1. {{International Society for Autism Research News}}. {Autism Res};2009 (Jul 16);2(3):182.
2. Benayed R, Choi J, Matteson PG, Gharani N, Kamdar S, Brzustowicz LM, Millonig JH. {{Autism-Associated Haplotype Affects the Regulation of the Homeobox Gene, ENGRAILED 2}}. {Biol Psychiatry};2009 (Jul 16)
BACKGROUND: Association analysis identified the homeobox transcription factor, ENGRAILED 2 (EN2), as a possible autism spectrum disorder (ASD) susceptibility gene (ASD [MIM 608636]; EN2 [MIM 131310]). The common alleles (underlined) of two intronic single nucleotide polymorphisms (SNPs), rs1861972 (A/G) and rs1861973 (C/T), are over-transmitted to affected individuals both singly and as a haplotype in three separate datasets (518 families total, haplotype p = .00000035). METHODS: Further support that EN2 is a possible ASD susceptibility gene requires the identification of a risk allele, a DNA variant that is consistently associated with ASD but is also functional. To identify possible risk alleles, additional association analysis and linkage disequilibrium (LD) mapping were performed. Candidate polymorphisms were then tested for functional differences by luciferase (Luc) reporter transfections and electrophoretic mobility shift assays (EMSAs). RESULTS: Association analysis of additional EN2 polymorphisms and LD mapping with Hapmap SNPs identified the rs1861972-rs1861973 haplotype as the most appropriate candidate to test for functional differences. Luciferase reporters for the two common rs1861972-rs1861973 haplotypes (A-C and G-T) were then transfected into human and rat cell lines as well as primary mouse neuronal cultures. In all cases the A-C haplotype resulted in a significant increase in Luc levels (p < .005). The EMSAs were then performed, and nuclear factors were bound specifically to the A and C alleles of both SNPs. CONCLUSIONS: These data indicate that the A-C haplotype is functional and, together with the association and LD mapping results, supports EN2 as a likely ASD susceptibility gene and the A-C haplotype as a possible risk allele.
3. King MD, Fountain C, Dakhlallah D, Bearman PS. {{Estimated Autism Risk and Older Reproductive Age}}. {Am J Public Health};2009 (Jul 16)
Objectives. We sought to estimate the risk for autism associated with maternal and paternal age across successive birth cohorts.Methods. We linked birth records and autism diagnostic records from the California Department of Developmental Services for children born in California between 1992 and 2000 to calculate the risk associated with maternal and paternal age for each birth cohort as well as for the pooled data.Results. The categorical risks associated with maternal age over 40 years ranged from a high of 1.84 (95% confidence interval [CI]=1.37, 2.47) to a low of 1.27 (95% CI=0.95, 1.69). The risk associated with paternal age ranged from 1.29 (95% CI=1.03, 1.6) to 1.71 (95% CI=1.41, 2.08).Conclusions. Pooling data across multiple birth cohorts inflates the risk associated with paternal age. Analyses that do not suffer from problems produced by pooling across birth cohorts demonstrated that advanced maternal age, rather than paternal age, may pose greater risk. Future research examining parental age as a risk factor must be careful to avoid the paradoxes that can arise from pooling data, particularly during periods of social demographic change.
4. Mayes SD, Calhoun SL, Murray MJ, Morrow JD, Yurich KK, Mahr F, Cothren S, Purichia H, Bouder JN, Petersen C. {{Comparison of Scores on the Checklist for Autism Spectrum Disorder, Childhood Autism Rating Scale, and Gilliam Asperger’s Disorder Scale for Children with Low Functioning Autism, High Functioning Autism, Asperger’s Disorder, ADHD, and Typical Development}}. {J Autism Dev Disord};2009 (Jul 16)
Reliability and validity for three autism instruments were compared for 190 children with low functioning autism (LFA), 190 children with high functioning autism or Asperger’s disorder (HFA), 76 children with attention deficit hyperactivity disorder (ADHD), and 64 typical children. The instruments were the Checklist for Autism Spectrum Disorder (designed for children with LFA and HFA), Childhood Autism Rating Scale (CARS) for children with LFA, and Gilliam Asperger’s Disorder Scale (GADS). For children with LFA or ADHD, classification accuracy was 100% for the Checklist and 98% for the CARS clinician scores. For children with HFA or ADHD, classification accuracy was 99% for the Checklist and 93% for the GADS clinician scores. Clinician-parent diagnostic agreement was high (90% Checklist, 90% CARS, and 84% GADS).
5. Minagawa-Kawai Y, Naoi N, Kikuchi N, Yamamoto JI, Nakamura K, Kojima S. {{Cerebral laterality for phonemic and prosodic cue decoding in children with autism}}. {Neuroreport};2009 (Jul 16)
This study examined the cerebral functional lateralization, from a phonological perspective, in children with autism spectrum disorder (ASD) and typically developing children (TDC). With near infrared spectroscopy, we measured auditory evoked-responses in the temporal areas to phonemic and prosodic contrasts in word contexts. The results of TDC showed stronger left-dominant and right-dominant responses to phonemic and prosodic differences, respectively. Furthermore, although ASD children displayed similar tendencies, the functional asymmetry for phonemic changes was relatively weak, suggesting less-specialized left-brain functions. The typical asymmetry for the prosodic condition was further discussed in terms of acoustic-physical perceptual ability of ASD children. The study revealed differential neural recruitment in decoding phonetic cues between ASD children and TDC and verified the applicability of near infrared spectroscopy as a suitable neuroimaging method for children with developmental disorders.
6. Senju A, Southgate V, White S, Frith U. {{Mindblind Eyes: An Absence of Spontaneous Theory of Mind in Asperger Syndrome}}. {Science};2009 (Jul 16)
Adults with Asperger syndrome can understand mental states such as desires and beliefs (mentalizing) when explicitly prompted to do so, despite having impairments in social communication. We directly tested the hypothesis that such individuals nevertheless fail to mentalize spontaneously. To this end, we used an eye tracking task that has revealed the spontaneous ability to mentalize in typically developing infants. We showed that, like infants, neurotypical adults’ (N = 17) eye movements anticipated an actor’s behavior on the basis of her false belief. This was not the case for individuals with Asperger syndrome (N = 19). Thus, these individuals do not attribute mental states spontaneously, but may be able to do so in explicit tasks through compensatory learning.
