Citations

ObjectivesTo examine the independent effects of sex on the risk of rapid cycling and other indicators of adverse illness course in patients with bipolar I disorder (BP‐I) or bipolar II disorder (BP‐II).MethodsWe analyzed data from the first 1,225 patients enrolled in the Mayo Clinic Individualized Medicine Biobank for Bipolar Disorder. Demographic and clinical variables were ascertained using standardized questionnaires; height and weight were assessed to determine body mass index (BMI). Rates of rapid cycling, cycle acceleration, and increased severity of mood episodes over time were compared between women and men overall and within subgroups defined by bipolar disorder subtype (BP‐I or BP‐II). Multiple logistic regression analysis was used to assess the independent effect of sex on the risk of these indicators of adverse illness course.ResultsWomen had significantly higher rates of rapid cycling than men. Overall rates of rapid cycling were higher in patients with BP‐II than BP‐I; and sex differences in the rate of rapid cycling were more pronounced in patients with BP‐II than BP‐I, although the power to detect statistically significant differences was reduced due to the lower sample size of subjects with BP‐II. Female sex was a significant predictor of rapid cycling, cycle acceleration, and increased severity of mood episodes over time after adjusting for age, bipolar disorder subtype, BMI, having any comorbid psychiatric disorder, and current antidepressant use.ConclusionsFemale sex was associated with significantly higher risk of rapid cycling, cycle acceleration, and increased severity of mood episodes over time in a sample of 1,225 patients with bipolar disorders.

ObjectivesBrain‐derived neurotrophic factor (BDNF) Val66Met (rs6265) functional polymorphism has been implicated in early‐onset bipolar disorder. However, results of studies are inconsistent. We aimed to further explore this association.MethodsDNA samples from the Treatment of Early Age Mania (TEAM) and Mayo Clinic Bipolar Disorder Biobank were investigated for association of rs6265 with early‐onset bipolar disorder. Bipolar cases were classified as early onset if the first manic or depressive episode occurred at age ≤19 years (versus adult‐onset cases at age >19 years). After quality control, 69 TEAM early‐onset bipolar disorder cases, 725 Mayo Clinic bipolar disorder cases (including 189 early‐onset cases), and 764 controls were included in the analysis of association, assessed with logistic regression assuming log‐additive allele effects.ResultsComparison of TEAM cases with controls suggested association of early‐onset bipolar disorder with the rs6265 minor allele [odds ratio (OR) = 1.55, p = 0.04]. Although comparison of early‐onset adult bipolar disorder cases from the Mayo Clinic versus controls was not statistically significant, the OR estimate indicated the same direction of effect (OR = 1.21, p = 0.19). When the early‐onset TEAM and Mayo Clinic early‐onset adult groups were combined and compared with the control group, the association of the minor allele rs6265 was statistically significant (OR = 1.30, p = 0.04).ConclusionsThese preliminary analyses of a relatively small sample with early‐onset bipolar disorder are suggestive that functional variation in BDNF is implicated in bipolar disorder risk and may have a more significant role in early‐onset expression of the disorder.

ObjectivesThe aim of the present study was to engage a national advocacy group and local stakeholders for guidance in developing a bipolar disorder biobank through a web‐based survey and a community advisory board.MethodsThe Depression and Bipolar Support Alliance and the Mayo Clinic Bipolar Biobank conducted a national web‐based survey inquiring about interest in participating in a biobank (i.e., giving DNA and clinical information). A community advisory board was convened to guide establishment of the biobank and identify key deliverables from the research project and for the community.ResultsAmong 385 survey respondents, funding source (87%), professional opinion (76%), mental health consumer opinion (79%), and return of research results (91%) were believed to be important for considering study participation. Significantly more patients were willing to participate in a biobank managed by a university or clinic (78.2%) than one managed by government (63.4%) or industry (58.2%; both p < 0.001). The nine‐member community advisory board expressed interest in research to help predict the likelihood of bipolar disorder developing in a child of an affected parent and which medications to avoid. The advisory board endorsed the use of a comprehension questionnaire to evaluate participants' understanding of the study (e.g., longevity of DNA specimens, right to remove samples, accessing medical records) as a means to strengthen the informed consent process.ConclusionsThese national survey and community advisory data support the merit of establishing a biobank to enable studies of disease risk, provided that health records and research results are adequately protected. The goals of earlier diagnosis and individualized treatment of bipolar disorder were endorsed.

ObjectivesTo determine whether clinical features of bipolar disorder, such as history of psychosis, and cardiovascular disease (CVD) risk factors contribute to a higher risk of CVD among patients with bipolar disorder.MethodsThis cross‐sectional study included a sample of 988 patients with bipolar I or bipolar II disorder or schizoaffective bipolar type confirmed by the Structured Clinical Interview for DSM‐IV‐TR disorders (SCID). Medical comorbidity burden was quantified utilizing the Cumulative Illness Severity Rating Scale (CIRS). This 13‐item organ‐based scale includes cardiac disease severity quantification. Confirmed by medical record review, patients who scored 1 (current mild or past significant problem) or higher in the cardiac item were compared by logistic regression to patients who scored 0 (no impairment), adjusting for CVD risk factors that were selected using a backwards stepwise approach or were obtained from the literature.ResultsIn a multivariate model, age [odds ratio (OR) = 3.03, 95% confidence interval (CI): 1.66–5.54, p < 0.0001], hypertension (OR = 2.43, 95% CI: 1.69–3.55, p < 0.0001), and history of psychosis (OR = 1.48, 95% CI: 1.03–2.13, p = 0.03) were associated with CVD. When CVD risk factors from the literature were added to the analysis, age (OR = 3.19, 95% CI: 1.67–6.10, p = 0.0005) and hypertension (OR = 2.46, 95% CI: 1.61–3.76, p < 0.01) remained significant, with psychosis being at the trend level (OR = 1.43, 95% CI: 0.96–2.13, p = 0.08).ConclusionsThe phenotype of psychotic bipolar disorder may reflect higher illness severity with associated cardiac comorbidity. Further studies are encouraged to clarify the effect of the disease burden (i.e., depression), lifestyle, and treatment interventions (i.e., atypical antipsychotics) on this risk association.

ABSTRACT Objectives To determine whether α‐synuclein dinucleotide repeat (REP1) genotypes are associated with survival in Parkinson's disease (PD). Methods Investigators from the Genetic Epidemiology of Parkinson's Disease Consortium provided REP1 genotypes and baseline and follow‐up clinical data for cases. The primary outcome was time to death. Cox proportional hazards regression models were used to assess the association of REP1 genotypes with survival. Results Twenty‐one sites contributed data for 6,154 cases. There was no significant association between α‐synuclein REP1 genotypes and survival in PD. However, there was a significant association between REP1 genotypes and age at onset of PD (hazard ratio: 1.06; 95% confidence interval: 1.01‐1.10; P value = 0.01). Conclusions In our large consortium study, α‐synuclein REP1 genotypes were not associated with survival in PD. Further studies of α‐synuclein's role in disease progression and long‐term outcomes are needed. © 2014 International Parkinson and Movement Disorder Society

Abstract Integrative genomics has the potential to uncover relevant loci, as clinical outcome and response to chemotherapies are most likely not due to a single gene (or data type) but rather a complex relationship involving genetic variation, mRNA, DNA methylation, and copy number variation. In addition to this complexity, many complex phenotypes are thought to be controlled by the interplay of multiple genes within the same molecular pathway or gene set (GS). To address these two challenges, we propose an integrative gene set analysis approach and apply this strategy to a cisplatin (CDDP) pharmacogenomics study involving lymphoblastoid cell lines for which genome-wide SNP and mRNA expression data was collected. Application of the integrative GS analysis implicated the role of the RNA binding and cytoskeletal part GSs. The genes LMNB1 and CENPF, within the cytoskeletal part GS, were functionally validated with siRNA knockdown experiments, where the knockdown of LMNB1 and CENPF resulted in CDDP resistance in multiple cancer cell lines. This study demonstrates the utility of an integrative GS analysis strategy for detecting novel genes associated with response to cancer therapies, moving closer to tailored therapy decisions for cancer patients.

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.

IntroductionUnderstanding the course and determinants of sleep disturbances in alcoholic patients may help identify patients at high risk of persistent sleep problems, relapse and guide treatment interventions.MethodsWe prospectively administered the Pittsburgh Sleep Quality Index (PSQI) to all patients (N = 196) admitted to a 1‐month residential treatment program. Our analysis excluded patients with active drug abuse/dependence. Demographic data, psychiatric diagnoses, Patient Health Questionnaire‐9 (PHQ‐9), Alcohol Use Disorders Identification Test (AUDIT) and Inventory of Drug Taking Situations (IDTS) scores were obtained. Univariate and logistic regression analyses were performed using sex, age, hazardous alcohol use, PHQ‐9 scores, hypnotic use, and use of alcohol as a hypnotic as correlates to admission PSQI scores and improvement in PSQI scores.ResultsA total of 119 alcoholic patients met inclusion criteria (mean age 50.6 ± 13.2 years). The rates of sleep disturbances at admission and discharge were 69.3% and 49.1%, respectively. Self report of using alcohol to fall asleep and use of hypnotics were associated with elevated PSQI scores. Total PSQI scores improved over 4 weeks (p < .001). Change in PSQI scores was not effected by gender, use of hypnotics, hazardous alcohol use, use of alcohol as a hypnotic or co‐morbid psychiatric diagnosis. Older age predicted improvement in PSQI scores in patients with sleep disturbances (p = .004).ConclusionWhile a large proportion of alcoholics had sleep disturbances upon admission and at discharge from a residential treatment program, only older age was associated with improvements in sleep disturbances during early alcohol recovery. (Am J Addict 2014;23:21–26)

Background and ObjectivesThe aim of this study was to investigate potential gender differences in situations associated with heavy alcohol drinking.MethodsData from 395 alcohol dependent patients participating in the Mayo Clinic Intensive Addiction Program were evaluated. Each participant completed the inventory of drug taking situations (IDTS), Penn alcohol craving scale (PACS), patient health questionnaire (PHQ‐9), and/or Beck depression inventory (BDI). Gender differences in IDTS scores representing three domains (negative, positive, and temptation) of situations associated with heavy alcohol use were examined.ResultsWomen with alcohol dependence report a higher frequency of heavy drinking in unpleasant emotional (IDTS negative scores mean ± SD women vs. men: 52.3 ± 22.1 vs. 43.8 ± 21.8; p = .0006), and as a result of temptation (IDTS temptation scores mean ± SD women vs. men: 40.4 ± 23.0 vs. 35.3 ± 20.8; p = .035). Upon admission, women also scored significantly higher on depressive symptoms as measured by the BDI (23.4 ± 11.4 vs. 18.2 ± 9.8, p < .001). After controlling for depressive symptom severity as a covariate, the IDTS gender differences were no longer significant.Conclusion and Scientific SignificanceOur results suggest that unpleasant or temptation based emotional situations are a vulnerability risk factor for heavy drinking particularly in females. This risk appears to be at least partially driven by depressive symptom burden. Future research is needed to further investigate this finding. (Am J Addict 2013;22:437–442)