nature genetics: doi:10.1038/ng · 2014-10-29 · nature genetics: doi:10.1038/ng.3105...

Nature Genetics: doi:10.1038/ng.3105

Supplementary Figure 1

Schematic of the study design.



Quantile-quantile (Q-Q) plot of the association results in the stage 1 DLBCL GWAS (red) and after removing SNPs from the HLA region (green).



Manhattan plot showing the statistical significance of the association for all genotyped SNPs in the stage 1 DLBCL GWAS.

SNPs are plotted on the x axis according to their position on each chromosome against the significance of the association on the y axis (shown as –log10 P value). The dotted line denotes P = 5 × 10

–8 statistical significance.



Association results, recombination hotspots and LD plots for the region 5q31.3 with DLBCL.

Top, association results of GWAS data from the stage 1 DLBCL GWAS (gray diamonds) and combined data of stages 1–3 (red diamond) are shown with –log10 (P values) (left y axis). Overlaid are the likelihood ratio statistics (right y axis) to estimate putative recombination hotspots across the region on the basis of 5 unique sets of 100 randomly selected control samples. Bottom, LD heatmap based on r

2 values from combined control populations for all SNPs included in the GWAS.



Chromatin state dynamics of DLBCL-associated SNPs in nine human cell lines.

For details, see the Online Methods.



Plot of estimated admixture for individuals in the NHL GWAS (stage 1).

For details, see the Online Methods. Individuals with <80% European ancestry were excluded.


Supplementary Figure 7 Plot of top eigenvectors from DLBCL GWAS (stage 1) data based on principal-components analysis. For details, see the Online Methods.

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SUPPLEMENTARY INFORMATION

Genome-wide association study identifies multiple susceptibility loci for diffuse large B-cell lymphoma

SUPPLEMENTARY TABLES, page 2

SUPPLEMENTARY NOTE, page 25


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1. SUPPLEMENTARY TABLES

Supplementary Table 1. Description and study design of studies included in stages 1-3, diffuse large B-cell lymphoma (DLBCL) GWAS study

Study Name Study Abbreviation

No. Casesa

No. Controlsa

Design, location Source of cases Source of controls Study Reference

Stage 1 - DLBCL-GWAS Cohort Studies Alpha-Tocopherol, Beta-Carotene Lung Cancer Prevention Study

ATBC 60 240b Nested case-control, Finland

Identified through linkage to the Finnish Cancer Registry

Cohort participants without a diagnosis of cancer

[PMID: 8205268] The alpha-tocopherol, beta-carotene lung cancer prevention study: design, methods, participant characteristics, and compliance. The ATBC Cancer Prevention Study Group. Ann Epidemiol. 1994 Jan;4(1):1-10.

American Cancer Society Cancer Prevention Study-II Nutrition Cohort

CPS-II 218 220b Nested case-control, USA

Self-report through biannual questionnaires (starting in 1997). Verified by medical records or linkage to state cancer registry

Cohort participants alive at time of case diagnosis without cancer

[PMID:11900235] Calle EE. et al. The American Cancer Society Cancer Prevention Study II Nutrition Cohort: rationale, study design, and baseline characteristics. Cancer 2002;94:2490-501.

European Prospective Investigation into Cancer, Chronic Diseases, Nutrition and Lifestyles

EPIC 48 773 Nested case-control, multiple European countries

Cases identified through population cancer registries in seven of the participating countries (Denmark, Italy, The Netherlands, Norway, Spain, Sweden and the UK) and through a combination of methods including health insurance records, cancer and pathology registries, and by active follow-up through study subjects and their next-of-kin in three countries (France, Germany and Greece)

Cohort participants matched by age, sex and study center who were alive and cancer-free at the time of diagnosis of the corresponding case

[PMID:9126529]Riboli E. et al. The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J of Epidemiol 1997;26(1):S6-14. [PMID:12639222] Riboli E. et al. European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. Public Health Nutr 2002;5(6B):1113-24.

Health Professionals Follow-up Study

HPFS 12 86 Nested case-control, USA

Self-report through bi-annual questionnaires. Verified by medical records and pathology report

Cohort participants alive at time of case diagnosis without cancer, matched on date of birth, ethnicity, date and time of day of blood collection, and fasting status

[PMID: 1678444] Rimm E. et al. Prospective study of alcohol consumption and risk of coronary disease in men. Lancet 1991;338:464-8.


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No. Casesa

No. Controlsa


The Melbourne Collaborative Cohort Study

MCCS 75 246 Nested case-control, Australia

Incident cases ascertained through national cancer registries

Controls were unaffected cohort participants

[PMID: 12484128] Giles GG. et al. The Melbourne Collaborative Cohort Study. IARC Sci Publ 2002;156:69-70.

Nurses' Health Study NHS 28 90 Nested case-control, USA

Self-report through bi-annual questionnaires. Verified by medical records and pathology report

Cohort participants alive at time of case diagnosis without cancer, matched on date of birth, ethnicity, date and time of day of blood collection, and fasting status

[PMID: 15864280] Colditz GA. et al. The Nurses' Health Study: lifestyle and health among women. Nat Rev Cancer 2005;5:388-96. [PMID: 7658481] Hankinson SE. et al. Alcohol, height and adiposity in relation to estrogen and prolactin levels in postmenopausal women. J Natl Cancer Inst. J Natl Cancer Inst 1995;87:1297-302.

New York University Women's Health Study

NYU-WHS 10 56 Nested case-control, USA

Self-report through questionnaires every 2-4 years, confirmed by medical and pathology records; and linkages to tumor registries of NY, NJ and Florida and NDI

Cohort participants selected by incidence density sampling (alive and free of cancer at time of case diagnosis

[PMID: 7707406] Toniolo P. et al. A prospective study of endogenous estrogens and breast cancer in postmenopausal women. J Natl Cancer Inst 1995; 87:190-7. [PMID: 20373009] Gu Y. et al. Circulating cytokines and risk of B-cell non-Hodgkin lymphoma: a prospective study. Cancer Causes Control 2010; 21(8):1323-33.

Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

PLCO 162 3076b Nested case-control, USA

Self-report through annual questionnaires. Verified by medical records and pathology report

Previously scanned controls; controls were alive at time of case diagnosis without cancer diagnosis

[PMID: 20494998] Troy JD, et al. Associations between anthropometry, cigarette smoking, alcohol consumption, and non-Hodgkin lymphoma in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Am J Epidemiol 2010;171:1270-81. [PMID: 16054167] Hayes RB et al. Methods for etiologic and early marker investigations in the PLCO trial. Mutat Res 2005;592:147-54.


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No. Casesa

No. Controlsa


Women's Health Initiative WHI 257 395 Nested case-control, USA

Self-report through semi-annual clinic visits or annual contact. Verified through medical records

Cohort participants without a diagnosis of cancer

[PMID: 14575938] Anderson GL, et al. Implementation of the Women's Health Initiative study design. Ann Epidemiol. 2003 Oct;13(9 Suppl):S5-17.

Population-based case-control studies British Columbia Non-Hodgkin Lymphoma Study

BC 100 390 Population-based case-control study, Canada

First primary NHL diagnosis from Vancouver and Victoria metropolitan areas identified through the BC Cancer Registry (excluding HIV-infected and post-transplant cases)

Controls from the same areas, matched on area, age, and sex ascertained from the British Columbia Health Insurance files

[PMID:17722095] Spinelli JJ. et al. Organochlorines and risk of non-Hodgkin lymphoma. Int J Cancer 2007; 121(12):2767-75.

Epidemiology & Genetics Unit Lymphoma Case-Control study

ELCCS 237 461 Population-based case-control study, UK

Cases were patients aged between 18-69 residing in predefined geographic areas and newly diagnosed with NHL between 1998 and 2003. Diagnoses were pathologically confirmed and coded to the WHO Classification for Oncology

For each case, one age- and sex- matched control was randomly selected from population based General practice registers

[PMID: 15456990] Willett EV. et al. Tobacco and alcohol consumption and the risk of non-Hodgkin lymphoma. Cancer Causes Control 2004;15:771-80. [PMID: 19736055] Worrillow L. et al. Polymorphisms in the nucleotide excision repair gene ERCC2/XPD and risk of non-Hodgkin lymphoma. Cancer Epidemiol 2009;33(3-4):257-60. [PMID 20832384] Crouch S. et al. Illness patterns prior to diagnosis of lymphoma: analysis of UK medical records. Cancer Epidemiol 2001;35(2):145-50.

Multicenter Italian study on gene-environment interactions in lymphoma etiology: translational aspects

Italian GxE 15 54 Population-based case-control study, Italy

First primary NHL diagnosis identified in the Hematology Departments of the participating centers

Cohort participants alive at time of case diagnosis without cancer


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No. Casesa

No. Controlsa


National Cancer Institute-Surveillance, Epidemiology, and End Results Interdisciplinary Case-Control Study of Non-Hodgkin's Lymphoma

NCI-SEER 287 689 Population-based case-control study, USA

First primary NHL diagnosis identified through 4 SEER registries (excluding HIV-infected cases)

Controls from the same areas, matched on area, age, sex, and race ascertained though random digit dialing (<65 years of age) and CMMS files (≥65 years of age)

[PMID: 15342441] Chatterjee N. et al. Risk of non-Hodgkin's lymphoma and family history of lymphatic, hematology, and other cancers. CEBP 2004;13:1415-21. [PMID: 17018637] Wang SS. et al. Common genetic variants in proinflammatory and other immunoregulatory genes and risk for non-Hodgkin lymphoma. Cancer Res 2006;66(19):9771-80.

NSW non-Hodgkin lymphoma study

NSW 123 397 Population-based case-control study, Australia and New Zealand

Incident NHL diagnosis identified through NSW or ACT cancer registry (excluding HIV-infected cases and transplant recipients)

Controls randomly selected from electoral rolls, matched on age, sex and State of residence at diagnosis

[PMID: 15095310] Hughes AM, et al. Pigmentary characteristics, sun sensitivity and non-Hodgkin lymphoma. IJC 2004;110:429-34.

Scandinavian Lymphoma Etiology Study

SCALE 419 301 Population-based case-control study, Scandinavia

Patients with incident primary NHL diagnosed through rapid case-ascertainment network in Sweden and Denmark

Frequency matched (age in 10 year intervals, sex and country) population controls prospectively identified every 6 months in nationwide population registers (incidence density sampling)

[PMID: 15687363] Smedby KE. et al. Ultraviolet radiation exposure and risk of malignant lymphomas. Inst. J Natl Cancer Inst 2005;97(3)199-209.

Molecular Epidemiology of non-Hodgkin lymphoma

UCSF2 40 10 Population-based case-control study, USA

RCA/SEER Incident NHL diagnosis for patients diagnosed in hospitals in 6 San Francisco Bay Area Counties and who were residents of the Bay Area at the time of diagnosis

Controls ascertained through RDD were frequency matched to cases on age in 5-year groups, sex and county of residence; Random sampling of CMS lists for person residing in the same 6 Bay Area counties were used to supplement recruitment of controls aged 65+

[PMID: 20639881] Conde, et al. Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32. Nat Genet 2010; 42(8):661-4 [PMID: 22697504] Mikhak B. et al. Intake of vitamins d and a and calcium and risk of non-Hodgkin lymphoma: San Francisco Bay Area population-based case-control study. Nutr Cancer 2012;64(5):674-84.


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No. Casesa

No. Controlsa


Population-based case-control study in Connecticut women

Yale 136 504 Population-based case-control study, USA

First primary NHL diagnosis identified through the Rapid Case Shared Resources from all the hospitals in Connecticut

Population-based controls through random digit dialing for cases <65 years and Medicare files for ≥65 years

[PMID: 19822571] Zhang Y et al. Genetic variations in xenobiotic metabolic pathway genes, personal hair dye use and risk of non-Hodgkin lymphoma. Am J Epidemiol 2009;170(10):1222-30.

Clinic or hospital-based or mixed case-control studies Environmental and genetic risks factors study in adult lymphoma

ENGELA 69 278 Hospital-based case-control study, France

Recent diagnosis of a NHL as per the WHO classification (ICD-O-3) / Cases with AIDS or on immunosuppressant drugs were not eligible. Pathology reports for 100%, slides review for selected NHL

Hospitalized in the same hospitals as the cases, for any reason except cancer, an accident or a disease directly related to the subject’s occupation, smoking, or alcohol consumption. HIV negative

[PMID: 18781390] Monnereau A. et al. Cigarette smoking, alcohol drinking, and risk of lymphoid neoplasms: results of a French case-control study. Cancer Causes Control 2008;19(10):1147-60.

Epilymph case-control study in six European countries

EpiLymph 239 1172 Multicenter case-control study, hospital-based and population-based, Europe

First primary lymphoma diagnosis (according to the 2001 WHO classification of lymphoma

Controls from Germany and Italy were randomly selected by sampling from the general population, matched to cases on gender, 5-year age-group, and residence area. The rest of the centers used matched hospital controls, with eligibility criteria limited to diagnoses other than cancer, infectious diseases and immunodeficient diseases

[PMID:16557575] Besson H. et al. Tobacco smoking, alcohol drinking and non-Hodgkin's lymphoma: A European multicenter case-control study (Epilymph). Int J Cancer 2006;119:901-8.

Iowa-Mayo SPORE Molecular Epidemiology Resource

Iowa-Mayo SPORE

148 Clinic-based case registry, USA

Consecutive patients with newly diagnosed, histologically-confirmed non-Hodgkin lymphoma (excluding HIV-infected cases) who were residents of US

N/A [PMCID:PMC2953973] Drake MT. et al. Vitamin D insufficiency and prognosis in non-Hodgkin’s lymphoma. J Clin Oncol 2010;28:4191-8.


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No. Casesa

No. Controlsa


Mayo Clinic Case-Control Study of NHL and CLL

Mayo Case-Control

26 911 Clinic-based case-control study, USA

Consecutive patients with newly diagnosed, histologically-confirmed non-Hodgkin lymphoma (excluding HIV-infected cases) who were residents of Minnesota, Iowa or Wisconsin

Controls were selected from patients seen in the general medicine clinics at Mayo with a pre-scheduled general medical examination, frequency on age, sex, and geographic region

[PMCID:PMC3110384] Cerhan JR. et al. Design and validity of a clinic-based case-control study on the molecular epidemiology of lymphoma. Int J Mol Epidemiol Genet 2011;2(2):95-113.

Memorial-Sloan Kettering Lymphoproliferative disorders Study

MSKCC 194 9 Hospital-based case-study and NYCP controls, USA

Hospital clinic based ascertainment in a tertiary referral center

NYCP controls from same geographic area

PMID: 23349640] Joseph V et al. Susceptibility loci associated with specific and shared subtypes of lymphoid malignancies.. PLoS Genet 2013;9(1):e1003220..

Stage 2 - In silico GWAS Molecular Epidemiology of non-Hodgkin lymphoma

UCSF2 256 751 Population-based case-control study, USA

RCA/SEER Incident NHL diagnosis for patients diagnosed in hospitals in 6 San Francisco Bay Area Counties and who were residents of the Bay Area at the time of diagnosis

Controls ascertained through RDD were frequency matched to cases on age in 5-year groups, sex and county of residence; Random sampling of CMS lists for person residing in the same 6 Bay Area counties were used to supplement recruitment of controls aged 65+

[PMID: 20639881] Conde, et al. Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32. Nat Genet 2010; 42(8):661-4 [PMID: 22697504] Mikhak B. et al. Intake of vitamins d and a and calcium and risk of non-Hodgkin lymphoma: San Francisco Bay Area population-based case-control study. Nutr Cancer 2012;64(5):674-84.

Mayo Clinic Case-Control Study of NHL and CLL and Iowa-Mayo SPORE Molecular Epidemiology Resource

MAYO 402 184 Clinic-based case-control study and clinic-based registry, USA



[PMCID:PMC3110384] Cerhan JR. et al. Design and validity of a clinic-based case-control study on the molecular epidemiology of lymphoma. Int J Mol Epidemiol Genet 2011;2(2):95-113.

Treatment program of DLBCL patients from the Groupe d'Etude des Lymphomes de l'Adulte (GELA) consisting in

GELA

576 525 Cases from randomized clinical trial with

Patients recruited in the study that consented to DNA analysis

Controls were from EPIC

[PMID: 22118442] Récher C et al. Groupe d'Etude des Lymphomes de l'Adulte. Intensified chemotherapy with


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No. Casesa

No. Controlsa


LNH03-1B, 2B, 3B, 39B, 6B and 7B.

population-based controls from EPIC

ACVBP plus rituximab versus standard CHOP plus rituximab for the treatment of diffuse large B-cell lymphoma (LNH03-2B): an open-label randomised phase 3 trial. Lancet. 2011 Nov 26;378(9806):1858-67. [PMID: 23578722] Delarue R, et al. A. Dose-dense rituximab-CHOP compared with standard rituximab-CHOP in elderly patients with diffuse large B-cell lymphoma (the LNH03-6B study): a randomised phase 3 trial. Lancet Oncol. 2013 May;14(6):525-33 [PMID: 21482186] Peyrade F, et al. Attenuated immunochemotherapy regimen (R-miniCHOP) in elderly patients older than 80 years with diffuse large B-cell lymphoma: a multicentre, single-arm, phase 2 trial. Lancet Oncol. 2011 May;12(5):460-8. [PMID: 21546499] Fitoussi O, et al. C. Survival impact of rituximab combined with ACVBP and upfront consolidation autotransplantation in high-risk diffuse large B-cell lymphoma for GELA. Haematologica. 2011 Aug;96(8):1136-43 [PMID: 23235801] Ketterer N, et al.. Phase III study of ACVBP versus ACVBP plus rituximab for patients with localized low-risk diffuse large B-cell lymphoma (LNH03-1B). Ann Oncol. 2013 Apr;24(4):1032-7.


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No. Casesa

No. Controlsa


Stage 3 – TaqMan Replication Iowa-Mayo SPORE Molecular Epidemiology Resource

Iowa-Mayo SPORE

139 0c Clinic-based case registry, USA

Consecutive patients with newly diagnosed, histologically-confirmed non-Hodgkin lymphoma (excluding HIV-infected cases) who were residents of US

N/A [PMID: 20713849] Drake MT. et al. Vitamin D insufficiency and prognosis in non-Hodgkin’s lymphoma. J Clin Oncol 2010;28:4191-8.

Mayo Clinic Case-Control Study of NHL

Mayo Case-Control

181 400 Clinic-based case-control study, USA



[PMID: 21686124] Cerhan JR. et al. Design and validity of a clinic-based case-control study on the molecular epidemiology of lymphoma. Int J Mol Epidemiol Genet 2011;2(2):95-113.

MD Anderson lymphoma case-control study

MD Anderson

374 374 Case-control, USA

MD Anderson Cancer Center Kelsey Seybold Clinics

Memorial-Sloan Kettering Lymphoproliferative disorders Study

MSKCC 497 373 Hospital-based case-study and NYCP controls, USA

Hospital clinic based ascertainment in a tertiary referral center

NYCP controls from same geographic area

[PMID: 23349640] Joseph V. et al. Susceptibility loci associated with specific and shared subtypes of lymphoid malignancies. PLoS Genet.2013;9(1):e1003220.

NCI Replication Study NCI Rep 202 3431 Mixed study of population and hospital-based cases and controls

DLBCL cases from the stage 1 studies that did not have sufficient DNA for scanning or failed in scanning due to low completion

Controls from the stage 1 studies that were not scanned or failed scanning due to low completion

See stage 1 studies above.

aNumber of DLBCL cases and controls with DNA available that qualified for scanning (stage 1 or 2) or for taqman replication (stage 3). bControls scanned previously on the Illumina Omni2.5 cNo controls were ascertained for this study. For stage 3, the Iowa-Mayo SPORE and the Mayo Case-Control studies were considered to be a single study


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Study Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Cases Controls Total

ATBC 50 7 240 43 240 283CPS-II 218 22 1 6 1 220 188 220 408EPIC 46 275 9 1 46 265 311HPFS 12 86 1 12 85 97MCCS 75 76 3 1 1 71 75 146NHS 28 90 2 28 88 116NYU-WHS 10 56 2 3 8 53 61PLCO 162 7 2 3076 153 3076 3229WHI 257 250 13 19 3 1 3 240 228 468Subtotal 858 833 54 34 1 1 11 0 3 4 0 3536 789 4330 5119Population-based case-control studies

BCCA 100 110 6 1 2 92 109 201ELCCS 236 251 7 5 1 229 245 474Italian-GxE 19 54 2 8 1 1 16 45 61NCI-SEER 280 298 29 23 2 3 251 270 521NSW 118 157 2 2 1 1 115 154 269SCALE 419 299 12 6 2 2 405 291 696UCSF2 40 10 2 38 10 48YALE 132 149 4 3 1 1 126 146 272Subtotal 1344 1328 64 48 2 5 1 0 5 5 0 0 1272 1270 2542Clinic or hospital-based or mixed case-control studiesENGELA 69 77 13 14 56 63 119Epilymph 239 250 38 35 2 1 1 3 198 211 409Iowa-Mayo SPORE 148 1 1 146 146MAYO Case-Control 26 357 1 12 1 1 25 343 368MSKCC 194 9 5 5 14 175 4 179Subtotal 676 693 58 66 2 0 0 2 16 4 0 0 600 621 1221Grand total 2878 2854 176 148 5 6 12 2 24 13 0 3536 2661 6221 8882

Cohort studies

Subjects from previous scan

Final subjects included in the analysis

Exclusions

Genotyped Subjects High missing rate Gender discordance Unexpected duplicates Non CEU

Supplementary Table 2. Stage 1 DLBCL case and control subjects genotyped, quality control exclusions, and subjects included in the analysis


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Supplementary Table 3. Characteristics of the DLBCL cases and controls included in the final analysis for stages 1-3 No. of subjects % Male Mean age (SD) Study Cases Controls Cases Controls Cases Controls Stage 1: DLBCL GWAS ATBC 43 240 100.0% 100.0% 72.56(5.88) 68.35(7.67) BCCA 92 109 70.7% 56.0% 58.98(14.05) 60.70(12.66) CPSII 188 220 52.7% 49.5% 72.65(6.74) 68.41(6.28) EPIC 46 265 50.0% 45.3% 60.17(8.01) 62.65(8.42) Engela 56 63 67.9% 65.1% 53.14(11.06) 55.25(11.34) Epilymph 198 211 54.5% 54.0% 56.64(16.13) 59.31(12.96) HPFS 12 85 100.0% 100.0% 72.08(7.69) 70.56(8.43) IOWASPORE 131 0 60.3% NA 58.37(17.37) NA ITALIANGE 16 45 56.3% 62.2% 53.00(18.17) 55.38(11.68) MAYOCC 25 343 64.0% 61.2% 60.52(15.41) 60.90(13.35) MAYOSPORE 15 0 53.3% NA 54.40(13.42) NA MCCS 71 75 47.9% 52.0% 67.21(11.62) 70.96(7.85) MSKCC 175 4 52.6% 0.0% 56.47(15.04) 41.25(9.36) NCI-SEER 251 270 55.0% 54.1% 55.65(12.79) 56.57(11.94) NHS 28 88 0.0% 0.0% 65.04(6.57) 64.01(6.91) NSW 115 154 57.4% 60.4% 59.03(11.89) 57.19(11.13) NYU-WHS 8 53 0.0% 0.0% 69.88(6.60) 76.17(9.20) PLCO 153 3076 58.2% 95.7% 70.58(6.73) 69.54(6.19) SCALE (DENMARK) 180 201 57.8% 54.7% 56.25(12.38) 61.07(11.48) SCALE (SWEDEN) 225 90 61.3% 64.4% 57.08(12.86) 57.64(13.15) UCB 38 10 52.6% 60.0% 55.50(18.29) 43.40(14.83) UK 229 245 54.6% 50.6% 52.97(8.50) 53.19(8.19) WHI 240 228 0.0% 0.0% 72.85(7.12) 77.66(6.58) YALE 126 146 0.0% 0.0% 60.18(15.04) 61.68(13.47) Total - Stage 1 2661 6221 49.1% 72.8% 60.77(14.01) 66.04(10.44) Stage 2: In silico GWAS GELA/EPIC DLBCL 549 525 57.0% 45.0% 58.65(16.71) 58.49(7.22) MAYO-DLBCL 393 172 52.7% 38.4% 61.72(14.39) 51.08(13.72) UCSF2-DLBCL 254 748 55.9% 57.6% 62.37(13.94) 61.44(12.99) Total - Stage 2 1196 1445 55.4% 50.7% 60.45(15.50) 59.13(12.38) Stage 3: Additional Replication Studies MAYOCC+IOWASPORE 299 379 60.2% 57.0% 61.57(16.07) 62.26(11.99) MD Anderson 374 374 57.8% 57.5% 58.40(14.53) 60.19(12.13) MSKCC 484 373 51.4% 18.2% 56.07(16.34) 57.69(11.80) NCI Replication 202 3431 49.5% 44.3% 59.36(14.33) 60.67(14.37) Total - Stage 3 1359 4557 54.8% 44.2% 58.41(15.65) 60.52(13.85)


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No. of cases in file

No. of controls in

Minimum sample call Exclusions

No.cases after

No. controls after MAF

SNP Call rate* P for HWE

NCI GWASNCI GWAS 2878 6390a >=93% 1) Abnormal

heterozygosity; 2) gender discordance;

3) unexpected duplicates; 4) Non

CEU

2661 6221 Illumina OmniExpress

BeadStudio (GenCall)

>= 0.01 >=0.95 >=1e-6 611844 IMPUTE2 21554489b

MAYO 398 172 >=95% Non CEU 393 172 Illumina HumanHap

660W


>= 0.01 >=0.95 >=1e-6 523949 IMPUTE2 11880085

UCSF2 256 751 >=95% 1) Abnormal heterozygosity; 2) PCA

outlier

254 748 Illumina HumanCNV370-

Duo


>= 0.01 >=0.95 >=1e-6 290523 IMPUTE2 14514047

GELA 754 NA >=95% 1) Non CEU 2) NHL NOS subtype

549 Illumina HumanHap

610K


>= 0.01 >=0.95 >=1e-6 513264 IMPUTE2 14149132

EPIC NA 928 >=95% 1) Genetically not matched with cases based on combined

PCA with GELA

525 Illumina HumanHap

610K and 660W


>= 0.01 >=0.95 >=1e-6 513264 IMPUTE2 14149132

a. A total of 3536 control subjects from ATBC, CPSII and PLCO cohorts that previously genotyped on Illumina Omni 2.5M chips were pooled into the NCI set

b. Use both MAF>0.001 and INFO>0.3 for post imputation SNP filtering. NCI set resulted in more SNPs being retained for analysis

In silico GWAS

Inclusion/exclusion criteria

Study

Sample QC Genotyping and Imputation

Platform

Genotype calling

algorithm

Supplementary Table 4. Information on genotyping methods, quality control, imputation, and analysis for primary and in silico GWAS included in stage 1 or stage 2

Inclusion criteria for Imputation SNPs that met QC criteria

Imputation Software

SNPs in meta-analysis


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Supplementary Table 5. Results of meta-analysis of Stages 1 and 2 for SNPs having a P<5.0x10-8, sorted by chromosome and position.

SNP CHR Position Study

Imputed or

geno-typed

Information Content

Controls (N)

Cases (N)

Ref Allele

Effect Allele

Effect Allele MAF,

Controls

Effect Allele MAF, Cases OR (95% CI) P

P hetero-geneity I2

rs9831894 chr3 121800487 NCI GWAS i 0.9863 6221 2660 A C 0.404 0.353 0.81 (0.76-0.87) 3.08E-09 GELA GWAS g 1.0000 525 549 A C 0.386 0.372 0.94 (0.78-1.12) 0.47322 MAYO GWAS g 1.0000 172 393 A C 0.392 0.354 0.82 (0.62-1.08) 0.1511 UCSF2 GWAS g 1.0000 748 254 A C 0.382 0.368 0.94 (0.77-1.16) 0.59283 Combined 7666 3856 0.83 (0.7852-0.8863) 4.52E-09 0.299 18.30 rs2681416 chr3 121817613 NCI GWAS i 0.9921 6220 2661 G A 0.311 0.354 1.26 (1.17-1.35) 7.37E-10 GELA GWAS i 0.9922 524 549 G A 0.328 0.334 1.05 (0.87-1.26) 0.6017 MAYO GWAS i 0.9988 172 392 G A 0.348 0.364 1.09 (0.83-1.43) 0.53908 UCSF2 GWAS i 0.9941 747 253 G A 0.314 0.311 0.99 (0.80-1.23) 0.91864 Combined 7663 3855 1.20 (1.1243-1.2747) 1.92E-08 0.071 57.30 rs12333255 chr6 479361 NCI GWAS i 0.9319 6220 2661 G A 0.011 0.022 2.41 (1.81-3.21) 1.92E-09 GELA GWAS i 0.9685 525 548 G A 0.012 0.022 1.97 (1.00-3.90) 0.051303 MAYO GWAS i 0.9895 171 393 G A 0.018 0.025 1.13 (0.42-3.03) 0.80084 Combined 6916 3602 2.23 (1.7243-2.8739) 8.22E-10 0.330 9.86 rs76106586 chr6 483593 NCI GWAS i 0.9720 6220 2660 A G 0.019 0.038 2.26 (1.82-2.81) 1.39E-13 GELA GWAS i 0.9655 525 549 A G 0.018 0.038 2.42 (1.40-4.18) 0.0016 MAYO GWAS i 0.9829 172 393 A G 0.026 0.038 1.37 (0.63-3.00) 0.42956 UCSF2 GWAS i 0.9163 747 253 A G 0.013 0.045 5.45 (2.61-11.37) 6.33E-06 Combined 7664 3855 2.35 (1.9432-2.8326) 7.34E-19 0.073 56.94 rs116446171 chr6 484453 NCI GWAS i 0.9844 6220 2661 C G 0.019 0.037 2.26 (1.82-2.81) 1.48E-13 GELA GWAS i 0.9730 524 548 C G 0.017 0.038 2.51 (1.45-4.34) 0.0009637 MAYO GWAS i 0.9919 171 393 C G 0.026 0.037 1.34 (0.61-2.94) 0.46343 UCSF2 GWAS i 0.9376 748 253 C G 0.012 0.045 5.71 (2.73-11.97) 3.88E-06 Combined 7663 3855 2.36 (1.9562-2.8533) 4.33E-19 0.053 60.86 rs116613194 chr6 29832481 NCI GWAS i 0.9638 6221 2661 T C 0.252 0.217 0.80 (0.74-0.87) 1.16E-07 GELA GWAS i 0.9550 525 549 T C 0.281 0.250 0.80 (0.65-0.98) 0.027812 MAYO GWAS i 0.9565 171 392 T C 0.208 0.213 1.06 (0.76-1.49) 0.72812 UCSF2 GWAS i 0.9681 747 254 T C 0.257 0.227 0.84 (0.66-1.06) 0.14999 Combined 7664 3856 0.81 (0.7590-0.8740) 1.19E-08 0.450 0.00 rs114069626 chr6 29832482 NCI GWAS i 0.9701 6220 2660 C T 0.254 0.219 0.80 (0.74-0.87) 1.22E-07 GELA GWAS i 0.9591 524 549 C T 0.282 0.251 0.80 (0.65-0.98) 0.029285 MAYO GWAS i 0.9605 172 392 C T 0.209 0.214 1.07 (0.76-1.49) 0.70182 UCSF2 GWAS i 0.9717 747 253 C T 0.258 0.228 0.84 (0.66-1.06) 0.1473 Combined 7663 3854 0.82 (0.7605-0.8752) 1.36E-08 0.435 0.00


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rs114320989 chr6 29832526 NCI GWAS i 0.9943 6220 2660 T C 0.263 0.227 0.81 (0.75-0.87) 1.21E-07 GELA GWAS i 0.9934 524 548 T C 0.306 0.269 0.79 (0.65-0.96) 0.016739 MAYO GWAS i 0.9978 172 392 T C 0.224 0.224 1.05 (0.76-1.44) 0.76644 UCSF2 GWAS i 0.9972 747 254 T C 0.272 0.242 0.85 (0.67-1.07) 0.1599 Combined 7663 3854 0.82 (0.7641-0.8761) 8.75E-09 0.438 0.00 rs115127508 chr6 29832600 NCI GWAS i 0.9977 6221 2661 T C 0.264 0.228 0.81 (0.75-0.88) 1.46E-07 GELA GWAS i 0.9957 524 548 T C 0.306 0.269 0.79 (0.65-0.96) 0.017736 MAYO GWAS i 0.9987 171 393 T C 0.224 0.224 1.05 (0.76-1.44) 0.76787 UCSF2 GWAS i 0.9975 747 253 T C 0.272 0.242 0.85 (0.67-1.07) 0.15659 Combined 7663 3855 0.82 (0.7654-0.8773) 1.06E-08 0.449 0.00 rs2523607 chr6 31322790 NCI GWAS i 0.9913 6221 2661 T A 0.120 0.155 1.45 (1.29-1.64) 7.10E-10 GELA GWAS i 0.9888 525 548 T A 0.119 0.128 1.09 (0.85-1.41) 0.49528 MAYO GWAS i 0.9896 172 393 T A 0.139 0.140 0.98 (0.68-1.42) 0.9306 UCSF2 GWAS i 0.9874 747 254 T A 0.122 0.153 1.32 (0.98-1.78) 0.065779 Combined 7665 3856 1.34 (1.2180-1.4811) 3.35E-09 0.074 56.74 rs2596495 chr6 31323416 NCI GWAS i 0.9914 6221 2661 G C 0.120 0.155 1.45 (1.29-1.64) 7.10E-10 GELA GWAS i 0.9908 524 549 G C 0.119 0.127 1.09 (0.85-1.41) 0.5023 MAYO GWAS i 0.9898 171 392 G C 0.139 0.140 0.98 (0.68-1.42) 0.93034 UCSF2 GWAS i 0.9878 747 254 G C 0.122 0.153 1.32 (0.98-1.78) 0.064406 Combined 7663 3856 1.34 (1.2180-1.4811) 3.36E-09 0.073 56.99 rs140786044 chr6 31323506 NCI GWAS i 0.9914 6221 2660 C T 0.120 0.155 1.45 (1.29-1.64) 7.08E-10 GELA GWAS i 0.9907 524 548 C T 0.119 0.127 1.09 (0.85-1.41) 0.5022 MAYO GWAS i 0.9898 171 392 C T 0.139 0.140 0.98 (0.68-1.42) 0.93044 UCSF2 GWAS i 0.9879 747 254 C T 0.122 0.153 1.32 (0.98-1.78) 0.064203 Combined 7663 3854 1.34 (1.2180-1.4811) 3.33E-09 0.073 56.98 rs58467928 chr8 129074450 NCI GWAS i 0.9934 6221 2661 G A 0.368 0.403 1.15 (1.08-1.24) 5.94E-05 GELA GWAS i 0.9915 524 549 G A 0.368 0.441 1.28 (1.07-1.52) 0.0058667 MAYO GWAS i 0.9945 171 393 G A 0.328 0.409 1.39 (1.05-1.85) 0.023078 UCSF2 GWAS i 0.9763 747 253 G A 0.366 0.413 1.21 (0.99-1.48) 0.064587 Combined 7663 3856 1.18 (1.1136-1.2564) 4.88E-08 0.467 0.00 rs13254990 chr8 129076451 NCI GWAS i 0.9769 6220 2661 C T 0.315 0.354 1.20 (1.11-1.29) 1.22E-06 GELA GWAS i 0.9780 524 548 C T 0.324 0.387 1.25 (1.04-1.51) 0.016879 MAYO GWAS i 0.9775 171 392 C T 0.277 0.373 1.50 (1.12-2.00) 0.0057134 UCSF2 GWAS i 0.9408 747 254 C T 0.313 0.364 1.26 (1.01-1.56) 0.037198 Combined 7662 3855 1.22 (1.1477-1.3023) 4.53E-10 0.504 0.00 rs13255292 chr8 129076573 NCI GWAS g 1.0000 6221 2661 C T 0.321 0.362 1.19 (1.11-1.28) 1.25E-06 GELA GWAS g 1.0000 525 549 C T 0.330 0.393 1.26 (1.05-1.51) 0.012717 MAYO GWAS g 1.0000 172 393 C T 0.294 0.380 1.44 (1.08-1.91) 0.011654


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UCSF2 GWAS i 0.9453 747 253 C T 0.321 0.374 1.27 (1.03-1.58) 0.027982 Combined 7665 3856 1.22 (1.1452-1.2963) 4.19E-10 0.589 0.00 rs2142199 chr8 129266826 NCI GWAS i 0.9990 6221 2660 T C 0.523 0.477 0.84 (0.78-0.90) 2.76E-07 GELA GWAS i 0.9973 525 549 T C 0.504 0.458 0.85 (0.72-1.00) 0.056394 MAYO GWAS i 0.9991 172 393 T C 0.540 0.497 0.86 (0.65-1.13) 0.27884 UCSF2 GWAS i 0.9967 748 253 T C 0.519 0.469 0.82 (0.67-1.00) 0.047288 Combined 7666 3855 0.84 (0.7906-0.8887) 3.32E-09 0.990 0.00 rs4733601 chr8 129269466 NCI GWAS g 1.0000 6221 2661 A G 0.523 0.478 0.84 (0.79-0.90) 4.22E-07 GELA GWAS g 1.0000 525 549 A G 0.504 0.460 0.85 (0.72-1.01) 0.069269 MAYO GWAS g 1.0000 172 393 A G 0.541 0.498 0.86 (0.65-1.13) 0.27336 UCSF2 GWAS g 1.0000 748 254 A G 0.518 0.469 0.82 (0.67-1.00) 0.051399 Combined 7666 3857 0.84 (0.7933-0.8915) 6.03E-09 0.990 0.00 rs1120501 chr8 129274183 NCI GWAS i 0.9915 6220 2660 A T 0.527 0.482 0.84 (0.78-0.90) 3.13E-07 GELA GWAS i 0.9929 524 548 A T 0.506 0.461 0.85 (0.72-1.01) 0.062911 MAYO GWAS i 0.9942 171 392 A T 0.543 0.500 0.85 (0.65-1.12) 0.25116 UCSF2 GWAS i 0.9920 747 253 A T 0.522 0.471 0.81 (0.67-1.00) 0.044749 Combined 7662 3853 0.84 (0.7903-0.8887) 3.55E-09 0.989 0.00 rs74351635 chr19 48800330 NCI GWAS i 0.8789 6220 2660 C T 0.030 0.013 0.52 (0.42-0.66) 2.20E-08 GELA GWAS i 0.9715 525 549 C T 0.017 0.013 0.73 (0.36-1.50) 0.39311

UCSF2 GWAS i 0.6830 747 253 C T 0.015 0.011 0.69 (0.24-1.97) 0.48641 Combined 7492 3462 0.55 (0.4420-0.6742) 1.91E-08 0.621 0.00


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Supplementary Table 6 (Results of meta-analysis of Stages 1 and 2 for SNPs having a P<5.0x10-7, sorted by chromosome and position.) – in excel file


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Supplementary Table 7. Results of meta-analysis of Stages 1-3 for the 9 SNPs selected for Stage 3 replication.

SNP CHR Position Study

Imputed or geno-

typed

Information

Content Controls

(N) Cases

(N) Ref

Allele Effect Allele

Effect Allele MAF,

Controls

Effect Allele MAF, Cases OR (95% CI) P

P hetero-geneity I2

rs79480871 chr2 24694472 NCI GWAS i 0.912 6220 2660 C T 0.062 0.076 1.35 (1.17-1.55) 3.51E-05 GELA GWAS i 0.949 524 548 C T 0.043 0.083 2.07 (1.43-3.00) 0.00011 MAYO GWAS i 0.956 172 393 C T 0.068 0.072 0.95 (0.55-1.63) 0.85 UCSF2 GWAS i 0.929 747 254 C T 0.064 0.087 1.46 (0.97-2.19) 0.068 Stage 3 (Taqman) g 1.000 4524 1344 C T 0.063 0.076 1.19 (0.98-1.46) 0.084 Combined 12187 5199 1.34 (1.21-1.49) 4.23E-08 0.15 34.6

rs6773363 chr3 27793632 NCI GWAS i 0.975 6220 2660 T C 0.453 0.488 1.16 (1.08-1.24) 2.34E-05 GELA GWAS i 0.976 525 548 T C 0.449 0.448 0.99 (0.83-1.19) 0.92 MAYO GWAS i 0.981 171 393 T C 0.466 0.512 1.22 (0.94-1.59) 0.13 UCSF2 GWAS i 0.937 747 253 T C 0.425 0.521 1.48 (1.21-1.82) 0.00016 Stage 3 (Taqman) g 1.000 4466 1290 A G 0.484 0.515 0.98 (0.88-1.09) 0.72 Combined 12129 5144 1.12 (1.06-1.18) 1.89E-05 0.00 88.5

rs2681416 chr3 121817613 NCI GWAS GWAS i 0.992 6220 2661 G A 0.311 0.354 1.26 (1.17-1.35) 7.37E-10 GELA GWAS i 0.992 524 549 G A 0.328 0.334 1.05 (0.87-1.26) 0.60 MAYO GWAS i 0.999 172 392 G A 0.348 0.364 1.09 (0.83-1.43) 0.54 UCSF2 GWAS i 0.994 747 253 G A 0.314 0.311 0.99 (0.80-1.23) 0.92 Stage 3 (Taqman) g 1.000 4488 1320 G A 0.315 0.339 1.06 (0.95-1.18) 0.32 Combined 12151 5175 1.16 (1.10-1.23) 8.17E-08 0.01 61.1

rs79464052 chr5 141035174 NCI GWAS GWAS i 0.986 6220 2660 G C 0.056 0.076 1.41 (1.23-1.62) 1.18E-06 GELA GWAS i 0.987 525 548 G C 0.051 0.071 1.34 (0.93-1.94) 0.12 MAYO GWAS i 0.980 171 393 G C 0.040 0.057 1.19 (0.61-2.30) 0.61 UCSF2 GWAS i 0.978 748 253 G C 0.063 0.066 1.05 (0.70-1.59) 0.80 Stage 3 (Taqman) g 1.000 4483 1334 C G 0.061 0.078 1.29 (1.04-1.59) 0.022 Combined 12147 5188 1.34 (1.21-1.49) 5.57E-08 0.37 7.8

rs116446171 chr6 484453 NCI GWAS i 0.984 6220 2661 C G 0.019 0.037 2.26 (1.82-2.81) 1.48E-13 GELA GWAS i 0.973 524 548 C G 0.017 0.038 2.51 (1.45-4.34) 0.0010 MAYO GWAS i 0.992 171 393 C G 0.026 0.037 1.34 (0.61-2.94) 0.46 UCSF2 GWAS i 0.938 748 253 C G 0.012 0.045 5.71 (2.73-11.97) 3.88E-06 Stage 3 (Taqman) g 1.000 4460 1351 C G 0.019 0.031 1.78 (1.29-2.46) 0.00040 Combined 12123 5206 2.20 (1.87-2.59) 2.33E-21 0.17 32.8


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rs2523607 chr6 31322790 NCI GWAS i 0.991 6221 2661 T A 0.120 0.155 1.45 (1.29-1.64) 7.10E-10 GELA GWAS i 0.989 525 548 T A 0.119 0.128 1.09 (0.85-1.41) 0.50 MAYO GWAS i 0.990 172 393 T A 0.139 0.140 0.98 (0.68-1.42) 0.93 UCSF2 GWAS i 0.987 747 254 T A 0.122 0.153 1.32 (0.98-1.78) 0.066 Stage 3 (Taqman) g 1.000 1102 1114 T A 0.109 0.123 1.25 (1.04-1.51) 0.019 Combined 8767 4970 1.32 (1.21-1.44) 2.40E-10 0.26 21.6

rs45483501 chr6 41622097 NCI GWAS i 0.787 6220 2660 C G 0.125 0.105 0.78 (0.69-0.88) 3.53E-05 GELA GWAS i 0.763 524 548 C G 0.134 0.129 0.87 (0.64-1.17) 0.35 MAYO GWAS i 0.766 171 392 C G 0.158 0.111 0.55 (0.35-0.87) 0.010 UCSF2 GWAS i 0.722 747 253 C G 0.128 0.112 0.82 (0.58-1.16) 0.27 Stage 3 (Taqman) g 1.000 4467 1346 C G 0.127 0.126 0.94 (0.80-1.10) 0.43 Combined 12129 5199 0.82 (0.75-0.90) 8.14E-06 0.38 6.6

rs13255292 chr8 129076573 NCI GWAS g 1.000 6221 2661 C T 0.321 0.362 1.19 (1.11-1.28) 1.25E-06 GELA GWAS g 1.000 525 549 C T 0.330 0.393 1.26 (1.05-1.51) 0.013 MAYO GWAS g 1.000 172 393 C T 0.294 0.380 1.44 (1.08-1.91) 0.012 UCSF2 GWAS i 0.945 747 253 C T 0.321 0.374 1.27 (1.03-1.58) 0.028 Stage 3 (Taqman) g 1.000 4498 1322 C T 0.330 0.361 1.22 (1.09-1.36) 0.00058 Combined 12163 5178 1.22 (1.15-1.29) 9.98E-13 0.37 8.3

rs4733601 chr8 129269466 NCI GWAS g 1.000 6221 2661 A G 0.523 0.478 0.84 (0.79-0.90) 4.22E-07 GELA GWAS g 1.000 525 549 A G 0.504 0.460 0.85 (0.72-1.01) 0.069 MAYO GWAS g 1.000 172 393 A G 0.541 0.498 0.86 (0.65-1.13) 0.27 UCSF2 GWAS g 1.000 748 254 A G 0.518 0.469 0.82 (0.67-1.00) 0.051 Stage 3 (Taqman) g 1.000 4523 1337 A G 0.513 0.455 0.84 (0.76-0.94) 0.0016 Combined 12189 5194 0.84 (0.80-0.89) 3.63E-11 0.09 43.9


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Supplementary Table 8. Association of suggestive (P<5x10-7) SNPs wth risk of diffuse large B-cell lymphoma (DLBCL), stages 1-3.

LocationNearest gene(s) SNP Positiona

Risk alleleb

Other allele RAFc Stage

No. Cases/ No. controls OR (95% CI) P Phet I2

5q31.3 ARAP3 rs79464052 141035174 C G 0.076 Stage 1 2,660/6,220 1.41 (1.23-1.62) 1.18x10-6

0.056 Stage 2 1,194/1,444 1.20 (0.93-1.55) 0.150.061 Stage 3 1,334/4,483 1.29 (1.04-1.59) 0.022

Combined 5,188/12,147 1.34 (1.21-1.49) 5.57x10-8 0.37 7.753q13.33 CD86 rs2681416 121,817,613 A G 0.311 Stage 1 2,611/6,220 1.26 (1.17-1.35) 7.37X10-10

0.330 Stage 2 1,194/1,443 1.04 (0.92-1.18) 0.570.315 Stage 3 1,320/4,488 1.06 (0.95-1.18) 0.32

Combined 5,175/12,151 1.16 (1.10-1.23) 8.17x10-8 0.01 61.09aPosition according to human reference NCBI37/hg19; bAllele associated w ith an increased risk of DLBCL; cRisk allele frequency in controls; dNot genotyped in NCI Replication study.


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AA/Allele StudyEffect Allele1

Other Allele1 EAF2

Information3 OR P

P heterogen

eityHLA_B_08:01 NCI GWAS P A 0.119 1.029 1.36 (1.22 - 1.52) 2.13E-08

GELA GWAS P A 0.110 1.084 1.14 (0.88 - 1.50) 0.3251MAYO GWAS P A 0.133 1.105 0.95 (0.65 - 1.37) 0.7692UCSF2 GWAS P A 0.114 1.038 1.28 (0.95 - 1.73) 0.1056Combined 1.30 (1.18 - 1.42) 3.16E-08 2.16E-01

Supplementary Table 9. Results of a meta-analysis of Stage 1 and Stage 2 for HLA associations (P <5 x10-8) based on imputation using SNP2HLA.

(95% CI)

1P= presence of allele, A=absence of allele2EAF=effect allele frequency3Information is the imuptaiton quality score (r2) from Beagle


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SNPGene

transcriptEffect allele

Other allele

Beta for NHL SNPa

P for NHL SNPa

Pconditioned on peak SNPb

Peak SNP for

transcriptcBeta for

Peak SNPdP for Peak

SNPdPconditioned on NHL SNPe

rs116446171 HIST1H3F C G -0.8201 5.45E-06 0.75 rs76106586 -0.8279 4.38E-06 0.50rs2523607 HCG27 T A -0.5591 1.40E-05 0.19 rs116794933 -0.6146 5.86E-14 1.71E-13*All novel SNPs were evaluated.aBeta and p-value for the association between the NHL SNP and gene transcript.bp-value for the association between the NHL SNP and gene transcript after adjustment for the peak SNPcPeak SNP is the most significant SNP associated with the gene transcriptdBeta and p-value for the association between the peak SNP and the gene transcripteP-value for the association between the peak SNP and the gene transcript after adjustment for the NHL SNP

Supplementary Table 10. Expression quantitative trait loci (eqtl) associations* with FDR < 1% from the childhood asthma dataset


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Proxy SNP in LD Loc (hg19) r2 PROBE P FDR rho Genotype countsrs3130923 rs1634726 6:30985828 0.80 LY6G6E:NR_003673 9.99E-05 4.18E-02 0.61 AA(0) AG(7) GG(28)rs3130923 rs2156874 6:31335976 0.84 FLOT1:NM_005803 3.17E-04 4.30E-02 -0.53 CC(0) CG(12) GG(29)rs3130923 rs2156874 6:31335976 0.84 RNF5:NM_006913 2.76E-04 4.30E-02 -0.54 CC(0) CG(12) GG(29)rs3130923 rs2596430 6:31335431 0.84 FLOT1:NM_005803 3.17E-04 4.30E-02 -0.53 CC(0) CT(12) TT(29)rs3130923 rs2596430 6:31335431 0.84 RNF5:NM_006913 2.76E-04 4.30E-02 -0.54 CC(0) CT(12) TT(29)rs3130923 rs2596565 6:31353329 0.81 RNF5:NM_006913 5.55E-05 3.10E-02 -0.61 AA(0) AG(11) GG(27)rs3130923 rs2596565 6:31353329 0.81 FLOT1:NM_005803 3.72E-04 4.30E-02 -0.55 AA(0) AG(11) GG(27)rs3130923 rs2734583 6:31505480 0.83 RNF5:NM_006913 5.55E-05 3.10E-02 -0.61 GG(0) GA(11) AA(27)rs3130923 rs2734583 6:31505480 0.83 FLOT1:NM_005803 3.72E-04 4.30E-02 -0.55 GG(0) GA(11) AA(27)rs3130923 rs2844559 6:31340075 0.81 RNF5:NM_006913 2.15E-04 4.30E-02 -0.58 TT(0) TC(10) CC(26)rs3130923 rs2844577 6:31334422 0.80 LY6G6E:NR_003673 7.22E-05 3.45E-02 0.61 CC(0) CT(7) TT(29)rs3130923 rs2922994 6:31335901 0.84 FLOT1:NM_005803 3.17E-04 4.30E-02 -0.53 GG(0) GA(12) AA(29)rs3130923 rs2922994 6:31335901 0.84 RNF5:NM_006913 2.76E-04 4.30E-02 -0.54 GG(0) GA(12) AA(29)rs3130923 rs3094005 6:31465047 0.86 RNF5:NM_006913 5.55E-05 3.10E-02 -0.61 TT(0) TG(11) GG(27)rs3130923 rs3094005 6:31465047 0.86 FLOT1:NM_005803 3.72E-04 4.30E-02 -0.55 TT(0) TG(11) GG(27)rs3130923 rs3099844 6:31448976 0.86 RNF5:NM_006913 5.55E-05 3.10E-02 -0.61 AA(0) AC(11) CC(27)rs3130923 rs3099844 6:31448976 0.86 FLOT1:NM_005803 3.72E-04 4.30E-02 -0.55 AA(0) AC(11) CC(27)rs3130923 rs3130612 6:31482097 0.92 RNF5:NM_006913 3.86E-04 4.31E-02 -0.53 GG(0) GT(12) TT(28)rs3130923 rs3130612 6:31482097 0.92 FLOT1:NM_005803 4.45E-04 4.72E-02 -0.53 GG(0) GT(12) TT(28)rs3130923 rs3130614 6:31476458 0.92 FLOT1:NM_005803 3.17E-04 4.30E-02 -0.53 AA(0) AT(12) TT(29)rs3130923 rs3130614 6:31476458 0.92 RNF5:NM_006913 2.76E-04 4.30E-02 -0.54 AA(0) AT(12) TT(29)rs3130923 rs3130923 6:31462135 NA FLOT1:NM_005803 2.47E-04 4.30E-02 -0.57 AA(0) AG(12) GG(25)rs3130923 rs3131618 6:31434621 0.86 RNF5:NM_006913 5.55E-05 3.10E-02 -0.61 GG(0) GA(11) AA(27)rs3130923 rs3131618 6:31434621 0.86 FLOT1:NM_005803 3.72E-04 4.30E-02 -0.55 GG(0) GA(11) AA(27)rs3130923 rs3132472 6:31386131 0.92 FLOT1:NM_005803 3.17E-04 4.30E-02 -0.53 AA(0) AG(12) GG(29)rs3130923 rs3132472 6:31386131 0.92 RNF5:NM_006913 2.76E-04 4.30E-02 -0.54 AA(0) AG(12) GG(29)rs3130923 rs3132473 6:31408329 0.90 LY6G6E:NR_003673 1.71E-04 4.30E-02 0.61 AA(0) AT(7) TT(26)rs3130923 rs3132473 6:31408329 0.90 LSM2:NM_021177 4.51E-04 4.72E-02 -0.58 AA(0) AT(7) TT(26)rs3130923 rs3134792 6:31312326 0.81 RNF5:NM_006913 5.55E-05 3.10E-02 -0.61 GG(0) GT(11) TT(27)rs3130923 rs3134792 6:31312326 0.81 FLOT1:NM_005803 3.72E-04 4.30E-02 -0.55 GG(0) GT(11) TT(27)rs3130923 rs4143332 6:31348365 0.84 FLOT1:NM_005803 3.17E-04 4.30E-02 -0.53 AA(0) AG(12) GG(29)rs3130923 rs4143332 6:31348365 0.84 RNF5:NM_006913 2.76E-04 4.30E-02 -0.54 AA(0) AG(12) GG(29)

Supplementary Table 11. Results from eQTL analysis of novel DLBCL loci and SNPs in LD (r2≥0.80). Only eQTLS with FDR<0.05 are shown.


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Supplementary Table 12 (HaploReg v2 results for all loci r2 ≥ 0.6 with DLBCL index SNP) – in excel file


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Supplementary Table 13. Published DLBCL loci at P<5x10-7 (by Chromosome and Position)

SNP CHR LOC Gene GROUP

Imputed or geno-

typed INFO

N CONTR

OLSN

CASESREF

ALLELEEFFECT ALLELE

EFFECT_ALLELE_FREQ_CONTROL

EFFECT_ALLELE_FREQ_C

ASE OR CI PP

heterog. Pub-ORPub-P-value

Pub-MAF cont Ref

rs6773854 chr3 187649419 BCL6/LPP NCI_DLBCL g 1.0000 6221 2661 T C 0.215 0.232 1.08 (1.00-1.17) 0.06GELA g 1.0000 525 549 T C 0.215 0.209 0.95 (0.77-1.17) 0.62MAYO_DLBCL g 1.0000 172 393 T C 0.212 0.196 0.79 (0.57-1.10) 0.16UCSF g 1.0000 748 254 T C 0.203 0.246 1.28 (1.01-1.63) 0.040Combined 7666 3857 1.06 (0.99-1.14) 0.081 0.08 1.47 1.14E-11 0.22

rs1800629 chr6 31543031 TNF-308‡ NCI_DLBCL g 1.0000 6221 2661 G A 0.163 0.187 1.20 (1.08-1.32) 0.00050GELA i 0.9949 524 549 G A 0.161 0.166 1.10 (0.87-1.39) 0.41MAYO_DLBCL i 0.9964 172 393 G A 0.200 0.174 0.86 (0.61-1.21) 0.38UCSF i 0.9969 747 254 G A 0.160 0.178 1.14 (0.87-1.50) 0.34Combined 7664 3857 1.15§ (1.06-1.26) 0.00093 0.32 1.28* 3.70E-06 0.16

rs909253 chr6 31540313 LTA 252‡ NCI_DLBCL g 1.0000 6221 2661 A G 0.329 0.353 1.10 (1.03-1.19) 0.0083GELA i 1.0000 524 549 A G 0.321 0.320 1.05 (0.88-1.27) 0.57MAYO_DLBCL i 1.0000 172 393 A G 0.358 0.338 0.94 (0.72-1.24) 0.68UCSF i 1.0000 747 254 A G 0.311 0.337 1.12 (0.90-1.38) 0.30Combined 7664 3857 1.09§ (1.02-1.16) 0.0076 0.71 1.12* 6.00E-03 0.32

rs10484561 chr6 32665420 HLAD-DQB1 NCI_DLBCL i 1.0000 6221 2661 T G 0.121 0.138 1.18 (1.07-1.30) 0.0014GELA g 1.0000 525 549 T G 0.131 0.138 1.07 (0.84-1.37) 0.58MAYO_DLBCL g 1.0000 172 393 T G 0.111 0.141 1.22 (0.83-1.81) 0.31UCSF i 1.0000 748 254 T G 0.131 0.169 1.35 (1.02-1.80) 0.036Combined 7666 3857 1.18 (1.08-1.29) 0.00015 0.68 1.36 1.41E-07 0.11

rs751837 chr14 103484825 CDC42BP NCI_DLBCL g 1.0000 6221 2661 T C 0.110 0.108 0.97 (0.88-1.09) 0.64GELA g 1.0000 525 549 T C 0.091 0.082 0.88 (0.65-1.20) 0.42MAYO_DLBCL g 1.0000 172 393 T C 0.137 0.125 1.03 (0.70-1.53) 0.87UCSF g 1.0000 748 254 T C 0.116 0.110 0.94 (0.69-1.28) 0.69Combined 7666 3857 0.97 (0.88-1.06) 0.46 0.91 3.51 3.30E-07 0.008

*OR for dominant model§When restricted to cohort studies [which were not in the Skibola (2010) publication]: rs1800629 OR=1.15, p=0.095 and rs909253 OR=1.07, p=0.30.

‡LTA 252A>G/TNF –308G>A haplotype global p=2.5 3 10-7 TNF –308G>A and IL10-1082A>G/IL10-3575T>A Haplotypes

Kumar, 2011

Tan, 2013

Skibola, 2010

Skibola, 2010

Smedby, 2011


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SUPPLEMENTARY NOTE

Support for individual studies: ATBC – Intramural Research Program of the National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. U.S. Public Health Service contracts (N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C). BC (J.S., A.B.W.) – Canadian Institutes for Health Research (CIHR). Canadian Cancer Society. Michael Smith Foundation for Health Research. CPSII (L.T.) – The American Cancer Society funds the creation, maintenance, and updating of the CPSII cohort. The authors thank the CPS-II participants and Study Management Group for their invaluable contributions to this research. The authors would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. ELCCS (E.R.) - Leukaemia & Lymphoma Research. ENGELA (J.C.) – Fondation ARC pour la Recherche sur le Cancer. Fondation de France. French Agency for Food, Environmental and Occupational Health & Safety (ANSES),the French National Cancer Institute (INCa). EPIC (E.R.) – Coordinated Action (Contract #006438, SP23-CT-2005-006438). HuGeF (Human Genetics Foundation), Torino, Italy. EPILYMPH – European Commission (grant references QLK4-CT-2000-00422 and FOOD-CT-2006-023103); the Spanish Ministry of Health (grant references CIBERESP, PI11/01810, RCESP C03/09, RTICESP C03/10 and RTIC RD06/0020/0095), the Marató de TV3 Foundation (grant reference 051210), the Agència de Gestiód’AjutsUniversitarisi de Recerca – Generalitat de Catalunya (grant reference 2009SGR1465) who had no role in the data collection, analysis or interpretation of the results; the NIH (contract NO1-CO-12400); the Compagnia di San Paolo—Programma Oncologia; the Federal Office for Radiation Protection grants StSch4261 and StSch4420, the José Carreras Leukemia Foundation grant DJCLS-R12/23, the German Federal Ministry for Education and Research (BMBF-01-EO-1303); the Health Research Board, Ireland and Cancer Research Ireland; Czech Republic supported by MH CZ – DRO (MMCI, 00209805) and RECAMO, CZ.1.05/2.1.00/03.0101; Fondation de France and Association de Recherche Contre le Cancer. GELA (G.S.) – The French National Cancer Institute (INCa). HPFS (Walter C. Willet) – The HPFS was supported in part by National Institutes of Health grants CA167552, CA149445, CA098122, CA098566 (K.A.B.), and K07 CA115687 (B.M.B.). We would like to thank the participants and staff of the Health Professionals Follow-up Study for their valuable contributions as well as the following


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state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. In addition, this study was approved by the Connecticut Department of Public Health (DPH) Human Investigations Committee. Certain data used in this publication were obtained from the DPH. The authors assume full responsibility for analyses and interpretation of these data. Iowa-Mayo SPORE (G.W., J.R.C., T.E.W.) – National Institutes of Health (CA97274). NCI Specialized Programs of Research Excellence (SPORE) in Human Cancer (P50 CA97274). Molecular Epidemiology of Non-Hodgkin Lymphoma Survival (R01 CA129539). Henry J. Predolin Foundation. Italian GxE (P.C.) - Italian Ministry for Education, University and Research Research (PRIN 2007 prot.2007WEJLZB, PRIN 2009 prot. 20092ZELR2); the Italian Association for Cancer Research (AIRC, Investigator Grant 11855). (M.G.E.) - Regional Law N. 7, 2007: “Basic research” (Progetti di ricerca fondamentale o di base) by the Regional Administration of Sardinia (CRP-59812/2012), Fondazione Banco di Sardegna 2010-2012. Mayo Clinic Case-Control (J.R.C.) – National Institutes of Health (R01 CA92153). National Center for Advancing Translational Science (UL1 TR000135) MCCS (G.G.G., G.S.) – The Melbourne Collaborative Cohort Study recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. MD Anderson (X.W.) – Institutional support to the Center for Translational and Public Health Genomics. MSKCC (K.O.) – Geoffrey Beene Cancer Research Grant, Lymphoma Foundation (LF5541). Barbara K. Lipman Lymphoma Research Fund (74419). Robert and Kate Niehaus Clinical Cancer Genetics Research Initiative (57470), U01 HG007033. ENCODE, U01 HG007033 (J.V.). NCI-SEER – Intramural Research Program of the National Cancer Institute, National Institutes of Health, and Public Health Service (N01-PC-65064,N01-PC-67008, N01-PC-67009, N01-PC-67010, N02-PC-71105). NHS (Meir J. Stampfer) – The NHS was supported in part by National Institutes of Health grants CA87969, CA49449, CA149445, CA098122, CA098566 (K.A.B.), and K07 CA115687 (B.M.B.). We would like to thank the participants and staff of the Nurses' Health Study for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. In addition, this study was approved by the Connecticut Department of Public Health (DPH) Human Investigations Committee. Certain data used in this publication


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were obtained from the DPH. The authors assume full responsibility for analyses and interpretation of these data. NSW (C.M.Vajdic) - was supported by grants from the Australian National Health and Medical Research Council (ID990920), the Cancer Council NSW, and the University of Sydney Faculty of Medicine. NYUWHS - National Cancer Institute (R01 CA098661, P30 CA016087). National Institute of Environmental Health Sciences (ES000260). PLCO - This research was supported by the Intramural Research Program of the National Cancer Institute and by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. SCALE (K.E.S., H.O.A., H.H.) – Swedish Cancer Society (2009/659). Stockholm County Council (20110209) and the Strategic Research Program in Epidemiology at Karolinska Institute. Swedish Cancer Society grant (02 6661). Danish Cancer Research Foundation Grant. Lundbeck Foundation Grant (R19-A2364). Danish Cancer Society Grant (DP 08-155). National Institutes of Health (5R01 CA69669-02). Plan Denmark. UCSF (E.A.H., P.M.B, C.F.S.) – The UCSF studies were supported by the NCI, National Institutes of Health, CA1046282 (C.F.S.) and CA154643 (C.F.S.). The collection of cancer incidence data used in this study 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; the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement #1U58 DP000807-01 awarded to the Public Health Institute. The ideas and opinions expressed herein are those of the authors, and endorsement by the State of California, the California Department of Health Services, the National Cancer Institute, or the Centers for Disease Control and Prevention or their contractors and subcontractors is not intended nor should be inferred. WHI - The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. YALE (T.Z.) – National Cancer Institute (CA62006).


nature genetics: doi:10.1038/ng · 2014-10-29 · nature genetics: doi:10.1038/ng.3105...

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