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Rutter LA, Cope H, MacKay MJ, Herranz R, Das S, Ponomarev SA, Costes SV, Paul AM, Barker R, Taylor DM, Bezdan D, Szewczyk NJ, Muratani M, Mason CE, Giacomello S. Astronaut omics and the impact of space on the human body at scale. Nat Commun 2024; 15:4952. [PMID: 38862505 PMCID: PMC11166943 DOI: 10.1038/s41467-024-47237-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 03/22/2024] [Indexed: 06/13/2024] Open
Abstract
Future multi-year crewed planetary missions will motivate advances in aerospace nutrition and telehealth. On Earth, the Human Cell Atlas project aims to spatially map all cell types in the human body. Here, we propose that a parallel Human Cell Space Atlas could serve as an openly available, global resource for space life science research. As humanity becomes increasingly spacefaring, high-resolution omics on orbit could permit an advent of precision spaceflight healthcare. Alongside the scientific potential, we consider the complex ethical, cultural, and legal challenges intrinsic to the human space omics discipline, and how philosophical frameworks may benefit from international perspectives.
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Affiliation(s)
- Lindsay A Rutter
- Transborder Medical Research Center, University of Tsukuba, 305-8575, Tsukuba, Japan
- Department of Genome Biology, Institute of Medicine, University of Tsukuba, 305-8575, Tsukuba, Japan
- School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Henry Cope
- School of Medicine, University of Nottingham, Derby, DE22 3DT, UK
| | - Matthew J MacKay
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10065, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, 10021, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Raúl Herranz
- Centro de Investigaciones Biológicas "Margarita Salas" (CSIC), Ramiro de Maeztu 9, Madrid, 28040, Spain
| | - Saswati Das
- Department of Biochemistry, Atal Bihari Vajpayee Institute of Medical Sciences & Dr. Ram Manohar Lohia Hospital, New Delhi, 110001, India
| | - Sergey A Ponomarev
- Department of Immunology and Microbiology, Institute for the Biomedical Problems, Russian Academy of Sciences, 123007, Moscow, Russia
| | - Sylvain V Costes
- Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA
| | - Amber M Paul
- Embry-Riddle Aeronautical University, Department of Human Factors and Behavioral Neurobiology, Daytona Beach, FL, 32114, USA
| | - Richard Barker
- Department of Botany, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Deanne M Taylor
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniela Bezdan
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, 72076, Germany
- NGS Competence Center Tübingen (NCCT), University of Tübingen, Tübingen, 72076, Germany
- yuri GmbH, Meckenbeuren, 88074, Germany
| | - Nathaniel J Szewczyk
- School of Medicine, University of Nottingham, Derby, DE22 3DT, UK
- Ohio Musculoskeletal and Neurological Institute (OMNI), Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, 45701, USA
| | - Masafumi Muratani
- Transborder Medical Research Center, University of Tsukuba, 305-8575, Tsukuba, Japan
- Department of Genome Biology, Institute of Medicine, University of Tsukuba, 305-8575, Tsukuba, Japan
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10065, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, 10021, USA.
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, 10065, USA.
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, 10065, USA.
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2
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Kalaidopoulou Nteak S, Völlmy F, Lukassen MV, van den Toorn H, den Boer MA, Bondt A, van der Lans SPA, Haas PJ, van Zuilen AD, Rooijakkers SHM, Heck AJR. Longitudinal Fluctuations in Protein Concentrations and Higher-Order Structures in the Plasma Proteome of Kidney Failure Patients Subjected to a Kidney Transplant. J Proteome Res 2024; 23:2124-2136. [PMID: 38701233 PMCID: PMC11165583 DOI: 10.1021/acs.jproteome.4c00064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/09/2024] [Accepted: 04/26/2024] [Indexed: 05/05/2024]
Abstract
Using proteomics and complexome profiling, we evaluated in a year-long study longitudinal variations in the plasma proteome of kidney failure patients, prior to and after a kidney transplantation. The post-transplant period was complicated by bacterial infections, resulting in dramatic changes in the proteome, attributed to an acute phase response (APR). As positive acute phase proteins (APPs), being elevated upon inflammation, we observed the well-described C-reactive protein and Serum Amyloid A (SAA), but also Fibrinogen, Haptoglobin, Leucine-rich alpha-2-glycoprotein, Lipopolysaccharide-binding protein, Alpha-1-antitrypsin, Alpha-1-antichymotrypsin, S100, and CD14. As negative APPs, being downregulated upon inflammation, we identified the well-documented Serotransferrin and Transthyretin, but added Kallistatin, Heparin cofactor 2, and interalpha-trypsin inhibitor heavy chain H1 and H2 (ITIH1, ITIH2). For the patient with the most severe APR, we performed plasma complexome profiling by SEC-LC-MS on all longitudinal samples. We observed that several plasma proteins displaying alike concentration patterns coelute and form macromolecular complexes. By complexome profiling, we expose how SAA1 and SAA2 become incorporated into high-density lipid particles, replacing largely Apolipoprotein (APO)A1 and APOA4. Overall, our data highlight that the combination of in-depth longitudinal plasma proteome and complexome profiling can shed further light on correlated variations in the abundance of several plasma proteins upon inflammatory events.
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Affiliation(s)
- Sofia Kalaidopoulou Nteak
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
| | - Franziska Völlmy
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
| | - Marie V. Lukassen
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
| | - Henk van den Toorn
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
| | - Maurits A. den Boer
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
| | - Albert Bondt
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
| | - Sjors P. A. van der Lans
- Department
of Medical Microbiology, University Medical
Center Utrecht, Utrecht 3584 CH, The Netherlands
| | - Pieter-Jan Haas
- Department
of Medical Microbiology, University Medical
Center Utrecht, Utrecht 3584 CH, The Netherlands
| | - Arjan D. van Zuilen
- Department
of Nephrology and Hypertension, University
Medical Center Utrecht, Utrecht University, Utrecht 3584 CH, The Netherlands
| | - Suzan H. M. Rooijakkers
- Department
of Medical Microbiology, University Medical
Center Utrecht, Utrecht 3584 CH, The Netherlands
| | - Albert J. R. Heck
- Biomolecular
Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular
Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584 CH, The Netherlands
- Netherlands
Proteomics Center, Utrecht 3584 CH, The Netherlands
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3
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Yang JC, Chen SP, Wang YF, Chang CH, Chang KH, Fuh JL, Chow LH, Han CL, Chen YJ, Wang SJ. Cerebrospinal Fluid Proteome Map Reveals Molecular Signatures of Reversible Cerebral Vasoconstriction Syndrome. Mol Cell Proteomics 2024; 23:100794. [PMID: 38839039 PMCID: PMC11263949 DOI: 10.1016/j.mcpro.2024.100794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 04/08/2024] [Accepted: 05/07/2024] [Indexed: 06/07/2024] Open
Abstract
Reversible cerebral vasoconstriction syndrome (RCVS) is a complex neurovascular disorder characterized by repetitive thunderclap headaches and reversible cerebral vasoconstriction. The pathophysiological mechanism of this mysterious syndrome remains underexplored and there is no clinically available molecular biomarker. To provide insight into the pathogenesis of RCVS, this study reported the first landscape of dysregulated proteome of cerebrospinal fluid (CSF) in patients with RCVS (n = 21) compared to the age- and sex-matched controls (n = 20) using data-independent acquisition mass spectrometry. Protein-protein interaction and functional enrichment analysis were employed to construct functional protein networks using the RCVS proteome. An RCVS-CSF proteome library resource of 1054 proteins was established, which illuminated large groups of upregulated proteins enriched in the brain and blood-brain barrier (BBB). Personalized RCVS-CSF proteomic profiles from 17 RCVS patients and 20 controls reveal proteomic changes involving the complement system, adhesion molecules, and extracellular matrix, which may contribute to the disruption of BBB and dysregulation of neurovascular units. Moreover, an additional validation cohort validated a panel of biomarker candidates and a two-protein signature predicted by machine learning model to discriminate RCVS patients from controls with an area under the curve of 0.997. This study reveals the first RCVS proteome and a potential pathogenetic mechanism of BBB and neurovascular unit dysfunction. It also nominates potential biomarker candidates that are mechanistically plausible for RCVS, which may offer potential diagnostic and therapeutic opportunities beyond the clinical manifestations.
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Affiliation(s)
- Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan; Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Shih-Pin Chen
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; Division of Translational Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Clinical Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Yen-Feng Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chan-Hua Chang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan; Department of Chemistry, National Central University, Taoyuan, Taiwan
| | - Kun-Hao Chang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan; Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan; Department of Chemistry, Institute of Chemistry, Academia Sinica, Naitonal Tsing Hua University, Hsinchu, Taiwan
| | - Jong-Ling Fuh
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Lok-Hi Chow
- College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Anesthesiology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chia-Li Han
- Master Program in Clinical Genomics and Proteomics, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan; Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Chemistry, National Taiwan University, Taipei, Taiwan.
| | - Shuu-Jiun Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan; College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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4
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Zhou J, Huang C, Gao X. Patient privacy in AI-driven omics methods. Trends Genet 2024; 40:383-386. [PMID: 38637270 DOI: 10.1016/j.tig.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/20/2024]
Abstract
Artificial intelligence (AI) in omics analysis raises privacy threats to patients. Here, we briefly discuss risk factors to patient privacy in data sharing, model training, and release, as well as methods to safeguard and evaluate patient privacy in AI-driven omics methods.
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Affiliation(s)
- Juexiao Zhou
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia; Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia
| | - Chao Huang
- Ningbo Institute of Information Technology Application, Chinese Academy of Sciences (CAS), Ningbo, China
| | - Xin Gao
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia; Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia.
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Shome M, MacKenzie TMG, Subbareddy SR, Snyder MP. The Importance, Challenges, and Possible Solutions for Sharing Proteomics Data While Safeguarding Individuals' Privacy. Mol Cell Proteomics 2024; 23:100731. [PMID: 38331191 PMCID: PMC10915627 DOI: 10.1016/j.mcpro.2024.100731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 01/28/2024] [Accepted: 02/05/2024] [Indexed: 02/10/2024] Open
Abstract
Proteomics data sharing has profound benefits at the individual level as well as at the community level. While data sharing has increased over the years, mostly due to journal and funding agency requirements, the reluctance of researchers with regard to data sharing is evident as many shares only the bare minimum dataset required to publish an article. In many cases, proper metadata is missing, essentially making the dataset useless. This behavior can be explained by a lack of incentives, insufficient awareness, or a lack of clarity surrounding ethical issues. Through adequate training at research institutes, researchers can realize the benefits associated with data sharing and can accelerate the norm of data sharing for the field of proteomics, as has been the standard in genomics for decades. In this article, we have put together various repository options available for proteomics data. We have also added pros and cons of those repositories to facilitate researchers in selecting the repository most suitable for their data submission. It is also important to note that a few types of proteomics data have the potential to re-identify an individual in certain scenarios. In such cases, extra caution should be taken to remove any personal identifiers before sharing on public repositories. Data sets that will be useless without personal identifiers need to be shared in a controlled access repository so that only authorized researchers can access the data and personal identifiers are kept safe.
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Affiliation(s)
- Mahasish Shome
- Department of Genetics, Stanford University, Palo Alto, California, USA
| | - Tim M G MacKenzie
- Department of Genetics, Stanford University, Palo Alto, California, USA
| | | | - Michael P Snyder
- Department of Genetics, Stanford University, Palo Alto, California, USA.
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Mundt F, Albrechtsen NJW, Mann SP, Treit P, Ghodgaonkar-Steger M, O’Flaherty M, Raijmakers R, Vizcaíno JA, Heck AJ, Mann M. Foresight in clinical proteomics: current status, ethical considerations, and future perspectives. OPEN RESEARCH EUROPE 2023; 3:59. [PMID: 37645494 PMCID: PMC10446044 DOI: 10.12688/openreseurope.15810.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/26/2023] [Indexed: 08/31/2023]
Abstract
With the advent of robust and high-throughput mass spectrometric technologies and bioinformatics tools to analyze large data sets, proteomics has penetrated broadly into basic and translational life sciences research. More than 95% of FDA-approved drugs currently target proteins, and most diagnostic tests are protein-based. The introduction of proteomics to the clinic, for instance to guide patient stratification and treatment, is already ongoing. Importantly, ethical challenges come with this success, which must also be adequately addressed by the proteomics and medical communities. Consortium members of the H2020 European Union-funded proteomics initiative: European Proteomics Infrastructure Consortium-providing access (EPIC-XS) met at the Core Technologies for Life Sciences (CTLS) conference to discuss the emerging role and implementation of proteomics in the clinic. The discussion, involving leaders in the field, focused on the current status, related challenges, and future efforts required to make proteomics a more mainstream technology for translational and clinical research. Here we report on that discussion and provide an expert update concerning the feasibility of clinical proteomics, the ethical implications of generating and analyzing large-scale proteomics clinical data, and recommendations to ensure both ethical and effective implementation in real-world applications.
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Affiliation(s)
- Filip Mundt
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicolai J. Wewer Albrechtsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, University Hospital, Bispebjerg Hospital, Bispebjerg, Denmark
| | | | - Peter Treit
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
| | | | - Martina O’Flaherty
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Reinout Raijmakers
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Albert J.R. Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
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7
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Vernardis SI, Demichev V, Lemke O, Grüning NM, Messner C, White M, Pietzner M, Peluso A, Collet TH, Henning E, Gille C, Campbell A, Hayward C, Porteous DJ, Marioni RE, Mülleder M, Zelezniak A, Wareham NJ, Langenberg C, Farooqi IS, Ralser M. The Impact of Acute Nutritional Interventions on the Plasma Proteome. J Clin Endocrinol Metab 2023; 108:2087-2098. [PMID: 36658456 PMCID: PMC10348471 DOI: 10.1210/clinem/dgad031] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 01/14/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
CONTEXT Humans respond profoundly to changes in diet, while nutrition and environment have a great impact on population health. It is therefore important to deeply characterize the human nutritional responses. OBJECTIVE Endocrine parameters and the metabolome of human plasma are rapidly responding to acute nutritional interventions such as caloric restriction or a glucose challenge. It is less well understood whether the plasma proteome would be equally dynamic, and whether it could be a source of corresponding biomarkers. METHODS We used high-throughput mass spectrometry to determine changes in the plasma proteome of i) 10 healthy, young, male individuals in response to 2 days of acute caloric restriction followed by refeeding; ii) 200 individuals of the Ely epidemiological study before and after a glucose tolerance test at 4 time points (0, 30, 60, 120 minutes); and iii) 200 random individuals from the Generation Scotland study. We compared the proteomic changes detected with metabolome data and endocrine parameters. RESULTS Both caloric restriction and the glucose challenge substantially impacted the plasma proteome. Proteins responded across individuals or in an individual-specific manner. We identified nutrient-responsive plasma proteins that correlate with changes in the metabolome, as well as with endocrine parameters. In particular, our study highlights the role of apolipoprotein C1 (APOC1), a small, understudied apolipoprotein that was affected by caloric restriction and dominated the response to glucose consumption and differed in abundance between individuals with and without type 2 diabetes. CONCLUSION Our study identifies APOC1 as a dominant nutritional responder in humans and highlights the interdependency of acute nutritional response proteins and the endocrine system.
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Affiliation(s)
- Spyros I Vernardis
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Vadim Demichev
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Oliver Lemke
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Nana-Maria Grüning
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Christoph Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Matt White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0SL, UK
- Computational Medicine, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Alina Peluso
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Tinh-Hai Collet
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
- Service of Endocrinology, Diabetology, Nutrition and Therapeutic Education, Department of Medicine, Geneva University Hospitals, 1211 Geneva, Switzerland
| | - Elana Henning
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Christoph Gille
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Aleksej Zelezniak
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius SE-412 96, Lithuania
- Randall Centre for Cell & Molecular Biophysics, King's College London, New Hunt's House, Guy's Campus, SE1 1UL London, UK
| | | | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0SL, UK
- Computational Medicine, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, E1 1HH, UK
| | - I Sadaf Farooqi
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
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8
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Safarlou CW, Jongsma KR, Vermeulen R, Bredenoord AL. The ethical aspects of exposome research: a systematic review. EXPOSOME 2023; 3:osad004. [PMID: 37745046 PMCID: PMC7615114 DOI: 10.1093/exposome/osad004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
In recent years, exposome research has been put forward as the next frontier for the study of human health and disease. Exposome research entails the analysis of the totality of environmental exposures and their corresponding biological responses within the human body. Increasingly, this is operationalized by big-data approaches to map the effects of internal as well as external exposures using smart sensors and multiomics technologies. However, the ethical implications of exposome research are still only rarely discussed in the literature. Therefore, we conducted a systematic review of the academic literature regarding both the exposome and underlying research fields and approaches, to map the ethical aspects that are relevant to exposome research. We identify five ethical themes that are prominent in ethics discussions: the goals of exposome research, its standards, its tools, how it relates to study participants, and the consequences of its products. Furthermore, we provide a number of general principles for how future ethics research can best make use of our comprehensive overview of the ethical aspects of exposome research. Lastly, we highlight three aspects of exposome research that are most in need of ethical reflection: the actionability of its findings, the epidemiological or clinical norms applicable to exposome research, and the meaning and action-implications of bias.
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Affiliation(s)
- Caspar W. Safarlou
- Department of Global Public Health and Bioethics, Julius Center for
Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The
Netherlands
| | - Karin R. Jongsma
- Department of Global Public Health and Bioethics, Julius Center for
Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The
Netherlands
| | - Roel Vermeulen
- Department of Global Public Health and Bioethics, Julius Center for
Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The
Netherlands
- Department of Population Health Sciences, Utrecht University,
Utrecht, The Netherlands
| | - Annelien L. Bredenoord
- Department of Global Public Health and Bioethics, Julius Center for
Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The
Netherlands
- Erasmus School of Philosophy, Erasmus University Rotterdam,
Rotterdam, The Netherlands
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9
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Kreft IC, Hoogendijk AJ, van der Zwaan C, van Alphen FPJ, Boon-Spijker M, Prinsze F, Meijer AB, de Korte D, van den Hurk K, van den Biggelaar M. Mass spectrometry-based analysis on the impact of whole blood donation on the global plasma proteome. Transfusion 2023; 63:564-573. [PMID: 36722460 DOI: 10.1111/trf.17254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/27/2022] [Accepted: 12/27/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Biomonitoring may provide important insights into the impact of a whole blood donation for individual blood donors. STUDY DESIGN AND METHODS Here, we used unbiased mass spectrometry (MS)-based proteomics to assess longitudinal changes in the global plasma proteome, after a single blood donation for new and regular donors. Subsequently, we compared plasma proteomes of 76 male and female whole blood donors, that were grouped based on their ferritin and hemoglobin (Hb) levels. RESULTS The longitudinal analysis showed limited changes in the plasma proteomes of new and regular donors after a whole blood donation during a 180-day follow-up period, apart from a significant short-term decrease in fibronectin. No differences were observed in the plasma proteomes of donors with high versus low Hb and/or ferritin levels. Plasma proteins with the highest variation between and within donors included pregnancy zone protein, which was associated with sex, Alfa 1-antitrypsin which was associated with the allelic variation, and Immunoglobulin D. Coexpression analysis revealed clustering of proteins that are associated with platelet, red cell, and neutrophil signatures as well as with the complement system and immune responses, including a prominent correlating cluster of immunoglobulin M (IgM), immunoglobulin J chain (JCHAIN), and CD5 antigen-like (CD5L). DISCUSSION Overall, our proteomic approach shows that whole blood donation has a limited impact on the plasma proteins measured. Our findings suggest that plasma profiling can be successfully employed to consistently detect proteins and protein complexes that reflect the functionality and integrity of platelets, red blood cells, and immune cells in blood donors and thus highlights its potential use for donor health monitoring.
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Affiliation(s)
- Iris C Kreft
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Arie J Hoogendijk
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Carmen van der Zwaan
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Floris P J van Alphen
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Mariette Boon-Spijker
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Femmeke Prinsze
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Alexander B Meijer
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
- Department of Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands
| | - Dirk de Korte
- Department of Blood Cell Research, Sanquin Research, Amsterdam, The Netherlands
- Department of Product and Process Development, Sanquin Blood Bank, Amsterdam, The Netherlands
| | - Katja van den Hurk
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Maartje van den Biggelaar
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
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10
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Fierro-Monti I, Wright JC, Choudhary JS, Vizcaíno JA. Identifying individuals using proteomics: are we there yet? Front Mol Biosci 2022; 9:1062031. [PMID: 36523653 PMCID: PMC9744771 DOI: 10.3389/fmolb.2022.1062031] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/16/2022] [Indexed: 08/31/2023] Open
Abstract
Multi-omics approaches including proteomics analyses are becoming an integral component of precision medicine. As clinical proteomics studies gain momentum and their sensitivity increases, research on identifying individuals based on their proteomics data is here examined for risks and ethics-related issues. A great deal of work has already been done on this topic for DNA/RNA sequencing data, but it has yet to be widely studied in other omics fields. The current state-of-the-art for the identification of individuals based solely on proteomics data is explained. Protein sequence variation analysis approaches are covered in more detail, including the available analysis workflows and their limitations. We also outline some previous forensic and omics proteomics studies that are relevant for the identification of individuals. Following that, we discuss the risks of patient reidentification using other proteomics data types such as protein expression abundance and post-translational modification (PTM) profiles. In light of the potential identification of individuals through proteomics data, possible legal and ethical implications are becoming increasingly important in the field.
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Affiliation(s)
- Ivo Fierro-Monti
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | | | | | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, United Kingdom
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11
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Nierves L, Guo J, Chen S, Tsui J, Uzozie AC, Bush JW, Huan T, Lange PF. Multi-omic profiling of the leukemic microenvironment shows bone marrow interstitial fluid is distinct from peripheral blood plasma. Exp Hematol Oncol 2022; 11:56. [PMID: 36109804 PMCID: PMC9476264 DOI: 10.1186/s40164-022-00310-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/05/2022] [Indexed: 11/21/2022] Open
Abstract
Background The bone marrow is the place of hematopoiesis with a microenvironment that supports lifelong maintenance of stem cells and high proliferation. It is not surprising that this environment is also favourable for malignant cells emerging in the bone marrow or metastasizing to it. While the cellular composition of the bone marrow microenvironment has been extensively studied, the extracellular matrix and interstitial fluid components have received little attention. Since the sinusoids connect the bone marrow interstitial fluid to the circulation, it is often considered to have the same composition as peripheral blood plasma. Stark differences in the cellular composition of the bone marrow and peripheral blood with different secretory capacities would however suggest profound differences. Methods In this study we set out to better define if and how the bone marrow interstitial fluid (BMIF) compares to the peripheral blood plasma (PBP) and how both are remodeled during chemotherapy. We applied a multi-omic strategy to quantify the metabolite, lipid and protein components as well as the proteolytic modification of proteins to gain a comprehensive understanding of the two compartments. Results We found that the bone marrow interstitial fluid is clearly distinct from peripheral blood plasma, both during active pediatric acute lymphoblastic leukemia and following induction chemotherapy. Either compartment was shaped differently by active leukemia, with the bone marrow interstitial fluid being rich in extracellular vesicle components and showing protease dysregulation while the peripheral blood plasma showed elevation of immune regulatory proteins. Following chemotherapy, the BMIF showed signs of cellular remodeling and impaired innate immune activation while the peripheral blood plasma was characterized by restored lipid homeostasis. Conclusion This study provides a comprehensive examination of the fluid portion of the acute lymphoblastic leukemia microenvironment and finds the contribution of either microenvironment to tumourigenesis. Supplementary Information The online version contains supplementary material available at 10.1186/s40164-022-00310-0.
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12
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Baros-Steyl SS, Al Heialy S, Semreen AH, Semreen MH, Blackburn JM, Soares NC. A review of mass spectrometry-based analyses to understand COVID-19 convalescent plasma mechanisms of action. Proteomics 2022; 22:e2200118. [PMID: 35809024 PMCID: PMC9349457 DOI: 10.1002/pmic.202200118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 07/04/2022] [Accepted: 07/05/2022] [Indexed: 01/08/2023]
Abstract
The spread of coronavirus disease 2019 (COVID‐19) viral pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has become a worldwide pandemic claiming several thousands of lives worldwide. During this pandemic, several studies reported the use of COVID‐19 convalescent plasma (CCP) from recovered patients to treat severely or critically ill patients. Although this historical and empirical treatment holds immense potential as a first line of response against eventual future unforeseen viral epidemics, there are several concerns regarding the efficacy and safety of this approach. This critical review aims to pinpoint the possible role of mass spectrometry‐based analysis in the identification of unique molecular component proteins, peptides, and metabolites of CCP that explains the therapeutic mechanism of action against COVID‐19. Additionally, the text critically reviews the potential application of mass spectrometry approaches in the search for novel plasma biomarkers that may enable a rapid and accurate assessment of the safety and efficacy of CCP. Considering the relative low‐cost value involved in the CCP therapy, this proposed line of research represents a tangible scientific challenge that will be translated into clinical practice and help save several thousand lives around the world, specifically in low‐ and middle‐income countries.
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Affiliation(s)
- Seanantha S Baros-Steyl
- Department of Integrative Biomedical Sciences, Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Saba Al Heialy
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.,Meakin-Christie Laboratories, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Ahlam H Semreen
- College of Pharmacy-Department of Medicinal Chemistry, University of Sharjah, United Arab Emirates.,Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Mohammad H Semreen
- College of Pharmacy-Department of Medicinal Chemistry, University of Sharjah, United Arab Emirates.,Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Jonathan M Blackburn
- Department of Integrative Biomedical Sciences, Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Nelson C Soares
- College of Pharmacy-Department of Medicinal Chemistry, University of Sharjah, United Arab Emirates.,Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
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13
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Dayon L, Cominetti O, Affolter M. Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications. Expert Rev Proteomics 2022; 19:131-151. [PMID: 35466824 DOI: 10.1080/14789450.2022.2070477] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids. AREAS COVERED We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics. EXPERT OPINION While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.
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Affiliation(s)
- Loïc Dayon
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ornella Cominetti
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland
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14
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Deutsch EW, Omenn GS, Sun Z, Maes M, Pernemalm M, Palaniappan KK, Letunica N, Vandenbrouck Y, Brun V, Tao SC, Yu X, Geyer PE, Ignjatovic V, Moritz RL, Schwenk JM. Advances and Utility of the Human Plasma Proteome. J Proteome Res 2021; 20:5241-5263. [PMID: 34672606 PMCID: PMC9469506 DOI: 10.1021/acs.jproteome.1c00657] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.
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Affiliation(s)
- Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Gilbert S Omenn
- Institute for Systems Biology, Seattle, Washington 98109, United States.,Departments of Computational Medicine & Bioinformatics, Internal Medicine, and Human Genetics and School of Public Health, University of Michigan, Ann Arbor, Michigan 48109-2218, United States
| | - Zhi Sun
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Michal Maes
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Maria Pernemalm
- Department of Oncology and Pathology/Science for Life Laboratory, Karolinska Institutet, 171 65 Stockholm, Sweden
| | | | - Natasha Letunica
- Murdoch Children's Research Institute, 50 Flemington Road, Parkville 3052, Victoria, Australia
| | - Yves Vandenbrouck
- Université Grenoble Alpes, CEA, Inserm U1292, Grenoble 38000, France
| | - Virginie Brun
- Université Grenoble Alpes, CEA, Inserm U1292, Grenoble 38000, France
| | - Sheng-Ce Tao
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, B207 SCSB Building, 800 Dongchuan Road, Shanghai 200240, China
| | - Xiaobo Yu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Philipp E Geyer
- OmicEra Diagnostics GmbH, Behringstr. 6, 82152 Planegg, Germany
| | - Vera Ignjatovic
- Murdoch Children's Research Institute, 50 Flemington Road, Parkville 3052, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, 50 Flemington Road, Parkville 3052, Victoria, Australia
| | - Robert L Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Jochen M Schwenk
- Affinity Proteomics, Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Tomtebodavägen 23, SE-171 65 Solna, Sweden
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15
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Omenn GS, Lane L, Overall CM, Paik YK, Cristea IM, Corrales FJ, Lindskog C, Weintraub S, Roehrl MHA, Liu S, Bandeira N, Srivastava S, Chen YJ, Aebersold R, Moritz RL, Deutsch EW. Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project. J Proteome Res 2021; 20:5227-5240. [PMID: 34670092 DOI: 10.1021/acs.jproteome.1c00590] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.
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Affiliation(s)
- Gilbert S Omenn
- University of Michigan, Ann Arbor, Michigan 48109, United States.,Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | | | - Young-Ki Paik
- Yonsei Proteome Research Center and Yonsei University, Seoul 03722, Korea
| | - Ileana M Cristea
- Princeton University, Princeton, New Jersey 08544, United States
| | | | | | - Susan Weintraub
- University of Texas Health, San Antonio, San Antonio, Texas 78229-3900, United States
| | - Michael H A Roehrl
- Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
| | - Siqi Liu
- BGI Group, Shenzhen 518083, China
| | - Nuno Bandeira
- University of California, San Diego, La Jolla, California 92093, United States
| | | | - Yu-Ju Chen
- National Taiwan University, Academia Sinica, Nankang, Taipei 11529, Taiwan
| | - Ruedi Aebersold
- ETH-Zurich and University of Zurich, 8092 Zurich, Switzerland
| | - Robert L Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
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16
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Keane TM, O'Donovan C, Vizcaíno JA. The growing need for controlled data access models in clinical proteomics and metabolomics. Nat Commun 2021; 12:5787. [PMID: 34599180 PMCID: PMC8486822 DOI: 10.1038/s41467-021-26110-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 09/17/2021] [Indexed: 01/25/2023] Open
Abstract
More and more clinical studies include potentially sensitive human proteomics or metabolomics datasets, but bioinformatics resources for managing the access to these data are not yet available. This commentary discusses current best practices and future perspectives for the responsible handling of clinical proteomics and metabolomics data.
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Affiliation(s)
- Thomas M Keane
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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17
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Mann M, Kumar C, Zeng WF, Strauss MT. Artificial intelligence for proteomics and biomarker discovery. Cell Syst 2021; 12:759-770. [PMID: 34411543 DOI: 10.1016/j.cels.2021.06.006] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 05/07/2021] [Accepted: 06/28/2021] [Indexed: 12/14/2022]
Abstract
There is an avalanche of biomedical data generation and a parallel expansion in computational capabilities to analyze and make sense of these data. Starting with genome sequencing and widely employed deep sequencing technologies, these trends have now taken hold in all omics disciplines and increasingly call for multi-omics integration as well as data interpretation by artificial intelligence technologies. Here, we focus on mass spectrometry (MS)-based proteomics and describe how machine learning and, in particular, deep learning now predicts experimental peptide measurements from amino acid sequences alone. This will dramatically improve the quality and reliability of analytical workflows because experimental results should agree with predictions in a multi-dimensional data landscape. Machine learning has also become central to biomarker discovery from proteomics data, which now starts to outperform existing best-in-class assays. Finally, we discuss model transparency and explainability and data privacy that are required to deploy MS-based biomarkers in clinical settings.
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Affiliation(s)
- Matthias Mann
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
| | - Chanchal Kumar
- Translational Science & Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
| | - Wen-Feng Zeng
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
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18
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Forensic proteomics. Forensic Sci Int Genet 2021; 54:102529. [PMID: 34139528 DOI: 10.1016/j.fsigen.2021.102529] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 05/06/2021] [Accepted: 05/07/2021] [Indexed: 12/19/2022]
Abstract
Protein is a major component of all biological evidence, often the matrix that embeds other biomolecules such as polynucleotides, lipids, carbohydrates, and small molecules. The proteins in a sample reflect the transcriptional and translational program of the originating cell types. Because of this, proteins can be used to identify body fluids and tissues, as well as convey genetic information in the form of single amino acid polymorphisms, the result of non-synonymous SNPs. This review explores the application and potential of forensic proteomics. The historical role that protein analysis played in the development of forensic science is examined. This review details how innovations in proteomic mass spectrometry have addressed many of the historical limitations of forensic protein science, and how the application of forensic proteomics differs from proteomics in the life sciences. Two more developed applications of forensic proteomics are examined in detail: body fluid and tissue identification, and proteomic genotyping. The review then highlights developing areas of proteomics that have the potential to impact forensic science in the near future: fingermark analysis, species identification, peptide toxicology, proteomic sex estimation, and estimation of post-mortem intervals. Finally, the review highlights some of the newer innovations in proteomics that may drive further development of the field. In addition to potential impact, this review also attempts to evaluate the stage of each application in the development, validation and implementation process. This review is targeted at investigators who are interested in learning about proteomics in a forensic context and expanding the amount of information they can extract from biological evidence.
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19
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Bandeira N, Deutsch EW, Kohlbacher O, Martens L, Vizcaíno JA. Data Management of Sensitive Human Proteomics Data: Current Practices, Recommendations, and Perspectives for the Future. Mol Cell Proteomics 2021; 20:100071. [PMID: 33711481 PMCID: PMC8056256 DOI: 10.1016/j.mcpro.2021.100071] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/01/2021] [Accepted: 03/02/2021] [Indexed: 12/12/2022] Open
Abstract
Today it is the norm that all relevant proteomics data that support the conclusions in scientific publications are made available in public proteomics data repositories. However, given the increase in the number of clinical proteomics studies, an important emerging topic is the management and dissemination of clinical, and thus potentially sensitive, human proteomics data. Both in the United States and in the European Union, there are legal frameworks protecting the privacy of individuals. Implementing privacy standards for publicly released research data in genomics and transcriptomics has led to processes to control who may access the data, so-called "controlled access" data. In parallel with the technological developments in the field, it is clear that the privacy risks of sharing proteomics data need to be properly assessed and managed. In our view, the proteomics community must be proactive in addressing these issues. Yet a careful balance must be kept. On the one hand, neglecting to address the potential of identifiability in human proteomics data could lead to reputational damage of the field, while on the other hand, erecting barriers to open access to clinical proteomics data will inevitably reduce reuse of proteomics data and could substantially delay critical discoveries in biomedical research. In order to balance these apparently conflicting requirements for data privacy and efficient use and reuse of research efforts through the sharing of clinical proteomics data, development efforts will be needed at different levels including bioinformatics infrastructure, policymaking, and mechanisms of oversight.
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Affiliation(s)
- Nuno Bandeira
- Center for Computational Mass Spectrometry, University of California, San Diego (UCSD), La Jolla, California, USA; Department Computer Science and Engineering, University of California, San Diego (UCSD), La Jolla, California, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego (UCSD), La Jolla, California, USA
| | | | - Oliver Kohlbacher
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Quantitative Biology Center, University of Tübingen, Tübingen, Germany; Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany; Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
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20
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Mann SP, Treit PV, Geyer PE, Omenn GS, Mann M. Ethical Principles, Constraints and Opportunities in Clinical Proteomics. Mol Cell Proteomics 2021; 20:100046. [PMID: 33453411 PMCID: PMC7950205 DOI: 10.1016/j.mcpro.2021.100046] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 01/04/2021] [Indexed: 12/11/2022] Open
Abstract
Recent advances in mass spectrometry (MS)-based proteomics have vastly increased the quality and scope of biological information that can be derived from human samples. These advances have rendered current workflows increasingly applicable in biomedical and clinical contexts. As proteomics is poised to take an important role in the clinic, associated ethical responsibilities increase in tandem with impacts on the health, privacy, and wellbeing of individuals. We conducted and here report a systematic literature review of ethical issues in clinical proteomics. We add our perspectives from a background of bioethics, the results of our accompanying paper extracting individual-sensitive results from patient samples, and the literature addressing similar issues in genomics. The spectrum of potential issues ranges from patient re-identification to incidental findings of clinical significance. The latter can be divided into actionable and unactionable findings. Some of these have the potential to be employed in discriminatory or privacy-infringing ways. However, incidental findings may also have great positive potential. A plasma proteome profile, for instance, could inform on the general health or disease status of an individual regardless of the narrow diagnostic question that prompted it. We suggest that early discussion of ethical issues in clinical proteomics can ensure that eventual healthcare practices and regulations reflect the considered judgment of the community and anticipate opportunities and problems that may arise as the technology matures.
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Affiliation(s)
- Sebastian Porsdam Mann
- Department of Media, Cognition and Communication, University of Copenhagen, Copenhagen, Denmark; Uehiro Center for Practical Ethics, University of Oxford, Oxford, UK; New address: Faculty of Law, University of Oxford, Oxford, UK.
| | - Peter V Treit
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Philipp E Geyer
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; New address: OmicEra Diagnostics GmbH, Planegg, Germany
| | - Gilbert S Omenn
- Departments of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
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