HIV-1 subtype distribution trends and evidence of transmission clusters among incident cases in a rural clinical cohort in southwest Uganda, 2004-2010

Infection with HIV-1 subtype D among acutely infected Ugandans is associated with higher median concentration of cytokines compared to subtype A

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HIV-1 subtype D exhibited significantly higher median concentrations of cytokines

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IL-12/23p40 and IL-1α were associated with faster CD4⁺T cell count decline

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bFGF was associated with maintenance of CD4+ counts above 350 cells/microliter

Objective

The observation that HIV-1 subtype D progresses faster to disease than subtype A prompted us to examine cytokine levels early after infection within the predominant viral subtypes that circulate in Uganda and address the following research questions: (1) Do cytokine levels vary between subtypes A1 and D? (2) Do cytokine profiles correlate with disease outcomes?

Methods

To address these questions, HIV-1 subtypes were determined by population sequencing of the HIV-1 pol gene and 37 plasma cytokine concentrations were evaluated using V-Plex kits on Meso Scale Discovery platform in 65 recent sero-converters.

Results

HIV-1 subtype D (pol) infections exhibited significantly higher median plasma concentrations of IL-5, IL-16, IL-1α, IL-7, IL-17A, CCL11 (Eotaxin-1), CXCL10 (IP-10), CCL13 (MCP-4) and VEGF-D compared to subtype A1 (pol) infections. We also found that IL-12/23p40 and IL-1α were associated with faster CD4⁺T cell count decline, while bFGF was associated with maintenance of CD4+ counts above 350 cells/microliter.

Conclusion

Our results suggest that increased production of cytokines in early HIV infection may trigger a disruption of the immune environment and contribute to pathogenic mechanisms underlying the accelerated disease progression seen in individuals infected with HIV-1 subtype D in Uganda.

Incorporating Within-Host Diversity in Phylogenetic Analyses for Detecting Clusters of New HIV Diagnoses

Background

Phylogenetic analyses of HIV sequences are used to detect clusters and inform public health interventions. Conventional approaches summarize within-host HIV diversity with a single consensus sequence per host of the pol gene, obtained from Sanger or next-generation sequencing (NGS). There is growing recognition that this approach discards potentially important information about within-host sequence variation, which can impact phylogenetic inference. However, whether alternative summary methods that incorporate intra-host variation impact phylogenetic inference of transmission network features is unknown.

Methods

We introduce profile sampling, a method to incorporate within-host NGS sequence diversity into phylogenetic HIV cluster inference. We compare this approach to Sanger- and NGS-derived pol and near-whole-genome consensus sequences and evaluate its potential benefits in identifying molecular clusters among all newly-HIV-diagnosed individuals over six months at the largest HIV center in Rhode Island.

Results

Profile sampling cluster inference demonstrated that within-host viral diversity impacts phylogenetic inference across individuals, and that consensus sequence approaches can obscure both magnitude and effect of these impacts. Clustering differed between Sanger- and NGS-derived consensus and profile sampling sequences, and across gene regions.

Discussion

Profile sampling can incorporate within-host HIV diversity captured by NGS into phylogenetic analyses. This additional information can improve robustness of cluster detection.

The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003–2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06–1.54), being >25 years (aOR = 1.52; 95% CI, 1.16–2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22–9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections.

Phylogenetic and Demographic Characterization of Directed HIV-1 Transmission Using Deep Sequences from High-Risk and General Population Cohorts/Groups in Uganda

Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care.

Phylogeography of HIV-1 suggests that Ugandan fishing communities are a sink for, not a source of, virus from general populations

Although fishing communities (FCs) in Uganda are disproportionately affected by HIV-1 relative to the general population (GP), the transmission dynamics are not completely understood. We earlier found most HIV-1 transmissions to occur within FCs of Lake Victoria. Here, we test the hypothesis that HIV-1 transmission in FCs is isolated from networks in the GP. We used phylogeography to reconstruct the geospatial viral migration patterns in 8 FCs and 2 GP cohorts and a Bayesian phylogenetic inference in BEAST v1.8.4 to analyse the temporal dynamics of HIV-1 transmission. Subtype A1 (pol region) was most prevalent in the FCs (115, 45.1%) and GP (177, 50.4%). More recent HIV transmission pairs from FCs were found at a genetic distance (GD) <1.5% than in the GP (Fisher’s exact test, p = 0.001). The mean time depth for pairs was shorter in FCs (5 months) than in the GP (4 years). Phylogeographic analysis showed strong support for viral migration from the GP to FCs without evidence of substantial viral dissemination to the GP. This suggests that FCs are a sink for, not a source of, virus strains from the GP. Targeted interventions in FCs should be extended to include the neighbouring GP for effective epidemic control.

HIV-1 transmission networks in high risk fishing communities on the shores of Lake Victoria in Uganda: A phylogenetic and epidemiological approach

BACKGROUND

Fishing communities around Lake Victoria in sub-Saharan Africa have been characterised as a population at high risk of HIV-infection.

METHODS

Using data from a cohort of HIV-positive individuals aged 13-49 years, enrolled from 5 fishing communities on Lake Victoria between 2009-2011, we sought to identify factors contributing to the epidemic and to understand the underlying structure of HIV transmission networks. Clinical and socio-demographic data were combined with HIV-1 phylogenetic analyses. HIV-1 gag-p24 and env-gp-41 sub-genomic fragments were amplified and sequenced from 283 HIV-1-infected participants. Phylogenetic clusters with ≥2 highly related sequences were defined as transmission clusters. Logistic regression models were used to determine factors associated with clustering.

RESULTS

Altogether, 24% (n = 67/283) of HIV positive individuals with sequences fell within 34 phylogenetically distinct clusters in at least one gene region (either gag or env). Of these, 83% occurred either within households or within community; 8/34 (24%) occurred within household partnerships, and 20/34 (59%) within community. 7/12 couples (58%) within households clustered together. Individuals in clusters with potential recent transmission (11/34) were more likely to be younger 71% (15/21) versus 46% (21/46) in un-clustered individuals and had recently become resident in the community 67% (14/21) vs 48% (22/46). Four of 11 (36%) potential transmission clusters included incident-incident transmissions. Independently, clustering was less likely in HIV subtype D (adjusted Odds Ratio, aOR = 0.51 [95% CI 0.26-1.00]) than A and more likely in those living with an HIV-infected individual in the household (aOR = 6.30 [95% CI 3.40-11.68]).

CONCLUSIONS

A large proportion of HIV sexual transmissions occur within house-holds and within communities even in this key mobile population. The findings suggest localized HIV transmissions and hence a potential benefit for the test and treat approach even at a community level, coupled with intensified HIV counselling to identify early infections.

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.

Virological Response and Antiretroviral Drug Resistance Emerging during Antiretroviral Therapy at Three Treatment Centers in Uganda

Background

With the scale-up of antiretroviral therapy (ART), monitoring programme performance is needed to maximize ART efficacy and limit HIV drug resistance (HIVDR).

Methods

We implemented a WHO HIVDR prospective survey protocol at three treatment centers between 2012 and 2013. Data were abstracted from patient records at ART start (T1) and after 12 months (T2). Genotyping was performed in the HIV pol region at the two time points.

Results

Of the 425 patients enrolled, at T2, 20 (4.7%) had died, 66 (15.5%) were lost to follow-up, 313 (73.6%) were still on first-line, 8 (1.9%) had switched to second-line, 17 (4.0%) had transferred out and 1 (0.2%) had stopped treatment. At T2, 272 out of 321 on first and second line (84.7%) suppressed below 1000 copies/ml and the HIV DR prevention rate was 70.1%, just within the WHO threshold of ≥70%. The proportion of participants with potential HIVDR was 20.9%, which is higher than the 18.8% based on pooled analyses from African studies. Of the 35 patients with mutations at T2, 80% had M184V/I, 65.7% Y181C, and 48.6% (54.8% excluding those not on Tenofovir) had K65R mutations. 22.9% had Thymidine Analogue Mutations (TAMs). Factors significantly associated with HIVDR prevention at T2 were: baseline viral load (VL) <100,000 copies/ml [Adjusted odds ratio (AOR) 3.13, 95% confidence interval (CI): 1.36–7.19] and facility. Independent baseline predictors for HIVDR mutations at T2 were: CD4 count <250 cells/μl (AOR 2.80, 95% CI: 1.08–7.29) and viral load ≥100,000 copies/ml (AOR 2.48, 95% CI: 1.00–6.14).

Conclusion

Strengthening defaulter tracing, intensified follow-up for patients with low CD4 counts and/or high VL at ART initiation together with early treatment initiation above 250 CD4 cells/ul and adequate patient counselling would improve ART efficacy and HIVDR prevention. The high rate of K65R and TAMs could compromise second line regimens including NRTIs.

Impaired natural killer cell responses are associated with loss of the highly activated NKG2A(+)CD57(+)CD56(dim) subset in HIV-1 subtype D infection in Uganda

Objective:

Of the predominant HIV-1 subtypes in Uganda, subtype D infection confers a worse prognosis. HIV-1 infection causes perturbations to natural killer (NK) cells, and yet these cells can exert immune pressure on the virus and influence clinical outcome. Here, we studied NK cell activation and function in Ugandans with chronic untreated HIV-1 subtype D infection in comparison to uninfected community matched controls.

Methods:

Cryopreserved peripheral blood mononuclear cells (PBMCs) from 42 HIV-infected individuals and 28 HIV-negative controls were analysed using eight-colour flow cytometry. NK cell surface expression of CD16, CD56, CD57, HLA-DR and NKG2A were used to investigate activation, maturation and differentiation status. NK cell function was evaluated by measuring interferon-gamma (IFNγ) production in response to K562 cells, or interleukin (IL)-12 and IL-18.

Results:

CD56^dim NK cells from HIV-infected individuals produced less IFNγ in response to IL-12 and IL-18 than did CD56^dim NK cells from uninfected controls. Infected individuals had lower levels of CD56^dim NK cells coexpressing the differentiation markers NKG2A and CD57 than controls. In addition, their NKG2A⁺CD57⁺ CD56^dim NK cells displayed elevated activation levels as assessed by HLA-DR expression. Cytokine-induced IFNγ production correlated directly with coexpression of CD57 and NKG2A on CD56^dim NK cells.

Conclusion:

HIV-1 subtype D infection is associated with impaired NK cell responsiveness to cytokines, decline of the NKG2A⁺CD57⁺ CD56^dim NK cell subset, as well as elevated activation in this subset. These alterations within the NK cell compartment may contribute to immunopathogenesis of HIV-1 subtype D infection in Ugandans.

Concentrated HIV subepidemics in generalized epidemic settings

PURPOSE OF REVIEW

A relatively neglected topic to date has been the occurrence of concentrated epidemics within generalized epidemic settings and the potential role of targeted interventions in such settings. We review recent studies in high-risk groups as well as findings relating to geographical heterogeneity and the potential for targeting 'high-transmission zones' in the 10 countries with highest HIV prevalence.

RECENT FINDINGS

Our review of recent studies confirmed earlier findings that, even in the context of generalized epidemics, MSM have a substantially higher prevalence than the general population. Estimates of prevalence of HIV among people who inject drugs (PWID) in sub-Saharan African countries are rarely available and, when they are, often outdated. We identified recent studies of sex workers in Kenya and Uganda. In all three cases - MSM, PWID, and sex workers - HIV prevalence estimates are mostly based on convenience. Moreover, good estimates of the total size of these populations are not available. Our review of recent studies of high-risk populations defined on the basis of geography showed high levels of both new and existing infections in Kenya (slums), South Africa (peri-urban communities), and Uganda (fishing villages).

SUMMARY

Recent empirical findings combined with evidence from phylogenetic studies and supported by mathematical models provide a clear rationale for testing the feasibility, acceptability, and effectiveness of targeted HIV prevention approaches in hyperendemic populations to supplement measures aimed at the general population.

Effect of HIV-1 subtypes on disease progression in rural Uganda: a prospective clinical cohort study

Objective

We examined the association of HIV-1 subtypes with disease progression based on three viral gene regions.

Design

A prospective HIV-1 clinical cohort study in rural Uganda.

Methods

Partial gag, env and pol genes were sequenced. Cox proportional hazard regression modelling was used to estimate adjusted hazard ratios (aHRs) of progression to: CD4≤250, AIDS onset and death, adjusted for sex, age and CD4 count at enrolment.

Results

Between 1990 and 2010, 292 incident cases were subtyped: 25% had subtype A, 45% had D, 26% had A/D recombinants, 1% had C and 4% were other recombinant forms. Of the 278 incident cases included in the disease progression analysis, 62% progressed to CD4≤250, 32% to AIDS, and 34% died with a higher proportion being among subtype D cases. The proportions of individuals progressing to the three endpoints were significantly higher among individuals infected with subtype D. Throughout the study period, individuals infected with subtype D progressed faster to CD4≤250, adjusted HR (aHR), (95% CI) = 1.72 (1.16–2.54), but this was mainly due to events in the period before antiretroviral therapy (ART) introduction, when individuals infected with subtype D significantly progressed faster to CD4≤250 than subtype A cases; aHR (95% CI) = 1.78 (1.01–3.14).

Conclusions

In this population, HIV-1 subtype D was the most prevalent and was associated with faster HIV-1 disease progression than subtype A. Further studies are needed to examine the effect of HIV-1 subtypes on disease progression in the ART period and their effect on the virological and immunological ART outcomes.