Genomic ancestry and ethnoracial self-classification based on 5,871 community-dwelling Brazilians (The Epigen Initiative)
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Citações na Scopus
107
Tipo de produção
article
Data de publicação
2015
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ISSN da Revista
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Editora
NATURE PUBLISHING GROUP
Autores
LIMA-COSTA, M. Fernanda
RODRIGUES, Laura C.
BARRETO, Mauricio L.
GOUVEIA, Mateus
HORTA, Bernardo L.
MAMBRINI, Juliana
KEHDY, Fernanda S. G.
RODRIGUES-SOARES, Fernanda
VICTORA, Cesar G.
Citação
SCIENTIFIC REPORTS, v.5, article ID 9812, 7p, 2015
Resumo
Brazil never had segregation laws defining membership of an ethnoracial group. Thus, the composition of the Brazilian population is mixed, and its ethnoracial classification is complex. Previous studies showed conflicting results on the correlation between genome ancestry and ethnoracial classification in Brazilians. We used 370,539 Single Nucleotide Polymorphisms to quantify this correlation in 5,851 community-dwelling individuals in the South (Pelotas), Southeast (Bambui) and Northeast ( Salvador) Brazil. European ancestry was predominant in Pelotas and Bambui (median= 85.3% and 83.8%, respectively). African ancestry was highest in Salvador (median = 50.5%). The strength of the association between the phenotype and median proportion of African ancestry varied largely across populations, with pseudo R-2 values of 0.50 in Pelotas, 0.22 in Bambui and 0.13 in Salvador. The continuous proportion of African genomic ancestry showed a significant S-shape positive association with self-reported Blacks in the three sites, and the reverse trend was found for self reported Whites, with most consistent classifications in the extremes of the high and low proportion of African ancestry. In self-classified Mixed individuals, the predicted probability of having African ancestry was bell-shaped. Our results support the view that ethnoracial self-classification is affected by both genome ancestry and non-biological factors.
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Referências
- Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
- Almeida N, 2005, SOC PSYCH PSYCH EPID, V40, P214, DOI 10.1007/s00127-005-0883-4
- Altshuler DM, 2010, NATURE, V467, P52, DOI 10.1038/nature09298
- Barreto ML, 2006, BMC PULM MED, V23, P6
- Cardena MMSG, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0062005
- Chor D, 2013, CAD SAUDE PUBLICA, V29, P1272, DOI 10.1590/S0102-311X2013000700002
- Chor Dóra, 2005, Cad Saude Publica, V21, P1586, DOI 10.1590/S0102-311X2005000500033
- Chor D, 2004, INT J EPIDEMIOL, V33, P100, DOI 10.1093/ije/dyg277
- Durso D. F., 2014, PLOS ONE, V9
- Fagerland M. W., STATA J, V12, P447
- Fernandes F, 1972, NEGRO MUNDO BRANCOS
- Horta BL, 2008, REV SAUDE PUBL, V42, P108
- I.B.G.E. (Instituto Brasileiro de Geografia e Estatistica), ATL CENS DEM 2010
- Koenker R, 2005, QUANTILE REGRESSION
- Li JZ, 2008, SCIENCE, V319, P1100, DOI 10.1126/science.1153717
- Lima-Costa MF, 2011, INT J EPIDEMIOL, V40, P862, DOI 10.1093/ije/dyq143
- Macinko J, 2012, INT J EQUITY HEALTH, V11, DOI 10.1186/1475-9276-11-80
- Magalhaes da Silva T., 2014, EUR J HUM GENET, DOI [10.1038/ejhg.2014.215, DOI 10.1038/EJHG.2014.215]
- Matijasevich A, 2008, AM J PUBLIC HEALTH, V98, P692, DOI 10.2105/AJPH.2006.093492
- McCulloch C. E., 2008, LINEAR MIXED MODELS, V2nd
- Parra FC, 2003, P NATL ACAD SCI USA, V100, P177, DOI 10.1073/pnas.0126614100
- Pena SDJ, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0017063
- Perreira KM, 2014, SOC SCI MED, V116, P241, DOI 10.1016/j.socscimed.2014.05.054
- Ruiz-Linares A, 2014, PLOS GENET, V10, DOI 10.1371/journal.pgen.1004572
- Santos NPC, 2010, HUM MUTAT, V31, P184, DOI 10.1002/humu.21159
- Telles E. E., 2004, RACE ANOTHER AM SIGN
- Thornton T, 2012, AM J HUM GENET, V91, P122, DOI 10.1016/j.ajhg.2012.05.024
- Travassos C, 2011, INT J EQUITY HEALTH, V10, DOI 10.1186/1475-9276-10-35
- Victora CG, 2006, INT J EPIDEMIOL, V35, P237, DOI 10.1093/ije/dyi290