Science
UCLA researchers analyze data from 94,000 people and identify association with PTPRU gene Differences in drug response by race confirmed, bringing era of precision medicine closer


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A research team at UCLA Health has identified genetic clues that could predict the effectiveness of GLP-1–class obesity medications, opening a new chapter in personalized obesity treatment.
According to Chinese biotechnology publication BioOn on the 8th, the team published the findings in the international journal Cell. The study analyzed genetic data and electronic health records (EHRs) from 93,936 people enrolled in the UCLA ATLAS Community Health Initiative biobank.
The analysis found that weight-loss response to the GLP-1–class drug semaglutide was genetically associated with a specific gene called PTPRU. The finding represents the first study to identify a relationship between the effects of GLP-1 medications and a specific gene.
The study is particularly significant because it was based on a large, racially diverse population. Daniel Geschwind, UCLA’s senior associate dean for precision medicine and the study’s lead investigator, emphasized, "Because ATLAS data represent real-world patient populations, these findings can be directly applied to populations that have historically been underrepresented in medicine."
The ATLAS biobank reflects the population of Los Angeles County, one of the most racially diverse regions in the world. Unlike existing databases that have been disproportionately focused on people of European ancestry, the research team analyzed data from 36 detailed racial and ethnic groups, including Armenian, Filipino and Mexican American populations.
Through this analysis, the team identified multiple new gene-disease associations within specific racial groups, including an association between the ANKZF1 gene and peripheral vascular disease among people of African ancestry and a relationship between the EPG5 gene and cholesterol levels among Ashkenazi Jews.
Dr. Geschwind said, "This study demonstrates how important genetic information from diverse patient populations is for understanding the genetic basis of disease and treatment response," adding, "We are conducting pilot studies so that the findings can be applied in actual clinical settings."

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