Altered Microbiota, Impaired Quality of Life, Malabsorption, Infection, and Inflammation in CVID Patients With Diarrhoea

© Copyright © 2020 van Schewick, Nöltner, Abel, Burns, Workman, Symes, Guzman, Proietti, Bulashevska, Moreira, Soetedjo, Lowe and Grimbacher. Background: Diarrhoea is the commonest gastrointestinal symptom in patients with common variable immunodeficiency (CVID). Objective: The aim of this study was to describe the prevalence and clinical presentation of chronic and recurrent diarrhoea in the Royal-Free-Hospital (RFH) London CVID cohort, including symptoms, infections, level of inflammation, and microbial diversity. Methods: A cross-sectional study of adult CVID patients (139 out of 172 diagnosed with CVID completed the screening questionnaire). Those with diarrhoea ≥6 days/month had stool and blood samples analysed and completed the short Inflammatory Bowel Disease Questionnaire (sIBDQ). BMI, spleen-size, lymphocytes and gut-microbial diversity were compared. Due to logistical and clinical restraints, not all patients could be analysed on all measures. Results: 46/139 (33.1%) patients had current significant diarrhoea. In patients with past or present diarrhoea, BMI was lower (median 23.7 vs. 26, p = 0.005), malabsorption more common (57.97 vs. 35.71%, p = 0.011). CD4+ lymphocytes were higher in patients with diarrhoea (p = 0.028; n = 138), but CD4+ naïve lymphocytes were significantly higher in non-diarrhoea patients (p = 0.009, N = 28). Nine patients had confirmed or probable current gastrointestinal infections. Calprotectin was >60 μg/g in 13/29 with significant diarrhoea including 9 without infection. SIBDQ revealed a low median score of 4.74. Microbial alpha diversity was significantly lower in CVID patients compared to healthy household controls. There was no significant difference in alpha diversity in relation to antibiotic intake during the 6 weeks prior to providing samples. Conclusion: Patients with CVID and significant diarrhoea had infections, raised calprotectin, malabsorption, a lower BMI, an impaired quality of life (comparable to active IBD), and they differed from non-diarrhoea patients in their lymphocyte phenotyping. Furthermore, microbial diversity was altered. These findings strongly imply that there may be an inflammatory nature and a systemic predisposition to diarrhoea in CVID, which necessitates further investigation

Bayesian statistical modelling of human protein interaction network incorporating protein disorder information

<p>Abstract</p> <p>Background</p> <p>We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each node's contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely <it>social</it>, as revealed based on the local <it>sociality </it>parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: <it>a priori </it>knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.</p> <p>Results</p> <p>We applied the statistical modelling to the human protein interaction network obtained with Y2H experiments. Bayesian approach for the estimation of the parameters was employed. We deduced <it>social </it>proteins, essential for the formation of the network, while incorporating into the model information on protein disorder. <it>Intrinsically disordered </it>are proteins which lack a well-defined three-dimensional structure under physiological conditions. We predicted the fold group (ordered or disordered) of proteins in the network from their primary sequences. The network analysis indicated that protein disorder has a positive effect on the connectivity of proteins in the network, but do not fully explains the interactivity.</p> <p>Conclusions</p> <p>The approach opens a perspective to study effects of biological properties of individual entities on the structure of biological networks.</p

Computational Biology and Bioinformatics in Nigeria

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. © 2014 Fatumo et al.SAF was supported by H3ABioNet NABDA Node, Abuja, Nigeria with NIH Common Fund Award/NHGRI Grant Number U41HG006941 and Genetic Epidemiology Group at Wellcome Trust Sanger Institute.Published versio

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes

Motivation: PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program

Targeted Gene Panel Sequencing for Early-onset Inflammatory Bowel Disease and Chronic Diarrhea

Background: In contrast to adult-onset inflammatory bowel disease (IBD), where many genetic loci have been shown to be involved in complex disease etiology, early-onset IBD (eoIBD) and associated syndromes can sometimes present as monogenic conditions. As a result, the clinical phenotype and ideal disease management in these patients often differ from those in adult-onset IBD. However, due to high costs and the complexity of data analysis, high-throughput screening for genetic causes has not yet become a standard part of the diagnostic work-up of eoIBD patients. Methods: We selected 28 genes of interest associated with monogenic IBD and performed targeted panel sequencing in 71 patients diagnosed with eoIBD or early-onset chronic diarrhea to detect causative variants. We compared these results to whole-exome sequencing (WES) data available for 25 of these patients. Results: Target coverage was significantly higher in the targeted gene panel approach compared with WES, whereas the cost of the panel was considerably lower (approximately 25% of WES). Disease-causing variants affecting protein function were identified in 5 patients (7%), located in genes of the IL10 signaling pathway (3), WAS (1), and DKC1 (1). The functional effects of 8 candidate variants in 5 additional patients (7%) are under further investigation. WES did not identify additional causative mutations in 25 patients. Conclusions: Targeted gene panel sequencing is a fast and effective screening method for monogenic causes of eoIBD that should be routinely established in national referral centers.info:eu-repo/semantics/publishedVersio

Influence of Statistical Estimators of Mutual Information and Data Heterogeneity on the Inference of Gene Regulatory Networks

The inference of gene regulatory networks from gene expression data is a difficult problem because the performance of the inference algorithms depends on a multitude of different factors. In this paper we study two of these. First, we investigate the influence of discrete mutual information (MI) estimators on the global and local network inference performance of the C3NET algorithm. More precisely, we study different MI estimators (Empirical, Miller-Madow, Shrink and Schürmann-Grassberger) in combination with discretization methods (equal frequency, equal width and global equal width discretization). We observe the best global and local inference performance of C3NET for the Miller-Madow estimator with an equal width discretization. Second, our numerical analysis can be considered as a systems approach because we simulate gene expression data from an underlying gene regulatory network, instead of making a distributional assumption to sample thereof. We demonstrate that despite the popularity of the latter approach, which is the traditional way of studying MI estimators, this is in fact not supported by simulated and biological expression data because of their heterogeneity. Hence, our study provides guidance for an efficient design of a simulation study in the context of network inference, supporting a systems approach

'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools

<p>Abstract</p> <p>Background</p> <p>Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes.</p> <p>Results</p> <p>In order to develop a method for enhanced prediction of subcellular localization, we integrated the outputs of available localization prediction tools by several strategies, and tested the performance of each strategy with known mitochondrial proteins. The accuracy obtained (up to 92%) surpasses by far the individual tools. The method of integration proved crucial to the performance. For the prediction of mitochondrion-located proteins, integration via a two-layer decision tree clearly outperforms simpler methods, as it allows emphasis of biologically relevant features such as the mitochondrial targeting peptide and transmembrane domains.</p> <p>Conclusion</p> <p>We developed an approach that enhances the prediction accuracy of mitochondrial proteins by uniting the strength of specialized tools. The combination of machine-learning based integration with biological expert knowledge leads to improved performance. This approach also alleviates the conundrum of how to choose between conflicting predictions. Our approach is easy to implement, and applicable to predicting subcellular locations other than mitochondria, as well as other biological features. For a trial of our approach, we provide a webservice for mitochondrial protein prediction (named YimLOC), which can be accessed through the AnaBench suite at http://anabench.bcm.umontreal.ca/anabench/. The source code is provided in the Additional File <supplr sid="S2">2</supplr>.</p> <suppl id="S2"> <title> <p>Additional file 2</p> </title> <text> <p>This file contains scripts for the online server YimLOC. Please note that there scripts only codes for the ready-to-use STACK-mem-DT described in the main text. The scripts do not provide the training process.</p> </text> <file name="1471-2105-8-420-S2.pdf"> <p>Click here for file</p> </file> </suppl

Clinical and Immunological Phenotype of Patients With Primary Immunodeficiency Due to Damaging Mutations in NFKB2

Non-canonical NF-κB-pathway signaling is integral in immunoregulation. Heterozygous mutations in NFKB2 have recently been established as a molecular cause of common variable immunodeficiency (CVID) and DAVID-syndrome, a rare condition combining deficiency of anterior pituitary hormone with CVID. Here, we investigate 15 previously unreported patients with primary immunodeficiency (PID) from eleven unrelated families with heterozygous NFKB2-mutations including eight patients with the common p.Arg853* nonsense mutation and five patients harboring unique novel C-terminal truncating mutations. In addition, we describe the clinical phenotype of two patients with proximal truncating mutations. Cohort analysis extended to all 35 previously published NFKB2-cases revealed occurrence of early-onset PID in 46/50 patients (mean age of onset 5.9 years, median 4.0 years). ACTH-deficiency occurred in 44%. Three mutation carriers have deceased, four developed malignancies. Only two mutation carriers were clinically asymptomatic. In contrast to typical CVID, most patients suffered from early-onset and severe disease manifestations, including clinical signs of T cell dysfunction e.g., chronic-viral or opportunistic infections. In addition, 80% of patients suffered from (predominately T cell mediated) autoimmune (AI) phenomena (alopecia > various lymphocytic organ-infiltration > diarrhea > arthritis > AI-cytopenia). Unlike in other forms of CVID, auto-antibodies or lymphoproliferation were not common hallmarks of disease. Immunophenotyping showed largely normal or even increased quantities of naïve and memory CD4+ or CD8+ T-cells and normal T-cell proliferation. NK-cell number and function were also normal. In contrast, impaired B-cell differentiation and hypogammaglobinemia were consistent features of NFKB2-associated disease. In addition, an array of lymphocyte subpopulations, such as regulatory T cell, Th17-, cTFH-, NKT-, and MAIT-cell numbers were decreased. We conclude that heterozygous damaging mutations in NFKB2 represent a distinct PID entity exceeding the usual clinical spectrum of CVID. Impairment of the non-canonical NF-κB pathways affects function and differentiation of numerous lymphocyte-subpopulations and thus causes a heterogeneous, more severe form of PID phenotype with early-onset. Further characteristic features are multifaceted, primarily T cell-mediated autoimmunity, such as alopecia, lymphocytic organ infiltration, and in addition frequently ACTH-deficiency

Bagging Statistical Network Inference from Large-Scale Gene Expression Data

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository

Characterization of the Clinical and Immunologic Phenotype and Management of 157 Individuals with 56 Distinct Heterozygous NFKB1 Mutations

Background: An increasing number of NFKB1 variants are being identified in patients with heterogeneous immunologic phenotypes. Objective: To characterize the clinical and cellular phenotype as well as the management of patients with heterozygous NFKB1 mutations. Methods: In a worldwide collaborative effort, we evaluated 231 individuals harboring 105 distinct heterozygous NFKB1 variants. To provide evidence for pathogenicity, each variant was assessed in silico; in addition, 32 variants were assessed by functional in vitro testing of nuclear factor of kappa light polypeptide gene enhancer in B cells (NF-κB) signaling. Results: We classified 56 of the 105 distinct NFKB1 variants in 157 individuals from 68 unrelated families as pathogenic. Incomplete clinical penetrance (70%) and age-dependent severity of NFKB1-related phenotypes were observed. The phenotype included hypogammaglobulinemia (88.9%), reduced switched memory B cells (60.3%), and respiratory (83%) and gastrointestinal (28.6%) infections, thus characterizing the disorder as primary immunodeficiency. However, the high frequency of autoimmunity (57.4%), lymphoproliferation (52.4%), noninfectious enteropathy (23.1%), opportunistic infections (15.7%), autoinflammation (29.6%), and malignancy (16.8%) identified NF-κB1-related disease as an inborn error of immunity with immune dysregulation, rather than a mere primary immunodeficiency. Current treatment includes immunoglobulin replacement and immunosuppressive agents. Conclusions: We present a comprehensive clinical overview of the NF-κB1-related phenotype, which includes immunodeficiency, autoimmunity, autoinflammation, and cancer. Because of its multisystem involvement, clinicians from each and every medical discipline need to be made aware of this autosomal-dominant disease. Hematopoietic stem cell transplantation and NF-κB1 pathway-targeted therapeutic strategies should be considered in the future.info:eu-repo/semantics/publishedVersio