Research Article: Inferring HIV Transmission Dynamics from Phylogenetic Sequence Relationships

Date Published: March 18, 2008

Publisher: Public Library of Science

Author(s): Christopher D Pilcher, Joseph K Wong, Satish K Pillai

Abstract: New insights into HIV transmission dynamics, say the authors, are likely to come from analyzing the viral sequence information that is being routinely collected during HIV genotyping.

Partial Text: Despite the range of resources directed at understanding the HIV pandemic over the past 25 years, surprisingly little is known about how HIV infection spreads through populations. Unlike some other infectious diseases, acute infection with HIV is difficult to identify. HIV disease most often manifests years after the transmission event. Together with the special challenges involved in determining exposures related to sexual behavior or drug use, all of these factors have made it difficult to apply the tools of traditional epidemiologic investigation. Recent antibody testing strategies to identify incident HIV for surveillance programs have met with limited success [1]. Key questions that remain unanswered by empirical data include the role of acute infections in sustaining the current pandemic, and the effects of antiretroviral treatment programs on transmission of drug-resistant and drug-susceptible strains of HIV. Without really understanding how HIV spreads, it is difficult to optimize prevention or control strategies.

Leigh Brown and colleagues were interested in better understanding the epidemiology of HIV among men who have sex with men in London. To this end, they obtained access to a relatively large convenience sample of HIV pol sequences (see Glossary) obtained through the routine testing of 2,126 unique HIV-infected patients served by a large university medical center in London. They used a “phylodynamic” approach, an interdisciplinary blend of immunodynamics, epidemiology, and evolutionary biology, to infer the short-term dynamics of HIV transmission in the base population from relationships among sequences in their study sample.

Phylogenetic sequence analysis has been used extensively in HIV epidemiology. These data are commonly used to support the identity of supposed “transmission pairs” for purposes of contact investigation [3], translational biological studies [4], and epidemiologic studies in which HIV transmission is an outcome [5]. Looking at larger sequence databases, a number of investigators have taken the clustering outcome as evidence of individual membership in a contact network or as an (indirect) marker of infectivity. Their studies have correlated clustering with acute disease stage [6–8], viral factors [9], risk behaviors [7,10], and even geography [10]. The present study is distinguished from these reports by its focus on the internal architecture of the sequence clusters. Leigh Brown and colleagues’ ability to study internal cluster structure clearly depends on access to large numbers of clustered sequences (which might relate in turn to either the structure of underlying contact networks or to the density of population sampling).

If application of Leigh Brown and colleagues’ phylodynamic methods to HIV can be further validated and their results confirmed by additional investigators, the finding that HIV is frequently transmitted through discrete outbreaks would suggest the need for a stronger emphasis on outbreak detection and network intervention/outbreak control strategies [11]. These strategies are currently used for other diseases, such as syphilis and tuberculosis. In this context, it is worth noting that sequence data-mining techniques can be as easily misused as used properly [12]. Guidelines are needed to clarify individual privacy rights and provide a legal framework for dealing with such sequence data that balances patient autonomy with scientific and public health objectives. Until then, exceptional caution should be used in dealing with phylogenetic/dynamic associations at the individual level.



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