Citations

Abstract Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.

ObjectiveExamine the effects of obesity and metabolic syndrome on outcome in bipolar disorder.MethodThe Comparative Effectiveness of a Second Generation Antipsychotic Mood Stabilizer and a Classic Mood Stabilizer for Bipolar Disorder (Bipolar CHOICE) study randomized 482 participants with bipolar disorder in a 6‐month trial comparing lithium‐ and quetiapine‐based treatment. Baseline variables were compared between groups with and without obesity, with and without abdominal obesity, and with and without metabolic syndrome respectively. The effects of baseline obesity, abdominal obesity, and metabolic syndrome on outcomes were examined using mixed effects linear regression models.ResultsAt baseline, 44.4% of participants had obesity, 48.0% had abdominal obesity, and 27.3% had metabolic syndrome; neither obesity, nor abdominal obesity, nor metabolic syndrome were associated with increased global severity, mood symptoms, or suicidality, or with poorer functioning or life satisfaction. Treatment groups did not differ on prevalence of obesity, abdominal obesity, or metabolic syndrome. By contrast, among the entire cohort, obesity was associated with less global improvement and less improvement in total mood and depressive symptoms, suicidality, functioning, and life satisfaction after 6 months of treatment. Abdominal obesity was associated with similar findings. Metabolic syndrome had no effect on outcome.ConclusionObesity and abdominal obesity, but not metabolic syndrome, were associated with less improvement after 6 months of lithium‐ or quetiapine‐based treatment.

A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT–CLPTM1L gene region on chromosome 5p15.33. Because this region is characterized by low linkage disequilibrium, we sought to identify whether additional single nucleotide polymorphisms (SNPs) could be related to pancreatic cancer risk, independently of rs401681. We performed an in‐depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, odds ratio = 0.85; 95% confidence interval = 0.80–0.90, p = 8.3 × 10−8). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low linkage disequilibrium between them (r2 = 0.07, D′ = 0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (p = 3.0 × 10−5), rs4583925 (p = 4.0 × 10−5) and rs2735948 (p = 5.0 × 10−5). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants.

Abstract Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.

Objective: This study examines characteristics of individuals with bipolar disorder who sought psychotherapy versus those who did not. Methods: Bipolar CHOICE was an 11-site comparative effectiveness study of lithium versus quetiapine in symptomatic outpatients ( N = 482) with bipolar disorder. At baseline, participants’ psychotherapy use within the past 3 months, mood, functioning, and overall health were assessed. Logistic regressions were used to test whether psychotherapy users and non-users differed on various demographic and clinical variables at baseline. Mixed-effects regression was used to determine whether psychotherapy groups differed on response to treatment over the 6-month study. Kaplan-Meier plots and log-rank tests were employed to test whether there were any differences in time to recovery (CGI-BP ≤ 2 for at least 8 weeks) between the groups. Results: Thirty one percent of participants reported using psychotherapy services. Psychotherapy users reported greater medication side effect burden than non-users and were more likely to have moderate to high suicide risk and at least one anxiety disorder. Participants not utilizing medications or psychotherapy had greater mania symptom severity, were younger, and less educated than medication only users. Medication only users were more likely to be married than the other participants. Conclusions: These data suggest that a minority of individuals with bipolar disorder attend psychotherapy services, and those that do have greater illness burden.

ObjectivesIndividuals with bipolar disorder have high rates of other medical comorbidity, which is associated with higher mortality rates and worse course of illness. The present study examined common predictors of medical comorbidity.MethodsThe Clinical and Health Outcomes Initiative in Comparative Effectiveness for Bipolar Disorder study (Bipolar CHOICE) enrolled 482 participants with bipolar I or bipolar II disorder in a six‐month, randomized comparative effectiveness trial. Baseline assessments included current and lifetime DSM‐IV‐TR diagnoses, demographic information, psychiatric and medical history, severity of psychiatric symptoms, level of functioning, and a fasting blood draw. Medical comorbidities were categorized into two groups: cardiometabolic (e.g., diabetes, hyperlipidemia, and metabolic syndrome) and non‐cardiovascular (e.g., seizures, asthma, and cancer). Additionally, we looked at comorbid substance use (e.g., smoking and drug dependence).ResultsWe found that 96.3% of participants had at least one other medical comorbidity. Older age predicted a greater likelihood of having a cardiometabolic condition. Early age of onset of bipolar symptoms was associated with a lower chance of having a cardiometabolic condition, but a greater chance of having other types of medical comorbidity. Additional predictors of other medical comorbidities in bipolar disorder included more time spent depressed, less time spent manic/hypomanic, and longer duration of illness. Medications associated with weight gain were associated with low high‐density lipoprotein and abnormal triglycerides.ConclusionsThere appears to be a substantial medical burden associated with bipolar disorder, highlighting the need for collaborative care among psychiatric and general medical providers to address both psychiatric and other medical needs concomitantly in this group of patients.

ScopeWe reevaluated previously reported associations between variants in pathways of one‐carbon (1‐C) (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake.Methods and resultsOdds ratios (OR) for 446 genetic variants were estimated among 13 410 OC cases and 22 635 controls, and among 2281 cases and 3444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for dihydropyrimidine dehydrogenase (DPYD) variants rs11587873 (OR = 0.92; p = 6 × 10−5) and rs828054 (OR = 1.06; p = 1 × 10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT, and TYMS, also interacted significantly with folate in a multivariant analysis (corrected p = 9.9 × 10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in 1‐C transfer, previously reported with OC, suggested lower risk at higher folate (pinteraction = 0.03–0.006).ConclusionVariation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP‐by‐folate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC.