1. Anderson BM, Schnetz-Boutaud NC, Bartlett J, Wotawa AM, Wright HH, Abramson RK, Cuccaro ML, Gilbert JR, Pericak-Vance MA, Haines JL. {{Examination of association of genes in the serotonin system to autism}}. {Neurogenetics};2009 (Jul);10(3):209-216.

Autism is characterized as one of the pervasive developmental disorders, a spectrum of often severe behavioral and cognitive disturbances of early development. The high heritability of autism has driven multiple efforts to identify genetic variation that increases autism susceptibility. Numerous studies have suggested that variation in peripheral and central metabolism of serotonin (5-hydroxytryptamine) may play a role in the pathophysiology of autism. We screened 403 autism families for 45 single nucleotide polymorphisms in ten serotonin pathway candidate genes. Although genome-wide linkage scans in autism have provided support for linkage to various loci located within the serotonin pathway, our study does not provide strong evidence for linkage to any specific gene within the pathway. The most significant association (p = 0.0002; p = 0.02 after correcting for multiple comparisons) was found at rs1150220 (HTR3A) located on chromosome 11 ( approximately 113 Mb). To test specifically for multilocus effects, multifactor dimensionality reduction was employed, and a significant two-way interaction (p value = 0.01) was found between rs10830962, near MTNR1B (chromosome11; 92,338,075 bp), and rs1007631, near SLC7A5 (chromosome16; 86,413,596 bp). These data suggest that variation within genes on the serotonin pathway, particularly HTR3A, may have modest effects on autism risk.

2. Annaz D, Karmiloff-Smith A, Johnson MH, Thomas MS. {{A cross-syndrome study of the development of holistic face recognition in children with autism, Down syndrome, and Williams syndrome}}. {J Exp Child Psychol};2009 (Apr);102(4):456-486.

We report a cross-syndrome comparison of the development of holistic processing in face recognition in school-aged children with developmental disorders: autism, Down syndrome, and Williams syndrome. The autism group was split into two groups: one with high-functioning children and one with low-functioning children. The latter group has rarely been studied in this context. The four disorder groups were compared with typically developing children. Cross-sectional trajectory analyses were used to compare development in a modified version of Tanaka and Farah’s part-whole task. Trajectories were constructed linking part-whole performance either to chronological age or to several measures of mental age (receptive vocabulary, visuospatial construction, and the Benton Facial Recognition Test). In addition to variable delays in onset and rate of development, we found an atypical profile in all disorder groups. These profiles were atypical in different ways, indicating multiple pathways to, and variable outcomes in, the development of face recognition. We discuss the implications for theories of face recognition in both atypical and typical development, including the idea that part-whole and rotation manipulations may tap different aspects of holistic and/or configural processing.

3. Burd L, Li Q, Kerbeshian J, Klug MG, Freeman RD. {{Tourette syndrome and comorbid pervasive developmental disorders}}. {J Child Neurol};2009 (Feb);24(2):170-175.

We examined the rates of comorbid pervasive developmental disorders in participants with Tourette syndrome. We used 7288 participants from the Tourette Syndrome International Database Consortium Registry. We found 334 (4.6%; 1 of every 22 participants) with Tourette syndrome had a comorbid pervasive developmental disorder. In participants with Tourette syndrome and comorbid pervasive developmental disorders, 98.8% had one or more comorbidities (pervasive developmental disorder was not counted) compared to 13.2% in the group of participants with Tourette syndrome only. Variables from logistic modeling that were significant predictors of Tourette syndrome and pervasive developmental disorders were: male gender; no family history of tics/Tourette syndrome; and an increased number of comorbidities (P < .001). We found rates of comorbid Tourette syndrome and pervasive developmental disorders to be increased by 13 times. Identification of differences between subgroups of patients with Tourette syndrome may increase understanding of syndromal susceptibility, severity, and outcome.

4. Frye RE, Beauchamp MS. {{Receptive language organization in high-functioning autism}}. {J Child Neurol};2009 (Feb);24(2):231-236.

One of the core defining components of autism is impairment in communication, typically manifested as a delay in speech development. To date, neuroimaging studies have shed limited light on the mechanisms behind delay in speech development in autism. We performed magnetoencephalographic-based auditory language mapping in 2 cases of high-functioning autism. Overall, 2 distinct characteristics were found, such as the use of atypical language pathways and cortical hyperexcitability. These neurophysiological findings parallel those reported in 2 other developmental disorders, developmental dyslexia and Rett syndrome. We discuss common mechanisms that may account for cognitive delays across these developmental disorders.

5. Johnson S, Marlow N. {{Positive screening results on the modified checklist for autism in toddlers: implications for very preterm populations}}. {J Pediatr};2009 (Apr);154(4):478-480.

6. Kuban KC, O’Shea TM, Allred EN, Tager-Flusberg H, Goldstein DJ, Leviton A. {{Positive screening on the Modified Checklist for Autism in Toddlers (M-CHAT) in extremely low gestational age newborns}}. {J Pediatr};2009 (Apr);154(4):535-540 e531.

OBJECTIVE: To test the hypothesis that children born preterm are more likely to screen positive on the M-CHAT for an autism spectrum disorder. STUDY DESIGN: We compared the M-CHAT positive rate of those with cerebral palsy, cognitive impairment, and vision and hearing impairments to those without such deficits. RESULTS: Relative to children who could walk, the odds for screening positive on the M-CHAT were increased 23-fold for those unable to sit or stand independently and more than 7-fold for those requiring assistance to walk. Compared with children without a diagnosis of cerebral palsy, those with quadriparesis were 13 times more likely to screen positive, and those with hemiparesis were 4 times more likely to screen positive. Children with major vision or hearing impairments were 8 times more likely to screen positive than those without such impairments. Relative to those with a Mental Development Index (MDI) of >70, the odds for screening positive were increased 13-fold for those with an MDI of <55 and more than 4-fold for those with an MDI of 55 to 69. CONCLUSIONS: Major motor, cognitive, visual, and hearing impairments appear to account for more than half of the positive M-CHAT screens in extremely low gestational age newborns. Even after those with such impairments were eliminated, 10% of children–nearly double the expected rate–screened positive.

7. Li MR, Pan H, Bao XH, Zhu XW, Cao GN, Zhang YZ, Wu XR. {{[Methyl-CpG-binding protein 2 gene and CDKL5 gene mutation in patients with Rett syndrome: analysis of 177 Chinese pediatric patients]}}. {Zhonghua Yi Xue Za Zhi};2009 (Feb 3);89(4):224-229.

OBJECTIVE: To study the spectrum of mutations in methyl-CpG-binding protein 2 gene (MECP2) and cyclin-dependent kinase-like 5 gene (CDKL5) in Chinese pediatric patients with Rett syndrome (RTT), and establish a simple, quick, and efficient gene test method as well as screen a strategy of genetic diagnosis for RTT. METHODS: Genomic DNA was extracted using standard procedures from the peripheral blood leukocytes of 117 pediatric patients diagnosed from 1987 to 2007. PCR was used to amplify the exons 1 – 4 of MECP2 using published primers. If no mutation was identified after screening exons 2 – 4, exon 1 was screened. If no mutation was identified in MECP2 by sequencing, multiplex ligation dependent probe amplification (MLPA) was employed to screen for large deletions by using P015C kit. If no mutation was identified in the MECP2 by sequencing and MLPA respectively, then the coding region of CDKL5 was screened by denaturing high performance liquid chromatography (DHPLC). RESULTS: The total mutation frequency in MECP2 and CDKL5 genes among all RTT patients was 82%. MECP2 mutations were found in 86% (137/159) of the patients with classical RTT and in 44% (8/18) of those with atypical RTT. Most of the mutations were missense mutations, accounting for 39%, followed in order of frequency by nonsense mutations 28%, frame shift mutations 17% and large deletions 14.5%. The eight most frequent MECP2 mutations were p.T158M (13%), p.R168X (12%), c.806delG (7%), p.R255X (6%), p.R270X (5%), p.R133C (5%), p.R306C (4%), and p.R106W (3%), with p.T158M as the most common of the MECP2 mutations and c.806delG as a hotspot mutation in Chinese patients with RTT. Only one synonymous mutation was identified in CDKL5. CONCLUSION: The spectrum of MECP2 mutations within the mainland Chinese RTT patients is similar to that of those patients reported in the world. p.T158M, p.R168X, c.806delG, p.R255X, p.R270X, p.R133C, p.R306C, and p.R106W are the hotspot mutations of MECP2 and c.806delG is a specific hotspot mutation in Chinese patients with RTT. The most effective method to screen mutations is to screen the exon 4. MLPA is an effective supplement to the routine methods.

8. Peng CZ, Hatlestad P, Klug MG, Kerbeshian J, Burd L. {{Health care costs and utilization rates for children with pervasive developmental disorders in North Dakota from 1998 to 2004: impact on Medicaid}}. {J Child Neurol};2009 (Feb);24(2):140-147.

In this study, we used data from the North Dakota Medicaid claims database from 1998 through 2004 to estimate health care utilization rates and cost of care for children with pervasive developmental disorders. From the dataset, we developed a group comprised of children with pervasive developmental disorders (n = 546) and 2 comparison groups: children with other mental disorders (n = 18 363) and children who did not have pervasive developmental disorders or any mental disorders (n = 63 202). Participants with pervasive developmental disorders utilized 4.6% of all visits and 5% of the total cost of health care over the 7-year period. The average annual cost of care for children with pervasive developmental disorders was much higher than the cost for children without mental disorders for outpatient services ($5051 vs $360, ratio = 14:1), inpatient services ($1585 vs $458, ratio = 3.4:1), and pharmacy services ($1258 vs $82, ratio = 15:1). Children with pervasive developmental disorders covered by Medicaid have increased costs of health care.