Exploring public genomics data for population pharmacogenomics

Lakiotaki, Kleanthi; Kanterakis, Alexandros; Kartsaki, Evgenia; Κάτσιλα, Θεοδώρα; Patrinos, George P.; Potamias, George

doi:10.1371/journal.pone.0182138

Cited by 35 publications

(29 citation statements)

References 48 publications

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“…This locus exhibits significant difference between Africans and non-Africans [ 35 ] which is evident in our gPC plot as well. Lakiotaki et al [ 36 ] identified this variant to belong to the 10 most different ones in worldwide populations. Unlike the previously mentioned locus in VKORC1, the frequency of globally minor allele of rs2242480 in the investigated Roma population (0.3012) is higher than in European populations and corresponds to the frequency range of South Asian populations.…”

Section: Discussionmentioning

confidence: 99%

Characterization of ADME genes variation in Roma and 20 populations worldwide

et al. 2018

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The products of the polymorphic ADME genes are involved in Absorption, Distribution, Metabolism, and Excretion of drugs. The pharmacogenetic data have been studied extensively due to their clinical importance in the appropriate drug prescription, but such data from the isolated populations are rather scarce. We analyzed the distribution of 95 polymorphisms in 31 core ADME genes in 20 populations worldwide and in newly genotyped samples from the Roma (Gypsy) population living in Croatia. Global distribution of ADME core gene loci differentiated three major clusters; (1) African, (2) East Asian, and (3) joint European, South Asian and South American cluster. The SLCO1B3 (rs4149117) and CYP3A4 (rs2242480) genes differentiated at the highest level the African group of populations, while NAT2 gene loci (rs1208, rs1801280, and rs1799929) and VKORC1 (rs9923231) differentiated East Asian populations. The VKORC1 rs9923231 was among the investigated loci the one with the largest global minor allele frequency (MAF) range; its MAF ranged from 0.027 in Nigeria to 0.924 in Han Chinese. The distribution of the investigated gene loci positions Roma population within the joined European and South Asian clusters, suggesting that their ADME gene pool is a combination of ancestral (Indian) and more recent (European) surrounding, as it was already implied by other genetic markers. However, when compared to the populations worldwide, the Croatian Roma have extreme MAF values in 10 out of the 95 investigated ADME core gene loci. Among loci which have extraordinary MAFs in Roma population two have strong proof of clinical importance: rs1799853 (CYP2C9) for warfarin dosage, and rs12248560 (CYP2C19) for clopidogrel dosage, efficacy and toxicity. This finding confirms the importance of taking the Roma as well as the other isolated populations`genetic profiles into account in pharmaco-therapeutic practice.

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Section: Discussionmentioning

confidence: 99%

Characterization of ADME genes variation in Roma and 20 populations worldwide

et al. 2018

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“…However, with decreasing costs of sequencing allowing for studies with larger numbers of participants common variants in non-Caucasian populations and rare variants in all populations are now being identified. [23][24][25][26] Even with robust research findings, clinical translation of basic research findings remains a challenge. For example, despite the growing body of research characterizing PGx variants with clinical value (Table 2) and leading to curation of over 650 medications in PharmGKB, there are currently only approximately 132 medications that have annotated clinical guidelines.…”

Section: Clinical Researchmentioning

confidence: 99%

<p>Concepts Driving Pharmacogenomics Implementation Into Everyday Healthcare</p>

Giri¹,

Moyer²,

Bielinski³

et al. 2019

PGPM

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Pharmacogenomics (PGx) is often promoted as the domain of precision medicine with the greatest potential to readily impact everyday healthcare. Rapid advances in PGx knowledge derived from extensive basic and clinical research along with decreasing costs of laboratory testing have led to an increased interest in PGx and expectations of imminent clinical translation with substantial clinical impact. However, the implementation of PGx into clinical workflows is neither simple nor straightforward, and comprehensive processes and multidisciplinary collaboration are required. Several national and international institutions have pioneered models for implementing clinical PGx, and these initial models have led to a better understanding of unresolved challenges. In this review, we have categorized and explored the most relevant of these challenges to highlight potential gaps and present possible solutions. We describe the ongoing need for basic and clinical research to drive further developments in evidence-based medicine. Integration into daily clinical workflows introduces new challenges requiring innovative solutions; specifically those related to the electronic health record and embedded clinical decision support. We describe advances in PGx testing and result reporting and describe the critical need for increased standardization in these areas across laboratories. We also explore the complexity of the PGx knowledge required for clinical practice and the need for educational strategies to ensure adequate understanding among members of current and future healthcare teams. Finally, we evaluate knowledge obtained from previous implementation efforts and discuss how to best apply these learnings to future projects. Despite these challenges, the future of precision medicine appears promising due to the rapidity of recent advances in the field and current multidisciplinary efforts to effectively translate PGx to everyday clinical practice.

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“…We posit that GA provides a number of advantages over racial/ethnic categories for biomedical research: (i) it can be characterized independently of the social and environmental dimensions of race/ethnicity, (ii) it can be measured objectively and with precision, and (iii) it can be quantified as a continuous variable, as opposed to categorical racial/ethnic labels. Indeed, a number of recent studies have focused on PGx variation among populations defined by GA rather than racial and ethnic groups [25][26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Population structure and pharmacogenomic risk stratification in the United States

2020

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Background Pharmacogenomic (PGx) variants mediate how individuals respond to medication, and response differences among racial/ethnic groups have been attributed to patterns of PGx diversity. We hypothesized that genetic ancestry (GA) would provide higher resolution for stratifying PGx risk, since it serves as a more reliable surrogate for genetic diversity than self-identified race/ethnicity (SIRE), which includes a substantial social component. We analyzed a cohort of 8628 individuals from the United States (US), for whom we had both SIRE information and whole genome genotypes, with a focus on the three largest SIRE groups in the US: White, Black (African-American), and Hispanic (Latino). Our approach to the question of PGx risk stratification entailed the integration of two distinct methodologies: population genetics and evidence-based medicine. This integrated approach allowed us to consider the clinical implications for the observed patterns of PGx variation found within and between population groups. Results Whole genome genotypes were used to characterize individuals’ continental ancestry fractions—European, African, and Native American—and individuals were grouped according to their GA profiles. SIRE and GA groups were found to be highly concordant. Continental ancestry predicts individuals’ SIRE with > 96% accuracy, and accordingly, GA provides only a marginal increase in resolution for PGx risk stratification. In light of the concordance between SIRE and GA, taken together with the fact that information on SIRE is readily available to clinicians, we evaluated PGx variation between SIRE groups to explore the potential clinical utility of race and ethnicity. PGx variants are highly diverged compared to the genomic background; 82 variants show significant frequency differences among SIRE groups, and genome-wide patterns of PGx variation are almost entirely concordant with SIRE. The vast majority of PGx variation is found within rather than between groups, a well-established fact for almost all genetic variants, which is often taken to argue against the clinical utility of population stratification. Nevertheless, analysis of highly differentiated PGx variants illustrates how SIRE partitions PGx variation based on groups’ characteristic ancestry patterns. These cases underscore the extent to which SIRE carries clinically valuable information for stratifying PGx risk among populations, albeit with less utility for predicting individual-level PGx alleles (genotypes), supporting the concept of population pharmacogenomics. Conclusions Perhaps most interestingly, we show that individuals who identify as Black or Hispanic stand to gain far more from the consideration of race/ethnicity in treatment decisions than individuals from the majority White population.

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Exploring public genomics data for population pharmacogenomics

Cited by 35 publications

References 48 publications

Characterization of ADME genes variation in Roma and 20 populations worldwide

Characterization of ADME genes variation in Roma and 20 populations worldwide

<p>Concepts Driving Pharmacogenomics Implementation Into Everyday Healthcare</p>

Population structure and pharmacogenomic risk stratification in the United States

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