A Two-sample Mendelian randomization analysis of the relationship between inflammatory factors and nasopharyngeal carcinoma

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Previous studies are susceptible to confounding factors. To solve this problem, this study uses Mendelian randomization (MR) to discover the causal relationship between inflammatory factors and NPC from a genetic perspective. Methods A two-sample MR analysis was performed using data from genome-wide association analysis studies of 41 inflammatory factors and NPC. The following methods were used to analyze the causal relationship between inflammatory factors and NPC: Inverse-Variance Weighted, MR-Egger, Weighted Median, Simple Mode and Weighted Median. MR Steiger test was used to determine the direction of the interaction between inflammatory factors and NPC. The robustness of the analysis was ensured by means of Cochran's Q test, leave-one-out analysis and MR-Egger regression analysis. Reverse MR was performed to investigate whether there is reverse causality between inflammatory factors and CTS. Results There was a positive causal relationship between granulocyte colony-stimulating factor (G-CSF) levels and NPC ( OR : 3.659, 95% CI : 1.398–9.581, P = 0. 008), and there was no pleiotropy or reverse causality between the level of G-CSF and NPC. The sensitivity analysis showed that the results of the analyses did not contain heterogeneity, horizontal pleiotropy, or individual single nucleotide polymorphisms that significantly influenced the results of the analyses. Conclusion G-CSF is a potential risk factor for NPC. The results of this study may provide new research ideas for identifying tumor markers and therapeutic targets for NPC.. nasopharyngeal carcinoma inflammatory factors tumor microenvironment granulocyte colony-stimulating factor Mendelian randomization Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from the nasopharyngeal epithelium with obvious epidemiological characteristics of regional aggregation and population susceptibility. The Chinese population exhibits a high incidence of NPC, with the Guangdong province of China demonstrating a particularly elevated rate of this malignancy. This observation has led to the colloquial designation of the disease as “Guangdong carcinoma”. NPC demonstrates highly sensitive to radiotherapy and chemotherapy. Patients often experience enhanced therapeutic outcomes following systematic treatment regimens. However, these treatments are associated with numerous adverse reactions, which can result in physiological and psychological dysfunction. Consequently, patients may experience a decline in their quality of life and a decrease in treatment motivation. NPC is characterized by its high degree of invasiveness, which is manifested in its biological behavior. This invasive nature leads to strong regional invasion and distant metastasis, resulting in a high risk of recurrence and metastasis after treatment. Local recurrence and distant metastasis are the primary factors contributing to mortality in cases of NPC [ 1 – 2 ] . Therefore, it is imperative to identify a treatment that is both efficacious and devoid of deleterious side effects, while also ensuring its sustainability to enhance the quality of life and extend the survival duration of patients. The tumor microenvironment (TME) is composed of tumor cells and a multitude of other cell types. It is the milieu that fosters tumorigenesis and tumor development. Tumor cells secrete an array of inflammatory factors and recruit inflammatory cells, which form an integral component of the tumor microenvironment. Tumor-related inflammation is a hallmark manifestation of tumors. Inflammation pathways activated by inflammatory factors, such as PI3K/Akt, MAPK/ERK, NF-κB and JAK/STAT, etc., are classic tumor-related pathways. The tumor microenvironment establishes an internal milieu conducive to tumor growth, metastasis, immune escape, and angiogenesis by mediating common pathways of inflammation and tumors. Anti-inflammatory therapy is regarded as a means of mitigating the occurrence of tumors and the associated risk of mortality, signifying a prospective avenue for anti-tumor treatment. NPC has been shown to be associated with Epstein-Barr virus infection. Epstein-Barr virus has been shown to induce an inflammatory response in NPC cells, thereby promoting the production of inflammatory factors and contributing to the formation of the TME of NPC [ 3 – 4 ] . In addition, the inflammatory microenvironment, under the long-term influence of inflammatory factors such as CCL3, CCL4, IL-1β, IL-6, IL-8 and IL-10, increases the risk of NPC pathogenesis and metastasis [ 5 ] . The present study was guided by the hypothesis that inflammatory responses have a carcinogenic effect on malignant tumors. To investigate the causal relationship between inflammatory factors and the incidence of NPC, genetic instrumental variables were derived through Mendelian randomization (MR). We hope that our study will provide ideas and references for future research on the prevention and treatment of NPC. Materials and methods 2.1 Study design The causal relationship between 41 inflammatory factors and NPC is to be evaluated based on a two-sample MR analysis. 41 inflammatory factors were utilized as exposure factors, NPC as an outcome factor, and genetic variants with significant statistical significance in the inflammatory factors, namely single nucleotide polymorphisms (SNPs), were selected as instrumental variables (IVs) for the two-sample MR analysis. 1.2 Data sources A publicly available genome-wide association study (GWAS) database was selected for the present analysis, and the data on exposure factors and outcome factors were obtained from the Finnish population in Europe. Refer to previous studies, the data for 41 inflammatory factors were obtained from an investigation included in the NHGRI-EBI Catalog database ( https://www.ebi.ac.uk/gwas ) concerning the genetic associations of circulating inflammatory factors in 8,293 Finns (GWAS ID: ebi-a-GCST004458) [ 6 – 7 ] . This investigation encompasses population cohort data from three autonomous studies: the "Cardiovascular Risk in Young Finns study", "FINRISK1997", and "FINRISK2002". Detailed information on these 41 inflammatory factors can be found in Supplementary material. The data for NPC were derived from a research project entitled "Malignant neoplasm of nasopharynx (controls excluding all cancers)" in the FINNGEN database( https://r11.finngen.fi ). The data for NPC were based on the results of 89 cases of NPC compared with 345,118 healthy individuals. 1.3 IVs selection The IVs in this study met the following hypotheses (Fig. 1): (1) Correlation Hypothesis: IVs are strongly associated with exposure factors; (2) Independence Hypothesis: IVs are not associated with confounders; (3) Exclusion Hypothesis: IVs influence outcome factors only through exposure factors. In selection process of IVs, given that there were few SNPs satisfying the p < 5×10 − 8 condition, the SNPs significance level was set to P < 5×10 − 6 to ensure relevance [ 8 ] ; for linkage disequilibrium SNP elimination, set the coefficient to r 2 < 0.001 and kb < 10000; based on the formula \(\:F=\frac{{R}^{2}\left(n-1-k\right)}{\left(1-{R}^{2}\right)k}\) and \(\:{R}^{2}=2\times\:\left(1-MAF\right)\times\:MAF\times\:\frac{\beta\:}{SD}\) to remove SNPs with F ≤10 to avoid weak IVs correlation bias [ 9 ] ; remove SNPs associated with confounders using the LDlink database ( https://ldlink.nih.gov/ ), remove palindromic sequences to achieve allelic alignment and eliminate duplicate SNPs. In the reverse MR analysis, the SNP screening criteria we applied was the same as the forwards MR analysis, which is P < 5×10 −6 . 1.4 Statistical analysis Inverse-Variance Weighted (IVW), MR-Egger, Weighted Median, Simple Mode, and Weighted Mode were selected for MR analysis. The IVW method has the highest test efficiency when horizontal pleiotropy of instrumental variables does not exist; therefore, it was used as the primary analysis method [ 10 ] . The Bonferroni correction formula is 0.05/ (number of exposures included in the study * number of outcomes included in the study) [ 11 ] . Therefore, in the study, P values of less than 0.0012 (0.05/41) were considered to indicate a strong association, and P values between 0.0012 and 0.05 were considered to indicate a suggestive association. To ensure the robustness of the analysis results, Cochran's Q test was used to assess heterogeneity in IVW and MR-Egger; the leave-one-out analysis was used to test whether a single SNP had an excessive influence on the results of the MR analysis, and MR-Egger regression analysis was used to test for horizontal pleiotropy and visualize the analysis results. In the reverse MR analysis, genetic data of NPC were used as exposure, while genetic data of 41 inflammatory factors were used as outcome to determine whether there was a reverse causality between NPC and inflammatory factors. The screening criteria for SNPs were as serious as those in the forwards MR analysis. The Steiger direction test is a methodological instrument employed for the purpose of analyzing to analyze and subsequently determining the direction of the causal relationship between exposure and outcome factors. The utilization of Steiger direction test guarantees a robust correlation between the exposure factor and SNPs, while ensuring that the SNPs exclusively influence the outcome factor through the exposure factor. This methodological framework precludes the occurrence of bias owing to reverse causality [ 12 ] . 5 Statistical analysis software settings Statistical analysis was conducted using the "TwoSampleMR" package in R software (version 4.4.1) [ 13 – 14 ] , with a statistical significance threshold of P < 0.05. The relationship between exposure and the outcome factors was quantified using odds ratio (OR). An OR of 1 indicated that the exposure factor was not associated with the outcome factor. An OR greater than 1 indicates that the exposure factor is a risk factor for the outcome factor, while an OR less than 1 indicates that the exposure factor is a protective factor for the outcome factor. Results 2.1 IVs Following the elimination of linkage disequilibrium, SNPs associated with confounding factors, SNPs with reverse sequences, and SNPs with weak instrumental variables, a total of 8 SNPs remained. 2.2 The forwards MR analysis To account for any linkage disequilibrium, we excluded IVs with an r 2 value below 0.01 within a range of 1000KB. The calculation formula of the F value was used to value the F values of the IVs selected in this study. The effect of them were found to be strong, because the F values were all greater than 10. No confounding factors were association with NPC. After MR analysis of each inflammatory factor and NPC, it was found that there was a positive causal relationship between granulocyte colony-stimulating factor (G-CSF) and NPC (IVW- OR : 3.659, 95% CI : 1.398–9.581, P = 0.008). The results of the IVW, MR-Egger, Weighted Median, and Weighted Mode provide substantial evidence that supports the conclusion that G-CSF levels are associated with an increased risk of NPC (Table 1 and Fig. 2). The results of the simple mode analysis did not attain statistical significance; however, the OR value corroborated the hypothesis that G-CSF levels have the potential to elevate the risk of NPC. (Fig. 3). Table 1: MR analysis results of G-CSF levels and NPC MR analysis method β SE OR 95% CI P MR-Egger 1.816 0.726 6.145 1.481-25.498 0.046 Weighted median 1.384 0.697 3.992 1.018-15.659 0.047 Inverse variance weighted 1.297 0.491 3.659 1.398-9.581 0.008 Simple mode 0.706 1.233 2.026 0.181-22.703 0.585 Weighted mode 2.118 0.805 8.313 1.716-40.275 0.034 β =beta value , SE =Standard Error , OR =odds ratio, 95% CI =confidence interval, P =P value . 2.3 The reverse MR analysis and MR Steiger test In the reverse MR analysis, although the SNP screening criteria we applied were the same as those in forwards MR analysis, there were no suitable SNPs. This finding indicates that genetic vulnerability to NPC does not have a substantial impact on genetic predisposition to inflammatory factors. The causal relationship between NPC and inflammatory factors is influenced by complex confounding factors, necessitating discussion of the potential association between inflammatory factors and NPC. The results of the Steiger direction test demonstrated a strong relation between SNPs and G-CSF levels (exposure factor r 2 = 0.032 > outcome factor r 2 = 0). The direction of the overall SNPs and each SNP affecting NPC were TRUE (P < 0.05), indicating that there is no reverse causality. 2.4 Sensitivity analysis The scatter plot demonstrated that the direction of causality was consistent across the five analysis methods (Fig. 4). The Cochran Q test values for IVW ( P = 0.537) and MR-Egger ( P = 0.533) were not statistically significant, indicating that there was no heterogeneity among the included SNPs and no potential bias in the association between G-CSF levels and NPC. The value of the MR-Egger regression analysis ( P = 0.370) was not statistically significant, and the intercept of -0.1142308 was close to 0, indicating that there was no horizontal pleiotropy and that the association between G-CSF levels and NPC is not influenced by other factors. The leave-one-out analysis demonstrates that the results following the exclusion of each SNP are not significantly different from the overall results, thus indicating that the results of the MR analysis are robust and not driven by a single IV. Discussion The inflammatory environment is a critical factor in tumor development and can influence the microenvironment of tumor growth by altering tissue homeostasis. Inflammatory factors in the TME are critical for the regulation of various cellular processes including cell proliferation, differentiation, migration, and apoptosis. Inflammatory factors play pivotal roles in the regulation of both inflammatory response and immune response processes. Inflammatory factors exert their influence on the TME through a complex network of bidirectional regulatory mechanisms. On the one hand, some inflammatory factors can stimulate the immune response to play an anti-tumor effect, and on the other hand, some inflammatory factors can induce the immune escape to play a tumor-promoting role [ 15 ] . In consideration of the paradoxical state of inflammatory factors in tumors, the present study elected to utilize a MR analysis, with the objective of elucidating the role of inflammatory factors in the occurrence and development of NPC. According to the results of MR analysis in this study, G-CSF levels in inflammatory factors are risk factors for NPC. G-CSF is a glycoprotein belonging to the hematopoietic growth factor, inflammatory factor, and immune stimulating factor. It is capable of promoting the differentiation and proliferation of neutrophil progenitor cells and enhancing the function of mature neutrophils. G-CSF is commonly used in the treatment of neutropenia caused by various reasons. The biological effects of G-CSF are mediated by the G-CSF receptor (G-CSFR), which is primarily involved in cell differentiation and proliferation. G-CSF has been observed to trigger the activation of signaling molecules, including pro-inflammatory transcription factors such as STAT1, STAT3, and STAT5. These molecules activate three major signaling pathways: PI3K/AKT, MAPK/ERK, and JAK/STAT [ 16 ] . Under normal conditions, the activation of these signaling pathways leads to the maturation and mobilization of neutrophils into the bloodstream. Conversely, abnormal activation or mutation of the G-CSFR pathway can affect tumor cells directly, thereby playing a significant role in tumor growth, invasion, metastasis, angiogenesis, and immune escape [ 17 ] . G-CSF and G-CSFR have been found to promote tumor progression in cellular and animal experiments [ 18 – 20 ] , and their tumor-promoting mechanisms are as follows: enhancement of epithelial-to-mesenchymal cell transformation through M2 macrophage recruitment, which promotes tumor growth; induction of bone marrow endothelial progenitor cell mobilization, which promotes angiogenesis and tumor regeneration; activation of tumor cell gelatinases through receptors, which promotes tumor metastasis; inflammatory and immunomodulatory effects by mediating innate and adaptive immune responses, inhibiting the expression of CD4+, CD8+, and CD16 + cells, which in turn inhibits the mobilization and activity of NK cells, macrophages, and T cells, contributing to the acquisition of immune escape by tumor [ 21 ] . Furthermore, elevated levels of G-CSF, along with the presence of G-CSFR expression-positive tumors, are associated with a biologically more malignant state, reduced differentiation, and a worse clinical prognosis [ 22 – 24 ] . Relevant studies have shown that in head and neck cancer, including NPC, tumor-produced G-CSF can lead to poor patient prognosis by regulating the PI3K-AKT pathway, Mcl-1 expression, Granulocyte bone marrow-derived inhibitory cell-dependent mechanisms and caspase-3 levels. Even G-CSF has been identified as a predictor of tumor growth and poor prognosis in head and neck cancers such as nasopharyngeal carcinoma [ 25 – 26 ] . However, given that the majority of prior studies were primarily focused on fundamental experiments and clinical trials, they were unavoidably influenced by confounding factors and reverse causation, leading to a certain degree of result bias. In the present study, MR analysis was utilized to ascertain the association between G-CSF levels and the risk of NPC at the level of genetic variation, while excluding the effect of confounding factors. The administration of chemotherapy and radiation therapy to treat malignancies can result in bone marrow suppression, leading to a decrease in the number of neutrophils. In cases of severe neutrophil deficiency, the therapeutic or prophylactic administration of G-CSF is necessary to elevate neutrophil levels. G-CSFR is prevalent in primary and metastatic foci of head and neck tumors, and it produces G-CSF by autocrine or paracrine secretion and shows high expression [ 27 – 28 ] . Given the direct action of exogenous G-CSF on G-CSFR-positive tumors, patients with NPC and neutrophil deficiencies are imperative to assess G-CSFR expression to select the appropriate therapeutic dose prior to G-CSF supplementation. Concurrently, G-CSF can be utilized as a potential tumor marker to observe disease progression in specific tumors or to evaluate effects of therapy. Inhibition of G-CSF and blockade of G-CSFR may offer therapeutic benefits in the treatment of specific tumors. The targeting of G-CSF and G-CSFR has emerged as a promising therapeutic strategy [ 29 – 31 ] . Conclusion G-CSF levels in inflammatory factors function as risk factors for NPC. G-CSF has the capability of exerting its influence on the TME by binding to the G-CSFR of tumor cells and activating signaling pathways such as PI3K/AKT, MAPK/ERK, JAK/STAT, and others. Such pathways serve as mediators of a multitude of critical processes, including tumor proliferation, invasion, metastasis, apoptosis, angiogenesis, immune escape, and numerous additional aspects. Meanwhile, exogenous supplementation of G-CSF promotes the progression of G-CSFR-expressing tumors, leading to high levels of G-CSF which are associated with poor patient prognosis. This suggests that clinical care is needed to assess the benefits and harms of using G-CSF in the course of tumor therapy. In this study, the causal relationship and mechanism of action between G-CSF, classified as an inflammatory factor, and NPC were investigated. These findings corroborated the conclusions of previous studies that G-CSF promotes tumor progression. However, the study's analysis of the causal relationship between 41 inflammatory factors and NPC in terms of MR is limited by the absence of corroborating research evidence and the need for high-quality clinical randomized controlled trials to validate the findings. The findings are subject to certain limitations; therefore, in future studies, the inclusion of data from larger samples and more rates will be necessary to draw more generalizable results. Declarations Acknowledgments The authors are grateful to the GWAS and Finngen studies. Funding Statement The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. MJ was supported by the “co-financed project of Guangzhou Science and Technology Bureau Municipal School (College) (202201020515)”. Data availability statement The datasets of this study can be found from online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material. Ethics statement The data used in this study were obtained from publicly aggregated IEU Open GWAS and Finngen. Therefore, no additional ethical approval was required for the study. Author contributions KL: Project administration, Writing-review and editing, Writing-original draft, Methodology, Software, Validation, Visualization. JH: Project administration, Writing-review and editing, Data curation, Methodology, Supervision, Validation, Visualization. GQ: Conceptualization, administration, Validation, Writing-review and editing. MJ: Conceptualization, Funding acquisition, Project administration, Validation, Writing-review and editing. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6129830","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":423219320,"identity":"40678387-a8b3-4534-83a6-fcdd6c6d5fac","order_by":0,"name":"Keyun Lin","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Keyun","middleName":"","lastName":"Lin","suffix":""},{"id":423219321,"identity":"3c3c443d-1866-4f5b-a843-36f4561e30c9","order_by":1,"name":"Jiaxiang Hu","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiaxiang","middleName":"","lastName":"Hu","suffix":""},{"id":423219322,"identity":"a6789eec-de45-440a-9c66-1855a2250b0b","order_by":2,"name":"Guanying Qiao","email":"","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Guanying","middleName":"","lastName":"Qiao","suffix":""},{"id":423219323,"identity":"204c3e0b-a867-4da3-8b47-6cde70e4c801","order_by":3,"name":"Mei Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYBACxmYIzcPG39j44ANMmIcYLXwShw8bziBGCxzIMaSlCcNV4tPC3M787OHXHBsZNoYzZsw2v+oS+6cdYHzwto1B3hynw9jMjWW3pfGwMfeYPc7tY0uccTuB2XBuG4PhzgacfjGTltx2mAdoi7lxbg9P4gbpBDZp3jaGBIMDuLSwfwNq+Q/UkmMmbdkjAdLC/hu/Fh4zyY/bDgC1pKVJM/wwANvCTEBLmTTjtmQeNlAg9zYkGM+4ndgsOeechOEGHFoM+49vk/y5zc5evh8YlT/+1Mn2z04++OFNmY08LlsMgcHCDI8FxjYwCRRjkMCuHgjkQUp+wLl/cCocBaNgFIyCEQwA6LxWvHRi21EAAAAASUVORK5CYII=","orcid":"","institution":"Guangzhou University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Mei","middleName":"","lastName":"Jiang","suffix":""}],"badges":[],"createdAt":"2025-02-28 15:23:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6129830/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6129830/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77702657,"identity":"1c18cea5-4c1c-429b-870a-fb90e2ab103f","added_by":"auto","created_at":"2025-03-04 11:33:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73673,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of MR analysis assumptions\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6129830/v1/811e43b05bf73f9aa4d10d67.png"},{"id":77702658,"identity":"2004f579-6cb5-4c1a-9290-b7f63847467d","added_by":"auto","created_at":"2025-03-04 11:33:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77345,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of MR analysis of G-CSF levels and NPC\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6129830/v1/2ee3a41a6c79fa6b6a06d602.png"},{"id":77702659,"identity":"80890471-b4cf-4f52-855a-eae97fce4b47","added_by":"auto","created_at":"2025-03-04 11:33:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54308,"visible":true,"origin":"","legend":"\u003cp\u003eMR analysis of G-CSF levels and NPC based on leave-one-out method\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6129830/v1/5ee9ed4880f76acab60a8953.png"},{"id":77702665,"identity":"9e58ce91-5b87-4383-9128-c4b7022209c5","added_by":"auto","created_at":"2025-03-04 11:33:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":92806,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot of MR analysis of G-CSF levels and NPC\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6129830/v1/b3d7b3e1b2d288f070838cfd.png"},{"id":83984228,"identity":"5322b52b-5cb4-463d-b1bb-d9b54e7f0ac9","added_by":"auto","created_at":"2025-06-05 10:39:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":825222,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6129830/v1/17e7717b-d71b-47bd-827c-7bc8f73c833a.pdf"},{"id":77702656,"identity":"57c9219f-3646-42c7-ac57-4ea60098ca86","added_by":"auto","created_at":"2025-03-04 11:33:40","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22825,"visible":true,"origin":"","legend":"","description":"","filename":"additionalfile.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6129830/v1/6c236494a3a6ec6fb0bdb25d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Two-sample Mendelian randomization analysis of the relationship between inflammatory factors and nasopharyngeal carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNasopharyngeal carcinoma (NPC) is a malignant tumor originating from the nasopharyngeal epithelium with obvious epidemiological characteristics of regional aggregation and population susceptibility. The Chinese population exhibits a high incidence of NPC, with the Guangdong province of China demonstrating a particularly elevated rate of this malignancy. This observation has led to the colloquial designation of the disease as \u0026ldquo;Guangdong carcinoma\u0026rdquo;.\u003c/p\u003e \u003cp\u003eNPC demonstrates highly sensitive to radiotherapy and chemotherapy. Patients often experience enhanced therapeutic outcomes following systematic treatment regimens. However, these treatments are associated with numerous adverse reactions, which can result in physiological and psychological dysfunction. Consequently, patients may experience a decline in their quality of life and a decrease in treatment motivation. NPC is characterized by its high degree of invasiveness, which is manifested in its biological behavior. This invasive nature leads to strong regional invasion and distant metastasis, resulting in a high risk of recurrence and metastasis after treatment. Local recurrence and distant metastasis are the primary factors contributing to mortality in cases of NPC\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Therefore, it is imperative to identify a treatment that is both efficacious and devoid of deleterious side effects, while also ensuring its sustainability to enhance the quality of life and extend the survival duration of patients.\u003c/p\u003e \u003cp\u003eThe tumor microenvironment (TME) is composed of tumor cells and a multitude of other cell types. It is the milieu that fosters tumorigenesis and tumor development. Tumor cells secrete an array of inflammatory factors and recruit inflammatory cells, which form an integral component of the tumor microenvironment. Tumor-related inflammation is a hallmark manifestation of tumors. Inflammation pathways activated by inflammatory factors, such as PI3K/Akt, MAPK/ERK, NF-κB and JAK/STAT, etc., are classic tumor-related pathways. The tumor microenvironment establishes an internal milieu conducive to tumor growth, metastasis, immune escape, and angiogenesis by mediating common pathways of inflammation and tumors. Anti-inflammatory therapy is regarded as a means of mitigating the occurrence of tumors and the associated risk of mortality, signifying a prospective avenue for anti-tumor treatment.\u003c/p\u003e \u003cp\u003eNPC has been shown to be associated with Epstein-Barr virus infection. Epstein-Barr virus has been shown to induce an inflammatory response in NPC cells, thereby promoting the production of inflammatory factors and contributing to the formation of the TME of NPC\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In addition, the inflammatory microenvironment, under the long-term influence of inflammatory factors such as CCL3, CCL4, IL-1β, IL-6, IL-8 and IL-10, increases the risk of NPC pathogenesis and metastasis\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. The present study was guided by the hypothesis that inflammatory responses have a carcinogenic effect on malignant tumors.\u003c/p\u003e \u003cp\u003eTo investigate the causal relationship between inflammatory factors and the incidence of NPC, genetic instrumental variables were derived through Mendelian randomization (MR). We hope that our study will provide ideas and references for future research on the prevention and treatment of NPC.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003eThe causal relationship between 41 inflammatory factors and NPC is to be evaluated based on a two-sample MR analysis. 41 inflammatory factors were utilized as exposure factors, NPC as an outcome factor, and genetic variants with significant statistical significance in the inflammatory factors, namely single nucleotide polymorphisms (SNPs), were selected as instrumental variables (IVs) for the two-sample MR analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Data sources\u003c/h2\u003e \u003cp\u003eA publicly available genome-wide association study (GWAS) database was selected for the present analysis, and the data on exposure factors and outcome factors were obtained from the Finnish population in Europe. Refer to previous studies, the data for 41 inflammatory factors were obtained from an investigation included in the NHGRI-EBI Catalog database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/gwas\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/gwas\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) concerning the genetic associations of circulating inflammatory factors in 8,293 Finns (GWAS ID: ebi-a-GCST004458)\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. This investigation encompasses population cohort data from three autonomous studies: the \"Cardiovascular Risk in Young Finns study\", \"FINRISK1997\", and \"FINRISK2002\". Detailed information on these 41 inflammatory factors can be found in Supplementary material. The data for NPC were derived from a research project entitled \"Malignant neoplasm of nasopharynx (controls excluding all cancers)\" in the FINNGEN database(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://r11.finngen.fi\u003c/span\u003e\u003cspan address=\"https://r11.finngen.fi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The data for NPC were based on the results of 89 cases of NPC compared with 345,118 healthy individuals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.3 IVs selection\u003c/h2\u003e \u003cp\u003eThe IVs in this study met the following hypotheses (Fig.\u0026nbsp;1): (1) Correlation Hypothesis: IVs are strongly associated with exposure factors; (2) Independence Hypothesis: IVs are not associated with confounders; (3) Exclusion Hypothesis: IVs influence outcome factors only through exposure factors. In selection process of IVs, given that there were few SNPs satisfying the p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e condition, the SNPs significance level was set to \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e to ensure relevance\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e; for linkage disequilibrium SNP elimination, set the coefficient to \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and kb\u0026thinsp;\u0026lt;\u0026thinsp;10000; based on the formula \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:F=\\frac{{R}^{2}\\left(n-1-k\\right)}{\\left(1-{R}^{2}\\right)k}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}^{2}=2\\times\\:\\left(1-MAF\\right)\\times\\:MAF\\times\\:\\frac{\\beta\\:}{SD}\\)\u003c/span\u003e\u003c/span\u003e to remove SNPs with \u003cem\u003eF\u003c/em\u003e\u0026le;10 to avoid weak IVs correlation bias\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e; remove SNPs associated with confounders using the LDlink database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ldlink.nih.gov/\u003c/span\u003e\u003cspan address=\"https://ldlink.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), remove palindromic sequences to achieve allelic alignment and eliminate duplicate SNPs. In the reverse MR analysis, the SNP screening criteria we applied was the same as the forwards MR analysis, which is P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;6\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eInverse-Variance Weighted (IVW), MR-Egger, Weighted Median, Simple Mode, and Weighted Mode were selected for MR analysis. The IVW method has the highest test efficiency when horizontal pleiotropy of instrumental variables does not exist; therefore, it was used as the primary analysis method\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. The Bonferroni correction formula is 0.05/ (number of exposures included in the study * number of outcomes included in the study) \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Therefore, in the study, P values of less than 0.0012 (0.05/41) were considered to indicate a strong association, and P values between 0.0012 and 0.05 were considered to indicate a suggestive association.\u003c/p\u003e \u003cp\u003eTo ensure the robustness of the analysis results, Cochran's Q test was used to assess heterogeneity in IVW and MR-Egger; the leave-one-out analysis was used to test whether a single SNP had an excessive influence on the results of the MR analysis, and MR-Egger regression analysis was used to test for horizontal pleiotropy and visualize the analysis results.\u003c/p\u003e \u003cp\u003eIn the reverse MR analysis, genetic data of NPC were used as exposure, while genetic data of 41 inflammatory factors were used as outcome to determine whether there was a reverse causality between NPC and inflammatory factors. The screening criteria for SNPs were as serious as those in the forwards MR analysis.\u003c/p\u003e \u003cp\u003eThe Steiger direction test is a methodological instrument employed for the purpose of analyzing to analyze and subsequently determining the direction of the causal relationship between exposure and outcome factors. The utilization of Steiger direction test guarantees a robust correlation between the exposure factor and SNPs, while ensuring that the SNPs exclusively influence the outcome factor through the exposure factor. This methodological framework precludes the occurrence of bias owing to reverse causality \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e5 Statistical analysis software settings\u003c/h3\u003e\n\u003cp\u003eStatistical analysis was conducted using the \"TwoSampleMR\" package in R software (version 4.4.1) \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, with a statistical significance threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The relationship between exposure and the outcome factors was quantified using odds ratio (OR). An OR of 1 indicated that the exposure factor was not associated with the outcome factor. An OR greater than 1 indicates that the exposure factor is a risk factor for the outcome factor, while an OR less than 1 indicates that the exposure factor is a protective factor for the outcome factor.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 IVs\u003c/h2\u003e\n \u003cp\u003eFollowing the elimination of linkage disequilibrium, SNPs associated with confounding factors, SNPs with reverse sequences, and SNPs with weak instrumental variables, a total of 8 SNPs remained.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 The forwards MR analysis\u003c/h2\u003e\n \u003cp\u003eTo account for any linkage disequilibrium, we excluded IVs with an r\u003csup\u003e2\u003c/sup\u003e value below 0.01 within a range of 1000KB. The calculation formula of the F value was used to value the F values of the IVs selected in this study. The effect of them were found to be strong, because the F values were all greater than 10. No confounding factors were association with NPC.\u003c/p\u003e\n \u003cp\u003eAfter MR analysis of each inflammatory factor and NPC, it was found that there was a positive causal relationship between granulocyte colony-stimulating factor (G-CSF) and NPC (IVW-\u003cem\u003eOR\u003c/em\u003e: 3.659, 95% \u003cem\u003eCI\u003c/em\u003e: 1.398\u0026ndash;9.581, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). The results of the IVW, MR-Egger, Weighted Median, and Weighted Mode provide substantial evidence that supports the conclusion that G-CSF levels are associated with an increased risk of NPC (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig. 2). The results of the simple mode analysis did not attain statistical significance; however, the OR value corroborated the hypothesis that G-CSF levels have the potential to elevate the risk of NPC. (Fig. 3).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1: MR analysis results of G-CSF levels and NPC\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eMR analysis method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eMR-Egger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e6.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.481-25.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eWeighted median\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.018-15.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eInverse variance weighted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.398-9.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eSimple mode\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e1.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e2.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e0.181-22.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 208px;\"\u003e\n \u003cp\u003eWeighted mode\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e8.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.716-40.275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e=beta value\u003cem\u003e, SE\u003c/em\u003e=Standard Error\u003cem\u003e, OR\u003c/em\u003e=odds ratio,\u0026nbsp;95%\u003cem\u003eCI\u003c/em\u003e=confidence interval, \u003cem\u003eP\u003c/em\u003e=P value\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 The reverse MR analysis and MR Steiger test\u003c/h2\u003e\n \u003cp\u003eIn the reverse MR analysis, although the SNP screening criteria we applied were the same as those in forwards MR analysis, there were no suitable SNPs. This finding indicates that genetic vulnerability to NPC does not have a substantial impact on genetic predisposition to inflammatory factors. The causal relationship between NPC and inflammatory factors is influenced by complex confounding factors, necessitating discussion of the potential association between inflammatory factors and NPC.\u003c/p\u003e\n \u003cp\u003eThe results of the Steiger direction test demonstrated a strong relation between SNPs and G-CSF levels (exposure factor \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.032\u0026thinsp;\u0026gt;\u0026thinsp;outcome factor \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0). The direction of the overall SNPs and each SNP affecting NPC were TRUE (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that there is no reverse causality.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Sensitivity analysis\u003c/h2\u003e\n \u003cp\u003eThe scatter plot demonstrated that the direction of causality was consistent across the five analysis methods (Fig.\u0026nbsp;4).\u003c/p\u003e\n \u003cp\u003eThe Cochran Q test values for IVW (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.537) and MR-Egger (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.533) were not statistically significant, indicating that there was no heterogeneity among the included SNPs and no potential bias in the association between G-CSF levels and NPC. The value of the MR-Egger regression analysis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.370) was not statistically significant, and the intercept of -0.1142308 was close to 0, indicating that there was no horizontal pleiotropy and that the association between G-CSF levels and NPC is not influenced by other factors. The leave-one-out analysis demonstrates that the results following the exclusion of each SNP are not significantly different from the overall results, thus indicating that the results of the MR analysis are robust and not driven by a single IV.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe inflammatory environment is a critical factor in tumor development and can influence the microenvironment of tumor growth by altering tissue homeostasis. Inflammatory factors in the TME are critical for the regulation of various cellular processes including cell proliferation, differentiation, migration, and apoptosis. Inflammatory factors play pivotal roles in the regulation of both inflammatory response and immune response processes. Inflammatory factors exert their influence on the TME through a complex network of bidirectional regulatory mechanisms. On the one hand, some inflammatory factors can stimulate the immune response to play an anti-tumor effect, and on the other hand, some inflammatory factors can induce the immune escape to play a tumor-promoting role\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. In consideration of the paradoxical state of inflammatory factors in tumors, the present study elected to utilize a MR analysis, with the objective of elucidating the role of inflammatory factors in the occurrence and development of NPC. According to the results of MR analysis in this study, G-CSF levels in inflammatory factors are risk factors for NPC.\u003c/p\u003e \u003cp\u003eG-CSF is a glycoprotein belonging to the hematopoietic growth factor, inflammatory factor, and immune stimulating factor. It is capable of promoting the differentiation and proliferation of neutrophil progenitor cells and enhancing the function of mature neutrophils. G-CSF is commonly used in the treatment of neutropenia caused by various reasons. The biological effects of G-CSF are mediated by the G-CSF receptor (G-CSFR), which is primarily involved in cell differentiation and proliferation. G-CSF has been observed to trigger the activation of signaling molecules, including pro-inflammatory transcription factors such as STAT1, STAT3, and STAT5. These molecules activate three major signaling pathways: PI3K/AKT, MAPK/ERK, and JAK/STAT\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Under normal conditions, the activation of these signaling pathways leads to the maturation and mobilization of neutrophils into the bloodstream. Conversely, abnormal activation or mutation of the G-CSFR pathway can affect tumor cells directly, thereby playing a significant role in tumor growth, invasion, metastasis, angiogenesis, and immune escape\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. G-CSF and G-CSFR have been found to promote tumor progression in cellular and animal experiments\u003csup\u003e[\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e, and their tumor-promoting mechanisms are as follows: enhancement of epithelial-to-mesenchymal cell transformation through M2 macrophage recruitment, which promotes tumor growth; induction of bone marrow endothelial progenitor cell mobilization, which promotes angiogenesis and tumor regeneration; activation of tumor cell gelatinases through receptors, which promotes tumor metastasis; inflammatory and immunomodulatory effects by mediating innate and adaptive immune responses, inhibiting the expression of CD4+, CD8+, and CD16\u0026thinsp;+\u0026thinsp;cells, which in turn inhibits the mobilization and activity of NK cells, macrophages, and T cells, contributing to the acquisition of immune escape by tumor \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Furthermore, elevated levels of G-CSF, along with the presence of G-CSFR expression-positive tumors, are associated with a biologically more malignant state, reduced differentiation, and a worse clinical prognosis\u003csup\u003e[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Relevant studies have shown that in head and neck cancer, including NPC, tumor-produced G-CSF can lead to poor patient prognosis by regulating the PI3K-AKT pathway, Mcl-1 expression, Granulocyte bone marrow-derived inhibitory cell-dependent mechanisms and caspase-3 levels. Even G-CSF has been identified as a predictor of tumor growth and poor prognosis in head and neck cancers such as nasopharyngeal carcinoma \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. However, given that the majority of prior studies were primarily focused on fundamental experiments and clinical trials, they were unavoidably influenced by confounding factors and reverse causation, leading to a certain degree of result bias. In the present study, MR analysis was utilized to ascertain the association between G-CSF levels and the risk of NPC at the level of genetic variation, while excluding the effect of confounding factors.\u003c/p\u003e \u003cp\u003eThe administration of chemotherapy and radiation therapy to treat malignancies can result in bone marrow suppression, leading to a decrease in the number of neutrophils. In cases of severe neutrophil deficiency, the therapeutic or prophylactic administration of G-CSF is necessary to elevate neutrophil levels. G-CSFR is prevalent in primary and metastatic foci of head and neck tumors, and it produces G-CSF by autocrine or paracrine secretion and shows high expression\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Given the direct action of exogenous G-CSF on G-CSFR-positive tumors, patients with NPC and neutrophil deficiencies are imperative to assess G-CSFR expression to select the appropriate therapeutic dose prior to G-CSF supplementation. Concurrently, G-CSF can be utilized as a potential tumor marker to observe disease progression in specific tumors or to evaluate effects of therapy. Inhibition of G-CSF and blockade of G-CSFR may offer therapeutic benefits in the treatment of specific tumors. The targeting of G-CSF and G-CSFR has emerged as a promising therapeutic strategy\u003csup\u003e[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eG-CSF levels in inflammatory factors function as risk factors for NPC. G-CSF has the capability of exerting its influence on the TME by binding to the G-CSFR of tumor cells and activating signaling pathways such as PI3K/AKT, MAPK/ERK, JAK/STAT, and others. Such pathways serve as mediators of a multitude of critical processes, including tumor proliferation, invasion, metastasis, apoptosis, angiogenesis, immune escape, and numerous additional aspects. Meanwhile, exogenous supplementation of G-CSF promotes the progression of G-CSFR-expressing tumors, leading to high levels of G-CSF which are associated with poor patient prognosis. This suggests that clinical care is needed to assess the benefits and harms of using G-CSF in the course of tumor therapy.\u003c/p\u003e \u003cp\u003eIn this study, the causal relationship and mechanism of action between G-CSF, classified as an inflammatory factor, and NPC were investigated. These findings corroborated the conclusions of previous studies that G-CSF promotes tumor progression.\u003c/p\u003e \u003cp\u003eHowever, the study's analysis of the causal relationship between 41 inflammatory factors and NPC in terms of MR is limited by the absence of corroborating research evidence and the need for high-quality clinical randomized controlled trials to validate the findings. The findings are subject to certain limitations; therefore, in future studies, the inclusion of data from larger samples and more rates will be necessary to draw more generalizable results.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the GWAS and Finngen studies.\u003c/p\u003e\n\u003cp\u003eFunding Statement\u003c/p\u003e\n\u003cp\u003eThe author(s) declare that financial support was received for the research, authorship, and/or publication of this article. MJ was supported by the \u0026ldquo;co-financed project of Guangzhou Science and Technology Bureau Municipal School (College) (202201020515)\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eData availability statement\u003c/p\u003e\n\u003cp\u003eThe datasets of this study can be found from online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.\u003c/p\u003e\n\u003cp\u003eEthics statement\u003c/p\u003e\n\u003cp\u003eThe data used in this study were obtained from publicly aggregated IEU Open GWAS and Finngen. Therefore, no additional ethical approval was required for the study.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eKL: Project administration, Writing-review and editing, Writing-original draft, Methodology, Software, Validation, Visualization. JH: Project administration, Writing-review and editing, Data curation, Methodology, Supervision, Validation, Visualization. GQ: Conceptualization, administration, Validation, Writing-review and editing. MJ: Conceptualization, Funding acquisition, Project administration, Validation, Writing-review and editing.\u003c/p\u003e\n\u003cp\u003eConflict of interest\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003ePublisher\u0026rsquo;s note\u003c/p\u003e\n\u003cp\u003eAll claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMa SB, Lin DD, Liu HY. Inflammatory cytokines as therapeutic targets in tumor immunotherapy. 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Drug Resist Updat. 2022;64:100849. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.drup.2022.100849\u003c/span\u003e\u003cspan address=\"10.1016/j.drup.2022.100849\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"nasopharyngeal carcinoma, inflammatory factors, tumor microenvironment, granulocyte colony-stimulating factor, Mendelian randomization","lastPublishedDoi":"10.21203/rs.3.rs-6129830/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6129830/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNasopharyngeal carcinoma (NPC) is an important health concern worldwide. Previous studies are susceptible to confounding factors. To solve this problem, this study uses Mendelian randomization (MR) to discover the causal relationship between inflammatory factors and NPC from a genetic perspective.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA two-sample MR analysis was performed using data from genome-wide association analysis studies of 41 inflammatory factors and NPC. The following methods were used to analyze the causal relationship between inflammatory factors and NPC: Inverse-Variance Weighted, MR-Egger, Weighted Median, Simple Mode and Weighted Median. MR Steiger test was used to determine the direction of the interaction between inflammatory factors and NPC. The robustness of the analysis was ensured by means of Cochran's Q test, leave-one-out analysis and MR-Egger regression analysis. Reverse MR was performed to investigate whether there is reverse causality between inflammatory factors and CTS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere was a positive causal relationship between granulocyte colony-stimulating factor (G-CSF) levels and NPC (\u003cem\u003eOR\u003c/em\u003e: 3.659, 95% \u003cem\u003eCI\u003c/em\u003e: 1.398\u0026ndash;9.581, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0. 008), and there was no pleiotropy or reverse causality between the level of G-CSF and NPC. The sensitivity analysis showed that the results of the analyses did not contain heterogeneity, horizontal pleiotropy, or individual single nucleotide polymorphisms that significantly influenced the results of the analyses.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eG-CSF is a potential risk factor for NPC. The results of this study may provide new research ideas for identifying tumor markers and therapeutic targets for NPC..\u003c/p\u003e","manuscriptTitle":"A Two-sample Mendelian randomization analysis of the relationship between inflammatory factors and nasopharyngeal carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-04 11:33:36","doi":"10.21203/rs.3.rs-6129830/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0e1445c5-9ef2-4cba-a0e0-625be0b1774c","owner":[],"postedDate":"March 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-05T10:38:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-04 11:33:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6129830","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6129830","identity":"rs-6129830","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}