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Nduva GM, Otieno F, Kimani J, Wahome E, McKinnon LR, Cholette F, Majiwa M, Masika M, Mutua G, Anzala O, Graham SM, Gelmon L, Price MA, Smith AD, Bailey RC, Baele G, Lemey P, Hassan AS, Sanders EJ, Esbjörnsson J. Quantifying rates of HIV-1 flow between risk groups and geographic locations in Kenya: A country-wide phylogenetic study. Virus Evol 2022; 8:veac016. [PMID: 35356640 PMCID: PMC8962731 DOI: 10.1093/ve/veac016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/23/2022] [Accepted: 03/01/2022] [Indexed: 12/14/2022] Open
Abstract
In Kenya, HIV-1 key populations including men having sex with men (MSM), people who inject drugs (PWID) and female sex workers (FSW) are thought to significantly contribute to HIV-1 transmission in the wider, mostly heterosexual (HET) HIV-1 transmission network. However, clear data on HIV-1 transmission dynamics within and between these groups are limited. We aimed to empirically quantify rates of HIV-1 flow between key populations and the HET population, as well as between different geographic regions to determine HIV-1 'hotspots' and their contribution to HIV-1 transmission in Kenya. We used maximum-likelihood phylogenetic and Bayesian inference to analyse 4058 HIV-1 pol sequences (representing 0.3 per cent of the epidemic in Kenya) sampled 1986-2019 from individuals of different risk groups and regions in Kenya. We found 89 per cent within-risk group transmission and 11 per cent mixing between risk groups, cyclic HIV-1 exchange between adjoining geographic provinces and strong evidence of HIV-1 dissemination from (i) West-to-East (i.e. higher-to-lower HIV-1 prevalence regions), and (ii) heterosexual-to-key populations. Low HIV-1 prevalence regions and key populations are sinks rather than major sources of HIV-1 transmission in Kenya. Targeting key populations in Kenya needs to occur concurrently with strengthening interventions in the general epidemic.
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Affiliation(s)
- George M Nduva
- Department of Translational Medicine, Lund University, Faculty of Medicine, Lund University, Box 117 SE-221 00 Lund, Sweden
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
| | - Frederick Otieno
- Nyanza Reproductive Health Society, United Mall, P.O. Box 1764, Kisumu, Kenya
| | - Joshua Kimani
- Department of Medical Microbiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
| | - Elizabeth Wahome
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
| | - Lyle R McKinnon
- Department of Medical Microbiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Doris Duke Medical Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Private Bag X7, Congella 4013, South Africa
| | - Francois Cholette
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
- National Microbiology Laboratory at the JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, 745 Logan Avenue, Winnipeg, Canada
| | - Maxwell Majiwa
- Kenya Medical Research Institute/Center for Global Health Research, KEMRI-CGHR, P.O. Box 20778-00202, Kisumu, Kenya
| | - Moses Masika
- Faculty of Health Sciences 3RD Floor Wing B, KAVI Institute of Clinical Research, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya
| | - Gaudensia Mutua
- Faculty of Health Sciences 3RD Floor Wing B, KAVI Institute of Clinical Research, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya
| | - Omu Anzala
- Faculty of Health Sciences 3RD Floor Wing B, KAVI Institute of Clinical Research, University of Nairobi, P.O. Box 19676-00202, Nairobi, Kenya
| | - Susan M Graham
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
- Department of Epidemiology, University of Washington, Office of the Chair, UW Box # 351619, Seattle, DC, USA
| | - Larry Gelmon
- Department of Medical Microbiology, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Max Rady College of Medicine, Room 543-745 Bannatyne Avenue, University of Manitoba (Bannatyne campus), Winnipeg MB R3E 0J9, Canada
| | - Matt A Price
- IAVI Global Headquarters, 125 Broad Street, 9th Floor, New York, NY 10004, USA
- Department of Epidemiology and Biostatistics, University of California, Mission Hall: Global Health & Clinical Sciences Building, 550 16th Street, 2nd Floor, San Francisco, CA 94158-2549, USA
| | - Adrian D Smith
- Nuffield Department of Medicine, The University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK
| | - Robert C Bailey
- Nyanza Reproductive Health Society, United Mall, P.O. Box 1764, Kisumu, Kenya
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago, 1603 W Taylor St, Chicago, IL 60612, USA
| | - Guy Baele
- KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Evolutionary and Computational Virology, Rega-Herestraat 49-box 1040, Leuven 3000, Belgium
| | - Philippe Lemey
- KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Evolutionary and Computational Virology, Rega-Herestraat 49-box 1040, Leuven 3000, Belgium
| | - Amin S Hassan
- Department of Translational Medicine, Lund University, Faculty of Medicine, Lund University, Box 117 SE-221 00 Lund, Sweden
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
| | - Eduard J Sanders
- Kenya Medical Research Institute-Wellcome Trust Research Programme, KEMRI-Center For Geographic Medicine Research, P.O. Box 230-80108, Kilifi, Kenya
- Nuffield Department of Medicine, The University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK
| | - Joakim Esbjörnsson
- Department of Translational Medicine, Lund University, Faculty of Medicine, Lund University, Box 117 SE-221 00 Lund, Sweden
- Nuffield Department of Medicine, The University of Oxford, Old Road Campus, Headington, Oxford OX3 7BN, UK
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Nduva GM, Nazziwa J, Hassan AS, Sanders EJ, Esbjörnsson J. The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review. Viruses 2021; 13:1174. [PMID: 34205246 PMCID: PMC8235305 DOI: 10.3390/v13061174] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/09/2021] [Accepted: 06/10/2021] [Indexed: 12/19/2022] Open
Abstract
To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.
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Affiliation(s)
- George M. Nduva
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
| | - Jamirah Nazziwa
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
| | - Amin S. Hassan
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
| | - Eduard J. Sanders
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, The University of Oxford, Oxford OX1 2JD, UK
| | - Joakim Esbjörnsson
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, The University of Oxford, Oxford OX1 2JD, UK
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Adhiambo M, Makwaga O, Adungo F, Kimani H, Mulama DH, Korir JC, Mwau M. Human immunodeficiency virus (HIV) type 1 genetic diversity in HIV positive individuals on antiretroviral therapy in a cross-sectional study conducted in Teso, Western Kenya. Pan Afr Med J 2021; 38:335. [PMID: 34046145 PMCID: PMC8140725 DOI: 10.11604/pamj.2021.38.335.26357] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 04/01/2021] [Indexed: 11/16/2022] Open
Abstract
Introduction high HIV-1 infection rates and genetic diversity especially in African population pose significant challenges in HIV-1 clinical management and drug design and development. HIV-1 is a major health challenge in Kenya and causes mortality and morbidity in the country as well as straining the healthcare system and the economy. This study sought to identify HIV-1 genetic subtypes circulating in Teso, Western Kenya which borders the Republic of Uganda. Methods a cross-sectional study was conducted in January 2019 to December 2019. Sequencing of the partial pol gene was carried out on 80 HIV positive individuals on antiretroviral therapy. Subtypes and recombinant forms were generated using the jumping profile hidden Markov model. Alignment of the sequences was done using ClustalW program and phylogenetic tree constructed using MEGA7 neighbor-joining method. Results sixty three samples were successful sequenced. In the analysis of these sequences, it was observed that HIV-1 subtype A1 was predominant 43 (68.3%) followed by D 8 (12.7%) and 1 (1.6%) each of C, G and B and inter-subtype recombinants A1-D 3 (4.8%), A1-B 2 (3.2%) and 1 (1.6%) each of A1-A2, A1-C, BC and BD. Phylogenetic analysis of these sequences showed close clustering of closely related and unrelated sequences with reference sequences. Conclusion there was observed increased genetic diversity of HIV-1 subtypes which not only pose a challenge in disease control and management but also drug design and development. Therefore, there is need for continued surveillance to enhance future understanding of the geographical distribution and transmission patterns of the HIV epidemic.
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Affiliation(s)
- Maureen Adhiambo
- Department of Biological Sciences, Masinde Muliro University of Science and Technology, Kakamega, Kenya.,Department of Infectious Diseases Control Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Olipher Makwaga
- Department of Biological Sciences, Masinde Muliro University of Science and Technology, Kakamega, Kenya.,Department of Infectious Diseases Control Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Ferdinard Adungo
- Department of Infectious Diseases Control Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Humphrey Kimani
- Department of Infectious Diseases Control Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - David Hughes Mulama
- Department of Biological Sciences, Masinde Muliro University of Science and Technology, Kakamega, Kenya
| | - Jackson Cheruiyot Korir
- Department of Biological Sciences, Masinde Muliro University of Science and Technology, Kakamega, Kenya
| | - Matilu Mwau
- Department of Infectious Diseases Control Research, Kenya Medical Research Institute, Nairobi, Kenya
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Nduva GM, Hassan AS, Nazziwa J, Graham SM, Esbjörnsson J, Sanders EJ. HIV-1 Transmission Patterns Within and Between Risk Groups in Coastal Kenya. Sci Rep 2020; 10:6775. [PMID: 32317722 PMCID: PMC7174422 DOI: 10.1038/s41598-020-63731-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 03/30/2020] [Indexed: 11/09/2022] Open
Abstract
HIV-1 transmission patterns within and between populations at different risk of HIV-1 acquisition in Kenya are not well understood. We investigated HIV-1 transmission networks in men who have sex with men (MSM), injecting drug users (IDU), female sex workers (FSW) and heterosexuals (HET) in coastal Kenya. We used maximum-likelihood and Bayesian phylogenetics to analyse new (N = 163) and previously published (N = 495) HIV-1 polymerase sequences collected during 2005-2019. Of the 658 sequences, 131 (20%) were from MSM, 58 (9%) IDU, 109 (17%) FSW, and 360 (55%) HET. Overall, 206 (31%) sequences formed 61 clusters. Most clusters (85%) consisted of sequences from the same risk group, suggesting frequent within-group transmission. The remaining clusters were mixed between HET/MSM (7%), HET/FSW (5%), and MSM/FSW (3%) sequences. One large IDU-exclusive cluster was found, indicating an independent sub-epidemic among this group. Phylodynamic analysis of this cluster revealed a steady increase in HIV-1 infections among IDU since the estimated origin of the cluster in 1987. Our results suggest mixing between high-risk groups and heterosexual populations and could be relevant for the development of targeted HIV-1 prevention programmes in coastal Kenya.
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Affiliation(s)
- George M Nduva
- Lund University, Lund, Sweden
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
| | - Amin S Hassan
- Lund University, Lund, Sweden
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
| | | | - Susan M Graham
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- University of Washington, Seattle, WA, USA
| | - Joakim Esbjörnsson
- Lund University, Lund, Sweden.
- The University of Oxford, Oxford, United Kingdom.
| | - Eduard J Sanders
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- The University of Oxford, Oxford, United Kingdom
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5
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Distinct rates and patterns of spread of the major HIV-1 subtypes in Central and East Africa. PLoS Pathog 2019; 15:e1007976. [PMID: 31809523 PMCID: PMC6897401 DOI: 10.1371/journal.ppat.1007976] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 07/11/2019] [Indexed: 12/21/2022] Open
Abstract
Since the ignition of the HIV-1 group M pandemic in the beginning of the 20th century, group M lineages have spread heterogeneously throughout the world. Subtype C spread rapidly through sub-Saharan Africa and is currently the dominant HIV lineage worldwide. Yet the epidemiological and evolutionary circumstances that contributed to its epidemiological expansion remain poorly understood. Here, we analyse 346 novel pol sequences from the DRC to compare the evolutionary dynamics of the main HIV-1 lineages, subtypes A1, C and D. Our results place the origins of subtype C in the 1950s in Mbuji-Mayi, the mining city of southern DRC, while subtypes A1 and D emerged in the capital city of Kinshasa, and subtypes H and J in the less accessible port city of Matadi. Following a 15-year period of local transmission in southern DRC, we find that subtype C spread at least three-fold faster than other subtypes circulating in Central and East Africa. In conclusion, our results shed light on the origins of HIV-1 main lineages and suggest that socio-historical rather than evolutionary factors may have determined the epidemiological fate of subtype C in sub-Saharan Africa.
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6
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Reconstruction of the Genetic History and the Current Spread of HIV-1 Subtype A in Germany. J Virol 2019; 93:JVI.02238-18. [PMID: 30944175 DOI: 10.1128/jvi.02238-18] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Accepted: 03/13/2019] [Indexed: 12/15/2022] Open
Abstract
HIV-1 non-B infections have been increasing in Europe for several years. In Germany, subtype A belongs to the most abundant non-B subtypes showing an increasing prevalence of 8.3% among new infections in 2016. Here we trace the origin and examine the current spread of the German HIV-1 subtype A epidemic. Bayesian coalescence and birth-death analyses were performed with 180 German HIV-1 pol sequences and 528 related and publicly available sequences to reconstruct the population dynamics and fluctuations for each of the transmission groups. Our reconstructions indicate two distinct sources of the German subtype A epidemic, with an Eastern European and an Eastern African lineage both cocirculating in the country. A total of 13 German-origin clusters were identified; among these, 6 clusters showed recent activity. Introductions leading to further countrywide spread originated predominantly from Eastern Africa when introduced before 2005. Since 2005, however, spreading introductions have occurred exclusively within the Eastern European clade. Moreover, we observed changes in the main route of subtype A transmission. The beginning of the German epidemic (1985 to 1995) was dominated by heterosexual transmission of the Eastern African lineage. Since 2005, transmissions among German men who have sex with men (MSM) have been increasing and have been associated with the Eastern European lineage. Infections among people who inject drugs dominated between 1998 and 2005. Our findings on HIV-1 subtype A infections provide new insights into the spread of this virus and extend the understanding of the HIV epidemic in Germany.IMPORTANCE HIV-1 subtype A is the second most prevalent subtype worldwide, with a high prevalence in Eastern Africa and Eastern Europe. However, an increase of non-B infections, including subtype A infections, has been observed in Germany and other European countries. There has simultaneously been an increased flow of refugees into Europe and especially into Germany, raising the question of whether the surge in non-B infections resulted from this increased immigration or whether German transmission chains are mainly involved. This study is the first comprehensive subtype A study from a western European country analyzing in detail its phylogenetic origin, the impact of various transmission routes, and its current spread. The results and conclusions presented provide new and substantial insights for virologists, epidemiologists, and the general public health sector. In this regard, they should be useful to those authorities responsible for developing public health intervention strategies to combat the further spread of HIV/AIDS.
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Ratmann O, Grabowski MK, Hall M, Golubchik T, Wymant C, Abeler-Dörner L, Bonsall D, Hoppe A, Brown AL, de Oliveira T, Gall A, Kellam P, Pillay D, Kagaayi J, Kigozi G, Quinn TC, Wawer MJ, Laeyendecker O, Serwadda D, Gray RH, Fraser C. Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis. Nat Commun 2019; 10:1411. [PMID: 30926780 PMCID: PMC6441045 DOI: 10.1038/s41467-019-09139-4] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 02/22/2019] [Indexed: 11/09/2022] Open
Abstract
To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these 'source' populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8-28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.
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Affiliation(s)
- Oliver Ratmann
- Department of Mathematics, Imperial College London, London, SW72AZ, UK.
- Department of Infectious Disease, Epidemiology School of Public Health, Imperial College London, London, W21PG, UK.
| | - M Kate Grabowski
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
| | - Matthew Hall
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Tanya Golubchik
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Chris Wymant
- Department of Infectious Disease, Epidemiology School of Public Health, Imperial College London, London, W21PG, UK
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Lucie Abeler-Dörner
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - David Bonsall
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Anne Hoppe
- Division of Infection and Immunity, University College London, London, WC1E 6BT, UK
| | - Andrew Leigh Brown
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
| | - Tulio de Oliveira
- College of Health Sciences, University of KwaZulu-Natal, Durban, 4041, South Africa
| | - Astrid Gall
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Paul Kellam
- Department of Medicine, Imperial College London, London, W12 0HS, UK
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, WC1E 6BT, UK
- Africa Health Research Institute, Private Bag X7, Durban, 4013, South Africa
| | - Joseph Kagaayi
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
| | - Godfrey Kigozi
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
| | - Thomas C Quinn
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, 20892-9806, USA
| | - Maria J Wawer
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, 20892-9806, USA
| | - David Serwadda
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
- Makerere University School of Public Health, Kampala, 8HQG+3V, Uganda
| | - Ronald H Gray
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Christophe Fraser
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
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Tanser F, Bärnighausen T, Dobra A, Sartorius B. Identifying 'corridors of HIV transmission' in a severely affected rural South African population: a case for a shift toward targeted prevention strategies. Int J Epidemiol 2019; 47:537-549. [PMID: 29300904 PMCID: PMC5913614 DOI: 10.1093/ije/dyx257] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2017] [Indexed: 11/24/2022] Open
Abstract
Background In the context of a severe generalized African HIV epidemic, the value of geographically targeted prevention interventions has only recently been given serious consideration. However, to date no study has performed a population-based analysis of the micro-geographical clustering of HIV incident infections, limiting the evidential support for such a strategy. Methods We followed 17 984 HIV-uninfected individuals aged 15–54 in a population-based cohort in rural KwaZulu-Natal, South Africa, and observed individual HIV sero-conversions between 2004 and 2014. We geo-located all individuals to an exact homestead of residence (accuracy <2 m). We then employed a two-dimensional Gaussian kernel of radius 3 km to produce robust estimates of HIV incidence which vary across continuous geographical space. We also applied Tango's flexibly shaped spatial scan statistic to identify irregularly shaped clusters of high HIV incidence. Results Between 2004 and 2014, we observed a total of 2 311 HIV sero-conversions over 70 534 person-years of observation, at an overall incidence of 3.3 [95% confidence interval (CI), 3.1-3.4] per 100 person-years. Three large irregularly-shaped clusters of new HIV infections (relative risk = 1.6, 1.7 and 2.3) were identified in two adjacent peri-urban communities near the National Road (P = 0.001, 0.015) as well as in a rural node bordering a recent coal mine development (P = 0.020), respectively. Together the clusters had a significantly higher age-sex standardized incidence of 5.1 (95% CI, 4.7-5.6) per 100 person-years compared with a standardized incidence of 3.0 per 100 person-years (95% CI, 2.9-3.2) in the remainder of the study area. Though these clusters comprise just 6.8% of the study area, they account for one out of every four sero-conversions observed over the study period. Conclusions Our study has revealed clear ‘corridors of transmission’ in this typical rural, hyper-endemic population. Even in a severely affected rural African population, an approach that seeks to provide preventive interventions to the most vulnerable geographies could be more effective and cost-effective in reducing the overall rate of new HIV infections. There is an urgent need to develop and test such interventions as part of an overall combination prevention approach.
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Affiliation(s)
- Frank Tanser
- Africa Health Research Institute, Durban, South Africa.,School of Nursing and Public Health, University of KwaZulu-Natal, South Africa.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa.,Institute of Epidemiology and Health Care, University College London, London, UK
| | - Till Bärnighausen
- Africa Health Research Institute, Durban, South Africa.,Institute of Epidemiology and Health Care, University College London, London, UK.,Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Institute for Public Health, University of Heidelberg, Heidelberg, Germany
| | - Adrian Dobra
- Department of Statistics, Department of Biobehavioral Nursing and Health Informatics, Center for Statistics and the Social Sciences and Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA
| | - Benn Sartorius
- School of Nursing and Public Health, University of KwaZulu-Natal, South Africa
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9
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Hassan AS, Bibby DF, Mwaringa SM, Agutu CA, Ndirangu KK, Sanders EJ, Cane PA, Mbisa JL, Berkley JA. Presence, persistence and effects of pre-treatment HIV-1 drug resistance variants detected using next generation sequencing: A Retrospective longitudinal study from rural coastal Kenya. PLoS One 2019; 14:e0210559. [PMID: 30759103 PMCID: PMC6373901 DOI: 10.1371/journal.pone.0210559] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Accepted: 12/27/2018] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND The epidemiology of HIV-1 drug resistance (HIVDR) determined by Sanger capillary sequencing, has been widely studied. However, much less is known about HIVDR detected using next generation sequencing (NGS) methods. We aimed to determine the presence, persistence and effect of pre-treatment HIVDR variants detected using NGS in HIV-1 infected antiretroviral treatment (ART) naïve participants from rural Coastal Kenya. METHODS In a retrospective longitudinal study, samples from HIV-1 infected participants collected prior [n = 2 time-points] and after [n = 1 time-point] ART initiation were considered. An ultra-deep amplicon-based NGS assay, calling for nucleotide variants at >2.0% frequency of viral population, was used. Suspected virologic failure (sVF) was defined as a one-off HIV-1 viral load of >1000 copies/ml whilst on ART. RESULTS Of the 50 eligible participants, 12 (24.0% [95% CI: 13.1-38.2]) had at least one detectable pre-treatment HIVDR variant against Protease Inhibitors (PIs, n = 6 [12%]), Nucleoside Reverse Transcriptase Inhibitors (NRTIs, n = 4 [8.0%]) and Non-NRTIs (n = 3 [6.0%]). Overall, 15 pre-treatment resistance variants were detected (frequency, range: 2.3-92.0%). A positive correlation was observed between mutation frequency and absolute load for NRTI and/or NNRTI variants (r = 0.761 [p = 0.028]), but not for PI variants (r = -0.117 [p = 0.803]). Participants with pre-treatment NRTI and/or NNRTI resistance had increased odds of sVF (OR = 6.0; 95% CI = 1.0-36.9; p = 0.054). CONCLUSIONS Using NGS, pre-treatment resistance variants were common, though observed PI variants were unlikely transmitted, but rather probably generated de novo. Even when detected from a low frequency, pre-treatment NRTI and/or NNRTI resistance variants may adversely affect treatment outcomes.
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Affiliation(s)
| | - David F. Bibby
- Virus Reference Department, Public Health England, London, United Kingdom
| | | | | | | | - Eduard J. Sanders
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom
| | - Patricia A. Cane
- Virus Reference Department, Public Health England, London, United Kingdom
| | - Jean L. Mbisa
- Virus Reference Department, Public Health England, London, United Kingdom
| | - James A. Berkley
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom
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10
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Hassan AS, Esbjörnsson J, Wahome E, Thiong’o A, Makau GN, Price MA, Sanders EJ. HIV-1 subtype diversity, transmission networks and transmitted drug resistance amongst acute and early infected MSM populations from Coastal Kenya. PLoS One 2018; 13:e0206177. [PMID: 30562356 PMCID: PMC6298690 DOI: 10.1371/journal.pone.0206177] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 10/08/2018] [Indexed: 11/21/2022] Open
Abstract
Background HIV-1 molecular epidemiology amongst men who have sex with men (MSM) in sub-Saharan Africa remains not well characterized. We aimed to determine HIV-1 subtype distribution, transmission clusters and transmitted drug resistance (TDR) in acute and early infected MSM from Coastal Kenya. Methods Analysis of HIV-1 partial pol sequences from MSM recruited 2005–2017 and sampled within six months of the estimated date of infection. Volunteers were classified as men who have sex with men exclusively (MSME) or with both men and women (MSMW). HIV-1 subtype and transmission clusters were determined by maximum-likelihood phylogenetics. TDR mutations were determined using the Stanford HIV drug resistance database. Results Of the 97 volunteers, majority (69%) were MSMW; 74%, 16%, 9% and 1% had HIV-1 subtypes A1, D, C or G, respectively. Overall, 65% formed transmission clusters, with substantial mixing between MSME and MSMW. Majority of volunteer sequences were either not linked to any reference sequence (56%) or clustered exclusively with sequences of Kenyan origin (19%). Eight (8% [95% CI: 4–16]) had at least one TDR mutation against nucleoside (n = 2 [2%]) and/or non-nucleoside (n = 7 [7%]) reverse transcriptase inhibitors. The most prevalent TDR mutation was K103N (n = 5), with sequences forming transmission clusters of two and three taxa each. There were no significant differences in HIV-1 subtype distribution and TDR between MSME and MSMW. Conclusions This HIV-1 MSM epidemic was predominantly sub-subtype A1, of Kenyan origin, with many transmission clusters and having intermediate level of TDR. Targeted HIV-1 prevention, early identification and care interventions are warranted to break the transmission cycle amongst MSM from Coastal Kenya.
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Affiliation(s)
- Amin S. Hassan
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Lund University, Lund, Sweden
- * E-mail:
| | | | | | | | - George N. Makau
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Lund University, Lund, Sweden
| | - Mathew A. Price
- International AIDS Vaccine Initiative, New York, New York, United States of America
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, California, United States of America
| | - Eduard J. Sanders
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Oxford University, Oxford, United Kingdom
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11
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Ratmann O, Wymant C, Colijn C, Danaviah S, Essex M, Frost S, Gall A, Gaseitsiwe S, Grabowski MK, Gray R, Guindon S, von Haeseler A, Kaleebu P, Kendall M, Kozlov A, Manasa J, Minh BQ, Moyo S, Novitsky V, Nsubuga R, Pillay S, Quinn TC, Serwadda D, Ssemwanga D, Stamatakis A, Trifinopoulos J, Wawer M, Brown AL, de Oliveira T, Kellam P, Pillay D, Fraser C, on behalf of the PANGEA-HIV Consort. HIV-1 full-genome phylogenetics of generalized epidemics in sub-Saharan Africa: impact of missing nucleotide characters in next-generation sequences. AIDS Res Hum Retroviruses 2017; 33:1083-1098. [PMID: 28540766 PMCID: PMC5597042 DOI: 10.1089/aid.2017.0061] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
To characterize HIV-1 transmission dynamics in regions where the burden of HIV-1 is greatest, the “Phylogenetics and Networks for Generalised HIV Epidemics in Africa” consortium (PANGEA-HIV) is sequencing full-genome viral isolates from across sub-Saharan Africa. We report the first 3,985 PANGEA-HIV consensus sequences from four cohort sites (Rakai Community Cohort Study, n = 2,833; MRC/UVRI Uganda, n = 701; Mochudi Prevention Project, n = 359; Africa Health Research Institute Resistance Cohort, n = 92). Next-generation sequencing success rates varied: more than 80% of the viral genome from the gag to the nef genes could be determined for all sequences from South Africa, 75% of sequences from Mochudi, 60% of sequences from MRC/UVRI Uganda, and 22% of sequences from Rakai. Partial sequencing failure was primarily associated with low viral load, increased for amplicons closer to the 3′ end of the genome, was not associated with subtype diversity except HIV-1 subtype D, and remained significantly associated with sampling location after controlling for other factors. We assessed the impact of the missing data patterns in PANGEA-HIV sequences on phylogeny reconstruction in simulations. We found a threshold in terms of taxon sampling below which the patchy distribution of missing characters in next-generation sequences (NGS) has an excess negative impact on the accuracy of HIV-1 phylogeny reconstruction, which is attributable to tree reconstruction artifacts that accumulate when branches in viral trees are long. The large number of PANGEA-HIV sequences provides unprecedented opportunities for evaluating HIV-1 transmission dynamics across sub-Saharan Africa and identifying prevention opportunities. Molecular epidemiological analyses of these data must proceed cautiously because sequence sampling remains below the identified threshold and a considerable negative impact of missing characters on phylogeny reconstruction is expected.
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Affiliation(s)
- Oliver Ratmann
- MRC Centre for Outbreak Analyses and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Chris Wymant
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Caroline Colijn
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Siva Danaviah
- Africa Health Research Institute, KwaZulu-Natal, South Africa
| | - Max Essex
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Simon Frost
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Astrid Gall
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Mary K. Grabowski
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Rakai Health Sciences Program, Entebbe, Uganda
| | - Ronald Gray
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Rakai Health Sciences Program, Entebbe, Uganda
| | - Stephane Guindon
- Department of Statistics, University of Auckland, Auckland, New Zealand
- Laboratoire d'Informatique, de Robotique et de Microelectronique de Montpellier–UMR 5506, CNRS & UM, Montpellier, France
| | - Arndt von Haeseler
- Centre for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, Vienna, Austria
- Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria
| | | | - Michelle Kendall
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Alexey Kozlov
- Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
| | - Justen Manasa
- Africa Health Research Institute, KwaZulu-Natal, South Africa
| | - Bui Quang Minh
- Centre for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, Vienna, Austria
| | - Sikhulile Moyo
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Vlad Novitsky
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | | | | | - Thomas C. Quinn
- Rakai Health Sciences Program, Entebbe, Uganda
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, Maryland
- Department of Medicine Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - David Serwadda
- Rakai Health Sciences Program, Entebbe, Uganda
- Makerere University School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda
| | | | - Alexandros Stamatakis
- Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
- Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Jana Trifinopoulos
- Centre for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, Vienna, Austria
| | - Maria Wawer
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Rakai Health Sciences Program, Entebbe, Uganda
| | - Andy Leigh Brown
- School of Biological Sciences, Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Tulio de Oliveira
- Nelson R. Mandela School of Medicine, School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Paul Kellam
- Department of Infectious Diseases and Immunity, Imperial College London, United Kingdom
| | - Deenan Pillay
- Africa Health Research Institute, KwaZulu-Natal, South Africa
- Division of Infection & Immunity, Faculty of Medical Sciences, University College London, London, United Kingdom
| | - Christophe Fraser
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
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12
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Vesa J, Chaillon A, Wagner GA, Anderson CM, Richman DD, Smith DM, Little SJ. Increased HIV-1 superinfection risk in carriers of specific human leukocyte antigen alleles. AIDS 2017; 31:1149-1158. [PMID: 28244954 PMCID: PMC5559224 DOI: 10.1097/qad.0000000000001445] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
OBJECTIVE The aim of this study was to characterize the demographic, behavioural, clinical and immunogenetic determinants of HIV-1 superinfection in a high-risk cohort of MSM. DESIGN A retrospective cohort study of prospectively followed MSM. METHODS Ninety-eight MSM with acute or early HIV-1 monoinfection were followed for a median of 15.6 months. Demographic and human leukocyte antigen (HLA) genotype data were collected at enrolment. Sexual behaviour, clinical and the infection status (monoinfection or superinfection) data were recorded at each visit (at enrolment and thereafter at a median of 4.2-month intervals). HIV-1 superinfection risk was determined by Cox regression and Kaplan-Meier survival analysis. RESULTS Ten individuals (10.2%) had superinfection during follow-up. Cox regression did not show significantly increased superinfection risk for individuals with an increased amount of condomless anal intercourse, lower CD4 T-cell count or higher viral load, but higher number of sexual contacts demonstrated a trend towards significance [hazard ratio, 4.74; 95% confidence interval (95% CI), 0.87-25.97; P = 0.073]. HLA-A*29 (hazard ratio, 4.10; 95% CI, 0.88-14.76; P = 0.069), HLA-B*35 (hazard ratio, 4.64; 95% CI, 1.33-18.17; P = 0.017), HLA-C*04 (hazard ratio, 5.30; 95% CI, 1.51-20.77; P = 0.010), HLA-C*16 (hazard ratio, 4.05; 95% CI, 0.87-14.62; P = 0.071), HLA-DRB1*07 (hazard ratio, 3.29; 95% CI, 0.94-12.90; P = 0.062) and HLA-DRB1*08 (hazard ratio, 15.37; 95% CI, 2.11-79.80; P = 0.011) were associated with an increased risk of superinfection at α = 0.10, whereas HLA-DRB1*11 was associated with decreased superinfection risk (hazard ratio, 0.13; 95% CI, 0.00-1.03; P = 0.054). CONCLUSION HLA genes may, in part, elucidate the genetic basis of differential superinfection risk, and provide important information for the development of efficient prevention and treatment strategies of HIV-1 superinfection.
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Affiliation(s)
- Jouni Vesa
- University of California San Diego, La Jolla
| | | | | | | | - Douglas D. Richman
- University of California San Diego, La Jolla
- Veterans Affairs San Diego Healthcare System, San Diego, California, USA
| | - Davey M. Smith
- University of California San Diego, La Jolla
- Veterans Affairs San Diego Healthcare System, San Diego, California, USA
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13
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Kitawi RC, Hunja CW, Aman R, Ogutu BR, Muigai AWT, Kokwaro GO, Ochieng W. Partial HIV C2V3 envelope sequence analysis reveals association of coreceptor tropism, envelope glycosylation and viral genotypic variability among Kenyan patients on HAART. Virol J 2017; 14:29. [PMID: 28196510 PMCID: PMC5310022 DOI: 10.1186/s12985-017-0703-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Accepted: 02/08/2017] [Indexed: 01/18/2023] Open
Abstract
Background HIV-1 is highly variable genetically and at protein level, a property it uses to subvert antiviral immunity and treatment. The aim of this study was to assess if HIV subtype differences were associated with variations in glycosylation patterns and co-receptor tropism among HAART patients experiencing different virologic treatment outcomes. Methods A total of 118 HIV env C2V3 sequence isolates generated previously from 59 Kenyan patients receiving highly active antiretroviral therapy (HAART) were examined for tropism and glycosylation patterns. For analysis of Potential N-linked glycosylation sites (PNGs), amino acid sequences generated by the NCBI’s Translate tool were applied to the HIVAlign and the N-glycosite tool within the Los Alamos Database. Viral tropism was assessed using Geno2Pheno (G2P), WebPSSM and Phenoseq platforms as well as using Raymond’s and Esbjörnsson’s rules. Chi square test was used to determine independent variables association and ANOVA applied on scale variables. Results At respective False Positive Rate (FPR) cut-offs of 5% (p = 0.045), 10% (p = 0.016) and 20% (p = 0.005) for CXCR4 usage within the Geno2Pheno platform, HIV-1 subtype and viral tropism were significantly associated in a chi square test. Raymond’s rule (p = 0.024) and WebPSSM (p = 0.05), but not Phenoseq or Esbjörnsson showed significant associations between subtype and tropism. Relative to other platforms used, Raymond’s and Esbjörnsson’s rules showed higher proportions of X4 variants, while WebPSSM resulted in lower proportions of X4 variants across subtypes. The mean glycosylation density differed significantly between subtypes at positions, N277 (p = 0.034), N296 (p = 0.036), N302 (p = 0.034) and N366 (p = 0.004), with HIV-1D most heavily glycosylated of the subtypes. R5 isolates had fewer PNGs than X4 isolates, but these differences were not significant except at position N262 (p = 0.040). Cell-associated isolates from virologic treatment success subjects were more glycosylated than cell-free isolates from virologic treatment failures both for the NXT (p = 0.016), and for all the patterns (p = 0.011). Conclusion These data reveal significant associations of HIV-1 subtype diversity, viral co-receptor tropism, viral suppression and envelope glycosylation. These associations have important implications for designing therapy and vaccines against HIV. Heavy glycosylation and preference for CXCR4 usage of HIV-1D may explain rapid disease progression in patients infected with these strains.
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Affiliation(s)
- Rose C Kitawi
- Center for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.,Jomo Kenyatta University of Agriculture and Technology, P.O Box 62000 -00200, Nairobi, Kenya
| | - Carol W Hunja
- Center for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.,South Eastern Kenya University, P.O Box 170-90200, Kitui, Kenya
| | - Rashid Aman
- Center for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.,African Center for Clinical Trials, P.O. Box 2288-00202, Nairobi, Kenya.,Kenya Medical Research Institute, P.O. Box 54840-00200, Nairobi, Kenya
| | - Bernhards R Ogutu
- Center for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.,Institute of Healthcare Management, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya.,Kenya Medical Research Institute, P.O. Box 54840-00200, Nairobi, Kenya
| | - Anne W T Muigai
- Jomo Kenyatta University of Agriculture and Technology, P.O Box 62000 -00200, Nairobi, Kenya
| | - Gilbert O Kokwaro
- Institute of Healthcare Management, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya
| | - Washingtone Ochieng
- Center for Research in Therapeutic Sciences, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya. .,Institute of Healthcare Management, Strathmore University, P.O. Box 59857-00200, Nairobi, Kenya. .,Kenya Medical Research Institute, P.O. Box 54840-00200, Nairobi, Kenya. .,Immunology and Infectious Diseases Dept, Harvard School of Public Health, Boston, MA, USA.
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14
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HIV diversity and drug resistance from plasma and non-plasma analytes in a large treatment programme in western Kenya. J Int AIDS Soc 2014; 17:19262. [PMID: 25413893 PMCID: PMC4238965 DOI: 10.7448/ias.17.1.19262] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2014] [Revised: 09/23/2014] [Accepted: 10/10/2014] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION Antiretroviral resistance leads to treatment failure and resistance transmission. Resistance data in western Kenya are limited. Collection of non-plasma analytes may provide additional resistance information. METHODS We assessed HIV diversity using the REGA tool, transmitted resistance by the WHO mutation list and acquired resistance upon first-line failure by the IAS-USA mutation list, at the Academic Model Providing Access to Healthcare (AMPATH), a major treatment programme in western Kenya. Plasma and four non-plasma analytes, dried blood-spots (DBS), dried plasma-spots (DPS), ViveST(TM)-plasma (STP) and ViveST-blood (STB), were compared to identify diversity and evaluate sequence concordance. RESULTS Among 122 patients, 62 were treatment-naïve and 60 treatment-experienced; 61% were female, median age 35 years, median CD4 182 cells/µL, median viral-load 4.6 log10 copies/mL. One hundred and ninety-six sequences were available for 107/122 (88%) patients, 58/62 (94%) treatment-naïve and 49/60 (82%) treated; 100/122 (82%) plasma, 37/78 (47%) attempted DBS, 16/45 (36%) attempted DPS, 14/44 (32%) attempted STP from fresh plasma and 23/34 (68%) from frozen plasma, and 5/42 (12%) attempted STB. Plasma and DBS genotyping success increased at higher VL and shorter shipment-to-genotyping time. Main subtypes were A (62%), D (15%) and C (6%). Transmitted resistance was found in 1.8% of plasma sequences, and 7% combining analytes. Plasma resistance mutations were identified in 91% of treated patients, 76% NRTI, 91% NNRTI; 76% dual-class; 60% with intermediate-high predicted resistance to future treatment options; with novel mutation co-occurrence patterns. Nearly 88% of plasma mutations were identified in DBS, 89% in DPS and 94% in STP. Of 23 discordant mutations, 92% in plasma and 60% in non-plasma analytes were mixtures. Mean whole-sequence discordance from frozen plasma reference was 1.1% for plasma-DBS, 1.2% plasma-DPS, 2.0% plasma-STP and 2.3% plasma-STB. Of 23 plasma-STP discordances, one mutation was identified in plasma and 22 in STP (p<0.05). Discordance was inversely significantly related to VL for DBS. CONCLUSIONS In a large treatment programme in western Kenya, we report high HIV-1 subtype diversity; low plasma transmitted resistance, increasing when multiple analytes were combined; and high-acquired resistance with unique mutation patterns. Resistance surveillance may be augmented by using non-plasma analytes for lower-cost genotyping in resource-limited settings.
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15
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Dennis AM, Herbeck JT, Brown AL, Kellam P, de Oliveira T, Pillay D, Fraser C, Cohen MS. Phylogenetic studies of transmission dynamics in generalized HIV epidemics: an essential tool where the burden is greatest? J Acquir Immune Defic Syndr 2014; 67:181-95. [PMID: 24977473 PMCID: PMC4304655 DOI: 10.1097/qai.0000000000000271] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Efficient and effective HIV prevention measures for generalized epidemics in sub-Saharan Africa have not yet been validated at the population level. Design and impact evaluation of such measures requires fine-scale understanding of local HIV transmission dynamics. The novel tools of HIV phylogenetics and molecular epidemiology may elucidate these transmission dynamics. Such methods have been incorporated into studies of concentrated HIV epidemics to identify proximate and determinant traits associated with ongoing transmission. However, applying similar phylogenetic analyses to generalized epidemics, including the design and evaluation of prevention trials, presents additional challenges. Here we review the scope of these methods and present examples of their use in concentrated epidemics in the context of prevention. Next, we describe the current uses for phylogenetics in generalized epidemics and discuss their promise for elucidating transmission patterns and informing prevention trials. Finally, we review logistic and technical challenges inherent to large-scale molecular epidemiological studies of generalized epidemics and suggest potential solutions.
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Affiliation(s)
- Ann M. Dennis
- Division of Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Andrew Leigh Brown
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Paul Kellam
- Wellcome Trust Sanger Institute, Cambridge, UK
- Division of Infection and Immunity, University College London, London, UK
| | - Tulio de Oliveira
- Wellcome Trust-Africa Centre for Health and Population Studies, University of Kwazula-Natal, ZA
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, UK
| | - Christophe Fraser
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Myron S. Cohen
- Division of Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC
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16
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Kiwelu IE, Novitsky V, Kituma E, Margolin L, Baca J, Manongi R, Sam N, Shao J, McLane MF, Kapiga SH, Essex M. HIV-1 pol diversity among female bar and hotel workers in Northern Tanzania. PLoS One 2014; 9:e102258. [PMID: 25003939 PMCID: PMC4087014 DOI: 10.1371/journal.pone.0102258] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2014] [Accepted: 06/16/2014] [Indexed: 11/18/2022] Open
Abstract
A national ART program was launched in Tanzania in October 2004. Due to the existence of multiple HIV-1 subtypes and recombinant viruses co-circulating in Tanzania, it is important to monitor rates of drug resistance. The present study determined the prevalence of HIV-1 drug resistance mutations among ART-naive female bar and hotel workers, a high-risk population for HIV-1 infection in Moshi, Tanzania. A partial HIV-1 pol gene was analyzed by single-genome amplification and sequencing in 45 subjects (622 pol sequences total; median number of sequences per subject, 13; IQR 5-20) in samples collected in 2005. The prevalence of HIV-1 subtypes A1, C, and D, and inter-subtype recombinant viruses, was 36%, 29%, 9% and 27%, respectively. Thirteen different recombination patterns included D/A1/D, C/A1, A1/C/A1, A1/U/A1, C/U/A1, C/A1, U/D/U, D/A1/D, A1/C, A1/C, A2/C/A2, CRF10_CD/C/CRF10_CD and CRF35_AD/A1/CRF35_AD. CRF35_AD was identified in Tanzania for the first time. All recombinant viruses in this study were unique, suggesting ongoing recombination processes among circulating HIV-1 variants. The prevalence of multiple infections in this population was 16% (n = 7). Primary HIV-1 drug resistance mutations to RT inhibitors were identified in three (7%) subjects (K65R plus Y181C; N60D; and V106M). In some subjects, polymorphisms were observed at the RT positions 41, 69, 75, 98, 101, 179, 190, and 215. Secondary mutations associated with NNRTIs were observed at the RT positions 90 (7%) and 138 (6%). In the protease gene, three subjects (7%) had M46I/L mutations. All subjects in this study had HIV-1 subtype-specific natural polymorphisms at positions 36, 69, 89 and 93 that are associated with drug resistance in HIV-1 subtype B. These results suggested that HIV-1 drug resistance mutations and natural polymorphisms existed in this population before the initiation of the national ART program. With increasing use of ARV, these results highlight the importance of drug resistance monitoring in Tanzania.
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Affiliation(s)
- Ireen E. Kiwelu
- Kilimanjaro Christian Medical Centre and College, Tumaini University, Moshi, Tanzania
- Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Vladimir Novitsky
- Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Elimsaada Kituma
- Kilimanjaro Christian Medical Centre and College, Tumaini University, Moshi, Tanzania
- Kilimanjaro Reproductive Health Program, Moshi, Tanzania
| | - Lauren Margolin
- Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Jeannie Baca
- Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Rachel Manongi
- Kilimanjaro Christian Medical Centre and College, Tumaini University, Moshi, Tanzania
- Kilimanjaro Reproductive Health Program, Moshi, Tanzania
| | - Noel Sam
- Kilimanjaro Christian Medical Centre and College, Tumaini University, Moshi, Tanzania
- Kilimanjaro Reproductive Health Program, Moshi, Tanzania
| | - John Shao
- Kilimanjaro Christian Medical Centre and College, Tumaini University, Moshi, Tanzania
| | - Mary F. McLane
- Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Saidi H. Kapiga
- London School of Hygiene and Tropical Medicine, London, United Kingdom
- Kilimanjaro Reproductive Health Program, Moshi, Tanzania
| | - M. Essex
- Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
- * E-mail:
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17
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Tanser F, de Oliveira T, Maheu-Giroux M, Bärnighausen T. Concentrated HIV subepidemics in generalized epidemic settings. Curr Opin HIV AIDS 2014; 9:115-25. [PMID: 24356328 PMCID: PMC4228373 DOI: 10.1097/coh.0000000000000034] [Citation(s) in RCA: 103] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW A relatively neglected topic to date has been the occurrence of concentrated epidemics within generalized epidemic settings and the potential role of targeted interventions in such settings. We review recent studies in high-risk groups as well as findings relating to geographical heterogeneity and the potential for targeting 'high-transmission zones' in the 10 countries with highest HIV prevalence. RECENT FINDINGS Our review of recent studies confirmed earlier findings that, even in the context of generalized epidemics, MSM have a substantially higher prevalence than the general population. Estimates of prevalence of HIV among people who inject drugs (PWID) in sub-Saharan African countries are rarely available and, when they are, often outdated. We identified recent studies of sex workers in Kenya and Uganda. In all three cases - MSM, PWID, and sex workers - HIV prevalence estimates are mostly based on convenience. Moreover, good estimates of the total size of these populations are not available. Our review of recent studies of high-risk populations defined on the basis of geography showed high levels of both new and existing infections in Kenya (slums), South Africa (peri-urban communities), and Uganda (fishing villages). SUMMARY Recent empirical findings combined with evidence from phylogenetic studies and supported by mathematical models provide a clear rationale for testing the feasibility, acceptability, and effectiveness of targeted HIV prevention approaches in hyperendemic populations to supplement measures aimed at the general population.
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Affiliation(s)
- Frank Tanser
- Africa Centre for Health and Population Studies, University of KwaZulu-Natal, SA
| | - Tulio de Oliveira
- Africa Centre for Health and Population Studies, University of KwaZulu-Natal, SA
| | - Mathieu Maheu-Giroux
- Department of Global Health and Population, Harvard School of Public Health, USA
| | - Till Bärnighausen
- Africa Centre for Health and Population Studies, University of KwaZulu-Natal, SA
- Department of Global Health and Population, Harvard School of Public Health, USA
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18
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Bezemer D, Faria NR, Hassan A, Hamers RL, Mutua G, Anzala O, Mandaliya K, Cane P, Berkley JA, Rinke de Wit TF, Wallis C, Graham SM, Price MA, Coutinho RA, Sanders EJ. HIV Type 1 transmission networks among men having sex with men and heterosexuals in Kenya. AIDS Res Hum Retroviruses 2014; 30:118-26. [PMID: 23947948 DOI: 10.1089/aid.2013.0171] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
We performed a molecular phylogenetic study on HIV-1 polymerase sequences of men who have sex with men (MSM) and heterosexual patient samples in Kenya to characterize any observed HIV-1 transmission networks. HIV-1 polymerase sequences were obtained from samples in Nairobi and coastal Kenya from 84 MSM, 226 other men, and 364 women from 2005 to 2010. Using Bayesian phylogenetics, we tested whether sequences clustered by sexual orientation and geographic location. In addition, we used trait diffusion analyses to identify significant epidemiological links and to quantify the number of transmissions between risk groups. Finally, we compared 84 MSM sequences with all HIV-1 sequences available online at GenBank. Significant clustering of sequences from MSM at both coastal Kenya and Nairobi was found, with evidence of HIV-1 transmission between both locations. Although a transmission pair between a coastal MSM and woman was confirmed, no significant HIV-1 transmission was evident between MSM and the comparison population for the predominant subtype A (60%). However, a weak but significant link was evident when studying all subtypes together. GenBank comparison did not reveal other important transmission links. Our data suggest infrequent intermingling of MSM and heterosexual HIV-1 epidemics in Kenya.
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Affiliation(s)
| | - Nuno Rodrigues Faria
- Department of Microbiology and Immunology, University of Leuven, Leuven, Belgium
| | - Amin Hassan
- Kenya Medical Research Institute, Centre for Geographic Medicine Research–Coast, Kilifi, Kenya
| | - Raph L. Hamers
- PharmAccess Foundation, Department of Global Health, Academic Medical Center of the University of Amsterdam, Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | - Gaudensia Mutua
- Kenya AIDS Vaccine Initiative, University of Nairobi, Nairobi, Kenya
| | - Omu Anzala
- Kenya AIDS Vaccine Initiative, University of Nairobi, Nairobi, Kenya
| | | | | | - James A. Berkley
- Kenya Medical Research Institute, Centre for Geographic Medicine Research–Coast, Kilifi, Kenya
- Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Tobias F. Rinke de Wit
- PharmAccess Foundation, Department of Global Health, Academic Medical Center of the University of Amsterdam, Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | | | - Susan M. Graham
- Kenya Medical Research Institute, Centre for Geographic Medicine Research–Coast, Kilifi, Kenya
- University of Washington, Seattle, Washington
| | - Matthew A. Price
- International AIDS Vaccine Initiative, New York, New York
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, California
| | - Roel A. Coutinho
- Centre for Infectious Disease Control, RIVM, Utrecht, The Netherlands
- Julius Center for Health Science and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Eduard J. Sanders
- Kenya Medical Research Institute, Centre for Geographic Medicine Research–Coast, Kilifi, Kenya
- Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
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19
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Kouyos RD, Rauch A, Boni J, Yerly S, Shah C, Aubert V, Klimkait T, Kovari H, Calmy A, Cavassini M, Battegay M, Vernazza PL, Bernasconi E, Ledergerber B, Gunthard HF, Aubert V, Barth J, Battegay M, Bernasconi E, Boni J, Bucher HC, Burton-Jeangros C, Calmy A, Cavassini M, Egger M, Elzi L, Fehr J, Fellay J, Francioli P, Furrer H, Fux CA, Gorgievski M, Gunthard H, Haerry D, Hasse B, Hirsch HH, Hirschel B, Hosli I, Kahlert C, Kaiser L, Keiser O, Kind C, Klimkait T, Kovari H, Ledergerber B, Martinetti G, Martinez de Tejada B, Metzner K, Muller N, Nadal D, Pantaleo G, Rauch A, Regenass S, Rickenbach M, Rudin C, Schmid P, Schultze D, Schoni-Affolter F, Schupbach J, Speck R, Taffe P, Tarr P, Telenti A, Trkola A, Vernazza P, Weber R, Yerly S. Clustering of HCV coinfections on HIV phylogeny indicates domestic and sexual transmission of HCV. Int J Epidemiol 2014; 43:887-96. [DOI: 10.1093/ije/dyt276] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
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20
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Koning FA, Badhan A, Shaw S, Fisher M, Mbisa JL, Cane PA. Dynamics of HIV type 1 recombination following superinfection. AIDS Res Hum Retroviruses 2013; 29:963-70. [PMID: 23495713 DOI: 10.1089/aid.2013.0009] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
There are currently few detailed studies describing HIV-1 recombination events or the potential impact of recombination on drug resistance. We describe here the viral recombination dynamics in a drug-naive patient initially infected with a circulating recombinant form 19 (CRF19) virus containing transmitted drug resistance mutations followed by superinfection with "wild-type" subtype B virus. Single genome analysis showed replacement of the primary CRF19 virus by recombinants of the CRF19 virus and the superinfecting subtype B virus. The CRF19/B recombinant virus dominating after superinfection had lost drug resistance mutations and at no time was the superinfecting subtype B variant found to be dominant in blood plasma. Furthermore, the detection of recombinant viruses in seminal plasma indicates the potential for onward transmission of these strains.
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Affiliation(s)
- Fransje A. Koning
- Virus Reference Department, Public Health England, London, United Kingdom
| | - Anjna Badhan
- Virus Reference Department, Public Health England, London, United Kingdom
| | - Simon Shaw
- Brighton and Sussex University Hospitals NHS Trust, Department of HIV and GUM, Royal Sussex County Hospital, Brighton, United Kingdom
| | - Martin Fisher
- Brighton and Sussex University Hospitals NHS Trust, Department of HIV and GUM, Royal Sussex County Hospital, Brighton, United Kingdom
| | - Jean L. Mbisa
- Virus Reference Department, Public Health England, London, United Kingdom
| | - Patricia A. Cane
- Virus Reference Department, Public Health England, London, United Kingdom
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21
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Nyamache AK, Muigai AW, Khamadi SA. Circulating trends of non-B HIV type 1 subtypes among Kenyan individuals. AIDS Res Hum Retroviruses 2013; 29:400-3. [PMID: 22916803 DOI: 10.1089/aid.2012.0213] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
As the AIDS pandemic progresses, an increasingly broad range of genetic diversity continues to be reported within the main (M) group of HIV-1 viruses with viral subtype predominating in specific geographic areas. To determine the genetic diversity of HIV-1 subtypes among Kenyan individuals, the env-C2-V3 gene was successfully sequenced in samples from 176 patients. Analysis of the sequences showed that a majority of them belonged to subtype A1: 73.9% (130/176), followed by C: 10.8% (19/176), D: 10.2% (18/176), and 0.6% (1/176) for G and A2 as pure subtypes while the rest were recombinants of A1/U: 2.3% (4/176) and 0.6% (1/176) each for D/U, A/C/U, and AC. Similar to previous studies conducted in other parts of Kenya, HIV-1 subtype A1 still remains the most predominant subtype while subtype C continues to show an increasing prevalence. Continued surveillance of circulating subtypes of HIV-1 in Kenya is important in determining the evolution of the HIV/AIDS epidemic in Kenya.
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Affiliation(s)
- Anthony Kebira Nyamache
- Department of Plant and Microbial Sciences, Kenyatta University, Nairobi, Kenya
- Centre for Virus Research, Kenya Medical Research Institute, Nairobi, Kenya
| | - Anne W.T. Muigai
- Department of Botany and Microbiology, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
| | - Samoel A. Khamadi
- Centre for Virus Research, Kenya Medical Research Institute, Nairobi, Kenya
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22
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Hassan AS, Mwaringa SM, Obonyo CA, Nabwera HM, Sanders EJ, Rinke de Wit TF, Cane PA, Berkley JA. Low prevalence of transmitted HIV type 1 drug resistance among antiretroviral-naive adults in a rural HIV clinic in Kenya. AIDS Res Hum Retroviruses 2013; 29:129-35. [PMID: 22900472 DOI: 10.1089/aid.2012.0167] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Low levels of HIV-1 transmitted drug resistance (TDR) have previously been reported from many parts of sub-Saharan Africa (sSA). However, recent data, mostly from urban settings, suggest an increase in the prevalence of HIV-1 TDR. Our objective was to determine the prevalence of TDR mutations among HIV-1-infected, antiretroviral (ARV)-naive adults enrolling for care in a rural HIV clinic in Kenya. Two cross-sectional studies were carried out between July 2008 and June 2010. Plasma samples from ARV-naive adults (>15 years old) at the time of registering for care after HIV diagnosis and before starting ARVs were used. A portion of the pol subgenomic region of the virus containing the protease and part of the reverse transcriptase genes was amplified and sequenced. TDR mutations were identified and interpreted using the Stanford HIV drug resistance database and the WHO list for surveillance of drug resistance strains. Overall, samples from 182 ARV-naive adults [mean age (95% CI): 34.9 (33.3-36.4) years] were successfully amplified and sequenced. Two TDR mutations to nucleoside reverse transcriptase inhibitors [n=1 (T215D)] and protease inhibitors [n=1 (M46L)] were identified, giving an overall TDR prevalence of 1.1% (95% CI: 0.1-3.9). Despite reports of an increase in the prevalence of HIV-1 TDR in some urban settings in sSA, we report a prevalence of HIV-1 TDR of less than 5% at a rural HIV clinic in coastal Kenya. Continued broader surveillance is needed to monitor the extent of TDR in sSA.
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Affiliation(s)
| | | | | | | | - Eduard J. Sanders
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Clinical Vaccinology and Tropical Medicine, University of Oxford, Oxford, United Kingdom
| | - Tobias F. Rinke de Wit
- PharmAccess Foundation, Amsterdam, The Netherlands
- Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | | | - James A. Berkley
- KEMRI/Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Clinical Vaccinology and Tropical Medicine, University of Oxford, Oxford, United Kingdom
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23
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Delatorre EO, Bello G. Phylodynamics of HIV-1 subtype C epidemic in east Africa. PLoS One 2012; 7:e41904. [PMID: 22848653 PMCID: PMC3407063 DOI: 10.1371/journal.pone.0041904] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2012] [Accepted: 06/27/2012] [Indexed: 11/18/2022] Open
Abstract
The HIV-1 subtype C accounts for an important fraction of HIV infections in east Africa, but little is known about the genetic characteristics and evolutionary history of this epidemic. Here we reconstruct the origin and spatiotemporal dynamics of the major HIV-1 subtype C clades circulating in east Africa. A large number (n = 1,981) of subtype C pol sequences were retrieved from public databases to explore relationships between strains from the east, southern and central African regions. Maximum-likelihood phylogenetic analysis of those sequences revealed that most (>70%) strains from east Africa segregated in a single regional-specific monophyletic group, here called CEA. A second major Ethiopian subtype C lineage and a large collection of minor Kenyan and Tanzanian subtype C clades of southern African origin were also detected. A Bayesian coalescent-based method was then used to reconstruct evolutionary parameters and migration pathways of the CEA African lineage. This analysis indicates that the CEA clade most probably originated in Burundi around the early 1960s, and later spread to Ethiopia, Kenya, Tanzania and Uganda, giving rise to major country-specific monophyletic sub-clusters between the early 1970s and early 1980s. The results presented here demonstrate that a substantial proportion of subtype C infections in east Africa resulted from dissemination of a single HIV local variant, probably originated in Burundi during the 1960s. Burundi was the most important hub of dissemination of that subtype C clade in east Africa, fueling the origin of new local epidemics in Ethiopia, Kenya, Tanzania and Uganda. Subtype C lineages of southern African origin have also been introduced in east Africa, but seem to have had a much more restricted spread.
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Affiliation(s)
| | - Gonzalo Bello
- Laboratório de AIDS & Imunologia Molecular, Instituto Oswaldo Cruz, Rio de Janeiro, Brazil
- * E-mail:
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