Symptom improvement in depression due to antidepressant treatment is highly variable and clinically unpredictable. Linking neuronal connectivity and genetic risk factors in predicting antidepressant response has clinical implications. Our investigation assessed whether indices of white matter integrity, serotonin transporter-linked polymorphism (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) val66met polymorphism predicted magnitude of depression symptom change following antidepressant treatment. Fractional anisotropy (FA) was used as an indicator of white matter integrity and was assessed in the uncinate fasciculus and superior longitudinal fasciculus using tract-based spatial statistics (TBSS) and probabilistic tractography. Forty-six medication-free patients with major depressive disorder participated in a diffusion tensor imaging scan prior to completing an 8-week treatment regime with citalopram or quetiapine XR. Indexed improvements in Hamilton Depression Rating Scale score from baseline to 8-week endpoint were used as an indicator of depression improvement. Carriers of the BDNF met allele exhibited lower FA values in the left uncinate fasciculus relative to val/val individuals [F(1, 40) = 7.314, p = 0.009]. Probabilistic tractography identified that higher FA in the left uncinate fasciculus predicted percent change in depression severity, with BDNF moderating this association [F(3, 30) = 3.923, p = 0.018]. An interaction between FA in the right uncinate fasciculus and 5-HTTLPR also predicted percent change in depression severity [F(5, 25) = 5.315, p = 0.002]. Uncorrected TBSS results revealed significantly higher FA in hippocampal portions of the cingulum bundle in responders compared to non-responders (p = 0.016). The predictive value of prefrontal and amygdala/hippocampal WM connectivity on antidepressant treatment response may be influenced by 5-HTTLPR and BDNF polymorphisms in MDD.
IntroductionDepression is the leading cause of disability worldwide, affecting approximately 350 million people. Evidence indicates that only 60–70% of persons with major depressive disorder who tolerate antidepressants respond to first-line drug treatment; the remainder become treatment resistant. Electroconvulsive therapy (ECT) is considered an effective therapy in persons with treatment-resistant depression. The use of ECT is controversial due to concerns about temporary cognitive impairment in the acute post-treatment period. We will conduct a meta-analysis to examine the effects of ECT on cognition in persons with depression.MethodsThis systematic review and meta-analysis has been registered with PROSPERO (registration number: CRD42014009100). We developed our methods following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. We are searching MEDLINE, PsychINFO, EMBASE, CINAHL and Cochrane from the date of database inception to the end of October 2014. We are also searching the reference lists of published reviews and evidence reports for additional citations. Comparative studies (randomised controlled trials, cohort and case–control) published in English will be included in the meta-analysis. Three clinical neuropsychologists will group the cognitive tests in each included article into a set of mutually exclusive cognitive subdomains. The risk of bias of randomised controlled trials will be assessed using the Jadad scale. We will supplement the Jadad scale with additional questions based on the Cochrane risk of bias tool. The risk of bias of cohort and case–control studies will be assessed using the Newcastle-Ottawa Scale. We will employ the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the strength of evidence.Statistical analysisSeparate meta-analyses will be conducted for each ECT treatment modality and cognitive subdomain using Comprehensive Meta-Analysis V.2.0.
Current theory suggests that the processing of different types of threat is supported by distinct neural networks. Here we tested whether there are distinct neural correlates associated with different types of threat processing in shyness. Using fMRI and multivariate techniques, we compared neural responses and functional connectivity during the processing of imminent (i.e., congruent angry/angry face pairs) and ambiguous (i.e., incongruent angry/neutral face pairs) social threat in young adults selected for high and low shyness. To both types of threat processing, non-shy adults recruited a right medial prefrontal cortex (mPFC) network encompassing nodes of the default mode network involved in automatic emotion regulation, whereas shy adults recruited a right dorsal anterior cingulate cortex (dACC) network encompassing nodes of the frontoparietal network that instantiate active attentional and cognitive control. Furthermore, in shy adults, the mPFC interacted with the dACC network for ambiguous threat, but with a distinct network encompassing nodes of the salience network for imminent threat. These preliminary results expand our understanding of right mPFC function associated with temperamental shyness. They also provide initial evidence for differential neural networks associated with shy and non-shy profiles in the context of different types of social threat processing.
This novel questionnaire can be used in both clinical and research settings to better understand the impact of memory changes on the day-to-day functioning of older adults and to monitor outcomes of support programs for this population.
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