Biernacka, Joanna M.

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)

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.

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.

Abstract It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene-set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol-dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the ‘synthesis and degradation of ketone bodies’ pathway. Our results also support the potential involvement of the ‘neuroactive ligand–receptor interaction’ pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence.