David Worth

Brain cyclosporin A levels are determined by ontogenic regulation of mdr1a expression.

Cyclosporin A (CyA) toxicity is a common occurrence in pediatric organ transplant patients. We hypothesized that reduced mdr1a expression in newborn and developing mice would affect CyA accumulation within organs and/or toxicity. For functional studies, CyA was administered (5 mg kg–1 i.p.) to 1-, 12-, and 19-day, and adult male and female mdr1a+/+ and mdr1a–/– mice. Peak blood CyA was lower in 1-, 12-, and 19-day-old (1000 ng ml–1) versus adult (1500 ng ml–1) mice but was similar in mdr1a+/+ and mdr1a–/– mice. Kidney mdr1a expression (measured by quantitative polymerase chain reaction) increased 2.5-fold in 19-day-old male and female mice and increased another 4-fold in adult females compared with adult males. Liver mdr1a expression increased 6-fold by day 12 compared with neonatal mice. Thereafter, maintenance of hepatic mdr1a expression in females and a reduction to neonatal levels in males was observed. Kidney/blood (8- to 9-fold) and liver/blood (12- to 15-fold) CyA levels were highest on days 12 and 19 and were not dependent on maturational changes in mdr1a mRNA levels. Adults had higher brain expression of mdr1a mRNA (3-fold), a corresponding 5-fold increase in immunodetectable P-glycoprotein, and 80% lower brain accumulation of CyA compared with 1-day-old mice. Conversely, in mdr1a-null mice, brain/blood CyA was similar in newborn and adult mice. A similar pattern was observed for the brain accumulation of the mdr1a substrate 3H-digoxin. We conclude that the risk for central nervous system drug toxicity could be higher in neonates or young children as a consequence of underdeveloped P-glycoprotein.

Drug and chemical metabolites in clinical toxicology investigations: The importance of ethylene glycol, methanol and cannabinoid metabolite analyses

Metabolic pathways in humans have been elucidated for most therapeutic drugs, drugs of abuse, and various chemical/solvents. In most drug overdose cases and chemical exposures, laboratory analysis is directed toward identification and quantitation of the unchanged drug or chemical in a biologic fluid such as serum or whole blood. Specifically, most clinical laboratories routinely screen and quantitate unchanged methanol and/or ethylene glycol in suspected poisonings without toxic metabolite analysis. Martin-Amat established in 1978 that methanol associated toxicity to the optic nerve in human poisonings was due to the toxic metabolite formic acid found in methanol poisonings and not due to the direct action by unchanged methanol. Jacobsen reported in 1981 that ethylene glycol central nervous system and renal toxicity were primarily due to one acidic metabolite (glycolic acid) and not due to unchanged ethylene glycol. The first objective of this review is to describe clinical experience with formic acid and glycolic acid analysis in methanol and ethylene glycol human poisonings. Drug metabolite analysis also provides useful information in the assessment and monitoring of drug use in psychiatry and substance abusing populations. Drug analysis in substance abuse monitoring is focused on urine analysis of one or more major metabolites, and less frequently on the unchanged drug(s). Serial monitoring of the major urinary cannabinoid metabolite (delta(9)-THC-COOH) to creatinine ratios in paired urine specimens (collected at least 24 h apart) could differentiate new marijuana or hashish use from residual cannabinoid metabolite excretion in urine after drug use according to Huestis. The second objective is to demonstrate that creatinine corrected urine specimens positive for cannabinoids may help differentiate new marijuana use from the excretion of residual delta(9) -THC-COOH in chronic users of marijuana or hashish. Analysis of toxic chemical metabolites are helpful in the assessment and treatment of chemical poisoning whereas serial monitoring of urinary cannabinoid metabolites are predictive of illicit drug use in the substance abusing population.

Urinary excretion profiles of 11-nor-9-carboxy-Δ9-tetrahydrocannabinol: a Δ9-THC-COOH to creatinine ratio study #2

Huestis and Cone reported in [J. Anal. Toxicol. 22 (1998) 445] that serial monitoring of Delta9-THC-COOH/creatinine ratios in paired urine specimens collected at least 24h apart could differentiate new drug use from residual Delta(9)-THC-COOH excretion following acute marijuana use in a controlled setting. The best accuracy (85.4%) for predicting new marijuana use was for a Delta(9)-THC-COOH/creatinine ratio > or = 0.5 (dividing the Delta9-THC-COOH/creatinine ratio of specimen no. 2 by the specimen no. 1 ratio). In previous studies in this laboratory [J. Anal. Toxicol. 23 (1999) 531 and Forensic Sci. Int. 133 (2003) 26], urine specimens were collected from chronic marijuana users > or = 24 h or > = 48 h apart in an uncontrolled setting. Subjects with a history of chronic marijuana use were screened for cannabinoids with the EMIT II Plus cannabinoids assay (cut-off 50 ng/ml) followed by confirmation for Delta9-THC-COOH by GC-MS (cut-off 15 ng/ml). Creatinine was analyzed as an index of dilution. The objective of the present study was to evaluate whether creatinine corrected specimens could differentiate new marijuana or hashish use from the excretion of residual Delta(9)-THC-COOH in chronic marijuana users based on the Huestis 0.5 ratio. Urine specimens (N=376) were collected from 29 individuals > or = 96 h between urine collections. The mean urinary Delta9-THC-COOH concentration was 464.4 ng/ml, mean Delta9-THC-COOH/creatinine ratio (ng/(ml Delta9-THC-COOH mmoll creatinine)) was 36.8 and the overall mean Delta9-THC-COOH/creatinine ratio of specimen 2/mean Delta9-THC-COOH/creatinine ratio of specimen 1 was 1.37. The Huestis ratio calculation indicated new drug use in 83% of all sequentially paired urine specimens. The data were sub-divided into three groups (Groups A-C) based on mean Delta9-THC-COOH/creatinine values. Interindividual mean Delta9-THC-COOH/creatinine values ranged from 4.7 to 13.4 in Group A where 80% of paired specimens indicated new drug use (N=10) and 20.4-39.6 in Group B where 83.6% of paired specimens indicated new drug use (N=7). Individual mean Delta9-THC-COOH/creatinine values ranged from 44.2 to 120.2 in Group C where 84.5% of paired urine specimens indicated new marijuana use (N=12). Correcting Delta9-THC-COOH excretion for urinary dilution and comparing Delta9-THC-COOH/creatinine concentration ratios of sequentially paired specimens (collected > or = 96 h apart) may provide an objective indicator of ongoing marijuana or hashish use in this population.

Monitoring urinary excretion of cannabinoids by fluorescence-polarization immunoassay: a cannabinoid-to-creatinine ratio study.

Drug testing in substance abuse treatment programs is focused on urine analysis of parent drugs and major metabolites. Huestis reported that serial monitoring of the major urinary cannabinoid metabolite (&Dgr;9-THC-COOH)-to-creatinine ratios in paired urine specimens (collected at least 24 hours apart) could differentiate new marijuana or hashish use from residual cannabinoid metabolite excretion in urine after previous drug use. Subjects with a history of chronic marijuana use were screened for cannabinoids in urine over several months by an enzyme immunoassay (EMIT) with a cut-off value of 50 ng/mL. Presumptive positive specimens were confirmed by gas chromatography–mass spectrometry (GC-MS) for &Dgr;9-THC-COOH with a cut-off value of 15 ng/mL. The objective of this study was to determine whether a semiquantitative cannabinoids immunoassay (corrected for creatinine concentration) could differentiate new marijuana use from residual cannabinoid excretion in chronic users of marijuana or hashish compared with GC-MS. The criterion for new marijuana use was a cannabinoid-to-creatinine ratio ≥0.5 (dividing the immunoassay quantitative result to creatinine ratio of specimen 2 by the specimen 1 ratio, specimen 3 by the specimen 2 ratio, etc.). Urine specimens were analyzed by fluorescence-polarization immunoassay (FPIA) on an Abbott TDxFLx analyzer after analysis by GC-MS. In 90 urine specimens (group A) with &Dgr;9-THC-COOH values determined by GC-MS, the mean &Dgr;9-THC-COOH concentration was 44.4 ng/mL (range, 16–100), and the mean FPIA total cannabinoids value was 91.7 ng/mL (range, 21–204 ng/mL) with a correlation coefficient of 0.993 (group A). In 111 specimens (group B), the mean &Dgr;9-THC-COOH concentration was 361 ng/mL (range, 101–960 ng/mL). The mean FPIA value was 657 ng/mL (range, 211–1,270 ng/mL), and the correlation coefficient of the B series was 0.975. Percent cross-reactivity for &Dgr;9-THC-COOH standards prepared in drug-free urine by FPIA was 82% at 25 ng/mL, 45% at 50 ng/mL, and 50% at 100 ng/mL. Overall, there was 89% agreement (132 of 148 specimens) between FPIA and GC-MS. In 16 of 148 specimens, however, the FPIA and GC-MS paired urine data did not agree. The sensitivity of the FPIA assay was 95.3%, and the specificity was 44.4%. The authors conclude that FPIA cannabinoid analysis should be further evaluated as an alternative to GC-MS quantitation to help distinguish new marijuana use from residual marijuana metabolite excretion in clinical drug treatment programs.