Thomas Bernd Dschietzig1,2, Karl-Heinz Kellner3, Katrin Sasse4, Felix Boschann4, Robert Klüsener4, Jana Ruppert5, Franz Paul Armbruster5, Dragic Bankovic6, Andreas Meinitzer7, Veselin Mitrovic8, Christoph Melzer4. 1. Immundiagnostik AG, Bensheim, Germany, thomas.dschietzig@t-online.de. 2. Department of Cardiology and Angiology, Campus Mitte, Charité University Medicine Berlin, Berlin, Germany, thomas.dschietzig@t-online.de. 3. Neuroimmun GmbH, Karlsruhe, Germany. 4. Department of Cardiology and Angiology, Campus Mitte, Charité University Medicine Berlin, Berlin, Germany. 5. Immundiagnostik AG, Bensheim, Germany. 6. Department of Mathematical Sciences, State University of Novi Pazar, Novi Pazar, Serbia. 7. Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria. 8. Kerckhoff Clinic, Bad Nauheim, Germany.
Abstract
BACKGROUND: Kynurenine, a metabolite of the L-tryptophan pathway, plays a pivotal role in neuro-inflammation, cancer immunology, and cardiovascular inflammation, and has been shown to predict cardiovascular events. OBJECTIVES: It was our objective to increase the body of data regarding the value of kynurenine as a biomarker in chronic heart failure (CHF). METHODS: We investigated the predictive value of plasma kynurenine in a CHF cohort (CHF, n = 114); in a second cohort of defibrillator carriers with CHF (AICD, n = 156), we determined clinical and biochemical determinants of the marker which was measured by enzyme immunoassay. RESULTS: In the CHF cohort, both kynurenine and NT-proBNP increased with NYHA class. Univariate binary logistic regression showed kynurenine to predict death within a 6-month follow-up (OR 1.43, 95% CI 1.03-2.00, p = 0.033) whereas NT-proBNP did not contribute significantly. Kynurenine, like NT-proBNP, was able to discriminate at a 30% threshold of left ventricular ejection fraction (LVEF; AUC-ROC, both 0.74). Kynurenine correlated inversely with LVEF (ϱ = -0.394), glomerular filtration fraction (GFR; ϱ = -0.615), and peak VO2 (ϱ = -0.626). Moreover, there was a strong correlation of kynurenine with NT-proBNP (ϱ = 0.615). In the AICD cohort, multiple linear regression analysis demonstrated highly significant associations of kynurenine with GFR, hsCRP, and tryptophan, as well as a significant impact of age. CONCLUSIONS: This work speaks in favor of kynurenine being a new and valuable biomarker of CHF, with particular attention placed on its ability to predict mortality and reflect exercise capacity.
BACKGROUND:Kynurenine, a metabolite of the L-tryptophan pathway, plays a pivotal role in neuro-inflammation, cancer immunology, and cardiovascular inflammation, and has been shown to predict cardiovascular events. OBJECTIVES: It was our objective to increase the body of data regarding the value of kynurenine as a biomarker in chronic heart failure (CHF). METHODS: We investigated the predictive value of plasma kynurenine in a CHF cohort (CHF, n = 114); in a second cohort of defibrillator carriers with CHF (AICD, n = 156), we determined clinical and biochemical determinants of the marker which was measured by enzyme immunoassay. RESULTS: In the CHF cohort, both kynurenine and NT-proBNP increased with NYHA class. Univariate binary logistic regression showed kynurenine to predict death within a 6-month follow-up (OR 1.43, 95% CI 1.03-2.00, p = 0.033) whereas NT-proBNP did not contribute significantly. Kynurenine, like NT-proBNP, was able to discriminate at a 30% threshold of left ventricular ejection fraction (LVEF; AUC-ROC, both 0.74). Kynurenine correlated inversely with LVEF (ϱ = -0.394), glomerular filtration fraction (GFR; ϱ = -0.615), and peak VO2 (ϱ = -0.626). Moreover, there was a strong correlation of kynurenine with NT-proBNP (ϱ = 0.615). In the AICD cohort, multiple linear regression analysis demonstrated highly significant associations of kynurenine with GFR, hsCRP, and tryptophan, as well as a significant impact of age. CONCLUSIONS: This work speaks in favor of kynurenine being a new and valuable biomarker of CHF, with particular attention placed on its ability to predict mortality and reflect exercise capacity.
Authors: Abbas F Almulla; Thitiporn Supasitthumrong; Chavit Tunvirachaisakul; Ali Abbas Abo Algon; Hussein K Al-Hakeim; Michael Maes Journal: BMC Infect Dis Date: 2022-07-15 Impact factor: 3.667
Authors: Cristina Razquin; Miguel Ruiz-Canela; Estefania Toledo; Pablo Hernández-Alonso; Clary B Clish; Marta Guasch-Ferré; Jun Li; Clemens Wittenbecher; Courtney Dennis; Angel Alonso-Gómez; Montse Fitó; Liming Liang; Dolores Corella; Enrique Gómez-Gracia; Ramon Estruch; Miquel Fiol; Jose Lapetra; Lluis Serra-Majem; Emilio Ros; Fernando Aros; Jordi Salas-Salvadó; Frank B Hu; Miguel A Martínez-González Journal: Am J Clin Nutr Date: 2021-11-08 Impact factor: 8.472