Variation In Metabolism Genes Research Articles

Variants in Iron Metabolism Genes Predict Higher Blood Lead Levels in Young Children

BackgroundGiven the association between iron deficiency and lead absorption, we hypothesized that variants in iron metabolism genes would predict higher blood lead levels in young children.ObjectiveWe examined the association between common missense variants in the hemochromatosis (HFE) and transferrin (TF) genes and blood lead levels in 422 Mexican children.MethodsArchived umbilical cord blood samples were genotyped for HFE (H63D and C282Y) and TF (P570S) variants. Blood lead was measured at 24, 30, 36, 42, and 48 months of age. A total of 341 subjects had at least one follow-up blood lead level available and data available on covariates of interest for inclusion in the longitudinal analyses. We used random-effects models to examine the associations between genotype (HFE, TF, and combined HFE + TF) and repeated measures of blood lead, adjusting for maternal blood lead at delivery and child’s concurrent anemia status.ResultsOf 422 children genotyped, 17.7, 3.3, and 18.9% carried the HFE H63D, HFE C282Y, and TF P570S variants, respectively. One percent of children carried both the HFE C282Y and TF P570S variants, and 3% of children carried both the HFE H63D and TF P570S variants. On average, carriers of either the HFE (β = 0.11, p = 0.04) or TF (β = 0.10, p = 0.08) variant had blood lead levels that were 11% and 10% higher, respectively, than wild-type subjects. In models examining the dose effect, subjects carrying both variants (β = 0.41, p = 0.006) had blood lead 50% higher than wild-type subjects and a significantly higher odds of having a blood lead level > 10 μg/dL (odds ratio = 18.3; 95% confidence interval, 1.9–177.1).ConclusionsIron metabolism gene variants modify lead metabolism such that HFE variants are associated with increased blood lead levels in young children. The joint presence of variant alleles in the HFE and TF genes showed the greatest effect, suggesting a gene-by-gene-by-environment interaction.

Adaptations to climate in candidate genes for common metabolic disorders.

Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders.

Maternal Caffeine Intake, Selected Metabolic Gene Variants, and Neural Tube Defects (NTDs)

Using data from the National Birth Defects Prevention Study, we examined associations between NTDs and maternal caffeine intake, gene variants for caffeine metabolism, and their joint effects. Total average caffeine per day was summed from maternal interview reports of coffee, tea, soda, and chocolate intake. Buccal swab samples from infants and birth parents were genotyped for CYP1A2∗1F, NAT2 C481T and G590A, NAT1 C1095A and rs13278990. CYP1A2∗1F was classified by oxidation status (fast vs. slow) and NAT2 variants were categorized by acetylation status (rapid vs. slow). Logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) for total caffeine, each caffeine source, and maternal and infant gene variants. We also conducted family-based and hybrid log-linear analyses to examine the association of each gene variant with NTDs, and used case-control, case-only, and family-based methods to assess interaction effects between caffeine intake and each gene variant. We found an association between maternal caffeine intake and spina bifida (SB), which varied by caffeine source across multiple and isolated case status. Mothers who consumed caffeine and were CYP1A2∗1F fast oxidizers and NAT2 slow acetylators had the greatest estimated risk for an NTD-affected pregnancy, although interaction effects were significant only for infant CYP1A2∗1F fast oxidizer status. There was a significant association of maternal CYP1A2∗1F fast oxidation status with NTDs that was stronger for isolated cases, non-Hispanic White mothers, and mothers of CYP1A2∗1F fast oxidizing infants. Infant slow NAT2 acetylator status was significantly associated with an increased NTD risk in the family-based analyses. There was not strong evidence for an increased risk of NTDs associated with infant NAT1 C1095A. Maternal caffeine and its metabolites may be associated with increased risk for a NTD-affected pregnancy in certain subgroups. There is an association of maternal CYP1A2∗1F fast oxidation status with NTDs that should be examined further in the context of its other substrates.

Genetic polymorphism of xenobiotic metabolising enzymes, diet and cancer susceptibility.

There is increasing evidence identifying the crucial role of numerous dietary components in modifying the process of carcinogenesis. The varied effects exerted by nutrient and non-nutrient dietary compounds on human health and cancer risk are one of the new challenges for nutritional sciences. In the present paper, an attempt is made to review the most recent epidemiological data on interactions between dietary factors and metabolic gene variants in terms of cancer risk. The majority of case-control studies indicate the significant relationship between cancer risk and polymorphic xenobiotic metabolising enzymes in relation to dietary components. The risk of colorectal cancer is associated not only with CYP2E1 high-activity alleles, but also GSTA1 low-activity alleles, among consumers of red or processed meat. Genetic polymorphisms of NAT1 and NAT2 may be also a breast-cancer susceptibility factor among postmenopausal women with a high intake of well-done meat. On the other hand, phytochemicals, especially isothiocyanates, have a protective effect against colorectal and lung cancers in individuals lacking GST genes. Moreover, polymorphism of GSTM1 seems to be involved in the dietary regulation of DNA damage. The European Prospective Investigation into Cancer and Nutrition study shows a significant inverse association between the polycyclic aromatic hydrocarbon-DNA adduct level and dietary antioxidants only among GSTM1-null individuals. However, the absence of a modulatory effect of polymorphic xenobiotic metabolising enzymes and diet on the development of cancer has been indicated by some epidemiological investigations. Studies of interactions between nutrients and genes may have great potential for exploring mechanisms, identifying susceptible populations/individuals and making practical use of study results to develop preventive strategies beneficial to human health.

Developmental and genetic modulation of arsenic biotransformation: A gene by environment interaction?

The complexity of arsenic toxicology has confounded the identification of specific pathways of disease causation. One focal point of arsenic research is aimed at fully characterizing arsenic biotransformation in humans, a process that appears to be quite variable, producing a mixture of several arsenic species with greatly differing toxic potencies. In an effort to characterize genetic determinants of variability in arsenic biotransformation, a genetic association study of 135 subjects in western Sonora, Mexico was performed by testing 23 polymorphic sites in three arsenic biotransformation candidate genes. One gene, arsenic 3 methyltransferase (AS3MT), was strongly associated with the ratio of urinary dimethylarsinic acid to monomethylarsonic acid ( D/ M) in children (7–11 years) but not in adults (18–79 years). Subsequent analyses revealed that the high D/M values associated with variant AS3MT alleles were primarily due to lower levels of monomethylarsonic acid as percent of total urinary arsenic (%MMA5). In light of several reports of arsenic-induced disease being associated with relatively high %MMA5 levels, these findings raise the possibility that variant AS3MT individuals may suffer less risk from arsenic exposure than non-variant individuals. These analyses also provide evidence that, in this population, regardless of AS3MT variant status, children tend to have lower %MMA5 values than adults, suggesting that the global developmental regulation of arsenic biotransformation may interact with genetic variants in metabolic genes to result in novel genetic effects such as those in this report.

Metabolic Gene Variants and Risk of Non-Hodgkin's Lymphoma

Genes involved in metabolism of environmental chemical exposures exhibit sequence variability that may mediate the risk of non-Hodgkin's lymphoma. We evaluated associations between non-Hodgkin's lymphoma and 15 variants in AHR, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2E1, GSTP1, GSTM3, EPHX1, NQO1, and PON1. Cases were identified from four Surveillance, Epidemiology, and End Results registries in the United States, and population-based controls were identified through random-digit dialing and Medicare eligibility files. Metabolic gene variants were characterized for the 1,172 (89% of total) cases and 982 (93%) controls who provided biological samples for genotyping. Subjects who were heterozygous or homozygous for the cytochrome P450 gene variant CYP1B1 V432L G allele were at slightly greater risk of non-Hodgkin's lymphoma [odds ratio (OR), 1.27; 95% confidence interval (95% CI), 0.97-1.65]; these results were consistent across B-cell lymphoma subtypes and among both non-Hispanic White and Black subjects, although not statistically significant. The CYP2E1 -1054T allele was associated with decreased risk of non-Hodgkin's lymphoma (CT and TT genotypes combined OR, 0.59; 95% CI, 0.37-0.93), and this pattern was observed among all histologic subtypes. The numbers of cases of particular subtypes were rather small for stable estimates, but we noted that the PON1 L55M AA allele, associated with slightly increased risk of non-Hodgkin's lymphoma (variant homozygotes OR, 1.36; 95% CI, 0.96-1.95), was most strongly associated with follicular non-Hodgkin's lymphoma and T-cell lymphoma, with ORs for variant homozygotes of 2.12 and 2.93, respectively. There was no overall association with non-Hodgkin's lymphoma for the other gene variants we examined. The modest effects we observed may reflect the context of exposures within the general population represented in our study.

Genetic risk profiles for cancer susceptibility and therapy response

Cells in the body are permanently attacked by DNA-reactive species, both from intracellular and environmental sources. Inherited and acquired deficiencies in host defense mechanisms against DNA damage (metabolic and DNA repair enzymes) can modify cancer susceptibility as well as therapy response. Genetic profiles should help to identify high-risk individuals who subsequently can be enrolled in preventive measures or treated by tailored therapy regimens. Some of our attempts to define such risk profiles are presented. Cancer susceptibility: Single nucleotide polymorphisms (SNPs) in metabolic and repair genes were investigated in a hospital-based lung cancer case—control study. When evaluating the risk associated with different genotypes for N-acetyltransferases (Wikman et al. 2001) and glutathione-S-transferases (Risch et al. 2001), it is mandatory to distinguish between the three major histological subtypes of lung tumors. A promoter polymorphism of the myeloperoxidase gene MPO was shown to decrease lung cancer susceptibility mainly in small cell lung cancer (SCLC) (Dally et al. 2002). The CYP3A4*1B allele was also linked to an increased SCLC risk and in smoking women increased the risk of lung cancer eightfold (Dally et al. 2003b). Polymorphisms in DNA repair genes were shown to modulate lung cancer risk in smokers, and reduced DNA repair capacity elevated the disease risk (Rajaee-Behbahani et al. 2001). Investigations of several DNA repair gene variants revealed that lung cancer risk was only moderately affected by a single variant but was enhanced up to approximately threefold by specific risk allele combinations (Popanda et al. 2004). Therapy response: Interindividual differences in therapy response are consistently observed with cancer chemotherapeutic agents. Initial results from ongoing studies showed that certain polymorphisms in drug transporter genes (ABCB1) differentially affect response outcome in histological subgroups of lung cancer. Stronger beneficial effects were seen in non-small cell lung cancer (NSCLC) patients following gemcitabine and in SCLC patients following etoposide-based treatment. Several DNA repair parameters (polymorphisms, RNA expression, and DNA repair capacity) were measured in vitro in lymphocytes of patients before radiotherapy and correlated with the occurrence of acute side effects (radio-hypersensitivity). Our initial analysis of several repair gene variants in breast cancer patients (n=446) who received radiotherapy revealed no association of single polymorphisms and the development of side effects (moist desquamation of the irradiated normal skin). The risk for this side effect was, however, strongly reduced in normal weight women carrying a combination of XRCC1 399Gln and APE1 148Glu alleles, indicating that these variants afford some protection against radio-hypersensitivity (Chang-Claude et al. 2005). Based on these data we conclude that specific metabolic and DNA repair gene variants can affect cancer risk and therapy outcome. Predisposition to hereditary cancer syndromes is dominated by the strong effects of some high-penetrance tumor susceptibility genes, while predisposition to sporadic cancer is influenced by the combination of multiple low-penetrance genes, of which as a major challenge, many disease-relevant combinations remain to be identified. Before translating these findings into clinical use and application for public health measures, large populationbased studies and validation of the results will be required.

Indoor coal combustion emissions, GSTM1 and GSTT1 genotypes, and lung cancer risk: a case-control study in Xuan Wei, China

The lung cancer mortality rate in Xuan Wei County, China is among the highest in the country and has been associated with exposure to indoor smoky coal emissions that contain high levels of polycyclic aromatic hydrocarbons. This risk may be modified by variation in metabolism genes, including GSTM1, which encodes an enzyme known to detoxify polycyclic aromatic hydrocarbons. To investigate the relationship between GST genotypes and lung cancer risk in Xuan Wei County, we analyzed GSTM1 and GSTT1 genotypes in a population-based case-control study. A total of 122 lung cancer patients and 122 controls, individually matched by age, sex, and home fuel type, were studied. Compared to subjects who used less than 130 tons of smoky coal during their lifetime, heavier users (> or =130 tons) had a 2.4-fold (95% confidence interval, 1.3-4.4) increased risk of lung cancer. The GSTM1-null genotype was associated with a 2.3-fold (95% confidence interval, 1.3-4.2) increased risk of lung cancer. Furthermore, there was some evidence that smoky coal use was more strongly associated with lung cancer risk among GSTM1-null versus GSTM1-positive individuals. In contrast, the GSTT1 genotype was not significantly associated with lung cancer risk. Our data suggest that the GSTM1-null genotype may enhance susceptibility to air pollution from indoor coal combustion emissions.