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12 citation(s) found for "Xu, Yanwen".

Abstract 1315: Estimating sex-specific effects of genetic loci associated with glioma risk
Kinnersley, Ben , Wrensch, Margaret , Eckel‐Passow, Jeanette E. , Armstrong, Georgina , Rice, Terri, Wiencke, John, McCoy, Lucie , Hansen, Helen M. , Bernstein, Jonine L. , Claus, Elizabeth B. , Johansen, Christoffer , Lai, Rose , Lau, Ching C. , Merrell, Ryan , Sadetzki, Siegal, Schildkraut, Joellen, Shete, Sanjay , Houlston, Richard S. , Jenkins, Robert B. , Melin, Beatrice , Ostrom, Quinn T. , Armstrong, Georgina , Chen, Yanwen , Wiencke, John K. , Amos, Christopher I. , Il’yasova, Dora , Lachance, Daniel Honore , Olson, Sara H. , Bondy, Melissa L. , Barnholtz‐Sloan, Jill S. , Houlston, Richard S

Cancer Research | July 31, 2017 | Volume: 77 | Issue: 13_Supplement | Pages: 1315-1315

10.1158/1538-7445.am2017-1315 Get It

Abstract BACKGROUND: Incidence of glioma varies significantly by sex, and most glioma histologies occur with greater incidence in males. Previous analyses have examined the impact of estrogen exposure as a risk factor for these tumors, but have found results of varying significance and low effect size. There may be differences in effect of previously discovered risk alleles that contribute to sex differences. METHODS: Using data collected for three previous glioma GWAS in European-ancestry populations (MD Anderson Cancer Center, the San Francisco Adult Glioma Study, and the Glioma International Case Control Study) we assessed sex-specific effects for 14 previously identified and 13 newly identified glioma risk SNPs (27 total) overall and for glioblastoma (GBM) and non-GBM tumors separately. There were 3,892 male cases (59% GBM), 4,522 male controls, 2,500 female cases (52% GBM) and 4,940 female controls. Sex-specific odds ratios (ORM and ORF), 95% confidence intervals (95% CI) and p values (pM and pF) were generated using stratified logistic regression models. Data from each study were analyzed separately and combined using inverse variance weighted meta-analysis. Results were considered statistically significant at p<6.2x10-4. RESULTS: In GBM, rs11979158 (7p11.2, pM=1.01x10-10, ORM=1.43 [95% CI: 1.28-1.59]; pF=3.43x10-3, ORF=1.22 [95% CI: 1.07-1.39]) and rs2562152 (16p13.3, pM=5.59x10-4, ORM=1.23 [95% CI: 1.09-1.39]; pF=1.22x10-1, ORF=1.12 [95% CI: 0.97-1.29]) had significant effect in males only. In non-GBM gliomas, rs12076373 (1q44, pM=3.56x10-7, ORM=1.41, 95% CI: 1.23-1.61; pF=1.76x10-2, ORF=1.20, 95% CI: 1.03-1.38), rs11979158 (7p11.2, pM=1.77x10-5, ORM=1.32 [95% CI: 1.16-1.49]; pF=2.73x10-1, ORF=1.08 [95% CI: 0.94-1.24]), and rs3751667 (16p13.3, pM=9.44x10-7, ORM=1.30 [95% CI: 1.17-1.44]; pF=5.18x10-2, ORF=1.13 [95% CI: 1.00-1.28]) had significant effect in males only. Effect size for rs55705857 (8q24.21) varied significantly by sex, with ORM=2.63 (95% CI: 2.24-3.09, pM=4.42x10-32), as compared to ORF=3.95 (95% CI: 3.28-4.76, pF=1.82x10-47). A sensitivity analysis was performed due to allele frequency heterogeneity by study and results did not change. CONCLUSIONS: Sex differences and other demographic differences in cancer susceptibility can provide important clues to etiology, and these differences can be leveraged for discovery in genetic association studies. Significant differences in effect size may suggest variation in genetic effect of risk alleles or in unidentified risk factors that vary in prevalence or effect by sex. There may also be differences in the distribution of molecular subtypes within each histology by sex. Further investigation using an agnostic approach may further elucidate the relationship between effect of risk alleles and sex. Citation Format: Quinn T. Ostrom, Ben Kinnersley, Margaret Wrensch, Jeanette E. Eckel-Passow, Georgina Armstrong, Terri Rice, Yanwen Chen, John Wiencke, Lucie McCoy, Helen Hansen, Christopher Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel Lachance, Rose Lai, Ching C. Lau, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa Bondy, Jill S. Barnholtz-Sloan. Estimating sex-specific effects of genetic loci associated with glioma risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1315. doi:10.1158/1538-7445.AM2017-1315
Variation in Age at Cancer Diagnosis in Familial versus Nonfamilial Barrett's Esophagus
Chak, Amitabh , Vengoechea, Jaime , Canto, Marcia I., Elston, Robert C. , Falk, Gary W. , Guda, Kishore , Kinnard, Margaret, Markowitz, Sanford D. , Mittal, Sumeet K. , Prasad, Ganapathy A., Shaheen, Nicholas J. , Barnholtz‐Sloan, Jill S. , Chen, Yanwen , Grady, William M. , Willis, Joseph , Barnholtz-Sloan, Jill S

Cancer Epidemiology, Biomarkers & Prevention | February 7, 2012 | Volume: 21 | Issue: 2 | Pages: 376-383

10.1158/1055-9965.epi-11-0927 | PMID 22178570 Get It

Abstract Background: Genetic influences may be discerned in families that have multiple affected members and may manifest as an earlier age of cancer diagnosis. In this study, we determine whether cancers develop at an earlier age in multiplex Familial Barrett's Esophagus (FBE) kindreds, defined by 3 or more members affected by Barrett's esophagus (BE) or esophageal adenocarcinoma (EAC). Methods: Information on BE/EAC risk factors and family history was collected from probands at eight tertiary care academic hospitals. Age of cancer diagnosis and other risk factors were compared between nonfamilial (no affected relatives), duplex (two affected relatives), and multiplex (three or more affected relatives) FBE kindreds. Results: The study included 830 nonfamilial, 274 duplex, and 41 multiplex FBE kindreds with 274, 133, and 43 EAC and 566, 288, and 103 BE cases, respectively. Multivariable mixed models adjusting for familial correlations showed that multiplex kindreds were associated with a younger age of cancer diagnosis (P = 0.0186). Median age of cancer diagnosis was significantly younger in multiplex compared with duplex and nonfamilial kindreds (57 vs. 62 vs. 63 years, respectively, P = 0.0448). Mean body mass index was significantly lower in multiplex kindreds (P = 0.0033), as was smoking (P < 0.0001), and reported regurgitation (P = 0.0014). Conclusions: Members of multiplex FBE kindreds develop EAC at an earlier age compared with nonfamilial EAC cases. Multiplex kindreds do not have a higher proportion of common risk factors for EAC, suggesting that this aggregation might be related to a genetic factor. Impact: These findings indicate that efforts to identify susceptibility genes for BE and EAC will need to focus on multiplex kindreds. Cancer Epidemiol Biomarkers Prev; 21(2); 376–83. ©2011 AACR.