Genetic risk prediction in Hispanics/Latinos: milestones, challenges, and social-ethical considerations

• Published in: Journal of community genetics Vol. 14; no. 6; pp. 543 - 553
• Main Authors: Maldonado, Betzaida L., Piqué, Daniel G., Kaplan, Robert C., Claw, Katrina G., Gignoux, Christopher R.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-12-2023; Springer Nature B.V
• Subjects: Biomedical and Life Sciences; Biomedicine; Epidemiology; Ethics; Gene Function; Gene Therapy; Genetic diversity; Genome-wide association studies; Hispanic Americans; Human Genetics; Minority & ethnic groups; Multiculturalism & pluralism; Precision medicine; Prediction models; Public Health; Review; Polygenic risk scores; Genomic studies; Latin Americans; Latinos; Personalized medicine; Hispanics; Polygenic scores; Health disparities
• ISSN: 1868-310X; 1868-6001; 1868-6001
• DOI: 10.1007/s12687-023-00686-4

Genome-wide association studies (GWAS) have allowed the identification of disease-associated variants, which can be leveraged to build polygenic scores (PGSs). Even though PGSs can be a valuable tool in personalized medicine, their predictive power is limited in populations of non-European ancestry, particularly in admixed populations. Recent efforts have focused on increasing racial and ethnic diversity in GWAS, thus, addressing some of the limitations of genetic risk prediction in these populations. Even with these efforts, few studies focus exclusively on Hispanics/Latinos. Additionally, Hispanic/Latino populations are often considered a single population despite varying admixture proportions between and within ethnic groups, diverse genetic heterogeneity, and demographic history. Combined with highly heterogeneous environmental and socioeconomic exposures, this diversity can reduce the transferability of genetic risk prediction models. Given the recent increase of genomic studies that include Hispanics/Latinos, we review the milestones and efforts that focus on genetic risk prediction, summarize the potential for improving PGS transferability, and highlight the challenges yet to be addressed. Additionally, we summarize social-ethical considerations and provide ideas to promote genetic risk prediction models that can be implemented equitably.