Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/26556
Title: Equations defined using gene expression and histological data resolve coeliac disease biopsies within the Marsh score continuum
Contributor(s): Charlesworth, Richard P G  (author); Agnew, Linda L  (author)orcid ; Scott, David R (author); Andronicos, Nicholas M  (author)orcid 
Publication Date: 2019-01
Early Online Version: 2018-11-03
DOI: 10.1016/j.compbiomed.2018.10.036
Handle Link: https://hdl.handle.net/1959.11/26556
Abstract: Background/Aim: The gold standard diagnostic for coeliac disease (CD) is subjective histological assignment of biopsies into the Marsh score categories. It is hypothesized that discrete Marsh score categories can be quantitatively resolved into a continuum using discriminant equations defined using histological and gene expression data. Therefore, the aim of this study was to use a combination of histological and gene expression data to develop equations that classify CD patient biopsies into a quantitative Marsh score continuum which could be used by clinicians to monitor CD treatment efficacy. Methods: Both empirical and simulated gene expression and histological data were used to define predictive Marsh score equations. The distances of treated sample biopsies from the Marsh score standards were determined using the Mahalanobis distance calculation. Results: Three function, high resolution discriminant equations derived from simulated data were used to accurately classify 99.6% of simulated and empirically derived biopsy data. The first function resolved active (Marsh type 3) CD from mild (Marsh type 1) CD. The second function resolved normal (no specific pathology) biopsies from mild CD. The third function resolved active Marsh score 3 into a and b subcategories. Finally, measuring the Mahalanobis distance enabled the conversion of discrete Marsh score categories into a continuum. Conclusions: This proof-of-concept study successfully demonstrated that the discrete Marsh score scale can be converted into a quantitative continuum capable of high resolution monitoring of patient treatment efficacy using equations defined by gene expression and histology data.
Publication Type: Journal Article
Source of Publication: Computers in Biology and Medicine, v.104, p. 183-196
Publisher: Pergamon Press
Place of Publication: United Kingdom
ISSN: 0010-4825
1879-0534
Field of Research (FOR): 110799 Immunology not elsewhere classified
Socio-Economic Outcome Codes: 860802 Human Diagnostics
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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