Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

Abstract

Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities, and complications. Here, we report the development and validation of a novel, quantitative method for the determination of a selected panel of 34 metabolite biomarkers from human plasma. We selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings. We validated the method in terms of limits of detection (LOD) and quantitation (LOQ), linearity (R2), and intra- and inter-day repeatability of each metabolite. The method’s performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes, as well as specific bile acids, were associated with macro-albuminuria. Additionally, specific bile acids were associated with glycemic control, anti-hypertensive medication, statin medication, and clinical lipid measurements. The developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic.

Current Status of Metabolomic Biomarker Discovery: Impact of Study Design and Demographic Characteristics

“…Study recruitment must balance demographic characteristics among participants in each cohort and provide sufficient sample size to satisfy requirements for sufficient statistical power at the anticipated false discovery rate. For example, a cohort of 50 type 1 diabetics underwent measurements of amino acids like tyrosine and homocitrulline previously linked to participant demographic characteristics [44]. No age or BMI dependent changes in tyrosine, tryptophan, glutamine, or phenylalanine levels were reported, contradicting prior studies conducted with a larger sample size (Table 1).…”

“…The metabolome is directly linked to perturbations in cell metabolism caused by environmental stimuli as well as disease, thus metabolomics has been successfully used to measure phenotypic outcomes in vitro and in vivo [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][40][41][42][43][44][45][46][47][48][49]. Examples include observations of oncometabolites, such as 2-hyroxybutyrate, sarcosine, choline, succinate, lactate, fumarate, and glucose, associated with tumor growth and metastasis that may also function as biomarkers for leukemia, renal carcinoma, breast, brain, or prostate cancer [26][27][28][29][30][31][32].…”

Dyslipidemia: A Trigger for Coronary Heart Disease in Romanian Patients with Diabetes

“…Other molecules, namely 1,5-anhydroglucitol and β-hydroxypyruvate, have been associated with mechanisms responsible for the control of glucose levels, whereas 1,5-anhydroglucitol, glutamic acid, glutamine, L-aspartic acid, norvaline, symmetric dimethylarginine and tyrosine have emerged as biomarkers which can predict the development of T2DM-related complications [35]. Other studies have also hypothesized that the prevalence of T2DM may be associated with essential and non-essential amino acids.…”

MitofusinsMfn1andMfn2are required to preserve glucose-but not incretin- stimulated beta cell connectivity and insulin secretion

“…diabetes complications and metabolic dysfunction. These molecules were fully quantified using targeted ultra-high-performance liquid-chromatography coupled triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS) as described earlier (Ahonen, Jäntti et al 2019). The second method aimed to measure a broad array of lipid species.…”