Genetic evidence identifies a causal relationship between EBV infection and multiple myeloma risk

被引:1
作者
Li, Jian [1 ,5 ]
Tan, Rong [2 ]
Yang, Bing [1 ,3 ]
Du, Changpu [1 ,5 ]
Tian, Jie [1 ,4 ,5 ]
Yang, Zhu [5 ]
Tang, Dongxin [4 ,5 ]
机构
[1] Guizhou Univ Tradit Chinese Med, Coll Clin Med 1, Affiliated Hosp 1, 71,Baoshan North Rd, Guiyang 550001, Guizhou, Peoples R China
[2] Guizhou Univ Tradit Chinese Med, Affiliated Hosp 1, Dept Pharmaceut, Guiyang, Guizhou, Peoples R China
[3] Guizhou Univ Tradit Chinese Med, Affiliated Hosp 1, Student Management Off, Guiyang, Guizhou, Peoples R China
[4] Guizhou Univ Tradit Chinese Med, Affiliated Hosp 1, Dept Oncol, Guiyang, Guizhou, Peoples R China
[5] Guizhou Univ Tradit Chinese Med, 4,Dongqing Rd, Guiyang 550025, Guizhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Epstein-Barr virus; Multiple myeloma; Causal association; Mendelian randomization; EPSTEIN-BARR-VIRUS; MENDELIAN RANDOMIZATION; INHIBITION; DIAGNOSIS; CANCER;
D O I
10.1038/s41598-025-90479-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Previous observational studies have suggested a potential association between Epstein-Barr virus (EBV) infection and the development of multiple myeloma (MM), but this relationship is not clear. Therefore, we conducted a systematic Mendelian randomization (MR) analysis to investigate the causal relationship between EBV infection and the risk of MM, while exploring the possible mediating role of immune cells in this association. Methods: The study first conducted a two-sample MR analysis using the MM R11 dataset from the FinnGen Consortium to evaluate the causal relationship between five EBV infection-related antibodies (AEB-IgG, EA-D, EBNA-1, VCA-p18, and ZEBRA) and MM, with validation in the MM R10 dataset. A reverse MR analysis was then performed. For significant results, multivariable MR (MVMR) was used to adjust for the effects of confounding risk factors. Next, a two-step MR mediation analysis was applied to investigate the potential mediating role of 731 immune cell types between positive exposure and MM. Multiple sensitivity analyses were conducted to assess the robustness of the findings. Results: A two-sample MR study found that EBNA-1 antibodies (OR = 1.36, 95% CI: 1.06-1.73; P = 0.015) were associated with an increased risk of MM, with similar results observed in the FinnGen Consortium R10 replication study. Although the association did not remain statistically significant after false discovery rate (FDR) adjustment (P_fdr = 0.075), further adjustment for relevant confounders using multivariable MR (MVMR) demonstrated that EBNA-1 antibodies (OR = 1.33, 95% CI: 1.01-1.75; P = 0.041) were still significantly associated with an increased risk of MM. Reverse MR analysis indicated no causal effect of MM on EBV-related antibodies. A two-sample MR analysis involving 731 immune cell phenotypes identified 27 potential mediating cell types. Ultimately, two-step MR confirmed that HLA-DR on myeloid dendritic cells (HLA-DR+ mDC) serves as a mediating factor, with EBNA-1 antibodies downregulating HLA-DR+ mDC, thereby increasing MM risk. Multiple sensitivity analyses supported the robustness of these findings. Conclusion: The findings of this study suggest that EBNA-1 antibodies may increase the risk of MM by downregulating HLA-DR+ mDC. This indicates that chronic EBV infection may contribute to an elevated risk of MM. We hope these results provide new insights for future research on the prevention and treatment of MM.
引用
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页数:9
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共 51 条
[1]   Epstein Barr Virus-Encoded EBNA1 Interference with MHC Class I Antigen Presentation Reveals a Close Correlation between mRNA Translation Initiation and Antigen Presentation [J].
Apcher, Sebastien ;
Daskalogianni, Chrysoula ;
Manoury, Benedicte ;
Fahraeus, Robin .
PLOS PATHOGENS, 2010, 6 (10)
[2]   Obesity and cancer risk: Emerging biological mechanisms and perspectives [J].
Avgerinos, Konstantinos, I ;
Spyrou, Nikolaos ;
Mantzoros, Christos S. ;
Dalamaga, Maria .
METABOLISM-CLINICAL AND EXPERIMENTAL, 2019, 92 :121-135
[3]   Epstein-Barr virus infection is associated with clinical characteristics and poor prognosis of multiple myeloma [J].
Bing Xia ;
Xi Wang ;
Yang, Ruifang ;
Li Mengzhen ;
Yang, Kunpeng ;
Li Ren ;
Li, Suxia ;
Wang, Shuye ;
Zhang, Yizhuo .
BIOSCIENCE REPORTS, 2019, 39
[4]   Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator [J].
Bowden, Jack ;
Smith, George Davey ;
Haycock, Philip C. ;
Burgess, Stephen .
GENETIC EPIDEMIOLOGY, 2016, 40 (04) :304-314
[5]   Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J].
Bray, Freddie ;
Laversanne, Mathieu ;
Sung, Hyuna ;
Ferlay, Jacques ;
Siegel, Rebecca L. ;
Soerjomataram, Isabelle ;
Jemal, Ahmedin .
CA-A CANCER JOURNAL FOR CLINICIANS, 2024, 74 (03) :229-263
[6]   Research Techniques Made Simple: Using Genetic Variants for Randomization [J].
Budu-Aggrey, Ashley ;
Paternoster, Lavinia .
JOURNAL OF INVESTIGATIVE DERMATOLOGY, 2019, 139 (07) :1416-+
[7]   Genetic Determinants of Antibody-Mediated Immune Responses to Infectious Diseases Agents: A Genome-Wide and HLA Association Study [J].
Butler-Laporte, Guillaume ;
Kreuzer, Devin ;
Nakanishi, Tomoko ;
Harroud, Adil ;
Forgetta, Vincenzo ;
Richards, J. Brent .
OPEN FORUM INFECTIOUS DISEASES, 2020, 7 (11)
[8]   Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians [J].
Davies, Neil M. ;
Holmes, Michael V. ;
Smith, George Davey .
BMJ-BRITISH MEDICAL JOURNAL, 2018, 362
[9]   Investigating the relationship between Epstein-Barr virus infection and gastric cancer: A systematic review and meta-analysis [J].
Dokanei, Saman ;
Minai-Tehrani, Dariush ;
Moghoofei, Mohsen ;
Rostamian, Mosayeb .
HEALTH SCIENCE REPORTS, 2024, 7 (03)
[10]   Sonocatalytic oncolysis microbiota curb intrinsic microbiota lactate metabolism and blockade CD24-Siglec10 immune escape to revitalize immunological surveillance [J].
Dong, Xiulin ;
Liu, Hui ;
Fang, Chao ;
Zhang, Yan ;
Yang, Qiaoling ;
Wang, Hai ;
Li, Xiaolong ;
Zhang, Kun .
BIOMATERIALS, 2024, 311