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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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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
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5 tweeters

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13 Dimensions

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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, 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.

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

Geographical breakdown

Country Count As %
Finland 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 27%
Unspecified 8 17%
Student > Bachelor 5 10%
Other 5 10%
Student > Ph. D. Student 4 8%
Other 13 27%
Readers by discipline Count As %
Medicine and Dentistry 11 23%
Biochemistry, Genetics and Molecular Biology 10 21%
Unspecified 9 19%
Agricultural and Biological Sciences 7 15%
Chemistry 3 6%
Other 8 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 April 2016.
All research outputs
#6,430,939
of 12,441,812 outputs
Outputs from Human Genetics
#2,009
of 2,487 outputs
Outputs of similar age
#100,193
of 270,160 outputs
Outputs of similar age from Human Genetics
#18
of 26 outputs
Altmetric has tracked 12,441,812 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,487 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 19th percentile – i.e., 19% 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 270,160 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.