HIV-1 second-line failure and drug resistance at high-level and low-level viremia in Western Kenya.

OBJECTIVE: Characterize failure and resistance above and below guidelines-recommended 1000 copies/ml virologic threshold, upon second-line failure. DESIGN: Cross-sectional study. METHODS: Kenyan adults on lopinavir/ritonavir-based second-line were enrolled at AMPATH (Academic Model Providing Access to Healthcare). Charts were reviewed for demographic/clinical characteristics and CD4/viral load were obtained. Participants with detectable viral load had a second visit and pol genotyping was attempted in both visits. Accumulated resistance was defined as mutations in the second, not the first visit. Low-level viremia (LLV) was detectable viral load less than 1000 copies/ml. Failure and resistance associations were evaluated using logistic and Poisson regression, Fisher Exact and t-tests. RESULTS: Of 394 participants (median age 42, 60% women, median 1.9 years on second-line) 48% had detectable viral load; 21% had viral load more than 1000 copies/ml, associated with younger age, tuberculosis treatment, shorter time on second-line, lower CD4count/percentage, longer first-line treatment interruption and pregnancy. In 105 sequences from the first visit (35 with LLV), 79% had resistance (57% dual-class, 7% triple-class; 46% with intermediate-to-high-level resistance to ≥1 future drug option). LLV was associated with more overall and NRTI-associated mutations and with predicted resistance to more next-regimen drugs. In 48 second-visit sequences (after median 55 days; IQR 28-33), 40% accumulated resistance and LLV was associated with more mutation accumulation. CONCLUSION: High resistance upon second-line failure exists at levels above and below guideline-recommended virologic-failure threshold, impacting future treatment options. Optimization of care should include increased viral load monitoring, resistance testing and third-line ART access, and consideration of lowering the virologic failure threshold, though this demands further investigation.

HIV diversity and drug resistance from plasma and non-plasma analytes in a large treatment programme in western Kenya.

INTRODUCTION: Antiretroviral resistance leads to treatment failure and resistance transmission. Resistance data in western Kenya are limited. Collection of non-plasma analytes may provide additional resistance information. METHODS: We assessed HIV diversity using the REGA tool, transmitted resistance by the WHO mutation list and acquired resistance upon first-line failure by the IAS-USA mutation list, at the Academic Model Providing Access to Healthcare (AMPATH), a major treatment programme in western Kenya. Plasma and four non-plasma analytes, dried blood-spots (DBS), dried plasma-spots (DPS), ViveST(TM)-plasma (STP) and ViveST-blood (STB), were compared to identify diversity and evaluate sequence concordance. RESULTS: Among 122 patients, 62 were treatment-naïve and 60 treatment-experienced; 61% were female, median age 35 years, median CD4 182 cells/µL, median viral-load 4.6 log10 copies/mL. One hundred and ninety-six sequences were available for 107/122 (88%) patients, 58/62 (94%) treatment-naïve and 49/60 (82%) treated; 100/122 (82%) plasma, 37/78 (47%) attempted DBS, 16/45 (36%) attempted DPS, 14/44 (32%) attempted STP from fresh plasma and 23/34 (68%) from frozen plasma, and 5/42 (12%) attempted STB. Plasma and DBS genotyping success increased at higher VL and shorter shipment-to-genotyping time. Main subtypes were A (62%), D (15%) and C (6%). Transmitted resistance was found in 1.8% of plasma sequences, and 7% combining analytes. Plasma resistance mutations were identified in 91% of treated patients, 76% NRTI, 91% NNRTI; 76% dual-class; 60% with intermediate-high predicted resistance to future treatment options; with novel mutation co-occurrence patterns. Nearly 88% of plasma mutations were identified in DBS, 89% in DPS and 94% in STP. Of 23 discordant mutations, 92% in plasma and 60% in non-plasma analytes were mixtures. Mean whole-sequence discordance from frozen plasma reference was 1.1% for plasma-DBS, 1.2% plasma-DPS, 2.0% plasma-STP and 2.3% plasma-STB. Of 23 plasma-STP discordances, one mutation was identified in plasma and 22 in STP (p<0.05). Discordance was inversely significantly related to VL for DBS. CONCLUSIONS: In a large treatment programme in western Kenya, we report high HIV-1 subtype diversity; low plasma transmitted resistance, increasing when multiple analytes were combined; and high-acquired resistance with unique mutation patterns. Resistance surveillance may be augmented by using non-plasma analytes for lower-cost genotyping in resource-limited settings.

Antiretroviral treatment interruptions induced by the Kenyan postelection crisis are associated with virological failure.

BACKGROUND: Antiretroviral treatment interruptions (TIs) cause suboptimal clinical outcomes. Data on TIs during social disruption are limited. METHODS: We determined effects of unplanned TIs after the 2007-2008 Kenyan postelection violence on virological failure, comparing viral load (VL) outcomes in HIV-infected adults with and without conflict-induced TI. RESULTS: Two hundred and one patients were enrolled, median 2.2 years after conflict and 4.3 years on treatment. Eighty-eight patients experienced conflict-related TIs and 113 received continuous treatment. After adjusting for preconflict CD4, patients with TIs were more likely to have detectable VL, VL >5,000 and VL >10,000. CONCLUSIONS: Unplanned conflict-related TIs are associated with increased likelihood of virological failure.

Detection of HIV-1 minority variants containing the K103N drug-resistance mutation using a simple method to amplify RNA targets (SMART).

The simple method for amplifying RNA targets (SMART) was used to detect K103N, a common HIV-1 reverse transcriptase drug-resistance mutation. Novel amplifiable SMART probes served as reporter molecules for RNA sequences that are captured and separated on a microfluidic platform under zero-flow conditions. Assays were performed both off chip and in a microchip reservoir using a modified version of real-time nucleic acid sequence-based amplification, without the noncyclic phase, and 65°C preheat. A total of 6000 copies/mL of the synthetic sequences were detected within 180 minutes of amplification. Although the sensitivity of research platforms is higher, SMART has the potential to offer comparable sensitivity and speed to commercially available viral load and HIV detection kits. Furthermore, SMART uses an inexpensive, practical, and more accurate isothermal exponential amplification technique. The use of molecular beacons resulted in relatively fast real-time detection (<180 minutes); however, they were also shown to hinder the amplification process when compared with end point detection. Finally, SMART probes were used for modeling of K103N concentrations within an unknown sample. Only 1% of the SMART probes was detected within the wild-type population (6 × 10(8) copies/mL). These results establish the groundwork for point-of-care drug resistance and viral load monitoring in clinical samples, which can revolutionize HIV patient care globally.

Extensive drug resistance in HIV-infected Cambodian children who are undetected as failing first-line antiretroviral therapy by WHO 2010 guidelines.

Antiretroviral therapy in resource-limited settings is monitored clinically and immunologically according to WHO guidelines. Frequent misclassification of virologic failure is reported, mostly in adults, leading to early therapy switch or late failure diagnosis. Pediatric treatment monitoring and resistance data upon first-line failure are limited, particularly when the 2010-WHO pediatric guidelines are used without routine viral load monitoring. We previously reported high treatment failure misclassification rates by pediatric 2010 guidelines in Cambodian children on first-line therapy. Here we determine the extent and patterns of resistance, with yearly viral load and 6-monthly CD4. Drug resistance mutations were determined using the IAS-USA 2011 list. Predicted resistance interpretation was determined with Stanford Database tools. Fifty-one children with available genotypes met inclusion criteria. All but one (subtype B) were CRF01_AE. The most common regimen was stavudine, lamivudine, and nevirapine (96%), taken for a median of 2.2 years. Resistance was seen in 98%; 96% to nucleoside and nonnucleoside reverse transcriptase inhibitors (NRTIs and NNRTIs); 51% with ≥4 mutations. The most common NRTI mutations were 184V/I and 67N and the most common NNRTI mutations were 181C/Y/I/V and 190A/S. A total of 22% had multiresistant mutations and 18% had predicted high-level resistance to subsequent therapy options didanosine, abacavir, etravirine, and tenofovir. In 98% of Cambodian children misclassified as nonfailing first-line therapy by 2010 guidelines, 51% had extensive drug resistance to current and 18% to subsequent antiretroviral therapy. Affordable routine viral load monitoring allowing for early and more accurate treatment failure diagnosis is desperately needed in resource-limited settings.

Prediction of treatment failure using 2010 World Health Organization Guidelines is associated with high misclassification rates and drug resistance among HIV-infected Cambodian children.

BACKGROUND: Antiretroviral therapy (ART) in resource-limited settings (RLSs) is monitored clinically and immunologically, according to World Health Organization (WHO) or national guidelines. Revised WHO pediatric guidelines were published in 2010, but their ability to accurately identify virological failure is unclear. METHODS: We evaluated performance of WHO 2010 guidelines and compared them with WHO 2006 and Cambodia 2011 guidelines among children on ≥6 months of first-line ART at Angkor Hospital for Children between January 2005 and September 2010. We determined sensitivity, specificity, positive and negative predictive values, and accuracy using bootstrap resampling to account for multiple tests per child. Human immunodeficiency virus (HIV) resistance was compared between those correctly and incorrectly identified by each guideline. RESULTS: Among 457 children with 1079 viral loads (VLs), 20% had >400 copies/mL. For children with WHO stage 1/2 HIV, misclassification as failure (met CD4 failure criteria, but VL undetectable) was 64% for WHO 2006 guidelines, 33% for WHO 2010 guidelines, and 81% for Cambodia 2011 guidelines; misclassification as success (did not meet CD4 failure, but VL detectable) was 11%, 12%, and 12%, respectively. For children with WHO stage 3/4 HIV, misclassification as failure was 35% for WHO 2006 guidelines, 40% for WHO 2010 guidelines, and 43% for Cambodia 2011 guidelines; misclassification as success was 13%, 24%, and 21%, respectively. Compared with WHO 2006 guidelines, WHO 2010 guidelines significantly increased the risk of misclassification as success in stage 3/4 HIV (P < .05). The WHO 2010 guidelines failed to identify 98% of children with extensive reverse-transcriptase resistance. CONCLUSIONS: In our cohort, lack of virological monitoring would result in unacceptable treatment failure misclassification, leading to premature ART switch and resistance accumulation. Affordable virological monitoring suitable for use in RLSs is desperately needed.

QColors: an algorithm for conservative viral quasispecies reconstruction from short and non-contiguous next generation sequencing reads.

Next generation sequencing technologies have recently been applied to characterize mutational spectra of the heterogeneous population of viral genotypes (known as a quasispecies) within HIV-infected patients. Such information is clinically relevant because minority genetic subpopulations of HIV within patients enable viral escape from selection pressures such as the immune response and antiretroviral therapy. However, methods for quasispecies sequence reconstruction from next generation sequencing reads are not yet widely used and remains an emerging area of research. Furthermore, the majority of research methodology in HIV has focused on 454 sequencing, while many next-generation sequencing platforms used in practice are limited to shorter read lengths relative to 454 sequencing. Little work has been done in determining how best to address the read length limitations of other platforms. The approach described here incorporates graph representations of both read differences and read overlap to conservatively determine the regions of the sequence with sufficient variability to separate quasispecies sequences. Within these tractable regions of quasispecies inference, we use constraint programming to solve for an optimal quasispecies subsequence determination via vertex coloring of the conflict graph, a representation which also lends itself to data with non-contiguous reads such as paired-end sequencing. We demonstrate the utility of the method by applying it to simulations based on actual intra-patient clonal HIV-1 sequencing data.