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Find video protocols related to scientific articles indexed in Pubmed.
Bipolar disorder with comorbid binge eating history: a genome-wide association study implicates APOB.
J Affect Disord
PUBLISHED: 03-20-2014
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Bipolar disorder (BD) is a highly heritable disease. While genome-wide association (GWA) studies have identified several genetic risk factors for BD, few of these studies have investigated the genetic etiology of specific disease subtypes. In particular, BD is positively associated with eating dysregulation traits such as binge eating behavior (BE), yet the genetic risk factors underlying BD with comorbid BE have not been investigated.
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Does ?-synuclein have a dual and opposing effect in preclinical vs. clinical Parkinson's disease?
Parkinsonism Relat. Disord.
PUBLISHED: 02-10-2014
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?-Synuclein gene (SNCA) multiplications cause familial parkinsonism and allele-length polymorphisms within the SNCA dinucleotide repeat REP1 increase the risk for developing Parkinson's disease (PD). Since SNCA multiplications increase SNCA expression, and REP1 genotypes that increase the risk of developing PD show increased SNCA expression in cell-culture systems, animal models, and human blood and brain, PD therapies seek to reduce SNCA expression. We conducted an observational study of 1098 PD cases to test the hypothesis that REP1 genotypes correlated with reduced SNCA expression are associated with better motor and cognitive outcomes. We evaluated the association of REP1 genotypes with survival free of Hoehn and Yahr stages 4 or 5 (motor outcome) and of Modified Telephone Interview for Cognitive Status score ?27 or Alzheimer's Disease Dementia Screening Interview score ?2 (cognitive outcome). Median disease duration at baseline was 3.3 years and median lag time from baseline to follow-up was 7.8 years. Paradoxically, REP1 genotypes associated with increased risk of developing PD and increased SNCA expression were associated with better motor (HR = 0.87, p = 0.046, covariate-adjusted age-scale analysis; HR = 0.85, p = 0.020, covariate-adjusted time-scale analysis) and cognitive outcomes (HR = 0.90, p = 0.12, covariate-adjusted age-scale analysis; HR = 0.85, p = 0.023, covariate-adjusted time-scale analysis). Our findings raise the possibility that SNCA has a dual, opposing, and time-dependent role. This may have implications for the development of therapies that target SNCA expression.
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Mass spectrometry and molecular modeling studies on the inclusion complexes between alendronate and ?-cyclodextrin.
J Incl Phenom Macrocycl Chem
PUBLISHED: 01-17-2014
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Complexation of alendronate sodium (AlnNa) with ?-cyclodextrin (?-CD) was studied by means of ESI-mass spectrometry. The experimental results show that stable 1:1 inclusion complexes between selected bisphosphonates and ?-CD were formed. In addition, complexes with different stoichiometry were observed. DFT/B3LYP calculations were performed to elucidate the different inclusion behavior between alendronate and ?-CD. Molecular modeling showed that the inclusion complex of Aln-?-CD where the two phosphonate groups bound to the central carbon atom of bisphosphonate were inserted into the cavity of ?-CD from its "top" side was thermodynamically more favorable than when they were inserted from its "bottom" side; the complexation energy was -74.05 versus -60.85 kcal/mol. The calculations indicated that the formation of conventional hydrogen bonds was the main factor for non-covalent ?-CD:Aln complex formation and stabilization in the gas phase.
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Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics.
OMICS
PUBLISHED: 11-07-2013
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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 cancer patients.
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Prediction of bioavailability of selected bisphosphonates using in silico methods towards categorization into a biopharmaceutical classification system.
Acta Pol Pharm
PUBLISHED: 10-24-2013
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The physicochemical properties relevant to biological activity of selected bisphosphonates such as clodronate disodium salt, etidronate disodium salt, pamidronate disodium salt, alendronate sodium salt, ibandronate sodium salt, risedronate sodium salt and zoledronate disodium salt were determined using in silico methods. The main aim of our research was to investigate and propose molecular determinants thataffect bioavailability of above mentioned compounds. These determinants are: stabilization energy (deltaE), free energy of solvation (deltaG(solv)), electrostatic potential, dipole moment, as well as partition and distribution coefficients estimated by the log P and log D values. Presented values indicate that selected bisphosphonates a recharacterized by high solubility and low permeability. The calculated parameters describing both solubility and permeability through biological membranes seem to be a good bioavailability indicators of bisphosphonates examined and can be a useful tool to include into Biopharmaceutical Classification System (BCS) development.
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The course of sleep disturbances in early alcohol recovery: an observational cohort study.
Am J Addict
PUBLISHED: 06-06-2013
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Understanding 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.
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A retrospective study of gender differences in depressive symptoms and risk of relapse in patients with alcohol dependence.
Am J Addict
PUBLISHED: 05-30-2013
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The aim of this study was to investigate potential gender differences in situations associated with heavy alcohol drinking.
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Gene-environment interactions in genome-wide association studies: current approaches and new directions.
J Child Psychol Psychiatry
PUBLISHED: 05-03-2013
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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.
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Clinical phenotype of bipolar disorder with comorbid binge eating disorder.
J Affect Disord
PUBLISHED: 04-10-2013
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To explore the relationship between binge eating disorder (BED) and obesity in patients with bipolar disorder (BP).
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Replication of genome wide association studies of alcohol dependence: support for association with variation in ADH1C.
PLoS ONE
PUBLISHED: 02-08-2013
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Genome-wide association studies (GWAS) have revealed many single nucleotide polymorphisms (SNPs) associated with complex traits. Although these studies frequently fail to identify statistically significant associations, the top association signals from GWAS may be enriched for true associations. We therefore investigated the association of alcohol dependence with 43 SNPs selected from association signals in the first two published GWAS of alcoholism. Our analysis of 808 alcohol-dependent cases and 1,248 controls provided evidence of association of alcohol dependence with SNP rs1614972 in the ADH1C gene (unadjusted p?=?0.0017). Because the GWAS study that originally reported association of alcohol dependence with this SNP [1] included only men, we also performed analyses in sex-specific strata. The results suggest that this SNP has a similar effect in both sexes (men: OR (95%CI)?=?0.80 (0.66, 0.95); women: OR (95%CI)?=?0.83 (0.66, 1.03)). We also observed marginal evidence of association of the rs1614972 minor allele with lower alcohol consumption in the non-alcoholic controls (p?=?0.081), and independently in the alcohol-dependent cases (p?=?0.046). Despite a number of potential differences between the samples investigated by the prior GWAS and the current study, data presented here provide additional support for the association of SNP rs1614972 in ADH1C with alcohol dependence and extend this finding by demonstrating association with consumption levels in both non-alcoholic and alcohol-dependent populations. Further studies should investigate the association of other polymorphisms in this gene with alcohol dependence and related alcohol-use phenotypes.
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FKBP5 genetic variation: association with selective serotonin reuptake inhibitor treatment outcomes in major depressive disorder.
Pharmacogenet. Genomics
PUBLISHED: 01-18-2013
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FKBP51 (51 kDa immunophilin) acts as a modulator of the glucocorticoid receptor and a negative regulator of the Akt pathway. Genetic variation in FKBP5 plays a role in antidepressant response. The aim of this study was to comprehensively assess the role of genetic variation in FKBP5, identified by both Sanger and Next Generation DNA resequencing, as well as genome-wide single nucleotide polymorphisms (SNPs) associated with FKBP5 expression in the response to the selective serotonin reuptake inhibitor (SSRI) treatment of major depressive disorder.
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Genetic susceptibility loci, environmental exposures, and Parkinsons disease: a case-control study of gene-environment interactions.
Parkinsonism Relat. Disord.
PUBLISHED: 01-16-2013
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Prior studies causally linked mutations in SNCA, MAPT, and LRRK2 genes with familial Parkinsonism. Genome-wide association studies have demonstrated association of single nucleotide polymorphisms (SNPs) in those three genes with sporadic Parkinsons disease (PD) susceptibility worldwide. Here we investigated the interactions between SNPs in those three susceptibility genes and environmental exposures (pesticides application, tobacco smoking, coffee drinking, and alcohol drinking) also associated with PD susceptibility.
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PDYN rs2281285 Variant Association with Drinking to Avoid Emotional or Somatic Discomfort.
PLoS ONE
PUBLISHED: 01-01-2013
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One of the proposed psychobiological pathways of craving attributes the desire for drinking in the context of tension, discomfort or unpleasant emotions, to "negative" (or "relief") craving. The aim of this study was to replicate a previously reported association of the PDYN rs2281285 variant with negative craving using a different phenotyping approach.
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Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report.
Mirko Manchia, Mazda Adli, Nirmala Akula, Raffaella Ardau, Jean-Michel Aubry, Lena Backlund, Claudio Em Banzato, Bernhard T Baune, Frank Bellivier, Susanne Bengesser, Joanna M Biernacka, Clara Brichant-Petitjean, Elise Bui, Cynthia V Calkin, Andrew Tai Ann Cheng, Caterina Chillotti, Sven Cichon, Scott Clark, Piotr M Czerski, Clarissa Dantas, Maria Del Zompo, J Raymond Depaulo, Sevilla D Detera-Wadleigh, Bruno Etain, Peter Falkai, Louise Frisén, Mark A Frye, Jan Fullerton, Sebastien Gard, Julie Garnham, Fernando S Goes, Paul Grof, Oliver Gruber, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Rebecca Hoban, Liping Hou, Stéphane Jamain, Jean-Pierre Kahn, Layla Kassem, Tadafumi Kato, John R Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Po-Hsiu Kuo, Ichiro Kusumi, Gonzalo Laje, Catharina Lavebratt, Marion Leboyer, Susan G Leckband, Carlos A López Jaramillo, Mario Maj, Alain Malafosse, Lina Martinsson, Takuya Masui, Philip B Mitchell, Frank Mondimore, Palmiero Monteleone, Audrey Nallet, Maria Neuner, Tomas Novak, Claire O'Donovan, Urban Osby, Norio Ozaki, Roy H Perlis, Andrea Pfennig, James B Potash, Daniela Reich-Erkelenz, Andreas Reif, Eva Reininghaus, Sara Richardson, Guy A Rouleau, Janusz K Rybakowski, Martin Schalling, Peter R Schofield, Oliver K Schubert, Barbara Schweizer, Florian Seemüller, Maria Grigoroiu-Serbanescu, Giovanni Severino, Lisa R Seymour, Claire Slaney, Jordan W Smoller, Alessio Squassina, Thomas Stamm, Jo Steele, Pavla Stopkova, Sarah K Tighe, Alfonso Tortorella, Gustavo Turecki, Naomi R Wray, Adam Wright, Peter P Zandi, David Zilles, Michael Bauer, Marcella Rietschel, Francis J McMahon, Thomas G Schulze, Martin Alda.
PLoS ONE
PUBLISHED: 01-01-2013
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The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study.
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Use of the gamma method for self-contained gene-set analysis of SNP data.
Eur. J. Hum. Genet.
PUBLISHED: 12-14-2011
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Gene-set analysis (GSA) evaluates the overall evidence of association between a phenotype and all genotyped single nucleotide polymorphisms (SNPs) in a set of genes, as opposed to testing for association between a phenotype and each SNP individually. We propose using the Gamma Method (GM) to combine gene-level P-values for assessing the significance of GS association. We performed simulations to compare the GM with several other self-contained GSA strategies, including both one-step and two-step GSA approaches, in a variety of scenarios. We denote a one-step GSA approach to be one in which all SNPs in a GS are used to derive a test of GS association without consideration of gene-level effects, and a two-step approach to be one in which all genotyped SNPs in a gene are first used to evaluate association of the phenotype with all measured variation in the gene and then the gene-level tests of association are aggregated to assess the GS association with the phenotype. The simulations suggest that, overall, two-step methods provide higher power than one-step approaches and that combining gene-level P-values using the GM with a soft truncation threshold between 0.05 and 0.20 is a powerful approach for conducting GSA, relative to the competing approaches assessed. We also applied all of the considered GSA methods to data from a pharmacogenomic study of cisplatin, and obtained evidence suggesting that the glutathione metabolism GS is associated with cisplatin drug response.
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Trazodone and alcohol relapse: a retrospective study following residential treatment.
Am J Addict
PUBLISHED: 09-29-2011
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Trazodone is one of the most commonly prescribed hypnotic medications in patients with sleep disturbances in alcohol recovery. A recent study concluded that treating insomnia with trazodone in patients with alcohol dependence might impede improvements in alcohol consumption and lead to increased drinking when trazodone is stopped. We set out to investigate the relationship between trazodone use during alcoholism treatment and relapse rates in patients who were discharged from a residential alcohol treatment program. We retrospectively reviewed records of patients with a diagnosis of alcohol dependence in a residential addiction treatment center from 2005 to 2008 and analyzed the association of trazodone use at discharge and alcohol relapse at 6 months. We also assessed the association between trazodone use and relapse at 6 months adjusting for sex, drug dependence, nonsubstance use Axis I psychiatric diagnoses, patient self-report of difficulties with sleep, and anti-dipsotropic medication use at discharge and evaluated pair-wise interactions of trazodone use with the adjustment variables. Of 283 patients eligible for inclusion, 85 (30%) were taking trazodone at discharge. Older age, self-reported sleep problems, and having a nonsubstance use Axis I psychiatric diagnosis were associated with trazodone use. After discharge, 170 (60%) subjects responded to follow-up efforts. Neither intent to treat nor responder only analysis revealed any association between trazodone use and relapse. Our retrospective study of a complex patient population discharged from a residential treatment setting did not find an association between trazodone use at discharge and relapse rates at 6 months.
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Effect of cytochrome P450 enzyme polymorphisms on pharmacokinetics of venlafaxine.
Ther Drug Monit
PUBLISHED: 08-11-2011
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This study examines the relationship between blood concentrations of venlafaxine and its active metabolite, O-desmethyl venlafaxine (ODV), and genetic variants of the cytochrome P450 enzymes CYP2D6 and CYP2C19 in human subjects. Trough blood concentrations were measured at steady state in patients treated with venlafaxine extended release in a clinical practice setting. CYP2D6 and CYP2C19 genotypes were converted to activity scores based on known activity levels of the two alleles comprising a genotype. After adjusting for drug dose and gender effects, higher CYP2D6 and CYP2C19 activity scores were significantly associated with lower venlafaxine concentrations (P < 0.001 for each). Only CYP2D6 was associated with the concentration of ODV (P < 0.001), in which genotypes with more active alleles were associated with higher ODV concentrations. The sum of venlafaxine plus ODV concentration showed the same pattern as venlafaxine concentrations with CYP2D6 and CYP2C19 genotypes with higher activity scores being associated with a lower venlafaxine plus ODV concentration (2D6 P = 0.01; 2C19 P < 0.001). Because allelic variants in both CYP2D6 and CYP2C19 influence the total concentration of the active compounds venlafaxine and ODV, both CYP2D6 and CYP2C19 genotypes should be considered when using pharmacogenomic information for venlafaxine dose alterations.
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Genetic variability in the NMDA-dependent AMPA trafficking cascade is associated with alcohol dependence.
Addict Biol
PUBLISHED: 07-18-2011
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Model studies in mice indicate that the severity of alcohol withdrawal is associated with polymorphic variation and expression of the MPDZ gene. Current knowledge about variation in the human MPDZ gene is limited; however, our data indicate its potential association with alcohol dependence. The multi-PDZ protein is an important part of the N-methyl-D-aspartate (NMDA)-dependent ?-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor trafficking cascade that controls glutamate-related excitatory neurotransmission. To investigate association of variation in the NMDA-dependent AMPA trafficking cascade with alcohol dependence, we performed a gene-set (pathway) analysis using single nucleotide polymorphism (SNP) data from the Study of Addiction: Genetic and Environment. Rather than testing for association with each SNP individually, which typically has low power to detect small effects of multiple SNPs, gene-set analysis applies a single statistical test to evaluate whether variation in a set of genes is associated with the phenotype of interest. Gene-set analysis of 988 SNPs in 13 genes in the pathway demonstrated a significant association with alcohol dependence, with P < 0.01 for the global effect of variation in this pathway. The statistically significant association of alcohol dependence with genetic variation in the NMDA-dependent AMPA receptor trafficking cascade indicates a need for further investigation of the role of this pathway in alcohol dependence.
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Do interactions between SNCA, MAPT, and LRRK2 genes contribute to Parkinsons disease susceptibility?
Parkinsonism Relat. Disord.
PUBLISHED: 06-21-2011
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Polymorphisms in SNCA, MAPT and LRRK2 genes have recently been confirmed as risk factors for Parkinsons disease (PD), although with small individual attributable risk. Here we investigated the association of PD with interactions between variants of these genes.
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Pharmacogenomics of antidepressant induced mania: a review and meta-analysis of the serotonin transporter gene (5HTTLPR) association.
J Affect Disord
PUBLISHED: 05-18-2011
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Antidepressants can trigger a rapid mood switch from depression to mania. Identifying genetic risk factors associated with antidepressant induced mania (AIM) may enable individualized treatment strategies for bipolar depression. This review and meta-analysis evaluates the evidence for association between the serotonin transporter gene promoter polymorphism (5HTTLPR) and AIM.
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Relationship between FKBP5 polymorphisms and depression symptoms among kidney transplant recipients.
Depress Anxiety
PUBLISHED: 05-03-2011
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Several polymorphisms in FK506 Binding Protein gene (FKBP5) and a history of child abuse have been shown to be associated with an increased risk for posttraumatic stress disorder (PTSD). It has also been demonstrated that the same polymorphisms of FKBP5 are associated with increased recurrence of depressive episodes and rapid response to antidepressant treatment. However, there are only limited numbers of studies replicating the polymorphisms as vulnerability factors for the development of mental illnesses, such as PTSD and depression after stressful life event, especially with a specific incidence, such as kidney transplant surgery.
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Gene set analysis of SNP data: benefits, challenges, and future directions.
Eur. J. Hum. Genet.
PUBLISHED: 04-13-2011
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The last decade of human genetic research witnessed the completion of hundreds of genome-wide association studies (GWASs). However, the genetic variants discovered through these efforts account for only a small proportion of the heritability of complex traits. One explanation for the missing heritability is that the common analysis approach, assessing the effect of each single-nucleotide polymorphism (SNP) individually, is not well suited to the detection of small effects of multiple SNPs. Gene set analysis (GSA) is one of several approaches that may contribute to the discovery of additional genetic risk factors for complex traits. Complex phenotypes are thought to be controlled by networks of interacting biochemical and physiological pathways influenced by the products of sets of genes. By assessing the overall evidence of association of a phenotype with all measured variation in a set of genes, GSA may identify functionally relevant sets of genes corresponding to relevant biomolecular pathways, which will enable more focused studies of genetic risk factors. This approach may thus contribute to the discovery of genetic variants responsible for some of the missing heritability. With the increased use of these approaches for the secondary analysis of data from GWAS, it is important to understand the different GSA methods and their strengths and weaknesses, and consider challenges inherent in these types of analyses. This paper provides an overview of GSA, highlighting the key challenges, potential solutions, and directions for ongoing research.
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Variants in estrogen-related genes and risk of Parkinsons disease.
Mov. Disord.
PUBLISHED: 04-05-2011
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Incidence rates of Parkinsons disease are higher in men than in women at all ages, and these differences may be a result of the neuroprotective effects of estrogen on the nigrostriatal pathway. We investigated the association of common variants in 4 estrogen-related genes with Parkinsons disease. Tagging single-nucleotide polymorphisms in the CYP19A1, ESR1, ESR2, and PRDM2 genes were selected from the International Haplotype Map and genotyped in 1103 Parkinsons disease cases from the upper Midwest of the United States and in 1103 individually matched controls (654 unaffected siblings, and 449 unrelated controls from the same region). Of 137 informative single-nucleotide polymorphisms, 2 PRDM2 single-nucleotide polymorphisms were significantly associated with an increased risk of Parkinsons disease at the Bonferroni-corrected significance level of 0.0004 (rs2744690: OR, 1.54; SE(logOR), .109; 99.96% CI, 1.05-2.26; uncorrected P = .0001; rs2744687: OR, 1.53; SE(logOR), .113; 99.96% CI, 1.03-2.29, uncorrected P = .0002); the association was significant in the women-only stratum but not in the men-only stratum. An additional 6 single-nucleotide polymorphisms in PRDM2, 2 in ESR1, 1 in ESR2, and 1 in CYP19A1 had significant P values in the overall sample before Bonferroni correction. None of the single-nucleotide polymorphisms were significantly associated with age at onset of Parkinsons disease after Bonferroni correction. Our results confirm the association of PRDM2 variants with Parkinsons disease susceptibility, especially in women.
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CYP2C19 variation and citalopram response.
Pharmacogenet. Genomics
PUBLISHED: 04-01-2011
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Variations in cytochrome P450 (CYP) genes have been shown to be associated with both accelerated and delayed pharmacokinetic clearance of many psychotropic medications. Citalopram is metabolized by three CYP enzymes. CYP2C19 and CYP3A4 play a primary role in citalopram metabolism, whereas CYP2D6 plays a secondary role.
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Functional role of the polymorphic 647 T/C variant of ENT1 (SLC29A1) and its association with alcohol withdrawal seizures.
PLoS ONE
PUBLISHED: 01-24-2011
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Adenosine is involved in several neurological and behavioral disorders including alcoholism. In cultured cell and animal studies, type 1 equilibrative nucleoside transporter (ENT1, slc29a1), which regulates adenosine levels, is known to regulate ethanol sensitivity and preference. Interestingly, in humans, the ENT1 (SLC29A1) gene contains a non-synonymous single nucleotide polymorphism (647 T/C; rs45573936) that might be involved in the functional change of ENT1.
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Utilization of residential alcoholism treatment in bipolar disorder.
Am J Addict
PUBLISHED: 11-12-2010
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Despite the high prevalence rate of comorbid alcohol dependence and bipolar disorder, little is known about how many bipolar patients are actively engaged in addiction treatment or the alcohol consumption characteristics of this group. This retrospective study reviewed the medical records from patients with alcohol dependence admitted to residential treatment at our institution (n = 588). The analyses focused on alcoholism severity measures and discharge clinical diagnoses. Patients with alcoholism + bipolar disorder compromised only 5% of the total study group. The number of drinking years was lower for patients with alcoholism + bipolar disorder (23.1 ± 17.7) than for those with alcoholism + depression (26.8 ± 13.9) or alcoholism alone (28.1 ± 13.2). A trend of higher mean lifetime maximum daily drinks was observed for patients with alcoholism + bipolar disorder; this was because of the significantly higher maximum drinks for women with bipolar disorder (21.0 ± 11.5) than for women in other diagnostic groups. Despite high rates of comorbidity in community-based studies, this retrospective study suggests that patients with bipolar disorder are not highly represented in residential alcoholism addiction treatment. Future studies are encouraged to better understand utilization rates of addiction treatment among patients with bipolar disorder and to identify clinical correlates that predispose bipolar women to high-dose drinking.?
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Gender differences in the relationship between depressive symptoms and cravings in alcoholism.
Am J Addict
PUBLISHED: 07-27-2010
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This study examines the clinical correlates of alcohol craving in men and women self-referred for addiction treatment. Admission clinical data from patients participating in the Mayo Clinic 1-month Intensive Addictions Program were evaluated. Women had higher BDI and PACS scores compared with men in both the entire cohort and Dual Diagnoses group. Alcohol-dependent females had the most marked correlation between BDI and PACS (rho= .78). Further prospective study is encouraged to evaluate whether depressive symptoms and concomitant alcohol cravings in women are a marker for relief cravings and, as such, a target symptom for treatment intervention.
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Common variants in PARK loci and related genes and Parkinsons disease.
Mov. Disord.
PUBLISHED: 06-08-2010
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Rare mutations in PARK loci genes cause Parkinsons disease (PD) in some families and isolated populations. We investigated the association of common variants in PARK loci and related genes with PD susceptibility and age at onset in an outbred population. A total of 1,103 PD cases from the upper Midwest, USA, were individually matched to unaffected siblings (n = 654) or unrelated controls (n = 449) from the same region. Using a sequencing approach in 25 cases and 25 controls, single nucleotide polymorphisms (SNPs) in species-conserved regions of PARK loci and related genes were detected. We selected additional tag SNPs from the HapMap. We genotyped a total of 235 SNPs and two variable number tandem repeats in the ATP13A2, DJ1, LRRK1, LRRK2, MAPT, Omi/HtrA2, PARK2, PINK1, SNCA, SNCB, SNCG, SPR, and UCHL1 genes in all 2,206 subjects. Case-control analyses were performed to study association with PD susceptibility, while cases-only analyses were used to study association with age at onset. Only MAPT SNP rs2435200 was associated with PD susceptibility after correction for multiple testing (OR = 0.74, 95% CI = 0.64-0.86, uncorrected P < 0.0001, log additive model); however, 16 additional MAPT variants, seven SNCA variants, and one LRRK2, PARK2, and UCHL1 variants each had significant uncorrected P-values. There were no significant associations for age at onset after correction for multiple testing. Our results confirm the association of MAPT and SNCA genes with PD susceptibility but show limited association of other PARK loci and related genes with PD.
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Self-contained gene-set analysis of expression data: an evaluation of existing and novel methods.
PLoS ONE
PUBLISHED: 06-01-2010
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Gene set methods aim to assess the overall evidence of association of a set of genes with a phenotype, such as disease or a quantitative trait. Multiple approaches for gene set analysis of expression data have been proposed. They can be divided into two types: competitive and self-contained. Benefits of self-contained methods include that they can be used for genome-wide, candidate gene, or pathway studies, and have been reported to be more powerful than competitive methods. We therefore investigated ten self-contained methods that can be used for continuous, discrete and time-to-event phenotypes. To assess the power and type I error rate for the various previously proposed and novel approaches, an extensive simulation study was completed in which the scenarios varied according to: number of genes in a gene set, number of genes associated with the phenotype, effect sizes, correlation between expression of genes within a gene set, and the sample size. In addition to the simulated data, the various methods were applied to a pharmacogenomic study of the drug gemcitabine. Simulation results demonstrated that overall Fishers method and the global model with random effects have the highest power for a wide range of scenarios, while the analysis based on the first principal component and Kolmogorov-Smirnov test tended to have lowest power. The methods investigated here are likely to play an important role in identifying pathways that contribute to complex traits.
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Identification of gene-gene interaction using principal components.
BMC Proc
PUBLISHED: 12-15-2009
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After more than 200 genome-wide association studies, there have been some successful identifications of a single novel locus. Thus, the identification of single-nucleotide polymorphisms (SNP) with interaction effects is of interest. Using the Genetic Analysis Workshop 16 data from the North American Rheumatoid Arthritis Consortium, we propose an approach to screen for SNP-SNP interaction using a two-stage method and an approach for detecting gene-gene interactions using principal components. We selected a set of 17 rheumatoid arthritis candidate genes to assess both approaches. Our approach using principal components holds promise in detecting gene-gene interactions. However, further study is needed to evaluate the power and the feasibility for a whole genome-wide association analysis using the principal components approach.
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Single versus multiple imputation for genotypic data.
BMC Proc
PUBLISHED: 12-15-2009
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Due to the growing need to combine data across multiple studies and to impute untyped markers based on a reference sample, several analytical tools for imputation and analysis of missing genotypes have been developed. Current imputation methods rely on single imputation, which ignores the variation in estimation due to imputation. An alternative to single imputation is multiple imputation. In this paper, we assess the variation in imputation by completing both single and multiple imputations of genotypic data using MACH, a commonly used hidden Markov model imputation method. Using data from the North American Rheumatoid Arthritis Consortium genome-wide study, the use of single and multiple imputation was assessed in four regions of chromosome 1 with varying levels of linkage disequilibrium and association signals. Two scenarios for missing genotypic data were assessed: imputation of untyped markers and combination of genotypic data from two studies. This limited study involving four regions indicates that, contrary to expectations, multiple imputations may not be necessary.
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Identification of genes and haplotypes that predict rheumatoid arthritis using random forests.
BMC Proc
PUBLISHED: 12-15-2009
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Random forest (RF) analysis of genetic data does not require specification of the mode of inheritance, and provides measures of variable importance that incorporate interaction effects. In this paper we describe RF-based approaches for assessment of gene and haplotype importance, and apply these approaches to a subset of the North American Rheumatoid Arthritis Consortium case-control data provided by Genetic Analysis Workshop 16. The RF analyses of 37 genes identified many of the same genes as logistic regression, but also suggested importance of certain single-nucleotide polymorphism and genes that were not ranked highly by logistic regression. A new permutation method did not reveal strong evidence of gene-gene interaction effects in these data. Although RFs are a promising approach for genetic data analysis, extensions beyond simple single-nucleotide polymorphism analyses and modifications to improve computational feasibility are needed.
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Assessment of genotype imputation methods.
BMC Proc
PUBLISHED: 12-15-2009
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Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE. We compared the methods imputation error rates and performance of association tests using the imputed data, in the context of imputing completely untyped markers as well as imputing missing genotypes to combine two datasets genotyped at different sets of markers. As expected, all methods performed better for single-nucleotide polymorphisms (SNPs) in high linkage disequilibrium with genotyped SNPs. However, MACH and IMPUTE generated lower imputation error rates than fastPHASE and PLINK. Association tests based on allele "dosage" from MACH and tests based on the posterior probabilities from IMPUTE provided results closest to those based on complete data. However, in both situations, none of the imputation-based tests provide the same level of evidence of association as the complete data at SNPs strongly associated with disease.
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Machine learning in genome-wide association studies.
Genet. Epidemiol.
PUBLISHED: 11-20-2009
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Recently, genome-wide association studies have substantially expanded our knowledge about genetic variants that influence the susceptibility to complex diseases. Although standard statistical tests for each single-nucleotide polymorphism (SNP) separately are able to capture main genetic effects, different approaches are necessary to identify SNPs that influence disease risk jointly or in complex interactions. Experimental and simulated genome-wide SNP data provided by the Genetic Analysis Workshop 16 afforded an opportunity to analyze the applicability and benefit of several machine learning methods. Penalized regression, ensemble methods, and network analyses resulted in several new findings while known and simulated genetic risk variants were also identified. In conclusion, machine learning approaches are promising complements to standard single-and multi-SNP analysis methods for understanding the overall genetic architecture of complex human diseases. However, because they are not optimized for genome-wide SNP data, improved implementations and new variable selection procedures are required.
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A composite-likelihood approach for identifying polymorphisms that are potentially directly associated with disease.
Eur. J. Hum. Genet.
PUBLISHED: 09-29-2009
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If a linkage signal can be fully accounted for by the association of a particular polymorphism with the disease, this polymorphism may be the sole causal variant in the region. On the other hand, if the linkage signal exceeds that explained by the association, different or additional directly associated loci must exist in the region. Several methods have been proposed for testing the hypothesis that association with a particular candidate single-nucleotide polymorphism (SNP) can explain an observed linkage signal. When several candidate SNPs exist, all of the existing methods test the hypothesis for each candidate SNP separately, by fitting the appropriate model for each individual candidate SNP. Here we propose a method that combines analyses of two or more candidate SNPs using a composite-likelihood approach. We use simulations to demonstrate that the proposed method can lead to substantial power increases over the earlier single SNP analyses.
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Sequence variations of the human MPDZ gene and association with alcoholism in subjects with European ancestry.
Alcohol. Clin. Exp. Res.
PUBLISHED: 01-21-2009
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Mpdz gene variations are known contributors of acute alcohol withdrawal severity and seizures in mice.
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Alcohol craving as a predictor of relapse.
Am J Addict
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Alcoholism treatment interventions, both psychosocial and pharmacologic, aim to reduce cravings to drink. Yet, the role of craving in treatment outcomes remains unclear. This study evaluated craving intensity measured with the Penn Alcohol Craving Scale (PACS) at admission and discharge from residential treatment as a predictive factor of relapse after treatment.
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Association of the PDYN gene with alcohol dependence and the propensity to drink in negative emotional states.
Int. J. Neuropsychopharmacol.
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Synthetic ?-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.
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Association of GATA4 sequence variation with alcohol dependence.
Addict Biol
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To 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.
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SNP interaction detection with Random Forests in high-dimensional genetic data.
BMC Bioinformatics
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Identifying variants associated with complex human traits in high-dimensional data is a central goal of genome-wide association studies. However, complicated etiologies such as gene-gene interactions are ignored by the univariate analysis usually applied in these studies. Random Forests (RF) are a popular data-mining technique that can accommodate a large number of predictor variables and allow for complex models with interactions. RF analysis produces measures of variable importance that can be used to rank the predictor variables. Thus, single nucleotide polymorphism (SNP) analysis using RFs is gaining popularity as a potential filter approach that considers interactions in high-dimensional data. However, the impact of data dimensionality on the power of RF to identify interactions has not been thoroughly explored. We investigate the ability of rankings from variable importance measures to detect gene-gene interaction effects and their potential effectiveness as filters compared to p-values from univariate logistic regression, particularly as the data becomes increasingly high-dimensional.
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Genome-wide gene-set analysis for identification of pathways associated with alcohol dependence.
Int. J. Neuropsychopharmacol.
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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.
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Genomic determinants of motor and cognitive outcomes in Parkinsons disease.
Parkinsonism Relat. Disord.
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Little is known regarding genetic factors associated with motor or cognitive outcomes in Parkinsons disease (PD).
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Comprehensive research synopsis and systematic meta-analyses in Parkinsons disease genetics: The PDGene database.
PLoS Genet.
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More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinsons disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of -27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P < 5 × 10(-8)) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P? =? 1.3 × 10(-8)). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.
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Pretransplant psychiatric and substance use comorbidity in patients with cholangiocarcinoma who received a liver transplant.
Psychosomatics
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Psychopathology has been commonly observed in liver transplant candidates, and up to 40% have comorbid psychiatric disorders. This illness burden may negatively impact quality of life and transplant outcome. Liver transplantation for cholangiocarcinoma remains uncommon due to the complex treatment protocol. We assessed for pretransplant psychopathology and substance use disorders in liver transplant recipients with cholangiocarcinoma to better characterize this patient group.
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Merging pharmacometabolomics with pharmacogenomics using 1000 Genomes single-nucleotide polymorphism imputation: selective serotonin reuptake inhibitor response pharmacogenomics.
Pharmacogenet. Genomics
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We set out to test the hypothesis that pharmacometabolomic data could be efficiently merged with pharmacogenomic data by single-nucleotide polymorphism (SNP) imputation of metabolomic-derived pathway data on a scaffolding of genome-wide association (GWAS) SNP data to broaden and accelerate pharmacometabolomics-informed pharmacogenomic studies by eliminating the need for initial genotyping and by making broader SNP association testing possible.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.