Longitudinal Trends in Western Australian HIV-1 Sequence Diversity and Viral Transmission Networks and Their Influence on Clinical Parameters: 2000-2014

Adaptation to HLA-associated immune pressure over the course of HIV infection and in circulating HIV-1 strains

Adaptation to human leukocyte antigen (HLA)-associated immune pressure represents a major driver of human immunodeficiency virus (HIV) evolution at both the individual and population level. To date, there has been limited exploration of the impact of the initial cellular immune response in driving viral adaptation, the dynamics of these changes during infection and their effect on circulating transmitting viruses at the population level. Capturing detailed virological and immunological data from acute and early HIV infection is challenging as this commonly precedes the diagnosis of HIV infection, potentially by many years. In addition, rapid initiation of antiretroviral treatment following a diagnosis is the standard of care, and central to global efforts towards HIV elimination. Yet, acute untreated infection is the critical period in which the diversity of proviral reservoirs is first established within individuals, and associated with greater risk of onward transmissions in a population. Characterizing the viral adaptations evident in the earliest phases of infection, coinciding with the initial cellular immune responses is therefore relevant to understanding which changes are of greatest impact to HIV evolution at the population level. In this study, we utilized three separate cohorts to examine the initial CD8+ T cell immune response to HIV (cross-sectional acute infection cohort), track HIV evolution in response to CD8+ T cell-mediated immunity over time (longitudinal chronic infection cohort) and translate the impact of HLA-driven HIV evolution to the population level (cross-sectional HIV sequence data spanning 30 years). Using next generation viral sequencing and enzyme-linked immunospot interferon-gamma recall responses to peptides representing HLA class I-specific HIV T cell targets, we observed that CD8+ T cell responses can select viral adaptations prior to full antibody seroconversion. Using the longitudinal cohort, we uncover that viral adaptations have the propensity to be retained over time in a non-selective immune environment, which reflects the increasing proportion of pre-adapted HIV strains within the Western Australian population over an approximate 30-year period.

Natural selection favoring more transmissible HIV detected in United States molecular transmission network

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.

HIV-1 subtype diversity, transmitted drug resistance and phylogenetics in Australia

Australia has maintained a low prevalence of HIV, with a mainly concentrated epidemic and successful public health response. With the widespread availability of HIV genotyping for resistance testing, and development of phylogenetic methodologies, the field of molecular epidemiology has evolved a deeper understanding of diversity and transmission dynamics of HIV. Studies combining HIV genotype with epidemiological data have allowed insights to be gained into the changing subtype diversity, rates of transmitted drug resistance and transmission networks of HIV in Australia. This review provides an overview of HIV molecular epidemiology studies in Australia.

Defining HIV-1 transmission clusters based on sequence data

Understanding HIV-1 transmission dynamics is relevant to both screening and intervention strategies of HIV-1 infection. Commonly, HIV-1 transmission chains are determined based on sequence similarity assessed either directly from a sequence alignment or by inferring a phylogenetic tree. This review is aimed at both nonexperts interested in understanding and interpreting studies of HIV-1 transmission, and experts interested in finding the most appropriate cluster definition for a specific dataset and research question. We start by introducing the concepts and methodologies of how HIV-1 transmission clusters usually have been defined. We then present the results of a systematic review of 105 HIV-1 molecular epidemiology studies summarizing the most common methods and definitions in the literature. Finally, we offer our perspectives on how HIV-1 transmission clusters can be defined and provide some guidance based on examples from real life datasets.

A national study of the molecular epidemiology of HIV-1 in Australia 2005-2012

Introduction

Rates of new HIV-1 diagnoses are increasing in Australia, with evidence of an increasing proportion of non-B HIV-1 subtypes reflecting a growing impact of migration and travel. The present study aims to define HIV-1 subtype diversity patterns and investigate possible HIV-1 transmission networks within Australia.

Methods

The Australian Molecular Epidemiology Network (AMEN) HIV collaborating sites in Western Australia, South Australia, Victoria, Queensland and western Sydney (New South Wales), provided baseline HIV-1 partial pol sequence, age and gender information for 4,873 patients who had genotypes performed during 2005–2012. HIV-1 phylogenetic analyses utilised MEGA V6, with a stringent classification of transmission pairs or clusters (bootstrap ≥98%, genetic distance ≤1.5% from at least one other sequence in the cluster).

Results

HIV-1 subtype B represented 74.5% of the 4,873 sequences (WA 59%, SA 68.4%, w-Syd 73.8%, Vic 75.6%, Qld 82.1%), with similar proportion of transmission pairs and clusters found in the B and non-B cohorts (23% vs 24.5% of sequences, p = 0.3). Significantly more subtype B clusters were comprised of ≥3 sequences compared with non-B clusters (45.0% vs 24.0%, p = 0.021) and significantly more subtype B pairs and clusters were male-only (88% compared to 53% CRF01_AE and 17% subtype C clusters). Factors associated with being in a cluster of any size included; being sequenced in a more recent time period (p<0.001), being younger (p<0.001), being male (p = 0.023) and having a B subtype (p = 0.02). Being in a larger cluster (>3) was associated with being sequenced in a more recent time period (p = 0.05) and being male (p = 0.008).

Conclusion

This nationwide HIV-1 study of 4,873 patient sequences highlights the increased diversity of HIV-1 subtypes within the Australian epidemic, as well as differences in transmission networks associated with these HIV-1 subtypes. These findings provide epidemiological insights not readily available using standard surveillance methods and can inform the development of effective public health strategies in the current paradigm of HIV prevention in Australia.