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The Challenges of Genome-Wide Interaction Studies: Lessons to Learn from the Analysis of HDL Blood Levels

Author

Listed:
  • Elisabeth M van Leeuwen
  • Françoise A S Smouter
  • Tony Kam-Thong
  • Nazanin Karbalai
  • Albert V Smith
  • Tamara B Harris
  • Lenore J Launer
  • Colleen M Sitlani
  • Guo Li
  • Jennifer A Brody
  • Joshua C Bis
  • Charles C White
  • Alok Jaiswal
  • Ben A Oostra
  • Albert Hofman
  • Fernando Rivadeneira
  • Andre G Uitterlinden
  • Eric Boerwinkle
  • Christie M Ballantyne
  • Vilmundur Gudnason
  • Bruce M Psaty
  • L Adrienne Cupples
  • Marjo-Riitta Järvelin
  • Samuli Ripatti
  • Aaron Isaacs
  • Bertram Müller-Myhsok
  • Lennart C Karssen
  • Cornelia M van Duijn

Abstract

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value

Suggested Citation

  • Elisabeth M van Leeuwen & Françoise A S Smouter & Tony Kam-Thong & Nazanin Karbalai & Albert V Smith & Tamara B Harris & Lenore J Launer & Colleen M Sitlani & Guo Li & Jennifer A Brody & Joshua C Bis , 2014. "The Challenges of Genome-Wide Interaction Studies: Lessons to Learn from the Analysis of HDL Blood Levels," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-13, October.
    • Handle: RePEc:plo:pone00:0109290
    DOI: 10.1371/journal.pone.0109290
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