Evidence map›Paper›PMID 39984542›Full record

ArticleScientific reports2025

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

Jian Li, Rong Tan, Bing Yang, Changpu Du, Jie Tian, Zhu Yang, Dongxin Tang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jian LiThe First College of Clinical Medicine, Guizhou University of Traditional Chinese Medicine, No. 71, Baoshan North Road, Yunyan District, Guiyang, 550001, Guizhou, China.
Rong TanDepartment of Pharmaceutics, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China.
Bing YangThe First College of Clinical Medicine, Guizhou University of Traditional Chinese Medicine, No. 71, Baoshan North Road, Yunyan District, Guiyang, 550001, Guizhou, China.
Changpu DuThe First College of Clinical Medicine, Guizhou University of Traditional Chinese Medicine, No. 71, Baoshan North Road, Yunyan District, Guiyang, 550001, Guizhou, China.
Jie TianThe First College of Clinical Medicine, Guizhou University of Traditional Chinese Medicine, No. 71, Baoshan North Road, Yunyan District, Guiyang, 550001, Guizhou, China. tianjie597@gzy.edu.cn.
Zhu YangGuizhou University of Traditional Chinese Medicine, No. 4, Dongqing Road, Huaxi District, Guiyang, 550025, Guizhou, China. yangzhu20150426@163.com.
Dongxin TangDepartment of Oncology, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China. hemingankang@sina.com.

Funding

Guizhou Higher Education Institutions Chinese Medicine and Ethnic Medicine to Prevent and Control Tumor Medical Translational Engineering Research Center of Guizhou Education and Technology [2023] No. 037National Natural Science Foundation of China No. 82260957National Natural Science Foundation of China No. 82274610National Natural Science Foundation of China No. 82460918
6 · The paper itself

Abstract

backgroundPrevious 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.

methodsThe 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.

resultsA 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.

conclusionThe 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.

Indexed as

Epstein-Barr Virus InfectionsHerpesvirus 4, HumanMultiple MyelomaAntibodies, ViralEpstein-Barr Virus Nuclear AntigensGenetic Predisposition to DiseaseHumansMendelian Randomization AnalysisRisk FactorsAntibodies, ViralEpstein-Barr Virus Nuclear AntigensCausal associationEpstein-Barr virusMendelian randomizationMultiple myeloma

Identifiers

PMID39984542
PMCPMC11845450

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.