Exploring depression treatment response by using polygenic risk scoring across diverse populations

Affiliations

¹ Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: sandra.lapinska@pennmedicine.upenn.edu.
² Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA.
³ Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁴ Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
⁵ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁷ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Data and Technology Advancement Scholar, National Institutes of Health, Office of Data Science Strategy, National Institute of Dental and Craniofacial Research, Bethesda, MD, USA.
⁸ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, USA.
⁹ Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁰ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute of Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: bogdan.pasaniuc@pennmedicine.upenn.edu.

PMID: 40580956
PMCID: PMC12362525 (available on 2026-02-07)
DOI: 10.1016/j.ajhg.2025.06.003

Exploring depression treatment response by using polygenic risk scoring across diverse populations

Sandra Lapinska et al. Am J Hum Genet. 2025.

. 2025 Aug 7;112(8):1877-1891.

doi: 10.1016/j.ajhg.2025.06.003. Epub 2025 Jun 27.

Authors

Affiliations

¹ Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: sandra.lapinska@pennmedicine.upenn.edu.
² Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA.
³ Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁴ Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
⁵ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁷ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Data and Technology Advancement Scholar, National Institutes of Health, Office of Data Science Strategy, National Institute of Dental and Craniofacial Research, Bethesda, MD, USA.
⁸ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, USA.
⁹ Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁰ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute of Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: bogdan.pasaniuc@pennmedicine.upenn.edu.

PMID: 40580956
PMCID: PMC12362525 (available on 2026-02-07)
DOI: 10.1016/j.ajhg.2025.06.003

Abstract

Treatment-resistant depression (TRD), usually defined as limited or no response to at least two antidepressants, occurs in approximately one-third of individuals diagnosed with major depressive disorder (MDD). Studies of individuals of European ancestry highlight a genetic overlap between TRD and MDD. We analyzed two large and diverse biobanks, the UCLA ATLAS Community Health Study (ATLAS) and the All of Us Research Program (AoU), to test for associations between a polygenic score for major depression (MDD-PGS) and TRD. Compared to treatment responders, TRD individuals have higher MDD-PGS across all ancestries. MDD-PGS was significantly associated with response to selective serotonin reuptake inhibitors in individuals of European and Hispanic/Latin American genetic ancestries in both biobanks. In AoU, a decreased MDD-PGS was observed in response to tricyclics or serotonin modulators in individuals of European American ancestry and in response to serotonin and norepinephrine reuptake inhibitors in individuals of African American ancestry. ATLAS found that MDD-PGS showed lower odds of responding to atypical agents than did TRD in MDD-affected individuals belonging to the Hispanic/Latin American group, MDD-PGS was associated with atypical agents. Overall, by leveraging larger sample sizes from two diverse biobanks, we provide new insights into antidepressant response and treatment specificity for MDD in individuals of diverse genetic ancestries.

Keywords: antidepressant response; biobanks; diverse ancestry; electronic health records; genetics; major depressive disorder; polygenic risk scores; treatment-related phenotypes.

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Conflict of interest statement

Declaration of interests The authors declare no competing interests.

References

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Exploring depression treatment response by using polygenic risk scoring across diverse populations

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Exploring depression treatment response by using polygenic risk scoring across diverse populations

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