Role of Gag mutations in PI resistance in the Swiss HIV cohort study: bystanders or contributors?

Background

HIV Gag mutations have been reported to confer PI drug resistance. However, clinical implications are still controversial and most current genotyping algorithms consider solely the protease gene for assessing PI resistance.

Objectives

Our goal was to describe for HIV infections in Switzerland the potential role of the C-terminus of Gag (NC-p6) in PI resistance. We aimed to characterize resistance-relevant mutational patterns in Gag and protease and their possible interactions.

Methods

Resistance information on plasma samples from 2004-12 was collected for patients treated by two diagnostic centres of the Swiss HIV Cohort Study. Sequence information on protease and the C-terminal Gag region was paired with the corresponding patient treatment history. The prevalence of Gag and protease mutations was analysed for PI treatment-experienced patients versus PI treatment-naive patients. In addition, we modelled multiple paths of an assumed ordered accumulation of genetic changes using random tree mixture models.

Results

More than half of all PI treatment-experienced patients in our sample set carried HIV variants with at least one of the known Gag mutations, and 17.9% (66/369) carried at least one Gag mutation for which a phenotypic proof of PI resistance by in vitro mutagenesis has been reported. We were able to identify several novel Gag mutations that are associated with PI exposure and therapy failure.

Conclusions

Our analysis confirmed the association of Gag mutations, well known and new, with PI exposure. This could have clinical implications, since the level of potential PI drug resistance might be underestimated.

Global prevalence and genotype distribution of hepatitis C virus infection in 2015: a modelling study

BACKGROUND

The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of-and expansion on-the 2014 analysis, which reported 80 million (95% CI 64-103) viraemic infections in 2013.

METHODS

We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data.

FINDINGS

Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8-1·1) in 2015, corresponding to 71·1 million (62·5-79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively).

INTERPRETATION

The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections.

FUNDING

John C Martin Foundation.

The global spread of HIV-1 subtype B epidemic

Human immunodeficiency virus type 1 (HIV-1) was discovered in the early 1980s when the virus had already established a pandemic. For at least three decades the epidemic in the Western World has been dominated by subtype B infections, as part of a sub-epidemic that traveled from Africa through Haiti to United States. However, the pattern of the subsequent spread still remains poorly understood. Here we analyze a large dataset of globally representative HIV-1 subtype B strains to map their spread around the world over the last 50years and describe significant spread patterns. We show that subtype B travelled from North America to Western Europe in different occasions, while Central/Eastern Europe remained isolated for the most part of the early epidemic. Looking with more detail in European countries we see that the United Kingdom, France and Switzerland exchanged viral isolates with non-European countries than with European ones. The observed pattern is likely to mirror geopolitical landmarks in the post-World War II era, namely the rise and the fall of the Iron Curtain and the European colonialism. In conclusion, HIV-1 spread through specific migration routes which are consistent with geopolitical factors that affected human activities during the last 50years, such as migration, tourism and trade. Our findings support the argument that epidemic control policies should be global and incorporate political and socioeconomic factors.

Transmission of HIV Drug Resistance and the Predicted Effect on Current First-line Regimens in Europe

Transmitted human immunodeficiency virus drug resistance in Europe is stable at around 8%. The impact of baseline mutation patterns on susceptibility to antiretroviral drugs should be addressed using clinical guidelines. The impact on baseline susceptibility is largest for nonnucleoside reverse transcriptase inhibitors.

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 susceptibility was largest for NNRTIs. The prevalence of TDR assessed by epidemiological surveys does not clearly indicate to what degree susceptibility to different drug classes is affected.

Primary resistance to integrase strand-transfer inhibitors in Europe

OBJECTIVES

The objective of this study was to define the natural genotypic variation of the HIV-1 integrase gene across Europe for epidemiological surveillance of integrase strand-transfer inhibitor (InSTI) resistance.

METHODS

This was a multicentre, cross-sectional study within the European SPREAD HIV resistance surveillance programme. A representative set of 300 samples was selected from 1950 naive HIV-positive subjects newly diagnosed in 2006-07. The prevalence of InSTI resistance was evaluated using quality-controlled baseline population sequencing of integrase. Signature raltegravir, elvitegravir and dolutegravir resistance mutations were defined according to the IAS-USA 2014 list. In addition, all integrase substitutions relative to HXB2 were identified, including those with a Stanford HIVdb score ≥ 10 to at least one InSTI. To rule out circulation of minority InSTI-resistant HIV, 65 samples were selected for 454 integrase sequencing.

RESULTS

For the population sequencing analysis, 278 samples were retrieved and successfully analysed. No signature resistance mutations to any of the InSTIs were detected. Eleven (4%) subjects had mutations at resistance-associated positions with an HIVdb score ≥ 10. Of the 56 samples successfully analysed with 454 sequencing, no InSTI signature mutations were detected, whereas integrase substitutions with an HIVdb score ≥ 10 were found in 8 (14.3%) individuals.

CONCLUSIONS

No signature InSTI-resistant variants were circulating in Europe before the introduction of InSTIs. However, polymorphisms contributing to InSTI resistance were not rare. As InSTI use becomes more widespread, continuous surveillance of primary InSTI resistance is warranted. These data will be key to modelling the kinetics of InSTI resistance transmission in Europe in the coming years.

Near Full-Length Characterization and Population Dynamics of the Human Immunodeficiency Virus Type I Circulating Recombinant Form 42 (CRF42_BF) in Luxembourg

A new recombinant form representing a mosaic of HIV-1 subtype B and F1 and designated as CRF42_BF was identified in Luxembourg. We confirmed the inedited nature of CRF42_BF by near full-length genome characterization and retrieved a possible ancestor originating from Brazil. The demographic history of CRF42_BF in Luxembourg using Bayesian coalescent-based methods was investigated. The exponential phase of the logistic growth happened in a very short time period of approximately 5 months associated with a high mean rate of population growth of 15.02 new infections per year. However, CRF42_BF was not characterized by either a higher ex vivo replication capacity in peripheral blood mononuclear cells (PBMCs) or a higher ex vivo transmission efficiency from monocyte-derived dendritic cells to PBMCs as compared to B and F1 viruses. These data do not support a high pathogenic potential of CFR42_BF but rather an initial bursting spread of the recombinant probably due to a more favorable transmission route.

Strategies to manage hepatitis C virus (HCV) infection disease burden - volume 2

The hepatitis C virus (HCV) epidemic was forecasted through 2030 for 15 countries, and the relative impact of two scenarios was considered: (i) increased treatment efficacy while holding the treated population constant and (ii) increased treatment efficacy and increased annual treated population. Increasing levels of diagnosis and treatment, in combination with improved treatment efficacy, were critical for achieving substantial reductions in disease burden. In most countries, the annual treated population had to increase several fold to achieve the largest reductions in HCV-related morbidity and mortality. This suggests that increased capacity for screening and treatment will be critical in many countries. Birth cohort screening is a helpful tool for maximizing resources. In most of the studied countries, the majority of patients were born between 1945 and 1985.

The present and future disease burden of hepatitis C virus (HCV) infections with today's treatment paradigm - volume 2

Morbidity and mortality attributable to chronic hepatitis C virus (HCV) infection are increasing in many countries as the infected population ages. Models were developed for 15 countries to quantify and characterize the viremic population, as well as estimate the number of new infections and HCV related deaths from 2013 to 2030. Expert consensus was used to determine current treatment levels and outcomes in each country. In most countries, viremic prevalence has already peaked. In every country studied, prevalence begins to decline before 2030, when current treatment levels were held constant. In contrast, cases of advanced liver disease and liver related deaths will continue to increase through 2030 in most countries. The current treatment paradigm is inadequate if large reductions in HCV related morbidity and mortality are to be achieved.

Historical epidemiology of hepatitis C virus (HCV) in select countries - volume 2

Chronic hepatitis C virus (HCV) infection is a leading cause of liver related morbidity and mortality. In many countries, there is a lack of comprehensive epidemiological data that are crucial in implementing disease control measures as new treatment options become available. Published literature, unpublished data and expert consensus were used to determine key parameters, including prevalence, viremia, genotype and the number of patients diagnosed and treated. In this study of 15 countries, viremic prevalence ranged from 0.13% in the Netherlands to 2.91% in Russia. The largest viremic populations were in India (8 666 000 cases) and Russia (4 162 000 cases). In most countries, males had a higher rate of infections, likely due to higher rates of injection drug use (IDU). Estimates characterizing the infected population are critical to focus screening and treatment efforts as new therapeutic options become available.

Global Dispersal Pattern of HIV Type 1 Subtype CRF01_AE: A Genetic Trace of Human Mobility Related to Heterosexual Sexual Activities Centralized in Southeast Asia

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) subtype CRF01_AE originated in Africa and then passed to Thailand, where it established a major epidemic. Despite the global presence of CRF01_AE, little is known about its subsequent dispersal pattern.

METHODS

We assembled a global data set of 2736 CRF01_AE sequences by pooling sequences from public databases and patient-cohort studies. We estimated viral dispersal patterns, using statistical phylogeographic analysis run over bootstrap trees estimated by the maximum likelihood method.

RESULTS

We show that Thailand has been the source of viral dispersal to most areas worldwide, including 17 of 20 sampled countries in Europe. Japan, Singapore, Vietnam, and other Asian countries have played a secondary role in the viral dissemination. In contrast, China and Taiwan have mainly imported strains from neighboring Asian countries, North America, and Africa without any significant viral exportation.

DISCUSSION

The central role of Thailand in the global spread of CRF01_AE can be probably explained by the popularity of Thailand as a vacation destination characterized by sex tourism and by Thai emigration to the Western world. Our study highlights the unique case of CRF01_AE, the only globally distributed non-B clade whose global dispersal did not originate in Africa.

COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification

Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1,090,698 and 10,625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.

Patterns of transmitted HIV drug resistance in Europe vary by risk group

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.

HIV-1 tropism determination using a phenotypic Env recombinant viral assay highlights overestimation of CXCR4-usage by genotypic prediction algorithms for CRF01_AE and CRF02_AG [corrected]

BACKGROUND

Human Immunodeficiency virus type-1 (HIV) entry into target cells involves binding of the viral envelope (Env) to CD4 and a coreceptor, mainly CCR5 or CXCR4. The only currently licensed HIV entry inhibitor, maraviroc, targets CCR5, and the presence of CXCX4-using strains must be excluded prior to treatment. Co-receptor usage can be assessed by phenotypic assays or through genotypic prediction. Here we compared the performance of a phenotypic Env-Recombinant Viral Assay (RVA) to the two most widely used genotypic prediction algorithms, Geno2Pheno[coreceptor] and webPSSM.

METHODS

Co-receptor tropism of samples from 73 subtype B and 219 non-B infections was measured phenotypically using a luciferase-tagged, NL4-3-based, RVA targeting Env. In parallel, tropism was inferred genotypically from the corresponding V3-loop sequences using Geno2Pheno[coreceptor] (5-20% FPR) and webPSSM-R5X4. For discordant samples, phenotypic outcome was retested using co-receptor antagonists or the validated Trofile® Enhanced-Sensitivity-Tropism-Assay.

RESULTS

The lower detection limit of the RVA was 2.5% and 5% for X4 and R5 minority variants respectively. A phenotype/genotype result was obtained for 210 samples. Overall, concordance of phenotypic results with Geno2Pheno[coreceptor] was 85.2% and concordance with webPSSM was 79.5%. For subtype B, concordance with Geno2pheno[coreceptor] was 94.4% and concordance with webPSSM was 79.6%. High concordance of genotypic tools with phenotypic outcome was seen for subtype C (90% for both tools). Main discordances involved CRF01_AE and CRF02_AG for both algorithms (CRF01_AE: 35.9% discordances with Geno2Pheno[coreceptor] and 28.2% with webPSSM; CRF02_AG: 20.7% for both algorithms). Genotypic prediction overestimated CXCR4-usage for both CRFs. For webPSSM, 40% discordance was observed for subtype A.

CONCLUSIONS

Phenotypic assays remain the most accurate for most non-B subtypes and new subtype-specific rules should be developed for non-B subtypes, as research studies more and more draw conclusions from genotypically-inferred tropism, and to avoid unnecessarily precluding patients with limited treatment options from receiving maraviroc or other entry inhibitors.

Limited cross-border infections in patients newly diagnosed with HIV in Europe

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.

HIV-1 subtype distribution and its demographic determinants in newly diagnosed patients in Europe suggest highly compartmentalized epidemics

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%). Substantial differences in the proportion of new diagnoses with distinct subtypes were found between European countries: the lowest proportion of subtype B was found in Israel (27.9%) and Portugal (39.2%), while the highest was observed in Poland (96.2%) and Slovenia (93.6%). Other subtypes were significantly more diagnosed in immigrant populations. Subtype B was significantly more diagnosed in men than in women and in MSM > IDUs > heterosexuals. Furthermore, the subtype distribution according to continent of origin of the patients suggests they acquired their infection there or in Europe from compatriots.

Conclusions

The association of subtype with demographic parameters suggests highly compartmentalized epidemics, determined by social and behavioural characteristics of the patients.

Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients

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 treatment was associated with higher viral load and lower CD4 cell counts also in treatment-naive patients, which could primarily be attributed to well-known compensatory mutations at highly polymorphic positions. By contrast, treatment-related mutations in reverse transcriptase could not explain viral load or CD4 cell count variability.

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 has the potential to contribute to faster disease progression in the newly infected host and to shape the HIV-1 epidemic at a population level.

Treatment with interleukin-18 binding protein ameliorates Toxoplasma gondii-induced small intestinal pathology that is induced by bone marrow cell-derived interleukin-18

Peroral infection with Toxoplasma gondii results in a Th1-type immunopathology characterized by small intestinal necrosis and is dependent on IL-18. In the present study, we investigated whether treatment with IL-18 binding protein (IL-18bp) prevents ileal pathology. We observed increased expression of IL-18bp in intestinal biopsies of mice following infection. Whereas small intestines of control mice showed severe necrosis with complete destruction of the small intestinal architecture, mice treated with IL-18bp daily displayed only mild inflammatory changes including flattening of villi and edema in the space between the epithelium and lamina propria. Small intestinal parasite loads and concentrations of pro-inflammatory cytokines did not differ in control and IL-18bp-treated mice. Binding of IL-18 to immobilized IL-18bp revealed a remarkably slow dissociation rate, indicating high affinity. Using chimeric mice we observed that bone marrow-derived rather than stromal cells were the primary source of IL-18 that resulted in small intestinal pathology following peroral infection with T. gondii. In conclusion, the results presented here suggest that IL-18bp may be an effective and safe treatment for small intestinal inflammation. Antigen-presenting rather than epithelial cells appear to be the main source of IL-18 in T. gondii-induced small intestinal inflammation.

Automated sequence analysis and editing software for HIV drug resistance testing

BACKGROUND

Access to antiretroviral treatment in resource-limited-settings is inevitably paralleled by the emergence of HIV drug resistance. Monitoring treatment efficacy and HIV drugs resistance testing are therefore of increasing importance in resource-limited settings. Yet low-cost technologies and procedures suited to the particular context and constraints of such settings are still lacking. The ART-A (Affordable Resistance Testing for Africa) consortium brought together public and private partners to address this issue.

OBJECTIVES

To develop an automated sequence analysis and editing software to support high throughput automated sequencing.

STUDY DESIGN

The ART-A Software was designed to automatically process and edit ABI chromatograms or FASTA files from HIV-1 isolates.

RESULTS

The ART-A Software performs the basecalling, assigns quality values, aligns query sequences against a set reference, infers a consensus sequence, identifies the HIV type and subtype, translates the nucleotide sequence to amino acids and reports insertions/deletions, premature stop codons, ambiguities and mixed calls. The results can be automatically exported to Excel to identify mutations. Automated analysis was compared to manual analysis using a panel of 1624 PR-RT sequences generated in 3 different laboratories. Discrepancies between manual and automated sequence analysis were 0.69% at the nucleotide level and 0.57% at the amino acid level (668,047 AA analyzed), and discordances at major resistance mutations were recorded in 62 cases (4.83% of differences, 0.04% of all AA) for PR and 171 (6.18% of differences, 0.03% of all AA) cases for RT.

CONCLUSIONS

The ART-A Software is a time-sparing tool for pre-analyzing HIV and viral quasispecies sequences in high throughput laboratories and highlighting positions requiring attention.

Bioinformatics as a driver, not a passenger, of translational biomedical research: Perspectives from the 6th Benelux bioinformatics conference

The 6^th Benelux Bioinformatics Conference (BBC11) held in Luxembourg on 12 and 13 December 2011 attracted around 200 participants, including internationally-renowned guest speakers and more than 100 peer-reviewed submissions from 3 continents. Researchers from the public and private sectors convened at BBC11 to discuss advances and challenges in a wide spectrum of application areas. A key theme of the conference was the contribution of bioinformatics to enable and accelerate translational and clinical research. The BBC11 stressed the need for stronger collaborating efforts across disciplines and institutions. The demonstration of the clinical relevance of systems approaches and of next-generation sequencing-based measurement technologies are among the existing opportunities for increasing impact in translational research. Translational bioinformatics will benefit from research models that strike a balance between the importance of protecting intellectual property and the need to openly access scientific and technological advances. The full conference proceedings are freely available at http://www.bbc11.lu.

Efficacy of antiretroviral therapy switch in HIV-infected patients: a 10-year analysis of the EuResist Cohort

INTRODUCTION

Highly active antiretroviral therapy (HAART) has been shown to be effective in many recent trials. However, there is limited data on time trends of HAART efficacy after treatment change.

METHODS

Data from different European cohorts were compiled within the EuResist Project. The efficacy of HAART defined by suppression of viral replication at 24 weeks after therapy switch was analyzed considering previous treatment modifications from 1999 to 2008.

RESULTS

Altogether, 12,323 treatment change episodes in 7,342 patients were included in the analysis. In 1999, HAART after treatment switch was effective in 38.0% of the patients who had previously undergone 1-5 therapies. This figure rose to 85.0% in 2008. In patients with more than 5 previous therapies, efficacy rose from 23.9 to 76.2% in the same time period. In patients with detectable viral load at therapy switch, the efficacy rose from 23.3 to 66.7% with 1-5 previous treatments and from 14.4 to 55.6% with more than 5 previous treatments.

CONCLUSION

The results of this large cohort show that the outcome of HAART switch has improved considerably over the last years. This result was particularly observed in the context after viral rebound. Thus, changing HAART is no longer associated with a high risk of treatment failure.

Rescue of HIV-1 long-time archived X4 strains to escape maraviroc

Entry of Human Immunodeficiency Virus type 1 (HIV-1) into target cells is mediated by the CD4 receptor and a coreceptor, CCR5 or CXCR4. Maraviroc interferes with HIV entry by binding the CCR5 coreceptor. Virological failure to maraviroc-containing regimens can occur through the emergence of resistance, or through tropism evolution and broadened coreceptor usage. In the latter case, the physiological relevance of minority strains is a major concern. Here we report a retrospective analysis of coreceptor-usage and evolution based on 454-ultra-deep-sequencing of plasma and Peripheral Blood Mononuclear Cell (PBMC)-derived envelope V3-loops, accounting for coreceptor usage, from a patient who failed a maraviroc-containing regimen through the emergence of X4 strains. The X4 maraviroc-escape variant resulted from recombination between a long time archived proviral sequence from 2003 (5'-portion, including the V3-loop) and the dominant R5 strains circulating in plasma at the time of maraviroc-treatment initiation (3'-portion). Phylogenetic analyses and BEAST modeling highlighted that an early diverse viral quasispecies underwent a severe bottleneck following reinitiation of HAART and repeated IL-2 cycles between 1999 and 2001, leading to the transient outgrowth and archiving of one highly homogeneous X4 population from plasma, and to the expansion in plasma of one PBMC-derived R5 strain. Under maraviroc selective pressure, the early, no longer detectable X4 strains archived in PBMC were partially rescued to provide X4-determinants to the main circulating strain.

Antiretroviral therapy optimisation without genotype resistance testing: a perspective on treatment history based models

Background

Although genotypic resistance testing (GRT) is recommended to guide combination antiretroviral therapy (cART), funding and/or facilities to perform GRT may not be available in low to middle income countries. Since treatment history (TH) impacts response to subsequent therapy, we investigated a set of statistical learning models to optimise cART in the absence of GRT information.

Methods and Findings

The EuResist database was used to extract 8-week and 24-week treatment change episodes (TCE) with GRT and additional clinical, demographic and TH information. Random Forest (RF) classification was used to predict 8- and 24-week success, defined as undetectable HIV-1 RNA, comparing nested models including (i) GRT+TH and (ii) TH without GRT, using multiple cross-validation and area under the receiver operating characteristic curve (AUC). Virological success was achieved in 68.2% and 68.0% of TCE at 8- and 24-weeks (n = 2,831 and 2,579), respectively. RF (i) and (ii) showed comparable performances, with an average (st.dev.) AUC 0.77 (0.031) vs. 0.757 (0.035) at 8-weeks, 0.834 (0.027) vs. 0.821 (0.025) at 24-weeks. Sensitivity analyses, carried out on a data subset that included antiretroviral regimens commonly used in low to middle income countries, confirmed our findings. Training on subtype B and validation on non-B isolates resulted in a decline of performance for models (i) and (ii).

Conclusions

Treatment history-based RF prediction models are comparable to GRT-based for classification of virological outcome. These results may be relevant for therapy optimisation in areas where availability of GRT is limited. Further investigations are required in order to account for different demographics, subtypes and different therapy switching strategies.

Prediction of response to antiretroviral therapy by human experts and by the EuResist data-driven expert system (the EVE study)

OBJECTIVES

The EuResist expert system is a novel data-driven online system for computing the probability of 8-week success for any given pair of HIV-1 genotype and combination antiretroviral therapy regimen plus optional patient information. The objective of this study was to compare the EuResist system vs. human experts (EVE) for the ability to predict response to treatment.

METHODS

The EuResist system was compared with 10 HIV-1 drug resistance experts for the ability to predict 8-week response to 25 treatment cases derived from the EuResist database validation data set. All current and past patient data were made available to simulate clinical practice. The experts were asked to provide a qualitative and quantitative estimate of the probability of treatment success.

RESULTS

There were 15 treatment successes and 10 treatment failures. In the classification task, the number of mislabelled cases was six for EuResist and 6-13 for the human experts [mean±standard deviation (SD) 9.1±1.9]. The accuracy of EuResist was higher than the average for the experts (0.76 vs. 0.64, respectively). The quantitative estimates computed by EuResist were significantly correlated (Pearson r=0.695, P<0.0001) with the mean quantitative estimates provided by the experts. However, the agreement among experts was only moderate (for the classification task, inter-rater κ=0.355; for the quantitative estimation, mean±SD coefficient of variation=55.9±22.4%).

CONCLUSIONS

With this limited data set, the EuResist engine performed comparably to or better than human experts. The system warrants further investigation as a treatment-decision support tool in clinical practice.

Only slight impact of predicted replicative capacity for therapy response prediction

Background

Replication capacity (RC) of specific HIV isolates is occasionally blamed for unexpected treatment responses. However, the role of viral RC in response to antiretroviral therapy is not yet fully understood.

Materials and Methods

We developed a method for predicting RC from genotype using support vector machines (SVMs) trained on about 300 genotype-RC pairs. Next, we studied the impact of predicted viral RC (pRC) on the change of viral load (VL) and CD4⁺ T-cell count (CD4) during the course of therapy on about 3,000 treatment change episodes (TCEs) extracted from the EuResist integrated database. Specifically, linear regression models using either treatment activity scores (TAS), the drug combination, or pRC or any combination of these covariates were trained to predict change in VL and CD4, respectively.

Results

The SVM models achieved a Spearman correlation (ρ) of 0.54 between measured RC and pRC. The prediction of change in VL (CD4) was best at 180 (360) days, reaching a correlation of ρ = 0.45 (ρ = 0.27). In general, pRC was inversely correlated to drug resistance at treatment start (on average ρ = −0.38). Inclusion of pRC in the linear regression models significantly improved prediction of virological response to treatment based either on the drug combination or on the TAS (t-test; p-values range from 0.0247 to 4 10⁻⁶) but not for the model using both TAS and drug combination. For predicting the change in CD4 the improvement derived from inclusion of pRC was not significant.

Conclusion

Viral RC could be predicted from genotype with moderate accuracy and could slightly improve prediction of virological treatment response. However, the observed improvement could simply be a consequence of the significant correlation between pRC and drug resistance.

Transmission of drug-resistant HIV-1 is stabilizing in Europe

The SPREAD Programme investigated prospectively the time trend from September 2002 through December 2005 of transmitted drug resistance (TDR) among 2793 patients in 20 European countries and in Israel with newly diagnosed human immunodeficiency virus type 1 (HIV-1) infection. The overall prevalence of TDR was 8.4% (225 of 2687 patients; 95% confidence interval [CI], 7.4%-9.5%), the prevalence of nucleoside reverse-transcriptase inhibitor (NRTI) resistance was 4.7% (125 of 2687 patients; 95% CI, 3.9%-5.5%), the prevalence of nonucleoside reverse-transcriptase inhibitor (NNRTI) resistance was 2.3% (62 of 2687 patients; 95% CI, 1.8%-2.9%), and the prevalence of protease inhibitor (PI) resistance was 2.9% (79 of 2687 patients; 95% CI, 2.4%-3.6%). There was no time trend in the overall TDR or in NRTI resistance, but there was a statistically significant decrease in PI resistance (P = .04) and in NNRTI resistance after an initial increase (P = .02). We found that TDR appears to be stabilizing in Europe, consistent with recent reports of decreasing drug resistance and improved viral suppression in patients treated for HIV-1 infection.

Tracing the HIV-1 subtype B mobility in Europe: a phylogeographic approach

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.

Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment

Background

The extreme flexibility of the HIV type-1 (HIV-1) genome makes it challenging to build the ideal antiretroviral treatment regimen. Interpretation of HIV-1 genotypic drug resistance is evolving from rule-based systems guided by expert opinion to data-driven engines developed through machine learning methods.

Methods

The aim of the study was to investigate linear and non-linear statistical learning models for classifying short-term virological outcome of antiretroviral treatment. To optimize the model, different feature selection methods were considered. Robust extra-sample error estimation and different loss functions were used to assess model performance. The results were compared with widely used rule-based genotypic interpretation systems (Stanford HIVdb, Rega and ANRS).

Results

A set of 3,143 treatment change episodes were extracted from the EuResist database. The dataset included patient demographics, treatment history and viral genotypes. A logistic regression model using high order interaction variables performed better than rule-based genotypic interpretation systems (accuracy 75.63% versus 71.74–73.89%, area under the receiver operating characteristic curve [AUC] 0.76 versus 0.68–0.70) and was equivalent to a random forest model (accuracy 76.16%, AUC 0.77). However, when rule-based genotypic interpretation systems were coupled with additional patient attributes, and the combination was provided as input to the logistic regression model, the performance increased significantly, becoming comparable to the fully data-driven methods.

Conclusions

Patient-derived supplementary features significantly improved the accuracy of the prediction of response to treatment, both with rule-based and data-driven interpretation systems. Fully data-driven models derived from large-scale data sources show promise as antiretroviral treatment decision support tools.

Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment

BACKGROUND

The extreme flexibility of the HIV type-1 (HIV-1) genome makes it challenging to build the ideal antiretroviral treatment regimen. Interpretation of HIV-1 genotypic drug resistance is evolving from rule-based systems guided by expert opinion to data-driven engines developed through machine learning methods.

METHODS

The aim of the study was to investigate linear and non-linear statistical learning models for classifying short-term virological outcome of antiretroviral treatment. To optimize the model, different feature selection methods were considered. Robust extra-sample error estimation and different loss functions were used to assess model performance. The results were compared with widely used rule-based genotypic interpretation systems (Stanford HIVdb, Rega and ANRS).

RESULTS

A set of 3,143 treatment change episodes were extracted from the EuResist database. The dataset included patient demographics, treatment history and viral genotypes. A logistic regression model using high order interaction variables performed better than rule-based genotypic interpretation systems (accuracy 75.63% versus 71.74-73.89%, area under the receiver operating characteristic curve [AUC] 0.76 versus 0.68-0.70) and was equivalent to a random forest model (accuracy 76.16%, AUC 0.77). However, when rule-based genotypic interpretation systems were coupled with additional patient attributes, and the combination was provided as input to the logistic regression model, the performance increased significantly, becoming comparable to the fully data-driven methods.

CONCLUSIONS

Patient-derived supplementary features significantly improved the accuracy of the prediction of response to treatment, both with rule-based and data-driven interpretation systems. Fully data-driven models derived from large-scale data sources show promise as antiretroviral treatment decision support tools.

Comparison of classifier fusion methods for predicting response to anti HIV-1 therapy

Background

Analysis of the viral genome for drug resistance mutations is state-of-the-art for guiding treatment selection for human immunodeficiency virus type 1 (HIV-1)-infected patients. These mutations alter the structure of viral target proteins and reduce or in the worst case completely inhibit the effect of antiretroviral compounds while maintaining the ability for effective replication. Modern anti-HIV-1 regimens comprise multiple drugs in order to prevent or at least delay the development of resistance mutations. However, commonly used HIV-1 genotype interpretation systems provide only classifications for single drugs. The EuResist initiative has collected data from about 18,500 patients to train three classifiers for predicting response to combination antiretroviral therapy, given the viral genotype and further information. In this work we compare different classifier fusion methods for combining the individual classifiers.

Principal Findings

The individual classifiers yielded similar performance, and all the combination approaches considered performed equally well. The gain in performance due to combining methods did not reach statistical significance compared to the single best individual classifier on the complete training set. However, on smaller training set sizes (200 to 1,600 instances compared to 2,700) the combination significantly outperformed the individual classifiers (p<0.01; paired one-sided Wilcoxon test). Together with a consistent reduction of the standard deviation compared to the individual prediction engines this shows a more robust behavior of the combined system. Moreover, using the combined system we were able to identify a class of therapy courses that led to a consistent underestimation (about 0.05 AUC) of the system performance. Discovery of these therapy courses is a further hint for the robustness of the combined system.

Conclusion

The combined EuResist prediction engine is freely available at http://engine.euresist.org.

Selecting anti-HIV therapies based on a variety of genomic and clinical factors

Motivation: Optimizing HIV therapies is crucial since the virus rapidly develops mutations to evade drug pressure. Recent studies have shown that genotypic information might not be sufficient for the design of therapies and that other clinical and demographical factors may play a role in therapy failure. This study is designed to assess the improvement in prediction achieved when such information is taken into account. We use these factors to generate a prediction engine using a variety of machine learning methods and to determine which clinical conditions are most misleading in terms of predicting the outcome of a therapy.

Results: Three different machine learning techniques were used: generative–discriminative method, regression with derived evolutionary features, and regression with a mixture of effects. All three methods had similar performances with an area under the receiver operating characteristic curve (AUC) of 0.77. A set of three similar engines limited to genotypic information only achieved an AUC of 0.75. A straightforward combination of the three engines consistently improves the prediction, with significantly better prediction when the full set of features is employed. The combined engine improves on predictions obtained from an online state-of-the-art resistance interpretation system. Moreover, engines tend to disagree more on the outcome of failure therapies than regarding successful ones. Careful analysis of the differences between the engines revealed those mutations and drugs most closely associated with uncertainty of the therapy outcome.

Availability: The combined prediction engine will be available from July 2008, see http://engine.euresist.org

Contact:rosen@il.ibm.com

Hepatitis C virus genotypes distribution and transmission risk factors in Luxembourg from 1991 to 2006

AIM: To analyze the Hepatitis C virus (HCV) genotype distribution and transmission risk factors in a population of unselected patients in Luxembourg.

METHODS: Epidemiological information (gender, age and transmission risks) were collected from 802 patients newly diagnosed for hepatitis C and living in Luxembourg, among whom 228 patients referred from prison. Genotyping using 5’noncoding (5’NC) sequencing was performed. We compared categorical data using the Fisher’s exact F-test and odds ratios (OR) were calculated for evaluating association of HCV genotype and risk factors.

RESULTS: The sex ratio was predominantly male (2.2) and individuals aged less than 40 years represented 49.6% of the population. Genotype 1 was predominant (53.4%) followed by genotype 3 (33%). Among risk factors, intravenous drug usage (IVDU) was the most frequently reported (71.4%) followed by medical-related transmission (17.6%) including haemophilia, transfusion recipients and other nosocomial reasons. Genotype 3 was significantly associated to IVDU (OR = 4.84, P < 0.0001) whereas genotype 1 was significantly associated with a medical procedure (OR = 2.42, P < 0.001). The HCV genotype distribution from inmate patients differed significantly from the rest of the population (Chi-square test with four degrees of freedom, P < 0.0001) with a higher frequency of genotype 3 (46.5% vs 27.5%) and a lower frequency of genotype 1 and 4 (44.7% vs 56.8% and 5.3% vs 9.6%, respectively). IVDU was nearly exclusively reported as a risk factor in prison.

CONCLUSION: We report the first description of the HCV genotype distribution in Luxembourg. The repartition is similar to other European countries, with one of the highest European prevalence rates of genotype 3 (33%). Since serology screening became available in 1991, IVDU remains the most common way of HCV transmission in Luxembourg.

[Using the method of central relationship conflict topic in a study of the process and outcome of long-term inpatient group psychotherapy]

Within a research project dealing with the process and outcome of inpatient group psychotherapy, the core conflictual relationship theme method (CCRT) was used to determine if the central basic interpersonal problems of patients differ in comparison of individual pre- and postreatment sessions, if the CCRT determined at the beginning of treatment is related to outcome, and if there is a similarity between the CCRT from individual and group sessions. Comparisons of the CRRT(-components) from the beginning and the end of treatment (related to 19 patients) indicated marked changes on the levels of wishes and responses from others as well as "formal" changes of the narratives (temporal relations as well as the objects mentioned). The second part of the study (n = 26) revealed differences between subgroups determined on the basis of differential outcome measures with respect to the structure of their conflicts. The similarity of the CCRT from group and individual sessions which was studied for nine patients appeared to be moderate. The study revealed that the CCRT might need some minor revisions but appears to be an important method to thoroughly describe the effects of psychotherapies.

Efficacy of Pasteurella haemolytica subunit antigens in a goat model of pasteurellosis

The effectiveness of Pasteurella haemolytica biovar A, serovar 1 (Ph1) subunit vaccines was tested in goats, using challenge exposure by transthoracic injection. Twenty-two weanling male Spanish goats were randomly allotted to 4 groups. Six goats were given 2 transthoracic injections into the lung 18 days apart with live Ph1 impregnated in agar beads (positive controls). Six goats were not given injections (negative controls). Five goats were given 2 transthoracic injections into the lung 18 days apart with 4.6 mg of cytotoxin in agar beads. The remaining 5 goats were given 2 IM injections, 18 days apart, into the thigh with 4.6 mg of cytotoxin emulsified in incomplete Freund's adjuvant. Twenty-four days after the second injection, all goats were challenge-exposed to live Ph1 by transthoracic injection into the lung, and 4 days later, all goats were euthanatized and necropsied. Serum neutralizing anticytotoxin titer was measured throughout the experiment. Mean volume of consolidated lung tissue was 0.38 cm3 for the positive control group, 32 cm3 for the negative control group; 19 cm3 for the cytotoxin-lung group; and 88 cm3 for the cytotoxin-adjuvant-IM group. Only the positive control group was protected from Ph1 challenge exposure. The Ph1 cytotoxin subunit vaccine alone appeared to be ineffective, and the anticytotoxin titer was not correlated with protection. In a separate trial, 32 weanling male Spanish goats were randomly allotted to 5 groups. Each was given 2 transthoracic injections into the lung 22 days apart. Six goats were given Ph1 cytotoxin impregnated into agar beads; 6 were given Ph1 lipopolysaccharide impregnated in agar beads; 6 were given Ph1 capsule impregnated in agar beads. Six goats were given agar beads only (negative controls), and 6 were given live Ph1 impregnated into agar beads (positive controls). Twenty days after the second injection, all goats were challenge-exposed to live Ph1 by transthoracic injection into the lung, and 4 days later, all goats were euthanatized and necropsied. Mean volume of consolidated lung tissue was 0.14 cm3 for the positive control group, 7.59 cm3 for the negative control group, 11.21 cm3 for the cytotoxin group, 10.19 cm3 for the lipopolysaccharide group, and 1.6 cm3 for the capsule group. Again, only injection of live Ph1 (positive controls) induced solid protection; however, the capsule subunit vaccine induced partial protection against challenge exposure in this trial. Lipopolysaccharide and cytotoxin subunit vaccines were ineffective in protecting goats against challenge exposure with live Ph1.