Early life stress has been found to be a strong predictor of depression severity, with genetic risk factors such as the serotonin transporter promotor (5-HTTLPR) and brain derived neurotrophic factor (BDNF) polymorphisms moderating depression development. Our investigation aims to extend these findings to examine the impact of depression severity, genetic risk factors, and childhood maltreatment on neuronal connectivity changes using tract based spatial statistics (TBSS) and probabilistic tractography. Fifty-five medication-free patients with major depressive disorder (MDD) [x̅ age: 36.4, M/F: 22/33] and 18 controls [x̅ age: 33.2, M/F: 8/10] underwent diffusion tensor imaging scanning, genotyping and completed the Childhood Trauma Questionairre. Corrected TBSS findings revealed trends toward significantly reduced FA in the right anterior internal capsule [p=0.051], fornix [p=0.085] and right anterior corona radiata [p=0.084] in the MDD group. Probabilistic tractography analysis examined fractional anisotropy (FA) in the cingulum bundle, uncinate fasciculus and superior longitudinal fasciculus. Individuals scoring high in depression severity and who experienced severe childhood physical neglect (PN) and emotional neglect (EN) had higher FA in the uncinate [PN: p=0.003, EN: p=0.029] and superior longitudinal fasciculus [PN: p=0.0748], with BDNF and 5-HTTLPR moderating these associations. BDNF polymorphisms also exhibited a stronger impact on uncinate FA in individuals with high depression severity, with val-BDNF exhibiting higher FA than met carriers [p=0.021]. In conclusion, MDD patients exhibit widespread decreases in FA across many neural regions. Furthermore, the impact that depression severity has on FA is considerably influenced by early life neglect. / Thesis / Master of Science (MSc)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/15994 |
Date | 11 1900 |
Creators | Tatham, Erica |
Contributors | Hall, Geoff, Neuroscience |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
Type | Thesis |
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