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Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches

Overview of attention for article published in American Journal of Human Genetics, January 2018
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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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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14 news outlets
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31 X users
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1 Facebook page

Citations

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67 Dimensions

Readers on

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136 Mendeley
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Title
Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches
Published in
American Journal of Human Genetics, January 2018
DOI 10.1016/j.ajhg.2017.12.013
Pubmed ID
Authors

Lucia Guidugli, Hermela Shimelis, David L. Masica, Vernon S. Pankratz, Gary B. Lipton, Namit Singh, Chunling Hu, Alvaro N.A. Monteiro, Noralane M. Lindor, David E. Goldgar, Rachel Karchin, Edwin S. Iversen, Fergus J. Couch

Abstract

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ≥99% probability of pathogenicity, and 73 had ≥95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.

X Demographics

X Demographics

The data shown below were collected from the profiles of 31 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 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 136 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 20%
Student > Ph. D. Student 15 11%
Other 11 8%
Student > Master 11 8%
Student > Bachelor 8 6%
Other 18 13%
Unknown 46 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 38 28%
Medicine and Dentistry 19 14%
Agricultural and Biological Sciences 18 13%
Computer Science 2 1%
Pharmacology, Toxicology and Pharmaceutical Science 2 1%
Other 5 4%
Unknown 52 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 124. 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 22 May 2018.
All research outputs
#335,436
of 25,382,440 outputs
Outputs from American Journal of Human Genetics
#118
of 5,881 outputs
Outputs of similar age
#7,793
of 450,332 outputs
Outputs of similar age from American Journal of Human Genetics
#5
of 47 outputs
Altmetric has tracked 25,382,440 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 5,881 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one has done particularly well, scoring higher than 97% 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 450,332 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 47 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.