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Masuoka S, Nishio J, Yamada S, Saito K, Kaneko K, Kaburaki M, Tanaka N, Sato H, Muraoka S, Kawazoe M, Mizutani S, Furukawa K, Ishii-Watabe A, Kawai S, Saito Y, Nanki T. Relationship Between the Lipidome Profile and Disease Activity in Patients with Rheumatoid Arthritis. Inflammation 2024:10.1007/s10753-024-01986-8. [PMID: 38401020 DOI: 10.1007/s10753-024-01986-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/08/2024] [Accepted: 02/07/2024] [Indexed: 02/26/2024]
Abstract
Lipid mediators have been suggested to play important roles in the pathogenesis of rheumatoid arthritis (RA). Lipidomics has recently allowed for the comprehensive analysis of lipids and has revealed the potential of lipids as biomarkers for the early diagnosis of RA and prediction of therapeutic responses. However, the relationship between disease activity and the lipid profile in RA remains unclear. In the present study, we performed a plasma lipidomic analysis of 278 patients with RA during treatment and examined relationships with disease activity using the Disease Activity Score in 28 joints (DAS28)-erythrocyte sedimentation rate (ESR). In all patients, five lipids positively correlated and seven lipids negatively correlated with DAS28-ESR. Stearic acid [FA(18:0)] (r = -0.45) and palmitic acid [FA(16:0)] (r = -0.38) showed strong negative correlations. After adjustments for age, body mass index (BMI), and medications, stearic acid, palmitic acid, bilirubin, and lysophosphatidylcholines negatively correlated with disease activity. Stearic acid inhibited osteoclast differentiation from peripheral blood monocytes in in vitro experiments, suggesting its contribution to RA disease activity by affecting bone metabolism. These results indicate that the lipid profile correlates with the disease activity of RA and also that some lipids may be involved in the pathogenesis of RA.
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Affiliation(s)
- Shotaro Masuoka
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Junko Nishio
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
- Department of Immunopathology and Immunoregulation, Toho University School of Medicine, Tokyo, Japan
| | - Soichi Yamada
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Kosuke Saito
- Division of Medicinal Safety Science, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan
| | - Kaichi Kaneko
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Makoto Kaburaki
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Nahoko Tanaka
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Hiroshi Sato
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Sei Muraoka
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Mai Kawazoe
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Satoshi Mizutani
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Karin Furukawa
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
| | - Akiko Ishii-Watabe
- Division of Biological Chemistry and Biologicals, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan
| | - Shinichi Kawai
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan
- Department of Inflammation and Pain Control Research, Toho University School of Medicine, Tokyo, Japan
| | - Yoshiro Saito
- Division of Medicinal Safety Science, National Institute of Health Sciences, Kawasaki, Kanagawa, Japan
| | - Toshihiro Nanki
- Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan.
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Guo K, Savelieff MG, Rumora AE, Alakwaa FM, Callaghan BC, Hur J, Feldman EL. Plasma Metabolomics and Lipidomics Differentiate Obese Individuals by Peripheral Neuropathy Status. J Clin Endocrinol Metab 2022; 107:1091-1109. [PMID: 34878536 PMCID: PMC8947234 DOI: 10.1210/clinem/dgab844] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Indexed: 12/19/2022]
Abstract
CONTEXT Peripheral neuropathy (PN) is a frequent prediabetes and type 2 diabetes (T2D) complication. Multiple clinical studies reveal that obesity and dyslipidemia can also drive PN progression, independent of glycemia, suggesting a complex interplay of specific metabolite and/or lipid species may underlie PN. OBJECTIVE This work aimed to identify the plasma metabolomics and lipidomics signature that underlies PN in an observational study of a sample of individuals with average class 3 obesity. METHODS We performed plasma global metabolomics and targeted lipidomics on obese participants with (n = 44) and without PN (n = 44), matched for glycemic status, vs lean nonneuropathic controls (n = 43). We analyzed data by Wilcoxon, logistic regression, partial least squares-discriminant analysis, and group-lasso to identify differential metabolites and lipids by obesity and PN status. We also conducted subanalysis by prediabetes and T2D status. RESULTS Lean vs obese comparisons, regardless of PN status, identified the most significant differences in gamma-glutamyl and branched-chain amino acid metabolism from metabolomics analysis and triacylglycerols from lipidomics. Stratification by PN status within obese individuals identified differences in polyamine, purine biosynthesis, and benzoate metabolism. Lipidomics found diacylglycerols as the most significant subpathway distinguishing obese individuals by PN status, with additional contributions from phosphatidylcholines, sphingomyelins, ceramides, and dihydroceramides. Stratifying the obese group by glycemic status did not affect discrimination by PN status. CONCLUSION Obesity may be as strong a PN driver as prediabetes or T2D in a sample of individuals with average class 3 obesity, at least by plasma metabolomics and lipidomics profile. Metabolic and complex lipid pathways can differentiate obese individuals with and without PN, independent of glycemic status.
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Affiliation(s)
- Kai Guo
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, Michigan, USA
| | - Masha G Savelieff
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, Michigan, USA
| | - Amy E Rumora
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, Michigan, USA
| | - Fadhl M Alakwaa
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, Michigan, USA
| | - Brian C Callaghan
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, Michigan, USA
| | - Junguk Hur
- Department of Biomedical Sciences, University of North Dakota, Grand Forks, North Dakota, USA
| | - Eva L Feldman
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
- NeuroNetwork for Emerging Therapies, University of Michigan, Ann Arbor, Michigan, USA
- Correspondence: Eva L. Feldman, MD, PhD, Department of Neurology, University of Michigan 5017 AAT-BSRB, 109 Zina Pitcher Pl, Ann Arbor, MI 48109-0588, USA.
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Tan SH, Koh HWL, Chua JY, Burla B, Ong CC, Teo LSL, Yang X, Benke PI, Choi H, Torta F, Richards AM, Wenk MR, Chan MY. Variability of the Plasma Lipidome and Subclinical Coronary Atherosclerosis. Arterioscler Thromb Vasc Biol 2021; 42:100-112. [PMID: 34809445 PMCID: PMC8691371 DOI: 10.1161/atvbaha.121.316847] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Supplemental Digital Content is available in the text. Objective: While the risk of acute coronary events has been associated with biological variability of circulating cholesterol, the association with variability of other atherogenic lipids remains less understood. We evaluated the longitudinal variability of 284 lipids and investigated their association with asymptomatic coronary atherosclerosis. Approach and Results: Circulating lipids were extracted from fasting blood samples of 83 community-sampled symptom-free participants (age 41–75 years), collected longitudinally over 6 months. Three types of coronary plaque volume (calcified, lipid-rich, and fibrotic) were quantified using computed tomography coronary angiogram. We first deconvoluted between-subject (CVg) and within-subject (CVw) lipid variabilities. We then tested whether the mean lipid abundance was different across groups categorized by Framingham risk score and plaques phenotypes (lipid-rich, fibrotic, and calcified). Finally, we investigated whether visit-to-visit variability of each lipid was associated with plaque burden. Most lipids (72.5%) exhibited higher CVg than CVw. Among the lipids (n=145) with 1.2-fold higher CVg than CVw, 26 species including glycerides and ceramides were significantly associated with Framingham risk score and the 3 plaque phenotypes (false discovery rate <0.05). In an exploratory analysis of person-specific visit-to-visit variability without multiple testing correction, high variability of 3 lysophospholipids (lysophosphatidylethanolamines 16:0, 18:0, and lysophosphatidylcholine O-18:1) was associated with lipid-rich and fibrotic (noncalcified) plaque volume while high variability of diacylglycerol 18:1_20:0, triacylglycerols 52:2, 52:3, and 52:4, ceramide d18:0/20:0, dihexosylceramide d18:1/16:0, and sphingomyelin 36:3 was associated with calcified plaque volume. Conclusions: High person-specific longitudinal variation of specific nonsterol lipids is associated with the burden of subclinical coronary atherosclerosis. Larger studies are needed to confirm these exploratory findings.
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Affiliation(s)
- Sock Hwee Tan
- Cardiovascular Research Institute (S.H.T., H.W.L.K., X.Y., H.C., A.M.R., M.Y.C.), Singapore Lipidomics Incubator (SLING), National University of Singapore.,National University Heart Center, Singapore (S.H.T., J.Y.C., A.M.R., M.Y.C.)
| | - Hiromi W L Koh
- Cardiovascular Research Institute (S.H.T., H.W.L.K., X.Y., H.C., A.M.R., M.Y.C.), Singapore Lipidomics Incubator (SLING), National University of Singapore
| | - Jing Yi Chua
- National University Heart Center, Singapore (S.H.T., J.Y.C., A.M.R., M.Y.C.)
| | - Bo Burla
- Life Sciences Institute (B.B., P.I.B., F.T., M.R.W.), National University of Singapore
| | - Ching Ching Ong
- Department of Diagnostic Imaging, National University Hospital, Singapore (C.C.O., L.S.L.T.)
| | - Li San Lynette Teo
- Department of Diagnostic Imaging, National University Hospital, Singapore (C.C.O., L.S.L.T.)
| | - Xiaoxun Yang
- Cardiovascular Research Institute (S.H.T., H.W.L.K., X.Y., H.C., A.M.R., M.Y.C.), Singapore Lipidomics Incubator (SLING), National University of Singapore
| | - Peter I Benke
- Life Sciences Institute (B.B., P.I.B., F.T., M.R.W.), National University of Singapore
| | - Hyungwon Choi
- Cardiovascular Research Institute (S.H.T., H.W.L.K., X.Y., H.C., A.M.R., M.Y.C.), Singapore Lipidomics Incubator (SLING), National University of Singapore
| | - Federico Torta
- Department of Biochemistry and Precision Medicine Translational Research Programme (F.T., M.R.W.), Singapore Lipidomics Incubator (SLING), National University of Singapore.,Life Sciences Institute (B.B., P.I.B., F.T., M.R.W.), National University of Singapore
| | - A Mark Richards
- Cardiovascular Research Institute (S.H.T., H.W.L.K., X.Y., H.C., A.M.R., M.Y.C.), Singapore Lipidomics Incubator (SLING), National University of Singapore.,National University Heart Center, Singapore (S.H.T., J.Y.C., A.M.R., M.Y.C.).,Christchurch Heart Institute, University of Otago Christchurch, Christchurch Hospital (A.M.R.)
| | - Markus R Wenk
- Department of Biochemistry and Precision Medicine Translational Research Programme (F.T., M.R.W.), Singapore Lipidomics Incubator (SLING), National University of Singapore.,Life Sciences Institute (B.B., P.I.B., F.T., M.R.W.), National University of Singapore
| | - Mark Y Chan
- Cardiovascular Research Institute (S.H.T., H.W.L.K., X.Y., H.C., A.M.R., M.Y.C.), Singapore Lipidomics Incubator (SLING), National University of Singapore.,National University Heart Center, Singapore (S.H.T., J.Y.C., A.M.R., M.Y.C.)
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Carrard J, Gallart-Ayala H, Infanger D, Teav T, Wagner J, Knaier R, Colledge F, Streese L, Königstein K, Hinrichs T, Hanssen H, Ivanisevic J, Schmidt-Trucksäss A. Metabolic View on Human Healthspan: A Lipidome-Wide Association Study. Metabolites 2021; 11:metabo11050287. [PMID: 33946321 PMCID: PMC8146132 DOI: 10.3390/metabo11050287] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 04/23/2021] [Accepted: 04/28/2021] [Indexed: 12/22/2022] Open
Abstract
As ageing is a major risk factor for the development of non-communicable diseases, extending healthspan has become a medical and societal necessity. Precise lipid phenotyping that captures metabolic individuality could support healthspan extension strategies. This study applied ‘omic-scale lipid profiling to characterise sex-specific age-related differences in the serum lipidome composition of healthy humans. A subset of the COmPLETE-Health study, composed of 73 young (25.2 ± 2.6 years, 43% female) and 77 aged (73.5 ± 2.3 years, 48% female) clinically healthy individuals, was investigated, using an untargeted liquid chromatography high-resolution mass spectrometry approach. Compared to their younger counterparts, aged females and males exhibited significant higher levels in 138 and 107 lipid species representing 15 and 13 distinct subclasses, respectively. Percentage of difference ranged from 5.8% to 61.7% (females) and from 5.3% to 46.0% (males), with sphingolipid and glycerophophospholipid species displaying the greatest amplitudes. Remarkably, specific sphingolipid and glycerophospholipid species, previously described as cardiometabolically favourable, were found elevated in aged individuals. Furthermore, specific ether-glycerophospholipid and lyso-glycerophosphocholine species displayed higher levels in aged females only, revealing a more favourable lipidome evolution in females. Altogether, age determined the circulating lipidome composition, while lipid species analysis revealed additional findings that were not observed at the subclass level.
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Affiliation(s)
- Justin Carrard
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Hector Gallart-Ayala
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, CH-1005 Lausanne, Switzerland; (H.G.-A.); (T.T.)
| | - Denis Infanger
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Tony Teav
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, CH-1005 Lausanne, Switzerland; (H.G.-A.); (T.T.)
| | - Jonathan Wagner
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Raphael Knaier
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Flora Colledge
- Division of Sports Science, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland;
| | - Lukas Streese
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Karsten Königstein
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Timo Hinrichs
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Henner Hanssen
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Julijana Ivanisevic
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, CH-1005 Lausanne, Switzerland; (H.G.-A.); (T.T.)
- Correspondence: (J.I.); (A.S.-T.)
| | - Arno Schmidt-Trucksäss
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
- Correspondence: (J.I.); (A.S.-T.)
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Beyene HB, Olshansky G, T. Smith AA, Giles C, Huynh K, Cinel M, Mellett NA, Cadby G, Hung J, Hui J, Beilby J, Watts GF, Shaw JS, Moses EK, Magliano DJ, Meikle PJ. High-coverage plasma lipidomics reveals novel sex-specific lipidomic fingerprints of age and BMI: Evidence from two large population cohort studies. PLoS Biol 2020; 18:e3000870. [PMID: 32986697 PMCID: PMC7544135 DOI: 10.1371/journal.pbio.3000870] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 10/08/2020] [Accepted: 09/01/2020] [Indexed: 12/11/2022] Open
Abstract
Obesity and related metabolic diseases show clear sex-related differences. The growing burden of these diseases calls for better understanding of the age- and sex-related metabolic consequences. High-throughput lipidomic analyses of population-based cohorts offer an opportunity to identify disease-risk-associated biomarkers and to improve our understanding of lipid metabolism and biology at a population level. Here, we comprehensively examined the relationship between lipid classes/subclasses and molecular species with age, sex, and body mass index (BMI). Furthermore, we evaluated sex specificity in the association of the plasma lipidome with age and BMI. Some 747 targeted lipid measures, representing 706 molecular lipid species across 36 classes/subclasses, were measured using a high-performance liquid chromatography coupled mass spectrometer on a total of 10,339 participants from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), with 563 lipid species being validated externally on 4,207 participants of the Busselton Health Study (BHS). Heat maps were constructed to visualise the relative differences in lipidomic profile between men and women. Multivariable linear regression analyses, including sex-interaction terms, were performed to assess the associations of lipid species with cardiometabolic phenotypes. Associations with age and sex were found for 472 (66.9%) and 583 (82.6%) lipid species, respectively. We further demonstrated that age-associated lipidomic fingerprints differed by sex. Specific classes of ether-phospholipids and lysophospholipids (calculated as the sum composition of the species within the class) were inversely associated with age in men only. In analyses with women alone, higher triacylglycerol and lower lysoalkylphosphatidylcholine species were observed among postmenopausal women compared with premenopausal women. We also identified sex-specific associations of lipid species with obesity. Lysophospholipids were negatively associated with BMI in both sexes (with a larger effect size in men), whilst acylcarnitine species showed opposing associations based on sex (positive association in women and negative association in men). Finally, by utilising specific lipid ratios as a proxy for enzymatic activity, we identified stearoyl CoA desaturase (SCD-1), fatty acid desaturase 3 (FADS3), and plasmanylethanolamine Δ1-desaturase activities, as well as the sphingolipid metabolic pathway, as constituent perturbations of cardiometabolic phenotypes. Our analyses elucidate the effect of age and sex on lipid metabolism by offering a comprehensive view of the lipidomic profiles associated with common cardiometabolic risk factors. These findings have implications for age- and sex-dependent lipid metabolism in health and disease and suggest the need for sex stratification during lipid biomarker discovery, establishing biological reference intervals for assessment of disease risk.
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Affiliation(s)
- Habtamu B. Beyene
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
| | | | | | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Kevin Huynh
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Michelle Cinel
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | | | - Gemma Cadby
- School of Population and Global Health, University of Western Australia, Perth, Australia
| | - Joseph Hung
- Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia
| | - Jennie Hui
- School of Population and Global Health, University of Western Australia, Perth, Australia
- PathWest Laboratory Medicine of Western Australia, Nedlands, Western Australia
| | - John Beilby
- PathWest Laboratory Medicine of Western Australia, Nedlands, Western Australia
| | - Gerald F. Watts
- Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia
- Lipid Disorders Clinic, Department of Cardiology, Royal Perth Hospital, Perth, Australia
| | | | - Eric K. Moses
- Menzies Institute for Medical Research, University of Tasmania, Tasmania, Australia
| | - Dianna J. Magliano
- Baker Heart and Diabetes Institute, Melbourne, Australia
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Peter J. Meikle
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
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6
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Balgoma D, Zelleroth S, Grönbladh A, Hallberg M, Pettersson C, Hedeland M. Anabolic androgenic steroids exert a selective remodeling of the plasma lipidome that mirrors the decrease of the de novo lipogenesis in the liver. Metabolomics 2020; 16:12. [PMID: 31925559 PMCID: PMC6954146 DOI: 10.1007/s11306-019-1632-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 12/31/2019] [Indexed: 01/01/2023]
Abstract
INTRODUCTION The abuse of anabolic androgenic steroids (AASs) is a source of public concern because of their adverse effects. Supratherapeutic doses of AASs are known to be hepatotoxic and regulate the lipoproteins in plasma by modifying the metabolism of lipids in the liver, which is associated with metabolic diseases. However, the effect of AASs on the profile of lipids in plasma is unknown. OBJECTIVES To describe the changes in the plasma lipidome exerted by AASs and to discuss these changes in the light of previous research about AASs and de novo lipogenesis in the liver. METHODS We treated male Wistar rats with supratherapeutic doses of nandrolone decanoate and testosterone undecanoate. Subsequently, we isolated the blood plasma and performed lipidomics analysis by liquid chromatography-high resolution mass spectrometry. RESULTS Lipid profiling revealed a decrease of sphingolipids and glycerolipids with palmitic, palmitoleic, stearic, and oleic acids. In addition, lipid profiling revealed an increase in free fatty acids and glycerophospholipids with odd-numbered chain fatty acids and/or arachidonic acid. CONCLUSION The lipid profile presented herein reports the imprint of AASs on the plasma lipidome, which mirrors the downregulation of de novo lipogenesis in the liver. In a broader perspective, this profile will help to understand the influence of androgens on the lipid metabolism in future studies of diseases with dysregulated lipogenesis (e.g. type 2 diabetes, fatty liver disease, and hepatocellular carcinoma).
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Affiliation(s)
- David Balgoma
- Analytical Pharmaceutical Chemistry, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden.
- Uppsala Biomedicinska Centrum BMC, Husargatan 3, Box 574, 751 23, Uppsala, Sweden.
| | - Sofia Zelleroth
- The Beijer Laboratory, Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Alfhild Grönbladh
- The Beijer Laboratory, Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Mathias Hallberg
- The Beijer Laboratory, Biological Research on Drug Dependence, Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Curt Pettersson
- Analytical Pharmaceutical Chemistry, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - Mikael Hedeland
- Analytical Pharmaceutical Chemistry, Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
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7
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Burla B, Arita M, Arita M, Bendt AK, Cazenave-Gassiot A, Dennis EA, Ekroos K, Han X, Ikeda K, Liebisch G, Lin MK, Loh TP, Meikle PJ, Orešič M, Quehenberger O, Shevchenko A, Torta F, Wakelam MJO, Wheelock CE, Wenk MR. MS-based lipidomics of human blood plasma: a community-initiated position paper to develop accepted guidelines. J Lipid Res 2018; 59:2001-2017. [PMID: 30115755 PMCID: PMC6168311 DOI: 10.1194/jlr.s087163] [Citation(s) in RCA: 197] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Revised: 08/11/2018] [Indexed: 12/19/2022] Open
Abstract
Human blood is a self-regenerating lipid-rich biological fluid that is routinely collected in hospital settings. The inventory of lipid molecules found in blood plasma (plasma lipidome) offers insights into individual metabolism and physiology in health and disease. Disturbances in the plasma lipidome also occur in conditions that are not directly linked to lipid metabolism; therefore, plasma lipidomics based on MS is an emerging tool in an array of clinical diagnostics and disease management. However, challenges exist in the translation of such lipidomic data to clinical applications. These relate to the reproducibility, accuracy, and precision of lipid quantitation, study design, sample handling, and data sharing. This position paper emerged from a workshop that initiated a community-led process to elaborate and define a set of generally accepted guidelines for quantitative MS-based lipidomics of blood plasma or serum, with harmonization of data acquired on different instrumentation platforms across independent laboratories as an ultimate goal. We hope that other fields may benefit from and follow such a precedent.
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Affiliation(s)
- Bo Burla
- Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore
| | - Makoto Arita
- Laboratory for Metabolomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Cellular and Molecular Epigenetics Laboratory, Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan
- Division of Physiological Chemistry and Metabolism, Keio University Faculty of Pharmacy, Tokyo, Japan
| | - Masanori Arita
- National Institute of Genetics, Shizuoka, Japan and RIKEN Center for Sustainable Resource Science, Yokohama, Japan
| | - Anne K Bendt
- Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore
| | - Amaury Cazenave-Gassiot
- Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore
| | - Edward A Dennis
- Departments of Pharmacology and Chemistry and Biochemistry, School of Medicine, University of California at San Diego, La Jolla, CA
| | - Kim Ekroos
- Lipidomics Consulting Ltd., Esbo, Finland
| | - Xianlin Han
- Barshop Institute for Longevity and Aging Studies and Department of Medicine-Diabetes, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Kazutaka Ikeda
- Laboratory for Metabolomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Cellular and Molecular Epigenetics Laboratory, Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan
| | - Gerhard Liebisch
- Institute of Clinical Chemistry and Laboratory Medicine, University of Regensburg, Regensburg, Germany
| | - Michelle K Lin
- Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore
| | - Tze Ping Loh
- Department of Laboratory Medicine, National University Hospital, Singapore
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Matej Orešič
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland and School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Oswald Quehenberger
- Departments of Pharmacology and Medicine, School of Medicine, University of California at San Diego, La Jolla, CA
| | - Andrej Shevchenko
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Federico Torta
- Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore
| | | | - Craig E Wheelock
- Division of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden
| | - Markus R Wenk
- Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore
- Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore
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