Biology subjects

Van Damme, P.

Publications and source records attributed to Van Damme, P..

5 recordsLinked to original sources

bioRxiv2018

An ODE-based mixed modelling approach for B- and T-cell dynamics induced by Varicella-Zoster Virus vaccines in adults shows higher T-cell proliferation with Shingrix compared to Varilrix

Clinical trials covering the immunogenicity of a vaccine aim to study the longitudinal dynamics of certain immune cells after vaccination. The corresponding immunogenicity datasets are mainly analyzed by the use of statistical (mixed effects) models. This paper proposes the use of mathematical ordinary differential equation (ODE) models, combined with a mixed effects approach. ODE models are capable of translating underlying immunological post vaccination processes into mathematical formulas thereby enabling a testable data analysis. Mixed models include both population-averaged parameters (fixed effects) and individual-specific parameters (random effects) for dealing with inter-and intra-individual variability, respectively.\n\nThis paper models B-cell and T-cell datasets of a phase I/II, open-label, randomized, parallel-group study in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix).\n\nSince few significant correlations were assessed between the B-cell datasets and T-cell datasets, each dataset was modeled separately. By following a general approach to both the formulation of several different models and the procedure of selecting the most suitable model, we were able propose a mathematical ODE mixed-effects model for each dataset. As such, the use of ODE-based mixed effects models offers a suitable framework for handling longitudinal vaccine immunogenicity data. Moreover, it is possible to test differences in immunological processes between the two vaccines.\n\nWe found that the Shingrix vaccination schedule led to a more pronounced proliferation of T-cells, without a difference in T-cell decay rate compared to the Varilrix vaccination schedule.\n\nAuthor summaryUpon vaccination, B-cells and T-cells are activated to induce an immune response against the vaccine antigen at hand. In this paper, we study and compare the longitudinal dynamics of the specific immune response based on a vaccine trial in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix). We combine the use of ordinary differential equations (ODEs), i.e. mathematical models which are used to describe the dynamics of the immune response, with advanced regression analyses enabling us to infer the model parameters describing these dynamics. The resulting ODE-based mixed effects models enable describing the immune response dynamics allowing for both inter-and intra-individual variability; comparing the dynamics induced by the two vaccines and studying the B-and T-cell interactions. We found a more pronounced proliferation of T-cells for the Shingrix vaccination schedule as compared to the Varilrix vaccination schedule. The proposed methodology offers a suitable framework for better understanding the immunogenicity of vaccines.

immunology↗

bioRxiv2018

Low frequency and rare coding variation contributes to multiple sclerosis risk

Multiple sclerosis is a common, complex neurological disease, where almost 20% of risk heritability can be attributed to common genetic variants, including >230 identified by genome-wide association studies (Patsopoulos et al., 2017). Multiple strands of evidence suggest that the majority of the remaining heritability is also due to the additive effects of individual variants, rather than epistatic interactions between these variants, or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that as much as 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common variant signals, which highlight a key role for regulatory T cell homeostasis and regulation, IFN{gamma} biology and NF{kappa}B signaling in MS pathogenesis. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

genetics↗

bioRxiv2017

Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis

The most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility of disease. We have therefore begun Project MinE, an international collaboration that seeks to analyse whole-genome sequence data of at least 15,000 ALS patients and 7,500 controls. Here, we report on the design of Project MinE and pilot analyses of newly whole-genome sequenced 1,264 ALS patients and 611 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1 %), the vast majority of which is absent in public data sets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.

genetics↗

bioRxiv2017

REPARATION: Ribosome Profiling Assisted (Re-)Annotation of Bacterial genomes.

Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated methods depend heavily on sequence context and often underestimate the complexity of the proteome. We developed REPARATION (RibosomeE Profiling Assisted (Re-)AnnotaTION), a de novo algorithm that takes advantage of experimental protein translation evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation. REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds based on a growth curve model to screen for spurious ORFs. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel (small) ORFs including variants of previously annotated ORFs. Our predictions were supported by matching mass spectrometry (MS) proteomics data, sequence composition and conservation analysis. REPARATION is unique in that it makes use of experimental translation evidence to perform de novo ORF delineation in bacterial genomes irrespective of the sequence context of the reading frame.

microbiology↗

bioRxiv2016

A Unique Ribosome Signature Reveals Bacterial Translation Initiation Sites

ABSTRCTWhile methods for annotation of genes are increasingly reliable the exact identification of the translation initiation site remains a challenging problem. Since the N-termini of proteins often contain regulatory and targeting information developing a robust method for start site identification is crucial. Ribosome profiling reads show distinct patterns of read length distributions around translation initiation sites. These patterns are typically lost in standard ribosome profiling analysis pipelines, when reads from footprints are adjusted to determine the specific codon being translated. Using these unique signatures we build a model capable of predicting translation initiation sites and demonstrate its high accuracy using N-terminal proteomics. Applying this to prokaryotic samples, we re-annotate translation initiation sites and provide evidence of N-terminal truncations and elongations of annotated coding sequences. These re-annotations are supported by the presence of Shine-Dalgarno sequences, structural and sequence based features and N-terminal peptides. Finally, our model identifies 61 novel genes previously undiscovered in the genome.

bioinformatics↗