Monday, October 8, 2012

Genetic profile predicts postradiation erectile dysfunction


Genetic profile predicts postradiation erectile dysfunction

Published on October 1, 2012 at 5:15 PM · No Comments
By Lynda Williams, Senior medwireNews Reporter
Scientists have identified a group of genetic markers that can predict the risk forerectile dysfunction (ED) after radiotherapy for prostate cancer.
The team says that the 12 single nucleotide polymorphisms (SNPs) each gave an odds ratio for ED of between 1.6 and 5.6 in a discovery cohort of 132 men with ED afterbrachytherapy and/or external beam radiotherapy and 103 men without this side effect.
The risk for ED increased significantly with the number of the SNPs carried, by a factor of 2.2 for each additional allele, after adjusting for patient ancestry and clinical factors.
When the pooled SNP profile was applied during treatment planning, alongside other risk factors such as age and treatment, the researchers were able to predict the likelihood of ED after radiotherapy with 84% sensitivity and 75% specificity in a validation cohort of 230 men, 128 of whom developed ED.
"The risk of developing erectile dysfunction after radiation treatment is highly variable, suggesting there may be a genetic component to determining that risk," commented author Barry Rosenstein (Mount Sinai School of Medicine, New York, USA) in a press release.
"Our study confirms that specific markers make certain patients more susceptible to this side effect."
Although none of the SNPs met the strict criteria for genome-wide significance, the researchers believe they may "represent true associations" because of their increased predictive power compared with other types of variable such as age, race, and body mass index.
"Notably, these 12 SNPs lie in or near genes involved in erectile function or other normal cellular functions (adhesion and signaling) rather than DNA damage repair," the team writes in the International Journal of Radiation Oncology Biology Physics.
The researchers suggest that further genetic analysis may lead to the identification of more predictive SNPs or rare variants that directly impact protein expression, modification, or transcription regulation.
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