Publications of Kyrylo Bessonov
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See detailIntegration of Gene Expression and Methylation to unravel Biological Networks in Glioblastoma Patients
Bessonov, Kyrylo ULg; Gadaleta, Francesco; Van Steen, Kristel ULg

in Genetic Epidemiology (2017)

The vast amount of heterogeneous omics data, encompassing a broad range of biomolecular information, requires novel methods of analysis, including those that integrate the available levels of information ... [more ▼]

The vast amount of heterogeneous omics data, encompassing a broad range of biomolecular information, requires novel methods of analysis, including those that integrate the available levels of information. In this work we describe Regression2Net, a computational approach that is able to integrate gene expression and genomic or methylome data in two steps. First, penalized regressions are used to build Expression-Expression (EEnet) and Expression-Genome or –Methylome (EMnet) networks. Second, network theory is used to highlight important communities of genes. When applying our approach Regression2Net to gene expression and methylation profiles for individuals with glioblastoma multiforme, we identified respectively 284 and 447 potentially interesting genes in relation to glioblastoma pathology. These genes showed at least one connection in the integrated networks ANDnet and XORnet derived from aforementioned EEnet and EMnet networks. Whereas the edges in ANDnet occur in both EEnet and EMnet, the edges in XORnet occur in EMnet but not in EEnet. In-depth biological analysis of connected genes in ANDnet and XORnet revealed genes that are related to energy metabolism, cell cycle control (AATF), immune system response and several cancer types. Importantly, we observed significant over-representation of cancer related pathways including glioma, especially in the XORnet network, suggesting a non-ignorable role of methylation in glioblastoma multiforma. In the ANDnet, we furthermore identified potential glioma suppressor genes ACCN3 and ACCN4 linked to the NBPF1 neuroblastoma breakpoint family, as well as numerous ABC transporter genes (ABCA1, ABCB1) suggesting drug resistance of glioblastoma tumors. [less ▲]

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See detailPractical aspects of gene regulatory inference via conditional inference forests from expression data
Bessonov, Kyrylo ULg; Van Steen, Kristel ULg

in Genetic Epidemiology (2016)

Gene regulatory network (GRN) inference is an active area of research that facilitates understanding the complex interplays between biological molecules. We propose a novel framework to create such GRNs ... [more ▼]

Gene regulatory network (GRN) inference is an active area of research that facilitates understanding the complex interplays between biological molecules. We propose a novel framework to create such GRNs, based on Conditional Inference Forests (CIFs) as proposed by Strobl et al. Our framework consists of using ensembles of Conditional Inference Trees (CITs) and selecting an appropriate aggregation scheme for variant selection prior to network construction. We show on synthetic microarray data that taking the original implementation of CIFs with conditional permutation scheme (CIFcond) may lead to improved performance compared to Breiman's implementation of Random Forests (RF). Among all newly introduced CIF-based methods and five network scenarios obtained from the DREAM4 challenge, CIFcond performed best. Networks derived from well-tuned CIFs, obtained by simply averaging P-values over tree ensembles (CIFmean) are particularly attractive, because they combine adequate performance with computational efficiency. Moreover, thresholds for variable selection are based on significance levels for P-values and, hence, do not need to be tuned. From a practical point of view, our extensive simulations show the potential advantages of CIFmean-based methods. Although more work is needed to improve on speed, especially when fully exploiting the advantages of CITs in the context of heterogeneous and correlated data, we have shown that CIF methodology can be flexibly inserted in a framework to infer biological interactions. Notably, we confirmed biologically relevant interaction between IL2RA and FOXP1, linked to the IL-2 signaling pathway and to type 1 diabetes. [less ▲]

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See detailFrom Statistical to Biological Interactions via Omics Integration
Bessonov, Kyrylo ULg

Doctoral thesis (2016)

The XXI century opened a new ‘Big Data’ era in which, thanks to rapid technological advancements and appearance of high throughput technologies, vast amounts of unstructured omics data (e.g ... [more ▼]

The XXI century opened a new ‘Big Data’ era in which, thanks to rapid technological advancements and appearance of high throughput technologies, vast amounts of unstructured omics data (e.g., transcriptomic, genomic, etc.) are generated every day. This thesis mainly focuses on solving the problems related diverse omics data integration and interaction identification tasks. Particular attention is given to useful knowledge extraction in the context of complex diseases including pathological mechanisms with the development of software tools and pipelines. The diseases covered included glioblastoma multiforme, asthma, and ankylosing spondylitis. Interactions detection in genomic data requires standardization of the protocols. In Chapter 3, we tested the impact of different settings in a genome-wide association interaction study (GWAIS). Some of the settings included marker selection strategy, the LD pruning, lower order effects adjustment, analytical tool. We were able to show that even small changes in each setting can have drastic impacts requiring careful assessment of proper settings and results comparisons across several analysis protocols. The greatest impact was attributed to the input dataset composition highlighting the importance of the marker selection strategy and use of prior knowledge. Expression of genes can be affected by nearby (‘cis’) or distant (‘trans’) genotypes. Thus, we developed methodology to identify complex trans/cis regulatory mechanisms between expression and genotype data in the context of asthma (CAMP data). Significant overlap between ‘trans’ and ‘cis’ gene regulatory components related to immune and signaling pathways was clearly identified matching asthma disease pathology. The semi-parametric Model-Based Multifactor Dimensionality Reduction (MB-MDR) method was applied for the first time in the context eQTL study achieving low false discovery and family-wise error rates (FDR and FWER). Identification of a meaningful data structure from omics data is a pressing topic nowadays. Gene regulatory networks (GRN) conveniently summarize large amounts of data allowing for useful knowledge generation. GRN inference is especially attractive for deciphering of complex diseases mechanisms allowing biologists to formulate a better hypothesis. We were able to generate GRNs from a single source (e.g., microarray expression data) using conditional inference forest (CIF) with more attractive features compared to classical Random-Forest (RF) including unbiased node variable selection even in the context of highly correlated variables particularly relevant in transcriptomics. The CIF methods provided attractive features and performance characteristics coupled to valuable pathological insights into type 1 diabetes. [less ▲]

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See detailA cautionary note on the impact of protocol changes for Genome-Wide Association SNP x SNP Interaction studies: an example on ankylosing spondylitis
Bessonov, Kyrylo ULg; Gusareva, Elena ULg; Van Steen, Kristel ULg

in Human Genetics (2015)

Genome-wide association interaction (GWAI) studies have increased in popularity. Yet to date, no standard protocol exists. In practice, any GWAI workflow involves making choices about quality control ... [more ▼]

Genome-wide association interaction (GWAI) studies have increased in popularity. Yet to date, no standard protocol exists. In practice, any GWAI workflow involves making choices about quality control strategy, SNP filtering, linkage disequilibrium (LD) pruning, analytic tool to model or to test for genetic interactions. Each of these can have an impact on the final epistasis findings and may affect their reproducibility in follow-up analyses. Choosing an analytic tool is not straightforward, as different such tools exist and current understanding about their performance is based on often very particular simulation settings. In the present study, we wish to create awareness for the impact of (minor) changes in a GWAI analysis protocol can have on final epistasis findings. In particular, we investigate the influence of marker selection and marker prioritization strategies, LD pruning and the choice of epistasis detection analytics on study results, giving rise to 8 GWAI protocols. Discussions are made in the context of the ankylosing spondylitis (AS) data obtained via the Wellcome Trust Case Control Consortium (WTCCC2). As expected, the largest impact on AS epistasis findings is caused by the choice of marker selection criterion, followed by marker coding and LD pruning. In MB-MDR, co-dominant coding of main effects is more robust to the effects of LD pruning than additive coding. We were able to reproduce previously reported epistasis involvement of HLA-B and ERAP1 in AS pathology. In addition, our results suggest involvement of MAGI3 and PARK2, responsible for cell adhesion and cellular trafficking. Gene Ontology (GO) biological function enrichment analysis across the 8 considered GWAI protocols also suggested that AS could be associated to the Central Nervous System (CNS) malfunctions, specifically, in nerve impulse propagation and in neurotransmitters metabolic processes. [less ▲]

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See detailFramework for the integration of genomics, epigenomics, and transcriptomics in complex diseases
Pineda San Juan, Silvia ULg; Gómez-Rubio, Paulina; Antoni, Picornell et al

in Human Heredity (2015)

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See detailFramework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases.
Pineda, Silvia; Gomez-Rubio, Paulina; Picornell, Antonio et al

in Human Heredity (2015), 79(3-4), 124-36

OBJECTIVES: Different types of '-omics' data are becoming available in the post-genome era; still a single -omics assessment provides limited insights to understand the biological mechanism of complex ... [more ▼]

OBJECTIVES: Different types of '-omics' data are becoming available in the post-genome era; still a single -omics assessment provides limited insights to understand the biological mechanism of complex diseases. Genomics, epigenomics and transcriptomics data provide insight into the molecular dysregulation of neoplastic diseases, among them urothelial bladder cancer (UBC). Here, we propose a detailed analytical framework necessary to achieve an adequate integration of the three sets of -omics data to ultimately identify previously hidden genetic mechanisms in UBC. METHODS: We built a multi-staged framework to study possible pair-wise combinations and integrated the data in three-way relationships. SNP genotypes, CpG methylation levels and gene expression levels were determined for a total of 70 individuals with UBC and with fresh tumour tissue available. RESULTS: We suggest two main hypothesis-based scenarios for gene regulation based on the -omics integration analysis, where DNA methylation affects gene expression and genetic variants co-regulate gene expression and DNA methylation. We identified several three-way trans-association 'hotspots' that are found at the molecular level and that deserve further studies. CONCLUSIONS: The proposed integrative framework allowed us to identify relationships at the whole-genome level providing some new biological insights and highlighting the importance of integrating -omics data. [less ▲]

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See detailShort-term Effect of Infliximab Is Reflected in the Clot Lysis Profile of Patients with Inflammatory Bowel Disease: A Prospective Study.
Bollen, Lize; Vande Casteele, Niels; Peeters, Miet et al

in Inflammatory bowel diseases (2015), 21(3), 570-8

BACKGROUND: Inflammatory bowel disease (IBD) is recognized as an independent risk factor for thrombosis. First, we investigate whether the concentration of fibrinolysis inhibitors is increased in patients ... [more ▼]

BACKGROUND: Inflammatory bowel disease (IBD) is recognized as an independent risk factor for thrombosis. First, we investigate whether the concentration of fibrinolysis inhibitors is increased in patients with IBD. Second, we investigate the effect of infliximab induction therapy on the hemostatic profile. METHODS: This prospective study included 103 patients with IBD starting infliximab therapy and 113 healthy controls. Plasma was collected before the first infliximab infusion (wk 0) and after induction therapy (wk 14). Patients not showing a clinical response on induction were considered as primary nonresponders. Fibrinolysis inhibitors were measured by enzyme-linked immunosorbent assay. Using a clot lysis assay, the area under the curve (global marker for coagulation/fibrinolysis), 50% clot lysis time (marker for fibrinolytic capacity), and amplitude (indicator for clot formation) were determined. RESULTS: Patients with IBD selected for infliximab treatment have higher area under the curve (median 29 [interquartile range, 20-38]) and amplitude (0.4 [0.3-0.5]) compared with healthy controls (18 [13-24] and 0.3 [0.2-0.3], respectively, P < 0.001). Primary nonresponders showed a decrease neither in inflammatory markers nor in hemostatic parameters, whereas in primary responders, a decrease in inflammatory markers was associated with a decrease in both area under the curve (29 [20-38] (wk 0) to 20 [14-28] (wk 14), P < 0.001) and amplitude (0.4 [0.3-0.5] (wk 0) to 0.3 [0.3-0.4] (wk 14), P < 0.001). CONCLUSIONS: This is the first prospective study demonstrating that the clot lysis profile differs between patients with IBD and healthy individuals. On infliximab induction treatment, this clot lysis profile normalizes in responders suggesting that infliximab treatment is advisable for patients with IBD with an activated hemostatic profile. [less ▲]

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See detailGene Regulatory Network Inference via Conditional Inference Trees and Forests
Bessonov, Kyrylo ULg

Poster (2014, August 28)

Trees are classical data structures allowing effectively classifying and predicting responses. Due to versatility and high performance in classification and prediction, there exist plenty of tree-based ... [more ▼]

Trees are classical data structures allowing effectively classifying and predicting responses. Due to versatility and high performance in classification and prediction, there exist plenty of tree-based methods including popular Conditional Inference Tree (CIT) and Forests (CIF), Random Forests (RF), Randomized Trees (RT), randomized C4.5, etc. In this work we assessed the performance of CIT and CIF methods in correct gene regulatory network (GRN) prediction from expression data by using reference golden standard built from real transcriptional regulatory network of E. coli. The synthetic microarray expression data was obtained from DREAM4 challenge. The performance of each network inference method was assessed via Area Under Receiver Operating Characteristic (AUROC) and Area Under Precision Recall (AUPR) metrics. Our preliminary results show that CIT and CIF successfully predict directed GRNs at acceptable performance rates although not optimal (the best AUROC at 0.68 and AUPR at 0.13 for CIF and the best AUROC at 0.58 and AUPR at 0.18 for CIT). Surprisingly by using the current aggregation scheme of feature importance that prefers features with the highest number of observations, a single CIT was a better performer compared to CIFs in all 5 networks. Nevertheless, the CIFs showed an overall 10% improvement in AUROC. A single CIT has 24% and CIFs have 27% lower overall performance compared to the best performer of DREAM4 Challenge based on cumulative areas of PR and ROC curves. We plan to test other feature importance aggregation techniques in a single tree and in tree ensembles in order to outperform the top DREAM4 algorithms. In addition the effects of expression data standardization to unit variance will be presented. In future, the developed CIF framework will be used to perform data integration analysis of multi-omics datasets. [less ▲]

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See detailGenome-Wide Association Interaction Analysis for Alzheimer’s Disease
Gusareva, Elena ULg; Carrasquillo, Minerva M.; Bellenguez, Céline et al

in Neurobiology of Aging (2014)

We propose a minimal protocol for exhaustive genome-wide association interaction analysis that involves screening for epistasis over large-scale genomic data combining strengths of different methods and ... [more ▼]

We propose a minimal protocol for exhaustive genome-wide association interaction analysis that involves screening for epistasis over large-scale genomic data combining strengths of different methods and statistical tools. The different steps of this protocol are illustrated on a real-life data application for Alzheimer's disease (AD) (2259 patients and 6017 controls from France). Particularly, in the exhaustive genome-wide epistasis screening we identified AD-associated interacting SNPs-pair from chromosome 6q11.1 (rs6455128, the KHDRBS2 gene) and 13q12.11 (rs7989332, the CRYL1 gene) (p = 0.006, corrected for multiple testing). A replication analysis in the independent AD cohort from Germany (555 patients and 824 controls) confirmed the discovered epistasis signal (p = 0.036). This signal was also supported by a meta-analysis approach in 5 independent AD cohorts that was applied in the context of epistasis for the first time. Transcriptome analysis revealed negative correlation between expression levels of KHDRBS2 and CRYL1 in both the temporal cortex (β = -0.19, p = 0.0006) and cerebellum (β = -0.23, p < 0.0001) brain regions. This is the first time a replicable epistasis associated with AD was identified using a hypothesis free screening approach. [less ▲]

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See detailOn collaboration and competition in scientific community
Bessonov, Kyrylo ULg

Speech/Talk (2014)

Competition in sciences is increasing today to the levels that it becomes damaging to the scientific progress. In this talk we will talk about benefits of collaboration of healthy competition. Will also ... [more ▼]

Competition in sciences is increasing today to the levels that it becomes damaging to the scientific progress. In this talk we will talk about benefits of collaboration of healthy competition. Will also concentrate on negative aspects of competition and will provide detailed examples illustrating each of the negative points of stiff competition. In addition historical outlook of the scientific community organization and formalization of science will be briefly touched upon in the talk [less ▲]

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See detailGenome-wide association interaction analysis for Alzheimer’s disease.
Gusareva, Elena ULg; Bellenguez, C; Cuyvers, E et al

Poster (2014, January 27)

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See detailSequence Alignment Practical
Bessonov, Kyrylo ULg

Learning material (2013)

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See detailGenome-wide environmental interaction analysis using multidimensional data reduction principles to identify asthma pharmacogenetic loci in relation to corticosteroid therapy
Van Lishout, François ULg; Bessonov, Kyrylo ULg; Duan, Quingling et al

Poster (2013, October 25)

Genome-wide gene-environment (GxE) and gene-gene (GxG) interaction studies share a lot of challenges via the common genetic component they involve. GWEI studies may therefore benefit from the abundance of ... [more ▼]

Genome-wide gene-environment (GxE) and gene-gene (GxG) interaction studies share a lot of challenges via the common genetic component they involve. GWEI studies may therefore benefit from the abundance of methodologies that are available in the context of genome-wide epistasis detection methods. One of these is Model-Based Multifactor Dimensionality Reduction (MB-MDR), which does not make any assumption about the genetic inheritance model. MB-MDR involves reducing a high-dimensional GxE space to GxE factor levels that either exhibit high or low or no evidence for their association to disease outcome. In contrast to logistic regression and random forests, MB-MDR can be used to detect GxE interactions in the absence of any main effects or when sample sizes are too small to be able to model all main and GxE interaction effects. In this ongoing study, we demonstrate the opportunities and challenges of MB-MDR for genome-wide GxE interaction analysis and analyzed the difference in prebronchodilator FEV1 following 8 weeks of inhaled corticosteroid therapy, for 565 pediatric Caucasian CAMP (ages 5-12) from the SHARE project. [less ▲]

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See detailIdentification of asthma-related trans-acting epistatic eQTLs using Model-Based Multifactor Dimensionality Reduction (MB-MDR)
Bessonov, Kyrylo ULg

Poster (2013, October 22)

Epistasis is likely to underlie most complex traits, including gene expression, yet it is very difficult to detect using standard approaches. SNPs located inside a gene coding region or in its vicinity (i ... [more ▼]

Epistasis is likely to underlie most complex traits, including gene expression, yet it is very difficult to detect using standard approaches. SNPs located inside a gene coding region or in its vicinity (i.e. ≤2 Mb from each 5’ and 3’ side) can influence the corresponding gene expression levels. These expression quantitative trait loci (eQTLs) are referred to as cisSNPs. In contrast, eQTLs that are outside the aforementioned gene range can also influence the gene’s expression, in which case, they are called transSNPS to that gene. In this study we considered significant cisSNPs previously identified via generalized least squares (GLS) regression modeling. We then identified those genes transcripts whose expression is regulated by cis/transSNP interaction. In this work we aimed at identifying transcripts whose expression is regulated by a cis/transSNP interactions using Model-Based Multifactor Dimensionality Reduction (MB-MDR) [2]. This model-free approach to detect trans-epistasis involves reducing a high-dimensional GxG space to GxG factor levels that either exhibit high evidence, low evidence or no evidence at all for their association to gene expression levels of interest. Our protocol was applied on real-life data from the childhood asthma management program (CAMP) [1]. It involved coupling a traditional a priori eQTL search to an a posteriori trans-epistasis analysis to identify genetic modifiers to statistically significant cisSNPs. Such an approach allows to reveal previously unreported inter-dependencies that may be important in understanding of biological mechanisms underlying human complex diseases such as asthma. The proposed protocol identified a large number trans-epistasis gene-gene effects of eQTLs. [less ▲]

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See detailGenome-wide association interaction analysis for Alzheimer’s disease.
Gusareva, Elena ULg; Bellenguez, C; Cuyvers, E et al

Speech/Talk (2013)

Identification of epistasis is a challenging task that when successful gives new clues to systems-level genetics where the complexity of underling biology of human disease can be better understood. Though ... [more ▼]

Identification of epistasis is a challenging task that when successful gives new clues to systems-level genetics where the complexity of underling biology of human disease can be better understood. Though many novel methods for detecting epistasis have been proposed and many studies for epistasis detection have been conducted, so far few studies can demonstrate replicable epistasis. In the present work, we propose a minimal protocol for exhaustive genome-wide association interaction (GWAI) analysis that involves screening for epistasis over large-scale genomic data combining strengths of different methods and statistical tools. The different steps of this protocol are illustrated on a real-life data application for Alzheimer’s disease (a large cohort of 2259 patients and 6017 controls from France). Using this protocol, we identified AD-associated interacting SNPs-pair from chromosome 6q11.1 (rs6455128, the KHDRBS2 gene) and 13q12.11 (rs7989332, the CRYL1 gene) and male-specific epistasis between SNPs from chromosome 5q34 (rs729149 and rs3733980, the WWC1 gene) and 15q22.2 (rs9806612, rs9302230 and rs7175766, the TLN2 gene). The transcriptome analysis revealed negative correlation between expression levels of KHDRBS2 and CRYL1 in both the temporal cortex and cerebellum brain regions and positive correlation between the expression levels of CRYL1 and WWC1 in the temporal cortex brain region. A replication analysis strategy and a meta-analysis approach in independent data confirmed effects of some of the discovered interactions. [less ▲]

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See detailReplication of large-scale epistasis studies: an example on ankylosing spondylitis
Bessonov, Kyrylo ULg; Van Steen, Kristel ULg

Poster (2013, September 17)

Ankylosing spondylitis (AS) is a common form of inflammatory arthritis occurring in approximately 5 out of 1,000 adults of European descent. Recently, the Australo-Anglo-American Spondyloarthritis ... [more ▼]

Ankylosing spondylitis (AS) is a common form of inflammatory arthritis occurring in approximately 5 out of 1,000 adults of European descent. Recently, the Australo-Anglo-American Spondyloarthritis Consortium and the WTCCC2 showed that polymorphisms of ERAP1 only affect AS risk in HLA-B27-positive individuals, hereby establishing an interaction between ERAP1 and HLA in the TASC, WTCCC2 and replication datasets [2,5]. We were able to confirm this interaction although using other SNPs. In this study, we use the aforementioned data from WTTCC2 on AS to address unresolved issues when performing large-scale SNP-SNP interaction studies, so as to better guarantee “stable” and “truly replicable” results. These issues are 1) the choice of variable selection method (e.g., of known loci mapping to genes part of know pathways), 2) the choice of SNPs representing a genomic region (e.g., SNPs with modest versus negligible LD between them), 3) the choice of analysis method (e.g., regression-based versus data-reduction (non-parametric) based), 4) different adjustment schemes for lower-order effects (using additive/co-dominant genetic models). We show that even modest changes in 1)-4) may give rise to quite varying epistasis findings for AS, and motivate some “optimal” choices via extensive simulation studies. In this work we rely on a minimal GWAI protocol for genome-wide epistasis detection using SNPs, as developed in our lab [6][9], using the advanced non-parametric Model-Based Multifactor Dimensionality Reduction (MB-MDR) method [1] and an adapted [*] BOolean Operation-based Screening and Testing (BOOST) algorithm [4]. [*] A BOOST [4] like implementation based on the original BOOST algorithm which accounts for missing genotypes [less ▲]

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See detailBioinformatics opportunities in Genomics and Genetics
Bessonov, Kyrylo ULg

Speech/Talk (2013)

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See detailA comparative Genome-Wide Association Interaction study using BOOST and MB-MDR algorithms on Ankylosing Spondylitis
Bessonov, Kyrylo ULg

Poster (2013, April 29)

Genome-Wide Association (GWA) studies have gained popularity after the completion of the Human Genome Project and advancement of high-throughput technologies. These studies aim to scan thousands of ... [more ▼]

Genome-Wide Association (GWA) studies have gained popularity after the completion of the Human Genome Project and advancement of high-throughput technologies. These studies aim to scan thousands of genomic variations (e.g., SNPs) for their association to phenotypic variables (i.e. traits), such as disease related phenotypes, with the hope of extracting biologically and clinically relevant information. Understanding of genetic, environmental as well as other components of the disease brings the key insights into disease pathology and approaches us closer to the ultimate goal - personalized medicine. In this work we rely on a minimal GWAI protocol for genome-wide epistasis detection using SNPs, as developed in our lab [6][9]. Using the advanced non-parametric Model-Based Multifactor Dimensionality Reduction (MB-MDR) method [1] and BOolean Operation-based Screening and Testing (BOOST) algorithms [4][*] for detection of statistically significant epistatic SNP-SNP interactions, we investigate the effect of exhaustive (BOOST) and non-exhaustive (MB-MDR) marker processing strategies, LD effects, as well as different adjustment schemes for lower-order effects (i.e. epistasis). Our approach was tested on Ankylosing Spondylitis (AS) data as provided by the WTCCC2 consortium [1]. AS is a long-term / chronic disease characterized by inflammation of the joints between the spinal bones. Non-steroidal anti-inflammatory drugs calming down the immune system inflammatory responses are used as a treatment but there is no permanent cure for AS. The disease has also a strong environmental component and affects 3.5 - 13 per 1,000 people in USA [5] [less ▲]

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See detailParameterization of the proline analogue Aze (azetidine-2-carboxylic acid) for molecular dynamics simulations and evaluation of its effect on homo-pentapeptide conformations.
Bessonov, Kyrylo ULg; Vassall, Kenrick A.; Harauz, George

in Journal of Molecular Graphics and Modelling (2013), 39

We have parameterized and evaluated the proline homologue Aze (azetidine-2-carboxylic acid) for the gromos56a3 force-field for use in molecular dynamics simulations using GROMACS. Using bi-phasic ... [more ▼]

We have parameterized and evaluated the proline homologue Aze (azetidine-2-carboxylic acid) for the gromos56a3 force-field for use in molecular dynamics simulations using GROMACS. Using bi-phasic cyclohexane/water simulation systems and homo-pentapeptides, we measured the Aze solute interaction potential energies, ability to hydrogen bond with water, and overall compaction, for comparison to Pro, Gly, and Lys. Compared to Pro, Aze has a slightly higher H-bonding potential, and stronger electrostatic but weaker non-electrostatic interactions with water. The 20-ns simulations revealed the preferential positioning of Aze and Pro at the interface of the water and cyclohexane layers, with Aze spending more time in the aqueous layer. We also demonstrated through simulations of the homo-pentapeptides that Aze has a greater propensity than Pro to undergo trans-->cis peptide bond isomerization, which results in a severe 180 degrees bend in the polypeptide chain. The results provide evidence for the hypothesis that the misincorporation of Aze within proline-rich regions of proteins could disrupt the formation of poly-proline type II structures and compromise events such as recognition and binding by SH3-domains. [less ▲]

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