Search

Background: International travel plays a role in the spread of HIV-1 across Europe. It is, however, not known whether international travel is more important for spread of the epidemic as compared to endogenous infections within single countries. In this study, phylogenetic associations among HIV of newly diagnosed patients were determined across Europe.Results: Data came from the SPREAD programme which collects samples of newly diagnosed patients that are representative for national HIV epidemics. 4260 pol sequences from 25 European countries and Israel collected in 2002-2007 were included.We identified 457 clusters including 1330 persons (31.2% of all patients). The cluster size ranged between 2 and 28. A number of 987 patients (74.2%) were part of a cluster that consisted only of patients originating from the same country. In addition, 135 patients (10.2%) were in a cluster including only individuals from neighboring countries. Finally, 208 patients (15.6%) clustered with individuals from countries without a common border. Clustering with patients from the same country was less prevalent in patients being infected with B subtype (P-value <0.0001), in men who have sex with men (P-value <0.0001), and in recently infected patients (P-value =0.045).Conclusions: Our findings indicate that the transmission of HIV-1 in Europe is predominantly occurring between patients from the same country. This could have implications for HIV-1 transmission prevention programmes. Because infections through travelling between countries is not frequently observed it is important to have good surveillance of the national HIV-1 epidemics.

© The Author 2015. Background. Numerous studies have shown that baseline drug resistance patterns may influence the outcome of antiretroviral therapy. Therefore, guidelines recommend drug resistance testing to guide the choice of initial regimen. In addition to optimizing individual patient management, these baseline resistance data enable transmitted drug resistance (TDR) to be surveyed for public health purposes. The SPREAD program systematically collects data to gain insight into TDR occurring in Europe since 2001. Methods. Demographic, clinical, and virological data from 4140 antiretroviral-naive human immunodeficiency virus (HIV)-infected individuals from 26 countries who were newly diagnosed between 2008 and 2010 were analyzed. Evidence of TDR was defined using the WHO list for surveillance of drug resistance mutations. Prevalence of TDR was assessed over time by comparing the results to SPREAD data from 2002 to 2007. Baseline susceptibility to antiretroviral drugs was predicted using the Stanford HIVdb program version 7.0. Results. The overall prevalence of TDR did not change significantly over time and was 8.3% (95% confidence interval, 7.2%-9.5%) in 2008-2010. The most frequent indicators of TDR were nucleoside reverse transcriptase inhibitor (NRTI) mutations (4.5%), followed by nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations (2.9%) and protease inhibitor mutations (2.0%). Baseline mutations were most predictive of reduced susceptibility to initial NNRTI-based regimens: 4.5% and 6.5% of patient isolates were predicted to have resistance to regimens containing efavirenz or rilpivirine, respectively, independent of current NRTI backbones. Conclusions. Although TDR was highest for NRTIs, the impact of baseline drug resistance patterns on susceptibi

Background: In Europe, a continuous programme (SPREAD) has been in place for ten years to study transmission of drug resistant HIV. We analysed time trends of transmitted drug resistance mutations (TDRM) in relation to the risk behaviour reported. Methods: HIV-1 patients newly diagnosed in 27 countries from 2002 through 2007 were included. Inclusion was representative for risk group and geographical distribution in the participating countries in Europe. Trends over time were calculated by logistic regression. Results: From the 4317 patients included, the majority was men-having-sex-with-men -MSM (2084, 48%), followed by heterosexuals (1501, 35%) and injection drug users (IDU) (355, 8%). MSM were more often from Western Europe origin, infected with subtype B virus, and recently infected (<1 year) (p<0.001). The prevalence of TDRM was highest in MSM (prevalence of 11.1%), followed by heterosexuals (6.6%) and IDU (5.1%, p<0.001). TDRM was predominantly ascribed to nucleoside reverse transcriptase inhibitors (NRTI) with a prevalence of 6.6% in MSM, 3.3% in heterosexuals and 2.0% in IDU (p = 0.001). A significant increase in resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) and a decrease in resistance to protease inhibitors was observed in MSM (p = 0.008 and p = 0.006, respectively), but not in heterosexual patients (p = 0.68 and p = 0.14, respectively). Conclusions: MSM showed to have significantly higher TDRM prevalence compared to heterosexuals and IDU. The increasing NNRTI resistance in MSM is likely to negatively influence the therapy response of first-line therapy, as most include NNRTI drugs.

We aimed to study epidemic trends and predictors for transmitted drug resistance (TDR) in our region, its clinical impact and its association with transmission clusters. We included 778 patients from the AIDS Reference Center in Leuven (Belgium) diagnosed from 1998 to 2012. Resistance testing was performed using population-based sequencing and TDR was estimated using the WHO-2009 surveillance list. Phylogenetic analysis was performed using maximum likelihood and Bayesian techniques. The cohort was predominantly Belgian (58.4%), men who have sex with men (MSM) (42.8%), and chronically infected (86.5%). The overall TDR prevalence was 9.6% (95% confidence interval (Cl): 7.7-11.9), 6.5% (CI: 5.0-8.5) for nucleoside reverse transcriptase inhibitors (NRTI), 2.2% (CI: 1.4-3.5) for non-NRTI (NNRTI), and 2.2% (CI: 1.4-3.5) for protease inhibitors. A significant parabolic trend of NNRTI-TDR was found (p = 0.019). Factors significantly associated with TDR in univariate analysis were male gender, Belgian origin, MSM, recent infection, transmission clusters and subtype B, while multivariate and Bayesian network analysis singled out subtype B as the most predictive factor of TDR. Subtype B was related with transmission clusters with TDR that included 42.6% of the TDR patients. Thanks to resistance testing, 83% of the patients with TDR who started therapy had undetectable viral load whereas half of the patients would likely have received a suboptimal therapy without this test. In conclusion, TDR remained stable and a NNRTI up-and-down trend was observed. While the presence of clusters with TDR is worrying, we could not identify an independent, non-sequence based predictor for TDR or transmission clusters with TDR that could help with guidelines or public health measures.

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naive patients into sequences from patients failing treatment. In this study, we compared four FLs trained with different sequence populations. Epistatic interactions were learned from three different cross-sectional BNs, trained with sequence from patients experienced with indinavir (BNT), all protease inhibitors (PIs) (BNP) or all PI except indinavir (BND). Scaling the fitness landscape was done using cross-sectional data from drug naive and indinavir experienced patients (Fcross using BNT) and using longitudinal sequences from patients failing indinavir In pairwise FL comparisons we found significant correlation between fitness values for individual sequences, and this correlation improved after correcting for the subtype. Furthermore, FLs could predict the failing sequence under indinavir-containing combinations. At 12 and 48 weeks, all parameters from all FLs and indinavir GSS (both for Rega and HIVdb) were predictive of therapy outcome, except MR for FlongT and FlongP. The fitness landscapes have similar predictive power for treatment respon

Background: Understanding HIV-1 subtype distribution and epidemiology can assist preventive measures and clinical decisions. Sequence variation may affect antiviral drug resistance development, disease progression, evolutionary rates and transmission routes. Results: We investigated the subtype distribution of HIV-1 in Europe and Israel in a representative sample of patients diagnosed between 2002 and 2005 and related it to the demographic data available. 2793 PRO-RT sequences were subtyped either with the REGA Subtyping tool or by a manual procedure that included phylogenetic tree and recombination analysis. The most prevalent subtypes/CRFs in our dataset were subtype B (66.1%), followed by sub-subtype A1 (6.9%), subtype C (6.8%) and CRF02_AG (4.7% Conclusions: The association of subtype with demographic parameters suggests highly compartmentalized epidemics, determined by social and behavioural characteristics of the patients.

Background: International travel plays a role in the spread of HIV-1 across Europe. It is, however, not known whether international travel is more important for spread of the epidemic as compared to endogenous infections within single countries. In this study, phylogenetic associations among HIV of newly diagnosed patients were determined across Europe. Results: Data came from the SPREAD programme which collects samples of newly diagnosed patients that are representative for national HIV epidemics. 4260 pol sequences from 25 European countries and Israel collected in 2002-2007 were included. We identified 457 clusters including 1330 persons (31.2% of all patients). The cluster size ranged between 2 and 28. A number of 987 patients (74.2%) were part of a cluster that consisted only of patients originating from the same country. In addition, 135 Conclusions: Our findings indicate that the transmission of HIV-1 in Europe is predominantly occurring between patients from the same country. This could have implications for HIV-1 transmission prevention programmes. Because infections through travelling between countries is not frequently observed it is important to have good surveillance of the national HIV-1 epidemics.

Background: Superinfection with drug resistant HIV strains could potentially contribute to compromised therapy in patients initially infected with drug-sensitive virus and receiving antiretroviral therapy. To investigate the importance of this potential route to drug resistance, we developed a bioinformatics pipeline to detect superinfection from routinely collected genotyping data, and assessed whether superinfection contributed to increased drug resistance in a large European cohort of viremic, drug treated patients. Methods: We used sequence data from routine genotypic tests spanning the protease and partial reverse transcriptase regions in the Virolab and EuResist databases that collated data from five European countries. Superinfection was indicated when sequences of a patient failed to cluster together in phylogenetic trees constructed with selected sets of control sequences. A subset of the indicated cases was validated by re-sequencing pol and env regions from the original samples. Results: 4425 patients had at least two sequences in the database, with a total of 13816 distinct sequence entries (of which 86% belonged to subtype B). We identified 107 patients with phylogenetic evidence for superinfection. In 14 of these cases, we analyzed newly amplified sequences from the original samples for validation purposes: only 2 cases were verified as superinfections in the repeated analyses, the other 12 cases turned out to involve sample or sequence misidentification. Resistance Conclusions: Routine genotyping data are informative for the detection of HIV superinfection; however, most cases of non-monophyletic clustering in patient phylogenies arise from sample or sequence mix-up rather than from superinfection, which emphasizes the importance of validation. Non-transient superinfection was rare in our mainly treatment experienced cohort, and we found a single case of possible transmitted drug resistance by this route. We therefore conclude that in our large cohort

Background: The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission. While compensatory mutations increase fitness during treatment, their presence may also modulate viral fitness and virulence in absence of therapy and major resistance mutations. We previously designed a modeling technique that quantifies genotypic footprints of in vivo treatment selective pressure, including both drug resistance mutations and polymorphic compensatory mutations, through the quantitative description of a fitness landscape from virus genetic sequences. Results: Genotypic correlates of viral load and CD4 cell count were evaluated in subtype B sequences from recently diagnosed treatment-naive patients enrolled in the SPREAD programme. The association of surveillance drug resistance mutations, reported compensatory mutations and fitness estimated from drug selective pressure fitness landscapes with baseline viral load and CD4 cell count was evaluated using regression techniques. Protease genotypic variability estimated to increase fitness during Conclusions: These results suggest that polymorphic compensatory mutations in protease, reported to be selected during treatment, may improve the replicative capacity of HIV-1 even in absence of drug selective pressure or major resistance mutations. The presence of this polymorphic variation may either reflect a history of drug selective pressure, i.e. transmission from a treated patient, or merely be a result of diversity in wild-type virus. Our findings suggest that transmitted drug resistance

Background: HIV-1 genotypic drug resistance is an important threat to the success of antiretroviral therapy and transmitted resistance has reached 9% prevalence in Europe. Studies have demonstrated that HIV-1 DNA load in peripheral blood mononuclear cells (PBMC) have a predictive value for disease progression, independently of CD4 counts and plasma viral load. Methodology/Principal Findings: Molecular-beacon-based real-time PCR was used to measure HIV-1 second template switch (STS) DNA in PBMC in newly-diagnosed HIV-1 patients across Europe. These patients were representative for the HIV-1 epidemic in the participating countries and were carrying either drug-resistant or sensitive viral strains. The assay design was improved from a previous version to specifically detect M-group HIV-1 and human CCR5 alleles. The findings resulted in a median of 3.32 log(10) HIV-1 copies/10(6) PBMC and demonstrated for the first time no correlation between cellular HIV-1 DNA load and transmitted drug-resistance. A weak association between cellular HIV-1 DNA levels with plasma viral RNA load and CD4(+) T-cell counts was also reconfirmed. Co-receptor tropism for 91% of samples, whether or not they conferred resistance, was CCR5. A comparison of pol sequences derived from RNA and DNA, resulted in a high similarity between the two. Conclusions/Significance: An improved molecular-beacon-based real-time PCR assay is reported for the measurement of HIV-1 DNA in PBMC and has investigated the association between cellular HIV-1 DNA levels and transmitted resistance to antiretroviral therapy in newly-diagnosed patients from across Europe. The findings show no correlation between these two parameters, suggesting that transmitted resistance does not impact disease progression in HIV-1 infected individuals. The CCR5 co-receptor tropism predominance implies that both resistant and non-resistant strains behave similarly in early infection. Furthermore, a correlation found between RNA-and DNA-derived

Background: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. Methodology/Principal Findings: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8-16) weeks (2152 TCEs), 24 (16-32) weeks (2570 TCEs), and 48 (44-52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92 +/- 1.17, compared to Rega and ANRS, with 2.22 +/- 1.09 and 2.23 +/- 1.05, respectively. However, similar odds ratio's were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5-1.7] for HIVdb, 1.7 [1.5-1.8] for ANRS, and 1.7 [1.9-1.6] for Rega. Odds ratio's increased over time, but remained comparable (odds ratio's ranging between 1.9-2.1 at 24 weeks and 1.9-2.2 at 48 weeks). The Area under the curve of the ROC did not differ between the systems at all time points; p = 0.60 at week 12, p = 0.71 at week 24, and p = 0.97 at week 48. Conclusions/Significance: Three commonly used HIV drug resistance interpretation systems ANRS, Rega and HIVdb predict virological response at 12, 24

Programs that monitor local, national, and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programs. To accurately compare transmitted drug resistance rates across geographic regions and times, the World Health Organization has recommended the adoption of a consensus genotypic definition of transmitted HIV-1 drug resistance. In January 2007, we outlined criteria for developing a list of mutations for drug-resistance surveillance and compiled a list of 80 RT and protease mutations meeting these criteria (surveillance drug resistance mutations; SDRMs). Since January 2007, several new drugs have been approved and several new drug-resistance mutations have been identified. In this paper, we follow the same procedures described previously to develop an updated list of SDRMs that are likely to be useful for ongoing and future studies of transmitted drug resistance. The updated SDRM list has 93 mutations including 34 NRTI-resistance mutations at 15 RT positions, 19 NNRTI-resistance mutations at 10 RT positions, and 40 PI-resistance mutations at 18 protease positions.

Background: The prevalence and the origin of HIV-1 subtype B, the most prevalent circulating clade among the long-term residents in Europe, have been studied extensively. However the spatial diffusion of the epidemic from the perspective of the virus has not previously been traced. Results: In the current study we inferred the migration history of HIV-1 subtype B by way of a phylogeography of viral sequences sampled from 16 European countries and Israel. Migration events were inferred from viral phylogenies by character reconstruction using parsimony. With regard to the spatial dispersal of the HIV subtype B sequences across viral phylogenies, in most of the countries in Europe the epidemic was introduced by multiple sources and subsequently spread within local networks. Poland provides an exception where most of the infections were the result of a single point introduction. According to the significant migratory pathways, we show that there are considerable differences across Europe. Specifically, Greece, Portugal, Serbia and Spain, provide sources shedding HIV-1; Austria, Belgium and Luxembourg, on the other hand, are migratory targets, while for Denmark, Germany, Italy, Israel, Norway, the Netherlands, Sweden, Switzerland and the UK we inferred significant bidirectional migration. For Poland no significant migratory pathways were inferred. Conclusion: Subtype B phylogeographies provide a new insight about the geographical distribution of viral lineages, as well as the significant pathways of virus dispersal across Europe, suggesting that intervention strategies should also address tourists, travellers and migrants.

In most European countries, HIV drug resistance testing has become a routine clinical tool. However, its practical implementation in a clinical context is demanding. The European HIV Drug Resistance Panel was established to make recommendations to clinicians and virologists on this topic and to propose quality control measures. The panel recommends resistance testing for the following indications: i) drug-naive patients with acute or recent infection; ii) therapy failure, including suboptimal treatment response, when treatment change is considered; iii) pregnant HIV-1-infected women and paediatric patients with detectable viral load when treatment initiation or change is considered; and iv) genotype source patient when post-exposure prophylaxis is considered. In addition, for drug-naive patients with chronic infection in whom treatment is to be started, the panel suggests that resistance testing should be strongly considered and recommends testing the earliest sample for drug resistance if suspicion of resistance is high or prevalence of resistance in this population exceeds 10%. The panel does not favour genotyping over phenotype, however it is anticipated that genotyping will be used more often because of its greater accessibility, lower cost and faster turnaround time. For the interpretation of resistance data, clinically validated systems should be used to the greatest extent possible. It is mandatory that laboratories performing HIV resistance tests take regular part in quality assurance programs. Similarly, it is necessary that HIV clinicians and virologists take part in continuous education and meet regularly to discuss problematic clinical cases. Indeed, resistance test results should be used in the context of all other clinically relevant information for predicting therapy response. The panel also encourages the timely collection of epidemiological information to estimate the impact of transmission of resistant HIV and the prevalence of HIV-1 non-B subtypes

The evolutionary rate of the human T-cell lymphotropic virus type-1 (HTLV-1) is considered to be very low, in strong contrast to the related human retrovirus HIV. However, current estimates of the HTLV-1 rate rely on the anthropological calibration of phylogenies using assumed dates of human migration events. To obtain an independent rate estimate, we analyzed two variable regions of the HTLV-1 genome (LTR and env) from eight infected families. Remarkable genetic stability was observed, as only two mutations in LTR (756 bp) and three mutations in env (522 bp) occurred within the 16 vertical transmission chains, including one ambiguous position in each region. The evolutionary rate in HTLV-1 was then calculated using a maximum-likelihood approach that used the highest and lowest possible times of HTLV-1 shared ancestry, given the known transmission histories. The rates for the LTR and env regions were 9.58 x 10(-8)-1.25 x 10(-5) and 7.84 x 10(-7)-2.33 x 10(-5) nucleotide substitutions per site per year, respectively. A more precise estimate was obtained for the combined LTR-env data set, which was 7.06 x 10(-7)-1.38 x 10(-5) substitutions per site per year. We also note an interesting correlation between the occurrence of mutations in HTLV-1 and the age of the individual infected.

BACKGROUND: Resistance testing is increasingly accepted as a tool in guiding the selection of human immunodeficiency virus type 1 (HIV-1) antiretroviral therapy in HIV-1 infected individuals who fail their current regimen. OBJECTIVES: To descriptively compare the correlation between virologic treatment response and results using three genotypic HIV-1 drug resistance interpretation systems: the VERSANT HIV-1 Resistance Assay (LiPA) system and two sequence-based interpretation systems. STUDY DESIGN: Specimens from 213 HIV-1-infected subjects, either starting (n=104) or switching to (n=109) a regimen of three or four antiretroviral drugs, were collected retrospectively at baseline and after 3 months of uninterrupted therapy. The correlation between viral load change and the number of predicted active drugs in the treatment regimen was assessed. An interpretation algorithm was recently developed to process VERSANT HIV-1 Resistance Assay (LiPA) data. The number of active drugs predicted using this algorithm was rank correlated with the viral load change over a 3-month treatment period. For comparison, a similar calculation was made using two sequence-based algorithms (REGA version 5.5 and VGI GuideLines Rules 4.0), both applied on the same sequences. RESULTS: Statistically significant (p<0.05) correlation coefficients for each of the three HIV-1 drug resistance interpretation systems were observed in the treatment-experienced subjects on a 3-drug regimen (-0.39, -0.38, and -0.42, respectively) as well as on a 4-drug regimen (-0.33, -0.31, and -0.37, respectively). However, no significant correlation was observed in treatment-naive subjects, probably due to the very low frequency of drug resistance in these subjects. CONCLUSION: All three genotypic drug resistance interpretation systems (LiPA version 1, REGA version 5.5, and VGI GuideLines Rules 4.0) were statistically significantly correlated with virologic therapy response as measured by viral load testing.

Objective: We evaluated the prevalence of HIV-1 non-clade B over time in a formerly clade B-restricted area. Protease and reverse transcriptase regions of the pot gene were used for phylogenetic and recombination analysis and for clade assignment to HIV-1 A-D, F-H, J, and K strains of the M group. Methods: The pot gene of 349 HIV-1 patients belonging to the Italian Cohort Naive for Antiretrovirals (ICONA) were genotypically analyzed to study the prevalence of antiretroviral-associated resistance mutations. All HIV-1 pot sequences and 32 HIV reference strains were analyzed, including the reference strains for the major HIV-1 subtypes. The non-clade B sequences according to the HIV-1 Subtyping Tool program were further studied by a bootscan analysis (SimPlot) to investigate the likelihood of recombination between subtypes. Results: Phylogenetic analysis detected 19 of 349 (5.4%) non-clade B subtypes. The proportions of patients carrying non-clade B virus before and after 1997 were 1.9% and 8.4%, respectively (p = .008). Among whites, heterosexual infection and female gender were significantly associated with the presence of non-clade B subtypes (p = .001 and .005, respectively). Non-clade B HIV-1 was harbored by 14.5% of the heterosexuals who were found to be HIV-1 positive after 1997, 60% of whom were women. Bootscan analysis identified four strains as F, two as A, one as C, one as G, and 11 (57.9 %) as non-clade B recombinant subtypes. Conclusion: Detection of HIV-1 subtypes and intersubtype recombinants in a previously clade B-homogeneous area indicates that the HIV-1 epidemic is evolving in Italy and that heterosexuals and women are at increased risk of infection with non-clade B HIV-1 subtypes. Sequences inferred from the pot gene yield to establish the subtype of circulating HIV-1 strains. As a consequence, genotyping of pot gene for testing resistance to antiretrovirals warrants concomitant surveillance of non-clade B subtypes.

Eight Belgian AIDS Reference Laboratories established a multicentre quality control to evaluate the performance of their diagnostic human immunodeficiency virus type 1 (HIV-1) DNA polymerase chain reaction (PCR). A set of Belgian and African HIV-1 seropositive and seronegative patient samples, collected in Belgium, and the British Medical Research Council (MRC) HIV-1 PCR reference reagent kit, containing plasmid HIV-1 DNA at several dilutions in human carrier DNA with appropriate negative controls, were tested by the laboratories. No false positive results were reported. Ah laboratories were able to detect one to two copies of HIV-1 DNA. Among the 17 Belgian and African HIV-1 seropositives, some laboratories reported up to four indeterminate results, mainly due to failure of the SK38-39, SK68-69 (Ou et al. (1988) Science 239, 295-297) and/or gag881-882 (Simmonds et al. (1990) J. Virol. 64, 864-872) primers and a poorly performing algorithm. Only the H1POL4235-4538 nested pol primer set, developed by one of the laboratories, correctly identified all the tested HIV-1 positive and negative samples. Consequently, the laboratories decided to evaluate these pol primers as a reference primer set and to standardise the testing algorithm. All laboratories achieved a sensitivity and specificity of 100% on testing 10 additional Belgian and African patient samples, when adapting a standardised algorithm based on three HIV-1 primer sets, one of which is the H1POL4235-4538 primer set.