Author:
Ichikawa Naho,Lisi Giuseppe,Yahata Noriaki,Okada Go,Takamura Masahiro,Hashimoto Ryu-ichiro,Yamada Takashi,Yamada Makiko,Suhara Tetsuya,Moriguchi Sho,Mimura Masaru,Yoshihara Yujiro,Takahashi Hidehiko,Kasai Kiyoto,Kato Nobumasa,Yamawaki Shigeto,Seymour Ben,Kawato Mitsuo,Morimoto Jun,Okamoto Yasumasa
Abstract
AbstractThe limited efficacy of available antidepressant therapies may be due to how they affect the underlying brain network. The purpose of this study was to develop a melancholic MDD biomarker to identify critically important functional connections (FCs), and explore their association to treatments. Resting state fMRI data of 130 individuals (65 melancholic major depressive disorder (MDD) patients, 65 healthy controls) were included to build a melancholic MDD classifier, and 10 FCs were selected by our sparse machine learning algorithm. This biomarker generalized to a drug-free independent cohort of melancholic MDD, and did not generalize to other MDD subtypes or other psychiatric disorders. Moreover, we found that antidepressants had a heterogeneous effect on the identified FCs of 25 melancholic MDDs. In particular, it did impact the FC between left dorsolateral prefrontal cortex (DLPFC)/inferior frontal gyrus (IFG) and posterior cingulate cortex (PCC)/precuneus, ranked as the second ‘most important’ FC based on the biomarker weights, whilst other eight FCs were normalized. Given that left DLPFC has been proposed as an explicit target of depression treatments, this suggest that the limited efficacy of antidepressants might be compensated by combining therapies with targeted treatment as an optimized approach in the future.
Publisher
Springer Science and Business Media LLC
Cited by
51 articles.
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