Lipid trait variants and the risk of non-hodgkin lymphoma subtypes: a mendelian randomization study

Geffen Kleinstern, Nicola J. Camp, Sonja I. Berndt, Brenda M. Birmann, Alexandra Nieters, Paige M. Bracci, James D. McKay, Herve Ghesquieres, Qing Lan, Henrik Hjalgrim, Yolanda Benavente, Alain Monnereau, Sophia S. Wang, Yawei Zhang, Mark P. Purdue, Anne Zeleniuch-Jacquotte, Graham G. Giles, Roel Vermeulen, Pierluigi Cocco, Demetrius AlbanesLauren R. Teras, Angela R. Brooks-Wilson, Claire M. Vajdic, Eleanor Kane, Neil E. Caporaso, Karin E. Smedby, Gilles Salles, Joseph Vijai, Stephen J. Chanock, Christine F. Skibola, Nathaniel Rothman, Susan L. Slager, James R. Cerhan

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Lipid traits have been inconsistently linked to risk of non-Hodgkin lymphoma (NHL). We examined the association of genetically predicted lipid traits with risk of diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and marginal zone lymphoma (MZL) using Mendelian randomization (MR) analysis. Methods: Genome-wide association study data from the InterLymph Consortium were available for 2,661 DLBCLs, 2,179 CLLs, 2,142 FLs, 824 MZLs, and 6,221 controls. SNPs associated (P < 5 108) with high-density lipoprotein (HDL, n ¼ 164), low-density lipoprotein (LDL, n ¼ 137), total cholesterol (TC, n ¼ 161), and triglycerides (TG, n ¼ 123) were used as instrumental variables (IV), explaining 14.6%, 27.7%, 16.8%, and 12.8% of phenotypic variation, respectively. Associations between each lipid trait and NHL subtype were calculated using the MR inverse variance–weighted method, estimating odds ratios (OR) per standard deviation and 95% confidence intervals (CI). Results: HDL was positively associated with DLBCL (OR ¼ 1.14; 95% CI, 1.00–1.30) and MZL (OR ¼ 1.09; 95% CI, 1.01–1.18), while TG was inversely associated with MZL risk (OR ¼ 0.90; 95% CI, 0.83–0.99), all at nominal significance (P < 0.05). A positive trend was observed for HDL with FL risk (OR ¼ 1.08; 95% CI, 0.99–1.19; P ¼ 0.087). No associations were noteworthy after adjusting for multiple testing. Conclusions: We did not find evidence of a clear or strong association of these lipid traits with the most common NHL subtypes. While these IVs have been previously linked to other cancers, our findings do not support any causal associations with these NHL subtypes. Impact: Our results suggest that prior reported inverse associations of lipid traits are not likely to be causal and could represent reverse causality or confounding.

Original languageEnglish
Pages (from-to)1074-1078
Number of pages5
JournalCancer Epidemiology Biomarkers and Prevention
Volume29
Issue number5
DOIs
StatePublished - May 2020
Externally publishedYes

Bibliographical note

Funding Information:
Spanish Ministry of Economy and Competitiveness - Carlos III Institute of Health cofunded by FEDER funds/European Regional Development Fund (ERDF) - a way to build Europe (grant numbers PI17/01280 and PI14/01219); Centro de Investigación Biomédica en Red: Epidemiología y Salud Pública [CIBERESP, Spain; grant sponsor: Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR), CERCA Programme/ Generalitat de Catalunya for institutional support; grant number: 2017SGR1085]. GEC: NIH CA 118444. GELA: The French National Cancer Institute (INCa). HPFS: The HPFS was supported in part by NIH grants UM1 CA167552, R01 CA149445, and R01 CA098122. 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 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, and WY. The study protocol was approved by the institutional review boards of the Brigham and Women's Hospital and Harvard T.H. Chan School of Public Health, and those of participating registries as required. Iowa-Mayo SPORE: NIH (CA97274), NCI Specialized Programs of Research Excellence (SPORE) in Human Cancer (P50 CA97274), Molecular Epidemiology of Non-Hodgkin Lymphoma Survival (R01 CA129539), and Henry J. Predolin Foundation. Italian GxE: Italian Ministry for Education, University and Research (PRIN 2007 prot. 2007WEJLZB, PRIN 2009 prot. 20092ZELR2), and the Italian Association for Cancer Research (AIRC, Investigator Grant 11855). Mayo Clinic Case-Control: NIH (R01 CA92153) and National Center for Advancing Translational Science (UL1 TR000135) MCCS: The Melbourne Collaborative Cohort Study recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian National Health and Medical Research Council (NHMRC) grants 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. MD Anderson: Institutional support to the Center for Translational and Public Health Genomics. MSKCC: 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. NCI-SEER: Intramural Research Program of the NCI, NIH, and Public Health Service (N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105).

Funding Information:
G. Kleinstern was supported by the NIH grant R25 CA92049 (Mayo Cancer Genetic Epidemiology Training Program). Research reported in this article was supported by the NCI of the NIH under award number R01 CA200703 (to J.R. Cerhan). ATBC: Intramural Research Program of the NIH, NCI, Division of Cancer Epidemiology and Genetics. BC: Canadian Institutes for Health Research. CPSII: The American Cancer Society funds the creation, maintenance, and updating of the CPSII cohort. The authors thank the CPSII 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 NCI Surveillance, Epidemiology, and End Results Program.

Funding Information:
ELCCS: Leukaemia and Lymphoma Research. ENGELA: 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: 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 CIBER-ESP, PI11/01810, RCESP C03/09, RTICESP C03/10, and RTIC RD06/0020/0095), the Marató de TV3 Foundation (grant reference 051210), the Agència de Ges-tiód'AjutsUniversitarisi de Recerca – Generalitat de Catalunya (grant reference 2009SGR1465), which 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 JoséCarreras 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; and Fondation de France and Association de Recherche Contre le Cancer.

Publisher Copyright:
© 2020 American Association for Cancer Research.

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

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