Causal association between oral disease and chronic obstructive pulmonary disease: A Mendelian Randomization study

Causal association between oral disease and chronic obstructive pulmonary disease: A 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 Causal association between oral disease and chronic obstructive pulmonary disease: A Mendelian Randomization study Fanye Wu, Mingzhe Cao, Minghui Zeng, Liqing Wang, Zejun Chen, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3179826/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 The association between oral diseases and chronic obstructive pulmonary disease (COPD) has been revealed by many epidemiological studies in clinical aspects. Therefore, we elucidate genetic relationships using Mendelian randomization (MR) in this study. Method We utilized MR analysis with summary datasets from a genome-wide association study (GWAS) to investigate the causal relationship between COPD and 12 oral traits such as periodontitis and denture and ensured that there were no confounders like smoking, and every F-value was greater than 10. Inverse variance weighting (IVW) was applied with MR analysis as the primary outcome. Additionally, the horizontal pleiotropy was assessed by MR-PRESSO methods, and the heterogeneity was detected using Cochran's Q statistics. Result This study found a significant causal effect of implant dentures on COPD by univariate and multivariate MR (OR = 1.077, 95%CI = 1.044 ~ 1.111, p_adjust = 6.58E-05). Although univariate MR showed that excessive attrition of teeth had a significant causal effect on later COPD (OR = 1.061, 95%CI = 1.020 ~ 1.104, p_adjust = 0.037), this causal relationship was not found in multivariate MR. This study found no significant effect of periodontitis on COPD (p > 0.05), either acute or chronic. Conclusion Our MR Analysis findings suggested that implant dentures and excessive attrition of teeth significantly promotes the risk of COPD and elder COPD, respectively. However, the evidence for a causal relationship between periodontitis and COPD is still insufficient and previous studies may have been affected by confounding factors. mendelian randomization CODP periodontitis denture tooth attrition Figures Figure 1 Figure 2 Figure 3 Figure 4 Background COPD is a progressive respiratory illness that obstructs airflow in the lungs leading to breathing difficulty ( 1 ). COPD is a significant cause of morbidity and mortality worldwide ( 2 ), which causes more than 3 million deaths yearly ( 3 ). COPD is primarily caused by long-term exposure to noxious particles such as tobacco smoke, cooking smoke, and industrial pollutants. Although COPD is characterized primarily by chronic bronchitis and emphysema, it is also often associated with a significant systemic inflammatory response ( 4 ), osteoporosis ( 5 ), diabetes ( 6 ) and cardiovascular disease ( 7 ), leading to chronic cough with sputum production, shortness of breath, and reduced exercise capacity. In previous studies, COPD has been reported to be associated with oral disease, especially periodontitis ( 8 – 10 ). Some studies have suggested that these associations may be established through systemic immunity and inflammation ( 11 , 12 ). However, some studies have not found a relationship between typical periodontitis and COPD( 13 – 15 ). Furthermore, even if a correlation were established, it would disappear after adjusting for factors such as smoking( 13 ). Therefore, more studies are needed to clarify the interaction between oral problems and COPD. Mendelian randomization (MR) investigates postulated causality between exposure and outcome using genetic variation as an instrumental variable (IV) in genetic epidemiological studies ( 16 ). Previous MR studies have demonstrated the causal relationship between oral disease and asthma risk ( 17 ) and causal relationship between oral disease and lung function impairment ( 18 ). However, few MR analyses have been reported to investigate the oral disease contributing to respiratory disease and function, and the causal relationship between oral disease and COPD risk remains unclear, particularly after excluding the confound factors such as smoking. In this study, we used MR to systematically assess genetic causality between 12 oral health conditions and COPD-related outcomes using the latest GWAS data. IVW is the most recognized univariate MR Method and was mainly used in this study( 19 , 20 ). To exclude the interference between these oral health conditions, multivariable MR was used to investigate the independent role of oral health conditions on COPD. In addition, all IVs associated with confounders were excluded. This study has the potential to provides a new starting point for research on the underlying pathological mechanisms of COPD and inform prevention strategies for COPD at different stages of development. Materials and Methods Study design In this study, the causal associations between 12 oral health conditions traits and three COPD-related outcomes were assessed. The 12 oral traits included: Painful gums, Loose teeth, Dentures, Mouth ulcers, Dental caries, Chronic periodontitis, Excessive attrition of teeth, Acute periodontitis, Impacted teeth, Deposits (accretions) on teeth, Bleeding gums, wisdom teeth surgery. First, the effects of 12 oral traits and COPD risk were evaluated, and then further investigated other COPD-related outcomes, including COPD in elder. To conduct an MR study, the instrumental SNPs used must meet three criteria to ensure their validity: ( 1 ) the genetic variants are associated with the exposure of interest; ( 2 ) there are no unmeasured confounders of the associations between genetic variants and outcome; and ( 3 ) the genetic variants affect the outcome only via the exposure of interest (Fig. 1). Figure 1. Study design. The effects of twelve oral traits on three COPD-related outcomes were investigated. IVs of oral traits that have been reported as associated with any confounders were removed. The list on the confounders box indicates risk factors specific to acute COPD exacerbations. Outcome terms listed in black in the outcome box represented the primary outcomes in the forward MR and were used as exposure in reverse MR. COPD: chronic obstructive pulmonary disease. GWAS data on oral traits The GWAS data of some of the oral traits such as “Chronic periodontitis”,“Acute periodontitis ”,“Dental caries”,“Impacted teeth”,“Deposits [accretions] on teeth” and “Excessive attrition of teeth” were obtained from FinnGen ( https://www.finngen.fi/en ), a large-scale genomic research project developed in Finland, which was identified as “finn-b-K11_PERIODON_CHRON”, “finn-b-K11_PERIODON_ACUTE”, “finn-b-K11_CARIES”, “finn-b-K11_IMPACTED_TEETH”, “finn-b-K11_DEPOSITS” and “finn-b-K11_ATTRITION”, respectively. The GWAS data of the others oral traits “Bleeding gums”, “Painful gums”, “Dentures”, “Loose teeth”, “Mouth ulcers”, “wisdom teeth surgery” from a dataset published by the UK Biobank on the IEU OpenGWAS project website ( https://gwas.mrcieu.ac.uk ), which were identified as “ukb-b-7872”, “ukb-b-11161”, “ukb-b-12930”, “ukb-b-12849”, “ukb-a-427”, “ukb-b-14782”, respectively. Detailed information regarding oral traits is provided in Table 1 . Table 1 The characteristics of each exposure and genetic IVs in univariable Mendelian Randomization. Trait name Associated SNPs Filtered IVs Sample size range Painful gums 98 9 461113 Dentures 6115 121 461113 Excessive attrition of teeth 64 9 195687 Loose teeth 920 16 461113 wisdom teeth surgery 480 26 462933 Chronic periodontitis 133 12 198441 Acute periodontitis 56 6 195762 Dental caries 67 8 199565 Bleeding gums 613 38 461113 Deposits [accretions] on teeth 62 11 196169 Mouth ulcers 11310 65 336138 Impacted teeth 136 5 218792 GWAS data on COPD To avoid population stratification, our request for COPD data sources was also specific to the European population. The COPD data were extracted for the UK Biobank on the IEU OpenGWAS project website, which was named: “COPD differential diagnosis”, which was identified as “ukb-d-COPD_EXCL” with a total sample size of 361,194 (26,710 cases and 334,484 controls). Older COPD data with a total sample size of 215,284(> 65; 3,087 cases and 212,197 controls) were obtained from FinnGen. Detailed information of all exposures and outcomes are provided in Additional file 1: Table S1 . Selection of instrumental variables The MR Analysis follows three main assumptions (Fig. 1). Because IVs need to be closely related to exposure, there were only significant SNPS (P values < 5×10 − 6), including the largest exposure GWAS (hypothesis 1). The MR Design also requires that IVs influence outcomes only through exposure (hypothesis 3) and not due to other confounding factors (hypothesis 2). Therefore, a three-step filtering process is used to eliminate suspect IVs. To meet this criterion, suspicious IVs were identified and excluded through a 3-step filtering process. First, all relevant SNPs selected as genetic instruments satisfied a relatively relaxed threshold of P < 1 × 10–5. IVs associated with confounders were excluded, and the confounders were primarily selected from outcome risk factors and listed in Table 1 . The summary statistics of the associations between IVs and confounders were searched for in the NHGRI-EBI GWAS Catalog with the corresponding terms. Second, the IVs were clumped to ensure independence between SNP markers (linkage disequilibrium - LD - r2 value 10 MB). Lastly, remove the IVs that were not included in the outcome GWAS and the IVs that were palindromic. To confirm that the retained IVs do not have any impact on unknown confounders, pleiotropy test was conducted. Additionally, F-statistics were computed to test the strength of the retained IVs .F statistics larger than 10 are regarded as no evidence of weak instrument bias ( 19 ). Mendelian Randomization Two analytical approaches were employed to analyze the data with retained IVs: univariable and multivariable MR. For univariable MR, the causal relationship of each variable was evaluated independently using an IVW. The odds ratio (OR) value (exp(β2)) for disease risk was calculated using the Wald-type estimator and with β1 and β3 representing the effect of each variable on exposure and outcome, respectively. These estimates were combined using IVW to produce an overall β2, while Cochran’s Q was used to test for heterogeneity among each β2. The random-effects model was used to combine β2 values when there was heterogeneity. Several additional univariable MR methods, including: MR-Egger, weighted median, MR-PRESSO, and PARS, were also used to confirm the robustness of the results ( 21 ). In the multivariable MR analysis, the interdependent relationship between various oral traits was assessed ( 22 ). The R package TwoSampleMR (version = 0.5.5) ( 21 , 23 ) was used to conduct univariable and multivariable MR analyses ( 21 ). The mRnd tool and the R package MVMR (version = 0.3) were used for power analysis in univariable and multivariable MR, respectively ( 24 ). We used false discovery rate (FDR) to adjust for multiple testing, and an FDR < 0.05 was deemed statistically significant. Result Instrumental Variables Oral -problem-associated SNPs were selected as IVs of the 12 oral problem traits. The other SNPs were excluded from further analysis, mainly due to LD-pruning. The filtered IVs did not show any directional pleiotropy (all P-values > 0.050) (Additional file 1: Table S4). Dentures increase the risk of COPD Regarding the causal relationship between Oral problems and COPD, the IVW showed that the causal relationship between implant dentures and COPD was significant (OR = 1.077, 95% CI = 1.044 ~ 1.111, p_adjust = 6.58E-05) (Fig. A), which was found out 121 IVs (Additional file 1: Table S2). However, IVs were identified as heterogeneous by Cochran's Q (p = 6.408E-04) (Additional file 1: Table S4). We used multiplicative random effects IVWs to calculate the OR (OR = 1.077, 95% CI = 1.044 ~ 1.111, p_adjust = 2.96E-06), which proved the reliability of the selected IVs. The pleiotropy test did not identify directional pleiotropy of the IVs ( P-value ≥ 0.080). As shown in the scatter plot, the risk of COPD increases with implant denture (Fig. 2B). The leave-one-out sensitivity analysis with one SNP removed at a time showed stable results (Fig. 2C). The causal effect of each SNP on IPF is shown in the forest plot (Additional file 1: Figure S1 ). In the multivariable MR, in which we screened 72 nSNPs as IVs, we also identified the causality of implant dentures (OR = 1.062, 95% CI = 1.035 ~ 1.090, p = 5.428E-06) with COPD (Fig. 2D). Figure 2. Effect of each oral trait on COPD risk (A) Calculation of the effect of each oral trait on COPD by IVW, which is the most commonly used univariate MR method. (B) Four other univariate MR methods. (C) Leave-one-out plots for the MR analyses of the denture on COPD. (D) Correction of the interaction between different oral traits by multivariate MR. Excessive attrition of teeth increased the risk of older COPD Regarding COPD risk in older adults, IVW of univariate MR showed that excessive attrition of teeth had a significant effect on COPD in older (OR = 1.061, 95% CI = 1.020 ~ 1.104, p = 0.003) (Fig. 3A), which was found out 9 IVs (Additional file 1: Table S3). There was no heterogeneity or pleiotropy (P-value > 0.05) in the analysis. As shown in the scatter plot, excessive attrition of teeth increases with the increasing the risk of elder COPD (Fig. 3B). The leave-one-out sensitivity analysis with one SNP removed at a time showed stable results (Fig. 3C). However, This significant causal relationship was not found in the multivariate MR (OR = 1.006, 95% CI = 0.965 ~ 1.050,p = 0.753). Figure 3. Effect of each oral trait on elder COPD risk (A) Calculation of the effect of each oral trait on elder COPD by IVW, which is the most commonly used univariate MR method. (B) Four other univariate MR methods. (C) Leave-one-out plots for the MR analyses of excessive attrition of teeth on elder COPD. Periodontitis did not increase the risk of COPD, either acute or chronic Regarding the causal relationship between periodontitis and COPD, the IVW in this study showed that periodontitis had no significant effect on COPD risk, either acute(p = 0.936, CI = 1.000 (0.999–1.001) ) or chronic(p = 0.987, CI = 1.000(0.997–1.003)) (Fig. 4). This causal relationship is also not detected in MR Egger, simple median or weighted median. Figure 4. Effect of acute and chronic periodontitis on elder COPD risk Discussion In conclusion, in this study by univariate as well as multivariate MR it was found that 1) implant dentures had a significant causal effect on COPD (OR = 1.077, 95% CI = 1.044 ~ 1.111, p_adjust = 6.58E-05), although there was heterogeneity (p = 6.408E-04). We eliminated the effect by random effects model; 2) Excessive attrition of teeth significantly increase the risk of COPD (OR = 1.061, 95% CI = 1.020 to 1.104, p_adjust = 0.037). However, this causal relationship was not found in multivariate MR; 3) Unlike previous epidemiological studies, the present study did not find any significant effect of periodontitis (either acute or chronic) on COPD. To our knowledge, this is the first MR framework of investigation oral traits and COPD. The association of oral problems with pulmonary diseases, especially COPD, has been a popular topic in epidemiology. Studies have shown that, unlike dental biofilms, biofilms formed on denture materials contain more yeasts and that Candida yeasts, particularly Candida albicans, have been shown to have a solid pathogenic correlation with the presence of denture stomatitis ( 25 , 26 ). Poor denture hygiene promotes the accumulation of bacterial and fungal plaque and results in direct interaction with the prosthetic area mucosa ( 27 ). Essentially, dentures encourage the growth of flora, and infections caused by bacteria and viruses in lower airways, such as pneumonia and bronchitis, exacerbate COPD. These findings align with our study’s results. Additionally, prolonged Excessive attrition of teeth may exacerbate the systemic inflammatory burden, which leads to slight bronchial inflammation that can cause COPD. Nevertheless, other potential oral factors should be taken into account when drawing this conclusion. The association between periodontitis and COPD is widely studied as a link between oral and respiratory disease. According to an epidemiological survey from Korea, patients with COPD had a higher prevalence of periodontitis (58.1%) than those without COPD (34.0%, P < 0.001) ( 28 ). This finding is supported by a population-based study from Spain as well (P < 0.001), with rates of 26.5% and 22.2%, respectively ( 29 ). The latest study suggests that this may be attributed to periodontitis affecting Th1 profile cell processes, cytokines, and pulmonary alterations ( 11 ), which is further corroborated by transcriptomic analysis ( 12 ). However, the current evidence is, at best, indirectly supportive of the link between COPD and periodontitis. Other studies have failed to find these associations, which showing no significant relationship between periodontitis and COPD. Bergstrom et al. found that smoking, rather than COPD, was the primary risk factor for periodontal pocket depth (OR 24.2; 95% CI 2.0-286.8) ( 30 ). Another analysis of the NHANES survey found no association between the two diseases in those who had never smoked, although subgroup analyses found such an association in those who were smoking or former smokers ( 13 , 31 ). An analysis of kNHANES from Korea also showed that the prevalence of periodontitis was not significantly associated with reduced lung function ( 14 , 15 ). In this study, the findings align with these epidemiological studies, founding no significant causal relationship between periodontitis and COPD by MR, implying that the reported epidemiological associations could result from unmeasured confounding. We adjusted for various confounders, including smoking, BMI, education and economic status, when conducting the analysis, while many earlier epidemiological studies did not consider these factors. For example, Shen et al. failed to correct for smoking status ( 32 ), while the study by Leuckfeld et al. did not adjust for socioeconomic factors ( 30 ). After adjusting for these effects, numerous studies have shown that periodontitis and COPD are no longer correlated ( 13 , 31 , 33 , 34 ). In the hypothesis of a causal relationship between periodontitis and COPD, the oral cavity is an essential reservoir of pulmonary pathogens, then pathogens in dental plaque can be inhaled into the respiratory system through the oral cavity, causing aspiration pneumonia and thus exacerbating COPD ( 35 , 36 ). A meta-analysis has reported that oral hygiene and antibiotic intervention significantly reduced the risk of pneumonia in these populations, supporting a causal relationship between oral pathogens and lower respiratory tract infections ( 37 ). However, most relevant studies have been conducted in intensive care settings, and it is unclear whether the findings can be generalized to a broader population. This study has the following strengths: First, it is the first attempt to explore the effects of different oral traits on COPD through a two-sample MR analysis using GWAS summary-level statistics and minimizes the effects of confounding factors. Secondly, the findings were validated by applying multiple MR methods and sensitivity analyses with different model assumptions, and the effects of outliers and pleiotropy were evaluated comprehensively. Finally, this study provides a new starting point for research on the pathogenesis of COPD and can provide new diagnostic strategy treatment strategies for COPD patients, especially those with oral disease However, this study also has some limitations. First, although the GWAS dataset of this study all from European populations, the data was not from a single genomics research project and included data from the UK Biobank and FinnGen, which may influence the results. Secondly, caution should be observed in generalizing the findings to other populations due to the limited representation of European population data and the lack of ethnic diversity. Lastly, the analysis could not be stratified by different levels of periodontitis severity because no existing GWAS had identified IVs associated with such classifications, necessitating further investigation of the effect of different levels of periodontitis on COPD. Conclusion This study provides genetic evidence supporting the causal role of implant dentures on COPD and high levels of tooth wear in older individuals with COPD. Our results suggest that the evidence for a causal relationship between periodontitis and COPD is still insufficient and previous studies may have been affected by confounding factors. More experimental studies are needed to confirm our findings. Abbreviations GWAS Genome-wide association studyIV:Instrumental variable COPD Chronic obstructive pulmonary diseaseMR:Mendelian randomizationIVW:Inverse variance weighting OR odds ratio LD linkage disequilibrium Declarations Availability of data and materials All data generated or analysed during this study are included in this published article. Acknowledgements The authors thank to the Internet for providing the main data (https://gwas.mrcieu.ac.uk/) (https://www.finngen.fi/en). Funding The design and performance of this study were funded by the National Natural Science Foundation of China (82170044). Author information Authors and Affiliations The Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China Fanye Wu, Zejun Chen, Zhengran Li, Yuxin Sun and Zijin Wang; Department of Ophthalmology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China Mingzhe Cao Institute of Scientific Research, Southern Medical University, Guangzhou, 510515, China Minghui Zeng Department of Pharmacy, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China Liqing Wang The First Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China Tong Wu Emergency Department, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, China Fanke Meng Contributions FW, MC and FM designed the study and drafted the manuscript. LW, ZL, YS, ZW and TW performed the data collection and analysis. MZ, ZZ and ZC performed validation and analysis. All authors read and approved the final manuscript. Corresponding author Correspondence to Fanke Meng. Ethics declarations 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 Watz H, Waschki B, Kirsten A, Müller KC, Kretschmar G, Meyer T, et al. The Metabolic Syndrome in Patients With Chronic Bronchitis and COPD: Frequency and Associated Consequences for Systemic Inflammation and Physical Inactivity. Chest. 2009 Oct 1;136(4):1039–46. GBD 2013 Mortality and Causes of Death Collaborators. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015 Jan 10;385(9963):117–71. Rabe KF, Watz H. Chronic obstructive pulmonary disease. Lancet. 2017 May 13;389(10082):1931–40. Nussbaumer-Ochsner Y, Rabe KF. Systemic manifestations of COPD. Chest. 2011 Jan;139(1):165–73. Johnston AK, Mannino DM, Hagan GW, Davis KJ, Kiri VA. Relationship between lung function impairment and incidence or recurrence of cardiovascular events in a middle-aged cohort. Thorax. 2008 Jul;63(7):599–605. Mannino DM, Thorn D, Swensen A, Holguin F. Prevalence and outcomes of diabetes, hypertension and cardiovascular disease in COPD. Eur Respir J. 2008 Oct;32(4):962–9. Watanabe R, Tanaka T, Aita K, Hagiya M, Homma T, Yokosuka K, et al. Osteoporosis is highly prevalent in Japanese males with chronic obstructive pulmonary disease and is associated with deteriorated pulmonary function. J Bone Miner Metab. 2015 Jul;33(4):392–400. Qian Y, Yuan W, Mei N, Wu J, Xu Q, Lu H, et al. Periodontitis increases the risk of respiratory disease mortality in older patients. Exp Gerontol. 2020 May;133:110878. Saito M, Shimazaki Y, Yoshii S, Takeyama H. Periodontitis and the incidence of chronic obstructive pulmonary disease: A longitudinal study of an adult Japanese cohort. Journal of Clinical Periodontology. 2023;50(6):717–26. Sapey E, Yonel Z, Edgar R, Parmar S, Hobbins S, Newby P, et al. The clinical and inflammatory relationships between periodontitis and chronic obstructive pulmonary disease. J Clin Periodontol. 2020 Sep;47(9):1040–52. Rosa EP, Murakami-Malaquias-da-Silva F, Palma-Cruz M, de Carvalho Garcia G, Brito AA, Andreo L, et al. The impact of periodontitis in the course of chronic obstructive pulmonary disease: Pulmonary and systemic effects. Life Sci. 2020 Nov 15;261:118257. Liu S, Fu Y, Ziebolz D, Li S, Schmalz G, Li F. Transcriptomic analysis reveals pathophysiological relationship between chronic obstructive pulmonary disease (COPD) and periodontitis. BMC Med Genomics. 2022 Jun 8;15(1):130. Chen H, Zhang X, Luo J, Dong X, Jiang X. The association between periodontitis and lung function: Results from the National Health and Nutrition Examination Survey 2009 to 2012. Journal of Periodontology. 2022;93(6):901–10. Jung ES, Lee KH, Choi YY. Association between oral health status and chronic obstructive pulmonary disease in Korean adults. Int Dent J. 2020 Jun;70(3):208–13. Lee E, Lee SW. Prevalence of Periodontitis and Its Association with Reduced Pulmonary Function: Results from the Korean National Health and Nutrition Examination Survey. Medicina. 2019 Sep;55(9):581. Burgess S, Timpson NJ, Ebrahim S, Davey Smith G. Mendelian randomization: where are we now and where are we going? Int J Epidemiol. 2015 Apr;44(2):379–88. Jiao R, Li W, Song J, Chen Z. Causal Association Between Asthma and Periodontitis: A Two-Sample Mendelian Randomization Analysis. Oral Dis. 2023 Mar 23; Baumeister SE, Nolde M, Holtfreter B, Baurecht H, Gläser S, Kocher T, et al. Periodontitis and pulmonary function: a Mendelian randomization study. Clin Oral Investig. 2021 Aug;25(8):5109–12. Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013 Nov;37(7):658–65. Bowden J, Del Greco M F, Minelli C, Davey Smith G, Sheehan N, Thompson J. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Statistics in Medicine. 2017;36(11):1783–802. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018 May 30;7:e34408. Burgess S, Thompson SG. Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. Am J Epidemiol. 2015 Feb 15;181(4):251–60. Hemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017 Nov;13(11):e1007081. Sanderson E, Spiller W, Bowden J. Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization. Stat Med. 2021 Nov 10;40(25):5434–52. Figueiral MH, Azul A, Pinto E, Fonseca PA, Branco FM, Scully C. Denture-related stomatitis: identification of aetiological and predisposing factors - a large cohort. J Oral Rehabil. 2007 Jun;34(6):448–55. Campos MS, Marchini L, Bernardes L a. S, Paulino LC, Nobrega FG. Biofilm microbial communities of denture stomatitis. Oral Microbiol Immunol. 2008 Oct;23(5):419–24. Sumi Y, Miura H, Sunakawa M, Michiwaki Y, Sakagami N. Colonization of denture plaque by respiratory pathogens in dependent elderly. Gerodontology. 2002 Jul;19(1):25–9. Chung JH, Hwang HJ, Kim SH, Kim TH. Associations Between Periodontitis and Chronic Obstructive Pulmonary Disease: The 2010 to 2012 Korean National Health and Nutrition Examination Survey. J Periodontol. 2016 Aug;87(8):864–71. Lopez-de-Andrés A, Vazquez-Vazquez L, Martinez-Huedo MA, Hernández-Barrera V, Jimenez-Trujillo I, Tapias-Ledesma MA, et al. Is COPD associated with periodontal disease? A population-based study in Spain. Int J Chron Obstruct Pulmon Dis. 2018;13:3435–45. Leuckfeld I, Obregon-Whittle MV, Lund MB, Geiran O, Bjørtuft Ø, Olsen I. Severe chronic obstructive pulmonary disease: association with marginal bone loss in periodontitis. Respir Med. 2008 Apr;102(4):488–94. Hyman JJ, Reid BC. Cigarette smoking, periodontal disease: and chronic obstructive pulmonary disease. J Periodontol. 2004 Jan;75(1):9–15. Shen TC, Chang PY, Lin CL, Chen CH, Tu CY, Hsia TC, et al. Risk of Periodontal Diseases in Patients With Chronic Obstructive Pulmonary Disease: A Nationwide Population-based Cohort Study. Medicine (Baltimore). 2015 Nov;94(46):e2047. Liu Z, Zhang W, Zhang J, Zhou X, Zhang L, Song Y, et al. Oral hygiene, periodontal health and chronic obstructive pulmonary disease exacerbations. Journal of Clinical Periodontology. 2012;39(1):45–52. Bergström J, Cederlund K, Dahlén B, Lantz AS, Skedinger M, Palmberg L, et al. Dental health in smokers with and without COPD. PLoS One. 2013;8(3):e59492. Scannapieco FA, Wang B, Shiau HJ. Oral bacteria and respiratory infection: effects on respiratory pathogen adhesion and epithelial cell proinflammatory cytokine production. Ann Periodontol. 2001 Dec;6(1):78–86. Bansal M, Khatri M, Taneja V. Potential role of periodontal infection in respiratory diseases - a review. J Med Life. 2013 Sep 15;6(3):244–8. Scannapieco FA, Bush RB, Paju S. Associations between periodontal disease and risk for nosocomial bacterial pneumonia and chronic obstructive pulmonary disease. A systematic review. Ann Periodontol. 2003 Dec;8(1):54–69. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.pdf File name: Additional file 1 File format: pdf Title of data: Table S1. Data source of genome-wide association studies included in the Mendelian randomization analysis. Table S2. Characteristics of the genetic variants used for Mendelian randomization analysis of implant denture on COPD risk. Table S3.Characteristics of the genetic variants used for Mendelian randomization analysis of excessive attrition of teeth on elder COPD. Table S4. Heterogeneity and pleiotropy, investigating MR assumption violation. Figure S1. Forest plot for the causal effect of each SNP on COPD risk. Figure S2. Funnel plot for the overall heterogeneity in the effect of denture on COPD risk. Figure S3. Forest plot for the causal effect of each SNP on elder COPD risk. Figure S4. Funnel plot for the overall heterogeneity in the effect of excessive attrition of teeth on elder COPD Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3179826","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":220021476,"identity":"492aba00-2a32-4c04-9869-2e74f3cb5112","order_by":0,"name":"Fanye Wu","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fanye","middleName":"","lastName":"Wu","suffix":""},{"id":220021477,"identity":"7d69e0ea-6575-4b79-8773-5d1fbc865d08","order_by":1,"name":"Mingzhe Cao","email":"","orcid":"","institution":"The Seventh Affiliated Hospital of Sun Yat-Sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mingzhe","middleName":"","lastName":"Cao","suffix":""},{"id":220021478,"identity":"76682eeb-9c1b-4064-865f-805528d1eeab","order_by":2,"name":"Minghui Zeng","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minghui","middleName":"","lastName":"Zeng","suffix":""},{"id":220021479,"identity":"cd503969-7380-4b60-85ae-9ff98c1ae664","order_by":3,"name":"Liqing Wang","email":"","orcid":"","institution":"The Seventh Affiliated Hospital of Sun Yat-Sen University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Liqing","middleName":"","lastName":"Wang","suffix":""},{"id":220021480,"identity":"1ef4b4f3-b703-4586-8499-9e9dc83de41c","order_by":4,"name":"Zejun Chen","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zejun","middleName":"","lastName":"Chen","suffix":""},{"id":220021481,"identity":"9dcdc669-f5e9-40a7-8c8a-16d8f6aa1a20","order_by":5,"name":"Zhengran Li","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhengran","middleName":"","lastName":"Li","suffix":""},{"id":220021482,"identity":"67d559b2-3dae-4a69-9bdf-ced2a1ceacee","order_by":6,"name":"Yuxin Sun","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuxin","middleName":"","lastName":"Sun","suffix":""},{"id":220021483,"identity":"44df8f8d-d7e9-487b-8974-aeb75c9b7d6e","order_by":7,"name":"Ziran Zhang","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ziran","middleName":"","lastName":"Zhang","suffix":""},{"id":220021484,"identity":"b98bf8b5-dbdb-42f2-b046-fa8a424fa684","order_by":8,"name":"Zijin Wang","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zijin","middleName":"","lastName":"Wang","suffix":""},{"id":220021485,"identity":"9d98cc43-e7d2-4cbb-9cbe-0a5f2965fd04","order_by":9,"name":"Tong Wu","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tong","middleName":"","lastName":"Wu","suffix":""},{"id":220021486,"identity":"ef9291b0-3bd2-42d5-823b-1ba27c77da3f","order_by":10,"name":"Fanke Meng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIie3RMUsDMRTA8XcE3i2hrjmueH6EVw5aHUQ/Sopgp4LjDQ4VIbfcB3AQP8NNglvKg3Yp3CroUBFucnO5oYN3g1ubc3TIfwpJfoQkAD7ff0wAApBtB4K3qrk9xjC3fyQhXtNZsUoHcqP7zmkJtORIkspQTJ/UJTn30zqsP+XNezIRQPQqcWYUaGiy58OE5SSVVI9e7kF/PJwO5ya+s0GxeXMRjCVxUDLYVEmcm6HVIjAuEtYduSg5WMQ7FDNUmnoIjDsyLVmAUih0L4lYjqNH4quSESkqViPTPvLSdZdBta7V147Py6r67r4ySfJ8uW2yw+TE7pvdO/lbsnCt+nw+n6/rB2OtVwxr8gk0AAAAAElFTkSuQmCC","orcid":"","institution":"Zhujiang Hospital of Southern Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Fanke","middleName":"","lastName":"Meng","suffix":""}],"badges":[],"createdAt":"2023-07-18 03:29:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3179826/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3179826/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":40473054,"identity":"c20a2259-341c-4fdb-ad99-a04f6e8c4460","added_by":"auto","created_at":"2023-07-24 13:49:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1802830,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy design.\u003c/strong\u003e The effects of twelve oral traits on three COPD-related outcomes were investigated. IVs of oral traits that have been reported as associated with any confounders were removed. The list on the confounders box indicates risk factors specific to acute COPD exacerbations. Outcome terms listed in black in the outcome box represented the primary outcomes in the forward MR and were used as exposure in reverse MR. COPD: chronic obstructive pulmonary disease.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3179826/v1/0eea7425d75fec569576f8e3.png"},{"id":40473055,"identity":"c9821e6c-b866-434f-a35f-45db1dfb51d9","added_by":"auto","created_at":"2023-07-24 13:49:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":893094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of each oral trait on COPD risk: \u003c/strong\u003e(A) Calculation of the effect of each oral trait on COPD by IVW, which is the most commonly used univariate MR method. (B) Four other univariate MR methods. (C) Leave-one-out plots for the MR analyses of the denture on COPD. (D) Correction of the interaction between different oral traits by multivariate MR.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3179826/v1/b367ea7a8bc212a095b5733d.png"},{"id":40473052,"identity":"3b2bfe4b-8d5a-4a6e-818c-542210f20769","added_by":"auto","created_at":"2023-07-24 13:49:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":637979,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of each oral trait on elder COPD risk \u003c/strong\u003e(A) Calculation of the effect of each oral trait on elder COPD by IVW, which is the most commonly used univariate MR method. (B) Four other univariate MR methods. (C) Leave-one-out plots for the MR analyses of excessive attrition of teeth on elder COPD.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-3179826/v1/179a59a88df8e58b334389e3.png"},{"id":40474301,"identity":"5f6947d3-0400-4d1d-b346-6b90cc340871","added_by":"auto","created_at":"2023-07-24 13:57:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":53932,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of acute and chronic periodontitis on elder COPD risk\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-3179826/v1/c847b5e4c2eaf6334b52b57e.png"},{"id":40601882,"identity":"c798b192-88d1-458d-9dd9-68cc09e8b568","added_by":"auto","created_at":"2023-07-26 13:37:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1386585,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3179826/v1/c5418f9f-f98e-4a5d-b409-2e8893afe06c.pdf"},{"id":40473056,"identity":"4918efde-192d-4b61-92bf-727ebaeceb17","added_by":"auto","created_at":"2023-07-24 13:49:52","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":714949,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFile name: \u003c/strong\u003eAdditional file 1\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFile format: \u003c/strong\u003epdf\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTitle of data: Table S1.\u003c/strong\u003e Data source of genome-wide association studies included in the Mendelian randomization analysis. \u003cstrong\u003eTable S2.\u003c/strong\u003e Characteristics of the genetic variants used for Mendelian randomization analysis of implant denture on COPD risk. \u003cstrong\u003eTable S3.\u003c/strong\u003eCharacteristics of the genetic variants used for Mendelian randomization analysis of excessive attrition of teeth on elder COPD. \u003cstrong\u003eTable S4. \u003c/strong\u003eHeterogeneity and pleiotropy, investigating MR assumption violation. \u003cstrong\u003eFigure S1.\u003c/strong\u003e Forest plot for the causal effect of each SNP on COPD risk. \u003cstrong\u003eFigure S2. \u003c/strong\u003eFunnel plot for the overall heterogeneity in the effect of denture on COPD risk. \u003cstrong\u003eFigure S3.\u003c/strong\u003e Forest plot for the causal effect of each SNP on elder COPD risk. \u003cstrong\u003eFigure S4. \u003c/strong\u003eFunnel plot for the overall heterogeneity in the effect of excessive attrition of teeth on elder COPD\u003c/p\u003e","description":"","filename":"Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3179826/v1/6a1829fd6a74548236609cce.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal association between oral disease and chronic obstructive pulmonary disease: A Mendelian Randomization study","fulltext":[{"header":"Background","content":"\u003cp\u003eCOPD is a progressive respiratory illness that obstructs airflow in the lungs leading to breathing difficulty (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). COPD is a significant cause of morbidity and mortality worldwide (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), which causes more than 3\u0026nbsp;million deaths yearly (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). COPD is primarily caused by long-term exposure to noxious particles such as tobacco smoke, cooking smoke, and industrial pollutants. Although COPD is characterized primarily by chronic bronchitis and emphysema, it is also often associated with a significant systemic inflammatory response (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), osteoporosis (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), diabetes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and cardiovascular disease (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), leading to chronic cough with sputum production, shortness of breath, and reduced exercise capacity.\u003c/p\u003e \u003cp\u003eIn previous studies, COPD has been reported to be associated with oral disease, especially periodontitis (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Some studies have suggested that these associations may be established through systemic immunity and inflammation (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, some studies have not found a relationship between typical periodontitis and COPD(\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Furthermore, even if a correlation were established, it would disappear after adjusting for factors such as smoking(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Therefore, more studies are needed to clarify the interaction between oral problems and COPD.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) investigates postulated causality between exposure and outcome using genetic variation as an instrumental variable (IV) in genetic epidemiological studies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Previous MR studies have demonstrated the causal relationship between oral disease and asthma risk (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and causal relationship between oral disease and lung function impairment (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, few MR analyses have been reported to investigate the oral disease contributing to respiratory disease and function, and the causal relationship between oral disease and COPD risk remains unclear, particularly after excluding the confound factors such as smoking.\u003c/p\u003e \u003cp\u003eIn this study, we used MR to systematically assess genetic causality between 12 oral health conditions and COPD-related outcomes using the latest GWAS data. IVW is the most recognized univariate MR Method and was mainly used in this study(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). To exclude the interference between these oral health conditions, multivariable MR was used to investigate the independent role of oral health conditions on COPD. In addition, all IVs associated with confounders were excluded. This study has the potential to provides a new starting point for research on the underlying pathological mechanisms of COPD and inform prevention strategies for COPD at different stages of development.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eIn this study, the causal associations between 12 oral health conditions traits and three COPD-related outcomes were assessed. The 12 oral traits included: Painful gums, Loose teeth, Dentures, Mouth ulcers, Dental caries, Chronic periodontitis, Excessive attrition of teeth, Acute periodontitis, Impacted teeth, Deposits (accretions) on teeth, Bleeding gums, wisdom teeth surgery. First, the effects of 12 oral traits and COPD risk were evaluated, and then further investigated other COPD-related outcomes, including COPD in elder.\u003c/p\u003e \u003cp\u003eTo conduct an MR study, the instrumental SNPs used must meet three criteria to ensure their validity: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) the genetic variants are associated with the exposure of interest; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) there are no unmeasured confounders of the associations between genetic variants and outcome; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) the genetic variants affect the outcome only via the exposure of interest (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;1. Study design.\u003c/b\u003e The effects of twelve oral traits on three COPD-related outcomes were investigated. IVs of oral traits that have been reported as associated with any confounders were removed. The list on the confounders box indicates risk factors specific to acute COPD exacerbations. Outcome terms listed in black in the outcome box represented the primary outcomes in the forward MR and were used as exposure in reverse MR. COPD: chronic obstructive pulmonary disease.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eGWAS data on oral traits\u003c/h2\u003e \u003cp\u003eThe GWAS data of some of the oral traits such as \u0026ldquo;Chronic periodontitis\u0026rdquo;,\u0026ldquo;Acute periodontitis \u0026rdquo;,\u0026ldquo;Dental caries\u0026rdquo;,\u0026ldquo;Impacted teeth\u0026rdquo;,\u0026ldquo;Deposits [accretions] on teeth\u0026rdquo; and \u0026ldquo;Excessive attrition of teeth\u0026rdquo; were obtained from FinnGen (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.finngen.fi/en\u003c/span\u003e\u003cspan address=\"https://www.finngen.fi/en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a large-scale genomic research project developed in Finland, which was identified as \u0026ldquo;finn-b-K11_PERIODON_CHRON\u0026rdquo;, \u0026ldquo;finn-b-K11_PERIODON_ACUTE\u0026rdquo;, \u0026ldquo;finn-b-K11_CARIES\u0026rdquo;, \u0026ldquo;finn-b-K11_IMPACTED_TEETH\u0026rdquo;, \u0026ldquo;finn-b-K11_DEPOSITS\u0026rdquo; and \u0026ldquo;finn-b-K11_ATTRITION\u0026rdquo;, respectively.\u003c/p\u003e \u003cp\u003eThe GWAS data of the others oral traits \u0026ldquo;Bleeding gums\u0026rdquo;, \u0026ldquo;Painful gums\u0026rdquo;, \u0026ldquo;Dentures\u0026rdquo;, \u0026ldquo;Loose teeth\u0026rdquo;, \u0026ldquo;Mouth ulcers\u0026rdquo;, \u0026ldquo;wisdom teeth surgery\u0026rdquo; from a dataset published by the UK Biobank on the IEU OpenGWAS project website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which were identified as \u0026ldquo;ukb-b-7872\u0026rdquo;, \u0026ldquo;ukb-b-11161\u0026rdquo;, \u0026ldquo;ukb-b-12930\u0026rdquo;, \u0026ldquo;ukb-b-12849\u0026rdquo;, \u0026ldquo;ukb-a-427\u0026rdquo;, \u0026ldquo;ukb-b-14782\u0026rdquo;, respectively. Detailed information regarding oral traits is provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe characteristics of each exposure and genetic IVs in univariable Mendelian Randomization.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociated SNPs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiltered IVs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size range\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePainful gums\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e461113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDentures\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e461113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExcessive attrition of teeth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e195687\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLoose teeth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e461113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ewisdom teeth surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e462933\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic periodontitis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e198441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcute periodontitis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e195762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDental caries\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e199565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBleeding gums\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e461113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDeposits [accretions] on teeth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e196169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMouth ulcers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e336138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eImpacted teeth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e218792\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGWAS data on COPD\u003c/h2\u003e \u003cp\u003eTo avoid population stratification, our request for COPD data sources was also specific to the European population.\u003c/p\u003e \u003cp\u003eThe COPD data were extracted for the UK Biobank on the IEU OpenGWAS project website, which was named: \u0026ldquo;COPD differential diagnosis\u0026rdquo;, which was identified as \u0026ldquo;ukb-d-COPD_EXCL\u0026rdquo; with a total sample size of 361,194 (26,710 cases and 334,484 controls).\u003c/p\u003e \u003cp\u003eOlder COPD data with a total sample size of 215,284(\u0026gt;\u0026thinsp;65; 3,087 cases and 212,197 controls) were obtained from FinnGen. Detailed information of all exposures and outcomes are provided in Additional file 1: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSelection of instrumental variables\u003c/h2\u003e \u003cp\u003eThe MR Analysis follows three main assumptions (Fig.\u0026nbsp;1). Because IVs need to be closely related to exposure, there were only significant SNPS (P values\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;6), including the largest exposure GWAS (hypothesis 1). The MR Design also requires that IVs influence outcomes only through exposure (hypothesis 3) and not due to other confounding factors (hypothesis 2). Therefore, a three-step filtering process is used to eliminate suspect IVs.\u003c/p\u003e \u003cp\u003eTo meet this criterion, suspicious IVs were identified and excluded through a 3-step filtering process. First, all relevant SNPs selected as genetic instruments satisfied a relatively relaxed threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10\u0026ndash;5. IVs associated with confounders were excluded, and the confounders were primarily selected from outcome risk factors and listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The summary statistics of the associations between IVs and confounders were searched for in the NHGRI-EBI GWAS Catalog with the corresponding terms. Second, the IVs were clumped to ensure independence between SNP markers (linkage disequilibrium - LD - r2 value\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and distance\u0026thinsp;\u0026gt;\u0026thinsp;10 MB). Lastly, remove the IVs that were not included in the outcome GWAS and the IVs that were palindromic. To confirm that the retained IVs do not have any impact on unknown confounders, pleiotropy test was conducted. Additionally, F-statistics were computed to test the strength of the retained IVs .F statistics larger than 10 are regarded as no evidence of weak instrument bias (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMendelian Randomization\u003c/h2\u003e \u003cp\u003eTwo analytical approaches were employed to analyze the data with retained IVs: univariable and multivariable MR. For univariable MR, the causal relationship of each variable was evaluated independently using an IVW. The odds ratio (OR) value (exp(β2)) for disease risk was calculated using the Wald-type estimator and with β1 and β3 representing the effect of each variable on exposure and outcome, respectively. These estimates were combined using IVW to produce an overall β2, while Cochran\u0026rsquo;s Q was used to test for heterogeneity among each β2. The random-effects model was used to combine β2 values when there was heterogeneity.\u003c/p\u003e \u003cp\u003eSeveral additional univariable MR methods, including: MR-Egger, weighted median, MR-PRESSO, and PARS, were also used to confirm the robustness of the results (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In the multivariable MR analysis, the interdependent relationship between various oral traits was assessed (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe R package TwoSampleMR (version\u0026thinsp;=\u0026thinsp;0.5.5) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) was used to conduct univariable and multivariable MR analyses (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The mRnd tool and the R package MVMR (version\u0026thinsp;=\u0026thinsp;0.3) were used for power analysis in univariable and multivariable MR, respectively (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). We used false discovery rate (FDR) to adjust for multiple testing, and an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eInstrumental Variables\u003c/h2\u003e \u003cp\u003eOral -problem-associated SNPs were selected as IVs of the 12 oral problem traits. The other SNPs were excluded from further analysis, mainly due to LD-pruning. The filtered IVs did not show any directional pleiotropy (all \u003cem\u003eP-values\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.050) (Additional file 1: Table S4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDentures increase the risk of COPD\u003c/h2\u003e \u003cp\u003eRegarding the causal relationship between Oral problems and COPD, the IVW showed that the causal relationship between implant dentures and COPD was significant (OR\u0026thinsp;=\u0026thinsp;1.077, 95% CI\u0026thinsp;=\u0026thinsp;1.044\u0026thinsp;~\u0026thinsp;1.111, p_adjust\u0026thinsp;=\u0026thinsp;6.58E-05) (Fig. A), which was found out 121 IVs (Additional file 1: Table S2). However, IVs were identified as heterogeneous by Cochran's Q (p\u0026thinsp;=\u0026thinsp;6.408E-04) (Additional file 1: Table S4). We used multiplicative random effects IVWs to calculate the OR (OR\u0026thinsp;=\u0026thinsp;1.077, 95% CI\u0026thinsp;=\u0026thinsp;1.044\u0026thinsp;~\u0026thinsp;1.111, p_adjust\u0026thinsp;=\u0026thinsp;2.96E-06), which proved the reliability of the selected IVs. The pleiotropy test did not identify directional pleiotropy of the IVs ( P-value\u0026thinsp;\u0026ge;\u0026thinsp;0.080). As shown in the scatter plot, the risk of COPD increases with implant denture (Fig.\u0026nbsp;2B). The leave-one-out sensitivity analysis with one SNP removed at a time showed stable results (Fig.\u0026nbsp;2C). The causal effect of each SNP on IPF is shown in the forest plot (Additional file 1: Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the multivariable MR, in which we screened 72 nSNPs as IVs, we also identified the causality of implant dentures (OR\u0026thinsp;=\u0026thinsp;1.062, 95% CI\u0026thinsp;=\u0026thinsp;1.035\u0026thinsp;~\u0026thinsp;1.090, p\u0026thinsp;=\u0026thinsp;5.428E-06) with COPD (Fig.\u0026nbsp;2D).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFigure\u0026nbsp;2. Effect of each oral trait on COPD risk\u003c/strong\u003e \u003cp\u003e(A) Calculation of the effect of each oral trait on COPD by IVW, which is the most commonly used univariate MR method. (B) Four other univariate MR methods. (C) Leave-one-out plots for the MR analyses of the denture on COPD. (D) Correction of the interaction between different oral traits by multivariate MR.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eExcessive attrition of teeth increased the risk of older COPD\u003c/h2\u003e \u003cp\u003eRegarding COPD risk in older adults, IVW of univariate MR showed that excessive attrition of teeth had a significant effect on COPD in older (OR\u0026thinsp;=\u0026thinsp;1.061, 95% CI\u0026thinsp;=\u0026thinsp;1.020\u0026thinsp;~\u0026thinsp;1.104, p\u0026thinsp;=\u0026thinsp;0.003) (Fig.\u0026nbsp;3A), which was found out 9 IVs (Additional file 1: Table S3). There was no heterogeneity or pleiotropy (P-value\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in the analysis. As shown in the scatter plot, excessive attrition of teeth increases with the increasing the risk of elder COPD (Fig.\u0026nbsp;3B). The leave-one-out sensitivity analysis with one SNP removed at a time showed stable results (Fig.\u0026nbsp;3C). However, This significant causal relationship was not found in the multivariate MR (OR\u0026thinsp;=\u0026thinsp;1.006, 95% CI\u0026thinsp;=\u0026thinsp;0.965\u0026thinsp;~\u0026thinsp;1.050,p\u0026thinsp;=\u0026thinsp;0.753).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;3. Effect of each oral trait on elder COPD risk\u003c/b\u003e (A) Calculation of the effect of each oral trait on elder COPD by IVW, which is the most commonly used univariate MR method. (B) Four other univariate MR methods. (C) Leave-one-out plots for the MR analyses of excessive attrition of teeth on elder COPD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePeriodontitis did not increase the risk of COPD, either acute or chronic\u003c/h2\u003e \u003cp\u003eRegarding the causal relationship between periodontitis and COPD, the IVW in this study showed that periodontitis had no significant effect on COPD risk, either acute(p\u0026thinsp;=\u0026thinsp;0.936, CI\u0026thinsp;=\u0026thinsp;1.000 (0.999\u0026ndash;1.001) ) or chronic(p\u0026thinsp;=\u0026thinsp;0.987, CI\u0026thinsp;=\u0026thinsp;1.000(0.997\u0026ndash;1.003)) (Fig.\u0026nbsp;4). This causal relationship is also not detected in MR Egger, simple median or weighted median.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;4.\u003c/b\u003e Effect of acute and chronic periodontitis on elder COPD risk\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn conclusion, in this study by univariate as well as multivariate MR it was found that 1) implant dentures had a significant causal effect on COPD (OR\u0026thinsp;=\u0026thinsp;1.077, 95% CI\u0026thinsp;=\u0026thinsp;1.044\u0026thinsp;~\u0026thinsp;1.111, p_adjust\u0026thinsp;=\u0026thinsp;6.58E-05), although there was heterogeneity (p\u0026thinsp;=\u0026thinsp;6.408E-04). We eliminated the effect by random effects model; 2) Excessive attrition of teeth significantly increase the risk of COPD (OR\u0026thinsp;=\u0026thinsp;1.061, 95% CI\u0026thinsp;=\u0026thinsp;1.020 to 1.104, p_adjust\u0026thinsp;=\u0026thinsp;0.037). However, this causal relationship was not found in multivariate MR; 3) Unlike previous epidemiological studies, the present study did not find any significant effect of periodontitis (either acute or chronic) on COPD. To our knowledge, this is the first MR framework of investigation oral traits and COPD.\u003c/p\u003e \u003cp\u003eThe association of oral problems with pulmonary diseases, especially COPD, has been a popular topic in epidemiology. Studies have shown that, unlike dental biofilms, biofilms formed on denture materials contain more yeasts and that Candida yeasts, particularly Candida albicans, have been shown to have a solid pathogenic correlation with the presence of denture stomatitis (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Poor denture hygiene promotes the accumulation of bacterial and fungal plaque and results in direct interaction with the prosthetic area mucosa (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Essentially, dentures encourage the growth of flora, and infections caused by bacteria and viruses in lower airways, such as pneumonia and bronchitis, exacerbate COPD. These findings align with our study\u0026rsquo;s results. Additionally, prolonged Excessive attrition of teeth may exacerbate the systemic inflammatory burden, which leads to slight bronchial inflammation that can cause COPD. Nevertheless, other potential oral factors should be taken into account when drawing this conclusion.\u003c/p\u003e \u003cp\u003eThe association between periodontitis and COPD is widely studied as a link between oral and respiratory disease. According to an epidemiological survey from Korea, patients with COPD had a higher prevalence of periodontitis (58.1%) than those without COPD (34.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). This finding is supported by a population-based study from Spain as well (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with rates of 26.5% and 22.2%, respectively (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe latest study suggests that this may be attributed to periodontitis affecting Th1 profile cell processes, cytokines, and pulmonary alterations (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), which is further corroborated by transcriptomic analysis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, the current evidence is, at best, indirectly supportive of the link between COPD and periodontitis.\u003c/p\u003e \u003cp\u003eOther studies have failed to find these associations, which showing no significant relationship between periodontitis and COPD. Bergstrom et al. found that smoking, rather than COPD, was the primary risk factor for periodontal pocket depth (OR 24.2; 95% CI 2.0-286.8) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Another analysis of the NHANES survey found no association between the two diseases in those who had never smoked, although subgroup analyses found such an association in those who were smoking or former smokers (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). An analysis of kNHANES from Korea also showed that the prevalence of periodontitis was not significantly associated with reduced lung function (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, the findings align with these epidemiological studies, founding no significant causal relationship between periodontitis and COPD by MR, implying that the reported epidemiological associations could result from unmeasured confounding. We adjusted for various confounders, including smoking, BMI, education and economic status, when conducting the analysis, while many earlier epidemiological studies did not consider these factors. For example, Shen et al. failed to correct for smoking status (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), while the study by Leuckfeld et al. did not adjust for socioeconomic factors (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). After adjusting for these effects, numerous studies have shown that periodontitis and COPD are no longer correlated (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the hypothesis of a causal relationship between periodontitis and COPD, the oral cavity is an essential reservoir of pulmonary pathogens, then pathogens in dental plaque can be inhaled into the respiratory system through the oral cavity, causing aspiration pneumonia and thus exacerbating COPD (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). A meta-analysis has reported that oral hygiene and antibiotic intervention significantly reduced the risk of pneumonia in these populations, supporting a causal relationship between oral pathogens and lower respiratory tract infections (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). However, most relevant studies have been conducted in intensive care settings, and it is unclear whether the findings can be generalized to a broader population.\u003c/p\u003e \u003cp\u003eThis study has the following strengths: First, it is the first attempt to explore the effects of different oral traits on COPD through a two-sample MR analysis using GWAS summary-level statistics and minimizes the effects of confounding factors. Secondly, the findings were validated by applying multiple MR methods and sensitivity analyses with different model assumptions, and the effects of outliers and pleiotropy were evaluated comprehensively. Finally, this study provides a new starting point for research on the pathogenesis of COPD and can provide new diagnostic strategy treatment strategies for COPD patients, especially those with oral disease\u003c/p\u003e \u003cp\u003eHowever, this study also has some limitations. First, although the GWAS dataset of this study all from European populations, the data was not from a single genomics research project and included data from the UK Biobank and FinnGen, which may influence the results. Secondly, caution should be observed in generalizing the findings to other populations due to the limited representation of European population data and the lack of ethnic diversity. Lastly, the analysis could not be stratified by different levels of periodontitis severity because no existing GWAS had identified IVs associated with such classifications, necessitating further investigation of the effect of different levels of periodontitis on COPD.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides genetic evidence supporting the causal role of implant dentures on COPD and high levels of tooth wear in older individuals with COPD. Our results suggest that the evidence for a causal relationship between periodontitis and COPD is still insufficient and previous studies may have been affected by confounding factors. More experimental studies are needed to confirm our findings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGWAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGenome-wide association studyIV:Instrumental variable\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic obstructive pulmonary diseaseMR:Mendelian randomizationIVW:Inverse variance weighting\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elinkage disequilibrium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank to the Internet for providing the main data (https://gwas.mrcieu.ac.uk/) (https://www.finngen.fi/en).\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe design and performance of this study were funded by the National Natural Science Foundation of China (82170044).\u003c/p\u003e\n\u003cp\u003eAuthor information\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003eThe Second Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China\u003c/p\u003e\n\u003cp\u003eFanye Wu, Zejun Chen, Zhengran Li, Yuxin Sun and Zijin Wang;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment of Ophthalmology, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China\u003c/p\u003e\n\u003cp\u003eMingzhe Cao\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInstitute of Scientific Research, Southern Medical University, Guangzhou, 510515, China\u003c/p\u003e\n\u003cp\u003eMinghui Zeng\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDepartment\u0026nbsp;of\u0026nbsp;Pharmacy, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China\u003c/p\u003e\n\u003cp\u003eLiqing Wang\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe First Clinical Medicine School, Southern Medical University, Guangzhou, Guangdong, China\u003c/p\u003e\n\u003cp\u003eTong Wu\u003c/p\u003e\n\u003cp\u003eEmergency Department, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, China\u003c/p\u003e\n\u003cp\u003eFanke Meng\u003c/p\u003e\n\u003cp\u003eContributions\u003c/p\u003e\n\u003cp\u003eFW, MC and FM designed the study and drafted the manuscript. LW, ZL, YS, ZW and TW performed the data collection and analysis. MZ, ZZ and ZC performed validation and analysis. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCorresponding author\u003c/p\u003e\n\u003cp\u003eCorrespondence to Fanke Meng.\u003c/p\u003e\n\u003cp\u003eEthics declarations\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWatz H, Waschki B, Kirsten A, M\u0026uuml;ller KC, Kretschmar G, Meyer T, et al. The Metabolic Syndrome in Patients With Chronic Bronchitis and COPD: Frequency and Associated Consequences for Systemic Inflammation and Physical Inactivity. Chest. 2009 Oct 1;136(4):1039\u0026ndash;46. \u003c/li\u003e\n\u003cli\u003eGBD 2013 Mortality and Causes of Death Collaborators. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015 Jan 10;385(9963):117\u0026ndash;71. \u003c/li\u003e\n\u003cli\u003eRabe KF, Watz H. Chronic obstructive pulmonary disease. Lancet. 2017 May 13;389(10082):1931\u0026ndash;40. \u003c/li\u003e\n\u003cli\u003eNussbaumer-Ochsner Y, Rabe KF. Systemic manifestations of COPD. Chest. 2011 Jan;139(1):165\u0026ndash;73. \u003c/li\u003e\n\u003cli\u003eJohnston AK, Mannino DM, Hagan GW, Davis KJ, Kiri VA. Relationship between lung function impairment and incidence or recurrence of cardiovascular events in a middle-aged cohort. Thorax. 2008 Jul;63(7):599\u0026ndash;605. \u003c/li\u003e\n\u003cli\u003eMannino DM, Thorn D, Swensen A, Holguin F. Prevalence and outcomes of diabetes, hypertension and cardiovascular disease in COPD. Eur Respir J. 2008 Oct;32(4):962\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eWatanabe R, Tanaka T, Aita K, Hagiya M, Homma T, Yokosuka K, et al. Osteoporosis is highly prevalent in Japanese males with chronic obstructive pulmonary disease and is associated with deteriorated pulmonary function. J Bone Miner Metab. 2015 Jul;33(4):392\u0026ndash;400. \u003c/li\u003e\n\u003cli\u003eQian Y, Yuan W, Mei N, Wu J, Xu Q, Lu H, et al. Periodontitis increases the risk of respiratory disease mortality in older patients. Exp Gerontol. 2020 May;133:110878. \u003c/li\u003e\n\u003cli\u003eSaito M, Shimazaki Y, Yoshii S, Takeyama H. Periodontitis and the incidence of chronic obstructive pulmonary disease: A longitudinal study of an adult Japanese cohort. Journal of Clinical Periodontology. 2023;50(6):717\u0026ndash;26. \u003c/li\u003e\n\u003cli\u003eSapey E, Yonel Z, Edgar R, Parmar S, Hobbins S, Newby P, et al. The clinical and inflammatory relationships between periodontitis and chronic obstructive pulmonary disease. J Clin Periodontol. 2020 Sep;47(9):1040\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eRosa EP, Murakami-Malaquias-da-Silva F, Palma-Cruz M, de Carvalho Garcia G, Brito AA, Andreo L, et al. The impact of periodontitis in the course of chronic obstructive pulmonary disease: Pulmonary and systemic effects. Life Sci. 2020 Nov 15;261:118257. \u003c/li\u003e\n\u003cli\u003eLiu S, Fu Y, Ziebolz D, Li S, Schmalz G, Li F. Transcriptomic analysis reveals pathophysiological relationship between chronic obstructive pulmonary disease (COPD) and periodontitis. BMC Med Genomics. 2022 Jun 8;15(1):130. \u003c/li\u003e\n\u003cli\u003eChen H, Zhang X, Luo J, Dong X, Jiang X. The association between periodontitis and lung function: Results from the National Health and Nutrition Examination Survey 2009 to 2012. Journal of Periodontology. 2022;93(6):901\u0026ndash;10. \u003c/li\u003e\n\u003cli\u003eJung ES, Lee KH, Choi YY. Association between oral health status and chronic obstructive pulmonary disease in Korean adults. Int Dent J. 2020 Jun;70(3):208\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eLee E, Lee SW. Prevalence of Periodontitis and Its Association with Reduced Pulmonary Function: Results from the Korean National Health and Nutrition Examination Survey. Medicina. 2019 Sep;55(9):581. \u003c/li\u003e\n\u003cli\u003eBurgess S, Timpson NJ, Ebrahim S, Davey Smith G. Mendelian randomization: where are we now and where are we going? Int J Epidemiol. 2015 Apr;44(2):379\u0026ndash;88. \u003c/li\u003e\n\u003cli\u003eJiao R, Li W, Song J, Chen Z. Causal Association Between Asthma and Periodontitis: A Two-Sample Mendelian Randomization Analysis. Oral Dis. 2023 Mar 23; \u003c/li\u003e\n\u003cli\u003eBaumeister SE, Nolde M, Holtfreter B, Baurecht H, Gl\u0026auml;ser S, Kocher T, et al. Periodontitis and pulmonary function: a Mendelian randomization study. Clin Oral Investig. 2021 Aug;25(8):5109\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003eBurgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013 Nov;37(7):658\u0026ndash;65. \u003c/li\u003e\n\u003cli\u003eBowden J, Del Greco M F, Minelli C, Davey Smith G, Sheehan N, Thompson J. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Statistics in Medicine. 2017;36(11):1783\u0026ndash;802. \u003c/li\u003e\n\u003cli\u003eHemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018 May 30;7:e34408. \u003c/li\u003e\n\u003cli\u003eBurgess S, Thompson SG. Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. Am J Epidemiol. 2015 Feb 15;181(4):251\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eHemani G, Tilling K, Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017 Nov;13(11):e1007081. \u003c/li\u003e\n\u003cli\u003eSanderson E, Spiller W, Bowden J. Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization. Stat Med. 2021 Nov 10;40(25):5434\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eFigueiral MH, Azul A, Pinto E, Fonseca PA, Branco FM, Scully C. Denture-related stomatitis: identification of aetiological and predisposing factors - a large cohort. J Oral Rehabil. 2007 Jun;34(6):448\u0026ndash;55. \u003c/li\u003e\n\u003cli\u003eCampos MS, Marchini L, Bernardes L a. S, Paulino LC, Nobrega FG. Biofilm microbial communities of denture stomatitis. Oral Microbiol Immunol. 2008 Oct;23(5):419\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eSumi Y, Miura H, Sunakawa M, Michiwaki Y, Sakagami N. Colonization of denture plaque by respiratory pathogens in dependent elderly. Gerodontology. 2002 Jul;19(1):25\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eChung JH, Hwang HJ, Kim SH, Kim TH. Associations Between Periodontitis and Chronic Obstructive Pulmonary Disease: The 2010 to 2012 Korean National Health and Nutrition Examination Survey. J Periodontol. 2016 Aug;87(8):864\u0026ndash;71. \u003c/li\u003e\n\u003cli\u003eLopez-de-Andr\u0026eacute;s A, Vazquez-Vazquez L, Martinez-Huedo MA, Hern\u0026aacute;ndez-Barrera V, Jimenez-Trujillo I, Tapias-Ledesma MA, et al. Is COPD associated with periodontal disease? A population-based study in Spain. Int J Chron Obstruct Pulmon Dis. 2018;13:3435\u0026ndash;45. \u003c/li\u003e\n\u003cli\u003eLeuckfeld I, Obregon-Whittle MV, Lund MB, Geiran O, Bj\u0026oslash;rtuft \u0026Oslash;, Olsen I. Severe chronic obstructive pulmonary disease: association with marginal bone loss in periodontitis. Respir Med. 2008 Apr;102(4):488\u0026ndash;94. \u003c/li\u003e\n\u003cli\u003eHyman JJ, Reid BC. Cigarette smoking, periodontal disease: and chronic obstructive pulmonary disease. J Periodontol. 2004 Jan;75(1):9\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eShen TC, Chang PY, Lin CL, Chen CH, Tu CY, Hsia TC, et al. Risk of Periodontal Diseases in Patients With Chronic Obstructive Pulmonary Disease: A Nationwide Population-based Cohort Study. Medicine (Baltimore). 2015 Nov;94(46):e2047. \u003c/li\u003e\n\u003cli\u003eLiu Z, Zhang W, Zhang J, Zhou X, Zhang L, Song Y, et al. Oral hygiene, periodontal health and chronic obstructive pulmonary disease exacerbations. Journal of Clinical Periodontology. 2012;39(1):45\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eBergstr\u0026ouml;m J, Cederlund K, Dahl\u0026eacute;n B, Lantz AS, Skedinger M, Palmberg L, et al. Dental health in smokers with and without COPD. PLoS One. 2013;8(3):e59492. \u003c/li\u003e\n\u003cli\u003eScannapieco FA, Wang B, Shiau HJ. Oral bacteria and respiratory infection: effects on respiratory pathogen adhesion and epithelial cell proinflammatory cytokine production. Ann Periodontol. 2001 Dec;6(1):78\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eBansal M, Khatri M, Taneja V. Potential role of periodontal infection in respiratory diseases - a review. J Med Life. 2013 Sep 15;6(3):244\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eScannapieco FA, Bush RB, Paju S. Associations between periodontal disease and risk for nosocomial bacterial pneumonia and chronic obstructive pulmonary disease. A systematic review. Ann Periodontol. 2003 Dec;8(1):54\u0026ndash;69. \u003c/li\u003e\n\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":"mendelian randomization, CODP, periodontitis, denture, tooth attrition","lastPublishedDoi":"10.21203/rs.3.rs-3179826/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3179826/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe association between oral diseases and chronic obstructive pulmonary disease (COPD) has been revealed by many epidemiological studies in clinical aspects. Therefore, we elucidate genetic relationships using Mendelian randomization (MR) in this study.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eWe utilized MR analysis with summary datasets from a genome-wide association study (GWAS) to investigate the causal relationship between COPD and 12 oral traits such as periodontitis and denture and ensured that there were no confounders like smoking, and every F-value was greater than 10. Inverse variance weighting (IVW) was applied with MR analysis as the primary outcome. Additionally, the horizontal pleiotropy was assessed by MR-PRESSO methods, and the heterogeneity was detected using Cochran's Q statistics.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThis study found a significant causal effect of implant dentures on COPD by univariate and multivariate MR (OR\u0026thinsp;=\u0026thinsp;1.077, 95%CI\u0026thinsp;=\u0026thinsp;1.044\u0026thinsp;~\u0026thinsp;1.111, p_adjust\u0026thinsp;=\u0026thinsp;6.58E-05). Although univariate MR showed that excessive attrition of teeth had a significant causal effect on later COPD (OR\u0026thinsp;=\u0026thinsp;1.061, 95%CI\u0026thinsp;=\u0026thinsp;1.020\u0026thinsp;~\u0026thinsp;1.104, p_adjust\u0026thinsp;=\u0026thinsp;0.037), this causal relationship was not found in multivariate MR. This study found no significant effect of periodontitis on COPD (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), either acute or chronic.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur MR Analysis findings suggested that implant dentures and excessive attrition of teeth significantly promotes the risk of COPD and elder COPD, respectively. However, the evidence for a causal relationship between periodontitis and COPD is still insufficient and previous studies may have been affected by confounding factors.\u003c/p\u003e","manuscriptTitle":"Causal association between oral disease and chronic obstructive pulmonary disease: A Mendelian Randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-24 13:49:47","doi":"10.21203/rs.3.rs-3179826/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":"1c934de2-f3c8-4fbf-9c1e-af8c421fef94","owner":[],"postedDate":"July 24th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-09-18T05:29:21+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-24 13:49:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3179826","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3179826","identity":"rs-3179826","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}