Skip to main content
Download PDF

The genetic liability to rheumatoid arthritis may decrease hepatocellular carcinoma risk in East Asian population: a Mendelian randomization study

Arthritis Research & Therapy volume 25, Article number: 49 (2023) Cite this article

Abstract

Background

Patients with rheumatoid arthritis (RA) have a rising possibility of acquiring certain kinds of cancers than the general public. The causal risk association between RA and hepatocellular carcinoma (HCC) remains unknown.

Methods

Genetic summary data from genome-wide association study (GWAS), including RA (n = 19,190) and HCC (n = 197,611), was analyzed. The inverse-variance weighted (IVW) approach was used as the principal analysis, complemented with weighted median, weighted mode, simple median method, and MR-Egger analyses. The genetic data of RA (n = 212,453) was used to verify the results in eastern Asia populations.

Results

The results from the IVW methods indicated that genetically predicted RA was significantly linked with a declined possibility of HCC for East Asians (OR = 0.86; 95% CI: 0.78, 0.95; p = 0.003). The weighted median and the weighted mode also supported similar results (all p < 0.05). Additionally, neither the funnel plots nor the MR-Egger intercepts revealed any directional pleiotropic effects between RA and HCC. Moreover, the other set of RA data validated the results.

Conclusion

The RA may decrease the risk of being susceptible to the HCC in eastern Asia populations, which was beyond expectation. In the future, additional investigations should be made into potential biomedical mechanisms.

Introduction

Hepatocellular carcinoma (HCC), accounting for about 90% of primary liver cancer, is the fifth most prevalent cancer and the third leading cause of cancer-related mortality globally, with an annual incidence of roughly 500,000 cases [1, 2]. Regarding the global impact of HCC, an initiative to enhance the understanding of HCC risk factors and natural history to establish surveillance projects and manage high-risk populations is ongoing [3]. Meanwhile, rheumatoid arthritis (RA), a chronic, systemic autoimmune disease with global distribution, is one of the leading causes of human disability [4]. In industrialized countries, 0.5 to 1.0% of adults are affected with RA, with an incidence of 5 to 50 per 100,000 annually [5]. Regarding the huge disease burden of HCC and the growing RA epidemic [3, 4], the comorbidities of both diseases may not be uncommon.

Previous studies showed that RA was linked to cancer incidence, and most suggested that it may be correlated with an increased risk of certain kinds of cancers compared to the general population [6,7,8]. However, it is unknown whether RA is associated with the risk of developing HCC, and few studies paid attention to this issue. A 10-year population-based cohort study investigated the possible causative link between RA and the risk of acquiring HCC, revealing that RA was associated with a lower incidence of HCC (0.66% vs. 1.41% events) [9]. Nonetheless, unmeasurable or undetected confounding factors inevitably exist, which may potentially cause biases. Moreover, featured as chronic inflammation, RA may promote hepatic oncogenesis as there were clues from biochemical studies. Research by Wang et al. indicated that RA patients have significantly increased levels of methyltransferase-like 3 (METTL3) expression, which is positively correlated to disease activity [10], and it has been demonstrated that the METTL3 expression increases in HCC and facilitates cancer cell proliferation, metastasis, and colony formation [11].

Here, we assessed the potential causal association between RA and HCC through two-sample Mendelian randomization (MR). Our study provided new evidence for the relationship between RA and HCC, which may offer novel insight into further mechanistic linking investigations.

Methods

Method selection and study design

The baseline association between RA and HCC is always confounded by unmeasured or irrelevant factors when conducting observational epidemiological studies, which may result in misleading conclusions. Mendelian randomization (MR) provides a new way for causal inference using genetic variants strongly correlated with exposure factors as instrumental variables (IVs) to infer the causal impact of exposure factors on specific outcomes [12]. Because the creation of gametes follows the Mendelian inheritance law of “random allocation of parental alleles to descendant,” genetic variation is unaffected by conventional confounding factors such as environmental influence, socioeconomic factors, and individual behaviors, and its association with outcomes is temporally rational; thus, MR could minimize confounding and reverse causality in traditional observations, providing stronger evidence versus the observational studies [13]. Figure 1 illustrates the research design flow chart.

Fig. 1
figure 1

Directed acyclic graph of the MR framework investigating the causal relationship between RA and HCC. Instrumental variable assumptions: (1) the genetic instrument variables (GIVs) must be strongly associated with RA, (2) the GIVs must not be associated with any potential confounder of the RA vs. HCC relationship, and (3) the GIVs should only affect the risk of HCC through RA. SNPs, single nucleotide polymorphisms; RA, rheumatoid arthritis; HCC, hepatocellular carcinoma; MR, Mendelian randomization

Full size image

Data sources

This study utilized summary-level data from published studies and databases. The informed consent from involved patients was waived based on ethical approval. The genetic data of RA, as well as of HCC, were obtained by meta-analysis of genome-wide association studies (GWAS) including 19,190 samples (3636 cases and 15,554 controls) and 197,611 samples (1,866 cases and 195,745 controls), respectively (accessible at https://gwas.mrcieu.ac.uk/). We extracted the GWAS with the East Asian ancestry group as the population data to diminish potential biases in population stratification. The project details had been described in a previous study published in Nature [14]. The summary-level data used to verify the eastern Asia results was taken from the IEU Open GWAS database (https://gwas.mrcieu.ac.uk/), namely rheumatoid arthritis (GWAS ID: bbj-a-151). In addition, we used 11 sets of data to assess the causal relationship between RA and HCC in European populations. Detailed information on GWAS summary data for the European population was provided in Table S3.

Genetic instrumental variable selection

Single nucleotide polymorphisms (SNPs), which served as IVs for RA, were attained from the Biobank Japan. RA-related SNPs were selected as IVs at the genome-wide significant threshold (p < 5 × 10−8, indicating a substantial relevance with SNPs and RA) and after screening criteria (the linkage disequilibrium R2 < 0.001, the length between adjacent SNPs < 10,000 kb). In the summary statistics, HCC-related IVs were removed. After data harmonization, palindromic IVs were excluded due to palindromic with intermediate allele frequencies. Moreover, the F-statistic of more than 10 was used as the threshold for excluding genetic variations as potential IVs [15, 16].

Statistical analyses

MR analyses were conducted with the “MR-PRESSO” [17] and “TwoSampleMR” [18] packages in R version 4.2.1. Principally, the inverse-variance weighted (IVW) technique was adopted to assess the influence of exposure (RA) on the outcome (HCC). Four supplemental analyses were utilized to confirm the findings, which contained weighted mode, weighted median, simple median, and MR-Egger regression. The weighted median method could give relatively robust causal estimations [19]. The MR-Egger regression was used to evaluate the directional pleiotropy of IVs [20]. Moreover, the directed pleiotropy can be adjusted when calculating a causal estimate using the slope of the MR-Egger regression [20, 21]. The MR pleiotropy residual sum and outlier (MR-PRESSO) test was utilized to distinguish horizontal pleiotropy and revised it with outlier removal [18], and the modified Cochran’s Q test was adopted for assessing heterogeneity (p < 0.05) among SNPs. Finally, we carried out the leave-one-out test to determine if our evaluation was generated from particular SNPs with a substantial impact. The odds ratio (OR) and its 95% confidence intervals (CI) measured the relationships between RA and HCC. p-value < 0.05 was considered statistically significant. Additionally, we drew scatter plots to clearly visualize the SNP-related RA and HCC risk.

Results

Selection of instruments for RA-related SNPs

Forty-seven RA-related SNPs were extracted as IVs (R2 < 0.001, p < 5 × 10−8) from the GWAS study (Table S1). Two SNPs were excluded due to being unavailable in the corresponding data for HCC. Three SNPs (rs13330176, rs1858037, and rs909685) were eliminated from the relevant MR studies after data harmonization due to palindromic with intermediate allele frequencies. The other SNPs’ F-statistics were then computed and were all above 10, with values ranging from 49.97 to 3044.57. This showed that the remaining IVs would not likely be subjected to instrument bias and adhered to the first assumption sufficiently [16, 22]. The specifics of the chosen IVs were detailed in Table S1. Ultimately, forty-two SNPs were selected as genetic instruments for MR analyses. The information on RA-related genetic variants and their consequences on HCC was shown in Table 1.

Table 1 Characteristic of the genetic variants associated with RA and their effects on HCC (42 SNPs)
Full size table

The effect of RA on HCC

The causal effect of genetic liability to RA on acquiring HCC was obvious from the IVW analysis (OR = 0.86; 95% CI: 0.78, 0.95; p = 0.003), showing the presence of RA may be a protective factor for HCC incidence in East Asians (Table 2), and it was visualized in the scatter plot that HCC risk in RA patients decreased (Fig. 2). Moreover, the results of the weighted median method (OR = 0.81; 95% CI: 0.71, 0.92; p = 0.002) and the weighted mode method (OR = 0.85; 95% CI: 0.74, 0.98; p = 0.032) supported the similar results (Table 2). The MR-Egger method’s intercept p-value was 0.89 (> 0.05), implying that IVs did not exist in horizontal pleiotropy. Through the MR-PRESSO method, outliers for HCC were not found. The other RA dataset of East Asian people came to similar results (Table S2), indicating our outcome was steady. Additionally, only one set of data showed a slight increase between RA and HCC risk in European populations, which might be caused by errors. The other data showed that both were uncorrelated. Detailed information is shown in Table S4.

Table 2 Effect estimates of the associations between RA and hepatocellular carcinoma
Full size table
Fig. 2
figure 2

Scatter plot showing the causal effect of RA on hepatocellular carcinoma. SNP, single nucleotide polymorphism; MR, Mendelian randomization

Full size image

Sensitivity analysis

For the stability of the results, Cochran’s Q test demonstrated that no evident heterogeneity was found under the impact of SNPs (Q = 53.22; p = 0.096) (Fig. 3). Meanwhile, the leave-one-out sensitivity tests identified the influence of every SNP on the overall causal estimates. When deleting a single SNP, no evident shifts in the assessed causal effects were identified (Fig. 4).

Fig. 3
figure 3

Forest plot of the causal effect of RA-associated SNPs on hepatocellular carcinoma

Full size image
Fig. 4
figure 4

Funnel plot showing no significant heterogeneity among the SNPs. SE, standard error

Full size image

Discussion

As far as we know, this is the first two-sample MR study that comprehensively evaluated the causal association of the genetic predisposition to RA on the risk of developing HCC. Through the 42 SNPs as IVs, we drew the conclusion that genetically predicted RA was significantly linked with a declined possibility of HCC in the population of East Asians, which paves the way for the necessity to conduct relevant molecular mechanisms, access clinical influence, enhancing epidemiological surveillance, and making a public health decision.

Most previous studies showed that RA was associated with an ascending risk of several cancers [23, 24], including lung cancer [25], lymphoma [8], prostate cancer [26], and ovarian malignancy [27], while a few suggested that RA was related to no increase or lower risk of certain cancer [28, 29] like breast cancer and colorectal cancer [6, 30]. As for HCC, only one study we could find was a 10-year population-based cohort study, which showed that RA was associated with a lower risk of HCC (0.66% vs. 1.41% events) [31]. However, there were several shortcomings in the previous research. Owing to the limitations of observational research designs, reverse causation may introduce bias into the findings. Moreover, current epidemiological research has not assessed the impact of potential confounding variables, such as the length of research periods, differences in cancer screening programs between nations, environmental exposures, and data-collecting methodologies, which may distort the underlying link between RA and HCC. Thus, it may be insufficient to draw a sound conclusion.

MR is a novel approach that employs genetic variations of exposures as instruments to identify the effect of certain outcomes. Firstly, the impact of genetics is rather steady and basically immune from the environment influence. The genetic variants are determined when conceived, which is before the disease develops. In addition, MR applies tight quality control conditions and analytic methods and examines the causal effects using a variety of models. Consequently, MR is able to overcome the limits of conventional observational research hampered by reverse causality and confusion as well as generate reliable research findings [12, 32, 33], and this MR study found potential evidence of reduced odds of HCC in RA patients, which might offer insight into successive planned high-quality, large-scale, and long-term cohort studies for investigating the latent relationship between RA and HCC.

Our finding seems to be contrary to the common knowledge that RA leads to a higher risk of cancer. However, the pathogenesis of HCC is likely multifactorial in RA patients. Firstly, the potential protective impact may be by lowering the pathway of liver precancerous diseases, like cirrhosis. The large cohort study [31] indicated that people suffering from RA had a decreased percentage of liver cirrhosis. In addition, using immunomodulatory agents for RA not only affects the human body’s immune status but will also alter the risk of malignancies [8]. Most population-based cohort researches indicated that antirheumatic treatment may not exactly be associated with the cancer recurrence risk in RA patients, either in those receiving conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) or biologic DMARDs (bDMARDs) [31, 34,35,36,37,38] like tumor necrosis factor (TNF) [39,40,41,42], and a few studies found that using bDMARDs reduced the overall risk of acquiring malignancies except for hematologic malignancies [43]. Thirdly, it might be attributed to chronic inflammation with immune failure [44], which may motivate tumor suppressor pathways, induce premature and accelerated cell senescence, and ultimately lower the incidence of malignancies in people suffering from RA. These findings implied that biological processes behind the association between RA and HCC were more complicated than immunomodulation and inflammation.

Although the exact mechanism by which RA reduced HCC risk is unclear, a few underlying molecular pathways involving cell growth signal transference may shed light on the relationship. For example, changes in protein levels of G protein-coupled receptor kinase 2 (GRK2), a serine/threonine kinase participating in numerous crucial signaling pathways, may play a crucial role in RA and HCC. On the one hand, the prostaglandin E2-prostaglandin E4 receptor-G protein-coupled receptor kinase 2 (PGE2-EP4-GRK2) signaling pathway has been demonstrated to be relevant in the incidence and progression of RA in animal models. At the functional level, PGE2 binds to the EP4 receptor, triggering excessive GRK2 translocation to the cell membrane and EP4 desensitization, hence downregulating cAMP, malfunctioning FLS, and synovium hyperplasia [45, 46]. On the other hand, Ma et al. discovered that GRK2 inhibits insulin-like growth factor 1 (IGF1)-induced proliferation and migration of HCC cells. Overexpression of GRK2 leads to decreased expression of early growth response-1 (EGR1). Silencing EGR1 mitigates cell proliferation mediated by GRK2 overexpression [47]. In all, the pathogenesis between RA and HCC still needs further investigation.

Additionally, the results should be interpreted with caution due to the following limitations. First, the populations included are of East Asian and European ancestries. Therefore, more studies should be done on other populations. Second, the subgroup analysis is unavailable owing to a lack of clinic-specific data, for example, the lack of gender-specific summary data on instrument exposure related to RA, and the duration of RA exposure, rheumatic activity levels, and therapy impact may have potential bias. More research is needed to confirm a definite causal relationship between RA and HCC.

Conclusion

Overall, the underlying evidence, a causal effect of reduced probabilities of HCC in RA patients in East Asia, was revealed by this MR research, and it paves the way for the necessity to conduct relevant molecular mechanisms, access clinical influence, enhance epidemiological surveillance, and make a public health decision.

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.

    Article  PubMed  Google Scholar 

  2. Calderaro J, Seraphin TP, Luedde T, Simon TG. Artificial intelligence for the prevention and clinical management of hepatocellular carcinoma. J Hepatol. 2022;76(6):1348–61.

    Article  PubMed  Google Scholar 

  3. Villanueva A. Hepatocellular carcinoma. N Engl J Med. 2019;380(15):1450–62.

    Article  CAS  PubMed  Google Scholar 

  4. Smolen JS, Aletaha D, Barton A, Burmester GR, Emery P, Firestein GS, Kavanaugh A, McInnes IB, Solomon DH, Strand V, Yamamoto K. Rheumatoid arthritis. Nat Rev Dis Primers. 2018;4:18001.

    Article  Google Scholar 

  5. Scott DL, Wolfe F, Huizinga TWJ. Rheumatoid arthritis. Lancet (London, England). 2010;376(9746):1094–108.

    Article  PubMed  Google Scholar 

  6. Wilton KM, Matteson EL. Malignancy incidence, management, and prevention in patients with rheumatoid arthritis. Rheumatol Ther. 2017;4(2):333–47.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Lee H. The risk of malignancy in Korean patients with rheumatoid arthritis. Yonsei Med J. 2019;60(2):223–9.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Simon TA, Thompson A, Gandhi KK, Hochberg MC, Suissa S. Incidence of malignancy in adult patients with rheumatoid arthritis: a meta-analysis. Arthritis Res Ther. 2015;17(1):212.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hsu CS, Lang HC, Huang KY, Chao YC, Chen CL. Risks of hepatocellular carcinoma and cirrhosis-associated complications in patients with rheumatoid arthritis: a 10-year population-based cohort study in Taiwan. Hepatol Int. 2018;12(6):531–43.

    Article  PubMed  Google Scholar 

  10. Wang J, Yan S, Lu H, Wang S, Xu D. METTL3 attenuates LPS-induced inflammatory response in macrophages via NF-B signaling pathway. Mediators Inflamm. 2019;2019:3120391.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Chen M, Wei L, Law C-T, Tsang FH-C, Shen J, Cheng CL-H, Tsang L-H, Ho DW-H, Chiu DK-C, Lee JM-F, et al. RNA N6-methyladenosine methyltransferase-like 3 promotes liver cancer progression through YTHDF2-dependent posttranscriptional silencing of SOCS2. Hepatology (Baltimore, Md). 2018;67(6):2254–70.

    Article  CAS  PubMed  Google Scholar 

  12. Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362: k601.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Skrivankova VW, Richmond RC, Woolf BAR, Davies NM, Swanson SA, VanderWeele TJ, Timpson NJ, Higgins JPT, Dimou N, Langenberg C, et al. Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. BMJ. 2021;375: n2233.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, Kochi Y, Ohmura K, Suzuki A, Yoshida S, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 2014;506(7488):376–81.

    Article  CAS  PubMed  Google Scholar 

  15. Rajesh Y, Pal I, Banik P, Chakraborty S, Borkar SA, Dey G, Mukherjee A, Mandal M. Insights into molecular therapy of glioma: current challenges and next generation blueprint. Acta Pharmacol Sin. 2017;38(5):591–613.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40(3):755–64.

    Article  PubMed  Google Scholar 

  17. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R et al: The MR-Base platform supports systematic causal inference across the human phenome. ELife. 2018;7.

  18. Verbanck M, Chen C-Y, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40(4):304–14.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG. Sensitivity analyses for robust causal inference from mendelian randomization analyses with multiple genetic variants. Epidemiology. 2017;28(1):30–42.

    Article  PubMed  Google Scholar 

  21. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Sun W, Zhang L, Liu W, Tian M, Wang X, Liang J, Wang Y, Ding L, Pei L, Lu J, et al. Stroke and myocardial infarction: a bidirectional Mendelian randomization study. Int J Gen Med. 2021;14:9537–45.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bhandari B, Basyal B, Sarao MS, Nookala V, Thein Y. Prevalence of cancer in rheumatoid arthritis: epidemiological study based on the National Health and Nutrition Examination Survey (NHANES). Cureus. 2020;12(4): e7870.

    PubMed  PubMed Central  Google Scholar 

  24. Lim XR, Xiang W, Tan JWL, Koh LW, Lian TY, Leong KP, Koh E-T. Incidence and patterns of malignancies in a multi-ethnic cohort of rheumatoid arthritis patients. Int J Rheum Dis. 2019;22(9):1679–85.

    Article  PubMed  Google Scholar 

  25. Fragoulis GE, Chatzidionysiou K. Lung cancer in rheumatoid arthritis. Is there a need for better risk assessment and screening? Clin Rheumatol. 2020;39(3):957–61.

    Article  PubMed  Google Scholar 

  26. Wheeler AM, Roul P, Yang Y, Brittan KM, Sayles H, Singh N, Sauer BC, Cannon GW, Baker JF, Mikuls TR et al. Risk of prostate cancer in US veterans with rheumatoid arthritis. Arthritis Care Res (Hoboken). 2022. https://0-doi-org.brum.beds.ac.uk/10.1002/acr.24890.

  27. Huang Z, Tan L, Ling Y, Huang F, Ma W. Association between rheumatoid arthritis disease activity and risk of ovarian malignancy in middle-aged and elderly women. Biomed Res Int. 2022;2022:1062703.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ko KM, Moon S-J: Prevalence, incidence, and risk factors of malignancy in patients with rheumatoid arthritis: a nationwide cohort study from Korea. Korean J Intern Med. 2023;38(1):113-24. https://0-doi-org.brum.beds.ac.uk/10.3904/kjim.2021.

  29. Sugimoto N, Tanaka E, Inoue E, Abe M, Sugano E, Sugitani N, Saka K, Ochiai M, Higuchi Y, Yamaguchi R et al. Trends in risks of malignancies in Japanese patients with rheumatoid arthritis: analyses from a 14-year observation of the IORRA cohort. Modern Rheumatol. 2022. roac085. https://0-doi-org.brum.beds.ac.uk/10.1093/mr/roac085.

  30. Huang W-K, Chiou M-J, Kuo C-F, Lin Y-C, Yu K-H, See L-C. No overall increased risk of cancer in patients with rheumatoid arthritis: a nationwide dynamic cohort study in Taiwan. Rheumatol Int. 2014;34(10):1379–86.

    Article  PubMed  Google Scholar 

  31. Hsu C-S, Lang H-C, Huang K-Y, Chao Y-C, Chen C-L. Risks of hepatocellular carcinoma and cirrhosis-associated complications in patients with rheumatoid arthritis: a 10-year population-based cohort study in Taiwan. Hep Intl. 2018;12(6):531–43.

    Article  Google Scholar 

  32. Smith GD, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1).

  33. Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23(R1):R89–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. de Germay S, Bagheri H, Despas F, Rousseau V, Montastruc F. Abatacept in rheumatoid arthritis and the risk of cancer: a world observational post-marketing study. Rheumatology (Oxford). 2020;59(9):2360–7.

    Article  PubMed  Google Scholar 

  35. Simon TA, Boers M, Hochberg M, Baker N, Skovron ML, Ray N, Singhal S, Suissa S, Gomez-Caminero A. Comparative risk of malignancies and infections in patients with rheumatoid arthritis initiating abatacept versus other biologics: a multi-database real-world study. Arthritis Res Ther. 2019;21(1):228.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Seror R, Lafourcade A, De Rycke Y, Pinto S, Castaneda J, Fautrel B, Mariette X, Tubach F. Risk of malignancy in rheumatoid arthritis patients initiating biologics: an historical propensity score matched cohort study within the French nationwide healthcare database. RMD Open. 2022;8(2).

  37. Xie W, Xiao S, Huang Y, Sun X, Gao D, Ji L, Li G, Zhang Z. A meta-analysis of biologic therapies on risk of new or recurrent cancer in patients with rheumatoid arthritis and a prior malignancy. Rheumatology (Oxford). 2020;59(5):930–9.

    Article  CAS  PubMed  Google Scholar 

  38. Huss V, Bower H, Wadström H, Frisell T, Askling J. Short- and longer-term cancer risks with biologic and targeted synthetic disease-modifying antirheumatic drugs as used against rheumatoid arthritis in clinical practice. Rheumatology (Oxford). 2022;61(5):1810–8.

    Article  CAS  PubMed  Google Scholar 

  39. Staples MP, March L, Hill C, Lassere M, Buchbinder R. Malignancy risk in Australian rheumatoid arthritis patients treated with anti-tumour necrosis factor therapy: an update from the Australian Rheumatology Association Database (ARAD) prospective cohort study. BMC Rheumatol. 2019;3:1.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Raaschou P, Söderling J, Turesson C, Askling J. Tumor necrosis factor inhibitors and cancer recurrence in Swedish patients with rheumatoid arthritis: a nationwide population-based cohort study. Ann Intern Med. 2018;169(5):291–9.

    Article  PubMed  Google Scholar 

  41. Raaschou P, Frisell T, Askling J. TNF inhibitor therapy and risk of breast cancer recurrence in patients with rheumatoid arthritis: a nationwide cohort study. Ann Rheum Dis. 2015;74(12):2137–43.

    Article  CAS  PubMed  Google Scholar 

  42. Choi B, Park HJ, Song Y-K, Oh Y-J, Kim I-W, Oh JM. The risk of newly diagnosed cancer in patients with rheumatoid arthritis by TNF inhibitor use: a nationwide cohort study. Arthritis Res Ther. 2022;24(1):191.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Cho S-K, Lee J, Han M, Bae S-C, Sung Y-K. The risk of malignancy and its incidence in early rheumatoid arthritis patients treated with biologic DMARDs. Arthritis Res Ther. 2017;19(1):277.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell. 2010;140(6):883–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Jia X-Y, Chang Y, Wei F, Dai X, Wu Y-J, Sun X-J, Xu S, Wu H-X, Wang C, Yang X-Z, et al. CP-25 reverses prostaglandin E4 receptor desensitization-induced fibroblast-like synoviocyte dysfunction via the G protein-coupled receptor kinase 2 in autoimmune arthritis. Acta Pharmacol Sin. 2019;40(8):1029–39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Yang X, Zhao Y, Jia X, Wang C, Wu Y, Zhang L, Chang Y, Wei W. CP-25 combined with MTX/LEF ameliorates the progression of adjuvant-induced arthritis by the inhibition on GRK2 translocation. Biomed Pharmacother. 2019;110:834–43.

    Article  CAS  PubMed  Google Scholar 

  47. Ma Y, Han C-C, Huang Q, Sun W-Y, Wei W. GRK2 overexpression inhibits IGF1-induced proliferation and migration of human hepatocellular carcinoma cells by downregulating EGR1. Oncol Rep. 2016;35(5):3068–74.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors appreciate Qinyi Xu (MA, college of comparative law, China University of Political Science and Law) for editing the manuscript.

Funding

This work was supported by a grant from the 2020–2021 Popularization of Science and Technology Innovation Special Project of Guangdong Province of China (2020A1414070007); the Science and Technology Program of Guangzhou, China (202206010103); and the Natural Science Foundation of Guangdong Province (2022A1515012469).

Author information

Author notes

  1. Yuzhuo Zhang, Yudong Zhang, and Peng He are joint first authors.

Authors and Affiliations

  1. Guangzhou Medical University, Guangzhou, 511436, Guangdong, China

    Yuzhuo Zhang, Peng He, Fan Ge & Zhenyu Huo

  2. Department of Thoracic Surgery & Department of Cardiothoracic Surgery of East Division, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510062, Guangdong, China

    Yudong Zhang

  3. National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Fan Ge & Zhenyu Huo

  4. Department of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China

    Guibin Qiao

  5. Shantou University Medical College, Shantou, China

    Guibin Qiao

  6. The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510515, China

    Guibin Qiao

Authors
  1. Yuzhuo Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yudong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peng He
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fan Ge
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhenyu Huo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guibin Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

This study was proposed by ZYZ. ZYZ and HP extracted the data. ZYZ and HP analyzed the data. ZYZ and ZYD wrote the initial draft of the manuscript. HZY and QGB revised the final manuscript. All authors have contributed to the revision of the manuscript. ZYZ is the guarantor. The final manuscript was approved by all authors.

Corresponding authors

Correspondence to Fan Ge, Zhenyu Huo or Guibin Qiao.

Ethics declarations

Ethics approval and consent to participate

This study has been approved by the Institutional Review Board (IRB) of Guangdong.

Provincial People’s Hospital. Because the study used public databases, the ethics committee waived informed consent for all patients.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1:

Table S1. Selecting instrumental variables related to RA by GWAS threshold (p-value < 5 × 10–8) (58 SNPs). SNP, single nucleotide polymorphism; Chr, chromosome; EA, effect allele; OA, other allele, SE, standard error. aR2 were calculated using the following formula: 2 × MAF × (1-MAF) × Beta2, where MAF is the minor allele frequency, Beta is the estimated effect on hip osteoarthritis. bF were calculated using the following formula: R2(N-2)/(1- R2), where R2 is the proportion of variance in hip osteoarthritis explained by each instrument and N is the sample size of the GWAS for the hip osteoarthritis association.

Additional file 2:

Table S2. Verification of the associations between RA and HCC in eastern Asia populations. SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; IVW, inverse-variance-weighted; MR, Mendelian randomization; MR-PRESSO, MR pleiotropy residual sum and outlier. ap-value of the intercept from MR Egger regression analysis. bp-value of MR-PRESSO global test.

Additional file 3:

Table S3. Details of studies of RA and HCC for European populations.

Additional file 4:

Table S4. Effect estimates of the associations between RA and HCC in European populations. SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; IVW, inverse-variance-weighted; MR, Mendelian randomization; MR-PRESSO, MR pleiotropy residual sum and outlier. ap-value of the intercept from MR Egger regression analysis. bp-value of MR-PRESSO global test.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Zhang, Y., He, P. et al. The genetic liability to rheumatoid arthritis may decrease hepatocellular carcinoma risk in East Asian population: a Mendelian randomization study. Arthritis Res Ther 25, 49 (2023). https://0-doi-org.brum.beds.ac.uk/10.1186/s13075-023-03029-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s13075-023-03029-3

Keywords

Arthritis Research & Therapy

ISSN: 1478-6362

Contact us