http://rdf.disgenet.org/resource/nanopub/NP377407.RAxSuTHJjwD-PcaNjEh21PiqNQqoK8vxj2tgv-Sw4fNN8
type: Nanopublication
created: 2015-08-25T14:41:18+02:00
rights: http://opendatacommons.org/licenses/odbl/1.0/
rights holder: IBIGroup
subject: SIO_000983
used data: disgenetv3.0rdf
authored by: http://orcid.org/0000-0001-5999-6269
authored by: http://orcid.org/0000-0002-7534-7661
authored by: 0000-0002-9383-528X
authored by: http://orcid.org/0000-0003-0169-8159
authored by: http://orcid.org/0000-0003-1244-7654
created by: http://orcid.org/0000-0003-0169-8159
version: v3.0.0.0

http://rdf.disgenet.org/resource/nanopub/NP377407.RAxSuTHJjwD-PcaNjEh21PiqNQqoK8vxj2tgv-Sw4fNN8130_assertion
type: Assertion
description: [Logistic regression analysis of genotypes obtained via Illumina GoldenGate and Sequenom iPlex technologies revealed the following age- and study-adjusted associations: EPHX1 rs1051740 with increased serous ovarian cancer risk [per-allele odds ratio (OR) 1.17, 95% confidence interval (95% CI) 1.04-1.32, P = 0.01), ADH4 r1042364 with decreased ovarian cancer risk (OR 0.90, 95% CI: 0.81-1.00, P = 0.05), and NQO1 rs291766 with increased ovarian cancer risk (OR 1.11, 95% CI: 1.00-1.23, P = 0.04).]. Sentence from MEDLINE/PubMed, a database of the U.S. National Library of Medicine.
evidence: DisGeNET evidence - LITERATURE
SIO_000772: http://identifiers.org/pubmed/21480392
was generated by: ECO_0000203

befree-20150227
imported on: 2015-02-27

DisGeNET evidence - LITERATURE
type: ECO_0000212
comment: Gene-disease associations inferred from text-mining the literature.

disgenetv3.0rdf
version: v3.0.0