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Masuda R, Wist J, Lodge S, Kimhofer T, Hunter M, Hui J, Beilby JP, Burnett JR, Dwivedi G, Schlaich MP, Bong SH, Loo RL, Holmes E, Nicholson JK, Yeap BB. Plasma lipoprotein subclass variation in middle-aged and older adults: Sex-stratified distributions and associations with health status and cardiometabolic risk factors. J Clin Lipidol 2023; 17:677-687. [PMID: 37442713 DOI: 10.1016/j.jacl.2023.06.004] [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: 09/08/2022] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/15/2023]
Abstract
BACKGROUND Circulating lipids and lipoproteins mediate cardiovascular risk, however routine plasma lipid biochemistry provides limited information on pro-atherogenic remnant particles. OBJECTIVE We analysed plasma lipoprotein subclasses including very low-density and intermediate-density lipoprotein (VLDL and IDL); and assessed their associations with health and cardiometabolic risk. METHODS From 1,976 community-dwelling adults aged 45-67 years, 114/1071 women (10.6%) and 153/905 men (16.9%) were categorised as very healthy. Fasting plasma lipoprotein profiles comprising 112 parameters were measured using 1H nuclear magnetic resonance (NMR) spectroscopy, and associations with health status and cardiometabolic risk factors examined. RESULTS HDL cholesterol was higher, and IDL and VLDL cholesterol and triglycerides lower, in very healthy women compared to other women, and women compared to men. IDL and VLDL cholesterol and triglyceride were lower in very healthy men compared to other men. HDL cholesterol and apolipoprotein (apo) A-I were inversely, and IDL and VLDL cholesterol, apoB-100, and apoB-100/apoA-I ratio directly associated with body mass index (BMI) in women and men. In women, LDL, IDL and VLDL cholesterol increased with age. Women with diabetes and cardiovascular disease had higher cholesterol, triglycerides, phospholipids and free cholesterol across IDL and VLDL fractions, with similar trends for men with diabetes. CONCLUSION Lipoprotein subclasses and density fractions, and their lipid and apolipoprotein constituents, are differentially distributed by sex, health status and BMI. Very healthy women and men are distinguished by favorable lipoprotein profiles, particularly lower concentrations of VLDL and IDL, providing reference intervals for comparison with general populations and adults with cardiometabolic risk factors.
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Affiliation(s)
- Reika Masuda
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia
| | - Julien Wist
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Chemistry Department, Universidad del Valle, 76001, Cali, Colombia
| | - Samantha Lodge
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia
| | - Torben Kimhofer
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia
| | - Michael Hunter
- School of Population and Global Health, University of Western Australia, Perth, WA, 6009, Australia
| | - Jennie Hui
- PathWest Laboratory Medicine, Queen Elizabeth II Medical Centre, Perth, WA, 6009, Australia
| | - John P Beilby
- School of Biomedical Sciences, University of Western Australia, Perth, WA, 6009, Australia
| | - John R Burnett
- Department of Clinical Biochemistry, PathWest Laboratory Medicine, Royal Perth Hospital & Fiona Stanley Hospital Network, Perth, WA, 6000, Australia; Medical School, University of Western Australia, Perth, WA, 6009, Australia
| | - Girish Dwivedi
- Medical School, University of Western Australia, Perth, WA, 6009, Australia; Harry Perkins Institute of Medical Research, Perth, WA, 6150, Australia; Department of Cardiology, Fiona Stanley Hospital, Perth, WA, 6150, Australia
| | - Markus P Schlaich
- Medical School, University of Western Australia, Perth, WA, 6009, Australia; Dobney Hypertension Centre, Royal Perth Hospital Medical Research Foundation, University of Western Australia, Perth, WA, 6000, Australia; Departments of Cardiology and Nephrology, Royal Perth Hospital, Perth, WA, 6000, Australia
| | - Sze-How Bong
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia
| | - Ruey Leng Loo
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia
| | - Elaine Holmes
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, 6150, Australia; Medical School, University of Western Australia, Perth, WA, 6009, Australia; Institute of Global Health Innovation, Imperial College London, London SW7 2AZ, United Kingdom.
| | - Bu B Yeap
- Medical School, University of Western Australia, Perth, WA, 6009, Australia; Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth WA, 6150, Australia.
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Lodge S, Lawler NG, Gray N, Masuda R, Nitschke P, Whiley L, Bong SH, Yeap BB, Dwivedi G, Spraul M, Schaefer H, Gil-Redondo R, Embade N, Millet O, Holmes E, Wist J, Nicholson JK. Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction. Int J Mol Sci 2023; 24:11614. [PMID: 37511373 PMCID: PMC10380980 DOI: 10.3390/ijms241411614] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/10/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.
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Affiliation(s)
- Samantha Lodge
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Nathan G. Lawler
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Nicola Gray
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Reika Masuda
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Philipp Nitschke
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Luke Whiley
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Bu B. Yeap
- Medical School, University of Western Australia, Perth, WA 6150, Australia; (B.B.Y.); (G.D.)
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | - Girish Dwivedi
- Medical School, University of Western Australia, Perth, WA 6150, Australia; (B.B.Y.); (G.D.)
- Department of Cardiology, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | | | | | - Rubén Gil-Redondo
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Nieves Embade
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Elaine Holmes
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK
| | - Julien Wist
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
| | - Jeremy K. Nicholson
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, Faculty Building, South Kensington Campus, London SW7 2NA, UK
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Masuda R, Lodge S, Whiley L, Gray N, Lawler N, Nitschke P, Bong SH, Kimhofer T, Loo RL, Boughton B, Zeng AX, Hall D, Schaefer H, Spraul M, Dwivedi G, Yeap BB, Diercks T, Bernardo-Seisdedos G, Mato JM, Lindon JC, Holmes E, Millet O, Wist J, Nicholson JK. Exploration of Human Serum Lipoprotein Supramolecular Phospholipids Using Statistical Heterospectroscopy in n-Dimensions (SHY- n): Identification of Potential Cardiovascular Risk Biomarkers Related to SARS-CoV-2 Infection. Anal Chem 2022; 94:4426-4436. [PMID: 35230805 DOI: 10.1021/acs.analchem.1c05389] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited 1H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC1, SPC2, and SPC3) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC3/SPC2 ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS).
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Affiliation(s)
- Reika Masuda
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Samantha Lodge
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Luke Whiley
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Nicola Gray
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Nathan Lawler
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Philipp Nitschke
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Sze-How Bong
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Torben Kimhofer
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Ruey Leng Loo
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Berin Boughton
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Annie X Zeng
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Drew Hall
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | | | - Manfred Spraul
- Bruker Biospin GmbH, Silberstreifen, Ettlingen 76275, Germany
| | - Girish Dwivedi
- Department of Cardiology, Fiona Stanley Hospital, Medical School, University of Western Australia, Perth 6150, Western Australia, Australia
| | - Bu B Yeap
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Medical School, University of Western Australia, Perth 6150, Western Australia, Australia
| | - Tammo Diercks
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - Ganeko Bernardo-Seisdedos
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - José M Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - John C Lindon
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - Elaine Holmes
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia.,Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - Julien Wist
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia.,Chemistry Department, Universidad del Valle, 76001 Cali, Colombia
| | - Jeremy K Nicholson
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia.,Department of Cardiology, Fiona Stanley Hospital, Medical School, University of Western Australia, Perth 6150, Western Australia, Australia.,Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K
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Nitschke P, Lodge S, Kimhofer T, Masuda R, Bong SH, Hall D, Schäfer H, Spraul M, Pompe N, Diercks T, Bernardo-Seisdedos G, Mato JM, Millet O, Susic D, Henry A, El-Omar EM, Holmes E, Lindon JC, Nicholson JK, Wist J. J-Edited DIffusional Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum. Anal Chem 2022; 94:1333-1341. [DOI: 10.1021/acs.analchem.1c04576] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Philipp Nitschke
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Torben Kimhofer
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Reika Masuda
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Drew Hall
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Hartmut Schäfer
- Bruker Biospin GmbH, Silberstreifen, 76287, Rheinstetten 76287, Germany
| | - Manfred Spraul
- Bruker Biospin GmbH, Silberstreifen, 76287, Rheinstetten 76287, Germany
| | - Niels Pompe
- Bruker Biospin GmbH, Silberstreifen, 76287, Rheinstetten 76287, Germany
| | - Tammo Diercks
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - Ganeko Bernardo-Seisdedos
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - José M. Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - Daniella Susic
- School of Women’s and Children’s Health, University of New South Wales, Sydney, New South Wales 2052, Australia
- UNSW Microbiome Research Centre, St George Hospital, Kogarah, New South Wales 2217, Australia
| | - Amanda Henry
- School of Women’s and Children’s Health, University of New South Wales, Sydney, New South Wales 2052, Australia
- UNSW Microbiome Research Centre, St George Hospital, Kogarah, New South Wales 2217, Australia
| | - Emad M El-Omar
- Microbiome Research Centre, St George & Sutherland Clinical School, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Elaine Holmes
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - John C. Lindon
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - Jeremy K. Nicholson
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
- Institute of Global Health Innovation Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K
| | - Julien Wist
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
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Lee SH, Yang YR, Cheon HY, Shin NH, Lee JW, Bong SH, Hwangbo S, Kong IK, Shin MK. Effects of hydrogenated fat-spray-coated β-carotene supplement on plasma β-carotene concentration and conception rate after embryo transfer in Hanwoo beef cows. Animal 2021; 15:100407. [PMID: 34839225 DOI: 10.1016/j.animal.2021.100407] [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] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 10/19/2022] Open
Abstract
We hypothesised that hydrogenated fat (HF)-spray-coated β-carotene (βC) supplement could be used to increase plasma βC concentration and conception rates after embryo transfer (ET) in Hanwoo beef cows. In Experiment 1, 12 multiparous Hanwoo cows were fed one of four experimental diets in a triplicate 4 × 4 Latin square design for a 28-day period. Treatments included no βC addition (control), HF-uncoated βC (HFuβC), HF-spray-coated βC (HFβC), and HF-spray-coated βC and vitamin A (HFβCA). The cows under βC-supplemented treatments were fed 400 mg/day of βC, and a daily intake for vitamin A of HFβCA treatment was 30 000 IU/day as retinyl acetate. Blood was collected on days 0, 26, 27, and 28 to analyse βC and other metabolite concentrations. In Experiment 2, 199 Hanwoo cows with low fertility were randomly assigned to either control (n = 99) or HFβC treatments (n = 100) based on the results of Experiment 1. The oestrus of the cows was synchronised for ET. The HFβC group was fed from 4 weeks before to 4 weeks after ET with a daily intake of 400 mg βC. Pregnancy for conception rates was diagnosed on day 60 after ET, and blood was collected for βC concentrations on the day before ET. Supplementing βC resulted in a high plasma βC concentration (P < 0.001). Supplementing HFβC or HFβCA resulted in higher βC concentrations than HFuβC (P < 0.001); however, there was no difference between HFβC and HFβCA groups. Plasma retinol concentration was lower in the HFβCA treatment than in the control and HFβC groups (P < 0.05). Blood metabolites were unaffected by the treatments. The retinol:βC ratio was lower in the βC-supplemented treatments than in the controls, and was lower in HFβC and HFβCA than in HFuβC groups (P < 0.001). Plasma βC concentration was positively correlated with plasma high-density lipoprotein, low-density lipoprotein, and total cholesterol (P < 0.05). Plasma retinol concentration was negatively associated with plasma protein (P < 0.01), but positively associated with plasma creatinine (P < 0.001) and urea (P < 0.01). Supplementing HFβC to low-fertility cows resulted in higher plasma βC concentration (P < 0.001) and conception rates (P = 0.024) than those in the controls. In conclusion, HFβC had a better bioavailability than HFuβC, and an increase in conception rates by supplementing HFβC may be beneficial for producing more calves given the low pregnancy rates of bovine ET in Korea.
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Affiliation(s)
- S H Lee
- Gyeongsangnamdo Provincial Livestock Research Institute, Sancheong 52263, Republic of Korea
| | - Y R Yang
- Gyeongsangnamdo Provincial Livestock Research Institute, Sancheong 52263, Republic of Korea
| | - H Y Cheon
- Gyeongsangnamdo Provincial Livestock Research Institute, Sancheong 52263, Republic of Korea
| | - N H Shin
- Gyeongsangnamdo Provincial Livestock Research Institute, Sancheong 52263, Republic of Korea
| | - J W Lee
- Gyeongsangnamdo Provincial Livestock Research Institute, Sancheong 52263, Republic of Korea
| | - S H Bong
- Nuvo Bio & Technologies Corp., Seoul 01838, Republic of Korea
| | - S Hwangbo
- Department of Animal Science, Gyeongbuk Provincial College, Yecheon 36830, Republic of Korea
| | - I K Kong
- Division of Applied Life Science (BK21 Plus), Gyeongsang National University, Jinju 52828, Republic of Korea
| | - M K Shin
- Department of Microbiology and Convergence Medical Science, College of Medicine, Gyeongsang National University, Jinju 52727, Republic of Korea.
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6
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Masuda R, Lodge S, Nitschke P, Spraul M, Schaefer H, Bong SH, Kimhofer T, Hall D, Loo RL, Bizkarguenaga M, Bruzzone C, Gil-Redondo R, Embade N, Mato JM, Holmes E, Wist J, Millet O, Nicholson JK. Integrative Modeling of Plasma Metabolic and Lipoprotein Biomarkers of SARS-CoV-2 Infection in Spanish and Australian COVID-19 Patient Cohorts. J Proteome Res 2021; 20:4139-4152. [PMID: 34251833 DOI: 10.1021/acs.jproteome.1c00458] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping.
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Affiliation(s)
- Reika Masuda
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Philipp Nitschke
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Manfred Spraul
- Bruker Biospin GmbH, Silberstreifen, Ettlingen 76275, Germany
| | | | - Sze-How Bong
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Torben Kimhofer
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Drew Hall
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Ruey Leng Loo
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Maider Bizkarguenaga
- CIC bioGUNE, Asociación Centro de Investigación Cooperativa en Biociencias, Bizkaia Science and Technology Park, Building 800, 48160 Derio, Bizkaia, Spain
| | - Chiara Bruzzone
- CIC bioGUNE, Asociación Centro de Investigación Cooperativa en Biociencias, Bizkaia Science and Technology Park, Building 800, 48160 Derio, Bizkaia, Spain
| | - Rubén Gil-Redondo
- CIC bioGUNE, Asociación Centro de Investigación Cooperativa en Biociencias, Bizkaia Science and Technology Park, Building 800, 48160 Derio, Bizkaia, Spain
| | - Nieves Embade
- CIC bioGUNE, Asociación Centro de Investigación Cooperativa en Biociencias, Bizkaia Science and Technology Park, Building 800, 48160 Derio, Bizkaia, Spain
| | - José M Mato
- CIC bioGUNE, Asociación Centro de Investigación Cooperativa en Biociencias, Bizkaia Science and Technology Park, Building 800, 48160 Derio, Bizkaia, Spain
| | - Elaine Holmes
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Section for Nutrition Research, Department of Metabolism, Nutrition and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, London SW7 2AZ, U.K
| | - Julien Wist
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Chemistry Department, Universidad del Valle, 76001 Cali, Colombia
| | - Oscar Millet
- CIC bioGUNE, Asociación Centro de Investigación Cooperativa en Biociencias, Bizkaia Science and Technology Park, Building 800, 48160 Derio, Bizkaia, Spain
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia.,Institute of Global Health Innovation, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K
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7
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Holmes E, Wist J, Masuda R, Lodge S, Nitschke P, Kimhofer T, Loo RL, Begum S, Boughton B, Yang R, Morillon AC, Chin ST, Hall D, Ryan M, Bong SH, Gay M, Edgar DW, Lindon JC, Richards T, Yeap BB, Pettersson S, Spraul M, Schaefer H, Lawler NG, Gray N, Whiley L, Nicholson JK. Incomplete Systemic Recovery and Metabolic Phenoreversion in Post-Acute-Phase Nonhospitalized COVID-19 Patients: Implications for Assessment of Post-Acute COVID-19 Syndrome. J Proteome Res 2021; 20:3315-3329. [PMID: 34009992 PMCID: PMC8147448 DOI: 10.1021/acs.jproteome.1c00224] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Indexed: 12/15/2022]
Abstract
We present a multivariate metabotyping approach to assess the functional recovery of nonhospitalized COVID-19 patients and the possible biochemical sequelae of "Post-Acute COVID-19 Syndrome", colloquially known as long-COVID. Blood samples were taken from patients ca. 3 months after acute COVID-19 infection with further assessment of symptoms at 6 months. Some 57% of the patients had one or more persistent symptoms including respiratory-related symptoms like cough, dyspnea, and rhinorrhea or other nonrespiratory symptoms including chronic fatigue, anosmia, myalgia, or joint pain. Plasma samples were quantitatively analyzed for lipoproteins, glycoproteins, amino acids, biogenic amines, and tryptophan pathway intermediates using Nuclear Magnetic Resonance (NMR) spectroscopy and mass spectrometry. Metabolic data for the follow-up patients (n = 27) were compared with controls (n = 41) and hospitalized severe acute respiratory syndrome SARS-CoV-2 positive patients (n = 18, with multiple time-points). Univariate and multivariate statistics revealed variable patterns of functional recovery with many patients exhibiting residual COVID-19 biomarker signatures. Several parameters were persistently perturbed, e.g., elevated taurine (p = 3.6 × 10-3 versus controls) and reduced glutamine/glutamate ratio (p = 6.95 × 10-8 versus controls), indicative of possible liver and muscle damage and a high energy demand linked to more generalized tissue repair or immune function. Some parameters showed near-complete normalization, e.g., the plasma apolipoprotein B100/A1 ratio was similar to that of healthy controls but significantly lower (p = 4.2 × 10-3) than post-acute COVID-19 patients, reflecting partial reversion of the metabolic phenotype (phenoreversion) toward the healthy metabolic state. Plasma neopterin was normalized in all follow-up patients, indicative of a reduction in the adaptive immune activity that has been previously detected in active SARS-CoV-2 infection. Other systemic inflammatory biomarkers such as GlycA and the kynurenine/tryptophan ratio remained elevated in some, but not all, patients. Correlation analysis, principal component analysis (PCA), and orthogonal-partial least-squares discriminant analysis (O-PLS-DA) showed that the follow-up patients were, as a group, metabolically distinct from controls and partially comapped with the acute-phase patients. Significant systematic metabolic differences between asymptomatic and symptomatic follow-up patients were also observed for multiple metabolites. The overall metabolic variance of the symptomatic patients was significantly greater than that of nonsymptomatic patients for multiple parameters (χ2p = 0.014). Thus, asymptomatic follow-up patients including those with post-acute COVID-19 Syndrome displayed a spectrum of multiple persistent biochemical pathophysiology, suggesting that the metabolic phenotyping approach may be deployed for multisystem functional assessment of individual post-acute COVID-19 patients.
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Affiliation(s)
- Elaine Holmes
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
- Department of Metabolism, Digestion, and Reproduction,
Faculty of Medicine, Imperial College London, Sir Alexander
Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Julien Wist
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
- Chemistry Department, Universidad del
Valle, 76001 Cali, Colombia
| | - Reika Masuda
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
| | - Philipp Nitschke
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Torben Kimhofer
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
| | - Ruey Leng Loo
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
| | - Sofina Begum
- Department of Metabolism, Digestion, and Reproduction,
Faculty of Medicine, Imperial College London, Sir Alexander
Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Berin Boughton
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
| | - Rongchang Yang
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Aude-Claire Morillon
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Sung-Tong Chin
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Drew Hall
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Monique Ryan
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
| | - Melvin Gay
- Bruker Pty. Ltd., Preston,
VIC 3072, Australia
| | - Dale W. Edgar
- State Adult Burn Unit, Fiona Stanley
Hospital, Murdoch, WA 6150, Australia
- Burn Injury Research Node, The University
of Notre Dame, Fremantle, WA 6160, Australia
| | - John C. Lindon
- Department of Surgery and Cancer, Faculty of
Medicine, Imperial College London, London SW7 2AZ,
U.K.
| | - Toby Richards
- Department of Surgery, Fiona Stanley Hospital, Medical
School, University of Western Australia,Harry Perkins Building,
Murdoch, Perth, WA 6150, Australia
| | - Bu B. Yeap
- Department of Endocrinology and Diabetes, Fiona
Stanley Hospital, Medical School, University of Western
Australia, Harry Perkins Building, Murdoch, Perth, WA 6150,
Australia
| | - Sven Pettersson
- Singapore National NeuroScience
Centre, Mandalay Road, Singapore 308232,
Singapore
- Lee Kong Chian School of Medicine.
Nanyang Technological University, Mandalay Road, Singapore
308232, Singapore
- Department of Life Science Centre,
Sunway University, Kuala Lumpur 47500,
Malaysia
| | | | | | - Nathan G. Lawler
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
| | - Nicola Gray
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
| | - Luke Whiley
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Perron Institute for Neurological and
Translational Science, Nedlands, WA 6009,
Australia
| | - Jeremy K. Nicholson
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, 5 Robin
Warren Drive, Perth, WA 6150, Australia
- Center for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, 5 Robin Warren Drive,
Perth, WA 6150, Australia
- Institute of Global Health Innovation,
Imperial College London, Level 1, Faculty Building, South
Kensington Campus, London SW7 2AZ, U.K.
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8
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Kimhofer T, Lodge S, Whiley L, Gray N, Loo RL, Lawler NG, Nitschke P, Bong SH, Morrison DL, Begum S, Richards T, Yeap BB, Smith C, Smith KGC, Holmes E, Nicholson JK. Correction to "Integrative Modeling of Quantitative Plasma Lipoprotein, Metabolic, and Amino Acid Data Reveals a Multiorgan Pathological Signature of SARS-CoV-2 Infection". J Proteome Res 2021; 20:3400. [PMID: 33949867 PMCID: PMC8504796 DOI: 10.1021/acs.jproteome.1c00273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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9
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Lodge S, Nitschke P, Kimhofer T, Wist J, Bong SH, Loo RL, Masuda R, Begum S, Richards T, Lindon JC, Bermel W, Reinsperger T, Schaefer H, Spraul M, Holmes E, Nicholson JK. Diffusion and Relaxation Edited Proton NMR Spectroscopy of Plasma Reveals a High-Fidelity Supramolecular Biomarker Signature of SARS-CoV-2 Infection. Anal Chem 2021; 93:3976-3986. [PMID: 33577736 PMCID: PMC7908063 DOI: 10.1021/acs.analchem.0c04952] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 01/28/2021] [Indexed: 12/13/2022]
Abstract
We have applied nuclear magnetic resonance spectroscopy based plasma phenotyping to reveal diagnostic molecular signatures of SARS-CoV-2 infection via combined diffusional and relaxation editing (DIRE). We compared plasma from healthy age-matched controls (n = 26) with SARS-CoV-2 negative non-hospitalized respiratory patients and hospitalized respiratory patients (n = 23 and 11 respectively) with SARS-CoV-2 rRT-PCR positive respiratory patients (n = 17, with longitudinal sampling time-points). DIRE data were modelled using principal component analysis and orthogonal projections to latent structures discriminant analysis (O-PLS-DA), with statistical cross-validation indices indicating excellent model generalization for the classification of SARS-CoV-2 positivity for all comparator groups (area under the receiver operator characteristic curve = 1). DIRE spectra show biomarker signal combinations conferred by differential concentrations of metabolites with selected molecular mobility properties. These comprise the following: (a) composite N-acetyl signals from α-1-acid glycoprotein and other glycoproteins (designated GlycA and GlycB) that were elevated in SARS-CoV-2 positive patients [p = 2.52 × 10-10 (GlycA) and 1.25 × 10-9 (GlycB) vs controls], (b) two diagnostic supramolecular phospholipid composite signals that were identified (SPC-A and SPC-B) from the -+N-(CH3)3 choline headgroups of lysophosphatidylcholines carried on plasma glycoproteins and from phospholipids in high-density lipoprotein subfractions (SPC-A) together with a phospholipid component of low-density lipoprotein (SPC-B). The integrals of the summed SPC signals (SPCtotal) were reduced in SARS-CoV-2 positive patients relative to both controls (p = 1.40 × 10-7) and SARS-CoV-2 negative patients (p = 4.52 × 10-8) but were not significantly different between controls and SARS-CoV-2 negative patients. The identity of the SPC signal components was determined using one and two dimensional diffusional, relaxation, and statistical spectroscopic experiments. The SPCtotal/GlycA ratios were also significantly different for control versus SARS-CoV-2 positive patients (p = 1.23 × 10-10) and for SARS-CoV-2 negatives versus positives (p = 1.60 × 10-9). Thus, plasma SPCtotal and SPCtotal/GlycA are proposed as sensitive molecular markers for SARS-CoV-2 positivity that could effectively augment current COVID-19 diagnostics and may have value in functional assessment of the disease recovery process in patients with long-term symptoms.
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Affiliation(s)
- Samantha Lodge
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
| | - Philipp Nitschke
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
| | - Torben Kimhofer
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
| | - Julien Wist
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
- Chemistry
Department, Universidad del Valle, Cali 76001, Colombia
| | - Sze-How Bong
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
| | - Ruey Leng Loo
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
| | - Reika Masuda
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
| | - Sofina Begum
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
- Department
of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Toby Richards
- Division
of Surgery, Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Harry Perkins Building, Murdoch, Perth WA6150, Australia
| | - John C. Lindon
- Department
of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Wolfgang Bermel
- Bruker
Biospin GmbH, Silberstreifen, Ettlingen 76275, Germany
| | | | | | - Manfred Spraul
- Bruker
Biospin GmbH, Silberstreifen, Ettlingen 76275, Germany
| | - Elaine Holmes
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
- Department
of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Jeremy K. Nicholson
- Australian
National Phenome Center, and Center for Computational and Systems
Medicine, Health Futures Institute, Murdoch
University, Harry Perkins Building, Perth WA6150, Australia
- Division
of Surgery, Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Harry Perkins Building, Murdoch, Perth WA6150, Australia
- Institute
of Global Health Innovation, Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K.
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10
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Lodge S, Nitschke P, Kimhofer T, Coudert JD, Begum S, Bong SH, Richards T, Edgar D, Raby E, Spraul M, Schaefer H, Lindon JC, Loo RL, Holmes E, Nicholson JK. NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines. J Proteome Res 2021; 20:1382-1396. [PMID: 33426894 PMCID: PMC7805607 DOI: 10.1021/acs.jproteome.0c00876] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Indexed: 02/08/2023]
Abstract
To investigate the systemic metabolic effects of SARS-CoV-2 infection, we analyzed 1H NMR spectroscopic data on human blood plasma and co-modeled with multiple plasma cytokines and chemokines (measured in parallel). Thus, 600 MHz 1H solvent-suppressed single-pulse, spin-echo, and 2D J-resolved spectra were collected on plasma recorded from SARS-CoV-2 rRT-PCR-positive patients (n = 15, with multiple sampling timepoints) and age-matched healthy controls (n = 34, confirmed rRT-PCR negative), together with patients with COVID-19/influenza-like clinical symptoms who tested SARS-CoV-2 negative (n = 35). We compared the single-pulse NMR spectral data with in vitro diagnostic research (IVDr) information on quantitative lipoprotein profiles (112 parameters) extracted from the raw 1D NMR data. All NMR methods gave highly significant discrimination of SARS-CoV-2 positive patients from controls and SARS-CoV-2 negative patients with individual NMR methods, giving different diagnostic information windows on disease-induced phenoconversion. Longitudinal trajectory analysis in selected patients indicated that metabolic recovery was incomplete in individuals without detectable virus in the recovery phase. We observed four plasma cytokine clusters that expressed complex differential statistical relationships with multiple lipoproteins and metabolites. These included the following: cluster 1, comprising MIP-1β, SDF-1α, IL-22, and IL-1α, which correlated with multiple increased LDL and VLDL subfractions; cluster 2, including IL-10 and IL-17A, which was only weakly linked to the lipoprotein profile; cluster 3, which included IL-8 and MCP-1 and were inversely correlated with multiple lipoproteins. IL-18, IL-6, and IFN-γ together with IP-10 and RANTES exhibited strong positive correlations with LDL1-4 subfractions and negative correlations with multiple HDL subfractions. Collectively, these data show a distinct pattern indicative of a multilevel cellular immune response to SARS CoV-2 infection interacting with the plasma lipoproteome giving a strong and characteristic immunometabolic phenotype of the disease. We observed that some patients in the respiratory recovery phase and testing virus-free were still metabolically highly abnormal, which indicates a new role for these technologies in assessing full systemic recovery.
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Affiliation(s)
- Samantha Lodge
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, Murdoch, Western
Australia 6150, Australia
| | - Philipp Nitschke
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
| | - Torben Kimhofer
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, Murdoch, Western
Australia 6150, Australia
| | - Jerome D. Coudert
- Centre for Molecular Medicine and Innovative
Therapeutics, Murdoch University, Harry Perkins Building,
Perth, Western Australia 6150, Australia
- Perron Institute for Neurological and
Translational Science, Nedlands, Western Australia 6009,
Australia
- School of Medicine, University of Notre
Dame, Fremantle, Western Australia 6160,
Australia
| | - Sofina Begum
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
- Section of Nutrition Research , Department of Metabolism,
Nutrition and Reproduction, Faculty of Medicine, Sir Alexander Fleming Building,
Imperial College London, London SW7 2AZ,
U.K.
| | - Sze-How Bong
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
| | - Toby Richards
- Division of Surgery, Medical School, Faculty of Health
and Medical Sciences, University of Western Australia, Harry
Perkins Building, Robert Warren Drive, Murdoch, Perth, Western Australia 6150,
Australia
| | - Dale Edgar
- Faculty of Health and Medical Sciences,
University of Western Australia, Harry Perkins Building,
Robert Warren Drive, Murdoch, Perth, Western Australia 6150,
Australia
| | - Edward Raby
- Department of Clinical Microbiology,
PathWest Laboratory Medicine WA, Murdoch, Perth, Western
Australia 6150, Australia
| | | | | | - John C. Lindon
- Division of Systems Medicine, Department of
Metabolism, Nutrition and Reproduction, Faculty of Medicine, Sir Alexander Fleming
Building, Imperial College London, London SW7 2AZ,
U.K.
| | - Ruey Leng Loo
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, Murdoch, Western
Australia 6150, Australia
| | - Elaine Holmes
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, Murdoch, Western
Australia 6150, Australia
- Section of Nutrition Research , Department of Metabolism,
Nutrition and Reproduction, Faculty of Medicine, Sir Alexander Fleming Building,
Imperial College London, London SW7 2AZ,
U.K.
| | - Jeremy K. Nicholson
- Australian National Phenome Centre, Health Futures
Institute, Murdoch University, Harry Perkins Building, Perth,
Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health
Futures Institute, Murdoch University, Murdoch, Western
Australia 6150, Australia
- Division of Surgery, Medical School, Faculty of Health
and Medical Sciences, University of Western Australia, Harry
Perkins Building, Robert Warren Drive, Murdoch, Perth, Western Australia 6150,
Australia
- Institute of Global Health Innovation,
Imperial College London, Level 1, Faculty Building South
Kensington Campus, London SW7 2NA, U.K.
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11
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Lodge S, Nitschke P, Loo RL, Kimhofer T, Bong SH, Richards T, Begum S, Spraul M, Schaefer H, Lindon JC, Holmes E, Nicholson JK. Low Volume in Vitro Diagnostic Proton NMR Spectroscopy of Human Blood Plasma for Lipoprotein and Metabolite Analysis: Application to SARS-CoV-2 Biomarkers. J Proteome Res 2021; 20:1415-1423. [PMID: 33491459 PMCID: PMC7857136 DOI: 10.1021/acs.jproteome.0c00815] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Indexed: 11/29/2022]
Abstract
The utility of low sample volume in vitro diagnostic (IVDr) proton nuclear magnetic resonance (1H NMR) spectroscopic experiments on blood plasma for information recovery from limited availability or high value samples was exemplified using plasma from patients with SARS-CoV-2 infection and normal controls. 1H NMR spectra were obtained using solvent-suppressed 1D, spin-echo (CPMG), and 2-dimensional J-resolved (JRES) spectroscopy using both 3 mm outer diameter SampleJet NMR tubes (100 μL plasma) and 5 mm SampleJet NMR tubes (300 μL plasma) under in vitro diagnostic conditions. We noted near identical diagnostic models in both standard and low volume IVDr lipoprotein analysis (measuring 112 lipoprotein parameters) with a comparison of the two tubes yielding R2 values ranging between 0.82 and 0.99 for the 40 paired lipoprotein parameters samples. Lipoprotein measurements for the 3 mm tubes were achieved without time penalty over the 5 mm tubes as defined by biomarker recovery for SARS-CoV-2. Overall, biomarker pattern recovery for the lipoproteins was extremely similar, but there were some small positive offsets in the linear equations for several variables due to small shimming artifacts, but there was minimal degradation of the biological information. For the standard untargeted 1D, CPMG, and JRES NMR experiments on the same samples, the reduced signal-to-noise was more constraining and required greater scanning times to achieve similar differential diagnostic performance (15 min per sample per experiment for 3 mm 1D and CPMG, compared to 4 min for the 5 mm tubes). We conclude that the 3 mm IVDr method is fit-for-purpose for quantitative lipoprotein measurements, allowing the preparation of smaller volumes for high value or limited volume samples that is common in clinical studies. If there are no analytical time constraints, the lower volume experiments are equally informative for untargeted profiling.
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Affiliation(s)
- Samantha Lodge
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Philipp Nitschke
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Ruey Leng Loo
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Torben Kimhofer
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Sze-How Bong
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Toby Richards
- Division
of Surgery, Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Harry Perkins Building, Robert Warren
Drive, Murdoch, Perth, WA 6150, Australia
| | - Sofina Begum
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Division
of Systems Medicine, Department of Metabolism, Nutrition and Reproduction,
Sir Alexander Fleming Building, Imperial
College London, London SW7 2AZ, U.K.
| | | | | | - John C. Lindon
- Division
of Systems Medicine, Department of Metabolism, Nutrition and Reproduction,
Sir Alexander Fleming Building, Imperial
College London, London SW7 2AZ, U.K.
| | - Elaine Holmes
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Division
of Systems Medicine, Department of Metabolism, Nutrition and Reproduction,
Sir Alexander Fleming Building, Imperial
College London, London SW7 2AZ, U.K.
| | - Jeremy K. Nicholson
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Institute
of Global Health Innovation, Imperial College
London, Level 1, Faculty Building South Kensington Campus, London SW7 2NA, U.K.
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12
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Gray N, Lawler NG, Yang R, Morillon AC, Gay MC, Bong SH, Holmes E, Nicholson JK, Whiley L. A simultaneous exploratory and quantitative amino acid and biogenic amine metabolic profiling platform for rapid disease phenotyping via UPLC-QToF-MS. Talanta 2021; 223:121872. [DOI: 10.1016/j.talanta.2020.121872] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/03/2020] [Accepted: 11/04/2020] [Indexed: 12/26/2022]
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13
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Kimhofer T, Lodge S, Whiley L, Gray N, Loo RL, Lawler NG, Nitschke P, Bong SH, Morrison DL, Begum S, Richards T, Yeap BB, Smith C, Smith KGC, Holmes E, Nicholson JK. Integrative Modeling of Quantitative Plasma Lipoprotein, Metabolic, and Amino Acid Data Reveals a Multiorgan Pathological Signature of SARS-CoV-2 Infection. J Proteome Res 2020; 19:4442-4454. [PMID: 32806897 PMCID: PMC7489050 DOI: 10.1021/acs.jproteome.0c00519] [Citation(s) in RCA: 115] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Indexed: 02/06/2023]
Abstract
The metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on human blood plasma were characterized using multiplatform metabolic phenotyping with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Quantitative measurements of lipoprotein subfractions, α-1-acid glycoprotein, glucose, and biogenic amines were made on samples from symptomatic coronavirus disease 19 (COVID-19) patients who had tested positive for the SARS-CoV-2 virus (n = 17) and from age- and gender-matched controls (n = 25). Data were analyzed using an orthogonal-projections to latent structures (OPLS) method and used to construct an exceptionally strong (AUROC = 1) hybrid NMR-MS model that enabled detailed metabolic discrimination between the groups and their biochemical relationships. Key discriminant metabolites included markers of inflammation including elevated α-1-acid glycoprotein and an increased kynurenine/tryptophan ratio. There was also an abnormal lipoprotein, glucose, and amino acid signature consistent with diabetes and coronary artery disease (low total and HDL Apolipoprotein A1, low HDL triglycerides, high LDL and VLDL triglycerides), plus multiple highly significant amino acid markers of liver dysfunction (including the elevated glutamine/glutamate and Fischer's ratios) that present themselves as part of a distinct SARS-CoV-2 infection pattern. A multivariate training-test set model was validated using independent samples from additional SARS-CoV-2 positive patients and controls. The predictive model showed a sensitivity of 100% for SARS-CoV-2 positivity. The breadth of the disturbed pathways indicates a systemic signature of SARS-CoV-2 positivity that includes elements of liver dysfunction, dyslipidemia, diabetes, and coronary heart disease risk that are consistent with recent reports that COVID-19 is a systemic disease affecting multiple organs and systems. Metabolights study reference: MTBLS2014.
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Affiliation(s)
- Torben Kimhofer
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Luke Whiley
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
- Perron Institute for Neurological and
Translational Science, Nedlands, Western Australia 6009,
Australia
| | - Nicola Gray
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Ruey Leng Loo
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Nathan G. Lawler
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Philipp Nitschke
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - David L. Morrison
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Sofina Begum
- Section for Nutrition Research, Imperial
College London, Sir Alexander Fleming Building, South Kensington, London
SW7 2AZ, U.K.
| | - Toby Richards
- Medical School, Faculty of Health and Medical
Sciences, University of Western Australia, and Department of Endocrinology and Diabetes,
Fiona Stanley Hospital, Harry Perkins Building, Murdoch,
Perth, Western Australia 6150, Australia
| | - Bu B. Yeap
- Medical School, Faculty of Health and Medical
Sciences, University of Western Australia, and Department of Endocrinology and Diabetes,
Fiona Stanley Hospital, Harry Perkins Building, Murdoch,
Perth, Western Australia 6150, Australia
| | - Chris Smith
- The Cambridge Institute of Therapeutic Immunology and
Infectious Disease, Department of Medicine, University of Cambridge,
Addenbrooke’s Hospital, Cambridge CB2 0QQ,
U.K.
| | - Kenneth G. C. Smith
- The Cambridge Institute of Therapeutic Immunology and
Infectious Disease, Department of Medicine, University of Cambridge,
Addenbrooke’s Hospital, Cambridge CB2 0QQ,
U.K.
| | - Elaine Holmes
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
- Section for Nutrition Research, Imperial
College London, Sir Alexander Fleming Building, South Kensington, London
SW7 2AZ, U.K.
| | - Jeremy K. Nicholson
- Australian National Phenome Centre, Computational and
Systems Medicine, Health Futures Institute, Murdoch University,
Harry Perkins Building, Perth, Western Australia 6150, Australia
- Medical School, Faculty of Health and Medical
Sciences, University of Western Australia, and Department of Endocrinology and Diabetes,
Fiona Stanley Hospital, Harry Perkins Building, Murdoch,
Perth, Western Australia 6150, Australia
- Institute of Global Health Innovation, Imperial
College London, Level 1, Faculty Building South Kensington Campus, London
SW7 2AZ, U.K.
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14
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Loo RL, Lodge S, Kimhofer T, Bong SH, Begum S, Whiley L, Gray N, Lindon JC, Nitschke P, Lawler NG, Schäfer H, Spraul M, Richards T, Nicholson JK, Holmes E. Quantitative In-Vitro Diagnostic NMR Spectroscopy for Lipoprotein and Metabolite Measurements in Plasma and Serum: Recommendations for Analytical Artifact Minimization with Special Reference to COVID-19/SARS-CoV-2 Samples. J Proteome Res 2020; 19:4428-4441. [PMID: 32852212 PMCID: PMC7640974 DOI: 10.1021/acs.jproteome.0c00537] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Indexed: 12/14/2022]
Abstract
Quantitative nuclear magnetic resonance (NMR) spectroscopy of blood plasma is widely used to investigate perturbed metabolic processes in human diseases. The reliability of biochemical data derived from these measurements is dependent on the quality of the sample collection and exact preparation and analysis protocols. Here, we describe systematically, the impact of variations in sample collection and preparation on information recovery from quantitative proton (1H) NMR spectroscopy of human blood plasma and serum. The effects of variation of blood collection tube sizes and preservatives, successive freeze-thaw cycles, sample storage at -80 °C, and short-term storage at 4 and 20 °C on the quantitative lipoprotein and metabolite patterns were investigated. Storage of plasma samples at 4 °C for up to 48 h, freezing at -80 °C and blood sample collection tube choice have few and minor effects on quantitative lipoprotein profiles, and even storage at 4 °C for up to 168 h caused little information loss. In contrast, the impact of heat-treatment (56 °C for 30 min), which has been used for inactivation of SARS-CoV-2 and other viruses, that may be required prior to analytical measurements in low level biosecurity facilities induced marked changes in both lipoprotein and low molecular weight metabolite profiles. It was conclusively demonstrated that this heat inactivation procedure degrades lipoproteins and changes metabolic information in complex ways. Plasma from control individuals and SARS-CoV-2 infected patients are differentially altered resulting in the creation of artifactual pseudo-biomarkers and destruction of real biomarkers to the extent that data from heat-treated samples are largely uninterpretable. We also present several simple blood sample handling recommendations for optimal NMR-based biomarker discovery investigations in SARS CoV-2 studies and general clinical biomarker research.
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Affiliation(s)
- Ruey Leng Loo
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
| | - Samantha Lodge
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
| | - Torben Kimhofer
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
| | - Sze-How Bong
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Sofina Begum
- Section
for Nutrition Research, Imperial College
London, Sir Alexander Fleming Building, South Kensington, London SW72AZ, U.K.
| | - Luke Whiley
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
- Perron
Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia
| | - Nicola Gray
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
| | - John C. Lindon
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
- Department
of Metabolism, Nutrition and Reproduction, Imperial College London, Sir Alexander Fleming Building, London SW72AZ, U.K.
| | - Philipp Nitschke
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
| | - Nathan G. Lawler
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
| | | | - Manfred Spraul
- Biospin
GmbH, Silberstreifen, 76287 Rheinstetten, Germany
| | - Toby Richards
- Division
of Surgery, Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Harry Perkins Building, Robert Warren Drive, Murdoch, Perth, WA 6150, Australia
- Department
of Endocrinology and Diabetes, Fiona Stanley
Hospital, Harry Perkins
Building, Murdoch, Perth, WA 6150, Australia
| | - Jeremy K. Nicholson
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
- Division
of Surgery, Medical School, Faculty of Health and Medical Sciences, University of Western Australia, Harry Perkins Building, Robert Warren Drive, Murdoch, Perth, WA 6150, Australia
- Institute
of Global Health Innovation, Imperial College
London, Level 1, Faculty Building, South Kensington Campus, London SW72NA, U.K.
| | - Elaine Holmes
- Australian
National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch, Perth, WA 6150, Australia
- Section
for Nutrition Research, Imperial College
London, Sir Alexander Fleming Building, South Kensington, London SW72AZ, U.K.
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