Verification of the brain network marker of major depressive disorder: Test-retest reliability and anterograde generalization performance for newly acquired data

Recently, we developed a generalizable brain network marker for the diagnosis of major depressive disorder (MDD) across multiple imaging sites using resting-state functional magnetic resonance imaging. Here, we applied this brain network marker to newly acquired data to verify its test-retest reliability and anterograde generalization performance for new patients. We tested the sensitivity and specificity of our brain network marker of MDD using data acquired from 43 new patients with MDD as well as new data from 33 healthy controls (HCs) who participated in our previous study. To examine the test-retest reliability of our brain network marker, we evaluated the intraclass correlation coefficients (ICCs) between the brain network marker-based classifier's output (probability of MDD) in two sets of HC data obtained at an interval of approximately 1 year. Test-retest correlation between the two sets of the classifier's output (probability of MDD) from HCs exhibited moderate reliability with an ICC of 0.45 (95 % confidence interval,0.13–0.68). The classifier distinguished patients with MDD and HCs with an accuracy of 69.7 % (sensitivity, 72.1 %; specificity, 66.7 %). The data of patients with MDD in this study were cross-sectional, and the clinical significance of the marker, such as whether it is a state or trait marker of MDD and its association with treatment responsiveness, remains unclear. The results of this study reaffirmed the test-retest reliability and generalization performance of our brain network marker for the diagnosis of MDD. •We applied a previously developed brain network marker to newly acquired data.•In measurements of the same person, the classifier's output was acceptably stable.•We confirmed that sufficient sensitivity can be reproduced for new patients with MDD.