Cellular and molecular mechanisms of IMMunE dysfunction and Recovery from SEpsis-related critical illness in adults: An observational cohort study (IMMERSE) protocol paper

Abstract

Sepsis is a common illness. Immune responses are considered major drivers of sepsis illness and outcomes. However, there are no proven immunomodulator therapies in sepsis. We hypothesised that in-depth characterisation of sepsis-specific immune trajectory may inform immunomodulation in sepsis-related critical illness. We describe the protocol of the IMMERSE study to address this hypothesis. We include critically ill sepsis patients without documented immune comorbidity and age–sex matched cardiac surgical patients as controls. We plan to perform an in-depth biological characterisation of innate and adaptive immune systems, platelet function, humoral components and transcriptional determinants of the immune system responses in sepsis. This will be done at pre-specified time points during their critical illness to generate an illness trajectory. The sample size for each biological assessment is different and is described in detail. In summary, the overall aim of the IMMERSE study is to increase the granularity of longitudinal immunology model of sepsis to inform future immunomodulation trials.

Keywords

Sepsis lymphocyte immunology transcriptomics

Introduction

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection and includes septic shock as a more severe subset.^1,2 Sepsis is a major global issue with an extrapolated incidence of 48.9 million cases worldwide and 11 million sepsis-related deaths, representing 19.7% of all deaths in 2017.³ Hospital mortality exceeds 20% for sepsis-related critical illness.^4,5 Furthermore, patients who recover from sepsis (sepsis survivors) are at greater risk of rehospitalisation and death compared to both the age- and sex-matched general population and hospitalised patients without sepsis.^6–8 Improving outcomes and enhancing survivorship are clinical priorities.

Immune responses are central to sepsis pathophysiology⁹ and are considered major determinants of outcome. Despite, or perhaps because of, a plethora of immune changes,⁹ there are no immune therapies confirmed to improve outcomes in large prospective trials. Improved patient selection and optimal timing of intervention could change this scenario.^10,11 To achieve this in immunomodulation trials, we need to understand how immune abnormalities change over time (referred to as the longitudinal immunological model in this article), the major determinants of this change and the major immune abnormalities with a modifiable attributable risk.¹² We hypothesised that this could be achieved by concurrently studying changes in immune cell phenotypes, functionality and their transcriptional determinants. Similar issues apply for coagulation abnormalities.¹³ Herein, we describe the protocol of the IMMERSE study to address these hypotheses.

Rationale for the study and evidence gap addressed by the study

Sepsis-related immune responses involve both humoral and leukocyte components of the innate and adaptive immune systems.¹⁴ Previous studies have assessed the immune response in sepsis by characterising the pan-leukocyte transcriptome, with microarray as the analytic platform.^15–18 The currently accepted sepsis immune trajectory model is a consensus model with limited data-driven evidence. Excessive inflammation and immunosuppression, which occur simultaneously in most patients, change over time. However, published studies are mostly single time point assessments from patients who are likely at various stages of immune activation or suppression. Averaging phenotypic profiles across patients at various stages of inflammation and immunosuppression may obscure critical disease pathways. Thus, there is a pressing need for standardised lymphocyte immunophenotyping in sepsis as described in the human immunology project,¹⁹ and, crucially, at multiple time points. Similarly, in terms of days from critical care admission, we do not know when the dominant immune signal in sepsis-related critical illness changes from inflammation to immunosuppression, how best to identify this change and therefore when to shift from immunosuppressive therapy towards possible immune stimulation. IMMERSE aims to increase the granularity of this longitudinal immunology model of sepsis to inform immunomodulation trial design.¹¹

In most adult sepsis cohort studies, the study population has a mean age of around 60 years, and often have comorbidities or treatments such as malignancy and chemotherapy that can affect normal immunological responses.¹⁵ This prompted us to consider the issue of control populations when designing our cohort study.²⁰ We plan to use age- and sex-matched controls with blood sampling taken before and after uncomplicated cardiac surgery. The key rationale for our choice of control population is that their hospital admission diagnosis is unrelated to our exposure of interest (i.e. sepsis). Additional advantages include feasibility, comparable information quality, receipt of treatment in the same health care setting and the ability to perform paired sampling both before and after a sterile surgical insult at fixed time points to understand early immune changes.

There are numerous immunological interventions with known effects that may be of value.¹⁴ However, ex vivo assessment of the reversibility of these sepsis-related immunological abnormalities is seldom performed. Furthermore, in early phase clinical trials of these interventions,^21,22 assessment of the biological pharmacodynamic effects of intervention is often limited, compared to pharmacokinetic and safety aspects. Thus, there is a need for systematic assessment of the ex vivo biological effect of putative interventions. The IMMERSE study addresses this question by concurrently evaluating biological reversibility, using the ex vivo experimental set-up as described previously,²³ alongside immune cell phenotypes and molecular abnormalities.

In sepsis patients, thrombocytopenia is associated with a more severe disease and an increased risk of death.²⁴ In addition to their role in haemostasis and thrombosis, platelets are widely accepted as key components of the cellular immune system. Platelets contribute to the inflammatory response in both allergic²⁵ and non-allergic inflammation²⁶ and are critical to host defence in infectious disease.^26,27 Although platelets have been heavily discussed in the context of sepsis,²⁸ little work has been done to assess how their function may change through the trajectory of the disease, both in terms of haemostasis and immune (inflammatory) function. The IMMERSE study will help define how platelet function is altered during sepsis, its association with immune changes and the potential of highlighting novel therapeutic avenues.

Aims

First, to describe longitudinal changes in B and T cell counts and phenotypic changes within immune cell subsets¹⁹ during sepsis-related critical illness commencing at critical care admission, at one or more time points during their critical care stay and at critical care discharge. Second, to explain the observed phenotypic changes in B and T cell subsets at the molecular level using functional readouts with cell culture and transcriptomic experiments. Third, to describe changes in platelet phenotype and function. Fourth, to contribute towards refining the longitudinal sepsis immunology model by integrating these orthogonal (statistically independent) multilevel data with repeated measurements.

Methods and analysis

Study design

IMMERSE is a prospective observational cohort study in adult critically ill sepsis patients, with age- and sex-matched non-sepsis controls.

Setting

The study will recruit from multiple intensive care units, high dependency units and cardiac surgical wards at Guy’s and St Thomas’ NHS Foundation Trust, London, England. This is a tertiary referral hospital with 120 critical care beds, a mixed medical–surgical case mix and includes a severe respiratory failure centre. The basic science work will be conducted within the School of Immunology & Microbial Sciences and the Institute of Pharmaceutical Science at King’s College London.

Study cohorts and eligibility criteria

We plan to enrol two hospitalised cohorts (sepsis and cardiac surgery) and age–sex matched non-hospitalised participants to address our research aims.

Sepsis (including septic shock) will be defined as per the Sepsis-3 criteria.¹ Inclusion criteria include patients >18 years of age, admitted with suspected or proven infection with an admission day Sepsis-related Organ Failure Assessment (SOFA) Score of 2 or higher, and provision of written consent by patient or by professional or personal consultee.

Elective uncomplicated surgical control participants will also be enrolled to explore how the immune system responds to the sterile insult of cardiac surgery. Inclusion criteria include patients >18 years of age, admitted for planned cardiac surgery and provision of written consent by patient or by professional or personal consultee.

Exclusion criteria for the sepsis and cardiac surgical cohorts are aimed at removing confounding effects of concomitant immune abnormalities in host immune responses to infection and injury. Such exclusions include any limitations of care order set, including ‘do not attempt cardiopulmonary resuscitation’ or not for readmission to critical care, and one or more of the following conditions associated with immunosuppression as defined in the APACHE II score²⁹: human immunodeficiency virus (HIV) diagnosed at any point prior to enrolment; leukaemia within the last 5 years; lymphoma (treated or eligible for treatment by radiotherapy or chemotherapy) within the last 5 years; multiple myeloma (treated or eligible for treatment by radiotherapy or chemotherapy within the last 5 years); malignancy (treated or eligible for treatment by radiotherapy or chemotherapy) within the last 5 years; being treated with immunosuppressive therapy including corticosteroids for 2 weeks or longer at a daily prednisolone (or equivalent) dose of 30 mg or higher; receipt of an organ (including bone marrow) transplant with ongoing immunosuppressive medication and immunosuppression due to another cause including congenital hypogammaglobulinaemia or other congenital immunodeficiency; nephrotic syndrome; known protein-losing enteropathies; or receipt of treatment with intravenous immunoglobulins in the preceding 3 months.

Clinical data

For all patients included in the cohort, we will collect and summarise demographic data, daily laboratory results for white blood counts, C-reactive protein, daily worst physiological and biochemical variables to derive the SOFA score, critical care length of stay, critical care mortality, hospital length of stay and hospital mortality.

Blood sampling and biological assessments

In the sepsis and cardiac surgical cohorts, we will collect, process and store blood samples for leukocyte phenotyping, whole blood transcriptomics, platelets for functional analyses (aggregation and chemotaxis), cellular and molecular analysis of antigen expression, receptor repertoire and serum and plasma for biomarker assessments. In sepsis patients, these samples will be collected at four time points: within 24 h of critical care admission, on day 3 (±1 day), on day 5 (±1 day) and on critical care discharge. In the cardiac surgical cohort, these samples will be collected before and 24 h following cardiac surgery. In healthy controls, we will collect one sample only. To reduce technical variation between samples, we plan to multiplex leukocyte phenotyping, use the same technical control in every experiment and publish our experimental methods. Leukocyte phenotyping will be done using flow cytometry and mass cytometry (CyTOF) to gain insights into cellular phenotype and function.^30–32 Strand-specific, poly(A)+ ribonucleic acid sequencing (RNA-seq) will be performed with a sequencing depth of ∼35–40 million 150 bp paired-end reads per sample to determine mRNA expression.

To understand the importance of platelets throughout the trajectory of sepsis, circulating platelet concentrations will be quantified and platelet activation markers (e.g. β-thromboglobulin and Regulated upon Activation, Normal T Cell Expressed and Presumably Secreted (RANTES)) will be measured by ELISA. Changes in haemostatic and inflammatory platelet function will be evaluated using in vitro functional assays of platelet aggregation and chemotaxis, respectively. Platelets will be stimulated using endogenous purinergic receptor agonists, and downstream function assessed, as previously described.³³ Platelet surface expression of purinergic receptors, P2Y₁, P2Y₁₂ and P2Y₁₄ will be measured using flow cytometry and other molecular techniques.

Sample size

The overall study sample size of the sepsis cohort of 110 patients was determined using precision estimates for lymphocyte counts based on our previous study, where we observed a standard deviation of 1.07 cells × 10⁹/L³⁴ and we wanted a precision of 0.2 cells × 10⁹/L for a Z value of 1.95 for 95% confidence interval. This will be used as a guide for recruiting patients. Each research question will address experiment-specific sample size requirements, as described.

For paired transcriptomics experiments, we used pilot microarray data in sepsis patients to inform sample size calculations. Among the 522 differentially expressed genes in T cells, there were 12 genes with more than a threefold increase and four genes with more than a threefold decrease in expression, compared with age- and sex-matched healthy controls. Among 182 differentially expressed genes in B cells, there were 26 genes with more than a twofold increase and nine genes with more than a twofold decrease in expression compared with age- and sex-matched healthy controls.³⁴ Based on the above, we will sample a minimum of 18 sepsis patients and controls to perform paired analysis where required (such as with ex vivo stimulation experiments and longitudinal data), which will allow for the detection of candidates with a minimum of 50 reads that differ by a factor of 2, achieving 0.9 power with an alpha error of 0.05.³⁵

For platelet studies, the coefficient of variation in platelet counts prior to cardiac surgery (n = 20 patients) and at admission day in sepsis (n = 30 patients) were 32.3% and 58.4%, respectively. Therefore, we estimated a sample size of 36 sepsis patients with at least two repeated time-point measurements for platelet experiments, to achieve 0.8 power with an alpha error of 0.05, for functional differences.

Data analysis plan

The primary exposure is Sepsis-3 criteria defined sepsis. The primary outcome is sepsis-specific biological traits to refine the longitudinal immunology model. Transcriptomic experiments will generate RNA-seq data which will be analysed to determine changes in RNA abundance at the gene level as well as the transcript isoform level using open source software (such as kallisto,³⁶ DESeq2,³⁷ and sleuth³⁶) and our High-Performance Computing Cluster (Rosalind) within King’s College London. Post-transcriptional steps of gene expression, such as alternative splicing and polyadenylation, will also be analysed. Gene set enrichment analysis (GSEA) will be performed using Ingenuity Pathway Analysis.

Whole blood flow cytometry assays will be used to measure absolute counts of CD4 + and CD8+ T cells, B cells and all by memory and naïve phenotype. FlowJo will be used to manually gate populations of interest to determine cell count changes over time and sepsis-specific changes compared to sterile inflammation. For mass cytometry experiments, we will analyse complex cellular interactions in multiple immune populations. All time points from a patient and a healthy technical control will be barcoded prior to staining and acquisition. Samples will be acquired in multiple FCS files on the Helios (Fluidigm). For analysis, FCS files will be normalised,³⁸ concatenated and debarcoded.³⁹ This process is advantageous as it reduces non-biological variation derived from experiment procedure and machine variability over time. To analyse immune cells of interest, manual gating will identify defined cell populations of interest. Exploratory analysis will be carried out using unsupervised clustering and dimensional reduction techniques.⁴⁰ Populations identified will be used to understand sepsis trajectory and sepsis-specific alterations by comparing to sterile inflammation.

Current study status

We started recruitment on 10 July 2019. To date, we have recruited 30 cardiac surgical patients, 32 sepsis patients and 7 healthy controls.

Strengths and limitations of this study

We include non-sepsis controls with age and sex matching. We perform in-depth phenotyping of immune cell subsets at multiple time points during the sepsis illness, using multiplexing to reduce technical variation. Finally, there is concurrent evaluation of molecular mechanisms to explain phenotypic changes in immune cells. Our study has limitations. We are including all sepsis patients to increase generalisability but at the risk of increasing heterogeneity by not restricting by site of infection. The use of cardiac surgical controls could be confounded by their well-understood risk of endotoxaemia, which may lower the chances of identifying a sepsis-specific signature. Our sample size for transcriptomic experiments is based on previous microarray data and may be insufficient.

Ethics, regulations and governance

Study management

The study is managed by the Department of Critical Care Medicine at Guy’s and St Thomas’ Hospital NHS Foundation Trust.

Sponsorship

The study sponsors are Guy's and St Thomas' Hospital NHS Foundation Trust.

Funding

This study is partly funded by the National Institute of Academic Anaesthesia – British Journal of Anaesthesia and Royal College Of Anaesthetists non-clinical PhD Studentship grant. The funders had no role in study design.

Duration of the Study

The Study recruited its first patient on 10 July 2019. Recruitment is expected to take a maximum of 3 years and be completed by 7 February 2022.

Ethical and regulatory approval

The study will be conducted according to the ethical principles outlined in the declaration of Helsinki. South Central Berkshire Research Ethics Committee has granted ethical approval 19/SC/0187. The study has been registered with the UK National Institute for Health Research (NIHR) Clinical Research Portfolio.

Protocol compliance

We will conduct the study as per the protocol given a favourable opinion by the Research Ethics Committee (REC). Protocol changes will require REC favourable opinion prior to implementation. The study team will monitor protocol compliance as it is an observational cohort study. We will have a data dictionary for all variables collected in the study.

Patient confidentiality

At the point of sample collection, all patient samples are assigned a unique study ID. The only link between patient identity and unique identifier will be held securely at the study site.

Dissemination

Our four major aims will be addressed using multiple peer-reviewed publications, and we plan to provide the corresponding open access resource data with each publication.

Summary

The IMMERSE study is a cohort study in adult critically ill patients with sepsis, with age- and sex-matched hospitalised patients acting as the clinical and biological comparator population. Our aims are to describe the longitudinal immune system changes at a cellular and molecular level with enough granularity to refine the sepsis illness model.

Executive summary

Introduction: Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Despite the immune system being a key driver of sepsis pathophysiology, there are no proven immunomodulatory therapies for sepsis. This is explained partly by the illness heterogeneity and poorly characterised illness trajectory in sepsis patients. Therefore, we hypothesised that understanding immune heterogeneity and trajectory could inform patient selection for future clinical trials. We aim to describe sepsis-specific changes in leukocyte phenotype, function and transcriptional state, over the course of critical illness.

Methods and analysis: We plan to conduct a prospective, observational cohort study analysing blood samples from patients admitted to the critical care unit with sepsis defined as per the Sepsis-3 criteria (sepsis cohort), and compare against age- and sex-matched cardiac patients undergoing elective cardiac surgery (cardiac cohort) and/or age- and sex-matched healthy volunteers, who have not been hospitalised in the previous 6 months (healthy cohort). We will use flow cytometry and mass cytometry to describe sepsis-specific changes in the leukocyte phenotype, cell culture and fluorospot, for functional characterisation, and next-generation sequencing for gene expression analysis, alongside clinical data.

Ethics and dissemination: This study will be conducted in accordance with principles outlined in the Declaration of Helsinki. Ethical approval has been obtained from the South-Central Berkshire research ethics committee. On conclusion of the study, results will be disseminated through peer-reviewed journals and conferences.

Checklist: We have included a STROBE Checklist for observational studies (see Supplementary Material). As a protocol paper, the results and discussion sections are not applicable.

Supplemental Material

sj-pdf-1-inc-10.1177_1751143720966286 - Supplemental material for Cellular and molecular mechanisms of IMMunE dysfunction and Recovery from SEpsis-related critical illness in adults: An observational cohort study (IMMERSE) protocol paper

Supplemental material, sj-pdf-1-inc-10.1177_1751143720966286 for Cellular and molecular mechanisms of IMMunE dysfunction and Recovery from SEpsis-related critical illness in adults: An observational cohort study (IMMERSE) protocol paper by Matthew Fish, Kate Arkless, Aislinn Jennings, Julie Wilson, Michael J Carter, Gill Arbane, Sara Campos, Neus Novellas, Rianne Wester, Nedyalko Petrov, Umar Niazi, Barney Sanderson, Richard Ellis, Mansoor Saqi, Jo Spencer, Mervyn Singer, Rocio T Martinez-Nunez, Simon Pitchford, Chad M Swanson and Manu Shankar-Hari in Journal of the Intensive Care Society

Footnotes

Authors’ contributions

MSH conceived the study. MF/KA/MSH wrote the first draft of the manuscript. All authors contributed to the critical care vision of the manuscript. All authors read the final draft of the manuscript prior to publication.

Acknowledgements

The authors thank past and future patients, their families and medical professionals who have been involved in the IMMERSE study. We thank the flow cytometry core at the NIHR Biomedical Research Centre for logistical support. We would like to thank Guy’s and St Thomas’s Hospital, the Critical Care Department and Cardiothoracic Surgery Department who have helped facilitate this study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Mr Matthew Fish is supported by the National Institute of Academic Anaesthesia BJA-RCOA PhD Fellowship (WKR0-2018-0047). Ms Kate Arkless is supported by Medical Research Council Doctoral Training programme (MRC-DTP) at KCL. Dr Shankar-Hari is supported by the National Institute for Health Research Clinician Scientist Award (CS-2016-16-011) and this research was funded/supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care.

Supplemental Material

The supplementary material for this article is available online.

ORCID iDs

Sara Campos

Umar Niazi

Barney Sanderson

Mervyn Singer

Chad M Swanson

Manu Shankar-Hari

References

Singer

Deutschman

Seymour

, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315: 801–810.

Shankar-Hari

Phillips

Levy

, et al. Developing a new definition and assessing new clinical criteria for septic shock: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315: 775–787.

Rudd

Johnson

Agesa

, et al. Global, regional, and national sepsis incidence and mortality, 1990–2017: Analysis for the Global Burden of Disease Study. Lancet 2020; 395: 200–211.

Shankar-Hari

Harrison

Rubenfeld

, et al. Epidemiology of sepsis and septic shock in critical care units: Comparison between sepsis-2 and sepsis-3 populations using a national critical care database. Br J Anaesth 2017; 119: 626–636.

Kaukonen

Bailey

Suzuki

, et al. Mortality related to severe sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-2012. JAMA 2014; 311: 1308–1316.

Shankar-Hari

Saha

Wilson

, et al. Rate and risk factors for rehospitalisation in sepsis survivors: Systematic review and meta-analysis. Intensive Care Med 2020; 46: 619–636.

Shankar-Hari

Harrison

Ferrando-Vivas

, et al. Risk factors at index hospitalization associated with longer-term mortality in adult sepsis survivors. JAMA Netw Open 2019; 2: e194900.

Prescott

Angus

. Enhancing recovery from sepsis: A review. JAMA 2018; 319: 62–75.

Rubio

Osuchowski

Shankar-Hari

, et al. Current gaps in sepsis immunology: New opportunities for translational research. Lancet Infect Dis 2019; 19: e422–e436.

10.

Marshall

. Why have clinical trials in sepsis failed? Trends Mol Med 2014; 20: 195–203.

11.

Shankar-Hari

Rubenfeld

. Population enrichment for critical care trials: Phenotypes and differential outcomes. Curr Opin Crit Care 2019; 25: 489–497.

12.

Shankar-Hari

Harrison

Rowan

, et al. Estimating attributable fraction of mortality from sepsis to inform clinical trials. J Crit Care 2018; 45: 33–39.

13.

Levi

van der Poll

. Coagulation and sepsis. Thromb Res 2017; 149: 38–44.

14.

van der Poll

van de Veerdonk

Scicluna

, et al. The immunopathology of sepsis and potential therapeutic targets. Nat Rev Immunol 2017; 17: 407–420.

15.

Scicluna

van Vught

Zwinderman

, et al. Classification of patients with sepsis according to blood genomic endotype: A prospective cohort study. Lancet Resp Med 2017; 5: 816–826.

16.

Burnham

Davenport

Radhakrishnan

, et al. Shared and distinct aspects of the sepsis transcriptomic response to fecal peritonitis and pneumonia. Am J Respir Crit Care Med 2017; 196: 328–339.

17.

Davenport

Burnham

Radhakrishnan

, et al. Genomic landscape of the individual host response and outcomes in sepsis: A prospective cohort study. Lancet Resp Med 2016; 4: 259–271.

18.

Sweeney

Shidham

Wong

, et al. A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci Transl Med 2015; 7: 287ra271.

19.

Maecker

McCoy

Nussenblatt

. Standardizing immunophenotyping for the Human Immunology Project. Nat Rev Immunol 2012; 12: 191–200.

20.

Grimes

Schulz

. Compared to what? Finding controls for case-control studies. Lancet 2005; 365: 1429–1433.

21.

Hotchkiss

Colston

Yende

, et al. Immune checkpoint inhibition in sepsis: A Phase 1b randomized study to evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics of nivolumab. Intensive Care Med 2019; 45: 1360–1371.

22.

Hotchkiss

Colston

Yende

, et al. Immune checkpoint inhibition in sepsis: A Phase 1b randomized, placebo-controlled, single ascending dose study of antiprogrammed cell death-ligand 1 antibody (BMS-936559). Crit Care Med 2019; 47: 632–642.

23.

Thampy

Remy

Walton

, et al. Restoration of T cell function in multi-drug resistant bacterial sepsis after interleukin-7, anti-PD-L1, and OX-40 administration. PLoS One 2018; 13: e0199497.

24.

Claushuis

van Vught

Scicluna

, et al. Thrombocytopenia is associated with a dysregulated host response in critically ill sepsis patients. Blood 2016; 127: 3062–3072.

25.

Pitchford

Momi

Baglioni

, et al. Allergen induces the migration of platelets to lung tissue in allergic asthma. Am J Respir Crit Care Med 2008; 177: 604–612.

26.

Amison

O'Shaughnessy

Arnold

, et al. Platelet depletion impairs host defense to pulmonary infection with Pseudomonas aeruginosa in mice. Am J Respir Cell Mol Biol 2018; 58: 331–340.

27.

de Stoppelaar

van't Veer

Claushuis

, et al. Thrombocytopenia impairs host defense in gram-negative pneumonia-derived sepsis in mice. Blood 2014; 124: 3781–3790.

28.

Middleton

Rondina

. Platelets in infectious disease. Hematology Am Soc Hematol Educ Program 2016; 2016: 256–261.

29.

Knaus

Wagner

Draper

, et al. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 1991; 100: 1619–1636.

30.

Spitzer

Nolan

. Mass cytometry: Single cells, many features. Cell 2016; 165: 780–791.

31.

Seshadri

Brat

Yorkgitis

, et al. Phenotyping the immune response to trauma: A multiparametric systems immunology approach. Crit Care Med 2017; 45: 1523–1530.

32.

Lakshmikanth

Olin

Chen

, et al. Mass cytometry and topological data analysis reveal immune parameters associated with complications after allogeneic stem cell transplantation. Cell Rep 2017; 20: 2238–2250.

33.

Amison

Jamshidi

Rahman

, et al. Diverse signalling of the platelet P2Y1 receptor leads to a dichotomy in platelet function. Eur J Pharmacol 2018; 827: 58–70.

34.

Shankar-Hari

Fear

Lavender

, et al. Activation-associated accelerated apoptosis of memory B cells in critically ill patients with sepsis. Crit Care Med 2017; 45: 875–882.

35.

Hart

Therneau

Zhang

, et al. Calculating sample size estimates for RNA sequencing data. J Comput Biol 2013; 20: 970–978.

36.

Bray

Pimentel

Melsted

, et al. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 2016; 34: 525–527.

37.

Love

Huber

Anders

. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15: 550.

38.

Finck

Simonds

Jager

, et al. Normalization of mass cytometry data with bead standards. Cytometry A 2013; 83: 483–494.

39.

Van Gassen

Gaudilliere

Angst

, et al. CytoNorm: A normalization algorithm for cytometry data. Cytometry A 2020; 97: 268–278.

40.

Kimball

Oko

Bullock

, et al. A beginner's guide to analyzing and visualizing mass cytometry data. J Immunol 2018; 200: 3–22.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.10 MB