[Early prognostic of ASD: A challenge].

Autism Spectrum Disorders (ASD) are born in the womb generated by intrauterine genetic or environmental insult. ASD diagnostic is made at the age of 3-5 years in Europe and in the US. Relying on this, we have tested the hypothesis of identifying already at birth babies who might be diagnosed later with ASD, thereby facilitating an early use of psychoeducative techniques to attenuate the severity of the symptoms.

Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.

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%.