1Department of Chemistry, Sharif University of Technology, Tehran, Iran
2Department of Chemistry, Tarbiat Modares University, Tehran, Iran
3Department of Electrical Engineer, Payam Nonprofit Higher Education Institution, Golpayegan, Iran
4Department of Basic Science Faculty of Paramedical, Shahid Beheshti University of Medical Sciences, Tehran, Iran
5Gastroenterology Department, Worcestershire Royal Hospital Worcester, UK
6Gastroenterology and Liver Disease Research center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
International Journal of Celiac Disease.
2014,
Vol. 2 No. 2, 44-46
DOI: 10.12691/ijcd-2-2-3
Copyright © 2014 Science and Education PublishingCite this paper: Fariba Fathi, Fatemeh Ektefa, Kaveh Sohrabzadeh, Afsaneh Arefi-Oskouie, Mohsen Tafazzoli, Kamran Rostami, Mohammad-Reza Zali, Mohammad Rostami-Nejad. A Metabonomics Study on Celiac Disease by CART.
International Journal of Celiac Disease. 2014; 2(2):44-46. doi: 10.12691/ijcd-2-2-3.
Correspondence to: Mohammad Rostami-Nejad, Gastroenterology and Liver Disease Research center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Email:
Tafazzoli@sharif.edu, m.rostamii@gmail.comAbstract
Celiac disease (CD) is an immune reaction as a consequence of ingestion of gluten. Diagnosis of CD is not easily using the clinical tests. Then, the discovery of appropriate methods for CD diagnosis is necessary. This study was concentrated to seek the metabolic biomarkers causes of CD compare to healthy subjects.In the present study, we classify CD and healthy subjects using classification and regression tree (CART). To find metabolites in serum which are helpful for the diagnosis of CD, the metabolic profiling was employed using the proton nuclear magnetic resonance spectroscopy (1HNMR). Based on CART results, it was concluded that just using one descriptor, CD and control groups could be classified separately. The 89 % of data in the test set was predicted correctly by the obtained classification model. Our study indicates that quantitative metabolite analysis of serum can be employed to distinguish healthy from CD subjects.
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