Kynurenine pathway metabolites as potential biomarkers in age-related macular degeneration: an ELISA-based...

Age-related macular degeneration (AMD), in which oxidative stress, inflammation and metabolic imbalances play a role in its pathogenesis, is one of the leading causes of irreversible vision loss. The kynurenine (KYN) pathway, one of the principal routes of tryptophan (TRP) metabolism, constitutes an important mechanism in retinal neurodegeneration. Based on this information, our study aimed to compare the serum TRP, KYN, kynurenic acid (KYNA), 3-hydroxykynurenine (3HK), 3-hydroxyanthranilic acid (3HAA) and, quinolinic acid (QA) levels of AMD patients and to investigate the diagnostic values ​​of these biomarkers.

Serum samples were collected from AMD patients and control groups. TRP, KYN, KYNA, 3HK, 3HAA, and QA levels were measured using a commercial ELISA method. KYN pathway activity, KYN/TRP and, KYNA/3HK ratios were also assessed. Mann-Whitney U test, ROC analysis, Spearman correlation were applied for statistical comparisons.

According to our results, 3HK was significantly higher in the AMD group, while TRP, KYN, QA, and KYNA/3HK ratio were higher in the control. ROC analysis revealed 3HK to be the strongest discriminatory marker. The KYNA/3HK ratio also provided significant diagnostic value. Correlation analysis revealed strong negative correlations between 3HK and KYN, QA, and especially KYNA/3HK. Conversely, strong positive correlations were found between KYN and KYNA/3HK, and between TRP, KYN, QA, and KYNA.

KYN pathway metabolites exhibit significant alterations in patients with AMD. 3HK levels and the reduction of the KYNA/3HK ratio suggest a disruption of the neurotoxic-neuroprotective balance and imply that KYN pathway dysfunction may play a role in the pathogenesis of AMD. Among the biomarkers examined, 3HK displayed the highest diagnostic performance, while the KYNA/3HK ratio emerged as an additional biological indicator. These findings indicate that 3HK and the KYNA/3HK ratio may serve as potential biomarker candidates for the early diagnosis and monitoring of AMD.