The use of individuals' ethno-specific genotypes and admixture measures to further improve predictability of pharmacogenetic-guided models has been addressed to some extent in recent studies. Most of the existing pharmacogenomic (PGx) algorithms and clinical implementation guidelines have been derived from findings in individuals of mostly European descent, and therefore they often refer to variants commonly found in white people only. Multiple ethno-specific variants occurring across several drug-related pharmacogenes are generally overlooked and, consequently, the utility of existing prediction models and guidelines is limited in patients from other ancestries. Healthcare disparities could be exacerbated when such actionable recommendations are not suitable to populations with ethno-geographic particularities, which are often neglected in human genomic studies.
Studies have shown that the performance of PGx guided prescription is lower when the recommendations based on European population studies are applied into populations from different ethnicities. Important pharmacogene variants present in neglected people are, many times, not known and implementation of the current knowledge in these populations could not bring them the expected benefits. Failure to account for ethno-specific genotypes, adjustments by admixture, and a better use of available predictive tools has raised some concerns about expected benefits of genotyping patients to guide pharmacotherapies and improve clinical outcomes, leading to a lack of full endorsement by medical organizations and payers. The more complete the PGx characterization and the more learned the prediction models, the better benefit. Encouraging the study of neglected populations PGx is crucial and needed for the democratic use of this valuable tool.
Taking altogether, the goal of this Research Topic is to discuss ongoing and previous efforts in global pharmacogenomic studies and clinical implementations with a focus on current accomplishments, challenges, lessons learnt, and opportunities for further advances in the field towards a better understanding of the PGx background in neglected populations, especially those that do not have a predominance of European descent or are historically admixed, in order to enhance health equity worldwide.
Manuscripts submitted can be original research articles including surveys, reviews, case studies, short communications, opinions and perspectives related to any one or more of the following themes:
● Current availability and/or limitations of clinical PGx studies aimed at ascertaining the role of ethno-specific genotypes and admixture measures in outcome predictions.
● Challenges to identify and include ethno-specific variants and/or admixture measures in PGx-guided prediction models and guidelines across different ethno-geographic regions or countries.
● Integration of ethno-specific genotypes and admixture measures in actionable recommendations from clinical implementation guidelines and clinical decision support tools.
● Challenges, failures and pitfalls in the application of current PGx clinical guidelines in neglected populations or ethnicities.
● Feasibility and cost-effectiveness of adding ethno-specific genotypes and admixture measures in PGx-guided prediction models and guidelines.
● Applications of machine-learning tools, artificial intelligence and neural networks in pharmacogenomic studies to better predict medical outcomes in understudied populations or ethnicities.
● Efforts to measure admixture and characterize ancestry diversity, population stratification and infer unique genomic structures and haplotype blocks of underrepresented populations or ethnicities.
● Case studies/series to illustrate the impact of novel, missing ethno-specific alleles on PGx predictions.
The use of individuals' ethno-specific genotypes and admixture measures to further improve predictability of pharmacogenetic-guided models has been addressed to some extent in recent studies. Most of the existing pharmacogenomic (PGx) algorithms and clinical implementation guidelines have been derived from findings in individuals of mostly European descent, and therefore they often refer to variants commonly found in white people only. Multiple ethno-specific variants occurring across several drug-related pharmacogenes are generally overlooked and, consequently, the utility of existing prediction models and guidelines is limited in patients from other ancestries. Healthcare disparities could be exacerbated when such actionable recommendations are not suitable to populations with ethno-geographic particularities, which are often neglected in human genomic studies.
Studies have shown that the performance of PGx guided prescription is lower when the recommendations based on European population studies are applied into populations from different ethnicities. Important pharmacogene variants present in neglected people are, many times, not known and implementation of the current knowledge in these populations could not bring them the expected benefits. Failure to account for ethno-specific genotypes, adjustments by admixture, and a better use of available predictive tools has raised some concerns about expected benefits of genotyping patients to guide pharmacotherapies and improve clinical outcomes, leading to a lack of full endorsement by medical organizations and payers. The more complete the PGx characterization and the more learned the prediction models, the better benefit. Encouraging the study of neglected populations PGx is crucial and needed for the democratic use of this valuable tool.
Taking altogether, the goal of this Research Topic is to discuss ongoing and previous efforts in global pharmacogenomic studies and clinical implementations with a focus on current accomplishments, challenges, lessons learnt, and opportunities for further advances in the field towards a better understanding of the PGx background in neglected populations, especially those that do not have a predominance of European descent or are historically admixed, in order to enhance health equity worldwide.
Manuscripts submitted can be original research articles including surveys, reviews, case studies, short communications, opinions and perspectives related to any one or more of the following themes:
● Current availability and/or limitations of clinical PGx studies aimed at ascertaining the role of ethno-specific genotypes and admixture measures in outcome predictions.
● Challenges to identify and include ethno-specific variants and/or admixture measures in PGx-guided prediction models and guidelines across different ethno-geographic regions or countries.
● Integration of ethno-specific genotypes and admixture measures in actionable recommendations from clinical implementation guidelines and clinical decision support tools.
● Challenges, failures and pitfalls in the application of current PGx clinical guidelines in neglected populations or ethnicities.
● Feasibility and cost-effectiveness of adding ethno-specific genotypes and admixture measures in PGx-guided prediction models and guidelines.
● Applications of machine-learning tools, artificial intelligence and neural networks in pharmacogenomic studies to better predict medical outcomes in understudied populations or ethnicities.
● Efforts to measure admixture and characterize ancestry diversity, population stratification and infer unique genomic structures and haplotype blocks of underrepresented populations or ethnicities.
● Case studies/series to illustrate the impact of novel, missing ethno-specific alleles on PGx predictions.