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Clinical Summary

A study was performed to assess the ability to utilize the ARISk^® Autism Risk Assessment Test and an associated gender specific genetic risk scoring model to identify autism risk in siblings of children diagnosed with an autism spectrum disorder.

Click here for a copy of the technical report on this study.

Sixty-five SNPs were used to build new gender

specific GSs with 37 SNPs in males and 36

in females. Table 3 lists the gene location,

associated chromosome and gender specificity

for each SNP.

The ability of these SNPs to discriminate

individuals with autism from their unaffected

siblings was then evaluated in a sample of 803

families from AGRE and the University of

Pennsylvania including 1314 affected children

(1056 males and 258 females; 4:1 male to female

sex ratio) and 391 unaffected siblings (179 males

and 212 females). All individuals were fully

genotyped for the 37 SNPs in males and 36

SNPs in females.

GSs ranged from 27 to 56 for males with an

AUC of 0.70 (95% CI = 0.65 - 0.74) compared to

an AUC of 0.59 for the previous 8 SNPs panel.

For females, GSs ranged from 29 to 54 with an

AUC of 0.74 (95% CI = 0.69 - 0.79), whereas it

was 0.66 for the 8 SNPs panel alone.

65 SNPs were used to build new gender specific genetics scores (click here for information on these SNPs).
The ability of these SNPs to discriminate individuals with autism from their unaffected siblings was then evaluated in a sample of 803 families including 1,314 affected children and 391 unaffected siblings.
All affected children met the diagnostic criteria for “strict” autism according to the Autism Diagnostic Interview Revisited (ADI-R).
All individuals were fully genotyped for the 37 SNPs in males and 36 SNPs in females.
Genetic scores ranged from 27 to 56 for males and from 29 to 54 for females.

Risk Class
Definitions

Genetic score distributions were used to stratify patients, by gender, into differing risk categories.
The inital risk category identified was associated with “no change” in risk corresponding to the class where the risk is similar to the recurrence risk of autism in siblings of affected children.
Using the above as a starting point, additional risk classeswere identified using odds ratios (OR) and corresponding p values.
Genetic score ranges varied by gender.

Click here for the distribution of affected and unaffected males and females by risk category.

Conclusion

The results of this study demonstrate that a gender specific scoring model based on the presence of multiple common susceptibility variants can allow for the identification of siblings of children with autism who have a significantly higher risk of autism.

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Conception and realisation SWAD

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