HIV infection and hepatitis C virus genotype 1a are associated with phylogenetic clustering among people with recently acquired hepatitis C virus infection

Widespread hepatitis C virus transmission network among people who inject drugs in Kenya

OBJECTIVES

Hepatitis C virus (HCV) disproportionately affects people who inject drugs (PWID) worldwide. Despite carrying a high HCV burden, little is known about transmission dynamics in low- and middle-income countries.

METHODS

We recruited PWID from Nairobi and coastal cities and towns of Mombasa, Kilifi, and Malindi in Kenya at needle and syringe programs. Next-generation sequencing data from HCV hypervariable region 1 were analyzed using Global Hepatitis Outbreak and Surveillance Technology to identify transmission clusters.

RESULTS

HCV strains belonged to genotype 1a (n = 64, 46.0%), 4a (n = 72, 51.8%) and mixed HCV/1a/4a (n = 3, 2.2%). HCV/1a was dominant (61.2%) in Nairobi, whereas HCV/4a was dominant in Malindi (85.7%) and Kilifi (60.9%), and both genotypes were evenly identified in Mombasa (45.3% for HCV/1a and 50.9% for HCV/4a). Global Hepatitis Outbreak and Surveillance Technology identified 11 transmission clusters involving 90 cases. Strains in the two largest clusters (n = 38 predominantly HCV/4a and n = 32 HCV/1a) were sampled from all four sites.

CONCLUSIONS

Transmission clusters involving 64.7% of cases indicate an effective sampling of major HCV strains circulating among PWID. Large clusters involving 77.8% of clustered strains from Nairobi and Coast suggest successful introduction of two ancestral HCV/1a and HCV/4a strains to PWID and the existence of a widespread transmission network in the country. The disruption of this network is essential for HCV elimination.

Patterns and correlates of hepatitis C virus phylogenetic clustering among people living with HIV in Australia in the direct-acting antiviral era: A molecular epidemiology study among participants in the CEASE cohort

Background and Aims

In moving towards the elimination of hepatitis C virus (HCV) infection among people living with HIV, understanding HCV transmission patterns may provide insights to guide and evaluate interventions. In this study, we evaluated patterns of, and factors associated with HCV phylogenetic clustering among people living with HIV/HCV co-infection in Australia in the direct-acting antiviral era.

Methods

HCV RNA was extracted from dried blood spot (DBS) samples collected between 2014 and 2018 in the CEASE cohort study. The HCV Core-E2 region was amplified by a polymerase chain reaction and Sanger sequenced. Maximum likelihood phylogenetic trees (1000 bootstrap replicates) were used to identify patterns of clustering (3% genetic distance threshold). Mixed-effects logistic regression was used to determine correlates of phylogenetic clustering. Factors assessed were sexual risk behavior, education, injecting drug use, housing, employment, HIV viral load, age, sex, and sexuality.

Results

Phylogenetic trees were reconstructed for HCV subtype 1a (n = 139) and 3a (n = 63) sequences, with 29% (58/202) in a pair or cluster. Overall (n = 202), phylogenetic clustering was positively associated with younger age (under 40; adjusted odds ratio [aOR] 2.52, 95% confidence interval [CI] 1.20-5.29), and among gay and bisexual men (n = 168), was positively associated with younger age (aOR 2.61, 95% CI 1.10-6.19), higher education (aOR 2.58, 95% CI 1.09-6.13), and reporting high-risk sexual behavior (aOR 3.94, 95% CI 1.31-11.84). During follow-up, five reinfections were observed, but none were in phylogenetic clusters.

Conclusion

This study found a high proportion of phylogenetic relatedness, predominantly among younger people and gay and bisexual men reporting high-risk sexual behavior. Despite this, few reinfections were observed, and reinfections demonstrated little relationship with known clusters. These findings highlight the importance of rapid HCV treatment initiation, together with monitoring of the phylogeny.

Hepatitis C Co-infection in People Living With HIV—Epidemiologic Differences Between Men Who Have Sex With Men MSM and Non-MSM

People living with human immunodeficiency virus (PLHIV) constitute a unique group at higher risk of hepatitis C virus (HCV) co-infection. In light of the diverse profiles of PLHIV, we differentiated between men who have sex with men (MSM) and non-MSM in the characterization of the epidemiologic features of HIV/HCV co-infection. Clinical data of HCV co-infection patients from the HIV specialist clinic in Hong Kong were retrospectively collected in conjunction with their HIV subtypes and HCV genotypes. Logistic regression models were used to identify factors associated with HIV/HCV co-infection in MSM. Survival analysis was performed to compare the time lag between HIV and HCV diagnoses between two groups. Latent class analysis was conducted to describe the features of different classes of co-infections. Four classes of HIV/HCV co-infections were identified: local MSM acquiring HCV after HIV diagnosis, local MSM with HIV/HCV co-diagnoses, local non-MSM, and non-local non-MSM. Accounting for over half of the co-infections, MSM were more likely to be younger, local residents, and associated with HCV genotype 3, compared to genotypes 1 and 6 in non-MSM. Overall, MSM had higher odds of achieving HIV viral suppression and co-diagnosing with a sexually transmitted infection at HCV diagnosis, and having a longer time lag between HIV and HCV diagnoses. Drug injection accounted for a majority of non-MSM HCV infection. There were distinctive epidemiologic differences between MSM and non-MSM co-infected with HIV and HCV, the characteristics of which could inform intervention strategies for achieving HCV micro-elimination.

Identification of Genetically Related HCV Infections Among Self-Described Injecting Partnerships

BACKGROUND

The current opioid epidemic across the United States has fueled a surge in the rate of new hepatitis C virus (HCV) infections among young persons who inject drugs (PWIDs). Paramount to interrupting transmission is targeting these high-risk populations and understanding the underlying network structures facilitating transmission within these communities.

METHODS

Deep sequencing data were obtained for 52 participants from 32 injecting partnerships enrolled in the U-Find-Out (UFO) Partner Study, which is a prospective study of self-described injecting dyad partnerships from a large community-based study of HCV infection in young adult PWIDs from San Francisco. Phylogenetically linked transmission events were identified using traditional genetic-distance measures and viral deep sequence phylogenies reconstructed to determine the statistical support of inferences and the direction of transmission within partnerships.

RESULTS

Using deep sequencing data, we found that 12 of 32 partnerships were genetically similar and clustered. Three additional phylogenetic clusters were found describing novel putative transmission links outside of the injecting relationship. Transmission direction was inferred correctly for 5 partnerships with the incorrect transmission direction inferred in more than 50% of cases. Notably, we observed that phylogenetic linkage was most often associated with a lower number of network partners and involvement in a sexual relationship.

CONCLUSIONS

Deep sequencing of HCV among self-described injecting partnerships demonstrates that the majority of transmission events originate from outside of the injecting partnership. Furthermore, these findings caution that phylogenetic methods may be unable to routinely infer the direction of transmission among PWIDs especially when transmission events occur in rapid succession within high-risk networks.

Factors associated with phylogenetic clustering of hepatitis C among people who inject drugs in Baltimore

Background

The availability of effective, oral direct acting antivirals (DAAs) for hepatitis C virus (HCV) treatment has put elimination of HCV as a public health challenge within reach. However, little is known about the characteristics of transmission networks of people who inject drugs (PWID).

Methods

Sequencing of a segment of the HCV genome was performed on samples collected from a community-based cohort of PWID between August 2005 and December 2016. Phylogenetic trees were inferred, and clusters were identified (70% bootstrap threshold; 0.04 maximum genetic distance threshold). We describe sex, race, age difference, and HIV infection status of potential transmission partners. Logistic regression was used to assess factors associated with being in an HCV cluster.

Results

Of 508 HCV genotype 1 viremic PWID, 8% (n = 41) were grouped into 20 clusters, consisting of 19 pairs and 1 triad. In adjusted analyses, female sex (odds ratio [OR] 2.3 [95% confidence interval (CI) 1.2–4.5]) and HIV infection (OR 5.7 [CI 2.7–11.9]) remained independently associated with being in an HCV infection cluster.

Conclusions

Molecular epidemiological analysis reveals that, in this cohort of PWID in Baltimore, HIV infection and female sex were associated with HCV clustering. Combination HCV prevention interventions targeting HIV infected PWID and addressing HCV infection prevention needs of women have potential to advance HCV elimination efforts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-020-05546-x.

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.

Inferring putative transmission clusters with Phydelity

Current phylogenetic clustering approaches for identifying pathogen transmission clusters are limited by their dependency on arbitrarily defined genetic distance thresholds for within-cluster divergence. Incomplete knowledge of a pathogen’s underlying dynamics often reduces the choice of distance threshold to an exploratory, ad hoc exercise that is difficult to standardise across studies. Phydelity is a new tool for the identification of transmission clusters in pathogen phylogenies. It identifies groups of sequences that are more closely related than the ensemble distribution of the phylogeny under a statistically principled and phylogeny-informed framework, without the introduction of arbitrary distance thresholds. Relative to other distance threshold- and model-based methods, Phydelity outputs clusters with higher purity and lower probability of misclassification in simulated phylogenies. Applying Phydelity to empirical datasets of hepatitis B and C virus infections showed that Phydelity identified clusters with better correspondence to individuals that are more likely to be linked by transmission events relative to other widely used non-parametric phylogenetic clustering methods without the need for parameter calibration. Phydelity is generalisable to any pathogen and can be used to identify putative direct transmission events. Phydelity is freely available at https://github.com/alvinxhan/Phydelity.

A latent class approach to identify multi-risk profiles associated with phylogenetic clustering of recent hepatitis C virus infection in Australia and New Zealand from 2004 to 2015

INTRODUCTION

Over the last two decades, the incidence of hepatitis C virus (HCV) co-infection among men who have sex with men (MSM) living with HIV began increasing in post-industrialized countries. Little is known about transmission of acute or recent HCV, in particular among MSM living with HIV co-infection, which creates uncertainty about potential for reinfection after HCV treatment. Using phylogenetic methods, clinical, epidemiological and molecular data can be combined to better understand transmission patterns. These insights may help identify strategies to reduce reinfection risk, enhancing effectiveness of HCV treatment as prevention strategies. The aim of this study was to identify multi-risk profiles and factors associated with phylogenetic pairs and clusters among people with recent HCV infection.

METHODS

Data and specimens from five studies of recent HCV in Australia and New Zealand (2004 to 2015) were used. HCV Core-E2 sequences were used to infer maximum likelihood trees. Clusters were identified using 90% bootstrap and 5% genetic distance threshold. Multivariate logistic regression and latent class analyses were performed.

RESULTS

Among 237 participants with Core-E2 sequences, 47% were in a pair/cluster. Among HIV/HCV co-infected participants, 60% (74/123) were in a pair/cluster, compared to 30% (34/114) with HCV mono-infection (p < 0.001). HIV/HCV co-infection (vs. HCV mono-infection; adjusted odds ratio (AOR), 2.37, 95% confidence interval (CI), 1.45, 5.15) was independently associated with phylogenetic clustering. Latent class analysis identified three distinct risk profiles: (1) people who inject drugs, (2) HIV-positive gay and bisexual men (GBM) with low probability of injecting drug use (IDU) and (3) GBM with IDU & sexual risk behaviour. Class 2 (vs. Class 1, AOR 3.40; 95% CI, 1.52, 7.60), was independently associated with phylogenetic clustering. Many clusters displayed homogeneous characteristics, such as containing individuals exclusively from one city, individuals all with HIV/HCV co-infection or individuals sharing the same route of acquisition of HCV.

CONCLUSIONS

Clusters containing individuals with specific characteristics suggest that HCV transmission occurs through discrete networks, particularly among HIV/HCV co-infected individuals. The greater proportion of clustering found among HIV/HCV co-infected participants highlights the need to provide broad direct-acting antiviral access encouraging rapid uptake in this population and ongoing monitoring of the phylogeny.

Eliminating HIV/HCV co-infection in gay and bisexual men: is it achievable through scaling up treatment?

INTRODUCTION

Broad availability of direct-acting antiviral therapy for hepatitis C virus (HCV) raises the possibility that HCV prevalence and incidence can be reduced through scaling-up treatment, leading to the elimination of HCV. High rates of linkage to HIV care among HIV-infected gay and bisexual men may facilitate high uptake of HCV treatment, possibly making HCV elimination more achievable in this group. Areas covered: This review covers HCV elimination in HIV-infected gay and bisexual men, including epidemiology, spontaneous clearance and long term sequelae in the absence of direct-acting antiviral therapy; direct-acting antiviral therapy uptake and effectiveness in this group; HCV reinfection following successful treatment; and areas for further research. Expert commentary: Early data from the direct-acting antiviral era suggest that treatment uptake is increasing among HIV infected GBM, and SVR rates are very promising. However, in order to sustain current treatment rates, additional interventions at the behavioral, physician, and structural levels may be required to increase HCV diagnosis, including prompt detection of HCV reinfection. Timely consideration of these issues is required to maximize the population-level impact of HCV direct-acting antiviral therapy. Potential HCV transmissions from HIV-uninfected GBM, across international borders, and from those who are not GBM also warrant consideration.

Complex patterns of Hepatitis-C virus longitudinal clustering in a high-risk population

We investigated longitudinal viral clustering among and within subjects in a highly networked cohort of people who inject drugs (PWID). All subjects had estimated dates of infection and two or more E1 sequences (bp 943-1288 relative to H77) with 1 to 14years of follow up. Two methods (HIV-TRACE and PhyloPart) were used to determine clusters. Genetic distance thresholds were determined by comparing intra-and inter-host distances. Additional phylogenetic analysis was performed on subjects with complicated viral histories. At the optimal threshold of 3.9%, HIV-TRACE found 77 clusters and PhyloPart found 63 clusters, of which 27 and 32 contained multiple subjects, respectively. Furthermore, 1/3 of the subjects had sequences in different clusters over the course of the study, including some cases in which a later-sampled sequence matched a cluster detected much earlier in the infection, despite being separated by RNA-negative lab visit and detection of sequences in different clusters. A detailed phylogenetic analysis of four subjects with such patterns showed that in all four cases, the earlier and later variants grouped closely on the tree, and did not group with concurrent sequences from any other subject. These observations suggest that subjects are either experiencing rapid and recurring infection-clearance-reinfection cycles from the same source, or a single transmission event produces a chronic infection that may go undetected and/or co-circulate with different viruses from separate transmission events. Furthermore, our results show the utility of using longitudinal sampling to obtain a more comprehensive view of the viral linkages in high-risk populations.

A molecular transmission network of recent hepatitis C infection in people with and without HIV: Implications for targeted treatment strategies

Combining phylogenetic and network methodologies has the potential to better inform targeted interventions to prevent and treat infectious diseases. This study reconstructed a molecular transmission network for people with recent hepatitis C virus (HCV) infection and modelled the impact of targeting directly acting antiviral (DAA) treatment for HCV in the network. Participants were selected from three Australian studies of recent HCV from 2004 to 2014. HCV sequence data (Core-E2) from participants at the time of recent HCV detection were analysed to infer a network by connecting pairs of sequences whose divergence was ≤.03 substitutions/site. Logistic regression was used to identify factors associated with connectivity. Impact of targeting HCV DAAs at both HIV co-infected and random nodes was simulated (1 million replicates). Among 236 participants, 21% (n=49) were connected in the network. HCV/HIV co-infected participants (47%) were more likely to be connected compared to HCV mono-infected participants (16%) (OR 4.56; 95% CI; 2.13-9.74). Simulations targeting DAA HCV treatment to HCV/HIV co-infected individuals prevented 2.5 times more onward infections than providing DAAs to randomly selected individuals. Results demonstrate that genetic distance-based network analyses can be used to identify characteristics associated with HCV transmission, informing targeted prevention and treatment strategies.