Introduction
Sepsis represents an ongoing challenge in intensive care units (ICUs) and remains the most common cause of mortality in this setting [
1],[
2]. Increased oxidative stress, as a consequence of the systemic inflammatory response, has been suggested as a major causative factor for the development and progression of the disease. However, there is little conclusive evidence that a targeted treatment with antioxidants in patients with sepsis could be beneficial [
3],[
4]. This may suggest the involvement of alternative mediators of cellular stress in the pathophysiology of sepsis.
Reactive carbonyl species (RCS) have emerged as effective mediators of cellular dysfunction. RCS are a heterogeneous group of reactive low-molecular-weight carbonyls, which are able to interact with various biomolecules, such as proteins, deoxyribonucleic acid, or phospholipids, resulting in structural distortions and functional impairment [
5]. The detrimental effects of RCS are comparable to those caused by reactive oxygen species (ROS), except that RCS are significantly more stable and can readily diffuse out of the cell and have effects far from the original site of their formation [
5]. Furthermore, several of the most reactive RCS are derived from glucose metabolism (in particular, glycolysis) [
5]. As ROS require three stages of metabolism before they are produced, RCS can be viewed as providing a more direct insult to the macromolecular integrity of the cell.
Methylglyoxal (MG) is a highly reactive RCS, produced endogenously from the spontaneous degradation of triosephosphates—glyceraldehyde-3-phosphate (GA3P) and dihydroxyacetone phosphate (DHAP)—during glycolysis. It is estimated that approximately 0.089% of triosephosphates are converted to MG and that the total body rate of formation for a healthy adult human is about 3 mmol per day [
6]. The formation of MG is closely linked to the rate of glycolysis within the cell. It would be expected that under physiological conditions, where there is either an increase in glycolytic flux or an increased dependence on glycolysis for energy, the rate of MG formation would be increased [
7],[
8]. This has proven to be the case in patients with diabetes mellitus, in which complications such as nephropathy, neuropathy, and retinopathy can be linked to increases in cellular levels of glycated proteins, which then are referred to as advanced glycation end products (AGEs) [
9].
A clinical feature of patients with sepsis is hyperglycemia [
10],[
11]. However, the consequences of elevated blood glucose in sepsis, particularly with respect to production of MG and its potential role in the development and progression of the disease, have yet to be fully investigated. The aims of this study were to assess the impact of MG formation in different inflammatory settings and to evaluate its use for early diagnosis as well as prognosis of sepsis.
Materials and methods
Selection of patients and study procedures
The observational clinical pilot study was approved by the local ethics committee (Ethics Committee of the Medical Faculty of Heidelberg: Trial Code Number S123-2009/German Clinical Trials Register: DRKS00000505) and was conducted in the surgical ICU of the University Hospital of Heidelberg, Germany. Study and control patients or their legal designees provided written informed consent. In total, 120 patients in three groups were consecutively enrolled into the study from August 2009 to July 2010. The three groups were the following: (1) 60 patients with septic shock, according to the criteria of the International Sepsis Definitions Conference [
12] (referred to as the septic group, or S) (Table
1), due to documented or suspected infection according to the criteria of the International Sepsis Forum Consensus Conference on Definitions of Infection in the ICU (Additional file
1: Table S1) [
13]; (2) 30 postoperative controls following major abdominal surgery without any evidence of infection (the postoperative group, or P) (Table
2); and (3) 30 healthy volunteers (the volunteer group, or V) (Table
2). Blood samples from patients with septic shock were collected at sepsis onset (T0) and 24 hours (T1), 4 days (T2), 7 days (T3), 14 days (T4), and 28 days (T5) later. Blood samples from the postoperative group were collected prior to surgery (T0), immediately following the end of the surgical procedure (T1), and 24 hours later (T2). Blood samples from the volunteer group were collected once (T0).
Table 1
Characteristics of 60 patients in the septic group
Demographic data
|
Age, years | 70 (64-76) |
Male sex | 46 (76.7%) |
ASA status: I; II; III; IV; V | 1 (1.7%); 11 (18.3%); 29 (48.3%); 15 (25.0%); 1 (1.7%) |
Primary site of infection (double-naming feasible)
|
Lung | 12 (20.0%) |
Gastrointestinal tract | 32 (53.3%) |
Genitourinary tract | 6 (10.0%) |
Others | 18 (30.0%) |
Unknown | 4 (6.7%) |
Infection type
|
Gram-positive isolates | 16 (26.7%) |
Gram-negative isolates | 16 (26.7%) |
Combination of both | 18 (30.0%) |
Suspected infection without any microbiological finding | 10 (16.7%) |
Septic organ failures
|
Septic shock | 60 (100.0%) |
Acute renal failure | 35 (58.3%) |
Acute respiratory distress syndrome | 49 (81.2%) |
Acute liver failure | 15 (25.0%) |
Disease severity scoring
|
S/T0
|
S/T1
|
APACHE II score | 33 (27-38) | 33 (28-39) |
SAPS | 75 (66-86) | 73 (64-84) |
SOFA score | 14 (11-15) | 14 (12-15) |
Clinical data
|
S/T0
|
S/T1
|
Norepinephrine, μg/kg per minute | 0.20 (0.06-0.31) | 0.20 (0.08-0.32) |
Maximum heart rate, 1/minute | 115 (97-130) | 113 (102-127) |
Minimum MAP, mm Hg | 57 (50-64) | 60 (54-66) |
FiO2, none | 0.65 (0.50-0.80) | 0.58 (0.46-0.70) |
Table 2
Characteristics of 30 patients in the postoperative group and 30 individuals in the volunteer group
Demographic data
|
Age, years | 62 (57-70) |
Male sex | 16 (53.3%) |
ASA status: I; II; III; IV; V | 0 (0.0%); 9 (30.0%); 20 (66.7%); 1 (3.3%); 0 (0.0%) |
Site of surgery (double-naming feasible)
|
Liver | 7 (23.3%) |
Pancreas | 11 (36.7%) |
Gastrointestinal | 27 (90.0%) |
Volunteer group (n = 30)
|
Demographic data
|
Age, years | 26 (24-28) |
Male sex | 19 (63.3%) |
ASA status: I; II; III; IV; V | 21 (70.0%); 9 (30.0%); 0 (0.0%); 0 (0.0%); 0 (0.0%) |
Immunoassays
Plasma concentrations of total antioxidant capacity (TAC), methylglyoxal-derived advanced glycation end products (MG-AGE), and interleukin-6 (IL-6) were measured by using enzyme-linked immunosorbent assay (ELISA) kits in accordance with the instructions of the manufacturer (TAC and MG-AGE: Biocat, Heidelberg, Germany; IL-6: R&D Systems, Minneapolis, MN, USA). Plasma levels of soluble CD14 subtype (sCD14-ST) were measured by using the Pathfast Presepsin chemiluminescent enzyme immunoassay in accordance with the instructions of the manufacturer (Mitsubishi Chemical, Tokyo, Japan).
Methylglyoxal measurements with high-performance liquid chromatography
The concentrations of MG in plasma were determined by derivatization with 1,2-diamino-4,5-dimethoxybenzene and high-performance liquid chromatography of the quinoxaline adduct by fluorescence detection [
14],[
15].
Preparation of peripheral blood mononuclear cells
Peripheral blood mononuclear cells (PBMCs) were separated immediately after blood collection. Ethylenediaminetetraacetic acid (EDTA)-anticoagulated whole blood was loaded carefully onto a lymphocyte separation medium (PAA Laboratories GmbH, Pasching, Austria) and centrifuged for 25 minutes at 1,200 rpm without brakes at 4°C. The PBMC-containing band was aspirated, and the cells were washed three times with NaCl 0.9%.
RNA extraction and quantitative polymerase chain reaction
RNA extraction was performed by using the column-based RNeasy Plus Mini Kit (Qiagen, Hilden, Germany) in accordance with the instructions of the manufacturer. RNA (250 ng) was reverse-transcribed by using the QuantiTect Reverse Transcription Kit (Qiagen) in accordance with the instructions of the manufacturer. Subsequent real-time polymerase chain reaction (PCR) analysis was performed on a StepOnePlus PCR cycler (Applied Biosystems, Weiterstadt, Germany) by using predesigned TaqMan assays for glyoxalase-1 (GLO-1) (assay ID Hs00198702_m1) and β-Actin (assay ID Hs99999903_m1). PCRs were set up by using the TaqMan Universal PCR Master Mix (Applied Biosystems, Weiterstadt, Germany). All experiments were run in triplicate. Results are interpreted by calculating the change in cycle threshold (∆Ct) value (Ct β-actin – Ct GLO-1) of each sample.
Statistical analysis
The present clinical investigation was conducted as a pilot study. Group sizes were set at 60 individuals in the septic group and 30 individuals in both the healthy and postoperative groups. Resulting study data was entered into an electronic database (Microsoft Excel 2010, Microsoft Corporation, Redmond, WA, USA) and evaluated by using SPSS software (Statistical Product and Services Solutions, Version 20.0, SPSS Inc., Chicago, IL, USA) or Graphpad Prism for Macintosh (Version 5.0f, GraphPad Software, San Diego, CA, USA). Categorical data were summarized by means of absolute and relative frequencies. Quantitative data were summarized by using medians (with quartiles). Wherever appropriate, data was visualized by using line or bar charts. The Kolmogorov-Smirnov test was applied to check for normal distribution. Owing to non-normally distributed data in this study, non-parametric methods for evaluation were used. Furthermore, a receiver operating characteristic (ROC) curve was calculated with suitable parameters in order to create cutoff values to determine the diagnostic or prognostic value of each parameter with regard to the diagnosis as well as the prognosis of sepsis. Comparisons of the areas under two or more correlated ROC curves were performed as described by Delong
et al. [
16]. Correlation analysis was performed calculating Spearman-Rho (r). A
P value of less than 0.05 was considered statistically significant. The following symbols were used with regard to higher orders of significance: *
P <0.05, **
P <0.01, ***
P <0.001.
Discussion
In this study, MG was identified as a marker for monitoring the onset, development, and remission of sepsis. It was found to be more useful than routine diagnostic markers, such as CRP, PCT, IL-6, and sCD14-ST. This finding is of great interest, as it has been suggested that the currently used biomarkers for sepsis do not have either the specificity or sensitivity to be routinely used in clinical practice [
17].
The major source of endogenous MG is from the non-enzymatic degradation of the triosephosphate intermediates within glycolysis. Under conditions of increased glycolytic flux, such as hyperglycemia (a symptom often observed in patients with sepsis), it would be safe to assume that there should be an increase in MG production. In this study, blood sugar levels were significantly elevated in patients with septic shock. Measured plasma MG in these patients was also elevated, but only a weak correlation with blood glucose levels could be shown. This would suggest that there are other factors contributing to the measured increased plasma levels of MG than only hyperglycemia.
In this study, patients with septic shock characteristically have an increased state of oxidative stress and this correlates positively with plasma MG levels, suggesting that a relationship exists between these two forms of metabolic stress. GLO-1, the major pathway for detoxification of MG, is a glutathione (GSH)-dependent enzyme [
18]. Previous studies have shown that under conditions of oxidative stress, both GSH and nicotinamide-adenine-dinucleotide-phosphate-hydrate (NADPH) are depleted, which in turn decreases the
in situ activity of GLO-1 [
19], thereby increasing the concentration of MG. The loss of essential cofactors in a situation of increased oxidative stress could therefore be one explanation for the increased plasma MG observed in the patients with sepsis. However, it was also found that patients with sepsis syndrome had a significant reduction in the expression of mononuclear GLO-1, suggesting that patients with sepsis are more susceptible to the accumulation of MG through the loss of the GLO-1 rather than the loss of an essential cofactor. It has been proposed that the engagement of the receptor for advanced glycation end products (RAGE) by inflammatory mediators, such as carboxylmethyl-lysine (CML) and high-mobility group box protein-1 (HMGB1), can reduce expression of GLO-1 [
20]. In this study, the cell-surface expression of RAGE was increased in the monocytes of patients with septic shock; however, there was also a significant reduction in the plasma concentration of the classic RAGE ligands (data not shown). It has also been proposed that hyperglycemic conditions, such as those observed in diabetes, can directly reduce GLO-1 activity. However, the underlying mechanism for this effect remains unclear [
21].
One of the primary effects of elevated MG is the post-translational modification of proteins to form AGEs [
22],[
23]. This study could show that the concentration of MG-AGEs in plasma paralleled the levels of MG and that the highest concentrations were observed 24 hours after the onset of sepsis. This may simply reflect a cause-and-effect relationship in the plasma; however, it may also indicate an increased turnover of MG-modified or damaged proteins within the tissue [
6]. Such modified proteins are degraded by cellular proteolysis, releasing not only modified peptides but also the modified amino acid, which is eventually excreted in the urine [
6]. Several studies have shown that MG-derived hydroimidazolone (MG-H1) [
24], the adduct formed from MG modification of arginine, is the major quantitative modified adduct excreted in humans and rats [
25],[
26]. Increased excretion of this modified product, particularly in diabetes mellitus, is associated with the development and progression of complications, such as neuropathy, nephropathy, and retinopathy [
9],[
27]-[
30]. It has also been shown that MG-AGEs, specifically MG-H1, can interact with RAGE. Monocytes can bind, internalize, and degrade albumin which has been minimally modified by MG, leading to synthesis and secretion of pro-inflammatory mediators such as IL-1β, macrophage colony-stimulating factor, and tumor necrosis factor-alpha. It has been suggested that this binding is mediated by RAGE [
31]-[
35], making it possible that the high circulating levels of MG-AGE proteins found in patients with sepsis could activate circulating monocytes by ligating RAGE. This may result in the downregulation of GLO-1 and the induction of the pro-inflammatory phenotype observed in patients with septic shock. Further
in vitro studies using MG-modified proteins, modified to a similar extent as those observed in patients with sepsis, are required to confirm this observation.
The findings of increased MG and MG protein damage in sepsis suggest that MG metabolism is an important and generally overlooked biochemical pathway for the induction of cellular dysfunction or inflammation (or both) in sepsis. Furthermore, prevention of MG overload might represent a new therapeutic option in sepsis. Unfortunately, there are currently no MG scavengers approved for clinical use. As in diabetes, tight blood glucose control in patients with sepsis may offer a strategy for reducing the amount of MG accumulation. Accordingly, recent clinical guidelines for the treatment of sepsis have recommended that blood glucose levels should be maintained at not more than 180 mg/dL [
36]. An alternative treatment strategy could be to increase GLO-1 activity. It has been shown
in vitro that GLO-1 transcription is regulated by the antioxidant transcription factor nuclear factor (erythroid-derived 2)-like 2 (Nrf2) [
37]. Activation of this transcription factor by isothiocyanates, such as sulphoraphane, can lead to increased GLO-1 activity and decreased MG and MG-derived AGEs [
38]. Such compounds are found in high abundance in cruciferous vegetables. However, the effect of such treatment
in vivo remains unknown and requires further investigation to determine whether it would be effective in acute illnesses such as sepsis.
Further investigations are required to determine whether the diagnostic and prognostic value of MG can be confirmed and validated in a large study cohort. Moreover, to link the clinical observations of our study to functional implications, it needs to be evaluated
in vitro, whether MG modifications are responsible for the cellular dysfunction or inflammation (or both) observed in sepsis. Critical to this process would be to identify the cellular targets involved in this modification. It could already be shown that mitochondrial proteins are particularly susceptible to modification by MG [
39]. The ELISA-based method used to detect MG-AGEs in this study is unable to differentiate whether the MG-AGEs measured are complete proteins, peptides, or the free amino acids. In future studies, the measurement of both MG and MG-AGEs should be performed by using the gold-standard technique of stable isotope dilution, liquid chromatography tandem mass spectroscopy, which could provide robust identification, particularly with respect to the proteins or amino acids (or both) modified by MG [
26],[
40].
Acknowledgments
The authors gratefully acknowledge Ute Krauser, Roland Galmbacher, Serap Kaymak, Anja Buhl, and Divija Deshpande for their excellent technical assistance. This investigation was carried out with financial resources of the Department of Anesthesiology (University of Heidelberg, Germany), the Department of Medicine I and Clinical Chemistry (University of Heidelberg), the Department of Surgery (University of Heidelberg), the Department of Infectious Diseases (University of Heidelberg), and the Institute of Medical Biometry and Informatics (University of Heidelberg).
Competing interests
The authors declare that they have no competing interests and that they have full control of all primary data. The authors agree to allow the journal to review their data if requested.
Authors’ contributions
TBre was involved in the conception, hypothesis delineation, and design of the study. He performed data acquisition and data analysis and wrote the manuscript. TF was involved in the conception, hypothesis delineation as well as design of the study and helped to write the manuscript. FU, SS, FS, and ES performed data acquisition and were involved in revising the manuscript critically. AU and SZ participated in the design of the study and revised the manuscript critically. TBru participated in the design of the study and performed the statistical analyses. EM, PPN, MAW, and SH conceived the study, participated in its design, and coordinated and helped to draft the manuscript. AB conceived of the study and participated in its design. All authors read and approved the final manuscript.