# For the GWAS stage, B-cell NHL cases which small numbers (N<20) were excluded from analysis.

Supplementary Table 1a. Subtype Breakdown of all analyzed samples Stage GWAS Singapore Validation 1 Guangzhou Validation 2 Guangzhou Validation 3 Beijing Total No. of B-Cell Cases 253 # 168^ 294^ 713^ 1428 B-Cell NHLs Subtype Follicular lymphoma 51 19 32 80 182 Diffuse large B-cell Lymphoma 148 102 235 503 988 Marginal zone lymphoma 54 - - - 54 MALT - - - 61 61 Mantle cell lymphoma - 4-25 29 Unspecified B-cell NHLs - 43 27-70 CLL/SLL - - - 44 44 No. of non B-cell (T/NK-cell) Cases 49 71 66 276 462 No. of Controls 1438 1632 2127 1733 6930 Table above lists all samples which had passed QC filters and were selected for analysis. # For the GWAS stage, B-cell NHL cases which small numbers (N<20) were excluded from analysis. ^ For the validation Stages, the unspecified NHLs and Burkitt s lymphomas were excluded from analysis. MALT: Mucosa associated lymphoid tissue lymphoma, CLL/SLL: Chronic lymphocytic leukemia/small lymphocytic lymphoma

Supplementary Table 1b. Age and gender information for all samples analyzed Age and gender details of study participants Stage/Details GWAS Singapore Validation 1 Guangzhou Validation 2 Guangzhou Validation 3 Beijing Cases Controls Cases Controls Cases Controls Cases Controls Total 253 1438 168 1632 # 294 2127 713 1733 Average age in years 57.88 + 14.78 30.56 + 17.32 44.49 + 20.96 37.39 + 15.40 48.59 + 16.42 43.82 + 13. 50.01 + 16.32 53.87 + 12.39 No. of males 147 762 105 1081 # 166 1366 400 1132 No. of females 106 676 63 531 # 128 761 313 601 Females to males ratio 1 : 1.38 1 : 1.12 1 : 1.66 1 : 2.03 1 : 1.29 1 : 1.79 1 : 1.27 1 : 1.88 Table above lists the age and gender information for all samples that were recruited for this study. # 20 controls were without age/gender information, and excluded from calculations.

Supplementary Table 2a. List of SNPs (P < 1.0 10-4 ) in the GWAS stage and the validation 1 association analysis data CHR SNP Minor allele cases controls GWAS P value GWAS OR cases controls Validation P-value Validation OR Meta-P Meta-OR I 2 P Heterogeneity 8 rs273429# G 0.52 0.40 8.42E-05 1.46 0.50 0.37 7.58E-05 1.65 1.35E-08 1.56 0 0.4473 3 rs6773854# G 0.31 0.20 2.30E-06 1.68 0.26 0.18 5.83E-04 1.56 1.54E-08 1.66 0 0.836 1 rs3087908# A 0.15 0.24 6.01E-05 0.59 0.20 0.25 0.03157 0.75 2.22E-05 0.64 0 0.6144 12 rs2632214# A 0.45 0.35 4.92E-05 1.50 0.41 0.35 0.04737 1.27 6.95E-06 1.44 0 0.386 5 rs2069478# A 0.12 0.06 7.46E-05 1.90 0.10 0.06 0.06071 1.64 1.44E-05 1.79 0 0.478 12 rs7977174 G 0.24 0.17 7.23E-05 1.58 0.20 0.17 0.07256 1.16 3.92E-05 1.48 0 0.4985 13 rs13313317 A 0.15 0.09 6.25E-05 1.76 0.12 0.09 0.1297 1.40 2.04E-05 1.65 2.43 0.3114 19 rs673153 G 0.49 0.40 9.09E-05 1.46 0.40 0.40 0.2296 1.01 3.35E-04 1.32 9.68 0.2927 16 rs10871275 G 0.25 0.34 1.25E-04 0.65 0.31 0.33 0.1644 0.91 1.34E-04 0.71 16.5 0.2738 7 rs10235691 A 0.34 0.42 5.18E-05 0.66 0.39 0.42 0.1251 0.88 2.85E-05 0.71 33.92 0.2186 6 rs622342 C 0.08 0.15 1.28E-04 0.53 0.14 0.15 0.2335 0.94 3.00E-04 0.62 44.14 0.1809 6 rs7746862 G 0.36 0.27 4.71E-05 1.53 0.30 0.27 0.4673 1.15 0.001373 1.31 47.47 0.1677 7 rs7804000 A 0.42 0.32 6.19E-05 1.48 0.36 0.33 0.2803 1.14 9.43E-05 1.37 48.73 0.1626 13 rs535367 A 0.32 0.23 9.30E-05 1.51 0.28 0.23 0.3063 1.29 1.00E-04 1.40 53.69 0.1417 19 rs891061 G 0.49 0.40 1.12E-04 1.45 0.43 0.43 0.5193 0.99 7.27E-04 1.30 56.79 0.1282 12 rs2306517 G 0.29 0.21 4.43E-06 1.65 0.21 0.21 0.3621 1.01 9.99E-05 1.42 61.46 0.1072 9 rs1162211 A 0.36 0.45 2.86E-05 0.66 0.43 0.44 0.3005 0.94 3.80E-05 0.72 64.83 0.0917 17 rs8066330 G 0.38 0.48 9.34E-05 0.67 0.44 0.47 0.2583 0.87 1.79E-05 0.70 67.47 0.0795 4 rs11098416 G 0.16 0.25 1.08E-04 0.61 0.21 0.27 0.3422 0.75 2.60E-04 0.70 67.61 0.0789 15 rs17737742 A 0.14 0.08 9.02E-05 1.76 0.09 0.08 0.5191 1.18 6.52E-05 1.64 69.39 0.0707 13 rs6491241 A 0.34 0.42 9.81E-05 0.67 0.41 0.41 0.6935 0.99 7.58E-04 0.76 71.49 0.0611 5 rs6873372 A 0.08 0.04 1.15E-04 2.13 0.06 0.04 0.59 1.30 8.33E-05 1.92 73.27 0.0531 5 rs31549 G 0.37 0.46 6.30E-05 0.67 0.46 0.45 0.9654 1.03 0.006052 0.80 76.87 0.0376 19 rs2191139 A 0.52 0.43 9.39E-05 1.47 0.45 0.46 0.9271 0.97 0.002694 1.27 80.54 0.0234 4 rs1865532 G 0.2 0.28 9.56E-05 0.63 0.29 0.27 0.6437 1.10 0.02257 0.81 82.55 0.0167 8 rs2597384 C 0.27 0.35 1.26E-04 0.66 0.35 0.36 0.7493 0.97 0.008192 0.79 83.31 0.0144 18 rs10502994 A 0.17 0.26 4.74E-05 0.59 0.23 0.26 0.9637 0.84 0.002366 0.74 83.46 0.0139 8 rs4739895 A 0.17 0.11 5.73E-05 1.70 0.11 0.11 0.6013 0.99 0.002352 1.42 83.52 0.0138 4 rs522636 G 0.41 0.50 6.75E-05 0.68 0.55 0.49 0.5456 1.29 0.009939 0.82 84.48 0.0111

Supplementary 2a continued. CHR SNP Minor allele cases controls GWAS P value GWAS OR cases controls Validation P-value Validation OR Meta-P Meta-OR I 2 P Heterogeneity 5 rs4443401 G 0.27 0.19 8.69E-05 1.54 0.18 0.20 0.3877 0.86 0.01494 1.25 84.93 0.01 14 rs6572635 A 0.18 0.12 1.01E-04 1.65 0.09 0.13 0.2663 0.71 0.01941 1.30 85.66 0.0083 6 rs10499010 G 0.25 0.18 7.91E-05 1.58 0.16 0.18 0.4066 0.88 0.007489 1.30 85.8 0.008 22 rs737865 G 0.33 0.28 1.01E-04 1.51 0.28 0.30 0.4541 0.89 0.009634 1.25 86.4 0.0067 12 rs7303892 G 0.38 0.28 4.15E-07 1.68 0.33 0.30 0.8045 1.17 9.71E-05 1.39 88.48 0.0032 7 rs4719687 A 0.49 0.41 1.43E-05 1.54 0.43 0.45 0.6058 0.95 1.12E-03 1.30 88.58 0.0031 22 rs2020917 A 0.34 0.28 6.85E-05 1.52 0.27 0.31 0.3134 0.83 0.01045 1.25 88.71 0.0029 3 rs17041034 A 0.2 0.15 1.60E-05 1.75 0.12 0.15 0.2007 0.74 0.02067 1.29 88.81 0.0028 1 rs2818765 A 0.38 0.47 5.36E-05 0.67 0.51 0.45 0.3555 1.25 0.006194 0.80 89.44 0.0021 6 rs9366597 G 0.5 0.41 4.68E-06 1.56 0.39 0.42 0.2277 0.90 0.01196 1.22 90.01 0.0016 12 rs7971281 A 0.39 0.28 5.16E-08 1.74 0.33 0.30 0.8045 1.15 1.86E-05 1.43 90.58 0.0011 5 rs16875141 A 0.23 0.15 1.74E-05 1.69 0.13 0.15 0.1731 0.86 0.001569 1.40 91.44 0.0006 15 rs2925199 G 0.46 0.38 8.61E-05 1.47 0.35 0.39 0.08698 0.83 0.04203 1.18 91.69 0.0005 10 rs11003927 A 0.31 0.24 7.73E-05 1.53 0.22 0.25 0.118 0.83 0.01134 1.26 91.95 0.0004 2 rs2357887 C 0.29 0.38 6.56E-05 0.65 0.39 0.36 0.1874 1.10 0.01707 0.82 91.96 0.0004 14 rs3210043 A 0.1 0.06 3.24E-06 2.27 0.03 0.06 0.02282 0.51 0.001337 1.69 93.23 0.0001 19 rs2082465 A 0.47 0.41 1.24E-04 1.46 0.36 0.43 0.01444 0.76 0.136 1.13 93.59 0.0001 1 rs12029838 A 0.13 0.19 4.67E-05 0.56 0.25 0.18 0.00254 1.47 0.4822 0.93 95.71 0.0002 Meta-analysis was performed using inverse variance weight under the fixed-effect model as described in online methods. Only SNPs fulfilling the selection criteria of replication P < 0.06 with no evidence of heterogeneity (P Heterogeneity > 0.10, I 2 < 20) in the primary meta-analysis were selected for validation. # These SNPs were selected for validation.

Supplementary Table 2b. List of SNPs (P < 1.0 x 10-4 ) in the GWAS stage that failed Sequenom primer design and genotyping CHR SNP Minor allele cases controls GWAS P value GWAS OR Remarks 2 rs6710386 C 0.43 0.38 1.34E-04 1.46 Failed sequenom Design 2 rs1424339 C 0.32 0.28 1.30E-04 1.48 Failed sequenom Design 4 rs4498140 A 0.09 0.05 4.96E-05 2.02 Failed sequenom Design 6 rs12528998 C 0.17 0.26 1.33E-04 0.62 Failed sequenom Design 8 rs10095520 A 0.04 0.09 1.38E-04 0.40 Failed sequenom Design 11 rs11037804 G 0.15 0.10 1.49E-05 1.83 Failed sequenom Design 16 rs1110554 A 0.55 0.44 1.78E-05 1.52 Failed sequenom Design 3 rs12632303 A 0.3 0.20 3.45E-06 1.67 Failed Genotyping 5 rs10045706 G 0.38 0.30 5.36E-05 1.49 Failed Genotyping 8 rs9692729 A 0.29 0.20 4.81E-05 1.56 Failed Genotyping 12 rs6538745 A 0.36 0.26 9.46E-07 1.66 Failed Genotyping 16 rs4887979 A 0.37 0.28 1.96E-06 1.63 Failed Genotyping SNP PCR primers with either high dimerization potential or high interference to other SNP PCR primers were considered as failed design as determined automatically with the Sequenom MassArray Assay Designer software. SNP with genotyping call rate < 95%, poor cluster plots or zero extension (no amplification of SNP allele) were considered as failed genotyping and are listed above. All primers used were ordered from and synthesized by Integrated DNA technologies (IDT) as according to Sequenom protocol requirements.

Supplementary Table 3. Summary statistics for remaining 4 candidate SNPs in 2 nd and 3 rd validation SNP Cases Controls Study/Stage rs273429 rs3087908 rs2632214 rs2069478 cases controls Trend P OR (95% CI) 294 2127 Validation 2 -Guangzhou 0.43 0.43 0.81 0.98 (0.83 1.16) 713 1733 Validation 3 -Beijing - - - - 294 2127 Validation 2 -Guangzhou 0.24 0.22 0.41 1.14 (0.93 1.40) 713 1733 Validation 3 -Beijing 0.24 0.24 0.63 1.04 (0.90 1.19) 294 2127 Validation 2 -Guangzhou 0.37 0.38 0.83 0.98 (0.82 1.18) 713 1733 Validation 3 -Beijing 0.36 0.34 0.13 1.11 (0.96 1.28) 294 2127 Validation 2 -Guangzhou 0.05 0.08 0.07 0.63 (0.43 0.92) 713 1733 Validation 3 -Beijing 0.06 0.06 0.66 1.05 (0.81 1.36) Statistical tests were performed using Cocharn-Armitage trend test. As can been seen, no evidence of association for these markers were observed and they were not further analyzed. rs273429 was not brought forward for the 3 rd validation in the Beijing Cohort.

Supplementary Table 4.Stratified analysis for rs6773854 Supplementary Table 4. Summary of statistic for rs6773854 in GWAS and all validation for DLCBL, FL and Non-B Cell NHL Subtype/stage Cases Controls cases controls Trend P OR (95% CI) Meta-P Meta-OR (95% CI) DLBCL + FL P heterogeneity (I 2 ) GWAS 199 1438 0.31 0.22 4.50 10-6 1.64 (1.29 2.08) - - - Validation 1 121 1632 0.27 0.18 5.00 10-4 1.71 (1.25 2.34) - - - (Guangzhou) Validation 2 267 2127 0.27 0.21 8.00 10-4 1.41 (1.15 1.73) - - - (Guangzhou) Validation 3 583 1733 0.21 0.17 0.003 1.34 (1.14 1.58) - - - (Beijing) DLBCL GWAS 148 1438 0.31 0.22 1.04 10-4 1.71 (1.31 2.24) - - - Validation 1 102 1632 0.29 0.18 1.77 10-4 1.87 (1.35 2.59) - - - (Guangzhou) Validation 2 235 2127 0.27 0.21 0.0013 1.42 (1.14 1.76) - - - (Guangzhou) Validation 3 503 1733 0.21 0.17 0.0009 1.34 (1.13 1.59) - - - (Beijing) FL GWAS 51 1438 0.31 0.22 0.09 1.48 (0.94 2.33) - - - Validation 1 19 1632 0.18 0.18 0.96 1.02 (0.45 2.32) - - - (Guangzhou) Validation 2 32 2127 0.26 0.21 0.28 1.35 (0.78 2.34) - - - (Guangzhou) Validation 3 80 1733 0.22 0.17 0.06 1.44 (0.99 2.10) - - - (Beijing) Non B-cell NHL GWAS 49 1438 0.26 0.22 0.24 1.33 (0.83 2.12) - - - Validation 1 71 1632 0.22 0.18 0.22 1.29 (0.85 1.97) - - - (Guangzhou) Validation 2 66 2127 0.27 0.21 0.09 1.41 (0.95 2.09) - - - (Guangzhou) Validation 3 276 1733 0.16 0.17 0.68 0.95 (0.75 1.21) - - - (Beijing) Combined a DLBCL + FL 1170 6930 - - - - 4.17 10-12 1.45 (1.30 1.61) 0.40 (0) DLBCL 988 6930 - - - - 1.14 10-11 1.47 (1.32 1.65) 0.21 (33) *2.14 10-8 FL 182 6930 - - - - 0.008 1.36 (1.08 1.77) 0.88 (0) Non B-cell 462 6930 - - - - 0.17 1.12 (0.94 1.33) 0.25 (25)

a Includes all samples from GWAS and Validations 1-3 * Meta analysis P value under the random effects model for DLBCL, results remains at genome-wide significance.

Supplementary Table 5. Look-up of previously reported DLBCL and FL susceptibility loci Subtype Chr SNP Closest Gene Minor Trend OR Study by allele cases controls P value FL 6 rs2647012 HLA Class II A 0.11 0.18 0.10 0.61 Smeby et al 1 FL 6 rs6457327 STG/PSORS1 A 0.37 0.33 0.37 1.21 Skibola et al 2 DLBCL 1 rs11161557 - T 0.14 0.13 0.54 1.12 Conde et al 3 DLBCL 1 rs1925036 - G 0.27 0.30 0.29 0.86 DLBCL 2 rs4663995 TRPM8 T 0.35 0.41 0.03 0.75 DLBCL 3 rs11129295 - C* 0.21 0.24 0.26 0.85 DLBCL 3 rs13060887 FGD5 T 0.23 0.27 0.23 0.84 DLBCL 3 rs1494837 - C* 0.42 0.39 0.31 1.14 DLBCL 3 rs17035210 # - - - - - - DLBCL 3 rs4683793 CLSTN2 G 0.13 0.18 0.03 0.68 DLBCL 4 rs2024160 Q9ULE4_HUMAN C 0.21 0.21 0.76 0.95 DLBCL 4 rs2286771 Q9ULE4_HUMAN G 0.11 0.11 0.88 1.03 DLBCL 6 rs4870090 C6orf98 A 0.17 0.15 0.32 1.17 FL 6 rs7755224 HLA Class II G 0.00 0.03 0.99 0.00 FL 6 rs10484561 HLA Class II G 0.00 0.02 0.11 0.00 DLBCL 8 rs11778623 - T 0.29 0.32 0.36 0.89 DLBCL 8 rs1481737 - A 0.42 0.49 0.02 0.76 DLBCL 8 rs2011620 NP_113654.3 A 0.04 0.05 0.43 0.79 DLBCL 8 rs7015105 - C 0.26 0.31 0.14 0.82 DLBCL 9 rs4740560 NFIB A* 0.38 0.38 0.95 1.01 DLBCL 10 rs1341678 - C 0.15 0.18 0.25 0.82 DLBCL 10 rs827271 - C 0.34 0.35 0.57 0.93 DLBCL 11 rs1938651 OR5B17 C 0.13 0.12 0.66 1.09 DLBCL 11 rs1938672 - T 0.12 0.12 0.75 1.06 DLBCL 11 rs750129 - A 0.37 0.36 0.79 1.04 DLBCL 12 rs12371846 GRIP1 T 0.11 0.08 0.09 1.40 DLBCL 12 rs2239194 SH2B3 T 0.30 0.32 0.48 0.91 DLBCL 12 rs6486990 - A 0.24 0.24 0.88 1.02 DLBCL 12 rs873908 GRIP1 C* 0.47 0.46 0.84 1.03 DLBCL 13 rs12019900 # - - - - - - DLBCL 14 rs11628857 SMOC1 A 0.00 0.00 1.00 0.00 DLBCL 14 rs1958442 - T 0.23 0.22 0.66 1.07 DLBCL 14 rs227418 SMOC1 T 0.05 0.05 0.96 1.01 DLBCL 14 rs4898844 SAMD4A G* 0.17 0.20 0.16 0.80 DLBCL 15 rs11637853 Q6ZSY1_HUMAN G 0.04 0.03 0.33 1.35 DLBCL 15 rs2280265 - C 0.07 0.09 0.32 0.79 DLBCL 15 rs4778857 # - - - - - - DLBCL 17 rs9889486 CCDC46 C* 0.24 0.19 0.04 1.34 DLBCL 18 rs1442366 - A 0.11 0.12 0.75 0.94 DLBCL 19 rs166988 - T* 0.10 0.14 0.10 0.72 DLBCL 20 rs871750 Q4G0G3_HUMAN T 0.11 0.15 0.11 0.74 DLBCL 21 rs2225409 - C 0.02 0.03 0.29 0.61 DLBCL 21 rs2225410 - A 0.02 0.03 0.31 0.62 DLBCL 22 rs2076118 # - - - - - - DLBCL 1 rs1800890 # IL 10 - - - - - Rothman et al 4 DLBCL 6 rs1800629 TNF A 0.11 0.10 0.36 1.19

; minor allele frequency, OR; per-allele odds ratio Total number of FL; 51, DLBCL; 148, Controls; 1438 # We were unable to impute these SNPs. * These SNPs have reversed minor allele as compared to study by Conde et al 3

Supplementary Table 6. NHL incidence rates across different parts of China Subpopulation Region Age-standardized (world) incidence (per 100,000; male/female) Reference Year obtained Northern China Beijing 3.4 / 2.5 CI5Vol8 a 1993-1997 Tianjin 2.7 / 1.6 CI5Vol8 a 1993-1997 Harbin city 3.1 / 1.9 CI5Vol9 b 1998-2002 Central China Shanghai 4.3 / 3.0 CI5Vol8 a 1993-1997 Shanghai 5.5 / 3.5 CI5Vol9 b 1998-2002 Jiashan, Zhejiang 3.5 / 1.5 CI5Vol8 a 1993-1997 Jiashan, Zhejiang 3.4 / 1.6 CI5Vol9 b 1998-2002 Wuhan 4.3 / 2.2 CI5Vol8 a 1993-1997 Southern China Guangzhou 6.7 / 4.2 CI5Vol9 b 2000-2002 Hong Kong 8.3 / 5.4 CI5Vol8 a 1993-1997 Hong Kong 8.1 / 5.3 CI5Vol9 b 1998-2002 CI5: Cancer incidence in 5 continent. Data were obtained from: a CI5Vol8 : Cancer incidence in 5 continent volume VIII, IARC Scientific Publication No 155, Edited by D.M. Parkin, S.L. Whelan, J. Ferlay, L. Teppo and D.B. Thomas b CI5Vol9 : Cancer incidence in 5 continent volume IX, IARC Scientific Publication No 160, Edited by M. P. Curado, B. Edwards, H. R. Shin, H. Storm, J. Ferlay, M. Heanue and P. Boyle.

Supplementary Figure 1. Flowchart describing our GWAS study approach

Supplementary Figure 2a. Principal components analysis (PCA) plot of GWAS stage study participants, including the additional 1,189 population controls. The Singapore genome variation project (SGVP) 5 reference panels were used.

Supplementary Figure 2b. Principal components analysis (PCA) plot of GWAS stage study participants without the Singapore genome variation project (SGVP) reference panel.

Supplementary Figure 3. Manhattan plot for the combined B-cell NHL analysis comprising 253 cases 1438 controls

Supplementary Figure 4. Quantile-quantile (QQ) plot

Supplementary Figure 5. Illumina beadchip genotyping cluster plot for rs6773854 Norm R 2.20 2.00 1.80 1.60 1.40 1.20 1 0.80 0.60 0.40 0.20 0-0.20 rs6773854 559 335 63 0 0.20 0.40 0.60 0.80 1 Norm Theta

References 1. Smedby, K.E. et al. GWAS of follicular lymphoma reveals allelic heterogeneity at 6p21.32 and suggests shared genetic susceptibility with diffuse large B-cell lymphoma. PLoS Genet 7, e1001378 (2011). 2. Skibola, C.F. et al. Genetic variants at 6p21.33 are associated with susceptibility to follicular lymphoma. Nat Genet 41, 873-5 (2009). 3. Conde, L. et al. Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32. Nat Genet 42, 661-4 (2010). 4. Rothman, N. et al. Genetic variation in TNF and IL10 and risk of non-hodgkin lymphoma: a report from the InterLymph Consortium. The Lancet Oncology 7, 27-38 (2006). 5. Teo, Y.Y. et. al. Singapore Genome Variation Project: a haplotype map of three Southeast Asian populations. Genome Res 11, 2154-62 (2009).