1. Bolte S, Golan O, Goodwin MS, Zwaigenbaum L. {{What can innovative technologies do for Autism Spectrum Disorders?}}. {Autism} (May);14(3):155-159.
2. Finegold SM, Dowd SE, Gontcharova V, Liu C, Henley KE, Wolcott RD, Youn E, Summanen PH, Granpeesheh D, Dixon D, Liu M, Molitoris DR, Green JA, 3rd. {{Pyrosequencing Study of Fecal Microflora of Autistic and Control Children}}. {Anaerobe} (Jul 2)
There is evidence of genetic predisposition to autism, but the percent of autistic subjects with this background is unknown. It is clear that other factors, such as environmental influences, may play a role in this disease. In the present study, we have examined the fecal microbial flora of 33 subjects with various severities of autism with gastrointestinal symptoms, 7 siblings not showing autistic symptoms (sibling controls) and eight non-sibling control subjects, using the bacterial tag encoded FLX amplicon pyrosequencing (bTEFAP) procedure. The results provide us with information on the microflora of stools of young children and a compelling picture of unique fecal microflora of children with autism with gastrointestinal symptomatology. Differences based upon maximum observed and maximum predicted operational taxonomic units were statistically significant when comparing autistic and control subjects with p values ranging from <0.001 to 0.009 using both parametric and non-parametric estimators. At the phylum level, Bacteroidetes and Firmicutes showed the most difference between groups of varying severities of autism. Bacteroidetes was found at high levels in the severely autistic group, while Firmicutes were more predominant in the control group. Smaller, but significant, differences also occurred in the Actinobacterium and Proteobacterium phyla. Desulfovibrio species and Bacteroides vulgatus are present in significantly higher numbers in stools of severely autistic children than in controls. If the unique microbial flora is found to be a causative or consequent factor in this type of autism, it may have implications with regard to a specific diagnostic test, its epidemiology, and for treatment and prevention.
3. Koyama T, Inokuchi E, Inada N, Kuroda M, Moriwaki A, Katagiri M, Noriuchi M, Kamio Y. {{Utility of the Japanese version of the Checklist for Autism in Toddlers for predicting pervasive developmental disorders at age 2}}. {Psychiatry Clin Neurosci} (Jun);64(3):330-332.
We evaluated the utility of the Japanese version of the Checklist for Autism in Toddlers for predicting pervasive developmental disorders (PDD) among 2-year-old children in clinical settings. Confirmed diagnosis revealed that the pass rate on four items (social interest, proto-imperative pointing, proto-declarative pointing and joint-attention) was significantly lower in 52 PDD children than in 48 non-PDD children, and if abnormal development was reported in two or more items, the sensitivity, specificity, and positive/negative predictive values for PDD diagnosis were 0.85, 0.73, and 0.77/0.81, respectively. This simple screening tool can provide valuable information to clinicians when diagnosing PDD.
