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Impact of atopy on risk of glioma: a Mendelian randomisation study

Overview of attention for article published in BMC Medicine, March 2018
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  • Good Attention Score compared to outputs of the same age (68th percentile)

Mentioned by

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11 tweeters

Citations

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22 Dimensions

Readers on

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42 Mendeley
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Title
Impact of atopy on risk of glioma: a Mendelian randomisation study
Published in
BMC Medicine, March 2018
DOI 10.1186/s12916-018-1027-5
Pubmed ID
Authors

Linden Disney-Hogg, Alex J. Cornish, Amit Sud, Philip J. Law, Ben Kinnersley, Daniel I. Jacobs, Quinn T. Ostrom, Karim Labreche, Jeanette E. Eckel-Passow, Georgina N. Armstrong, Elizabeth B. Claus, Dora Il’yasova, Joellen Schildkraut, Jill S. Barnholtz-Sloan, Sara H. Olson, Jonine L. Bernstein, Rose K. Lai, Minouk J. Schoemaker, Matthias Simon, Per Hoffmann, Markus M. Nöthen, Karl-Heinz Jöckel, Stephen Chanock, Preetha Rajaraman, Christoffer Johansen, Robert B. Jenkins, Beatrice S. Melin, Margaret R. Wrensch, Marc Sanson, Melissa L. Bondy, Richard S. Houlston

Abstract

An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis. Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194). Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 21%
Researcher 8 19%
Student > Master 6 14%
Student > Bachelor 5 12%
Student > Doctoral Student 2 5%
Other 3 7%
Unknown 9 21%
Readers by discipline Count As %
Medicine and Dentistry 8 19%
Biochemistry, Genetics and Molecular Biology 7 17%
Social Sciences 2 5%
Chemistry 2 5%
Nursing and Health Professions 2 5%
Other 7 17%
Unknown 14 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 May 2018.
All research outputs
#4,136,001
of 15,922,425 outputs
Outputs from BMC Medicine
#1,729
of 2,485 outputs
Outputs of similar age
#88,222
of 281,061 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 15,922,425 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,485 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.8. This one is in the 30th percentile – i.e., 30% 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 281,061 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 68% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them