Blood metabolic signatures of hikikomori, pathological social withdrawal.
Blood metabolic signatures of hikikomori, pathological social withdrawal.
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DOI：
10.1080/19585969.2022.2046978
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发表时间：
2021
影响因子：
8.3
通讯作者：
中科院分区：
文献类型：
--
作者：
一种严重的病理性社交退缩--“隐居小森”--已经在日本得到认可，并在全球范围内蔓延，成为一个全球性的健康问题。Hikikomori的病理生理机制尚不清楚，其生物学特性也尚不清楚。无药物的隐匿症患者(n = 42例)和健康对照(n = 41例)。心理评估的严重程度，躲猫猫和抑郁症。进行血液生化检测和血浆代谢组学分析。在综合信息的基础上，创建了机器学习模型，以区分Hikikomori病例和健康对照组，预测Hikikomori的严重程度，对病例进行分层，并识别对每个模型有贡献的代谢特征。胆红素、精氨酸、鸟氨酸和血清精氨酸酶在男性隐匿症患者中有显著差异。判别随机森林模型性能良好，ROC曲线下面积为0.854(可信区间=0.648-1.000)。为了预测Hikikomori的严重程度，成功地建立了具有高度线性和实用精度的偏最小二乘偏最小二乘回归模型。此外，血清尿酸和血浆胆固醇酯有助于病例的分层。这些发现揭示了Hikikomori的血液代谢特征，这是阐明Hikikomori的病理生理学的关键，也是监测康复治疗过程的有用指标。
A severe form of pathological social withdrawal, ‘hikikomori,’ has been acknowledged in Japan, spreading worldwide, and becoming a global health issue. The pathophysiology of hikikomori has not been clarified, and its biological traits remain unexplored. Drug-free patients with hikikomori (n = 42) and healthy controls (n = 41) were recruited. Psychological assessments for the severity of hikikomori and depression were conducted. Blood biochemical tests and plasma metabolome analysis were performed. Based on the integrated information, machine-learning models were created to discriminate cases of hikikomori from healthy controls, predict hikikomori severity, stratify the cases, and identify metabolic signatures that contribute to each model. Long-chain acylcarnitine levels were remarkably higher in patients with hikikomori; bilirubin, arginine, ornithine, and serum arginase were significantly different in male patients with hikikomori. The discriminative random forest model was highly performant, exhibiting an area under the ROC curve of 0.854 (confidential interval = 0.648–1.000). To predict hikikomori severity, a partial least squares PLS-regression model was successfully created with high linearity and practical accuracy. In addition, blood serum uric acid and plasma cholesterol esters contributed to the stratification of cases. These findings reveal the blood metabolic signatures of hikikomori, which are key to elucidating the pathophysiology of hikikomori and also useful as an index for monitoring the treatment course for rehabilitation.
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影响因子：
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