Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Abstract

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra‐fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross‐sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty‐one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty‐eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2‐propenal, 2‐propanol, butane‐ 2,3‐dione and 2‐methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.

Profile of urinary exosomal microRNAs and their contribution to diabetic kidney disease through a predictive classification model

“…19 Furthermore, miR-21-5p and miR-30b-5p have been identified with differential expression in individuals with diabetic kidney disease and poor renal function. 17 On the other hand, another study detected patterns of chemical markers, distinguishing patients with T2DM and clinical healthy people, 28 DKD, 29 and chronic obstructive pulmonary disease. 30 In this regard, our study established a predictive classification model for DKD, in which exomiRs were implemented in conjunction with clinical parameters.…”

Diabetes noninvasive diagnostics and monitoring through volatile biomarkers analysis in the exhaled breath using optical absorption spectroscopy

“…An ultra‐fast gas chromatography system equipped with an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of VMBs in 20 T2DM patients (>126 mg/dL of fasting BG; and >6.5% of HbA1c) and 21 healthy volunteers urine samples [145]. Eighty‐eight VMBs were identified, including hydrocarbon, aldehyde, ketones, alcohols, esters, carboxylic acids, amines, and ethers.…”

Potential for Early Noninvasive COVID-19 Detection Using Electronic-Nose Technologies and Disease-Specific VOC Metabolic Biomarkers

“…Electronic-nose instruments have been developed for numerous healthcare applications ranging from detection of infectious diseases caused by numerous microbial pathogens [ 24 , 25 , 26 ], to prescreening detection of genetic disorders [ 27 , 28 ], and noninfectious diseases (such as asthma and COPD [ 29 , 30 , 31 ], cancer [ 32 , 33 , 34 , 35 ], cardiovascular diseases [ 36 , 37 , 38 ], diabetes [ 39 ], predicting effectiveness of chemotherapy treatments [ 40 ], and mental health [ 41 ] to long-term disease monitoring [ 17 , 42 ]. These devices represent various types of electronic aroma detection (EAD) technologies capable of discriminating between a wide range of complex gas mixtures composed of relatively low-molecular-weight (<300 Daltons) biomarker metabolites, primarily volatile organic compounds (VOCs) derived from a wide diversity of chemical classes [ 43 ].…”