Receptor–Mitochondria Crosstalk in the Kynurenine Metabolic Pathway: Integrating Metabolomics and Clinical Mass Spectrometry

Mitochondria orchestrate energy transfer, redox poise, and cell fate. Within this landscape, tryptophan catabolism yields kynurenines (KYNs), a versatile metabolite shaping organelle function. Emerging studies implicate G protein–coupled receptor 35 (GPR35), the aryl hydrocarbon receptor (AhR), and N-methyl-D-aspartate (NMDA) receptors as conduits between extracellular cues and adenosine 5′-triphosphate (ATP) maintenance, calcium handling, mitophagy, and inflammasome restraint. Parallel work links quinolinate driven de novo nicotinamide adenine dinucleotide (NAD⁺) synthesis to tricarboxylic cycle (TCA) control and sirtuin programs across tissues. Yet the field lacks an integrated view that connects receptor pharmacology to NAD⁺ economics and respiration, and it lacks single run clinical assays that quantify both KYN and TCA nodes. This review addresses those gaps by mapping receptor specific mitochondrial mechanisms of KYNA, delineating pathway–cycle crosstalk, and appraising unified liquid chromatography–mass spectrometry (LC–MS) strategies for simultaneous quantification. We synthesize evidence for mitochondrial GPR35 signaling that preserves ATP, AhR programs that tune mitophagy and oxidative defenses, and NMDA antagonism that limits excitotoxic stress. These mechanisms are integrated with quinolinate dependent NAD⁺ biogenesis and α-ketoglutarate checkpoints, then benchmarked against chromatographic and ionization solutions suitable for clinical workflows. Here we highlight a receptor to organelle axis that couples KYN metabolism flux to respiratory control and offer a practical roadmap for standardized, single run LC–MS panels. The framework can sharpen target validation in ischemia, neurodegeneration, psychiatry, and oncology, while de-risking biomarker qualification through harmonized analytics. More broadly, resolving temporal dynamics, compartmental signaling, and cross matrix comparability will accelerate movement from association to intervention and enable decision grade metrics for patient selection, pharmacodynamic readouts, and therapeutic design.