# Uncovering the link between kynurenic acid pathway and kidney failure

Carolla El Chamieh, Sophie Liabeuf, Islam Amine Larabi, Natalia Alencar de Pinho, Margaux Costes-Albrespic, Luc Frimat, Céline Lange, Yves-Édouard Herpe, Jean-Charles Martin, Pierre Letourneau, et al.

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Carolla El Chamieh, Sophie Liabeuf, Islam Amine Larabi, Natalia Alencar de Pinho, Margaux Costes-Albrespic, et al.. Uncovering the link between kynurenic acid pathway and kidney failure. Kidney International Reports, 2025, 10 (5), pp.1404-1414. 10.1016/j.ekir.2025.02.024. hal-04982161

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Uncovering the link between kynureninic acid pathway and kidney failure

Carolla El Chamieh, PhD, Sophie Liabeuf, PharmD, PhD, Islam Amine Larabi, PharmD, PhD, Natalia Alencar De Pinho, PhD, Margaux Costes-Albrespic, MPH, Luc Frimat, MD, PhD, Céline Lange, Yves-Édouard Herpe, PhD, Jean-Charles Martin, Pierre Letourneau, MD, Benoit Bérengère, PhD, Christophe Soulage, PhD, Stéphane Burtey, MD, PhD, Jean-Claude Alvarez, PharmD, PhD, Laetitia Koppe, MD, PhD, Ziad A. Massy, MD, PhD, on behalf of the Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) Study Group

PII: S2468-0249(25)00114-7

DOI: https://doi.org/10.1016/j.ekir.2025.02.024

Reference: EKIR 3245

To appear in: *Kidney International Reports*

Received Date: 2 December 2024

Revised Date: 10 February 2025

Accepted Date: 25 February 2025

Please cite this article as: El Chamieh C, Liabeuf S, Larabi IA, De Pinho NA, Costes-Albrespic M, Frimat L, Lange C, Herpe YÉ, Martin JC, Letourneau P, Bérengère B, Soulage C, Burtey S, Alvarez JC, Koppe L, Massy ZA, on behalf of the Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) Study Group, Uncovering the link between kynureninic acid pathway and kidney failure, *Kidney International Reports* (2025), doi: https://doi.org/10.1016/j.ekir.2025.02.024.

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
**Title page**

Uncovering the link between kynurenic acid pathway and kidney failure

**\#Corresponding author:** Ziad A Massy and Sophie Liabeuf.

E-mail address: **ziad.massy@auraparis.org**; 185 Rue Raymond Losserand, 75014 Paris.

E-mail address: **Liabeuf.Sophie@chu-amiens.fr**; Service de pharmacologie clinique, Département de recherche clinique, Avenue R. Laennec - 80054 AMIENS.

Carolla El Chamieh, PhD <fnref n="1" />, Sophie Liabeuf, PharmD, PhD <fnref n="2" />,<fnref n="3" />#, Islam Amine Larabi, PharmD, PhD <fnref n="4" />,<fnref n="5" />, Natalia Alencar De Pinho, PhD <fnref n="1" />, Margaux Costes-Albrespic, MPH <fnref n="1" />, Luc Frimat, MD, PhD <fnref n="6" />,<fnref n="7" />, Céline Lange <fnref n="1" />, Yves-Édouard Herpe, PhD <fnref n="8" />, Jean-Charles Martin <fnref n="9" />, Pierre Letourneau, MD <fnref n="10" />, Benoit Bérengère, PhD <fnref n="11" />, Christophe Soulage, PhD <fnref n="11" />, Stéphane Burtey, MD, PhD <fnref n="12" />,<fnref n="13" />, Jean-Claude Alvarez, PharmD, PhD <fnref n="4" />,<fnref n="5" />, Laetitia Koppe, MD, PhD <fnref n="10" />,<fnref n="11" />, Ziad A Massy, MD, PhD <fnref n="1" />,<fnref n="14" />,<fnref n="15" /> # on behalf of the Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) Study Group

# These two authors contributed equally to the paper

**Running headline:** Kynurenic acid and kidney failure in chronic kidney disease patients.

<footnote n="1">¹ Centre for Research in Epidemiology and Population Health (CESP), INSERM UMRS 1018, Université Paris-Saclay, Université Versailles Saint Quentin, 94807 Villejuif, France.</footnote>

<footnote n="2">²Pharmacoepidemiology Unit, Department of Clinical Pharmacology, Amiens-Picardie University Medical Center, 80054 Amiens, France.</footnote>

<footnote n="3">³MP3CV Laboratory, Jules Verne University of Picardie, 80054 Amiens, France.</footnote>

<footnote n="4">⁴Department of Pharmacology and Toxicology, Raymond Poincaré Hospital, AP-HP, 92380 Garches, France.</footnote>

<footnote n="5">⁵UVSQ, Université Paris-Saclay, Inserm U1018, CESP, Équipe MOODS, 78180 Montigny-le-Bretonneux, France.</footnote>

<footnote n="6">⁶Nephrology Department, CHRU de Nancy, 54000 Vandoeuvre-lès-Nancy, France.</footnote>

<footnote n="7">⁷Lorraine University, APEMAC, 54000 Vandoeuvre-lès-Nancy, France.</footnote>

<footnote n="8">⁸Biobanque de Picardie, CHU Amiens-Picardie, Amiens, France.</footnote>

<footnote n="9">⁹Centre de Recherche Cardiovasculaire et Nutritionnelle (C2VN), INSERM, Institut National pour la Recherche en Agriculture et l'Environnement (INRAE), BioMet, Aix-Marseille Université, Marseille, France.</footnote>

<footnote n="10">¹⁰Département of Nephrology, Hospices Civils de Lyon, Lyon Sud Hospital, 69495 Pierre Bénite, France.</footnote>

<footnote n="11">¹¹Laboratoire CarMeN, INSERM U.1060, INRAE U1397, Université Claude Bernard Lyon 1, Pierre Bénite, France.</footnote>

<footnote n="12">¹²Aix-Marseille University, C2VN, INSERM 1263, Institut National pour la Recherche en Agriculture et l'Environnement (INRAE) 1260, Faculté SMPM, Marseille, France.</footnote>

<footnote n="13">¹³Aix-Marseille University, Centre de Nephrologie et Transplantation Renale, AP-HM Hopital de la Conception, Marseille, France.</footnote>

<footnote n="14">¹⁴Association pour l'Utilisation du Rein Artificiel dans la région parisienne (AURA), Paris, France</footnote>

<footnote n="15">¹⁵Ambroise Paré University Hospital, APHP, Department of Nephrology Boulogne-Billancourt/Paris, France.</footnote>
**Abstract**

**Introduction:** Recent studies have focused on some uremic toxins, in particular those derived from tryptophan, as potential modifiable risk factors of chronic kidney disease (CKD) progression. The kynurenine pathway is the major enzymatic pathway for sequentially catabolizing the tryptophan, resulting in key metabolites including kynurenine and kynurenic acid (KA) by the aminoadipate aminotransferase. We aimed at evaluating the association of serum KA levels and KA/kynurenine ratio (as indicators of aminoadipate aminotransferase activity) with kidney failure.

**Methods:** The CKD-REIN study is a prospective cohort of CKD patients having an estimated glomerular filtration rate <60 ml/min/1.73m². Baseline samples of uremic toxins were measured using a validated liquid chromatography tandem mass spectrometry technique. Cause-specific Cox models were used to estimate hazard ratios for our outcome. The kidney gene expression of the kynurenine pathway was evaluated in 5/6 nephrectomy CKD mice and adenine-diet CKD mice under nephroprotective low protein diet (5% w/w).

**Results:** Over a median follow-up period of 5 years, 608 out of the 2406 patients progressed to kidney failure. A 2-fold increase in serum KA levels and KA/kynurenine ratio were respectively associated with a 22% and 20%-increase in the hazard of kidney failure after multiple adjustments. In mouse model, positive correlation was found between aminoadipate aminotransferase expression and fibrosis-related genes and kidney fibrosis. A low-protein diet was associated with a decrease in aminoadipate aminotransferase expression in the kidney as well as in inflammatory and fibrosis markers.

**Conclusion:** Our findings suggest that the kynurenine pathway is associated with kidney failure, and that the inhibition of aminoadipate aminotransferase and the subsequent reduction of KA accumulation is a promising target to mitigate kidney disease progression.

**Keywords:** chronic kidney disease; kidney failure; kynurenine; tryptophan; kynurenic acid pathway.
Introduction

Chronic kidney disease (CKD) is a global public health concern, affecting more than 840 million individuals worldwide ¹,². Progression to kidney failure, the end stage of CKD characterized by an estimated glomerular filtration rate (eGFR) <15 mL/min/1.73 m² or necessitating dialysis or kidney transplantation, stands as a major morbid complication of CKD ³,⁴. Kidney failure leads to substantial financial burdens at the societal level, as well as a notable decline in quality of life and an increased incidence of premature mortality at the individual level ³⁻⁵. Therefore, it is crucial to identify pathophysiological processes underlying CKD progression in order to develop effective strategies that target these harmful pathways to prevent or slow down disease progression.

Uremic toxins, solutes that accumulate in patients with CKD ⁶, have recently drawn attention in the nephrology community as potential modifiable risk factors of disease progression ⁷,⁸. For example, higher levels of uric acid, indoxyl sulfate and p-cresyl sulfate have been associated with an increased risk of CKD progression ⁹⁻¹⁵. Emerging evidence suggests that the kynurenine-pathway may be also involved in the progression of CKD ¹⁶.

The kynurenine pathway is the major route of tryptophan metabolism, leading to the formation of many biologically active agents including kynurenic acid (KA) ¹⁷,¹⁸. Kynurenine aminotransferase 2, is the common enzyme that catalyzes the transformation of kynurenine into KA. *In vitro* studies have shown that some kynurenine metabolites, including KA, affect mesangial cell proliferation and mitochondrial activity ¹⁹⁻²². Furthermore, previous studies have highlighted that several end-product metabolites of the kynurenine pathway exert strong biological effects through the aryl hydrocarbon receptor, potentially mediating renal fibrosis ²³,²⁴. However, very few experimental studies have evaluated the specific effect of KA on renal impairment ¹⁹,²⁰,²⁵.
Clinically, the association of KA with kidney failure has been rarely reported, and only in a small sample of CKD patients, in type 2 diabetes patients, in a cohort of African American adults without clinically significant kidney disease, or through measurement of urinary clearance of KA <sup>26-29</sup>. Therefore, no previous study has evaluated the association between serum KA and kidney failure in a large representative sample of pre-dialysis patients. Accordingly, this study aimed to evaluate the association between serum KA levels, the KA/kynurenine ratio (as an index of aminoadipate aminotransferase activity), and the progression of CKD to kidney failure in a large French cohort of pre-dialysis patients. Additionally, CKD mouse models and low-protein diets were used to investigate the enzyme involved in the production of these metabolites.

# Methods

## Cohort

## Study design and participants

The Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) is a large prospective cohort that enrolled 3 033 adult patients between July 2013 and April 2016 from 40 representative nephrology outpatient clinics in France. Briefly, the eligibility criteria were age 18 or over, a confirmed diagnosis of moderate or advanced CKD (eGFR <60 ml/min/1.73 m²), and no prior maintenance dialysis or kidney transplantation. All patients provided written informed consent to participate in the cohort and were included for five years of annual follow-up. Details of the study protocol have been published elsewhere <sup>30</sup>.

The CKD-REIN study was approved by the French National Institute of Health and Medical Research (INSERM, Paris, France) institutional review board (IRB00003888) and the Ethics Committee (CCTIRS12.360/CPP).
The present study included 2 406 patients who provided available biological samples within a
3-month window of inclusion (Figure 1).

Data collection

Data were collected by trained clinical research associates from medical records or patient
interviews at baseline and then annually. Upon enrolment of the patients, urine and serum
samples were collected. eGFR was calculated from serum creatinine and cystatin C using the
Chronic Kidney Disease - Epidemiology Collaboration (CKD-EPI) equation (2021) ³¹, and the
ACR was either measured or estimated by an equation based on proteinuria measurements.
More details concerning data collection are found in the Supplementary Methods.

Quantification of uremic toxins

Total and free fractions of KA, indoxyl sulfate, indole-3-acetic acid (IAA), and p-cresyl sulfate were assayed in serum using a validated liquid chromatography tandem mass spectrometry technique, as described in the Supplementary Methods ³². Free KA values were below the lower limit of quantification (LOQ) for most of the participants of CKD-REIN (<0.01mg/L), so we were not able to include the free fraction of KA in the analyses of the present study. The KA/kynurenine ratio included the free fraction of kynurenine given that this fraction was the active one to be metabolized into KA.

Outcome: progression to kidney failure

Our outcome of interest is any progression to kidney failure that will be defined as initiation of
chronic dialysis or pre-emptive transplantation whatever occurred first. These events were
traced from hospital and medical records and/or by linkage with the French National Renal
Epidemiology Information Network registry (REIN).
## Animal studies

Details concerning 5/6 Nephrectomy CKD Mouse Model and Adenine-Diet CKD Mouse Models are available in the Supplementary Methods and Supplementary References.

All experimental procedures were performed in accordance with the guidelines laid down by the French Ministry of Agriculture (n°2013-118) and the European Union Council Directive for the protection of animals used for scientific purposes of September 22nd, 2010 (2010/63UE). The study protocol was approved by the local ethics committee (reference APAFIS #38825-2022080515563596 v6 and #30603-2021012517248777 v3).

Details regarding measurement of diuresis and 24h proteinuria, gene expression analysis, renal histology or tissue and blood collection are available in the Supplementary Methods and Supplementary References.

## Statistical analysis

Participants' baseline characteristics are described for the overall sample (n = 2406) and by tertiles of serum KA levels. Continuous variables are presented as the median [interquartile range (IQR)] and compared between the three groups with the Kruskal-Wallis test. Categorical variables are presented as percentages and compared between groups with the Chi-square test. The variations of serum KA and KA/kynurenine ratio according to CKD stages are compared between groups with the Kruskal-Wallis test, and followed by a post-hoc analysis using Dunn's test (Supplementary Figure S1 and S2).

Given that the serum uremic toxins and urine albumin-to-creatinine ratio (ACR), either measured or estimated from protein-to-creatinine ratio ³³, values were not normally distributed they were log-transformed. We used cause-specific Cox models to estimate crude and adjusted hazard ratios (HRs) [95% CI] associated with KA levels and KA/kynurenine ratio. Kidney failure events were censored on the date of last follow-up (completion of 5 years of follow-up,
study withdrawal, or end of follow-up on December 31, 2020), or the date of death before
kidney failure.

Covariates known to be associated with kidney failure, or with KA and kidney failure were a
priori determined based on the literature review and biological plausibility<sup>26,34–38</sup>. A first model
was adjusted for age at baseline, sex, high-sensitivity C-reactive protein (CRP), smoking status,
history of acute kidney injury, serum urea, serum albumin, serum bicarbonate, hemoglobin,
history of cardiovascular disease, body mass index (BMI), diabetes, systolic blood pressure,
baseline eGFR, ACR, prescription of renin-angiotensin system inhibitors (RASi), proton pump
inhibitors (PPI), diuretics. A second model added indoxyl sulfate and IAA (as metabolites of
the indolic pathway derived from tryptophan metabolism and strongly associated with CKD
progression), and p-cresyl sulfate (already known to be associated with kidney failure)<sup>15,23</sup>.

The HRs of Cox models were transformed back into the original unlogged scales, in order to
obtain better interpretable values. Each model's validity (according to the proportional hazard
assumption) was checked by testing the Schoenfeld residuals. The method used to manage
missing data is presented in the Supplementary methods. Statistical analyses for the cohort were
performed with open source R software <sup>39</sup>.

For animal experiment, sample size was chosen on the basis of our earlier experience and no
statistical test was used for its predetermination. All quantitative data are expressed as the mean
± standard error (SEM) of the mean. Simple comparisons were performed using a two-tailed
Student's t test. Pearson correlation analysis was used to evaluate the correlation between
kynurenine metabolites and fibrosis-related genes and kidney fibrosis. Statistical analyses were
performed in GraphPad Prism 10 (GraphPad software, La Jolla, CA)
(https://www.graphpad.com).

In all analyses, the threshold for statistical significance was P < 0.05.
# Results

## Clinical characteristics of CKD participants

Table 1 presents the characteristics of the 2 406 patients included in this study, compared between the tertiles of KA levels. The median [Q1-Q3] age of the participants was 68 [60-76] years, 66% were men, and the median BMI was 27.9 [24.7-31.7] kg/m². The median systolic blood pressure was 140 [128-153] mmHg, 76% of the patients had RASi prescription at baseline and 52% had diuretics prescription at baseline. 23% of the patients had an history of acute kidney injury, about half of them presented a history of cardiovascular disease (52%), and 41% had diabetes. The overall median eGFR was 29 [21-39] ml/min/1.73 m², and was significantly lower in patients with the highest KA tertiles. The median ACR was 106 [22-492] mg/g, and was significantly higher in patients with the highest KA tertiles.

The distribution of serum KA levels and KA/kynurenine ratio by CKD stage are presented in the Supplementary Figures S1 and S2. KA levels and the KA/kynurenine ratio were significantly higher in more advanced CKD stages compared to stages 2 and 3.

## KA and KA/kynurenine ratio and kidney failure

Over a median [Q1-Q3] follow-up period of 5 [4.6-5.2] years, 608 out of the 2 406 patients progressed to kidney failure.

### Association with kynurenic acid

Serum KA levels were significantly associated with the progression of CKD to kidney failure, even after multiple adjustments (Table 2). A 2-fold increase in serum KA levels was associated with a 22%-increased hazard of kidney failure (adjusted HR [95% CI]: 1.22 [1.07, 1.4]), independently of age, sex, kidney function (evidenced through eGFR and ACR), indoxyl
sulfate, IAA, p-cresyl sulfate, RASi prescription and other factors known to be associated with kidney failure.

## Association with the ratio kynurenic acid/kynurenine

The crude analysis showed that a doubling of KA/kynurenine ratio was significantly associated with a 64%-increase in the hazard of kidney failure (HR [95% CI]: 1.64 [1.42, 1.89]; Table 3). This association was attenuated but remained significant after multiple adjustments (Table 3). A 2-fold increase in KA/kynurenine ratio was associated with a 20%-increased hazard of kidney failure (adjusted HR [95% CI]: 1.20 [1.08, 1.33]), independently of age, sex, eGFR, ACR, RASi prescription, serum IS and p-cresyl sulfate levels and other factors known to be associated with kidney failure.

## Aminoadipate aminotransferase gene expression and kidney fibrosis in CKD mice models

Given the association between the KA/kynurenine ratio (used as an indicator of aminoadipate aminotransferase activity) and CKD progression, we investigated aminoadipate aminotransferase expression in the kidneys of two mouse models. The 5/6 nephrectomy model induces an alteration of kidney function parameters and is associated with an increase in kynurenine and KA plasmatic levels (Table 4a and Figure 2 c). As shown in Figure 2 d, there was an increase in the gene expression of major fibrotic components, such as collagen α-1, in CKD mice compared to sham mice, along with a reduction in antioxidant enzymes and an increase in inflammatory markers. Consistent with the positive association of serum levels of KA and the KA/kynurenine ratio with CKD progression in humans, high blood levels of KA and the KA/kynurenine ratio are positively correlated with fibrotic markers and kidney dysfunction, and negatively correlated with antioxidant enzymes (Figure 2 e). Interestingly, the expression aminoadipate aminotransferase is significantly higher in CKD mice (Figure 2 d).
Pearson analysis showed a positive correlation between aminoadipate aminotransferase expression and KA/kynurenine ratio (Figure 2 e).

To further explore the relationship between aminoadipate aminotransferase and kidney progression, we measured its expression in the kidney during a nephroprotective diet consisting of a reduced protein intake (Figure 2 f). A low-protein diet in CKD mice was associated with a reduction in proteinuria and kidney fibrosis (Table 4b). Interestingly, a low-protein diet was associated with a reduction in plasmatic KA and the KA/kynurenine ratio, but not kynurenine and tryptophan (Figure 2 g), and a decrease in aminoadipate aminotransferase expression in the kidney as well as in inflammatory and fibrosis markers (Figure 2 h).

Discussion

The results of this large national cohort study of pre-dialysis patients showed that higher serum levels of KA and a higher KA/kynurenine ratio were independently associated with a higher incidence of CKD progression to kidney failure. These results were further supported by an animal study, demonstrating that high blood levels of KA and the KA/kynurenine ratio were positively correlated with fibrotic markers and kidney dysfunction, but negatively correlated with antioxidant enzymes. Furthermore, we found that aminoadipate aminotransferase expression and downstream metabolites (KA) are reduced in CKD mice fed by a nephroprotective diet (low-protein diet).

To the best of our knowledge, no previous observational studies have evaluated the association between KA/kynurenine ratio and CKD progression. Regarding the association between KA and kidney failure, results from previous studies are contradictory. Chen et al. 29 highlighted a significant association between lower clearance of KA and greater risks of CKD progression in pre-dialysis population. This was also investigated by a recent nested case-control study that found that each 50% lower clearance of KA was associated with 2.20-fold higher odds of eGFR
decline and kidney disease progression<sup>27</sup>. However, a recent study by Liu et al.<sup>26</sup> reported a significant association between plasma KA and disease progression in the inverse direction: higher plasma concentrations of KA were inversely associated with risk for kidney failure; nevertheless this study has been conducted in type 2 diabetes patients. In contrast, one previous nested case-control study failed to find significant differences in plasma KA between 40 fast progressors patients to kidney failure and 40 slow progressors. The significance of this study is however limited by a small sample size and a short follow-up period<sup>28</sup>.

To understand the renal parenchymal implications of changes in KA and KA/kynurenine, we performed molecular characterization in two different CKD mouse models. Only one previous study has evaluated the effect of UTs, including KA, on oxidative stress *in vitro* and *in vivo*<sup>20</sup>. This study demonstrated that KA increased the production of intracellular reactive oxygen species in proximal tubule cells, and induced the production of NLRP3 inflammasome and interleukin-1 beta. Given that the kidney is a highly active metabolic organ with an important mitochondrial oxidative activity, it is particularly susceptible to damage from oxidative stress that is then shown to accelerate renal tissue apoptosis and kidney disease progression<sup>20,40,41</sup>. Furthermore, several studies concluded that activation of aryl hydrocarbon receptor is involved in oxidative stress, renal pro-inflammatory phenotypes, renal fibrosis and glomerular damage<sup>19,23,42-45</sup>. Notably, kynurenine pathway metabolites are ligands of aryl hydrocarbon receptor, and KA is the strongest aryl hydrocarbon receptor ligand among them<sup>25,44,46</sup>. Therefore, we can reasonably assume the physiopathological effect of KA on kidney failure via aryl hydrocarbon receptor activation despite that no previous experimental study has evaluated that specific mechanism.

The present study is the first to evaluate the association between high KA/kynurenine ratio and kidney dysfunction in humans and in animals, showing a significant association between them. In fact, KA is a uremic toxin derived from kynurenine via the aminoadipate aminotransferase
enzyme of the KA branch (Figure 2 a). Accordingly, the KA/kynurenine ratio represents the KA branch of the kynurenine pathway and the enzymatic conversion of kynurenine into KA, which could form an interesting target to prevent CKD progression. Interestingly, our experimental study suggests that KA is not merely a consequence of passive accumulation, but also could result from the over activation of enzymes involved in its production. As previously observed in CKD rats ⁴⁷, we found an overexpression of aminoadipate aminotransferase in the kidneys under uremic conditions. In contrast, CKD mice treated with a low-protein diet showed a decrease in aminoadipate aminotransferase expression, leading to reduced KA levels (but not kynurenine) and improved renal function. Although we did not measure enzyme activity directly in this study or explore the consequences of aminoadipate aminotransferase inhibition, these findings suggest a key role for aminoadipate aminotransferase in kidney failure and identify it as a potential new therapeutic target.

Our study has several strengths. First, the present cohort study emphasizes for the first time on the association between KA/kynurenine and kidney failure, and is supported by an animal study. Second, this study included a large sample size of CKD patients that are nationally representative of nephrology practices in France with a sufficient follow-up period of 5 years. This ensured a sufficiently high statistical power and allowed for extensive adjustments for confounders (including eGFR, ACR, RASi). Third, uremic toxin assays were centralized using the validated ultra-high-performance liquid chromatography tandem mass spectrometry technique. Last, the statistical analysis of the data considered competitive risk events for our outcome.

It is important to keep in mind some limitations. First, we did not investigate the time-varying effect of serum KA levels on kidney failure. Second, our results might have been influenced by residual confounding, given that unknown risk factors might not have been included in our analyses. Nevertheless, we adjusted for many major parameters known to influence KA and
kidney failure, including serum kynurenine and the Kidney Failure Risk Equation (KFRE) predictors ³⁸. Third, although our models were adjusted for eGFR and ACR and included an experimental component, we were unable to confirm the direction of causation between KA and kidney failure—specifically, whether individuals with worse kidney function have higher KA levels. Our results remain hypothesis-generating, and future interventional studies are necessary to establish causality. Fourth, kynurenine is the precursor of many other metabolites besides KA, such as quinolinic acid, which might have a significant association with kidney failure ¹⁹. However, we could not evaluate this in the present study, nor compare the renal toxic effect between KA and these metabolites or other known biomarkers. Our study serves as an etiological evaluation rather than making predictive analyses, which will be necessary in future studies. Moreover, an external validation is also required to confirm the most reliable biomarker for CKD progression. Lastly, we cannot neglect some limitations of the experimental part of our study, such as missing controls (given that these are preliminary data), absence of protein assay or absence of the enzymatic activity measurement. These points need to be evaluated in future studies before concluding for the importance of inhibiting aminoadipate aminotransferase specifically. Moreover, the low-protein diet intervention was not highly specific; but it is currently the only option available to assess variations in metabolic pathways, and constituted an appropriate approach for our preliminary study.

In summary, this large study showed that higher serum KA levels and a higher KA/kynurenine ratio were associated with an elevated risk of progression to kidney failure in pre-dialysis patients. Our experimental study was a preliminary, hypothesis-generating study that highlights the importance of evaluating in the future the causal relationship between the kynurenine pathway and the progression to kidney failure. It would be interesting for future studies to further evaluate the results by infusing kynurenine into mice and assessing the use of pharmacological inhibitors of AADAT, such as PF-04859989, to reduce the KA/kynurenine
ratio, and explore the roles of other KAT isoenzymes (than aminoadipate aminotransferase) and question their implication. Assessing KA branch is a first significant step in the understanding of kynurenine metabolites' effect on kidney failure, pointing out its place as a potential future target to limit CKD progression. Future research should consider exploring the effect of other metabolites of the kynurenine pathway, and other uremic toxins that accumulate during CKD, on kidney failure. This is crucial in order to design the most adequate therapeutic interventions to prevent kidney failure, ultimately improving patient outcomes. It is however important to keep in mind that kidney failure is a complex condition with many and intermingled contributing factors.

**Data Sharing Statement**

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidential reasons of the national CKD-REIN study.

**Disclosure Statement**

C.E.C., S.L., I.A.L., M.C-A, L.F., C.L., Y-E.H, J-C.M, P.L., B.B., C.S., and J.-C.A. have nothing to disclose. N.A.D.P. coordinates the CKD-REIN cohort study, and received funding as indicated below. S.B. received grants from AstraZeneca, Vifor CSL, Amgen, BI Lilly, and Alexion. Z.A.M. report having received grants for CKD-REIN and other research projects from Amgen, Baxter, Fresenius Medical Care, GlaxoSmithKline, Merck Sharp & Dohme-Chibret, Sanofi-Genzyme, Lilly, Otsuka, AstraZeneca, Vifor and the French government, as well as fees and grants to charities from AstraZeneca, Boehringer Ingelheim, and GlaxoSmithKline. L.K. reports having received grants from Fresenius Kabi, Nestlé, Lallemand, AstraZeneca and consultancy or speaker fees or travel support from Astrazeneca, Lilly, Baxter, Bayer, and Fresenius Kabi. The sponsors had no role in the design, execution, interpretation, or writing of the study.

**Acknowledgements**

We thank Claudie PINTEUR for her help in the management of animal experiments. We acknowledge the CKD-REIN study coordination staff for their efforts in setting up the CKD-REIN cohort (Marie Metzger, Elodie Speyer, Céline Lange and all the clinical research associates) as well as the CKD-REIN clinical sites and investigators:
Alsace: Prs T. Hannedouche and B. Moulin (CHU, Strasbourg), Dr A. Klein (CH Colmar).
Aquitaine: Pr C. Combe (CHU, Bordeaux), Dr J.P. Bourdenx (Clinique St Augustin, Bordeaux),
Dr A. Keller, Dr C. Delclaux (CH, Libourne), Dr B. Vendrely (Clinique St Martin, Pessac), Dr
B. Deroure (Clinique Delay, Bayonne), Dr A. Lacraz (CH, Bayonne) Basse. Normandie: Dr T.
Lobbedez (CHU, Caen), Dr I. Landru (CH, Lisieux). Ile de France: Pr Z. Massy (CHU,
Boulogne—Billancourt), Pr P. Lang (CHU, Créteil), Dr X. Belenfant (CH, Montreuil), Pr E.
Thervet (CHU, Paris), Dr P. Urena (Clinique du Landy, St Ouen), Dr M. Delahousse (Hôpital
Foch, Suresnes). Languedoc—Roussillon: Dr C. Vela (CH, Perpignan). Limousin: Pr M. Essig,
Dr D. Clément (CHU, Limoges). Lorraine: Dr H. Sekhri, Dr M. Smati (CH, Epinal) Dr M.
Jamali, Dr B. Hacq (Clinique Louis Pasteur, Essey-les-Nancy), Dr V. Panescu, Dr M. Bellou
(Polyclinique de Gentilly, Nancy), Pr Luc Frimat (CHU, Vandœuvre-les-Nancy). Midi-
Pyrénées: Pr N Kamar (CHU, Toulouse). Nord-Pas-de-Calais: Prs C. Noël et F. Glowacki
(CHU, Lille), Dr N. Maisonneuve (CH, Valenciennes), Dr R. Azar (CH, Dunkerque), Dr M.
Hoffmann (Hôpital privé La Louvière, Lille). Pays-de-la Loire: Pr M. Hourmant (CHU,
Nantes), Dr A. Testa (Centre de dialyse, Rezé), Dr D. Besnier (CH, St Nazaire). Picardie: Pr G.
Choukroun (CHU, Amiens), Dr G. Lambrey (CH, Beauvais). Provence-Alpes—Côte d'Azur:
Pr S. Burtey (CHU, Marseille), Dr G. Lebrun (CH, Aix-en-Provence), Dr E. Magnant
(Polyclinique du Parc Rambot, Aix-en-Provence). Rhône-Alpes: Pr M. Laville, Pr D. Fouque
(CHU, Lyon-Sud) and L. Juillard (CHU Edouard Herriot, Lyon), Dr C. Chazot (Centre de rein
artificiel Tassin Charcot, Ste Foy-les-Lyon), Pr P. Zaoui (CHU, Grenoble), Dr F. Kuentz
(Centre de santé rénale, Grenoble).

The authors would like to thank the teams of all the biological resources centers (See the
supplement for the List of biological resources centers) that participated in the project: the
Biobanque de Picardie (BB-0033-00017), NeuroBioTec (BB-0033-00046), Centre de
ressources biologiques (CRB)-Centre Hospitalier Universitaire de Nantes Hôtel Dieu (BB-
0033–00040), CRB-Centre Hospitalier Universitaire Grenoble Alpes (BB-0033–00069), CRB-Centre Hospitalier Régional Universitaire de Nancy (BB-0033–00035), Service de Néphrologie, Centre Hospitalier de Perpignan, the Plateforme de Ressources Biologiques-Hôpital Henri Mondor (BB-0033–00021), the Centre d'Investigation Clinique Plurithématique CIC-1435, Plateforme de Ressources Biologiques-Hôpital européen Georges-Pompidou (BB-0033–00063), L'Etablissement Français du sang (EFS) Hauts de France—Normandie (Site de Bois-Guillaume, Site de Loos-Eurasanté), EFS Nouvelle Aquitaine (site Pellegrin), EFS Ile de France (Site Avicenne), EFS Occitanie (Site de Toulouse), EFS Grand-Est (Site de Colmar, Site de Metz), EFS PACA-Corse (Site de Marseille) (Supplementary Material).

# SUPPLEMENTARY MATERIAL

## Supplementary Methods

**Table S1.** Food composition of the diets

**Table S2.** Sequences primers

**Figure S1.** Distribution of kynurenic acid according to the stages of chronic kidney disease.

**Figure S2.** Distribution of kynurenic acid/kynurenine according to the stages of chronic kidney disease.

## List of biological resources centers

## Supplementary References

## STROBE checklist (PDF)

Supplementary information is available at KI Report's website.
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**Figure 1.** Flowchart of the study

**Figure 2.** Kidney fibrosis is associated with upregulation of *aminoadipate aminotransferase*

(a) Tryptophane pathway. AADAT: aminoadipate aminotransferase, IDO: Indoleamine 2,3-Dioxygenase; KMO:

Kynurenine 3-Monooxygenase; KYNU: Kynureninase; TDO: Tryptophan 2,3-Dioxygenase. (b) Chronogram of the experiment. (c) Concentrations of KA, kynurenine, tryptophan, and KA/ kynurenine ratio in the plasma expressed as fold change from the control group. (d) Relative mRNA expression for *Col1a1*, *IL-6*; *TNF alfa*, *Ccl2*,
Nqo1, Sod2, Gp9, Gpx4, Cat and AADAT in the kidney (n=5-17). (e) Heatmap showing the Pearson correlation coefficients between the concentration of KA, kynurenine and ratio KA/ kynurenine and kidney function parameters (n=3-10). (f) Chronogram of the experiment. (g) Concentrations of KA, kynurenine, tryptophan, and the KA/kynurenine ratio in the plasma expressed as fold change from the control group. (h) Relative mRNA expression for Coll1a1, IL-6; TGF beta and AADAT in the kidney (n=5). * P < 0.05, ** P < 0.01, *** P < 0.001 and **** P < 0.0001 correspond to significant differences between groups by unpaired Student's t test.

<table><caption>Table 1. Characteristics of the study population according to the tertiles of serum kynurenine acid</caption><thead><tr><th rowspan="2">Characteristics</th><th rowspan="2">Total</th><th colspan="3">Tertiles of serum kynurenine acid (mg/L)</th><th rowspan="2">P-value<sup>2</sup></th><th rowspan="2">Missing data</th></tr><tr><th>N = 2 406<sup>1</sup></th><th>T1 &lt;0.024 (n=759)<sup>1</sup></th><th>T2 [0.024, 0.04] (n=831)<sup>1</sup></th><th>T3 &gt;=0.04 (n=816)<sup>1</sup></th></tr></thead><tbody><tr><td>Age at baseline (years)</td><td>68 [60-76]</td><td>69 [62-75]</td><td>68 [61-76]</td><td>67 [59-76]</td><td>0.2</td><td>0%</td></tr><tr><td>Men</td><td>66%</td><td>65%</td><td>65%</td><td>68%</td><td>0.5</td><td>0%</td></tr><tr><td>eGFR at baseline (ml/min/1.73m<sup>2</sup>)</td><td>29 [21-39]</td><td>37 [30-46]</td><td>29 [23-37]</td><td>22 [17-29]</td><td><strong>&lt;0.0001</strong></td><td>0.5%</td></tr><tr><td>Albumin-to-creatinine ratio (mg/g)</td><td>106 [22-492]</td><td>45 [13-243]</td><td>102 [20-477]</td><td>272 [46-770]</td><td><strong>&lt;0.0001</strong></td><td>11.5%</td></tr><tr><td>History of acute kidney injury</td><td>23%</td><td>20%</td><td>23%</td><td>27%</td><td><strong>0.015</strong></td><td>7.2%</td></tr><tr><td>Smoking status</td><td></td><td></td><td></td><td></td><td>0.9</td><td></td></tr><tr><td>Never-smoker</td><td>40%</td><td>42%</td><td>39%</td><td>40%</td><td></td><td></td></tr><tr><td>Current smoker</td><td>13%</td><td>12%</td><td>13%</td><td>12%</td><td></td><td>0.6%</td></tr><tr><td>Former smoker</td><td>47%</td><td>47%</td><td>48%</td><td>47%</td><td></td><td></td></tr><tr><td>Systolic blood pressure (mmHg)</td><td>140 [128-153]</td><td>140 [127-153]</td><td>139 [128-154]</td><td>140 [130-153]</td><td>0.6</td><td>0.5%</td></tr><tr><td>Diabetes mellitus</td><td>41%</td><td>42%</td><td>40%</td><td>42%</td><td>0.7</td><td>0.2%</td></tr><tr><td>Dyslipidemia</td><td>74%</td><td>71%</td><td>76%</td><td>73%</td><td>0.08</td><td>0.4%</td></tr><tr><td>History of cardiovascular disease</td><td>52%</td><td>54%</td><td>52%</td><td>50%</td><td>0.3</td><td>0.5%</td></tr><tr><td>Serum bicarbonate (mmol/L)</td><td>25 [23-27]</td><td>25.5 [23.5-28]</td><td>25 [23-27]</td><td>24 [22-26]</td><td><strong>&lt;0.0001</strong></td><td>8.8%</td></tr><tr><td>Serum albumin (g/L)</td><td>40.4 [38-43]</td><td>40 [38-43]</td><td>40.6 [38-43]</td><td>40.5 [37.5-43]</td><td>0.3</td><td>14.5%</td></tr></tbody></table>
<table><tr><td>Hemoglobin (g/dL)</td><td>13 [11.8-14.2]</td><td>13.3 [12.2-14.4]</td><td>13 [11.9-14.5]</td><td>12.7 [11.5-13.8]</td><td><strong>&lt;0.0001</strong></td><td>0.9%</td></tr><tr><td>High-sensitivity C-reactive protein (mg/L)</td><td>2.4 [1.1-5.1]</td><td>2.3 [1.1-5]</td><td>2.4 [1.1-4.9]</td><td>2.4 [1.1-5.3]</td><td>0.9</td><td>5.4%</td></tr><tr><td>Body mass index (kg/m<fnref n="2" />)</td><td>27.9 [24.7-31.7]</td><td>27.7 [24.6-31.6]</td><td>27.8 [24.6-31.5]</td><td>28.2 [24.9-31.2]</td><td>0.2</td><td>1.9%</td></tr><tr><td>PPI prescription at baseline</td><td>32%</td><td>34%</td><td>32%</td><td>32%</td><td>0.5</td><td>0.2%</td></tr><tr><td>Diuretics prescription at baseline</td><td>52%</td><td>50%</td><td>53%</td><td>58%</td><td><strong>0.002</strong></td><td>0.3%</td></tr><tr><td>RASi prescription at baseline</td><td>76%</td><td>76%</td><td>78%</td><td>75%</td><td>0.5</td><td>0.3%</td></tr><tr><td>Serum urea (mmol/L)</td><td>12.6 [9.5-17]</td><td>10.3 [8.2-13.3]</td><td>12.5 [9.7-16.3]</td><td>15.7 [11.9-20.5]</td><td><strong>&lt;0.0001</strong></td><td>6%</td></tr><tr><td>Kynurenic acid (mg/L)</td><td>0.03 [0.02-0.04]</td><td>0.02 [0.01-0.02]</td><td>0.03 [0.027-0.034]</td><td>0.05 [0.04-0.06]</td><td>-</td><td>0%</td></tr><tr><td>Kynurenic acid/kynurenine</td><td>0.24 [0.16-0.35]</td><td>0.16 [0.11-0.23]</td><td>0.25 [0.18-0.34]</td><td>0.34 [0.24-0.48]</td><td><strong>&lt;0.0001</strong></td><td>0%</td></tr></table>

<table><caption>Table 2. Hazard ratio of progression to kidney failure associated with a 2-fold increase in baseline serum kynurenic acid level (mg/L).</caption><thead><tr><td></td><td>Kynurenic acid (mg/L)</td><td>P-value</td></tr></thead><tbody><tr><td>Unadjusted HR [95% CI] – p-value</td><td>2.8 [2.56, 3.16]</td><td><strong>&lt;0.0001</strong></td></tr><tr><td>Adjusted HR<fnref n="1" /> [95% CI] – p-value</td><td>1.24 [1.09, 1.41]</td><td><strong>0.0006</strong></td></tr><tr><td>Adjusted HR<fnref n="2" /> [95% CI] – p-value</td><td>1.22 [1.07, 1.4]</td><td><strong>0.002</strong></td></tr></tbody></table>

<footnote n="1">¹ Median [Q1-Q3]; %</footnote>

<footnote n="2">² Kruskal-Wallis rank sum test; Pearson's Chi-squared test
eGFR: estimated glomerular filtration rate; PPI: proton pump inhibitor; RASi: renin-angiotensin system inhibitors.</footnote>

<footnote n="1">¹Model adjusted for age at baseline, sex, smoking status, CRP, history of acute kidney injury, urea, serum albumin, serum bicarbonate, hemoglobin, history of cardiovascular disease, BMI, diabetes, systolic blood pressure, baseline eGFR, ACR, use of RASi, PPI, diuretics.</footnote>

<footnote n="2">² 2+ serum free indoxyl sulfate, indole-3-acetic acid and p-Cresyl Sulfate.</footnote>
<table><caption>Table 3. Hazard ratio of progression to kidney failure associated with a 2-fold increase in baseline KA/kynurenine ratio.</caption><thead><tr><th></th><th>KA/kynurenine ratio</th><th>P-value</th></tr></thead><tbody><tr><td>Unadjusted HR [95% CI] – p-value</td><td>1.64 [1.42, 1.89]</td><td><strong>&lt;0.0001</strong></td></tr><tr><td>Adjusted HR<sup>1</sup> [95% CI] – p-value</td><td>1.19 [1.07, 1.32]</td><td><strong>0.0006</strong></td></tr><tr><td>Adjusted HR<sup>2</sup> [95% CI] – p-value</td><td>1.20 [1.08, 1.33]</td><td><strong>0.0003</strong></td></tr></tbody></table>

<table><caption>Table 4a : Renal parameters in sham and CKD mice</caption><thead><tr><th></th><th>Sham</th><th>CKD</th><th>p-value</th></tr></thead><tbody><tr><td>N</td><td>5</td><td>16</td><td></td></tr><tr><td>Urea (mM)</td><td>9.46 ± 1.66</td><td>25.4 ± 1.89</td><td>&lt;0.0001</td></tr><tr><td>Urine protein/creatinine ratio</td><td>1.66 ± 0.46</td><td>2.7 ± 0.43</td><td>0.076</td></tr><tr><td>Renal fibrosis% area</td><td>4.51 ± 0.21</td><td>10.0 ± 1.29</td><td>0.0157</td></tr></tbody></table>

Data are expressed as mean ± SEM.

<table><caption>Table 4b : Renal parameters in CKD mice under show diet and low protein diet (LPD)</caption><thead><tr><th></th><th>Show</th><th>CKD-LPD</th><th>p-value</th></tr></thead><tbody><tr><td>N</td><td>5</td><td>5</td><td></td></tr><tr><td>Urea (mM)</td><td>22.8 ± 1.42</td><td>5.26 ± 1.07</td><td>&lt;0.0001</td></tr><tr><td>Urine protein/creatinine ratio</td><td>2.1 ± 0.07</td><td>0.61 ± 0.20</td><td>&lt;0.0001</td></tr><tr><td>Renal fibrosis% area</td><td>3.8 ± 0.56</td><td>2.39 ± 0.48</td><td>0.0421</td></tr></tbody></table>

Data are expressed as mean ± SEM.

<footnote n="1">¹Model adjusted for age at baseline, sex, smoking status, CRP, history of acute kidney injury, urea, serum albumin, serum bicarbonate, hemoglobin, history of cardiovascular disease, BMI, diabetes, systolic blood pressure, baseline eGFR, ACR, use of RASi, PPI, diuretics.</footnote>

<footnote n="2">² 1+ serum free indoxyl sulfate, indole-3-acetic acid and p-Cresyl Sulfate.</footnote>
Total participants in
the CKD-REIN study,
**n=3 033**

Patients with available samples to
measure uremic toxins at baseline,
**n=2 675**

Excluded:

- date of sampling greater than 3 months
from the date of inclusion, **n=268**

- empty biobank tube, **n=1**

Total included patients, **n=**
**2 406**
a

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c

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d

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e

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f

<figure><img src="image_7.png" /></figure>

g

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h

<figure><img src="image_9.png" /></figure>