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Autoimmune Responses to Soluble Aggregates of Amyloidogenic Proteins Involved in Neurodegenerative Diseases: Overlapping Aggregation Prone and Autoimmunogenic regions

Overview of attention for article published in Scientific Reports, February 2016
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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 (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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Citations

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Title
Autoimmune Responses to Soluble Aggregates of Amyloidogenic Proteins Involved in Neurodegenerative Diseases: Overlapping Aggregation Prone and Autoimmunogenic regions
Published in
Scientific Reports, February 2016
DOI 10.1038/srep22258
Pubmed ID
Authors

Sandeep Kumar, A. Mary Thangakani, R. Nagarajan, Satish K. Singh, D. Velmurugan, M. Michael Gromiha

Abstract

Why do patients suffering from neurodegenerative diseases generate autoantibodies that selectively bind soluble aggregates of amyloidogenic proteins? Presently, molecular basis of interactions between the soluble aggregates and human immune system is unknown. By analyzing sequences of experimentally validated T-cell autoimmune epitopes, aggregating peptides, amyloidogenic proteins and randomly generated peptides, here we report overlapping regions that likely drive aggregation as well as generate autoantibodies against the aggregates. Sequence features, that make short peptides susceptible to aggregation, increase their incidence in human T-cell autoimmune epitopes by 4-6 times. Many epitopes are predicted to be significantly aggregation prone (aggregation propensities ≥10%) and the ones containing experimentally validated aggregating regions are enriched in hydrophobicity by 10-20%. Aggregate morphologies also influence Human Leukocyte Antigen (HLA) - types recognized by the aggregating regions containing epitopes. Most (88%) epitopes that contain amyloid fibril forming regions bind HLA-DR, while majority (63%) of those containing amorphous β-aggregating regions bind HLA-DQ. More than two-thirds (70%) of human amyloidogenic proteins contain overlapping regions that are simultaneously aggregation prone and auto-immunogenic. Such regions help clear soluble aggregates by generating selective autoantibodies against them. This can be harnessed for early diagnosis of proteinopathies and for drug/vaccine design against them.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 21%
Other 3 10%
Student > Bachelor 3 10%
Student > Master 3 10%
Professor > Associate Professor 2 7%
Other 5 17%
Unknown 7 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 28%
Biochemistry, Genetics and Molecular Biology 6 21%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Immunology and Microbiology 2 7%
Chemistry 2 7%
Other 4 14%
Unknown 5 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 08 March 2016.
All research outputs
#2,938,842
of 23,538,320 outputs
Outputs from Scientific Reports
#25,095
of 127,344 outputs
Outputs of similar age
#46,923
of 299,175 outputs
Outputs of similar age from Scientific Reports
#688
of 3,381 outputs
Altmetric has tracked 23,538,320 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 127,344 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.4. This one has done well, scoring higher than 80% 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 299,175 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 3,381 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.