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

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.

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.

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.

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.

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.

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.

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).

Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study

BACKGROUND

Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).

METHODS

The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

RESULTS

Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

CONCLUSIONS

We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.

IMPACT

The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

The association between blood copper concentration and biomarkers related to cardiovascular disease risk - analysis of 206 individuals in the Northern Finland Birth Cohort 1966

BACKGROUND

Copper is an abundant trace element in humans where alterations in the circulating concentration could inform on chronic disease aetiology. To date, data are lacking to study how copper may associate with cardiovascular disease (CVD) risk factors in young and healthy population. Molecular evidence suggests an important role of copper in liver metabolism, an essential organ in maintaining cardiovascular health and inflammation, therefore supporting copper as an associated biomarker of the risk.

OBJECTIVE

We performed a cross-sectional analysis to examine the possible associations between blood copper levels and risk factors for CVD and pre-inflammatory process.

DESIGN

The data has been collected from a sub-sample set of the Northern Finland Birth Cohort 1966 (NFBC1966) at 31 years.

PARTICIPANTS

The study included 206 individuals, 116 men and 90 women. To reduce environmental individual variations affecting both copper and the metabolic profile in the study sample, the participants were selected as: i) being born in Finnish Lapland and ii) living in their birth place for the last five years preceding blood sampling.

MAIN OUTCOME MEASURES

Fasting blood copper concentration was measured by inductively coupled plasma mass spectrometer. The CVD risk factors included 6 metabolic clusters (30 cardiovascular and pro-inflammatory factors) assessed by nuclear magnetic resonance. Multivariate linear regression analysis was performed to test the linear association between blood copper and 6 metabolic clusters for CVD risk. Associations were assessed under correction for multiple testing.

RESULTS

Copper (Cu) levels were comparable in men and women, with no difference between sexes (p-value <0.60). In multiple regression models, sex adjusted, copper was associated with 9 metabolites from 4 metabolic clusters. After adjustment with BMI, copper was associated with 4 metabolites from 3 metabolic clusters: glutamine, beta-hydroxybutyrate, alpha-1-acid glycoprotein (AGP) and high-sensitive C-reactive protein (hs-CRP). After correction for multiple testing, Cu was found positively associated with only 2 biomarkers of inflammation including AGP [p = 0.04] and hs-CRP [p = 0.0001].

CONCLUSIONS

Considering the strength and limitation of the study design, the present study does not support evidence for an independent role of copper on biomarkers for CVD risk. Nevertheless, we are reporting a robust association of copper with the inflammatory load that is important to consider in light with the inflammatory component of chronic health. In addition, the association of copper with metabolites may be attributable to BMI or environmental factors associated to it, and warrants further research in large population samples.

Metabolite Profiling of Clinical Cancer Biofluid Samples by NMR Spectroscopy

Metabolomics is a comprehensive characterization of the small polar molecules (metabolites) in different biological systems. One of the analytical platforms commonly used to study metabolic alterations in biofluid samples is proton nuclear magnetic resonance (¹H NMR) spectroscopy. NMR spectroscopy is very specific, quantitative, and highly reproducible. Moreover, sample preparation for NMR experiments is very simple and straightforward, and this gives NMR spectroscopy a distinct advantage over other metabolic profiling methods. It has already been shown that ¹H NMR-based profiling of biological fluids can be effective in differentiating benign from malignant lesions and in investigating the efficacy of specific cancer treatments. Therefore, ¹H NMR spectroscopy may become a promising tool for early noninvasive diagnosis and rapid assessment of treatment effects in cancer patients. Here, we describe a detailed protocol for ¹H NMR metabolite profiling in serum, plasma, and urine samples, including sample collection procedures, sample preparation for ¹H NMR experiments, spectral acquisition and processing, and quantitative profiling of ¹H NMR spectra. We also discuss several aspects of appropriate study design and some multivariate statistical methods that are commonly used to analyze metabolomics datasets.

Metabolomics and Age-Related Macular Degeneration

Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers can potentially provide opportunities for clinical intervention at a stage of the disease when irreversible changes are yet to take place. One of the most metabolically active tissues in the human body is the retina, making the use of hypothesis-free techniques, like metabolomics, to measure molecular changes in AMD appealing. Indeed, there is increasing evidence that metabolic dysfunction has an important role in the development and progression of AMD. Therefore, metabolomics appears to be an appropriate platform to investigate disease-associated biomarkers. In this review, we explored what is known about metabolic changes in the retina, in conjunction with the emerging literature in AMD metabolomics research. Methods for metabolic biomarker identification in the eye have also been discussed, including the use of tears, vitreous, and aqueous humor, as well as imaging methods, like fluorescence lifetime imaging, that could be translated into a clinical diagnostic tool with molecular level resolution.

Associations of Body Mass and Fat Indexes With Cardiometabolic Traits

BACKGROUND

Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear.

OBJECTIVES

The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood.

METHODS

BMI was examined alongside total, trunk, arm, and leg fat indexes (each in kilograms per square meter) from dual-energy x-ray absorptiometry at ages 10 and 18 years in relation to 230 traits from targeted metabolomics at age 18 years in 2,840 offspring from the Avon Longitudinal Study of Parents and Children.

RESULTS

Higher total fat mass index and BMI at age 10 years were similarly associated with cardiometabolic traits at age 18 years, including higher systolic and diastolic blood pressure, higher very low-density lipoprotein and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher triglycerides, and higher insulin and glycoprotein acetyls. Associations were stronger for both indexes measured at age 18 years and for gains in each index from age 10 to 18 years (e.g., 0.45 SDs [95% confidence interval: 0.38 to 0.53] in glycoprotein acetyls per SD unit gain in fat mass index vs. 0.38 SDs [95% confidence interval: 0.27 to 0.48] per SD unit gain in BMI). Associations resembled those for trunk fat index. Higher lean mass index was weakly associated with traits and was not protective against higher fat mass index.

CONCLUSIONS

The results of this study support abdominal fatness as a primary driver of cardiometabolic dysfunction and BMI as a useful tool for detecting its effects.

Blood Metabolomic Measures Associate With Present and Future Glycemic Control in Type 2 Diabetes

OBJECTIVE

We studied whether blood metabolomic measures in people with type 2 diabetes (T2D) are associated with insufficient glycemic control and whether this association is influenced differentially by various diabetes drugs. We then tested whether the same metabolomic profiles were associated with the initiation of insulin therapy.

METHODS

A total of 162 metabolomic measures were analyzed using a nuclear magnetic resonance-based method in people with T2D from four cohort studies (n = 2641) and one replication cohort (n = 395). Linear and logistic regression analyses with adjustment for potential confounders, followed by meta-analyses, were performed to analyze associations with hemoglobin A1c levels, six glucose-lowering drug categories, and insulin initiation during a 7-year follow-up period (n = 698).

RESULTS

After Bonferroni correction, 26 measures were associated with insufficient glycemic control (HbA1c >53 mmol/mol). The strongest association was with glutamine (OR, 0.66; 95% CI, 0.61 to 0.73; P = 7.6 × 10-19). In addition, compared with treatment-naive patients, 31 metabolomic measures were associated with glucose-lowering drug use (representing various metabolite categories; P ≤ 3.1 × 10-4 for all). In drug-stratified analyses, associations with insufficient glycemic control were only mildly affected by different glucose-lowering drugs. Five of the 26 metabolomic measures (apolipoprotein A1 and medium high-density lipoprotein subclasses) were also associated with insulin initiation during follow-up in both discovery and replication. The strongest association was observed for medium high-density lipoprotein cholesteryl ester (OR, 0.54; 95% CI, 0.42 to 0.71; P = 4.5 × 10-6).

CONCLUSION

Blood metabolomic measures were associated with present and future glycemic control and might thus provide relevant cues to identify those at increased risk of treatment failure.

Metabolomic consequences of genetic inhibition of PCSK9 compared with statin treatment

Background

Both statins and PCSK9 inhibitors lower blood low-density lipoprotein cholesterol (LDL-C) levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these two lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial.

Methods

228 circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5,359 individuals (2,659 on treatment) in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial at 6-months post-randomization. The corresponding metabolic measures were analyzed in eight population cohorts (N=72,185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.

Results

Scaled to an equivalent lowering of LDL-C, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein (VLDL) lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of VLDL-cholesterol compared with statin therapy (54% vs. 77% reduction, relative to the lowering effect on LDL-C; P=2x10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA) whereas statin treatment weakly lowered GlycA levels.

Conclusions

Genetic inhibition of PCSK9 had similar metabolic effects to statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on VLDL lipids compared with statins for an equivalent lowering of LDL-C, which potentially translate into smaller reductions in cardiovascular disease risk.

Cross-sectional associations between Ideal Cardiovascular Health scores and vascular phenotypes in 11- to 12-year-olds and their parents: The Longitudinal Study of Australian Children

BACKGROUND

Understanding early-life relationships between the Ideal Cardiovascular Health (ICVH) score and vascular phenotypes could inform likely effectiveness and timing of cardiovascular disease prevention strategies. We aimed to describe associations between ICVH scores and vascular phenotypes in 11- to 12-year-old children and their parents.

METHODS AND RESULTS

Cross-sectional ICVH scores (range 0-7, higher indicating better health), derived by summing dichotomized metrics for cholesterol, glucose, blood pressure (BP), body mass index (BMI), diet, physical activity and smoking, were constructed for 1235 adults (89% female, mean age 43 years) and 1028 children (48% female, 12 years). The median scores were 4 and 5 for adults and children respectively. Child ICVH scores were associated with parent scores (0.18 higher child score per additional point in parent's score, 95% CI 0.12 to 0.22, P < 0.001). Each additional point in the adult ICVH score was associated with slower carotid-femoral pulse wave velocity (PWV, -0.32 m/s, 95% CI -0.37 to -0.27), greater carotid elasticity (0.017%/mm Hg, 95% CI 0.014 to 0.020) and reduced carotid intima-media thickness (IMT, -7.3 μm, 95% CI -12.0 to -2.5). An additional point in the child score was associated with functional phenotypes (PWV -0.07 m/s, 95% CI -0.11 to -0.03; carotid elasticity 0.009%/mm Hg, 95% CI 0.004 to 0.015) but not structural phenotypes (IMT -1.8 μm, 95% CI -5.2 to 1.5).

CONCLUSION

Few Australian children and even fewer parents have ideal cardiovascular health. Lower ICVH scores were associated with adverse adult vascular phenotypes and adverse child vascular function. Family-based interventions optimizing ICVH metrics may delay onset and progression of subclinical atherosclerosis and later cardiovascular disease.

Circulating metabolic biomarkers of renal function in diabetic and non-diabetic populations

Using targeted NMR spectroscopy of 227 fasting serum metabolic traits, we searched for novel metabolic signatures of renal function in 926 type 2 diabetics (T2D) and 4838 non-diabetic individuals from four independent cohorts. We furthermore investigated longitudinal changes of metabolic measures and renal function and associations with other T2D microvascular complications. 142 traits correlated with glomerular filtration rate (eGFR) after adjusting for confounders and multiple testing: 59 in diabetics, 109 in non-diabetics with 26 overlapping. The amino acids glycine and phenylalanine and the energy metabolites citrate and glycerol were negatively associated with eGFR in all the cohorts, while alanine, valine and pyruvate depicted opposite association in diabetics (positive) and non-diabetics (negative). Moreover, in all cohorts, the triglyceride content of different lipoprotein subclasses showed a negative association with eGFR, while cholesterol, cholesterol esters (CE), and phospholipids in HDL were associated with better renal function. In contrast, phospholipids and CEs in LDL showed positive associations with eGFR only in T2D, while phospholipid content in HDL was positively associated with eGFR both cross-sectionally and longitudinally only in non-diabetics. In conclusion, we provide a wide list of kidney function-associated metabolic traits and identified novel metabolic differences between diabetic and non-diabetic kidney disease.

Quantitative Lipoprotein Subclass and Low Molecular Weight Metabolite Analysis in Human Serum and Plasma by 1H NMR Spectroscopy in a Multilaboratory Trial

We report an extensive 600 MHz NMR trial of quantitative lipoprotein and small-molecule measurements in human blood serum and plasma. Five centers with eleven 600 MHz NMR spectrometers were used to analyze 98 samples including 20 quality controls (QCs), 37 commercially sourced, paired serum and plasma samples, and two National Institute of Science and Technology (NIST) reference material 1951c replicates. Samples were analyzed using rigorous protocols for sample preparation and experimental acquisition. A commercial lipoprotein subclass analysis was used to quantify 105 lipoprotein subclasses and 24 low molecular weight metabolites from the NMR spectra. For all spectrometers, the instrument specific variance in measuring internal QCs was lower than the percentage described by the National Cholesterol Education Program (NCEP) criteria for lipid testing [triglycerides <2.7%; cholesterol <2.8%; low-density lipoprotein (LDL) cholesterol <2.8%; high-density lipoprotein (HDL) cholesterol <2.3%], showing exceptional reproducibility for direct quantitation of lipoproteins in both matrixes. The average relative standard deviations (RSDs) for the 105 lipoprotein parameters in the 11 instruments were 4.6% and 3.9% for the two NIST samples, whereas they were 38% and 40% for the 37 commercially sourced plasmas and sera, respectively, showing negligible analytical compared to biological variation. The coefficient of variance (CV) obtained for the quantification of the small molecules across the 11 spectrometers was below 15% for 20 out of the 24 metabolites analyzed. This study provides further evidence of the suitability of NMR for high-throughput lipoprotein subcomponent analysis and small-molecule quantitation with the exceptional required reproducibility for clinical and other regulatory settings.

Associations of device-measured physical activity across adolescence with metabolic traits: Prospective cohort study

BACKGROUND

Multiple occasions of device-measured physical activity have not been previously examined in relation to metabolic traits. We described associations of total activity, moderate-to-vigorous physical activity (MVPA), and sedentary time from three accelerometry measures taken across adolescence with detailed traits related to systemic metabolism.

METHODS AND FINDINGS

There were 1,826 male and female participants recruited at birth in 1991-1992 via mothers into the Avon Longitudinal Study of Parents and Children offspring cohort who attended clinics in 2003-2005, 2005-2006, and 2006-2008 who were included in ≥1 analysis. Waist-worn uniaxial accelerometers measured total activity (counts/min), MVPA (min/d), and sedentary time (min/d) over ≥3 d at mean age 12y, 14y, and 15y. Current activity (at age 15y), mean activity across occasions, interaction by previous activity, and change in activity were examined in relation to systolic and diastolic blood pressure, insulin, C-reactive protein, and 230 traits from targeted metabolomics (nuclear magnetic resonance spectroscopy), including lipoprotein cholesterol and triglycerides, amino and fatty acids, glycoprotein acetyls, and others, at age 15y. Mean current total activity was 477.5 counts/min (SD = 164.0) while mean MVPA and sedentary time durations were 23.6 min/d (SD = 17.9) and 522.1 min/d (SD = 66.0), respectively. Mean body mass index at age 15y was 21.4 kg/m2 (SD = 3.5). Correlations between first and last activity measurement occasions were low (e.g., r = 0.40 for counts/min). Current activity was most strongly associated with cholesterol and triglycerides in high-density lipoprotein (HDL) and very low-density lipoprotein (VLDL) particles (e.g., -0.002 mmol/l or -0.18 SD units; 95% CI -0.24--0.11 for triglycerides in chylomicrons and extremely large very low-density lipoprotein [XL VLDL]) and with glycoprotein acetyls (-0.02 mmol/l or -0.16 SD units; 95% CI -0.22--0.10), among others. Associations were similar for mean activity across 3 occasions. Attenuations were modest with adjustment for fat mass index based on dual-energy X-ray absorptiometry (DXA). In mutually adjusted models, higher MVPA and sedentary time were oppositely associated with cholesterol and triglycerides in VLDL and HDL particles (MVPA more strongly with glycoprotein acetyls and sedentary time more strongly with amino acids). Associations appeared less consistent for sedentary time than for MVPA based on longer-term measures and were weak for change in all activity types from age 12y-15y. Evidence was also weak for interaction between activity types at age 15y and previous activity measures in relation to most traits (minimum P = 0.003; median P = 0.26 for counts/min) with interaction coefficients mostly positive. Study limitations include modest sample sizes and relatively short durations of accelerometry measurement on each occasion (3-7 d) and of time lengths between first and last accelerometry occasions (<4 years), which can obscure patterns from chance variation and limit description of activity trajectories. Activity was also recorded using uniaxial accelerometers which predated more sensitive triaxial devices.

CONCLUSIONS

Our results support associations of physical activity with metabolic traits that are small in magnitude and more robust for higher MVPA than lower sedentary time. Activity fluctuates over time, but associations of current activity with most metabolic traits do not differ by previous activity. This suggests that the metabolic effects of physical activity, if causal, depend on most recent engagement.

Statin Effects on Metabolic Profiles: Data From the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial)

BACKGROUND

Statins lower cholesterol by inhibiting HMG-CoA reductase, the rate-limiting enzyme of the metabolic pathway that produces cholesterol and other isoprenoids. Little is known about their effects on metabolite and lipoprotein subclass profiles. We, therefore, investigated the molecular changes associated with pravastatin treatment compared with placebo administration using a nuclear magnetic resonance-based metabolomics platform.

METHODS AND RESULTS

We performed metabolic profiling of 231 lipoprotein and metabolite measures in the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial) study, a placebo-controlled randomized clinical trial designed to test the effects of pravastatin (40 mg once daily) on cardiovascular risk. Metabolic profiles were assessed at baseline and after 3 months of treatment. Pravastatin lowered low-density lipoprotein cholesterol (change in SD units [95% confidence interval]: -1.01 [-1.14, -0.88]), remnant cholesterol (change in SD units [95% confidence interval]: -1.03 [-1.17, -0.89]), and apolipoprotein B (change in SD units [95% confidence interval]: -0.98 [-1.11, -0.86]) with similar effect magnitudes. In addition, pravastatin globally lowered levels of lipoprotein subclasses, with the exception of high-density lipoprotein subclasses, which displayed a more heterogeneous response pattern. The lipid-lowering effect of pravastatin was accompanied by selective changes in lipid composition, particularly in the cholesterol content of very-low-density lipoproteinparticles. In addition, pravastatin reduced levels of several fatty acids but had limited effects on fatty acid ratios.

CONCLUSIONS

These randomized clinical trial data demonstrate the widespread effects of pravastatin treatment on lipoprotein subclass profiles and fatty acids.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT03073018.

Metabolomic Profiles Reveal Potential Factors that Correlate with Lactation Performance in Sow Milk

Sow milk contains necessary nutrients for piglets; however, the relationship between the levels of metabolites in sow milk and lactation performance has not been thoroughly elucidated to date. In this study, we analysed the metabolites in sow milk from Yorkshire sows with high lactation (HL) or low lactation (LL) performance; these categories were assigned based on the weight gain of piglets during the entire lactation period (D1 to D21). The concentration of milk fat in the colostrum tended to be higher in the HL group (P = 0.05), the level of mannitol was significantly lower in the HL group (P < 0.05) and the level of glucuronic acid lactone was significantly higher in the HL group (P < 0.05) compared to those in LL group. In mature milk, the levels of lactose, creatine, glutamine, glutamate, 4-hydroxyproline, alanine, asparagine, and glycine were significantly higher (P < 0.05) in the HL group than those in LL group. The level of fatty acids showed no significant difference between the two groups in both the colostrum and mature milk. This study suggested that lactation performance may be associated with the levels of lactose and several amino acids in sow milk, and these results can be used to develop new feed additives to improve lactation performance in sows.

Circulating amino acids and the risk of macrovascular, microvascular and mortality outcomes in individuals with type 2 diabetes: results from the ADVANCE trial

AIMS/HYPOTHESES

We aimed to quantify the association of individual circulating amino acids with macrovascular disease, microvascular disease and all-cause mortality in individuals with type 2 diabetes.

METHODS

We performed a case-cohort study (N = 3587), including 655 macrovascular events, 342 microvascular events (new or worsening nephropathy or retinopathy) and 632 all-cause mortality events during follow-up, in a secondary analysis of the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) study. For this study, phenylalanine, isoleucine, glutamine, leucine, alanine, tyrosine, histidine and valine were measured in stored plasma samples by proton NMR metabolomics. Hazard ratios were modelled per SD increase in each amino acid.

RESULTS

In models investigating associations and potential mechanisms, after adjusting for age, sex and randomised treatment, phenylalanine was positively, and histidine inversely, associated with macrovascular disease risk. These associations were attenuated to the null on further adjustment for extended classical risk factors (including eGFR and urinary albumin/creatinine ratio). After adjustment for extended classical risk factors, higher tyrosine and alanine levels were associated with decreased risk of microvascular disease (HR 0.78; 95% CI 0.67, 0.91 and HR 0.86; 95% CI 0.76, 0.98, respectively). Higher leucine (HR 0.79; 95% CI 0.69, 0.90), histidine (HR 0.89; 95% CI 0.81, 0.99) and valine (HR 0.79; 95% CI 0.70, 0.88) levels were associated with lower risk of mortality. Investigating the predictive ability of amino acids, addition of all amino acids to a risk score modestly improved classification of participants for macrovascular (continuous net reclassification index [NRI] +35.5%, p < 0.001) and microvascular events (continuous NRI +14.4%, p = 0.012).

CONCLUSIONS/INTERPRETATION

We report distinct associations between circulating amino acids and risk of different major complications of diabetes. Low tyrosine appears to be a marker of microvascular risk in individuals with type 2 diabetes independently of fundamental markers of kidney function.

Association of circulating metabolites with healthy diet and risk of cardiovascular disease: analysis of two cohort studies

Diet may modify metabolomic profiles towards higher or lower cardiovascular disease (CVD) risk. We aimed to identify metabolite profiles associated with high adherence to dietary recommendations - the Alternative Healthy Eating Index (AHEI) - and the extent to which metabolites associated with AHEI also predict incident CVD. Relations between AHEI score and 80 circulating lipids and metabolites, quantified by nuclear magnetic resonance metabolomics, were examined using linear regression models in the Whitehall II study (n = 4824, 55.9 ± 6.1 years, 28.0% women) and were replicated in the Cardiovascular Risk in Young Finns Study (n = 1716, 37.7 ± 5.0 years, 56.3% women). We used Cox models to study associations between metabolites and incident CVD over the 15.8-year follow-up in the Whitehall II study. After adjustment for confounders, higher AHEI score (indicating healthier diet) was associated with higher degree of unsaturation of fatty acids (FA) and higher ratios of polyunsaturated FA, omega-3 and docosahexaenoic acid relative to total FA in both Whitehall II and Young Finns studies. A concordance of associations of metabolites with higher AHEI score and lower CVD risk was observed in Whitehall II. Adherence to healthy diet seems to be associated with specific FA that reduce risk of CVD.

Patients with Concurrent Tuberculosis and Diabetes Have a Pro-Atherogenic Plasma Lipid Profile

BACKGROUND

Type 2 diabetes mellitus (DM) is a major risk factor for development of tuberculosis (TB), however the underlying molecular foundations are unclear. Since lipids play a central role in the development of both DM and TB, lipid metabolism may be important for TB-DM pathophysiology.

METHODS

A 1H NMR spectroscopy-based platform was used to determine 225 lipid and other metabolic intermediates in plasma samples of healthy controls (n = 50) and patients with TB (n = 50), DM (n = 50) or TB-DM (n = 27).

RESULTS

TB patients presented with wasting disease, represented by decreased amino acid levels including histidine and alanine. Conversely, DM patients were dyslipidemic as evidenced by high levels of very low-density lipoprotein triglycerides and low high-density lipoprotein cholesterol. TB-DM patients displayed metabolic characteristics of both wasting and dyslipidemia combined with disease interaction-specific increases in phospholipid metabolites (e.g. sphingomyelins) and atherogenic remnant-like lipoprotein particles. Biomarker analysis identified the ratios of phenylalanine/histidine and esterified cholesterol/sphingomyelin as markers for TB classification regardless of DM-status.

CONCLUSIONS

TB-DM patients possess a distinctive plasma lipid profile with pro-atherogenic properties. These findings support further research on the benefits of improved blood lipid control in the treatment of TB-DM.

The association of omega-3 fatty acid levels with personality and cognitive reactivity

OBJECTIVE

Low omega (n)-3 polyunsaturated fatty acid (PUFA) levels have been found in patients with various major psychiatric disorders. This study aims to identify whether psychological vulnerabilities (personality and cognitive reactivity) underlying these psychiatric conditions are also associated with n-3 PUFA blood levels.

METHODS

Data was used from 2912 subjects (mean age 41.9 years, 66.4% female) from the Netherlands Study of Depression and Anxiety (NESDA). Five personality dimensions (NEO Five Factor Inventory) and cognitive reactivity measures (Leiden Index of Depression Sensitivity-Revised and Anxiety Sensitivity Index) were assessed. Plasma n-3 PUFA and docosahexaenoic acid (DHA) levels (as ratios against total fatty acids; mmol%) were assessed using a nuclear magnetic resonance platform.

RESULTS

Low n-3 PUFA and DHA levels were associated with high neuroticism (Standardized beta (Beta) = -0.045, 95% Confidence Interval (CI) = -0.079 to -0.010, p = 0.011; Beta = -0.058, 95%CI = -0.093 to -0.022, p = 0.001), low extraversion (Beta = 0.065, 95%CI = 0.031 to 0.099, p < 0.001; Beta = 0.074, 95%CI = 0.039 to 0.109, p < 0.001) and low conscientiousness (Beta = 0.060, 95%CI = 0.027 to 0.093, p < 0.001; Beta = 0.074, 95%CI = 0.039 to 0.108, p < 0.001). Low n-3 PUFA and DHA levels were related to high hopelessness/suicidality (Beta = -0.059, 95%CI = -0.096 to -0.023, p = 0.001; Beta = -0.078, 95%CI = -0.116 to -0.041, p < 0.001), but not with other cognitive reactivity measures. Directions of associations were generally consistent in subjects with and without a current depressive disorder.

CONCLUSION

Low n-3 PUFA and DHA levels are associated with personality (high neuroticism, low extraversion and low conscientiousness) and cognitive reactivity (high hopelessness/suicidality). Effect sizes were rather small, but in line with previous research on personality and chronic diseases. Future research should examine which lifestyle and/or biological pathways underlie these associations.