Pauline Favre

22 mars 2019

INSERM U995, équipe « Psychiatrie translationnelle » et Neurospin CEA Paris - Saclay, équipe UNIACT, 91191 Gif-sur-Yvette, France

title : What can we learn from large scale imaging studies ? The example of bipolar disorder

invitée par Guillaume Auzias


Functional and structural MRI have been used for 15 years to highlight abnormalities in cerebral functioning that may explain bipolar disorder (BD). First results from our group demonstrated abnormal fronto-limbic connectivity in patients with BD but also abnormal communication between theses brain regions and those of the default mode network suggesting that abnormal emotion processing may underlie mood disturbances in this disease (Houenou et al., 2011 ; Favre et al., 2014, 2015). In addition, we showed that these functional and anatomic deficits could be moderated after the application of structured psychotherapeutic programs in the patients (Favre et al., 2013, 2016). Recently data sharing across international groups has considerably increased the power of MRI studies of BD. The study of such cohorts, as gathered by our team (n = 300), allowed to highlight specific impairment in subgroups of patients with, for instance, history of psychotic symptoms (Sarrazin et al., 2014, 2015). In addition, in collaboration with the ENIGMA consortium (http://enigma.ini.usc.edu/), we coordinated the analysis of an unprecedented sample of diffusion MRI data of patients with BD (n = 3033), which allowed to identify widespread white matter abnormalities in BD and also to demonstrate the interest of the use of machine learning methods to predict the diagnosis based on these measurements and allowed us to identify relevant subgroups of patients. In this talk, I will present the results from our group and the pros and cons of working on such large cohorts.

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