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Aristizabal-Henao JJ, Biltoft-Jensen AP, Christensen T, Stark KD. Lipidomic and Fatty Acid Biomarkers in Whole Blood Can Predict the Dietary Intake of Eicosapentaenoic and Docosahexaenoic Acids in a Danish Population. J Nutr 2024; 154:2108-2119. [PMID: 38710305 PMCID: PMC11282468 DOI: 10.1016/j.tjnut.2024.04.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 04/23/2024] [Accepted: 04/27/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND The intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been associated with health benefits. Blood levels of these fatty acids, measured by gas chromatography (GC), are associated with their dietary intake, but the relationships with lipidomic measurements are not well defined. OBJECTIVES This study aimed to determine the lipidomic biomarkers in whole blood that predict intakes of EPA + DHA and examine the relationship between lipidomic and GC-based n-3 polyunsaturated fatty acid (n-3 PUFA) biomarkers. METHODS Lipidomic and fatty acid analyses were completed on 120 whole blood samples collected from Danish participants. Dietary intakes were completed using a web-based 7-d food diary. Stepwise multiple linear regression was used to identify the fatty acid and lipidomic variables that predict intakes of EPA + DHA and to determine lipidomic species that predict commonly used fatty acid biomarkers. RESULTS Stepwise regression selected lipidomic variables with an R2 = 0.52 for predicting EPA + DHA intake compared to R2 = 0.40 for the selected fatty acid GC-based variables. More predictive models were generated when the lipidomic variables were selected for females only (R2 = 0.62, n = 68) and males only (R2 = 0.72, n = 52). Phosphatidylethanolamine plasmalogen species containing EPA or DHA tended to be the most predictive lipidomic variables. Stepwise regression also indicated that selected lipidomic variables can predict commonly used fatty acid GC-based n-3 PUFA biomarkers as the R2 values ranged from 0.84 to 0.91. CONCLUSIONS Both fatty acid and lipidomic data can be used to predict EPA + DHA intakes, and fatty acid GC-based biomarkers can be emulated by lipidomic species. Lipidomic-based biomarkers appear to be influenced by sex differences, probably in n-3 PUFA and lipoprotein metabolism. These results improve our ability to understand the relationship between novel lipidomic data and GC fatty acid data and will increase our ability to apply lipidomic methods to fatty acid and lipid nutritional research.
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Affiliation(s)
- Juan J Aristizabal-Henao
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada; Platforms and Translational Sciences, BPGbio Inc., Framingham, MA, United States
| | | | - Tue Christensen
- National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Ken D Stark
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.
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Bondareva O, Rodríguez-Aguilera JR, Oliveira F, Liao L, Rose A, Gupta A, Singh K, Geier F, Schuster J, Boeckel JN, Buescher JM, Kohli S, Klöting N, Isermann B, Blüher M, Sheikh BN. Single-cell profiling of vascular endothelial cells reveals progressive organ-specific vulnerabilities during obesity. Nat Metab 2022; 4:1591-1610. [PMID: 36400935 PMCID: PMC9684070 DOI: 10.1038/s42255-022-00674-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 09/30/2022] [Indexed: 11/20/2022]
Abstract
Obesity promotes diverse pathologies, including atherosclerosis and dementia, which frequently involve vascular defects and endothelial cell (EC) dysfunction. Each organ has distinct EC subtypes, but whether ECs are differentially affected by obesity is unknown. Here we use single-cell RNA sequencing to analyze transcriptomes of ~375,000 ECs from seven organs in male mice at progressive stages of obesity to identify organ-specific vulnerabilities. We find that obesity deregulates gene expression networks, including lipid handling, metabolic pathways and AP1 transcription factor and inflammatory signaling, in an organ- and EC-subtype-specific manner. The transcriptomic aberrations worsen with sustained obesity and are only partially mitigated by dietary intervention and weight loss. For example, dietary intervention substantially attenuates dysregulation of liver, but not kidney, EC transcriptomes. Through integration with human genome-wide association study data, we further identify a subset of vascular disease risk genes that are induced by obesity. Our work catalogs the impact of obesity on the endothelium, constitutes a useful resource and reveals leads for investigation as potential therapeutic targets.
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Affiliation(s)
- Olga Bondareva
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Jesús Rafael Rodríguez-Aguilera
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Fabiana Oliveira
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Longsheng Liao
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Alina Rose
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Anubhuti Gupta
- Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Kunal Singh
- Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Florian Geier
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
| | - Jenny Schuster
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
| | - Jes-Niels Boeckel
- Klinik und Poliklinik für Kardiologie, Universitätsklinikum Leipzig, University of Leipzig, Leipzig, Germany
| | - Joerg M Buescher
- Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Germany
| | - Shrey Kohli
- Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Nora Klöting
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Berend Isermann
- Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig, Leipzig, Germany
| | - Bilal N Sheikh
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich, Leipzig, Germany.
- Medical Faculty, University of Leipzig, Leipzig, Germany.
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Ferracane A, Aloisi I, Galletta M, Zoccali M, Tranchida PQ, Micalizzi G, Mondello L. Automated sample preparation and fast GC–MS determination of fatty acids in blood samples and dietary supplements. Anal Bioanal Chem 2022; 414:8423-8435. [DOI: 10.1007/s00216-022-04379-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/30/2022]
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Lippa KA, Aristizabal-Henao JJ, Beger RD, Bowden JA, Broeckling C, Beecher C, Clay Davis W, Dunn WB, Flores R, Goodacre R, Gouveia GJ, Harms AC, Hartung T, Jones CM, Lewis MR, Ntai I, Percy AJ, Raftery D, Schock TB, Sun J, Theodoridis G, Tayyari F, Torta F, Ulmer CZ, Wilson I, Ubhi BK. Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC). Metabolomics 2022; 18:24. [PMID: 35397018 PMCID: PMC8994740 DOI: 10.1007/s11306-021-01848-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/07/2021] [Indexed: 12/17/2022]
Abstract
INTRODUCTION The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research. OBJECTIVES This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data. RESULTS The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities. CONCLUSIONS The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.
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Affiliation(s)
- Katrice A Lippa
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD, 20899, USA
| | - Juan J Aristizabal-Henao
- Department of Physiological Sciences, Center for Environmental and Human Toxicology, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32610, USA
- BERG LLC, 500 Old Connecticut Path, Building B, 3rd Floor, Framingham, MA, 01710, USA
| | - Richard D Beger
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), Jefferson, AR, 72079, USA
| | - John A Bowden
- Department of Physiological Sciences, Center for Environmental and Human Toxicology, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Corey Broeckling
- Analytical Resources Core: Bioanalysis and Omics Center, Colorado State University, Fort Collins, CO, 80523, USA
| | | | - W Clay Davis
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Charleston, SC, 29412, USA
| | - Warwick B Dunn
- School of Biosciences, Institute of Metabolism and Systems Research and Phenome Centre Birmingham, University of Birmingham, Birmingham, B15, 2TT, UK
| | - Roberto Flores
- Division of Program Coordination, Planning and Strategic Initiatives, Office of Nutrition Research, Office of the Director, National Institutes of Health (NIH), Bethesda, MD, 20892, USA
| | - Royston Goodacre
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, BioSciences Building, Crown St., Liverpool, L69 7ZB, UK
| | - Gonçalo J Gouveia
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, 30602, USA
| | - Amy C Harms
- Biomedical Metabolomics Facility Leiden, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Thomas Hartung
- Bloomberg School of Public Health, Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Christina M Jones
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD, 20899, USA
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, London, SW7 2AZ, UK
| | - Ioanna Ntai
- Thermo Fisher Scientific, San Jose, CA, 95134, USA
| | - Andrew J Percy
- Cambridge Isotope Laboratories, Inc., Tewksbury, MA, 01876, USA
| | - Dan Raftery
- Northwest Metabolomics Research Center, University of Washington, Seattle, WA, 98109, USA
| | - Tracey B Schock
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Charleston, SC, 29412, USA
| | - Jinchun Sun
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), Jefferson, AR, 72079, USA
| | | | - Fariba Tayyari
- Department of Internal Medicine, University of Iowa, Iowa City, IA, 52242, USA
| | - Federico Torta
- Centre for Life Sciences, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Candice Z Ulmer
- Centers for Disease Control and Prevention (CDC), Atlanta, GA, 30341, USA
| | - Ian Wilson
- Computational & Systems Medicine, Imperial College, Exhibition Rd, London, SW7 2AZ, UK
| | - Baljit K Ubhi
- MOBILion Systems Inc., 4 Hillman Drive Suite 130, Chadds Ford, PA, 19317, USA.
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Rapid and miniaturized qualitative and quantitative gas chromatography profiling of human blood total fatty acids. Anal Bioanal Chem 2020; 412:2327-2337. [DOI: 10.1007/s00216-020-02424-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 12/13/2019] [Accepted: 01/15/2020] [Indexed: 02/06/2023]
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Total Fatty Acid Analysis of Human Blood Samples in One Minute by High-Resolution Mass Spectrometry. Biomolecules 2018; 9:biom9010007. [PMID: 30591667 PMCID: PMC6359376 DOI: 10.3390/biom9010007] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2018] [Revised: 12/13/2018] [Accepted: 12/17/2018] [Indexed: 12/14/2022] Open
Abstract
Total fatty acid analysis is a routine method in many areas, including lipotyping of individuals in personalized medicine, analysis of foodstuffs, and optimization of oil production in biotechnology. This analysis is commonly done by converting fatty acyl (FA) chains of intact lipids into FA methyl esters (FAMEs) and monitoring these by gas-chromatography (GC)-based methods, typically requiring at least 15 min of analysis per sample. Here, we describe a novel method that supports fast, precise and accurate absolute quantification of total FA levels in human plasma and serum samples. The method uses acid-catalyzed transesterification with 18O-enriched H2O (i.e., H218O) to convert FA chains into 18O-labeled free fatty acids. The resulting “mass-tagged” FA analytes can be specifically monitored with improved signal-to-background by 1 min of high resolution Fourier transform mass spectrometry (FTMS) on an Orbitrap-based mass spectrometer. By benchmarking to National Institute of Standards and Technology (NIST) certified standard reference materials we show that the performance of our method is comparable, and at times superior, to that of gold-standard GC-based methods. In addition, we demonstrate that the method supports the accurate quantification of FA differences in samples obtained in dietary intervention studies and also affords specific monitoring of ingested stable isotope-labeled fatty acids (13C16-palmitate) in normoinsulinemic and hyperinsulinemic human subjects. Overall, our novel high-throughput method is generic and suitable for many application areas, spanning basic research to personalized medicine, and is particularly useful for laboratories equipped with high resolution mass spectrometers, but lacking access to GC-based instrumentation.
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Vuckovic D. Improving metabolome coverage and data quality: advancing metabolomics and lipidomics for biomarker discovery. Chem Commun (Camb) 2018; 54:6728-6749. [PMID: 29888773 DOI: 10.1039/c8cc02592d] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This Feature Article highlights some of the key challenges within the field of metabolomics and examines what role separation and analytical sciences can play to improve the use of metabolomics in biomarker discovery and personalized medicine. Recent progress in four key areas is highlighted: (i) improving metabolite coverage, (ii) developing accurate methods for unstable metabolites including in vivo global metabolomics methods, (iii) advancing inter-laboratory studies and reference materials and (iv) improving data quality, standardization and quality control of metabolomics studies.
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Affiliation(s)
- Dajana Vuckovic
- Department of Chemistry and Biochemistry, Concordia University, 7141 Sherbrooke Street West, Montréal, Québec H4B 1R6, Canada.
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Benner BA, Schantz MM, Powers CD, Schleicher RL, Camara JE, Sharpless KE, Yen JH, Sniegoski LT. Standard Reference Material (SRM) 2378 fatty acids in frozen human serum. Certification of a clinical SRM based on endogenous supplementation of polyunsaturated fatty acids. Anal Bioanal Chem 2018; 410:2321-2329. [PMID: 29435636 PMCID: PMC5851844 DOI: 10.1007/s00216-017-0841-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 12/01/2017] [Accepted: 12/18/2017] [Indexed: 10/18/2022]
Abstract
Dietary fatty acids can be both beneficial and detrimental to human health depending on the degree and type of saturation. Healthcare providers and research scientists monitor the fatty acid content of human plasma and serum as an indicator of health status and diet. In addition, both the Centers for Disease Control & Prevention (CDC) and the National Institutes of Health - Office of Dietary Supplements are interested in circulating fatty acids (FAs) because they may be predictive of coronary heart disease. The National Institute of Standards and Technology (NIST) provides a wide variety of reference materials (RMs) and Standard Reference Materials® (SRM®s) including blood, serum, plasma, and urine with values assigned for analytes of clinical interest. NIST SRM 2378 Fatty Acids in Frozen Human Serum was introduced in 2015 to help validate methods used for the analysis of FAs in serum, and consists of three different pools of serum acquired from (1) healthy donors who had taken fish oil dietary supplements (at least 1000 mg per day) for at least one month (level 1 material), (2) healthy donors who had taken flaxseed oil dietary supplements (at least 1000 mg per day) for at least one month (level 2 material), and (3) healthy donors eating "normal" diets who had not taken dietary supplements containing fish or plant oils (level 3 material). The use of dietary supplements by donors provided SRMs with natural endogenous ranges of FAs at concentrations observed in human populations. Results from analyses using two methods at NIST, including one involving a novel microwave-assisted acid hydrolysis procedure, and one at the CDC are presented here. These results and their respective uncertainties were combined to yield certified values with expanded uncertainties for 12 FAs and reference values with expanded uncertainties for an additional 18 FAs.
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Affiliation(s)
- Bruce A Benner
- Chemical Sciences Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA.
| | - Michele M Schantz
- Chemical Sciences Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA
| | - Carissa D Powers
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy, Atlanta, GA, 30341, USA
| | - Rosemary L Schleicher
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 4770 Buford Hwy, Atlanta, GA, 30341, USA
| | - Johanna E Camara
- Chemical Sciences Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA
| | - Katherine E Sharpless
- Chemical Sciences Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA
| | - James H Yen
- Statistical Engineering Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA
| | - Lorna T Sniegoski
- Chemical Sciences Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA
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