Publications

2024

Anwar, Mohammad Y, Heather Highland, Victoria Lynn Buchanan, Mariaelisa Graff, Kristin Young, Kent D Taylor, Russell P Tracy, et al. (2024) 2024. “Machine Learning-Based Clustering Identifies Obesity Subgroups With Differential Multi-Omics Profiles and Metabolic Patterns.”. Obesity (Silver Spring, Md.) 32 (11): 2024-34. https://doi.org/10.1002/oby.24137.

OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns.

METHODS: We performed machine learning-based, integrative unsupervised clustering to identify proteomics- and metabolomics-defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m2), leveraging data from 243 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits.

RESULTS: We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high-density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2.

CONCLUSIONS: Although the two identified clusters may represent progressive obesity-related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage.

2023

Shah, Ravi, V, Lyn M Steffen, Matthew Nayor, Jared P Reis, David R Jacobs, Norrina B Allen, Donald Lloyd-Jones, et al. (2023) 2023. “Dietary Metabolic Signatures and Cardiometabolic Risk.”. European Heart Journal 44 (7): 557-69. https://doi.org/10.1093/eurheartj/ehac446.

AIMS: Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood.

METHODS AND RESULTS: In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study.

CONCLUSION: Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.

Ardiansyah, Edwin, Julian Avila Pacheco, Le Thanh Hoang Nhat, Sofiati Dian, Dao Nguyen Vinh, Hoang Thanh Hai, Kevin Bullock, et al. (2023) 2023. “Tryptophan Metabolism Determines Outcome in Tuberculous Meningitis: A Targeted Metabolomic Analysis.”. MedRxiv : The Preprint Server for Health Sciences. https://doi.org/10.1101/2023.01.08.23284316.

BACKGROUND: Cellular metabolism is critical for the host immune function against pathogens, and metabolomic analysis may help understand the characteristic immunopathology of tuberculosis. We performed targeted metabolomic analyses in a large cohort of patients with tuberculous meningitis (TBM), the most severe manifestation of tuberculosis, focusing on tryptophan metabolism.

METHODS: We studied 1069 Indonesian and Vietnamese adults with TBM (26.6% HIV-positive), 54 non-infectious controls, 50 with bacterial meningitis, and 60 with cryptococcal meningitis. Tryptophan and downstream metabolites were measured in cerebrospinal fluid (CSF) and plasma using targeted liquid chromatography mass-spectrometry. Individual metabolite levels were associated with survival, clinical parameters, CSF bacterial load and 92 CSF inflammatory proteins.

RESULTS: CSF tryptophan was associated with 60-day mortality from tuberculous meningitis (HR=1.16, 95%CI=1.10-1.24, for each doubling in CSF tryptophan) both in HIV-negative and HIV-positive patients. CSF tryptophan concentrations did not correlate with CSF bacterial load nor CSF inflammation but were negatively correlated with CSF interferon-gamma concentrations. Unlike tryptophan, CSF concentrations of an intercorrelating cluster of downstream kynurenine metabolites did not predict mortality. These CSF kynurenine metabolites did however correlate with CSF inflammation and markers of blood-CSF leakage, and plasma kynurenine predicted death (HR 1.54, 95%CI=1.22-1.93). These findings were mostly specific for TBM, although high CSF tryptophan was also associated with mortality from cryptococcal meningitis.

CONCLUSION: TBM patients with a high baseline CSF tryptophan or high systemic (plasma) kynurenine are at increased risk of mortality. These findings may reveal new targets for host-directed therapy.

FUNDING: This study was supported by National Institutes of Health (R01AI145781) and the Wellcome Trust (110179/Z/15/Z and 206724/Z/17/Z).

Santos, José L, Miguel Ruiz-Canela, Cristina Razquin, Clary B Clish, Marta Guasch-Ferre, Nancy Babio, Dolores Corella, et al. (2023) 2023. “Circulating Citric Acid Cycle Metabolites and Risk of Cardiovascular Disease in the PREDIMED Study.”. Nutrition, Metabolism, and Cardiovascular Diseases : NMCD 33 (4): 835-43. https://doi.org/10.1016/j.numecd.2023.01.002.

BACKGROUND AND AIM: Plasma citric acid cycle (CAC) metabolites might be likely related to cardiovascular disease (CVD). However, studies assessing the longitudinal associations between circulating CAC-related metabolites and CVD risk are lacking. The aim of this study was to evaluate the association of baseline and 1-year levels of plasma CAC-related metabolites with CVD incidence (a composite of myocardial infarction, stroke or cardiovascular death), and their interaction with Mediterranean diet interventions.

METHODS AND RESULTS: Case-cohort study from the PREDIMED trial involving participants aged 55-80 years at high cardiovascular risk, allocated to MedDiets or control diet. A subcohort of 791 participants was selected at baseline, and a total of 231 cases were identified after a median follow-up of 4.8 years. Nine plasma CAC-related metabolites (pyruvate, lactate, citrate, aconitate, isocitrate, 2-hydroxyglutarate, fumarate, malate and succinate) were measured using liquid chromatography-tandem mass spectrometry. Weighted Cox multiple regression was used to calculate hazard ratios (HRs). Baseline fasting plasma levels of 3 metabolites were associated with higher CVD risk, with HRs (for each standard deviation, 1-SD) of 1.46 (95%CI:1.20-1.78) for 2-hydroxyglutarate, 1.33 (95%CI:1.12-1.58) for fumarate and 1.47 (95%CI:1.21-1.78) for malate (p of linear trend <0.001 for all). A higher risk of CVD was also found for a 1-SD increment of a combined score of these 3 metabolites (HR = 1.60; 95%CI: 1.32-1.94, p trend <0.001). This result was replicated using plasma measurements after one-year. No interactions were detected with the nutritional intervention.

CONCLUSION: Plasma 2-hydroxyglutarate, fumarate and malate levels were prospectively associated with increased cardiovascular risk.

CLINICAL TRIAL NUMBER: ISRCTN35739639.

Cronjé, Héléne T, Michael Y Mi, Thomas R Austin, Mary L Biggs, David S Siscovick, Rozenn N Lemaitre, Bruce M Psaty, et al. (2023) 2023. “Plasma Proteomic Risk Markers of Incident Type 2 Diabetes Reflect Physiologically Distinct Components of Glucose-Insulin Homeostasis.”. Diabetes 72 (5): 666-73. https://doi.org/10.2337/db22-0628.

UNLABELLED: High-throughput proteomics allows researchers to simultaneously explore the roles of thousands of biomarkers in the pathophysiology of diabetes. We conducted proteomic association studies of incident type 2 diabetes and physiologic responses to an intravenous glucose tolerance test (IVGTT) to identify novel protein contributors to glucose homeostasis and diabetes risk. We tested 4,776 SomaScan proteins measured in relation to 18-year incident diabetes risk in participants from the Cardiovascular Health Study (N = 2,631) and IVGTT-derived measures in participants from the HERITAGE Family Study (N = 752). We characterize 51 proteins that were associated with longitudinal diabetes risk, using their respective 39, 9, and 8 concurrent associations with insulin sensitivity index (SI), acute insulin response to glucose (AIRG), and glucose effectiveness (SG). Twelve of the 51 diabetes associations appear to be novel, including β-glucuronidase, which was associated with increased diabetes risk and lower SG, suggesting an alternative pathway to insulin for glucose disposal; and plexin-B2, which also was associated with increased diabetes risk, but with lower AIRG, and not with SI, indicating a mechanism related instead to pancreatic dysfunction. Other novel protein associations included alcohol dehydrogenase-1C, fructose-bisphosphate aldolase-B, sorbitol dehydrogenase with elevated type 2 diabetes risk, and a leucine-rich repeat containing protein-15 and myocilin with decreased risk.

ARTICLE HIGHLIGHTS: Plasma proteins are associated with the risk of incident diabetes in older adults independent of various demographic, lifestyle, and biochemical risk factors. These same proteins are associated with subtle differences in measures of glucose homeostasis earlier in life. Proteins that are associated with lower insulin sensitivity in individuals without diabetes tend to be associated with appropriate compensatory mechanisms, such as a stronger acute insulin response or higher glucose effectiveness. Proteins that are associated with future diabetes risk, but not with insulin insensitivity, tend to be associated with lower glucose effectiveness and/or impaired acute insulin response.

Zhao, Jiawei, Yuemeng Jia, Dilnar Mahmut, Amy A Deik, Sarah Jeanfavre, Clary B Clish, and Vijay G Sankaran. (2023) 2023. “Human Hematopoietic Stem Cell Vulnerability to Ferroptosis.”. Cell 186 (4): 732-747.e16. https://doi.org/10.1016/j.cell.2023.01.020.

Hematopoietic stem cells (HSCs) have a number of unique physiologic adaptations that enable lifelong maintenance of blood cell production, including a highly regulated rate of protein synthesis. Yet, the precise vulnerabilities that arise from such adaptations have not been fully characterized. Here, inspired by a bone marrow failure disorder due to the loss of the histone deubiquitinase MYSM1, characterized by selectively disadvantaged HSCs, we show how reduced protein synthesis in HSCs results in increased ferroptosis. HSC maintenance can be fully rescued by blocking ferroptosis, despite no alteration in protein synthesis rates. Importantly, this selective vulnerability to ferroptosis not only underlies HSC loss in MYSM1 deficiency but also characterizes a broader liability of human HSCs. Increasing protein synthesis rates via MYSM1 overexpression makes HSCs less susceptible to ferroptosis, more broadly illustrating the selective vulnerabilities that arise in somatic stem cell populations as a result of physiologic adaptations.

Abbott, Keene L, Ahmed Ali, Dominick Casalena, Brian T Do, Raphael Ferreira, Jaime H Cheah, Christian K Soule, et al. (2023) 2023. “Screening in Serum-Derived Medium Reveals Differential Response to Compounds Targeting Metabolism.”. BioRxiv : The Preprint Server for Biology. https://doi.org/10.1101/2023.02.25.529972.

A challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels to propagate cells. Which nutrients are available can influence how cancer cells use metabolism to proliferate and impact sensitivity to some drugs, but a general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To enable screening of compounds to determine how the nutrient environment impacts drug efficacy, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We used this system to screen several small molecule libraries and found that compounds targeting metabolic enzymes were enriched as having differential efficacy in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.

Zhou, Wen, Petra Simic, Iris Y Zhou, Peter Caravan, Xavier Vela Parada, Donghai Wen, Onica L Washington, et al. (2023) 2023. “Kidney Glycolysis Serves As a Mammalian Phosphate Sensor That Maintains Phosphate Homeostasis.”. The Journal of Clinical Investigation 133 (8). https://doi.org/10.1172/JCI164610.

How phosphate levels are detected in mammals is unknown. The bone-derived hormone fibroblast growth factor 23 (FGF23) lowers blood phosphate levels by reducing kidney phosphate reabsorption and 1,25(OH)2D production, but phosphate does not directly stimulate bone FGF23 expression. Using PET scanning and LC-MS, we found that phosphate increases kidney-specific glycolysis and synthesis of glycerol-3-phosphate (G-3-P), which then circulates to bone to trigger FGF23 production. Further, we found that G-3-P dehydrogenase 1 (Gpd1), a cytosolic enzyme that synthesizes G-3-P and oxidizes NADH to NAD+, is required for phosphate-stimulated G-3-P and FGF23 production and prevention of hyperphosphatemia. In proximal tubule cells, we found that phosphate availability is substrate-limiting for glycolysis and G-3-P production and that increased glycolysis and Gpd1 activity are coupled through cytosolic NAD+ recycling. Finally, we show that the type II sodium-dependent phosphate cotransporter Npt2a, which is primarily expressed in the proximal tubule, conferred kidney specificity to phosphate-stimulated G-3-P production. Importantly, exogenous G-3-P stimulated FGF23 production when Npt2a or Gpd1 were absent, confirming that it was the key circulating factor downstream of glycolytic phosphate sensing in the kidney. Together, these findings place glycolysis at the nexus of mineral and energy metabolism and identify a kidney-bone feedback loop that controls phosphate homeostasis.

Lee, Min-Sik, Courtney Dennis, Insia Naqvi, Lucas Dailey, Alireza Lorzadeh, George Ye, Tamara Zaytouni, et al. (2023) 2023. “Ornithine Aminotransferase Supports Polyamine Synthesis in Pancreatic Cancer.”. Nature 616 (7956): 339-47. https://doi.org/10.1038/s41586-023-05891-2.

There is a need to develop effective therapies for pancreatic ductal adenocarcinoma (PDA), a highly lethal malignancy with increasing incidence1 and poor prognosis2. Although targeting tumour metabolism has been the focus of intense investigation for more than a decade, tumour metabolic plasticity and high risk of toxicity have limited this anticancer strategy3,4. Here we use genetic and pharmacological approaches in human and mouse in vitro and in vivo models to show that PDA has a distinct dependence on de novo ornithine synthesis from glutamine. We find that this process, which is mediated through ornithine aminotransferase (OAT), supports polyamine synthesis and is required for tumour growth. This directional OAT activity is usually largely restricted to infancy and contrasts with the reliance of most adult normal tissues and other cancer types on arginine-derived ornithine for polyamine synthesis5,6. This dependency associates with arginine depletion in the PDA tumour microenvironment and is driven by mutant KRAS. Activated KRAS induces the expression of OAT and polyamine synthesis enzymes, leading to alterations in the transcriptome and open chromatin landscape in PDA tumour cells. The distinct dependence of PDA, but not normal tissue, on OAT-mediated de novo ornithine synthesis provides an attractive therapeutic window for treating patients with pancreatic cancer with minimal toxicity.

Toledo, Estefania, Clemens Wittenbecher, Cristina Razquin, Miguel Ruiz-Canela, Clary B Clish, Liming Liang, Alvaro Alonso, et al. (2023) 2023. “Plasma Lipidome and Risk of Atrial Fibrillation: Results from the PREDIMED Trial.”. Journal of Physiology and Biochemistry 79 (2): 355-64. https://doi.org/10.1007/s13105-023-00958-0.

The potential role of the lipidome in atrial fibrillation (AF) development is still widely unknown. We aimed to assess the association between lipidome profiles of the Prevención con Dieta Mediterránea (PREDIMED) trial participants and incidence of AF. We conducted a nested case-control study (512 incident centrally adjudicated AF cases and 735 controls matched by age, sex, and center). Baseline plasma lipids were profiled using a Nexera X2 U-HPLC system coupled to an Exactive Plus orbitrap mass spectrometer. We estimated the association between 216 individual lipids and AF using multivariable conditional logistic regression and adjusted the p values for multiple testing. We also examined the joint association of lipid clusters with AF incidence. Hitherto, we estimated the lipidomics network, used machine learning to select important network-clusters and AF-predictive lipid patterns, and summarized the joint association of these lipid patterns weighted scores. Finally, we addressed the possible interaction by the randomized dietary intervention.Forty-one individual lipids were associated with AF at the nominal level (p < 0.05), but no longer after adjustment for multiple-testing. However, the network-based score identified with a robust data-driven lipid network showed a multivariable-adjusted ORper+1SD of 1.32 (95% confidence interval: 1.16-1.51; p < 0.001). The score included PC plasmalogens and PE plasmalogens, palmitoyl-EA, cholesterol, CE 16:0, PC 36:4;O, and TG 53:3. No interaction with the dietary intervention was found. A multilipid score, primarily made up of plasmalogens, was associated with an increased risk of AF. Future studies are needed to get further insights into the lipidome role on AF.Current Controlled Trials number, ISRCTN35739639.