Prostate Cancer (PCa) Risk Variants and Risk of Fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
EUROPEAN UROLOGY
Authors: Shui, Irene M.; Lindstroem, Sara; Kibel, Adam S.; Berndt, Sonja I.; Campa, Daniele; Gerke, Travis; Penney, Kathryn L.; Albanes, Demetrius; Berg, Christine; Bueno-de-Mesquita, H. Bas; Chanock, Stephen; Crawford, E. David; Diver, W. Ryan; Gapstur, Susan M.; Gaziano, J. Michael; Giles, Graham G.; Henderson, Brian; Hoover, Robert; Johansson, Mattias; Le Marchand, Loic; Ma, Jing; Navarro, Carmen; Overvad, Kim; Schumacher, Fredrick R.; Severi, Gianluca; Siddiq, Afshan; Stampfer, Meir; Stevens, Victoria L.; Travis, Ruth C.; Trichopoulos, Dimitrios; Vineis, Paolo; Mucci, Lorelei A.; Yeager, Meredith; Giovannucci, Edward; Kraft, Peter
Abstract
Background: Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM). Objective: To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM. Design, setting, and participants: We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred. Outcome measurements and statistical analysis: The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls. Results and limitations: Among the cases, we found that 8 of the 47 SNPs were significantly associated (p < 0.05) with time to PCSM. The risk allele of rs11672691 (intergenic) was associated with an increased risk for PCSM, while 7 SNPs had risk alleles inversely associated (rs13385191 [C2orf43], rs17021918 [PDLIM5], rs10486567 [JAZF1], rs6465657 [LMTK2], rs7127900 (intergenic), rs2735839 [KLK3], rs10993994 [MSMB], rs13385191 [C2orf43]). In the case-control analysis, 22 SNPs were associated (p < 0.05) with the risk of fatal PCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only. Conclusions: Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa. Patient summary: In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that could aid prediction. (C) 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved.
Interactions between a natural food web, shellfish farming and exotic species: The case of the Bay of Mont Saint Michel (France)
ESTUARINE COASTAL AND SHELF SCIENCE
Authors: Leloup, F. Arbach; Desroy, N.; Le Mao, P.; Pauly, D.; Le Pape, O.
Abstract
To ensure sustainable uses of the coastal zone, an integrated ecosystemic approach and ecosystem models are required to frame ecological processes and evaluate environmental impacts. Here, a mass-balance trophic (Ecopath) model of the Mont Saint Michel Bay (MSMB) was developed, to analyze the bay's functioning as an ecosystem. This bay, intensively exploited by fishing and for shellfish farming, is also suffering from the proliferation of the gastropod Crepidula fornicata, an exotic species. The MSMB model has 18 compartments, from the primary producers to top predators, and emphasizes the large biomass of filter feeders. The model identified the MSMB as a highly productive ecosystem controlled largely from the bottom-up, and strongly impacted by huge biomasses of filter feeders. However, the low transfer efficiency rates imply that a large part of the primary production is not transferred upward to higher trophic levels, but is lost in high hydrodynamic exchanges and in the trophic impasse represented by a large biomass of Crepidula fornicata. (c) 2007 Elsevier Ltd. All rights reserved.