PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Radiat Res. Author manuscript; available in PMC 2010 May 25.
Published in final edited form as:
PMCID: PMC2875679
NIHMSID: NIHMS192717

Thyroid nodules, polymorphic variants in DNA repair and RET-related genes, and interaction with ionizing radiation exposure from nuclear tests in Kazakhstan

Abstract

Risk factors for thyroid cancer remain largely unknown except for ionizing radiation exposure during childhood and a history of benign thyroid nodules. Because thyroid nodules are more common than thyroid cancers and are associated with thyroid cancer risk, we evaluated several polymorphisms potentially relevant to thyroid tumors and assessed interaction with ionizing radiation exposure to the thyroid gland. Thyroid nodules were detected in 1998 by ultrasound screening of 2997 persons who lived near the Semipalatinsk nuclear test site in Kazakhstan when they were children (1949-62). Cases with thyroid nodules (n=907) were frequency matched (1:1) to those without nodules by ethnicity (Kazakh or Russian), gender, and age at screening. Thyroid gland radiation doses were estimated from fallout deposition patterns, residence history, and diet. We analyzed 23 polymorphisms in 13 genes and assessed interaction with ionizing radiation exposure using likelihood ratio tests (LRT). Elevated thyroid nodule risks were associated with the minor alleles of RET S836S (rs1800862, p = 0.03) and GFRA1 -193C>G (rs not assigned, p = 0.05) and decreased risk with XRCC1 R194W (rs1799782, p-trend = 0.03) and TGFB1 T263I (rs1800472, p = 0.009). Similar patterns of association were observed for a small number of papillary thyroid cancers (n=25). Ionizing radiation exposure to the thyroid gland was associated with significantly increased risk of thyroid nodules (age and gender adjusted excess odds ratio/Gy = 0.30, 95% confidence interval 0.05-0.56), with evidence for interaction by genotype found for XRCC1 R194W (LRT p value = 0.02). Polymorphisms in RET signaling, DNA repair, and proliferation genes may be related to risk of thyroid nodules, consistent with some previous reports on thyroid cancer. Borderline support for gene-radiation interaction was found for a variant in XRCC1, a key base excision repair protein. Other pathways, such as genes in double strand break repair, apoptosis, and genes related to proliferation should also be pursued.

Keywords: Thyroid nodules, single nucleotide polymorphisms, epidemiology, thyroid cancer, ionizing radiation, interaction

Introduction

There are few putative risk factors for thyroid cancer except a previous history of benign thyroid adenoma and ionizing radiation exposure during childhood (1-4). It is likely that genetic susceptibility affects radiation-related thyroid cancer risk in view of the inter-individual variation in response to radiation dose and familial aggregation of thyroid disease and thyroid cancer (5-8). Genetic factors associated with thyroid tumorigenesis have been reported (9), but most studies have been constrained by small sample sizes. Benign thyroid nodules are approximately 10 times more frequent than thyroid cancer, with about 300,000 diagnosed in the US each year (10) and a strong link between benign thyroid nodules and thyroid cancer has been demonstrated (11). Thus, single nucleotide polymorphism (SNP) and haplotype comparisons between persons with and without prevalent nodules may be informative about thyroid cancer risk.

Polymorphic variation (either SNPs or repeat length polymorphisms) associated with increased or decreased thyroid cancer risk have been described for several genes including the proto-oncogene rearranged-during-transfection (RET), (12-14) and selected DNA repair genes (15-16) although not all studies were consistent. No study of papillary thyroid cancer has been of sufficient size to conduct analysis of gene-radiation interaction.

Recently thyroid gland radiation doses were retrospectively estimated among persons who lived downwind of the Semipalatinsk Nuclear Test Site (SNTS) in northeastern Kazakhstan when they were children and who participated as adults in a 1998 thyroid nodule screening study (17). Nuclear fallout doses around the SNTS are believed to have been about an order of magnitude greater than those from the Nevada Test Site in the United States (18). We evaluated 23 polymorphic variants using DNA from archived Guthrie cards in 13 genes suspected to be involved in thyroid tumorigenesis, including RET signaling, thyroid stimulating hormone receptor, DNA repair, and growth stimulation and to assess interaction with ionizing radiation dose to the thyroid gland.

Materials and Methods

Study population and screening

In the early 1960's, the Kazakhstan Research Institute of Radiation Medicine and Ecology assembled a cohort of approximately 10,000 people in northeast Kazakhstan who lived in villages that were downwind of the Semipalatinsk Nuclear Test Site (SNTS) and 10,000 residents of less exposed settlements (19). In 1998, thyroid disease prevalence was evaluated by ultrasound in a sub-set of the original exposed cohort plus other village residents (20) and forms the parent study of the present genetic sub-study. The parent study comprised current residents in eight villages who were under age 20 at the time of one or more of the major atmospheric nuclear weapons tests conducted during 1949-1962 and were either cohort members (N=1989) or selected comparison subjects (N=1008). A total of 2,997 people were screened and interviewed. The screened population was approximately 40% Russian and 60% Kazakh. Questionnaire-based interviews were used to collect information on ethnicity, age, gender, smoking, residential history, general medical information, and selected dietary information. The screening protocol included thyroid ultrasound examination, fine-needle aspiration (FNA) of suspicious nodules with determination of malignancy by cytopathological results of the FNA, height/weight measurement, and finger-stick phlebotomy dried on Guthrie cards for thyroid stimulating hormone (TSH) analysis (for full study details, see (17)).

One or more thyroid nodules (discrete masses ≥ 3 mm in the largest diameter) were found in 920 subjects; 491 persons with nodules ≥ 1 cm underwent FNA (all but two agreed to FNA) and 25 papillary carcinomas were diagnosed. Cases were study participants with nodules detected by ultrasound. Controls were selected from among those without nodules and were frequency matched to cases using a 1:1 matching ratio on ethnicity (Kazakh or Russian), gender, age at the time of screening in 5 year strata, and cohort sub-group (described by Land et al (17) to be roster and non-roster subjects plus non-roster individuals from an eighth village). For some strata there were insufficient control numbers to retain the 1:1 ratio, so all possible controls in each such stratum were selected. Human subject protection review was obtained by the parent study from the institutional review boards at the National Cancer Institute in Bethesda, Maryland, USA, and the Semipalatinsk State Medical Academy in Kazakhstan. All subjects provided informed consent for finger-stick phlebotomy and ultrasound screening. The sub-study was based on anonymized Guthrie card material remaining after TSH analysis, for which a human subjects exemption was obtained. Anonymization entailed linking the epidemiologic and clinical data (stripped of personal identifiers) with the genotyping results and then the link was destroyed.

Genotyping

Following TSH assays performed in 1998, the Guthrie cards were stored at room temperature in a dry container until June 2003 when 3 mm samples from the cards were punched and processed. Laboratory investigators were blinded to case and control status. Approximately 10 ng of genomic DNA extracted from the Guthrie cards were used as template in Taqman 5′-nuclease assays for all SNPs. Taqman assays were performed using 450 nanomolar primer concentrations and 100 nanomolar probe concentrations and Taqman Universal Master Mix (Applied Biosystems, Foster City, CA). Probes specific for each SNP were designed with Primer Express software (Applied Biosystems, Foster City, CA) and labeled with either 6-FAM, TET, or VIC as reporter dyes with either Black Hole Quencher-1 (IDT, Inc., Coralville, IA) or MGB-NFQ (Applied Biosystems, Foster City, CA) as quenchers. Most assays were performed in 20 microliter reactions in 96-well trays using an ABI 7700 instrument (Applied Biosystems, Foster City, CA), but some were performed in 5 microliter reactions in 384-well trays using an ABI 7900HT instrument (Applied Biosystems, Foster City, CA).

Subjects with each of the possible genotypes for each SNP (excluding those for which no homozygous variant subject had ever been identified) were confirmed by sequencing and included on each genotyping tray. As a quality control check for genotyping, approximately 2.4% of samples (2 to 8 aliquots for each of 13 individuals) were duplicates and to which laboratory investigators were completely blinded. Of the approximately 800 genotypes scored for these duplicates, 99.6% were concordant with other results from the same individual. The inconsistent genotypes occurred for 3 separate SNPs in 2 individuals and probably do not reflect a systematic error with any single assay.

Thyroid gland radiation dose reconstruction

Ionizing radiation dose reconstruction has been described in detail elsewhere (17). Briefly, individual radiation doses to the thyroid gland were based on fallout deposition patterns from 11 different nuclear tests conducted at the SNTS between August 1949 and September 1962, residential histories from personal interviews, and childhood diet. Milk consumption was especially important because of the Iodine 131 (131I) fallout-pasture-animal grazing-milk pathway. Thyroid doses were calculated as the sum of gamma radiation from external sources and beta radiation from ingested 131I, given that the epidemiologic study found little evidence to suggest that the relative biologic effectiveness of the two components of dose differed (17).

Statistical Methods

Unconditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CI) for thyroid nodules by genotype. We assumed a co-dominant mode of inheritance unless the homozygote numbers for the minor allele were ≤ 1% of the total, in which case we combined them with the heterozygotes. Tests for linear trend were calculated across all genotypes unless there were no persons homozygous for the minor allele. Potential confounding factors considered were thyroid volume, body weight, and TSH, as well as the matching variables of age, ethnicity, sub-group, and gender, but these factors did not appreciably affect the odds ratios and were not included in the models. Deviation from the expectation of Hardy-Weinberg Equilibrium (HWE) was determined by chi-square testing in controls because deviation among cases is presumptive of an association with disease. In analyses of thyroid nodules, the 25 individuals with thyroid cancer were excluded and analyzed separately. Haplotypes for the four RET SNPs were estimated using SNPHAP (http://www-gene.cimr.cam.ac.uk/clayton/software/), as implemented in HapScope (21). Associations between haplotypes and disease status were evaluated with SAS PROC HAPLOTYPE. We also used quasi-likelihood hierarchical regression modeling (22-23) to account for the potential correlation of multiple SNPs and to increase the accuracy and precision of SNP effect estimates over conventional methods (24-26). All tests were two-sided. Analyses were done using SPSS version 13.0 (Chicago, IL), SAS/GLIMMIX version 8.02 and SAS/GENETICS version 9.0 (SAS Institute, Inc., Cary, NC).

The main effect of thyroid radiation dose was assessed by modeling the odds ratio as a linear function in logistic regression models:

OR=1+βD

where D is the continuous radiation dose and β is the excess odds ratio (EOR) per unit dose in Gray (Gy). To test whether SNPs modified the relation between radiation and thyroid nodule risk, we allowed the radiation-related EOR to vary by genotype while adjusting for the genotype effect. EOR heterogeneity across genotype categories was assessed using likelihood ratio tests (LRT). Confidence intervals for radiation risk estimates were derived using the profile likelihood method. We used EPICURE software (Hirosoft, Seattle, WA) for the linear dose-response analyses.

Results

There were 1840 individuals eligible for inclusion, with genotyping attempted for 1827. Guthrie cards were missing for seven cases and three controls, and exhaustion of controls within some age/gender/ethnic strata further reduced numbers available by three. Among the 1827 individuals who were genotyped, six had missing nodule information, leaving 907 cases and 914 controls available for analysis. Due to missing dose information, the sample size for gene-radiation interaction analyses was slightly reduced to 879 cases and 884 controls. For any given SNP, variable numbers of samples were successfully genotyped, ranging from 99.7% to 91.2%. Among the controls, significant deviation from HWE was found for RAD18 R302Q (p= 0.006).

Descriptive characteristics of the subjects with thyroid nodules (cases) and their frequency matched controls without nodules are shown in Table 1. Ethnic Kazakhs and Russians made up 64.1% and 35.9% of the study group, respectively. Age and gender distributions were similar among cases and controls owing to the frequency matched design, although cases among the Kazakhs tended to be younger than those among the Russians. The proportions of individuals with one versus two or more ultrasound-detected nodules and with papillary thyroid cancer were equivalent between Kazakhs and Russians. TSH levels were similar between cases and controls (not shown). For 12 of the 23 SNPs evaluated, the frequency of genotypes between Russian controls and Kazakh controls differed significantly (Table 2).

Table 1
Descriptive characteristics for those residents found to have thyroid nodules (cases) and those without thyroid nodules (controls) at ultrasound examination by ethnicity among residents near Semipalatinsk, Kazakhstan, 1998
Table 2
Number genotyped and allele frequencies among Kazakhs and Russians, residents near Semipalatinsk, Kazakhstan, 1998

The age and gender adjusted excess odds ratio per Gy (EOR/Gy) was 0.30, (95% confidence interval (CI), 0.05-0.56). Increased thyroid nodule risk was associated with RET S836S (rs1800862; CT vs. CC (referent), OR = 1.4; 95% CI, 1.0-2.0) and GFRA1 -193C>G (rs not assigned; CG vs. CC, OR=1.8; 95% CI, 1.0-3.1, p=0.051) and decreased risk with XRCC1 R194W (rs1799782; p-trend=0.03 for increasing minor alleles) and TGFB1 T263I (rs1800472; CT vs CC, OR=0.5; 95% CI, 0.3-0.8) (Table 3). When we analyzed each SNP stratified by ethnicity (Table 4), the associations with the above four SNPs tended to be consistent and strongest among Kazakh individuals and the directions of the risk estimates were similar among Russian individuals. Associations between genotypes and papillary thyroid cancer risk are shown in Table 5. Two of the four SNPs that were associated with increased risk of thyroid nodules were suggestively associated with increased risk of thyroid cancer: RET S836S (OR=4.4, 95% CI, 1.7-11.4) and GFRA1 -193C>G (OR=4.0, 95% CI, 0.9-18.4). Thyroid cancer risk was decreased for the minor allele of XRCC1 R194W and there were no carriers of the TGFB1 T263I minor allele among papillary thyroid cancer cases. Increased thyroid cancer risk was associated with TSHR D727E and decreased risk with ZNF350 L66P and S472P. Haplotyping and hierarchical regression did not add any information to that gained by single SNP analyses (not shown). Analyses of thyroid nodules stratified by gender showed similar risk patterns for GFRA1 -193C>G, XRCC1 R194W, and TGFB1 T263I, however the increased risk of thyroid nodules associated with RET S836S was limited to women only (data not shown).

Table 3
Risk of thyroid nodules associated with single nucleotide polymorphisms (SNP) and interaction with ionizing radiation exposure to the thyroid gland in a Kazakh and Russian population residing near Semipalatinsk, Kazakhstan, 1998.
Table 4
Risk of thyroid nodules associated with single nucleotide polymorphisms by ethnicity in a Kazakh and Russian population residing near Semipalatinsk, Kazakhstan, 1998
Table 5
Risk of papillary thyroid cancer associated with single nucleotide polymorphisms in a Kazakh and Russian population, Semipalatinsk, Kazakhstan.

Among genotypes consistent with HWE in controls, two interactions between thyroid gland radiation dose from fallout and genotype were statistically significant (Table 3). XRCC1 R194W and BRIP1 P919S both had LRT p values = 0.02. The common homozygous XRCC1 R194W alleles were associated with increased radiation-related risk of thyroid nodules (EOR/Gy = 0.51, 95% CI, 0.18-0.98) and the minor allele was consistent with no elevated radiation-related risk. For BRIP1 P919S, the common homozygous and heterozygous variant alleles were associated with increased radiation-related risk of thyroid nodules and the homozygous variant alleles were consistent with no elevated risk.

Discussion

Thyroid carcinogenesis is hypothesized to result from mutational events combined with growth stimulation (4), a hypothesis consistent with the marked inverse association observed between radiation dose-response and exposure age. All the SNPs and genes were selected because they could affect the likelihood of mutations from DNA misrepair or might constitutively influence cellular proliferation. In this study we identified two polymorphisms, RET S836S and GFRA1 -193 C>G, the variant forms of which were associated with an increased risk of both thyroid nodules and papillary thyroid cancer. Two other polymorphisms were associated with decreased risk of thyroid nodules, TGFB1 T263I and XRCC1 R194W, with TGFB1 T263I also associated with decreased risk of papillary thyroid cancer. XRCC1 R194W and BRIP1 P919S modified the radiation-related risk of thyroid nodules. The results suggest that, at least in the population studied here, several SNPs may be related to thyroid nodule and cancer risk, or that other variants in linkage disequilibrium, are risk alleles.

The RET S836S polymorphism has been associated with both differentiated thyroid cancer and benign thyroid disease, with adjusted odds ratios of 2.5 (95% CI 1.0-6.6) and 2.2 (0.7-6.8) observed, respectively, for the minor allele (13). However, Lesueur et al (12) and Lönn et al (14) did not find an association with RET S836S and sporadic papillary thyroid cancer, but did observe an increased risk associated with RET L769L and RET G691S, respectively. It may be that the synonymous RET polymorphisms exert their effects by affecting protein folding or altering RNA secondary structures resulting in reduced protein function (reviewed in (27)). Two RET haplotypes have been associated with risk of benign thyroid disease, but not with differentiated thyroid cancer (13). In our RET haplotype analysis, we found no additional information beyond that obtained from analyzing SNPs individually.

RET activation requires binding with one of the four RET ligands that interact preferentially with four high-affinity glycosyl-phosphatidylinositol co-receptors called GFRA1 through GFRA4 (reviewed in (28)). Polymorphic variants in the genes GFRA1-GFRA4 have been analyzed in relation to sporadic medullary thyroid cancer, (29-31) but medullary thyroid cancer is histologically distinct from and probably uninformative for comparisons with papillary thyroid cancer. To our knowledge, GFRA1 gene polymorphisms have not been evaluated previously in persons with benign thyroid nodules.

Several of the villages studied in Kazakhstan are in mild to moderately iodine deficient areas (17, 32). In geographic regions of iodine deficiency, the thyroid glands of residents are exposed to mild chronic TSH stimulation that could increase H2O2 and free radical production (reviewed in (33)), causing damage to DNA. We evaluated several gene variants in DNA damage repair pathways as we hypothesized these would be important among persons with marginal iodine intake and exposure to radioactive fallout. We included the base excision repair (BER) pathway because oxidative and some radiation damage to nucleotides would be repaired by this mechanism. In radiation challenge assays, frequencies of chromatid breaks per cell after lymphoctye γ-radiation were higher among papillary thyroid cancer cases than controls and benign thyroid disease cases were intermediate between the two groups (34), suggesting higher radiation sensitivity or compromised radiation-induced damage repair ability was a risk factor for thyroid tumors. XRCC1 is a key BER scaffolding protein and the XRCC1 R194W minor allele was associated with a statistically significantly decreased risk of thyroid nodules and the common allele with a suggestive radiation-related increased thyroid nodule risk. In other words, the more common C allele appeared to be the risk allele, associated both with thyroid nodules and nodules related to radiation exposure to the thyroid gland. BRIP1 is a BRCA1 interacting protein for which one SNP (P919S) modified the radiation-related thyroid nodule risk. However, absent a main effect, it is more difficult to ascribe importance to the possible gene-radiation interaction observed for BRIP1 P919S when a chance finding is also possible.

Transforming growth factor β is a cytokine with multiple regulatory actions and responses to cellular damage (including from radiation) and can promote or suppress carcinogenesis depending on the timing and specific function mediated by its extracellular signaling (reviewed in (35)). We found that the TGFB1 T263I minor allele was associated with statistically significantly decreased risk of thyroid nodules; the minor allele was not represented among any thyroid cancer cases compared to 4.9% of controls. Further detailed evaluation of the polymorphic variation in the TGFβ1 gene and thyroid tumors, such as could be obtained from collaborative efforts, should be considered.

Strengths of this study were the relatively large sample size, having 84% power to detect an OR of 1.5 with alpha set at 0.002 (Bonferroni correction for 23 tests) if the allele frequency was ≥ 30%, and that the thyroid nodules were detected within a screened population under standard conditions. We were able to test for variation across two diverse populations and for two thyroid disease endpoints. While not an exhaustive set of risk factors, we were able to assess the impact of selected co-variates such as TSH levels, thyroid volume, body weight, and the matching variables. We found several SNP and thyroid nodule associations for which one might argue the papillary thyroid cancer results provided some corroboration of the findings. Confounding by population stratification is unlikely because thyroid nodule prevalence did not differ by ethnicity and no inconsistencies were found when we conducted our analyses stratified by ethnicity.

Several limitations should also be considered, including the large number of tests conducted and the relatively modest genotypic associations seen. Using a Bonferroni correction, none of the p-values for the genotype associations with thyroid nodule risk would be considered significant (p < 0.002). Power for detecting less common variants was low: 38% to detect an OR of 1.5 with alpha set at 0.002 and an allele frequency of 10%. However, the gene-radiation interaction analyses were more exploratory in nature and require replication as the primary safeguard against false positive associations. The radiation doses to the thyroid gland are uncertain and efforts have been made to re-contact village residents to collect additional key data on milk consumption besides from cows, housing construction, and patterns of animal husbandry (location of grazing areas around the villages). Analyses of uncertainties are planned after the doses are revised based on incorporating the new information.

In summary, the associations found with thyroid nodules and papillary cancer suggest polymorphic variation in RET S836S, GFRA1 -193 C>G, and TGFB1 T263I, were related to risk. The common allele of XRCC1 R194W was related to risk of thyroid nodules and suggestively modified the radiation-associated nodule risk. Other pathways, such as genes in double strand break repair, apoptosis, and additional genes related to proliferation should also be pursued.

Acknowledgments

We are very grateful to the residents of the Kazakhstan villages who participated in this study. This study was supported in part by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics of the National Cancer Institute, National Institutes of Health, Department of Health and Human Services and by the Harkin Award for research on thyroid cancer.

Footnotes

Conflicts of interest: None

References

1. Ron E, Schneider AB. Thyroid Cancer. In: Schottenfeld D, Fraumeni JF Jr, editors. Cancer Epidemiology and Prevention. 3rd. Oxford University Press; NY: 2006. pp. 975–994.
2. Ron E, Lubin JH, Shore RE, Mabuchi K, Modan B, Pottern LM, Schneider AB, Tucker MA, Boice JD., Jr Thyroid cancer after exposure to external radiation: a pooled analysis of seven studies. Radiat Res. 1995;141:259–277. [PubMed]
3. Shore RE. Issues and epidemiological evidence regarding radiation-induced thyroid cancer. Radiat Res. 1992;131:98–111. [PubMed]
4. Williams ED. Mechanisms and pathogenesis of thyroid cancer in animals and man. Mutation Res. 1995;333:123–129. [PubMed]
5. Hansen PS, Brix TH, Bennedbæk FN, Bonnema SJ, Iachine I, Kyvik KO, Hegedüs L. The relative importance of genetic and environmental factors in the aetiology of thyroid nodularity: a study of healthy Danish twins. Clin Endocrinol. 2005;62:380–386. [PubMed]
6. Memon A, Berrigton de González A, Luqmani Y, Suresh A. Family history of benign thyroid disease and cancer and risk of thyroid cancer. Eur J Cancer. 2004;40:754–760. [PubMed]
7. Pal T, Vogl FD, Chappuis PO, Tsang R, Brierley J, Renard H, Sanders K, Kantemiroff T, Bagha S, Goldgar DE, Narod SA, Foulkes WD. Increased risk for nonmedullary thyroid cancer in the first degree relatives of prevalent cases of nonmedullary thyroid cancer: a hospital-based study. J Clin Endocrinol Metab. 2001;86:5307–5312. [PubMed]
8. Frich L, Glattre E, Akslen LA. Familial occurrence of nonmedullary thyroid cancer: a population-based study of 5673 first-degree relatives of thyroid cancer patients from Norway. Cancer Epidemiol Biomarkers Prev. 2001;10:113–117. [PubMed]
9. Kondo T, Ezzat S, Asa SL. Pathogenetic mechanisms in thyroid follicular-cell neoplasia. Nat Rev Cancer. 2006;6:292–306. [PubMed]
10. Castro MR, Gharib H. Continuing controversies in the management of thyroid nodules. Ann Intern Med. 2005;142:926–931. [PubMed]
11. Franceschi S, Preston-Martin S, Dal Maso L, Negri E, La Vecchia C, Mack WJ, McTiernan A, Kolonel L, Mark SD, Mabuchi K, Jin F, Wingren G, Galanti R, Hallquist A, Glattre E, Lund E, Levi F, Linos D, Ron E. A pooled analysis of case-control studies of thyroid cancer. IV. Benign thyroid diseases. Cancer Causes Control. 1999;10:583–595. [PubMed]
12. Lesueur F, Corbex M, Mckay JD, Lima J, Soares P, Griseri P, Burgess J, Ceccherini I, Landolfi S, Papotti M, Amorim A, Goldgar DE, Romeo G. Specific haplotypes of the RET proto-oncogene are over-represented in patients with sporadic papillary thyroid carcinoma. J Med Genet. 2002;39:260–265. [PMC free article] [PubMed]
13. Ho T, Li G, Zhao C, Wei Q, Sturgis EM. RET polymorphisms and haplotypes and risk of differentiated thyroid cancer. Laryngoscope. 2005;115:1035–1041. [PubMed]
14. Lönn S, Bhatti P, Alexander BH, Pineda MA, Doody MM, Struewing JP, Sigurdson AJ. Papillary thyroid cancer and polymorphic variants in TSHR- and RET-related genes: a nested case-control study within a cohort of U.S. Radiologic Technologists. Cancer Epidemiol Biomarkers Prev. 2007;16:174–177. [PubMed]
15. Sturgis EM, Zhao C, Zheng R, Wei Q. Radiation response genotype and risk of differentiated thyroid cancer: a case-control analysis. Laryngoscope. 2005;115:938–945. [PubMed]
16. Silva SN, Gil OM, Oliveira VC, Cabral MN, Azevedo AP, Faber A, Manita I, Ferreira TC, Limbert E, Pina JE, Rueff J, Gaspar J. Association of polymorphisms in ERCC2 gene with non-familial thyroid cancer risk. Cancer Epidemiol Biomarkers Prev. 2005;14:2407–2412. [PubMed]
17. Land CE, Zhumadilov Z, Gusev BI, Hartshorne MH, Wiest PW, Woodward PW, Crooks LA, Luckyanov NK, Fillmore CM, Carr Z, Abisheva G, Beck HL, Bouville A, Langer J, Weinstock R, Gordeev KI, Simon SL. Thyroid Nodule Prevalence and Radiation Dose from Fallout: Preliminary Analysis. Radiat Res. 2008;169:373–383. [PMC free article] [PubMed]
18. Bouville A, Anspaugh L, Balonov MI, Gordeev KI, Kiselev VI, Loborev VM, Luckyanov NK, Pauli E, Robison WL, Savkin M, Sudako VV, Zelentsov S. Estimation of Doses. In: Warner F, Kirchmann RJC, editors. Nuclear test explosions: environmental and human impacts Scientific Committee on Problems on the Environment (SCOPE) John Wiley and Sons, Ltd; West Sussex, England: 2000. pp. 115–177.
19. Grosche B, Land C, Bauer S, Pivina LM, Abylkassimova ZN, Gusev BI. Fallout from nuclear tests: health effects in Kazakhstan. Radiat Environ Biophys. 2002;41:75–80. [PubMed]
20. Gusev B, Abylkassimova Zh, Apsalikov K. The Semipalatinsk Nuclear Test Site: a first assessment of the radiological situation and the test-related radiation doses in the surrounding territories. Radiat Environ Biophys. 1997;36:201–204. [PubMed]
21. Zhang J, Rowe WL, Struewing JP, Buetow KH. HapScope: a software system for automated and visual analysis of functionally annotated haplotypes. Nucleic Acids Res. 2002;30:5213–5221. [PMC free article] [PubMed]
22. Greenland S. Principles of multilevel modeling. Int J Epidemiol. 2000;29:158–167. [PubMed]
23. Witte JS, Greenland S, Kim LL, Arab L. Multilevel modeling in epidemiology with GLIMMIX. Epidemiol. 2000;11:684–688. [PubMed]
24. Hung RJ, Brennan P, Malaveille C, Porru S, Donato F, Boffetta P, Witte JS. Using Hierarchical Modeling in Genetic Association Studies with Multiple Markers: Application to a Case-Control Study of Bladder Cancer. Cancer Epidemiol Biomarkers Prev. 2004;13:1013–1021. [PubMed]
25. de Roos AJ, Rothman N, Inskip PD, Linet MS, Shapiro WR, Selker RG, Fine HA, Black PM, Pittman GS, Bell DA. Genetic Polymorphisms in GSTM1, -P1, T-1 and CYP2E1 and the Risk of Adult Brain Tumors. Cancer Epidemiol Biomarkers Prev. 2003;12:14–22. [PubMed]
26. de Roos AJ, Smith MT, Chanock S, Rothman N. IARC Scientific Publications No. 157. 2004. Toxicological Considerations in the Application and Interpretation of Susceptibility Biomarkers in Epidemiological Studies Mechanisms of Carcinogenesis: Contributions of Molecular Epidemiology; pp. 105–125. [PubMed]
27. Sauna ZE, Kimchi-Sarfaty C, Ambudkar SV, Gottesman MM. Pharmacogenomics. 2007;8:527–532. [PubMed]
28. Alberti L, Carniti C, Miranda C, Roccato E, Peirotti MA. RET and NTRK1 proto-oncogenes in human diseases. J Cell Physiol. 2003;195:168–186. [PubMed]
29. Gimm O, Dziema H, Brown J, Hoang-Vu C, Hinze R, Dralle H, Mulligan LM, Eng C. Over-representation of a germline variant in the gene encoding RET co- receptor GFRalpha-1 but not GFRalpha-2 or GFRalpha-3 in cases with sporadic medullary thyroid carcinoma. Oncogene. 2001;20:2161–2170. [PubMed]
30. Borrego S, Fernández RM, Dziema H, Japón MA, Marcos I, Eng C, Antinolo G. Evaluation of germline sequence variants of GFRA1, GFRA2, and GFRA3 genes in a cohort of Spanish patients with sporadic medullary thyroid cancer. Thyroid. 2002;12:1017–1022. [PubMed]
31. Cebrian A, Lesueur F, Martin S, Leyland J, Ahmed S, Luccarini C, Smith PL, Luben R, Whittaker J, Pharoah PD, Dunning AM, Ponder BAJ. Polymorphisms in the initiators of RET (rearranged during transfection) signaling pathway and susceptibility to sporadic medullary thyroid carcinoma. J Clin Endocrinol Metab. 2005;90:6268–6274. [PubMed]
32. Hamada A, Takamura N, Meirmanov S, Alipov G, Mine M, Ensebaev R, Sagandikova S, Ohashi T, Yamashita S. No evidence of radiation risk for thyroid gland among schoolchildren around Semipalatinsk nuclear testing site. Endocrine J. 2003;50:85–89. [PubMed]
33. Corvilain B, van Sande J, Dumont JE, Vassart G. Somatic and germline mutations of the TSH receptor and thyroid diseases. Clin Endocrinol. 2001;55:143–158. [PubMed]
34. Xiong P, Zheng R, Wang L, Bondy ML, Shen H, Borer MM, Wei Q, Sturgis EM. A pilot case-control study of gamma-radiation sensitivity and risk of papillary thyroid cancer. Thyroid. 2005;15:94–99. [PubMed]
35. Barcellos-Hoff MH, Brooks AL. Extracellular signaling through the microenvironment: a hypothesis relating carcinogenesis, bystander effects, and genomic instability. Radiat Res. 2001;156:618–627. [PubMed]