Matthias Assel

Comparison of HIV-1 genotypic resistance test interpretation systems in predicting virological outcomes over time

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 Stanfords 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 ratios 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 ratios increased over time, but remained comparable (odds ratios 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, and 48 weeks, after change of treatment to the same extent.

Large knowledge collider: a service-oriented platform for large-scale semantic reasoning

Recent advances in the Semantic Web community have yielded a variety of reasoning methods used to process and exploit semantically annotated data. However, most of those methods have only been approved for small, closed, trustworthy, consistent, and static domains. Still, there is a deep mismatch between the requirements for reasoning on a Web scale and the existing efficient reasoning algorithms over restricted subsets. This paper describes the pilot implementation of LarKC -- the Large Knowledge Collider, a platform, which focuses on supporting large-scale reasoning over billions of structured data in heterogeneous data sets. The architecture of LarKC allows for an effective combination of techniques coming from different Semantic Web domains by following a service-oriented approach, supplied by sustainable infrastructure solutions.

Virtual Laboratory for Development and Execution of Biomedical Collaborative Applications

The ViroLab Virtual Laboratory is a collaborative platform for scientists representing multiple fields of expertise while working together on common scientific goals. This environment makes it possible to combine efforts of computer scientists, virology and epidemiology experts and experienced physicians to support future advances in HIV-related research and treatment. The paper explains the challenges involved in building a modern, inter-organizational platform to support science and gives an overview of solutions to these challenges. Examples of real-world problems applied in the presented environment are also described to prove the feasibility of the solution.

RegaDB: community-driven data management and analysis for infectious diseases

Summary: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface. Availability and implementation: Source code, binaries and documentation are available on http://rega.kuleuven.be/cev/regadb. RegaDB is written in the Java programming language, using a web-service-oriented architecture. Contact: pieter.libin@rega.kuleuven.be

Superinfection with drug-resistant HIV is rare and does not contribute substantially to therapy failure in a large European cohort.

BackgroundSuperinfection 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.MethodsWe 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.Results4425 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 to drugs used at the time of strain replacement did not change in these two patients. A third case could not be validated by re-sequencing, but was supported as superinfection by an intermediate sequence with high degenerate base pair count within the time frame of strain switching. Drug resistance increased in this single patient.ConclusionsRoutine 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, superinfection with drug resistant HIV did not compromise the efficiency of antiretroviral treatment.

Resource fabrics: The next level of Grids and Clouds

With the growing amount of computational resources not only locally (multi-core), but also across the web, utility computing (aka Clouds and Grids) becomes more and more interesting as a means to outsource management and services. So far, these machines still act like external resources that have to be explicitly selected, integrated, accessed etc. - much like the concept of “Virtual Organisation” prescribes. This paper will describe how the development of dealing with increased scale and heterogeneity of future systems will implicitly open the door for new ways if integrating and using remote resources through a kind of web-based “fabric”.

ViroLab Security and Virtual Organization Infrastructure

This paper introduces security requirements and solutions present in the ViroLab Virtual Laboratory. Our approach is to use a federated Single Sign-On mechanism based on the Shibboleth framework that enables multiple partners to authenticate against their local identity systems and use resources provided by all other partners. Since the basic Shibboleth capabilities do not meet our specific requirements related to supporting non-web-based services, we created a set of custom tools that allow us to develop a homogeneous, Shibboleth-based security solution for both Web and non-web-based software components. This paper describes these tools in detail, together with other services of the virtual laboratory which have been integrated with the security infrastructure. A decentralized, attribute-based approach facilitating the creation and management of virtual organizations is the key achievement of our work.

Integrating and Accessing Medical Data Resources within the ViroLab Virtual Laboratory

This paper presents the data access solutions which have been developed in the ViroLab Virtual Laboratory infrastructure to enable medical researchers and practitioners to conduct experiments in the area of HIV treatment. Such experiments require access to a number of geographically distributed data sets (residing at various hospitals) with heavy focus on integration and security issues. Scientists conducting virtual experiments need to be able to manipulate such distributed data in a consistent and secure manner. We describe the main components of the Virtual Laboratory framework being devoted to data access and explain how data is processed in the presented environment.

A collaborative environment allowing clinical investigations on integrated biomedical databases.

In order to perform clinical investigations on integrated biomedical data sets and to predict virological and epidemiological outcome, medical experts require an IT-based collaborative environment that provides them a user-friendly space for building and executing their complex studies and workflows on largely available and high-quality data repositories. In this paper, the authors introduce such a novel collaborative working environment a so-called virtual laboratory for clinicians and medical researchers, which allows users to interactively access and browse several biomedical research databases and re-use relevant data sets within own designed experiments. Firstly, technical details on the integration of relevant data resources into the virtual laboratory infrastructure and specifically developed user interfaces are briefly explained. The second part describes research possibilities for medical scientists including potential application fields and benefits as using the virtual laboratory functionalities for a particular exemplary study.

Distributed Parallelization of Semantic Web Java Applications by Means of the Message-Passing Interface

In the recent years, performance has become a key point for a number of Java applications. For some of them, such as from the Semantic Web domain, where the size and the scale of the analyzed data is of a big challenge for a conventional computer, use of the High Performance Computing (HPC) systems is a major factor in achieving the required scalability and performance demands. Parallelization is a key mechanism that leverages HPC for such applications. However, the high development effort for a scalable parallel application has been a major drawback towards the efficient application of HPC to the applications designed for a serial execution only. The Message-Passing Interface (MPI) is a well-known programming standard for large-scale parallel applications development. However, MPI has found its most wide use in the applications written in C and Fortran. We show how MPI can be beneficially applied for the parallelization of the Java applications as well. We describe a parallel implementation of a Random Indexing application that performs similarity search in the large text corpora on the web, which allowed us to improve the performance by up to 33 times on the already 16 nodes of a testbed HPC system.