A groundbreaking study expands the understanding of human genetic diversity by including understudied populations, revealing a more complete picture of gene expression patterns across the world.
For decades, the majority of research in human genetics has disproportionately focused on individuals of European ancestry. This systemic bias has limited the accuracy of scientific predictions for people from diverse backgrounds. Now, a team of researchers from Johns Hopkins University has created a comprehensive catalog of human gene expression data, drawing from individuals across the globe. This extensive database, which represents a significant leap forward in genetic research, aims to rectify past inequalities and unlock a deeper understanding of human genetic variation.
The study, published in *Nature*, analyzes gene expressionâthe process by which genes are activated and translated into RNA moleculesâin a diverse cohort of 731 individuals from 26 populations across five continents. The researchers analyzed RNA from these individuals, who were previously part of the 1000 Genomes Project, a collaborative effort to map the genetic makeup of human populations.
"We now have this global view of how gene expression contributes to the world's diversity, the broadest picture to date in populations that have been poorly represented in previous studies," says senior author Rajiv McCoy, a Johns Hopkins geneticist. "We're trying to better understand the connection between variation at the level of our DNA and variation at the level of our traits, which previous genetic studies have looked at but with a really persistent bias that often excludes non-European ancestry populations."
The study reveals that gene expression patterns are often shared between populations, challenging the simplistic notion that our differences are solely defined by geographical, political, or social labels. Importantly, the researchers discovered that most differences in gene expression occur within populations rather than between them, emphasizing the need to investigate variations within diverse groups.
The new dataset provides valuable insights into the relationship between genetic mutations and specific traits and health risks. By analyzing individuals from understudied populations, researchers can identify mutations that might be driving gene expression changes and ultimately contribute to variations in traits or susceptibility to diseases.
Lead author Dylan Taylor, a Johns Hopkins doctoral candidate in biology, emphasizes the importance of inclusivity in genetic research for personalized medicine. "We can't really use these studies in a predictive fashion for personalized medicine equitably unless we have more diverse datasets," Taylor says. "If you try to use results from a study using only European individuals to predict gene expression in individuals from an underrepresented populationâSouth Asians, for exampleâyour results won't necessarily be very reliable."
This groundbreaking research is a significant step towards bridging the gap in understanding human genetic diversity. The inclusion of understudied populations in future genetic research will enable scientists to develop more accurate and equitable health interventions. As Taylor notes, "The field is starting to move in this exciting direction to include diverse individuals in human genetic studies... We are demonstrating we can really do this, and we should, and it's valuable."
