Long-term leisure-time physical activity and serum metabolome

A Plasma Metabolite Score Related to Psychological Distress and Diabetes Risk: A Nested Case-control Study in US Women

CONTEXT

Psychological distress has been linked to diabetes risk. Few population-based, epidemiologic studies have investigated the potential molecular mechanisms (eg, metabolic dysregulation) underlying this association.

OBJECTIVE

To evaluate the association between a metabolomic signature for psychological distress and diabetes risk.

METHODS

We conducted a nested case-control study of plasma metabolomics and diabetes risk in the Nurses' Health Study, including 728 women (mean age: 55.2 years) with incident diabetes and 728 matched controls. Blood samples were collected between 1989 and 1990 and incident diabetes was diagnosed between 1992 and 2008. Based on our prior work, we calculated a weighted plasma metabolite-based distress score (MDS) comprised of 19 metabolites. We used conditional logistic regression accounting for matching factors and other diabetes risk factors to estimate odds ratios (OR) and 95% confidence intervals (CI) for diabetes risk according to MDS.

RESULTS

After adjusting for sociodemographic factors, family history of diabetes, and health behaviors, the OR (95% CI) for diabetes risk across quintiles of the MDS was 1.00 (reference) for Q1, 1.16 (0.77, 1.73) for Q2, 1.30 (0.88, 1.91) for Q3, 1.99 (1.36, 2.92) for Q4, and 2.47 (1.66, 3.67) for Q5. Each SD increase in MDS was associated with 36% higher diabetes risk (95% CI: 1.21, 1.54; P-trend <.0001). This association was moderately attenuated after additional adjustment for body mass index (comparable OR: 1.17; 95% CI: 1.02, 1.35; P-trend = .02). The MDS explained 17.6% of the association between self-reported psychological distress (defined as presence of depression or anxiety symptoms) and diabetes risk (P = .04).

CONCLUSION

MDS was significantly associated with diabetes risk in women. These results suggest that differences in multiple lipid and amino acid metabolites may underlie the observed association between psychological distress and diabetes risk.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility

BACKGROUND

Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance.

METHODS

In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI).

FINDINGS

The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92).

INTERPRETATION

The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

Maternal metabolic profiling across body mass index groups: An exploratory longitudinal study

INTRODUCTION

Increased BMI has been identified as a risk factor for most pregnancy complications, but the underlying metabolic factors mediating the detrimental effects of BMI are largely unknown. We aimed to compare metabolic profiles in overweight/obese women (body mass index [BMI] ≥ 25 kg/m2 ) and normal weight/underweight women (BMI < 25 kg/m2 ) across gestation. We also explored how gestational weight gain (GWG) affected maternal metabolic profiles.

MATERIAL AND METHODS

Exploratory nested case-control study based on a prospective longitudinal cohort of women who were healthy prior to pregnancy and gave birth at Oslo University Hospital from 2002 to 2008. The sample consisted of 48 women who were overweight/obese and 59 normal-weight/underweight women. Plasma samples from four time points in pregnancy (weeks 14-16, 22-24, 30-32 and 36-38) were analyzed by nuclear magnetic resonance spectroscopy and 91 metabolites were measured. Linear regression models were fitted for each of the metabolites at each time point.

RESULTS

Overweight or obese women had higher levels of lipids in very-low-density lipoprotein (VLDL), total triglycerides, triglycerides in VLDL, total fatty acids, monounsaturated fatty acids, saturated fatty acids, leucine, valine, and total branched-chain amino acids in pregnancy weeks 14-16 compared to underweight and normal-weight women. Docosahexaenoic acid and degree of unsaturation were significantly lower in overweight/obese women in pregnancy weeks 36-38. In addition, overweight or obese women had higher particle concentration of XXL-VLDL and glycoprotein acetyls (GlycA) at weeks 14-16 and 30-32. GWG did not seem to affect the metabolic profile, regardless of BMI group when BMI was treated as a dichotomous variable, ≥25 kg/m2 (yes/no).

CONCLUSIONS

Overweight or obese women had smaller pregnancy-related metabolic alterations than normal-weight/underweight women. There was a trend toward higher triglyceride and VLDL particle concentration in overweight/obese women. As this was a hypothesis-generating study, the similarities with late-onset pre-eclampsia warrant further investigation. The unfavorable development of fatty acid composition in overweight/obese women, with possible implication for the offspring, should also be studied further in the future.

Research advances in the application of metabolomics in exercise science

Exercise training can lead to changes in the metabolic composition of an athlete's blood, the magnitude of which depends largely on the intensity and duration of exercise. A variety of behavioral, biochemical, hormonal, and immunological biomarkers are commonly used to assess an athlete's physical condition during exercise training. However, traditional invasive muscle biopsy testing methods are unable to comprehensively detect physiological differences and metabolic changes in the body. Metabolomics technology is a high-throughput, highly sensitive technique that provides a comprehensive assessment of changes in small molecule metabolites (molecular weight <1,500 Da) in the body. By measuring the overall metabolic characteristics of biological samples, we can study the changes of endogenous metabolites in an organism or cell at a certain moment in time, and investigate the interconnection and dynamic patterns between metabolites and physiological changes, thus further understanding the interactions between genes and the environment, and providing possibilities for biomarker discovery, precise training and nutritional programming of athletes. This paper summaries the progress of research on the application of exercise metabolomics in sports science, and looks forward to the future development of exercise metabolomics, with a view to providing new approaches and perspectives for improving human performance, promoting exercise against chronic diseases, and advancing sports science research.

Human HDL subclasses modulate energy metabolism in skeletal muscle cells

In addition to its antiatherogenic role, HDL reportedly modulates energy metabolism at the whole-body level. HDL functionality is associated with its structure and composition, and functional activities can differ between HDL subclasses. Therefore, we studied if HDL2 and HDL3, the two major HDL subclasses, are able to modulate energy metabolism of skeletal muscle cells. Differentiated mouse and primary human skeletal muscle myotubes were used to investigate the influences of human HDL2 and HDL3 on glucose and fatty uptake and oxidation. HDL-induced changes in lipid distribution and mRNA expression of genes related to energy substrate metabolism, mitochondrial function, and HDL receptors were studied with human myotubes. Additionally, we examined the effects of apoA-I and discoidal, reconstituted HDL particles on substrate metabolism. In mouse myotubes, HDL subclasses strongly enhanced glycolysis upon high and low glucose concentrations. HDL3 caused a minor increase in ATP-linked respiration upon glucose conditioning but HDL2 improved complex I-mediated mitochondrial respiration upon fatty acid treatment. In human myotubes, glucose metabolism was attenuated but fatty acid uptake and oxidation were markedly increased by both HDL subclasses, which also increased mRNA expression of genes related to fatty acid metabolism and HDL receptors. Finally, both HDL subclasses induced incorporation of oleic acid into different lipid classes. These results, demonstrating that HDL subclasses enhance fatty acid oxidation in human myotubes but improve anaerobic metabolism in mouse myotubes, support the role of HDL as a circulating modulator of energy metabolism. Exact mechanisms and components of HDL causing the change, require further investigation.

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease Among Low-Income Black and White Americans

BACKGROUND

Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

METHODS

In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults.

RESULTS

Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score (r=0.61) and inverse association with CHD (odds ratio, 0.57 [0.49-0.65]), robust to adjustment for LE8 score and across participants with different sociodemographic and health status ([odds ratios, 0.42-0.69]; all P<0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort (r=0.49; odds ratio, 0.57 [0.46-0.69]).

CONCLUSIONS

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

Metabolomic Signatures of Sedentary Behavior and Cardiometabolic Traits in US Hispanics/Latinos: Results from HCHS/SOL

PURPOSE

The aim of this study was to understand the serum metabolomic signatures of moderate-to-vigorous physical activity (MVPA) and sedentary behavior, and further associate their metabolomic signatures with incident cardiometabolic diseases.

METHODS

This analysis included 2711 US Hispanics/Latinos from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) aged 18-74 yr (2008-2011). An untargeted, liquid chromatography-mass spectrometry was used to profile the serum metabolome. The associations of metabolites with accelerometer-measured MVPA and sedentary time were examined using survey linear regressions adjusting for covariates. The weighted correlation network analysis identified modules of correlated metabolites in relation to sedentary time, and the modules were associated with incident diabetes, dyslipidemia, and hypertension over the 6-yr follow-up.

RESULTS

Of 624 metabolites, 5 and 102 were associated with MVPA and sedentary behavior at false discovery rate (FDR) <0.05, respectively, after adjusting for socioeconomic and lifestyle factors. The weighted correlation network analysis identified 8 modules from 102 metabolites associated with sedentary time. Four modules (branched-chain amino acids, erythritol, polyunsaturated fatty acid, creatine) were positively, and the other four (acyl choline, plasmalogen glycerol phosphatidyl choline, plasmalogen glycerol phosphatidyl ethanolamine, urea cycle) were negatively correlated with sedentary time. Among these modules, a higher branched-chain amino acid score and a lower plasmalogen glycerol phosphatidyl choline score were associated with increased risks of diabetes and dyslipidemia. A higher erythritol score was associated with an increased risk of diabetes, and a lower acyl choline score was linked to an increased risk of hypertension.

CONCLUSIONS

In this study of US Hispanics/Latinos, we identified multiple serum metabolomic signatures of sedentary behavior and their associations with risk of incident diabetes, hypertension, and dyslipidemia. These findings suggest a potential role of circulating metabolites in the links between sedentary behavior and cardiometabolic diseases.

Plasma metabolite profiles associated with the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and future risk of cardiovascular disease and type 2 diabetes

BACKGROUND

A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk.

METHODS

In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models.

RESULTS

The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38-0.77 for dichotomous HL, and 0.22, 0.11-0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42-0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31-1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile.

CONCLUSIONS

In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD.

TRIAL REGISTRATION

The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).

Aerobic exercise training and gut microbiome-associated metabolic shifts in women with overweight: a multi-omic study

Physical activity is essential in weight management, improves overall health, and mitigates obesity-related risk markers. Besides inducing changes in systemic metabolism, habitual exercise may improve gut's microbial diversity and increase the abundance of beneficial taxa in a correlated fashion. Since there is a lack of integrative omics studies on exercise and overweight populations, we studied the metabolomes and gut microbiota associated with programmed exercise in obese individuals. We measured the serum and fecal metabolites of 17 adult women with overweight during a 6-week endurance exercise program. Further, we integrated the exercise-responsive metabolites with variations in the gut microbiome and cardiorespiratory parameters. We found clear correlation with several serum and fecal metabolites, and metabolic pathways, during the exercise period in comparison to the control period, indicating increased lipid oxidation and oxidative stress. Especially, exercise caused co-occurring increase in levels of serum lyso-phosphatidylcholine moieties and fecal glycerophosphocholine. This signature was associated with several microbial metagenome pathways and the abundance of Akkermansia. The study demonstrates that, in the absence of body composition changes, aerobic exercise can induce metabolic shifts that provide substrates for beneficial gut microbiota in overweight individuals.

The Association of Metabolomic Profiles of a Healthy Lifestyle with Heart Failure Risk in a Prospective Study

Lifestyle has been linked to the incidence of heart failure, but the underlying biological mechanisms remain unclear. Using the metabolomic, lifestyle, and heart failure data of the UK Biobank, we identified and validated healthy lifestyle-related metabolites in a matched case-control and cohort study, respectively. We then evaluated the association of healthy lifestyle-related metabolites with heart failure (HF) risk and the added predictivity of these healthy lifestyle-associated metabolites for HF. Of 161 metabolites, 8 were identified to be significantly related to healthy lifestyle. Notably, omega-3 fatty acids and docosahexaenoic acid (DHA) positively associated with a healthy lifestyle score (HLS) and exhibited a negative association with heart failure risk. Conversely, creatinine negatively associated with a HLS, but was positively correlated with the risk of HF. Adding these three metabolites to the classical risk factor prediction model, the prediction accuracy of heart failure incidence can be improved as assessed by the C-statistic (increasing from 0.806 [95% CI, 0.796-0.816] to 0.844 [95% CI, 0.834-0.854], p-value < 0.001). A healthy lifestyle is associated with significant metabolic alterations, among which metabolites related to healthy lifestyle may be critical for the relationship between healthy lifestyle and HF. Healthy lifestyle-related metabolites might enhance HF prediction, but additional validation studies are necessary.

Normal range CAG repeat size variations in the HTT gene are associated with an adverse lipoprotein profile partially mediated by body mass index

Tandem cytosine-adenine-guanine (CAG) repeat sizes of 36 or more in the huntingtin gene (HTT) cause Huntington's disease (HD). Apart from neuropsychiatric complications, the disease is also accompanied by metabolic dysregulation and weight loss, which contribute to a progressive functional decline. Recent studies also reported an association between repeats below the pathogenic threshold (<36) for HD and body mass index (BMI), suggesting that HTT repeat sizes in the non-pathogenic range are associated with metabolic dysregulation. In this study, we hypothesized that HTT repeat sizes < 36 are associated with metabolite levels, possibly mediated through reduced BMI. We pooled data from three European cohorts (n = 10 228) with genotyped HTT CAG repeat size and metabolomic measurements. All 145 metabolites were measured on the same targeted platform in all studies. Multilevel mixed-effects analysis using the CAG repeat size in HTT identified 67 repeat size metabolite associations. Overall, the metabolomic profile associated with larger CAG repeat sizes in HTT were unfavorable-similar to those of higher risk of coronary artery disease and type 2 diabetes-and included elevated levels of amino acids, fatty acids, low-density lipoprotein (LDL)-, very low-density lipoprotein- and intermediate density lipoprotein (IDL)-related metabolites while with decreased levels of very large high-density lipoprotein (HDL)-related metabolites. Furthermore, the associations of 50 metabolites, in particular, specific very large HDL-related metabolites, were mediated by lower BMI. However, no mediation effect was found for 17 metabolites related to LDL and IDL. In conclusion, our findings indicate that large non-pathogenic CAG repeat sizes in HTT are associated with an unfavorable metabolomic profile despite their association with a lower BMI.

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease among Low-Income Black and White Americans

Background and Aims

Life's Essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

Methods

In a nested case-control study of coronary heart disease (CHD) among 598 Black and 596 White low-income Americans, we estimated LE8 score, conducted untargeted plasma metabolites profiling, and used elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. Mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 598 Chinese adults.

Results

Higher LE8 score was associated with lower CHD risk [standardized OR (95% CI)=0.61 (0.53-0.69)]. The identified MetaSig, consisting of 133 metabolites, showed strong correlation with LE8 score ( r =0.61) and inverse association with CHD risk [OR (95% CI)=0.57 (0.49-0.65)], robust to adjustment for LE8 score and across participants with different sociodemographic and health status (ORs: 0.42-0.69; all P <0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%) ( P <0.001). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort [ r =0.49; OR (95% CI)=0.57 (0.46-0.69)].

Conclusions

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective and comprehensive measure of LE8 score and its metabolic phenotype relevant to CHD prevention among diverse populations.

Efficacy of an mHealth Behavior Change Intervention for Promoting Physical Activity in the Workplace: Randomized Controlled Trial

BACKGROUND

Insufficient physical activity (PA) is a well-established risk factor for several noncommunicable diseases such as cardiovascular diseases, cancer, diabetes, depression, and dementia. The World Health Organization (WHO) advises that individuals engage in 150 minutes of moderate PA per week or 75 minutes of intense PA per week. According to the WHO's latest report, 23% of adults fail to meet the minimum recommended level of PA. The percentage was even higher in a recent global study that showed 27% of adults were insufficiently active and reported a 5% increase in the prevalence trend of insufficient PA between 2001 and 2016. The study also showed the rate of insufficient PA among countries varied significantly. For instance, it was estimated that 40% were insufficiently active in the United States, and the percentage was even higher in Saudi Arabia (more than 50%). Governments are actively developing policies and methods to successfully establish a PA-inducing environment that encourages a healthy lifestyle in order to address the global steady decline in PA.

OBJECTIVE

The purpose of this study was to determine the effectiveness of mobile health (mHealth) interventions, particularly SMS text messaging interventions, to improve PA and decrease BMI in healthy adults in the workplace.

METHODS

In this parallel, 2-arm randomized controlled trial, healthy adults (N=327) were randomized to receive an mHealth intervention (tailored text messages combined with self-monitoring (intervention; n=166) or no intervention (control; n=161). Adults who were fully employed in an academic institution and had limited PA during working hours were recruited for the study. Outcomes, such as PA and BMI, were assessed at baseline and 3 months later.

RESULTS

Results showed significant improvement in PA levels (weekly step counts) in the intervention group (β=1097, 95% CI 922-1272, P<.001). There was also a significant reduction in BMI (β=0.60, 95% CI 0.50-0.69, P<.001).

CONCLUSIONS

Combining tailored text messages and self-monitoring interventions to improve PA and lower BMI was significantly effective and has the potential to leverage current methods to improve wellness among the public.

Association between Nordic and Mediterranean diets with lipoprotein phenotype assessed by 1HNMR in children with familial hypercholesterolemia

BACKGROUND AND AIMS

Both Nordic and Mediterranean diets are considered healthy despite notable regional differences. Although these dietary patterns may lower cardiovascular risk, it is unclear if they improve the lipoprotein phenotype in children with familial hypercholesterolemia (FH). The aim is to determine the impact of Nordic and Mediterranean diets on the advanced lipoprotein profile in children with heterozygous FH (HeFH).

METHODS

This was a cross-sectional study performed in children with FH recruited from the Lipid Clinics at Sant Joan University Hospital in Reus (Spain) and Oslo University Hospital (Norway). Two-hundred fifty-six children (mean age 10 y/o; 48% girls): 85 Spanish and 29 Norwegian FH children, and 142 non-FH healthy controls (119 from Spain and 23 from Norway) were included in the study. A pathogenic FH-associated genetic variant was present in 81% of Spanish children with FH and all Norwegian children with FH. An ¹H NMR based advanced lipoprotein test (Nightingale®) providing information on the particle number, size and lipid composition of 14 lipoprotein subclasses was performed and correlated to the dietary components.

RESULTS

Levels of LDL-C, HDL-C and triglycerides were not significantly different between the Nordic and Mediterranean FH groups. Spanish children with FH had more LDL particles, mainly of the large and medium LDL subclasses, than Norwegian FH children. Spanish FH children also had more HDL particles, mainly medium and small, than Norwegian FH children. The mean LDL size of Spanish FH children was larger, while the HDL size was smaller than that of the Norwegian FH children. The HDL particle number and size were the main determinants of differences between the two groups. In Norwegian children with FH, dietary total fat and MUFAs showed a significant correlation with all apolipoprotein B-containing lipoproteins and LDL size, whereas there was no correlation to SFA. A weaker association pattern was observed in the Spanish children.

CONCLUSIONS

The lipoprotein profiles of Spanish and Norwegian children showed differences when studied by ¹H NMR. These differences were in part associated with differences in dietary patterns.

Exploring the association of physical activity with the plasma and urine metabolome in adolescents and young adults

BACKGROUND

Regular physical activity elicits many health benefits. However, the underlying molecular mechanisms through which physical activity influences overall health are less understood. Untargeted metabolomics enables system-wide mapping of molecular perturbations which may lend insights into physiological responses to regular physical activity. In this study, we investigated the associations of habitual physical activity with plasma and urine metabolome in adolescents and young adults.

METHODS

This cross-sectional study included participants from the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study with plasma samples n = 365 (median age: 18.4 (18.1, 25.0) years, 58% females) and 24 h urine samples n = 215 (median age: 18.1 (17.1, 18.2) years, 51% females). Habitual physical activity was assessed using a validated Adolescent Physical Activity Recall Questionnaire. Plasma and urine metabolite concentrations were determined using ultra-high-performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) methods. In a sex-stratified analysis, we conducted principal component analysis (PCA) to reduce the dimensionality of metabolite data and to create metabolite patterns. Multivariable linear regression models were then applied to assess the associations between self-reported physical activity (metabolic equivalent of task (MET)-hours per week) with single metabolites and metabolite patterns, adjusted for potential confounders and controlling the false discovery rate (FDR) at 5% for each set of regressions.

RESULTS

Habitual physical activity was positively associated with the "lipid, amino acids and xenometabolite" pattern in the plasma samples of male participants only (β = 1.02; 95% CI: 1.01, 1.04, p = 0.001, adjusted p = 0.042). In both sexes, no association of physical activity with single metabolites in plasma and urine and metabolite patterns in urine was found (all adjusted p > 0.05).

CONCLUSIONS

Our explorative study suggests that habitual physical activity is associated with alterations of a group of metabolites reflected in the plasma metabolite pattern in males. These perturbations may lend insights into some of underlying mechanisms that modulate effects of physical activity.

Maternal first trimester metabolic profile in pregnancies with transposition of the great arteries

BACKGROUND

Higher maternal body mass index (BMI) and abnormal glucose metabolism during early pregnancy are associated with congenital heart defects in the offspring, but the exact mechanisms are unknown.

METHODS

We evaluated the association between maternal first trimester metabolic profile and transposition of the great arteries (TGA) in the offspring in a matched case-control study with 100 TGA mothers and 200 controls born in Finland during 2004-2014. Cases and controls were matched by birth year, child sex, and maternal age and BMI. Serum samples collected between 10- and 14-weeks of gestation were analyzed for 73 metabolic measures. Conditional logistic regression was used to assess the risk for TGA in the offspring, and a subgroup analysis among mothers with high BMI was conducted.

RESULTS

Higher concentrations of four subtypes of extremely large very-low-density lipoprotein (VLDL) particles and one of large VLDL particles were observed in TGA mothers. This finding did not reach statistical significance after multiple testing correction. The pooled odds ratio (OR) of the all metabolic variables was slightly higher in TGA mothers in the subgroup with maternal BMI over 25 (OR 1.25) and significantly higher in the subgroup with maternal BMI over 30 (OR 1.95) compared to the original population (OR 1.18).

CONCLUSIONS

Our findings indicate that an abnormal maternal early pregnancy metabolic profile might be associated with TGA in the offspring, especially in obese mothers. A trend indicating altered VLDL subtype composition in TGA pregnancies warrants further research.

Association of physical activity with metabolic profile from adolescence to adulthood

OBJECTIVE

Physical activity benefits cardiometabolic health, but little is known about its detailed links with serum lipoproteins, amino acids, and glucose metabolism at young age. We therefore studied the association of physical activity with a comprehensive metabolic profile measured repeatedly in adolescence.

METHODS

The cohort is derived from the longitudinal Special Turku Coronary Risk Factor Intervention Project. At ages 13, 15, 17, and 19 years, data on physical activity were collected by a questionnaire, and circulating metabolic measures were quantified by nuclear magnetic resonance metabolomics from repeatedly assessed serum samples (age 13: n = 503, 15: n = 472, 17: n = 466, and 19: n = 361).

RESULTS

Leisure-time physical activity (LTPA;MET h/wk) was directly associated with concentrations of polyunsaturated fatty acids, and inversely with the ratio of monounsaturated fatty acids to total fatty acids (-0.006SD; [-0.008, -0.003]; p < 0.0001). LTPA was inversely associated with very-low-density lipoprotein (VLDL) particle concentration (-0.003SD; [-0.005, -0.001]; p = 0.002) and VLDL particle size (-0.005SD; [-0.007, -0.003]; p < 0.0001). LTPA showed direct association with the particle concentration and size of high-density lipoprotein (HDL), and HDL cholesterol concentration (0.004SD; [0.002, 0.006]; p < 0.0001). Inverse associations of LTPA with triglyceride and total lipid concentrations in large to small sized VLDL subclasses were found. Weaker associations were seen for other metabolic measures including inverse associations with concentrations of lactate, isoleucine, glycoprotein acetylation, and a direct association with creatinine concentration. The results remained after adjusting for body mass index and proportions of energy intakes from macronutrients.

CONCLUSIONS

Physical activity during adolescence is beneficially associated with the metabolic profile including novel markers. The results support recommendations on physical activity during adolescence to promote health and possibly reduce future disease risks.

Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic

BACKGROUND/OBJECTIVE

This observational study dissects the complex temporal associations between body-mass index (BMI), waist-hip ratio (WHR) and circulating metabolomics using a combination of longitudinal and cross-sectional population-based datasets and new systems epidemiology tools.

SUBJECTS/METHODS

Firstly, a data-driven subgrouping algorithm was employed to simplify high-dimensional metabolic profiling data into a single categorical variable: a self-organizing map (SOM) was created from 174 metabolic measures from cross-sectional surveys (FINRISK, n = 9708, ages 25-74) and a birth cohort (NFBC1966, n = 3117, age 31 at baseline, age 46 at follow-up) and an expert committee defined four subgroups of individuals based on visual inspection of the SOM. Secondly, the subgroups were compared regarding BMI and WHR trajectories in an independent longitudinal dataset: participants of the Young Finns Study (YFS, n = 1286, ages 24-39 at baseline, 10 years follow-up, three visits) were categorized into the four subgroups and subgroup-specific age-dependent trajectories of BMI, WHR and metabolic measures were modelled by linear regression.

RESULTS

The four subgroups were characterised at age 39 by high BMI, WHR and dyslipidemia (designated TG-rich); low BMI, WHR and favourable lipids (TG-poor); low lipids in general (Low lipid) and high low-density-lipoprotein cholesterol (High LDL-C). Trajectory modelling of the YFS dataset revealed a dynamic BMI divergence pattern: despite overlapping starting points at age 24, the subgroups diverged in BMI, fasting insulin (three-fold difference at age 49 between TG-rich and TG-poor) and insulin-associated measures such as triglyceride-cholesterol ratio. Trajectories also revealed a WHR progression pattern: despite different starting points at the age of 24 in WHR, LDL-C and cholesterol-associated measures, all subgroups exhibited similar rates of change in these measures, i.e. WHR progression was uniform regardless of the cross-sectional metabolic profile.

CONCLUSIONS

Age-associated weight variation in adults between 24 and 49 manifests as temporal divergence in BMI and uniform progression of WHR across metabolic health strata.

Healthy lifestyle, plasma metabolites, and risk of cardiovascular disease among individuals with diabetes

BACKGROUND AND AIMS

Lifestyle management is a fundamental aspect of diabetes care to prevent cardiovascular disease (CVD); however, the underlying metabolic mechanism is not well established. We aimed to identify metabolites associated with different lifestyle factors, and estimate their mediating roles between lifestyle and CVD risk among people with diabetes.

METHODS

Lifestyle and metabolomic data were available for 5072 participants with diabetes who were free of CVD at baseline in the UK Biobank. The healthy level of 5 lifestyle factors was defined as non-central obesity, non-current smoking, moderate alcohol intake, physically active, and healthy diet. A total of 44 biomarkers across 7 metabolic pathways including lipoprotein particles, fatty acids, amino acids, fluid balance, inflammation, ketone bodies, and glycolysis were quantified by nuclear magnetic resonance (NMR) spectroscopy.

RESULTS

All 44 assayed metabolites were significantly associated with at least one lifestyle factor. Approximately half of metabolites, which were mostly lipoprotein particles and fatty acids, showed a mediating effect between at least one lifestyle factor and CVD risk. NMR metabolites jointly mediated 43.4%, 30.0%, 16.8%, 43.4%, and 65.5% of the association of non-central obesity, non-current smoking, moderate alcohol intake, physically active, and healthy diet with lower CVD risk, respectively. In general, though metabolites that significantly associated with lifestyle were mostly different across the 5 lifestyle factors, the pattern of association was consistent between fatty acids and all 5 lifestyle factors. Further, fatty acids showed significant mediating effects in the association between all 5 lifestyle factors and CVD risk with mediation proportion ranging from 12.2% to 26.8%.

CONCLUSIONS

There were large-scale differences in circulating NMR metabolites between individuals with diabetes who adhered to a healthy lifestyle and those did not. Differences in metabolites, especial fatty acids, could partially explain the association between adherence to multiple healthy lifestyle and lower CVD risk among people with diabetes.

Extracellular vesicles and high-density lipoproteins: Exercise and oestrogen-responsive small RNA carriers

Decreased systemic oestrogen levels (i.e., menopause) affect metabolic health. However, the detailed mechanisms underlying this process remain unclear. Both oestrogens and exercise have been shown to improve metabolic health, which may be partly mediated by circulating microRNA (c-miR) signalling. In recent years, extracellular vesicles (EV) have increased interest in the field of tissue crosstalk. However, in many studies on EV-carried miRs, the co-isolation of high-density lipoprotein (HDL) particles with EVs has not been considered, potentially affecting the results. Here, we demonstrate that EV and HDL particles have distinct small RNA (sRNA) content, including both host and nonhost sRNAs. Exercise caused an acute increase in relative miR abundancy in EVs, whereas in HDL particles, it caused an increase in transfer RNA-derived sRNA. Furthermore, we demonstrate that oestrogen-based hormonal therapy (HT) allows the acute exercise-induced miR-response to occur in both EV and HDL particles in postmenopausal women, while the response was absent in nonusers.

Cross-sectionally calculated metabolic ageing does not relate to longitudinal metabolic changes - support for stratified ageing models

CONTEXT

Ageing varies between individuals with profound consequences for chronic diseases and longevity. One hypothesis to explain the diversity is a genetically regulated molecular clock that runs differently between individuals. Large and long enough human studies to test the hypothesis are rare due to practical challenges, but statistical models of ageing are built as proxies for the molecular clock by comparing young and old individuals cross-sectionally. These models remain untested against longitudinal data.

OBJECTIVE

We applied novel methodology to test if cross-sectional modelling can distinguish slow versus accelerated ageing in a human population.

DESIGN

We trained a machine learning model to predict age from 153 clinical and cardiometabolic traits. The model was tested against longitudinal data from another cohort.

PATIENTS OR OTHER PARTICIPANTS

The training data came from cross-sectional surveys of the Finnish population (n = 9,708; ages 25-74 years). The validation data included three time points across 10 years in the Young Finns Study (YFS; n = 1,009; ages 24-49 years).

INTERVENTION(S)

Predicted metabolic age in 2007 was compared against observed ageing rate from the 2001 visit to the 2011 visit in the YFS dataset.

MAIN OUTCOME MEASURE(S)

Correlation between predicted versus observed metabolic ageing.

RESULTS

The cross-sectional proxy failed to predict longitudinal observations (R2 = 0.018%, P = 0.67).

CONCLUSIONS

The finding is unexpected under the clock hypothesis that would produce a positive correlation between predicted and observed ageing. Our results are better explained by a stratified model where ageing rates per se are similar in adulthood but differences in starting points explain diverging metabolic fates.

Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults

BACKGROUND

Quantification of metabolic changes over the human life course is essential to understanding ageing processes. Yet longitudinal metabolomics data are rare and long gaps between visits can introduce biases that mask true trends. We introduce new ways to process quantitative time-series population data and elucidate metabolic ageing trends in two large cohorts.

METHODS

Eligible participants included 1672 individuals from the Cardiovascular Risk in Young Finns Study and 3117 from the Northern Finland Birth Cohort 1966. Up to three time points (ages 24-49 years) were analysed by nuclear magnetic resonance metabolomics and clinical biochemistry (236 measures). Temporal trends were quantified as median change per decade. Sample quality was verified by consistency of shared biomarkers between metabolomics and clinical assays. Batch effects between visits were mitigated by a new algorithm introduced in this report. The results below satisfy multiple testing threshold of P < 0.0006.

RESULTS

Women gained more weight than men (+6.5% vs +5.0%) but showed milder metabolic changes overall. Temporal sex differences were observed for C-reactive protein (women +5.1%, men +21.1%), glycine (women +5.2%, men +1.9%) and phenylalanine (women +0.6%, men +3.5%). In 566 individuals with ≥+3% weight gain vs 561 with weight change ≤-3%, divergent patterns were observed for insulin (+24% vs -10%), very-low-density-lipoprotein triglycerides (+32% vs -6%), high-density-lipoprotein2 cholesterol (-6.5% vs +4.7%), isoleucine (+5.7% vs -6.0%) and C-reactive protein (+25% vs -22%).

CONCLUSION

We report absolute and proportional trends for 236 metabolic measures as new reference material for overall age-associated and specific weight-driven changes in real-world populations.

Metabolic profiles of ultra-processed food consumption and their role in obesity risk in British children

BACKGROUND & AIMS

Higher consumption of ultra-processed foods (UPF) has been associated with childhood obesity, but underlying mechanisms remain unclear. We investigated plasma nuclear magnetic resonance metabolic profiles of higher UPF consumption and their role in obesity risk in the British ALSPAC cohort.

METHODS

We performed cross-sectional and prospective metabolome wide association analyses of UPF, calculated from food diaries using the NOVA classification. In cross-sectional analysis, we tested the association between UPF consumption and metabolic profile at 7 years (N = 4528), and in the prospective analysis we tested the association between UPF consumption at 13 years and metabolic profile at 17 years (N = 3086). Effects of UPF-associated metabolites at 7 years on subsequent fat mass accumulation were assessed using growth curve models.

RESULTS

At 7 years, UPF was associated with 115 metabolic traits including lower levels of branched-chain and aromatic amino acids and higher levels of citrate, glutamine, and monounsaturated fatty acids, which were also associated with greater fat mass accumulation. Reported intake of nutrients mediated associations with most metabolites, except for citrate.

CONCLUSIONS

UPF consumption among British children is associated with perturbation of multiple metabolic traits, many of which contribute to child obesity risk.

Transcriptional targets of senataxin and E2 promoter binding factors are associated with neuro-degenerative pathways during increased autophagic flux

Autophagy is an intracellular recycling process that degrades harmful molecules and enables survival during starvation, with implications for diseases including dementia, cancer and atherosclerosis. Previous studies demonstrate how a limited number of transcription factors (TFs) can increase autophagy. However, this knowledge has not resulted in translation into therapy, thus, to gain understanding of more suitable targets, we utilized a systems biology approach. We induced autophagy by amino acid starvation and mTOR inhibition in HeLa, HEK 293 and SH-SY5Y cells and measured temporal gene expression using RNA-seq. We observed 456 differentially expressed genes due to starvation and 285 genes due to mTOR inhibition (P_FDR < 0.05 in every cell line). Pathway analyses implicated Alzheimer's and Parkinson's diseases (P_FDR ≤ 0.024 in SH-SY5Y and HeLa) and amyotrophic lateral sclerosis (ALS, P_FDR < 0.05 in mTOR inhibition experiments). Differential expression of the Senataxin (SETX) target gene set was predicted to activate multiple neurodegenerative pathways (P_FDR ≤ 0.04). In the SH-SY5Y cells of neuronal origin, the E2F transcription family was predicted to activate Alzheimer's disease pathway (P_FDR ≤ 0.0065). These exploratory analyses suggest that SETX and E2F may mediate transcriptional regulation of autophagy and further investigations into their possible role in neuro-degeneration are warranted.

Metabolic Alterations Differentiating Cardiovascular Maladaptation from Athletic Training in American-Style Football Athletes

PURPOSE

Metabolomics identifies molecular products produced in response to numerous stimuli, including both adaptive (includes exercise training) and disease processes. We analyzed a longitudinal cohort of American-style football (ASF) athletes, who reliably acquire maladaptive cardiovascular (CV) phenotypes during competitive training, with high-resolution metabolomics to determine whether metabolomics can discriminate exercise-induced CV adaptations from early CV pathology.

METHODS

Matched discovery ( n = 42) and validation ( n = 40) multicenter cohorts of collegiate freshman ASF athletes were studied with longitudinal echocardiography, applanation tonometry, and high-resolution metabolomics. Liquid chromatography-mass spectrometry identified metabolites that changed ( P < 0.05, false discovery rate <0.2) over the season. Metabolites demonstrating similar changes in both cohorts were further analyzed in linear and mixed-effects models to identify those associated with left ventricular mass, tissue-Doppler myocardial E ' velocity (diastolic function), and arterial function (pulse wave velocity).

RESULTS

In both cohorts, 20 common metabolites changed similarly across the season. Metabolites reflective of favorable CV health included an increase in arginine and decreases in hypoxanthine and saturated fatty acids (heptadecanoate, arachidic acid, stearate, and hydroxydecanoate). In contrast, metabolic perturbations of increased lysine and pipecolate, reflective of adverse CV health, were also observed. Adjusting for player position, race, height, and changes in systolic blood pressure, weight, and pulse wave velocity, increased lysine ( β = 0.018, P = 0.02) and pipecolate ( β = 0.018, P = 0.02) were associated with increased left ventricular mass index. In addition, increased lysine ( β = -0.049, P = 0.01) and pipecolate ( β = -0.052, P = 0.008) were also associated with lower E ' (reduced diastolic function).

CONCLUSIONS

ASF athletes seem to develop metabolomic changes reflective of both favorable CV health and early CV maladaptive phenotypes. Whether metabolomics can discriminate early pathologic CV transformations among athletes is a warranted future research direction.

Substantial Fat Loss in Physique Competitors Is Characterized by Increased Levels of Bile Acids, Very-Long Chain Fatty Acids, and Oxylipins

Weight loss and increased physical activity may promote beneficial modulation of the metabolome, but limited evidence exists about how very low-level weight loss affects the metabolome in previously non-obese active individuals. Following a weight loss period (21.1 ± 3.1 weeks) leading to substantial fat mass loss of 52% (−7.9 ± 1.5 kg) and low body fat (12.7 ± 4.1%), the liquid chromatography-mass spectrometry-based metabolic signature of 24 previously young, healthy, and normal weight female physique athletes was investigated. We observed uniform increases (FDR < 0.05) in bile acids, very-long-chain free fatty acids (FFA), and oxylipins, together with reductions in unsaturated FFAs after weight loss. These widespread changes, especially in the bile acid profile, were most strongly explained (FDR < 0.05) by changes in android (visceral) fat mass. The reported changes did not persist, as all of them were reversed after the subsequent voluntary weight regain period (18.4 ± 2.9 weeks) and were unchanged in non-dieting controls (n = 16). Overall, we suggest that the reported changes in FFA, bile acid, and oxylipin profiles reflect metabolic adaptation to very low levels of fat mass after prolonged periods of intense exercise and low-energy availability. However, the effects of the aforementioned metabolome subclass alteration on metabolic homeostasis remain controversial, and more studies are warranted to unravel the complex physiology and potentially associated health implications. In the end, our study reinforced the view that transient weight loss seems to have little to no long-lasting molecular and physiological effects.

An approach to assess and adjust for the influence of multicollinear covariates on metabolomics association patterns-applied to a study of the associations between a comprehensive lipoprotein profile and the homeostatic model assessment of insulin resistance

INTRODUCTION

Comprehensive lipoprotein profiling using proton nuclear magnetic resonance (NMR) spectroscopy of serum represents an alternative to the homeostatic model assessment of insulin resistance (HOMA-IR). Both adiposity and physical (in)activity associate to insulin resistance, but quantification of the influence of these two lifestyle related factors on the association pattern of HOMA-IR to lipoproteins suffers from lack of appropriate methods to handle multicollinear covariates.

OBJECTIVES

We aimed at (i) developing an approach for assessment and adjustment of the influence of multicollinear and even linear dependent covariates on regression models, and (ii) to use this approach to examine the influence of adiposity and physical activity on the association pattern between HOMA-IR and the lipoprotein profile.

METHODS

For 841 children, lipoprotein profiles were obtained from serum proton NMR and physical activity (PA) intensity profiles from accelerometry. Adiposity was measured as body mass index, the ratio of waist circumference to height, and skinfold thickness. Target projections were used to assess and isolate the influence of adiposity and PA on the association pattern of HOMA-IR to the lipoproteins.

RESULTS

Adiposity explained just over 50% of the association pattern of HOMA-IR to the lipoproteins with strongest influence on high-density lipoprotein features. The influence of PA was mainly attributed to a strong inverse association between adiposity and moderate and high-intensity physical activity.

CONCLUSION

The presented covariate projection approach to obtain net association patterns, made it possible to quantify and interpret the influence of adiposity and physical (in)activity on the association pattern of HOMA-IR to the lipoprotein features.

Accelerometer-Based Sedentary Time, Physical Activity, and Serum Metabolome in Young Men

Physical activity (PA) has been shown to associate with many health benefits but studies with metabolome-wide associations with PA are still lacking. Metabolome studies may deepen the mechanistic understanding of PA on the metabolic pathways related to health outcomes. The aim of the present study was to study the association of accelerometer based sedentary time (SB) and PA with metabolome measures. SB and PA were measured by a hip-worn accelerometer in 314 young adult men (age: mean 28, standard deviation 7 years). Metabolome was analyzed from fasting serum samples consisting of 66 metabolome measures (nuclear magnetic resonance-based metabolomics). The associations were analyzed using a single and compositional approach with regression analysis. The compositional analysis revealed that 4 metabolome variables were significantly (γ: 0.32−0.44, p ≤ 0.002), and 13 variables with a trend towards significance (p < 0.05), associated with SB with varying metabolic pathways. Trends towards significant associations (p < 0.05) were observed with 5 variables with moderate-to-vigorous and 1 variable with light intensity PA with varying metabolic pathways. The present study revealed possible mechanistic pathways relevant for the interaction between especially SB but also PA of moderate-to-vigorous intensity with ketone bodies and amino acid concentration related to exercised-induced energy production and lipid metabolism.

Physical activity and health: Findings from Finnish monozygotic twin pairs discordant for physical activity

Genetic and early environmental differences including early health habits associate with future health. To provide insight on the causal nature of these associations, monozygotic (MZ) twin pairs discordant for health habits provide an interesting natural experiment. Twin pairs discordant for leisure‐time physical activity (LTPA) in early adult life is thus a powerful study design to investigate the associations between long‐term LTPA and indicators of health and wellbeing. We have identified 17 LTPA discordant twin pairs from two Finnish twin cohorts and summarize key findings of these studies in this paper. The carefully characterized rare long‐term LTPA discordant MZ twin pairs have participated in multi‐dimensional clinical examinations. Key findings highlight that compared with less active twins in such MZ twin pairs, the twins with higher long‐term LTPA have higher physical fitness, reduced body fat, reduced visceral fat, reduced liver fat, increased lumen diameters of conduit arteries to the lower limbs, increased bone mineral density in loaded bone areas, and an increased number of large high‐density lipoprotein particles. The findings increase our understanding on the possible site‐specific and system‐level effects of long‐term LTPA.

Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology: disclosure of fundamental structural and metabolic relationships

BACKGROUND

Quantitative lipoprotein analytics using nuclear magnetic resonance (NMR) spectroscopy is currently commonplace in large-scale studies. One methodology has become widespread and is currently being utilized also in large biobanks. It allows the comprehensive characterization of 14 lipoprotein subclasses, clinical lipids, apolipoprotein A-I and B. The details of these data are conceptualized here in relation to lipoprotein metabolism with particular attention on the fundamental characteristics of subclass particle numbers, lipid concentrations and compositional measures.

METHODS AND RESULTS

The NMR methodology was applied to fasting serum samples from Northern Finland Birth Cohorts 1966 and 1986 with 5651 and 5605 participants, respectively. All results were highly consistent between the cohorts. Circulating lipid concentrations in a particular lipoprotein subclass arise predominantly as the result of the circulating number of those subclass particles. The spherical lipoprotein particle shape, with a radially oriented surface monolayer, imposes size-dependent biophysical constraints for the lipid composition of individual subclass particles and inherently restricts the accommodation of metabolic changes via compositional modifications. The new finding that the relationship between lipoprotein subclass particle concentrations and the particle size is log-linear reveals that circulating lipoprotein particles are also under rather strict metabolic constraints for both their absolute and relative concentrations.

CONCLUSIONS

The fundamental structural and metabolic relationships between lipoprotein subclasses elucidated in this study empower detailed interpretation of lipoprotein metabolism. Understanding the intricate details of these extensive data is important for the precise interpretation of novel therapeutic opportunities and for fully utilizing the potential of forthcoming analyses of genetic and metabolic data in large biobanks.

Association of Modifiable Lifestyle Factors with Plasma Branched-Chain Amino Acid Metabolites in Women

BACKGROUND

Circulating branched-chain amino acids (BCAAs-isoleucine, leucine, and valine) are strongly associated with higher risk of incident type 2 diabetes (T2D); however, determinants of elevated fasting BCAA concentrations are largely unknown.

OBJECTIVES

We aimed to characterize the modifiable lifestyle factors related to plasma BCAAs.

METHODS

We performed a cross-sectional analysis among n = 18,897 women (mean ± SD age: 54.9 ± 7.2 y) in the Women's Health Study, free of T2D and cardiovascular disease at baseline blood draw. Lifestyle factors, weight, and height were self-reported via questionnaire, including smoking status, alcohol, leisure-time physical activity (LTPA), diet quality scores [2010 Alternative Healthy Eating Index (without alcohol) (aHEI); alternate Mediterranean Diet (aMED)], and dietary sources of BCAAs. Plasma BCAAs were quantified via NMR spectroscopy. We calculated multivariable-adjusted percentage mean differences (95% CIs) and P values for linear trend of BCAAs stratified by categoric lifestyle factors. We estimated R2 from univariate cubic spline regression models to estimate the variability in BCAAs explained.

RESULTS

Compared with women with BMI (in kg/m2) <25.0, BCAAs were 8.6% (95% CI: 8.0%, 9.3%), 15.3% (95% CI: 14.4%, 16.3%), and 21.0% (95% CI: 18.2%, 23.9%) higher for the BMI strata 25.0-29.9, 30.0-39.9, and ≥40.0, respectively (P-trend < 0.0001). Women with higher LTPA and higher alcohol intake compared with lower had modestly (∼1%) lower plasma BCAAs (P-trend = 0.014 and 0.0003, respectively). Differences in smoking status, aHEI, and aMED score were not related to plasma BCAAs. Women with higher dietary BCAAs had dose-response higher plasma BCAA concentrations, 3.4% (95% CI: 2.5%, 4.4%) higher when comparing the highest with the lowest quintile (P-trend < 0.0001). BMI explained 11.6% of the variability of BCAAs, whereas other factors explained between 0.1% and 1%.

CONCLUSIONS

Our findings among a large cohort of US women indicate that BMI, but less so diet, physical activity, and other lifestyle factors, is related to plasma BCAAs.This trial was registered at clinicaltrials.gov as NCT00000479.

Branched-Chain Amino Acid Deprivation Decreases Lipid Oxidation and Lipogenesis in C2C12 Myotubes

Impaired lipid metabolism is a common risk factor underlying several metabolic diseases such as metabolic syndrome and type 2 diabetes. Branched-chain amino acids (BCAAs) that include valine, leucine and isoleucine have been proven to share a role in lipid metabolism and hence in maintaining metabolic health. We have previously introduced a hypothesis suggesting that BCAA degradation mechanistically connects to lipid oxidation and storage in skeletal muscle. To test our hypothesis, the present study examined the effects of BCAA deprivation and supplementation on lipid oxidation, lipogenesis and lipid droplet characteristics in murine C2C12 myotubes. In addition, the role of myotube contractions on cell metabolism was studied by utilizing in vitro skeletal-muscle-specific exercise-like electrical pulse stimulation (EPS). Our results showed that the deprivation of BCAAs decreased both lipid oxidation and lipogenesis in C2C12 myotubes. BCAA deprivation further diminished the number of lipid droplets in the EPS-treated myotubes. EPS decreased lipid oxidation especially when combined with high BCAA supplementation. Similar to BCAA deprivation, high BCAA supplementation also decreased lipid oxidation. The present results highlight the role of an adequate level of BCAAs in healthy lipid metabolism.

Association of Genetically Predicted BCAA Levels with Muscle Fiber Size in Athletes Consuming Protein

Branched-chain amino acid (BCAA) levels are associated with skeletal muscle cross-sectional area (CSA). Serum BCAA levels are enhanced by whey protein supplementation (WPS), and evidence in clinical populations suggests an association of single nucleotide polymorphisms (SNPs) with BCAA metabolite levels. It is not known whether the same SNPs are associated with the ability to catabolise BCAAs from exogenous sources, such as WPS. The present study investigated whether possessing a higher number of alleles associated with increased BCAA metabolites correlates with muscle fiber CSA of m. vastus lateralis in physically active participants, and whether any relationship is enhanced by WPS. Endurance-trained participants (n = 75) were grouped by self-reported habitual WPS consumption and genotyped for five SNPs (PPM1K rs1440580, APOA5 rs2072560, CBLN1 rs1420601, DDX19B rs12325419, and TRMT61A rs58101275). Body mass, BMI, and fat percentage were significantly lower and muscle mass higher in the WPS group compared to Non-WPS. The number of BCAA-increasing alleles was correlated with fiber CSA in the WPS group (r = 0.75, p < 0.0001) and was stronger for fast-twitch fibers (p = 0.001) than slow-twitch fibers (p = 0.048). Similar results remained when corrected for multiple covariates (age, physical activity, and meat and dairy intake). No correlation was found in the Non-WPS group. This study presents novel evidence of a positive relationship between BCAA-increasing alleles and muscle fiber CSA in athletes habitually consuming WPS. We suggest that a high number of BCAA-increasing alleles improves the efficiency of WPS by stimulation of muscle protein synthesis, and contributes to greater fiber CSA.

Associations of lipoprotein particle profile and objectively measured physical activity and sedentary time in schoolchildren: a prospective cohort study

Background

Our understanding of the mechanisms through which physical activity might benefit lipoprotein metabolism is inadequate. Here we characterise the continuous associations between physical activity of different intensities, sedentary time, and a comprehensive lipoprotein particle profile.

Methods

Our cohort included 762 fifth grade (mean [SD] age = 10.0 [0.3] y) Norwegian schoolchildren (49.6% girls) measured on two separate occasions across one school year. We used targeted proton nuclear magnetic resonance (1H NMR) spectroscopy to produce 57 lipoprotein measures from fasted blood serum samples. The children wore accelerometers for seven consecutive days to record time spent in light-, moderate-, and vigorous-intensity physical activity, and sedentary time. We used separate multivariable linear regression models to analyse associations between the device-measured activity variables—modelled both prospectively (baseline value) and as change scores (follow-up minus baseline value)—and each lipoprotein measure at follow-up.

Results

Higher baseline levels of moderate-intensity and vigorous-intensity physical activity were associated with a favourable lipoprotein particle profile at follow-up. The strongest associations were with the larger subclasses of triglyceride-rich lipoproteins. Sedentary time was associated with an unfavourable lipoprotein particle profile, the pattern of associations being the inverse of those in the moderate-intensity and vigorous-intensity physical activity analyses. The associations with light-intensity physical activity were more modest; those of the change models were weak.

Conclusion

We provide evidence of a prospective association between time spent active or sedentary and lipoprotein metabolism in schoolchildren. Change in activity levels across the school year is of limited influence in our young, healthy cohort.

Trial registration

ClinicalTrials.gov, #NCT02132494. Registered 7th April 2014

Cross-sectional associations between cardiorespiratory fitness and NMR-derived metabolic biomarkers in children - the PANIC study

OBJECTIVE

Cardiorespiratory fitness has been inversely associated with cardiovascular risk across the lifespan. Some studies in adults suggest that higher cardiorespiratory fitness is associated with cardioprotective metabolite profile, but the evidence in children is lacking. Therefore, we investigated the cross-sectional association of cardiorespiratory fitness with serum nuclear magnetic resonance derived metabolic biomarkers in children.

METHODS

A population sample of 450 children aged 6-8 years was examined. Cardiorespiratory fitness was assessed by a maximal exercise test on a cycle ergometer and quantified as maximal power output normalised for lean body mass assessed by dual-energy X-ray absorbtiometry. Serum metabolites were assessed using a high throughput nuclear magnetic resonance platform. The data were analysed using linear regression analyses adjusted for age and sex and subsequently for body fat percentage (BF%) assessed by DXA.

RESULTS

Cardiorespiratory fitness was directly associated with high density lipoprotein (HDL) cholesterol (β=0.138, 95% CI=0.042 to 0.135, p=0.005), average HDL particle diameter (β=0.102, 95% CI=0.004 to 0.199, p=0.041), and the concentrations of extra-large HDL particles (β=0.103, 95% CI=0.006 to 0.201, p=0.038), large HDL particles (β=0.122, 95% CI=0.025 to 0.220, p=0.014), and medium HDL particles (β=0.143, 95% CI=0.047 to 0.239, p=0.004) after adjustment for age and sex. Higher cardiorespiratory fitness was also associated with higher concentrations of ApoA1 (β=0.145, 95% CI=0.047 to 0.242, p=0.003), glutamine (β=0.161, 95% CI=0.064 to 0.257, p=0.001), and phenylalanine (β=0.187, 95% CI=0.091 to 0.283, p<0.001). However, only the direct associations of cardiorespiratory fitness with the concentrations of HDL cholesterol (β=0.114, 95% CI=0.018 to 0.210, p=0.021), medium HDL particles (β=0.126, 95% CI=0.030 to 0.223, p=0.010), ApoA1 (β=0.126, 95% CI=0.030 to 0.223, p=0.011), glutamine (β=0.147, 95% CI=0.050 to 0.224, p=0.003), and phenylalanine (β=0.217, 95% CI=0.122 to 0.311, p<0.001) remained statistically significant after further adjustment for BF%.

CONCLUSIONS

Higher cardiorespiratory fitness was associated with a cardioprotective biomarker profile in children. Most associations were independent of BF% suggesting that the differences in serum metabolites between children are driven by cardiorespiratory fitness and not adiposity.

Influence of adiposity and physical activity on the cardiometabolic association pattern of lipoprotein subclasses to aerobic fitness in prepubertal children

Aerobic fitness (AF) and lipoprotein subclasses associate to each other and to cardiovascular health. Adiposity and physical activity (PA) influence the association pattern of AF to lipoproteins almost inversely making it difficult to assess their independent and joint influence on the association pattern. This study, including 841 children (50% boys) 10.2 ± 0.3 years old with BMI 18.0 ± 3.0 kg/m2 from rural Western Norway, aimed at examining the association pattern of AF to the lipoprotein subclasses and to estimate the independent and joint influence of PA and adiposity on this pattern. We used multivariate analysis to determine the association pattern of a profile of 26 lipoprotein features to AF with and without adjustment for three measures of adiposity and a high-resolution PA descriptor of 23 intensity intervals derived from accelerometry. For data not adjusted for adiposity or PA, we observed a cardioprotective lipoprotein pattern associating to AF. This pattern withstood adjustment for PA, but the strength of association to AF was reduced by 58%, while adjustment for adiposity weakened the association of AF to the lipoproteins by 85% and with strongest changes in the associations to a cardioprotective high-density lipoprotein subclass pattern. When adjusted for both adiposity and PA, the cardioprotective lipoprotein pattern still associated to AF, but the strength of association was reduced by 90%. Our results imply that the (negative) influence of adiposity on the cardioprotective association pattern of lipoproteins to AF is considerably stronger than the (positive) contribution of PA to this pattern. However, our analysis shows that PA contributes also indirectly through a strong inverse association to adiposity. The trial was registered 7 May, 2014 in clinicaltrials.gov with trial reg. no.: NCT02132494 and the URL is https://clinicaltrials.gov/ct2/results?term=NCT02132494&cntry=NO.

Discovering metabolite quantitative trait loci in asthma using an isolated population

BACKGROUND

Integration of metabolomics with genetics may advance understanding of disease pathogenesis but has been underutilized in asthma genetic studies.

OBJECTIVE

We aimed to discover new genetic effects in asthma and to characterize the molecular consequences of asthma genetic risk through integration with the metabolome in a homogenous population.

METHODS

From fasting serum samples collected on 348 Tangier Island residents, we quantified 2,612 compounds using untargeted metabolomics. Genotyping was performed using Illumina's MEGA array imputed to the TOPMed reference panel. To prioritize metabolites for genome-wide association analysis (GWAS), we performed a metabolome-wide association study with asthma, selecting asthma-associated metabolites with heritability q-value<0.01 for GWAS. We also tested the association between all metabolites and 8,451 candidate asthma SNPs previously associated with asthma in the UK Biobank. We followed up significant associations by characterizing shared genetic signal for metabolites and asthma using colocalization analysis. For detailed Methods, please see this article's Online Repository at www.jacionline.org RESULTS: 60 metabolites were associated with asthma (p<0.01), including 40 heritable metabolites tested in GWAS. We observed a strong association peak for the endocannabinoid linoleoyl ethanolamide on chromosome 6 in VNN1 (p<2.7E-9). We found strong evidence (co-localization posterior probability >75%) for a shared causal variant between three metabolites and asthma, including the polyamine acisoga and variants in LPP, and derivative leukotriene B4 and intergenic variants in chr10p14.

CONCLUSION

We identified novel metabolite quantitative trait loci with asthma associations. Identification and characterization of these genetically-driven metabolites may provide insight into the functional consequences of genetic risk factors for asthma.

Physical Activity and Stool Metabolite Relationships Among Adults at High Risk for Colorectal Cancer

BACKGROUND

Adenomatous polyps are associated with an increased risk of developing colorectal cancer. Physical activity (PA) and spending less time sedentary may reduce risk of polyp recurrence and cancer incidence. This study examined associations between PA, sedentary time, and stool metabolites in adults at high risk for developing colorectal cancer.

METHODS

Participants were ≥18 years old with ≥1 adenomatous polyps removed in the previous 3 years. PA and sedentary time were assessed using an activPAL™ accelerometer. Stool samples were analyzed for short-chain fatty acids, and primary/secondary bile acid metabolites by mass spectrometry. Linear regression models examined associations between PA, sedentary time, and stool parameters, with dietary fiber as a covariate.

RESULTS

Participants (N = 21) were 59 (9) years old and had a body mass index of 28.1 (3.35 kg/m2). Light-intensity PA was associated with butyrate (β = 1.88; 95% confidence interval [CI], 0.477 to 3.291) and propionate (β = 1.79; 95% CI, 0.862 to 2.724). Moderate to vigorous PA was associated with deoxycholic acid (β = -6.13; 95% CI, -12.14 to -0.11) and ursodeoxycholic acid (β = -0.45; 95% CI, -0.80 to -0.12) abundance.

CONCLUSIONS

Both light and moderate to vigorous PA were associated with gut microbial metabolite production. These findings suggest the importance of examining PA intensity alongside stool metabolites for colorectal cancer prevention.

Effect of Caloric Restriction on Aging: Fixing the Problems of Nutrient Sensing in Postmitotic Cells?

The review discusses the role of metabolic disorders (in particular, insulin resistance) in the development of age-related diseases and normal aging with special emphasis on the changes in postmitotic cells of higher organisms. Caloric restriction helps to prevent such metabolic disorders, which could probably explain its ability to prolong the lifespan of laboratory animals. Maintaining metabolic homeostasis is especially important for the highly differentiated long-lived body cells, whose lifespan is comparable to the lifespan of the organism itself. Normal functioning of these cells can be ensured only upon correct functioning of the cytoplasm clean-up system and availability of all required nutrients and energy sources. One of the central problems in gerontology is the age-related disruption of glucose metabolism leading to obesity, diabetes, metabolic syndrome, and other related pathologies. Along with the adipose tissue, skeletal muscles are the main consumers of insulin; hence the physical activity of muscles, which supports their energy metabolism, delays the onset of insulin resistance. Insulin resistance disrupts the metabolism of cardiomyocytes, so that they fail to utilize the nutrients to perform their functions even being surrounded by a nutrient-rich environment, which contributes to the development of age-related cardiovascular diseases. Metabolic pathologies also alter the nutrient sensitivity of neurons, thus disrupting the action of insulin in the central nervous system. In addition, there is evidence that neurons can develop insulin resistance as well. It has been suggested that affecting nutritional sensors (e.g., AMPK) in postmitotic cells might improve the state of the entire multicellular organism, slow down its aging, and increase the lifespan.

A map of metabolic phenotypes in patients with myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease usually presenting after infection. Emerging evidence supports that energy metabolism is affected in ME/CFS, but a unifying metabolic phenotype has not been firmly established. We performed global metabolomics, lipidomics, and hormone measurements, and we used exploratory data analyses to compare serum from 83 patients with ME/CFS and 35 healthy controls. Some changes were common in the patient group, and these were compatible with effects of elevated energy strain and altered utilization of fatty acids and amino acids as catabolic fuels. In addition, a set of heterogeneous effects reflected specific changes in 3 subsets of patients, and 2 of these expressed characteristic contexts of deregulated energy metabolism. The biological relevance of these metabolic phenotypes (metabotypes) was supported by clinical data and independent blood analyses. In summary, we report a map of common and context-dependent metabolic changes in ME/CFS, and some of them presented possible associations with clinical patient profiles. We suggest that elevated energy strain may result from exertion-triggered tissue hypoxia and lead to systemic metabolic adaptation and compensation. Through various mechanisms, such metabolic dysfunction represents a likely mediator of key symptoms in ME/CFS and possibly a target for supportive intervention.

Sex-Specific Relationship between the Cardiorespiratory Fitness and Plasma Metabolite Patterns in Healthy Humans-Results of the KarMeN Study

Cardiorespiratory fitness (CRF) represents a strong predictor of all-cause mortality and is strongly influenced by regular physical activity (PA). However, the biological mechanisms involved in the body's adaptation to PA remain to be fully elucidated. The aim of this study was to systematically examine the relationship between CRF and plasma metabolite patterns in 252 healthy adults from the cross-sectional Karlsruhe Metabolomics and Nutrition (KarMeN) study. CRF was determined by measuring the peak oxygen uptake during incremental exercise. Fasting plasma samples were analyzed by nuclear magnetic resonance spectroscopy and mass spectrometry coupled to one- or two-dimensional gas chromatography or liquid chromatography. Based on this multi-platform metabolomics approach, 427 plasma analytes were detected. Bi- and multivariate association analyses, adjusted for age and menopausal status, showed that CRF was linked to specific sets of metabolites primarily indicative of lipid metabolism. However, CRF-related metabolite patterns largely differed between sexes. While several phosphatidylcholines were linked to CRF in females, single lyso-phosphatidylcholines and sphingomyelins were associated with CRF in males. When controlling for further assessed clinical and phenotypical parameters, sex-specific CRF tended to be correlated with a smaller number of metabolites linked to lipid, amino acid, or xenobiotics-related metabolism. Interestingly, sex-specific CRF explanation models could be improved when including selected plasma analytes in addition to clinical and phenotypical variables. In summary, this study revealed sex-related differences in CRF-associated plasma metabolite patterns and proved known associations between CRF and risk factors for cardiometabolic diseases such as fat mass, visceral adipose tissue mass, or blood triglycerides in metabolically healthy individuals. Our findings indicate that covariates like sex and, especially, body composition have to be considered when studying blood metabolic markers related to CRF.

Metabolic profiling links cardiovascular risk and vascular end organ damage

BACKGROUND AND AIMS

An untargeted metabolomics approach allows for a better understanding and identification of new candidate metabolites involved in the etiology of vascular disease. We aimed to investigate the associations of cardiovascular (CV) risk factors with the metabolic fingerprint and macro- and microvascular health in an untargeted metabolomic approach in predefined CV risk groups of aged individuals.

METHODS

The metabolic fingerprint and the macro- and microvascular health from 155 well-characterized aged (50-80 years) individuals, based on the EXAMIN AGE study, were analysed. Nuclear magnetic resonance spectroscopy was used to analyse the metabolic fingerprint. Carotid-femoral pulse wave velocity and retinal vessel diameters were assessed to quantify macro- and microvascular health.

RESULTS

The metabolic fingerprint became more heterogeneous with an increasing number of risk factors. There was strong evidence for higher levels of glutamine [estimate (95% CI): -14.54 (-17.81 to -11.27), p < 0.001], glycine [-5.84 (-7.88 to -3.79), p < 0.001], histidine [-0.73 (-0.96 to -0.50), p < 0.001], and acetate [-1.68 (-2.91 to -0.46), p = 0.007] to be associated with a lower CV risk profile. Tryptophan, however, was positively associated with higher CV risk [0.31 (0.06-0.56), p = 0.015]. The combination of a priori defined CV risk factors explained up to 45.4% of the metabolic variation. The metabolic fingerprint explained 20% of macro- and 23% of microvascular variation.

CONCLUSIONS

Metabolic profiling has the potential to improve CV risk stratification by identifying new underlying metabolic pathways associated with atherosclerotic disease development, from cardiovascular risk to metabolites, to vascular end organ damage.

Metabolomic profiles of being physically active and less sedentary: a critical review

BACKGROUND

Being physically active has multiple salutary effects on human health, likely mediated by changes in energy metabolism. Recent reviews have summarized metabolomic responses to acute exercise. However, metabolomic profiles of individuals who exercise regularly are heterogeneous.

AIM OF REVIEW

We conducted a systematic review to identify metabolites associated with physical activity (PA), fitness, and sedentary time in community-dwelling adults and discussed involved pathways. Twenty-two studies were eligible because they (1) focused on community-dwelling adults from observational studies; (2) assessed PA, fitness, and/or sedentary time, (3) assessed metabolomics in biofluid, and (4) reported on relationships of metabolomics with PA, fitness, and/or sedentary time.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Several metabolic pathways were associated with higher PA and fitness and less sedentary time, including tricarboxylic acid cycle, glycolysis, aminoacyl-tRNA biosynthesis, urea cycle, arginine biosynthesis, branch-chain amino acids, and estrogen metabolism. Lipids were strongly associated with PA. Cholesterol low-density lipoproteins and triglycerides were lower with higher PA, while cholesterol high-density lipoproteins were higher. Metabolomic profiles of being physically active and less sedentary indicate active skeletal muscle biosynthesis supported by enhanced oxidative phosphorylation and glycolysis and associated with profound changes in lipid and estrogen metabolism. Future longitudinal studies are needed to understand whether these metabolomic changes account for health benefits associated with PA.

Longitudinal associations of physical activity with plasma metabolites among colorectal cancer survivors up to 2 years after treatment

We investigated longitudinal associations of moderate-to-vigorous physical activity (MVPA) and light-intensity physical activity (LPA) with plasma concentrations of 138 metabolites after colorectal cancer (CRC) treatment. Self-reported physical activity data and blood samples were obtained at 6 weeks, and 6, 12 and 24 months post-treatment in stage I-III CRC survivors (n = 252). Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQp180 kit). Linear mixed models were used to evaluate confounder-adjusted longitudinal associations. Inter-individual (between-participant differences) and intra-individual associations (within-participant changes over time) were assessed as percentage difference in metabolite concentration per 5 h/week of MVPA or LPA. At 6 weeks post-treatment, participants reported a median of 6.5 h/week of MVPA (interquartile range:2.3,13.5) and 7.5 h/week of LPA (2.0,15.8). Inter-individual associations were observed with more MVPA being related (FDR-adjusted q-value < 0.05) to higher concentrations of arginine, citrulline and histidine, eight lysophosphatidylcholines, nine diacylphosphatidylcholines, 13 acyl-alkylphosphatidylcholines, two sphingomyelins, and acylcarnitine C10:1. No intra-individual associations were found. LPA was not associated with any metabolite. More MVPA was associated with higher concentrations of several lipids and three amino acids, which have been linked to anti-inflammatory processes and improved metabolic health. Mechanistic studies are needed to investigate whether these metabolites may affect prognosis.

Cardiometabolic Associations between Physical Activity, Adiposity, and Lipoprotein Subclasses in Prepubertal Norwegian Children

Lipoprotein subclasses possess crucial cardiometabolic information. Due to strong multicollinearity among variables, little is known about the strength of influence of physical activity (PA) and adiposity upon this cardiometabolic pattern. Using a novel approach to adjust for covariates, we aimed at determining the "net" patterns and strength for PA and adiposity to the lipoprotein profile. Principal component and multivariate pattern analysis were used for the analysis of 841 prepubertal children characterized by 26 lipoprotein features determined by proton nuclear magnetic resonance spectroscopy, a high-resolution PA descriptor derived from accelerometry, and three adiposity measures: body mass index, waist circumference to height, and skinfold thickness. Our approach focuses on revealing and validating the underlying predictive association patterns in the metabolic, anthropologic, and PA data to acknowledge the inherent multicollinear nature of such data. PA associates to a favorable cardiometabolic pattern of increased high-density lipoproteins (HDL), very large and large HDL particles, and large size of HDL particles, and decreasedtriglyceride, chylomicrons, very low-density lipoproteins (VLDL), and their subclasses, and to low size of VLDL particles. Although weakened in strength, this pattern resists adjustment for adiposity. Adiposity is inversely associated to this pattern and exhibits unfavorable associations to low-density lipoprotein (LDL) features, including atherogenic small and very small LDL particles. The observed associations are still strong after adjustment for PA. Thus, lipoproteins explain 26.0% in adiposity after adjustment for PA compared to 2.3% in PA after adjustment for adiposity.

Metabolomics and cancer preventive behaviors in the BC Generations Project

Metabolomics can detect metabolic shifts resulting from lifestyle behaviors and may provide insight on the relevance of changes to carcinogenesis. We used non-targeted nuclear magnetic resonance to examine associations between metabolic measures and cancer preventive behaviors in 1319 participants (50% male, mean age 54 years) from the BC Generations Project. Behaviors were dichotomized: BMI < 25 kg/m², ≥ 5 servings of fruits or vegetables/day, ≤ 2 alcoholic drinks/day for men or 1 drink/day for women and ≥ 30 min of moderate or vigorous physical activity/day. Linear regression was used to estimate coefficients and 95% confidence intervals with a false discovery rate (FDR) of 0.10. Of the 218 metabolic measures, 173, 103, 71 and 6 were associated with BMI, fruits and vegetables, alcohol consumption and physical activity. Notable findings included negative associations between glycoprotein acetyls, an inflammation-related metabolite with lower BMI and greater fruit and vegetable consumption, a positive association between polyunsaturated fatty acids and fruit and vegetable consumption and positive associations between high-density lipoprotein subclasses with lower BMI. These findings provide insight into metabolic alterations in the context of cancer prevention and the diverse biological pathways they are involved in. In particular, behaviors related to BMI, fruit and vegetable and alcohol consumption had a large metabolic impact.

The Impact of COVID-19-Related Lockdown on Diet and Serum Markers in Healthy Adults

Due to limited data about the impact of lockdown on health status, the present study aimed to investigate the impact of COVID-19-related lockdown on changes in dietary habits, physical activity and serum markers in healthy adults. A total of 38 asymptomatic adults aged from 23 to 59 with a normal BMI (22.5 kg/m²) participated in baseline and post-lockdown measurements that included dietary and physical activity assessment, anthropometric measurements and blood samples; and the lockdown survey which included dietary assessment and questionnaires about changes in lifestyle and physical activity. A decreased diet quality during lockdown was observed (Healthy Eating Index reduced from 64.59 to 61.08), which returned to near baseline post-lockdown. Energy intake decreased during lockdown (p = 0.002) and returned to baseline post-lockdown. Despite lower physical activity levels during lockdown (p = 0.035), we observed no significant changes in body composition. However, we observed a significant increase in serum glucose (p = 0.005), total cholesterol (p = 0.003), and low-density lipoprotein (LDL) (p = 0.049) post-lockdown. Increase in serum glucose levels was pronounced in subjects with higher increase in energy intake (p = 0.039), increased omega-6 fatty acids intake (p = 0.016), those who were exposed to several risky contacts (p = 0.018, compared to those with less risky contacts) and those who were not active in nature (p = 0.008, compared to those active in nature). Increased serum LDL was correlated to decreased monounsaturated fatty acids intake (p = 0.028). Within the limits of this preliminary report, changes in serum markers observed among healthy subjects point to a possible impact of COVID-19-related lockdown on adults’ health to be confirmed in larger groups.

Systemic cross-talk between brain, gut, and peripheral tissues in glucose homeostasis: effects of exercise training (CROSSYS). Exercise training intervention in monozygotic twins discordant for body weight

BACKGROUND

Obesity and physical inactivity are major global public health concerns, both of which increase the risk of insulin resistance and type 2 diabetes. Regulation of glucose homeostasis involves cross-talk between the central nervous system, peripheral tissues, and gut microbiota, and is affected by genetics. Systemic cross-talk between brain, gut, and peripheral tissues in glucose homeostasis: effects of exercise training (CROSSYS) aims to gain new systems-level understanding of the central metabolism in human body, and how exercise training affects this cross-talk.

METHODS

CROSSYS is an exercise training intervention, in which participants are monozygotic twins from pairs discordant for body mass index (BMI) and within a pair at least the other is overweight. Twins are recruited from three population-based longitudinal Finnish twin studies, including twins born in 1983-1987, 1975-1979, and 1945-1958. The participants undergo 6-month-long exercise intervention period, exercising four times a week (including endurance, strength, and high-intensity training). Before and after the exercise intervention, comprehensive measurements are performed in Turku PET Centre, Turku, Finland. The measurements include: two positron emission tomography studies (insulin-stimulated whole-body and tissue-specific glucose uptake and neuroinflammation), magnetic resonance imaging (brain morphology and function, quantification of body fat masses and organ volumes), magnetic resonance spectroscopy (quantification of fat within heart, pancreas, liver and tibialis anterior muscle), echocardiography, skeletal muscle and adipose tissue biopsies, a neuropsychological test battery as well as biosamples from blood, urine and stool. The participants also perform a maximal exercise capacity test and tests of muscular strength.

DISCUSSION

This study addresses the major public health problems related to modern lifestyle, obesity, and physical inactivity. An eminent strength of this project is the possibility to study monozygotic twin pairs that share the genome at the sequence level but are discordant for BMI that is a risk factor for metabolic impairments such as insulin resistance. Thus, this exercise training intervention elucidates the effects of obesity on metabolism and whether regular exercise training is able to reverse obesity-related impairments in metabolism in the absence of the confounding effects of genetic factors.

TRIAL REGISTRATION

ClinicalTrials.gov , NCT03730610 . Prospectively registered 5 November 2018.