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Multiple sclerosis risk loci and disease severity in 7,125 individuals from 10 studies

Overview of attention for article published in Neurology: Genetics, August 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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2 news outlets
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6 X users
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1 Facebook page

Citations

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74 Dimensions

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74 Mendeley
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Title
Multiple sclerosis risk loci and disease severity in 7,125 individuals from 10 studies
Published in
Neurology: Genetics, August 2016
DOI 10.1212/nxg.0000000000000087
Pubmed ID
Authors

Michaela F George, Farren B S Briggs, Xiaorong Shao, Milena A Gianfrancesco, Ingrid Kockum, Hanne F Harbo, Elisabeth G Celius, Steffan D Bos, Anna Hedström, Ling Shen, Allan Bernstein, Lars Alfredsson, Jan Hillert, Tomas Olsson, Nikolaos A Patsopoulos, Philip L De Jager, Annette B Oturai, Helle B Søndergaard, Finn Sellebjerg, Per S Sorensen, Refujia Gomez, Stacy J Caillier, Bruce A C Cree, Jorge R Oksenberg, Stephen L Hauser, Sandra D'Alfonso, Maurizio A Leone, Filippo Martinelli Boneschi, Melissa Sorosina, Ingrid van der Mei, Bruce V Taylor, Yuan Zhou, Catherine Schaefer, Lisa F Barcellos

Abstract

We investigated the association between 52 risk variants identified through genome-wide association studies and disease severity in multiple sclerosis (MS). Ten unique MS case data sets were analyzed. The Multiple Sclerosis Severity Score (MSSS) was calculated using the Expanded Disability Status Scale at study entry and disease duration. MSSS was considered as a continuous variable and as 2 dichotomous variables (median and extreme ends; MSSS of ≤5 vs >5 and MSSS of <2.5 vs ≥7.5, respectively). Single nucleotide polymorphisms (SNPs) were examined individually and as both combined weighted genetic risk score (wGRS) and unweighted genetic risk score (GRS) for association with disease severity. Random-effects meta-analyses were conducted and adjusted for cohort, sex, age at onset, and HLA-DRB1*15:01. A total of 7,125 MS cases were analyzed. The wGRS and GRS were not strongly associated with disease severity after accounting for cohort, sex, age at onset, and HLA-DRB1*15:01. After restricting analyses to cases with disease duration ≥10 years, associations were null (p value ≥0.05). No SNP was associated with disease severity after adjusting for multiple testing. The largest meta-analysis of established MS genetic risk variants and disease severity, to date, was performed. Results suggest that the investigated MS genetic risk variants are not associated with MSSS, even after controlling for potential confounders. Further research in large cohorts is needed to identify genetic determinants of disease severity using sensitive clinical and MRI measures, which are critical to understanding disease mechanisms and guiding development of effective treatments.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 1%
Unknown 73 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 19%
Researcher 14 19%
Other 7 9%
Student > Master 6 8%
Student > Doctoral Student 4 5%
Other 16 22%
Unknown 13 18%
Readers by discipline Count As %
Medicine and Dentistry 24 32%
Neuroscience 12 16%
Agricultural and Biological Sciences 8 11%
Biochemistry, Genetics and Molecular Biology 6 8%
Social Sciences 2 3%
Other 2 3%
Unknown 20 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 27 November 2022.
All research outputs
#1,776,262
of 25,374,917 outputs
Outputs from Neurology: Genetics
#58
of 703 outputs
Outputs of similar age
#32,939
of 381,902 outputs
Outputs of similar age from Neurology: Genetics
#3
of 24 outputs
Altmetric has tracked 25,374,917 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 703 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has done particularly well, scoring higher than 91% 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 381,902 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 91% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.