Abstract
Background and aimsThe task of identifying a representative and yet manageable target gene list for assessing the pathogenesis of complicated and multifaceted diseases is challenging. Using Inflammatory Bowel Disease (IBD) as an example, we conceived a bioinformatic approach to identify novel genes associated with the various disease subtypes, in combination with known clinical control genes.MethodsFrom the available literature, we used Acumenta Literature LabTM (LitLab), network analyses, and LitLab Gene Retriever to assemble a gene pool that has a high likelihood of representing immunity-related subtype-specific signatures of IBD.ResultsWe generated six relevant gene lists and 21 intersections that contain genes with unique literature associations to Crohn’s Disease (n = 60), Ulcerative Colitis (n = 17), and unclassified (n = 45) subtypes of IBD. From this gene pool, we then filtered and constructed, using network analysis, a final list of 142 genes that are the most representative of the disease and its subtypes.ConclusionsIn this paper, we present the bioinformatic construction of a gene panel that putatively contains subtype signatures of IBD, a multifactorial disease. These gene signatures will be tested as biomarkers to classify patients with IBD, which has been a clinically challenging task. Such approach to diagnose and monitor complicated disease pathogenesis is a stepping-stone towards personalized care.
Highlights
Background and aimsThe task of identifying a representative and yet manageable target gene list for assessing the pathogenesis of complicated and multifaceted diseases is challenging
Despite the vast amount of transcriptomic data generated in the past decade, specific Inflammatory Bowel Disease (IBD) subtype signatures have not been clearly identified
With the need to reduce the complexity of an ever-growing pool of potential biomarkers, we present here the dissection of the putatively unique and common gene lists for IBD, queried by a combined approach using a wide-scale literature mining, network analysis, and gene ontology tools
Summary
Background and aimsThe task of identifying a representative and yet manageable target gene list for assessing the pathogenesis of complicated and multifaceted diseases is challenging. Using Inflammatory Bowel Disease (IBD) as an example, we conceived a bioinformatic approach to identify novel genes associated with the various disease subtypes, in combination with known clinical control genes. IBD is classified into three major subtypes [3]: Ulcerative Colitis (UC), which primarily affects the colon, Crohn’s Disease (CD), which affects various GIT sites [4], and a third subtype where histology assessments do not categorize to either UC or CD. The latter subtype is defined as “Inflammatory Bowel Disease, type unclassified” (IBDU) [5, 6]. Non-invasive routine laboratory investigations, on the other hand, cannot
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