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Scientifica
Volume 2013, Article ID 637629, 30 pages
http://dx.doi.org/10.1155/2013/637629
Review Article

Genetics of Proteasome Diseases

1Department of Neurobiology, Physiology, and Behavior, University of California, Davis, CA 95616, USA
2Department of Physiology and Membrane Biology, University of California, Davis, CA 95616, USA

Received 20 October 2013; Accepted 18 November 2013

Academic Editors: I. Alvarez, M. Cardelli, N. Osna, M. Salio, and T. Vellai

Copyright © 2013 Aldrin V. Gomes. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The proteasome is a large, multiple subunit complex that is capable of degrading most intracellular proteins. Polymorphisms in proteasome subunits are associated with cardiovascular diseases, diabetes, neurological diseases, and cancer. One polymorphism in the proteasome gene PSMA6 (−8C/G) is associated with three different diseases: type 2 diabetes, myocardial infarction, and coronary artery disease. One type of proteasome, the immunoproteasome, which contains inducible catalytic subunits, is adapted to generate peptides for antigen presentation. It has recently been shown that mutations and polymorphisms in the immunoproteasome catalytic subunit PSMB8 are associated with several inflammatory and autoinflammatory diseases including Nakajo-Nishimura syndrome, CANDLE syndrome, and intestinal M. tuberculosis infection. This comprehensive review describes the disease-related polymorphisms in proteasome genes associated with human diseases and the physiological modulation of proteasome function by these polymorphisms. Given the large number of subunits and the central importance of the proteasome in human physiology as well as the fast pace of detection of proteasome polymorphisms associated with human diseases, it is likely that other polymorphisms in proteasome genes associated with diseases will be detected in the near future. While disease-associated polymorphisms are now readily discovered, the challenge will be to use this genetic information for clinical benefit.