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A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci

Overview of attention for article published in Cancer Epidemiology, Biomarkers & Prevention, December 2016
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Article details
Title
A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci
Published in
Cancer Epidemiology, Biomarkers & Prevention, December 2016
DOI 10.1158/1055-9965.epi-15-1193
Pubmed ID
Authors

Kristin A Rand, Chi Song, Eric Dean, Daniel J Serie, Karen Curtin, Xin Sheng, Donglei Hu, Carol Ann Huff, Leon Bernal-Mizrachi, Michael H Tomasson, Sikander Ailawadhi, Seema Singhal, Karen Pawlish, Edward S Peters, Cathryn H Bock, Alex Stram, David J Van Den Berg, Christopher K Edlund, David V Conti, Todd Zimmerman, Amie E Hwang, Scott Huntsman, John Graff, Ajay Nooka, Yinfei Kong, Silvana L Pregja, Sonja I Berndt, William J Blot, John Carpten, Graham Casey, Lisa Chu, W Ryan Diver, Victoria L Stevens, Michael R Lieber, Phyllis J Goodman, Anselm J M Hennis, Ann W Hsing, Jayesh Mehta, Rick A Kittles, Suzanne Kolb, Eric A Klein, Cristina Leske, Adam B Murphy, Barbara Nemesure, Christine Neslund-Dudas, Sara S Strom, Ravi Vij, Benjamin A Rybicki, Janet L Stanford, Lisa B Signorello, John S Witte, Christine B Ambrosone, Parveen Bhatti, Esther M John, Leslie Bernstein, Wei Zheng, Andrew F Olshan, Jennifer J Hu, Regina G Ziegler, Sarah J Nyante, Elisa V Bandera, Brenda M Birmann, Sue A Ingles, Michael F Press, Djordje Atanackovic, Martha J Glenn, Lisa A Cannon-Albright, Brandt Jones, Guido Tricot, Thomas G Martin, Shaji K Kumar, Jeffrey L Wolf, Sandra L Deming Halverson, Nathaniel Rothman, Angela R Brooks-Wilson, S Vincent Rajkumar, Laurence N Kolonel, Stephen J Chanock, Susan L Slager, Richard K Severson, Nalini Janakiraman, Howard R Terebelo, Elizabeth E Brown, Anneclaire J De Roos, Ann F Mohrbacher, Graham A Colditz, Graham G Giles, John J Spinelli, Brian C Chiu, Nikhil C Munshi, Kenneth C Anderson, Joan Levy, Jeffrey A Zonder, Robert Z Orlowski, Sagar Lonial, Nicola J Camp, Celine M Vachon, Elad Ziv, Daniel O Stram, Dennis J Hazelett, Christopher A Haiman, Wendy Cozen

Abstract

Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM). We performed association testing of common variation in eight regions in 1,264 MM patients and 1,479 controls of European ancestry (EA) and 1,305 MM patients and 7,078 controls of African ancestry (AA) and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (p<0.05) associated with MM risk in AAs and EAs and the variant in 3p22.1 was associated in EAs only. In a combined AA-EA meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically signficantly associated with MM risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR=1.32, p=2.93x10-7) in TNFRSF13B, encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. We found that reported MM susceptibility regions contain risk variants important across populations supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. A subset of reported risk loci for multiple myeloma have consistent affects across populations and are likely to be functional.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 15 19%
Researcher 11 14%
Professor 7 9%
Student > Master 7 9%
Other 6 7%
Other 10 12%
Unknown 25 31%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 25 31%
Biochemistry, Genetics and Molecular Biology 12 15%
Agricultural and Biological Sciences 4 5%
Immunology and Microbiology 4 5%
Nursing and Health Professions 3 4%
Other 5 6%
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 28 February 2018.
All research outputs
#24,275,229
of 34,601,305 outputs
Outputs from Cancer Epidemiology, Biomarkers & Prevention
#4,436
of 5,762 outputs
Outputs of similar age
#302,367
of 454,128 outputs
Outputs of similar age from Cancer Epidemiology, Biomarkers & Prevention
#32
of 40 outputs
Altmetric has tracked 34,601,305 research outputs across all sources so far. This one is in the 28th percentile – i.e., 28% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,762 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.6. This one is in the 21st percentile – i.e., 21% 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 454,128 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.