Longitudinal RNA-Seq Analysis of the Repeatability of Gene Expression and Splicing in Human Platelets Identifies a Platelet SELP Splice QTL

Heterogeneity of platelets and their responses

There has been increasing recognition of heterogeneity in blood platelets and their responses, particularly in recent years, where next-generation technologies and advanced bioinformatic tools that interrogate "big data" have enabled large-scale studies of RNA and protein expression across a growing list of disease states. However, pioneering platelet biologists and clinicians were already hypothesizing upon and investigating heterogeneity in platelet (and megakaryocyte) activity and platelet metabolism and aggregation over half a century ago. Building on their foundational hypotheses, in particular Professor Marian A. Packham's pioneering work and a State of the Art lecture in her memoriam at the 2023 International Society on Thrombosis and Haemostasis Congress by Anandi Krishnan, this review outlines the key features that contribute to the heterogeneity of platelets between and within individuals. Starting with important epidemiologic factors, we move stepwise through successively smaller scales down to heterogeneity revealed by single-cell technologies in health and disease. We hope that this overview will urge future scientific and clinical studies to recognize and account for heterogeneity of platelets and aim to apply methods that capture that heterogeneity. Finally, we summarize other exciting new data presented on this topic at the 2023 International Society on Thrombosis and Haemostasis Congress.

Mitofusin-2 Regulates Platelet Mitochondria and Function

BACKGROUND

Single-nucleotide polymorphisms linked with the rs1474868 T allele (MFN2 [mitofusin-2] T/T) in the human mitochondrial fusion protein MFN2 gene are associated with reduced platelet MFN2 RNA expression and platelet counts. This study investigates the impact of MFN2 on megakaryocyte and platelet biology.

METHODS

Mice with megakaryocyte/platelet deletion of Mfn2 (Mfn2-/- [Mfn2 conditional knockout]) were generated using Pf4-Cre crossed with floxed Mfn2 mice. Human megakaryocytes were generated from cord blood and platelets isolated from healthy subjects genotyped for rs1474868. Ex vivo approaches assessed mitochondrial morphology, function, and platelet activation responses. In vivo measurements included endogenous/transfused platelet life span, tail bleed time, transient middle cerebral artery occlusion, and pulmonary vascular permeability/hemorrhage following lipopolysaccharide-induced acute lung injury.

RESULTS

Mitochondria was more fragmented in megakaryocytes derived from Mfn2-/- mice and from human cord blood with MFN2 T/T genotype compared with control megakaryocytes. Human resting platelets of MFN2 T/T genotype had reduced MFN2 protein, diminished mitochondrial membrane potential, and an increased rate of phosphatidylserine exposure during ex vivo culture. Platelet counts and platelet life span were reduced in Mfn2-/- mice accompanied by an increased rate of phosphatidylserine exposure in resting platelets, especially aged platelets, during ex vivo culture. Mfn2-/- also decreased platelet mitochondrial membrane potential (basal) and activated mitochondrial oxygen consumption rate, reactive oxygen species generation, calcium flux, platelet-neutrophil aggregate formation, and phosphatidylserine exposure following dual agonist activation. Ultimately, Mfn2-/- mice showed prolonged tail bleed times, decreased ischemic stroke infarct size after cerebral ischemia-reperfusion, and exacerbated pulmonary inflammatory hemorrhage following lipopolysaccharide-induced acute lung injury. Analysis of MFN2 SNPs in the iSPAAR study (Identification of SNPs Predisposing to Altered ALI Risk) identified a significant association between MFN2 and 28-day mortality in patients with acute respiratory distress syndrome.

CONCLUSIONS

Mfn2 preserves mitochondrial phenotypes in megakaryocytes and platelets and influences platelet life span, function, and outcomes of stroke and lung injury.

Platelet protein synthesis, regulation, and post-translational modifications: mechanics and function

Dogma had been firmly entrenched in the minds of the scientific community that the anucleate mammalian platelet was incapable of protein biosynthesis since their identification in the late 1880s. These beliefs were not challenged until the 1960s when several reports demonstrated that platelets possessed the capacity to biosynthesize proteins. Even then, many still dismissed the synthesis as trivial and unimportant for at least another two decades. Research in the field expanded after the 1980s and numerous reports have since been published that now clearly demonstrate the potential significance of platelet protein synthesis under normal, pathological, and activating conditions. It is now clear that the platelet proteome is not a static entity but can be altered slowly or rapidly in response to external signals to support physiological requirements to maintain hemostasis and other biological processes. All the necessary biological components to support protein synthesis have been identified in platelets along with post-transcriptional processing of mRNAs, regulators of translation, and post-translational modifications such as glycosylation. The last comprehensive review of the subject appeared in 2009 and much work has been conducted since that time. The current review of the field will briefly incorporate the information covered in earlier reviews and then bring the reader up to date with more recent findings.

Autophagy and its consequences for platelet biology

Autophagy, the continuous recycling of intracellular building blocks, molecules, and organelles is necessary to preserve cellular function and homeostasis. In this context, it was demonstrated that autophagy plays an important role in megakaryopoiesis, the development and differentiation of hematopoietic progenitor cells into megakaryocytes. Furthermore, in recent years, autophagic proteins were detected in platelets, anucleate cells generated by megakaryocytes, responsible for hemostasis, thrombosis, and a key cell in inflammation and host immune responses. In the last decade studies have indicated the occurrence of autophagy in platelets. Moreover, autophagy in platelets was subsequently demonstrated to be involved in platelet aggregation, adhesion, and thrombus formation. Here, we review the current knowledge about autophagy in platelets, its function, and clinical implications. However, at the advent of platelet autophagy research, additional discoveries derived from evolving work will be required to precisely define the contributions of autophagy in platelets, and to expand the ever increasing physiologic and pathologic roles these remarkable and versatile blood cells play.

Sources of variability in the human platelet transcriptome

Platelets are anucleated cells produced by megakaryocytes, from which they inherit all the components necessary to carry their functions. They circulate in blood vessels where they play essential roles in coagulation, wound repair or inflammation, and have been implicated in various pathological conditions such as thrombosis, viral infection or cancer progression. The importance of these cells has been established over a century ago, and effective anti-platelet medications with different mechanisms of action have since been developed. However, these therapies are not always effective and can incur adverse events, thus a better understanding of platelets molecular processes is needed to address these issues and improve our understanding of platelet functions. In recent years, an increasing number of studies have leveraged OMICs technologies to analyze their content and identify molecular signatures and mechanisms associated with platelet functions and platelet related disorders. In particular, the increased accessibility of microarrays and RNA sequencing opened the way for studies of the platelet transcriptome under a wide array of conditions. These studies revealed distinct expression profiles in diverse pathologies, which could lead to the discovery of novel biomarkers and therapeutic targets, and suggests a dynamic transcriptome that could influence platelet mechanisms. In this review, we highlight the different sources of transcript level variability in platelets while summarizing recent advances and discoveries from this emerging field.

PlateletSeq: A novel method for discovery of blood-based biomarkers

Platelets are small circulating fragments of cells that play important roles in thrombosis, haemostasis, immune response, inflammation and cancer growth. Although anucleate, they contain a rich RNA repertoire which offers an opportunity to characterise changes in platelet gene expression in health and disease. Whilst this can be achieved with conventional RNA sequencing, a large input of high-quality RNA, and hence blood volume, is required (unless a pre-amplification step is added), along with specialist bioinformatic skills for data analysis and interpretation. We have developed a transcriptomics next-generation sequencing-based approach that overcomes these limitations. Termed PlateletSeq, this method requires very low levels of RNA input and does not require specialist bioinformatic analytical skills. Here we describe the methodology, from sample collection to processing and data analysis. Specifically, blood samples can be stored for up to 8 days at 4 °C prior to analysis. Platelets are isolated using multi-step centrifugation and a purity of ≤ 1 leucocyte per 0.26x106 platelets is optimal for gene expression analysis. We have applied PlateletSeq to normal adult blood samples and show there are no age-associated variations and only minor gender-associated differences. In contrast, platelets from patients with myeloproliferative neoplasms show differences in platelet transcript profiles from normal and between disease subtypes. This illustrates the potential applicability of PlateletSeq for biomarker discovery and studying platelet biology in patient samples. It also opens avenues for assessing platelet quality in other fields such as transfusion research.

Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

ISLET: individual-specific reference panel recovery improves cell-type-specific inference

We propose a statistical framework ISLET to infer individual-specific and cell-type-specific transcriptome reference panels. ISLET models the repeatedly measured bulk gene expression data, to optimize the usage of shared information within each subject. ISLET is the first available method to achieve individual-specific reference estimation in repeated samples. Using simulation studies, we show outstanding performance of ISLET in the reference estimation and downstream cell-type-specific differentially expressed genes testing. We apply ISLET to longitudinal transcriptomes profiled from blood samples in a large observational study of young children and confirm the cell-type-specific gene signatures for pancreatic islet autoantibody. ISLET is available at https://bioconductor.org/packages/ISLET .

Applications of Artificial Intelligence in Philadelphia-Negative Myeloproliferative Neoplasms

Philadelphia-negative (Ph-) myeloproliferative neoplasms (MPNs) are a group of hematopoietic malignancies identified by clonal proliferation of blood cell lineages and encompasses polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). The clinical and laboratory features of Philadelphia-negative MPNs are similar, making them difficult to diagnose, especially in the preliminary stages. Because treatment goals and progression risk differ amongst MPNs, accurate classification and prognostication are critical for optimal management. Artificial intelligence (AI) and machine learning (ML) algorithms provide a plethora of possible tools to clinicians in general, and particularly in the field of malignant hematology, to better improve diagnosis, prognosis, therapy planning, and fundamental knowledge. In this review, we summarize the literature discussing the application of AI and ML algorithms in patients with diagnosed or suspected Philadelphia-negative MPNs. A literature search was conducted on PubMed/MEDLINE, Embase, Scopus, and Web of Science databases and yielded 125 studies, out of which 17 studies were included after screening. The included studies demonstrated the potential for the practical use of ML and AI in the diagnosis, prognosis, and genomic landscaping of patients with Philadelphia-negative MPNs.

A narrative review for platelets and their RNAs in cancers: New concepts and clinical perspectives

Recent years have witnessed a growing body of evidence suggesting that platelets are involved in several stages of the metastatic process via direct or indirect interactions with cancer cells, contributing to the progression of neoplastic malignancies. Cancer cells can dynamically exchange components with platelets in and out of blood vessels, and directly phagocytose platelets to hijack their proteome, transcriptome, and secretome, or be remotely regulated by metabolites or microparticles released by platelets, resulting in phenotypic, genetic, and functional modifications. Moreover, platelet interactions with stromal and immune cells in the tumor microenvironment lead to alterations in their components, including the ribonucleic acid (RNA) profile, and complicate the impact of platelets on cancers. A deeper understanding of the roles of platelets and their RNAs in cancer will contribute to the development of anticancer strategies and the optimization of clinical management. Encouragingly, advances in high-throughput sequencing, bioinformatics data analysis, and machine learning have allowed scientists to explore the potential of platelet RNAs for cancer diagnosis, prognosis, and guiding treatment. However, the clinical application of this technique remains controversial and requires larger, multicenter studies with standardized protocols. Here, we integrate the latest evidence to provide a broader insight into the role of platelets in cancer progression and management, and propose standardized recommendations for the clinical utility of platelet RNAs to facilitate translation and benefit patients.

A New Role of NAP1L1 in Megakaryocytes and Human Platelets

Platelets (PLTs) are anucleate and considered incapable of nuclear functions. Contrastingly, nuclear proteins were detected in human PLTs. For most of these proteins, it is unclear if nuclear or alternatively assigned functions are performed, a question we wanted to address for nuclear assembly protein 1like 1 (NAP1L1). Using a wide array of molecular methods, including RNAseq, co-IP, overexpression and functional assays, we explored expression pattern and functionality of NAP1L1 in PLTs, and CD34⁺-derived megakaryocytes (MKs). NAP1L1 is expressed in PLTs and MKs. Co-IP experiments revealed that dihydrolipolylysine-residue acetyltransferase (DLAT encoded protein PDC-E2, ODP2) dynamically interacts with NAP1L1. PDC-E2 is part of the mitochondrial pyruvate-dehydrogenase (PDH) multi-enzyme complex, playing a crucial role in maintaining cellular respiration, and promoting ATP-synthesis via the respiratory chain. Since altered mitochondrial function is a hallmark of infectious syndromes, we analyzed PDH activity in PLTs from septic patients demonstrating increased activity, paralleling NAP1L1 expression levels. MKs PDH activity decreased following an LPS-challenge. Furthermore, overexpression of NAP1L1 significantly altered the ability of MKs to form proplatelet extensions, diminishing thrombopoiesis. These results indicate that NAP1L1 performs in other than nucleosome-assembly functions in PTLs and MKs, binding a key mitochondrial protein as a potential chaperone, and gatekeeper, influencing PDH activity and thrombopoiesis.

Identification of potential immune/diagnosis related gene-immunocyte subtype networks in extracellular immune response to respiratory syncytial virus infection

INTRODUCTION

Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The diagnostic model based on hub genes and machine learning makes it possible to diagnose the extracellular immune response to RSV infection early.

OBJECTIVE

The aim of the present study was to identify potential immune, diagnose and treatment related genes expressed in RSV-infected cells.

METHODS

Firstly, gene expression data were downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Secondly, WGCNA was performed based on DEGs to obtain hub genes related to immunity score. Thirdly, protein-protein interaction (PPI) and the immune infiltration analysis of hub immune related genes were performed. Finally, diagnostic and immune related genes were identified by machine learning, followed by functional analysis.

RESULTS

Totally, 2063 DEGs were identified in the extracellular immune response to RSV infection. Among which, 10 key immune and diagnosis related genes were identified, including ITGA2B, GP9, ITGB3, SELP, PPBP, MPL, CXCL8, NFE2, PTGS1 and LY6G6F. Several immune/diagnosis related gene-immunocyte subtype networks were identified, such as CXCL8-Type 17 T helper cell, LY6G6F-CD56 bright natural killer cell, PPBP-activated CD4 T cell/T follicular helper cell, NFE2/PTGS1/SELP-activated dendritic cell, GP9/ITGA2B/MPL-activated CD8 T cell. ITGB3, MPL and PTGS1 could be considered as therapeutic targets. Some significantly enriched signaling pathways were identified, including hematopoietic cell lineage (involving GP9 and ITGA2B), cytokine-cytokine receptor interaction (involving MPL), chemokine signaling pathway (involving PPBP) and arachidonic acid metabolism (involving PTGS1).

CONCLUSIONS

The 10-immune related gene signature may be used as potential diagnostic markers for the extracellular immune response to RSV infection, which may provide a new field in searching for diagnostic and therapeutic molecules in the extracellular immune response to RSV infection.

Evaluate the immune-related eRNA models and signature score to predict the response to immunotherapy in thyroid carcinoma

BACKGROUND

The functional alterations of eRNAs have been reported to be correlated with tumorigenesis. However, the roles of eRNAs in thyroid cancer (THCA) remain still unclear. This study aimed to construct an immune-related eRNA prognostic signature that could effectively predict the survival and prognosis for THCA.

METHODS

The Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify THCA-specific immune-related hub genes and immune-related eRNAs were obtained using Pearson correlation analysis. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression were conducted to construct an immune-related eRNA prognostic signature in training cohort, and the predictive capability was verified in test cohort and entire cohort. Kaplan-Meier analysis, principal component analysis (PCA), receiver operating characteristic (ROC) curves, and nomogram were used to validate the risk signature. Furthermore, CIBERSORT, ESTIMATE and ssGSEA were analyzed to explore the tumor immune microenvironment (TIME) of the risk signature, and the response of potential immunotherapeutic were also discussed.

RESULTS

A total of 125 immune-related eRNAs were obtained and 16 immune-related eRNAs were significantly correlated with overall survival (OS). A 9-immune-related eRNA prognostic signature was constructed, and the risk score was identified as an independent predictor. High-risk groups were associated with a poorer OS. Immune microenvironment analysis indicated that low risk score was correlated with higher immuneScore, high immune cell infiltration, and the better response of immunotherapy. Additionally, we also detected 9 immune-related eRNA expression levels in sixty-two matched tumorous and non-tumorous tissues using qRT-PCR analysis.

CONCLUSION

Our immune-related eRNA risk signature that was an independent prognostic factor was strongly correlated with the immune microenvironment and may be promising for the clinical prediction of prognosis and immunotherapeutic responses in THCA patients.

Aspirin for the Primary Prevention of Cardiovascular Disease: Time for a Platelet-Guided Approach

Aspirin protects against atherothrombosis while increasing the risk of major bleeding. Although it is widely used to prevent cardiovascular disease (CVD), its benefit does not outweigh its risk for primary CVD prevention in large population settings. The recent United States Preventive Services Task Force guidelines on aspirin use to prevent CVD reflect this clinical tradeoff as well as the persistent struggle to define a population that would benefit from prophylactic aspirin therapy. Past clinical trials of primary CVD prevention with aspirin have not included consideration of a biomarker relevant to aspirin's mechanism of action, platelet inhibition. This approach is at odds with the paradigm used in other key areas of pharmacological CVD prevention, including antihypertensive and statin therapy, which combine cardiovascular risk assessment with the measurement of mechanistic biomarkers (eg, blood pressure and LDL [low-density lipoprotein]-cholesterol). Reliable methods for quantifying platelet activity, including light transmission aggregometry and platelet transcriptomics, exist and should be considered to identify individuals at elevated cardiovascular risk due to a hyperreactive platelet phenotype. Therefore, we propose a new, platelet-guided approach to the study of prophylactic aspirin therapy. We think that this new approach will reveal a population with hyperreactive platelets who will benefit most from primary CVD prevention with aspirin and usher in a new era of precision-guided antiplatelet therapy.

A method based on plateletpheresis to obtain functional platelet, CD3+ and CD14+ matched populations for research immunological studies

BACKGROUND

In previous studies with peripheral blood cells, platelet factors were found to be associated with severe allergic phenotypes. A reliable method yielding highly concentrated and pure platelet samples is usually not available for immunological studies. Plateletpheresis is widely used in the clinics for donation purposes. In this study, we designed a protocol based on plateletpheresis to obtain Platelet-Rich Plasma (PRP), Platelet-Poor Plasma (PPP) as well as CD3⁺ and CD14⁺ cells matched samples from a waste plateletpheresis product for immunological studies.

METHODS

Twenty-seven subjects were voluntarily subjected to plateletpheresis. PRP, PPP and blood cell concentrate contained in a leukocyte reduction system chamber (LRSC) were obtained in this process. CD3⁺ and CD14⁺ cells were isolated from the LRSC by density-gradient centrifugation and positive magnetic bead isolation. RNA was isolated from PRP, CD3⁺ and CD14⁺ cell samples and used for transcriptomic studies by Affymetrix. PRP and PPP samples were used for platelet protein quantification by multiplex assays.

RESULTS

A reliable high yield method to obtain matched samples of PRP, PPP, CD3⁺ and CD14⁺ from a single donor for RNA and protein analyses has been designed. The RNA quality indicators (RQI) routinely used for other cell types were not suitable for platelet RNA characterization. Despite this, the platelet RNA was valid for transcriptomic studies by Affymetrix, as platelet transcripts obtained in our previous studies were confirmed in PRP samples. Platelet samples were enriched in platelet factors as determined in protein multiplex analysis.

CONCLUSIONS

We have developed a method that yields not only high content and pure platelet samples from a single donor but also CD3⁺ and CD14⁺ matched samples that can be used for RNA and protein analyses in immunological studies.

Cardiac megakaryocytes in SARS-CoV-2 positive autopsies

Thromboembolic phenomena are an important complication of infection by severe acute respiratory coronavirus 2 (SARS‐CoV‐2). Increasing focus on the management of the thrombotic complications of Coronavirus Disease 2019 (COVID‐19) has led to further investigation into the role of platelets, and their precursor cell, the megakaryocyte, during the disease course. Previously published postmortem evaluations of patients who succumbed to COVID‐19 have reported the presence of megakaryocytes in the cardiac microvasculature. Our series evaluated a cohort of autopsies performed on SARS‐CoV‐2‐positive patients in 2020 (n = 36) and prepandemic autopsies performed in early 2020 (n = 12) and selected to represent comorbidities common in cases of severe COVID‐19, in addition to infectious and noninfectious pulmonary disease and thromboembolic phenomena. Cases were assessed for the presence of cardiac megakaryocytes and correlated with the presence of pulmonary emboli and laboratory platelet parameters and inflammatory markers. Cardiac megakaryocytes were detected in 64% (23/36) of COVID‐19 autopsies, and 40% (5/12) prepandemic autopsies, with averages of 1.77 and 0.84 megakaryocytes per cm², respectively. Within the COVID‐19 cohort, autopsies with detected megakaryocytes had significantly higher platelet counts compared with cases throughout; other platelet parameters were not statistically significant between groups. Although studies have supported a role of platelets and megakaryocytes in the response to viral infections, including SARS‐CoV‐2, our findings suggest cardiac megakaryocytes may be representative of a nonspecific inflammatory response and are frequent in, but not exclusive to, COVID‐19 autopsies.

Identification of Novel Therapeutic Candidates Against SARS-CoV-2 Infections: An Application of RNA Sequencing Toward mRNA Based Nanotherapeutics

Due to fast transmission and various circulating SARS-CoV-2 variants, a significant increase of coronavirus 2019 infection cases with acute respiratory symptoms has prompted worries about the efficiency of current vaccines. The possible evasion from vaccine immunity urged scientists to identify novel therapeutic targets for developing improved vaccines to manage worldwide COVID-19 infections. Our study sequenced pooled peripheral blood mononuclear cells transcriptomes of SARS-CoV-2 patients with moderate and critical clinical outcomes to identify novel potential host receptors and biomarkers that can assist in developing new translational nanomedicines and vaccine therapies. The dysregulated signatures were associated with humoral immune responses in moderate and critical patients, including B-cell activation, cell cycle perturbations, plasmablast antibody processing, adaptive immune responses, cytokinesis, and interleukin signaling pathway. The comparative and longitudinal analysis of moderate and critically infected groups elucidated diversity in regulatory pathways and biological processes. Several immunoglobin genes (IGLV9-49, IGHV7-4, IGHV3-64, IGHV1-24, IGKV1D-12, and IGKV2-29), ribosomal proteins (RPL29, RPL4P2, RPL5, and RPL14), inflammatory response related cytokines including Tumor Necrosis Factor (TNF, TNFRSF17, and TNFRSF13B), C-C motif chemokine ligands (CCL3, CCL25, CCL4L2, CCL22, and CCL4), C-X-C motif chemokine ligands (CXCL2, CXCL10, and CXCL11) and genes related to cell cycle process and DNA proliferation (MYBL2, CDC20, KIFC1, and UHCL1) were significantly upregulated among SARS-CoV-2 infected patients. 60S Ribosomal protein L29 (RPL29) was a highly expressed gene among all COVID-19 infected groups. Our study suggested that identifying differentially expressed genes (DEGs) based on disease severity and onset can be a powerful approach for identifying potential therapeutic targets to develop effective drug delivery systems against SARS-CoV-2 infections. As a result, potential therapeutic targets, such as the RPL29 protein, can be tested in vivo and in vitro to develop future mRNA-based translational nanomedicines and therapies to combat SARS-CoV-2 infections.

Platelet proteome reveals features of cell death, antiviral response and viral replication in covid-19

Coronavirus disease 2019 (COVID-19) has affected over 400 million people worldwide, leading to 6 million deaths. Among the complex symptomatology of COVID-19, hypercoagulation and thrombosis have been described to directly contribute to lethality, pointing out platelets as an important SARS-CoV-2 target. In this work, we explored the platelet proteome of COVID-19 patients through a label-free shotgun proteomics approach to identify platelet responses to infection, as well as validation experiments in a larger patient cohort. Exclusively detected proteins (EPs) and differentially expressed proteins (DEPs) were identified in the proteomic dataset and thus classified into biological processes to map pathways correlated with pathogenesis. Significant changes in the expression of proteins related to platelet activation, cell death, and antiviral response through interferon type-I were found in all patients. Since the outcome of COVID-19 varies highly among individuals, we also performed a cross-comparison of proteins found in survivors and nonsurvivors. Proteins belonging to the translation pathway were strongly highlighted in the nonsurvivor group. Moreover, the SARS-CoV-2 genome was fully sequenced in platelets from five patients, indicating viral internalization and preprocessing, with CD147 as a potential entry route. In summary, platelets play a significant role in COVID-19 pathogenesis via platelet activation, antiviral response, and disease severity.

The Analysis of the Human Megakaryocyte and Platelet Coding Transcriptome in Healthy and Diseased Subjects

Platelets are generated and released into the bloodstream from their precursor cells, megakaryocytes that reside in the bone marrow. Though platelets have no nucleus or DNA, they contain a full transcriptome that, during platelet formation, is transported from the megakaryocyte to the platelet. It has been described that transcripts in platelets can be translated into proteins that influence platelet response. The platelet transcriptome is highly dynamic and has been extensively studied using microarrays and, more recently, RNA sequencing (RNA-seq) in relation to diverse conditions (inflammation, obesity, cancer, pathogens and others). In this review, we focus on bulk and single-cell RNA-seq studies that have aimed to characterize the coding transcriptome of healthy megakaryocytes and platelets in humans. It has been noted that bulk RNA-seq has limitations when studying in vitro-generated megakaryocyte cultures that are highly heterogeneous, while single-cell RNA-seq has not yet been applied to platelets due to their very limited RNA content. Next, we illustrate how these methods can be applied in the field of inherited platelet disorders for gene discovery and for unraveling novel disease mechanisms using RNA from platelets and megakaryocytes and rare disease bioinformatics. Next, future perspectives are discussed on how this field of coding transcriptomics can be integrated with other next-generation technologies to decipher unexplained inherited platelet disorders in a multiomics approach.

Co-expression analysis to identify key modules and hub genes associated with COVID-19 in platelets

Corona virus disease 2019 (COVID-19) increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The underlying pathophysiological processes are complex, and remain poorly understood. To this end, platelets play important roles in regulating the cardiovascular system, including via contributions to coagulation and inflammation. There is ample evidence that circulating platelets are activated in COVID-19 patients, which is a primary driver of the observed thrombotic outcome. However, the comprehensive molecular basis of platelet activation in COVID-19 disease remains elusive, which warrants more investigation. Hence, we employed gene co-expression network analysis combined with pathways enrichment analysis to further investigate the aforementioned issues. Our study revealed three important gene clusters/modules that were closely related to COVID-19. These cluster of genes successfully identify COVID-19 cases, relative to healthy in a separate validation data set using machine learning, thereby validating our findings. Furthermore, enrichment analysis showed that these three modules were mostly related to platelet metabolism, protein translation, mitochondrial activity, and oxidative phosphorylation, as well as regulation of megakaryocyte differentiation, and apoptosis, suggesting a hyperactivation status of platelets in COVID-19. We identified the three hub genes from each of three key modules according to their intramodular connectivity value ranking, namely: COPE, CDC37, CAPNS1, AURKAIP1, LAMTOR2, GABARAP MT-ND1, MT-ND5, and MTRNR2L12. Collectively, our results offer a new and interesting insight into platelet involvement in COVID-19 disease at the molecular level, which might aid in defining new targets for treatment of COVID-19–induced thrombosis.

Inference on the structure of gene regulatory networks

In this paper, we conduct theoretical analyses on inferring the structure of gene regulatory networks. Depending on the experimental method and data type, the inference problem is classified into 20 different scenarios. For each scenario, we discuss the problem that with enough data, under what assumptions, what can be inferred about the structure. For scenarios that have been covered in the literature, we provide a brief review. For scenarios that have not been covered in literature, if the structure can be inferred, we propose new mathematical inference methods and evaluate them on simulated data. Otherwise, we prove that the structure cannot be inferred.

A new trauma frontier: Exploratory pilot study of platelet transcriptomics in trauma patients

BACKGROUND

The earliest measurable changes to postinjury platelet biology may be in the platelet transcriptome, as platelets are known to carry messenger ribonucleic acids (RNAs), and there is evidence in other inflammatory and infectious disease states of differential and alternative platelet RNA splicing in response to changing physiology. Thus, the aim of this exploratory pilot study was to examine the platelet transcriptome and platelet RNA splicing signatures in trauma patients compared with healthy donors.

METHODS

Preresuscitation platelets purified from trauma patients (n = 9) and healthy donors (n = 5) were assayed using deep RNA sequencing. Differential gene expression analysis, weighted gene coexpression network analysis, and differential alternative splicing analyses were performed. In parallel samples, platelet function was measured with platelet aggregometry, and clot formation was measured with thromboelastography.

RESULTS

Differential gene expression analysis identified 49 platelet RNAs to have differing abundance between trauma patients and healthy donors. Weighted gene coexpression network analysis identified coexpressed platelet RNAs that correlated with platelet aggregation. Differential alternative splicing analyses revealed 1,188 splicing events across 462 platelet RNAs that were highly statistically significant (false discovery rate <0.001) in trauma patients compared with healthy donors. Unsupervised principal component analysis of these platelet RNA splicing signatures segregated trauma patients in two main clusters separate from healthy controls.

CONCLUSION

Our findings provide evidence of finetuning of the platelet transcriptome through differential alternative splicing of platelet RNA in trauma patients and that this finetuning may have relevance to downstream platelet signaling. Additional investigations of the trauma platelet transcriptome should be pursued to improve our understanding of the platelet functional responses to trauma on a molecular level.

Toward platelet transcriptomics in cancer diagnosis, prognosis and therapy

Widespread adoption of next-generation techniques such as RNA-sequencing (RNA-seq) has enabled research examining the transcriptome of anucleate blood platelets in health and disease, thus revealing a rich platelet transcriptomic signature that is reprogrammed in response to disease. Platelet signatures not only capture information from parent megakaryocytes and progenitor hematopoietic stem cells but also the bone marrow microenvironment, and underlying disease states. In cancer, the substantive body of research in patients with solid tumours has identified distinct signatures in 'tumour-educated platelets', reflecting influences of the tumour, stroma and vasculature on splicing, sequestration of tumour-derived RNAs, and potentially cytokine and microvesicle influences on megakaryocytes. More recently, platelet RNA expression has emerged as a highly sensitive approach to profiling chronic progressive haematologic malignancies, where the combination of large data cohorts and machine-learning algorithms enables precise feature selection and potential prognostication. Despite these advances, however, our ability to translate platelet transcriptomics toward clinical diagnostic and prognostic efforts remains limited. In this Perspective, we present a few actionable steps for our basic, translational and clinical research communities in advancing the utility of the platelet transcriptome as a highly sensitive biomarker in cancer and collectively enable efforts toward clinical translation and patient benefit.

DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer

The genomic variant features (mutations, deletions, structural variants, etc.) within gastric cancer impact its evolution and immunogenicity. The tumor has developed several coping strategies to respond to these changes by DNA repair and replication (DRR). However, the intrinsic relationship between the associated DRR-related genes and gastric cancer progression remained unknown. This study selected DRR-related genes with tumor mutation burden based on the TCGA (The Cancer Genome Atlas) database of gastric cancer transcriptome and mutation data. The prognosis model of seven genes (LAMA2, CREB3L3, SELP, ABCC9, CYP1B1, CDH2, and GAMT) was constructed by a univariate and LASSO regression analysis and divided into high-risk and low-risk groups with the median risk score. Survival analysis showed that overall survival (OS) was lower in the high-risk group than that in the low-risk group. Moreover, patients with gastric cancer in the high-risk group have worse survival in different subgroups, including age, gender, histological grade, and TNM stage. The nomogram that included risk scores for DRR-related genes could accurately foresee OS of patients with gastric cancer. Interestingly, the tumor mutation burden score was higher in the low-risk group than that in the high-risk group, and the risk score for DRR-related genes was negatively correlated with tumor mutation burden in gastric cancer. Next, we further combined the risk score and tumor mutation burden to evaluate the prognosis of gastric cancer patients. The low-risk cohort had a better prognosis than the high-risk cohort in the high tumor mutation burden subgroup. The number of mutation types in the high-risk group was lower than that in the low-risk group. In the immune microenvironment of gastric cancer, more naïve B cells, memory resting CD4+ T cells, Treg cells, monocytes cells, and resting mast cells were infiltrated in the high-risk group. At last, PD-L1 and IAP expressions were negatively correlated with the risk scores; patients with gastric cancer in the low-risk group showed better immunotherapy outcomes than those in the high-risk group. Overall, the DRR-related gene signature based on tumor mutation burden is a novel biomarker for prognostic and immunotherapy response in patients with gastric cancer.

Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits

Alternate splicing events can create isoforms that alter gene function, and genetic variants associated with alternate gene isoforms may reveal molecular mechanisms of disease. We used subcutaneous adipose tissue of 426 Finnish men from the METSIM study and identified splice junction quantitative trait loci (sQTLs) for 6,077 splice junctions (FDR < 1%). In the same individuals, we detected expression QTLs (eQTLs) for 59,443 exons and 15,397 genes (FDR < 1%). We identified 595 genes with an sQTL and exon eQTL but no gene eQTL, which could indicate potential isoform differences. Of the significant sQTL signals, 2,114 (39.8%) included at least one proxy variant (linkage disequilibrium r2 > 0.8) located within an intron spanned by the splice junction. We identified 203 sQTLs that colocalized with 141 genome-wide association study (GWAS) signals for cardiometabolic traits, including 25 signals for lipid traits, 24 signals for body mass index (BMI), and 12 signals for waist-hip ratio adjusted for BMI. Among all 141 GWAS signals colocalized with an sQTL, we detected 26 that also colocalized with an exon eQTL for an exon skipped by the sQTL splice junction. At a GWAS signal for high-density lipoprotein cholesterol colocalized with an NR1H3 sQTL splice junction, we show that the alternative splice product encodes an NR1H3 transcription factor that lacks a DNA binding domain and fails to activate transcription. Together, these results detect splicing events and candidate mechanisms that may contribute to gene function at GWAS loci.

Platelet Heterogeneity in Myeloproliferative Neoplasms

Myeloproliferative neoplasms (MPNs) are a group of malignant disorders of the bone marrow where a dysregulated balance between proliferation and differentiation gives rise to abnormal numbers of mature blood cells. MPNs encompass a spectrum of disease entities with progressively more severe clinical features, including complications with thrombosis and hemostasis and an increased propensity for transformation to acute myeloid leukemia. There is an unmet clinical need for markers of disease progression. Our understanding of the precise mechanisms that influence pathogenesis and disease progression has been limited by access to disease-specific cells as biosources. Here, we review the landscape of MPN pathology and present blood platelets as potential candidates for disease-specific understanding. We conclude with our recent work discovering progressive platelet heterogeneity by subtype in a large clinical cohort of patients with MPN.

Aspirin effects on platelet gene expression are associated with a paradoxical, increase in platelet function

Aspirin has known effects beyond inhibiting platelet cyclooxygenase-1 (COX-1) that have been incompletely characterized. Transcriptomics can comprehensively characterize the on- and off-target effects of medications. We used a systems pharmacogenomics approach of aspirin exposure in volunteers coupled with serial platelet function and purified platelet mRNA sequencing to test the hypothesis that aspirin's effects on the platelet transcriptome are associated with platelet function. We prospectively recruited 74 adult volunteers for a randomized crossover study of 81- vs. 325 mg/day, each for 4 weeks. Using mRNA sequencing of purified platelets collected before and after each 4-week exposure, we identified 208 aspirin-responsive genes with no evidence for dosage effects. In independent cohorts of healthy volunteers and patients with diabetes, we validated aspirin's effects on five genes: EIF2S3, CHRNB1, EPAS1, SLC9A3R2 and HLA-DRA. Functional characterization of the effects of aspirin on mRNA as well as platelet ribosomal RNA demonstrated that aspirin may act as an inhibitor of protein synthesis. Database searches for small molecules that mimicked the effects of aspirin on platelet gene expression in vitro identified aspirin but no other molecules that share aspirin's known mechanisms of action. The effects of aspirin on platelet mRNA were correlated with higher levels of platelet function both at baseline and after aspirin exposure-an effect that counteracts aspirin's known antiplatelet effect. In summary, this work collectively demonstrates a dose-independent effect of aspirin on the platelet transcriptome that counteracts the well-known antiplatelet effects of aspirin.

Platelet transcriptome identifies progressive markers and potential therapeutic targets in chronic myeloproliferative neoplasms

Predicting disease progression remains a particularly challenging endeavor in chronic degenerative disorders and cancer, thus limiting early detection, risk stratification, and preventive interventions. Here, profiling the three chronic subtypes of myeloproliferative neoplasms (MPNs), we identify the blood platelet transcriptome as a proxy strategy for highly sensitive progression biomarkers that also enables prediction of advanced disease via machine-learning algorithms. The MPN platelet transcriptome reveals an incremental molecular reprogramming that is independent of patient driver mutation status or therapy. Subtype-specific markers offer mechanistic and therapeutic insights, and highlight impaired proteostasis and a persistent integrated stress response. Using a LASSO model with validation in two independent cohorts, we identify the advanced subtype MF at high accuracy and offer a robust progression signature toward clinical translation. Our platelet transcriptome snapshot of chronic MPNs demonstrates a proof-of-principle for disease risk stratification and progression beyond genetic data alone, with potential utility in other progressive disorders.

Transcriptomic landscape of blood platelets in healthy donors

Blood platelet RNA-sequencing is increasingly used among the scientific community. Aberrant platelet transcriptome is common in cancer or cardiovascular disease, but reference data on platelet RNA content in healthy individuals are scarce and merit complex investigation. We sought to explore the dynamics of platelet transcriptome. Datasets from 204 healthy donors were used for the analysis of splice variants, particularly with regard to age, sex, blood storage time, unit of collection or library size. Genes B2M, PPBP, TMSB4X, ACTB, FTL, CLU, PF4, F13A1, GNAS, SPARC, PTMA, TAGLN2, OAZ1 and OST4 demonstrated the highest expression in the analysed cohort, remaining substantial transcription consistency. CSF3R gene was found upregulated in males (fold change 2.10, FDR q < 0.05). Cohort dichotomisation according to the median age, showed upregulated KSR1 in the older donors (fold change 2.11, FDR q < 0.05). Unsupervised hierarchical clustering revealed two clusters which were irrespective of age, sex, storage time, collecting unit or library size. However, when donors are analysed globally (as vectors), sex, storage time, library size, the unit of blood collection as well as age impose a certain degree of between- and/or within-group variability. Healthy donor platelet transcriptome retains general consistency, with very few splice variants deviating from the landscape. Although multidimensional analysis reveals statistically significant variability between and within the analysed groups, biologically, these changes are minor and irrelevant while considering disease classification. Our work provides a reference for studies working both on healthy platelets and pathological conditions affecting platelet transcriptome.

CRISPR-edited megakaryocytes for rapid screening of platelet gene functions

Human anucleate platelets cannot be directly modified using traditional genetic approaches. Instead, studies of platelet gene function depend on alternative models. Megakaryocytes (the nucleated precursor to platelets) are the nearest cell to platelets in origin, structure, and function. However, achieving consistent genetic modifications in primary megakaryocytes has been challenging, and the functional effects of induced gene deletions on human megakaryocytes for even well-characterized platelet genes (eg, ITGA2B) are unknown. Here we present a rapid and systematic approach to screen genes for platelet functions in CD34+ cell-derived megakaryocytes called CRIMSON (CRISPR-edited megakaryocytes for rapid screening of platelet gene functions). By using CRISPR/Cas9, we achieved efficient nonviral gene editing of a panel of platelet genes in megakaryocytes without compromising megakaryopoiesis. Gene editing induced loss of protein in up to 95% of cells for platelet function genes GP6, RASGRP2, and ITGA2B; for the immune receptor component B2M; and for COMMD7, which was previously associated with cardiovascular disease and platelet function. Gene deletions affected several select responses to platelet agonists in megakaryocytes in a manner largely consistent with those expected for platelets. Deletion of B2M did not significantly affect platelet-like responses, whereas deletion of ITGA2B abolished agonist-induced integrin activation and spreading on fibrinogen without affecting the translocation of P-selectin. Deletion of GP6 abrogated responses to collagen receptor agonists but not thrombin. Deletion of RASGRP2 impaired functional responses to adenosine 5'-diphosphate (ADP), thrombin, and collagen receptor agonists. Deletion of COMMD7 significantly impaired multiple responses to platelet agonists. Together, our data recommend CRIMSON for rapid evaluation of platelet gene phenotype associations.

Platelet electrical resistance for measuring platelet activation and adhesion in human health and disease

BACKGROUND

The ability to measure changes in platelet reactivity is important to identify novel aspects of platelet biology and develop targeted therapeutics to prevent bleeding or thrombosis. Current platelet function testing allows for single agonist analysis at a time. The ability to phenotype platelets in a single assay with multiple agonists and adhesion substrates could yield more insights into altered pathways than are feasible with current approaches. We hypothesized platelet electrical resistance (PER) could be used for more comprehensive phenotyping of platelets.

METHODS

Platelets were isolated from male and female healthy donors (age 39.6 ± 6.9) and septic patients (age 44.0 ± 13.5). PER 96-well plates were coated with various substrates, including fibrinogen and collagen. Platelets were added to the coated plates in the presence or absence of thrombin or convulxin. Platelet activation and spreading was monitored by measuring changes in electrical impedance.

RESULTS

Platelets adhesion to fibrinogen and collagen increased impedance. In addition, impedance increased in response to thrombin or convulxin. No changes in impedance were observed in the absence of platelets or when wells were uncoated, indicating changes in impedance were directly due to platelet adhesion and activation. Inhibiting integrin αIIbβ3 decreased impedance when fibrinogen was used as a substrate, consistent with platelet-dependent effects. Platelets from septic patients caused increased impedance compared to healthy donors, demonstrating this assay can be used to assess platelet hyperreactivity.

CONCLUSION

PER can be applied as a high throughput tool to measure platelet reactivity in health and disease, where platelet activation is increased.

Circulating platelets as liquid biopsy sources for cancer detection

Nucleic acids and proteins are shed into the bloodstream by tumor cells and can be exploited as biomarkers for the detection of cancer. In addition, cancer detection biomarkers can also be nontumor‐derived, having their origin in other organs and cell types. Hence, liquid biopsies provide a source of direct tumor cell‐derived biomolecules and indirect nontumor‐derived surrogate markers that circulate in body fluids or are taken up by circulating peripheral blood cells. The capacity of platelets to take up proteins and nucleic acids and alter their megakaryocyte‐derived transcripts and proteins in response to external signals makes them one of the richest liquid biopsy biosources. Platelets are the second most abundant cell type in peripheral blood and are routinely isolated through well‐established and fast methods in clinical diagnostics but their value as a source of cancer biomarkers is relatively recent. Platelets do not have a nucleus but have a functional spliceosome and protein translation machinery, to process RNA transcripts. Platelets emerge as important repositories of potential cancer biomarkers, including several types of RNAs (mRNA, miRNA, circRNA, lncRNA, and mitochondrial RNA) and proteins, and several preclinical studies have highlighted their potential as a liquid biopsy source for detecting various types and stages of cancer. Here, we address the usability of platelets as a liquid biopsy for the detection of cancer. We describe several studies that support the use of platelet biomarkers in cancer diagnostics and discuss what is still lacking for their implementation into the clinic.

The Dynamic Platelet Transcriptome in Obesity and Weight Loss

OBJECTIVE

Adiposity is associated with oxidative stress, inflammation, and glucose intolerance. Previous data suggest that platelet gene expression is associated with key cardiometabolic phenotypes, including body mass index but stable in healthy individuals over time. However, modulation of gene expression in platelets in response to metabolic shifts (eg, weight reduction) is unknown and may be important to defining mechanism. Approach and Results: Platelet RNA sequencing and aggregation were performed from 21 individuals with massive weight loss (>45 kg) following bariatric surgery. Based on RNA sequencing data, we measured the expression of 67 genes from isolated platelet RNA using high-throughput quantitative reverse transcription quantitative PCR in 1864 FHS (Framingham Heart Study) participants. Many transcripts not previously studied in platelets were differentially expressed with bariatric surgical weight loss, appeared specific to platelets (eg, not differentially expressed in leukocytes), and were enriched for a nonalcoholic fatty liver disease pathway. Platelet aggregation studies did not detect alteration in platelet function after significant weight loss. Linear regression models demonstrated several platelet genes modestly associated with cross-sectional cardiometabolic phenotypes, including body mass index. There were no associations between studied transcripts and incident diabetes or cardiovascular end points.

CONCLUSIONS

In summary, while there is no change in platelet aggregation function after significant weight loss, the human platelet experiences a dramatic transcriptional shift that implicates pathways potentially relevant to improved cardiometabolic risk postweight loss (eg, nonalcoholic fatty liver disease). Further studies are needed to determine the mechanistic importance of these observations.

Platelet gene expression and function in patients with COVID-19

There is an urgent need to understand the pathogenesis of coronavirus disease 2019 (COVID-19). In particular, thrombotic complications in patients with COVID-19 are common and contribute to organ failure and mortality. Patients with severe COVID-19 present with hemostatic abnormalities that mimic disseminated intravascular coagulopathy associated with sepsis, with the major difference being increased risk of thrombosis rather than bleeding. However, whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection alters platelet function to contribute to the pathophysiology of COVID-19 remains unknown. In this study, we report altered platelet gene expression and functional responses in patients infected with SARS-CoV-2. RNA sequencing demonstrated distinct changes in the gene-expression profile of circulating platelets of COVID-19 patients. Pathway analysis revealed differential gene-expression changes in pathways associated with protein ubiquitination, antigen presentation, and mitochondrial dysfunction. The receptor for SARS-CoV-2 binding, angiotensin-converting enzyme 2 (ACE2), was not detected by messenger RNA (mRNA) or protein in platelets. Surprisingly, mRNA from the SARS-CoV-2 N1 gene was detected in platelets from 2 of 25 COVID-19 patients, suggesting that platelets may take-up SARS-COV-2 mRNA independent of ACE2. Resting platelets from COVID-19 patients had increased P-selectin expression basally and upon activation. Circulating platelet-neutrophil, -monocyte, and -T-cell aggregates were all significantly elevated in COVID-19 patients compared with healthy donors. Furthermore, platelets from COVID-19 patients aggregated faster and showed increased spreading on both fibrinogen and collagen. The increase in platelet activation and aggregation could partially be attributed to increased MAPK pathway activation and thromboxane generation. These findings demonstrate that SARS-CoV-2 infection is associated with platelet hyperreactivity, which may contribute to COVID-19 pathophysiology.

Megakaryocyte and Platelet Transcriptomics for Discoveries in Human Health and Disease

Anucleate platelets, long viewed as merely cell fragments with a limited repertoire of rapid-acting hemostatic functions, are now recognized to have a complex and dynamic transcriptome mirroring that of many nucleated cells. The field of megakaryocyte and platelet transcriptomics has been rapidly growing, particularly with the advent of newer technologies such as next-generation RNA-sequencing. Studies interrogating the megakaryocyte and platelet transcriptome have led to a number of key insights into human health and disease. In this brief focused review, we will discuss some of the recent discoveries made through transcriptome analysis of megakaryocytes and platelets. We will also highlight the utility of integrating ribosome footprint analysis to augment discoveries. Both bulk and single-cell sequencing approaches will be reviewed, along with comparative studies between human and murine platelets under basal healthy settings and during acute systemic inflammatory diseases.