Citations

Objective: To derive new criteria sets for defining manic and hypomanic episodes (and thus for defining the bipolar I and II disorders), an international Task Force was assembled and termed AREDOC reflecting its role of Assessment, Revision and Evaluation of DSM and other Operational Criteria. This paper reports on the first phase of its deliberations and interim criteria recommendations. Method: The first stage of the process consisted of reviewing Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and recent International Classification of Diseases criteria, identifying their limitations and generating modified criteria sets for further in-depth consideration. Task Force members responded to recommendations for modifying criteria and from these the most problematic issues were identified. Results: Principal issues focussed on by Task Force members were how best to differentiate mania and hypomania, how to judge ‘impairment’ (both in and of itself and allowing that functioning may sometimes improve during hypomanic episodes) and concern that rejecting some criteria (e.g. an imposed duration period) might risk false-positive diagnoses of the bipolar disorders. Conclusion: This first-stage report summarises the clinical opinions of international experts in the diagnosis and management of the bipolar disorders, allowing readers to contemplate diagnostic parameters that may influence their clinical decisions. The findings meaningfully inform subsequent Task Force stages (involving a further commentary stage followed by an empirical study) that are expected to generate improved symptom criteria for diagnosing the bipolar I and II disorders with greater precision and to clarify whether they differ dimensionally or categorically.

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the TYMS-ENOSF1 3′ gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97–1.22; p = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03–1.24; p = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed (p = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa (r = 0.51, p = 1.7 × 10−28), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.

Abstract Ovarian cancer is the most lethal gynecologic malignancy and the sixth most common cause of death from all cancer in women, with an estimated 140,000 deaths per year worldwide. Endometrial cancer (cancer of the uterine lining) is the most commonly diagnosed gynecologic cancer, ranking sixth in incident cancer in women. Ovarian and endometrial cancer share many epidemiologic, histopathologic, and tumor genetic characteristics. Meta-analyses of genome-wide association study (GWAS) datasets across etiologically related diseases have successfully been used to increase statistical power and identify novel genetic risk regions. We hypothesised that joint meta-analysis of ovarian and endometrial cancer GWAS datasets would identify novel genetic loci for both cancers. Following quality control, summary statistics for >11 million genetic variants were available from the largest genome-wide association studies performed by the Ovarian Cancer Association Consortium (OCAC, Phelan et al., Nature Genetics 2017) and the Endometrial Cancer Association Consortium (ECAC, unpublished). A total of 35,312 cancer cases from all histologic subtypes (22,406 ovarian and 12,906 endometrial cancer cases) and 149,920 controls were included in the analysis. Summary statistics were combined using an inverse-variance, fixed-effects model in METAL and identified ten loci at genome-wide significance (P < 5 x 10-8), of which one locus at 14q23.3 (rs4072776 combined OR 0.94; 95% CI 0.92-0.96; P = 8.0 x 10-9) had not been previously associated with the risk of either cancer. Integration with chromatin conformation data (RNAPolII HiChIP) from the Ishikawa endometrial cancer cell line suggests interaction between the risk signal and the promoter of FUT8. FUT8 encodes a fucosyltransferase and its expression has been implicated in breast, stomach, and melanoma and lung cancer. Interestingly, FUT8 is a downstream target regulated by the loss of PAX2 and mutated p53, which is the earliest known molecular aberration in the progression of the fallopian tissue epithelial to serous ovarian cancer. Further functional evaluation of the 14q23.3 risk region is required to determine the regulatory effect of genetic risk variants on FUT8. Future meta-analyses of datasets, stratifying results by histologic subtypes, will be undertaken. Citation Format: Tracy A. O'Mara, Dylan M. Glubb, Daniel D. Buchanan, Diether Lambrechts, Per Hall, Emma Tham, Jone Trovik, Ellen L. Goode, Peter Fasching, Thilo Dörk, Rodney J. Scott, Paul L. Auer, Roger L. Milne, Graham G. Giles, John Perry, Immaculata de Vivo, Ian Tomlinson, Douglas F. Easton, Deborah J. Thompson, Amanda B. Spurdle, E2C2, BCAC, OCAC, ECAC. Joint genome-wide association study of endometrial cancer and ovarian cancer identifies a novel genetic risk region at 14q23.3 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 230.

Abstract Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.

AbstractEpidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (rg = 0.23, P = 9.3 × 10−3), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10−3) and concordance in effect direction (P = 2.0 × 10−3) between the two diseases. Cross‐disease GWAS meta‐analysis highlighted 13 distinct loci associated at P ≤ 10−5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10−8, OR = 1.11, 95% CI = 1.07–1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross‐disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.

Objective: Activation encompasses energy and activity and is a central feature of bipolar disorder. However, the impact of activation on treatment response of bipolar depression requires further exploration. The aims of this study were to assess the association of decreased activation and sustained remission in bipolar depression and test for factors that could affect this association. Methods: We assessed participants with Diagnostic and Statistical Manual of Mental Disorders (4th ed) bipolar depression ( n = 303) included in a comparative effectiveness study of lithium- and quetiapine-based treatments (the Bipolar CHOICE study). Activation was evaluated using items from the Bipolar Inventory of Symptoms Scale. The selection of these items was based on a dimension of energy and interest symptoms associated with poorer treatment response in major depression. Results: Decreased activation was associated with lower remission rates in the raw analyses and in a logistic regression model adjusted for baseline severity and subsyndromal manic symptoms (odds ratio = 0.899; p = 0.015). The manic features also predicted lower remission (odds ratio = 0.934; p < 0.001). Remission rates were similar in the two treatment groups. Conclusion: Decreased activation and subsyndromal manic symptoms predict lower remission rates in bipolar depression. Patients with these features may require specific treatment approaches, but new studies are necessary to identify treatments that could improve outcomes in this population.