The role of HIV replicative fitness in perinatal transmission of HIV

Using viral sequence diversity to estimate time of HIV infection in infants

Age at HIV acquisition may influence viral pathogenesis in infants, and yet infection timing (i.e. date of infection) is not always known. Adult studies have estimated infection timing using rates of HIV RNA diversification, however, it is unknown whether adult-trained models can provide accurate predictions when used for infants due to possible differences in viral dynamics. While rates of viral diversification have been well defined for adults, there are limited data characterizing these dynamics for infants. Here, we performed Illumina sequencing of gag and pol using longitudinal plasma samples from 22 Kenyan infants with well-characterized infection timing. We used these data to characterize viral diversity changes over time by designing an infant-trained Bayesian hierarchical regression model that predicts time since infection using viral diversity. We show that diversity accumulates with time for most infants (median rate within pol = 0.00079 diversity/month), and diversity accumulates much faster than in adults (compare previously-reported adult rate within pol = 0.00024 diversity/month [1]). We find that the infant rate of viral diversification varies by individual, gene region, and relative timing of infection, but not by set-point viral load or rate of CD4+ T cell decline. We compare the predictive performance of this infant-trained Bayesian hierarchical regression model with simple linear regression models trained using the same infant data, as well as existing adult-trained models [1]. Using an independent dataset from an additional 15 infants with frequent HIV testing to define infection timing, we demonstrate that infant-trained models more accurately estimate time since infection than existing adult-trained models. This work will be useful for timing HIV acquisition for infants with unknown infection timing and for refining our understanding of how viral diversity accumulates in infants, both of which may have broad implications for the future development of infant-specific therapeutic and preventive interventions.

Effective early antiretroviral therapy in perinatal-HIV infection reduces subsequent plasma inflammatory profile

BACKGROUND

The long-term immunologic effects of antiretroviral therapy (ART) in children with perinatally-acquired HIV (PHIV) have not been fully elucidated. Here, we investigated how the timing of ART initiation affects the long-term immune profile of children living with PHIV by measuring immunomodulatory plasma cytokines, chemokines, and adenosine deaminases (ADAs).

METHODS

40 PHIV participants initiated ART during infancy. 39 participant samples were available; 30 initiated ART ≤6 months (early-ART treatment); 9 initiated ART >6 months and <2 years (late-ART treatment). We compared plasma cytokine and chemokine concentrations and ADA enzymatic activities between early-ART and late-ART treatment 12.5 years later and measured correlation with clinical covariates.

RESULTS

Plasma concentrations of 10 cytokines and chemokines (IFNγ, IL-12p70, IL-13, IL-17A, IL-IRA, IL-5, IL-6, and IL-9 as well as CCL7, CXCL10), ADA1, and ADA total were significantly higher in late-ART compared to early-ART treatment. Furthermore, ADA1 was significantly positively correlated with IFNγ, IL-17A, and IL-12p70. Meanwhile, total ADA was positively correlated with IFNγ, IL-13, IL-17A, IL-1RA, IL-6, and IL-12p70 as well as CCL7.

CONCLUSIONS

Elevation of several pro-inflammatory plasma analytes in late-ART despite 12.5 years of virologic suppression compared to early-ART treatment suggests that early treatment dampens the long-term plasma inflammatory profile in PHIV participants.

IMPACT

This study examines differences in the plasma cytokine, chemokine, and ADA profiles 12.5 years after treatment between early (≤6months) and late (>6 months and <2 years) antiretroviral therapy (ART) treatment initiation in a cohort of European and UK study participants living with PHIV. Several cytokines and chemokines (e.g., IFNγ, IL-12p70, IL-6, and CXCL10) as well as ADA-1 are elevated in late-ART treatment in comparison to early-ART treatment. Our results suggest that effective ART treatment initiated within 6 months of life in PHIV participants dampens a long-term inflammatory plasma profile as compared to late-ART treatment.

Clinical Determinants of HIV-1B Between-Host Evolution and their Association with Drug Resistance in Pediatric Patients

Understanding the factors that modulate the evolution of virus populations is essential to design efficient control strategies. Mathematical models predict that factors affecting viral within-host evolution may also determine that at the between-host level. Although HIV-1 within-host evolution has been associated with clinical factors used to monitor AIDS progression, such as patient age, CD4 cells count, viral load, and antiretroviral experience, little is known about the role of these clinical factors in determining between-host HIV-1 evolution. Moreover, whether the relative importance of such factors in HIV-1 evolution vary in adult and children patients, in which the course of infection is different, has seldom been analysed. To address these questions, HIV-1 subtype B (HIV-1B) pol sequences of 163 infected children and 450 adults of Madrid, Spain, were used to estimate genetic diversity, rates of synonymous and non-synonymous mutations, selection pressures and frequency of drug-resistance mutations (DRMs). The role and relative importance of patient age, %CD4, CD4/mm3, viral load, and antiretroviral experience in HIV-1B evolution was analysed. In the pediatric HIV-1B population, three clinical factors were primary predictors of virus evolution: Higher HIV-1B genetic diversity was observed with increasing children age, decreasing CD4/mm3 and upon antiretroviral experience. This was mostly due to higher rates of non-synonymous mutations, which were associated with higher frequency of DRMs. Using this data, we have also constructed a simple multivariate model explaining between 55% and 66% of the variance in HIV-1B evolutionary parameters in pediatric populations. On the other hand, the analysed clinical factors had little effect in adult-infecting HIV-1B evolution. These findings highlight the different evolutionary dynamics of HIV-1B in children and adults, and contribute to understand the factors shaping HIV-1B evolution and the appearance of drug-resistance mutation in pediatric patients.