Genetic Test Predicts Autism Risk With High Degree of Accuracy
Medscape News
September 19, 2012 — Investigators have developed a genetic diagnostic classifier that is able to predict the risk of
developing autism spectrum disorder (ASD) with more than 70% accuracy in persons of central European descent,
new research shows.
Stan Skafidas, PhD, from the University of Melbourne in Australia, and colleagues have developed a diagnostic test
for a genetically homogeneous group of individuals with ASD.
"This test could assist in the early detection of the condition in babies and children and help in the early management
of those who become diagnosed," Dr. Skafidas said in a statement.
"It would be particularly relevant for families who have a history of autism or related conditions, such as Asperger's
syndrome," he added.
The study was published online September 11 in Molecular Psychiatry.
The team first interrogated single-nucleotide polymorphisms (SNPs) of individuals with ASD from the Autism Genetic
Resource Exchange (AGRE) database.
The test was then applied to 2 independent samples for validation: 1 from the Simons Foundation Autism Research
Initiative (SFARI) and the second from the Wellcome Trust 1958 normal birth cohort (WTBC).
"Using AGRE SNP data from a Central European (CEU) cohort, we created a genetic diagnostic classifier consisting
of 237 SNPs in 146 genes that correctly predicted ASD diagnosis in 85.6% of CEU cases [as well as] 84.3% of
cases in an ethnically related Tuscan cohort," investigators write.
"Our diagnostic classifier [also] correctly predicted ASD diagnosis with an accuracy of 71.7% in CEU individuals from
the SFARI (ASD) and WTBC (controls) validation data sets."
Ethnicity Matters
Data from 2609 probands with ASD, including autism, Asperger's, and pervasive developmental disorder–not
otherwise specified, as well as 4165 relatives of probands were available from the AGRE database.
"From the 775 SNPs identified within the CEU cohort, accurate genetic classification of ASD versus non-ASD was
possible using 237 SNPs determined to be highly significant (P < 0.005)," the authors write.
In contrast, said Dr. Skafidas, if the same classifier were to be used in an ethnically diverse population, "results
would be nowhere near as good."
For example, when investigators tested a smaller cohort of Han Chinese in the same study, "our performance was
approximately 55% — little better than flipping a coin," he said.
As Dr. Skafidas explained, all ethnic backgrounds have "markedly different" SNP allele rates.
Nevertheless, "what is consistent and what we show in our study are the signalling pathways, and this indicates that
the same systems (glutamatergic and innate immunity) are probably important to understanding the disorder but not
ideal for building classifiers," he told Medscape Medical News.
Potential for Early Intervention
Investigators were also able to identify the presence of some SNPs that contributed to an individual's vulnerability to
develop ASD, whereas they identified other SNPs that were protective.
"Eight SNPs in 3 genes, GRM5, GNAO1 and KCNMB4, were highly discriminatory in determining an individual's
classification as ASD or non-ASD," investigators state.
Other SNPs appeared to be equally protective against ASD.
"There is a big focus on finding genes that are the cause [of ASD], and I believe less focus has been spent on genes
that are protective or reduce risk," Dr. Skafidas observed.
"These genes may prove to be interesting avenues for further investigation, [as] it would be interesting to understand
why SNPs in these genes reduce ASD risk."
Renee Testa, MD, from the University of Melbourne and Monash University, in Australia, noted in a press release that
the new diagnostic classifier would allow clinicians to provide early interventions that may reduce behavioral and
cognitive difficulties in children and adults with ASD.
"Early identification of risk means we can provide interventions to improve overall functioning for those affected,
including families," she said.
original article attached
Medscape News
September 19, 2012 — Investigators have developed a genetic diagnostic classifier that is able to predict the risk of
developing autism spectrum disorder (ASD) with more than 70% accuracy in persons of central European descent,
new research shows.
Stan Skafidas, PhD, from the University of Melbourne in Australia, and colleagues have developed a diagnostic test
for a genetically homogeneous group of individuals with ASD.
"This test could assist in the early detection of the condition in babies and children and help in the early management
of those who become diagnosed," Dr. Skafidas said in a statement.
"It would be particularly relevant for families who have a history of autism or related conditions, such as Asperger's
syndrome," he added.
The study was published online September 11 in Molecular Psychiatry.
The team first interrogated single-nucleotide polymorphisms (SNPs) of individuals with ASD from the Autism Genetic
Resource Exchange (AGRE) database.
The test was then applied to 2 independent samples for validation: 1 from the Simons Foundation Autism Research
Initiative (SFARI) and the second from the Wellcome Trust 1958 normal birth cohort (WTBC).
"Using AGRE SNP data from a Central European (CEU) cohort, we created a genetic diagnostic classifier consisting
of 237 SNPs in 146 genes that correctly predicted ASD diagnosis in 85.6% of CEU cases [as well as] 84.3% of
cases in an ethnically related Tuscan cohort," investigators write.
"Our diagnostic classifier [also] correctly predicted ASD diagnosis with an accuracy of 71.7% in CEU individuals from
the SFARI (ASD) and WTBC (controls) validation data sets."
Ethnicity Matters
Data from 2609 probands with ASD, including autism, Asperger's, and pervasive developmental disorder–not
otherwise specified, as well as 4165 relatives of probands were available from the AGRE database.
"From the 775 SNPs identified within the CEU cohort, accurate genetic classification of ASD versus non-ASD was
possible using 237 SNPs determined to be highly significant (P < 0.005)," the authors write.
In contrast, said Dr. Skafidas, if the same classifier were to be used in an ethnically diverse population, "results
would be nowhere near as good."
For example, when investigators tested a smaller cohort of Han Chinese in the same study, "our performance was
approximately 55% — little better than flipping a coin," he said.
As Dr. Skafidas explained, all ethnic backgrounds have "markedly different" SNP allele rates.
Nevertheless, "what is consistent and what we show in our study are the signalling pathways, and this indicates that
the same systems (glutamatergic and innate immunity) are probably important to understanding the disorder but not
ideal for building classifiers," he told Medscape Medical News.
Potential for Early Intervention
Investigators were also able to identify the presence of some SNPs that contributed to an individual's vulnerability to
develop ASD, whereas they identified other SNPs that were protective.
"Eight SNPs in 3 genes, GRM5, GNAO1 and KCNMB4, were highly discriminatory in determining an individual's
classification as ASD or non-ASD," investigators state.
Other SNPs appeared to be equally protective against ASD.
"There is a big focus on finding genes that are the cause [of ASD], and I believe less focus has been spent on genes
that are protective or reduce risk," Dr. Skafidas observed.
"These genes may prove to be interesting avenues for further investigation, [as] it would be interesting to understand
why SNPs in these genes reduce ASD risk."
Renee Testa, MD, from the University of Melbourne and Monash University, in Australia, noted in a press release that
the new diagnostic classifier would allow clinicians to provide early interventions that may reduce behavioral and
cognitive difficulties in children and adults with ASD.
"Early identification of risk means we can provide interventions to improve overall functioning for those affected,
including families," she said.
original article attached
