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      Pharmacogenomic Diversity among Brazilians: Influence of Ancestry, Self-Reported Color, and Geographical Origin


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          By virtue of being the product of the genetic admixture of three ancestral roots: Europeans, Africans, and Amerindians, the present-day Brazilian population displays very high levels of genomic diversity, which have important pharmacogenetic/-genomic (PGx) implications. Recognition of this fact has prompted the creation of the Brazilian Pharmacogenomics Network (Refargen), a nationwide consortium of research groups, with the mission to provide leadership in PGx research and education in Brazil, with a population heath impact. Here, we present original data and review published results from a Refargen comprehensive study of the distribution of PGx polymorphisms in a representative cohort of the Brazilian people, comprising 1,034 healthy, unrelated adults, self-identified as white, brown, or black, according to the Color categories adopted by the Brazilian Census. Multinomial log-linear regression analysis was applied to infer the statistical association between allele, genotype, and haplotype distributions among Brazilians (response variables) and self-reported Color, geographical region, and biogeographical ancestry (explanatory variables), whereas Wright’s F ST statistics was used to assess the extent of PGx divergence among different strata of the Brazilian population. Major PGx implications of these findings are: first, extrapolation of data from relatively well-defined ethnic groups is clearly not applicable to the majority of Brazilians; second, the frequency distribution of polymorphisms in several pharmacogenes of clinical relevance (e.g., ABCB1, CYP3A5, CYP2C9, VKORC) varies continuously among Brazilians and is not captured by race/Color self-identification; third, the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of PGx studies in order to avoid spurious conclusions based on improper matching of study cohorts.

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          The Genomic Ancestry of Individuals from Different Geographical Regions of Brazil Is More Uniform Than Expected

          Based on pre-DNA racial/color methodology, clinical and pharmacological trials have traditionally considered the different geographical regions of Brazil as being very heterogeneous. We wished to ascertain how such diversity of regional color categories correlated with ancestry. Using a panel of 40 validated ancestry-informative insertion-deletion DNA polymorphisms we estimated individually the European, African and Amerindian ancestry components of 934 self-categorized White, Brown or Black Brazilians from the four most populous regions of the Country. We unraveled great ancestral diversity between and within the different regions. Especially, color categories in the northern part of Brazil diverged significantly in their ancestry proportions from their counterparts in the southern part of the Country, indicating that diverse regional semantics were being used in the self-classification as White, Brown or Black. To circumvent these regional subjective differences in color perception, we estimated the general ancestry proportions of each of the four regions in a form independent of color considerations. For that, we multiplied the proportions of a given ancestry in a given color category by the official census information about the proportion of that color category in the specific region, to arrive at a “total ancestry” estimate. Once such a calculation was performed, there emerged a much higher level of uniformity than previously expected. In all regions studied, the European ancestry was predominant, with proportions ranging from 60.6% in the Northeast to 77.7% in the South. We propose that the immigration of six million Europeans to Brazil in the 19th and 20th centuries - a phenomenon described and intended as the “whitening of Brazil” - is in large part responsible for dissipating previous ancestry dissimilarities that reflected region-specific population histories. These findings, of both clinical and sociological importance for Brazil, should also be relevant to other countries with ancestrally admixed populations.
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            The genetic structure of human populations studied through short insertion-deletion polymorphisms.

            In a landmark study Rosenberg et al. (2002) analyzed human genome diversity with 377 microsatellites in the HGDP-CEPH Genome Diversity Panel and reported that the populations were structured into five geographical regions: America, Sub-Saharan Africa, East Asia, Oceania and a cluster composed of Europe, the Middle East and Central Asia. They also observed that the within-population component accounted for 93-95%, and that the among-regions portion was only 3.6%, of the total genetic variance. We have also studied the HGDP-CEPH Diversity Panel (1,064 individuals from 52 populations) with a set of 40 biallelic slow-evolving short insertion-deletion polymorphisms (indels). We confirmed the partition of worldwide diversity into five genetic clusters that correspond to major geographic regions. Using the indels we have also disclosed an among-regions component of genetic variance considerably larger (12.1%) than had been estimated using microsatellites. Our study demonstrates that a set of 40 well-chosen biallelic markers is sufficient for the characterization of human population structure at the global level.
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              Self-reported skin color, genomic ancestry and the distribution of GST polymorphisms.

              Skin color and self-reported ethnicity have systematically been used in the pharmacogenetic/-genomic literature as phenotypic proxies for geographical ancestry. Population admixture, however, challenges the appropriateness of this approach. We compared the effectiveness of color-based and marker-based biogeographical ancestry classifications in typing polymorphisms in GSTM1, GSTM3 and GSTT1 in the heterogeneous Brazilian population. Individual DNA from 335 healthy Brazilians was typed for a set of insertion/deletion polymorphisms, previously validated as ancestry informative markers. GSTM1-null and GSTT1-null polymorphisms were detected by multiplex PCR and the GSTM3*B polymorphism by restriction-fragment length polymorphism. Nonlinear logistic regression modeling was developed to describe the association between the GST polymorphisms and ancestry estimated by the ancestry informative markers. Analysis of the ancestry informative markers data with the Structure software revealed the existence of only two significant clusters, one of which was inferred to be an estimate of the African component of ancestry. Nonlinear logistic regression showed that the odds of having the GSTM1-null genotype decreases (P<0.0004, Wald statistics), whereas the odds of having the GSTM3*B allele increases (P<0.0001) with the increase of the African component of ancestry, throughout the range (0.13-0.95) observed in the population sample. The African component of ancestry proportion was not associated with GSTT1-null frequency. Within the self-reported Black and Intermediate groups, there were significant differences in ancestry informative markers between GSTM1-null and non-null individuals, and between carriers and noncarriers of the GSTM3*B allele. Interethnic admixture is a source of cryptic population structure that may lead to spurious genotype-phenotype associations in pharmacogenetic/-genomic studies. Logistic regression modeling of GST polymorphisms shows that admixture must be dealt with as a continuous variable, rather than proportioned in arbitrary subcategories for the convenience of data quantification and analysis.

                Author and article information

                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                06 November 2012
                : 3
                [1] 1Programa de Farmacologia, Coordenação de Pesquisa, Instituto Nacional de Câncer Rio de Janeiro, Brazil
                [2] 2Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais Belo Horizonte, Brazil
                [3] 3Programa de Computação Científica, Fundação Oswaldo Cruz Rio de Janeiro, Brazil
                [4] 4Departamento de Genética, Universidade Federal do Rio Grande do Sul Porto Alegre, Brazil
                Author notes

                Edited by: José A. G. Agúndez, University of Extremadura, Spain

                Reviewed by: Alfonso Dueñas-González, Instituto Nacional de Cancerología, Mexico; Luis Abel Quiñones, University of Chile, Chile

                *Correspondence: Guilherme Suarez-Kurtz, Programa de Farmacologia, Coordenação de Pesquisa, Instituto Nacional de Câncer, Rua André Cavalcanti 37, Rio de Janeiro 22290-290, Brazil. e-mail: kurtz@ 123456inca.gov.br

                This article was submitted to Frontiers in Pharmacogenetics and Pharmacogenomics, a specialty of Frontiers in Pharmacology.

                Copyright © 2012 Suarez-Kurtz, Pena, Struchiner and Hutz.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                Page count
                Figures: 7, Tables: 2, Equations: 0, References: 21, Pages: 7, Words: 4975
                Review Article

                Pharmacology & Pharmaceutical medicine
                population admixture,pharmacogenomic diversity,biogeographical ancestry,brazilian pharmacogenomic network,refargen,fst statistics


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