Zhang Yushan, Maimaiti Rena, Lou Shan, Abula Reyila, Abulaiti Adila, Kelimu Asimuguli
Department of Child and Maternal Health, School of Public Health, Xinjiang Medical University, Urumqi 830011, PR China; Key Laboratory of Special Environment and Health Research in Xinjiang, Urumqi 830001, PR China.
Department of Child Health, Health Management Institute, The First Affiliated Hospital, Xinjiang Medical University, Urumqi 830001, PR China.
J Affect Disord. 2022 Dec 1;318:1-6. doi: 10.1016/j.jad.2022.08.130. Epub 2022 Aug 31.
Changes of toxic metals and essential elements during childhood may be the risk factor of autism spectrum disorder (ASD). This research established an accurate personalized predictive model of ASD behaviors among children by using the blood element detection index of children in Xinjiang, China.
A total of 1537 children (240 ASD behavior children and 1297 non-ASD behavior children) aged 0-7 were collected from September 2018 to September 2019 in Urumqi Children's Hospital and the health management institute of Xinjiang Medical University. For measuring the copper (Cu), zinc (Zn), magnesium (Mg), iron (Fe), calcium (Ca), lead (Pb), and cadmium (Cd), 80 μL of blood was taken from each participant's ring finger. Univariate logistic regression analysis was used to select predictors, then the multivariate logistic regression was used to establish the predictive model. The discriminability, calibration and clinical validity of the model were evaluated by the receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test and decision curve analysis (DCA).
Gender, concentrations of Pb, Ca and Zn in children's blood specimens were found to be the independent risk factors of ASD behaviors and were used to develop the nomogram model. The area under the ROC curve (AUC) in the development group (AUC = 0.778) and the validation group (AUC = 0.775) showed the model had discrimination ability. The calibration curve indicated the model was accurate, and the DCA proved its clinical application value.
The nomogram model can be used as a reliable tool to predict the risk of ASD behaviors among children.
儿童期有毒金属和必需元素的变化可能是自闭症谱系障碍（ASD）的危险因素。本研究利用中国新疆儿童的血液元素检测指标，建立了准确的儿童ASD行为个性化预测模型。
2018年9月至2019年9月，从乌鲁木齐儿童医院和新疆医科大学健康管理研究所收集了1537名0至7岁儿童（240名有ASD行为儿童和1297名无ASD行为儿童）。从每位参与者的无名指采集80μL血液，用于测量铜（Cu）、锌（Zn）、镁（Mg）、铁（Fe）、钙（Ca）、铅（Pb）和镉（Cd）。采用单因素逻辑回归分析选择预测因素，然后采用多因素逻辑回归建立预测模型。通过受试者工作特征（ROC）曲线、Hosmer-Lemeshow检验和决策曲线分析（DCA）对模型的判别能力、校准和临床有效性进行评估。
发现儿童血液标本中的性别、Pb、Ca和Zn浓度是ASD行为的独立危险因素，并用于建立列线图模型。开发组（AUC = 0.778）和验证组（AUC = 0.775）的ROC曲线下面积（AUC）表明模型具有判别能力。校准曲线表明模型准确，DCA证明了其临床应用价值。
列线图模型可作为预测儿童ASD行为风险的可靠工具。
