**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Mohapatra, Sadik, Tykocinski, Dietze, Poschet, Heiland and Opitz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Immune and Neuroendocrine Trait and State Markers in Psychotic Illness: Decreased Kynurenines Marking Psychotic Exacerbations

Livia De Picker 1,2 \*, Erik Fransen3 , Violette Coppens 1,2, Maarten Timmers 4,5 , Peter de Boer 4 , Herbert Oberacher 6 , Dietmar Fuchs 7 , Robert Verkerk 8 , Bernard Sabbe1,2 and Manuel Morrens 1,2

1 Faculty of Medicine and Health Sciences, Collaborative Antwerp Psychiatric Research Institute, University of Antwerp, Antwerp, Belgium, 2 University Department of Psychiatry, Campus Duffel, Antwerp, Belgium, 3 StatUa Center for Statistics, University of Antwerp, Antwerp, Belgium, 4 Janssen Research and Development, Janssen Pharmaceutica N.V., Beerse, Belgium, 5 Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium, 6 Core Facility Metabolomics, Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria, 7 Biocenter, Division of Biological Chemistry, Medical University of Innsbruck, Innsbruck, Austria, 8 Department of Pharmaceutical Sciences, University of Antwerp, Antwerp, Belgium

### Edited by:

Kai Fang, University of California, Los Angeles, United States

#### Reviewed by:

Ana Maria Teixeira, University of Coimbra, Portugal Trevor William Stone, University of Oxford, United Kingdom Martin Samuelsson, Linköping University, Sweden

> \*Correspondence: Livia De Picker<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Inflammation, a section of the journal Frontiers in Immunology

Received: 22 July 2019 Accepted: 03 December 2019 Published: 17 January 2020

#### Citation:

De Picker L, Fransen E, Coppens V, Timmers M, de Boer P, Oberacher H, Fuchs D, Verkerk R, Sabbe B and Morrens M (2020) Immune and Neuroendocrine Trait and State Markers in Psychotic Illness: Decreased Kynurenines Marking Psychotic Exacerbations. Front. Immunol. 10:2971. doi: 10.3389/fimmu.2019.02971 Objective: Different patterns of immune system upregulation are present in the acute vs. post-treatment states of psychotic illness. We explored the existence of state and trait markers in the peripheral immune system and two immune-associated neuroendocrine pathways (IDO and GTP-CH1 pathway) in a longitudinal sample of psychosis patients. We also evaluated the association of these markers with neuropsychiatric symptomatology.

Method: Plasma concentrations of peripheral blood markers were measured in a transdiagnostic group of 49 inpatients with acute psychosis and 52 matched healthy control subjects. Samples were obtained in patients within 48 h after hospital admission for an acute psychotic episode (before initiation of antipsychotics), after 1–2 weeks and again after 8 weeks of treatment. Kynurenine, kynurenic acid (KA), 3-hydroxykynurenine (3-HK), quinolinic acid (QA), phenylalanine, tyrosine, nitrite, and neopterin were measured using HPLC and LC-MS/MS analysis. Concentrations of CRP, CCL2 (MCP1) and cytokines were determined with multiplex immunoassay. PANSS interviews and cognitive tests were performed at baseline and follow-up. Mixed model analyses were used to identify trait and state markers.

Results: Patients had significantly higher plasma concentrations of CRP, CCL2, IL1RA, and lower concentrations of KA and KA/Kyn at all time points (F7.5–17.5, all p < 0.001). Increased concentrations of IL6, IL8, IL1RA, TNFα, and CCL2 and decreased QA and 3-HK (F8.7–21.0, all p < 0.005) were found in the acute psychotic state and normalized after treatment. Low nitrite concentrations at admission rose sharply after initiation of antipsychotic medication (F42.4, p < 0.001). PANSS positive scale scores during the acute episode correlated with pro-inflammatory immune markers (r ≥ |0.5|), while negative scale scores correlated inversely with IDO pathway markers (r ≥ |0.4|). Normalization of KA and 3-HK levels between admission and follow-up corresponded to a larger improvement of negative symptoms (r = 0.5, p < 0.030) A reverse association was found between relative improvement of SDST scores and decreasing KA levels (r = 0.5, p < 0.010).

Conclusion: The acute psychotic state is marked by state-specific increases of immune markers and decreases in peripheral IDO pathway markers. Increased CRP, CCL2, and IL1RA, and decreased KA and KA/Kyn are trait markers of psychotic illness.

Keywords: psychosis, schizophrenia, cytokines, kynurenines, kynurenic acid, inflammation, immune, biomarkers

### INTRODUCTION

Premorbid dysregulation of the immune system has been identified as an important factor of vulnerability for schizophrenia (1–3). Immune system activation could also be involved in schizophrenia symptom development by upregulating two neuroendocrine pathways which affect the biological availability of the two main monoamine neurotransmitter precursors: tryptophan (Trp) and tyrosine (Tyr) (cfr. **Figure 1**).

Stimulation by inflammatory molecules, particularly IFNγ, strongly activates indoleamine-2,3-dioxygenase (IDO) and the closely related tryptophan 2,3-dioxygenase 2 (TDO2), the first and rate-limiting enzymes of tryptophan breakdown into kynurenine (Kyn). In particular IDO has been linked to immune functioning: the enzyme is found in a variety of immune cells, including microglia in the central nervous system (CNS), and is often upregulated when the immune response is activated (4). Kynurenine is further degraded into downstream metabolites such as 3-hydroxykynurenine (3-HK), quinolinic acid (QA), and kynurenic acid (KA), which directly affect neuronal functioning. KA is an endogenous antagonist of all ionotropic excitatory amino acid receptor activities and therefore considered a protective metabolite against neurotoxic NMDA receptor agonist QA (5). However, abnormal accumulation of KA could lead to glutamatergic hypofunctioning and induce psychotomimetic effects (6, 7). In animal models, elevated KA levels are associated with sensory gating deficits and schizophrenia-like cognitive dysfunctions (e.g., deficits in set-shifting tasks, spatial working memory, hippocampal long-term potentiation, and attentional processing of environmental stimuli) (8–12).

A second neuroendocrine pathway which is upregulated by proinflammatory cytokines runs through GTP cyclohydrolase 1 (GTP-CH1), producing neopterin and tetrahydrobiopterin (BH4). BH4 is an essential cofactor of phenylalanine-hydroxylase (PHA), tyrosine-hydroxylase, tryptophan-hydroxylase, and nitric oxide synthases (NOS) and plays a fundamental role in the synthesis of monoamine neurotransmitters (13). Neopterin is released by activated human monocytic cells at the expense of BH4 activity. BH4 is particularly sensitive to oxidative stress and BH4 deficiencies have been reported in patients afflicted with various chronic inflammatory conditions as well as schizophrenia (14–16). In summary, the IDO and GTP-CH1 pathways may represent a neuroendocrine link between the immune system abnormalities and neuropsychiatric symptoms of psychosis patients.

Meta-analyses have confirmed peripheral changes in the levels of cytokines, chemokines, lymphocytes, and oxidative stress markers of patients with schizophrenia during acute exacerbations (acute psychotic relapse or first psychotic episode), which normalize with antipsychotic treatment (summarized in De Picker et al.) (17). These "state" markers are differentiated from other "trait" markers that remain significantly altered throughout the disorder (18, 19). Thus, different patterns of immune system upregulation are present in the acute vs. posttreatment states of psychotic illness. We hypothesized similar state-dependent changes to exist in the immune-associated neuroendocrine pathways.

The aim of this study was to identify state and trait IDO and GTP-CH1 pathway markers together with immune system markers in a longitudinal sample of patients during acute psychotic exacerbation, and to evaluate the association of these markers with neuropsychiatric symptomatology.

### MATERIALS AND METHODS

### Participants

We recruited a transdiagnostic group of 49 inpatients fulfilling the Diagnostic and Statistical Manual of Mental Disorders (DSM−5) criteria for a diagnosis within the spectrum of primary psychotic illnesses (DSM-5 #295.1–295.6, 295.9, 298.9). Patients were newly admitted to one of three major psychiatric hospitals in the Antwerp region of Belgium (University Psychiatric Hospital Antwerp Campus Duffel, Multiversum Campus Alexianen, and Campus Amedeus) for first-episode psychosis or for acute relapse of psychosis, as defined by Positive and Negative Syndrome Scale (PANSS) interview scores (20), and were antipsychotics-naïve or–free for at least 4 weeks prior to hospital admission. Additionally, 52 healthy age-, gender-, and BMI-matched controls from the same area were enrolled. All controls were considered healthy based on clinical evaluation with vital signs and laboratory tests (including liver enzymes, hematology, HBV, HCV, and HIV serology, and urinalysis). Individuals with a personal medical history of (1) auto-immune disorders or any chronic or recent acute physical illnesses associated with abnormal immune changes or who used anti-inflammatory or immunomodulating drugs or systemic corticosteroids within the last 3 weeks; or (2) substance use disorders according to DSM-5 criteria (except nicotine or caffeine) within the last 3 months were excluded. Control subjects with a personal history of any psychiatric disorders or family

history (first degree relatives) of psychotic or bipolar disorders were also excluded.

Patients' symptom severity was measured using the Positive and Negative Syndrome Scale (PANSS). Psychotic exacerbations were defined by a total score of ≥14 on the positive scale of the PANSS and at least a score of 5 on one item or a score of 4 on two "psychotic" PANSS items P1, P3, P5, or G9 at Screening (20, 21). PANSS interviews were conducted with patients during the acute psychotic state and at follow-up (within 1 week of each blood sampling) by a trained interviewer. Together with the interviews, cognitive measures (Symbol-Digit Substitution Task Test and WAIS IV Letter-Number Sequencing Task) were obtained.

The study procedures were described in detail to all participants, who gave written informed consent. The local ethics committees of University Hospital Antwerp, Emmaüs, Brothers of Charity, and Spes et Fides approved the study.

### Blood Sampling

Non-fasting blood samples were obtained from all participants in a standardized manner at three different occasions in patients and two occasions in controls. Whenever possible, a first (Unmedicated Psychosis; UMP) sample was obtained from patients within 48 h of hospital admission (available for 37 of 49 patients), after which antipsychotic medication was initiated as determined by clinical needs. Subsequently, a sample was obtained during the first 2 weeks of hospitalization (Psychosis, in some patients this represented the first study sample; mean 10.2 ± 5.6 days after UMP sample) together with the first PANSS interview and cognitive tests. Finally, the last (Follow-up) sample was obtained after at least 8 weeks of treatment (mean 81.2 ± 25.9 days after Psychosis sample) together with the second PANSS interview and cognitive tests. In controls, two samples were drawn at the same time of day at least 6 weeks apart (mean 77.1 ± 43.2 days). Blood samples were collected from January 2014 to May 2016 without any dietary or fasting protocols and drawn via a forearm vein in EDTA and citrate containing tubes. See **Supplementary Figure 1** for timing of blood draws. Blood samples were transferred to the laboratory (<30 min) on cold packs and centrifuged for 10 min at 4◦C immediately after arrival. The resulting plasma was aliquoted into Eppendorf tubes which were frozen immediately at −80◦C and kept frozen until analysis.

### LCMS Quantitative Analysis of Trp, Kyn, QA, and KA by LC-MS/MS

IDO pathway analytes Trp, Kyn, QA, and KA were measured in citrate plasma samples using liquid chromatography–tandem mass spectrometry (LCMS) analysis at the Institute of Legal Medicine and Core Facility Metabolomics of the Medical University of Innsbruck, Austria as described elsewhere (22). Samples were shipped frozen to Innsbruck where they were stored at −20◦C until analysis. Samples were processed in batches of 20–30 samples. Additionally, two quality control samples were analyzed with each batch of patient samples added to each batch. These plasma samples were kindly donated by the blood bank of the Medical University of Innsbruck. They were stored at −20◦C prior to use. The order in which the samples were processed was pre-specified to make sure all samples belonging to the same participant were in the same batch, and each batch contained a similar number of patient and control samples (see also **Supplementary Material**).

### HPLC Quantitative Analysis of Phe, Tyr, Nitrite, and Neopterin

Free concentrations of phenylalanine (Phe), Tyr, nitrite, and neopterin were measured in EDTA plasma samples by high performance liquid chromatography (HPLC) analysis at the Center of Chemistry & Biomedicine of the Medical University of Innsbruck, Austria as described elsewhere (4, 13). For an estimate of NO production, the stable NO metabolite nitrite (NO2−) was determined in the cell-free culture supernatants by the Griess reaction assay (Promega, Madison, Wisconsin).

Plasma aliquots were shipped frozen to Innsbruck at two different timepoints (6 months interval) and were stored at −20◦C until analysis. They were processed in batches of 20–30 samples with a pre-specified order, as above.

### HPLC Quantitative Analysis of 3-HK

3-hydroxykynurenine (3-HK) was measured at the University of Antwerp Department of Pharmaceutical Sciences by HPLC with electrochemical detection as described elsewhere (23). Two hundred milliliters of citrate plasma sample was deproteinized with 40 ml of 0.23 M perchloric acid. To 120 ml of deproteinized sample was added a solution of 20 g/l sodium decane sulphonate and 1 g/l EDTA in acetonitrile:water (40:60) and injected into a HPLC system equipped with a Chromolith Performance 3.0 × 100 mm column with a Chromolith guard cartridge. Elution solvent was 2.0 g/l decane sulphonic acid, 100 mg EDTA, and 5.9 ml phosphoric acid in 1,250 ml of water and 130 ml ACN. pH is brought to 3.5 with trimethylamine. Flow was 1.7 ml/min. Detection was coulometrically using an ESA electrochemical detector at 350 mV. Recovery of 3-HK was more than 95%. Within-assay CV was 4.7%, between-assay CV was 14.7%. Specificity was checked by observing retention by changing solvent composition.

### Quantitative Immunoassays

Immune markers of interest were measured in duplicate in EDTA plasma by an electrochemiluminescence immunoassay technique developed by Mesoscale Discovery (Rockville, USA), according to the manufacturer's instructions. We used standardized kits V-PLEX Proinflammatory Panel 1 Human Kit (for detection of IFNγ, IL10, IL12p70, IL1B, IL6, IL8, and TNFα), V-PLEX Cytokine Panel 1 Human Kit (for IL17A), V-PLEX Chemokine Panel 1 Human Kit (for monocyte chemoattractant protein-1, MCP1/CCL2) and V-PLEX Vascular Injury Panel 2 Human Kit (for C-reactive protein, CRP). Additionally, IL-1RA was detected using a custom 4-Spot Prototype Human IL-1RA kit. Concentrations for each cytokine were calculated by fitting the sample signals on a 4-parametric logistic calibration curve. Assays were excluded if concentrations were below detection threshold in >50% of participants (as was the case for IFNγ, IL10, IL12p70, IL17A), as well as all data points with an intra-assay coefficient of variation >15% (cfr. **Table 2**).

### Statistical Analysis

To estimate the activity of PHA, the ratio of the substrate Phe vs. the concentrations of the enzyme product Tyr (Phe/Tyr) was calculated. A similar ratio was calculated for Kyn/Trp and KA/Kyn as indices of IDO and KAT, respectively.

All statistical analyses were performed in JMP version 13 and Review Manager 5.3. Non-normally distributed markers were log normalized prior to the use of parametric statistics (IL1RA, IL6, IL8, CCL2, TNFα, CRP, QA, QA/KA). We applied a reflected transformation to the distribution of neopterin because of negative skew. Outlier plasma concentrations of markers (>3 × z-score) were excluded from analysis.

Baseline differences in clinical and demographic parameters between cohorts were examined by two-tailed independent ttests for continuous variables and Pearson chi-square test for categorical variables. Pearson correlation analyses tested the association between different markers and symptom severity. All medium-to-high strength correlations (r > |0.3|) are reported. All data are presented as mean ± SD unless otherwise indicated.

A series of linear mixed model restricted maximum likelihood (REML) analyses were performed with the different immune and neuroendocrine markers as the dependent variables. To model trait differences in peripheral immune and neuroendocrine markers between the cohorts as well as differences related to the acute psychotic state vs. post-treatment state in patients, Subject was included as random effect and Cohort, State (i.e., the psychotic state, including both UMP, and Psychosis timepoints) nested in Cohort and Batch as fixed effects (marker = [SubjID] + Cohort + State[Cohort] + Batch). Because the graphical presentation of the identified markers (demonstrated in **Figure 2**) indicated distinct results for the samples taken at admission (during Unmedicated Psychosis; UMP), the above linear mixed model for each marker was repeated using UMP as State. Dependent variables which demonstrated significant effects for State [Cohort] in either of two mixed models were considered state markers, whereas variables for which Cohort was significant in both mixed model analyses were considered trait markers. Subsequently, the models were adjusted for sex, age, BMI, and smoking.

All significance levels are reported as two-sided P-values, corrected for multiple testing using the Benjamini-Hochberg implementation (24) of the False Discovery Rate

TABLE 1 | Demographics, PANSS interview, and cognitive test results at baseline and follow-up.

Data are expressed as mean values ± SD.

(FDR) correction. An FDR adjusted p-value of 0.05 was used as cutoff for significance (significant p-values are indicated by ∗ ).

SDST score (numbers correct) 44.0 ± 12.0 48.0 ± 11.7 t2.84, df37,

LNS adjusted score 5.0 ± 2.2 5.2 ± 2.4 t0.77, df37,

### RESULTS

### Demographics

We enrolled 52 controls and 49 patients, of whom seven dropped out of the study prior to the last timepoint. The first unmedicated UMP blood sample was available for 37 out of 49 patients. Demographic information and patients' PANSS scores are presented in **Table 1**. PANSS scores were not available for analysis in three patients. Patients' baseline PANSS total scores, positive subscale and general psychopathology subscale scores were significantly higher than at follow-up.

### Trait and State Markers of Psychosis

Increased concentrations of IL6, IL8, TNFα, CCL2, and decreased Nitrite were identified as markers of the unmedicated acute psychotic state [State(Cohort) for UMP: all F = 8.68– 42.36; p = ≤ 0.001–0.004), whereas increased IL1RA (F = 8.33; p = 0.005) and decreased 3-HK (F = 12.81; p = 0.001) and QA (F = 16.07; p < 0.001) were state markers of the whole acute psychotic episode, both before and after initiation of antipsychotic medication. We identified increased IL1RA, CRP, and CCL2 and decreased KA and KA/Kyn as trait markers (Cohort: all F = 5.96–17.39; p = ≤ 0.001–0.017) (see **Figure 2**). No significant differences were identified for Trp, Phe, Tyr, Phe/Tyr, and Neopterin. Results of the analyses are summarized in **Table 2** and **Supplementary Table 1**.

### Adjustment for Confounders

The above analyses were adjusted for the effects of sex, BMI, smoking, and age: (1) A significant interaction between cohort and sex existed in KA (F = 17.39; p < 0.001) and KA/Kyn (F = 13.64; p < 0.001), with male controls demonstrating higher KA and male patients demonstrating lower KA; (2) Nitrite levels were lower in men compared to women in both cohorts (F = 12.0, p < 0.001); (3) Higher BMI significantly increased concentrations of CRP, IL1RA, and QA in both cohorts; (4) The effect of smoking was not significant; (5) A significant interaction between cohort and age was found for IL1B (F = 7.96; p = 0.006) and Kyn/Trp (F = 8.94; p = 0.004) and a significant main effect of age for IL6 (F = 7.45; p = 0.008). Results are summarized in **Supplementary Table 1**.

### Relationship Between Immune and Neuroendocrine Markers

TNFα concentrations in patients but not controls correlated with Kyn (r = 0.310–0.509), Kyn/Trp (r = 0.361–0.451), QA (r = 0.432–0.481), and QA/KA (r = 0.349–0.518), but not with KA at each of the three timepoints. In contrast, in controls CRP and IL1RA concentrations correlated with IDO pathway metabolites. Results are summarized in **Supplementary Table 2**.

### Relationship With Clinical Symptoms and Patient Characteristics

PANSS positive scale scores during the acute psychotic state correlated with concentrations of IL1B (r = 0.463, p = 0.026), IL6 (r = 0.541, p = 0.008), and CRP (r = 0.507, p = 0.014) and correlated inversely with Neopterin (r = −0.427, p = 0.021), whereas PANSS negative scale scores correlated with Kyn (r = 0.458, p = 0.013), QA/KA (r = 0.379, p = 0.040) and inversely with KA/Kyn (r = −0.400, p = 0.032). Furthermore, the relative change in PANSS negative scale scores between the acute and post-treatment states [(acute–post-treatment)/acute] correlated inversely with the relative change in KA (r = −0.470, p = 0.024) as well as 3-HK (r = −0.465, p = 0.026).

Both groups improved between the first and second rounds of cognitive testing but patients performed significantly poorer compared to controls (SDST controls 70.0 ± 12.1, vs. patients 45.6 ± 12.1, within-pairs F = 0.76, p = 0.386, among-pairs F = 85.0, p < 0.001; LNS controls 9.96 ± 2.9 vs. patients 5.10 ± 2.3, within-pairs F = 5.6, p = 0.020, among-pairs F = 85.4, p < 0.001). The relative change in SDST performance over time in patients [(acute–post-treatment)/acute] correlated inversely with the relative change in KA (r = −0.489, p = 0.010) and KA/Kyn (r = −0.358, p = 0.067).

p = 0.008

p = 0.446

### DISCUSSION

### Trait and State Markers of Psychotic Illness

In the present study, we tested the hypothesis that state or trait increases in levels of pro-inflammatory cytokines may be accompanied by state-specific IDO and GTP-CH1 pathway abnormalities in schizophrenia spectrum disorders. We defined five immune (IL1RA, IL6, IL8, TNF, CCL2) and three neuroendocrine (QA, 3-HK, Nitrite) state markers of acute exacerbations which normalized after treatment with antipsychotics. Five trait markers (IL1RA, CRP, CCL2, KA, KA/Kyn) differentiated between patients and controls at any of the timepoints. IL1RA and CCL2 were both state and trait markers, distinguishing patients from controls as well as patients during a psychotic episode from those at post-treatment followup. Kyn/Trp was a trait marker only in participants older than 30 years of age.

Our findings confirm the association of schizophrenia and the acute psychotic state with increased peripheral (proinflammatory) immune markers, as described earlier by Miller et al. in two meta-analyses of blood cytokine and CRP levels. Miller et al. identified IL1B, IL6, and TGFβ as state markers for acute exacerbations, while IL12, IFNγ, TNFα, sIL2R, and CRP were trait markers. IFNγ and IL12p70 were measured in our study but did not meet quality control criteria required for further analysis. CCL2 was also identified as a trait marker (defined here as elevated in both first- and multiple-episode schizophrenia patients irrespective of treatment) in another recent meta-analysis (25).

However, although our patients exhibited state and trait immune activation, the GTP-CH1 pathway did not differentiate patients from controls (except for nitrite) and the IDO pathway appeared overall downregulated in patients vs. controls. Although this finding contradicts our original hypothesis of immune-activated IDO upregulation, it is in line with results from two recent amino-acid profiling studies (one cross-sectional study in 208 first episode psychosis patients and one 7 month follow-up study in 38 schizophrenia patients) in which tryptophan and kynurenine were decreased in participants with schizophrenia vs. controls (26, 27).

Furthermore, subgroup analyses of a recent meta-analysis by Plitman et al. of 13 studies in schizophrenia demonstrated that KA levels were increased centrally (cerebrospinal fluid and brain tissue, n = 7 studies) but not peripherally (n = 5 studies) (28). However, two studies of peripheral IDO pathway metabolites which have emerged since then suggest a relative decrease in KA even in the presence of a pro-inflammatory state (29, 30). We therefore repeated this meta-analysis using the same methods, while adding the data of the two newer studies plus our own findings. Significant study heterogeneity existed in the main analysis (I² = 90%), with the funnel plot indicating the smallest and oldest study (31) acted as an outlier, influencing the overall result. When this study was excluded, the meta-analysis of the remaining seven studies indicated KA levels were mildly but significantly decreased in the blood of patients with schizophrenia compared to controls (standardized mean difference −0.35, p = 0.020) (cfr. **Figure 3**).

Our study has specifically looked at state-specific changes of neuroendocrine markers. Only a few other studies have longitudinally investigated IDO pathway metabolite concentrations in both arms downstream from kynurenine in psychosis patients. Myint et al. (32) studied 53 medication-free patients with schizophrenia admitted to hospital with psychotic symptoms and treated with antipsychotic medication over 6 weeks. They also identified decreased KA and KA/Kyn as trait markers, but found increased 3-HK at admission, which normalized after 6 weeks of treatment (32). Fazio et al. (33) found decreased QA and 3-HK in first- and multiple-episode schizophrenia patients, the latter of which increased significantly in first-episode patients after 1 year of treatment. KA levels were found to be increased in their study, however this result may have been confounded by a gender imbalance in this study (69% male in patients vs. 44% in controls), considering KA levels are lower in females than males (33, 34). Szymona et al. (30) analyzed blood levels of KA and 3-HK in 51 chronic schizophrenia patients during acute relapse, after 4 weeks of therapy and at remission. KA levels were significantly lower in comparison with controls throughout the study, whereas 3-HK did not differ from controls at admission and during therapy but increased at remission and correlated negatively with the improvement of negative symptoms (SANS scores) at discharge–matching our findings for PANSS negative scale scores. Finally, Wurfel et al. demonstrated reductions in serum KA and KA/QA in acutely ill inpatients with affective psychosis.

### Age and Sex Effects

The term "inflammaging" (35) has been coined to indicate significant relationships between aging and circulating concentrations of immune markers such as IL-6 and neopterin, as well as increased tryptophan breakdown in the presence of immune activation in the elderly (36). Moreover, we have recently demonstrated important age effects on microglial activity during psychosis in a subpopulation of our current sample, in whom TSPO radioligand uptake was measured using Positron Emission Tomography (37, 38).

In the current study, we observed that state and trait increases in IL1RA and IL6 became more pronounced in older patients, while state-dependent changes of QA and 3-HK were more pronounced in younger patients. Not unimportantly given the sexual dimorphism in age of onset and progression of schizophrenia, a significant interaction between cohort and sex existed in KA.

### Limitations

There are some noteworthy limitations to the present study. Firstly, the number of samples obtained was not the same in all patients. Our aim was to obtain blood samples at the earliest possible time during the acute psychotic episode. Therefore, some patients were enrolled in the study within 48 h of being admitted to hospital and before the initiation of antipsychotic medication (UMP timepoint), whereas others only entered the study at a later timepoint (Psychosis, timepoint) within the first 2 weeks of hospitalization. We therefore preferred methods of analyses which are less affected by missing or unbalanced data, such as

FIGURE 3 | Funnel and forest plots of studies on peripheral KA levels. Funnel plot depicts standardized mean differences (SMDs) of studies on peripheral KA levels. Forest plot excludes Ravikumar et al. from analysis.

TABLE 2 | Concentrations of different immune markers at the different timepoints.

Data are expressed as mean values ± SD. Phe and Tyr are not represented due to significant batch effects.

linear mixed models. Secondly, our naturalistic study design does not allow us to differentiate to which extent changes between the different illness states can be accounted for by effects of treatment with antipsychotic medication, non-specific aspects of being hospitalized or natural illness course. Furthermore, although there is a significant reduction between baseline and follow-up PANSS total and positive subscale scores, our followup period of 8 weeks may still have been too short for the immune markers to normalize. A longitudinal study with longer follow-up period would be needed to monitor the evolution of state makers and to verify if the trait markers indeed remain altered in patients irrespective of their clinical course (39).

All patients in our study were started on a regimen of antipsychotic treatment during the follow-up period. Unfortunately, our data did not allow us to compare neuroimmune markers against the type and dose of antipsychotic treatment. Antipsychotics in general have been suggested to increase nitric oxide plasma levels, which would explain the sharp increase in nitrite levels in patients after antipsychotics were initiated (40). Thirdly, our findings concern peripheral measures which cannot be generalized to the central nervous system and are susceptible to confounding by factors which affect peripheral bioavailability. We repeated our analysis controlled for albumin concentration which did not alter our findings. All samples were taken in non-fasting conditions, except UMP which were usually drawn together with routine clinical sampling in early morning fasting conditions—as plasma kynurenine is typically lower in non-fasting conditions, it is unlikely this would explain our findings (41). Our IDO pathway results were very consistent despite having been generated in two different labs (University of Antwerp and University of Innsbruck) and with two different methods (LC-MS/MS vs. HPLC). In contrast, the GTP-CH1 pathway results were subject to considerable batch effects which could have nullified any biological differences in Phe, Tyr, and Neopterin.

The importance of IDO pathway metabolites is usually linked to their actions in the central nervous system. TRP, KYN, and 3-HK readily cross the blood-brain barrier while KA and QA cannot (42). Human brain kynurenines are not autonomous but are linked to, and influenced by, the peripheral IDO pathway (5). Sixty to eighty percentage of cerebral KYN the predominant source of downstream cerebral IDO pathway metabolites—is contributed from the periphery, where the highly regulated IDO pathway accounts for ∼80% of nonprotein-bound Trp metabolism (43, 44). During inflammation and enhanced tryptophan breakdown, increased amounts of peripheral KYN are transported across the blood-brain barrier and become available for further downstream metabolization in astrocytes and microglia of the central nervous system. Finally, while our work has focused on IDO-initiated kynurenine metabolism, it is worth pointing out the existence of an alternative—albeit less well-studied—route catalyzed by TDO2. While TDO2 expression in mammals is mostly restricted to the liver, one study has demonstrated a 1.6-fold increase in TDO2 mRNA as well as increased density of TDO2-immunopositive astrocytes in postmortem tissue of patients with schizophrenia (45). Clearly further work is needed to elucidate the differential pathophysiological roles of IDO- vs. TDO2-mediated kynurenine metabolism in pro-inflammatory states.

### Clinical Relevance and Recommendations for Future Research

After adjustment for potential confounders and multiple testing we find that immune and neuroendocrine profiles of patients differ throughout the course of a psychotic episode. Future studies evaluating these compounds in both exploratory or interventional designs should therefore carefully select or differentiate between patients in different illness stages.

While positive symptom scores during the acute episode correlated mostly with markers of the pro-inflammatory state, IDO pathway markers were associated with negative symptom scores. Normalization of KA and 3-HK levels between admission and follow-up corresponded to a larger improvement of negative symptoms. A reverse association was found between relative improvement of SDST scores and decreased KA levels, which could represent the first evidence in humans of the preclinical findings that sudden increases in brain kynurenic acid impair cognitive flexibility (8). More comprehensive research in larger samples would be needed to further explore this relationship.

Clearly, the most unexpected finding of this study is the global downregulation of both arms of the IDO pathway in psychosis. The IDO or kynurenine pathway has been of interest to schizophrenia research because of its strong relation to the immune system as well as the fact that KA tightly controls glutamatergic and dopaminergic neurotransmission and influences behavior in animals (46). In humans, exogenous glutamate receptor antagonists induce schizophrenia-like phenomena in healthy controls.

Based on our findings, which are echoed by recently published evidence on decreased peripheral KA concentrations, a critical re-evaluation of the kynurenic acid hypothesis is needed. Alternative hypotheses to identify the origins of the IDO pathway abnormalities in schizophrenia, their relation to treatment responses and in particular the striking discrepancies between central and peripheral findings should be considered (29). Similar to a mechanism proposed in glioblastoma patients, in whom plasma concentrations of Trp, Kyn, KA, and QA were found to be decreased compared with healthy controls in the context of CNS IDO1 upregulation (47), decreased peripheral KA could be indicative of an increased demand for and transfer of Trp or Kyn through the blood–brain barrier to serve as substrate for local synthesis of KA in brain tissue. This corresponds to increased KA concentrations in the CSF of patients with schizophrenia (48). This hypothesis however does not explain why KA remains decreased throughout the illness course as trait marker while, especially in younger patients, 3- HK and QA concentrations increase post-treatment. Nor does it clarify why we found Kyn, 3-HK, and QA concentrations to correlate with TNFα concentrations in patients while KA levels did not.

Despite several decades of increased attention for kynurenines in the field of mental health research, many basic issues about their pathophysiology remain unsettled as recently extensively reviewed by Schwarcz and Stone (42). The effect of persistent up- or downregulation of kynurenine pathway metabolism in the periphery on the dynamics of blood-brain barrier transport have not yet been studied. Future work is needed to clarify the functional dynamics of IDO pathway metabolism in the CNS as well as the implications of peripheral kynurenine changes. Ideally future studies in psychosis patients should look at both kynurenine pathway arms, comparing both CSF and plasma and longitudinally following patients throughout the course of their illness.

### CONCLUSION

To our knowledge, this is the first study to comprehensively and longitudinally evaluate state and trait changes of IDO and GTP-CH1 pathway metabolites in parallel to immune markers in psychosis patients. Our study confirmed that the acutely psychotic (and unmedicated) state is marked by specific state increases of immune markers (IL6, IL8, TNFα, CCL2, IL1RA) and decreased Nitrite. We also demonstrated these increases in peripheral pro-inflammatory immune markers are accompanied by state-specific decreases in peripheral 3-HK and QA. Trait markers which differentiate psychosis patients from healthy controls throughout the illness course were increased CRP, CCL2, and IL1RA, and decreased KA and KA/Kyn. While PANSS positive scale scores during the acute episode correlated with pro-inflammatory immune markers, IDO pathway markers were associated with negative scale scores and normalization of KA and 3-HK levels between admission and follow-up corresponded to a larger improvement of negative symptoms. A reverse association was found between relative improvement of SDST scores and decreasing KA levels.

### DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

### ETHICS STATEMENT

The studies involving human participants were reviewed and approved by University Hospital Antwerp, Wilrijkstraat, Edegem, Belgium (main EC); supplemental approval from local

### REFERENCES

Belgian ECs Emmaüs, Brothers of Charity, Spes et Fides. The patients/participants provided their written informed consent to participate in this study.

### AUTHOR CONTRIBUTIONS

LDP, PB, MT, BS, and MM devised the project, the main conceptual ideas, and proof outline. LDP, RV, VC, DF, and HO carried out the experiments. EF verified the statistical analysis methods. LDP wrote the manuscript with support from MM, VC, and BS. All authors discussed the results and contributed to the final manuscript.

### FUNDING

This study was in part funded by research grants from the Flanders' Agency for Innovation by Science and Technology (IWT-SB 121373) and Janssen Research and Development, a division of Janssen Pharmaceutica N.V. Neither funding body was responsible for the design, collection and analysis of data or the decision to publish.

### ACKNOWLEDGMENTS

The authors are thankful to J. Schuermans, D. Ooms, and G. Koppen for support with the MSD multiplex procedures. The authors are equally thankful to I. Vanderplas, S. Apers, L. Claes, and S. Debruyne for their support with all patientrelated procedures. Finally, we would like to express our gratitude to all the participants of this study.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.02971/full#supplementary-material

long-term potentiation in adulthood. Front Behav Neurosci. (2014) 8:451. doi: 10.3389/fnbeh.2014.00451

**Conflict of Interest:** MT and PB are employees of Janssen Pharmaceutica N.V. and the findings of this research may affect future research lines within the company.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 De Picker, Fransen, Coppens, Timmers, de Boer, Oberacher, Fuchs, Verkerk, Sabbe and Morrens. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Tryptophan Co-Metabolism at the Host-Pathogen Interface

Claudio Costantini 1 , Marina M. Bellet 1 , Giorgia Renga1 , Claudia Stincardini 1 , Monica Borghi 1 , Marilena Pariano1 , Barbara Cellini 1 , Nancy Keller 2 , Luigina Romani 1 and Teresa Zelante1 \*

1 Department of Experimental Medicine, University of Perugia, Perugia, Italy, 2 Department of Medical Microbiology and Immunology, Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, United States

Keywords: tryptophan, co-metabolism, xenobiotic receptor, microbiota, kynurenine, 3-IAld

### HOST-MICROBE TRYPTOPHAN CO-METABOLISM

Microbes have evolved to exploit humans as a rich source of nutrients to support survival and replication. Although mammals and microbes may differ in their requirement for tryptophan (Trp), being an essential amino acid in the former and produced, with some exceptions, by bacteria and fungi, common catabolic enzymes are shared by both host and pathogens. Indoleamine 2,3-dioxygenases (IDOs) catabolize Trp to kynurenines and are widely distributed from bacteria to metazoans. The evolutionary conservation of the kynurenine pathway may be linked to the importance of the de novo synthesis of nicotinamide adenine dinucleotide (NAD+), to which it ultimately leads, although additional functions of kynurenines are increasingly being recognized. Indeed, it is now clearly established that mammalian IDOs regulate infection and drive immune tolerance by means of Trp deprivation and the generation of active metabolites, including kynurenines. An additional level of complexity can be envisaged when microbes utilize Trp via alternative pathways upon colonization of the host in a relationship that can be either commensalism or pathogenic. In these situations, the host and microbes are found to share common substrates but the presence of dissimilar metabolic pathways may result in the generation of metabolites, such as indoles or tryptamine that can cross-regulate each others metabolism. Here, we discuss the potential relevance of Co-Trp metabolism or alternative secondary pathways of Trp degradation in modulating host immune response and eventually the xenobiotic receptors (XRs), while regulating microbe fitness. These concepts are expected to open a novel scenario in which a comprehensive assessment of the metabolic status is crucial to correctly evaluate pathological colonization and drive the most appropriate therapeutic strategy.

### CO-METABOLISM DICTATES PATHOGEN VIRULENCE

Trp is one of the 20 amino acids used for building proteins with the unique characteristic of bearing an indole, a bicyclic ring formed by a benzene and a pyrrole group, linked to the α-carbon by a –CH2-group (1). The presence of the indole group not only dictates the biochemical properties of Trp, a highly hydrophobic amino acid that guarantees the stabilization of protein and peptide structures, but also makes Trp a reservoir of indole-based bioactive molecules with fundamental implications in organism physiopathology (1, 2). The relevance of Trp and its catabolic pathways acquires a novel dimension when they are envisioned in the context of a relationship between host and microbes. Indeed, the different entities involved in the relationship share the same Trp substrate, which is fundamental for all the parties at play, but is catabolized along peculiar patterns. Therefore, multiple levels of interactions can be foreseen, starting from the competition of the Trp substrate to the generation of bioactive molecules via shared or exclusive catabolic pathways with cross-regulatory properties, and each will be discussed upon in the following sections.

### Edited by:

Juliane Günther, Leibniz Institute for Farm Animal Biology, Germany

#### Reviewed by:

Walter Däubener, Universitätsklinikum Düsseldorf, Germany

\*Correspondence: Teresa Zelante<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Inflammation, a section of the journal Frontiers in Immunology

Received: 16 October 2019 Accepted: 10 January 2020 Published: 29 January 2020

#### Citation:

Costantini C, Bellet MM, Renga G, Stincardini C, Borghi M, Pariano M, Cellini B, Keller N, Romani L and Zelante T (2020) Tryptophan Co-Metabolism at the Host-Pathogen Interface. Front. Immunol. 11:67. doi: 10.3389/fimmu.2020.00067

**84**

First, the requirement for Trp differs between the organisms. Indeed, while Trp is an essential amino acid in mammals, microorganisms, and higher plants possess the ability to synthesize Trp from chorismate, a common precursor of aromatic amino acids produced by the shikimate pathway from phosphoenol pyruvate and erythrose-4-phosphate (3). This dependence of mammals from external sources of Trp creates a first level of interaction in the host/microbe interface. Indeed, mammals might obtain Trp not only from the diet, but also from commensal microorganisms that possess the shikimate pathway and may represent a source of Trp. On the contrary, pathogens may co-opt host mechanisms of Trp degradation as a strategy to evade the host immune response (4). For instance, in a murine model, the gut pathogen Clostridium difficile induced IDO1 expression to deplete the Trp pool and increase kynurenine production in the cecal tissue by IDO1-expressing CD11c+ myeloid cells, among other stromal cells. As a consequence, neutrophil accumulation and pathogen clearance were limited (4, 5). Other pathogens however, depend on the host for Trp availability, including common intracellular pathogens, and it is the host that depletes the Trp pool to limit the virulence of the pathogens (4, 6). For instance, the parasite Toxoplasma gondii is Trp-auxotroph and IDO activity suppresses its growth, as first demonstrated by Pfefferkorn and co-workers in cultured human fibroblasts treated with IFNγ (7). Thus, Trp itself appears as a double-edged sword in the host-microbe interaction: on the one hand, it may ensure a positive symbioses between the host and Trp synthesizing microbes; on the other hand, it may be used as a weapon to deprive the host or, vice versa, Trpauxotroph pathogens of Trp, resulting in increased or reduced virulence, respectively.

Second, Trp may be catabolized via shared catabolic pathways. In mammals, Trp is metabolized along four different pathways leading to the formation of (i) serotonin and melatonin, (ii) tryptamine, (iii) indolepyruvic acid, and (iv) kynurenine (8). The kynurenine pathway accounts for nearly 95% of all Trp degradation (8), and the rate-limiting step is catalyzed by one of three enzymes, namely indoleamine 2,3-dioxygenase 1 (IDO1), IDO2, and tryptophan 2,3-dioxygenase (TDO), with distinct localization, affinity, and regulation (8). The evolution of IDOs and TDO has been the subject of intense research. TDO is widely present in metazoan and many bacterial species, but not in fungi, and is characterized by a high efficiency for Trp degradation throughout the evolution (9). On the contrary, IDO is found in mammals, lower vertebrates, invertebrates, fungi, and bacterial species, but only mammalian IDO1 and fungal IDOs show high efficiency for Trp degradation (9). Irrespective of the ancestral role of IDOs and TDO and their evolution, it is evident that microorganisms are endowed with the ability to catabolize Trp along the kynurenine pathway, as partially demonstrated by experiments in germ-free mice that show a decrease in the kynurenine pathway (10). In this scenario, two opposite outcomes are possible. Indeed, not only the distinct dioxygenases might compete for the same substrate to produce kynurenine for self-advantage, but they can also compensate each other in physiological or pathological conditions characterized by kynurenine deficiency, again identifying Trp and its catabolism as a double-edged sword in host-microbe interaction. Unfortunately, studies on the kynurenine pathway in microbes and how it intersects with host metabolism are still very scarce, and it is not possible to draw any conclusions in support of one or the other possibility.

As a third level of interaction, Trp may be catalyzed via distinct catabolic pathways by the host and microbes, resulting in the generation of metabolites that can cross-regulate each other metabolism. In recent years, we have identified and characterized the "postbiotic" molecule indole-3-aldehyde (3- IAld) derived from the microbial degradation of Trp and produced by probiotics such as lactobacilli (11). 3-IAld proved critical in the maintenance and restoration of intestinal epithelial integrity. Indeed, by binding the aryl hydrocarbon receptor (AhR) and activating the expression of IL-22, 3-IAld promotes the repair of the intestinal epithelial lining and the reduction of inflammatory markers (11). Another interesting example is represented by indole, produced by bacteria and some plants from Trp via the enzymes tryptophanase and indole-3-glycerol phosphate lyases, respectively (12). Interestingly, indole negatively regulates the virulence of various pathogens, such as the gastrointestinal tract pathogens enterohemorrhagic Escherichia coli (EHEC) (13, 14) and Citrobacter rodentium (14). For instance, mice infected with C. rodentium and manipulated to contain different concentrations of indole in the gastrointestinal tract showed an inverse correlation between colonization/mortality and amounts of indole (14). In addition, indole can enhance the competitiveness of commensal microorganisms, for instance by promoting the growth of E. coli in mixed-cultures with Pseudomonas aeruginosa via inhibition of quorum sensing (15). However, microorganisms may also adopt specialized ways to use Trp and catabolic intermediates as pathogenic molecules. For instance, A. fumigatus can incorporate Trp and/or anthranilate via non-ribosomal peptide synthetases to generate toxic molecules (16), such as the Trp-derived iron (III) complex hexadehydroastechrome that increased the virulence of A. fumigatus and the mortality in a neutropenic murine pulmonary model upon overexpression (17).

Overall, these examples illustrate how Trp and catabolic molecules play a fundamental role in regulating the interaction between the host and the microbes, which can occur at multiple levels and with opposite outcomes. Indeed, Trp and its metabolites may serve to establish a symbiotic relationship or otherwise be used to weaken the partner by depleting essential molecules or creating toxic substances.

### TRYPTOPHAN DEGRADATION BY MICROBES: TOXICITY VS. IMMUNOMODULATION

### Indole: The Interkingdom Molecule

The enzyme tryptophanase (TnA) is responsible of Trp degradation and release of indole and indole-derivatives. Importantly, TnA is widely expressed in Gram-negative as well as in Gram-positive bacteria (14, 18). The indole ring is found in humans as the nucleus of human hormones as serotonin or melatonin, but is also found in plants in auxins, which may affect plant orientation by promoting cell division to one side of the plant in response to sunlight and gravity. Indole is also synthesized in the bowel by microbes, regulating the biofilm as quorum sensing molecule or the intestinal physiology. Thus, the indole ring being diffused in different ecosystems, is considered a type of "archetypical hormone" able to regulate the relation between the host and microbes in plants but also in the animal kingdom. The mechanisms of action in the host by indole and indole derivatives are not well-characterized yet, although a very large part of research has focused the mechanistic function on their capacity to bid the XRs (11, 19, 20). Interestingly, animals can't synthesize indole, while many bacteria and also fungi produce indole and indole-derivatives with some pathogens such as A. fumigatus synthesizing toxic indole alkaloids (21). In addition, indole and indole-derivatives are detected in the human blood as well as in peripheral tissues in physiological conditions. Frequently, indoles can be measured in urine but traces are also present in lymph nodes (22–24). A good example of co-metabolism with the host among the indole-derivatives is the indoxyl sulfate, typically representing a uremic toxin, derived from indole in the liver via the actions of cytochrome P450 enzymes (25).

### The Indole Pyruvate (IPyA) Route: A Direct Effect on Immunity

The indole-3-pyruvic acid (IPyA) route is key to converting aromatic amino acids to aroma compounds via transamination of Trp (26). IPyA secondary metabolites are indol-3 acetaldehyde (3-IAAld), indole-3-acetic-acid (IAA), and indole-3-carboxaldehyde (3-IAld)—all known as being AhR ligands (11) (**Figure 1**). AhR is part of the XRs family. XRs have evolved as cellular sensors for ligands (endogenous and exogenous) able to transcribe for genes encoding for drug-metabolizing enzymes.

XRs are also extremely involved in regulating general physiology since they can also transcribe for genes involved in immune regulation, cell metabolism, energy homeostasis (**Figure 1**). Families of XRs may bind a very large family of unrelated ligands by direct or indirect binding (27, 28). XRs may include the pregnane X receptor (PXR), the AhR, the constitutive androstane receptor (CAR), and the peroxisome proliferator-activated receptors (PPARs) (**Figure 1**). More recently, XRs family has been deeply investigated for their ability to directly communicate with the gut microbiota (11, 29, 30).

XRs respond to different metabolites produced by the host as well as by the microbiota. Thus, metabolism and co-metabolism are strictly related to XR activation pathway (30). Therefore, the acute or chronic symptoms of dysbacteriosis generally reflect the XR role in regulating the host physiology as energy metabolism, glucose homeostasis, immune-regulation.

Indeed, it was demonstrated that certain bacterial tryptophan-derived metabolites activate PXR particularly expressed in intestinal epithelial cells. The downstream signaling of intestinal PXR affects murine intestinal permeability, gut inflammation, and in peripheral tissue bile acid metabolism and drug resistance. Thus, in case of dysbiosis, where there is a severe lack of PXR ligands homeostasis is seriously compromised. Restoration of PXR signaling by using gnotobiotic mice or by administering PXR ligands, may result in abolishing pro-inflammatory signs and loss of barrier dysfunction in the context of intestinal inflammation (31).

In addition, we have demonstrated in mice that the indole-derivative 3-IAld is an AhR ligand that promotes IL-22 production. 3-IAld restored antifungal resistance and increased IL-22 production, ameliorated colitis via gut NKp46+ cells and via the XR AhR. These results suggest that the activity of 3-IAld could be exploited to

guarantee homeostasis and microbial cooperation at mucosal surfaces in conditions of immune dysregulation (11, 32). More recently, 3-IAld has been proved also changing together with a tryptophan-rich diet, the program of intraepithelial CD4+ T cells into immunoregulatory T cells in mice (20).

### Kynurenines: Immunomodulatory Functions

As in mammalians, Trp may also be degraded in to kynurenines by microbes. For example, Pseudomonas aeruginosa, a Gramnegative bacteria frequently involved in healthcare-associated pneumonia, catabolizes tryptophan through the kynurenine pathway. Thus, bacterial metabolites may interfere with the host's immune response during in vivo infection and acute lung injury (33). Another important evidence of co-metabolism, was demonstrated for the opportunistic fungus Candida albicans (34). Trp metabolites produced by the fungus Candida, in particular 5-hydroxytryptophan metabolites, are also able to modulate Th17 response, similarly to kynurenines as shown for mammalians (34). The opportunistic fungal pathogen A. fumigatus also has three ido genes (idoA,B,C) in its genome (35– 37). Enzymatic studies suggest that Idos of A. oryzae, participate in Trp degradation (38). Furthermore, previous studies on A. fumigatus grown on Trp showed upregulation of these ido genes (36). However, the relative contributions of individual Idos and adaptation to the host's environment, as well as the impact of kynurenines released by the fungus during lung infection in vivo, remain unclear.

### REFERENCES

### CONCLUSIONS

The scientific proof for a contribution of the XRs in the control of barrier function and immune regulation would serve as a basis toward improvement of non-toxic probes and ligands as drugs (30). This is also put forward by the fact that several of those microbial metabolites are found in human blood at levels comparable to host metabolites (3-IAld 0.01–0.1µM; IAA 0.1–1µM), suggesting that systemic responses may be easily activated by targeted XR-based therapy. These systems are thought to provide an additional level of interchange between the microbes and the host at the edge of their co-metabolism (**Figure 1**).

### AUTHOR CONTRIBUTIONS

CC and TZ wrote the manuscript. MMB, GR, CS, MB, MP, BC, NK, and LR edited the manuscript and provided valuable discussions and criticisms.

### FUNDING

This work was supported by the Specific Targeted Research Project FunMeta (ERC-2011-AdG-293714).

### ACKNOWLEDGMENTS

The authors wish to thank C. Massi Benedetti for digital art and image editing.

pathogenic fungus Aspergillus fumigatus. J Am Chem Soc. (2013) 135:2064–7. doi: 10.1021/ja311145n

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Costantini, Bellet, Renga, Stincardini, Borghi, Pariano, Cellini, Keller, Romani and Zelante. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Activation of the Kynurenine Pathway in Human Malignancies Can Be Suppressed by the Cyclin-Dependent Kinase Inhibitor Dinaciclib

Christin Riess 1,2,3, Björn Schneider 4 , Hanna Kehnscherper 3 , Julia Gesche3 , Nina Irmscher 3 , Fatemeh Shokraie1 , Carl Friedrich Classen1 , Elisa Wirthgen1 , Grazyna Domanska5 , Annette Zimpfer 4 , Daniel Strüder 6 , Christian Junghanss 3 and Claudia Maletzki 3 \*

1 University Children's Hospital, Rostock University Medical Centre, Rostock, Germany, 2 Institute for Medical Microbiology, Virology, and Hygiene, Rostock University Medical Centre, Rostock, Germany, 3 Medical Clinic III - Hematology, Oncology, Palliative Care, Department of Internal Medicine, Rostock University Medical Center, Rostock, Germany, 4 Institute of Pathology, Rostock University Medical Center, University of Rostock, Rostock, Germany, 5 Institute of Immunology and Transfusion Medicine, University of Greifswald, Greifswald, Germany, 6 Department of Otorhinolaryngology, Head and Neck Surgery "Otto Koerner", Rostock University Medical Center, Rostock, Germany

#### Edited by:

Ignacio Melero, University of Navarra, Spain

#### Reviewed by:

Benjamin Heng, Macquarie University, Australia Michael Platten, German Cancer Research Center (DKFZ), Germany

\*Correspondence:

Claudia Maletzki<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

> Received: 16 September 2019 Accepted: 09 January 2020 Published: 14 February 2020

#### Citation:

Riess C, Schneider B, Kehnscherper H, Gesche J, Irmscher N, Shokraie F, Classen CF, Wirthgen E, Domanska G, Zimpfer A, Strüder D, Junghanss C and Maletzki C (2020) Activation of the Kynurenine Pathway in Human Malignancies Can Be Suppressed by the Cyclin-Dependent Kinase Inhibitor Dinaciclib. Front. Immunol. 11:55. doi: 10.3389/fimmu.2020.00055 Indoleamine 2,3-dioxygenase (IDO) and tryptophan 2,3-dioxygenase (TDO2) are the key enzymes of tryptophan (TRP) metabolism in the kynurenine pathway (KP). Both enzymes function as indicators of immunosuppression and poor survival in cancer patients. Direct or indirect targeting of either of these substances seems thus reasonable to improve therapy options for patients. In this study, glioblastoma multiforme (GBM) as well as head and neck squamous cell carcinomas (HNSCC) were examined because of their different mechanisms of spontaneous and treatment-induced immune escape. Effects on gene expression and protein levels were examined. Accompanying assessment of TRP metabolites from treated GBM cell culture supernatants was conducted. Our results show a heterogeneous and inversely correlated expression profile of TRP-metabolizing genes among GBM and HNSCC cells, with low, but inducible IDO1 expression upon IFNγ treatment. TDO2 expression was higher in GBM cells, while genes encoding kynurenine aminotransferases were mainly confined to HNSCC cells. These data indicate that the KP is active in both entities, with however different enzymes involved in TRP catabolism. Upon treatment with Temozolomide, the standard of care for GBM patients, IDO1 was upregulated. Comparable, although less pronounced effects were seen in HNSCC upon Cetuximab and conventional drugs (i.e., 5-fluorouracil, Gemcitabine). Here, IDO1 and additional genes of the KP (KYAT1, KYAT2, and KMO) were induced. Vice versa, the novel yet experimental cyclin-dependent kinase inhibitor Dinaciclib suppressed KP in both entities. Our comprehensive data imply inhibition of the TRP catabolism by Dinaciclib, while conventional chemotherapeutics tend to activate this pathway. These data point to limitations of conventional therapy and highlight the potential of targeted therapies to interfere with the cells' metabolism more than anticipated.

Keywords: targeted therapy, solid tumor models, tryptophan metabolites, IDO1, chemotherapy

**89**

## INTRODUCTION

Tumor cells release immunosuppressive factors that shape a tolerogenic environment and enable progression and invasion. Indoleamine 2,3-dioxygenase (IDO1) is an intracellular monomeric, immune-checkpoint molecule that degrades the essential amino acid l-tryptophan along the kynurenine pathway (KP) (1, 2). Like other immune checkpoints, including programmed cell death protein 1 and cytotoxic T-lymphocyteassociated protein 4, IDO suppresses the hosts' antitumor immunity by inducing apoptosis in T- and natural killer cells (3). As a direct consequence of this, many cancer and cancerassociated cells express IDO1 (mesenchymal stromal cells, myeloid-derived suppressor cells, dendritic cells, endothelial cells, tumor-associated macrophages, and fibroblasts) (3–6). IDO1 is influenced by interferon-γ (IFNγ) (7–9), nitric oxide (10), pro- [interleukin (IL)-1β, tumor necrosis factor α] and anti-inflammatory (IL4, IL10, transforming growth factor β) cytokines. IDO1 activity inhibits T-cell activation and proliferation and even mediates regulatory T-cell recruitment to the tumor microenvironment, provoking local immune tolerance. In head and neck squamous cell carcinomas (HNSCCs), IDO1 inversely correlates with programmed cell death protein ligand 1, which constitutes an important prognostic biomarker for immune-checkpoint inhibition (11). The increased IDO1 activation decreases intratumoral TRP levels, resulting in tumor starvation and increase in kynurenine (KYN) metabolites (which are toxic to lymphocytes) (12). This immune exhaustion may be further boosted by conventional chemotherapeutics, leading to decreased efficacy. Therefore, IDO1 overexpression in the tumor microenvironment intimately impairs patients' outcome and may serve as a future prognostic predictor and drug target (13–18).

In the KP, most studies focused on IDO1 because this molecule is amenable to pharmacological intervention (19–22), and a couple of specific and global IDO inhibitors [including natural compounds (17, 23, 24)] already entered clinical trials, mostly reporting safe application and efficacy (stable disease at best outcome) (25). Current trials are evaluating the efficacy of IDO1 inhibitors in combination with chemotherapy, radiotherapy, and other immunotherapies including cytotoxic T-lymphocyteassociated protein 4 blockade (11, 22). The latter is based on the observation of an enhanced lytic ability of tumor-antigenspecific T cells upon IDO1 inhibition and decreased numbers of local immunosuppressive cells such as regulatory T cells and myeloid-derived suppressor cells (20, 26). The efficacy and toxicity data from recent clinical trials with IDO1 inhibitors is reviewed in Yentz and Smith (27). In most cases, however, overall survival was not significantly improved, leaving the future role for this combination therapy in question (28). More key enzymes are involved in TRP metabolism: tryptophan 2.3-dioxygenase (TDO2), a member of the oxidoreductases family, catalyzes the same initial step of the KP as IDO1 (2). Thus, TDO2 has been shown to be constitutively and highly expressed in various cancer cells such as malignant glioma and HNSCC (29, 30). More importantly, TDO2 also has immunomodulatory functions by promoting immune tolerance. This, in turn, promotes survival, growth, invasion, and metastasis and decreases patients' survival (just like IDO1) (13, 22, 31, 32).

In this study, we performed a comprehensive analysis on the expression status of genes belonging to the KP. HNSCC and glioblastoma multiforme (GBM) were picked as prime examples for different spontaneous and treatment-induced immune escape mechanisms. Therefore, expression changes were determined under standard and targeted therapy, and results were compared among each other.

### MATERIALS AND METHODS

### Tumor Cell Lines and Culture Conditions

Patient-derived GBM cell lines (N = 13; HROG02, HROG04, HROG05, HROG06, HROG10, HROG15, HROG24, HROG36, HROG38, HROG52, HROG63, HROG73, HROG75) and HNSCC cell lines (N = 6; FADU, Detroit-562, Cal-33, PE/CA/PJ-15, UT-SCC-14, UT-SCC-15) were either established and basically characterized in our lab or originally obtained from the German collection of cell cultures (DSMZ; Braunschweig, Germany). UT-SCC14 and UT-SCC15 cells were kindly provided by Prof. R. Grenman [University of Turku, Finland (33)]. All cells were routinely cultured in our lab and maintained in full medium: Dulbecco's modified Eagle Medium/HamsF12 supplemented with 10% fetal calf serum, glutamine (2 mmol/L), and antibiotics (medium and supplements were purchased from PAA, Cölbe, Germany). For functional analysis, cell lines from each tumor entity were chosen, and all subsequent experiments were performed with these lines only.

### IFNγ Stimulation

Cells were cultured in six-well plates or ibidi chamber slides, incubated overnight and treated with IFNγ (50 ng/ml, Immunotools, Friesoythe, Germany) for 24 and 72 h, respectively. Thereafter, cells were harvested and further processed.

### Cytostatic Drugs and Targeted Substance

Cytostatics used in this study included 5-fluorouracil (5-FU) (2.5µM), Cisplatin (0.2µM), Gemcitabine (0.0002µM), and Cetuximab (0.34µM) for HNSCC, as well as Temozolomide (10µM, TMZ) for GBM (pharmacy of the University Hospital Rostock). CDKi Dinaciclib (10 or 100 nM) was used as experimental targeted drug. All substances were used in doses below the IC50 as determined before.

### Apoptosis/Necrosis Assay

A Yo-Pro-1/PI-based assay for discriminating early apoptotic, late apoptotic, and necrotic cells was applied as described before (34).

### Hemolysis Assay

Hemolytic activity of Dinaciclib was determined by hemoglobin release from whole blood cells after 2 h of incubation. Briefly,

**Abbreviations:** CDKi, cyclin-dependent kinase inhibitor; GBM, glioblastoma multiforme; HNSCC, head and neck squamous cell carcinoma; IDO1, indoleamine 2,3-dioxygenase; IFN, interferon; KYAT, kynurenine aminotransferase; KP, kynurenine pathway; PBMC, peripheral blood mononuclear cells; SCC, squamous cell carcinoma; TDO2, tryptophan 2,3-dioxygenase.

whole blood of healthy donors (N = 5) was seeded in 96 well plates and treated with increasing Dinaciclib doses (ranging from 1, 5, and 10µM). Negative controls were left untreated, and positive controls (=maximum lysis) were treated with 1% sodium dodecyl sulfate. Following the incubation period, cell-free supernatants were transferred into a new 96-well plate, and absorption was measured on a plate reader at 560 nm (reference wave length, 750 nm). Hemolytic activity was quantified according to the following formula and corrected for spontaneous hemolysis (=untreated controls):

 $ $HOemolysis = ($ OD\_{560\text{nm}} $sample\\$ -OD\_{560\text{nm}} $buffer)/OD\_{560\text{nm}}$ max - OD\_{560\text{nm}} $buffer) × 100 $ $

In addition, peripheral blood mononuclear cells' (PBMC) viability (N = 5) were determined by Calcein AM staining. This was done upon 24 h incubation at the above-mentioned doses. Fluorescence measurement and quantification were done as described (34).

### IDO1 Immunofluorescence

Tumor cells were treated with 50 ng/ml of IFNγ (Immunotools), TMZ, Cetuximab, or Dinaciclib for 24 h in chamber slides, respectively. Cells were washed with phosphate-buffered saline, fixed in 4% paraformaldehyde w/o methanol (Thermo Scientific, Darmstadt, Germany) for 20 min, washed again, followed by cell permeabilization in 0.3% Triton X−100/5% normal bovine serum in phosphate-buffered saline for 60 min. Cells were then incubated overnight at 4◦C in monoclonal rabbit IDO1 primary antibody (1:100; Cell Signaling Technology, Frankfurt/Main, Germany). Cells were washed, labeled with fluorochromeconjugated secondary antibody using goat antirabbit secondary antibody (1:250, Boster Biological Technology, Pleasanton CA, USA), and incubated in the dark for 2 h. Cell nuclei were stained with 4′ ,6-diamidino-2-phenylindole (DAPI), and cells were analyzed with a Zeiss LSM-780 Confocal Laser Microscope (Zeiss, Jena, Germany). Quantification of staining intensity was done using the ImageJ software. Therefore, channels were split into red, green, and blue. Subsequently, integrated density profiles of the same size were measured in the green channel.

### IDO1 Immunohistochemistry on Patients' Tumor Samples

Primary antibody against IDO1 (rabbit IgG, clone D5J4E, Cell Signaling Technology, dilution 1:200) was used. All samples were pretreated for 20 min at 97◦C and pH 6.9. Standard immunoperoxidase technique was applied using an automated immunostainer (DAKO link) with diaminobenzidine as chromogen. IDO1 expression was defined as cytoplasmatic and membranous staining in >1% inflammatory cells.

### Quantification of Tryptophan, Kynurenine, and Kynurenic Acid in Cell Culture Supernatant by Liquid Chromatography Tandem Mass Spectrometry System

The basis for the measurement was the method of Fuertig et al. which was adapted to the system used here (35).

### Sample Preparation

Cell culture supernatant was mixed 1:1 with internal standards [10µM D5-kynurenic acid (Buchem BV, Apeldoorn, Netherlands), 10µM D5-phenylalanine (Cambridge Isotope Laboratories, Inc. Andover, MA, United States), 5µM D4-kynurenine (Cambridge Isotope Laboratories), 10µM D5-tryptophan (Sigma Aldrich, Hamburg, Germany), 10µM D3-quinolinic acid (Buchem BV), 5.5 nM 15N5-8-hydroxy-2 deoxyguanosine (Cambridge Isotope Laboratories)], and with 10 µl of mobile phase (0.4% formic acid, 1% acetonitrile in water). Reagents were gently shaken on a mixer, and 150 µl of ice-cold methanol was added. Samples were incubated overnight at −20◦C to allow protein precipitation. On the following day, samples were centrifugated at 0◦C and 18,000×g for 15 min. Supernatants were transferred to a new tube, and the liquid phase was removed by evaporation at 30◦C among vacuum. Solid samples were stored until measurement at −20◦C. Afterwards, dried extracts were reconstituted in 100 µl of acidified mobile phase. Samples were incubated at 40◦C (1 h), centrifuged (4◦C, 18,000×g, 5 min), and clear supernatant (100 µl) was transferred onto a 96-well plate.

### Liquid Chromatography Tandem Mass Spectrometry

Measurements were performed on an AB Sciex 5500 QTrapTM mass spectrometer (AB SCIEX, Darmstadt, Germany) with electrospray ionization in positive mode combined with a high-performance liquid chromatography system (Agilent 1260 Infinity Binary LC, Santa Clara, United States) including a degasser unit, column oven, autosampler, and a binary pump. Twenty microliters of the supernatant was injected and separated using a VisionHT C18 column (100 × 2.1 mm; particle size, 3µm; Grace, MD, United States). To prevent contamination, a precolumn (VisionHT C18, Guard 5 × 2 mm) was used additionally. The temperature of the column oven was set at 15◦C. The flowrate was set to 0.4 ml/min, and the sample was separated in a total run time of 11 min using solution A (water + 0.1% formic acid + 0.01% trifluoroacetic acid) and solution B (MeOH + 0.1% formic acid + 0.01% trifluoroacetic acid) with the following gradient: 0–2.8 min, 97% A, 3% B; 2.8–3.3 min, 70% A, 30% B; 3.3–4.4, 40% A, 60% B; 4.5– 5.0 min, 40% A, 60% B; 5.0–5.5, 5% A, 95% B; 5.5–6.9 min, 5% A, 95% B; 6.9–7.0 min, 97% A, 3% B; 7.0–11.0 min, 97% A, 3% B.

The eluate between 0.5 and 9 min was introduced into the mass spectrometer and analyzed in MRM mode. The ion spray voltage (IS) was 4,000 V, the curtain gas flow was 40.0 psi, and the ion source temperature were set at 550◦C.

Internal standards were used for metabolite quantification (**Table 1**). Data analysis, including peak integration and concentration determination, was performed with Analyst software (Version 1.5.1, AB Sciex, Darmstadt, Germany).

### RNA Isolation, cDNA Synthesis, and Quantitative Real-Time PCR

Total RNA was isolated with RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturers' instructions. RNA was reverse transcribed into complementary DNA (cDNA) from 1 µg RNA using 1 µl dNTP mix (10 mM), oligo (dT)15 primer (50 ng/µl), 1 µl reverse transcriptase (100 U), and 4 µl 5× reverse transcription buffer complete (all purchased from Bioron GmbH, Ludwigshafen, Germany). Final reaction volume was 20 µl (filled with RNAse free water). cDNA synthesis conditions were as follows: 70◦C for 10 min, 45◦C for 120 min, and 70◦C for 10 min. Target cDNA levels of human cell lines were analyzed by quantitative real-time PCR using TaqMan Universal PCR Master Mix and self-designed TaqMan gene expression assays either labeled with 6-FAM-3′ BHQ-1 or 5′ HEX−3 ′ BHQ-1 to be used as duplex: IDO1, TDO2, KMO, HAAO, KYAT1/2/3/4, KYNU, QPRT, and GAPDH

TABLE 1 | Internal standards.

or ß-actin were used as housekeeping genes. Reaction was performed in the light cycler Viia7 (Applied Biosystems, Foster City, USA) with the following PCR conditions: 95◦C for 10 min, 40 cycles of 15 s at 95◦C, and 1 min at 60◦C. All reactions were run in triplicates. The messenger RNA (mRNA) levels of target genes were normalized to GAPDH/β-actin. Reactions were performed in triplicate wells and repeated four times. The general expression level of each sample was considered by calculating 2−1CT (1Ct = Cttarget – CtHousekeeping genes).

### Statistical Analysis

All values are reported as mean ± SD. After proving the assumption of normality, differences between controls and treated cells were determined using the unpaired Student's ttest. If normality failed, the non-parametric Mann-Whitney Utest was applied. Statistical evaluation was performed using GraphPad PRISM software, version 5.02 (GraphPad Software, San Diego, CA, USA). In case of multiple comparisons, two- or one-way ANOVA on ranks (Bonferroni's multiple comparison test) was used. The criterion for significance was taken to be p < 0.05.

FIGURE 2 | IDO1 immunohistochemistry. Representative images of primary glioblastoma multiforme (GBM) [HROG36 (a,b), HROG63 (c,d), and HROG73 (e,f)] and head and neck squamous cell carcinoma (HNSCC) [HNSCC06 (g,h), HNSCC02 (i,j), HNSCC01 (k,l)] samples. Left panel: Routine HE staining. Right panel: Note the focal IDO1 expression on tumor-infiltrating lymphocytes exclusively in HNSCC cases. HNSCC case 1 (g,h): tonsil (HPVpositive); case 2 (i,j): mouth base (HPVnegative , relapse); case 3 (k,l): larynx (HPVnegative). Pictures were taken at 20× and 10× magnification, respectively.

### RESULTS

### Basal IDO1 and Related Genes in GBM and HNSCC Cell Lines

While IDO1 itself is not the only mechanism by which tumors can resist immune-mediated killing, we studied the expression status of different KP-related genes on a panel of human GBM and HNSCC cell lines. These experiments revealed not only differences between both entities but also a heterogeneous profile of all tested genes among cell lines (**Figure 1**). IDO1 was differently expressed by most glioma samples (11/13) analyzed. In general, IDO1 was only detectable at very low levels (**Figure 1**). TDO2, the other rate-limiting enzyme of the KP (36), was constitutively expressed by all glioma samples, and expression was even higher in comparison to IDO1. Generally, expression status for TDO2 and kynurenine hydrolase (KYNU) was higher in GBM, while HNSCC expressed more kynurenine aminotransferases (KYAT) (**Figure 1**). Hence, these data indicate that the KP is active in both entities, with however different enzymes being involved in TRP catabolism.

Still, tumor cell lines grown in vitro not necessarily represent the in vivo situation; we therefore analyzed the IDO1 abundance in clinical resection specimens (**Figure 2**). In GBM, IDO1 was detectable in one of three cases (representative images are shown in **Figure 2**). By contrast, HNSCC samples presented with IDO1 but only on a small fraction of tumorinfiltrating lymphocytes (**Figure 2**). Although not analyzed systematically, the only HPVpositive case in this small cohort showed highest IDO1 abundance, nicely reflecting the tumors' immunogenicity (11, 37).

### Gene Expression and Protein Changes Upon IFNγ Stimulation

IDO1 is an IFNγ-inducible enzyme. Upon stimulation, the KP is activated to induce immunosuppression. In vitro stimulation with IFNγ mimics the in vivo situation of an inflammatory microenvironment. Hence, upon immunemediated inflammation, IDO1-negative tumor cells may upregulate IDO1 as resistance mechanism.

with IFNγ (50 ng/ml) for 24 h. (A) The graphs indicate the mRNA expression normalized to the housekeeping genes (2−1CT). GBM N = 5 cell lines (HROG02, HROG05, HROG52, HROG63, HROG75); HNSCC, N = 4 cell lines (FADU, Detroit-562, Cal-33, PE/CA/PJ-15). (B) IDO1 immunofluorescence in selected cell lines. Cell nuclei were stained with DAPI, and IDO1 was depicted by monoclonal rabbit IDO1 primary antibody (1:100; Cell Signaling Technology), followed by secondary antibody (1:250, Boster Biological Technology Pleasanton, CA, United States) labeling. Cells were analyzed with a Zeiss LSM-780 Confocal Laser Microscope. Original magnification 20×.

Using five individual GBM cell lines, IDO1 expression was inducible in all cases (**Figure 3A**). Upregulation of IDO1 was high on protein levels in HROG05 cells and marginal in HROG63 (**Figure 3B**). TDO2 and KYAT3 were suppressed upon IFNγ stimulation in three of five samples and hardly detectable in one cell line, supporting data from a recent publication (38). KYNU was not affected by IFNγ stimulation (**Figure 3A**).

Just as in GBM, IDO1 was inducible in HNSCC cells (**Figure 3A**). Immunofluorescence revealed focal expression of singular cells with different intensity (**Figure 3B**). Of note, IFNγ stimulation even induced upregulation of KYAT1, KYAT2, KYAT3, and KYAT4 (**Figure 3A** and data not shown), most likely constituting a compensatory mechanism as described before in experimental autochthonous tumor models (39).

### Interference With the KP of Cytostatic and Targeted Therapies

Next, we examined whether cytostatic and targeted drugs have an influence on the KP. For GBM, TMZ was chosen, and for HNSCC, 5-FU, Cisplatin, Gemcitabine, as well as Cetuximab were used. As a targeted yet still experimental agent, the potent and specific CDKi Dinaciclib was applied to cells of both entities.

Before this experiment, drug doses were carefully tested in dose-response analyses (data not shown) along with discrimination of apoptosis and necrosis. Generally, drugs used in this study tended to induce necrosis, while apoptosis, if present, was only detectable at early time points. Exemplary results for the HNSCC cell line Detroit-562 are given in **Supplementary Figures 1A,B**. While cytostatics are well-known to affect normal cells' viability, the impact of the CDKi Dinaciclib on immune and red blood cells is less clear. We therefore performed a hemolysis and leukocyte viability assay. In this experiment, no toxicity was seen against normal cells (**Supplementary Figure 1C**). Even at high concentrations, Dinaciclib impaired cellular viability/integrity only marginally (**Supplementary Figure 1C**).

TMZ is an oral alkylating agent that methylates DNA at the O6 position of guanine causing cell cycle arrest at G2/M. It is used as standard of care for GBM. However, acquired resistance, a process not fully understood, leads to

major limitations in treatment. Here, TMZ downregulated IDO1 in three of five GBM cell lines but led to increased expression in HROG52 and HROG63—a paired GBM cell line established from the very same patient (primary lesion and upon relapse) (**Figure 4**). Gene expression of KYAT2, KYAT4, and KMO was heterogeneous. Generally, there was a trend toward higher expression of those genes but with cell-linespecific differences (e.g., KYAT3: p < 0.05 vs. control in HROG05 cells; **Figure 4**). KYNU expression was not affected by TMZ (data not shown). Interestingly, the combination of IFNγ and TMZ that mimics the in vivo situation led to similar or even stronger IDO1 upregulation compared to IFNγ alone in two out of four glioma samples (**Figure 5**). Adding Dinaciclib to either IFNγ or TMZ lowered the mRNA expression of IDO1 massively. Other KP-related genes like

TDO2 and KYAT1-4 were similarly downregulated (**Figure 5**). **Supplementary Table for Figure 5** provides a detailed statistical analysis of each cell line in relation to the individual treatment regimens.

In HNSCC cells, Cetuximab was the only IDO1-inducing substance (exemplary results for Detroit-562 cells are given in **Figure 6**). Beyond that, the cytostatics as well as Cetuximab induced at least one of the KP-related genes (p < 0.05 vs. control), implicating activation of this pathway via different effectors. By adding Dinaciclib to cytostatic drugs, this effect was abrogated, even in the presence of IFNγ (**Figure 6** and data not shown). Of note, Dinaciclib alone as well as in combination with other substances effectively suppressed all KPrelated genes, implying inhibition of the TRP catabolism by this CDKi.

## Dinaciclib Blocks IFNγ-Induced IDO1 Expression in GBM and HNSCC Cells

Considering the active downregulation of KP-related genes by Dinaciclib, we investigated whether this CDKi is able to inhibit or reverse IFNγ-induced IDO1 upregulation in GBM and HNSCC cells on a protein level. TMZ and Cetuximab were included as active inductors of IDO1 and associated KP-related genes.

IFNγ and selected drugs were added simultaneously for 72 h. Dinaciclib effectively blocked IFNγ-induced IDO1 protein in both entities, while TMZ alone as well as the combination with IFNγ strongly enhanced IDO1 protein level (**Figure 7**). Hence, mRNA expression data were nicely confirmed.

When Dinaciclib was combined with IFNγ and TMZ, the IDO1-inducing stimulus of these latter substances was far too strong to be suppressed (**Figure 7**). However, the low number of residual cells in this combination hints toward additive or even synergistic effects independent from IDO1 (**Figures 7A,B**).

While IDO1 was highly inducible in GBM cells only, we then determined protein level upon IFNγ-prestimulation approaching the in vivo situation. The cytotoxic effect of Dinaciclib was preserved; however, levels of IDO1 enzyme were not significantly altered (**Supplementary Figures 2A,B**). Comparable results were obtained for TMZ. Virtually, all residual cells showed positive staining; still there was a trend toward lower intensity in monotherapy and in combination (**Supplementary Figure 2B**).

Taken together, the CDKi Dinaciclib is able to block IFNγmediated and thus most likely even chemotherapy-induced IDO1 upregulation in GBM and HNSCC cells. However, blunt interference with this TRP-metabolizing enzyme is unlikely.

### Treatment Induced Influence on KP-Related Metabolites

Our data revealed IDO1 induction by TMZ, which is reversible by Dinaciclib. Thus, we examined the influence on KP-related metabolites in GBM cell lines.

TRP, KYN, and the downstream metabolite kynurenic acid (KYNA) were quantified by MS using cell culture supernatants of GBM cell lines (**Figures 8A,B**). TRP was catabolized after 24 h from all cell lines among all treatment regimens. Adding TMZ or Dinaciclib in monotherapy marginally affected TRP consumption as well as KYN and KYNA production. Stimulation with either IFNγ or a combination of TMZ resulted in greatly enhanced TRP depletion and increased KYN levels, although to varying degrees in the different cell lines (**Figure 8A**). Small amounts of KYNA were produced constitutively and to a greater extent after IFNγ mono- and TMZ combination in all cell lines (**Figure 8A**). In contrast, KYNA level remained unchanged upon Dinaciclib in combination with IFNγ, confirming immunofluorescence results (please see **Figure 7** for details). The same was true for the KYN/TRP ratio, being only

affected in samples treated with IFNγ as well as the combination of IFNγ and TMZ (**Figure 8B**).

These data underline our gene and protein expression data. The CDKi Dinaciclib is directly or indirectly capable of blocking the KP. TMZ particularly in combination with the proinflammatory cytokine IFNγ accelerates TRP consumption accompanied by KYN and KYNA production in GBM cells.

### DISCUSSION

The finding that high IDO1 expression is associated with shorter survival in cancer patients made IDO1 a promising target either by specific inhibitors or indirectly by immunomodulation. A recent study described dramatically suppressed tumor growth upon IDO1 knockdown by increasing the number of CD4+ and CD8+ T cells in murine GBM models (9). However, the exact mechanisms underlying IDO1 and thus TRP metabolism along the KP remain unclear. Therefore, we focused on the expression of IDO1 and IDO-related KP genes and their potential involvement in immune evasion in experimental models of HNSCC and GBM.

We were able to show that the KP is active in both entities, with different enzymes involved in TRP catabolism. Of note, basal IDO1 expression was low and inversely correlated with TDO2. In the only prior study on primary GBM cultures, similar results were described with constitutive TDO2 expression in

most GBM cell cultures (29). In here, TDO2 likely promotes tumor growth by suppressing antitumor immune responses (2, 31). KP products are considered as therapeutic targets because IDO1 and other genes of the TRP metabolism are not expressed in healthy brain tissue, but gradually increase with GBM dedifferentiation (low vs. high grade GBM). In HNSCC, different results on IDO1 are documented, and expression is heterogeneous among different HNSCC cell lines. Of note, IDO1 abundance of primary resection specimen and cultured cells seems to be independent from anatomical site and HPV status (40). Still, IDO1 is a useful marker for progression of in oral squamous cell carcinoma (41). In esophageal squamous cell carcinoma, progression and metastasis correlates with strong inflammation at the tumors' invasive front and disturbed TRP metabolism (42). These cumulative data highlight the biological relevance of the KP in malignancies and may explain why IDO1 is barely detectable upon long-term in vitro culture. By mimicking the inflamed microenvironment and thus taking a step closer to the in vivo situation, IFNγ was added as strong IDO1 inductor (43). While GBM cells responded with the expected IDO1 upregulation on mRNA expression and protein level as well as accelerated TRP consumption, this molecule was barely inducible in HNSCC cells. It is conceivable that this is due to the duration of in vitro culture. GBM cells were established recently and thus used in defined low passages (<P40), whereas half of the HNSCC cell lines were long-term cultures with more or less unknown passage [Detroit-562 as well as UT-SCC14 and UT-SCC15 (44) are the only exceptions; <P40]. Cell lines may acquire additional mutations overtime changing their protein expression. Another in vitro limitation is that experiments were conducted without immunological pressure. In vivo studies are desirable to verify the results.

Indirect effects of TRP metabolism include interference with other biological functions like migration, angiogenesis, and cell growth regulation (18, 40). To investigate the influence of anticancer drugs on TRP catabolism, we performed a comprehensive analysis using conventional chemotherapy (TMZ, 5-FU, Cisplatin, Gemcitabine) and targeted drugs

(Cetuximab, Dinaciclib). The KP-related gene expression and metabolites were determined in residual cells. In GBM, the standard of care drug TMZ was applied either with or without IFNγ stimulation. While this substance affected IDO1 on the expression level, the amount of the resulting protein increased. This may be explained by either increased protein's half-life due to a reduced rate of degradation or the preferential translation during cellular stress. In previous studies, exposure of several cultured human malignant glioma cell lines, primary neurons, and a neuroblastoma cell line to IFNγ reduced TRP levels in culture medium accompanied by increased IDO1 expression and KYN production (29, 45). Our results confirm these data, and in addition, we were able to demonstrate that IFNγ stimulation in combination with TMZ stimulated KYN and KYNA production and TRP catabolism in GBM cell cultures. The increase in TRP catabolism and KYN production (KYN/TRP ratio) is widely used as indirect indicator of the cumulative activities of TDO2, IDO1, and IDO-2 (38, 46). The KP in brain tumors is likely triggered by IFNγ from immediate surrounding tissue (29, 47, 48). Thus, IDO1 expression in brain tumor cells is likely to be triggered when IFNγ is produced from activated T cells and/or microglia and neurons. Furthermore, gliomas and glioneuronal tumors have an elevated tryptophan uptake and catabolism in vivo (49). Given our observation on a further enhanced KP activity upon TMZ treatment, this might provide an explanation of (acquired) drug resistance and final relapse. Hence, IDO1 blocking agents should be investigated in TMZ-tailored therapeutic approaches.

In HNSCC cells, KP activation was different. KP-related genes were exclusively induced by standard drugs, and only Cetuximab induced IDO1. Additional upregulated genes involved kynurenine aminotransferases, responsible for synthesizing a neuroprotectant, and KMO. While the specific biochemical activity of these molecules and biological relevance in cancer is barely examined, we interpret this result as one possible mechanism of resistance upon therapy—a finding quite common after conventional chemotherapy and usually also being associated with poor response toward neoadjuvant therapy in other entities (50).

Mechanistically, this can be attributed to the secretion of proinflammatory substances, such as prostaglandin E2 or highmobility group protein B1 by dying tumor cells, secondary contributing to KP activation. By accumulating TRP, toxic metabolites of tumor cells actively shape an immunosuppressive microenvironment. Breaking down this shield is one of the main objectives in pharmacological inhibition of KP. Questions remain why most inhibitors failed in clinical trials, and mechanisms are only just beginning to become clear. A fact worth mentioning is the functional redundancy of IDO1, IDO-2, and TDO2 (51), augmenting the risk of mechanistic bypass.

Dinaciclib is a potent and specific CDK inhibitor of CDK1, CDK2, CDK5, and CDK9. Preclinical studies showed that this inhibitor is capable of decelerating tumor growth in numerous cancer entities via cell cycle arrest and apoptosis induction (52, 53). In our study, Dinaciclib was the only KP-inhibiting substance tested here. Of note, impairment of the KP was independent from the combination partner, and this CDKi effectively suppressed IFNγ-induced IDO1 upregulation after simultaneous treatment. While this result was completely unexpected and has—to the best of our knowledge—not been described previously, our data do not support the idea of blunt interference with the KP. GBM cells with strong IDO1 expression showed only marginally reduced IDO1 protein level after Dinaciclib treatment. This effect might be boosted after long or repeated treatment cycles. In line with these findings, several preclinical studies already proposed synergistic effects of selective and unselective IDO1 inhibitors when administered in conjunction with chemo- and/or radiotherapy (4). This may finally have impact for secondor third-line immunotherapeutic approaches. Therefore, the late KYN/TRP index is indeed a relevant clinical benchmark providing prognostic value for GBM patients (54).

Summarizing our findings, we provide evidence for the relevance of TRP catabolism in malignancies especially in the context of standard therapy. The CDKi Dinaciclib was identified as indirect KP inhibitor. Lastly, specific KP inhibition may increase the efficacy of standard drugs by restoring immune function and thus improve patients' outcome.

### DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

### AUTHOR CONTRIBUTIONS

CR performed experiments, analyzed data, and participated in manuscript writing. BS and AZ performed immunohistochemistry and analysis, and provided images. HK, JG, NI, and FS performed experiments and analyzed data. GD performed LC-MS analyses. CC and CJ participated in paper

### REFERENCES

finalization and critically revised the manuscript. DS and EW critically revised the manuscript. CM designed study, the outline of the manuscript, performed data interpretation, and wrote the manuscript.

### FUNDING

CM was supported by grants from the Deutsche Forschungsgemeinschaft (MA5799/2-1 and MA5799/2-2).

### ACKNOWLEDGMENTS

The authors are also grateful to Susanne Neumeister and Dr. Ann-Kristin Henning from the Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, for assisting with the quantification of TRP metabolites.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2020.00055/full#supplementary-material

Supplementary Figure 1 | Quantitative analysis of cell death in Detroit-562 HNSCC cells upon cytostatic drugs and targeted therapy. The cells were treated with the given substances for 24 and 72 h. Thereafter, cells were harvested and stained with Yo-Pro-1 to detect early and late apoptotic cells, as well as propidium iodide for necrosis determination. Apoptosis/necrosis discrimination was done on a flow cytometer (BD FACSVerseTM) as described in material and methods. (A) Quantitative analysis of cell death after 24 and 72 h, respectively. ∗p < 0.05 vs. control; ∗∗p < 0.01 vs. control. t-test. (B) Representative dot plots showing elevated numbers of necrotic cells upon treatment. (C) Hemolysis and viability of PBMC upon treatment with Dinaciclib. Therefore, whole blood and PBMC were cultured in the presence of increasing Dinaciclib concentrations (1, 5, and 10µM) for 2 and 24 h, respectively. Hemolytic activity was determined from cell-free supernatants (red blood cell lysis), Calcein AM was used for quantifying viability of PBMC. Mean + SD, N = 5 individual donors.

Supplementary Figure 2 | IDO1 protein abundance in HROG05 GBM cells upon cytostatic drugs and targeted therapy. The cells were pretreated with IFNγ (50 ng/ml) for 24 h. Thereafter TMZ, Dinaciclib and the combination of both substances was added to see whether IFNγ-induced upregulation of IDO1 is reversible. (A) None of these substances downregulated IDO1 in the sequential setting. Cell nuclei were stained with DAPI. Original magnification 20x. (B) Quantification was done to score staining intensity in untreated and treated HROG05 cells. This was carried out by using ImageJ software as described in material and methods.

Supplementary Table for Figure 5 | Statistical analysis of individual treatment regimens, depicted for each cell line, and genes analyzed.

on patient-derived tumor models. Biomed Res Int. (2019) 2019:4938285. doi: 10.1155/2019/4938285

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Riess, Schneider, Kehnscherper, Gesche, Irmscher, Shokraie, Classen, Wirthgen, Domanska, Zimpfer, Strüder, Junghanss and Maletzki. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Host and Microbial Tryptophan Metabolic Profiling in Multiple Sclerosis

Lorenzo Gaetani 1 , Francesca Boscaro2 , Giuseppe Pieraccini 2 , Paolo Calabresi 3 , Luigina Romani 4 , Massimiliano Di Filippo1† and Teresa Zelante4 \* †

*1 Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy, 2 Mass Spectrometry Centre (CISM), Department of Health Sciences, University of Florence, Florence, Italy, 3 Section of Neurology, Department of Neuroscience, Agostino Gemelli Hospital, Catholic University of the Sacred Heart, Rome, Italy, 4 Department of Experimental Medicine, University of Perugia, Perugia, Italy*

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that is associated with demyelination and neuronal loss. Over recent years, the immunological and neuronal effects of tryptophan (Trp) metabolites have been largely investigated, leading to the hypothesis that these compounds and the related enzymes are possibly involved in the pathophysiology of MS. Specifically, the kynurenine pathway of Trp metabolism is responsible for the synthesis of intermediate products with potential immunological and neuronal effects. More recently, Trp metabolites, originating also from the host microbiome, have been identified in MS, and it has been shown that they are differently regulated in MS patients. Here, we sought to discuss whether, in MS patients, a specific urinary signature of host/microbiome Trp metabolism can be potentially identified so as to select novel biomarkers and guide toward the identification of specific metabolic pathways as drug targets in MS.

#### Edited by:

*Dietmar Fuchs, Innsbruck Medical University, Austria*

#### Reviewed by:

*Giuseppina Ruggiero, University of Naples Federico II, Italy Trevor William Stone, University of Oxford, United Kingdom*

#### \*Correspondence:

*Teresa Zelante<EMAIL_ADDRESS>
*†These authors have contributed equally to this work*

#### Specialty section:

*This article was submitted to Inflammation, a section of the journal Frontiers in Immunology*

Received: *15 October 2019* Accepted: *21 January 2020* Published: *18 February 2020*

#### Citation:

*Gaetani L, Boscaro F, Pieraccini G, Calabresi P, Romani L, Di Filippo M and Zelante T (2020) Host and Microbial Tryptophan Metabolic Profiling in Multiple Sclerosis. Front. Immunol. 11:157. doi: 10.3389/fimmu.2020.00157* Keywords: tryptophan, urine, signature, metabolite, multiple sclerosis, kynurenine, indole-3-propionic acid, microbiota

### INTRODUCTION

The levels of the essential amino acid Tryptophan (Trp) and the function of Trp derivatives have long been a subject of research interest in autoimmunity. Mammals utilize Trp for different reasons, such as protein synthesis, the release of immunomodulant catabolites, and the synthesis of the aminergic neurotransmitter serotonin, the neurohormone melatonin, several neuroactive kynuramine metabolites of melatonin, and trace amine tryptamine. Indeed, Trp is metabolized by the mammalian host cells via four different pathways, of which the most relevant is the kynurenine pathway. The other two pathways provide the transamination and decarboxylation of Trp. The hydroxylation in serotonin occurs for only 1% of dietary Trp. Interestingly, the metabolic products of the kynurenine pathway are known to have several effects on vascular system, immune system, immunotolerance, and infections.

From the time when Trp and Trp derivatives were administered in multiple sclerosis (MS) to treat autoimmunity empirically (1), many advances have been made on the knowledge of Trp metabolic functions (2). It is almost universally agreed that the catabolism of Trp has different physiological implications, such as having antimicrobial and immunomodulant properties. For all of these reasons, Trp metabolites have been largely investigated in MS (3).

From a pathophysiological point of view, MS is characterized, from its earliest stages, by the coexistence of acute focal inflammation, glial cell hyperactivation, and progressive neuroaxonal loss (4). In the relapsing-remitting phenotype of the disease, inflammatory mechanisms are prominent and are largely responsible for the clinical manifestations of the disease, which are usually transient and recurrent (4). On the contrary, the progressive phenotype of the disease, which often follows the relapsing-remitting phase, is thought to be largely sustained by neurodegenerative mechanisms, probably as the ultimate consequence of previous recurrent episodes of brain and spinal cord inflammation (5). Additionally, the development of meningeal lymphocytic infiltrates and B-cell follicle-like structures in progressive MS patients may enhance neurodegenerative phenomena (6). MS can be extremely variable between individuals, with huge differences in the frequency of episodes of focal inflammation, in the possibility of the transition from the relapsing-remitting to the progressive phenotype, in the rate of progression, and in disability outcomes (7). Among the numerous factors potentially underlying this variability, a link between environment, microbial commensals, and host immunity has been suggested (8).

The earlier findings that Trp metabolized by indoleamine-2,3-dioxygenase (IDO) along the kynurenine pathway, plays a role in the pathophysiology of neuroinflammatory and neurodegenerative disorders, led several groups of researchers to study the changes in the levels of kynurenines in plasma, urine and cerebrospinal fluid in MS patients or in mice with experimental autoimmune encephalitis (EAE), the animal model of MS (9–13).

Systemic activation of Trp metabolism may have critical effects in MS. For instance, it has been demonstrated that Trp degradation is increased in the brain during the acute phase of EAE (14). Experimental results obtained by the use of the pharmacological inhibitor of IDO (1-methyl-Trp) also support a role for this pathway in MS. Indeed, the treatment of mice with 1-methyl-Trp resulted in EAE exacerbation (14). This latter evidence might suggest a protective role of IDO metabolites in EAE, although some downstream products of the kynurenine pathway, such as quinolinic acid, may also promote neurotoxicity.

Recently, metabolomics provided new insights into the research field of MS immunopathology, showing significant promise for unraveling the sources of disease heterogeneity, for understanding the interaction between the environment and immunity, and for monitoring disease progression and response to treatment in MS patients. For instance, untargeted metabolomics has been used recently in plasma samples of EAE mice to find a signature of 44 metabolites corresponding to six major pathways that were considerably altered, including bile acid biosynthesis, taurine metabolism, tryptophan and histidine metabolism, and linoleic acid and D-arginine metabolic pathways (9). Interestingly, the signature also included various metabolites categorized under the xenobiotics class, which are normally not synthesized in the body but can be metabolized by the microbiome as equolsulphate, homostachydrine, hippurate, and a Trp-derivative, indoleacrylate, which is also excreted in urine. Besides, another Trp-derivative metabolite produced by the microbiota, indole-3-propionic acid, was found to be elevated in the plasma of EAE mice (9).

From a clinical perspective, one of the most important outcomes in MS is the risk of developing a progressive disease course (15). Indeed, while the relapsing-remitting phase can be effectively managed with immunomodulatory drugs, few treatments are available for progressive MS, and the progression of neurological disability is difficult to manage (16). In this context, Lim et al. recently wrote a paper targeted at deciphering a metabolic signature in serum to predict the transition from relapsing-remitting to progressive MS and to find a metabolic biomarker. Accordingly, they examined the role of the kynurenine pathway in MS progression and found that this pathway has a strong association with MS subtypes, correlating with disease severity scores (17).

Metabolomics has also been done on urine samples, which are readily available for analysis, and this has been used as a potential source of biomarkers in MS (18). Nuclear magnetic resonance (NMR) spectroscopy of urine allowed for the identification of metabolites that differentiated EAE-mice from healthy and MS drug-treated EAE mice (19). More recently, the metabolic profile in urine of mice bearing chronic EAE was performed with an untargeted combined metabolomics approach using gas chromatography- and liquid chromatography-mass spectrometry (GC-MS and LC-MS) (20). The authors identified eight metabolites characterizing EAE mice that are commonly found in plasma and urine and are potential biomarkers (20). Interestingly, the amino acid metabolism was primarily affected during EAE, as supported by urine analysis (20).

It is worth noting that in the diagnostic and/or therapeutic work-up of MS patients, standard urine analysis is usually performed, which makes urine sampling feasible for other investigations also. Additionally, urine is a metabolite-rich fluid that reflects the body's homeostasis and gut microbiome changes. Thus, a combined metabolomics analysis in urine, where both changes in host inflammatory/metabolic responses and in gut microbiome during MS may be highlighted, might help identifying novel biomarkers. This may provide a model to characterize pathogenic aspects of MS and to develop therapeutic approaches. We have therefore decided to perform an observational study aimed at investigating a broad panel of Trp metabolites, of both human and microbial origin, in urine samples from relapsing-remitting MS (RRMS) patients, in order to specifically investigate the possible relationship of Trp metabolites with the earliest inflammatory phase of the disease. We have compared the findings in RRMS patients to a control group of healthy individuals, and we have specifically looked for differences between MS patients and controls and for possible associations with disease characteristics.

### MATERIALS AND METHODS

### Patients

Urine samples were obtained from 47 consecutive patients with RRMS and 43 healthy controls, i.e., individuals without MS or autoimmune or inflammatory diseases. Patients and Gaetani et al. Tryptophan Metabolomics in Multiple Sclerosis

healthy controls were prospectively and consecutively recruited over a 1-year period at the Section of Neurology, Department of Medicine, University of Perugia (Italy). For MS patients, inclusion criteria were: (i) a diagnosis of RRMS according to the 2010 revision of the McDonald criteria (21); (ii) no recent history of infectious disorders (i.e., <30 days before the inclusion in the study); (iii) age >18 years. The study was approved by the local Ethics Committee (# 2925/16), and patients gave informed consent for the collection of samples and subsequent analysis. The main demographic and clinical characteristics of patients were collected by experienced neurologists. For each patient, the disability level at the time of urine sampling was quantified by scoring on the Expanded Disability Status Scale (EDSS) (22). Urine samples were collected at the same time of the day (between 09:00 and 12:00) in order to avoid any potential confounding effect of diurnal rhythm. Urine samples were subsequently analyzed by laboratory technicians who were blinded to clinical data.

### Urine Analysis

Urine Trp metabolites were assessed by means of highperformance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). We used a targeted approach where a set of host or microbial metabolites derived from Trp were measured in urine. Details of HPLC-MS/MS analysis are reported in the **Supplementary Methods**. The following Trp metabolites and ratios were determined: (i) Trp; (ii) kynurenine; (iii) anthranilate; (iv) kynurenine/Trp (K/T) ratio; (v) kynurenine/anthranilate (K/A) ratio; (vi) 3-hydroxykynurenine; (vii) 3-hydroxyanthranilate; (viii) serotonin; (ix) tryptamine; (x) indole-3-acetic acid; (xi) indole-3-acetamide; (xii) indole-3-lactic acid; (xiii) indole-3-propionic acid.

### Statistical Analysis

Continuous variables are reported as mean ± standard deviation (SD) if normally distributed or as median, interquartile range (IQR), if non-normally distributed. Logarithmic transformation was applied to Trp metabolite values in order to reach normality, as verified with the Shapiro-Wilk test. Differences of (log) Trp metabolite values between groups were tested with the Student's t-test, while their association with continuous variables was tested with Pearson's correlation coefficient test. General linear models were performed for multivariable analysis. All tests were two-sided, and the significance threshold was set to p < 0.05. IBM SPSS Statistics software version 22 was used for statistical analysis.

### RESULTS

### The Trp Metabolic Urinary Signature of RRMS Patients

The main demographic and clinical characteristics of RRMS patients and controls are reported in **Table 1**. A total of 35 patients (74.5%) were under disease modifying drugs at the time of urine sampling. In the entire cohort of MS patients and controls, females had significantly lower urinary tryptophan (p = 0.001), kynurenine (p = 0.01), anthranilate (p = 0.01), and serotonin (p = 0.01) concentrations (p = 0.04) than males (data TABLE 1 | Main patient and control characteristics.

*aData are shown as number (percentage).*

*bData are shown as mean* ± *standard deviation.*

*EDSS, Expanded Disability Status Scale; HC, healthy controls; ND, not determinable; NS, not significant; RRMS, relapsing-remitting multiple sclerosis.*

not shown). After adjusting for gender, RRMS patients had a significantly lower urine concentration of kynurenine (1.4µM, IQR: 0.5–3µM vs. 4µM, IQR: 1.9–6.8µ, p = 0.01) and a lower K/T ratio (19, IQR: 15.5–27.5 vs. 29.8, IQR: 13.5–43, p = 0.04) than healthy controls (**Figure 1**). In contrast, no significant difference between patients and control subjects was found in the other Trp analyzed metabolites (see Materials and Methods). Within the RRMS cohort, Trp metabolites were not correlated with age and disease duration. In contrast, we found significant correlations between EDSS scores and urine concentrations of the following metabolites: (i) tryptophan (r = 0.5, p = 0.001), (ii) K/T (r = −0.3, p = 0.03), and (iii) indole-3-propionic acid (r = 0.5, p < 0.001; **Figure 1**). In a multivariate model taking into account age and gender, the correlations were confirmed for tryptophan (β = 0.1, p < 0.04), K/T (β = −0.02, p = 0.003), and indole-3-propionic acid (β = 4.4, p = 0.001). Finally, in RRMS patients, we found no difference in treated compared to untreated individuals, nor were there significant variations depending on the type of ongoing treatment.

In our cohort of RRMS patients, we found that urinary Trp metabolites were differently expressed in patients who had had a recent relapse (i.e., within 30 days before urine sampling). Specifically, the urine K/A ratio was significantly lower in patients with a recent relapse than in clinically stable patients (2.3µM, IQR: 1.2–4.3µM vs. 6.6µM, IQR: 2.5–13.7µM, p = 0.03), with a significantly higher urinary anthranilate concentration in relapsing vs. stable patients (1.1µM, IQR: 0.5–1.8µM vs. 0.2µM, IQR: 0.1–0.3µM, p = 0.02) (data not shown). Finally, relapsing patients had significantly higher urine indole-3-propionic acid concentrations than stable patients (0.05µM, IQR: 0–0.1µM vs. 0.01µM, IQR: 0–0.04µM, p = 0.04; **Figure 1**).

### DISCUSSION

The pathophysiology of MS is extremely complex since it relies on the interplay between several players, such as the peripheral immune system, central nervous system resident

immune cells and glial cells, and neurons (23). MS is supposed to have a multifactorial etiology, and different environmental and genetic risk factors may play a role in determining the risk of developing the disease and in driving different phenotypic disease characteristics (24). Interestingly, Trp metabolism can be influenced both by the individual genetic background and interaction with environmental factors, such as diet. A great deal of interest is now being taken in determining how microbial commensals can modulate the host immune system, since this could lead to the potential discovery of new therapeutic targets.

In this study, we found some intriguing preliminary clues that a dysbalanced human Trp metabolism may have an association with MS, a finding that is supported by the evidence that this specific metabolism plays a central role in the control of immune activation (25). Specifically, we found that in the earliest and most inflammatory phenotype of MS, i.e., RRMS, there is a specific urinary Trp metabolite signature, which is characterized by a lower concentration of kynurenine and a lower K/T ratio than in healthy controls. Additionally, K/T was negatively and independently correlated with the degree of disability at the time of urine sampling. Taken together, these findings seem to suggest that in the earliest stages of MS, a reduced Trp metabolism toward kynurenine can be found, and the lower the synthesis of kynurenine, the worse the degree of clinical impairment due to MS. Of interest, the synthesis of kynurenine via the IDO1 enzyme has been hypothesized to enhance the conversion of naïve T CD4+ cells into regulatory T cells (26), and kynurenine has shown immunoregulatory properties via the activation of the Aryl hydrocarbon Receptor (AhR) (27). Thereafter, reduced synthesis of kynurenine and a subsequent lower urinary kynurenine and K/T ratio may play a role in the pathophysiology of MS, where dysfunctional regulatory T cells favor autoimmune processes in the central nervous system (28).

From a biological point of view, once Trp is converted into kynurenine, the kynurenine pathway of Trp degradation is activated, which leads to the synthesis of a variety of compounds with both neurotoxic and neuroprotective properties that can influence MS pathology and, consequently, the degree of neurological impairment (29). Among the human urinary kynurenine downstream metabolites that we have measured in our study (i.e., 3-hydroxykynurenine and 3 hydroxyanthranilate), we did not find any significant association with the degree of disability apart from the above-mentioned negative correlation between K/T and EDSS. However, when interpreting this latter result, it should be noted that most of our patients had a low disability score. Therefore, the correlation between urinary Trp metabolites and the degree of neurological impairment deserves further confirmation on larger and more heterogeneous cohorts of MS patients, also including patients with progressive MS and with a longer disease duration.

Our findings are different from those reported for serum by Lim et al., who described higher serum K/T in MS patients than in controls (17). It is possible that this opposite result relies on the use of different biological samples (i.e., urine vs. serum), potentially reflecting different phases of Trp metabolism and/or different activities of the involved enzymes at different body sites. In this context, in order to understand the relationship between Trp metabolite concentrations in different biofluids, studies examining urine, blood, and cerebrospinal fluid in the same subjects at the same time are highly desirable.

Another possible explanation for the discrepancy between our findings and those coming from the literature might be the different characteristics of the enrolled patients. For instance, in the cohorts investigated by Lim et al., progressive MS patients were also included, and none of the patients was under diseasemodifying drugs. Moreover, in the same paper, no information was provided on recent disease activity, although it can be assumed that enrolled patients had no history of recent relapses since, in the previous 3 months, they had not undergone steroid therapy (17).

The latter point could be extremely important in influencing Trp metabolite concentrations in body fluids, since we found that their urinary concentrations change in proximity to a clinical relapse, with a decrease in K/A and an increase in indole-3 propionic acid.

The decrease in K/A might either reflect a reduction in urinary kynurenine, a compound with immunoregulatory properties as discussed above, or an increase in anthranilate, or both. Of interest, anthranilate has been shown to increase in the blood in a wide range of human diseases, probably with a sort of "cleaning up" effect after an acute injury (30). Indeed, anthranilate has been associated with an antagonism to other neurotoxic kynurenines, such as quinolinic acid, as well as with a reduction in oxidative stress and in inflammatory responses (30–32). Thereafter, the decrease in urinary K/A in proximity of MS clinical relapses could reflect both a decrease in urinary kynurenine, which could enhance inflammatory responses, and an increase in urinary anthranilate, probably as a consequence of compensatory mechanisms following acute inflammation.

Also, the association between indole-3-propionic acid and MS disease activity is particularly interesting, since this molecule is one of the Trp-derived metabolites produced by the microbiota, called post-biotics (33, 34), that have been deeply investigated in recent years because of their presence in peripheral tissues and their ability to bind xenobiotic receptors. Indole-3-propionic acid is now known to contribute to changes in body weight gain on a tryptophan-rich diet (35). It may destroy indoxyl sulfate-induced expression of fibrosis and inflammation in kidney proximal tubular cells (36). More interestingly, it is also considered an antioxidant and has been reported to be neuroprotective (37). More recently, the mechanism by which the indole-3-propionic acid interacts with the mammalian host epithelial barrier has been described: the xenobiotic receptor pregnane X receptor (PXR) is, in fact, able to recognize this metabolite and reduce gut inflammation (38, 39). Interestingly, high blood levels of indole-3-propionic acid have also been found by other research groups in mice with EAE (9).

Since indole-3-propionic acid has been shown to have an antioxidant effect (40), its urinary increase may reflect an additional compensatory mechanism, driven by microbial commensals, trying to counteract the negative effects of acute inflammation. On the other hand, it is not possible to rule out a deleterious effect of indole-3-propionic acid, given the positive correlation that we have found between this Trp derivative and the degree of disability. Further studies investigating the possible immune and neuronal effects of indole-3-propionic acid are therefore needed to understand its pathophysiological role in MS.

In conclusion, although our findings are preliminary and deserve further confirmation on larger and unselected cohorts, they seem to suggest that a misbalanced human Trp metabolism is associated with MS, probably reflecting disease activity and severity. More interestingly, we found some clues that commensal microbials may interact with the host, especially in proximity to MS relapses, by synthesizing compounds such as indole-3-propionic acid.

### FUTURE PERSPECTIVES

The study of Trp metabolites in MS is providing the scientific community with fascinating clues on the interaction between the microbiota and the human immune system in the context of autoimmune diseases. Our study, performed on urinary Trp metabolites, showed some preliminary and very interesting results, such as reduced urinary K/T in RRMS and its negative correlation with disability measures. In this sense, an altered Trp metabolism could either precede or follow autoimmune pathophysiological processes taking place in MS and could have an association with acute episodes of inflammatory activity during a chronic disease such as MS. More generally, it will be fundamental to understand if Trp metabolites are associated with a pathogenic effect and/or if they reflect the bystander activation of compensatory mechanisms to the ongoing MSrelated autoimmunity. This step is required in order to proceed further in the Trp metabolism research field in search of novel potential therapeutic targets. In the near future, the study of Trp metabolism with the help of artificial intelligence and machine learning may become extremely effective in assisting medical doctors and biologists to address and solve complex diagnostic, prognostic, and therapeutic tasks. Indeed, probabilistic graphical models may be used to decipher or predict how the host and the microbiota share a common metabolic nutrient such as Trp and how this shared catabolism may be affected during immunopathology. Additionally, further studies on larger cohorts of MS patients are required in order to better investigate the correlations between Trp metabolites in different biofluids and more specific disease characteristics, such as neuroradiological and cerebrospinal fluid findings.

### DATA AVAILABILITY STATEMENT

All datasets generated for this study are included in the article/**Supplementary Material**.

### ETHICS STATEMENT

The studies involving human participants were reviewed and approved by the Umbria Region Ethics Committee (CER), Perugia, Italy (# 2925/16). The patients/participants provided their written informed consent to participate in this study.

### AUTHOR CONTRIBUTIONS

LG collected the samples, critically read, analyzed, and discussed the literature, and conceived the outline of the manuscript. LG, MD, and TZ wrote the manuscript. GP and FB performed mass

### REFERENCES

spectrometry on urine samples. PC and LR edited the manuscript and provided valuable discussion and criticism.

### FUNDING

This research came from the Italian Grant Programma per Giovani Ricercatori—Rita Levi Montalcini 2013 (Project No. PGR13XNIDJ) to TZ, the Specific Targeted Research Project FunMeta (ERC-2011-AdG-293714) to LR, and the Italian Fondazione Cassa di Risparmio di Perugia (Project No. 2018.0412.021) to TZ.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2020.00157/full#supplementary-material

and inflammatory genes in proximal tubular cells. Nagoya J Med Sci. (2017) 79:477–86. doi: 10.18999/nagjms.79.4.477

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Gaetani, Boscaro, Pieraccini, Calabresi, Romani, Di Filippo and Zelante. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Inflammation-Induced Tryptophan Breakdown is Related With Anemia, Fatigue, and Depression in Cancer

Lukas Lanser 1 , Patricia Kink 1 , Eva Maria Egger 1 , Wolfgang Willenbacher 2,3 , Dietmar Fuchs 4 , Guenter Weiss 1 and Katharina Kurz 1 \*