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A New Classification System for IgG4 Autoantibodies

Overview of attention for article published in Frontiers in immunology, February 2018
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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Title
A New Classification System for IgG4 Autoantibodies
Published in
Frontiers in immunology, February 2018
DOI 10.3389/fimmu.2018.00097
Pubmed ID
Authors

Inga Koneczny

Abstract

IgG4 autoimmune diseases are characterized by the presence of antigen-specific autoantibodies of the IgG4 subclass and contain well-characterized diseases such as muscle-specific kinase myasthenia gravis, pemphigus, and thrombotic thrombocytopenic purpura. In recent years, several new diseases were identified, and by now 14 antigens targeted by IgG4 autoantibodies have been described. The IgG4 subclass is considered immunologically inert and functionally monovalent due to structural differences compared to other IgG subclasses. IgG4 usually arises after chronic exposure to antigen and competes with other antibody species, thus "blocking" their pathogenic effector mechanisms. Accordingly, in the context of IgG4 autoimmunity, the pathogenicity of IgG4 is associated with blocking of enzymatic activity or protein-protein interactions of the target antigen. Pathogenicity of IgG4 autoantibodies has not yet been systematically analyzed in IgG4 autoimmune diseases. Here, we establish a modified classification system based on Witebsky's postulates to determine IgG4 pathogenicity in IgG4 autoimmune diseases, review characteristics and pathogenic mechanisms of IgG4 in these disorders, and also investigate the contribution of other antibody entities to pathophysiology by additional mechanisms. As a result, three classes of IgG4 autoimmune diseases emerge: class I where IgG4 pathogenicity is validated by the use of subclass-specific autoantibodies in animal models and/orin vitromodels of pathogenicity; class II where IgG4 pathogenicity is highly suspected but lack validation by the use of subclass specific antibodies inin vitromodels of pathogenicity or animal models; and class III with insufficient data or a pathogenic mechanism associated with multivalent antigen binding. Five out of the 14 IgG4 antigens were validated as class I, five as class II, and four as class III. Antibodies of other IgG subclasses or immunoglobulin classes were present in several diseases and could contribute additional pathogenic mechanisms.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 141 100%

Demographic breakdown

Readers by professional status Count As %
Other 20 14%
Researcher 19 13%
Student > Ph. D. Student 14 10%
Student > Master 14 10%
Student > Bachelor 12 9%
Other 30 21%
Unknown 32 23%
Readers by discipline Count As %
Medicine and Dentistry 35 25%
Biochemistry, Genetics and Molecular Biology 21 15%
Immunology and Microbiology 19 13%
Agricultural and Biological Sciences 10 7%
Neuroscience 10 7%
Other 11 8%
Unknown 35 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 31 October 2023.
All research outputs
#1,892,129
of 25,498,750 outputs
Outputs from Frontiers in immunology
#1,775
of 31,842 outputs
Outputs of similar age
#44,782
of 455,053 outputs
Outputs of similar age from Frontiers in immunology
#56
of 664 outputs
Altmetric has tracked 25,498,750 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 31,842 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 94% 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 455,053 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 664 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.