Ciara Morris

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.

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.

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.

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.

Body mass index mediates inflammatory response to acute dietary challenges

SCOPE Acute metabolic challenges provide an opportunity to identify mechanisms of metabolic and nutritional health. In this study, we assessed the transcriptomic response to oral glucose and lipid challenges in a cohort of individuals ranging in age and BMI. The main goal is to identify whether BMI can mediate the metabolic and transcriptional response to dietary challenges, and the differences between lipid and glucose tests. METHODS AND RESULTS Two hundred fourteen healthy adults were assigned to the challenges and twenty-three individuals were selected for further transcriptomic proofing, using microarray analysis of peripheral blood mononuclear cells. Through linear-mixed models and network analysis, different sets of transcripts and pathways were identified that responded to the challenges depending on BMI. Different transcripts that responded to the lipid and glucose tests, independently of BMI, were also identified. In the network analysis, inflammatory and adhesion processes were strongly represented for both challenges. CONCLUSION Our results indicate that BMI is strongly linked to the transcriptomic and metabolic response to acute challenges. The emerging biological processes are mainly inflammation-related pathways, highlighting an interconnection between obesity, inflammation/adhesion, and response to nutritional challenge. The comparison between lipid and glucose challenges shows how these trigger a substantially different molecular response.

Phenotypic and genotypic determinants of postprandial lipaemic response variation in healthy adults

Response to dietary fat plays a key role in metabolic and cardiovascular health. While this response can vary widely between individuals, variation within an individual and the associated contribution of phenotypic and genotypic factors is less well defined. Understanding these issues is fundamental to the goal of achieving personalised nutrition. This work aimed to describe withinand between-person variation in lipaemic response to a repeated oral lipid tolerance test (OLTT) in 51 healthy adults as part of a larger randomised controlled trial. Fasting and postprandial plasma were collected hourly over 5 hours, from which SNP genotype and detailed biochemistry data, including triglyceride (TAG), non-esterified fatty acid, glucose and hormonal, were collected. Body composition (DXA, BodPod1), strength (isokinetic dynamometry), metabolic rate (indirect calorimetry) and fitness (sub-VO2max) among other variables were also assessed. A TAG variability score (Sv), derived from the cumulative difference in TAG level at each time point across OLTTs, was assigned to each person as a proxy measure of lipaemic response. Those with the lowest variation in TAG concentration across OLTTs (LOW n 17) were compared to those of the highest variation (HIGH n 17). Analysis showed postprandial TAG response did not differ (p = 0.64) between visits for the group as a whole, with 82% exhibiting low variation (Sv<3.48) in TAG response. When LOW and HIGH individuals were compared however, significant phenotypic and genotypic differences were observed. Phenotype association: HIGH individuals were significantly (p<0.05) younger, heavier, taller, had a larger waist circumference, higher truncal bone mineral density and metabolic rate (kJ/kg FFM) and displayed higher TAG and lower NEFA levels at fasting. Genotype association: Exploratory analysis revealed associations between high Sv and SNPs in genes associated with satiety, lipoprotein metabolism, adipogenesis and type 2 diabetes risk after correction for phenotypic variables. In conclusion this work (1) confirms preliminary findings that postprandial lipaemic response is highly constant within the majority of healthy adults, and (2) strongly suggests that people who do exhibit the most variable response have a defined set of phenotypic and genotypic characteristics that warrant further research.

Peripheral blood mononuclear cell gene expression and plasma protein profiles are differentially affected by glucose and lipid tolerance tests

Peripheral blood mononuclear cells (PBMC) are an easily accessed tissue type that show differential gene expression following nutritional stimulus in vivo. This study addressed the hypothesis that the PBMC transcriptomic signature and the associated metabolic phenotype would be differentially regulated by lipid v. carbohydrate nutritional challenges. An oral lipid tolerance test (OLTT) and a glucose tolerance test (OGTT) were completed in a ‘lean’ cohort of ten individuals selected from a representative sample of 200 healthy Irish adults aged 18–60 years (age: 24.6 SD 3.84 years, BMI: 24.5 SD 2.2 kg.m). Fasting and postprandial peak plasma and PBMC samples were taken at 1 and 4 h post-OGTT and -OLTT, respectively. RNA was hybridised to Affymetrix Human Gene ST 1.0 arrays. Microarray data were normalised using RMA and R/BioConductor determined differentially expressed genes. The metabolic profile of volunteers was characterised including plasma TAG, NEFA, glucose, insulin and inflammatory profiles were determined. A total of 2292 genes were differentially expressed following OLTT. No single genes were significantly differentially expressed following OGTT. The genes showing greatest changes in expression post-OLTT include CENPK, CLC, OCLN, TMEM176A, FOLR3, ANKRD22, VNN1 and PGA5 (all log Fc> 1.3). Key genes involved in lipid metabolism (LPL, LRP1, PLIN3) and inflammation (IKBKG, NLRP3) were increased following the OLTT, but not OGTT. The KEGG pathway showing greatest enrichment, Fc gamma R-mediated phagocytosis, also contains genes related to inflammation. Most notably, the ERK-activated cPLA2 gene is present, which modulates arachidonic acid (AA) and EPA release from DAG. Given the central role of AA/EPA, this may affect downstream eicosanoid, prostaglandin, leukotriene or resolvin production. The transcriptomic signature will be related to the metabolic phenotype, which included an increase in plasma glucose following the OGTT (P<0.0001), elevated plasma TAG post-OLTT (P = 0.0354) and lower NEFA concentration following both OGTT (P<0.0001) and OLTT (P = 0.001). Interestingly the increase in inflammatory gene expression was associated with greater postprandial plasma IL-6 (P = 0.0091) and EGF (P = 0.0053) and a decrease in IFNG (P = 0.104) concentrations post-OLTT, with no such changes post-OGTT. In conclusion, the OLTT induced a pro-inflammatory state in the PBMC transcriptome and plasma protein markers implicated in insulin resistance, the Metabolic Syndrome and T2DM, with no such response following OGTT.