Pretreatment Brain Connectome Fingerprint Predicts Treatment Response in Major Depressive Disorder.
ACTA ACUST UNITED AC 2021;
4:2470547020984726. [PMID:
33458556 PMCID:
PMC7783890 DOI:
10.1177/2470547020984726]
[Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 12/10/2020] [Indexed: 12/04/2022]
Abstract
Background
Major depressive disorder (MDD) treatment is characterized by low remission
rate and often involves weeks to months of treatment. Identification of
pretreatment biomarkers of response may play a critical role in novel drug
development, in enhanced prognostic predictions, and perhaps in providing
more personalized medicine. Using a network restricted strength predictive
modeling (NRS-PM) approach, the goal of the current study was to identify
pretreatment functional connectome fingerprints (CFPs) that (1) predict
symptom improvement regardless of treatment modality and (2) predict
treatment specific improvement.
Methods
Functional magnetic resonance imaging and behavioral data from unmedicated
patients with MDD (n = 200) were investigated. Participants were randomized
to daily treatment of sertraline or placebo for 8 weeks. NRS-PM with 1000
iterations of 10 cross-validation were implemented to identify brain
connectivity signatures that predict percent improvement in depression
severity at week-8.
Results
The study identified a pretreatment CFP that significantly predicts symptom
improvement independent of treatment modality but failed to identify a
treatment specific CFP. Regardless of treatment modality, improved
antidepressant response was predicted by high pretreatment connectivity
between modules in the default mode network and the rest of the brain, but
low external connectivity in the executive network. Moreover, high
pretreatment internal nodal connectivity in the bilateral caudate predicted
better response.
Conclusions
The identified CFP may contribute to drug development and ultimately to
enhanced prognostic predictions. However, the results do not assist with
providing personalized medicine, as pretreatment functional connectivity
failed to predict treatment specific response.
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