Data for good: $30M award to informatics research center expands possibilities of precision health
The University of Michigan will dramatically boost the amount and type of genetic information stored in its massive TOPMed data center and used by researchers and health care providers around the world looking to genomes to treat disease.
With a $30 million award from the National Heart, Lung, and Blood Institute, the TOPMed Informatics Research Center at U-M will enhance the usability of the vast amounts of genetic and genomic health data, and the demands of storing it, sorting it and making it available for endless possible queries for researchers and health care providers.
The five-year contract is the largest for U-M’s School of Public Health and is another step in advancing the field of precision medicine by multiplying the data available and making it more meaningful.
“This award is a testament to our researchers’ significant impact in harnessing the power of genomic data for groundbreaking scientific discovery and precision health,” said F. DuBois Bowman, dean of the School of Public Health. “This funding will enable our dedicated team to accelerate research that will improve the health and lives of people around the world.”
TOPMed’s data includes nearly 200,000 fully sequenced human genomes, 22 million CT scan images and other health information from 10,000-plus patients whose DNA, RNA and other biological details are made available for researching and treating diseases.
The grant specifically funds the informatics and biostatistics work behind the genomic data that is the backbone of TOPMed, Trans-Omics for Precision Medicine, which formed 10 years ago and is now among the largest such genetic data collections in the world. TOPMed’s data focuses on diseases of the heart, lungs, blood and sleep disorders.
“The main goal is to generate a large volume of genomics data that has sufficient statistical power for scientific discovery, and because the data has been harmonized and cleaned in a manner at a central facility like ours, discovery can happen more easily and quickly,” said Albert Smith, a biostatistics research scientist at the School of Public Health.
Biostatisticians like Smith, who leads the U-M Informatics Research Center, and his team along with partners across the country turn TOPMed’s oceans of initially indecipherable incoming patient information into purposeful, protected data sets for researchers and healthcare providers searching for answers in the similarities, anomalies and genetic patterns that exist in human genomes.
Managing and protecting the ever-growing number of fully sequenced genomes and other genetic information is a mammoth undertaking. The biostatisticians design the system that finds connections and meaning behind the data and make it accessible.
“We apply genomic techniques to analyze different aspects of the molecules in the body in different ways so researchers, physicians and others can try to understand underlying causes of disease in some way,” Smith said. “What we do is aimed at utilizing and refining and improving precision medicine.”
Researchers and physicians can request data to further their knowledge for any number of situations: Why does immunotherapy work for some cancer patients and not others? What is the genetic material in a cancerous tumor? Which genetic mutations are triggering disease?
“Really, what we do is use biostatistics to make sense of this important, complex data that is benefiting people worldwide, and that is the biggest honor,” Smith said. “To be clear, we don’t actually do the phenotype analysis that might point to the likelihood of a heart defect, but within TOPMed is data that can shed light on the genetic factors behind that heart defect.”
TOPMed subcontracts with the University of Texas Houston Health Science Center, Baylor College of Medicine, Stanford University and Vanderbilt Medical Center on the many components that come with adding to and making sense of the large batches of patient data submitted regularly by institutions conducting research studies and cohorts. A vital part of TOPMed is offering a diverse patient and genomic data.
“From its beginning, TOPMed has emphasized diversity in the samples,” Smith said. “The TOPMed program is designed to capture aspects of diversity that other studies have been unable to do. It still remains a challenge to make sure ethnic diversity is captured, but it is a hallmark of TOPMed.”
Ideally in the future, Smith said, TOPMed and similar programs such as All of Us and the U.K. Biobank will link their data and systems.