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Genome sequencing uncovers phenocopies in primary progressive multiple sclerosis

Overview of attention for article published in Annals of Neurology, July 2018
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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 (86th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

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26 tweeters
facebook
3 Facebook pages

Citations

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2 Dimensions

Readers on

mendeley
9 Mendeley
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1 CiteULike
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Title
Genome sequencing uncovers phenocopies in primary progressive multiple sclerosis
Published in
Annals of Neurology, July 2018
DOI 10.1002/ana.25263
Pubmed ID
Authors

Xiaoming Jia, Lohith Madireddy, Stacy Caillier, Adam Santaniello, Federica Esposito, Giancarlo Comi, Olaf Stuve, Yuan Zhou, Bruce Taylor, Trevor Kilpatrick, Filippo Martinelli-Boneschi, Bruce A.C. Cree, Jorge R. Oksenberg, Stephen L. Hauser, Sergio E Baranzini

Abstract

Primary progressive multiple sclerosis (PPMS) causes accumulation of neurologic disability from disease onset without clinical attacks typical of relapsing multiple sclerosis (RMS). However, whether genetic variation influences the disease course remains unclear. We aimed to determine whether mutations causative of neurologic disorders that share features with MS contribute to risk for developing PPMS. We examined whole-genome sequencing (WGS) data from 38 PPMS and 81 healthy subjects of European ancestry. We selected pathogenic variants exclusively found in PPMS patients that cause monogenic neurologic disorders, and performed two rounds of replication genotyping in 746 PPMS, 3049 RMS, and 1000 healthy subjects. To refine our findings, we examined the burden of rare, potentially pathogenic mutations in 41 genes that cause hereditary spastic paraplegias (HSP) in PPMS (n=314), SPMS (n=587), RMS (n=2,248), and healthy subjects (n=987) genotyped using the MS replication chip. WGS and replication studies identified 3 pathogenic variants in PPMS patients that cause neurologic disorders sharing features with MS: KIF5A p.Ala361Val in Spastic Paraplegia 10, MLC1 p.Pro92Ser in Megalencephalic Leukodystrophy with Subcortical Cysts, and REEP1 c.606 + 43G>T in Spastic Paraplegia 31. Moreover, we detected a significant enrichment of HSP-related mutations in PPMS patients compared to controls (RR=1.95, 95% CI: 1.27-2.98, p=0.002), as well as in SPMS patients compared to controls (RR=1.57, 95% CI: 1.18-2.10, p=0.002). Importantly, this enrichment was not detected in RMS. This study provides evidence to support the hypothesis that rare Mendelian genetic variants contribute to the risk for developing progressive forms of multiple sclerosis. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 26 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 33%
Professor 2 22%
Other 1 11%
Student > Doctoral Student 1 11%
Student > Master 1 11%
Other 1 11%
Readers by discipline Count As %
Unspecified 3 33%
Neuroscience 3 33%
Medicine and Dentistry 2 22%
Biochemistry, Genetics and Molecular Biology 1 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 01 August 2018.
All research outputs
#872,308
of 12,427,514 outputs
Outputs from Annals of Neurology
#400
of 3,833 outputs
Outputs of similar age
#35,361
of 270,398 outputs
Outputs of similar age from Annals of Neurology
#13
of 36 outputs
Altmetric has tracked 12,427,514 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,833 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one has done well, scoring higher than 89% 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 270,398 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 36 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 63% of its contemporaries.