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• Depressive mixed state and anxious distress as risk factors for suicidal behavior during major depressive episodes

  Ota, K; Shinzato, H; Otsuka, N; Zamami, Y; Kurihara, K; Futenma, K; Kondo, T; Takaesu, Y

  SCIENTIFIC REPORTS ( Scientific Reports )  15 ( 1 ) 11918 - 11918   2025年04月 [ 査読有り ]

  掲載種別: 研究論文（学術雑誌）

  　概要を見る

  Accurately assessing and predicting suicidal behavior in patients with depression are challenging for researchers and clinicians. We examined various risk factors for suicidal behavior during major depressive episodes (MDE), especially focusing on depressive mixed state (DMX) and anxious distress (AD). We recruited 187 patients with MDE and divided them into two groups-with and without suicidal behavior-defined as the cut-off score of 1 or more on the suicidal behavior sub-item in the quick inventory of depressive symptomatology-self report. The presence of DMX was defined as a total score of 13 or more on the self-administered 8-item questionnaire for DMX. We used multivariate logistic regression analysis with the presence or absence of suicidal behavior as a dependent variable for investigating factors associated with suicidal behavior. The with suicidal behavior group was younger and indicated a greater proportion of past suicide attempts, AD, and DMX than the without suicidal behavior group. Logistic regression analysis revealed that AD (P = 0.020) and DMX (P = 0.018) were significantly associated with suicidal behavior. AD and DMX may promote suicidal behavior during MDE. These two psychopathological features should be carefully monitored and intensively treated for the prevention of suicide-related events.

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• Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study.

  Bayer JMM, van Velzen LS, Pozzi E, Davey C, Han LKM, Bauduin SEEC, Bauer J, Benedetti F, Berger K, Bonnekoh LM, Brosch K, Bülow R, Couvy-Duchesne B, Cullen KR, Dannlowski U, Dima D, Dohm K, Evans JW, Fu CHY, Fuentes-Claramonte P, Godlewska BR, Goltermann J, Gonul A, Goya-Maldonado R, Grabe HJ, Groenewold NA, Grotegerd D, Gruber O, Hahn T, Hall GB, Hamilton J, Harrison BJ, Hatton SN, Hermesdorf M, Hickie IB, Ho TC, Jahanshad N, Jansen A, Jamieson AJ, Kamishikiryo T, Kircher T, Klimes-Dougan B, Krämer B, Kraus A, Krug A, Leehr EJ, Leenings R, Li M, McIntosh A, Medland SE, Meinert S, Melloni E, Mwangi B, Nenadić I, Okada G, Oudega M, Portella MJ, Rodríguez E, Romaniuk L, Rosa PG, Sacchet MD, Salvador R, Sämann PG, Shinzato H, Sim K, Simulionyte E, Soares JC, Stein DJ, Stein F, Stolicyn A, Straube B, Strike LT, Teutenberg L, Thomas-Odenthal F, Thomopoulos SI, Usemann P, van der Wee NJA, Völzke H, Wagenmakers M, Walter M, Whalley HC, Whittle S, Winter NR, Wittfeld K, Wu M, Yang TT, Zarate CA, Zunta-Soares GB, Thompson PM, Veltman DJ, Marquand AF, Schmaal L

  bioRxiv : the preprint server for biology     2025年03月 [ 査読有り ]

  掲載種別: 研究論文（学術雑誌）

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• The 12-item self-report Questionnaire for Difficulty in Social Communication as a simultaneous prescreening of autism spectrum and social anxiety

  Teruya, M; Kurihara, K; Ishibashi, T; Ota, K; Shinzato, H; Takaesu, Y; Kondo, T

  PSYCHIATRY AND CLINICAL NEUROSCIENCES REPORTS ( Psychiatry and Clinical Neurosciences Reports )  4 ( 1 ) e70084   2025年03月 [ 査読有り ]

  掲載種別: 研究論文（学術雑誌）

  　概要を見る

  AIM: Young patients with social communication difficulties are often diagnosed with autism spectrum disorder (ASD), social communication disorder (SCD), or social anxiety disorder (SAD). This study aimed to develop a questionnaire, especially focusing on the prescreening of SAD complicated by ASD/SCD. METHODS: The 12-item self-report Questionnaire for Difficulty in Social Communication (DISC-12) was developed and analyzed using exploratory factor analysis in 94 patients with ASD/SCD (35 with SAD, 59 without). An additional 17 patients with only SAD were included. Convergent validity was assessed via correlations with the Autism Spectrum Quotient (AQ) and Liebowitz Social Anxiety Scale (LSAS). DISC-12 scores and demographics were compared across ASD/SCD, ASD/SCD + SAD, and SAD groups. Receiver operating characteristic (ROC) analysis of DISC-12 subscales distinguished autistic traits from social anxiety. RESULTS: Factor analysis revealed a three-factor model for the DISC-12, comprising nonassertiveness, poor empathy, and interpersonal hypersensitivity. DISC-12 showed significant correlations with the AQ (r = 0.412, p < 0.001) and LSAS (r = 0.429, p < 0.001). Patients with ASD/SCD had higher Poor Empathy scores, while SAD patients had higher Interpersonal Hypersensitivity scores than the other groups. ROC analysis indicated that Poor Empathy and Interpersonal Hypersensitivity subscale scores effectively differentiated ASD/SCD from patients with SAD and vice versa. CONCLUSION: DISC-12 is a rapid and effective prescreening tool for identifying both ASD and social anxiety, particularly in young patients with self-reported difficulties in social communication.

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• Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets

  Yuji Takahara, Yuto Kashiwagi, Tomoki Tokuda, Junichiro Yoshimoto, Yuki Sakai, Ayumu Yamashita, Toshinori Yoshioka, Hidehiko Takahashi, Hiroto Mizuta, Kiyoto Kasai, Akira Kunimitsu, Naohiro Okada, Eri Itai, Hotaka Shinzato, Satoshi Yokoyama, Yoshikazu Masuda, Yuki Mitsuyama, Go Okada, Yasumasa Okamoto, Takashi Itahashi, Haruhisa Ohta, Ryu-ichiro Hashimoto, Kenichiro Harada, Hirotaka Yamagata, Toshio Matsubara, Koji Matsuo, Saori C. Tanaka, Hiroshi Imamizu, Koichi Ogawa, Sotaro Momosaki, Mitsuo Kawato, Okito Yamashita

  Neural Networks ( Elsevier BV )    107335 - 107335   2025年02月 [ 査読有り ]

  掲載種別: 研究論文（学術雑誌）

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• Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group

  Poirot, MG; Boucherie, DE; Caan, MWA; Goya-Maldonado, R; Belov, V; Corruble, E; Colle, R; Couvy-Duchesne, B; Kamishikiryo, T; Shinzato, H; Ichikawa, N; Okada, G; Okamoto, Y; Harrison, B; Davey, CG; Jamieson, AJ; Cullen, KR; Basgöze, Z; Klimes-Dougan, B; Mueller, BA; Benedetti, F; Poletti, S; Melloni, EMT; Ching, CRK; Zeng, LL; Radua, J; Han, LKM; Jahanshad, N; Thomopoulos, SI; Pozzi, E; Veltman, DJ; Schmaal, L; Thompson, PM; Ruhe, HG; Reneman, L; Schrantee, A

  HUMAN BRAIN MAPPING ( Human Brain Mapping )  46 ( 1 ) e70053   2025年01月 [ 査読有り ]

  掲載種別: 研究論文（学術雑誌）

  　概要を見る

  Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.5 ± 15.3 years; 154 (59%) female; mean response rate = 57%). Treatment response was defined as a ≥ 50% reduction in symptom severity score after 4-12 weeks post-initiation of antidepressant treatment. Structural MRI was acquired before, or < 14 days after, treatment initiation. The cortex was parcellated using FreeSurfer, from which cortical thickness and surface area were measured. We tested several machine learning pipeline configurations, which varied in (i) the way we presented the cortical data (i.e., average values per region of interest, as a vector containing voxel-wise cortical thickness and surface area measures, and as cortical thickness and surface area projections), (ii) whether we included clinical data, and the (iii) machine learning model (i.e., gradient boosting, support vector machine, and neural network classifiers) and (iv) cross-validation methods (i.e., k-fold and leave-one-site-out) we used. First, we tested if the overall predictive performance of the pipelines was better than chance, with a corrected 10-fold cross-validation permutation test. Second, we compared if some machine learning pipeline configurations outperformed others. In an exploratory analysis, we repeated our first analysis in three subpopulations, namely patients (i) from a single site, (ii) with comparable response rates, and (iii) showing the least (first quartile) and the most (fourth quartile) treatment response, which we call the extreme (non-)responders subpopulation. Finally, we explored the effect of including subcortical volumetric data on model performance. Overall, performance predicting antidepressant treatment response was not significantly better than chance (balanced accuracy = 50.5%; p = 0.66) and did not vary with alternative pipeline configurations. Exploratory analyses revealed that performance across models was only significantly better than chance in the extreme (non-)responders subpopulation (balanced accuracy = 63.9%, p = 0.001). Including subcortical data did not alter the observed model performance. Cortical structural MRI alone could not reliably predict individual pharmacotherapeutic treatment response in MDD. None of the used machine learning pipeline configurations outperformed the others. In exploratory analyses, we found that predicting response in the extreme (non-)responders subpopulation was feasible on both cortical data alone and combined with subcortical data, which suggests that specific MDD subpopulations may exhibit response-related patterns in structural data. Future work may use multimodal data to predict treatment response in MDD.

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• 専門医のための臨床精神神経薬理学テキスト

  近藤毅、新里輔鷹 ( 担当: 分担執筆 , 担当範囲: Ⅲ－4 双極性障害の治療薬 p230-238 )

  星和書店  2021年03月 ( ページ数: xxxiii, 412p )

• 精神科薬物療法に再チャレンジ : 豊富な症例と具体的な解説で学ぶ処方の実際

  近藤 毅, 新里 輔鷹 ( 担当: 分担執筆 , 担当範囲: 第7章 成人の発達障害に投与する薬 )

  星和書店  2020年07月 ( ページ数: vi, 264p )

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• うつ病の特定用語

  伊賀淳一, 高江洲義和, 新里輔鷹, 座間味優, 竹島正浩, 吉野祐太, 越智紳一郎, 馬場元

  日本うつ病学会総会プログラム・抄録集   21st   2024年

   

  J-GLOBAL

• バセドウ病に由来する症状精神病の1例

  松元純大, 松元純大, 上原敬生, 石橋孝勇, 嵩原駿平, 座間味優, 新里輔鷹, 高江洲義和

  九州精神神経学会・九州精神医療学会プログラム・抄録集   76th-69th   2024年

   

  J-GLOBAL

• 維持透析中のせん妄患者に対してブロナンセリン経皮吸収型製剤が奏功した一例

  寺師春菜, 須田和桂子, 石橋孝勇, 新里輔鷹, 高江洲義和, 近藤毅

  九州神経精神医学   69 ( 2 )   2024年

   

  J-GLOBAL

• 症状間の密性指標の探索:うつ病痕跡ネットワークの報告に基づく検討

  横山仁史, 横山仁史, 橋詰健太, 岡田剛, 高垣耕企, 板井江梨, 神原広平, 光山裕生, 新里輔鷹, 増田慶一, 神人蘭, 岡本泰昌

  日本うつ病学会総会プログラム・抄録集   21st   2024年

   

  J-GLOBAL

• 双極症 外来治療 2 軽度~中等度の抑うつエピソードの治療

  新里輔鷹, 高江洲義和

  精神科Resident   5 ( 2 )   2024年

   

  J-GLOBAL

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• 縦断的MRIによる混合性うつ病及び双極性障害の評価と合理的治療方針の確立

  若手研究

  課題番号: 22K15763

  研究期間: 2022年04月  -  2025年03月 

  代表者: 新里 輔鷹 

  直接経費: 2,300,000（円）  間接経費: 2,990,000（円）  金額合計: 690,000（円）

• 抑うつ性混合状態の定量的診断と生物学的背景の検討

  基盤研究(C)

  課題番号: 17K10311

  研究期間: 2017年04月  -  2021年03月 

  代表者: 近藤 毅, 三原 一雄, 甲田 宗良, 新里 輔鷹 

  直接経費: 3,600,000（円）  間接経費: 4,680,000（円）  金額合計: 1,080,000（円）

  　概要を見る

  本年度は、研究者らが開発した抑うつ性混合状態（depressive mixed state: DMX）の定量的な自記式評価票（DMX-12）を公表し、その症候学的構造を明らかにするとともに、本評価票を指標として一般的なうつ病エピソードにみられるDMXの実態を明らかにした（Shinzato et al, Neuropsychiatr Dis Treat, 2019）。DMX-12は「内発的な不安定さ」「脆弱な応答性」「破壊的感情/行動」の3つの症候クラスターにより構成され、うつ病の重症度が高く潜在的に双極性を有する若年患者がDMXを呈しやすいことが示唆された。破壊的感情/行動クラスターはカテゴリカル診断である混合性うつ病（mixed depression：MD）や混合性の特徴（mixed features specifier：MF）の識別に有用であった。 特に、receiver operating characteristic（ROC）解析により、DMX-12の中の過剰反応、内的緊張、思考促迫・混雑、衝動性、易刺激性、攻撃性、危険行為、不快気分の8症状の総スコアが同一のカットオフ値をもってMD、MFを高い感度と特異性で識別できることから、一定の重症度を持つDMXのスクリーニングに有用となる可能性が示唆されており、現在、これらの成果を投稿中である。 また、DMX-12を用いてDMXと自閉スペクトラム症（autism spectrum disorder：ASD）および自殺行動リスクとの関連についても検討し、MDはASDや自殺関連行動との関連が深く、ASDのうつ病エピソードにおいては「転導性」「気分易変」「衝動性」などの内発的な不安定さを特徴とすることが判明した（新里他，日本精神神経学会，2019）。