Chronic obstructive pulmonary disease (COPD), asthma and cystic fibrosis (CF) are characterized by airway obstruction and an inflammatory process. Reaching early diagnosis and discrimination of subtypes of these respiratory diseases are quite a challenging task than other chronic illnesses. Metabolomics is the study of metabolic pathways and the measurement of unique biochemical molecules generated in a living system. In the last decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. In this article, we review the current state of the metabolomics of COPD, asthma and CF with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and translation into clinic as diagnostic aids for the choice of patient-specific therapies.

The metabolomics of airway diseases, including COPD, asthma and cystic fibrosis.

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.

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Metabolomic analysis of human cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis diseases.

Application of metabolomics in autoimmune diseases: Insight into biomarkers and pathology

Autism spectrum disorders (ASD) make a dishomogeneous group of psychiatric diseases having either genetic and environmental components, including changes of the microbiota. The rate of diagnosis, based on a series of psychological tests and observed behavior, dramatically increased in the past few decades. Currently, no biological markers are available and the pathogenesis is not defined. The purpose of this study was to evaluate the potential use of 1 H-NMR metabolomics to analyze the global biochemical signature of ASD patients (n = 21) and controls (n = 21), these being siblings of autistic patients. A multivariate model has been used to extrapolate the variables of importance. The discriminating urinary metabolites were identified; in particular, significantly increased levels of hippurate, glycine, creatine, tryptophan, and d-threitol and decreased concentrations of glutamate, creatinine, lactate, valine, betaine, and taurine were observed in ASD patients. Based on the identified discriminant metabolites, the attention was focused on two possible mechanisms that could be involved in ASD: oxidative stress conditions and gut microflora modifications. In conclusion, nuclear magnetic resonance-based metabolomics analysis of the urine seems to have the potential for the identification of a metabolic fingerprint of ASD phenotypes and appears to be suitable for further investigation of the disease mechanisms. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1058-1066. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

The urinary 1 H-NMR metabolomics profile of an italian autistic children population and their unaffected siblings.

In contrast to bronchial and nasal lavages, the analysis of exhaled breath condensate (EBC) is a promising, simple, non-invasive, repeatable, and diagnostic method for studying the composition of airway lining fluid with the potential to assess lung inflammation, exacerbations, and disease severity, and to monitor the effectiveness of treatment regimens. Recent investigations have revealed the potential applications of EBC analysis in systemic diseases. In this review, we highlight the analytical studies conducted on non-volatile compounds/biomarkers in EBC. In contrast to other related articles, this review is classified on the basis of analytical techniques and includes almost all the applied methods and their methodological limitations for quantification of non-volatile compounds in EBC samples, providing a guideline for further researches. The studies were identified by searching the SCOPUS database with the keywords “biomarkers,” “non-volatile compounds,” “determination method,” and “EBC.”

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Non-volatile compounds in exhaled breath condensate: review of methodological aspects

Background
Celiac disease (CD) is a disorder associated with body reaction to gluten. After the gluten intake, an immune reaction against the protein occurs and damages villi of small intestine in celiac patients gradually.

Advantage of Applying OSC to 1 H NMR-Based Metabonomic Data of Celiac Disease

Crohn’s disease and celiac disease belong to a group of autoimmune conditions that affect the digestive system, specifically the small intestine. They both attack the digestive tract and share many symptoms. Thus, the discovery of proper methods would be a major step toward differentiating celiac disease from Crohn’s disease. The aim of this study was to search for the metabolic biomarkers to differentiate between these two diseases. Proton nuclear magnetic resonance spectroscopy (1H NMR) was employed as the metabolic profiling method to look for serum metabolites that differentiate between celiac disease and Crohn’s disease. Classification of celiac disease and Crohn’s disease was done using random forest (RF). Based on RF results, Crohn’s disease and celiac disease groups could be classified separately, using just two descriptors. The classification model showed 93 % correct classification of Crohn’s disease and celiac disease subjects for the external test set. Based on feature importance of variables, isoleucine and lactate were selected. The findings of the present study reveal differentiating metabolites for Crohn’s disease and celiac disease. These metabolites may provide diagnostic biomarkers and/or monitoring tools as well as insight into potential targets for prevention and disease therapy.

The Differential Diagnosis of Crohn’s Disease and Celiac Disease Using Nuclear Magnetic Resonance Spectroscopy

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 1 H 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.

Mohamad Rostami Nejad

Papers

Advantage of Applying OSC to 1 H NMR-Based Metabonomic Data of Celiac Disease

The Differential Diagnosis of Crohn’s Disease and Celiac Disease Using Nuclear Magnetic Resonance Spectroscopy

Investigation of metabonomics technique by analyze of NMR data, which method is better? Mean center or auto scale?