Patient stratification using plasma cytokines and their regulators in sepsis: relationship to outcomes, treatment effect and leucocyte transcriptomic subphenotypes

RATIONALE

Heterogeneity of the host response within sepsis, acute respiratory distress syndrome (ARDS) and more widely critical illness, limits discovery and targeting of immunomodulatory therapies. Clustering approaches using clinical and circulating biomarkers have defined hyper-inflammatory and hypo-inflammatory subphenotypes in ARDS associated with differential treatment response. It is unknown if similar subphenotypes exist in sepsis populations where leucocyte transcriptomic-defined subphenotypes have been reported.

OBJECTIVES

We investigated whether inflammatory clusters based on cytokine protein abundance were seen in sepsis, and the relationships with previously described transcriptomic subphenotypes.

METHODS

Hierarchical cluster and latent class analysis were applied to an observational study (UK Genomic Advances in Sepsis (GAinS)) (n=124 patients) and two clinical trial datasets (VANISH, n=155 and LeoPARDS, n=484) in which the plasma protein abundance of 65, 21, 11 circulating cytokines, cytokine receptors and regulators were quantified. Clinical features, outcomes, response to trial treatments and assignment to transcriptomic subphenotypes were compared between inflammatory clusters.

MEASUREMENTS AND MAIN RESULTS

We identified two (UK GAinS, VANISH) or three (LeoPARDS) inflammatory clusters. A group with high levels of pro-inflammatory and anti-inflammatory cytokines was seen that was associated with worse organ dysfunction and survival. No interaction between inflammatory clusters and trial treatment response was found. We found variable overlap of inflammatory clusters and leucocyte transcriptomic subphenotypes.

CONCLUSIONS

These findings demonstrate that differences in response at the level of cytokine biology show clustering related to severity, but not treatment response, and may provide complementary information to transcriptomic sepsis subphenotypes.

TRIAL REGISTRATION NUMBER

ISRCTN20769191, ISRCTN12776039.

A Transcriptomic Approach to Understand Patient Susceptibility to Pneumonia After Abdominal Surgery

OBJECTIVE

To describe immune pathways and gene networks altered following major abdominal surgery and to identify transcriptomic patterns associated with postoperative pneumonia.

BACKGROUND

Nosocomial infections are a major healthcare challenge, developing in over 20% of patients aged 45 or over undergoing major abdominal surgery, with postoperative pneumonia associated with an almost 5-fold increase in 30-day mortality.

METHODS

From a prospective consecutive cohort (n=150) undergoing major abdominal surgery, whole-blood RNA was collected preoperatively and at 3 time-points postoperatively (2-6, 24, and 48 h). Twelve patients diagnosed with postoperative pneumonia and 27 matched patients remaining infection-free were identified for analysis with RNA-sequencing.

RESULTS

Compared to preoperative sampling, 3639 genes were upregulated and 5043 downregulated at 2 to 6 hours. Pathway analysis demonstrated innate-immune activation with neutrophil degranulation and Toll-like-receptor signaling upregulation alongside adaptive-immune suppression. Cell-type deconvolution of preoperative RNA-sequencing revealed elevated S100A8/9-high neutrophils alongside reduced naïve CD4 T-cells in those later developing pneumonia. Preoperatively, a gene-signature characteristic of neutrophil degranulation was associated with postoperative pneumonia acquisition ( P =0.00092). A previously reported Sepsis Response Signature (SRSq) score, reflecting neutrophil dysfunction and a more dysregulated host response, at 48 hours postoperatively, differed between patients subsequently developing pneumonia and those remaining infection-free ( P =0.045). Analysis of the novel neutrophil gene-signature and SRSq scores in independent major abdominal surgery and polytrauma cohorts indicated good predictive performance in identifying patients suffering later infection.

CONCLUSIONS

Major abdominal surgery acutely upregulates innate-immune pathways while simultaneously suppressing adaptive-immune pathways. This is more prominent in patients developing postoperative pneumonia. Preoperative transcriptomic signatures characteristic of neutrophil degranulation and postoperative SRSq scores may be useful predictors of subsequent pneumonia risk.

BurkHostGEN: a study protocol for evaluating variations in the Burkholderia pseudomallei and host genomes associated with melioidosis infection

Background

Melioidosis is a frequently fatal disease caused by an environmental bacterium Burkholderia pseudomallei. The disease is prevalent in northeast Thailand, particularly among rice field farmers who are at risk of bacterial exposure through contact with contaminated soil and water. However, not all exposure results in disease, and infection can manifest diverse outcomes. We postulate that genetic factors, whether from the bacterium, the host or the combination of both, may influence disease outcomes. To address this hypothesis, we aim to collect, sequence, and analyse genetic data from melioidosis patients and controls, along with isolates of B. pseudomallei obtained from patients. Additionally, we will study the metagenomics of the household water supply for both patients and controls, including the presence of B. pseudomallei.

Methods

BurkHostGEN is an ongoing observational study being conducted at Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand. We are obtaining consent from 600 melioidosis patients and 700 controls, spanning both sexes, to collect 1 mL of blood for host DNA analysis, 3 mL of blood for RNA analysis, as well as 5 L of household water supply for metagenomic analysis. Additionally, we are isolating B. pseudomallei from the melioidosis patients to obtain bacterial DNA. This comprehensive approach will allow us to identify B. pseudomallei and their paired host genetic factors associated with disease acquisition and severity. Ethical approvals have been obtained for BurkHostGEN. Host and bacterial genetic data will be uploaded to European Genome-Phenome Archive (EGA) and European Nucleotide Archive (ENA), respectively.

Conclusions

BurkHostGEN holds the potential to discover bacterial and host genetic factors associated with melioidosis infection and severity of illness. It can also support various study designs, including biomarker validation, disease pathogenesis, and epidemiological analysis not only for melioidosis but also for other infectious diseases.

Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis

Sepsis arises from diverse and incompletely understood dysregulated host response processes following infection that leads to life-threatening organ dysfunction. Here we showed that neutrophils and emergency granulopoiesis drove a maladaptive response during sepsis. We generated a whole-blood single-cell multiomic atlas (272,993 cells, n = 39 individuals) of the sepsis immune response that identified populations of immunosuppressive mature and immature neutrophils. In co-culture, CD66b⁺ sepsis neutrophils inhibited proliferation and activation of CD4⁺ T cells. Single-cell multiomic mapping of circulating hematopoietic stem and progenitor cells (HSPCs) (29,366 cells, n = 27) indicated altered granulopoiesis in patients with sepsis. These features were enriched in a patient subset with poor outcome and a specific sepsis response signature that displayed higher frequencies of IL1R2⁺ immature neutrophils, epigenetic and transcriptomic signatures of emergency granulopoiesis in HSPCs and STAT3-mediated gene regulation across different infectious etiologies and syndromes. Our findings offer potential therapeutic targets and opportunities for stratified medicine in severe infection.

An atlas of genetic scores to predict multi-omic traits

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

Inducible apelin receptor knockdown reduces differentiation efficiency and contractility of hESC-derived cardiomyocytes

AIMS

The apelin receptor, a G protein-coupled receptor, has emerged as a key regulator of cardiovascular development, physiology, and disease. However, there is a lack of suitable human in vitro models to investigate the apelinergic system in cardiovascular cell types. For the first time we have used human embryonic stem cell-derived cardiomyocytes (hESC-CMs) and a novel inducible knockdown system to examine the role of the apelin receptor in both cardiomyocyte development and to determine the consequences of loss of apelin receptor function as a model of disease.

METHODS AND RESULTS

Expression of the apelin receptor and its ligands in hESCs and hESC-CMs was determined. hESCs carrying a tetracycline-inducible short hairpin RNA targeting the apelin receptor were generated using the sOPTiKD system. Phenotypic assays characterized the consequences of either apelin receptor knockdown before hESC-CM differentiation (early knockdown) or in 3D engineered heart tissues as a disease model (late knockdown). hESC-CMs expressed the apelin signalling system at a similar level to the adult heart. Early apelin receptor knockdown decreased cardiomyocyte differentiation efficiency and prolonged voltage sensing, associated with asynchronous contraction. Late apelin receptor knockdown had detrimental consequences on 3D engineered heart tissue contractile properties, decreasing contractility and increasing stiffness.

CONCLUSIONS

We have successfully knocked down the apelin receptor, using an inducible system, to demonstrate a key role in hESC-CM differentiation. Knockdown in 3D engineered heart tissues recapitulated the phenotype of apelin receptor down-regulation in a failing heart, providing a potential platform for modelling heart failure and testing novel therapeutic strategies.

Transcriptional reprogramming from innate immune functions to a pro-thrombotic signature by monocytes in COVID-19

Although alterations in myeloid cells have been observed in COVID-19, the specific underlying mechanisms are not completely understood. Here, we examine the function of classical CD14+ monocytes in patients with mild and moderate COVID-19 during the acute phase of infection and in healthy individuals. Monocytes from COVID-19 patients display altered expression of cell surface receptors and a dysfunctional metabolic profile that distinguish them from healthy monocytes. Secondary pathogen sensing ex vivo leads to defects in pro-inflammatory cytokine and type-I IFN production in moderate COVID-19 cases, together with defects in glycolysis. COVID-19 monocytes switch their gene expression profile from canonical innate immune to pro-thrombotic signatures and are functionally pro-thrombotic, both at baseline and following ex vivo stimulation with SARS-CoV-2. Transcriptionally, COVID-19 monocytes are characterized by enrichment of pathways involved in hemostasis, immunothrombosis, platelet aggregation and other accessory pathways to platelet activation and clot formation. These results identify a potential mechanism by which monocyte dysfunction may contribute to COVID-19 pathology.

Genetically personalised organ-specific metabolic models in health and disease

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.

Mechanistic study of the effect of Endothelin SNPs in microvascular angina – Protocol of the PRIZE Endothelin Sub-Study

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Microvascular angina is a common cause of ischemia with non-obstructive coronary arteries (INOCA).

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Endothelin-1 (ET-1) is a potent vasoconstrictor implicated in the pathophysiology of microvascular angina.

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Zibotentan, an Endothelin Receptor Antagonist is being tested as a treatment for microvascular angina in the ‘PRIZE’ trial using a genetic ‘precision medicine’ approach.

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The PRIZE ET Sub-study will provide a comprehensive genotype and phenotype bio-resource for microvascular angina patients.

Introduction

Microvascular angina is a common cause of ischemia with non-obstructive coronary arteries (INOCA) and limited therapeutic options are available to those affected. Endothelin-1 (ET-1) is a potent vasoconstrictor implicated in the pathophysiology of microvascular angina. A large randomised, double blinded, placebo controlled crossover trial, the PRecIsion medicine with ZibotEntan in microvascular angina (PRIZE) trial is currently underway, investigating an endothelin receptor antagonist – Zibotentan, as a new drug treatment for microvascular angina. The trial uses a 'precision medicine' approach by preferential selection of those with higher ET-1 expression conferred by the PHACTR1 minor G allele single nucleotide polymorphism (SNP). The incidence of this SNP occurs in approximately one third of the population therefore a considerable number of screened patients will be ineligible for randomisation and the treatment phase of the trial.

Methods

In the PRIZE Endothelin (ET) Sub-Study, patients screened out of the PRIZE trial will be genotyped for other genetic variants in the ET-1 pathway. These will be correlated with phenotypic characteristics including exercise tolerance, angina severity and quantitative measures of microvascular function on cardiovascular MRI as well as mechanistic data on endothelin pathway signalling.

Conclusions

The study will provide a comprehensive genotype and phenotype bio-resource identifying novel ET-1 genotypes to inform the potential wider use of endothelin receptor antagonists for this indication.

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19.

Blood leukocyte transcriptomes in gram-positive and gram-negative community-acquired pneumonia

BACKGROUND

Gram-positive and Gram-negative bacteria are the most common causative pathogens in community-acquired pneumonia (CAP) on the intensive care unit (ICU). The aim of this study was to determine whether the host immune response differs between Gram-positive and Gram-negative CAP upon ICU admission.

METHODS

Sixteen host response biomarkers providing insight in pathophysiological mechanisms implicated in sepsis and blood leukocyte transcriptomes were analysed in patients with CAP upon ICU admission in two tertiary hospitals in the Netherlands.

RESULTS

309 patients with CAP with a definite or probable likelihood (determined by predefined criteria) were included. A causative pathogen was determined in 74.4% of admissions. Patients admitted with Gram-positive CAP (n=90) were not different from those admitted with Gram-negative CAP (n=75) regarding demographics, chronic comorbidities, severity of disease and mortality. Host response biomarkers reflective of systemic inflammation, coagulation activation and endothelial cell function, as well as blood leukocytes transcriptomes, were largely similar between Gram-positive and Gram-negative CAP. Blood leukocyte transcriptomes were also similar in Gram-positive and Gram-negative CAP in two independent validation cohorts. On a pathogen-specific level, Streptococcus pneumoniae and Escherichia coli induced the most distinct host immune response.

CONCLUSION

Outcome and host response are similar in critically ill patients with CAP due to Gram-positive bacteria compared to Gram-negative bacteria.

Interactions Between Genome-Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus

OBJECTIVE

To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE).

METHODS

For the study, 673 patients with SLE (diagnosed according to the American College of Rheumatology 1997 updated classification criteria) were matched by age, sex, and race (first 3 genetic principal components) to 3,272 control subjects without a history of connective tissue disease. Smoking status was classified as current smoking/having recently quit smoking within 4 years before diagnosis (or matched index date for controls) versus distant past/never smoking. In total, 86 single-nucleotide polymorphisms and 10 classic HLA alleles previously associated with SLE were included in a weighted genetic risk score (wGRS), with scores dichotomized as either low or high based on the median value in control subjects (low wGRS being defined as less than or equal to the control median; high wGRS being defined as greater than the control median). Conditional logistic regression models were used to estimate both the risk of SLE and risk of anti-double-stranded DNA autoantibody-positive (dsDNA+) SLE. Additive interactions were assessed using the attributable proportion (AP) due to interaction, and multiplicative interactions were assessed using a chi-square test (with 1 degree of freedom) for the wGRS and for individual risk alleles. Separate repeated analyses were carried out among subjects of European ancestry only.

RESULTS

The mean ± SD age of the SLE patients at the time of diagnosis was 36.4 ± 15.3 years. Among the 673 SLE patients included, 92.3% were female and 59.3% were dsDNA+. Ethnic distributions were as follows: 75.6% of European ancestry, 4.5% of Asian ancestry, 11.7% of African ancestry, and 8.2% classified as other ancestry. A high wGRS (odds ratio [OR] 2.0, P = 1.0 × 10^-51 versus low wGRS) and a status of current/recent smoking (OR 1.5, P = 0.0003 versus distant past/never smoking) were strongly associated with SLE risk, with significant additive interaction (AP 0.33, P = 0.0012), and associations with the risk of anti-dsDNA+ SLE were even stronger. No significant multiplicative interactions with the total wGRS (P = 0.58) or with the HLA-only wGRS (P = 0.06) were found. Findings were similar in analyses restricted to only subjects of European ancestry.

CONCLUSION

The strong additive interaction between an updated SLE genetic risk score and current/recent smoking suggests that smoking may influence specific genes in the pathogenesis of SLE.

IMPACT: Genomic Annotation of Cell-State-Specific Regulatory Elements Inferred from the Epigenome of Bound Transcription Factors

Despite significant progress in annotating the genome with experimental methods, much of the regulatory noncoding genome remains poorly defined. Here we assert that regulatory elements may be characterized by leveraging local epigenomic signatures where specific transcription factors (TFs) are bound. To link these two features, we introduce IMPACT, a genome annotation strategy that identifies regulatory elements defined by cell-state-specific TF binding profiles, learned from 515 chromatin and sequence annotations. We validate IMPACT using multiple compelling applications. First, IMPACT distinguishes between bound and unbound TF motif sites with high accuracy (average AUPRC 0.81, SE 0.07; across 8 tested TFs) and outperforms state-of-the-art TF binding prediction methods, MocapG, MocapS, and Virtual ChIP-seq. Second, in eight tested cell types, RNA polymerase II IMPACT annotations capture more cis-eQTL variation than sequence-based annotations, such as promoters and TSS windows (25% average increase in enrichment). Third, integration with rheumatoid arthritis (RA) summary statistics from European (N = 38,242) and East Asian (N = 22,515) populations revealed that the top 5% of CD4+ Treg IMPACT regulatory elements capture 85.7% of RA h2, the most comprehensive explanation for RA h2 to date. In comparison, the average RA h2 captured by compared CD4+ T histone marks is 42.3% and by CD4+ T specifically expressed gene sets is 36.4%. Lastly, we find that IMPACT may be used in many different cell types to identify complex trait associated regulatory elements.

Discovering in vivo cytokine-eQTL interactions from a lupus clinical trial

BACKGROUND

Cytokines are critical to human disease and are attractive therapeutic targets given their widespread influence on gene regulation and transcription. Defining the downstream regulatory mechanisms influenced by cytokines is central to defining drug and disease mechanisms. One promising strategy is to use interactions between expression quantitative trait loci (eQTLs) and cytokine levels to define target genes and mechanisms.

RESULTS

In a clinical trial for anti-IL-6 in patients with systemic lupus erythematosus, we measure interferon (IFN) status, anti-IL-6 drug exposure, and whole blood genome-wide gene expression at three time points. We show that repeat transcriptomic measurements increases the number of cis eQTLs identified compared to using a single time point. We observe a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 drug exposure and find many novel interactions that have not been previously described. Finally, we find transcription factor binding motifs interrupted by eQTL interaction SNPs, which point to key regulatory mediators of these environmental stimuli and therefore potential therapeutic targets for autoimmune diseases. In particular, genes with IFN interactions are enriched for ISRE binding site motifs, while those with anti-IL-6 interactions are enriched for IRF4 motifs.

CONCLUSIONS

This study highlights the potential to exploit clinical trial data to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

A community approach to mortality prediction in sepsis via gene expression analysis

Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.

Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study

BACKGROUND

Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis.

METHODS

This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice.

FINDINGS

The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0·022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1·86 [95% CI 1·21-2·86]; p=0·0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0·64 [0·40-1·04]; p=0·061), 16 (23%) of 71 people with a Mars3 endotype (HR 0·71 [0·41-1·22]; p=0·19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1·13 [0·63-2·04]; p=0·69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0·33 (0·09-0·58; p=0·008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype.

INTERPRETATION

This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials.

FUNDING

Center for Translational Molecular Medicine, Netherlands.

Shared and Distinct Aspects of the Sepsis Transcriptomic Response to Fecal Peritonitis and Pneumonia

RATIONALE

Heterogeneity in the septic response has hindered efforts to understand pathophysiology and develop targeted therapies. Source of infection, with different causative organisms and temporal changes, might influence this heterogeneity.

OBJECTIVES

To investigate individual and temporal variations in the transcriptomic response to sepsis due to fecal peritonitis, and to compare these with the same parameters in community-acquired pneumonia.

METHODS

We performed genome-wide gene expression profiling in peripheral blood leukocytes of adult patients admitted to intensive care with sepsis due to fecal peritonitis (n = 117) or community-acquired pneumonia (n = 126), and of control subjects without sepsis (n = 10).

MEASUREMENTS AND MAIN RESULTS

A substantial portion of the transcribed genome (18%) was differentially expressed compared with that of control subjects, independent of source of infection, with eukaryotic initiation factor 2 signaling being the most enriched canonical pathway. We identified two sepsis response signature (SRS) subgroups in fecal peritonitis associated with early mortality (P = 0.01; hazard ratio, 4.78). We defined gene sets predictive of SRS group, and serial sampling demonstrated that subgroup membership is dynamic during intensive care unit admission. We found that SRS is the major predictor of transcriptomic variation; a small number of genes (n = 263) were differentially regulated according to the source of infection, enriched for IFN signaling and antigen presentation. We define temporal changes in gene expression from disease onset involving phagosome formation as well as natural killer cell and IL-3 signaling.

CONCLUSIONS

The majority of the sepsis transcriptomic response is independent of the source of infection and includes signatures reflecting immune response state and prognosis. A modest number of genes show evidence of specificity. Our findings highlight opportunities for patient stratification and precision medicine in sepsis.

Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study

BACKGROUND

Effective targeted therapy for sepsis requires an understanding of the heterogeneity in the individual host response to infection. We investigated this heterogeneity by defining interindividual variation in the transcriptome of patients with sepsis and related this to outcome and genetic diversity.

METHODS

We assayed peripheral blood leucocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with sepsis due to community-acquired pneumonia and evidence of organ dysfunction. We then validated our findings in a replication cohort consisting of a further 106 patients. We mapped genomic determinants of variation in gene transcription between patients as expression quantitative trait loci (eQTL).

FINDINGS

We discovered that following admission to intensive care, transcriptomic analysis of peripheral blood leucocytes defines two distinct sepsis response signatures (SRS1 and SRS2). The presence of SRS1 (detected in 108 [41%] patients in discovery cohort) identifies individuals with an immunosuppressed phenotype that included features of endotoxin tolerance, T-cell exhaustion, and downregulation of human leucocyte antigen (HLA) class II. SRS1 was associated with higher 14 day mortality than was SRS2 (discovery cohort hazard ratio (HR) 2·4, 95% CI 1·3-4·5, p=0·005; validation cohort HR 2·8, 95% CI 1·5-5·1, p=0·0007). We found that a predictive set of seven genes enabled the classification of patients as SRS1 or SRS2. We identified cis-acting and trans-acting eQTL for key immune and metabolic response genes and sepsis response networks. Sepsis eQTL were enriched in endotoxin-induced epigenetic marks and modulated the individual host response to sepsis, including effects specific to SRS group. We identified regulatory genetic variants involving key mediators of gene networks implicated in the hypoxic response and the switch to glycolysis that occurs in sepsis, including HIF1α and mTOR, and mediators of endotoxin tolerance, T-cell activation, and viral defence.

INTERPRETATION

Our integrated genomics approach advances understanding of heterogeneity in sepsis by defining subgroups of patients with different immune response states and prognoses, as well as revealing the role of underlying genetic variation. Our findings provide new insights into the pathogenesis of sepsis and create opportunities for a precision medicine approach to enable targeted therapeutic intervention to improve sepsis outcomes.

FUNDING

European Commission, Medical Research Council (UK), and the Wellcome Trust.

Chronic mucocutaneous candidiasis: characterization of a family with STAT-1 gain-of-function and development of an ex-vivo assay for Th17 deficiency of diagnostic utility

Chronic mucocutaneous candidiasis (CMC) is characterized by recurrent and persistent superficial infections, with Candida albicans affecting the mucous membranes, skin and nails. It can be acquired or caused by primary immune deficiencies, particularly those that impair interleukin (IL)−17 and IL‐22 immunity. We describe a single kindred with CMC and the identification of a STAT1 GOF mutation by whole exome sequencing (WES). We show how detailed clinical and immunological phenotyping of this family in the context of WES has enabled revision of disease status and clinical management. Together with analysis of other CMC cases within our cohort of patients, we used knowledge arising from the characterization of this family to develop a rapid ex‐vivo screening assay for the detection of T helper type 17 (Th17) deficiency better suited to the routine diagnostic setting than established in‐vitro techniques, such as intracellular cytokine staining and enzyme‐linked immunosorbent assay (ELISA) using cell culture supernatants. We demonstrate that cell surface staining of unstimulated whole blood for CCR6⁺CXCR3^–CCR4⁺CD161⁺ T helper cells generates results that correlate with intracellular cytokine staining for IL‐17A, and is able to discriminate between patients with molecularly defined CMC and healthy controls with 100% sensitivity and specificity within the cohort tested. Furthermore, removal of CCR4 and CD161 from the antibody staining panel did not affect assay performance, suggesting that the enumeration of CCR6⁺CXCR3^–CD4⁺ T cells is sufficient for screening for Th17 deficiency in patients with CMC and could be used to guide further investigation aimed at identifying the underlying molecular cause.

Application of whole genome and RNA sequencing to investigate the genomic landscape of common variable immunodeficiency disorders

Common Variable Immunodeficiency Disorders (CVIDs) are the most prevalent cause of primary antibody failure. CVIDs are highly variable and a genetic causes have been identified in <5% of patients. Here, we performed whole genome sequencing (WGS) of 34 CVID patients (94% sporadic) and combined them with transcriptomic profiling (RNA-sequencing of B cells) from three patients and three healthy controls. We identified variants in CVID disease genes TNFRSF13B, TNFRSF13C, LRBA and NLRP12 and enrichment of variants in known and novel disease pathways. The pathways identified include B-cell receptor signalling, non-homologous end-joining, regulation of apoptosis, T cell regulation and ICOS signalling. Our data confirm the polygenic nature of CVID and suggest individual-specific aetiologies in many cases. Together our data show that WGS in combination with RNA-sequencing allows for a better understanding of CVIDs and the identification of novel disease associated pathways.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

Genome-wide association study of survival from sepsis due to pneumonia: an observational cohort study

BACKGROUND

Sepsis continues to be a major cause of death, disability, and health-care expenditure worldwide. Despite evidence suggesting that host genetics can influence sepsis outcomes, no specific loci have yet been convincingly replicated. The aim of this study was to identify genetic variants that influence sepsis survival.

METHODS

We did a genome-wide association study in three independent cohorts of white adult patients admitted to intensive care units with sepsis, severe sepsis, or septic shock (as defined by the International Consensus Criteria) due to pneumonia or intra-abdominal infection (cohorts 1-3, n=2534 patients). The primary outcome was 28 day survival. Results for the cohort of patients with sepsis due to pneumonia were combined in a meta-analysis of 1553 patients from all three cohorts, of whom 359 died within 28 days of admission to the intensive-care unit. The most significantly associated single nucleotide polymorphisms (SNPs) were genotyped in a further 538 white patients with sepsis due to pneumonia (cohort 4), of whom 106 died.

FINDINGS

In the genome-wide meta-analysis of three independent pneumonia cohorts (cohorts 1-3), common variants in the FER gene were strongly associated with survival (p=9·7 × 10(-8)). Further genotyping of the top associated SNP (rs4957796) in the additional cohort (cohort 4) resulted in a combined p value of 5·6 × 10(-8) (odds ratio 0·56, 95% CI 0·45-0·69). In a time-to-event analysis, each allele reduced the mortality over 28 days by 44% (hazard ratio for death 0·56, 95% CI 0·45-0·69; likelihood ratio test p=3·4 × 10(-9), after adjustment for age and stratification by cohort). Mortality was 9·5% in patients carrying the CC genotype, 15·2% in those carrying the TC genotype, and 25·3% in those carrying the TT genotype. No significant genetic associations were identified when patients with sepsis due to pneumonia and intra-abdominal infection were combined.

INTERPRETATION

We have identified common variants in the FER gene that associate with a reduced risk of death from sepsis due to pneumonia. The FER gene and associated molecular pathways are potential novel targets for therapy or prevention and candidates for the development of biomarkers for risk stratification.

FUNDING

European Commission and the Wellcome Trust.

Transcriptomic profiling facilitates classification of response to influenza challenge

Abstract

Despite increases in vaccination coverage, reductions in influenza-related mortality have not been observed. Better vaccines are therefore required and influenza challenge studies can be used to test the efficacy of new vaccines. However, this requires the accurate post-challenge classification of subjects by outcome, which is limited in current methods that use artificial thresholds to assign ‘symptomatic’ and ‘asymptomatic’ phenotypes. We present data from an influenza challenge study in which 22 healthy adults (11 vaccinated) were inoculated with H3N2 influenza (A/Wisconsin/67/2005). We generated genome-wide gene expression data from peripheral blood taken immediately before the challenge and at 12, 24 and 48 h post-challenge. Variation in symptomatic scoring was found amongst those with laboratory confirmed influenza. By combining the dynamic transcriptomic data with the clinical parameters this variability can be reduced. We identified four subjects with severe laboratory confirmed influenza that show differential gene expression in 1103 probes 48 h post-challenge compared to the remaining subjects. We have further reduced this profile to six genes (CCL2, SEPT4, LAMP3, RTP4, MT1G and OAS3) that can be used to define these subjects. We have used this gene set to predict symptomatic infection from an independent study. This analysis gives further insight into host-pathogen interactions during influenza infection. However, the major potential value is in the clinical trial setting by providing a more quantitative method to better classify symptomatic individuals post influenza challenge.

Key message

Differential gene expression signatures are seen following influenza challenge.

Expression of six predictive genes can classify response to influenza challenge.

The genomic influenza response classification replicates in an independent dataset.

Electronic supplementary material

The online version of this article (doi:10.1007/s00109-014-1212-8) contains supplementary material, which is available to authorized users.

A common haplotype of the TNF receptor 2 gene modulates endotoxin tolerance

Endotoxin tolerance is characterized by the suppression of further TNF release upon recurrent exposure to LPS. This phenomenon is proposed to act as a homeostatic mechanism preventing uncontrolled cytokine release such as that observed in bacterial sepsis. The regulatory mechanisms and interindividual variation of endotoxin tolerance induction in man remain poorly characterized. In this paper, we describe a genetic association study of variation in endotoxin tolerance among healthy individuals. We identify a common promoter haplotype in TNFRSF1B (encoding TNFR2) to be strongly associated with reduced tolerance to LPS (p = 5.82 × 10(-6)). This identified haplotype is associated with increased expression of TNFR2 (p = 4.9 × 10(-5)), and we find basal expression of TNFR2, irrespective of genotype and unlike TNFR1, is associated with secondary TNF release (p < 0.0001). Functional studies demonstrate a positive-feedback loop via TNFR2 of LPS-induced TNF release, confirming this previously unrecognized role for TNFR2 in the modulation of LPS response.