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Individual common variants exert weak effects on the risk for autism spectrum disorders

Overview of attention for article published in Human Molecular Genetics, July 2012
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
1 news outlet
blogs
5 blogs
policy
1 policy source
twitter
14 X users
facebook
6 Facebook pages
googleplus
1 Google+ user
reddit
1 Redditor

Citations

dimensions_citation
324 Dimensions

Readers on

mendeley
457 Mendeley
citeulike
4 CiteULike
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Title
Individual common variants exert weak effects on the risk for autism spectrum disorders
Published in
Human Molecular Genetics, July 2012
DOI 10.1093/hmg/dds301
Pubmed ID
Authors

Richard Anney, Lambertus Klei, Dalila Pinto, Joana Almeida, Elena Bacchelli, Gillian Baird, Nadia Bolshakova, Sven Bölte, Patrick F. Bolton, Thomas Bourgeron, Sean Brennan, Jessica Brian, Jillian Casey, Judith Conroy, Catarina Correia, Christina Corsello, Emily L. Crawford, Maretha de Jonge, Richard Delorme, Eftichia Duketis, Frederico Duque, Annette Estes, Penny Farrar, Bridget A. Fernandez, Susan E. Folstein, Eric Fombonne, John Gilbert, Christopher Gillberg, Joseph T. Glessner, Andrew Green, Jonathan Green, Stephen J. Guter, Elizabeth A. Heron, Richard Holt, Jennifer L. Howe, Gillian Hughes, Vanessa Hus, Roberta Igliozzi, Suma Jacob, Graham P. Kenny, Cecilia Kim, Alexander Kolevzon, Vlad Kustanovich, Clara M. Lajonchere, Janine A. Lamb, Miriam Law-Smith, Marion Leboyer, Ann Le Couteur, Bennett L. Leventhal, Xiao-Qing Liu, Frances Lombard, Catherine Lord, Linda Lotspeich, Sabata C. Lund, Tiago R. Magalhaes, Carine Mantoulan, Christopher J. McDougle, Nadine M. Melhem, Alison Merikangas, Nancy J. Minshew, Ghazala K. Mirza, Jeff Munson, Carolyn Noakes, Gudrun Nygren, Katerina Papanikolaou, Alistair T. Pagnamenta, Barbara Parrini, Tara Paton, Andrew Pickles, David J. Posey, Fritz Poustka, Jiannis Ragoussis, Regina Regan, Wendy Roberts, Kathryn Roeder, Bernadette Roge, Michael L. Rutter, Sabine Schlitt, Naisha Shah, Val C. Sheffield, Latha Soorya, Inês Sousa, Vera Stoppioni, Nuala Sykes, Raffaella Tancredi, Ann P. Thompson, Susanne Thomson, Ana Tryfon, John Tsiantis, Herman Van Engeland, John B. Vincent, Fred Volkmar, JAS Vorstman, Simon Wallace, Kirsty Wing, Kerstin Wittemeyer, Shawn Wood, Danielle Zurawiecki, Lonnie Zwaigenbaum, Anthony J. Bailey, Agatino Battaglia, Rita M. Cantor, Hilary Coon, Michael L. Cuccaro, Geraldine Dawson, Sean Ennis, Christine M. Freitag, Daniel H. Geschwind, Jonathan L. Haines, Sabine M. Klauck, William M. McMahon, Elena Maestrini, Judith Miller, Anthony P. Monaco, Stanley F. Nelson, John I. Nurnberger, Guiomar Oliveira, Jeremy R. Parr, Margaret A. Pericak-Vance, Joseph Piven, Gerard D. Schellenberg, Stephen W. Scherer, Astrid M. Vicente, Thomas H. Wassink, Ellen M. Wijsman, Catalina Betancur, Joseph D. Buxbaum, Edwin H. Cook, Louise Gallagher, Michael Gill, Joachim Hallmayer, Andrew D. Paterson, James S. Sutcliffe, Peter Szatmari, Veronica J. Vieland, Hakon Hakonarson, Bernie Devlin

Abstract

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 457 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 2%
United Kingdom 3 <1%
Netherlands 3 <1%
Ireland 3 <1%
Brazil 1 <1%
Portugal 1 <1%
Canada 1 <1%
Germany 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 435 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 89 19%
Researcher 80 18%
Student > Master 48 11%
Student > Bachelor 45 10%
Professor 27 6%
Other 84 18%
Unknown 84 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 117 26%
Medicine and Dentistry 65 14%
Biochemistry, Genetics and Molecular Biology 62 14%
Neuroscience 44 10%
Psychology 33 7%
Other 34 7%
Unknown 102 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 63. 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 August 2023.
All research outputs
#692,100
of 25,837,817 outputs
Outputs from Human Molecular Genetics
#87
of 8,398 outputs
Outputs of similar age
#3,460
of 181,202 outputs
Outputs of similar age from Human Molecular Genetics
#1
of 82 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,398 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done particularly well, scoring higher than 98% 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 181,202 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 97% of its contemporaries.
We're also able to compare this research output to 82 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 98% of its contemporaries.