↓ Skip to main content

Targeted massively parallel sequencing of autism spectrum disorder-associated genes in a case control cohort reveals rare loss-of-function risk variants

Overview of attention for article published in Molecular Autism, July 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)

Mentioned by

1 blog
19 tweeters
1 Wikipedia page


42 Dimensions

Readers on

94 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Targeted massively parallel sequencing of autism spectrum disorder-associated genes in a case control cohort reveals rare loss-of-function risk variants
Published in
Molecular Autism, July 2015
DOI 10.1186/s13229-015-0034-z
Pubmed ID

Anthony J. Griswold, Nicole D. Dueker, Derek Van Booven, Joseph A. Rantus, James M. Jaworski, Susan H. Slifer, Michael A. Schmidt, William Hulme, Ioanna Konidari, Patrice L. Whitehead, Michael L. Cuccaro, Eden R. Martin, Jonathan L. Haines, John R. Gilbert, John P. Hussman, Margaret A. Pericak-Vance


Autism spectrum disorder (ASD) is highly heritable, yet genome-wide association studies (GWAS), copy number variation screens, and candidate gene association studies have found no single factor accounting for a large percentage of genetic risk. ASD trio exome sequencing studies have revealed genes with recurrent de novo loss-of-function variants as strong risk factors, but there are relatively few recurrently affected genes while as many as 1000 genes are predicted to play a role. As such, it is critical to identify the remaining rare and low-frequency variants contributing to ASD. We have utilized an approach of prioritization of genes by GWAS and follow-up with massively parallel sequencing in a case-control cohort. Using a previously reported ASD noise reduction GWAS analyses, we prioritized 837 RefSeq genes for custom targeting and sequencing. We sequenced the coding regions of those genes in 2071 ASD cases and 904 controls of European white ancestry. We applied comprehensive annotation to identify single variants which could confer ASD risk and also gene-based association analysis to identify sets of rare variants associated with ASD. We identified a significant over-representation of rare loss-of-function variants in genes previously associated with ASD, including a de novo premature stop variant in the well-established ASD candidate gene RBFOX1. Furthermore, ASD cases were more likely to have two damaging missense variants in candidate genes than controls. Finally, gene-based rare variant association implicates genes functioning in excitatory neurotransmission and neurite outgrowth and guidance pathways including CACNAD2, KCNH7, and NRXN1. We find suggestive evidence that rare variants in synaptic genes are associated with ASD and that loss-of-function mutations in ASD candidate genes are a major risk factor, and we implicate damaging mutations in glutamate signaling receptors and neuronal adhesion and guidance molecules. Furthermore, the role of de novo mutations in ASD remains to be fully investigated as we identified the first reported protein-truncating variant in RBFOX1 in ASD. Overall, this work, combined with others in the field, suggests a convergence of genes and molecular pathways underlying ASD etiology.

Twitter Demographics

The data shown below were collected from the profiles of 19 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 2%
Netherlands 1 1%
Russia 1 1%
Brazil 1 1%
Unknown 89 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 24%
Researcher 19 20%
Student > Master 9 10%
Professor 8 9%
Student > Bachelor 6 6%
Other 17 18%
Unknown 12 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 22%
Biochemistry, Genetics and Molecular Biology 14 15%
Neuroscience 10 11%
Medicine and Dentistry 6 6%
Psychology 5 5%
Other 19 20%
Unknown 19 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 June 2021.
All research outputs
of 19,787,208 outputs
Outputs from Molecular Autism
of 620 outputs
Outputs of similar age
of 242,286 outputs
Outputs of similar age from Molecular Autism
of 1 outputs
Altmetric has tracked 19,787,208 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 620 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 28.9. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 242,286 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them