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Assessing the genetic architecture of epithelial ovarian cancer histological subtypes

Overview of attention for article published in Human Genetics, April 2016
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Title
Assessing the genetic architecture of epithelial ovarian cancer histological subtypes
Published in
Human Genetics, April 2016
DOI 10.1007/s00439-016-1663-9
Pubmed ID
Authors

Gabriel Cuellar-Partida, Yi Lu, Suzanne C. Dixon, Australian Ovarian Cancer Study, Peter A. Fasching, Alexander Hein, Stefanie Burghaus, Matthias W. Beckmann, Diether Lambrechts, Els Van Nieuwenhuysen, Ignace Vergote, Adriaan Vanderstichele, Jennifer Anne Doherty, Mary Anne Rossing, Jenny Chang-Claude, Anja Rudolph, Shan Wang-Gohrke, Marc T. Goodman, Natalia Bogdanova, Thilo Dörk, Matthias Dürst, Peter Hillemanns, Ingo B. Runnebaum, Natalia Antonenkova, Ralf Butzow, Arto Leminen, Heli Nevanlinna, Liisa M. Pelttari, Robert P. Edwards, Joseph L. Kelley, Francesmary Modugno, Kirsten B. Moysich, Roberta B. Ness, Rikki Cannioto, Estrid Høgdall, Claus Høgdall, Allan Jensen, Graham G. Giles, Fiona Bruinsma, Susanne K. Kjaer, Michelle A. T. Hildebrandt, Dong Liang, Karen H. Lu, Xifeng Wu, Maria Bisogna, Fanny Dao, Douglas A. Levine, Daniel W. Cramer, Kathryn L. Terry, Shelley S. Tworoger, Meir Stampfer, Stacey Missmer, Line Bjorge, Helga B. Salvesen, Reidun K. Kopperud, Katharina Bischof, Katja K. H. Aben, Lambertus A. Kiemeney, Leon F. A. G. Massuger, Angela Brooks-Wilson, Sara H. Olson, Valerie McGuire, Joseph H. Rothstein, Weiva Sieh, Alice S. Whittemore, Linda S. Cook, Nhu D. Le, C. Blake Gilks, Jacek Gronwald, Anna Jakubowska, Jan Lubiński, Tomasz Kluz, Honglin Song, Jonathan P. Tyrer, Nicolas Wentzensen, Louise Brinton, Britton Trabert, Jolanta Lissowska, John R. McLaughlin, Steven A. Narod, Catherine Phelan, Hoda Anton-Culver, Argyrios Ziogas, Diana Eccles, Ian Campbell, Simon A. Gayther, Aleksandra Gentry-Maharaj, Usha Menon, Susan J. Ramus, Anna H. Wu, Agnieszka Dansonka-Mieszkowska, Jolanta Kupryjanczyk, Agnieszka Timorek, Lukasz Szafron, Julie M. Cunningham, Brooke L. Fridley, Stacey J. Winham, Elisa V. Bandera, Elizabeth M. Poole, Terry K. Morgan, Ellen L. Goode, Joellen M. Schildkraut, Celeste L. Pearce, Andrew Berchuck, Paul D. P. Pharoah, Penelope M. Webb, Georgia Chenevix-Trench, Harvey A. Risch, Stuart MacGregor

Abstract

Epithelial ovarian cancer (EOC) is one of the deadliest common cancers. The five most common types of disease are high-grade and low-grade serous, endometrioid, mucinous and clear cell carcinoma. Each of these subtypes present distinct molecular pathogeneses and sensitivities to treatments. Recent studies show that certain genetic variants confer susceptibility to all subtypes while other variants are subtype-specific. Here, we perform an extensive analysis of the genetic architecture of EOC subtypes. To this end, we used data of 10,014 invasive EOC patients and 21,233 controls from the Ovarian Cancer Association Consortium genotyped in the iCOGS array (211,155 SNPs). We estimate the array heritability (attributable to variants tagged on arrays) of each subtype and their genetic correlations. We also look for genetic overlaps with factors such as obesity, smoking behaviors, diabetes, age at menarche and height. We estimated the array heritabilities of high-grade serous disease ([Formula: see text] = 8.8 ± 1.1 %), endometrioid ([Formula: see text] = 3.2 ± 1.6 %), clear cell ([Formula: see text] = 6.7 ± 3.3 %) and all EOC ([Formula: see text] = 5.6 ± 0.6 %). Known associated loci contributed approximately 40 % of the total array heritability for each subtype. The contribution of each chromosome to the total heritability was not proportional to chromosome size. Through bivariate and cross-trait LD score regression, we found evidence of shared genetic backgrounds between the three high-grade subtypes: serous, endometrioid and undifferentiated. Finally, we found significant genetic correlations of all EOC with diabetes and obesity using a polygenic prediction approach.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 1%
Unknown 78 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 18%
Other 8 10%
Student > Bachelor 8 10%
Student > Ph. D. Student 5 6%
Student > Master 5 6%
Other 15 19%
Unknown 24 30%
Readers by discipline Count As %
Medicine and Dentistry 15 19%
Biochemistry, Genetics and Molecular Biology 9 11%
Agricultural and Biological Sciences 7 9%
Unspecified 5 6%
Chemistry 3 4%
Other 12 15%
Unknown 28 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 April 2016.
All research outputs
#13,975,135
of 22,862,742 outputs
Outputs from Human Genetics
#2,419
of 2,954 outputs
Outputs of similar age
#155,059
of 300,866 outputs
Outputs of similar age from Human Genetics
#15
of 32 outputs
Altmetric has tracked 22,862,742 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,954 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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 300,866 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.