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Questa M, Weimer BC, Fiehn O, Chow B, Hill SL, Ackermann MR, Lidbury JA, Steiner JM, Suchodolski JS, Marsilio S. Unbiased serum metabolomic analysis in cats with naturally occurring chronic enteropathies before and after medical intervention. Sci Rep 2024; 14:6939. [PMID: 38521833 PMCID: PMC10960826 DOI: 10.1038/s41598-024-57004-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/13/2024] [Indexed: 03/25/2024] Open
Abstract
Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.
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Affiliation(s)
- Maria Questa
- Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA
| | - Bart C Weimer
- Department of Population Health and Reproduction, 100K Pathogen Genome Project, University of California School of Veterinary Medicine, University of California, Davis, Davis, CA, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA, USA
| | - Betty Chow
- VCA Animal Specialty & Emergency Center, Los Angeles, CA, USA
| | - Steve L Hill
- Veterinary Specialty Hospital, San Diego, CA, USA
| | - Mark R Ackermann
- US Department of Agriculture, National Animal Disease Center, Ames, IA, USA
| | - Jonathan A Lidbury
- Gastrointestinal Laboratory, Texas A&M University, College Station, TX, USA
| | - Joerg M Steiner
- Gastrointestinal Laboratory, Texas A&M University, College Station, TX, USA
| | - Jan S Suchodolski
- Gastrointestinal Laboratory, Texas A&M University, College Station, TX, USA
| | - Sina Marsilio
- Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.
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Ferrell M, Wang Z, Anderson JT, Li XS, Witkowski M, DiDonato JA, Hilser JR, Hartiala JA, Haghikia A, Cajka T, Fiehn O, Sangwan N, Demuth I, König M, Steinhagen-Thiessen E, Landmesser U, Tang WHW, Allayee H, Hazen SL. Publisher Correction: A terminal metabolite of niacin promotes vascular inflammation and contributes to cardiovascular disease risk. Nat Med 2024:10.1038/s41591-024-02899-7. [PMID: 38448791 DOI: 10.1038/s41591-024-02899-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Affiliation(s)
- Marc Ferrell
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Systems Biology and Bioinformatics Program, Department of Nutrition, Case Western Reserve University, Cleveland, OH, USA
| | - Zeneng Wang
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - James T Anderson
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Xinmin S Li
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Marco Witkowski
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Cardiology, Angiology and Intensive Care, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin, Berlin, Germany
| | - Joseph A DiDonato
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - James R Hilser
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jaana A Hartiala
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Arash Haghikia
- Department of Cardiology, Angiology and Intensive Care, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Friede Springer Cardiovascular Prevention Center at Charité, Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tomas Cajka
- West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA
- Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA
| | - Naseer Sangwan
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ilja Demuth
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
| | - Maximilian König
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Ulf Landmesser
- Department of Cardiology, Angiology and Intensive Care, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Friede Springer Cardiovascular Prevention Center at Charité, Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - W H Wilson Tang
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Hooman Allayee
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Stanley L Hazen
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA.
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3
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Bhargava A, Knapp JD, Fiehn O, Neylan TC, Inslicht SS. The lipidome of posttraumatic stress disorder. bioRxiv 2024:2024.02.23.581833. [PMID: 38464224 PMCID: PMC10925102 DOI: 10.1101/2024.02.23.581833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Posttraumatic stress disorder (PTSD) can develop after trauma exposure. Some studies report that women develop PTSD at twice the rate of men, despite greater trauma exposure in men. Lipids and their metabolites (lipidome) regulate a myriad of key biological processes and pathways such as membrane integrity, oxidative stress, and neuroinflammation in the brain by maintaining neuronal connectivity and homeostasis. In this study, we analyzed the lipidome of 40 individuals with PTSD and 40 trauma-exposed non-PTSD individuals. Plasma samples were analyzed for lipidomics using Quadrupole Time-of-Flight (QToF) mass spectrometry. Additionally, ~ 90 measures were collected, on sleep, mental and physical health indices. Sleep quality worsened as PTSD severity increased in both sexes. The lipidomics analysis identified a total of 348 quantifiable known lipid metabolites and 1951 lipid metabolites that are yet unknown; known metabolites were part of 13 classes of lipids. After adjusting for sleep quality, in women with PTSD, only one lipid subclass, phosphatidylethanolamine (PE) was altered, whereas, in men with PTSD, 9 out of 13 subclasses were altered compared to non-PTSD women and men, respectively. Severe PTSD was associated with 22% and 5% of altered lipid metabolites in men and women, respectively. Of the changed metabolites, only 0.5% measures (2 PEs and cholesterol) were common between women and men with PTSD. Several sphingomyelins, PEs, ceramides, and triglycerides were increased in men with severe PTSD. The triglycerides and ceramide metabolites that were most highly increased were correlated with cholesterol metabolites and systolic blood pressure in men but not always in women with PTSD. Alterations in triglycerides and ceramides are linked with cardiac health and metabolic function in humans. Thus, disturbed sleep and higher weight may have contributed to changes in the lipidome found in PTSD.
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Affiliation(s)
- Aditi Bhargava
- Center for Reproductive Sciences, Department of Obstetrics and Gynecology, University of California San Francisco, CA 94143, USA
- Aseesa Inc., CA 94010, USA
| | | | - Oliver Fiehn
- NIH West Coast Metabolomics Center, University of California Davis Genome Center, Davis, CA 95616, USA
| | - Thomas C. Neylan
- San Francisco VA Health Care System, 4150 Clement St. (116P), San Francisco, CA 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, CA 94143, USA
| | - Sabra S. Inslicht
- San Francisco VA Health Care System, 4150 Clement St. (116P), San Francisco, CA 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, CA 94143, USA
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Curley EO, Abu Aboud O, Chmiel KJ, Nayak AP, Fiehn O, Zeki AA, Sharma P. Heated tobacco product IQOS induces unique metabolic signatures in human bronchial epithelial cells. ERJ Open Res 2024; 10:00805-2023. [PMID: 38444658 PMCID: PMC10910264 DOI: 10.1183/23120541.00805-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 12/04/2023] [Indexed: 03/07/2024] Open
Abstract
Metabolic signatures are lacking for heated tobacco products, making it crucial to identify new biosignatures of lung damage. This will enable the establishment of product-specific guidelines and an understanding of associated toxicity. https://bit.ly/3TkhBox.
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Affiliation(s)
- Erin O. Curley
- Center for Translational Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Jane and Leonard Korman Respiratory Institute, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | | | | | - Ajay P. Nayak
- Center for Translational Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Jane and Leonard Korman Respiratory Institute, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA, USA
| | - Amir A. Zeki
- UC Davis Lung Center, Davis, CA, USA
- UC Davis Reversible Obstructive Airway Disease Center, Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of California, Davis, CA, USA
- Veterans Affairs Medical Center, Sacramento, CA, USA
- A.A. Zeki and P. Sharma contributed equally to this article as lead authors and supervised the work
| | - Pawan Sharma
- Center for Translational Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, Jane and Leonard Korman Respiratory Institute, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- A.A. Zeki and P. Sharma contributed equally to this article as lead authors and supervised the work
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5
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Wen X, Fretts AM, Miao G, Malloy KM, Zhang Y, Umans JG, Cole SA, Best LG, Fiehn O, Zhao J. Plasma lipidomic markers of diet quality are associated with incident coronary heart disease in American Indian adults: the Strong Heart Family Study. Am J Clin Nutr 2024; 119:748-755. [PMID: 38160800 DOI: 10.1016/j.ajcnut.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/15/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association. OBJECTIVES This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD. METHODS Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of <0.05. RESULTS Among 1542 lipid species measured, 71 lipid species (23 known), including acylcarnitine, cholesterol esters, glycerophospholipids, sphingomyelins and triacylglycerols, were associated with AHEI. Most of the identified lipids were associated with consumption of ω-3 (n-3) fatty acids. In total, 147 participants developed CHD during a mean follow-up of 17.8 years. Among the diet-related lipids, 10 lipids [5 known: cholesterol ester (CE)(22:5)B, phosphatidylcholine (PC)(p-14:0/22:1)/PC(o-14:0/22:1), PC(p-38:3)/PC(o-38:4)B, phosphatidylethanolamine (PE)(p-18:0/20:4)/PE(o-18:0/20:4), and sphingomyelin (d36:2)A] were associated with incident CHD. On average, each standard deviation increase in the baseline level of these 5 lipids was associated with 17%-23% increased risk of CHD (from HR: 1.17; 95% CI: 1, 1.36; to HR: 1.23; 95% CI: 1.05, 1.43). CONCLUSIONS In this study, lipidomic markers of diet quality in American Indian adults are found. Some diet-related lipids are associated with risk of CHD beyond established risk factors.
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Affiliation(s)
- Xiaoxiao Wen
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States
| | - Kimberly M Malloy
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Ying Zhang
- Center for American Indian Health Research, Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Jason G Umans
- Biomarker, Biochemistry, and Biorepository Core, MedStar Health Research Institute, Hyattsville, MD, United States; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, United States
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Lyle G Best
- Missouri Breaks Industries Research, Timber Lake, SD, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, CA, United States
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States; Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, United States.
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Cajka T, Hricko J, Rakusanova S, Brejchova K, Novakova M, Rudl Kulhava L, Hola V, Paucova M, Fiehn O, Kuda O. Hydrophilic Interaction Liquid Chromatography-Hydrogen/Deuterium Exchange-Mass Spectrometry (HILIC-HDX-MS) for Untargeted Metabolomics. Int J Mol Sci 2024; 25:2899. [PMID: 38474147 DOI: 10.3390/ijms25052899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 02/17/2024] [Accepted: 02/26/2024] [Indexed: 03/14/2024] Open
Abstract
Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time-m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, with 90% of signals classified as unknowns. To enhance the metabolite annotation rates, researchers employ tandem mass spectral libraries and challenging in silico fragmentation software. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) may offer an additional layer of structural information in untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate the potential of hydrophilic interaction liquid chromatography (HILIC)-HDX-MS in untargeted metabolomics. Specifically, we evaluate the effectiveness of two approaches using hypothetical targets: the post-column addition of deuterium oxide (D2O) and the on-column HILIC-HDX-MS method. To illustrate the practical application of HILIC-HDX-MS, we apply this methodology using the in silico fragmentation software MS-FINDER to an unknown compound detected in various biological samples, including plasma, serum, tissues, and feces during HILIC-MS profiling, subsequently identified as N1-acetylspermidine.
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Affiliation(s)
- Tomas Cajka
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Jiri Hricko
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Stanislava Rakusanova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Kristyna Brejchova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Michaela Novakova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Lucie Rudl Kulhava
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Veronika Hola
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Michaela Paucova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Ondrej Kuda
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
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Habra H, Meijer JL, Shen T, Fiehn O, Gaul DA, Fernández FM, Rempfert KR, Metz TO, Peterson KE, Evans CR, Karnovsky A. metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics. Metabolites 2024; 14:125. [PMID: 38393017 PMCID: PMC10891690 DOI: 10.3390/metabo14020125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 02/04/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
Liquid chromatography-high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a "primary" feature list is used as a template for matching compounds in "target" feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution's in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.
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Affiliation(s)
- Hani Habra
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA;
| | - Jennifer L. Meijer
- Department of Medicine, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA;
| | - Tong Shen
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA; (T.S.); (O.F.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA; (T.S.); (O.F.)
| | - David A. Gaul
- School of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive, Atlanta, GA 30332, USA; (D.A.G.); (F.M.F.)
| | - Facundo M. Fernández
- School of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive, Atlanta, GA 30332, USA; (D.A.G.); (F.M.F.)
| | - Kaitlin R. Rempfert
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA; (K.R.R.); (T.O.M.)
| | - Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA; (K.R.R.); (T.O.M.)
| | - Karen E. Peterson
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA;
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Charles R. Evans
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA;
| | - Alla Karnovsky
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA;
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8
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Chen L, Dai J, Yu G, Pang WW, Rahman ML, Liu X, Fiehn O, Guivarch C, Chen Z, Zhang C. Metabolomic Biomarkers of Dietary Approaches to Stop Hypertension (DASH) Dietary Patterns in Pregnant Women. Nutrients 2024; 16:492. [PMID: 38398816 PMCID: PMC10892314 DOI: 10.3390/nu16040492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/29/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Objective: the aim of this study was to identify plasma metabolomic markers of Dietary Approaches to Stop Hypertension (DASH) dietary patterns in pregnant women. Methods: This study included 186 women who had both dietary intake and metabolome measured from a nested case-control study within the NICHD Fetal Growth Studies-Singletons cohort (FGS). Dietary intakes were ascertained at 8-13 gestational weeks (GW) using the Food Frequency Questionnaire (FFQ) and DASH scores were calculated based on eight food and nutrient components. Fasting plasma samples were collected at 15-26 GW and untargeted metabolomic profiling was performed. Multivariable linear regression models were used to examine the association of individual metabolites with the DASH score. Least absolute shrinkage and selection operator (LASSO) regression was used to select a panel of metabolites jointly associated with the DASH score. Results: Of the total 460 known metabolites, 92 were individually associated with DASH score in linear regressions, 25 were selected as a panel by LASSO regressions, and 18 were identified by both methods. Among the top 18 metabolites, there were 11 lipids and lipid-like molecules (i.e., TG (49:1), TG (52:2), PC (31:0), PC (35:3), PC (36:4) C, PC (36:5) B, PC (38:4) B, PC (42:6), SM (d32:0), gamma-tocopherol, and dodecanoic acid), 5 organic acids and derivatives (i.e., asparagine, beta-alanine, glycine, taurine, and hydroxycarbamate), 1 organic oxygen compound (i.e., xylitol), and 1 organoheterocyclic compound (i.e., maleimide). Conclusions: our study identified plasma metabolomic markers for DASH dietary patterns in pregnant women, with most of being lipids and lipid-like molecules.
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Affiliation(s)
- Liwei Chen
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (L.C.); (J.D.); (X.L.)
| | - Jin Dai
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (L.C.); (J.D.); (X.L.)
| | - Guoqi Yu
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Wei Wei Pang
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Mohammad L. Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA;
| | - Xinyue Liu
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (L.C.); (J.D.); (X.L.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA;
| | - Claire Guivarch
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Zhen Chen
- Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Bethesda, MD 20892, USA;
| | - Cuilin Zhang
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
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9
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Miao G, Pechlaner R, Fiehn O, Malloy KM, Zhang Y, Umans JG, Mayr M, Willeit J, Kiechl S, Zhao J. Longitudinal Lipidomic Signature of Coronary Heart Disease in American Indian People. J Am Heart Assoc 2024; 13:e031825. [PMID: 38293910 DOI: 10.1161/jaha.123.031825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/14/2023] [Indexed: 02/01/2024]
Abstract
BACKGROUND Dyslipidemia is an independent risk factor for coronary heart disease (CHD). Standard lipid panel cannot capture the complexity of the blood lipidome (ie, all molecular lipids in the blood). To date, very few large-scale epidemiological studies have assessed the full spectrum of the blood lipidome on risk of CHD, especially in a longitudinal setting. METHODS AND RESULTS Using an untargeted liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species from 1835 unique American Indian participants who attended 2 clinical visits (≈5.5 years apart) and followed up to 17.8 years in the Strong Heart Family Study (SHFS). We first identified baseline lipid species associated with risk of CHD, followed by replication in a European population. The model adjusted for age, sex, body mass index, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, estimated glomerular filtration rate, education, and physical activity at baseline. We then examined the longitudinal association between changes in lipid species and changes in cardiovascular risk factors during follow-up. Multiple testing was controlled by the false discovery rate. We found that baseline levels of multiple lipid species (eg, phosphatidylcholines, phosphatidylethanolamines, and ceramides) were associated with the risk of CHD and improved the prediction accuracy over conventional risk factors in American Indian people. Some identified lipids in American Indian people were replicated in European people. Longitudinal changes in multiple lipid species (eg, acylcarnitines, phosphatidylcholines, and triacylglycerols) were associated with changes in cardiovascular risk factors. CONCLUSIONS Baseline plasma lipids and their longitudinal changes over time are associated with risk of CHD. These findings provide novel insights into the role of dyslipidemia in CHD.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine University of Florida Gainesville FL
- Center for Genetic Epidemiology and Bioinformatics University of Florida Gainesville FL
| | - Raimund Pechlaner
- Department of Neurology Medical University Innsbruck Innsbruck Austria
| | - Oliver Fiehn
- West Coast Metabolomics Center University of California Davis CA
| | - Kimberly M Malloy
- Department of Biostatistics and Epidemiology University of Oklahoma Health Sciences Center Oklahoma City OK
| | - Ying Zhang
- Department of Biostatistics and Epidemiology University of Oklahoma Health Sciences Center Oklahoma City OK
| | | | - Manuel Mayr
- National Heart & Lung Institute Imperial College London UK
| | - Johann Willeit
- Department of Neurology Medical University Innsbruck Innsbruck Austria
| | - Stefan Kiechl
- Department of Neurology Medical University Innsbruck Innsbruck Austria
- Research Centre on Vascular Ageing and Stroke Innsbruck Austria
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine University of Florida Gainesville FL
- Center for Genetic Epidemiology and Bioinformatics University of Florida Gainesville FL
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10
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Ferrell M, Wang Z, Anderson JT, Li XS, Witkowski M, DiDonato JA, Hilser JR, Hartiala JA, Haghikia A, Cajka T, Fiehn O, Sangwan N, Demuth I, König M, Steinhagen-Thiessen E, Landmesser U, Tang WHW, Allayee H, Hazen SL. A terminal metabolite of niacin promotes vascular inflammation and contributes to cardiovascular disease risk. Nat Med 2024; 30:424-434. [PMID: 38374343 DOI: 10.1038/s41591-023-02793-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 12/22/2023] [Indexed: 02/21/2024]
Abstract
Despite intensive preventive cardiovascular disease (CVD) efforts, substantial residual CVD risk remains even for individuals receiving all guideline-recommended interventions. Niacin is an essential micronutrient fortified in food staples, but its role in CVD is not well understood. In this study, untargeted metabolomics analysis of fasting plasma from stable cardiac patients in a prospective discovery cohort (n = 1,162 total, n = 422 females) suggested that niacin metabolism was associated with incident major adverse cardiovascular events (MACE). Serum levels of the terminal metabolites of excess niacin, N1-methyl-2-pyridone-5-carboxamide (2PY) and N1-methyl-4-pyridone-3-carboxamide (4PY), were associated with increased 3-year MACE risk in two validation cohorts (US n = 2,331 total, n = 774 females; European n = 832 total, n = 249 females) (adjusted hazard ratio (HR) (95% confidence interval) for 2PY: 1.64 (1.10-2.42) and 2.02 (1.29-3.18), respectively; for 4PY: 1.89 (1.26-2.84) and 1.99 (1.26-3.14), respectively). Phenome-wide association analysis of the genetic variant rs10496731, which was significantly associated with both 2PY and 4PY levels, revealed an association of this variant with levels of soluble vascular adhesion molecule 1 (sVCAM-1). Further meta-analysis confirmed association of rs10496731 with sVCAM-1 (n = 106,000 total, n = 53,075 females, P = 3.6 × 10-18). Moreover, sVCAM-1 levels were significantly correlated with both 2PY and 4PY in a validation cohort (n = 974 total, n = 333 females) (2PY: rho = 0.13, P = 7.7 × 10-5; 4PY: rho = 0.18, P = 1.1 × 10-8). Lastly, treatment with physiological levels of 4PY, but not its structural isomer 2PY, induced expression of VCAM-1 and leukocyte adherence to vascular endothelium in mice. Collectively, these results indicate that the terminal breakdown products of excess niacin, 2PY and 4PY, are both associated with residual CVD risk. They also suggest an inflammation-dependent mechanism underlying the clinical association between 4PY and MACE.
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Affiliation(s)
- Marc Ferrell
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Systems Biology and Bioinformatics Program, Department of Nutrition, Case Western Reserve University, Cleveland, OH, USA
| | - Zeneng Wang
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - James T Anderson
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Xinmin S Li
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Marco Witkowski
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Cardiology, Angiology and Intensive Care, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin, Berlin, Germany
| | - Joseph A DiDonato
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - James R Hilser
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jaana A Hartiala
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Arash Haghikia
- Department of Cardiology, Angiology and Intensive Care, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Friede Springer Cardiovascular Prevention Center at Charité, Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tomas Cajka
- West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA
- Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA
| | - Naseer Sangwan
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ilja Demuth
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
| | - Maximilian König
- Department of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Ulf Landmesser
- Department of Cardiology, Angiology and Intensive Care, Deutsches Herzzentrum der Charité, Campus Benjamin Franklin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Friede Springer Cardiovascular Prevention Center at Charité, Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - W H Wilson Tang
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Hooman Allayee
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Stanley L Hazen
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
- Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA.
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11
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Barupal DK, Ramos ML, Florio AA, Wheeler WA, Weinstein SJ, Albanes D, Fiehn O, Graubard BI, Petrick JL, McGlynn KA. Identification of pre-diagnostic lipid sets associated with liver cancer risk using untargeted lipidomics and chemical set analysis: A nested case-control study within the ATBC cohort. Int J Cancer 2024; 154:454-464. [PMID: 37694774 PMCID: PMC10845132 DOI: 10.1002/ijc.34726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/17/2023] [Accepted: 08/23/2023] [Indexed: 09/12/2023]
Abstract
In pre-disposed individuals, a reprogramming of the hepatic lipid metabolism may support liver cancer initiation. We conducted a high-resolution mass spectrometry based untargeted lipidomics analysis of pre-diagnostic serum samples from a nested case-control study (219 liver cancer cases and 219 controls) within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Out of 462 annotated lipids, 158 (34.2%) were associated with liver cancer risk in a conditional logistic regression analysis at a false discovery rate (FDR) <0.05. A chemical set enrichment analysis (ChemRICH) and co-regulatory set analysis suggested that 22/28 lipid classes and 47/83 correlation modules were significantly associated with liver cancer risk (FDR <0.05). Strong positive associations were observed for monounsaturated fatty acids (MUFA), triacylglycerols (TAGs) and phosphatidylcholines (PCs) having MUFA acyl chains. Negative associations were observed for sphingolipids (ceramides and sphingomyelins), lysophosphatidylcholines, cholesterol esters and polyunsaturated fatty acids (PUFA) containing TAGs and PCs. Stearoyl-CoA desaturase enzyme 1 (SCD1), a rate limiting enzyme in fatty acid metabolism and ceramidases seems to be critical in this reprogramming. In conclusion, our study reports pre-diagnostic lipid changes that provide novel insights into hepatic lipid metabolism reprogramming may contribute to a pro-cell growth and anti-apoptotic tissue environment and, in turn, support liver cancer initiation.
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Affiliation(s)
- Dinesh K Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mark L Ramos
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Andrea A Florio
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | | | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, California, USA
| | - Barry I Graubard
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Jessica L Petrick
- Slone Epidemiology Center at Boston University, Boston, Massachusetts, USA
| | - Katherine A McGlynn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
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12
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Mahajan P, Fiehn O, Barupal D. IDSL.GOA: gene ontology analysis for interpreting metabolomic datasets. Sci Rep 2024; 14:1299. [PMID: 38221536 PMCID: PMC10788336 DOI: 10.1038/s41598-024-51992-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 01/11/2024] [Indexed: 01/16/2024] Open
Abstract
Biological interpretation of metabolomic datasets often ends at a pathway analysis step to find the over-represented metabolic pathways in the list of statistically significant metabolites. However, definitions of biochemical pathways and metabolite coverage vary among different curated databases, leading to missed interpretations. For the lists of genes, transcripts and proteins, Gene Ontology (GO) terms over-presentation analysis has become a standardized approach for biological interpretation. But, GO analysis has not been achieved for metabolomic datasets. We present a new knowledgebase (KB) and the online tool, Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.GOA) to conduct GO over-representation analysis for a metabolite list. The IDSL.GOA KB covers 2393 metabolic GO terms and associated 3144 genes, 1,492 EC annotations, and 2621 metabolites. IDSL.GOA analysis of a case study of older versus young female brain cortex metabolome highlighted 82 GO terms being significantly overrepresented (FDR < 0.05). We showed how IDSL.GOA identified key and relevant GO metabolic processes that were not yet covered in other pathway databases. Overall, we suggest that interpretation of metabolite lists should not be limited to only pathway maps and can also leverage GO terms as well. IDSL.GOA provides a useful tool for this purpose, allowing for a more comprehensive and accurate analysis of metabolite pathway data. IDSL.GOA tool can be accessed at https://goa.idsl.me/ .
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Affiliation(s)
- Priyanka Mahajan
- Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, 10954, USA
| | - Oliver Fiehn
- NIH-West Coast Metabolomics Center, University of California, Davis, CA, 95616, USA
| | - Dinesh Barupal
- Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, 10954, USA.
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13
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Mahajan P, Fiehn O, Barupal D. IDSL.GOA: Gene Ontology Analysis for Interpreting Metabolomic datasets. bioRxiv 2024:2023.03.25.534225. [PMID: 37034715 PMCID: PMC10081191 DOI: 10.1101/2023.03.25.534225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/17/2023]
Abstract
Biological interpretation of metabolomic datasets often ends at a pathway analysis step to find the over-represented metabolic pathways in the list of statistically significant metabolites. However, definitions of biochemical pathways and metabolite coverage vary among different curated databases, leading to missed interpretations. For the lists of genes, transcripts and proteins, Gene Ontology (GO) terms over-presentation analysis has become a standardized approach for biological interpretation. But, GO analysis has not been achieved for metabolomic datasets. We present a new knowledgebase (KB) and the online tool, Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.GOA) to conduct GO over-representation analysis for a metabolite list. The IDSL.GOA KB covers 2,393 metabolic GO terms and associated 3,144 genes, 1,492 EC annotations, and 2,621 metabolites. IDSL.GOA analysis of a case study of older vs young female brain cortex metabolome highlighted 82 GO terms being significantly overrepresented (FDR <0.05). We showed how IDSL.GOA identified key and relevant GO metabolic processes that were not yet covered in other pathway databases. Overall, we suggest that interpretation of metabolite lists should not be limited to only pathway maps and can also leverage GO terms as well. IDSL.GOA provides a useful tool for this purpose, allowing for a more comprehensive and accurate analysis of metabolite pathway data. IDSL.GOA tool can be accessed at https://goa.idsl.me/.
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Affiliation(s)
- Priyanka Mahajan
- Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA 10954
| | - Oliver Fiehn
- NIH-West Coast Metabolomics Center, University of California, Davis, California, 95616, USA
| | - Dinesh Barupal
- Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA 10954
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14
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Wanichthanarak K, In-on A, Fan S, Fiehn O, Wangwiwatsin A, Khoomrung S. Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0. Gigascience 2024; 13:giae005. [PMID: 38488666 PMCID: PMC10941642 DOI: 10.1093/gigascience/giae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/22/2023] [Accepted: 02/02/2024] [Indexed: 03/18/2024] Open
Abstract
In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.
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Affiliation(s)
- Kwanjeera Wanichthanarak
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Ammarin In-on
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sili Fan
- Department of Biostatistics, University of California Davis, Davis, CA 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis Genome Center, Davis, CA 95616, USA
| | - Arporn Wangwiwatsin
- Department of Systems Biosciences and Computational Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Sakda Khoomrung
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10700, Thailand
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15
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Deans JR, Deol P, Titova N, Radi SH, Vuong LM, Evans JR, Pan S, Fahrmann J, Yang J, Hammock BD, Fiehn O, Fekry B, Eckel-Mahan K, Sladek FM. HNF4α isoforms regulate the circadian balance between carbohydrate and lipid metabolism in the liver. Front Endocrinol (Lausanne) 2023; 14:1266527. [PMID: 38111711 PMCID: PMC10726135 DOI: 10.3389/fendo.2023.1266527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 11/06/2023] [Indexed: 12/20/2023] Open
Abstract
Hepatocyte Nuclear Factor 4α (HNF4α), a master regulator of hepatocyte differentiation, is regulated by two promoters (P1 and P2) which drive the expression of different isoforms. P1-HNF4α is the major isoform in the adult liver while P2-HNF4α is thought to be expressed only in fetal liver and liver cancer. Here, we show that P2-HNF4α is indeed expressed in the normal adult liver at Zeitgeber time (ZT)9 and ZT21. Using exon swap mice that express only P2-HNF4α we show that this isoform orchestrates a distinct transcriptome and metabolome via unique chromatin and protein-protein interactions, including with different clock proteins at different times of the day leading to subtle differences in circadian gene regulation. Furthermore, deletion of the Clock gene alters the circadian oscillation of P2- (but not P1-)HNF4α RNA, revealing a complex feedback loop between the HNF4α isoforms and the hepatic clock. Finally, we demonstrate that while P1-HNF4α drives gluconeogenesis, P2-HNF4α drives ketogenesis and is required for elevated levels of ketone bodies in female mice. Taken together, we propose that the highly conserved two-promoter structure of the Hnf4a gene is an evolutionarily conserved mechanism to maintain the balance between gluconeogenesis and ketogenesis in the liver in a circadian fashion.
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Affiliation(s)
- Jonathan R. Deans
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
- Genetics, Genomics and Bioinformatics Graduate Program, University of California, Riverside, Riverside, CA, United States
| | - Poonamjot Deol
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
| | - Nina Titova
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
| | - Sarah H. Radi
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
- Biochemistry and Molecular Biology Graduate Program, University of California, Riverside, Riverside, CA, United States
| | - Linh M. Vuong
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
| | - Jane R. Evans
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
| | - Songqin Pan
- Proteomics Core, Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA, United States
| | - Johannes Fahrmann
- National Institutes of Health West Coast Metabolomics Center, University of California, Davis, Davis, CA, United States
| | - Jun Yang
- Department of Entomology and Nematology & UCD Comprehensive Cancer Center, University of California, Davis, Davis, CA, United States
| | - Bruce D. Hammock
- Department of Entomology and Nematology & UCD Comprehensive Cancer Center, University of California, Davis, Davis, CA, United States
| | - Oliver Fiehn
- National Institutes of Health West Coast Metabolomics Center, University of California, Davis, Davis, CA, United States
| | - Baharan Fekry
- Department of Biochemistry and Molecular Biology, McGovern Medical School at the University of Texas Health Science Center (UT Health), Houston, TX, United States
| | - Kristin Eckel-Mahan
- Department of Biochemistry and Molecular Biology, McGovern Medical School at the University of Texas Health Science Center (UT Health), Houston, TX, United States
- Institute of Molecular Medicine, McGovern Medical School at the University of Texas Health Science Center (UT Health), Houston, TX, United States
| | - Frances M. Sladek
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
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16
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Song Y, Lu R, Yu G, Rahman ML, Chen L, Zhu Y, Tsai MY, Fiehn O, Chen Z, Zhang C. Longitudinal lipidomic profiles during pregnancy and associations with neonatal anthropometry: findings from a multiracial cohort. EBioMedicine 2023; 98:104881. [PMID: 38006745 PMCID: PMC10709105 DOI: 10.1016/j.ebiom.2023.104881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 11/06/2023] [Accepted: 11/06/2023] [Indexed: 11/27/2023] Open
Abstract
BACKGROUND Maternal lipidomic profiling offers promise for characterizing lipid metabolites during pregnancy, but longitudinal data are limited. This study aimed to examine associations of longitudinal lipidomic profiles during pregnancy with multiple neonatal anthropometry using data from a multiracial cohort. METHODS We measured untargeted plasma lipidome profiles among 321 pregnant women from the NICHD Fetal Growth Study-Singletons using plasma samples collected longitudinally during four study visits at gestational weeks (GW) 10-14, 15-26, 23-31, and 33-39, respectively. We evaluated individual lipidomic metabolites at each study visit in association with neonatal anthropometry. We also evaluated the associations longitudinally by constructing lipid networks using weighted correlation network analysis and common networks using consensus network analysis across four visits using linear mixed-effects models with the adjustment of false discover rate. FINDINGS Multiple triglycerides (TG) were positively associated with birth weight (BW), BW Z-score, length and head circumference, while some cholesteryl ester (CE), phosphatidylcholine (PC), sphingomyelines (SM), phosphatidylethanolamines (PE), and lysophosphatidylcholines (LPC 20:3) families were inversely associated with BW, length, abdominal and head circumference at different GWs. Longitudinal trajectories of TG, PC, and glucosylcermides (GlcCer) were associated with BW, and CE (18:2) with BW z-score, length, and sum of skinfolds (SS), while some PC and PE were significantly associated with abdominal and head circumference. Modules of TG at GW 10-14 and 15-26 mainly were associated with BW. At GW 33-39, two networks of LPC (20:3) and of PC, TG, and CE, showed inverse associations with abdominal circumference. Distinct trajectories within two consensus modules with changes in TG, CE, PC, and LPC showed significant differences in BW and length. INTERPRETATION The results demonstrated that longitudinal changes of TGs during early- and mid-pregnancy and changes of PC, LPC, and CE during late-pregnancy were significantly associated with neonatal anthropometry. FUNDING National Institute of Child Health and Human Development intramural funding.
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Affiliation(s)
- Yiqing Song
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, USA
| | - Ruijin Lu
- Division of Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Guoqi Yu
- Global Center for Asian Women's Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Mohammad L Rahman
- National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Liwei Chen
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Yeiyi Zhu
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, 451 Health Sciences Drive, Davis, CA, USA
| | - Zhen Chen
- Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Bethesda, MD, USA
| | - Cuilin Zhang
- Global Center for Asian Women's Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
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17
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Kong F, Keshet U, Shen T, Rodriguez E, Fiehn O. LibGen: Generating High Quality Spectral Libraries of Natural Products for EAD-, UVPD-, and HCD-High Resolution Mass Spectrometers. Anal Chem 2023; 95:16810-16818. [PMID: 37939222 DOI: 10.1021/acs.analchem.3c02263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Compound annotation using spectral-matching algorithms is vital for (MS/MS)-based metabolomics research, but is hindered by the lack of high-quality reference MS/MS library spectra. Finding and removing errors from libraries, including noise ions, is mostly done manually. This process is both error-prone and time-consuming. To address these challenges, we have developed an automated library curation pipeline, LibGen, to universally build novel spectral libraries. This pipeline corrects mass errors, denoises spectra by subformula assignments, and performs quality control of the reference spectra by calculating explained intensity and spectral entropy. We employed LibGen to generate three high-quality libraries with chemical standards of 2241 natural products. To this end, we used an IQ-X orbital ion trap mass spectrometer to generate 1947 classic high-energy collision dissociation spectra (HCD) as well as 1093 ultraviolet-photodissociation (UVPD) mass spectra. The third library was generated by an electron-activated collision dissociation (EAD) 7600 ZenoTOF mass spectrometer yielding 3244 MS/MS spectra. The natural compounds covered 140 chemical classes from prenol lipids to benzypyrans with >97% of the compounds showing <0.2 Tanimoto-similarity, demonstrating a very high structural variance. Mass spectra showed much higher information content for both UVPD- and EAD-mass spectra compared to classic HCD spectra when using spectral entropy calculations. We validated the denoising algorithm by acquiring MS/MS spectra at high concentration and at 13-fold diluted chemical standards. At low concentrations, a higher proportion of spectra showed apparent fragment ions that could not be explained by subformula losses of the parent molecule. When more than 10% of the total intensity of MS/MS fragments was regarded as noise ions, spectra were considered as low quality and were not included in the libraries. As the overall process is fully automated, LibGen can be utilized by all researchers who create or curate mass spectral libraries. The libraries we created here are publicly available at MassBank.us.
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Affiliation(s)
- Fanzhou Kong
- Chemistry Department, One Shields Avenue, University of California-Davis, Davis, California 95616, United States
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Uri Keshet
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Tong Shen
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Elys Rodriguez
- Chemistry Department, One Shields Avenue, University of California-Davis, Davis, California 95616, United States
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
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18
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Vaniya A, Karlstaedt A, Gulkok DA, Thottakara T, Liu Y, Fan S, Eades H, Fukunaga R, Vernon HJ, Fiehn O, Roselle Abraham M. Lipid metabolism drives allele-specific early-stage hypertrophic cardiomyopathy. bioRxiv 2023:2023.11.10.564562. [PMID: 38014251 PMCID: PMC10680657 DOI: 10.1101/2023.11.10.564562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Hypertrophic cardiomyopathy (HCM) results from pathogenic variants in sarcomeric protein genes, that increase myocyte energy demand and lead to cardiac hypertrophy. But it is unknown whether a common metabolic trait underlies the cardiac phenotype at early disease stage. This study characterized two HCM mouse models (R92W-TnT, R403Q-MyHC) that demonstrate differences in mitochondrial function at early disease stage. Using a combination of cardiac phenotyping, transcriptomics, mass spectrometry-based metabolomics and computational modeling, we discovered allele-specific differences in cardiac structure/function and metabolic changes. TnT-mutant hearts had impaired energy substrate metabolism and increased phospholipid remodeling compared to MyHC-mutants. TnT-mutants showed increased incorporation of saturated fatty acid residues into ceramides, cardiolipin, and increased lipid peroxidation, that could underlie allele-specific differences in mitochondrial function and cardiomyopathy.
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19
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Nemet I, Funabashi M, Li XS, Dwidar M, Sangwan N, Skye SM, Romano KA, Cajka T, Needham BD, Mazmanian SK, Hajjar AM, Rey FE, Fiehn O, Tang WHW, Fischbach MA, Hazen SL. Microbe-derived uremic solutes enhance thrombosis potential in the host. mBio 2023; 14:e0133123. [PMID: 37947418 PMCID: PMC10746243 DOI: 10.1128/mbio.01331-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 09/25/2023] [Indexed: 11/12/2023] Open
Abstract
p-Cresol sulfate (pCS) and indoxyl sulfate (IS), gut microbiome-derived metabolites, are traditionally associated with cardiovascular disease (CVD) risks in the setting of impaired kidney function. While pharmacologic provision of pCS or IS can promote pro-thrombotic phenotypes, neither the microbial enzymes involved nor direct gut microbial production have been linked to CVD. Untargeted metabolomics was performed on a discovery cohort (n = 1,149) with relatively preserved kidney function, followed by stable isotope-dilution mass spectrometry quantification of pCS and IS in an independent validation cohort (n = 3,954). Genetic engineering of human commensals to produce p-cresol and indole gain-of-function and loss-of-function mutants, followed by colonization of germ-free mice, and studies on host thrombosis were performed. Systemic pCS and IS levels were independently associated with all-cause mortality. Both in vitro and within colonized germ-free mice p-cresol productions were recapitulated by collaboration of two organisms: a Bacteroides strain that converts tyrosine to 4-hydroxyphenylacetate, and a Clostridium strain that decarboxylates 4-hydroxyphenylacetate to p-cresol. We then engineered a single organism, Bacteroides thetaiotaomicron, to produce p-cresol, indole, or both metabolites. Colonizing germ-free mice with engineered strains, we show the gut microbial genes for p-cresol (hpdBCA) and indole (tryptophanase) are sufficient to confer a pro-thrombotic phenotype in vivo. Moreover, human fecal metagenomics analyses show that abundances of hpdBCA and tryptophanase are associated with CVD. These studies show that pCS and IS, two abundant microbiome-derived metabolites, play a broader potential role in CVD than was previously known. They also suggest that therapeutic targeting of gut microbial p-cresol- and indole-producing pathways represent rational targets for CVD.IMPORTANCEAlterations in gut microbial composition and function have been linked to numerous diseases. Identifying microbial pathways responsible for producing molecules that adversely impact the host is an important first step in the development of therapeutic interventions. Here, we first use large-scale clinical observations to link blood levels of defined microbial products to cardiovascular disease risks. Notably, the previously identified uremic toxins p-cresol sulfate and indoxyl sulfate were shown to predict 5-year mortality risks. After identifying the microbes and microbial enzymes involved in the generation of these uremic toxins, we used bioengineering technologies coupled with colonization of germ-free mice to show that the gut microbial genes that generate p-cresol and indole are sufficient to confer p-cresol sulfate and indoxyl sulfate formation, and a pro-thrombotic phenotype in vivo. The findings and tools developed serve as a critical step in both the study and targeting of these gut microbial pathways in vivo.
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Affiliation(s)
- Ina Nemet
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Masanori Funabashi
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, California, USA
- ChEM-H Institute, Stanford University, Stanford, California, USA
| | - Xinmin S. Li
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Mohammed Dwidar
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Naseer Sangwan
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Sarah M. Skye
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Kymberleigh A. Romano
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Tomas Cajka
- West Coast Metabolomics Center, University of California, Davis, California, USA
| | - Brittany D. Needham
- Departments of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Sarkis K. Mazmanian
- Departments of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Adeline M. Hajjar
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
| | - Federico E. Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, California, USA
| | - W. H. Wilson Tang
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
- Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Michael A. Fischbach
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, California, USA
- ChEM-H Institute, Stanford University, Stanford, California, USA
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Stanley L. Hazen
- Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland, Ohio, USA
- Center for Microbiome & Human Health, Cleveland Clinic, Cleveland, Ohio, USA
- Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, USA
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20
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Riquelme S, Campos JV, Alzamora R, Fiehn O, Pérez AJ. Lipidomics analysis reveals the effect of Sirex noctilio infestation on the lipid metabolism in Pinus radiata needles. Plant Sci 2023; 336:111858. [PMID: 37673219 DOI: 10.1016/j.plantsci.2023.111858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 08/25/2023] [Accepted: 09/01/2023] [Indexed: 09/08/2023]
Abstract
The Sirex noctilio's climatic adaption and rapid proliferation have caused Pinus mortality worldwide. The infestation combines the early effect of female S. noctilio gland secretion and the spreading symbiotic fungus Amylostereum areolatum. 'Lipidomics' is the study of all non-water-soluble components of the metabolome. Most of these non-water-soluble compounds correspond to lipids which can provide information about a biological activity, an organelle, an organism, or a disease. Using HPLC-MS/MS based lipidomics, 122 lipids were identified in P. radiata needles during S. noctilio infestation. Phosphatidic acids, N-acylethanolamines, and phosphatidylinositol-ceramides accumulated in infested trees could suggest a high level of phospholipases activities. The phosphatidylcholines were the most down-regulated species during infection, which could also suggest that they may be used as a substrate for up-regulated lipids. The accumulation of very long-chain fatty acids and long-chain fatty acids during the infestation could imply the tree defense response to create a barrier in the drilled zone to avoid larvae development and fungus proliferation. Also, the growth arrest phase of the trees during the prolonged infestation suggests a resistance response, regulated by the accumulation of NAE, which potentially shifts the tree energy to respond to the infestation.
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Affiliation(s)
- Sebastián Riquelme
- Departamento de Análisis Instrumental, Facultad de Farmacia, Universidad de Concepción, Concepción, Chile
| | - Jasna V Campos
- Departamento de Análisis Instrumental, Facultad de Farmacia, Universidad de Concepción, Concepción, Chile
| | - Rosa Alzamora
- Departamento Manejo de Bosques y Medio Ambiente, Facultad de Ciencias Forestales, Universidad de Concepción, Concepción, Chile
| | - Oliver Fiehn
- UC Davis Genome Center, University of California, Davis, CA, USA
| | - Andy J Pérez
- Departamento de Análisis Instrumental, Facultad de Farmacia, Universidad de Concepción, Concepción, Chile.
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21
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Taylor JE, Palur DSK, Zhang A, Gonzales JN, Arredondo A, Coulther TA, Lechner ABJ, Rodriguez EP, Fiehn O, Didzbalis J, Siegel JB, Atsumi S. Awakening the natural capability of psicose production in Escherichia coli. NPJ Sci Food 2023; 7:54. [PMID: 37838768 PMCID: PMC10576766 DOI: 10.1038/s41538-023-00231-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 10/02/2023] [Indexed: 10/16/2023] Open
Abstract
Due to the rampant rise in obesity and diabetes, consumers are desperately seeking for ways to reduce their sugar intake, but to date there are no options that are both accessible and without sacrifice of palatability. One of the most promising new ingredients in the food system as a non-nutritive sugar substitute with near perfect palatability is D-psicose. D-psicose is currently produced using an in vitro enzymatic isomerization of D-fructose, resulting in low yield and purity, and therefore requiring substantial downstream processing to obtain a high purity product. This has made adoption of D-psicose into products limited and results in significantly higher per unit costs, reducing accessibility to those most in need. Here, we found that Escherichia coli natively possesses a thermodynamically favorable pathway to produce D-psicose from D-glucose through a series of phosphorylation-epimerization-dephosphorylation steps. To increase carbon flux towards D-psicose production, we introduced a series of genetic modifications to pathway enzymes, central carbon metabolism, and competing metabolic pathways. In an attempt to maximize both cellular viability and D-psicose production, we implemented methods for the dynamic regulation of key genes including clustered regularly interspaced short palindromic repeats inhibition (CRISPRi) and stationary-phase promoters. The engineered strains achieved complete consumption of D-glucose and production of D-psicose, at a titer of 15.3 g L-1, productivity of 2 g L-1 h-1, and yield of 62% under test tube conditions. These results demonstrate the viability of whole-cell catalysis as a sustainable alternative to in vitro enzymatic synthesis for the accessible production of D-psicose.
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Affiliation(s)
- Jayce E Taylor
- Department of Chemistry, University of California, Davis, Davis, CA, 95616, USA
| | | | - Angela Zhang
- Department of Chemistry, University of California, Davis, Davis, CA, 95616, USA
| | - Jake N Gonzales
- Plant Biology Graduate Group, University of California, Davis, Davis, CA, 95616, USA
| | - Augustine Arredondo
- Department of Chemistry, University of California, Davis, Davis, CA, 95616, USA
| | | | | | - Elys P Rodriguez
- Department of Chemistry, University of California, Davis, Davis, CA, 95616, USA
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, Davis, CA, 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, Davis, CA, 95616, USA
| | - John Didzbalis
- Mars, Incorporated, 6885 Elm Street, McLean, VA, 22101, USA
| | - Justin B Siegel
- Department of Chemistry, University of California, Davis, Davis, CA, 95616, USA
- Genome Center, University of California, Davis, Davis, CA, 95616, USA
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Sacramento, CA, 95616, USA
| | - Shota Atsumi
- Department of Chemistry, University of California, Davis, Davis, CA, 95616, USA.
- Plant Biology Graduate Group, University of California, Davis, Davis, CA, 95616, USA.
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22
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Miao G, Fiehn O, Chen M, Zhang Y, Umans JG, Lee ET, Howard BV, Roman MJ, Devereux RB, Zhao J. Longitudinal lipidomic signature of carotid atherosclerosis in American Indians: Findings from the Strong Heart Family Study. Atherosclerosis 2023; 382:117265. [PMID: 37722315 DOI: 10.1016/j.atherosclerosis.2023.117265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/20/2023]
Abstract
BACKGROUND AND AIMS Dyslipidemia is an independent risk factor for atherosclerosis and atherosclerotic cardiovascular disease (ASCVD). To date, a comprehensive assessment of individual lipid species associated with atherosclerosis is lacking in large-scale epidemiological studies, especially in a longitudinal setting. We investigated the association of circulating lipid species and its longitudinal changes with carotid atherosclerosis. METHODS Using liquid chromatograph-mass spectrometry, we repeatedly measured 1542 lipid species in 3687 plasma samples from 1918 unique American Indians attending two visits (mean ∼5 years apart) in the Strong Heart Family Study. Carotid atherosclerotic plaques were assessed by ultrasonography at each visit. We identified lipids associated with prevalence or progression of carotid plaques, adjusting age, sex, BMI, smoking, hypertension, diabetes, and eGFR. Then we examined whether longitudinal changes in lipids were associated with changes in cardiovascular risk factors. Multiple testing was controlled at false discovery rate (FDR) < 0.05. RESULTS Higher levels of sphingomyelins, ether-phosphatidylcholines, and triacylglycerols were significantly associated with prevalence or progression of carotid plaques (odds ratios ranged from 1.15 to 1.34). Longitudinal changes in multiple lipid species (e.g., acylcarnitines, phosphatidylcholines, triacylglycerols) were associated with changes in cardiometabolic traits (e.g., BMI, blood pressure, fasting glucose, eGFR). Network analysis identified differential lipid networks associated with plaque progression. CONCLUSIONS Baseline and longitudinal changes in multiple lipid species were significantly associated with carotid atherosclerosis and its progression in American Indians. Some plaque-related lipid species were also associated with risk for CVD events.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Mingjing Chen
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Elisa T Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Mary J Roman
- Weill Cornell Medical College, New York, NY, 10065, USA
| | | | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA.
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23
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Abstract
Public repositories of metabolomics mass spectra encompass more than 1 billion entries. With open search, dot product or entropy similarity, comparisons of a single tandem mass spectrometry spectrum take more than 8 h. Flash entropy search speeds up calculations more than 10,000 times to query 1 billion spectra in less than 2 s, without loss in accuracy. It benefits from using multiple threads and GPU calculations. This algorithm can fully exploit large spectral libraries with little memory overhead for any mass spectrometry laboratory.
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Affiliation(s)
- Yuanyue Li
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA, USA.
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24
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Dahabiyeh LA, Nimer RM, Rashed M, Wells JD, Fiehn O. Serum-Based Lipid Panels for Diagnosis of Idiopathic Parkinson's Disease. Metabolites 2023; 13:990. [PMID: 37755270 PMCID: PMC10537766 DOI: 10.3390/metabo13090990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 09/28/2023] Open
Abstract
Parkinson's disease (PD) is a highly prevalent neurodegenerative movement disorder with an unclear etiology and a lack of definite diagnostic tests and effective treatments. About 95% of PD cases are idiopathic, in which none of the well-known genes underlying familial parkinsonism are mutated. We used untargeted liquid chromatography-mass spectrometry (LC-MS/MS) to profile the serum lipidome of 50 patients with different stages of idiopathic PD (early, mid, or advanced) and 45 age-matched controls. When comparing the PD patients to the control subjects, 169 lipids were significantly altered in both a univariate analysis and a multivariate partial least-squares discriminant analysis (PLS-DA). Compared to the controls, the patients with PD had higher levels of unsaturated triacylglycerides (e.g., TG O-56:9 and TG 52:3), saturated lysophosphatidylcholines (LPC 17:0, 16:0, and 15:0), and hydroxyeicosatetraenoic acid (12-HETE), while lower levels of phosphatidylserines (e.g., PS 40:4 and PS 16:0_22:4), sphingomyelins (SM 42:1), and ceramides (e.g., Cer 40:0 and 42:0) were found between the PD patients and the controls. A panel of 10 significantly altered lipids (PS 40:0, Cer 40:0, Cer 42:0, LPC 17:0, LPC 15:0, PC 37:7, PE O-40:8, PC O-42:4, FA 23:0, and SM 42:1) resulted in a strong receiver operating characteristic curve with an AUC = 0.974. This panel may, therefore, be useful for diagnosing PD. In addition, lipid panels may prove useful for distinguishing among the progression stages of PD. Using one-way ANOVA, 155 lipid species were significantly altered among the PD stages. Parkinson's disease progressed from the early to advanced stages with decreasing levels of PC 31:1, PC 38:4, and LPE 22:5. Conversely, LPC-O 20:0, PC O-42:3, FA 19:0, and FA 22:2 showed an increase in their levels with disease progression. Overall, this study shows an intriguing number of robust changes in specific serum lipids that may become useful for diagnosing PD and its progression, once panels have been validated in larger clinical trials and prospective studies.
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Affiliation(s)
- Lina A. Dahabiyeh
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman 11942, Jordan
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
| | - Refat M. Nimer
- Department of Medical Laboratory Sciences, Jordan University of Science and Technology, Irbid 22110, Jordan
| | - Maha Rashed
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Jeremiah D. Wells
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
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25
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Sluka KA, Wager TD, Sutherland SP, Labosky PA, Balach T, Bayman EO, Berardi G, Brummett CM, Burns J, Buvanendran A, Caffo B, Calhoun VD, Clauw D, Chang A, Coffey CS, Dailey DL, Ecklund D, Fiehn O, Fisch KM, Frey Law LA, Harris RE, Harte SE, Howard TD, Jacobs J, Jacobs JM, Jepsen K, Johnston N, Langefeld CD, Laurent LC, Lenzi R, Lindquist MA, Lokshin A, Kahn A, McCarthy RJ, Olivier M, Porter L, Qian WJ, Sankar CA, Satterlee J, Swensen AC, Vance CG, Waljee J, Wandner LD, Williams DA, Wixson RL, Zhou XJ. Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures. Pain 2023; 164:1912-1926. [PMID: 37326643 PMCID: PMC10436361 DOI: 10.1097/j.pain.0000000000002938] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 03/02/2023] [Accepted: 03/02/2023] [Indexed: 06/17/2023]
Abstract
ABSTRACT Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS's initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.
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Affiliation(s)
- Kathleen A. Sluka
- Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Tor D. Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH
| | - Stephani P. Sutherland
- Department of Biostatistics, Johns Hopkins Bloomberg Schools of Public Health, Baltimore, MD
| | - Patricia A. Labosky
- Office of Strategic Coordination, Division of Program Coordination, Planning and Strategic Initiatives, Office of the Director, National Institutes of Health, Bethesda, MD
| | - Tessa Balach
- Department of Orthopaedic Surgery and Rehabilitation Medicine, The University of Chicago, Chicago, IL
| | - Emine O. Bayman
- Clinical Trials and Data Management Center, Department of Biostatistics, University of Iowa, Iowa City, IA
| | - Giovanni Berardi
- Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Chad M. Brummett
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI
| | - John Burns
- Division of Behavioral Sciences, Rush Medical College, Chicago, IL
| | | | - Brian Caffo
- Department of Biostatistics, Johns Hopkins Bloomberg Schools of Public Health, Baltimore, MD
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA
| | - Daniel Clauw
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI
| | - Andrew Chang
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Christopher S. Coffey
- Clinical Trials and Data Management Center, Department of Biostatistics, University of Iowa, Iowa City, IA
| | - Dana L. Dailey
- Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Dixie Ecklund
- Clinical Trials and Data Management Center, Department of Biostatistics, University of Iowa, Iowa City, IA
| | - Oliver Fiehn
- University of California, Davis, Davis, CA, United States
| | - Kathleen M. Fisch
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, San Diego, CA, United States
- Center for Computational Biology and Bioinformatics, University of California San Diego, San Diego, CA, United States
| | - Laura A. Frey Law
- Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Richard E. Harris
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI
| | - Steven E. Harte
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI
| | - Timothy D. Howard
- Department of Biochemistry, Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC
- Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC
| | - Joshua Jacobs
- Department of Orthopedic Surgery, Rush Medical College, CHicago, IL
| | - Jon M. Jacobs
- Environmental and Molecular Sciences Laboratory, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA
| | | | | | - Carl D. Langefeld
- Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC
- Department of Biostatistics and Data Science, Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC
| | - Louise C. Laurent
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Diego, San Diego, CA, United States
| | - Rebecca Lenzi
- Office of Strategic Coordination, Division of Program Coordination, Planning and Strategic Initiatives, Office of the Director, National Institutes of Health, Bethesda, MD
| | - Martin A. Lindquist
- Department of Biostatistics, Johns Hopkins Bloomberg Schools of Public Health, Baltimore, MD
| | | | - Ari Kahn
- Texas Advanced Computing Center, University of Texas, AUstin, TX
| | | | - Michael Olivier
- Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC
- Department of Internal Medicine, Center for Precision Medicine, Wake Forest School of Medicine, Winstom-Salem, NC
| | - Linda Porter
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
- Office of Pain Policy and Planning National Institutes of Health, Bethesda, MD
| | - Wei-Jun Qian
- Environmental and Molecular Sciences Laboratory, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA
| | - Cheryse A. Sankar
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | | | - Adam C. Swensen
- Environmental and Molecular Sciences Laboratory, Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA
| | - Carol G.T. Vance
- Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Jennifer Waljee
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Laura D. Wandner
- National Institute of Neurological Disorders and Stroke, Bethesda, MD
| | - David A. Williams
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI
| | | | - Xiaohong Joe Zhou
- Center for MR Research and Departments of Radiology, Neurosurgery, and Bioengineering, University of Illinois College of Medicine at Chicago, Chicago, IL, United States
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Mukherjee A, Bezwada D, Greco F, Zandbergen M, Shen T, Chiang CY, Tasdemir M, Fahrmann J, Grapov D, La Frano MR, Vu HS, Faubert B, Newman JW, McDonnell LA, Nezi L, Fiehn O, DeBerardinis RJ, Lengyel E. Adipocytes reprogram cancer cell metabolism by diverting glucose towards glycerol-3-phosphate thereby promoting metastasis. Nat Metab 2023; 5:1563-1577. [PMID: 37653041 DOI: 10.1038/s42255-023-00879-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 07/27/2023] [Indexed: 09/02/2023]
Abstract
In the tumor microenvironment, adipocytes function as an alternate fuel source for cancer cells. However, whether adipocytes influence macromolecular biosynthesis in cancer cells is unknown. Here we systematically characterized the bidirectional interaction between primary human adipocytes and ovarian cancer (OvCa) cells using multi-platform metabolomics, imaging mass spectrometry, isotope tracing and gene expression analysis. We report that, in OvCa cells co-cultured with adipocytes and in metastatic tumors, a part of the glucose from glycolysis is utilized for the biosynthesis of glycerol-3-phosphate (G3P). Normoxic HIF1α protein regulates the altered flow of glucose-derived carbons in cancer cells, resulting in increased glycerophospholipids and triacylglycerol synthesis. The knockdown of HIF1α or G3P acyltransferase 3 (a regulatory enzyme of glycerophospholipid synthesis) reduced metastasis in xenograft models of OvCa. In summary, we show that, in an adipose-rich tumor microenvironment, cancer cells generate G3P as a precursor for critical membrane and signaling components, thereby promoting metastasis. Targeting biosynthetic processes specific to adipose-rich tumor microenvironments might be an effective strategy against metastasis.
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Affiliation(s)
- Abir Mukherjee
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology-Center for Integrative Sciences, University of Chicago, Chicago, IL, USA
| | - Divya Bezwada
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Francesco Greco
- Fondazione Pisana per la Scienza ONLUS, San Giuliano Terme, Italy
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Malu Zandbergen
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology-Center for Integrative Sciences, University of Chicago, Chicago, IL, USA
| | - Tong Shen
- NIH West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Chun-Yi Chiang
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology-Center for Integrative Sciences, University of Chicago, Chicago, IL, USA
| | - Medine Tasdemir
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology-Center for Integrative Sciences, University of Chicago, Chicago, IL, USA
| | - Johannes Fahrmann
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dmitry Grapov
- NIH West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Michael R La Frano
- NIH West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Hieu S Vu
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Brandon Faubert
- Department of Medicine/Section of Hematology and Oncology, University of Chicago, Chicago, IL, USA
| | - John W Newman
- NIH West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Liam A McDonnell
- Institute of Life Sciences, Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Luigi Nezi
- Department of Experimental Oncology, IRCCS European Institute of Oncology, Milano, Italy
| | - Oliver Fiehn
- NIH West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Ralph J DeBerardinis
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- 9Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ernst Lengyel
- Department of Obstetrics and Gynecology/Section of Gynecologic Oncology-Center for Integrative Sciences, University of Chicago, Chicago, IL, USA.
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27
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Brydges C, Che X, Lipkin WI, Fiehn O. Bayesian Statistics Improves Biological Interpretability of Metabolomics Data from Human Cohorts. Metabolites 2023; 13:984. [PMID: 37755264 PMCID: PMC10535181 DOI: 10.3390/metabo13090984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 08/07/2023] [Accepted: 08/28/2023] [Indexed: 09/28/2023] Open
Abstract
Univariate analyses of metabolomics data currently follow a frequentist approach, using p-values to reject a null hypothesis. We here propose the use of Bayesian statistics to quantify evidence supporting different hypotheses and discriminate between the null hypothesis versus the lack of statistical power. We used metabolomics data from three independent human cohorts that studied the plasma signatures of subjects with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The data are publicly available, covering 84-197 subjects in each study with 562-888 identified metabolites of which 777 were common between the two studies and 93 were compounds reported in all three studies. We show how Bayesian statistics incorporates results from one study as "prior information" into the next study, thereby improving the overall assessment of the likelihood of finding specific differences between plasma metabolite levels. Using classic statistics and Benjamini-Hochberg FDR-corrections, Study 1 detected 18 metabolic differences and Study 2 detected no differences. Using Bayesian statistics on the same data, we found a high likelihood that 97 compounds were altered in concentration in Study 2, after using the results of Study 1 as the prior distributions. These findings included lower levels of peroxisome-produced ether-lipids, higher levels of long-chain unsaturated triacylglycerides, and the presence of exposome compounds that are explained by the difference in diet and medication between healthy subjects and ME/CFS patients. Although Study 3 reported only 92 compounds in common with the other two studies, these major differences were confirmed. We also found that prostaglandin F2alpha, a lipid mediator of physiological relevance, was reduced in ME/CFS patients across all three studies. The use of Bayesian statistics led to biological conclusions from metabolomic data that were not found through frequentist approaches. We propose that Bayesian statistics is highly useful for studies with similar research designs if similar metabolomic assays are used.
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Affiliation(s)
| | - Xiaoyu Che
- Center for Infection and Immunity, Mailman School of Public Health of Columbia University, New York, NY 10032, USA; (X.C.); (W.I.L.)
- Department of Biostatistics, Mailman School of Public Health of Columbia University, New York, NY 10032, USA
| | - Walter Ian Lipkin
- Center for Infection and Immunity, Mailman School of Public Health of Columbia University, New York, NY 10032, USA; (X.C.); (W.I.L.)
- Vagelos College of Physicians and Surgeons of Columbia University, New York, NY 10032, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis, Davis, CA 95616, USA;
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28
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Bishop LM, Shen T, Fiehn O. Improving Quantitative Accuracy in Nontargeted Lipidomics by Evaluating Adduct Formation. Anal Chem 2023; 95:12683-12690. [PMID: 37582244 DOI: 10.1021/acs.analchem.3c01221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
For large-scale lipidomic analyses, accurate and reproducible quantification of endogenous lipids is crucial for comparing results within and across studies. Many lipids present in liquid chromatography-electrospray ionization-mass spectrometry form various adducts with buffer components. The mechanisms and conditions that dictate adduct formation are still poorly understood. In a positive mode, neutral lipids like mono-, di-, and triacylglycerides and cholesteryl esters typically generate [M + NH4]+ adduct ions, although [M + Na]+, [M + K]+, and other (more complex) species can also be significantly abundant in MS1 precursor ion spectra. Variations in the ratios of these adducts (within and between matrices) can lead to dramatic inaccuracies during quantification. Here, we examine 48 unique diacylglycerol (DAG) species across 2366 mouse samples for eight matrix-specific data sets of plasma, liver, kidney, brain, heart muscle, gastrocnemius muscle, gonadal, and inguinal fat. Typically, no single adduct ion species accounted for more than 60% of the total observed abundance across each data set. Even within a single matrix, DAGs showed a high variability of adduct ratios. The ratio of [M + NH4]+ adduct ions was increased for longer-chain DAGs and for polyunsaturated DAGs, at the expense of reduced ratios of [M + Na]+ adducts. When using three deuterated internal DAG standards, we found that absolute concentrations were estimated with up to 70% error when only one adduct ion was used instead of all adducts combined. Importantly, when combining [M + NH4]+ and [M + Na]+ adduct ions, quantification results were within 5% accuracy compared to all adduct ions combined. Additional variance can be caused by other factors, such as instrument conditions or matrix effects.
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Affiliation(s)
- Lauren M Bishop
- Department of Chemistry, University of California Davis, Davis, California 95616, United States
| | - Tong Shen
- West Coast Metabolomics Center, 451 Health Sci. Drive, University of California Davis, Davis, California 95616, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, 451 Health Sci. Drive, University of California Davis, Davis, California 95616, United States
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29
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Cajka T, Hricko J, Rudl Kulhava L, Paucova M, Novakova M, Fiehn O, Kuda O. Exploring the Impact of Organic Solvent Quality and Unusual Adduct Formation during LC-MS-Based Lipidomic Profiling. Metabolites 2023; 13:966. [PMID: 37755246 PMCID: PMC10536874 DOI: 10.3390/metabo13090966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 08/19/2023] [Accepted: 08/21/2023] [Indexed: 09/28/2023] Open
Abstract
Liquid chromatography-mass spectrometry (LC-MS) is the key technique for analyzing complex lipids in biological samples. Various LC-MS modes are used for lipid separation, including different stationary phases, mobile-phase solvents, and modifiers. Quality control in lipidomics analysis is crucial to ensuring the generated data's reliability, reproducibility, and accuracy. While several quality control measures are commonly discussed, the impact of organic solvent quality during LC-MS analysis is often overlooked. Additionally, the annotation of complex lipids remains prone to biases, leading to potential misidentifications and incomplete characterization of lipid species. In this study, we investigate how LC-MS-grade isopropanol from different vendors may influence the quality of the mobile phase used in LC-MS-based untargeted lipidomic profiling of biological samples. Furthermore, we report the occurrence of an unusual, yet highly abundant, ethylamine adduct [M+46.0651]+ that may form for specific lipid subclasses during LC-MS analysis in positive electrospray ionization mode when acetonitrile is part of the mobile phase, potentially leading to lipid misidentification. These findings emphasize the importance of considering solvent quality in LC-MS analysis and highlight challenges in lipid annotation.
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Affiliation(s)
- Tomas Cajka
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Jiri Hricko
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Lucie Rudl Kulhava
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Michaela Paucova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Michaela Novakova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, 451 Health Sciences Drive, Davis, CA 95616, USA;
| | - Ondrej Kuda
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic; (J.H.); (L.R.K.); (M.P.); (M.N.); (O.K.)
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30
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Wang S, Valdiviez L, Ye H, Fiehn O. Automatic Assignment of Molecular Ion Species to Elemental Formulas in Gas Chromatography/Methane Chemical Ionization Accurate Mass Spectrometry. Metabolites 2023; 13:962. [PMID: 37623905 PMCID: PMC10456597 DOI: 10.3390/metabo13080962] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 08/15/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023] Open
Abstract
Gas chromatography-mass spectrometry (GC-MS) usually employs hard electron ionization, leading to extensive fragmentations that are suitable to identify compounds based on library matches. However, such spectra are less useful to structurally characterize unknown compounds that are absent from libraries, due to the lack of readily recognizable molecular ion species. We tested methane chemical ionization on 369 trimethylsilylated (TMS) derivatized metabolites using a quadrupole time-of-flight detector (QTOF). We developed an algorithm to automatically detect molecular ion species and tested SIRIUS software on how accurate the determination of molecular formulas was. The automatic workflow correctly recognized 289 (84%) of all 345 detected derivatized standards. Specifically, strong [M - CH3]+ fragments were observed in 290 of 345 derivatized chemicals, which enabled the automatic recognition of molecular adduct patterns. Using Sirius software, correct elemental formulas were retrieved in 87% of cases within the top three hits. When investigating the cases for which the automatic pattern analysis failed, we found that several metabolites showed a previously unknown [M + TMS]+ adduct formed by rearrangement. Methane chemical ionization with GC-QTOF mass spectrometry is a suitable avenue to identify molecular formulas for abundant unknown peaks.
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Affiliation(s)
- Shunyang Wang
- Department of Chemistry, University of California, Davis, CA 95616, USA
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA (H.Y.)
| | - Luis Valdiviez
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA (H.Y.)
| | - Honglian Ye
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA (H.Y.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA 95616, USA (H.Y.)
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31
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Zhang Y, Barupal DK, Fan S, Gao B, Zhu C, Flenniken AM, McKerlie C, Nutter LMJ, Lloyd KCK, Fiehn O. Sexual Dimorphism of the Mouse Plasma Metabolome Is Associated with Phenotypes of 30 Gene Knockout Lines. Metabolites 2023; 13:947. [PMID: 37623890 PMCID: PMC10456929 DOI: 10.3390/metabo13080947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Although metabolic alterations are observed in many monogenic and complex genetic disorders, the impact of most mammalian genes on cellular metabolism remains unknown. Understanding the effect of mouse gene dysfunction on metabolism can inform the functions of their human orthologues. We investigated the effect of loss-of-function mutations in 30 unique gene knockout (KO) lines on plasma metabolites, including genes coding for structural proteins (11 of 30), metabolic pathway enzymes (12 of 30) and protein kinases (7 of 30). Steroids, bile acids, oxylipins, primary metabolites, biogenic amines and complex lipids were analyzed with dedicated mass spectrometry platforms, yielding 827 identified metabolites in male and female KO mice and wildtype (WT) controls. Twenty-two percent of 23,698 KO versus WT comparison tests showed significant genotype effects on plasma metabolites. Fifty-six percent of identified metabolites were significantly different between the sexes in WT mice. Many of these metabolites were also found to have sexually dimorphic changes in KO lines. We used plasma metabolites to complement phenotype information exemplified for Dhfr, Idh1, Mfap4, Nek2, Npc2, Phyh and Sra1. The association of plasma metabolites with IMPC phenotypes showed dramatic sexual dimorphism in wildtype mice. We demonstrate how to link metabolomics to genotypes and (disease) phenotypes. Sex must be considered as critical factor in the biological interpretation of gene functions.
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Affiliation(s)
- Ying Zhang
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
- Department of Chemistry, University of California Davis, Davis, CA 95616, USA
| | - Dinesh K. Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Sili Fan
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
| | - Bei Gao
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Chao Zhu
- College of Medicine & Nursing, Dezhou University, Dezhou 253023, China
| | - Ann M. Flenniken
- The Centre for Phenogenomics, Toronto, ON M5T 3H7, Canada; (A.M.F.); (C.M.); (L.M.J.N.)
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Colin McKerlie
- The Centre for Phenogenomics, Toronto, ON M5T 3H7, Canada; (A.M.F.); (C.M.); (L.M.J.N.)
- The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Lauryl M. J. Nutter
- The Centre for Phenogenomics, Toronto, ON M5T 3H7, Canada; (A.M.F.); (C.M.); (L.M.J.N.)
- The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Kevin C. Kent Lloyd
- Department of Surgery, School of Medicine, and Mouse Biology Program, University of California Davis, Davis, CA 95616, USA;
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
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32
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Aboud O, Liu Y, Dahabiyeh L, Abuaisheh A, Li F, Aboubechara JP, Riess J, Bloch O, Hodeify R, Tagkopoulos I, Fiehn O. Profile Characterization of Biogenic Amines in Glioblastoma Patients Undergoing Standard-of-Care Treatment. Biomedicines 2023; 11:2261. [PMID: 37626757 PMCID: PMC10452138 DOI: 10.3390/biomedicines11082261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 07/29/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
INTRODUCTION Biogenic amines play important roles throughout cellular metabolism. This study explores a role of biogenic amines in glioblastoma pathogenesis. Here, we characterize the plasma levels of biogenic amines in glioblastoma patients undergoing standard-of-care treatment. METHODS We examined 138 plasma samples from 36 patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma at multiple stages of treatment. Untargeted gas chromatography-time of flight mass spectrometry (GC-TOF MS) was used to measure metabolite levels. Machine learning approaches were then used to develop a predictive tool based on these datasets. RESULTS Surgery was associated with increased levels of 12 metabolites and decreased levels of 11 metabolites. Chemoradiation was associated with increased levels of three metabolites and decreased levels of three other metabolites. Ensemble learning models, specifically random forest (RF) and AdaBoost (AB), accurately classified treatment phases with high accuracy (RF: 0.81 ± 0.04, AB: 0.78 ± 0.05). The metabolites sorbitol and N-methylisoleucine were identified as important predictive features and confirmed via SHAP. CONCLUSION To our knowledge, this is the first study to describe plasma biogenic amine signatures throughout the treatment of patients with glioblastoma. A larger study is needed to confirm these results with hopes of developing a diagnostic algorithm.
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Affiliation(s)
- Orwa Aboud
- Department of Neurology, University of California, Davis, Sacramento, CA 95817, USA
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
| | - Yin Liu
- Department of Neurology, University of California, Davis, Sacramento, CA 95817, USA
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
- Department of Ophthalmology, University of California, Davis, Sacramento, CA 95817, USA
| | - Lina Dahabiyeh
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Ahmad Abuaisheh
- School of Medicine, Al Balqa Applied University, Al-Salt 19117, Jordan
| | - Fangzhou Li
- Department of Computer Science, University of California, Davis, Sacramento, CA 95616, USA
- Genome Center, University of California, Davis, Sacramento, CA 95616, USA
- USDA/NSF AI Institute for Next Generation Food Systems (AIFS), Davis, CA 95616, USA
| | | | - Jonathan Riess
- Comprehensive Cancer Center, University of California Davis, Sacramento, CA 95817, USA
- Department of Internal Medicine, Division of Hematology and Oncology, University of California, Davis, Sacramento, CA 95817, USA
| | - Orin Bloch
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA 95817, USA
| | - Rawad Hodeify
- Department of Biotechnology, School of Arts and Sciences, American University of Ras Al Khaimah, Ras Al-Khaimah 10021, United Arab Emirates
| | - Ilias Tagkopoulos
- Department of Computer Science, University of California, Davis, Sacramento, CA 95616, USA
- Genome Center, University of California, Davis, Sacramento, CA 95616, USA
- USDA/NSF AI Institute for Next Generation Food Systems (AIFS), Davis, CA 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA
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33
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Zhang Y, Fan S, Wohlgemuth G, Fiehn O. Denoising Autoencoder Normalization for Large-Scale Untargeted Metabolomics by Gas Chromatography-Mass Spectrometry. Metabolites 2023; 13:944. [PMID: 37623887 PMCID: PMC10456436 DOI: 10.3390/metabo13080944] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 07/31/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Large-scale metabolomics assays are widely used in epidemiology for biomarker discovery and risk assessments. However, systematic errors introduced by instrumental signal drifting pose a big challenge in large-scale assays, especially for derivatization-based gas chromatography-mass spectrometry (GC-MS). Here, we compare the results of different normalization methods for a study with more than 4000 human plasma samples involved in a type 2 diabetes cohort study, in addition to 413 pooled quality control (QC) samples, 413 commercial pooled plasma samples, and a set of 25 stable isotope-labeled internal standards used for every sample. Data acquisition was conducted across 1.2 years, including seven column changes. In total, 413 pooled QC (training) and 413 BioIVT samples (validation) were used for normalization comparisons. Surprisingly, neither internal standards nor sum-based normalizations yielded median precision of less than 30% across all 563 metabolite annotations. While the machine-learning-based SERRF algorithm gave 19% median precision based on the pooled quality control samples, external cross-validation with BioIVT plasma pools yielded a median 34% relative standard deviation (RSD). We developed a new method: systematic error reduction by denoising autoencoder (SERDA). SERDA lowered the median standard deviations of the training QC samples down to 16% RSD, yielding an overall error of 19% RSD when applied to the independent BioIVT validation QC samples. This is the largest study on GC-MS metabolomics ever reported, demonstrating that technical errors can be normalized and handled effectively for this assay. SERDA was further validated on two additional large-scale GC-MS-based human plasma metabolomics studies, confirming the superior performance of SERDA over SERRF or sum normalizations.
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Affiliation(s)
| | | | | | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis, 451 Health Sciences Drive, Davis, CA 95616, USA; (Y.Z.); (S.F.); (G.W.)
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Bremer PL, Fiehn O. SMetaS: A Sample Metadata Standardizer for Metabolomics. Metabolites 2023; 13:941. [PMID: 37623884 PMCID: PMC10456726 DOI: 10.3390/metabo13080941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 07/26/2023] [Accepted: 08/10/2023] [Indexed: 08/26/2023] Open
Abstract
Metabolomics has advanced to an extent where it is desired to standardize and compare data across individual studies. While past work in standardization has focused on data acquisition, data processing, and data storage aspects, metabolomics databases are useless without ontology-based descriptions of biological samples and study designs. We introduce here a user-centric tool to automatically standardize sample metadata. Using such a tool in frontends for metabolomic databases will dramatically increase the FAIRness (Findability, Accessibility, Interoperability, and Reusability) of data, specifically for data reuse and for finding datasets that share comparable sets of metadata, e.g., study meta-analyses, cross-species analyses or large scale metabolomic atlases. SMetaS (Sample Metadata Standardizer) combines a classic database with an API and frontend and is provided in a containerized environment. The tool has two user-centric components. In the first component, the user designs a sample metadata matrix and fills the cells using natural language terminology. In the second component, the tool transforms the completed matrix by replacing freetext terms with terms from fixed vocabularies. This transformation process is designed to maximize simplicity and is guided by, among other strategies, synonym matching and typographical fixing in an n-grams/nearest neighbors model approach. The tool enables downstream analysis of submitted studies and samples via string equality for FAIR retrospective use.
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Affiliation(s)
- Parker Ladd Bremer
- Department of Chemistry, University of California, Davis, CA 95616, USA;
| | - Oliver Fiehn
- West Coast Metabolomics Center for Compound Identification, UC Davis Genome Center, University of California, Davis, CA 95616, USA
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Cumeras R, Shen T, Valdiviez L, Tippins Z, Haffner BD, Fiehn O. Differences in the Stool Metabolome between Vegans and Omnivores: Analyzing the NIST Stool Reference Material. Metabolites 2023; 13:921. [PMID: 37623865 PMCID: PMC10456543 DOI: 10.3390/metabo13080921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 07/27/2023] [Accepted: 08/03/2023] [Indexed: 08/26/2023] Open
Abstract
To gain confidence in results of omic-data acquisitions, methods must be benchmarked using validated quality control materials. We report data combining both untargeted and targeted metabolomics assays for the analysis of four new human fecal reference materials developed by the U.S. National Institute of Standards and Technologies (NIST) for metagenomics and metabolomics measurements. These reference grade test materials (RGTM) were established by NIST based on two different diets and two different samples treatments, as follows: firstly, homogenized fecal matter from subjects eating vegan diets, stored and submitted in either lyophilized (RGTM 10162) or aqueous form (RGTM 10171); secondly, homogenized fecal matter from subjects eating omnivore diets, stored and submitted in either lyophilized (RGTM 10172) or aqueous form (RGTM 10173). We used four untargeted metabolomics assays (lipidomics, primary metabolites, biogenic amines and polyphenols) and one targeted assay on bile acids. A total of 3563 compounds were annotated by mass spectrometry, including 353 compounds that were annotated in more than one assay. Almost half of all compounds were annotated using hydrophilic interaction chromatography/accurate mass spectrometry, followed by the lipidomics and the polyphenol assays. In total, 910 metabolites were found in at least 4-fold different levels in fecal matter from vegans versus omnivores, specifically for peptides, amino acids and lipids. In comparison, only 251 compounds showed 4-fold differences between lyophilized and aqueous fecal samples, including DG O-34:0 and methionine sulfoxide. A range of diet-specific metabolites were identified to be significantly different between vegans and omnivores, exemplified by citrinin and C17:0-acylcarnitine for omnivores, and curcumin and lenticin for vegans. Bioactive molecules like acyl alpha-hydroxy-fatty acids (AAHFA) were differentially regulated in vegan versus omnivore fecal materials, highlighting the importance of diet-specific reference materials for dietary biomarker studies.
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Affiliation(s)
- Raquel Cumeras
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA; (R.C.)
- Oncology Department, Institut d’Investigació Sanitària Pere Virgili (IISPV), Univeristat Rovira i Virgili (URV), 43204 Reus, Spain
- Nutrition and Metabolism Department, Institut d’Investigació Sanitària Pere Virgili (IISPV), Univeristat Rovira i Virgili (URV), 43204 Reus, Spain
| | - Tong Shen
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA; (R.C.)
| | - Luis Valdiviez
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA; (R.C.)
| | - Zakery Tippins
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA; (R.C.)
| | - Bennett D. Haffner
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA; (R.C.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA 95616, USA; (R.C.)
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Chen M, Miao G, Zhang Y, Umans JG, Lee ET, Howard BV, Fiehn O, Zhao J. Longitudinal Lipidomic Profile of Hypertension in American Indians: Findings From the Strong Heart Family Study. Hypertension 2023; 80:1771-1783. [PMID: 37334699 PMCID: PMC10526703 DOI: 10.1161/hypertensionaha.123.21144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 06/06/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND Dyslipidemia is an important risk factor for hypertension and cardiovascular disease. Standard lipid panel cannot reflect the complexity of blood lipidome. The associations of individual lipid species with hypertension remain to be determined in large-scale epidemiological studies, especially in a longitudinal setting. METHODS Using liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species in 3699 fasting plasma samples at 2 visits (1905 at baseline, 1794 at follow-up, ~5.5 years apart) from 1905 unique American Indians in the Strong Heart Family Study. We first identified baseline lipids associated with prevalent and incident hypertension, followed by replication of top hits in Europeans. We then conducted repeated measurement analysis to examine the associations of changes in lipid species with changes in systolic blood pressure, diastolic blood pressure, and mean arterial pressure. Network analysis was performed to identify lipid networks associated with the risk of hypertension. RESULTS Baseline levels of multiple lipid species, for example, glycerophospholipids, cholesterol esters, sphingomyelins, glycerolipids, and fatty acids, were significantly associated with both prevalent and incident hypertension in American Indians. Some lipids were confirmed in Europeans. Longitudinal changes in multiple lipid species, for example, acylcarnitines, phosphatidylcholines, fatty acids, and triacylglycerols, were significantly associated with changes in blood pressure measurements. Network analysis identified distinct lipidomic patterns associated with the risk of hypertension. CONCLUSIONS Baseline plasma lipid species and their longitudinal changes are significantly associated with hypertension development in American Indians. Our findings shed light on the role of dyslipidemia in hypertension and may offer potential opportunities for risk stratification and early prediction of hypertension.
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Affiliation(s)
- Mingjing Chen
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL
| | - Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Jason G. Umans
- MedStar Health Research Institute, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Elisa T. Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Barbara V. Howard
- MedStar Health Research Institute, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, CA
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL
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Miao G, Fiehn O, Malloy KM, Zhang Y, Lee ET, Howard BV, Zhao J. Longitudinal lipidomic signatures of all-cause and CVD mortality in American Indians: findings from the Strong Heart Study. GeroScience 2023; 45:2669-2687. [PMID: 37055600 PMCID: PMC10651623 DOI: 10.1007/s11357-023-00793-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 04/05/2023] [Indexed: 04/15/2023] Open
Abstract
Dyslipidemia is an independent and modifiable risk factor for aging and age-related disorders. Routine lipid panel cannot capture all individual lipid species in blood (i.e., blood lipidome). To date, a comprehensive assessment of the blood lipidome associated with mortality is lacking in large-scale community-dwelling individuals, especially in a longitudinal setting. Using liquid chromatograph-mass spectrometry, we repeatedly measured individual lipid species in 3,821 plasma samples collected at two visits (~ 5.5 years apart) from 1,930 unique American Indians in the Strong Heart Family Study. We first identified baseline lipids associated with risks for all-cause mortality and CVD mortality (mean follow-up period: 17.8 years) in American Indians, followed by replication of top hits in European Caucasians in the Malmö Diet and Cancer-Cardiovascular Cohort (n = 3,943, mean follow-up period: 23.7 years). The model adjusted age, sex, BMI, smoking, hypertension, diabetes, and LDL-c at baseline. We then examined the associations between changes in lipid species and risk of mortality. Multiple testing was controlled by false discovery rate (FDR). We found that baseline levels and longitudinal changes of multiple lipid species, e.g., cholesterol esters, glycerophospholipids, sphingomyelins, and triacylglycerols, were significantly associated with risks of all-cause or CVD mortality. Many lipids identified in American Indians could be replicated in European Caucasians. Network analysis identified differential lipid networks associated with risk of mortality. Our findings provide novel insight into the role of dyslipidemia in disease mortality and offer potential biomarkers for early prediction and risk reduction in American Indians and other ethnic groups.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32610, USA
- Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, CA, USA
| | - Kimberly M Malloy
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Elisa T Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32610, USA.
- Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA.
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Bremer PL, Wohlgemuth G, Fiehn O. The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples. J Cheminform 2023; 15:66. [PMID: 37475020 PMCID: PMC10359220 DOI: 10.1186/s13321-023-00734-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 07/08/2023] [Indexed: 07/22/2023] Open
Abstract
Metabolomics by gas chromatography/mass spectrometry (GC/MS) provides a standardized and reliable platform for understanding small molecule biology. Since 2005, the West Coast Metabolomics Center at the University of California at Davis has collated GC/MS metabolomics data from over 156,000 samples and 2000 studies into the standardized BinBase database. We believe that the observations from these samples will provide meaningful insight to biologists and that our data treatment and webtool will provide insight to others who seek to standardize disparate metabolomics studies. We here developed an easy-to-use query interface, BinDiscover, to enable intuitive, rapid hypothesis generation for biologists based on these metabolomic samples. BinDiscover creates observation summaries and graphics across a broad range of species, organs, diseases, and compounds. Throughout the components of BinDiscover, we emphasize the use of ontologies to aggregate large groups of samples based on the proximity of their metadata within these ontologies. This adjacency allows for the simultaneous exploration of entire categories such as "rodents", "digestive tract", or "amino acids". The ontologies are particularly relevant for BinDiscover's ontologically grouped differential analysis, which, like other components of BinDiscover, creates clear graphs and summary statistics across compounds and biological metadata. We exemplify BinDiscover's extensive applicability in three showcases across biological domains.
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Affiliation(s)
| | - Gert Wohlgemuth
- West Coast Metabolomics Center for Compound Identification, UC Davis Genome Center, University of California, Davis, CA 95616 USA
| | - Oliver Fiehn
- West Coast Metabolomics Center for Compound Identification, UC Davis Genome Center, University of California, Davis, CA 95616 USA
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Rodríguez EP, Li Y, Vaniya A, Shih PM, Fiehn O. Alternative Identification of Glycosides Using MS/MS Matching with an In Silico-Modified Aglycone Mass Spectra Library. Anal Chem 2023. [PMID: 37390485 DOI: 10.1021/acs.analchem.3c00957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2023]
Abstract
Glycosylation of metabolites serves multiple purposes. Adding sugars makes metabolites more water soluble and improves their biodistribution, stability, and detoxification. In plants, the increase in melting points enables storing otherwise volatile compounds that are released by hydrolysis when needed. Classically, glycosylated metabolites were identified by mass spectrometry (MS/MS) using [M-sugar] neutral losses. Herein, we studied 71 pairs of glycosides with their respective aglycones, including hexose, pentose, and glucuronide moieties. Using liquid chromatography (LC) coupled to electrospray ionization high-resolution mass spectrometry, we detected the classic [M-sugar] product ions for only 68% of glycosides. Instead, we found that most aglycone MS/MS product ions were conserved in the MS/MS spectra of their corresponding glycosides, even when no [M-sugar] neutral losses were observed. We added pentose and hexose units to the precursor masses of an MS/MS library of 3057 aglycones to enable rapid identification of glycosylated natural products with standard MS/MS search algorithms. When searching unknown compounds in untargeted LC-MS/MS metabolomics data of chocolate and tea, we structurally annotated 108 novel glycosides in standard MS-DIAL data processing. We uploaded this new in silico-glycosylated product MS/MS library to GitHub to enable users to detect natural product glycosides without authentic chemical standards.
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Affiliation(s)
- Elys P Rodríguez
- Department of Chemistry, University of California Davis, Davis, California 95616, United States
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
| | - Yuanyue Li
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
| | - Arpana Vaniya
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
| | - Patrick M Shih
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, California 94720, United States
- Feedstocks Division, Joint BioEnergy Institute, Emeryville, California 94608, United States
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 97420, United States
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California 94720, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, California 95616, United States
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40
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Watkins BA, Newman JW, Kuchel GA, Fiehn O, Kim J. Dietary Docosahexaenoic Acid and Glucose Systemic Metabolic Changes in the Mouse. Nutrients 2023; 15:2679. [PMID: 37375583 DOI: 10.3390/nu15122679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 05/31/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
The endocannabinoid system (ECS) participates in regulating whole body energy balance. Overactivation of the ECS has been associated with the negative consequence of obesity and type 2 diabetes. Since activators of the ECS rely on lipid-derived ligands, an investigation was conducted to determine whether dietary PUFA could influence the ECS to affect glucose clearance by measuring metabolites of macronutrient metabolism. C57/blk6 mice were fed a control or DHA-enriched semi-purified diet for a period of 112 d. Plasma, skeletal muscle, and liver were collected after 56 d and 112 d of feeding the diets for metabolomics analysis. Key findings characterized a shift in glucose metabolism and greater catabolism of fatty acids in mice fed the DHA diet. Glucose use and promotion of fatty acids as substrate were found based on levels of metabolic pathway intermediates and altered metabolic changes related to pathway flux with DHA feeding. Greater levels of DHA-derived glycerol lipids were found subsequently leading to the decrease of arachidonate-derived endocannabinoids (eCB). Levels of 1- and 2-arachidonylglcerol eCB in muscle and liver were lower in the DHA diet group compared to controls. These findings demonstrate that DHA feeding in mice alters macronutrient metabolism and may restore ECS tone by lowering arachidonic acid derived eCB.
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Affiliation(s)
- Bruce A Watkins
- Department of Nutrition, University of California, Davis, Davis, CA 95616, USA
- Center on Aging, University of Connecticut Health Center, Farmington, CT 06030, USA
| | - John W Newman
- United States Department of Agriculture, Agricultural Research Service, Western Human Nutrition Research Center, Davis, CA 95616, USA
| | - George A Kuchel
- Center on Aging, University of Connecticut Health Center, Farmington, CT 06030, USA
| | - Oliver Fiehn
- NIH UC Davis West Coast Metabolomics Center, Davis, CA 95616, USA
| | - Jeffrey Kim
- Genome and Biomedical Sciences Facility, University of California, Davis, Davis, CA 95616, USA
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Miao G, Deen J, Struzeski JB, Chen M, Zhang Y, Cole SA, Fretts AM, Lee ET, Howard BV, Fiehn O, Zhao J. Plasma lipidomic profile of depressive symptoms: a longitudinal study in a large sample of community-dwelling American Indians in the strong heart study. Mol Psychiatry 2023; 28:2480-2489. [PMID: 36653676 PMCID: PMC10753994 DOI: 10.1038/s41380-023-01948-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 01/05/2023] [Accepted: 01/06/2023] [Indexed: 01/20/2023]
Abstract
Dyslipidemia has been associated with depression, but individual lipid species associated with depression remain largely unknown. The temporal relationship between lipid metabolism and the development of depression also remains to be determined. We studied 3721 fasting plasma samples from 1978 American Indians attending two exams (2001-2003, 2006-2009, mean ~5.5 years apart) in the Strong Heart Family Study. Plasma lipids were repeatedly measured by untargeted liquid chromatography-mass spectrometry (LC-MS). Depressive symptoms were assessed using the 20-item Center for Epidemiologic Studies for Depression (CES-D). Participants at risk for depression were defined as total CES-D score ≥16. Generalized estimating equation (GEE) was used to examine the associations of lipid species with incident or prevalent depression, adjusting for covariates. The associations between changes in lipids and changes in depressive symptoms were additionally adjusted for baseline lipids. We found that lower levels of sphingomyelins and glycerophospholipids and higher level of lysophospholipids were significantly associated with incident and/or prevalent depression. Changes in sphingomyelins, glycerophospholipids, acylcarnitines, fatty acids and triacylglycerols were associated with changes in depressive symptoms and other psychosomatic traits. We also identified differential lipid networks associated with risk of depression. The observed alterations in lipid metabolism may affect depression through increasing the activities of acid sphingomyelinase and phospholipase A2, disturbing neurotransmitters and membrane signaling, enhancing inflammation, oxidative stress, and lipid peroxidation, and/or affecting energy storage in lipid droplets or membrane formation. These findings illuminate the mechanisms through which dyslipidemia may contribute to depression and provide initial evidence for targeting lipid metabolism in developing preventive and therapeutic interventions for depression.
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Affiliation(s)
- Guanhong Miao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
- Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA
| | - Jason Deen
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Joseph B Struzeski
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
- Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA
| | - Mingjing Chen
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
- Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Shelley A Cole
- Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Elisa T Lee
- Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, California, CA, USA
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA.
- Center for Genetic Epidemiology and Bioinformatics, University of Florida, Gainesville, FL, USA.
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Che X, Roy A, Bresnahan M, Mjaaland S, Reichborn-Kjennerud T, Magnus P, Stoltenberg C, Shang Y, Zhang K, Susser E, Fiehn O, Lipkin WI. Metabolomic analysis of maternal mid-gestation plasma and cord blood in autism spectrum disorders. Mol Psychiatry 2023; 28:2355-2369. [PMID: 37037873 DOI: 10.1038/s41380-023-02051-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 04/12/2023]
Abstract
The discovery of prenatal and neonatal molecular biomarkers has the potential to yield insights into autism spectrum disorder (ASD) and facilitate early diagnosis. We characterized metabolomic profiles in ASD using plasma samples collected in the Norwegian Autism Birth Cohort from mothers at weeks 17-21 gestation (maternal mid-gestation, MMG, n = 408) and from children on the day of birth (cord blood, CB, n = 418). We analyzed associations using sex-stratified adjusted logistic regression models with Bayesian analyses. Chemical enrichment analyses (ChemRICH) were performed to determine altered chemical clusters. We also employed machine learning algorithms to assess the utility of metabolomics as ASD biomarkers. We identified ASD associations with a variety of chemical compounds including arachidonic acid, glutamate, and glutamine, and metabolite clusters including hydroxy eicospentaenoic acids, phosphatidylcholines, and ceramides in MMG and CB plasma that are consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission and neurotoxicity. Girls with ASD have disruption of ether/non-ether phospholipid balance in the MMG plasma that is similar to that found in other neurodevelopmental disorders. ASD boys in the CB analyses had the highest number of dysregulated chemical clusters. Machine learning classifiers distinguished ASD cases from controls with area under the receiver operating characteristic (AUROC) values ranging from 0.710 to 0.853. Predictive performance was better in CB analyses than in MMG. These findings may provide new insights into the sex-specific differences in ASD and have implications for discovery of biomarkers that may enable early detection and intervention.
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Affiliation(s)
- Xiaoyu Che
- Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ayan Roy
- Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Michaeline Bresnahan
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | | | - Ted Reichborn-Kjennerud
- Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Per Magnus
- Norwegian Institute of Public Health, Oslo, Norway
| | - Camilla Stoltenberg
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health, University of Bergen, Bergen, Norway
| | - Yimeng Shang
- Department of Public Health Sciences, College of Medicine, Penn State University, State College, PA, 16801, USA
| | - Keming Zhang
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ezra Susser
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Oliver Fiehn
- UC Davis Genome Center-Metabolomics, University of California, Davis, CA, USA
| | - W Ian Lipkin
- Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA.
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
- Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
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Fong L, Huebner K, Jing R, Smalley K, Brydges C, Fiehn O, Farber J, Croce C. Zinc treatment reverses and anti-Zn-regulated miRs suppress esophageal carcinomas in vivo. Proc Natl Acad Sci U S A 2023; 120:e2220334120. [PMID: 37155893 PMCID: PMC10193985 DOI: 10.1073/pnas.2220334120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 04/04/2023] [Indexed: 05/10/2023] Open
Abstract
Esophageal squamous cell carcinoma (ESCC) is a deadly disease with few prevention or treatment options. ESCC development in humans and rodents is associated with Zn deficiency (ZD), inflammation, and overexpression of oncogenic microRNAs: miR-31 and miR-21. In a ZD-promoted ESCC rat model with upregulation of these miRs, systemic antimiR-31 suppresses the miR-31-EGLN3/STK40-NF-κB-controlled inflammatory pathway and ESCC. In this model, systemic delivery of Zn-regulated antimiR-31, followed by antimiR-21, restored expression of tumor-suppressor proteins targeted by these specific miRs: STK40/EGLN3 (miR-31), PDCD4 (miR-21), suppressing inflammation, promoting apoptosis, and inhibiting ESCC development. Moreover, ESCC-bearing Zn-deficient (ZD) rats receiving Zn medication showed a 47% decrease in ESCC incidence vs. Zn-untreated controls. Zn treatment eliminated ESCCs by affecting a spectrum of biological processes that included downregulation of expression of the two miRs and miR-31-controlled inflammatory pathway, stimulation of miR-21-PDCD4 axis apoptosis, and reversal of the ESCC metabolome: with decrease in putrescine, increase in glucose, accompanied by downregulation of metabolite enzymes ODC and HK2. Thus, Zn treatment or miR-31/21 silencing are effective therapeutic strategies for ESCC in this rodent model and should be examined in the human counterpart exhibiting the same biological processes.
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Affiliation(s)
- Louise Y. Fong
- Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University, Philadelphia, PA19107
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA19107
| | - Kay Huebner
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH43210
| | - Ruiyan Jing
- Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University, Philadelphia, PA19107
| | - Karl J. Smalley
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA19107
| | - Christopher R. Brydges
- NIH West Coast Metabolomics Center, The Genome Center, University of California, Davis, CA95616
| | - Oliver Fiehn
- NIH West Coast Metabolomics Center, The Genome Center, University of California, Davis, CA95616
| | - John L. Farber
- Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University, Philadelphia, PA19107
| | - Carlo M. Croce
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH43210
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Folz J, Culver RN, Morales JM, Grembi J, Triadafilopoulos G, Relman DA, Huang KC, Shalon D, Fiehn O. Human metabolome variation along the upper intestinal tract. Nat Metab 2023; 5:777-788. [PMID: 37165176 PMCID: PMC10229427 DOI: 10.1038/s42255-023-00777-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 03/03/2023] [Indexed: 05/12/2023]
Abstract
Most processing of the human diet occurs in the small intestine. Metabolites in the small intestine originate from host secretions, plus the ingested exposome1 and microbial transformations. Here we probe the spatiotemporal variation of upper intestinal luminal contents during routine daily digestion in 15 healthy male and female participants. For this, we use a non-invasive, ingestible sampling device to collect and analyse 274 intestinal samples and 60 corresponding stool homogenates by combining five mass spectrometry assays2,3 and 16S rRNA sequencing. We identify 1,909 metabolites, including sulfonolipids and fatty acid esters of hydroxy fatty acids (FAHFA) lipids. We observe that stool and intestinal metabolomes differ dramatically. Food metabolites display trends in dietary biomarkers, unexpected increases in dicarboxylic acids along the intestinal tract and a positive association between luminal keto acids and fruit intake. Diet-derived and microbially linked metabolites account for the largest inter-individual differences. Notably, two individuals who had taken antibiotics within 6 months before sampling show large variation in levels of bioactive FAHFAs and sulfonolipids and other microbially related metabolites. From inter-individual variation, we identify Blautia species as a candidate to be involved in FAHFA metabolism. In conclusion, non-invasive, in vivo sampling of the human small intestine and ascending colon under physiological conditions reveals links between diet, host and microbial metabolism.
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Affiliation(s)
- Jacob Folz
- West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Rebecca Neal Culver
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Jessica Grembi
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | | | - David A Relman
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Kerwyn Casey Huang
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA, USA.
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45
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Shalon D, Culver RN, Grembi JA, Folz J, Treit PV, Shi H, Rosenberger FA, Dethlefsen L, Meng X, Yaffe E, Aranda-Díaz A, Geyer PE, Mueller-Reif JB, Spencer S, Patterson AD, Triadafilopoulos G, Holmes SP, Mann M, Fiehn O, Relman DA, Huang KC. Profiling the human intestinal environment under physiological conditions. Nature 2023; 617:581-591. [PMID: 37165188 PMCID: PMC10191855 DOI: 10.1038/s41586-023-05989-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 03/21/2023] [Indexed: 05/12/2023]
Abstract
The spatiotemporal structure of the human microbiome1,2, proteome3 and metabolome4,5 reflects and determines regional intestinal physiology and may have implications for disease6. Yet, little is known about the distribution of microorganisms, their environment and their biochemical activity in the gut because of reliance on stool samples and limited access to only some regions of the gut using endoscopy in fasting or sedated individuals7. To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. Collection of 240 intestinal samples from 15 healthy individuals using the device and subsequent multi-omics analyses identified significant differences between bacteria, phages, host proteins and metabolites in the intestines versus stool. Certain microbial taxa were differentially enriched and prophage induction was more prevalent in the intestines than in stool. The host proteome and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Furthermore, microbially conjugated bile acid concentrations exhibited amino acid-dependent trends that were not apparent in stool. Overall, non-invasive, longitudinal profiling of microorganisms, proteins and bile acids along the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.
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Affiliation(s)
| | - Rebecca Neal Culver
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
| | - Jessica A Grembi
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Jacob Folz
- West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA
| | - Peter V Treit
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, Germany
| | - Handuo Shi
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Florian A Rosenberger
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, Germany
| | - Les Dethlefsen
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Eitan Yaffe
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Philipp E Geyer
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, Germany
| | - Johannes B Mueller-Reif
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, Germany
| | - Sean Spencer
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, CA, USA
| | - Andrew D Patterson
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA
| | - George Triadafilopoulos
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, CA, USA
- Silicon Valley Neurogastroenterology and Motility Center, Mountain View, CA, USA
| | - Susan P Holmes
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, Germany
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, Davis, CA, USA.
- Department of Food Science and Technology, University of California, Davis, Davis, CA, USA.
| | - David A Relman
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
- Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA.
| | - Kerwyn Casey Huang
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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Hricko J, Rudl Kulhava L, Paucova M, Novakova M, Kuda O, Fiehn O, Cajka T. Short-Term Stability of Serum and Liver Extracts for Untargeted Metabolomics and Lipidomics. Antioxidants (Basel) 2023; 12:antiox12050986. [PMID: 37237852 DOI: 10.3390/antiox12050986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 04/18/2023] [Accepted: 04/21/2023] [Indexed: 05/28/2023] Open
Abstract
Thermal reactions can significantly alter the metabolomic and lipidomic content of biofluids and tissues during storage. In this study, we investigated the stability of polar metabolites and complex lipids in dry human serum and mouse liver extracts over a three-day period under various temperature conditions. Specifically, we tested temperatures of -80 °C (freezer), -24 °C (freezer), -0.5 °C (polystyrene box with gel-based ice packs), +5 °C (refrigerator), +23 °C (laboratory, room temperature), and +30 °C (thermostat) to simulate the time between sample extraction and analysis, shipping dry extracts to different labs as an alternative to dry ice, and document the impact of higher temperatures on sample integrity. The extracts were analyzed using five fast liquid chromatography-mass spectrometry (LC-MS) methods to screen polar metabolites and complex lipids, and over 600 metabolites were annotated in serum and liver extracts. We found that storing dry extracts at -24 °C and partially at -0.5 °C provided comparable results to -80 °C (reference condition). However, increasing the storage temperatures led to significant changes in oxidized triacylglycerols, phospholipids, and fatty acids within three days. Polar metabolites were mainly affected at storage temperatures of +23 °C and +30 °C.
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Affiliation(s)
- Jiri Hricko
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Lucie Rudl Kulhava
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Michaela Paucova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Michaela Novakova
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Ondrej Kuda
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Tomas Cajka
- Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech Republic
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Chehab RF, Ferrara A, Zheng S, Barupal DK, Ngo AL, Chen L, Fiehn O, Zhu Y. In utero metabolomic signatures of refined grain intake and risk of gestational diabetes: A metabolome-wide association study. Am J Clin Nutr 2023; 117:731-740. [PMID: 36781127 PMCID: PMC10273195 DOI: 10.1016/j.ajcnut.2023.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 01/06/2023] [Accepted: 02/08/2023] [Indexed: 02/13/2023] Open
Abstract
BACKGROUND Epidemiologic evidence has linked refined grain intake to a higher risk of gestational diabetes (GDM), but the biological underpinnings remain unclear. OBJECTIVES We aimed to identify and validate refined grain-related metabolomic biomarkers for GDM risk. METHODS In a metabolome-wide association study of 91 cases with GDM and 180 matched controls without GDM (discovery set) nested in the prospective Pregnancy Environment and Lifestyle Study (PETALS), refined grain intake during preconception and early pregnancy and serum untargeted metabolomics were assessed at gestational weeks 10-13. We identified refined grain-related metabolites using multivariable linear regression and examined their prospective associations with GDM risk using conditional logistic regression. We further examined the predictivity of refined grain-related metabolites selected by least absolute shrinkage and selection operator regression in the discovery set and validation set (a random PETALS subsample of 38 individuals with and 336 without GDM). RESULTS Among 821 annotated serum (87.4% fasting) metabolites, 42 were associated with refined grain intake, of which 17 (70.6% in glycerolipids, glycerophospholipids, and sphingolipids clusters) were associated with subsequent GDM risk (all false discovery rate-adjusted P values <0.05). Adding 7 of 17 metabolites to a conventional risk factor-based prediction model increased the C-statistic for GDM risk in the discovery set from 0.71 (95% CI: 0.64, 0.77) to 0.77 (95% CI: 0.71, 0.83) and in the validation set from 0.77 (95% CI: 0.69, 0.86) to 0.81 (95% CI: 0.74, 0.89), both with P-for-difference <0.05. CONCLUSIONS Clusters of glycerolipids, glycerophospholipids, and sphingolipids may be implicated in the association between refined grain intake and GDM risk, as demonstrated by the significant associations of these metabolites with both refined grains and GDM risk and the incremental predictive value of these metabolites for GDM risk beyond the conventional risk factors. These findings provide evidence on the potential biological underpinnings linking refined grain intake to the risk of GDM and help identify novel disease-related dietary biomarkers to inform diet-related preventive strategies for GDM.
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Affiliation(s)
- Rana F Chehab
- Division of Research, Kaiser Permanente Northern California, Oakland, CA.
| | - Assiamira Ferrara
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Siwen Zheng
- School of Public Health, University of California, Berkeley, CA
| | - Dinesh K Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, NY
| | - Amanda L Ngo
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Liwei Chen
- Department of Epidemiology, University of California, Los Angeles, CA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA
| | - Yeyi Zhu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA.
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Martin-Pelaez S, Rabow Z, de la Fuente A, Draheim P, Loynachan A, Fiehn O, Meyers S, Lyman C, Dini P. Effect of pentobarbital as a euthanasia agent on equine in vitro embryo production. Theriogenology 2023; 205:1-8. [PMID: 37084499 DOI: 10.1016/j.theriogenology.2023.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/20/2023] [Accepted: 04/02/2023] [Indexed: 04/07/2023]
Abstract
Postmortem and pre-euthanasia oocyte retrieval provides the last opportunity to preserve the genetic material in mares. Pentobarbital (PB) is the most common euthanasia agent; however, its effect on the developmental competence of oocytes has not been determined. Here, we evaluated the concentration of PB in equine follicular fluid (FF) and investigated its effect on the developmental competence of oocytes using a bovine IVF model to overcome the low availability of equine oocytes. The concentration of PB was measured by gas-chromatography/mass-spectrometry in FF collected from mare ovaries immediately after euthanasia (n = 10), 24 h post-euthanasia (n = 10), and from the ovaries collected by ovariectomy (negative control; n = 10). The serum concentration of PB was also evaluated as a positive control. PB was detected in all FF samples with an average concentration of 56.5 μg/ml. Next, bovine cumulus-oocyte complexes (COC) were held in holding media with PB for 6 h at 60 μg/ml (H60, n = 196), 164 μg/ml (H164, n = 215) or without PB (control; n = 212). After holding, the oocytes were matured and fertilized in vitro, followed by in vitro culture to the blastocyst stage. The cumulus expansion grade, cleavage rate, blastocyst rate, embryo kinetic rate and the blastocyst cell numbers were compared among the experimental groups of bovine COC. Higher rates of Grade 1 cumulus expansion were found in controls (54%, 32-76%; median, min-max) in comparison to H60 and H164 (24%,11-33% and 13%, 8-44%; P < 0.001). The cleavage rate was higher in the controls than in H164 (64% vs. 44%; P < 0.01). Blastocyst rates (blastocyst/cleaved oocytes) and total cell number were not different among the groups (control 29%, H60 25%, and H164 24%). In a preliminary study, equine oocytes (n = 28) were exposed to PB in vitro for 6 h followed by intracytoplasmic sperm injection (ICSI) and in vitro embryo production. Exposed oocytes showed a numerically lower maturation rate (43% Vs 52%; P > 0.05) in comparison to the laboratory-established rate during the same timepoints. Overall, we showed that PB reaches the FF immediately after euthanasia, exposing oocytes to this drug. This exposure affected cumulus expansion and cleavage rates in a bovine model, suggesting initial damage caused by PB that may not completely impede the formation of embryos, although lower overall embryo numbers might be obtained.
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49
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Berg AL, Showalter MR, Kosaisawe N, Hu M, Stephens NC, Sa M, Heil H, Castro N, Chen JJ, VanderVorst K, Wheeler MR, Rabow Z, Cajka T, Albeck J, Fiehn O, Carraway KL. Cellular transformation promotes the incorporation of docosahexaenoic acid into the endolysosome-specific lipid bis(monoacylglycerol)phosphate in breast cancer. Cancer Lett 2023; 557:216090. [PMID: 36773796 PMCID: PMC10589064 DOI: 10.1016/j.canlet.2023.216090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 01/26/2023] [Accepted: 02/04/2023] [Indexed: 02/12/2023]
Abstract
Bis(monoacylglycero)phosphates (BMPs), a class of lipids highly enriched within endolysosomal organelles, are key components of the lysosomal intraluminal vesicles responsible for activating sphingolipid catabolic enzymes. While BMPs are understudied relative to other phospholipids, recent reports associate BMP dysregulation with a variety of pathological states including neurodegenerative diseases and lysosomal storage disorders. Since the dramatic lysosomal remodeling characteristic of cellular transformation could impact BMP abundance and function, we employed untargeted lipidomics approaches to identify and quantify BMP species in several in vitro and in vivo models of breast cancer and comparative non-transformed cells and tissues. We observed lower BMP levels within transformed cells relative to normal cells, and consistent enrichment of docosahexaenoic acid (22:6) fatty acyl chain-containing BMP species in both human- and mouse-derived mammary tumorigenesis models. Our functional analysis points to a working model whereby 22:6 BMPs serve as reactive oxygen species scavengers in tumor cells, protecting lysosomes from oxidant-induced lysosomal membrane permeabilization. Our findings suggest that breast tumor cells might divert polyunsaturated fatty acids into BMP lipids as part of an adaptive response to protect their lysosomes from elevated reactive oxygen species levels, and raise the possibility that BMP-mediated lysosomal protection is a tumor-specific vulnerability that may be exploited therapeutically.
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Affiliation(s)
- Anastasia L Berg
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Megan R Showalter
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA
| | - Nont Kosaisawe
- Department of Molecular and Cellular Biology, University of California Davis, Davis, CA, USA
| | - Michelle Hu
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Nathanial C Stephens
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA
| | - Michael Sa
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA
| | - Hailey Heil
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA
| | - Noemi Castro
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Jenny J Chen
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Kacey VanderVorst
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Madelyn R Wheeler
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA
| | - Zachary Rabow
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA
| | - Tomas Cajka
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA; Institute of Physiology of the Czech Academy of Sciences, Prague, 14200, Czech Republic
| | - John Albeck
- Department of Molecular and Cellular Biology, University of California Davis, Davis, CA, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California Davis, Davis, CA, USA
| | - Kermit L Carraway
- Department of Biochemistry and Molecular Medicine and UC Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, USA.
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50
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Buckner T, Johnson RK, Vanderlinden LA, Carry PM, Romero A, Onengut-Gumuscu S, Chen WM, Kim S, Fiehn O, Frohnert BI, Crume T, Perng W, Kechris K, Rewers M, Norris JM. Genome-wide analysis of oxylipins and oxylipin profiles in a pediatric population. Front Nutr 2023; 10:1040993. [PMID: 37057071 PMCID: PMC10086335 DOI: 10.3389/fnut.2023.1040993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 03/14/2023] [Indexed: 03/30/2023] Open
Abstract
Background Oxylipins are inflammatory biomarkers derived from omega-3 and-6 fatty acids implicated in inflammatory diseases but have not been studied in a genome-wide association study (GWAS). The aim of this study was to identify genetic loci associated with oxylipins and oxylipin profiles to identify biologic pathways and therapeutic targets for oxylipins. Methods We conducted a GWAS of plasma oxylipins in 316 participants in the Diabetes Autoimmunity Study in the Young (DAISY). DNA samples were genotyped using the TEDDY-T1D Exome array, and additional variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) multi-ancestry reference panel. Principal components analysis of 36 plasma oxylipins was used to capture oxylipin profiles. PC1 represented linoleic acid (LA)- and alpha-linolenic acid (ALA)-related oxylipins, and PC2 represented arachidonic acid (ARA)-related oxylipins. Oxylipin PC1, PC2, and the top five loading oxylipins from each PC were used as outcomes in the GWAS (genome-wide significance: p < 5×10-8). Results The SNP rs143070873 was associated with (p < 5×10-8) the LA-related oxylipin 9-HODE, and rs6444933 (downstream of CLDN11) was associated with the LA-related oxylipin 13 S-HODE. A locus between MIR1302-7 and LOC100131146, rs10118380 and an intronic variant in TRPM3 were associated with the ARA-related oxylipin 11-HETE. These loci are involved in inflammatory signaling cascades and interact with PLA2, an initial step to oxylipin biosynthesis. Conclusion Genetic loci involved in inflammation and oxylipin metabolism are associated with oxylipin levels.
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Affiliation(s)
- Teresa Buckner
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
- Department of Kinesiology, Nutrition, and Dietetics, University of Northern Colorado, Greeley, CO, United States
| | - Randi K. Johnson
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
- Department of Biomedical Informatics, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Lauren A. Vanderlinden
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Patrick M. Carry
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
- Colorado Program for Musculoskeletal Research, Department of Orthopedics, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Alex Romero
- Department of Biomedical Informatics, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States
| | - Soojeong Kim
- Department of Health Administration, Dongseo University, Busan, Republic of Korea
| | - Oliver Fiehn
- NIH-West Coast Metabolomics Center, University of California-Davis, Davis, CA, United States
| | - Brigitte I. Frohnert
- The Barbara Davis Center for Diabetes, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Tessa Crume
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Wei Perng
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Marian Rewers
- The Barbara Davis Center for Diabetes, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
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