Researchers identify new mechanism for drug-related autoimmune reactions

May 23 2012

In an article available online today in the journal AIDS, the team found that in certain at-risk patients, the anti-HIV drug Ziagen (abacavir) causes the immune system to "see" a patient's own healthy tissues and proteins as a foreign invader. The effect is similar to what happens when the immune system recognizes a viral or bacterial protein during an infection.

Abacavir is known to cause allergic reactions in certain, at-risk patients. These reactions can range from mild skin reactions to severe allergic shock and even death. 

Abacavir interacts with molecules in the immune system called Human Leukocyte Antigens (HLAs), specifically HLA-B*5701, which help the body to distinguish "self" versus "foreign" proteins. The drug can cause HLA-B*5701 to present for the first time certain "self" proteins that the body has not seen before. Because the body has not previously recognized these "self" proteins, it mistakenly treats them as foreign, resulting in the body trying to destroy its own tissues. HLA-B*5701 is known to be a risk factor for serious reactions to abacavir.

"This discovery is a new step towards understanding how and why certain drugs cause severe allergic reactions in some patients," said Janet Woodcock, M.D., director of FDA's Center for Drug Evaluation and Research (CDER). "We hope that, in the future, health care professionals will be able to identify people who are at high risk of developing serious reactions to various drugs, and offer them alternative treatments."

The research team's work will provide the FDA with new tools to analyze the safety of drugs that have the potential to cause severe allergic reactions. This latest discovery will advance the FDA's ability to approve therapies that are personalized for safety.

The results also may give biopharmaceutical companies and other research organizations new methods to identify early in the development process drugs with the potential to cause severe adverse drug reactions. This may also serve as a model for future research to predict drug reactions in different populations of at-risk patients.