Bridging epidemiology with population genetics in a low incidence MSM-driven HIV-1 subtype B epidemic in Central Europe

Global associations of key populations with HIV-1 recombinants: a systematic review, global survey, and individual participant data meta-analysis

Introduction

Global HIV infections due to HIV-1 recombinants are increasing and impede prevention and treatment efforts. Key populations suffer most new HIV infections, but their role in the spread of HIV-1 recombinants is unknown. We conducted a global analysis of the associations between key populations and HIV-1 recombinants.

Methods

We searched PubMed, EMBASE, CINAHL, and Global Health for HIV-1 subtyping studies published from 1/1/1990 to 31/12/2015. Unpublished data was collected through a global survey. We included studies with HIV-1 subtyping data of key populations collected during 1990-2015. Key populations assessed were heterosexual people (HET), men who have sex with men (MSM), people who inject drugs (PWID), vertical transmissions (VERT), commercial sex workers (CSW), and transfusion-associated infections (BLOOD). Logistic regression was used to determine associations of key populations with HIV-1 recombinants. Subgroup analyses were performed for circulating recombinant forms (CRFs), unique recombinant forms (URFs), regions, and time periods.

Results

Eight hundred and eighty five datasets including 77,284 participants from 83 countries were included. Globally, PWID were associated with the greatest odds of recombinants and CRFs (OR 2.6 [95% CI 2.46-2.74] and 2.99 [2.83-3.16]), compared to HET. CSW were associated with increased odds of recombinants and URFs (1.59 [1.44-1.75] and 3.61 [3.15-4.13]). VERT and BLOOD were associated with decreased odds of recombinants (0.58 [0.54-0.63] and 0.43 [0.33-0.56]). MSM were associated with increased odds of recombinants in 2010-2015 (1.43 [1.35-1.51]). Subgroup analyses supported our main findings.

Discussion

As PWID, CSW, and MSM are associated with HIV-1 recombinants, increased preventative measures and HIV-1 molecular surveillance are crucial within these key populations.

Systematic review registration

PROSPERO [CRD42017067164].

Temporal Trends in the Epidemiology of HIV in Turkey

OBJECTIVE

The aim of this study was to analyze the temporal trends of HIV epidemiology in Turkey from 2011 to 2016.

METHODS

Thirty-four teams from 28 centers at 17 different cities participated in this retrospective study. Participating centers were asked to complete a structured form containing questions about epidemiologic, demographic and clinical characteristics of patients presented with new HIV diagnosis between 2011 and 2016. Demographic data from all centers (complete or partial) were included in the analyses. For the cascade of care analysis, 15 centers that provided full data from 2011 to 2016 were included. Overall and annual distributions of the data were calculated as percentages and the Chi square test was used to determine temporal changes.

RESULTS

A total of 2,953 patients between 2011 and 2016 were included. Overall male to female ratio was 5:1 with a significant increase in the number of male cases from 2011 to 2016 (p<0.001). The highest prevalence was among those aged 25-34 years followed by the 35-44 age bracket. The most common reason for HIV testing was illness (35%). While the frequency of sex among men who have sex with men increased from 16% to 30.6% (p<0.001) over the study period, heterosexual intercourse (53%) was found to be the most common transmission route. Overall, 29% of the cases presented with a CD4 count of >500 cells/mm3 while 46.7% presented with a CD4 T cell count of <350 cells/mm3. Among newly diagnosed cases, 79% were retained in care, and all such cases initiated ART with 73% achieving viral suppression after six months of antiretroviral therapy.

CONCLUSION

The epidemiologic profile of HIV infected individuals is changing rapidly in Turkey with an increasing trend in the number of newly diagnosed people disclosing themselves as MSM. New diagnoses were mostly at a young age. The late diagnosis was found to be a challenging issue. Despite the unavailability of data for the first 90, Turkey is close to the last two steps of 90-90-90 targets.

Analysis of HIV-1 diversity, primary drug resistance and transmission networks in Croatia

Molecular epidemiology of HIV-1 infection in treatment-naive HIV-1 infected persons from Croatia was investigated. We included 403 persons, representing 92.4% of all HIV-positive individuals entering clinical care in Croatia in 2014–2017. Overall prevalence of transmitted drug resistance (TDR) was estimated at 16.4%. Resistance to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside RTI (NNRTIs) and protease inhibitors (PIs) was found in 11.4%, 6.7% and 2.5% of persons, respectively. Triple-class resistance was determined in 2.2% of individuals. In addition, a single case (1.0%) of resistance to integrase strand-transfer inhibitors (InSTIs) was found. Deep sequencing was performed on 48 randomly selected samples and detected additional TDR mutations in 6 cases. Phylogenetic inference showed that 347/403 sequences (86.1%) were part of transmission clusters and identified forward transmission of resistance in Croatia, even that of triple-class resistance. The largest TDR cluster of 53 persons with T215S was estimated to originate in the year 1992. Our data show a continuing need for pre-treatment HIV resistance testing in Croatia. Even though a low prevalence of resistance to InSTI was observed, surveillance of TDR to InSTI should be continued.

HIV-1 transmitted drug resistance in Slovenia and its impact on predicted treatment effectiveness: 2011-2016 update

HIV-positive individuals that have a detected transmitted drug resistance (TDR) at baseline have a higher risk of virological failure with antiretroviral therapy (ART). This study offers an update on the prevalence of TDR in Slovenia, looks for onward transmission of TDR, and reassesses the need for baseline drug resistance testing. Blinded questionnaires and partial pol sequences were obtained from 54.5% (168/308) of all of the patients diagnosed with HIV-1 from 2011 to 2016. Subtype B was detected in 82.7% (139/168) of patients, followed by subtype A (8.3%), subtype C (2.4%), and CRF01_AE (1.8%). Surveillance drug resistance mutations (SDRMs) were found in four individuals (2.4%), all of them men who have sex with men (MSM) and infected with subtype B. K103N was detected in two patients and T68D and T215D in one person each, corresponding to a prevalence of 0%, 1.2%, and 1.2% of TDR to protease inhibitors (PIs), nucleoside reverse transcriptase inhibitors (NRTIs), and non-NRTIs (NNRTIs), respectively. The impact of mutations on drug susceptibility was found to be most pronounced for NNRTIs. No forward spread of TDR within the country was observed; however, phylogenetic analysis revealed several new introductions of HIV into Slovenia in recent years, possibly due to increased risky behavior by MSM. This was indirectly confirmed by a substantial increase in syphilis cases and HIV-1 non-B subtypes during the study period. A drug-resistant HIV variant with good transmission fitness is thus more likely to be imported into Slovenia in the near future, and so TDR should be closely monitored.

Phylogenetic analysis of the Belgian HIV-1 epidemic reveals that local transmission is almost exclusively driven by men having sex with men despite presence of large African migrant communities

To improve insight in the drivers of local HIV-1 transmission in Belgium, phylogenetic, demographic, epidemiological and laboratory data from patients newly diagnosed between 2013 and 2015 were combined and analyzed. Characteristics of clustered patients, paired patients and patients on isolated branches in the phylogenetic tree were compared. The results revealed an overall high level of clustering despite the short time frame of sampling, with 47.6% of all patients having at least one close genetic counterpart and 36.6% belonging to a cluster of 3 or more individuals. Compared to patients on isolated branches, patients in clusters more frequently reported being infected in Belgium (95.1% vs. 47.6%; p < 0.001), were more frequently men having sex with men (MSM) (77.9% vs. 42.8%; p < 0.001), of Belgian origin (68.2% vs. 32.9%; p < 0.001), male gender (92.6% vs. 65.8%; p < 0.001), infected with subtype B or F (87.8% vs. 43.4%; p < 0.001) and diagnosed early after infection (55.4% vs. 29.0%; p < 0.001). Strikingly, Sub-Saharan Africans (SSA), overall representing 27.1% of the population were significantly less frequently found in clusters than on individual branches (6.0% vs. 41.8%; p < 0.001). Of the SSA that participated in clustered transmission, 66.7% were MSM and this contrasts sharply with the overall 12.0% of SSA reporting MSM. Transmission clusters with SSA were more frequently non-B clusters than transmission clusters without SSA (44.4% versus 18.2%). MSM-driven clusters with patients of mixed origin may account, at least in part, for the increasing spread of non-B subtypes to the native MSM population, a cross-over that has been particularly successful for subtype F and CRF02_AG. The main conclusions from this study are that clustered transmission in Belgium remains almost exclusively MSM-driven with very limited contribution of SSA. There were no indications for local ongoing clustered transmission of HIV-1 among SSA.

The molecular epidemiology of HIV-1 in the Comunidad Valenciana (Spain): analysis of transmission clusters

HIV infections are still a very serious concern for public heath worldwide. We have applied molecular evolution methods to study the HIV-1 epidemics in the Comunidad Valenciana (CV, Spain) from a public health surveillance perspective. For this, we analysed 1804 HIV-1 sequences comprising protease and reverse transcriptase (PR/RT) coding regions, sampled between 2004 and 2014. These sequences were subtyped and subjected to phylogenetic analyses in order to detect transmission clusters. In addition, univariate and multinomial comparisons were performed to detect epidemiological differences between HIV-1 subtypes, and risk groups. The HIV epidemic in the CV is dominated by subtype B infections among local men who have sex with men (MSM). 270 transmission clusters were identified (>57% of the dataset), 12 of which included ≥10 patients; 11 of subtype B (9 affecting MSMs) and one (n = 21) of CRF14, affecting predominately intravenous drug users (IDUs). Dated phylogenies revealed these large clusters to have originated from the mid-80s to the early 00 s. Subtype B is more likely to form transmission clusters than non-B variants and MSMs to cluster than other risk groups. Multinomial analyses revealed an association between non-B variants, which are not established in the local population yet, and different foreign groups.

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.

HIV transmission clusters among injecting drug users in Romania

Injection drug use is increasingly an important route of HIV transmission in Romania (from 1.5% of the newly diagnosed cases prior to 2010 to 31% in 2013). In this study we investigated the viral characteristics and relationships in newly HIV infected persons who inject drugs in Bucharest, Romania.

RESULTS

HIV-1 pol sequencing, followed by phylogenetic and clustering analysis was performed on blood from 37 injecting drug users (IDUs) newly diagnosed with HIV infection. While HIV subtype F1, the dominant strain in Romania since 1990, remains prevalent, new subtypes were found including G, B, B/G and B/F recombinants. Overall, 27 of the available sequences (72.9%) clustered with at least one other. Network and phylogenetic analysis revealed tight monophyletic clusters for both subtypes F and G, with short genetic distances between sequences, suggesting recent numerous acute to acute transmissions or single burst-type episodes. No transmitted drug-resistance mutations were identified. Greater immunosuppression was present in subjects forming the subtype G cluster, possibly indicating a faster rate of progression associated with this subtype.

CONCLUSIONS

The recent increasing numbers of IDU related HIV transmissions in Bucharest, has resulted in closely-knit transmission networks that maychange the genetic profile of the local HIV epidemic.

Phylodynamic and Phylogeographic Profiles of Subtype B HIV-1 Epidemics in South Spain

BACKGROUND

Since 1982, HIV-1 epidemics have evolved to different scenarios in terms of transmission routes, subtype distribution and characteristics of transmission clusters. We investigated the evolutionary history of HIV-1 subtype B in south Spain.

PATIENTS & METHODS

We studied all newly diagnosed HIV-1 subtype B patients in East Andalusia during the 2005-2012 period. For the analysis, we used the reverse transcriptase and protease sequences from baseline resistance, and the Trugene® HIV Genotyping kit (Siemens, Barcelona, Spain). Subtyping was done with REGA v3.0. The maximum likelihood trees constructed with RAxML were used to study HIV-1 clustering. Phylogeographic and phylodynamic profiles were studied by Bayesian inference methods with BEAST v1.7.5 and SPREAD v1.0.6.

RESULTS

Of the 493 patients infected with HIV-1 subtype B, 234 grouped into 55 clusters, most of which were small (44 clusters ≤ 5 patients, 31 with 2 patients, 13 with 3). The rest (133/234) were grouped into 11 clusters with ≥ 5 patients, and most (82%, 109/133) were men who have sex with men (MSM) grouped into 8 clusters. The association with clusters was more frequent in Spanish (p = 0.02) men (p< 0.001), MSM (p<0.001) younger than 35 years (p = 0.001) and with a CD4+ T-cell count above 350 cells/ul (p<0.001). We estimated the date of HIV-1 subtype B regional epidemic diversification around 1970 (95% CI: 1965-1987), with an evolutionary rate of 2.4 (95%CI: 1.7-3.1) x 10-3 substitutions/site/year. Most clusters originated in the 1990s in MSMs. We observed exponential subtype B HIV-1 growth in 1980-1990 and 2005-2008. The most significant migration routes for subtype B went from inland cities to seaside locations.

CONCLUSIONS

We provide the first data on the phylodynamic and phylogeographic profiles of HIV-1 subtype B in south Spain. Our findings of transmission clustering among MSMs should alert healthcare managers to enhance preventive measures in this risk group in order to prevent future outbreaks.

Integrating molecular epidemiology and social network analysis to study infectious diseases: Towards a socio-molecular era for public health

The number of public health applications for molecular epidemiology and social network analysis has increased rapidly since the improvement in computational capacities and the development of new sequencing techniques. Currently, molecular epidemiology methods are used in a variety of settings: from infectious disease surveillance systems to the description of disease transmission pathways. The latter are of great epidemiological importance as they let us describe how a virus spreads in a community, make predictions for the further epidemic developments, and plan preventive interventions. Social network methods are used to understand how infections spread through communities and what the risk factors for this are, as well as in improved contact tracing and message-dissemination interventions. Research is needed on how to combine molecular and social network data as both include essential, but not fully sufficient information on infection transmission pathways. The main differences between the two data sources are that, firstly, social network data include uninfected individuals unlike the molecular data sampled only from infected network members. Thus, social network data include more detailed picture of a network and can improve inferences made from molecular data. Secondly, network data refer to the current state and interactions within the social network, while molecular data refer to the time points when transmissions happened, which might have happened years before the sampling date. As of today, there have been attempts to combine and compare the data obtained from the two sources. Even though there is no consensus on whether and how social and genetic data complement each other, this research might significantly improve our understanding of how viruses spread through communities.

•

We summarise and analyse the roles of molecular evolution studies in molecular epidemiology of infectious diseases.

•

We review how social network and molecular sequence data have been integrated in the past.

•

We show how integrating social network and molecular evolution approaches may change the study of infectious diseases.