| Title |
Genetics and autoantibodies
|
|---|---|
| Published in |
Immunologic Research, April 2013
|
| DOI | 10.1007/s12026-013-8396-9 |
| Pubmed ID | |
| Authors |
Carlo Perricone, Nancy Agmon-Levin, Fulvia Ceccarelli, Guido Valesini, Juan-Manuel Anaya, Yehuda Shoenfeld |
| Abstract |
Autoimmune diseases (ADs) are chronic conditions initiated by the loss of immunological tolerance to self-antigens. The pathogenic hypothesis comprises a complex interaction between genetic, environmental and hormonal factors that interact with an individual over time generating a dysregulation of the immune system leading to disease development. Several polymorphic genes contribute to the development of ADs. Furthermore, age and gender play a major role by influencing hormone levels that can represent the fulcrum unbalancing from susceptibility to protection. Evidences suggest that while all these steps occur, the susceptible individual develops autoantibodies over a long time lapse. Such autoantibody production is genetically determined and finally, their presence seems to determine the clinical presentation of ADs. The genetic predisposition to the developments of autoantibodies and toward the disease process may overlap. The unveiling of these mechanisms could allow not only to treat but also to prevent the development of autoimmune diseases. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 1% |
| Colombia | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 65 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 12% |
| Student > Bachelor | 8 | 12% |
| Student > Master | 8 | 12% |
| Researcher | 6 | 9% |
| Professor | 4 | 6% |
| Other | 10 | 15% |
| Unknown | 24 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 21 | 31% |
| Biochemistry, Genetics and Molecular Biology | 7 | 10% |
| Immunology and Microbiology | 5 | 7% |
| Agricultural and Biological Sciences | 3 | 4% |
| Engineering | 2 | 3% |
| Other | 7 | 10% |
| Unknown | 23 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 16 July 2013.
All research outputs
#15,274,524
of 22,714,025 outputs
Outputs from Immunologic Research
#557
of 905 outputs
Outputs of similar age
#124,691
of 199,519 outputs
Outputs of similar age from Immunologic Research
#16
of 22 outputs
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