Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.
Fiche du document
2011
- doi: 10.1371/journal.pone.0016542
- issn: 1932-6203
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0016542
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/21339799
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/1932-6203
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_A59C7FE62C496
info:eu-repo/semantics/openAccess , Copying allowed only for non-profit organizations , https://serval.unil.ch/disclaimer
Sujets proches
Units of inheritance Units of heredityCiter ce document
K. Banasik et al., « Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease. », Serveur académique Lausannois, ID : 10.1371/journal.pone.0016542
Métriques
Partage / Export
Résumé
ObjectiveCandidate 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.Research Design and MethodsBy 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).Results273 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