On the selection of patients with developmental delay/mental retardation and autism spectrum disorders for genetic studies

2007 ◽  
Vol 143A (8) ◽  
pp. 789-790 ◽  
Author(s):  
A. Battaglia
Keyword(s):  
Mental Retardation ◽  
Autism Spectrum Disorders ◽  
Developmental Delay ◽  
Autism Spectrum ◽  
Genetic Studies ◽  
Spectrum Disorders ◽  
Selection Of Patients ◽  
Selection Of

scholarly journals Dopaminergic Gene Dosage in Autism versus Developmental Delay: From Complex Networks to Machine Learning approaches

2020 ◽  
Author(s):  
André Santos ◽  
Francisco Caramelo ◽  
Joana Barbosa de Melo ◽  
Miguel Castelo-Branco
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorders ◽  
Network Analysis ◽  
Developmental Delay ◽  
Gene Dosage ◽  
Genetic Alterations ◽  
Autism Spectrum ◽  
Compact Set ◽  
Neural Basis ◽  
Spectrum Disorders

AbstractThe neural basis of behavioural changes in Autism Spectrum Disorders (ASD) remains a controversial issue. One factor contributing to this challenge is the phenotypic heterogeneity observed in ASD, which suggests that several different system disruptions may contribute to diverse patterns of impairment between and within study samples. Here, we took a retrospective approach, using SFARI data to study ASD by focusing on participants with genetic imbalances targeting the dopaminergic system. Using complex network analysis, we investigated the relations between participants, Gene Ontology (GO) and gene dosage related to dopaminergic neurotransmission from a polygenic point of view. We converted network analysis into a machine learning binary classification problem to differentiate ASD diagnosed participants from DD (developmental delay) diagnosed participants. Using 1846 participants to train a Random Forest algorithm, our best classifier achieved on average a diagnosis predicting accuracy of 85.18% (sd 1.11%) on a test sample of 790 participants using gene dosage features. In addition, we observed that if the classifier uses GO features it was also able to infer a correct response based on the previous examples because it is tied to a set of biological process, molecular functions and cellular components relevant to the problem. This yields a less variable and more compact set of features when comparing with gene dosage classifiers. Other facets of knowledge-based systems approaches addressing ASD through network analysis and machine learning, providing an interesting avenue of research for the future, are presented through the study.Lay SummaryThere are important issues in the differential diagnosis of Autism Spectrum Disorders. Gene dosage effects may be important in this context. In this work, we studied genetic alterations related to dopamine processes that could impact brain development and function of 2636 participants. On average, from a genetic sample we were able to correctly separate autism from developmental delay with an accuracy of 85%.

scholarly journals Cerebral Palsy, Autism Spectrum Disorders, and Developmental Delay in Children Born After Assisted Conception

2009 ◽  
Vol 163 (1) ◽  
pp. 72 ◽  
Author(s):  
Dorte Hvidtjørn ◽  
Laura Schieve ◽  
Diana Schendel ◽  
Bo Jacobsson ◽  
Claus Sværke ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Autism Spectrum Disorders ◽  
Developmental Delay ◽  
Autism Spectrum ◽  
Assisted Conception ◽  
Spectrum Disorders

Autism Spectrum Disorders and Mental Retardation

2010 ◽  
pp. 186-192
Author(s):  
Jean-Michel Scherrmann ◽  
Kim Wolff ◽  
Christine A. Franco ◽  
Marc N. Potenza ◽  
Tayfun Uzbay ◽  
...  
Keyword(s):  
Mental Retardation ◽  
Autism Spectrum Disorders ◽  
Autism Spectrum ◽  
Spectrum Disorders
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