Publications
33 results found
Lau C-HE, Manou M, Markozannes G, et al., 2023, NMR metabolomic modelling of age and lifespan: a multi-cohort analysis., medRxiv
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.
Robinson O, Lau CE, 2023, How do metabolic processes age: Evidence from human metabolomic studies, Current Opinion in Chemical Biology, Vol: 76, Pages: 1-7, ISSN: 1367-5931
Metabolomics, the global profiling of small molecules in the body, has emerged as a promising analytical approach for assessing molecular changes associated with ageing at the population level. Understanding root metabolic ageing pathways may have important implications for managing age-related disease risk. In this short review, relevant studies published in the last few years that have made valuable contributions to this field will be discussed. These include large-scale studies investigating metabolic changes with age, metabolomic clocks, and metabolic pathways associated with ageing phenotypes. Recent significant advances include the use of longitudinal study designs, populations spanning the whole life course, standardised analytical platforms of enhanced metabolome coverage and development of multivariate analyses. While many challenges remain, recent studies have demonstrated the considerable promise of this field.
Robinson O, Lau C-HE, Joo S, et al., 2023, Associations of four biological age markers with child development: a multi-omic analysis in the European HELIX cohort, eLife, Vol: 12, Pages: 1-30, ISSN: 2050-084X
Background: While biological age in adults is often understood as representing general health and resilience, the conceptual interpretation of accelerated biological age in children and its relationship to development remains unclear. We aimed to clarify the relationship of accelerated biological age, assessed through two established biological age indicators, telomere length and DNA methylation age, and two novel candidate biological age indicators , to child developmental outcomes, including growth and adiposity, cognition, behaviour, lung function and onset of puberty, among European school-age children participating in the HELIX exposome cohort.Methods: The study population included up to 1,173 children, aged between 5 and 12 years, from study centres in the UK, France, Spain, Norway, Lithuania, and Greece. Telomere length was measured through qPCR, blood DNA methylation and gene expression was measured using microarray, and proteins and metabolites were measured by a range of targeted assays. DNA methylation age was assessed using Horvath's skin and blood clock, while novel blood transcriptome and 'immunometabolic' (based on plasma protein and urinary and serum metabolite data) clocks were derived and tested in a subset of children assessed six months after the main follow-up visit. Associations between biological age indicators with child developmental measures as well as health risk factors were estimated using linear regression, adjusted for chronological age, sex, ethnicity and study centre. The clock derived markers were expressed as Δ age (i.e., predicted minus chronological age).Results: Transcriptome and immunometabolic clocks predicted chronological age well in the test set (r= 0.93 and r= 0.84 respectively). Generally, weak correlations were observed, after adjustment for chronological age, between the biological age indicators. Among associations with health risk factors, higher birthweight was associated with greater immunometabolic Δ ag
Fabbri L, Garlantézec R, Audouze K, et al., 2023, Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic profiles: a panel study., Environment International, Vol: 173, Pages: 1-16, ISSN: 0160-4120
BACKGROUND: Individuals are exposed to environmental pollutants with endocrine disrupting activity (endocrine disruptors, EDCs) and the early stages of life are particularly susceptible to these exposures. Previous studies have focused on identifying molecular signatures associated with EDCs, but none have used repeated sampling strategy and integrated multiple omics. We aimed to identify multi-omic signatures associated with childhood exposure to non-persistent EDCs. METHODS: We used data from the HELIX Child Panel Study, which included 156 children aged 6 to 11. Children were followed for one week, in two time periods. Twenty-two non-persistent EDCs (10 phthalate, 7 phenol, and 5 organophosphate pesticide metabolites) were measured in two weekly pools of 15 urine samples each. Multi-omic profiles (methylome, serum and urinary metabolome, proteome) were measured in blood and in a pool urine samples. We developed visit-specific Gaussian Graphical Models based on pairwise partial correlations. The visit-specific networks were then merged to identify reproducible associations. Independent biological evidence was systematically sought to confirm some of these associations and assess their potential health implications. RESULTS: 950 reproducible associations were found among which 23 were direct associations between EDCs and omics. For 9 of them, we were able to find corroborating evidence from previous literature: DEP - serotonin, OXBE - cg27466129, OXBE - dimethylamine, triclosan - leptin, triclosan - serotonin, MBzP - Neu5AC, MEHP - cg20080548, oh-MiNP - kynurenine, oxo-MiNP - 5-oxoproline. We used these associations to explore possible mechanisms between EDCs and health outcomes, and found links to health outcomes for 3 analytes: serotonin and kynurenine in relation to neuro-behavioural development, and leptin in relation to obesity and insulin resistance. CONCLUSIONS: This multi-omics network analysis at two time points identified biologically relevant molecular si
Maitre L, Bustamante M, Hernandez-Ferrer C, et al., 2022, Multi-omics signatures of the human early life exposome, Nature Communications, Vol: 13, Pages: 1-18, ISSN: 2041-1723
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.
Chan Q, Wren G, Lau CH, et al., 2022, Blood pressure interactions with the DASH dietary pattern, sodium, and potassium: The International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP), The American Journal of Clinical Nutrition, Vol: 116, Pages: 216-229, ISSN: 1938-3207
BackgroundAdherence 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.ObjectiveAmong free-living populations, delineate metabolic signatures associated with the DASH diet adherence, 24-hr urinary sodium and potassium excretions and the potential metabolic pathways involved.Design24-hr urinary metabolic profiling by proton nuclear magnetic resonance spectroscopy was used to characterize the metabolic signatures associated with the DASH dietary pattern score (DASH score) and 24-hr excretion of sodium and potassium among participants in the United States (n=2,164) 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.ResultsAdherence to DASH diet was associated with urinary potassium excretion (correlation coefficient, r = 0.42, P<0.0001). In multivariable regression analyses, a five-point higher DASH score (range 7 to 35) was associated with a lower systolic BP by 1.35 mmHg (95% confidence interval: -1.95, -0.80, 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 five metabolites (succinate, alanine, S-methyl cysteine sulfoxide, 4-hydroxyhippurate, phenylacetylglutamine) were found specific to the DASH-BP relation.ConclusionsGreater adherence to DASH diet is associated with lower BP and higher potassium intake across levels of sodium intake. The DASH diet recommends greater intake of fruits, veget
Graca G, Cai Y, Lau C-H, et al., 2022, Automated annotation of untargeted all-ion fragmentation LC-MS metabolomics data with MetaboAnnotatoR, Analytical Chemistry, Vol: 94, Pages: 3446-3455, ISSN: 0003-2700
Untargeted metabolomics and lipidomics LC-MS experiments produce complex datasets, usually containing tens of thousands of features from thousands of metabolites whose annotation requires additional MS/MS experiments and expert knowledge. All-ion fragmentation (AIF) LC-MS/MS acquisition provides fragmentation data at no additional experimental time cost. However, analysis of such datasets requires reconstruction of parent fragment relationships and annotation of the resulting pseudo-MS/MS spectra. Here we propose a novel approach for automated annotation of isotopologues, adducts and in-source fragments from AIF LC-MS datasets by combining correlation-based parent-fragment linking with molecular fragment matching. Our workflow focuses on a subset of features rather than trying to annotate the full dataset, saving time and simplifying the process. We demonstrate the workflow in three human serum datasets containing 599 features manually annotated by experts. Precision and recall values of 82- 92% and 82-85% respectively, were obtained for features found in the highest-rank scores (1-5). These results equal or outperform those obtained using MS-DIAL software, the current state-of-the-art for AIF data annotation. Further validation for other biological matrices and different instrument types showed variable precision (60-89%) and recall (10-88%) particularly for datasets dominated by non-lipid metabolites. The workflow is freely available as an open-source R package, MetaboAnnotatoR, together with the fragment libraries from Github (https://github.com/gggraca/MetaboAnnotatoR).
Stratakis N, Siskos AP, Papadopoulou E, et al., 2022, Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health, eLife, Vol: 11, Pages: 1-20, ISSN: 2050-084X
Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used 1H NMR spectroscopy in a multicountry study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate, N-methylnicotinic acid, urea, and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food consumption and also had higher capacity in discriminating children’s diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.
Handakas E, Lau CH, Alfano R, et al., 2022, A systematic review of metabolomic studies of childhood obesity: State of the evidence for metabolic determinants and consequences, Obesity Reviews, Vol: 23, Pages: 1-13, ISSN: 1467-7881
Childhood obesity has become a global epidemic and carries significant long-term consequences to physical and mental health. Metabolomics, the global profiling of small molecules or metabolites, may reveal the mechanisms of development of childhood obesity and clarify links between obesity and metabolic disease. A systematic review of metabolomic studies of childhood obesity was conducted, following Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, searching across Scopus, Ovid, Web of Science and PubMed databases for articles published from January 1, 2005 to July 8, 2020, retrieving 1271 different records and retaining 41 articles for qualitative synthesis. Study quality was assessed using a modified Newcastle–Ottawa Scale. Thirty-three studies were conducted on blood, six on urine, three on umbilical cord blood, and one on saliva. Thirty studies were primarily cross-sectional, five studies were primarily longitudinal, and seven studies examined effects of weight-loss following a life-style intervention. A consistent metabolic profile of childhood obesity was observed including amino acids (particularly branched chain and aromatic), carnitines, lipids, and steroids. Although the use of metabolomics in childhood obesity research is still developing, the identified metabolites have provided additional insight into the pathogenesis of many obesity-related diseases. Further longitudinal research is needed into the role of metabolic profiles and child obesity risk.
Stratakis N, Siskos AP, Papadopoulou E, et al., 2021, Author response: Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health
Stratakis N, Siskos AP, Papadopoulou E, et al., 2021, Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health
<jats:title>Abstract</jats:title><jats:p>Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used<jats:sup>1</jats:sup>H-NMR spectroscopy in a multi-country study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate,<jats:italic>N</jats:italic>-methylnicotinic acid, urea and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food (UPF) consumption and also had higher capacity in discriminating children’s diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.</jats:p>
Gallego-Paüls M, Hernández-Ferrer C, Bustamante M, et al., 2021, Variability of multi-omics profiles in a population-based child cohort., BMC Medicine, Vol: 19, Pages: 1-16, ISSN: 1741-7015
BACKGROUND: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. METHODS: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. RESULTS: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. CONCLUSIONS: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.
Robinson O, Lau C, 2021, DNA methylation age as a biomarker for cancer, International Journal of Cancer, Vol: 148, Pages: 2652-2663, ISSN: 0020-7136
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.
Robinson O, Carter AR, Aola-Korpela M, et al., 2021, Metabolic profiles of socioeconomic position: a multi-cohort analysis, International Journal of Epidemiology, Vol: 50, Pages: 768-782, ISSN: 0300-5771
BackgroundLow socioeconomic position (SEP) is a risk factor for multiple health outcomes, but its molecular imprints in the body remain unclear. MethodsWe examined SEP as a determinant of serum nuclear magnetic resonance metabolic profiles, in approximately 30,000 adults and 4,000 children across ten UK and Finnish cohort studies. ResultsIn risk factor-adjusted analysis of 233 metabolic measures, low educational attainment was associated with 37 measures including higher levels of triglycerides in small high-density lipoproteins (HDL) and lower levels of docosahexaenoic acid (DHA), omega-3 fatty acids, apolipoprotein A1, large and very large HDL particles (including levels of their respective lipid constituents), and cholesterol measures across different density lipoproteins. Among adults whose father worked in manual occupations, associations with apolipoprotein A1, large and very large HDL particles and HDL-2 cholesterol remained after adjustment for SEP in later life. Among manual workers, levels of glutamine were higher compared to non-manual workers. All three indicators of low SEP were associated with lower DHA, omega-3 fatty acids and HDL diameter. At all ages, children of manual workers had lower levels of DHA as a proportion of total fatty acids.ConclusionsOur work indicates that social and economic factors have a measurable impact on human physiology. Lower SEP was independently associated with a generally unfavorable metabolic profile, consistent across ages and cohorts. The metabolites we found associated with SEP, including DHA, are known to predict cardiovascular disease and cognitive decline in later life and may contribute to health inequalities.
Maitre L, Bustamante M, Hernández-Ferrer C, et al., 2021, Multi-omics signatures of the human early life exposome
<jats:title>Summary</jats:title><jats:p>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 1,301 mother-child pairs, we associated individual exposomes consisting of >100 chemical, physical and lifestyle exposures assessed in pregnancy and childhood, with multi-omics profiles (methylome, transcriptome, metabolome and proteins) in childhood. We identified 1,170 associations, 249 in pregnancy and 921 in childhood, which revealed potential biological responses and sources of exposure. The methylome best captures the persistent influence of pregnancy exposures, including maternal smoking; while childhood exposures were associated with features from all omics layers, revealing novel signatures for indoor air quality, essential trace elements, endocrine disruptors and weather conditions. This study provides a unique resource (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://helixomics.isglobal.org/">https://helixomics.isglobal.org/</jats:ext-link>) to guide future investigation on the biological effects of the early life exposome.</jats:p>
Lau CH, Taylor-Bateman V, Vorkas PA, et al., 2020, Metabolic signatures of gestational weight gain and postpartum weight loss in a lifestyle intervention study of overweight and obese women, Metabolites, Vol: 10, ISSN: 2218-1989
BACKGROUND: Overweight and obesity amongst women of reproductive age are increasingly common in developed economies and are shown to adversely affect birth outcomes and both childhood and adulthood health risks in the offspring. Metabolic profiling in conditions of overweight and obesity in pregnancy could potentially be applied to elucidate the molecular basis of the adverse effects of gestational weight gain (GWG) and postpartum weight loss (WL) on future risks for cardiovascular disease (CVD) and other chronic diseases. METHODS: Biofluid samples were collected from 114 ethnically diverse pregnant women with body mass index (BMI) between 25 and 40 kg/m2 from Chicago (US), as part of a randomized lifestyle intervention trial (Maternal Offspring Metabolics: Family Intervention Trial; NCT01631747). At 15 weeks, 35 weeks of gestation, and at 1 year postpartum, the blood plasma lipidome and metabolic profile of urine samples were analyzed by liquid chromatography mass spectrometry (LC-MS) and 1H nuclear magnetic resonance spectroscopy (1H NMR) respectively. RESULTS: Urinary 4-deoxyerythronic acid and 4-deoxythreonic acid were found to be positively correlated to BMI. Seventeen plasma lipids were found to be associated with GWG and 16 lipids were found to be associated with WL, which included phosphatidylinositols (PI), phosphatidylcholines (PC), lysophospholipids (lyso-), sphingomyelins (SM) and ether phosphatidylcholine (PC-O). Three phospholipids found to be positively associated with GWG all contained palmitate side-chains, and amongst the 14 lipids that were negatively associated with GWG, seven were PC-O. Six of eight lipids found to be negatively associated with WL contained an 18:2 fatty acid side-chain. CONCLUSIONS: Maternal obesity was associated with characteristic urine and plasma metabolic phenotypes, and phospholipid profile was found to be associated with both GWG and postpartum WL in metabolically healthy pregnant women with overweight/obesity. Postpartu
Calvo-Serra B, Maitre L, Lau C-HE, et al., 2020, Urinary metabolite quantitative trait loci in children and their interaction with dietary factors, Human Molecular Genetics, Vol: 29, Pages: 3830-3844, ISSN: 0964-6906
Human metabolism is influenced by genetic and environmental factors. Previous studies have identified over 23 loci associated with more than 26 urine metabolites levels in adults, which are known as urinary metabolite quantitative trait loci (metabQTLs). The aim of the present study is the identification for the first time of urinary metabQTLs in children and their interaction with dietary patterns. Association between genome-wide genotyping data and 44 urine metabolite levels measured by proton nuclear magnetic resonance spectroscopy was tested in 996 children from the Human Early Life Exposome project. Twelve statistically significant urine metabQTLs were identified, involving 11 unique loci and 10 different metabolites. Comparison with previous findings in adults revealed that six metabQTLs were already known, and one had been described in serum and three were involved the same locus as other reported metabQTLs but had different urinary metabolites. The remaining two metabQTLs represent novel urine metabolite-locus associations, which are reported for the first time in this study [single nucleotide polymorphism (SNP) rs12575496 for taurine, and the missense SNP rs2274870 for 3-hydroxyisobutyrate]. Moreover, it was found that urinary taurine levels were affected by the combined action of genetic variation and dietary patterns of meat intake as well as by the interaction of this SNP with beverage intake dietary patterns. Overall, we identified 12 urinary metabQTLs in children, including two novel associations. While a substantial part of the identified loci affected urinary metabolite levels both in children and in adults, the metabQTL for taurine seemed to be specific to children and interacted with dietary patterns.
Calvo B, Lau CH, Siskos A, et al., 2020, Identification of urinary metabolite quantitative trait loci in children and their interaction with dietary factors, Publisher: SPRINGERNATURE, Pages: 728-729, ISSN: 1018-4813
Robinson O, Lau C, 2020, Measuring biological age using metabolomics, Aging, Vol: 12, Pages: 22352-22353, ISSN: 1945-4589
Robinson O, 2020, In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children, BMC Medicine, Vol: 18, Pages: 1-19, ISSN: 1741-7015
BackgroundThe 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.MethodsWe 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.ResultsMaternal 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.ConclusionIn 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
Wilson I, Dargue R, Zia R, et al., 2020, Metabolism and effects on endogenous metabolism of paracetamol (acetaminophen) in a porcine model of liver failure, Toxicological Sciences, Vol: 175, Pages: 87-97, ISSN: 1096-0929
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). Anaesthetized 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 0.5-4g/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 methaemoglobinemia 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 hydrolysed 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 e.g., the rat and dog which are the pre-clinical species normally employed for safety assessment.
Graca G, Lau C-HE, Goncalves LG, 2020, Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics, TUMOR MICROENVIRONMENT: THE MAIN DRIVER OF METABOLIC ADAPTATION, Vol: 1219, Pages: 367-385, ISSN: 0065-2598
- Author Web Link
- Cite
- Citations: 7
Gibson R, Lau C, Loo RL, et al., 2019, The association of fish consumption and its urinary metabolites with cardiovascular risk factors: The International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP), American Journal of Clinical Nutrition, Vol: 111, Pages: 280-290, ISSN: 0002-9165
BackgroundResults from observational studies regarding associations between fish (including shellfish) intake and cardiovascular disease risk factors, including blood pressure (BP) and BMI, are inconsistent.ObjectiveTo investigate associations of fish consumption and associated urinary metabolites with BP and BMI in free-living populations.MethodsWe used cross-sectional data from the International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP), including 4680 men and women (40–59 y) from Japan, China, the United Kingdom, and United States. Dietary intakes were assessed by four 24-h dietary recalls and BP from 8 measurements. Urinary metabolites (2 timed 24-h urinary samples) associated with fish intake acquired from NMR spectroscopy were identified. Linear models were used to estimate BP and BMI differences across categories of intake and per 2 SD higher intake of fish and its biomarkers.ResultsNo significant associations were observed between fish intake and BP. There was a direct association with fish intake and BMI in the Japanese population sample (P trend = 0.03; fully adjusted model). In Japan, trimethylamine-N-oxide (TMAO) and taurine, respectively, demonstrated area under the receiver operating characteristic curve (AUC) values of 0.81 and 0.78 in discriminating high against low fish intake, whereas homarine (a metabolite found in shellfish muscle) demonstrated an AUC of 0.80 for high/nonshellfish intake. Direct associations were observed between urinary TMAO and BMI for all regions except Japan (P < 0.0001) and in Western populations between TMAO and BP (diastolic blood pressure: mean difference 1.28; 95% CI: 0.55, 2.02 mmHg; P = 0.0006, systolic blood pressure: mean difference 1.67; 95% CI: 0.60, 2.73 mmHg; P = 0.002).ConclusionsUrinary TMAO showed a stronger association with fish intake in the Japanese compared with the Western population sample. Urinary TMAO was directly associated with BP in the Western but not the Japanese popula
Lau CH, Siskos AP, Maitre L, et al., 2018, Determinants of the urinary and serum metabolome in children from six European populations, BMC Medicine, Vol: 16, ISSN: 1741-7015
BackgroundEnvironment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment–health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project (http://www.projecthelix.eu).MethodsMetabolic phenotypes of matched urine and serum samples from 1192 children (aged 6–11) recruited from birth cohorts in six European countries were measured using high-throughput 1H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit).ResultsWe identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythronic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of
Maitre L, de Bont J, Casas M, et al., 2018, Human Early Life Exposome (HELIX) study: a European population-based exposome cohort, BMJ Open, Vol: 8, ISSN: 2044-6055
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 molecul
Athersuch TJ, Lau CH, Behrends V, et al., 2018, CHAPTER 13: NMR Spectroscopy of Cell Culture, Tissues, and Other Biofluids, New Developments in NMR, Pages: 324-359, ISBN: 9781788011044
NMR spectroscopy can provide a wealth of information on cellular metabolism and is frequently used in metabolomics application that use cultured cells, tissues, and whole organisms. Central to these analyses are the protocols for sample harvest, which incorporate procedures for quenching metabolic processes to preserve samples in a state that is representative of their source. In this chapter, the main considerations are discussed with reference to literature exemplars. In the latter half of the chapter, less commonly studied biofluids that also have specific sample preparation requirements are discussed, with a focus on cerebrospinal fluid, faeces, bile, seminal fluid, and milk.
Maitre L, Lau C-HE, Vizcaino E, et al., 2017, Assessment of metabolic phenotypic variability in children's urine using H-1 NMR spectroscopy, Scientific Reports, Vol: 7, ISSN: 2045-2322
The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8–9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.
Lau C-HE, Tredwell GD, Ellis JK, et al., 2017, Metabolomic characterisation of the effects of oncogenic PIK3CA transformation in a breast epithelial cell line, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
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.
Itkonen HM, Brown M, Urbanucci A, et al., 2017, Lipid degradation promotes prostate cancer cell survival, ONCOTARGET, Vol: 8, Pages: 38264-38275, ISSN: 1949-2553
Prostate cancer is the most common male cancer and androgen receptor (AR) is the major driver of the disease. Here we show that Enoyl-CoA delta isomerase 2 (ECI2) is a novel AR-target that promotes prostate cancer cell survival. Increased ECI2 expression predicts mortality in prostate cancer patients (p = 0.0086). ECI2 encodes for an enzyme involved in lipid metabolism, and we use multiple metabolite profiling platforms and RNA-seq to show that inhibition of ECI2 expression leads to decreased glucose utilization, accumulation of fatty acids and down-regulation of cell cycle related genes. In normal cells, decrease in fatty acid degradation is compensated by increased consumption of glucose, and here we demonstrate that prostate cancer cells are not able to respond to decreased fatty acid degradation. Instead, prostate cancer cells activate incomplete autophagy, which is followed by activation of the cell death response. Finally, we identified a clinically approved compound, perhexiline, which inhibits fatty acid degradation, and replicates the major findings for ECI2 knockdown. This work shows that prostate cancer cells require lipid degradation for survival and identifies a small molecule inhibitor with therapeutic potential.
Koufaris C, Gallage S, Yang T, et al., 2016, Suppression of MTHFD2 in MCF-7 Breast Cancer Cells Increases Glycolysis, Dependency on Exogenous Glycine, and Sensitivity to Folate Depletion, Journal of Proteome Research, Vol: 15, Pages: 2618-2625, ISSN: 1535-3907
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.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.