Transcriptomics in Human Septic Shock: State of the Art

Abstract

Background:

Septic shock is a complex syndrome characterized by signs of intense systemic inflammation and a profound dysregulation of the immune response. Large-scale gene expression analysis is a valuable tool in this scenario because sepsis affects various cellular components and signaling pathways.

Results:

In this article, we provide an overview of the transcriptomic studies that investigated human sepsis from 2007 to 2024, highlighting their major contributions.

Conclusions:

The field, however, still faces substantial limitations and several challenges. To advance further, we believe that standardization of sample collection and data analysis, preservation of cell and tissue architecture, and integration with other omics techniques are crucial for a broader understanding of this lethal disease.

Introduction

Bacterial sepsis, commonly referred to as sepsis, is a major healthcare concern with estimates ranging from 19 to 48.9 million cases per year worldwide.¹ It is a leading cause of death that claims around 10 million lives annually across the globe. According to the new definition (Sepsis-3), sepsis is defined as a life-threatening organ dysfunction, induced by a dysregulated host response to infection. The Sequential Organ Failure Assessment score is used to measure disease severity and the association with mortality.²

Septic shock is the most severe form of sepsis, characterized by circulatory failure and profound cellular and metabolic abnormalities. The most frequent sources of infection are the lungs (64%), the abdomen (20%), blood stream (15%), and the urinary tract (14%). Staphylococcus aureus accounts for 20% of the gram-positive isolates, whereas the most common gram-negative isolates are Pseudomonas aeruginosa (20%) and Escherichia coli (16%).³ Although sepsis can impact people at any age, it is more common at both ends of the age spectrum. About 70% of sepsis cases are community acquired, and it is critical to seek prompt treatment to improve outcomes. National surveys indicate that there is low community awareness of sepsis.⁴ However, because sepsis and COVID-19 share many clinical and pathophysiological features, the impact of the COVID-19 pandemic may increase sepsis awareness soon.^5,6

The understanding of sepsis pathophysiology is limited. The current knowledge is that pathogen-associated molecular patterns activate the immune system, inducing the release of several inflammatory mediators, such as cytokines, chemokines, proteases, kinins, prostaglandins, and reactive oxygen/nitrogen species. These mediators, in turn, orchestrate bacterial clearance but when exaggerated can lead to self-injury. The coagulation system is also activated in sepsis, further contributing to vascular injury and, in extreme cases, the development of disseminated intravascular coagulation. The severity of the disease and its progression to septic shock depends on the equilibrium between pro-inflammatory signals promoting the eradication of the invading microorganism and anti-inflammatory signals suppressing the overall inflammatory cascade.

Moreover, the immune response during sepsis triggers extensive epigenetic and metabolic reprogramming,^7,8 an aspect that was not considered previously but is gaining increasing attention nowadays.^9,10 Patients with sepsis can present with organ dysfunction in any part of the body, regardless of the primary site of infection,¹¹ and multiple organ failure is a substantial risk factor for death in the later stages of the disease.¹² Pioneering studies in late sepsis suggested a profound immunosuppression resulting from sepsis, which was believed as a biphasic immune response. However, recent studies have shown that immunosuppression can occur both at early and late stages of sepsis. Even in patients who survive sepsis, signs of inflammation and immunosuppression can persist for weeks to months, resulting in a condition known as persistent inflammation/immunosuppression and catabolism syndrome (PICS).¹³

Damage-associated molecular patterns (DAMPs) that are produced by injured organs and tissues, such as histones, mitochondrial DNA, high-mobility group B1 protein, S100 family members, heat shock proteins, adenosine triphosphate (ATP), adenosine and hyaluronan products, are likely to drive PICS.¹⁴ Despite decades of research, sepsis deaths are still poorly understood. Autopsies in patients who died of sepsis showed that tissue damage was relatively minimal compared with the degree of organ dysfunction reported.¹⁵ Nonetheless, refractory shock and withdrawal of care because of terminal illness or expected low quality of life remain the most common reasons justifying sepsis deaths.¹⁶ Presently, the treatment of sepsis still depends mainly on early antibiotic agents’ administration and resuscitation techniques, such as mechanical ventilation, hemodialysis, and vasopressors,¹⁷ as well as early surgical source control where indicated.

Despite more than 100 therapeutic clinical trials conducted in sepsis, there are currently no FDA-approved treatment options to improve sepsis survival rates.¹⁸ However, new approaches to deal with the sepsis burden are emerging, such as interventions targeting specific cell signaling pathways (such as immune checkpoint blockade),^19,20 multi-omics investigation,²¹ artificial intelligence,²² and personalized therapies.^23,24 Transcriptomics is a robust technique used to identify pathophysiological signatures and therapeutic targets during infectious diseases.²⁵ Numerous gene expression profiling studies have been conducted in sepsis, investigating samples obtained from animal models or critically ill patients. In this article, we review the transcriptomic studies in human beings and explore future prospects to advance our knowledge of sepsis. Studies where the definition of sepsis is vague and those focused solely on the investigation of non-coding RNAs were not included.

Early Transcriptomic Studies

Beginning in 2006, researchers have used DNA microarrays to study septic shock, attempting to distinguish between sterile and infectious systemic inflammation.²⁶ Much of this pioneering work was conducted by the Wong group on pediatric populations.^27–30 Typically, such transcriptomic studies are conducted on whole blood or isolated blood cell populations. These studies based on DNA microarray technology revealed a massive activation of innate immune pathways and persistent repression of genes involved in adaptive immunity and zinc-related biology, which is present from the earliest stages of the disease.³⁰

Using whole blood-derived RNA, Wong et al. observed upregulation of oxidative phosphorylation, interleukin (IL)-10 signaling, Toll-like receptor (TLR) signaling, NFE2-like BZIP Transcription factor 2 (NRF2)-mediated oxidative stress responses, ubiquinone biosynthesis, Triggering Receptor Expressed On Myeloid Cells (TREM) signaling, Nuclear Factor-κB (NF-κB) signaling, protein ubiquitination pathways, and IL-6 signaling in macrophages. They also found downregulation of T lymphocyte pathways and CCR5 signaling.³¹ Similarly, Cvijanovich et al. detected upregulation of TLR, IL-10, IL-6, and NF-κB signaling and downregulation of T lymphocyte activation. They also detected upregulation of acute phase responses, p38 mitogen-activated protein kinase (MAPK), the complement system, and some nuclear receptor signaling molecules (Liver X Nuclear Receptor [LXR] and peroxisome proliferator activated receptor [PPAR]) associated with the downregulation of antigen presentation pathways.²⁹

Global gene expression experiments by Shanley et al., using whole blood-derived RNA from patients in septic shock agreed with these studies. However, they also observed the upregulation of integrin, insulin-like growth factor 1, granulocyte-macrophage colony-stimulating factor, and insulin receptor signaling.²⁸ A seminal study in patients with non-infected severe blunt trauma similarly found activation of a large number of genes involved in inflammation, pattern recognition, and antimicrobial functions with the simultaneous suppression of genes involved in antigen presentation and T-cell proliferation, proposing that severe inflammatory stress of any origin may have similar genomic signatures.³² Tang et al. report for the first time the activation of many apoptotic genes, including CARD12, APAF1, and ELMOD2 in mononuclear cells from patients with sepsis.³³ More recently, publications defend that transcriptomics can differentiate between sepsis and sterile inflammation and even detect septic shock subpopulations.^34–42

Septic shock affects patients with different profiles such as aged people, patients with diabetes, trauma victims, surgical patients, obese people, and children. Historically, it has been accepted that each specific subset of patients with sepsis may have its characteristics of its own immunoinflammatory phenotype. Certain populations of patients with sepsis may benefit from a particular approach, whereas others may not.⁴³ Few studies, however, have investigated different populations of patients with sepsis. One of these studies compared the transcriptomic response of aged patients with the young.⁴⁴ Their results confirmed that both the young and the elderly respond similarly to severe infection, regarding the production of tumor necrosis factor-α, IL-6, IL-1β, TLRs, and other classical markers of cell activation. Some specific pathways, however, are more critically affected in the elderly, such as oxidative phosphorylation, TGF-β, Wnt/β-catenin, and calcium signaling.

Other subgroups of patients with sepsis investigated to date include the pediatric population and patients submitted to particular therapeutic approaches. Wynn et al. found that neonates with septic shock demonstrate reduced expression of genes representing key pathways of innate and adaptive immunity, in comparison with older children.³⁷ In 2015, the same group showed that the host response in neonates is substantially affected by the timing of the sepsis episode relative to birth.⁴⁵ Wong et al. showed that the administration of corticosteroids in pediatric septic shock is associated with additional repression of genes corresponding to adaptive immunity.⁴⁶

RNA-Sequencing Transcriptomic Studies

Sixteen bulk RNA-sequencing (RNA-seq) studies have been performed on samples from patients with sepsis to date. These studies began in 2014, with two articles published on PubMed in the same month.^47,48 Tsalik et al. compared whole blood of sepsis survivors and non-survivors. They found lower expression of several immune pathways in non-survivors, including the response to interferon-gamma (IFN-γ), the defense response, the innate immune response, antigen processing and presentation, and protein kinase signaling. Meanwhile, the study from Pena et al. performed a meta-analysis to characterize an “endotoxin tolerance phenotype” and found that sepsis is strongly associated with this phenotype, which occurs early during the clinical course of sepsis and is linked to disease severity.

In 2018, Barcella et al. described the transcriptomic profile of patients with sepsis and their response to supportive hemodynamic therapy. They suggested that the activation of genes involved in T-cell-mediated immunity, granulocyte, natural-killer functions, and bacterial lipid clearance are associated with an improvement in organ function⁴⁹ (Fig. 1).

FIG. 1.

Timeline of landmark transcriptomics investigations conducted on human sepsis from 2007 to 2024.

Washburn et al. analyzed purified blood CD4 T cells, CD8 T cells, and monocytes from patients with sepsis, critically ill patients with no sepsis, patients with metastatic colon cancer, and healthy control group were analyzed by RNA sequencing. They found five times more differentially expressed genes (DEGs) in CD4 T cells and monocytes than in CD8 T cells, when comparing patients with sepsis and healthy control group. In CD4 and CD8 T cells, most of the immune response pathways were increased in patients with sepsis, whereas in monocytes the majority was suppressed. Numerous pathways and genes associated with costimulation of monocytes and T cells, such as CD86, OX40L, and TIMD4, were downregulated in monocytes from patients with sepsis, when compared with healthy control group. Patients with sepsis and patients with cancer exhibited many common immunosuppressive mechanisms, including decreased major histocompatibility complex expression, impaired IFN-γ production, increased myeloid-derived suppressor and T regulatory cell signatures, and increased expression of inhibitory receptor ligands. The authors argue that the robust immunosuppression detected in monocytes must be related to the timing of sample collection, around 48 hours after the onset of sepsis, whereas most previous studies that show immune activation examined the early initial phase of the disorder.⁵⁰

Braga et al. examined the transcriptional response of septic shock and cardiogenic shock, using blood samples collected at several time points. They conclude that alarmins (S100A8, S100A9, S100A12), interleukin receptors (IL10RB, IL17RA, IL4R), pathogen recognition patterns (TLR1, TLR4, TLR8), and inflammasome signaling (NAIP, NLRC4) are downregulated, whereas DNA replication genes are substantially upregulated (MCM2, MCM3, MCM5, MCM7) in both types of shock, suggesting shared mechanisms.⁵¹

Englert et al. performed RNA-seq of peripheral blood samples from 12 patients with sepsis, but the primary aim of their study was to investigate acute respiratory distress syndrome (ARDS) in patients undergoing allogeneic hematopoietic stem cell transplantation.⁵²

Hato et al. investigated sepsis-induced acute kidney injury. They performed experiments in mice that were validated in human renal biopsies through RNA sequencing. They showed that the initial phase of sepsis involves similar cell responses despite the initiating pathogen.⁵³

The study by Liepelt et al. examined monocyte activation during sepsis. They found substantial differences when comparing the CD14+ monocytes of patients with sepsis with those from non-infected critically ill individuals. The enriched Gene Ontology pathways in patients with sepsis were related to immune response, but there was also an accumulation of pathways associated with metabolism, cell differentiation, and proliferation.⁵⁴

Ng et al. performed an RNA-seq study of preterm infants during late-onset sepsis. Transcriptional alterations included genes involved in pathogen recognition (Toll-like receptors), cytokine signaling (IFN-α/β, IFN-γ, IL-1β, among others), hematological regulation (alternative complement activation), cell death (BCL2 Associated Agonist Of Cell Death [BAD] activation), and metabolism (cholesterol biosynthesis).⁵⁵

Bustamante et al. compared RNA isolated from the parietal cortex gray matter of 12 subjects who died of sepsis and 12 who died of a non-infectious critical illness. They found 176 DEGs. The most DEGs were related to immunity, including DAMPs (S100A8, S100A9, and members of the Heat Shock Protein [HSP] family), markers of astrocyte activation (HSPB2, GBP2, and SERPINA3), and macrophage and microglial signatures (SOC3, CHI3L2, and CHI3L1).⁵⁶

In a recent study, Ng et al. investigated the transcriptome profile of Sars-CoV-2 infections, which included some blood samples of patients with bacterial sepsis among the control group. Although it wasn’t the focus of the study, they found upregulation of immune-mediated pathways, as well as pathways associated with hematological development in bacterial sepsis. Several differences were observed when bacterial sepsis and COVID-19 were compared.⁵⁷

Ito et al. compared the RNA expression differences in patients with COVID-19 and patients with bacterial sepsis in more detail. They found that mitochondrial-related transcripts that were upregulated in patients with COVID-19 and downregulated in the sepsis population, compared with healthy control group. Moreover, transcript concentrations of some proapoptotic genes were upregulated in the COVID-19 samples, whereas those of antiapoptotic genes, such as BCL2L11 and BCL2L1, were upregulated in bacterial sepsis.⁵⁸

Herwanto et al. recently provided raw and processed RNA sequencing data, obtained from whole blood of 105 individuals (uncomplicated infections, sepsis, and healthy control group). This dataset is a valuable resource to replicate and validate current studies and for further ideas.⁵⁹

Hortová-Kohoutková et al. published a combined RNA-seq and proteomic analysis of polymorphonuclear cells from patients with sepsis. They suggested that hyperactivation of these cells during the initial early stages of sepsis, resulting from increased type I interferon, IL-1 family, and NF-κB signaling, might be associated with early death.⁶⁰

Dai et al. performed RNA sequencing in neutrophils of sepsis patients and healthy control group. They detected increased gene expression of ARG1 in the sepsis samples and found that inhibition of ARG1 in the neutrophils leads to a marked restoration of CD8+ T cells’ immune function ex vivo.⁶¹

Finally, in 2022, Kalantar et al. published the first host and pathogen metagenomic RNA and DNA next-generation sequencing of whole blood and plasma, exhibiting its potential for sepsis diagnosis.⁶²

Single Cells RNA-seq

Gene expression studies at the single-cell concentration have highlighted that individual cells from an apparently homogenous population can display high heterogeneity at the mRNA concentration, providing greater resolution of different cell types and states, in addition to the discovery of novel cell types.⁶³

Single-cell-based approaches offer important advantages over bulk cell analysis, as signals from uninfected or non-specific cells dilute information about the host–pathogen interaction.⁶⁴ Multiple technologies, such as single-cell multi-omics sequencing, can provide even more information about the mechanisms under investigation.⁶⁵

In the context of septic shock, RNA sequencing of single cells (scRNA-seq) has brought valuable information, with applications in six studies to date.⁶⁶

Reyes et al. profiled a total of 106,545 blood mononuclear cells and 19,806 dendritic cells in 29 septic individuals and 36 healthy control group, defining 16 immune cell states. One of these states, found in monocytes and named MS1, is composed of CD14+ cells with high expression of RETN, ALOX5AP, and IL1R2. The authors found that MS1 is enriched in patients with sepsis. Performing a differential expression analysis in this cluster, compared with samples from critically ill non-infected patients, they propose that two genes (PLAC8 and CLU) could differentiate these two groups⁶⁷ (Fig. 2).

FIG. 2.

Illustration of key genes and gene families in septic shock, according to the transcriptomics studies conducted on human blood samples from 2007 to 2024 (curated analysis). APAF1 = apoptotic peptidase activating factor 1; CARD12 = caspase recruitment domain 12; CCNB2 = cyclin B2; CCR5 = C-C motif chemokine receptor 5; CD4 = CD4 molecule; CD86 = CD86 molecule; CD177 = CD177 molecule; CD244 = CD244 molecule; CD247 = CD247 molecule; CTSG = cathepsin G; CYTOKINES = cytokines family; ELANE = elastase; ELMOD2 = ELMO domain containing 2; GM-CSF = granulocyte-macrophage colony-stimulating factor; GZMB = Granzyme B; HIF1A = hypoxia inducible factor subunit alpha; HP = haptoglobin; IGF-1 = insulin-like growth factor 1; ITGs = integrins; KIRs = killer cell immunoglobulin like receptors; MAPKs = mitogen-activated protein kinases; MHC-II = major histocompatibility complex class II; MMPs = matrix metallopeptidases; OXPHOS = oxidative phosphorylation genes; PPARs = peroxisome proliferator activated receptors; TLRs = Toll-like receptors; ZRB = zinc-related biology (upregulated in red, downregulated in blue).

Jiang et al. compared patients with sepsis with ARDS with patients with sepsis that did not develop ARDS. They identified 53 DEGs. Among them, several IFN-related genes were upregulated in sepsis + ARDS compared with sepsis-only patients, with a preferential upregulation of type I IFN–regulated genes in the CD16⁺ monocyte cluster. Other intriguing genes included HLA-DQB1, a member of the HLA complex, and NAMPT, a regulator of intracellular NAD pool and cellular metabolism. REG, which encodes amphiregulin, was among the downregulated genes. Analyzing 29 genes that were selectively differentially regulated in the monocyte population, they found more genes of interest, such as RAB11A (a small GTPase that inhibits neutrophil efferocytosis), ATP2B1 (a gene that encodes a calcium pump), and SPARC, which promotes processing of procollagen to collagen.⁶⁸

Qiu et al. compared patients that survived septic shock with patients that did not. Blood samples were collected at an early time point, and fatal sepsis was associated with an expansion of platelets and erythrocyte precursors, and overall expression of genes related to hypoxic stress and inflammation, especially in the monocytes. Additionally, the lymphocyte subsets from non-survivors expressed genes related to exhaustion, and a switch in metabolic state was observed in platelets and monocytes, from oxidative phosphorylation to glycolysis.⁶⁹

Next, Darden et al. performed a scRNA-seq investigation of non-myeloid circulating cells in a limited number of surgical late sepsis patients (n = 4) and found signs of immunosuppression and low-grade inflammation in the lymphocytes.⁷⁰ Meanwhile, Wang et al. used scRNA-seq to profile the dynamics of peripheral blood mononuclear cells in two patients with sepsis secondary to bacterial pneumonia.⁷¹ Even though both studies are interesting, their sample size is too small.

Finally, Cheng et al. enrolled 18 immunocompromised patients with sepsis to identify transcriptomic features in this sepsis population. They found compromised T-cell function, altered metabolic signaling, and decreased T-cell diversity compared with immunocompetent control group.⁷²

Studies on sepsis, however, must consider both the host and the bacterial sides. Sepsis is a multi-faceted syndrome where the interplay between the host and the pathogen triggers varied functional states. An innovative technique, dual RNA-seq,⁷³ has been developed to investigate the correlation between bacterial gene activity and specific host responses.⁷⁴ A similar method for capturing both programs in single cells (scDual-seq) is also in progress, despite its technical limitations.⁶³

Future Challenges

Despite substantial advances, transcriptomics in sepsis still has limitations and challenges require attention. A substantial issue is the variability in study design, including patient populations, timing and number of samples, preanalytical and analytical methodology, and how the data were processed and statistically analyzed. Therefore, standardization of sample collection, processing, and data analysis are fundamental to the field's progression.

Another limitation of transcriptomic studies is the difficulty in identifying cell-specific and tissue-specific expression changes during sepsis. Such information might provide a better understanding of the mechanisms underlying immune cell dysfunction and subsequent organ failure. Advancement in single-cell transcriptomics and spatial transcriptomics technology may address this limitation by permitting the examination of unique transcriptional profiles from different cell types and preserving tissue architecture during gene expression analysis.⁷⁵

Sepsis is a lethal syndrome with heterogeneous clinical and molecular manifestations, making investigation challenging. Studies in human beings typically sample peripheral blood, which may not fully reflect events happening in other tissues. High-throughput transcriptomic studies using autopsy samples are crucial for a comprehensive investigation into this disease. Recently, our group published the first RNA-seq analysis conducted on autopsy samples from patients with sepsis, investigating multiple tissues. We investigated samples from the prefrontal cortex, hippocampus, heart, lung, kidney, and colon of seven individuals who succumbed to sepsis and seven uninfected control group. Our findings revealed that sepsis exhibits striking heterogeneity, even when comparing different tissues of the same patient. We found that sepsis is a heterogeneous disease at the organ level, but depending on the tissue investigated, certain innate immune pathways are preferentially activated.⁷⁶

Conclusions

It is essential to recognize the intricate nature of the subject matter explored in this review, as our collective comprehension of septic shock through transcriptomic data is multi-faceted. Each gene, pathway, and regulatory element unveiled represents a piece of the larger puzzle, underscoring the diverse viewpoints within the discipline. By recognizing the complexity and variability inherent in this area, we advance toward a more comprehensive and cohesive understanding of the molecular landscape that underlies human septic shock.

Similarly, it is crucial to acknowledge the significance of addressing potential discrepancies and conflicts observed in various transcriptomic studies within the realm of human septic shock, possibly influenced by factors such as time dependency and the foundational etiology of sepsis. It is evident that many findings warrant further validation, particularly considering the relatively early stage of development in this field.

Transcriptomic studies have substantially contributed to sepsis research, by revealing extensive gene expression dysregulation from the early stages of the disease. Integration of transcriptomic data with other omics data (such as genomics, proteomics, and metabolomics) may provide a more complete understanding of the molecular changes underlying sepsis and aid in identifying novel therapeutic targets and biomarkers.

The identification of robust biomarkers of immune dysfunction and the development of personalized therapies for patient subgroups are exciting prospects. Standardization of sample collection and data analysis, preservation of cell and tissue architecture, and integration with other omics data are imperative for further advancement of the field.

Footnotes

Authors’ Contributions

FPS reviewed the literature, wrote the manuscript and prepared the figures.

Author Disclosure Statement

The author declares no conflict of interest.

Funding Information

FPS is supported by the São Paulo Research Foundation (grant # 2020/03905-8).

References

Chiu

, Legrand

. Epidemiology of sepsis and septic shock. Curr Opin Anaesthesiol, 2021; 34(2):71–76, doi: 10.1097/ACO.0000000000000958

Singer

, Deutschman

, Seymour

, et al. The third international consensus definitions for Sepsis and Septic Shock (Sepsis-3). JAMA, 2016; 315(8):801–10, doi: 10.1001/jama.2016.0287

Font

, Thyagarajan

, Khanna

. Sepsis and Septic Shock—Basics of diagnosis, pathophysiology and clinical decision making. Med Clin North Am, 2020; 104(4):573–585, doi: 10.1016/j.mcna.2020.02.011

Reinhart

, Daniels

, Kissoon

, et al. Recognizing sepsis as a global health priority—a WHO resolution. N Engl J Med, 2017; 377(5):414–417, doi: 10.1056/NEJMp1707170

Olwal

, Nganyewo

, Tapela

, et al. Parallels in sepsis and COVID-19 conditions: Implications for managing severe COVID-19. Front Immunol, 2021; 12:602848, doi: 10.3389/fimmu.2021.602848

Dong

, Wang

, Liu

, et al. Lessons learned comparing immune system alterations of bacterial sepsis and SARS-CoV-2 sepsis. Front Immunol, 2020; 11:598404, doi: 10.3389/fimmu.2020.598404

Vachharajani

, McCall

. Epigenetic and metabolic programming of innate immunity in sepsis. Innate Immun, 2019; 25(5):267–279, doi: 10.1177/1753425919842320

Cross

, Drury

, Hill

, et al. Epigenetics in sepsis: Understanding its role in endothelial dysfunction, immunosuppression, and potential therapeutics. Front Immunol, 2019; 10:1363, doi: 10.3389/fimmu.2019.01363

Koutroulis

, Batabyal

, McNamara

, et al. Sepsis immunometabolism: From defining sepsis to understanding how energy production affects immune response. Crit Care Explor, 2019; 1(11):e0061, doi: 10.1097/CCE.0000000000000061

10.

Eckerle

, Ambroggio

, Puskarich

, et al. Metabolomics as a driver in advancing precision medicine in sepsis. Pharmacotherapy, 2017; 37(9):1023–1032, doi: 10.1002/phar.1974

11.

Caraballo

, Jaimes

. Organ dysfunction in sepsis: An ominous trajectory from infection to death. Yale J Biol Med, 2019; 92(4):629–640.

12.

Cecconi

, Evans

, Levy

, et al. Sepsis and septic shock. Lancet, 2018; 392(10141):75–87, doi: 10.1016/S0140-6736(18)30696-2

13.

Hotchkiss

, Moldawer

, Opal

, et al. Sepsis and septic shock. Nat Rev Dis Primers, 2016; 2(16045, doi: 10.1038/nrdp.2016.45

14.

Rubartelli

, Lotze

. Inside, outside, upside down: Damage-associated molecular-pattern molecules (DAMPs) and redox. Trends Immunol, 2007; 28(10):429–36, doi: 10.1016/j.it.2007.08.004

15.

Hotchkiss

, Karl

. The pathophysiology and treatment of sepsis. N Engl J Med, 2003; 348(2):138–50, doi: 10.1056/NEJMra021333

16.

Moskowitz

, Omar

, Chase

, et al. Reasons for death in patients with sepsis and septic shock. J Crit Care, 2017; 38:284–288, doi: 10.1016/j.jcrc.2016.11.036

17.

Thompson

, Venkatesh

, Finfer

. Sepsis and septic shock: Current approaches to management. Intern Med J, 2019; 49(2):160–170, doi: 10.1111/imj.14199

18.

Delano

, Ward

. The immune system's role in sepsis progression, resolution, and long-term outcome. Immunol Rev, 2016; 274(1):330–353, doi: 10.1111/imr.12499

19.

McBride

, Patil

, Bohannon

, et al. Immune checkpoints: Novel therapeutic targets to attenuate sepsis-induced immunosuppression. Front Immunol, 2020; 11:624272, doi: 10.3389/fimmu.2020.624272

20.

Liu

, Shou

, Chai

. Immune checkpoints in sepsis: New hopes and challenges. Int Rev Immunol, 2021; 1–10, doi: 10.1080/08830185.2021.1884247

21.

Evangelatos

, Satyamoorthy

, Levidou

, et al. Multi-omics research trends in sepsis: A bibliometric, comparative analysis between the United States, the European Union 28 Member States, and China. OMICS, 2018; 22(3):190–197, doi: 10.1089/omi.2017.0192

22.

Zhang

, Pan

, Ge

, et al. Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values. EBioMedicine, 2020; 62:103081, doi: 10.1016/j.ebiom.2020.103081

23.

Scicluna

, van Vught

, Zwinderman

, et al. Classification of patients with sepsis according to blood genomic endotype: A prospective cohort study. Lancet Respir Med, 2017; 5(10):816–826, doi: 10.1016/S2213-2600(17)30294-1

24.

Stanski

, Wong

. Prognostic and predictive enrichment in sepsis. Nat Rev Nephrol, 2020; 16(1):20–31, doi: 10.1038/s41581-019-0199-3

25.

Gliddon

, Herberg

, Levin

, et al. Genome-wide host RNA signatures of infectious diseases: Discovery and clinical translation. Immunology, 2018; 153(2):171–178, doi: 10.1111/imm.12841

26.

Chung

, Laramie

, Meyer

, et al. Molecular diagnostics in sepsis: From bedside to bench. J Am Coll Surg, 2006; 203(5):585–598, doi: 10.1016/j.jamcollsurg.2006.06.028

27.

Wong

, Shanley

, Sakthivel

, et al. Genome-level expression profiles in pediatric septic shock indicate a role for altered zinc homeostasis in poor outcome. Physiol Genomics, 2007; 30(2):146–55, doi: 10.1152/physiolgenomics.00024.2007

28.

Shanley

, Cvijanovich

, Lin

, et al. Genome-level longitudinal expression of signaling pathways and gene networks in pediatric septic shock. Mol Med, 2007; 13(9–10):495–508, doi: 10.2119/2007-00065.Shanley

29.

Cvijanovich

, Shanley

, Lin

, et al. Validating the genomic signature of pediatric septic shock. Physiol Genomics, 2008; 34(1):127–34, doi: 10.1152/physiolgenomics.00025.2008

30.

Wong

, Cvijanovich

, Allen

, et al. Genomic expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum. Crit Care Med, 2009; 37(5):1558–66, doi: 10.1097/CCM.0b013e31819fcc08

31.

Wong

, Freishtat

, Monaco

, et al. Leukocyte subset-derived genomewide expression profiles in pediatric septic shock. Pediatr Crit Care Med, 2010; 11(3):349–55, doi: 10.1097/PCC.0b013e3181c519b4

32.

Xiao

, Mindrinos

, Seok

, et al. A genomic storm in critically injured humans. J Exp Med, 2011; 208(13):2581–90, doi: 10.1084/jem.20111354

33.

Tang

, McLean

, Dawes

, et al. Gene-expression profiling of peripheral blood mononuclear cells in sepsis. Crit Care Med, 2009; 37(3):882–8, doi: 10.1097/CCM.0b013e31819b52fd

34.

Davenport

, Burnham

, Radhakrishnan

, et al. Genomic landscape of the individual host response and outcomes in sepsis: A prospective cohort study. Lancet Respir Med, 2016; 4(4):259–71, doi: 10.1016/S2213-2600(16)00046-1

35.

Wong

, Cvijanovich

, Lin

, et al. Identification of pediatric septic shock subclasses based on genome-wide expression profiling. BMC Med, 2009; 7:34, doi: 10.1186/1741-7015-7-34

36.

Maslove

, Tang

, McLean

. Identification of sepsis subtypes in critically ill adults using gene expression profiling. Crit Care, 2012; 16(5):R183, doi: 10.1186/cc11667

37.

Wynn

, Cvijanovich

, Allen

, et al. The influence of developmental age on the early transcriptomic response of children with septic shock. Mol Med, 2011; 17(11–12):1146–56, doi: 10.2119/molmed.2011.00169

38.

Severino

, Silva

, Baggio-Zappia

, et al. Patterns of gene expression in peripheral blood mononuclear cells and outcomes from patients with sepsis secondary to community acquired pneumonia. PLoS One, 2014; 9(3):e91886, doi: 10.1371/journal.pone.0091886

39.

Kangelaris

, Prakash

, Liu

, et al. Increased expression of neutrophil-related genes in patients with early sepsis-induced ARDS. Am J Physiol Lung Cell Mol Physiol, 2015; 308(11):L1102–L13, doi: 10.1152/ajplung.00380.2014

40.

McHugh

, Seldon

, Brandon

, et al. A molecular host response assay to discriminate between sepsis and infection-negative systemic inflammation in critically ill patients: Discovery and validation in independent cohorts. PLoS Med, 2015; 12(12):e1001916, doi: 10.1371/journal.pmed.1001916

41.

Rittirsch

, Schoenborn

, Lindig

, et al. An integrated clinico-transcriptomic approach identifies a central role of the Heme degradation pathway for septic complications after trauma. Ann Surg, 2016; 264(6):1125–1134, doi: 10.1097/SLA.0000000000001553

42.

Banerjee

, Mohammed

, Wong

, et al. Machine learning identifies complicated sepsis course and subsequent mortality based on 20 genes in peripheral blood immune cells at 24 H post-ICU Admission. Front Immunol, 2021; 12:592303, doi: 10.3389/fimmu.2021.592303

43.

Pinheiro da Silva

, Machado

Cesar

. Personalized medicine for sepsis. Am J Med Sci, 2015; 350(5):409–13, doi: 10.1097/MAJ.0000000000000558

44.

Vieira da Silva Pellegrina

, Severino

, Vieira Barbeiro

, et al. Septic shock in advanced age: Transcriptome analysis reveals altered molecular signatures in neutrophil granulocytes. PLoS One, 2015; 10(6):e0128341, doi: 10.1371/journal.pone.0128341

45.

Wynn

, Guthrie

, Wong

, et al. Postnatal age is a critical determinant of the neonatal host response to sepsis. Mol Med, 2015; 21:496–504, doi: 10.2119/molmed.2015.00064

46.

Wong

, Cvijanovich

, Allen

, et al. Corticosteroids are associated with repression of adaptive immunity gene programs in pediatric septic shock. Am J Respir Crit Care Med, 2014; 189(8):940–6, doi: 10.1164/rccm.201401-0171OC

47.

Tsalik

, Langley

, Dinwiddie

, et al. An integrated transcriptome and expressed variant analysis of sepsis survival and death. Genome Med, 2014; 6(11):111, doi: 10.1186/s13073-014-0111-5

48.

Pena

, Hancock

, Lyle

, et al. An endotoxin tolerance signature predicts sepsis and organ dysfunction at initial clinical presentation. EBioMedicine, 2014; 1(1):64–71, doi: 10.1016/j.ebiom.2014.10.003

49.

Barcella

, Bollen Pinto

, Braga

, et al. Identification of a transcriptome profile associated with improvement of organ function in septic shock patients after early supportive therapy. Crit Care, 2018; 22(1):312, doi: 10.1186/s13054-018-2242-3

50.

Washburn

, Wang

, Walton

, et al. T cell- and monocyte-specific RNA-sequencing analysis in septic and nonseptic critically ill patients and in patients with cancer. J Immunol, 2019; 203(7):1897–1908, doi: 10.4049/jimmunol.1900560

51.

Braga

, Barcella

, Herpain

, et al. A longitudinal study highlights shared aspects of the transcriptomic response to cardiogenic and septic shock. Crit Care, 2019; 23(1):414, doi: 10.1186/s13054-019-2670-8

52.

Englert

, Cho

, Lamb

, et al. Whole blood RNA sequencing reveals a unique transcriptomic profile in patients with ARDS following hematopoietic stem cell transplantation. Respir Res, 2019; 20(1):15, doi: 10.1186/s12931-019-0981-6

53.

Hato

, Maier

, Syed

, et al. Bacterial sepsis triggers an antiviral response that causes translation shutdown. J Clin Invest, 2019; 129(1):296–309, doi: 10.1172/JCI123284

54.

Liepelt

, Hohlstein

, Gussen

, et al. Differential gene expression in circulating CD14(+) monocytes indicates the prognosis of critically ill patients with sepsis. J Clin Med, 2020; 9(1), doi: 10.3390/jcm9010127

55.

, Strunk

, Lee

, et al. Whole blood transcriptional responses of very preterm infants during late-onset sepsis. PLoS One, 2020; 15(6):e0233841, doi: 10.1371/journal.pone.0233841

56.

Bustamante

, Opron

, Ehlenbach

, et al. Transcriptomic profiles of sepsis in the human brain. Am J Respir Crit Care Med, 2020; 201(7):861–863, doi: 10.1164/rccm.201909-1713LE

57.

, Granados

, Santos

, et al. A diagnostic host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood. Sci Adv, 2021; 7(6), doi: 10.1126/sciadv.abe5984

58.

Ito

, Ishikawa

, Matsumoto

, et al. Transcriptional differences between coronavirus disease 2019 and bacterial sepsis. Virol J, 2022; 19(1):198, doi: 10.1186/s12985-022-01930-y

59.

Herwanto

, Tang

, Wang

, et al. Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis. BMC Res Notes, 2021; 14(1):76, doi: 10.1186/s13104-021-05488-w

60.

Hortova-Kohoutkova

, De Zuani

, Laznickova

, et al. Polymorphonuclear cells show features of dysfunctional activation during fatal sepsis. Front Immunol, 2021; 12:741484, doi: 10.3389/fimmu.2021.741484

61.

Dai

, Ding

, Tan

, et al. Neutrophils inhibit CD8(+) T cells immune response by arginase-1 signaling in patients with sepsis. World J Emerg Med, 2022; 13(4):266–273, doi: 10.5847/wjem.j.1920-8642.2022.068

62.

Kalantar

, Neyton

, Abdelghany

, et al. Integrated host-microbe plasma metagenomics for sepsis diagnosis in a prospective cohort of critically ill adults. Nat Microbiol, 2022; 7(11):1805–1816, doi: 10.1038/s41564-022-01237-2

63.

Penaranda

, Hung

. Single-cell RNA sequencing to understand host-pathogen interactions. ACS Infect Dis, 2019; 5(3):336–344, doi: 10.1021/acsinfecdis.8b00369

64.

Chattopadhyay

, Roederer

, Bolton

. A deadly dance: the choreography of host-pathogen interactions, as revealed by single-cell technologies. Nat Commun, 2018; 9(1):4638, doi: 10.1038/s41467-018-06214-0

65.

Yasen

, Aini

, Wang

, et al. Progress and applications of single-cell sequencing techniques. Infect Genet Evol, 2020; 80:104198, doi: 10.1016/j.meegid.2020.104198

66.

Burel

, Apte

, Doolan

. Systems approaches towards molecular profiling of human immunity. Trends Immunol, 2016; 37(1):53–67, doi: 10.1016/j.it.2015.11.006

67.

Reyes

, Filbin

, Bhattacharyya

, et al. An immune-cell signature of bacterial sepsis. Nat Med, 2020; 26(3):333–340, doi: 10.1038/s41591-020-0752-4

68.

Jiang

, Rosborough

, Chen

, et al. Single cell RNA sequencing identifies an early monocyte gene signature in acute respiratory distress syndrome. JCI Insight, 2020; 5(13), doi: 10.1172/jci.insight.135678

69.

Qiu

, Li

, Bonenfant

, et al. Dynamic changes in human single-cell transcriptional signatures during fatal sepsis. J Leukoc Biol, 2021; 110(6):1253–1268, doi: 10.1002/JLB.5MA0721-825R

70.

Darden

, Dong

, Brusko

, et al. A novel single cell RNA-seq analysis of non-myeloid circulating cells in late sepsis. Front Immunol, 2021; 12(696536, doi: 10.3389/fimmu.2021.696536

71.

Wang

, Zhang

, Liu

, et al. Single-cell RNA sequencing reveals the sustained immune cell dysfunction in the pathogenesis of sepsis secondary to bacterial pneumonia. Genomics, 2021; 113(3):1219–1233, doi: 10.1016/j.ygeno.2021.01.026

72.

Cheng

, Chen

, Jiang

, et al. Using RNA-Seq to investigate immune-metabolism features in immunocompromised patients with sepsis. Front Med (Lausanne), 2021; 8(747263, doi: 10.3389/fmed.2021.747263

73.

Westermann

, Barquist

, Vogel

. Resolving host-pathogen interactions by dual RNA-seq. PLoS Pathog, 2017; 13(2):e1006033, doi: 10.1371/journal.ppat.1006033

74.

Saliba

, S

, Vogel

. New RNA-seq approaches for the study of bacterial pathogens. Curr Opin Microbiol, 2017; 35:78–87, doi: 10.1016/j.mib.2017.01.001

75.

Stubbington

MJT

, Rozenblatt-Rosen

, Regev

, et al. Single-cell transcriptomics to explore the immune system in health and disease. Science, 2017; 358(6359):58–63, doi: 10.1126/science.aan6828

76.

Pinheiro da Silva

, Goncalves

ANA

, Duarte-Neto

, et al. Transcriptome analysis of six tissues obtained post-mortem from sepsis patients. J Cell Mol Med, 2023; 27(20):3157–3167, doi: 10.1111/jcmm.17938