A meta-analysis of Hodgkin lymphoma reveals 19p13.3 TCF3 as a novel susceptibility locus

Abstract

Recent genome-wide association studies (GWAS) of Hodgkin lymphoma (HL) have identified associations with genetic variation at both HLA and non-HLA loci; however, much of heritable HL susceptibility remains unexplained. Here we perform a meta-analysis of three HL GWAS totaling 1,816 cases and 7,877 controls followed by replication in an independent set of 1,281 cases and 3,218 controls to find novel risk loci. We identify a novel variant at 19p13.3 associated with HL (rs1860661; odds ratio (OR)=0.81, 95% confidence interval (95% CI)=0.76-0.86, P_combined =3.5 × 10^-10 ), located in intron 2 of TCF3 (also known as E2A), a regulator of B- and T-cell lineage commitment known to be involved in HL pathogenesis. This meta-analysis also notes associations between previously published loci at 2p16, 5q31, 6p31, 8q24 and 10p14 and HL subtypes. We conclude that our data suggest a link between the 19p13.3 locus, including TCF3, and HL risk.

ARTICLE

Received 13 Aug 2013 | Accepted 11 Apr 2014 | Published 12 Jun 2014

DOI: 10.1038/ncomms4856

A meta-analysis of Hodgkin lymphoma reveals 19p13.3 TCF3 as a novel susceptibility locus

W. Cozen1,*, M.N. Timofeeva2,3,*, D. Li4,*, A. Diepstra5,*, D. Hazelett1,*, M. Delahaye-Sourdeix2,*,C.K. Edlund1, L. Franke5, K. Rostgaard6, D.J. Van Den Berg1, V.K. Cortessis1, K.E. Smedby7, S.L. Glaser8,H.-J. Westra5, L.L. Robison9, T.M. Mack1, H. Ghesquieres10, A.E. Hwang1, A. Nieters11, S. de Sanjose12,T. Lightfoot13, N. Becker14, M. Maynadie15, L. Foretova16, E. Roman13, Y. Benavente12, K.A. Rand1, B.N. Nathwani17,B. Glimelius18, A. Staines19, P. Boffetta20, B.K. Link21, L. Kiemeney22, S.M. Ansell23, S. Bhatia17, L.C. Strong24,P. Galan25, L. Vatten26, T.M. Habermann23, E.J. Duell12, A. Lake27, R.N. Veenstra5, L. Visser5, Y. Liu5,K.Y. Urayama28, D. Montgomery27, V. Gaborieau2, L.M. Weiss29, G. Byrnes2, M. Lathrop30, P. Cocco31, T. Best32, A.D. Skol32, H.-O. Adami7,33, M. Melbye6, J.R. Cerhan23, A. Gallagher27, G.M. Taylor34, S.L. Slager23, P. Brennan2, G.A. Coetzee1, D.V. Conti1, K. Onel32,*, R.F. Jarrett27,*, H. Hjalgrim6,*, A. van den Berg5,* & J.D. McKay2,*

Recent genome-wide association studies (GWAS) of Hodgkin lymphoma (HL) have identied associations with genetic variation at both HLA and non-HLA loci; however, much of heritable HL susceptibility remains unexplained. Here we perform a meta-analysis of three HL GWAS totaling 1,816 cases and 7,877 controls followed by replication in an independent set of 1,281 cases and 3,218 controls to nd novel risk loci. We identify a novel variant at 19p13.3 associated with HL (rs1860661; odds ratio (OR) 0.81, 95% condence interval (95%

CI) 0.760.86, P

combined

1 USC Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California 90089-9175, USA. 2 International Agency for Research on Cancer (IARC), 69372 Lyon, France. 3 Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, UK.

4 Cedars-Sinai Medical Center, Los Angeles, California 90048, USA. 5 University of Groningen, University Medical Centre Groningen, 9700 RB Groningen, The Netherlands. 6 Statens Serum Institut, DK-2300 Copenhagen, Denmark. 7 Karolinska Institutet and Karolinska University Hospital, S-221 00 Stockholm, Sweden.

8 Cancer Prevention Institute of California, Fremont, California 94538, USA. 9 St Jude Childrens Hospital, Cordova, Tennessee 38105, USA. 10 Centre Lon Brard, UMR CNRS 5239Universit Lyon 1, 69008 Lyon, France. 11 University Medical Centre Freiburg, D-79085 Freiburg, Germany. 12 IDIBELL Institut Catal dOncologia, 8907 Barcelona, Spain. 13 University of York, YO10 5DD York, UK. 14 German Cancer Research Centre, D-69120 Heidelberg, Germany. 15 CHU de Dijon, EA 4184, University of Burgundy, 21070 Dijon, France. 16 Masaryk Memorial Cancer Institute, 656 53 Brno, Czech Republic. 17 City of Hope National Medical Center, Duarte, California 91010, USA. 18 Uppsala University, 75285 Uppsala, Sweden. 19 School of Nursing and Human Sciences, Dublin City University, Glasnevin, Dublin 9, Ireland.

20 Icahn School of Medicine at Mount Sinai, New York City, New York 10029-6574, USA. 21 University of Iowa College of Medicine, Iowa City, Iowa 52242, USA.

22 Radboud University Nijmegen Medical Centre, 6500HB Nijmegen, The Netherlands. 23 Mayo Clinic, Rochester, Minnesota 55905, USA. 24 MD Anderson Cancer Center, University of Texas, Houston, Texas 77030, USA. 25 INSERM U557 (UMR Inserm; INRA; CNAM, Universit Paris 13), 93017 Paris, France. 26 Norwegian University of Science and Technology, NO-7491 Trondheim, Norway. 27 MRC University of Glasgow Centre for Virus Research, Garscube Estate, University of Glasgow, G12 8QQ Glasgow, Scotland, UK. 28 Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University, Tokyo 104-0044, Japan.

29 Clarient Pathology Services, Aliso Viejo, California 92656, USA. 30 Genome Quebec, Montreal, Canada H3A 0G1. 31 Institute of Occupational Health, University of Cagliari, Monserrato, 09042 Cagliari, Italy. 32 The University of Chicago, Chicago, Illinois 60637-5415, USA. 33 Harvard University School of Public Health, Boston, Massachusetts 02115, USA. 34 School of Cancer Sciences, University of Manchester, St Marys Hospital, M13 0JH Manchester, UK. * These authors contributed equally to the work. Correspondence and requests for materials should be addressed to J.D.M. (email: mailto:[email protected]

Web End [email protected] ) or to W.C. (email: mailto:[email protected]

Web End [email protected] ) or to A.v.d.B. (email: mailto:[email protected]

Web End [email protected] ).

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3.5 10 10), located in intron 2 of TCF3 (also known as E2A), a

regulator of B- and T-cell lineage commitment known to be involved in HL pathogenesis. This meta-analysis also notes associations between previously published loci at 2p16, 5q31, 6p31, 8q24 and 10p14 and HL subtypes. We conclude that our data suggest a link between the 19p13.3 locus, including TCF3, and HL risk.

ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms4856

Hodgkin lymphoma (HL) is an aetiologically and histologically heterogeneous disease characterized by the presence of rare malignant Hodgkin ReedSternberg (HRS)

cells1. It is one of the most common cancers among young adults in Western countries2,3. Classical HL (cHL) makes up the vast majority of HL and itself comprises several subtypes. Nodular sclerosis HL (NSHL) is the most common subtype among adolescents and young adults and is typically EpsteinBarr virus (EBV) negative46. Mixed cellularity HL (MCHL) is more common among young children and older individuals and its tumour cells typically contain EBV (EBV-positive HL)46. HL has a strong genetic component, with a highly increased risk in monozygotic compared with dizygotic co-twins7 and other siblings8 of a case, whose risk in turn is several times higher than the risk to an average person.

It has been demonstrated that HLA is strongly associated with the risk of HL and that associated loci vary by EBV tumour status, with EBV-positive cHL associated with HLA-A*01 and HLA-A*02 class I alleles, and EBV-negative cHL associated with markers in or near the HLA class II region6,9,10. Three independent HL genome-wide association studies (GWAS) in persons of European origin have recently been published; two included all patients with cHL11,12 and one was limited to adolescent/young adult patients with NSHL13. The most signicantly associated SNPs in all three GWAS were located at the 6p21.32 region, which contains the HLA genes. Multiple independent variants within this region were associated with HL, with heterogeneity based on EBV tumour status and histological subtype1113. Non-HLA risk loci were also identied, including REL, GATA3 and IL13, some of which showed heterogeneity by histological subtype or EBV subgroup11,12. These studies collectively do not explain all genetic susceptibility for HL.

Here we perform a meta-analysis to identify additional variants associated with HL and to investigate shared and unique susceptibility loci for different HL histological subtypes and EBV status-stratied subgroups. This study is the largest to date for this disease, with 3,097 cases and 11,095 controls included in the combined discovery and replication sets. We note HL subtype-specic associations with previously reported SNPs and identify a new HL susceptibility locus at 19p13.3.

ResultsThe discovery set included 1,816 cases and 7,877 controls from three GWAS conducted at the following centres: University of Southern California (USC)13; International Agency for Research on Cancer (IARC)12; and University of Chicago (UC)14 (Fig. 1, Supplementary Fig. 1, Supplementary Table 1). Of the 1,816 cases, 58% were diagnosed between the ages of 15 and 35, 49% were female and 68% had HL tumours classied as NSHL. EBV tumour status was available for 1,063 cases; of these 27% were EBV positive. Fifty percent of the EBV-positive cases were MCHL. Conversely, 57% and 20% of MCHL and NSHL, respectively, were EBV positive, roughly similar to the distribution observed in a California population.5 Adolescents and young adults aged 1535 diagnosed with NSHL had the lowest proportion of EBV-positive tumours (17%), as expected.

For the meta-analysis, we rst applied quality control methods and imputation, which resulted in a total of 1,004,829 SNPs that were in common between the three studies (Fig. 1, Supplementary Fig. 2 (ref. 15)). When considering the global GWAS results, there was some evidence of a general ination of the test statistic (l 1.10, and excluding the MHC region, l 1.09). However,

after normalizing for sample size16, the degree of ination was modest (l1000 1.03). The discovery meta-analyses of HL and

subtypes were based on the 1,816 overall HL, 1,694 classical, 1,233

NSHL, 792 NSHL diagnosed between 1535 years old, and 320 MCHL cases, each compared with the same 7,877 controls. Analyses stratied on EBV tumour status were based on 287 EBV-positive HL and 776 EBV-negative HL compared with 6,863 controls from the subset of studies with EBV testing (Supplementary Table 1). The individual study results were combined using an inverse variance-weighted meta-analysis under the xed effects model used to generate all P-values reported below for GWAS associations.

The meta-analysis revealed HL subtype-specic associations with genotypic variants at 2p16 (REL), 5q31 (IL13), 6p21 (HLA), 8q24 and 10p14 (GATA3) and the two recently described loci at 3p24 (EOMES) and 6q23 (HBS1L-MYB), consistent with previous reports1113,17 (Figs 2, 3, Supplementary Table 2 (ref. 15), Supplementary Fig. 3). As expected, the SNPs near genes coding HLA class I alleles were strongly associated with EBV-positive HL and MCHL, but not EBV-negative HL or NSHL, while associations with SNPs near or in genes coding HLA class II alleles showed the opposite pattern (Fig. 2). We identied two SNPs within the regions of 2p16 (REL) and 10p14 (GATA3), rs13034020 (P 3.2 10 6) and rs444929 (P 3.1 10 6), in

our analysis that were more signicantly associated with HL than the previously reported SNPs rs1432295 and rs485411 (ref. 11) in these respective regions (Supplementary Fig. 3). When conditioned on the previously reported SNPs, the association between HL and rs13034020 (P 1.2 10 3) and rs444929

(P 1.8 10 3) remained signicant (Supplementary Table 3).

These SNPs, in addition to rs20541 in the IL13 gene region, were more strongly associated with EBV-negative HL and NSHL compared with EBV-positive and MCHL (Fig. 2, Supplementary Table 2). There was little difference in association by subtype/ subgroup for the loci in the 3p24 and 6q23 regions (Fig. 2).

We found a novel susceptibility variant (rs1860661) surpassing the threshold for genome-wide signicance located at chromo-some 19p13.3 within intron 2 of the TCF3 gene (OR 0.78,

P 2.0 10 8, I2 0%) (Fig. 3, Table 1). This variant was also

signicantly associated with all HL (OR 0.85, P 0.0024) in the

replication series of 1,163 all HL cases and 2,580 controls of European descent (Table 1, Fig. 4). In the combined analysis, rs1860661 was strongly associated with all HL (OR 0.81,

P 3.5 10 10), with no evidence of statistically signicant

heterogeneity between contributing studies (Phom 0.41,

I2 0%). Inconsistent associations by histologic subtype (MCHL)

and EBV status (EBV-positive HL) between the discovery and replication sets were likely to be chance ndings due to small numbers (Table 1).

For all HL combined, two other novel variants at chromosome 3q32 (CLSTN2, rs6439924, P 8.3 10 8, I2 0%) and chro

mosome 7p21 (ARL4A-ETV1, rs2058613, P 6.6 10 7,

I2 0%) approached genome-wide levels of signicance in the

discovery set, but were not signicant in the replication set (Supplementary Table 4).

We used a bioinformatic approach (FunciSNP18) to identify potential functional variants tagged by rs1860661. By querying the 20110521 release of 1,000 genomes database19, we identied four SNPs correlated (r240.5) with the index SNP (rs1860661).

We then extracted publically available ENCODE20 data on biofeatures, and found that the index SNP rs1860661 and two correlated SNPs, rs10413888 (r2 0.90) and rs8103453

(r2 0.89), map in or near marks of open chromatin and in

DNAse hypersensitivity sites in TCF3 in CD20 B-cell lines.

Interestingly, the protective haplotype dened by the minor alleles G-G-G of all three SNPs potentially enhances the efciency of the binding sites for transcription factors ZBTB7a and E2F1 (Fig. 5). The relative frequencies of each nucleotide (based on a position weight matrix) for the alleles in the ZBTB7A motif of

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IARC GWAS cases (n=1,279)lllumina 660w-Quad BeadChips (597,260 SNPs)

IARC Controls(n=5,752)lllumina HumanHap300 (317,139 SNPs), CNV370-Duo (353,202 SNPs), HumanHap550 (558,542 SNPs), Human 1.2MDuo (~1,200,000 SNPs)

USC HL GWAS (n=380) IIIumina 610 Quad BeadChip (599,011 SNPs)

USC HL GWAS Controls (CGEMS) (n=1,142)

IIIumina Human Hap550(v.1.1) (515,512 SNPs)

UC GWAS (CCSS cases) (n=214)

Affymetrix Genome-wide Human SNP Array 6.0

UC GWAS controls (GAIN) (n=1,016) Affymetrix

(741,279 SNPs in cases and controls combined)

2 Samples excluded

38 Samples excluded

94,746 SNPs excluded

Imputed with minimac, 1000 genome Phase I, release 2010-08, 11,210,656 SNPs for GWAS analysis

26 Samples excluded

14 Samples excluded

5 Samples excluded

5 Samples excluded

QC was performed separately within each of the control series based on SNP call rate (<98%), deviation from HWE (P<1e-07), MAF (<0.01) or concordance with case SNPs.

150,499 SNPs excluded

67,000 SNPs excluded

244,278 SNPs excluded

Imputed with IMPUTE 2, HapMap Phase III CEU 1,138,465 SNPs for GWAS analysis

Imputed with MACH 2, HapMap Phase III CEU 1,065,076 SNPs for GWAS analysis

Meta-analysis based on 1,004,829 variants common across all case and control series IARC GWAS: 1,241 cases, 5,726 controls,; USC GWAS: 366 cases and 1,137 controls; UC GWAS: 209 cases and 1,014 controls

Figure 1 | Quality control for subjects and SNPs in the GWAS discovery meta-analysis. Details for each GWAS have been previously published1214.

index SNP r1860661 are G:99.8% A:0.2% and for rs10413888 (r2 0.90) are T:0.4% G:97.4%. For rs8103453 (r2 0.89) the

E2F1 nucleotide frequencies are A:0% G:97%.

To investigate the function of rs1860661, we measured the expression levels of TCF3, and its two alternative transcripts, E12 and E47, in lymphoblastoid cell lines (LCLs) derived from circulating normal B cells from 49 post-therapy HL patients and 25 unaffected controls using linear models to assess correlation between genotype and TCF3 expression levels (Fig. 5). There was little evidence for correlation with TCF3 expression levels in this small sample, with only a weak association observed in LCLs from controls with the TCF3-E47 isoform (P 0.02), whose

transcription start site is located close to rs1860661 (Fig. 5). Similarly, there was little evidence in public databases21 that rs1860661 acts as a TCF3 eQTL, although eQTLs for the two isoforms were not available. Evidence for downregulation of both TCF3 isoforms was observed in seven HL-derived cell lines compared with germinal centre B cells sorted from three different tonsils (Pt-testo0.05) (Supplementary Fig. 4). Exome sequencing of the same set of seven HL cell lines identied a TCF3 missense mutation, p.N551K, (Supplementary Fig. 4) which has also been observed in Burkitt lymphoma22.

Finally, we selected the subset of 21,608 SNPs included in our GWAS previously identied as cis-eQTLs in B cells alone or both B cells and monocytes23. Within this subset, the genomic ination factor (l) was estimated as 1.16 (Supplementary Table 5,

Supplementary Fig. 5). A l of 1.16 was not observed within any of 1,000 random draws of 21,608 SNPs of similar minor allele frequency (MAF) taken from the complete HL meta-analysis,

(Supplementary Table 5), suggesting a relative overrepresentation of associated variants within this subgroup.

DiscussionIn this meta-analysis of 1,816 HL cases and 7,877 controls, we have identied a new susceptibility locus for HL at 19p13.3 in the TCF3 gene and noted associations with previously identied loci at 2p16REL, 5q31IL13, 6p21HLA region, 8q24 and 10p14GATA3. TCF3 is essential for the commitment of lymphoid progenitors to both B-cell and T-cell lineage development2426. In B cells, homodimers of the E47 isoform of TCF3 lead to transcriptional activation of TCF3 target genes including the B cell-specic transcription factors Oct-2, PU.1 and Bob.1 (ref. 25). A molecular and phenotypic hallmark of cHL is the loss of B-cell signature in HRS cells, including lack of the B-cell receptor, and the lineage markers CD19 and CD20. This loss has been attributed to downregulation of Oct-2, PU.1 and Bob.1 as a consequence of decreased formation of TCF3-E47 homodimers due to an increased expression of ABF-1 and ID2, two proteins that bind to and inhibit TCF3 (refs 2628). However, it is also possible that decreased transcription of the TCF3 gene contributes. Renne et al.26 reported lower average levels of TCF3 expression in cHL-derived cell lines compared with B-cell lines, and we observed signicantly lower levels of both TCF3 splice variants in cHL-derived cell lines compared with sorted tonsillar germinal centre B cells. These observations are consistent with the hypothesis that higher TCF3 levels in HRS precursor cells may lead to enhanced retention of the B-cell phenotype,

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SNPs P OR 95% CI

rs13034020, 2p16, REL, G

rs3806624, 3p24, EOMES, G

rs20541, 5q31, IL13, A

rs2069757, 5q31, IL13,A

rs2734986, 6p21, HLA class I, C

rs6904029, 6p21, HLA class I, A

rs6903608, 6p21, HLA class II, C

rs204999, 6p21, HLA class II, G

rs9402684, 6q23, HBS1L-MYB, T

rs2019960, 8q24, C

rs444929, 10p14, GATA3, T

All HL (P = 0.42)

All HL (P = 0.06)

All HL (P = 0.76)

All HL (P = 0.04)

All HL (P = 0.86)

All HL (P = 0.31)

All HL (P = 0.10)

All HL (P = 0.26)

All HL (P = 0.10)

All HL (P = 0.90)

All HL (P = 0.24)

3 10

2 10

1.281.261.081.291.261.03

1.171.221.151.261.071.17

1.371.481.211.501.491.05

1.591.661.491.841.751.13

1.321.232.011.180.942.20

0.860.880.630.931.040.47

1.641.801.141.902.030.96

0.770.671.070.610.641.16

1.191.201.231.191.181.19

1.301.291.211.421.421.22

1.261.331.051.381.281.00

1.161.431.111.450.841.381.111.491.091.460.811.31

1.081.271.091.350.951.391.121.420.961.190.981.40

1.251.511.311.680.971.511.311.711.301.690.841.31

1.391.821.401.981.082.041.532.211.472.100.811.57

1.191.471.071.421.592.541.011.380.801.101.782.71

0.790.940.780.980.510.790.821.060.921.180.370.59

1.511.781.612.000.941.391.692.141.812.280.791.17

0.700.850.590.760.871.320.520.710.560.730.961.40

1.091.301.081.331.011.501.061.341.061.331.001.43

1.181.431.151.460.981.511.251.621.251.611.001.50

1.151.391.181.510.831.341.201.581.121.470.801.25

6 10

3 10

1 10

1 10

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

NS MC NS

EBV negative EBV positive

0.54 7 100.0010.83

0.14

0.240.08

2 100.1 2 10 3 100.7

2 10

7 100.01 5 10

8 100.46

3 100.004 5 100.040.42

1 10

0.0010.03 4 100.290.52 4 10

7 10 1 100.19 6 10 7 100.68

2 10

1 100.51 6 10 2 100.13

5 10

9 100.040.0040.0040.05

6.6 103.5 100.081.2 104.9 100.05

3.1 107.8 100.683.6 10 3 10

1

0.5 1.0 1.5 2.5

Odds ratios

Figure 2 | Effect of genetic risk variants on the risk of Hodgkin lymphoma. Combined ORs and 95% CIs were derived from combining the three individual GWAS-specic estimates in a meta-analysis using a xed-effect model. Individual GWAS estimates (OR and 95% CIs) were derived from the unconditional logistic regression adjusted for sex, study center (for European Collaborative GWAS only) and signicant principal components, assuming additive model of inheritance. P-values for homogeneity between different subgroups were calculated using Cochrans Q-statistic. Squares represent summary estimates; the size of the square represents inverse of the variance of the log ORs; horizontal lines represent 95% CIs; diamonds represent results for the total HL; solid vertical lines represent OR 1.

Note that rs9402684 is substituted for rs7745098 (r2 0.90), which was not available in all three contributing GWAS. All HL, all subtypes of Hodgkin lymphoma

combined (1,816 cases, 7,877 controls), NS, nodular sclerosis (1,233 cases, 7,877 controls), MC, mixed cellularity (320 cases, 7,877 controls), NSyoung, nodular sclerosis diagnosed in young adults 1535 years old (792 cases, 7,877 controls), EBV negative (776 cases, 6,863 controls), EBV positive (287 cases, 6,863 controls).

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thereby conferring a protective effect for HL. A biofeature analysis suggests that rs1860661 is located in a transcription factor binding site; however, further study is necessary to determine whether rs1860661 is a causal SNP and associated with a true biological effect on TCF3 expression. Interestingly, in one out of seven HL cell lines, we observed a p.N551K missense TCF3 mutation, a mutation also found in Burkitt lymphoma samples22, suggesting that investigation of such mutations in HRS cells may be warranted.

As expected, previously published subtype (histology) and subgroup (tumour EBV status) associations with SNPs in 2p16, 5q31, 6p31.2, 8q4 and 10p14 regions were observed1113, although at higher signicance levels due to the increased power of the meta-analysis, supporting the proposition that cHL is aetiologically heterogeneous. There are clear associations between HLA class I loci and risk of both EBV-positive HL and MCHL, and between HLA class II, IL13, REL and GATA3 loci and risk of both EBV-negative HL and NSHL. Our data are inconclusive at this time regarding subset heterogeneity for rs1860661.

Thus, our data suggest a link between the 19p13.3 locus, including TCF3, and HL risk. Although we did not demonstrate functionality of rs1860661, it is located in a gene that is known to be downregulated in HL and thus merits further study. Because HL is a rare cancer, amassing substantial numbers of patients for a GWAS study is difcult. Nevertheless, our meta-analysis increased the ability to detect additional loci, to the level of an OR of 1.25 for a MAF of 30% with 80% power, in line with other meta-GWAS. Even so, we considered the potential for the existence of additional risk HL alleles by assessing the evidence for association within genetic variants linked with gene expression levels in B-cell lymphocytes (eQTLs)23 compared with unselected genetic variants. The existence of additional, as yet unidentied risk variants for HL is suggested by the observation that eQTLs were enriched among the top associations with HL as compared with non-eQTLs (Supplementary Table 5).

Methods

Ethics. All studies were approved by the following human subjects protection committees at the respective institutions: The University of Southern California Institutional Review Board, The Mayo Clinic Institutional Review Boards, The WHO International Agency for Research on Cancer Human Subjects Committee, The University of Chicago Institutional Review Board, Ethics Committees of Dijon and Lyon University Hospitals, Medical Ethical Review Committee of the UMCG, The Regional Ethical Review Board in Stockholm, The Scientic Ethics Committee for the Capital Region of Copenhagen, Research Ethics Committee for Wales 08/MRE09/72, West of Scotland Research Ethic Committee REC4 09/S0704/73, Multi-Centre Research Ethics Committee for Scotland 06/MRE00/83 and the Northern & Yorkshire Regional Ethics Committee. All patients and replication controls signed informed consent. De-identied publically available GWASdata were obtained for the control comparisons in the three-discovery-set GWAS.

Source of subjects and GWAS discovery. The discovery of meta-analysis was undertaken by two centres (IARC and USC) and was based on summary data from three previously reported GWAS providing genotype data on 1,816 HL cases and 7,877 controls of European descent: The European Collaborative GWAS12 and The University of Southern California (USC)13/University of Chicago (UC)14 GWAS studies were combined for a single meta-analysis.

The European Collaborative GWAS, presented elsewhere12, included 1,241 HL cases aged 1380 (median age 33 years) from ve European-based HL studies

and 5,726 generic controls aged 1794 (mean age 62) used in the initial GWAS

scan. In addition to the cHL cases described in the initial GWAS, 41 non-cHL cases were also included in the total. The distribution of cases among the ve European-based HL studies is as follows: The EPILYMPH Study (N 196)29, the

Scotland and Newcastle Lymphoma Group and the Young Adult Hodgkin Disease CaseControl Study (N 397)30, The Scandinavian Lymphoma Aetiology Study

(SCALE) (N 344)31,32 and the Northern Dutch Hodgkin Lymphoma Study

(N 304)33. The distribution of the controls by study is as follows: Alcohol-Related

Cancers and Genetic Susceptibility in Europe Study (N 323)34; The International

Agency for Research on Cancer Central Europe Study (N 443)35; The Pancreatic

35

6p21

30

25

log 10(P-value)

20

13

5q31

10

8q24

19p13, TCF3

8

10p14

6

3q32

2p16 3p24

7p21

6q23

4

2

0

1 2 3 4 5 6 7 8 9 10

11

12

13

14

15

17

19

21

Chromosome

Plotted SNPs

r 2

0.80.60.40.2

8 6 4

rs1860661 100

80

Recombination rate (cM/Mb)

10

log 10(P-value)

60 40 20 0

2 0

1.5 1.6

Position on chr19 (Mb)

1.7 1.8

Figure 3 | Results of a meta-analysis of three GWAS of Hodgkin lymphoma. (a) Manhattan plot of genome-wide results of a casecontrol comparison of 1,816 Hodgkin lymphoma patients and 7,877 controls of European origin. P-values were determined for each SNP based on the overall meta-analysis using a xed-effects model. Five loci surpassed the genome-wide signicance level of P 5 10 8, including four previously

reported SNPs at 6p21 (HLA class II) and 5q31 (IL13) and one novel SNP (rs1860661 at 19p13.3) located in TCF3. Noteworthy loci from previous reports replicated here at P r0.05 are also shown, including those at

2p16 (REL), 3p24 (EOMES), 6q23 (HBS1L-MYB), 8q24 and 10p14 (GATA3), in addition to two novel loci at 3q32 (CLSTN2) and 7p21 (ARLA4-ETV1) from this meta-analysis that did not replicate. Note that data for rs7745098 at 6q23 were not available in all three contributing GWAS, thus data for rs9402684 at r2 0.90 was substituted. Variants with I2 values Z75%

indicative of signicant heterogeneity were excluded. (b) Regional plot of the 19p13.3 locus. Results ( log10P) are shown for SNPs genotyped and

imputed within the region. The diamond represents the most signicant SNP in the locus and the r2 values for the other SNPs are indicated by different colours depending on the LD level in the CEU population. The genes within the region are annotated and shown as arrows. (c) Linkage disequilibrium map of the 19p13.3 locus (red represents r240.9).

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Table 1 | The association of the G allele of SNP rs1860661* with risk of Hodgkin lymphoma by EBV subgroup and histological subset.

SNP N MAF OR (95% CI) Pw Phomz I2w

(Ca) (Co) (Ca) (Co)

Discovery

All HL 1,816 7,877 0.35 0.41 0.78 (0.720.85) 2.0 10 8 0.38 0

Classical 1,694 7,877 0.35 0.41 0.78 (0.710.85) 2.3 10 8 0.05 67

NS 1,233 7,877 0.35 0.41 0.76 (0.680.85) 8.3 10 7 0.24 30

MC 320 7,877 0.34 0.41 0.69 (0.560.84) 2.1 10 4 0.12 53

EBV-neg 776 6,863 0.38 0.41 0.83 (0.740.93) 1.3 10 3 0.36 0

EBV-pos 287 6,863 0.37 0.41 0.84 (0.701.01) 0.06 0.64 0 NS (1535 y/o) 792 7,877 0.35 0.41 0.76 (0.670.85) 6.3 10 6 0.18 42

ReplicationAll HL 1,163 2,580 0.39 0.43 0.85 (0.760.94) 2.4 10 3 0.42 0

Classical 1,080 2,580 0.39 0.43 0.86 (0.770.96) 6.4 10 3 0.32 0

NS 854 2,580 0.39 0.43 0.83 (0.740.93) 1.7 10 3 0.23 30

MC 155 2,580 0.46 0.43 1.03 (0.801.32) 0.81 0.71 0 EBV-neg 513 2,580 0.35 0.43 0.73 (0.630.84) 2.05 10 5 0.82 0

EBV-pos 177 2,580 0.48 0.43 1.12 (0.901.39) 0.33 0.23 31 NS (1535 y/o) 505 2,580 0.38 0.43 0.81 (0.700.93) 3.2 10 3 0.93 0

CombinedAll HL 2,979 10,457 0.35 0.41 0.81 (0.760.86) 3.5 10 10 0.41 0

Classical 2,774 10,457 0.35 0.41 0.81 (0.760.87) 1.5 10 9 0.06 56

NS 2,087 10,457 0.35 0.41 0.79 (0.730.86) 9.4 10 9 0.25 26

MC 475 10,457 0.34 0.41 0.81 (0.690.94) 0.03 0.01 63 EBV-neg 1,289 9,443 0.38 0.41 0.79 (0.720.86) 1.6 10 7 0.51 0

EBV-pos 464 9,443 0.37 0.41 0.94 (0.821.08) 0.41 0.14 45 NS (1535 y/o) 1,297 10,457 0.35 0.41 0.78 (0.710.85) 8.6 10 8 0.41 0

Ca, cases; Co, controls; 95% CI, 95% condence interval; EBV-neg, EBV negative; EBV-pos, EBV positive; HL, Hodgkin lymphoma; MAF, minor allele frequency; MC, mixed cellularity; NS, nodular sclerosis;

OR, odds ratio.

*19p13.3, position 1601134.

wP-value generated from a meta-analysis using the xed effects model.

zP-value from Cochrans Q-statistic.

Odds ratio

TCF3, rs1860661,G P

OR 95% CI

Overall (Phom=0.41)

By study

Discovery (Phom=0.38)

Replication (Phom=0.42)

European Collaborative GWAS UC GWASUSC GWASMayo Clinic replication EPILYMPH replicationFrench replicationUK replication

0.810.780.85

0.810.680.740.770.870.940.79

0.760.860.720.850.760.94

0.730.890.530.860.580.950.591.000.551.360.801.100.660.94

3.51010

1.9108

0.002

2.21050.0020.0180.0440.540.440.008

0.6 0.8 1.0 1.4

Figure 4 | Forest plot of discovery and replication ORs and 95% CIs for the association between 19p13.3 TCF3 rs1860661 and Hodgkin lymphoma by study. ORs and 95% CIs were derived from the unconditional logistic regression adjusted for sex and signicant principal components (for individual GWAS analysis only), assuming additive model of inheritance. Squares represent ORs; the size of the square represents inverse of the variance of the log ORs; horizontal lines represent 95% CIs; diamonds represent summary estimate combining the study-specic estimates with a xed-effects model; solid vertical lines represent OR 1; the dashed vertical line represents the overall OR. P-values for homogeneity between different subgroups were calculated

using Cochrans Q-statistic. Samples sizes are as follows: combined discovery and replication (3,097 cases and 11,095 controls); overall discovery (1,816 cases and 7,877 controls) consisted of European Collaborative GWAS (1,241 cases and 5,726 controls); USC GWAS (366 cases and 1,137 controls); UC GWAS (209 cases and 1,014 controls); overall replication (1,163 cases and 2,580 controls) consisted of Mayo Clinic (234 cases and 223 controls); EPILYMPH (64 cases and 141 controls); French Replication Series (LYSA/CNG Evry France) (366 cases and 1,696 controls); UK Replication Series (ELCCS (York)/Scotland and Newcastle Epidemiological Study of Hodgkin Disease (499 cases and 520 controls). The Scandinavian SCALE studyis not included as rs1860661 could not be genotyped in controls using Sequenom.

Cancer Cohort Consortium (N 321)36; The Nijmegen Biomedical Study

(N 1,769)37 and The Wellcome Trust CaseControl Consortium (N 2870)38.

Cases were genotyped at the Centre National de Gnotypage using the Illumina

Innium Human660-Quad BeadChip (Illumina San Diego, CA). Multiple sources of generic controls were genotyped on compatible Illumina BeadChips platforms.

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20 kb

1,630,000 1,635,000 1,640,000 1,645,000 1,655,000

Scale

chr19:

CTCF

1,610,000 1,615,000 1,620,000 1,625,000

rs1142110590.5025

hg19

1,650,000

1,660,000

DNasel

H3K27Ac

H3K4me2

H3K4me3

Txn

Factor ChIP

E47

TCF3

rs104138880.8991

rs81034530.8894

rs1860661

rs118831850.6961

rs10045140.5443

E12

ZBTB7A/LRF:

E2F1:

ZBTB7A/LRF:

Bits

2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

d

Motif: Genomic sequence:

rs10413888

TCF3 total controls

Bits

210 1 2 3 4 5 6 7 8

Position

Bits

210 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

d

1

9 10 11 12 13 14 15

d

Position

Position

rs8103453 rs1860661

AF: 0.40 AF: 0.38 AF: 0.41

TCF3 isoform E12 controls

NS

TCF3 isoform E47 controls

TCF3 isoform E47 patients

TCF3 total patients TCF3 isoform E12 patients

8

6

4

2

0

NS

P=0.022

NS NS NS

2Ct

2Ct

2Ct

2Ct

2.5

2.0

1.5

1.0

0.5

0.0

AA GA GG AA GA GG AA GA GG

4

2

3

1

0

2Ct

10

8

6

4

2

0

10

8

6

4

2

0

2Ct

10

8

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4

2

0

AA GA GG AA GA GG AA GA GG

Figure 5 | Bioinformatic and expression analysis of the TCF3 SNP. (a) Browser view of TCF3 genomic region. Position of ENCODE data for the chromatin biofeatures used to lter correlated SNPs are shown in the top ve tracks as black bars. The FunciSNP18 analysis track displays correlated SNP positions with the name and r2 value. Red arrows highlight the putative functional SNPs for this region. Genomic sequence surrounding the affected SNPs is shown at bottom under the motif-logo of the matched transcription factor, with the risk allele for Hodgkin lymphoma boxed in red. The alternative (protective) allele is displayed next to the SNP name, with allele frequency for Europeans in 1,000 genomes19. (b) TCF3 expression levels determined on RNA isolated from lymphoblastoid cell lines generated by transformation of blood B cells obtained from healthy controls (n 25) and post-therapy Hodgkin lymphoma

(n 49) patients, using qRTPCR. Linear models were used to assess correlation between genotype and TCF3 expression levels.

The USC HL GWAS included 366 European-origin cases (from an original 380) from four sources, (age range 758, mean age 29.5); 233 patients, diagnosed o45

years of age between 2000 and 2008, were ascertained from two California SEER registries13, and 133 patients, diagnosed between the ages of 7 and 58 from 1975 through 2006, were ascertained from two USC twin registries: the population-based California Twin Program and volunteer International Twin Study7,39. Of the 366 HL cases, 251 (69%) were diagnosed as NSHL; 72 (20%) as MCHL; 11 (3%) as other cHL; 11 (3%) as lymphocyte predominant HL; and 21 (5%) as not specied. Of the 129 specimens tested for EBV by in situ hybridization40, 107 (83%) were negative and 22 (17%) were positive. 90% of the NSHL and 50% of the mixed cellularity tumours were EBV negative. Fourteen cases from the original analysis13 were removed due to additional QC measures. Controls were 1,137 (from an original 1,142) European-origin females aged 2542 who were breast cancer controls in the Cancer Genetic Markers and Susceptibility Project (CGEMS)41,42. USC cases were genotyped using the Illumina 610 Quad BeadChip and controls were genotyped using the Illumina HumanHap550 (v.1.1).

The third GWAS was conducted at UC14, in which cases consisted of 209 (from an original 214) HL patients diagnosed prior to age 21 (mean age 16) who were

participants in the Childrens Cancer Survivor Study, a retrospective study of 14,358 survivors of childhood cancer diagnosed before 21 years of age and

surviving at least ve years43. Of these, 142 (68%) were diagnosed as NSHL and 18 (9%) as MCHL. Five cases from the original analysis14 were removed due to additional QC measures. Tumour EBV status was not available. Controls were 1,014 (from an original 1,016) cancer-free individuals of European ancestry (464 males and 550 females) from the Genetic Association Informative Network schizophrenia study cohort (phs000021.v1.p1)44. Cases were genotyped at UC on the Affymetrix Genome-Wide Human SNP Array 6.0. Permission was obtained for use of CGEMS and GAIN results from dbGAP (dbgap.ncbi.nlm.nih.gov/aa/ dbgap)41.

Stringent quality control was performed on the genome-wide genotypes by each of the three GWAS centres that conducted a GWAS based on standard procedures1214. To rene associations with previously reported loci and to identify new disease loci, we imputed untyped genotypes using IMPUTE2 (refs 15,45) and HapMap Phase III (http://hapmap.ncbi.nlm.nih.gov

Web End =http://hapmap.ncbi.nlm.nih.gov) reference genotypes for the USC and UC HL GWAS data and minimac15,46 software and 1000 Genome Project data release 201008 reference genotypes19 for the European Collaborative GWAS12. Poorly imputed SNPs, dened by an r2o0.30 with MACH1 (ref. 46)/

minimac15 or an information measure (Is) o0.30 with IMPUTE2 (ref. 33), were excluded from the analyses. Each GWAS study used a 10% threshold for missingness.

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Technical validation of the three novel SNPs with genome-wide signicance was performed in the IARC European Collaborative GWAS (300 discovery set case samples and 90 HapMap Ceu Samples) and USC GWAS (36 discovery case samples) using the same TaqMan probes. Concordance for rs1860661, rs6439924 and rs2058613 across GWAS and replication genotyping platforms was between99.6% for the European Collaborative GWAS and 100% for the USC GWAS.

Replication series and genotyping. Novel SNP associations were further validated in an independent replication series comprising 1,281 cases and 3,218 control subjects from multiple casecontrol or case series. DNA from the European subjects was genotyped at the Centre National Genotypage (1,047 HL cases and 2,995 controls from four contributing studies, mean age 42). The EPILYMPH

replication set included 64 cases aged 1878 at diagnosis and 141 controls aged 1881 from the Czech Republic, France, Germany, Ireland, Italy and Spain29;the French replication series included 366 cases aged 1593 at diagnosis from a prospective biologic study carried out by LYSA (Lymphoma Study Association)47 and 1696 French controls genotyped by the Centre National Genotypage (CNG Evry, France); the UK replication series included 499 cases aged 1590 at diagnosis and 520 controls aged 1687 at participation from the ELCCS (York) casecontrol study48, the Scotland and Newcastle Epidemiological Study of Hodgkins disease30 and the Young Adult Hodgkins Disease CaseControl Study; and the Scandinavian Lymphoma Aetiology Study (SCALE) replication series included 118 cases aged 1875 and 638 controls aged 1975 from Sweden and Denmark31,32, not included in the discovery GWAS. The Mayo Clinic Replication series included 234 cases ages 1889 at diagnosis and 223 internal medicine or family medicine clinic controls seen for routine appointments49 (mean age of Mayo Clinic cases and controls 44 years), genotyped at the Molecular Genomics Core of USC. A subset

of European controls was also genotyped at the Centre National Genotypage using the Illumina Sentrix HumanHap300 BeadChip (French controls, n 1,696) or

Sequenom (SCALE31 controls, n 638). A TaqMan Pre-Designed SNP Genotyping

Assay Mix (containing probes and primers) was used for each SNP (Applied Biosystems, Carlsbad, CA, assay-on-demand order code C__32302340_10 for rs6439924 and C__11969900_10 for rs1860661). No assay could be designed for rs2058613 and therefore a proxy variant (R2 1.0, D0 1.0 in CEU) rs6946457

(assay C__2678118_10) was genotyped. Similarly, rs1860661 could not be genotyped by Sequenom in the SCALE31 controls as this assay was not able to be designed for this platform. The performance of the assays was validated at the Centre National Genotypage by re-genotyping CEU HapMap samples (US residents with Northern and Western European ancestry) and comparing the results to HapMap genotypes (http://hapmap.ncbi.nlm.nih.gov

Web End =http://hapmap.ncbi.nlm.nih.gov) (IARC) and by re-genotyping 32 samples from the GWAS and comparing the results to the array based genotypes (USC). Within the study samples, duplicate genotyping concordance was greater than 99%.

Statistical analysis. All calculations were performed using PLINK50 (http://pngu.mgh.harvard.edu/~purcell/plink

Web End =http:// http://pngu.mgh.harvard.edu/~purcell/plink

Web End =pngu.mgh.harvard.edu/Bpurcell/plink ), SAS version 9.2 (SAS Institute, Cary, NC, USA) and R15.1 (R project). LocusZoom51 was used for regional visualization of results. LD statistics were calculated based on HapMap3 release 2 using SNAP Proxy Search52. In each of the three discovery GWAS analyses, quality control included removal of individuals with cryptic relatedness and a genotyping call rate of o0.95. In addition, SNPs with a call rate of o0.95, a MAF of o0.01 in the data, deviation from HardyWeinberg equilibrium (Po1 10 5), or whose genotypes

resulted from artifacts were removed. Associations between SNP genotypes and HL risk were evaluated under a log-additive model of inheritance adjusting for sex, study centre (European Collaborative GWAS only) and signicant principal components to control for population stratication53.

A meta-analysis using a xed effects model weighted on the inverse of the variance was conducted based on GWAS summary statistics for the log-additive model of inheritance54. Only variants available in all three GWAS studies, successfully genotyped/imputed, with no evidence of ambiguous strand calls between studies, were included. We examined overdispersion using P-values from the meta-analysis to generate QuantileQuantile plots and estimate an ination factor l, calculated as a ratio of the median of the observed l2 statistics for association from the Wald tests over the median ( 0.455) of the l2 distribution

with 1 df54 (Supplementary Figs 1 and 2). The HLA region was excluded when calculating the l to reduce the ination due to numerous SNPs in LD capturing this previously known locus. Associations between the risk alleles and HL and subtypes were assessed using logistic regression to estimate ORs and 95% CIs and P-values within individual studies. Cochrans Q-statistic to test for heterogeneity and the I2 statistic to quantify the proportion of the total variation due to heterogeneity was calculated. Fixed-effect values Z75% are considered the characteristic of large heterogeneity and corresponding variants were excluded from the analysis. Replication analyses were conducted using logistic regression to estimate ORs, 95% CIs and P-values within individual studies. Study-specic estimates were summarized using a meta-analysis procedure as described above.

FunciSNP functional annotation. To integrate chromatin biofeature annotations with 1000 Genomes19 genotyping data, we used an in-house developed R package FunciSNP18, available at http://www.Bioconductor.org

Web End =www.Bioconductor.org . We selected publicly available

data sets relevant to the development of the B-cell lineage and thus the following ENCODE data sets were employed to lter correlated SNPs that lie within putative enhancer regions with Gene Expression Omnibus accession IDs: B cells CD20

RO01778 DGF Peaks (GSM1014525), B cells CD20 RO01778 DNaseI HS Peaks

(GSM1024765, GSM1024766), B cells CD20 RO01794 HS Peaks (GSM1008588),

CD20 (RO 01778) H3K4me3 Histone Mod chromatin immunoprecipitation

(ChIP)-seq Peaks (GSM945229), CD20 RO01794 H3K27ac Histone Mods by

ChIP-seq Peaks (GSM1003459), CD20 (RO01794) H3K4me3 Histone Mod

ChIP-seq Peaks (GSM945198), CD20 CTCF Histone Mods by ChIP-seq

Peaks (GSM1003474), CD20 H2A.Z Histone Mods by ChIP-seq Peaks

(GSM1003476), CD20 H3K4me2 Histone Mods by ChIP-seq Peaks

(GSM1003471). To dene other physical map features (transcription start sites, 50UTR, 30UTR), we downloaded annotations from the February 2009 release of the human genome (GRCh37/hg19) available from the UCSC genome browser55. Finally, we used the highly conserved set of predicted targets of microRNA targeting at http://www.mircode.org

Web End =www.mircode.org (miRcode 11, June 2012 release), and conserved high-quality microRNA target species from http://www.microRNA.org

Web End =www.microRNA.org (June 2010 release).

FunciSNP18 was run with the following settings: a window size of 1 Mb around the index SNP was used with r240.5. To determine whether FunciSNP-generated

SNPs potentially affect the binding of known transcription factors, position-specic weight matrices were employed from Wang et al.56 To distinguish between neutral and potentially damaging (or activating) variants, both alleles of the SNP were scored by adding up the total matrix score of each of 119 transcription factor motifs for each of the possible start sites in a window around the SNP and agging the start positions that surpassed a threshold of 80% of the maximum score for each motif. In addition, the scoring was weighted by the difference between maximum and minimum score at each position, so that unconserved and noncritical sites did not inuence the score. SNPs that were found within the binding sites of 80% maximum or better were reported along with the score of the alternate allele. A quality score derived from the ratio of the difference in scores/ 1 (maximum allelic binding to the TF at that position) was used to rank the

SNPs and classify them as neutral, damaging or activating.

TCF3 expression experiments. LCLs were generated from blood samples collected from 74 individuals, including 25 healthy controls and 49 post-therapy cHL patients (from blood samples collected at least 1 year after completion of all therapies) by infection of PBMCs with the EBV strain B95-8. Genotyping of the LCLs was carried out using a TaqMan SNP assay. Expression levels were assessed using quantitative reverse transcriptase PCR which was performed on all cell lines using the TCF3 assay and isoform-specic primer sets. Association between TCF3 gene expression levels and TCF3 genotype was assessed by linear regression, separately for cHL cases and controls, using PLINK50.

To compare TCF3 expression in cHL cell lines to normal tonsillar germinal centre B cells, germinal centre B cells were sorted from three independent tonsils (CD19 CD38 IgD ). HL-derived cell lines, that is, L428, L540, L591, L1236,

KM-H2, SUPHD1 (available from Braunschweig, Germany) and DEV (A. van den Berg Laboratory)57, were cultured in RPMI 1640 medium (Lonza Walkersville, Walkersville, MD) supplemented with 520% fetal calf serum, 100U ml 1 penicillin/streptomycin and ultraglutamine (Lonza Walkersville) in a 5% CO2 atmosphere at 37 C.

DNA isolation and genotyping (TaqMan SNP assay, C_11969900_10) was carried out using standard procedures. RNA was isolated using Trizol (Invitrogen, Carlsbad, USA) and DNAse treated (Ambion, Foster City, CA). The RNA concentration was measured with a NanodropTM 1000 Spectrophotometer (Thermo Fisher Scientic, Waltham, USA) and integrity was evaluated by the Experion system. cDNA was synthesized using 500 ng input RNA, Superscript II and random primers according to the manufacturers protocol (Invitrogen). quantitative reverse transcriptase PCR was performed on all samples using the TCF3 assay and isoform-specic primer sets in triplicate. Relative expression levels were calculated using TBP as housekeeping gene and data were expressed as the 2-deltaCt values. A t-test was used to test for TCF3 expression level differences in cHL cell lines compared with germinal centre B cells.

TCF3 mutation analysis. In an ongoing whole-exome sequencing analysis, we noted a missense mutation (p.N551K) in the TCF3 gene in one out of seven HL-derived cell lines, that is, SUPHD1. To conrm the presence of the mutation and expression of the mutant allele, we amplied cDNA of the SUPHD1 cell line by PCR with AmpliTaq Gold DNA Polymerase, PE Buffer II and MgCl2 (Applied

Biosystems) and primers designed for the region of interest (Primer Express, Applied Biosystems). Primers were ordered with an M13-tail (underlined), to allow direct sequencing of the PCR product (forward 50-gtaaaacgacggccagtcggaggaggagaagaaggag-30 and reversed 50-ggaaacagctatgaccatggcttggtctgcgctttgtc-30). PCR products were run on an agarose gel to check efciency and puried by high pure PCR product purication kit (Roche, Mannheim, Germany) and sent for sequencing (LGC Genomics).

HL GWAS genetic variants in eQTLs. From the HL GWAS meta-analysis, we selected a subset of genetic variants that were (cis) eQTLs in (B cells alone or both

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B cells and monocytes), based on Fairfax et al.23 Variants located within the HLA region (Position 6:25,000,000 to 6:35,000,000) were excluded due to the very high degree of LD, leaving 21,608 SNPs. We used a permutation procedure to consider the range of l expected by chance by randomly drawing 1,000 subsets (with replacement) of 21,608 SNPs taken from the complete HL meta-analysis 885,168 non-MHC genetics variants of the original HL meta-analysis. We then estimated l within each of randomly selected 1,000 subsets of 21,608 SNPs.

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Acknowledgements

The European Collaborative Study and replications were supported by: LInstitut National du Cancer, France; Spanish Ministry of Health grant CIBERESP (FIS 08-1555 and 06/02/0073 to S.d.S.); Ministry of Health of the Czech Republic (MZ0 MOU2005 toL.F.); German Jos Carreras Leukemia Foundation (DJCLS_R04/08 to A.N.); Federal Ofce for Radiation Protection (StSch4261 and StSch4420 to N.B.); European Commission 5th Framework Program Quality of Life (QLK4-CT-2000-00422 to P.Br.); European Commission 6th Framework Program (FP6-2003-FOOD-2-B to P.Bo.); La Fondation de France (1999-008471 to M.Ma.); Compagnia di San Paolo-Programma Oncologia (P.C.); Health Research Board, Ireland (A.S.); Leukaemia & Lymphoma Research (08031 and 05045 to R.F.J.); Kay Kendall Leukaemia Fund (R.F.J. and G.M.T.); National Institutes of Health (R01CA69269 to M.Me.), Nordic Cancer Union (16-02-D to H.H.); Plan Danmark; Danish Cancer Research Foundation (41-08 to M.M.); Lund-beck Foundation (R19-A2364 to H.H.); Danish Cancer Society (DP 08-155 to H.H.); Swedish Cancer Society (2009/1084 to K.E.S.); Dutch Cancer Society (KWF grants RUG 2009-4313 to A.v.d.B. and RUG 2010-4860 to A.D.); the Netherlands Organization of Scientic Research (NWO-MW grant 920-03-136 to A.D.); Leukaemia & Lymphoma Research (00/73 and 06001 to E.R.). The U.S. GWAS, replications and bioinformatics work was supported by grants from the National Institutes of Health (R03CA110836 to W.C.; HD0433871, CA129045, and CA40046 to K.O.; CA55727 to L.L.R.; R01CA58839 to T.M.M., R01CA136924 to G.C., CA092153 and CA097274 to J.R.C.); the United States Army Medical Research and Materiel Command (Department of Defense PR054600 to W.D.O.C.); the American Cancer Society Illinois Division (to K.O.); the American Lebanese Syrian Associated Charities (to L.L.R.); the Leukemia & Lymphoma Society (TR6137-07 to W.D.O.C.); and the Cancer Research Foundation (to K.O.). This project was funded in whole or in part with federal funds from the National Cancer Institute Surveillance Epidemiology and End Results Population-based Registry Program, National Institutes of Health, Department of Health and Human Services, under

contracts N01-PC-35139 (to W.D.O.C.) and N01-PC-35136 (to the Cancer Prevention Institute of California), and from the National Cancer Institute contract 263-MQ-417755 (to S.L.G.). The collection of incident HL patients used in this publication was supported by the California Department of Health Services as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. This publication was made possible by grant number 1U58DP000807-01 from the Centers for Disease Control and Prevention. We thank G. Thomas and Synergy Lyon Cancer (Lyon France) for high performance computing support.

Author contributions

W.C., M.L., D.V.C., G.A.C., M.L., P.B., K.O., R.F.J., H.H., A.v.d.B. and J.D.M. designed the study. M.N.T., D.L., D.H., K.A.R., M.D.-S., C.K.E., Y.B., V.G., G.B. and J.D.M. performed the statistical analysis. W.C., K.A.R., D.J.V.D.B., L.F., K.E.S., S.L.G., H.-J.W.,L.L.R., T.M.M., H.G., A.E.G., A.N., S.d.S., V.K.C., T.L., N.B., L.F., E.R., M.M., B.N.N., B.G., A.S., P.B., B.K.L., L.K., S.M.A., S.B., L.C.S., T.M.H., P.G., L.Va., E.J.D., A.L., R.N.V.,L.Vi., Y.L., K.Y.U., D.M., L.M.W., M.L., H.-O.A., M.Me., J.R.C., A.G., G.M.T., S.L.S., P.B., T.B., A.S., D.V.C., G.A.C., K.O., R.F.J., H.H., A.v.d.B. and J.D.M. provided samples and data. W.C., A.D., K.O., R.F.J., H.H., A.v.d.B. and J.D.M. drafted the manuscript. All authors contributed to the nal paper.

Additional information

Accession codes: Exome sequence data for the TCF3 gene in 7 Hodgkin lymphoma cell lines has been deposited in the EMBL European Bioinformatics Institute database under the accession code PRJEB5699 (or ERP005119).

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Competing nancial interests: The authors declare no competing nancial interests.

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How to cite this article: Cozen, W. et al. A meta-analysis of Hodgkin lymphoma reveals 19p13.3 TCF3 as a novel susceptibility locus. Nat. Commun. 5:3856doi: 10.1038/ncomms4856 (2014).

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