The complex patterns of genetic ancestry uncovered from genomic data in healthcare systems can provide valuable information about the genetic and environmental factors underlying many common and rare diseases – much more targeted and specific information than those derived from traditional ethnic or racial labels such as Hispanic or Black, according to a team of researchers from Mount Sinai.
In a study in the journal Cell, the team said this information could be used to better understand and predict which populations are more susceptible to certain disorders – including cancers, asthma, diabetes and cardiovascular disease – and to possibly develop early interventions.
“This is the first time that researchers have shown how genetic ancestry data could be used to improve our understanding of disease risk and management at the health system level,” says senior author Eimear Kenny, PhD , professor of medicine and genetics and genomic sciences. at the Icahn School of Medicine at Mount Sinai. “By linking this data directly to health outcomes, we believe we are contributing to an ongoing conversation to move beyond the current role of race and ethnicity in medicine.
The research team drew on Mount Sinai’s BioMe ™ BioBank program, recognized as one of the world’s leading repositories of genomic information for various populations, for their study. Using a machine learning methodology, the scientists identified 17 distinct ethnic communities among the 30,000 participants in the BioMe BioBank. They then linked that data to thousands of health outcomes residing in Mount Sinai’s electronic health records. Among the findings, 25% of BioMe participants had genetic links to populations – such as Ashkenazi and Puerto Rican Jews – that predisposed them to certain genetic diseases.
“Traditional use of demographics by health systems fails to capture the rich ethnic heritage of patients, and therefore all the genetic and environmental factors that can influence disease rates even within a single population.” says Dr. Kenny, founding director of the Mount Sinai Institute for Genomic Health. “Our study used genomic data embedded in health system records to show how patients from different countries in the Americas can have different disease rates. For example, people of Puerto Rican and Mexican descent are generally classified as Hispanic or Latin, but the former population has one of the highest asthma rates in the world, while the latter population has one of the highest. low. “
The Mount Sinai study cited the APOL1 gene, which may confer a significantly higher risk of kidney and cardiovascular disease, as another reason to go beyond the traditional demographic labels used by healthcare systems. The risky variants of APOL1 are most commonly seen in populations of the Americas who share African genetic ancestry. However, there are many populations of African descent around the world who might not self-identify as Africans, and therefore not be aware that they might harbor these risk variants. In addition, this lack of knowledge can lead to an under-representation of these populations in APOL1 research.
“Our study points out that there are limits to the narrow demographic labels used in medicine and research today – and in society at large, for that matter – in attempting to characterize the disease and its risk factors,” says Dr. Kenny. “The types of information that can be derived from the use of biological markers of ancestry, however, convey a much richer and more sophisticated layer of understanding of the risk and burden of disease, which could have enormous implications. for health systems around the world. “