Diagnostics Of Inflammatory Bowel Diseases Research Articles

ASCA-related antibodies in the blood sera of healthy donors and patients with colorectal cancer: characterization with oligosaccharides related to Saccharomyces cerevisiae mannan.

Mannans are polysaccharide antigens expressed on the cell wall of different fungal species including Saccharomyces cerevisiae and Candida spp. These fungi are components of the normal intestinal microflora, and the presence of antibodies to fungal antigens is known to reflect the features of the patient's immune system. Thus, titers of IgG and IgA antibodies against Saccharomyces cerevisiae mannan (ASCA) are markers for clinical diagnostics of inflammatory bowel diseases. The complex organization and heterogeneity of cell-wall mannans may reduce the quality and reproducibility of ELISA results due to interference by different antigenic epitopes. In this research, we analyzed the levels of IgG antibodies in the sera of healthy donors and patients with colorectal cancer using an array of synthetic oligosaccharides related to distinct fragments of fungal mannan. This study aimed to establish the influence of oligosaccharide structure on their antigenicity. Variations in the structure of the previously established ASCA epitope (changing type of linkage, chain length, and the presence of branches) significantly modified the ability of ligands to bind to circulating antibodies in blood sera. The study showed that surface presentation density of the ligand critically affects the results of enzyme immunoassay. The transition from natural coating antigens to their corresponding synthetic mimetics with a defined structure opens new opportunities for improving existing ELISA test systems, as well as developing diagnostic kits with new properties.

The Role of Radiomics in Fibrosis Crohn's Disease: A Review.

Inflammatory bowel disease (IBD) is a global health concern that has been on the rise in recent years. In addition, imaging is the established method of care for detecting, diagnosing, planning treatment, and monitoring the progression of IBD. While conventional imaging techniques are limited in their ability to provide comprehensive information, cross-sectional imaging plays a crucial role in the clinical management of IBD. However, accurately characterizing, detecting, and monitoring fibrosis in Crohn's disease remains a challenging task for clinicians. Recent advances in artificial intelligence technology, machine learning, computational power, and radiomic emergence have enabled the automated evaluation of medical images to generate prognostic biomarkers and quantitative diagnostics. Radiomics analysis can be achieved via deep learning algorithms or by extracting handcrafted radiomics features. As radiomic features capture pathophysiological and biological data, these quantitative radiomic features have been shown to offer accurate and rapid non-invasive tools for IBD diagnostics, treatment response monitoring, and prognosis. For these reasons, the present review aims to provide a comprehensive review of the emerging radiomics methods in intestinal fibrosis research that are highlighted and discussed in terms of challenges and advantages.

Results and lessons learned from the sbv IMPROVER metagenomics diagnostics for inflammatory bowel disease challenge

A growing body of evidence links gut microbiota changes with inflammatory bowel disease (IBD), raising the potential benefit of exploiting metagenomics data for non-invasive IBD diagnostics. The sbv IMPROVER metagenomics diagnosis for inflammatory bowel disease challenge investigated computational metagenomics methods for discriminating IBD and nonIBD subjects. Participants in this challenge were given independent training and test metagenomics data from IBD and nonIBD subjects, which could be wither either raw read data (sub-challenge 1, SC1) or processed Taxonomy- and Function-based profiles (sub-challenge 2, SC2). A total of 81 anonymized submissions were received between September 2019 and March 2020. Most participants’ predictions performed better than random predictions in classifying IBD versus nonIBD, Ulcerative Colitis (UC) versus nonIBD, and Crohn’s Disease (CD) versus nonIBD. However, discrimination between UC and CD remains challenging, with the classification quality similar to the set of random predictions. We analyzed the class prediction accuracy, the metagenomics features by the teams, and computational methods used. These results will be openly shared with the scientific community to help advance IBD research and illustrate the application of a range of computational methodologies for effective metagenomic classification.

Histopathological assessment of the microscopic activity in inflammatory bowel diseases: What are we looking for?

Advances in diagnostics of inflammatory bowel diseases (IBD) and improved treatment strategies allowed the establishment of new therapeutic endpoints. Currently, it is desirable not only to cease clinical symptoms, but mainly to achieve endoscopic remission, a macroscopic normalization of the bowel mucosa. However, up to one-third of IBD patients in remission exhibit persisting microscopic activity of the disease. The evidence suggests a better predictive value of histology for the development of clinical complications such as clinical relapse, surgical intervention, need for therapy escalation, or development of colorectal cancer. The proper assessment of microscopic inflammatory activity thus became an important part of the overall histopathological evaluation of colonic biopsies and many histopathological scoring indices have been established. Nonetheless, a majority of them have not been validated and no scoring index became a part of the routine bioptic practice. This review summarizes a predictive value of microscopic disease activity assessment for the subsequent clinical course of IBD, describes the most commonly used scoring indices for Crohn's disease and ulcerative colitis, and comments on current limitations and unresolved issues.

Proteomic and lipidomic biomarkers in the diagnosis and progression of inflammatory bowel disease - a review.

There is an increasing prevalence of inflammatory bowel disease (IBD) and to date, no effective treatment has been developed and the exact etiology of this disease remains unknown. Nevertheless, a growing number of proteomic and lipidomic studies have identified certain proteins and lipids which can be used successfully in patients to improve diagnoses and monitoring of treatment. We have focused on the applications of proteins and lipids for IBD diagnostics, including differentiation of Crohn's disease (CD) and ulcerative colitis (UC), treatment monitoring, monitoring of clinical state, likelihood of relapse, and their potential for novel targeted treatments. Analysis of protein and lipid profiles can: improve the availability and use of diagnostic markers; improve understanding of the pathomechanisms of IBD, for example, several studies have implicated platelet dysfunction (PF4), autoimmune responses (granzyme B, perforin), and abnormal metabolism (arachidonic acid pathways); aid in monitoring patient health; and improve therapeutics (experimental phosphatidylcholine therapy has been shown to result in an improvement in intestinal condition). Despite the enormous progress of proteomics and lipidomics in recent years and the development of new technologies, further research is needed to select some of the most sensitive and specific markers applicable in diagnosing and treating IBD.

Natural NADH and FAD Autofluorescence as Label-Free Biomarkers for Discriminating Subtypes and Functional States of Immune Cells.

Immune cell activity is a major factor for disease progression in inflammatory bowel diseases (IBD). Classifying the type and functional state of immune cells is therefore crucial in clinical diagnostics of IBD. Label-free optical technologies exploiting NADH and FAD autofluorescence, such as multiphoton microscopy, have been used to describe tissue morphology in healthy and inflamed colon samples. Nevertheless, a strategy for the identification of single immune cell subtypes within the tissue is yet to be developed. This work aims to initiate an understanding of autofluorescence changes depending on immune cell type and activation state. For this, NADH and FAD autofluorescence signals of different murine immune cell subtypes under native conditions, as well as upon in vitro stimulation and cell death, have been evaluated. Autofluorescence was assessed using flow cytometry and multiphoton microscopy. Our results reveal significantly increased NADH and FAD signals in innate immune cells compared to adaptive immune cells. This allowed identification of relative amounts of neutrophils and CD4+ T cells in mixed cell suspensions, by using NADH signals as a differentiation marker. Furthermore, in vitro stimulation significantly increased NADH and FAD autofluorescence in adaptive immune cells and macrophages. Cell death induced a significant drop in NADH autofluorescence, while FAD signals were hardly affected. Taken together, these results demonstrate the value of autofluorescence as a tool to characterize immune cells in different functional states, paving the way to the label-free clinical classification of IBD in the future.

P240 Clinical diagnostics of fecal calprotectin: a comparative study of a semi-quantitative rapid test and a quantitative lab test

Abstract Background The non-specific and heterogeneous clinical symptoms complicate the diagnosis of Inflammatory bowel disease (IBD). Colonoscopy, the primary method in IBD diagnostics, is costly and invasive, and not optimal for routine disease monitoring. Fast, user-friendly, and cost-effective diagnostic tests facilitate the timely identification of inflammation and disease monitoring. Calprotectin is a pro-inflammatory protein released by neutrophils at the intestinal mucosa, and detectable in feces. Fecal calprotectin (fCal) is a sensitive biomarker that helps to detect IBD, as its concentration is directly proportional to the degree of intestinal inflammation. Furthermore, fCal analysis helps to confirm disease activity in suspected flares and guides decision-making in drug therapy allocation. Methods In this study the accuracy of fCal detection by the semi-quantitative Actim Calprotectin rapid test and the quantitative automated LIAISON Calprotectin assay was assessed on a panel of 119 clinical stool samples. Actim Calprotectin is a visually interpreted, semi-quantitative dipstick test that is hygienically performed in a single tube. LIAISON Calprotectin is an automated quantitative chemiluminescence immunoassay (CLIA). Analyses were performed at NordLab Oulu clinical laboratory (Oulu University Hospital, Finland). Results fCal testing took only about 15 min of hands-on time with Actim Calprotectin, and 40 minutes with LIAISON Calprotectin. The mean fCal concentration in the 119 analyzed clinical samples was 191.8 μg/g (median 41.9 μg/g; range 0-6,290 μg/g) as quantified by LIAISON Calprotectin. The Actim Calprotectin and LIAISON Calprotectin assays agreed on 94 samples (79.0%) (Figure 1). The fCal concentration range-specific inter-assay agreement was as follows: 81.2% at < 50 µg/g, 65.6% at 50–200 µg/g, and 94.4% at >200 µg/g. The sensitivity of Actim Calprotectin was 94.0% (n=47) for the 50 µg/g cut-off when compared to the quantitative LIAISON Calprotectin. The three samples with fCal concentrations above 50 µg/g in the LIAISON Calprotectin test but interpreted as having fCal concentration below 50 µg/g in the Actim Calprotectin test, had an fCal concentration very close to the 50 µg/g cut-off (< 70 µg/g). Conclusion Actim Calprotectin is a suitable method for fCal detection in a clinical setting, supporting fast disease activity and treatment response monitoring in patients with gastrointestinal inflammation. The rapid test can be utilized for the initial differentiation between negative and positive samples in an outpatient setting, thus helping to limit the use of more laborious quantitative methods to positive samples. Future investigations could focus on evaluating the utility of Actim Calprotectin in routine disease monitoring.

Emerging use of artificial intelligence in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a complex, immune-mediated gastrointestinal disorder with ill-defined etiology, multifaceted diagnostic criteria, and unpredictable treatment response. Innovations in IBD diagnostics, including developments in genomic sequencing and molecular analytics, have generated tremendous interest in leveraging these large data platforms into clinically meaningful tools. Artificial intelligence, through machine learning facilitates the interpretation of large arrays of data, and may provide insight to improving IBD outcomes. While potential applications of machine learning models are vast, further research is needed to generate standardized models that can be adapted to target IBD populations.

The value of combined positron emission tomography/magnetic resonance imaging to diagnose inflammatory bowel disease: a prospective study.

The clinical utility of positron emission tomography/magnetic resonance imaging (PET/MRI) in comparison to standard work-up with patients with known or suspected inflammatory bowel disease (IBD) is unknown. To evaluate the value of 18F-fluorodeoxyglucose (18F-FDG) PET/MRI in the diagnostics of IBD and further compare the data obtained using PET/MRI to histological findings. Ten patients with relapse in IBD or with symptoms of suspected IBD were recruited either from a gastroenterology outpatient clinic or from a hospital ward. Intestinal inflammation was assessed with histology and 18F-FDG PET/MRI. Maximum standard uptake values (SUVmax) were calculated in six regions of the intestine (small bowel, ascending, transverse, descending and sigmoid colon, and rectum) and compared to histological analysis of inflammation activity. The study showed that both the inflammation activity (P = 0.008) and the region of the biopsy in the intestine (P = 0.015) had a significant effect on SUV. SUVs obtained from severe inflammation activity emerged significantly from the background (P = 0.006). In addition, the SUVs obtained from moderate inflammation raised from background, but the difference was not statistically significant (P = 0.083), while SUVs of mild inflammation were at the same level with SUVs of normal bowel wall (P = 0.988). 18F-FDG PET/MRI is a promising method of detecting especially severe inflammatory bowel lesions. More data are required to define its sensitivity and specificity.

Evaluation of bacterial biomarkers to aid in challenging inflammatory bowel diseases diagnostics and subtype classification.

BACKGROUNDThe challenges for inflammatory bowel disease (IBD) diagnostics are to discriminate it from gut conditions with similar symptoms such as irritable bowel syndrome (IBS), to distinguish IBD subtypes, to predict disease progression, and to establish the risk to develop colorectal cancer (CRC). Alterations in gut microbiota have been proposed as a source of information to assist in IBD diagnostics. Faecalibacterium prausnitzii (F. prausnitzii), its phylogroups, and Escherichia coli (E. coli) have been reported as potential biomarkers, but their performance in challenging IBD diagnostic situations remains elusive. We hypothesize that bacterial biomarkers based in these species may help to discriminate these conditions of complex diagnostics.AIMTo evaluate the usefulness of indices calculated from the quantification of these species as biomarkers to aid in IBD diagnostics.METHODSA retrospective study of 131 subjects (31 controls (H); 45 Crohn’s disease (CD), 25 ulcerative colitis (UC), 10 IBS, and 20 CRC patients) was performed to assess the usefulness of bacterial biomarkers in biopsies. Further, the performance of biomarkers in faeces was studied in 29 stool samples (19 CD, 10 UC). Relative abundances of total F. prausnitzii (FP), its phylogroups (PHGI and PHGII), and E. coli (E) quantification were determined by qPCR. Loads were combined to calculate the FP-E index, the PHGI–E index and the PHGII-E index. Biomarkers accuracy to discriminate among conditions was measured by the area under the receiver operating characteristic curve (AUC).RESULTSIn biopsies, FP-E index was good for discriminating IBS from CD (AUC = 0.752) while PHGII-E index was suitable for discriminating IBS from UC (AUC = 0.632). The FP-E index would be the choice to discriminate IBD from CRC, especially from all UC subtypes (AUC ≥ 0.875), regardless of the activity status of the patient. Discrimination between UC patients that had the longest disease duration and those with CRC featured slightly lower AUC values. Concerning differentiation in IBD with shared location, PHGI-E index can establish progression from proctitis and left-sided colitis to ulcerative pancolitis (AUC ≥ 0.800). PHG I-E index analysis in tissue would be the choice to discriminate within IBD subtypes of shared location (AUC ≥ 0.712), while in non-invasive faecal samples FP or PHGI could be good indicators (AUC ≥ 0.833).CONCLUSIONF. prausnitzii phylogroups combined with E. coli offer potential to discriminate between IBD and CRC patients and can assist in IBD subtypes classification, which may help in solving IBD diagnostics challenges.

ECHOGRAPHY IN THE DIAGNOSTICS OF INFLAMMATORY BOWEL DISEASES IN CHILDREN

Crohn’s disease (CD) and ulcerative colitis (UC) are pathologies that have various clinical manifestations, which sometimes cause problems in putting a correct diagnosis by clinicians. The review of domestic and foreign literature highlighted the relevance in improving the diagnostics of inflammatory bowel disease (IBD). Modern diagnostic techniques (computed tomography, magnetic resonance imaging, various endoscopic and radiological methods) are widespread in clinical practice, but they have a number of limitations in pediatric practice and are associated with certain risks. Significant drawbacks are radiation loading at the child’s organism and general anesthesia. So, a diagnostic tool which provides sufficient information, widely available, safe and non-invasive is a need . The ultrasound examination meets all the above mentioned demands. Unfortunately, currently there are no explicit protocols to be used for ultrasound examination of children with CD and UC. Researches in this direction should be continued, so as to confirm the effectiveness of this technique in diagnosing the intestinal tube pathology and to develop algorithms for practical application of this imaging technique, particular in pediatric patients with IBD.

Automated Fecal Biomarker Profiling - a Convenient Procedure to Support Diagnosis for Patients with Inflammatory Bowel Diseases

Fecal calprotectin is a valuable non-invasive marker for intestinal inflammation and contributes to the selection of patients with suspected inflammatory bowel disease (IBD) for endoscopy. The aim of this study was to evaluate the performance of three automated immunoassays for fecal calprotectin (FC), fecal lactoferrin (FL) and fecal alpha-1-antitrypsin (A1AT) for diagnosis and follow-up of IBD, to investigate if automated analysis of this biomarker profile may further improve the diagnostic process, and to compare them to manual ELISA tests from different manufacturers. Stool samples from 72 patients with Crohn's disease (42), ulcerative colitis (17), irritable bowel syndrome (5), other gastrointestinal inflammation (8), and 72 healthy controls were analyzed for FC, FL, and A1AT on the automated Alegria® system (ORGENTEC Diagnostika, Germany). The results were verified by commercially available manual ELISA tests and discrepancies were further analyzed by immunoblotting. The fecal test results were correlated with the patients' endoscopic findings and with disease activity. The automated assays FC and FL for Alegria® detected endoscopically active intestinal inflammation with a sensitivity and specificity of 74% and 87% (FC) and 62% and 87% (FL), respectively, and efficiently discriminated IBD from non-IBD samples in the patient cohort. Healthy controls tested negative in all assays. The results of the automated biomarker assays significantly correlated to those of the manual ELISAs. Alegria® results for FC were confirmed by immunoblotting in 7 discrepant samples. Levels of A1AT out of the normal range were detectable in a substantial number of IBD and irritable bowel syndrome (IBS) samples: 50% Crohn's disease, 35% ulcerative colitis, and 60% IBS, reflecting the disease-related changes of intestinal permeability in these patients. In IBD patients, elevated levels of A1AT correlated with relapsing disease. Measurement of FC concentrations with Alegria® is a convenient, promising, and useful tool for improving laboratory diagnostic accuracy and accelerating the diagnostic process and helps to identify those patients in whom endoscopy may be avoided. Automated analysis of a comprehensive profile of fecal biomarkers with Alegria®, including A1AT, provides further substantial benefit for laboratory diagnostics of IBD by improving stratification of patients for treatment and care.

DOP27 Sequencing-based hematopoietic miRNA landscape reveals common and distinct features of autoimmune inflammatory phenotypes

MiRNAs represent a class of small non-coding RNAs which are involved in regulation of protein-coding gene expression. Being implicated in various processes such as development and regulatory circuits of cells, miRNAs also play an important role in the etiology of a variety of diseases. Imbalance of the regulatory processes within immune system development and response may lead to disturbed production of pro-inflammatory cytokines and over-reactivity of the immune cells, thus causing relapsing inflammation, a characteristic feature of inflammatory bowel disease (IBD). Recent studies of colonic miRNAs employed NGS for the distinction between CD, UC and healthy controls, or among different CD subtypes. However, NGS-based profiles of blood-circulating miRNAs have thus far not been investigated in the context of IBD together with other immune-mediated diseases, including ankylosing spondylitis, psoriasis, systemic lupus erythematosus, rheumatoid arthritis and sarcoidosis, as well as non-immune hemolytic-uremic syndrome. Study participants were recruited in Germany and Sweden, where peripheral blood samples (PAXgene) as well as phenotypical and clinical information (such as treatment status, disease activity and location) was collected. Small RNA transcriptomes of 680 individuals (Figure 1) were sequenced using Illumina NGS platform. Small RNA-seq data preprocessing and quantification were performed using cutadapt and miraligner (ref. miRBase v22), respectively. Differential expression analysis (DESeq2) and correlation (Spearman) analysis have been performed to identify disease activity-, trait- and treatment-specific miRNA signatures. These signatures were then utilized in a machine-learning approach to build classification models for IBD diagnostics. The results of multiple pairwise differential expression analyses among different immune-mediated inflammatory conditions and healthy controls revealed inflammation-specific as well and disease-specific deregulation of miRNAs. Correlation analysis identified miRNAs positively and negatively correlated with IBD activity. The preliminary results of machine learning classifiers based on miRNA profiles showed that median Matthews correlation coefficient for all model types showed remarkable predictive performance estimated as being 1.00 (median over main diagnoses), as well as ranging from 0.68 to 0.76 (median over CD location) and from 0.69 to 0.77 (median over UC extent). Immune-mediated inflammatory diseases share common and distinct differentially expressed miRNAs, which have a potential to be used in the diagnostics of IBD, including the evaluation of the disease activity.

P206. Combined positron emission tomography and magnetic resonance imaging in the diagnostics of inflammatory bowel disease: a preliminary report

P206. Combined positron emission tomography and magnetic resonance imaging in the diagnostics of inflammatory bowel disease: a preliminary report

Biomarkers of Inflammatory Bowel Disease: From Classical Laboratory Tools to Personalized Medicine.

Diagnostics of inflammatory bowel diseases (IBDs) currently relies on a combination of biological and morphological tests. The current method of diagnostic remains a critical challenge for physicians in part due to their invasiveness and also for their limitations in term of diagnosis, prognosis, disease activity and severity assessment, and therapeutic outcomes. Laboratory biomarkers can be used in the diagnosis and management of IBD, but none of them has been proven to be ideal. Increasing efforts are being made to discover new biomarkers that can discriminate between the types of IBD, predict future responses to treatment, and aid in differential diagnosis, treatment planning, and prognosis prediction. This review addresses the potential for current biomarkers and the emergence of the concept of biomarker signatures in IBD diagnostic and personalized medicine.

Su1201 Proximity Extension Assay Technology Identifies Novel Serum Biomarkers for Predicting Inflammatory Bowel Disease: IBD Character Consortium

Introduction Advances in protein profiling using proximity extension assays (PEA) have transformed our ability to compare concentrations of multiple proteins across biological samples. PEA utilises the specificity of antibody proximity and the sensitivity of polymerase chain reaction (qPCR) to detect proteins of interest. As part of the EC funded IBD Character initiative to discover biomarkers for clinical use using multiomic technologies, we performed high-throughput prospective case-control serum profiling to identify protein biomarkers that can predict Inflammatory Bowel Disease (IBD). Method Utilising Proseek Multiplex panels (Olink Bioscience, Sweden), serum profiling was performed in patients with a new diagnosis of IBD. Our control group consisted of symptomatic individuals. Phenotypic data was captured including age, sex, diagnosis and IBD medications. Statistical analysis was performed using R. Data were normalised and then batch corrected using ComBAT. Linear models were created for each protein including age and sex as covariates. After quality control, data from 186 proteins was available for analysis. Results A total of 245 patient serum samples (n = 153) newly diagnosed IBD, n = 92 symptomatic controls) from 4 IBD centres from Norway, United Kingdom and Sweden were included in the study from December 2012 to June 2014. 70 had Crohn’s disease (CD), 70 ulcerative colitis (UC) and 13 Inflammatory Bowel Disease Unclassified (IBDU). The mean age of the entire cohort was 33 years (range 0–79 years) and 54% were female. Multivariable analysis identified a set of 48 protein markers that were significantly associated with IBD. The 5 most significant protein markers were MMP-12 (Holm-adjusted p = 3.3 × 10 –13 ), OSM (p = 2.4 × 10 –12 ), CXCL9 (p = 1.7 × 10 –9 ), MMP10 (p = 1.7 × 10 –9 ) and EGFR (p = 1.8 × 10 –9 ). Of these five, all except EGFR were upregulated in IBD. The top 2 markers, MMP-12 and OSM were able to discriminate IBD from controls with an area under the receiver operator characteristics curve of 0.81 and 0.75 respectively. Using linear discriminant analysis, a combined biomarker consisting of MMP-12 and OSM was able to discriminate IBD from controls with a sensitivity and specificity of 80% and 72% respectively. Conclusion We have identified serum biomarkers that can predict IBD. These data demonstrate a potential for a PEA multiplex technology in IBD diagnostics and its ability to identify novel proteins that may be relevant in disease pathogenesis. Disclosure of interest R. Kalla Grant/Research Support from: IBD Character, N. Kennedy Grant/Research Support from: Wellcome Trust, Conflict with: Abbvie, MSD, Warner Chilcott, Ferring speaker fees, F. Hjelm: None Declared, E. Modig: None Declared, M. Sundell: None Declared, J. Soderholm: None Declared, B. Andreassen: None Declared, D. Bergemalm: None Declared, N. Ventham Grant/Research Support from: IBD BIOM, H. Hjortswang: None Declared, R. Petr: None Declared, M. Vatn: None Declared, J. Halfvarson: None Declared, M. Gullberg: None Declared, J. Satsangi Grant/Research Support from: EC Grants, Wellcome, CSO, MRC, Consultant for: Takeda, Conflict with: MSD speaker fees.

Anti-Outer membrane protein C and anti-glycoprotein 2 antibodies in inflammatory bowel disease and their association with complicated forms of Crohn's disease.

BackgroundPrecise diagnostics of inflammatory bowel disease (IBD) and identification of potentially more aggressive phenotypes of Crohn’s disease (CD) is urgently needed. The aim of our prospective study was to assess the relationship between serum anti-OmpC IgA (Outer membrane protein C), anti-GP2 (anti-glycoprotein 2) IgG and anti-GP2 IgA antibodies with IBD and their association with complicated forms of CD.MethodsThe study included 86 patients with CD, 25 patients with UC and 45 controls, blood donors. In CD group, 24/86 (28%) had B1 phenotype, 20/86 (23%) B2, 13/86 (15%) B3 and 29/86 (34%) B2 + B3. L1 involvement was present in 13/86 (15%), L2 in 13/86 (15%), L3 in 60/86 (70%). Serum anti-OmpC IgA, anti-GP2 IgG and IgA antibodies were investigated by means of ELISA. The data obtained were tested statistically by means of descriptive statistics, non-paired t-test, Mann-Whitney rank sum test, Spearman rank order correlation and Pearson product moment correlation using SigmaStat software.ResultsAnti-OmpC IgA were noted to be significantly higher in CD (median 32.6, inter-quartile range (IQR) 18.9-60.7) compared to the controls (median 18.3, IQR 11.1-23.1), p < 0.001. Anti-GP2 IgG were significantly higher in CD (median 13.9, IQR 8.6-25.6) compared to the controls (median 8.0, IQR 4.7-10.8), p < 0.001. Anti-GP2 IgA were significantly higher in CD (median 20.1, IQR 9.1-40.4) compared to the controls (median 9.8, IQR 5.6-16.9), p < 0.001. Significant difference was found in anti-OmpC IgA between UC (median 26.2, IQR 20.2-36.4) and the controls (median 18.3, IQR 11.1-23.1), p < 0.001. In CD anti-OmpC IgA were significantly higher in B2 compared to B1: p = 0.041 and in B2 + B3 compared to B1: p = 0.036. Anti-GP2 IgA were significantly higher in B2 + B3 compared to B1: p = 0.009 and in B3 compared to B1: p = 0.029. In CD there was a significant difference in anti-OmpC IgA between patients with surgery and without surgery, p = 0.005.ConclusionsWe have confirmed association between anti-OmpC IgA and IBD (CD and UC) and an association between anti-GP2 (IgG and IgA) and CD. Patients with complicated forms of CD have significantly higher levels of anti-OmpC IgA and anti-GP2 IgA.

Potential relevance of microRNAs in the diagnostics of inflammatory bowel diseases

Inflammatory bowel diseases are chronic inflammatory disorders characterized by relapses and remissions. Several factors have been suggested to participate in their development, although their detailed pathogenesis still remains largely unknown. MicroRNAs are single strained, non-coding RNAs, consisting of 18-25 nucleotides that regulate gene expression at the posttranscriptional level. Aberrant expression of microRNAs has been found in several malignant tumors. Recently the role of microRNAs in the pathogenesis of inflammatory-autoimmune disorders (such as inflammatory bowel disease) is being intensively investigated. Beside their pathogenic roles, microRNAs can also be exploited as diagnostic markers, especially in cases where the interpretation of histological data is difficult. In this review the authors discuss recent findings in the field of microRNAs in the diagnosis and pathogenesis of inflammatory bowel diseases.

Serum and urine metabolomic fingerprinting in diagnostics of inflammatory bowel diseases

To evaluate the utility of serum and urine metabolomic analysis in diagnosing and monitoring of inflammatory bowel diseases (IBD). Serum and urine samples were collected from 24 patients with ulcerative colitis (UC), 19 patients with the Crohn's disease (CD) and 17 healthy controls. The activity of UC was assessed with the Simple Clinical Colitis Activity Index, while the activity of CD was determined using the Harvey-Bradshaw Index. The analysis of serum and urine samples was performed using proton nuclear magnetic resonance (NMR) spectroscopy. All spectra were exported to Matlab for preprocessing which resulted in two data matrixes for serum and urine. Prior to the chemometric analysis, both data sets were unit variance scaled. The differences in metabolite fingerprints were assessed using partial least-squares-discriminant analysis (PLS-DA). Receiver operating characteristic curves and area under curves were used to evaluate the quality and prediction performance of the obtained PLS-DA models. Metabolites responsible for separation in models were tested using STATISTICA 10 with the Mann-Whitney-Wilcoxon test and the Student's t test (α = 0.05). The comparison between the group of patients with active IBD and the group with IBD in remission provided good PLS-DA models (P value 0.002 for serum and 0.003 for urine). The metabolites that allowed to distinguish these groups were: N-acetylated compounds and phenylalanine (up-regulated in serum), low-density lipoproteins and very low-density lipoproteins (decreased in serum) as well as glycine (increased in urine) and acetoacetate (decreased in urine). The significant differences in metabolomic profiles were also found between the group of patients with active IBD and healthy control subjects providing the PLS-DA models with a very good separation (P value < 0.001 for serum and 0.003 for urine). The metabolites that were found to be the strongest biomarkers included in this case: leucine, isoleucine, 3-hydroxybutyric acid, N-acetylated compounds, acetoacetate, glycine, phenylalanine and lactate (increased in serum), creatine, dimethyl sulfone, histidine, choline and its derivatives (decreased in serum), as well as citrate, hippurate, trigonelline, taurine, succinate and 2-hydroxyisobutyrate (decreased in urine). No clear separation in PLS-DA models was found between CD and UC patients based on the analysis of serum and urine samples, although one metabolite (formate) in univariate statistical analysis was significantly lower in serum of patients with active CD, and two metabolites (alanine and N-acetylated compounds) were significantly higher in serum of patients with CD when comparing jointly patients in the remission and active phase of the diseases. Contrary to the results obtained from the serum samples, the analysis of urine samples allowed to distinguish patients with IBD in remission from healthy control subjects. The metabolites of importance included in this case up-regulated acetoacetate and down-regulated citrate, hippurate, taurine, succinate, glycine, alanine and formate. NMR-based metabolomic fingerprinting of serum and urine has the potential to be a useful tool in distinguishing patients with active IBD from those in remission.

Assessment of the validity of a multigene analysis in the diagnostics of inflammatory bowel disease

The findings of a previous multigene study indicated that the expression of a panel of seven specific genes had strong differential power regarding inflammatory bowel disease (IBD) versus non-IBD, as well as ulcerative colitis (UC) versus Crohn's disease (CD). This prospective confirmatory study based on an independent patient cohort from a national Danish IBD centre was conducted in an attempt to verify these earlier observations. A total of 119 patients were included in the study (CD, UC and controls). Three mucosal biopsies were retrieved from the left side of the colon of each patient. RNA was extracted, and RT-PCR was performed to retain expression profiles from the seven selected genes. Expression data from the training set (18 CD, 20 UC and 20 controls) were used to build a classification model, using quadratic discriminant analysis, and data from the test set (20 CD, 21 UC and 20 controls) were used to test the validity of the model. The present investigation did not confirm the previous observation that a panel of seven specific genes is able to distinguish between patients with CD and UC, whereas the discriminative power for IBD versus control subjects was substantiated. Our results fail to demonstrate that the previously identified seven-gene classification model is able to discriminate between CD and UC but suggest that the gene panel merely discriminates between inflamed and noninflamed colonic tissue. Thus, a reliable and simple diagnostic tool is still warranted for optimal diagnosis and treatment of patients with IBD, especially the subgroup with unclassified disease.