Metabolomics Reveals Metabolically Healthy and Unhealthy Obese Individuals Differ in their Response to a Caloric Challenge.

OBJECTIVE: To determine if metabolically healthy obese (MHO) individuals have a different metabolic response to a standardized diet compared to lean healthy (LH) and metabolically unhealthy obese (MUO) individuals. METHODS: Thirty adults (35-70 yrs) were classified as LH, MHO, and MUO according to anthropometric and clinical measurements. Participants consumed a standardized high calorie meal (~1330 kcal). Blood glucose and insulin were measured at fasting, and 15, 30, 60, 90 and 120 min postprandially. Additional blood samples were collected for the targeted analysis of amino acids (AAs) and derivatives, and fatty acids (FAs). RESULTS: The postprandial response (i.e., area under the curve, AUC) for serum glucose and insulin were similar between MHO and LH individuals, and significantly lower than MUO individuals (p < 0.05). Minor differences were found in postprandial responses for AAs between MHO and MUO individuals, while three polyunsaturated FAs (linoleic acid, γ-linolenic acid, arachidonic acid) showed smaller changes in serum after the meal in MHO individuals compared to MUO. Fasting levels for various AAs (notably branched-chain AA) and FAs (e.g., saturated myristic and palmitic acids) were found to correlate with glucose and insulin AUC. CONCLUSION: MHO individuals show preserved insulin sensitivity and a greater ability to adapt to a caloric challenge compared to MUO individuals.

Multiplexed separations for biomarker discovery in metabolomics: Elucidating adaptive responses to exercise training.

High efficiency separations are needed to enhance selectivity, mass spectral quality, and quantitative performance in metabolomic studies. However, low sample throughput and complicated data preprocessing remain major bottlenecks to biomarker discovery. We introduce an accelerated data workflow to identify plasma metabolite signatures of exercise responsiveness when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). This multiplexed separation platform takes advantage of customizable serial injections to enhance sample throughput and data fidelity based on temporally resolved ion signals derived from seven different sample segments analyzed within a single run. MSI-CE-MS was applied to explore the adaptive metabolic responses of a cohort of overweight/obese women (BMI > 25, n = 9) performing a 6-wk high-intensity interval training intervention using a repeated measures/cross-over study design. Venous blood samples were collected from each subject at three time intervals (baseline, postexercise, recovery) in their naïve and trained states while completing standardized cycling trials at the same absolute workload. Complementary statistical methods were used to classify dynamic changes in plasma metabolism associated with strenuous exercise and training status. Positive adaptations to exercise were associated with training-induced upregulation in plasma l-carnitine at rest due to improved muscle oxidative capacity, and greater antioxidant capacity as reflected by lower circulating glutathionyl-l-cysteine mixed disulfide. Attenuation in plasma hypoxanthine and higher O-acetyl-l-carnitine levels postexercise also indicated lower energetic stress for trained women.

Serum and adipose tissue amino acid homeostasis in the metabolically healthy obese.

A subgroup of obese individuals, referred to as metabolically healthy obese (MHO), have preserved insulin sensitivity and a normal lipid profile despite being obese. The molecular basis for this improved cardiometabolic profile remains unclear. Our objective was to integrate metabolite and gene expression profiling to elucidate the molecular distinctions between MHO and metabolically unhealthy obese (MUO) phenotypes. A subset of individuals were selected from the Diabetes Risk Assessment study and classified into three groups using anthropometric and clinical measurements: lean healthy (LH), MHO, and MUO. Serum metabolites were profiled using gas chromatography coupled to mass spectrometry. Multivariate data analysis uncovered metabolites that differed between groups, and these were subsequently validated by capillary electrophoresis coupled to mass spectrometry. Subcutaneous adipose tissue (SAT) gene expression profiling using microarrays was performed in parallel. Amino acids were the most relevant class of metabolites distinguishing MHO from MUO individuals. Serum levels of glutamic acid, valine, and isoleucine were positively associated (i.e., LH < MHO < MUO) with homeostasis model assessment-insulin resistance (HOMA-IR) and glycated hemoglobin (HbA1c) values, while leucine was only correlated with HOMA-IR. The glutamine-to-glutamic acid ratio and glycine were inversely correlated (i.e., LH > MHO > MUO) with HbA1c values. Concomitantly, SAT gene expression profiling revealed that genes related to branched-chain amino acid catabolism and the tricarboxylic acid cycle were less down-regulated in MHO individuals compared to MUO individuals. Together, this integrated analysis revealed that MHO individuals have an intermediate amino acid homeostasis compared to LH and MUO individuals.

Comprehensive plasma thiol redox status determination for metabolomics.

Thiol homeostasis plays an important role in human health and aging by regulation of cellular responses to oxidative stress. Due to major constraints that hamper reliable plasma thiol/disulfide redox status assessment in clinical research, we introduce an improved strategy for comprehensive thiol speciation using capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) that overcomes sensitivity, selectivity and dynamic range constraints of conventional techniques. This method integrates both specific and nonspecific approaches toward sensitivity enhancement for artifact-free quantification of labile plasma thiols without complicated sample handling. A multivariate model was developed to predict increases in ionization efficiency for reduced thiols when conjugated to various maleimide analogs based on their intrinsic physicochemical properties. Optimization of maleimide labeling in conjunction with online sample preconcentration allowed for simultaneous analysis of nanomolar levels of reduced thiols and free oxidized thiols as their intact symmetric or mixed disulfides. Identification of low-abundance thiols and various other polar metabolites detected in plasma was supported by prediction of their relative migration times using CE as a qualitative tool complementary to ESI-MS. Plasma thiol redox status determination together with untargeted metabolite profiling offers a systemic approach for elucidation of the causal role of dysregulated thiol metabolism in the etiology of human diseases.