Potential metabolic monitoring indicators of suicide attempts in first episode and drug naive young patients with major depressive disorder: a cross-sectional study

• Main Authors: Ke Zhao, Siyao Zhou, Xiang Shi, Jianjun Chen, Yaoyao Zhang, Kaili Fan, Xiangyang Zhang, Wei Wang, Wei Tang
• Format: Article
• Language: English
• Published: BMC 2020-07-01
• Series: BMC Psychiatry
• Subjects: Major depressive disorder; Suicide attempt; Metabolism; Biomarker
• Online Access: http://link.springer.com/article/10.1186/s12888-020-02791-x

Abstract Backgrounds Major depressive disorder is an ordinary mental disorder, and suicide is considered to be a major concern among patients with MDD. Previous studies focused on the relationship between suicide attempts and metabolism in elderly patients with MDD, while ignore the young people. The aim of this study is to find the potential relationship between suicide attempts and metabolism in young patients with MDD to find a way to prevent and ultimately reduce suicide in young patients with MDD. Methods Cross-sectional design was employed in the study.740 patients aged between 18 and 45 years old with MDD had been consecutively recruited in this study between 2011 and 2017, 128 of whom had suicide attempts. Their serum samples used to monitor fasting blood glucose, serum lipids as well as socio-demographic characteristics were collected. Besides, some clinical scales were also employed to measure symptoms of anxiety, depression and other conditions. Results This study indicated that compared with non-suicide attempters, suicide attempters in young patients with MDD showed higher levels of FBG, TC, LDL-C (all p <  0.05) and lower levels of HDL-C(p <  0.001). Further logistic regression analysis suggested that suicide attempts were associated with increased FBG, decreased HDL-C, the course of disease, HAMD scores and obvious anxiety. Conclusions Suicide attempts in young patients with MDD may be predicted by metabolic levels in the future. And our findings suggested that the level of FBG and HDL-C can be promising biomarkers to predict the occurrence of this event.