Alcohol-induced metabolomic differences in humans

Chronic alcohol and nicotine consumption as catalyst for systemic inflammatory storm and bone destruction in apical periodontitis

AIM

To assess the periapical alveolar bone pattern and the serum levels of proinflammatory cytokines, biochemical markers and metabolites in rats subjected to chronic alcohol and nicotine consumption and induced apical periodontitis.

METHODOLOGY

Twenty-eight male Wistar rats were divided into four groups: Control, Alcohol, Nicotine and Alcohol+Nicotine. The alcohol groups were exposed to self-administration of a 25% alcohol solution, while the other groups were given only filtered water. The nicotine groups received daily intraperitoneal injections of a nicotine solution (0.19 μL of nicotine/mL), whereas the other groups received saline solution. Periapical lesions were induced by exposing the pulps of the left mandibular first molars for 28 days. After euthanasia, the mandibles were removed and the percentage bone volume, bone mineral density, trabecular thickness, trabecular separation and trabecular number of the periapical bone were measured using micro-computed tomography images. Serum samples were collected for analysis of proinflammatory cytokines (IL-1β, IL-4, IL-6 and TNF-α), biochemical and metabolomic analysis. Statistical analysis was performed with a significance level of 5%. Nonparametric data were analysed using the Kruskal-Wallis test followed by Dunn's test, while one-way anova followed by Tukey's test was performed for parametric data.

RESULTS

The groups exposed to alcohol or nicotine consumption exhibited an altered bone pattern indicating lower bone density and higher levels of IL-1β, IL-6 and TNF-α compared to the Control group (p < .05). Significant differences were observed among the groups in the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase, cholesterol, triglycerides, urea, creatinine, albumin, uric acid, bilirubin and calcium. Metabolomic analysis revealed significant differences in glycine, phosphocholine, lysine, lactate, valine, pyruvate and lipids (CH2 CH2 CO), n(CH2 ) and n(CH3 ). Most of these parameters were even more altered in the simultaneous consumption of both substances compared to single consumption.

CONCLUSION

Alcohol and nicotine chronic consumption altered several metabolic markers, impaired liver and kidney function, increased the production of systemic proinflammatory mediators and harmed the periapical bone microarchitecture in the presence of apical periodontitis. The simultaneous consumption of alcohol and nicotine intensified these detrimental effects.

Novel insight into the lipid network of plasma extracellular vesicles reveal sex-based differences in the lipidomic profile of alcohol use disorder patients

BACKGROUND

Alcohol use disorder (AUD) is one of the most common psychiatric disorders, with the consumption of alcohol considered a leading cause of preventable deaths worldwide. Lipids play a crucial functional role in cell membranes; however, we know little about the role of lipids in extracellular vesicles (EVs) as regulatory molecules and disease biomarkers.

METHODS

We employed a sensitive lipidomic strategy to characterize lipid species from the plasma EVs of AUD patients to evaluate functional roles and enzymatic activity networks to improve the knowledge of lipid metabolism after alcohol consumption. We analyzed plasma EV lipids from AUD females and males and healthy individuals to highlight lipids with differential abundance and biologically interpreted lipidomics data using LINEX2, which evaluates enzymatic dysregulation using an enrichment algorithm.

RESULTS

Our results show, for the first time, that AUD females exhibited more significant substrate-product changes in lysophosphatidylcholine/phosphatidylcholine lipids and phospholipase/acyltransferase activity, which are potentially linked to cancer progression and neuroinflammation. Conversely, AUD males suffer from dysregulated ceramide and sphingomyelin lipids involving sphingomyelinase, sphingomyelin phosphodiesterase, and sphingomyelin synthase activity, which relates to hepatotoxicity. Notably, the analysis of plasma EVs from AUD females and males demonstrates enrichment of lipid ontology terms associated with "negative intrinsic curvature" and "positive intrinsic curvature", respectively.

CONCLUSIONS

Our methodological developments support an improved understanding of lipid metabolism and regulatory mechanisms, which contribute to the identification of novel lipid targets and the discovery of sex-specific clinical biomarkers in AUD.

Alcohol use associated alterations in the circulating metabolite profile in the general population and in individuals with major depressive disorder

Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in persons with depression. If so, these findings could partially explain the link between alcohol use and depression. We applied a targeted liquid chromatography mass spectrometry method to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the non-depressed general population (GP) (n = 247) and a cohort of individuals with major depressive disorder (MDD) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of hippuric acid in the GP cohort. In the GP cohort, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the MDD cohort, but in these individuals it was regardless of their level of alcohol use. Reduced serum concentrations of hippuric acid suggest that already moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and depression.

Circulating metabolites may illustrate relationship of alcohol consumption with cardiovascular disease

BACKGROUND

Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD.

METHODS

Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine, and liquor on average of 19 years in 2428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure).

RESULTS

We identified 60 metabolites associated with cumulative average alcohol consumption (p < 0.05/211 ≈ 0.00024). For example, 1 g/day increase of alcohol consumption was associated with higher levels of cholesteryl esters (e.g., CE 16:1, beta = 0.023 ± 0.002, p = 6.3e - 45) and phosphatidylcholine (e.g., PC 32:1, beta = 0.021 ± 0.002, p = 3.1e - 38). Survival analysis identified that 10 alcohol-associated metabolites were also associated with a differential CVD risk after adjusting for age, sex, and batch. Further, we built two alcohol consumption weighted metabolite scores using these 10 metabolites and showed that, with adjustment age, sex, batch, and common CVD risk factors, the two scores had comparable but opposite associations with incident CVD, hazard ratio 1.11 (95% CI = [1.02, 1.21], p = 0.02) vs 0.88 (95% CI = [0.78, 0.98], p = 0.02).

CONCLUSIONS

We identified 60 long-term alcohol consumption-associated metabolites. The association analysis with incident CVD suggests a complex metabolic basis between alcohol consumption and CVD.

Higher Plasma Creatinine Is Associated with an Increased Risk of Death in Patients with Non-Metastatic Rectal but Not Colon Cancer: Results from an International Cohort Consortium

Colorectal cancer (CRC) is increasingly recognized as a heterogeneous disease. No studies have prospectively examined associations of blood metabolite concentrations with all-cause mortality in patients with colon and rectal cancer separately. Targeted metabolomics (Biocrates AbsoluteIDQ p180) and pathway analyses (MetaboAnalyst 4.0) were performed on pre-surgery collected plasma from 674 patients with non-metastasized (stage I-III) colon (n = 394) or rectal cancer (n = 283). Metabolomics data and covariate information were received from the international cohort consortium MetaboCCC. Cox proportional hazards models were computed to investigate associations of 148 metabolite levels with all-cause mortality adjusted for age, sex, tumor stage, tumor site (whenever applicable), and cohort; the false discovery rate (FDR) was used to account for multiple testing. A total of 93 patients (14%) were deceased after an average follow-up time of 4.4 years (60 patients with colon cancer and 33 patients with rectal cancer). After FDR adjustment, higher plasma creatinine was associated with a 39% increase in all-cause mortality in patients with rectal cancer. HR: 1.39, 95% CI 1.23-1.72, pFDR = 0.03; but not colon cancer: pFDR = 0.96. Creatinine is a breakdown product of creatine phosphate in muscle and may reflect changes in skeletal muscle mass. The starch and sucrose metabolisms were associated with increased all-cause mortality in colon cancer but not in rectal cancer. Genes in the starch and sucrose metabolism pathways were previously linked to worse clinical outcomes in CRC. In summary, our findings support the hypothesis that colon and rectal cancer have different etiological and clinical outcomes that need to be considered for targeted treatments.

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts

BACKGROUND

Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways.

METHODS

We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed.

RESULTS

We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism.

CONCLUSION

Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.

Circulating Metabolites May Illustrate Relationship of Alcohol Consumption with Cardiovascular Disease

Background

Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD.

Methods

Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine and liquor on average of 19 years in 2,428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure).

Results

We identified 60 metabolites associated with cumulative average alcohol consumption (p<0.05/211≈0.00024). For example, one g/day increase of alcohol consumption was associated with higher levels of cholesteryl esters (e.g., CE 16:1, beta=0.023±0.002, p=6.3e-45) and phosphatidylcholine (e.g., PC 32:1, beta=0.021±0.002, p=3.1e-38). Survival analysis identified that 10 alcohol-associated metabolites were also associated with a differential CVD risk after adjusting for age, sex, and batch. Further, we built two alcohol consumption weighted metabolite scores using these 10 metabolites and showed that, with adjustment age, sex, batch, and common CVD risk factors, the two scores had comparable but opposite associations with incident CVD, hazard ratio 1.11(95% CI=[1.02, 1.21],p=0.02) vs 0.88 (95% CI=[0.78, 0.98], p=0.02).

Summary

We identified 60 long-term alcohol consumption-associated metabolites. The association analysis with incident CVD suggests a complex metabolic basis between alcohol consumption and CVD.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Metabolic signature of HepaRG cells exposed to ethanol and tumor necrosis factor alpha to study alcoholic steatohepatitis by LC-MS-based untargeted metabolomics

Despite the high prevalence of alcoholic liver disease, its identification and characterization remain poor, especially in early stages such as alcoholic fatty liver disease and alcoholic steatohepatitis. This latter implies diagnostic difficulties, few therapeutic options and unclear mechanisms of action. To elucidate the metabolic alterations and pinpoint affected biochemical pathways, alcoholic steatohepatitis was simulated in vitro by exposing HepaRG cells to ethanol (IC₁₀, 368 mM) and tumor necrosis factor alpha (TNF-α, 50 ng/mL) for 24 h. This combined exposure was compared to solely ethanol-exposed as well as -nonexposed cells. Four different metabolomics platforms were used combining liquid chromatography, high-resolution mass spectrometry and drift tube ion mobility to elucidate both intracellular and extracellular metabolic alterations. Some of the key findings include the influence of TNF-α in the upregulation of hepatic triglycerides and the downregulation of hepatic phosphatidylethanolamines and phosphatidylcholines. S-Adenosylmethionine showed to play a central role in the progression of alcoholic steatohepatitis. In addition, fatty acyl esters of hydroxy fatty acid (FAHFA)-containing triglycerides were detected for the first time in human hepatocytes and their alterations showed a potentially important role during the progression of alcoholic steatohepatitis. Ethoxylated phosphorylcholine was identified as a potential new biomarker of ethanol exposure.

Untargeted Metabolome Analysis of Alcohol-Exposed Pregnancies Reveals Metabolite Differences That Are Associated with Infant Birth Outcomes

Prenatal alcohol exposure can produce offspring growth deficits and is a leading cause of neurodevelopmental disability. We used untargeted metabolomics to generate mechanistic insight into how alcohol impairs fetal development. In the Western Cape Province of South Africa, 52 women between gestational weeks 5-36 (mean 18.5 ± 6.5) were recruited, and they provided a finger-prick fasting bloodspot that underwent mass spectrometry. Metabolomic data were analyzed using partial least squares-discriminant analyses (PLS-DA) to identify metabolites that correlated with alcohol exposure and infant birth outcomes. Women who consumed alcohol in the past seven days were distinguished by a metabolite profile that included reduced sphingomyelins, cholesterol, and pregnenolones, and elevated fatty acids, acyl and amino acyl carnitines, and androsterones. Using PLS-DA, 25 of the top 30 metabolites differentiating maternal groups were reduced by alcohol with medium-chain free fatty acids and oxidized sugar derivatives having the greatest influence. A separate ortho-PLS-DA analysis identified a common set of 13 metabolites that were associated with infant length, weight, and head circumference. These included monoacylglycerols, glycerol-3-phosphate, and unidentified metabolites, and most of their associations were negative, implying they represent processes having adverse consequences for fetal development.

Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer

Three metabolite patterns have previously shown prospective inverse associations with the risk of aggressive prostate cancer within the European Prospective Investigation into Cancer and Nutrition (EPIC). Here, we investigated dietary and lifestyle correlates of these three prostate cancer-related metabolite patterns, which included: 64 phosphatidylcholines and three hydroxysphingomyelins (Pattern 1), acylcarnitines C18:1 and C18:2, glutamate, ornithine, and taurine (Pattern 2), and 8 lysophosphatidylcholines (Pattern 3). In a two-stage cross-sectional discovery (n = 2524) and validation (n = 518) design containing 3042 men free of cancer in EPIC, we estimated the associations of 24 dietary and lifestyle variables with each pattern and the contributing individual metabolites. Associations statistically significant after both correction for multiple testing (False Discovery Rate = 0.05) in the discovery set and at p < 0.05 in the validation set were considered robust. Intakes of alcohol, total fish products, and its subsets total fish and lean fish were positively associated with Pattern 1. Body mass index (BMI) was positively associated with Pattern 2, which appeared to be driven by a strong positive BMI-glutamate association. Finally, both BMI and fatty fish were inversely associated with Pattern 3. In conclusion, these results indicate associations of fish and its subtypes, alcohol, and BMI with metabolite patterns that are inversely associated with risk of aggressive prostate cancer.

Metabolic Signatures of Healthy Lifestyle Patterns and Colorectal Cancer Risk in a European Cohort

BACKGROUND & AIMS

Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort.

METHODS

Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression.

RESULTS

Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants.

CONCLUSIONS

Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.

Metabolic Signature of Ethanol-Induced Hepatotoxicity in HepaRG Cells by Liquid Chromatography-Mass Spectrometry-Based Untargeted Metabolomics

Alcoholic liver disease is highly prevalent but poorly identified and characterized, leading to knowledge gaps, which impairs early diagnosis. Excessive alcohol consumption is known to alter lipid metabolism, followed by progressive intracellular lipid accumulation, resulting in alcoholic fatty liver disease. In this study, HepaRG cells were exposed to ethanol at IC₁₀ and 1/10 IC₁₀ for 24 and 48 h. Metabolic alterations were investigated intra- and extracellularly with liquid chromatography-high-resolution mass spectrometry. Ion mobility was added as an extra separation dimension for untargeted lipidomics to improve annotation confidence. Distinctive patterns between exposed and control cells were consistently observed, with intracellular upregulation of di- and triglycerides, downregulation of phosphatidylcholines and phosphatidylethanolamines, sphingomyelins, and S-adenosylmethionine, among others. Several intracellular metabolic patterns could be related to changes in the extracellular environment, such as increased intracellular hydrolysis of sphingomyelins, leading to increased phosphorylcholine secretion. Carnitines showed alterations depending on the size of their carbon chain, which highlights the interplay between β-oxidation in mitochondria and peroxisomes. Potential new biomarkers of ethanol-induced hepatotoxicity have been observed, such as ceramides with a sphingadienine backbone, octanoylcarnitine, creatine, acetylcholine, and ethoxylated phosphorylcholine. The combination of the metabolic fingerprint and footprint enabled a comprehensive investigation of the pathophysiology behind ethanol-induced hepatotoxicity.

Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort

BACKGROUND

Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2).

METHODS

To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786).

RESULTS

For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed.

CONCLUSIONS

These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.

Novel Biomarkers of Habitual Alcohol Intake and Associations With Risk of Pancreatic and Liver Cancers and Liver Disease Mortality

BACKGROUND

Alcohol is an established risk factor for several cancers, but modest alcohol-cancer associations may be missed because of measurement error in self-reported assessments. Biomarkers of habitual alcohol intake may provide novel insight into the relationship between alcohol and cancer risk.

METHODS

Untargeted metabolomics was used to identify metabolites correlated with self-reported habitual alcohol intake in a discovery dataset from the European Prospective Investigation into Cancer and Nutrition (EPIC; n = 454). Statistically significant correlations were tested in independent datasets of controls from case-control studies nested within EPIC (n = 280) and the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC; n = 438) study. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations of alcohol-associated metabolites and self-reported alcohol intake with risk of pancreatic cancer, hepatocellular carcinoma (HCC), liver cancer, and liver disease mortality in the contributing studies.

RESULTS

Two metabolites displayed a dose-response association with self-reported alcohol intake: 2-hydroxy-3-methylbutyric acid and an unidentified compound. A 1-SD (log2) increase in levels of 2-hydroxy-3-methylbutyric acid was associated with risk of HCC (OR = 2.54, 95% CI = 1.51 to 4.27) and pancreatic cancer (OR = 1.43, 95% CI = 1.03 to 1.99) in EPIC and liver cancer (OR = 2.00, 95% CI = 1.44 to 2.77) and liver disease mortality (OR = 2.16, 95% CI = 1.63 to 2.86) in ATBC. Conversely, a 1-SD (log2) increase in questionnaire-derived alcohol intake was not associated with HCC or pancreatic cancer in EPIC or liver cancer in ATBC but was associated with liver disease mortality (OR = 2.19, 95% CI = 1.60 to 2.98) in ATBC.

CONCLUSIONS

2-hydroxy-3-methylbutyric acid is a candidate biomarker of habitual alcohol intake that may advance the study of alcohol and cancer risk in population-based studies.

Changes in the metabolic profile of human male postmortem frontal cortex and cerebrospinal fluid samples associated with heavy alcohol use

Heavy alcohol use is one of the top causes of disease and death in the world. The brain is a key organ affected by heavy alcohol use. Here, our aim was to measure changes caused by heavy alcohol use in the human brain metabolic profile. We analyzed human postmortem frontal cortex and cerebrospinal fluid (CSF) samples from males with a history of heavy alcohol use (n = 74) and controls (n = 74) of the Tampere Sudden Death Series cohort. We used a nontargeted liquid chromatography mass spectrometry-based metabolomics method. We observed differences between the study groups in the metabolite levels of both frontal cortex and CSF samples, for example, in amino acids and derivatives, and acylcarnitines. There were more significant alterations in the metabolites of frontal cortex than in CSF. In the frontal cortex, significant alterations were seen in the levels of neurotransmitters (e.g., decreased levels of GABA and acetylcholine), acylcarnitines (e.g., increased levels of acylcarnitine 4:0), and in some metabolites associated with alcohol metabolizing enzymes (e.g., increased levels of 2-piperidone). Some of these changes were also significant in the CSF samples (e.g., elevated 2-piperidone levels). Overall, these results show the metabolites associated with neurotransmitters, energy metabolism and alcohol metabolism, were altered in human postmortem frontal cortex and CSF samples of persons with a history of heavy alcohol use.

Effect of intravenous ghrelin administration, combined with alcohol, on circulating metabolome in heavy drinking individuals with alcohol use disorder

BACKGROUND

Ghrelin may influence several alcohol-related behaviors in animals and humans by modulating central and/or peripheral biological pathways. The aim of this exploratory analysis was to investigate associations between ghrelin administration and the human circulating metabolome during alcohol exposure in nontreatment seeking, heavy drinking individuals with alcohol use disorder (AUD).

METHODS

We used serum samples from a randomized, crossover, double-blind, placebo-controlled human laboratory study with intravenous (IV) ghrelin or placebo infusion in two experiments. During each session, participants received a loading dose (3 µg/kg) followed by continuous infusion (16.9 ng/kg/min) of acyl ghrelin or placebo. The first experiment included an IV alcohol self-administration (IV-ASA) session and the second experiment included an IV alcohol clamp (IV-AC) session, both with the counterbalanced infusion of ghrelin or placebo. Serum metabolite profiles were analyzed from repeated blood samples collected during each session.

RESULTS

In both experiments, ghrelin infusion was associated with an altered serum metabolite profile, including significantly increased levels of cortisol (IV-ASA q-value = 0.0003 and IV-AC q < 0.0001), corticosterone (IV-ASA q = 0.0202 and IV-AC q < 0.0001), and glycochenodeoxycholic acid (IV-ASA q = 0.0375 and IV-AC q = 0.0013). In the IV-ASA experiment, ghrelin infusion increased levels of cortisone (q = 0.0352) and fatty acids 18:1 (q = 0.0406) and 18:3 (q = 0.0320). Moreover, in the IV-AC experiment, ghrelin infusion significantly increased levels of glycocholic acid (q < 0.0001) and phenylalanine (q = 0.0458).

CONCLUSION

IV ghrelin infusion, combined with IV alcohol administration, was associated with increases in the circulating metabolite levels of corticosteroids and glycine-conjugated bile acids, among other changes. Further research is needed to understand the role that metabolomic changes play in the complex interaction between ghrelin and alcohol.

Investigation of circulating metabolites associated with breast cancer risk by untargeted metabolomics: a case-control study nested within the French E3N cohort

BACKGROUND

Perturbations in circulating metabolites prior to a breast cancer diagnosis are not well characterised. We aimed to gain more detailed knowledge to help understand and prevent the disease.

METHODS

Baseline plasma samples from 791 breast cancer cases and 791 matched controls from the E3N (EPIC-France) cohort were profiled by nuclear magnetic resonance (NMR)-based untargeted metabolomics. Partial least-squares discriminant analysis (PLS-DA) models were built from NMR profiles to predict disease outcome, and odds ratios and false discovery rate (FDR)-adjusted CIs were calculated for 43 identified metabolites by conditional logistic regression.

RESULTS

Breast cancer onset was predicted in the premenopausal subgroup with modest accuracy (AUC 0.61, 95% CI: 0.49-0.73), and 10 metabolites associated with risk, particularly histidine (OR = 1.70 per SD increase, FDR-adjusted CI 1.19-2.41), N-acetyl glycoproteins (OR = 1.53, FDR-adjusted CI 1.18-1.97), glycerol (OR = 1.55, FDR-adjusted CI 1.11-2.18) and ethanol (OR = 1.44, FDR-adjusted CI 1.05-1.97). No predictive capacity or significant metabolites were found overall or for postmenopausal women.

CONCLUSIONS

Perturbed metabolism compared to controls was observed in premenopausal but not postmenopausal cases. Histidine and NAC have known involvement in inflammatory pathways, and the robust association of ethanol with risk suggests the involvement of alcohol intake.

A Pilot Metabolomic Study on Myocardial Injury Caused by Chronic Alcohol Consumption-Alcoholic Cardiomyopathy

Chronic alcohol consumption leads to myocardial injury, ventricle dilation, and cardiac dysfunction, which is defined as alcoholic cardiomyopathy (ACM). To explore the induced myocardial injury and underlying mechanism of ACM, the Liber-DeCarli liquid diet was used to establish an animal model of ACM and histopathology, echocardiography, molecular biology, and metabolomics were employed. Hematoxylin-eosin and Masson's trichrome staining revealed disordered myocardial structure and local fibrosis in the ACM group. Echocardiography revealed thinning wall and dilation of the left ventricle and decreased cardiac function in the ACM group, with increased serum levels of brain natriuretic peptide (BNP) and expression of myocardial BNP mRNA measured through enzyme-linked immunosorbent assay and real-time quantitative polymerase chain reaction (PCR), respectively. Through metabolomic analysis of myocardium specimens, 297 differentially expressed metabolites were identified which were involved in KEGG pathways related to the biosynthesis of unsaturated fatty acids, vitamin digestion and absorption, oxidative phosphorylation, pentose phosphate, and purine and pyrimidine metabolism. The present study demonstrated chronic alcohol consumption caused disordered cardiomyocyte structure, thinning and dilation of the left ventricle, and decreased cardiac function. Metabolomic analysis of myocardium specimens and KEGG enrichment analysis further demonstrated that several differentially expressed metabolites and pathways were involved in the ACM group, which suggests potential causes of myocardial injury due to chronic alcohol exposure and provides insight for further research elucidating the underlying mechanisms of ACM.

Multi-omics integration in biomedical research - A metabolomics-centric review

Recent advances in high-throughput technologies have enabled the profiling of multiple layers of a biological system, including DNA sequence data (genomics), RNA expression levels (transcriptomics), and metabolite levels (metabolomics). This has led to the generation of vast amounts of biological data that can be integrated in so-called multi-omics studies to examine the complex molecular underpinnings of health and disease. Integrative analysis of such datasets is not straightforward and is particularly complicated by the high dimensionality and heterogeneity of the data and by the lack of universal analysis protocols. Previous reviews have discussed various strategies to address the challenges of data integration, elaborating on specific aspects, such as network inference or feature selection techniques. Thereby, the main focus has been on the integration of two omics layers in their relation to a phenotype of interest. In this review we provide an overview over a typical multi-omics workflow, focusing on integration methods that have the potential to combine metabolomics data with two or more omics. We discuss multiple integration concepts including data-driven, knowledge-based, simultaneous and step-wise approaches. We highlight the application of these methods in recent multi-omics studies, including large-scale integration efforts aiming at a global depiction of the complex relationships within and between different biological layers without focusing on a particular phenotype.

Characterization of dietary patterns and assessment of their relationships with metabolomic profiles: A community-based study

BACKGROUND & AIMS

Determining dietary patterns in China is challenging due to lack of external validation and objective measurements. We aimed to characterize dietary patterns in a community-based population and to validate these patterns using external validation cohort and metabolomic profiles.

DESIGN

We studied 5145 participants, aged 18-80 years, from two districts of Hangzhou, China. We used one district as the discovery cohort (N = 2521) and the other as the external validation cohort (N = 2624). We identified dietary patterns using a k-means clustering. Associations between dietary patterns and metabolic conditions were analyzed using adjusted logistic models. We assessed relationships between metabolomic profile and dietary patterns in 214 participants with metabolomics data.

RESULTS

We identified three dietary patterns: the traditional (rice-based), the mixed (rich in dairy products, eggs, nuts, etc.), and the high-alcohol diets. Relative to the traditional diet, the mixed (OR_adj = 1.7, CI 1.3-2.4) and the high-alcohol diets (OR_adj = 1.9, CI 1.3-2.7) were associated with type 2 diabetes and hypertension, respectively. Similar results were confirmed in the external validation cohort. In addition, we also identified 18 and 22 metabolites that could distinguish the mixed (error rate = 12%; AUC = 96%) and traditional diets (error rate = 19%; AUC = 88%) from the high-alcohol diet.

CONCLUSIONS

Despite the complexity of Chinese diet, identifying dietary patterns helps distinguish groups of individuals with high risk of metabolic diseases, which can also be validated by external population and metabolomic profiles.

Changes in Circulating Metabolome Precede Alcohol-Related Diseases in Middle-Aged Men: A Prospective Population-Based Study With a 30-Year Follow-Up

BACKGROUND

Heavy alcohol use has been associated with altered circulating metabolome. We investigated whether changes in the circulating metabolome precede incident diagnoses of alcohol-related diseases.

METHODS

This is a prospective population-based cohort study where the participants were 42- to 60-year-old males at baseline (years 1984 to 1989). Subjects who received a diagnosis for an alcohol-related disease during the follow-up were defined as cases (n = 92, mean follow-up of 13.6 years before diagnosis). Diagnoses were obtained through linkage with national health registries. We used 2 control groups: controls who self-reported similar levels of alcohol use as compared to cases at baseline (alcohol-controls, n = 92), and controls who self-reported only light drinking at baseline (control-controls, n = 90). A nontargeted metabolomics analysis of baseline serum samples was performed.

RESULTS

There were significant differences between the study groups in the baseline serum levels of 64 metabolites: in amino acids (e.g., glutamine [FDR-corrected q-value = 0.0012]), glycerophospholipids (e.g., lysophosphatidylcholine 16:1 [q = 0.0008]), steroids (e.g., cortisone [q = 0.00001]), and fatty acids (e.g., palmitoleic acid [q = 0.0031]). The main finding was that after controlling for baseline levels of self-reported alcohol use and the biomarker of alcohol use, gamma-glutamyl transferase, and when compared to both alcohol-control and control-control group, the alcohol-case group had lower serum levels of asparagine (Cohen's d = -0.48 [95% CI -0.78 to -0.19] and d = -0.49 [-0.78 to -0.19], respectively) and serotonin (d = -0.45 [-0.74 to -0.15], and d = -0.46 [-0.75 to -0.16], respectively), with no difference between the two control groups (asparagine d = 0.00 [-0.29 to 0.29] and serotonin d = -0.01 [-0.30 to 0.29]).

CONCLUSIONS

Changes in the circulating metabolome, especially lower serum levels of asparagine and serotonin, are associated with later diagnoses of alcohol-related diseases, even after adjustment for the baseline level of alcohol use.

Plasma metabolites associated with colorectal cancer stage: Findings from an international consortium

Colorectal cancer is the second most common cause of cancer-related death globally, with marked differences in prognosis by disease stage at diagnosis. We studied circulating metabolites in relation to disease stage to improve the understanding of metabolic pathways related to colorectal cancer progression. We investigated plasma concentrations of 130 metabolites among 744 Stages I-IV colorectal cancer patients from ongoing cohort studies. Plasma samples, collected at diagnosis, were analyzed with liquid chromatography-mass spectrometry using the Biocrates AbsoluteIDQ™ p180 kit. We assessed associations between metabolite concentrations and stage using multinomial and multivariable logistic regression models. Analyses were adjusted for potential confounders as well as multiple testing using false discovery rate (FDR) correction. Patients presented with 23, 28, 39 and 10% of Stages I-IV disease, respectively. Concentrations of sphingomyelin C26:0 were lower in Stage III patients compared to Stage I patients (pFDR  < 0.05). Concentrations of sphingomyelin C18:0 and phosphatidylcholine (diacyl) C32:0 were statistically significantly higher, while citrulline, histidine, phosphatidylcholine (diacyl) C34:4, phosphatidylcholine (acyl-alkyl) C40:1 and lysophosphatidylcholines (acyl) C16:0 and C17:0 concentrations were lower in Stage IV compared to Stage I patients (pFDR  < 0.05). Our results suggest that metabolic pathways involving among others citrulline and histidine, implicated previously in colorectal cancer development, may also be linked to colorectal cancer progression.

Identification of 102 Correlations between Serum Metabolites and Habitual Diet in a Metabolomics Study of the Prostate, Lung, Colorectal, and Ovarian Cancer Trial

BACKGROUND

Metabolomics has proven useful for detecting objective biomarkers of diet that may help to improve dietary measurement. Studies to date, however, have focused on a relatively narrow set of lipid classes.

OBJECTIVE

The aim of this study was to uncover candidate dietary biomarkers by identifying serum metabolites correlated with self-reported diet, particularly metabolites in underinvestigated lipid classes, e.g. triglycerides and plasmalogens.

METHODS

We assessed dietary questionnaire data and serum metabolite correlations from 491 male and female participants aged 55-75 y in an exploratory cross-sectional study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Self-reported intake was categorized into 50 foods, food groups, beverages, and supplements. We examined 522 identified metabolites using 2 metabolomics platforms (Broad Institute and Massachusetts General Hospital). Correlations were identified using partial Pearson's correlations adjusted for age, sex, BMI, smoking status, study site, and total energy intake [Bonferroni-corrected level of 0.05/(50 × 522) = 1.9 × 10-6]. We assessed prediction of dietary intake by multiple-metabolite linear models with the use of 10-fold crossvalidation least absolute shrinkage and selection operator (LASSO) regression.

RESULTS

Eighteen foods, beverages, and supplements were correlated with ≥1 serum metabolite at the Bonferroni-corrected significance threshold, for a total of 102 correlations. Of these, only 5 have been reported previously, to our knowledge. Our strongest correlations were between citrus and proline betaine (r = 0.55), supplements and pantothenic acid (r = 0.46), and fish and C40:9 phosphatidylcholine (PC) (r = 0.35). The multivariate analysis similarly found reasonably large correlations between metabolite profiles and citrus (r = 0.59), supplements (r = 0.57), and fish (r = 0.44).

CONCLUSIONS

Our study of PLCO participants identified many novel food-metabolite associations and replicated 5 previous associations. These candidate biomarkers of diet may help to complement measures of self-reported diet in nutritional epidemiology studies, though further validation work is still needed.

Sphingolipids and the link between alcohol and cancer

Epidemiological evidence underscores alcohol consumption as a strong risk factor for multiple cancer types, with liver cancer being most commonly associated with alcohol intake. While mechanisms linking alcohol consumption to malignant tumor development are not fully understood, the likely players in ethanol-induced carcinogenesis are genotoxic stress caused by formation of acetaldehyde, increased oxidative stress, and altered nutrient metabolism, including the impairment of methyl transfer reactions. Alterations of sphingolipid metabolism and associated signaling pathways are another potential link between ethanol and cancer development. In particular, ceramides are involved in the regulation of cellular proliferation, differentiation, senescence, and apoptosis and are known to function as important regulators of malignant transformation as well as tumor progression. However, to date, the cross-talk between ceramides and alcohol in cancer disease is largely an open question and only limited data are available on this subject. Most studies linking ceramide to cancer considered liver steatosis as the underlying mechanism, which is not surprising taking into consideration that ceramide pathways are an integral part of the overall lipid metabolism. This review summarizes the latest studies pointing to ceramide as an important mediator of cancer-promoting effects of chronic alcohol consumption and underscores the necessity of understanding the role of sphingolipids and lipid signaling in response to alcohol in order to prevent and/or successfully manage diseases caused by alcohol.

Targeted Approaches for In Situ Gut Microbiome Manipulation

The 2019 Dudrick Research Symposium, entitled "Targeted Approaches for In Situ Gut Microbiome Manipulation," was held on March 25, 2019, at the American Society for Parenteral and Enteral Nutrition (ASPEN) 2019 Nutrition Science & Practice Conference in Phoenix, AZ. The Dudrick Symposium honors the many pivotal and innovative contributions to the development and advancement of parenteral nutrition (PN) made by Dr Stanley J. Dudrick, physician scientist, academic leader, and a founding member of ASPEN. As the 2018 recipient of the Dudrick award, Dr Gail Cresci organized and chaired the symposium. The symposium addressed the evolving field of nutrition manipulation of the gut microbiome as a means to mitigate disease and support health. Presentations focused on (1) the role of prebiotics as a means to beneficially support gut microbiome composition and function and health; (2) designer synbiotics targeted to support metabolic by-products altered by ethanol exposure and microbial effectors that manipulate host metabolic outcomes; and, lastly, (3) types of intervention designs used to study diet-gut microbiome interactions in humans and a review of findings from recent interventions, which tested the effects of diet on the microbiome and the microbiome's effect on dietary exposures. New molecular techniques and multiomic approaches have improved knowledge of the structure and functional activity of the gut microbiome; however, challenges remain in establishing causal relationships between changes in the gut microbial-community structure and function and health outcomes in humans.

Alcohol consumption and serum metabolite concentrations in young women

PURPOSE

Alcohol consumption is an established breast cancer risk factor, though further research is needed to advance our understanding of the mechanism underlying the association. We used global metabolomics profiling to identify serum metabolites and metabolic pathways that could potentially mediate the alcohol-breast cancer association.

METHODS

A cross-sectional analysis of reported alcohol consumption and serum metabolite concentrations was conducted among 211 healthy women 25-29 years old who participated in the Dietary Intervention Study in Children 2006 Follow-Up Study (DISC06). Alcohol-metabolite associations were evaluated using multivariable linear mixed-effects regression.

RESULTS

Alcohol was significantly (FDR p < 0.05) associated with several serum metabolites after adjustment for diet composition and other potential confounders. The amino acid sarcosine, the omega-3 fatty acid eicosapentaenoate, and the steroid 4-androsten-3beta,17beta-diol monosulfate were positively associated with alcohol intake, while the gamma-tocopherol metabolite gamma-carboxyethyl hydroxychroman (CEHC) was inversely associated. Positive associations of alcohol with 2-methylcitrate and 4-androsten-3beta,17beta-diol disulfate were borderline significant (FDR p < 0.10). Metabolite set enrichment analysis identified steroids and the glycine pathway as having more members associated with alcohol consumption than expected by chance.

CONCLUSIONS

Most of the metabolites associated with alcohol in the current analysis participate in pathways hypothesized to mediate the alcohol-breast cancer association including hormonal, one-carbon metabolism, and oxidative stress pathways, but they could also affect risk via alternative pathways. Independent replication of alcohol-metabolite associations and prospective evaluation of confirmed associations with breast cancer risk are needed.

Changes in the Human Metabolome Associated With Alcohol Use: A Review

AIMS

The metabolome refers to the functional status of the cell, organ or the whole body. Metabolomic methods measure the metabolome (metabolite profile) which can be used to examine disease progression and treatment responses. Here, our aim was to review metabolomics studies examining effects of alcohol use in humans.

METHODS

We performed a literature search using PubMed and Web of Science for reports on changes in the human metabolite profile associated with alcohol use; we found a total of 23 articles published before end of 2018.

RESULTS

Most studies had investigated plasma, serum or urine samples; only four studies had examined other sample types (liver, faeces and broncho-alveolar lavage fluid). Levels of 51 metabolites were altered in two or more of the reviewed studies. Alcohol use was associated with changes in the levels of lipids and amino acids. In general, levels of fatty acids, phosphatidylcholine diacyls and steroid metabolites tended to increase, whereas those of phosphatidylcholine acyl-alkyls and hydroxysphingomyelins declined. Common alterations in circulatory levels of amino acids included decreased levels of glutamine, and increased levels of tyrosine and alanine.

CONCLUSIONS

More studies, especially with a longitudinal study design, or using more varied sample materials (e.g. organs or saliva), are needed to clarify alcohol-induced diseases and alterations at a target organ level. Hopefully, this will lead to the discovery of new treatments, improved recognition of individuals at high risk and identification of those subjects who would benefit most from certain treatments.

The Association between Alcohol Consumption and Serum Metabolites and the Modifying Effect of Smoking

Alcohol consumption is an important lifestyle factor that is associated with several health conditions and a behavioral link with smoking is well established. Metabolic alterations after alcohol consumption have yet to be comprehensively investigated. We studied the association of alcohol consumption with metabolite patterns (MPs) among 2433 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study, and a potential modification by smoking. Alcohol consumption was self-reported through dietary questionnaires and serum metabolites were measured by a targeted approach. The metabolites were summarized as MPs using the treelet transform analysis (TT). We fitted linear models with alcohol consumption continuously and in five categories. We stratified the continuously modelled alcohol consumption by smoking status. All models were adjusted for potential confounders. Among men, alcohol consumption was positively associated with six MPs and negatively associated with one MP. In women, alcohol consumption was inversely associated with one MP. Heavy consumers differed from other consumers with respect to the "Long and short chain acylcarnitines" MP. Our findings suggest that long and short chain acylcarnitines might play an important role in the adverse effects of heavy alcohol consumption on chronic diseases. The relations seem to depend on gender and smoking status.

Clinical Profiles of Selected Biomarkers Identifying Infection and Cancer Patients: A Gorzów Hospital Example

Introduction

Many pathobiological processes that manifest in a patient's organs could be associated with biomarker levels that are detectable in different human systems. However, biomarkers that promote early disease diagnosis should not be tested only in personalized medicine but also in large-scale diagnostic evaluations of patients, such as for medical management.

Objective

We aimed to create an easy algorithmic risk assessment tool that is based on obtainable "everyday" biomarkers, identifying infection and cancer patients.

Patients

We obtained the study data from the electronic medical records of 517 patients (186 infection and 331 cancer episodes) hospitalized at Gorzów Hospital, Poland, over a one and a half-year period from the 1^st of January 2017 to the 30^th of June 2018.

Methods and Results

A set of consecutive statistical methods (cluster analysis, ANOVA, and ROC analysis) was used to predict infection and cancer. For in-hospital diagnosis, our approach showed independent clusters of patients by age, sex, MPV, and disease fractions. From the set of available "everyday" biomarkers, we established the most likely bioindicators for infection and cancer together with their classification cutoffs.

Conclusions

Despite infection and cancer being very different diseases in their clinical characteristics, it seems possible to discriminate them using "everyday" biomarkers and popular statistical methods. The estimated cutoffs for the specified biomarkers can be used to allocate patients to appropriate risk groups for stratification purposes (medical management or epidemiological administration).

Changes in the serum metabolite profile correlate with decreased brain gray matter volume in moderate-to-heavy drinking young adults

Our aim was to analyze metabolite profile changes in serum associated with moderate-to-heavy consumption of alcohol in young adults and to evaluate whether these changes are connected to reduced brain gray matter volumes. These study population consisted of young adults with a 10-year history of moderate-to-heavy alcohol consumption (n = 35) and light-drinking controls (n = 27). We used the targeted liquid chromatography mass spectrometry method to measure concentrations of metabolites in serum, and 3.0 T magnetic resonance imaging to assess brain gray matter volumes. Alterations in amino acid and energy metabolism were observed in the moderate-to-heavy drinking young adults when compared to the controls. After correction for multiple testing, the group of moderate-to-heavy drinking young adults had increased serum concentrations of 1-methylhistamine (p = 0.001, d = 0.82) when compared to the controls. Furthermore, concentrations of 1-methylhistamine (r = -0.48, p = 0.004) and creatine (r = -0.52, p = 0.001) were negatively correlated with the brain gray matter volumes in the females. Overall, our results show association between moderate-to-heavy use of alcohol and altered metabolite profile in young adults as well as suggesting that some of these changes could be associated with the reduced brain gray matter volume.

Microbiome as a therapeutic target in alcohol-related liver disease

Alcohol-related liver disease is associated with significant changes in gut microbial composition. The transmissibility of ethanol-induced liver disease has been demonstrated using faecal microbiota transfer in preclinical models. This technique has also led to improved survival in patients with severe alcoholic hepatitis, suggesting that changes in the composition and function of the gut microbiota are causatively linked to alcohol-related liver disease. A major mechanism by which gut microbiota influence the development of alcohol-related liver disease is through a leaky intestinal barrier. This permits translocation of viable bacteria and microbial products to the liver, where they induce and promote inflammation, as well as contribute to hepatocyte death and the fibrotic response. In addition, gut dysbiosis is associated with changes in the metabolic function of the intestinal microbiota, bile acid composition and circulation, immune dysregulation during onset and progression of alcohol-related liver disease. Findings from preclinical and human studies will be used to demonstrate how alcohol causes intestinal pathology and contributes to alcohol-related liver disease and how the latter is self-perpetuating. Additionally, we summarise the effects of untargeted treatment approaches on the gut microbiota, such as diet, probiotics, antibiotics and faecal microbial transplantation in alcohol-related liver disease. We further discuss how targeted approaches can restore intestinal homeostasis and improve alcohol-related liver disease. These approaches are likely to add to the therapeutic options for alcohol-related liver disease independently or in conjunction with steroids.

Night Shift Work Affects Urine Metabolite Profiles of Nurses with Early Chronotype

Night shift work can have a serious impact on health. Here, we assess whether and how night shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424 waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate <0.05) affected in nurses working in night shifts. One metabolite, acylcarnitine C10:2, was consistently identified with all three normalization methods. We further observed 11 and 4 metabolites significantly associated with night shift in early and late chronotype classes, respectively. Increased levels of medium- and long chain acylcarnitines indicate a strong impairment of the fatty acid oxidation. Our results show that night shift work influences acylcarnitines and BCAAs, particularly in nurses in the early chronotype class. Women with intermediate and late chronotypes appear to be less affected by night shift work.

Lipidomic signature of serum from the rats exposed to alcohol for one year

Alcohol abuse and its related diseases are the major risk factors for human health. Although the mechanism of alcohol-related disorders has been widely investigated, serum metabolites associated with long-term alcohol intake have not been well explored. In this study, we aimed to investigate the profiles of serum metabolites and lipid species of rats chronically exposed to alcohol, which may be involved in the pathogenesis of alcohol-associated disease. An ¹H NMR-based metabolomics and Q-TOF/MS-based lipidomics approach were applied to investigate the profile of serum metabolites and lipid species of rats administrated daily with alcohol (12% vol/vol, 10 ml/kg per day, i.g.) for one year continuously. The rats administered with sterile water (10 ml/kg per day, i.g.) were used as control. We found that alcohol affected mostly the lipid species rather than small molecule metabolites in the serum of both female and male rats. Among the modified lipids, glycerophospholipid, sphingolipid and glycerolipids metabolism pathways were profoundly altered. The prominent changes in lipid profiles included diacylglycerol (DG), lysophosphatidylcholine (LysoPC), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylethanolamine (PE) and triacylglycerol (TG). Moreover, fatty-acyl profile of lipids and total degree of unsaturation of fatty acid were also significantly altered by alcohol. The modified lipidomic profile may help to understand the pathogenesis of alcohol-associated diseases and also be of value for clinical evaluation of alcohol abuse, alcohol-associated disease diagnosis.

Circulating Metabolites Associated with Alcohol Intake in the European Prospective Investigation into Cancer and Nutrition Cohort

Identifying the metabolites associated with alcohol consumption may provide insights into the metabolic pathways through which alcohol may affect human health. We studied associations of alcohol consumption with circulating concentrations of 123 metabolites among 2974 healthy participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Alcohol consumption at recruitment was self-reported through dietary questionnaires. Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQTM p180 kit). Data were randomly divided into discovery (2/3) and replication (1/3) sets. Multivariable linear regression models were used to evaluate confounder-adjusted associations of alcohol consumption with metabolite concentrations. Metabolites significantly related to alcohol intake in the discovery set (FDR q-value < 0.05) were further tested in the replication set (Bonferroni-corrected p-value < 0.05). Of the 72 metabolites significantly related to alcohol intake in the discovery set, 34 were also significant in the replication analysis, including three acylcarnitines, the amino acid citrulline, four lysophosphatidylcholines, 13 diacylphosphatidylcholines, seven acyl-alkylphosphatidylcholines, and six sphingomyelins. Our results confirmed earlier findings that alcohol consumption was associated with several lipid metabolites, and possibly also with specific acylcarnitines and amino acids. This provides further leads for future research studies aiming at elucidating the mechanisms underlying the effects of alcohol in relation to morbid conditions.

Comprehensive Metabolic Profiling Reveals a Lipid-Rich Fingerprint of Free Thyroxine Far Beyond Classic Parameters

OBJECTIVE

Thyroid hormones are ubiquitously involved in human metabolism. However, the precise molecular patterns associated with alterations in thyroid hormones levels remain to be explored in detail. A number of recent studies took great advantage of metabolomics profiling to outline the metabolic actions of thyroid hormones in humans.

METHODS

Among 952 participants in the Study of Health in Pomerania, data on serum free thyroxine (FT4) and thyrotropin and comprehensive nontargeted metabolomics data from plasma and urine samples were available. Linear regression analyses were performed to assess the association between FT4 or thyrotropin and metabolite levels.

RESULTS AND CONCLUSION

After accounting for major confounders, 106 of 613 plasma metabolites were significantly associated with FT4. The associations in urine were minor (12 of 587). Most of the plasma metabolites consisted of lipid species, and subsequent analysis of highly resolved lipoprotein subclasses measured by proton nuclear magnetic resonance spectroscopy revealed a consistent decrease in several of these species (e.g., phospholipids) and large low-density lipoprotein and small high-density lipoprotein particles. The latter was unique to men. Several polyunsaturated and saturated fatty acids displayed an association with FT4 in women only. A random forest-based variable selection approach using phenotypic characteristics revealed higher alcohol intake in men and an adverse thyroid state and menopause in women as the putative mediating factors. In general, our observations have confirmed the lipolytic and lipogenic effect of thyroid hormones even in the physiological range and revealed different phenotypic characteristics (e.g., lifestyle differences) as possible confounders for sex-specific findings.

On metabolic reprogramming and tumor biology: A comprehensive survey of metabolism in breast cancer

Altered metabolism in tumor cells has been a focus of cancer research for as long as a century but has remained controversial and vague due to an inhomogeneous overall picture. Accumulating genomic, metabolomic, and lastly panomic data as well as bioenergetics studies of the past few years enable a more comprehensive, systems-biologic approach promoting deeper insight into tumor biology and challenging hitherto existing models of cancer bioenergetics. Presenting a compendium on breast cancer-specific metabolome analyses performed thus far, we review and compile currently known aspects of breast cancer biology into a comprehensive network, elucidating previously dissonant issues of cancer metabolism. As such, some of the aspects critically discussed in this review include the dynamic interplay or metabolic coupling between cancer (stem) cells and cancer-associated fibroblasts, the intratumoral and intertumoral heterogeneity and plasticity of cancer cell metabolism, the existence of distinct metabolic tumor compartments in need of separate yet simultaneous therapeutic targeting, the reliance of cancer cells on oxidative metabolism and mitochondrial power, and the role of pro-inflammatory, pro-tumorigenic stromal conditioning. Comprising complex breast cancer signaling networks as well as combined metabolomic and genomic data, we address metabolic consequences of mutations in tumor suppressor genes and evaluate their contribution to breast cancer predisposition in a germline setting, reasoning for distinct personalized preventive and therapeutic measures. The review closes with a discussion on central root mechanisms of tumor cell metabolism and rate-limiting steps thereof, introducing essential strategies for therapeutic targeting.

Beyond genomics: understanding exposotypes through metabolomics

BACKGROUND

Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact.

MAIN TEXT

Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics.

CONCLUSIONS

Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation.

Intestinal dysbiosis and permeability: the yin and yang in alcohol dependence and alcoholic liver disease

Alcohol dependence and alcoholic liver disease represent a major public health problem with substantial morbidity and mortality. By yet incompletely understood mechanisms, chronic alcohol abuse is associated with increased intestinal permeability and alterations of the gut microbiota composition, allowing bacterial components, bacteria, and metabolites to reach the portal and the systemic circulation. These gut-derived bacterial products are recognized by immune cells circulating in the blood or residing in remote organs such as the liver leading to the release of pro-inflammatory cytokines which are considered important mediators of the liver-gut-brain communication. Although circulating cytokines are likely not the sole factors involved, they can induce liver inflammation/damage and reach the central nervous system where they favor neuroinflammation which is associated with change in mood, cognition, and drinking behavior. In this review, the authors focus on the current evidence describing the changes that occur in the intestinal microbiota with chronic alcohol consumption in conjunction with intestinal barrier breakdown and inflammatory changes sustaining the concept of a gut-liver-brain axis in the pathophysiology of alcohol dependence and alcoholic liver disease.

Epidemiology in Germany-general development and personal experience

Did you ever hear about epidemiology in Germany? Starting from an epidemiological desert the discipline has grown remarkably, especially during the last 10-15 years: research institutes have been established, research funding has improved, multiple curriculae in Epidemiology and Public Health are offered. This increase has been quite steep, and now the epidemiological infrastructure is much better. Several medium-sized and even big population cohorts are ongoing, and the number and quality of publications from German epidemiologists has reached a respectable level. My own career in epidemiology started in the field of environmental health. After German reunification I concentrated for many years on environmental problems in East Germany and observed the health benefits after improvement of the situation. Later, I concentrated on population-based cohorts in newborns (GINI/LISA) and adults (KORA, German National Cohort), and on biobanking. This Essay describes the development in Germany after worldwar 2, illustrated by examples of research results and build-up of epidemiological infractructures worth mentioning.

Metabolomics and fetal alcohol spectrum disorder

Fetal alcohol spectrum disorder (FASD) is a major public health issue that encompass an array of physical, neurological, and behavioral effects due to alcohol consumption during pregnancy. The classical biomarkers of FASD that are currently used lack sensitivity and specificity, and as such there is an opportunity through the use of novel metabolomics analysis to identify new biomarkers to identify those at risk for FASD, which could more effectively aid in early intervention. The focus of this minireview is to identify current work that is being done in the field of metabolomics in FASD in utero, and to highlight promising metabolites that could act as biomarkers in the future. We will conclude with suggestions for further research, as there is a large gap of knowledge in this particular area of metabolomics.

Metabolomics for clinical use and research in chronic kidney disease

Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.

Lessons on dietary biomarkers from twin studies

Metabolomic and microbiome profiling are promising tools to identify biomarkers of food intake and health status. The individual's genetic makeup plays a significant role on health, metabolism, gut microbes and diet and twin studies provide unique opportunities to untangle gene-environment effects on complex phenotypes. This brief review discusses the value of twin studies in nutrition research with a particular focus on metabolomics and the gut microbiome. Although, the twin model is a powerful tool to segregate the genetic component, to date, very few studies combine the twin design and metabolomics/microbiome in nutritional sciences. Moreover, since the individual's diet has a strong influence on the microbiome composition and the gut microbiome is modifiable (60 % of microbiome diversity is due to the environment), future studies should target the microbiome via dietary interventions.

Key elements of metabolomics in the study of biomarkers of diabetes

Metabolomics is instrumental in the analysis of disease mechanisms and biomarkers of disease. The human metabolome is influenced by genetics and environmental interactions and reveals characteristic signatures of disease. Population studies with metabolomics require special study designs and care needs to be taken with pre-analytics. Gas chromatography coupled to mass spectrometry, liquid chromatography coupled to mass spectrometry or NMR are popular techniques used for metabolomic analyses in human cohorts. Metabolomics has been successfully used in the biomarker search for disease prediction and progression, for analyses of drug action and for the development of companion diagnostics. Several metabolites or metabolite classes identified by metabolomics have gained much attention in the field of diabetes research in the search for early disease detection, differentiation of progressor types and compliance with medication. This review summarises a presentation given at the 'New approaches beyond genetics' symposium at the 2015 annual meeting of the EASD. It is accompanied by another review from this symposium by Bernd Mayer (DOI: 10.1007/s00125-016-4032-2 ) and an overview by the Session Chair, Leif Groop (DOI: 10.1007/s00125-016-4014-4 ).

Cardiovascular Risk Factors Associated With Blood Metabolite Concentrations and Their Alterations During a 4-Year Period in a Population-Based Cohort

Background—

The effects of lifestyle risk factors considered collectively on the human metabolism are to date unknown. We aim to investigate the association of these risk factors with metabolites and their changes during 4 years.

Methods and Results—

One hundred and sixty-three metabolites were measured in serum samples with the AbsoluteIDQ kit p150 (Biocrates) following a targeted metabolomics approach, in a population-based cohort of 1030 individuals, aged 45 to 83 years at baseline. We evaluated associations between metabolite concentrations (28 acylcarnitines, 14 amino acids, 9 lysophosphocholines, 72 phosphocholines, 10 sphingomyelins and sum of hexoses) and 5 lifestyle risk factors (body mass index [BMI], alcohol consumption, smoking, diet, and exercise). Multilevel or simple linear regression modeling adjusted for relevant covariates was used for the evaluation of cross-sectional or longitudinal associations, respectively; multiple testing correction was based on false discovery rate. BMI, alcohol consumption, and smoking were associated with lipid metabolism (reduced lyso- and acyl-alkyl-phosphatidylcholines and increased diacylphosphatidylcholines concentrations). Smoking showed positive associations with acylcarnitines, and BMI correlated inversely with nonessential amino acids. Fewer metabolites showed relative changes that were associated with baseline risk factors: increases in 5 different acyl-alkyl phosphatidylcholines were associated with lower alcohol consumption and BMI and with a healthier diet. Increased levels of tyrosine were associated with BMI. Sex-specific effects of smoking and BMI were found specifically related to acylcarnitine metabolism: in women higher BMI and in men more pack-years were associated with increases in acylcarnitines.

Conclusions—

This study showed sex-specific effects of lifestyle risks factors on human metabolism and highlighted their long-term metabolic consequences.

Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects

BACKGROUND

Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD.

OBJECTIVES

To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics.

METHOD

Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC).

RESULTS

The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0).

CONCLUSION

This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy.

Metabolic profiling of alcohol consumption in 9778 young adults

Background: High alcohol consumption is a major cause of morbidity, yet alcohol is associated with both favourable and adverse effects on cardiometabolic risk markers. We aimed to characterize the associations of usual alcohol consumption with a comprehensive systemic metabolite profile in young adults.

Methods: Cross-sectional associations of alcohol intake with 86 metabolic measures were assessed for 9778 individuals from three population-based cohorts from Finland (age 24–45 years, 52% women). Metabolic changes associated with change in alcohol intake during 6-year follow-up were further examined for 1466 individuals. Alcohol intake was assessed by questionnaires. Circulating lipids, fatty acids and metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays.

Results: Increased alcohol intake was associated with cardiometabolic risk markers across multiple metabolic pathways, including higher lipid concentrations in HDL subclasses and smaller LDL particle size, increased proportions of monounsaturated fatty acids and decreased proportion of omega-6 fatty acids, lower concentrations of glutamine and citrate (P < 0.001 for 56 metabolic measures). Many metabolic biomarkers displayed U-shaped associations with alcohol consumption. Results were coherent for men and women, consistent across the three cohorts and similar if adjusting for body mass index, smoking and physical activity. The metabolic changes accompanying change in alcohol intake during follow-up resembled the cross-sectional association pattern (R²= 0.83, slope = 0.72 ± 0.04).

Conclusions: Alcohol consumption is associated with a complex metabolic signature, including aberrations in multiple biomarkers for elevated cardiometabolic risk. The metabolic signature tracks with long-term changes in alcohol consumption. These results elucidate the double-edged effects of alcohol on cardiovascular risk.

The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women

Background

The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible.

Objective

The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and¹H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics.

Methods

Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,¹H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods.

Results

The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway.

Conclusions

We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and¹H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study.

Trial Registration

German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx)

Low-Level Environmental Phthalate Exposure Associates with Urine Metabolome Alteration in a Chinese Male Cohort

The general population is exposed to phthalates through various sources and routes. Integration of omics data and epidemiological data is a key step toward directly linking phthalate biomonitoring data with biological response. Urine metabolomics is a powerful tool to identify exposure biomarkers and delineate the modes of action of environmental stressors. The objectives of this study are to investigate the association between low-level environmental phthalate exposure and urine metabolome alteration in male population, and to unveil the metabolic pathways involved in the mechanisms of phthalate toxicity. In this retrospective cross-sectional study, we studied the urine metabolomic profiles of 364 male subjects exposed to low-level environmental phthalates. Di(2-ethylhexyl) phthalate (DEHP) and dibutyl phthalate (DBP) are the most widely used phthalates. ∑DEHP and MBP (the major metabolite of DBP) were associated with significant alteration of global urine metabolome in the male population. We observed significant increase in the levels of acetylneuraminic acid, carnitine C8:1, carnitine C18:0, cystine, phenylglycine, phenylpyruvic acid and glutamylphenylalanine; and meanwhile, decrease in the levels of carnitine C16:2, diacetylspermine, alanine, taurine, tryptophan, ornithine, methylglutaconic acid, hydroxyl-PEG2 and keto-PGE2 in high exposure group. The observations indicated that low-level environmental phthalate exposure associated with increased oxidative stress and fatty acid oxidation and decreased prostaglandin metabolism. Urea cycle, tryptophan and phenylalanine metabolism disruption was also observed. The urine metabolome disruption effects associated with ∑DEHP and MBP were similar, but not identical. The multibiomarker models presented AUC values of 0.845 and 0.834 for ∑DEHP and MBP, respectively. The predictive accuracy rates of established models were 81% for ΣDEHP and 73% for MBP. Our results suggest that low-level environmental phthalate exposure associates with urine metabolome disruption in male population, providing new insight into the early molecular events of phthalate exposure.