Proteomics in thrombosis research

The Proteome Content of Blood Clots Observed Under Different Conditions: Successful Role in Predicting Clot Amyloid(ogenicity)

A recent analysis compared the proteome of (i) blood clots seen in two diseases-sepsis and long COVID-when blood was known to have clotted into an amyloid microclot form (as judged by staining with the fluorogenic amyloid stain thioflavin T) with (ii) that of those non-amyloid clots considered to have formed normally. Such fibrinaloid microclots are also relatively resistant to fibrinolysis. The proteins that the amyloid microclots contained differed markedly both from the soluble proteome of typical plasma and that of normal clots, and also between the diseases studied (an acute syndrome in the form of sepsis in an ITU and a chronic disease represented by Long COVID). Many proteins in the amyloid microclots were low in concentration in plasma and were effectively accumulated into the fibres, whereas many other abundant plasma proteins were excluded. The proteins found in the microclots associated with the diseases also tended to be themselves amyloidogenic. We here ask effectively the inverse question. This is: can the clot proteome tell us whether the clots associated with a particular disease contained proteins that are observed uniquely (or are highly over-represented) in known amyloid clots relative to normal clots, and thus were in fact amyloid in nature? The answer is in the affirmative in a variety of major coagulopathies, viz., venous thromboembolism, pulmonary embolism, deep vein thrombosis, various cardiac issues, and ischaemic stroke. Galectin-3-binding protein and thrombospondin-1 seem to be especially widely associated with amyloid-type clots, and the latter has indeed been shown to be incorporated into growing fibrin fibres. These may consequently provide useful biomarkers with a mechanistic basis.

Exploration of the plasma proteomic profile of patients at risk of thromboembolic events

Background

The elevated health burden of thromboembolic events necessitates development of blood-based risk monitoring tools.

Objectives

We explored the potential of mass spectrometry-based plasma proteomics to provide insights into underlying plasma protein signatures associated with treatment and occurrence of thromboembolic events.

Methods

Utilizing a high-throughput, data-independent acquisition, discovery-based proteomics workflow, we analyzed 434 plasma proteomes from different groups of individuals with elevated risk of thromboembolic events, including individuals I) on vitamin K antagonists (VKAs; n = 130), II) with a prior venous thromboembolism (n = 10), III) with acute cerebral venous sinus thrombosis (n = 10, and IV) with SARS-CoV-2 infection (n = 67). Plasma protein levels measured with mass spectrometry were correlated with international normalized ratio and conventional clinical laboratory measurements. Plasma profile differences between different groups were assessed using principal component analysis, moderated t-test, and clustering analysis.

Results

Plasma protein levels were in agreement with conventional clinical laboratory parameters, including albumin and fibrinogen. Levels of vitamin K-dependent proteins inversely correlated with international normalized ratio. In the individual studies, we found decreased levels of vitamin K-dependent coagulation proteins in patients on VKAs, alterations in inflammatory signatures among CVST patients and a distinctive signature indicative of SARS-CoV-2 infection. However, no protein signature associated with a thromboembolic event could be identified neither in individual nor combined studies.

Conclusion

Although VKA treatment-specific and disease-specific signatures were captured, our study highlights that the challenges of discovering biomarkers in patients at risk of thromboembolic events lie in the heterogeneity of individual plasma profiles in relation to treatment and etiology.

Quantitative protein mass spectrometry for multiplex measurement of coagulation and fibrinolytic proteins towards clinical application: What, why and how?

Plasma proteins involved in coagulation and fibrinolysis are essential to hemostasis. Consequently, their circulating levels and functionality are critical in bleeding and thrombosis development. Well-established laboratory tests to assess these are available; however, said tests do not allow high multiplicity, require large volumes of plasma and are often costly. A novel technology to quantify plasma proteins is quantitative protein mass spectrometry (QPMS). Aided by stable isotope-labeled internal standards a large number of proteins can be quantified in one single analytical run requiring <30 μL of plasma. This provides an opportunity to improve insight in the etiology and prognosis of bleeding and thrombotic disorders, in which the balance between different proteins plays a crucial role. This manuscript aims to give an overview of the QPMS potential applications in thrombosis and hemostasis research (quantifying the 38 proteins assigned to coagulation and fibrinolysis by the KEGG database), but also to explore the potential and hurdles if designed for clinical practice. Advantages and limitations of QPMS are described and strategies for improved analysis are proposed, using as an example the test requirements for antithrombin. Application of this technology in the future could represent a step towards individualized patient care.

Overall haemostatic potential assay for prediction of outcomes in venous and arterial thrombosis and thrombo-inflammatory diseases

Thromboembolic diseases including arterial and venous thrombosis are common causes of morbidity and mortality globally. Thrombosis frequently recurs and can also complicate many inflammatory conditions through the process of 'thrombo-inflammation,' as evidenced during the COVID-19 pandemic. Current candidate biomarkers for thrombosis prediction, such as D-dimer, have poor predictive efficacy. This limits our capacity to tailor anticoagulation duration individually and may expose lower risk individuals to undue bleeding risk. Global coagulation assays, such as the Overall Haemostatic Potential (OHP) assay, that investigate fibrin generation and fibrinolysis, may provide a more accurate and functional assessment of hypercoagulability. We present a review of fibrin's critical role as a central modulator of thrombotic risk. The results of our studies demonstrating the OHP assay as a predictive biomarker in venous thromboembolism, chronic renal disease, diabetes mellitus, post-thrombotic syndrome, and COVID-19 are discussed. As a comprehensive and global measurement of fibrin generation and fibrinolytic capacity, the OHP assay may be a valuable addition to future multi-modal predictive tools in thrombosis.

Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis

Comprehensive protein analyses of plasma are made possible by high-throughput proteomic screens, which may help find new therapeutic targets and diagnostic biomarkers. Patients with cancer are frequently affected by venous thromboembolism (VTE). The limited predictive accuracy of current VTE risk assessment tools highlights the need for new, more targeted biomarkers. Although coagulation biomarkers for the diagnosis, prognosis, and treatment of VTE have been investigated, none of them have the necessary clinical validation or diagnostic accuracy. Proteomics holds the potential to uncover new biomarkers and thrombotic pathways that impact the risk of thrombosis. This review explores the fundamental methods used in proteomics and focuses on particular biomarkers found in VTE and cancer-associated thrombosis.

Oncogenes and cancer associated thrombosis: what can we learn from single cell genomics about risks and mechanisms?

Single cell analysis of cancer cell transcriptome may shed a completely new light on cancer-associated thrombosis (CAT). CAT causes morbid, and sometimes lethal complications in certain human cancers known to be associated with high risk of venous thromboembolism (VTE), pulmonary embolism (PE) or arterial thromboembolism (ATE), all of which worsen patients' prognosis. How active cancers drive these processes has long evaded scrutiny. While "unspecific" microenvironmental effects and consequences of patient care (e.g., chemotherapy) have been implicated in pathogenesis of CAT, it has also been suggested that oncogenic pathways driven by either genetic (mutations), or epigenetic (methylation) events may influence the coagulant phenotype of cancer cells and stroma, and thereby modulate the VTE/PE risk. Consequently, the spectrum of driver events and their downstream effector mechanisms may, to some extent, explain the heterogeneity of CAT manifestations between cancer types, molecular subtypes, and individual cases, with thrombosis-promoting, or -protective mutations. Understanding this molecular causation is important if rationally designed countermeasures were to be deployed to mitigate the clinical impact of CAT in individual cancer patients. In this regard, multi-omic analysis of human cancers, especially at a single cell level, has brought a new meaning to concepts of cellular heterogeneity, plasticity, and multicellular complexity of the tumour microenvironment, with profound and still relatively unexplored implications for the pathogenesis of CAT. Indeed, cancers may contain molecularly distinct cellular subpopulations, or dynamic epigenetic states associated with different profiles of coagulant activity. In this article we discuss some of the relevant lessons from the single cell "omics" and how they could unlock new potential mechanisms through which cancer driving oncogenic lesions may modulate CAT, with possible consequences for patient stratification, care, and outcomes.