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Int J Mol Epidemiol Genet 2010;1(4):320-331.
Original Article
Effect of genome-wide simultaneous hypotheses tests on the discovery rate
Simone P. Pinheiro, Margaret A. Gates, Immaculata DeVivo, Bernard A. Rosner, Shelley S. Tworoger, Linda Titus-Ernstoff,
Susan E. Hankinson, Daniel W. Cramer
Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA;
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Obstetrics and Gynecology Epidemiology
Center, Brigham and Women’s Hospital, Boston, MA, USA; Department of Biostatistics, Harvard School of Public Health,
Boston, MA, USA; Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Received June 6, 2010; accepted July , 2010; available online July , 2010
Abstract: Inflammation and non-steroidal anti-inflammatory agents (NSAIDs) may play important role in ovarian cancer.
However, epidemiologic data are inconsistent, possibly reflecting inter-individual genetic differences affecting the metabolism
of NSAIDs. We examined whether common polymorphisms affecting the metabolism of NSAIDs modify the association
between NSAIDs and ovarian cancer risk. We genotyped 1,353 DNA samples from women who developed ovarian cancer and
1,823 samples from matched controls participating in the New England Case-Control study and the Nurses’ Health Studies.
Conditional logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) associated with regular use of
NSAIDs and with relevant polymorphisms on ovarian cancer risk. Multivariable unconditional logistic regression estimated the
association of NSAID use across stratum of each genotype. Regular use of NSAIDs was not associated with ovarian cancer
risk. Multivariable OR (95% CI) associated with use NSAIDs was 0.85 (95% CI: 0.71-1.02). Associations between NSAID use
and ovarian cancer risk did not differ significantly across strata of genotypes. None of the studied polymorphisms was
associated with ovarian cancer risk. The multivariable ORs (95% CI) associated with CYP2C9 and UGT1A6 variant genotypes
were 0.99 (0.90-1.08) and 0.93 (0.82-1.05), respectively. The multivariable ORs (95% CI) associated with PPAR-γ, COX-2 -765
G>C, and COX-2 Ex10+837T>C polymorphisms were 1.02 (0.87-1.20), 0.87 (0.75-1.00), and 0.97 (0.87-1.09), respectively. In
this relatively large study, we found no convincing evidence supporting an association between NSAIDs use and ovarian cancer
risk. Furthermore, data did not suggest interaction between selected polymorphisms and use of NSAIDs in relation to ovarian
cancer risk. (IJMEG1006003).
Key words: Non-steroidal anti-inflammatory drugs, ovarian cancer, pharmacogenetics, interaction, CYP2C9, UGT1A6, PPAR-γ,
COX, polymorphism
Full Text PDF
Address all correspondence to:
Simone P. Pinheiro, ScD
10903 New Hampshire Avenue, Building
22, Mail Stop 2411, Silver Spring,
MD 20910, USA.
Tel: 301-792-4951, Fax: 301-792-9850
Email: simone.pinheiro@post.harvard.edu
Original Article
Effect of genome-wide simultaneous hypotheses tests on the discovery rate
Simone P. Pinheiro, Margaret A. Gates, Immaculata DeVivo, Bernard A. Rosner, Shelley S. Tworoger, Linda Titus-Ernstoff,
Susan E. Hankinson, Daniel W. Cramer
Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA;
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Obstetrics and Gynecology Epidemiology
Center, Brigham and Women’s Hospital, Boston, MA, USA; Department of Biostatistics, Harvard School of Public Health,
Boston, MA, USA; Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Received June 6, 2010; accepted July , 2010; available online July , 2010
Abstract: Inflammation and non-steroidal anti-inflammatory agents (NSAIDs) may play important role in ovarian cancer.
However, epidemiologic data are inconsistent, possibly reflecting inter-individual genetic differences affecting the metabolism
of NSAIDs. We examined whether common polymorphisms affecting the metabolism of NSAIDs modify the association
between NSAIDs and ovarian cancer risk. We genotyped 1,353 DNA samples from women who developed ovarian cancer and
1,823 samples from matched controls participating in the New England Case-Control study and the Nurses’ Health Studies.
Conditional logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) associated with regular use of
NSAIDs and with relevant polymorphisms on ovarian cancer risk. Multivariable unconditional logistic regression estimated the
association of NSAID use across stratum of each genotype. Regular use of NSAIDs was not associated with ovarian cancer
risk. Multivariable OR (95% CI) associated with use NSAIDs was 0.85 (95% CI: 0.71-1.02). Associations between NSAID use
and ovarian cancer risk did not differ significantly across strata of genotypes. None of the studied polymorphisms was
associated with ovarian cancer risk. The multivariable ORs (95% CI) associated with CYP2C9 and UGT1A6 variant genotypes
were 0.99 (0.90-1.08) and 0.93 (0.82-1.05), respectively. The multivariable ORs (95% CI) associated with PPAR-γ, COX-2 -765
G>C, and COX-2 Ex10+837T>C polymorphisms were 1.02 (0.87-1.20), 0.87 (0.75-1.00), and 0.97 (0.87-1.09), respectively. In
this relatively large study, we found no convincing evidence supporting an association between NSAIDs use and ovarian cancer
risk. Furthermore, data did not suggest interaction between selected polymorphisms and use of NSAIDs in relation to ovarian
cancer risk. (IJMEG1006003).
Key words: Non-steroidal anti-inflammatory drugs, ovarian cancer, pharmacogenetics, interaction, CYP2C9, UGT1A6, PPAR-γ,
COX, polymorphism
Full Text PDF
Address all correspondence to:
Simone P. Pinheiro, ScD
10903 New Hampshire Avenue, Building
22, Mail Stop 2411, Silver Spring,
MD 20910, USA.
Tel: 301-792-4951, Fax: 301-792-9850
Email: simone.pinheiro@post.harvard.edu
