Beyond single-marker analyses: mining whole genome scans for insights into treatment responses in severe sepsis

Genetic variants associated with sepsis

BACKGROUND

The variable presentations and different phenotypes of sepsis suggest that risk of sepsis comes from many genes each having a small effect. The cumulative effect can be used to create individual risk profile. The purpose of this study was to create a polygenic risk score and determine the genetic variants associated with sepsis.

METHODS

We sequenced ~14 million single nucleotide polymorphisms with a minimac imputation quality R2>0.3 and minor allele frequency >10-6 in patients with Sepsis-2 or Sepsis-3. Genome-wide association was performed using Firth bias-corrected logistic regression. Semi-parsimonious logistic regression was used to create polygenic risk scores and reduced regression to determine the genetic variants independently associated with sepsis.

FINDINGS

2261 patients had sepsis and 13,068 control patients did not. The polygenic risk scores had good discrimination: c-statistic = 0.752 ± 0.005 for Sepsis-2 and 0.752 ± 0.007 for Sepsis-3. We found 772 genetic variants associated with Sepsis-2 and 442 with Sepsis-3, p<0.01. After multivariate adjustment, 100 variants on 85 genes were associated with Sepsis-2 and 69 variants in 54 genes with Sepsis-3. Twenty-five variants were present in both the Sepsis-2 and Sepsis-3 groups out of 32 genes that were present in both groups. The other 7 genes had different variants present. Most variants had small effect sizes.

CONCLUSIONS

Sepsis-2 and Sepsis-3 have both separate and shared genetic variants. Most genetic variants have small effects sizes, but cumulatively, the polygenic risk scores have good discrimination.

Immune System Disequilibrium-Neutrophils, Their Extracellular Traps, and COVID-19-Induced Sepsis

Equilibrium within the immune system can often determine the fate of its host. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic. Immune dysregulation remains one of the main pathophysiological components of SARS-CoV-2-associated organ injury, with over-activation of the innate immune system, and induced apoptosis of adaptive immune cells. Here, we provide an overview of the innate immune system, both in general and relating to COVID-19. We specifically discuss "NETosis," the process of neutrophil release of their extracellular traps, which may be a more recently described form of cell death that is different from apoptosis, and how this may propagate organ dysfunction in COVID-19. We complete this review by discussing Stem Cell Therapies in COVID-19 and emerging COVID-19 phenotypes, which may allow for more targeted therapy in the future. Finally, we consider the array of potential therapeutic targets in COVID-19, and associated therapeutics.

Pharmacometabolomics identifies candidate predictor metabolites of an L-carnitine treatment mortality benefit in septic shock

Sepsis‐induced metabolic dysfunction contributes to organ failure and death. L‐carnitine has shown promise for septic shock, but a recent phase II study of patients with vasopressor‐dependent septic shock demonstrated a non‐significant reduction in mortality. We undertook a pharmacometabolomics study of these patients (n = 250) to identify metabolic profiles predictive of a 90‐day mortality benefit from L‐carnitine. The independent predictive value of each pretreatment metabolite concentration, adjusted for L‐carnitine dose, on 90‐day mortality was determined by logistic regression. A grid‐search analysis maximizing the Z‐statistic from a binomial proportion test identified specific metabolite threshold levels that discriminated L‐carnitine responsive patients. Threshold concentrations were further assessed by hazard ratio and Kaplan‐Meier estimate. Accounting for L‐carnitine treatment and dose, 11 ¹H‐NMR metabolites and 12 acylcarnitines were independent predictors of 90‐day mortality. Based on the grid‐search analysis numerous acylcarnitines and valine were identified as candidate metabolites of drug response. Acetylcarnitine emerged as highly viable for the prediction of an L‐carnitine mortality benefit due to its abundance and biological relevance. Using its most statistically significant threshold concentration, patients with pretreatment acetylcarnitine greater than or equal to 35 µM were less likely to die at 90 days if treated with L‐carnitine (18 g) versus placebo (p = 0.01 by log rank test). Metabolomics also identified independent predictors of 90‐day sepsis mortality. Our proof‐of‐concept approach shows how pharmacometabolomics could be useful for tackling the heterogeneity of sepsis and informing clinical trial design. In addition, metabolomics can help understand mechanisms of sepsis heterogeneity and variable drug response, because sepsis induces alterations in numerous metabolite concentrations.

Genetic Predisposition to the Mortality in Septic Shock Patients: From GWAS to the Identification of a Regulatory Variant Modulating the Activity of a CISH Enhancer

The high mortality rate in septic shock patients is likely due to environmental and genetic factors, which influence the host response to infection. Two genome-wide association studies (GWAS) on 832 septic shock patients were performed. We used integrative bioinformatic approaches to annotate and prioritize the sepsis-associated single nucleotide polymorphisms (SNPs). An association of 139 SNPs with death based on a false discovery rate of 5% was detected. The most significant SNPs were within the CISH gene involved in cytokine regulation. Among the 139 SNPs associated with death and the 1311 SNPs in strong linkage disequilibrium with them, we investigated 1439 SNPs within non-coding regions to identify regulatory variants. The highest integrative weighted score (IW-score) was obtained for rs143356980, indicating that this SNP is a robust regulatory candidate. The rs143356980 region is located in a non-coding region close to the CISH gene. A CRISPR-Cas9-mediated deletion of this region and specific luciferase assays in K562 cells showed that rs143356980 modulates the enhancer activity in K562 cells. These analyses allowed us to identify several genes associated with death in patients with septic shock. They suggest that genetic variations in key genes, such as CISH, perturb relevant pathways, increasing the risk of death in sepsis patients.

Biomarkers in critical care nutrition

The goal of nutrition support is to provide the substrates required to match the bioenergetic needs of the patient and promote the net synthesis of macromolecules required for the preservation of lean mass, organ function, and immunity. Contemporary observational studies have exposed the pervasive undernutrition of critically ill patients and its association with adverse clinical outcomes. The intuitive hypothesis is that optimization of nutrition delivery should improve ICU clinical outcomes. It is therefore surprising that multiple large randomized controlled trials have failed to demonstrate the clinical benefit of restoring or maximizing nutrient intake. This may be in part due to the absence of biological markers that identify patients who are most likely to benefit from nutrition interventions and that monitor the effects of nutrition support. Here, we discuss the need for practical risk stratification tools in critical care nutrition, a proposed rationale for targeted biomarker development, and potential approaches that can be adopted for biomarker identification and validation in the field.

Precision Medicine in Critical Illness: Sepsis and Acute Respiratory Distress Syndrome

Sepsis and the acute respiratory distress syndrome (ARDS) each cause substantial morbidity and mortality. In contrast to other lung diseases, the entire course of disease in these syndromes is measured in days to weeks rather than months to years, which raises unique challenges in achieving precision medicine. We review advances in sepsis and ARDS resulting from omics studies, including those involving genome-wide association, gene expression, targeted proteomics, and metabolomics approaches. We focus on promising evidence of biological subtypes in both sepsis and ARDS that consistently display high risk for death. In sepsis, a gene expression signature with dysregulated adaptive immune signaling has evidence for a differential response to systemic steroid therapy, whereas in ARDS, a hyperinflammatory pattern identified in plasma using targeted proteomics responded more favorably to randomized interventions including high positive end-expiratory pressure, volume conservative fluid therapy, and simvastatin therapy. These early examples suggest heterogeneous biology that may be challenging to detect by clinical factors alone and speak to the promise of a precision approach that targets the right treatment at the right time to the right patient.

CTLA-4 Genetic Variants Predict Survival in Patients with Sepsis

Cytotoxic T lymphocyte-associated protein 4 (CTLA-4) is a coinhibitory checkpoint protein expressed on the surface of T cells. A recent study by our working group revealed that the rs231775 single nucleotide polymorphism (SNP) in the CTLA-4 gene was associated with the survival of patients with sepsis and served as an independent prognostic variable. To further investigate the impact of CTLA-4 genetic variants on sepsis survival, we examined the effect of two functional SNPs, CTLA-4 rs733618 and CTLA-4 rs3087243, and inferred haplotypes, on the survival of 644 prospectively enrolled septic patients. Kaplan⁻Meier survival analysis revealed significantly lower 90-day mortality for rs3087243 G allele carriers (n = 502) than for AA-homozygous (n = 142) patients (27.3% vs. 40.8%, p = 0.0024). Likewise, lower 90-day mortality was observed for TAA haplotype-negative patients (n = 197; compound rs733618 T/rs231775 A/rs3087243 A) than for patients carrying the TAA haplotype (n = 447; 24.4% vs. 32.9%, p = 0.0265). Carrying the rs3087243 G allele hazard ratio (HR): 0.667; 95% confidence interval (CI): 0.489⁻0.909; p = 0.0103) or not carrying the TAA haplotype (HR: 0.685; 95% CI: 0.491⁻0.956; p = 0.0262) remained significant covariates for 90-day survival in the multivariate Cox regression analysis and thus served as independent prognostic variables. In conclusion, our findings underscore the significance of CTLA-4 genetic variants as predictors of survival of patients with sepsis.

Sepsis Diagnostics in the Era of "Omics" Technologies

Sepsis is a multifactorial clinical syndrome with an extremely dynamic clinical course and with high diverse clinical phenotype. Early diagnosis is crucial for the final clinical outcome. Previous studies have not identified a biomarker for the diagnosis of sepsis which would have sufficient sensitivity and specificity. Identification of the infectious agents or the use of molecular biology, next gene sequencing, has not brought significant benefit for the patient in terms of early diagnosis. Therefore, we are currently searching for biomarkers, through "omics" technologies with sufficient diagnostic specificity and sensitivity, able to predict the clinical course of the disease and the patient response to therapy. Current progress in the use of systems biology technologies brings us hope that by using big data from clinical trials such biomarkers will be found.

Nutritional metabolomics in critical illness

PURPOSE OF REVIEW

Disruption of metabolic homeostasis is universal in the critically ill. Macronutrients and micronutrients are major environmental regulators of metabolite production through their gene regulation effects. The study of large numbers of circulating metabolites is beginning to emerge through the comprehensive profiling of the critically ill. In the critically ill, metabolomic studies consistently show that changes in fatty acids, lipids and tryptophan metabolite pathways are common and are associated with disease state and outcomes.

RECENT FINDINGS

Metabolomics is now being applied in research studies to determine the critical illness response to nutrient deficiency and delivery. Nutritional metabolomics approaches in nutrient deficiency, malnutrition and nutrient delivery have included single time point studies and dynamic studies of critically ill patients over time. Integration of metabolomics and clinical outcome data may create a more complete understanding of the control of metabolism in critical illness.

SUMMARY

The integration of metabolomic profiling with transcription and genomic data may allow for a unique window into the mechanism of how nutrient deficiency and delivery alters cellular homeostasis during critical illness and modulates the regain of cellular homeostasis during recovery. The progress and the challenges of the study of nutritional metabolomics are reviewed here.

Pharmacogenomic biomarkers do not predict response to drotrecogin alfa in patients with severe sepsis

Purpose

To explore potential design for pharmacogenomics trials in sepsis, we investigate the interaction between pharmacogenomic biomarkers and response to drotrecogin alfa (activated) (DrotAA). This trial was designed to validate whether previously identified improved response polymorphisms (IRPs A and B) were associated with an improved response to DrotAA in severe sepsis.

Methods

Patients with severe sepsis at high risk of death, who received DrotAA or not, with DNA available were included and matched to controls adjusting for age, APACHE II or SAPS II, organ dysfunction, ventilation, medical/surgical status, infection site, and propensity score (probability that a patient would have received DrotAA given their baseline characteristics). Independent genotyping and two-phase data transfer mitigated bias. The primary analysis compared the effect of DrotAA in IRP+ and IRP− groups on in-hospital 28-day mortality. Secondary endpoints included time to death in hospital; intensive care unit (ICU)-, hospital-, and ventilator-free days; and overall DrotAA treatment effect on mortality.

Results

Six hundred and ninety-two patients treated with DrotAA were successfully matched to 1935 patients not treated with DrotAA. Genotyping was successful for 639 (DrotAA) and 1684 (nonDrotAA) matched patients. The primary hypothesis of a genotype-by-treatment interaction (assessed by conditional logistic regression analysis) was not significant (P = 0.30 IRP A; P = 0.78 IRP B), and there was no significant genotype by treatment interaction for any secondary endpoint.

Conclusions

Neither IRP A nor IRP B predicted differential response to DrotAA on in-hospital 28-day mortality.

ClinicalTrials.gov registration NCT01486524

Electronic supplementary material

The online version of this article (10.1186/s13613-018-0353-2) contains supplementary material, which is available to authorized users.

The coming era of precision medicine for intensive care

Recent advances in technology and better understanding of mechanisms underlying disease are beginning to enable us to better characterize critically ill patients. Instead of using nonspecific syndromic groupings, such as sepsis or acute respiratory distress syndrome, we can now classify individual patients according to various specific characteristics, such as immune status. This "personalized" medicine approach will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses that will influence their need for and responses (both negative and positive) to specific treatments. Treatments will be able to be chosen more accurately for each patient, resulting in more rapid institution of appropriate, effective therapy. We will also increasingly be able to conduct trials in groups of patients specifically selected as being most likely to respond to the intervention in question. This has already begun with, for example, some new interventions being tested only in patients with coagulopathy or immunosuppressive patterns. Ultimately, as we embrace this era of precision medicine, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.

Stem Cell–based Therapies for Sepsis

Sepsis is a life-threatening syndrome resulting in shock and organ dysfunction stemming from a microbial infection. Sepsis has a mortality of 40% and is implicated in half of all in-hospital deaths. The host immune response to microbial infection is critical, with early-phase sepsis characterized by a hyperinflammatory immune response, whereas the later phase of sepsis is often complicated by suppression. Sepsis has no treatment, and management remains supportive.

Stem cells constitute exciting potential therapeutic agents for sepsis. In this review, we examine the rationale for stem cells in sepsis, focusing on mesenchymal stem/stromal cells, which currently demonstrate the greatest therapeutic promise. We examine the preclinical evidence base and evaluate potential mechanisms of action of these cells that are important in the setting of sepsis. We discuss early-phase clinical trials and critically appraise translational barriers to the use of mesenchymal stem/stromal cells in patients with sepsis.

Genome-wide association study of sepsis in extremely premature infants

OBJECTIVE

To identify genetic variants associated with sepsis (early-onset and late-onset) using a genome-wide association (GWA) analysis in a cohort of extremely premature infants.

STUDY DESIGN

Previously generated GWA data from the Neonatal Research Network's anonymised genomic database biorepository of extremely premature infants were used for this study. Sepsis was defined as culture-positive early-onset or late-onset sepsis or culture-proven meningitis. Genomic and whole-genome-amplified DNA was genotyped for 1.2 million single-nucleotide polymorphisms (SNPs); 91% of SNPs were successfully genotyped. We imputed 7.2 million additional SNPs. p Values and false discovery rates (FDRs) were calculated from multivariate logistic regression analysis adjusting for gender, gestational age and ancestry. Target statistical value was p<10-5. Secondary analyses assessed associations of SNPs with pathogen type. Pathway analyses were also run on primary and secondary end points.

RESULTS

Data from 757 extremely premature infants were included: 351 infants with sepsis and 406 infants without sepsis. No SNPs reached genome-wide significance levels (5×10-8); two SNPs in proximity to FOXC2 and FOXL1 genes achieved target levels of significance. In secondary analyses, SNPs for ELMO1, IRAK2 (Gram-positive sepsis), RALA, IMMP2L (Gram-negative sepsis) and PIEZO2 (fungal sepsis) met target significance levels. Pathways associated with sepsis and Gram-negative sepsis included gap junctions, fibroblast growth factor receptors, regulators of cell division and interleukin-1-associated receptor kinase 2 (p values<0.001 and FDR<20%).

CONCLUSIONS

No SNPs met genome-wide significance in this cohort of extremely low birthweight infants; however, areas of potential association and pathways meriting further study were identified.

Toward Smarter Lumping and Smarter Splitting: Rethinking Strategies for Sepsis and Acute Respiratory Distress Syndrome Clinical Trial Design

Both quality improvement and clinical research efforts over the past few decades have focused on consensus definition of sepsis and acute respiratory distress syndrome (ARDS). Although clinical definitions based on readily available clinical data have advanced recognition and timely use of broad supportive treatments, they likely hinder the identification of more targeted therapies that manipulate select biological mechanisms underlying critical illness. Sepsis and ARDS are by definition heterogeneous, and patients vary in both their underlying biology and their severity of illness. We have long been able to identify subtypes of sepsis and ARDS that confer different prognoses. The key is that we are now on the verge of identifying subtypes that may confer different response to therapy. In this perspective, inspired by a 2015 American Thoracic Society International Conference Symposium entitled "Lumpers and Splitters: Phenotyping in Critical Illness," we highlight promising approaches to uncovering patient subtypes that may predict treatment responsiveness and not just differences in prognosis. We then discuss how this information can be leveraged to improve the success and translatability of clinical trials by using predictive enrichment and other design strategies. Last, we discuss the challenges and limitations to identifying biomarkers and endotypes and incorporating them into routine clinical practice.

A path to precision in the ICU

Precision medicine is increasingly touted as a groundbreaking new paradigm in biomedicine. In the ICU, the complexity and ambiguity of critical illness syndromes have been identified as fundamental justifications for the adoption of a precision approach to research and practice. Inherently protean diseases states such as sepsis and acute respiratory distress syndrome have manifestations that are physiologically and anatomically diffuse, and that fluctuate over short periods of time. This leads to considerable heterogeneity among patients, and conditions in which a “one size fits all” approach to therapy can lead to widely divergent results. Current ICU therapy can thus be seen as imprecise, with the potential to realize substantial gains from the adoption of precision medicine approaches. A number of challenges still face the development and adoption of precision critical care, a transition that may occur incrementally rather than wholesale. This article describes a few concrete approaches to addressing these challenges.

First, novel clinical trial designs, including registry randomized controlled trials and platform trials, suggest ways in which conventional trials can be adapted to better accommodate the physiologic heterogeneity of critical illness. Second, beyond the “omics” technologies already synonymous with precision medicine, the data-rich environment of the ICU can generate complex physiologic signatures that could fuel precision-minded research and practice. Third, the role of computing infrastructure and modern informatics methods will be central to the pursuit of precision medicine in the ICU, necessitating close collaboration with data scientists. As work toward precision critical care continues, small proof-of-concept studies may prove useful in highlighting the potential of this approach.

Enhanced understanding of the host-pathogen interaction in sepsis: new opportunities for omic approaches

Progress in sepsis research has been severely hampered by a heterogeneous disease phenotype, limiting the interpretation of clinical trials and the development of effective therapeutic interventions. Application of omics-based methodologies is advancing understanding of the dysregulated host immune response to infection in sepsis. However, the frequently elusive nature of the infecting organism in sepsis has limited efforts to understand the effect of disease heterogeneity involving the pathogen. Recent advances in nucleic acid sequencing-based pathogen analysis provide the opportunity for more accurate and comprehensive microbiological diagnosis. In this Review, we explore how better understanding of the host-pathogen interaction can substantially enhance, and in turn benefit from, current and future application of omics-based approaches to understand the host response in sepsis. We illustrate this using recent work accounting for heterogeneity involving the pathogen. We propose that there is a timely opportunity to further resolve sepsis heterogeneity by considering host-pathogen interactions, enabling progress towards a precision medicine approach.

A novel approach for selecting combination clinical markers of pathology applied to a large retrospective cohort of surgically resected pancreatic cysts

OBJECTIVE

Our objective was to develop an approach for selecting combinatorial markers of pathology from diverse clinical data types. We demonstrate this approach on the problem of pancreatic cyst classification.

MATERIALS AND METHODS

We analyzed 1026 patients with surgically resected pancreatic cysts, comprising 584 intraductal papillary mucinous neoplasms, 332 serous cystadenomas, 78 mucinous cystic neoplasms, and 42 solid-pseudopapillary neoplasms. To derive optimal markers for cyst classification from the preoperative clinical and radiological data, we developed a statistical approach for combining any number of categorical, dichotomous, or continuous-valued clinical parameters into individual predictors of pathology. The approach is unbiased and statistically rigorous. Millions of feature combinations were tested using 10-fold cross-validation, and the most informative features were validated in an independent cohort of 130 patients with surgically resected pancreatic cysts.

RESULTS

We identified combinatorial clinical markers that classified serous cystadenomas with 95% sensitivity and 83% specificity; solid-pseudopapillary neoplasms with 89% sensitivity and 86% specificity; mucinous cystic neoplasms with 91% sensitivity and 83% specificity; and intraductal papillary mucinous neoplasms with 94% sensitivity and 90% specificity. No individual features were as accurate as the combination markers. We further validated these combinatorial markers on an independent cohort of 130 pancreatic cysts, and achieved high and well-balanced accuracies. Overall sensitivity and specificity for identifying patients requiring surgical resection was 84% and 81%, respectively.

CONCLUSIONS

Our approach identified combinatorial markers for pancreatic cyst classification that had improved performance relative to the individual features they comprise. In principle, this approach can be applied to any clinical dataset comprising dichotomous, categorical, and continuous-valued parameters.

Genetic Factors of the Disease Course After Sepsis: Rare Deleterious Variants Are Predictive

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. For its clinical course, host genetic factors are important and rare genomic variants are suspected to contribute. We sequenced the exomes of 59 Greek and 15 German patients with bacterial sepsis divided into two groups with extremely different disease courses. Variant analysis was focusing on rare deleterious single nucleotide variants (SNVs).

We identified significant differences in the number of rare deleterious SNVs per patient between the ethnic groups. Classification experiments based on the data of the Greek patients allowed discrimination between the disease courses with estimated sensitivity and specificity > 75%. By application of the trained model to the German patients we observed comparable discriminatory properties despite lower population-specific rare SNV load. Furthermore, rare SNVs in genes of cell signaling and innate immunity related pathways were identified as classifiers discriminating between the sepsis courses.

Sepsis patients with favorable disease course after sepsis, even in the case of unfavorable preconditions, seem to be affected more often by rare deleterious SNVs in cell signaling and innate immunity related pathways, suggesting a protective role of impairments in these processes against a poor disease course.

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Rare SNV load is higher in the Greek vs. German population.

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Subsets of rare deleterious SNVs are predictive for the disease course after sepsis.

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Patients with favorable disease course seem to carry protective deleterious variants in sepsis related pathways.

Sepsis is a life-threatening disease caused by improper response to infection. Only little is known about the role of genetic factors. From > 4000 patients we selected the most extreme cases showing either a favorable or adverse disease course. We determined rare (< 1/200) protein-damaging genetic variants, as they may have a large effect. Using a computational model that includes knowledge on genes we can predict the disease course with > 75% accuracy. Surprisingly, favorable courses can be expected if defense mechanisms are damaged and prevented from overshooting. This underlines the relevance of rare variants for better understanding of sepsis and may offer new treatment options.

Genetic Factors of the Disease Course after Sepsis: A Genome-Wide Study for 28Day Mortality

Sepsis is the dysregulated host response to an infection which leads to life-threatening organ dysfunction that varies by host genomic factors. We conducted a genome-wide association study (GWAS) in 740 adult septic patients and focused on 28 day mortality as outcome. Variants with suggestive evidence for an association (p ≤ 10^− 5) were validated in two additional GWA studies (n = 3470) and gene coding regions related to the variants were assessed in an independent exome sequencing study (n = 74).

In the discovery GWAS, we identified 243 autosomal variants which clustered in 14 loci (p ≤ 10^− 5). The best association signal (rs117983287; p = 8.16 × 10^− 8) was observed for a missense variant located at chromosome 9q21.2 in the VPS13A gene. VPS13A was further supported by additional GWAS (p = 0.03) and sequencing data (p = 0.04). Furthermore, CRISPLD2 (p = 5.99 × 10^− 6) and a region on chromosome 13q21.33 (p = 3.34 × 10^− 7) were supported by both our data and external biological evidence.

We found 14 loci with suggestive evidence for an association with 28 day mortality and found supportive, converging evidence for three of them in independent data sets. Elucidating the underlying biological mechanisms of VPS13A, CRISPLD2, and the chromosome 13 locus should be a focus of future research activities.

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A low frequency missense variant in VPS13A on chromosome 9q21.2 was associated with 28 day mortality after sepsis

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A frequent intronic variant in CRISPLD2 was also supported and was reported to be associated with procalcitonin levels

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Similarly supported was an intergenic frequent variant on chromosome13q21.33 – a region related to chronic kidney disease

Sepsis is the dysregulated host response to an infection which leads to life-threatening organ dysfunction that is known to vary by host genomic factors. However, the detection of genetic variants related to sepsis outcomes has been challenging so far. We conducted a discovery genome-wide association study (GWAS) in 740 adult patients with sepsis looking for variants that vary with 28 day mortality. We followed-up our best findings by additional GWAS and exome sequencing data in 3544 adult patients and report three regions including the genes VPS13A and CRISPLD2 that were supported by our data and external biological evidence.

Elucidating the role of genomics in neonatal sepsis

Sepsis is a major cause of neonatal morbidity and mortality, especially in vulnerable preterm populations. Immature immune defenses, and environmental and maternal factors contribute to this risk, with as many as a third of very preterm infants experiencing sepsis during their stay in the neonatal intensive care unit (NICU). Epidemiologic and twin studies have suggested that there is a genetic contribution to sepsis predilection. Several investigators have conducted candidate gene association studies on variants of specific interest and potential functional significance in neonatal sepsis. In this review, we describe details of studies that have evaluated genetic susceptibility in neonatal sepsis, and summarize findings from a review of candidate gene association studies.

Pharmacometabolomics of l-carnitine treatment response phenotypes in patients with septic shock

RATIONALE

Sepsis therapeutics have a poor history of success in clinical trials, due in part to the heterogeneity of enrolled patients. Pharmacometabolomics could differentiate drug response phenotypes and permit a precision medicine approach to sepsis.

OBJECTIVES

To use existing serum samples from the phase 1 clinical trial of l-carnitine treatment for severe sepsis to metabolically phenotype l-carnitine responders and nonresponders.

METHODS

Serum samples collected before (T0) and after completion of the infusion (T24, T48) from patients randomized to either l-carnitine (12 g) or placebo for the treatment of vasopressor-dependent septic shock were assayed by untargeted (1)H-nuclear magnetic resonance metabolomics. The normalized, quantified metabolite data sets of l-carnitine- and placebo-treated patients at each time point were compared by analysis of variance with post-hoc testing for multiple comparisons. Pathway analysis was performed to statistically rank metabolic networks.

MEASUREMENTS AND MAIN RESULTS

Thirty-eight metabolites were identified in all samples. Concentrations of 3-hydroxybutyrate, acetoacetate, and 3-hydroxyisovalerate were different at T0 and over time in l-carnitine-treated survivors versus nonsurvivors. Pathway analysis of pretreatment metabolites revealed that synthesis and degradation of ketone bodies had the greatest impact in differentiating l-carnitine treatment response. Analysis of all patients based on pretreatment 3-hydroxybutyrate concentration yielded distinct phenotypes. Using the T0 median 3-hydroxybutyrate level (153 μM), patients were categorized as either high or low ketone. l-Carnitine-treated low-ketone patients had greater use of carnitine as evidenced by lower post-treatment l-carnitine levels. The l-carnitine responders also had faster resolution of vasopressor requirement and a trend toward a greater improvement in mortality at 1 year (P = 0.038) compared with patients with higher 3-hydroxybutyrate.

CONCLUSIONS

The results of this preliminary study, which were not readily apparent from the parent clinical trial, show a unique metabolite profile of l-carnitine responders and introduce pharmacometabolomics as a viable strategy for informing l-carnitine responsiveness. The approach taken in this study represents a concrete example for the application of precision medicine to sepsis therapeutics that warrants further study.

Normal values for pancreatic stone protein in different age groups

Background

Pancreatic stone protein (PSP) has been identified as a promising sepsis marker in adults, children and neonates. However, data on population-based reference values are lacking. This study aimed to establish age-specific reference values for PSP.

Methods

PSP was determined using a specific ELISA. PSP serum concentrations were determined in 372 healthy subjects including 217 neonates, 94 infants and children up to 16 years, and 61 adults. The adjacent categories method was used to determine which age categories had significantly different PSP concentrations.

Results

PSP circulating levels were not gender-dependent and ranged from 1.0 to 99.4 ng/ml with a median of 9.2 ng/ml. PSP increased significantly between the age categories, from a median of 2.6 ng/ml in very preterm newborns, to 6.3 ng/ml in term newborns, to 16.1 ng/ml in older children (p < 0.001). PSP levels were higher on postnatal day three compared to levels measured immediately post delivery (p < 0.001). Paired umbilical artery and umbilical vein samples were strongly correlated (p < 0.001). Simultaneously obtained capillary heel-prick versus venous samples showed a good level of agreement for PSP (Rho 0.89, bias 19 %).

Conclusions

This study provides age-specific normal values that may be used to define cut-offs for future trials on PSP. We demonstrate an age-dependent increase of PSP from birth to childhood.

Interleukin-10 rs2227307 and CXCR2 rs1126579 polymorphisms modulate the predisposition to septic shock

Despite major improvements in its treatment and diagnosis, sepsis is still a leading cause of death and admittance to the intensive care unit (ICU). Failure to identify patients at high risk of developing septic shock contributes to an increase in the sepsis burden and rapid molecular tests are currently the most promising avenue to aid in patient risk determination and therapeutic anticipation. The primary goal of this study was to evaluate the genetic susceptibility that affects sepsis outcome in 72 sepsis patients admitted to the ICU. Seven polymorphisms were genotyped in key inflammatory response genes in sepsis, including tumour necrosis factor-α, interlelukin (IL)-1β, IL-10, IL-8, Toll-like receptor 4, CXCR1 and CXCR2. The primary finding showed that patients who were homozygous for the major A allele in IL-10 rs1800896 had almost five times higher chance to develop septic shock compared to heterozygotes. Similarly, selected clinical features and CXCR2 rs1126579 single nucleotide polymorphisms modulated septic shock susceptibility without affecting survival. These data support the hypothesis that molecular testing has clinical usefulness to improve sepsis prognostic models. Therefore, enrichment of the ICU portfolio by including these biomarkers will aid in the early identification of sepsis patients who may develop septic shock.

Variants in the Mannose-binding Lectin Gene MBL2 do not Associate With Sepsis Susceptibility or Survival in a Large European Cohort

BACKGROUND

Sepsis is an increasingly common condition, which continues to be associated with unacceptably high mortality. A large number of association studies have investigated susceptibility to, or mortality from, sepsis for variants in the functionally important immune-related gene MBL2. These studies have largely been underpowered and contradictory.

METHODS

We genotyped and analyzed 4 important MBL2 single nucleotide polymorphisms (SNPs; rs5030737, rs1800450, rs1800451, and rs7096206) in 1839 European community-acquired pneumonia (CAP) and peritonitis sepsis cases, and 477 controls from the United Kingdom. We analyzed the following predefined subgroups and outcomes: 28-day and 6 month mortality from sepsis due to CAP or peritonitis combined, 28-day mortality from CAP sepsis, peritonitis sepsis, pneumococcal sepsis or sepsis in younger patients, and susceptibility to CAP sepsis or pneumococcal sepsis in the United Kingdom.

RESULTS

There were no significant associations (all P-values were greater than .05 after correction for multiple testing) between MBL2 genotypes and any of our predefined analyses.

CONCLUSIONS

In this large, well-defined cohort of immune competent adult patients, no associations between MBL2 genotype and sepsis susceptibility or outcome were identified.

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.

A functional synonymous coding variant in the IL1RN gene is associated with survival in septic shock

RATIONALE

Death from infection is a highly heritable trait, yet there are few genetic variants with known mechanism influencing survival during septic shock.

OBJECTIVES

We hypothesized that a synonymous coding variant in the IL-1 receptor antagonist gene (IL1RN), rs315952, previously associated with reduced risk for acute respiratory distress syndrome, would be functional and associate with improved survival in septic shock.

METHODS

We used a human endotoxin (LPS) model of evoked inflammatory stress to measure plasma IL-1 receptor antagonist (IL1RA) following low-dose Food and Drug Administration-grade LPS injection (1 ng/kg) in 294 human volunteers. RNA sequencing of adipose tissue pre- and post-LPS was used to test for allelic imbalance at rs315952. In the Vasopressin and Septic Shock Trial cohort, we performed a genetic association study for survival, mortality, and organ failure-free days.

MEASUREMENTS AND MAIN RESULTS

Adipose tissue displayed significant allelic imbalance favoring the rs315952C allele in subjects of European ancestry. Consistent with this, carriers of rs315952C had slightly higher plasma IL1RA at baseline (0.039) and higher evoked IL1RA post-LPS (0.011). In the Vasopressin and Septic Shock Trial cohort, rs315952C associated with improved survival (P = 0.028), decreased adjusted 90-day mortality (P = 0.044), and faster resolution of shock (P = 0.029).

CONCLUSIONS

In European ancestry subjects, the IL1RN variant rs315952C is preferentially transcribed and associated with increased evoked plasma IL1RA and with improved survival from septic shock. It may be that genetically determined IL1RA levels influence survival from septic shock.

GWAS of 126,559 individuals identifies genetic variants associated with educational attainment

A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

Pharmacogenomics in clinical practice and drug development

Genome-wide association studies (GWAS) of responses to drugs, including clopidogrel, pegylated-interferon and carbamazepine, have led to the identification of specific patient subgroups that benefit from therapy. However, the identification and replication of common sequence variants that are associated with either efficacy or safety for most prescription medications at odds ratios (ORs) >3.0 (equivalent to >300% increased efficacy or safety) has yet to be translated to clinical practice. Although some of the studies have been completed, the results have not been incorporated into therapy, and a large number of commonly used medications have not been subject to proper pharmacogenomic analysis. Adoption of GWAS, exome or whole genome sequencing by drug development and treatment programs is the most striking near-term opportunity for improving the drug candidate pipeline and boosting the efficacy of medications already in use.