Using gene chips and data mining in MS

Pharmaceutics and computer science researchers at the University at Buffalo have teamed up to develop a method for making use of gene expression microarray data generated using MS patients and controls. These microarrays, which measure expression levels of thousands of genes, generate huge amounts of data that can be difficult to interpret. However, computers can be used to detect patterns that lie within the data. Using data mining technology, these researchers found a cluster of genes that they can use to tell whether a person is a MS patient being treated with interferon-beta, an untreated MS patient, or a healthy control.

There are all kinds of potential applications for these technologies -- determining who has MS and who doesn't, determining who will respond well to a treatment and who won't, predicting the course of disease for someone with MS, etc. One benefit is that you don't really have to understand anything about what the disease is doing to the body in order to use these techniques. That's particularly handy in MS because the disease mechanisms are far from being well understood.