1. Fernell E. {{The co-occurrence of autism and birth defects}}. {Dev Med Child Neurol};2009 (Mar 30)

2. Hendren RL, Bertoglio K, Ashwood P, Sharp F. {{Mechanistic biomarkers for autism treatment}}. {Med Hypotheses};2009 (Jul 18)

OBJECTIVE: Autism is a syndrome with a number of etiologies with differing mechanisms that lead to abnormal development. This review highlights the need to identify autism subgroups as they each might require unique approaches for prevention or treatment. METHODS: Targeting treatments to specific mechanisms and utilizing biomarkers can more rapidly advance our understanding of how to classify and treat autism subgroups based on translational mechanisms. We illustrate this approach using mechanisms that may influence the course of autism and provide rationale for selected biomarkers that could guide treatments targeted anywhere from DNA to symptom expression. CONCLUSIONS: The use of potential biomarkers that point to specific mechanisms of disordered neurodevelopment will help identify meaningful subtypes of autism and will help tailor treatment or prevention strategies for each mechanism rather than solely to a symptom category.

3. Jacob FD, Ramaswamy V, Andersen J, Bolduc FV. {{Atypical Rett syndrome with selective FOXG1 deletion detected by comparative genomic hybridization: case report and review of literature}}. {Eur J Hum Genet};2009 (Jul 22)

Rett syndrome is a severe neurodegenerative disorder characterized by acquired microcephaly, communication dysfunction, psychomotor regression, seizures and stereotypical hand movements. Mutations in methyl CpG binding protein 2 (MECP2) are identified in most patients with classic Rett syndrome. Genetic studies in patients with a Rett variant have expanded the spectrum of underlying genetic etiologies. Recently, a deletion encompassing several genes in the long arm of chromosome 14 has been associated with the congenital Rett-syndrome phenotype. Using array-based comparative genomic hybridization, we identified a 3-year-old female with a Rett-like syndrome carrying a de novo single-gene deletion of FOXG1. Her presentation included intellectual disability, epilepsy and a Rett-like phenotype. The variant features included microcephaly at birth and prominent synophrys. Our results confirm that congenital Rett syndrome can be caused by copy-number variation in FOXG1 and expand the clinical phenotypic spectrum of FOXG1 defect in humans.European Journal of Human Genetics advance online publication, 22 July 2009; doi:10.1038/ejhg.2009.95.

4. Loo CY, Graham RM, Hughes CV. {{Behaviour guidance in dental treatment of patients with autism spectrum disorder}}. {Int J Paediatr Dent};2009 (Jul 9)

International Journal of Paediatric Dentistry 2009Background. Autism spectrum disorder (ASD) is a neurodevelopmental disorder categorized into autism, pervasive developmental disorder – not otherwise specified (PDD-NOS) and Asperger syndrome. Aims. To identify factors associated with the behaviour of patients with ASD in a dental setting, use of general anaesthesia (GA), and protective stabilization. Design. The dental charts of 395 patients with ASD patients and 386 unaffected patients were reviewed. The following data were analysed: ASD diagnosis, age, gender, residence, seizure disorder, additional diagnosis (mental retardation, cerebral palsy, self-injurious behaviour or pica), medications, caries prevalence and severity, dental treatment history, behaviour, and behaviour guidance technique(s) used. Results. Within both groups, younger patients were more uncooperative. ASD patients with autism were more uncooperative than patients with PDD-NOS; patients with an additional diagnosis were also more uncooperative. ASD patients with higher caries severity, who were uncooperative or female, were more likely to require GA. Use of protective stabilization was associated with lower caries severity, presence of seizure disorder, uncooperative behaviour, male gender, or residency in a group home/institution. Conclusions. Autism spectrum disorder patients with autism, younger age and an additional diagnosis were more uncooperative. Factors associated with the use of GA and protective stabilization in patients with ASD were also identified.

5. Rubin DM, Feudtner C, Localio R, Mandell DS. {{State Variation in Psychotropic Medication Use by Foster Care Children With Autism Spectrum Disorder}}. Pediatrics;2009 (Jul 20)

Objective: The objective of this study was to compare on a national cohort of children with autism spectrum disorder (ASD) the concurrent use of >/=3 psychotropic medications between children in foster care and children who have disabilities and receive Supplemental Security Income, and to describe variation among states in the use of these medications by children in foster care. Methods: Studied was the concurrent use of >/=3 classes of psychotropic medications, identified from the 2001 Medicaid claims of 43 406 children who were aged 3 to 18 years and had >/=1 annual claim for ASD. Medicaid enrollment as a child in foster care versus a child with disabilities was compared. Multilevel logistic regression, clustered at the state level and controlling for demographics and comorbidities, yielded standardized (adjusted) estimates of concurrent use of >/=3 medications and estimated variation in medication use within states that exceeded 1 and 2 SDs from the average across states. Results: Among children in foster care, 20.8% used >/=3 classes of medication concurrently, compared with 10.1% of children who were classified as having a disability. Differences grew in relationship to overall use of medications within a state; for every 5% increase in concurrent use of >/=3 medication classes by a state’s population with disabilities, such use by children in a state’s foster care population increased by 8.3%. Forty-three percent (22) of states were >1 SD from the adjusted mean for children who were using >/=3 medications concurrently, and 14% (7) of the states exceeded 2 SDs. Conclusions: Among children with ASD, children in foster care were more likely to use >/=3 medications concurrently than children with disabilities. State-level differences underscore policy or programmatic differences that might affect the receipt of medications in this population.