The Broad Institute of MIT and Harvard has received an award of more than $18 million from the National Heart, Lung and Blood Institute (NHLBI) to support studies aimed at unveiling the genetic variations that underlie common human diseases.
The funds will help build a common data resource for the entire biomedical community that systematically combines genetic analyses of heart, lung, blood and sleep disorders with detailed information about disease characteristics in a range of patient groups.
"The research funded by this award should result in new insights into how genetic variation contributes to health and disease," said Stacey Gabriel, principal investigator of the grant and director of the genetic analysis platform and the National Center for Genotyping and Analysis at the Broad Institute. "We will work together with other members of the candidate gene association resource, or CARE, network to combine new methods for measuring genetic variation with an unprecedented collection of large, well-characterized clinical cohorts."
CARE will survey the DNA of 50,000 individuals, using large-scale genotyping technologies and advanced informatics, to highlight the differences contained in specific genes of interest. These "candidate" genes represent a prioritized list of the likely sources of inherited variation that are most relevant for human disease.
The sheer scale of this project with genetic data collected from as many as 50,000 participants allows for more in-depth analyses of diseases across multiple races and ethnicities," said NHLBI Director Elizabeth G. Nabel, M.D.
While inherited differences within our genes likely play roles in common diseases that affect major organ systems, such as the heart, lung and blood, their contributions appear to be complex and multifaceted, and therefore difficult for scientists to identify. The sequencing of the human genome and recent completion of the Haplotype Map ("HapMap"), a comprehensive catalog of common genetic differences in humans, has laid the groundwork needed to begin this task.
A version of this article appeared in MIT Tech Talk on May 10, 2006 (download PDF).
