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Race and the Personalization of Medicine

One of the current stand-ins for personalized medicine is ethnicity, as people with different ancestral backgrounds can have varying risks for disease. However, a recent study led by researchers at Mount Sinai School of Medicine in New York found that "in the genomic era, conventional racial/ethnic labels are of little value" when translated to the clinic. As they report in PLoS One, the researchers genotyped people from the New York City area who self-identified as African American, European American, or Hispanic. Though they found that the three groups had broad ancestral clustering, there was wide divergence among the Hispanic samples. The researchers say those sub-clusters represent Mexican Americans, people from the Caribbean, and African Americans, and such a wide range of ancestral origins makes "classification by race/ethnicity uninformative," they write. "The great variability in those populations means the genomic risk of something like Body Mass Index may be valid for certain individuals and not others," senior author Erwin Bottinger author tells NPR's Shots blog. "That requires much more detailed analysis of genetic background of local communities."

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