A team from the Icahn School of Medicine at Mount Sinai has developed “BridgePRS,” a new statistical technique to improve disease prediction for non-European individuals, especially those of African descent. This method addresses the limitations of current polygenic risk scores, which are less accurate for non-European ancestries, and marks a significant step towards personalized medicine and reducing healthcare inequities. Credit: SciTechDaily.com
Statistical technique enhances genetic disease prediction in non-European populations, addressing healthcare equity.
A team of scientists from Icahn School of Medicine at Mount Sinai has developed a groundbreaking statistical technique, “BridgePRS,” to enhance disease prediction in people of non-European ancestry, particularly those of African descent. This development represents a substantial step towards reducing healthcare inequities and a future of more personalized and precise medical interventions based on genetic information. Details of their work were published today (December 20, 2023) in Nature Genetics.
Addressing Healthcare Inequity With Enhanced Polygenic Risk Scores
Current polygenic risk scores (PRS), essential tools for predicting disease risk encoded in our DNADNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).” data-gt-translate-attributes=”[{“attribute”:”data-cmtooltip”, “format”:”html”}]” tabindex=”0″ role=”link”>DNA, are predominantly based on genetic data from individuals of European ancestry. This bias makes them less accurate for people of African or Asian ancestry, exacerbating health care inequity among different ethnic groups.
The researchers embarked on this study to improve disease prediction from genetics in non-European individuals. A key goal of personalized medicine is disease prevention, yet current PRS are weak predictors, especially in non-European populations.
BridgePRS improves prediction of African ancestry individuals in the New York BioMe cohort. Credit: Icahn School of Medicine at Mount Sinai
Bridging the Gap in Genetic Disease Prediction
“While we need more genetic data from diverse ancestries, our method combines existing data to help maximize disease prediction across all people,” explained Clive Hoggart, Ph.D., Assistant Professor of Genetics and Genomic Sciences and lead author of the paper. “The biology causing diseases is remarkably similar across ancestries, enabling this advancement.”
“We hope that our method opens up scientific investigation of disease risk in diverse populations worldwide,” stated Paul O’Reilly, Ph.D., Associate Professor of Genetics and Genomic Sciences and senior author. “Disease prevalence and the importance of different biological pathways can vary globally. Understanding these differences is crucial for advancing disease prediction and treatment.”
The field of optimizing disease prediction through PRS Is highly competitive, fostering rapid advancements. Dr. O’Reilly notes, “Our BridgePRS method is particularly promising for predicting disease in individuals of African ancestry, a group with rich genetic diversity that can offer novel insights into human diseases.”
While recognizing the potential of genetics and DNA in predicting future disease and the role of PRS in precision medicine, it’s vital to understand that the biology causing diseases does not differ significantly across ancestry groups or races.
Reference: “BridgePRS leverages shared genetic effects across ancestries to increase polygenic risk score portability” 20 December 2023, Nature Genetics.
DOI: 10.1038/s41588-023-01583-9
The remaining authors, all with Icahn Mount Sinai except where indicated, are Shing Wan Choi, Ph.D. (Regeneron Genetics Center), Judit García-González, Ph.D., Tade Souaiaia, Ph.D. (Suny Downstate Health Sciences), and Michael Preuss, Ph.D.
The study was funded by grant number R01MH122866 from the National Institute of Mental Health and grant number R01HG012773 from the National Human Genome Research Institute.
Source: SciTechDaily
