| Literature DB >> 32103088 |
Naho Ichikawa1, Giuseppe Lisi2, Noriaki Yahata3, Go Okada1, Masahiro Takamura1, Ryu-Ichiro Hashimoto4, Takashi Yamada2, Makiko Yamada3,5, Tetsuya Suhara3, Sho Moriguchi6, Masaru Mimura6, Yujiro Yoshihara7, Hidehiko Takahashi7,8, Kiyoto Kasai9, Nobumasa Kato4, Shigeto Yamawaki1, Ben Seymour10,11, Mitsuo Kawato2, Jun Morimoto2, Yasumasa Okamoto12.
Abstract
The 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.Entities:
Year: 2020 PMID: 32103088 PMCID: PMC7044159 DOI: 10.1038/s41598-020-60527-z
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379