Dr. David Miller, in his article examined the methods of testing for autism. He concluded that a discovery of genetic variables contributing to autism (ASD) is the first step in developing effective clinical diagnostic genetic tests. He concluded that most cases are still unexplained by current genetic testing and will require ongoing discovery to improve the yield from clinical testing. Miller (2010). In other words, Miller suggests that the current genetic testing is not yielding the results that would best explain the causes of autism and in light of the available testing mechanisms. As a solution to this issue, Miller suggests that the ideal genetic test would identify genetic susceptibility to autism. Miller (2010) .
In light of Miller's testing theories and to illustrate an example of how genes are evaluated in autism studies, in the Traylor study, six subjects were studied from different areas of the world. Study subjects 1 and 2 were ascertained by Genetic Health Services Victoria in Melbourne, Australia while study subjects 3-6 were ascertained by Signature Genomic Laboratories. Traylor (2010). Study subjects 1 and 2 initially had Single nucleotide polymorphism (SNP) array analysis performed using the 250K-feature Nsp Gene-Chip according to the manufacturer's, -- Affymetrix, Santa Clara, CA -- protocols. The SNP is related to the DNA sequence in the patients. Genetic deletions in the patients were ascertained in Subjects 3-6 and initially identified by aCGH using various microarray platforms at Signature Genomic Laboratories. Traylor (2010). In summary, these studies illustrate two methods that have been used in the past to determine gene abnormality in autistic patients.
Currently, the G-banded karyotype is the first-tier cytogenetic test for patients. The G-
banded karyotype is a method which tests for chromosomal abnormalities in patients and yields approximately 2%-3% of patients with autism. Miller (2010). Miller suggests that this method should be replaced with Chromosomal microarray (CMA) as the first tier cytogenetic test for patients. This is a form of array comparative genomic hybridization that detects the vast majority of events seen by karyotype and can detect many more events that appear below karyotypic resolution. This method of testing yields of 7 -- 10% of patients...
Miller (2010) and is thus a stronger method of abnormal chromosomal detection than the G-banded karyotype.
Putative ASD Traits Identified
In the Steer article, seven factors were revealed that have became characteristic of ASD and are known as putative ASD traits. Specifically, Factor 1: Verbal ability, factor 2: Language acquisition, factor 3: Social understanding factor 4: Semantic-pragmatic skills factor 5: Repetitive-stereotyped behavior, factor 6: Articulation and factor 7: Social inhibition. Steer (2010). A mean score in these seven factors is the strongest variable associated with ASD status. The age groups studied ranged from six months to nine years. Steer (2010). Combined analysis of these identified traits revealed that only traits 5 and 6 failed to have an independent association not related to ASD. Steer (2010). Additionally, further studies show that the presence of these traits is more common in the ASD population than in the general population. It is important to note, however, that not all factors were identified for each age group studied, but as the frequency and intensity of these factors increased, this was associated more with autism in the patient.
Incidents and Prevalence
The Steer study was referred to as the Avon Longitudinal Study of Parents and Children (ALSPAC) sample. The study originally recruited 14,541 pregnant women with expected delivery dates between April 1992 and December 1992. Of the children in the study with ASD there were 86 such children identified with the disorder by age 11 years giving a prevalence of 62 per 10,000 children. These numbers were based upon the original recruited sample of 13, 971 children. Steer (2010). However, these numbers are somewhat lower than previous numbers. For example, a recent study by Baron-Cohen et. al suggests a prevalence rate of 0.9% based upon a survey of special educational needs (SEN) children among 96 schools. Steer (2010).
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