Limbic system white matter microstructure and long-term treatment outcome in major depressive disorder: a diffusion tensor imaging study using legacy data.

Hoogenboom WS, Perlis RH, Smoller JW, Zeng-Treitler Q, Gainer VS, Murphy SN, Churchill SE, Kohane IS, Shenton ME, Iosifescu DV. Limbic system white matter microstructure and long-term treatment outcome in major depressive disorder: a diffusion tensor imaging study using legacy data. The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry. 2014 Feb 1; 15(2):122-34.

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Abstract:

OBJECTIVES: Treatment-resistant depression is a common clinical occurrence among patients with major depressive disorder (MDD), but its neurobiology is poorly understood. We used data collected as part of routine clinical care to study white matter integrity of the brain's limbic system and its association to treatment response. METHODS: Electronic medical records of multiple large New England hospitals were screened for patients with an MDD billing diagnosis, and natural language processing was subsequently applied to find those with concurrent diffusion-weighted images, but without any diagnosed brain pathology. Treatment outcome was determined by review of clinical charts. MDD patients (n = 29 non-remitters, n = 26 partial-remitters, and n = 37 full-remitters), and healthy control subjects (n = 58) were analyzed for fractional anisotropy (FA) of the fornix and cingulum bundle. RESULTS: Failure to achieve remission was associated with lower FA among MDD patients, statistically significant for the medial body of the fornix. Moreover, global and regional-selective age-related FA decline was most pronounced in patients with treatment-refractory, non-remitted depression. CONCLUSIONS: These findings suggest that specific brain microstructural white matter abnormalities underlie persistent, treatment-resistant depression. They also demonstrate the feasibility of investigating white matter integrity in psychiatric populations using legacy data.