Comparative Metabolomics Elucidates Postprandial Metabolic Modifications in Plasma of Obese Individuals with Metabolic Syndrome

Although higher intakes of dairy milk are associated with a lower risk of metabolic syndrome (MetS), the underlying protective mechanism remains unclear. This study investigated the dynamic metabolic profile shift following the ingestion of low-fat milk or an isocaloric volume of rice milk in obese individuals with metabolic syndrome (MetS). In a randomized, double-blind, crossover study, postprandial plasma samples (<i>n</i> = 266) were collected from 19 MetS participants. Plasma samples were analyzed by a targeted metabolomics platform which specifically detects 117 metabolites from 25 metabolic pathways. The comprehensive time-course metabolic profiling in MetS participants indicated that the postprandial metabolic profiles distinguish low-fat milk and rice milk consumption in a time-dependent manner. Metabolic biomarkers, such as orotate, leucine/isoleucine and adenine, showed significantly different trends in the two test beverages. Bayesian statistics identified 12 metabolites associated with clinical characteristics of postprandial vascular endothelial function, such as flow-mediated dilation (FMD), postprandial plasma markers of oxidative stress and NO status. Furthermore, metabolic pathway analysis based on these metabolite data indicated the potential utility of metabolomics to provide mechanistic insights of dietary interventions to regulate postprandial metabolic excursions

Daily nutrient intakes at baseline (habitual diet) and during each dietary phase¹.

<p><i>¹Values are mean ± SD.</i></p><p><i>²Determined from 3-day diet records.</i></p><p>Daily nutrient intakes at baseline (habitual diet) and during each dietary phase^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0113605#nt105" target="_blank">1</a>}.</p

Cumulative change from baseline in (A) body mass and fat mass from dual-energy x-ray absorptiometry, (B) fasting lipoproteins, (C) insulin resistance determined from homeostatic model assessment (HOMA), and (D) blood pressure in 16 subjects who switched to a very low carbohydrate diet and then incrementally increased carbohydrate every 3 wk over six sequential phases (C1→C2→C3→C4→C5→C6).

<p>BL  =  baseline, FL  =  free-living low-carbohydrate diet). Significant differences from Baseline vs C1 were determined by dependent t-test and indicated by an asterisk. Differences from C1 to C6 were determined by repeated measures ANOVA and Fisher's LSD post hoc. Different letters at a time point indicate statistical significance.</p

Baseline subject characteristics¹.

<p><i>¹Values are mean ± SD (range).</i></p><p><i>²Determined by dual-energy X-ray absorptiometry.</i></p><p><i>³HOMA  =  homeostatic model assessment  =  [fasting glucose (mmol/L) x insulin (mU/L)]/22.5.</i></p><p><i>*5 subjects were using anti-hypertensive medications.</i></p><p>Baseline subject characteristics^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0113605#nt101" target="_blank">1</a>}.</p

Plasma fatty acid responses¹.

<p><i>¹Values are mean ± SD from 16. SFA  =  total saturated fatty acids; MUFA  =  total monounsaturated fatty acids.</i></p><p><i>²C1  =  lowest carbohydrate diet and C6  =  highest carbohydrate intake.</i></p><p><i>³3wk run-in diet phase before entering feeding portion of study.</i></p><p><i>⁴Dependent t-test (Baseline vs C1).</i></p><p>Plasma fatty acid responses^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0113605#nt107" target="_blank">1</a>}.</p