Depression is increasingly understood as a disorder of neuroimmune and synaptic dysregulation. Vitamin D deficiency (VDD), common in patients with depression, has been associated with inflammatory imbalance and poorer clinical outcomes, but the mechanisms linking VDD to circuit-level pathology remain incompletely defined. In this review, we examine evidence that VDD may influence depression-relevant neurobiology through two interacting routes. First, reduced vitamin D signaling may weaken complement restraint, favoring C3-associated microglial synaptic remodeling and pathological pruning. Second, altered vitamin D binding protein (VDBP) biology may engage neuronal megalin-SRC signaling, contributing to neuronal stress and excitatory-inhibitory disequilibrium. We further consider how these routes may intersect with VDR- and Sirt6-related regulatory programs, gut-brain inflammatory signaling, and biomarker heterogeneity. Rather than advancing a single definitive mechanism, this review offers an integrative neuroimmune interpretation that helps organize fragmented findings and identify testable questions. A key implication is that inconsistent effects of vitamin D supplementation in depression may partly reflect biological heterogeneity rather than uniform inefficacy. Future work should test whether composite panels integrating 25(OH)D, complement-related markers, inflammatory indices, and VDBP-associated measures can improve mechanistic stratification and guide biomarker-enriched studies of vitamin D-related interventions in depression. Legend: Conceptual summary of the candidate neuroimmune mechanisms discussed in this review. Vitamin D deficiency (VDD) is depicted as an upstream state that may contribute to depression-related synaptic pathology and circuit dysfunction through two interacting pathways: (1) complement-associated microglial synaptic remodeling and (2) VDBP–megalin-related neuronal stress signaling. The dashed connector indicates candidate cross-talk rather than an established feedforward mechanism. This graphical abstract summarizes a hypothesis-generating framework and does not imply quantitative effect size, causal certainty, or a clinical decision algorithm.
Yang et al. (Wed,) studied this question.