Open Forum Infectious Diseases MAJOR ARTICLE Increased Indoleamine-2,3-Dioxygenase Activity Is Associated With Poor Clinical Outcome in Adults Hospitalized With Influenza in the INSIGHT FLU003Plus Study 1,2,3 4,5 6 7 8 9 10 Sarah L. Pett, Ken M. Kunisaki, Deborah Wentworth, Timothy J. Griffin, Ioannis Kalomenidis, Raquel Nahra, Rocio Montejano Sanchez, 4 11,12 13 14 4,5 Shane W. Hodgson, Kiat Ruxrungtham, Dominic Dwyer, Richard T. Davey, and Chris H. Wendt ; for the INSIGHT FLU003 Plus Study Group* 1 2 Medical Research Council Clinical Trials Unit (MRC CTU), Institute of Clinical Trials and Methodology, University College London, UK; Clinical Research Group, Infections and Population Health, 3 4 5 UCL, London, UK; Kirby Institute, University of New South Wales, Kensington, Australia; Minneapolis VA Health Care System, Minneapolis, Minnesota; Division of Pulmonary, Allergy, Critical 6 7 8 Care and Sleep Medicine, Division of Biostatistics, and Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, Minnesota; 1st Department of Critical Care and Pulmonary Medicine, University of Athens School of Medicine, Evangelismos General Hospital, Athens, Greece; Cooper University Hospital, Division of Infectious Disease, 10 11 12 Camden, New Jersey; Hospital La Paz, Madrid, Spain; HIV-NAT, Thai Red Cross AIDS Research Center, Bangkok, Thailand; Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; 13 14 Institute of Clinical Pathology and Medical Research, Pathology West and NSW Health Pathology, Westmead Hospital and University of Sydney, Westmead, Australia; and National National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland Background. Indoleamine-2,3-dioxygenase (IDO) mediated tryptophan (TRP) depletion has antimicrobial and immuno-regu- latory effects. Increased kynurenine (KYN)-to-TRP (KT) ratios, reflecting increased IDO activity, have been associated with poorer outcomes from several infections. Methods. We performed a case-control (1:2; age and sex matched) analysis of adults hospitalized with influenza A(H1N1) pdm09 with protocol-defined disease progression (died/transferred to ICU/mechanical ventilation) aer enr ft ollment (cases) or sur - vived without progression (controls) over 60 days of follow-up. Conditional logistic regression was used to analyze the relationship between baseline KT ratio and other metabolites and disease progression. Results. We included 32 cases and 64 controls with a median age of 52 years; 41% were female, and the median durations of in- uenza sy fl mptoms prior to hospitalization were 8 and 6 days for cases and controls, respectively (P = .04). Median baseline KT ratios were 2-fold higher in cases (0.24 mM/M; IQR, 0.13–0.40) than controls (0.12; IQR, 0.09–0.17; P ≤ .001). When divided into tertiles, 59% of cases vs 20% of controls had KT ratios in the highest tertile (0.21–0.84 mM/M). When adjusted for symptom duration, the odds ratio for disease progression for those in the highest vs lowest tertiles of KT ratio was 9.94 (95% CI, 2.25–43.90). Conclusions. High KT ratio was associated with poor outcome in adults hospitalized with influenza A(H1N1)pdm09. The clin- ical utility of this biomarker in this setting merits further exploration. ClinicalTrials.gov Identifier. NCT01056185. Keywords. influenza; indoleamine-2,3-dioxygenase; kynurenine; outcome; tryptophan. L-tryptophan (TRP) is an essential amino acid for many life forms of tryptophan in the immune response to many pathogens (eg, including humans. Tryptophan is also an essential amino acid fungi, tuberculosis, trypanosomiasis, chronic viral infections) for protein synthesis for some bacteria, many fungi, and possibly is an area of increased interest [1–3]. There is also considerable some viruses. It is also the precursor molecule for several impor- interest in the central role of tryptophan in the immune response tant neurotransmitters, that is, serotonin and melatonin. The role and/or surveillance of malignant cells/tumors, and inhibitors of tryptophan metabolism (indoleamine 2,3-dioxygenase [IDO] inhibitors) are being developed as adjunctive immunotherapeu- tics in the cancer setting . Received 12 June 2017; editorial decision 27 August 2017; accepted 24 October 2017. Presented in part: Was presented as an oral poster (poster no. A6850) at the American With respect to the role in the immune response to some Thoracic Society Conference, Washington DC, May 19–24, 2017. pathogens, tryptophan depletion through the catabolic enzyme, *See the full listing of the INSIGHT FLU003 Plus Study Group after the References. Correspondence: S. L. Pett, FRACP, FRCPE, PhD, Medical Research Council Clinical Trials Unit IDO, is thought to be a mechanism to “starve” pathogens of this (MRC CTU) at University College London, Aviation House, 125, Kingsway, London, WC2B 6NH, essential amino acid, but in turn it is coupled with a damping UK (firstname.lastname@example.org or email@example.com). down of the immune response, as downstream metabolites Open Forum Infectious Diseases © The Author(s) 2017. Published by Oxford University Press on behalf of Infectious Diseases of tryptophan ae ff ct the host immune response as well. There Society of America. This is an Open Access article distributed under the terms of the Creative appear to be 3 tryptophan-catabolizing enzymes , of which Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/ by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any IDO1 appears to be most important in the immune response medium, provided the original work is not altered or transformed in any way, and that the work to pathogens. IDO1 catabolizes TRP to kynurenine (KYN), an is properly cited. For commercial re-use, please contact firstname.lastname@example.org. DOI: 10.1093/ofid/ofx228 aryl hydrocarbon receptor ligand; subsequent catabolism of IDO Activity and Influenza Outcome • OFID • 1 Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 L-Tryptophan Tryptophan 2, 3-dioxygenase Indoleamine 2, 3-dioxygenase Formylkynurenine Kynurenine formamidase Kynurenine transaminase Kynureninase Kynurenic acid L-Kynurenine Anthranilic acid Kynurenine 3-monooxygenase Kynurenine transaminase Xanthurenic acid 3-Hydroxykynurenine Kynureninase 3-Hydoxyanthranilic acid 3-Hydroxyanthranilate-3, 4-dioxygenase 2-Amino-3-carboxymuconic semialdehyde Aminocarboxymuconate- Spontaneously semialdehyde Glutaryl-CoA decarboxylase Nicotinic acid Quinolinic acid Picolinic acid Acetyl-CoA Figure 1. L-tryptophan metabolic pathway. KYN leads to a number of KYN pathway metabolites (Figure 1). patients were divided into nonsepsis, sepsis, severe sepsis, and IDO1, found in the placenta, gut, and T cells, appears to play an septic shock categories, there was a clear correlation between important role in immune tolerance. IDO activity is induced increasing sepsis severity and increasing levels of KYN, decreas- by the immunomodulatory cytokine interferon-gamma (IFN-γ; ing levels of TRP, and, as a result, increasing KT ratios indicative which also appears to play an important role in mobilizing of IDO activation. Nonsurvivors also had significantly higher tryptophan into cells), other pro-inflammatory cytokines KT ratios than survivors . including interleukin-1 (IL-1) and tumor necrosis factor alpha To date, relatively little is known about the role of IDO in (TNF-α), amyloid peptides, and lipopolysaccharides. Increased the human immune response to influenza, with most published IDO activity ultimately leads, via the production of KYN (the data from murine influenza models. In the murine influenza “L-Kynurenine shunt”), to T-cell apoptosis, reduced T-cell pro- model, influenza induced IDO activity in mouse lung tissue and liferation, and an anergic state, with increased immunosup- draining lymph nodes . Moreover, IDO knockout mice and pressant, T-regulatory cells [6, 7]. The exact pathways for the mice treated with IDO inhibitors had better outcomes [11, 12]. interaction between antigen-presenting cells and the suppres- In a multiplex biomarker analysis of patients enrolled with sion of T-cell activity via IDO is not completely understood. influenza A(H1N1)pdm09 virus in FLU003 Plus (see the Increased plasma KYN levels and KYN-to-TRP (KT) ratios Methods), Davey and colleagues  found several biomarkers (as a measure of IDO activity) have been found in patients with that predicted poor clinical outcomes (defined as death, in-pa- systemic inflammatory response syndrome, sepsis, and septic tient stay of >28 days, or intensive care unit [ICU] admission), shock, but as yet, it is unclear what the findings mean . Suzuki including markers of macrophage activation/chemokines, and colleagues  explored the correlation between KT ratio T-cell activation, and acute phase reactants. and clinical outcome in patients hospitalized with communi- We therefore hypothesized that increased KT ratio would be ty-acquired pneumonia (CAP). In this group of patients, there associated with poor clinical outcomes (as defined by Davey was a significant positive correlation between both KYN levels and colleagues ) from influenza. In this analysis, we present and KT ratio with severity of CAP. Moreover, when these CAP novel data on the association of increased KT ratio and disease 2 • OFID • Pett et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Laboratory Methods progression and the association of KT ratio with the selected bio- Plasma Samples Preparation markers identified by Davey and colleagues  and, additionally, Local labs at the sites stored plasma samples using the method- interleukin-17 (IL-17) and interferon-gamma (IFN-γ), chosen ology described in the FLU003Plus laboratory manual. At study specifically because of their role in regulating IDO activity. enrollment, blood was drawn into EDTA tubes and processed METHODS within 4 hours. All samples were centrifuged at room temper- ature at 1200 g × 15 minutes, and the plasma aliquoted. These FLU003Plus is an ongoing, international observational study aliquots were then either stored immediately at –70/–80°C or of adults hospitalized with influenza that began in 2009, fol- initially at –20°C for a maximum of 4 days before being moved lowing the emergence of the influenza A(H1N1)pdm09 virus (on dry ice) into a –70/–80°C freezer. All samples used in this . Participants are eligible for enrollment in FLU003Plus analysis had undergone 1 freeze-thaw cycle. if they have laboratory-confirmed influenza based on a local nucleic acid test (NAT) or influenza is suspected and a local Mass Spectrometry Analysis NAT test has been performed. At enrollment, an upper respira- Sample Preparation tory tract swab is sent to a central laboratory for confirmation The method used is as described by Gulcev and colleagues of influenza using polymerase chain reaction (PCR)–based . Aliquots of 100 µL plasma had a heavy standard of 3 μL NAT. FLU003Plus captures a wide range of clinical informa- of 100 μM of kynurenine D6 and 3 µL of 1 mM tryptophan tion, including the reasons for hospitalization, type of ward to 13C11 (Cambridge Isotope Laboratories, Inc., Tewksbury, MA) which the patient was first admitted, and in subsequent visits at added prior to any preparation. These aliquots were then mixed day 28 and day 60, clinical status including death. The primary with 400 µL of ice-cold solvent (100% methanol), vortexed, and end point of FLU003Plus is disease progression, defined as a placed on ice for 10 minutes. Samples were then centrifuged composite of death, prolonged hospitalization >28 days, and at 13 000× g for 10 minutes at 4°C, and the supernatant was postenrollment intensive care/mechanical ventilation/extra- removed and transferred into a clean low-retention vial. This corporeal membrane oxygenation (ECMO) within 60 days of step was repeated once. Samples were concentrated using a vac- enrollment. uum centrifuge to ~50 µL. Formic acid was used to acidify the plasma samples that were added to the starting buffer used in Ethics Statement ultraperformance liquid chromatography (5% acetonitrile, 95% The FLU003Plus protocol and information statement and con- water, 0.1% formic acid) to 100 µL. sent form were approved by both the local institutional eth- ics committees/review boards of the participant sites and the Untargeted Mass Spectrometry Analysis ethics committee of the sponsor of this study, the University Undiluted sample (10 uL) was injected into a Thermo of Minnesota. All participants or their representatives (when Q-Exactive liquid chromatography–mass spectrometry (LC- participants were unable to consent for themselves and where MS; ThermoFisher Scientific, Marietta, OH) at 40°C. The sam- the ethics permission allowed for consent by a third party) pro- ples were subjected to a gradient going from Buffer A to Buffer vided written informed consent prior to their enrollment. B over 15 minutes, then flushing for 5 minutes. Buffer A con- Study Design and Objectives sisted of 99.9% water with 0.1% formic acid, while Buffer B was This was a matched case-control study. Cases were FLU003Plus 99.9% acetonitrile with 0.1% formic acid. patients with PCR-confirmed influenza A(H1N1)pdm09 virus with disease progression; controls had PCR-confirmed influ- XCMS Processing enza A(H1N1)pdm09 virus and were matched on age (+/-4 The RAW files from the Q-exactive were converted into mzXML years) and sex. Cases and controls were chosen from a subset using MSconvert  and processed using XCMS online under of 209 FLU003Plus participants who were the focus of previous the Q-Exactive parameters. The resulting file was used to ex- work on biomarkers . Our primary objective was to explore tract intensities of a specific tryptophan and kynurenine metab- the association of baseline (ie, the sample taken at the time of olite’s m/z and RT. enrollment into FLU003Plus) KT ratio, as a marker of IDO activity, with disease progression. Key secondary objectives Liquid Chromatography–Tandem Mass Spectrometry Selective explored the association of baseline KT ratio with death, the Reaction Monitoring Analysis of Tryptophan and Kynurenine multiplex panel of inflammatory biomarkers (as described by Diluted (1:1000 tryptophan and 1:100 for kynurenine) samples Davey et al. ), and baseline IFN-γ and IL-17. As described (20 µL) were subjected to injection using an Agilent autosampler by Davey et al. , biomarkers were classified as belonging to liquid chromatography–tandem mass spectrometry (LC-MS/ 1 of 4 groups, that is, macrophage proinflammatory activation MS) with an analytical Waters Symmetry C18, 3.5-µm column response, acute phase response, T-cell activation response, and connected to the 5500 iontrap (Sciex, Framingham, MA) fitted macrophage chemokine response. with a turbo V electrospray source. The samples were subjected IDO Activity and Influenza Outcome • OFID • 3 Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 to a linear gradient of 2% acetonitrile, 0.1% formic acid to 98% Luminex instrument (Bioplex 200) that determines the analyte acetonitrile 0.1% formic acid for 10 minutes at a column flow being detected via color coding; the other measures the magni- rate of 250 µL/min. Transitions monitored are in Table S1. The tude of the PE signal from the detection antibody, which is pro- data were analyzed using MultiQuant (Applied Biosystems, portional to the amount of analyte bound to the bead. Samples Foster City, CA), which provided the peak area for the tran- were run in duplicate, and values were interpolated from 5-par- sitions. A standard curve was constructed using concentration ameter fitted standard curves. ratios of heavy tryptophan/tryptophan and heavy kynurenine/ kynurenine from fentomole to nanomole in 20 µL. Measurement of Other Inflammatory Biomarkers Other inflammatory markers (see Table 1) were previously pub- Measurement of IL-17 and IFN-γ lished  and were used in this current analysis. IL-17 and IFN-γ were measured using the Luminex platform at the University of Minnesota Cytokine Reference Laboratory Statistical Methods (CLIA’88 licensed). Following the manufacturer’s instructions, With 96 samples, power was 80% to detect a difference of fluorescent magnetic beads (R&D Systems, Minneapolis, MN) 0.089 mM in KT ratios between cases and controls. Descriptive coated with IL-17 and IFN-γ antibodies were added to each statistics were used to summarize the baseline characteristics. sample. After incubation and washing, biotinylated detection Spearman rank correlation coefficients were used to explore antibody was added, followed by phycoerythrin-conjugated associations of baseline biomarkers with KT ratio. Conditional streptavidin. The beads were read on a dual-laser fluidics–based logistic regression was used to summarize the association of Table 1. Clinical Characteristics, Kynurenine, Tryptophan, and KT Ratio, Multiplex Panel of Inflammatory Biomarkers of Cases and Controls Hospitalized With Influenza A(H1N1)pdm09 Case (n = 32) Control (n = 64) No. (%) or Median (25th, 75th %) No. (%) or Median (25th, 75th %) P Value Female 13 (41) 26 (41) - Age 52 (41, 60) 53 (40, 60) - Nonwhite race 7 (22) 13 (20) .84 Smoker 10 (36) 22 (34) .86 Days since onset of influenza symptoms 8 (6, 10) 6 (4, 7) .04 Asthma or chronic obstructive pulmonary 6 (19) 14 (22) .70 disease Immune suppressive condition/treatment 8 (25) 7 (11) .33 Cardiovascular or chronic liver/renal disease 8 (25) 11 (17) .10 6.1 (3.9, 12.2) 3.9 (3.0, 5.9) .003 KYN μM TRP μM 32.4 (23.7, 40.7) 37.0 (27.1, 44.9) .10 KT ratio 0.24 (0.13, 0.40) 0.12 (0.09, 0.17) <.001 Macrophage proinflammatory activation response biomarkers IL-6, pg/mL 17.2 (12.9, 24.5) 10.7 (4.2, 19.0) .01 TNA-α, pg/mL 14.4 (11.2, 18.4) 12.4 (10.3, 16.1) .02 CD163, ng/mL 1608 (963, 2629) 710 (516, 1078) <.001 sICAM-1, ng/mL 526 (294, 791) 237 (95.7, 404) .002 IL-8, pg/mL 50.4 (26.0, 77.3) 23.5 (13.7, 44.7) .004 Acute phase response biomarkers 3.55 (1.4, 5.0) 1.04 (0.6, 1.7) <.001 D-dimer, μg/mL LBP, μg/mL 35.4 (14.1, 57.3) 18.2 (9.7, 45.0) .07 sVCAM-1, ng/mL 715 (527, 970) 392 (177, 667) .002 T-cell activation response biomarkers IL-2, pg/mL 3.67 (2.4, 7.9) 2.08 (1.2, 4.2) .009 IL-10, pg/mL 26.7 (11.6, 95.5) 10.8 (6.7, 19.4) .003 Macrophage chemokine response biomarkers MCP-1, pg/mL 1164 (539, 2440) 585 (379, 930) .001 IP-10, pg/mL 3160 (919, 7308) 1068 (518, 2453) .009 For biomarkers, values are log transformed for significance testing. Abbreviations: IL, interleukin; KT, kynurenine-to-tryptophan ratio; KYN, kynurenine; LBP, lipopolysaccharide-binding protein; TRP, tryptophan. Univariate conditional logistic. Matching factor. 4 • OFID • Pett et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 the baseline KT ratio at enrollment with disease progression. ratio in the lowest tertile (0.04–0.10 mM/M). Table 3 shows the Odd ratios (ORs) for upper and middle vs lower tertiles of the unadjusted and adjusted (for duration of symptoms at the time KT ratios are provided with the 95% confidence intervals and of enrollment) conditional logistic analyses. The unadjusted P values. This analysis was repeated with adjustment for dur- odds ratio (cases vs controls) was 5.94 (95% CI, 1.7–20.3) for ation of symptoms at enrollment, with and without additional those in the highest tertile of KT ratio as compared with the adjustment for log transformed biomarkers IL-10, sVCAM1, lowest tertile. When adjusted for symptom duration alone, the IL-2, and MCP-1. These particular biomarkers were chosen as OR for disease progression (ie, case vs control status) for those they represented the biomarkers most strongly related to dis- in the highest vs lowest KT ratio tertile was 9.94 (95% CI, 2.25– ease progression in the categories of macrophage proinflamma- 43.90; P ≤ .001). When restricted to the cases who died (n = 22), tory activation response, acute phase response, T-cell activation the OR for death (cases vs controls, and adjusted for symptom response, and macrophage chemokine response, respectively. P duration) for those in the highest vs lowest KT ratio tertile was values were not adjusted for these multiple comparisons. 12.14 (95% CI, 1.69–87.25; P = .004; data not shown). e a Th nalysis was repeated adjusting for duration of symp- RESULTS toms at enrollment and log transformed biomarkers IL-10, sVCAM1, IL-2, and MCP-1. With this adjustment, the pre- Thirty-two participants met our case definition; 22 of these dictive value of the highest KT ratio tertile vs the lowest tertile died. Two controls were available for all cases. Cases had been for disease progression, was attenuated to 3.34 (95% CI, 0.55– symptomatic for a median of 8 days, whereas controls had been 20.33; P = .06; data not shown). symptomatic for a median of 6 days (P = .04 for the difference) In addition, we explored the relationship of poor outcome (Table 1). Median baseline KT ratios were 2-fold higher for cases with downstream metabolites of L-kynurenine (Figure 1). We (0.24 mM/M; 25th, 75th percentiles, 0.13, 0.40) than controls found clear associations between poor outcomes and higher (0.12 mM/M; 25th, 75th percentiles, 0.09, 0.17; P ≤ .001). All levels of downstream KYN metabolites that included kynurenic 12 inflammatory biomarkers except lipopolysaccharide-bind- acid, anthranilic acid, 3-hydroxykynurenine, and quinolinic ing protein were significantly elevated in cases compared with acid (Table 4). One downstream metabolite, glutaryl-CoA, was controls (Table 1). The correlation of KYN, TRP, and KT ratios decreased in cases compared with controls. with each of the 12 biomarkers is described in Table 2; all 12 of IFN-γ and IL-17 were measured in cases and controls; 83% these biomarkers correlated with the KT ratio. of the IFN-γ levels were below the lower detection limit (data When KT ratios were divided into tertiles (Table 3), 60% of not shown), and therefore we could not analyze relationships cases vs 20% of controls had a KT ratio in the highest tertile between IFN-γ and outcomes. IL-17 levels (Table 5) were cat- (0.21–0.84 mM/M), and 16% of cases vs 39% of controls had a egorized as below the lower detection limit, and approximate median levels in those with detectable results. Equivalent num- Table 2. Correlation of Baseline Biomarkers With KYN, TRP, and the KT bers of cases and controls had IL-17 levels below the detection Ratio limit at study enrollment. KYN TRP KT Ratio DISCUSSION Coeff P Value Coeff P Value Coeff P Value Despite the relatively small cohort of patients studied, our data Macrophage proinflammatory activation response biomarkers reveal a strong association between high KT ratio and poor IL-6, pg/mL 0.44 <.001 –0.06 .55 0.40 <.001 clinical outcome in adults hospitalized with influenza. TNA-α, pg/mL 0.53 <.001 –0.04 .69 0.47 <.001 e hig Th h levels of metabolites of the tryptophan metabolic CD163, ng/mL 0.51 <.001 –0.13 .20 0.50 <.001 pathway also strengthen the evidence for IDO activation in this sICAM-1, ng/mL 0.20 .05 –0.12 .25 0.26 .010 IL-8, pg/mL 0.62 <.001 –0.08 .45 0.55 <.001 setting. IDO is induced by pro-inflammatory cytokines such as Acute phase response biomarkers TNF-α and IFN-γ following viral infection. In murine models, D-dimer, μg/mL 0.42 <.001 –0.09 .36 0.45 <.001 influenza induces IDO expression in lung tissue and lymph 0.38 <.001 –0.05 .66 0.35 <.001 LBP, μg/mL nodes [10, 11], and IDO inhibitors improve T-cell responses sVCAM-1, ng/mL 0.24 .02 –0.08 .44 0.28 .005 toward the virus . Most of the effects of tryptophan catabol- T-cell activation response biomarkers ism come from accumulation of its active downstream metabo- IL-2, pg/mL 0.54 <.001 –0.05 .64 0.49 <.001 IL-10, pg/mL 0.51 <.001 –0.13 .19 0.53 <.001 lites, many of which modulate the inflammatory state. Kynurenic Macrophage chemokine response biomarkers acid is a potent agonist of the orphan G-protein-coupled recep- MCP-1, pg/mL 0.56 <.001 –0.19 .06 0.58 <.001 tor GPR35, whose expression in T cells leads to an immuno- IP-10, pg/mL 0.63 <.001 –0.08 .45 0.56 <.001 suppressive phenotype . In monocytes and macrophages, P Values are from a univariate conditional logistic model. the interaction of GPR35 with kynurenic acid downregulates Abbreviations: IL, interleukin; KT, kynurenine-to-tryptophan ratio; KYN, kynurenine; LBP, lipopolysaccharide-binding protein; TRP, tryptophan. the pro-inflammatory effects of bacterial lipoloysaccharide IDO Activity and Influenza Outcome • OFID • 5 Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Table 3. Odds Ratios for Tertiles of KYN, TRP, and KT Ratio a a Case (n = 32) Control (n = 64) Unadjusted Adjusted a a Tertiles No. Pct. No. Pct. OR 95% CI OR 95% CI Kynurenine, μM 2.00–3.67 6 18.8 26 40.6 ref. ref. 3.68–5.89 9 28.1 23 35.9 1.55 0.51–4.70 2.61 0.64–7.28 5.90–33.9 17 53.1 15 23.4 4.25 1.39–12.98 5.95 1.60–22.08 P value, trend .003 .005 Tryptophan, μM 9.7–28.3 13 40.6 19 29.7 2.46 0.80–7.58 3.73 1.07–13.01 28.4–41.0 12 37.5 20 31.3 2.10 0.70–6.27 3.11 0.90–10.67 41.1–62.1 7 21.9 25 39.1 ref. ref. P value, trend .10 .06 KT ratio, mM/M 0.04–0.10 5 15.6 25 39.1 ref. ref. 0.11–0.20 8 25.0 26 40.6 1.50 0.40–5.64 1.96 0.44–8.79 0.21–0.84 19 59.4 13 20.3 5.94 1.74–20.33 9.94 2.25–43.90 P value <.001 <.001 Abbreviations: KT, kynurenine-to-tryptophan ratio; KYN, kynurenine; OR, odds ratio; TRP, tryptophan. Conditional logistic. Adjusted model contains covariates for duration of symptoms at time of enrollment. P value shown is for lab result as a continuous variable. [18–20]. Quinolinic acid is an end-product of L-kynurenine reactive oxygen species capable of inducing the secretion of metabolism and is a known agonist to N-methyl-D-aspartate potent chemokines and pro-inflammatory cytokines [21, 22]. receptors in nerve cells. Quinolinic acid also generates e m Th etabolite 3-hydroxykynurenine (3-HK) is a redox active Table 4. Odds Ratios for Tertiles of KYN Metabolites a a Case (n = 32) Control (n = 64) Unadjusted Adjusted a a Tertiles (log ) No. Pct. No. Pct. OR 95% CI OR 95% CI Kynurenic acid 6.54–6.93 8 25.0 24 37.5 ref. ref. 6.93–7.13 9 28.1 23 35.9 1.01 0.29–3.46 0.88 0.24–3.17 7.14–8.99 15 46.9 17 26.6 2.86 0.94–8.70 2.34 0.72–7.62 P value, trend .002 .004 Anthranilic acid 6.34–6.71 6 18.8 26 40.6 ref. ref. 6.72–6.90 9 28.1 23 35.9 1.84 0.52–6.44 1.88 0.50–7.00 6.91–7.72 17 53.1 15 23.4 5.45 1.52–19.44 5.59 1.43–21.84 P value, trend <.001 .002 3-hydroxykynurenine 6.26–6.72 6 18.8 26 40.6 ref. ref. 6.73–7.09 8 25.0 24 37.5 1.10 0.32–3.78 1.49 0.38–5.90 7.10–8.25 18 56.3 14 21.9 3.98 1.39–11.36 5.18 1.54–17.42 P value, trend .003 .003 Quinolinic acid 5.66–6.58 7 21.9 25 39.1 ref. ref. 6.59–6.92 7 21.9 25 39.1 1.09 0.31–3.92 1.59 0.38–6.60 6.93–8.32 18 56.3 14 21.9 4.01 1.28–12.54 5.21 1.42–19.10 P value, trend .001 .001 Glutaryl-CoA 5.03–6.59 17 53.1 15 23.4 37.52 4.19–336.1 27.39 3.01–249.4 6.60–6.92 13 40.6 19 29.7 16.96 2.16–133.4 16.07 2.02–127.8 7.08–7.72 2 6.3 30 46.9 ref. ref. P value, trend .003 .009 Abbreviations: KYN, kynurenine; OR, odds ratio. Conditional logistic. Adjusted model contains a covariate for duration of symptoms at time of enrollment. P value shown is for lab result as a continuous variable. 6 • OFID • Pett et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 Table 5. Odds Ratios for Categories of Baseline IL-17 Levels a a Case (n = 32) Control (n = 64) Unadjusted Adjusted a a IL-17 Levels No. Pct. No. Pct. OR 95% CI OR 95% CI Undetectable 15 46.9 30 46.9 ref. ref. 0.16–0.59 pg/mL 6 18.8 18 28.1 0.61 0.18–2.06 0.33 0.08–1.33 0.60–15.5 pg/mL 11 34.4 16 25.0 1.30 0.49–3.43 0.98 0.34–2.78 Abbreviation: OR, odds ratio. Conditional logistic. Adjusted model contains covariate for duration of symptoms at time of enrollment. clinical outcomes in those with CAP +/- sepsis and septic shock compound that regulates the local oxidative status. In a pro-ox- [3, 9] or sepsis alone . Moreover, in these other studies, IDO idative state, 3-HK demonstrates cellular toxicity . activity was predictive of mortality, unlike the respiratory rate or Although the effect of downstream metabolites was diluted the C-reactive protein level ; in 1 study of sepsis, decreases in somewhat when we controlled for baseline levels of other the median KT ratio over time correlated with decreases in the cytokines, there was still a trend to significance for the highest Sequential Organ Failure Assessment score, an objective assess- KT ratio tertile compared with the lowest as a predictor of poor ment of improving clinical outcome . While tryptophan clinical outcome. It is important to note that we did not set out deficiency alone can lead to cell dysfunction or death, most of to show that KT ratio performed better than the multiplex panel the effects of tryptophan catabolism come from accumulation of of inflammatory cytokines/vascular markers. Rather, our aim in its active downstream metabolites, such as kynurenine [31, 32], exploring this association was to try and understand the bio- which inhibits the clonal expansion of CD4 logical relationship between these inflammatory markers and T cells, leading to the IDO pathway in this setting. Our data suggest that activa- increased tolerance and immunosuppression. Quinolinic acid, tion of the IDO pathway might contribute to poor outcomes, another downstream metabolite, in nanamolar concentrations, independent of other inflammatory pathways. is metabolized to nicotinic acid mononucleotide and the nico- We were unable to quantify IFN-γ levels in the majority tinamide adenine dinucleotide via a salvage pathway, but in of patients in this subanalysis, which we suspect was due to a high concentration, it is directly toxic to cells [22, 32]. technical issue related to the samples utilized having already It will be important to expand our understanding of the role undergone 1 freeze-thaw cycle  and this cytokine being vul- of this immunoregulatory metabolic pathway in all types of in- nerable to a freeze-thaw cycle in a way that assessment of amino uenza (a fl nd other concurrent infections) and the relative bal- acids and their metabolite measured using LC-MS/MS are not. ance of immune activation vs immunosuppression. These data Another reason for this may have been the prolonged interval will help discern whether the many IDO inhibitors currently in from symptom onset to sampling or inadequate responses . development as adjunctive therapies for cancer may have po- IL-17 appears to have a dual role both as a pro- and anti-inflam- tential clinical utility as therapeutic agents in severe influenza matory cytokine, especially when produced by regulatory T and/or other infections. However, clinicians considering the use cells [26–29]. With respect to IL-17, there was no clear differ - of IDO inhibition in this setting should proceed with caution, as ence in the baseline levels between cases and controls, and as drugs inhibiting 1 part of an interlinked and complex metabolic such, in this analysis at least, we have no evidence that IL-17 was pathway may have a detrimental effect via the upregulation of contributing to the cytokine storm or, conversely, and reflecting compensatory pro-inflammatory and/or immunosuppressive its dual role, contributing to an immunosuppressive state. pathways. In this analysis, we chose death and/or mechanical ventila- tion as the end points of interest, as both are clinically impor- Conclusion and Future Directions tant, robust, and verifiable. While sites were required to report In summary, in this small case-control study, we have shown suspected/confirmed infections with other pathogens including that adults hospitalized with influenza A(H1N1)pdm09 and bacteria, the study did not require the submission of supporting high KT ratio have greater odds of progression to death or documentation. As such, we felt we could not verify these sep- mechanical ventilation. Measurement of this biomarker can be sis/bacterial infection events with sufficient certainty to include performed on plasma or serum, utilizing a standard tandem them as either an end point or covariate in the analysis. Our mass spectrometry approach available in most analytical labo- findings, however, may still represent the net effect of influenza ratories; moreover, the assay is robust and reproducible across plus secondary bacterial (and/or other pathogen) infections different laboratories. While this initial study reveals IDO activ- in both cases and controls, especially as they are similar to ity as a putative biomarker to identify those at risk of deteri- the findings revealed by other groups that have demonstrated oration, our findings need to be confirmed in further studies a strong association between elevated IDO activity and poor of all types/subtypes of influenza, preferably with longitudinal IDO Activity and Influenza Outcome • OFID • 7 Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 11. Huang L, LiL L, Klonowski KD, et al. Induction and role of indoleamine 2,3dioxy- sampling, in which clinical outcomes are rigorously captured. genase in mouse models of influenza a virus infection. PLoS One 2013; 8:e66546. Lastly, future studies in which peripheral blood mononuclear 12. Fox JM, Sage LK, Huang L, et al. Inhibition of indoleamine 2,3-dioxygenase cells are collected and isolated would potentially identify the enhances the T-cell response to influenza virus infection. J Gen Virol 2013; 94:1451–61. cellular production of IDO and give insight into the relationship 13. Davey RT Jr, Lynfield R, Dwyer DE, et al; INSIGHT FLU 002 & 003 Study Groups. of this metabolic pathway with the innate immune response. The association between serum biomarkers and disease outcome in influenza A(H1N1)pdm09 virus infection: results of two international observational cohort studies. PLoS One 2013; 8:e57121. Supplementary Data 14. https://clinicaltrials.gov. ClinicalTrials.gov. Identifier: NCT01056185. Supplementary materials are available at Open Forum Infectious Diseases 15. Gulcev M, Reilly C, Griffin TJ, et al. Tryptophan catabolism in acute exacerba- online. Consisting of data provided by the authors to benefit the reader, tions of chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis 2016; 11:2435–46. the posted materials are not copyedited and are the sole responsibility of 16. http://proteowizard.sourceforge.net/tools.shtml. Accessed 1 April 2017. the authors, so questions or comments should be addressed to the corre- 17. Sage LK, Fox JM, Mellor AL, et al. Indoleamine 2,3-dioxygenase (IDO) activity sponding author. during the primary immune response to influenza infection modifies the mem- ory T cell response to influenza challenge. Viral Immunol 2014; 27:112–23. Acknowledgments 18. Wang J, Simonavicius N, Wu X, et al. Kynurenic acid as a ligand for orphan G protein-coupled receptor GPR35. J Biol Chem 2006; 281:22021–8. We extend our grateful thanks to all the volunteers who have been partici- 19. Barth MC, Ahluwalia N, Anderson TJ, et al. Kynurenic acid triggers firm arrest pating in this study. of leukocytes to vascular endothelium under flow conditions. J Biol Chem 2009; Financial support. e INS Th IGHT FLU studies are funded under 284:19189–95. a Subcontract award 13XS134 under Leidos Biomed’s Prime Contract 20. Tiszlavicz Z, Németh B, Fülöp F, et al. Different inhibitory effects of kynurenic HHSN261200800001E and HHSN261201500003I, NCI/NIAID. acid and a novel kynurenic acid analogue on tumour necrosis factor-α (TNF- Potential conifl cts of interest. e v Th iews expressed in this article are α) production by mononuclear cells, HMGB1 production by monocytes and those of the authors and do not reflect the views of the US Government, HNP1-3 secretion by neutrophils. Naunyn Schmiedebergs Arch Pharmacol 2011; 383:447–55. the National Institutes of Health, the Department of Veterans Affairs, the 21. Guillemin GJ, Croitoru-Lamoury J, Dormont D, et al. Quinolinic acid upregulates funders, or any of the authors’ affiliated academic institutions. Sarah L. Pett: chemokine production and chemokine receptor expression in astrocytes. Glia grants from the University of Minnesota to support the conduct of the trial 2003; 41:371–81. at the FLU003Plus sites under the jurisdiction of the University of New 22. Guillemin GJ. Quinolinic acid, the inescapable neurotoxin. FEBS J 2012; South Wales; funding from the University of New South Wales to conduct 279:1356–65. the FLU003Plus trial at the clinical site. Ken Kunisaki: protected research 23. Okuda S, Nishiyama N, Saito H, Katsuki H. 3-Hydroxykynurenine, an endogen- time was provided by the Department of Veterans Affairs Office of Research ous oxidative stress generator, causes neuronal cell death with apoptotic features and Development. Deborah Wentworth: none. Timothy Griffin: none. and region selectivity. J Neurochem 1998; 70:299–307. Ioannis Kalomenidis: none. Raquel Nahra: none. Rocio Montejano Sanchez: 24. Yin P, Peter A, Franken H, et al. Preanalytical aspects and sample quality assess- ment in metabolomics studies of human blood. Clin Chem 2013; 59:833–45. none. Shane Hodgson: none. Kiat Ruxrungtham: protected research time 25. Lee N, Wong CK, Chan PK, et al. Hypercytokinemia and hyperactivation of phos- was provided by the Department of Medicine, The Faculty of Medicine, pho-p38 mitogen-activated protein kinase in severe human influenza A virus Chulalongkorn University, Thailand. Chris Wendt: protected research time infection. Clin Infect Dis 2007; 45:723–31. was provided by the Department of Veterans Affairs Office of Research and 26. Onishi RM, Gaffen SL. Interleukin-17 and its target genes: mechanisms of inter- Development. Dominic Dwyer: funding from the University of New South leukin-17 function in disease. Immunology 2010; 129:311–21. Wales to support the conduct of the FLU003Plus clinical trial at the clinical 27. Astry B, Venkatesha SH, Moudgil KD. Involvement of the IL-23/IL-17 axis and site. Richard Davey: funding from the University of Minnesota to support the Th17/Treg balance in the pathogenesis and control of autoimmune arthritis. the conduct of the FLU003Plus clinical trial at the clinical site. All authors Cytokine 2015; 74:54–61. have submitted the ICMJE Form for Disclosure of Potential Conflicts of 28. Voo KS, Wang YH, Santori FR, et al. Identification of IL-17-producing FOXP3+ regulatory T cells in humans. Proc Natl Acad Sci U S A 2009; 106:4793–8. Interest. Conflicts that the editors consider relevant to the content of the 29. Mercer F, Khaitan A, Kozhaya L, et al. Differentiation of IL-17-producing ef- manuscript have been disclosed. fector and regulatory human T cells from lineage-committed naive precursors. J Immunol 2014; 193:1047–54. References 30. Darcy CJ, Davis JS, Woodberry T, et al. An observational cohort study of the 1. Yeung AW, Terentis AC, King NJ, Thomas SR. 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An expanding range of targets for kynurenine metabolites of tryptophan. Trends Pharmacol Sci 2013; 34:136–43. The INSIGHT FLU003 Plus Study Group. 6. Fallarino F, Grohmann U, You S, et al. The combined effects of tryptophan star- International coordinating centers: Copenhagen: J. Lundgren, P. Jansson, vation and tryptophan catabolites down-regulate T cell receptor zeta-chain and M. Pearson, B. Aagaard; London: F. Hudson, R. Bennet, F. Pacciarini, induce a regulatory phenotype in naive T cells. J Immunol 2006; 176:6752–61. 7. Puccetti P, Grohmann U. IDO and regulatory T cells: a role for reverse signalling B. Angus, N. Paton, Y. Collaco Moraes; Sydney: D. Cooper, S. Pett, and non-canonical NF-kappaB activation. Nat Rev Immunol 2007; 7:817–23. S. Emery, D. Courtney-Rogers, R. Robson; Washington: F. Gordin, 8. Changsirivathanathamrong D, Wang Y, Rajbhandari D, et al. Tryptophan metab- A. Sanchez, B. Standridge, M. Vjecha. 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Brown 8 • OFID • Pett et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018 (Leidos Biomedical Research, Inc.); M. Hoover (ABML). National Institute V. Estrada; Hospital Universitario de Álava (n = 22): P. Lopetegui; Hospital of Allergy and Infectious Disease/Leidos: J. Beigel, R. T. Davey Jr., R. Dewar, Universitario Infanta Leonor (n = 20): T. Gimenez Julvez, P. Ryan; Hospital E. Gover, R. McConnell, J. Metcalf, V. Natarajan, T. Rehman, J. Voell. Centre Universitario Príncipe de Asturias (n = 13): J. Sanz Moreno; Hospital del for Infectious Diseases and Microbiology Laboratory Services (Westmead Mar (n = 10): H. Knobel; Hospital Carlos III (n = 5): V. Soriano; Hospital Hospital and University of Sydney, Westmead, New South Wales, Australia): Universitari Mutua Terrassa (n = 2): D. Dalmau; United Kingdom (n = 186); D. E. Dwyer, J. Kok. Centers for Disease Control and Prevention: T. Uyeki. Sheffield Teaching Hospitals (n = 76): D. Dockrell; Churchill Hospital Community Representative: D. Munroe. Clinical site investigators: United (n = 43): B. Angus; Newcastle Hospitals (n = 40): D. Price; Royal Sussex States (n = 484); Baystate Infectious Diseases Clinical Research (n = 99): County Hospital (n = 23): M. Newport; The James Cook University Hospital A. Paez, M. Bertrand; Mayo Clinic (n = 69): Z. Temesgen, S. Rizza; Duke (n = 4): D. Chadwick; Denmark (n = 181); Aarhus Universitetshospital, University (n = 45): C. Wolfe, J. Carbonneau; University of Illinois at Skejby (n = 88): L. Østergaard, Y. Yehdego; Odense University Hospital Chicago (n = 39): R. Novak, M. Schwarber; Miami Valley Hospital (n = 32): (n = 37): C. Pedersen, L. Hergens; CHIP, Rigshospitalet, Department H. Polenakovik, L. Clark; Brigham and Women’s Hospital (n = 30): N. Patil; of Infectious Diseases, Section 2100 (n = 26): Z. Joensen, B. Aagaard; Montefiore Medical Center (n = 26): P. Riska, J. Omotosho; Henry Ford Hvidovre University Hospital, Department of Infectious Diseases Health System (n = 25): L. Faber, N. Markowitz; Weill Cornell Medical (n = 14): G. Kronborg, P. Collins; Aalborg Hospital (n = 12): H. Nielsen; College (n = 25): M. Glesby, K. Ham; George Washington Medical Faculty Rigshospitalet, Infektionsmedicinsk Ambulatorium 8622 (n = 4): Associates (n = 23): D. Parenti, G. Simon; Cooper University Hospital J. Gerstoft, B. Baadegaard; Greece (n = 161); 1st Respiratory Medicine (n = 13): J. Baxter, P. Coburn; University of Pittsburgh Medical Center Dept, Athens Hospital for Diseases of the Chest, Sotiria Hospital (n = 89): (n = 12): M. Freiberg, G. Koerbel; NJMS Adult Clinical Research Center N. Koulouris; Attikon University General Hospital (n = 44): A. Antoniadou, (n = 10): N. Dharan, M. Paez-Quinde; University of Tennessee College K. Protopappas; 3rd Pulmonary Dept and 2nd Internal Medicine Dept, of Medicine (n = 9): J. Gunter; Medical College of Wisconsin (n = 7): Sismanoglio Athens General Hospital (n = 13): V. Polixronopoulos, M. Beilke, Z. Lu; Minneapolis Medical Research Foundation, Hennepin F. Diamantea; Hippokration University General Hospital of Athens (n = 12): County Medical Center (n = 4): E. Gunderson, J. Baker; The Ohio State H. Sambatakou, I. Mariolis; 12th Respiratory and TB Medical Dept, Athens University Medical Center (n = 4): S. Koletar, H. Harber; UNC AIDS Hospital for Diseases of the Chest, Sotiria Hospital (n = 3): N. Vassilopoulos, Clinical Trials Unit (n = 3): C. Hurt, C. Marcus; Washington DC VA A. Gerogiannis; Peru (n = 133); Hospital Nacional Arzobispo Loayza Medical Center (n = 3): M. Allen, S. Cummins; David Geffen School of (n = 105): Y. Pinedo Ramirez, E. Cornelio Mauricio; Hospital Nacional Medicine at UCLA (n = 2): D. Uslan, T. Bonam; Community Research Guillermo Almenara Irigoyen (n = 28): J. Vega Bazalar, R. Castillo Cordova; Initiative - Springfield (n = 1): A. Paez, F. Santiago; Denver Public Health Germany (n = 112); Uniklinik Köln (n = 57): G. Fãtkenhuerer, E. o Th mas; (n = 1): D. States, E. Gardner; SUNY Downstate Medical Center (n = 1): Charité Universitätsklinikum Berlin (n = 15): F. Bergmann, U. Fõllmer; J. DeHovitz, S. Holman; Virginia Commonwealth University (n = 1): Universitätsklinikum Bonn (n = 15): J. Rockstroh, A. Englehardt; V. Watson, D. Nixon; Australia (n = 338); Westmead Hospital (n = 287): Universitätsklinikum Frankfurt (n = 11): C. Stephan, E. o Th mas; Klinikum D. Dwyer, M. Kabir; St. Vincent’s Hospital (n = 26): S. Pett, F. Kilkenny; The der Universität München (n = 7): J. Bogner; Klinikum der Ruhr-Universität Alfred Hospital (n = 22): J. Elliott, J. Garlick; Cairns Sexual Health Service Bochum (n = 4): N. Brockmeyer; Universitätsklinikum Würzburg (n = 3): (n = 3): J. McBride, S. Richmond; Argentina (n = 216); Hospital Italiano de H. Klinker; Thailand (n = 61); Khon Kaen University, Srinagarind Hospital Buenos Aires (n = 92): L. Barcan, M. Sanchez; Hospital Profesor Bernardo (n = 43): P. Chetchotisakd, T. Jumpimai; Chulalongkorn University and the Houssay (n = 49): G. Lopardo, L. Barcelona; CEMIC (n = 37): P. Bonvehi, HIV-NAT (n = 18): A. Avihingsanon, K. Ruxrungtham; Belgium (n = 56); E. R. Temporiti; Hospital General de Agudos J. M. Ramos Mejia (n = 34): Centre Hospitalier Universitaire St. Pierre: N. Clumeck, K. Kameya; China M. Losso, L. Macias; Hospital Nacional Profesor Alejandro Posadas (n = 3): (n = 24); Queen Elizabeth Hospital: M. Y. Chu, T. C. Wu; Poland (n = 14); H. Laplume, L. Daciuk; Hospital Interzonal General de Agudos Dr. Diego Wojewodzki Szpital Zakazny: A. Horban, E. Bakowska; Austria (n = 11); Paroissien (n = 1): E. Warley, S. Tavella; Spain (n = 195); Hospital General University Vienna General Hospital: H. Burgmann, S. Tobudic; Norway Universitario Gregorio Marañón (n = 61): E. Fernandez Cruz; Hospital (n = 9); Oslo University Hospital, Ullevål: A. Maagaard; Chile (n = 2); Universitario La Paz (n = 37): J. Paño; Hospital Clínico San Carlos (n = 25): Fundación Arriarán: M. Wolff, G. Allendes. IDO Activity and Influenza Outcome • OFID • 9 Downloaded from https://academic.oup.com/ofid/article-abstract/5/1/ofx228/4565598 by Ed 'DeepDyve' Gillespie user on 16 March 2018
Open Forum Infectious Diseases – Oxford University Press
Published: Jan 1, 2018
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