Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases

Abstract

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data, from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiologic function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biologic processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology, and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology, to complement traditional means of diagnostic and therapeutic discovery.

Multi-omic Analyses Reveal Complex Interactions Between HCV and Hepatocytes Demonstrating That the Red Queen Is Up and Running

“…This multiomics approach is of particular value for studying multifactorial diseases as HCC, and an evasive and devious pathogen such as HCV. 20,21 This study confirms that the "red queen" is still in the running in the case of HCV and HCV-associated diseases are still a topic of high priority. The answer to the question of who will win will be determined not only by the ability to eradicate the virus by DAAs, but also by the ability to prevent HCV-induced pathogenesis pre-and post-SVR.…”

Limitations of non-invasive tests for assessment of liver fibrosis

“…106 This single nucleotide polymorphism is strongly associated with more hepatic fat deposition and fibrosis, with recent data linking it with a higher risk of liverrelated events and death in patients with NAFLD. 107 Other approaches using plasma DNA methylation, 108 modified singlenucleotide aptamer-based assays, 109 circulating microRNA, 110 and gut microbiome metagenomic profiling, are examples of the wealth of promising data that is generated by technological advances, 111 but also highlight the need for further studies to validate these candidate NASH biomarkers. There will be issues regarding cost, reproducibility, and high-throughput capability.…”

<p>SEPSIS. Educational and Best Practice Frontiers. Beyond the Boundaries of Fatality, Enhancing Clinical Skills and Precision Medicine</p>

“…Conversely, (below in the figure), increased resources dedicated to focused information and dissemination, to big-data management with sustainable technology solutions, and to an appropriate enhancement of educational and work-force profiles, are the opposite factors, leading to favorable solutions of the problem that we wish to analyze and manage by the proposed intervention. the future achievements of bioinformatics or omics techniques, 21,22 as in cancer, 23,24 in liver and digestive disease 25 and in environmental and infection-related disease, 26 but also by point-of-care direct imaging and insight for the prevention of the possible emerging source of dissemination. 27 A realistic perception of disease is the basis for a strong agreement and alliance of doctors and patients against diseases that have many hidden effects.…”