A23 Identification of HIV drug resistance mutation patterns using illumina MiSeq next generation sequencing in patients failing second-line boosted protease inhibitor therapy in Nigeria

There is limited information of patterns of protease inhibitor (PI) resistance in adults failing second-line therapy. Next generation sequencing (NGS) detects drug resistance mutations as low as 1%. However, the clinical implications of these minority variants to treatment outcomes are still in debate. Approximately 5% of antiretroviral treatment (ART) exposed patients in our treatment program are on second-line boosted protease inhibitor (PI). Population-based sequencing conducted on some of these patients revealed no major HIV drug resistance mutations (DRMs) to PIs. We compared population-based sequencing and NGS results with the view of identifying patterns of drug resistance mutations and minority variants. Forty-eight plasma samples from 40 patients on second-line NRTI/NNRTI and boosted PI regimens with evidence of virologic failures (VL ≥1,000 copies/ml) were used in this study. Of these, eight were obtained at the time of first-line failure while the remaining 40 at the time of second-line failure. Ultra-deep sequencing sample preparation was achieved using Illumina Nextera XT protocol. This required that target amplicon be subjected to fragmentation, tagging, indexing, size exclusion bead purification, normalization, and pooling. MiSeq data analysis was performed using the Geneious software by applying 1% cutoff at major drug resistance sites. Electropherogram data were generated using ABI 3130 genetic analyzer and analysis performed using Stanford Genotyping Resistance Interpretation Algorithm available at http://sierra2.stanford.edu/sierra/servlet/JSierra and IAS-USA 2015 Drug Resistance Interpretation list. MiSeq sequencing showed that 53% (n = 23) of the patients developed PI resistance, 93% (n = 40) had NRTI resistance, and 70% (n = 30) had NNRTI resistance. Of the DRMs detected in protease, L90M mutation was the most common mutation (28%, n = 12) followed by L76V (21%, n = 9), then I47V (7%, n = 3) and I84V (7%, n = 3). Among the NRTI associated mutations L74V was the predominant mutation (77%, n = 33) followed by M184V/I (60%, n = 26) then TAMS (51%, n = 22). Of these, 33% of patients (n = 14) showed NRTI + NNRTI mutations, 39% (n = 17) showed NRTI + NNRTI + PI mutations, 7% (n = 3) showed NRTI + PI mutations, whereas 21% (n = 9) and 2.3% (n = 1) exclusively showed NRTI and NNRTIs mutations respectively. Twenty-eight samples that had both MiSeq and Sanger sequencing data were available for a comparison of mutational patterns in the PI region. Miseq sequencing revealed minority PI mutations in 10 samples that were wild type by Sanger sequencing and one sample showed mutations in both Sanger and NGS. The ten samples revealing mutations based on MiSeq data comprised of minority variants including L90M (50%, n = 5), L76V (20%, n = 2), I50V (10%, n = 1), and N88S (20%, n= 2). Our data suggest that even in the absence of PI mutations based on Sanger data, those minority variants can be present. NGS revealed the presence of PI resistance mutations in patients who had wild-type using population-based sequencing. Given that patient regimen revealed that minority variants were unlikely selected by ART pressure, our results suggest poor adherence as the likely contributor to second-line failure due to the high genetic barrier of PIs. Since ART adherence in these patients was monitored using clinico-immunological parameters and virological tests only when treatment failure was suspected, our results suggest the need for routine virological monitoring. This should provide early opportunity for adherence intervention and thereby avoiding the need for switch to salvage or third-line treatment options, which is more expensive and not readily available in our setting.