- Research article
- Open Access
- Open Peer Review
Association of the Tyrosine/Nitrotyrosine pathway with death or ICU admission within 30 days for patients with community acquired pneumonia
© The Author(s). 2018
- Received: 12 December 2017
- Accepted: 15 August 2018
- Published: 24 August 2018
Oxidative stress is a modifiable risk-factor in infection causing damage to human cells. As an adaptive response, cells catabolize Tyrosine to 3-Nitrotyrosine (Tyr-NO2) by nitrosylation. We investigated whether a more efficient reduction in oxidative stress, mirrored by a lowering of Tyrosine, and an increase in Tyr-NO2 and the Tyrosine/Tyr-NO2 ratio was associated with better clinical outcomes in patients with community-acquired pneumonia (CAP).
We measured Tyrosine and Tyr-NO2 in CAP patients from a previous randomized Swiss multicenter trial. The primary endpoint was adverse outcome defined as death or ICU admission within 30-days; the secondary endpoint was 6-year mortality.
Of 278 included CAP patients, 10.4% experienced an adverse outcome within 30 days and 45.0% died within 6 years. After adjusting for the pneumonia Severity Index [PSI], BMI and comorbidities, Tyrosine nitrosylation was associated with a lower risk for short-term adverse outcome and an adjusted OR of 0.44 (95% CI 0.20 to 0.96, p = 0.039) for Tyr-NO2 and 0.98 (95% CI 0.98 to 0.99, p = 0.043) for the Tyrosine/Tyr-NO2 ratio. There were no significant associations for long-term mortality over six-years for Tyr-NO2 levels (adjusted hazard ratio 0.81, 95% CI 0.60 to 1.11, p = 0.181) and Tyrosine/Tyr-NO2 ratio (adjusted hazard ratio 1.00, 95% CI 0.99 to 1.00, p = 0.216).
Tyrosine nitrosylation in our cohort was associated with better clinical outcomes of CAP patients at short-term, but not at long term. Whether therapeutic modulation of the Tyrosine/Tyr-NO2 pathway has beneficial effects should be evaluated in future studies.
ISRCTN95122877. Registered 31 July 2006.
However, the significance and prognostic value of metabolomic markers of oxidative stress remains understudied. In 2013, a single-center study found the ratio of Tyr-NO2 to Tyrosine, to be predictive of mortality in critically ill patients with acute kidney injury . To the best of our knowledge, there are no published data for other clinical patient populations. More profound knowledge about oxidative pathways in patients with systemic infections is interesting as it is modifiable by drugs, and is thus a potential therapeutic target. Herein, we measured baseline levels of Tyrosine and Tyr-NO2 in a well-defined cohort of patients with community acquired pneumonia (CAP) followed prospectively for 6 years. Our aim was to study associations of initial Tyrosine, Tyr-NO2 levels and their ratio respectively, with short-term adverse outcomes defined as death or ICU admission within 30 days, and long-term mortality. We hypothesized that a more efficient reduction in oxidative stress mirrored by an increase in Tyr-NO2, and a lowering of Tyrosine and the ratio of Tyrosine to Tyr-NO2 would be associated with better clinical outcomes.
Study design, inclusion and exclusion criteria
Detailed information about the initial trial has been published previously [11, 12]. In brief, patients were included if they presented from the community or a nursing home to the emergency department, and met the inclusion criteria (≥18 years of age plus one or more of the following: cough, dyspnea, pleural pain, sputum production or tachypnea; plus, one or more sign of infection or positive auscultation. All patients with CAP had a radiologically confirmed infiltrate. Exclusion criteria were language barriers or dementia precluding the ability to give written informed consent, intravenous drug use, patients with terminal conditions and patients with hospital-acquired pneumonia. The blood samples and clinical data were gathered at admission to the emergency department. All involved clinicians were blinded for the results of the blood markers.
Analysis of serum biomarkers
At emergency department admission, blood samples from each patient were taken, centrifuged and frozen at − 80 °C directly for later measurement of metabolomic biomarkers [14–17]. Baseline Tyrosine and Tyr-NO2 were measured in blood samples of 278 patients. The AbsoluteIDQ p180 Kit (BIOCRATES Life Sciences AG, Innsbruck, Austria) was used for laboratory testing [18–23], after validation of the method in our lab Samples were prepared according to the manufacturer’s protocol. Analysis was performed using an Ultimate 3000 UHPLC system (Thermo Fisher, San Jose, California, USA) coupled to an ABSciex 5500 QTRAP quadrupole mass spectrometer (ABSciex, Darmstadt, Germany). Analytes were separated on a Thermo Syncronis aQ 50 × 2.1 mm 1.7 μm column prior to targeted screening using multiple reaction monitoring (MRM). Quantification of analytes was done by reference corrected to appropriate internal standards. The lowest calibrator for Tyr and NO2-Tyr was set as the lower limit of quantification (LLoQ) and not investigated in detail. Also the limit of detection was not investigated in detail. LLoQ was 5 μmol/L for Tyr and 1 μmol/L for NO2-Tyr, respectively. Calibration curve was controlled by quality control samples. Concentration of calibrator and quality control (QC) samples were given by the manufacturer and were not changed. All QC samples met the criteria adapted from the manufacturer of the p180 kit. Concentrations are reported in μmol/L .
Main outcome measurements
The primary endpoint was adverse outcome defined as a composite of ICU admission and/or death within 30 days after study inclusion. The decision for ICU admission was based on clinical judgement of the treating physician team. The secondary endpoint was death at 6 years. Trained medical students ascertained vital status through structured phone interviews at day 30, 180 and 540 and at 6 years [23, 24]. We contacted the treating general practitioners if neither patients nor their household members were reached.
We used STATA 12.1 (Stata Corp, College Station, TX, USA) for all statistical analyses. A p-value of < 0.05 was considered to indicate statistical significance. Continuous variables are reported as medians (interquartile range (IQR)) and categorical variables are expressed as percentages (numbers). We used Chi-square (Wald) tests for frequency comparisons, and we executed nonparametric (Spearman’s rank correlation) tests for two-group comparisons.
The distribution of Tyrosine and Tyr-NO2 (subsequently referred to as “biomarkers”) were skewed. After logarithmic transformation at a base of 10, the distribution of the biomarkers approximated a normal distribution. We studied associations of biomarkers with the primary endpoint by calculation of logistic regression models. We used univariate and multivariate linear regression models adjusted for predefined confounders such as age, sex, BMI and comorbidities. Odds ratios (OR) were calculated and reported with 95% CIs. Area under the receiver operating characteristic curves (AUCs) with 95% CIs are presented to illustrate discrimination. We additionally performed univariate and multivariate Cox regression models to investigate associations between biomarker levels at baseline and long-term mortality. These associations are reported as hazard ratios (HRs) with 95% confidence intervals (CIs) and significance levels for the chi-square (Wald) test. We further illustrated mortality with a Kaplan-Meier curve, stratifying patients based on the median Tyrosine level.
Baseline characteristics stratified by the first endpoint (adverse outcome)
Non-adverse outcome at 30d
Adverse outcome at 30d
Age in years median (IQR)
71.5 (57, 82)
71 (57, 82)
76 (67, 83)
Gender, n (%)
BMI, median (IQR)
24.8 (22.0, 27.7)
24.6 (21.8, 27.5)
26.6 (24.4, 29.5)
Coronary Heart Disease, n (%)
Congestive Heart Failure, n (%)
Chronic Kidney Disease, n (%)
Diabetes mellitus, n (%)
Tumor, n (%)
COPD, n (%)
Pulse rate, bpm, median (IQR)
94 (82, 107)
94 (82.5, 106)
97 (75, 114)
Temperature, °C, median (IQR)
38 (37.2, 38.9)
38 (37.2, 39)
37.4 (36.7, 38.4)
Systolic BP, mmHg, median (IQR)
130 (118, 146)
131 (120, 147)
124 (102, 139)
Markers of oxidative stress and inflammation
Tyrosine, median (IQR)
81.7 (63.2, 118.0)
81.6 (61.8, 117.0)
84.0 (66.4, 122.0)
Tyr-NO2, median (IQR)
1.5 (0.8, 11.7)
1.5 (0.9, 12.3)
1.4 (0.5, 4.0)
Ratio Tyr-NO2/Tyrosine, median (IQR)
2.0 (1.0, 7.6)
2.1 (1.0, 8.3)
1.9 (0.9, 3.5)
CRP, median (IQR)
136 (63, 252)
132 (61, 246)
176 (106, 336)
PCT, median (IQR)
0.45 (0.16, 3.20)
0.40 (0.15, 2.96)
0.64 (0.21, 6.30)
Association of markers of oxidative stress with clinical parameters and markers of inflammation
Rank-sum correlations of markers of oxidative stress levels with demographics, comorbidities, vital signs, clinical scores and inflammatory biomarkers
r 0.1748, p = 0.0230
r 0.0856, p = 0.2684
r 0.0158, p = 0.8383
r − 0.0253, p = 0.7441
r 0.0458, p = 0.5545
r 0.0508, p = 0.5116
r − 0.0870, p = 0.2608
r − 0.0100, p = 0.8973
r 0.0039, p = 0.9594
Coronary heart disease
r 0.0263, p = 0.7059
r − 0.0020, p = 0.9775
r − 0.0224, p = 0.7483
Chronic heart failure
r 0.0586, p = 0.4005
r 0.1123, p = 0.1064
r 0.0681, p = 0.3285
Chronic Kidney Disease
r 0.0178, p = 0.7981
r 0.0104, p = 0.8809
r 0.0083, p = 0.9050
r − 0.0156, p = 0.8225
r 0.1052, p = 0.1305
r 0.1205, p = 0.0830
r 0.0430, p = 0.5378
r − 0.0559, p = 0.4228
r − 0.0832, p = 0.2321
r 0.0816, p = 0.2413
r 0.0392, p = 0.5741
r 0.0149, p = 0.8310
r − 0.0761, p = 0.2893
r − 0.0981, p = 0.1714
r − 0.0592, p = 0.4096
r-0.0305, p = 0.6716
r − 0.0113, p = 0.8753
r 0.0066, p = 0.9270
r − 0.0226, p = 0.7532
r 0.2403, p = 0.0007
r 0.2804, p = 0.0001
r 0.1264, p = 0.0689
r 0.0932, p = 0.1805
r 0.0464, p = 0.5060
r 0.1243, p = 0.0737
r 0.1008, p = 0.1474
r 0.0508, p = 0.4662
r 0.0307, p = 0.6594
r 0.1132, p = 0.1034
r 0.1074, p = 0.1226
r − 0.2662, p = 0.0001
r − 0.0994, p = 0.1540
r − 0.0338, p = 0.6286
r − 0.1607, p = 0.0207
r 0.0519, p = 0.4579
r 0.1158, p = 0.0967
r − 0.0586, p = 0.4018
r 0.0080, p = 0.9091
r 0.0397, p = 0.5703
Association between markers of oxidative stress and short-term adverse outcome
After 30 days of study inclusion, the composite primary endpoint was reached by 29 (10.4%) of patients. Lower levels of Tyr-NO2 and the ratio of Tyr-NO2 to Tyrosine were associated with a lower risk for 30-day adverse outcome, as evidenced by a PSI, BMI and comorbidities-adjusted OR of 0.44 (95% CI 0.20 to 0.95, p = 0.039) and 0.98 (95% CI 0.98 to 0.99, p = 0.043) respectively. Results for Tyrosine were not significant in univariate analysis (OR 3.3, 95% CI 0.63 to 17.36), p = 0.159), nor in multivariate analysis (OR 0.84 (95% CI 0.15 to 4.65.), p = 0.841).
Association of initial levels of oxidative stress markers with endpoints
Entire Cohort (n = 278)
Adverse outcome at 30d
6 year Mortality
OR (95% CI); p-value
HR (95% CI); p-value
3.30 (0.63 to 17.36), p = 0.159
1.88 (0.90 to 3.91), p = 0.093
0.84 (0.15 to 4.65), p = 0.841
1.58 (0.72 to 3.47), p = 0.256
0.55 (0.44 to 0.66)
0.60 (0.54 to 0.67)
0.65 (0.35 to 1.20), p = 0.167
0.96 (0.73 to 1.27), p = 0.778
0.44 (0.20 to 0.96), p = 0.039
0.81 (0.6 to 1.1), p = 0.181
0.43 (0.31 to 0.56)
0.50 (0.42 to 0.58)
0.91 (0.81 to 1.02), p = 0.098
0.99 (0.95 to 1.02), p = 0.457
0.98 (0.97 to 0.99), p = 0.043
1.00 (0.99 to 1.00), p = 0.216
0.42 (0.30 to 0.53)
0.48 (0.40 to 0.56)
Association between markers of oxidative stress and long-term mortality
Oxidative stress has been recognized as a potentially modifiable risk factor in inflammation and infection, but there is a lack of clinical data regarding the significance of specific metabolomic markers of oxidative stress. In this study of CAP patients followed prospectively for 6 years, we tested the hypothesis that a more efficient reduction in oxidative stress, mirrored by metabolomic markers of oxidative stress, would be associated with better health outcomes. Our results indicate that levels of Tyr-NO2 tend to be lower and the ratio of Tyrosine to Tyr-NO2 tends to be higher in patients with adverse short-term outcomes and higher long-term mortality, however many results did not reach levels of statistical significance.
In the setting of a systemic inflammatory disease such as CAP, an increase in the production of ONOO.- takes place, which is primarily mediated by an upregulation of inducible nitric oxide synthase in macrophages, leading to nitric oxide reacting with also increased levels of superoxide O2.- . This process represents the generation of nitrosative stress in addition to oxidative stress, which may lead to uncontrolled nitrosylation of molecules and in turn to dysfunction of proteins, cells and organs . It is important to bear in mind, that the equilibrium between Tyrosine, Tyr-NO2 and Peroxynitrite is quite complex and can be influenced by a plethora of interfering physiological processes, such as alternative elimination pathways of NO via the reaction with metal ions, principally with iron , the not well known pathway of catabolism of Tyr-NO2 . We hypothesized that the capacity to process oxidative stress via this pathway could be indicative of the ability to resist damage from oxidative insults. While knowledge of these pathways is mainly based on preclinical studies [1–9], there is a lack of patient data showing markers of oxidative stress is associated with clinical outcomes [29–31]. Herein, we measured initial levels of Tyrosine and Tyr-NO2 levels in a relatively large and well-defined cohort of CAP patients over a 6-year follow-up period. Interestingly, in an analysis adjusted for age, sex and comorbidities, low admission levels of Tyr-NO2 were associated with a lower risk for reaching the primary composite endpoint and showed a trend with the secondary endpoint of death at 6 years, however this association does not persist after adjustment for multiple testing. Although levels of Tyrosine and the Tyr-NO2/Tyrosine ratio did not show a significant correlation with either the composite endpoint or with 6-year mortality, trends persisted indicating worse outcomes in patients with higher Tyrosine levels and lower ratios. Importantly, from our analysis it remains unclear whether systemic inflammation impedes the Tyrosine/Tyr-NO2-pathway, implying an observational correlation; or whether a higher capacity for detoxification is a patient-specific characteristic (measure of resources), suggesting a causative relation of Tyrosine nitrosylation on clinical outcome. Yet, we did not find associations of comorbidities and levels of Tyrosine, Tyr-NO2 or their ratio. Blood markers of inflammation (i.e. CRP and PCT), on the other hand, showed a weak, however significant association with Tyrosine, as well as age. However, these associations did not persist after adjusting for multiple testing and should thus be rather viewed as exploratory. A higher Tyr-NO2 and Tyr-NO2/Tyrosine ratio were associated with body temperature, possibly reflecting a more intact physiological response to inflammation.
The main strengths of this study are the measurement of different oxidative stress markers in a well characterized cohort of CAP patients where clinical data have been sparse on the significance of oxidative stress markers. Our cohort included patients with CAP of various severities, who were followed over 6 years. Still, there are a number of limitations to this study. Firstly, the number of included patients reaching an endpoint was relatively small, limiting the statistical power. In fact, a post-hoc power analysis showed that we only had 20% and 34% power to find a significant difference in levels of Tyrosine and Tyr-NO2, respectively, regarding the primary endpoint. This may explain the borderline significant results found in some of the analyses. Secondly, we did not measure the serum levels of Peroxynitrite in the original blood samples, which could have given a more complete picture of the biochemical pathway. Thirdly the data were generated in Swiss hospitals only, limiting generalizability to other countries. Further, the cause of death was not verified by autopsy. Because of this, we investigated all-cause mortality rather than mortality related to infection. We did not differentiate the degree of severity of infection (e.g. whether sepsis or septic shock was present on presentation). Finally, we did not further explore whether oxidative stress markers would improve risk scores of pneumonia such as CURB65 because our results indicated a rather low discriminative performance in regard to AUCs. We also did not measure the maximum time to analysis for the obtained blood samples. As a secondary analysis of a randomized controlled trial, this investigation is rather hypothesis-generating, but may help to stimulate more interest into oxidative stress in future studies. Study of an animal model might help to further advance the understanding of the Tyrosine/Tyr-NO2 pathway, as well as the effects of therapeutic intervention on outcomes.
In conclusion, our data suggest that more efficient reduction in oxidative stress, mirrored by metabolomic markers, could be associated with fewer adverse clinical outcomes in CAP patients at short-term, but not at long-term. Further research, however, is needed to validate our findings and to better understand causal effects. Also, whether therapeutic modulation of the Tyrosine/Tyr-NO2 pathway improves clinical outcomes should be evaluated in future studies.
The abstract of this paper was presented at the annual meeting of the Swiss Society of Endocrinology and Diabetes (SGED) in Bern on 17th of November 2017.
We would like to acknowledge the contributions of the staff of the emergency department, medical clinic, and central laboratory of the University Hospital Basel and the cantonal Hospitals of Aarau, Lucerne, Liestal, and Muensterlingen, and the ‘Buergerspital’ Solothurn for their assistance and technical support. We would additionally like to thank all patients, their relatives as well as all local general practitioners for their participation. Finally, the authors acknowledge the ProHOSP Study Group for their valuable support.
Consent for publication
Availability of data and materials
The dataset supporting the conclusions of this article is available in the Open Science Framework repository, [https://osf.io/267bw/].
CS, LB and AH performed laboratory measurements of the p180-kit. TB and PS performed the statistical analyses. TB, MCC, CH1, CH2 RT, WZ, BM and PS contributed to data acquisition. TB, GZ, YW, MM and PS contributed to the drafting and interpretation of the analyses. TB, GZ, YW, MM, MCC, CH1, CH2, RT, WZ, BM and PS contributed to the critical review for important content, and final approval of the manuscript. PS had full access to all data in the study and takes responsibility for the integrity of the work and the accuracy of the data analysis. All authors read and approved the final manuscript.
This study was supported by the Swiss National Science Foundation (SNSF Professorship, PP00P3_150531) and the Forschungsrat of the Kantonsspital Aaarau (1410.000.058 and 1410.000.044).
Ethics approval and consent to participate
The initial study protocol has been performed in accordance with the declaration of Helsinki and was approved by the ethics committee of the University of Basel, written informed consent for the study including consent for the use of the data in secondary blood marker analyses and follow-up was obtained from all participating patients. The trial was registered at http://controlled-trials.com (identifier ISRCTN95122877).
The authors declare that they have no competing interests.
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- Padmaja S, Huie RE. The reaction of nitric oxide with organic peroxyl radicals. Biochem Biophys Res Commun. 1993;195(2):539–44. Epub 1993/09/15View ArticlePubMedGoogle Scholar
- Ohshima H, Friesen M, Brouet I, Bartsch H. Nitrotyrosine as a new marker for endogenous nitrosation and nitration of proteins. Food Chem Toxicol. 1990;28(9):647–52. Epub 1990/09/01View ArticlePubMedGoogle Scholar
- Liu X, Miller MJ, Joshi MS, Thomas DD, Lancaster JR Jr. Accelerated reaction of nitric oxide with O2 within the hydrophobic interior of biological membranes. Proc Natl Acad Sci U S A. 1998;95(5):2175–9. Epub 1998/04/16View ArticlePubMedPubMed CentralGoogle Scholar
- Liochev SI, Fridovich I. Reversal of the superoxide dismutase reaction revisited. Free Radic Biol Med. 2003;34(7):908–10. Epub 2003/03/26View ArticlePubMedGoogle Scholar
- Ischiropoulos H, Nadziejko CE, Kikkawa Y. Effect of aging on pulmonary superoxide dismutase. Mech Ageing Dev. 1990;52(1):11–26. Epub 1990/03/01View ArticlePubMedGoogle Scholar
- Ischiropoulos H, Zhu L, Chen J, Tsai M, Martin JC, Smith CD, et al. Peroxynitrite-mediated tyrosine nitration catalyzed by superoxide dismutase. Arch Biochem Biophys. 1992;298(2):431–7. Epub 1992/11/01View ArticlePubMedGoogle Scholar
- Smith CD, Carson M, van der Woerd M, Chen J, Ischiropoulos H, Beckman JS. Crystal structure of peroxynitrite-modified bovine Cu,Zn superoxide dismutase. Arch Biochem Biophys. 1992;299(2):350–5. Epub 1992/12/01View ArticlePubMedGoogle Scholar
- Nathan C, Xie QW. Nitric oxide synthases: roles, tolls, and controls. Cell. 1994;78(6):915–8. Epub 1994/09/23View ArticlePubMedGoogle Scholar
- Nathan C, Xie QW. Regulation of biosynthesis of nitric oxide. J Biol Chem. 1994;269(19):13725–8. Epub 1994/05/13PubMedGoogle Scholar
- Qian J, You H, Zhu Q, Ma S, Zhou Y, Zheng Y, et al. Nitrotyrosine level was associated with mortality in patients with acute kidney injury. PLoS One. 2013;8(11):e79962. Epub 2013/11/28View ArticlePubMedPubMed CentralGoogle Scholar
- Schuetz P, Christ-Crain M, Wolbers M, Schild U, Thomann R, Falconnier C, et al. Procalcitonin guided antibiotic therapy and hospitalization in patients with lower respiratory tract infections: a prospective, multicenter, randomized controlled trial. BMC Health Serv Res. 2007;7:102. Epub 2007/07/07View ArticlePubMedPubMed CentralGoogle Scholar
- Schuetz P, Christ-Crain M, Thomann R, Falconnier C, Wolbers M, Widmer I, et al. Effect of procalcitonin-based guidelines vs standard guidelines on antibiotic use in lower respiratory tract infections: the ProHOSP randomized controlled trial. JAMA. 2009;302(10):1059–66.View ArticlePubMedGoogle Scholar
- Alan M, Grolimund E, Kutz A, Christ-Crain M, Thomann R, Falconnier C, et al. Clinical risk scores and blood biomarkers as predictors of long-term outcome in patients with community-acquired pneumonia: a 6-year prospective follow-up study. J Intern Med. 2014;Google Scholar
- Nickler M, Ottiger M, Steuer C, Huber A, Anderson JB, Muller B, et al. Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections. Respir Res. 2015;16(1):125. Epub 2015/10/17View ArticlePubMedPubMed CentralGoogle Scholar
- Nickler M, Schaffner D, Christ-Crain M, Ottiger M, Thomann R, Hoess C, et al. Prospective evaluation of biomarkers for prediction of quality of life in community-acquired pneumonia. Clinical chemistry and laboratory medicine : CCLM / FESCC. 2016;54(11):1831–46. Epub 2016/04/22View ArticleGoogle Scholar
- Nickler M, Ottiger M, Steuer C, Kutz A, Christ-Crain M, Zimmerli W, et al. Time-dependent association of glucocorticoids with adverse outcome in community-acquired pneumonia: a 6-year prospective cohort study. Crit Care. 2017;21(1):72. Epub 2017/03/25View ArticlePubMedPubMed CentralGoogle Scholar
- Ottiger M, Nickler M, Steuer C, Odermatt J, Huber A, Christ-Crain M, et al. Trimethylamine-N-oxide (TMAO) predicts fatal outcomes in community-acquired pneumonia patients without evident coronary artery disease. Eur J Intern Med. 2016;36:67–73. Epub 2016/08/28View ArticlePubMedGoogle Scholar
- Weinberger KM. [metabolomics in diagnosing metabolic diseases]. Therapeutische Umschau revue therapeutique. 2008;65(9):487-91. Epub 2008/09/16. Einsatz von Metabolomics zur Diagnose von Stoffwechselkrankheiten. Google Scholar
- Yet I, Menni C, Shin SY, Mangino M, Soranzo N, Adamski J, et al. Genetic influences on metabolite levels: a comparison across Metabolomic platforms. PLoS One. 2016;11(4):e0153672. Epub 2016/04/14View ArticlePubMedPubMed CentralGoogle Scholar
- Illig T, Gieger C, Zhai G, Romisch-Margl W, Wang-Sattler R, Prehn C, et al. A genome-wide perspective of genetic variation in human metabolism. Nat Genet. 2010;42(2):137–41. Epub 2009/12/29View ArticlePubMedGoogle Scholar
- Muller A, Heseler K, Schmidt SK, Spekker K, Mackenzie CR, Daubener W. The missing link between indoleamine 2,3-dioxygenase mediated antibacterial and immunoregulatory effects. J Cell Mol Med. 2009;13(6):1125–35. Epub 2009/07/16View ArticlePubMedGoogle Scholar
- Berger M, Gray JA, Roth BL. The expanded biology of serotonin. Annu Rev Med. 2009;60:355–66. Epub 2009/07/28View ArticlePubMedPubMed CentralGoogle Scholar
- Majno G, Palade GE, Schoefl GI. Studies on inflammation. II. The site of action of histamine and serotonin along the vascular tree: a topographic study. J Biophys Biochem Cytol. 1961;11:607–26. Epub 1961/12/01View ArticlePubMedPubMed CentralGoogle Scholar
- Muller AJ, Malachowski WP, Prendergast GC. Indoleamine 2,3-dioxygenase in cancer: targeting pathological immune tolerance with small-molecule inhibitors. Expert Opin Ther Targets. 2005;9(4):831–49. Epub 2005/08/09View ArticlePubMedGoogle Scholar
- Robinson MA, Baumgardner JE, Otto CM. Oxygen-dependent regulation of nitric oxide production by inducible nitric oxide synthase. Free Radic Biol Med. 2011;51(11):1952–65. Epub 2011/10/01View ArticlePubMedGoogle Scholar
- Singer M. The role of mitochondrial dysfunction in sepsis-induced multi-organ failure. Virulence. 2014;5(1):66–72. Epub 2013/11/05View ArticlePubMedGoogle Scholar
- Pacher P, Beckman JS, Liaudet L. Nitric oxide and peroxynitrite in health and disease. Physiol Rev. 2007;87(1):315–424. Epub 2007/01/24View ArticlePubMedPubMed CentralGoogle Scholar
- Nishino SF, Spain JC. Biodegradation of 3-nitrotyrosine by Burkholderia sp. strain JS165 and Variovorax paradoxus JS171. Appl Environ Microbiol. 2006;72(2):1040–4. Epub 2006/02/08View ArticlePubMedPubMed CentralGoogle Scholar
- Fukuyama N, Takebayashi Y, Hida M, Ishida H, Ichimori K, Nakazawa H. Clinical evidence of peroxynitrite formation in chronic renal failure patients with septic shock. Free Radic Biol Med. 1997;22(5):771–4. Epub 1997/01/01View ArticlePubMedGoogle Scholar
- Pacher P, Obrosova IG, Mabley JG, Szabo C. Role of nitrosative stress and peroxynitrite in the pathogenesis of diabetic complications. Emerging new therapeutical strategies. Curr Med Chem. 2005;12(3):267–75. Epub 2005/02/23View ArticlePubMedPubMed CentralGoogle Scholar
- Pacher P, Schulz R, Liaudet L, Szabo C. Nitrosative stress and pharmacological modulation of heart failure. Trends Pharmacol Sci. 2005;26(6):302–10. Epub 2005/06/01View ArticlePubMedPubMed CentralGoogle Scholar