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Association of modifiers and other genetic factors explain Marfan syndrome clinical variability

Overview of attention for article published in European Journal of Human Genetics, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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Title
Association of modifiers and other genetic factors explain Marfan syndrome clinical variability
Published in
European Journal of Human Genetics, August 2018
DOI 10.1038/s41431-018-0164-9
Pubmed ID
Authors

Melodie Aubart, Steven Gazal, Pauline Arnaud, Louise Benarroch, Marie-Sylvie Gross, Julien Buratti, Anne Boland, Vincent Meyer, Habib Zouali, Nadine Hanna, Olivier Milleron, Chantal Stheneur, Thomas Bourgeron, Isabelle Desguerre, Marie-Paule Jacob, Laurent Gouya, Emmanuelle Génin, Jean-François Deleuze, Guillaume Jondeau, Catherine Boileau

Abstract

Marfan syndrome (MFS) is a rare autosomal dominant connective tissue disorder related to variants in the FBN1 gene. Prognosis is related to aortic risk of dissection following aneurysm. MFS clinical variability is notable, for age of onset as well as severity and number of clinical manifestations. To identify genetic modifiers, we combined genome-wide approaches in 1070 clinically well-characterized FBN1 disease-causing variant carriers: (1) an FBN1 eQTL analysis in 80 fibroblasts of FBN1 stop variant carriers, (2) a linkage analysis, (3) a kinship matrix association study in 14 clinically concordant and discordant sib-pairs, (4) a genome-wide association study and (5) a whole exome sequencing in 98 extreme phenotype samples.Three genetic mechanisms of variability were found. A new genotype/phenotype correlation with an excess of loss-of-cysteine variants (P = 0.004) in severely affected subjects. A second pathogenic event in another thoracic aortic aneurysm gene or the COL4A1 gene (known to be involved in cerebral aneurysm) was found in nine individuals. A polygenic model involving at least nine modifier loci (named gMod-M1-9) was observed through cross-mapping of results. Notably, gMod-M2 which co-localizes with PRKG1, in which activating variants have already been described in thoracic aortic aneurysm, and gMod-M3 co-localized with a metalloprotease (proteins of extra-cellular matrix regulation) cluster. Our results represent a major advance in understanding the complex genetic architecture of MFS and provide the first steps toward prediction of clinical evolution.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 17%
Researcher 9 12%
Student > Master 7 9%
Student > Postgraduate 5 6%
Student > Bachelor 4 5%
Other 11 14%
Unknown 28 36%
Readers by discipline Count As %
Medicine and Dentistry 20 26%
Biochemistry, Genetics and Molecular Biology 14 18%
Neuroscience 3 4%
Engineering 2 3%
Immunology and Microbiology 2 3%
Other 8 10%
Unknown 28 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 29 October 2019.
All research outputs
#5,534,562
of 23,099,576 outputs
Outputs from European Journal of Human Genetics
#1,377
of 3,460 outputs
Outputs of similar age
#94,172
of 330,798 outputs
Outputs of similar age from European Journal of Human Genetics
#18
of 53 outputs
Altmetric has tracked 23,099,576 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,460 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has gotten more attention than average, scoring higher than 60% 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 330,798 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 71% of its contemporaries.
We're also able to compare this research output to 53 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 66% of its contemporaries.