Introduction
Leukemia is the most common cancer among children under 15 years of age, accounting for 32 % of all childhood malignancies [
1]. In California, Hispanics have the highest reported annual age-adjusted childhood leukemia incidence (56.2 per million), followed by non-Hispanic whites, Asian/Pacific Islanders, and non-Hispanic blacks (44.6, 40.0, and 29.1 per million, respectively) [
2]. Although acute lymphoblastic leukemia (ALL) is the most common subtype of childhood leukemia, comprising ~80 % of total disease [
1], it is much rarer than most cancers in adults and consequently more difficult to study epidemiologically. The etiology of ALL in children is believed to be distinct from that in adults, due largely to the clearer role for early life exposures. However, few risk factors have been conclusively established, including ionizing radiation, chemotherapeutic agents, and specific genetic abnormalities [
3].
Recent studies from our group and others have found elevated childhood ALL risks associated with self-reported use of pesticides at home [
4], household paint exposure [
5], paternal smoking before conception [
6,
7], and surrogate measures of exposure to motor vehicle exhaust [
8‐
11]. In order to exert their effects, these potentially harmful xenobiotic (exogenous) chemicals must first gain entry into target cells and undergo cellular metabolic processes that alter their activity. Membrane transporters such as those encoded by the multiple drug resistance (
ABCB1/
MDR1) gene act as efflux pumps to expel compounds from the cell and are strategically expressed in regions of the body that act as epithelial barriers or perform excretory functions [
12]. In addition, enzymes involved in phase I (bioactivation) and phase II (detoxification) metabolism maintain a critical balance of activation and inactivation of a wide range of chemical exposures of relevance to childhood ALL, including drugs, chemical carcinogens, insecticides, petroleum products, nitrosamines, polycyclic aromatic hydrocarbons, and other environmental pollutants [
13].
In order to shed light on the role of genes involved in xenobiotic transport and metabolism, both alone and in conjunction with household chemical exposures, in childhood ALL risk, we utilized a haplotype-tagging approach to characterize genetic variation in a population-based study of 377 ALL case children and 448 control children in Northern and Central California. Furthermore, we examined whether effects of exposure to common household chemicals (including paints, solvents, pesticides, herbicides and tobacco smoke) previously linked to risk of childhood ALL or other childhood cancers were modified by these genetic variants.
Results
Due to the matched case–control design of the NCCLS, the distribution of age, gender, race, and ethnicity was comparable between the 377 ALL cases and the 448 controls (Table
1). The 42 xenobiotic transport and metabolism pathway genes we examined are listed in Supplementary Table A. We found that htSNPs in eight genes (
ABCC1,
CYP1A2,
CYP1B1,
CYP2B6,
CYP3A5,
GSS,
IDH1, and
UGT1A9) showed significant heterogeneity of effect between Hispanics and non-Hispanics (
p ≤ 0.05); further analyses for these genes were stratified by ethnicity.
Table 1
Characteristics of childhood acute lymphoblastic leukemia cases and controls, NCCLS
Total | 377 (100.0) | 448 (100.0) |
Sex |
Male | 200 (53.1) | 237 (52.9) |
Female | 177 (46.9) | 211 (47.1) |
Age at diagnosis or reference date |
Under 1 year | 12 (3.2) | 19 (4.2) |
1–5 years | 243 (64.5) | 282 (62.9) |
6–10 years | 85 (22.5) | 95 (21.2) |
11–14 years | 37 (9.8) | 52 (11.6) |
Child’s self-reported ethnicity |
Non-Hispanic | 221 (58.6) | 269 (60.0) |
Hispanic | 156 (41.4) | 179 (40.0) |
Child’s self-reported race |
White | 214 (56.8) | 255 (56.9) |
Black | 15 (4.0) | 16 (3.6) |
Native American | 7 (1.9) | 8 (1.8) |
Asian/Pacific Islander | 25 (6.6) | 35 (7.8) |
Mixed | 110 (29.2) | 133 (29.7) |
Do not know | 6 (1.6) | 1 (0.2) |
Genetic ancestrya
| | |
African | 7.3 (14.7) | 7.1 (14.5) |
Amerindian | 24.2 (23.7) | 22.2 (22.8) |
European | 68.5 (27.3) | 70.7 (26.9) |
Results for genes with significant (
p ≤ 0.05) haplotype effects that persisted through increasingly larger windows are presented in Supplementary Figure 1. Haplotype trend regression results estimating the magnitudes of effect for haplotypes with the lowest multi-SNP p-value in sliding window analyses are shown in Table
2.
Table 2
Haplotype trend regression results: xenobiotic transport and metabolism genes in childhood acute lymphoblastic leukemia risk, NCCLS
ABCB1
|
rs2520464,
rs12334183,
rs1202179,
rs17327442
| All | Rare haplotypes | 0.022 | 0.016 | 0.42 (0.08, 2.09) | 0.289 | 0.019 |
G–A–A–T | 0.080 | 0.107 | 1.66 (0.83, 3.32) | 0.153 |
G–A–G–T | 0.136 | 0.096 |
0.44 (0.23, 0.85)
|
0.015
|
G–A–A–A | 0.142 | 0.165 | 1.25 (0.70, 2.24) | 0.454 |
G–G–G–T | 0.168 | 0.144 | 0.68 (0.39, 1.20) | 0.185 |
A–A–A–T | 0.452 | 0.472 | Ref | |
ARNT
|
rs2228099,
rs4379678
| All | Rare haplotypes | <0.001 | <0.001 | – | 0.011 | 0.003 |
G–G | 0.064 | 0.101 |
4.93 (1.94, 12.53)
|
0.001
|
C–A | 0.410 | 0.389 | 1.09 (0.72, 1.66) | 0.675 |
G–A | 0.526 | 0.511 | Ref | |
CYP2C8
|
rs1934954,
rs7073968,
rs7077618,
rs10509681
| All | Rare haplotypes | 0.026 | 0.026 | 1.29 (0.36, 4.62) | 0.699 | 0.046 |
G–G–T–G | 0.059 | 0.092 |
3.18 (1.45, 6.95)
|
0.004
|
A–G–T–A | 0.239 | 0.260 | 1.57 (0.96, 2.56) | 0.071 |
A–A–T–A | 0.258 | 0.261 | 1.34 (0.83, 2.15) | 0.232 |
A–A–A–A | 0.417 | 0.361 | Ref | |
GCLC
|
rs553822,
rs3799696
| All | Rare haplotypes | 0.015 | 0.032 |
17.47 (2.63, 116.1)
|
0.003
| 0.012 |
A–G | 0.297 | 0.287 | 1.23 (0.75, 2.02) | 0.408 |
G–G | 0.327 | 0.349 | 1.42 (0.89, 2.27) | 0.145 |
A–A | 0.361 | 0.332 | Ref | |
CYP1A2
|
rs11854147,
rs11072508
| NH | Rare haplotypes | 0.046 | 0.022 |
0.14 (0.03, 0.76)
|
0.022
| 0.001 |
G–G | 0.117 | 0.081 | 0.49 (0.20, 1.19) | 0.116 |
A–G | 0.315 | 0.414 |
2.19 (1.28, 3.77)
|
0.005
|
G–A | 0.522 | 0.483 | Ref | |
CYP1B1
|
rs162557,
rs162556
| NH | A–A | 0.081 | 0.040 |
0.11 (0.02, 0.56)
|
0.007
| 0.007 |
A–G | 0.140 | 0.160 | 1.71 (0.80, 3.68) | 0.169 |
G–G | 0.301 | 0.339 | 1.18 (0.62, 2.24) | 0.612 |
G–A | 0.478 | 0.461 | Ref | |
CYP2B6
|
rs3760657,
rs2054675,
rs8100458,
rs3745274
| NH | Rare haplotypes | 0.009 | 0.028 |
16.92 (1.54, 186.3)
|
0.021
| 0.037 |
G–A–G–C | 0.086 | 0.094 | 1.18 (0.48, 2.94) | 0.719 |
A–G–A–A | 0.207 | 0.245 | 1.53 (0.81, 2.90) | 0.193 |
A–A–G–C | 0.256 | 0.211 | 0.70 (0.36, 1.36) | 0.292 |
A–A–A–C | 0.442 | 0.423 | Ref | |
IDH1
|
rs1992739,
rs4290589
| Hisp | C–G | 0.054 | 0.048 | 0.55 (0.11, 2.81) | 0.474 | 0.008 |
C–C | 0.058 | 0.127 |
6.12 (1.75, 21.36)
|
0.005
|
G–G | 0.144 | 0.103 | 0.61 (0.22, 1.73) | 0.355 |
G–C | 0.743 | 0.722 | Ref | |
Among all subjects,
ABCB1,
ARNT,
CYP2C8, and
GCLC showed significant associations that persisted through progressively larger SNP windows (Table
2). In
ABCB1, haplotype G–A–G–T was associated with a significantly reduced risk (OR = 0.44,
p = 0.015). Haplotypes G–G of
ARNT and G–G–T–G of
CYP2C8 were significantly associated with increased risks of childhood ALL (OR = 4.93 and
p = 0.001, OR = 3.18 and
p = 0.004, respectively). The observed significant global haplotype association of
GCLC was attributed to a rare haplotype; no further analysis was performed for this gene.
Among non-Hispanics, CYP1A2 and CYP1B1 showed significant haplotype associations. Haplotype A–G of CYP1A2 was significantly associated with an increased risk (OR = 2.19, p = 0.005), while haplotype A–A of CYP1B1 was significantly associated with a decreased risk (OR = 0.11, p = 0.007). The observed significant global haplotype association of CYP2B6 was attributed to rare haplotypes. Among Hispanics, the two SNPs in IDH1 showed a haplotype association stronger than either SNP individually (global p = 0.008), and the C–C haplotype was significantly associated with an increased risk of ALL (OR = 6.12, p = 0.005).
Two of the most commonly studied xenobiotic metabolism genes to date in childhood ALL are the glutathione S transferase genes
GSTM1 and
GSTT1, whose principal variants are deletions [
30]. The
GSTM1 deletion showed significantly different effects by Hispanic ethnicity (
p < 0.001): among Hispanics the deletion was associated with elevated risk (OR = 1.85, 95 % CI 1.19–2.88,
p = 0.007) while among non-Hispanics, the association was in the opposite direction (OR = 0.62, 95 % CI 0.43–0.89,
p = 0.010). In addition, there was no evidence of association for the
GSTT1 deletion (
p = 0.526).
Finally, we examined interactions between household chemical exposures of interest and xenobiotic gene variants. For this analysis, we focused on haplotypes with at least 5 % frequency among controls and showed nominally significant main effects (global
p ≤ 0.05) among Hispanics and non-Hispanics combined. We found significant interactions between
CYP2C8 haplotype G–G–T–G and self-reported use of paints after birth (
p
FDR = 0.016), and
ABCB1 haplotype G–A–G–T and self-reported use of indoor insecticides before birth (
p
FDR = 0.035) (Table
3). As shown in Table
4, our analysis indicates that the risks of childhood ALL associated with use of paints and indoor insecticides vary by presence or absence of these haplotypes. The increased risks associated with paint use appears confined to those with
CYP2C8 haplotype G–G–T–G (OR = 1.67, 95 % CI 1.21–2.30), while in the small subgroup without the G–G–T–G haplotype (5.9 % among controls), paint use appears to be associated with a non-significant reduced risk (OR = 0.45, 95 % CI = 0.20–1.02). Similarly, the increased risk associated with use of indoor insecticides appears to be limited to the small population with the
ABCB1 G–A–G–T haplotype (13.6 % among controls, OR for indoor insecticides = 3.03, 95 % CI = 1.59–5.78), while among those without the G–A–G–T haplotype, the risk associated with indoor insecticide use was null (OR = 1.02, 95 % CI = 0.74–1.41).
Table 3
Interactions of household chemical exposures with xenobiotic metabolism and transport genes on childhood acute lymphoblastic leukemia risk a
CYP2C8
| Hap G–G–T–G | 0.014 |
0.001
|
0.016
|
0.022
| 0.082 | 0.253 | 0.474 | 0.013 | 0.067 | 0.300 | 0.501 |
ABCB1
| Hap G–A–G–T | 0.013 | 0.850 | 0.931 | 0.587 | 0.834 | 0.869 | 0.931 |
0.005
|
0.035
| 0.612 | 0.834 |
ARNT
| Hap G–G | 0.009 | 0.699 | 0.874 | 0.028 | 0.083 | 0.996 | 0.996 | 0.068 | 0.146 | 0.042 | 0.105 |
Table 4
Chemical by haplotype interaction analysis: effect sizes for childhood ALL risk
CYP2C8 G–G–T–G | Paint in house, ever |
N | N | 133 | 202 | 1.00 (ref) | |
N | Y | 178 | 195 | 1.67 (1.21–2.30) |
0.0020
|
Y | N | 29 | 13 | 1.00 (ref) | |
Y | Y | 37 | 38 | 0.45 (0.20–1.02) | 0.0571 |
ABCB1 G–A–G–T | Indoor insecticide, pre-birth |
N | N | 136 | 146 | 1.00 (ref) | |
N | Y | 174 | 186 | 1.02 (0.74–1.41) | 0.8976 |
Y | N | 21 | 65 | 1.00 (ref) | |
Y | Y | 46 | 51 | 3.03 (1.59–5.78) |
0.0008
|
Discussion
In this population-based case–control study, we examined the risk of childhood ALL associated with several genes within the xenobiotic transport and metabolism pathways, utilizing a haplotype-tagging approach to maximize capture of genetic variation. We identified haplotypes of several genes that were significantly associated with childhood ALL, including ABCB1, ARNT, CYP2C8, CYP1A2, CYP1B1, and IDH1. In addition, we observed significant interactions of identified risk haplotypes with a number of self-reported household chemical exposures, including use of paints and indoor insecticides. Although confirmation is required, our findings provide evidence that genes involved in the xenobiotic transport and metabolism pathway may play a role in mediating risk of childhood ALL, and that the childhood ALL risks associated with various household chemical exposures may be modified by these variation in these genes.
A haplotype of
ABCB1, which encodes a membrane transporter of lipophilic compounds, was significantly associated with childhood ALL risk and showed significant interaction with indoor insecticides, mirroring an earlier finding utilizing different genetic variants in the same gene [
31]. Our results indicate that the increased risk associated with use of indoor insecticides before birth is limited to subjects carrying the G–A–G–T haplotype. The SNPs in this risk haplotype are 21 kb from the nearest of the 3′ SNPs examined in our previous analysis, in which no significant haplotype main effect was observed [
31]. This is in agreement with the current analysis, which also shows no main effect of haplotypes at the 3′ end of the gene.
We also found significant childhood ALL associations with haplotypes in three genes in the CYP gene family:
CYP2C8,
CYP1A2, and
CYP1B1. The
CYP2C8 gene product is involved in metabolism of numerous drugs and other compounds [
32]. In addition to a significant association with childhood ALL, the risk haplotype for
CYP2C8 showed significant interaction with self-reported household paint use, with the increased risk associated with paint use being limited largely to those without the
CYP2C8 G–G–T–G haplotype. For the common haplotype in
CYP1A2 (31.5 % frequency among controls), we found an elevated risk of childhood ALL. The SNPs composing this haplotype are outside the
CYP1A2 coding region, the nearest (rs11854147) being 5.4 kb from the 3′ end. The
CYP1A2 gene product metabolizes polycyclic aromatic hydrocarbons (PAHs, found in tobacco smoke and vehicle exhaust); in utero exposures to PAHs have been linked to chromosomal aberrations [
33].
CYP1B1, for which we observed a significant haplotype association with childhood ALL risk, is also involved in metabolism of PAHs, as well as steroids [
34].
The
ARNT gene product is a key transporter of PAHs and other compounds, and a transcription inducer of xenobiotic metabolism genes including
CYP1A1 and
CYP1A2 [
35] that metabolize PAHs. We identified a risk haplotype for
ARNT that showed a markedly higher risk of childhood ALL. We also observed a strong haplotype association for
IDH1; a somatic mutation in
IDH1 has been linked to survival in adult glioblastoma and AML [
36,
37]. The two SNPs we examined are downstream from and in strong LD with SNPs in the
IDH1 coding region.
In gauging these results, consideration must be given to several factors. First, despite this study’s relatively large sample size compared to those of most previous candidate gene studies, the presence of genetic heterogeneity due to the ethnic and racial diversity of the California population may have influenced our ability to detect associations. Our SNP selection strategy included elements designed to maximize capture of genetic variation in Hispanics. We examined Hispanics separately from non-Hispanics where there was significant heterogeneity in between-group effects of individual SNPs. Although this approach may have limited our ability to detect associations in the population as a whole, we believe it was necessary given that genetic susceptibility may be different in Hispanics versus non-Hispanics due to the Hispanic population’s relatively recent genetic admixture [
22]. Results that differ between Hispanics and non-Hispanics may be due to differences in allele frequency and/or haplotype structure or may reflect underlying differences in exposures that modulate the effects of genes. Regardless, if the results are not spurious, they represent potential risk loci, and we present them in either or both ethnic groups for replication and further followup. Whereas the entire study population yielded adequate power to detect modest effect sizes (81 % power for OR
log additive = 1.40, minor allele frequency = 20 %), power was lower among Hispanics and non-Hispanics separately (44 and 59 %, respectively). In addition, the limited size of racial/ethnic sub-populations within the non-Hispanic group precluded further stratification of this group; as such, genetic heterogeneity among non-Hispanics might have obscured results. However, we found no evidence of strong confounding due to estimated genetic ancestry [
23], minimizing concerns about the impact of population stratification on the results.
Two large genome-wide association studies on childhood ALL have been published to date (with 907 cases and 2,398 adult and child controls, and 317 cases and 17,958 adult controls, respectively) [
38,
39]. Although these studies have identified a number of novel loci, no significant associations were observed for genes in the pathways we studied here. Null findings for these genes in the genome-wide studies may be due to stringent multiple testing adjustment (at the
p ≤ 1 × 10
−7 level) to account for the large number of individual variants under study. In contrast to the agnostic approach to discovery used in genome-wide studies, our study focused on relatively few genes representing key elements of the xenobiotic transport and metabolism pathways. We concede that results of our study may be due to chance and therefore must be replicated. However, the haplotype-tagging approach we adopted maximizes capture of total variation within each candidate gene and the haplotype analysis increases statistical power to detect associations over analyses of individual variants. Furthermore, although the haplotype-tagging approach does not pinpoint potential causal SNPs, it does localize risk-associated regions for further investigation such as fine-mapping.
In this study, we examined potential interactions of xenobiotic transport and metabolism genes with self-reported household chemical exposures early in childhood in the modulation of childhood ALL risk, focusing on haplotype findings observed for both ethnicities (Hispanics and non-Hispanics) combined, as the sizes of the individual ethnic groups were considered too small to permit adequately powered examinations of gene–environment interactions. Our observation that the increased risk associated with paint and indoor insecticide use [
5,
20] was limited to specific subgroups defined by haplotypes of specific genes is suggestive that these genes work in concert with chemical use to modulate risk. Although we focused on a limited number of biologically plausible interactions according to a rigorous a priori analysis plan, we acknowledge that this analysis might be considered exploratory. As such we report only those interactions that were significant after accounting for multiple hypothesis testing. We recognize that our total sample size (377 cases, 448 controls) may be insufficient to observe modest interaction effects with adequate statistical power. Furthermore, although the environmental chemical exposures we examined have been previously associated with childhood leukemia risk [
5,
21], these measures are derived from maternal self-reports, which are prone to reporting errors and recall bias in that mothers of cases may recall exposures differently than mothers of controls. Since this study was population-based with participation rates of 86–87 % and biospecimen collection rates >95 % for interviewed subjects, it is unlikely the results presented here are driven by bias in selection or participation. Further studies with improved measures of chemical exposure are needed to confirm the interactions observed.
In summary, we set out to investigate the role of genes in the xenobiotic transport and metabolism pathway in risk of childhood ALL in greater depth and with larger sample size than previous candidate gene studies. We also sought to examine the putative joint effects of these genes with environmental chemical exposures for which we have observed significant main effects. Our results provide evidence that elements of the xenobiotic transport and metabolism pathway may be associated with childhood ALL, and that some of these elements interact with chemical exposures to modulate risk. This study does not address the potential effects of maternal genes, which may influence in utero susceptibility to chemical exposures. The associations and interactions identified should be considered targets for further study in additional studies, with larger sample sizes, high quality environmental exposure data, maternal genes, and finer coverage of SNPs in the identified associated regions.
Acknowledgments
We thank our clinical collaborators and NCCLS participating hospitals: University of California Davis (J. Ducore), University of California San Francisco (M. Loh and K. Matthay), Children’s Hospital of Central California (V. Crouse), Lucile Packard Children’s Hospital (G. Dahl), Children’s Hospital Oakland (J. Feusner), Kaiser Permanente Roseville (K. Jolly and V. Kiley), Kaiser Permanente Santa Clara (A. Wong and C. Russo), Kaiser Permanente San Francisco (K. Leung), and Kaiser Permanente Oakland (D. Kronish and S. Month). We thank the entire NCCLS staff and the UC Berkeley Survey Research Center for their effort and dedication. Finally, we thank the families who participated in the NCCLS for their strong support and selflessness, without which this research could not have been conducted. We acknowledge funding support from the National Institute of Environmental Health Sciences (PS42ES04705 and R01ES09137) and the Children with Cancer UK Foundation (2005/027, 2005/028, 2006/053). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIEHS or the Children with Cancer UK Foundation.