Dataset Information

Association between Glucuronidation Genotypes and Urinary NNAL Metabolic Phenotypes in Smokers.

ABSTRACT: The most abundant and potent carcinogenic tobacco-specific nitrosamine in tobacco and tobacco smoke is 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). In vivo, NNK is rapidly metabolized to both the (R)- and (S)-enantiomers of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), which possesses similar carcinogenic properties as NNK. The major detoxification pathway for both NNAL enantiomers is glucuronidation by UDP-glucuronosyltransferase (UGT) enzymes including UGT2B10 and UGT2B17. The goal of the present study was to directly examine the role of UGT genotypes on urinary levels of NNAL glucuronides in smokers.NNAL-N-Gluc, (R)-NNAL-O-Gluc, (S)-NNAL-O-Gluc, and free NNAL were simultaneously and directly quantified in the urine of smokers by LC/MS analysis. Genotypes were determined by TaqMan assay using genomic DNA.The functional knockout polymorphism in the UGT2B10 gene at codon 67 (Asp>Tyr) was significantly (P < 0.0001) associated with a 93% decrease in creatinine-adjusted NNAL-N-Gluc. The polymorphic whole-gene deletion of the UGT2B17 gene was associated with significant (P = 0.0048) decreases in the levels of creatinine-adjusted (R)-NNAL-O-Gluc, with a 32% decrease in the levels of urinary (R)-NNAL-O-Gluc/(S)-NNAL-O-Gluc among subjects with the UGT2B17 (*2/*2) genotype as compared to subjects with the UGT2B17 (*1/*1) genotype.These results suggest that functional polymorphisms in UGT2B10 and UGT2B17 are associated with a reduced detoxification capacity against NNAL and may therefore affect individual cancer risk upon exposure to tobacco.This is the first report to clearly demonstrate strong genotype-phenotype associations between both the UGT2B10 codon 67 Asp

SUBMITTER: Chen G

PROVIDER: S-EPMC5087993 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Association between Glucuronidation Genotypes and Urinary NNAL Metabolic Phenotypes in Smokers.

Chen Gang G Luo Shaman S Kozlovich Shannon S Lazarus Philip P

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20160509 7

<h4>Background</h4>The most abundant and potent carcinogenic tobacco-specific nitrosamine in tobacco and tobacco smoke is 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). In vivo, NNK is rapidly metabolized to both the (R)- and (S)-enantiomers of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), which possesses similar carcinogenic properties as NNK. The major detoxification pathway for both NNAL enantiomers is glucuronidation by UDP-glucuronosyltransferase (UGT) enzymes including UGT2B ...[more]

PMID: 27197298

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Project description:Background & purposeObesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM.Patients & methodsWe analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk.ResultsThere were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively.ConclusionMetabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden.

Project description:Background Cytochrome P450 system is implicated in vascular pathologies, including stroke. Besides its role as a drug metabolizer, it also plays an important role in the metabolism of several endogenous substances like fatty acids, arachidonic acid, etc., which have pro-inflammatory effects. On the other hand, leptin and adiponectin are two of the most common adipose tissue-derived cytokines (adipokines), which are pro-inflammatory and anti-inflammatory in nature, respectively. Both of them are implicated in the pathogenesis of stroke. Methods We prospectively recruited ischemic stroke patients (within three months of occurrence of an attack of stroke). The occurrence of composite outcome (recurrence of transient ischemic attack/ischemic stroke or death) was evaluated for association with genetic variants of CYP2C19 (allele *2, *17, *3, and *4, i.e., single nucleotide polymorphism (SNP) 1/2/3/4, identified using TaqMan assays and DNA sequencing). Adiponectin and leptin levels were determined using an enzyme-linked immunosorbent assay. Comparisons were made between stroke vs. control patients and between CYP2C19 intermediate metabolizer (IM)/poor metabolizer (PM) vs. extensive metabolizer (EM)/ultra metabolizer (UM) (PM: *2/*2; IM: *1/*2 vs. EM: *1/*1; UM: *1/*17). P < 0.05 was taken as the threshold for statistical significance. Results A total of 204 patients and 101 controls were recruited. With regard to the occurrence of stroke, SNP2 showed a significant positive association. Haplotypes (SNP1/SNP2) AC (OR = 1.75 (1.08-2.83), p = 0.024) and GT (OR = 3.33 (1.53-7.22), p = 0.0026) were strongly associated with the occurrence of ischemic stroke even after adjustment for age and sex (global haplotype association p-value: 0.0062). Haplotype phenotype gender interaction was evident. Among stroke patients, with regard to composite outcome, only SNP1 showed a positive association. The AC haplotype was significantly associated with the occurrence of composite outcome (OR = 2.27 (1.17-4.41), p = 0.016). Among stroke patients, a significant positive association was seen between death and SNP1 (OR = 2.35 (1.13-4.90), p = 0.021) and AC haplotype (OR = 2.73 (1.20-6.22), p = 0.018). However, none of the SNPs or haplotypes showed any association with recurrence. Significant higher leptin and lower adiponectin levels were observed among stroke patients compared to controls. Leptin levels were higher in IM/PM group. IM/PM phenotypes showed a higher incidence of occurrence of composite outcome (hazard ratio = 2.07 (0.96-4.47), p = 0.056). Conclusion CYP2C19 polymorphisms may play a significant role in the pathogenesis of stroke. Leptin could serve as a prominent biomarker of atherosclerosis and inflammation in the early post-stroke period; however, further study is warranted with a larger sample size.

Project description:PurposeSerum uric acid (UA) not only affects the development of obesity but also alters the metabolic status in obese subjects; thus we investigated the relationship between serum UA and the overweight/obese metabolic phenotypes.MethodsThe demographic, biochemical, and hematological data were collected for 12,876 patients undergoing routine physical examination, and 6,912 participants were enrolled in our study. Participants were classified into four obesity metabolic phenotypes according to their BMI and the presence of metabolic syndrome: metabolically healthy overweight/obese (MHOO), metabolically healthy and normal weighted (MHNW), metabolically abnormal and overweight/obese (MAOO), and metabolically abnormal but normal weighted (MANW). Univariate and multivariate logistic regression analysis, stratified analysis, and also interaction analysis were conducted to analyze the relationship between serum UA and obesity metabolic phenotypes.ResultsMultivariable logistic regression analysis showed that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes relative to MHNW. After adjusting for the confounding factors, the odds ratios (OR) for individuals with hyperuricemia to be MHOO, MANW, and MAOO phenotypes were 1.86 (1.42-2.45), 2.30 (1.44-3.66), and 3.15 (2.34-4.24), respectively. The ORs for having MHOO, MANW, and MAOO increased 6% [OR: 1.06 (1.05-1.07), P < 0.0001], 5% [OR: 1.05 (1.03-1.07), P < 0.0001], and 11% [OR: 1.11 (1.10-1.13), P < 0.0001] for each 10 unit (μmol/L) of increase in serum UA level. Stratification analysis as well as an interaction test showed that sex and age did not interfere with the association of hyperuricemia with each metabolic phenotype. In terms of the components of the metabolic syndrome, after adjusting for other confounding factors including all of the metabolic indicators except itself, hyperuricemia was positively associated with increased BMI [OR: 1.66 (1.32-2.09), P < 0.0001], hypertriglyceridemia [OR: 1.56 (1.21-2.02), P = 0.0006], and hypertension [OR: 1.22 (1.03-1.46), P = 0.0233], while it had no significant association with hyperglycemia and low HDL-C (all P > 0.05).ConclusionIn our study, we discovered that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes, and this relationship was independent of sex and age.

Dataset Information

Association between Glucuronidation Genotypes and Urinary NNAL Metabolic Phenotypes in Smokers.

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Association between Glucuronidation Genotypes and Urinary NNAL Metabolic Phenotypes in Smokers.

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