Simultaneous determination of human plasma levels of citalopram, paroxetine, sertraline, and their metabolites by gas chromatography-mass spectrometry.

A gas chromatography-mass spectrometry method is presented which allows the simultaneous determination of the plasma concentrations of the selective serotonin reuptake inhibitors citalopram, paroxetine, sertraline, and their pharmacologically active N-demethylated metabolites (desmethylcitalopram, didesmethylcitalopram, and desmethylsertraline) after derivatization with the reagent N-methyl-bis(trifluoroacetamide). No interferences from endogenous compounds are observed following the extraction of plasma samples from six different human subjects. The standard curves are linear over a working range of 10-500 ng/mL for citalopram, 10-300 ng/mL for desmethylcitalopram, 5-60 ng/mL for didesmethylcitalopram, 20-400 ng/mL for sertraline and desmethylsertraline, and 10-200 ng/mL for paroxetine. Recoveries measured at three concentrations range from 81 to 118% for the tertiary amines (citalopram and the internal standard methylmaprotiline), 73 to 95% for the secondary amines (desmethylcitalopram, paroxetine and sertraline), and 39 to 66% for the primary amines (didesmethylcitalopram and desmethylsertraline). Intra- and interday coefficients of variation determined at three concentrations range from 3 to 11% for citalopram and its metabolites, 4 to 15% for paroxetine, and 5 to 13% for sertraline and desmethylsertraline. The limits of quantitation of the method are 2 ng/mL for citalopram and paroxetine, 1 ng/mL for sertraline, and 0.5 ng/mL for desmethylcitalopram, didesmethylcitalopram, and desmethylsertraline. No interferences are noted from 20 other psychotropic drugs. This sensitive and specific method can be used for single-dose pharmacokinetics. It is also useful for therapeutic drug monitoring of these three drugs and could possibly be adapted for the quantitation of the two other selective serotonin reuptake inhibitors on the market, namely fluoxetine and fluvoxamine.

Novel method to estimate the phenotypic variation explained by genome-wide association studies reveals large fraction of the missing heritability.

Genome-wide association studies (GWAS) are conducted with the promise to discover novel genetic variants associated with diverse traits. For most traits, associated markers individually explain just a modest fraction of the phenotypic variation, but their number can well be in the hundreds. We developed a maximum likelihood method that allows us to infer the distribution of associated variants even when many of them were missed by chance. Compared to previous approaches, the novelty of our method is that it (a) does not require having an independent (unbiased) estimate of the effect sizes; (b) makes use of the complete distribution of P-values while allowing for the false discovery rate; (c) takes into account allelic heterogeneity and the SNP pruning strategy. We applied our method to the latest GWAS meta-analysis results of the GIANT consortium. It revealed that while the explained variance of genome-wide (GW) significant SNPs is around 1% for waist-hip ratio (WHR), the observed P-values provide evidence for the existence of variants explaining 10% (CI=[8.5-11.5%]) of the phenotypic variance in total. Similarly, the total explained variance likely to exist for height is estimated to be 29% (CI=[28-30%]), three times higher than what the observed GW significant SNPs give rise to. This methodology also enables us to predict the benefit of future GWA studies that aim to reveal more associated genetic markers via increased sample size.