Artificial neural networks reveal sex differences in gene methylation, and connections between maternal risk factors and symptom severity in autism spectrum disorder

被引：9

作者：

Stoccoro, Andrea ^{[1
]}

Gallo, Roberta ^{[1
]}

Calderoni, Sara ^{[2
,3
]}

Cagiano, Romina ^{[2
]}

Muratori, Filippo ^{[2
,3
]}

Migliore, Lucia ^{[1
]}

Grossi, Enzo ^{[4
]}

Coppede, Fabio ^{[1
]}

机构：

[1] Univ Pisa, Med Sch, Dept Translat Res & New Surg & Med Technol, Via Roma 55, I-56126 Pisa, Italy

[2] IRCCS Stella Maris Fdn, I-56128 Pisa, Italy

[3] Univ Pisa, Dept Clin & Expt Med, Via Roma 55, I-56126 Pisa, Italy

[4] Villa Santa Maria Fdn, I-22038 Como, Italy

来源：

EPIGENOMICS | 2022年 / 14卷 / 19期

关键词：

artificial neural networks; ASD; autism spectrum disorder; DNA methylation; epigenetics; maternal risk factors; sex difference; DNA METHYLATION; PROMOTER METHYLATION; PERIPHERAL-BLOOD; FRONTAL-CORTEX; BRAIN; BDNF; RELN; PREDICTORS; BIOMARKER; SYSTEM;

D O I：

10.2217/epi-2022-0179

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Aim and methods: Artificial neural networks were used to unravel connections among blood gene methylation levels, sex, maternal risk factors and symptom severity evaluated using the Autism Diagnostic Observation Schedule 2 (ADOS-2) score in 58 children with autism spectrum disorder (ASD). Results: Methylation levels of MECP2, HTR1A and OXTR genes were connected to females, and those of EN2, BCL2 and RELN genes to males. High gestational weight gain, lack of folic acid supplements, advanced maternal age, preterm birth, low birthweight and living in rural context were the best predictors of a high ADOS-2 score. Conclusion: Artificial neural networks revealed links among ASD maternal risk factors, symptom severity, gene methylation levels and sex differences in methylation that warrant further investigation in ASD.

引用

页码：1181 / 1195

页数：16

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