Do common variants play a role in risk for autism? Evidence and theoretical musings
Open accessAbstract
Both rare and common genetic variants underlie risk for almost any complex disease. Over the past few years a common tool for identifying common risk variants is genome-wide association or GWA. Our analyses focus on results from GWA targeting common variants affecting risk for autism spectrum disorders (ASD). Thus far three large GWA studies have been published, each of which highlights a single, non-overlapping risk locus. Evaluation of these studies suggests that combination of their data would diminish evidence for all of these loci, making none of them significant. Despite this paucity of findings, statistical theory can be used to infer a plausible distribution of effect sizes for SNPs affecting risk for ASD. We lay out this theory, calculate plausible distributions, and discuss the results in the context of results from GWA studies for schizophrenia.
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The study reports the first common risk variants robustly associated with ASD by more than doubling the discovery sample size compared to previous GWAS.
“Here we report the first common risk variants robustly associated with ASD by more than doubling the discovery sample size compared to previous GWAS 5-8 .”
From Identification of common genetic risk variants for autism spectrum disorder (2019) · cites this paper as [7]
In §3, Statistical interpretation of GWA results (page unavailable), the paper concludes that no common variants were convincingly associated with ASD across the reported GWAS data. The Discussion likewise says that no susceptibility loci had been reliably replicated. This is a review and statistical analysis of prior studies, not a report of newly discovered, robustly associated variants from a doubled discovery sample. (LLM, conf=0.92)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe largest GWAS to date (n=7387 cases scanned) did not conclusively identify single variants at genome-wide significance.
“the largest GWAS to date (n=7387 cases scanned) -while providing compelling evidence for the bulk contribution of common variants -did not conclusively identify single variants at genome-wide significance 5-7 .”
From Identification of common genetic risk variants for autism spectrum disorder (2019) · cites this paper as [7]
Section 3 (page unavailable) concludes that no common variants were convincingly associated with autism at genome-wide significance across the reported data, supporting the claim about inconclusive single-variant findings. The paper reviews three large GWAS rather than identifying a largest study with 7,387 cases scanned; that sample size is not supported by our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe effect sizes of common variants in ASD are small.
“but the effect sizes are small [15]”
From Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes (2013) · cites this paper as [15]
The analyses in Devlin et al. (28) cannot be precise when predicting the number of loci with common variants of modest impact on risk (0.8< risk <1.2); the modelling is consistent with a range of loci from zero to many thousands.
“The analyses laid out in Devlin et al. (28) cannot be precise when predicting the number of loci with common variants of modest impact on risk (0.8< risk <1.2); the modelling is consistent with a range of loci from zero to many thousands.”
From Individual common variants exert weak effects on the risk for autism spectrum disorders (2012) · cites this paper as [28]
Earlier analyses predicted that few if any common variants have an impact on risk exceeding 1.2 (or below its inverse).
“These analyses predicted that few if any common variants have an impact on risk exceeding 1.2 (or below its inverse).”
From Individual common variants exert weak effects on the risk for autism spectrum disorders (2012) · cites this paper as [28]
Early ASD GWAS had low statistical power to robustly identify genome-wide significant loci at effect sizes OR < 1.15.
“Early GWAS [12, 14–17] were performed using a variety of genotyping arrays, and the independent samples sizes were of low statistical power to robustly identify genome-wide significant (GWS) loci at the lower effect sizes (OR <1.15) [18].”
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- Authors
- Devlin, B., Melhem, N., & Roeder, K.
- Affiliations
- University of Pittsburgh (US)
- Carnegie Mellon University (US)
- Corresponding author
- Devlin, Bernie
- Venue
- Brain Research
- Publisher
- Elsevier BV
- Published
- 2011-03
- Volume
- 1380
- Pages
- 78-84
- ISSN
- 0006-8993 (ISSN-L)
- PMC
- PMC3638767
- OpenAlex
- W2055157121
- Cited by
- 105
- References
- 33
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 5 · 2022: 2 · 2021: 3 · 2020: 4 · 2019: 5 · 2018: 2 · 2017: 8 · 2016: 6 · 2015: 7 · 2014: 19 · 2013: 12 · 2012: 19
- FWCI
- 0.94
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Brain Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (MH057881, MH077930)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- autism spectrum disorder, common genetic variants, genome-wide association study, genetic susceptibility loci, effect size distribution, rare variants, schizophrenia genetics
- MeSH terms
- Child, Child Development Disorders, Pervasive, Child, Preschool, Humans, Infant, Polymorphism, Genetic, Genetic Variation, Genetic Predisposition to Disease, Genome-Wide Association Study
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