Genetically predicted 15 circulating blood cell traits and Esophageal Cancer：a comprehensive Mendelian randomization study

Genetically predicted 15 circulating blood cell traits and Esophageal Cancer：a comprehensive Mendelian randomization study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetically predicted 15 circulating blood cell traits and Esophageal Cancer：a comprehensive Mendelian randomization study Xiang long li, Wanying Xie, Yu Tan, Shaofeng Yang, Qingyu Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4250357/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Epidemiologic evidence indicates that circulating blood cell traits may be linked to both the incidence and outcome of Esophageal Cancer. Nevertheless, these studies are at risk of being influenced by confounding factors. In our research, we conducted Mendelian randomization to explore the potential causal association between circulating blood cell traits and EC. Methods : This study utilized genome-wide association studies (GWAS) datasets to analyze genetic variation using a two-sample MR design. The EC data was obtained from a GWAS study involving 740 cases and 372,016 controls (identifier: ieu-b-4960), while data for 15 circulating blood cell traits were sourced from a GWAS with 562,132 participants. Various statistical methods including Inverse variance weighted (IVW), Weighted median, MR Egger regression, Weighted mode, and Simple mode were employed to assess the causal connection between the circulating blood cell traits and EC. Additionally, a series of sensitivity analyses were conducted to ensure the robustness of the findings. Results : The results found significant association between elevated circulating BAS counts (odds ratio, OR: 1.0012, 95 % confidence interval, CI: 1.0004-1.0020, p =0.0037), and decreased circulating levels of HBG (OR: 0.9994, 95% CI: 0.9989-1.0000, p =0.0403) with the risk of EC in the IVW approach. In addition,circulating blood cell traits including MPV (OR: 0.0506, 95% CI:0.0034 -0.7435, p =0.0295 ) and LYM (OR: 0.1356, 95% CI:0.0209-0.8816, p =0.0364) are suggested to be the consequences of EC Conclusions : In this research, we systematically examined the association between the 15 circulating blood cell traits and the occurrence of EC. We identified upstream regulators (BAS counts) and downstream effectors (HBG concentration) associated with EC. In addition, EC affects circulating levels of LYM counts and MPV. Our results provide valuable insights into the role of circulating blood cell traits in the development of EC, offering new avenues for further research and potential interventions in the prevention and management of EC. Circulating blood cell traits Esophageal cancer Mendelian randomization genome-wide association study Figures Figure 1 Introduction Esophageal cancer (EC) is a prevalent malignant tumor within the digestive system, presenting high incidence, mortality rates, and poor outlook. Epidemiological data reveals EC as the seventh most frequent global cancer type and the sixth largest contributor to cancer-related deaths. In 2020, there were 604,000 new EC cases recorded, with approximately 545,000 resulting in fatalities [ 1 , 2 ]. On a global scale, the number of new esophageal cancer cases is projected to increase from 73,966 in 2020 to 987,723 in 2040, with corresponding death rates of 723,466 in 2030 and 914,304 in 2040. This represents a rise of 31.4% and 33.0% in cases, and 63.5% and 68.0% in deaths, respectively[ 3 ]. Currently, surgical resection combined with neoadjuvant radiotherapy and other multidisciplinary therapies are considered to be the best treatment modality for esophageal cancer, but due to the limitations of the lack of early symptoms and low early diagnosis rate, most of the patients have already progressed to the advanced stage of the cancer by the time the diagnosis is made, and they have missed the optimal time for surgery, and the local recurrence rate and distant metastasis rate are still very high, and the longterm survival is not optimist[ 4 ] .Therefore, Identification of the factors that contribute to the development of EC is urgently needed for early diagnosis and treatment. Circulating blood cell traits such as White blood cell(WBC)counts, red blood cell (RBC) counts, lymphocyte༈LYM༉counts, hemoglobin (HBG) concentration and hematocrit (HCT) are tested during routine blood tests and are one of the common indicators for assessing physical health[ 5 , 6 ]. Changes of circulating blood cell traits have been found to be strongly associated with the susceptibility, severity, progression, prognosis and mortality of diseases. For example, Decreased levels of eosinophils and basophils, both important components of the immune system's response to IgE-mediated immunity, have been found to be associated with an increased risk of developing EC and poorer survival outcomes.[ 7 , 8 ]. In addition, anemia, which is the low level of HBG concentration in the blood, increases the risk of many malignant tumors such as EC and liver cancer and is associated with their sensitivity to treatment and prognosis[ 9 ]. While observational studies have indicated a significant correlation between circulating blood cell traits and endometrial cancer, it is important to recognize the limitations of these findings. The sample sizes of the studies are often relatively small, which can impact the reliability of the results. Additionally, there may be biases present in the data collection and analysis processes that could influence the accuracy of the conclusions drawn from these studies[ 10 ]. Consequently, to establish a clear link between circulating blood cell traits and EC, it is imperative to implement a more rigorous study design that effectively reduces or eliminates any potential biases. Mendelian randomization (MR) utilizes single-nucleotide polymorphisms (SNPs) as instrumental variables to determine potential causal relationships between exposure and outcome by minimizing the impact of confounding factors and nonmeasurement errors[ 11 ]. By adhering to Mendelian inheritance laws, MR can help avoid issues such as reverse causality[ 12 ]. Consequently, This study sought to investigate the causal link between circulating blood cell traits and EC through a thorough two-sample bidirectional MR analysis. Study design To find the relationship between the risk of circulating blood cell traits and EC, we used a two-sample MR method. Figure 1 clearly explains the study design. This study utilized SNPs as instrumental factors to evaluate the relationship between exposure factors (15 circulating blood cell traits) and outcome (EC). A successful Mendelian randomization analysis hinges on the following key assumptions: correlation, which indicates a strong relationship between genetic variation and the exposure being studied; independence, which suggests that genetic variation is not influenced by any confounding variables that could distort the relationship between exposure and outcome; and exclusion restriction, which posits that genetic variation impacts the outcome solely through the exposure being investigated. Correlation is essential for ensuring that any genetic influence on the exposure factor is accurately reflected in the analysis. Independence is crucial in order to eliminate the possibility of confounding variables skewing the results and leading to incorrect conclusions. Exclusion restriction helps to establish a clear causal pathway between genetic variation and the outcome, attributing any effects solely to the exposure being studied.In conclusion, adherence to these three basic assumptions is paramount in conducting a successful Mendelian randomization analysis. By ensuring correlation, independence, and exclusion restriction are met, researchers can accurately assess the causal association between genetic variation, exposure, and outcome in their studies.[ 13 ]. Data collection Data related to EC were obtained from the IEU Open GWAS public database, specifically the GWAS summary dataset ID "ieu-b-4960." This dataset was utilized to investigate the genetic variants associated with EC, sourced from the United Kingdom Biobank with the latest update available in 2021. The GWAS included 740 individuals diagnosed with EC and 372,016 controls, providing a comprehensive dataset for analysis and interpretation.One of the key challenges in Mendelian randomization (MR) studies is the potential bias introduced by population stratification, where allele frequencies can vary across different ancestral populations. [ 14 ]. To mitigate this bias, summary statistics for circulating blood cell traits were gathered from a study involving 746,667 participants, of which 184,535 were non-European populations. To ensure consistency and accuracy in the analysis, only data from studies with populations of European ancestry totaling 562,132 individuals were selected for inclusion[ 15 ].This approach aimed to minimize confounding factors and enhance the reliability of the findings related to genetic associations with EC. The selection of instrumental variables To explore the causal link between blood cell traits and EC, a thorough selection process was carried out for instrumental variables (IVs) along with quality control measures. Initially, genome-wide significant SNPs were identified from the GWAS database utilizing a strict threshold of P < 5×10 –8 . Nonetheless, given the scarcity of SNPs meeting this criteria for most EC cases (fewer than 3), a less stringent significance threshold (P < 5×10 –6 ) was adopted for IVs selection. After this selection process, SNPs were clustered based on the European 1000 Genomes Project reference panel to evaluate their independence (r 2 < 0.01 and clump distance = 10,000 kb). Feeble IVs with F-statistics below 10 were eliminated from the analysis due to their inadequate robustness, emphasizing the significance of utilizing strong IVs in the research. On the whole, the process involved in selecting instrumental variables and conducting quality control measures in the investigation of the causal relationship between blood cell traits and EC was meticulous and systematic. By carefully choosing SNPs with significant thresholds and evaluating their independence and strength as IVs, the investigation strived to ensure the dependability and validity of the findings obtained. The exclusion of weak instrumental variables underscored the importance of using robust IVs to establish a solid foundation for the analysis and interpretation of data. Statistical analysis In this research, we utilized the R programming language (version 4.3.2) to investigate the potential causal link between characteristics of circulating blood cells and susceptibility to EC. The main analytical approach employed was inverse variance weighting (IVW) for evaluating the impact of exposure on the final outcome. To ensure the accuracy of causal estimations, adherence to the three fundamental principles of Mendelian randomization (MR) studies was essential.While IVW is a valuable tool, it is not without limitations, especially since it heavily relies on the aforementioned assumptions and can only account for confounders in the absence of horizontal pleiotropy. It is crucial to account for potential impacts arising from horizontal pleiotropy when utilizing the IVW method.Hence, to validate our findings, we also employed various alternative techniques such as Weighted Median, Weighted Mode, MR Egger, Simple Mode, and MR-Presso to evaluate the causal association between exposure and outcome. The combination of MR-Egger and MR-Presso was used to identify horizontal pleiotropy (significant at P < 0.05). Additionally, Cochran's Q test was conducted to detect heterogeneity among the chosen SNPs (significant at P < 0.05, as indicated in Table 1).Unlike MR-Egger, which assesses horizontal pleiotropy through an intercept test, MR-Presso was capable of detecting and addressing outliers beyond the scope of horizontal pleiotropy. Lastly, we conducted a sensitivity analysis through "leave-one-out" analysis to test the consistency of our results, as shown in Supplementary Figures S1 –S4. Results Genetic prediction suggests a correlation between circulating blood cell traits and susceptibility to EC, as evidenced in our results. Using the IVW method, we found that elevated levels of Basophils (BAS) (OR: 1.0012, 95% CI: 1.0004–1.0020, p = 0.0037) were linked to an increased risk of EC. Analysis did not reveal any horizontal pleiotropy as indicated by the MR-Egger intercept, and both MR-Egger and IVW tests showed no significant heterogeneity (P-value > 0.05). Sensitivity analyses reaffirmed the reliability of these results. Notably, lower HBG levels were associated with a reduced risk of EC (OR: 0.9994, 95% CI: 0.9989-1.0000, p = 0.0403) based on the IVW method. Similarly to the BAS findings, no heterogeneity or pleiotropy was detected in the analysis (P-value > 0.05). Refer to Tables 1 and 2 for detailed results, with additional sensitivity analyses displayed in Supplementary Figures S1 and S2. Switching the perspective to investigate EC as the exposure factor and circulating blood cell traits as the outcome, our study found that EC resulted in a decrease in both Mean platelet volume (MPV) and LYM counts. Odds ratios for these associations were 0.0506 (95% CI: 0.0034–0.7435, p = 0.0295) for MPV and 0.1356 (95% CI: 0.0209–0.8816, p = 0.0364) for LYM counts using the IVW method. No signs of pleiotropy or heterogeneity were noted in these results. Tables 1 and 2 present a comprehensive overview of the findings, and supplemental materials such as the Catter Plot, Funnel Plot, Leave-one-out Analysis, and Forest Plot of BAS on EC are included for further reference. Discussion Recent research has shown a connection between circulating blood cell traits and the occurrence of EC[ 9 ]. However, the majority of existing studies are observational and may be influenced by external factors. In this analysis using Mendelian randomization, genetic data from a GWAS meta-analysis was used to assess the potential causal link between circulating blood cell characteristics and the risk of EC.This study provides new evidence that altered circulating blood traits are associated with EC susceptibility. Circulating blood cell traits have been shown to have a significant correlation with the risk of developing certain types of cancer, including lung cancer, breast cancer, and gastric cancer[ 16 ]. In EC, changes in specific blood cell traits may be strongly associated with susceptibility and prognosis [ 9 ]. Our findings support and expand upon existing observational evidence, highlighting the significant role of certain blood cell traits in the pathophysiology of EC.BAS, a type of leukocyte, can traverse the capillary wall and localize to sites of bacterial invasion to combat infections by surrounding, engulfing, and destroying the pathogens. An increase in BAS counts is often linked to allergic diseases, hematological disorders, malignant tumors, and infectious diseases.[ 17 ].In a prior observational investigation, a correlation was discovered between elevated preoperative BAS counts in blood of patients with EC and the prognosis of EC[ 18 ]. Prior to surgery, lower counts of preoperative BAS were associated with advanced tumor staging and were determined as an autonomous risk element for unfavorable recurrence-free survival (RFS). In cases of EC, individuals with low BAS counts showed a greater predisposition to hematogenous metastasis in contrast to individuals with elevated BAS counts. However, our research proposes that an elevation in BAS counts in the bloodstream could indeed escalate the incidence of EC, contradicting prior results. This discrepancy could be attributed to potential confounding factors in observational studies that may lead to biased results. HBG is a crucial protein responsible for transporting oxygen in red blood cells, giving blood its characteristic red color.[ 19 ]. Hemoglobin levels are commonly used as a marker in blood tests and changes in its levels can indicate various health conditions like anemia[ 20 ], pulmonary heart disease[ 21 ], and cancers[ 22 ]. A previous 12-year cohort study revealed a link between anemia and increased risk of cancers like esophageal, gastric, and breast cancers.[ 9 ].Additionally, the study showed that esophageal cancer patients with high HBG levels prior to surgery had a longer survival time[ 23 ].Our Mendelian randomization analysis aligns with previous observational studies suggesting that hemoglobin levels may lower the risk of EC. The reverse analysis results revealed that EC has the potential to reduce LYM counts in the bloodstream, aligning with the findings of an earlier observational study. The diminished lymphocyte counts in individuals with EC might be attributed to extended tumor length, advanced T stage, a weight loss of ≥ 3 kg and body mass index of ≤ 18.5 kg/m2 within the preceding 3 months[ 24 ]. In addition, the reduced number of LYM severely affected their response to therapy, survival, prognosis, and toxicity [ 25 ]. Additionally, our research uncovered a correlation between EC and the reduction in MPV. While there is a lack of empirical evidence demonstrating a direct link between EC and a decline in MPV, a separate study indicated a marked difference in 5-year overall survival (OS) and recurrence-free survival (RFS) rates between individuals with high MPV and those with low MPV. This study ultimately concluded that elevated MPV served as a stand-alone prognostic indicator for both OS and RFS outcomes[ 8 ]. There are some strengths to our study.Firstly, studies on circulating blood cell traits in patients with EC are very limited, and most of the extant studies are observational. This study is the first to explore the connection between circulating blood cell traits and EC using a large-scale GWAS dataset and MR analysis. By utilizing this method, our findings are more trustworthy compared to observational studies. Additionally, the study's validity was confirmed through the use of an extensive database, stringent adjustments for numerous comparisons, and convenient examination of gene expression in human specimens.However,there are several restrictions in our research.Firstly, our investigation was carried out with a European population and did not encompass other demographics, thus restricting its generalizability. Secondly, we utilized summarized statistical information instead of individual-level data, which impedes our capacity to delve deeper into causal connections among different groups, like males and females. Additionally, the genetic information in the GWAS repository lacks specific disease stages, patient age, and associated medical conditions, preventing us from conducting thorough subgroup analyses. Conclusion Our study focused on analyzing the impact of 15 different circulating blood cell traits on the incidence of EC. We found that the BAS counts and HBG concentration were associated with increased and decreased risk of EC, respectively. Additionally, a reduction in LYM counts and (MPV) may be predictive of the development of EC. These findings provide valuable new information on the underlying mechanisms of EC and could potentially lead to the identification of novel therapeutic targets for the disease. Abbreviations EC Esophageal Cancer MR Mendelian randomization SNPs Single-nucleotide polymorphisms IVs Instrumental variables IVW Inverse variance weighting BAS Basophil Eosin Eosinophil HCT Hematocrit HGB Hemoglobin LYM Lymphocyte MCH Mean corpuscular hemoglobin MCHC Mean corpuscular hemoglobin concentration MCV Mean corpuscular volume Mono Monocyte MPV Mean platelet volume NEU Neutrophil PLT Platelet RBC Red blood cell RDW RBC distribution width WBC White blood cell RFS Recurrence-free survival OS Overall survival Declarations Supplementary material The Supplementary Material for this article can be found online at: Acknowledgements We thank all individuals and investigators for sharing the genome-wide summary statistics from the corresponding GWAS publicly available. Author contributions All authors designed this study. L-XL: Writing-original draft, Writing-review and editing. X-WY and TY: Data curation and Writing-review. Y-SF: Data collection and analysis. Z-QY:Project administration, Supervision, Writing-review and editing. Funding This research received no funding Data availability statement The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021, 71:209–249. Waters JK, Reznik SI. Update on Management of Squamous Cell Esophageal Cancer. Curr Oncol Rep. 2022, 24:375–385. Liu CQ, Ma YL, Qin Q, Wang PH, Luo Y, Xu PF, Cui Y. Epidemiology of esophageal cancer in 2020 and projections to 2030 and 2040. 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Chen MH, Raffield LM, Mousas A, Sakaue S, Huffman JE, Moscati A, Trivedi B, Jiang T, Akbari P, Vuckovic D et al . Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations. Cell. 2020, 182:1198–1213 e1114. Detopoulou P, Panoutsopoulos GI, Mantoglou M, Michailidis P, Pantazi I, Papadopoulos S, Rojas Gil AP. Relation of Mean Platelet Volume (MPV) with Cancer: A Systematic Review with a Focus on Disease Outcome on Twelve Types of Cancer. Curr Oncol. 2023, 30:3391–3420. Chen K, Hao Y, Guzman M, Li G, Cerutti A. Antibody-mediated regulation of basophils: emerging views and clinical implications. Trends Immunol. 2023, 44:408–423. Maruyama S, Okamura A, Kanie Y, Kuriyama K, Sakamoto K, Kanamori J, Imamura Y, Watanabe M. Prognostic significance of circulating basophil counts in patients who underwent esophagectomy for esophageal cancer. Langenbecks Arch Surg. 2023, 408:235. Gell DA. Structure and function of haemoglobins. Blood Cells Mol Dis. 2018, 70:13–42. Balarajan Y, Ramakrishnan U, Ozaltin E, Shankar AH, Subramanian SV. Anaemia in low-income and middle-income countries. Lancet. 2011, 378:2123–2135. Buehler PW, Baek JH, Lisk C, Connor I, Sullivan T, Kominsky D, Majka S, Stenmark KR, Nozik-Grayck E, Bonaventura J et al . Free hemoglobin induction of pulmonary vascular disease: evidence for an inflammatory mechanism. Am J Physiol Lung Cell Mol Physiol. 2012, 303:L312-326. Clarke H, Pallister CJ. The impact of anaemia on outcome in cancer. Clin Lab Haematol. 2005, 27:1–13. Zhang F, Chen Z, Wang P, Hu X, Gao Y, He J. Combination of platelet count and mean platelet volume (COP-MPV) predicts postoperative prognosis in both resectable early and advanced stage esophageal squamous cell cancer patients. Tumour Biol. 2016, 37:9323–9331. Wang JL, Ma R, Kong W, Zhao R, Wang YY. Lymphopenia in Esophageal Cancer: What Have We Learned? Front Oncol. 2021, 11:625963. Inoue H, Shiozaki A, Fujiwara H, Konishi H, Kiuchi J, Ohashi T, Shimizu H, Arita T, Yamamoto Y, Morimura R et al . Absolute lymphocyte count and C-reactive protein-albumin ratio can predict prognosis and adverse events in patients with recurrent esophageal cancer treated with nivolumab therapy. Oncol Lett. 2022, 24:257. Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.pdf Table 1 Heterogeneity test of the IVW and MR egger analyses and pleiotropy test (egger intercept). Table2.pdf Table 2 Bidirectional Mendelian randomization estimates of circulating blood cell traits and EC (IVW, Weighted median, Weighted mode,MR-egger, simple mode ). 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02:29:45","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":349165,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2 Bidirectional Mendelian randomization estimates of circulating blood cell traits and EC (IVW, Weighted median, Weighted mode,MR-egger, simple mode ).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Table2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4250357/v1/fa1c11dfe148c2b9daba5848.pdf"},{"id":55060099,"identity":"976d8065-2576-4443-afa0-a2087ccded76","added_by":"auto","created_at":"2024-04-22 02:21:45","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1066196,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4250357/v1/386d5989d71bdf6d6e3a0a7f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetically predicted 15 circulating blood cell traits and Esophageal Cancer：a comprehensive Mendelian randomization study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEsophageal cancer (EC) is a prevalent malignant tumor within the digestive system, presenting high incidence, mortality rates, and poor outlook. Epidemiological data reveals EC as the seventh most frequent global cancer type and the sixth largest contributor to cancer-related deaths. In 2020, there were 604,000 new EC cases recorded, with approximately 545,000 resulting in fatalities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. On a global scale, the number of new esophageal cancer cases is projected to increase from 73,966 in 2020 to 987,723 in 2040, with corresponding death rates of 723,466 in 2030 and 914,304 in 2040. This represents a rise of 31.4% and 33.0% in cases, and 63.5% and 68.0% in deaths, respectively[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Currently, surgical resection combined with neoadjuvant radiotherapy and other multidisciplinary therapies are considered to be the best treatment modality for esophageal cancer, but due to the limitations of the lack of early symptoms and low early diagnosis rate, most of the patients have already progressed to the advanced stage of the cancer by the time the diagnosis is made, and they have missed the optimal time for surgery, and the local recurrence rate and distant metastasis rate are still very high, and the longterm survival is not optimist[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] .Therefore, Identification of the factors that contribute to the development of EC is urgently needed for early diagnosis and treatment.\u003c/p\u003e \u003cp\u003eCirculating blood cell traits such as White blood cell(WBC)counts, red blood cell (RBC) counts, lymphocyte༈LYM༉counts, hemoglobin (HBG) concentration and hematocrit (HCT) are tested during routine blood tests and are one of the common indicators for assessing physical health[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Changes of circulating blood cell traits have been found to be strongly associated with the susceptibility, severity, progression, prognosis and mortality of diseases. For example, Decreased levels of eosinophils and basophils, both important components of the immune system's response to IgE-mediated immunity, have been found to be associated with an increased risk of developing EC and poorer survival outcomes.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, anemia, which is the low level of HBG concentration in the blood, increases the risk of many malignant tumors such as EC and liver cancer and is associated with their sensitivity to treatment and prognosis[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. While observational studies have indicated a significant correlation between circulating blood cell traits and endometrial cancer, it is important to recognize the limitations of these findings. The sample sizes of the studies are often relatively small, which can impact the reliability of the results. Additionally, there may be biases present in the data collection and analysis processes that could influence the accuracy of the conclusions drawn from these studies[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Consequently, to establish a clear link between circulating blood cell traits and EC, it is imperative to implement a more rigorous study design that effectively reduces or eliminates any potential biases.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) utilizes single-nucleotide polymorphisms (SNPs) as instrumental variables to determine potential causal relationships between exposure and outcome by minimizing the impact of confounding factors and nonmeasurement errors[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. By adhering to Mendelian inheritance laws, MR can help avoid issues such as reverse causality[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Consequently, This study sought to investigate the causal link between circulating blood cell traits and EC through a thorough two-sample bidirectional MR analysis.\u003c/p\u003e"},{"header":"Study design","content":"\u003cp\u003eTo find the relationship between the risk of circulating blood cell traits and EC, we used a two-sample MR method. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e clearly explains the study design. This study utilized SNPs as instrumental factors to evaluate the relationship between exposure factors (15 circulating blood cell traits) and outcome (EC). A successful Mendelian randomization analysis hinges on the following key assumptions: correlation, which indicates a strong relationship between genetic variation and the exposure being studied; independence, which suggests that genetic variation is not influenced by any confounding variables that could distort the relationship between exposure and outcome; and exclusion restriction, which posits that genetic variation impacts the outcome solely through the exposure being investigated. Correlation is essential for ensuring that any genetic influence on the exposure factor is accurately reflected in the analysis. Independence is crucial in order to eliminate the possibility of confounding variables skewing the results and leading to incorrect conclusions. Exclusion restriction helps to establish a clear causal pathway between genetic variation and the outcome, attributing any effects solely to the exposure being studied.In conclusion, adherence to these three basic assumptions is paramount in conducting a successful Mendelian randomization analysis. By ensuring correlation, independence, and exclusion restriction are met, researchers can accurately assess the causal association between genetic variation, exposure, and outcome in their studies.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eData related to EC were obtained from the IEU Open GWAS public database, specifically the GWAS summary dataset ID \"ieu-b-4960.\" This dataset was utilized to investigate the genetic variants associated with EC, sourced from the United Kingdom Biobank with the latest update available in 2021. The GWAS included 740 individuals diagnosed with EC and 372,016 controls, providing a comprehensive dataset for analysis and interpretation.One of the key challenges in Mendelian randomization (MR) studies is the potential bias introduced by population stratification, where allele frequencies can vary across different ancestral populations. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. To mitigate this bias, summary statistics for circulating blood cell traits were gathered from a study involving 746,667 participants, of which 184,535 were non-European populations. To ensure consistency and accuracy in the analysis, only data from studies with populations of European ancestry totaling 562,132 individuals were selected for inclusion[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].This approach aimed to minimize confounding factors and enhance the reliability of the findings related to genetic associations with EC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eThe selection of instrumental variables\u003c/h2\u003e \u003cp\u003eTo explore the causal link between blood cell traits and EC, a thorough selection process was carried out for instrumental variables (IVs) along with quality control measures. Initially, genome-wide significant SNPs were identified from the GWAS database utilizing a strict threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026ndash;8\u003c/sup\u003e. Nonetheless, given the scarcity of SNPs meeting this criteria for most EC cases (fewer than 3), a less stringent significance threshold (P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026ndash;6\u003c/sup\u003e) was adopted for IVs selection. After this selection process, SNPs were clustered based on the European 1000 Genomes Project reference panel to evaluate their independence (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and clump distance\u0026thinsp;=\u0026thinsp;10,000 kb). Feeble IVs with F-statistics below 10 were eliminated from the analysis due to their inadequate robustness, emphasizing the significance of utilizing strong IVs in the research. On the whole, the process involved in selecting instrumental variables and conducting quality control measures in the investigation of the causal relationship between blood cell traits and EC was meticulous and systematic. By carefully choosing SNPs with significant thresholds and evaluating their independence and strength as IVs, the investigation strived to ensure the dependability and validity of the findings obtained. The exclusion of weak instrumental variables underscored the importance of using robust IVs to establish a solid foundation for the analysis and interpretation of data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eIn this research, we utilized the R programming language (version 4.3.2) to investigate the potential causal link between characteristics of circulating blood cells and susceptibility to EC. The main analytical approach employed was inverse variance weighting (IVW) for evaluating the impact of exposure on the final outcome. To ensure the accuracy of causal estimations, adherence to the three fundamental principles of Mendelian randomization (MR) studies was essential.While IVW is a valuable tool, it is not without limitations, especially since it heavily relies on the aforementioned assumptions and can only account for confounders in the absence of horizontal pleiotropy. It is crucial to account for potential impacts arising from horizontal pleiotropy when utilizing the IVW method.Hence, to validate our findings, we also employed various alternative techniques such as Weighted Median, Weighted Mode, MR Egger, Simple Mode, and MR-Presso to evaluate the causal association between exposure and outcome. The combination of MR-Egger and MR-Presso was used to identify horizontal pleiotropy (significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, Cochran's Q test was conducted to detect heterogeneity among the chosen SNPs (significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, as indicated in Table\u0026nbsp;1).Unlike MR-Egger, which assesses horizontal pleiotropy through an intercept test, MR-Presso was capable of detecting and addressing outliers beyond the scope of horizontal pleiotropy. Lastly, we conducted a sensitivity analysis through \"leave-one-out\" analysis to test the consistency of our results, as shown in Supplementary Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S4.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eGenetic prediction suggests a correlation between circulating blood cell traits and susceptibility to EC, as evidenced in our results. Using the IVW method, we found that elevated levels of Basophils (BAS) (OR: 1.0012, 95% CI: 1.0004\u0026ndash;1.0020, p\u0026thinsp;=\u0026thinsp;0.0037) were linked to an increased risk of EC. Analysis did not reveal any horizontal pleiotropy as indicated by the MR-Egger intercept, and both MR-Egger and IVW tests showed no significant heterogeneity (P-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Sensitivity analyses reaffirmed the reliability of these results. Notably, lower HBG levels were associated with a reduced risk of EC (OR: 0.9994, 95% CI: 0.9989-1.0000, p\u0026thinsp;=\u0026thinsp;0.0403) based on the IVW method. Similarly to the BAS findings, no heterogeneity or pleiotropy was detected in the analysis (P-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Refer to Tables\u0026nbsp;1 and 2 for detailed results, with additional sensitivity analyses displayed in Supplementary Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and S2.\u003c/p\u003e \u003cp\u003eSwitching the perspective to investigate EC as the exposure factor and circulating blood cell traits as the outcome, our study found that EC resulted in a decrease in both Mean platelet volume (MPV) and LYM counts. Odds ratios for these associations were 0.0506 (95% CI: 0.0034\u0026ndash;0.7435, p\u0026thinsp;=\u0026thinsp;0.0295) for MPV and 0.1356 (95% CI: 0.0209\u0026ndash;0.8816, p\u0026thinsp;=\u0026thinsp;0.0364) for LYM counts using the IVW method. No signs of pleiotropy or heterogeneity were noted in these results. Tables\u0026nbsp;1 and 2 present a comprehensive overview of the findings, and supplemental materials such as the Catter Plot, Funnel Plot, Leave-one-out Analysis, and Forest Plot of BAS on EC are included for further reference.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRecent research has shown a connection between circulating blood cell traits and the occurrence of EC[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, the majority of existing studies are observational and may be influenced by external factors. In this analysis using Mendelian randomization, genetic data from a GWAS meta-analysis was used to assess the potential causal link between circulating blood cell characteristics and the risk of EC.This study provides new evidence that altered circulating blood traits are associated with EC susceptibility.\u003c/p\u003e \u003cp\u003eCirculating blood cell traits have been shown to have a significant correlation with the risk of developing certain types of cancer, including lung cancer, breast cancer, and gastric cancer[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In EC, changes in specific blood cell traits may be strongly associated with susceptibility and prognosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Our findings support and expand upon existing observational evidence, highlighting the significant role of certain blood cell traits in the pathophysiology of EC.BAS, a type of leukocyte, can traverse the capillary wall and localize to sites of bacterial invasion to combat infections by surrounding, engulfing, and destroying the pathogens. An increase in BAS counts is often linked to allergic diseases, hematological disorders, malignant tumors, and infectious diseases.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].In a prior observational investigation, a correlation was discovered between elevated preoperative BAS counts in blood of patients with EC and the prognosis of EC[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Prior to surgery, lower counts of preoperative BAS were associated with advanced tumor staging and were determined as an autonomous risk element for unfavorable recurrence-free survival (RFS). In cases of EC, individuals with low BAS counts showed a greater predisposition to hematogenous metastasis in contrast to individuals with elevated BAS counts. However, our research proposes that an elevation in BAS counts in the bloodstream could indeed escalate the incidence of EC, contradicting prior results. This discrepancy could be attributed to potential confounding factors in observational studies that may lead to biased results. HBG is a crucial protein responsible for transporting oxygen in red blood cells, giving blood its characteristic red color.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hemoglobin levels are commonly used as a marker in blood tests and changes in its levels can indicate various health conditions like anemia[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], pulmonary heart disease[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and cancers[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A previous 12-year cohort study revealed a link between anemia and increased risk of cancers like esophageal, gastric, and breast cancers.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].Additionally, the study showed that esophageal cancer patients with high HBG levels prior to surgery had a longer survival time[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].Our Mendelian randomization analysis aligns with previous observational studies suggesting that hemoglobin levels may lower the risk of EC.\u003c/p\u003e \u003cp\u003eThe reverse analysis results revealed that EC has the potential to reduce LYM counts in the bloodstream, aligning with the findings of an earlier observational study. The diminished lymphocyte counts in individuals with EC might be attributed to extended tumor length, advanced T stage, a weight loss of \u0026ge;\u0026thinsp;3 kg and body mass index of \u0026le;\u0026thinsp;18.5 kg/m2 within the preceding 3 months[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In addition, the reduced number of LYM severely affected their response to therapy, survival, prognosis, and toxicity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, our research uncovered a correlation between EC and the reduction in MPV. While there is a lack of empirical evidence demonstrating a direct link between EC and a decline in MPV, a separate study indicated a marked difference in 5-year overall survival (OS) and recurrence-free survival (RFS) rates between individuals with high MPV and those with low MPV. This study ultimately concluded that elevated MPV served as a stand-alone prognostic indicator for both OS and RFS outcomes[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are some strengths to our study.Firstly, studies on circulating blood cell traits in patients with EC are very limited, and most of the extant studies are observational. This study is the first to explore the connection between circulating blood cell traits and EC using a large-scale GWAS dataset and MR analysis. By utilizing this method, our findings are more trustworthy compared to observational studies. Additionally, the study's validity was confirmed through the use of an extensive database, stringent adjustments for numerous comparisons, and convenient examination of gene expression in human specimens.However,there are several restrictions in our research.Firstly, our investigation was carried out with a European population and did not encompass other demographics, thus restricting its generalizability. Secondly, we utilized summarized statistical information instead of individual-level data, which impedes our capacity to delve deeper into causal connections among different groups, like males and females. Additionally, the genetic information in the GWAS repository lacks specific disease stages, patient age, and associated medical conditions, preventing us from conducting thorough subgroup analyses.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study focused on analyzing the impact of 15 different circulating blood cell traits on the incidence of EC. We found that the BAS counts and HBG concentration were associated with increased and decreased risk of EC, respectively. Additionally, a reduction in LYM counts and (MPV) may be predictive of the development of EC. These findings provide valuable new information on the underlying mechanisms of EC and could potentially lead to the identification of novel therapeutic targets for the disease.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eEC Esophageal Cancer\u003c/p\u003e \u003cp\u003eMR Mendelian randomization\u003c/p\u003e \u003cp\u003eSNPs Single-nucleotide polymorphisms\u003c/p\u003e \u003cp\u003eIVs Instrumental variables\u003c/p\u003e \u003cp\u003eIVW Inverse variance weighting\u003c/p\u003e \u003cp\u003eBAS Basophil\u003c/p\u003e \u003cp\u003eEosin Eosinophil\u003c/p\u003e \u003cp\u003eHCT Hematocrit\u003c/p\u003e \u003cp\u003eHGB Hemoglobin\u003c/p\u003e \u003cp\u003eLYM Lymphocyte\u003c/p\u003e \u003cp\u003eMCH Mean corpuscular hemoglobin\u003c/p\u003e \u003cp\u003eMCHC Mean corpuscular hemoglobin concentration\u003c/p\u003e \u003cp\u003eMCV Mean corpuscular volume\u003c/p\u003e \u003cp\u003eMono Monocyte\u003c/p\u003e \u003cp\u003eMPV Mean platelet volume\u003c/p\u003e \u003cp\u003eNEU Neutrophil\u003c/p\u003e \u003cp\u003ePLT Platelet\u003c/p\u003e \u003cp\u003eRBC Red blood cell\u003c/p\u003e \u003cp\u003eRDW RBC distribution width\u003c/p\u003e \u003cp\u003eWBC White blood cell\u003c/p\u003e \u003cp\u003eRFS Recurrence-free survival\u003c/p\u003e \u003cp\u003eOS Overall survival\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Supplementary Material for this article can be found online at:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all individuals and investigators for sharing the genome-wide summary statistics from the corresponding GWAS publicly available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors designed this study. L-XL: Writing-original draft, Writing-review and editing. X-WY and TY: Data curation and Writing-review. Y-SF: Data collection and analysis. Z-QY:Project administration, Supervision, Writing-review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians. 2021, 71:209\u0026ndash;249.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaters JK, Reznik SI. 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Oncol Lett. 2022, 24:257.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\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":"Circulating blood cell traits, Esophageal cancer, Mendelian randomization, genome-wide association study","lastPublishedDoi":"10.21203/rs.3.rs-4250357/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4250357/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Epidemiologic evidence indicates that circulating blood cell traits may be linked to both the incidence and outcome of Esophageal Cancer. Nevertheless, these studies are at risk of being influenced by confounding factors. In our research, we conducted Mendelian randomization to explore the potential causal association between circulating blood cell traits and EC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This study utilized genome-wide association studies (GWAS) datasets to analyze genetic variation using a two-sample MR design. The EC data was obtained from a GWAS study involving 740 cases and 372,016 controls (identifier: ieu-b-4960), while data for 15 circulating blood cell traits were sourced from a GWAS with 562,132 participants. Various statistical methods including Inverse variance weighted (IVW), Weighted median, MR Egger regression, Weighted mode, and Simple mode were employed to assess the causal connection between the circulating blood cell traits and EC. Additionally, a series of sensitivity analyses were conducted to ensure the robustness of the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The results found significant association between elevated circulating BAS counts (odds ratio, OR: 1.0012, 95 % confidence interval, CI: 1.0004-1.0020, p =0.0037), and decreased circulating levels of HBG (OR: 0.9994, 95% CI: 0.9989-1.0000, p =0.0403) with the risk of EC in the IVW approach. In addition,circulating blood cell traits including MPV (OR: 0.0506, 95% CI:0.0034 -0.7435, p =0.0295 ) and LYM (OR: 0.1356, 95% CI:0.0209-0.8816, p =0.0364) are suggested to be the consequences of EC\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: In this research, we systematically examined the association between the 15 circulating blood cell traits and the occurrence of EC. We identified upstream regulators (BAS counts) and downstream effectors (HBG concentration) associated with EC. In addition, EC affects circulating levels of LYM counts and MPV. Our results provide valuable insights into the role of circulating blood cell traits in the development of EC, offering new avenues for further research and potential interventions in the prevention and management of EC.\u003c/p\u003e","manuscriptTitle":"Genetically predicted 15 circulating blood cell traits and Esophageal Cancer：a comprehensive Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-22 02:21:40","doi":"10.21203/rs.3.rs-4250357/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":"a4bdac4e-8eb5-401c-9dbe-be1224799d77","owner":[],"postedDate":"April 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-09T04:07:54+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-22 02:21:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4250357","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4250357","identity":"rs-4250357","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}