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Mol Psychiatry. 2016 May;21(5):680-5. doi: 10.1038/mp.2015.109. Epub 2015 Aug 11.

Brain connectomics predict response to treatment in social anxiety disorder.

Author information

1
Poitras Center for Affective Disorders Research, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
2
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
3
Department of Otology and Laryngoloy, Harvard Medical School, Boston, MA, USA.
4
Department of Speech, Language and Hearing Sciences, Boston University, Boston, MA, USA.
5
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA.
6
Department of Psychiatry, Rush University Medical Center, Chicago, IL, USA.

Abstract

We asked whether brain connectomics can predict response to treatment for a neuropsychiatric disorder better than conventional clinical measures. Pre-treatment resting-state brain functional connectivity and diffusion-weighted structural connectivity were measured in 38 patients with social anxiety disorder (SAD) to predict subsequent treatment response to cognitive behavioral therapy (CBT). We used a priori bilateral anatomical amygdala seed-driven resting connectivity and probabilistic tractography of the right inferior longitudinal fasciculus together with a data-driven multivoxel pattern analysis of whole-brain resting-state connectivity before treatment to predict improvement in social anxiety after CBT. Each connectomic measure improved the prediction of individuals' treatment outcomes significantly better than a clinical measure of initial severity, and combining the multimodal connectomics yielded a fivefold improvement in predicting treatment response. Generalization of the findings was supported by leave-one-out cross-validation. After dividing patients into better or worse responders, logistic regression of connectomic predictors and initial severity combined with leave-one-out cross-validation yielded a categorical prediction of clinical improvement with 81% accuracy, 84% sensitivity and 78% specificity. Connectomics of the human brain, measured by widely available imaging methods, may provide brain-based biomarkers (neuromarkers) supporting precision medicine that better guide patients with neuropsychiatric diseases to optimal available treatments, and thus translate basic neuroimaging into medical practice.

PMID:
26260493
DOI:
10.1038/mp.2015.109
[Indexed for MEDLINE]

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