Genotype-Environment Interaction Analysis of NQO1, CYP2E1, and NAT2 Polymorphisms and the Risk of Childhood Acute Lymphoblastic Leukemia: A Report From the Mexican Interinstitutional Group for the Identification of the Causes of Childhood Leukemia

Background: Acute lymphoblastic leukemia (ALL) is the main type of cancer in children. In Mexico and other Hispanic populations, the incidence of this neoplasm is one of the highest reported worldwide. Functional polymorphisms of various enzymes involved in the metabolism of xenobiotics have been associated with an increased risk of developing ALL, and the risk is different by ethnicity. The aims of the present study were to identify whether NQO1, CYP2E1, and NAT2 polymorphisms or some genotype-environmental interactions were associated with ALL risk in Mexican children.

Methods: We conducted a case-control study including 478 pediatric patients diagnosed with ALL and 284 controls (children without leukemia). Ancestry composition of a subset of cases and controls was assessed using 32 ancestry informative markers. Genetic-environmental interactions for the exposure to hydrocarbons were assessed by logistic regression analysis.

Results: The polymorphisms rs1801280 (OR 1.54, 95% CI 1.21–1.93), rs1799929 (OR 1.96, 95% CI 1.55–2.49), and rs1208 (OR 1.44, 95% CI 1.14–1.81) were found to increase the risk of ALL; being the risks higher under a recessive model (OR 2.20, 95% CI 1.30–1.71, OR 3.87, 95% CI 2.20–6.80, and OR 2.26, 95% CI 1.32–3.87, respectively). Gene-environment interaction analysis showed that NAT2 rs1799929 TT genotype confers high risk to ALL under exposure to fertilizers, insecticides, hydrocarbon derivatives, and parental tobacco smoking. No associations among NQO1, CYP2E1, and ALL were observed.

Conclusion: Our study provides evidence for the association between NAT2 polymorphisms/gene-environment interactions, and the risk of childhood ALL in Mexican children.

Altered activity of xenobiotic detoxifying enzymes at menopause - A cross-sectional study

Xenobiotic metabolism at menopause is an under-investigated topic, albeit women spend one-third of their life in the postmenopausal period. The present study examined the effect of menopause on the in vivo activities of CYP1A2, CYP2A6, xanthine oxidase (XO) and N-acetyltransferase-2 (NAT2) xenobiotic metabolizing enzymes. Enzyme activity was determined in 152 non-smoking volunteers following oral intake of a single dose of 200 mg caffeine and subsequent determination of caffeine metabolite ratios (CMRs) in a 6-h urine sample as follows: CYP1A2: (AFMU+1U+1X)/17U, CYP2A6: 17U/(17U + 17X), XO: 1U/(1U+1X) and NAT2: AFMU/(AFMU+1U+1X). CMRs among groups were analyzed using one-way ANOVA. Significantly lower CYP1A2 and higher CYP2A6 CMRs were observed in postmenopausal compared to premenopausal women and age-matched men. These changes could be attributed to menopause rather than chronological aging since an age-related effect was not observed in premenopausal women or men of any age group. XO CMRs were higher in postmenopausal women and men>50 compared to premenopausal women and men<50, respectively, suggesting an age-related increase in XO activity. No significant alterations were discerned in NAT2 CMRs, in either slow- or rapid-acetylators, indicating that menopause exerts minimal modulation of xenobiotics metabolized by this enzyme. This study provides evidence that the transition to menopause induces significant alterations in xenobiotic-metabolizing enzymes independent of chronological aging suggesting altered metabolism of pharmaceutical and environmental agents.

Study of correlation between the NAT2 phenotype and genotype status among Greenlandic Inuit

N-acetyltransferase 2 (NAT2) is the main enzyme metabolizing isoniazid and genotype-based treatment has been studied for years without becoming common practice. To investigate whether genotype-based isoniazid treatment is feasible in Greenland, we sequenced the coding sequence of NAT2 and determined the NAT2 enzyme-activity by caffeine test. No additional genetic variants were identified in the coding sequence of NAT2, so that genotype status in 260 study participants could be assessed by a well-established 7-SNP panel. Studying the enzyme activity by the ratio of the two caffeine metabolites AFMU and 1X in 260 participants showed a high rate of slow phenotypes with intermediate or rapid genotype. These misclassifications were mainly observed in urine samples with pH<3, a deviation from the standard protocol due to the field work character of the study, where immediate pH adjustment to pH=3.5 was not possible. We excluded these samples. For the remaining 143 individuals with pH>3, we observed a moderate level of discrepancies (19 of the 116 individuals with intermediate or rapid genotype status having a slow phenotype). Further investigation showed that drinking coffee and not tea or cola was the most important factor for high levels of both metabolites. The concordance between phenotype and genotype status with regard to slow metabolism supported the recommendation of lower isoniazid doses in individuals with slow genotype status in order to avoid liver injury, a frequent side effect. The phenotypical variation observed for individuals with intermediate or rapid genotype status warrants further research before increased dosing of isoniazid can be recommended.

N-Acetyltransferase-2 (NAT2) phenotype is influenced by genotype-environment interaction in Ethiopians

BACKGROUND AND OBJECTIVES

N-acetyltransferase 2 (NAT2) metabolize several drugs including isoniazid. We investigated the effect of genotype, geographical difference, and smoking habit on NAT2 phenotype in Ethiopians.

METHODS

Genotyping for NAT2 191G > A, 341 T > C, 590G > A, and 857G > A was performed in 163 unrelated healthy Ethiopians (85 living in Ethiopia and 78 living in Sweden). The NAT2 phenotype was determined using caffeine as a probe and log AFMU/(AFMU + 1X + 1 U) urinary metabolic ratio (MR) as an index.

RESULTS

The frequencies of NAT2*4, *5, *6, *7, and *14 haplotypes were 14.1, 48.5, 30.1, 5.5, and 1.8%, respectively. The frequencies of rapid (NAT2*4/*4), intermediate (heterozygous *4), and slow (no *4 allele) acetylator genotypes were 1.8, 24.6, and 73.6%, respectively. The distribution NAT2 MR was bimodal with 70% being phenotypically slow acetylators. NAT2 genotype (p < 0.0001) and country of residence (p = 0.004) independently predicted NAT2 phenotype. Controlling for the effect of genotype, ethnic Ethiopians living in Ethiopia had significantly higher NAT2 MR than those living in Sweden (p = 0.006). NAT2 genotype-phenotype concordance rate was 75%. Distinct country-of-residence-based genotype-phenotype discordance was observed. The proportion of phenotypically determined rapid acetylators was significantly higher and slow acetylators was lower in Ethiopians living in Ethiopia (39% rapid, 61% slow) than in Sweden (20% rapid, 80% slow). Sex and smoking had no significant effect on NAT2 MR.

CONCLUSIONS

We report a high prevalence of NAT 2 slow acetylators in Ethiopians and a conditional NAT2 genotype-phenotype discordance implicating a partial phenotype conversion and metabolic adaptation. Gene-environment interactions regulate NAT2 phenotype.

Interindividual Differences in Caffeine Metabolism and Factors Driving Caffeine Consumption

Most individuals adjust their caffeine intake according to the objective and subjective effects induced by the methylxanthine. However, to reach the desired effects, the quantity of caffeine consumed varies largely among individuals. It has been known for decades that the metabolism, clearance, and pharmacokinetics of caffeine is affected by many factors such as age, sex and hormones, liver disease, obesity, smoking, and diet. Caffeine also interacts with many medications. All these factors will be reviewed in the present document and discussed in light of the most recent data concerning the genetic variability affecting caffeine levels and effects at the pharmacokinetic and pharmacodynamic levels that both critically drive the level of caffeine consumption. The pharmacokinetics of caffeine are highly variable among individuals due to a polymorphism at the level of the CYP1A2 isoform of cytochrome P450, which metabolizes 95% of the caffeine ingested. Moreover there is a polymorphism at the level of another critical enzyme, N-acetyltransferase 2. At the pharmacodynamic level, there are several polymorphisms at the main brain target of caffeine, the adenosine A2A receptor or ADORA2. Genetic studies, including genome-wide association studies, identified several loci critically involved in caffeine consumption and its consequences on sleep, anxiety, and potentially in neurodegenerative and psychiatric diseases. We start reaching a better picture on how a multiplicity of biologic mechanisms seems to drive the levels of caffeine consumption, although much more knowledge is still required to understand caffeine consumption and effects on body functions.

Studies on N-Acetyltransferase (NAT2) Genotype Relationships in Emiratis: Confirmation of the Existence of Phenotype Variation among Slow Acetylators

BACKGROUND AND PURPOSE

Individuals with slow N-acetylation phenotype often experience toxicity from drugs such as isoniazid, sulfonamides, procainamide, and hydralazine, whereas rapid acetylators may not respond to these medications. The highly polymorphic N-acetyltransferase 2 enzyme encoded by the NAT2 gene is one of the N-acetylators in humans with a clear impact on the metabolism of a significant number of important drugs. However, there are limited studies on N-acetylation phenotypes and NAT2 genotypes among Emiratis, and thus this study was carried out to fill this gap.

METHODS

Five hundred seventy-six Emirati subjects were asked to consume a soft drink containing caffeine (a nontoxic and reliable probe for predicting the acetylation phenotype) and then provide a buccal swab along with a spot urine sample. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to determine the genotype of each individual. Phenotyping was carried out by analyzing the caffeine metabolites using high-performance liquid chromatography (HPLC) analysis.

RESULTS

We found that 78.5%, 19.1%, and 2.4% of the Emirati subjects were slow, intermediate, and rapid acetylators, respectively. In addition, we found that 77.4% of the subjects were homozygous or heterozygous for two nonreference alleles, whereas 18.4% and 4.2% were heterozygous or homozygous for the reference allele (NAT2*4), respectively. The most common genotypes found were NAT2*5B/*7B, NAT2*5B/*6A, NAT2*7B/*14B, and NAT2*4/*5B, with frequencies of 0.255, 0.135, 0.105, and 0.09, respectively. The degree of phenotype/genotype concordance was 96.2%. The NAT2*6A/*6A, NAT2*6A/*7B, NAT2*7B/*7B, and NAT2*5A/*5B genotypes were found to be associated with the lowest 5-acetylamino-6-formylamino-3-methyluracil/1-methylxanthine (AFMU/1X) ratios.

CONCLUSIONS

There is a high percentage of slow acetylators among Emiratis, which correlates with the presence of nonreference alleles for the NAT2 gene. Individuals who carried NAT2*6A/*6A, NAT2*6A/*7B, NAT2*7B/*7B, or NAT2*5A/*5B genotypes might be at higher risk of toxicity with some drugs and some diseases compared to others, as these genotypes are associated with the slowest acetylation status.

Caffeine Consumption Contributes to Skin Intrinsic Fluorescence in Type 1 Diabetes

BACKGROUND

A variant (rs1495741) in the gene for the N-acetyltransferase 2 (NAT2) protein is associated with skin intrinsic fluorescence (SIF), a noninvasive measure of advanced glycation end products and other fluorophores in the skin. Because NAT2 is involved in caffeine metabolism, we aimed to determine whether caffeine consumption is associated with SIF and whether rs1495741 is associated with SIF independently of caffeine.

MATERIALS AND METHODS

SIF was measured in 1,181 participants with type 1 diabetes from the Epidemiology of Diabetes Interventions and Complications study. Two measures of SIF were used: SIF1, using a 375-nm excitation light-emitting diode (LED), and SIF14 (456-nm LED). Food frequency questionnaires were used to estimate mean caffeine intake. To establish replication, we examined a second type 1 diabetes cohort.

RESULTS

Higher caffeine intake was significantly associated with higher SIF1(LED 375 nm[0.6, 0.2]) (P=2×10(-32)) and SIF14L(ED 456 nm[0.4, 0.8]) (P=7×10(-31)) and accounted for 4% of the variance in each after adjusting for covariates. When analyzed together, caffeine intake and rs1495741 both remained highly significantly associated with SIF1(LED 375 nm[0.6, 0.2]) and SIF14(LED 456 nm[0.4, 0.8]). Mean caffeinated coffee intake was also positively associated with SIF1(LED 375 nm[0.6, 0.2]) (P=9×10(-12)) and SIF14(LED 456 nm[0.4, 0.8]) (P=4×10(-12)), but no association was observed for decaffeinated coffee intake. Finally, caffeine was also positively associated with SIF1(LED 375 nm[0.6, 0.2]) and SIF14(LED 456 nm[0.4, 0.8]) (P<0.0001) in the replication cohort.

CONCLUSIONS

Caffeine contributes to SIF. The effect of rs1495741 on SIF appears to be partially independent of caffeine consumption. Because SIF and coffee intake are each associated with cardiovascular disease, our findings suggest that accounting for coffee and/or caffeine intake may improve risk prediction models for SIF and cardiovascular disease in individuals with diabetes.