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HIV-1 Genetic Diversity

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Front. Microbiol. | doi: 10.3389/fmicb.2018.02799

Combining Phylogenetic and Network Approaches to Identify HIV-1 Transmission Links in San Mateo County, California

 Sudeb C. Dalai1, 2, 3*,  Dennis M. Junqueira4, 5*, Eduan Wilkinson4, 5, Sergei L. Kosakovsky Pond6,  Ranee Mehra7, Vivian Levy1, 2, Dennis Israelski8, Tulio de Oliveira4, 5 and  David Katzenstein1, 2
  • 1Division of Infectious Disease, School of Medicine, Stanford University, United States
  • 2Division of Infectious Disease, School of Medicine, Stanford University, United States
  • 3Division of Epidemiology, School of Public Health, University of California, Berkeley, United States
  • 4KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), South Africa
  • 5School of Laboratory Medicine and Medical Science, University of KwaZulu-Natal, South Africa
  • 6Department of Psychology, Temple University, United States
  • 7Department of Chronic Disease Epidemiology, Yale University School of Public Health, United States
  • 8School of Medicine, Stanford University, United States

The HIV epidemic in San Mateo County is sustained by multiple overlapping risk groups and is an important hub for HIV transmission in northern California. Limited access to care has historically led to delayed clinical presentation, higher rates of opportunistic infections, and high prevalence of antiretroviral drug resistance. The virologic and clinical consequences of treatment within these multiple ethnic and behavioral groups are poorly understood, highlighting the need for efficient surveillance strategies that are able to elucidate transmission networks and drug resistance patterns. We obtained sequence data from a group of 316 HIV-positive individuals in the San Mateo AIDS Program over a 14-year period and integrated epidemiologic, phylogenetic, and network approaches to characterize transmission clusters, risk factors and drug resistance. Drug resistance mutations were identified using the Stanford HIV Drug Resistance Database. A maximum likelihood tree was inferred in RAxML and subjected to clustering analysis in ClusterPicker. Network analysis using pairwise genetic distances was performed in HIV-TRACE. Participants were primarily male (60%), white Hispanics and non-Hispanics (32%) and African American (20.6%). The most frequent behavior risk factor was male-male sex (33.5%), followed by heterosexual (23.4%) and intravenous drug use (9.5%). Nearly all sequences were subtype B (96%) with subtypes A, C, and CRF01_AE also observed. Sequences from 65% of all participants had at least one drug resistance mutation. Clustered transmissions included a higher number of women when compared to non-clustered individuals and were more likely to include heterosexual or people who inject drugs (PWID). Detailed analysis of the largest network (N=47) suggested that PWID played a central role in overall transmission of HIV-1 as well as bridging men who have sex with men (MSM) transmission with heterosexual/PWID among primarily African American men. Combined phylogenetic and network analysis of HIV sequence data identified several overlapping risk factors in the epidemic, including MSM, heterosexual and PWID transmission with a disproportionate impact on African Americans and a high prevalence of drug resistance.

Keywords: HIV, Transmission links, California, phylogenetics, network

Received: 07 Aug 2018; Accepted: 31 Oct 2018.

Edited by:

Michael M. Thomson, Instituto de Salud Carlos III, Spain

Reviewed by:

Samuel R. Friedman, National Development and Research Institutes, United States
Juan Angel P. Galindo, Columbia University, United States  

Copyright: © 2018 Dalai, Junqueira, Wilkinson, Kosakovsky Pond, Mehra, Levy, Israelski, de Oliveira and Katzenstein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
MD, PhD. Sudeb C. Dalai, Division of Infectious Disease, School of Medicine, Stanford University, Stanford, 94305, California, United States,
Dr. Dennis M. Junqueira, KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Durban, 4001, South Africa,