Percorrer por autor "Kaiser, Rolf"
A mostrar 1 - 8 de 8
Resultados por página
Opções de ordenação
- 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.
- HIV multidrug class resistance prediction with a time sliding anchor approachPublication . Arslan, Nurhan; Eggeling, Ralf; Reuter, Bernhard; Leathem, Kristel Van; Pingarilho, Marta; Gomes, Perpétua; Sönnerborg, Anders; Kaiser, Rolf; Zazzi, Maurizio; Pfeifer, Nico; EuResist Network Study GroupMotivation: The emergence of multidrug class resistance (MDR) in Human Immunodeficiency Virus (HIV) is a rare but significant challenge in antiretroviral therapy (ART). MDR, which may arise from prolonged drug exposure, treatment failures, or transmission of resistant strains, accelerates disease progression and poses particular challenges in resource-limited settings with restricted access to resistance testing and advanced therapies. Early prediction of future MDR development is important to inform therapeutic decisions and mitigate its occurrence. Results: In this study, we employ various machine learning classifiers to predict future resistance to all four major antiretroviral drug classes using features extracted from clinical HIV sequence data. We systematically explore several variations of the problem that differ in the pre-existing resistance level and the temporal gap between sample collection and observed MDR occurrence. Our models show the ability to predict multidrug class resistance even in the most challenging variations, albeit at a reduced accuracy. Feature importance analysis reveals that our models primarily utilize known drug resistance mutations for easier classification tasks, but rely on new mutations for the difficult task of distinguishing four class drug resistance from three class drug resistance. Availability and implementation: All analysis was performed using the Euresist Integrated DataBase (EIDB). Researchers wishing to reproduce, validate or extend these findings can request access to the latest EIDB release via the Euresist Network.
- HIV-2 EU—supporting standardized HIV-2 drug resistance interpretation : an updatePublication . Charpentier, Charlotte; Berzow, Dirk; Hingrat, Quentin Le; Kaiser, Rolf; Gomes, Perpétua; Miranda, Ana Cláudia; Damond, Florence; Ghosn, Jade; Kampen, Jeroen J. A. van; Jensen, Björn-Erik Ole; Böhm, Michael; Wensing, Annemarie M. J.; Descamps, Diane; Obermeier, MartinHuman immunodeficiency virus type 2 (HIV-2) is an attenuated retroviral infection characterized by specific natural susceptibility to antiretroviral drugs and acquired resistance profiles. Based on the latest knowledge of phenotypic data and clinical follow-up, HIV-2 resistance interpretation rules have been updated and implemented in a freely available resistance analysis tool.
- 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
- The role of late presenters in HIV-1 transmission clusters in EuropePublication . Miranda, Mafalda N. S.; Pimentel, Victor; Gomes, Perpétua; Martins, Maria do Rosário O.; Seabra, Sofia G.; Kaiser, Rolf; Böhm, Michael; Seguin-Devaux, Carole; Paredes, Roger; Bobkova, Marina; Zazzi, Maurizio; Incardona, Francesca; Pingarilho, Marta; Abecasis, Ana B.Background: Investigating the role of late presenters (LPs) in HIV-1 transmission is important, as they can contribute to the onward spread of HIV-1 virus before diagnosis, when they are not aware of their HIV status. Objective: To characterize individuals living with HIV-1 followed up in Europe infected with subtypes A, B, and G and to compare transmission clusters (TC) in LP vs. non-late presenter (NLP) populations. Methods: Information from a convenience sample of 2679 individuals living with HIV-1 was collected from the EuResist Integrated Database between 2008 and 2019. Maximum likelihood (ML) phylogenies were constructed using FastTree. Transmission clusters were identified using Cluster Picker. Statistical analyses were performed using R. Results: 2437 (91.0%) sequences were from subtype B, 168 (6.3%) from subtype A, and 74 (2.8%) from subtype G. The median age was 39 y/o (IQR: 31.0–47.0) and 85.2% of individuals were males. The main transmission route was via homosexual (MSM) contact (60.1%) and 85.0% originated from Western Europe. In total, 54.7% of individuals were classified as LPs and 41.7% of individuals were inside TCs. In subtype A, individuals in TCs were more frequently males and natives with a recent infection. For subtype B, individuals in TCs were more frequently individuals with MSM transmission route and with a recent infection. For subtype G, individuals in TCs were those with a recent infection. When analyzing cluster size, we found that LPs more frequently belonged to small clusters (<8 individuals), particularly dual clusters (2 individuals). Conclusion: LP individuals are more present either outside or in small clusters, indicating a limited role of late presentation to HIV-1 transmission.
- Spectrum of non-nucleoside reverse transcriptase inhibitor-associated drug resistance mutations in persons living with HIV-1 receiving rilpivirinePublication . Nagarajan, Pavithra; Zhou, Jinru; Teodoro, Giulia Di; Incardona, Francesca; Seguin-Devaux, Carole; Kaiser, Rolf; Abecasis, Ana B.; Gomes, Perpétua; Tao, Kaiming; Zazzi, Maurizio; Shafer, Robert W.; on behalf of the EuResist NetworkIntroduction: Few data are currently available on the nonnucleoside reverse transcriptase (RT) inhibitors (NNRTI) resistance mutations selected in persons living with HIV-1 (PLWH) who develop virological failure while receiving rilpivirine (RPV). Methods: We analyzed pooled HIV-1 RT genotypic data from 280 PLWH in the multicenter EuResist database and 115 PLWH in the Stanford HIV Drug Resistance Database (HIVDB) who received RPV as their only NNRTI. Results: Among the 395 PLWH receiving RPV, 180 (45.6%) had one or more NNRTI-associated DRMs. Overall, 44 NNRTI-associated DRMs were identified, including 26 that occurred in two or more PLWHs. Seven mutations had a prevalence ≥10% among the 180 PLWH with one or more NNRTI-associated DRM: E138K (32.2%), V90I (25.0%), K101E (17.8%), Y181C (17.2%), E138A (13.9%), H221Y (12.2%), and K103N (10.6%). Y181C was significantly more likely to co-occur with K101E, V179F, H221Y, and M230L. Ten novel non-polymorphic mutations at known NNRTI-associated mutation positions were also identified, usually in just one PLWH: L100F, V108A, T139I, P225S, M230V, Y232C, and T240A/I/M/S. Conclusions: Our analysis extends the spectrum of mutations emerging in PLWH receiving RPV. Additional phenotypic characterization of RPV-selected mutations is necessary to better understand their biological and possible clinical significance.
- 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.