BioWorld International Correspondent

LONDON - People with fewer copies of a gene that is expressed by cells of the immune system are at higher risk of developing certain kinds of autoimmune disease, a recent study has found.

The study is one of the first to confirm that variation in the number of copies of a gene is a common cause of human disease, and suggested that measurement of gene copy number variation will, in the future, become an important diagnostic tool for clinicians.

Timothy Aitman, professor of clinical and molecular genetics at Imperial College in London, told BioWorld International, "The findings of this study make it clear that gene copy number variation is an important cause of common human diseases, something that was not previously appreciated."

Aitman and his collaborators showed that people who have below the average number of copies of a gene called FCGR3B have an increased risk of developing autoimmune diseases such as systemic lupus erythematosus (SLE).

FCGR3B encodes a protein that is found in neutrophils and eosinophils, which is known to play a role in linking neutrophils to immune complexes, and in clearing immune complexes. The researchers hypothesized that the reduced clearance of immune complexes in individuals with SLE may predispose them to disease in the glomeruli of the kidneys, and at other sites.

A report of the study appears in the May 21 issue of Nature Genetics, in a paper titled "FCGR3B copy number variation is associated with susceptibility to systemic, but not organ-specific, autoimmunity."

"We are now looking to see what the mechanism is for the disease in patients lacking the disease gene," Aitman said. "If we can find the exact mechanism, it may give us clues to help us develop new treatments, or explain why patients develop this disease."

Over the past few years there have been increasing signs that copy number variation - whether extra copies or deleted copies of a gene - is likely to be important in determining someone's risk of common diseases. Last year, for example, an international consortium published a map of copy number variation throughout the genome, which confirmed that there was an average of 70 copy number variations in each DNA sample studied (See BioWorld International, Nov. 29, 2006).

Aitman and his colleagues started out by trying to determine the genetic cause of an autoimmune type of kidney disease called crescentic glomerulonephritis. They were looking for single nucleotide polymorphisms (SNPs) - but then they came across a rat model for the disease and realized that while normal animals had four copies of the FCGR3B gene, those that developed the disease only had three copies.

"We thought this was very unusual, because we were looking for SNPs, but in these animals, a whole copy of the gene was deleted. We wondered whether the same was true in human kidney disease," Aitman said.

As the study reported in Nature Genetics confirmed, researchers found that their hunch was correct: many people with SLE who had kidney disease were missing a copy of FCGR3B. People with Wegener's granulomatosis or microscopic polyangiitis, both autoimmune conditions that commonly affect the kidneys, also were statistically significantly more likely to have fewer copies of FCGR3B than normal healthy controls. Aitman's team also has identified 25 people out of more than 1,200 with autoimmune diseases, who have no copies of FCGR3B (2 percent), compared to 1 out of 862 controls (0.1 percent).

"We now want to find out whether the individuals who are completely lacking this gene have a different pattern of disease," Aitman said. "We are going to try to find out if they respond better to certain treatments than those with these diseases who have the normal number of genes, and we hope to find the exact mechanism that causes the disease."

He concluded: "We can now see that structural variations in the genome, instead of just being in the form of single-letter changes in the genetic code, may encompass maybe 1,000 to 1 million extra or missing letters. The challenge now is to find out how these large variations influence someone's risk of a range of common diseases."

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