Pao D, Fisher M, Hue S, Dean G, Murphy G, Cane PA, et al. Transmission of HIV-1 during primary infection: relationship to sexual risk and sexually transmitted infections

University of Birmingham, Birmingham, England, United Kingdom
AIDS (Impact Factor: 5.55). 02/2005; 19(1):85-90. DOI: 10.1097/00002030-200501030-00010
Source: PubMed

ABSTRACT To study primary HIV-1 infections (PHI) using molecular and epidemiological approaches in order to assess correlates of transmission in this population.
Individuals with PHI were recruited prospectively from a discrete cohort of 1235 individuals under follow-up in a well-defined geographical area between 1999 and 2003. PHI was diagnosed by one of the following: negative HIV antibody test within 18 months, evolving antibody response, or application of the serological testing algorithm for recent HIV seroconversion. The pol gene was sequenced to identify genotypic resistance and facilitate molecular epidemiological analysis. Clinical data were collected and linked in an irretrievable fashion when informed consent was obtained.
A total of 103 individuals with PHI diagnosed between 1999 and 2003 were included in the study; 99 (96%) were male and 90 (91%) were men who have sex with men. Viruses from 35 out of 103 (34%) appeared within 15 phylogenetically related clusters. Significant associations with clustering were: young age, high CD4 cell count, number of sexual contacts, and unprotected anal intercourse (UAI) in the 3 months before diagnosis (P < 0.05 for all). High rates of acute sexually transmitted infections (STI) were observed in both groups with a trend towards higher rates in those individuals with viruses within a cluster (42.9 versus 27.9%; P = 0.13).
High rates of partner change, UAI and STI are factors that facilitate onward transmission during PHI. More active identification of individuals during PHI, the management of STI and highly active antiretroviral therapy may all be useful methods to break transmission networks.

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Available from: Patricia Cane, Sep 29, 2015
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    • "Even after an average of 19 months of observation and nearly 9 years of follow-up, divergence remained below 2% for all mono-infected individuals. These findings indicate that the 1% genetic distance cutoff invoked in previous epidemiological linkage studies is likely a conservative estimate to infer individuals belonging to the same transmission network [32], [33], [34]. "
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    ABSTRACT: Characterize intra-individual HIV-1 subtype B pol evolution in antiretroviral naive individuals. Longitudinal cohort study of individuals enrolled during primary infection. Eligible individuals were antiretroviral naïve participants enrolled in the cohort from December 1997-December 2005 and having at least two blood samples available with the first one collected within a year of their estimated date of infection. Population-based pol sequences were generated from collected blood samples and analyzed for genetic divergence over time in respect to dual infection status, HLA, CD4 count and viral load. 93 participants were observed for a median of 1.8 years (Mean = 2.2 years, SD = 1.9 years). All participants classified as mono-infected had less than 0.7% divergence between any two of their pol sequences using the Tamura-Nei model (TN93), while individuals with dual infection had up to 7.0% divergence. The global substitution rates (substitutions/nucleotide/year) for mono and dually infected individuals were significantly different (p<0.001); however, substitution rates were not associated with HLA haplotype, CD4 or viral load. Even after a maximum of almost 9 years of follow-up, all mono-infected participants had less than 1% divergence between baseline and longitudinal sequences, while participants with dual infection had 10 times greater divergence. These data support the use of HIV-1 pol sequence data to evaluate transmission events, networks and HIV-1 dual infection.
    PLoS ONE 06/2013; 8(6):e68188. DOI:10.1371/journal.pone.0068188 · 3.23 Impact Factor
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    • "Partial HIV-1 pol gene sequences routinely obtained for genotypic drug resistance testing are adequate to infer transmission events and to characterize epidemiological patterns of public health relevance (Hué et al., 2004). Phylogenetic analyses have been used to understand the contribution of recent HIV infections to onward transmission (Brenner et al., 2007; Pao et al., 2005), drug-resistance transmission in untreated populations (Brenner et al., 2008; Callegaro et al., 2011; Hué et al., 2009; Skoura et al., 2011; Yerly et al., 2009), HIV transmission in specific risk groups like MSM (Fisher et al., 2010; Lewis et al., 2008; Zehender et al., 2010), heterosexual population (Hughes et al., 2009) or injecting drug users (Skar et al., 2011), and the introduction and spread of different HIV-1 subtypes in Western countries (Gifford et al., 2007; von Wyl et al., 2011). Specifically , Bayesian Markov chain-Monte Carlo (MCMC) approaches that include molecular clock models have greatly contributed by placing HIV-1 transmissions in a real time-frame, allowing the estimation of the origin and tempo of HIV spread (Brenner et al., 2011; Callegaro et al., 2011; Chalmet et al., 2010; Gifford et al., 2007; Hué et al., 2009; Hué et al., 2005; Hughes et al., 2009; Lewis et al., 2008; Zehender et al., 2010). "
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    ABSTRACT: Background: The combination of phylogenetic analyses of HIV sequences with patients' demographic data allows us to understand local HIV transmission, a necessary knowledge for designing prevention strategies. The Community of Madrid represents a challenge for the control of HIV epidemic in Spain given its high HIV prevalence and increasing proportion of immigrant people among HIV-infected population. Methods: We applied maximum likelihood methods and Bayesian Markov chain Monte Carlo (MCMC) inference using the program BEAST to a set of HIV-1 pol sequences from 1293 patients diagnosed in 1995-2010 in Madrid, Spain. Results: Two-hundred and thirty six patients (18.2% of the cohort) were included in 100 transmission chains using phylogenetic criteria, 67 (67%) belonging to HIV-1 subtype B and 33 (33%) to 11 different non-B strains, especially BG and BF recombinants. Most networks involved transmission between MSM (48/100). Half of non-B clusters (15/33) included at least one Spaniard. Sub-Saharan African patients presented a low linkage rate (9%) in contrast to Spanish (21%) and Latin American (25%) patients. Three clusters involving treatment-independent transmission of drug-resistance mutations were found. Conclusions: One out of five HIV-infected patients in our cohort in Madrid was epidemically linked, mainly by transmission pairs. The inclusion in transmission networks was more likely for MSM, Spaniards and patients from Latin America. We found no evidence of self-sustained non-B epidemics due to the absence of large transmission chains with the exception of Cuban BG recombinants and CRF47_BF. However, the differences in transmission across variants are probably determined by the patient profile, especially the infection route.
    Infection, genetics and evolution: journal of molecular epidemiology and evolutionary genetics in infectious diseases 01/2013; 14(1). DOI:10.1016/j.meegid.2012.12.006 · 3.02 Impact Factor
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    • "Diagnoses of infection cases of chronic viruses in early phase are usually made in only a small population of individuals (Pao et al., 2005; Pilcher et al., 2005). Clinical surveillance can also acquire a small number of patients as compared with a whole population of person who is infected in virus with very rapid spreading, such as pandemic influenza. "
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    ABSTRACT: Viral infections by sexual and droplet transmission routes typically spread through a complex host-to-host contact network. Clarifying the transmission network and epidemiological parameters affecting the variations and dynamics of a specific pathogen is a major issue in the control of infectious diseases. However, conventional methods such as interview and/or classical phylogenetic analysis of viral gene sequences have inherent limitations and often fail to detect infectious clusters and transmission connections. Recent improvements in computational environments now permit the analysis of large datasets. In addition, novel analytical methods have been developed that serve to infer the evolutionary dynamics of virus genetic diversity using sample date information and sequence data. This type of framework, termed "phylodynamics," helps connect some of the missing links on viral transmission networks, which are often hard to detect by conventional methods of epidemiology. With sufficient number of sequences available, one can use this new inference method to estimate theoretical epidemiological parameters such as temporal distributions of the primary infection, fluctuation of the pathogen population size, basic reproductive number, and the mean time span of disease infectiousness. Transmission networks estimated by this framework often have the properties of a scale-free network, which are characteristic of infectious and social communication processes. Network analysis based on phylodynamics has alluded to various suggestions concerning the infection dynamics associated with a given community and/or risk behavior. In this review, I will summarize the current methods available for identifying the transmission network using phylogeny, and present an argument on the possibilities of applying the scale-free properties to these existing frameworks.
    Frontiers in Microbiology 07/2012; 3:278. DOI:10.3389/fmicb.2012.00278 · 3.99 Impact Factor
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