Serum BICC1 levels are significantly different in various mood disorders

Mood disorders are recurrent chronic disorders with fluctuating mood states and energy, and misdiagnosis is common when based solely on clinical interviews because of overlapping symptoms. Because misdiagnosis may lead to inappropriate treatment and poor prognosis, finding an easily implemented objective tool for the discrimination of different mood disorders is very necessary and urgent. However, there has been no accepted objective tool until now. Recently, BICC1 has been identified as a candidate gene relating to major depressive disorder (MDD). Therefore, the aim of this study is to evaluate the ability of serum BICC1 to discriminate between various mood disorders, including MDD and the manic and depressive phases of bipolar disorder, namely bipolar mania (BM) and bipolar depression (BD).

Serum BICC1 levels in drug-free patients with MDD (n=30), BM (n=30), and BD (n=13), and well-matched healthy controls (HC, n=30) were measured with ELISA kits. Pearson correlation analyses were used to analyze the correlations between serum BICC1 levels and clinical information. Receiver operating characteristic (ROC) curve analysis was used to analyze the differential discriminative potential of BICC1 for different mood disorders.

One-way ANOVA indicated that serum BICC1 levels were significantly increased in all patient groups compared with the HC group and significantly different between each pair of patient groups. Correlation analyses found no relationship between serum BICC1 levels and any clinical variables in any study group. ROC curve analysis showed that serum BICC1 could discriminate among all three mood disorders from each other accurately with fair-to-excellent discriminatory capacity (area under the ROC curve from 0.787 to 1.0).

The findings of this preliminary study indicated significant differences in serum BICC1 levels in patients with different mood disorders. This study provides preliminary evidence that serum BICC1 may be regarded as a promising, objective, easy-to-use tool for diagnosing different mood disorders.