UMSOM researchers receive $ 5 million federal grant to improve use of genetic risk scores

University of Maryland School of Medicine (UMSOM) researchers received $ 5 million federal grant to pool genomic information from existing and new datasets – primarily in African and African American populations – in order to calculate the risk of developing specific diseases. They will use sophisticated modeling and genetic data sets to calculate risk, known as the polygenic risk score, with an emphasis on studying people of different ancestry.

The grant was awarded to Principal Investigator Sally Adebamowo, MBBS, MSc, ScD, Associate Professor of Epidemiology and Public Health at UMSOM. Dr Adebamowo is also a cancer epidemiology researcher at the University of Maryland Greenebaum Comprehensive Cancer Center. His collaborators at UMSOM are Braxton Mitchell, PhD, professor of medicine, Clement Adebamowo, ScD, professor of epidemiology and public health, and Yuji Zhang, PhD, associate professor of epidemiology and public health.

Some polygenic risk scores have already been developed, but these are largely based on genetic data from European populations. We aim to expand the datasets on which these risk scores are based with this study. The larger the populations you have, the wider the range of allelic data, the more easily these scores can be translated into clinical practice. “

Dr. Sally Adebamowo, Associate Professor of Epidemiology and Public Health, UMSOM

The researchers are part of a new consortium established by the National Human Genome Research Institute (NHGRI), which is part of the NIH, which is funding the five-year grant. The ultimate goal is to identify best practices to ensure that scores accurately predict disease in diverse populations.

“One of our biggest concerns is that the data used to calculate polygenic risk scores does not include a sufficient number of individuals from various populations, which does not effectively predict disease risk in populations. non-European, ”said Teri Manolio, MD, Ph.D., director of the genomic medicine division at NHGRI. “This is an area where the work of the consortium will be critical.”

Polygenic risk scores, often referred to as PRS, are a genetic estimate of a person’s risk for specific diseases. Researchers and clinicians calculate polygenic risk scores by comparing genomic data from people with and without a particular disease.

Bioinformatics analysis is used to identify groups of genomic variants that are found more frequently in people with the disease, and then statistical calculations are used to estimate how a person’s variants affect their risk of getting the disease. .

In recent years, researchers have used large-scale genomic datasets available to develop the ability to calculate polygenic risk scores for many conditions, such as coronary heart disease and diabetes, and to identify those at high risk. . This began to allow clinicians to use polygenic risk scores in combination with a person’s lifestyle and environmental factors to tailor their medical management.

Dr Adebamowo and his colleagues at UMSOM plan to develop a genomic dataset comprising more than 50,000 participants from African, Jamaican and African American populations. This will look for genetic variants involved in cardiometabolic disorders like high blood pressure, diabetes, and heart disease. They also plan to include 100,000 additional participants from other databases to explore genomic and lifestyle factors involved in cervical and breast cancer and the spread of the carcinogenic HPV virus.

“There has long been a recognized need to include more diverse populations in genetic studies, and this new research aims to address this problem,” said E. Albert Reece, MD, PhD, MBA, executive vice president of business Doctors, UM Baltimore; and Distinguished Professor and Dean John Z. and Akiko K. Bowers of the University of Maryland School of Medicine. “The hope is that it will ultimately provide a solid scientific basis for the medical community to implement these scores in their clinical practice.”


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