TITLE:
Topological Modelling of Deep Ulcerations in Patients with Ulcerative Colitis
AUTHORS:
Ian Morilla, Mathieu Uzzan, Dominique Cazals-Hatem, Hatem Zaag, Eric Ogier-Denis, Gilles Wainrib, Xavier Tréton
KEYWORDS:
Ulcerative Colitis, Deep Ulcers, Fast Random Walk Graph Kernels, Conjugate Gradient Methods, Spectral Graph Theory
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.5 No.11,
November
24,
2017
ABSTRACT: Aims: Steadily the clinicians of our team in inflammatory bowel disease encounter ulcerative colitis patients that develop deep ulcers during their treatment. Currently, these practitioners are only equipped with their grade of expertise in inflammatory domains to decide what new therapy maybe use in such cases. Encouraged by the limited knowledge of this frequent pathology, we seek to determine the molecular conditions underlying the recurrent formation of deep ulcerations in certain group of patients. Method: The goal of this strategy is to expose differences between groups of patients based on similarities computed by random walk graph kernels and performing functional inference on those differences. Results: We apply the methodology to a cohort of eleven miRNA microarrays of ulcerative colitis patients. Our results showed how the group of ulcerative colitis patients with presence of deep ulcers is topologically more similar (0.35) than ulcerative colitis patients (0.18) to control. Such topological constraint drove functional inference to complete the information that clinicians need. Conclusions: Our analyses reveal highly interpretable in the guidance of practitioners to eventually correct initial therapies of ulcerative colitis patients that develop deep ulcers. The methodology can provide them with useful molecular hypotheses necessaries prior to make any decision on the newest course of the treatment.