GEN Exclusives

More »

GEN News Highlights

More »
Oct 25, 2007

Gene Logic Discovers Gene Expression Patterns for MS

  • Gene Logic reports that it identified gene expression patterns in white blood cells (WBC) that are statistically associated with multiple sclerosis (MS). The company also found gene patterns linked to two recently approved therapies for MS.

    “These studies lay the foundation for several MS diagnostics that could have significant clinical applications,” notes Larry Tiffany, svp and general manager of genomics at Gene Logic. “A blood-based test that can definitively diagnose MS would clearly be of high value to physicians. A rule-out test demonstrating that a patient does not have MS would also be clinically useful since it eliminates a lengthy, costly, and often invasive medical workup in many patients with symptoms similar to MS.”

    Gene Logic scientists evaluated the WBC samples using gene expression microarrays. They compared untreated MS samples with non-MS samples from nondiseased and other autoimmune disorders as well as MS samples before and after treatment with Biogen Idec’s Avonex® and Teva Pharmaceutical Industries’ Copaxone®. Statistically significant gene expression differences between the groups were determined to identify gene sets.

    Gene Logic says that it is preparing an abstract for submission to a conference in the spring. The company also is using blood samples from the repository of the Accelerated Cure Project for Multiple Sclerosis (ACP) to validate and extend its initial positive findings. ACP has assembled the largest multidisciplinary biobank for MS research, according to the company.



Jobs

GEN Jobs powered by HireLifeScience.com connects you directly to employers in pharma, biotech, and the life sciences. View 40 to 50 fresh job postings daily or search for employment opportunities including those in R&D, clinical research, QA/QC, biomanufacturing, and regulatory affairs.
 Searching...
More »

GEN Poll

More » Poll Results »

Stopping Research Fraud

What is the best approach to curbing scientific misconduct and outright fraud?