ABSTRACT
Metabolome analysis is used to evaluate the characteristics and interactions of low molecular weight metabolites under a specific set of conditions. In cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease [NAFLD] and non-alcoholic steatotic hepatitis [NASH] the liver does not function thoroughly due to long-term damage. Unfortunately the early detection of cirrhosis, HCC, NAFLD and NASH is a clinical problem and determining a sensitive, specific and predictive novel method based on biomarker discovery is an important task. On the other hand, metabolomics has been reported as a new and powerful technology in biomarker discovery and dynamic field that cause global comprehension of system biology. In this review, it has been collected a heterogeneous set of metabolomics published studies to discovery of biomarkers in researches to introduce diagnostic biomarkers for early detection and the choice of patient-specific therapies
ABSTRACT
Metabolomics studies provide useful information about health and disease status. Metabolite based investigations on various cancers is a powerful approach to diagnosis, prognosis and therapy of cancer diseases. Recently by using advanced analytical techniques such as NMR and MS and its hyphenation methods, global metabolic profiling of diseases has been possible. It is predictable that international contributions and software developments in the future will lead to accurate instrumental analysis based on a large number of human samples that finally will improve validation methods and reach this field from the research phase to the clinical phase. In this review, we also discussed the latest developments in analytical methods, application of data analysis, investigation of useful databases and the curent application of metabolomics in cancer diseases that have led to the identification of related biomarkers. In continuation, we listed biomarkers involved in cancer diseases that have been published during recent years
ABSTRACT
The factors such as disease can disrupt homeostasis, resulting in perturbations of endogenous biochemicals that are involved in key metabolic profiles. Metabonomics is useful technique to quantitative description of endogenous metabolites present in a biological sample such as urine, plasma and tissue. High resolution 1H nuclear magnetic resonance [NMR]-based metabonomics is a technique used to analyze and interpret multivariate metabolic data that correlate with changes of physiological conditions. Before any explanation for metabolite data, preprocessing the spectroscopic data is essential. In this paper, we show scaling effects in metabonomics investigation of patients diagnosed with Crohn's and Celiac disease. two techniques of scaling were applied as follows: mean centering and auto scaling. Results reveal that the mean centering is more useful to segregate patients from healthy subjects in the data set of Crohn's and Celiac disease
ABSTRACT
This study evaluated serum levels of zinc in patient with CD compare to healthy subjects. Celiac disease [CD] is characterized by small intestinal malabsorption of nutrients as a consequence of ingestion of wheat gluten. Zinc is an essential trace element that it has vital biological functions. Sera of 30 celiac cases and 30 healthy normal cohorts as control group were obtained. Atomic absorption spectrophotometer was employed for estimating serum zinc level. Zinc concentrations in patients diagnosed with CD were significantly lower than healthy subjects [75.97 +/- 12 compared with 92.83 +/- 18, P-value < 0.0001]. The result of this study shows that serum zinc concentration is decreased in celiac patients compare to healthy controls. Serum zinc may thus be a marker of CD in adults presenting with gastrointestinal symptoms
Subject(s)
Humans , Female , Male , Zinc/blood , Spectrophotometry, AtomicABSTRACT
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 [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