.6% of specimens with 1, 2, 3 and 4-class RAMs observed in 28.2%, 19.1%, 10.2% and 1.1%, respectively. The most frequent RAMs observed in each class were PI: L90M (7.5%), NRTI: M184V (27.2%), NNRTI: K103N (19.8%), and INI: N155H (1.5%). Common TAMs (M41L, D67N, K70R, T215F/Y) were present in 9 – 13% of specimens. Overall, the prevalence of individual RAMs, as well as samples with any RAMs, was observed to decrease between 2015 and 2018. The prevalence of RAMs was higher in patients under 20 and over 50. Differences across gender and geographic regions were subtle but statistically significant. Conclusion: Analysis of a large set of HIV DNA sequencing test results submitted for routine testing demonstrated that RAMs are commonly identified. Minor differences in the prevalence of RAMs were associated with gender and geographic location. More striking changes were associated with age. Increased prevalence of RAMs was observed in patients over 50 and may reflect increased rates of exposure to multiple regimens. We also noted an increased prevalence of RAMs in patients under 20 that warrants further study. 544 DETECTION OF ARCHIVED MUTATIONS IN PATIENTS INFECTED WITH MULTICLASS RESISTANT HIV-1 Martin Daeumer 1 , Eva Wolf 2 , Markus Bickel 3 , Albrecht Stoehr 4 , Silke Heldwein 2 , Heribert Knechten 5 , Patrick Braun 5 , Stefan Esser 6 , Ivanka Krznaric 7 , Christoph Wyen 8 , Markus Müller 9 , Jürgen Brust 10 , Jan-Christian Wasmuth 11 , Alexander Thielen 12 , Christian Hoffmann 13 1 Deutsche Gesellschaft für Immungenetik, Kaiserslautern, Germany, 2 MVZ Karlsplatz HIV Research and Clinical Care Center, Munich, Germany, 3 Infektiologikum, Frankfurt, Germany, 4 Institute for Interdisciplinary Medicine, Hamburg, Germany, 5 Praxiszentrum Aachen, Aachen, Germany, 6 University Hospital Essen, Essen, Germany, 7 Center for Infectiology, Berlin, Germany, 8 Cologne University Hospital, Cologne, Germany, 9 Gemeinschaftspraxis Schwabstraße, Stuttgart, Germany, 10 Mannheimer Onkologie Praxis, Mannheim, Germany, 11 Bonn University Hospital, Bonn, Germany, 12 Seq-it GmbH & Co KG, Kaiserslautern, Germany, 13 ICH Study Center, Hamburg, Germany Background: Deep sequencing (DS) assays may represent a reproducible approach to analyse HIV-1 mutation patterns in proviral DNA, even at frequencies well below those routinely detectable by population sequencing. DS data on pts with multiple drug resistance-associated mutations (DRMs) and with VS (less than 50 HIV RNA copies) is scarce. Methods: LOWER is a nation-wide study of 243 pts with presence of major DRMs (defined according to Stanford HIVdb v8.6.1) in at least three classes of NRTIs, NNRTIs, PIs or INSTIs. In pts with VS, mutational patterns in proviral DNA (using different cut-offs of 15% and 2% after APOBEC filtering) were compared with cumulative DRMs available from all historical resistance reports. Results: In 195/243 pts who had achieved VS for a median of 8.5 years (range, 0-18.6), a mean of 11.1 DRMs (range, 3-28) were identified. Re-detection rate was highest for NRTI DRMs and lowest for INSTI DRMs. Almost 10% of all DRMs were newly detected with DS, and a lower cut-off of 2% yielded a total of 14.9% additional DRMs (Table 1). However, re-detection rates showed a high inter-class variability even in highly prevalent DRMs (= total prevalence > 10%). Among NRTI DRMs, re-detection rates were highest for T69D/N (77.1%) and M41L (75.4%) and lowest for K65R/E/N (21.1%) and L74V (26.2%). For NNRTIs

Poster Abstracts

543 HIV RESISTANCE–ASSOCIATED MUTATIONS OBSERVED IN CELL- ASSOCIATED DNA SEQUENCING ASSAY Dongmei Yang, Johnny Lai, Suqin Cai, Jonathan Toma, Yuping Tan, Christos Petropoulos, Charles Walworth , Jeannette Whitcomb

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