Quantifying absolute glutamate concentrations in nucleus accumbens of prescription opioid addicts by using 1H MRS.

INTRODUCTION: The diagnosis of psychoactive substance use disorders has been based primarily on descriptive, symptomatic checklist criteria. In opioid addiction, there are no objective biological indicators specific enough to guide diagnosis, monitor disease status, and evaluate efficacy of therapeutic interventions. Proton magnetic resonance spectroscopy (1H MRS) of the brain has potential to identify and quantify biomarkers for the diagnosis of opioid dependence. The purpose of this study was to detect the absolute glutamate concentration in the nucleus accumbens (NAc) of patients with prescription opioid dependence using 1H MRS, and to analyze its clinical associations. METHODS: Twenty patients with clinically diagnosed definitive prescription opioid dependent (mean age = 26.5 ± 4.3 years) and 20 matched healthy controls (mean age = 26.1 ± 3.8 years) participated in this study. Patients were evaluated with the Barratt Impulsiveness Scale (BIS-11), the Self-Rating Anxiety Scale (SAS), and the opiate Addiction Severity Inventory (ASI). We used point-resolved spectroscopy to quantify the absolute concentrations of metabolites (glutamate, choline, N-acetylaspartate, glutamine, creatine) within the NAc. The difference between metabolite levels of groups and Pearson's correlation between glutamate levels and psychometric scores in patients were analyzed statistically. RESULTS: Glutamate concentrations in the NAc were significantly higher in prescription opiate addicts than in controls (t = 3.84, p = .001). None of the other metabolites differed significantly between the two groups (all ps > .05). The glutamate concentrations correlated positively with BIS-11 scores in prescription opiate addicts (r = .671, p = .001), but not with SAS score and ASI index. CONCLUSIONS: Glutamate levels in the NAc measured quantitatively with in vivo 1H MRS could be used as a biomarker to evaluate disease condition in opioid-dependent patients.

Improving QTL mapping resolution based on genotypic sampling--a case using a RIL population.

The QTL mapping results were compared with the genotypically selected and random samples of the same size on the base of a RIL population. The results demonstrated that there were no obvious differences in the trait distribution and marker segregation distortion between the genotypically selected and random samples with the same population size. However, a significant increase in QTL detection power, sensitivity, specificity, and QTL resolution in the genotypically selected samples were observed. Moreover, the highly significant effect was detected in small size of genotypically selected samples. In QTL mapping, phenotyping is a more sensitive limiting factor than genotyping so that the selection of samples could be an attractive strategy for increasing genome-wide QTL mapping resolution. The efficient selection of samples should be more helpful for QTL maker assistant selection, fine mapping, and QTL cloning.