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SNP-SNP interactions as risk factors for aggressive prostate cancer.
Vaidyanathan, Venkatesh; Naidu, Vijay; Karunasinghe, Nishi; Jabed, Anower; Pallati, Radha; Marlow, Gareth; R Ferguson, Lynnette.
Affiliation
  • Vaidyanathan V; Discipline of Nutrition and Dietetics, FM & HS, University of Auckland, Auckland, New Zealand.
  • Naidu V; Auckland Cancer Society Research Centre, Auckland, New Zealand.
  • Karunasinghe N; School of Engineering,Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
  • Jabed A; Auckland Cancer Society Research Centre, Auckland, New Zealand.
  • Pallati R; Department of Molecular Medicine and Pathology, FM & HS, University of Auckland, Auckland, New Zealand.
  • Marlow G; Discipline of Nutrition and Dietetics, FM & HS, University of Auckland, Auckland, New Zealand.
  • R Ferguson L; Experimental Cancer Medicine Centre, Cardiff University, Cardiff, UK.
F1000Res ; 6: 621, 2017.
Article in En | MEDLINE | ID: mdl-28580135
ABSTRACT
Prostate cancer (PCa) is one of the most significant male health concerns worldwide. Single nucleotide polymorphisms (SNPs) are becoming increasingly strong candidate biomarkers for identifying susceptibility to PCa. We identified a number of SNPs reported in genome-wide association analyses (GWAS) as risk factors for aggressive PCa in various European populations, and then defined SNP-SNP interactions, using PLINK software, with nucleic acid samples from a New Zealand cohort. We used this approach to find a gene x environment marker for aggressive PCa, as although statistically gene x environment interactions can be adjusted for, it is highly impossible in practicality, and thus must be incorporated in the search for a reliable biomarker for PCa. We found two intronic SNPs statistically significantly interacting with each other as a risk for aggressive prostate cancer on being compared to healthy controls in a New Zealand population.
Key words

Full text: 1 Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: F1000Res Year: 2017 Type: Article Affiliation country: New Zealand

Full text: 1 Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: F1000Res Year: 2017 Type: Article Affiliation country: New Zealand