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Gyllensten U, Bosdotter Enroth S, Stålberg K, Sundfeldt K, Enroth S. Preoperative Fasting and General Anaesthesia Alter the Plasma Proteome. Cancers (Basel) 2020; 12:cancers12092439. [PMID: 32867270 PMCID: PMC7564209 DOI: 10.3390/cancers12092439] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 08/22/2020] [Accepted: 08/26/2020] [Indexed: 01/15/2023] Open
Abstract
Background: Blood plasma collected at time of surgery is an excellent source of patient material for investigations into disease aetiology and for the discovery of novel biomarkers. Previous studies on limited sets of proteins and patients have indicated that pre-operative fasting and anaesthesia can affect protein levels, but this has not been investigated on a larger scale. These effects could produce erroneous results in case-control studies if samples are not carefully matched. Methods: The proximity extension assay (PEA) was used to characterize 983 unique proteins in a total of 327 patients diagnosed with ovarian cancer and 50 age-matched healthy women. The samples were collected either at time of initial diagnosis or before surgery under general anaesthesia. Results: 421 of the investigated proteins (42.8%) showed statistically significant differences in plasma abundance levels comparing samples collected at time of diagnosis or just before surgery under anaesthesia. Conclusions: The abundance levels of the plasma proteome in samples collected before incision, i.e., after short-time fasting and under general anaesthesia differs greatly from levels in samples from awake patients. This emphasizes the need for careful matching of the pre-analytical conditions of samples collected from controls to cases at time of surgery in the discovery as well as clinical use of protein biomarkers.
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Affiliation(s)
- Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-751 08 Uppsala, Sweden;
| | | | - Karin Stålberg
- Department of Women’s and Children’s Health, Uppsala University, SE-751 85 Uppsala, Sweden;
| | - Karin Sundfeldt
- Department of Obstetrics and Gynaecology, Institute of Clinical Sciences, Sahlgrenska Academy at Gothenburg University, SE-416 85 Gothenburg, Sweden;
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Box 815, Uppsala University, SE-751 08 Uppsala, Sweden;
- Correspondence: ; Tel.: +46-18-4714913
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Folkersen L, Fauman E, Sabater-Lleal M, Strawbridge RJ, Frånberg M, Sennblad B, Baldassarre D, Veglia F, Humphries SE, Rauramaa R, de Faire U, Smit AJ, Giral P, Kurl S, Mannarino E, Enroth S, Johansson Å, Enroth SB, Gustafsson S, Lind L, Lindgren C, Morris AP, Giedraitis V, Silveira A, Franco-Cereceda A, Tremoli E, Gyllensten U, Ingelsson E, Brunak S, Eriksson P, Ziemek D, Hamsten A, Mälarstig A. Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease. PLoS Genet 2017; 13:e1006706. [PMID: 28369058 PMCID: PMC5393901 DOI: 10.1371/journal.pgen.1006706] [Citation(s) in RCA: 147] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 04/17/2017] [Accepted: 03/20/2017] [Indexed: 11/18/2022] Open
Abstract
Recent advances in highly multiplexed immunoassays have allowed systematic large-scale measurement of hundreds of plasma proteins in large cohort studies. In combination with genotyping, such studies offer the prospect to 1) identify mechanisms involved with regulation of protein expression in plasma, and 2) determine whether the plasma proteins are likely to be causally implicated in disease. We report here the results of genome-wide association (GWA) studies of 83 proteins considered relevant to cardiovascular disease (CVD), measured in 3,394 individuals with multiple CVD risk factors. We identified 79 genome-wide significant (p<5e-8) association signals, 55 of which replicated at P<0.0007 in separate validation studies (n = 2,639 individuals). Using automated text mining, manual curation, and network-based methods incorporating information on expression quantitative trait loci (eQTL), we propose plausible causal mechanisms for 25 trans-acting loci, including a potential post-translational regulation of stem cell factor by matrix metalloproteinase 9 and receptor-ligand pairs such as RANK-RANK ligand. Using public GWA study data, we further evaluate all 79 loci for their causal effect on coronary artery disease, and highlight several potentially causal associations. Overall, a majority of the plasma proteins studied showed evidence of regulation at the genetic level. Our results enable future studies of the causal architecture of human disease, which in turn should aid discovery of new drug targets. Several proteins that circulate in blood have been linked to cardiovascular disease through the use of classic epidemiology and correlation studies. If individuals with higher risk of disease have higher levels of a protein, the protein may be associated with disease. However, this does not necessarily mean that the protein causes disease; it may merely be an innocent bystander or a consequence of the disease process. To establish whether a protein causes disease, a genetic approach, insensitive to reverse causation, can be used. Instead of correlating the levels of the protein itself, gene variants that regulate the protein levels are used in the analysis. This approach requires prior knowledge of which genetic variants are linked to individual proteins. Therefore we completed a map of how common genetic variants affect the blood concentration levels of 83 proteins that have been implicated in cardiovascular disease. By using this map of cause-to-effect findings, we gained insights into the regulation of a majority of the proteins under study and how they relate to risk of coronary artery disease. This study provides a map of genetic regulation of important cardiovascular plasma proteins, insights into their upstream regulatory environment, as well as novel leads for cardiovascular drug development.
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Affiliation(s)
- Lasse Folkersen
- Department of Systems Biology, Technical University of Denmark, Copenhagen, Denmark
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Eric Fauman
- Pfizer Worldwide Research & Development, Cambridge, Massachusetts, United States of America
| | - Maria Sabater-Lleal
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Rona J. Strawbridge
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Mattias Frånberg
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Bengt Sennblad
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Damiano Baldassarre
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università di Milano, Milan, Italy
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | | | - Steve E. Humphries
- British Heart Foundation Laboratories, University College of London, Department of Medicine, Rayne Building, London, United Kingdom
| | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Ulf de Faire
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, and Department of Cardiology, Karolinska University Hospital, Solna, Karolinska Institutet, Stockholm, Sweden
| | - Andries J. Smit
- Department of Medicine, University Medical Center Groningen, Groningen, the Netherlands
| | - Philippe Giral
- Assistance Publique - Hopitaux de Paris; Service Endocrinologie-Metabolisme, Groupe Hôpitalier Pitie-Salpetriere, Unités de Prévention Cardiovasculaire, Paris, France
| | - Sudhir Kurl
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Elmo Mannarino
- Internal Medicine, Angiology and Arteriosclerosis Diseases, Department of Clinical and Experimental Medicine, University of Perugia, Perugia, Italy
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala, Uppsala University, Uppsala, Sweden
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala, Uppsala University, Uppsala, Sweden
| | | | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Cecilia Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Andrew P. Morris
- Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom
| | - Vilmantas Giedraitis
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Angela Silveira
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Anders Franco-Cereceda
- Cardiothoracic Surgery Unit, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Elena Tremoli
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università di Milano, Milan, Italy
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | | | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory Uppsala, Uppsala University, Uppsala, Sweden
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Søren Brunak
- Department of Systems Biology, Technical University of Denmark, Copenhagen, Denmark
| | - Per Eriksson
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Daniel Ziemek
- Pfizer Worldwide Research & Development, Cambridge, Massachusetts, United States of America
| | - Anders Hamsten
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Anders Mälarstig
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Pfizer Worldwide Research and Development, Stockholm, Sweden
- * E-mail:
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Enroth S, Bosdotter Enroth S, Johansson Å, Gyllensten U. Effect of genetic and environmental factors on protein biomarkers for common non-communicable disease and use of personally normalized plasma protein profiles (PNPPP). Biomarkers 2015; 20:355-64. [PMID: 26551787 DOI: 10.3109/1354750x.2015.1093546] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE To study the impact of genetic and lifestyle factors on protein biomarkers and develop personally normalized plasma protein profiles (PNPPP) controlling for non-disease-related variance. MATERIALS AND METHODS Proximity extension assays were used to measure 145 proteins in 632 controls and 344 cases with non-communicable diseases. RESULTS Genetic and lifestyle factors explained 20-88% of the variation in healthy controls. Adjusting for these factors reduced the number of candidate biomarkers by 63%. CONCLUSION PNPPP efficiently controls for non-disease-related variance, allowing both for efficient discovery of novel biomarkers and for covariate-independent linear cut-offs suitable for clinical use.
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Affiliation(s)
- Stefan Enroth
- a Department of Immunology , Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University , Uppsala , Sweden and
| | | | - Åsa Johansson
- a Department of Immunology , Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University , Uppsala , Sweden and
| | - Ulf Gyllensten
- a Department of Immunology , Genetics, and Pathology, Biomedical Center, SciLifeLab Uppsala, Uppsala University , Uppsala , Sweden and
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