Association of Native American, European, and African Ancestry with CYP450 Pharmacogenetics and Metabolic Phenotypes in Admixed Latin American Populations from Ecuador and Nicaragua

Background/Objectives: Interethnic variability significantly influences drug response, highlighting the importance of assessing genomic ancestry for personalized medicine. Although Latin American populations are highly admixed, they remain underrepresented in pharmacogenetic research. This study examined the association between genomic ancestry, CYP450 genetic variation, and metabolic phenotypes in Ecuadorian (ECU) and Nicaraguan (NIC) populations. Methods: A total of 236 healthy volunteers were studied. Genomic ancestry was evaluated using 83 ancestry-informative markers comprising European (EUR), Native American (NAT), and African (AFR) ancestral components. Genetic variants in CYP2D6, CYP2C9, CYP2C19, CYP3A4, and CYP1A2 were genotyped using TaqMan® assays. Enzyme metabolic capacity was assessed using the CEIBA cocktail-based on five test drugs. and expressed as the logarithm of the metabolic ratio (logMR). Results: The combined genomic ancestry composition was 48.16% NAT, 40.40% EUR and 11.40% AFR. EUR ancestry was associated with CYP2C9*2 (adjusted p- =0.049), CYP2C19*2 (adjusted p = 0.029), and CYP2D6*41 (adjusted p = 0.010) alleles. AFR ancestry was associated with CYP2D6*17 (adjusted p = 0.001) and CYP2D6*4 (adjusted p = 0.132) alleles. Regarding genotype-predicted metabolic phenotypes, EUR ancestry was associated with CYP2C9 gIM (adjusted p = 0.033), whereas AFR ancestry with CYP2D6 gIM (adjusted p = 0.047) and gPM (adjusted p = 0.047). Furthermore, ancestry-related differences in measured metabolic capacity were observed: AFR ancestry was associated with higher logMR values for, CYP1A2, and CYP3A4, while EUR ancestry was associated with higher logMR values for CYP2C9. Overall, substantial overlap in measured metabolic activity (logMR) was observed across genotype-predicted groups for all genes, although some differences were identified. Conclusions: Genomic ancestry was associated with the distribution of CYP450 alleles and genotype-predicted metabolizer categories in Ecuadorian and Nicaraguan populations. However, both ancestry and genotype-based classifications showed limited ability to explain interindividual variability in measured metabolic activity, highlighting the complexity of CYP450 phenotype prediction.

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Journal
Pharmaceuticals
Published
2026-09-10
DOI
https://doi.org/10.3390/ph19091432
Primary Topic
Pharmacogenetics and Drug Metabolism
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article

Association of Native American, European, and African Ancestry with CYP450 Pharmacogenetics and Metabolic Phenotypes in Admixed Latin American Populations from Ecuador and Nicaragua

Enrique Terán, Caíque Manóchio, Adrián LLerena, Fernando de Andrés et al.
Pharmaceuticals
Pharmacogenetics and Drug Metabolism
article

Association of Native American, European, and African Ancestry with CYP450 Pharmacogenetics and Metabolic Phenotypes in Admixed Latin American Populations from Ecuador and Nicaragua

Enrique Terán, Caíque Manóchio, Adrián LLerena, Fernando de Andrés, Fernanda Rodrigues‐Soares, Pedro Dorado, Ronald Ramírez‐Roa, Juan Antonio Villatoro-García, M. Carmen Mata-Martín, Carla González de la Cruz, Eva M. Peñas-Lledó, Catalina Altamirano-Tinoco
article en

Abstract

Background/Objectives: Interethnic variability significantly influences drug response, highlighting the importance of assessing genomic ancestry for personalized medicine. Although Latin American populations are highly admixed, they remain underrepresented in pharmacogenetic research. This study examined the association between genomic ancestry, CYP450 genetic variation, and metabolic phenotypes in Ecuadorian (ECU) and Nicaraguan (NIC) populations. Methods: A total of 236 healthy volunteers were studied. Genomic ancestry was evaluated using 83 ancestry-informative markers comprising European (EUR), Native American (NAT), and African (AFR) ancestral components. Genetic variants in CYP2D6, CYP2C9, CYP2C19, CYP3A4, and CYP1A2 were genotyped using TaqMan® assays. Enzyme metabolic capacity was assessed using the CEIBA cocktail-based on five test drugs. and expressed as the logarithm of the metabolic ratio (logMR). Results: The combined genomic ancestry composition was 48.16% NAT, 40.40% EUR and 11.40% AFR. EUR ancestry was associated with CYP2C9*2 (adjusted p- =0.049), CYP2C19*2 (adjusted p = 0.029), and CYP2D6*41 (adjusted p = 0.010) alleles. AFR ancestry was associated with CYP2D6*17 (adjusted p = 0.001) and CYP2D6*4 (adjusted p = 0.132) alleles. Regarding genotype-predicted metabolic phenotypes, EUR ancestry was associated with CYP2C9 gIM (adjusted p = 0.033), whereas AFR ancestry with CYP2D6 gIM (adjusted p = 0.047) and gPM (adjusted p = 0.047). Furthermore, ancestry-related differences in measured metabolic capacity were observed: AFR ancestry was associated with higher logMR values for, CYP1A2, and CYP3A4, while EUR ancestry was associated with higher logMR values for CYP2C9. Overall, substantial overlap in measured metabolic activity (logMR) was observed across genotype-predicted groups for all genes, although some differences were identified. Conclusions: Genomic ancestry was associated with the distribution of CYP450 alleles and genotype-predicted metabolizer categories in Ecuadorian and Nicaraguan populations. However, both ancestry and genotype-based classifications showed limited ability to explain interindividual variability in measured metabolic activity, highlighting the complexity of CYP450 phenotype prediction.

PharmaceuticalsVol. 19(9)
Universidade Federal de Minas Gerais (BR), Government of Extremadura (ES), Red de Investigación en Sida (ES), Universidade Federal do Triângulo Mineiro (BR), Universidad Nacional Autónoma de Nicaragua-León (NI), Central American University (NI), La Universidad Americana (NI), Centro de Implantología Cirugía Oral y Maxilofacial (ES), Universidad American College (NI), Universidad San Francisco de Quito (EC), Universidad de Extremadura (ES)
Good health and well-being
Openalex Percentile: Top 9%
Pharmacogenetics and Drug Metabolism
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