Vitamin D and Depression: Systematic Review and Bayesian Meta-analysis of Mendelian Randomization Evidence
Description
Background: Observational links between low 25(OH)D and depression may reflect confounding or reverse causation. Methods: We systematically reviewed Mendelian-randomization (MR) studies through November 2024, appraising instrument strength, pleiotropy safeguards, bidirectionality, and dose–response/nonlinearity; certainty was graded using an MR-adapted GRADE framework. Because of between-study heterogeneity and scale differences, we did not perform conventional frequentist pooling. Instead, we conducted a de novo Bayesian random-effects meta-analysis of study-level MR estimates (harmonized to log-odds per 10 nmol/L where possible) and synthesized available nonlinear contrasts. Results: Sixteen studies met inclusion criteria. Most linear MR estimates were null or near-null. Method-dependent signals appeared under correlated-instrument models and in low-quantile/nonlinear analyses. Bidirectional MR more often supported the reverse direction (depression → lower 25(OH)D). Certainty for nonlinearity was downgraded owing to missing stratum-level instrument strength and incomplete multiplicity control. In the Bayesian meta-analysis, the pooled average effect suggested a small protective association of higher 25(OH)D with depression risk (OR ≈ 0.988 per 10 nmol/L; posterior P [μ < 0] = 0.997). Available nonlinear syntheses indicated stronger benefit at low 25(OH)D with flattening beyond ~50–60 nmol/L. Conclusions: Current MR evidence does not support a large population-wide linear effect of 25(OH)D on depression. Any average effect appears small; signals confined to severely deficient strata should be considered hypothesis-generating and require replication across methods, datasets, and ancestries. Universal supplementation for depression prevention is not supported; testing and correction of marked deficiency remain reasonable. Keywords: Vitamin D; Depression; Mendelian Randomization; Systematic Review; Threshold Effect; Causal Inference
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This work was supported by the National Natural Science Foundation of China (81573150), Military Key Discipline Construction Projects of China (HL21JD1206), the Project of Naval Medical University (2022MS002), and Natural Science Research Project from Jiading District, Shanghai (JDKW-2024-0013).