Ethnic equity in precision medicine
Last Updated on September 21, 2022 by Joseph Gut – thasso
September 21, 2022 – Here, a big bias in genetic research into its applicability on “personalized”, or “precision”, or “theragenomic” medicine is finally addressed and brought forward to all involved in these fields. The problem until now is (and was} that in that in the research in into genetics of diseases mostly people of European ancestry. who only constitute about 16% of the global population but account for nearly 80% of all genome-wide association study participants have been involved. This makes up a big bias when it comes to predict disease risk from genetics in those patients of non-European ancestry.
Researchers have started to address this bias by analyzing genetic ancestry data from a large genomic repository, the UCLA ATLAS Precision Health Biobank, in a highly diverse patient population that’s consistent with the global diversity of Los Angeles, one of the most ethnically diverse cities in the world and an ideal location to pursue personalized and precision medicine for ethnically underrepresented populations.The researchers at the UCLA are beginning to leverage this information to evaluate disease risk, prevention strategies, and treatment options based on a person’s individual genetic makeup, or genotype, and their phenotype, which consists of personal, observable characteristics that come from the interaction between their genotype and the environment.
As mentioned above, people of European ancestry constitute about 16% of the global population, but they account for nearly 80% of all genome-wide association study participants, making existing methods to predict disease risk from genetics vastly inaccurate in those of non-European ancestry, ethnic equity to precision medicine.
When talking about their race and ethnicity, people tend to describe social constructs that include shared values, cultural norms, and behaviors within their subgroups. But the UCLA study looks at genetic ancestry, the history of one individual’s genome, and takes both into consideration. The study open up the opportunity to explore the interplay between the two genetic background (i.e. ethnic backgrounds) and social constructs (i.e., environmental influences). Especially among those individuals who describe themselves as multiracial, genetic ancestry bears little correlation to self-reported race and ethnicity, notes Dr. Pasaniuc, senior author of an article appearing in Genome Medicine that reports early findings from the UCLA ATLAS Community Health Initiative.
So far, the researchers have analyzed the genomes of about 30,000 patients and found a stunning amount of genetic diversity. Ancestries from virtually all continents are represented among UCLA patients, and by extension, the Los Angeles area.
Looking at an even finer scale, the researchers found clusters of patients of Filipino, Korean, Japanese, Persian, Armenian and many other ancestries. Given the fact that California and especially the Los Angeles greater area has been a target for immigration of people from all over the word since very longtime, these findings may not be too surprising but very useful. These ethnically diverse groups are providing for huge amounts of data great value lies in how the data is mined, analyzed, and leveraged to improve research and healthcare, especially for otherwise underrepresented or not even recognized populations, The prevalence of genetic factors that impact disease risk can vary from one ancestry group to another, highlighting the need to take genetic ancestry into account when studying risk and seeking to improve personalized healthcare in an overall population as diverse as that in the Los Angeles community, but, of corse, and perhaps even more so, when applying precision medicine approaches to the individuals of the differing ethnicities in their homelands. Moreover, under the impression of movements of populations as refugees because of wars , oder because of hunger, or because of cultural discriminations, there will be an ever increasing mixing of ethnicities on a given place. This will pose an increasingly extraordinary challenge on adequate clinical precision treatments worldwide. This challenge of course also applies when treating members of indigenous populations, equally all over the world.
Overall, the present ATLAS study collects biological samples from consenting UCLA Health patients, codes the samples, removes any personally identifying information, and provides the samples to approved researchers seeking new ways to prevent, detect and treat health problems. Self-reported demographics, including race and ethnicity designations, come from linked electronic health records. These also are de-personalized for anonymity. The results underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping efforts linked with electronic health records phenotyping where phenotypes are derived from clinical conditions documented in medical records. This approach guarantees eventually the validity of derived genotype-phenotype correlations in true ethnic groups of patients.
We may also proudly say that ethnicity has been and still is an important issue on thasso. Thus, we had several articles on the theme such as “Ethnic disparities in the occurrence of prostate cancer“, on Cancer is not like cancer: Ethnic background matters“, on “Degree of African ancestry may influence gene expression levels“, on “Gene expression and ethnicity: Does it matter?“, on “Mutant genes linked to Parkinson’s disease in some patients of Japanese or European descent“, or on “Are Asians at higher genetic risk of serious adverse events to common medications?“, all of which have to do with ethnicity.
See here a seminar on the many aspects of “Race” (better yet “Ethnicity”) and Precision Medicine: