Neural mechanisms of depressive symptoms in bipolar disorder and major depressive disorder revealed by resting-state functional connectivity

Poster Session E - Monday, March 31, 2025, 2:30 – 4:30 pm EDT, Back Bay Ballroom/Republic Ballroom

Ayumu Yamashita^1,2 (ayumu722@gmail.com), Suzuka Narukawa^1,3, Yutaro Hori^1,4, Takashi Itahashi⁵, Yuki Sakai^1,6, Saori Tanaka^1,7, Go Okada⁸, Kouji Kamagata⁹, Ryuichiro Hashimoto^1,5,10, Haruto Takagishi¹¹, Toshiya Murai¹², Koichi Hosomi¹³, Yoshiyuki Hirano¹⁴, Masaru Mimura¹⁵, Koji Matsuo¹⁶, Shinsuke Koike¹⁷, Kiyoto Kasai^18,19, Hidehiko Takahashi¹², Takuya Hayashi²¹, Mitsuo Kawato^1,6, Okito Yamashita^1,23; ¹Advanced Telecommunications Research Institute International (ATR), Brain Information Communication Research Laboratory Group, ²Graduate School of Information Science and Technology, The University of Tokyo, ³The Graduate University for Advanced Studies, ⁴College of Arts and Sciences, The University of Tokyo, ⁵Medical Institute of Developmental Disabilities Research, Showa University, ⁶XNef Inc., ⁷Graduate School of Advanced Science and Technology, Nara Institute of Science and Technology, ⁸Department of Psychiatry and Neurosciences, Hiroshima University, ⁹Department of Radiology, Juntendo University School of Medicine, ¹⁰Faculty of Humanities and Social Sciences, Tokyo Metropolitan University, ¹¹Brain Science Institute, Tamagawa University, ¹²Graduate School of Medicine, Kyoto University, ¹³Graduate School of Medicine, Osaka University, ¹⁴Research Center for Child Mental Development, Chiba University, ¹⁵School of Medicine, Keio University, ¹⁶Faculty of Medicine, Saitama Medical University, ¹⁷Graduate School of Arts and Sciences, The University of Tokyo, ¹⁸Graduate School of Medicine, The University of Tokyo, ¹⁹International Research Center for Neurointelligence, Institutes for Advanced Study, The University of Tokyo, ²⁰Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, ²¹Center for Biosystems Dynamics Research (BDR), RIKEN, ²²Brain Connectomics, Graduate School of Medicine, Kyoto University, ²³Center for Advanced Intelligence Project (AIP), RIKEN

Both patients with bipolar disorder (BD) and major depressive disorder (MDD) have depressive conditions with similar depressive symptoms. However, the neurobiological mechanisms underlying these conditions may differ and remain largely unknown. Since this similarity frequently results in diagnostic errors and inappropriate treatment strategies, a deeper understanding of the neural basis of depressive symptoms and distinguishing between BD and MDD based on biological abnormalities is a critical challenge. Functional connectivity (FC), which defined as the temporal correlation of BOLD signals between brain regions, estimated using resting state fMRI (rs-fMRI) is a powerful tool to investigate biological abnormalities. Since it is easy to acquire large-scale data from multiple imaging sites, rs-fMRI can be analyzed by AI techniques. In this study, we extracted symptom factors using detailed depressive symptoms (subscales of BDI-II) of 1444 individuals and extracted FCs associated with each factor. We also constructed a brain network marker that discriminate between MDD and BD based on the FC patterns of MDD (N=824) and BD type I (N=81) and II (N=130). We found two to four symptom factors and each associated with different FCs. The results of 10-fold cross validation showed that MDD and BD were classified with AUC=0.7. Furthermore, our results showed that BD type I was more biologically distinct from MDD than BD type II. The identification of the neural basis of depressive symptoms can be used as a diagnostic support tool for disorders with similar symptoms, and leads to a better understanding of the relationship between BD and MDD.

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