Ben-Ari Y, Caly H, Rabiei H, Lemonnier É. [Early prognostic of ASD: A challenge].
Med Sci (Paris) 2022;
38:431-437. [PMID:
35608465 DOI:
10.1051/medsci/2022054]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
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. Here, we discuss the various approaches that have been used to enable an early diagnosis. We have ourselves used an approach based on a "without a priori" machine learning analysis of all maternity biological and ultrasound data available in French maternities (around 116) in utero and after birth. This program made it possible to identify at birth almost all (96%) of babies who will be later neurotypical and around half of those who will be diagnosed with ASD. Some of the parameters allowing this identification were largely unexpected with no known links with ASD. This approach will enable an early identification of babies at risk, but also might be used to diagnose ASD later on, and perhaps could help to get a better understanding of the heterogeneity of ASD.
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