Detection of microRNAs in patients with sepsis

Michael A. Puskarich, Utsav Nandi, Nathan I. Shapiro, Stephen Trzeciak, Jeffrey A. Kline, Alan E. Jones*Department of Emergency Medicine, University of Mississippi Medical Center, Jackson, MS, USADepartments of Medicine, Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USADepartment of Emergency Medicine, Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USADepartments of Medicine, Division of Critical Care Medicine and Emergency Medicine, Cooper University Hospital, Camden, New Jersey, USADepartment of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN, USADepartment of Cellular and Integrative Physiology, Indiana University School of Medicine, Indianapolis, IN, USA

Detection of microRNAs in patients with sepsis

Michael A. Puskarich1, Utsav Nandi1, Nathan I. Shapiro2,3, Stephen Trzeciak4, Jeffrey A. Kline5,6, Alan E. Jones1*
1Department of Emergency Medicine, University of Mississippi Medical Center, Jackson, MS, USA
2Departments of Medicine, Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
3Department of Emergency Medicine, Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
4Departments of Medicine, Division of Critical Care Medicine and Emergency Medicine, Cooper University Hospital, Camden, New Jersey, USA
5Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
6Department of Cellular and Integrative Physiology, Indiana University School of Medicine, Indianapolis, IN, USA

ARTICLE INFO ABSTRACT

Article history:

Received 6 February 2015

Received in revised form 8 February 2015 Accepted 11 February 2015

Available online 13 February 2015

Keywords:

Diagnostic and prognostic value

microRNAs

Logistic regression models

Sepsis

Objective: To externally validate the diagnostic and prognostic value of three previously identified microRNAs in emergency department patients with sepsis. Methods: Patients meeting consensus criteria for sepsis and septic shock were compared to controls. Three microRNAs (miR-150, miR-146a, and miR-223) were measured using real-time quantitative PCR, and levels of miRNAs were compared among the three cohorts. The association between miRNAs and both inflammatory markers and Sequential Organ Failure Assessment (SOFA) score were compared. To assess the prognostic value of each miRNA, unadjusted and adjusted logistic regression models were constructed using in-hospital mortality as the dependent variable. Results: Ninetythree patients were enrolled; 24 controls, 29 with sepsis, and 40 with septic shock. We found no difference in serum plasma miR-146a or miR-223 between cohorts, and found no association among these microRNAs and either inflammatory markers or SOFA score. miR-150 demonstrated a significant correlation with SOFA score (ρ= 0.31, P=0.01) and IL-10 (ρ=0.37, P=0.001), but no IL-6 or TNF-α (P=0.046, P=0.59). Logistic regression demonstrated miR-150 to be independently associated with mortality, even after adjusting for SOFA score (P=0.003) or initial lactate (P=0.01). Conclusions: miR-146a and miR-223 demonstrated no significantly diagnostic or prognostic ability in this cohort. miR-150 was associated with inflammation, severity of illness, and mortality. Given the independent predictive value of miR-150, additional research regarding its role in sepsis is warranted.

E-mail: aejones@umc.edu

Foundation Project: Supported by the American Heart Association and an Emergency Medicine Foundation Career Development Grant (10POST3560001).

1. Introduction

Severe sepsis remains a significant public health concern, with over 750 000 patients hospitalized annually in the United States based on data from over 10 years ago, a number that appears to be increasing[1,2]. However, even as the incidence of this critical disease increases, novel, reliable diagnostic or prognostic markers to aid in early detection, and treatment, have not been developed with reproducible success[3]. Early intervention improves outcomes in severe sepsis[4,5], and delays in treatment are common[6]. It is neccessary to develop new markers that will aid in either early detection or provide clues regarding prognosis, thus guiding treatment in a more expedited manner.

Previous research into biomarkers of sepsis have examined inflammatory and cytokine profiles[3], procalcitonin[7], metabolomic and proteomic approaches[8], amongst others. However, only a few limited and primarilyprognostic markers have been successfully incorporated into regular clinical practice, demonstrating the need for further investigation into novel areas. micro-RNAs (miRNA) are small, approximately 22 nucleotide long, non-coding RNAs with regulatory functions for gene expression and protein translation. Recent studies have found evidence that miRNAs may have potential as early biomarkers in a number of disease processes, including sepsis. While the specific roles of the numerous miRNAs on cellular function are still being elucidated, their roles as potential biomarkers have already received considerable interest. Previous research in sepsis has identified at least 3 miRNAs, miR-146a, miR-223 and miR-150 as being potentially dysregulated in sepsis[9,10]. In this study, we sought to evaluate the diagnostic and prognostic value of these three miRNAs in emergency department (ED) patients with sepsis.

2. Materials and methods

We performed a prospective observational study of a convenience sample of patients presenting to three large, urban, tertiary care emergency departments. This cohort has been previously described[11], and the study was approved by the institutional review boards at the participating institutions. Patients were enrolled into one of three cohorts: sepsis, septic shock and control. The diagnosis of sepsis and septic shock followed American College of Chest Physicians /Society of Critical Care Medicine consensus definitions[12]. The sepsis cohort required suspected or confirmed infection, two or more SIRS criteria (heart rate＞90 beats/min, respiratory rate＞20 breaths/min, temperature＞38 ℃ or ＜36℃, white blood cell＞12 000 cells/mm3or ＜4 000 cells/mm3or ＞10% bands) and no hypotension after adequate fluid resuscitation (systolic blood pressure＞90 mmHg after 20 mL/kg crystalloids). The septic shock cohort had to meet the inclusion criteria of suspected or confirmed infection, two or more SIRS criteria, and required refractory hypotension after fluid challenge or requirement for vasopressors. The third cohort comprised uninfected ED control patients in whom infection was not suspected, no SIRS criteria were met and there was no evidence of hypoperfusion or hypotension.

Patients were excluded if they were ＜18 years old, pregnant or had an established “Do Not Resuscitate”order prior to enrollment. And we excluded patients with any of the following primary diagnoses: acute traumatic or burn injury, acute cerebrovascular event, acute coronary syndrome, acute pulmonary edema, cardiac dysrhythmia, acute and active gastrointestinal bleeding, acute drug overdose. Patients were excluded who had a requirement for immediate surgery or were unable to obtain written informed consent. The study was approved by the Institutional Review Board at all institutions. Demographic variables, comorbidities, vital signs, and pertinent laboratory data were collected on all patients. Clinical management at each institution was in agreement with the Surviving Sepsis Campaign guidelines[13].

Plasma samples were drawn immediately following informed consent in the emergency department. Analyte concentrations were measured and quantified using a Bio-Plex suspension array system (Bio-Rad, Hercules, CA, USA). Assays for IL-6 and IL-10 (Bio-Rad) were performed according to the manufacturer’s instructions. These assays use color-coded bead sets, each of which is conjugated with analyte-specific antibodies and designed in a capture sandwich immunoassay format. The samples were diluted with the supplied diluents as directed. The antibodycoupled beads were mixed and incubated with diluted plasma samples, or with the standards. Unbound proteins were removed by washing in the Bio-Plex Pro wash station and a biotinylated detection antibody was added to the beads. Each captured analyte was detected by the addition of a reporter molecule, streptavidin-phycoerythrin. The contents of each well were drawn into the Bio-Plex array reader where precision fluidics align the beads and lasers excite them in order to quantify the captured analytes. Analyte concentrations were automatically calculated with Bio-Plex Manager software by using a standard curve derived from the recombinant standard provided with the assays. Total RNA was isolated from plasma using the miRNeasy Mini Kit (Qiagen, Valencia, CA) with modifications. Briefly, 700 μL of Qiazol was added to 200 μL of plasma and vortexed for 15 seconds. A synthetic miRNA (cel-miR-39; IDT, San Diego, CA) was spiked into the plasma samples to a final concentration of 125 pmol/ L to monitor the isolation efficiency and to serve as the internal control for subsequent comparative Ct calculations. Following chloroform extraction, two 350 μL and 500 μL washes were performed using relative wall thickness and retinal pigment epithelium buffer, respectively, prior to elution in 50 μL of nuclease-free water. First-strand complementary DNA synthesis was performed using TaqMan? MicroRNA Reverse Transcription Kit primed with a miR-specific primer for hsa-miR-223, hsa-miR-150, or hsa-miR-146a (Applied Biosystems, Foster City, CA, USA). The RT reaction mixture consisted of 0.15 μL of 100 mmol/ L dNTPs, 1 μL of MultiscribeTM Reverse Transcriptase (50 unit/μL), 1.5 μL 10× Reverse Transcription Buffer, 0.19 μL RNase Inhibitor (20 unit/μL), 4.16 μL nuclease-free water, 5 μL of RNA sample and 3 μL of primer. RT was carried out in a GeneAmp? PCR System 9700 (Applied Biosystems)at 16 ℃ for 30 min, 42 ℃ for 30 min, and 85 ℃ for 5 min. Real-time quantitative RT-PCR (qRT-PCR) was performed using the TaqMan? MicroRNA Assays (Applied Biosystems), following the manufacturer’s recommendations. PCR reactions consisted of 1.33 μL product from the RT reaction, 1 μL Taqman? MicroRNA Assay (20×), 10 μL TaqMan? 2× Universal PCR Master Mix, and 7.67 μL of nucleasefree water. PCR amplification was achieved using an ABI Prism 7500 Sequence Detection System programmed for an initial denaturation at 95 ℃ for 10 min followed by 40 cycles at 95 ℃ for 15 seconds, and 60 ℃ for 30 seconds. Fold change values were calculated by comparative Ct analysis and normalized to cel-miR-39 concentrations (Livak and Schmittgen, 2001).

Inflammatory cytokine concentrations were measured and quantified using a Bio-Plex Suspension Array System (Bio-Rad, Hercules, CA, USA). Assays for IL6 and IL10 (Bio-Rad) were performed according to the manufacturer’s instructions. The antibody-coupled beads were mixed and incubated with diluted serum samples, or with the standards. Unbound proteins were removed by washing in the Bio-Plex Pro wash station and a biotinylated detection antibody was added to the beads. Each captured analyte was detected by the addition of a reporter molecule, streptavidin-phycoerythrin. The contents of each well were drawn into the Bio-plex array reader. Analyte concentrations were automatically calculated with Bio-Plex Manager software by using a standard curve derived from the recombinant standard provided.

Baseline characteristics of the three groups were collected and continuous data were summarized using means or medians and standard deviations or interquartile ranges, as appropriate. Comparisons between groups were performed using One-way ANOVA or Kruskal-Wallis tests, as appropriate. Categorical data were compared using Chi-square, or Fisher exact tests, as appropriate. Correlations between inflammatory markers IL-6 and IL-10 were performed using Pearson’s product moment correlation coefficient. A Bonferroni correction for multiple comparisons was applied. In order to assess the prognostic value of miRNA levels among the patients with sepsis, we constructed a logistic regression model using in-hospital mortality as the dependent variable, and miR-150, miR-146a, and miR-223 levels as the variables of interest in three separate models of only patients with sepsis and septic shock. Data were transformed as necessary. Candidate variables were selected based on known predictors of severity of illness, and the model was refined using reverse stepwise elimination. Candidate variables with a P＜0.10 were maintained in the initial stages of the model, while only those variables continuing to maintain P＜0.05 were maintained in the final model. Bootstrap and jackknife estimations were performed on each of the models. Data were analyzed using commercially available statistical software (StatsDirect 2.7.7, Cheshire, England and STATA 10.0, College Station, TX). All statistical tests were two sided with P＜0.05 considered significant.

3. Results

Baseline clinical data of the three cohorts are presented in Table 1. As expected, comorbidities, severity of illness, and in-hospital mortality were higher in the septic shock cohorts. There were more female patients in the control cohort compared to the sepsis cohorts. Other baselinecharacteristics were similar between cohorts. As expected, both IL-10 and IL-6 levels differed significantly among groups, being significantly higher among patients with sepsis as compared to control patients (P=0.0001), and higher in those with septic shock compared to sepsis (P=0.0001). Both pro- and anti-inflammatory interleukins were moderately correlated with severity of illness as estimated by SOFA score (IL-10: ρ=0.57, P＜0.000 1; IL-6: ρ=0.56, P＜0.000 1).

Table 1Patient demographics, clinical characteristics, and inflammatory cytokine concentrations by cohort.

We found no significant differences in miRNA levels between male and female, or among different races within our cohort. As opposed to a previous report regarding the level of miRs 146a and 223 abnormalities in patients with sepsis, we found no significant difference in plasma miR-146a or miR-223 levels between controls and patients with either sepsis or septic shock who were enrolled in the ED (Figure 1a-b, P=0.29, P=0.95), potentially limiting the diagnostic and prognostic utility of these tests on hospital presentation. Furthermore, we found no association among these microRNAs and either the measured inflammatory markers or SOFA score at enrollment. Neither miR146a nor miR223 were significantly associated with mortality in either unadjusted or adjusted logistic regression models.

Figures 1a-1c. Boxplots of plasma levels of miR146a, miR223, and miR150 by cohort at enrollment.miRNA levels reported as 2-??Ct. Levels of mir-150 (1c) were significantly higher in the septic shock cohort than the sepsis or control groups (*: P＜0.05). No other significant differences were detected between groups.

On the other hand, miR-150 was significantly higher in the group of patients with septic shock compared to patients in both the control and sepsis groups (Figure 1c, P=0.01). miR-150 levels demonstrated a moderate but significant correlation with SOFA score after Bonferroni correction (ρ=0.31, P=0.01) and IL-10 (ρ=0.37, P=0.001), but not IL-6 (P=0.046), suggesting a relationship between this biomarker and both level of inflammation and severity of illness at presentation shown in Figure 2. In order to further investigate the prognostic potential of miR-150, a logistic regression model was constructed to determine its relationship to mortality.

Figure 2. Scatterplots demonstrating the relationship between miR-150 and both IL-10 and SOFA score.

After excluding control patients, levels of miRNAs were significantly higher in non-survivors than survivors (Figure 3). Our unadjusted logistic regression model demonstrated miR-150 to be associated with mortality in patients with both sepsis and septic shock (P＜0.001). This relationshippersisted even after adjusting for SOFA score (P=0.003, pseudo R2=0.32) or initial lactate (P=0.01, pseudo R2= 0.37). Examination of residuals demonstrated no significant violation of any of the model assumptions. Bootstrap and jackknife estimations were consistent with the results of the models. These data suggest additional prognostic potential of this biomarker above and beyond commonly used clinical methods to predict patient outcome.

Figure 3. Boxplot demonstrating the difference in log-transformed mir-150 levels between survivors and non-survivors of patients with sepsis.

4. Discussion

In this study of ED patients with sepsis, septic shock, and control patients, we evaluated 3 previously identified microRNAs for their diagnostic and prognostic ability to both discriminate between non-infected control and patients with sepsis, and give prognostic data regarding severity of illness and mortality. miR-146a and miR-223 demonstrated no discriminatory or prognostic value in this study. miR-150 demonstrated some discriminatory potential, though there was significant overlap between control patients and patients with sepsis. These data suggest its role as a diagnostic marker would have significant limitations. However, miR-150 demonstrated a moderate, but significant, association with severity of illness and mortality, and the effect size was small. This relationship with mortality persisted in logistic regression modeling even after controlling for commonly used prognostic markers, namely SOFA score and lactate, suggesting potential additional clinical utility as a prognostic marker, should be validated in a larger cohort. Furthermore, given its independent association with mortality even after controlling for severity of illness, further investigation into the role of miR-150 in the pathophysiology of disease is warranted.

Many efforts in early detection research have shifted from pathogen detection to the host response markers– thus focusing on inflammatory marker, including cytokines, procalcitonin and recently microRNAs. Recent studies have identified an association between certain microRNAs and sepsis. We focused on 3 miRNAs: miR-146a, miR-223 and miR-150 as identified by Vasilescu et al.[10] and Wang et al.[9] in their respective studies in an attempt to externally validate their data in a group of ED patients. Based on our analysis, only miR-150 was found to be correlated to SOFA score and with mortality, confirming the prognostic potential of this microRNA.

There are several potential reasons why our results regarding miR-146a and 223 may have differed from previous literature. Other microRNA studies have focused on sample collection post ICU admission; this method, though beneficial in detecting levels of miRNA and associated inflammatory markers, may not be an ideal representation of the patient’s host response at ED presentation. Therefore the data provide more information on the microRNA response during initial presentation, consistent with our goal of developing novel biomarker for sepsis that can be used by clinicians on patient presentation. Previous literature also represented a preponderance of patients with intra-abdominal and surgical sources of sepsis. However, this population is not representative of the typical patient presenting to the ED with sepsis, who typically present with respiratory infections rather than intraabdominal infections[1], and may be responsible for some of the differences in our findings. Finally, previous work with miRs 146a and 223 took place in China, and it is entirely possible that the microRNA profile among different ethnicities varies considerably in response to sepsis.

This study has several strengths and weaknesses that deserve consideration. First, we enrolled patients at presentation rather than later in the intensive care unit, which allows for a more clinically relevant assessment of a potential diagnostic or prognostic test, which would be of most use early after presentation. Assessors of clinical outcomes and those conducting the miRNA measurements were blinded to the other measurements, minimizing the chance of introduction of bias. While we only focused on 3 microRNAs previously described in the literature,this focused rather than array approach decreases the likelihood of false positive discoveries which become increasingly common with larger sample sizes. There are several weaknesses that deserve consideration as well. We only focused this study on diagnostic and prognostic usefulness of these therapies, but did not conduct in depth pathophysiologic study regarding their potential downstream effects, and we cannot comment on the effect. These regulators are having during the disease state, nor their potential as therapeutic targets. This is particularly relevant as we only chose to focus on 2 inflammatory markers, while the downstream effects of these microRNAs might be on other mediators. However, the lack of difference of miRNAs 146a and 223 between control patients and those with sepsis, and the lack of association with clinically relevant variables such as severity of illness and mortality would lead one to question the clinical significance of such an association, even if it existed. Second, while all patients met consensus criteria for sepsis and septic shock, not all patients had culture proven sepsis, which always confounds diagnostic trials for sepsis. However, as many patients with sepsis never have a positive blood culture for a specific microorganism, this is a common shortcoming of conducting clinical research in this patient population. Finally, the overall severity of illness of patients in this trial is relatively low, and it is possible that a more critically ill cohort of patients would demonstrate different findings.

We found no significant difference in previously identified miRNAs miR223 and miR146a between patients with and without sepsis or septic shock. While miR-150 levels at presentation were correlated with inflammation and disease severity in emergency department patients with sepsis, these correlations are at best moderate. However, miR-150 was significantly associated with mortality, even after adjusting for severity of illness, suggesting incremental benefit as a prognostic marker in patients with sepsis. Further research into the mechanistic role of miR-150 and whether it plays a pathogenic role in sepsis are of future interest.

Conflict of interest statement

The authors report no conflict of interest.

References

[1] Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 2001; 29(7): 1303-1310.

[2] Gaieski D, Edwards J, Kallan M, Carr B. Benchmarking the incidence and mortality of severe sepsis in the United States. Crit Care Med 2013; 41: 1167-1174.

[3] Samraj RS, Zingarelli B, Wong HR. Role of biomarkers in sepsis care. Shock 2013; 40: 358-365.

[4] Jones AE, Brown MD, Trzeciak S, Shapiro NI, Garrett JS, Heffner AC, et al. The effect of a quantitative resuscitation strategy on mortality in patients with sepsis: a meta-analysis. Crit Care Med 2008; 36: 2734-2739.

[5] Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 2006; 34(6): 1589-1596.

[6] Levy MM, Dellinger RP, Townsend SR, Linde-Zwirble WT, Marshall JC, Bion J, et al. The surviving sepsis campaign: results of an international guideline-based performance improvement program targeting severe sepsis. Crit Care Med 2010; 38: 367-374.

[7] Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and metaanalysis. Lancet Infect Dis 2013; 13: 426-435.

[8] Liu X, Ren H, Peng D. Sepsis biomarkers: an omics perspective. Front Med 2014; 8: 58-67.

[9] Wang JF, Yu ML, Yu G, Bian JJ, Deng XM, Wan XJ, et al. Serum miR-146a and miR-223 as potential new biomarkers for sepsis. Biochem Biophys Res Commun 2010; 394: 184-188.

[10] Vasilescu C, Rossi S, Shimizu M, Tudor S, Veronese A, Ferracin M, et al. MicroRNA fingerprints identify miR-150 as a plasma prognostic marker in patients with sepsis. PLoS One 2009; doi: 10.1371/journal.pone.0007405.

[11] Puskarich MA, Shapiro NI, Trzeciak S, Kline JA, Jones AE. Plasma levels of mitochondrial DNA in patients presenting to the emergency department with sepsis. Shock 2012; 38: 337-340.

[12] Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest 1992; 101(6): 1644-1655.

[13] Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, et al. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med 2008; 36(1): 296-327.

doi:Document heading

*Corresponding author:Alan E. Jones, MD, Chair, Department of Emergency Medicine, University of Mississippi Medical Center, 2500 N State Street, Jackson, MS, 39216, USA.