Miriam Ryan

The relationship between BMI and metabolomic profiles: a focus on amino acids

The role of metabolomics in the field of nutrition is continuing to grow and it has the potential to assist in the understanding of metabolic regulation and explain how minor perturbations can have a multitude of biochemical endpoints. It is this development, which creates the potential to provide the knowledge necessary to facilitate a more targeted approach to nutrition. In recent years, there has been interest in applying metabolomics to examine alterations in the metabolic profile according to weight gain/obesity. Emerging from these studies is the strong evidence that alterations in the amino acid (AA) profiles are associated with obesity. Several other studies have also shown a relationship between branched-chain amino acids (BCAA), obesity and insulin resistance. The present review focuses on the proposed link between AA and in particular BCAA, obesity and insulin resistance. In conclusion, a wealth of information is accumulating to support the role of AA, and in particular of the BCAA, in obesity.

Effect of insulin treatment on the body composition of Type 2 diabetic patients.

Objective  Insulin is used commonly in Type 2 diabetes and is often accompanied by weight gain. The composition of this weight gain is poorly understood. Predominant increases in fat mass could increase cardiovascular risks. The aim of the study was to evaluate insulin‐induced body composition changes.

The relationship between aerobic fitness level and metabolic profiles in healthy adults

SCOPE Application of metabolomics to nutrition and health research is increasing and while much effort has been invested in understanding factors that influence the metabolomic profile there is relatively little known about the impact of fitness level. This study aimed to examine the relationship between fitness level, substrate oxidation rates, and the metabolic profile. METHODS AND RESULTS Two hundred and fourteen healthy adults (18-60 years) were recruited and 65 subjects were selected based on their estimated maximal oxygen consumption levels. Metabolomic analysis was performed. The subjects were split into fitness groups according to their maximal oxygen consumption levels (mL/kg/min) and analysis revealed significant differences in normalized fat and carbohydrate oxidation levels between the groups. Urinary metabolomic analysis revealed significantly different profiles in the groups with 15 amino acids significantly higher in the low fitness groups. Effects of fitness level in the plasma metabolic profiles were also demonstrated. CONCLUSION This study demonstrates a relationship between fitness level and the amino acid profile. Moreover, the metabolite changes show that a reduced excretion of amino acids in adults is associated with increased fitness levels and an increased fat oxidation rate during exercise. Interestingly, higher levels of branched chain amino acids were associated with lower fitness levels and higher insulin resistance.

Identification of Differential Responses to an Oral Glucose Tolerance Test in Healthy Adults

Background In recent years an individual’s ability to respond to an acute dietary challenge has emerged as a measure of their biological flexibility. Analysis of such responses has been proposed to be an indicator of health status. However, for this to be fully realised further work on differential responses to nutritional challenge is needed. This study examined whether metabolic phenotyping could identify differential responders to an oral glucose tolerance test (OGTT) and examined the phenotypic basis of the response. Methods and Results A total of 214 individuals were recruited and underwent challenge tests in the form of an OGTT and an oral lipid tolerance test (OLTT). Detailed biochemical parameters, body composition and fitness tests were recorded. Mixed model clustering was employed to define 4 metabotypes consisting of 4 different responses to an OGTT. Cluster 1 was of particular interest, with this metabotype having the highest BMI, triacylglycerol, hsCRP, c-peptide, insulin and HOMA- IR score and lowest VO2max. Cluster 1 had a reduced beta cell function and a differential response to insulin and c-peptide during an OGTT. Additionally, cluster 1 displayed a differential response to the OLTT. Conclusions This work demonstrated that there were four distinct metabolic responses to the OGTT. Classification of subjects based on their response curves revealed an “at risk” metabolic phenotype.

Within-person variation in the postprandial lipemic response of healthy adults

BACKGROUND The response to dietary fat plays a key role in metabolic health. Although this can vary widely between individuals, variation within an individual and the associated contribution of phenotypic and genotypic factors to this variation are less defined. OBJECTIVES The objectives were to quantify within-person variation in triacylglycerol response by means of a novel variation score (S(v)) and to explore the phenotypic and genotypic factors associated with this score. DESIGN Two consecutive 5-h oral-lipid-tolerance tests (OLTTs) were conducted in 51 healthy adults aged 18-60 y with a BMI (in kg/m²) of 18.5 to 49.8. Detailed body composition, physical function, biochemistry, and genotype data were gathered. RESULTS The postprandial triacylglycerol response profile did not differ (P = 0.64) across OLTTs for the group; nor did average concentrations of functional markers apolipoprotein C2 (P = 0.73) and apolipoprotein C3 (P = 0.74). S(v) was low in most (82%) of the adults and was significantly (P < 0.05) associated with age, fasting triacylglycerol, triacylglycerol AUC, and fasting nonessential fatty acids. Significant associations were also observed between S(v) and single nucleotide polymorphisms in 7 genes (APOA1, IL1α, IL1β, TLR4, TCF7L2, CCK1Rec, and STAT3) after correction for phenotypic differences. CONCLUSIONS This work showed that the within-person variability in postprandial lipemic response is low in most healthy adults. It also showed that variability in this response is associated with a defined set of phenotypic and genotypic characteristics.

Resting energy expenditure is not increased in mildly hyperglycaemic obese diabetic patients

Resting energy expenditure (REE) is believed to be increased in type 2 diabetes, an increase that is associated with deteriorating glucose tolerance during its development. Meanwhile, insulin resistance, a state linked to obesity and observed in all type 2 diabetic patients, is associated with reduced REE. Our aim was to compare REE in obese patients with and without diabetes. REE, body composition (total body water, density, percentage fat and fat-free mass: 3-compartment model) and metabolic control were assessed in fifty obese Caucasian patients with diabetes (glycated haemoglobin level 7.6 (SD 1.5) %) and fifty obese patients who were non-diabetic. Despite being more overweight and younger, obese non-diabetic patients had an absolute REE (7.73 (SD 1.44) v. 8.12 (SD 1.37) MJ; P=0.17) and percentage fat-free mass similar to those of obese diabetic patients. Even when adjusted for differences in body composition, REE remained similar in both groups. Furthermore, REE (absolute and adjusted) was unaffected by both glucose level and control (glycated haemoglobin), with fat-free mass being the only determinant of REE. We conclude that REE is not necessarily increased by the presence of diabetes in obese people.

Habitual dietary intake impacts on the lipidomic profile

Reliable dietary assessments are essential when attempting to understand the complex links between diet and health. Traditional methods for collecting dietary exposure can be unreliable, therefore there is an increasing interest in identifying biomarkers to provide a more accurate measurement. Metabolomics is a technology that offers great promise in this area. The aim of this study was to use a multivariate statistical strategy to link lipidomic patterns with dietary data in an attempt to identify dietary biomarkers. We assessed the relationship between lipidomic profiles and dietary data in volunteers (n=34) from the Metabolic Challenge Study (MECHE). Principal component analysis (PCA), linear regression and receiver operating characteristic (ROC) analysis were used to (1) reduce the lipidomic data into lipid patterns (LPs), (2) investigate relationships between these patterns and dietary data and (3) identify biomarkers of dietary intake. Our study identified a total of 6 novel LPs. LP1 was highly predictive of dietary fat intake (area under the curve AUC=0.82). A random forest (RF) classification model used to discriminate between low and high consumers resulted with an error rate of >10%, with a panel of six metabolites identified as the most predictive. LP4 was highly predictive of alcohol intake (AUC=0.81) with lysophosphatidylcholine alkyl C18:0 (LPCeC18:0) identified as a potential biomarker of alcohol consumption. LP6 had a reasonably good ability to predict dietary fish intake (AUC=0.76), with lysophosphatidylethanolamine acyl C18:2 (LPEaC18:2) phoshatidylethanolamine diaclyl C38:4 (PEaaC38:4) identified as potential biomarkers. The identification of these LPs and specific biomarkers will help in better classifying a persons dietary intake and in turn will improve the assessment of the relationship between diet and disease. Linking these LPs and specific biomarkers with health parameters will be an important future step.

High-Density Lipoprotein Proteomic Composition, and not Efflux Capacity, Reflects Differential Modulation of Reverse Cholesterol Transport by Saturated and Monounsaturated Fat Diets

Background— Acute inflammation impairs reverse cholesterol transport (RCT) and reduces high-density lipoprotein (HDL) function in vivo. This study hypothesized that obesity-induced inflammation impedes RCT and alters HDL composition, and investigated if dietary replacement of saturated (SFA) for monounsaturated (MUFA) fatty acids modulates RCT. Methods and Results— Macrophage-to-feces RCT, HDL efflux capacity, and HDL proteomic profiling was determined in C57BL/6j mice following 24 weeks on SFA- or MUFA-enriched high-fat diets (HFDs) or low-fat diet. The impact of dietary SFA consumption and insulin resistance on HDL efflux function was also assessed in humans. Both HFDs increased plasma 3H-cholesterol counts during RCT in vivo and ATP-binding cassette, subfamily A, member 1–independent efflux to plasma ex vivo, effects that were attributable to elevated HDL cholesterol. By contrast, ATP-binding cassette, subfamily A, member 1–dependent efflux was reduced after both HFDs, an effect that was also observed with insulin resistance and high SFA consumption in humans. SFA-HFD impaired liver-to-feces RCT, increased hepatic inflammation, and reduced ABC subfamily G member 5/8 and ABC subfamily B member 11 transporter expression in comparison with low-fat diet, whereas liver-to-feces RCT was preserved after MUFA-HFD. HDL particles were enriched with acute-phase proteins (serum amyloid A, haptoglobin, and hemopexin) and depleted of paraoxonase-1 after SFA-HFD in comparison with MUFA-HFD. Conclusions— Ex vivo efflux assays validated increased macrophage-to-plasma RCT in vivo after both HFDs but failed to capture differential modulation of hepatic cholesterol trafficking. By contrast, proteomics revealed the association of hepatic-derived inflammatory proteins on HDL after SFA-HFD in comparison with MUFA-HFD, which reflected differential hepatic cholesterol trafficking between groups. Acute-phase protein levels on HDL may serve as novel biomarkers of impaired liver-to-feces RCT in vivo.

PBMCs reflect the immune component of the WAT transcriptome--implications as biomarkers of metabolic health in the postprandial state.

SCOPE Food and nutrition studies often require accessing metabolically active tissues, including adipose tissue. This can involve invasive biopsy procedures that can be a limiting factor in study design. In contrast, peripheral blood mononuclear cells (PBMCs) are a population of circulating immune cells that are easily accessible through venipuncture. As transcriptomics is of growing importance in food and metabolism research, understanding the transcriptomic relationship between these tissue types can provide insight into the utility of PBMCs in this field. METHODS AND RESULTS We examine this relationship within eight subjects, in two postprandial states (following oral lipid tolerance test and oral glucose tolerance test). Multivariate analysis techniques were used to examine variation between tissues, samples, and subjects in order to define which genes havecommon/disparate expression profiles associated with highly defined metabolic phenotypes. We demonstrate global similarities in gene expression between PBMCs and white adipose tissue, irrespective of the metabolic challenge type. Closer examination of individual genes revealed this similarity to be strongest in pathways related to immune response/inflammation. Notably, the expression of metabolism-related nuclear receptors, including PPARs, LXR, etc. was discordant between tissues CONCLUSION The PBMC transcriptome may therefore provide a unique insight into the inflammatory component of metabolic health, as opposed to directly reflecting the metabolic component of the adipose tissue transcriptome.

Glycemic, Insulinemic, and Appetite Responses of Patients With Type 2 Diabetes to Commonly Consumed Breads

Purpose The purpose of this study was to identify the breads most commonly consumed by adults with type 2 diabetes (T2DM) and then examine the postprandial glycemic, insulinemic, and appetite responses that these breads elicit. Methods One hundred people with T2DM were surveyed to identify the varieties of bread they most frequently consumed. According to a randomized crossover design, 11 fasting participants with T2DM consumed 50 g of available carbohydrate from 4 breads. Glucose and insulin concentrations and appetite ratings were determined over 270 minutes. Results Three commonly consumed varieties (white, whole wheat buttermilk, whole grain) identified in the survey—plus a lower-glycemic-index “control” bread (pumpernickel rye)—were tested in the second phase. Despite perceived differences between “brown” and “white” breads, the white, whole wheat buttermilk, and wholegrain breads promoted similar glycemic and insulinemic responses. Pumpernickel bread resulted in a significantly lower peak glucose (P < .01) than all other breads and a lower peak insulin (P < .001) than white or wholegrain bread. Similar appetite responses were found with all 4 breads. Conclusions Adults with T2DM are choosing a variety of breads with perceived differential effects on glycemic, insulinemic, and appetite responses. Appreciable benefits, however, are not conferred by the commonly consumed breads. If breads known to promote favorable metabolic responses are unavailable, the primary emphasis in education should be placed on portion control. Conveying this information to patients is crucial if nutrition education is to achieve its aim of empowering individuals to manage their diabetes through their food choices.