1
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Sato Y, Okada G, Yokoyama S, Ichikawa N, Takamura M, Mitsuyama Y, Shimizu A, Itai E, Shinzato H, Kawato M, Yahata N, Okamoto Y. Resting-state functional connectivity disruption between the left and right pallidum as a biomarker for subthreshold depression. Sci Rep 2023; 13:6349. [PMID: 37072448 PMCID: PMC10113366 DOI: 10.1038/s41598-023-33077-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 04/06/2023] [Indexed: 05/03/2023] Open
Abstract
Although the identification of late adolescents with subthreshold depression (StD) may provide a basis for developing effective interventions that could lead to a reduction in the prevalence of StD and prevent the development of major depressive disorder, knowledge about the neural basis of StD remains limited. The purpose of this study was to develop a generalizable classifier for StD and to shed light on the underlying neural mechanisms of StD in late adolescents. Resting-state functional magnetic resonance imaging data of 91 individuals (30 StD subjects, 61 healthy controls) were included to build an StD classifier, and eight functional connections were selected by using the combination of two machine learning algorithms. We applied this biomarker to an independent cohort (n = 43) and confirmed that it showed generalization performance (area under the curve = 0.84/0.75 for the training/test datasets). Moreover, the most important functional connection was between the left and right pallidum, which may be related to clinically important dysfunctions in subjects with StD such as anhedonia and hyposensitivity to rewards. Investigation of whether modulation of the identified functional connections can be an effective treatment for StD may be an important topic of future research.
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Affiliation(s)
- Yosuke Sato
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Satoshi Yokoyama
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Naho Ichikawa
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
- Deloitte Analytics R&D, Deloitte Touche Tohmatsu LLC, Tokyo, Japan
| | - Masahiro Takamura
- Department of Neurology, Shimane University, Matsue, Japan
- Center for Brain, Mind and KANSEI Research Sciences, Hiroshima University, Hiroshima, Japan
| | - Yuki Mitsuyama
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Ayaka Shimizu
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Eri Itai
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Hotaka Shinzato
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan
| | - Mitsuo Kawato
- ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
| | - Noriaki Yahata
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
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2
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Nakamura Y, Ishida T, Tanaka SC, Mitsuyama Y, Yokoyama S, Shinzato H, Itai E, Okada G, Kobayashi Y, Kawashima T, Miyata J, Yoshihara Y, Takahashi H, Aoki R, Nakamura M, Ota H, Itahashi T, Morita S, Kawakami S, Abe O, Okada N, Kunimatsu A, Yamashita A, Yamashita O, Imamizu H, Morimoto J, Okamoto Y, Murai T, Hashimoto RI, Kasai K, Kawato M, Koike S. Distinctive alterations in the mesocorticolimbic circuits in various psychiatric disorders. Psychiatry Clin Neurosci 2023. [PMID: 36905180 DOI: 10.1111/pcn.13542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 03/03/2023] [Accepted: 03/07/2023] [Indexed: 03/12/2023]
Abstract
AIM Increasing evidence suggests that psychiatric disorders are linked to alterations in the mesocorticolimbic dopamine-related circuits. However, the common and disease-specific alterations remain to be examined in schizophrenia (SCZ), major depressive disorder (MDD), and autism spectrum disorder (ASD). Thus, this study aimed to examine common and disease-specific features related to mesocorticolimbic circuits. METHODS This study included 555 participants from four institutes with five scanners: 140 individuals with SCZ (45.0% female), 127 individuals with MDD (44.9%), 119 individuals with ASD (15.1%), and 169 healthy controls (HC) (34.9%). All participants underwent resting-state functional magnetic resonance imaging. A parametric empirical Bayes approach was adopted to compare estimated effective connectivity among groups. Intrinsic effective connectivity focusing on the mesocorticolimbic dopamine-related circuits including the ventral tegmental area (VTA), shell and core parts of the nucleus accumbens (NAc), and medial prefrontal cortex (mPFC) were examined using a dynamic causal modeling analysis across these psychiatric disorders. RESULTS The excitatory shell-to-core connectivity was greater in the all patients than in the HC group. The inhibitory shell-to-VTA and shell-to-mPFC connectivities were greater in the ASD group than in the HC, MDD, and SCZ groups. Furthermore, the VTA-to-core and VTA-to-shell connectivities were excitatory in the ASD group, while those connections were inhibitory in the HC, MDD, and SCZ groups. CONCLUSION Impaired signaling in the mesocorticolimbic dopamine-related circuits could be an underlying neuropathogenesis of various psychiatric disorders. These findings will improve the understanding of unique neural alternations of each disorder and will facilitate identification of effective therapeutic targets. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yuko Nakamura
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, the University of Tokyo, Meguro-ku, Tokyo, 153-8902, Japan.,University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Meguro-ku, Tokyo, 153-8902, Japan
| | - Takuya Ishida
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, the University of Tokyo, Meguro-ku, Tokyo, 153-8902, Japan.,Department of Neuropsychiatry, Graduate School of Wakayama Medical University, Wakayama, 641-8509, Japan
| | - Saori C Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, 619-0288, Japan.,Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, 630-0192, Japan
| | - Yuki Mitsuyama
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Satoshi Yokoyama
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Hotaka Shinzato
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Eri Itai
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Yuko Kobayashi
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Takahiko Kawashima
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Jun Miyata
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Yujiro Yoshihara
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Tokyo Medical and Dental University, Tokyo, 113-8510, Japan
| | - Ryuta Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, 157-8577, Japan
| | - Motoaki Nakamura
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, 157-8577, Japan
| | - Haruhisa Ota
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, 157-8577, Japan
| | - Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, 157-8577, Japan
| | - Susumu Morita
- Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Shintaro Kawakami
- Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, the University of Tokyo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Naohiro Okada
- The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan
| | - Akira Kunimatsu
- Department of Radiology, International University of Health and Welfare Mita Hospital, Tokyo, 108-8329, Japan
| | - Ayumu Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, 619-0288, Japan.,Department of Psychiatry, Boston University School of Medicine, MA, 02118, USA
| | - Okito Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, 619-0288, Japan.,Center for Advanced Intelligence Project, RIKEN, Tokyo, 103-0027, Japan
| | - Hiroshi Imamizu
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, 619-0288, Japan.,Department of Psychology, Graduate School of Humanities and Sociology, the University of Tokyo, Tokyo, 113-8654, Japan
| | - Jun Morimoto
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, 619-0288, Japan.,Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, 606-8501, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Ryu-Ichiro Hashimoto
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, 157-8577, Japan.,Department of Language Sciences, Tokyo Metropolitan University, Tokyo, 192-0397, Japan
| | - Kiyoto Kasai
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, the University of Tokyo, Meguro-ku, Tokyo, 153-8902, Japan.,University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Meguro-ku, Tokyo, 153-8902, Japan.,Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, 113-8655, Japan.,The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan
| | - Mitsuo Kawato
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, 619-0288, Japan
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, the University of Tokyo, Meguro-ku, Tokyo, 153-8902, Japan.,University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Meguro-ku, Tokyo, 153-8902, Japan.,The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan
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3
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Ishida T, Nakamura Y, Tanaka SC, Mitsuyama Y, Yokoyama S, Shinzato H, Itai E, Okada G, Kobayashi Y, Kawashima T, Miyata J, Yoshihara Y, Takahashi H, Morita S, Kawakami S, Abe O, Okada N, Kunimatsu A, Yamashita A, Yamashita O, Imamizu H, Morimoto J, Okamoto Y, Murai T, Kasai K, Kawato M, Koike S. Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets. Schizophr Bull 2023:7074397. [PMID: 36919870 DOI: 10.1093/schbul/sbad022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
BACKGROUND AND HYPOTHESIS Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders. STUDY DESIGN We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network. STUDY RESULTS DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively. CONCLUSIONS DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders.
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Affiliation(s)
- Takuya Ishida
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan.,Department of Neuropsychiatry, Graduate School of Wakayama Medical University, Wakayama, Japan
| | - Yuko Nakamura
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan.,University of Tokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
| | - Saori C Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan.,Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan
| | - Yuki Mitsuyama
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Satoshi Yokoyama
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Hotaka Shinzato
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Eri Itai
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Yuko Kobayashi
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takahiko Kawashima
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Jun Miyata
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yujiro Yoshihara
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Tokyo Medical and Dental University, Tokyo, Japan.,Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Susumu Morita
- Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Shintaro Kawakami
- Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Naohiro Okada
- The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, Tokyo, Japan
| | - Akira Kunimatsu
- Department of Radiology, International University of Health and Welfare Mita Hospital, Tokyo, Japan
| | - Ayumu Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan.,Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Okito Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan.,Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan
| | - Hiroshi Imamizu
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan.,Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan
| | - Jun Morimoto
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan.,Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kiyoto Kasai
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan.,University of Tokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM), Tokyo, Japan.,Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.,The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, Tokyo, Japan
| | - Mitsuo Kawato
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan.,University of Tokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM), Tokyo, Japan.,The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, Tokyo, Japan
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4
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Okada G, Sakai Y, Shibakawa M, Yoshioka T, Itai E, Shinzato H, Yamamoto O, Kurata K, Tamura T, Jitsuiki H, Yamashita H, Mantani A, Yokota N, Kawato M, Okamoto Y. Examining the usefulness of the brain network marker program using fMRI for the diagnosis and stratification of major depressive disorder: a non-randomized study protocol. BMC Psychiatry 2023; 23:63. [PMID: 36694153 PMCID: PMC9875439 DOI: 10.1186/s12888-023-04560-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 01/19/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Although many studies have reported the biological basis of major depressive disorder (MDD), none have been put into practical use. Recently, we developed a generalizable brain network marker for MDD diagnoses (diagnostic marker) across multiple imaging sites using resting-state functional magnetic resonance imaging (rs-fMRI). We have planned this clinical trial to establish evidence for the practical applicability of this diagnostic marker as a medical device. In addition, we have developed generalizable brain network markers for MDD stratification (stratification markers), and the verification of these brain network markers is a secondary endpoint of this study. METHODS This is a non-randomized, open-label study involving patients with MDD and healthy controls (HCs). We will prospectively acquire rs-fMRI data from 50 patients with MDD and 50 HCs and anterogradely verify whether our diagnostic marker can distinguish between patients with MDD and HCs. Furthermore, we will longitudinally obtain rs-fMRI and clinical data at baseline and 6 weeks later in 80 patients with MDD treated with escitalopram and verify whether it is possible to prospectively distinguish MDD subtypes that are expected to be effectively responsive to escitalopram using our stratification markers. DISCUSSION In this study, we will confirm that sufficient accuracy of the diagnostic marker could be reproduced for data from a prospective clinical study. Using longitudinally obtained data, we will also examine whether the "brain network marker for MDD diagnosis" reflects treatment effects in patients with MDD and whether treatment effects can be predicted by "brain network markers for MDD stratification". Data collected in this study will be extremely important for the clinical application of the brain network markers for MDD diagnosis and stratification. TRIAL REGISTRATION Japan Registry of Clinical Trials ( jRCTs062220063 ). Registered 12/10/2022.
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Affiliation(s)
- Go Okada
- grid.257022.00000 0000 8711 3200Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yuki Sakai
- grid.418163.90000 0001 2291 1583Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan ,XNef, Inc., Kyoto, Japan
| | | | - Toshinori Yoshioka
- grid.418163.90000 0001 2291 1583Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan ,XNef, Inc., Kyoto, Japan
| | - Eri Itai
- grid.257022.00000 0000 8711 3200Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Hotaka Shinzato
- grid.257022.00000 0000 8711 3200Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | | | | | | | | | | | | | | | - Mitsuo Kawato
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan. .,XNef, Inc., Kyoto, Japan.
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
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5
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Han LK, Dinga R, Leenings R, Hahn T, Cole JH, Aftanas LI, Amod AR, Besteher B, Colle R, Corruble E, Couvy-Duchesne B, Danilenko KV, Fuentes-Claramonte P, Gonul AS, Gotlib IH, Goya-Maldonado R, Groenewold NA, Hamilton P, Ichikawa N, Ipser JC, Itai E, Koopowitz SM, Li M, Okada G, Okamoto Y, Churikova OS, Osipov EA, Penninx BW, Pomarol-Clotet E, Rodríguez-Cano E, Sacchet MD, Shinzato H, Sim K, Stein DJ, Uyar-Demir A, Veltman DJ, Schmaal L. A large-scale ENIGMA multisite replication study of brain age in depression. Neuroimage: Reports 2022. [DOI: 10.1016/j.ynirp.2022.100149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
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6
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Kamishikiryo T, Okada G, Itai E, Masuda Y, Yokoyama S, Takamura M, Fuchikami M, Yoshino A, Mawatari K, Numata S, Takahashi A, Ohmori T, Okamoto Y. Left DLPFC activity is associated with plasma kynurenine levels and can predict treatment response to escitalopram in major depressive disorder. Psychiatry Clin Neurosci 2022; 76:367-376. [PMID: 35543406 PMCID: PMC9544423 DOI: 10.1111/pcn.13373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 03/16/2022] [Accepted: 04/24/2022] [Indexed: 11/27/2022]
Abstract
AIM To establish treatment response biomarkers that reflect the pathophysiology of depression, it is important to use an integrated set of features. This study aimed to determine the relationship between regional brain activity at rest and blood metabolites related to treatment response to escitalopram to identify the characteristics of depression that respond to treatment. METHODS Blood metabolite levels and resting-state brain activity were measured in patients with moderate to severe depression (n = 65) before and after 6-8 weeks of treatment with escitalopram, and these were compared between Responders and Nonresponders to treatment. We then examined the relationship between blood metabolites and brain activity related to treatment responsiveness in patients and healthy controls (n = 36). RESULTS Thirty-two patients (49.2%) showed a clinical response (>50% reduction in the Hamilton Rating Scale for Depression score) and were classified as Responders, and the remaining 33 patients were classified as Nonresponders. The pretreatment fractional amplitude of low-frequency fluctuation (fALFF) value of the left dorsolateral prefrontal cortex (DLPFC) and plasma kynurenine levels were lower in Responders, and the rate of increase of both after treatment was correlated with an improvement in symptoms. Moreover, the fALFF value of the left DLPFC was significantly correlated with plasma kynurenine levels in pretreatment patients with depression and healthy controls. CONCLUSION Decreased resting-state regional activity of the left DLPFC and decreased plasma kynurenine levels may predict treatment response to escitalopram, suggesting that it may be involved in the pathophysiology of major depressive disorder in response to escitalopram treatment.
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Affiliation(s)
- Toshiharu Kamishikiryo
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Eri Itai
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Yoshikazu Masuda
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Satoshi Yokoyama
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Masahiro Takamura
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo-shi, Japan
| | - Manabu Fuchikami
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Atsuo Yoshino
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
| | - Kazuaki Mawatari
- Department of Preventive Environment and Nutrition, Institute of Biomedical Sciences, Tokushima University, Tokushima, Japan
| | - Shusuke Numata
- Department of Psychiatry, Institute of Biomedical Science, Tokushima University Graduate School, Tokushima, Japan
| | - Akira Takahashi
- Department of Preventive Environment and Nutrition, Institute of Biomedical Sciences, Tokushima University, Tokushima, Japan
| | - Tetsuro Ohmori
- Department of Psychiatry, Institute of Biomedical Science, Tokushima University Graduate School, Tokushima, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan
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7
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Yokoyama S, Okada G, Takagaki K, Itai E, Kambara K, Mitsuyama Y, Shinzato H, Masuda Y, Jinnin R, Okamoto Y. Trace of depression: network structure of depressive symptoms in different clinical conditions. Eur Psychiatry 2022; 65:1-30. [PMID: 35272734 PMCID: PMC8988270 DOI: 10.1192/j.eurpsy.2022.12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 02/21/2022] [Accepted: 02/24/2022] [Indexed: 11/23/2022] Open
Abstract
Background Psychopathological network model has received attention recently in the traditional debate about the continuity of depression. However, there is little evidence for comparing the network structure of depressive symptoms in several depressive states at different clinical stages. Through this study of a broad sample of patients with nonclinical to clinical depression, we examined differences in the network structure of depressive symptoms. Methods Four groups of participants, including cohorts of clinical depression (current depression, n = 294; remitted depression, n = 118) and nonclinical depression (subthreshold depression, N = 184; healthy control, n = 257), responded to Beck Depression Inventory-II (BDI-II). After adjusting for age and sex, the residual scores of the 21 BDI-II items were input into a regularized partial correlation network for each group. Then, the estimated edge strengths/densities and node characteristics were compared. Results Current depression has a discontinuous structure with a stronger and denser network of symptoms compared with nonclinical groups. Interestingly, remitted depression had improved to the level in healthy controls; however, it retained the same network structure as current depression, which indicates a trace of depression. Conclusions We found the traces of depression that remained even after the symptoms disappeared. This study might provide a novel framework for elucidating the development and formation of depression.
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Affiliation(s)
- Satoshi Yokoyama
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Koki Takagaki
- Health Service Center, Hiroshima University, Hiroshima, Japan
| | - Eri Itai
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Kohei Kambara
- Graduate School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan
| | - Yuki Mitsuyama
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Hotaka Shinzato
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Yoshikazu Masuda
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Ran Jinnin
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
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