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Evaluation of ACMG-Guideline-Based Variant Classification of Cancer Susceptibility and Non-Cancer-Associated Genes in Families Affected by Breast Cancer

Overview of attention for article published in American Journal of Human Genetics, May 2016
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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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
9 news outlets
blogs
1 blog
twitter
31 X users
patent
1 patent
facebook
2 Facebook pages

Citations

dimensions_citation
105 Dimensions

Readers on

mendeley
215 Mendeley
citeulike
2 CiteULike
Title
Evaluation of ACMG-Guideline-Based Variant Classification of Cancer Susceptibility and Non-Cancer-Associated Genes in Families Affected by Breast Cancer
Published in
American Journal of Human Genetics, May 2016
DOI 10.1016/j.ajhg.2016.02.024
Pubmed ID
Authors

Kara N. Maxwell, Steven N. Hart, Joseph Vijai, Kasmintan A. Schrader, Thomas P. Slavin, Tinu Thomas, Bradley Wubbenhorst, Vignesh Ravichandran, Raymond M. Moore, Chunling Hu, Lucia Guidugli, Brandon Wenz, Susan M. Domchek, Mark E. Robson, Csilla Szabo, Susan L. Neuhausen, Jeffrey N. Weitzel, Kenneth Offit, Fergus J. Couch, Katherine L. Nathanson

Abstract

Sequencing tests assaying panels of genes or whole exomes are widely available for cancer risk evaluation. However, methods for classification of variants resulting from this testing are not well studied. We evaluated the ability of a variant-classification methodology based on American College of Medical Genetics and Genomics (ACMG) guidelines to define the rate of mutations and variants of uncertain significance (VUS) in 180 medically relevant genes, including all ACMG-designated reportable cancer and non-cancer-associated genes, in individuals who met guidelines for hereditary cancer risk evaluation. We performed whole-exome sequencing in 404 individuals in 253 families and classified 1,640 variants. Potentially clinically actionable (likely pathogenic [LP] or pathogenic [P]) versus nonactionable (VUS, likely benign, or benign) calls were 95% concordant with locus-specific databases and Clinvar. LP or P mutations were identified in 12 of 25 breast cancer susceptibility genes in 26 families without identified BRCA1/2 mutations (11%). Evaluation of 84 additional genes associated with autosomal-dominant cancer susceptibility identified LP or P mutations in only two additional families (0.8%). However, individuals from 10 of 253 families (3.9%) had incidental LP or P mutations in 32 non-cancer-associated genes, and 9% of individuals were monoallelic carriers of a rare LP or P mutation in 39 genes associated with autosomal-recessive cancer susceptibility. Furthermore, 95% of individuals had at least one VUS. In summary, these data support the clinical utility of ACMG variant-classification guidelines. Additionally, evaluation of extended panels of cancer-associated genes in breast/ovarian cancer families leads to only an incremental clinical benefit but substantially increases the complexity of the results.

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 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Canada 2 <1%
Italy 2 <1%
Korea, Republic of 1 <1%
Unknown 208 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 21%
Student > Ph. D. Student 37 17%
Other 26 12%
Student > Master 18 8%
Student > Doctoral Student 11 5%
Other 35 16%
Unknown 43 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 70 33%
Medicine and Dentistry 46 21%
Agricultural and Biological Sciences 34 16%
Computer Science 2 <1%
Engineering 2 <1%
Other 11 5%
Unknown 50 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 89. 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 05 August 2021.
All research outputs
#476,447
of 25,371,288 outputs
Outputs from American Journal of Human Genetics
#197
of 5,878 outputs
Outputs of similar age
#8,762
of 311,861 outputs
Outputs of similar age from American Journal of Human Genetics
#10
of 63 outputs
Altmetric has tracked 25,371,288 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 5,878 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 96% 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 311,861 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 63 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.