Percorrer por autor "Kaiser, Rolf"
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- Earlier initiation of antiretroviral treatment coincides with an initial control of the HIV-1 sub-subtype F1 outbreak among men-having-sex-with-men in Flanders, BelgiumPublication . Vinken, Lore; Fransen, Katrien; Cuypers, Lize; Alexiev, Ivailo; Balotta, Claudia; Debaisieux, Laurent; Seguin-Devaux, Carole; Ribas, Sergio García; Gomes, Perpétua; Incardona, Francesca; Kaiser, Rolf; Ruelle, Jean; Sayan, Murat; Paraschiv, Simona; Paredes, Roger; Peeters, Martine; Sönnerborg, Anders; Vancutsem, Ellen; Vandamme, Anne-Mieke; Van den Wijngaert, Sigi; Van Ranst, Marc; Verhofstede, Chris; Stadler, Tanja; Lemey, Philippe; Van Laethem, KristelHuman immunodeficiency virus type 1 (HIV-1) non-B subtype infections occurred in Belgium since the 1980s, mainly amongst migrants and heterosexuals, whereas subtype B predominated in men-having-sex-with-men (MSM). In the last decade, the diagnosis of F1 sub-subtype in particular has increased substantially, which prompted us to perform a detailed reconstruction of its epidemiological history. To this purpose, the Belgian AIDS Reference Laboratories collected HIV-1 pol sequences from all sub-subtype F1-infected patients for whom genotypic drug resistance testing was requested as part of routine clinical follow-up. This data was complemented with HIV-1 pol sequences from countries with a high burden of F1 infections or a potential role in the global origin of sub-subtype F1. The molecular epidemiology of the Belgian subtype F1 epidemic was investigated using Bayesian phylogenetic inference and transmission dynamics were characterized based on birth-death models. F1 sequences were retained from 297 patients diagnosed and linked to care in Belgium between 1988 and 2015. Phylogenetic inference indicated that among the 297 Belgian F1 sequences, 191 belonged to a monophyletic group that mainly contained sequences from people likely infected in Belgium (OR 26.67, 95% CI 9.59–74.15), diagnosed in Flanders (OR 7.28, 95% CI 4.23–12.53), diagnosed at a recent stage of infection (OR 7.19, 95% CI 2.88-17.95) or declared to be MSM (OR 34.8, 95% CI 16.0–75.6). Together with a Spanish clade, this Belgian clade was embedded in the genetic diversity of Brazilian subtype F1 strains and most probably emerged after one or only a few migration events from Brazil to the European continent before 2002. The origin of the Belgian outbreak was dated back to 2002 (95% higher posterior density 2000–2004) and birth-death models suggested that its extensive growth had been controlled (Re < 1) by 2012, coinciding with a time period where delay in antiretroviral treatment initiation substantially declined. In conclusion, phylogenetic reconstruction of the Belgian HIV-1 sub-subtype F1 epidemic illustrates the introduction and substantial dissemination of viral strains in a geographically restricted risk group that was most likely controlled by effective treatment as prevention.
- A genotypic method for determining HIV-2 coreceptor usage enables epidemiological studies and clinical decision supportPublication . Döring, Matthias; Borrego, Pedro; Büch, Joachim; Martins, Andreia; Friedrich, Georg; Camacho, Ricardo Jorge; Eberle, Josef; Kaiser, Rolf; Lengauer, Thomas; Taveira, Nuno; Pfeifer, NicoBackground: CCR5-coreceptor antagonists can be used for treating HIV-2 infected individuals. Before initiating treatment with coreceptor antagonists, viral coreceptor usage should be determined to ensure that the virus can use only the CCR5 coreceptor (R5) and cannot evade the drug by using the CXCR4 coreceptor (X4-capable). However, until now, no online tool for the genotypic identification of HIV-2 coreceptor usage had been available. Furthermore, there is a lack of knowledge on the determinants of HIV-2 coreceptor usage. Therefore, we developed a data-driven web service for the prediction of HIV-2 coreceptor usage from the V3 loop of the HIV-2 glycoprotein and used the tool to identify novel discriminatory features of X4-capable variants. Results: Using 10 runs of tenfold cross validation, we selected a linear support vector machine (SVM) as the model for geno2pheno[coreceptor-hiv2], because it outperformed the other SVMs with an area under the ROC curve (AUC) of 0.95. We found that SVMs were highly accurate in identifying HIV-2 coreceptor usage, attaining sensitivities of 73.5% and specificities of 96% during tenfold nested cross validation. The predictive performance of SVMs was not significantly different (p value 0.37) from an existing rules-based approach. Moreover, geno2pheno[coreceptor-hiv2] achieved a predictive accuracy of 100% and outperformed the existing approach on an independent data set containing nine new isolates with corresponding phenotypic measurements of coreceptor usage. geno2pheno[coreceptor-hiv2] could not only reproduce the established markers of CXCR4-usage, but also revealed novel markers: the substitutions 27K, 15G, and 8S were significantly predictive of CXCR4 usage. Furthermore, SVMs trained on the amino-acid sequences of the V1 and V2 loops were also quite accurate in predicting coreceptor usage (AUCs of 0.84 and 0.65, respectively). Conclusions: In this study, we developed geno2pheno[coreceptor-hiv2], the first online tool for the prediction of HIV-2 coreceptor usage from the V3 loop. Using our method, we identified novel amino-acid markers of X4-capable variants in the V3 loop and found that HIV-2 coreceptor usage is also influenced by the V1/V2 region. The tool can aid clinicians in deciding whether coreceptor antagonists such as maraviroc are a treatment option and enables epidemiological studies investigating HIV-2 coreceptor usage. geno2pheno[coreceptor-hiv2] is freely available at http://coreceptor-hiv2.geno2pheno.org.
- New findings in HCV genotype distribution in selected West European, Russian and Israeli regionsPublication . Kartashev, Vladimir; Döring, Matthias; Nieto, Leonardo; Coletta, Eleda; Kaiser, Rolf; Sierra, Saleta; HCV EuResist Study group; Guerrero, A.; Stoiber, H.; Paar, C.; Vandamme, A. M.; Nevens, F.; Ranst, M. Van; Cuypers, L.; Braun, P.; Ehret, R.; Obermeier, M.; Schneeweiss, S.; Scholten, S.; Römer, K.; Isernhagen, K.; Qurashi, N.; Heger, E.; Knops, E.; Neumann-Fraune, M.; Timm, J.; Walker, A.; Lübke, N.; Wedemeyer, H.; Wiesch, J. Schulze zur; Lütgehetmann, M.; Polywka, S.; Däumer, M.; Hoffmann, D.; Protzer, U.; Marascio, N.; Foca, A.; Liberto, M. C.; Barreca, G. S.; Galati, L.; Torti, C.; Pisani, V.; Perno, C. F.; Ceccherini-Silberstein, F.; Cento, V.; Ciotti, M.; Zazzi, M.; Rossetti, A.; De Luca, A.; Caudai, C.; Mor, O.; Devaux, C.; Staub, T.; Araujo, F.; Gomes, P.; Cabanas, J.; Markin, N.; Khomenko, I.; Govorukhina, M.; Lugovskaya, G.; Dontsov, D.; Mas, A.; Martró, E.; Saludes, V.; Rodríguez-Frías, F.; García, F.; Casas, P.; Iglesia, A. de la; Alados, J. C.; Pena-López, M. J.; Rodríguez, M. J.; Galán, J. C.; Suárez, A.; Cardeñoso, L.; Guerrero, M. D.; Vegas-Dominguez, C.; Blas-Espada, J.; García, R.; García-Bujalance, S.; Benítez-Gutiérrez, L.; Mendoza, C. de; Montiel, N.; Santos, J.; Viciana, I.; Delgado, A.; Martínez-Sanchez, P. A.; Fernández-Alonso, M.; Reina, G.; Trigo, M.; Echeverría, M. J.; Aguilera, A.; Navarro, D.; Bernal, S.; Lozano, M. C.; Fernández-Cuenca, F.; Orduña, A.; Eiros, J. M.; Ortíz de Lejarazu, R.; Martínez-Sapiña, A. M.; García-Díaz, A.; Haque, T.BACKGROUND: HCV affects 185 million people worldwide and leads to death and morbidities. HCV has a high genetic diversity and is classified into seven genotypes and 67 subtypes. Novel anti-HCV drugs (Direct-Acting-Antivirals) eligibility, resistance and cure rates depend on HCV geno/subtype (GT). OBJECTIVES: Analysis of epidemiological information and viral GT from patients undergoing viral genotyping in 2011-2015. STUDY DESIGN: Anonymized information from 52 centers was analyzed retrospectively. RESULTS: 37,839 samples were included in the study. We show that the GT distribution is similar throughout Western European countries, with some local differences. Here GTs 1 and 2 prevalences are lower and of GT4 higher than in all previous reports. Israel has a unique GT pattern and in South Russia the GT proportions are more similar to Asia. GTs 5 and 6 were detected in very low proportions. Three cases of the recombinant genotype P were reported in Munich (Germany). In addition, we observed that GT proportion was dependant on patientś gender, age and transmission route: GTs 1b and 2 were significantly more common in female, older, nosocomially-infected patients, while GTs 1a, 3 and 4 were more frequent in male, younger patients infected by tattooing, drug consume, and/or sexual practices. In infections acquired by drug consume, GTs 1a (35.0%) and 3 (28.1%) prevailed. In infections related to sexual practices lower proportion of GT3 (14.0%) and higher of GT4 (20.2%) were detected. GT4 was mostly abundant in MSM (29.6%). HIV coinfection was significantly associated with higher proportions GTs 1a and 4 (42.5% and 19.3%, respectively). CONCLUSION: Genotype prevalence evolves and correlates to epidemiological factors. Continuous surveillance is necessary to better assess hepatitis C infection in Europe and to take appropriate actions
- Using drug exposure for predicting drug resistance - A data-driven genotypic interpretation toolPublication . Pironti, Alejandro; Pfeifer, Nico; Walter, Hauke; Jensen, Björn-Erik O.; Zazzi, Maurizio; Gomes, Perpétua; Kaiser, Rolf; Lengauer, ThomasAntiretroviral treatment history and past HIV-1 genotypes have been shown to be useful predictors for the success of antiretroviral therapy. However, this information may be unavailable or inaccurate, particularly for patients with multiple treatment lines often attending different clinics. We trained statistical models for predicting drug exposure from current HIV-1 genotype. These models were trained on 63,742 HIV-1 nucleotide sequences derived from patients with known therapeutic history, and on 6,836 genotype-phenotype pairs (GPPs). The mean performance regarding prediction of drug exposure on two test sets was 0.78 and 0.76 (ROC-AUC), respectively. The mean correlation to phenotypic resistance in GPPs was 0.51 (PhenoSense) and 0.46 (Antivirogram). Performance on prediction of therapy-success on two test sets based on genetic susceptibility scores was 0.71 and 0.63 (ROC-AUC), respectively. Compared to geno2pheno[resistance], our novel models display a similar or superior performance. Our models are freely available on the internet via www.geno2pheno.org. They can be used for inferring which drug compounds have previously been used by an HIV-1-infected patient, for predicting drug resistance, and for selecting an optimal antiretroviral therapy. Our data-driven models can be periodically retrained without expert intervention as clinical HIV-1 databases are updated and therefore reduce our dependency on hard-to-obtain GPPs.