MS Gene Tests Inch Toward the Clinic
American Academy of Neurology meeting report
NEW ORLEANS—Efforts to develop gene-based tests that can help patients with multiple sclerosis are beginning to show promise of clinical benefits, according to researchers at the American Academy of Neurology meeting in New Orleans on Tuesday, April 24.
In one study, a combination of six single-nucleotide “letters” in the genetic code predicted patients’ response to glatiramer acetate (Copaxone) with 90% accuracy. These results plant the seeds for a simple, quick genetic test that could help clinicians decide which patients should receive the drug, investigators reported. The team, led by Fabio Macciardi, a geneticist at the University of California, Irvine, analyzed DNA samples taken from 599 patients in the FORTE study—a Phase III trial funded by the pharmaceutical company Teva that examined the effectiveness of high-dose Copaxone. Within that group, the researchers identified patients on the far ends of the drug-response spectrum, whom they called the superresponders and the super-nonresponders.
If the test works in other patient groups, it could provide a powerful clinical tool, says Timothy Vollmer, a neurologist at the University of Colorado School of Medicine in Aurora. Currently, many treatments exist, yet predicting which drug regimen will help any particular patient poses a tremendous challenge (see “Choosing Therapies”).
Using a DNA chip that assesses which nucleotide is present at certain spots in the genome, the researchers found 31 so-called single-nucleotide polymorphisms (SNPs) that showed a statistically significant link to Copaxone response in the extreme-responding patients. Each individual SNP only partially predicted whether the drug would reduce relapse frequency, but the combination of six particular SNPs provided significantly more prognostic oomph. It forecasted—with 90% accuracy—whether the drug would work in both the extreme responders and in the whole group of subjects. (Three of the SNPs correlated with nonresponse, and the other three with response.)
The genes that are presumably affected by the 31 SNPs seem to be involved in two related networks that regulate the immune system, Macciardi says. Only one of the 31 Copaxone response–associated SNPs is among the list of 60-odd genes so far linked with the risk of developing MS (see “Genetic Associations”). The data are preliminary, Macciardi stresses, adding that his team is now validating the test in other groups of patients. (He and his colleagues will present results from one such validation study in a poster on Wednesday.) With an increasing armamentarium of drugs to treat MS entering the clinic, the ability to predict which patients will benefit from which drugs is becoming increasingly important, he says.
Philip De Jager, a geneticist at Harvard Medical School in Boston, who chaired the session in which the data were presented, cautions that it is too soon to tell whether the approach will work. “It’s a reasonable design,” he says, but “many of these things fail” because the results might not extrapolate to other groups of patients.
Meanwhile, researchers at the University of Texas Southwestern Medical Center in Dallas, working with the molecular diagnostics company DioGenix in Gaithersburg, Maryland, are developing a different kind of gene test—one that would help diagnose MS by detecting a gene signature in B cells taken from spinal fluid using next-generation gene-sequencing technology. The approach builds upon recent work that showed an increase in mutation rates of antibody genes in B cells taken from MS patients’ cerebrospinal fluid (Cameron et al., 2009). That initial paper, in combination with efforts by UT Southwestern neurologist Benjamin Greenberg and colleagues to test the diagnostic potential of this gene signature, hints at which patients experiencing a clinically isolated syndrome will go on to develop MS, and might help distinguish patients with MS from those with other central nervous system immune disorders such as neuromyelitis optica, says Greenberg, who presented the findings. Such a technique provides potential value because it can offer a quick and clear-cut diagnosis compared to current methods, which are not always straightforward or robust.
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