Disease Prognostic Biomarkers in Inflammatory Bowel Diseases-A Reality Check

Precision Medicine in Inflammatory Bowel Disease: A Spotlight on Emerging Molecular Biomarkers

Inflammatory bowel diseases (IBD) remain challenging in terms of understanding their causes and in terms of diagnosing, treating, and monitoring patients. Modern diagnosis combines biomarkers, imaging, and endoscopic methods. Common biomarkers like CRP and fecal calprotectin, while invaluable tools, have limitations and are not entirely specific to IBD. The limitations of existing markers and the invasiveness of endoscopic procedures highlight the need to discover and implement new markers. With an ideal biomarker, we could predict the risk of disease development, as well as the possibility of response to a particular therapy, which would be significant in elucidating the pathogenesis of the disease. Recent research in the fields of machine learning, proteomics, epigenetics, and gut microbiota provides further insight into the pathogenesis of the disease and is also revealing new biomarkers. New markers, such as BAFF, PGE-MUM, oncostatin M, microRNA panels, αvβ6 antibody, and S100A12 from stool, are increasingly being identified, with αvβ6 antibody and oncostatin M being potentially close to being presented into clinical practice. However, the specificity of certain markers still remains problematic. Furthermore, the use of expensive and less accessible technology for detecting new markers, such as microRNAs, represents a limitation for widespread use in clinical practice. Nevertheless, the need for non-invasive, comprehensive markers is becoming increasingly important regarding the complexity of treatment and overall management of IBD.

Keratin 7 expression in different anatomical parts of colonic epithelium in inflammatory bowel diseases and its prognostic value: a 3-year follow-up study

The diagnosis of inflammatory bowel diseases (IBD) may be challenging and their clinical course, characterized by relapses and spontaneous or drug-induced remissions, is difficult to predict. Novel prognostic biomarkers are needed. Keratin 7 (K7) is a cytoskeletal intermediate filament protein which is not normally expressed in the colonic epithelium. It was recently shown that K7 expression in the colonic epithelium is associated with ulcerative colitis and Crohn's disease, the two main subtypes of IBD. Here we investigated IBD associated K7 neo-expression in different regions of colon and terminal ileum. The correlation of the K7 expression with the inflammatory activity of the epithelium was analyzed in each region. The prognostic value of K7 was estimated by comparing the clinical disease activity after 3 years with the K7 expression at the time of enrollment. Our data shows that the level of K7 expression in inflamed epithelium varies depending on the anatomical region and it is the most pronounced in ascending and descending colon, but it did not predict the severity of IBD for the following 3 years. These results warrant future studies focusing on the biological role of K7 in colon and its utilization as potential IBD biomarker.

Current and emerging biomarkers for ulcerative colitis

INTRODUCTION

Ulcerative colitis (UC) is a chronic illness requiring lifelong management that could be enhanced by personalizing care using biomarkers.

AREAS COVERED

The main biomarker discovery modalities are reviewed, highlighting recent results across the spectrum of applications, including diagnostics (serum anti-αvβ6 antibodies achieving an area under the curve [AUC] = 0.99; serum oncostatin M AUC = 0.94), disease activity assessment (fecal calprotectin and serum trefoil factor 3: AUC > 0.90), prognostication of the need for treatment escalation (whole blood transcriptomic panels and CLEC5A/CDH2 ratio: AUC > 0.90), prediction of treatment response, and early identification of patients with subclinical disease. The use of established biomarkers is discussed, along with new evidence regarding autoantibodies, proteins, proteomic panels, transcriptomic signatures, deoxyribonucleic acid methylation patterns, and UC-specific glycomic and metabolic disturbances.

EXPERT OPINION

Novel biomarkers will pave the way for optimized UC care. However, validation, simplification, and direct clinical translation of complex models may prove challenging. Currently, few candidates exist to assess key characteristics, such as UC susceptibility, histological disease activity, drug response, and long-term disease behavior. Further research will likely not only reveal new tools to tackle these issues but also contribute to understanding UC pathogenesis mechanisms.

Spatiotemporal analysis of small bowel capsule endoscopy videos for outcomes prediction in Crohn's disease

Background

Deep learning techniques can accurately detect and grade inflammatory findings on images from capsule endoscopy (CE) in Crohn's disease (CD). However, the predictive utility of deep learning of CE in CD for disease outcomes has not been examined.

Objectives

We aimed to develop a deep learning model that can predict the need for biological therapy based on complete CE videos of newly-diagnosed CD patients.

Design

This was a retrospective cohort study. The study cohort included treatment-naïve CD patients that have performed CE (SB3, Medtronic) within 6 months of diagnosis. Complete small bowel videos were extracted using the RAPID Reader software.

Methods

CE videos were scored using the Lewis score (LS). Clinical, endoscopic, and laboratory data were extracted from electronic medical records. Machine learning analysis was performed using the TimeSformer computer vision algorithm developed to capture spatiotemporal characteristics for video analysis.

Results

The patient cohort included 101 patients. The median duration of follow-up was 902 (354-1626) days. Biological therapy was initiated by 37 (36.6%) out of 101 patients. TimeSformer algorithm achieved training and testing accuracy of 82% and 81%, respectively, with an Area under the ROC Curve (AUC) of 0.86 to predict the need for biological therapy. In comparison, the AUC for LS was 0.70 and for fecal calprotectin 0.74.

Conclusion

Spatiotemporal analysis of complete CE videos of newly-diagnosed CD patients achieved accurate prediction of the need for biological therapy. The accuracy was superior to that of the human reader index or fecal calprotectin. Following future validation studies, this approach will allow for fast and accurate personalization of treatment decisions in CD.

Machine learning-based solution reveals cuproptosis features in inflammatory bowel disease

Background

Cuproptosis, a new cell death mode, is majorly modulated by mitochondrial metabolism and protein lipoylation. Nonetheless, cuproptosis-related genes (CRGs) have not yet been thoroughly studied for their clinical significance and relationship with the immune microenvironment in inflammatory bowel disease (IBD).

Methods

We screened CRGs that had a significant correlation with immune status, which was determined utilizing single-sample GSEA (ssGSEA) and Gene Expression Omnibus datasets (GSE75214). Furthermore, utilizing the R package "CensusClusterPlus", these CRGs' expression was used to obtain different patient clusters. Subsequently, gene-set enrichment analysis (GSEA), gene set variation analysis (GSVA), and CIBERSORT assessed the variations in the enrichment of gene function and the abundance of immune cell infiltration and immune functions across these clusters. Additionally, weighted gene co-expression network analysis (WGCNA) and analysis of differentially expressed genes (DEGs) were executed, and for the purpose of identifying hub genes between these clusters, the construction of protein-protein interaction (PPI) network was done. Lastly, we used the GSE36807 and GSE10616 datasets as external validation cohorts to validate the immune profiles linked to the expression of CRG. ScRNA-seq profiling was then carried out using the publicly available dataset to examine the CRGs expression in various cell clusters and under various conditions.

Results

Three CRGs, PDHA1, DLD, and FDX1, had a significant association with different immune profiles in IBD. Patients were subsequently classified into two clusters: low expression levels of DLD and PDHA1, and high expression levels of FDX1 were observed in Cluster 1 compared to Cluster 2. According to GSEA, Cluster 2 had a close association with the RNA processes and protein synthesis whereas Cluster 1 was substantially linked to environmental stress response and metabolism regulations. Furthermore, Cluster 2 had more immune cell types, which were characterized by abundant memory B cells, CD4+ T memory activated cells, and follicular helper T cells, and higher levels of immune-related molecules (CD44, CD276,CTLA4 and ICOS) than Cluster 1. During the analysis, the PPI network was divided into three significant MCODEs using the Molecular Complex Detection (MCODE) algorithm. The three MCODEs containing four genes respectively were linked to mitochondrial metabolism, cell development, ion and amino acid transport. Finally, external validation cohorts validated these findings, and scRNA-seq profiling demonstrated diverse intestinal cellular compositions with a wide variation in CRGs expression in the gut of IBD patients.

Conclusions

Cuproptosis has been implicated in IBD, with PDHA1, DLD, and FDX1 having the potential as immune biomarkers and therapeutic targets. These results offer a better understanding of the development of precise, dependable, and cutting-edge diagnosis and treatment of IBD.

Pediatric Inflammatory Bowel Disease

Inflammatory bowel diseases (IBDs) are chronic, immune-mediated disorders that include Crohn's disease and ulcerative colitis. A pediatric onset of disease occurs in about 10% of all cases. Clinical presentation of IBD with rectal bleeding or perianal disease warrants direct referral for endoscopic evaluation. In the absence of red-flag symptoms, a combination of patient history and blood and fecal biomarkers can help to distinguish suspected IBD from other causes of abdominal pain or diarrhea. The therapeutic management of pediatric IBD has evolved by taking into account predictors of poor outcome, which justifies the upfront use of anti-tumor necrosis factor therapy for patients at high risk for complicated disease. In treating patients with IBD, biochemical or endoscopic remission, rather than clinical remission, is the therapeutic goal because intestinal inflammation often persists despite resolution of abdominal symptoms. Pediatric IBD comes with unique additional challenges, such as growth impairment, pubertal delay, the psychology of adolescence, and development of body image. Even after remission has been achieved, many patients with IBD continue to experience nonspecific symptoms like abdominal pain and fatigue. Transfer to adult care is a well-recognized risk for disease relapse, which highlights patient vulnerability and the need for a transition program that is continued by the adult-oriented IBD team. The general pediatrician is an invaluable link in integrating these challenges in the clinical care of patients with IBD and optimizing their outcomes. This state-of-the-art review aims to provide general pediatricians with an update on pediatric IBD to facilitate interactions with pediatric gastrointestinal specialists.

Colonocyte keratin 7 is expressed de novo in inflammatory bowel diseases and associated with pathological changes and drug-resistance

The clinical course of IBD, characterized by relapses and remissions, is difficult to predict. Initial diagnosis can be challenging, and novel disease markers are needed. Keratin 7 (K7) is a cytoskeletal intermediate filament protein not expressed in the colonic epithelium but has been reported in IBD-associated colorectal tumors. Our aim was to analyze whether K7 is expressed in chronic colonic inflammatory diseases and evaluate its potential as a novel biomarker. K7 was analyzed in two patient cohorts using immunohistochemistry-stained colon samples and single-cell quantitative digital pathology methods. K7 was correlated to pathological changes and clinical patient characteristics. Our data shows that K7 is expressed de novo in the colonic epithelium of ulcerative colitis and Crohn's disease IBD patients, but not in collagenous or lymphocytic colitis. K7 mRNA expression was significantly increased in colons of IBD patients compared to controls when assessed in publicly available datasets. While K7 increased in areas with inflammatory activity, it was not expressed in specific crypt compartments and did not correlate with neutrophils or stool calprotectin. K7 was increased in areas proximal to pathological alterations and was most pronounced in drug-resistant ulcerative colitis. In conclusion, colonic epithelial K7 is neo-expressed selectively in IBD patients and could be investigated for its potential as a disease biomarker.

Epigenetics in IBD: a conceptual framework for disease pathogenesis

The global incidence and prevalence of paediatric inflammatory bowel disease (IBD) is increasing, with a notable emergence in developing countries with historically low rates. This suggests that environmental and epigenetic factors may play an important role in the pathogenesis and progression of IBD. Epigenetics refers to the study of biological mechanisms that result in a change of phenotype, without an change in the underlying DNA sequence. Epigenetic mechanisms drive many biological processes that occur in health, such as development and ageing, and are also implicated in disease, including cancer and other inflammatory diseases. Importantly, identification of cell-type-specific epigenetic mechanisms could lead to the identification of molecular disease subtypes allowing a personalised treatment approach. In this short review, we provide a summary of epigenetic mechanisms operative in mammals, and their potential involvement in IBD pathogenesis. Furthermore, we discuss key challenges associated with investigating epigenetics in IBD and provide potential strategies to overcome these, such as through the use of 'omics' and organoid technologies.