↓ Skip to main content

Natural disease history and characterisation of SUMF1 molecular defects in ten unrelated patients with multiple sulfatase deficiency

Overview of attention for article published in Orphanet Journal of Rare Diseases, March 2015
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 (84th percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
35 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
Natural disease history and characterisation of SUMF1 molecular defects in ten unrelated patients with multiple sulfatase deficiency
Published in
Orphanet Journal of Rare Diseases, March 2015
DOI 10.1186/s13023-015-0244-7
Pubmed ID
Authors

Frédérique Sabourdy, Lionel Mourey, Emmanuelle Le Trionnaire, Nathalie Bednarek, Catherine Caillaud, Yves Chaix, Marie-Ange Delrue, Anne Dusser, Roseline Froissart, Roselyne Garnotel, Nathalie Guffon, André Megarbane, Hélène Ogier de Baulny, Jean-Michel Pédespan, Samia Pichard, Vassili Valayannopoulos, Alain Verloes, Thierry Levade

Abstract

Multiple sulfatase deficiency is a rare inherited metabolic disorder caused by mutations in the SUMF1 gene. The disease remains poorly known, often leading to a late diagnosis. This study aimed to provide improved knowledge of the disease, through complete clinical, biochemical, and molecular descriptions of a cohort of unrelated patients. The main objective was to identify prognostic markers, both phenotypic and genotypic, to accelerate the diagnosis and improve patient care. The phenotypes of ten unrelated patients were fully documented at the clinical and biochemical levels. The long-term follow-up of each patient allowed correlations of the phenotypes to the disease outcomes. Each patient's molecular defects were also identified. Site-directed mutagenesis was used to individually express the mutants and assess their stability. Characterisation of the protein mutants was completed by in silico analyses based on sequence comparisons and structural models. The most severe cases were characterised by the presence of non-neurological symptoms as well as the occurrence of psychomotor regression before 2 years of age. Nine novel SUMF1 mutations were identified. Clinically severe forms were often associated with SUMF1 mutations that strongly affected the protein stability and/or catalytic function as predicted from in silico and western blot analyses. This detailed clinical description and follow-up of a cohort of patients, together with the molecular characterisation of their underlying defects, contribute to improved knowledge of multiple sulfatase deficiency. Predictors of a bad prognosis were the presence of several non-neurological symptoms and the onset of psychomotor regression before 2 years of age. No strict correlation existed between in vitro residual sulfatase activity and disease severity. Genotype-phenotype correlations related to previously reported mutants were strengthened. These and previous observations allow not only improved prediction of the disease outcome but also provision of appropriate care for patients, in the expectation of specific treatment development.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Researcher 8 23%
Other 4 11%
Student > Bachelor 3 9%
Professor 2 6%
Other 7 20%
Unknown 2 6%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 31%
Agricultural and Biological Sciences 11 31%
Medicine and Dentistry 6 17%
Social Sciences 2 6%
Neuroscience 1 3%
Other 1 3%
Unknown 3 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 07 September 2017.
All research outputs
#2,015,870
of 15,922,017 outputs
Outputs from Orphanet Journal of Rare Diseases
#245
of 1,696 outputs
Outputs of similar age
#33,392
of 219,646 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#1
of 1 outputs
Altmetric has tracked 15,922,017 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,696 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 85% 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 219,646 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 84% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them