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The immuno-behavioural covariation associated with the treatment response to bumetanide in young children with autism spectrum disorder

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机构: [1]Department of Computational Biology, School of Life Sciences, Fudan University, 200438 Shanghai, China. [2]Department of Developmental and Behavioural Pediatric & Child Primary Care, Brain and Behavioural Research Unit of Shanghai Institute for Pediatric Research and MOE-Shanghai Key Laboratory for Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, 200092 Shanghai, China. [3]Center for Experimental Studies and Research, The First Affiliated Hospital of Kunming Medical University, 650032 Kunming, China. [4]Collaborative Innovation Center for Brain Science, Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China. [5]Department of Psychiatry and the Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge CB21TN, UK. [6]National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Institutes of Brain Science and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433 Shanghai, China. [7]Human Phenome Institute, Fudan University, 201203 Shanghai, China. [8]Center for Computational Psychiatry, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired, Research Institute of Intelligent Complex Systems, Fudan University, 200040 Shanghai, China
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Bumetanide, a drug being studied in autism spectrum disorder (ASD) may act to restore gamma-aminobutyric acid (GABA) function, which may be modulated by the immune system. However, the interaction between bumetanide and the immune system remains unclear. Seventy-nine children with ASD were analysed from a longitudinal sample for a 3-month treatment of bumetanide. The covariation between symptom improvements and cytokine changes was calculated and validated by sparse canonical correlation analysis. Response patterns to bumetanide were revealed by clustering analysis. Five classifiers were used to test whether including the baseline information of cytokines could improve the prediction of the response patterns using an independent test sample. An immuno-behavioural covariation was identified between symptom improvements in the Childhood Autism Rating Scale (CARS) and the cytokine changes among interferon (IFN)-gamma, monokine induced by gamma interferon and IFN-alpha 2. Using this covariation, three groups with distinct response patterns to bumetanide were detected, including the best (21.5%, n = 17; Hedge's g of improvement in CARS = 2.16), the least (22.8%, n = 18; g = 1.02) and the medium (55.7%, n = 44; g = 1.42) responding groups. Including the cytokine levels significantly improved the prediction of the best responding group before treatment (the best area under the curve, AUC = 0.832) compared with the model without the cytokine levels (95% confidence interval of the improvement in AUC was [0.287, 0.319]). Cytokine measurements can help in identifying possible responders to bumetanide in ASD children, suggesting that immune responses may interact with the mechanism of action of bumetanide to enhance the GABA function in ASD.

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大类 | 1 区 医学
小类 | 1 区 精神病学
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大类 | 1 区 医学
小类 | 1 区 精神病学
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Q1 PSYCHIATRY
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Q1 PSYCHIATRY

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第一作者机构: [1]Department of Computational Biology, School of Life Sciences, Fudan University, 200438 Shanghai, China.
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通讯机构: [6]National Clinical Research Center for Aging and Medicine at Huashan Hospital, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Institutes of Brain Science and Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433 Shanghai, China. [7]Human Phenome Institute, Fudan University, 201203 Shanghai, China. [8]Center for Computational Psychiatry, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired, Research Institute of Intelligent Complex Systems, Fudan University, 200040 Shanghai, China
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