Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

Metabolic profiling of tissue-specific insulin resistance in human obesity: results from the Diogenes study and the Maastricht Study

BACKGROUND

Recent evidence indicates that insulin resistance (IR) in obesity may develop independently in different organs, representing different etiologies toward type 2 diabetes and other cardiometabolic diseases. The aim of this study was to investigate whether IR in the liver and IR in skeletal muscle are associated with distinct metabolic profiles.

METHODS

This study includes baseline data from 634 adults with overweight or obesity (BMI ≥ 27 kg/m²) (≤65 years; 63% women) without diabetes of the European Diogenes Study. Hepatic insulin resistance index (HIRI) and muscle insulin sensitivity index (MISI), were derived from a five-point OGTT. At baseline 17 serum metabolites were identified and quantified by nuclear-magnetic-resonance spectroscopy. Linear mixed model analyses (adjusting for center, sex, body mass index (BMI), waist-to-hip ratio) were used to associate HIRI and MISI with these metabolites. In an independent sample of 540 participants without diabetes (BMI ≥ 27 kg/m²; 40-65 years; 46% women) of the Maastricht Study, an observational prospective population-based cohort study, 11 plasma metabolites and a seven-point OGTT were available for validation.

RESULTS

Both HIRI and MISI were associated with higher levels of valine, isoleucine, oxo-isovaleric acid, alanine, lactate, and triglycerides, and lower levels of glycine (all p < 0.05). HIRI was also associated with higher levels of leucine, hydroxyisobutyrate, tyrosine, proline, creatine, and n-acetyl and lower levels of acetoacetate and 3-OH-butyrate (all p < 0.05). Except for valine, these results were replicated for all available metabolites in the Maastricht Study.

CONCLUSIONS

In persons with obesity without diabetes, both liver and muscle IR show a circulating metabolic profile of elevated (branched-chain) amino acids, lactate, and triglycerides, and lower glycine levels, but only liver IR associates with lower ketone body levels and elevated ketogenic amino acids in circulation, suggestive of decreased ketogenesis. This knowledge might enhance developments of more targeted tissue-specific interventions to prevent progression to more severe disease stages.

Association of brachial-cuff excess pressure with carotid intima-media thickness in Australian adults: a cross-sectional study

OBJECTIVE

Reservoir pressure parameters [e.g. reservoir pressure (RP) and excess pressure (XSP)] measured using tonometry predict cardiovascular events beyond conventional risk factors. However, the operator dependency of tonometry impedes widespread use. An operator-independent cuff-based device can reasonably estimate the intra-aortic RP and XSP from brachial volumetric waveforms, but whether these estimates are clinically relevant to preclinical phenotypes of cardiovascular risk has not been investigated.

METHODS

The RP and XSP were derived from brachial volumetric waveforms measured using cuff oscillometry (SphygmoCor XCEL) in 1691 mid-life adults from the CheckPoint study (a population-based cross-sectional study nested in the Longitudinal Study of Australian Children). Carotid intima--media thickness (carotid IMT, n = 1447) and carotid--femoral pulse wave velocity (PWV, n = 1632) were measured as preclinical phenotypes of cardiovascular risk. Confounders were conventional risk factors that were correlated with both exposures and outcomes or considered as physiologically important.

RESULTS

There was a modest association between XSP and carotid IMT (β = 0.76 μm, 95% CI, 0.25-1.26 partial R = 0.8%) after adjusting for age, sex, BMI, heart rate, smoking, diabetes, high-density lipoprotein cholesterol and mean arterial pressure. Neither RP nor XSP were associated with PWV in the similarly adjusted models (β = -0.47 cm/s, 95% CI, -1.15 to 0.20, partial R = 0.2% for RP, and β = 0.04 cm/s, 95% CI, -0.59 to 0.67, partial R = 0.01% for XSP).

CONCLUSION

Cuff-based XSP associates with carotid IMT independent of conventional risk factors, including traditional BP, but the association was weak, indicating that further investigation is warranted to understand the clinical significance of reservoir pressure parameters.

Circulating Fatty Acids and Risk of Coronary Heart Disease and Stroke: Individual Participant Data Meta-Analysis in Up to 16 126 Participants

Background We aimed at investigating the association of circulating fatty acids with coronary heart disease (CHD) and stroke risk. Methods and Results We conducted an individual-participant data meta-analysis of 5 UK-based cohorts and 1 matched case-control study. Fatty acids (ie, omega-3 docosahexaenoic acid, omega-6 linoleic acid, monounsaturated and saturated fatty acids) were measured at baseline using an automated high-throughput serum nuclear magnetic resonance metabolomics platform. Data from 3022 incident CHD cases (13 104 controls) and 1606 incident stroke cases (13 369 controls) were included. Logistic regression was used to model the relation between fatty acids and odds of CHD and stroke, adjusting for demographic and lifestyle variables only (ie, minimally adjusted model) or with further adjustment for other fatty acids (ie, fully adjusted model). Although circulating docosahexaenoic acid, but not linoleic acid, was related to lower CHD risk in the fully adjusted model (odds ratio, 0.85; 95% CI, 0.76-0.95 per standard unit of docosahexaenoic acid), there was evidence of high between-study heterogeneity and effect modification by study design. Stroke risk was consistently lower with increasing circulating linoleic acid (odds ratio for fully adjusted model, 0.82; 95% CI, 0.75-0.90). Circulating monounsaturated fatty acids were associated with higher CHD risk across all models and with stroke risk in the fully adjusted model (odds ratio, 1.22; 95% CI, 1.03-1.44). Saturated fatty acids were not related to increased CHD risk in the fully adjusted model (odds ratio, 0.94; 95% CI, 0.82-1.09), or stroke risk. Conclusions We found consistent evidence that linoleic acid was associated with decreased risk of stroke and that monounsaturated fatty acids were associated with increased risk of CHD. The different pattern between CHD and stroke in terms of fatty acids risk profile suggests future studies should be cautious about using composite events. Different study designs are needed to assess which, if any, of the associations observed is causal.

Metabolomics Profile in Depression: A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls

BACKGROUND

Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons.

METHODS

Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses.

RESULTS

Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein A1 were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms.

CONCLUSIONS

This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity.

Glycoprotein A as a biomarker of pulmonary infection and inflammation in children with cystic fibrosis

BACKGROUND

Serum Glycoprotein A (GlycA) levels are increased in a variety of inflammatory disease states. However, GlycA has not been previously evaluated in children with cystic fibrosis (CF). We assessed the relationship between GlycA and pulmonary infection, inflammation, bronchial wall thickening (BWT) and bronchiectasis in young children with CF.

METHODS

From 95 patients, we obtained 311 paired serum and bronchoalveolar lavage (BAL) samples at multiple timepoints, with concurrent chest computed tomography on 168 occasions. Quantitative GlycA was determined using high-throughput nuclear magnetic resonance metabolomic testing. Participants were considered to be infected if ≥1 significant proinflammatory organism was isolated from their BAL. The presence of free neutrophil elastase (NE) above the limit of detection was considered evidence of inflammation. The relationships between GlycA levels and infection state, inflammation, and bronchiectasis were examined using a generalized estimating equation approach.

RESULTS

There was a positive relationship between GlycA (mean 1.01 mmol/L, range 0.68-1.92 mmol/L) and being infected with one or more proinflammatory organisms, even after adjusting for age and gender (odds ratio [OR], 1.2 per 0.1 mmol/L, 95% confidence interval [CI], 1.02, 1.4, P = .03). There was also a positive relationship between GlycA and NE (unadjusted OR, 1.2 95% CI, 1.01, 1.4, P = .04), not significant after adjustment. GlycA concentration was associated with BWT but not bronchiectasis.

CONCLUSIONS

Although GlycA levels were higher on average in those who had an infection or neutrophilic inflammation, there was also considerable variability, limiting the clinical utility of this biomarker alone in determining early disease status in CF.

Genome-Wide Association Study for Serum Omega-3 and Omega-6 Polyunsaturated Fatty Acids: Exploratory Analysis of the Sex-Specific Effects and Dietary Modulation in Mediterranean Subjects with Metabolic Syndrome

Many early studies presented beneficial effects of polyunsaturated fatty acids (PUFA) on cardiovascular risk factors and disease. However, results from recent meta-analyses indicate that this effect would be very low or nil. One of the factors that may contribute to the inconsistency of the results is that, in most studies, genetic factors have not been taken into consideration. It is known that fatty acid desaturase (FADS) gene cluster in chromosome 11 is a very important determinant of plasma PUFA, and that the prevalence of the single nucleotide polymorphisms (SNPs) varies greatly between populations and may constitute a bias in meta-analyses. Previous genome-wide association studies (GWAS) have been carried out in other populations and none of them have investigated sex and Mediterranean dietary pattern interactions at the genome-wide level. Our aims were to undertake a GWAS to discover the genes most associated with serum PUFA concentrations (omega-3, omega-6, and some fatty acids) in a scarcely studied Mediterranean population with metabolic syndrome, and to explore sex and adherence to Mediterranean diet (MedDiet) interactions at the genome-wide level. Serum PUFA were determined by NMR spectroscopy. We found strong robust associations between various SNPs in the FADS cluster and omega-3 concentrations (top-ranked in the adjusted model: FADS1-rs174547, p = 3.34 × 10-14; FADS1-rs174550, p = 5.35 × 10-14; FADS2-rs1535, p = 5.85 × 10-14; FADS1-rs174546, p = 6.72 × 10-14; FADS2-rs174546, p = 9.75 × 10-14; FADS2- rs174576, p = 1.17 × 10-13; FADS2-rs174577, p = 1.12 × 10-12, among others). We also detected a genome-wide significant association with other genes in chromosome 11: MYRF (myelin regulatory factor)-rs174535, p = 1.49 × 10-12; TMEM258 (transmembrane protein 258)-rs102275, p = 2.43 × 10-12; FEN1 (flap structure-specific endonuclease 1)-rs174538, p = 1.96 × 10-11). Similar genome-wide statistically significant results were found for docosahexaenoic fatty acid (DHA). However, no such associations were detected for omega-6 PUFAs or linoleic acid (LA). For total PUFA, we observed a consistent gene*sex interaction with the DNTTIP2 (deoxynucleotidyl transferase terminal interacting protein 2)-rs3747965 p = 1.36 × 10-8. For adherence to MedDiet, we obtained a relevant interaction with the ME1 (malic enzyme 1) gene (a gene strongly regulated by fat) in determining serum omega-3. The top-ranked SNP for this interaction was ME1-rs3798890 (p = 2.15 × 10-7). In the regional-wide association study, specifically focused on the FADS1/FASD2/FADS3 and ELOVL (fatty acid elongase) 2/ELOVL 5 regions, we detected several statistically significant associations at p < 0.05. In conclusion, our results confirm a robust role of the FADS cluster on serum PUFA in this population, but the associations vary depending on the PUFA. Moreover, the detection of some sex and diet interactions underlines the need for these associations/interactions to be studied in all specific populations so as to better understand the complex metabolism of PUFA.

Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug-metabolite atlas

Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug-metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug-metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).

Metabolomic Signature of Angiopoietin-Like Protein 3 Deficiency in Fasting and Postprandial State

Objective- Loss-of-function (LOF) variants in the ANGPTL3 (angiopoietin-like protein 3) have been associated with low levels of plasma lipoproteins and decreased coronary artery disease risk. We aimed to determine detailed metabolic effects of genetically induced ANGPTL3 deficiency in fasting and postprandial state. Approach and Results- We studied individuals carrying S17X LOF mutation in ANGPTL3 (6 homozygous and 32 heterozygous carriers) and 38 noncarriers. Nuclear magnetic resonance metabolomics was used to quantify 225 circulating metabolic measures. We compared metabolic differences between LOF carriers and noncarriers in fasting state and after a high-fat meal. In fasting, ANGPTL3 deficiency was characterized by similar extent of reductions in LDL (low-density lipoprotein) cholesterol (0.74 SD units lower concentration per LOF allele [95% CI, 0.42-1.06]) as observed for many TRL (triglyceride-rich lipoprotein) measures, including VLDL (very-low-density lipoprotein) cholesterol (0.75 [95% CI, 0.45-1.05]). Within most lipoprotein subclasses, absolute levels of cholesterol were decreased more than triglycerides, resulting in the relative proportion of cholesterol being reduced within TRLs and their remnants. Further, β-hydroxybutyrate was elevated (0.55 [95% CI, 0.21-0.89]). Homozygous ANGPTL3 LOF carriers showed essentially no postprandial increase in TRLs and fatty acids, without evidence for adverse compensatory metabolic effects. Conclusions- In addition to overall triglyceride- and LDL cholesterol-lowering effects, ANGPTL3 deficiency results in reduction of cholesterol proportion within TRLs and their remnants. Further, ANGPTL3 LOF carriers had elevated ketone body production, suggesting enhanced hepatic fatty acid β-oxidation. The detailed metabolic profile in human knockouts of ANGPTL3 reinforces inactivation of ANGPTL3 as a promising therapeutic target for decreasing cardiovascular risk.

Metabolomics analysis in adults with high bone mass identifies a relationship between bone resorption and circulating citrate which replicates in the general population

OBJECTIVE

Bone turnover, which regulates bone mass, may exert metabolic consequences, particularly on markers of glucose metabolism and adiposity. To better understand these relationships, we examined cross-sectional associations between bone turnover markers (BTMs) and metabolic traits in a population with high bone mass (HBM, BMD Z-score ≥+3.2).

DESIGN

β-C-terminal telopeptide of type-I collagen (β-CTX), procollagen type-1 amino-terminal propeptide (P1NP) and osteocalcin were assessed by electrochemiluminescence immunoassays. Metabolic traits, including lipids and glycolysis-related metabolites, were measured using nuclear magnetic resonance spectroscopy. Associations of BTMs with metabolic traits were assessed using generalized estimating equation linear regression, accounting for within-family correlation, adjusting for potential confounders (age, sex, height, weight, menopause, bisphosphonate and oral glucocorticoid use).

RESULTS

A total of 198 adults with HBM had complete data, mean [SD] age 61.6 [13.7] years; 77% were female. Of 23 summary metabolic traits, citrate was positively related to all BTMs: adjusted ββ-CTX  = 0.050 (95% CI 0.024, 0.076), P = 1.71 × 10-4 , βosteocalcin  = 6.54 × 10-4 (1.87 × 10-4 , 0.001), P = .006 and βP1NP  = 2.40 × 10-4 (6.49 × 10-5 , 4.14 × 10-4 ), P = .007 (β = increase in citrate (mmol/L) per 1 µg/L BTM increase). Inverse relationships of β-CTX (β = -0.276 [-0.434, -0.118], P = 6.03 × 10-4 ) and osteocalcin (-0.004 [-0.007, -0.001], P = .020) with triglycerides were also identified. We explored the generalizability of these associations in 3664 perimenopausal women (age 47.9 [4.4] years) from a UK family cohort. We confirmed a positive, albeit lower magnitude, association between β-CTX and citrate (adjusted βwomen  = 0.020 [0.013, 0.026], P = 1.95 × 10-9 ) and an inverse association of similar magnitude between β-CTX and triglycerides (β = -0.354 [-0.471, -0.237], P = 3.03 × 10-9 ).

CONCLUSIONS

Bone resorption is positively related to circulating citrate and inversely related to triglycerides. Further studies are justified to determine whether plasma citrate or triglyceride concentrations are altered by factors known to modulate bone resorption, such as bisphosphonates.

A plasma proteogenomic signature for fibromuscular dysplasia

AIMS

Fibromuscular dysplasia (FMD) is a poorly understood disease that predominantly affects women during middle-life, with features that include stenosis, aneurysm, and dissection of medium-large arteries. Recently, plasma proteomics has emerged as an important means to understand cardiovascular diseases. Our objectives were: (i) to characterize plasma proteins and determine if any exhibit differential abundance in FMD subjects vs. matched healthy controls and (ii) to leverage these protein data to conduct systems analyses to provide biologic insights on FMD, and explore if this could be developed into a blood-based FMD test.

METHODS AND RESULTS

Females with 'multifocal' FMD and matched healthy controls underwent clinical phenotyping, dermal biopsy, and blood draw. Using dual-capture proximity extension assay and nuclear magnetic resonance-spectroscopy, we evaluated plasma levels of 981 proteins and 31 lipid sub-classes, respectively. In a discovery cohort (Ncases = 90, Ncontrols = 100), we identified 105 proteins and 16 lipid sub-classes (predominantly triglycerides and fatty acids) with differential plasma abundance in FMD cases vs. controls. In an independent cohort (Ncases = 23, Ncontrols = 28), we successfully validated 37 plasma proteins and 10 lipid sub-classes with differential abundance. Among these, 5/37 proteins exhibited genetic control and Bayesian analyses identified 3 of these as potential upstream drivers of FMD. In a 3rd cohort (Ncases = 506, Ncontrols = 876) the genetic locus of one of these upstream disease drivers, CD2-associated protein (CD2AP), was independently validated as being associated with risk of having FMD (odds ratios  = 1.36; P = 0.0003). Immune-fluorescence staining identified that CD2AP is expressed by the endothelium of medium-large arteries. Finally, machine learning trained on the discovery cohort was used to develop a test for FMD. When independently applied to the validation cohort, the test showed a c-statistic of 0.73 and sensitivity of 78.3%.

CONCLUSION

FMD exhibits a plasma proteogenomic and lipid signature that includes potential causative disease drivers, and which holds promise for developing a blood-based test for this disease.

Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition

Cholesteryl ester transfer protein (CETP) inhibition reduces vascular event risk, but confusion surrounds its effects on low-density lipoprotein (LDL) cholesterol. Here, we clarify associations of genetic inhibition of CETP on detailed lipoprotein measures and compare those to genetic inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). We used an allele associated with lower CETP expression (rs247617) to mimic CETP inhibition and an allele associated with lower HMGCR expression (rs12916) to mimic the well-known effects of statins for comparison. The study consists of 65,427 participants of European ancestries with detailed lipoprotein subclass profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% reduction in relative risk of coronary heart disease (CHD). We also examined observational associations of the lipoprotein subclass measures with risk of incident CHD in 3 population-based cohorts totalling 616 incident cases and 13,564 controls during 8-year follow-up. Genetic inhibition of CETP and HMGCR resulted in near-identical associations with LDL cholesterol concentration estimated by the Friedewald equation. Inhibition of HMGCR had relatively consistent associations on lower cholesterol concentrations across all apolipoprotein B-containing lipoproteins. In contrast, the associations of the inhibition of CETP were stronger on lower remnant and very-low-density lipoprotein (VLDL) cholesterol, but there were no associations on cholesterol concentrations in LDL defined by particle size (diameter 18–26 nm) (−0.02 SD LDL defined by particle size; 95% CI: −0.10 to 0.05 for CETP versus −0.24 SD, 95% CI −0.30 to −0.18 for HMGCR). Inhibition of CETP was strongly associated with lower proportion of triglycerides in all high-density lipoprotein (HDL) particles. In observational analyses, a higher triglyceride composition within HDL subclasses was associated with higher risk of CHD, independently of total cholesterol and triglycerides (strongest hazard ratio per 1 SD higher triglyceride composition in very large HDL 1.35; 95% CI: 1.18–1.54). In conclusion, CETP inhibition does not appear to affect size-specific LDL cholesterol but is likely to lower CHD risk by lowering concentrations of other atherogenic, apolipoprotein B-containing lipoproteins (such as remnant and VLDLs). Inhibition of CETP also lowers triglyceride composition in HDL particles, a phenomenon reflecting combined effects of circulating HDL, triglycerides, and apolipoprotein B-containing particles and is associated with a lower CHD risk in observational analyses. Our results reveal that conventional composite lipid assays may mask heterogeneous effects of emerging lipid-altering therapies.

Inhibition of cholesteryl ester transfer protein does not affect size-specific low-density lipoprotein cholesterol, but may lower coronary heart disease risk by lowering cholesterol concentrations in other apolipoprotein-B containing atherogenic lipoproteins, and by lowering triglyceride content of high-density lipoprotein particles.

Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease

BACKGROUND AND AIMS

Population subgrouping has been suggested as means to improve coronary heart disease (CHD) risk assessment. We explored here how unsupervised data-driven metabolic subgrouping, based on comprehensive lipoprotein subclass data, would work in large-scale population cohorts.

METHODS

We applied a self-organizing map (SOM) artificial intelligence methodology to define subgroups based on detailed lipoprotein profiles in a population-based cohort (n = 5789) and utilised the trained SOM in an independent cohort (n = 7607). We identified four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk and compared those to univariate subgrouping by apolipoprotein B quartiles.

RESULTS

The SOM-based subgroup with highest concentrations for non-HDL measures had the highest, and the subgroup with lowest concentrations, the lowest risk for CHD. However, apolipoprotein B quartiles produced better resolution of risk than the SOM-based subgroups and also striking dose-response behaviour.

CONCLUSIONS

These results suggest that the majority of lipoprotein-mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles. Therefore, even advanced multivariate subgrouping, with comprehensive data on lipoprotein metabolism, may not advance CHD risk assessment.

Statistical reporting of metabolomics data: experience from a high-throughput NMR platform and epidemiological applications

INTRODUCTION

Meta-analysis is the cornerstone of robust biomedical evidence.

OBJECTIVES

We investigated whether statistical reporting practices facilitate metabolomics meta-analyses.

METHODS

A literature review of 44 studies that used a comparable platform.

RESULTS

Non-numeric formats were used in 31 studies. In half of the studies, less than a third of all measures were reported. Unadjusted P-values were missing from 12 studies and exact P-values from 9 studies.

CONCLUSION

Reporting practices can be improved. We recommend (i) publishing all results as numbers, (ii) reporting effect sizes of all measured metabolites and (iii) always reporting unadjusted exact P-values.

Circulating metabolites and the risk of type 2 diabetes: a prospective study of 11,896 young adults from four Finnish cohorts

AIMS/HYPOTHESIS

Metabolomics technologies have identified numerous blood biomarkers for type 2 diabetes risk in case-control studies of middle-aged and older individuals. We aimed to validate existing and identify novel metabolic biomarkers predictive of future diabetes in large cohorts of young adults.

METHODS

NMR metabolomics was used to quantify 229 circulating metabolic measures in 11,896 individuals from four Finnish observational cohorts (baseline age 24-45 years). Associations between baseline metabolites and risk of developing diabetes during 8-15 years of follow-up (392 incident cases) were adjusted for sex, age, BMI and fasting glucose. Prospective metabolite associations were also tested with fasting glucose, 2 h glucose and HOMA-IR at follow-up.

RESULTS

Out of 229 metabolic measures, 113 were associated with incident type 2 diabetes in meta-analysis of the four cohorts (ORs per 1 SD: 0.59-1.50; p< 0.0009). Among the strongest biomarkers of diabetes risk were branched-chain and aromatic amino acids (OR 1.31-1.33) and triacylglycerol within VLDL particles (OR 1.33-1.50), as well as linoleic n-6 fatty acid (OR 0.75) and non-esterified cholesterol in large HDL particles (OR 0.59). The metabolic biomarkers were more strongly associated with deterioration in post-load glucose and insulin resistance than with future fasting hyperglycaemia. A multi-metabolite score comprised of phenylalanine, non-esterified cholesterol in large HDL and the ratio of cholesteryl ester to total lipid in large VLDL was associated with future diabetes risk (OR 10.1 comparing individuals in upper vs lower fifth of the multi-metabolite score) in one of the cohorts (mean age 31 years).

CONCLUSIONS/INTERPRETATION

Metabolic biomarkers across multiple molecular pathways are already predictive of the long-term risk of diabetes in young adults. Comprehensive metabolic profiling may help to target preventive interventions for young asymptomatic individuals at increased risk.

Insulin resistance and systemic metabolic changes in oral glucose tolerance test in 5340 individuals: an interventional study

BACKGROUND

Insulin resistance (IR) is predictive for type 2 diabetes and associated with various metabolic abnormalities in fasting conditions. However, limited data are available on how IR affects metabolic responses in a non-fasting setting, yet this is the state people are mostly exposed to during waking hours in the modern society. Here, we aim to comprehensively characterise the metabolic changes in response to an oral glucose test (OGTT) and assess the associations of these changes with IR.

METHODS

Blood samples were obtained at 0 (fasting baseline, right before glucose ingestion), 30, 60, and 120 min during the OGTT. Seventy-eight metabolic measures were analysed at each time point for a discovery cohort of 4745 middle-aged Finnish individuals and a replication cohort of 595 senior Finnish participants. We assessed the metabolic changes in response to glucose ingestion (percentage change in relative to fasting baseline) across the four time points and further compared the response profile between five groups with different levels of IR and glucose intolerance. Further, the differences were tested for covariate adjustment, including gender, body mass index, systolic blood pressure, fasting, and 2-h glucose levels. The groups were defined as insulin sensitive with normal glucose (IS-NGT), insulin resistant with normal glucose (IR-NGT), impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and new diabetes (NDM). IS-NGT and IR-NGT were defined as the first and fourth quartile of fasting insulin in NGT individuals.

RESULTS

Glucose ingestion induced multiple metabolic responses, including increased glycolysis intermediates and decreased branched-chain amino acids, ketone bodies, glycerol, and triglycerides. The IR-NGT subgroup showed smaller responses for these measures (mean + 23%, interquartile 9-34% at 120 min) compared to IS-NGT (34%, 23-44%, P < 0.0006 for difference, corrected for multiple testing). Notably, the three groups with glucose abnormality (IFG, IGT, and NDM) showed similar metabolic dysregulations as those of IR-NGT. The difference between the IS-NGT and the other subgroups was largely explained by fasting insulin, but not fasting or 2 h glucose. The findings were consistent after covariate adjustment and between the discovery and replication cohort.

CONCLUSIONS

Insulin-resistant non-diabetic individuals are exposed to a similar adverse postprandial metabolic milieu, and analogous cardiometabolic risk, as those with type 2 diabetes. The wide range of metabolic abnormalities associated with IR highlights the necessity of diabetes diagnostics and clinical care beyond glucose management.

High-density lipoprotein cholesterol efflux capacity is not associated with atherosclerosis and prevalence of cardiovascular outcome: The CODAM study

BACKGROUND

Cholesterol Efflux Capacity (CEC) is considered to be a key atheroprotective property of high-density lipoproteins (HDL). However, the role of HDL-CEC in atherosclerosis and cardiovascular (CV) risk is still controversial, and data in individuals with diabetes are limited.

OBJECTIVE

In this study, we have investigated the relationship of CEC and other HDL characteristics with clinical and subclinical atherosclerosis in subjects with elevated cardiovascular diseases (CVD) risk and Type 2 Diabetes Mellitus (T2DM).

METHODS

Using multiple linear regression analyses, we determined the relationship of HDL-CEC with carotid intima-media thickness (cIMT, Z-Score), an endothelial dysfunction (EnD) Score (Z-Score), prevalent CVD (n = 150 cases) and history of CV events (CVE, n = 85 cases) in an observational cohort (CODAM, n = 574, 59.6 ± 0.3 yr, 61.3% men, 24.4% T2DM). Stratified analyses were performed to determine if the associations differed between individuals with normal glucose metabolism (NGM) and those with disturbed glucose metabolism.

RESULTS

HDL-CEC was not associated with either marker of atherosclerosis (cIMT, EnD Score) nor with CVD or CVE. In contrast, other HDL characteristics that is, HDL-Cholesterol (HDL-C, Z-Score), apolipoprotein A-I (apoA-I, Z-Score), HDL size (Z-Score) and HDL particle number (HDL-P, Z-Score) were inversely and significantly associated with the EnD Score (s -0.226 to -0.097, P < .05) and CVE (ORs 0.61 to 0.68, P < .05). In stratified analyses, HDL size and HDL-P were significantly associated with the EnD Score in individuals with NGM (P_interaction .039 and .005, respectively), but not in those with (pre)diabetes. HDL-C and apoA-I were inversely associated with prevalent CVD in individuals with (pre)diabetes (P_interaction = .074 and .034, respectively), but not in those with NGM.

CONCLUSION

HDL-CEC is not associated with clinical or subclinical atherosclerosis, neither in the whole population nor in individuals with (pre)diabetes, while other HDL characteristics show atheroprotective associations. The atheroprotective associations of HDL-size and HDL-P are lost in (pre)diabetes, while higher concentrations of HDL-C and apoA-I are associated with a lower prevalence of CVD in (pre)diabetes.

Elevated serum alpha-1 antitrypsin is a major component of GlycA-associated risk for future morbidity and mortality

Background

GlycA is a nuclear magnetic resonance (NMR) spectroscopy biomarker that predicts risk of disease from myriad causes. It is heterogeneous; arising from five circulating glycoproteins with dynamic concentrations: alpha-1 antitrypsin (AAT), alpha-1-acid glycoprotein (AGP), haptoglobin (HP), transferrin (TF), and alpha-1-antichymotrypsin (AACT). The contributions of each glycoprotein to the disease and mortality risks predicted by GlycA remain unknown.

Methods

We trained imputation models for AAT, AGP, HP, and TF from NMR metabolite measurements in 626 adults from a population cohort with matched NMR and immunoassay data. Levels of AAT, AGP, and HP were estimated in 11,861 adults from two population cohorts with eight years of follow-up, then each biomarker was tested for association with all common endpoints. Whole blood gene expression data was used to identify cellular processes associated with elevated AAT.

Results

Accurate imputation models were obtained for AAT, AGP, and HP but not for TF. While AGP had the strongest correlation with GlycA, our analysis revealed variation in imputed AAT levels was the most predictive of morbidity and mortality for the widest range of diseases over the eight year follow-up period, including heart failure (meta-analysis hazard ratio = 1.60 per standard deviation increase of AAT, P-value = 1×10⁻¹⁰), influenza and pneumonia (HR = 1.37, P = 6×10⁻¹⁰), and liver diseases (HR = 1.81, P = 1×10⁻⁶). Transcriptional analyses revealed association of elevated AAT with diverse inflammatory immune pathways.

Conclusions

This study clarifies the molecular underpinnings of the GlycA biomarker’s associated disease risk, and indicates a previously unrecognised association between elevated AAT and severe disease onset and mortality.

A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

Genetic studies of metabolites have identified thousands of variants, many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context-specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements, mostly lipids, across distinct time points as well as information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 228 new associations. Our analysis pinpoints a small number of master metabolic regulator genes, balancing the relative proportion of dozens of metabolite levels. We further identify associations to changes in metabolic levels across time as well as genetic interactions with statin at both the master metabolic regulator and genome-wide level.

Sex differences in postprandial responses to different dairy products on lipoprotein subclasses: a randomised controlled cross-over trial

Men have earlier first-time event of CHD and higher postprandial TAG response compared with women. The aim of this exploratory sub-study was to investigate if intake of meals with the same amount of fat from different dairy products affects postprandial lipoprotein subclasses differently in healthy women and men. A total of thirty-three women and fourteen men were recruited to a randomised controlled cross-over study with four dairy meals consisting of butter, cheese, whipped cream or sour cream, corresponding to 45 g of fat (approximately 60 energy percent). Blood samples were taken at 0, 2, 4 and 6 h postprandially. Lipoprotein subclasses were measured using NMR and analysed using a linear mixed model. Sex had a significant impact on the response in M-VLDL (P=0·04), S-LDL (P=0·05), XL-HDL (P=0·009) and L-HDL (P=0·001) particle concentration (P), with women having an overall smaller increase in M-VLDL-P, a larger decrease in S-LDL-P and a larger increase in XL- and L-HDL-P compared with men, independent of meal. Men showed a decrease in XS-VLDL-P compared with women after intake of sour cream (P<0·01). In men only, XS-VLDL-P decreased after intake of sour cream compared with all other meals (v. butter: P=0·001; v. cheese: P=0·04; v. whipped cream: P=0·006). Meals with the same amount of fat from different dairy products induce different postprandial effects on lipoprotein subclass concentrations in men and women.

A detailed lipoprotein profile in relation to intima-media thickness and echogenicity of three major arteries

OBJECTIVE

To investigate differences in risk-factor profile, with special emphasis on detailed characterization of the lipoprotein profile, for intima-media thickness (IMT) and echogenicity of the intima-media complex (IM-GSM) in three major arteries: the carotid, femoral and brachial arteries.

METHODS

IMT and IM-GSM were measured by ultrasound in the carotid, femoral and brachial arteries in 778 subjects, all aged 75 years (50% women), in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study, in which a detailed lipoprotein profile was also determined by nuclear magnetic resonance spectroscopy.

RESULTS

First, IMT was considerably lower, and IM-GSM higher, in the brachial artery compared to the other two arteries. Second, IMT and IM-GSM in the arteries were related to each other. Third, significant different traditional risk-factor profiles were seen for both IMT and IM-GSM, with generally weaker relationships for IMT in the femoral and brachial arteries compared with the carotid artery. Fourth, the strength of associations between an atherogenic lipoprotein profile and IMT in the carotid artery was attenuated in the femoral artery and virtually absent in the brachial artery. Fifth, slightly different lipoprotein profiles were seen for IM-GSM in the three arteries.

CONCLUSION

Differences between the carotid, femoral and brachial artery IMT and IM-GSM were seen regarding the traditional risk factors, as well as the lipoprotein profile.

Total liver phosphatidylcholine content associates with non-alcoholic steatohepatitis and glycine N-methyltransferase expression

BACKGROUND & AIMS

Alterations in liver phosphatidylcholine (PC) metabolism have been implicated in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Although genetic variation in the phosphatidylethanolamine N-methyltransferase (PEMT) enzyme synthesizing PC has been associated with disease, the functional mechanism linking PC metabolism to the pathogenesis of non-alcoholic steatohepatitis (NASH) remains unclear.

METHODS

Serum PC levels and liver PC contents were measured using proton nuclear magnetic resonance (NMR) spectroscopy in 169 obese individuals [age 46.6 ± 10 (mean ± SD) years, BMI 43.3 ± 6 kg/m² , 53 men and 116 women] with histological assessment of NAFLD; 106 of these had a distinct liver phenotype. All subjects were genotyped for PEMT rs7946 and liver mRNA expression of PEMT and glycine N-methyltransferase (GNMT) was analysed.

RESULTS

Liver PC content was lower in those with NASH (P = 1.8 x 10^-6 ) while serum PC levels did not differ between individuals with NASH and normal liver (P = 0.591). Interestingly, serum and liver PC did not correlate (r_s  = -0.047, P = 0.557). Serum PC and serum cholesterol levels correlated strongly (r_s  = 0.866, P = 7.1 x 10^-49 ), while liver PC content did not correlate with serum cholesterol (r_s  = 0.065, P = 0.413). Neither PEMT V175M genotype nor PEMT expression explained the association between liver PC content and NASH. Instead, liver GNMT mRNA expression was decreased in those with NASH (P = 3.8 x 10^-4 ) and correlated with liver PC content (r_s  = 0.265, P = 0.001).

CONCLUSIONS

Decreased liver PC content in individuals with the NASH is independent of PEMT V175M genotype and could be partly linked to decreased GNMT expression.

Associations between Blood Metabolic Profile at 7 Years Old and Eating Disorders in Adolescence: Findings from the Avon Longitudinal Study of Parents and Children

Eating disorders are severe illnesses characterized by both psychiatric and metabolic factors. We explored the prospective role of metabolic risk in eating disorders in a UK cohort (n = 2929 participants), measuring 158 metabolic traits in non-fasting EDTA-plasma by nuclear magnetic resonance. We associated metabolic markers at 7 years (exposure) with risk for anorexia nervosa and binge-eating disorder (outcomes) at 14, 16, and 18 years using logistic regression adjusted for maternal education, child’s sex, age, body mass index, and calorie intake at 7 years. Elevated very low-density lipoproteins, triglycerides, apolipoprotein-B/A, and monounsaturated fatty acids ratio were associated with lower odds of anorexia nervosa at age 18, while elevated high-density lipoproteins, docosahexaenoic acid and polyunsaturated fatty acids ratio, and fatty acid unsaturation were associated with higher risk for anorexia nervosa at 18 years. Elevated linoleic acid and n-6 fatty acid ratios were associated with lower odds of binge-eating disorder at 16 years, while elevated saturated fatty acid ratio was associated with higher odds of binge-eating disorder. Most associations had large confidence intervals and showed, for anorexia nervosa, different directions across time points. Overall, our results show some evidence for a role of metabolic factors in eating disorders development in adolescence.

Metabolic profiling of adolescent non-alcoholic fatty liver disease

Background: Adolescent non-alcoholic fatty liver disease (NAFLD) is associated with cardiometabolic risk factors. The association between adolescent NAFLD and a wide range of metabolic biomarkers is unclear. We have attempted to determine the differences in metabolic profile of adolescents with and without markers of NAFLD. Methods: We performed cross-sectional analyses in a sample of 3,048 participants from the Avon Longitudinal Study of Parents and Children at age 17. We used three indicators of NAFLD: ALT >40 U/l; AST >40 U/l and ultrasound scan-assessed steatosis. Associations between each measure of NAFLD and 154 metabolic traits, assessed by Nuclear Magnetic Resonance, were analyzed by multivariable linear regression, adjusting for age, sex and BMI. Results: All three indicators of NAFLD were associated with ~0.5 standard deviation (SD) greater concentrations of all extremely large to small very low-density lipoproteins (VLDL) measures. ALT >40U/l was associated with ~0.5SD greater concentrations of very small VLDLs, intermediate-density lipoproteins and low-density lipoproteins. Concentrations of most cholesterols, including remnant cholesterol, all triglycerides and monounsaturated fatty acids, in addition to glycoprotein acetyls (inflammatory marker), were also higher in participants with NAFLD. Conclusions: We have identified differing metabolic profiles between adolescents with and without indicators of NAFLD. These results provide the foundations for future research to determine whether these differences persist and result in adverse future cardiometabolic health.

Metabolic profiling of adolescent non-alcoholic fatty liver disease

Background: Adolescent non-alcoholic fatty liver disease (NAFLD) is associated with cardiometabolic risk factors. The association between adolescent NAFLD and a wide range of metabolic biomarkers is unclear. We have attempted to determine the differences in metabolic profile of adolescents with and without markers of NAFLD. Methods: We performed cross-sectional analyses in a sample of 3,048 participants from the Avon Longitudinal Study of Parents and Children at age 17. We used three indicators of NAFLD: ALT >40 U/l; AST >40 U/l and ultrasound scan-assessed steatosis. Associations between each measure of NAFLD and 154 metabolic traits, assessed by Nuclear Magnetic Resonance, were analyzed by multivariable linear regression, adjusting for age, sex and BMI. Results: All three indicators of NAFLD were associated with ~0.5 standard deviation (SD) greater concentrations of all extremely large to small very low-density lipoproteins (VLDL) measures. ALT >40U/l was associated with ~0.5SD greater concentrations of very small VLDLs, intermediate-density lipoproteins and low-density lipoproteins. Concentrations of most cholesterols, including remnant cholesterol, all triglycerides and monounsaturated fatty acids, in addition to glycoprotein acetyls (inflammatory marker), were also higher in participants with NAFLD. Conclusions: We have identified differing metabolic profiles between adolescents with and without indicators of NAFLD. These results provide the foundations for future research to determine whether these differences persist and result in adverse future cardiometabolic health.

Differences in Pregnancy Metabolic Profiles and Their Determinants between White European and South Asian Women: Findings from the Born in Bradford Cohort

There is widespread metabolic disruption in women upon becoming pregnant. South Asians (SA) compared to White Europeans (WE) have more fat mass and are more insulin-resistant at a given body mass index (BMI). Whether these are reflected in other gestational metabolomic differences is unclear. Our aim was to compare gestational metabolic profiles and their determinants between WE and SA women. We used data from a United Kingdom (UK) cohort to compare metabolic profiles and associations of maternal age, education, parity, height, BMI, tricep skinfold thickness, gestational diabetes (GD), pre-eclampsia, and gestational hypertension with 156 metabolic measurements in WE (n = 4072) and SA (n = 4702) women. Metabolic profiles, measured in fasting serum taken between 26–28 weeks gestation, were quantified by nuclear magnetic resonance. Distributions of most metabolic measures differed by ethnicity. WE women had higher levels of most lipoprotein subclasses, cholesterol, glycerides and phospholipids, monosaturated fatty acids, and creatinine but lower levels of glucose, linoleic acid, omega-6 and polyunsaturated fatty acids, and most amino acids. Higher BMI and having GD were associated with higher levels of several lipoprotein subclasses, triglycerides, and other metabolites, mostly with stronger associations in WEs. We have shown differences in gestational metabolic profiles between WE and SA women and demonstrated that associations of exposures with these metabolites differ by ethnicity.

A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals

Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18-109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.

Exome sequencing of Finnish isolates enhances rare-variant association power

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

A Cross-Cohort Study Examining the Associations of Metabolomic Profile and Subclinical Atherosclerosis in Children and Their Parents: The Child Health CheckPoint Study and Avon Longitudinal Study of Parents and Children

Background High-throughput nuclear magnetic resonance profiling of circulating metabolites is suggested as an adjunct for cardiovascular risk evaluation. The relationship between metabolites and subclinical atherosclerosis remains unclear, particularly among children. Therefore, we examined the associations of metabolites with carotid intima-media thickness ( cIMT ) and arterial pulse wave velocity ( PWV ). Methods and Results Data from two independent population-based studies was examined; (1) cross-sectional associations with cIMT and PWV in 1178 children (age 11-12 years, 51% female) and 1316 parents (mean age 45 years, 87% female) from the CheckPoint study (Australia); and (2) longitudinal associations in 4249 children (metabolites at 7-8 years, PWV at 10-11 years, 52% female), and cross-sectional associations in 4171 of their mothers (mean age 48 years, cIMT data) from ALSPAC (The Avon Longitudinal Study of Parents and Children; UK ). Metabolites were measured by the same nuclear magnetic resonance platform in both studies, comprising of 69 biomarkers. Biophysical assessments included body mass index, blood pressure, cIMT and PWV . In linear regression analyses adjusted for age, sex, body mass index, and blood pressure, there was no evidence of metabolite associations in either children or adults for cIMT at a 10% false discovery threshold. In CheckPoint adults, glucose was positively, and some high-density lipoprotein-cholesterol derived measures and amino acids (glutamine, histidine, tyrosine) inversely associated with PWV. Conclusions These data suggest that in children circulating metabolites have no consistent association with cIMT and PWV once adjusted for body mass index and blood pressure. In their middle-aged parents, some evidence of metabolite associations with PWV were identified that warrant further investigation.

Metabolomics: population epidemiology and concordance in Australian children aged 11-12 years and their parents

OBJECTIVES

Nuclear magnetic resonance (NMR) metabolomics is high throughput and cost-effective, with the potential to improve the understanding of disease and risk. We examine the circulating metabolic profile by quantitative NMR metabolomics of a sample of Australian 11-12 year olds children and their parents, describe differences by age and sex, and explore the correlation of metabolites in parent-child dyads.

DESIGN

The population-based cross-sectional Child Health CheckPoint study nested within the Longitudinal Study of Australian Children.

SETTING

Blood samples collected from CheckPoint participants at assessment centres in seven Australian cities and eight regional towns; February 2015-March 2016.

PARTICIPANTS

1180 children and 1325 parents provided a blood sample and had metabolomics data available. This included 1133 parent-child dyads (518 mother-daughter, 469 mother-son, 68 father-daughter and 78 father-son).

OUTCOME MEASURES

228 metabolic measures were obtained for each participant. We focused on 74 biomarkers including amino acid species, lipoprotein subclass measures, lipids, fatty acids, measures related to fatty acid saturation, and composite markers of inflammation and energy homeostasis.

RESULTS

We identified differences in the concentration of specific metabolites between childhood and adulthood and in metabolic profiles in children and adults by sex. In general, metabolite concentrations were higher in adults than children and sex differences were larger in adults than in children. Positive correlations were observed for the majority of metabolites including isoleucine (CC 0.33, 95% CI 0.27 to 0.38), total cholesterol (CC 0.30, 95% CI 0.24 to 0.35) and omega 6 fatty acids (CC 0.28, 95% CI 0.23 to 0.34) in parent-child comparisons.

CONCLUSIONS

We describe the serum metabolite profiles from mid-childhood and adulthood in a population-based sample, together with a parent-child concordance. Differences in profiles by age and sex were observed. These data will be informative for investigation of the childhood origins of adult non-communicable diseases and for comparative studies in other populations.

Food neophobia associates with poorer dietary quality, metabolic risk factors, and increased disease outcome risk in population-based cohorts in a metabolomics study

BACKGROUND

Food neophobia is considered a behavioral trait closely linked to adverse eating patterns and reduced dietary quality, which have been associated with increased risk of obesity and noncommunicable diseases.

OBJECTIVES

In a cross-sectional and prospective study, we examined how food neophobia is associated with dietary quality, health-related biomarkers, and disease outcome incidence in Finnish and Estonian adult populations.

METHODS

The study was conducted based on subsamples of the Finnish DIetary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) cohort (n = 2982; age range: 25-74 y) and the Estonian Biobank cohort (n = 1109; age range: 18-83 y). The level of food neophobia was assessed using the Food Neophobia Scale, dietary quality was evaluated using the Baltic Sea Diet Score (BSDS), and biomarker profiles were determined using an NMR metabolomics platform. Disease outcome information was gathered from national health registries. Follow-up data on the NMR-based metabolomic profiles and disease outcomes were available in both populations.

RESULTS

Food neophobia associated significantly (adjusted P < 0.05) with health-related biomarkers [e.g., ω-3 (n-3) fatty acids, citrate, α1-acid glycoprotein, HDL, and MUFA] in the Finnish DILGOM cohort. The significant negative association between the severity of food neophobia and ω-3 fatty acids was replicated in all cross-sectional analyses in the Finnish DILGOM and Estonian Biobank cohorts. Furthermore, food neophobia was associated with reduced dietary quality (BSDS: β: -0.03 ± 0.006; P = 8.04 × 10-5), increased fasting serum insulin (β: 0.004 ± 0.0013; P = 5.83 × 10-3), and increased risk of type 2 diabetes during the ∼8-y follow-up (HR: 1.018 ± 0.007; P = 0.01) in the DILGOM cohort.

CONCLUSIONS

In the Finnish and Estonian adult populations, food neophobia was associated with adverse alteration of health-related biomarkers and risk factors that have been associated with an increased risk of noncommunicable diseases. We also found that food neophobia associations with ω-3 fatty acids and associated metabolites are mediated through dietary quality independent of body weight.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

Metabolomic discrimination of the edible mushrooms Kuehneromyces mutabilis and Hypholoma capnoides (Strophariaceae, Agaricales) by NMR spectroscopy

Two edible, cultivable mushroom species of the family Strophariaceae, Kuehneromyces mutabilis (sheathed woodtuft) and Hypholoma capnoides (conifer tuft), were studied using proton nuclear magnetic resonance metabolomic approach. The variation in the metabolites of the two species and their metabolic behaviour regarding caps and stipes and different collection sites were analysed by multivariate analysis methods. Altogether 169 cap and stipe samples of the mushrooms were investigated. The clearest difference between the species was in the sugar composition, which was more diverse in H. capnoides. When mushroom samples collected from different locations were compared, more variance was found in H. capnoides, whereas K. mutabilis appeared more homogeneous as a species. As far as the caps and stipes were concerned, in both species the amount of α-α-trehalose was clearly higher in the stipes, and the caps contained a larger proportion of the amino acids and organic acids.

Associations of physical activity and sedentary time with lipoprotein subclasses in Norwegian schoolchildren: The Active Smarter Kids (ASK) study

BACKGROUND AND AIMS

Physical activity is favourably associated with certain markers of lipid metabolism. The relationship of physical activity with lipoprotein particle profiles in children is not known. Here we examine cross-sectional associations between objectively measured physical activity and sedentary time with serum markers of lipoprotein metabolism.

METHODS

Our cohort included 880 children (49.0% girls, mean age 10.2 years). Physical activity intensity and time spent sedentary were measured objectively using accelerometers. 30 measures of lipoprotein metabolism were quantified using nuclear magnetic resonance spectroscopy. Multiple linear regression models adjusted for age, sex, sexual maturity and socioeconomic status were used to determine associations of physical activity and sedentary time with lipoprotein measures. Additional models were adjusted for adiposity. Isotemporal substitution models quantified theoretical associations of replacing 30 min of sedentary time with 30 min of moderate- to vigorous-intensity physical activity (MVPA).

RESULTS

Time spent in MVPA was associated with a favourable lipoprotein profile independent of sedentary time. There were inverse associations with a number of lipoprotein measures, including most apolipoprotein B-containing lipoprotein subclasses and triglyceride measures, the ratio of total to high-density lipoprotein (HDL) cholesterol, and non-HDL cholesterol concentration. There were positive associations with larger HDL subclasses, HDL cholesterol concentration and particle size. Reallocating 30 min of sedentary time to MVPA had broadly similar associations. Sedentary time was only partly and weakly associated with an unfavourable lipoprotein profile.

CONCLUSIONS

Physical activity of at least moderate-intensity is associated with a favourable lipoprotein profile in schoolchildren, independent of time spent sedentary, adiposity and other confounders.

Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics

BACKGROUND

Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available.

METHODS

We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548).

RESULTS

Intra-assay metabolite variations were mostly <5%, indicating high robustness and accuracy of urine NMR spectroscopy methodology per se. Intra-individual metabolite variations were large, ranging from 6% to 194%. However, population-based inter-individual metabolite variations were even larger (from 14% to 1655%), providing a sound base for epidemiological applications. Metabolic associations between urine and serum were found to be clearly weaker than those within serum and within urine, indicating that urinary metabolomics data provide independent metabolic information. Two previous genome-wide hits for formate and 2-hydroxyisobutyrate were replicated at genome-wide significance.

CONCLUSION

Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided.

Epidemiologists of the Future: Data Collectors or Scientists?

Epidemiology is the study of epidemics. It is a biological science that includes expertise in many disciplines in social and behavioral sciences. Epidemiology is also a key component of preventive medicine and public health. Unfortunately, over recent years, academic epidemiology has lost its relationship with preventive medicine, as well as much of its focus on epidemics. The new "-omics" technologies to measure risk factors and phenotypes, and advances in genomics (e.g., host susceptibility) consistent with good epidemiology methods will likely enhance epidemiology research. There is a need based on these new technologies to modify training, especially for the first-level doctorate epidemiologist.

Disentangling the Effects of Monounsaturated Fatty Acids from Other Components of a Mediterranean Diet on Serum Metabolite Profiles: A Randomized Fully Controlled Dietary Intervention in Healthy Subjects at Risk of the Metabolic Syndrome

SCOPE

The Mediterranean (MED) diet has been associated with a decreased risk of cardiovascular diseases. It is unclear whether this health effect can be mainly contributed to high intakes of monounsaturated fatty acids (MUFA), characteristic for the MED diet, or whether other components of a MED diet also play an important role.

METHODS AND RESULTS

A randomized fully controlled parallel trial is performed to examine the effects of the consumption of a saturated fatty acid rich diet, a MUFA-rich diet, or a MED diet for 8 weeks on metabolite profiles, in 47 subjects at risk of the metabolic syndrome. A total of 162 serum metabolites are assessed before and after the intervention by using a targeted NMR platform. Fifty-two metabolites are changed during the intervention (false discovery rate [FDR] p < 0.05). Both the MUFA and MED diet decrease exactly the same fractions of LDL, including particle number, lipid, phospholipid, and free cholesterol fraction (FDR p < 0.05). The MED diet additionally decreases the larger subclasses of very-low-density lipoprotein (VLDL), related VLDL fractions, VLDL-triglycerides, and serum-triglycerides (FDR p < 0.05).

CONCLUSION

The findings clearly demonstrate that the MUFA component is responsible for reducing LDL subclasses and fractions, and therefore causes an antiatherogenic lipid profile. Interestingly, consumption of the other components in the MED diet show additional health effects.

Direct Estimation of HDL-Mediated Cholesterol Efflux Capacity from Serum

BACKGROUND

HDL-mediated cholesterol efflux capacity (HDL-CEC) is a functional attribute that may have a protective role in atherogenesis. However, the estimation of HDL-CEC is based on in vitro cell assays that are laborious and hamper large-scale phenotyping.

METHODS

Here, we present a cost-effective high-throughput nuclear magnetic resonance (NMR) spectroscopy method to estimate HDL-CEC directly from serum. We applied the new method in a population-based study of 7603 individuals including 574 who developed incident coronary heart disease (CHD) during 15 years of follow-up, making this the largest quantitative study for HDL-CEC.

RESULTS

As estimated by NMR-spectroscopy, a 1-SD higher HDL-CEC was associated with a lower risk of incident CHD (hazards ratio, 0.86; 95%CI, 0.79-0.93, adjusted for traditional risk factors and HDL-C). These findings are consistent with published associations based on in vitro cell assays.

CONCLUSIONS

These corroborative large-scale findings provide further support for a potential protective role of HDL-CEC in CHD and substantiate this new method and its future applications.

Resistance Training Induces Antiatherogenic Effects on Metabolomic Pathways

INTRODUCTION

Arising evidence suggests that resistance training has the potential to induce beneficial modulation of biomarker profile. To date, however, only immediate responses to resistance training have been investigated using high-throughput metabolomics whereas the effects of chronic resistance training on biomarker profile have not been studied in detail.

METHODS

A total of 86 recreationally active healthy men without previous systematic resistance training background were allocated into (i) a resistance training (RT) group (n = 68; age, 33 ± 7 yr; body mass index, 28 ± 3 kg·m) and (ii) a non-RT group (n = 18; age, 31 ± 4 yr; body mass index, 27 ± 3 kg·m). Blood samples were collected at baseline (PRE), after 4 wk (POST-4wk), and after 16 wk of resistance training intervention (POST-16wk), as well as baseline and after the non-RT period (20-24 wk). Nuclear magnetic resonance-metabolome platform was used to determine metabolomic responses to chronic resistance training.

RESULTS

Overall, the resistance training intervention resulted in favorable alterations (P < 0.05) in body composition with increased levels of lean mass (~2.8%), decreased levels of android (~9.6%), and total fat mass (~7.5%). These changes in body composition were accompanied by antiatherogenic alterations in serum metabolome profile (false discovery rate < 0.05) as reductions in non-high-density lipoprotein cholesterol (e.g., free cholesterol, remnant cholesterol, intermediate-density lipoprotein cholesterols, low-density lipoprotein cholesterols) and related apolipoprotein B, and increments in conjugated linoleic fatty acids levels were observed. Individuals with the poorest baseline status (i.e., body composition, metabolome profile) benefitted the most from the resistance training intervention.

CONCLUSIONS

In conclusion, resistance training improves cardiometabolic risk factors and serum metabolome even in previously healthy young men. Thus, suggesting attenuated risk for future cardiovascular disease.

Gut Microbial Associations to Plasma Metabolites Linked to Cardiovascular Phenotypes and Risk

RATIONALE

Altered gut microbial composition has been linked to cardiovascular diseases (CVDs), but its functional links to host metabolism and immunity in relation to CVD development remain unclear.

OBJECTIVES

To systematically assess functional links between the microbiome and the plasma metabolome, cardiometabolic phenotypes, and CVD risk and to identify diet-microbe-metabolism-immune interactions in well-documented cohorts.

METHODS AND RESULTS

We assessed metagenomics-based microbial associations between 231 plasma metabolites and microbial species and pathways in the population-based LLD (Lifelines DEEP) cohort (n=978) and a clinical obesity cohort (n=297). After correcting for age, sex, and body mass index, the gut microbiome could explain ≤11.1% and 16.4% of the variation in plasma metabolites in the population-based and obesity cohorts, respectively. Obese-specific microbial associations were found for lipid compositions in the VLDL, IDL, and LDL lipoprotein subclasses. Bacterial L-methionine biosynthesis and a Ruminococcus species were associated to cardiovascular phenotypes in obese individuals, namely atherosclerosis and liver fat content, respectively. Integration of microbiome-diet-inflammation analysis in relation to metabolic risk score of CVD in the population cohort revealed 48 microbial pathways associated to CVD risk that were largely independent of diet and inflammation. Our data also showed that plasma levels rather than fecal levels of short-chain fatty acids were relevant to inflammation and CVD risk.

CONCLUSIONS

This study presents the largest metagenome-based association study on plasma metabolism and microbiome relevance to diet, inflammation, CVD risk, and cardiometabolic phenotypes in both population-based and clinical obesity cohorts. Our findings identified novel bacterial species and pathways that associated to specific lipoprotein subclasses and revealed functional links between the gut microbiome and host health that provide a basis for developing microbiome-targeted therapy for disease prevention and treatment.

Delayed postprandial TAG peak after intake of SFA compared with PUFA in subjects with and without familial hypercholesterolaemia: a randomised controlled trial

Postprandial hypertriacylglycerolaemia is associated with an increased risk of developing CVD. How fat quality influences postprandial lipid response is scarcely explored in subjects with familial hypercholesterolaemia (FH). The aim of this study was to investigate the postprandial response of TAG and lipid sub-classes after consumption of high-fat meals with different fat quality in subjects with FH compared with normolipidaemic controls. A randomised controlled double-blind cross-over study with two meals and two groups was performed. A total of thirteen hypercholesterolaemic subjects with FH who discontinued lipid-lowering treatment 4 weeks before and during the study, and fourteen normolipidaemic controls, were included. Subjects were aged 18-30 years and had a BMI of 18·5-30·0 kg/m2. Each meal consisted of a muffin containing 60 g (70 E%) of fat, either mainly SFA (40 E%) or PUFA (40 E%), eaten in a random order with a wash-out period of 3-5 weeks between the meals. Blood samples were collected at baseline (fasting) and 2, 4 and 6 h after intake of the meals. In both FH and control subjects, the level of TAG and the largest VLDL sub-classes peaked at 2 h after intake of PUFA and at 4 h after intake of SFA. No significant differences were found in TAG levels between meals or between groups (0·25≤P≤0·72). The distinct TAG peaks may reflect differences in the postprandial lipid metabolism after intake of fatty acids with different chain lengths and degrees of saturation. The clinical impact of these findings remains to be determined.

The Effect of Pre-Analytical Conditions on Blood Metabolomics in Epidemiological Studies

Serum and plasma are commonly used in metabolomic-epidemiology studies. Their metabolome is susceptible to differences in pre-analytical conditions and the impact of this is unclear. Participant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (n = 151 traits). Correlations and differences in mean of metabolite concentrations were compared between reference (pre-storage: 4 °C, 1.5 h; post-storage: no buffer addition delay or NMR analysis delay) and four pre-storage blood processing conditions, where samples were incubated at (i) 4 °C, 24 h; (ii) 4 °C, 48 h; (iii) 21 °C, 24 h; and (iv) 21 °C, 48 h, before centrifugation; and two post-storage sample processing conditions in which samples thawed overnight (i) then left for 24 h before addition of sodium buffer followed by immediate NMR analysis; and (ii) addition of sodium buffer, then left for 24 h before NMR profiling. We used multilevel linear regression models and Spearman’s rank correlation coefficients to analyse the data. Most metabolic traits had high rank correlation and minimal differences in mean concentrations between samples subjected to reference and the different conditions tested, that may commonly occur in studies. However, glycolysis metabolites, histidine, acetate and diacylglycerol concentrations may be compromised and this could bias results in association/causal analyses.

GlycA, a Nuclear Magnetic Resonance Spectroscopy Measure for Protein Glycosylation, is a Viable Biomarker for Disease Activity in IBD

BACKGROUND AND AIMS

Glycoprotein acetylation [GlycA] is a novel nuclear magnetic resonance [NMR] biomarker, measured in serum or plasma, that summarizes the signals originating from glycan groups of certain acute-phase glycoproteins. This biomarker has been shown to be robustly associated with cardiovascular and short-term all-cause mortality, and with disease severity in several inflammatory conditions. We investigated GlycA levels in a cohort of healthy individuals [HCs], patients with Crohn's disease [CD] and patients with ulcerative colitis [UC] prior to and after therapeutic control of inflammation.

METHODS

Serum samples of 10 HCs, 37 CD patients and 21 UC patients before and after biologic therapy were subjected to high-throughput NMR analysis by Nightingale Health Ltd. Paired C-reactive protein [CRP] and fecal calprotectin [fCal] measurements were used to characterize baseline differences, treatment effects and post-treatment association with endoscopic response [50% SES-CD decrease at Week 24] and mucosal healing [SES-CD ≤ 2 for CD, Mayo endoscopic score ≤ 1 for UC].

RESULTS

GlycA levels were significantly higher in patients with active inflammamtory bowel disease [IBD] compared with those in healthy controls, and accurately reflected the mucosal recovery to a 'healthy' state in both CD and UC patients achieving mucosal healing. In CD patients who experienced an endoscopic response without achieving full mucosal healing, GlycA levels also decreased but did not normalize to HC levels. Overall, GlycA correlated well with CRP and fCal, and accurately tracked disease activity in CRP-negative patients [<5 mg/dL].

CONCLUSION

GlycA holds promise as a viable serological biomarker for disease activity in IBD, even in patients without elevated CRP, and should therefore be tested in large prospective cohorts.

NAFLD risk alleles in PNPLA3, TM6SF2, GCKR and LYPLAL1 show divergent metabolic effects

Fatty liver has been associated with unfavourable metabolic changes in circulation. To provide insights in fatty liver-related metabolic deviations, we compared metabolic association profile of fatty liver versus metabolic association profiles of genotypes increasing the risk of non-alcoholic fatty liver disease (NAFLD). The cross-sectional associations of ultrasound-ascertained fatty liver with 123 metabolic measures were determined in 1810 (N_{fatty liver} = 338) individuals aged 34–49 years from The Cardiovascular Risk in Young Finns Study. The association profiles of NAFLD-risk alleles in PNPLA3, TM6SF2, GCKR, and LYPLAL1 with the corresponding metabolic measures were obtained from a publicly available metabolomics GWAS including up to 24 925 Europeans. The risk alleles showed different metabolic effects: PNPLA3 rs738409-G, the strongest genetic NAFLD risk factor, did not associate with metabolic changes. Metabolic effects of GCKR rs1260326-T were comparable in many respects to the fatty liver associations. Metabolic effects of LYPLAL1 rs12137855-C were similar, but statistically less robust, to the effects of GCKR rs1260326-T. TM6SF2 rs58542926-T displayed opposite metabolic effects when compared with the fatty liver associations. The metabolic effects of the risk alleles highlight heterogeneity of the molecular pathways leading to fatty liver and suggest that the fatty liver-related changes in the circulating lipids and metabolites may vary depending on the underlying pathophysiological mechanism. Despite the robust cross-sectional associations on population level, the present results showing neutral or cardioprotective metabolic effects for some of the NAFLD risk alleles advocate that hepatic lipid accumulation by itself may not increase the level of circulating lipids or other metabolites.

The second generation of The Avon Longitudinal Study of Parents and Children (ALSPAC-G2): a cohort profile

Background: The Avon Longitudinal Study of Parents and Children-Generation 2 (ALSPAC-G2) was set up to provide a unique multi-generational cohort. It builds on the existing ALSPAC resource, which recruited 14,541 pregnancies to women resident in the South West of England who were expected to deliver between 01/04/1991 and 31/12/1992. Those women and their partners (Generation 0; ALSPAC-G0) and their offspring (ALSPAC-G1) have been followed for the last 26 years. This profile describes recruitment and data collection on the next generation (ALSPAC-G2)-the grandchildren of ALSPAC-G0 and children of ALSPAC-G1. Recruitment: Recruitment began on the 6 th of June 2012 and we present details of recruitment and participants up to 30 th June 2018 (~6 years). We knew at the start of recruitment that some ALSPAC-G1 participants had already become parents and ALSPAC-G2 is an open cohort; we recruit at any age. We hope to continue recruiting until all ALSPAC-G1 participants have completed their families. Up to 30 th June 2018 we recruited 810 ALSPAC-G2 participants from 548 families. Of these 810, 389 (48%) were recruited during their mother's pregnancy, 287 (35%) before age 3 years, 104 (13%) between 3-6 years and 30 (4%) after 6 years. Over 70% of those invited to early pregnancy, late pregnancy, second week of life, 6-, 12- and 24-month assessments (whether for their recruitment, or a follow-up, visit) have attended, with attendance being over 60% for subsequent visits up to 7 years (to few are eligible for the 9- and 11-year assessments to analyse). Data collection: We collect a wide-range of social, lifestyle, clinical, anthropometric and biological data on all family members repeatedly. Biological samples include blood (including cord-blood), urine, meconium and faeces, and placental tissue. In subgroups detailed data collection, such as continuous glucose monitoring and videos of parent-child interactions, are being collected.

The second generation of The Avon Longitudinal Study of Parents and Children (ALSPAC-G2): a cohort profile

Background: The Avon Longitudinal Study of Parents and Children-Generation 2 (ALSPAC-G2) was set up to provide a unique multi-generational cohort. It builds on the existing ALSPAC resource, which recruited 14,541 pregnancies to women resident in the South West of England who were expected to deliver between 01/04/1991 and 31/12/1992. Those women and their partners (Generation 0; ALSPAC-G0) and their offspring (ALSPAC-G1) have been followed for the last 26 years. This profile describes recruitment and data collection on the next generation (ALSPAC-G2)-the grandchildren of ALSPAC-G0 and children of ALSPAC-G1. Recruitment: Recruitment began on the 6 ^th of June 2012 and we present details of recruitment and participants up to 30 ^th June 2018 (~6 years). We knew at the start of recruitment that some ALSPAC-G1 participants had already become parents and ALSPAC-G2 is an open cohort; we recruit at any age. We hope to continue recruiting until all ALSPAC-G1 participants have completed their families. Up to 30 ^th June 2018 we recruited 810 ALSPAC-G2 participants from 548 families. Of these 810, 389 (48%) were recruited during their mother's pregnancy, 287 (35%) before age 3 years, 104 (13%) between 3-6 years and 30 (4%) after 6 years. Over 70% of those invited to early pregnancy, late pregnancy, second week of life, 6-, 12- and 24-month assessments (whether for their recruitment, or a follow-up, visit) have attended, with attendance being over 60% for subsequent visits up to 7 years (to few are eligible for the 9- and 11-year assessments to analyse). Data collection: We collect a wide-range of social, lifestyle, clinical, anthropometric and biological data on all family members repeatedly. Biological samples include blood (including cord-blood), urine, meconium and faeces, and placental tissue. In subgroups detailed data collection, such as continuous glucose monitoring and videos of parent-child interactions, are being collected.

The effect of apolipoprotein E polymorphism on serum metabolome - a population-based 10-year follow-up study

Apolipoprotein E (apoE) is the key regulator of plasma lipids, mediating altered functionalities in lipoprotein metabolism - affecting the risk of coronary artery (CAD) and Alzheimer's diseases, as well as longevity. Searching pathways influenced by apoE prior to adverse manifestations, we utilized a metabolome dataset of 228 nuclear-magnetic-resonance-measured serum parameters with a 10-year follow-up from the population-based Young Finns Study cohort of 2,234 apoE-genotyped (rs7412, rs429358) adults, aged 24-39 at baseline. At the end of our follow-up, by limiting FDR-corrected p < 0.05, regression analyses revealed 180/228 apoE-polymorphism-related associations with the studied metabolites, in all subjects - without indications of apoE x sex interactions. Across all measured apoE- and apoB-containing lipoproteins, ε4 allele had consistently atherogenic and ε2 protective effect on particle concentrations of free/esterified cholesterol, triglycerides, phospholipids and total lipids. As novel findings, ε4 associated with glycoprotein acetyls, LDL-diameter and isoleucine - all reported biomarkers of CAD-risk, inflammation, diabetes and total mortality. ApoE-subgroup differences persisted through our 10-year follow-up, although some variation of individual metabolite levels was noticed. In conclusion, apoE polymorphism associate with a complex metabolic change, including aberrations in multiple novel biomarkers related to elevated cardiometabolic and all-cause mortality risk, extending our understanding about the role of apoE in health and disease.

Development of a rapid profiling method for the analysis of polar analytes in urine using HILIC-MS and ion mobility enabled HILIC-MS

INTRODUCTION

As large scale metabolic phenotyping is increasingly employed in preclinical studies and in the investigation of human health and disease the current LC-MS/MS profiling methodologies adopted for large sample sets can result in lengthy analysis times, putting strain on available resources. As a result of these pressures rapid methods of untargeted analysis may have value where large numbers of samples require screening.

OBJECTIVES

To develop, characterise and evaluate a rapid UHP-HILIC-MS-based method for the analysis of polar metabolites in rat urine and then extend the capabilities of this approach by the addition of IMS to the system.

METHODS

A rapid untargeted HILIC LC-MS/MS profiling method for the analysis of small polar molecules has been developed. The 3.3 min separation used a Waters BEH amide (1 mm ID) analytical column on a Waters Synapt G2-Si Q-Tof enabled with ion mobility spectrometry (IMS). The methodology, was applied to the metabolic profiling of a series of rodent urine samples from vehicle-treated control rats and animals administered tienilic acid. The same separation was subsequently linked to IMS and MS to evaluate the benefits that IMS might provide for metabolome characterisation.

RESULTS

The rapid HILIC-MS method was successfully applied to rapid analysis of rat urine and found, based on the data generated from the data acquired for the pooled quality control samples analysed at regular intervals throughout the analysis, to be robust. Peak area and retention times for the compounds detected in these samples showed good reproducibility across the batch. When used to profile the urine samples obtained from vehicle-dosed control and those administered tienilic acid the HILIC-MS method detected 3007 mass/retention time features. Analysis of the same samples using HILIC-IMS-MS enabled the detection of 6711 features. Provisional metabolite identification for a number of compounds was performed using the high collision energy MS/MS information compared against the Metlin MS/MS database and, in addition, both calculated and measured CCS values from an experimentally derived CCS database.

CONCLUSION

A rapid metabolic profiling method for the analysis of polar metabolites has been developed. The method has the advantages of speed and both reducing sample and solvent consumption compared to conventional profiling methods. The addition of IMS added an additional dimension for feature detection and the identification of metabolites.

High-Throughput Metabolomics by 1D NMR

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.

The effect of a lifestyle intervention in obese pregnant women on gestational metabolic profiles: findings from the UK Pregnancies Better Eating and Activity Trial (UPBEAT) randomised controlled trial

BACKGROUND

Pregnancy is associated with widespread change in metabolism, which may be more marked in obese women. Whether lifestyle interventions in obese pregnant women improve pregnancy metabolic profiles remains unknown. Our objectives were to determine the magnitude of change in metabolic measures during obese pregnancy, to indirectly compare these to similar profiles in a general pregnant population, and to determine the impact of a lifestyle intervention on change in metabolic measures in obese pregnant women.

METHODS

Data from a randomised controlled trial of 1158 obese (BMI ≥ 30 kg/m²) pregnant women recruited from six UK inner-city obstetric departments were used. Women were randomised to either the UPBEAT intervention, a tailored complex lifestyle intervention focused on improving diet and physical activity, or standard antenatal care (control group). UPBEAT has been shown to improve diet and physical activity during pregnancy and up to 6-months postnatally in obese women and to reduce offspring adiposity at 6-months; it did not affect risk of gestational diabetes (the primary outcome). Change in the concentrations of 158 metabolic measures (129 lipids, 9 glycerides and phospholipids, and 20 low-molecular weight metabolites), quantified three times during pregnancy, were compared using multilevel models. The role of chance was assessed with a false discovery rate of 5% adjusted p values.

RESULTS

All very low-density lipoprotein (VLDL) particles increased by 1.5-3 standard deviation units (SD) whereas intermediate density lipoprotein and specific (large, medium and small) LDL particles increased by 1-2 SD, between 16 and 36 weeks' gestation. Triglycerides increased by 2-3 SD, with more modest changes in other metabolites. Indirect comparisons suggest that the magnitudes of change across pregnancy in these obese women were 2- to 3-fold larger than in unselected women (n = 4260 in cross-sectional and 583 in longitudinal analyses) from an independent, previously published, study. The intervention reduced the rate of increase in extremely large, very large, large and medium VLDL particles, particularly those containing triglycerides.

CONCLUSION

There are marked changes in lipids and lipoproteins and more modest changes in other metabolites across pregnancy in obese women, with some evidence that this is more marked than in unselected pregnant women. The UPBEAT lifestyle intervention may contribute to a healthier metabolic profile in obese pregnant women, but our results require replication.

TRIAL REGISTRATION

UPBEAT was registered with Current Controlled Trials, ISRCTN89971375 , on July 23, 2008 (prior to recruitment).