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Carrier Testing for Severe Childhood Recessive Diseases by Next-Generation Sequencing

Overview of attention for article published in Science Translational Medicine, January 2011
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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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Citations

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473 Dimensions

Readers on

mendeley
495 Mendeley
citeulike
13 CiteULike
Title
Carrier Testing for Severe Childhood Recessive Diseases by Next-Generation Sequencing
Published in
Science Translational Medicine, January 2011
DOI 10.1126/scitranslmed.3001756
Pubmed ID
Authors

C. J. Bell, D. L. Dinwiddie, N. A. Miller, S. L. Hateley, E. E. Ganusova, J. Mudge, R. J. Langley, L. Zhang, C. C. Lee, F. D. Schilkey, V. Sheth, J. E. Woodward, H. E. Peckham, G. P. Schroth, R. W. Kim, S. F. Kingsmore

Abstract

Of 7028 disorders with suspected Mendelian inheritance, 1139 are recessive and have an established molecular basis. Although individually uncommon, Mendelian diseases collectively account for ~20% of infant mortality and ~10% of pediatric hospitalizations. Preconception screening, together with genetic counseling of carriers, has resulted in remarkable declines in the incidence of several severe recessive diseases including Tay-Sachs disease and cystic fibrosis. However, extension of preconception screening to most severe disease genes has hitherto been impractical. Here, we report a preconception carrier screen for 448 severe recessive childhood diseases. Rather than costly, complete sequencing of the human genome, 7717 regions from 437 target genes were enriched by hybrid capture or microdroplet polymerase chain reaction, sequenced by next-generation sequencing (NGS) to a depth of up to 2.7 gigabases, and assessed with stringent bioinformatic filters. At a resultant 160x average target coverage, 93% of nucleotides had at least 20x coverage, and mutation detection/genotyping had ~95% sensitivity and ~100% specificity for substitution, insertion/deletion, splicing, and gross deletion mutations and single-nucleotide polymorphisms. In 104 unrelated DNA samples, the average genomic carrier burden for severe pediatric recessive mutations was 2.8 and ranged from 0 to 7. The distribution of mutations among sequenced samples appeared random. Twenty-seven percent of mutations cited in the literature were found to be common polymorphisms or misannotated, underscoring the need for better mutation databases as part of a comprehensive carrier testing strategy. Given the magnitude of carrier burden and the lower cost of testing compared to treating these conditions, carrier screening by NGS made available to the general population may be an economical way to reduce the incidence of and ameliorate suffering associated with severe recessive childhood disorders.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 495 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 16 3%
Germany 5 1%
United Kingdom 5 1%
Australia 3 <1%
Spain 3 <1%
Brazil 3 <1%
Netherlands 2 <1%
Japan 2 <1%
Sweden 1 <1%
Other 7 1%
Unknown 448 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 125 25%
Student > Ph. D. Student 83 17%
Other 57 12%
Student > Master 57 12%
Student > Bachelor 50 10%
Other 100 20%
Unknown 23 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 209 42%
Medicine and Dentistry 112 23%
Biochemistry, Genetics and Molecular Biology 87 18%
Computer Science 15 3%
Engineering 7 1%
Other 34 7%
Unknown 31 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 99. 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 19 December 2019.
All research outputs
#176,787
of 14,155,721 outputs
Outputs from Science Translational Medicine
#611
of 3,935 outputs
Outputs of similar age
#171,637
of 13,402,088 outputs
Outputs of similar age from Science Translational Medicine
#610
of 3,900 outputs
Altmetric has tracked 14,155,721 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,935 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 62.2. This one has done well, scoring higher than 84% 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 13,402,088 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 98% of its contemporaries.
We're also able to compare this research output to 3,900 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.