3,4-Dehydrodebrisoquine, a novel debrisoquine metabolite formed from 4-hydroxydebrisoquine that affects the CYP2D6 metabolic ratio

Considerable unexplained intersubject variability in the debrisoquine metabolic ratio (urinary debrisoquine/4-hydroxydebrisoquine) exists within individual CYP2D6 genotypes. We speculated that debrisoquine was converted to as yet undisclosed metabolites. Thirteen healthy young volunteers, nine CYP2D6*1 homozygotes [extensive metabolizers (EMs)] and four CYP2D6*4 homozygotes [poor metabolizers (PMs)] took 12.8 mg of debrisoquine hemisulfate by mouth and collected 0- to 8- and 8- to 24-h urines, which were analyzed by gas chromatography-mass spectrometry (GCMS) before and after treatment with beta-glucuronidase. Authentic 3,4-dehydrodebrisoquine was synthesized and characterized by GCMS, liquid chromatography-tandem mass spectrometry, and (1)H NMR. 3,4-Dehydrodebrisoquine is a novel metabolite of debrisoquine excreted variably in 0- to 24-h urine, both in EMs (3.1-27.6% of dose) and PMs (0-2.1% of dose). This metabolite is produced from 4-hydroxydebrisoquine in vitro by human and rat liver microsomes. A previously unstudied CYP2D6*1 homozygote was administered 10.2 mg of 4-hydroxydebrisoquine orally and also excreted 3,4-dehydrodebrisoquine. EMs excreted 6-hydroxydebrisoquine (0-4.8%) and 8-hydroxydebrisoquine (0-1.3%), but these phenolic metabolites were not detected in PM urine. Debrisoquine and 4-hydroxydebrisoquine glucuronides were excreted in a highly genotype-dependent manner. A microsomal activity that probably does not involve cytochrome P450 participates in the further metabolism of 4-hydroxydebrisoquine, which we speculate may also lead to the formation of 1- and 3-hydroxydebrisoquine and their ring-opened products. In conclusion, this study suggests that the traditional metabolic ratio is not a true measure of the debrisoquine 4-hydroxylation capacity of an individual and thus may, in part, explain the wide intragenotype variation in metabolic ratio.

In bacterial meningitis cortical brain damage is associated with changes in parenchymal MMP-9/TIMP-1 ratio and increased collagen type IV degradation

Adverse outcome in bacterial meningitis is associated with the breakdown of the blood-brain barrier (BBB). Matrix-metalloproteinases (MMPs) facilitate this process by degradation of components of the BBB. This in turn results in acute complications of bacterial meningitis including edema formation, increased intracranial pressure and subsequent ischemia. We determined the parenchymal balance of MMP-9 and TIMP-1 (tissue inhibitor of MMP) and the structural integrity of the BBB in relation to cortical damage in an infant rat model of pneumococcal meningitis. The data demonstrate that the extent of cortical damage is significantly associated with parenchymal gelatinolytic activity and collagen type IV degradation. The increased gelatinolysis was found to be associated with a brain parenchymal imbalance of MMP-9/TIMP-1. These findings provide support to the concept that MMPs mediated disruption of the BBB contributes to the pathogenesis of bacterial meningitis and that protection of the vascular unit may have neuroprotective potential.

Limitations of the Odds Ratio in Gauging the Performance of a Diagnostic or Prognostic Marker

A marker that is strongly associated with outcome (or disease) is often assumed to be effective for classifying individuals according to their current or future outcome. However, for this to be true, the associated odds ratio must be of a magnitude rarely seen in epidemiological studies. An illustration of the relationship between odds ratios and receiver operating characteristic (ROC) curves shows, for example, that a marker with an odds ratio as high as 3 is in fact a very poor classification tool. If a marker identifies 10 percent of controls as positive (false positives) and has an odds ratio of 3, then it will only correctly identify 25 percent of cases as positive (true positives). Moreover, the authors illustrate that a single measure of association such as an odds ratio does not meaningfully describe a marker’s ability to classify subjects. Appropriate statistical methods for assessing and reporting the classification power of a marker are described. The serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated.