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Large-Scale Pathway-Based Analysis of Bladder Cancer Genome-Wide Association Data from Five Studies of European Background

Overview of attention for article published in PLOS ONE, January 2012
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Title
Large-Scale Pathway-Based Analysis of Bladder Cancer Genome-Wide Association Data from Five Studies of European Background
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029396
Pubmed ID
Authors

Idan Menashe, Jonine D. Figueroa, Montserrat Garcia-Closas, Nilanjan Chatterjee, Nuria Malats, Antoni Picornell, Dennis Maeder, Qi Yang, Ludmila Prokunina-Olsson, Zhaoming Wang, Francisco X. Real, Kevin B. Jacobs, Dalsu Baris, Michael Thun, Demetrius Albanes, Mark P. Purdue, Manolis Kogevinas, Amy Hutchinson, Yi-Ping Fu, Wei Tang, Laurie Burdette, Adonina Tardón, Consol Serra, Alfredo Carrato, Reina García-Closas, Josep Lloreta, Alison Johnson, Molly Schwenn, Alan Schned, Gerald Andriole, Amanda Black, Eric J. Jacobs, Ryan W. Diver, Susan M. Gapstur, Stephanie J. Weinstein, Jarmo Virtamo, Neil E. Caporaso, Maria Teresa Landi, Joseph F. Fraumeni, Stephen J. Chanock, Debra T. Silverman, Nathaniel Rothman

Abstract

Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I(2) statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways ('Aromatic amine metabolism' [P(GSEA) = 0.0100, P(ARTP) = 0.0020], 'NAD biosynthesis' [P(GSEA) = 0.0018, P(ARTP) = 0.0086], 'NAD salvage' [P(ARTP) = 0.0068], 'Clathrin derived vesicle budding' [P(ARTP) = 0.0018], 'Lysosome vesicle biogenesis' [P(GSEA) = 0.0023, P(ARTP)<0.00012], 'Retrograde neurotrophin signaling' [P(GSEA) = 0.00840], and 'Mitotic metaphase/anaphase transition' [P(GSEA) = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.

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Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 8%
Spain 3 5%
Sweden 1 2%
France 1 2%
United Kingdom 1 2%
Unknown 54 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 31%
Student > Ph. D. Student 14 22%
Other 6 9%
Professor 5 8%
Student > Master 4 6%
Other 9 14%
Unknown 7 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 37%
Medicine and Dentistry 18 28%
Biochemistry, Genetics and Molecular Biology 5 8%
Computer Science 2 3%
Engineering 2 3%
Other 6 9%
Unknown 8 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 January 2012.
All research outputs
#17,654,408
of 22,661,413 outputs
Outputs from PLOS ONE
#146,212
of 193,502 outputs
Outputs of similar age
#191,343
of 244,244 outputs
Outputs of similar age from PLOS ONE
#2,153
of 3,052 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
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