Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.
Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.
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DOI：
10.1038/s41598-021-86320-0
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发表时间：
2021-03-25
影响因子：
4.6
通讯作者：
Ben-Ari Y
中科院分区：
文献类型：
--
作者：
Caly H;Rabiei H;Coste-Mazeau P;Hantz S;Alain S;Eyraud JL;Chianea T;Caly C;Makowski D;Hadjikhani N;Lemonnier E;Ben-Ari Y
为了识别有患ASD风险的新生儿，并在出生后早期检测ASD生物标志物，我们对后来诊断为ASD或在怀孕和分娩期间常规收集的神经典型(NT)的婴儿进行了回顾性的超声和生物测量比较。我们使用有监督的机器学习算法和交叉验证技术对NT和ASD婴儿进行分类，并进行各种统计测试。将假阳性率降至最低，96%的NT和41%的ASD婴儿被确定为阳性预测值为77%。我们确定了以下与ASD相关的生物标志物：性别、母亲自身免疫性疾病的家族史、母亲对CMV的免疫接种、CMV抗体水平、胎儿头部旋转的时间、妊娠晚期股骨长度、妊娠晚期白细胞计数、分娩时胎心率、新生儿喂养以及出生后与出生后1天的温差。此外，统计模型显示，38%的ASD高危婴儿的胎儿头围明显大于年龄匹配的NT婴儿，这表明ASD幼儿报告的大脑更大是源于宫内。我们的结果表明，妊娠随访测量可能提供ASD的早期预后，使症状前的行为干预能够有效地减轻ASD的发展后遗症。
To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological measurements of babies diagnosed later with ASD or neurotypical (NT) that are collected routinely during pregnancy and birth. We used a supervised machine learning algorithm with a cross-validation technique to classify NT and ASD babies and performed various statistical tests. With a minimization of the false positive rate, 96% of NT and 41% of ASD babies were identified with a positive predictive value of 77%. We identified the following biomarkers related to ASD: sex, maternal familial history of auto-immune diseases, maternal immunization to CMV, IgG CMV level, timing of fetal rotation on head, femur length in the 3rd trimester, white blood cell count in the 3rd trimester, fetal heart rate during labor, newborn feeding and temperature difference between birth and one day after. Furthermore, statistical models revealed that a subpopulation of 38% of babies at risk of ASD had significantly larger fetal head circumference than age-matched NT ones, suggesting an in utero origin of the reported bigger brains of toddlers with ASD. Our results suggest that pregnancy follow-up measurements might provide an early prognosis of ASD enabling pre-symptomatic behavioral interventions to attenuate efficiently ASD developmental sequels.
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影响因子：
3
作者：
Combrisson, Etienne;Jerbi, Karim
通讯作者：
Jerbi, Karim
影响因子：
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作者：
Emerson RW;Adams C;Nishino T;Hazlett HC;Wolff JJ;Zwaigenbaum L;Constantino JN;Shen MD;Swanson MR;Elison JT;Kandala S;Estes AM;Botteron KN;Collins L;Dager SR;Evans AC;Gerig G;Gu H;McKinstry RC;Paterson S;Schultz RT;Styner M;IBIS Network;Schlaggar BL;Pruett JR Jr;Piven J
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Piven J
影响因子：
4.7
作者：
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通讯作者：
Nordahl, Christine Wu
DOI：
10.1073/pnas.1604288113
发表时间：
2016-12-13
影响因子：
11.1
作者：
Chareyron, Loic J.;Amaral, David G.;Lavenex, Pierre
通讯作者：
Lavenex, Pierre
影响因子：
4.7
作者：
Bonnet-Brilhault, Frederique;Rajerison, Toky A.;Roux, Sylvie
通讯作者：
Roux, Sylvie