Effects of smoking and smoking cessation on human serum metabolite profile: results from the KORA cohort study

Serum metabolome perturbation in relation to noise exposure: Exploring the potential role of serum metabolites in noise-induced arterial stiffness

Noise pollution has grown to be a major public health issue worldwide. We sought to profile serum metabolite expression changes related to occupational noise exposure by untargeted metabolomics, as well as to evaluate the potential roles of serum metabolites in occupational noise-associated arterial stiffness (AS). Our study involved 30 noise-exposed industrial personnel (Lipo group) and 30 noise-free controls (Blank group). The untargeted metabolomic analysis was performed by employing a UPLC-HRMS. The associations of occupational noise and significant differential metabolites (between Blank/Lipo groups) with AS were evaluated using multivariable-adjusted generalized linear models. We performed the least absolute shrinkage and selection operator regression analysis to further screen for AS's risk metabolites. We explored 177 metabolites across 21 categories significantly differentially expressed between Blank/Lipo groups, and these metabolites were enriched in 20 metabolic pathways. Moreover, 15 metabolites in 4 classes (including food, glycerophosphocholine, sphingomyelin [SM] and triacylglycerols [TAG]) were adversely associated with AS (all P < 0.05). Meanwhile, five metabolites (homostachydrine, phosphatidylcholine (PC) (32:1e), PC (38:6p), SM (d41:2) and TAG (45:1) have been proven to be useful predictors of AS prevalence. However, none of these 15 metabolites were found to have a mediating influence on occupational noise-induced AS. Our study reveals specific metabolic changes caused by occupational noise exposure, and several metabolites may have protective effects on AS. However, the roles of serum metabolites in noise-AS association remain to be validated in future studies.

Sex difference in association between suicide attempts and lipid profile in first-episode and drug naive patients with major depressive disorder

BACKGROUND

The relationship between suicide attempts and lipid profiles in patients with major depressive disorder (MDD) remains uncertain. The purpose of this study was to investigate sex differences in the relationship between suicide attempts and plasma lipid profiles in a large sample of first-episode and drug naive (FEDN) MDD patients.

METHODS

We recruited 1718 FEDN MDD patients and gathered demographic, clinical, and blood lipid data. The Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale and the Positive and Negative Syndrome Scale were used to assess the symptoms of patients.

RESULTS

There was no significant difference in the prevalence of suicide attempts between male and female MDD patients. The suicide attempt group had higher levels of depression, anxiety, psychotic symptoms, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C), but lower levels of high-density lipoprotein cholesterol (HDL-C) levels than the non-suicide attempt group. Binary logistic regression showed that TC levels were significantly correlated with suicidal attempts in both male and female patients. Correlation analysis revealed that the levels of TC, HDL-C and LDL-C were significantly associated with the number of suicide attempts in both male and female patients. Further multiple linear regression revealed that TC levels were significantly associated with the number of suicide attempts in male patients only.

CONCLUSIONS

Lipid biomarkers, particularly high TC levels, are associated with suicide attempts in both male and female MDD patients. However, there is gender difference in association between lipid biomarkers, especially TC levels, and the number of suicide attempts in MDD patients.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility

BACKGROUND

Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance.

METHODS

In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI).

FINDINGS

The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92).

INTERPRETATION

The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

MASH: MEDIATION ANALYSIS OF SURVIVAL OUTCOME AND HIGH-DIMENSIONAL OMICS MEDIATORS WITH APPLICATION TO COMPLEX DISEASES

Environmental exposures such as cigarette smoking influence health outcomes through intermediate molecular phenotypes, such as the methylome, transcriptome, and metabolome. Mediation analysis is a useful tool for investigating the role of potentially high-dimensional intermediate phenotypes in the relationship between environmental exposures and health outcomes. However, little work has been done on mediation analysis when the mediators are high-dimensional and the outcome is a survival endpoint, and none of it has provided a robust measure of total mediation effect. To this end, we propose an estimation procedure for Mediation Analysis of Survival outcome and High-dimensional omics mediators (MASH) based on sure independence screening for putative mediator variable selection and a second-moment-based measure of total mediation effect for survival data analogous to the R 2 measure in a linear model. Extensive simulations showed good performance of MASH in estimating the total mediation effect and identifying true mediators. By applying MASH to the metabolomics data of 1919 subjects in the Framingham Heart Study, we identified five metabolites as mediators of the effect of cigarette smoking on coronary heart disease risk (total mediation effect, 51.1%) and two metabolites as mediators between smoking and risk of cancer (total mediation effect, 50.7%). Application of MASH to a diffuse large B-cell lymphoma genomics data set identified copy-number variations for eight genes as mediators between the baseline International Prognostic Index score and overall survival.

Association between pre-diagnostic circulating lipid metabolites and colorectal cancer risk: a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC)

BACKGROUND

Altered lipid metabolism is a hallmark of cancer development. However, the role of specific lipid metabolites in colorectal cancer development is uncertain.

METHODS

In a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC), we examined associations between pre-diagnostic circulating concentrations of 97 lipid metabolites (acylcarnitines, glycerophospholipids and sphingolipids) and colorectal cancer risk. Circulating lipids were measured using targeted mass spectrometry in 1591 incident colorectal cancer cases (55% women) and 1591 matched controls. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between concentrations of individual lipid metabolites and metabolite patterns with colorectal cancer risk.

FINDINGS

Of the 97 assayed lipids, 24 were inversely associated (nominally p < 0.05) with colorectal cancer risk. Hydroxysphingomyelin (SM (OH)) C22:2 (ORper doubling 0.60, 95% CI 0.47-0.77) and acylakyl-phosphatidylcholine (PC ae) C34:3 (ORper doubling 0.71, 95% CI 0.59-0.87) remained associated after multiple comparisons correction. These associations were unaltered after excluding the first 5 years of follow-up after blood collection and were consistent according to sex, age at diagnosis, BMI, and colorectal subsite. Two lipid patterns, one including 26 phosphatidylcholines and all sphingolipids, and another 30 phosphatidylcholines, were weakly inversely associated with colorectal cancer.

INTERPRETATION

Elevated pre-diagnostic circulating levels of SM (OH) C22:2 and PC ae C34:3 and lipid patterns including phosphatidylcholines and sphingolipids were associated with lower colorectal cancer risk. This study may provide insight into potential links between specific lipids and colorectal cancer development. Additional prospective studies are needed to validate the observed associations.

FUNDING

World Cancer Research Fund (reference: 2013/1002); European Commission (FP7: BBMRI-LPC; reference: 313010).

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease Among Low-Income Black and White Americans

BACKGROUND

Life's essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about the LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

METHODS

In a nested case-control study of coronary heart disease (CHD) among 299 pairs of Black and 298 pairs of White low-income Americans from the Southern Community Cohort Study, we estimated LE8 score and applied untargeted plasma metabolomics and elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. The mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 299 pairs of Chinese adults.

RESULTS

Higher LE8 score was associated with lower CHD risk (standardized odds ratio, 0.61 [95% CI, 0.53-0.69]). The MetaSig, consisting of 133 metabolites, showed significant correlation with LE8 score (r=0.61) and inverse association with CHD (odds ratio, 0.57 [0.49-0.65]), robust to adjustment for LE8 score and across participants with different sociodemographic and health status ([odds ratios, 0.42-0.69]; all P<0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort (r=0.49; odds ratio, 0.57 [0.46-0.69]).

CONCLUSIONS

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective measure of LE8 and its metabolic phenotype relevant to CHD prevention among diverse populations.

Longitudinal associations between metabolites and immediate, short- and medium-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Short-term exposure to air pollution has been reported to be associated with cardiopulmonary diseases, but the underlying mechanisms remain unclear. This study aimed to investigate changes in serum metabolites associated with immediate, short- and medium-term exposures to ambient air pollution.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in this analysis. We collected daily averages of fine particles (PM2.5), coarse particles (PMcoarse), nitrogen dioxide (NO2), and ozone (O3) at urban background monitors located in Augsburg, Germany. Covariate-adjusted generalized additive mixed-effects models were used to examine the associations between immediate (2-day average of same day and previous day as individual's blood withdrawal), short- (2-week moving average), and medium-term exposures (8-week moving average) to air pollution and metabolites. We further performed pathway analysis for the metabolites significantly associated with air pollutants in each exposure window.

RESULTS

Of 9,620 observations from 4,261 study participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed quality control, multiple significant associations between metabolites and air pollutants with several exposure windows were identified at a Bonferroni corrected p-value threshold (p < 3.9 × 10-5). We found the highest number of associations for NO2, particularly at the medium-term exposure windows. Among the identified metabolic pathways based on the metabolites significantly associated with air pollutants, the glycerophospholipid metabolism was the most robust pathway in different air pollutants exposures.

CONCLUSIONS

Our study suggested that short- and medium-term exposure to air pollution might induce alterations of serum metabolites, particularly in metabolites involved in metabolic pathways related to inflammatory response and oxidative stress.

Associations between Smoking and Smoking Cessation during Pregnancy and Newborn Metabolite Concentrations: Findings from PRAMS and INSPIRE Birth Cohorts

Newborn metabolite perturbations may identify potential biomarkers or mechanisms underlying adverse, smoking-related childhood health outcomes. We assessed associations between third-trimester smoking and newborn metabolite concentrations using the Tennessee Pregnancy Risk Assessment Monitoring System (PRAMS, 2009-2019) as the discovery cohort and INSPIRE (2012-2014) as the replication cohort. Children were linked to newborn screening metabolic data (33 metabolites). Third-trimester smoking was ascertained from birth certificates (PRAMS) and questionnaires (INSPIRE). Among 8600 and 1918 mother-child dyads in PRAMS and INSPIRE cohorts, 14% and 13% of women reported third-trimester smoking, respectively. Third-trimester smoking was associated with higher median concentrations of free carnitine (C0), glycine (GLY), and leucine (LEU) at birth (PRAMS: C0: adjusted fold change 1.11 [95% confidence interval (CI) 1.08, 1.14], GLY: 1.03 [95% CI 1.01, 1.04], LEU: 1.04 [95% CI 1.03, 1.06]; INSPIRE: C0: 1.08 [95% CI 1.02, 1.14], GLY: 1.05 [95% CI 1.01, 1.09], LEU: 1.05 [95% CI 1.01, 1.09]). Smoking cessation (vs. continued smoking) during pregnancy was associated with lower median metabolite concentrations, approaching levels observed in infants of non-smoking women. Findings suggest potential pathways underlying fetal metabolic programming due to in utero smoke exposure and a potential reversible relationship of cessation.

Metabolomics profiles alterations in cigarette smokers and heated tobacco product users

BACKGROUND

Heated tobacco products (HTPs) have gained global popularity, but their health risks remain unclear. Therefore, the current study aimed to identify plasma metabolites associated with smoking and HTP use in a large Japanese population to improve health risk assessment.

METHODS

Metabolomics data from 9,922 baseline participants of the Tsuruoka Metabolomics Cohort Study (TMCS) were analyzed to determine the association between smoking habits and plasma metabolites. Moreover, alterations in smoking-related metabolites among HTP users were examined based on data obtained from 3,334 participants involved from April 2018 to June 2019 in a follow-up survey.

RESULTS

Our study revealed that cigarette smokers had metabolomics profiles distinct from never smokers, with 22 polar metabolites identified as candidate biomarkers for smoking. These biomarker profiles of HTP users were closer to those of cigarette smokers than those of never smokers. The concentration of glutamate was higher in cigarette smokers, and biomarkers involved in glutamate metabolism were also associated with cigarette smoking and HTP use. Network pathway analysis showed that smoking was associated with the glutamate pathway, which could lead to endothelial dysfunction and atherosclerosis of the vessels.

CONCLUSIONS

Our study showed that the glutamate pathway is affected by habitual smoking. These changes in the glutamate pathway may partly explain the mechanism by which cigarette smoking causes cardiovascular disease. HTP use was also associated with glutamate metabolism, indicating that HTP use may contribute to the development of cardiovascular disease through mechanisms similar to those in cigarette use.

Preliminary Findings on the Salivary Metabolome of Hookah and Cigarette Smokers

The aim of the study was to evaluate the salivary metabolomic profile of patients who habitually smoke hookah and cigarettes. The groups consisted of 33 regular and exclusive hookah smokers, 26 regular and exclusive cigarette smokers, and 30 nonsmokers. Unstimulated whole saliva was collected for the measurement of salivary metabolites by gas chromatography coupled with tandem mass spectrometry (GC-MS/MS). The MetaboAnalyst software was used for statistical analysis and evaluation of biomarkers. 11 smoking salivary biomarkers were identified using the area under receiving-operator curver criterion and threshold of 0.9. Xylitol and octadecanol were higher in cigarette smokers compared to controls; arabitol and maltose were higher in controls compared to cigarette smokers; octadecanol and tyramine were higher in hookah smokers compared to controls; phenylalanine was higher in controls compared to hookah smokers; and fructose, isocitric acid, glucuronic acid, tryptamine, maltose, tyramine, and 3-hydroxyisolvaleric acid were higher in hookah smokers compared to cigarettes smokers. Conclusions: The evaluation of the salivary metabolome of hookah smokers, showing separation between the groups, especially between the control versus hookah groups and cigarette versus hookah groups, and it seems to demonstrate that the use of hookah tobacco is more damaging to health.

Role of untargeted omics biomarkers of exposure and effect for tobacco research

Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.

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.

Metabolite Signature of Life's Essential 8 and Risk of Coronary Heart Disease among Low-Income Black and White Americans

Background and Aims

Life's Essential 8 (LE8) is a comprehensive construct of cardiovascular health. Yet, little is known about LE8 score, its metabolic correlates, and their predictive implications among Black Americans and low-income individuals.

Methods

In a nested case-control study of coronary heart disease (CHD) among 598 Black and 596 White low-income Americans, we estimated LE8 score, conducted untargeted plasma metabolites profiling, and used elastic net with leave-one-out cross-validation to identify metabolite signature (MetaSig) of LE8. Associations of LE8 score and MetaSig with incident CHD were examined using conditional logistic regression. Mediation effect of MetaSig on the LE8-CHD association was also examined. The external validity of MetaSig was evaluated in another nested CHD case-control study among 598 Chinese adults.

Results

Higher LE8 score was associated with lower CHD risk [standardized OR (95% CI)=0.61 (0.53-0.69)]. The identified MetaSig, consisting of 133 metabolites, showed strong correlation with LE8 score ( r =0.61) and inverse association with CHD risk [OR (95% CI)=0.57 (0.49-0.65)], robust to adjustment for LE8 score and across participants with different sociodemographic and health status (ORs: 0.42-0.69; all P <0.05). MetaSig mediated a large portion of the LE8-CHD association: 53% (32%-80%) ( P <0.001). Significant associations of MetaSig with LE8 score and CHD risk were found in validation cohort [ r =0.49; OR (95% CI)=0.57 (0.46-0.69)].

Conclusions

Higher LE8 score and its MetaSig were associated with lower CHD risk among low-income Black and White Americans. Metabolomics may offer an objective and comprehensive measure of LE8 score and its metabolic phenotype relevant to CHD prevention among diverse populations.

Untargeted metabolomics unravel serum metabolic alterations in smokers with hypertension

Background: Cigarette smoking is an important environmental risk factor for cardiovascular events of hypertension (HTN). Existing studies have provided evidence supporting altered gut microbiota by cigarette smoking, especially in hypertensive patients. Metabolic biomarkers play a central role in the functional potentials of the gut microbiome but are poorly characterized in hypertensive smokers. To explore whether serum metabolomics signatures and compositions of HTN patients were varied in smokers, and investigate their connecting relationship to gut microbiota, the serum metabolites were examined in untreated hypertensive patients using untargeted liquid chromatography-mass spectrometry (LC/MS) analysis. Results: A dramatic difference and clear separation in community features of circulating metabolomics members were seen in smoking HTN patients compared with the non-smoking controls, according to partial least squares discrimination analysis (PLS-DA) and orthogonal partial least squares discrimination analysis (OPLS-DA). Serum metabolic profiles and compositions of smoking patients with HTN were significantly distinct from the controls, and were characterized by enrichment of 12-HETE, 7-Ketodeoxycholic acid, Serotonin, N-Stearoyl tyrosine and Deoxycholic acid glycine conjugate, and the depletion of Tetradecanedioic acid, Hippuric acid, Glyceric acid, 20-Hydroxyeicosatetraenoic acid, Phenylpyruvic acid and Capric acid. Additionally, the metabolome displayed prominent functional signatures, with a majority proportion of the metabolites identified to be discriminating between groups distributed in Starch and sucrose metabolism, Caffeine metabolism, Pyruvate metabolism, Glycine, serine and threonine metabolism, and Phenylalanine metabolic pathways. Furthermore, the observation of alterations in metabolites associated with intestinal microbial taxonomy indicated that these metabolic members might mediate the effects of gut microbiome on the smoking host. Indeed, the metabolites specific to smoking HTNs were strongly organized into co-abundance networks, interacting with an array of clinical parameters, including uric acid (UA), low-denstiy lipoprotein cholesterol (LDLC) and smoking index. Conclusions: In conclusion, we demonstrated disparate circulating blood metabolome composition and functional potentials in hypertensive smokers, showing a linkage between specific metabolites in blood and the gut microbiome.

Longitudinal associations between metabolites and long-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Long-term exposure to air pollution has been associated with cardiopulmonary diseases, while the underlying mechanisms remain unclear.

OBJECTIVES

To investigate changes in serum metabolites associated with long-term exposure to air pollution and explore the susceptibility characteristics.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in the current analysis. Land-use regression (LUR) models were used to estimate annual average concentrations of ultrafine particles, particulate matter (PM) with an aerodynamic diameter less than 10 μm (PM₁₀), coarse particles (PM_coarse), fine particles, PM_2.5 absorbance (a proxy of elemental carbon related to traffic exhaust, PM_2.5abs), nitrogen oxides (NO₂, NO_x), and ozone at individuals' residences. We applied confounder-adjusted mixed-effects regression models to examine the associations between long-term exposure to air pollution and metabolites.

RESULTS

Among 9,620 observations from 4,261 KORA participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed stringent quality control across three study points in time, we identified nine significant negative associations between phosphatidylcholines (PCs) and ambient pollutants at a Benjamini-Hochberg false discovery rate (FDR) corrected p-value < 0.05. The strongest association was seen for an increase of 0.27 μg/m³ (interquartile range) in PM_2.5abs and decreased phosphatidylcholine acyl-alkyl C36:3 (PC ae C36:3) concentrations [percent change in the geometric mean: -2.5% (95% confidence interval: -3.6%, -1.5%)].

CONCLUSIONS

Our study suggested that long-term exposure to air pollution is associated with metabolic alterations, particularly in PCs with unsaturated long-chain fatty acids. These findings might provide new insights into potential mechanisms for air pollution-related adverse outcomes.

Fetal Exposure to Maternal Smoking and Neonatal Metabolite Profiles

Fetal tobacco exposure has persistent effects on growth and metabolism. The underlying mechanisms of these relationships are yet unknown. We investigated the associations of fetal exposure to maternal smoking with neonatal metabolite profiles. In a population-based cohort study among 828 mother-infant pairs, we assessed maternal tobacco use by questionnaire. Metabolite concentrations of amino acids, non-esterified fatty acids, phospholipids and carnitines were determined by using LC-MS/MS in cord blood samples. Metabolite ratios reflecting metabolic pathways were computed. Compared to non-exposed neonates, those exposed to first trimester only tobacco smoking had lower neonatal mono-unsaturated acyl-alkyl-phosphatidylcholines (PC.ae) and alkyl-lysophosphatidylcholines (Lyso.PC.e) 18:0 concentrations. Neonates exposed to continued tobacco smoking during pregnancy had lower neonatal mono-unsaturated acyl-lysophosphatidylcholines (Lyso.PC.a), Lyso.PC.e.16:0 and Lyso.PC.e.18:1 concentration (False discovery rate (FDR) p-values < 0.05). Dose-response associations showed the strongest effect estimates in neonates whose mothers continued smoking ≥5 cigarettes per day (FDR p-values < 0.05). Furthermore, smoking during the first trimester only was associated with altered neonatal metabolite ratios involved in the Krebs cycle and oxidative stress, whereas continued smoking during pregnancy was associated with inflammatory, transsulfuration, and insulin resistance markers (p-value < 0.05). Thus, fetal tobacco exposure seems associated with neonatal metabolite profile adaptations. Whether these changes relate to later life metabolic health should be studied further.

Creatine riboside is a cancer cell-derived metabolite associated with arginine auxotrophy

The metabolic dependencies of cancer cells have substantial potential to be exploited to improve the diagnosis and treatment of cancer. Creatine riboside (CR) is identified as a urinary metabolite associated with risk and prognosis in lung and liver cancer. However, the source of high CR levels in patients with cancer as well as their implications for the treatment of these aggressive cancers remain unclear. By integrating multiomics data on lung and liver cancer, we have shown that CR is a cancer cell–derived metabolite. Global metabolomics and gene expression analysis of human tumors and matched liquid biopsies, together with functional studies, revealed that dysregulation of the mitochondrial urea cycle and a nucleotide imbalance were associated with high CR levels and indicators of a poor prognosis. This metabolic phenotype was associated with reduced immune infiltration and supported rapid cancer cell proliferation that drove aggressive tumor growth. CR^hi cancer cells were auxotrophic for arginine, revealing a metabolic vulnerability that may be exploited therapeutically. This highlights the potential of CR not only as a poor-prognosis biomarker but also as a companion biomarker to inform the administration of arginine-targeted therapies in precision medicine strategies to improve survival for patients with cancer.

Metabolomic profile of combined healthy lifestyle behaviours in humans: A systematic review

A combination of healthy lifestyle behaviours (i.e. regular physical activity, nutritious diet, no smoking, moderate alcohol, and healthy body mass) has been consistently associated with beneficial health outcomes including reduced risk of cardiometabolic diseases. Metabolomic profiles, characterized by distinct sets of biomarkers, have been described for healthy lifestyle behaviours individually and in combination. However, recent literature calls for systematic evaluation of these heterogenous data to identify potential clinical biomarkers relating to a combined healthy lifestyle. The objective was to systematically review existing literature on the metabolomic profile of combined healthy lifestyle behaviours. MEDLINE, EMBASE and Cochrane databases were searched through March 2022. Studies in humans outlining the metabolomic profile of a combination of two or more healthy lifestyle behaviours were included. Collectively, the metabolomic profile following regular adherence to combined healthy lifestyle behaviours points to a positive association with beneficial fatty acids and phosphocreatine, and inverse associations with triglycerides, trimethylamine N-oxide, and acylcarnitines. The findings suggest that a unique metabolomic profile is associated with combined healthy lifestyle behaviours. Additional research is warranted to further describe this metabolomic profile using targeted and untargeted metabolomic approaches along with uniform definitions of combined healthy lifestyle variables across populations. This article is protected by copyright. All rights reserved.

Assessment of Serum Urea, Creatinine and Uric Acid in Oral Cancer

Background: Oral squamous cell carcinoma (OSCC) is a common malignancy worldwide, leading to significant disease-associated social and financial burdens. The investigation of underlying mechanisms involved in carcinogenesis and tumor progression in OSCC might provide new therapeutic perspectives with an impact on disease control and patient survival. Our study aims to investigate the interrelation between metabolic processes, expressed through final catabolism products and clinicopathological characteristics in OSCC. Materials and methods: This is a single cancer comparative retrospective study investigating metabolic byproducts, namely serum urea, creatinine and uric acid, detected at the moment of diagnosis in patients with OSCC, in comparison to healthy controls. Clinical and paraclinical data regarding exposure to risk factors, disease staging and pathological characteristics were collected for all patients. Subjects with co-existing systemic or metabolic diseases, or with a history of malignancy, were excluded from the study. Subsequently, the metabolic byproducts revealing significant changes in OSCC patients were considered for a correlation analysis with the disease clinico-pathological characteristics. Results: Blood levels for urea, creatinine and uric acid were determined in a total of 225 subjects: 145 patients diagnosed with OSCC and 80 healthy control subjects admitted to our hospital between 2016 and 2021. The comparative analysis between groups revealed that the serum urea level was significantly lower in OSCC patients (p = 0.0344). Serum creatinine and uric acid did not reveal significant differences between groups. Furthermore, in advanced stages of the disease (stages III and IV), the blood level of urea was significantly lower compared to incipient OSCC (stages I and II) (p = 0.003). We found a negative correlation of serum urea levels with smoking (p = 0.0004) and cervical lymph node metastasis (p = 0.0070), and a positive correlation with aging (p = 0.0000). We found no significant correlation of serum urea with primary tumor size (p = 0.5061) and patient survival (p = 0.2932). Conclusions: Decreased serum urea levels are detected in patients with advanced OSCC, in correlation with lymph node metastasis. The invasive features of tumor cells in OSCC might be promoted in association with dysregulation of protein catabolism processes, facilitating aggressive behavior in OSCC.

Prenatal Maternal Smoke, DNA Methylation, and Multi-omics of Tissues and Child Health

PURPOSE OF REVIEW

Maternal tobacco smoking during pregnancy is of public health concern, and understanding the biological mechanisms can help to promote smoking cessation campaigns. This non-systematic review focuses on the effects of maternal smoking during pregnancy on offspring's epigenome, consistent in chemical modifications of the genome that regulate gene expression.

RECENT FINDINGS

Recent meta-analyses of epigenome-wide association studies have shown that maternal smoking during pregnancy is consistently associated with offspring's DNA methylation changes, both in the placenta and blood. These studies indicate that effects on blood DNA methylation can persist for years, and that the longer the duration of the exposure and the higher the dose, the larger the effects. Hence, DNA methylation scores have been developed to estimate past exposure to maternal smoking during pregnancy as biomarkers. There is robust evidence for DNA methylation alterations associated with maternal smoking during pregnancy; however, the role of sex, ethnicity, and genetic background needs further exploration. Moreover, there are no conclusive studies about exposure to low doses or during the preconception period. Similarly, studies on tissues other than the placenta and blood are scarce, and cell-type specificity within tissues needs further investigation. In addition, biological interpretation of DNA methylation findings requires multi-omics data, poorly available in epidemiological settings. Finally, although several mediation analyses link DNA methylation changes with health outcomes, they do not allow causal inference. For this, a combination of data from multiple study designs will be essential in the future to better address this topic.

Metabolome-wide association study of estimated glomerular filtration rates in Hispanics

Circulating metabolites are by-products of endogenous metabolism or exogenous sources and may inform disease states. Our study aimed to identify the source of variability in the association of metabolites with estimated glomerular filtration rate (eGFR) in Hispanics/Latinos with low chronic kidney disease prevalence by testing the association of 640 metabolites in 3,906 participants of the Hispanic Community Health Study/Study of Latinos. Metabolites were quantified in fasting serum through non-targeted mass spectrometry analysis. eGFR was regressed on inverse normally transformed metabolites in models accounting for study design and covariates. To identify the source of variation on eGFR associations, we tested the interaction of metabolites with lifestyle and clinical risk factors, and results were integrated with genotypes to identify metabolite genetic regulation. The mean age was 46 years, 43% were men, 22% were current smokers, 47% had a Caribbean Hispanic background, 19% had diabetes and the mean cohort eGFR was 96.4 ml/min/1.73 m². We identified 404 eGFR-metabolite associations (False Discovery Rate under 0.05). Of these, 69 were previously reported, and 79 were novel associations with eGFR replicated in one or more published studies. There were significant interactions with lifestyle and clinical risk factors, with larger differences in eGFR-metabolite associations within strata of age, urine albumin to creatinine ratio, diabetes and Hispanic/Latino background. Several newly identified metabolites were genetically regulated, and variants were located at genomic regions previously associated with eGFR. Thus, our results suggest complex mechanisms contribute to the association of eGFR with metabolites and provide new insights into these associations.

Impacts of Cigarette Smoking Status on Metabolomic and Gut Microbiota Profile in Male Patients With Coronary Artery Disease: A Multi-Omics Study

Background: Cigarette smoking has been considered a modifiable risk factor for coronary artery disease (CAD). Changes in gut microbiota and microbe-derived metabolites have been shown to influence atherosclerotic pathogenesis. However, the effect of cigarette smoking on the gut microbiome and serum metabolites in CAD remains unclear. Method: We profiled the gut microbiota and serum metabolites of 113 male participants with diagnosed CAD including 46 current smokers, 34 former smokers, and 33 never smokers by 16S ribosomal RNA (rRNA) gene sequencing and untargeted metabolomics study. A follow-up study was conducted. PICRUSt2 was used for metagenomic functional prediction of important bacterial taxa. Results: In the analysis of the microbial composition, the current smokers were characterized with depleted Bifidobacterium catenulatum, Akkermansia muciniphila, and enriched Enterococcus faecium, Haemophilus parainfluenzae compared with the former and never smokers. In the untargeted serum metabolomic study, we observed and annotated 304 discriminant metabolites, uniquely including ceramides, acyl carnitines, and glycerophospholipids. Pathway analysis revealed a significantly changed sphingolipids metabolism related to cigarette smoking. However, the change of the majority of the discriminant metabolites is possibly reversible after smoking cessation. While performing PICRUSt2 metagenomic prediction, several key enzymes (wbpA, nadM) were identified to possibly explain the cross talk between gut microbiota and metabolomic changes associated with smoking. Moreover, the multi-omics analysis revealed that specific changes in bacterial taxa were associated with disease severity or outcomes by mediating metabolites such as glycerophospholipids. Conclusions: Our results indicated that both the gut microbiota composition and metabolomic profile of current smokers are different from that of never smokers. The present study may provide new insights into understanding the heterogenic influences of cigarette smoking on atherosclerotic pathogenesis by modulating gut microbiota as well as circulating metabolites.

Prevalence and Associated Factors of Dyslipidemia Among Psychiatric Patients on Antipsychotic Treatment at Hawassa University Comprehensive Specialized Hospital

Background:

Dyslipidemia is one of the adverse metabolic outcomes associated with psychotropic medications and the nature of the mental illness itself. Therefore, this study aimed to assess magnitude of dyslipidemia and associated factors among patients with severe mental illness on antipsychotic treatments.

Methods:

A cross-sectional study was conducted among 245 patients with severe mental illness in Hawassa University Comprehensive Specialized Hospital, Sidama Regional state, Southern Ethiopia. Socio-demographic and other important data were collected using a structured questionnaire through a systematic random sampling technique. Individual dyslipidemia was characterized by the National Cholesterol Education Program Adult Treatment Panel-III (NCEP ATP-III) guideline.

Results:

Mean total cholesterol (TC) was significantly higher in males when compared to females (162.2 mg/dl vs 121 mg/dl, P = .023). While, mean LDL-cholesterol was significantly higher in females when compared to males (100.9 mg/dl vs 93.6 mg/dl, P = .028). Overall 58.4% (95% CI: 52.2-64.8) of participants had at least 1 dyslipidemia. The prevalence of TC ⩾200 mg/dl, HDL-cholesterol <40 mg/dl, triglyceride (TG) and LDL-cholesterol were 61 (24.9%), 75 (30.6%), 66 (26.9%), and 47 (19.2%), respectively. Female sex and smoking were significantly and positively associated with LDL-c dyslipidemia, the aOR (95% CI) were 2.1 (1.0-4.2) for female sex and 3.4 (1.1-10.5) for smoking. Also, Age >40 years was significantly associated with TC dyslipidemia, the aOR (95% CI) was 2.0 (1.1-3.7).

Conclusion:

More than half of psychiatric patients are at risk of developing cardiovascular and other related health problems. Therefore, periodic screening of lipid profiles during healthcare follow-up is mandatory to limit risks of cardiovascular-related comorbidities among patients with severe mental illness.

Ketone body 3-hydroxybutyrate as a biomarker of aggression

Human aggression is a complex behaviour, the biological underpinnings of which remain poorly known. To gain insights into aggression biology, we studied relationships with aggression of 11 low-molecular-weight metabolites (amino acids, ketone bodies), processed using ¹H nuclear magnetic resonance spectroscopy. We used a discovery sample of young adults and an independent adult replication sample. We studied 725 young adults from a population-based Finnish twin cohort born 1983-1987, with aggression levels rated in adolescence (ages 12, 14, 17) by multiple raters and blood plasma samples at age 22. Linear regression models specified metabolites as the response variable and aggression ratings as predictor variables, and included several potential confounders. All metabolites showed low correlations with aggression, with only one-3-hydroxybutyrate, a ketone body produced during fasting-showing significant (negative) associations with aggression. Effect sizes for different raters were generally similar in magnitude, while teacher-rated (age 12) and self-rated (age 14) aggression were both significant predictors of 3-hydroxybutyrate in multi-rater models. In an independent replication sample of 960 adults from the Netherlands Twin Register, higher aggression (self-rated) was also related to lower levels of 3-hydroxybutyrate. These exploratory epidemiologic results warrant further studies on the role of ketone metabolism in aggression.

Molecular approaches to lung cancer prevention

Lung cancer is generally diagnosed at advanced stages when surgical resection is not possible. Late diagnosis, along with development of chemoresistance, results in high mortality. Preventive approaches, including smoking cessation, chemoprevention and early detection are needed to improve survival. Smoking cessation combined with low-dose computed tomography screening has modestly improved survival. Chemoprevention has also shown some promise. Despite these successes, most lung cancer cases remain undetected until advanced stages. Additional early detection strategies may further improve survival and treatment outcome. Molecular alterations taking place during lung carcinogenesis have the potential to be used in early detection via noninvasive methods and may also serve as biomarkers for success of chemopreventive approaches. This review focuses on the utilization of molecular biomarkers to increase the efficacy of various preventive approaches.

Method comparison of HPLC-ninhydrin-photometry and UHPLC-PITC-tandem mass spectrometry for serum amino acid analyses in patients with complex congenital heart disease and controls

INTRODUCTION

Metabolomics studies are not routine when quantifying amino acids (AA) in congenital heart disease (CHD).

OBJECTIVES

Comparative analysis of 24 AA in serum by traditional high-performance liquid chromatography (HPLC) based on ion exchange and ninhydrin derivatisation followed by photometry (PM) with ultra-high-performance liquid chromatography and phenylisothiocyanate derivatisation followed by tandem mass spectrometry (TMS); interpretation of findings in CHD patients and controls.

METHODS

PM: Sample analysis as above (total run time, ~ 119 min). TMS: Sample analysis by AbsoluteIDQ® p180 kit assay (BIOCRATES Life Sciences AG, Innsbruck, Austria), which employs PITC derivatisation; separation of analytes on a Waters Acquity UHPLC BEH18 C18 reversed-phase column, using water and acetonitrile with 0.1% formic acid as the mobile phases; and quantification on a Triple-Stage Quadrupole tandem mass spectrometer (Thermo Fisher Scientific, Waltham, MA) with electrospray ionisation in the presence of internal standards (total run time, ~ 8 min). Calculation of coefficients of variation (CV) (for precision), intra- and interday accuracies, limits of detection (LOD), limits of quantification (LOQ), and mean concentrations.

RESULTS

Both methods yielded acceptable results with regard to precision (CV < 10% PM, < 20% TMS), accuracies (< 10% PM, < 34% TMS), LOD, and LOQ. For both Fontan patients and controls AA concentrations differed significantly between methods, but patterns yielded overall were parallel.

CONCLUSION

Serum AA concentrations differ with analytical methods but both methods are suitable for AA pattern recognition. TMS is a time-saving alternative to traditional PM under physiological conditions as well as in patients with CHD.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier NCT03886935, date of registration March 27th, 2019 (retrospectively registered).

A lipid-related metabolomic pattern of diet quality

BACKGROUND

Adherence to a healthy diet has been associated with reduced risk of chronic diseases. Identifying nutritional biomarkers of diet quality may be complementary to traditional questionnaire-based methods and may provide insights concerning disease mechanisms and prevention.

OBJECTIVE

To identify metabolites associated with diet quality assessed via the Alternate Healthy Eating Index (AHEI) and its components.

METHODS

This cross-sectional study used FFQ data and plasma metabolomic profiles, mostly lipid related, from the Nurses' Health Study (NHS, n = 1460) and Health Professionals Follow-up Study (HPFS, n = 1051). Linear regression models assessed associations of the AHEI and its components with individual metabolites. Canonical correspondence analyses (CCAs) investigated overlapping patterns between AHEI components and metabolites. Principal component analysis (PCA) and explanatory factor analysis were used to consolidate correlated metabolites into uncorrelated factors. We used stepwise multivariable regression to create a metabolomic score that is an indicator of diet quality.

RESULTS

The AHEI was associated with 83 metabolites in the NHS and 96 metabolites in the HPFS after false discovery rate adjustment. Sixty-three of these significant metabolites overlapped between the 2 cohorts. CCA identified "healthy" AHEI components (e.g., nuts, whole grains) and metabolites (n = 27 in the NHS and 33 in the HPFS) and "unhealthy" AHEI components (e.g., red meat, trans fat) and metabolites (n = 56 in the NHS and 63 in the HPFS). PCA-derived factors composed of highly saturated triglycerides, plasmalogens, and acylcarnitines were associated with unhealthy AHEI components while factors composed of highly unsaturated triglycerides were linked to healthy AHEI components. The stepwise regression analysis contributed to a metabolomics score as a predictor of diet quality.

CONCLUSION

We identified metabolites associated with healthy and unhealthy eating behaviors. The observed associations were largely similar between men and women, suggesting that metabolomics can be a complementary approach to self-reported diet in studies of diet and chronic disease.

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

BACKGROUND

The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows.

METHODS

We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites.

RESULTS

Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure.

CONCLUSION

In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.

Caution in studying and interpreting the lupus metabolome

Several metabolomics studies have shed substantial light on the pathophysiological pathways underlying multiple diseases including systemic lupus erythematosus (SLE). This review takes stock of our current understanding of this field. We compare, collate, and investigate the metabolites in SLE patients and healthy volunteers, as gleaned from published metabolomics studies on SLE. In the surveyed primary reports, serum or plasma samples from SLE patients and healthy controls were assayed using mass spectrometry or nuclear magnetic resonance spectroscopy, and metabolites differentiating SLE from controls were identified. Collectively, the circulating metabolome in SLE is characterized by reduced energy substrates from glycolysis, Krebs cycle, fatty acid β oxidation, and glucogenic and ketogenic amino acid metabolism; enhanced activity of the urea cycle; decreased long-chain fatty acids; increased medium-chain and free fatty acids; and augmented peroxidation and inflammation. However, these findings should be interpreted with caution because several of the same metabolic pathways are also significantly influenced by the medications commonly used in SLE patients, common co-morbidities, and other factors including smoking and diet. In particular, whereas the metabolic alterations relating to inflammation, oxidative stress, lipid peroxidation, and glutathione generation do not appear to be steroid-dependent, the other metabolic changes may in part be influenced by steroids. To conclude, metabolomics studies of SLE and other rheumatic diseases ought to factor in the potential contributions of confounders such as medications, co-morbidities, smoking, and diet.

Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

Metabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term 'metabolomics' refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

Impact of maternal smoking associated lyso-phosphatidylcholine 20:3 on offspring brain development

Maternal smoking during pregnancy affects fetal neurological development. Metabolomic studies in the general population suggest that smoking is associated with characteristic metabolic alterations. We investigated the association between the maternal smoking status, the fetal metabolome and head circumference at birth, as a surrogate parameter of brain development. 320 mother/newborn pairs of the Berlin Birth Cohort were investigated. Anthropometric parameters, including head circumference, of newborns of smoking mothers, former smoking mothers, and never smoking mothers were compared to assess the impact of maternal smoking behavior. Associations between maternal smoking behavior and 163 cord blood metabolites and associations between newborn head circumference and concentrations of smoking behavior related metabolites were analysed. Male newborns of smoking mothers had a reduced head circumference when compared with newborns from former smoking and never smoking mothers (p < 0.05). Using linear regression models corrected for established confounding factors, maternal smoking during pregnancy showed an independent association with head circumference (95% CI: -0.75～-0.41 cm, p = 2.45×10^-11). In a stepwise linear regression model corrected for known confounding factors of brain growth lyso-phosphatidylcholine 20:3 (95% CI: 6.68～39.88 cm, p = 4.62×10^-4) was associated with head circumference in male offspring only. None of the metabolites were associated with head circumference of female newborns. In conclusion, maternal smoking during pregnancy impacted on male offspring's development including brain development. The smoking related metabolite lyso-phosphatidylcholine 20:3 was associated with head circumference of male offspring.

Change in moderate alcohol consumption and quality of life: evidence from 2 population-based cohorts

BACKGROUND

Although the association of moderate alcohol consumption with specific disorders, such as cardiovascular disease and cancers, has been well documented, the evidence of the broader impact of alcohol consumption on health-related quality of life is less clear. Our objective was to examine the association of drinking patterns with changes in physical and mental well-being across populations.

METHODS

We conducted a multilevel analysis with multivariate responses in the population-representative FAMILY Cohort in the Hong Kong Special Administrative Region, China, to examine the association between alcohol drinking patterns across 2 waves (2009-2013) (i.e., quitters, initiators, persistent drinkers, persistent former drinkers and lifetime abstainers) and changes in physical and mental well-being (Physical and Mental Component Summary of the 12-Item Short Form Health Survey [SF-12]). Analyses were stratified by sex. We validated findings using a nationally representative cohort in the United States, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, 2001-2005).

RESULTS

In the FAMILY Cohort (n = 10 386; median follow-up 2.3 yr), the change in mental well-being was more favourable in female quitters than in lifetime abstainers (β = 1.44, 95% confidence interval [CI] 0.43 to 2.45; mean score change of +2.0 for quitters and +0.02 for lifetime abstainers). This association was validated in the NESARC (n = 31 079; median follow-up 3.1 yr) (β = 0.83, 95% CI 0.08 to 1.58; mean score change of -1.1 for quitters and -1.6 for lifetime abstainers).

INTERPRETATION

The change in mental well-being was more favourable in female quitters, approaching the level of mental well-being of lifetime abstainers within 4 years of quitting in both Chinese and American populations.

Disruption of histidine and energy homeostasis in chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a systemic condition that is too complex to be assessed by lung function alone. Metabolomics has the potential to help understand the mechanistic underpinnings that contribute to COPD pathogenesis. Since blood metabolomics may be affected by sex and body mass index (BMI), the aim of this study was to determine the metabolomic variability in male smokers with and without COPD who have a narrow BMI range.

Methods

We compared the quantitative proton nuclear magnetic resonance acquired serum metabolomics of a male Chinese Han population of non-smokers without COPD, and smokers with and without COPD. We also assessed the impact of smoking status on metabolite concentrations and the associations between metabolite concentrations and inflammatory markers such as serum interleukin-6 and histamine, and blood cell differential (%). Metabolomics data were log-transformed and auto-scaled for parametric statistical analysis. Mean normalized metabolite concentration values and continuous demographic variables were compared by Student’s t-test with Welch correction or ANOVA with post-hoc Tukey’s test, as applicable; t-test p-values for metabolomics data were corrected for false discovery rate (FDR). A Pearson association matrix was built to evaluate the relationship between metabolite concentrations, clinical parameters and markers of inflammation.

Results

Twenty-eight metabolites were identified and quantified. Creatine, glycine, histidine, and threonine concentrations were reduced in COPD patients compared to non-COPD smokers (FDR ≤15%). Concentrations of these metabolites were inversely correlated with interleukin-6 levels. COPD patients had overall dampening of metabolite concentrations including energy-related metabolic pathways such as creatine metabolism. They also had higher histamine levels and percent basophils compared to smokers without COPD.

Conclusion

COPD is associated with alterations in the serum metabolome, including a disruption in the histidine-histamine and creatine metabolic pathways. These findings support the use of metabolomics to understand the pathogenic mechanisms involved in COPD.

Trial registrationwww.clinicaltrials.gov, NCT03310177.

Association between the XKR6 rs7819412 SNP and serum lipid levels and the risk of coronary artery disease and ischemic stroke

Background

The present study aimed to expound the association between the XK related 6 gene (XKR6) rs7819412 single nucleotide polymorphism (SNP) and serum lipid profiles and the risk of coronary artery disease (CAD) and ischemic stroke.

Methods

The genetic makeup of the XKR6 rs7819412 SNP in 1783 unrelated participants (controls, 643; CAD, 588 and ischemic stroke, 552) of Han Chinese was obtained by the Snapshot technology.

Results

The genotypic frequencies of the SNP were disparate between CAD (GG, 81.0%; GA/AA, 19.0%) or ischemic stroke (GG, 81.2%; GA/AA, 18.8%) patients and healthy controls (GG, 85.7%, GA/AA, 14.3%; P < 0.05 vs. CAD or ischemic stroke; respectively). The A allele frequency was also diverse between CAD (10.1%) or ischemic stroke (10.0%) and control groups (7.5%; P < 0.05 vs. CAD or ischemic stroke; respectively). The GA/AA genotypes and A allele were associated with high risk of CAD and ischemic stroke (CAD: P = 0.026 for GA/AA vs. GG, P = 0.024 for A vs. G; Ischemic stroke: P = 0.029 for GA/AA vs. GG, P = 0.036 for A vs. G). The GA/AA genotypes were also associated with increased serum triglyceride (TG) concentration in CAD and total cholesterol (TC) concentration in ischemic stroke patients.

Conclusions

These data revealed that the XKR6 rs7819412 A allele was related to increased serum TG levels in CAD, TC levels in ischemic stroke patients and high risk of CAD and ischemic stroke.

Serum lipidome screening in patients with stage I non-small cell lung cancer

The ability of early lung cancer diagnosis is an unmet need in clinical practice. Lung cancer metabolomic analyses conducted so far have demonstrated several abnormalities in cancer lipid profile providing a rationale for further study of blood lipidome of the patients. In the present research, we performed a targeted lipidome screening to select molecules that show promise for early lung cancer detection. The study was conducted on serum samples collected from newly diagnosed, stage I non-small cell lung cancer (NSCLC) patients and non-cancer controls. A high-throughput mass spectrometry-based platform with confirmed interlaboratory reproducibility was used. The analyzed profile consisted of acylcarnitines, sphingomyelins, phosphatidylcholines and lysophosphatidylcholines. Among the assayed lipid species, the significant differences between NSCLC and non-cancer subjects were observed in the group of phosphatidylcholines (PC) and lysophosphatidylcholines (lysoPC), especially in the levels of lysoPC a C26:0; lysoPC a C26:1; PC aa C42:4; and PC aa C34:4. The metabolites mentioned above were used to create a multivariate classification model, which reliability was proved by permutation tests as well as external validation. Our study indicated choline-containing phospholipids as potential lung cancer markers. Further investigations of phospholipidome are crucial to better describe the shifts in metabolite composition occurring in lung cancer patients.

Biological and Functional Changes in Healthy Adult Smokers Who Are Continuously Abstinent From Smoking for One Year: Protocol for a Prospective, Observational, Multicenter Cohort Study

Background

The harm of smoking results mainly from long-term exposure to harmful and potentially harmful constituents (HPHCs) generated by tobacco combustion. Smoking cessation (SC) engenders favorable changes of clinical signs, pathomechanisms, and metabolic processes that together could reduce the harm of smoking-related diseases to a relative risk level approximating that of never-smokers over time. In most SC studies, the main focus is on the quitting rate of the SC program being tested. As there is limited information in the literature on short to multiple long-term functional or biological changes following SC, more data on short to mid-term favorable impacts of SC are needed.

Objective

The overall aim of the study was to assess the reversibility of the harm related to smoking over 1 year of continuous smoking abstinence (SA). This has been verified by assessing a set of biomarkers of exposure to HPHCs and a set of biomarkers of effect indicative of multiple pathophysiological pathways underlying the development of smoking-related diseases.

Methods

This multiregional (United States, Japan, and Europe), multicenter (42 sites) cohort study consisting of a 1-year SA period in an ambulatory setting was conducted from May 2015 to May 2017. A total of 1184 male and female adult healthy smokers, willing to quit smoking, were enrolled in the study. Nicotine replacement therapy (NRT) was provided for up to 3 months upon the subject’s request. SC counseling and behavioral support were continuously provided. Biomarkers of exposure to HPHCs and biomarkers of effect were assessed in urine and blood at baseline, Month 3, Month 6, and Month 12. Cardiovascular biomarkers of effect included parameters reflecting inflammation (white blood cell), lipid metabolism (high-density lipoprotein cholesterol), endothelial function (soluble intercellular adhesion molecule-1), platelet function (11-dehydrothromboxane B2), oxidative stress (8-epi-prostaglandin F2 alpha), and carbon monoxide exposure (carboxyhemoglobin). Respiratory biomarkers of effect included lung function parameters and cough symptoms. The biomarkers of effect to evaluate genotoxicity (total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol) and xenobiotic metabolism (cytochrome P450 2A6 activity) were also assessed. Continuous SA was verified at each visit following the actual quit date using self-reporting and chemical verification. Safety assessments included adverse events and serious adverse events, body weight, vital signs, spirometry, electrocardiogram, clinical chemistry, hematology and urine analysis safety panel, physical examination, and concomitant medications.

Results

In total, 1184 subjects (50.1% male) were enrolled; 30% of them quit smoking successfully for 1 year. Data analyses of the study results are ongoing and will be published after study completion.

Conclusions

This study provides insights into biological and functional changes and health effects, after continuous SA over 1 year. Study results will be instrumental in assessing novel alternative products to cigarettes considered for tobacco harm reduction strategies.

Trial Registration

ClinicalTrials.gov NCT02432729; http://clinicaltrials.gov/ct2/show/NCT02432729 (Archived by WebCite at http://www.webcitation.org/78QxovZrr)

International Registered Report Identifier (IRRID)

DERR1-10.2196/12138

The Metabolomic Signatures of Weight Change

Obesity represents a major health concern, not just in the West but increasingly in low and middle income countries. In order to develop successful strategies for losing weight, it is essential to understand the molecular pathogenesis of weight change. A number of pathways, implicating oxidative stress but also the fundamental regulatory of insulin, have been implicated in weight gain and in the regulation of energy expenditure. In addition, a considerable body of work has highlighted the role of metabolites generated by the gut microbiome, in particular short chain fatty acids, in both processes. The current review provides a brief understanding of the mechanisms underlying the associations of weight change with changes in lipid and amino acid metabolism, energy metabolism, dietary composition and insulin dynamics, as well as the influence of the gut microbiome. The changes in metabolomic profiles and the models outlined can be used as an accurate predictor for obesity and obesity related disorders.

Characterizing acyl-carnitine biosignatures for schizophrenia: a longitudinal pre- and post-treatment study

Subjects with schizophrenia have high risks of metabolic abnormalities and bioenergetic dysfunction. Acyl-carnitines involved in bioenergetic pathways provide potential biomarker targets for identifying early changes and onset characteristics in subjects with schizophrenia. We measured 29 acyl-carnitine levels within well-characterized plasma samples of adults with schizophrenia and healthy controls using liquid chromatography-mass spectrometry (LC-MS). Subjects with schizophrenia were measured at baseline and after 8 weeks of treatment. A total of 225 subjects with schizophrenia and 175 age- and gender-matched healthy controls were enrolled and 156 subjects completed the 8-week follow-up. With respect to plasma acyl-carnitines, the individuals with schizophrenia at baseline showed significantly higher levels of C4-OH (C3-DC) and C16:1, but lower concentrations of C3, C8, C10, C10:1, C10:2, C12, C14:1-OH, C14:2, and C14:2-OH when compared with healthy controls after controlling for age, sex, body mass index (BMI), smoking, and drinking. For the comparison between pretreatment and posttreatment subjects, all detected acyl-carnitines were significantly different between the two groups. Only the concentration of C3 and C4 were increased after selection by variable importance in projection (VIP) value >1.0 and false discovery rate (FDR) q value <0.05. A panel of acyl-carnitines were selected for the ability to differentiate subjects of schizophrenia at baseline from controls, pre- from post-treatment, and posttreatment from controls. Our data implicated acyl-carnitines with abnormalities in cellular bioenergetics of schizophrenia. Therefore, acyl-carnitines can be potential targets for future investigations into their roles in the pathoetiology of schizophrenia.

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.

Metabolic signature of healthy lifestyle and its relation with risk of hepatocellular carcinoma in a large European cohort

Background

Studies using metabolomic data have identified metabolites from several compound classes that are associated with disease-related lifestyle factors.

Objective

In this study, we identified metabolic signatures reflecting lifestyle patterns and related them to the risk of hepatocellular carcinoma (HCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

Design

Within a nested case-control study of 147 incident HCC cases and 147 matched controls, partial least squares (PLS) analysis related 7 modified healthy lifestyle index (HLI) variables (diet, BMI, physical activity, lifetime alcohol, smoking, diabetes, and hepatitis) to 132 targeted serum-measured metabolites and a liver function score. The association between the resulting PLS scores and HCC risk was examined in multivariable conditional logistic regression models, where ORs and 95% CIs were computed.

Results

The lifestyle component's PLS score was negatively associated with lifetime alcohol, BMI, smoking, and diabetes, and positively associated with physical activity. Its metabolic counterpart was positively related to the metabolites sphingomyelin (SM) (OH) C14:1, C16:1, and C22:2, and negatively related to glutamate, hexoses, and the diacyl-phosphatidylcholine PC aaC32:1. The lifestyle and metabolomics components were inversely associated with HCC risk, with the ORs for a 1-SD increase in scores equal to 0.53 (95% CI: 0.38, 0.74) and 0.28 (0.18, 0.43), and the associated AUCs equal to 0.64 (0.57, 0.70) and 0.74 (0.69, 0.80), respectively.

Conclusions

This study identified a metabolic signature reflecting a healthy lifestyle pattern which was inversely associated with HCC risk. The metabolic profile displayed a stronger association with HCC than did the modified HLI derived from questionnaire data. Measuring a specific panel of metabolites may identify strata of the population at higher risk for HCC and can add substantial discrimination compared with questionnaire data. This trial was registered at clinicaltrials.gov as NCT03356535.

Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case-Control Study in EPIC

Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites.Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk.Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%.Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk.Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators. Cancer Epidemiol Biomarkers Prev; 27(5); 531-40. ©2018 AACR.

NMR-based metabolomics of biofluids in cancer

This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.

BCL3-PVRL2-TOMM40 SNPs, gene-gene and gene-environment interactions on dyslipidemia

Little is known about the association of the BCL3-PVRL2-TOMM40 SNPs and dyslipidemia. This study was to detect 12 BCL3-PVRL2-TOMM40 SNPs, gene-gene and gene-environment interactions on dyslipidemia in the Chinese Maonan population. Genotyping was performed in 1130 normal and 832 dyslipidemia participants. Generalized multifactor dimensionality reduction was used to screen the best interaction combination among SNPs and environmental exposures. Allele and genotype frequencies of the detected SNPs were different between the two groups (P < 0.05-0.001). Association of the 12 SNPs and serum lipid levels was observed (P < 0.004-0.001). Multiple-locus linkage disequilibrium was not statistically independent in the population (D' = 0.01-0.98). The dominant model of rs8100239 and rs157580 SNPs, several haplotypes and G × G interaction haplotypes contributed to a protection, whereas the dominant model of rs10402271, rs3810143, rs519113, rs6859 SNPs, another haplotypes and G × G interaction haplotypes revealed an increased morbidity function (P < 0.05-0.001). There were significant three-locus model involving SNP-SNP, SNP-environment, haplotype-haplotype interactions (P < 0.05-0.001). The subjects carrying several genotypes and haplotypes decreased dyslipidemia risk, whereas the subjects carrying other genotypes and haplotypes increased dyslipidemia risk. The BCL3-PVRL2-TOMM40 SNPs, gene-gene and gene-environment interactions on dyslipidemia were observed in the Chinese Maonan population.

Untargeted metabolomics reveals multiple metabolites influencing smoking-related DNA methylation

AIM

We conducted a joint metabolomic-epigenomic study to identify patterns of epigenetic associations with smoking-related metabolites.

PATIENTS & METHODS

We performed an untargeted metabolome-wide association study of smoking and epigenome-wide association studies of smoking-related metabolites among 180 male twins. We examined the patterns of epigenetic association linked to smoking-related metabolites using hierarchical clustering.

RESULTS

Among 12 annotated smoking-related metabolites identified from a metabolome-wide association study, we observed significant hypomethylation associated with increased level of N-acetylpyrrolidine, cotinine, 5-hydroxycotinine and nicotine and hypermethylation associated with increased level of 8-oxoguanine. Hierarchical clustering revealed common and unique epigenetic-metabolic associations related to smoking.

CONCLUSION

Our study suggested that a joint metabolome-epigenome approach can reveal additional details in molecular responses to the environmental exposure to understand disease risk.

Metabolic Pathways and Networks Associated With Tobacco Use in Military Personnel

OBJECTIVE

The aim of this study is to use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel.

METHODS

Four hundred deidentified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or nonusers according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification.

RESULTS

Eighty individuals were classified as tobacco users compared with 320 nonusers on the basis of cotinine levels at least 10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid, and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways.

CONCLUSIONS

Tobacco use has complex metabolic effects that must be considered in evaluation of deployment-associated environmental exposures in military personnel.

Comparative metabolic and lipidomic profiling of human breast cancer cells with different metastatic potentials

This study conducted comprehensive and comparative metabolic and lipidomic profiling of a human epithelial breast cell line (MCF-10A), a slightly metastatic (MCF-7), and a highly metastatic (MDA-MB-231) breast cancer cell line using gas chromatography mass spectrometry (GC-MS) and direct infusion mass spectrometry (DI-MS). Among 39 metabolites identified by GC-MS analysis, xanthine, glucose-6-phosphate, mannose-6-phosphate, guanine, and adenine were selected as prognostic markers of breast cancer metastasis. Major metabolic pathways involved in differentiation of the cell lines were alanine, aspartate, and glutamate metabolism, purine metabolism and glycine, serine, and threonine metabolism. Among 44 intact lipid species identified by DI-MS analysis, the levels of most phospholipids were higher in both metastatic groups than in normal cells. Specifically, the levels of phosphatidylserine (PS) 18:0/20:4, phosphatidylinositol (PI) 18:0/20:4, and phosphatidylcholine (PC) 18:0/20:4 were markedly higher while those of phosphatidylethanolamine (PE) 18:1/18:1 and PI 18:0/18:1 were lower in MDA-MB-231 cells than in MCF-7 cells. A partial-least-squares regression model was developed and validated for predicting the metastatic potential of breast cancer cells. The information obtained in this study will be useful when developing diagnostic tools and for identifying potential therapeutic targets for metastatic breast cancer.

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.