PLoS ONE (Jan 2011)

Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.

  • Karina Banasik,
  • Johanne M Justesen,
  • Malene Hornbak,
  • Nikolaj T Krarup,
  • Anette P Gjesing,
  • Camilla H Sandholt,
  • Thomas S Jensen,
  • Niels Grarup,
  • Asa Andersson,
  • Torben Jørgensen,
  • Daniel R Witte,
  • Annelli Sandbæk,
  • Torsten Lauritzen,
  • Bernard Thorens,
  • Søren Brunak,
  • Thorkild I A Sørensen,
  • Oluf Pedersen,
  • Torben Hansen

DOI
https://doi.org/10.1371/journal.pone.0016542
Journal volume & issue
Vol. 6, no. 1
p. e16542

Abstract

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Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.By integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.Using a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS.