Â鶹´«Ã½

News — Scientists will be able to pinpoint genetic causes of human diseases faster than ever thanks to a powerful new discovery method unveiled by the Southwest Foundation for Biomedical Research (SFBR) and an international team of researchers. In the Sept. 16 online edition of Nature Genetics, the team describes its method for isolating genes that are self-regulated, meaning they harbor variations that affect their own output, then rapidly narrowing in on genes that likely have a causal effect on a particular disease or disease trait. That approach makes it possible in many studies for researchers to quickly sift through the 25,000 genes in the human genome and see which ones should be the focus of follow-up investigations.

As proof of concept, the group recounts how it used this method to identify a gene " VNN1 " that regulates HDL, the "good" cholesterol, a finding with major implications for heart disease. "We basically just zeroed in on the low hanging fruit," said John Blangero of SFBR, who directed the study. "Instead of looking at all of the genes, we focused on the ones that strongly control their own outputs, and of those genes we then looked at the ones that correlate with disease risks. This approach narrows down the field of genes to target very quickly. While this has been done before on a very limited scale, the sheer power of our AT&T Genomics Computing Center, plus multiple generations of genetic data we have accumulated in the San Antonio Family Heart Study, allowed us to apply this method to a much larger number of study samples. No one has ever applied this method on an epidemiological scale before."

Home to the world's largest parallel computing cluster dedicated to human genetic research, SFBR's AT&T Genomics Computing Center allows the Foundation's scientists to analyze vast amounts of complex genetic data at record speed.

The researchers already are following up with analyses of 60 other genes that appear related to HDL cholesterol, and they are applying the method toward gene discovery for other factors related heart disease, as well as diabetes, obesity, and cystinosis, a rare genetic disorder. They so far have found approximately 100 genes that appear related to diabetes.

"Although in this paper we show how we used the method to find a gene with a big influence on HDL cholesterol, we've begun applying this same approach to every disease that we work on and have obtained outstanding results," said Harald Göring, an SFBR geneticist who is the lead author on the paper. "It's the biggest speed-up in discovery that we've ever experienced."

Genes that exhibit major control of their own outputs are known as "cis-regulated" genes. The output of these self-regulated genes is primarily affected by DNA variations within the genes themselves. This means that, if a cis-regulated gene is found to be correlated with a disease trait, there is a greater likelihood of quickly identifying genetic variations that play a causative role.

"This paper represents a proof of principle for a rapid approach to discover genes directly involved in disease," Blangero said. "The ability to pinpoint the cis-regulated genes not only speeds up the discovery process, but means that you immediately have a good target for drugs to treat those diseases that they influence."

A powerful new method for genetic discovery Blood samples from 1,240 participants in SFBR's ongoing San Antonio Family Heart Study provided the genetic material for the study detailed in Nature Genetics. That study includes approximately 1,400 members of 40 Mexican-American families in the San Antonio area, who are participating in a long-term investigation of the genetic determinants of heart disease, diabetes and obesity.

The researchers in this new investigation focused their analyses on lymphocytes (a subset of white blood cells) that had been obtained from the participants of the family study. Using newly available glass "chips" containing sensors for virtually all of the approximately 25,000 genes in the human genome, they measured the amount of messenger RNA, or mRNA, the output of genes that subsequently gets converted into the proteins that perform the genes' functions in the body.

In the next step, the researchers examined these gene expression patterns to identify the self-regulated genes, which come in slightly different forms that generate more or less messenger RNA.

"The expectation is that the more mRNA present, the more protein that will be made," Göring said.

This was done using extremely computer-intensive statistical analyses that are geared towards locating where in the human genome regulatory DNA variants are located. The investigators found several thousand genes that are likely to harbor DNA variants within themselves that determine how much mRNA and ultimately protein is produced by a gene. This told them which genes were cis-regulated.

Finding an HDL gene

To demonstrate how genetic expression patterns can be used to speed up the search for disease-influencing genes, the researchers chose HDL cholesterol as an example. To identify those genes that influence a person's "good cholesterol" level, they statistically correlated the gene expression profiles with the variable HDL cholesterol levels in the San Antonio Family Heart Study participants.

Of the more than 60 cis-regulated genes they found to have some correlation, one gene clearly stood out. That gene was VNN1, which produces the protein vanin-1. "VNN1 showed by far the strongest correlation with HDL cholesterol. High levels of the mRNA it produces correspond with high levels of HDL in our study participants," said Göring. "In addition, it was one of the genes that was most highly cis-regulated, meaning that sequence variations within the gene itself are highly likely to influence the level of production of vanin-1 and play a causative role in variation of HDL cholesterol levels among individuals."

So the logical next step for the group was to sequence the gene itself, focusing particularly on its "promoter region," the region known to be of the greatest regulatory importance in a gene. Analysis of that sequence revealed 20 variants within VNN1. Statistical investigations revealed that some of these influenced the gene's output and were correlated with HDL levels. Follow-up molecular studies in the laboratory showed one of those variants had a direct functional consequence on the gene's output and likely influences HDL levels.

"So we finished our study with a bit of biology to prove that the statistical associations that we saw also have direct biological validity," said Blangero.

The study was funded by ChemGenex Pharmaceuticals, based in Geelong, Victoria, Australia; the National Institutes of Health; and a philanthropic research grant from Richard and Dianne Azar of San Antonio.

Application to other health issues

"This research method has tremendous potential to accelerate the development of pharmaceutical therapies to target the genetic causes of a whole range of diseases that affect people worldwide," said Greg Collier, CEO of ChemGenex.

Other institutions participating in the study included the Deakin University in Waurn Ponds, Victoria, Australia; the International Diabetes Institute of Caulfield, Victoria, Australia; the University of Western Australia in Crawley, Western Australia; and the Medical College of Wisconsin in Milwaukee.

"This will become a standard approach in epidemiological studies because it gives you such a good overview of what the genes are doing," Blangero said. "It's an absolute gold mine for gene discovery.

About SFBR

Southwest Foundation for Biomedical Research is one of the leading independent biomedical research institutions in the United States, dedicated to advancing human health through innovative biomedical research. It is recognized within scientific and academic communities worldwide for the quality of its basic research into the nature, causes, preventions, and treatments for disease. SFBR's staff of more than 75 doctoral-level scientists conducts nearly 200 major research projects, with marked success in the areas of genetics, neonatal development, metabolic disorders and infectious diseases.