Precision medicine implementation challenges for APOL1 testing in chronic kidney disease in admixed populations

Chronic Kidney Disease (CKD) is a public health problem that presents genetic and environmental risk factors. Two alleles in the Apolipoprotein L1 (APOL1) gene were associated with chronic kidney disease; these alleles are common in individuals of African ancestry but rare in European descendants. Genomic studies on Afro-Americans have indicated a higher prevalence and severity of chronic kidney disease in people of African ancestry when compared to other ethnic groups. However, estimates in low- and middle-income countries are still limited. Precision medicine approaches could improve clinical outcomes in carriers of risk alleles in the Apolipoprotein L1 gene through early diagnosis and specific therapies. Nevertheless, to enhance the definition of studies on these variants, it would be necessary to include individuals with different ancestry profiles in the sample, such as Latinos, African Americans, and Indigenous peoples. There is evidence that measuring genetic ancestry improves clinical care for admixed people. For chronic kidney disease, this knowledge could help establish public health strategies for monitoring patients and understanding the impact of the Apolipoprotein L1 genetic variants in admixed populations. Therefore, researchers need to develop resources, methodologies, and incentives for vulnerable and disadvantaged communities, to develop and implement precision medicine strategies and contribute to consolidating diversity in science and precision medicine in clinical practice.

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Bibliographic Details
Main Authors: Giudicelli, Giovanna Câmara, Barbosa De Souza, Celia Mariana, Veríssimo Veronese, Francisco, Da Veiga Pereira, Lygia, Hünemeier, Tábita, Sales Luiz Vianna, Fernanda
Other Authors: Hospital de Clínicas de Porto Alegre
Format: artículo biblioteca
Published: Frontiers Media 2022-12-15
Subjects:Population genomic, Research, Genetic diversity, African ancestry, Health inequities, Personalized medicine,
Online Access:http://hdl.handle.net/10261/295574
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