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JACC: CardioOncology logoLink to JACC: CardioOncology
letter
. 2026 Jul 20;8(4):443–444. doi: 10.1016/j.jaccao.2026.02.005

Polygenic Risk Scores for Cardiovascular Risk Prediction in Breast Cancer Survivors

Implications for Asian Populations

Anirudh Govind ∗
PMCID: PMC13492439  PMID: 42474405

I read with great interest the study by Fiorica et al1 published in JACC: CardioOncology, which comprehensively evaluated 27 polygenic scores (PGS) for cardiometabolic disorder and cardiovascular disease risk in 3,620 breast cancer survivors across multiple ancestral groups. The author identified 23 significant PGS-event associations and demonstrated that cardiotoxic treatments—particularly trastuzumab and hormonal therapy—negatively affected PGS discriminatory performance. I wish to highlight several considerations of particular relevance to Asian populations, a demographic under-represented in this and similar studies.

Although the Pathways cohort included East Asian participants (11.4%), only 2 of the 8 best-performing PGS achieved statistical significance in this subgroup. This is especially pertinent given that South and East Asian women face distinct cardiometabolic risk profiles—including predisposition to type 2 diabetes, hypertension, and dyslipidemia at lower body mass index thresholds—relative to their European counterparts.2 The modest sample size of Asian participants limits generalizability and underscores the urgent need for ancestry-specific PGS development and validation in populations with breast cancer.

The finding that a European-derived PGS for coronary artery disease outperformed a multiancestry PGS in the African subgroup is counterintuitive and warrants cautious interpretation. It raises important questions about whether current multiancestry PGS construction methodologies sufficiently capture the genetic architecture of cardiovascular disease in non-European populations.3 Asian individuals harbor population-specific genetic variants with differing effect sizes that standard PGS frameworks—trained predominantly on European genome-wide association study data—may fail to adequately represent.

The author rightly note that no existing cardiotoxicity prediction model integrates germline genetic data.4 This gap is especially consequential in Asia, where anthracycline- and trastuzumab-based regimens remain the standard of care and where access to serial cardiac imaging for surveillance may be limited. Integrating PGS into clinical risk stratification frameworks—particularly for high-risk Asian patients receiving cardiotoxic therapies—could meaningfully improve survivorship outcomes if validated in prospective Asian cohorts.

I commend Fiorica et al1 for this rigorous and timely contribution to cardio-oncology. Future collaborative efforts to develop de novo PGS in diverse Asian breast cancer cohorts, coupled with prospective validation, are essential to realize the clinical potential of germline-based cardiovascular risk prediction in this growing survivor population.5

Acknowledgments

The author acknowledges the important contributions of Fiorica et al1 in advancing our understanding of cardiovascular risk in breast cancer survivors and thanks the Pathways Heart Study investigators for making their data publicly available.

Footnotes

The author has reported that they have no relationships relevant to the contents of this paper to disclose.

The author attests they are in compliance with human studies committees and animal welfare regulations of the author’s institution and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.

References

  • 1.Fiorica P.N., Zimbalist A., Sheng H., et al. Polygenic risk for cardiometabolic and cardiovascular disease in a multiethnic cohort of breast cancer survivors. JACC CardioOncol. 2026;8:65–76. doi: 10.1016/j.jaccao.2025.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Jeong S.M., Shin D.W., Lee J.E., et al. Cardiometabolic risk factors and cardiovascular disease in Asian cancer survivors. JAMA Netw Open. 2023;6 [Google Scholar]
  • 3.Patel A.P., Wang M., Ruan Y., et al. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease. Nat Med. 2023;29:1793–1803. doi: 10.1038/s41591-023-02429-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Kabore E.G., Macdonald C., Kabore A., et al. Risk prediction models for cardiotoxicity of chemotherapy among patients with breast cancer: a systematic review. JAMA Netw Open. 2023;6 doi: 10.1001/jamanetworkopen.2023.0569. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Truong B., Hull L.E., Ruan Y., et al. Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases. Cell Genom. 2024;4 doi: 10.1016/j.xgen.2024.100523. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from JACC: CardioOncology are provided here courtesy of Elsevier

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