DNA repair genotype and lung cancer risk in the beta-carotene and retinol efficacy trial

Jennifer A Doherty; Lori C Sakoda; Melissa M Loomis; Matt J Barnett; Liberto Julianto; Mark D Thornquist; Marian L Neuhouser; Noel S Weiss; Gary E Goodman; Chu Chen

. 2013 Mar 18;4(1):11–34.

DNA repair genotype and lung cancer risk in the beta-carotene and retinol efficacy trial

Jennifer A Doherty ^1,², Lori C Sakoda ^2,³, Melissa M Loomis ², Matt J Barnett ², Liberto Julianto ², Mark D Thornquist ², Marian L Neuhouser ², Noel S Weiss ^2,⁴, Gary E Goodman ², Chu Chen ^2,^4,⁵

PMCID: PMC3612452 PMID: 23565320

Abstract

Many carcinogens in tobacco smoke cause DNA damage, and some of that damage can be mitigated by the actions of DNA repair enzymes. In a case-control study nested within the Beta-Carotene and Retinol Efficacy Trial, a randomized chemoprevention trial in current and former heavy smokers, we examined whether lung cancer risk was associated with variation in 26 base excision repair, mismatch repair, and homologous recombination repair genes. Analyses were limited to Caucasians (744 cases, 1477 controls), and logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for individual SNPs and common haplotypes, with adjustment for matching factors. Lung cancer associations were observed (p<0.05) with SNPs in MSH5 (rs3131379, rs707938), MSH2 (rs2303428), UNG (rs246079), and PCNA (rs25406). MSH5 rs3131379 is a documented lung cancer susceptibility locus in complete linkage disequilibrium with rs3117582 in BAT3, and we observed associations similar in magnitude to those in prior studies (per A allele OR 1.37, 95% CI 1.13-1.65). UNG was associated with lung cancer risk at the gene level (p=0.02), and the A allele of rs246079 was associated with an increased risk (per A allele OR 1.15, 95% CI1.01-1.31). We observed stronger associations with UNG rs246079 among individuals who carried the risk genotypes (AG/AA) for MSH5 rs3131379 (p_interaction= 0.038). Our results provide additional evidence to suggest that the MSH5/BAT3 locus is associated with increased lung cancer risk among smokers, and that associations with other SNPs may vary depending upon MSH5/BAT3 genotype. Future studies to examine this possibility are warranted.

Keywords: Lung cancer, base excision repair, mismatch repair, homologous recombination repair, DNA repair, genetic polymorphism

Introduction

Lung cancer is the leading cause of cancer death worldwide, with over a million deaths annually [1]. The large majority (80-90%) of lung cancers develop in individuals who are either current or former cigarette smokers [2]. Tobacco smoke exposure can result in various types of damage to DNA, either directly by forming DNA adducts, or through the production of reactive oxygen or nitrogen species. These lesions are repaired by a wide variety of DNA repair mechanisms, including (but not limited to) base excision repair (BER), nucleotide excision repair (NER), mismatch repair (MMR), and double-strand break repair (DSB) which includes homologous recombination (HR) and non-homologous end-joining [3]. Therefore, it is plausible that genetic variation in these important pathways might influence lung cancer risk. Indeed, two of the five validated lung cancer susceptibility loci to date map to regions that include genes related to DNA repair. The 6p21.33 locus in the HLA region contains the genes BAT3 and MSH5, and MSH5 is a member of the mutS homolog gene family, involved in MMR. The association with the 12p13 locus is specific to squamous cell lung cancer, and this locus contains the RAD52 homolog gene which is involved in DSB and HR [4]. A recent meta-analysis of 16 GWAS studies with 14,900 cases and 29,485 controls of European descent confirmed these associations as well as those with 5p15 (TERT/CLPTM1L), and 15q25.1 (CHRNA5/CHRNA3/CHRNB4), and reported an additional association for squamous cell carcinoma at 9p21 (CDKN2A/p16^INK4A/p14^ARF/CDKN2B/p15^INK4B/ANRIL) [5]. An additional locus at 6p21.31, containing HLADQA1, was reported in a Japanese GWAS study [6].

Many candidate gene and candidate pathway studies as well as meta-analyses have investigated whether genetic variants in DNA repair pathways are associated with lung cancer risk, with mixed results for genes in MMR [7-15], BER [8,15-32], and HR [8,15,16,19-22,27,29,32]; NER will not be discussed since we have previously reported our findings from analyses of NER genes and lung cancer risk [33]. Herein we report results from our systematic evaluation of associations between 176 tag and functional SNP variants in genes involved in MMR (MLH1, MSH2, MSH4, MSH5, and MSH6), BER (APEX1, LIG3, MBD4, MPG, MUTYH, NEIL1, NEIL2, NTHL1, OGG1, PCNA, PNKP, POLB, POLI, PPP1R13L, RAD18, SMUG1, TDG, UNG, and XRCC1), and HR (XRCC2 and XRCC3) and risk of lung cancer in a nested case-control study of heavy smokers.

Materials and methods

Study population

Details of this study have been published previously [33]. In brief, this nested case-control study is comprised of participants from the multicenter β-Carotene and Retinol Efficacy Trial (CARET), which was a randomized, double-blinded, placebo-controlled chemoprevention trial to assess safety and efficacy of daily supplementation with β-carotene and retinyl palmitate among individuals at high risk of developing lung cancer [34-36]. The trial included men and women ages 50-69 years who were current or former heavy smokers (i.e., quit within six years prior to enrollment) with a cigarette smoking history of ≥20 pack-years (n=14,254). The trial also included men ages 45-69 years with a documented history of occupational asbestos exposure who were current or former heavy smokers (i.e., quit within fifteen years prior to enrollment) (n=4,060). Participants were asked to complete a questionnaire at baseline and annually thereafter, to obtain extensive information about smoking history as well as other risk factors. At baseline and every two years following, they were also asked to complete a food frequency questionnaire (FFQ) describing dietary intake in the prior year. After a mean of four years of follow up, the intervention was stopped in 1996 due to higher lung cancer incidence and overall mortality rates in the intervention versus placebo arm. CARET continued follow up for lung cancer and other outcomes until 2005. Tumor histology data were obtained from pathology reports collected as part of the CARET endpoint review process and through the California, Oregon, and Washington state cancer registries, since about 85% of all participants resided in these states at the time of CARET enrollment.

Participants were eligible for the present nested case-control study if they had provided a whole blood specimen for genetic research between February 1994 and January 1997. Cases included the 793 individuals who were diagnosed with primary lung cancer, and two lung cancer-free controls were matched to each case on age (±4 years), sex, race/ethnicity, enrollment year (two year intervals), baseline smoking status (current or former), history of occupational asbestos exposure, and length of follow-up. Controls were additionally required to have completed at least one FFQ. DNA was extracted from whole blood, and eighteen controls were excluded due to low DNA yield (≤10 μg), leaving a total of 793 cases and 1,568 controls available for genotyping. Three cases were excluded after genotyping, because their diagnoses were later learned to be benign or carcinoid lung tumors.

The Institutional Review Board of the Fred Hutchinson Cancer Research Center and the five other participating institutions approved all study protocols, and all participants provided written informed consent.

SNP selection and genotyping

Tag SNPs were selected from HapMap Phase I and II Centre d’Etude du Polymorphism Humain (CEU; NCBI build 36, dbSNP build 129) for the region spanning ±2,500 base pairs of each candidate gene using the ldSelect algorithm [37] to classify SNPs with a minor allele frequency (MAF) of >=5% into bins with a pair-wise linkage disequilibrium (LD) threshold of r²>=0.8. Additional putative functional SNPs were also selected (for more details, please see Sakoda et al. [33]). We assayed a total of 185 SNPs using three methods: 137 were genotyped in a custom 384-plex Illumina GoldenGate assay that included SNPs in DNA repair, cell cycle control and drug metabolism; 45 were genotyped using individual Applied Biosystem TaqMan assays; and three were genotyped using Sequenom at the Genome Analysis Core Facility at the University of California, San Francisco. Eleven SNPs failed assays, were monomorphic, or genotype frequencies among the non-Hispanic white controls deviated from those expected under Hardy-Weinberg equilibrium as assessed using Fisher’s exact test (p<0.001). After excluding these SNPs, the large majority of SNPs had genotype call success of greater than 99%; 8 SNPs had call success between 95.1 and 98.9%. Genotype concordance for all SNPs was 100% in a set of 82 randomly-placed blind duplicates. Data were excluded for 3 case and 6 control samples that failed the Illumina assays or were identified by Illumina to be gender-mismatched, leaving 787 cases and 1,562 controls available for analysis. A subset of the CARET samples (397 cases and 393 controls) were previously analyzed using the Illumina HumanHap300 BeadChip in an initial GWA study of lung cancer by Hung et al. [38], and these data (394 cases and 391 controls) are also included in the latest metaanalysis [5].

Genotype analysis

Due to small numbers of Hispanic and non-White individuals (43 cases, 85 controls), all analyses were restricted to non-Hispanic whites (744 cases, 1,477 controls). Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using logistic regression (Stata^® 11, StataCorp, College Station, TX) and were adjusted for the case-control matching variables (age, sex, enrollment year, baseline smoking status, and occupational asbestos exposure), using the most common homozygous genotype as the reference group. Per allele ORs and 95% CIs were calculated by coding SNP genotypes according to the number of minor alleles carried (0, 1, or 2).

We examined whether SNP associations varied by age (<70, ≥70 years), sex (male, female), smoking status at baseline (former, current), the number of pack-years smoked at baseline or time of blood draw (defined as the product of the average number of cigarette packs smoked per day and the total number of years smoked, divided into thirds of the distribution among controls), occupational asbestos exposure (yes, no), trial arm assignment (intervention, placebo), and tumor histology (non-small cell lung cancer, small cell lung cancer). Since MSH5 rs3131379/BAT3 rs3117582 and CHRNA5/CHRNA3/CHRNB4 rs16969968 are validated lung cancer susceptibility loci, we also examined associations stratified by these SNPs. Wald p-values of the cross product of SNP genotype and the categorical exposure of interest were generated to formally test for departure from multiplicative relationships. As these are exploratory analyses, the reported p-values are not adjusted for multiple comparisons.

Haplotype analysis

Pairwise linkage disequilibrium (LD) patterns were visualized for each gene region using Haploview, version 4.2 [39]. Haplotype imputation from tagSNP genotype data was conducted using the haplo.stats package (http://mayoresearch.mayo.edu/schaid_lab/software.cfm) in R, version 2.10.1. The expectation-maximization algorithm was used to calculate haplotype frequencies and global tests for each gene were used to evaluate whether there were case-control differences in haplotype frequencies. Additive model ORs and 95% CIs were calculated for each imputed haplotype with a frequency of >1% using the most common haplotype as the reference group, and adjusting for the matching variables.

In order to address issues of multiple testing, we performed gene-set analyses which take into account the number of SNPs tested and the LD between SNPs in each gene (PLINK version 1.04) [40]. Test statistics were averaged for SNPs in each gene and max(T) permutation was performed 10,000 times to calculate empirical p-values taking into account the matching factors.

Results

Baseline characteristics of this nested case-control study have been reported previously [33]. Two thirds of the participants were male, and 73% of participants were current smokers. The distribution of matching factors was broadly similar between cases and controls, though cases were slightly older than controls and were more likely to have reported a heavier smoking history. We successfully evaluated a total of 175 SNPs, with SNP coverage (the proportion of common SNPs represented by the genotyped SNPs through LD in the HapMap Phase I and II CEU populations) for all genes at >=95%, except for MLH1 (89%), MBD4 (93%) and XRCC2 (94%).

We observed associations with lung cancer for SNPs in the MMR genes MSH5 and MSH2, and in the BER genes PCNA and UNG. We observed a marginal association with a SNP in MPG. Specifically, the minor alleles of the MSH5 SNPs rs3131379 and rs707938 were associated with an increased risk of lung cancer, and there was no association with the only non-synonymous SNP in that gene (rs6905572). Perallele ORs (95% CI) for rs3131379 (A allele) and rs707938 (G allele) were, respectively 1.37 (1.13-1.65) and 1.15 (1.01-1.31) (Table 1). For rs3131379, the ORs and 95% CIs for one or two copies of the A allele (compared to none) were 1.31 (1.06-1.62) and 2.30 (1.12-4.72). The rs3131379 A allele was carried in a single haplotype that also contained the minor allele for rs707938 (although the minor allele for rs707938 was carried in several additional haplotypes), at a frequency of 11% in controls and 14% in cases. Compared to the haplotype containing no variant alleles, this haplotype was associated with an increased risk (OR 1.43, 95% CI 1.15-1.77; global p-value 0.02) (Table 3). Risk of lung cancer associated with this SNP/haplotype did not appear to vary by gender, current/former cigarette smoking, pack-years of smoking, asbestos exposure, or randomization arm, nor did it differ between small cell and non-small cell histologies (data are not shown, but are available upon request). MSH2 rs2303428 was associated with an increased risk of lung cancer (per-G-allele OR 1.24, 95% CI 1.01-1.52), and this association did not vary by any subgroup. The only haplotype that included the rs2303428 G allele was not associated with risk, nor were any other haplotypes in this gene (Table 3).

Table 1.

Per-allele ORs for BER, HR, and MMR SNPs and lung cancer risk among non-Hispanic white smokers

			Major allele	Minor allele		Genotype distribution^a						All

					MAF^c	Cases			Controls			(744 cases, 1,477 controls)

Pathway	Gene	SNP	(A)	(a)	(%)	AA	Aa	aa	AA	Aa	aa	OR	(95% CI)	p-value
MMR^b	MLH1	rs1800734	G	A	23.0%	470	212	46	858	520	66	0.91	(0.78, 1.06)	0.215
MMR	MLH1	rs1540354	T	A	17.0%	499	226	18	1026	399	50	1.05	(0.89, 1.24)	0.553
MMR	MLH1	rs4579	G	A	45.0%	224	361	159	454	719	304	1.03	(0.91, 1.17)	0.652
MMR	MSH2	rs10188090	G	A	37.0%	275	366	102	576	706	194	1.06	(0.93, 1.21)	0.394
MMR	MSH2	rs2059520	A	G	34.0%	299	355	84	626	675	166	1.05	(0.92, 1.20)	0.442
MMR	MSH2	rs2303428	A	G	9.0%	589	142	13	1204	266	6	1.24	(1.01, 1.52)	0.043
MMR	MSH2	rs12998837	T	A	13.0%	532	165	12	1068	313	32	1.00	(0.83, 1.21)	0.991
MMR	MSH2	rs6544991	A	C	18.0%	506	220	17	1008	413	52	0.97	(0.82, 1.14)	0.699
MMR	MSH2	rs13425206	C	A	4.0%	690	53	1	1356	118	2	0.90	(0.65, 1.24)	0.509
MMR	MSH2	rs17036577	A	G	9.0%	623	117	4	1227	241	8	0.96	(0.76, 1.20)	0.723
MMR	MSH2	rs1863332	A	C	8.0%	614	120	9	1239	226	12	1.09	(0.88, 1.36)	0.423
MMR	MSH2	rs1981929	A	G	41.0%	272	348	124	513	712	251	0.95	(0.84, 1.08)	0.459
MMR	MSH2	rs4638843	G	C	12.0%	581	151	11	1135	313	27	0.92	(0.76, 1.12)	0.41
MMR	MSH2	rs4952887	G	A	8.0%	627	108	9	1255	209	11	1.08	(0.86, 1.35)	0.506
MMR	MSH2	rs6741393	G	A	3.0%	697	45	2	1380	92	2	1.00	(0.71, 1.42)	0.992
MMR	MSH2	rs6753135	G	A	12.0%	579	152	12	1139	317	19	0.98	(0.81, 1.19)	0.828
MMR	MSH2	rs10191478	G	T	43.0%	229	376	139	477	730	270	1.04	(0.92, 1.18)	0.54
MMR	MSH2	rs4987188	G	A	2.0%	713	31	0	1428	47	1	1.29	(0.82, 2.04)	0.27
MMR	MSH4	rs5745325	G	A	28.0%	384	306	54	773	576	128	0.98	(0.86, 1.13)	0.797
MMR	MSH4	rs5745433	A	C	26.0%	424	247	69	823	547	106	1.02	(0.89, 1.17)	0.752
MMR	MSH4	rs3819949	A	G	34.0%	339	297	91	633	614	188	0.94	(0.82, 1.07)	0.333
MMR	MSH4	rs2047435	G	A	13.0%	552	173	17	1110	343	22	1.06	(0.89, 1.28)	0.507
MMR	MSH4	rs1146644	G	A	42.0%	249	363	131	515	683	278	1.00	(0.88, 1.13)	0.995
MMR	MSH4	rs1498313	A	G	40.0%	275	327	141	528	717	230	1.05	(0.92, 1.19)	0.477
MMR	MSH4	rs5745513	T	A	8.0%	616	122	4	1248	219	8	1.10	(0.88, 1.39)	0.39
MMR	MSH4	rs5745549	G	A	3.0%	690	53	1	1388	85	3	1.19	(0.85, 1.67)	0.317
MMR	MSH5	rs6905572	G	A	13%	572	162	10	1120	333	24	0.95	(0.79, 1.15)	0.621
MMR	MSH5	rs3131379	G	A	11%	548	180	16	1166	292	15	1.37	(1.13, 1.65)	0.001
MMR	MSH5	rs707937	C	G	20%	477	236	29	948	469	56	1.01	(0.86, 1.18)	0.884
MMR	MSH5	rs707938	A	G	32%	322	318	104	681	635	161	1.15	(1.01, 1.31)	0.038
MMR	MSH5	rs707939	C	A	35%	326	343	73	620	673	176	0.91	(0.80, 1.04)	0.184
MMR	MSH5	rs2299851	G	A	10%	604	133	5	1202	256	17	0.99	(0.80, 1.22)	0.928
MMR	MSH5	rs3117572	G	A	17%	514	201	29	1014	416	47	1.00	(0.85, 1.18)	0.999
MMR	MSH5	rs3131382	G	A	6%	645	80	6	1273	164	4	1.04	(0.80, 1.35)	0.76
MMR	MSH5	rs1802127	C	T	2%	716	28	0	1427	49	1	1.10	(0.69, 1.76)	0.683
MMR	MSH6	rs1800932	A	G	18%	498	220	25	990	428	53	1.00	(0.85, 1.18)	0.984
MMR	MSH6	rs1800937	G	A	11%	599	136	9	1169	297	10	0.95	(0.77, 1.17)	0.615
MMR	MSH6	rs1800935	A	G	29%	381	289	66	736	604	125	0.97	(0.84, 1.11)	0.641
MMR	MSH6	rs2710163	A	G	39%	278	340	124	551	690	233	1.02	(0.90, 1.16)	0.748
MMR	MSH6	rs2348244	A	G	14%	545	185	13	1084	358	33	0.98	(0.82, 1.18)	0.856
MMR	MSH6	rs3136245	G	A	19%	488	226	27	960	465	48	1.00	(0.85, 1.17)	0.972
MMR	MSH6	rs330792	A	C	11%	565	170	9	1156	307	14	1.13	(0.93, 1.37)	0.23
MMR	MSH6	rs1800936	C	T	13%	574	155	15	1110	350	17	0.94	(0.77, 1.13)	0.501
MMR	MSH6	rs3136329	A	G	42%	242	359	140	481	731	259	1.03	(0.90, 1.16)	0.701
BER^b	APEX1	rs1760945	C	T	8%	637	100	4	1249	213	10	0.92	(0.73, 1.17)	0.509
BER	APEX1	rs1760944	C	A	39%	270	352	119	547	694	231	1.03	(0.91, 1.18)	0.607
BER	APEX1	rs3136817	T	C	25%	411	276	57	840	541	96	1.08	(0.93, 1.24)	0.313
BER	APEX1	rs1130409	A	C	47%	192	361	190	413	723	338	1.10	(0.98, 1.25)	0.116
BER	LIG3	rs3135962	A	C	7%	647	95	2	1264	207	6	0.91	(0.71, 1.16)	0.443
BER	LIG3	rs3135989	A	C	6%	644	97	2	1301	174	1	1.17	(0.90, 1.51)	0.249
BER	LIG3	rs2074516	G	C	10%	598	135	8	1184	276	17	0.96	(0.78, 1.18)	0.696
BER	LIG3	rs4796030	C	A	42%	242	377	123	486	730	261	0.99	(0.87, 1.13)	0.904
BER	LIG3	rs1052536	G	A	47%	189	396	156	415	742	320	1.04	(0.91, 1.18)	0.584
BER	MBD4	rs3138360	G	A	6%	666	77	1	1292	174	3	0.85	(0.64, 1.12)	0.253
BER	MBD4	rs140696	G	A	9%	604	137	3	1210	257	10	1.04	(0.84, 1.29)	0.727
BER	MBD4	rs9821282	G	A	16%	537	185	20	1035	408	34	0.94	(0.79, 1.11)	0.453
BER	MPG	rs1013358	T	C	14%	577	153	14	1093	354	30	0.86	(0.71, 1.04)	0.110
BER	MPG	rs2562182	A	G	16%	559	164	18	1044	400	32	0.84	(0.70, 1.00)	0.050
BER	MPG	rs743725	C	T	19%	518	203	23	978	450	49	0.88	(0.75, 1.04)	0.140
BER	MUTYH	rs3219489	G	C	25%	417	279	42	825	562	79	1.00	(0.86, 1.15)	0.948
BER	MUTYH	rs3219487	G	A	8%	628	112	3	1240	225	9	0.96	(0.76, 1.21)	0.728
BER	MUTYH	rs3219484	G	A	7%	638	106	0	1273	198	6	1.01	(0.79, 1.30)	0.930
BER	MUTYH	rs3219474	A	G	8%	631	109	4	1255	212	6	1.04	(0.82, 1.32)	0.747
BER	NEIL1	rs7182283	G	T	50%	185	359	192	349	777	339	1.04	(0.91, 1.18)	0.578
BER	NEIL1	rs4462560	C	G	26%	428	274	41	813	565	99	0.91	(0.78, 1.05)	0.194
BER	NEIL2	rs4841593	C	G	8%	621	120	2	1256	209	11	1.08	(0.86, 1.36)	0.510
BER	NEIL2	rs904009	A	C	24%	434	252	57	851	535	88	1.02	(0.88, 1.18)	0.804
BER	NEIL2	rs2010628	G	T	23%	445	248	51	881	521	75	1.03	(0.89, 1.20)	0.664
BER	NEIL2	rs8191529	G	C	9%	634	105	5	1229	240	8	0.87	(0.69, 1.10)	0.238
BER	NEIL2	rs804267	A	G	33%	333	319	92	669	651	155	1.05	(0.92, 1.20)	0.456
BER	NEIL2	rs8191534	T	A	23%	441	250	53	865	528	82	1.01	(0.88, 1.17)	0.858
BER	NEIL2	rs8191542	G	C	22%	437	260	38	889	503	70	1.06	(0.91, 1.24)	0.422
BER	NEIL2	rs8191589	T	A	22%	443	263	37	889	516	72	1.04	(0.89, 1.20)	0.645
BER	NEIL2	rs4840581	G	A	45%	232	359	153	442	724	309	0.96	(0.85, 1.09)	0.563
BER	NEIL2	rs4840583	C	T	45%	219	367	158	425	771	281	1.03	(0.90, 1.17)	0.687
BER	NEIL2	rs804256	T	C	36%	304	338	102	597	695	185	1.01	(0.88, 1.15)	0.914
BER	NEIL2	rs8191604	A	C	26%	409	276	57	807	569	99	1.00	(0.87, 1.15)	0.987
BER	NEIL2	rs4840585	A	C	8%	627	115	2	1258	208	10	1.05	(0.83, 1.32)	0.700
BER	NEIL2	rs1874546	C	G	24%	456	254	31	859	526	83	0.87	(0.75, 1.01)	0.074
BER	NEIL2	rs8191649	C	T	22%	466	233	45	889	519	69	0.96	(0.83, 1.12)	0.620
BER	NEIL2	rs6982453	A	G	49%	200	389	154	374	755	345	0.92	(0.81, 1.04)	0.189
BER	NEIL2	rs1534862	G	A	23%	454	243	46	864	534	78	0.95	(0.82, 1.10)	0.464
BER	NEIL2	rs6997097	A	G	7%	654	84	4	1281	186	7	0.92	(0.71, 1.19)	0.514
BER	NEIL2	rs1043180	G	A	12%	575	160	8	1127	333	17	0.94	(0.77, 1.14)	0.533
BER	NEIL2	rs2645450	T	C	23%	426	273	45	878	531	68	1.10	(0.95, 1.28)	0.187
BER	NEIL2	rs904015	G	A	35%	321	327	95	614	678	174	0.99	(0.87, 1.13)	0.877
BER	NTHL1	rs12447809	G	T	19%	474	233	37	960	463	54	1.07	(0.92, 1.26)	0.361
BER	NTHL1	rs1132368	G	A	4%	689	54	1	1348	128	0	0.86	(0.62, 1.20)	0.379
BER	NTHL1	rs2531213	A	G	3%	697	47	0	1378	99	0	0.93	(0.65, 1.33)	0.672
BER	NTHL1	rs3211995	G	A	17%	517	205	22	1009	427	41	0.95	(0.81, 1.13)	0.579
BER	NTHL1	rs2516740	A	C	23%	452	255	37	880	524	73	0.96	(0.83, 1.12)	0.593
BER	NTHL1	rs2516739	G	A	22%	459	248	37	886	517	72	0.95	(0.82, 1.10)	0.495
BER	OGG1	rs159153	A	G	29%	353	307	84	748	584	140	1.11	(0.97, 1.27)	0.127
BER	OGG1	rs1052133	C	G	23%	440	265	39	873	519	85	1.00	(0.86, 1.16)	0.992
BER	OGG1	rs293795	A	G	18%	498	222	24	990	438	49	0.98	(0.83, 1.15)	0.815
BER	OGG1	rs293794	A	G	18%	499	221	24	986	439	49	0.97	(0.83, 1.14)	0.736
BER	OGG1	rs293796	G	A	8%	623	110	8	1260	207	8	1.14	(0.91, 1.43)	0.253
BER	PCNA	rs3729558	G	C	47%	223	373	148	422	719	335	0.92	(0.81, 1.05)	0.205
BER	PCNA	rs17349	G	A	12%	594	140	8	1147	309	19	0.88	(0.72, 1.07)	0.199
BER	PCNA	rs25406	G	A	40%	239	370	135	553	675	249	1.14	(1.01, 1.29)	0.038
BER	PCNA	rs25405	A	G	12%	591	141	8	1145	306	19	0.89	(0.73, 1.09)	0.262
BER	PCNA	rs4239761	A	G	19%	476	233	34	970	439	68	1.04	(0.90, 1.22)	0.587
BER	PNKP	rs7257463	T	A	34%	319	327	98	628	685	164	1.04	(0.92, 1.19)	0.518
BER	PNKP	rs1290646	G	A	50%	188	383	172	373	734	366	0.96	(0.85, 1.09)	0.558
BER	PNKP	rs3739177	C	T	8%	615	124	5	1259	211	7	1.20	(0.96, 1.51)	0.112
BER	PNKP	rs2257103	G	A	39%	265	362	115	546	699	224	1.04	(0.92, 1.19)	0.519
BER	PNKP	rs2353005	G	A	16%	543	187	14	1057	379	41	0.92	(0.77, 1.10)	0.356
BER	POLB	rs3136711	T	C	8%	627	111	6	1247	219	11	1.03	(0.82, 1.29)	0.829
BER	POLB	rs2976244	A	T	7%	645	95	2	1288	177	11	0.98	(0.76, 1.25)	0.851
BER	POLB	rs3136790	A	C	11%	585	154	5	1170	286	18	1.00	(0.82, 1.22)	0.991
BER	POLB	rs3136797	C	G	2%	716	28	0	1430	46	1	1.15	(0.72, 1.84)	0.569
BER	POLB	rs2073664	G	A	6%	647	89	2	1288	168	11	0.96	(0.75, 1.24)	0.761
BER	POLI	rs3730668	C	A	41%	283	336	116	524	681	254	0.91	(0.80, 1.03)	0.135
BER	POLI	rs476630	G	A	29%	367	300	77	750	600	126	1.08	(0.95, 1.24)	0.248
BER	POLI	rs686881	A	G	6%	643	100	1	1310	161	6	1.20	(0.92, 1.54)	0.173
BER	POLI	rs3730814	C	A	23%	431	272	40	886	499	89	1.04	(0.90, 1.20)	0.593
BER	POLI	rs3218786	A	G	3%	701	40	2	1391	82	0	1.06	(0.73, 1.53)	0.771
BER	POLI	rs8305	A	G	30%	359	315	70	716	630	131	1.03	(0.90, 1.18)	0.673
BER	POLI	rs596986	G	C	6%	643	100	1	1310	161	6	1.20	(0.92, 1.54)	0.173
BER	PPP1R13L	rs6966	T	A	16%	539	185	20	1048	377	47	0.95	(0.80, 1.12)	0.524
BER	PPP1R13L	rs4803817	A	G	23%	451	255	36	874	510	88	0.94	(0.81, 1.09)	0.425
BER	PPP1R13L	rs10412761	A	G	40%	282	357	105	541	681	252	0.92	(0.81, 1.05)	0.204
BER	PPP1R13L	rs1005165	G	A	17%	527	194	22	1016	410	45	0.93	(0.78, 1.10)	0.367
BER	RAD18	rs4389469	C	T	40%	282	349	113	547	691	239	0.97	(0.85, 1.10)	0.619
BER	RAD18	rs369032	A	G	38%	285	357	102	579	674	224	0.99	(0.87, 1.13)	0.915
BER	RAD18	rs2035221	G	A	9%	613	123	6	1227	235	10	1.05	(0.85, 1.31)	0.641
BER	RAD18	rs593205	G	C	8%	605	136	3	1251	211	12	1.23	(0.99, 1.53)	0.066
BER	RAD18	rs373572	A	G	26%	402	283	56	800	571	105	1.02	(0.88, 1.17)	0.805
BER	RAD18	rs13088787	C	A	13%	569	165	10	1127	326	24	0.98	(0.81, 1.19)	0.868
BER	RAD18	rs615967	T	C	21%	461	253	30	920	480	77	0.99	(0.85, 1.15)	0.850
BER	RAD18	rs604092	A	G	18%	501	220	22	1004	414	56	1.00	(0.85, 1.18)	0.962
BER	SMUG1	rs971	G	A	34%	324	323	93	654	647	172	1.03	(0.90, 1.17)	0.654
BER	SMUG1	rs3087404	G	A	46%	226	358	157	437	714	325	0.96	(0.85, 1.09)	0.573
BER	TDG	rs172814	A	G	16%	548	186	10	1052	384	40	0.87	(0.72, 1.03)	0.113
BER	TDG	rs4135054	G	A	11%	573	163	8	1170	291	16	1.11	(0.91, 1.35)	0.290
BER	TDG	rs4135061	A	G	27%	404	297	41	788	578	109	0.93	(0.80, 1.07)	0.305
BER	TDG	rs4135064	G	A	9%	599	140	4	1221	246	9	1.13	(0.91, 1.40)	0.274
BER	TDG	rs4135081	A	G	37%	273	370	101	579	695	200	1.06	(0.93, 1.21)	0.388
BER	TDG	rs3751206	G	A	7%	644	96	2	1292	174	9	1.04	(0.81, 1.34)	0.735
BER	TDG	rs4135087	G	A	10%	610	130	3	1184	278	13	0.87	(0.70, 1.08)	0.197
BER	TDG	rs167715	A	G	11%	576	160	8	1164	294	19	1.05	(0.87, 1.28)	0.598
BER	TDG	rs10861152	G	A	39%	291	350	97	538	715	216	0.91	(0.80, 1.03)	0.142
BER	TDG	rs1866074	A	G	51%	178	387	178	377	689	409	0.96	(0.85, 1.09)	0.517
BER	TDG	rs4135106	A	G	7%	654	86	2	1282	183	9	0.88	(0.68, 1.14)	0.326
BER	TDG	rs4135128	G	C	9%	617	123	3	1241	218	17	1.02	(0.82, 1.27)	0.849
BER	UNG	rs3890995	A	G	18%	491	233	20	986	461	30	1.06	(0.89, 1.25)	0.529
BER	UNG	rs1018783	T	A	16%	492	232	20	1033	403	41	1.13	(0.96, 1.33)	0.152
BER	UNG	rs2569987	A	G	17%	501	223	19	1009	421	45	1.01	(0.86, 1.19)	0.893
BER	UNG	rs246079	A	G	42%	217	381	145	485	750	241	1.15	(1.01, 1.31)	0.034
BER	UNG	rs34259	C	G	20%	446	266	30	938	476	62	1.10	(0.94, 1.28)	0.245
BER	XRCC1	rs25487	C	T	37%	288	365	91	604	664	209	1.00	(0.88, 1.14)	0.950
BER	XRCC1	rs25486	A	G	37%	288	365	90	599	664	209	1.00	(0.87, 1.13)	0.946
BER	XRCC1	rs25489	C	T	4%	685	57	2	1348	128	1	0.94	(0.69, 1.29)	0.701
BER	XRCC1	rs1799782	G	A	5%	661	82	1	1320	153	4	1.05	(0.80, 1.38)	0.733
BER	XRCC1	rs3213344	G	C	5%	661	80	1	1320	150	5	1.03	(0.78, 1.35)	0.844
BER	XRCC1	rs3213334	G	A	24%	434	266	44	866	509	102	0.99	(0.85, 1.14)	0.851
BER	XRCC1	rs2023614	G	C	8%	633	107	1	1249	220	6	0.92	(0.72, 1.18)	0.513
BER	XRCC1	rs2854510	A	G	21%	470	245	28	936	461	78	0.96	(0.82, 1.12)	0.586
BER	XRCC1	rs2854509	C	A	22%	456	242	42	914	480	80	1.02	(0.88, 1.18)	0.793
BER	XRCC1	rs3213266	G	A	8%	630	111	2	1238	232	7	0.92	(0.73, 1.16)	0.477
BER	XRCC1	rs3213255	A	G	43.0%	242	375	126	491	712	274	0.98	(0.86, 1.11)	0.759
HR^b	XRCC2	rs3218536	G	A	7%	631	109	2	1262	210	5	1.05	(0.82, 1.33)	0.715
HR	XRCC2	rs6964582	G	C	4%	663	77	2	1349	124	2	1.26	(0.95, 1.68)	0.114
HR	XRCC2	rs3218438	T	C	9%	598	138	8	1215	247	15	1.10	(0.89, 1.35)	0.378
HR	XRCC2	rs3218408	A	C	22%	430	278	35	901	494	78	1.08	(0.93, 1.25)	0.316
HR	XRCC2	rs3218373	C	A	9%	617	119	7	1230	235	10	1.03	(0.82, 1.28)	0.808
HR	XRCC2	rs2040639	G	A	48%	212	366	166	387	767	322	0.97	(0.85, 1.10)	0.625
HR	XRCC3	rs861539	G	A	39%	307	333	104	536	724	217	0.89	(0.78, 1.01)	0.067
HR	XRCC3	rs3212102	C	T	3%	711	33	0	1402	75	0	0.88	(0.58, 1.33)	0.539
HR	XRCC3	rs3212090	G	A	32%	311	354	78	694	628	151	1.12	(0.98, 1.28)	0.087
HR	XRCC3	rs3212079	G	A	7%	644	99	1	1271	191	12	0.93	(0.73, 1.19)	0.585
HR	XRCC3	rs861530	C	T	29%	362	328	54	733	625	119	1.01	(0.88, 1.17)	0.839
HR	XRCC3	rs1799794	A	G	18%	477	245	22	980	442	48	1.08	(0.92, 1.27)	0.340
HR	XRCC3	rs861528	G	A	26%	427	267	45	807	550	107	0.90	(0.78, 1.04)	0.157

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Among all cases and controls; AA, homozygous major allele; Aa, heterozygous; aa, homozygous minor allele; numbers do not sum to total due to missing.

MMR, mismatch repair; BER, base excision repair; HR, homologous recombination.

MAF, minor allele frequency.

Table 3.

MSH2, MSH5, PCNA, and UNG haplotypes and lung cancer risk

graphic file with name ijmeg0004-0011-t1.jpg

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For the BER genes, the A allele of PCNA rs25406 was associated with an increased risk of lung cancer (per-allele OR 1.14, 95% CI 1.01-1.29; Table 1), with an association present only among individuals ages 70 years and older (per allele OR 1.38 (1.14-1.66)); among women (1.37 (1.10-1.70)); and among participants who had not been exposed to asbestos (1.22 (1.06-1.40)) (data are not shown, but are available upon request). The G allele of UNG rs246079 was associated with lung cancer risk (per-allele OR 1.15, 95% CI 1.01-1.31; Table 1), and associations did not vary by subgroup. The p-value for gene-level significance for UNG was 0.02, and the haplotype that contained the major allele for all of the SNPs was more frequent in controls than cases (41.1% versus 37.9%, respectively). Four out of five of the other haplotypes included the minor allele of rs246079 and all had ORs that were greater than 1. Only the combined rare genotypes were strongly associated with an increased risk (OR 2.35, 95% CI 1.27-4.36; Table 3). The G allele of MPG rs2562182 was marginally associated with a decreased risk of lung cancer (per-allele OR 0.84, 95% CI 0.70, 1.00; Table 1), and this association was present only among individuals receiving placebo (per allele OR 0.68 (0.51-0.90)). While the p-value for gene-level significance for XRCC2 was 0.03, no SNPs (Table 1) or haplotypes in this gene were individually associated with risk. None of the SNPs in XRCC1 were associated with lung cancer risk overall, but the magnitude of the associations between 4 SNPs (representing 2 SNPs with r²<0.80) in XRCC1 and lung cancer risk appeared to differ between men and women, with interaction p-values less than 0.004 and 0.0001 for rs3213334 (data are not shown, but are available upon request).

In exploratory analyses stratified by the known lung cancer susceptibility loci CHRNA5 rs16969968 and MSH5 rs3131379 genotypes, we observed a departure from a multiplicative relationship (p<0.05) for SNPs in MSH2, MSH4, MSH5, LIG3, and XRCC2 by rs16969968 genotype, with generally stronger associations among individuals carrying the rs16969968 GG genotype than the AG/AA (risk) genotypes. When we stratified by MSH5 rs3131379 genotype, associations with lung cancer were generally stronger among individuals carrying at least one of the rs3131379 A (risk) alleles compared to the GG genotype (Table 2), with a departure from a multiplicative relationship for at least one SNP in each of the MMR genes studied (MLH1, MSH2, MSH4, and MSH6), as well as in the BER genes MUTYH, NTHL1, RAD18, and UNG and the HR gene XRCC2. Among SNPs for which we observed an overall association with lung cancer risk, associations varied by rs3131379 genotype only for UNG rs246079. The per G allele ORs and 95% CIs among AA/AG carriers and among GG carriers were 1.48 (1.13, 1.94) and 1.07 (0.92, 1.24), respectively (p_interaction= 0.038; Table 2).

Table 2.

Per-allele ORs for BER, HR, and MMR SNPs and lung cancer risk among non-Hispanic white smokers, stratified by MSH5 rs3131379 and CHRNA5 rs16969968 genotypes

			rs16969968 GG		rs16969968 AG/AA			rs3131379 GG		rs3131379 AG/AA
			(258 ca, 624 co)		(483 ca, 852 co)			(548 ca, 1,166 co)		(196 ca, 307 co)

Pathway	Gene	SNP	OR	(95% CI)	OR	(95% CI)	p^c	OR	(95% CI)	OR	(95% CI)	p^c
MMR^b	MLH1	rs1800734	0.99	(0.77, 1.28)	0.85	(0.70, 1.03)	0.410	0.93	(0.78, 1.11)	0.84	(0.61, 1.15)	0.505
MMR	MLH1	rs1540354	0.99	(0.76, 1.30)	1.11	(0.90, 1.37)	0.605	0.95	(0.78, 1.15)	1.40	(1.01, 1.95)	0.039
MMR	MLH1	rs4579	1.01	(0.82, 1.25)	1.03	(0.88, 1.21)	0.905	1.07	(0.92, 1.23)	0.91	(0.70, 1.19)	0.344
MMR	MSH2	rs10188090	1.13	(0.91, 1.41)	1.00	(0.85, 1.18)	0.392	1.01	(0.87, 1.17)	1.22	(0.93, 1.61)	0.190
MMR	MSH2	rs2059520	1.12	(0.89, 1.40)	1.02	(0.86, 1.21)	0.561	1.00	(0.85, 1.16)	1.25	(0.95, 1.65)	0.141
MMR	MSH2	rs2303428	1.42	(1.01, 2.01)	1.13	(0.87, 1.47)	0.280	1.30	(1.03, 1.64)	1.05	(0.67, 1.66)	0.457
MMR	MSH2	rs12998837	1.01	(0.75, 1.36)	1.01	(0.79, 1.28)	0.992	0.88	(0.71, 1.10)	1.47	(1.01, 2.13)	0.025
MMR	MSH2	rs6544991	0.99	(0.75, 1.30)	0.95	(0.77, 1.18)	0.840	0.86	(0.71, 1.04)	1.41	(1.00, 1.98)	0.012
MMR	MSH2	rs13425206	1.00	(0.59, 1.69)	0.84	(0.55, 1.28)	0.642	0.89	(0.62, 1.29)	0.88	(0.43, 1.81)	0.973
MMR	MSH2	rs17036577	0.77	(0.52, 1.15)	1.08	(0.81, 1.43)	0.179	0.94	(0.72, 1.22)	0.98	(0.62, 1.56)	0.796
MMR	MSH2	rs1863332	1.08	(0.74, 1.57)	1.12	(0.86, 1.47)	0.865	1.09	(0.86, 1.40)	1.17	(0.73, 1.88)	0.816
MMR	MSH2	rs1981929	0.90	(0.73, 1.11)	0.98	(0.84, 1.15)	0.549	0.97	(0.84, 1.12)	0.91	(0.70, 1.17)	0.606
MMR	MSH2	rs4638843	0.98	(0.72, 1.33)	0.90	(0.70, 1.15)	0.595	1.07	(0.86, 1.33)	0.57	(0.38, 0.86)	0.009
MMR	MSH2	rs4952887	1.53	(1.05, 2.22)	0.88	(0.66, 1.16)	0.022	1.12	(0.87, 1.44)	1.00	(0.62, 1.61)	0.663
MMR	MSH2	rs6741393	1.20	(0.66, 2.16)	0.85	(0.55, 1.32)	0.342	1.12	(0.76, 1.65)	0.65	(0.30, 1.44)	0.260
MMR	MSH2	rs6753135	0.90	(0.64, 1.26)	1.01	(0.79, 1.28)	0.616	0.99	(0.80, 1.24)	0.90	(0.60, 1.35)	0.768
MMR	MSH2	rs10191478	1.16	(0.93, 1.44)	0.97	(0.83, 1.14)	0.197	1.01	(0.87, 1.17)	1.15	(0.89, 1.50)	0.354
MMR	MSH2	rs4987188	1.55	(0.73, 3.27)	1.09	(0.61, 1.97)	0.487	1.71	(1.04, 2.83)	0.38	(0.11, 1.39)	0.034
MMR	MSH4	rs5745325	1.26	(1.01, 1.57)	0.85	(0.71, 1.02)	0.009	0.90	(0.77, 1.06)	1.26	(0.96, 1.66)	0.035
MMR	MSH4	rs5745433	0.97	(0.77, 1.23)	1.05	(0.88, 1.25)	0.589	0.97	(0.83, 1.14)	1.20	(0.91, 1.58)	0.250
MMR	MSH4	rs3819949	0.86	(0.69, 1.07)	0.97	(0.82, 1.15)	0.407	0.97	(0.83, 1.13)	0.84	(0.64, 1.10)	0.359
MMR	MSH4	rs2047435	0.97	(0.71, 1.31)	1.13	(0.90, 1.43)	0.464	1.18	(0.96, 1.45)	0.74	(0.50, 1.09)	0.053
MMR	MSH4	rs1146644	0.85	(0.69, 1.05)	1.09	(0.93, 1.28)	0.072	1.11	(0.96, 1.28)	0.69	(0.53, 0.89)	0.002
MMR	MSH4	rs1498313	0.95	(0.78, 1.17)	1.11	(0.94, 1.30)	0.275	1.05	(0.91, 1.22)	1.03	(0.80, 1.33)	0.842
MMR	MSH4	rs5745513	1.64	(1.16, 2.31)	0.87	(0.64, 1.19)	0.008	1.06	(0.81, 1.38)	1.23	(0.78, 1.94)	0.526
MMR	MSH4	rs5745549	0.83	(0.48, 1.44)	1.60	(1.02, 2.51)	0.067	1.59	(1.08, 2.34)	0.45	(0.21, 0.97)	0.005
MMR	MSH5	rs6905572	1.01	(0.74, 1.38)	0.93	(0.73, 1.19)	0.785	1.01	(0.82, 1.25)	0.80	(0.48, 1.34)	0.385
MMR	MSH5	rs3131379	1.12	(0.82, 1.52)	1.55	(1.22, 1.97)	0.101	NA			NA
MMR	MSH5	rs707937	0.93	(0.72, 1.21)	1.07	(0.88, 1.31)	0.361	1.02	(0.86, 1.22)	1.30	(0.84, 2.01)	0.361
MMR	MSH5	rs707938	0.96	(0.77, 1.19)	1.28	(1.09, 1.51)	0.028	1.03	(0.87, 1.21)	1.16	(0.79, 1.71)	0.593
MMR	MSH5	rs707939	1.18	(0.95, 1.47)	0.78	(0.65, 0.92)	0.003	0.96	(0.83, 1.12)	0.98	(0.67, 1.42)	0.975
MMR	MSH5	rs2299851	0.90	(0.63, 1.28)	1.05	(0.80, 1.37)	0.418	1.05	(0.83, 1.32)	0.85	(0.48, 1.49)	0.485
MMR	MSH5	rs3117572	0.90	(0.69, 1.19)	1.06	(0.86, 1.30)	0.435	1.11	(0.93, 1.32)	0.68	(0.40, 1.13)	0.094
MMR	MSH5	rs3131382	0.82	(0.53, 1.28)	1.19	(0.86, 1.65)	0.217	1.15	(0.88, 1.52)	0.60	(0.24, 1.49)	0.186
MMR	MSH5	rs1802127	0.90	(0.37, 2.19)	1.18	(0.68, 2.05)	0.596	1.02	(0.61, 1.71)	1.99	(0.58, 6.82)	0.342
MMR	MSH6	rs1800932	0.93	(0.71, 1.22)	1.05	(0.86, 1.29)	0.550	1.08	(0.90, 1.31)	0.75	(0.54, 1.04)	0.068
MMR	MSH6	rs1800937	0.79	(0.55, 1.15)	1.03	(0.80, 1.33)	0.298	0.81	(0.64, 1.04)	1.53	(1.01, 2.33)	0.012
MMR	MSH6	rs1800935	0.88	(0.70, 1.11)	1.02	(0.86, 1.22)	0.370	0.98	(0.83, 1.14)	0.91	(0.69, 1.21)	0.751
MMR	MSH6	rs2710163	1.05	(0.85, 1.29)	1.03	(0.87, 1.20)	0.914	1.09	(0.94, 1.26)	0.81	(0.62, 1.06)	0.063
MMR	MSH6	rs2348244	1.07	(0.80, 1.42)	0.95	(0.75, 1.19)	0.562	1.05	(0.85, 1.28)	0.82	(0.56, 1.21)	0.271
MMR	MSH6	rs3136245	1.12	(0.86, 1.44)	0.94	(0.76, 1.16)	0.371	1.03	(0.86, 1.23)	0.93	(0.66, 1.32)	0.569
MMR	MSH6	rs330792	1.19	(0.87, 1.63)	1.09	(0.85, 1.40)	0.675	1.14	(0.91, 1.43)	1.08	(0.72, 1.60)	0.801
MMR	MSH6	rs1800936	0.85	(0.62, 1.19)	0.99	(0.78, 1.25)	0.585	0.84	(0.67, 1.05)	1.38	(0.93, 2.04)	0.032
MMR	MSH6	rs3136329	1.04	(0.84, 1.30)	1.01	(0.86, 1.18)	0.799	0.96	(0.83, 1.11)	1.24	(0.96, 1.61)	0.090
BER^b	APEX1	rs1760945	0.83	(0.55, 1.26)	0.96	(0.72, 1.29)	0.521	0.97	(0.74, 1.27)	0.81	(0.49, 1.33)	0.576
BER	APEX1	rs1760944	0.96	(0.78, 1.18)	1.09	(0.92, 1.28)	0.307	1.05	(0.91, 1.21)	0.99	(0.76, 1.30)	0.622
BER	APEX1	rs3136817	1.05	(0.84, 1.32)	1.10	(0.92, 1.32)	0.729	1.01	(0.86, 1.20)	1.21	(0.92, 1.61)	0.288
BER	APEX1	rs1130409	1.21	(0.99, 1.49)	1.05	(0.90, 1.23)	0.327	1.06	(0.92, 1.22)	1.23	(0.96, 1.58)	0.376
BER	LIG3	rs3135962	0.78	(0.51, 1.21)	0.97	(0.71, 1.33)	0.348	1.01	(0.76, 1.33)	0.63	(0.35, 1.14)	0.147
BER	LIG3	rs3135989	1.72	(1.11, 2.66)	0.94	(0.68, 1.30)	0.029	1.18	(0.88, 1.60)	1.09	(0.63, 1.87)	0.807
BER	LIG3	rs2074516	0.86	(0.61, 1.21)	1.01	(0.78, 1.31)	0.586	0.97	(0.77, 1.22)	1.01	(0.64, 1.58)	0.883
BER	LIG3	rs4796030	0.88	(0.71, 1.09)	1.04	(0.88, 1.22)	0.202	0.99	(0.86, 1.15)	0.95	(0.73, 1.24)	0.785
BER	LIG3	rs1052536	1.18	(0.96, 1.46)	0.98	(0.84, 1.16)	0.190	1.03	(0.89, 1.19)	1.07	(0.82, 1.38)	0.812
BER	MBD4	rs3138360	0.87	(0.56, 1.35)	0.85	(0.59, 1.22)	0.907	0.84	(0.61, 1.17)	0.83	(0.48, 1.44)	0.985
BER	MBD4	rs140696	1.02	(0.72, 1.45)	1.09	(0.82, 1.44)	0.702	1.02	(0.79, 1.31)	1.14	(0.73, 1.78)	0.756
BER	MBD4	rs9821282	0.94	(0.71, 1.25)	0.95	(0.76, 1.19)	0.882	0.93	(0.76, 1.14)	0.95	(0.67, 1.33)	0.977
BER	MPG	rs1013358	1.04	(0.76, 1.42)	0.76	(0.61, 0.97)	0.146	0.84	(0.68, 1.03)	0.95	(0.63, 1.42)	0.537
BER	MPG	rs2562182	0.91	(0.67, 1.25)	0.80	(0.64, 0.99)	0.525	0.82	(0.67, 1.01)	0.92	(0.61, 1.39)	0.501
BER	MPG	rs743725	0.95	(0.71, 1.26)	0.86	(0.70, 1.05)	0.628	0.88	(0.73, 1.06)	0.92	(0.63, 1.32)	0.758
BER	MUTYH	rs3219489	0.90	(0.70, 1.16)	1.04	(0.86, 1.25)	0.419	0.90	(0.76, 1.07)	1.30	(0.97, 1.74)	0.028
BER	MUTYH	rs3219487	1.22	(0.86, 1.75)	0.85	(0.62, 1.16)	0.153	0.93	(0.71, 1.21)	1.06	(0.66, 1.69)	0.628
BER	MUTYH	rs3219484	0.80	(0.52, 1.23)	1.16	(0.85, 1.58)	0.159	1.10	(0.83, 1.45)	0.77	(0.44, 1.34)	0.277
BER	MUTYH	rs3219474	0.86	(0.58, 1.28)	1.20	(0.89, 1.62)	0.182	1.09	(0.82, 1.44)	0.91	(0.58, 1.43)	0.487
BER	NEIL1	rs7182283	1.14	(0.92, 1.40)	0.98	(0.83, 1.15)	0.267	1.04	(0.90, 1.21)	1.01	(0.78, 1.30)	0.780
BER	NEIL1	rs4462560	0.88	(0.70, 1.12)	0.93	(0.77, 1.13)	0.705	0.86	(0.72, 1.01)	1.11	(0.82, 1.51)	0.137
BER	NEIL2	rs4841593	1.01	(0.70, 1.46)	1.16	(0.86, 1.56)	0.561	1.14	(0.88, 1.48)	0.91	(0.56, 1.51)	0.462
BER	NEIL2	rs904009	1.07	(0.84, 1.37)	0.98	(0.82, 1.17)	0.569	0.97	(0.82, 1.14)	1.20	(0.90, 1.62)	0.221
BER	NEIL2	rs2010628	1.09	(0.85, 1.40)	1.00	(0.83, 1.20)	0.572	1.01	(0.86, 1.20)	1.09	(0.81, 1.47)	0.718
BER	NEIL2	rs8191529	0.81	(0.56, 1.18)	0.92	(0.68, 1.24)	0.666	0.91	(0.70, 1.18)	0.75	(0.44, 1.25)	0.512
BER	NEIL2	rs804267	1.09	(0.87, 1.36)	1.03	(0.87, 1.21)	0.716	1.03	(0.89, 1.20)	1.11	(0.84, 1.46)	0.675
BER	NEIL2	rs8191534	1.05	(0.82, 1.34)	0.99	(0.82, 1.18)	0.699	0.97	(0.82, 1.15)	1.16	(0.86, 1.55)	0.333
BER	NEIL2	rs8191542	1.20	(0.94, 1.55)	0.98	(0.80, 1.18)	0.198	1.04	(0.88, 1.24)	1.13	(0.83, 1.54)	0.662
BER	NEIL2	rs8191589	1.15	(0.90, 1.48)	0.96	(0.80, 1.17)	0.292	1.02	(0.85, 1.21)	1.09	(0.80, 1.48)	0.724
BER	NEIL2	rs4840581	0.89	(0.73, 1.09)	1.02	(0.87, 1.20)	0.308	0.99	(0.86, 1.15)	0.87	(0.68, 1.12)	0.372
BER	NEIL2	rs4840583	1.07	(0.86, 1.33)	1.00	(0.85, 1.17)	0.593	1.00	(0.86, 1.16)	1.12	(0.86, 1.46)	0.436
BER	NEIL2	rs804256	0.98	(0.80, 1.21)	1.04	(0.88, 1.23)	0.781	1.03	(0.89, 1.20)	0.94	(0.72, 1.22)	0.584
BER	NEIL2	rs8191604	0.98	(0.78, 1.25)	1.00	(0.84, 1.20)	0.949	0.97	(0.82, 1.14)	1.11	(0.84, 1.48)	0.395
BER	NEIL2	rs4840585	0.99	(0.68, 1.45)	1.11	(0.82, 1.49)	0.640	1.12	(0.86, 1.46)	0.87	(0.52, 1.44)	0.417
BER	NEIL2	rs1874546	0.77	(0.59, 0.99)	0.94	(0.78, 1.14)	0.207	0.87	(0.73, 1.04)	0.85	(0.63, 1.14)	0.869
BER	NEIL2	rs8191649	1.03	(0.80, 1.33)	0.91	(0.75, 1.10)	0.447	0.93	(0.78, 1.11)	1.07	(0.79, 1.44)	0.448
BER	NEIL2	rs6982453	0.90	(0.72, 1.11)	0.92	(0.79, 1.09)	0.834	0.92	(0.80, 1.07)	0.89	(0.69, 1.16)	0.787
BER	NEIL2	rs1534862	1.02	(0.79, 1.30)	0.89	(0.74, 1.08)	0.432	0.92	(0.78, 1.10)	1.02	(0.76, 1.37)	0.562
BER	NEIL2	rs6997097	0.85	(0.55, 1.30)	0.94	(0.68, 1.30)	0.728	0.84	(0.62, 1.13)	1.18	(0.71, 1.96)	0.237
BER	NEIL2	rs1043180	0.94	(0.69, 1.29)	0.96	(0.74, 1.23)	0.984	0.94	(0.75, 1.17)	1.03	(0.67, 1.58)	0.688
BER	NEIL2	rs2645450	1.05	(0.82, 1.33)	1.16	(0.96, 1.40)	0.550	1.09	(0.92, 1.29)	1.14	(0.84, 1.55)	0.757
BER	NEIL2	rs904015	1.10	(0.88, 1.36)	0.92	(0.78, 1.09)	0.225	0.96	(0.82, 1.12)	1.08	(0.83, 1.40)	0.466
BER	NTHL1	rs12447809	0.95	(0.72, 1.24)	1.13	(0.93, 1.37)	0.336	1.00	(0.83, 1.20)	1.30	(0.95, 1.79)	0.145
BER	NTHL1	rs1132368	1.04	(0.62, 1.75)	0.73	(0.48, 1.12)	0.329	0.65	(0.43, 0.96)	1.90	(1.01, 3.58)	0.007
BER	NTHL1	rs2531213	0.83	(0.47, 1.46)	1.09	(0.68, 1.77)	0.466	1.02	(0.68, 1.54)	0.66	(0.32, 1.39)	0.316
BER	NTHL1	rs3211995	0.89	(0.67, 1.20)	0.97	(0.79, 1.20)	0.753	0.91	(0.75, 1.11)	1.03	(0.73, 1.44)	0.501
BER	NTHL1	rs2516740	1.01	(0.78, 1.30)	0.92	(0.76, 1.11)	0.465	0.88	(0.74, 1.05)	1.18	(0.87, 1.60)	0.097
BER	NTHL1	rs2516739	0.97	(0.75, 1.25)	0.92	(0.76, 1.11)	0.650	0.88	(0.73, 1.05)	1.17	(0.86, 1.58)	0.107
BER	OGG1	rs159153	1.01	(0.80, 1.26)	1.18	(1.00, 1.40)	0.256	1.07	(0.92, 1.25)	1.24	(0.95, 1.62)	0.332
BER	OGG1	rs1052133	1.02	(0.80, 1.29)	1.01	(0.83, 1.22)	0.997	1.01	(0.85, 1.19)	0.97	(0.71, 1.32)	0.804
BER	OGG1	rs293795	0.79	(0.60, 1.05)	1.11	(0.90, 1.35)	0.066	0.95	(0.79, 1.15)	1.08	(0.76, 1.54)	0.424
BER	OGG1	rs293794	0.81	(0.61, 1.07)	1.08	(0.88, 1.32)	0.114	0.95	(0.79, 1.14)	1.06	(0.75, 1.50)	0.484
BER	OGG1	rs293796	0.96	(0.65, 1.41)	1.26	(0.95, 1.67)	0.228	1.15	(0.88, 1.49)	1.13	(0.71, 1.81)	0.918
BER	PCNA	rs3729558	0.93	(0.76, 1.14)	0.91	(0.78, 1.07)	0.977	0.94	(0.81, 1.08)	0.87	(0.67, 1.13)	0.607
BER	PCNA	rs17349	1.07	(0.78, 1.47)	0.78	(0.60, 1.02)	0.165	0.81	(0.64, 1.02)	1.11	(0.74, 1.69)	0.204
BER	PCNA	rs25406	1.07	(0.87, 1.32)	1.19	(1.02, 1.40)	0.522	1.16	(1.01, 1.34)	1.08	(0.82, 1.40)	0.636
BER	PCNA	rs25405	1.07	(0.77, 1.47)	0.81	(0.62, 1.05)	0.212	0.83	(0.66, 1.05)	1.11	(0.73, 1.68)	0.263
BER	PCNA	rs4239761	1.10	(0.86, 1.41)	1.03	(0.85, 1.26)	0.751	1.02	(0.85, 1.22)	1.10	(0.81, 1.51)	0.670
BER	PNKP	rs7257463	1.02	(0.82, 1.27)	1.05	(0.89, 1.24)	0.821	1.08	(0.93, 1.26)	0.96	(0.73, 1.26)	0.472
BER	PNKP	rs1290646	0.97	(0.78, 1.21)	0.96	(0.82, 1.12)	0.859	0.92	(0.80, 1.07)	1.09	(0.84, 1.41)	0.297
BER	PNKP	rs3739177	1.40	(0.97, 2.02)	1.09	(0.81, 1.45)	0.309	1.24	(0.96, 1.59)	1.11	(0.66, 1.87)	0.775
BER	PNKP	rs2257103	1.00	(0.81, 1.24)	1.07	(0.91, 1.26)	0.553	1.06	(0.92, 1.23)	0.99	(0.76, 1.30)	0.688
BER	PNKP	rs2353005	0.76	(0.57, 1.02)	1.04	(0.83, 1.30)	0.106	0.98	(0.81, 1.20)	0.76	(0.53, 1.10)	0.221
BER	POLB	rs3136711	0.99	(0.67, 1.45)	1.05	(0.79, 1.39)	0.853	1.02	(0.79, 1.33)	1.02	(0.64, 1.63)	0.952
BER	POLB	rs2976244	1.14	(0.76, 1.71)	0.88	(0.64, 1.21)	0.324	0.95	(0.71, 1.26)	1.05	(0.64, 1.73)	0.706
BER	POLB	rs3136790	1.11	(0.79, 1.54)	0.94	(0.73, 1.22)	0.468	0.96	(0.76, 1.22)	1.12	(0.74, 1.67)	0.562
BER	POLB	rs3136797	1.79	(0.93, 3.44)	0.73	(0.35, 1.49)	0.076	0.88	(0.48, 1.63)	1.67	(0.76, 3.67)	0.211
BER	POLB	rs2073664	1.14	(0.75, 1.72)	0.88	(0.64, 1.22)	0.330	0.94	(0.70, 1.27)	1.00	(0.60, 1.66)	0.834
BER	POLI	rs3730668	0.89	(0.72, 1.10)	0.89	(0.76, 1.05)	0.892	0.94	(0.81, 1.08)	0.83	(0.64, 1.08)	0.423
BER	POLI	rs476630	1.02	(0.82, 1.27)	1.15	(0.97, 1.37)	0.362	1.14	(0.98, 1.34)	0.94	(0.70, 1.25)	0.210
BER	POLI	rs686881	1.14	(0.74, 1.77)	1.20	(0.87, 1.65)	0.888	1.17	(0.87, 1.56)	1.37	(0.78, 2.42)	0.581
BER	POLI	rs3730814	0.99	(0.78, 1.25)	1.11	(0.92, 1.34)	0.389	1.12	(0.95, 1.32)	0.83	(0.61, 1.15)	0.093
BER	POLI	rs3218786	1.62	(0.85, 3.08)	0.84	(0.53, 1.33)	0.087	1.07	(0.71, 1.63)	1.16	(0.48, 2.81)	0.924
BER	POLI	rs8305	1.12	(0.89, 1.41)	1.00	(0.84, 1.18)	0.471	0.94	(0.81, 1.11)	1.26	(0.96, 1.66)	0.059
BER	POLI	rs596986	1.14	(0.74, 1.77)	1.20	(0.87, 1.65)	0.888	1.17	(0.87, 1.56)	1.37	(0.78, 2.42)	0.581
BER	PPP1R13L	rs6966	0.99	(0.74, 1.33)	0.91	(0.74, 1.13)	0.735	0.95	(0.78, 1.16)	0.94	(0.67, 1.33)	0.933
BER	PPP1R13L	rs4803817	0.96	(0.75, 1.22)	0.94	(0.78, 1.14)	0.996	0.99	(0.83, 1.17)	0.80	(0.58, 1.09)	0.252
BER	PPP1R13L	rs10412761	0.92	(0.75, 1.14)	0.91	(0.78, 1.07)	0.936	0.94	(0.81, 1.09)	0.87	(0.67, 1.12)	0.657
BER	PPP1R13L	rs1005165	0.91	(0.69, 1.20)	0.91	(0.73, 1.12)	0.840	0.90	(0.74, 1.10)	1.01	(0.71, 1.44)	0.563
BER	RAD18	rs4389469	0.93	(0.75, 1.15)	0.99	(0.84, 1.16)	0.623	1.00	(0.87, 1.16)	0.87	(0.67, 1.13)	0.307
BER	RAD18	rs369032	0.93	(0.75, 1.15)	1.04	(0.88, 1.22)	0.414	1.00	(0.87, 1.16)	0.96	(0.73, 1.25)	0.724
BER	RAD18	rs2035221	1.02	(0.70, 1.49)	1.05	(0.80, 1.38)	0.922	1.23	(0.95, 1.58)	0.67	(0.42, 1.08)	0.029
BER	RAD18	rs593205	1.37	(0.96, 1.97)	1.15	(0.87, 1.53)	0.453	1.28	(1.00, 1.66)	1.06	(0.67, 1.66)	0.439
BER	RAD18	rs373572	1.01	(0.80, 1.28)	1.01	(0.84, 1.21)	0.970	1.04	(0.88, 1.22)	0.95	(0.71, 1.26)	0.533
BER	RAD18	rs13088787	0.94	(0.69, 1.29)	1.01	(0.80, 1.29)	0.666	1.09	(0.88, 1.35)	0.72	(0.48, 1.09)	0.072
BER	RAD18	rs615967	0.95	(0.74, 1.21)	1.02	(0.84, 1.25)	0.584	0.94	(0.78, 1.12)	1.13	(0.83, 1.53)	0.356
BER	RAD18	rs604092	0.99	(0.76, 1.29)	1.01	(0.82, 1.24)	0.927	0.95	(0.79, 1.15)	1.14	(0.83, 1.57)	0.383
BER	SMUG1	rs971	0.92	(0.73, 1.14)	1.10	(0.94, 1.30)	0.181	0.95	(0.82, 1.11)	1.28	(0.98, 1.67)	0.064
BER	SMUG1	rs3087404	0.92	(0.75, 1.13)	0.99	(0.85, 1.16)	0.601	0.92	(0.80, 1.06)	1.10	(0.85, 1.43)	0.200
BER	TDG	rs172814	1.05	(0.79, 1.41)	0.77	(0.61, 0.97)	0.107	0.88	(0.72, 1.08)	0.81	(0.56, 1.18)	0.711
BER	TDG	rs4135054	1.03	(0.74, 1.44)	1.17	(0.92, 1.50)	0.578	1.13	(0.90, 1.42)	1.05	(0.70, 1.57)	0.817
BER	TDG	rs4135061	0.98	(0.77, 1.25)	0.90	(0.75, 1.07)	0.518	0.90	(0.76, 1.06)	1.04	(0.77, 1.41)	0.409
BER	TDG	rs4135064	0.95	(0.66, 1.37)	1.25	(0.95, 1.64)	0.264	1.14	(0.89, 1.47)	1.08	(0.70, 1.66)	0.848
BER	TDG	rs4135081	1.10	(0.89, 1.37)	1.03	(0.87, 1.21)	0.620	1.04	(0.89, 1.21)	1.12	(0.85, 1.47)	0.651
BER	TDG	rs3751206	1.06	(0.68, 1.66)	1.03	(0.76, 1.39)	0.891	1.10	(0.83, 1.46)	0.91	(0.52, 1.57)	0.483
BER	TDG	rs4135087	0.83	(0.59, 1.19)	0.92	(0.70, 1.22)	0.598	0.85	(0.66, 1.10)	0.86	(0.57, 1.29)	0.968
BER	TDG	rs167715	0.91	(0.64, 1.27)	1.13	(0.89, 1.44)	0.348	0.97	(0.77, 1.21)	1.43	(0.95, 2.16)	0.096
BER	TDG	rs10861152	0.95	(0.77, 1.18)	0.89	(0.75, 1.05)	0.637	0.88	(0.75, 1.02)	0.99	(0.76, 1.30)	0.408
BER	TDG	rs1866074	1.09	(0.89, 1.33)	0.88	(0.75, 1.03)	0.115	0.96	(0.84, 1.11)	0.95	(0.73, 1.24)	0.940
BER	TDG	rs4135106	0.88	(0.57, 1.37)	0.87	(0.63, 1.19)	0.912	0.87	(0.65, 1.17)	0.94	(0.54, 1.61)	0.789
BER	TDG	rs4135128	0.96	(0.65, 1.42)	1.03	(0.79, 1.36)	0.796	1.09	(0.85, 1.39)	0.86	(0.52, 1.42)	0.360
BER	UNG	rs3890995	0.95	(0.72, 1.27)	1.12	(0.91, 1.39)	0.375	1.03	(0.85, 1.25)	1.16	(0.82, 1.65)	0.601
BER	UNG	rs1018783	1.05	(0.80, 1.39)	1.16	(0.95, 1.43)	0.576	1.03	(0.85, 1.25)	1.45	(1.04, 2.03)	0.085
BER	UNG	rs2569987	1.01	(0.77, 1.34)	1.00	(0.81, 1.23)	0.848	1.08	(0.89, 1.30)	0.82	(0.58, 1.16)	0.175
BER	UNG	rs246079	1.06	(0.85, 1.31)	1.21	(1.03, 1.43)	0.326	1.07	(0.92, 1.24)	1.48	(1.13, 1.94)	0.038
BER	UNG	rs34259	1.13	(0.87, 1.45)	1.07	(0.88, 1.29)	0.723	1.02	(0.86, 1.22)	1.34	(0.98, 1.83)	0.128
BER	XRCC1	rs25487	0.91	(0.73, 1.13)	1.05	(0.90, 1.24)	0.309	0.98	(0.84, 1.14)	1.09	(0.83, 1.42)	0.566
BER	XRCC1	rs25486	0.90	(0.73, 1.13)	1.04	(0.88, 1.23)	0.343	0.97	(0.84, 1.13)	1.08	(0.83, 1.41)	0.548
BER	XRCC1	rs25489	1.06	(0.64, 1.74)	0.87	(0.58, 1.31)	0.604	0.87	(0.61, 1.24)	1.28	(0.64, 2.58)	0.323
BER	XRCC1	rs1799782	1.07	(0.68, 1.68)	1.05	(0.74, 1.49)	0.997	1.05	(0.77, 1.42)	1.17	(0.60, 2.27)	0.784
BER	XRCC1	rs3213344	1.09	(0.69, 1.71)	1.00	(0.70, 1.42)	0.799	1.02	(0.75, 1.39)	1.17	(0.60, 2.27)	0.732
BER	XRCC1	rs3213334	1.09	(0.86, 1.38)	0.95	(0.79, 1.14)	0.400	0.98	(0.83, 1.16)	0.99	(0.74, 1.32)	0.990
BER	XRCC1	rs2023614	0.87	(0.59, 1.30)	0.96	(0.70, 1.31)	0.705	0.86	(0.65, 1.14)	1.18	(0.71, 1.97)	0.269
BER	XRCC1	rs2854510	1.01	(0.78, 1.31)	0.93	(0.76, 1.12)	0.574	1.01	(0.84, 1.20)	0.82	(0.60, 1.12)	0.299
BER	XRCC1	rs2854509	1.17	(0.92, 1.50)	0.96	(0.79, 1.15)	0.203	1.02	(0.86, 1.21)	1.01	(0.75, 1.35)	0.952
BER	XRCC1	rs3213266	0.88	(0.60, 1.30)	0.94	(0.70, 1.27)	0.792	0.85	(0.65, 1.12)	1.20	(0.73, 1.96)	0.226
BER	XRCC1	rs3213255	1.12	(0.91, 1.39)	0.91	(0.78, 1.07)	0.124	1.01	(0.87, 1.17)	0.88	(0.68, 1.14)	0.387
HR^b	XRCC2	rs3218536	0.90	(0.60, 1.36)	1.18	(0.87, 1.60)	0.227	1.08	(0.82, 1.42)	0.95	(0.57, 1.58)	0.644
HR	XRCC2	rs6964582	1.43	(0.90, 2.30)	1.18	(0.81, 1.70)	0.502	1.18	(0.84, 1.66)	1.57	(0.89, 2.78)	0.400
HR	XRCC2	rs3218438	1.43	(1.03, 1.98)	0.94	(0.72, 1.23)	0.047	0.97	(0.76, 1.24)	1.62	(1.04, 2.52)	0.032
HR	XRCC2	rs3218408	1.00	(0.78, 1.30)	1.11	(0.93, 1.34)	0.495	1.18	(0.99, 1.40)	0.83	(0.61, 1.13)	0.049
HR	XRCC2	rs3218373	1.08	(0.76, 1.54)	1.02	(0.77, 1.35)	0.785	1.08	(0.84, 1.39)	0.89	(0.57, 1.42)	0.466
HR	XRCC2	rs2040639	0.93	(0.75, 1.15)	0.97	(0.82, 1.13)	0.854	0.93	(0.80, 1.08)	1.09	(0.84, 1.41)	0.340
HR	XRCC3	rs861539	0.90	(0.72, 1.11)	0.88	(0.75, 1.04)	0.936	0.89	(0.77, 1.04)	0.87	(0.67, 1.14)	0.852
HR	XRCC3	rs3212102	0.93	(0.47, 1.86)	0.85	(0.50, 1.46)	0.872	0.73	(0.44, 1.23)	1.20	(0.56, 2.54)	0.278
HR	XRCC3	rs3212090	1.08	(0.86, 1.34)	1.17	(0.98, 1.39)	0.646	1.20	(1.03, 1.40)	0.95	(0.72, 1.26)	0.133
HR	XRCC3	rs3212079	1.18	(0.81, 1.74)	0.80	(0.58, 1.10)	0.107	0.91	(0.68, 1.22)	0.94	(0.59, 1.49)	0.881
HR	XRCC3	rs861530	1.05	(0.83, 1.33)	0.98	(0.82, 1.18)	0.717	0.93	(0.79, 1.10)	1.25	(0.93, 1.67)	0.070
HR	XRCC3	rs1799794	0.99	(0.75, 1.29)	1.13	(0.92, 1.39)	0.372	1.02	(0.84, 1.22)	1.27	(0.91, 1.77)	0.226
HR	XRCC3	rs861528	0.88	(0.69, 1.12)	0.90	(0.75, 1.08)	0.900	0.91	(0.77, 1.07)	0.88	(0.66, 1.17)	0.878

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^aAmong all cases and controls; AA, homozygous major allele; Aa, heterozygous; aa, homozygous minor allele; numbers do not sum to total due to missing.

MMR, mismatch repair; BER, base excision repair; HR, homologous recombination.

p-value for interaction.

Discussion

As expected, we observed an association between the MSH5 rs3131379/BAT3 rs3117582 known susceptibility locus and lung cancer risk. These genes lie in the highly complex human leukocyte antigen (HLA) region on 6p21.33. The HLA locus on 6p21.31 has also been reported to be associated with lung cancer risk among Japanese individuals [6]. Interestingly, one of the major findings from The Cancer Genome Atlas comprehensive genomic analysis of squamous cell cancers is the description of somatic loss-of-function mutations in the HLA-A class I major histocompatibility gene, which is also located in the 6p21.3 region [41]. Our other observations include an increased risk of lung cancer associated with a SNP in UNG, particularly among individuals who were already at increased risk because they carried at least one of the MSH5 rs3131379 A alleles; and an increased risk of lung cancer associated with certain SNPs in MSH2 and PCNA. Like SMUG1, TDG, and MBD4, UNG is a BER uracil-DNA glycosylase which repairs the mis-incorporation of the RNA constituent uracil. UNG binds to PCNA at replication foci, and is the major enzyme that removes uracil from U:A pairs. It may also be involved in short patch BER of uracil and pre-replication repair of U:G pairs [42]. MSH2 is typically involved in post-replicative MMR, forming heterodimers with MSH6 to repair base mismatches and small insertion deletion loops, and with MSH3 to repair larger insertion deletion loops [43]. MSH2 also binds to PCNA [42,44]. Lynch Syndrome, which is associated with a dramatically increased risk of colon, endometrial and ovarian cancers as well as several other cancer types, is characterized by mutations in MLH1, MSH2, and MSH6. Mutations in MSH2 confer particularly high risks, though this does not appear to be true for lung cancer [45]. PCNA performs a central role not only in DNA repair, but also in DNA replication and recombination. It forms a trimer that encircles DNA at replication forks, where it recruits other proteins [46].

While UNG and MSH2 perform distinct functions with respect to DNA repair, they have a similar and overlapping role in adaptive immunity [42]. The main function of the adaptive immune system, to recognize and remember specific pathogens, is performed through the differentiation of immunoglobulin (Ig) genes. In humans, this is achieved through two processes, somatic hypermutation (SHM) which yields antibody diversification, and class switch recombination (CSR), which produces the five Ig isotypes IgM, IgD, IgE, IgE, and IgA [42]. Both somatic hypermutation and class switch recombination are initiated by activation-induced cytidine deaminase (AID) which allows the introduction of uracil, forming key intermediate U:G pairings in Ig DNA. Recognition of the U:G pairs in specific regions of Ig by both UNG and MSH2 coupled with MSH6 allows for accumulation of mutations and diversification. Both UNG and MSH2 bind to PCNA, and additional DNA repair genes including APE1, POLN, POLB, and others are involved in the later steps, particularly for class switch recombination [47]. Mouse models deficient in either UNG or MSH2 result in mice able to produce antibodies at a level 2 to 3-fold lower than in wild type mice [48], and models deficient in UNG result in mice that develop B-cell lymphomas late in life [42]. However, deficiency in both UNG and MSH2 results in mice incapable of antibody gene diversification [48]. In humans, mutations in UNG alone result in the autosomal recessive hyper-IgM syndrome, a class switch recombination disorder characterized by IgG, IgA, and IgE deficiencies [49].

In the lung, innate and adaptive immunity launch inflammatory responses to a variety of insults such as particulate matter in cigarette smoke and other pollutants, microbial infections, and cell damage/injury. Chronic inflammation, and the interaction between innate and adaptive immune response, play central roles in cancer development [50]. Chronic pulmonary inflammation has been hypothesized to be an underlying mechanism for the increased risk of lung cancer associated with tobacco smoking, chronic obstructive pulmonary disease [51], silicosis, asbestosis [52], and lung infections (i.e., tuberculosis, pneumonia [53]), and the increased incidence of lung cancer among individuals with human immunodeficiency virus [54].

Very few prior studies have interrogated variants in UNG, MSH2, and PCNA and lung cancer risk, and only in the context of candidate gene studies of DNA repair. Two comprehensive studies described in more detail below [8,15] that examined DNA repair pathway genotype data from samples assayed using the Illumina HumanHap300 BeadChip, did not observe differences in the genotype distribution between cases and controls for SNPs in MSH2, UNG or PCNA, but they did not directly measure the SNPs associated with risk in our study. A relatively small study of French Caucasian smokers (151 lung cancer cases and 172 hospital controls) [11] did not observe associations with MSH2 rs2303428 (G allele frequency 0.10 in cases, 0.12 in controls) or PCNA rs25406 (A allele frequency 0.40 in cases, 0.47 in controls (p=0.09)); data from this study is also included in the meta-analysis by Kazma et al. [15] described below. Two other studies examined associations with MSH2 rs2303428. A Korean study with 432 lung cancer patients matched to 432 healthy controls on age and gender observed that carriage of at least one C allele was associated with an increased risk of adenocarcinoma, compared to the TT genotype (adjusted OR, 1.52; 95% CI, 1.02-2.27; P = 0.04) [13], and while the confidence limit does not exclude 1, an elevated OR (1.29 (0.83—1.99)) was observed in a Taiwanese study of 156 NSCLC patients and 235 controls matched for age, gender and smoking [14]. A candidate SNP study of Caucasian smokers that included 343 NSCLC cases and 413 population-based controls matched on age, gender and smoking did not observe an association with PCNA rs25406 (MAF 0.38 in cases, 0.38 in controls; AG, and AA, versus GG, OR 0.73 (0.52–1.0) and 1.15 (0.74–1.79) [22]. These studies do not provide rigorous support for or against associations with the SNPs of interest, since a much larger sample size is needed in order to obtain stable risk estimates of the magnitude expected.

The largest and most comprehensive interrogations of DNA repair pathways and lung cancer risk were performed by Kazma et al. [15] and Yu et al. [8] Kazma et al. [15] included 1,655 SNPs in 211 DNA repair genes in 6,911 individuals pooled from four studies. Yu et al. [8] interrogated 1806 SNPs in 125 DNA repair genes in 1154 lung cancer cases and 1137 controls matched by smoking status. With the exception of MSH5 rs3131379, the SNPs that were associated with risk in our study are not present on the HumanHap300 BeadChip, but SNPs in LD with them (in HapMap-CEU) were not associated with risk in either study (UNG, rs2430682, in LD with rs246079 (r²=0.89); MSH2, rs2042649, in LD with rs2303428 (r²=1.0)). While they examined associations with SNPs in PCNA, none of the SNPs were in LD >0.52 with the SNP (rs25406) that we observed to be associated with risk in our study.

The variants (after MSH5 rs3131379) that were most strongly associated with lung cancer risk in Kazma et al. were in the genes UBE2N, SMC1L2, and POLB, with suggestive associations for variants in RAD52 and POLN [15]. Yu et al. observed associations with SNPs in XRCC4, but they were not replicated in a meta-analysis of these SNPs in four GWAS studies totaling ~12,000 cases and ~48,000 controls [8]. Other studies of DNA repair genes have reported associations with additional candidate SNPs. A hospital-based study of smokers including 722 cases and 929 controls interrogated 29 SNPs in the BER genes MPG, OGG1, PARP1, and XRCC1, one SNP in PARP1 and two SNPs in XRCC1 (rs1799782 and rs3213255) were associated with lung cancer risk [31]. Meta-analyses of selected SNPs have observed associations with OGG1 Ser326Cys rs1052133 [20,55,56] and XRCC3 T241M rs861539 [20]. Of the genes reported to be associated with lung cancer risk in prior studies, we only examined variants in POLB, XRCC1, OGG1 and XRCC3, and they were not related to risk in our study.

An important difference between our study and the meta-analysis by Kazma et al. is the prevalence of smoking, because Kazma et al. specifically limited their analysis to studies that included both smokers and non-smokers in order to evaluate interactions between SNPs and smoking. In our study, among the controls, none were never smokers, 27.6% were former, and 72.4% were current smokers, whereas in Kazma et al., 38.8% of the controls were never smokers, 25.6% were former, and 34.5% were current smokers. The distribution was identical in the cases and controls for our study because they were matched on smoking exposure, but the distribution in cases from Kazma et al. --9.7% never, 20.5% former, and 68.9% current--differed considerably from the distribution in their controls. It is possible that there are underlying differences in the distribution of genotypes in the controls due to differences in smoking exposure. A well-documented example of this is genetic variation in the nicotinic acetylcholine receptor gene cluster on chromosome 15q25.1. For rs1051730 (which is in complete LD with rs16969968 (r²=1.0, HapMap-CEU)), the frequency of the T allele increases with increasing numbers of cigarettes smoked, with a large difference in frequency between individuals smoking 1-10 cigarettes per day (T allele frequency 0.305) and 31 or more cigarettes per day (T allele frequency 0.391) [57]. Matching controls to cases based on cigarette smoking (as we did) is arguably an advantage when attempting to identify genetic factors that might differentiate between the ~20 % of smokers who develop lung cancer from the ~80 % who do not.

In conclusion, we observed associations with SNPs in UNG, MSH2, and PCNA, all of which are involved both in DNA repair pathways and also in adaptive immunity, and the associations with the UNG variants were stronger among individuals carrying the documented MSH5/BAT3 lung cancer susceptibility allele, which was also associated with risk in our study. We were unable to confirm associations reported in prior studies with POLB, XRCC1, OGG1 and XRCC3 SNPs, and we did not evaluate variation in UBE2N, SMC1L2, RAD52, or POLN. Our study was not large enough to be able to reliably identify the presence of true weak associations, and is limited by having genotype data on only two of the five documented lung cancer susceptibility loci described to date in Caucasian populations [5]. However, our study differs from most other prior studies because it is prospective in nature and includes only heavy smokers, with cases and controls matched on smoking history. Because lung cancer is so rapidly fatal, case control study response proportions can be very low, and our study is likely to have a more representative case group, specific to smoking-associated lung cancer, than case-control studies. Furthermore, no prior studies have reported pathway-based SNP results stratified by know lung cancer susceptibility loci. The patterns of associations observed should be viewed as hypothesis-generating, requiring follow up in other studies of smoking-related lung cancer.

Acknowledgements

We thank the CARET participants, along with the CARET investigators and staff at all participating trial institutions, for their effort and contribution to this research.

Abbreviations

APEX1: apurinic/apyrimidinic-endonuclease-1
CARET: β-Carotene and Retinol Efficacy Trial
CI: confidence interval
LIG3: ligase III
MBD4: methyl binding domain 4
MLH1: MutL homolog 1, colon cancer, nonpolyposis type 2 (E. coli)
MPG: N-methylpurine-DNA glycosylase
MSH2: mutS homolog 2, colon cancer, nonpolyposis type 1 (E. coli)
MSH4: mutS homolog 4, colon cancer, nonpolyposis type 1 (E. coli)
MSH5: mutS homolog 5, colon cancer, nonpolyposis type 1 (E. coli)
MSH6: mutS homolog 6, colon cancer, nonpolyposis type 1 (E. coli)
MUTYH: mutY homolog (E. coli)
NEIL1: nei endonuclease VIII-like 1 (E. coli)
NEIL2: nei endonuclease VIII-like 2 (E. coli)
NTHL1: nth endonuclease III-like 1 (E. coli)
OGG1: 8-oxo-guanine glycosylase-1
OR: odds ratio
PCNA: proliferating cell nuclear antigen
PNKP: polynucleotide kinase 3’-phosphatase
POLB: polymerase (DNA directed), beta
POLI: polymerase (DNA directed) iota
PPP1R13L: protein phosphatase 1, regulatory subunit 13 like
RAD18: RAD18 homolog (S. cerevisiae)
SD: standard deviation
SMUG1: single strand selective monofunctional uracil-DNA glycosylase
SNP: single nucleotide polymorphism
TDG: thymine/uracil mismatch DNA glycosylase
UNG: uracil-DNA glycosylase
XRCC1: X-ray repair complementing defective repair in Chinese-hamster cells 1
XRCC2: X-ray repair complementing defective repair in Chinese-hamster cells 2
XRCC3: X-ray repair complementing defective repair in Chinese-hamster cells 3

Financial support

This work is supported by R01 CA111703 and U01 CA63673 from the National Cancer Institute of the U.S. National Institutes of Health (NIH).

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PERMALINK

DNA repair genotype and lung cancer risk in the beta-carotene and retinol efficacy trial

Jennifer A Doherty

Lori C Sakoda

Melissa M Loomis

Matt J Barnett

Liberto Julianto

Mark D Thornquist

Marian L Neuhouser

Noel S Weiss

Gary E Goodman

Chu Chen

Abstract

Introduction

Materials and methods

Study population

SNP selection and genotyping

Genotype analysis

Haplotype analysis

Results

Table 1.

Table 3.

Table 2.

Discussion

Acknowledgements

Abbreviations

Financial support

References

ACTIONS

PERMALINK

RESOURCES

Cite

Add to Collections

PERMALINK

DNA repair genotype and lung cancer risk in the beta-carotene and retinol efficacy trial

Jennifer A Doherty

Lori C Sakoda

Melissa M Loomis

Matt J Barnett

Liberto Julianto

Mark D Thornquist

Marian L Neuhouser

Noel S Weiss

Gary E Goodman

Chu Chen

Abstract

Introduction

Materials and methods

Study population

SNP selection and genotyping

Genotype analysis

Haplotype analysis

Results

Table 1.

Table 3.

Table 2.

Discussion

Acknowledgements

Abbreviations

Financial support

References

ACTIONS

PERMALINK

RESOURCES

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