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Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis

Overview of attention for article published in PLOS ONE, March 2013
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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)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
1 blog
twitter
2 X users
patent
9 patents
facebook
1 Facebook page
wikipedia
3 Wikipedia pages

Readers on

mendeley
69 Mendeley
citeulike
1 CiteULike
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Article details
Title
Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0056379
Pubmed ID
Authors
Abstract

Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10(-6)). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 69 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 %
United States 1 1%
Germany 1 1%
Unknown 67 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 14 20%
Student > Ph. D. Student 10 14%
Student > Bachelor 9 13%
Student > Master 7 10%
Student > Doctoral Student 6 9%
Other 13 19%
Unknown 10 14%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 19 28%
Medicine and Dentistry 14 20%
Biochemistry, Genetics and Molecular Biology 10 14%
Computer Science 5 7%
Nursing and Health Professions 2 3%
Other 10 14%
Unknown 9 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 21 July 2026.
All research outputs
#3,284,706
of 34,360,889 outputs
Outputs from PLOS ONE
#34,564
of 224,520 outputs
Outputs of similar age
#23,315
of 242,028 outputs
Outputs of similar age from PLOS ONE
#823
of 5,741 outputs
Altmetric has tracked 34,360,889 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 224,520 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has done well, scoring higher than 84% 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 242,028 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 5,741 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.