Despite the extensive therapy options available for depression, treatment-resistant depression (TRD) occurs in 20-30% of depressed patients. . Consequently, identification of neural changes in TRD could support to better understand the mechanism of resistance and to improve the treatment of individual depressed patients. We aimed to investigate the white-matter microstructure in a sample of depressed patients in which response to treatment was subsequently evaluated 6 months after. Our findings suggest the abnormalities of the white-matter integrity in multiple white matter tracts, such as anterior limb of internal capsule and genu of corpus may play a role in the pathogenesis of treatment-resistant depression.
Despite the extensive therapy options available for depression, treatment-resistant depression (TRD) occurs in 20-30% of depressed patients1. Commonly, patients who do not respond present difficulties in social and occupational function, decline of physical health, suicidal thoughts, and increased health care utilization. Consequently, identification of neural changes in TRD could help to understand the mechanism of resistance and to improve the treatment of individual depressed patients.
Structural and functional neuroimaging studies have identified widespread alterations in patients with depression, including abnormalities in fronto-limbic networks. In order to better understand brain correlates of treatment resistance and predict evolution of depressive disorder, there is a growing interest in studying structural abnormalities in TRD. To date, only few magnetic resonance studies have examined the brain structure in TRD2-4. Functional abnormalities were reported within the left amygdala to anterior cingulate when comparing TRD to remitted depression5. Reduced FA values were also found in the ventromedial prefrontal cortex of patients with TRD compared with those with non-TRD2. Thus, multiple brain abnormalities may play a role in the pathophysiology of TRD, notably in limbic regions. In this study, we aimed to investigate the whole-brain white-matter microstructure in a sample of depressed patients in which response to treatment was subsequently evaluated at 6 months.
LONGIDEP is a routine care cohort of patients suffering from mood depressive disorder who underwent a clinical evaluation, neuropsychological testing and brain MRI. The population sample consists of 57 patients suffering from depression. The Clinical Global Impressions (CGI) improvement Scale was measured to quantify and track patient progress and treatment response after 6 months6. The CGI global improvement measure (CGI-I) is rated from 1 (very much improved) to 7 (very much worse). A composite measure of medication load for each patient was assessed using a previously established method7.
T1-weighted and diffusion tensor imaging (DTI) were acquired on a 3T Siemens Verio scanner with a 32-channel head coil. The diffusion scans were obtained in 30 directions using an EPI sequence with a b-value of 1000s/mm2. The DTI data were processed with the open source medical image processing toolbox Anima8. All the diffusion images underwent (1) eddy current distortion correction, (2) blockwise non-local means filtering and (3) skull stripping followed by (4) a voxel-wise calculation of fractional anisotropy (FA). The resulting maps were normalized into MNI template space. A linear regression analysis was used to assess the correlations between the FA values and the CGI scores (P < 0.05, FDR corrected) by using as covariates age, gender, duration of disease and medication load.
Julie Coloigner was supported by a INCR fellowship.
MRI data acquisition was supported by the Neurinfo MRI research facility from the University of Rennes I. Neurinfo is granted by the the European Union (FEDER), the French State, the Brittany Council, Rennes Metropole, Inria, Inserm and the University Hospital of Rennes.
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