An international research team led by Sarah Tishkoff, the David and Lyn Silfen University Associate Professor at Penn, has released its analysis of 365 African Americans, 203 people from 12 West African populations and 400 Europeans from 42 countries to provide a deeper genome-wide understanding of African and African-American ancestry.
The data revealed a number of critical advances. Tishkoff, a Penn Integrates Knowledge professor with appointments in the Department of Genetics in the School of Medicine and the Department of Biology in the School of Arts and Sciences, found that those who self-identify as African American may be as little as 1 percent West African or as much as 99 percent. Published in the Proceedings of the National Academy of Sciences, the study revealed far more genomic diversity and complexity among African and African-American populations than originally believed. Most importantly, the study revealed that scientists could reliably discern ancestry, identifying African and European ancestry at each region of the genome of participating African Americans.
The study, which may alter the concept of the term “African American,” has potential implications for ancestry reconstructions, could improve the personalization of medical and drug treatments, as well as provide strategies for mapping genetic risk factors for diseases common in African Americans such as hypertension, diabetes and prostate cancer.
“Africa, which is the homeland of all modern humans, contains more than 2,000 ethnolinguistic groups and harbors great genetic and phenotypic diversity; however, little is known about fine-scale population structure at a genome-wide level,” says Tishkoff.
“We were also able to show that there is little genetic differentiation among African Americans in the African portion of their ancestry, reflecting the fact that most African Americans have ancestry from several regions of western Africa. The greatest variation among African Americans is in their proportion of European ancestry, which has important implications for the design of personalized medical treatments.”
Click here to read more about the study.
Originally published on December 21, 2009