bioRxivMicrobiology
Characterisation of the HIV-1 Molecular Epidemiology in Nigeria: Origin, Diversity, Demography and Geographic Spread
J. Nazziwa, N. Faria, B. Chaplin, H. Razziwa, P. Dakum, A. Abimiku, M. Charurat, N. Ndembi, J. Esbjornsson
Abstract
Nigeria has been reported to have the highest number of AIDS-related deaths in the world. In this study, we aimed to determine the HIV-1 genetic diversity and phylodynamics in Nigeria. We analysed 1442 HIV-1 pol sequences collected 1999-2014 from four geopolitical zones in Nigeria. Phylogenetic analysis showed that the main circulating strains was the circulating recombinant strain (CRF) 02_AG (44% of the analysed sequences), subtype G (8%), and CRF43_02G (16%); and that these were introduced in Nigeria in the 1960s, 1970s and 1980s, respectively. The number of effective infections decreased in Nigeria after the introduction of free antiretroviral treatment in 2006. We also found a significant number of unique recombinant forms (22.7%). The majority of those were recombinants between two or three of the main circulating strains. Seven of those recombinants may represent novel CRFs. Finally, phylogeographic analysis suggested multiple occasions of HIV-1 transmissions between Lagos and Abuja (two of the main cities in Nigeria), that HIV-1 epidemic started in these cities, and then dispersed into rural areas.\n\nIMPORTANCENigeria has the second largest HIV-1 epidemic in the world with the highest number of AIDS-related deaths. The few previous reports have focused on local HIV-1 subtype/CRF distributions in different Nigerian regions, and the molecular epidemiology of HIV-1 in Nigeria as a whole is less well characterized. In this study, we describe the HIV-1 spatiotemporal dynamics of the five dominating transmission clusters representing the main characteristics of the epidemiology. Our results may contribute to inform prevention strategies against further spread of HIV-1 in Nigeria.
- organism: human
- assay: DNA methylation
- research focus: host-pathogen & immune response
- approach: statistical model
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