NMR metabolomic modeling of age and lifespan: A multicohort 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. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging 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, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort 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 CA 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.

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.

Multi-omics signatures of the human early life exposome.

Environmental exposures during early life play a critical role in life-course health, yet the molecular phenotypes underlying environmental effects on health are poorly understood. In the Human Early Life Exposome (HELIX) project, a multi-centre cohort of 1301 mother-child pairs, we associate individual exposomes consisting of >100 chemical, outdoor, social and lifestyle exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome, transcriptome, proteins and metabolites) in childhood. We identify 1170 associations, 249 in pregnancy and 921 in childhood, which reveal potential biological responses and sources of exposure. Pregnancy exposures, including maternal smoking, cadmium and molybdenum, are predominantly associated with child DNA methylation changes. In contrast, childhood exposures are associated with features across all omics layers, most frequently the serum metabolome, revealing signatures for diet, toxic chemical compounds, essential trace elements, and weather conditions, among others. Our comprehensive and unique resource of all associations ( https://helixomics.isglobal.org/ ) will serve to guide future investigation into the biological imprints of the early life exposome.

Blood pressure interactions with the DASH dietary pattern, sodium, and potassium: The International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP).

BACKGROUND: Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet enhances potassium intake and reduces sodium intake and blood pressure (BP), but the underlying metabolic pathways are unclear. OBJECTIVES: Among free-living populations, we delineated metabolic signatures associated with the DASH diet adherence, 24-hour urinary sodium and potassium excretions, and the potential metabolic pathways involved. METHODS: We used 24-hour urinary metabolic profiling by proton nuclear magnetic resonance spectroscopy to characterize the metabolic signatures associated with the DASH dietary pattern score (DASH score) and 24-hour excretion of sodium and potassium among participants in the United States (n = 2164) and United Kingdom (n = 496) enrolled in the International Study of Macro- and Micronutrients and Blood Pressure (INTERMAP). Multiple linear regression and cross-tabulation analyses were used to investigate the DASH-BP relation and its modulation by sodium and potassium. Potential pathways associated with DASH adherence, sodium and potassium excretion, and BP were identified using mediation analyses and metabolic reaction networks. RESULTS: Adherence to the DASH diet was associated with urinary potassium excretion (correlation coefficient, r = 0.42; P < 0.0001). In multivariable regression analyses, a 5-point higher DASH score (range, 7 to 35) was associated with a lower systolic BP by 1.35 mmHg (95% CI, -1.95 to -0.80 mmHg; P = 1.2 × 10-5); control of the model for potassium but not sodium attenuated the DASH-BP relation. Two common metabolites (hippurate and citrate) mediated the potassium-BP and DASH-BP relationships, while 5 metabolites (succinate, alanine, S-methyl cysteine sulfoxide, 4-hydroxyhippurate, and phenylacetylglutamine) were found to be specific to the DASH-BP relation. CONCLUSIONS: Greater adherence to the DASH diet is associated with lower BP and higher potassium intake across levels of sodium intake. The DASH diet recommends greater intake of fruits, vegetables, and other potassium-rich foods that may replace sodium-rich processed foods and thereby influence BP through overlapping metabolic pathways. Possible DASH-specific pathways are speculated but confirmation requires further study. INTERMAP is registered as NCT00005271 at www.clinicaltrials.gov.

DNA methylation age as a biomarker for cancer.

Cancer is well established as an age-associated disease, and there is substantial overlap in the molecular, cellular and physiological changes observed with both ageing and the progression of cancer. Age-specific declines in resilience mechanisms such as DNA repair or epigenetic maintenance may contribute to the development of cancer. These declines may be assessed through biomarkers that measure biological age and through the related concept of "age acceleration". Epigenetic clocks, assessed through DNA methylation levels, are among the most widely used biological age markers in cancer studies. In this review, we discuss the use of DNA methylation ageing measures to predict population cancer incidence, mortality and survival. Blood-based DNA methylation age estimators appear to be promising measures of increased cancer risk and mortality, although their reported effects are generally weak, thus its clinical relevance remains to be validated in large case-cohort and longitudinal studies. Future development of epigenetic and other biological age biomarkers will likely further elucidate the links between ageing and cancer.

In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children.

BACKGROUND: The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. METHODS: We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. RESULTS: Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. CONCLUSION: In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.

Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics.

Altered metabolism is one of the key hallmarks of cancer. The development of sensitive, reproducible and robust bioanalytical tools such as Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry techniques offers numerous opportunities for cancer metabolism research, and provides additional and exciting avenues in cancer diagnosis, prognosis and for the development of more effective and personalized treatments. In this chapter, we introduce the current state of the art of metabolomics and metabolic phenotyping approaches in cancer research and clinical diagnostics.

Metabolism and Effects on Endogenous Metabolism of Paracetamol (Acetaminophen) in a Porcine Model of Liver Failure.

The metabolic fate, toxicity, and effects on endogenous metabolism of paracetamol (acetaminophen, APAP) in 22 female Landrace cross large white pigs were evaluated in a model of acute liver failure (ALF). Anesthetized pigs were initially dosed at 250 mg/kg via an oroduodenal tube with APAP serum concentrations maintained above 300 mg/l using maintenance doses of 0.5-4 g/h until ALF. Studies were undertaken to determine both the metabolic fate of APAP and its effects on the endogenous metabolic phenotype of ALF in using 1H NMR spectroscopy. Increased concentrations of citrate combined with pre-ALF increases in circulating lactate, pyruvate, and alanine in plasma suggest mitochondrial dysfunction and a switch in hepatic energy metabolism to glycolysis in response to APAP treatment. A specific liquid chromatography-tandem mass spectrometry assay was used to quantify APAP and metabolites. The major circulating and urinary metabolite of APAP was the phenolic glucuronide (APAP-G), followed by p-aminophenol glucuronide (PAP-G) formed from N-deacetylated APAP. The PAP produced by N-deacetylation was the likely cause of the methemoglobinemia and kidney toxicity observed in this, and previous, studies in the pig. The phenolic sulfate of APAP, and the glutathione-derived metabolites of the drug were only found as minor components (with the cysteinyl conjugate detected but not the mercapturate). Given its low sulfation, combined with significant capacity for N-deacetylation the pig may represent a poor translational model for toxicology studies for compounds undergoing significant metabolism by sulfation, or which contain amide bonds which when hydrolyzed to unmask an aniline lead to toxicity. However, the pig may provide a useful model where extensive amide hydrolysis is seen for drugs or environmental chemicals in humans, but not in, eg, the rat and dog which are the preclinical species normally employed for safety assessment.

Human Early Life Exposome (HELIX) study: a European population-based exposome cohort.

PURPOSE: Essential to exposome research is the collection of data on many environmental exposures from different domains in the same subjects. The aim of the Human Early Life Exposome (HELIX) study was to measure and describe multiple environmental exposures during early life (pregnancy and childhood) in a prospective cohort and associate these exposures with molecular omics signatures and child health outcomes. Here, we describe recruitment, measurements available and baseline data of the HELIX study populations. PARTICIPANTS: The HELIX study represents a collaborative project across six established and ongoing longitudinal population-based birth cohort studies in six European countries (France, Greece, Lithuania, Norway, Spain and the UK). HELIX used a multilevel study design with the entire study population totalling 31 472 mother-child pairs, recruited during pregnancy, in the six existing cohorts (first level); a subcohort of 1301 mother-child pairs where biomarkers, omics signatures and child health outcomes were measured at age 6-11 years (second level) and repeat-sampling panel studies with around 150 children and 150 pregnant women aimed at collecting personal exposure data (third level). FINDINGS TO DATE: Cohort data include urban environment, hazardous substances and lifestyle-related exposures for women during pregnancy and their offspring from birth until 6-11 years. Common, standardised protocols were used to collect biological samples, measure exposure biomarkers and omics signatures and assess child health across the six cohorts. Baseline data of the cohort show substantial variation in health outcomes and determinants between the six countries, for example, in family affluence levels, tobacco smoking, physical activity, dietary habits and prevalence of childhood obesity, asthma, allergies and attention deficit hyperactivity disorder. FUTURE PLANS: HELIX study results will inform on the early life exposome and its association with molecular omics signatures and child health outcomes. Cohort data are accessible for future research involving researchers external to the project.

Metabolomic characterisation of the effects of oncogenic PIK3CA transformation in a breast epithelial cell line.

Somatic mutations in PIK3CA are frequently found in a number of human cancers, including breast cancer, altering cellular physiology and tumour sensitivity to chemotherapy. This renders PIK3CA an attractive molecular target for early detection and personalised therapy. Using 1H Nuclear Magnetic Resonance spectroscopy (NMR) and Gas Chromatography - Mass Spectrometery (GC-MS) together with 13C stable isotope-labelled glucose and glutamine as metabolic tracers, we probed the phenotypic changes in metabolism following a single copy knock-in of mutant PIK3CA (H1047R) in the MCF10A cell line, an important cell model for studying oncogenic transformation in breast tissues. We observed effects in several metabolic pathways, including a decrease in glycerophosphocholine level together with increases in glutaminolysis, de novo fatty acid synthesis and pyruvate entry into the tricarboxylic acid cycle. Our findings highlight altered glyceroplipid metabolism and lipogenesis, as key metabolic phenotypes of mutant PIK3CA transformation that are recapitulated in the MCF10A cellular model.

Suppression of MTHFD2 in MCF-7 Breast Cancer Cells Increases Glycolysis, Dependency on Exogenous Glycine, and Sensitivity to Folate Depletion.

Methylenetetrahydrofolate dehydrogenase (NAD(P)+ dependent) 2, methenyltetrahydrofolate cyclohydrolase (MTHFD2) is a mitochondrial enzyme involved in folate metabolism. A number of recent studies have highlighted this enzyme as being highly expressed in many solid tumors, including breast cancer, and to be correlated with poor survival. However, the metabolic functions of MTHFD2 in cancer cells have not been well-defined. To investigate the function of MTHFD2 in breast cancer cells, we generated and characterized MCF-7 cells with stable suppression of MTHFD2 expression using a combination of cellular assays and metabolic profiling. Loss of MTHFD2 caused MCF7 cells to become glycine auxotrophs, that is, reliant on exogenous glycine, and more sensitive to exogenous folate depletion. Another prominent metabolic alteration observed as a consequence of MTHFD2 suppression was a more glycolytic phenotype, consistent with widespread modifications of cellular metabolism. Collectively, these data suggest that targeting MTHFD2 activity is likely to influence multiple metabolic pathways in breast cancer and could be combined with a range of antimetabolite therapies.

Choline-releasing glycerophosphodiesterase EDI3 drives tumor cell migration and metastasis.

Metastasis from primary tumors remains a major problem for tumor therapy. In the search for markers of metastasis and more effective therapies, the tumor metabolome is relevant because of its importance to the malignant phenotype and metastatic capacity of tumor cells. Altered choline metabolism is a hallmark of cancer. More specifically, a decreased glycerophosphocholine (GPC) to phosphocholine (PC) ratio was reported in breast, ovarian, and prostate cancers. Improved strategies to exploit this altered choline metabolism are therefore required. However, the critical enzyme cleaving GPC to produce choline, the initial step in the pathway controlling the GPC/PC ratio, remained unknown. In the present work, we have identified the enzyme, here named EDI3 (endometrial differential 3). Purified recombinant EDI3 protein cleaves GPC to form glycerol-3-phosphate and choline. Silencing EDI3 in MCF-7 cells decreased this enzymatic activity, increased the intracellular GPC/PC ratio, and decreased downstream lipid metabolites. Downregulating EDI3 activity inhibited cell migration via disruption of the PKCα signaling pathway, with stable overexpression of EDI3 showing the opposite effect. EDI3 was originally identified in our screening study comparing mRNA levels in metastasizing and nonmetastasizing endometrial carcinomas. Both Kaplan-Meier and multivariate analyses revealed a negative association between high EDI3 expression and relapse-free survival time in both endometrial (P < 0.001) and ovarian (P = 0.029) cancers. Overall, we have identified EDI3, a key enzyme controlling GPC and choline metabolism. Because inhibition of EDI3 activity corrects the GPC/PC ratio and decreases the migration capacity of tumor cells, it represents a possible target for therapeutic intervention.