Impact of CYP2D6*2, CYP2D6*35, rs5758550, and related haplotypes on risperidone clearance in vivo.

PURPOSE: The CYP2D6 gene exhibits significant polymorphism, contributing to variability in responses to drugs metabolized by CYP2D6. While CYP2D6*2 and CYP2D6*35 are presently designated as alleles encoding normal metabolism, this classification is based on moderate level evidence. Additionally, the role of the formerly called "enhancer" single nucleotide polymorphism (SNP) rs5758550 is unclear. In this study, the impacts of CYP2D6*2, CYP2D6*35 and rs5758550 on CYP2D6 activity were investigated using risperidone clearance as CYP2D6 activity marker. METHODS: A joint parent-metabolite population pharmacokinetic model was used to describe 1,565 serum concentration measurements of risperidone and 9-hydroxyrisperidone in 512 subjects. Risperidone population clearance was modeled as the sum of a CYP2D6-independent clearance term and the partial clearances contributed from each individually expressed CYP2D6 allele or haplotype. In addition to the well-characterized CYP2D6 alleles (*3-*6, *9, *10 and *41), *2, *35 and two haplotypes assigned as CYP2D6*2-rs5758550G and CYP2D6*2-rs5758550A were evaluated. RESULTS: Each evaluated CYP2D6 allele was associated with significantly lower risperidone clearance than the reference normal function allele CYP2D6*1 (p < 0.001). Further, rs5758550 differentiated the effect of CYP2D6*2 (p = 0.005). The haplotype-specific clearances for CYP2D6*2-rs5758550A, CYP2D6*2-rs5758550G and CYP2D6*35 were estimated to 30%, 66% and 57%, respectively, relative to the clearance for CYP2D6*1. Notably, rs5758550 is in high linkage disequilibrium (R2 > 0.85) with at least 24 other SNPs and cannot be assigned as a functional SNP. CONCLUSION: CYP2D6*2 and CYP2D6*35 encode reduced risperidone clearance, and the extent of reduction for CYP2D6*2 is differentiated by rs5758550. Genotyping of these haplotypes might improve the precision of genotype-guided prediction of CYP2D6-mediated clearance.

Impact of the novel CYP2C:TG haplotype and CYP2B6 variants on sertraline exposure in a large patient population.

Sertraline is a commonly used SSRI antidepressant drug, metabolized by CYP2C19 and CYP2B6, that exhibits a substantial interindividual variation in clinical response, of which only a part can be attributed to known genetic variants. In the current study we have examined the role of a newly discovered ultrarapid CYP2C:TG haplotype and CYP2B6 variants in order to identify the possible missing heritability for such variation in sertraline response in a large patient population (n = 840). Compared to the reference group (CYP2C19*1/*1, n = 160), sertraline exposure was increased by 128% in CYP2C19 PMs (n = 29, p < 0.001) but decreased by about 20% in CYP2C19 ultrarapid metabolizers (Ums) (homozygous carriers of CYP2C19*17 and/or CYP2C:TG haplotype) with the diplotypes CYP2C19*17/*17, CYP2C:TG/TG, or CYP2C19*17/CYP2C:TG (n = 135, p < 0.003, p = 0.022, p < 0.003, respectively). Interestingly, in patients carrying the increased function CYP2B6*4 allele, and also carrying the CYP2C19*17 and CYP2C:TG alleles (n = 10), sertraline exposure was 35.4% lower compared to the reference group, whereas in subjects being poor metabolizers (PM) in both the CYP2C19 and CYP2B6 gene, the sertraline concentrations were raised by 189%. In summary, the CYP2C19 variants including the CYP2C:TG haplotype had a significant impact on sertraline metabolism, as well as the CYP2B6*4, *6, and *9 alleles. Knowing the CYP2B6 and CYP2C19 genotype, including the CYP2C:TG haplotype status, can prospectively be useful to clinicians in making more appropriate sertraline dosing decisions.

A Novel CYP2C-Haplotype Associated With Ultrarapid Metabolism of Escitalopram.

Escitalopram is one of the most commonly used antidepressant drugs but exhibits a substantial interindividual variation in clinical response. A key factor underlying response differences is the polymorphic nature of the CYP2C19 gene encoding the major enzyme responsible for escitalopram metabolism. Although pre-emptive CYP2C19 genotyping may improve escitalopram treatment outcome by dose individualization, much of the interindividual variability cannot be assigned to the currently known CYP2C19 gene variants. The aim of the present study was to search for novel CYP2C-haplotypes for better genetic prediction of escitalopram metabolism. First, the CYP2C18/CYP2C19 locus was sequenced from gDNA obtained from 24 patients previously genotyped as CYP2C19*1/*1 showing consistently low serum concentrations of escitalopram (< 25 nM/10 mg). Three new haplotypes of the CYP2C locus (CYP2C:TG, CYP2C:TA, and CYP2C:CG) were here identified, and their functional roles were evaluated using gDNA from 875 previously genotyped escitalopram-treated patients. The CYP2C:CG and CYP2C:TA haplotypes had no significant impact on escitalopram concentration. Based on the estimated effects of the novel CYP2C-haplotypes on escitalopram exposure, the predicted serum concentrations of escitalopram in homozygous CYP2C:TG and CYP2C19*17 carriers were 24.8% and 17.3% lower compared with the baseline (CYP2C:CG and CYP2C:TA), respectively. In conclusion, a novel CYP2C-haplotype defined by rs2860840T and rs11188059G associated with ultrarapid metabolism of escitalopram was identified. Further studies should clarify the genetic basis for the enhanced escitalopram metabolism and the impact of the CYP2C:TG haplotype on the metabolism of other CYP2C19 substrates like omeprazole, voriconazole, and clopidogrel.

Cecal microbiota association with tumor load in a colorectal cancer mouse model.

Background: Colorectal cancer (CRC) is one of the most common cancer types worldwide. The role of the intestinal microbiota in CRC, however, is not well established. In particular, the co-variation between age, tumor progression and microbiota remains largely unknown. Objective and design: We therefore used a recently developed A/J Min/+ mouse model resembling human CRC to investigate how microbial composition in cecum correlates with tumor progression, butyrate and age. Results: We found that the association between the gut microbiota and tumor load was stronger, by far, than the association with both butyrate and age. The strongest direct tumor association was found for mucosal bacteria, with nearly 60% of the significantly correlating operational taxonomic units being correlated with CRC tumor load alone. Conclusion: We favor a systemic association between tumor load and microbiota, since the correlations are associated with tumor load in gut segments other than the cecum (both small and large intestine).