The IR-Homeostat Hypothesis: Intron Retention as an Evolutionarily Conserved Fine-Tuning Layer and a Reversible Blood Biomarker of Homeostatic Dysregulation in Mood Disorders

Major depressive disorder (MDD) lacks reliable laboratory tests for diagnosis and treatment monitoring, underscoring the need for robust molecular readouts in blood. Beyond symptom-based classification, MDD can also be viewed as a condition involving impaired homeostatic regulation across stress-responsive, immune, metabolic, and neural systems. Consistent with this perspective, altered intron retention (IR) patterns have been observed in peripheral blood in depression-related and treatment-response contexts, supporting the translational relevance of this RNA-processing layer to mood disorders. A key observation underpinning this review is that IR can function as a reversible, intervention-responsive readout of physiological state. In a pre-symptomatic stress-like state in klotho mutant mice (a premature-aging model), widespread IR increases revert toward a healthy pattern upon treatment, suggesting that IR is embedded in a controllable homeostatic layer. Against the backdrop of limited cross-cohort transferability of differential gene expression (DGE) signatures, we propose that IR provides a mechanistically grounded biomarker layer because it reports regulated RNA processing states rather than context-fragile abundance endpoints. We operationalize IR as a post-transcriptional “throttle” on effective gene output, with increased IR/detained intron (DI) states acting as a reversible brake and decreased IR acting as an accelerator that increases translation-competent mRNA supply. Mechanistic exemplars across immune, metabolic, and neuronal systems (e.g., IFNG, OGT, MAT2A, neuronal activity-triggered intron excision, and intron detention-mediated stemness/differentiation switching in adult neural stem cells) show that defined inputs can switch IR/DI states to tune output kinetics. Integrating these findings, we propose an “Intron Retention Homeostat” (IR-Homeostat) model in which cells sense deviations from physiological set points and implement feedback control of gene output through switchable IR/DI regulation. This framework positions IR not only as a robust state readout for stratification, treatment response prediction, and pharmacodynamic profiling, but also as a tractable entry point to identify the molecular sensors and mediators that couple homeostatic signals to RNA processing control.