Elevated BICD2 DNA methylation in blood of major depressive disorder patients and reduction of depressive-like behaviors in hippocampal Bicd2-knockdown mice

Major depressive disorder (MDD) is a prevalent and devastating mental illness. To date, the diagnosis of MDD is largely dependent on clinical interviews and questionnaires and still lacks a reliable biomarker. DNA methylation has a stable and reversible nature and is likely associated with the course and therapeutic efficacy of complex diseases, which may play an important role in the etiology of a disease. Here, we identified and validated a DNA methylation biomarker for MDD from four independent cohorts of the Chinese Han population. First, we integrated the analysis of the DNA methylation microarray (n = 80) and RNA expression microarray data (n = 40) and identified BICD2 as the top-ranked gene. In the replication phase, we employed the Sequenom MassARRAY method to confirm the DNA hypermethylation change in a large sample size (n = 1,346) and used the methylation-sensitive restriction enzymes and a quantitative PCR approach (MSE-qPCR) and qPCR method to confirm the correlation between DNA hypermethylation and mRNA down-regulation of BICD2 (n = 60). The results were replicated in the peripheral blood of mice with depressive-like behaviors, while in the hippocampus of mice, Bicd2 showed DNA hypomethylation and mRNA/protein up-regulation. Hippocampal Bicd2 knockdown demonstrates antidepressant action in the chronic unpredictable mild stress (CUMS) mouse model of depression, which may be mediated by increased BDNF expression. Our study identified a potential DNA methylation biomarker and investigated its functional implications, which could be exploited to improve the diagnosis and treatment of MDD.

Automated summary

Major depressive disorder (MDD) is a prevalent and devastating mental illness. The diagnosis of MDD currently lacks reliable biomarkers. This study identified and validated a potential DNA methylation biomarker for MDD in the Chinese Han population, and investigated its functional implications, which could improve the diagnosis and treatment of MDD.