A Preliminary Study Showing the Impact of Genetic and Dietary Factors on GC–MS-Based Plasma Metabolome of Patients with and without PROX1-Genetic Predisposition to T2DM up to 5 Years Prior to Prediabetes Appearance

Risk factors for type 2 diabetes mellitus (T2DM) consist of a combination of an unhealthy, imbalanced diet and genetic factors that may interact with each other. Single nucleotide polymorphism (SNP) in the prospero homeobox 1 (PROX1) gene is a strong genetic susceptibility factor for this metabolic disorder and impaired β-cell function. As the role of this gene in T2DM development remains unclear, novel approaches are needed to advance the understanding of the mechanisms of T2DM development. Therefore, in this study, for the first time, postprandial changes in plasma metabolites were analysed by GC–MS in nondiabetic men with different PROX1 genotypes up to 5 years prior to prediabetes appearance. Eighteen contestants (12 with high risk (HR) and 6 with low risk (LR) genotype) participated in high-carbohydrate (HC) and normo-carbohydrate (NC) meal-challenge tests. Our study concluded that both meal-challenge tests provoked changes in 15 plasma metabolites (amino acids, carbohydrates, fatty acids and others) in HR, but not LR genotype carriers. Postprandial changes in the levels of some of the detected metabolites may be a source of potential specific early disturbances possibly associated with the future development of T2DM. Thus, accurate determination of these metabolites can be important for the early diagnosis of this metabolic disease.

Appetite-Related Hormones and Subjective Feelings of Hunger and Satiety in Adults Who Regularly Consume Dairy and Those Who Limit Dairy Consumption

Objectives To compare self-reported feelings of hunger and fullness with biological markers associated with appetite and satiety in men and women who are habitual dairy consumers (DC) vs limited dairy consumers (LD). We hypothesize that the DC group will have different appetite perceptions along with different concentrations of the hunger hormone, ghrelin, and the anabolic hormone, insulin, before and following a mixed meal challenge. Methods Adults from a cross-sectional study who completed the Block food frequency questionnaire were categorized as DC (n = 40, consumed >2 cup-eq/d of milk, yogurt, and/or cheese), or LD (n = 37, consumed < ½ cup-eq/d of dairy). On a test day, overnight fasted and postprandial blood samples were collected after a (non-dairy) mixed meal challenge at 30 min, 3h, and 6h. Feelings of hunger, fullness, desire to eat, and prospective consumption were measured by visual analog scales (VAS) in the fasted state, and immediately following the mixed meal at 20 min, 40 min, 1h, 1.5h, 2h, 3h, 4h, 5h, and 6 h. Differences in VAS ratings, fasting glucose, insulin, and ghrelin, and 6-h incremental area under the curve (iAUC) between groups were analyzed using t-tests. Results The DC group had lower mean fasting ghrelin (P < 0.001) and higher fasting glucose (P < 0.05) compared to LD. Fasting insulin levels were not different between groups (P = 0.87), nor were there differences for 6-h iAUC for glucose, ghrelin, or insulin. Hunger, fullness, desire to eat, and prospective consumption, summarized as 6-h AUC, were not different between groups. No correlations were found between hormone concentrations and feelings of hunger, fullness, desire to eat, or prospective consumption, at fasting or 30 min, 3h or 6h following meal challenge. Conclusions Regular consumption of ≥2 cup-eq. of dairy was associated with a reduced fasting ghrelin that might signal less hunger compared to low dairy consumers, but no relationship between ghrelin and hunger was found. The postprandial response in ghrelin, glucose, and insulin were not influenced by habitual dairy consumption. Funding Sources Funding was provided by the United States Department of Agriculture and Arla Foods Inc.

Metabolomic Profiling After a Meal Shows Greater Changes and Lower Metabolic Flexibility in Cardiometabolic Diseases

Context Metabolic flexibility is the physiologic acclimatization to differing energy availability and requirement states. Effectively maintaining metabolic flexibility remains challenging, particularly since metabolic dysregulations in meal consumption during cardiometabolic disease (CMD) pathophysiology are incompletely understood. Objective We compared metabolic flexibility following consumption of a standardized meal challenge among adults with or without CMDs. Design, Setting, and Participants Study participants (n = 349; age 37-54 years, 55% female) received a standardized meal challenge (520 kcal, 67.4 g carbohydrates, 24.3 g fat, 8.0 g protein; 259 mL). Blood samples were collected at baseline and 2 hours postchallenge. Plasma samples were assayed by high-resolution, nontargeted metabolomics with dual-column liquid chromatography and ultrahigh-resolution mass spectrometry. Metabolome-wide associations between features and meal challenge timepoint were assessed in multivariable linear regression models. Results Sixty-five percent of participants had ≥1 of 4 CMDs: 33% were obese, 6% had diabetes, 39% had hypertension, and 50% had metabolic syndrome. Log2-normalized ratios of feature peak areas (postprandial:fasting) clustered separately among participants with versus without any CMDs. Among participants with CMDs, the meal challenge altered 1756 feature peak areas (1063 reversed-phase [C18], 693 hydrophilic interaction liquid chromatography [HILIC]; all q < 0.05). In individuals without CMDs, the meal challenge changed 1383 feature peak areas (875 C18; 508 HILIC; all q < 0.05). There were 108 features (60 C18; 48 HILIC) that differed by the meal challenge and CMD status, including dipeptides, carnitines, glycerophospholipids, and a bile acid metabolite (all P < 0.05). Conclusions Among adults with CMDs, more metabolomic features differed after a meal challenge, which reflected lower metabolic flexibility relative to individuals without CMDs.

Macronutrient, Energy, and Bile Acid Metabolism Pathways Altered Following a Physiological Meal Challenge, Relative to Fasting, among Guatemalan Adults

ABSTRACT Background The healthy human metabolome, including its physiological responses after meal consumption, remains incompletely understood. One major research gap is the limited literature assessing how human metabolomic profiles differ between fasting and postprandial states after physiological challenges. Objectives Our study objective was to evaluate alterations in high-resolution metabolomic profiles following a standardized meal challenge, relative to fasting, in Guatemalan adults. Methods We studied 123 Guatemalan adults without obesity, hypertension, diabetes, metabolic syndrome, or comorbidities. Every participant received a standardized meal challenge (520 kcal, 67.4 g carbohydrates, 24.3 g fat, 8.0 g protein) and provided blood samples while fasting and at 2 h postprandial. Plasma samples were assayed by high-resolution metabolomics with dual-column LC [C18 (negative electrospray ionization), hydrophilic interaction LC (HILIC, positive electrospray ionization)] coupled to ultra-high-resolution MS. Associations between metabolomic features and the meal challenge timepoint were assessed in feature-by-feature multivariable linear mixed regression models. Two algorithms (mummichog, gene set enrichment analysis) were used for pathway analysis, and P values were combined by the Fisher method. Results Among participants (62.6% male, median age 43.0 y), 1130 features (C18: 777; HILIC: 353) differed between fasting and postprandial states (all false discovery rate–adjusted q < 0.05). Based on differing C18 features, top pathways included: tricarboxylic acid cycle (TCA), primary bile acid biosynthesis, and linoleic acid metabolism (all Pcombined < 0.05). Mass spectral features included: taurine and cholic acid in primary bile acid biosynthesis; and fumaric acid, malic acid, and citric acid in the TCA. HILIC features that differed in the meal challenge reflected linoleic acid metabolism (Pcombined < 0.05). Conclusions Energy, macronutrient, and bile acid metabolism pathways were responsive to a standardized meal challenge in adults without cardiometabolic diseases. Our findings reflect metabolic flexibility in disease-free individuals.

Early-Life Nutrition Supplementation Was Associated with Attenuated Postprandial Glycemia in Adulthood

Objectives Populations who were malnourished in early life are susceptible to cardiometabolic disturbances. Metabolic flexibility, the adaptive response to environmental signals such as food ingestion, is integral to cardiometabolic health. We hypothesized that participants exposed to improved nutrition in early life, compared with those unexposed, have better metabolic flexibility. Methods In 1969–77, Guatemalan participants were randomized at the village level to receive either a protein and energy supplement or a low-calorie control. In 2015–17, we collected plasma samples before and 2 h after a mixed-component meal challenge. We characterized metabolic flexibility through meal-induced lipid, glycemic, and pro- and anti-inflammatory responses. Using linear regression for single-marker responses and multivariate analysis of variance (MANOVA) for domain-specific responses, we compared metabolic flexibility between participants exposed to the nutrition supplement from conception to 2y (the “first 1000 days”) versus others. Using structural equation modelling (SEM), we investigated the relationships among postprandial biomarker responses. Results Among 1027 participants (aged 44.0 ± 4.2 y, 59.4% women) who completed the meal challenge, 22.9% were exposed to the supplement in the full first 1000 days. At the single-marker level, insulin increased the most (>2x), whereas non-esterified fatty acids (NEFA) decreased the most (by half) post meal, regardless of early-life nutritional exposure status (P > 0.05 for insulin and NEFA, respectively). Glucose increased by 11.4% in the exposed group, compared with 15.7% in the unexposed group (P < 0.05). SEM identified three latent variables (LV) for postprandial biomarker changes. LV1 and 3 were lipid response-dominant; LV2 was glycemic response-dominant (comparative fit index 0.89, root mean square error of approximation 0.10). MANOVA results showed that the glycemic domain differed by early-life nutritional exposure (P = 0.03). No difference was observed in other domains. Conclusions Early-life exposure to improved nutrition was associated with more favorable glycemic response in this population but not with significant differences in lipid or inflammatory responses. Funding Sources National Institutes of Health Grant No. HD075784.

Metabolomic Profile Responses to a Standardized Meal Challenge Differ by Cardiometabolic Disease Status

Objectives Metabolic flexibility is the physiologic adaptation to differing energy availability and requirement states, such as during meal consumption. Metabolic inflexibility is definitional of some cardiometabolic diseases (CMDs), however the metabolomic profile response (metabolomic flexibility) after meal consumption, relative to a fasting state, in CMDs remains unclear. We compared metabolomic flexibility following consumption of a standardized meal challenge among adults with or without CMDs. Methods Study participants (n = 349; 37–54 years, 55% female) received a standardized meal challenge (520 kcal, 67.4 g carbohydrates, 24.3 g fat, 8.0 g protein; 259 mL). Blood samples were collected at baseline and two hours post-challenge. Plasma samples were assayed by high-resolution metabolomic profiling with dual column liquid chromatography (carbon 18 (C18], negative electrospray ionization; hydrophilic interaction liquid chromatography [HILIC], positive electrospray ionization) coupled to ultra-high-resolution mass spectrometry. Participants were categorized by obesity, hypertension, diabetes and metabolic syndrome. Metabolome-wide associations between features and meal challenge timepoint were assessed in feature-by-feature multivariate generalized linear regression models, including disease profile, age, and sex. Results Two hundred and twenty-six participants (65%) had at least one of the four CMDs: 33% were considered obese, 6% had diabetes, 39% had hypertension, and 50% had metabolic syndrome. Log2-normalized ratios of feature peak areas (post-prandial: fasting) clustered separately among participants with versus without any CMDs. Among participants with CMDs, the meal challenge altered >1700 feature peak areas (all q < 0.05). In individuals without CMDs, the meal challenge changed >1100 feature peak areas (all q < 0.05). The response to the meal challenge of > 100 feature peak areas (C18, HILIC) differed by CMD status (all P < 0.05). These features included dipeptides, lipids (carnitines, glycerophospholipids), and a bile acid metabolite (all P < 0.05). Conclusions Compared to individuals without CMDs, macronutrient metabolism following a standardized meal challenge differed among those with CMDs, reflecting altered metabolic flexibility. Funding Sources National Institutes of Health.