HIV-1 drug resistance-associated mutations among HIV-1 infected drug-naïve antenatal clinic attendees in rural Kenya

Abstract

BackgroundAccess to antiretroviral therapy (ART) has increased dramatically in Sub-Saharan Africa. In Kenya, 560,000 people had access to ART by the end of 2011. This scaling up of ART has raised challenges to the Kenyan health system due to emergence of drug resistant viruses among those on treatment and possible onward transmission. To counter this, and come up with an effective treatment strategy, it has become vital to determine baseline mutations associated with drug resistance among the circulating strains of HIV-1in Kenya.MethodsThe prevalence of mutations associated with drug resistance in HIV-1 protease (PR) and reverse transcriptase (RT) regions from 188 HIV-1 infected treatment-naïve pregnant women was investigated in Kapsabet, Nandi Hills and Kitale district hospitals of Kenya. Blood samples were collected between April 2005 and June 2006. The HIV-1 pol gene was amplified using primers for HIV-1 PR and RT and sequenced using the BigDye chemistry. The mutations were analyzed based on the IAS algorithm as well as the Stanford University HIV Drug Resistance Database.ResultsBased on the PR and RT sequences, HIV-1 subtypes A1 (n=117, 62.2%), A2 (n=2, 1.1%), D (n=27, 14.4%), C (n=13, 6.9%), G (n=3, 1.6%), and possible recombinants (n=26, 13.8%) were detected. Mutations associated with nucleoside reverse transcriptase inhibitors (NRTI) and non-nucleoside RTI (NNRTI)-resistance were detected in 1.6% (3 of 188) and 1.1% (2 of 188), respectively. Mutations associated with PI resistance were detected in 0.5% (1 of 188) of the study population.ConclusionThe prevalence of drug resistance among drug-naïve pregnant women in rural North Rift, Kenya in 2006 was 3.2%. Major drug resistance mutations associated with PIs, NRTIs and NNRTIs do exist among treatment-naïve pregnant women in North Rift, Kenya. There is a need for consistent follow-up of drug-naïve individuals in this region to determine the impact of mutations on treatment outcomes.

Identifying Risk Factors for Recent HIV Infection in Kenya Using a Recent Infection Testing Algorithm: Results from a Nationally Representative Population-Based Survey

“…In addition, given the genetic diversity of HIV-1 subtypes in Kenya, some of these misclassified cases may be further explained by differential specificity of LAg by HIV-1 subtype. Dominate HIV-1 strains in Kenya are clade A virus, which comprise over 50% of HIV infection, and clade D virus which covers roughly 12% to 22% of infections [ 48 – 53 ]. Clade D HIV has shown to have high levels of false-recent misclassification on antibody-based HIV incidence assays due to deferred antibody maturation and rapid antibody decline [ 25 , 26 ].…”

HIV-1 protease inhibitor drug resistance in Kenyan antiretroviral treatment-naive and -experienced injection drug users and non-drug users

“…In addition, resistance to integrase inhibitors has also been detected in the country [ 32 ]. While a number of studies in the country show existence of resistance to PIs in ART-naive and -experienced individuals in adults and children from the general population, and treatment-naive female sex workers [ 16 , 18 , 29 , 33 , 34 ] no studies to date have established PI resistance in Kenyan IDUs. Since, high drug injection intensity particularly under the selection pressure of antiretroviral therapy accelerates emergence of resistance [ 35 ], this cross-sectional study, examined PI resistance in ART-naive and -experienced IDUs from Mombasa, a coastal city in Kenya.…”

Molecular Characterization of HIV-1 And Drug Resistance Among HIV-1 Infected Patients Attending Kayanza District Hospital, Burundi

“…From the first-round PCR products, 3 μL was used as a template to make 25μL for the second reaction volume with the second set of primers ;KS101(KS101(5'-GTAGGACCTACACCTGTTCAACATAATTGGAAG-3') and KS102 KS102(5' CCCATCCAAAGAAATGGAGGAGGTTCTTTCTGATC-3') using the same cycling conditions (Nyamache et al, 2011). The nested PCR product were run on a 2% agarose gel and electrophoresed at a voltage of 100 for 20 minutes (Kiptoo et al, 2013).…”

“…The samples were injected to electrophoresis in an ABI 3730xl DNA Analyzer (Applied Biosystems).A reaction mixture containing the following reagents was used for sequencing PCR: Thirteen (13) µl RNase free double distilled H2O,5x sequencing buffer,1.5 µl primers of 1 µM sense and antisense primer,1.0 µl big dye terminator and 1.0 µl PCR product making up a total reaction volume of 20 µl (Songok et al, 2004). The PCR tubes containing the samples were placed into the thermocycler under the following programmed conditions; Initial PCR activation step 96°C for 2 minutes; 30 cycles of: denaturation for 10 seconds at 96°C, annealing for 10 seconds at 50°C; extension for 4 minute at 60°C and thereafter the samples were held at 4°C (Kiptoo et al ., 2013;Lihana et al, 2009) .…”