Abstract
The aim of this study is to look for the proper methods that would be a major step towards untreated CD diagnosis and seek the metabolic biomarkers causes of CD and compare them to control group. Celiac disease (CD) is a common autoimmune disorder that is not easily diagnosed using the clinical tests. Thirty cases and 30 controls were entered into this study. Metabolic profiling was obtained using proton nuclear magnetic resonance spectroscopy ((1)HNMR) to seek metabolites that are helpful for the detection of CD. Classification of CD and healthy subject was done using random forest (RF). The obtained classification model showed an 89% correct classification of CD and healthy subject for the external test set. The metabolites that caused changes in people with CD were identified using RF; these metabolites include lactate, valine and lipid. The findings of the present study reveal serum lactate, valin and lipid levels in CD patient are lower than healthy cohorts. This metabolite may provide diagnostic tools as well as insight into potential targets for disease therapy.
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