NMR-Based Metabolomic Approach Tracks Potential Serum Biomarkers of Disease Progression in Patients with Type 2 Diabetes Mellitus

Abstract

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia associated with alterations in carbohydrate, lipid, and protein metabolism. The prognosis of T2DM patients is highly dependent on the development of complications, and therefore the identification of biomarkers of T2DM progression, with minimally invasive techniques, is a huge need. In the present study, we applied a 1H-Nuclear Magnetic Resonance (1H-NMR)-based metabolomic approach coupled with multivariate data analysis to identify serum metabolite profiles associated with T2DM development and progression. To perform this, we compared the serum metabolome of non-diabetic subjects, treatment-naïve non-complicated T2DM patients, and T2DM patients with complications in insulin monotherapy. Our analysis revealed a significant reduction of alanine, glutamine, glutamate, leucine, lysine, methionine, tyrosine, and phenylalanine in T2DM patients with respect to non-diabetic subjects. Moreover, isoleucine, leucine, lysine, tyrosine, and valine levels distinguished complicated patients from patients without complications. Overall, the metabolic pathway analysis suggested that branched-chain amino acid (BCAA) metabolism is significantly compromised in T2DM patients with complications, while perturbation in the metabolism of gluconeogenic amino acids other than BCAAs characterizes both early and advanced T2DM stages. In conclusion, we identified a metabolic serum signature associated with T2DM stages. These data could be integrated with clinical characteristics to build a composite T2DM/complications risk score to be validated in a prospective cohort.

Brain-Region Specific Metabolic Abnormalities in Parkinson’s Disease and Levodopa-Induced Dyskinesia

“…Metabolic abnormality has long been considered to be involved in a lot of diseases, such as neurodegenerative diseases including PD (Shao and Le, 2019) and Alzheimer' disease (Van Bulck et al, 2019), diabetes mellitus (Del Coco et al, 2019), chronic obstructive pulmonary disease (Lamonaca et al, 2017). 1 H-NMR based metabolomics has proven to be a key for the characterization of metabolic profiles relevant to brain function and disease (Ivanisevic and Siuzdak, 2015).…”

Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers

“…The main purposes supporting these contributions are to broaden the understanding on the metabolic environment of individuals in these different conditions, as well as potential molecular targets that link them all (Newgard, 2017). Studies have already shown the relationship between cardiometabolic diseases, obesity and diabetes with disturbances in the amino acid pathways such as aromatics and branched-chain amino acids (BCAA) (Newgard, 2017;Rauschert et al, 2017;Zhong et al, 2017;Libert et al, 2018;Del Coco et al, 2019).…”

1H-NMR Based Serum Metabolomics Highlights Different Specific Biomarkers between Early and Advanced Hepatocellular Carcinoma Stages

“…Representative proton Carr-Purcell-Meiboom-Gill nuclear magnetic resonance ( 1 H CPMG NMR) spectra obtained from serum patients in the EAR and ADV HCC stages are shown in Figure 1. 2D NMR (J-resolved, homonuclear correlation spectroscopy (COSY), heteronuclear single-quantum correlation spectroscopy (HSQC), and heteronuclear multiple bond correlation spectroscopy (HMBC)) experiments were used to accurately assign the resonances of the identified metabolites, according to literature data and public databases [8][9][10][11]. The 1 H-NMR spectra were dominated by high-intensity signals ascribable to the sugar moieties of α and β-glucose, lactate and some high molecular weight metabolites, such as lipoproteins (VLDL/LDL).…”

“…Serum samples (200 µL) were processed according to standard procedures for NMR metabolomics measurement [8,9,54]. Briefly, prior to NMR analysis, sera were thawed at room temperature, and an aliquot of 200 µL was added of 400 µL of saline buffer solution (NaCl 0.9%, 50 mM sodium phosphate buffer in D 2 O containing TSP 0.05% wt for chemical shift calibration, pH 7.4) to minimize the variation in pH and transferred in a 5 mm NMR tube [54][55][56].…”

“…In the last few years, metabolite quantification by Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy approaches have been used to obtain a global, unbiased view of small molecules in biofluids and organs, thus contributing to the understanding of the molecular characteristics of many diseases. Moreover, these approaches were also used to define a series of biomarkers for early diagnoses and treatments of different diseases [6][7][8][9]. In this study, the serum of 64 HCC patients diagnosed in early (28 patients) and advanced (36 patients) disease stages was collected and profiled by the 1 H-Nuclear Magnetic Resonance ( 1 H-NMR)-based metabolomics approach coupled with multivariate data analysis.…”