Long-term leisure-time physical activity and serum metabolome

Impact of Blood Collection Tubes and Sample Handling Time on Serum and Plasma Metabolome and Lipidome

Background: Metabolomics is emerging as a valuable tool in clinical science. However, one major challenge in clinical metabolomics is the limited use of standardized guidelines for sample collection and handling. In this study, we conducted a pilot analysis of serum and plasma to determine the effects of processing time and collection tube on the metabolome. Methods: Blood was collected in 3 tubes: Vacutainer serum separator tube (SST, serum), EDTA (plasma) and P100 (plasma) and stored at 4 degrees for 0, 0.5, 1, 2, 4 and 24 h prior to centrifugation. Compounds were extracted using liquid-liquid extraction to obtain a hydrophilic and a hydrophobic fraction and analyzed using liquid chromatography mass spectrometry. Differences among the blood collection tubes and sample processing time were evaluated (ANOVA, Bonferroni FWER ≤ 0.05 and ANOVA, Benjamini Hochberg FDR ≤ 0.1, respectively). Results: Among the serum and plasma tubes 93.5% of compounds overlapped, 382 compounds were unique to serum and one compound was unique to plasma. There were 46, 50 and 86 compounds affected by processing time in SST, EDTA and P100 tubes, respectively, including many lipids. In contrast, 496 hydrophilic and 242 hydrophobic compounds differed by collection tube. Forty-five different chemical classes including alcohols, sugars, amino acids and prenol lipids were affected by the choice of blood collection tube. Conclusion: Our results suggest that the choice of blood collection tube has a significant effect on detected metabolites and their overall abundances. Perhaps surprisingly, variation in sample processing time has less of an effect compared to collection tube; however, a larger sample size is needed to confirm this.

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.

A Distinct Pattern of Circulating Amino Acids Characterizes Older Persons with Physical Frailty and Sarcopenia: Results from the BIOSPHERE Study

Physical frailty and sarcopenia (PF&S) are hallmarks of aging that share a common pathogenic background. Perturbations in protein/amino acid metabolism may play a role in the development of PF&S. In this initial report, 68 community-dwellers aged 70 years and older, 38 with PF&S and 30 non-sarcopenic, non-frail controls (nonPF&S), were enrolled as part as the "BIOmarkers associated with Sarcopenia and Physical frailty in EldeRly pErsons" (BIOSPHERE) study. A panel of 37 serum amino acids and derivatives was assayed by UPLC-MS. Partial Least Squares⁻Discriminant Analysis (PLS-DA) was used to characterize the amino acid profile of PF&S. The optimal complexity of the PLS-DA model was found to be three latent variables. The proportion of correct classification was 76.6 ± 3.9% (75.1 ± 4.6% for enrollees with PF&S; 78.5 ± 6.0% for nonPF&S). Older adults with PF&S were characterized by higher levels of asparagine, aspartic acid, citrulline, ethanolamine, glutamic acid, sarcosine, and taurine. The profile of nonPF&S participants was defined by higher concentrations of α-aminobutyric acid and methionine. Distinct profiles of circulating amino acids and derivatives characterize older people with PF&S. The dissection of these patterns may provide novel insights into the role played by protein/amino acid perturbations in the disabling cascade and possible new targets for interventions.

The altered human serum metabolome induced by a marathon

INTRODUCTION

Endurance races have been associated with a substantial amount of adverse effects which could lead to chronic disease and long-term performance impairment. However, little is known about the holistic metabolic changes occurring within the serum metabolome of athletes after the completion of a marathon.

OBJECTIVES

Considering this, the aim of this study was to better characterize the acute metabolic changes induced by a marathon.

METHODS

Using an untargeted two dimensional gas chromatography time-of-flight mass spectrometry metabolomics approach, pre- and post-marathon serum samples of 31 athletes were analyzed and compared to identify those metabolites varying the most after the marathon perturbation.

RESULTS

Principle component analysis of the comparative groups indicated natural differentiation due to variation in the total metabolite profiles. Elevated concentrations of carbohydrates, fatty acids, tricarboxylic acid cycle intermediates, ketones and reduced concentrations of amino acids indicated a metabolic shift between various fuel substrate systems. Additionally, elevated odd-chain fatty acids and α-hydroxy acids indicated the utilization of α-oxidation and autophagy as alternative energy-producing mechanisms. Adaptations in gut microbe-associated markers were also observed and correlated with the metabolic flexibility of the athlete.

CONCLUSION

From these results it is evident that a marathon places immense strain on the energy-producing pathways of the athlete, leading to extensive protein degradation, oxidative stress, mammalian target of rapamycin complex 1 inhibition and autophagy. A better understanding of this metabolic shift could provide new insights for optimizing athletic performance, developing more efficient nutrition regimens and identify strategies to improve recovery.

Metabolic profiling of adherence to diet, physical activity and body size recommendations for cancer prevention

Maintaining a healthy body weight, eating well and being physically active lowers cancer risk by 30%. However, the biology underlying these relationships is not well understood. We examined cross-sectional associations between metabolites and cancer preventive behaviors as well as the relevance to cancer-related pathways among 120 participants (50% men, mean BMI 26.6 kg/m², mean age 54 years) with no history of smoking or cancer. Participants completed questionnaires, physical measurements and provided blood samples. Non-targeted nuclear magnetic resonance captured 223 metabolite measures. Factor analysis was performed separately for amino acid, fatty acid and lipoprotein groups. Multivariable-adjusted linear regression was used to evaluate associations between cancer preventive recommendations and metabolite-containing factors (p-value < 0.05, false discovery rate <0.20). An inflammation-related metabolite (glycoprotein acetylation) loaded strongly on a factor that was associated with excess adiposity (body fat ≥25% (men) or ≥30% (women) ß (SE) = 0.74 (0.18)) and not meeting physical activity recommendations (ß (SE) = 0.40 (0.20)). Insulin sensitivity-related metabolites including monounsaturated and polyunsaturated fats were lower among participants not meeting recommendations for adiposity, fruits and vegetables and physical activity while branched chain amino acids were higher. Cancer preventive behaviors were associated with complex metabolic signatures, including alterations in pathways known to be involved in cancer pathogenesis.

Cognition, psychosis risk and metabolic measures in two adolescent birth cohorts

BACKGROUND

Psychoses, especially schizophrenia, are often preceded by cognitive deficits and psychosis risk states. Altered metabolic profiles have been found in schizophrenia. However, the associations between metabolic profiles and poorer cognitive performance and psychosis risk in the population remain to be determined.

METHODS

Detailed molecular profiles were measured for up to 8976 individuals from two general population-based prospective birth cohorts: the Northern Finland Birth Cohort 1986 (NFBC 1986) and the Avon Longitudinal Study of Parents and Children (ALSPAC). A high-throughput nuclear magnetic resonance spectroscopy platform was used to quantify 70 metabolic measures at age 15-16 years in the NFBC 1986 and at ages 15 and 17 years in ALSPAC. Psychosis risk was assessed using the PROD-screen questionnaire at age 15-16 years in the NFBC 1986 or the psychotic-like symptoms assessment at age 17 years in ALSPAC. Cognitive measures included academic performance at age 16 years in both cohorts and general intelligence and executive function in ALSPAC. Logistic regression measured cross-sectional and longitudinal associations between metabolic measures and psychosis risk and cognitive performance, controlling for important covariates.

RESULTS

Seven metabolic measures, primarily fatty acid (FA) measures, showed cross-sectional associations with general cognitive performance, four across both cohorts (low density lipoprotein diameter, monounsaturated FA ratio, omega-3 ratio and docosahexaenoic acid ratio), even after controlling for important mental and physical health covariates. Psychosis risk showed minimal metabolic associations.

CONCLUSIONS

FA ratios may be important in marking risk for cognitive deficits in adolescence. Further research is needed to clarify whether these biomarkers could be causal and thereby possible targets for intervention.

Six-Week Endurance Exercise Alters Gut Metagenome That Is not Reflected in Systemic Metabolism in Over-weight Women

Recent studies suggest that exercise alters the gut microbiome. We determined whether six-weeks endurance exercise, without changing diet, affected the gut metagenome and systemic metabolites of overweight women. Previously sedentary overweight women (n = 19) underwent a six-weeks endurance exercise intervention, but two were excluded due to antibiotic therapy. The gut microbiota composition and functions were analyzed by 16S rRNA gene amplicon sequencing and metagenomics. Body composition was analyzed with DXA X-ray densitometer and serum metabolomics with NMR metabolomics. Total energy and energy-yielding nutrient intakes were analyzed from food records using Micro-Nutrica software. Serum clinical variables were determined with KONELAB instrument. Soluble Vascular Adhesion Protein 1 (VAP-1) was measured with ELISA and its' enzymatic activity as produced hydrogen peroxide. The exercise intervention was effective, as maximal power and maximum rate of oxygen consumption increased while android fat mass decreased. No changes in diet were observed. Metagenomic analysis revealed taxonomic shifts including an increase in Akkermansia and a decrease in Proteobacteria. These changes were independent of age, weight, fat % as well as energy and fiber intake. Training slightly increased Jaccard distance of genus level β-diversity. Training did not alter the enriched metagenomic pathways, which, according to Bray Curtis dissimilarity analysis, may have been due to that only half of the subjects' microbiomes responded considerably to exercise. Nevertheless, tranining decreased the abundance of several genes including those related to fructose and amino acid metabolism. These metagenomic changes, however, were not translated into major systemic metabolic changes as only two metabolites, phospholipids and cholesterol in large VLDL particles, decreased after exercise. Training also decreased the amine oxidase activity of pro-inflammatory VAP-1, whereas no changes in CRP were detected. All clinical blood variables were within normal range, yet exercise slightly increased glucose and decreased LDL and HDL. In conclusion, exercise training modified the gut microbiome without greatly affecting systemic metabolites or body composition. Based on our data and existing literature, we propose that especially Akkermansia and Proteobacteria are exercise-responsive taxa. Our results warrant the need for further studies in larger cohorts to determine whether exercise types other than endurance exercise also modify the gut metagenome.

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.

Effect of Dietary Counseling on a Comprehensive Metabolic Profile from Childhood to Adulthood

OBJECTIVES

To study the effects of repeated, infancy-onset dietary counseling on a detailed metabolic profile. Effects of dietary saturated fat replacement on circulating concentrations of metabolic biomarkers still remain unknown.

STUDY DESIGN

The Special Turku Coronary Risk Factor Intervention Project (STRIP) study is a longitudinal, randomized atherosclerosis prevention trial in which repeated dietary counseling aimed at reducing the proportion of saturated fat intake. Nuclear magnetic resonance metabolomics quantified circulating metabolites from serum samples assessed at age 9 (n = 554), 11 (n = 553), 13 (n = 508), 15 (n = 517), 17 (n = 457), and 19 (n = 417) years.

RESULTS

The intervention reduced dietary intake of saturated fat (mean difference in daily percentage of total energy intake: -2.1 [95% CI -1.9 to -2.3]) and increased intake of polyunsaturated fat (0.6 [0.5-0.7]). The dietary counseling intervention led to greater serum proportions of polyunsaturated fatty acids (P < .001), with greater proportions of both circulating omega-3 (P = .02) and omega-6 (P < .001) fatty acids. The proportion of saturated fatty acids in serum was lower for both boys and girls in the intervention group (P < .001), whereas the serum proportion of monounsaturated fat was lower for boys in the intervention group only (P < .001). The intervention also reduced circulating intermediate-density lipoprotein and low-density lipoprotein lipid concentrations (P < .01). Dietary intervention effects on nonlipid biomarkers were minor except from greater concentrations of glutamine in the intervention group.

CONCLUSIONS

Repeated dietary counseling from infancy to early adulthood yielded favorable effects on multiple circulating fatty acids and lipoprotein subclass lipids, particularly in boys. These molecular effects substantiate the beneficial role of saturated fat replacement on the metabolic risk profile.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT00223600.

Metabolic characterization of menopause: cross-sectional and longitudinal evidence

BACKGROUND

Women who experience menopause are at higher cardiometabolic risk and often display adverse changes in metabolic biomarkers compared with pre-menopausal women. It remains elusive whether the changes in cardiometabolic biomarkers during the menopausal transition are due to ovarian aging or chronological aging. Well-conducted longitudinal studies are required to determine this. The aim of this study was to explore the cross-sectional and longitudinal associations of reproductive status, defined according to the 2012 Stages of Reproductive Aging Workshop criteria, with 74 metabolic biomarkers, and establish whether any associations are independent of age-related changes.

METHODS

We determined cross-sectional associations of reproductive status with metabolic profiling in 3,312 UK midlife women. In a subgroup of 1,492 women who had repeat assessments after 2.5 years, we assessed how the change in reproductive status was associated with the changes in metabolic biomarkers. Metabolic profiles were measured by high-throughput quantitative nuclear magnetic resonance metabolomics. In longitudinal analyses, we compared the change in metabolic biomarkers for each reproductive-status category change to that of the reference of being pre-menopausal at both time points. As all women aged by a similar amount during follow-up, these analyses contribute to distinguishing age-related changes from those related to change in reproductive status.

RESULTS

Consistent cross-sectional and longitudinal associations of menopause with a wide range of metabolic biomarkers were observed, suggesting the transition to menopause induces multiple metabolic changes independent of chronological aging. The metabolic changes included increased concentrations of very small very low-density lipoproteins, intermediate-density lipoproteins, low-density lipoproteins (LDLs), remnant, and LDL cholesterol, and reduced LDL particle size, all toward an atherogenic lipoprotein profile. Increased inflammation was suggested via an inflammatory biomarker, glycoprotein acetyls, but not via C-reactive protein. Also, levels of glutamine and albumin increased during the transition. Most of these metabolic changes seen at the time of becoming post-menopausal remained or became slightly stronger during the post-menopausal years.

CONCLUSIONS

The transition to post-menopause has effects on multiple circulating metabolic biomarkers, over and above the underlying age trajectory. The adverse changes in multiple apolipoprotein-B-containing lipoprotein subclasses and increased inflammation may underlie women's increased cardiometabolic risk in their post-menopausal years.

Nuclear magnetic resonance-based metabolomics identifies phenylalanine as a novel predictor of incident heart failure hospitalisation: results from PROSPER and FINRISK 1997

Aims

We investigated the association between quantified metabolite, lipid and lipoprotein measures and incident heart failure hospitalisation (HFH) in the elderly, and examined whether circulating metabolic measures improve HFH prediction.

Methods and results

Overall, 80 metabolic measures from the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial were measured by proton nuclear magnetic resonance spectroscopy (n = 5341; 182 HFH events during 2.7‐year follow‐up). We repeated the work in FINRISK 1997 (n = 7330; 133 HFH events during 5‐year follow‐up). In PROSPER, the circulating concentrations of 13 metabolic measures were found to be significantly different in those who were later hospitalised for heart failure after correction for multiple comparisons. These included creatinine, phenylalanine, glycoprotein acetyls, 3‐hydroxybutyrate, and various high‐density lipoprotein measures. In Cox models, two metabolites were associated with risk of HFH after adjustment for clinical risk factors and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP): phenylalanine [hazard ratio (HR) 1.29, 95% confidence interval (CI) 1.10–1.53; P = 0.002] and acetate (HR 0.81, 95% CI 0.68–0.98; P = 0.026). Both were retained in the final model after backward elimination. Compared to a model with established risk factors and NT‐proBNP, this model did not improve the C‐index but did improve the overall continuous net reclassification index (NRI 0.21; 95% CI 0.06–0.35; P = 0.007) due to improvement in classification of non‐cases (NRI 0.14; 95% CI 0.12–0.17; P < 0.001). Phenylalanine was replicated as a predictor of HFH in FINRISK 1997 (HR 1.23, 95% CI 1.03–1.48; P = 0.023).

Conclusion

Our findings identify phenylalanine as a novel predictor of incident HFH, although prediction gains are low. Further mechanistic studies appear warranted.

Genetic Support for a Causal Role of Insulin Resistance on Circulating Branched-Chain Amino Acids and Inflammation

OBJECTIVE

Insulin resistance has deleterious effects on cardiometabolic disease. We used Mendelian randomization analyses to clarify the causal relationships of insulin resistance (IR) on circulating blood-based metabolites to shed light on potential mediators of the IR to cardiometabolic disease relationship.

RESEARCH DESIGN AND METHODS

We used 53 single nucleotide polymorphisms associated with IR from a recent genome-wide association study (GWAS) to explore their effects on circulating lipids and metabolites. We used published summary-level data from two GWASs of European individuals; data on the exposure (IR) were obtained from meta-GWASs of 188,577 individuals, and data on the outcomes (58 metabolic measures assessed by nuclear magnetic resonance) were taken from a GWAS of 24,925 individuals.

RESULTS

One-SD genetically elevated IR (equivalent to 55% higher geometric mean of fasting insulin, 0.89 mmol/L higher triglycerides, and 0.46 mmol/L lower HDL cholesterol) was associated with higher concentrations of all branched-chain amino acids (BCAAs)-isoleucine (0.56 SD; 95% CI 0.43, 0.70), leucine (0.42 SD; 95% CI 0.28, 0.55), and valine (0.26 SD; 95% CI 0.12, 0.39)-as well as with higher glycoprotein acetyls (an inflammation marker) (0.47 SD; 95% CI 0.32, 0.62) (P < 0.0003 for each). Results were broadly consistent when using multiple sensitivity analyses to account for potential genetic pleiotropy.

CONCLUSIONS

We provide robust evidence that IR causally affects each individual BCAA and inflammation. Taken together with existing studies, this implies that BCAA metabolism lies on a causal pathway from adiposity and IR to type 2 diabetes.

Specific plasma amino acid disturbances associated with metabolic syndrome

PURPOSE

The primary objective of the present study was to examine the association between branched chain and aromatic amino acid profiles (BCAA and AAA respectively) and the metabolic syndrome (MS), and to evaluate the clinical utility of these associations in the diagnostic process.

METHODS

Two hundred and sixty three healthy men with MS [MS(+): n = 165] and without MS [MS(-): n = 98] were enrolled in the observational study. Anthropometrical, biochemical, and amino acid measurements were performed. The ability of the BCAA and AAA to discriminate subjects with MS and insulin resistance was tested. Based on logistic discrimination, a multivariate early MS diagnostic model was built, and its discrimination properties were evaluated.

RESULTS

Two functionally independent amino acid clusters were identified. BCAA and phenylalanine differed significantly between MS(+) and MS(-) participants (P = 0.003). These factors were also found to be indicators of MS(+) individuals (AUC: 0.66; 95% CI: 0.5757-0.7469), and correlated with cardiometabolic factors. No statistically significant differences in amino acid concentrations between those with and without insulin resistance were noted, and none of the amino groups were indicators of insulin resistance. The proposed MS multivariate diagnostic model consisted of phenylalanine, insulin, leptin, and adiponectin, and had good discrimination properties [AUC 0.79; 95% CI: 0.7239-0.8646].

CONCLUSIONS

MS is associated with selective BCAA and AAA profile disturbances, which could be part of cardiometabolic disease pathogenesis and derive neither directly from insulin sensitivity impairment, nor obesity or muscle mass. The MS diagnostic model developed and described herein should be validated in future studies.

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

Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.

Association of leisure time physical activity and NMR-detected circulating amino acids in peripubertal girls: A 7.5-year longitudinal study

This study investigated the longitudinal associations of physical activity and circulating amino acids concentration in peripubertal girls. Three hundred ninety-six Finnish girls participated in the longitudinal study from childhood (mean age 11.2 years) to early adulthood (mean age 18.2 years). Circulating amino acids were assessed by nuclear magnetic resonance spectroscopy. LTPA was assessed by self-administered questionnaire. We found that isoleucine, leucine and tyrosine levels were significantly higher in individuals with lower LTPA than their peers at age 11 (p < 0.05 for all), independent of BMI. In addition, isoleucine and leucine levels increased significantly (~15%) from childhood to early adulthood among the individuals with consistently low LTPA (p < 0.05 for both), while among the individuals with consistently high LTPA the level of these amino acids remained virtually unchanged. In conclusion, high level of physical activity is associated lower serum isoleucine and leucine in peripubertal girls, independent of BMI, which may serve as a mechanistic link between high level of physical activity in childhood and its health benefits later in life. Further studies in peripubertal boys are needed to assess whether associations between physical activity and circulating amino acids in children adolescents are sex-specific.

Multivariable Analysis of Nutritional and Socio-Economic Profiles Shows Differences in Incident Anemia for Northern and Southern Jiangsu in China

Anemia is a prevalent public health problem associated with nutritional and socio-economic factors that contribute to iron deficiency. To understand the complex interplay of risk factors, we investigated a prospective population sample from the Jiangsu province in China. At baseline, three-day food intake was measured for 2849 individuals (20 to 87 years of age, mean age 47 ± 14, range 20-87 years, 64% women). At a five-year follow-up, anemia status was re-assessed for 1262 individuals. The dataset was split and age-matched to accommodate cross-sectional (n = 2526), prospective (n = 837), and subgroup designs (n = 1844). We applied a machine learning framework (self-organizing map) to define four subgroups. The first two subgroups were primarily from the less affluent North: the High Fibre subgroup had a higher iron intake (35 vs. 21 mg/day) and lower anemia incidence (10% vs. 25%) compared to the Low Vegetable subgroup. However, the predominantly Southern subgroups were surprising: the Low Fibre subgroup showed a lower anemia incidence (10% vs. 27%), yet also a lower iron intake (20 vs. 28 mg/day) compared to the High Rice subgroup. These results suggest that interventions and iron intake guidelines should be tailored to regional, nutritional, and socio-economic subgroups.

Lifestyle precision medicine: the next generation in type 2 diabetes prevention?

The driving force behind the current global type 2 diabetes epidemic is insulin resistance in overweight and obese individuals. Dietary factors, physical inactivity, and sedentary behaviors are the major modifiable risk factors for obesity. Nevertheless, many overweight/obese people do not develop diabetes and lifestyle interventions focused on weight loss and diabetes prevention are often ineffective. Traditionally, chronically elevated blood glucose concentrations have been the hallmark of diabetes; however, many individuals will either remain 'prediabetic' or regress to normoglycemia. Thus, there is a growing need for innovative strategies to tackle diabetes at scale. The emergence of biomarker technologies has allowed more targeted therapeutic strategies for diabetes prevention (precision medicine), though largely confined to pharmacotherapy. Unlike most drugs, lifestyle interventions often have systemic health-enhancing effects. Thus, the pursuance of lifestyle precision medicine in diabetes seems rational. Herein, we review the literature on lifestyle interventions and diabetes prevention, describing the biological systems that can be characterized at scale in human populations, linking them to lifestyle in diabetes, and consider some of the challenges impeding the clinical translation of lifestyle precision medicine.

Comprehensive lipid and metabolite profiling of children with and without familial hypercholesterolemia: A cross-sectional study

BACKGROUND AND AIMS

Individuals with familial hypercholesterolemia (FH) have elevated low-density lipoprotein cholesterol (LDL-C), accelerated atherosclerosis, and premature cardiovascular disease. Whereas children with lifestyle-induced dyslipidemias often present with complex lipid abnormalities, children with FH have isolated hypercholesterolemia. However, to the best of our knowledge, a comprehensive profiling of FH children is lacking. Therefore, we aimed to characterize the lipid-related and metabolic alterations associated with elevated LDL-C in children with FH and healthy children.

METHODS

We measured plasma metabolites in children with FH (n = 47) and in healthy children (n = 57) using a high-throughput nuclear magnetic resonance (NMR) spectroscopy platform, and compared the differences between FH and healthy children.

RESULTS

Both statin treated (n = 17) and non-statin treated FH children (n = 30) had higher levels of atherogenic ApoB-containing lipoproteins and lipids, and lipid fractions in lipoprotein subclasses, compared to healthy children (n = 57). FH children displayed alterations in HDL particle concentration and lipid content, compared with healthy children. Interestingly, the small HDL particles were characterized by higher content of cholesteryl esters, and lower levels of free cholesterol and phospholipids. Furthermore, plasma fatty acids were higher in non-statin treated FH children, particularly linoleic acid. Finally, acetoacetate and acetate were lower in FH children compared with healthy children.

CONCLUSIONS

Hypercholesterolemia in children associates with diverse metabolic repercussions and is more complex than previously believed. In particular, we found that hypercholesterolemia in FH children was paralleled not only by increased atherogenic ApoB-containing lipoproteins and lipid fractions, but also alterations in HDL subfractions that suggest impaired reverse cholesterol transport.

Low level activity thresholds for changes in NMR biomarkers and genes in high risk subjects for Type 2 Diabetes

Our objectives were to determine if there are quantitative associations between amounts and intensities of physical activities (PA) on NMR biomarkers and changes in skeletal muscle gene expressions in subjects with high risk for type 2 diabetes (T2D) performing a 3-month PA intervention. We found that PA was associated with beneficial biomarker changes in a factor containing several VLDL and HDL subclasses and lipids in principal component analysis (P = <0.01). Division of PA into quartiles demonstrated significant changes in NMR biomarkers in the 2nd - 4th quartiles compared to the 1st quartile representing PA of less than 2850 daily steps (P = 0.0036). Mediation analysis of PA-related reductions in lipoproteins showed that the effects of PA was 4-15 times greater than those of body weight or fat mass reductions. In a subset study in highly active subjects' gene expressions of oxidative fiber markers, Apo D, and G0/G1 Switch Gene 2, controlling insulin signaling and glucose metabolism were significantly increased. Slow walking at speeds of 2-3 km/h exceeding 2895 steps/day attenuated several circulating lipoprotein lipids. The effects were mediated rather by PA than body weight or fat loss. Thus, lower thresholds for PA may exist for long term prevention of cardio-metabolic diseases in sedentary overweight subjects.

Trajectories in Leisure-Time Physical Activity and Risk of Stroke in Women in the California Teachers Study

BACKGROUND AND PURPOSE

Whether changes in leisure-time physical activity (LTPA) over time are associated with lower risk of stroke is not well established. We examined the association between changes in self-reported LTPA 10 years apart, with risk of incident stroke in the CTS (California Teachers Study). We hypothesized that the risk of stroke would be lowest among those who remained active.

METHODS

Sixty-one thousand two hundred and fifty-six CTS participants reported LTPA at 2 intensity levels (moderate and strenuous activity) at 2 time points (baseline 1995-96; 10-year follow-up 2005-2006). LTPA at each intensity level was categorized based on American Heart Association (AHA) recommendations (moderate, >150 minutes/week; strenuous, >75 minutes/week). Changes in LTPA were summarized as follows: (1) not meeting recommendations at both time points; (2) meeting recommendations only at follow-up; (3) meeting recommendations only at baseline; and (4) meeting recommendations at both time points. Incident strokes were identified through California state hospitalization records. Using multivariable Cox models, we examined the associations between changes in LTPA with incident stroke.

RESULTS

Nine hundred and eighty-seven women were diagnosed with stroke who completed both questionnaires. Meeting AHA recommendations at both the time points was associated with a lower risk of all stroke (adjusted hazard ratio, 0.84; 95% confidence interval, 0.72-0.98). The protective effects for stroke were driven by meeting AHA recommendations for moderate activity and largely observed for ischemic strokes (adjusted hazard ratio, 0.70; 95% confidence interval, 0.55-0.88).

CONCLUSIONS

Meeting AHA recommendations for moderate activity had a protective effect for reducing ischemic stroke risk. Participants who met AHA recommendations at baseline but not at follow-up, however, were not afforded reduced stroke risk.

Association of pre-pregnancy body mass index with offspring metabolic profile: Analyses of 3 European prospective birth cohorts

BACKGROUND

A high proportion of women start pregnancy overweight or obese. According to the developmental overnutrition hypothesis, this could lead offspring to have metabolic disruption throughout their lives and thus perpetuate the obesity epidemic across generations. Concerns about this hypothesis are influencing antenatal care. However, it is unknown whether maternal pregnancy adiposity is associated with long-term risk of adverse metabolic profiles in offspring, and if so, whether this association is causal, via intrauterine mechanisms, or explained by shared familial (genetic, lifestyle, socioeconomic) characteristics. We aimed to determine if associations between maternal body mass index (BMI) and offspring systemic cardio-metabolic profile are causal, via intrauterine mechanisms, or due to shared familial factors.

METHODS AND FINDINGS

We used 1- and 2-stage individual participant data (IPD) meta-analysis, and a negative-control (paternal BMI) to examine the association between maternal pre-pregnancy BMI and offspring serum metabolome from 3 European birth cohorts (offspring age at blood collection: 16, 17, and 31 years). Circulating metabolic traits were quantified by high-throughput nuclear magnetic resonance metabolomics. Results from 1-stage IPD meta-analysis (N = 5327 to 5377 mother-father-offspring trios) showed that increasing maternal and paternal BMI was associated with an adverse cardio-metabolic profile in offspring. We observed strong positive associations with very-low-density lipoprotein (VLDL)-lipoproteins, VLDL-cholesterol (C), VLDL-triglycerides, VLDL-diameter, branched/aromatic amino acids, glycoprotein acetyls, and triglycerides, and strong negative associations with high-density lipoprotein (HDL), HDL-diameter, HDL-C, HDL2-C, and HDL3-C (all P < 0.003). Slightly stronger magnitudes of associations were present for maternal compared with paternal BMI across these associations; however, there was no strong statistical evidence for heterogeneity between them (all bootstrap P > 0.003, equivalent to P > 0.05 after accounting for multiple testing). Results were similar in each individual cohort, and in the 2-stage analysis. Offspring BMI showed similar patterns of cross-sectional association with metabolic profile as for parental pre-pregnancy BMI associations but with greater magnitudes. Adjustment of parental BMI-offspring metabolic traits associations for offspring BMI suggested the parental associations were largely due to the association of parental BMI with offspring BMI. Limitations of this study are that inferences cannot be drawn about the role of circulating maternal fetal fuels (i.e., glucose, lipids, fatty acids, and amino acids) on later offspring metabolic profile. In addition, BMI may not reflect potential effects of maternal pregnancy fat distribution.

CONCLUSION

Our findings suggest that maternal BMI-offspring metabolome associations are likely to be largely due to shared genetic or familial lifestyle confounding rather than to intrauterine mechanisms.

Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine-N-oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine.

Impact of exercise on fecal and cecal metabolome over aging: a longitudinal study in rats

Aim: Physical exercise can reduce adverse conditions during aging, while both exercise and aging act as metabolism modifiers. The present study investigates rat fecal and cecal metabolome alterations derived from exercise during rats’ lifespan. Methods & results: Groups of rats trained life-long or for a specific period of time were under study. The training protocol consisted of swimming, 15–18 min per day, 3–5 days per week, with load of 4–0% of rat's weight. Fecal samples and cecal extracts were analyzed by targeted and untargeted metabolic profiling methods (GC–MS and LC–MS/MS). Effects of exercise and aging on the rats’ fecal and cecal metabolome were observed. Conclusion: Fecal and cecal metabolomics are a promising field to investigate exercise biochemistry and age-related alterations.

Metabolic profiling of pregnancy: cross-sectional and longitudinal evidence

BACKGROUND

Pregnancy triggers well-known alterations in maternal glucose and lipid balance but its overall effects on systemic metabolism remain incompletely understood.

METHODS

Detailed molecular profiles (87 metabolic measures and 37 cytokines) were measured for up to 4260 women (24-49 years, 322 pregnant) from three population-based cohorts in Finland. Circulating molecular concentrations in pregnant women were compared to those in non-pregnant women. Metabolic profiles were also reassessed for 583 women 6 years later to uncover the longitudinal metabolic changes in response to change in the pregnancy status.

RESULTS

Compared to non-pregnant women, all lipoprotein subclasses and lipids were markedly increased in pregnant women. The most pronounced differences were observed for the intermediate-density, low-density and high-density lipoprotein triglyceride concentrations. Large differences were also seen for many fatty acids and amino acids. Pregnant women also had higher concentrations of low-grade inflammatory marker glycoprotein acetyls, higher concentrations of interleukin-18 and lower concentrations of interleukin-12p70. The changes in metabolic concentrations for women who were not pregnant at baseline but pregnant 6 years later (or vice versa) matched (or were mirror-images of) the cross-sectional association pattern. Cross-sectional results were consistent across the three cohorts and similar longitudinal changes were seen for 653 women in 4-year and 497 women in 10-year follow-up. For multiple metabolic measures, the changes increased in magnitude across the three trimesters.

CONCLUSIONS

Pregnancy initiates substantial metabolic and inflammatory changes in the mothers. Comprehensive characterisation of normal pregnancy is important for gaining understanding of the key nutrients for fetal growth and development. These findings also provide a valuable molecular reference in relation to studies of adverse pregnancy outcomes.

Branched-Chain Amino Acid Levels Are Related with Surrogates of Disturbed Lipid Metabolism among Older Men

Aims/hypothesis

Existing studies suggest that decreased branched-chain amino acid (BCAA) catabolism and thus elevated levels in blood are associated with metabolic disturbances. Based on such information, we have developed a hypothesis how BCAA degradation mechanistically connects to tricarboxylic acid cycle, intramyocellular lipid storage, and oxidation, thus allowing more efficient mitochondrial energy production from lipids as well as providing better metabolic health. We analyzed whether data from aged Finnish men are in line with our mechanistic hypothesis linking BCAA catabolism and metabolic disturbances.

Methods

Older Finnish men enriched with individuals having been athletes in young adulthood (n = 593; mean age 72.6 ± 5.9 years) responded to questionnaires, participated in a clinical examination including assessment of body composition with bioimpedance and gave fasting blood samples for various analytes as well as participated in a 2-h 75 g oral glucose tolerance test. Metabolomics measurements from serum included BCAAs (isoleucine, leucine, and valine).

Results

Out of the 593 participants, 59 had previously known type 2 diabetes, further 67 had screen-detected type 2 diabetes, 127 impaired glucose tolerance, and 125 impaired fasting glucose, while 214 had normal glucose regulation and one had missing glucose tolerance information. There were group differences in all of the BCAA concentrations (p ≤ 0.005 for all BCAAs), such that those with normal glucose tolerance had the lowest and those with diabetes mellitus had the highest BCAA concentrations. All BCAA levels correlated positively with body fat percentage (r = 0.29–0.34, p < 0.0001 for all). Expected associations with high BCAA concentrations and unfavorable metabolic profile indicators from metabolomics analysis were found. Except for glucose concentrations, the associations were stronger with isoleucine and leucine than with valine.

Conclusion/interpretation

The findings provided further support for our hypothesis by strengthening the idea that the efficiency of BCAA catabolism may be mechanistically involved in the regulation of fat oxidation, thus affecting the levels of metabolic disease risk factors.

Quantitative in vivo neurochemical profiling in humans: where are we now?

Proton nuclear magnetic resonance spectroscopy of biofluids has become one of the key techniques for metabolic profiling and phenotyping. This technique has been widely used in a number of epidemiological studies and in a variety of health disorders. However, its utilization in brain disorders is limited due to the blood-brain barrier, which not only protects the brain from unwanted substances in the blood, but also substantially limits the potential of finding biomarkers for neurological disorders in serum. This review article focuses on the potential of localized in vivo proton magnetic resonance spectroscopy (¹H-MRS) for non-invasive neurochemical profiling in the human brain. First, methodological aspects of ¹H-MRS (data acquisition, processing and metabolite quantification) that are essential for reliable non-invasive neurochemical profiling are described. Second, the power of ¹H-MRS-based neurochemical profiling is demonstrated using some examples of its application in neuroscience and neurology. Finally, the authors present their vision and propose necessary steps to establish ¹H-MRS as a method suitable for large-scale neurochemical profiling in epidemiological research.

Metabolic Profiling of Total Physical Activity and Sedentary Behavior in Community-Dwelling Men

Objective

Physical activity is known to be preventive against various non-communicable diseases. We investigated the relationship between daily physical activity level and plasma metabolites using a targeted metabolomics approach in a population-based study.

Methods

A total of 1,193 participants (male, aged 35 to 74 years) with fasting blood samples were selected from the baseline survey of a cohort study. Information on daily total physical activity, classified into four levels by quartile of metabolic equivalent scores, and sedentary behavior, defined as hours of sitting per day, was collected through a self-administered questionnaire. Plasma metabolite concentrations were quantified by capillary electrophoresis mass spectrometry method. We performed linear regression analysis models with multivariable adjustment and corrected p-values for multiple testing in the original population (n = 808). The robustness of the results was confirmed by replication analysis in a separate population (n = 385) created by random allocation.

Results

Higher levels of total physical activity were associated with various metabolite concentrations, including lower concentrations of amino acids and their derivatives, and higher concentrations of pipecolate (FDR p <0.05 in original population). The findings persisted after adjustment for age, body mass index, smoking, alcohol intake, and energy intake. Isoleucine, leucine, valine, 4-methyl-2-oxoisopentanoate, 2-oxoisopentanoate, alanine, and proline concentrations were lower with a shorter sitting time.

Conclusions

Physical activity is related to various plasma metabolites, including known biomarkers for future insulin resistance or type 2 diabetes. These metabolites might potentially play a key role in the protective effects of higher physical activity and/or less sedentary behavior on non-communicable diseases.

Objectively measured physical activity and plasma metabolomics in the Shanghai Physical Activity Study

BACKGROUND

Physical activity is associated with a variety of health benefits, but the biological mechanisms that explain these associations remain unclear. Metabolomics is a powerful tool to comprehensively evaluate global metabolic signature associated with physical activity and helps to pinpoint the pathways that mediate the health effects of physical activity. There has been limited research on metabolomics and habitual physical activity, and no metabolomics study has examined sedentary behaviour and physical activity of different intensities.

METHODS

In a group of Chinese adults (N = 277), we used an untargeted approach to examine 328 plasma metabolites in relation to accelerometer-measured physical activity, including overall volume of physical activity (physical activity energy expenditure (PAEE) and duration of physically active time) and sedentary time, and measures related to different intensities of physical activity (moderate-to-vigorous activity (MVPA), light activity, average physical activity intensity).

RESULTS

We identified 11 metabolites that were associated with total activity, with a false discovery rate of 0.2 or lower. Notably, we observed generally lower levels of amino acids in the valine, leucine and isoleucine metabolism pathway and of carbohydrates in sugar metabolism among participants with higher activity levels. Moreover, we found that PAEE, time spent in light activity and duration of physically active time were associated with a similar metabolic pattern, whereas the metabolic signature associated with sedentary time mirrored this pattern. In contrast, average activity intensity and time spent in MVPA appeared to be associated with somewhat different metabolic patterns.

CONCLUSIONS

Overall, the metabolomics patterns support a beneficial role of higher volume of physical activity in cardiometabolic health. Our findings identified candidate pathways and provide insight into the mechanisms underlying the health effects of physical activity.

Effects of hormonal contraception on systemic metabolism: cross-sectional and longitudinal evidence

Background: Hormonal contraception is commonly used worldwide, but its systemic effects across lipoprotein subclasses, fatty acids, circulating metabolites and cytokines remain poorly understood.

Methods: A comprehensive molecular profile (75 metabolic measures and 37 cytokines) was measured for up to 5841 women (age range 24–49 years) from three population-based cohorts. Women using combined oral contraceptive pills (COCPs) or progestin-only contraceptives (POCs) were compared with those who did not use hormonal contraception. Metabolomics profiles were reassessed for 869 women after 6 years to uncover the metabolic effects of starting, stopping and persistently using hormonal contraception.

Results: The comprehensive molecular profiling allowed multiple new findings on the metabolic associations with the use of COCPs. They were positively associated with lipoprotein subclasses, including all high-density lipoprotein (HDL) subclasses. The associations with fatty acids and amino acids were strong and variable in direction. COCP use was negatively associated with albumin and positively associated with creatinine and inflammatory markers, including glycoprotein acetyls and several growth factors and interleukins. Our findings also confirmed previous results e.g. for increased circulating triglycerides and HDL cholesterol. Starting COCPs caused similar metabolic changes to those observed cross-sectionally: the changes were maintained in consistent users and normalized in those who stopped using. In contrast, POCs were only weakly associated with metabolic and inflammatory markers. Results were consistent across all cohorts and for different COCP preparations and different types of POC delivery.

Conclusions: Use of COCPs causes widespread metabolic and inflammatory effects. However, persistent use does not appear to accumulate the effects over time and the metabolic perturbations are reversed upon discontinuation. POCs have little effect on systemic metabolism and inflammation.

Metabolic profiling of alcohol consumption in 9778 young adults

Background: High alcohol consumption is a major cause of morbidity, yet alcohol is associated with both favourable and adverse effects on cardiometabolic risk markers. We aimed to characterize the associations of usual alcohol consumption with a comprehensive systemic metabolite profile in young adults.

Methods: Cross-sectional associations of alcohol intake with 86 metabolic measures were assessed for 9778 individuals from three population-based cohorts from Finland (age 24–45 years, 52% women). Metabolic changes associated with change in alcohol intake during 6-year follow-up were further examined for 1466 individuals. Alcohol intake was assessed by questionnaires. Circulating lipids, fatty acids and metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays.

Results: Increased alcohol intake was associated with cardiometabolic risk markers across multiple metabolic pathways, including higher lipid concentrations in HDL subclasses and smaller LDL particle size, increased proportions of monounsaturated fatty acids and decreased proportion of omega-6 fatty acids, lower concentrations of glutamine and citrate (P < 0.001 for 56 metabolic measures). Many metabolic biomarkers displayed U-shaped associations with alcohol consumption. Results were coherent for men and women, consistent across the three cohorts and similar if adjusting for body mass index, smoking and physical activity. The metabolic changes accompanying change in alcohol intake during follow-up resembled the cross-sectional association pattern (R²= 0.83, slope = 0.72 ± 0.04).

Conclusions: Alcohol consumption is associated with a complex metabolic signature, including aberrations in multiple biomarkers for elevated cardiometabolic risk. The metabolic signature tracks with long-term changes in alcohol consumption. These results elucidate the double-edged effects of alcohol on cardiovascular risk.

Assessment of dietary exposure and effect in humans: The role of NMR

In human nutritional science progress has always depended strongly on analytical measurements for establishing relationships between diet and health. This field has undergone significant changes as a result of the development of NMR and mass spectrometry methods for large scale detection, identification and quantification of metabolites in body fluids. This has allowed systematic studies of the metabolic fingerprints that biological processes leave behind, and has become the research field of metabolomics. As a metabolic profiling technique, NMR is at its best when its unbiased nature, linearity and reproducibility are exploited in well-controlled nutritional intervention and cross-sectional population screening studies. Although its sensitivity is less good than that of mass spectrometry, NMR has maintained a strong position in metabolomics through implementation of standardisation protocols, hyphenation with mass spectrometry and chromatographic techniques, accurate quantification and spectral deconvolution approaches, and high-throughput automation. Thus, NMR-based metabolomics has contributed uniquely to new insights into dietary exposure, in particular by unravelling the metabolic fates of phytochemicals and the discovery of dietary intake markers. NMR profiling has also contributed to the understanding of the subtle effects of diet on central metabolism and lipoprotein metabolism. In order to hold its ground in nutritional metabolomics, NMR will need to step up its performance in sensitivity and resolution; the most promising routes forward are the analytical use of dynamic nuclear polarisation and developments in microcoil construction and automated fractionation.

The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women

Background

The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible.

Objective

The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and¹H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics.

Methods

Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,¹H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods.

Results

The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway.

Conclusions

We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and¹H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study.

Trial Registration

German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx)

Metabolic Characterization of a Rare Genetic Variation Within APOC3 and Its Lipoprotein Lipase-Independent Effects

BACKGROUND

Plasma triglyceride levels have been implicated in atherosclerosis and coronary heart disease. Apolipoprotein C-III (APOC3) plays a key role in the hydrolysis of triglyceride-rich lipoproteins to remnant particles by lipoprotein lipase (LPL) and their uptake by the liver. A rare variant in APOC3(rs138326449) has been associated with triglyceride, very low-density lipoprotein, and high-density lipoprotein levels, as well as risk of coronary heart disease. We aimed to characterize the impact of this locus across a broad set of mainly lipids-focused metabolic measures.

METHODS AND RESULTS

A high-throughput serum nuclear magnetic resonance metabolomics platform was used to quantify 225 metabolic measures in 13 285 participants from 2 European population cohorts. We analyzed the effect of the APOC3 variant on the metabolic measures and used the common LPL(rs12678919) polymorphism to test for LPL-independent effects. Eighty-one metabolic measures showed evidence of association with APOC3(rs138326449). In addition to previously reported triglyceride and high-density lipoprotein associations, the variant was also associated with very low-density lipoprotein and high-density lipoprotein composition measures, other cholesterol measures, and fatty acids. Comparison of the APOC3 and LPL associations revealed that APOC3 association results for medium and very large very low-density lipoprotein composition are unlikely to be solely predictable by the action of APOC3 through LPL.

CONCLUSIONS

We characterized the effects of the rare APOC3(rs138326449) loss of function mutation in lipoprotein metabolism, as well as the effects of LPL(rs12678919). Our results improve our understanding of the role of APOC3 in triglyceride metabolism, its LPL independent action, and the complex and correlated nature of human metabolites.

Prolonged sleep restriction induces changes in pathways involved in cholesterol metabolism and inflammatory responses

Sleep loss and insufficient sleep are risk factors for cardiometabolic diseases, but data on how insufficient sleep contributes to these diseases are scarce. These questions were addressed using two approaches: an experimental, partial sleep restriction study (14 cases and 7 control subjects) with objective verification of sleep amount, and two independent epidemiological cohorts (altogether 2739 individuals) with questions of sleep insufficiency. In both approaches, blood transcriptome and serum metabolome were analysed. Sleep loss decreased the expression of genes encoding cholesterol transporters and increased expression in pathways involved in inflammatory responses in both paradigms. Metabolomic analyses revealed lower circulating large HDL in the population cohorts among subjects reporting insufficient sleep, while circulating LDL decreased in the experimental sleep restriction study. These findings suggest that prolonged sleep deprivation modifies inflammatory and cholesterol pathways at the level of gene expression and serum lipoproteins, inducing changes toward potentially higher risk for cardiometabolic diseases.

Association between social and built environments and leisure-time physical activity among Chinese older adults--a multilevel analysis

Background

Social and physical environments are not only hypothesized to influence physical activity (PA), they are also interrelated and influence each other. However, few studies have examined the relationships of PA with social and physical environments simultaneously. Accordingly, the current study aims to examine the association between physical and social attributes of neighborhood with leisure-time physical activity (LTPA) among the Chinese elders.

Methods

By employing a two-stage stratified random sampling procedure, 2783 elders were identified from 47 neighborhoods in Shanghai during July and September in 2014. Social and physical attributes of neighborhood were assessed using a validated and psychometrically tested measures, and the Chinese version of the International Physical Activity Questionnaire—Long Form was used to assess LTPA. Control variables included sex, age, marital status, education level, self-rated health and chronic conditions. Multilevel logistic regression analysis was conducted to explore whether individual- and neighborhood-level social and physical attributes were associated with LTPA.

Results

The overall prevalence of leisure-time active (LTA) was 46.6 %. After controlling for individual covariates, 1) compared to participants with the first quartile of social participation, the odds ratios of LTA for participants with the second, third and fourth quartile of social participation were 1.86 (95 % CI: 1.44–2.41), 2.37 (95 % CI: 1.82–3.08) and 4.27 (95 % CI: 3.27–5.58); 2) compared to participants with the first quartile of social cohesion, the odds ratios of LTA for participants with the second, third and fourth quartile of social cohesion were 1.09 (95 % CI: 1.07–1.20), 1.14 (95 % CI: 1.08–3.50) and 1.31 (95 % CI: 1.11–1.58); 3) compared to participants living in neighborhoods with the first quartile of walkability, the odds ratios of LTA for participants living in neighborhoods with the second, third and fourth quartile of walkability were 1.13 (95 % CI: 1.03–2.02), 1.73 (95 % CI: 1.12–3.21) and 1.85 (95 % CI: 1.19–3.35).

Conclusions

Both social and physical attribute of neighborhood associate with LTPA among Chinese older adults. It may promote LTPA among Chinese older adults to encourage them to participate in social activities, meanwhile, building walkable and cohesive neighborhoods.

Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics

Metabolomics is becoming common in epidemiology due to recent developments in quantitative profiling technologies and appealing results from their applications for understanding health and disease. Our team has developed an automated high-throughput serum NMR metabolomics platform that provides quantitative molecular data on 14 lipoprotein subclasses, their lipid concentrations and composition, apolipoprotein A-I and B, multiple cholesterol and triglyceride measures, albumin, various fatty acids as well as on numerous low-molecular-weight metabolites, including amino acids, glycolysis related measures and ketone bodies. The molar concentrations of these measures are obtained from a single serum sample with costs comparable to standard lipid measurements. We have analyzed almost 250 000 samples from around 100 epidemiological cohorts and biobanks and the new international set-up of multiple platforms will allow an annual throughput of more than 250 000 samples. The molecular data have been used to study type 1 and type 2 diabetes etiology as well as to characterize the molecular reflections of the metabolic syndrome, long-term physical activity, diet and lipoprotein metabolism. The results have revealed new biomarkers for early atherosclerosis, type 2 diabetes, diabetic nephropathy, cardiovascular disease and all-cause mortality. We have also combined genomics and metabolomics in diverse studies. We envision that quantitative high-throughput NMR metabolomics will be incorporated as a routine in large biobanks; this would make perfect sense both from the biological research and cost point of view - the standard output of over 200 molecular measures would vastly extend the relevance of the sample collections and make many separate clinical chemistry assays redundant.

mActive: A Randomized Clinical Trial of an Automated mHealth Intervention for Physical Activity Promotion

BACKGROUND

We hypothesized that a fully automated mobile health (mHealth) intervention with tracking and texting components would increase physical activity.

METHODS AND RESULTS

mActive enrolled smartphone users aged 18 to 69 years at an ambulatory cardiology center in Baltimore, Maryland. We used sequential randomization to evaluate the intervention's 2 core components. After establishing baseline activity during a blinded run-in (week 1), in phase I (weeks 2 to 3), we randomized 2:1 to unblinded versus blinded tracking. Unblinding allowed continuous access to activity data through a smartphone interface. In phase II (weeks 4 to 5), we randomized unblinded participants 1:1 to smart texts versus no texts. Smart texts provided smartphone-delivered coaching 3 times/day aimed at individual encouragement and fostering feedback loops by a fully automated, physician-written, theory-based algorithm using real-time activity data and 16 personal factors with a 10 000 steps/day goal. Forty-eight outpatients (46% women, 21% nonwhite) enrolled with a mean±SD age of 58±8 years, body mass index of 31±6 kg/m(2), and baseline activity of 9670±4350 steps/day. Daily activity data capture was 97.4%. The phase I change in activity was nonsignificantly higher in unblinded participants versus blinded controls by 1024 daily steps (95% confidence interval [CI], -580 to 2628; P=0.21). In phase II, participants receiving texts increased their daily steps over those not receiving texts by 2534 (95% CI, 1318 to 3750; P<0.001) and over blinded controls by 3376 (95% CI, 1951 to 4801; P<0.001).

CONCLUSIONS

An automated tracking-texting intervention increased physical activity with, but not without, the texting component. These results support new mHealth tracking technologies as facilitators in need of behavior change drivers.

CLINICAL TRIAL REGISTRATION

URL: http://ClinicalTrials.gov/. Unique identifier: NCT01917812.

Interrelationships Between Job Resources, Vigor, Exercise Habit, and Serum Lipids in Japanese Employees: a Multiple Group Path Analysis Using Medical Checkup Data

BACKGROUND

Physical inactivity is one of the major risk factors for dyslipidemia and coronary heart disease. Job resources have been identified as determinants of employees' vigor and physical activity habits.

PURPOSE

Our first purpose was to comprehensively analyze the series of relationships of job resources, through vigor and exercise habit (i.e., one aspect of physical activity), to serum lipid levels in a sample of Japanese employees in a manufacturing company. Our second purpose was to investigate sex differences in these relationships using a multiple-group path analysis.

METHODS

Data were collected from 4543 employees (men = 4018, women = 525) during a medical checkup conducted in February and March 2012. Job resources (job control, skill utilization, suitable jobs, and meaningfulness of work), vigor, exercise habit, triglyceride, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured cross-sectionally.

RESULTS

Job resources and vigor were positively associated with exercise habit in both sexes. Exercise habit was inversely associated with triglyceride (-0.03 in men and -0.01 in women, ps < 0.05) and LDL-C (-0.07 in both sexes, ps < 0.05). HDL-C was positively associated with exercise habit (0.03 in both sexes, ps < 0.05). There was no significant difference by sex in path coefficients, except for the covariance between suitable jobs and meaningfulness of work.

CONCLUSION

Higher levels of job resources were associated with greater vigor, leading to exercise habit, which in turn, improved serum lipid levels. Longitudinal studies are required to demonstrate causality.

Physical activity, fitness, glucose homeostasis, and brain morphology in twins

PURPOSE

The main aim of the present study (FITFATTWIN) was to investigate how physical activity level is associated with body composition, glucose homeostasis, and brain morphology in young adult male monozygotic twin pairs discordant for physical activity.

METHODS

From a population-based twin cohort, we systematically selected 10 young adult male monozygotic twin pairs (age range, 32-36 yr) discordant for leisure time physical activity during the past 3 yr. On the basis of interviews, we calculated a mean sum index for leisure time and commuting activity during the past 3 yr (3-yr LTMET index expressed as MET-hours per day). We conducted extensive measurements on body composition (including fat percentage measured by dual-energy x-ray absorptiometry), glucose homeostasis including homeostatic model assessment index and insulin sensitivity index (Matsuda index, calculated from glucose and insulin values from an oral glucose tolerance test), and whole brain magnetic resonance imaging for regional volumetric analyses.

RESULTS

According to pairwise analysis, the active twins had lower body fat percentage (P = 0.029) and homeostatic model assessment index (P = 0.031) and higher Matsuda index (P = 0.021) compared with their inactive co-twins. Striatal and prefrontal cortex (subgyral and inferior frontal gyrus) brain gray matter volumes were larger in the nondominant hemisphere in active twins compared with those in inactive co-twins, with a statistical threshold of P < 0.001.

CONCLUSIONS

Among healthy adult male twins in their mid-30s, a greater level of physical activity is associated with improved glucose homeostasis and modulation of striatum and prefrontal cortex gray matter volume, independent of genetic background. The findings may contribute to later reduced risk of type 2 diabetes and mobility limitations.

Organ-specific physiological responses to acute physical exercise and long-term training in humans

Virtually all tissues in the human body rely on aerobic metabolism for energy production and are therefore critically dependent on continuous supply of oxygen. Oxygen is provided by blood flow, and, in essence, changes in organ perfusion are also closely associated with alterations in tissue metabolism. In response to acute exercise, blood flow is markedly increased in contracting skeletal muscles and myocardium, but perfusion in other organs (brain and bone) is only slightly enhanced or is even reduced (visceral organs). Despite largely unchanged metabolism and perfusion, repeated exposures to altered hemodynamics and hormonal milieu produced by acute exercise, long-term exercise training appears to be capable of inducing effects also in tissues other than muscles that may yield health benefits. However, the physiological adaptations and driving-force mechanisms in organs such as brain, liver, pancreas, gut, bone, and adipose tissue, remain largely obscure in humans. Along these lines, this review integrates current information on physiological responses to acute exercise and to long-term physical training in major metabolically active human organs. Knowledge is mostly provided based on the state-of-the-art, noninvasive human imaging studies, and directions for future novel research are proposed throughout the review.

Sex hormone-binding globulin associations with circulating lipids and metabolites and the risk for type 2 diabetes: observational and causal effect estimates

BACKGROUND

The causal role of circulating sex hormone-binding globulin (SHBG) for type 2 diabetes is controversial. Information on the relations between SHBG and new biomarkers of cardiometabolic risk is scarce.

METHODS

We applied quantitative nuclear magnetic resonance metabolomics in three Finnish population-based cohorts to comprehensively profile circulating lipids and metabolites and study their associations with SHBG. Mendelian randomization was used to examine potential causality of SHBG on the metabolic measures and insulin resistance. Prospective associations and causal effect estimates of SHBG on type 2 diabetes were assessed via meta-analysis including summary statistics from the DIAGRAM consortium.

RESULTS

In cross-sectional analysis in 6475 young adults (mean age 31, 57% men), higher SHBG was linked with a more favourable cardiometabolic risk profile, including associations with lipoprotein subclasses, fatty acid composition, amino acids, ketone bodies and inflammation-linked glycoproteins. Prospective analysis of 1377 young adults with 6-year follow-up indicated that SHBG is also associated with future insulin resistance. Mendelian randomization suggested only minor, if any, causal effects of SHBG on lipid and metabolite measures and insulin resistance(n = 10,895).Causal effect estimates on type 2 diabetes for 41,439 cases and 103,870 controls indicated a causative protective role of SHBG (OR = 0.83 per 1-SD, 95% CI: 0.76, 0.91); however, effects were considerably weaker than observed in meta-analysis of prospective studies [hazard ratio (HR) = 0.47 per 1-SD, 95% CI: 0.41, 0.53].

CONCLUSION

Circulating SHBG is strongly associated with systemic metabolism and predictive for insulin resistance and diabetes. The weaker causal estimates suggest that the observational associations are partly confounded rather than conferred directly via circulating SHBG.

The Human Blood Metabolome-Transcriptome Interface

Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the 'human blood metabolome-transcriptome interface' (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.

Health-Related Findings Among Twin Pairs Discordant for Leisure-Time Physical Activity for 32 Years: The TWINACTIVE Study Synopsis

We are lacking very long-term and controlled intervention studies investigating the effects of habitual physical activity on health-related factors. To address this gap, we performed a natural experiment by identifying same-sex twin pairs in which the co-twins of each pair differed with respect to leisure-time physical-activity habits throughout their adult life. Our criterion for the discordance was that the same co-twin had a higher leisure time-activity volume than that of the other member of the pair at the majority –– if not all –– of the follow-up time points according to reported/interviewed physical-activity data. Overall, we identified and conducted multidimensional health-related measurements (including fitness, body composition, cardiometabolic risk factor levels, bone and arterial status, and exercise motivation) of 16 twin pairs (seven monozygotic (MZ) and nine dizygotic (DZ) pairs, mean age 60 years) who had persistent discordance in leisure-time physical-activity habits over three decades (TWINACTIVE study). In our discordant-pair study design, after adjusting for sequence-level genes, both systemic-level metabolic, and site-specific structural findings differed significantly in the pairwise analysis in MZ pairs only. These findings included intrapair differences in accumulated fat depots and structure of heart, arteries, and bones. In addition, our study revealed intrapair differences in metabolic and regulatory pathways, which may partly explain the mechanistic links between long-term physical activity, phenotypic changes, and decreased risk of cardiometabolic diseases.

Former male elite athletes have better metabolic health in late life than their controls

Elite-class athletes have longer life expectancy and lower risk for chronic noncommunicable diseases possibly because of physically active and healthier lifestyle. In this study, we assessed former male Finnish elite-class athletes' (n = 392) and their matched controls' (n = 207) body composition, and risk for the metabolic syndrome (MS) and nonalcoholic fatty liver disease (NAFLD) in later life. Compared with the controls, the former athletes had lower body fat percentage (24.8% vs 26.0%, P = 0.021), lower risk for MS [odds ratio (OR) 0.57, 95% confidence interval (CI) 0.40-0.81], and NAFLD (OR 0.61, 95% CI 0.42-0.88). High volume of current leisure-time physical activity (LTPA) was associated with lower body fat percentage (P for trend < 0.001). When current volume of LTPA increased 1 MET h/week, the risk of MS and NAFLD decreased (OR 0.99, 95% CI 0.98-0.99 and OR 0.97, 95% CI 0.96-0.98, respectively). Although a career as an elite-class athlete during young adulthood may help to protect from developing metabolic syndrome, present exercise levels and volume of LTPA seem equally important as well.

Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts

BACKGROUND

High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.

METHODS AND RESULTS

We applied quantitative nuclear magnetic resonance metabolomics to identify the biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the National Finnish FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the Southall and Brent Revisited (SABRE) study (n=2622; 573 events) and British Women's Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes mellitus, and medication. When further adjusting for routine lipids, 4 metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation, 1.18; 95% confidence interval, 1.12-1.24; P=4×10(-10)) and monounsaturated fatty acid levels (1.17; 1.11-1.24; P=1×10(-8)) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84-0.94; P=6×10(-5)) and docosahexaenoic acid levels (0.90; 0.86-0.95; P=5×10(-5)) were associated with lower risk. A risk score incorporating these 4 biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the 2 validation cohorts (relative integrated discrimination improvement, 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5% to 10% risk range (net reclassification, 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289).

CONCLUSIONS

Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated fatty acids, and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment.