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.

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