Affiliations 

  • 1 University of California, Davis, Davis, United States
  • 2 University of California, Davis, Davis, CA, United States
  • 3 University of California, San Francisco, San Francisco, California, United States
  • 4 Instituto Nacional de Enfermedades Neoplásicas, Lima, Lima, Peru
  • 5 Instituto Nacional de Enfermedades Neoplásicas, Lima, lima, Peru
  • 6 Instituto Nacional de Enfermedades Neoplasicas, Lima, Lima, Peru
  • 7 Instituto Nacional de Enfermedades Neoplasicas, LIMA, LIMA, Peru
  • 8 Universidad de San Martin de Porres, Lima, Peru
  • 9 Harvard School of Public Health, Boston, MA, United States
  • 10 Harvard T. H. Chan School of Public Health, Boston, MA, United States
  • 11 University of California, Davis, Davis, California, United States
  • 12 University of Tolima, Ibague, Tolima, Colombia
  • 13 Dinamica, Colombia
  • 14 Sura, Medellin, Colombia
  • 15 Universidad del Tolima, Ibague, Colombia
  • 16 Instituto Mexicano del Seguro Social, Mèxico, Ciudad de Mexico, Mexico
  • 17 Instituto Mexicano del Seguro Social, Ciudad de México, Mexico City, Mexico
  • 18 University of Nottingham Malaysia Campus, Semenyih, Selangor, Malaysia
  • 19 Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
  • 20 Cancer Research Malaysia, Subang Jaya, Malaysia
  • 21 Stanford University, Palo Alto, CA, United States
  • 22 University of Southern California, Los Angeles, United States
  • 23 University of Southern California, Los Angeles, CA, United States
  • 24 National Institute of Public Health, Cuernavaca, Morelos, Mexico
  • 25 Kaiser Permanente, Pleasanton, CA, United States
  • 26 City of Hope, Duarte, California, United States
  • 27 University of California, San Francisco, San Francisco, CA, United States
PMID: 39625644 DOI: 10.1158/1055-9965.EPI-24-1247

Abstract

BACKGROUND: A substantial portion of the genetic predisposition for breast cancer is explained by multiple common genetic variants of relatively small effect. A subset of these variants, which have been identified mostly in individuals of European and Asian ancestry, have been combined to construct a polygenic risk score (PRS) to predict breast cancer risk, but the prediction accuracy of existing PRSs in Hispanic/Latinx individuals (H/L) remain relatively low. We assessed the performance of several existing PRS panels with and without addition of H/L specific variants among self-reported H/L women.

METHODS: PRS performance was evaluated using multivariable logistic regression and the area under the receiver operating characteristic curve (AUC).

RESULTS: Both European and Asian PRSs performed worse in H/L samples compared to original reports. The best European PRS performed better than the best Asian PRS in pooled H/L samples. European PRSs had decreased performance with increasing Indigenous American (IA) ancestry while Asian PRSs had increased performance with increasing IA ancestry. The addition of 2 H/L SNPs increased performance for all PRSs, most notably in the samples with high IA ancestry and did not impact the performance of PRSs in individuals with lower IA ancestry.

CONCLUSIONS: A single PRS that incorporates risk variants relevant to the multiple ancestral components of individuals from Latin America, instead of a set of ancestry specific panels, could be used in clinical practice.

IMPACT: Results highlight the importance of population-specific discovery and suggest a straightforward approach to integrate ancestry specific variants into PRS for clinical application.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.