Sifting through the 25,000 genes that make up the human genome to find the causes of disease may take a lot less time now, thanks to a new approach described Sunday in the online edition of the journal Nature Genetics. The technique applies the latest computer technology to a mountain of genetic data amassed over the past 25 years. But rather than focusing on the genes themselves, researchers are turning their attention to a new type of code: the human transcriptome.
It's been three years since the Human Genome Project was completed, ushering in a new era of science and medicine along the way. But sorting out which genetic variants aid, abet or outright cause which diseases has proven cumbersome and slow. As scientists have discovered, however, health and disease come down to more than just DNA. How frequently each gene is translated into a protein—a.k.a. its expression level—is just as important, if not more so.
"Looking one step down the line at the immediate output of genes has proven much more efficient than combing through the genome itself," says the study's lead author John Blangero, a scientist at the Southwest Foundation for Biomedical Research in San Antonio, Texas. That immediate output is an RNA transcript, a molecule that translates each gene into a different protein. By measuring how much RNA a gene produces, researchers can determine how active that gene is. The RNA output of all genes taken together is referred to as the human transcriptome.
In the current study, Blangero and his colleagues, using blood samples from 1,240 people, matched the level of high-density lipoprotein (HDL, the good cholesterol) against transcriptomes. People with high levels of HDL, which is known to protect against heart disease, also had high expression levels of the gene called VNN1. People with low HDL had low expression levels of VNN1 and a higher incidence of arteriosclerosis. The clear implication: VNN1 plays a role in HDL levels and heart disease.
"Right now we aren't saying that transcriptional analysis is the answer to everything," says Blangero. "This is essentially a discovery tool that will give us a much better idea of where to focus our attention." Still, Blangero and his colleagues hope that their technique will yield genetic suspects for a variety of unsolved cases. "We've been applying this technique to every disease that we work on now," Blangero says. "We're like kids in a candy store."