Dataset Information

Common variants in FKBP5 gene and major depressive disorder (MDD) susceptibility: a comprehensive meta-analysis.

ABSTRACT: Previous studies have investigated the association between common variants in FKBP5 and MDD; however, the results remain inconsistent. In order to conduct a comprehensive meta-analysis of the association between FKBP5 variants and MDD risk, seven studies involving 26582 subjects, including 12491 cases with MDD and 14091 controls, were enrolled totally. Four common SNPs (rs1360780, rs4713916, rs3800373 and rs755658) with complete data from two or more studies were analyzed. In the total sample, there was no evidence of a significant association between MDD and any of the four SNPs using a random-effects model. However, after removing one heterogeneous German study, as indicated by sensitivity analysis, both the rs1360780 T-allele (Z?=?2.95, P?=?0.003, OR?=?1.06, 95% CI?=?1.02-1.11) and the rs3800373 C-allele (Z?=?3.05, P?=?0.002, OR?=?1.07, 95% CI 1.02-1.12) were significantly associated with MDD in a fixed-effect model. Our study thus provides support for an association between specific FKBP5 genetic variants and MDD risk. Rs4713916 was not significantly associated with MDD; However, this analysis had limited statistical power and larger sample sizes are required to further validate this result. Future research should also investigate possible gender- and ethnicity-specific differences in the association between FKBP5 and MDD.

SUBMITTER: Rao S

PROVIDER: S-EPMC5013409 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Common variants in FKBP5 gene and major depressive disorder (MDD) susceptibility: a comprehensive meta-analysis.

Rao Shuquan S Yao Yao Y Ryan Joanne J Li Tao T Wang Duan D Zheng Chuan C Xu Yong Y Xu Qi Q

Scientific reports 20160907

Previous studies have investigated the association between common variants in FKBP5 and MDD; however, the results remain inconsistent. In order to conduct a comprehensive meta-analysis of the association between FKBP5 variants and MDD risk, seven studies involving 26582 subjects, including 12491 cases with MDD and 14091 controls, were enrolled totally. Four common SNPs (rs1360780, rs4713916, rs3800373 and rs755658) with complete data from two or more studies were analyzed. In the total sample, t ...[more]

PMID: 27601205

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Project description:Depressive symptoms are related to abnormalities in the autonomic nervous system (ANS), and physiological signals that can be used to measure and evaluate such abnormalities have previously been used as indicators for diagnosing mental disorder, such as major depressive disorder (MDD). In this study, we investigate the feasibility of developing an objective measure of depressive symptoms that is based on examining physiological abnormalities in individuals when they are experiencing mental stress. To perform this, we recruited 30 patients with MDD and 31 healthy controls. Then, skin conductance (SC) was measured during five 5-min experimental phases, comprising baseline, mental stress, recovery from the stress, relaxation, and recovery from the relaxation, respectively. For each phase, the mean amplitude of the skin conductance level (MSCL), standard deviations of the SCL (SDSCL), slope of the SCL (SSCL), mean amplitude of the non-specific skin conductance responses (MSCR), number of non-specific skin conductance responses (NSCR), and power spectral density (PSD) were evaluated from the SC signals, producing 30 parameters overall (six features for each phase). These features were used as input data for a support vector machine (SVM) algorithm designed to distinguish MDD patients from healthy controls based on their physiological responses. Statistical tests showed that the main effect of task was significant in all SC features, and the main effect of group was significant in MSCL, SDSCL, SSCL, and PSD. In addition, the proposed algorithm achieved 70% accuracy, 70% sensitivity, 71% specificity, 70% positive predictive value, 71% negative predictive value in classifying MDD patients and healthy controls. These results demonstrated that it is possible to extract meaningful features that reflect changes in ANS responses to various stimuli. Using these features, detection of MDD was feasible, suggesting that SC analysis has great potential for future diagnostics and prediction of depression based on objective interpretation of depressive states.

Dataset Information

Common variants in FKBP5 gene and major depressive disorder (MDD) susceptibility: a comprehensive meta-analysis.

Publications

Common variants in FKBP5 gene and major depressive disorder (MDD) susceptibility: a comprehensive meta-analysis.

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