Evidence map›Paper›PMID 25419701›Full record

ArticlePloS one2014

Exploring the distribution of genetic markers of pharmacogenomics relevance in Brazilian and Mexican populations.

Vania Bonifaz-Peña, Alejandra V Contreras, Claudio Jose Struchiner, Rosimeire A Roela, Tatiane K Furuya-Mazzotti, Roger Chammas, Claudia Rangel-Escareño, Laura Uribe-Figueroa, María José Gómez-Vázquez, Howard L McLeod and 4 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
8.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Frontiers in pharmacology · 2024
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  13. Distribution of a novelFrontiers in genetics · 2023
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  15. Review
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  17. Article
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  20. Influence ofAntimicrobial agents and chemotherapy · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 4 countries.

Vania Bonifaz-PeñaComputational Genomics Consortium, National Institute of Genomic Medicine, Mexico City, Mexico.
Alejandra V ContrerasNutrigenetics and Nutrigenomics Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico.
Claudio Jose StruchinerPrograma de Computação Científica, Fundação Oswaldo Cruz, Rio de Janeiro, Rio de Janeiro, Brazil.
Rosimeire A RoelaDepartamento de Radiologia e Oncologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Tatiane K Furuya-MazzottiDepartamento de Radiologia e Oncologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Roger ChammasDepartamento de Radiologia e Oncologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Claudia Rangel-EscareñoComputational Genomics Consortium, National Institute of Genomic Medicine, Mexico City, Mexico; Institute of Mathematical Sciences, Claremont Graduate University, Claremont, California, United States of America.
Laura Uribe-FigueroaGenotyping and Expression Analysis Unit, National Institute of Genomic Medicine, Mexico City, Mexico.
María José Gómez-VázquezComputational Genomics Consortium, National Institute of Genomic Medicine, Mexico City, Mexico.
Howard L McLeodDeBartolo Family Personalized Medicine Institute, University of South Florida Moffitt Cancer Center, Tampa, Florida, United States of America; Pharmacogenomics Department, Pharmacogenetics for Every Nation Initiative, Tampa, Florida, United States of America.
Alfredo Hidalgo-MirandaCancer Genomics Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico.
Esteban J ParraDepartment of Anthropology, University of Toronto at Mississauga, Mississauga, Ontario, Canada.
Juan Carlos Fernández-LópezComputational Genomics Consortium, National Institute of Genomic Medicine, Mexico City, Mexico.
Guilherme Suarez-KurtzDivisão de Farmacologia, Instituto Nacional de Câncer, Rio de Janeiro, Rio de Janeiro, Brazil.
National Institute of Genomic Medicine · MXUniversidade de São Paulo · BRClaremont Graduate University · USFundação Oswaldo Cruz · BRInstituto Nacional do Câncer · BRMoffitt Cancer Center · USUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies of pharmacogenomics-related traits are increasingly being performed to identify loci that affect either drug response or susceptibility to adverse drug reactions. However, the effect of the polymorphisms can differ in magnitude or be absent depending on the population being assessed. We used the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array to characterize the distribution of polymorphisms of pharmacogenetics and pharmacogenomics (PGx) relevance in two samples from the most populous Latin American countries, Brazil and Mexico. The sample from Brazil included 268 individuals from the southeastern state of Rio de Janeiro, and was stratified into census categories. The sample from Mexico comprised 45 Native American Zapotecas and 224 self-identified Mestizo individuals from 5 states located in geographically distant regions in Mexico. We evaluated the admixture proportions in the Brazilian and Mexican samples using a panel of Ancestry Informative Markers extracted from the DMET array, which was validated with genome-wide data. A substantial variation in ancestral proportions across census categories in Brazil, and geographic regions in Mexico was identified. We evaluated the extent of genetic differentiation (measured as FST values) of the genetic markers of the DMET Plus array between the relevant parental populations. Although the average levels of genetic differentiation are low, there is a long tail of markers showing large frequency differences, including markers located in genes belonging to the Cytochrome P450, Solute Carrier (SLC) and UDP-glucuronyltransferase (UGT) families as well as other genes of PGx relevance such as ABCC8, ADH1A, CHST3, PON1, PPARD, PPARG, and VKORC1. We show how differences in admixture history may have an important impact in the distribution of allele and genotype frequencies at the population level.

Indexed as

HaplotypesPolymorphism, Single NucleotideBrazilCytochrome P-450 CYP2D6Gene FrequencyGenetic LociGenetics, PopulationGenotypeGlucuronosyltransferaseHumansLogistic ModelsMexicoPharmacogeneticsUGT1A1 EnzymeVitamin K Epoxide ReductasesCytochrome P-450 CYP2D6GlucuronosyltransferaseUGT1A1 EnzymeVitamin K Epoxide ReductasesVKORC1 protein, human

Identifiers

PMID25419701
PMCPMC4242606
OpenAlexW2055924792

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.