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The contribution of de novo coding mutations to autism spectrum disorder

Overview of attention for article published in Nature, October 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
21 news outlets
blogs
15 blogs
policy
1 policy source
twitter
87 X users
patent
23 patents
weibo
15 weibo users
facebook
3 Facebook pages
wikipedia
4 Wikipedia pages
googleplus
2 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
2151 Dimensions

Readers on

mendeley
1802 Mendeley
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6 CiteULike
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Title
The contribution of de novo coding mutations to autism spectrum disorder
Published in
Nature, October 2014
DOI 10.1038/nature13908
Pubmed ID
Authors

Ivan Iossifov, Brian J. O’Roak, Stephan J. Sanders, Michael Ronemus, Niklas Krumm, Dan Levy, Holly A. Stessman, Kali T. Witherspoon, Laura Vives, Karynne E. Patterson, Joshua D. Smith, Bryan Paeper, Deborah A. Nickerson, Jeanselle Dea, Shan Dong, Luis E. Gonzalez, Jeffrey D. Mandell, Shrikant M. Mane, Michael T. Murtha, Catherine A. Sullivan, Michael F. Walker, Zainulabedin Waqar, Liping Wei, A. Jeremy Willsey, Boris Yamrom, Yoon-ha Lee, Ewa Grabowska, Ertugrul Dalkic, Zihua Wang, Steven Marks, Peter Andrews, Anthony Leotta, Jude Kendall, Inessa Hakker, Julie Rosenbaum, Beicong Ma, Linda Rodgers, Jennifer Troge, Giuseppe Narzisi, Seungtai Yoon, Michael C. Schatz, Kenny Ye, W. Richard McCombie, Jay Shendure, Evan E. Eichler, Matthew W. State, Michael Wigler

Abstract

Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

X Demographics

X Demographics

The data shown below were collected from the profiles of 87 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,802 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 19 1%
United Kingdom 5 <1%
Germany 4 <1%
Brazil 4 <1%
Spain 3 <1%
Netherlands 3 <1%
Italy 3 <1%
Chile 2 <1%
Portugal 2 <1%
Other 13 <1%
Unknown 1744 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 414 23%
Researcher 324 18%
Student > Bachelor 174 10%
Student > Master 168 9%
Student > Doctoral Student 102 6%
Other 304 17%
Unknown 316 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 424 24%
Biochemistry, Genetics and Molecular Biology 361 20%
Neuroscience 246 14%
Medicine and Dentistry 166 9%
Psychology 73 4%
Other 158 9%
Unknown 374 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 320. 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 20 February 2024.
All research outputs
#107,005
of 26,017,215 outputs
Outputs from Nature
#7,304
of 99,074 outputs
Outputs of similar age
#918
of 278,624 outputs
Outputs of similar age from Nature
#97
of 1,089 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 99,074 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.3. This one has done particularly well, scoring higher than 92% 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 278,624 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 99% of its contemporaries.
We're also able to compare this research output to 1,089 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.