267 Spanish Exomes Reveal Population-Specific Differences in Disease-Related Genetic Variation

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Dokumenter

  • Fulltext

    Forlagets udgivne version, 497 KB, PDF-dokument

  • Joaquín Dopazo
  • Alicia Amadoz
  • Marta Bleda
  • Luz Garcia-Alonso
  • Alejandro Alemán
  • Francisco García-García
  • Josephine T. Daub
  • Gerard Muntané
  • Antonio Rueda
  • Alicia Vela-Boza
  • Francisco J. López-Domingo
  • Javier P. Florido
  • Pablo Arce
  • Macarena Ruiz-Ferrer
  • Cristina Méndez-Vidal
  • Todd E. Arnold
  • Olivia Spleiss
  • Miguel Alvarez-Tejado
  • Arcadi Navarro
  • Shomi S. Bhattacharya
  • Salud Borrego
  • Javier Santoyo-López
  • Guillermo Antiñolo

Recent results from large-scale genomic projects suggest that allele frequencies, which are highly relevant for medical purposes, differ considerably across different populations. The need for a detailed catalog of local variability motivated the whole-exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population. Like in other studies, a considerable number of rare variants were found (almost one-third of the described variants). There were also relevant differences in allelic frequencies in polymorphic variants, including ∼10,000 polymorphisms private to the Spanish population. The allelic frequencies of variants conferring susceptibility to complex diseases (including cancer, schizophrenia, Alzheimer disease, type 2 diabetes, and other pathologies) were overall similar to those of other populations. However, the trend is the opposite for variants linked to Mendelian and rare diseases (including several retinal degenerative dystrophies and cardiomyopathies) that show marked frequency differences between populations. Interestingly, a correspondence between differences in allelic frequencies and disease prevalence was found, highlighting the relevance of frequency differences in disease risk. These differences are also observed in variants that disrupt known drug binding sites, suggesting an important role for local variability in population-specific drug resistances or adverse effects. We have made the Spanish population variant server web page that contains population frequency information for the complete list of 170,888 variant positions we found publicly available (http://spv.babelomics.org/), We show that it if fundamental to determine population-specific variant frequencies to distinguish real disease associations from population-specific polymorphisms.

OriginalsprogEngelsk
TidsskriftMolecular Biology and Evolution
Vol/bind33
Udgave nummer5
Sider (fra-til)1205-1218
Antal sider14
ISSN0737-4038
DOI
StatusUdgivet - 2016
Eksternt udgivetJa

Bibliografisk note

Funding Information:
The MGP is a joint initiative between the Consejeria de Salud de la Junta de Andalucia and Roche, supported by the Programa Nacional de Proyectos de investigacion Aplicada, I+D+i 2008, Subprograma de actuaciones Cientificas y Tecnologicas en Parques Cientificos y Tecnologicos (ACTEPARQ 2009), and European Regional Development Funds (ERDF). This work is also supported by grants BIO2014-57291-R and BFU2012-38236 from the Spanish Ministry of Economy and Competitiveness and Plataforma de Recursos Biomoleculares y Bioinformaticos PT 13/0001/0030 from the ISCIII, both cofunded with ERDF; grants PI1102923 and PI1001290 from the Fondo de Investigacion Sanitaria, PROMETEOII/2014/025 from the Generalitat Valenciana (GVA-FEDER), FP7-PEOPLE-2012-ITN MLPM2012 318861 from the EU FP7, Fundacio laMarato TV3 [20133134], and by Direccio General de Recerca, Generalitat de Catalunya (2014SGR1311). The CIBER de Enfermedades Raras is an Instituto de Salud Carlos III initiative. The authors express their gratitude to Carlos Freixas from Roche Diagnostics S.L., for his constant support of the MGP as well as to Javier Escalante, Anabel Lopez, and Federica Trombetta for their excellent work in the laboratory

Publisher Copyright:
© 2016 The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

ID: 327400271