Response to 'Predicting the diagnosis of autism spectrum disorder using gene pathway analysis'

Robinson, E. B., Howrigan, D., Yang, J., Ripke, S., Anttila, V., Duncan, L. E., Jostins, L., Barrett, J. C., Medland, S. E., Macarthur, D. G., Breen, G., O'Donovan, M. C., Wray, N. R., Devlin, B., Daly, M. J., Visscher, P. M., Sullivan, P. F. and Neale, B. M. (2013) Response to 'Predicting the diagnosis of autism spectrum disorder using gene pathway analysis'. Molecular Psychiatry, 19 8: 859-861. doi:10.1038/mp.2013.125

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Author Robinson, E. B.
Howrigan, D.
Yang, J.
Ripke, S.
Anttila, V.
Duncan, L. E.
Jostins, L.
Barrett, J. C.
Medland, S. E.
Macarthur, D. G.
Breen, G.
O'Donovan, M. C.
Wray, N. R.
Devlin, B.
Daly, M. J.
Visscher, P. M.
Sullivan, P. F.
Neale, B. M.
Title Response to 'Predicting the diagnosis of autism spectrum disorder using gene pathway analysis'
Journal name Molecular Psychiatry   Check publisher's open access policy
ISSN 1359-4184
Publication date 2013-10-27
Year available 2014
Sub-type Article (original research)
DOI 10.1038/mp.2013.125
Open Access Status File (Author Post-print)
Volume 19
Issue 8
Start page 859
End page 861
Total pages 3
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Language eng
Subject 1312 Molecular Biology
2738 Psychiatry and Mental health
2804 Cellular and Molecular Neuroscience
Formatted abstract
In a recent paper published online in Molecular Psychiatry, Skafidas et al. report a classifier for identifying individuals at risk for autism spectrum disorders (ASDs). Their classifier is based on 267 single-nucleotide polymorphisms (SNPs) that were selected from the results of a pathway analysis using cases from the Autism Genetic Resource Exchange (AGRE). Using within-sample cross-validation, the authors claim a classification accuracy for ASDs of 85.6%. They subsequently applied their classifier to ASD cases from the Simons Foundation Autism Research Initiative (SFARI) and controls from the Wellcome Trust Birth Cohort (WTBC) and report ASD classification accuracy of 71.7%.

We believe that the claims made by Skafidas et al. are inconsistent with current knowledge of the genetics of ASDs, and inconsistent with the expected precision of risk predictions for complex psychiatric disorders. Further, as classification accuracy depends on the size of the discovery sample, the results are also inconsistent with the size of the sample they employed (only 123 controls were included in the discovery set)...
Keyword Biochemistry & Molecular Biology
Biochemistry & Molecular Biology
Neurosciences & Neurology
Q-Index Code CX
Q-Index Status Confirmed Code
Grant ID G0800509
UL1 TR001079
UL1 RR025005
U01 HG004402
Institutional Status UQ
Additional Notes Advance online publication 22 October 2013

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
Queensland Brain Institute Publications
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Citation counts: TR Web of Science Citation Count  Cited 10 times in Thomson Reuters Web of Science Article | Citations
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Created: Wed, 12 Mar 2014, 01:06:37 EST by Debra McMurtrie on behalf of Queensland Brain Institute