Big data in IBD: big progress for clinical practice

Abstract

<jats:p>IBD is a complex multifactorial inflammatory disease of the gut driven by extrinsic and intrinsic factors, including host genetics, the immune system, environmental factors and the gut microbiome. Technological advancements such as next-generation sequencing, high-throughput omics data generation and molecular networks have catalysed IBD research. The advent of artificial intelligence, in particular, machine learning, and systems biology has opened the avenue for the efficient integration and interpretation of big datasets for discovering clinically translatable knowledge. In this narrative review, we discuss how big data integration and machine learning have been applied to translational IBD research. Approaches such as machine learning may enable patient stratification, prediction of disease progression and therapy responses for fine-tuning treatment options with positive impacts on cost, health and safety. We also outline the challenges and opportunities presented by machine learning and big data in clinical IBD research.</jats:p>

Lymphocyte infiltration and key differentially expressed genes in the ulcerative colitis

“…[ 3 ] Although a large number of studies had demonstrated that it was related to many factors, such as genes, environment, immunity, and infection, its exact etiology had not been clearly elucidated so far. [ 1 ] The histopathology showed that lots of immune cells would infiltrate in the mucosal layer of the intestinal wall, such as neutrophils, macrophages, dendritic cells, and T lymphocytes, etc. [ 6 ] In this study, we used bioinformatics method to find the possible targets for new diagnosis or treatment of UC, and we utilized the CIBERSORT algorithm to obtain the status of lymphocyte infiltration in UC inflamed colon tissues.…”

“…Ulcerative colitis (UC) was a type of inflammatory bowel diseases (IBD). [ 1 ] Its main clinical manifestations were gastrointestinal disorders; such as abdominal pain, diarrhea, tenesmus, bloody diarrhea with mucus, and these were varied in duration and severity. [ 2 ] UC was sometimes difficult to cure, it was easy to relapse, and then the patients could form polyps, even malignant turn into colon cancer.…”

“…Studies had shown that the disease was related to genetic, environmental, immune and infectious factors, etc. [ 1 ] There were approximately 8% to 14% of UC patients had a family history of IBD, and their first-degree relatives had a 4-fold risk of this disease. [ 2 ] The mucosal layer of the intestinal wall of UC patients obviously showed thickened and there were densely infiltrated neutrophils, macrophages, dendritic cells, T lymphocytes, and other immune cells.…”

Human Gut Microbiome-Based Knowledgebase as a Biomarker Screening Tool to Improve the Predicted Probability for Colorectal Cancer

“…Further advances, such as next-generation sequencing, have generated massive amounts of data on the CRC microbiome. Bioinformatics as well as machine learning methods additionally provide powerful tools to advance our understanding (Tabib et al, 2020). Metagenomics and 16S rRNA sequencing studies have revealed different abundance of some microbes between patients and healthy populations and effective combinations of microbial biomarkers could be applied for CRC diagnosis (Sze and Schloss, 2018;Thomas et al, 2019b).…”

Integrated Bioinformatics Analysis Identifies ELAVL1 and APP as Candidate Crucial Genes for Crohn’s Disease

“…Crohn's disease (CD), as a systemic inflammatory disease, mainly influences the gastrointestinal tract with a wide range of contributing factors including host genetics, immune system, environmental exposures, and the gut microbiome [ 1 ]. Although the pathogenesis is complex, the decades of studies have illustrated that CD is caused by environmental factors that broke the mucosal barrier and increased the luminal antigens into the lamina propria [ 2 ].…”