American Journal of Medical Genetics Part C : Seminars in Medical Genetics : Autism and intellectual disability : Two sides of the same coin

samedi 28 avril 2012

La revue American Journal of Medical Genetics consacre son numéro du mois de mai 2012 à l’autisme et à la déficience intellectuelle.

Autism and intellectual disability : Two sides of the same coin

1. Schwartz CE, Neri G. Autism and intellectual disability : Two sides of the same coin. American Journal of Medical Genetics Part C : Seminars in Medical Genetics. 2012 ; 160C(2) : 89-90.

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2. Fisch GS. Nosology and epidemiology in autism : Classification counts. American Journal of Medical Genetics Part C : Seminars in Medical Genetics. 2012 ; 160C(2) : 91-103.

Since its initial description by Kanner in 1943, the criteria by which a diagnosis of autism or autism-like disorders was made—and their alleged etiologies portrayed—have undergone manifold changes, from a psychiatric disorder engendered by “refridgerator” parents to a neurodevelopmental disability produced in the main by genetic abnormalities. In addition, the behavioral characterization of autism has also entered the public consciousness and professional domains increasingly in the past 30 years, the effects of which we are continually coming to terms. A diagnosis of autism that once seemed quite unusual is now considered almost epidemic. Increasing numbers of individuals diagnosed with autism and related pervasive developmental disabilities will, in turn, affect the calculated prevalence of the disorder. In this essay, I attempt to account for the increasing prevalence of autism and autism-related disorders by examining its changing criteria, the individuals and instruments used to make the diagnosis, the reliability and validity of same, and the sample sizes and other aspects of the methodology needed to make an accurate estimate of its prevalence.

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3. Gurrieri F. Working up autism : The practical role of medical genetics. American Journal of Medical Genetics Part C : Seminars in Medical Genetics. 2012 ; 160C(2) : 104-10.

The autism spectrum disorders (ASD) comprise a group of neurobehavioral phenotypes of heterogeneous etiology. In spite of a worldwide extensive research effort to unravel the genetic mystery of autism, medical geneticists are still facing an embarrassing lack of knowledge in dealing with the diagnosis, and consequently prognosis, of a child with autism. However, some lessons can be learned from accumulating experience in the clinical and molecular genetic evaluation of children with this condition. Patient evaluation, indications for molecular testing and counseling are the three aspects that will be discussed in this review.

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4. Zappella M. Reversible autism and intellectual disability in children. American Journal of Medical Genetics Part C : Seminars in Medical Genetics. 2012 ; 160C(2) : 111-7.

Studies on young children with reversible autism and intellectual disability are discussed. Present evidence suggests a clear cause in a minority of cases including early institutionalization, Landau and Kleffner syndrome, and other early onset epilepsies, intrauterine rubella, and blindness. The majority of cases have normal laboratory results and some have early onset Tourette syndrome. Preliminary data of a follow-up study of this last group are reported in 15 patients suggesting the possibility of two subgroups, one represented by early onset Tourette syndrome phenotype, characterized by a positive family history, and by its appearance at the same time as regression and persistence into adolescence while the other of a different nature. Genetic studies could be of help to clarify this issue and support a diagnosis of favorable outcome in young children.

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5. Coe BP, Girirajan S, Eichler EE. The genetic variability and commonality of neurodevelopmental disease. American Journal of Medical Genetics Part C : Seminars in Medical Genetics. 2012 ; 160C(2) : 118-29.

Despite detailed clinical definition and refinement of neurodevelopmental disorders and neuropsychiatric conditions, the underlying genetic etiology has proved elusive. Recent genetic studies have revealed some common themes : considerable locus heterogeneity, variable expressivity for the same mutation, and a role for multiple disruptive events in the same individual affecting genes in common pathways. Recurrent copy number variation (CNV), in particular, has emphasized the importance of either de novo or essentially private mutations creating imbalances for multiple genes. CNVs have foreshadowed a model where the distinction between milder neuropsychiatric conditions from those of severe developmental impairment may be a consequence of increased mutational burden affecting more genes.

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6. Kou Y, Betancur C, Xu H, Buxbaum JD, Ma’ayan A. Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability. American Journal of Medical Genetics Part C : Seminars in Medical Genetics. 2012 ; 160C(2) : 130-42.

Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (∼1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein–protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.

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