High Prevalence of HIV Low Abundance Drug-Resistant Variants in a Treatment-Naive Population in North Rift Kenya.

The advent of antiretroviral treatment (ART) has resulted in a dramatic reduction in AIDS-related morbidity and mortality. However, the emergence and spread of antiretroviral drug resistance (DR) threaten to negatively impact treatment regimens and compromise efforts to control the epidemic. It is recommended that surveillance of drug resistance occur in conjunction with scale-up efforts to ensure that appropriate first-line therapy is offered relative to the resistance that exists. However, standard resistance testing methods used in Sub-Saharan Africa rely on techniques that do not include low abundance DR variants (LADRVs) that have been documented to contribute to treatment failure. The use of next generation sequencing (NGS) has been shown to be more sensitive to LADRVS. We have carried out a preliminary investigation using NGS to determine the prevalence of LDRVS among a drug-naive population in North Rift Kenya. Antiretroviral-naive patients attending a care clinic in North Rift Kenya were requested to provide and with consent provided blood samples for DR analysis. DNA was extracted and amplified and nested PCR was conducted on the pol RT region using primers tagged with multiplex identifiers (MID). Resulting PCR amplicons were purified, quantified, and pyrosequenced using a GS FLX Titanium PicoTiterPlate (Roche). Valid pyrosequencing reads were aligned with HXB-2 and the frequency and distribution of nucleotide and amino acid changes were determined using an in-house Perl script. DR mutations were identified using the IAS-USA HIV DR mutation database. Sixty samples were successfully sequenced of which 26 were subtype A, 9 were subtype D, 2 were subtype C, and the remaining were recombinants. Forty-six (76.6%) had at least one drug resistance mutation, with 25 (41.6%) indicated as major and the remaining 21 (35%) indicated as minor. The most prevalent mutation was NRTI position K219Q/R (11/46, 24%) followed by NRTI M184V (5/46, 11%) and NNRTI K103N (4/46, 9%). Our use of NGS technology revealed a high prevalence of LADRVs among drug-naive populations in Kenya, a region with predominantly non-B subtypes. The impact of these mutations on the clinical outcome of ART can be ascertained only through long-term follow-up.

Effects of HIV-1 infection on malaria parasitemia in milo sub-location, western Kenya.

BACKGROUND: Malaria and HIV infections are both highly prevalent in sub-Saharan Africa, with HIV-infected patients being at higher risk of acquiring malaria. HIV-1 infection is known to impair the immune response and may increase the incidence of clinical malaria. However, a positive association between HIV-1 and malaria parasitaemia is still evolving. Equally, the effect of malaria on HIV-1 disease stage has not been well established, but when fever and parasitemia are high, malaria may be associated with transient increases in HIV-1 viral load, and progression of HIV-1 asymptomatic disease phase to AIDS. OBJECTIVE: To determine the effects of HIV-1 infection on malaria parasitaemia among consented residents of Milo sub-location, Bungoma County in western Kenya. STUDY DESIGN: Census study evaluating malaria parasitaemia in asymptomatic individuals with unknown HIV-1 status. METHODS: After ethical approvals from both Moi University and MTRH research ethics committees, data of 3,258 participants were retrieved from both Webuye health demographic surveillance system (WHDSS), and Academic Model Providing Access to Healthcare (AMPATH) in the year 2010. The current study was identifying only un-diagnosed HIV-1 individuals at the time the primary data was collected. The data was then analysed for significant statistical association for malaria parasitemia and HIV-1 infection, using SPSS version 19. Demographic characteristics such as age and sex were summarized as means and percentages, while relationship between malaria parasitaemia and HIV-1 (serostatus) was analyzed using Chi square. RESULTS: Age distribution for the 3,258 individuals ranged between 2 and 94 years, with a mean age of 26 years old. Females constituted 54.3%, while males were 45.8%. In terms of age distribution, 2-4 years old formed 15.1% of the study population, 5-9 years old were 8.8%, 10-14 years old were 8.6% while 15 years old and above were 67.5%. Of the 3,258 individuals whose data was eligible for analysis, 1.4% was newly diagnosed HIV-1 positive. Our findings showed a higher prevalence of malaria in children aged 2-10 years (73.4%), against the one reported in children in lake Victoria endemic region by the Kenya malaria indicator survey in the year 2010 (38.1%). There was no significant associations between the prevalence of asymptomatic malaria and HIV-1 status (p = 0.327). However, HIV-1/malaria co-infected individuals showed elevated mean malaria parasite density, compared to HIV-1 negative individuals, p = 0.002. CONCLUSION: HIV-1 status was not found to have effect on malaria infection, but the mean malaria parasite density was significantly higher in HIV-1 positive than the HIV-1 negative population.