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.

Abstract P106: Stabilization Muscles Drive Associations Between Lipoproteins And Total Abdominal Muscle And Intermuscular Adipose Tissue In The Multi-ethnic Study Of Atherosclerosis

Introduction: Quality and quantity of skeletal muscle decrease with age, largely due to adipose tissue infiltration, and are important determinants of metabolic health. To inform efforts to slow aging-related decline in muscle mass and prevent myosteatosis, a better understanding of the biological determinants of muscle atrophy and quality is needed. We used targeted lipidomics to identify, with a greater specificity, lipoproteins associated with muscle and intermuscular adipose tissue (IMAT) area (quantity) and density (quality) of the total abdominal, locomotion, and stabilization muscles in the Multi-Ethnic Study of Atherosclerosis. Hypothesis: Lower density lipoproteins will be positively associated with muscle and IMAT quantity, but negatively associated with quality. Methods: At visit one, 105 serum lipoproteins were measured by Bruker lipoprotein subclass analysis with 1 H-Nuclear Magnetic Resonance spectroscopy. Muscle and IMAT area (cm 2 ) and density (Hounsfield units) were estimated 2.6 years, on average, after visit 1 for the total abdominal, locomotion (psoas), and stabilization (paraspinal, oblique, and rectus abdominis) muscles from computed-tomography scans at the L4/L5 spinal junction. We identified lipoproteins associated with body composition using linear regression adjusting for age, gender, race, diet, physical activity, lipid-lowering medication, and multiple comparisons using a 1% false discovery rate. Results: Participants (N=947) were 44-84 years old (mean: 63), 51% men, 40% White, 16% Black, 16% Chinese American, and 27% Hispanic American. Among 105 lipoproteins, 24 were associated with total muscle area, whereas none were associated with muscle density. When examining specific muscle groups, 25 lipoproteins were associated with stabilization muscle area, driven by the oblique muscles. As for total IMAT area, there were 27 associations with lipoproteins. Specifically, 27 lipoproteins were associated with stabilization muscle IMAT area, driven by oblique and rectus abdominis muscles. Last, 39 lipoproteins were associated with total IMAT density, with 28 and 33 associated with locomotion and stabilization (driven by obliques) IMAT density, respectively. Higher VLDL: cholesterols, free cholesterols, phospholipids, and triglycerides and lower HDL: cholesterols and free cholesterols were associated with higher muscle area and IMAT area, but lower IMAT density (

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

AimsQuantitative lipoprotein analytics by NMR spectroscopy is currently commonplace in large-scale studies. One methodology has become widespread and is currently being utilised also in large biobanks. It allows comprehensive characterisation of 14 lipoprotein subclasses, clinical lipids, apolipoprotein A-I and B. The details of these data are conceptualised here in relation to lipoprotein metabolism with particular attention to the fundamental characteristics of subclass particle numbers, lipid concentrations and compositional measures.Methods and ResultsThe NMR methodology was applied to fasting serum samples from Northern Finland Birth Cohort 1966 and 1986 with 5,651 and 5,605 participants, respectively. All results were highly coherent 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 reveal that circulating lipoprotein particles are also under rather strict metabolic constraints for both their absolute and relative concentrations.ConclusionThe 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 consequential for the precise interpretation of novel therapeutic opportunities and for fully utilising the potential of forthcoming analyses of genetic and metabolic data in extensive biobanks.One-sentence SummaryNMR spectroscopy facilitates comprehensive characterisation of lipoprotein subclass metabolism and offers additional value to epidemiology, genetics and pharmacology in large-scale studies and biobanks.Key MessagesThe circulating particle number of a lipoprotein subclass is the defining measure for its lipid concentrations; the particle lipid composition is only in a minor role. The relationship between circulating lipoprotein subclass particle concentrations and the particle size is log-linear.The overall structure of lipoprotein subclass particles with a spherical shape and an oriented surface monolayer poses strong size-dependent biomolecular constraints for their lipid composition.The circulating lipoprotein subclass particle concentrations in humans are metabolically constraint for both elemental absolute and relative concentration ranges.The smallest HDL particle concentrations are negatively associated with those of large HDL and generally the associations of the smallest HDL particles are similar to those of apolipoprotein B-containing particles.The apolipoprotein B-containing particles constitute less than 10% of all lipoprotein particles but carry around two thirds of circulating lipoprotein lipids. LDL and IDL particles amount to almost 90% of all apolipoprotein B-containing particles.The supplemental role of lipoprotein subclass data in cardiometabolic risk assessment is slight.In the current era of biobanks and big data, the combination of lipoprotein subclass data with drug-target Mendelian randomization analyses provides great scientific synergy, intricate details and potential cost savings in drug development.Graphical abstract / key messages

Dissociation Between Insulin Resistance and Abnormalities in Lipoprotein Particle Concentrations and Sizes in Normal-Weight Chinese Adults

Insulin resistance in obesity coincides with abnormalities in lipid profile and lipoprotein subclass distribution and size even before abnormalities in glucose homeostasis manifest. We aimed to assess this relationship in the absence of obesity. Insulin sensitivity (3-h intravenous glucose tolerance test and minimal modeling) and lipoprotein particle concentrations and sizes (proton nuclear magnetic resonance spectroscopy) were evaluated in 15 insulin-resistant and 15 insulin-sensitive lean Asians of Chinese descent with normal glucose tolerance, matched on age, sex, and body mass index. Despite a ~50% lower insulin sensitivity index (Si) in insulin-resistant than in insulin-sensitive subjects, which was accompanied by significantly greater acute insulin response to glucose (AIRg) and fasting insulin concentration but not different fasting glucose concentration, there were no significant differences between groups in the blood lipid profile (p ≥ 0.44) or the lipoprotein subclass concentrations (p ≥ 0.30) and particle sizes (p ≥ 0.43). We conclude that, contrary to observations in subjects with obesity, insulin resistance is not accompanied by unfavorable changes in the plasma lipid profile and lipoprotein particle concentrations and sizes in lean Asians with normal glucose tolerance. Therefore, insulin resistance at the level of glucose metabolism is mechanistically or temporally dissociated from lipid and lipoprotein metabolism.Trial Registration:clinicaltrials.gov, NCT03264001.

Sex differences in systemic metabolites at four life stages: cohort study with repeated metabolomics

Background Males experience higher rates of coronary heart disease (CHD) than females, but the circulating traits underpinning this difference are poorly understood. We examined sex differences in systemic metabolites measured at four life stages, spanning childhood to middle adulthood. Methods Data were from the Avon Longitudinal Study of Parents and Children (7727 offspring, 49% male; and 6500 parents, 29% male). Proton nuclear magnetic resonance (1H-NMR) spectroscopy from a targeted metabolomics platform was performed on EDTA-plasma or serum samples to quantify 229 systemic metabolites (including lipoprotein-subclass-specific lipids, pre-glycaemic factors, and inflammatory glycoprotein acetyls). Metabolites were measured in the same offspring once in childhood (mean age 8 years), twice in adolescence (16 years and 18 years) and once in early adulthood (25 years), and in their parents once in middle adulthood (50 years). Linear regression models estimated differences in metabolites for males versus females on each occasion (serial cross-sectional associations). Results At 8 years, total lipids in very-low-density lipoproteins (VLDL) were lower in males; levels were higher in males at 16 years and higher still by 18 years and 50 years (among parents) for medium-or-larger subclasses. Larger sex differences at older ages were most pronounced for VLDL triglycerides—males had 0.19 standard deviations (SD) (95% CI = 0.12, 0.26) higher at 18 years, 0.50 SD (95% CI = 0.42, 0.57) higher at 25 years, and 0.62 SD (95% CI = 0.55, 0.68) higher at 50 years. Low-density lipoprotein (LDL) cholesterol, apolipoprotein-B, and glycoprotein acetyls were generally lower in males across ages. The direction and magnitude of effects were largely unchanged when adjusting for body mass index measured at the time of metabolite assessment on each occasion. Conclusions Our results suggest that males begin to have higher VLDL triglyceride levels in adolescence, with larger sex differences at older ages. Sex differences in other CHD-relevant metabolites, including LDL cholesterol, show the opposite pattern with age, with higher levels among females. Such life course trends may inform causal analyses with clinical endpoints in specifying traits which underpin higher age-adjusted CHD rates commonly seen among males.

Achievement of the Targets of the 20-Year Infancy-Onset Dietary Intervention—Association with Metabolic Profile from Childhood to Adulthood

The Special Turku Coronary Risk Factor Intervention Project (STRIP) is a prospective infancy-onset randomized dietary intervention trial targeting dietary fat quality and cholesterol intake, and favoring consumption of vegetables, fruit, and whole-grains. Diet (food records) and circulating metabolites were studied at six time points between the ages of 9–19 years (n = 549–338). Dietary targets for this study were defined as (1) the ratio of saturated fat (SAFA) to monounsaturated and polyunsaturated fatty acids (MUFA + PUFA) < 1:2, (2) intake of SAFA < 10% of total energy intake, (3) fiber intake ≥ 80th age-specific percentile, and (4) sucrose intake ≤ 20th age-specific percentile. Metabolic biomarkers were quantified by high-throughput nuclear magnetic resonance metabolomics. Better adherence to the dietary targets, regardless of study group allocation, was assoiated with higher serum proportion of PUFAs, lower serum proportion of SAFAs, and a higher degree of unsaturation of fatty acids. Achieving ≥ 1 dietary target resulted in higher low-density lipoprotein (LDL) particle size, lower circulating LDL subclass lipid concentrations, and lower circulating lipid concentrations in medium and small high-density lipoprotein subclasses compared to meeting 0 targets. Attaining more dietary targets (≥2) was associated with a tendency to lower lipid concentrations of intermediate-density lipoprotein and very low-density lipoprotein subclasses. Thus, adherence to dietary targets is favorably associated with multiple circulating fatty acids and lipoprotein subclass lipid concentrations, indicative of better cardio-metabolic health.