↓ Skip to main content

Low-frequency and common genetic variation in ischemic stroke

Overview of attention for article published in Neurology, March 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

blogs
1 blog
twitter
10 tweeters

Readers on

mendeley
29 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Low-frequency and common genetic variation in ischemic stroke
Published in
Neurology, March 2016
DOI 10.1212/wnl.0000000000002528
Pubmed ID
Authors

Rainer Malik, Matthew Traylor, Sara L. Pulit, Steve Bevan, Jemma C. Hopewell, Elizabeth G. Holliday, Wei Zhao, Patricia Abrantes, Philippe Amouyel, John R. Attia, Thomas W.K. Battey, Klaus Berger, Giorgio B. Boncoraglio, Ganesh Chauhan, Yu-Ching Cheng, Wei-Min Chen, Robert Clarke, Ioana Cotlarciuc, Stephanie Debette, Guido J. Falcone, Jose M. Ferro, Dale M. Gamble, Andreea Ilinca, Steven J. Kittner, Christina E. Kourkoulis, Robin Lemmens, Christopher R. Levi, Peter Lichtner, Arne Lindgren, Jingmin Liu, James F. Meschia, Braxton D. Mitchell, Sofia A. Oliveira, Joana Pera, Alex P. Reiner, Peter M. Rothwell, Pankaj Sharma, Agnieszka Slowik, Cathie L.M. Sudlow, Turgut Tatlisumak, Vincent Thijs, Astrid M. Vicente, Daniel Woo, Sudha Seshadri, Danish Saleheen, Jonathan Rosand, Hugh S. Markus, Bradford B. Worrall, Martin Dichgans

Abstract

To investigate the influence of common and low-frequency genetic variants on the risk of ischemic stroke (all IS) and etiologic stroke subtypes. We meta-analyzed 12 individual genome-wide association studies comprising 10,307 cases and 19,326 controls imputed to the 1000 Genomes (1 KG) phase I reference panel. We selected variants showing the highest degree of association (p < 1E-5) in the discovery phase for replication in Caucasian (13,435 cases and 29,269 controls) and South Asian (2,385 cases and 5,193 controls) samples followed by a transethnic meta-analysis. We further investigated the p value distribution for different bins of allele frequencies for all IS and stroke subtypes. We showed genome-wide significance for 4 loci: ABO for all IS, HDAC9 for large vessel disease (LVD), and both PITX2 and ZFHX3 for cardioembolic stroke (CE). We further refined the association peaks for ABO and PITX2. Analyzing different allele frequency bins, we showed significant enrichment in low-frequency variants (allele frequency <5%) for both LVD and small vessel disease, and an enrichment of higher frequency variants (allele frequency 10% and 30%) for CE (all p < 1E-5). Our findings suggest that the missing heritability in IS subtypes can in part be attributed to low-frequency and rare variants. Larger sample sizes are needed to identify the variants associated with all IS and stroke subtypes.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 4 14%
Student > Master 4 14%
Researcher 3 10%
Student > Ph. D. Student 3 10%
Student > Bachelor 3 10%
Other 7 24%
Unknown 5 17%
Readers by discipline Count As %
Medicine and Dentistry 7 24%
Biochemistry, Genetics and Molecular Biology 7 24%
Nursing and Health Professions 2 7%
Agricultural and Biological Sciences 2 7%
Unspecified 1 3%
Other 3 10%
Unknown 7 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 20 August 2016.
All research outputs
#890,185
of 13,474,817 outputs
Outputs from Neurology
#1,842
of 13,846 outputs
Outputs of similar age
#25,319
of 269,560 outputs
Outputs of similar age from Neurology
#85
of 300 outputs
Altmetric has tracked 13,474,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,846 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has done well, scoring higher than 86% 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 269,560 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 90% of its contemporaries.
We're also able to compare this research output to 300 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.