Joshua T. Herbeck

Founder Effects in the Assessment of HIV Polymorphisms and HLA Allele Associations

Escape from T cell–mediated immune responses affects the ongoing evolution of rapidly evolving viruses such as HIV. By applying statistical approaches that account for phylogenetic relationships among viral sequences, we show that viral lineage effects rather than immune escape often explain apparent human leukocyte antigen (HLA)–mediated immune-escape mutations defined by older analysis methods. Phylogenetically informed methods identified immune-susceptible locations with greatly improved accuracy, and the associations we identified with these methods were experimentally validated. This approach has practical implications for understanding the impact of host immunity on pathogen evolution and for defining relevant variants for inclusion in vaccine antigens.

Human immunodeficiency virus type 1 env evolves toward ancestral states upon transmission to a new host

ABSTRACT Selecting human immunodeficiency virus (HIV) sequences for inclusion within vaccines has been a difficult problem, as circulating HIV strains evolve relentlessly and become increasingly divergent over time. We report an assessment of this divergence from three perspectives: (i) across different hosts as a function of time of infection, (ii) between donors and recipients in known transmission pairs, and (iii) within individual hosts over time in relation to the initially replicating virus and to the deduced ancestral sequence of the intrahost viral population. Surprisingly, we consistently found less divergence between viruses from different individuals sampled in primary infection than in individuals sampled at more advanced stages of illness. Furthermore, longitudinal analysis of intrahost divergence revealed a 2- to 3-year period of evolution toward a common ancestral sequence at the start of infection, indicating that HIV recovers certain ancestral features when infecting a new host. These results have important implications for the study of HIV population genetics and rational vaccine design, including favoring the inclusion of viral gene sequences taken early in infection.

Viral evolution and escape during acute HIV-1 infection.

The extensive genetic diversity of human immunodeficiency virus type 1 (HIV-1) presents a significant barrier to the development of an effective and durable HIV vaccine. This variability not only makes it difficult to identify the targets against which immune responses should be directed, but it also confers on the virus the capacity for rapid escape from effective immune responses. Here, we describe recent investigations of the genetic diversity of HIV-1 at transmission and of the evolution of the virus as it adapts to the host immune environment during the acute phase of HIV-1 infection. These studies increase our understanding of the virology of the earliest stages of HIV-1 infection and provide critical insights into the mechanisms underlying viral replication and immune control of diverse HIV-1 strains. Such knowledge will inform the design of smarter, more effective vaccines capable of inducing immune control of HIV-1.

Association Study of Common Genetic Variants and HIV-1 Acquisition in 6,300 Infected Cases and 7,200 Controls

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6×10−11). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception of CCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size.

Demographic Processes Affect HIV-1 Evolution in Primary Infection before the Onset of Selective Processes

ABSTRACT HIV-1 transmission and viral evolution in the first year of infection were studied in 11 individuals representing four transmitter-recipient pairs and three independent seroconverters. Nine of these individuals were enrolled during acute infection; all were men who have sex with men (MSM) infected with HIV-1 subtype B. A total of 475 nearly full-length HIV-1 genome sequences were generated, representing on average 10 genomes per specimen at 2 to 12 visits over the first year of infection. Single founding variants with nearly homogeneous viral populations were detected in eight of the nine individuals who were enrolled during acute HIV-1 infection. Restriction to a single founder variant was not due to a lack of diversity in the transmitter as homogeneous populations were found in recipients from transmitters with chronic infection. Mutational patterns indicative of rapid viral population growth dominated during the first 5 weeks of infection and included a slight contraction of viral genetic diversity over the first 20 to 40 days. Subsequently, selection dominated, most markedly in env and nef. Mutants were detected in the first week and became consensus as early as day 21 after the onset of symptoms of primary HIV infection. We found multiple indications of cytotoxic T lymphocyte (CTL) escape mutations while reversions appeared limited. Putative escape mutations were often rapidly replaced with mutually exclusive mutations nearby, indicating the existence of a maturational escape process, possibly in adaptation to viral fitness constraints or to immune responses against new variants. We showed that establishment of HIV-1 infection is likely due to a biological mechanism that restricts transmission rather than to early adaptive evolution during acute infection. Furthermore, the diversity of HIV strains coupled with complex and individual-specific patterns of CTL escape did not reveal shared sequence characteristics of acute infection that could be harnessed for vaccine design.

Multistage Genomewide Association Study Identifies a Locus at 1q41 Associated with Rate of HIV-1 Disease Progression to Clinical AIDS

BACKGROUND A mean of 9-10 years of human immunodeficiency virus type 1 (HIV-1) infection elapse before clinical AIDS develops in untreated persons, but this rate of disease progression varies substantially among individuals. To investigate host genetic determinants of the rate of progression to clinical AIDS, we performed a multistage genomewide association study. METHODS The discovery stage comprised 156 individuals from the Multicenter AIDS Cohort Study, enriched with rapid and long-term nonprogressors to increase statistical power. This was followed by replication tests of putatively associated genotypes in an independent population of 590 HIV-1-infected seroconverters. RESULTS Significant associations with delayed AIDS progression were observed in a haplotype located at 1q41, 36 kb upstream of PROX1 on chromosome 1 (relative hazard ratio, 0.69; Fishers combined P = 6.23 X 10(-7)). This association was replicated further in an analysis stratified by transmission mode, with the effect consistent in sexual or mucosal and parenteral transmission (relative hazard ratios, 0.72 and 0.63, respectively; combined P = 1.63 X 10(-6)). CONCLUSIONS This study identified and replicated a locus upstream of PROX1 that is associated with delayed progression to clinical AIDS. PROX1 is a negative regulator of interferon-gamma expression in T cells and also mitigates the advancement of vascular neoplasms, such as Kaposi sarcoma, a common AIDS-defining malignancy. This study adds to the cumulative polygenic host component that effectively regulates the progression to clinical AIDS among HIV-1-infected individuals, raising prospects for potential new avenues for therapy and improvements in AIDS prognosis.

Is the virulence of HIV changing? A meta-analysis of trends in prognostic markers of HIV disease progression and transmission

Objective:The potential for changing HIV-1 virulence has significant implications for the AIDS epidemic, including changing HIV transmission rates, rapidity of disease progression, and timing of ART. Published data to date have provided conflicting results. Design:We conducted a meta-analysis of changes in baseline CD4+ T-cell counts and set point plasma viral RNA load over time in order to establish whether summary trends are consistent with changing HIV-1 virulence. Methods:We searched PubMed for studies of trends in HIV-1 prognostic markers of disease progression and supplemented findings with publications referenced in epidemiological or virulence studies. We identified 12 studies of trends in baseline CD4+ T-cell counts (21 052 total individuals), and eight studies of trends in set point viral loads (10 785 total individuals), spanning the years 1984–2010. Using random-effects meta-analysis, we estimated summary effect sizes for trends in HIV-1 plasma viral loads and CD4+ T-cell counts. Results:Baseline CD4+ T-cell counts showed a summary trend of decreasing cell counts [effect = −4.93 cells/&mgr;l per year, 95% confidence interval (CI) −6.53 to −3.3]. Set point viral loads showed a summary trend of increasing plasma viral RNA loads (effect = 0.013 log10 copies/ml per year, 95% CI −0.001 to 0.03). The trend rates decelerated in recent years for both prognostic markers. Conclusion:Our results are consistent with increased virulence of HIV-1 over the course of the epidemic. Extrapolating over the 30 years since the first description of AIDS, this represents a CD4+ T cells loss of approximately 148 cells/&mgr;l and a gain of 0.39 log10 copies/ml of viral RNA measured during early infection. These effect sizes would predict increasing rates of disease progression, and need for ART as well as increasing transmission risk.

Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load

Significance A proportion of the variation in HIV-1 viral load in the infected population is influenced by host genetics. Using a large sample of infected individuals (n = 6,315) with genome-wide genotype data, we sought to map genomic regions that influence HIV viral load and quantify their impact. We identified amino acid positions located in the binding groove of class I HLA proteins (HLA-A and -B) and SNPs in the chemokine (C-C motif) receptor 5 gene region that together explain 14.5% of the observed variation in HIV viral load. Controlling for these signals, we estimated that an additional 5.5% can be explained by common, additive genetic variation. Thus, we demonstrate that common variants of large effect explain the majority of the host genetic component of HIV viral load. Previous genome-wide association studies (GWAS) of HIV-1–infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between ∼8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation—mostly in the HLA and CCR5 regions—explains 25% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward.

Lack of Evidence for Changing Virulence of HIV-1 in North America

Background Several long-term cohort studies and in-vitro fitness assays have resulted in inconsistent reports on changes in HIV-1 virulence, including reports of decreasing, stable, and increasing virulence over the course of the AIDS pandemic. We tested the hypothesis of changing HIV-1 virulence by examining trends in prognostic clinical markers of disease progression from 1984 to 2005 among nearly 400 antiretroviral-naïve participants in the United States Multicenter AIDS Cohort Study (MACS), a longitudinal study of HIV infection in men who have sex with men (MSM). Methodology/Principal Findings Because clinical AIDS endpoints could not be used (due to antiretroviral therapies and prophylaxis), three prognostic markers of disease progression were used as proxies for HIV-1 virulence: plasma viral RNA load and CD4+ T cell count at “set point” (between ∼9 and ∼15 months after seroconversion), and rate of CD4 cell decline within three years after seroconversion. We performed multivariate analyses of the association between these markers and seroconversion year, with covariates including MACS site, race/ethnic group, seroconversion age, and CCR5Δ32 status. No statistically significant association was found between year of seroconversion and “set point” plasma viral load (at ∼9 months after seroconversion: slope = −0.004 log10 copies/mL/year, p = 0.76; at ∼15 months: slope = −0.005 log10 copies/mL/year, p = 0.71), CD4 cell count after seroconversion (at ∼9 months: slope = −0.112 cells/µL/year, p = 0.22; at ∼15 months: slope = −0.047 cells/µL/year, p = 0.64), or rate of CD4 cell decline over the first three years after seroconversion (slope = −0.010 cells/ul/yr2, p = 0.88). Conclusions/Significance The lack of significant trends from 1984 to 2005 in these prognostic markers of HIV disease progression suggests no major change in HIV-1 virulence over the AIDS pandemic in MSM in the US.

Phylogenetic studies of transmission dynamics in generalized HIV epidemics: an essential tool where the burden is greatest?

Abstract:Efficient and effective HIV prevention measures for generalized epidemics in sub-Saharan Africa have not yet been validated at the population level. Design and impact evaluation of such measures requires fine-scale understanding of local HIV transmission dynamics. The novel tools of HIV phylogenetics and molecular epidemiology may elucidate these transmission dynamics. Such methods have been incorporated into studies of concentrated HIV epidemics to identify proximate and determinant traits associated with ongoing transmission. However, applying similar phylogenetic analyses to generalized epidemics, including the design and evaluation of prevention trials, presents additional challenges. Here we review the scope of these methods and present examples of their use in concentrated epidemics in the context of prevention. Next, we describe the current uses for phylogenetics in generalized epidemics and discuss their promise for elucidating transmission patterns and informing prevention trials. Finally, we review logistic and technical challenges inherent to large-scale molecular epidemiological studies of generalized epidemics and suggest potential solutions.