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DOI: 10.1055/a-1690-8897
Proteomics in Thrombosis and Hemostasis
- Abstract
- Introduction
- Platelets
- Blood Clot Composition
- Venous Thromboembolism
- Stroke
- Therapeutics
- Future of Proteomics in Thrombosis and Hemostasis
- Key Considerations for Proteomics Studies
- References
Abstract
Proteomics, the simultaneous study of all proteins in a given cell, tissue or organism, is an innovative approach used to identify novel markers for diagnosis, prognosis and the pathophysiological mechanisms associated with diseases. Proteomic methodologies have been used in a variety of contexts such as investigating changes in protein abundance that may occur with disease presence, the response to therapeutic treatments as well as the impacts of age on the plasma proteome.
Over the last decade, significant technological advancements in proteomic techniques have resulted in an increase in the use of proteomics in thrombosis and hemostasis research, particularly in order to identify relevant and novel clinical markers associated with bleeding and thrombosis. This mini-review explores the use of proteomics in the setting of thrombosis and hemostasis from 2010-2020, across five main domains (platelets, blood clot composition, stroke, venous thromboembolism, and therapeutics), as well as provides insights into key considerations for conducting proteomic studies.
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Introduction
Proteomics represents the simultaneous study of many proteins in a given cell, tissue, or organism,[1] and is an innovative approach used in identifying novel markers for diagnosis, prognosis, and characterization of diseases, such as heart failure and cancer.[2] [3] This methodological approach can be utilized to study a variety of biological fluids such as saliva, urine, and blood, specifically focusing on changes in protein abundance that may occur with disease, age, or as a response to therapeutic treatments.[1]
Proteomic techniques have evolved rapidly over the past decade, with a decrease in sample volume requirement, and a subsequent increase in data acquisition and throughput. There has also been a significant decrease in the footprint and cost of mass spectrometers, “the workhorses” of proteomics, from large stand-alone analyzers to desktop analyzers, a development that has moved proteomics significantly closer toward real-time clinical integration. Due to these technological advancements, there has been an increase in the use of proteomics in thrombosis and hemostasis research, specifically in aspects such as stroke and venous thromboembolism (VTE).[4] [5] This mini-review explores the use of proteomics in the setting of thrombosis and hemostasis from 2010 to 2020, across five main domains (platelets, blood clot composition, VTE, stroke, and therapeutics), to reflect the focus of proteomics studies undertaken across this period.
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Platelets
Platelets play a key role in maintaining hemostasis by helping form clots to prevent bleeding.[6] We identified two studies from the past decade that used proteomics to gain a better understanding of the platelet proteome.[7] [8] Platelets can be modified by multiple external factors such as disease,[9] therapeutic treatments,[7] and diet.[10] Proteomics is an advantageous method to compare the effects of these modifiers. Proteomic discovery and validation studies have compared platelet proteomes between intracoronary platelets and peripheral arterial platelets from patients with ST-segment elevation myocardial infarction (STEMI). Four proteins were found differentially abundant in intracoronary platelets in comparison to arterial platelets.[8] In a population of type 2 diabetes patients with stable coronary ischemia, proteomics demonstrated that using dual-antiplatelet therapy in the form of clopidogrel in conjunction with aspirin differentially altered the abundance of several platelet proteins in comparison to aspirin alone.[7]
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Blood Clot Composition
Blood clots consist of a variety of components and proteomics has been used effectively in four studies to further understand the composition of blood clots ([Table 1]).[5] [11] [12] [13] Stachowicz et al investigated the differences in plasma clot composition in patients with thrombotic antiphospholipid syndrome compared with patients with VTE.[5] In plasma clots prepared ex vivo, 63 proteins were different, with results highlighting that the underlying disease plays a crucial role in the composition and mechanism of clots in distinct clinical settings.[5] Proteomics has enabled the identification of up to 467 proteins, with several functional roles such as cell differentiation, metabolism, and adhesion in coronary thrombi extracted from STEMI patients.[11] Plasma proteomic approaches have also been used in STEMI patients to identify death-inducer obliterator 1, a proapoptotic transcription factor, as a potential marker of coronary thrombosis.[11] Two studies prepared plasma clots ex vivo, using healthy adult samples to investigate the composition of clots.[12] [13] Ząbczyk et al identified 494 proteins in ex vivo prepared, plasma fibrin clot structures and demonstrated that body mass index and age have an impact on clot structure properties, such as lysis time.[13] Proteomics has also been useful in identifying specific mechanisms associated with fibrin cross-links, as well as specific substrates of FXIIIa, a protein responsible for cross-linking fibrin γ-chains in early phases of clot formation.[12] The formation of blood clots, as well as the precise balance between clotting and bleeding, is heavily regulated by thrombin. Proteomics studies have identified 54 different substrates of thrombin suggesting the need for future clinical studies of specific thrombin substrates in individuals based on age or health status.[14]
Abbreviations: β2GpI, anti-β2 glycoprotein I; 1-DE, one-dimensional electrophoresis; 2D-DIGE, two-dimensional gel electrophoresis; 2-DE MALDI-TOF/TOF, 2-dimensional electrophoresis matrix-assisted laser desorption/ionization-tandem time of flight mass spectrometry; 2-DE, 2 dimensional electrophoresis; AGP, alpha-1-acid glycoprotein; Apo A-I, apolipoprotein A-I; ApoB100, apolipoprotein B-100; APS, antiphospholipid syndrome; C5, complement C5; CBG, corticosteroid- binding globulin; CDC42hs, cell division control protein 42 homolog; CP, ceruloplasmin; DIDO1, death-inducer obliterator 1; DJ-1, Parkinson disease protein 7; ED, emergency department; ELISA, enzyme-linked immunosorbent; F2, factor 2 (prothrombin); FERM3, fermitin family homolog 3; FINC, fibronectin; FIX, factor 9; FXIIIa, factor XIIIa (Laki–Lorand factor); GPI, integrin beta-1; GPIIb, integrin alpha-IIb; GPIII, integrin beta-3; GPIX, platelet glycoprotein IX; GPX3, glutathione peroxidase 3; HIVEP1, zinc finger protein 40; HRG, histidine-rich glycoprotein; IGFBP-3, insulin-like growth factor-binding protein 3; IgM, immunoglobulin M; ITA2B, integrin alpha-IIb; LC/ MRM-MS, liquid chromatography/multiple reaction monitoring- mass spectrometry; LC-ESI-MS/MS, liquid chromatography-electrospray ionization-tandem mass spectrometry; LC-MALDI MS/MS, liquid chromatography matrix-assisted laser desorption/ionization-tandem mass spectrometry; LC-MS3, liquid chromatography triple mass spectrometry; LSEL, L-selectin; MMRN1, Multimerin-1; MRM-MS, multiple reaction monitoring-mass spectrometry; MS, mass spectrometry; NADPH, flavin reductase; PAI-1, plasminogen activator inhibitor 1; PARVB, beta-parvin; PDGFB, platelet-derived growth factor subunit-B; PF4, platelet factor 4; platelet glycoprotein Ib α and β chain (GPIbA, GPIbB); PON3, serum paraoxonase/lactonase 3; ProZ, protein Z, vitamin K dependent plasma glycoprotein; RAP1B, Ras-related protein Rap-1b; rFVIII, recombinant FVIII; RP-nanoHPLC mass spec, reversed phase-nano high-performance liquid chromatography mass spectrometry; SDS-PAGE, sodium dodecyl sulfate–polyacrylamide gel electrophoresis; SKAP-2, Src kinase-associated phosphoprotein 2; STEMI, ST-segment elevation myocardial infarction; SWATH-MS, sequential window acquisition of all theoretical mass spectra-mass spectrometry; T2D, type 2 diabetes; THBS1, thrombospondin-1; TIA, transient ischemic attack; TSP1, thrombospondin-1; VTE, venous thromboembolism; vWF, von Willebrand factor.
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Venous Thromboembolism
VTE affects 10 million individuals globally each year and the need for novel predictive biomarkers of VTE is imperative.[15] Two studies from the past 10 years utilized proteomics to identify novel biomarkers associated with VTE incidence in adults.[16] [17] A comprehensive study using plasma proteomics identified platelet-derived growth factor subunit B, a developmental protein, as a novel VTE-associated plasma protein, as well as a potential novel predictive marker of VTE.[16] Proteins ProZ, DJ-1, and transthyretin have also been identified as possible predictive biomarkers of VTE in adults.[17]
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Stroke
Globally, the prevalence of stroke is increasing at an alarming rate[18] and consequently there has been an increasing focus on mechanisms leading to stroke, as well as potential protein markers of clinical outcomes associated with stroke. Three studies used proteomics to investigate mechanisms of stroke and stroke-associated clinical outcomes.[4] [19] [20] Corticosteroid signaling was identified as the main differentiating mechanism between female and male stroke patients. Furthermore, sex-based differences of stroke severity and outcomes were determined using the marker circulating corticosteroid-binding globulin.[20] Proteomics has also shown that transient ischemic attack (TIA) drives changes in coagulation, cell adhesion, atrial fibrillation, and inflammation, and that there are 30 proteins differentially abundant among individuals with TIA in comparison to healthy controls.[19] This finding led to the validation of a plasma protein signature in a proof-of-concept study, identifying IGFBP-3 and PON3 as specific predictors of TIA.[4]
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Therapeutics
Therapeutics, and specifically blood-based therapeutics, are highly complex compounds made up of multiple plasma proteins and diverse cells, and are used to treat clotting deficiencies, such as hemophilia.[21] [22] The complex process involved in producing and manufacturing these therapeutics has been shown to cause several protein variations such as degradation, posttranslational modifications (PTMs) and phosphorylation.[23] Proteomic technologies have not only been used to identify novel protein-drug targets, but also in monitoring the pharmacodynamic effects of therapeutics.[23] In the last decade, proteomics has been used to investigate commercially available recombinant factor VIII, highlighting the excess amount of plasma proteins, such as von Willebrand factor.[22] These findings are important, particularly in the context of monitoring patients undergoing therapeutic treatments.
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Future of Proteomics in Thrombosis and Hemostasis
Proteomics is not only advantageous for the discovery of clinical markers and changes in protein abundance, but also for an array of additional applications, as shown in [Fig. 1]. The last decade has seen proteomics applied to a wide range of clinical settings from investigating commercially available therapeutics,[22] to identifying biomarkers of VTE[16] [17] and understanding the mechanisms associated with ischemic stroke.[20] The use of proteomics, particularly in the clinical setting, is crucial for precision and personalized medicine,[24] enhancing the ability to identify patient-specific therapeutic targets such as proteins and antibodies, and ultimately improving patient outcomes.[25]
With increasing use of proteomics, the discovery of relevant and novel clinical markers associated with diseases or predicting clinical outcomes (e.g., thrombosis or bleeding) is made possible and can be easily and practically translated into the clinical setting. Proteomics can also be used to aid in early-onset disease diagnosis, disease management, and monitoring of therapeutic interventions.[25]
The use of proteomics in the setting of thrombosis and hemostasis poses many advantages. With technological and methodological advancements, the shift from bench to bed-side can be achieved to translate proteomic research findings into the clinical setting and to improve patient outcomes.
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Key Considerations for Proteomics Studies
Similarly to any study, a well-designed proteomics study requires definition of a clear research question and a specific rationale for statistical analysis.[26] Proteomics studies also require a carefully selected population of interest. Proteomes change with age, sex, race, and disease, therefore selecting the most appropriate population prior to undertaking a proteomics study is crucial for accurate interpretation of the proteomic data. Considerations for sample size, specifically for clinical marker studies, should be dependent on the phase of proteomics study being undertaken.
Additionally, the type of sample to be analyzed must be carefully considered when executing a proteomics study. Understanding differences between plasma and serum is critical in choosing which sample type to use. Serum preparation involves activation of coagulation which in turn results in changes in the abundance of not only coagulation proteins, but also proteins involved in inflammation, and as such plasma is the preferred sample of choice for proteomics studies in the setting of hemostasis. By utilizing citrated plasma, it is possible to combine the results of proteomics analysis with functional coagulation assays.
Typical proteomics-based blood marker studies are conducted in three phases: discovery, verification, and validation. The discovery phase requires a small sample size (n = 10–50) and focuses on hundreds to potentially thousands of proteins in an untargeted manner (e.g., SWATH-MS). When it comes to the discovery phase, techniques such as the two-dimensional gel electrophoresis represent an outdated methodology that requires extensive multistep protocols from the sample itself to the generation of mass spectrometry data and have almost exclusively been replaced by liquid chromatography/mass spectrometry (LC/MS) and LC tandem MS (LC/MS/MS) approaches. LC/MS and LC/MS/MS approaches are associated with minimal preanalytical sample processing and maximized protein detection, and are used extensively in proteomics studies, especially in the setting of plasma proteomics. LC/MS/MS allows identification of approximately 500 proteins in a single run, as well as protein isoforms and PTMs.[27]
Verification is then conducted using a more targeted approach (e.g., MRM-MS) with a larger sample size (n = 50–100), focusing on several proteins of interest. Validation studies represent the last phase of clinical proteomics studies and are typically conducted using immunoassays, with a much larger sample size (n = 100–1,000), focusing on a small number of candidate proteins.[28]
These fundamental considerations ensure that results of proteomics studies can be efficiently translated into patient-specific benefits.
When it comes to clinical application of proteomics, recent advances have enabled extremely fast data acquisition. Specifically, plasma proteomes are able to be analyzed across a 1-minute gradient, resulting in identification of 180 proteins, a dataset that includes 47 Food and Drug Administration-approved biomarkers.[29] Combined with the fact that mass spectrometers already have a place in clinical laboratories and are utilized in clinical practice (e.g., newborn screening), it is only a matter of time before proteomics becomes a part of routine practice in the setting of thrombosis and hemostasis.
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Conflict of Interest
None declared.
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References
- 1 Aslam B, Basit M, Nisar MA, Khurshid M, Rasool MH. Proteomics: technologies and their applications. J Chromatogr Sci 2017; 55 (02) 182-196
- 2 Hanash S, Taguchi A. Application of proteomics to cancer early detection. Cancer J 2011; 17 (06) 423-428
- 3 Mebazaa A, Vanpoucke G, Thomas G. et al. Unbiased plasma proteomics for novel diagnostic biomarkers in cardiovascular disease: identification of quiescin Q6 as a candidate biomarker of acutely decompensated heart failure. Eur Heart J 2012; 33 (18) 2317-2324
- 4 Penn AM, Bibok MB, Saly VK. et al; SpecTRA study group. Validation of a proteomic biomarker panel to diagnose minor-stroke and transient ischaemic attack: phase 2 of SpecTRA, a large scale translational study. Biomarkers 2018; 23 (08) 793-803
- 5 Stachowicz A, Zabczyk M, Natorska J. et al. Differences in plasma fibrin clot composition in patients with thrombotic antiphospholipid syndrome compared with venous thromboembolism. Sci Rep 2018; 8 (01) 17301
- 6 Periayah MH, Halim AS, Mat Saad AZ. Mechanism action of platelets and crucial blood coagulation pathways in hemostasis. Int J Hematol Oncol Stem Cell Res 2017; 11 (04) 319-327
- 7 Azcona L, López Farré AJ, Jiménez Mateos-Cáceres P. et al. Impact of clopidogrel and aspirin treatment on the expression of proteins in platelets from type-2 diabetic patients with stable coronary ischemia. J Pharm Sci 2012; 101 (08) 2821-2832
- 8 Vélez P, Ocaranza-Sánchez R, López-Otero D. et al. 2D-DIGE-based proteomic analysis of intracoronary versus peripheral arterial blood platelets from acute myocardial infarction patients: upregulation of platelet activation biomarkers at the culprit site. Proteomics Clin Appl 2016; 10 (08) 851-858
- 9 McCafferty C, Van Den Helm S, Letunica N. et al. Increased platelet activation in SARS-CoV-2 infected non-hospitalised children and adults, and their household contacts. Br J Haematol 2021; 195 (01) 90-94
- 10 Bachmair E-M, Bots ML, Mennen LI. et al. Effect of supplementation with an 80:20 cis9,trans11 conjugated linoleic acid blend on the human platelet proteome. Mol Nutr Food Res 2012; 56 (07) 1148-1159
- 11 Alonso-Orgaz S, Moreno-Luna R, López JA. et al. Proteomic characterization of human coronary thrombus in patients with ST-segment elevation acute myocardial infarction. J Proteomics 2014; 109: 368-381
- 12 Schmitt LR, Henderson R, Barrett A. et al. Mass spectrometry-based molecular mapping of native FXIIIa cross-links in insoluble fibrin clots. J Biol Chem 2019; 294 (22) 8773-8778
- 13 Ząbczyk M, Stachowicz A, Natorska J, Olszanecki R, Wiśniewski JR, Undas A. Plasma fibrin clot proteomics in healthy subjects: relation to clot permeability and lysis time. J Proteomics 2019; 208: 103487
- 14 Bhagwat SR, Hajela K, Bhutada S. et al. Identification of unexplored substrates of the serine protease, thrombin, using N-terminomics strategy. Int J Biol Macromol 2020; 144: 449-459
- 15 ISTH Steering Committee for World Thrombosis Day. Thrombosis: a major contributor to the global disease burden. J Thromb Haemost 2014; 12 (10) 1580-1590
- 16 Bruzelius M, Iglesias MJ, Hong M-G. et al. PDGFB, a new candidate plasma biomarker for venous thromboembolism: results from the VEREMA affinity proteomics study. Blood 2016; 128 (23) e59-e66
- 17 Jensen SB, Hindberg K, Solomon T. et al. Discovery of novel plasma biomarkers for future incident venous thromboembolism by untargeted synchronous precursor selection mass spectrometry proteomics. J Thromb Haemost 2018; 16 (09) 1763-1774
- 18 Gorelick PB. The global burden of stroke: persistent and disabling. Lancet Neurol 2019; 18 (05) 417-418
- 19 Penn AM, Saly V, Trivedi A. et al. Differential proteomics for distinguishing ischemic stroke from controls: a pilot study of the SpecTRA project. Transl Stroke Res 2018; 9 (06) 590-599
- 20 O'Connell GC, Walsh KB, Burrage E, Adeoye O, Chantler PD, Barr TL. High-throughput profiling of the circulating proteome suggests sexually dimorphic corticosteroid signaling following ischemic stroke. Physiol Genomics 2018; 50 (10) 876-883
- 21 Thiele T, Steil L, Völker U, Greinacher A. Proteomics of blood-based therapeutics: a promising tool for quality assurance in transfusion medicine. BioDrugs 2007; 21 (03) 179-193
- 22 Timperio AM, Gevi F, Grazzini G, Vaglio S, Zolla L. Comparison among plasma-derived clotting factor VIII by using monodimensional gel electrophoresis and mass spectrometry. Blood Transfus 2010; 8 (Suppl. 03) s98-s104
- 23 Kimchi-Sarfaty C, Schiller T, Hamasaki-Katagiri N, Khan MA, Yanover C, Sauna ZE. Building better drugs: developing and regulating engineered therapeutic proteins. Trends Pharmacol Sci 2013; 34 (10) 534-548
- 24 Duarte TT, Spencer CT. Personalized proteomics: the future of precision medicine. Proteomes 2016; 4 (04) 29
- 25 Clarke W, Zhang Z, Chan DW. The application of clinical proteomics to cancer and other diseases. Clin Chem Lab Med 2003; 41 (12) 1562-1570
- 26 Ignjatovic V, Geyer PE, Palaniappan KK. et al. Mass spectrometry-based plasma proteomics: considerations from sample collection to achieving translational data. J Proteome Res 2019; 18 (12) 4085-4097
- 27 Deutsch EW, Omenn GS, Sun Z. et al. Advances and utility of the human plasma proteome. J Proteome Res 2021; 20 (12) 5241-5263
- 28 Geyer PE, Holdt LM, Teupser D, Mann M. Revisiting biomarker discovery by plasma proteomics. Mol Syst Biol 2017; 13 (09) 942
- 29 Messner CB, Demichev V, Bloomfield N. et al. Ultra-fast proteomics with Scanning SWATH. Nat Biotechnol 2021; 39 (07) 846-854
Address for correspondence
Publication History
Received: 10 October 2021
Accepted: 03 November 2021
Accepted Manuscript online:
09 November 2021
Article published online:
29 December 2021
© 2021. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
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References
- 1 Aslam B, Basit M, Nisar MA, Khurshid M, Rasool MH. Proteomics: technologies and their applications. J Chromatogr Sci 2017; 55 (02) 182-196
- 2 Hanash S, Taguchi A. Application of proteomics to cancer early detection. Cancer J 2011; 17 (06) 423-428
- 3 Mebazaa A, Vanpoucke G, Thomas G. et al. Unbiased plasma proteomics for novel diagnostic biomarkers in cardiovascular disease: identification of quiescin Q6 as a candidate biomarker of acutely decompensated heart failure. Eur Heart J 2012; 33 (18) 2317-2324
- 4 Penn AM, Bibok MB, Saly VK. et al; SpecTRA study group. Validation of a proteomic biomarker panel to diagnose minor-stroke and transient ischaemic attack: phase 2 of SpecTRA, a large scale translational study. Biomarkers 2018; 23 (08) 793-803
- 5 Stachowicz A, Zabczyk M, Natorska J. et al. Differences in plasma fibrin clot composition in patients with thrombotic antiphospholipid syndrome compared with venous thromboembolism. Sci Rep 2018; 8 (01) 17301
- 6 Periayah MH, Halim AS, Mat Saad AZ. Mechanism action of platelets and crucial blood coagulation pathways in hemostasis. Int J Hematol Oncol Stem Cell Res 2017; 11 (04) 319-327
- 7 Azcona L, López Farré AJ, Jiménez Mateos-Cáceres P. et al. Impact of clopidogrel and aspirin treatment on the expression of proteins in platelets from type-2 diabetic patients with stable coronary ischemia. J Pharm Sci 2012; 101 (08) 2821-2832
- 8 Vélez P, Ocaranza-Sánchez R, López-Otero D. et al. 2D-DIGE-based proteomic analysis of intracoronary versus peripheral arterial blood platelets from acute myocardial infarction patients: upregulation of platelet activation biomarkers at the culprit site. Proteomics Clin Appl 2016; 10 (08) 851-858
- 9 McCafferty C, Van Den Helm S, Letunica N. et al. Increased platelet activation in SARS-CoV-2 infected non-hospitalised children and adults, and their household contacts. Br J Haematol 2021; 195 (01) 90-94
- 10 Bachmair E-M, Bots ML, Mennen LI. et al. Effect of supplementation with an 80:20 cis9,trans11 conjugated linoleic acid blend on the human platelet proteome. Mol Nutr Food Res 2012; 56 (07) 1148-1159
- 11 Alonso-Orgaz S, Moreno-Luna R, López JA. et al. Proteomic characterization of human coronary thrombus in patients with ST-segment elevation acute myocardial infarction. J Proteomics 2014; 109: 368-381
- 12 Schmitt LR, Henderson R, Barrett A. et al. Mass spectrometry-based molecular mapping of native FXIIIa cross-links in insoluble fibrin clots. J Biol Chem 2019; 294 (22) 8773-8778
- 13 Ząbczyk M, Stachowicz A, Natorska J, Olszanecki R, Wiśniewski JR, Undas A. Plasma fibrin clot proteomics in healthy subjects: relation to clot permeability and lysis time. J Proteomics 2019; 208: 103487
- 14 Bhagwat SR, Hajela K, Bhutada S. et al. Identification of unexplored substrates of the serine protease, thrombin, using N-terminomics strategy. Int J Biol Macromol 2020; 144: 449-459
- 15 ISTH Steering Committee for World Thrombosis Day. Thrombosis: a major contributor to the global disease burden. J Thromb Haemost 2014; 12 (10) 1580-1590
- 16 Bruzelius M, Iglesias MJ, Hong M-G. et al. PDGFB, a new candidate plasma biomarker for venous thromboembolism: results from the VEREMA affinity proteomics study. Blood 2016; 128 (23) e59-e66
- 17 Jensen SB, Hindberg K, Solomon T. et al. Discovery of novel plasma biomarkers for future incident venous thromboembolism by untargeted synchronous precursor selection mass spectrometry proteomics. J Thromb Haemost 2018; 16 (09) 1763-1774
- 18 Gorelick PB. The global burden of stroke: persistent and disabling. Lancet Neurol 2019; 18 (05) 417-418
- 19 Penn AM, Saly V, Trivedi A. et al. Differential proteomics for distinguishing ischemic stroke from controls: a pilot study of the SpecTRA project. Transl Stroke Res 2018; 9 (06) 590-599
- 20 O'Connell GC, Walsh KB, Burrage E, Adeoye O, Chantler PD, Barr TL. High-throughput profiling of the circulating proteome suggests sexually dimorphic corticosteroid signaling following ischemic stroke. Physiol Genomics 2018; 50 (10) 876-883
- 21 Thiele T, Steil L, Völker U, Greinacher A. Proteomics of blood-based therapeutics: a promising tool for quality assurance in transfusion medicine. BioDrugs 2007; 21 (03) 179-193
- 22 Timperio AM, Gevi F, Grazzini G, Vaglio S, Zolla L. Comparison among plasma-derived clotting factor VIII by using monodimensional gel electrophoresis and mass spectrometry. Blood Transfus 2010; 8 (Suppl. 03) s98-s104
- 23 Kimchi-Sarfaty C, Schiller T, Hamasaki-Katagiri N, Khan MA, Yanover C, Sauna ZE. Building better drugs: developing and regulating engineered therapeutic proteins. Trends Pharmacol Sci 2013; 34 (10) 534-548
- 24 Duarte TT, Spencer CT. Personalized proteomics: the future of precision medicine. Proteomes 2016; 4 (04) 29
- 25 Clarke W, Zhang Z, Chan DW. The application of clinical proteomics to cancer and other diseases. Clin Chem Lab Med 2003; 41 (12) 1562-1570
- 26 Ignjatovic V, Geyer PE, Palaniappan KK. et al. Mass spectrometry-based plasma proteomics: considerations from sample collection to achieving translational data. J Proteome Res 2019; 18 (12) 4085-4097
- 27 Deutsch EW, Omenn GS, Sun Z. et al. Advances and utility of the human plasma proteome. J Proteome Res 2021; 20 (12) 5241-5263
- 28 Geyer PE, Holdt LM, Teupser D, Mann M. Revisiting biomarker discovery by plasma proteomics. Mol Syst Biol 2017; 13 (09) 942
- 29 Messner CB, Demichev V, Bloomfield N. et al. Ultra-fast proteomics with Scanning SWATH. Nat Biotechnol 2021; 39 (07) 846-854