Abstract Many germline genetic variants have been found to be associated with susceptibility to epithelial ovarian cancer (EOC), but currently few associations have been identified for EOC outcomes such as overall survival. In the absence of evidence for common germline markers, it is possible that rare variants not captured in GWAS arrays may be associated with overall survival. We hypothesize that rare variants, either individually or combined across a gene, may be associated with overall survival in EOC. We utilized data from two genotyping projects of the Ovarian Cancer Association Consortium (OCAC) that used commercial exome-based arrays. The primary sample, genotyped on the Affymetrix Axiom Exome Array at 227,892 standard and custom variants, consisted of 14 independent EOC studies (4293 cases; 2257 deaths). The secondary sample, genotyped on the Illumina Infinium HumanExome BeadChip at 114,620 variants, consisted of six additional EOC studies (1744 cases; 1027 deaths). Both sets were analyzed using Cox proportional hazards regression to determine the association of each variant with overall survival time. Meta-analysis was conducted across samples at 73,203 overlapping variants. Gene-level tests of over 18,000 genes were also conducted using burden tests and Sequencing Kernel Association Tests (SKAT) adapted for Cox proportional hazards models. Gene-level tests were conducted separately for the primary and secondary cases and then were meta-analyzed. Models were adjusted for age, site, and three principle components. Six individual variants had meta-analysis p-values < 1.0E-4, five of which were rare (MAF < 0.003). Common variant rs8170 (MAF = 0.2) in BABAM1 encoding BRISC and BRCA1 A complex member 1 - previously reported to be associated with EOC risk_showed evidence of association with overall survival (Pmeta = 1.5E-5) and consistent estimates of effect size across both samples (HR1 = 1.18, HR2 = 1.19). In imputed genotype data from over 18,000 subjects from OCAC genotyped on the COGS array, this association reaches genome-wide significance (HR = 1.15, P = 4.7E-9). Five genes had gene-level meta-analysis p-values < 1.0E-4, including top ranked ATG2B (p = 1.1E-6), an autophagy gene important for apoptosis; zinc finger protein PEG3 (p = 1.8E-5), playing a role in autophagy and down-regulated in EOC; helicase-like transcription factor HLTF (p = 1.9E-5), involved in post-replication DNA repair; mitochondrial fission regulator 1-like gene FAM54B (p = 3.1E-5); and T-cell surface glycoprotein CD1E (p = 8.8E-5). With over 6000 EOC cases in the primary and secondary samples, this is the largest genome-wide assessment of rare variant genetic associations with EOC overall survival. Variant rs8170 in BABAM1, a necessary component of the BRCA1 complex, is associated with overall survival. Single variant and gene-level analyses provide complementary approaches, suggesting additional candidates that warrant follow-up study. Citation Format: Stacey J. Winham, Brooke L. Fridley, Melissa C. Larson, Zachary Fogarty, Andrew Berchuck, Yian Ann Chen, Hui-Yi Lin, Georgia Chenevix-Trench, Jenny Permuth-Wey, Thomas A. Sellers, Ailith Pirie, Ellen L. Goode, Ovarian Cancer Association Consortium. Investigation of exome variants associated with overall survival in ovarian cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4636. doi:10.1158/1538-7445.AM2015-4636
Genome-wide Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes: Findings from the Ovarian Cancer Association Consortium
Background Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene–environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized gene–environment interactions are now fairly common in human genetic research, and with the shift toward genome‐wide association studies, genome‐wide gene–environment interaction studies are beginning to emerge. Methods We summarize the basic ideas behind gene–environment interaction, and provide an overview of possible study designs and traditional analysis methods in the context of genome‐wide analysis. We then discuss novel approaches beyond the traditional strategy of analyzing the interaction between the environmental factor and each polymorphism individually. Results Two‐step filtering approaches that reduce the number of polymorphisms tested for interactions can substantially increase the power of genome‐wide gene–environment studies. New analytical methods including data‐mining approaches, and gene‐level and pathway‐level analyses, also have the capacity to improve our understanding of how complex genetic and environmental factors interact to influence psychologic and psychiatric traits. Such methods, however, have not yet been utilized much in behavioral and mental health research. Conclusions Although methods to investigate gene–environment interactions are available, there is a need for further development and extension of these methods to identify gene–environment interactions in the context of genome‐wide association studies. These novel approaches need to be applied in studies of psychology and psychiatry.
Association of the PDYN gene with alcohol dependence and the propensity to drink in negative emotional states
AbstractSynthetic κ-opioid receptor (KOR) agonists induce dysphoric and pro-depressive effects and variations in the KOR (OPRK1) and prodynorphin (PDYN) genes have been shown to be associated with alcohol dependence. We genotyped 23 single nucleotide polymorphisms (SNPs) in the PDYN and OPRK1 genes in 816 alcohol-dependent subjects and investigated their association with: (1) negative craving measured by a subscale of the Inventory of Drug Taking Situations; (2) a self-reported history of depression; (3) the intensity of depressive symptoms measured by the Beck Depression Inventory-II. In addition, 13 of the 23 PDYN and OPRK1 SNPs, which were previously genotyped in a set of 1248 controls, were used to evaluate association with alcohol dependence. SNP and haplotype tests of association were performed. Analysis of a haplotype spanning the PDYN gene (rs6045784, rs910080, rs2235751, rs2281285) revealed significant association with alcohol dependence (p = 0.00079) and with negative craving (p = 0.0499). A candidate haplotype containing the PDYN rs2281285-rs1997794 SNPs that was previously associated with alcohol dependence was also associated with negative craving (p = 0.024) and alcohol dependence (p = 0.0008) in this study. A trend for association between depression severity and PDYN variation was detected. No associations of OPRK1 gene variation with alcohol dependence or other studied phenotypes were found. These findings support the hypothesis that sequence variation in the PDYN gene contributes to both alcohol dependence and the induction of negative craving in alcohol-dependent subjects.
Association of GATA4 sequence variation with alcohol dependence
AbstractTo further explore reports of association of alcohol dependence and response to acamprosate treatment with the GATA4 rs13273672 single nucleotide polymorphism (SNP), we genotyped this and 10 other GATA4 SNPs in 816 alcohol‐dependent cases and 1248 controls. We tested for association of alcohol dependence with the 11 SNPs individually and performed a global test for association using a principle components analysis. Our analyses demonstrate significant association between GATA4 and alcohol dependence at the gene level (P = 0.009) but no association with rs13273672. Further studies are needed to identify potential causal GATA4 variation(s) and the functional mechanism(s) contributing to this association.