Metabolome-wide Association Study Research Articles

Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the development of prognostic and therapeutic options for MAFLD. Moreover, the extent to which metabolic pathways are altered due to ongoing hepatic steatosis, inflammation and fibrosis and subsequent liver damage remains unclear. To uncover potential MAFLD pathogenesis in humans, we employed an untargeted nuclear magnetic resonance (NMR) spectroscopy- and high-resolution mass spectrometry (HRMS)-based multiplatform approach combined with a computational multiblock omics framework to characterize the plasma metabolomes and lipidomes of obese patients without (n = 19) or with liver biopsy confirmed MAFLD (n = 63). Metabolite features associated with MAFLD were identified using a metabolome-wide association study pipeline that tested for the relationships between feature responses and MAFLD. A metabolic pathway enrichment analysis revealed 16 pathways associated with MAFLD and highlighted pathway changes, including amino acid metabolism, bile acid metabolism, carnitine shuttle, fatty acid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and steroid metabolism. These results suggested that there were alterations in energy metabolism, specifically amino acid and lipid metabolism, and pointed to the pathways being implicated in alerted liver function, mitochondrial dysfunctions and immune system disorders, which have previously been linked to MAFLD in human and animal studies. Together, this study revealed specific metabolic alterations associated with MAFLD and supported the idea that MAFLD is fundamentally a metabolism-related disorder, thereby providing new perspectives for diagnostic and therapeutic strategies.

Mechanistic insights into the health benefits of fish-oil supplementation against fine particulate matter air pollution: a randomized controlled trial

Background:Dietary fish-oil supplementation might attenuate the associations between fine particulate matter (PM2.5) and subclinical biomarkers. However, the molecular mechanisms remain to be elucidated. This study aimed to explore the molecular mechanisms of fish-oil supplementation against the PM2.5-induced health effects.Methods:We conducted a randomized, double-blinded, and placebo-controlled trial among healthy college students in Shanghai, China, from September 2017 to January 2018. A total of 70 participants from the Fenglin campus of Fudan University were included. We randomly assigned participants to either supplementation of 2.5-gram fish oil (n = 35) or sunflower-seed oil (placebo) (n = 35) per day and conducted four rounds of health measurements in the last two months of the trial. As a post hoc exploratory study, the present untargeted metabolomics analysis used remaining blood samples collected in the previous trial and applied a Metabolome-Wide Association Study framework to compare the effects of PM2.5 on the metabolic profile between the sunflower-seed oil and fish oil groups.Results:A total of 65 participants completed the trial (34 of the fish oil group and 31 of the sunflower-seed oil group). On average, ambient PM2.5 concentration on the day of health measurements was 34.9 µg/m3 in the sunflower-seed oil group and 34.5 µg/m3 in the fish oil group, respectively. A total of 3833 metabolites were significantly associated with PM2.5 in the sunflower-seed oil group and 1757 in the fish oil group. Of these, 1752 metabolites showed significant between-group differences. The identified differential metabolites included arachidonic acid derivatives, omega-3 fatty acids, omega-6 fatty acids, and omega-9 fatty acids that were related to unsaturated fatty acid metabolism, which plays a role in the inflammatory responses.Conclusion:This trial suggests fish-oil supplementation could mitigate the PM2.5-induced inflammatory responses via modulating fatty acid metabolism, providing biological plausibility for the health benefits of fish-oil supplementation against PM2.5 exposure.Trial registration:This study is registered at ClinicalTrails.gov (NCT03255187).

Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer’s disease

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Metabolome-Wide Association Study of Multiple Plasma Metals with Serum Metabolomic Profile among Middle-to-Older-Aged Chinese Adults.

Metal exposure has been associated with risk of various cardio-metabolic disorders, and investigation on the association between exposure to multiple metals and metabolic responses may reveal novel clues to the underlying mechanisms. Based on a metabolome-wide association study of 17 plasma metals with untargeted metabolomic profiling of 189 serum metabolites among 1992 participants within the Dongfeng-Tongji cohort, we replicated two metal-associated pathways, linoleic acid metabolism and aminoacyl-tRNA biosynthesis, with novel metal associations (false discovery rate, FDR < 0.05), and we also identified two novel pathways, including biosynthesis of unsaturated fatty acids and alpha-linolenic acid metabolism, as associated with metal exposure (FDR < 0.05). Moreover, two-way orthogonal partial least-squares analysis showed that five metabolites, including aspartylphenylalanine, free fatty acid 14:1, uridine, carnitine C14:2, and LPC 18:2, contributed most to the joint covariation between the two data matrices (12.3%, 8.3%, 8.0%, 7.4%, and 7.3%, respectively). Further BKMR analysis showed significant positive joint associations of plasma Al, As, Ba, and Zn with aspartylphenylalanine and of plasma Ba, Co, Mn, and Pb with carnitine C14:2, when all the metals were at the 55th percentiles or above, compared with the median. We also found significant interactions between As and Ba in the association with aspartylphenylalanine (P for interaction = 0.048) and between Ba and Pb in the association with carnitine C14:2 (P for interaction < 0.001). Together, these findings may provide new insights into the mechanisms underlying the adverse health effects induced by metal exposure.

Metabolome-Wide Associations of Gestational Weight Gain in Pregnant Women with Overweight and Obesity.

Excessive gestational weight gain (GWG) is associated with adverse pregnancy outcomes. This metabolome-wide association study aimed to identify metabolomic markers for GWG. This longitudinal study included 39 Black and White pregnant women with a prepregnancy body mass index (BMI) of ≥ 25 kg/m2. Untargeted metabolomic profiling was performed using fasting plasma samples collected at baseline (mean: 12.1 weeks) and 32 weeks of gestation. The associations of metabolites at each time point and changes between the two time points with GWG were examined by linear and least absolute shrinkage and selection operator (LASSO) regression analyses. Pearson correlations between the identified metabolites and cardiometabolic biomarkers were examined. Of the 769 annotated metabolites, 88 metabolites at 32 weeks were individually associated with GWG, with four (phosphatidylcholine (PC) 34:4, triacylglycerol (TAG) 52:6, arachidonic acid, isoleucine) jointly associated with GWG (area under the receiver operating characteristic curve (AUC) for excessive GWG: 0.80, 95% CI: 0.67, 0.93). No correlations were observed between the 88 metabolites and insulin, C-peptide, and high-sensitivity C-reactive protein at 32 weeks. Twelve metabolites at baseline (AUC for excessive GWG: 0.80, 95% CI: 0.62, 0.99) and three metabolite changes (AUC for excessive GWG: 0.73, 95% CI: 0.44, 1.00) were jointly associated with GWG. We identified novel metabolites in the first and third trimesters associated with GWG, which may shed light on the pathophysiology of GWG.

Sleep duration, plasma metabolites, and obesity and diabetes: a metabolome-wide association study in US women.

Short and long sleep duration are associated with adverse metabolic outcomes, such as obesity and diabetes. We evaluated cross-sectional differences in metabolite levels between women with self-reported habitual short (<7 h), medium (7-8 h), and long (≥9 h) sleep duration to delineate potential underlying biological mechanisms. In total, 210 metabolites were measured via liquid chromatography-mass spectrometry in 9207 women from the Nurses' Health Study (NHS; N = 5027), the NHSII (N = 2368), and the Women's Health Initiative (WHI; N = 2287). Twenty metabolites were consistently (i.e. praw < .05 in ≥2 cohorts) and/or strongly (pFDR < .05 in at least one cohort) associated with short sleep duration after multi-variable adjustment. Specifically, levels of two lysophosphatidylethanolamines, four lysophosphatidylcholines, hydroxyproline and phenylacetylglutamine were higher compared to medium sleep duration, while levels of one diacylglycerol and eleven triacylglycerols (TAGs; all with ≥3 double bonds) were lower. Moreover, enrichment analysis assessing associations of metabolites with short sleep based on biological categories demonstrated significantly increased acylcarnitine levels for short sleep. A metabolite score for short sleep duration based on 12 LASSO-regression selected metabolites was not significantly associated with prevalent and incident obesity and diabetes. Associations of single metabolites with long sleep duration were less robust. However, enrichment analysis demonstrated significant enrichment scores for four lipid classes, all of which (most markedly TAGs) were of opposite sign than the scores for short sleep. Habitual short sleep exhibits a signature on the human plasma metabolome which is different from medium and long sleep. However, we could not detect a direct link of this signature with obesity and diabetes risk.

Exposure To Perfluoroalkyl Substances And Risk Of Hepatocellular Carcinoma In The Multiethnic Cohort

BACKGROUND AND AIM: Exposure to per- and polyfluoroalkyl substances (PFAS), a class of persistent organic pollutants, is ubiquitous. Animal studies suggest that PFAS may increase risk of fatty liver and hepatocellular carcinoma (HCC) via impacts on hepatic lipid, amino acid, and glucose metabolism, but human data are lacking. We examined associations of PFAS exposure, altered metabolic pathways, and risk of non-viral HCC. METHODS: In this nested case-control study, prediagnostic plasma PFAS and metabolomics were measured in 50 incident HCC cases and 50 individually matched controls from the Multiethnic Cohort Study (MEC). Cases and controls were matched by age, sex, race, and study area. PFAS exposure and risk of HCC were examined using conditional logistic regression. A metabolome wide association study and pathway enrichment analysis was performed for PFAS exposure and HCC risk, and key metabolites/metabolic pathways were identified using a meet in the middle approach. RESULTS: High perfluorooctane sulfonic acid (PFOS) levels (90th percentile from NHANES&amp;#x3e;55 &amp;#x3bc;g/L) were associated with more than 4 fold increased risk of HCC (OR=4.5; 95% CI: 1.2-16.0). The pathway enrichment analysis showed that PFOS exposure was associated with alterations in amino acid and glycan biosynthesis pathways, which were in turn associated with HCC risk. We identified four metabolites linking PFOS exposure with HCC, including glucose, butyric acid (a short chain fatty acid), α-Ketoisovaleric acid (a branched-chain α-keto acid), and 7alpha-Hydroxy-3-oxo-4-cholestenoate (a bile acid), each of which was positively associated with PFOS exposure and risk of HCC. CONCLUSTIONS: Exposure to high levels of PFOS was associated with increased risk of HCC, and the likely mechanisms were via alterations in glucose, amino acid, and bile acid metabolism. Larger studies are warranted to confirm these findings. Key Words: Chemical exposure, exposome, perfluorinated alkyl substance, hepatocellular carcinoma, metabolome, bile acid, metabolic pathway

Metabolic Pathways Altered by Air Pollution Exposure in Association with Lipid Profiles in Young Adults

BACKGROUND AND AIM: Air Pollution is a risk factor for obesity and cardiometabolic diseases in children and adults. We aim to examine the metabolic perturbations associated with air pollution and cardiometabolic health. METHODS: In year 2014 – 2018, we conducted a cross-sectional study assessing lipid profiles (triglycerides, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, very-low-density lipoprotein (VLDL) cholesterol), untargeted serum metabolomics using liquid chromatography-high-resolution mass spectrometry, and one-month and one-year averaged air pollution exposures to NO2, O3, PM2.5 and PM10 at residential addresses among 132 young adults in southern California. A Metabolome-wide association study was conducted to identify metabolomic signatures associated with air pollution exposure. Mummichog pathway enrichment analysis was used to assess altered metabolic pathways, followed by annotations of metabolomic features. Principal component analysis (PCA) of 36 metabolites with confirmed identity was performed to reduce dimensionality and identify clusters. Lastly, regression models were used to analyze the associations of metabolomic PC scores with air pollution and lipid profiles. RESULTS: In total, 4937 and 4372 metabolomic features were detected using HILIC positive and C18 negative modes, with 2047 and 1228 features significantly associated with at least one air pollutant in positive and negative ion mode, respectively (p &amp;#x3c; 0.05). Metabolic pathways associated with air pollution exposure included fatty acid, glycerophospholid, tryptophan, and tyrosine metabolism. PCA of 48 metabolites involved in the identified pathways indicated that one-month O3, PM10, PM2.5 and one-year NO2 air pollution exposure was positively associated with free fatty acids and oxidative byproducts-related PC score (p &amp;#x3c; 0.05). This PC score shown to be negatively associated with total cholesterol and LDL cholesterol (p &amp;#x3c; 0.05). CONCLUSIONS: This study indicated that air pollution exposure is associated with dysregulated fatty acid and lipid metabolism. KEYWORDS: Air Pollution; Metabolomics; Cardiometabolic Health; Lipolysis; Pathway Analysis

Metabolome-wide association study suggests antagonistic responses to cadmium and selenium in diseased human lungs

Background and Aim: Cadmium (Cd) is a toxic environmental metal that binds selenium (Se) and contributes to many lung diseases. Humans have widespread exposures to Cd through diet and cigarette smoking, and studies in rodent models show that Se can protect against Cd toxicities. We performed metabolome-wide association study (MWAS) of Cd and Se in diseased and non-diseased human lungs to test for possible Cd-Se interactions. Methods: We analyzed tissue from 31 human lung explants, including 25 from patients with end-stage lung diseases, including idiopathic pulmonary fibrosis, cystic fibrosis, and chronic obstructive lung disease (COPD)/emphysema. We used ICP-MS (Inductively Coupled Plasma Mass Spectrometry) to measure Cd and Se, and liquid chromatography-high-resolution mass spectrometry (LC-HRMS) to conduct metabolomics analysis. Results: Metabolic pathway associations with Cd were similar to those previously observed in experimental models, including amino acid, lipid and energy-related pathways, many of which were also associated with Se. Two-way hierarchical cluster analysis (HCA) of metabolites associated with Cd revealed separation of individuals according to disease, with COPD/emphysema in the highest Cd cluster, and non-diseased individuals in the lowest Cd cluster. HCA of Se-associated metabolites revealed that COPD/emphysema also clustered by lower Se compared to others. More pathway associations occurred for the ratio of Cd:Se than either Cd or Se alone, suggesting an antagonistic relationship, and network analysis showed that most metabolites were associated with either Cd or Se. A relatively small number of polyunsaturated fatty acids and metabolites associated with inflammatory signaling had high Eigenvector centrality scores, suggesting a central mechanism of antagonistic interaction. Conclusions: Overall, the data show that metabolic pathway responses in human lung vary with Cd:Se ratio in a pattern suggesting that Se is antagonistic to Cd toxicity. Keyword: Human lung disease, environmental metals, metabolic disruption, high-resolution metabolomics.

Agricultural pesticide exposure related to metabolic changes in Parkinson’s disease patients

Background: There are currently 13,543 pesticide products with 1059 active ingredients registered in California, potentially exposing residents of agricultural regions through drift and contamination. In order to comprehensively study agricultural pesticide exposure in a population-based study of Parkinson’s (PD), we determined networks of pesticide co-exposures due to living near agricultural applications (Central Valley, California). We estimated the risk of PD with patterns of co-exposure and assessed how PD-implicated co-exposures were related to the metabolome of patients in order to help understand biologic mechanisms and responses to exposure. Methods: We used lifetime participant address histories (n=1653), land-use maps, and the pesticide use reports database to estimate residential proximity-based exposure to 722 pesticides over a 40-year period. We applied an unsupervised, weighted pesticide co-exposure model based on WGCNA and exposure correlations to determine co-exposure modules, assessed influence on PD risk, and performed an exposure-related untargeted metabolome wide association study using LCMS data (5072 metabolites). Results: Our co-exposure model identified seven co-exposure modules based on 288 pesticides applied near the home of &amp;#x3e;25 participants. Of these, two were related to an increased risk of PD. Most strongly, one module representing co-exposures to 35 pesticides (OR=1.21 per SD, 95% CI=1.09, 1.38). Among the PD patients, this pesticide co-exposure module was related to differential intensity of 442 metabolites at p&amp;#x3c;0.05 (73 FDR&amp;#x3c;0.10, 10 FDR&amp;#x3c;0.05). This metabolite set was most strongly enriched for glycosphingolipid (p=0.002) and glycerophospholipid (p=0.003) metabolism pathways. Conclusions: Agriculturally, pesticides are rarely applied in isolation. We identified co-exposure modules related to PD risk. Among patients, the exposure mixture was strongly related to disturbances in biologic pathways relevant to PD pathogenesis (e.g., glycosphingolipids linked to inflammation and mitochondrial function in PD) and also known to be targeted by a number of pesticides (e.g., glycerophospholipids and choline/cholinergic pathways). Keywords: Pesticides; Metabolomics; Co-exposures; Parkinson’s disease

Metabolome-wide association study of prenatal exposure to air pollution and adverse birth outcomes in the Atlanta African American Maternal-Child cohort

Metabolome-wide association study of prenatal exposure to air pollution and adverse birth outcomes in the Atlanta African American Maternal-Child cohort

Use of high-resolution metabolomics to assess the biological perturbations associated with maternal exposure to Bisphenol A and Bisphenol F among pregnant African American women

BackgroundHuman and animal exposure to bisphenol A (BPA) has been associated with adverse developmental and reproductive effects. The molecular mechanisms by which BPA exposure exerts its effects are not well-understood, even less known about its analogues bisphenol F (BPF). To address these knowledge gaps, we conducted an untargeted metabolome-wide association study (MWAS) to identify metabolic perturbations associated with BPA/BPF exposures in a pregnant African American cohort. MethodsFrom a subset of study participants enrolled in the Atlanta African American Maternal-Child cohort, we collected both urine samples, for targeted exposure assessment of BPA (N = 230) and BPF (N = 48), and serum samples, for high-resolution metabolomics (HRM) profiling (N = 230), during early pregnancy (8–14 weeks’ gestation). Using an established untargeted HRM workflow consisting of MWAS modeling, pathway enrichment analysis, and chemical annotation and confirmation, we investigated the potential metabolic pathways and features associated with BPA/BPF exposures. ResultsThe geometric mean creatinine-adjusted concentrations of urinary BPA and BPF were 0.85 ± 2.58 and 0.70 ± 4.71 µg/g creatinine, respectively. After false positive discovery rate correction at 20 % level, 264 and 733 unique metabolic features were significantly associated with urinary BPA and BPF concentrations, representing 10 and 12 metabolic pathways, respectively. Three metabolic pathways, including steroid hormones biosynthesis, lysine and lipoate metabolism, were significantly associated with both BPA and BPF exposure. Using chemical standards, we have confirmed the chemical identity of 16 metabolites significantly associated with BPA or BPF exposure. ConclusionsOur findings support that exposure to BPA and BPF in pregnant women is associated with the perturbation of aromatic amino acid metabolism, xenobiotics metabolism, steroid biosynthesis, and other amino acid metabolism closely linked to stress responses, inflammation, neural development, reproduction, and weight regulation.

Metabolome-wide association study of the relationship between chlorpyrifos exposure and first trimester serum metabolite levels in pregnant Thai farmworkers

IntroductionOrganophosphate (OP) insecticides, including chlorpyrifos, have been linked with numerous harmful health effects on maternal and child health. Limited data are available on the biological mechanisms and endogenous pathways underlying the toxicity of chlorpyrifos exposures on pregnancy and birth outcomes. In this study, we measured a urinary chlorpyrifos metabolite and used high-resolution metabolomics (HRM) to identify biological perturbations associated with chlorpyrifos exposure among pregnant women in Thailand, who are disparately exposed to high levels of OP insecticides. MethodsThis study included 50 participants from the Study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE). We used liquid chromatography-high resolution mass spectrometry to conduct metabolic profiling on first trimester serum samples collected from participants to evaluate metabolic perturbations in relation to chlorpyrifos exposures. We measured 3,5,6-trichloro-2-pyridinol (TCPy), a specific metabolite of chlorpyrifos and chlorpyrifos-methyl, in first trimester urine samples to assess the levels of exposures. Following an untargeted metabolome-wide association study workflow, we used generalized linear models, pathway enrichment analyses, and chemical annotation to identify significant metabolites and pathways associated with urinary TCPy levels. ResultsIn the 50 SAWASDEE participants, the median urinary TCPy level was 4.36 μg TCPy/g creatinine. In total, 691 unique metabolic features were found significantly associated with TCPy levels (p < 0.05) after controlling for confounding factors. Pathway analysis of metabolic features associated with TCPy indicated perturbations in 24 metabolic pathways, most closely linked to the production of reactive oxygen species and cellular damage. These pathways include tryptophan metabolism, fatty acid oxidation and peroxisome metabolism, cytochromes P450 metabolism, glutathione metabolism, and vitamin B3 metabolism. We confirmed the chemical identities of 25 metabolites associated with TCPy levels, including glutathione, cystine, arachidic acid, itaconate, and nicotinamide adenine dinucleotide. DiscussionThe metabolic perturbations associated with TCPy levels were related to oxidative stress, cellular damage and repair, and systemic inflammation, which could ultimately contribute to health outcomes, including neurodevelopmental deficits in the child. These findings support the future development of sensitive biomarkers to investigate the metabolic underpinnings related to pesticide exposure during pregnancy and to understand its link to adverse outcomes in children.

Exposure to perfluoroalkyl substances and risk of hepatocellular carcinoma in a multiethnic cohort

Background & AimsExposure to poly- and perfluoroalkyl substances (PFAS), a class of persistent organic pollutants, is ubiquitous. Animal studies suggest that PFAS may increase risk of fatty liver and hepatocellular carcinoma (HCC) via impacts on hepatic lipid, amino acid, and glucose metabolism, but human data is lacking. We examined associations between PFAS exposure, altered metabolic pathways, and risk of non-viral HCC.MethodsIn this nested case-control study, pre-diagnostic plasma PFAS and metabolomics were measured in 50 incident HCC cases and 50 individually matched controls from the Multiethnic Cohort (MEC) study. Cases/controls were matched by age, sex, race, and study area. PFAS exposure and risk of HCC were examined using conditional logistic regression. A metabolome-wide association study and pathway enrichment analysis was performed for PFAS exposure and HCC risk, and key metabolites/metabolic pathways were identified using a meet in the middle approach.ResultsHigh perfluorooctane sulfonic acid (PFOS) levels (90th percentile from NHANES; >55 μg/L) were associated with 4.5-fold increased risk of HCC (odds ratio 4.5, 95% CI 1.2-16.0). Pathway enrichment analysis showed that PFOS exposure was associated with alterations in amino acid and glycan biosynthesis pathways, which were also associated with HCC risk. We identified 4 metabolites linking PFOS exposure with HCC, including glucose, butyric acid (a short-chain fatty acid), α-ketoisovaleric acid (a branched-chain α-keto acid), and 7α-hydroxy-3-oxo-4-cholestenoate (a bile acid), each of which was positively associated with PFOS exposure and risk of HCC.ConclusionThis proof-of-concept analysis shows that exposure to high PFOS levels was associated with increased risk of non-viral HCC, likely via alterations in glucose, amino acid, and bile acid metabolism. Larger studies are needed to confirm these findings.Lay summaryPer- and polyfluoroalkyl substances (PFAS), often referred to as “forever chemicals” because they are difficult to break down and stay in the human body for years, are extremely common and can cause liver damage. In a first of its kind study, we found that exposure to high levels of perfluorooctanesulfonic acid, one of the most common PFAS chemicals, was linked to increased risk of hepatocellular carcinoma in humans. Hepatocellular carcinoma is difficult to treat and is one of the most common forms of liver cancer, and these findings may provide new avenues for helping to prevent this disease.

Abstract MP14: In Utero Exposure To Metals And Trace Elements affects Cord Blood Metabolome Profile: Findings From An Urban Minority Birth Cohort In The United States

Background: Exposure to metals lead (Pb), mercury (Hg), and cadmium (Cd) and trace elements selenium (Se) and manganese (Mn) has been linked to the developmental origins of cardiometabolic diseases, but the mechanisms are not well-understood. Objective: Conduct a metabolome-wide association study to understand how in utero exposure to Pb, Hg, Cd, Se, and Mn affects the metabolic programming of fetuses. Methods: We used data from mother-infant pairs in the Boston Birth Cohort. We measured metals and trace elements in maternal red blood cells (RBCs) collected 24-72 hours after delivery, and metabolites in cord blood collected at birth. We used multivariable linear regression to examine associations of metals and trace elements with metabolites and Bonferroni correction to account for multiple comparisons. We assessed non-linear associations of metals and trace elements with metabolites using restricted cubic spline plots. Results: This analysis included 690 mother-infant pairs (57% Black and 24% Hispanic). After Bonferroni correction, 25 cord metabolites were associated with at least one metal or trace element (Figure). Pb was negatively associated with the xenobiotic piperine, Cd was positively associated with xenobiotics cotinine and hydroxycotinine, and Hg was associated with 8 lipid metabolites (in both directions). Mn and Se shared associations with 6 metabolites (in both directions), which mostly included nucleotides and amino acids; Mn was additionally associated C36:4 hydroxy phosphatidylcholine and Se was additionally associated with 7 metabolites (mostly amino acids, nucleotides, and carnitines). Most associations were linear. Discussion: Maternal RBC metal and trace element concentrations were associated in a dose-dependent fashion with cord blood metabolites. What remains to be determined is whether these metals- and trace elements-associated changes in cord metabolites can influence a child’s future risk of cardiometabolic diseases.

Abstract P203: Metabolomic Markers Of Gestational Weight Gain In Overweight And Obese Pregnant Women-a Longitudinal Study

Background: Optimal gestational weight gain (GWG) is critical for fetal development and maternal health. Few studies have investigated metabolomic markers of GWG. Thus, we performed a metabolome-wide association study with GWG among pregnant women in the US. Methods: This longitudinal study included overweight or obese pregnant women (pre-pregnancy BMI ≥ 25) enrolled in the Health in Pregnancy and Postpartum study in early pregnancy (mean gestational week (GW) at baseline=12). Fasting plasma samples were collected both at baseline (N=39) and 32 GW (N=29). Untargeted metabolomic profiling was conducted using three different analytical platforms, including GC-TOF MS, HILIC-QTOF MS/MS, and CSH-QTOF MS/MS. Linear regressions were performed to identify metabolites at each time point and the change between two time points (i.e., metabolites 32 wk - metabolites baseline )/metabolites baseline ) that were individually associated with total GWG, a difference between delivery weight and pre-pregnancy weight. The least absolute shrinkage and selection operator (LASSO) regressions were conducted to select metabolites that were jointly associated with total GWG. Results: The mean (SD) age of 39 women enrolled was 30.4 (5.4) years and 38.5% were Blacks. A total of 769 known metabolites were profiled and annotated. Eight metabolites at 32 GW, including PC (34:4), LPC (22:5), isoleucine, arachidonic acid, TAG (52:6), TAG (58:7), and glyceric acid were positively whereas 3-Hydroxybutyrylcarnitine was negatively associated with GWG in both linear regressions (FDR &lt; 0.1) and LASSO regressions (with no-zero coefficients) after adjusting for age, race, parity, and pre-pregnancy BMI (Figure 1). Metabolites at around 12 GW or changes between two time points were not associated with GWG (all FDRs ≥ 0.1). Conclusions: We identified eight metabolites at 32 GW that were significantly associated with total GWG in this longitudinal study of overweight and obese pregnant women. Future studies are warranted to replicate our findings.

Pharmacometabolomic study of drug response to antihypertensive medications for hypertension marker identification in Han Chinese individuals in Taiwan

Various groups of antihypertensive drugs targeting different pathways have been developed; however, the pharmacometabolic responses to these drugs have rarely been compared to elucidate the common pathway of blood pressure regulation. Here, we performed a comparative multi-dimensional pharmacometabolic study on the four major lines of antihypertensive drugs, namely angiotensin-converting enzyme inhibitors (ACEis), angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), and diuretics (DIURs), through ultra-performance liquid chromatography coupled to quantum time-of-flight mass spectrometry. Two hundred fifty patients with young-onset hypertension, who were equally divided among five study groups: non-medicated, ACEi, ARB, CCB, and DIUR groups, were recruited. In a metabolome-wide association study conducted through analysis of covariance, 37 molecular features significantly associated with pharmacometabolic responses to antihypertensive drugs were identified. One-third of these features were shared by multiple medications. ACEis, ARBs, and DIURs shared more features than CCB, partially reflecting that ACEis, ARBs, and DIURs affect the renin-angiotensin-aldosterone system. Thirteen molecular features were consistently identified by all four models of the analysis of covariance. A tandem mass spectrometry (or MS/MS) experiment was performed to decipher the chemical structure of these 13 molecular features, including ARB-associated lysophosphatidylcholine (P4135), CCB-associated diacylglycerol(15:0/18:2) (P1175), and DIUR-associated oleamide (P1516). In addition, diacylglycerol(15:0/14:2) (P408) was significantly associated with the pharmacometabolic response to all four antihypertensive drugs. The identified metabolites provide insights into the mechanisms of blood pressure regulation and potential predictive markers of pharmacometabolic responses to antihypertensive drugs.

Genome-wide scan of Alzheimer disease cohort identifies genetic loci associated with human brain metabolite levels.

Although metabolome-wide association study (MWAS) has been performed in a wide range of tissue types, such as serum, plasma, urine, saliva, and cerebrospinal fluid (CSF), it has not been conducted on any brain tissue. Here we seek to expand our knowledge on the genetic influence of brain metabolism and on the contribution of metabolism abnormality to AD with the metabolomics approach. We aim to identify metabolite quantitative trait loci (metabQTLs) with the largest AD brain cohort available. We performed the first brain MWAS with 460 parietal cortex brains from the Knight-ADRC. 880 metabolites were measured by the powerful non-targeted Metabolon platform (HD4). European individuals were selected, and the analyses were adjusted for age at death, sex, genotype array methods, and genetic components. We identified 31 locus-metabolite associations in 30 metabolites with genome-wide significance. 7 associations were significant after study-wide Bonferroni correction. We are performing functional characterization and replication leveraging datasets from ROSMAP brain cohort, WADRC CSF cohort, and other tissues' cohorts. The strongest locus-metabolite association (p=5.2e-104), found in N6-methyllysine in the discovery phase, was first identified in CSF MWAS (Panyard et al., biorxiv, 2020). The first brain metabolome-wide association study discovered the importance of genetic influence on brain metabolite levels. Following expectation, brain metabQTLs can be replicated in the CSF study, implicating that brain and CSF share genetic features in modulating metabolism.

Lead exposure and serum metabolite profiles in pregnant women in Mexico City

BackgroundLead (Pb) exposure is a global health hazard causing a wide range of adverse health outcomes. Yet, the mechanisms of Pb toxicology remain incompletely understood, especially during pregnancy. To uncover biological pathways impacted by Pb exposure, this study investigated serum metabolomic profiles during the third trimester of pregnancy that are associated with blood Pb and bone Pb.MethodsWe used data and specimens from 99 women enrolled in the Programming Research in Obesity, Growth, Environment, and Social Stressors birth cohort in Mexico City. Maternal Pb exposure was measured in whole blood samples from the third trimester of pregnancy and in the tibia and patella bones at 1 month postpartum. Third-trimester serum samples underwent metabolomic analysis; metabolites were identified based on matching to an in-house analytical standard library. A metabolome-wide association study was performed using multiple linear regression models. Class- and pathway-based enrichment analyses were also conducted.ResultsThe median (interquartile range) blood Pb concentration was 2.9 (2.6) µg/dL. Median bone Pb, measured in the tibia and patella, were 2.5 (7.3) µg/g and 3.6 (9.5) µg/g, respectively. Of 215 total metabolites identified in serum, 31 were associated with blood Pb (p < 0.05). Class enrichment analysis identified significant overrepresentation of metabolites classified as fatty acids and conjugates, amino acids and peptides, and purines. Tibia and patella Pb were associated with 14 and 8 metabolites, respectively (p < 0.05). Comparing results from bone and blood Pb, glycochenodeoxycholic acid, glycocholic acid, and 1-arachidonoylglycerol were positively associated with blood Pb and tibia Pb, and 7-methylguanine was negatively associated with blood Pb and patella Pb. One metabolite, 5-aminopentanoic acid, was negatively associated with all three Pb measures.ConclusionsThis study identified serum metabolites in pregnant women associated with Pb measured in blood and bone. These findings provide insights on the metabolic profile around Pb exposure in pregnancy and information to guide mechanistic studies of toxicological effects for mothers and children.

CSF metabolites associated with CSF NeuroToolKit biomarkers

AbstractBackgroundMetabolomics technology has emerged as a tool to study small molecules influenced by age, sex, genetics, lifestyle, and disease processes. Correlating metabolites in cerebrospinal fluid (CSF) with established and developing Alzheimer’s disease (AD) CSF biomarkers may elucidate additional changes that are associated with early AD pathology and enhance our knowledge of the disease.MethodThe relative abundance of untargeted metabolites was assessed via Metabolon’s UHPLC/MS platform in 161 non‐Hispanic white, cognitively unimpaired individuals from the Wisconsin Registry for Alzheimer’s Prevention (WRAP). A metabolome‐wide association study (MWAS) was conducted between 269 known CSF metabolites and CSF biomarkers, which were measured with the exploratory Roche NeuroToolKit assays, a panel of automated robust prototype immunoassays (Roche Diagnostics International Ltd): phosphorylated tau (P‐tau), total tau (T‐tau), amyloid β (Aβ42), Aβ42/40, neurofilament light protein (NFL), neurogranin, chitinase‐3‐like protein 1 (YKL‐40), S100b, glial fibrillary acidic protein (GFAP), interleukin‐6 (IL‐6), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and α‐synuclein. Linear mixed‐effects regression analyses were performed with random intercepts for individual and family adjusting for age, gender, body mass index, and years of education. The metabolome‐wide significance was determined by a false discovery rate (FDR)‐corrected p&lt;0.05. The significant metabolites from WRAP were subsequently tested in 154 non‐Hispanic white, cognitively unimpaired individuals from the Wisconsin Alzheimer’s Disease Research Center (ADRC). Using single nucleotide polymorphisms (SNP) associated with the top metabolites, we applied linear mixed‐effects models to perform mediation analyses.ResultThe MWAS results for each NeuroToolKit biomarker from WRAP are shown in Figure 1. Metabolites were significantly associated with all biomarkers except Ab42/40 and IL‐6. Top metabolites that were associated with multiple NeuroToolKit CSF biomarkers are shown in Table 1. Significant mediation effects of stearoyl sphingomyelin(d18:1/18:0)(SM(d18:1/18:0)) were detected for P‐tau and sTREM2 (Figure 2).ConclusionThis study provides evidence that CSF metabolites are associated with AD‐related pathology through most AD CSF biomarkers and may be influenced by upstream genetic variation. The significant results for Aβ42 and Aβ40, but nonsignificant results for Aβ42/40 indicate that the metabolites associated with Aβ42 and Aβ40 may influence production of amyloid in general versus clearance of the pathological form, Aβ42.