title: Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Hagedorn Research Institute, Gentofte, Denmark. kabs@hagedorn.dk
authors.forename: Karina
authors.initials: K
authors.lastname: Banasik
authors.forename: Johanne M
authors.initials: JM
authors.lastname: Justesen
authors.forename: Malene
authors.initials: M
authors.lastname: Hornbak
authors.forename: Nikolaj T
authors.initials: NT
authors.lastname: Krarup
authors.forename: Anette P
authors.initials: AP
authors.lastname: Gjesing
authors.forename: Camilla H
authors.initials: CH
authors.lastname: Sandholt
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Jensen
authors.forename: Niels
authors.initials: N
authors.lastname: Grarup
authors.forename: Asa
authors.initials: A
authors.lastname: Andersson
authors.forename: Torben
authors.initials: T
authors.lastname: Jørgensen
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Witte
authors.forename: Annelli
authors.initials: A
authors.lastname: Sandbæk
authors.forename: Torsten
authors.initials: T
authors.lastname: Lauritzen
authors.forename: Bernard
authors.initials: B
authors.lastname: Thorens
authors.forename: Søren
authors.initials: S
authors.lastname: Brunak
authors.forename: Thorkild I A
authors.initials: TI
authors.lastname: Sørensen
authors.forename: Oluf
authors.initials: O
authors.lastname: Pedersen
authors.forename: Torben
authors.initials: T
authors.lastname: Hansen
mesh_terms: D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D003718:Denmark; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D005234:Fatty Liver / Q000235:genetics; D006801:Humans; D024821:Metabolic Syndrome / Q000235:genetics; D008875:Middle Aged; D065626:Non-alcoholic Fatty Liver Disease; D009765:Obesity / Q000235:genetics; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D011485:Protein Binding; D040641:Quantitative Trait Loci