Two-sample Mendelian randomization study reveals no causal relationship between inflammatory bowel disease and urological cancers

doi:10.21203/rs.3.rs-3640477/v1

Background: Relationships between inflammatory bowel disease (IBD) and urologic cancers have been identified in previous epidemiologic and observational studies, but causality remains uncertain. We tried to examine whether IBD was causally associated with urological cancers in this Mendelian randomization (MR) study.

Methods: The causal relationship between IBD and its main subtypes and urological cancers were investigated using genome-wide association study (GWAS) data. To get a more reliable conclusion, all outcomes were then divided into training set and validation set. Eligible single-nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) based on the assumptions of the MR analysis. The Inverse variance weighted (IVW) was applied as the main method with four others as complementary methods.

Results: In this two-sample MR study, no genetic evidence for causal effect of IBD on urological cancers was found neither in the training set nor in the validation set using IVW method. Likewise, we did not observe any significant association of Crohn’s disease (CD) and ulcerative colitis (UC) on urological cancers. Results of other methods were in accordance with those of the IVW method.

Conclusion: In this study, we confirmed that IBD was not a genetic causal risk factor for urological cancers in European population.

Biological sciences/Cancer/Cancer genetics

Biological sciences/Cancer/Urological cancer

Health sciences/Medical research/Genetics research

Biological sciences/Cancer

Biological sciences/Computational biology and bioinformatics

Health sciences/Gastroenterology

Health sciences/Medical research

Health sciences/Oncology

Health sciences/Risk factors

Health sciences/Urology

inflammatory bowel disease

urological cancers

mendelian randomization

causality

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is a chronic inflammatory disease of the intestine, mainly accumulating in the ileum, rectum and colon^[1]. Epidemiology studies have identified that IBD has become a global condition and its incidence has increased, especially in newly industrialized areas^[2,3]. IBD is an autoimmune disease of unknown etiology, characterized by chronic gastrointestinal inflammation, with an increased risk of intestinal cancer in subsets of patients^[4,5]. Previous meta-analyses and population-based studies have established that IBD can also be accompanied by extraintestinal cancers^[6-9], which is thought to be the result of an underling inflammatory state and immunosuppressive treatments^[10].

Despite limited data, recent studies showed that patients with IBD were at increased risk of urological cancers. Population-based cohort studies suggested that IBD especial CD increases the risk of kidney cancer^[11,12]. The risk of bladder cancer was only mildly elevated in patients with CD^[12], but some researchers found potential key genes involved in CD with bladder cancer^[13]. IBD has been demonstrated as a risk factor for prostate cancer^[14-16], and preneoplastic changes have been observed in a mouse model of chemically-induced intestinal inflammation^[17]. While evidence suggested links between IBD and urological cancers, the mechanism of their relationships was still unclear. In addition, the association between IBD and urological cancers identified in observational studies might be biased due to confounding factors. Previous studies did not illustrate the existence of a causal relationship between IBD and urological cancers, hence our MR study from a genetic perspective.

Mendelian randomization (MR), an epidemiological method of analysis, is able to employ the single-nucleotide polymorphisms (SNPs) as an instrumental variable (IV) to investigate the causal relationship between an exposure and an outcome, with advantage of lessening bias because of confounding factors and reverse causality^[18-20]. In this two-sample MR study, we tried to examine whether IBD is causally associated with urological cancers.

Study design description

Figure 1 shows a description of our two-sample MR design between IBD and its main subtypes (CD and UC) and urological cancers. We split the data into a training set and a validation set using summary statistics from a genome-wide association study (GWAS) to investigate the causal relationship between IBD and urological cancers. A total of fourteen MR analyses were respectively performed considering IBD and its main subtypes as the exposure and urological cancers as the outcome. All participants included in this study were European. No ethical approval is required as the data for our study are sourced from publicly available summary statistics.

Filtering of instrumental variables for MR analyses

The following steps were used to select instrument variables to ensure the accuracy and authenticity of this study. First, single-nucleotide polymorphisms (SNPs) significantly related to urological cancers and IBD were selected at a threshold of genome-wide significance (p < 5\(\times\)10⁻⁸). Second, we conducted linkage disequilibrium (LD) analyses (r² = 0.001 and with 10000kb window) among included instrumental variables. Third, SNPs associating with the outcome (p < 5\(\times\)10⁻⁸) were excluded. The strength of the instrument was evaluated using the formula: F = (n-k-1/k)\(\times\)R²\(\times\)(1-R²), in which n denotes the sample size, k denotes the number of selected instrumental variables, and R² is the exposure variance explained by the included SNPs. When F < 10, it indicates there is a weak association between instrumental variables and exposure^[21].

Selection of data sources and instrumental variables for IBD

We considered IBD including overall IBD, CD and UC as the exposure, respectively. Statistics of IBD from European cases were downloaded from International IBD Genetics Consortium (IIBDGC)^[22], with 12882 cases, 21770 controls and 12716084 SNPs in overall IBD, 5956 cases, 14927 controls and 12276506 SNPs in CD, and 6968 cases, 20464 controls and 12255197 SNPs in UC (Supporting Information: Table 1).

Selection of data sources and instrumental variables for urological cancers

We selected kidney cancer, bladder cancer and prostate cancer as the outcome, and each outcome was divided into a training set and a validation set. In particular, there are two validation sets for prostate cancer. All related statistics of training sets were available in the UK Biobank (https://www.ukbiobank.ac.uk/), in which SNPs associated with kidney cancer were obtained from 701 European cases and 360493 controls, SNPs associated with bladder cancer were obtained from 1554 cases and 359640 controls, and SNPs associated with prostate cancer were obtained from 7872 cases and 160876 controls. The datasets for validation sets comes from FinnGen^[23], with 1830 cases and 259583 controls in kidney cancer, 2380 cases and 259583 controls in bladder cancer, and 79148 cases and 61106 controls in prostate cancer. The data for the other validation set in prostate cancer was taken from Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) Consortium (11590 cases and 110189 controls)^[24]. Detailed data were shown in Table 1.

Statistical analysis

Five different methods including Inverse variance weighted (IVW), MR-Egger, Weighted median, Simple mode and Weighted mode, with IVW being the main analysis to assess whether there was a causal effect of IBD on urological cancers. IVW can evaluate the causal effects of genetically predicted exposure on outcome by using weighted regression of SNP-specific Wald ratios when no horizontal pleiotropy exists. We performed MR-Egger regression to assess whether there was potential horizontal pleiotropy in the included SNPs. The potential outliers reflecting likely pleiotropic biases was detected by performing Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and any outlying SNP was excluded to correct horizontal pleiotropic effects. In addition, Cochran’s Q statistic was used to examine the heterogeneity among the selected SNPs. We also applied leave-one-out sensitivity analysis to identify whether there were potential strong influence SNPs. The results of MR analyses are expressed as odds ratios (ORs) and 95% CI (confidence intervals) to estimate the degree of the causal effect. All analyses in this study were conducted through the TwoSampleMR package (version 0.5.6) in R software (version 4.2.3, https://www.r-project.org/).

Selected genetic instrumental variables

We screened the IVs according to the criteria described above and finally selected 63, 52 and 39 independent SNPs as IVs of overall IBD, CD and UC. F statistics revealed there was no weak instrumental bias between the screened IVs and exposure (all F > 10). Detailed information of the selected SNPs and F analyses were presented in Tables S1-S3. The IVs of exposure used in fourteen MR analyses (IBD and urological cancers) all shared the same filtered SNPs.

The causal effect of IBD on kidney cancer

IVW results showed that overall IBD, CD and UC were not causally related to kidney cancer in either the training set (Overall IBD: OR=1.000002, 95%CI=0.9998-1.0002, P=0.986; CD: OR=1.00007, 95%CI=0.9999-1.0002, P=0.468; UC: OR=1.0001, 95%CI=0.9999-1.0004, P=0.343) or validation set (Overall IBD: OR=0.987, 95%CI=0.918-1.061, P=0.714; CD: OR=0.982, 95%CI=0.927-1.041, P=0.546; UC: OR=1.018, 95%CI=0.932-1.111, P=0.699). The overall effect of the training and validation sets also indicated no significant association between IBD and kidney cancer, and the results were shown in the forest plot drawn based on the IVW method (Figure 2). We also drew the forest plot based on the MR-Egger method and the results were consistent (Figure S1). Scatter plots and forest plots derived from the IVW method are shown in Figure S2 and S3. No significant association was observed in the other four models either. Detailed information of MR analyses was presented in Tables S4-S6. We therefore believed that IBD and its main subtypes were not the causal risk factors for kidney cancer in European population.

The causal effect of IBD on bladder cancer

Overall IBD, CD and UC were similarly not significantly associated with bladder cancer by the IVW method in training set (Overall IBD: OR=0.9999, 95%CI=0.9995-1.0002, P=0.482; CD: OR=0.99995, 95%CI=0.9997-1.0002, P=0.704; UC: OR=0.9999, 95%CI=0.9995-1.0003, P=0.556). Data from the validation set showed the same results (Overall IBD: OR=1.008, 95%CI=0.943-1.077, P=0.817); CD: OR=0.997, 95%CI=0.941-1.055, P=0.906; UC: OR=1.002, 95%CI=0.935-1.074, P=0.958). Forest plots depicting the overall effect also indicated that IBD and its major subtypes were not associated with bladder cancer based on the IVW method (Figure 2) and MR-Egger method (Figure S1). Figure S2 and S3 showed the scatter plots and forest plots based on the IVW method. No correlation was observed by other methods (Tables S4-S6). Hence, there was also no causal effect of IBD, CD and UC on bladder cancer in European population.

The causal effect of IBD on prostate cancer

Although there were observational studies that observed a correlation between IBD and prostate cancer^[14-16], it appeared that neither overall IBD, nor CD and UC had causal effects on prostate cancer under the IVW method in training set (Overall IBD: OR=0.9992, 95%CI=0.998-1.0004, P=0.192; CD: OR=0.9992, 95%CI=0.998-1.0002, P=0.125; UC: OR=0.9999, 95%CI=0.9984-1.001, P=0.882). The data from validation sets including FinnGen (Overall IBD: OR=1.014, 95%CI=0.998-1.051, P=0.458; CD: OR=1.005, 95%CI=0.976-1.034, P=0.741; UC: OR=1.018, 95%CI=0.971-1.067, P=0.459) and PRACTICAL Consortium (Overall IBD: OR=1.005, 95%CI=0.983-1.027, P=0.667; CD: OR=1.002, 95%CI=0.986-1.019, P=0.795; UC: OR=0.987, 95%CI=0.958-1.016, P=0.361) also indicated no significant association. Even when the overall effects of the training and validation sets were analyzed, the results did not show a noticeable tendency to be relevant depending on the IVW method (Figure 2), which were also uniform under the MR-Egger method. We also sketched the results using the IVW method in scatter plots and forest plots (Figure S2 and S3). While we observed a slight causal effect of UC on prostate cancer from the PRACTICAL database only under the Weighted mode method (validation set, OR=0.956, 95%CI=0.917-0.998, P=0.043), the genetic association was not significant in all other groups (Tables S4-S6). Thus, we concluded that IBD and its main subtypes could not serve as genetically predicted causal risk factors of prostate cancer in European population.

Sensitivity analysis

Pleiotropy and heterogeneity analyses were performed to validate the reliability of the MR analyses above (Table 2). No incidence of potential pleiotropy was identified in MR-Egger regression analyses and MR-PRESSO tests. Outlier SNPs in our study were excluded by the MR-PRESSO method. Additionally, we applied Cochran's Q p-value (Table 2) and funnel plots (Figure S4) in IVW and MR-Egger methods and the presence of heterogeneity was found in some analyses, such heterogeneity being acceptable in MR study. It was demonstrated by the results of leave-one-sensitivity analyses that the estimates of the causal effects of genetic prediction of IBD on urological cancers were reliable (Figure S5).

We appraised the genetic overlap and potential causal relationships between IBD and urological cancers by utilizing GWAS summary statistics, but no genetic evidence for causal effect of IBD on urological cancers was found in this two-sample MR study. The results from the validation sets were still consistent. We confirmed that IBD was not a genetic causal risk factor for urological cancers in European population.

While we did not obtain significant results, several hypotheses have been formulated about the association observed in previous observational and epidemiological studies. Firstly, the relationship between IBD and the increased risk of urological cancers remains controversial. Given scarce studies^{[11, 25]}, speculations of association between IBD and kidney cancer await confirmation. In a present meta-analysis, patients with IBD were only observed a trend toward an increased risk of bladder cancer in the CD subgroup^[26]. The association between IBD and bladder cancer was also not statistically significant in another study^[25]. IBD was not associated with an increased risk of prostate cancer in a population-based retrospective cohort study^[27]. In another meta-analysis, the increased risk of prostate cancer compared to the general population was just slight^[28]. Secondly, IBD and its main subtypes have been demonstrated to have an increased risk of extra-intestinal malignancies, thought to be a result of underlying inflammatory state and immunosuppressive therapies^[10]. Inflammation status was thought to play a role in the well-established association between IBD and the development of cancer in various solid tumors. Chronic kidney disease (CKD) was known to be a risk factor for kidney cancer^[29]. Potential mechanism connecting CKD and IBD involved IgA nephropathy, believed to be related to mucosal inflammation^[30]. Patients with IBD probably suffered an increased risk of kidney cancer through IBD-CKD pathway. Inflammation may lead to activation of angiogenesis, which finally caused progression of bladder cancer in patients with IBD^[31]. Chronic inflammation could cause DNA damage and promote carcinogenic epigenetic alterations, which as a result might contribute to prostate tumorigenesis^[32]. In addition, a range of drugs for IBD treatment, such as immunomodulators and biological agents, may increase the risk of extraintestinal cancer^[33]. A population-based cohort study also concluded that patients with IBD who are chronically exposed to immunosuppressive treatment might be considered at higher risk for cancer^[34]. Patients with IBD receiving thiopurines were proved more likely to acquire urinary tract cancers, including kidney cancer and bladder cancer^[35]. Previous observational studies might not eliminate bias from the use of immunosuppressive medications in patients with IBD on the risk of cancers. However, no direct evidence has been provided to accurately elucidate the correlation between immunosuppressive drugs and prostate cancer risk in patients with IBD. Moreover, patients with chronic inflammatory disease commonly have more frequent healthcare utilization and the association could be explained by detection bias^[36]. Due to the nature of the disease, men with IBD had a higher prevalence of rectal examinations. Cancers might be detected during routine medical tests with the rising numbers of physician office visits over time.

The application of comprehensive GWAS data for MR analyses improved the precision of the estimated effects. In this study, the most significant advantage is that causal estimates were obtained from MR, avoiding reverse causality and confounding bias. As far as we know, this study is the first MR analysis on this subject. However, our MR study still has some limitations. First, the mechanism of cancers caused by IBD is complex, and this study can only offer genetic evidence for the absence of causal relationships between IBD and urological cancers. Secondly, some heterogeneity could not be avoided through Cochran's Q value in the previous MR analyses. In addition, the MR study is limited by specific races, thus conclusions drawn from analyses of populations of different races would be invalid. This result is therefore limited to the European populations.

In conclusion, our MR study demonstrated that no causal effect of IBD on urological cancers was shown neither in the training set nor in the validation set in European populations. Considering the fact that patients with IBD are at an increased risk of cancer, further researches are encouraged to explore the mechanisms between IBD and cancers.

Data availability

The datasets generated and/or analyzed during the current study are available in the IEU open GWAS project (https://gwas.mrcieu.ac.uk/) and UK Biobank (https://www.ukbiobank.ac.uk/).

Author information

Haoyang Zhang and Can Hu contributed equally to this work and should be considered co-first authors.

Authors and Affiliations

Department of Urology, Dushu Lake Hospital Affiliated to Soochow University, No.9 Chongwen Road, 215123 Suzhou, Jiangsu, China

Haoyang Zhang

Department of Urology, Suzhou Xiangcheng People’s Hospital, Suzhou, China.

Can Hu

Department of Urology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, 215006 Suzhou, Jiangsu, China

Zhiyu Zhang

Department of Urology, Dushu Lake Hospital Affiliated to Soochow University, No.9 Chongwen Road, 215123 Suzhou, Jiangsu, China

Peng Li

Department of Urology, Dushu Lake Hospital Affiliated to Soochow University, No.9 Chongwen Road, 215123 Suzhou, Jiangsu, China

Gang Shen

Department of Urology, Dushu Lake Hospital Affiliated to Soochow University, No.9 Chongwen Road, 215123 Suzhou, Jiangsu, China

Jiale Sun

Contributions

H.Y.Z. and C.H.: writing the draft of the manuscript, statistical analysis, data curation, writing review, and editing. Z.Y.Z and P.L.: investigation, statistical analysis, and editing. G.S: critically reviewing and editing. J.L.S: conceptualization, study design, supervising, editing, and reviewing. All authors approved the final version.

Corresponding Author

Correspondence to Gang Shen and Jiale Sun.

Ethics declarations

Competing interests

The authors declare no competing interests.

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Table 1. The characteristics of GWAS studies on the exposures and outcomes.
Exposure	Consortium	Total population	Total SNPs	Cases	Controls	Ethnicity	References
Inflammatory bowel disease	IIBDGC	34652	12716084	12882	21770	European	PMID 26192919
Crohn's disease	IIBDGC	20883	12276506	5956	14927	European	PMID 26192919
Ulcerative colitis	IIBDGC	27432	12255197	6968	20464	European	PMID 26192919
Outcome	Consortium	Total population	Total SNPs	Cases	Controls	Ethnicity	References
Kidney cancer	UK Biobank	361194	13791467	701	360493	European	https://www.ukbiobank.ac.uk/
	FinnGen	261413	16380308	1830	259583	European	PMID 36653562
Bladder cancer	UK Biobank	361194	13791467	1554	359640	European	https://www.ukbiobank.ac.uk/
	FinnGen	261963	16380305	2380	259583	European	PMID 36653562
Prostate cancer	UK Biobank	168748	13791467	7872	160876	European	https://www.ukbiobank.ac.uk/
	FinnGen	140254	16377987	79148	61106	European	PMID 36653562
	PRACTICAL	121779	20346368	11590	110189	European	PMID 29892016
PRATICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium; SNPs, single nucleotide polymorphisms.

Table 2. Pleiotropy and heterogeneity analyses.
Exposure	Outcome	Consortium	No. of SNPs	MR-Egger regression		MR PRESSO	Heterogeneity analyses
				Intercept	p_intercept	Global test p	Method	Q	Q_pval
Inflammatory bowel disease	Kidney cancer	UK Biobank	54	-0.00002	0.690	0.246	MR-Egger	59.836	0.213
							IVW	60.021	0.236
		FinnGen	48	-0.03584	0.054	0.353	MR-Egger	44.926	0.517
							IVW	49.725	0.365
	Bladder cancer	UK Biobank	54	-0.00001	0.936	0.060	MR-Egger	70.191	0.047
							IVW	70.200	0.057
		FinnGen	48	0.00009	0.995	0.270	MR-Egger	52.834	0.227
							IVW	52.834	0.259
	Prostate cancer	UK Biobank	54	0.00018	0.469	0.399	MR-Egger	54.788	0.369
							IVW	55.349	0.386
		FinnGen	48	0.01325	0.118	0.083	MR-Egger	58.640	0.100
							IVW	61.873	0.072
		PRACTICAL	51	0.00857	0.086	0.570	MR-Egger	85.137	0.001
							IVW	90.458	<0.001
Crohn's disease	Kidney cancer	UK Biobank	44	-0.00002	0.665	0.513	MR-Egger	42.093	0.467
							IVW	42.284	0.502
		FinnGen	42	-0.02374	0.123	0.464	MR-Egger	38.094	0.556
							IVW	40.574	0.489
	Bladder cancer	UK Biobank	44	-0.00006	0.403	0.415	MR-Egger	44.105	0.383
							IVW	44.854	0.394
		FinnGen	42	-0.01461	0.329	0.196	MR-Egger	48.049	0.179
							IVW	49.224	0.177
	Prostate cancer	UK Biobank	44	0.00015	0.543	0.142	MR-Egger	53.131	0.117
							IVW	53.608	0.129
		FinnGen	42	0.00636	0.402	0.169	MR-Egger	48.923	0.157
							IVW	49.801	0.163
		PRACTICAL	41	0.00176	0.675	0.548	MR-Egger	59.553	0.019
							IVW	59.826	0.023
Ulcerative colitis	Kidney cancer	UK Biobank	31	-0.00007	0.254	0.342	MR-Egger	31.812	0.328
							IVW	33.296	0.310
		FinnGen	29	-0.03471	0.219	0.153	MR-Egger	33.895	0.169
							IVW	35.880	0.146
	Bladder cancer	UK Biobank	31	-0.00010	0.364	0.057	MR-Egger	42.888	0.047
							IVW	44.147	0.046
		FinnGen	29	-0.00439	0.844	0.873	MR-Egger	19.788	0.840
							IVW	19.827	0.871
	Prostate cancer	UK Biobank	31	0.00050	0.222	0.550	MR-Egger	48.632	0.013
							IVW	51.240	0.009
		FinnGen	28	-0.00652	0.666	0.154	MR-Egger	46.860	0.007
							IVW	47.204	0.009
		PRACTICAL	29	0.00364	0.654	0.137	MR-Egger	76.451	<0.001
							IVW	77.033	<0.001
PRATICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium; IVW, inverse variance weighted; MR PRESSO, Mendelian randomization pleiotropy residual sum and outlier; SNPs, single‐nucleotide polymorphisms.

No competing interests reported.

FigS1.tif
Figure S1. Forest plot: Causal associations of inflammatory bowel disease and its main subtypes with urological cancers using MR‐Egger method. (A) Effect of inflammatory bowel disease on urological cancers. (B) Effect of Crohn's disease on urological cancers. (C) Effect of ulcerative colitis on urological cancers. PRACTICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium; OR, odds ratio; CI, confidence interval.
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Figure S2. Scatter plots of the association between inflammatory bowel disease and its main subtypes and urological cancers. The five methods applied in this study were all demonstrated. Lines in different colors represent IVW, MR-Egger, weighted median, simple mode and weight mode methods. PRACTICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium; IVW, inverse variance weighted; SNP, single nucleotide polymorphism.
Fig.S3.tiff
Figure S3. Funnel plots were applied to detect whether the observed association was along with obvious heterogeneity using IVW and MR-Egger methods. PRACTICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium; IVW, inverse variance weighted.
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Figure S4. Leave-one-out analyses were applied to evaluate whether any single instrumental variable was driving the causal effect. PRACTICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium.
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Figure S5. Forest plots were applied to demonstrate the MR estimate and 95% CI values for each SNP, which also show the MR-Egger and IVW results at the bottom. PRACTICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium; IVW, inverse variance weighted.
TableS1.docx
Table S1. F-statistics to evaluate the instrument strength on inflammatory bowel disease.
TableS2.docx
Table S2. F-statistics to evaluate the instrument strength on Crohn's disease.
TableS3.docx
Table S3. F-statistics to evaluate the instrument strength on ulcerative colitis.
TableS4.docx
Table S4. Casual effect of inflammatory bowel disease on urological cancers in the MR analyses.
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Table S5. Casual effect of Crohn's disease on urological cancers in the MR analyses.
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Table S6. Casual effect of ulcerative colitis on urological cancers in the MR analyses.

Two-sample Mendelian randomization study reveals no causal relationship between inflammatory bowel disease and urological cancers

Status:

Version 1

Abstract

Figures

Introduction

Methods

Study design description

Filtering of instrumental variables for MR analyses

Selection of data sources and instrumental variables for IBD

Selection of data sources and instrumental variables for urological cancers

Statistical analysis

Results

Selected genetic instrumental variables

The causal effect of IBD on kidney cancer

The causal effect of IBD on bladder cancer

The causal effect of IBD on prostate cancer

Sensitivity analysis

Discussion

Conclusion

Declarations

Data availability

Author information

Authors and Affiliations

Contributions

Corresponding Author

Ethics declarations

Competing interests

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1