Diversity of the HIV-1 Long Terminal Repeat Following Mother-to-Child Transmission

AbstractA study of the human immunodeficiency virus Type 1 (HIV-1) 5′ long terminal repeat (LTR) was performed to determine the extent of variation found within the LTR from 19 mother–infant pairs in Tanzania and to assess whether the LTR is useful in distinguishing maternal sequences that were transmitted to infants. HIV-1 subtypes A, C, and D as well as intersubtype recombinant LTR sequences were detected in mothers and infants. The LTR subtype was 100% concordant between mothers and their infants. Diversity calculations showed a significant reduction in LTR variation in infants compared to their mothers. However, the overall magnitude of LTR variation was less than that found in the env gene from the same individuals. These data suggest a selective constraint active upon the 5′ long terminal repeat that is distinct from immune selective pressure(s) directed against HIV-1 structural genes. Detection of maternal LTR variants that were transmitted to infants may yield important information concerning nonstructural determinants of HIV-1 transmission from mother to infant

Time-Dependent Predictors of Loss to Follow-Up in a Large HIV Treatment Cohort in Nigeria

Background: Most evaluations of loss to follow-up (LTFU) in human immunodeficiency virus (HIV) treatment programs focus on baseline predictors, prior to antiretroviral therapy (ART) initiation. As risk of LTFU is a continuous issue, the aim of this evaluation was to augment existing information with further examination of time-dependent predictors of loss. Methods: This was a retrospective evaluation of data collected between 2004 and 2012 by the Harvard School of Public Health and the AIDS Prevention Initiative in Nigeria as part of PEPFAR-funded program in Nigeria. We used multivariate modeling methods to examine associations between CD4+ cell counts, viral load, and early adherence patterns with LTFU, defined as no refills collected for at least 2 months since the last scheduled appointment. Results: Of 51 953 patients initiated on ART between 2004 and 2011, 14 626 (28%) were LTFU by 2012. Factors associated with increased risk for LTFU were young age, having nonincome-generating occupations or no education, being unmarried, World Health Organization (WHO) stage, having a detectable viral load, and lower CD4+ cell counts. In a subset analysis, adherence patterns during the first 3 months of ART were associated with risk of LTFU by month 12. Conclusions: In settings with limited resources, early adherence patterns, as well as CD4+ cell counts and unsuppressed viral load, at any time point in treatment are predictive of loss and serve as effective markers for developing targeted interventions to reduce rates of attrition

Accumulation of Protease Mutations among Patients Failing Second-Line Antiretroviral Therapy and Response to Salvage Therapy in Nigeria

Background: To date, antiretroviral therapy (ART) guidelines and programs in resource-limited settings (RLS) have focused on 1st- and 2nd-line (2 L) therapy. As programs approach a decade of implementation, policy regarding access to 3rd-line (3 L) ART is needed. We aimed to examine the impact of maintaining patients on failing 2 L ART on the accumulation of protease (PR) mutations. Methods and Findings: From 2004–2011, the Harvard/APIN PEPFAR Program provided ART to >100,000 people in Nigeria. Genotypic resistance testing was performed on a subset of patients experiencing 2 L failure, defined as 2 consecutive viral loads (VL)>1000 copies/mL after ≥6 months on 2 L. Of 6714 patients who received protease inhibitor (PI)-based ART, 673 (10.0%) met virologic failure criteria. Genotypes were performed on 61 samples. Patients on non-suppressive 2 L therapy for 24 months. Patients developed a median of 0.6 (IQR: 0–1.4) IAS PR mutations per 6 months on failing 2 L therapy. In 38% of failing patients no PR mutations were present. For patients failing >24 months, high- or intermediate-level resistance to lopinavir and atazanavir was present in 63%, with 5% to darunavir. Conclusions: This is the first report assessing the impact of duration of non-suppressive 2 L therapy on the accumulation of PR resistance in a RLS. This information provides insight into the resistance cost of failing to switch non-suppressive 2 L regimens and highlights the issue of 3 L access

Technology in Massachusetts Schools, 2004-2005

BACKGROUND:ATCC HIV-1 drug resistance test kit was designed to detect HIV-1 drug resistance (HIVDR) mutations in the protease and reverse transcriptase genes for all HIV-1 group M subtypes and circulating recombinant forms. The test has been validated for both plasma and dried blood spot specimen types with viral load (VL) of ≥1000 copies/ml. We performed an in-country assessment on the kit to determine the genotyping sensitivity and its accuracy in detecting HIVDR mutations using plasma samples stored under suboptimal conditions. METHODS:Among 572 samples with VL ≥1000 copies/ml that had been genotyped by ViroSeq assay, 183 were randomly selected, including 85 successful genotyped and 98 unsuccessful genotyped samples. They were tested with ATCC kits following the manufacturer's instructions. Sequence identity and HIVDR patterns were analysed with Stanford University HIV Drug Resistance HIVdb program. RESULTS:Of the 183 samples, 127 (69.4%) were successfully genotyped by either method. While ViroSeq system genotyped 85/183 (46.5%) with median VL of 32,971 (IQR: 11,150-96,506) copies/ml, ATCC genotyped 115/183 (62.8%) samples with median VL of 23,068 (IQR: 7,397-86,086) copies/ml. Of the 98 unsuccessful genotyped samples with ViroSeq assay, 42 (42.9%) samples with lower median VL of 13,906 (IQR: 6,122-72,329) copies/ml were successfully genotyped using ATCC. Sequence identity analysis revealed that the sequences generated by both methods were >98% identical and yielded similar HIVDR profiles at individual patient level. CONCLUSION:This study confirms that ATCC kit showed greater sensitivity in genotyping plasma samples stored in suboptimal conditions experiencing frequent and prolonged power outage. Thus, it is more sensitive particularly for subtypes A and A/G HIV-1 in resource-limited settings

The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society

Epidemic expansion of HIV type 1 subtype C and recombinant genotypes in Tanzania

Human immunodeficiency virus type 1 (HIV-1) subtypes are distributed unevenly across African nations.1 In East and Central African countries such as Uganda, Rwanda, Kenya, and Tanzania, the HIV-1 epidemic has involved two HIV-1 subtypes, A and D. In contrast, HIV-1 subtype C has dominated the rapidly expanding epidemic in Malawi and South Africa.1-3 The relative roles played by virological, behavioral, and host determinants in the epidemic expansion of any particular HIV- 1 subtype are unclear. Characterization of the transmissibility and pathogenic potential of distinct HIV-1 genetic subtypes is currently under investigation in many regions of the world. Careful surveillance of genetic subtypes prevalent in a given population is one particularly important approach to better understand the biological properties of different HIV-1 subtypes. The presence of HIV-1 subtypes A and D in asymptomatic carriers and AIDS patients from several geographical locales in Tanzania has been previously described.4-7 An analysis of samples collected in 1988 showed that 10 of 15 (67%) envelope V3 sequences from Tanzanian samples were found to belong to subtype D. The remaining five samples (33%) belonged to HIV-1 subtype A.4 In Dar es Salaam, vpu and env sequences from 8 of 10 AIDS patients (80%) clustered with subtype D viruses and the remaining 2 (20%) with subtype A.5 A study in northern Tanzania reported that the env-encoded gp41 regions from 12 samples also clustered with HIV-1 subtypes A and D.6 In another report from northern Tanzania, four of eight (50%) envelope sequences sampled encompassing the C2V3 region belonged to subtype A and the other half to subtype D.7 Envelope sequences from HIV-1-infected individuals of Tanzanian origin, but living in Sweden, showed that three of four samples were HIV-1 subtype C and the remaining sample was HIV-1 subtype A.

HIV type 1 subtypes among bar and hotel workers in Moshi, Tanzania.

The HIV-1 prevalence among bar and hotel workers in Tanzania suggests they are a high-risk group for HIV-1 infection. We determined the HIV-1 subtype of 3'-p24/5'-p7 gag and C2-C5 env sequences from 40 individuals representing this population in Moshi. Genetic patterns composed of A(gag)-A(env), C(gag)-C(env), and D(gag)-D(env) were found in 19 (48.0%), 8 (20.0%), and 3 (8.0%) samples, respectively. The remaining 10 samples (25%) had different subtypes in gag and env, indicative of intersubtype recombinants. Among these recombinants, two contained sequences from HIV-1 subsubtype A2, a new genetic variant in Tanzania. Five bar and hotel workers may have been infected with viruses from a common source, based on phylogenetic analysis. The information obtained by surveillance of HIV-1 subtypes in a high-risk population should be useful in the design and evaluation of behavioral, therapeutic, and vaccine trial interventions aimed at reducing HIV-1 transmission

Characterisation of HIV-1 Molecular Epidemiology in Nigeria : Origin, Diversity, Demography and Geographic Spread

Nigeria has the highest number of AIDS-related deaths in the world. In this study, we characterised the HIV-1 molecular epidemiology by analysing 1442 HIV-1 pol sequences collected 1999-2014 from four geopolitical zones in Nigeria using state-of-the-art maximum-likelihood and Bayesian phylogenetic analyses. The main circulating forms were the circulating recombinant form (CRF) 02_AG (44% of the analysed sequences), CRF43_02G (16%), and subtype G (8%). Twenty-three percent of the sequences represented unique recombinant forms (URFs), whereof 37 (11%) could be grouped into seven potentially novel CRFs. Bayesian phylodynamic analysis suggested that five major Nigerian HIV-1 sub-epidemics were introduced in the 1960s and 1970s, close to the Nigerian Civil War. The analysis also indicated that the number of effective infections decreased in Nigeria after the introduction of free antiretroviral treatment in 2006. Finally, Bayesian phylogeographic analysis suggested gravity-like dynamics in which virus lineages first emerge and expand within large urban centers such as Abuja and Lagos, before migrating towards smaller rural areas. This study provides novel insight into the Nigerian HIV-1 epidemic and may have implications for future HIV-1 prevention strategies in Nigeria and other severely affected countries