Dexamethasone-Induced Perturbations in Tissue Metabolomics Revealed by Chemical Isotope Labeling LC-MS Analysis

Abstract

Dexamethasone (Dex) is a synthetic glucocorticoid (GC) drug commonly used clinically for the treatment of several inflammatory and immune-mediated diseases. Despite its broad range of indications, the long-term use of Dex is known to be associated with specific abnormalities in several tissues and organs. In this study, the metabolomic effects on five different organs induced by the chronic administration of Dex in the Sprague–Dawley rat model were investigated using the chemical isotope labeling liquid chromatography-mass spectrometry (CIL LC-MS) platform, which targets the amine/phenol submetabolomes. Compared to controls, a prolonged intake of Dex resulted in significant perturbations in the levels of 492, 442, 300, 186, and 105 metabolites in the brain, skeletal muscle, liver, kidney, and heart tissues, respectively. The positively identified metabolites were mapped to diverse molecular pathways in different organs. In the brain, perturbations in protein biosynthesis, amino acid metabolism, and monoamine neurotransmitter synthesis were identified, while in the heart, pyrimidine metabolism and branched amino acid biosynthesis were the most significantly impaired pathways. In the kidney, several amino acid pathways were dysregulated, which reflected impairments in several biological functions, including gluconeogenesis and ureagenesis. Beta-alanine metabolism and uridine homeostasis were profoundly affected in liver tissues, whereas alterations of glutathione, arginine, glutamine, and nitrogen metabolism pointed to the modulation of muscle metabolism and disturbances in energy production and muscle mass in skeletal muscle. The differential expression of multiple dipeptides was most significant in the liver (down-regulated), brain (up-regulation), and kidney tissues, but not in the heart or skeletal muscle tissues. The identification of clinically relevant pathways provides holistic insights into the tissue molecular responses induced by Dex and understanding of the underlying mechanisms associated with their side effects. Our data suggest a potential role for glutathione supplementation and dipeptide modulators as novel therapeutic interventions to mitigate the side effects induced by Dex therapy.

Targeted Metabolomics Analysis on Obstructive Sleep Apnea Patients after Multilevel Sleep Surgery

“…The biomarker and the ratio between the top 20 candidates were selected using the area-under-the-curve (AUC) of the Receiver Operating Characteristic (ROC) analysis, with a sample classification based on PLSDA with a latent number 2 [ 34 , 35 ]. The sample-set was first divided into a test set containing 70% of injections, and a validation set with the remaining 30%.…”

Obesity Connected Metabolic Changes in Type 2 Diabetic Patients Treated With Metformin

“…In order to minimize variations in the total sample amount of individual samples using the step-gradient LC-UV method ( Wu and Li, 2012 ), sample normalization was performed, as described in our recent publication ( Dahabiyeh et al, 2020 ). Each sample was labeled by 12 C-dansyl chloride and mixed in equal mole amount with a 13 C-dansyl chloride pool sample based on the LC-UV analysis quantification results.…”

“…Each sample was labeled by 12 C-dansyl chloride and mixed in equal mole amount with a 13 C-dansyl chloride pool sample based on the LC-UV analysis quantification results. The mixtures (2.5 μL containing 0.86 mmol of labeled metabolites) were analyzed by a Thermo Scientific Dionex Ultimate 3000 UHPLC System (Sunnyvale, CA) linked to a Bruker Maxis II quadrupole time-of-flight (Q-TOF) mass spectrometer (Bruker, Billerica, MA) using the same chromatography system and MS parameters described in our previous publication ( Dahabiyeh et al, 2020 ). The Quality control (QC) sample was prepared by mixing the 12 C- and 13 C-labeled pooled samples in equal mole amount.…”

Distinctive Metabolomics Patterns Associated With Insulin Resistance and Type 2 Diabetes Mellitus

“…The peak area ratios were used for quantitative metabolomics analysis; the same 13 C-labeled pool was spiked into all 12 C-labeled individual samples, and thus the peak ratio values of a labeled metabolite in different samples reflected the concentration differences of this metabolite in these samples. In other words, every 12 C-labeled metabolite from an individual sample had its corresponding 13 C-labeled metabolite in the pooled sample as a reference, resulting in high accuracy for relative quantification ( Jacob et al, 2019a ; Dahabiyeh et al, 2020 ).…”

“…Our goal is to identify potential metabolic biomarkers for IR and T2DM, other than HOMA-IR and HG. CIL is used to modify the chemical and physical properties of metabolites for much-improved separation and enhanced detection sensitivity, thereby increasing the number of detectable metabolites ( Jacob et al, 2019a ; Dahabiyeh et al, 2020 ). Using differential isotope labeling also provides more accurate and precise quantification of metabolite concentration differences in comparative samples (i.e., relative quantification) ( Jacob et al, 2019a ; Dahabiyeh et al, 2020 ).…”