In-silico analysis of inflammatory bowel disease (IBD) GWAS loci to novel connections

A broken network of susceptibility genes in the monocytes of Crohn's disease patients

Genome-wide association studies have identified over 200 genetic loci associated with inflammatory bowel disease; however, the mechanism of such a large amount of susceptibility genes remains uncertain. In this study, we integrated bioinformatics analysis and two independent single-cell transcriptome datasets to investigate the expression network of 232 susceptibility genes in Crohn's disease (CD) patients and healthy controls. The study revealed that most of the susceptibility genes are specifically and strictly expressed in the monocytes of the human intestinal tract. The susceptibility genes established a network within the monocytes of health control. The robustness of a gene network may prevent disease onset that is influenced by the genetic and environmental alteration in the expression of susceptibility genes. In contrast, we showed a sparse network in pediatric/adult CD patients, suggesting the broken network contributed to the CD etiology. The network status of susceptibility genes at the single-cell level of monocytes provided novel insight into the etiology.

Clinical relevance of genetic variants in the von Willebrand factor according to in-silico methods

Clinical interpretation of genetic variants in the context of the patient's phenotype is a time-consuming and costly process. In-silico analysis using in-silico prediction tools, and molecular modeling have been developed to predict the influence of genetic variants on the quality and/or quantity of the resulting translated protein, and in this way, to alert clinicians of disease likelihood in the absence of previous evidence. Our objectives were to evaluate the success rate of the in-silico analysis in predicting the disease-causing variants as pathogenic and the single-nucleotide variants as neutral, and to establish the reliability of in-silico analysis for determining pathogenicity or neutrality of von Willebrand factor gene-associated genetic variants. Using in-silico analysis, we studied pathogenicity in 31 disease-causing variants, and neutrality in 61 single-nucleotide variants from patients previously diagnosed as type 2 von Willebrand disease. Disease-causing variants and non-synonymous single-nucleotide variants were explored by in-silico tools that analyze the amino acidic sequence. Intronic and synonymous single-nucleotide variants were analyzed by in-silico methods that evaluate the nucleotidic sequence. We found a consistent agreement between predictions achieved by in-silico prediction tools and molecular modeling, both for defining the pathogenicity of disease-causing variants and the neutrality of single-nucleotide variants. Based on our results, the in-silico analysis would help to define the pathogenicity or neutrality in novel genetic variants observed in patients with clinical and laboratory phenotypes suggestive of von Willebrand disease.

Unveiling the Genetic Complexity of Teratozoospermia: Integrated Genomic Analysis Reveals Novel Insights into lncRNAs' Role in Male Infertility

Male infertility is a global health issue, affecting over 20 million men worldwide. Genetic factors are crucial in various male infertility forms, including teratozoospermia. Nonetheless, the genetic causes of male infertility remain largely unexplored. In this study, we employed whole-genome sequencing and RNA expression analysis to detect differentially expressed (DE) long-noncoding RNAs (lncRNAs) in teratozoospermia, along with mutations that are exclusive to teratozoospermic individuals within these DE lncRNAs regions. Bioinformatic tools were used to assess variants' impact on lncRNA structure, function, and lncRNA-miRNA interactions. Our analysis identified 1166 unique mutations in teratozoospermic men within DE lncRNAs, distinguishing them from normozoospermic men. Among these, 64 variants in 23 lncRNAs showed potential regulatory roles, 7 variants affected 4 lncRNA structures, while 37 variants in 17 lncRNAs caused miRNA target loss or gain. Pathway Enrichment and Gene Ontology analyses of the genes targeted by the affected miRNAs revealed dysregulated pathways in teratozoospermia and a link between male infertility and cancer. This study lists novel variants and lncRNAs associated for the first time with teratozoospermia. These findings pave the way for future studies aiming to enhance diagnosis and therapy in the field of male infertility.

Genotype-protein phenotype characterization of NOD2 and IL23R missense variants associated with inflammatory bowel disease: A paradigm from molecular modelling, dynamics, and docking simulations

Inflammatory bowel disease (IBD) is a gastrointestinal disease with an underlying contribution of genetic, microbial, environment, immunity factors. The coding region risk markers identified by IBD genome wide association studies have not been well characterized at protein phenotype level. Therefore, this study is conducted to characterize the role of NOD2 (Arg675Trp and Gly908Arg) and IL23R (Gly149Arg and Arg381Gln) missense variants on the structural and functional features of corresponding proteins. Thus, we used different variant pathogenicity assays, molecular modelling, secondary structure, stability, molecular dynamics, and molecular docking analysis methods. Our findings suggest that SIFT, Polyphen, GREP++, PhyloP, SiPhy and REVEL methods are very sensitive in determining pathogenicity of NOD2 and IL23R missense variants. We have also noticed that all the tested missense variants could potentially alter secondary (α-helices, β-strands, and coils) and tertiary (residue level deviations) structural features. Moreover, our molecular dynamics (MD) simulation findings have simulated that NOD2 (Arg675Trp and Gly908Arg) and IL23R (Gly149Arg and Arg381Gln) variants creates rigid local structures comprising the protein flexibility and conformations. These predictions are corroborated by molecular docking results, where we noticed that NOD2 and IL23R missense variants induce molecular interaction deformities with RIPK2 and JAK2 ligand molecules, respectively. These functional alterations could potentially alter the signal transduction pathway cascade involved in inflammation and autoimmunity. Drug library searches and findings from docking studies have identified the inhibitory effects of Tacrolimus and Celecoxib drugs on NOD2 and IL23R variant forms, underlining their potential to contribute to personalized medicine for IBD. The present study supports the utilization of computational methods as primary filters (pre-in vitro and in vivo) in studying the disease potential mutations in the context of genptype-protein phenotype characteristics.

Molecular docking and dynamics approach to in silico drug repurposing for inflammatory bowels disease by targeting TNF alpha

Inflammatory bowel disease is a chronic disorder of the large intestine with the prevalence of approximately 400 cases in 100000, and it is rising day by day. However, several drugs like sulfasalazine (composed of sulfapyridine and 5-aminosalicylic acid or 5-ASA), corticosteroids, and immunosuppressants manage the disease. But there are no absolute treatments for the pain and inflammation of the disease. TNFα is an important target, and drugs like infliximab and adalimumab have pharmacological potency but with pronounced toxicity. So, we choose this major target TNFα for the virtual screening of US-FDA-approved drugs for its repurposing using the in silico method. The protein TNFα (PDB ID: 2AZ5) with small molecule inhibitor and the US-FDA-approved drug molecules (from Zinc database) were first imported and prepared using Protein Preparation Wizard and LigPrep, respectively, followed by molecular docking, ADMET analysis and prime MMGBSA. After that, the drugs were shortlisted according to dock score, ADMET parameters and MM GBSA dG binding score. After that, the shortlisted drug molecules were subjected to an induced-fit docking analysis. Two of the most promising molecules, ZINC000003830957 (Iopromide) and ZINC000003830635 (Deferoxamine), were chosen for molecular dynamics simulation. Finally, the bioisosteric replacement was used to improve the ADMET properties of these molecules. This research provides an idea for drug exploration and computational tools for drug discovery in treating inflammatory bowel disease.Communicated by Ramaswamy H. Sarma.

Genome-wide prioritization reveals novel gene signatures associated with cardiotoxic effects of tyrosine kinase inhibitors

Tyrosine kinase inhibitors (TKIs) are characterized as multi-targeted anticancer agents that lack specificity, leading to cardiovascular adverse effects. To date, there are no reliable means to predict the cardiotoxicity of TKIs under development. The present study assessed the usual variants of genes to determine the molecular targets of TKIs associated with heart failure (HF). Gene or gene products affected by TKIs were assessed using the Drug Gene Interaction Database. These genes were investigated in genome-wide association studies (GWAS) datasets associated with HF at a genome-wide significant level (P<1×10⁻⁵). Subsequently, single-nucleotide polymorphisms (SNPs) that reached the established GWAS threshold (P<5×10⁻⁸) were investigated for genome-wide significance. Based on a threshold score of 3, nine gene loci yielded associations according to their biological function using RegulomeDB. Finally, comprehensive functional analysis of SNPs was performed using bioinformatics databases to identify potential drug targets. Using rSNPBase, rs7115242, rs143160639 and rs870064 were found to interfere with proximal transcription regulation, while rs7115242, rs143160639 and rs117153772 were involved in distal regulation, and most SNPs participated in post-transcriptional RNA binding protein-mediated regulation. rs191188930 on platelet-derived growth factor receptor (PDGFR) α was associated with numerous TKI drugs, including sunitinib, pazopanib, sorafenib, dasatinib and nilotinib. Using RegulomeDB and HaploReg v4.1, rs191188930 was predicted to be located in enhancer histone markers. PhenoScanner GWAS analysis revealed that rs191188930 was associated with other diseases or phenotypes, in addition to HF. Genotype-Tissue Expression analysis indicated that the PDGFRα gene had the highest median expression in ‘Cells-Transformed fibroblasts’, and the Search Tool for the Retrieval of Interacting Genes/Proteins revealed the protein-protein interaction network of PDGFRα. The present findings demonstrated the overlap of TKI-induced genes and those mediating HF risk, suggesting molecular mechanisms potentially responsible for TKI-induced HF risk. Additionally, the present genetic study may be helpful to further investigate off-target drug effects.

Epigenome-metabolome-microbiome axis in health and IBD

Environmental triggers in the context of genetic susceptibility drive phenotypes of complex immune disorders such as Inflammatory bowel disease (IBD). One such trigger of IBD is perturbations in enteric commensal bacteria, fungi or viruses that shape both immune and neuronal state. The epigenome acts as an interface between microbiota and context-specific gene expression and is thus emerging as a third key contributor to IBD. Here we review evidence that the host epigenome plays a significant role in orchestrating the bidirectional crosstalk between mammals and their commensal microorganisms. We discuss disruption of chromatin regulatory regions and epigenetic enzyme mutants as a causative factor in IBD patients and mouse models of intestinal inflammation and consider the possible translation of this knowledge. Furthermore, we present emerging insights into the intricate connection between the microbiome and epigenetic enzyme activity via host or bacterial metabolites and how these interactions fine-tune the microorganism-host relationship.

pCADD: SNV prioritisation in Sus scrofa

BACKGROUND

In animal breeding, identification of causative genetic variants is of major importance and high economical value. Usually, the number of candidate variants exceeds the number of variants that can be validated. One way of prioritizing probable candidates is by evaluating their potential to have a deleterious effect, e.g. by predicting their consequence. Due to experimental difficulties to evaluate variants that do not cause an amino-acid substitution, other prioritization methods are needed. For human genomes, the prediction of deleterious genomic variants has taken a step forward with the introduction of the combined annotation dependent depletion (CADD) method. In theory, this approach can be applied to any species. Here, we present pCADD (p for pig), a model to score single nucleotide variants (SNVs) in pig genomes.

RESULTS

To evaluate whether pCADD captures sites with biological meaning, we used transcripts from miRNAs and introns, sequences from genes that are specific for a particular tissue, and the different sites of codons, to test how well pCADD scores differentiate between functional and non-functional elements. Furthermore, we conducted an assessment of examples of non-coding and coding SNVs, which are causal for changes in phenotypes. Our results show that pCADD scores discriminate between functional and non-functional sequences and prioritize functional SNVs, and that pCADD is able to score the different positions in a codon relative to their redundancy. Taken together, these results indicate that based on pCADD scores, regions with biological relevance can be identified and distinguished according to their rate of adaptation.

CONCLUSIONS

We present the ability of pCADD to prioritize SNVs in the pig genome with respect to their putative deleteriousness, in accordance to the biological significance of the region in which they are located. We created scores for all possible SNVs, coding and non-coding, for all autosomes and the X chromosome of the pig reference sequence Sscrofa11.1, proposing a toolbox to prioritize variants and evaluate sequences to highlight new sites of interest to explain biological functions that are relevant to animal breeding.

Mucosal Metabolomic Profiling and Pathway Analysis Reveal the Metabolic Signature of Ulcerative Colitis

The onset of ulcerative colitis (UC) is characterized by a dysregulated mucosal immune response triggered by several genetic and environmental factors in the context of host–microbe interaction. This complexity makes UC ideal for metabolomic studies to unravel the disease pathobiology and to improve the patient stratification strategies. This study aims to explore the mucosal metabolomic profile in UC patients, and to define the UC metabolic signature. Treatment- naïve UC patients (n = 18), UC patients in deep remission (n = 10), and healthy volunteers (n = 14) were recruited. Mucosa biopsies were collected during colonoscopies. Metabolomic analysis was performed by combined gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) and ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS). In total, 177 metabolites from 50 metabolic pathways were identified. The most prominent metabolome changes among the study groups were in lysophosphatidylcholine, acyl carnitine, and amino acid profiles. Several pathways were found perturbed according to the integrated pathway analysis. These pathways ranged from amino acid metabolism (such as tryptophan metabolism) to fatty acid metabolism, namely linoleic and butyrate. These metabolic changes during UC reflect the homeostatic disturbance in the gut, and highlight the importance of system biology approaches to identify key drivers of pathogenesis which prerequisite personalized medicine.

REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification

Many in silico predictors of genetic variant pathogenicity have been previously developed, but there is currently no standard application of these algorithms for variant assessment. Using 4,094 ClinVar-curated missense variants in clinically actionable genes, we evaluated the accuracy and yield of benign and deleterious evidence in 5 in silico meta-predictors, as well as agreement of SIFT and PolyPhen2, and report the derived thresholds for the best performing predictor(s). REVEL and BayesDel outperformed all other meta-predictors (CADD, MetaSVM, Eigen), with higher positive predictive value, comparable negative predictive value, higher yield, and greater overall prediction performance. Agreement of SIFT and PolyPhen2 resulted in slightly higher yield but lower overall prediction performance than REVEL or BayesDel. Our results support the use of gene-level rather than generalized thresholds, when gene-level thresholds can be estimated. Our results also support the use of 2-sided thresholds, which allow for uncertainty, rather than a single, binary cut-point for assigning benign and deleterious evidence. The gene-level 2-sided thresholds we derived for REVEL or BayesDel can be used to assess in silico evidence for missense variants in accordance with current classification guidelines.

Differential genetic and functional background in inflammatory bowel disease phenotypes of a Greek population: a systems bioinformatics approach

Background

Crohn’s disease (CD) and Ulcerative colitis (UC) are the two main entities of inflammatory bowel disease (IBD). Previous works have identified more than 200 risk factors (including loci and signaling pathways) in populations of predominantly European ancestry. Our study was conducted on an extended population-specific cohort of 573 Greek IBD patients (364 CD and 209 UC) and 445 controls.

Aims

To highlight the different genetic and functional background of IBD and its phenotypes, utilizing contemporary systems bioinformatics methodologies.

Methods

Disease-associated SNPs, obtained via our own 89 loci IBD risk GWAS panel, were detected with the whole genome association analysis toolset PLINK. These SNPs were used as input for 2 novel and different pathway analysis methods to detect functional interactions. Specifically, PathwayConnector was used to create complementary networks of interacting pathways whereas; the online database of protein interactions STRING provided protein–protein association networks and their derived pathways. Network analyses metrics were employed to identify proteins with high significance and subsequently to rank the signaling pathways those participate in.

Results

The reported complementary pathway and enriched protein–protein association networks reveal several novel and well-known key players, in the functional background of IBD like Toll-like receptor, TNF, Jak-STAT, PI3K-Akt, T cell receptor, Apoptosis, MAPK and B cell receptor signaling pathways. IBD subphenotypes are found to have distinct genetic and functional profiles which can contribute to their accurate identification and classification. As a secondary result we identify an extended network of diseases with common molecular background to IBD.

Conclusions

IBD’s burden on the quality of life of patients and intricate functional background presents us constantly with new challenges. Our data and methodology provide researchers with new insights to a specific population, but also, to possible differentiation markers of disease classification and progression. This work, not only provides new insights into the interplay among IBD risk variants and their related signaling pathways, elucidates the mechanisms underlying IBD and its clinical sequelae, but also, introduces a generalized bioinformatics-based methodology which can be applied to studies of different disorders.

Electronic supplementary material

The online version of this article (10.1186/s13099-019-0312-y) contains supplementary material, which is available to authorized users.

Identification of key regulatory genes connected to NF-κB family of proteins in visceral adipose tissues using gene expression and weighted protein interaction network

Obesity is connected to the activation of chronic inflammatory pathways in both adipocytes and macrophages located in adipose tissues. The nuclear factor (NF)-κB is a central molecule involved in inflammatory pathways linked to the pathology of different complex metabolic disorders. Investigating the gene expression data in the adipose tissue would potentially unravel disease relevant gene interactions. The present study is aimed at creating a signature molecular network and at prioritizing the potential biomarkers interacting with NF-κB family of proteins in obesity using system biology approaches. The dataset GSE88837 associated with obesity was downloaded from Gene Expression Omnibus (GEO) database. Statistical analysis represented the differential expression of a total of 2650 genes in adipose tissues (p = <0.05). Using concepts like correlation, semantic similarity, and theoretical graph parameters we narrowed down genes to a network of 23 genes strongly connected with NF-κB family with higher significance. Functional enrichment analysis revealed 21 of 23 target genes of NF-κB were found to have a critical role in the pathophysiology of obesity. Interestingly, GEM and PPP1R13L were predicted as novel genes which may act as potential target or biomarkers of obesity as they occur with other 21 target genes with known obesity relationship. Our study concludes that NF-κB and prioritized target genes regulate the inflammation in adipose tissues through several molecular signaling pathways like NF-κB, PI3K-Akt, glucocorticoid receptor regulatory network, angiogenesis and cytokine pathways. This integrated system biology approaches can be applied for elucidating functional protein interaction networks of NF-κB protein family in different complex diseases. Our integrative and network-based approach for finding therapeutic targets in genomic data could accelerate the identification of novel drug targets for obesity.

Functional relevance for central cornea thickness-associated genetic variants by using integrative analyses

Background

The genetic architecture underlying central cornea thickness (CCT) is far from understood. Most of the CCT-associated variants are located in the non-coding regions, raising the difficulty of following functional characterizations. Thus, integrative functional analyses on CCT-associated loci might benefit in overcoming these issues by prioritizing the hub genes that are located in the center of CCT genetic network.

Methods

Integrative analyses including functional annotations, enrichment analysis, and protein-protein interaction analyses were performed on all reported CCT GWAS lead SNPs, together with their proxy variants. Functional annotations were conducted by CADD, GWAVA, and Eigen. Enrichment analyses for CCT-associated genes were performed using ToppGene suite. Protein-protein interaction network and gene co-expression analyses were performed by GeneMANIA.

Results

Functional annotations prioritized eight genes (ADAMSTS6, ARID5B, FOXO1, AKAP13, COL4A3, COL8A2, TBL1XR1, and KCMB2) harboring SNPs with strong evidence of regulatory potential. It was also shown that CCT-associated genes were significantly enriched in collagen-related pathways and the phenotype of keratoconus, and some of them were found to be involved in one interaction network.

Conclusion

This study revealed the hub genes that were located in the center of CCT genetic network and provided a new insight into the genetic regulation underlying CCT GWAS findings.

The evidence for fungus in Crohn's disease pathogenesis

Current evidence suggests the etiology of inflammatory bowel diseases (IBD) involves the confluence of host genetic, environmental, and microbial factors that lead to chronic, and often refractory, disease in susceptible individuals. The involvement of microbial triggers in IBD, including Crohn's disease (CD), is increasingly evident with supporting data provided with advancements in metagenomic sequencing that have identified perturbations in microbial structure and function-broadly termed dysbiosis-in CD patients compared with healthy subjects. This concept is supported by the finding germ-free animals with CD genetic susceptibility fail to develop disease; demonstrating microorganisms are necessary but not sufficient for CD. The vast majority of CD microbiome research has focused on the complex bacterial communities and microbiome dysbiosis in the gut with 16S metagenomic sequencing. However, emerging data capturing eukaryotes suggest fungal opportunistic pathogens are also associated with IBD pathogenesis and chronicity. This hypothesis is further supported by historical observations that CD patient populations display elevated antibodies against fungal targets, even evident before disease diagnosis. This review discusses the current findings in the field, followed by historical and metagenomic evidence for fungal pathogens in the development and recurrence of CD in adult and pediatric populations.

Computational Protein Phenotype Characterization of IL10RA Mutations Causative to Early Onset Inflammatory Bowel Disease (IBD)

The deleterious amino acid substitution mutations in IL-10 receptor alpha gene are most frequently reported in several autoimmune diseases including early onset-inflammatory bowel disease (IBD). Despite the important role of IL-10 RA in maintaining immune homeostasis, the specific structural and functional implications of these mutations on protein phenotype, stability, ligand binding and post translational characteristics is not well explored. Therefore, this study performed the multidimensional computational analysis of IL10RA missense variations causative to pediatric or early onset inflammatory bowel disease (<5 years of age). Our computational algorithmic screening identified the deleterious nature of p. W45G, p. Y57C, p. W69G, p.T84I, p.Y91C, p.R101W, p.R117C, and p.R117H, IBD causative IL10-RA mutations. The sensitivity and specificity analysis of different computational methods showed that CADD outperform SIFT, PolyPhen 2.0, FATHMM, LRT, MetaLR, MetaSVM, PROVEAN and Condel in predicting the pathogenicity of IL10RA mutations. Our three-dimensional protein modeling assays showed that the point mutations cause major drifts in the structural plasticity of IL10 RA molecule and negatively influence its stability. Findings from molecular docking analysis have shown that these point mutations decrease the binding affinity of IL10RA toward IL10 and may likely to disturb the IL10 signaling pathway. This study provides an easy frame work for phenotypic characterization of mutant IL10RA molecule in terms of structure, flexibility and stability aspects. Our approach may also add a new dimension to conventional functional biology assays in quickly studying IL10 RA mutations and also for designing and developing inhibitors for mutant IL10RA molecule.

Computational Analysis of Breast Cancer GWAS Loci Identifies the Putative Deleterious Effect of STXBP4 and ZNF404 Gene Variants

The genome-wide association studies (GWAS) have enabled us in identifying different breast cancer (BC) susceptibility loci. However, majority of these are non-coding variants with no annotated biological function. We investigated such 78 noncoding genome wide associated SNPs of BC and further expanded the list to 2,162 variants with strong linkage-disequilibrium (LD, r² ≥0.8). Using multiple publically available algorithms such as CADD, GWAVA, and FATHAMM, we classified all these variants into deleterious, damaging, or benign categories. Out of total 2,241 variants, 23 (1.02%) variants were extreme deleterious (rank 1), 70 (3.12%) variants were deleterious (rank 2), and 1,937 (86.43%) variants were benign (rank 3). The results show 14% of lead or associated variants are under strong negative selection (GERP++ RS ≥2), and ∼22% are under balancing selection (Tajima's D score >2) in CEU population of 1KGP-the regions being positively selected (GERP++ RS <0) in mammalian evolution. The expression quantitative trait loci of highest deleteriously ranked genes were tested on relevant adipose and breast tissues, the results of which were extended for protein expression on breast tissues. From the concordance analysis of ranking system of GWAVA, CADD, and FATHMM, eQTL and protein expression, we identified the deleterious SNPs localized in STXBP4 and ZNF404 genes which might play a role in BC development by dysregulating its gene expression. This simple approach will be easier to implement and to prioritize large scale GWAS data for variety of diseases and link to the potentially unrecognized functional roles of genes. J. Cell. Biochem. 118: 4296-4307, 2017. © 2017 Wiley Periodicals, Inc.

Comprehensive Computational Analysis of GWAS Loci Identifies CCR2 as a Candidate Gene for Celiac Disease Pathogenesis

Celiac disease (CD) is a gluten intolerance disorder with known genetic contribution. The recent fine mapping and genome-wide association studies (GWAS) have identified up to 57 non-HLA CD susceptibility SNPs, majority of which are non-coding variants lacking any functional annotation. Therefore, we adopted multidimensional computational approach for uncovering the plausible mechanisms through which these GWAS SNPs are connected to CD pathogenesis. At initial phase, we identified that 25 (43.85%) out of 57 CD-SNPs lies in evolutionarily constrained genetic element regions. In follow-up phases, through computational (CADD, GWAVA, and FATHMM algorithms) deleterious intensity measurements, we have discovered that 42 (3.94%) out of 1065 variants (57 CD-lead and 1008-linked SNPs; r²  ≥ 0.8) are differentially deleterious in nature to CD. Further functional scrutinization of these CD variants by public domain eQTL mapping, gene expression, knockout mouse model, and pathway analyses revealed that deleterious SNPs of CCR2 gene influences its expression levels and may also elicit a cascade of T-cell-mediated immunological events leading to intestinal gluten intolerance in genetically susceptible individuals. This study demonstrates the utility of integrated in silico analysis of annotations, gene expression, and pathways in prioritizing the potential complex disease variants from large-scale open source genomic data. J. Cell. Biochem. 118: 2193-2207, 2017. © 2017 Wiley Periodicals, Inc.

Inflammatory Bowel Disease: How Effective Is TNF-α Suppression?

Crohn’s Disease (CD) results from inappropriate response toward commensal flora. Earlier studies described CD as a Th1 mediated disease. Current models view both phenotypes as a continuum of various permutations between Th1, Th2 and Th17 pathways compounded by a range of Treg disfunctions. In the present paper, we develop a mathematical model, by a system of differential equations, which describe the dynamic relations among these T cells and their cytokines. The model identities four groups of CD patients according to up/down regulation of Th1 and Th2. The model simulations show that immunosuppression by TNF-α blockage benefits the group with Th1^High/Th2^Low while, by contrast, the group with Th1^Low/Th2^High will benefit from immune activation.

Insights into the pathogenesis of ulcerative colitis from a murine model of stasis-induced dysbiosis, colonic metaplasia, and genetic susceptibility

Gut dysbiosis, host genetics, and environmental triggers are implicated as causative factors in inflammatory bowel disease (IBD), yet mechanistic insights are lacking. Longitudinal analysis of ulcerative colitis (UC) patients following total colectomy with ileal anal anastomosis (IPAA) where >50% develop pouchitis offers a unique setting to examine cause vs. effect. To recapitulate human IPAA, we employed a mouse model of surgically created blind self-filling (SFL) and self-emptying (SEL) ileal loops using wild-type (WT), IL-10 knockout (KO) (IL-10), TLR4 KO (T4), and IL-10/T4 double KO mice. After 5 wk, loop histology, host gene/protein expression, and bacterial 16s rRNA profiles were examined. SFL exhibit fecal stasis due to directional motility oriented toward the loop end, whereas SEL remain empty. In WT mice, SFL, but not SEL, develop pouchlike microbial communities without accompanying active inflammation. However, in genetically susceptible IL-10-deficient mice, SFL, but not SEL, exhibit severe inflammation and mucosal transcriptomes resembling human pouchitis. The inflammation associated with IL-10 required TLR4, as animals lacking both pathways displayed little disease. Furthermore, germ-free IL-10 mice conventionalized with SFL, but not SEL, microbiota populations develop severe colitis. These data support essential roles of stasis-induced, colon-like microbiota, TLR4-mediated colonic metaplasia, and genetic susceptibility in the development of pouchitis and possibly UC. However, these factors by themselves are not sufficient. Similarities between this model and human UC/pouchitis provide opportunities for gaining insights into the mechanistic basis of IBD and for identification of targets for novel preventative and therapeutic interventions.