| Description | 1 BioInfoExperts, Thibodaux, Louisiana; 2 Big Data Institute, University of Oxford, United Kingdom; 3 Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), and 4 Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; 5 Genomics Unit, Research Technologies Section, Rocky Mountain Laboratories, Division of Intramural Research, NIAID, NIH, Hamilton, Montana 6 Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland; 7 Science Facilitation Department, FHI360, Durham, Chapel Hill, North Carolina; 8 Vaccine and Infectious Disease Science Division, Fred Hutchinson Cancer Research Institute, Seattle, Washington; 9 College of Medicine–Johns Hopkins Project, Blantyre, Malawi; 10 Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; 11 University of Zimbabwe, Harare; 12 YRGCARE Medical Centre, Chennai, India; 13 Research Institute for Health Sciences, Chiang Mai University, Thailand; 14 Hospital Geral de Nova Iguaçu and 15 Laboratorio de
AIDS e Imunologia Molecular (IOC/Fiocruz) and 16Instituto Nacional de Infectologia Evandro Chagas-INI-Fiocruz, Rio de Janeiro, Brazil; 17 Centers for Disease Control and Prevention (CDC) Division of HIV/AIDS Prevention/KEMRI–CDC Research and Public Health Collaboration HIV Research Branch, Kisumu, Kenya; 18 Botswana Harvard AIDS Institute, Gabarone; 19 Servico de Infectologia, Hospital Nossa Senhora da Conceicao/GHC, Porto Alegre, Brazil; 20 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. | pt_BR |
| Abstract | Background: We evaluated use of phylogenetic methods to predict the direction of human immunodeficiency virus (HIV) transmission. Methods: For 33 pairs of HIV-infected patients (hereafter, “index patients”) and their partners who acquired genetically linked HIV infection during the study, samples were collected from partners and index patients close to the time when the partner seroconverted (hereafter, “SC samples”); for 31 pairs, samples collected from the index patient at an earlier time point (hereafter, “early index samples”) were also available. Phylogenies were inferred using env next-generation sequences (1 tree per pair/subtype). The direction of transmission (DoT) predicted from each tree was classified as correct or incorrect on the basis of which sequences (those from the index patient or the partner) were closest to the root. DoT was also assessed using maximum parsimony to infer ancestral node states for 100 bootstrap trees. Results: DoT was predicted correctly for both single-pair and subtype-specific trees in 22 pairs (67%) by using SC samples and in 23 pairs (74%) by using early index samples. DoT was predicted incorrectly for 4 pairs (15%) by using SC or early index samples. In the bootstrap analysis, DoT was predicted correctly for 18 pairs (55%) by using SC samples and for 24 pairs (73%) by using early index samples. DoT was predicted incorrectly for 7 pairs (21%) by using SC samples and for 4 pairs (13%) by using early index samples. Conclusions: Phylogenetic methods based solely on the tree topolog. | pt_BR |
