Metabolic profiling of aortic stenosis and hypertrophic cardiomyopathy identifies mechanistic contrasts in substrate utilization.

Aortic stenosis (AS) and hypertrophic cardiomyopathy (HCM) are distinct disorders leading to left ventricular hypertrophy (LVH), but whether cardiac metabolism substantially differs between these in humans remains to be elucidated. We undertook an invasive (aortic root, coronary sinus) metabolic profiling in patients with severe AS and HCM in comparison with non-LVH controls to investigate cardiac fuel selection and metabolic remodeling. These patients were assessed under different physiological states (at rest, during stress induced by pacing). The identified changes in the metabolome were further validated by metabolomic and orthogonal transcriptomic analysis, in separately recruited patient cohorts. We identified a highly discriminant metabolomic signature in severe AS in all samples, regardless of sampling site, characterized by striking accumulation of long-chain acylcarnitines, intermediates of fatty acid transport across the inner mitochondrial membrane, and validated this in a separate cohort. Mechanistically, we identify a downregulation in the PPAR-α transcriptional network, including expression of genes regulating fatty acid oxidation (FAO). In silico modeling of ß-oxidation demonstrated that flux could be inhibited by both the accumulation of fatty acids as a substrate for mitochondria and the accumulation of medium-chain carnitines which induce competitive inhibition of the acyl-CoA dehydrogenases. We present a comprehensive analysis of changes in the metabolic pathways (transcriptome to metabolome) in severe AS, and its comparison to HCM. Our results demonstrate a progressive impairment of ß-oxidation from HCM to AS, particularly for FAO of long-chain fatty acids, and that the PPAR-α signaling network may be a specific metabolic therapeutic target in AS.

Plasma Metabolites and Life's Simple 7 in REGARDS.

BACKGROUND: The American Heart Association's Life's Simple 7 (LS7) is a health metric that captures important factors associated with cardiovascular and cerebrovascular health. Previous studies highlight the potential of plasma metabolites to serve as a marker for lifestyle and health behavior that could be a target for stroke prevention. The objectives of this study were to identify metabolites that were associated with LS7 and incident ischemic stroke and mediate the relationship between the two. METHODS: Targeted metabolomic profiling of 162 metabolites by liquid chromatography-tandem mass spectrometry was used to identify candidate metabolites in a stroke case-cohort nested within the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Weighted linear regression and weighted Cox proportional hazard models were used to identify metabolites that were associated with LS7 and incident ischemic stroke, respectively. Effect measures were based on a 1-SD change in metabolite level. Metabolite mediators were examined using inverse odds ratio weighting mediation analysis. RESULTS: The study comprised 1075 ischemic stroke cases and 968 participants in the random cohort sample. Three out of 162 metabolites were associated with the overall LS7 score including guanosine (ß, -0.46 [95% CI, -0.65 to -0.27]; P=2.87×10-6), cotinine (ß, -0.49 [95% CI, -0.70 to -0.28]; P=7.74×10-6), and acetylneuraminic acid (ß, -0.59 [95% CI, -0.77 to -0.42]; P=4.29×10-11). Guanosine (hazard ratio, 1.47 [95% CI, 1.31-1.65]; P=6.97×10-11), cotinine (hazard ratio, 1.30 [95% CI, 1.16-1.44]; P=2.09×10-6), and acetylneuraminic acid (hazard ratio, 1.29 [95% CI, 1.15-1.45]; P=9.24×10-6) were associated with incident ischemic stroke. The mediation analysis identified guanosine (27% mediation, indirect effect; P=0.002), cotinine (30% mediation, indirect effect; P=0.004), and acetylneurminic acid (22% mediation, indirect effect; P=0.041) partially mediated the relationship between LS7 and ischemic stroke. CONCLUSIONS: We identified guanosine, cotinine, and acetylneuraminic acid that were associated with LS7, incident ischemic stroke, and mediated the relationship between LS7 and ischemic stroke.

Plasma Metabolites Link Dietary Patterns to Stroke Risk.

OBJECTIVE: While dietary intake is linked to stroke risk, surrogate markers that could inform personalized dietary interventions are lacking. We identified metabolites associated with diet patterns and incident stroke in a nested cohort from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. METHODS: Levels of 162 metabolites were measured in baseline plasma from stroke cases (n = 1,198) and random controls (n = 904). We examined associations between metabolites and a plant-based diet pattern previously linked to reduced stroke risk in REGARDS. Secondary analyses included 3 additional stroke-associated diet patterns: a Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Southern diet. Metabolites were tested using Cox proportional hazards models with incident stroke as the outcome. Replication was performed in the Jackson Heart Study (JHS). Inverse odds ratio-weighted mediation was used to determine whether metabolites mediated the association between a plant-based diet and stroke risk. RESULTS: Metabolites associated with a plant-based diet included the gut metabolite indole-3-propionic acid (ß = 0.23, 95% confidence interval [CI] [0.14, 0.33], p = 1.14 × 10-6 ), guanosine (ß = -0.13, 95% CI [-0.19, -0.07], p = 6.48 × 10-5 ), gluconic acid (ß = -0.11, 95% CI [-0.18, -0.04], p = 2.06 × 10-3 ), and C7 carnitine (ß = -0.16, 95% CI [-0.24, -0.09], p = 4.14 × 10-5 ). All of these metabolites were associated with both additional diet patterns and altered stroke risk. Mediation analyses identified guanosine (32.6% mediation, p = 1.51 × 10-3 ), gluconic acid (35.7%, p = 2.28 × 10-3 ), and C7 carnitine (26.2%, p = 1.88 × 10-2 ) as mediators linking a plant-based diet to reduced stroke risk. INTERPRETATION: A subset of diet-related metabolites are associated with risk of stroke. These metabolites could serve as surrogate markers that inform dietary interventions. ANN NEUROL 2023;93:500-510.

Metabolic basis to Sherpa altitude adaptation.

The Himalayan Sherpas, a human population of Tibetan descent, are highly adapted to life in the hypobaric hypoxia of high altitude. Mechanisms involving enhanced tissue oxygen delivery in comparison to Lowlander populations have been postulated to play a role in such adaptation. Whether differences in tissue oxygen utilization (i.e., metabolic adaptation) underpin this adaptation is not known, however. We sought to address this issue, applying parallel molecular, biochemical, physiological, and genetic approaches to the study of Sherpas and native Lowlanders, studied before and during exposure to hypobaric hypoxia on a gradual ascent to Mount Everest Base Camp (5,300 m). Compared with Lowlanders, Sherpas demonstrated a lower capacity for fatty acid oxidation in skeletal muscle biopsies, along with enhanced efficiency of oxygen utilization, improved muscle energetics, and protection against oxidative stress. This adaptation appeared to be related, in part, to a putatively advantageous allele for the peroxisome proliferator-activated receptor A (PPARA) gene, which was enriched in the Sherpas compared with the Lowlanders. Our findings suggest that metabolic adaptations underpin human evolution to life at high altitude, and could have an impact upon our understanding of human diseases in which hypoxia is a feature.

Lipid zonation and phospholipid remodeling in nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) can progress from simple steatosis (i.e., nonalcoholic fatty liver [NAFL]) to nonalcoholic steatohepatitis (NASH), cirrhosis, and cancer. Currently, the driver for this progression is not fully understood; in particular, it is not known how NAFLD and its early progression affects the distribution of lipids in the liver, producing lipotoxicity and inflammation. In this study, we used dietary and genetic mouse models of NAFL and NASH and translated the results to humans by correlating the spatial distribution of lipids in liver tissue with disease progression using advanced mass spectrometry imaging technology. We identified several lipids with distinct zonal distributions in control and NAFL samples and observed partial to complete loss of lipid zonation in NASH. In addition, we found increased hepatic expression of genes associated with remodeling the phospholipid membrane, release of arachidonic acid (AA) from the membrane, and production of eicosanoid species that promote inflammation and cell injury. The results of our immunohistochemistry analyses suggest that the zonal location of remodeling enzyme LPCAT2 plays a role in the change in spatial distribution for AA-containing lipids. This results in a cycle of AA-enrichment in pericentral hepatocytes, membrane release of AA, and generation of proinflammatory eicosanoids and may account for increased oxidative damage in pericentral regions in NASH. CONCLUSION: NAFLD is associated not only with lipid enrichment, but also with zonal changes of specific lipids and their associated metabolic pathways. This may play a role in the heterogeneous development of NAFLD. (Hepatology 2017;65:1165-1180).

Integration of metabolomics, lipidomics and clinical data using a machine learning method.

BACKGROUND: The recent pandemic of obesity and the metabolic syndrome (MetS) has led to the realisation that new drug targets are needed to either reduce obesity or the subsequent pathophysiological consequences associated with excess weight gain. Certain nuclear hormone receptors (NRs) play a pivotal role in lipid and carbohydrate metabolism and have been highlighted as potential treatments for obesity. This realisation started a search for NR agonists in order to understand and successfully treat MetS and associated conditions such as insulin resistance, dyslipidaemia, hypertension, hypertriglyceridemia, obesity and cardiovascular disease. The most studied NRs for treating metabolic diseases are the peroxisome proliferator-activated receptors (PPARs), PPAR-α, PPAR-γ, and PPAR-δ. However, prolonged PPAR treatment in animal models has led to adverse side effects including increased risk of a number of cancers, but how these receptors change metabolism long term in terms of pathology, despite many beneficial effects shorter term, is not fully understood. In the current study, changes in male Sprague Dawley rat liver caused by dietary treatment with a PPAR-pan (PPAR-α, -γ, and -δ) agonist were profiled by classical toxicology (clinical chemistry) and high throughput metabolomics and lipidomics approaches using mass spectrometry. RESULTS: In order to integrate an extensive set of nine different multivariate metabolic and lipidomics datasets with classical toxicological parameters we developed a hypotheses free, data driven machine learning approach. From the data analysis, we examined how the nine datasets were able to model dose and clinical chemistry results, with the different datasets having very different information content. CONCLUSIONS: We found lipidomics (Direct Infusion-Mass Spectrometry) data the most predictive for different dose responses. In addition, associations with the metabolic and lipidomic data with aspartate amino transaminase (AST), a hepatic leakage enzyme to assess organ damage, and albumin, indicative of altered liver synthetic function, were established. Furthermore, by establishing correlations and network connections between eicosanoids, phospholipids and triacylglycerols, we provide evidence that these lipids function as a key link between inflammatory processes and intermediary metabolism.

Workplace food purchases, dietary intake, and gut microbial metabolites in a secondary analysis of the ChooseWell 365 study.

BACKGROUND: Dietary choices can affect human health through alterations in gut microbial metabolism, and gut microbial metabolites could serve as biomarkers for disease risk conferred by dietary intake. However, self-reported dietary intake may not reflect true intake. OBJECTIVES: We identified circulating metabolites, including gut microbiome-related metabolites, associated with adherence to a healthy diet in the ChooseWell 365 study. In this randomized clinical trial, the dietary choices of hospital employees were assessed over 24 mo using not only 24-h dietary recalls but also electronic records of hospital cafeteria purchases. METHODS: Plasma metabolites were profiled from 470 participants. Two targeted metabolomics methods were developed and implemented to expand detection coverage for metabolites related to gut microbial activity. Linear regression models were used to associate metabolites with Healthy Purchasing Scores (HPSs) derived from cafeteria purchases and Healthy Eating Index-2015 (HEI-15) scores derived from dietary recalls. RESULTS: Fourteen metabolites were concordantly associated with the HPS and HEI-15 scores in multivariable models adjusted for age, gender, and race, including the gut microbiome-related metabolites indole-3-propionic acid (HPS, ß: 0.16, 95% CI: 0.07, 0.26, P = 7.32 × 10-4; HEI-15, ß: 0.16, 95% CI: 0.07, 0.25, P = 6.79 × 10-4), hippuric acid (HPS, ß: 0.11, 95% CI: 0.02, 0.21, P = 1.97 × 10-2; HEI-15, ß: 0.10, 95% CI: 0.01, 0.19, P = 3.14 × 10-2), and indoxyl sulfate (HPS, ß = -0.13, 95% CI: -0.23, -0.03, P = 8.21 × 10-3; HEI-15, ß: -0.12, 95% CI: -0.22, -0.03, P = 8.50 × 10-3). These gut microbial metabolites were associated with the intake of specific food groups, such as whole fruits. These metabolites were also associated with clinical variables, including blood pressure, diabetes or prediabetes, and body mass index. CONCLUSIONS: In a secondary analysis of the ChooseWell 365 study, associations between circulating gut microbiome-related metabolites and a healthy diet were confirmed using both objective and subjective measures of consumption. Accurate identification of diet-associated metabolites may help guide dietary or microbiome-based interventions aimed at disease prevention.

Sex-Associated Metabolites and Incident Stroke, Incident Coronary Heart Disease, Hypertension, and Chronic Kidney Disease in the REGARDS Cohort.

BACKGROUND: Sex disparities exist in cardiometabolic diseases. Metabolomic profiling offers insight into disease mechanisms, as the metabolome is influenced by environmental and genetic factors. We identified metabolites associated with sex and determined if sex-associated metabolites are associated with incident stoke, incident coronary heart disease, prevalent hypertension, and prevalent chronic kidney disease. METHODS AND RESULTS: Targeted metabolomics was conducted for 357 metabolites in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) case-cohort substudy for incident stroke. Weighted logistic regression models were used to identify metabolites associated with sex in REGARDS. Sex-associated metabolites were replicated in the HyperGEN (Hypertension Genetic Epidemiology Network) and using the literature. Weighted Cox proportional hazard models were used to evaluate associations between metabolites and incident stroke. Cox proportional hazard models were used to evaluate associations between metabolites and incident coronary heart disease. Weighted logistic regression models were used to evaluate associations between metabolites and hypertension and chronic kidney disease. Fifty-one replicated metabolites were associated with sex. Higher levels of 6 phosphatidylethanolamines were associated with incident stroke. No metabolites were associated with incident coronary heart disease. Higher levels of uric acid and leucine and lower levels of a lysophosphatidylcholine were associated with hypertension. Higher levels of indole-3-lactic acid, 7 phosphatidylethanolamines, and uric acid, and lower levels of betaine and bilirubin were associated with chronic kidney disease. CONCLUSIONS: These findings suggest that the sexual dimorphism of the metabolome may contribute to sex differences in stroke, hypertension, and chronic kidney disease.

Associations Between Ultra-Processed Food Consumption and Adverse Brain Health Outcomes.

BACKGROUND AND OBJECTIVES: Ultra-processed foods (UPFs) are linked to cardiometabolic diseases and neurologic outcomes, such as cognitive decline and stroke. However, it is unclear whether food processing confers neurologic risk independent of dietary pattern information. We aimed to (1) investigate associations between UPFs and incident cognitive impairment and stroke and (2) compare these associations with other commonly recommended dietary patterns in the REasons for Geographic and Racial Differences in Stroke study. This prospective, observational cohort study enrolled Black and White adults in the United States from 2003 to 2007. METHODS: The NOVA system was used to categorize items from a baseline food frequency questionnaire according to the level of processing. Participants with incomplete or implausible self-reported dietary data were excluded. Consumption for each category (grams) was normalized to total grams consumed. Scores quantifying adherence to a Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet were also calculated. Incident cognitive impairment was defined using performance relative to a normative sample on memory and fluency assessments. Incident stroke was identified through adjudicated review of medical records. RESULTS: The cognitive impairment cohort (n = 14,175) included participants without evidence of impairment at baseline who underwent follow-up testing. The stroke cohort (n = 20,243) included participants without a history of stroke. In multivariable Cox proportional hazards models, a 10% increase in relative intake of UPFs was associated with higher risk of cognitive impairment (hazard ratio [HR] = 1.16, 95% CI 1.09-1.24, p = 1.01 × 10-5) and intake of unprocessed or minimally processed foods with lower risk of cognitive impairment (HR = 0.88, 95% CI 0.83-0.94, p = 1.83 × 10-4). Greater intake of UPFs (HR = 1.08, 95% CI 1.02-1.14, p = 1.12 × 10-2) and unprocessed or minimally processed foods (HR = 0.91, 95% CI 0.86-0.95, p = 2.13 × 10-4) were also associated with risk of stroke in multivariable Cox models. The effect of UPFs on stroke risk was greater among Black than White participants (UPF-by-race interaction HR = 1.15, 95% CI 1.03-1.29, p = 1.50 × 10-2). Associations between UPFs and both cognitive impairment and stroke were independent of adherence to the Mediterranean, DASH, and MIND diets. DISCUSSION: Food processing may be important to brain health in older adults independent of known risk factors and adherence to recommended dietary patterns.

Omega-3 Fatty Acids and Risk of Ischemic Stroke in REGARDS.

We examined associations between lipidomic profiles and incident ischemic stroke in the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. Plasma lipids (n = 195) were measured from baseline blood samples, and lipids were consolidated into underlying factors using exploratory factor analysis. Cox proportional hazards models were used to test associations between lipid factors and incident stroke, linear regressions to determine associations between dietary intake and lipid factors, and the inverse odds ratio weighting (IORW) approach to test mediation. The study followed participants over a median (IQR) of 7 (3.4-11) years, and the case-cohort substudy included 1075 incident ischemic stroke and 968 non-stroke participants. One lipid factor, enriched for docosahexaenoic acid (DHA, an omega-3 fatty acid), was inversely associated with stroke risk in a base model (HR = 0.84; 95%CI 0.79-0.90; P = 8.33 × 10-8) and fully adjusted model (HR = 0.88; 95%CI 0.83-0.94; P = 2.79 × 10-4). This factor was associated with a healthy diet pattern (ß = 0.21; 95%CI 0.12-0.30; P = 2.06 × 10-6), specifically with fish intake (ß = 1.96; 95%CI 0.95-2.96; P = 1.36 × 10-4). DHA was a mediator between fish intake and incident ischemic stroke (30% P = 5.78 × 10-3). Taken together, DHA-containing plasma lipids were inversely associated with incident ischemic stroke and mediated the relationship between fish intake and stroke risk.

A metabolomics investigation of non-genotoxic carcinogenicity in the rat.

Non-genotoxic carcinogens (NGCs) promote tumor growth by altering gene expression, which ultimately leads to cancer without directly causing a change in DNA sequence. As a result NGCs are not detected in mutagenesis assays. While there are proposed biomarkers of carcinogenic potential, the definitive identification of non-genotoxic carcinogens still rests with the rat and mouse long-term bioassay. Such assays are expensive and time-consuming and require a large number of animals, and their relevance to human health risk assessments is debatable. Metabolomics and lipidomics in combination with pathology and clinical chemistry were used to profile perturbations produced by 10 compounds that represented a range of rat non-genotoxic hepatocarcinogens (NGC), non-genotoxic non-hepatocarcinogens (non-NGC), and a genotoxic hepatocarcinogen. Each compound was administered at its maximum tolerated dose level for 7, 28, and 91 days to male Fisher 344 rats. Changes in liver metabolite concentration differentiated the treated groups across different time points. The most significant differences were driven by pharmacological mode of action, specifically by the peroxisome proliferator activated receptor alpha (PPAR-α) agonists. Despite these dominant effects, good predictions could be made when differentiating NGCs from non-NGCs. Predictive ability measured by leave one out cross validation was 87% and 77% after 28 days of dosing for NGCs and non-NGCs, respectively. Among the discriminatory metabolites we identified free fatty acids, phospholipids, and triacylglycerols, as well as precursors of eicosanoid and the products of reactive oxygen species linked to processes of inflammation, proliferation, and oxidative stress. Thus, metabolic profiling is able to identify changes due to the pharmacological mode of action of xenobiotics and contribute to early screening for non-genotoxic potential.

Trimethylamine N-Oxide and White Matter Hyperintensity Volume Among Patients With Acute Ischemic Stroke.

Importance: Although increasing evidence suggests that trimethylamine N-oxide (TMAO) is associated with atherosclerosis, little is known about whether TMAO and its related metabolites (ie, choline, betaine, and carnitine) are associated with small vessel disease. Objective: To evaluate the association between TMAO and its related metabolites with features of cerebral small vessel disease, including white matter hyperintensity volume (WMHV) and acute lacunar infarction. Design, Setting, and Participants: This cross-sectional study included patients enrolled in the Specialized Programs of Translational Research in Acute Stroke biorepository. The registry included 522 patients with acute ischemic stroke who were 18 years or older who presented at the Massachusetts General Hospital or Brigham and Women's Hospital within 9 hours after onset between January 2007 and April 2010. The analyses in this study were conducted between November 2022 and April 2023. Exposures: Plasma TMAO, choline, betaine, and carnitine were measured by liquid chromatography-tandem mass spectrometry. Main Outcomes and Measures: WMHV was quantified by a semiautomated approach using signal intensity threshold with subsequent manual editing. Ischemic stroke subtype was classified using the Causative Classification System. Results: Among 351 patients included in this study, the mean (SD) age was 69 (15) years; 209 patients (59.5%) were male and had a median (IQR) admission National Institute of Health Stroke Scale of 6 (3-13). The magnetic resonance imaging subgroup consisted of 291 patients with a mean (SD) age of 67 (15) years. Among these, the median (IQR) WMHV was 3.2 (1.31-8.4) cm3. TMAO was associated with WMHV after adjustment for age and sex (ß, 0.15; 95% CI, 0.01-0.29; P < .001). TMAO remained significant in a multivariate analysis adjusted for age, sex, hypertension, diabetes, and smoking (ß, 0.14; 95% CI, 0-0.29; P = .05). TMAO was associated with lacunar stroke but not other ischemic stroke subtypes in a model adjusted for age, sex, hypertension, diabetes, and smoking (OR, 1.67; 95% CI, 1.05-2.66; P = .03). Conclusions and Relevance: In this observational study, TMAO was associated with cerebral small vessel disease determined by WMHV and acute lacunar infarction. The association was independent of traditional vascular risk factors.

Acetylglutamine Differentially Associated with First-Time Versus Recurrent Stroke.

Approximately one-quarter of strokes occur in individuals with prior stroke. Despite the advancement in secondary stroke prevention, the long-term risk of recurrent stroke has remained unchanged. The objective of this study was to identify metabolite risk markers that are associated with recurrent stroke. We performed targeted metabolomic profiling of 162 metabolites by liquid chromatography-tandem mass spectrometry in baseline plasma in a stroke case-cohort study nested within the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, an observational cohort study of 30,239 individuals aged 45 and older enrolled in 2003-2007. Weighted Cox proportional hazard models were used to identify metabolites that had a differential effect on first-time versus recurrent stroke using an interaction term between metabolite and prior stroke at baseline (yes or no). The study included 1391 incident stroke cases identified during 7.1 ± 4.5 years of follow-up and 1050 participants in the random cohort sample. Among 162 metabolites, 13 candidates had a metabolite-by-prior stroke interaction at a p-value <0.05, with one metabolite, acetylglutamine, surpassing the Bonferroni adjusted p-value threshold (p for interaction = 5.78 × 10-5). In an adjusted model that included traditional stroke risk factors, acetylglutamine was associated with recurrent stroke (HR = 2.27 per SD increment, 95% CI = 1.60-3.20, p = 3.52 × 10-6) but not with first-time stroke (HR = 0.96 per SD increment, 95% CI = 0.87-1.06, p = 0.44). Acetylglutamine was associated with recurrent stroke but not first-time stroke, independent of traditional stroke risk factors. Future studies are warranted to elucidate the pathogenesis of acetylglutamine and recurrent stroke risk.

Association of Circulating Metabolites With Racial Disparities in Hypertension and Stroke in the REGARDS Study.

BACKGROUND AND OBJECTIVES: In the United States, the risk of stroke is greater among Black compared with that among White individuals. However, the reasons for the difference in stroke incidence are not fully elucidated. We aimed to identify metabolites that account for higher prevalent hypertension and incident ischemic stroke among Black adults. METHODS: We used a stroke case cohort nested within the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Targeted metabolomic profiling of 162 plasma metabolites was performed by liquid chromatography-tandem mass spectrometry. We identified metabolites that were associated with prevalent hypertension and incident ischemic stroke and mediated the relationship between hypertension and ischemic stroke by weighted logistic regression, Cox proportional hazard model, and inverse odds ratio weighting mediation analysis. RESULTS: Incident ischemic stroke cases adjudicated through April 1, 2019 (n = 1,075) were included in the study. The random cohort sample was derived from the full cohort using stratified sampling (n = 968). Among 162 metabolites, gluconic acid was associated with prevalent hypertension in Black adults (odds ratio [OR] 1.86, 95% CI 1.39-2.47, p = 2.58 × 10-5) but not in White adults (OR 1.00, 95% CI 0.80-1.24, p = 0.97; p for interaction = 4.57 × 10-4). Gluconic acid also demonstrated an association with incident ischemic stroke among Black participants (hazard ratio [HR] 1.53, 95% CI 1.28-1.81, p = 1.76 × 10-6) but not White participants (HR 1.16, 95% CI 1.00-1.34, p = 0.057; p for interaction = 0.019). In mediation analysis, gluconic acid mediated 25.4% (95% CI 4.1%-46.8%, p = 0.02) of the association between prevalent hypertension and incident ischemic stroke among Black individuals. Specific socioeconomic factors were linked to elevated gluconic acid level among Black adults in multivariable analysis, including a Southern dietary pattern (ß = 0.18, 95% CI 0.08-0.28, p < 0.001), lower educational attainment (ß = 0.45, 95% CI 0.19-0.72, p = 0.001), and a lack of exercise (ß = 0.26, 95% CI 0.01-0.51, p = 0.045). DISCUSSION: Gluconic acid is associated with prevalent hypertension and incident ischemic stroke and mediates the relationship between hypertension and ischemic stroke in Black but not White adults. Gluconic acid is a biomarker that is associated with social determinants of health including a Southern diet, low educational attainment, and low physical activity.

Metabolite profiles and DNA methylation in metabolic syndrome: a two-sample, bidirectional Mendelian randomization.

Introduction: Metabolic syndrome (MetS) increases the risk of cardiovascular disease and death. Previous '-omics' studies have identified dysregulated serum metabolites and aberrant DNA methylation in the setting of MetS. However, the relationship between the metabolome and epigenome have not been elucidated. In this study, we identified serum metabolites associated with MetS and DNA methylation, and we conducted bidirectional Mendelian randomization (MR) to assess causal relationships between metabolites and methylation. Methods: We leveraged metabolomic and genomic data from a national United States cohort of older adults (REGARDS), as well as metabolomic, epigenomic, and genomic data from a family-based study of hypertension (HyperGEN). We conducted metabolite profiling for MetS in REGARDS using weighted logistic regression models and validated them in HyperGEN. Validated metabolites were selected for methylation studies which fit linear mixed models between metabolites and six CpG sites previously linked to MetS. Statistically significant metabolite-CpG pairs were selected for two-sample, bidirectional MR. Results: Forward MR indicated that glucose and serine metabolites were causal on CpG methylation near CPT1A [B(SE): -0.003 (0.002), p = 0.028 and B(SE): 0.029 (0.011), p = 0.030, respectively] and that serine metabolites were causal on ABCG1 [B(SE): -0.008(0.003), p = 0.006] and SREBF1 [B(SE): -0.009(0.004), p = 0.018] methylation, which suggested a protective effect of serine. Reverse MR showed a bidirectional relationship between cg06500161 (ABCG1) and serine [B(SE): -1.534 (0.668), p = 0.023]. Discussion: The metabolome may contribute to the relationship between MetS and epigenetic modifications.

Gut microbiota-associated metabolites and risk of ischemic stroke in REGARDS.

Several metabolite markers are independently associated with incident ischemic stroke. However, prior studies have not accounted for intercorrelated metabolite networks. We used exploratory factor analysis (EFA) to determine if metabolite factors were associated with incident ischemic stroke. Metabolites (n = 162) were measured in a case-control cohort nested in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, which included 1,075 ischemic stroke cases and 968 random cohort participants. Cox models were adjusted for age, gender, race, and age-race interaction (base model) and further adjusted for the Framingham stroke risk factors (fully adjusted model). EFA identified fifteen metabolite factors, each representing a well-defined metabolic pathway. Of these, factor 3, a gut microbiome metabolism factor, was associated with an increased risk of stroke in the base (hazard ratio per one-unit standard deviation, HR = 1.23; 95%CI = 1.15-1.31; P = 1.98 × 10-10) and fully adjusted models (HR = 1.13; 95%CI = 1.06-1.21; P = 4.49 × 10-4). The highest tertile had a 45% increased risk relative to the lowest (HR = 1.45; 95%CI = 1.25-1.70; P = 2.24 × 10-6). Factor 3 was also associated with the Southern diet pattern, a dietary pattern previously linked to increased stroke risk in REGARDS (ß = 0.11; 95%CI = 0.03-0.18; P = 8.75 × 10-3). These findings highlight the role of diet and gut microbial metabolism in relation to incident ischemic stroke.

Hypoxanthine is a pharmacodynamic marker of ischemic brain edema modified by glibenclamide.

Brain edema after a large stroke causes significant morbidity and mortality. Here, we seek to identify pharmacodynamic markers of edema that are modified by intravenous (i.v.) glibenclamide (glyburide; BIIB093) treatment. Using metabolomic profiling of 399 plasma samples from patients enrolled in the phase 2 Glyburide Advantage in Malignant Edema and Stroke (GAMES)-RP trial, 152 analytes are measured using liquid chromatography-tandem mass spectrometry. Associations with midline shift (MLS) and the matrix metalloproteinase-9 (MMP-9) level that are further modified by glibenclamide treatment are compared with placebo. Hypoxanthine is the only measured metabolite that associates with MLS and MMP-9. In sensitivity analyses, greater hypoxanthine levels also associate with increased net water uptake (NWU), as measured on serial head computed tomography (CT) scans. Finally, we find that treatment with i.v. glibenclamide reduces plasma hypoxanthine levels across all post-treatment time points. Hypoxanthine, which has been previously linked to inflammation, is a biomarker of brain edema and a treatment response marker of i.v. glibenclamide treatment.

Nucleosides Associated With Incident Ischemic Stroke in the REGARDS and JHS Cohorts.

BACKGROUND AND OBJECTIVES: Both genetic and environmental factors contribute to stroke risk. We sought to identify novel metabolites associated with incident stroke in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort and determine whether they reflected genetic or environmental variation. METHODS: This was a stroke case-cohort observational study nested in REGARDS. Cases were defined as incident stroke and metabolomic profiles were compared to a randomly selected control cohort. In baseline plasma samples, 162 metabolites were measured using liquid chromatography-tandem mass spectrometry. Cox proportional hazards models were adjusted for age, sex, race, and age by race in the base model. Fully adjusted models included traditional stroke risk factors. Mediation analyses conducted for these stroke risk factors used the metabolite as mediator. Genome-wide associations with the leading candidate metabolites were calculated using array data. Replication analyses in the Jackson Heart Study (JHS) were conducted using random effects meta-analysis. RESULTS: There were 2,043 participants who were followed over an average period of 7.1 years, including 1,075 stroke cases and 968 random controls. Nine metabolites were associated with stroke in the base model, 8 of which were measured and remained significant in meta-analysis with JHS. In the fully adjusted model in REGARDS, guanosine (hazard ratio [HR] 1.34, 95% CI 1.18-1.53; p = 7.26 × 10-6) and pseudouridine (HR 1.28, 95% CI 1.13-1.45; p = 1.03 × 10-4) were associated with incident ischemic stroke following Bonferroni adjustment. Guanosine also partially mediated the relationship between hypertension and stroke (17.6%) and pseudouridine did not mediate any risk factor. Genome-wide association analysis identified loci rs34631560 and rs34631560 associated with pseudouridine, but these did not explain the association of pseudouridine with stroke. DISCUSSION: Guanosine and pseudouridine are nucleosides associated with incident ischemic stroke independently of other risk factors. Genetic and mediation analyses suggest that environmental exposures rather than genetic variation link nucleoside levels to stroke risk. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that guanosine and pseudouridine are associated with incident stroke.

Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke.

Hyperglycemia is a feature of worse brain injury after acute ischemic stroke, but the underlying metabolic changes and the link to cytotoxic brain injury are not fully understood. In this observational study, we applied regression and machine learning classification analyses to identify metabolites associated with hyperglycemia and a neuroimaging proxy for cytotoxic brain injury. Metabolomics and lipidomics were carried out using liquid chromatography-tandem mass spectrometry in admission plasma samples from 381 patients presenting with an acute stroke. Glucose was measured by a central clinical laboratory, and a subgroup of patients (n = 201) had apparent diffusion coefficient (ADC) imaging quantified on magnetic resonance imaging (MRI) to estimate cytotoxic injury. Uric acid was the leading metabolite in univariate analysis of both hyperglycemia (OR 19.6, 95% CI 8.6-44.7, P = 1.44 × 10-12) and ADC (OR 5.3, 95% CI 2.2-13.0, P = 2.42 × 10-4). To further prioritize model features and account for non-linear correlation structure, a random forest machine learning algorithm was applied to separately model hyperglycemia and ADC. The statistical techniques used have identified uric acid and gluconic acids as leading candidate markers common to all models (R2 = 68%, P = 2.2 × 10-10 for uric acid; R2 = 15%, P = 8.09 × 10-10 for gluconic acid). Both uric acid and gluconic acid were associated with hyperglycemia and cytotoxic brain injury. Both metabolites are linked to oxidative stress, which highlights two candidate targets for limiting brain injury after stroke.

Machine Learning-Driven Metabolomic Evaluation of Cerebrospinal Fluid: Insights Into Poor Outcomes After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality and poor neurologic outcomes. The biologic underpinnings of the morbidity and mortality associated with aSAH remain poorly understood. OBJECTIVE: To ascertain potential insights into pathological mechanisms of injury after aSAH using an approach of metabolomics coupled with machine learning methods. METHODS: Using cerebrospinal fluid (CSF) samples from 81 aSAH enrolled in a retrospective cohort biorepository, samples collected during the peak of delayed cerebral ischemia were analyzed using liquid chromatography-tandem mass spectrometry. A total of 138 metabolites were measured and quantified in each sample. Data were analyzed using elastic net (EN) machine learning and orthogonal partial least squares-discriminant analysis (OPLS-DA) to identify the leading CSF metabolites associated with poor outcome, as determined by the modified Rankin Scale (mRS) at discharge and at 90 d. Repeated measures analysis determined the effect size for each metabolite on poor outcome. RESULTS: EN machine learning and OPLS-DA analysis identified 8 and 10 metabolites, respectively, that predicted poor mRS (mRS 3-6) at discharge and at 90 d. Of these candidates, symmetric dimethylarginine (SDMA), dimethylguanidine valeric acid (DMGV), and ornithine were consistent markers, with an association with poor mRS at discharge (P = .0005, .002, and .0001, respectively) and at 90 d (P = .0036, .0001, and .004, respectively). SDMA also demonstrated a significantly elevated CSF concentration compared with nonaneurysmal subarachnoid hemorrhage controls (P = .0087). CONCLUSION: SDMA, DMGV, and ornithine are vasoactive molecules linked to the nitric oxide pathway that predicts poor outcome after severe aSAH. Further study of dimethylarginine metabolites in brain injury after aSAH is warranted.