Low prevalence of transmitted drug resistance among newly diagnosed HIV-1 patients in Latvia

Transmitted drug resistance (TDR) is a concern because it may reduce the efficacy of antiretroviral treatment. Plasma samples of 119 HIV-1-infected patients who were newly diagnosed at the Infectology Center of Latvia in 2005 and 2006 were analyzed by an in-house genotypic resistance assay to determine the prevalence of TDR in Latvia. TDR was identified using the WHO 2009 list of mutations for surveillance of TDR as implemented in the Stanford Calibrated Population Resistance tool. Neighbor-joining phylogenetic analyses were used to determine genetic subtype and investigate the relatedness of the sequences. Resistance testing was successful in 117 of 119 patients. The study population represented ～20% of all patients that were diagnosed in Latvia in 2005 and 2006 and was well distributed between gender, transmission routes, and areas of residence. Four patients showed evidence of TDR, which represents a prevalence of TDR of 3.4% (95% CI: 0.9-8.5%). All four patients displayed single, but different resistance mutations (M46I, F53L, M41L, and G190A). All patients, except one, were predicted to respond well to standard first-line therapy in Latvia. The prevalence of TDR in Latvia was low, which partly may be due to the low proportion of HIV-1 patients who receive antiretroviral therapy. The results indicate that routine resistance testing in Latvia currently should be focused on patients who display treatment failure, rather than treatment naive patients.     

Transmitted drug resistant HIV-1 and association with virologic and CD4 cell count response to combination antiretroviral therapy in the EuroSIDA Study

OBJECTIVES: To investigate prevalence of transmitted drug-resistant human immunodeficiency virus (TDR) and factors associated with TDR and to compare virological and CD4 count response to combination antiretroviral therapy. METHODS: In this study, 525 mostly chronically infected EuroSIDA patients were included who had genotypic resistance tests performed on plasma samples collected while antiretroviral therapy naive. TDR was defined as at least one resistance mutation from a list proposed for genotypic TDR surveillance. Multivariable logistic regression was used to analyze factors associated with detection of TDR, with virological (viral load<500 copies/mL) and CD4 count response (>or=50% increase) to combination antiretroviral therapy at months 6-12. RESULTS: The overall prevalence of TDR was 11.4%, which was stable over 1996-2004. There were no significant differences in virological suppression (those resistant to at least one drug prescribed versus susceptible), adjusted odds ratio: 0.68 (95% confidence interval: 0.27 to 1.71; P=0.408) or CD4 count response, adjusted odds ratio: 1.65 (95% confidence interval: 0.73 to 3.73; P=0.231). CONCLUSIONS: Prevalence of TDR in antiretroviral-naive patients was found to be in line with other European studies. No significant differences were found in virological and CD4 count response after initiation of first-line combination antiretroviral therapy between resistant and susceptible patients, possibly due to the small number of patients with resistance and consequently low power.     

Marked decrease in acquired resistance to antiretrovirals in latest years in Italy

ObjectivesThe aim of this study was to evaluate acquired drug resistance in Italy in the 2009–2018 period.MethodsWe analysed 3094 patients from the Italian ARCA database who had failed antiretroviral treatment and who had received a genotypic test after 6 months of treatment. Drug resistance mutations were identified using International AIDS Society (IAS)-USA tables and the Stanford HIVdb algorithm. The global burden of acquired resistance was calculated among all subjects with antiretroviral failure. Time trends and correlates of resistance were analysed using standard statistical tests.ResultsPatients of non-European origin and non-B subtypes increased significantly from 11.5% (103/896) to 19.2% (33/172) and from 13.1% (141/1079) to 23.8% (53/223), respectively, over time. Overall, 14.5% (448/3094), 12.1% (374/3094) and 37.8% (1169/3094) of patients failed first, second and later lines, respectively. According to both IAS and HIVdb, in the study period resistance to any class, nucleoside reverse inhibitor, non-nucleoside reverse inhibitor, and protease inhibitors (PIs) declined significantly. Integrase strand transfer inhibitor (INSTI) resistance declined significantly from 31% (36/116) to 20.8% (41/197) according to HIVdb but not to IAS. Divergent data were highlighted regarding the proportion of non-European patients carrying any, PI and INSTI resistance using IAS tables compared with the Stanford HIVdb algorithm, as the former failed to detect a decrease in resistance while the latter indicates a reduction of 1.6-, 5- and 1.8-fold resistance for such drug classes. In the multivariate analysis, the risk of resistance increased in patients with a larger number of treatment lines and higher viraemia and decreased in those starting therapy in the last biennium of the study.DiscussionA marked reduction in drug resistance was observed over 10 years, compatible with higher genetic barrier and potency of new antiretrovirals. Nonetheless, concerns remain for subjects with non-B subtypes when using mutation lists instead of interpretation systems because of the extensive polymorphism of the protease region.     

北京市2016年新确证未治疗HIV感染者传播性耐药突变研究

目的 分析北京市2016年新确证HIV感染者HIV病毒pol基因传播性耐药突变特征.方法 利用一步法逆转录PCR和巢式PCR扩增感染者体内HIV病毒的pol基因,并对扩增产物进行测序.对得到的序列信息进行分析,分别获得病毒的亚型分布、耐药突变类型和构成.结果 2016年北京市新确证HIV感染者传播性耐药突变比例为4.2％.712名感染者中,CRF01_AE亚型为主要流行亚型,占49.3％,CRF07_BC亚型占28.8％,B亚型占10.3％.结论 与往年的研究相比,北京市未治疗的HIV感染者耐药率有所下降,总体上属于低水平的HIV耐药流行.     

Resistance to antiretroviral therapy among patients in Uganda

OBJECTIVE: To characterize HIV-1 phenotypic resistance patterns and genotypic mutations among patients taking antiretroviral medications in Uganda. METHODS: We reviewed charts and retrieved archived plasma specimens from patients at an AIDS specialty center in Uganda where antiretroviral therapy has been used since 1996. Phenotypic and genotypic resistance testing was done on specimens associated with a viral load of 1000 copies/ml. RESULTS: Resistance testing of specimens was completed for 16 patients. Among 11 specimens collected before initiation of antiretroviral therapy, no phenotypic resistance or primary genotypic mutations were found. Among 8 patients taking lamivudine, phenotypic resistance was found for 9 (90%) of 10 specimens and was associated with an M184V mutation in all nine cases. Among 12 patients taking zidovudine, no phenotypic resistance and few primary mutations were found. For 6 patients who were receiving protease inhibitors, we observed no phenotypic resistance and only one primary genotypic mutation associated with resistance. CONCLUSIONS: The absence of apparent resistance among samples collected before antiretroviral therapy supports the notion that a similar approach to selection of antiretroviral therapy can generally be used against non-B subtypes. A genotypic marker of antiretroviral resistance to lamivudine in HIV-1 subtypes A, C, and D was similar to those in subtype B infections. These results suggest that the methods used for monitoring for the emergence of drug resistance in antiretroviral programs in Africa may be similar to those used in developed settings.     

Phylogenetic investigation of transmission pathways of drug-resistant HIV-1 utilizing pol sequences derived from resistance genotyping

OBJECTIVES: To investigate the nature of transmission links existing between patients recently infected with HIV strains containing transmitted drug resistance (TDR) mutations. METHODS: Virus from 63 individuals recently infected with HIV-1 containing TDR mutations was analyzed phylogenetically to determine virological links. Phylogenetic trees were reconstructed using maximum likelihood and distance-based methods. Monophyletic clusters detected on the basis of pol sequences were confirmed using env and gag sequences. Potential bias caused by the presence of drug resistance mutations was assessed by reanalyzing the pol sequence set after the omission of 16 drug resistance codons identified in the TDR population. RESULTS: Phylogenetic analysis revealed 9 apparent transmission clusters involving 24 of the 63 (38%) TDR patients. Each cluster was supported by high bootstrap values and low intracluster genetic distances. The 9 transmission clusters were confirmed in separate analyses using env and gag sequences and in pol sequences after the removal of codons associated with drug resistance. CONCLUSIONS: Pol sequences generated during baseline resistance genotyping for newly HIV-infected patients provide the opportunity for real-time phylogenetics to identify sources of multiple HIV transmission events. This study demonstrated the existence of several distinct clusters of patients whose TDR strains were linked. Several discrete clusters involving transmission of K103N- and/or M41L-resistant virus to multiple recipients were detected, suggesting that multiple transmission pathways can exist for viruses with the same resistance mutations.     

Trends in AIDS and mortality in HIV-infected subjects with hemophilia from 1985 to 2003: the competing risks for death between AIDS and liver disease

OBJECTIVE: To study trends in progression to AIDS, all-cause mortality, and cause-specific mortality (AIDS-related, liver disease, and hemorrhagic complications) over calendar periods with different exposure to highly active antiretroviral therapy (HAART) in a cohort of hemophiliacs in Spain, taking into account the competing risks of the causes of death. METHODS: Multicenter cohort of HIV-infected hemophiliacs. HIV seroconversion was estimated using mathematic techniques for interval-censored data from 1979 through 1985. Rates of AIDS and cause-specific death were calculated by Poisson regression, allowing for late entry, for the periods 1985 through 1992, 1993 through 1996, 1997 through 2000 (early HAART), and 2001 through 2003 (late HAART), also allowing for competing risks. RESULTS: Of 585 subjects, 44% were younger than 15 years of age, 82% had severe hemophilia, 86% had type A hemophilia, and the median seroconversion date was October 1982. Calendar period and age at HIV seroconversion strongly influenced AIDS and death rates. Compared with 1993 through 1996, decreases of 75% (relative risk [RR] = 0.25, 95% confidence interval [CI]: 0.14 to 0.43) and 72% (RR = 0.28, 95% CI: 0.12 to 0.63) in the RR of AIDS were observed in early and late HAART. For all-cause mortality, 72% (RR = 0.28, 95% CI: 0.18 to 0.42) and 83% (RR = 0.17, 95% CI: 0.09 to 0.33) decreases were observed by 1997 through 2000 and 2001 through 2003. For liver-related deaths, increases were observed in the late-HAART period (RR = 2.80, 95% CI: 0.94 to 8.36) compared with 1993 through 1996, but using competing risks, this RR was substantially reduced (RR = 1.70, 95% CI: 0.57 to 5.04). DISCUSSION: Major reductions in AIDS and death rates were observed from 1997 to 2003 in hemophiliacs. These survival improvements are largely attributable to decreases in AIDS-related deaths and have been accompanied by increases in liver disease death rates, which are overestimated if competing risks are not taken into account.     

Time to AIDS from 1992 to 1999 in HIV-1-infected subjects with known date of infection

To estimate the change in AIDS incubation time during three periods characterized by different availability of antiretroviral treatments, data from the French Hospital Database on HIV of 4702 HIV-1-positive subjects with a documented date of infection were analyzed. Times from seroconversion to AIDS were compared in three periods: period 1 from January 1992 to June 1995 (monotherapy); period 2 from July 1995 to June 1996 (dual therapy); and period 3 from July 1996 to June 1999 (triple therapy). Nonparametric survival analyses were performed to account for staggered entries in the database and during each period. From periods 1 to 3, antiretroviral treatments were initiated earlier after infection, more subjects were treated, and the nature of regimens changed (25.6% of subjects were treated with monotherapy in period 1, 34.6% were treated with dual therapy in period 2, and 53.4% were treated with triple therapy in period 3). Compared with period 1, the relative hazard (RH) of AIDS was 0.31 in period 3 (95% confidence interval [CI]: 0.24-0.39). When comparing period 3 with period 2, the RH of AIDS was 0.36 (CI: 0.29-0.45). Assuming a log normal distribution, the median time to AIDS was estimated as 8.0 years in period 1 (CI: 6.0-10.6), 9.8 years in period 2 (CI: 8.5, 11.2), and 20.0 years in period 3 (CI: 17.1-23.3). This lengthening in time to AIDS from 1992 to 1999 was particularly marked in the period after the introduction of triple therapy, including protease inhibitors.     

Primary antiretroviral drug resistance in newly human immunodeficiency virus-diagnosed individuals testing anonymously and confidentially

The purpose of this study was to determine if anonymous and confidential testers differ in recency of human immunodeficiency virus (HIV) infection at time of testing and prevalence of antiretroviral drug (ARV) resistance. We examined data from the Centers for Disease Control and Prevention-sponsored Antiretroviral Drug Resistance Testing project, which performed genotypic testing on leftover HIV diagnostic serum specimens of confidentially and anonymously tested ARV-na?ve persons newly diagnosed with HIV in Colorado (n?=?365 at 11 sites) and King County, Washington (n?=?492 at 44 sites). The serologic testing algorithm for recent HIV seroconversion was used to classify people as likely to have been recently infected or not. Type of testing, anonymous or confidential, was not significantly associated with either timing of HIV testing by serologic testing algorithm for recent HIV seroconversion or resistance rates. Mutations conferring any level of ARV resistance were present in 17% of testers, and high-level resistance mutations were present in 10%. Anonymous testers were significantly more likely to have CD4+ counts >500 cells per mm(3) (45% vs. 28%; p?=?0.018), indicative of an early infection. This study indicates that anonymous testers have demographic differences relative to confidential HIV testers but were not more likely to exhibit drug resistance. Findings related to when in the course of disease anonymous testers are tested are inconsistent, but anonymous testers had higher CD4 counts, which indicates early testing and is consistent with other studies.     

Prediction of early and confirmed virological response by genotypic inhibitory quotients for lopinavir in patients na?ve for lopinavir with limited exposure to previous protease inhibitors.

OBJECTIVE: To determine the impact of genotypic inhibitory quotient (GIQ) for lopinavir (LPV) in patients failing HAART with limited antiretroviral exposure. DESIGN: Retrospective analysis of a prospective trial. METHODS: Lopinavir GIQ was calculated as the ratio between the mean trough concentration (C(trough)) and the number of protease mutations using eight different HIV drug resistance mutation lists or algorithms. Early (by week 12) and confirmed (up to week 24) virological response (HIV-RNA< 400 copies/mL, ECVR) was used as dependent variable in logistic regression model. RESULTS: Seventy-one of 109 (65%) patients achieved ECVR. At multivariable logistic regression analysis, each mug/mL increase of GIQ was correlated with increasing probability of ECVR as far as the following mutations were computed: multi-protease inhibitor (PI) associated mutations listed by IAS (OR=1.17; 95% CI=0.99-1.39; P=0.058), mutations associated with LPV resistance by ANRS algorithm (OR=1.21; 95% CI=1.02-1.44; P=0.03), major mutations associated with LPV resistance by Stanford database (OR=1.16; 95% CI=1-1.35; P=0.05), and the whole set of mutations associated with LPV resistance in the same database (OR=1.22; 95% CI=1.02-1.46; P=0.03). Using ROC curve method, a specific threshold GIQ was assessed, above which this parameter could predict ECVR with the highest sensitivity (74.6% with GIQ obtained through Stanford LPV mutations) or specificity (89.5% with GIQ obtained through ANRS LPV mutations). CONCLUSIONS: Our results suggest that increasing GIQ can improve virological outcome even in patients with limited exposure to PIs. Further studies are necessary to understand what HIV protease mutations should be considered and whether such mutations should be weighted differently to improve LPV GIQ predictive value.     

Automating HIV drug resistance genotyping with RECall, a freely accessible sequence analysis tool

Genotypic HIV drug resistance testing is routinely used to guide clinical decisions. While genotyping methods can be standardized, a slow, labor-intensive, and subjective manual sequence interpretation step is required. We therefore performed external validation of our custom software RECall, a fully automated sequence analysis pipeline. HIV-1 drug resistance genotyping was performed on 981 clinical samples at the Stanford Diagnostic Virology Laboratory. Sequencing trace files were first interpreted manually by a laboratory technician and subsequently reanalyzed by RECall, without intervention. The relative performances of the two methods were assessed by determination of the concordance of nucleotide base calls, identification of key resistance-associated substitutions, and HIV drug resistance susceptibility scoring by the Stanford Sierra algorithm. RECall is freely available at http://pssm.cfenet.ubc.ca. In total, 875 of 981 sequences were analyzed by both human and RECall interpretation. RECall analysis required minimal hands-on time and resulted in a 25-fold improvement in processing speed (～150 technician-hours versus ～6 computation-hours). Excellent concordance was obtained between human and automated RECall interpretation (99.7% agreement for >1,000,000 bases compared). Nearly all discordances (99.4%) were due to nucleotide mixtures being called by one method but not the other. Similarly, 98.6% of key antiretroviral resistance-associated mutations observed were identified by both methods, resulting in 98.5% concordance of resistance susceptibility interpretations. This automated sequence analysis tool provides both standardization of analysis and a significant improvement in data workflow. The time-consuming, error-prone, and dreadfully boring manual sequence analysis step is replaced with a fully automated system without compromising the accuracy of reported HIV drug resistance data.