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New Whole Genome Homozygosity Association Method Uncovers Nine Genetic Risk Factors Associated with Schizophrenia
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New Whole Genome Homozygosity Association Method Uncovers Nine Genetic Risk Factors Associated with Schizophrenia

New Whole Genome Homozygosity Association Method Uncovers Nine Genetic Risk Factors Associated with Schizophrenia
News

New Whole Genome Homozygosity Association Method Uncovers Nine Genetic Risk Factors Associated with Schizophrenia

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Golden Helix, Inc. has announced that psychiatric researchers at the Zucker Hillside Hospital, working in collaboration with Golden Helix, Inc., have developed an analytic method, termed whole genome homozygosity association (WGHA).

Powered by Golden Helix’s HelixTree software, WGHA was recently used to identify nine genetic risk factors associated with schizophrenia, a debilitating disease that affects nearly one in every 100 people. Accepted for publication by the journal, Proceedings of the National Academy of Sciences, the study detailing the methods and findings appeared online December 5, 2007.

The past year has seen tremendous advances in medical genetics thanks to a new technology – DNA “microchips” that allow researchers to look at hundreds of thousands of variations across the entire human genome. Typically, these genome-wide association studies (GWAS) have employed a basic analytic approach in which each genetic snippet (called a SNP) is examined one-at-a-time.

While this method has led to several important new genes for illnesses ranging from diabetes to cancer, these studies have not yet exploited the full capabilities of the DNA chip technology and are often hindered by false discoveries resulting from simultaneously performing hundreds of thousands of statistical tests.

WGHA differs from standard analysis, in that it simultaneously looks at genetic information derived from the patient’s mother and father, looking for stretches of DNA (called runs of homozygosity (ROH)) that were inherited identically from both. Looking at ROHs rather than single SNPs exploits the correlation structure of high resolution whole genome data, reducing the number of statistical tests performed and increasing the ability to find rare genetic variants.

“Developing WGHA allowed us to look at patterns that emerged across clusters of SNPs, which moved us beyond our prior research,” said Todd Lencz, PhD, the first author of the study, and an investigator at Zucker Hillside and The Feinstein Institute for Medical Research.

“Even more importantly, the WGHA technique can now be applied to any other illness with a genetic component, potentially locating disease hotspots containing rare variants that might be missed with standard analytic techniques,” Lencz continued.

Validation of the new method is demonstrated in part by the fact that four of the nine ROH regions identified in Dr. Lencz’s study contain genes that have been previously associated with schizophrenia. The remaining regions contain newly discovered genes involved with the structure and survival of neurons. These results may improve the ability to diagnose, and ultimately develop new treatments for specific genetic subtypes of schizophrenia.

“We’re constantly seeking to develop and implement new analytical methods to help our customers get more out of today’s information-rich high resolution arrays,” affirmed Dr. Christophe Lambert, President and CEO of Golden Helix. “This was a great opportunity to work first hand with Dr. Lencz and his team to develop a novel method that will benefit the genetic research community as a whole.”

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