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

NMR metabolomic modelling of age and lifespan: a multi-cohort analysis

Metabolomic age models have been proposed for the study of biological aging, however they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. 98 metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈ 31,000 individuals, age range 24-86 years). We used non-linear and penalised regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with ageing risk factors and phenotypes. Within the UK Biobank (N≈ 102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, chronic obstructive pulmonary disease) and all-cause mortality. Cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47-0.65 in the training set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with chronological age were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06 / metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

Associations of lipoprotein subclasses with risk of all-cause and cardiovascular disease mortality in individuals with type 2 diabetes: A prospective cohort study

AIM

Although lipoproteins are well-established risk factors for cardiovascular disease (CVD) mortality, conventional measurements failed to identify lipoprotein particle sizes. This study aimed to investigate associations of lipoprotein subclasses categorized by particle sizes with risk of all-cause and CVD mortality in individuals with type 2 diabetes.

METHODS

This study included 6575 individuals with type 2 diabetes from the UK Biobank. Concentrations of very low-, low-, intermediate- and high-density lipoprotein [very-low-density lipoprotein (VLDL), low-density lipoprotein (LDL), intermediate-density lipoprotein and high-density lipoprotein (HDL)] particles in 14 subclasses and lipid constituents within each subclass were measured by quantitative nuclear magnetic resonance. Multivariable-adjusted Cox proportional-hazard regression models were used to estimate the hazard ratio (HR) for per standard deviation increment of log-transformed lipoprotein subclasses with risk of mortality. All p-values were adjusted by the false discovery rate method.

RESULTS

During a median follow-up of 11.4 years, 943 deaths were documented, including 310 CVD deaths. Small HDL particles were inversely associated with CVD mortality, with HR (95% CI) of 0.78 (0.69, 0.87), whereas very large and large HDL particles were positively associated with CVD mortality with HR (95% CI) of 1.28 (1.12, 1.45) and 1.19 (1.05, 1.35), respectively. A similar pattern was observed for all-cause mortality [small HDL particle (HR, 95% CI): 0.79, 0.74-0.85; large HDL particle: 1.15, 1.07-1.24; very large HDL particle: 1.26, 1.17-1.36]. For VLDL and LDL, very small VLDL particle was positively, while medium LDL particle was inversely associated with all-cause mortality, but not associated with CVD mortality. The pattern of association with all-cause and CVD mortality for cholesterol and triglyceride within lipoprotein particles was similar to those for lipoprotein particles themselves.

CONCLUSIONS

The associations between lipoprotein particles, particularly HDL particles, with all-cause and CVD mortality among patients with type 2 diabetes were significantly varied by particle sizes, highlighting the importance of particle size as a lipoprotein metric in mortality risk discrimination.

Postprandial glycemic and lipidemic effects of black rice anthocyanin extract fortification in foods of varying macronutrient compositions and matrices

Anthocyanin (ACN) fortification of commonly consumed foods is significant as a dietary strategy against the development of metabolic complications by delivering ACNs at high doses. However, its bioactivity and translated metabolic effects in the presence of varying food matrices and macro-constituents is particularly unclear. This end-to-end study investigates the metabolic effects of black rice ACN extract (BRAE) fortification-from in-vitro enzyme inhibitory activities and digestibility, to downstream in vivo impacts on GI, postprandial glycemia and lipidemia. The in vivo effects were investigated in two separate crossover randomised controlled trials (RCT) of 24 healthy participants each-the first RCT determined the postprandial blood glucose, insulin, and ACN bioavailability to a starch-rich single food over 2 h, while the second RCT determined the postprandial blood glucose, insulin, lipid panel, and lipoprotein particles and subfractions to a starch- and fat-rich composite meal over 4 h. In-vitro findings confirmed the inhibitory activities of major black rice ACNs on carbohydrases (p = 0.0004), lipases (p = 0.0002), and starch digestibility (p < 0.0001). in vivo, a 27-point mean GI reduction of wheat bread was observed with BRAE fortification, despite a non-significant attenuation in postprandial glycemia. Conversely, there were no differences in postprandial glycemia when fortified bread was consumed as a composite meal, but acute lipid profiles were altered: (1) improved plasma HDL-c, ([0.0140 mmol/L, 95% CI: (0.00639, 0.0216)], p = 0.0028), Apo-A1 ([0.0296 mmol/L, 95% CI: (0.00757, 0.0515)], p = 0.0203), and Apo-B ([0.00880 mmol/L, 95% CI: (0.00243, 0.0152)], p = 0.0185), (2) modified LDL and HDL subfractions (p < 0.05), and (3) remodelled lipid distributions in HDL and LDL particles. This end-to-end study indicates the potential of ACN fortification in GI reduction and modulating postprandial lipoprotein profiles to starch- and fat-rich composite meals.

Early ascending growth is associated with maternal lipoprotein profile during mid and late pregnancy and in cord blood

INTRODUCTION

Intrauterine conditions and accelerating early growth are associated with childhood obesity. It is unknown, whether fetal programming affects the early growth and could alterations in the maternal-fetal metabolome be the mediating mechanism. Therefore, we aimed to assess the associations between maternal and cord blood metabolite profile and offspring early growth.

METHODS

The RADIEL study recruited 724 women at high risk for gestational diabetes mellitus (GDM) BMI ≥ 30 kg/m2 and/or prior GDM) before or in early pregnancy. Blood samples were collected once in each trimester, and from cord. Metabolomics were analyzed by targeted nuclear magnetic resonance (NMR) technique. Following up on offsprings' first 2 years growth, we discovered 3 distinct growth profiles (ascending n = 80, intermediate n = 346, and descending n = 146) by using latent class mixed models (lcmm).

RESULTS

From the cohort of mother-child dyads with available growth profile data (n = 572), we have metabolomic data from 232 mothers from 1st trimester, 271 from 2nd trimester, 277 from 3rd trimester and 345 from cord blood. We have data on 220 metabolites in each trimester and 70 from cord blood. In each trimester of pregnancy, the mothers of the ascending group showed higher levels of VLDL and LDL particles, and lower levels of HDL particles (p < 0.05). When adjusted for gestational age, birth weight, sex, delivery mode, and maternal smoking, there was an association with ascending profile and 2nd trimester total cholesterol in HDL2, 3rd trimester total cholesterol in HDL2 and in HDL, VLDL size and ratio of triglycerides to phosphoglycerides (TG/PG ratio) in cord blood (p ≤ 0.002).

CONCLUSION

Ascending early growth was associated with lower maternal total cholesterol in HDL in 2nd and 3rd trimester, and higher VLDL size and more adverse TG/PG ratio in cord blood.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, http://www.

CLINICALTRIALS

com , NCT01698385.

Assessing the safety of lipid-modifying medications among Chinese adolescents: a drug-target Mendelian randomization study

BACKGROUND

With increasing hypercholesterolemia prevalence in East Asian adolescents, pharmacologic interventions (e.g., HMGCR inhibitors (statins) and PCSK9 inhibitors) may have to be considered although their longer-term safety in the general adolescent population is unclear. This study aims to investigate the longer-term safety of HMGCR inhibitors and PCSK9 inhibitors among East Asian adolescents using genetics.

METHODS

A drug-target Mendelian randomization study leveraging the Global Lipid Genetics Consortium (East Asian, n = 146,492) and individual-level data from Chinese participants in the Biobank clinical follow-up of Hong Kong's "Children of 1997" birth cohort (n = 3443, aged ~ 17.6 years). Safety outcomes (n = 100) included anthropometric and hematological traits, renal, liver, lung function, and other nuclear magnetic resonance metabolomics. Positive control outcomes were cholesterol markers from the "Children of 1997" birth cohort and coronary artery disease from Biobank Japan.

RESULTS

Genetic inhibition of HMGCR and PCSK9 were associated with reduction in cholesterol-related NMR metabolomics, e.g., apolipoprotein B (HMGCR: beta [95% CI], - 1.06 [- 1.52 to - 0.60]; PCSK9: - 0.93 [- 1.56 to - 0.31]) and had the expected effect on the positive control outcomes. After correcting for multiple comparisons (p-value < 0.006), genetic inhibition of HMGCR was associated with lower linoleic acid - 0.79 [- 1.25 to - 0.35]. Genetic inhibition of PCSK9 was not associated with the safety outcomes assessed.

CONCLUSIONS

Statins and PCSK9 inhibitors in East Asian adolescents appeared to be safe based on the outcomes concerned. Larger studies were warranted to verify these findings. This study serves as a proof of principle study to inform the medication safety among adolescents via genetics.

Metabolic fingerprinting on retinal pigment epithelium thickness for individualized risk stratification of type 2 diabetes mellitus

The retina is an important target organ of diabetes mellitus, with increasing evidence from patients and animal models suggesting that retinal pigment epithelium (RPE) may serve as an early marker for diabetes-related damages. However, their longitudinal relationship and the biological underpinnings remain less well understood. Here, we demonstrate that reduced in vivo measurements of RPE thickness (RPET) represents a significant risk factor for future type 2 diabetes mellitus (T2DM) and its microvascular phenotypes. After performing systematic analyses of circulating plasma metabolites using two complementary approaches, we identify a wide range of RPET metabolic fingerprints that are independently associated with reduced RPET. These fingerprints hold their potential to improve predictability and clinical utility for stratifying future T2DM and related microvascular phenotypes beyond traditional clinical indicators, providing insights into the promising role of retinas as a window to systemic health.

Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids

BACKGROUND

Metabolic differences have been reported between individuals with and without major depressive disorder (MDD), but their consistency and causal relevance have been unclear.

METHODS

We conducted a metabolome-wide association study of MDD with 249 metabolomic measures available in the UK Biobank (n = 29,757). We then applied two-sample bidirectional Mendelian randomization and colocalization analysis to identify potentially causal relationships between each metabolite and MDD.

RESULTS

A total of 191 metabolites tested were significantly associated with MDD (false discovery rate-corrected p < .05), which decreased to 129 after adjustment for likely confounders. Lower abundance of omega-3 fatty acid measures and a higher omega-6 to omega-3 ratio showed potentially causal effects on liability to MDD. There was no evidence of a causal effect of MDD on metabolite levels. Furthermore, genetic signals associated with docosahexaenoic acid colocalized with loci associated with MDD within the fatty acid desaturase gene cluster. Post hoc Mendelian randomization of gene-transcript abundance within the fatty acid desaturase cluster demonstrated a potentially causal association with MDD. In contrast, colocalization analysis did not suggest a single causal variant for both transcript abundance and MDD liability, but rather the likely existence of two variants in linkage disequilibrium with one another.

CONCLUSIONS

Our findings suggest that decreased docosahexaenoic acid and increased omega-6 to omega-3 fatty acids ratio may be causally related to MDD. These findings provide further support for the causal involvement of fatty acids in MDD.

From plasma triglycerides to triglyceride metabolism: effects on mortality in the Copenhagen General Population Study

AIMS

It is unclear whether higher triglyceride metabolism per se contributes to mortality separate from elevated triglyceride-rich lipoproteins and body mass index. This study tested the hypotheses that higher triglyceride metabolism, measured as higher plasma glycerol and β-hydroxybutyrate, is associated with increased all-cause, cardiovascular, cancer, and other mortality.

METHODS AND RESULTS

This study included 30 000 individuals nested within 109 751 individuals from the Copenhagen General Population Study. During a median follow-up of 10.7 years, 9897 individuals died (2204 from cardiovascular, 3366 from cancer, and 2745 from other causes), while none were lost to follow-up. In individuals with glycerol >80 µmol/L (highest fourth) vs. individuals with glycerol <52 µmol/L (lowest fourth), the multivariable adjusted hazard ratio for all-cause mortality was 1.31 (95% confidence interval 1.22-1.40). In individuals with β-hydroxybutyrate >154 µmol/L (highest fourth) vs. individuals with β-hydroxybutyrate <91 µmol/L (lowest fourth), the multivariable adjusted hazard ratio for all-cause mortality was 1.18 (1.11-1.26). Corresponding values for higher plasma glycerol and β-hydroxybutyrate were 1.37 (1.18-1.59) and 1.18 (1.03-1.35) for cardiovascular mortality, 1.24 (1.11-1.39) and 1.16 (1.05-1.29) for cancer mortality, and 1.45 (1.28-1.66) and 1.23 (1.09-1.39) for other mortality, respectively. Results were robust to exclusion of first years of follow-up, to stratification for covariates including plasma triglycerides and body mass index, and to further adjustments.

CONCLUSION

This study observed an increased risk of all-cause, cardiovascular, cancer, and other mortality with higher triglyceride metabolism. This was not explained by higher plasma triglycerides and body mass index. The hypothesis studied in the present paper should be further validated by isotope flux studies.

Low levels of small HDL particles predict but do not influence risk of sepsis

BACKGROUND

Low levels of high-density lipoprotein (HDL) cholesterol have been associated with higher rates and severity of infection. Alterations in inflammatory mediators and infection are associated with alterations in HDL cholesterol. It is unknown whether the association between HDL and infection is present for all particle sizes, and whether the observed associations are confounded by IL-6 signalling.

METHODS

In the UK Biobank, ~ 270,000 individuals have data on HDL subclasses derived from nuclear magnetic resonance analysis. We estimated the association of particle count of total HDL and HDL subclasses (small, medium, large, and extra-large HDL) with sepsis, sepsis-related death, and critical care admission in a Cox regression model. We subsequently utilised genetic data from UK Biobank and FinnGen to perform Mendelian randomisation (MR) of each HDL subclass and sepsis to test for a causal relationship. Finally, we explored the role of IL-6 signalling as a potential causal driver of changes in HDL subclasses.

RESULTS

In observational analyses, higher particle count of small HDL was associated with protection from sepsis (Hazard ratio, HR 0.80; 95% CI 0.74-0.86, p = 4 × 10-9 comparing Quartile 4, highest quartile of HDL to Quartile 1, lowest quartile of HDL), sepsis-related death (HR 0.80; 95% CI 0.74-0.86, p = 2 × 10-4), and critical care admission with sepsis (HR 0.72 95% CI 0.60-0.85, p = 2 × 10-4). Parallel associations with other HDL subclasses were likely driven by changes in the small HDL compartment. MR analyses did not strongly support causality of small HDL particle count on sepsis incidence (Odds ratio, OR 0.98; 95% CI 0.89-1.07, p = 0.6) or death (OR 0.94, 95% CI 0.75-1.17, p = 0.56), although the estimate on critical care admission with sepsis supported protection (OR 0.73, 95% CI 0.57-0.95, p = 0.02). Bidirectional MR analyses suggested that increased IL-6 signalling was associated with reductions in both small (beta on small HDL particle count - 0.16, 95% CI - 0.10 to - 0.21 per natural log change in SD-scaled CRP, p = 9 × 10-8).and total HDL particle count (beta - 0.13, 95% CI - 0.09 to - 0.17, p = 7 × 10-10), but that the reverse effect of HDL on IL-6 signalling was largely null.

CONCLUSIONS

Low number of small HDL particles are associated with increased hazard of sepsis, sepsis-related death, and sepsis-related critical care admission. However, genetic analyses did not strongly support this as causal. Instead, we demonstrate that increased IL-6 signalling, which is known to alter infection risk, could confound associations with reduced HDL particle count, and suggest this may explain part of the observed association between (small) HDL particle count and sepsis.

Prospective Association Between Plasma Concentrations of Fatty Acids and Other Lipids, and Multimorbidity in Older Adults

Biological mechanisms that lead to multimorbidity are mostly unknown, and metabolomic profiles are promising to explain different pathways in the aging process. The aim of this study was to assess the prospective association between plasma fatty acids and other lipids, and multimorbidity in older adults. Data were obtained from the Spanish Seniors-ENRICA 2 cohort, comprising noninstitutionalized adults ≥65 years old. Blood samples were obtained at baseline and after a 2-year follow-up period for a total of 1 488 subjects. Morbidity was also collected at baseline and end of the follow-up from electronic health records. Multimorbidity was defined as a quantitative score, after weighting morbidities (from a list of 60 mutually exclusive chronic conditions) by their regression coefficients on physical functioning. Generalized estimating equation models were employed to assess the longitudinal association between fatty acids and other lipids, and multimorbidity, and stratified analyses by diet quality, measured with the Alternative Healthy Eating Index-2010, were also conducted. Among study participants, higher concentrations of omega-6 fatty acids [coef. per 1-SD increase (95% CI) = -0.76 (-1.23, -0.30)], phosphoglycerides [-1.26 (-1.77, -0.74)], total cholines [-1.48 (-1.99, -0.96)], phosphatidylcholines [-1.23 (-1.74, -0.71)], and sphingomyelins [-1.65 (-2.12, -1.18)], were associated with lower multimorbidity scores. The strongest associations were observed for those with a higher diet quality. Higher plasma concentrations of omega-6 fatty acids, phosphoglycerides, total cholines, phosphatidylcholines, and sphingomyelins were prospectively associated with lower multimorbidity in older adults, although diet quality could modulate the associations found. These lipids may serve as risk markers for multimorbidity.

Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Biological age captures a person's age-related risk of unfavorable outcomes using biophysiological information. Multivariate biological age measures include frailty scores and molecular biomarkers. These measures are often studied in isolation, but here we present a large-scale study comparing them. In 2 prospective cohorts (n = 3 222), we compared epigenetic (DNAm Horvath, DNAm Hannum, DNAm Lin, DNAm epiTOC, DNAm PhenoAge, DNAm DunedinPoAm, DNAm GrimAge, and DNAm Zhang) and metabolomic-based (MetaboAge and MetaboHealth) biomarkers in reflection of biological age, as represented by 5 frailty measures and overall mortality. Biomarkers trained on outcomes with biophysiological and/or mortality information outperformed age-trained biomarkers in frailty reflection and mortality prediction. DNAm GrimAge and MetaboHealth, trained on mortality, showed the strongest association with these outcomes. The associations of DNAm GrimAge and MetaboHealth with frailty and mortality were independent of each other and of the frailty score mimicking clinical geriatric assessment. Epigenetic, metabolomic, and clinical biological age markers seem to capture different aspects of aging. These findings suggest that mortality-trained molecular markers may provide novel phenotype reflecting biological age and strengthen current clinical geriatric health and well-being assessment.

Triglyceride content increases while cholesterol content decreases in HDL and LDL+IDL fractions following normal meals: The Copenhagen General Population Study of 25,656 individuals

BACKGROUND AND AIMS

During fat tolerance tests, plasma triglycerides increase while high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and intermediate-density lipoprotein (IDL) cholesterol decrease. However, it is unknown whether triglyceride content increases and cholesterol content decreases in HDL and LDL + IDL fractions following normal meals in the general population. Therefore, we tested the hypothesis that triglyceride content increases while cholesterol content decreases in HDL and LDL + IDL fractions following normal meals.

METHODS

In this cross-sectional study, we included 25,656 individuals aged 20-100 years, all without lipid-lowering therapy at examination and selected for metabolomic profiling from the Copenhagen General Population Study. Triglyceride and cholesterol content of 14 lipoprotein fractions weas measured using nuclear magnetic resonance (NMR) spectroscopy. Time since last meal was recorded by the examiner immediately before blood sampling.

RESULTS

Following normal meals in age and sex-adjusted analyses and when compared with fasting levels, plasma triglycerides were higher for up to 5-6 h, and triglyceride content was higher for up to 6-7 h in HDL fractions, for up to 6-7 h in LDL + IDL fractions, and for up to 5-6 h in very-low-density lipoprotein (VLDL) fractions. Further, plasma cholesterol was lower for up to 2-3 h, and cholesterol content was lower for up to 0-1 h in HDL fractions and for up to 4-5 h in LDL + IDL fractions, while cholesterol content was higher for up to 4-5 h in VLDL fractions.

CONCLUSIONS

Following normal meals, triglyceride content increases while cholesterol content decreases in HDL and LDL + IDL fractions.

bubbleHeatmap: an R package for visualization of nightingale health metabolomics datasets

Summary

We present bubbleHeatmap, an R plotting package which combines elements of a bubble plot and heatmap to conveniently display two numerical variables for each data point across a categorical two dimensional grid. This has particular advantages for visualizing the 251 metabolomic measures produced by the automated, high-throughput, 1H-NMR-based platform provided by Nightingale Health, which includes 12 measures repeated across each of 14 lipoprotein subclasses. As these metabolomic profiles are currently available for large biobanks, we provide a figure template to aid the use of bubbleHeatmap in displaying results from analyses using these data.

Availability and implementation

https://cran.r-project.org/web/packages/bubbleHeatmap.

Combining serum metabolomic profiles with traditional risk factors improves 10-year cardiovascular risk prediction in people with type 2 diabetes

AIMS

To identify a group of metabolites associated with incident cardiovascular disease (CVD) in people with type 2 diabetes and assess its predictive performance over-and-above a current CVD risk score (QRISK3).

METHODS AND RESULTS

A panel of 228 serum metabolites was measured at baseline in 1066 individuals with type 2 diabetes (Edinburgh Type 2 Diabetes Study) who were then followed up for CVD over the subsequent 10 years. We applied 100 repeats of Cox least absolute shrinkage and selection operator to select metabolites with frequency >90% as components for a metabolites-based risk score (MRS). The predictive performance of the MRS was assessed in relation to a reference model that was based on QRISK3 plus prevalent CVD and statin use at baseline. Of 1021 available individuals, 255 (25.0%) developed CVD (median follow-up: 10.6 years). Twelve metabolites relating to fluid balance, ketone bodies, amino acids, fatty acids, glycolysis, and lipoproteins were selected to construct the MRS that showed positive association with 10-year cardiovascular risk following adjustment for traditional risk factors [hazard ratio (HR) 2.67; 95% confidence interval (CI) 1.96, 3.64]. The c-statistic was 0.709 (95%CI 0.679, 0.739) for the reference model alone, increasing slightly to 0.728 (95%CI 0.700, 0.757) following addition of the MRS. Compared with the reference model, the net reclassification index and integrated discrimination index for the reference model plus the MRS were 0.362 (95%CI 0.179, 0.506) and 0.041 (95%CI 0.020, 0.071), respectively.

CONCLUSION

Metabolomics data might improve predictive performance of current CVD risk scores based on traditional risk factors in people with type 2 diabetes. External validation is warranted to assess the generalizability of improved CVD risk prediction using the MRS.

Machine learning identifying peripheral circulating metabolites associated with intraocular pressure alterations

AIMS

To identify blood metabolite markers associated with intraocular pressure (IOP) in a population-based cross-sectional study.

METHODS

This study was conducted in a multiethnic Asian population (Chinese, n=2805; Indians, n=3045; Malays, n=3041 aged 40-80 years) in Singapore. All subjects underwent standardised systemic and ocular examinations, and biosamples were collected. Selected metabolites (n=228) in either serum or plasma were analysed and quantified using nuclear magnetic resonance spectroscopy. Least absolute shrinkage and selection operator regression was used for metabolites selection. Multivariable linear regression was used to evaluate the relationship between metabolites and IOP in each of the three ethnic groups, followed by a meta-analysis combining the three cohorts.

RESULTS

Six metabolites, including albumin, glucose, lactate, glutamine, ratio of saturated fatty acids to total fatty acids (SFAFA) and cholesterol esters in very large high-density lipoprotein (HDL), were significantly associated with IOP in all three cohorts. Higher levels of albumin (per SD, beta=0.24, p=0.002), lactate (per SD, beta=0.27, p=0.008), glucose (per SD, beta=0.11, p=0.010) and cholesterol esters in very large HDL (per SD, beta=0.47, p=0.006), along with lower levels of glutamine (per SD, beta=0.17, p<0.001) and SFAFA (per SD, beta=0.21, p=0.008) were associated with higher IOP levels.

CONCLUSION

We identify several novel blood metabolites associated with IOP. These findings may provide insight into the physiological and pathological processes underlying IOP control.

Integrating GWAS summary statistics, individual-level genotypic and omic data to enhance the performance for large-scale trait imputation

Recently, a non-parametric method has been proposed to impute the genetic component of a trait for a large set of genotyped individuals based on a separate genome-wide association study (GWAS) summary dataset of the same trait (from the same population). The imputed trait may contain linear, non-linear and epistatic effects of genetic variants, thus can be used for downstream linear or non-linear association analyses and machine learning tasks. Here, we propose an extension of the method to impute both genetic and environmental components of a trait using both single nucleotide polymorphism (SNP)-trait and omics-trait association summary data. We illustrate an application to a UK Biobank subset of individuals (n ≈ 80K) with both body mass index (BMI) GWAS data and metabolomic data. We divided the whole dataset into two equally sized and non-overlapping training and test datasets; we used the training data to build SNP- and metabolite-BMI association summary data and impute BMI on the test data. We compared the performance of the original and new imputation methods. As by the original method, the imputed BMI values by the new method largely retained SNP-BMI association information; however, the latter retained more information about BMI-environment associations and were more highly correlated with the original observed BMI values.

Glycoprotein acetyls and depression: Testing for directionality and potential causality using longitudinal data and Mendelian randomization analyses

BACKGROUND

Inflammation is associated with depression, but causality remains unclear. We investigated potential causality and direction of effect between inflammation and depression.

METHODS

Using data from the ALSPAC birth cohort (n = 4021; 42.18 % male), we used multivariable regression to investigate bidirectional longitudinal associations of GlycA and depression and depression symptoms, assessed at ages 18y and 24y. We used two-sample Mendelian randomization (MR) to investigate potential causality and directionality. Genetic variants for GlycA were obtained from UK Biobank (UKB) (N = 115,078); for depression from the Psychiatric Genomics Consortium and UKB (N = 500,199); and for depressive symptoms (N = 161,460) from the Social Science Genetic Association Consortium. In addition to the Inverse Variance Weighted method, we used sensitivity analyses to strengthen causal inference. We conducted multivariable MR adjusting for body mass index (BMI) due to known genetic correlation between inflammation, depression and BMI.

RESULTS

In the cohort analysis, after adjusting for potential confounders we found no evidence of associations between GlycA and depression symptoms score or vice versa. We observed an association between GlycA and depression (OR = 1∙18, 95 % CI: 1∙03-1∙36). MR suggested no causal effect of GlycA on depression, but there was a causal effect of depression on GlycA (mean difference in GlycA = 0∙09; 95 % CI: 0∙03-0∙16), which was maintained in some, but not all, sensitivity analyses.

LIMITATIONS

The GWAS sample overlap could incur bias.

CONCLUSION

We found no consistent evidence for an effect of GlycA on depression. There was evidence that depression increases GlycA in the MR analysis, but this may be confounded/mediated by BMI.

Increasing number of long-lived ancestors marks a decade of healthspan extension and healthier metabolomics profiles

Globally, the lifespan of populations increases but the healthspan is lagging behind. Previous research showed that survival into extreme ages (longevity) clusters in families as illustrated by the increasing lifespan of study participants with each additional long-lived family member. Here we investigate whether the healthspan in such families follows a similar quantitative pattern using three-generational data from two databases, LLS (Netherlands), and SEDD (Sweden). We study healthspan in 2143 families containing index persons with 26 follow-up years and two ancestral generations, comprising 17,539 persons. Our results provide strong evidence that an increasing number of long-lived ancestors associates with up to a decade of healthspan extension. Further evidence indicates that members of long-lived families have a delayed onset of medication use, multimorbidity and, in mid-life, healthier metabolomic profiles than their partners. We conclude that both lifespan and healthspan are quantitatively linked to ancestral longevity, making family data invaluable to identify protective mechanisms of multimorbidity.

Associations of circulating fatty acids with incident coronary heart disease: a prospective study of 89,242 individuals in UK Biobank

BACKGROUND

The role of fatty acids in coronary heart disease (CHD) remains uncertain. There is little evidence from large-scale epidemiological studies on the relevance of circulating fatty acids levels to CHD risk. This study aims to examine the independent associations of the major circulating types of fatty acids with CHD risk.

METHODS

UK Biobank is a prospective study of adults aged 40-69 in 2006-2010; in 2012-2013, a subset of the participants were resurveyed. Analyses were restricted to 89,242 participants with baseline plasma fatty acids (measured using nuclear magnetic resonance spectroscopy) and without prior CHD. Cox proportional hazards models were used to estimate hazard ratios (HRs) for the associations with incidence CHD, defined as the first-ever myocardial infarction, unstable angina pectoris, coronary-related death, or relevant procedure. And the major types of fatty acids were mutually adjusted to examine the independent associations. Hazard ratios were corrected for regression dilution using the correlation of baseline and resurvey fatty acids measures.

RESULTS

During a median follow-up of 11.8 years, 3,815 incident cases of CHD occurred. Independently of other fatty acids, CHD risk was positively associated with saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA), inversely associated with omega-3 polyunsaturated fatty acids (PUFA), but there was no strong evidence of an association with omega-6 PUFA: HR per standard deviation higher were 1.14 (95% CI, 1.09-1.20), 1.15 (1.10-1.21), 0.91 (0.87-0.94), and 1.04 (0.99-1.09) respectively. Independently of triglycerides and cholesterol, the inverse association with omega-3 PUFA was not materially changed, but the positive associations with SFA and MUFA attenuated to null after adjusting for triglycerides levels.

CONCLUSIONS

This large-scale study has quantitated the independent associations of circulating fatty acids with CHD risk. Omega-3 PUFA was inversely related to CHD risk, independently of other fatty acids and major lipid fractions. By contrast, independently of other fatty acids, the positive associations of circulating SFA and MUFA with CHD risk were mostly attributed to their relationship with triglycerides.

Cross-sectionally Calculated Metabolic Aging Does Not Relate to Longitudinal Metabolic Changes-Support for Stratified Aging Models

CONTEXT

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

OBJECTIVE

We applied novel methodology to test if cross-sectional modeling can distinguish slow vs accelerated aging in a human population.

METHODS

We trained a machine learning model to predict age from 153 clinical and cardiometabolic traits. The model was tested against longitudinal data from another cohort. The training data came from cross-sectional surveys of the Finnish population (n = 9708; ages 25-74 years). The validation data included 3 time points across 10 years in the Young Finns Study (YFS; n = 1009; ages 24-49 years). Predicted metabolic age in 2007 was compared against observed aging rate from the 2001 visit to the 2011 visit in the YFS dataset and correlation between predicted vs observed metabolic aging was determined.

RESULTS

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

CONCLUSION

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

Effects of Nightshift Work on Blood Metabolites in Female Nurses and Paramedic Staff: A Cross-sectional Study

Nightshift work disturbs the circadian rhythm, which might contribute to the development of cardio-metabolic disorders. In this cross-sectional study, we aimed to gain insight into perturbations of disease relevant metabolic pathways due to nightshift work. We characterized the metabolic profiles of 237 female nurses and paramedic staff participating in the Klokwerk study using the Nightingale Health platform. We performed analyses on plasma levels of 225 metabolites, including cholesterol, triglycerides, fatty acids, and amino acids. Using both principal component- and univariate-regression, we compared metabolic profiles of nightshift workers to metabolic profiles from workers that did not work night shifts (defined as day workers). We also assessed whether differential effects were observed between recently started versus more experienced workers. Within the group of nightshift workers, we compared metabolic profiles measured right after a nightshift with metabolic profiles measured on a day when no nightshift work was conducted. We observed evidence for an impact of nightshift work on the presence of unfavorable fatty acid profiles in blood. Amongst the fatty acids, effects were most prominent for PUFA/FA ratios (consistently decreased) and SFA/FA ratios (consistently elevated). This pattern of less favorable fatty acid profiles was also observed in samples collected directly after a night shift. Amino acid levels (histidine, glutamine, isoleucine, and leucine) and lipoproteins (especially HDL-cholesterol, VLDL-cholesterol, and triglycerides) were elevated when comparing nightshift workers with day workers. Amino acid levels were decreased in the samples that were collected directly after working a nightshift (compared to levels in samples that were collected during a non-nightshift period). The observed effects were generally more pronounced in samples collected directly after the nightshift and among recently started compared to more experienced nightshift workers. Our finding of a suggested impact of shift work on impaired lipid metabolism is in line with evidence that links disruption of circadian rhythmicity to obesity and metabolic disorders.

Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins

Background

The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remain underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers.

Methods

Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N=651) and the Netherlands Twin Register (NTR) (N=665). Follow-up comprised four BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated using latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. The sources of genetic and environmental variation underlying the protein abundances were quantified using twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) using mixed-effect models and correlation networks.

Results

We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 6 and 4 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with many metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers.

Conclusions

Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

The Effect of Carbohydrate Restriction on Lipids, Lipoproteins, and Nuclear Magnetic Resonance-Based Metabolites: CALIBER, a Randomised Parallel Trial

Low-carbohydrate high-fat (LCHF) diets can be just as effective as high-carbohydrate, lower-fat (HCLF) diets for improving cardiovascular disease risk markers. Few studies have compared the effects of the UK HCLF dietary guidelines with an LCHF diet on lipids and lipoprotein metabolism using high-throughput NMR spectroscopy. This study aimed to explore the effect of an ad libitum 8-week LCHF diet compared to an HCLF diet on lipids and lipoprotein metabolism and CVD risk factors. For 8 weeks, n = 16 adults were randomly assigned to follow either an LCHF (n = 8, <50 g CHO p/day) or an HCLF diet (n = 8). Fasted blood samples at weeks 0, 4, and 8 were collected and analysed for lipids, lipoprotein subclasses, and energy-related metabolism markers via NMR spectroscopy. The LCHF diet increased (p < 0.05) very small VLDL, IDL, and large HDL cholesterol levels, whereas the HCLF diet increased (p < 0.05) IDL and large LDL cholesterol levels. Following the LCHF diet alone, triglycerides in VLDL and HDL lipoproteins significantly (p < 0.05) decreased, and HDL phospholipids significantly (p < 0.05) increased. Furthermore, the LCHF diet significantly (p < 0.05) increased the large and small HDL particle concentrations compared to the HCLF diet. In conclusion, the LCHF diet may reduce CVD risk factors by reducing triglyceride-rich lipoproteins and improving HDL functionality.

Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease

Whilst most individuals with SARS-CoV-2 infection have relatively mild disease, managed in the community, it was noted early in the pandemic that individuals with cardiovascular risk factors were more likely to experience severe acute disease, requiring hospitalisation. As the pandemic has progressed, increasing concern has also developed over long symptom duration in many individuals after SARS-CoV-2 infection, including among the majority who are managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined. Here, we examine post-illness metabolomic profiles, using nuclear magnetic resonance (Nightingale Health Oyj), and gut-microbiome profiles, using shotgun metagenomic sequencing (Illumina Inc), in 2561 community-dwelling participants with SARS-CoV-2. Illness duration ranged from asymptomatic (n = 307) to Post-COVID Syndrome (n = 180), and included participants with prolonged non-COVID-19 illnesses (n = 287). We also assess a pre-established metabolomic biomarker score, previously associated with hospitalisation for both acute pneumonia and severe acute COVID-19 illness, for its association with illness duration. We found an atherogenic-dyslipidaemic metabolic profile, including biomarkers such as fatty acids and cholesterol, was associated with longer duration of illness, both in individuals with and without SARS-CoV-2 infection. Greater values of a pre-existing metabolomic biomarker score also associated with longer duration of illness, regardless of SARS-CoV-2 infection. We found no association between illness duration and gut microbiome profiles in convalescence. This highlights the potential role of cardiometabolic dysfunction in relation to the experience of long duration symptoms after symptoms of acute infection, both COVID-19 as well as other illnesses.

Lower levels of small HDL particles associated with increased infectious disease morbidity and mortality: a population-based cohort study of 30 195 individuals

AIMS

Low levels of HDL cholesterol have been associated with increased risk of infectious disease morbidity and mortality. Nuclear magnetic resonance (NMR) spectroscopy permits the measurement of HDL particle count and allows further subclassification according to particle size. We tested the hypothesis that low number of different HDL subfractions is associated with increased infectious disease morbidity and mortality.

METHODS AND RESULTS

HDL particle counts were measured using NMR spectroscopy in 30 195 individuals aged 22-99 years from the Copenhagen General Population Study. Using multiple-event Cox regression and cause-specific hazard models, we assessed risk of hospitalizations due to infection and infectious disease-related death, from 2003 through 2018. During follow-up, 9303 individuals had one or more infectious disease events, and 1558 experienced infectious disease-related death. In multifactorial adjusted analyses, low number of small and medium HDL particles was associated with increased risk of any infection and infectious disease-related death, whereas low number of large and extra-large HDL particles was not. A very high number of small and medium HDL particles was also associated with increased risk of any infection, but not with infectious disease-related death. For small and medium HDL particles and compared to individuals in the 91-95th percentile, hazard ratios (HRs) in individuals in the lowest percentile were 2.31 (95% confidence interval: 1.75, 3.05) for any infection and 3.23 (2.08, 5.02) for infectious disease-related death. For the highest percentile, corresponding HRs were 1.36 (1.07, 1.74) and 1.06 (0.57, 1.98), respectively. Individuals in the lowest percentile had increased risk of pneumonia (HR: 1.86; 95% confidence interval: 1.30, 2.65), sepsis (2.17; 1.37, 3.35), urinary tract infection (1.76; 1.17, 2.63), skin infection (1.87; 1.24, 2.81), gastroenteritis (1.78; 1.01, 3.16), and other infections (2.57; 1.28, 5.16).

CONCLUSION

Low number of the small HDL particles was associated with increased infectious disease morbidity and mortality.

Multi-omic underpinnings of epigenetic aging and human longevity

Biological aging is accompanied by increasing morbidity, mortality, and healthcare costs; however, its molecular mechanisms are poorly understood. Here, we use multi-omic methods to integrate genomic, transcriptomic, and metabolomic data and identify biological associations with four measures of epigenetic age acceleration and a human longevity phenotype comprising healthspan, lifespan, and exceptional longevity (multivariate longevity). Using transcriptomic imputation, fine-mapping, and conditional analysis, we identify 22 high confidence associations with epigenetic age acceleration and seven with multivariate longevity. FLOT1, KPNA4, and TMX2 are novel, high confidence genes associated with epigenetic age acceleration. In parallel, cis-instrument Mendelian randomization of the druggable genome associates TPMT and NHLRC1 with epigenetic aging, supporting transcriptomic imputation findings. Metabolomics Mendelian randomization identifies a negative effect of non-high-density lipoprotein cholesterol and associated lipoproteins on multivariate longevity, but not epigenetic age acceleration. Finally, cell-type enrichment analysis implicates immune cells and precursors in epigenetic age acceleration and, more modestly, multivariate longevity. Follow-up Mendelian randomization of immune cell traits suggests lymphocyte subpopulations and lymphocytic surface molecules affect multivariate longevity and epigenetic age acceleration. Our results highlight druggable targets and biological pathways involved in aging and facilitate multi-omic comparisons of epigenetic clocks and human longevity.

Circulating polyunsaturated fatty acids, fish oil supplementation, and risk of incident dementia: a prospective cohort study of 440,750 participants

Cohort studies report inconsistent associations between omega-3 polyunsaturated fatty acids (n-3 PUFA) or fish oil and dementia risk. Furthermore, evidence relating omega-6 polyunsaturated fatty acids (n-6 PUFA) with dementia is scarce. Here, we included 440,750 dementia-free participants from UK Biobank to comprehensively investigate the associations between plasma levels of different types of PUFA, fish oil supplementation, and dementia risk. During a median follow-up of 9.25 years, 7768 incident dementia events occurred. Higher plasma levels of five PUFA measures showed consistent associations with lower dementia risk (hazard ratios [95% confidence intervals] for per standard deviation increment of plasma concentrations 0.85 [0.81-0.89] for total PUFAs; 0.90 [0.86-0.95] for omega-3 PUFAs; 0.92 [0.87-0.96] for docosahexaenoic acid (DHA); 0.86 [0.82-0.90] for omega-6 PUFAs; 0.86 [0.82-0.90] for linoleic acid (LA); all p < 0.001). Compared with non-users, fish oil supplement users had a 7% decreased risk of developing all-cause dementia (0.93 [0.89-0.97], p = 0.002), and the relationship was partially mediated by plasma n-3 PUFA levels (omega-3 PUFAs: proportion of mediation = 57.99%; DHA: proportion of mediation = 56.95%). Furthermore, we observed significant associations of plasma n-3 PUFA levels and fish oil supplementation with peripheral immune markers that were related to dementia risk, as well as the positive associations of plasma PUFA levels with brain gray matter volumes and white matter microstructural integrity, suggesting they may affect dementia risk by affecting peripheral immunity and brain structure. Taken together, higher plasma PUFA levels and fish oil supplementation were associated with lower risk of incident dementia. This study may support the value of interventions to target PUFAs (specifically n-3 PUFAs) to prevent dementia.

Cardiovascular risk of metabolically healthy obesity in two european populations: Prevention potential from a metabolomic study

BACKGROUND

A new definition of metabolically healthy obesity (MHO) has recently been proposed to stratify the heterogeneous mortality risk of obesity. Metabolomic profiling provides clues to metabolic alterations beyond clinical definition. We aimed to evaluate the association between MHO and cardiovascular events and assess its metabolomic pattern.

METHODS

This prospective study included Europeans from two population-based studies, the FLEMENGHO and the Hortega study. A total of 2339 participants with follow-up were analyzed, including 2218 with metabolomic profiling. Metabolic health was developed from the third National Health and Nutrition Examination Survey and the UK biobank cohorts and defined as systolic blood pressure < 130 mmHg, no antihypertensive drugs, waist-to-hip ratio < 0.95 for women or 1.03 for men, and the absence of diabetes. BMI categories included normal weight, overweight, and obesity (BMI < 25, 25-30, ≥ 30 kg/m²). Participants were classified into six subgroups according to BMI category and metabolic healthy status. Outcomes were fatal and nonfatal composited cardiovascular events.

RESULTS

Of 2339 participants, the mean age was 51 years, 1161 (49.6%) were women, 434 (18.6%) had obesity, 117 (5.0%) were classified as MHO, and both cohorts had similar characteristics. Over a median of 9.2-year (3.7-13.0) follow-up, 245 cardiovascular events occurred. Compared to those with metabolically healthy normal weight, individuals with metabolic unhealthy status had a higher risk of cardiovascular events, regardless of BMI category (adjusted HR: 3.30 [95% CI: 1.73-6.28] for normal weight, 2.50 [95% CI: 1.34-4.66] for overweight, and 3.42 [95% CI: 1.81-6.44] for obesity), whereas those with MHO were not at increased risk of cardiovascular events (HR: 1.11 [95% CI: 0.36-3.45]). Factor analysis identified a metabolomic factor mainly associated with glucose regulation, which was associated with cardiovascular events (HR: 1.22 [95% CI: 1.10-1.36]). Individuals with MHO tended to present a higher metabolomic factor score than those with metabolically healthy normal weight (0.175 vs. -0.057, P = 0.019), and the score was comparable to metabolically unhealthy obesity (0.175 vs. -0.080, P = 0.91).

CONCLUSIONS

Individuals with MHO may not present higher short-term cardiovascular risk but tend to have a metabolomic pattern associated with higher cardiovascular risk, emphasizing a need for early intervention.

Distinct metabolic features of genetic liability to type 2 diabetes and coronary artery disease: a reverse Mendelian randomization study

BACKGROUND

Type 2 diabetes (T2D) and coronary artery disease (CAD) both have known genetic determinants, but the mechanisms through which their associated genetic variants lead to disease onset remain poorly understood.

METHODS

We used large-scale metabolomics data in a two-sample reverse Mendelian randomization (MR) framework to estimate effects of genetic liability to T2D and CAD on 249 circulating metabolites in the UK Biobank (N = 118,466). We examined the potential for medication use to distort effect estimates by conducting age-stratified metabolite analyses.

FINDINGS

Using inverse variance weighted (IVW) models, higher genetic liability to T2D was estimated to decrease high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) (e.g.

, HDL-C

 -0.05 SD; 95% CI -0.07 to -0.03, per doubling of liability), whilst increasing all triglyceride groups and branched chain amino acids (BCAAs). IVW estimates for CAD liability suggested an effect on reducing HDL-C as well as raising very-low density lipoprotein cholesterol (VLDL-C) and LDL-C. In pleiotropy-robust models, T2D liability was still estimated to increase BCAAs, but several estimates for higher CAD liability reversed and supported decreased LDL-C and apolipoprotein-B. Estimated effects of CAD liability differed substantially by age for non-HDL-C traits, with higher CAD liability lowering LDL-C only at older ages when statin use was common.

INTERPRETATION

Overall, our results support largely distinct metabolic features of genetic liability to T2D and CAD, illustrating both challenges and opportunities for preventing these commonly co-occurring diseases.

FUNDING

Wellcome Trust [218495/Z/19/Z], UK MRC [MC_UU_00011/1; MC_UU_00011/4], the University of Bristol, Diabetes UK [17/0005587], World Cancer Research Fund [IIG_2019_2009].

Insulin Resistance Is Associated with an Unfavorable Serum Lipoprotein Lipid Profile in Women with Newly Diagnosed Gestational Diabetes

Background: Gestational diabetes (GDM) is associated with various degrees of insulin resistance—a feature related to increased risk of adverse perinatal outcomes. We aimed to determine the previously poorly investigated associations between maternal insulin resistance and serum fasting metabolome at the time of GDM diagnosis. Methods: Serum lipoprotein and amino acid profile was analyzed in 300 subjects with newly diagnosed GDM using a validated nuclear magnetic resonance spectroscopy protocol. Associations between insulin resistance (homeostasis model assessment of insulin resistance, HOMA2-IR) and serum metabolites were examined with linear regression. Results: We found insulin resistance to be associated with a distinct lipid pattern: increased concentration of VLDL triglycerides and phospholipids and total triglycerides. VLDL size was positively related and LDL and HDL sizes were inversely related to insulin resistance. Of fatty acids, increased total fatty acids, relative increase in saturated and monounsaturated fatty acids, and relative decrease in polyunsaturated and omega fatty acids were related to maternal insulin resistance. Conclusions: In newly diagnosed GDM, the association between maternal insulin resistance and serum lipoprotein profile was largely as described in type 2 diabetes. Lifestyle interventions aiming to decrease insulin resistance from early pregnancy could benefit pregnancy outcomes via more advantageous lipid metabolism.

Association of physical activity with metabolic profile from adolescence to adulthood

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The metabolic profile of waist to hip ratio-A multi-cohort study

BACKGROUND

The genetic background of general obesity and fat distribution is different, pointing to separate underlying physiology. Here, we searched for metabolites and lipoprotein particles associated with fat distribution, measured as waist/hip ratio adjusted for fat mass (WHRadjfatmass), and general adiposity measured as percentage fat mass.

METHOD

The sex-stratified association of 791 metabolites detected by liquid chromatography-mass spectrometry (LC-MS) and 91 lipoprotein particles measured by nuclear magnetic spectroscopy (NMR) with WHRadjfatmass and fat mass were assessed using three population-based cohorts: EpiHealth (n = 2350) as discovery cohort, with PIVUS (n = 603) and POEM (n = 502) as replication cohorts.

RESULTS

Of the 193 LC-MS-metabolites being associated with WHRadjfatmass in EpiHealth (false discovery rate (FDR) <5%), 52 were replicated in a meta-analysis of PIVUS and POEM. Nine metabolites, including ceramides, sphingomyelins or glycerophosphatidylcholines, were inversely associated with WHRadjfatmass in both sexes. Two of the sphingomyelins (d18:2/24:1, d18:1/24:2 and d18:2/24:2) were not associated with fat mass (p>0.50). Out of 91, 82 lipoprotein particles were associated with WHRadjfatmass in EpiHealth and 42 were replicated. Fourteen of those were associated in both sexes and belonged to very-large or large HDL particles, all being inversely associated with both WHRadjfatmass and fat mass.

CONCLUSION

Two sphingomyelins were inversely linked to body fat distribution in both men and women without being associated with fat mass, while very-large and large HDL particles were inversely associated with both fat distribution and fat mass. If these metabolites represent a link between an impaired fat distribution and cardiometabolic diseases remains to be established.

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

BACKGROUND/OBJECTIVE

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

SUBJECTS/METHODS

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

RESULTS

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

CONCLUSIONS

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

Association between NMR metabolomic signatures of healthy lifestyle and incident coronary artery disease

AIMS

To identify metabolites associated with a healthy lifestyle and explore the possible mechanisms of lifestyle in coronary artery disease (CAD).

METHODS AND RESULTS

The nuclear magnetic resonance metabolomics platform was applied to perform metabolomic profiling of baseline plasma samples from a randomly selected subset of 121 733 UK Biobank participants. Cox proportional hazards models with covariate adjustments were used to investigate the associations between validated lifestyle-associated metabolites and incident CAD and to estimate the accuracy of the inclusion of metabolites to predict CAD compared with traditional prediction models. The discriminatory ability of each model was evaluated using Harrell's C statistic, integrated discrimination improvement (IDI), and continuous net reclassification improvement (NRI) indexes. During a median of 8.6 years of follow-up, 5513 incident CAD cases were documented. Among the 111 lifestyle-associated metabolites, 65 were significantly associated with incident CAD after multivariate adjustment (Bonferroni P < 3.11 × 10-04). The addition of these metabolites to classic risk prediction models [Framingham Risk Score (FRS) using lipids; FRS using body mass index] improved CAD prediction accuracy as assessed by the C statistic (increasing to 0.739 [95% CI, 0.731-0.747] and 0.752 [95% CI, 0.746-0.758]), respectively; continuous NRI (0.274 [0.227-0.325] and 0.266 [0.223-0.317]) and IDI (0.003 [0.002-0.004] and 0.003 [0.002-0.004]).

CONCLUSION

Healthy lifestyle-associated metabolites are associated with the incidence of CAD and may help improve the prediction of CAD risk. The use of metabolite information combined with the FRS model warrants further investigation before clinical implementation.

Maternal prenatal cholesterol levels predict offspring weight trajectories during childhood in the Norwegian Mother, Father and Child Cohort Study

BACKGROUND

Numerous intrauterine factors may affect the offspring's growth during childhood. We aimed to explore if maternal and paternal prenatal lipid, apolipoprotein (apo)B and apoA1 levels are associated with offspring weight, length, and body mass index from 6 weeks to eight years of age. This has previously been studied to a limited extent.

METHODS

This parental negative control study is based on the Norwegian Mother, Father and Child Cohort Study and uses data from the Medical Birth Registry of Norway. We included 713 mothers and fathers with or without self-reported hypercholesterolemia and their offspring. Seven parental metabolites were measured by nuclear magnetic resonance spectroscopy, and offspring weight and length were measured at 12 time points. Data were analyzed by linear spline mixed models, and the results are presented as the interaction between parental metabolite levels and offspring spline (age).

RESULTS

Higher maternal total cholesterol (TC) level was associated with a larger increase in offspring body weight up to 8 years of age (0.03 ≤ P_interaction ≤ 0.04). Paternal TC level was not associated with change in offspring body weight (0.17 ≤ P_interaction ≤ 0.25). Higher maternal high-density lipoprotein cholesterol (HDL-C) and apoA1 levels were associated with a lower increase in offspring body weight up to 8 years of age (0.001 ≤ P_interaction ≤ 0.005). Higher paternal HDL-C and apoA1 levels were associated with a lower increase in offspring body weight up to 5 years of age but a larger increase in offspring body weight from 5 to 8 years of age (0.01 ≤ P_interaction ≤ 0.03). Parental metabolites were not associated with change in offspring height or body mass index up to 8 years of age (0.07 ≤ P_interaction ≤ 0.99).

CONCLUSIONS

Maternal compared to paternal TC, HDL-C, and apoA1 levels were more strongly and consistently associated with offspring body weight during childhood, supporting a direct intrauterine effect.

Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank

Blood lipids and metabolites are markers of current health and future disease risk. Here, we describe plasma nuclear magnetic resonance (NMR) biomarker data for 118,461 participants in the UK Biobank. The biomarkers cover 249 measures of lipoprotein lipids, fatty acids, and small molecules such as amino acids, ketones, and glycolysis metabolites. We provide an atlas of associations of these biomarkers to prevalence, incidence, and mortality of over 700 common diseases ( nightingalehealth.com/atlas ). The results reveal a plethora of biomarker associations, including susceptibility to infectious diseases and risk of various cancers, joint disorders, and mental health outcomes, indicating that abundant circulating lipids and metabolites are risk markers beyond cardiometabolic diseases. Clustering analyses indicate similar biomarker association patterns across different disease types, suggesting latent systemic connectivity in the susceptibility to a diverse set of diseases. This work highlights the value of NMR based metabolic biomarker profiling in large biobanks for public health research and translation.

The metabolic differences of anestrus, heat, pregnancy, pseudopregnancy, and lactation in 800 female dogs

Introduction

Reproduction causes major hormonal and physiological changes to the female body. However, the metabolic changes occurring during canine reproduction are scarcely studied.

Methods

In this cross-sectional study, we assessed the metabolic effects of canine reproductive status using a ¹H NMR metabolomics platform optimized and validated for canine use. The study population consisted of a total of 837 healthy, intact female dogs in breeding age, of which 663 dogs were in anestrus, 78 in heat, 43 were pseudopregnant, 15 were pregnant, and 38 were lactating. The differences in metabolite profiles between these states were studied by the Kruskal-Wallis test with post-hoc tests performed using the Dunn's test, and visualized by box plots and a heatmap. The ability of the metabolite profile to differentiate pregnant dogs from non-pregnant ones was assessed by creating a multivariate Firth logistic regression model using forward stepwise selection.

Results

Lactation, pregnancy and heat all were associated with distinct metabolic changes; pregnancy caused major changes in the concentrations of glycoprotein acetyls, albumin and creatinine, and smaller changes in several lipids, citrate, glutamine, and alanine. Pseudopregnancy, on the other hand, metabolically largely resembled anestrus. Lactation caused major changes in amino acid concentrations and smaller changes in several lipids, albumin, citrate, creatinine, and glycoprotein acetyls. Heat, referring to proestrus and estrus, affected cholesterol and LDL metabolism, and increased HDL particle size. Albumin and glycoprotein acetyls were the metabolites included in the final multivariate model for pregnancy detection, and could differentiate pregnant dogs from non-pregnant ones with excellent sensitivity and specificity.

Discussion

These results increase our understanding of the metabolic consequences of canine reproduction, with the possibility of improving maternal health and ensuring reproductive success. The identified metabolites could be used for confirming canine pregnancy.

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

BACKGROUND AND AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Mediterranean diet related metabolite profiles and cognitive performance

BACKGROUND & AIMS

Evidence suggests that adherence to the Mediterranean diet (MedDiet) affects human metabolism and may contribute to better cognitive performance. However, the underlying mechanisms are not clear.

OBJECTIVE

We generated a metabolite profile for adherence to MedDiet and evaluated its cross-sectional association with aspects of cognitive performance.

METHODS

A total of 1250 healthy Greek middle-aged adults from the Epirus Health Study cohort were included in the analysis. Adherence to the MedDiet was assessed using the 14-point Mediterranean Diet Adherence Screener (MEDAS); cognition was measured using the Trail Making Test, the Verbal Fluency test and the Logical Memory test. A targeted metabolite profiling (n = 250 metabolites) approach was applied, using a high-throughput nuclear magnetic resonance platform. We used elastic net regularized regressions, with a 10-fold cross-validation procedure, to identify a metabolite profile for MEDAS. We evaluated the associations of the identified metabolite profile and MEDAS with cognitive tests, using multivariable linear regression models.

RESULTS

We identified a metabolite profile composed of 42 metabolites, mainly lipoprotein subclasses and fatty acids, significantly correlated with MedDiet adherence (Pearson r = 0.35, P-value = 5.5 × 10^-37). After adjusting for known risk factors and accounting for multiple testing, the metabolite profile and MEDAS were not associated with the cognitive tests.

CONCLUSIONS

A plasma metabolite profile related to better adherence to the MedDiet was not associated with the tested aspects of cognitive performance, in a middle-aged Mediterranean population.

Elevated LDL Triglycerides and Atherosclerotic Risk

BACKGROUND

It is unclear whether elevated low-density lipoprotein (LDL) triglycerides are associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD).

OBJECTIVES

This study tested the hypothesis that elevated LDL triglycerides are associated with an increased risk of ASCVD and of each ASCVD component individually.

METHODS

The study investigators used the Copenhagen General Population Study, which measured LDL triglycerides in 38,081 individuals with a direct automated assay (direct LDL triglycerides) and in another 30,208 individuals with nuclear magnetic resonance (NMR) spectroscopy (NMR LDL triglycerides). Meta-analyses aggregated the present findings with previously reported results.

RESULTS

During a median follow-up of 3.0 and 9.2 years, respectively, 872 and 5,766 individuals in the 2 cohorts received a diagnosis of ASCVD. Per 0.1 mmol/L (9 mg/dL) higher direct LDL triglycerides, HRs were 1.26 (95% CI: 1.17-1.35) for ASCVD, 1.27 (95% CI: 1.16-1.39) for ischemic heart disease, 1.28 (95% CI: 1.11-1.48) for myocardial infarction, 1.22 (95% CI: 1.08-1.38) for ischemic stroke, and 1.38 (95% CI: 1.21-1.58) for peripheral artery disease. Corresponding HRs for NMR LDL triglycerides were 1.26 (95% CI: 1.20-1.33), 1.33 (95% CI: 1.25-1.41), 1.41 (95% CI: 1.31-1.52), 1.13 (95% CI: 1.05-1.23), and 1.26 (95% CI: 1.10-1.43), respectively. The foregoing results were not entirely statistically explained by apolipoprotein B levels. In meta-analyses for the highest quartile vs the lowest quartile of LDL triglycerides, random-effects risk ratios were 1.50 (95% CI: 1.35-1.66) for ASCVD (4 studies; 71,526 individuals; 8,576 events), 1.62 (95% CI: 1.37-1.93) for ischemic heart disease (6 studies; 107,538 individuals; 9,734 events), 1.30 (95% CI: 1.13-1.49) for ischemic stroke (4 studies; 78,026 individuals; 4,273 events), and 1.53 (95% CI: 1.29-1.81) for peripheral artery disease (4 studies; 107,511 individuals; 1,848 events).

CONCLUSIONS

Elevated LDL triglycerides were robustly associated with an increased risk of ASCVD and of each ASCVD component individually in 2 prospective cohort studies and in meta-analyses of previous and present studies combined.

Practical Aspects of NMR-Based Metabolomics

While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for &gt;40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.

Metabolomics during canine pregnancy and lactation

During pregnancy and parturition, female dogs have to cope with various challenges such as providing nutrients for the growth of the fetuses, hormonal changes, whelping, nursing, milk production, and uterine involution. Metabolomic research has been used to characterize the influence of several factors on metabolism such as inter- and intra-individual factors, feeding, aging, inter-breed differences, drug action, behavior, exercise, genetic factors, neuter status, and pathologic processes. Aim of this study was to identify metabolites showing specific changes in blood serum at the different phases of pregnancy and lactation. In total, 27 privately owned female dogs of 21 different breeds were sampled at six time points: during heat, in early, mid and late pregnancy, at the suspected peak of lactation and after weaning. A validated and highly automated canine-specific NMR metabolomics technology was utilized to quantitate 123 measurands. It was evaluated which metabolite concentrations showed significant changes between the different time points. Metabolites were then grouped into five clusters based on concentration patterns and biochemical relationships between the metabolites: high in mid-pregnancy, low in mid-pregnancy, high in late pregnancy, high in lactation, and low in lactation. Several metabolites such as albumin, glycoprotein acetyls, fatty acids, lipoproteins, glucose, and some amino acids show similar patterns during pregnancy and lactation as shown in humans. The patterns of some other parameters such as branched-chain amino acids, alanine and histidine seem to differ between these species. For most metabolites, it is yet unstudied whether the observed changes arise from modified resorption from the intestines, modified production, or metabolism in the maternal or fetal tissues. Hence, further species-specific metabolomic research may support a broader understanding of the physiological changes caused by pregnancy that are likely to be key for the normal fetal growth and development. Our findings provide a baseline of normal metabolic changes during healthy canine pregnancy and parturition. Combined with future metabolomics findings, they may help monitor vital functions of pre-, intra-, and post-partum bitches and may allow early detection of illness.

Genetic Mimicry Analysis Reveals the Specific Lipases Targeted by the ANGPTL3-ANGPTL8 Complex and ANGPTL4

Angiopoietin-like proteins, ANGPTL3, ANGPTL4, and ANGPTL8, are involved in regulating plasma lipids. In vitro and animal-based studies point to LPL and endothelial lipase (EL, LIPG) as key targets of ANGPTLs. To examine the ANGPTL mechanisms for plasma lipid modulation in humans, we pursued a genetic mimicry analysis of enhancing or suppressing variants in the LPL, LIPG, lipase C hepatic type (LIPC), ANGPTL3, ANGPTL4, and ANGPTL8 genes using data on 248 metabolic parameters derived from over 110,000 nonfasted individuals in the UK Biobank and validated in over 13,000 overnight fasted individuals from 11 other European populations. ANGPTL4 suppression was highly concordant with LPL enhancement but not HL or EL, suggesting ANGPTL4 impacts plasma metabolic parameters exclusively via LPL. The LPL-independent effects of ANGPTL3 suppression on plasma metabolic parameters showed a striking inverse resemblance with EL suppression, suggesting ANGPTL3 not only targets LPL but also targets EL. Investigation of the impact of the ANGPTL3-ANGPTL8 complex on plasma metabolite traits via the ANGPTL8 R59W substitution as an instrumental variable showed a much higher concordance between R59W and EL activity than between R59W and LPL activity, suggesting the R59W substitution more strongly affects EL inhibition than LPL inhibition. Meanwhile, when using a rare and deleterious protein-truncating ANGPTL8 variant as an instrumental variable, the ANGPTL3-ANGPTL8 complex was very LPL specific. In conclusion, our analysis provides strong human genetic evidence that the ANGPTL3-ANGPTL8 complex regulates plasma metabolic parameters, which is achieved by impacting LPL and EL. By contrast, ANGPTL4 influences plasma metabolic parameters exclusively via LPL.

Metabolomics dissection of depression heterogeneity and related cardiometabolic risk

BACKGROUND

A recent hypothesis postulates the existence of an 'immune-metabolic depression' (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive symptoms, we aimed to identify depressions associated with an increased risk of adverse metabolic alterations.

METHOD

Clustering data were from 1094 individuals with major depressive disorder in the last 6 months and measures of 149 metabolites from a ¹H-NMR platform and 30 depressive symptoms (IDS-SR30). Canonical correlation analyses (CCA) were used to identify main independent metabolite-symptom axes of variance. Then, for the replication, we examined the association of the identified dimensions with metabolites from the same platform and cardiometabolic diseases in an independent population-based cohort (n = 6572).

RESULTS

CCA identified an overall depression dimension and a dimension resembling IMD, in which symptoms such as sleeping too much, increased appetite, and low energy level had higher relative loading. In the independent sample, the overall depression dimension was associated with lower cardiometabolic risk, such as (i.e. per s.d.) HOMA-1B -0.06 (95% CI -0.09 - -0.04), and visceral adipose tissue -0.10 cm² (95% CI -0.14 - -0.07). In contrast, the IMD dimension was associated with well-known cardiometabolic diseases such as higher visceral adipose tissue 0.08 cm² (95% CI 0.04-0.12), HOMA-1B 0.06 (95% CI 0.04-0.09), and lower HDL-cholesterol levels -0.03 mmol/L (95% CI -0.05 - -0.01).

CONCLUSIONS

Combining metabolomics and clinical symptoms we identified a replicable depression dimension associated with adverse metabolic alterations, in line with the IMD hypothesis. Patients with IMD may be at higher cardiometabolic risk and may benefit from specific treatment targeting underlying metabolic dysregulations.

Quantitative NMR Methods in Metabolomics

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two major analytical platforms in the field of metabolomics, the other being mass spectrometry (MS). NMR is less sensitive than MS and hence it detects a relatively small number of metabolites. However, NMR exhibits numerous unique characteristics including its high reproducibility and non-destructive nature, its ability to identify unknown metabolites definitively, and its capabilities to obtain absolute concentrations of all detected metabolites, sometimes even without an internal standard. These characteristics outweigh the relatively low sensitivity and resolution of NMR in metabolomics applications. Since biological mixtures are highly complex, increased demand for new methods to improve detection, better identify unknown metabolites, and provide more accurate quantitation continues unabated. Technological and methodological advances to date have helped to improve the resolution and sensitivity and detection of a larger number of metabolite signals. Efforts focused on measuring unknown metabolite signals have resulted in the identification and quantitation of an expanded pool of metabolites including labile metabolites such as cellular redox coenzymes, energy coenzymes, and antioxidants. This chapter describes quantitative NMR methods in metabolomics with an emphasis on recent methodological developments, while highlighting the benefits and challenges of NMR-based metabolomics.

High-density lipoprotein subclasses and cardiovascular disease and mortality in type 2 diabetes: analysis from the Hong Kong Diabetes Biobank

OBJECTIVE

High-density lipoproteins (HDL) comprise particles of different size, density and composition and their vasoprotective functions may differ. Diabetes modifies the composition and function of HDL. We assessed associations of HDL size-based subclasses with incident cardiovascular disease (CVD) and mortality and their prognostic utility.

RESEARCH DESIGN AND METHODS

HDL subclasses by nuclear magnetic resonance spectroscopy were determined in sera from 1991 fasted adults with type 2 diabetes (T2D) consecutively recruited from March 2014 to February 2015 in Hong Kong. HDL was divided into small, medium, large and very large subclasses. Associations (per SD increment) with outcomes were evaluated using multivariate Cox proportional hazards models. C-statistic, integrated discrimination index (IDI), and categorial and continuous net reclassification improvement (NRI) were used to assess predictive value.

RESULTS

Over median (IQR) 5.2 (5.0-5.4) years, 125 participants developed incident CVD and 90 participants died. Small HDL particles (HDL-P) were inversely associated with incident CVD [hazard ratio (HR) 0.65 (95% CI 0.52, 0.81)] and all-cause mortality [0.47 (0.38, 0.59)] (false discovery rate < 0.05). Very large HDL-P were positively associated with all-cause mortality [1.75 (1.19, 2.58)]. Small HDL-P improved prediction of mortality [C-statistic 0.034 (0.013, 0.055), IDI 0.052 (0.014, 0.103), categorical NRI 0.156 (0.006, 0.252), and continuous NRI 0.571 (0.246, 0.851)] and CVD [IDI 0.017 (0.003, 0.038) and continuous NRI 0.282 (0.088, 0.486)] over the RECODe model.

CONCLUSION

Small HDL-P were inversely associated with incident CVD and all-cause mortality and improved risk stratification for adverse outcomes in people with T2D. HDL-P may be used as markers for residual risk in people with T2D.

Systematic analysis of relationships between plasma branched-chain amino acid concentrations and cardiometabolic parameters: an association and Mendelian randomization study

BACKGROUND

Branched-chain amino acids (BCAAs; valine, leucine, and isoleucine) are essential amino acids that are associated with an increased risk of cardiometabolic diseases (CMD). However, there are still only limited insights into potential direct associations between BCAAs and a wide range of CMD parameters, especially those remaining after correcting for covariates and underlying causal relationships.

METHODS

To shed light on these relationships, we systematically characterized the associations between plasma BCAA concentrations and a large panel of 537 CMD parameters (including atherosclerosis-related parameters, fat distribution, plasma cytokine concentrations and cell counts, circulating concentrations of cardiovascular-related proteins and plasma metabolites) in 1400 individuals from the Dutch population cohort LifeLines DEEP and 294 overweight individuals from the 300OB cohort. After correcting for age, sex, and BMI, we assessed associations between individual BCAAs and CMD parameters. We further assessed the underlying causality using Mendelian randomization.

RESULTS

A total of 838 significant associations were detected for 409 CMD parameters. BCAAs showed both common and specific associations, with the most specific associations being detected for isoleucine. Further, we found that obesity status substantially affected the strength and direction of associations for valine, which cannot be corrected for using BMI as a covariate. Subsequent univariable Mendelian randomization (UVMR), after removing BMI-associated SNPs, identified seven significant causal relationships from four CMD traits to BCAA levels, mostly for diabetes-related parameters. However, no causal effects of BCAAs on CMD parameters were supported.

CONCLUSIONS

Our cross-sectional association study reports a large number of associations between BCAAs and CMD parameters. Our results highlight some specific associations for isoleucine, as well as obesity-specific effects for valine. MR-based causality analysis suggests that altered BCAA levels can be a consequence of diabetes and alteration in lipid metabolism. We found no MR evidence to support a causal role for BCAAs in CMD. These findings provide evidence to (re)evaluate the clinical importance of individual BCAAs in CMD diagnosis, prevention, and treatment.

Effects of dietary and exercise treatments on HDL subclasses in lactating women with overweight and obesity: a secondary analysis of a randomised controlled trial

Childbearing decreases HDL-cholesterol, potentially contributing to the increased risk of CVD in parous women. Large HDL particles (HDL-P) are associated with lower risk of CVD. In this secondary analysis of a randomised controlled trial, we investigated the effects of 12-week dietary and exercise treatments on HDL-P subclass concentration, size and apoA1 in lactating women with overweight/obesity. At 10-14 weeks postpartum, 68 women with pre-pregnant BMI 25-35 kg/m² were randomised to four groups using 2 × 2 factorial design: (1) dietary treatment for weight loss; (2) exercise treatment; (3) both treatments and (4) no treatment. Lipoprotein subclass profiling by NMR spectroscopy was performed in serum at randomisation and after 3 and 12 months, and the results analysed with two-way ANCOVA. Lipid concentrations decline naturally postpartum. At 3 months (5-6 months postpartum), both diet (P = 0·003) and exercise (P = 0·008) reduced small HDL-P concentration. Concurrently, exercise limited the decline in very large HDL-P (P = 0·002) and the effect was still significant at 12 months (15 months postpartum) (P = 0·041). At 12 months, diet limited the decline in very large HDL-P (P = 0·005), large HDL-P (P = 0·001) and apoA1 (P = 0·002) as well as HDL size (P = 0·002). The dietary treatment for weight loss and the exercise treatment both showed effects on HDL-P subclasses in lactating women with overweight and obesity possibly associated with lower CVD risk. The dietary treatment had more effects than the exercise treatment at 12 months, likely associated with a 10 % weight loss.

Sex-Specific Associations of Red Meat and Processed Meat Consumption with Serum Metabolites in the UK Biobank

Red meat consumption has been found to closely related to cardiometabolic health, with sex disparity. However, the specific metabolic factors corresponding to red meat consumption in men and women have not been examined previously. We analyzed the sex-specific associations of meat consumption, with 167 metabolites using multivariable regression, controlling for age, ethnicity, Townsend deprivation index, education, physical activity, smoking, and drinking status among ~79,644 UK Biobank participants. We also compared the sex differences using an established formula. After accounting for multiple testing with false discovery rate < 5% and controlling for confounders, the positive associations of unprocessed red meat consumption with branched-chain amino acids and several lipoproteins, and the inverse association with glycine were stronger in women, while the positive associations with apolipoprotein A1, creatinine, and monounsaturated fatty acids were more obvious in men. For processed meat, the positive associations with branched-chain amino acids, several lipoproteins, tyrosine, lactate, glycoprotein acetyls and inverse associations with glutamine, and glycine were stronger in women than in men. The study suggests that meat consumption has sex-specific associations with several metabolites. This has important implication to provide dietary suggestions for individuals with or at high risk of cardiometabolic disease, with consideration of sex difference.