SNP-SNP interactions as risk factors for aggressive prostate

نویسندگان

  • Syed Muhammad Shahid
  • Yog Raj Ahuja
  • Zeenath Jehan
چکیده

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. Venkatesh Vaidyanathan ( ) Corresponding author: [email protected] Competing interests: No competing interests were disclosed. Vaidyanathan V, Naidu V, Karunasinghe N How to cite this article: et al. SNP-SNP interactions as risk factors for aggressive prostate 2017, :621 (doi: ) cancer [version 1; referees: 2 approved] F1000Research 6 10.12688/f1000research.11027.1 © 2017 Vaidyanathan V . This is an open access article distributed under the terms of the , Copyright: et al Creative Commons Attribution Licence which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data associated with the article are available under the terms of the (CC0 1.0 Public domain dedication). Creative Commons Zero "No rights reserved" data waiver The author(s) declared that no grants were involved in supporting this work. Grant information: 03 May 2017, :621 (doi: ) First published: 6 10.12688/f1000research.11027.1 1,2 3 2 4

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تاریخ انتشار 2017