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Genetic determinants of telomere length and risk of common cancers: a Mendelian randomization study

Overview of attention for article published in Human Molecular Genetics, July 2015
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  • 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 (97th percentile)

Mentioned by

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4 news outlets
blogs
4 blogs
twitter
13 X users

Citations

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132 Dimensions

Readers on

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129 Mendeley
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Title
Genetic determinants of telomere length and risk of common cancers: a Mendelian randomization study
Published in
Human Molecular Genetics, July 2015
DOI 10.1093/hmg/ddv252
Pubmed ID
Authors

Chenan Zhang, Jennifer A. Doherty, Stephen Burgess, Rayjean J. Hung, Sara Lindström, Peter Kraft, Jian Gong, Christopher I. Amos, Thomas A. Sellers, Alvaro N.A. Monteiro, Georgia Chenevix-Trench, Heike Bickeböller, Angela Risch, Paul Brennan, James D. Mckay, Richard S. Houlston, Maria Teresa Landi, Maria N. Timofeeva, Yufei Wang, Joachim Heinrich, Zsofia Kote-Jarai, Rosalind A. Eeles, Ken Muir, Fredrik Wiklund, Henrik Grönberg, Sonja I. Berndt, Stephen J. Chanock, Fredrick Schumacher, Christopher A. Haiman, Brian E. Henderson, Ali Amin Al Olama, Irene L. Andrulis, John L. Hopper, Jenny Chang-Claude, Esther M. John, Kathleen E. Malone, Marilie D. Gammon, Giske Ursin, Alice S. Whittemore, David J. Hunter, Stephen B. Gruber, Julia A. Knight, Lifang Hou, Loic Le Marchand, Polly A. Newcomb, Thomas J. Hudson, Andrew T. Chan, Li Li, Michael O. Woods, Habibul Ahsan, Brandon L. Pierce

Abstract

Epidemiological studies have reported inconsistent associations between telomere length (TL) and risk for various cancers. These inconsistencies are likely attributable, in part, to biases that arise due to post-diagnostic and post-treatment TL measurement. To avoid such biases, we used a Mendelian randomization approach and estimated associations between nine TL-associated SNPs and risk for five common cancer types (breast, lung, colorectal, ovarian and prostate cancer, including subtypes) using data on 51,725 cases and 62,035 controls. We then used an inverse-variance weighted average of the SNP-specific associations to estimate the association between a genetic score representing long TL and cancer risk. The long TL genetic score was significantly associated with increased risk of lung adenocarcinoma (P=6.3x10(-15)), even after exclusion of a SNP residing in a known lung cancer susceptibility region (TERT-CLPTM1L) P=6.6x10(-6)). Under Mendelian randomization assumptions, the association estimate (odds ratio (OR)=2.78) is interpreted as the OR for lung adenocarcinoma corresponding to a 1000 base pair increase in TL. The weighted TL SNP score was not associated with other cancer types or subtypes. Our finding that genetic determinants of long TL increase lung adenocarcinoma risk avoids issues with reverse causality and residual confounding that arise in observational studies of TL and disease risk. Under Mendelian randomization assumptions, our finding suggests that longer TL increases lung adenocarcinoma risk. However, caution regarding this causal interpretation is warranted in light of the potential issue of pleiotropy, and a more general interpretation is that SNPs influencing telomere biology are also implicated in lung adenocarcinoma risk.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
Netherlands 1 <1%
Uruguay 1 <1%
Canada 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 122 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 22%
Student > Ph. D. Student 25 19%
Student > Master 15 12%
Student > Bachelor 12 9%
Student > Doctoral Student 8 6%
Other 16 12%
Unknown 24 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 23%
Agricultural and Biological Sciences 22 17%
Medicine and Dentistry 20 16%
Psychology 4 3%
Mathematics 3 2%
Other 15 12%
Unknown 35 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 63. 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 12 September 2017.
All research outputs
#605,716
of 23,577,654 outputs
Outputs from Human Molecular Genetics
#78
of 8,087 outputs
Outputs of similar age
#7,283
of 264,924 outputs
Outputs of similar age from Human Molecular Genetics
#3
of 127 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,087 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 99% 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 264,924 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 127 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.