Dopamine D2 receptor polymorphisms and susceptibility to alcohol dependence in Indian males: a preliminary study

<p>Abstract</p> <p>Background</p> <p>Dopamine is an important neurotransmitter involved in reward mechanism in the brain and thereby influences development and relapse of alcohol dependence. The dopamine D2 receptor (<it>DRD2</it>) gene on chromosome 11 (q22-q23) has been found to be associated with increased alcohol consumption through mechanisms involving incentive salience attributions and craving in alcoholic patients. Therefore, we investigated the association of three single nucleotide polymorphisms (SNP) in <it>DRD2 </it>gene with alcohol dependence in the north Indian subjects.</p> <p>Methods</p> <p>In a retrospective analysis, genetic association of three polymorphisms from <it>DRD2 </it>gene with alcohol dependence was investigated using a case-control approach. Alcohol dependence was determined by DSM-IV criteria and a total of 90 alcoholics and 60 healthy unrelated age-matched control subjects were recruited. Odds ratio and confidence interval was calculated to determine risk conferred by a predisposing allele/genotype/haplotype. Logistic regression analysis was carried out to correlate various clinical parameters with genotypes, and to study pair-wise interactions between SNPs.</p> <p>Results</p> <p>The study showed a significant association of -141C Ins allele and a trend of association of TaqI A1 allele of <it>DRD2 </it>with alcohol dependence. Haplotype with the predisposing -141C Ins and TaqI A1 alleles (-141C Ins-A-A1) seems to confer ≈ 2.5 times more risk to develop alcohol dependence.</p> <p>Conclusions</p> <p>The study provides preliminary insight into genetic risk to alcohol dependence in Indian males. Two polymorphisms namely, -141C Ins/Del and TaqI A in <it>DRD2 </it>gene may have clinical implications among Indian alcoholic subjects.</p

Generational Association Studies of Dopaminergic Genes in Reward Deficiency Syndrome (RDS) Subjects: Selecting Appropriate Phenotypes for Reward Dependence Behaviors

Abnormal behaviors involving dopaminergic gene polymorphisms often reflect an insufficiency of usual feelings of satisfaction, or Reward Deficiency Syndrome (RDS). RDS results from a dysfunction in the “brain reward cascade,” a complex interaction among neurotransmitters (primarily dopaminergic and opioidergic). Individuals with a family history of alcoholism or other addictions may be born with a deficiency in the ability to produce or use these neurotransmitters. Exposure to prolonged periods of stress and alcohol or other substances also can lead to a corruption of the brain reward cascade function. We evaluated the potential association of four variants of dopaminergic candidate genes in RDS (dopamine D1 receptor gene [DRD1]; dopamine D2 receptor gene [DRD2]; dopamine transporter gene [DAT1]; dopamine beta-hydroxylase gene [DBH]). Methodology: We genotyped an experimental group of 55 subjects derived from up to five generations of two independent multiple-affected families compared to rigorously screened control subjects (e.g., N = 30 super controls for DRD2 gene polymorphisms). Data related to RDS behaviors were collected on these subjects plus 13 deceased family members. Results: Among the genotyped family members, the DRD2 Taq1 and the DAT1 10/10 alleles were significantly (at least p < 0.015) more often found in the RDS families vs. controls. The TaqA1 allele occurred in 100% of Family A individuals (N = 32) and 47.8% of Family B subjects (11 of 23). No significant differences were found between the experimental and control positive rates for the other variants. Conclusions: Although our sample size was limited, and linkage analysis is necessary, the results support the putative role of dopaminergic polymorphisms in RDS behaviors. This study shows the importance of a nonspecific RDS phenotype and informs an understanding of how evaluating single subset behaviors of RDS may lead to spurious results. Utilization of a nonspecific “reward” phenotype may be a paradigm shift in future association and linkage studies involving dopaminergic polymorphisms and other neurotransmitter gene candidates

SLC6A3 and body mass index in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial

<p>Abstract</p> <p>Background</p> <p>To investigate the contribution of the dopamine transporter to dopaminergic reward-related behaviors and anthropometry, we evaluated associations between polymorphisms at the dopamine transporter gene(<it>SLC6A3</it>) and body mass index (BMI), among participants in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.</p> <p>Methods</p> <p>Four polymorphisms (rs6350, rs6413429, rs6347 and the 3' variable number of tandem repeat (3' VNTR) polymorphism) at the <it>SLC6A3 </it>gene were genotyped in 2,364 participants selected from the screening arm of PLCO randomly within strata of sex, age and smoking history. Height and weight at ages 20 and 50 years and baseline were assessed by questionnaire. BMI was calculated and categorized as underweight, normal, overweight and obese (<18.5, 18.5–24.9, 25.0–29.9, or ≥ 30 kg/m², respectively). Odds ratios (ORs) and 95% confidence intervals (CIs) of <it>SLC6A3 </it>genotypes and haplotypes were computed using conditional logistic regression.</p> <p>Results</p> <p>Compared with individuals having a normal BMI, obese individuals at the time of the baseline study questionnaire were less likely to possess the <it>3' </it>VNTR variant allele with 9 copies of the repeated sequence in a dose-dependent model (** is referent; OR_*9= 0.80, OR₉₉= 0.47, p_trend= 0.005). Compared with individuals having a normal BMI at age 50, overweight individuals (A-C-G-* is referent; OR_A-C-G-9= 0.80, 95% CI 0.65–0.99, p = 0.04) and obese individuals (A-C-G-* is referent; OR_A-C-G-9= 0.70, 95% CI 0.49–0.99, p = 0.04) were less likely to possess the haplotype with the 3'variant allele (A-C-G-9).</p> <p>Conclusion</p> <p>Our results support a role of genetic variation at the dopamine transporter gene, <it>SLC6A3</it>, as a modifier of BMI.</p

A method for comparing intra-tumoural radioactivity uptake heterogeneity in preclinical positron emission tomography studies

BACKGROUND: Non-uniformity influences the interpretation of nuclear medicine based images and consequently their use in treatment planning and monitoring. However, no standardised method for evaluating and ranking heterogeneity exists. Here, we have developed a general algorithm that provides a ranking and a visualisation of the heterogeneity in small animal positron emission tomography (PET) images. METHODS: The code of the algorithm was written using the Matrix Laboratory software (MATLAB). Parameters known to influence the heterogeneity (distances between deviating peaks, gradients and size compensations) were incorporated into the algorithm. All data matrices were mathematically constructed in the same format with the aim of maintaining overview and control. Histograms visualising the spread and frequency of contributions to the heterogeneity were also generated. The construction of the algorithm was tested using mathematically generated matrices and by varying post-processing parameters. It was subsequently applied in comparisons of radiotracer uptake in preclinical images in human head and neck carcinoma and endothelial and ovarian carcinoma xenografts. RESULTS: Using the developed algorithm, entire tissue volumes could be assessed and gradients could be handled in an indirect manner. Similar-sized volumes could be compared without modifying the algorithm. Analyses of the distribution of different tracers gave results that were generally in accordance with single plane preclinical images, indicating that it could appropriately handle comparisons of targeting vs. non-targeting tracers and also for different target levels. Altering the reconstruction algorithm, pixel size, tumour ROI volumes and lower cut-off limits affected the calculated heterogeneity factors in expected directions but did not reverse conclusions about which tumour was more or less heterogeneous. CONCLUSIONS: The algorithm constructed is an objective and potentially user-friendly tool for one-to-one comparisons of heterogeneity in whole similar-sized tumour volumes in PET imaging