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Robinson AE, Binek A, Ramani K, Sundararaman N, Barbier-Torres L, Murray B, Venkatraman V, Kreimer S, Ardle AM, Noureddin M, Fernández-Ramos D, Lopitz-Otsoa F, Gutiérrez de Juan V, Millet O, Mato JM, Lu SC, Van Eyk JE. Hyperphosphorylation of hepatic proteome characterizes nonalcoholic fatty liver disease in S-adenosylmethionine deficiency. iScience 2023; 26:105987. [PMID: 36756374 PMCID: PMC9900401 DOI: 10.1016/j.isci.2023.105987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/15/2022] [Accepted: 01/11/2023] [Indexed: 01/15/2023] Open
Abstract
Methionine adenosyltransferase 1a (MAT1A) is responsible for hepatic S-adenosyl-L-methionine (SAMe) biosynthesis. Mat1a -/- mice have hepatic SAMe depletion, develop nonalcoholic steatohepatitis (NASH) which is reversed with SAMe administration. We examined temporal alterations in the proteome/phosphoproteome in pre-disease and NASH Mat1a -/- mice, effects of SAMe administration, and compared to human nonalcoholic fatty liver disease (NAFLD). Mitochondrial and peroxisomal lipid metabolism proteins were altered in pre-disease mice and persisted in NASH Mat1a -/- mice, which exhibited more progressive alterations in cytoplasmic ribosomes, ER, and nuclear proteins. A common mechanism found in both pre-disease and NASH livers was a hyperphosphorylation signature consistent with casein kinase 2α (CK2α) and AKT1 activation, which was normalized by SAMe administration. This was mimicked in human NAFLD with a metabolomic signature (M-subtype) resembling Mat1a -/- mice. In conclusion, we have identified a common proteome/phosphoproteome signature between Mat1a -/- mice and human NAFLD M-subtype that may have pathophysiological and therapeutic implications.
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Affiliation(s)
- Aaron E. Robinson
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
| | - Aleksandra Binek
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
| | - Komal Ramani
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Davis Building, Room 2097, Los Angeles, CA 90048, USA
| | - Niveda Sundararaman
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
| | - Lucía Barbier-Torres
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Davis Building, Room 2097, Los Angeles, CA 90048, USA
| | - Ben Murray
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Davis Building, Room 2097, Los Angeles, CA 90048, USA
| | - Vidya Venkatraman
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
| | - Simion Kreimer
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
| | - Angela Mc Ardle
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
| | - Mazen Noureddin
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Davis Building, Room 2097, Los Angeles, CA 90048, USA
| | - David Fernández-Ramos
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology Park of Bizkaia, 48160 Derio, Bizkaia, Spain
| | - Fernando Lopitz-Otsoa
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology Park of Bizkaia, 48160 Derio, Bizkaia, Spain
| | - Virginia Gutiérrez de Juan
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology Park of Bizkaia, 48160 Derio, Bizkaia, Spain
| | - Oscar Millet
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology Park of Bizkaia, 48160 Derio, Bizkaia, Spain
| | - José M. Mato
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology Park of Bizkaia, 48160 Derio, Bizkaia, Spain
| | - Shelly C. Lu
- Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Davis Building, Room 2097, Los Angeles, CA 90048, USA
- Corresponding author
| | - Jennifer E. Van Eyk
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Advanced Health Sciences Pavilion, 127 S. San Vicente Blvd, Room 9302, Los Angeles, CA 90048, USA
- Corresponding author
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Mc Ardle A, Binek A, Moradian A, Chazarin Orgel B, Rivas A, Washington KE, Phebus C, Manalo DM, Go J, Venkatraman V, Coutelin Johnson CW, Fu Q, Cheng S, Raedschelders K, Fert-Bober J, Pennington SR, Murray CI, Van Eyk JE. Standardized Workflow for Precise Mid- and High-Throughput Proteomics of Blood Biofluids. Clin Chem 2022; 68:450-460. [PMID: 34687543 DOI: 10.1093/clinchem/hvab202] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [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: 04/13/2021] [Accepted: 08/30/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND Accurate discovery assay workflows are critical for identifying authentic circulating protein biomarkers in diverse blood matrices. Maximizing the commonalities in the proteomic workflows between different biofluids simplifies the approach and increases the likelihood for reproducibility. We developed a workflow that can accommodate 3 blood-based proteomes: naive plasma, depleted plasma and dried blood. METHODS Optimal conditions for sample preparation and data independent acquisition-mass spectrometry analysis were established in plasma then automated for depleted plasma and dried blood. The mass spectrometry workflow was modified to facilitate sensitive high-throughput analysis or deeper profiling with mid-throughput analysis. Analytical performance was evaluated by the linear response of peptides and proteins to a 6- or 7-point dilution curve and the reproducibility of the relative peptide and protein intensity for 5 digestion replicates per day on 3 different days for each biofluid. RESULTS Using the high-throughput workflow, 74% (plasma), 93% (depleted), and 87% (dried blood) displayed an inter-day CV <30%. The mid-throughput workflow had 67% (plasma), 90% (depleted), and 78% (dried blood) of peptides display an inter-day CV <30%. Lower limits of detection and quantification were determined for peptides and proteins observed in each biofluid and workflow. Based on each protein and peptide's analytical performance, we could describe the observable, reliable, reproducible, and quantifiable proteomes for each biofluid and workflow. CONCLUSION The standardized workflows established here allows for reproducible and quantifiable detection of proteins covering a broad dynamic range. We envisage that implementation of this standard workflow should simplify discovery approaches and facilitate the translation of candidate markers into clinical use.
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Affiliation(s)
- Angela Mc Ardle
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Aleksandra Binek
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Annie Moradian
- Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Blandine Chazarin Orgel
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alejandro Rivas
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Kirstin E Washington
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Conor Phebus
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Danica-Mae Manalo
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - James Go
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Vidya Venkatraman
- Precision Biomarker Laboratories, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | - Qin Fu
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Susan Cheng
- Smidt Heart Institute, Barbra Streisand Women's Heart Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Koen Raedschelders
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Justyna Fert-Bober
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Stephen R Pennington
- School of Medicine and Medical Sciences, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland
| | - Christopher I Murray
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jennifer E Van Eyk
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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Mc Ardle A, Kwasnik A, Szenpetery A, Hernandez B, Parnell A, de Jager W, de Roock S, FitzGerald O, Pennington SR. Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis. Arthritis Rheumatol 2021; 74:81-91. [PMID: 34114357 DOI: 10.1002/art.41899] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 06/08/2021] [Indexed: 11/10/2022]
Abstract
OBJECTIVES To identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) and may be used to support appropriate early intervention. METHODS The serum proteome of patients with PsA and RA was interrogated using nano-flow liquid chromatography mass spectrometry (nLC-MS/MS) (n=64 patients), an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients) and a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients). Multiple reaction monitoring assays (MRM) were developed to evaluate the performance of putative markers using the discovery cohort (n=60) and subsequently an independent cohort of PsA and RA patients (n=167). RESULTS Multivariate machine learning analysis of the protein discovery data from the three platforms revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for bead based immunoassay measurements and 0.73 for aptamer based analysis. Subsequently in the separate verification and evaluation studies, random forest models revealed that a subset of proteins measured by MRM could differentiate PsA and RA patients with AUCs of 0.79 and 0.85 respectively. CONCLUSION We report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. With continued evaluation and refinement using additional and larger patient cohorts including those with other arthropathies we suggest the panel identified here could contribute toward improved clinical decision making.
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Affiliation(s)
- Angela Mc Ardle
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Ireland
| | - Anna Kwasnik
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Ireland
| | - Agnes Szenpetery
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Ireland
| | - Belinda Hernandez
- School of Medical Gerontology, TILDA (The Irish Longitudinal Study on Aging), Trinity College Dublin, Ireland.,School of Mathematics and Statistics, University College Dublin, Ireland
| | - Andrew Parnell
- School of Mathematics and Statistics, University College Dublin, Ireland
| | - Wilco de Jager
- Department of Paediatric Immunology, Laboratory of Translation Immunology LTI, Wilhelmina Children Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands.,Multiplex Core Facility, Laboratory of Translational Immunology LTI, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Sytze de Roock
- Multiplex Core Facility, Laboratory of Translational Immunology LTI, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Oliver FitzGerald
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Ireland
| | - Stephen R Pennington
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Ireland
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Kwasnik A, Tonry C, Ardle AM, Butt AQ, Inzitari R, Pennington SR. Proteomes, Their Compositions and Their Sources. Modern Proteomics – Sample Preparation, Analysis and Practical Applications 2016; 919:3-21. [DOI: 10.1007/978-3-319-41448-5_1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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Abstract
Joint destruction, as evidenced by radiographic findings, is a significant problem for patients suffering from rheumatoid arthritis and psoriatic arthritis. Inherently irreversible and frequently progressive, the process of joint damage begins at and even before the clinical onset of disease. However, rheumatoid and psoriatic arthropathies are heterogeneous in nature and not all patients progress to joint damage. It is therefore important to identify patients susceptible to joint destruction in order to initiate more aggressive treatment as soon as possible and thereby potentially prevent irreversible joint damage. At the same time, the high cost and potential side effects associated with aggressive treatment mean it is also important not to over treat patients and especially those who, even if left untreated, would not progress to joint destruction. It is therefore clear that a protein biomarker signature that could predict joint damage at an early stage would support more informed clinical decisions on the most appropriate treatment regimens for individual patients. Although many candidate biomarkers for rheumatoid and psoriatic arthritis have been reported in the literature, relatively few have reached clinical use and as a consequence the number of prognostic biomarkers used in rheumatology has remained relatively static for several years. It has become evident that a significant challenge in the transition of biomarker candidates to clinical diagnostic assays lies in the development of suitably robust biomarker assays, especially multiplexed assays, and their clinical validation in appropriate patient sample cohorts. Recent developments in mass spectrometry-based targeted quantitative protein measurements have transformed our ability to rapidly develop multiplexed protein biomarker assays. These advances are likely to have a significant impact on the validation of biomarkers in the future. In this review, we have comprehensively compiled a list of candidate biomarkers in rheumatoid and psoriatic arthritis, evaluated the evidence for their potential as biomarkers of bone (joint) damage, and outlined how mass spectrometry-based targeted and multiplexed measurement of candidate biomarker proteins is likely to accelerate their clinical validation and the development of clinical diagnostic tests.
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Affiliation(s)
- Angela Mc Ardle
- Conway Institute of Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Brian Flatley
- Conway Institute of Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Stephen R Pennington
- Conway Institute of Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.
| | - Oliver FitzGerald
- Conway Institute of Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland. .,Department of Rheumatology, St Vincent's University Hospital, Elm Park, Dublin 4, Ireland.
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