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Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

ABSTRACT: HIV-1 set-point viral load-the approximately stable value of viraemia in the first years of chronic infection-is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from 6% to 59%. Here we used a dataset of 2,028 seroconverters infected between 1985 and 2013 from 5 European countries (Belgium, Switzerland, France, the Netherlands and the United Kingdom) and estimated the heritability of set-point viral load at 31% (CI 15%-43%). Specifically, heritability was measured using models of character evolution describing how viral load evolves on the phylogeny of whole-genome viral sequences. In contrast to previous studies, (i) we measured viral loads using standardized assays on a sample collected in a strict time window of 6 to 24 months after infection, from which the viral genome was also sequenced; (ii) we compared 2 models of character evolution, the classical "Brownian motion" model and another model ("Ornstein-Uhlenbeck") that includes stabilising selection on viral load; (iii) we controlled for covariates, including age and sex, which may inflate estimates of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral loads in cherries of the phylogenetic tree, showing that both models of character evolution fit the data well. An overall heritability of 31% (CI 15%-43%) is consistent with other studies based on regression of viral load in donor-recipient pairs. Thus, about a third of variation in HIV-1 virulence is attributable to viral genetic variation.

SUBMITTER: Blanquart F

PROVIDER: S-EPMC5467800 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

Blanquart François F Wymant Chris C Cornelissen Marion M Gall Astrid A Bakker Margreet M Bezemer Daniela D Hall Matthew M Hillebregt Mariska M Ong Swee Hoe SH Albert Jan J Bannert Norbert N Fellay Jacques J Fransen Katrien K Gourlay Annabelle J AJ Grabowski M Kate MK Gunsenheimer-Bartmeyer Barbara B Günthard Huldrych F HF Kivelä Pia P Kouyos Roger R Laeyendecker Oliver O Liitsola Kirsi K Meyer Laurence L Porter Kholoud K Ristola Matti M van Sighem Ard A Vanham Guido G Berkhout Ben B Kellam Paul P Reiss Peter P Fraser Christophe C

PLoS biology 20170612 6

HIV-1 set-point viral load-the approximately stable value of viraemia in the first years of chronic infection-is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from ...[more]

PMID: 28604782

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Project description:HIV viral load (VL) predicts both transmission potential and rate of disease progression. For reasons that are still not fully understood, the set point viral load (SPVL) established after acute infection varies across individuals and populations. Previous studies have suggested that population mean SPVL (MSPVL) has evolved near an optimum that reflects a trade-off between transmissibility and host survival. Sexual network structures affect rates of potential exposure during different within-host phases of infection marked by different transmission probabilities, and thus affect the number and timing of transmission events. These structures include relational concurrency, which has been argued to explain key differences in HIV burden across populations. We hypothesize that concurrency will alter the fitness landscape for SPVL in ways that differ from other network features whose impacts accrue at other times during infection. To quantitatively test this hypothesis, we developed a dynamic, stochastic, data-driven network model of HIV transmission, and evolution to assess the impact of key sexual network phenomena on MSPVL evolution. Experiments were repeated in sensitivity runs that made different assumptions about transmissibility during acute infection, SPVL heritability, and the functional form of the relationship between VL and transmissibility. For our main transmission model, scenarios yielded MSPVLs ranging from 4.4 to 4.75 log10 copies/ml, covering much of the observed empirical range. MSPVL evolved to be higher in populations with high concurrency and shorter relational durations, with values varying over a clinically significant range. In linear regression analyses on these and other predictors, main effects were significant (P < 0.05), as were interaction terms, indicating that effects are interdependent. We also noted a strong correlation between two key emergent properties measured at the end of the simulations-MSPVL and HIV prevalence-most clearly for phenomena that affect transmission networks early in infection. Controlling for prevalence, high concurrency yielded higher MSPVL than other network phenomena. Interestingly, we observed lower prevalence in runs in which SPVL heritability was zero, indicating the potential for viral evolution to exacerbate disease burden over time. Future efforts to understand empirical variation in MSPVL should consider local HIV burden and basic sexual behavioral and network structure.

Project description:Abstract Background HIV-1 set-point viral load (SPVL) is predictive of disease progression and shows variability across HIV-1-positive (HIV+) persons. Various factors may influence SPVL including viral features, environmental exposure and host genetics. To identify single nucleotide polymorphisms (SNPs) associated with SPVL, we performed a genome-wide association study (GWAS) on a subset of participants from the Strategic Timing of AntiRetroviral Treatment (START) study covering a demographically diverse population. Methods. Consenting participants were antiretroviral therapy (ART)-naïve and SPVL was taken as log10(HIV RNA) at study entry. Genotypic data were generated on a custom content Affymetrix Axiom SNP array covering 770,558 probes. The Ensembl Gene database, assembly GRCh37.p13, was used for annotation. Principal component analysis (PCA) was used to identify population structures, and analysis of variance (ANOVA) was performed to detect associations between SNPs and SPVL. SNPs with zero variance or minor allele frequency (MAF) ?0.05 were removed. Results. Among the 2,544 participants, PCA showed distinct population structures with strong separation between black (n = 578) and nonblack (n = 1,966) participants, Figure 1. ANOVA was performed independently on both subsets. Two SNPs located in the Major Histocompatibility Complex (MHC) class I region of chromosome six reached genome-wide significance (P < 5 × 10–8) in the non-black population: rs4418214 (P = 1.74 × 10-10), and rs57989216 (P = 3.96 × 10–8), Figure 2. Two additional SNPs, rs9264942 (P = 5.99 × 10–8) and rs7356880 (P = 9.69 × 10–8), in the same region approached significance. The minor alleles of all four SNPs were associated with lower SPVL, Figure 3. While no SNPs reached genome-wide significance in the black group, we observed similar trends toward lower SPVL for both rs4418214 and rs57989216. Conclusion. In this study we confirm the association of a previously reported SNP (rs4418214) and identify a novel candidate SNP (rs57989216) associated with lower SPVL in a population of nonblack, ART-naïve HIV+ persons. Current findings suggest that the effects of these SNPs are consistent across race groups, but further studies are required to confirm this. Our results support previous findings that variation in the MHC class I region is a major host determinant of HIV-1 control. Disclosures D. D. Murray, Centre of Excellence for Health, Immunity and Infectious diseases (CHIP), Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark: Employee, Salary. J. M. Molina, Gilead: Scientific Advisor, Consulting fee. Merck: Scientific Advisor, Consulting fee. ViiV: Scientific Advisor, Consulting fee. Teva: Scientific Advisor, Consulting fee.

Dataset Information

Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

Publications

Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe.

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