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

Clinical- and omics-based models of subclinical atherosclerosis in healthy Chinese adults: a cross-sectional exploratory study

BACKGROUND

Classical risk factors, such as fasting cholesterol, blood pressure (BP), and diabetes status are used today to predict the risk of developing cardiovascular disease (CVD). However, accurate prediction remains limited, particularly in low-risk groups such as women and younger individuals. Growing evidence suggests that biomarker concentrations following consumption of a meal challenge are better and earlier predictors of disease development than biomarker concentrations.

OBJECTIVE

To test the hypothesis that postprandial responses of circulating biomarkers differ between healthy subjects with and without subclinical atherosclerosis (SA) in an Asian population at low risk of coronary artery disease (CAD).

METHODS

One hundred healthy Chinese subjects (46 women, 54 men) completed the study. Subjects consumed a mixed-meal test and 164 blood biomarkers were analyzed over 6 h by using a combination of chemical and NMR techniques. Models were trained using different methodologies (including logistic regression, elastic net, random forest, sparse partial least square) on a random 75% subset of the data, and their performance was evaluated on the remaining 25%.

RESULTS

We found that models based on baseline clinical parameters or fasting biomarkers could not reliably predict SA. By contrast, an omics model based on magnitude and timing of postprandial biomarkers achieved high performance [receiving operating characteristic (ROC) AUC: 91%; 95% CI: 77, 100). Investigation of key features of this model enabled derivation of a considerably simpler model, solely based on postprandial BP and age, with excellent performance (AUC: 91%; 95% CI: 78, 100).

CONCLUSION

We report a novel model to detect SA based on postprandial BP and age in a population of Asian subjects at low risk of CAD. The use of this model in large-scale CVD prevention programs should be explored. This trial was registered at ClinicalTrials.gov as NCT03531879.

Spousal associations of serum metabolomic profiles by nuclear magnetic resonance spectroscopy

Phenotype-based assortative mating is well established in humans, with the potential for further convergence through a shared environment. To assess the correlation within infertile couples of physical, social, and behavioural characteristics and 155 circulating metabolic measures. Cross sectional study at a tertiary medical center of 326 couples undertaking IVF. Serum lipids, lipoprotein subclasses, and low-molecular weight metabolites as quantified by NMR spectroscopy (155 metabolic measures). Multivariable and quantile regression correlations within couples of metabolite profiles. Couples exhibited statistical correlations of varying strength for most physical, social, and behavioural characteristics including age, height, alcohol consumption, education, smoking status, physical activity, family history and ethnicity, with correlation coefficients ranging from 0.22 to 0.73. There was no evidence of within couple associations for BMI and weight, where the correlation coefficients were - 0.03 (95% CI - 0.14, 0.08) and 0.01 (95% CI - 0.10, 0.12), respectively. Within spousal associations of the metabolite measurements were all positive but with weak to modest magnitudes, with the median correlation coefficient across all 155 measures being 0.12 (range 0.01-0.37 and interquartile range 0.10-0.18). With just four having associations stronger than 0.3: docosahexaenoic acid (0.37, 95% CI 0.22, 0.52), omega-3 fatty acids (0.32, 95% CI 0.20, 0.43) histidine (0.32, 95% CI 0.23, 0.41) and pyruvate (0.32, 95% CI 0.22, 0.43). Infertile couples exhibit spousal similarities for a range of demographic and serum metabolite measures, supporting initial assortative mating, with diet-derived metabolites suggesting possible subsequent convergence of their individual metabolic profile.

Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies

The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.

Perception, knowledge and attitudes on advance medical directives among hospital staff: Using mixed methodology

BACKGROUND

It is necessary to examine the level of perception, knowledge and attitudes of the medical staff for advance medical directives, which are practical alternatives to good practice for end-of-life care in the actual medical field.

PURPOSE

This study was conducted to determine the degree of perception, knowledge and attitude of cancer hospital medical staff about advance medical directives, and to confirm the relationship between them. It also explored their experiences with advance medical directives.

METHODS

This study used a convergent design to collect quantitative and qualitative data separately in the mixed methodology. This design adheres to the STROBE guidelines. Participants were a total of 140 subjects (70 doctors and 70 nurses) with more than 3 years and considered to have sufficient experience related to the study purpose. Focus group participants were a total 19 persons (9 doctors and 10 nurses).

RESULTS

Mean score for perception was 35.40, which indicates lower perception when compared to the median value (37.50 points). Perception of advance medical directives had significant, positive relations with attitude of advance medical directives (p = .032). The perception on attitude of advance medical directives factor was significantly influencing (p = .021). As a result of the analysis based on qualitative research questions, six subjects and 11 categories were created by deriving meaningful sentences from the statements.

CONCLUSION

This study suggests that the perception of medical professionals about advance medical directives has a positive correlation with attitudes, as well as a causal relationship.

RELEVANCE TO CLINICAL PRACTICE

Based on the finding from this study, concrete strategies and interventions to improve the perception of advance medical directives among cancer hospital medical staff are needed.

Integrative analysis of metabolomic, genomic, and imaging-based phenotypes identify very-low-density lipoprotein as a potential risk factor for lumbar Modic changes

PURPOSE

Modic changes (MC) on magnetic resonance imaging (MRI) have been associated with the development and severity of low back pain (LBP). The etiology of MC remains elusive, but it has been suggested that altered metabolism may be a risk factor. As such, this study aimed to identify metabolomic biomarkers for MC phenotypes of the lumbar spine via a combined metabolomic-genomic approach.

METHODS

A population cohort of 3,584 southern Chinese underwent lumbar spine MRI. Blood samples were genotyped with single-nucleotide polymorphisms (SNP) arrays (n = 2,482) and serum metabolomics profiling using magnetic resonance spectroscopy (n = 757), covering 130 metabolites representing three molecular windows, were assessed. Genome-wide association studies (GWAS) were performed on each metabolite, to construct polygenic scores for predicting metabolite levels in subjects who had GWAS but not metabolomic data. Associations between predicted metabolite levels and MC phenotypes were assessed using linear/logistic regression and least absolute shrinkage and selection operator (LASSO). Two-sample Mendelian randomization analysis tested for causal relationships between metabolic biomarkers and MC.

RESULTS

20.4% had MC (10.6% type 1, 67.2% type 2, 22.2% mixed types). Significant MC metabolomic biomarkers were mean diameter of very-low-density lipoprotein (VLDL)/low-density lipoprotein (LDL) particles and cholesterol esters/phospholipids in large LDL. Mendelian randomization indicated that decreased VLDL mean diameter may lead to MC.

CONCLUSIONS

This large-scale study is the first to address metabolomics in subject with/without lumbar MC. Causality studies implicate VLDL related to MC, noting a metabolic etiology. Our study substantiates the field of "spino-metabolomics" and illustrates the power of integrating metabolomics-genomics-imaging phenotypes to discover biomarkers for spinal disorders, paving the way for more personalized spine care for patients.

Effects of dexmedetomidine, propofol, sevoflurane and S-ketamine on the human metabolome: A randomised trial using nuclear magnetic resonance spectroscopy

BACKGROUND

Pharmacometabolomics uses large-scale data capturing methods to uncover drug-induced shifts in the metabolic profile. The specific effects of anaesthetics on the human metabolome are largely unknown.

OBJECTIVE

We aimed to discover whether exposure to routinely used anaesthetics have an acute effect on the human metabolic profile.

DESIGN

Randomised, open-label, controlled, parallel group, phase IV clinical drug trial.

SETTING

The study was conducted at Turku PET Centre, University of Turku, Finland, 2016 to 2017.

PARTICIPANTS

One hundred and sixty healthy male volunteers were recruited. The metabolomic data of 159 were evaluable.

INTERVENTIONS

Volunteers were randomised to receive a 1-h exposure to equipotent doses (EC50 for verbal command) of dexmedetomidine (1.5 ng ml-1; n = 40), propofol (1.7 μg ml-1; n = 40), sevoflurane (0.9% end-tidal; n = 39), S-ketamine (0.75 μg ml-1; n = 20) or placebo (n = 20).

MAIN OUTCOME MEASURES

Metabolite subgroups of apolipoproteins and lipoproteins, cholesterol, glycerides and phospholipids, fatty acids, glycolysis, amino acids, ketone bodies, creatinine and albumin and the inflammatory marker GlycA, were analysed with nuclear magnetic resonance spectroscopy from arterial blood samples collected at baseline, after anaesthetic administration and 70 min postanaesthesia.

RESULTS

All metabolite subgroups were affected. Statistically significant changes vs. placebo were observed in 11.0, 41.3, 0.65 and 3.9% of the 155 analytes in the dexmedetomidine, propofol, sevoflurane and S-ketamine groups, respectively. Dexmedetomidine increased glucose, decreased ketone bodies and affected lipoproteins and apolipoproteins. Propofol altered lipoproteins, fatty acids, glycerides and phospholipids and slightly increased inflammatory marker glycoprotein acetylation. Sevoflurane was relatively inert. S-ketamine increased glucose and lactate, whereas branched chain amino acids and tyrosine decreased.

CONCLUSION

A 1-h exposure to moderate doses of routinely used anaesthetics led to significant and characteristic alterations in the metabolic profile. Dexmedetomidine-induced alterations mirror α2-adrenoceptor agonism. Propofol emulsion altered the lipid profile. The inertness of sevoflurane might prove useful in vulnerable patients. S-ketamine induced amino acid alterations might be linked to its suggested antidepressive properties.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02624401. URL: https://clinicaltrials.gov/ct2/show/NCT02624401.

Metabolomics datasets in the Born in Bradford cohort

Metabolomics is the quantification of small molecules, commonly known as metabolites. Collectively, these metabolites and their interactions within a biological system are known as the metabolome. The metabolome is a unique area of study, capturing influences from both genotype and environment. The availability of high-throughput technologies for quantifying large numbers of metabolites, as well as lipids and lipoprotein particles, has enabled detailed investigation of human metabolism in large-scale epidemiological studies. The Born in Bradford (BiB) cohort includes 12,453 women who experienced 13,776 pregnancies recruited between 2007-2011, their partners and their offspring. In this data note, we describe the metabolomic data available in BiB, profiled during pregnancy, in cord blood and during early life in the offspring. These include two platforms of metabolomic profiling: nuclear magnetic resonance and mass spectrometry. The maternal measures, taken at 26-28 weeks’ gestation, can provide insight into the metabolome during pregnancy and how it relates to maternal and offspring health. The offspring cord blood measurements provide information on the fetal metabolome. These measures, alongside maternal pregnancy measures, can be used to explore how they may influence outcomes. The infant measures (taken around ages 12 and 24 months) provide a snapshot of the early life metabolome during a key phase of nutrition, environmental exposures, growth, and development. These metabolomic data can be examined alongside the BiB cohorts’ extensive phenotype data from questionnaires, medical, educational and social record linkage, and other ‘omics data.

Metabolomics datasets in the Born in Bradford cohort

Metabolomics is the quantification of small molecules, commonly known as metabolites. Collectively, these metabolites and their interactions within a biological system are known as the metabolome. The metabolome is a unique area of study, capturing influences from both genotype and environment. The availability of high-throughput technologies for quantifying large numbers of metabolites, as well as lipids and lipoprotein particles, has enabled detailed investigation of human metabolism in large-scale epidemiological studies. The Born in Bradford (BiB) cohort includes 12,453 women who experienced 13,776 pregnancies recruited between 2007-2011, their partners and their offspring. In this data note, we describe the metabolomic data available in BiB, profiled during pregnancy, in cord blood and during early life in the offspring. These include two platforms of metabolomic profiling: nuclear magnetic resonance and mass spectrometry. The maternal measures, taken at 26-28 weeks' gestation, can provide insight into the metabolome during pregnancy and how it relates to maternal and offspring health. The offspring cord blood measurements provide information on the fetal metabolome. These measures, alongside maternal pregnancy measures, can be used to explore how they may influence outcomes. The infant measures (taken around ages 12 and 24 months) provide a snapshot of the early life metabolome during a key phase of nutrition, environmental exposures, growth, and development. These metabolomic data can be examined alongside the BiB cohorts' extensive phenotype data from questionnaires, medical, educational and social record linkage, and other 'omics data.

Novel Serum and Urinary Metabolites Associated with Diabetic Retinopathy in Three Asian Cohorts

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus, a metabolic disorder, but understanding of its pathophysiology remains incomplete. Meta-analysis of three population-based cross-sectional studies (2004–11) representing three major Asian ethnic groups (aged 40–80 years: Chinese, 592; Malays, 1052; Indians, 1320) was performed. A panel of 228 serum/plasma metabolites and 54 urinary metabolites were quantified using nuclear magnetic resonance (NMR) spectroscopy. Main outcomes were defined as any DR, moderate/above DR, and vision-threatening DR assessed from retinal photographs. The relationship between metabolites and DR outcomes was assessed using multivariate logistic regression models, and metabolites significant after Bonferroni correction were meta-analyzed. Among serum/plasma metabolites, lower levels of tyrosine and cholesterol esters to total lipids ratio in IDL and higher levels of creatinine were positively associated with all three outcomes of DR (all p < 0.005). Among urinary metabolites, lower levels of citrate, ethanolamine, formate, and hypoxanthine were positively associated with all three DR outcomes (all p < 0.005). Higher levels of serum/plasma 3-hydroxybutyrate and lower levels of urinary 3-hydroxyisobutyrate were associated with VTDR. Comprehensive metabolic profiling in three large Asian cohorts with DR demonstrated alterations in serum/plasma and urinary metabolites mostly related to amino acids, lipoprotein subclasses, kidney function, and glycolysis.

Overfeeding Saturated Fat Increases LDL (Low-Density Lipoprotein) Aggregation Susceptibility While Overfeeding Unsaturated Fat Decreases Proteoglycan-Binding of Lipoproteins

Supplemental Digital Content is available in the text.

Objective:

We recently showed that measurement of the susceptibility of LDL (low-density lipoprotein) to aggregation is an independent predictor of cardiovascular events. We now wished to compare effects of overfeeding different dietary macronutrients on LDL aggregation, proteoglycan-binding of plasma lipoproteins, and on the concentration of oxidized LDL in plasma, 3 in vitro parameters consistent with increased atherogenicity.

Approach and Results:

The participants (36 subjects; age, 48±10 years; body mass index, 30.9±6.2 kg/m²) were randomized to consume an extra 1000 kcal/day of either unsaturated fat, saturated fat, or simple sugars (CARB) for 3 weeks. We measured plasma proatherogenic properties (susceptibility of LDL to aggregation, proteoglycan-binding, oxidized LDL) and concentrations and composition of plasma lipoproteins using nuclear magnetic resonance spectroscopy, and in LDL using liquid chromatography mass spectrometry, before and after the overfeeding diets. LDL aggregation increased in the saturated fat but not the other groups. This change was associated with increased sphingolipid and saturated triacylglycerols in LDL and in plasma and reduction of clusterin on LDL particles. Proteoglycan binding of plasma lipoproteins decreased in the unsaturated fat group relative to the baseline diet. Lipoprotein properties remained unchanged in the CARB group.

Conclusions:

The type of fat during 3 weeks of overfeeding is an important determinant of the characteristics and functional properties of plasma lipoproteins in humans.

Registration:

URL: http://www.clinicaltrials.gov; Unique identifier NCT02133144.

Connecting the epigenome, metabolome and proteome for a deeper understanding of disease

Epigenome-wide association studies (EWAS) identify genes that are dysregulated by the studied clinical endpoints, thereby indicating potential new diagnostic biomarkers, drug targets and therapy options. Combining EWAS with deep molecular phenotyping, such as approaches enabled by metabolomics and proteomics, allows further probing of the underlying disease-associated pathways. For instance, methylation of the TXNIP gene is associated robustly with prevalent type 2 diabetes and further with metabolites that are short-term markers of glycaemic control. These associations reflect TXNIP's function as a glucose uptake regulator by interaction with the major glucose transporter GLUT1 and suggest that TXNIP methylation can be used as a read-out for the organism's exposure to glucose stress. Another case is the association between DNA methylation of the AHRR and F2RL3 genes with smoking and a protein that is involved in the reprogramming of the bronchial epithelium. These examples show that associations between DNA methylation and intermediate molecular traits can open new windows into how the body copes with physiological challenges. This knowledge, if carefully interpreted, may indicate novel therapy options and, together with monitoring of the methylation state of specific methylation sites, may in the future allow the early diagnosis of impending disease. It is essential for medical practitioners to recognize the potential that this field holds in translating basic research findings to clinical practice. In this review, we present recent advances in the field of EWAS with metabolomics and proteomics and discuss both the potential and the challenges of translating epigenetic associations, with deep molecular phenotypes, to biomedical applications.

Body muscle gain and markers of cardiovascular disease susceptibility in young adulthood: A cohort study

BACKGROUND

The potential benefits of gaining body muscle for cardiovascular disease (CVD) susceptibility, and how these compare with the potential harms of gaining body fat, are unknown. We compared associations of early life changes in body lean mass and handgrip strength versus body fat mass with atherogenic traits measured in young adulthood.

METHODS AND FINDINGS

Data were from 3,227 offspring of the Avon Longitudinal Study of Parents and Children (39% male; recruited in 1991-1992). Limb lean and total fat mass indices (kg/m2) were measured using dual-energy X-ray absorptiometry scans performed at age 10, 13, 18, and 25 y (across clinics occurring from 2001-2003 to 2015-2017). Handgrip strength was measured at 12 and 25 y, expressed as maximum grip (kg or lb/in2) and relative grip (maximum grip/weight in kilograms). Linear regression models were used to examine associations of change in standardised measures of these exposures across different stages of body development with 228 cardiometabolic traits measured at age 25 y including blood pressure, fasting insulin, and metabolomics-derived apolipoprotein B lipids. SD-unit gain in limb lean mass index from 10 to 25 y was positively associated with atherogenic traits including very-low-density lipoprotein (VLDL) triglycerides. This pattern was limited to lean gain in legs, whereas lean gain in arms was inversely associated with traits including VLDL triglycerides, insulin, and glycoprotein acetyls, and was also positively associated with creatinine (a muscle product and positive control). Furthermore, this pattern for arm lean mass index was specific to SD-unit gains occurring between 13 and 18 y, e.g., -0.13 SD (95% CI -0.22, -0.04) for VLDL triglycerides. Changes in maximum and relative grip from 12 to 25 y were both positively associated with creatinine, but only change in relative grip was also inversely associated with atherogenic traits, e.g., -0.12 SD (95% CI -0.18, -0.06) for VLDL triglycerides per SD-unit gain. Change in fat mass index from 10 to 25 y was more strongly associated with atherogenic traits including VLDL triglycerides, at 0.45 SD (95% CI 0.39, 0.52); these estimates were directionally consistent across sub-periods, with larger effect sizes with more recent gains. Associations of lean, grip, and fat measures with traits were more pronounced among males. Study limitations include potential residual confounding of observational estimates, including by ectopic fat within muscle, and the absence of grip measures in adolescence for estimates of grip change over sub-periods.

CONCLUSIONS

In this study, we found that muscle strengthening, as indicated by grip strength gain, was weakly associated with lower atherogenic trait levels in young adulthood, at a smaller magnitude than unfavourable associations of fat mass gain. Associations of muscle mass gain with such traits appear to be smaller and limited to gains occurring in adolescence. These results suggest that body muscle is less robustly associated with markers of CVD susceptibility than body fat and may therefore be a lower-priority intervention target.

A novel canine nuclear magnetic resonance spectroscopy-based metabolomics platform: Validation and sample handling

BACKGROUND

Metabolomics has been proven to be an invaluable research tool by providing comprehensive insight into systemic metabolism. However, the lack of scalable and quantitative methods with known reference intervals (RIs) and documented reproducibility has prevented the use of metabolomics in the clinical setting.

OBJECTIVE

The objective of this study was to validate the developed quantitative nuclear magnetic resonance (NMR) spectroscopy-based metabolomics platform for canine serum and plasma samples and determine optimal sample handling conditions for its use.

METHODS

Altogether, 8247 canine samples were analyzed using a Bruker's 500 MHz NMR spectrometer. Using statistical approaches derived from international guidelines, we studied method precision, measurand stability in various long- and short-term storage conditions, as well as the effect of prolonged contact with red blood cells (RBCs), and differences among blood collection tubes. We also screened interferences with lipemia, hemolysis, and bilirubinemia. The results were compared against routine clinical chemistry methods, and RIs were defined for all measurands.

RESULTS

We determined RIs for 123 measurands, most of which were previously unpublished. The reproducibility of the results of the NMR platform appeared generally outstanding, and the integrity of the results can be ensured by following standard blood drawing and processing guidelines.

CONCLUSIONS

Owing to the advantages of quantitative results, high reproducibility, and scalability, this canine metabolomics platform holds great potential for numerous clinical and research applications to improve canine health and well-being.

A Cross-Platform Metabolomics Comparison Identifies Serum Metabolite Signatures of Liver Fibrosis Progression in Chronic Hepatitis C Patients

Metabolomics offers new insights into disease mechanisms that is enhanced when adopting orthogonal instrumental platforms to expand metabolome coverage, while also reducing false discoveries by independent replication. Herein, we report the first inter-method comparison when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) and nuclear magnetic resonance (NMR) spectroscopy for characterizing the serum metabolome of patients with liver fibrosis in chronic hepatitis C virus (HCV) infection (n = 20) and non-HCV controls (n = 14). In this study, 60 and 30 serum metabolites were detected frequently (>75%) with good technical precision (median CV < 10%) from serum filtrate samples (n = 34) when using standardized protocols for MSI-CE-MS and NMR, respectively. Also, 20 serum metabolite concentrations were consistently measured by both methods over a 500-fold concentration range with an overall mean bias of 9.5% (n = 660). Multivariate and univariate statistical analyses independently confirmed that serum choline and histidine were consistently elevated (p < 0.05) in HCV patients with late-stage (F2-F4) as compared to early-stage (F0-F1) liver fibrosis. Overall, the ratio of serum choline to uric acid provided optimal differentiation of liver disease severity (AUC = 0.848, p = 0.00766) using a receiver operating characteristic curve, which was positively correlated with liver stiffness measurements by ultrasound imaging (r = 0.606, p = 0.0047). Moreover, serum 5-oxo-proline concentrations were higher in HCV patients as compared to non-HCV controls (F = 4.29, p = 0.0240) after adjustment for covariates (age, sex, BMI), indicative of elevated oxidative stress from glutathione depletion with the onset and progression of liver fibrosis. Both instrumental techniques enable rapid yet reliable quantification of serum metabolites in large-scale metabolomic studies with good overlap for biomarker replication. Advantages of MSI-CE-MS include greater metabolome coverage, lower operating costs, and smaller sample volume requirements, whereas NMR offers a robust platform supported by automated spectral and data processing software.

Association of Emulsifier and Highly Processed Food Intake with Circulating Markers of Intestinal Permeability and Inflammation in the Cancer Prevention Study-3 Diet Assessment Sub-Study

Compelling animal studies report increased intestinal permeability, inflammation, and colorectal carcinogenesis with exposure to certain emulsifiers commonly added to processed foods, but human data are lacking. Highly processed food consumption is also associated with obesity and higher risk of chronic diseases. We cross-sectionally examined the association of emulsifier and highly processed food consumption estimated from six 24-h dietary recalls among 588 U.S. men and women over one year, with biomarkers of intestinal permeability and inflammation measured from two fasting blood samples collected six months apart. In multivariable-adjusted generalized linear models, greater emulsifier intake (g/d) was not associated with antibodies to flagellin (P-trend = 0.88), lipopolysaccharide (LPS) (P-trend = 0.56), or the combined total thereof (P-trend = 0.65) but was positively associated with an inflammatory biomarker, glycoprotein acetyls (GlycA) (P-trend = 0.02). Highly processed food intake (% kcal/d) was associated with higher anti-LPS antibodies (P-trend = 0.001) and total anti-flagellin and anti-LPS antibodies (P-trend = 0.005) but not with other biomarkers, whereas processed food intake expressed as % g/d was associated with higher GlycA (P-trend = 0.02). Our findings suggest that, broadly, highly processed food consumption may be associated with intestinal permeability biomarkers, and both emulsifier and highly processed food intakes may be associated with inflammation. Additional studies are warranted to further evaluate these relationships.Supplemental data for this article is available online at https://doi.org/10.1080/01635581.2021.1957947.

The association between plasma metabolites and sleep quality in the Southall and Brent Revisited (SABRE) Study: A cross-sectional analysis

We examined the association between plasma metabolites and abnormal sleep patterns using data from the Southall and Brent REvisited (SABRE) cohort. Nuclear magnetic resonance spectroscopy provided 146 circulating plasma metabolites. Sleep questionnaires identified the presence or absence of: difficulty falling asleep, early morning waking, waking up tired, and snoring. Metabolites were compared between the sleep quality categories using the t test, and then filtered using a false discovery rate of 0.05. Generalised linear models with logit-link assessed the associations between filtered metabolites and sleep phenotypes. Adjustment was made for important demographic and health-related covariates. In all, 2,718 participants were included in the analysis. After correcting for multiple testing, three metabolites remained for difficulty falling asleep, 59 for snoring, and none for early morning waking and waking up tired. After adjusting for sex, age, ethnicity and years of education, 1 standard deviation increase in serum histidine and valine associated with lower odds of difficulty falling asleep by 0.89-0.90 (95% confidence intervals [CIs] 0.80-0.99). Branched-chain and aromatic amino acids (odds ratios [ORs] 1.19-1.25, 95% CIs 1.09-1.36) were positively associated with snoring. Total cholesterol in low-density lipoprotein (OR 0.90, 95% CI 0.83-0.97) and high-density lipoprotein (OR 0.88, 95% CI 0.81-0.95) associated with lower odds of snoring. In the fully adjusted model, most associations persisted. To conclude, histidine and valine associated with lower odds of difficulty falling asleep, while docosahexaenoic acid and cholesterol in low-density lipoprotein and high-density lipoprotein subfractions associated with lower odds of snoring. Identified metabolites could provide guidance on the metabolic pathways associated with adverse sleep quality.

A variant near DHCR24 associates with microstructural properties of white matter and peripheral lipid metabolism in adolescents

Visceral adiposity has been associated with altered microstructural properties of white matter in adolescents. Previous evidence suggests that circulating phospholipid PC(16:0/2:0) may mediate this association. To investigate the underlying biology, we performed a genome-wide association study (GWAS) of the shared variance of visceral fat, PC(16:0/2:0), and white matter microstructure in 872 adolescents from the Saguenay Youth Study. We further studied the metabolomic profile of the GWAS-lead variant in 931 adolescents. Visceral fat and white matter microstructure were assessed with magnetic resonance imaging. Circulating metabolites were quantified with serum lipidomics and metabolomics. We identified a genome-wide significant association near DHCR24 (Seladin-1) encoding a cholesterol-synthesizing enzyme (rs588709, p = 3.6 × 10-8); rs588709 was also associated nominally with each of the three traits (white matter microstructure: p = 2.1 × 10-6, PC(16:0/2:0): p = 0.005, visceral fat: p = 0.010). We found that the metabolic profile associated with rs588709 resembled that of a TM6SF2 variant impacting very low-density lipoprotein (VLDL) secretion and was only partially similar to that of a HMGCR variant. This suggests that the effect of rs588709 on VLDL lipids may arise due to altered phospholipid rather than cholesterol metabolism. The rs588709 was also nominally associated with circulating concentrations of omega-3 fatty acids in interaction with visceral fat and PC(16:0/2:0), and these fatty acid measures showed robust associations with white matter microstructure. Overall, the present study provides evidence that the DHCR24 locus may link peripheral metabolism to brain microstructure, an association with implications for cognitive impairment.

A computationally efficient Bayesian seemingly unrelated regressions model for high-dimensional quantitative trait loci discovery

Our work is motivated by the search for metabolite quantitative trait loci (QTL) in a cohort of more than 5000 people. There are 158 metabolites measured by NMR spectroscopy in the 31-year follow-up of the Northern Finland Birth Cohort 1966 (NFBC66). These metabolites, as with many multivariate phenotypes produced by high-throughput biomarker technology, exhibit strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate QTL analysis generally ignore phenotypic correlations or make restrictive assumptions about the associations between phenotypes and genetic loci. We present a computationally efficient Bayesian seemingly unrelated regressions model for high-dimensional data, with cell-sparse variable selection and sparse graphical structure for covariance selection. Cell sparsity allows different phenotype responses to be associated with different genetic predictors and the graphical structure is used to represent the conditional dependencies between phenotype variables. To achieve feasible computation of the large model space, we exploit a factorisation of the covariance matrix. Applying the model to the NFBC66 data with 9000 directly genotyped single nucleotide polymorphisms, we are able to simultaneously estimate genotype-phenotype associations and the residual dependence structure among the metabolites. The R package BayesSUR with full documentation is available at https://cran.r-project.org/web/packages/BayesSUR/.

Metabolic profiles of socio-economic position: a multi-cohort analysis

Background

Low socio-economic position (SEP) is a risk factor for multiple health outcomes, but its molecular imprints in the body remain unclear.

Methods

We examined SEP as a determinant of serum nuclear magnetic resonance metabolic profiles in ∼30 000 adults and 4000 children across 10 UK and Finnish cohort studies.

Results

In risk-factor-adjusted analysis of 233 metabolic measures, low educational attainment was associated with 37 measures including higher levels of triglycerides in small high-density lipoproteins (HDL) and lower levels of docosahexaenoic acid (DHA), omega-3 fatty acids, apolipoprotein A1, large and very large HDL particles (including levels of their respective lipid constituents) and cholesterol measures across different density lipoproteins. Among adults whose father worked in manual occupations, associations with apolipoprotein A1, large and very large HDL particles and HDL-2 cholesterol remained after adjustment for SEP in later life. Among manual workers, levels of glutamine were higher compared with non-manual workers. All three indicators of low SEP were associated with lower DHA, omega-3 fatty acids and HDL diameter. At all ages, children of manual workers had lower levels of DHA as a proportion of total fatty acids.

Conclusions

Our work indicates that social and economic factors have a measurable impact on human physiology. Lower SEP was independently associated with a generally unfavourable metabolic profile, consistent across ages and cohorts. The metabolites we found to be associated with SEP, including DHA, are known to predict cardiovascular disease and cognitive decline in later life and may contribute to health inequalities.

Associations of metabolomic profiles with circulating vitamin E and urinary vitamin E metabolites in middle-aged individuals

Vitamin E (α-tocopherol [α-TOH]) is transported in lipoprotein particles in blood, but little is known about the transportation of its oxidized metabolites. In the Netherlands Epidemiology of Obesity Study, we aimed to investigate the associations of 147 circulating metabolomic measures obtained through targeted nuclear magnetic resonance with serum α-TOH and its urinary enzymatic (α-CEHC) and oxidized (α-TLHQ) metabolites from 24-h urine quantified by liquid chromatography with tandem mass spectrometry. Multivariable linear regression analyses, in which multiple testing was taken into account, were performed to assess associations between metabolomic measures (determinants; standardized to mean = 0, SD = 1) and vitamin E metabolites (outcomes), adjusted for demographic factors. We analyzed 474 individuals (55% women, 45% men) with a mean (SD) age of 55.7 (6.0) y. Out of 147 metabolomic measures, 106 were associated (P < 1.34 × 10^-3) with serum α-TOH (median β [interquartile range] = 0.416 [0.383-0.466]), predominantly lipoproteins associated with higher α-TOH. The associations of metabolomic measures with urinary α-CEHC have directions similar to those with α-TOH, but effect sizes were smaller and non-significant (median β [interquartile range] = 0.065 [0.047-0.084]). However, associations of metabolomic measures with urinary α-TLHQ were markedly different from those with both serum α-TOH and urinary α-CEHC, with negative and small-to-null relations to most very-low-density lipoproteins and amino acids. Therefore, our results highlight the differences in the lipoproteins involved in the transportation of circulating α-TOH and oxidized vitamin E metabolites. This indicates that circulating α-TOH may be representative of the enzymatic but not the antioxidative function of vitamin E.

The potential of nuclear magnetic resonance (NMR) in metabolomics and lipidomics of microalgae- a review

Microalgae biotechnology has made it possible to derive secondary bioactive metabolites from microalgae strains that have opened up their entire potential to uncover a wide range of novel metabolic capabilities and turn these into bio-products for the development of sustainable bio-refineries. Nuclear Magnetic Resonance Technology (NMR) has been one of the most successful and functional research technology over the past two decades to analyse the composition, structure and functionality of distinct metabolites in the different microalgae strains. This technology offers qualitative as well as quantitative knowledge about the endogenous metabolites and lipids of low molecular mass to offer a good picture of the physiological state of biological samples in metabolomics and lipidomics studies. Henceforth, this review is aimed at introducing the metabolomics and lipidomics studies into the field of NMR technology and also highlights the protocols for the isolation and metabolic measurements of metabolites from microalgae that should be redirected to resource recovery and value-added products with a systematic and holistic approach for scalability or sustainability.

Very Low-Density Lipoprotein Cholesterol May Mediate a Substantial Component of the Effect of Obesity on Myocardial Infarction Risk: The Copenhagen General Population Study

BACKGROUND

Individuals with obesity have higher concentrations of very low-density lipoprotein (VLDL) cholesterol and increased risk of myocardial infarction. We hypothesized that VLDL cholesterol explains a fraction of the excess myocardial infarction risk in individuals with obesity.

METHODS

We included 29 010 individuals free of myocardial infarction at baseline, nested within 109 751 individuals from the Copenhagen General Population Study. During 10 years of follow-up, 2306 individuals developed myocardial infarction. Cholesterol content in large and small VLDLs, in intermediate-density lipoprotein (IDL), and in LDL was measured directly with nuclear magnetic resonance spectroscopy.

RESULTS

Median concentrations of cholesterol in large and small VLDLs were 0.12 mmol/L (interquartile range [IQR], 0.07-0.20 mmol/L; 4.5 mg/dL [IQR, 2.6-6.9 mg/dL]) and 0.6 mmol/L (IQR, 0.5-0.8 mmol/L; 25 mg/dL [IQR, 20-30 mg/dL]) in individuals with obesity vs 0.06 mmol/L (IQR, 0.03-0.1 mmol/L; 2.2 mg/dL [IQR, 1.1-3.8 mg/dL]), and 0.5 mmol/L (IQR, 0.4-0.6 mmol/L; 20 mg/dL (IQR, 16-25 mg/dL]) in individuals with normal weight; in contrast, concentrations of IDL and LDL cholesterol were similar across body mass index (BMI) categories. Cholesterol in large and small VLDLs combined explained 40% (95% CI, 27%-53%) of the excess risk of myocardial infarction associated with higher BMI. In contrast, IDL and LDL cholesterol did not explain excess risk of myocardial infarction, whereas systolic blood pressure explained 17% (11%-23%) and diabetes mellitus explained 8.6% (3.2%-14%).

CONCLUSIONS

VLDL cholesterol explains a large fraction of excess myocardial infarction risk in individuals with obesity. These novel findings support a focus on cholesterol in VLDL for prevention of myocardial infarction and atherosclerotic cardiovascular disease in individuals with obesity.

Systematic evaluation of the association between hemoglobin levels and metabolic profile implicates beneficial effects of hypoxia

Activation of the hypoxia-inducible factor (HIF) pathway reprograms energy metabolism. Hemoglobin (Hb) is the main carrier of oxygen. Using its normal variation as a surrogate measure for hypoxia, we explored whether lower Hb levels could lead to healthier metabolic profiles in mice and humans (n = 7175) and used Mendelian randomization (MR) to evaluate potential causality (n = 173,480). The results showed evidence for lower Hb levels being associated with lower body mass index, better glucose tolerance and other metabolic profiles, lower inflammatory load, and blood pressure. Expression of the key HIF target genes SLC2A4 and Slc2a1 in skeletal muscle and adipose tissue, respectively, associated with systolic blood pressure in MR analyses and body weight, liver weight, and adiposity in mice. Last, manipulation of murine Hb levels mediated changes to key metabolic parameters. In conclusion, low-end normal Hb levels may be favorable for metabolic health involving mild chronic activation of the HIF response.

Improved Automated Quantification Algorithm (AQuA) and Its Application to NMR-Based Metabolomics of EDTA-Containing Plasma

We have recently presented an Automated Quantification Algorithm (AQuA) and demonstrated its utility for rapid and accurate absolute metabolite quantification in ¹H NMR spectra in which positions and line widths of signals were predicted from a constant metabolite spectral library. The AQuA quantifies based on one preselected signal per metabolite and employs library spectra to model interferences from other metabolite signals. However, for some types of spectra, the interspectral deviations of signal positions and line widths can be pronounced; hence, interferences cannot be modeled using a constant spectral library. We here address this issue and present an improved AQuA that handles interspectral deviations. The improved AQuA monitors and characterizes the appearance of specific signals in each spectrum and automatically adjusts the spectral library to model interferences accordingly. The performance of the improved AQuA was tested on a large data set from plasma samples collected using ethylenediaminetetraacetic acid (EDTA) as an anticoagulant (n = 772). These spectra provided a suitable test system for the improved AQuA since EDTA signals (i) vary in intensity, position, and line width between spectra and (ii) interfere with many signals from plasma metabolites targeted for quantification (n = 54). Without the improvement, ca. 20 out of the 54 metabolites would have been overestimated. This included acetylcarnitine and ornithine, which are considered particularly difficult to quantify with ¹H NMR in EDTA-containing plasma. Furthermore, the improved AQuA performed rapidly (<10 s for all spectra). We believe that the improved AQuA provides a basis for automated quantification in other data sets where specific signals show interspectral deviations.

Childhood overeating is associated with adverse cardiometabolic and inflammatory profiles in adolescence

Childhood eating behaviour contributes to the rise of obesity and related noncommunicable disease worldwide. However, we lack a deep understanding of biochemical alterations that can arise from aberrant eating behaviour. In this study, we prospectively associate longitudinal trajectories of childhood overeating, undereating, and fussy eating with metabolic markers at age 16 years to explore adolescent metabolic alterations related to specific eating patterns in the first 10 years of life. Data are from the Avon Longitudinal Study of Parents and Children (n = 3104). We measure 158 metabolic markers with a high-throughput (1H) NMR metabolomics platform. Increasing childhood overeating is prospectively associated with an adverse cardiometabolic profile (i.e., hyperlipidemia, hypercholesterolemia, hyperlipoproteinemia) in adolescence; whereas undereating and fussy eating are associated with lower concentrations of the amino acids glutamine and valine, suggesting a potential lack of micronutrients. Here, we show associations between early behavioural indicators of eating and metabolic markers.

Meal-induced inflammation: postprandial insights from the Personalised REsponses to DIetary Composition Trial (PREDICT) study in 1000 participants

BACKGROUND

Meal-induced metabolic changes trigger an acute inflammatory response, contributing to chronic inflammation and associated diseases.

OBJECTIVES

We aimed to characterize variability in postprandial inflammatory responses using traditional (IL-6) and novel [glycoprotein acetylation (GlycA)] biomarkers of inflammation and dissect their biological determinants with a focus on postprandial glycemia and lipemia.

METHODS

Postprandial (0-6 h) glucose, triglyceride (TG), IL-6, and GlycA responses were measured at multiple intervals after sequential mixed-nutrient meals (0 h and 4 h) in 1002 healthy adults aged 18-65 y from the PREDICT (Personalised REsponses to DIetary Composition Trial) 1 study, a single-arm dietary intervention study. Measures of habitual diet, blood biochemistry, gut microbiome composition, and visceral fat mass (VFM) were also collected.

RESULTS

The postprandial changes in GlycA and IL-6 concentrations were highly variable between individuals. Participants eliciting an increase in GlycA and IL-6 (60% and 94% of the total participants, respectively) had mean 6-h increases of 11% and 190%, respectively. Peak postprandial TG and glucose concentrations were significantly associated with 6-h GlycA (r = 0.83 and r = 0.24, respectively; both P < 0.001) but not with 6-h IL-6 (both P > 0.26). A random forest model revealed the maximum TG concentration was the strongest postprandial TG predictor of postprandial GlycA and structural equation modeling revealed that VFM and fasting TG were most strongly associated with fasting and postprandial GlycA. Network Mendelian randomization demonstrated a causal link between VFM and fasting GlycA, mediated (28%) by fasting TG. Individuals eliciting enhanced GlycA responses had higher predicted cardiovascular disease risk (using the atherosclerotic disease risk score) than the rest of the cohort.

CONCLUSIONS

The variable postprandial increases in GlycA and their associations with TG metabolism highlight the importance of modulating TG in concert with obesity to reduce GlycA and associated low-grade inflammation-related diseases.This trial was registered at clinicaltrials.gov as NCT03479866.

Serum NMR metabolomics uncovers multiple metabolic changes in phenobarbital-treated dogs

INTRODUCTION

Phenobarbital is a commonly used anticonvulsant for the treatment of canine epileptic seizures. In addition to its central nervous system (CNS) depressing effects, long-term phenobarbital administration affects liver function. However, broader metabolic consequences of phenobarbital treatment are poorly characterized.

OBJECTIVES

To identify metabolic changes in the sera of phenobarbital-treated dogs and to investigate the relationship between serum phenobarbital concentration and metabolite levels.

METHODS

Leftovers of clinical samples were used: 58 cases with phenobarbital concentrations ranging from 7.8 µg/mL to 50.8 µg/mL, and 25 controls. The study design was cross-sectional. The samples were analyzed by a canine-specific 1H NMR metabolomics platform. Differences between the case and control groups were evaluated by logistic regression. The linear relationship between metabolite and phenobarbital concentrations was evaluated using linear regression.

RESULTS

Increasing concentrations of glycoprotein acetyls, LDL particle size, palmitic acid, and saturated fatty acids, and decreasing concentrations of albumin, glutamine, histidine, LDL particle concentration, multiple HDL measures, and polyunsaturated fatty acids increased the odds of the sample belonging to the phenobarbital-treated group, having a p-value < .0033, and area under the curve (AUC) > .7. Albumin and glycoprotein acetyls had the best discriminative ability between the groups (AUC: .94). No linear associations between phenobarbital and metabolite concentrations were observed.

CONCLUSION

The identified metabolites are known to associate with, for example, liver and CNS function, inflammatory processes and drug binding. The lack of a linear association to phenobarbital concentration suggests that other factors than the blood phenobarbital concentration contribute to the magnitude of metabolic changes.

Targeted metabolomic profiling and prediction of cardiovascular events: a prospective study of patients with psoriatic arthritis and psoriasis

OBJECTIVE

In patients with psoriatic disease (PsD), we sought serum metabolites associated with cardiovascular (CV) events and investigated whether they could improve CV risk prediction beyond traditional risk factors and the Framingham Risk Score (FRS).

METHODS

Nuclear magnetic resonance metabolomics identified biomarkers for incident CV events in patients with PsD. The association of each metabolite with incident CV events was analysed using Cox proportional hazards regression models first adjusted for age and sex, and subsequently for traditional CV risk factors. Variable selection was performed using penalisation with boosting after adjusting for age and sex, and the FRS.

RESULTS

Among 977 patients with PsD, 70 patients had incident CV events. In Cox regression models adjusted for CV risk factors, alanine, tyrosine, degree of unsaturation of fatty acids and high-density lipoprotein particles were associated with decreased CV risk. Glycoprotein acetyls, apolipoprotein B and cholesterol remnants were associated with increased CV risk. The age-adjusted and sex-adjusted expanded model with 13 metabolites significantly improved prediction of CV events beyond the model with age and sex alone, with an area under the receiver operator characteristic curve (AUC) of 79.9 versus 72.6, respectively (p=0.02). Compared with the FRS alone (AUC=73.9), the FRS-adjusted expanded model with 11 metabolites (AUC=75.0, p=0.72) did not improve CV risk discrimination.

CONCLUSIONS

We identify novel metabolites associated with the development of CV events in patients with PsD. Further study of their underlying causal role may clarify important pathways leading to CV events in this population.

Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis

Aims 

Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement.

Methods and results 

Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function.

Conclusions 

Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower risk of coronary heart disease and type 2 diabetes. These findings reinforce evidence that enhancing LPL activity (either directly or via upstream effects) through pharmacological approaches is likely to yield benefits to human health.

Urine metabolite profiling of Indian Antarctic Expedition members: NMR spectroscopy-based metabolomic investigation

The southernmost region of earth, Antarctica, has world's most challenging environments. Those who live for long time and work in Antarctic stations are subjected to environmental stresses such as cold weather, photoperiod variations leading to disrupted sleep cycles, constrained living spaces, dry air, non-availability of fresh food items, and high electromagnetic radiations, psychological factors, such as geographical and social isolation, etc. All these factors have a significant impact on the human body. The present study investigated the impact of Antarctica harsh environment on human physiology and its metabolic processes by evaluating urine metabolome, using 1H NMR spectroscopy and analyzing certain physiological and clinical parameters for correlation with physiological expression data and metabolite results. Two study groups - before Antarctic exposure (B) and after Antarctic exposure (E), consisting of 11 subjects, exposed to one-month summer expedition, were compared. 35 metabolites in urine samples were identified from the 700 MHz ¹H NMR spectra from where integral intensity of 22 important metabolites was determined. Univariate analysis indicated significant decrease in the levels of citrate and creatinine in samples collected post-expedition. Multivariate analysis was also performed using 1H NMR spectroscopy, because independent metabolite abundances may complement each other in predicting the dependent variables. 10 metabolites were identified among the groups; the OPLS-DA and VIP score indicated variation in appearance of metabolites over different time periods with insignificant change in the intensities. Metabolite results illustrate the impact of environmental stress or altered life style including the diet with absence of fresh fruits and vegetables, on the pathophysiology of the human health. Metabolic adaptation to Antarctic environmental stressors may help to highlight the effect of short-term physiological status and provide important information during Antarctic expeditions to formulate management programmes.

Activation of pregnane X receptor induces atherogenic lipids and PCSK9 by a SREBP2-mediated mechanism

BACKGROUND AND PURPOSE

Many drugs and environmental contaminants induce hypercholesterolemia and promote the risk of atherosclerotic cardiovascular disease. We tested the hypothesis that pregnane X receptor (PXR), a xenobiotic-sensing nuclear receptor, regulates the level of circulating atherogenic lipids in humans and utilized mouse experiments to identify the mechanisms involved.

EXPERIMENTAL APPROACH

We performed serum NMR metabolomics in healthy volunteers administered rifampicin, a prototypical human PXR ligand or placebo in a crossover setting. We used high-fat diet fed wild-type and PXR knockout mice to investigate the mechanisms mediating the PXR-induced alterations in cholesterol homeostasis.

KEY RESULTS

Activation of PXR induced cholesterogenesis both in pre-clinical and clinical settings. In human volunteers, rifampicin increased intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL) and total cholesterol and lathosterol-cholesterol ratio, a marker of cholesterol synthesis, suggesting increased cholesterol synthesis. Experiments in mice indicated that PXR activation causes widespread induction of the cholesterol synthesis genes including the rate-limiting Hmgcr and upregulates the intermediates in the Kandutsch-Russell cholesterol synthesis pathway in the liver. Additionally, PXR activation induced plasma proprotein convertase subtilisin/kexin type 9 (PCSK9), a negative regulator of hepatic LDL uptake, in both mice and humans. We propose that these effects were mediated through increased proteolytic activation of sterol regulatory element-binding protein 2 (SREBP2) in response to PXR activation.

CONCLUSION AND IMPLICATIONS

PXR activation induces cholesterol synthesis, elevating LDL and total cholesterol in humans. The PXR-SREBP2 pathway is a novel regulator of the cholesterol and PCSK9 synthesis and a molecular mechanism for drug- and chemical-induced hypercholesterolemia.

Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population

Biomarkers of low-grade inflammation have been associated with susceptibility to a severe infectious disease course, even when measured prior to disease onset. We investigated whether metabolic biomarkers measured by nuclear magnetic resonance (NMR) spectroscopy could be associated with susceptibility to severe pneumonia (2507 hospitalised or fatal cases) and severe COVID-19 (652 hospitalised cases) in 105,146 generally healthy individuals from UK Biobank, with blood samples collected 2007-2010. The overall signature of metabolic biomarker associations was similar for the risk of severe pneumonia and severe COVID-19. A multi-biomarker score, comprised of 25 proteins, fatty acids, amino acids, and lipids, was associated equally strongly with enhanced susceptibility to severe COVID-19 (odds ratio 2.9 [95%CI 2.1-3.8] for highest vs lowest quintile) and severe pneumonia events occurring 7-11 years after blood sampling (2.6 [1.7-3.9]). However, the risk for severe pneumonia occurring during the first 2 years after blood sampling for people with elevated levels of the multi-biomarker score was over four times higher than for long-term risk (8.0 [4.1-15.6]). If these hypothesis generating findings on increased susceptibility to severe pneumonia during the first few years after blood sampling extend to severe COVID-19, metabolic biomarker profiling could potentially complement existing tools for identifying individuals at high risk. These results provide novel molecular understanding on how metabolic biomarkers reflect the susceptibility to severe COVID-19 and other infections in the general population.

Cord serum metabolome and birth weight in patients with gestational diabetes treated with metformin, insulin, or diet alone

INTRODUCTION

Recent research has demonstrated the benefits of metformin treatment in gestational diabetes (GDM) on short-term pregnancy outcomes (including excessive fetal growth and pre-eclampsia), but its effects on fetal metabolism remain mostly unknown. Our aim was to study the effects of metformin treatment compared with insulin or diet on the cord serum metabolome and also to assess how these metabolites are related to birth weight (BW) in pregnancies complicated by GDM.

RESEARCH DESIGN AND METHODS

Cord serum samples were available from 113, 97, and 98 patients with GDM treated with diet, insulin, and metformin, respectively. A targeted metabolome was measured using nuclear magnetic resonance spectroscopy. The patients in the metformin and insulin groups had participated in a previous randomized trial (NCT01240785).

RESULTS

Cord serum alanine was elevated in the metformin group (0.53 mmol/L) compared with the insulin (0.45 mmol/L, p<0.001) and the diet groups (0.46 mmol/L, p<0.0001). All other measured metabolites were similar between the groups. The triglyceride (TG)-to-phosphoglyceride ratio, average very low-density lipoprotein particle diameter, docosahexaenoic acid, omega-3 fatty acids (FAs), and ratios of omega-3 and monounsaturated FA to total FA were inversely related to BW. The omega-6-to-total-FA and omega-6-to-omega-3-FA ratios were positively related to BW. Cholesterol in very large and large high-density lipoprotein (HDL) was positively (p<0.01) associated with BW when adjusted for maternal prepregnancy body mass index, gestational weight gain, glycated hemoglobin, and mode of delivery.

CONCLUSIONS

Metformin treatment in GDM leads to an increase in cord serum alanine. The possible long-term implications of elevated neonatal alanine in this context need to be evaluated in future studies. Although previous studies have shown that metformin increased maternal TG levels, the cord serum TG levels were not affected. Cord serum HDL cholesterol and several FA variables are related to the regulation of fetal growth in GDM. Moreover, these associations seem to be independent of maternal confounding factors.

TRIAL REGISTRATION NUMBER

NCT01240785.

Plasma Branched-Chain Amino Acids Are Associated With Greater Fasting and Postprandial Insulin Secretion in Non-diabetic Chinese Adults

Background: Plasma branched-chain amino acids (BCAA) are consistently elevated in subjects with obesity and type 2 diabetes (T2DM) and correlate with insulin resistance. The association of BCAA with insulin secretion and clearance rates has not been adequately described. Objective: To evaluate the relationships between fasting and postprandial plasma BCAA, insulin secretion and insulin clearance. Design: Ninety-five non-diabetic Chinese subjects (43 females) underwent a mixed-meal tolerance test; blood biomarkers including BCAAs (leucine, isoleucine, valine) were measured for 6 h. Fasting and postprandial insulin secretion rates (ISR) and insulin clearance were determined by oral minimal modeling of glucose and C-peptide. Results: Fasting and postprandial plasma BCAA correlated strongly with each other (ρ = 0.796, P < 0.001), and both were positively associated with basal ISR (ρ = 0.45/0.36, P < 0.001), total postprandial ISR AUC (ρ = 0.37/0.45, P < 0.001), and negatively with insulin clearance (ρ = -0.29/-0.29, P < 0.01), after adjusting for sex and body mass index. These relationships largely persisted after adjusting further for insulin resistance and postprandial glucose. Compared with subjects in the middle and lowest tertiles for fasting or postprandial plasma BCAA, subjects in the highest tertile had significantly greater postprandial glucose (by 7-10%) and insulin (by 74-98%) concentrations, basal ISRs (by 34-53%), postprandial ISR AUCs (by 41-49%), and lower insulin clearance rates (by 17-22%) (all P < 0.05). Conclusions: Fasting and postprandial plasma BCAA levels are associated with greater fasting and postprandial insulin secretion and reduced insulin clearance in healthy Chinese subjects. These observations potentially highlight an additional layer of involvement of BCAA in the regulation of glucose homeostasis.

Novel associations between parental and newborn cord blood metabolic profiles in the Norwegian Mother, Father and Child Cohort Study

BACKGROUND

More than one third of Norwegian women and men between 20 and 40 years of age have elevated cholesterol concentration. Parental metabolic health around conception or during pregnancy may affect the offspring's cardiovascular disease risk. Lipids are important for fetal development, but the determinants of cord blood lipids have scarcely been studied. We therefore aimed to describe the associations between maternal and paternal peri-pregnancy lipid and metabolic profile and newborn cord blood lipid and metabolic profile.

METHODS

This study is based on 710 mother-father-newborn trios from the Norwegian Mother, Father and Child Cohort Study (MoBa) and uses data from the Medical Birth Registry of Norway (MBRN). The sample included in this study consisted of parents with and without self-reported hypercholesterolemia the last 6 months before pregnancy and their partners and newborns. Sixty-four cord blood metabolites detected by nuclear magnetic resonance spectroscopy were analyzed by linear mixed model analyses. The false discovery rate procedure was used to correct for multiple testing.

RESULTS

Among mothers with hypercholesterolemia, maternal and newborn plasma high-density lipoprotein cholesterol, apolipoprotein A1, linoleic acid, docosahexaenoic acid, alanine, glutamine, isoleucine, leucine, valine, creatinine, and particle concentration of medium high-density lipoprotein were significantly positively associated (0.001 ≤ q ≤ 0.09). Among mothers without hypercholesterolemia, maternal and newborn linoleic acid, valine, tyrosine, citrate, creatinine, high-density lipoprotein size, and particle concentration of small high-density lipoprotein were significantly positively associated (0.02 ≤ q ≤ 0.08). Among fathers with hypercholesterolemia, paternal and newborn ratio of apolipoprotein B to apolipoprotein A1 were significantly positively associated (q = 0.04). Among fathers without hypercholesterolemia, no significant associations were found between paternal and newborn metabolites. Sex differences were found for many cord blood lipids.

CONCLUSIONS

Maternal and paternal metabolites and newborn sex were associated with several cord blood metabolites. This may potentially affect the offspring's long-term cardiovascular disease risk.

Per-Particle Triglyceride-Rich Lipoproteins Imply Higher Myocardial Infarction Risk Than Low-Density Lipoproteins: Copenhagen General Population Study

[Figure: see text].

Serum Metabolomic Signatures Can Predict Subclinical Atherosclerosis in Patients With Systemic Lupus Erythematosus

[Figure: see text].

The maternal serum metabolome by multisegment injection-capillary electrophoresis-mass spectrometry: a high-throughput platform and standardized data workflow for large-scale epidemiological studies

A standardized data workflow is described for large-scale serum metabolomic studies using multisegment injection-capillary electrophoresis-mass spectrometry. Multiplexed separations increase throughput (<4 min/sample) for quantitative determination of 66 polar/ionic metabolites in serum filtrates consistently detected (coefficient of variance (CV) <30%) with high frequency (>75%) from a multi-ethnic cohort of pregnant women (n = 1,004). We outline a validated protocol implemented in four batches over a 7-month period that includes details on preventive maintenance, sample workup, data preprocessing and metabolite authentication. We achieve stringent quality control (QC) and robust batch correction of long-term signal drift with good mutual agreement for a wide range of metabolites, including serum glucose as compared to a clinical chemistry analyzer (mean bias = 11%, n = 668). Control charts for a recovery standard (mean CV = 12%, n = 2,412) and serum metabolites in QC samples (median CV = 13%, n = 202) demonstrate acceptable intermediate precision with a median intraclass coefficient of 0.87. We also report reference intervals for 53 serum metabolites from a diverse population of women in their second trimester of pregnancy.

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

VLDL Cholesterol Accounts for One-Half of the Risk of Myocardial Infarction Associated With apoB-Containing Lipoproteins

BACKGROUND

Plasma apolipoprotein B (apoB) is a composite measure of all apoB-containing lipoproteins causing atherosclerotic cardiovascular disease; however, it is unclear which fraction of risk is explained by cholesterol and triglycerides, respectively, in very low-density lipoproteins (VLDLs).

OBJECTIVES

The authors tested the hypothesis that VLDL cholesterol and triglycerides each explain part of the myocardial infarction risk from apoB-containing lipoproteins.

METHODS

Nested within 109,751 individuals from the Copenhagen General Population Study, the authors examined 25,480 subjects free of lipid-lowering therapy and myocardial infarction at study entry. All had measurements of plasma apoB (quantitating number of apoB-containing lipoproteins) and cholesterol and triglyceride content of VLDL, intermediate-density lipoproteins (IDLs), and low-density lipoproteins (LDLs).

RESULTS

During a median 11 years of follow-up, 1,816 were diagnosed with myocardial infarction. Per 1-mmol/l higher levels, multivariable-adjusted hazard ratios for myocardial infarction were 2.07 (95% confidence interval [CI]: 1.81 to 2.36) for VLDL cholesterol, 1.19 (95% CI: 1.14 to 1.25) for VLDL triglycerides, 5.38 (95% CI: 3.73 to 7.75) for IDL cholesterol, and 1.86 (95% CI: 1.62 to 2.14) for LDL cholesterol. Per 1-g/l higher plasma apoB, the corresponding value was 2.21 (95% CI: 1.90 to 2.58). In a step-up Cox regression, risk factors for myocardial infarction entered by importance as VLDL cholesterol, systolic blood pressure, smoking, and IDL + LDL cholesterol, whereas VLDL triglycerides did not enter the model. VLDL cholesterol explained 50% and IDL + LDL cholesterol 29% of the risk of myocardial infarction from apoB-containing lipoproteins, whereas VLDL triglycerides did not explain risk.

CONCLUSIONS

VLDL cholesterol explained one-half of the myocardial infarction risk from elevated apoB-containing lipoproteins, whereas VLDL triglycerides did not explain risk.

Palmitic acid-rich oils with and without interesterification lower postprandial lipemia and increase atherogenic lipoproteins compared with a MUFA-rich oil: A randomized controlled trial

BACKGROUND

Interesterified (IE) fats are widely used in place of trans fats; however, little is known about their metabolism.

OBJECTIVES

To test the impact of a commonly consumed IE compared with a non-IE equivalent fat on in vivo postprandial and in vitro lipid metabolism, compared with a reference oil [rapeseed oil (RO)].

METHODS

A double-blinded, 3-phase crossover, randomized controlled trial was performed in healthy adults (n = 20) aged 45-75 y. Postprandial plasma triacylglycerol and lipoprotein responses (including stable isotope tracing) to a test meal (50 g fat) were evaluated over 8 h. The test fats were IE 80:20 palm stearin/palm kernel fat, an identical non-IE fat, and RO (control). In vitro, mechanisms of digestion were explored using a dynamic gastric model (DGM).

RESULTS

Plasma triacylglycerol 8-h incremental area under the curves were lower following non-IE compared with RO [-1.7 mmol/L⋅h (95% CI: -3.3, -0.0)], but there were no differences between IE and RO or IE and non-IE. LDL particles were smaller following IE and non-IE compared with RO (P = 0.005). Extra extra large, extra large, and large VLDL particle concentrations were higher following IE and non-IE compared with RO at 6-8 h (P < 0.05). No differences in the appearance of [13C]palmitic acid in plasma triacylglycerol were observed between IE and non-IE fats. DGM revealed differences in phase separation of the IE and non-IE meals and delayed release of SFAs compared with RO.

CONCLUSIONS

Interesterification did not modify fat digestion, postprandial lipemia, or lipid metabolism measured by stable isotope and DGM analysis. Despite the lower lipemia following the SFA-rich fats, increased proatherogenic large triacylglycerol-rich lipoprotein remnant and small LDL particles following the SFA-rich fats relative to RO adds a new postprandial dimension to the mechanistic evidence linking SFAs to cardiovascular disease risk.

C3 and alternative pathway components are associated with an adverse lipoprotein subclass profile: The CODAM study

BACKGROUND

Plasma lipoproteins contain heterogeneous subclasses. Previous studies on the associations of the complement system with lipids and lipoproteins are mainly limited to the major lipid classes, and associations of complement with lipoprotein subclass characteristics remain unknown.

OBJECTIVE

We investigated the associations of C3 and other components of the alternative complement pathway with plasma lipoprotein subclass profile.

METHODS

Plasma complement concentrations (complement component 3 [C3], properdin, factor H, factor D, MASP-3, C3a, Bb), and lipoprotein subclass profile (as measured by nuclear magnetic resonance spectroscopy) were obtained in 523 participants (59.6 ± 6.9 years, 60.8% men) of the Cohort on Diabetes and Atherosclerosis Maastricht (CODAM) study. Multiple linear regression was used to investigate the associations of C3 (primary determinant) and other alternative pathway components (secondary determinants) with characteristics (particle concentration and size [main outcomes], and lipid contents [secondary outcomes]) of 14 lipoprotein subclasses, ranging from extremely large VLDL to small HDL (all standardized [std] values).

RESULTS

Participants with higher C3 concentrations had more circulating VLDL (stdβs ranging from 0.27 to 0.36), IDL and LDL (stdβs ranging from 0.14 to 0.17), and small HDL (stdβ = 0.21). In contrast, they had fewer very large and large HDL particles (stdβs = -0.36). In persons with higher C3 concentrations, all lipoprotein subclasses were enriched in triglycerides. Similar but weaker associations were observed for properdin, factor H, factor D, and MASP-3, but not for C3a and Bb.

CONCLUSIONS

The alternative complement pathway, and most prominently C3, is associated with an adverse lipoprotein subclass profile that is characterized by more triglyceride-enriched lipoproteins but fewer large HDL.

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.

NMR Metabolite Profiles in Male Meat-Eaters, Fish-Eaters, Vegetarians and Vegans, and Comparison with MS Metabolite Profiles

Metabolomics may help to elucidate mechanisms underlying diet-disease relationships and identify novel risk factors for disease. To inform the design and interpretation of such research, evidence on diet-metabolite associations and cross-assay comparisons is needed. We aimed to compare nuclear magnetic resonance (NMR) metabolite profiles between meat-eaters, fish-eaters, vegetarians and vegans, and to compare NMR measurements to those from mass spectrometry (MS), clinical chemistry and capillary gas-liquid chromatography (GC). We quantified 207 serum NMR metabolite measures in 286 male participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Oxford cohort. Using univariate and multivariate analyses, we found that metabolite profiles varied by diet group, especially for vegans; the main differences compared to meat-eaters were lower levels of docosahexaenoic acid, total n-3 and saturated fatty acids, cholesterol and triglycerides in very-low-density lipoproteins, various lipid factions in high-density lipoprotein, sphingomyelins, tyrosine and creatinine, and higher levels of linoleic acid, total n-6, polyunsaturated fatty acids and alanine. Levels in fish-eaters and vegetarians differed by metabolite measure. Concentrations of 13 metabolites measured using both NMR and MS, clinical chemistry or GC were mostly similar. In summary, vegans' metabolite profiles were markedly different to those of men consuming animal products. The studied metabolomics platforms are complementary, with limited overlap between metabolite classes.

Evaluation of Fumaric Acid and Maleic Acid as Internal Standards for NMR Analysis of Protein Precipitated Plasma, Serum, and Whole Blood

Significant advances have been made in unknown metabolite identification and expansion of the number of quantifiable metabolites in human plasma, serum, and whole blood using NMR spectroscopy. However, reliable quantitation of metabolites is still a challenge. A major bottleneck is the lack of a suitable internal standard that does not interact with the complex blood sample matrix and also does not overlap with metabolite peaks apart from exhibiting other favorable characteristics. With the goal of addressing this challenge, a comprehensive investigation of fumaric and maleic acids as potential internal standards was made along with a comparison with the conventional standards, TSP (trimethylsilylpropionic acid) and DSS (trimethylsilylpropanesulfonic acid). Both fumaric acid and maleic acid exhibited a surprisingly high performance with a quantitation error <1%, while the TSP and DSS caused an average error of up to 35% in plasma, serum, and whole blood. Further, the results indicate that while fumaric acid is a robust standard for all three biospecimens, maleic acid is suitable for only plasma and serum. Maleic acid is not suited for the analysis of whole blood due to its overlap with coenzyme peaks. These findings provide new opportunities for improved and accurate quantitation of metabolites in human plasma, serum, and whole blood using NMR spectroscopy. Moreover, the use of protein precipitation prior to NMR analysis mirrors the sample preparation commonly used for mass spectrometry based metabolomics, such that these findings further strengthen efforts to combine and compare NMR and MS based metabolite data of human plasma, serum, and whole blood for metabolomics based research.

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.

Discovery of predictors of sudden cardiac arrest in diabetes: rationale and outline of the RESCUED (REcognition of Sudden Cardiac arrest vUlnErability in Diabetes) project

Introduction

Early recognition of individuals with increased risk of sudden cardiac arrest (SCA) remains challenging. SCA research so far has used data from cardiologist care, but missed most SCA victims, since they were only in general practitioner (GP) care prior to SCA. Studying individuals with type 2 diabetes (T2D) in GP care may help solve this problem, as they have increased risk for SCA, and rich clinical datasets, since they regularly visit their GP for check-up measurements. This information can be further enriched with extensive genetic and metabolic information.

Aim

To describe the study protocol of the REcognition of Sudden Cardiac arrest vUlnErability in Diabetes (RESCUED) project, which aims at identifying clinical, genetic and metabolic factors contributing to SCA risk in individuals with T2D, and to develop a prognostic model for the risk of SCA.

Methods

The RESCUED project combines data from dedicated SCA and T2D cohorts, and GP data, from the same region in the Netherlands. Clinical data, genetic data (common and rare variant analysis) and metabolic data (metabolomics) will be analysed (using classical analysis techniques and machine learning methods) and combined into a prognostic model for risk of SCA.

Conclusion

The RESCUED project is designed to increase our ability at early recognition of elevated SCA risk through an innovative strategy of focusing on GP data and a multidimensional methodology including clinical, genetic and metabolic analyses.

An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease

Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights.