Your browser doesn't support javascript.
loading
A panel of 32 AIMs suitable for population stratification correction and global ancestry estimation in Mexican mestizos.
Huerta-Chagoya, Alicia; Moreno-Macías, Hortensia; Fernández-López, Juan Carlos; Ordóñez-Sánchez, María Luisa; Rodríguez-Guillén, Rosario; Contreras, Alejandra; Hidalgo-Miranda, Alfredo; Alfaro-Ruíz, Luis Alberto; Salazar-Fernandez, Edgar Pavel; Moreno-Estrada, Andrés; Aguilar-Salinas, Carlos Alberto; Tusié-Luna, Teresa.
Afiliação
  • Huerta-Chagoya A; CONACYT, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico.
  • Moreno-Macías H; Departamento de Economía, Universidad Autónoma Metropolitana, Ciudad de Mexico, Mexico.
  • Fernández-López JC; Departamento de Genómica Computacional, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico.
  • Ordóñez-Sánchez ML; Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico.
  • Rodríguez-Guillén R; Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico.
  • Contreras A; Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico.
  • Hidalgo-Miranda A; Fox Chase Cancer Center, Philadelphia, USA.
  • Alfaro-Ruíz LA; Laboratorio de Genómica del Cáncer, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico.
  • Salazar-Fernandez EP; Laboratorio de Genómica del Cáncer, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico.
  • Moreno-Estrada A; Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO-UGA), CINVESTAV, Iraputato, Guanajuato, Mexico.
  • Aguilar-Salinas CA; Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO-UGA), CINVESTAV, Iraputato, Guanajuato, Mexico.
  • Tusié-Luna T; Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico.
BMC Genet ; 20(1): 5, 2019 01 08.
Article em En | MEDLINE | ID: mdl-30621578
ABSTRACT

BACKGROUND:

Association studies are useful to unravel the genetic basis of common human diseases. However, the presence of undetected population structure can lead to both false positive results and failures to detect genuine associations. Even when most of the approaches to deal with population stratification require genome-wide data, the use of a well-selected panel of ancestry informative markers (AIMs) may appropriately correct for population stratification. Few panels of AIMs have been developed for Latino populations and most contain a high number of markers (> 100 AIMs). For some association studies such as candidate gene approaches, it may be unfeasible to genotype a numerous set of markers to avoid false positive results. In such cases, methods that use fewer AIMs may be appropriate.

RESULTS:

We validated an accurate and cost-effective panel of AIMs, for use in population stratification correction of association studies and global ancestry estimation in Mexicans, as well as in populations having large proportions of both European and Native American ancestries. Based on genome-wide data from 1953 Mexican individuals, we performed a PCA and SNP weights were calculated to select subsets of unlinked AIMs within percentiles 0.10 and 0.90, ensuring that all chromosomes were represented. Correlations between PC1 calculated using genome-wide data versus each subset of AIMs (16, 32, 48 and 64) were r2 = 0.923, 0.959, 0.972 and 0.978, respectively. When evaluating PCs performance as population stratification adjustment covariates, no correlation was found between P values obtained from uncorrected and genome-wide corrected association analyses (r2 = 0.141), highlighting that population stratification correction is compulsory for association analyses in admixed populations. In contrast, high correlations were found when adjusting for both PC1 and PC2 for either subset of AIMs (r2 > 0.900). After multiple validations, including an independent sample, we selected a minimal panel of 32 AIMs, which are highly informative of the major ancestral components of Mexican mestizos, namely European and Native American ancestries. Finally, the correlation between the global ancestry proportions calculated using genome-wide data and our panel of 32 AIMs was r2 = 0.972.

CONCLUSIONS:

Our panel of 32 AIMs accurately estimated global ancestry and corrected for population stratification in association studies in Mexican individuals.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Grupos Populacionais / População Branca / Genética Populacional Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: Mexico Idioma: En Revista: BMC Genet Assunto da revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: México

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Grupos Populacionais / População Branca / Genética Populacional Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: Mexico Idioma: En Revista: BMC Genet Assunto da revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: México