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Vol. 79. (In progress)
(January - December 2024)
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Vol. 79. (In progress)
(January - December 2024)
Original articles
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Association between inflammatory bowel disease and the risk of parenteral malignancies: A two-sample Mendelian randomization study
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435
Peizhu Su, Yilin Wang, Huiwen Huang, Qinghua Lu, Qinyan Wu, Zhaotao Li
Corresponding author
LZT_foshanfirsthsp@outlook.com

Corresponding author.
Department of Digestive Disease, The First People's Hospital of Foshan City, Guangdong, P.R. China
Highlights

  • To provide some reference for parenteral malignancy prevention in patients with IBD.

  • IBD was potentially associated with diffuse large B-cell lymphoma and skin cancers.

  • Some information on preventing parenteral malignancies in IBD was provided.

  • Further studies are needed to explore mechanisms of the effect of IBD on skin cancers.

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Tables (3)
Table 1. Information of the data source for IBD and parenteral malignancies.
Table 2. SNPs selection and test for horizontal pleiotropy, strength, and heterogeneity.
Table 3. Association between IBD and parenteral malignancies.
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Additional material (1)
Abstract
Aim

Using Mendelian Randomization (MR) analysis to investigate the potential causal association between Inflammatory Bowel Disease (IBD) and the occurrence of parenteral malignancies, in order to provide some reference for the parenteral malignancy prevention in patients with IBD.

Methods

This was a two-sample MR study based on independent genetic variants strongly linked to IBD selected from the Genome-Wide Association Study (GWAS) meta-analysis carried out by the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC). Parenteral malignancy cases and controls were obtained from the FinnGen consortium and the UK Biobank (UKB) release data. Inverse Variance Weighted (IVW), weighted median, MR-Egger, and strength test (F) were utilized to explore the causal association of IBD with parenteral malignancies. In addition, Cochran's Q statistic was performed to quantify the heterogeneity of Instrumental Variables (IVs).

Results

The estimates of IVW showed that patients with IBD had higher odds of diffuse large B-cell lymphoma (OR = 1.2450, 95% CI: 1.0311‒1.5034). UC had potential causal associations with non-melanoma skin cancer (all p < 0.05), melanoma (OR = 1.0280, 95% CI: 0.9860‒1.0718), and skin cancer (OR = 1.0004, 95% CI: 1.0001‒1.0006). Also, having CD was associated with higher odds of non-melanoma skin cancer (all p < 0.05) and skin cancer (OR = 1.0287, 95% CI: 1.0022‒1.0559). In addition, results of pleiotropy and heterogeneity tests indicated these results are relatively robust.

Conclusions

IBD has potential causal associations with diffuse large B-cell lymphoma and skin cancers, which may provide some information on the prevention of parenteral malignancies in patients with IBD. Moreover, further studies are needed to explore the specific mechanisms of the effect of IBD on skin cancers.

Keywords:
Inflammatory bowel disease
Parenteral malignancies
Skin cancer
Mendelian randomization study
Causal relationship
Full Text
Introduction

Inflammatory Bowel Disease (IBD) is an immune-mediated intestinal tract disease, including Crohn's Disease (CD) and Ulcerative Colitis (UC), which is related to the complex interaction between the genetic, environmental, gut microbiome, and immune factors.1 Malignancy is now the second leading cause of mortality in patients with IBD.2 Due to the influencing of chronic inflammation in the gut, patients with IBD are more likely to develop Colorectal Cancer (CRC) and other intestinal malignancies, whereas the association between IBD and parenteral malignancies is unclear.3 Studies have shown that the majority of patients with IBD had parenteral malignancies, and the incidence was gradually increasing.4-6 With the widespread use of immunosuppressive therapy in IBD, the impaired immune environment of patients may weaken their defense against tumors, so systemic inflammation and long-term immunosuppression caused by IBD may lead to an increased risk of parenteral malignancy.5 In addition, the comorbidities and parenteral symptoms of IBD may increase the risk of parenteral malignancy as well.7 At present, some observational studies and related meta-studies have reported the risk of specific site malignant tumors in patients with IBD, but no consistent results have been obtained.8,9 Moreover, traditional epidemiological studies are susceptible to confounding factors and causal inversion, and the true relationship between IBD and the risk of parenteral malignancies is unrevealed.

Mendelian Randomization (MR) uses genetic variation as an instrumental variable for exposure to investigate causal associations between exposures and diseases.10 Because of Mendel's law of segregation and independent classification, the results of MR analyses are less susceptible to confounding bias than those of traditional observational epidemiological studies.11 Also, since the genetic code is not influenced by environmental factors or preclinical diseases, and is less susceptible to bias caused by reverse causation. Therefore, MR analysis is a good choice for the exploration on the causality of IBD with the occurrence of parenteral malignancies. In the latest MR study conducted by Gao et al.12 on the causal relationship between IBD and extracolonic cancers in different sites, they found IBD may play a risk role in the development of both the oral cavity and breast cancer. However, there are some unresolved problems with the robustness of the results in Gao's study, which are associated with the horizontal pleiotropy and heterogeneity (where the physical distance ≥ 5000 kb and the Linkage Disequilibrium [LD] r2 < 0.01).

Herein, based on the previous study, the authors conducted a two‐sample MR study to investigate the causal association between IBD to parenteral malignancies, with a stricter LD threshold (r2 = 0.001 and clumping distance of 10,000 kb). In addition, the authors calculated the power of the Inverse Variance Weighted (IVW) test, in order to improve the robustness of positive results. The authors hope the present findings may further verify the causal association between IBD and parenteral malignancies.

MethodsData sources

Figure 1 shows the study procedure. In this two-sample MR analysis, information on IBD and parenteral malignancies were extracted from the corresponding Genome-Wide Association Studies (GWASs): https://gwas.mrcieu.ac.uk/. Genetic variants of the IBD were extracted from the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC). IIBDGC is the largest global IBD genetics database, in which the authors obtained SNPs from the European populations. Parenteral malignancies cases and controls were obtained from the FinnGen consortium (https://finngen.gitbook.io/documentation/) as well as from the UK Biobank (UKB) (https://www.ukbiobank.ac.uk/). More information on study exposure and outcomes are shown in Table 1. Data in the current study are publicly available and de-identified. Each GWAS involved has obtained informed consent from participants and had ethical approval from their respective institutions. Therefore, no ethical approval from the Institutional Review Board (IRB) of The First People's Hospital of Foshan City was required. This Study follows the STROBE Statement.

Fig. 1.

Flowchart of the study procedure.

(0.09MB).
Table 1.

Information of the data source for IBD and parenteral malignancies.

Variables  GWAS ID
Exposures     
IBD  ieu-a-294   
UC  ieu-a-32   
CD  ieu-a-10   
Outcomes     
Breast cancer  finn-b-C3_BREAST  ukb-b-16890 
Glioma  finn-b-C3_GBM   
Brain cancer  finn-b-C3_BRAIN   
Meningioma  finn-b-C3_MENINGES   
Thyroid cancer  finn-b-C3_THYROID_GLAND   
Oral and pharyngeal cancer  finn-b-C3_LIP_ORAL_PHARYNX  ieu-b-4961 
Urinary organs cancer  finn-b-C3_URINARY_TRACT  ukb-d-C3_URINARY_TRACT 
Bladder cancer  finn-b-C3_BLADDER  ukb-d-C67 
Kidney cancer (except renal pelvis)  finn-b-C3_KIDNEY_NOTRENALPELVIS  ukb-b-1316 
Skin cancer  finn-b-C3_SKIN  ukb-b-12339 
Melanoma  finn-b-C3_MELANOMA_SKIN  ieu-b-4969 
Non-melanoma skin cancer  finn-b-C3_OTHER_SKIN  ieu-b-4959 
Respiratory system cancers  finn-b-C3_RESPIRATORY_INTRATHORACIC  ukb-d-C3_RESPIRATORY_INTRATHORACIC 
Bronchogenic carcinoma and lung cancer  finn-b-C3_BRONCHUS_LUNG  ukb-d-C34 
Non-small cell lung cancer  finn-b-C3_LUNG_NONSMALL   
Small cell lung cancer  finn-b-C3_SCLC   
Gastric carcinoma  finn-b-C3_STOMACH   
Esophagus cancer  finn-b-C3_OESOPHAGUS   
Liver cancer  finn-b-C3_LIVER_INTRAHEPATIC_BILE_DUCTS   
Pancreatic cancer  finn-b-C3_PANCREAS   
Female genital organs cancers  finn-b-C3_FEMALE_GENITAL  ukb-d-C_FEMALE_GENITAL 
Cervical cancer  finn-b-C3_CERVIX_UTERI  ukb-b-8777 
Uterine cancer  finn-b-C3_CORPUS_UTERI  ukb-d-C3_CORPUS_UTERI 
Ovarian cancer  finn-b-C3_OVARY  ukb-b-18157 
Hematopoietic system cancer  finn-b-CD2_PRIMARY_LYMPHOID_HEMATOPOIETIC  leukaemiaukb-d-C3_PRIMARY_LYMPHOID_HEMATOPOIETIC 
  finn-b-CD2_HODGKIN_LYMPHOMA   
Diffuse large B-cell lymphoma  finn-b-C3_DLBCL   
Follicular lymphoma  finn-b-CD2_FOLLICULAR_LYMPHOMA   
Mature T/NK-cell lymphomas  finn-b-CD2_TNK_LYMPHOMA   
Lymphoid leukaemia  finn-b-CD2_LYMPHOID_LEUKAEMIA   
Multiple myeloma and malignant plasma cell cancers  finn-b-CD2_MULTIPLE_MYELOMA_PLASMA_CELL  ieu-b-4957 
Male genital organs cancers  finn-b-C3_MALE_GENITAL  ukb-d-C_MALE_GENITAL 
Prostatic cancer  finn-b-C3_PROSTATE  ukb-b-2160 

IBD, Inflammatory Bowel Disease; GWAS, Genome Wide Association Study, UC, Ulcerative Colitis; CD, Crohn's Disease.

Single nucleotide polymorphisms selection

SNPs that significantly linked to IBD were selected as potential IVs. The threshold of p < 5.0 × 10−8 was used to select the IVs. The authors removed SNPs that Minor Allele Frequency (MAF) ≤ 0.01. The LD threshold and the clumping distance were respectively r2 = 0.001 and 10,000 kb. MR-Egger regression test was applied to monitor potential horizontal pleiotropy effect, that is the confounding effect resulted from other diseases, and could violate the MR analysis’ second assumption.13 The significant intercept item in MR-Egger represents there is a pleiotropy. Besides, due to the principle of MR is to ensure a same allele corresponds effects between SNPs and exposure/outcome, palindromic SNPs need to be deleted.

The assumptions of MR analysis

The MR analysis must conform to three important assumptions to minimize the impact of bias on the results. Firstly, the IVs must be independent of confounding factors related to exposure and outcome. Secondly, IVs should be significantly associated with the exposure. The authors estimated the relationship strength of IBD with IVs with the formulas: r2 = 2 * minor allele frequency (MAF) * (1 - MAF) * β * β / SD2; F = ((Sample size - numbers of IVs - 1) / numbers of IVs) * (r2 / (1 - r2)), in which β was the regression coefficient for IBD and IVs and SD represented standard deviation. F < 10 is considered as there is a weak association between IVs and exposure. Thirdly, IVs only affect outcomes through exposure, namely, no horizontal pleiotropy effect of IVs on the outcome.

Statistical analysis

Study statistical analysis was performed using R version 4.2.0 (Institute for Statistics and Mathematics, Vienna, Austria). MR analysis on potential causality from IBD to parenteral malignancies was explored through the R package “TwoSampleMR”; p < 0.05 means the evidence for potential causal effect was statistically significant. The calculation for the causal effect values used the IVW test, which is the primary method to acquire unbiased estimates when no horizontal pleiotropy exists. In addition, weighted-median method relatively provides a robust and consistent estimate of the effect even if nearly 50% of genetic variants were invalid instruments. Odds Ratios (ORs) and 95% Confidence Intervals (CIs) were used to express the effect size.

Test for heterogeneity was used Cochrane's Q method, IVs with p < 0.05 were considered as non-heterogeneous.14 MR-Egger regression's intercept examined the presence of potential pleiotropy in IVs, and p > 0.05 was recognized as no horizontal pleiotropy. Moreover, the authors calculated the test power of IVW method using the calculation tool on the webpage: https://shiny.cnsgenomics.com/mRnd/.

ResultsInstrumental variables selection

The authors respectively identified 7,495 SNPs as IVs for IBD, 6,616 SNPs as IVs for UC, and 2,860 SNPs as IVs for CD. After deleting LD and dropping all palindromic SNPs, the final numbers of SNPs in different outcomes are shown in Table 2. Then the authors evaluated the horizontal pleiotropy effect of both exposures and outcomes. For IBD, UC, and CD, none of the IVs in the analyses had horizontal pleiotropy or heterogeneity after removing pleiotropic SNPs that were identified respectively by the MR-Egger intercept test and MR-Egger Q test (all p > 0.05).

Table 2.

SNPs selection and test for horizontal pleiotropy, strength, and heterogeneity.

ExposuresPhenotypesOutcomesSelected SNPs (p < 5×10−8)Omitted LD SNPsDrop all palindromic SNPsHorizontal pleiotropic  HeterogeneityStrength 
MR-Egger intercept test, p  MR-Egger Q, p  IVW, p  F-value, R2 
IBDOthersBreast cancer  7495  132  125  -0.01, 0.09  153.83, 0.01  157.76, 0.01  31.858,0.061 
Glioma  7495  132  127  -0.02, 0.56  90.99, 0.96  91.33, 0.96  32.14,0.062 
Brain cancer  7495  132  125  -0.01, 0.41  94.63, 0.91  95.32, 0.91  32.672,0.062 
Meningioma  7495  132  129  -0.01, 0.72  113.55, 0.60  113.68, 0.62  32.288,0.064 
Thyroid cancer  7495  132  127  0.01, 0.55  91.72, 0.96  92.08, 0.96  32.733,0.063 
Oral and pharyngeal cancer  7495  132  127  0.02, 0.57  110.19, 0.63  110.51, 0.65  32.48,0.063 
Urinary systemUrinary organs cancer  7495  132  128  -0.00, 0.74  112.17, 0.61  112.28, 0.63  32.457,0.063 
Bladder cancer  7495  132  125  -0.01, 0.25  87.72, 0.97  89.07, 0.97  32.182,0.061 
Kidney cancer (except renal pelvis)  7495  132  125  0.01, 0.35  119.53, 0.39  120.43, 0.40  31.793,0.061 
SkinSkin cancer  7495  132  120  0.00, 0.98  110.60, 0.44  110.60, 0.47  33.015,0.06 
Melanoma  7495  132  129  0.00, 0.98  97.14, 0.92  97.14, 0.93  32.462,0.064 
Non-melanoma skin cancer  7495  132  120  0.00, 0.98  110.64, 0.44  110.64, 0.47  33.015,0.06 
Respiratory system and intrathoracic organsRespiratory system cancers  7495  132  123  0.00, 0.63  99.02, 0.80  99.26, 0.82  31.488,0.059 
Bronchogenic carcinoma and lung cancer  7495  132  121  -0.00, 0.65  90.58, 0.91  90.78, 0.92  32.045,0.059 
Non-small cell lung cancer  7495  132  127  -0.01, 0.12  116.77, 0.46  119.28, 0.42  32.691,0.063 
Small cell lung cancer  7495  132  127  0.02, 0.37  101.70, 0.83  102.51, 0.83  32.618,0.063 
Digestive systemGastric carcinoma  7495  132  130  -0.00, 0.91  104.66, 0.82  104.68, 0.84  32.331,0.064 
Esophagus cancer  7495  132  129  -0.02, 0.42  106.40, 0.77  107.06, 0.78  31.998,0.063 
Liver cancer  7495  132  125  0.00, 0.9  92.95, 0.93  92.97, 0.93  32.157,0.061 
Pancreatic cancer  7495  132  130  -0.00, 0.83  112.04, 0.66  112.09, 0.68  32.331,0.064 
Female genital organsFemale genital organs cancers  7495  132  127  0.01, 0.23  97.09, 0.90  98.57, 0.89  32.503,0.063 
Cervical cancer  7495  132  126  0.01, 0.44  98.86, 0.86  99.46, 0.86  32.099,0.062 
Uterine cancer  7495  132  125  0.01, 0.55  93.39, 0.92  93.74, 0.93  32.978,0.063 
Ovarian cancer  7495  132  128  -0.01, 0.56  103.07, 0.82  103.40, 0.83  32.071,0.063 
Primary lymphoid and hematopoietic systemHematopoietic system cancer  7495  132  127  0.01, 0.38  147.46, 0.03  148.44, 0.03  32.846,0.064 
Hodgkin lymphoma  7495  132  122  0.00, 0.92  100.10, 0.78  100.11, 0.80  32.908,0.061 
Diffuse large B-cell lymphoma  7495  132  129  -0.04, 0.15  119.13, 0.45  121.27, 0.42  32.123,0.063 
Follicular lymphoma  7495  132  126  -0.01, 0.41  128.21, 0.19  128.98, 0.19  31.277,0.06 
Mature T/NK-cell lymphomas  7495  132  129  -0.02, 0.52  106.17, 0.77  106.58, 0.79  31.928,0.063 
Lymphoid leukaemia  7495  132  129  0.03, 0.06  105.33, 0.81  108.81, 0.76  32.582,0.064 
Multiple myeloma and malignant plasma cell cancers  7495  132  126  0.01, 0.72  106.39, 0.70  106.52, 0.72  32.018,0.062 
Male genital organsMale genital organs cancers  7495  132  121  0.01, 0.14  102.09, 0.69  104.25, 0.66  33.259,0.061 
Prostatic cancer  7495  132  122  0.00, 0.46  114.96, 0.38  115.54, 0.39  32.938,0.061 
UCOthersBreast cancer  6616  38  35  0.00, 0.75  33.50, 0.18  33.63, 0.21  17.389,0.022 
Glioma  6616  38  35  0.07, 0.43  14.34, 0.98  14.99, 0.99  20.099,0.026 
Brain cancer  6616  38  35  0.03, 0.46  23.78, 0.64  24.33, 0.66  19.171,0.024 
Meningioma  6616  38  35  0.03, 0.34  17.47, 0.92  18.41, 0.92  19.215,0.025 
Thyroid cancer  6616  38  35  0.01, 0.68  22.69, 0.75  22.87, 0.78  20.099,0.026 
Oral and pharyngeal cancer  6616  38  36  0.05, 0.53  28.48, 0.44  28.90, 0.47  19.54,0.026 
Urinary systemUrinary organs cancer  6616  38  36  -0.02, 0.25  23.90, 0.69  25.30, 0.66  19.54,0.026 
Bladder cancer  6616  38  35  -0.03, 0.25  11.50, 1.00  12.90, 1.00  20.099,0.026 
Kidney cancer (except renal pelvis)  6616  38  36  -0.00, 0.93  33.08, 0.23  33.09, 0.27  19.54,0.026 
SkinSkin cancer  6616  38  34  -0.02, 0.05  19.53, 0.81  23.87, 0.64  17.512,0.022 
Melanoma  6616  38  36  -0.10, 0.27  23.05, 0.73  24.30, 0.71  19.54,0.026 
Non-melanoma skin cancer  6616  38  34  -0.02, 0.05  19.54, 0.81  23.84, 0.64  17.512,0.022 
Respiratory system and intrathoracic organsRespiratory system cancers  6616  38  34  -0.00, 0.86  27.11, 0.46  27.14, 0.51  19.971,0.025 
Bronchogenic carcinoma and lung cancer  6616  38  35  -0.02, 0.45  30.18, 0.35  30.80, 0.37  20.099,0.026 
Non-small cell lung cancer  6616  38  36  -0.04, 0.11  27.10, 0.51  29.91, 0.42  19.54,0.026 
Small cell lung cancer  6616  38  35  -0.02, 0.81  16.53, 0.94  16.59, 0.96  19.726,0.025 
Digestive systemGastric carcinoma  6616  38  36  0.00, 0.93  29.14, 0.41  29.15, 0.46  19.54,0.026 
Esophagus cancer  6616  38  35  -0.08, 0.26  34.54, 0.15  36.26, 0.14  19.47,0.025 
Liver cancer  6616  38  35  -0.06, 0.21  22.87, 0.69  24.52, 0.65  19.197,0.024 
Pancreatic cancer  6616  38  36  -0.06, 0.11  21.17, 0.82  23.92, 0.73  19.54,0.026 
Female genital organsFemale genital organs cancers  6616  38  36  0.02, 0.14  29.95, 0.37  32.48, 0.30  19.54,0.026 
Cervical cancer  6616  38  33  0.03, 0.25  25.74, 0.48  27.10, 0.46  17.974,0.022 
Uterine cancer  6616  38  35  0.00, 0.9  17.13, 0.93  17.15, 0.95  19.918,0.025 
Ovarian cancer  6616  38  34  -0.02, 0.64  20.47, 0.81  20.70, 0.84  20.301,0.025 
Primary lymphoid and hematopoietic systemHematopoietic system cancer  6616  38  34  0.00, 0.93  24.84, 0.53  24.84, 0.58  17.308,0.021 
Hodgkin lymphoma  6616  38  35  -0.02, 0.72  31.34, 0.26  31.49, 0.30  17.389,0.022 
Diffuse large B-cell lymphoma  6616  38  34  -0.05, 0.52  20.47, 0.77  20.89, 0.79  17.299,0.021 
Follicular lymphoma  6616  38  33  -0.00, 0.97  30.74, 0.24  30.74, 0.28  19.723,0.024 
Mature T/NK-cell lymphomas  6616  38  35  0.10, 0.18  24.19, 0.62  26.05, 0.57  19.152,0.024 
Lymphoid leukaemia  6616  38  35  0.04, 0.28  28.08, 0.46  29.29, 0.45  20.099,0.026 
Multiple myeloma and malignant plasma cell cancers  6616  38  34  -0.06, 0.08  25.01, 0.57  28.28, 0.45  20.505,0.025 
Male genital organsMale genital organs cancers  6616  38  35  0.01, 0.52  22.35, 0.72  22.77, 0.74  19.057,0.024 
Prostatic cancer  6616  38  35  0.01, 0.52  22.62, 0.71  23.05, 0.73  19.057,0.024 
CDOthersBreast cancer  2860  104  96  -0.00, 0.76  104.52, 0.16  104.62, 0.17  19.884,0.058 
Glioma  2860  104  101  0.04, 0.28  93.01, 0.57  94.19, 0.56  20.173,0.062 
Brain cancer  2860  104  99  0.00, 0.84  97.09, 0.39  97.13, 0.42  20.15,0.061 
Meningioma  2860  104  101  -0.00, 0.86  99.84, 0.37  99.87, 0.40  20.222,0.062 
Thyroid cancer  2860  104  100  0.01, 0.42  89.58, 0.64  90.23, 0.65  20.396,0.062 
Oral and pharyngeal cancer  2860  104  102  0.03, 0.34  73.16, 0.97  74.09, 0.97  20.326,0.063 
Urinary systemUrinary organs cancer  2860  104  101  -0.01, 0.45  110.78, 0.14  111.43, 0.15  20.304,0.062 
Bladder cancer  2860  104  96  -0.01, 0.47  83.72, 0.69  84.24, 0.71  20.337,0.059 
Kidney cancer (except renal pelvis)  2860  104  97  -0.01, 0.6  88.62, 0.58  88.89, 0.60  19.478,0.057 
SkinSkin cancer  2860  104  98  -0.00, 0.69  92.82, 0.49  92.99, 0.51  20.446,0.061 
Melanoma  2860  104  101  0.04, 0.31  83.45, 0.82  84.48, 0.81  20.503,0.063 
Non-melanoma skin cancer  2860  104  98  -0.00, 0.69  93.05, 0.48  93.21, 0.50  20.446,0.061 
Respiratory system and intrathoracic organsRespiratory system cancers  2860  104  99  0.01, 0.37  101.31, 0.29  102.18, 0.29  20.202,0.061 
Bronchogenic carcinoma and lung cancer  2860  104  97  0.00, 0.68  79.83, 0.81  80.00, 0.83  20.347,0.06 
Non-small cell lung cancer  2860  104  100  -0.00, 0.9  114.42, 0.09  114.44, 0.10  20.404,0.062 
Small cell lung cancer  2860  104  100  -0.01, 0.72  86.60, 0.72  86.73, 0.74  20.048,0.061 
Digestive systemGastric carcinoma  2860  104  103  -0.02, 0.27  80.06, 0.91  81.31, 0.90  20.232,0.063 
Esophagus cancer  2860  104  102  -0.05, 0.06  95.57, 0.52  99.27, 0.45  20.183,0.062 
Liver cancer  2860  104  98  0.00, 0.91  95.98, 0.40  96.00, 0.42  19.997,0.059 
Pancreatic cancer  2860  104  102  0.01, 0.5  94.89, 0.54  95.35, 0.56  20.275,0.063 
Female genital organsFemale genital organs cancers  2860  104  102  -0.00, 0.72  96.28, 0.50  96.41, 0.53  20.352,0.063 
Cervical cancer  2860  104  99  -0.02, 0.11  81.63, 0.81  84.21, 0.78  20.415,0.061 
Uterine cancer  2860  104  101  0.02, 0.14  95.31, 0.50  97.58, 0.46  20.416,0.063 
Ovarian cancer  2860  104  102  -0.01, 0.46  91.09, 0.65  91.65, 0.66  20.063,0.062 
Primary lymphoid and hematopoietic systemHematopoietic system cancer  2860  104  98  0.01, 0.44  85.09, 0.71  85.69, 0.72  20.571,0.061 
Hodgkin lymphoma  2860  104  101  0.04, 0.07  107.44, 0.20  111.32, 0.15  20.28,0.062 
Diffuse large B-cell lymphoma  2860  104  101  -0.01, 0.75  87.64, 0.72  87.75, 0.74  20.265,0.062 
Follicular lymphoma  2860  104  100  -0.02, 0.17  82.30, 0.82  84.25, 0.80  19.239,0.058 
Mature T/NK-cell lymphomas  2860  104  103  0.03, 0.36  104.92, 0.30  105.84, 0.30  20.232,0.063 
Lymphoid leukaemia  2860  104  101  0.02, 0.26  80.92, 0.86  82.20, 0.86  19.788,0.061 
Multiple myeloma and malignant plasma cell cancers  2860  104  98  -0.01, 0.72  92.18, 0.50  92.32, 0.53  20.521,0.061 
Male genital organsMale genital organs cancers  2860  104  100  0.00, 0.71  82.23, 0.82  82.37, 0.84  20.459,0.062 
Prostatic cancer  2860  104  100  0.00, 0.7  84.75, 0.77  84.91, 0.78  20.459,0.062 

SNP, Single Nucleotide Polymorphism; LD, Linkage Disequilibrium; MR, Mendelian Randomization; IVW, Inverse Variance Weighted; F, ((Sample size - numbers of IVs - 1) / numbers of IVs) * (r2 / (1 - r2)), r2 = 2 * minor allele frequency (MAF) * (1 - MAF) * β * β / SD2; IBD, Inflammatory Bowel Disease; UC, Ulcerative Colitis; CD, Crohn's Disease.

Two-sample MR analysis

Supplementary Table 1 was the analysis results of the potential causal relationship between IBD and parenteral malignancies through three different methods. In brief, Table 3 shows the significant association between IBD and parenteral malignancies. Patients with IBD had higher odds of diffuse large B-cell lymphoma (OR = 1.2450, 95% CI: 1.0311‒1.5034). Among the population in the FinnGen, having UC was associated with higher odds of both non-melanoma skin cancer (OR = 1.0449, 95% CI: 1.0030‒1.0886) and melanoma (OR = 1.0280, 95% CI: 0.9860‒1.0718). Also, having CD was associated with higher odds of both non-melanoma skin cancer (OR = 1.0288, 95% CI: 1.0023‒1.0560) and skin cancer (OR = 1.0287, 95% CI: 1.0022‒1.0559). In addition, these results were relatively robust due to all powers of the IVW method ≥ 98%.

Table 3.

Association between IBD and parenteral malignancies.

ExposuresOutcomesIVW
OR (95% CI)  Power (%) 
IBDFinnGen       
Diffuse large B-cell lymphoma  1.2450 (1.0311‒1.5034)  0.023  100 
UCFinnGen       
Non-melanoma skin cancer  1.0449 (1.0030‒1.0886)  0.035  100 
Melanoma  1.0280 (0.9860‒1.0718)  0.019  98 
Skin cancer  0.8581 (0.6283‒1.1720)  0.336   
UKB       
Non-melanoma skin cancer  1.0034 (1.0015‒1.0052)  <0.001 
Melanoma  1.0003 (0.9998‒1.0008)  0.311   
Skin cancer  1.0004 (1.0001‒1.0006)  0.007 
CDFinnGen       
Non-melanoma skin cancer  1.0288 (1.0023‒1.0560)  0.034  99 
Melanoma  1.0004 (0.7892‒1.2680)  0.998   
Skin cancer  1.0287 (1.0022‒1.0559)  0.033  99 
UKB       
Non-melanoma skin cancer  1.0017 (1.0001‒1.0033)  0.033 
Melanoma  1.0004 (0.9999 ‒1.0008)  0.076   
Skin cancer  1.0002 (0.9999 ‒1.0005)  0.078   

IBD, Inflammatory Bowel Disease; IVW, Inverse Variance Weighted; OR, Odds Ratio, CI, Confidence Interval; UC, Ulcerative Colitis; UKB, the UK Biobank; CD, Crohn's Disease.

Among the UKB population, patients who had UC or CD both seemed to have higher odds of non-melanoma skin cancer (all p < 0.05), whereas having UC was additionally associated with higher odds of skin cancer (OR = 1.0004, 95% CI: 1.0001‒1.0006). Although the power of results in the UKB population was less than 10%, the authors additionally performed the heterogeneity and pleiotropy tests (Supplementary Table 2 and Supplementary Table 3). The findings suggested that no heterogeneity and pleiotropy were found.

Discussion

The authors conducted a two-sample MR analysis to investigate the potential causal relationship between IBD and parenteral malignancies. Based on the large-scale summary statistics of independent genetic variants that are closely linked to IBD, the authors found patients with IBD have higher odds of both diffuse large B-cell lymphoma and skin cancers, including non-melanoma skin cancer and melanoma.

In the current study, the authors included multiple systems in extraintestinal manifestations of IBD, such as urinary, respiratory, digestive, genital, and hematopoietic systems. Previous studies have proposed that it is of great importance and urgency to clarify the relationship between IBD and parenteral malignancies. In a recent two-sample MR analysis, Lu et al. demonstrated15 that IBD, especially CD, is causally responsible for diffuse large B-cell lymphoma. The present study further proved Lu's results. In a large-sample prospective cohort study among adults from the UKB conducted by Wu et al.16 showed that IBD may be associated with an increased risk of overall cancer compared with non-IBD, and an increased risk of digestive cancers, non-melanoma skin cancer, and male genital cancers were observed in patients with IBD. These findings in UKB populations similarly indicated a potential causal relationship of UC with CD and non-melanoma skin cancer. This study used the MR analysis in addition to Wu's research, which is less susceptible to confounding bias than that of traditional observational epidemiological studies, and found no heterogeneity and pleiotropy in the potential causal association between UC and CD and non-melanoma skin cancer. Moreover, Gao et al.12 also performed a MR study on causality from IBD to 32 site-specific parenteral malignancies, and revealed that IBD has potential causal associations with oral cavity cancer as well as breast cancer. Unfortunately, although the authors explored these relationships in adults from both the FinnGen and UKB databases, we concluded potential causalities between IBD and diffuse large B-cell lymphoma and skin cancers instead of oral cavity cancer or breast cancer. The possible reasons to explain these differences in results between ours and Gao's may be that due to neither the UKB nor FinnGen databases containing the separate GWAS of oral cavity and pharynx cancers, Gao chose a previous conducted GWAS as the discovery cohort.17 The authors used the combined data on oral cavity and pharynx cancer, which may limit the true effect of IBD on the occurrence of oral cavity cancers. Also, data sources for cancer in Gao's study were from different databases (more than 5 databases) which may have caused the population heterogeneity. In the present study, the authors additionally calculated the power of the IVW method (powers of results in FinnGen population ≥ 98%) as well as performed the heterogeneity and pleiotropy tests on results among the UKB population (all p > 0.05). Since the relative robustness of the present findings, the authors may supplement Gao's results that IBD has a potential causal relationship with diffuse large B-cell lymphoma, melanoma, and non-melanoma skin cancer.

The underlying mechanisms of causal associations between IBD and diffuse large B-cell lymphoma and skin cancers are unclear, and speculations from previous studies are summarized as follows. Immune dysregulation as well as chronic inflammatory response play significant roles in IBD's development and progression.18,19 In autoimmunity and inflammation conditions, B cells are exposed to multiple types of antigens, which can activate B-cell receptor signaling pathways and also sustain response, proliferation, and clonal amplification. Besides, an increased risk of inherent genetic instability events in lymphocytes during B-cell maturation may in turn lead to malignant lymphoma ultimately development.20,21 IBD has been reported to be associated with an increased risk of melanoma, independent of the use of biological therapy.22 The risk of melanoma increased among patients with both CC (RR = 1.80) and UC (RR = 1.23). Also, patients with IBD, especially those who receive thiopurines, are at risk for non-melanoma skin cancer.23 The potential mechanisms of the causal relationship from IBD to melanoma and non-melanoma skin cancer are possibly related to epigenetic alterations, such as DNA methylation, histone hyperacetylation, and non-coding RNA in the disease progression,24 as well as the disturbance of the microbiota balance in IBD, for example the Staphylococcus aureus, Streptococcus pyogenes, Pseudomonas aeruginosa strains, β-Human papillomavirus genotypes, may contribute to the induction of a state of chronic self-maintaining inflammation, leading to skin cancers.25 Nevertheless, the specific mechanism that IBD results in skin cancers needs to be further verified.

As mentioned, MR may be a superior research design to confirm the causality from potential risk factors to diseases of interest compared with traditional observational studies. By exploring the potential causal relationship between IBD and parenteral malignancies, these results may facilitate the recommendation of public health policies as well as clinical interventions that effectively reduce the incidence and social burden of parenteral malignancies in patients with IBD. Compared to previous MR studies, statistical analyses in the current study are stricter. However, there are still some limitations in this study. The association between IBD and parenteral malignancies was limited to the European population, which may have possible selection biases, and the results can be generalizable to populations with other races needs further confirmation. Although the authors have made lots of effort to try to prevent IVs from affecting outcomes through confounding factors or other means, it is hard to avoid all confounding factors since carcinogenesis is multifactorial. Therefore, the positive effect of IBD on diffuse large B-cell lymphoma and skin cancers needs to be further validated in randomized controlled trials.

Conclusion

IBD may have a potential causal association with the risk of diffuse large B-cell lymphoma, melanoma, and non-melanoma skin cancer. Further studies are warranted to elucidate the underlying mechanisms of these causal relationships in patients with IBD.

Declarations

Ethics approval and consent to participate: Not applicable. Data in the current study are publicly available and de-identified. Each GWAS involved has obtained informed consent from participants and had ethical approval from their respective institutions. Therefore, no ethical approval from the Institutional Review Board (IRB) of The First People's Hospital of Foshan City was required.

Consent for publication: Not applicable

Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

(1) Peizhu Su, Zhaotao Li, conceiving and designing the study. (2) Peizhu Su, Yilin Wang, Huiwen Huang, Qinghua Lu, Qinyan Wu, collecting the data. (3) Peizhu Su, Yilin Wang, Huiwen Huang, Qinghua Lu, Qinyan Wu, analyzing and interpreting the data. (4) Peizhu Su, writing the manuscript. (5) Zhaotao Li, Peizhu Su, providing critical revisions that are important for the intellectual content. (6) Peizhu Su, Yilin Wang, Huiwen Huang, Qinghua Lu, Qinyan Wu, Zhaotao Li, approving the final version of the manuscript.

Funding

This work was supported in part by the Guangdong Medical Research Foundation (No. B2022173) and the Foshan 14th-fifth high-level key specialty construction project (FSGSP145001).

Acknowledgments

None.

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