Background: Genetic loci within the major histocompatibility complex (MHC) have been associated with nasopharyngeal carcinoma (NPC), an Epstein-Barr virus (EBV)-associated cancer, in several GWAS. Results outside this region have varied.

Methods: We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases; 3,740 controls). Forty-three noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of four independent case–control studies across three regions in Asia (4,716 cases; 5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed.

Results: In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR = 0.81; P value 6.3 × 10−13). Our results also provide support for associations reported from published NPC GWAS—rs6774494 (P = 1.5 × 10−12; located in the MECOM gene region), rs9510787 (P = 5.0 × 10−10; located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (P = 2.8 × 10−8, P = 7.0 × 10−7, and P = 8.4 × 10−7, respectively; located in the CDKN2A/B gene region).

Conclusions: We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene has been shown to be important for telomere maintenance and has been reported to be overexpressed in NPC, and an EBV protein expressed in NPC (LMP1) has been reported to modulate TERT expression/telomerase activity.

Impact: Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis. Cancer Epidemiol Biomarkers Prev; 25(1); 188–92. ©2015 AACR.

Nasopharyngeal carcinoma (NPC) is linked to Epstein-Barr virus (EBV) infection. While EBV infection is ubiquitous, NPC incidence varies considerably around the world (1). It is hypothesized that genetic differences across populations partly explain the predilection of this cancer to individuals of Southeast Asian descent. Several lines of evidence support a role for genetic susceptibility in NPC. The disease clusters within families (1). Also, numerous studies have implicated polymorphisms in candidate genes in NPC (2, 3). The most consistent evidence has been for an association between HLA and NPC, an association that is biologically plausible given the central role of EBV in NPC and of HLA in immune presentation/handling (4).

Several NPC GWAS have recently been published (5–9); all provided support for the importance of genetic factors and clearly confirmed the involvement of genes in the MHC region (region where HLA genes reside) in NPC. Associations outside the MHC were also reported from these GWAS but were not as strong or consistent, suggesting the need for pooling across studies and larger efforts to identify novel genes involved in this disease (5–9).

We report a meta-analysis of four published GWAS (2,152 cases; 3,740 controls), followed by replication of noteworthy findings in case–control studies from the populations where the GWAS were conducted (4,716 cases; 5,379 controls). Our analysis identified a novel association between CLPTM1L/TERT and NPC and confirmed reported associations for SNPs located in the MECOM, TNFRSF19, and CDKN2A/2B gene regions.

The GWAS contributing to our meta-analysis included histologically confirmed NPC cases and region-specific controls restricted to individuals of Chinese ethnicity (Table 1; refs. 5–8). Genotyping for these four GWAS was performed using Illumina platforms. The two Malaysian GWAS were analyzed as one. All data included passed QC filtering criteria as described for the respective studies (5–8).

To maximize coverage across studies, genome-wide imputations were performed for each study using typed SNPs. SNPs with call rates >90%, minor allele frequencies >3%, and that had genotype distributions that did not deviate from the expected by Hardy–Weinberg equilibrium (in controls; P > 10−6) were retained for imputation using IMPUTE2. HapMap reference data were used (HapMap phase III, CHB+CHD+JPT data from IMPUTE2 website). Imputed genotypes with information score <90%, MAF <3%, or missing >10% were excluded. GTOOL (http://www.well.ox.ac.uk/∼cfreeman/software/gwas/gtool.html) was used for data conversions.

For each GWAS, SNPs were analyzed by logistic regression under a log additive model, adjusting for age and cryptic population stratification. To define population stratification adjustment factors, principal component analysis was performed (EIGENSTRAT) using a pruned set of 30,956 SNPs defined based on pairwise linkage disequilibrium (r2 < 0.05 among Chinese) and restricted to SNPs with MAF >3%. The top 10 eigenvectors were evaluated for their association with NPC (separately for each individual GWAS) and included in the final logistic models if P-value <0.05 by the Wald test.

Using results from individual GWAS, we identified the 500 SNPs with the lowest P values from each of the studies after exclusion of SNPs that could not be imputed or failed QC filtering. We combined these study-specific lists of top-SNPs into a single list for consideration as part of the present meta-analysis. In total, 1,590 SNPs were identified through this process and these 1,590 SNPs comprised the basis for the present meta-analysis. Summary statistics (number cases/controls, genotype counts, β coefficients, and SDs) were obtained from individual studies for selected SNPs and a meta-analysis was performed using a fixed effects model (R-program).

SNPs were selected for replication as follows. We arbitrarily ranked (by P value) the top 200 hits (all with P values <0.0167) from the meta-analysis for which the direction of the association was consistent across all individual studies. We then selected SNPs with P values <1 × 10−5 that were 250 kb+ from other selected SNPs. For SNPs within 250kb of another SNP on the list, we retained SNPs that had an r2 ≤ 0.80 (based on Chinese data from the 1 k genome project) and the SNP with the smaller P value when the r2 between SNPs was >0.80. Thirty SNPs were selected based on these criteria. We added 14 SNPs nominated by consortium members based on results from individual GWAS and other information from candidate-based studies and other studies in the published literature. One SNP that qualified based on the criteria above but failed in the design of the custom array described below was excluded (rs11865086). A second SNP that qualified but failed in the custom array design (rs6931820) was replaced with a SNP in strong LD with the original SNP (rs1324103; r2 = 0.88). In total, 43 SNPs were evaluated in the replication phase of our effort.

Replication studies were restricted to studies among individuals of Chinese descent. In total, we included 4,716 cases and 5,379 controls across four case–control studies in Mainland China, Malaysia, and Taiwan (Table 1). All four studies were hospital-based, recruiting NPC cases from selected hospitals in their respective geographical area. For the southern China study, cases were recruited from the Sun Yat-Sen University Cancer Center (Guangzhou, China) and the Southern Medical University Hospital. For the Malaysia study, cases were recruited from the University of Malaysia Medical Center (Kuala Lumpur, Malaysia) and from a network of additional hospitals across the country. For the two Taiwan studies, cases were recruited form the National Taiwan University (Taipei, Taiwan) and MacKay Memorial hospitals and from the Chang Gung Memorial and Linkou hospitals, respectively. Cases were restricted to adults with histologically confirmed NPC. Geographically matched controls of Chinese descent were frequency (southern China, Malaysia, and Taiwan II studies) or individually (Taiwan I study) matched to cases on age and gender. Controls did not have a history of NPC diagnosis. Studies were reviewed/approved by ethical committees and informed consent was obtained from participants.

A custom designed array containing the 43 SNPs selected for replication was developed using the Sequenome MassARRAY iPlex assay (Supplementary Table S1). Testing was performed in one of two laboratories. To ensure comparable quality across laboratories, a common QC panel consisting of 94 HapMap samples was tested. Percent agreement across laboratories for the 43 SNPs tested was 97% (range: 82%–100%; agreement was >85% for all but two SNPs: rs189897 and rs4714505).

To analyze the replication studies, individual genotyping results were pooled and an additive logistic regression model used to evaluate the effect of each SNP, adjusting for study. To summarize information across the GWAS and replication studies, we conducted a meta-analysis using the fixed effect model to integrate estimates from all studies.

The initial meta-analysis across GWAS included a total of 2,152 cases and 3,740 controls. Results from the meta-analysis are summarized in Supplementary Table S2. As described in the Materials and Methods section, we identified 43 SNPs for replication based on the GWAS meta-analysis. Replication was performed on a total of 4,716 cases and 5,379 controls across four studies (Table 1). Results from this replication effort are summarized in Table 2. In this analysis, the strongest evidence in support of an association with NPC was observed for rs31489 (OR = 0.79; P = 4.3 × 10−11), an intronic SNP within CLPTM1L in the CLPTM1L/TERT region (chr.5p15.33). This represents a locus not reported in previously published NPC GWAS. Findings for this SNP were consistent in the mainland Chinese and two Taiwanese replication studies and absent from the Malaysian replication study, the smallest of the replication efforts (Supplementary Fig. S1). A second SNP within the CLPTM1L/TERT locus (rs2853668; r2 = 0.108 and D' = 0.917 with rs 31489 among controls in our replication studies) was also associated with NPC in the replication phase (OR = 1.11; P = 5.2 × 10−4), but the association was no longer statistically significant in analyses that conditioned on rs31489 (OR = 1.05; P = 0.15).

In analyses that combined the GWAS and replication studies, findings for rs31489 were strengthened (OR across GWA+replication studies = 0.81; Pvalue = 6.3 × 10−13; Table 2). Some evidence for heterogeneity across studies was observed (Pheterogeneity = 0.035). Additional associations (P ≤ 1 × 10−7) were observed in our combined GWA plus replication studies meta-analysis for rs6774494 (P = 1.5 × 10−12; MECOM gene region), rs9510787 (P = 5.0 × 10−10; TNFRSF19 gene region), rs1412829, rs4977756, and rs1063192 (P = 2.8 × 10−8, P = 7.0 × 10−7, and P = 8.4 × 10−7, respectively; CDKN2A/2B gene region; Table 2 and Supplementary Fig. S1).

We report herein results from a meta-analysis of NPC GWAS followed by replication studies across three regions in Asia. A novel association was observed within the CLPTM1L/TERT locus. This finding is of note given that SNPs in this region were reported from GWAS conducted for numerous other cancers, including lung, bladder, pancreas, testis, and central nervous system (10). A recent meta-analysis of 85 studies including over 490,000 subjects that evaluated 67 TERT/CLPTM1L locus polymorphisms and 24 tumor types identified 11 SNPs with strong cumulative evidence for an association with at least one cancer type. rs31489 was one of these SNPs and was found to have strong cumulative evidence for association with testicular cancer among Caucasians and moderate cumulative evidence for association with Asian lung cancer (10). Furthermore, a review of the literature identified candidate gene studies (two that evaluated SNPs and a third that evaluated a microsatellite marker) that reported an association between polymorphisms within the CLPTM1L/TERT locus and NPC (11–13). Two of the three SNPs evaluated in these studies are in LD with rs31489 (rs401681 r2 = 0.427 in 1 kG ASN and 0.512 in 1 kG CHB; rs402710 r2 = 0.433 in 1 kG ASN and 0.569 in 1 kG CHB). The third SNP is not in LD with rs31489, suggesting the possibility for the existence of greater than one independent susceptibility variant within the CLPTM1L/TERT locus (rs2736098 r2 = 0.016 in 1 kG ASN and 0.049 in 1 kG CHB). Our findings in the CLPTM1L/TERT locus gain added significance given the role of TERT in telomere length regulation (14), the finding that telomerase overexpression is observed in NPC (15), and that the EBV protein LMP1, a protein frequently expressed in NPC, activates TERT expression and enhances telomerase activity (16, 17). We did observe evidence for possible heterogeneity in effect observed for rs31489 across study populations (Pheterogeneity = 0.035). The evidence for heterogeneity was of marginal statistical significance and was driven primarily by the two Malaysian studies included in our effort. It is unclear at this time whether our findings reflect true heterogeneity, differential misclassification of ethnicity in the Malaysian studies, or a chance finding. This observation deserves further consideration in future studies.

Additional associations (P ≤ 1 × 10−7) were observed in our combined GWA plus replication studies meta-analysis for rs6774494 (P = 1.5 × 10−12; MECOM gene region), rs9510787 (P = 5.0 × 10−10; TNFRSF19 gene region), rs1412829, rs4977756, and rs1063192 (P = 2.8 × 10−8, P = 7.0 × 10−7, and P = 8.4 × 10−7, respectively; CDKN2A/2B gene region; Table 2 and Supplementary Fig. S1). These associations were previously reported from the Mainland China NPC GWAS and their potential biological implications discussed (6); our data provide support for these associations.

Strengths of our study include the fact that it evaluated associations with NPC across multiple GWAS and the large size of its replication effort. Limitations include the inability to further investigate potential heterogeneity of effects by exposure status or geographic/ethnic groups. Future studies should explore the associations reported herein in additional populations with differing ethnic makeup.

In conclusion, our GWAS meta-analysis and replication effort has identified an additional susceptibility locus for NPC within the CLPTM1L/TERT region of chromosome 5p15.33 and provides support for several previously reported NPC susceptibility loci.

No potential conflicts of interest were disclosed.

Conception and design: J.-X. Bei, W.-H. Su, K. Yu, P.-J. Lou, C.-J. Chen, Y.-S. Chang, A. Hildesheim

Development of methodology: J.-X. Bei, C.-C. Ng, P.-J. Lou, C.-J. Chen, A. Hildesheim

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J.-X. Bei, W.-H. Su, C.-C. Ng, W.-L. Hsu, C.-J. Chen, M.-Y. Chen, Q. Cui, F.-T. Feng, Q.-S. Feng, Y.-M. Guo, A. S.-B. Khoo, W.-S. Liu, K.-C. Pua, S.H. Teo, K.-P. Tse, Y.-F. Xia, H. Zhang, G. Zhou, J. Liu, A. Hildesheim

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.-X. Bei, W.-H. Su, C.-C. Ng, K. Yu, Y.-M. Chin, P.-J. Lou, J.D. McKay, C.-J. Chen, Y.-F. Xia, A. Hildesheim

Writing, review, and/or revision of the manuscript: J.-X. Bei, C.-C. Ng, Y.-M. Chin, W.-L. Hsu, C.-J. Chen, Y.-S. Chang, F.-T. Feng, A. S.-B. Khoo, J. Liu, A. Hildesheim

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J.-X. Bei, C.-C. Ng, Y.-M. Chin, P.-J. Lou, W.-L. Hsu, Y.-S. Chang, L.-Z. Chen, Q. Cui, W.-H. Jia, A. S.-B. Khoo, K.-P. Tse, A. Hildesheim

Study supervision: J.-X. Bei, Y.-S. Chang, Y.-X. Zeng, A. Hildesheim

The authors thank the full membership of the International NPC Genetics Working Group who contributed to this publication. They include Jin-Xin Bei; Kai-Ping Chang (Department of Otolaryngology, Chang Gung Memorial Hospital at Lin-Kou, Taoyuan, Taiwan); Yu-Sun Chang; Chien-Jen Chen; Yoon-Ming Chin; Charles Chung (Center for Genomics Research, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD); Allan Hildesheim; Wan-Lun Hsu; Alan Soo-Beng Khoo; Jian-Jun Liu; Pei-Jen Lou; James D. McKay; Ching-Ching Ng; Kin-Choo Pua; Lee-Chu See (Department of Biostatistics and Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan); Wen-Hui Su; Soo-Hwang Teo; Ngan-Ming Tsang (Department of Radiation Oncology, Chang Gung Memorial Hospital at Lin-Kou, Taoyuan, Taiwan); Ka-Po Tse (Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan); Meredith Yeager (Center for Genomics Research, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD); Chia-Jung Yu (Chang Gung Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan); Kai Yu; Yi-Xin Zeng.

The mainland China NPC Study Group: Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center—M.Y. Chen, H.Q. Mai, Y.F. Xia, X. Guo, H.Y. Mo, M.Y. Chen, C.N. Qian; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center—W.H. Jia, Y.X. Zeng, Q.S. Feng, L.Z. Chen, X.H. Zheng, Y. Zhang, Q. Cui, Y.M. Guo, F.T. Feng, W.S. Liu, J.X. Bei, J. Li; Department of Genomics & Proteomics, Beijing Institute of Radiation Medicine—G.Q. Zhou, F. He, H. Zhang; Beijing Proteome Research Center—G.Q. Zhou, F. He, H. Zhang; Department of Otorhinolaryngology and Head Surgery, First Affiliated Hospital of Guangxi Medical University—G.W. Huang, Z. Zhang; Department of Cancer Prevention Research, Cancer Prevention Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in Southern China—S.M. Cao; Clinical Trail Study Center, Sun Yat-sen University Cancer Center—M.H. Hong.

The Malaysia NPC Study Group: Hospital Pulau Pinang: K.C. Pua -Project Leader, S. Subathra, N. Punithavati, B.S. Tan, Y.S. Ee, L.M. Ong, R.A. Hamid, M. Goh, J.C.T. Quah, J. Lim; Hospital Kuala Lumpur/Universiti Putra Malaysia: Y.Y. Yap, B.D. Dipak, R. Deepak, F.N. Lau, P.V. Kam, S. Shri Devi; Queen Elizabeth Hospital: C.A. Ong, C.L. Lum, N.A. Ahmad, S. Halimuddin, M. Somasundran, A. Kam, M. Wodjin; Sarawak General Hospital/Universiti Malaysia Sarawak: S.K. Subramaniam, T.S. Tiong, T.Y. Tan, U.H. Sim, T.W. Tharumalingam, D. Norlida, M. Zulkarnaen, W.H. Lai; University of Malaya: G. Gopala Krishnan, C.C. Ng, A.Z. Bustam, S. Marniza, P. Shahfinaz, O. Hashim, S. Shamshinder, N. Prepageran, L.M. Looi, O. Rahmat, J. Amin, J. Maznan, L.Y. Yap; Hospital Universiti Sains Malaysia: S. Hassan, B. Biswal; Cancer Research Initiatives Foundation: S.H. Teo; Institute for Medical Research: A.S.B. Khoo - Program Leader, A. Munirah, A. Subasri, L.P. Tan, N.M. Kumaran, M.S. Nurul Ashikin, M.S. Nursyazwani, B. Norhasimah, R. Sasela Devi, S. Shri Devi, C.Y. Koh.

This work was supported by the National High Technology Research and Development Program of China (863; 2012AA02A501, 2012AA02A206; J.-X. Bei and Y. Zeng), the Major State Basic Research Development Program of China (973; 2011CB504302; to J.-X. Bei and Y. Zeng), the National Natural Science Foundation of China (81222035, 81101544; to J.-X. Bei and Y. Zeng), the Pearl River Nova Program and the Agency for Science, Technology, and Research of Singapore (to J.-X. Bei and J. Liu), the Ministry of Education of Taiwan, the Malaysian Ministry of Higher Education-High Impact Research (H-50001-A000023; to C. Ng and Y. Chin), and by the Intramural Research Program of the U.S. National Cancer Institute (to A. Hildesheim and K. Yu).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Chang
ET
,
Adami
HO
. 
The enigmatic epidemiology of nasopharyngeal carcinoma
.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
1765
77
.
2.
Bei
JX
,
Jia
WH
,
Zeng
YX
. 
Familial and large-scale case-control studies identify genes associated with nasopharyngeal carcinoma
.
Semin Cancer Biol
2012
;
22
:
96
106
.
3.
Hildesheim
A
,
Wang
CP
. 
Genetic predisposition factors and nasopharyngeal carcinoma risk: a review of epidemiological association studies, 2000–2011
.
Semin Cancer Biol
2012
;
22
:
107
16
.
4.
Su
WH
,
Hildesheim
A
,
Chang
YS
. 
Human leukocyte antigens and Epstein-Barr virus associated nasopharyngeal carcinoma: old associations offer new clues into the role of immunity in infection-associated cancers
.
Front Oncol
2013
;
3
:
299
.
5.
Ng
CC
,
Yew
PY
,
Puah
SM
,
Krishnan
G
,
Yap
LF
,
Teo
SH
, et al
A genome-wide association study identifies ITGA9 conferring risk of nasopharyngeal carcinoma
.
J Hum Genet
2009
;
54
:
392
7
.
6.
Bei
JX
,
Li
Y
,
Jia
WH
,
Feng
BJ
,
Zhou
G
,
Chen
LZ
, et al
A genome-wide association study of nasopharyngeal carcinoma identifies three new susceptibility loci
.
Nat Genetics
2010
;
42
:
599
603
.
7.
Tse
KP
,
Su
WH
,
Chang
KP
,
Feng
BJ
,
Zhou
G
,
Chen
LZ
, et al
Genome-wide association study reveals multiple nasopharyngeal carcinoma-associated loci within the HLA region at chromosome 6p21.3
.
Am J Hum Genet
2009
;
85
:
194
203
.
8.
Chin
YM
,
Mushiroda
T
,
Takahashi
A
,
Kubo
M
,
Krishnan
G
,
Yap
LF
, et al
HLA-A SNPs and amino acid variants are associated with nasopharyngeal carcinoma in Malaysian Chinese
.
Int J Cancer
2014
;
136
:
678
87
.
9.
Tang
M
,
Lautenberger
JA
,
Gao
X
,
Sezgin
E
,
Hendrickson
SL
,
Troyer
JL
, et al
The principal genetic determinants for nasopharyngeal carcinoma in China involve the HLA class I antigen recognition groove
.
PLoS Genetics
2012
;
8
:
e1003103
.
10.
Mocellin
S
,
Verdi
D
,
Pooley
KA
,
Landi
MT
,
Egan
KM
,
Baird
DM
, et al
Telomerase reverse transcriptase locus polymorphisms and cancer risk: A field synopsis and meta-analysis
.
J Natl Cancer Inst
2012
;
104
:
840
54
.
11.
Zhang
Y
,
Zhang
H
,
Zhai
Y
,
Wang
Z
,
Ma
F
,
Wang
H
, et al
A fuctional tándem-repeats polymorphism in the downstream of TERT is associated with the risk of nasopharyngeal carcinoma in Chinese population
.
BMC Med
2011
;
9
:
106
14
.
12.
Fachiroh
J
,
Sangrajrang
S
,
Johansson
M
,
Renard
H
,
Gaborieau
V
,
Chabrier
A
, et al
Tobacco consumption and genetic susceptibility to nasopharyngeal carcinoma (NPC) in Thailand
.
Cancer Causes Control
2012
;
23
:
1995
2002
.
13.
Ko
JMY
,
Dai
W
,
Hiu
E
,
Kwong
D
,
Tong Ng
W
,
Lee
A
, et al
Multigene pathway-based analyses identify nasopharyngeal carcinoma risk associations for cumulative adverse effects of TERT-CLPTM1L and DNA double-strand breaks repair
.
Int J Cancer
2014
;
135
:
1634
45
.
14.
Bellon
M
,
Nicot
C
. 
Regulation of telomerase and telomeres: Human tumor viruses take control
.
J Natl Cancer Inst
2008
;
100
:
98
108
.
15.
Cheng
RYS
,
Yuen
PW
,
Nicholls
JM
,
Zheng
Z
,
Wei
W
,
Sham
JS
, et al
Telomerase activation in nasopharyngeal carcinomas
.
Br J Cancer
1998
;
77
:
456
60
.
16.
Mei
YP
,
Zhu
XF
,
Zhou
JM
,
Huang
H
,
Deng
R
,
Zeng
YX
. 
siRNA targeting LMP1-induced apoptosis in EBV-positive lymphoma cells is associated with inhibition of telomerase activity and expression
.
Cancer Lett
2006
;
232
:
189
98
.
17.
Terrin
L
,
Col
JD
,
Rampazzo
E
,
Zancai
P
,
Pedrotti
M
,
Ammirabile
G
, et al
Latent membrane protein 1 of Epstein-Barr virus activates the hTERT promoter and enhances telomerase activity in B lymphocytes
.
J Virol
2008
;
82
:
10175
87
.