A Mendelian Randomization Study for Liposome on oral potentially malignant disorders and oral squamous cell carcinoma

A Mendelian Randomization Study for Liposome on oral potentially malignant disorders and oral squamous cell carcinoma | 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 Article A Mendelian Randomization Study for Liposome on oral potentially malignant disorders and oral squamous cell carcinoma Kaixin Su, Jia Mi, Rifu Wang, Jian Zhou, Fei Yan, Ousheng Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5310318/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 Introduction and aims: In oral mucosal disease (OMD), oral squamous cell carcinoma(OSCC) and oral potentially malignant disorders(OPMD), such as oral lichen planus (OLP) and oral leukoplakia (OLK), have the most complex etiology and worst prognosis among all OMDs. The use of liposomes shows great potential in diagnosing, treating, and preventing the mentioned diseases. Using mendelian randomization to explore the correlation between liposomes and OPMD as well as oral cancer, aiming to enhance the potential impact of liposomal genetic variations on early detection and treatment of oral diseases. Methods: This Mendelian randomization study utilized data from 7174 GWAS participants from GeneRISK, Finland, examining 179 lipid species. SNPs associated with OSCC, OLP, and OLK were analyzed using the inverse variance weighted (IVW) method, weighted mode, weighted median (WM), and MR-Egger methods. Sensitivity analysis was conducted with Cochrane's Q test and MR-PRESSO. Results: IVW analysis identified six liposome types associated with OSCC, 21 with OLP, and seven with OLK (p<0.05). Notable protective factors for OSCC included specific triacylglycerol, while OLK-related liposomes presented opposite risk factors. OLP-associated lipids included three risk-associated triglycerides. No heterogeneity or horizontal pleiotropy was detected, confirming the robustness of the findings. Conclusion: The study highlighted similarities in the metabolic components of the blood lipidome among OSCC, OLP, and OLK, though liposomes with identical structures exhibited differing effects on disease pathogenesis.The study revealed the protective and risk effects of liposomes on OLP, OLK, and OSCC, highlighting their dual nature. Related lipidomics support non-invasive disease identification in OPMD conditions, offering a potential strategy for targeted prevention and drug treatment. Biological sciences/Biochemistry/Lipidomics Biological sciences/Biochemistry/Lipids OLP OLK OSCC liposome MR analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Complexity of oral mucosal disease (OMD) arises from the vulnerability of the oral cavity as a gateway to various risks and influencing factors. However, prevalence of OMDs is significant, characterized by a wide age range 1 , similar lesion manifestations, and a high proportion of affected individuals. Furthermore, the malignant transformation potential of these diseases significantly impacts prognosis and quality of life. Therefore, it is crucial to investigate the etiology of OMDs, alleviate symptoms, and enhance prognosis. As a starting point, the significance of preventive measures cannot be overstated. Identifying and mitigating risk factors presents an opportunity for pioneering advancements in OMD research. In OMDs, oral squamous cell carcinoma (OSCC), oral lichen planus (OLP), and oral leukoplakia (OLK) exhibit the most complex etiology and the worst prognosis. OLP and OLK are considered precancerous conditions, with a potential for progression to OSCC 2 , making them crucial for clinical prognosis and a focal point in current research. Currently, the existing research evidence is largely derived from in vitro experiments 3 , epidemiological surveys 4 , and randomized controlled trials (RCTs) 5 . According to traditional clinical treatment guidelines, OLP can be managed with medication and relaxation, while OLK can be addressed through laser treatment, local drug therapy, or surgical removal depending on its size. OSCC represents a predominant subtype of oral cancer, impacting functions such as mouth opening and eating while infiltrating adjacent tissues. Epidemiological investigations have consistently demonstrated the strong correlation between OSCC and low survival rates as well as high disability rates 6 . Treatment modalities encompass surgical radical resection, targeted therapy, radiation therapy, and chemotherapy. Nevertheless, the intricate anatomical structures in the head and neck region pose significant operative risks alongside substantial postoperative complications, thereby underscoring the paramount importance of addressing oral malignancies. The utilization of liposomes as a novel therapeutic approach is currently at the forefront of research in the field of OMDs. Application of liposomal steroids has been employed for the treatment of OLP simultaneously 7 . Liposomes refers to the comprehensive analysis of lipid metabolic products in blood plasma, and it also encompasses an artificial spherical vesicle structure composed of a pair of lipid molecules that serves as a crucial nanocarrier tool 8 . By harnessing its ability to integrate with cell membranes as a vehicle for drug delivery such as OSCC 9 , it facilitates direct conveyance of the drug into the intracellular space. This strategy overcomes challenges related to tissue metabolism-mediated absorption during oral and intravenous administration, resulting in improved therapeutic effectiveness and reduced systemic toxicity, as supported by extensive empirical research 10 . The effectiveness and risks of this treatment were not well-supported by strong evidence at the time of the study. Within the domain of oral diseases, there exists an imperative to curtail off-target toxicity while optimizing targeting precision; leveraging the distinctive attributes of liposomes becomes particularly pivotal in tailoring personalized treatment regimens to mitigate adverse reactions, aligning seamlessly with the tenets of precision medicine. Mendelian randomization (MR) is a powerful approach that uses genetic variants associated with exposure as instruments to examine the potential causal association between exposure and outcome 11 . MR is less likely to be affected by confounding or reverse causality, as it mimics the randomized controlled trials by randomly assigning genetic variants at the time of conception 12 . The urgent need to study liposomes lies in understanding their causal impact on OMDs. Hence, this research aims to establish a clear correlation between liposomes and OSCC, OLP, and OLK through strong evidence, advancing early detection and treatment of oral diseases using liposomal interventions. Thereupon, our study plans to conduct a MR analysis using GWAS data on 179 lipid types from 7174 Finnish individuals, as reported in Nature Communications on October 23, 2023. The GWAS data for this analysis was obtained from the FinnGen and GWAS catalog Database, including 1223 OSCC cases and 2928 controls, 5791 OLP cases and 371486 controls, as well as 2598 OLK cases and 409583 controls, aiming to unveil the association between liposomes and OMDs. 2. Materials and methods 2.1 Data sources for the exprosure The summary statistics for lipid profiles were derived from a genome-wide association study (GWAS) catalog, specifically from entries GCST90277-238 to GCST90277-416. This study analyzed data from 7,174 unrelated Finnish individuals who were part of the GeneRISK cohort. The research tested 179 lipid species, categorized into 13 classes and 4 broader categories, utilizing single nucleotide polymorphisms (SNPs) for their analysis 13 . Detailed data and additional resources can be accessed via the GWAS catalog at https://www.ebi.ac.uk/GWAS/ . The GWAS data is summarized in Table 1 . Table 1 Summary of the GWAS included in this Mendelian randomization study. Exposures/outcomes Consortium Ethnicity Sample sizes Year Plasma lipidome GWAS catalog European 7174 2023 Oral cavity cancer GWAS catalog European 4151 2016 Oral lichen planus Risteys R9 European 377277 2023 Oral leukoplakia and related diseases Ristesys R10 European 412181 2023 2.2 Data sources for the outcome The GWAS data for this analysis was obtained from the FinnGen and GWAS catalog Database. This included 1223 cases and 2928 controls for OSCC, 5791 cases and 371486 controls for OLP, and 2598 cases and 409583 controls for OLK and related diseases. The GWAS data is summarized in Table 1 . 2.3 Selection of instrumental variables In this MR study, we employed SNPs associated with blood liposomes that reached a genome-wide significance level (p < 1 × 10⁻⁵) from previous GWASs 14 . To ensure the independence of each instrumental variable (IV) and to mitigate the influence of linkage disequilibrium (LD), SNPs within a 10,000 kb window were clumped, applying an r² threshold of < 0.001. To minimize the influence of weak instrument bias on the estimation of association effects, we evaluated the strength of the instruments using an F-statistic threshold greater than 10. The F-statistic was computed using the formula: F = R2(n − 2)/1 − R 215 , where n is the sample size. The R 2 value was derived from the minor allele frequency (MAF) and effect estimates (β) using the formula: R 2 = 2×MAF × (1-MAF)×β 2 . An F-statistic greater than 10 indicates that the results are not biased by weak IVs. 2.4 Two-sample of MR Analysis(TSMR) To investigate the causal relationship between blood liposomes and OMDs, various statistical methods were employed. These included the inverse variance weighted (IVW) method 16 , the weighted mode method 17 , the weighted median (WM) method 18 , and the Mendelian randomization-Egger (MR-Egger) method 19 . The IVW method is widely recognized and most effective when all IVs satisfy the core assumptions of MR, such as the absence of horizontal pleiotropy and unbiased effect estimates. The WM method, which calculates the median of all IV effect estimates, is particularly advantageous when some IVs deviate from MR assumptions, including the presence of horizontal pleiotropy. The MR-Egger method not only estimates causal effects but also identifies and corrects for horizontal pleiotropy, making it valuable when horizontal pleiotropy is suspected. Associations were considered significant if the IVW method yielded a p-value less than 0.05 and the direction of estimates from the other MR methods was consistent with that of the IVW method. 2.5 Sensitivity analysis Several tests were utilized to ensure the robustness of our findings, including the heterogeneity test, pleiotropy test, and leave-one-out sensitivity test in Fig. 1 . To assess overall pleiotropy in the IVW MR findings, Cochrane’s Q test was applied, with a p-value < 0.05 indicating the presence of heterogeneity. The average horizontal pleiotropy of the IVs in MR-Egger regression was determined using the intercept term and the assessment of funnel plot asymmetry. A significance level below p < 0.05 was considered indicative of heterogeneity. Subsequently, a leave-one-out analysis was performed to evaluate whether significant changes in causal effects occurred before and after the removal of outliers. Additionally, the MR-PRESSO method was employed to detect and correct for pleiotropy by identifying and excluding potential outliers 20 . These analyses were conducted using the TwoSampleMR (version 0.6.0) , MR (version 0.8.0), and MRPRESSO package (1.0) in R Software 4.3.3 ( https://www.R-project.org ) 3. Results 3.1 Causal effects of lipidomes and OSCC Although lipid components can be easily extracted from plasma, numerous studies have investigated their relationship with OSCC. However, it remains challenging to directly establish a linear correlation between lipid components and OSCC. Various statistical methods will be employed in two-sample MR analysis to screen liposomes associated with one-to-one outcomes in OSCC(nsnp = 9 ~ 23). This study aims to explore the association between liposomes and OSCC. The causal effect of liposomes on OSCC risk was assessed through our MR analysis, revealing that glycerol phospholipid and glycerolipids may influence the risk of OSCC and are considered protective factors in Fig. 2 . Among them, glycerophospholipids(GPs) include phosphatidylcholine (PC, O-16:2_18:0, p-val = 0.015), phosphatidylethanolamine (PE, O-18:2_20:4, p-val = 0.029), and phosphatidylinositol (PI, 18:1_20:4, p-val = 0.028). Glycerolipids compound with triacylglycerol (TG, 48:3, p-val = 0.035), TG(54:4, p-val = 0.034) and TG(56:5, p-val = 0.033). Recent studies have indicated that the composition of plasma lipids may serve as a valuable tool for guiding clinical staging and facilitating early diagnosis 21 . The six specific liposomes containing protective factors identified in this study could potentially be developed as a method for early diagnosis of OSCC. Triacylglycerol levels were observed to be lower in the plasma of OSCC patients compared to both the oral precancerous lesion group and the normal group. The study revealed that the inverse relationship between OSCC and triglycerides offers an explanation for this clinical phenomenon. In line with the findings regarding protective factors(or = 0.45 to 0.98, 95%CI). 3.2 Causal effects of lipidomes and OLP The OLP case-control study revealed a statistically significant elevation in TG levels within the case group compared to the control group 22 . Nevertheless, there is insufficient clear evidence to establish a causal relationship between TGs and OLP. Our study has revealed that the identical liposome structure may lead to inconsistent outcomes in OLP. Through a two-sample of MR analysis to assess the causal impact of liposomes on OLP, the findings indicate that steroids, GPs, and glycolipids may influence the likelihood of developing OLP in Fig. 3 . PE (O-16:1_20:4,p-val = 0.037), PC (17:0_20:4, p-val = 0.002), PC (18:0_20:5, p-val = 0.012), PC (16:1_20:4, p-val = 0.027), PC (18:2_20:4, p-val = 0.038), PC (20:4_0:0, p-val = 0.005),PC (16:0_22:4, p-val = 0.036) and PC (16:0_20:4, p-val = 0.041) are the protective factors of GPs(or = 0.84 to 1.00, 95%CI). Sterol ester (SE, 27:1/18:0, p-val = 0.020) and SE (27:1/20:5, p-val = 0.008) are the protective factors of steroid(or = 0.82 to 0.98, 95%CI). Glycerolipids with TG(46:1, p-val = 0.044), TG(54:3, p-val = 0.025) and TG(56:3, p-val = 0.046) as risk factors(or = 1.00 to 1.20, 95%CI). Only a SE(27:1/18:2, p-val = 0.003) is the risk factor of steroid(or = 1.04 to 1.22, 95%CI). OLP patients typically undergo topical steroid therapy 23 . This study identified two protective factors of steroids that may provide evidence for this treatment approach. However, there is also a risk factor associated with steroids, so the use of steroids as a treatment agent should be avoided when SE (27:1/18:2) is present. 3.3 Causal effects of lipidomes and OLK OLK is indicative of a precancerous lesion associated with OSCC, and their liposome composition is similar; however, their effects exhibit an opposite trend. In a small-scale comparative experiment on OLK plasma lipid components in India, no statistically significant differences were observed in TG, thereby addressing a gap in current research 24 .After conducting a two-sample of MR analysis to assess the causal impact of liposomes on OLK(nspn = 18 ~ 29), the findings suggest that GPs and glycolipids may influence the risk of OLK and are considered as potential risk factors. PC (O-18:2_18:2, p-val = 0.012), PE (18:0_18:2, p-val = 0.021), PI (18:1_18:1, p-val = 0.018), PI (18:1_18:2, p-val = 0.013) were among the four liposomes screened for glycerophospholipid risk factors(or = 1.03 to 1.52, 95%CI). Glycerolipids consist with TG(50:5, p-val = 0.023), TG(52:2, p-val = 0.038) and TG(58:8, p-val = 0.047) as risk factors(or = 1.00 to 1.35, 95%CI) in Fig. 4 . 3.4 Sensitivity analysis A comprehensive sensitivity analysis was performed to verify the robustness of our findings. Cochran’s Q statistic was utilized to evaluate heterogeneity for both the IVW and MR-Egger methods, with Q_pval values exceeding 0.05, indicating no heterogeneity and thus supporting the application of fixed-effect models for IVW(Table S1 ). This conclusion was further corroborated by the assessments using both funnel and forest plots, which also suggested the absence of heterogeneity. Outlier detection conducted via the MR-PRESSO method did not identify any outliers, as indicated by p-values greater than 0.05, reinforcing the validity of single-outcome conclusions for OSCC, OLP, and OLK within this liposome cohort. Additionally, the leave-one-out analysis demonstrated that no individual SNP had a significant impact on the results. Consequently, this Mendelian randomization analysis is considered reliable and robust. 4. Discussion This study is the first to explore the impact of different liposome populations on the occurrence of OSCC, OLP, and OLK, revealing intricate causal relationships between various liposome structures and OMDs. Specifically, PC, PE, and PI demonstrate protective effects against OSCC and risk effects on OLK. The lipid composition of OLP is complex, with varying chain lengths and double bond numbers of steroids and GPs associated with different risks and protective factors. In OSCC, glycolipid PC, which is linked to an increased risk of OLK, instead correlates with a protective factor. This correlation may require further research. Liposomes are considered to be one of the most promising drug delivery tools due to their functional characteristics, which closely resemble biological membranes and can be absorbed by the human body through oral formulations. However, this study indicates that certain types of liposomes may present a risk for OMDs. It is suggested that not all liposomes are suitable for use as drug-release vehicles in order to mitigate toxicity. In OSCC, the focus of targeted therapy for anti-cancer drugs has also shifted towards nanotechnology research. Ideal new treatment strategies involve targeted drug delivery and sustained release systems 25 . In addition to liposomes 26 , nanoparticles, nanoliposomes 27 , hydrogels 28 , exosomes, and other nanomaterials are under study. GP constitute the primary constituents of biological membranes. PC (O-16:2_18:0) serves as a protective lipid for OSCC. PC serves as the primary phospholipid constituent in eukaryotic membranes, and it can be biosynthesized via either the methylation pathway or the CDP-choline pathway 29 . Meanwhile, PC is thought to act as a protective barrier against bacterial invasion in the intestines 30 . Given the comparable levels present in bacterial membranes, it is widely accepted that the enzymatic methylation of PE through the methylation pathway represents the sole biochemical route for synthesizing PC in bacteria 31 . Under these conditions, PC has been thoroughly researched in the area of drug delivery. Oral administration of lipid nanoparticles containing PC and Lyso-PS can transform immunogenic substances into tolerogenic ones, thereby inducing immune tolerance to multiple antigens and reducing the occurrence of immune adverse reactions 32 . Various PC structures are associated with different levels of risk for specific diseases. The following PC species were identified as protective factors against OLP: PC(17:0_20:4), PC(18:0_20:5), PC(16:1_20:4), PC(18:2_20:4), PC(20:4_0:0), PC(16:0_22:4) and PC(16:0_20:4). Nonetheless, PC (O-16:2_18:0) exhibits significant potential as a drug delivery vehicle for OSCC. For instance, PC (O-18:2_18:2) exhibited a positive correlation with the risk of OLK. Similarly, PC(14:0_18:2), PC(18:0_20:2), PC(18:2_18:2), PC(O-18:1_18:2), and PC(O-18:2_18:2) demonstrated a positive correlation with the risk of OLP. This finding may indicate an imbalance in lipid metabolism in OLP. Therefore, the distinct and multifaceted impact of OLP on lipids can serve as a supplementary clinical diagnostic criterion, and exploring non-invasive methods for extracting lipids may replace invasive biopsies as the gold standard for diagnosis. PE (O-18:2_20:4) was identified as a protective factor against OSCC. PE (O-16:1_20:4) also serves as a protective factor for OLP. As a partner of PC, PE constitutes over 50% of the total phospholipid species present in eukaryotic membranes. It serves as a critical mediator in the modulation of the impact of reactive oxygen species (ROS) and their derivatives, active aldehydes (RA), on membrane proteins. However, the pro-apoptotic mechanism of ROS is associated with the inhibition of OSCC. Studies have demonstrated that lipid homeostasis and ROS activation mitigate lipotoxicity by down-regulating CES2, thereby impeding OSCC progression 33 . In terms of risk, PE facilitates the conformational changes of cofilin proteins 34 , stimulates oxidative phosphorylation 35 , contributes to cell apoptosis 36 , and is involved in ferroptosis pathways leading to cell death. This may potentially offer insights into the potential risk factors of PE(18:2_0:0) and PE(O-16:1_18:2) for OLP, while indicating that PE(18:0_18:2) could be a risk factor for OLK. PI is a membrane lipid that modulates the dynamics of cellular membranes 37 . PI(18:1_20:4) exhibits a protective effect against OSCC, while PI(18:1_18:1) and PI (18:1_18:2) are identified as risk factors for OLK. Enhanced intimate signal transduction may result in the inhibition of immune evasion in OSCC. While no studies have specifically focused on PI(18:1_18:1) and PI(18:1_18:2), the potential targeting effects of OLK on these molecules may be inferred from related signal inhibition. TG found in GPs serve as the primary mechanism for energy storage in the human body. The TG index is linked to various irregularities in plasma lipid metabolism. TG (54:4), TG (56:5), TG (48:3) are identified as protective factors for OSCC, while TG (56:3), TG (54:3), and TG (46:1) are identified as risk factors for OLP. Despite variations in their specific structures, they demonstrate similar lipid droplet classifications, indicating a high propensity for cancer in both OLK and OLP. Nevertheless, studies have examined lipidomics in OSCC patients and OPMD, revealing no significant differences in TG concentration among the control group, OSCC, and OPMD. This may be attributed to variations in dietary habits and genetic differences between Asian and European populations. SE serve as crucial storage compounds in numerous eukaryotic organisms and frequently constitute a significant component of lipid droplets within cells 38 . SE(27:1/18:0) and SE(27:1/20:5) have been identified as protective factors for OLP, whereas SE (27:1/18:2) are considered to be risk factors for OLP. The current literature on this topic is limited, thus presenting an opportunity for further research to complement existing areas of study. SE is extensively researched in the field of plant-relatedness and can be assimilated and stored by the human body 39 , such as margarine 40 , soybean oil, etc. The oral cavity functions as the entry point for food consumption, and ingested food initially passes through the mouth into the body. Therefore, it is crucial to carefully consider dietary structure in order to prevent the development of OLP, as this article underscores the dual significance of SE in promoting OLP. 5. Advantages and Limitations Our study has several notable strengths. Firstly, we are pioneers in thoroughly investigating the correlation between lipids and OMDs using the TSMR method. This study involves comprehensive data collection while minimizing potential confounding factors. Secondly, we conducted parallel comparison analyses to examine the similarities and differences between OLK, OLP, and OSCC to elucidate the relationship between oral cancer and OPMD. Our findings have significant implications for enhancing our understanding of oral disease identification and staging. Thirdly, our research on liposomes aligns with current trends in drug targeting vectors and OLP liposome therapy, providing a solid foundation and direction for clinical as well as experimental research endeavors. However, it is important to acknowledge certain limitations within our research. We employed a broader threshold of P < 5* 10 − 5 instead of the traditional threshold of 5* 10 − 8 when screening liposome SNPs to ensure an adequate number of SNPs were obtained. Therefore, further research is warranted to clarify the potential novel insights generated by our study. 6. Conclusion Our study has uncovered the associations between OSCC, OLP, and OLK with specific lipid components. This suggests that GPs and glycolipids offer protection against OSCC but pose a risk to OLK. Furthermore, this study aimed to elucidate the reasons for differential effects from the perspective of lipid composition structure in order to comprehend the complex lipid composition and investigate further the relationship between OMDs and lipid profiles. It underscores the significance of precision medicine and disease prevention. Glossary Oral mucosal disease (OMD) Oral potentially malignant disorders(OPMD) Oral squamous cell carcinoma (OSCC) Oral lichen planus (OLP) Oral leukoplakia (OLK) Mendelian Randomization (MR) Two-sample of MR Analysis (TSMR) Single nucleotide polymorphisms (SNPs) Instrumental variables (IVs) Inverse variance weighted (IVW) Linkage disequilibrium (LD) Glycerophospholipid(GP) Phosphatidylcholine (PC) Phosphatidylethanolamine (PE) Phosphatidylinositol (PI) Triacylglycerol (TG) Sterol ester (SE) Declarations Supplementary Materials: The following supporting information can be downloaded at: www.mdpi.com/xxx. Figure S1: IVW scatter diagram of the screened liposomes for OLK, Figure S2: Leave-one-out forest plots of the screened liposomes for OLK, Figure S3: IVW scatter diagram of the screened liposomes for OLP, Figure S4: Leave-one-out forest plots of the screened liposomes for OLP, Figure S5: IVW scatter diagram of the screened liposomes for OSCC, Figure S6: Leave-one-out forest plots of the screened liposomes for OSCC. Table S1:Heterogeneity of liposomes for OSCC, OLP and OLK. Funding This research was funded by Health and Family Planning Commission of Hunan Province, grant number 20201660, Health Commission of Hunan Province, grant number 202108031817, Natural Science Foundation of Hunan Province, grant number 2022JJ30872, Natural Science Foundation of Beijing Municipality, grant number 7222079. Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials Publicly available datasets were analyzed in this study. The data of lipidomics data can be found here: https://thl.fi/en/web/thl-biobank/forresearchers/sample-collections/generisk-study. The data of OSCC can be found here: https://gwas.mrcieu.ac.uk/. The data of OLK and OLP were predominantly sourced from the FinnGen r9, IEU OpenGWAS project (https://gwas.mrcieu.ac.uk/) Competing interests he authors declare that they have no competing interests Authors' contributions Kaixin Su: Criteria 1 contributed to conception and design & contributed to analysis and interpretation; Criteria 2 critically revised manuscript; Criteria 3 gave final approval; Criteria 4 agrees to be accountable for all aspects of work ensuring integrity and accuracy. Jia Mi: Criteria 1 contributed to conception and design & contributed to analysis and interpretation; Criteria 2 critically revised manuscript; Criteria 3 drafted manuscript & gave final approval; Criteria 4 agrees to be accountable for all aspects of work ensuring integrity and accuracy. Rifu Wang: Criteria 1 contributed to design; Criteria 2 critically revised manuscript; Criteria 3 gave final approval; Criteria 4 agrees to be accountable for all aspects of work ensuring integrity and accuracy. Jian Zhou: Criteria 1 contributed to conception & contributed to acquisition; Criteria 2 critically revised manuscript; Criteria 3 gave final approval; Criteria 4 agrees to be accountable for all aspects of work ensuring integrity and accuracy. Fei Yan: Criteria 1 contributed to conception & contributed to acquisition; Criteria 2 critically revised manuscript; Criteria 3 gave final approval; Criteria 4 agrees to be accountable for all aspects of work ensuring integrity and accuracy. Ousheng Liu: Criteria 1 contributed to conception & contributed to acquisition; Criteria 2 critically revised manuscript; Criteria 3 gave final approval; Criteria 4 agrees to be accountable for all aspects of work ensuring integrity and accuracy. 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Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44 , 512–525. 10.1093/ije/dyv080 (2015). Verbanck, M., Chen, C. Y., Neale, B. & Do, R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat. Genet. 50 , 693–698. 10.1038/s41588-018-0099-7 (2018). Wang, L. et al. Plasma lipid profiling and diagnostic biomarkers for oral squamous cell carcinoma. Oncotarget . 8 , 92324–92332. 10.18632/oncotarget.21289 (2017). Aniyan, K. Y., Guledgud, M. V. & Patil, K. Alterations of Serum Lipid Profile Patterns in Oral Lichen Planus Patients: A Case-Control Study. Contemp. Clin. Dent. 9 , S112–s121. 10.4103/ccd.ccd_111_18 (2018). Kusari, A., Ahluwalia, J. & Lichen Planus N Engl. J. Med. 379 , 567, doi: 10.1056/NEJMicm1802078 (2018). Mahesh, N. et al. Alterations of Plasma lipid profile patterns in oral leukoplakia. J. Int. Oral Health . 6 , 78–84 (2014). Zhang, M. et al. Current Trends of Targeted Drug Delivery for Oral Cancer Therapy. Front. Bioeng. Biotechnol. 8 , 618931. 10.3389/fbioe.2020.618931 (2020). Calori, I. R. & Tedesco, A. C. Lipid vesicles loading aluminum phthalocyanine chloride: Formulation properties and disaggregation upon intracellular delivery. J. Photochem. Photobiol., B . 160 , 240–247. https://doi.org/10.1016/j.jphotobiol.2016.03.050 (2016). Zhang, T., Chen, J., Zhang, Y., Shen, Q. & Pan, W. Characterization and evaluation of nanostructured lipid carrier as a vehicle for oral delivery of etoposide. Eur. J. Pharm. Sci. 43 , 174–179. https://doi.org/10.1016/j.ejps.2011.04.005 (2011). Tan, G. et al. A multifunctional MOF-based nanohybrid as injectable implant platform for drug synergistic oral cancer therapy. Chem. Eng. J. 390 , 124446. https://doi.org/10.1016/j.cej.2020.124446 (2020). Jacobs, R. L., Lingrell, S., Zhao, Y., Francis, G. A. & Vance, D. E. Hepatic CTP:phosphocholine cytidylyltransferase-alpha is a critical predictor of plasma high density lipoprotein and very low density lipoprotein. J. Biol. Chem. 283 , 2147–2155. 10.1074/jbc.M706628200 (2008). Stremmel, W. et al. Mucosal protection by phosphatidylcholine. Dig. Dis. 30 (Suppl 3), 85–91. 10.1159/000342729 (2012). Sohlenkamp, C., López-Lara, I. M. & Geiger, O. Biosynthesis of phosphatidylcholine in bacteria. Prog Lipid Res. 42 , 115–162. 10.1016/s0163-7827(02)00050-4 (2003). Nguyen, N. H., Chen, M., Chak, V. & Balu-Iyer, S. V. Biophysical Characterization of Tolerogenic Lipid-Based Nanoparticles Containing Phosphatidylcholine and Lysophosphatidylserine. J. Pharm. Sci. 111 , 2072–2082. 10.1016/j.xphs.2022.01.025 (2022). Chen, X. et al. Carboxylesterase 2 induces mitochondrial dysfunction via disrupting lipid homeostasis in oral squamous cell carcinoma. Mol. Metab. 65 , 101600. 10.1016/j.molmet.2022.101600 (2022). Bogdanov, M. & Dowhan, W. Lipid-assisted protein folding. J. Biol. Chem. 274 , 36827–36830. 10.1074/jbc.274.52.36827 (1999). Shinzawa-Itoh, K. et al. Structures and physiological roles of 13 integral lipids of bovine heart cytochrome c oxidase. Embo j. 26 , 1713–1725. 10.1038/sj.emboj.7601618 (2007). Kagan, V. E. et al. Oxidized arachidonic and adrenic PEs navigate cells to ferroptosis. Nat. Chem. Biol. 13 , 81–90. 10.1038/nchembio.2238 (2017). Li, S., Ghosh, C., Xing, Y. & Sun, Y. Phosphatidylinositol 4,5-bisphosphate in the Control of Membrane Trafficking. Int. J. Biol. Sci. 16 , 2761–2774. 10.7150/ijbs.49665 (2020). Holert, J., Brown, K., Hashimi, A., Eltis, L. D. & Mohn, W. W. Steryl Ester Formation and Accumulation in Steroid-Degrading Bacteria. Appl. Environ. Microbiol. 86 10.1128/aem.02353-19 (2020). Normén, L., Dutta, P., Lia, A. & Andersson, H. Soy sterol esters and beta-sitostanol ester as inhibitors of cholesterol absorption in human small bowel. Am. J. Clin. Nutr. 71 , 908–913. 10.1093/ajcn/71.4.908 (2000). de Jong, A., Plat, J., Lütjohann, D. & Mensink, R. P. Effects of long-term plant sterol or stanol ester consumption on lipid and lipoprotein metabolism in subjects on statin treatment. Br. J. Nutr. 100 , 937–941. 10.1017/s0007114508966113 (2008). Additional Declarations No competing interests reported. Supplementary Files Appendixinformation.docx STROBEMRchecklistfillable.docx TableS1heterogeneity.csv 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5310318","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":375683035,"identity":"d221edd6-0b7b-4282-88c1-f5211a0abe55","order_by":0,"name":"Kaixin Su","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Kaixin","middleName":"","lastName":"Su","suffix":""},{"id":375683036,"identity":"e597d8a2-ef1b-44b5-a346-cadcc40d4b9d","order_by":1,"name":"Jia Mi","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"","lastName":"Mi","suffix":""},{"id":375683037,"identity":"7dc0cdca-46bf-4060-8bff-8394e8627d92","order_by":2,"name":"Rifu Wang","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Rifu","middleName":"","lastName":"Wang","suffix":""},{"id":375683038,"identity":"6c93f26c-8b5b-4458-b87d-f47baa32d456","order_by":3,"name":"Jian Zhou","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhou","suffix":""},{"id":375683039,"identity":"21476e3b-24a9-4b47-a42e-1e8f877cc780","order_by":4,"name":"Fei Yan","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Yan","suffix":""},{"id":375683040,"identity":"ff95c595-2597-4efa-943a-07e153a035c7","order_by":5,"name":"Ousheng Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYBACPmYwdQCImQ8wwNn4ABtCC1sCkVoQyngMiNTCzmP4mOfPHTlz/jUfP/5sY5Dju5HA+LkAr8N4jI15254ZW854u1mat43BWPJGArP0DPxazKR5Gw4nbrhxdhszYxsDkJEAFCSkhefP4foNN848YwQ6rJ5ILWyHEwzO97AxAB2WYEBYC1ux4dy2w4YbbrAZS/OckzCceeZhszQ+Lfz8hzc+ePPnsLzB+cMPP/4os5HnO5588DM+LQggkQAmgZixgSgNQPsOEKlwFIyCUTAKRhwAAFubR4aGHCZUAAAAAElFTkSuQmCC","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Ousheng","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-10-22 09:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5310318/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5310318/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69912549,"identity":"cb004e1d-e2f5-4699-b7b0-f10a06716fa2","added_by":"auto","created_at":"2024-11-26 14:04:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9338964,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/0b0d2d725f51323e94e97726.png"},{"id":69911790,"identity":"d708478f-2151-4fa4-8e09-de5631644b20","added_by":"auto","created_at":"2024-11-26 13:56:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6975065,"visible":true,"origin":"","legend":"\u003cp\u003eA genetic randomization forest plot illustrating the impact of liposomes on OSCC. The odds ratio (OR), p-value, and 95% confidence interval (95%CI) were derived using the IVW method and presented in a forest plot. The p-value was adjusted using the FDR method. PC (O-16:2_18:0) is a specific glycerophospholipid molecule named according to its structure, with O-16:2 indicating a 16-carbon atom and 2 double bonds in the unsaturated fatty acid at the first position of the glycerol backbone, while 18:0 indicates an 18-carbon atom saturated fatty acid without double bonds connected to the glycerol framework. Both PC and PE adhere to the same nomenclature principle. TG(48:3) is a specific notation for expressing the molecular composition of a triglyceride. In this notation, \"48:3\" signifies that the total number of carbon atoms in the three fatty acid chains is 48, and the number \"3\" indicates the total number of double bonds present after combining these three fatty acid chains.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/c46a3d5530ad7e05ddb6eeec.png"},{"id":69911791,"identity":"b6053ff1-c5aa-4747-abb0-b97a5749b196","added_by":"auto","created_at":"2024-11-26 13:56:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":20665006,"visible":true,"origin":"","legend":"\u003cp\u003eA genetic random forest analysis was conducted to assess the impact of liposomes on OLP. The nomenclature for the steroids follows the same principles as illustrated in Figure 1. In contrast to the OR value of OSCC, lipidspheres of the same species exhibit a lack of clear consistency in risk.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/a11ceab89625786e69502edf.png"},{"id":69911787,"identity":"9a401ca0-c287-499d-99d5-600b4a0cd417","added_by":"auto","created_at":"2024-11-26 13:56:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":7909129,"visible":true,"origin":"","legend":"\u003cp\u003eA genetic random forest analysis of liposome effects on OLK indicates that both GPs and glycolipids are associated with increased risk.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/0efe938514a0dc2cc6e539ae.png"},{"id":80722398,"identity":"e6d6032d-f9a5-41fb-98b1-52a27f4ad22f","added_by":"auto","created_at":"2025-04-16 11:17:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":37537207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/0bb9dd65-549f-4e72-92dc-33bc83bc0b74.pdf"},{"id":69911789,"identity":"d285ec1f-a669-4bb0-b45d-5590d324d8b4","added_by":"auto","created_at":"2024-11-26 13:56:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":7171565,"visible":true,"origin":"","legend":"","description":"","filename":"Appendixinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/f29fff648e3eb593abc9d10a.docx"},{"id":69911784,"identity":"1e856d04-124f-49c4-bded-bd8695701c67","added_by":"auto","created_at":"2024-11-26 13:56:51","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":46167,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEMRchecklistfillable.docx","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/24a58f2319cc74d1da361534.docx"},{"id":69911786,"identity":"0a3a9cd1-b3eb-4149-a3c4-c7ed9420d718","added_by":"auto","created_at":"2024-11-26 13:56:51","extension":"csv","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":277407,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1heterogeneity.csv","url":"https://assets-eu.researchsquare.com/files/rs-5310318/v1/bf475fffbe0e6febfeb73df8.csv"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Mendelian Randomization Study for Liposome on oral potentially malignant disorders and oral squamous cell carcinoma","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eComplexity of oral mucosal disease (OMD) arises from the vulnerability of the oral cavity as a gateway to various risks and influencing factors. However, prevalence of OMDs is significant, characterized by a wide age range\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, similar lesion manifestations, and a high proportion of affected individuals. Furthermore, the malignant transformation potential of these diseases significantly impacts prognosis and quality of life. Therefore, it is crucial to investigate the etiology of OMDs, alleviate symptoms, and enhance prognosis. As a starting point, the significance of preventive measures cannot be overstated. Identifying and mitigating risk factors presents an opportunity for pioneering advancements in OMD research.\u003c/p\u003e \u003cp\u003eIn OMDs, oral squamous cell carcinoma (OSCC), oral lichen planus (OLP), and oral leukoplakia (OLK) exhibit the most complex etiology and the worst prognosis. OLP and OLK are considered precancerous conditions, with a potential for progression to OSCC\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, making them crucial for clinical prognosis and a focal point in current research. Currently, the existing research evidence is largely derived from in vitro experiments\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, epidemiological surveys\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, and randomized controlled trials (RCTs)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. According to traditional clinical treatment guidelines, OLP can be managed with medication and relaxation, while OLK can be addressed through laser treatment, local drug therapy, or surgical removal depending on its size. OSCC represents a predominant subtype of oral cancer, impacting functions such as mouth opening and eating while infiltrating adjacent tissues. Epidemiological investigations have consistently demonstrated the strong correlation between OSCC and low survival rates as well as high disability rates\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Treatment modalities encompass surgical radical resection, targeted therapy, radiation therapy, and chemotherapy. Nevertheless, the intricate anatomical structures in the head and neck region pose significant operative risks alongside substantial postoperative complications, thereby underscoring the paramount importance of addressing oral malignancies.\u003c/p\u003e \u003cp\u003eThe utilization of liposomes as a novel therapeutic approach is currently at the forefront of research in the field of OMDs. Application of liposomal steroids has been employed for the treatment of OLP simultaneously\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Liposomes refers to the comprehensive analysis of lipid metabolic products in blood plasma, and it also encompasses an artificial spherical vesicle structure composed of a pair of lipid molecules that serves as a crucial nanocarrier tool\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. By harnessing its ability to integrate with cell membranes as a vehicle for drug delivery such as OSCC\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, it facilitates direct conveyance of the drug into the intracellular space. This strategy overcomes challenges related to tissue metabolism-mediated absorption during oral and intravenous administration, resulting in improved therapeutic effectiveness and reduced systemic toxicity, as supported by extensive empirical research\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The effectiveness and risks of this treatment were not well-supported by strong evidence at the time of the study. Within the domain of oral diseases, there exists an imperative to curtail off-target toxicity while optimizing targeting precision; leveraging the distinctive attributes of liposomes becomes particularly pivotal in tailoring personalized treatment regimens to mitigate adverse reactions, aligning seamlessly with the tenets of precision medicine.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) is a powerful approach that uses genetic variants associated with exposure as instruments to examine the potential causal association between exposure and outcome\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. MR is less likely to be affected by confounding or reverse causality, as it mimics the randomized controlled trials by randomly assigning genetic variants at the time of conception\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe urgent need to study liposomes lies in understanding their causal impact on OMDs. Hence, this research aims to establish a clear correlation between liposomes and OSCC, OLP, and OLK through strong evidence, advancing early detection and treatment of oral diseases using liposomal interventions. Thereupon, our study plans to conduct a MR analysis using GWAS data on 179 lipid types from 7174 Finnish individuals, as reported in Nature Communications on October 23, 2023. The GWAS data for this analysis was obtained from the FinnGen and GWAS catalog Database, including 1223 OSCC cases and 2928 controls, 5791 OLP cases and 371486 controls, as well as 2598 OLK cases and 409583 controls, aiming to unveil the association between liposomes and OMDs.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources for the exprosure\u003c/h2\u003e \u003cp\u003eThe summary statistics for lipid profiles were derived from a genome-wide association study (GWAS) catalog, specifically from entries GCST90277-238 to GCST90277-416. This study analyzed data from 7,174 unrelated Finnish individuals who were part of the GeneRISK cohort. The research tested 179 lipid species, categorized into 13 classes and 4 broader categories, utilizing single nucleotide polymorphisms (SNPs) for their analysis\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Detailed data and additional resources can be accessed via the GWAS catalog at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/GWAS/\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/GWAS/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The GWAS data is summarized 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\u003eSummary of the GWAS included in this Mendelian randomization study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposures/outcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsortium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample sizes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlasma lipidome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGWAS catalog\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral cavity cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGWAS catalog\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral lichen planus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisteys R9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e377277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral leukoplakia and related diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRistesys R10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e412181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2023\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=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data sources for the outcome\u003c/h2\u003e \u003cp\u003eThe GWAS data for this analysis was obtained from the FinnGen and GWAS catalog Database. This included 1223 cases and 2928 controls for OSCC, 5791 cases and 371486 controls for OLP, and 2598 cases and 409583 controls for OLK and related diseases. The GWAS data is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Selection of instrumental variables\u003c/h2\u003e \u003cp\u003eIn this MR study, we employed SNPs associated with blood liposomes that reached a genome-wide significance level (p\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10⁻⁵) from previous GWASs\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. To ensure the independence of each instrumental variable (IV) and to mitigate the influence of linkage disequilibrium (LD), SNPs within a 10,000 kb window were clumped, applying an r\u0026sup2; threshold of \u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003cp\u003eTo minimize the influence of weak instrument bias on the estimation of association effects, we evaluated the strength of the instruments using an F-statistic threshold greater than 10. The F-statistic was computed using the formula: F\u0026thinsp;=\u0026thinsp;R2(n\u0026thinsp;\u0026minus;\u0026thinsp;2)/1\u0026thinsp;\u0026minus;\u0026thinsp;R\u003csup\u003e215\u003c/sup\u003e, where n is the sample size. The R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e value was derived from the minor allele frequency (MAF) and effect estimates (β) using the formula: R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2\u0026times;MAF \u0026times; (1-MAF)\u0026times;β\u003csup\u003e2\u003c/sup\u003e. An F-statistic greater than 10 indicates that the results are not biased by weak IVs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Two-sample of MR Analysis(TSMR)\u003c/h2\u003e \u003cp\u003eTo investigate the causal relationship between blood liposomes and OMDs, various statistical methods were employed. These included the inverse variance weighted (IVW) method\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, the weighted mode method\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, the weighted median (WM) method\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, and the Mendelian randomization-Egger (MR-Egger) method\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The IVW method is widely recognized and most effective when all IVs satisfy the core assumptions of MR, such as the absence of horizontal pleiotropy and unbiased effect estimates. The WM method, which calculates the median of all IV effect estimates, is particularly advantageous when some IVs deviate from MR assumptions, including the presence of horizontal pleiotropy. The MR-Egger method not only estimates causal effects but also identifies and corrects for horizontal pleiotropy, making it valuable when horizontal pleiotropy is suspected. Associations were considered significant if the IVW method yielded a p-value less than 0.05 and the direction of estimates from the other MR methods was consistent with that of the IVW method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.5 Sensitivity analysis\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eSeveral tests were utilized to ensure the robustness of our findings, including the heterogeneity test, pleiotropy test, and leave-one-out sensitivity test in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. To assess overall pleiotropy in the IVW MR findings, Cochrane\u0026rsquo;s Q test was applied, with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating the presence of heterogeneity. The average horizontal pleiotropy of the IVs in MR-Egger regression was determined using the intercept term and the assessment of funnel plot asymmetry. A significance level below p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered indicative of heterogeneity. Subsequently, a leave-one-out analysis was performed to evaluate whether significant changes in causal effects occurred before and after the removal of outliers. Additionally, the MR-PRESSO method was employed to detect and correct for pleiotropy by identifying and excluding potential outliers\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. These analyses were conducted using \u003cb\u003ethe TwoSampleMR (version 0.6.0)\u003c/b\u003e, \u003cb\u003eMR (version 0.8.0), and MRPRESSO package (1.0) in R Software 4.3.3 (\u003c/b\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.R-project.org\u003c/span\u003e\u003cspan address=\"https://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e)\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Causal effects of lipidomes and OSCC\u003c/h2\u003e \u003cp\u003eAlthough lipid components can be easily extracted from plasma, numerous studies have investigated their relationship with OSCC. However, it remains challenging to directly establish a linear correlation between lipid components and OSCC. Various statistical methods will be employed in two-sample MR analysis to screen liposomes associated with one-to-one outcomes in OSCC(nsnp\u0026thinsp;=\u0026thinsp;9\u0026thinsp;~\u0026thinsp;23). This study aims to explore the association between liposomes and OSCC. The causal effect of liposomes on OSCC risk was assessed through our MR analysis, revealing that glycerol phospholipid and glycerolipids may influence the risk of OSCC and are considered protective factors in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among them, glycerophospholipids(GPs) include phosphatidylcholine (PC, O-16:2_18:0, p-val\u0026thinsp;=\u0026thinsp;0.015), phosphatidylethanolamine (PE, O-18:2_20:4, p-val\u0026thinsp;=\u0026thinsp;0.029), and phosphatidylinositol (PI, 18:1_20:4, p-val\u0026thinsp;=\u0026thinsp;0.028). Glycerolipids compound with triacylglycerol (TG, 48:3, p-val\u0026thinsp;=\u0026thinsp;0.035), TG(54:4, p-val\u0026thinsp;=\u0026thinsp;0.034) and TG(56:5, p-val\u0026thinsp;=\u0026thinsp;0.033). Recent studies have indicated that the composition of plasma lipids may serve as a valuable tool for guiding clinical staging and facilitating early diagnosis\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The six specific liposomes containing protective factors identified in this study could potentially be developed as a method for early diagnosis of OSCC. Triacylglycerol levels were observed to be lower in the plasma of OSCC patients compared to both the oral precancerous lesion group and the normal group. The study revealed that the inverse relationship between OSCC and triglycerides offers an explanation for this clinical phenomenon. In line with the findings regarding protective factors(or =\u0026thinsp;0.45 to 0.98, 95%CI).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Causal effects of lipidomes and OLP\u003c/h2\u003e \u003cp\u003eThe OLP case-control study revealed a statistically significant elevation in TG levels within the case group compared to the control group\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Nevertheless, there is insufficient clear evidence to establish a causal relationship between TGs and OLP. Our study has revealed that the identical liposome structure may lead to inconsistent outcomes in OLP. Through a two-sample of MR analysis to assess the causal impact of liposomes on OLP, the findings indicate that steroids, GPs, and glycolipids may influence the likelihood of developing OLP in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. PE (O-16:1_20:4,p-val\u0026thinsp;=\u0026thinsp;0.037), PC (17:0_20:4, p-val\u0026thinsp;=\u0026thinsp;0.002), PC (18:0_20:5, p-val\u0026thinsp;=\u0026thinsp;0.012), PC (16:1_20:4, p-val\u0026thinsp;=\u0026thinsp;0.027), PC (18:2_20:4, p-val\u0026thinsp;=\u0026thinsp;0.038), PC (20:4_0:0, p-val\u0026thinsp;=\u0026thinsp;0.005),PC (16:0_22:4, p-val\u0026thinsp;=\u0026thinsp;0.036) and PC (16:0_20:4, p-val\u0026thinsp;=\u0026thinsp;0.041) are the protective factors of GPs(or =\u0026thinsp;0.84 to 1.00, 95%CI). Sterol ester (SE, 27:1/18:0, p-val\u0026thinsp;=\u0026thinsp;0.020) and SE (27:1/20:5, p-val\u0026thinsp;=\u0026thinsp;0.008) are the protective factors of steroid(or =\u0026thinsp;0.82 to 0.98, 95%CI). Glycerolipids with TG(46:1, p-val\u0026thinsp;=\u0026thinsp;0.044), TG(54:3, p-val\u0026thinsp;=\u0026thinsp;0.025) and TG(56:3, p-val\u0026thinsp;=\u0026thinsp;0.046) as risk factors(or =\u0026thinsp;1.00 to 1.20, 95%CI). Only a SE(27:1/18:2, p-val\u0026thinsp;=\u0026thinsp;0.003) is the risk factor of steroid(or =\u0026thinsp;1.04 to 1.22, 95%CI). OLP patients typically undergo topical steroid therapy\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. This study identified two protective factors of steroids that may provide evidence for this treatment approach. However, there is also a risk factor associated with steroids, so the use of steroids as a treatment agent should be avoided when SE (27:1/18:2) is present.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Causal effects of lipidomes and OLK\u003c/h2\u003e \u003cp\u003eOLK is indicative of a precancerous lesion associated with OSCC, and their liposome composition is similar; however, their effects exhibit an opposite trend. In a small-scale comparative experiment on OLK plasma lipid components in India, no statistically significant differences were observed in TG, thereby addressing a gap in current research\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.After conducting a two-sample of MR analysis to assess the causal impact of liposomes on OLK(nspn\u0026thinsp;=\u0026thinsp;18\u0026thinsp;~\u0026thinsp;29), the findings suggest that GPs and glycolipids may influence the risk of OLK and are considered as potential risk factors. PC (O-18:2_18:2, p-val\u0026thinsp;=\u0026thinsp;0.012), PE (18:0_18:2, p-val\u0026thinsp;=\u0026thinsp;0.021), PI (18:1_18:1, p-val\u0026thinsp;=\u0026thinsp;0.018), PI (18:1_18:2, p-val\u0026thinsp;=\u0026thinsp;0.013) were among the four liposomes screened for glycerophospholipid risk factors(or =\u0026thinsp;1.03 to 1.52, 95%CI). Glycerolipids consist with TG(50:5, p-val\u0026thinsp;=\u0026thinsp;0.023), TG(52:2, p-val\u0026thinsp;=\u0026thinsp;0.038) and TG(58:8, p-val\u0026thinsp;=\u0026thinsp;0.047) as risk factors(or =\u0026thinsp;1.00 to 1.35, 95%CI) in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Sensitivity analysis\u003c/h2\u003e \u003cp\u003eA comprehensive sensitivity analysis was performed to verify the robustness of our findings. Cochran\u0026rsquo;s Q statistic was utilized to evaluate heterogeneity for both the IVW and MR-Egger methods, with Q_pval values exceeding 0.05, indicating no heterogeneity and thus supporting the application of fixed-effect models for IVW(Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). This conclusion was further corroborated by the assessments using both funnel and forest plots, which also suggested the absence of heterogeneity. Outlier detection conducted via the MR-PRESSO method did not identify any outliers, as indicated by p-values greater than 0.05, reinforcing the validity of single-outcome conclusions for OSCC, OLP, and OLK within this liposome cohort. Additionally, the leave-one-out analysis demonstrated that no individual SNP had a significant impact on the results. Consequently, this Mendelian randomization analysis is considered reliable and robust.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study is the first to explore the impact of different liposome populations on the occurrence of OSCC, OLP, and OLK, revealing intricate causal relationships between various liposome structures and OMDs. Specifically, PC, PE, and PI demonstrate protective effects against OSCC and risk effects on OLK. The lipid composition of OLP is complex, with varying chain lengths and double bond numbers of steroids and GPs associated with different risks and protective factors. In OSCC, glycolipid PC, which is linked to an increased risk of OLK, instead correlates with a protective factor. This correlation may require further research.\u003c/p\u003e \u003cp\u003eLiposomes are considered to be one of the most promising drug delivery tools due to their functional characteristics, which closely resemble biological membranes and can be absorbed by the human body through oral formulations. However, this study indicates that certain types of liposomes may present a risk for OMDs. It is suggested that not all liposomes are suitable for use as drug-release vehicles in order to mitigate toxicity. In OSCC, the focus of targeted therapy for anti-cancer drugs has also shifted towards nanotechnology research. Ideal new treatment strategies involve targeted drug delivery and sustained release systems\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In addition to liposomes\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, nanoparticles, nanoliposomes\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, hydrogels \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, exosomes, and other nanomaterials are under study.\u003c/p\u003e \u003cp\u003eGP constitute the primary constituents of biological membranes. PC (O-16:2_18:0) serves as a protective lipid for OSCC. PC serves as the primary phospholipid constituent in eukaryotic membranes, and it can be biosynthesized via either the methylation pathway or the CDP-choline pathway\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Meanwhile, PC is thought to act as a protective barrier against bacterial invasion in the intestines\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Given the comparable levels present in bacterial membranes, it is widely accepted that the enzymatic methylation of PE through the methylation pathway represents the sole biochemical route for synthesizing PC in bacteria\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Under these conditions, PC has been thoroughly researched in the area of drug delivery. Oral administration of lipid nanoparticles containing PC and Lyso-PS can transform immunogenic substances into tolerogenic ones, thereby inducing immune tolerance to multiple antigens and reducing the occurrence of immune adverse reactions\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Various PC structures are associated with different levels of risk for specific diseases. The following PC species were identified as protective factors against OLP: PC(17:0_20:4), PC(18:0_20:5), PC(16:1_20:4), PC(18:2_20:4), PC(20:4_0:0), PC(16:0_22:4) and PC(16:0_20:4). Nonetheless, PC (O-16:2_18:0) exhibits significant potential as a drug delivery vehicle for OSCC. For instance, PC (O-18:2_18:2) exhibited a positive correlation with the risk of OLK. Similarly, PC(14:0_18:2), PC(18:0_20:2), PC(18:2_18:2), PC(O-18:1_18:2), and PC(O-18:2_18:2) demonstrated a positive correlation with the risk of OLP. This finding may indicate an imbalance in lipid metabolism in OLP. Therefore, the distinct and multifaceted impact of OLP on lipids can serve as a supplementary clinical diagnostic criterion, and exploring non-invasive methods for extracting lipids may replace invasive biopsies as the gold standard for diagnosis.\u003c/p\u003e \u003cp\u003ePE (O-18:2_20:4) was identified as a protective factor against OSCC. PE (O-16:1_20:4) also serves as a protective factor for OLP. As a partner of PC, PE constitutes over 50% of the total phospholipid species present in eukaryotic membranes. It serves as a critical mediator in the modulation of the impact of reactive oxygen species (ROS) and their derivatives, active aldehydes (RA), on membrane proteins. However, the pro-apoptotic mechanism of ROS is associated with the inhibition of OSCC. Studies have demonstrated that lipid homeostasis and ROS activation mitigate lipotoxicity by down-regulating CES2, thereby impeding OSCC progression\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In terms of risk, PE facilitates the conformational changes of cofilin proteins\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, stimulates oxidative phosphorylation\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, contributes to cell apoptosis\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, and is involved in ferroptosis pathways leading to cell death. This may potentially offer insights into the potential risk factors of PE(18:2_0:0) and PE(O-16:1_18:2) for OLP, while indicating that PE(18:0_18:2) could be a risk factor for OLK.\u003c/p\u003e \u003cp\u003ePI is a membrane lipid that modulates the dynamics of cellular membranes\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. PI(18:1_20:4) exhibits a protective effect against OSCC, while PI(18:1_18:1) and PI (18:1_18:2) are identified as risk factors for OLK. Enhanced intimate signal transduction may result in the inhibition of immune evasion in OSCC. While no studies have specifically focused on PI(18:1_18:1) and PI(18:1_18:2), the potential targeting effects of OLK on these molecules may be inferred from related signal inhibition.\u003c/p\u003e \u003cp\u003eTG found in GPs serve as the primary mechanism for energy storage in the human body. The TG index is linked to various irregularities in plasma lipid metabolism. TG (54:4), TG (56:5), TG (48:3) are identified as protective factors for OSCC, while TG (56:3), TG (54:3), and TG (46:1) are identified as risk factors for OLP. Despite variations in their specific structures, they demonstrate similar lipid droplet classifications, indicating a high propensity for cancer in both OLK and OLP. Nevertheless, studies have examined lipidomics in OSCC patients and OPMD, revealing no significant differences in TG concentration among the control group, OSCC, and OPMD. This may be attributed to variations in dietary habits and genetic differences between Asian and European populations.\u003c/p\u003e \u003cp\u003eSE serve as crucial storage compounds in numerous eukaryotic organisms and frequently constitute a significant component of lipid droplets within cells\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. SE(27:1/18:0) and SE(27:1/20:5) have been identified as protective factors for OLP, whereas SE (27:1/18:2) are considered to be risk factors for OLP. The current literature on this topic is limited, thus presenting an opportunity for further research to complement existing areas of study. SE is extensively researched in the field of plant-relatedness and can be assimilated and stored by the human body\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, such as margarine\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, soybean oil, etc. The oral cavity functions as the entry point for food consumption, and ingested food initially passes through the mouth into the body. Therefore, it is crucial to carefully consider dietary structure in order to prevent the development of OLP, as this article underscores the dual significance of SE in promoting OLP.\u003c/p\u003e"},{"header":"5. Advantages and Limitations","content":" \u003cp\u003eOur study has several notable strengths. Firstly, we are pioneers in thoroughly investigating the correlation between lipids and OMDs using the TSMR method. This study involves comprehensive data collection while minimizing potential confounding factors. Secondly, we conducted parallel comparison analyses to examine the similarities and differences between OLK, OLP, and OSCC to elucidate the relationship between oral cancer and OPMD. Our findings have significant implications for enhancing our understanding of oral disease identification and staging. Thirdly, our research on liposomes aligns with current trends in drug targeting vectors and OLP liposome therapy, providing a solid foundation and direction for clinical as well as experimental research endeavors. However, it is important to acknowledge certain limitations within our research. We employed a broader threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;5* 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e instead of the traditional threshold of 5* 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e when screening liposome SNPs to ensure an adequate number of SNPs were obtained. Therefore, further research is warranted to clarify the potential novel insights generated by our study.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eOur study has uncovered the associations between OSCC, OLP, and OLK with specific lipid components. This suggests that GPs and glycolipids offer protection against OSCC but pose a risk to OLK. Furthermore, this study aimed to elucidate the reasons for differential effects from the perspective of lipid composition structure in order to comprehend the complex lipid composition and investigate further the relationship between OMDs and lipid profiles. It underscores the significance of precision medicine and disease prevention.\u003c/p\u003e"},{"header":"Glossary","content":"\u003cp\u003eOral mucosal disease (OMD)\u003c/p\u003e\n\u003cp\u003eOral potentially malignant disorders(OPMD)\u003c/p\u003e\n\u003cp\u003eOral squamous cell carcinoma (OSCC)\u003c/p\u003e\n\u003cp\u003eOral\u0026nbsp;lichen planus (OLP)\u003c/p\u003e\n\u003cp\u003eOral\u0026nbsp;leukoplakia (OLK)\u003c/p\u003e\n\u003cp\u003eMendelian Randomization (MR)\u003c/p\u003e\n\u003cp\u003eTwo-sample of MR Analysis (TSMR)\u003c/p\u003e\n\u003cp\u003eSingle nucleotide polymorphisms (SNPs)\u003c/p\u003e\n\u003cp\u003eInstrumental variables (IVs)\u003c/p\u003e\n\u003cp\u003eInverse variance weighted (IVW)\u003c/p\u003e\n\u003cp\u003eLinkage disequilibrium (LD)\u003c/p\u003e\n\u003cp\u003eGlycerophospholipid(GP)\u003c/p\u003e\n\u003cp\u003ePhosphatidylcholine (PC)\u003c/p\u003e\n\u003cp\u003ePhosphatidylethanolamine (PE)\u003c/p\u003e\n\u003cp\u003ePhosphatidylinositol (PI)\u003c/p\u003e\n\u003cp\u003eTriacylglycerol (TG)\u003c/p\u003e\n\u003cp\u003eSterol ester (SE)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following supporting information can be downloaded at: www.mdpi.com/xxx. Figure S1: IVW scatter diagram of the screened liposomes for OLK, Figure S2: Leave-one-out forest plots of the screened liposomes for OLK, Figure S3: IVW scatter diagram of the screened liposomes for OLP, Figure S4: Leave-one-out forest plots of the screened liposomes for OLP, Figure S5: IVW scatter diagram of the screened liposomes for OSCC, Figure S6: Leave-one-out forest plots of the screened liposomes for OSCC. Table S1:Heterogeneity of liposomes for OSCC, OLP and OLK.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Health and Family Planning Commission of Hunan Province, grant number 20201660, Health Commission of Hunan Province, grant number 202108031817, Natural Science Foundation of Hunan Province, grant number 2022JJ30872, Natural Science Foundation of Beijing Municipality, grant number 7222079.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. The data of lipidomics data can be found here: https://thl.fi/en/web/thl-biobank/forresearchers/sample-collections/generisk-study. The data of OSCC can be found here: https://gwas.mrcieu.ac.uk/. The data of OLK and OLP were predominantly sourced from the FinnGen r9, IEU OpenGWAS project\u003c/p\u003e\n\u003cp\u003e(https://gwas.mrcieu.ac.uk/)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ehe authors declare that they have no competing interests\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKaixin Su:\u003c/strong\u003e \u003cstrong\u003eCriteria 1\u0026nbsp;\u003c/strong\u003econtributed to conception and design \u0026amp; contributed to analysis and interpretation;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCriteria 2\u003c/strong\u003e critically revised manuscript; \u003cstrong\u003eCriteria 3\u0026nbsp;\u003c/strong\u003egave final approval; \u003cstrong\u003eCriteria 4\u0026nbsp;\u003c/strong\u003eagrees to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eJia Mi: Criteria 1\u0026nbsp;\u003c/strong\u003econtributed to conception and design \u0026amp; contributed to analysis and interpretation;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCriteria 2\u003c/strong\u003e critically revised manuscript; \u003cstrong\u003eCriteria 3\u0026nbsp;\u003c/strong\u003edrafted manuscript \u0026amp; gave final approval; \u003cstrong\u003eCriteria 4\u0026nbsp;\u003c/strong\u003eagrees to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRifu Wang:\u003c/strong\u003e \u003cstrong\u003eCriteria 1\u0026nbsp;\u003c/strong\u003econtributed to design;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCriteria 2\u003c/strong\u003e critically revised manuscript; \u003cstrong\u003eCriteria 3\u0026nbsp;\u003c/strong\u003egave final approval; \u003cstrong\u003eCriteria 4\u0026nbsp;\u003c/strong\u003eagrees to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJian Zhou:\u003c/strong\u003e \u003cstrong\u003eCriteria 1\u0026nbsp;\u003c/strong\u003econtributed to conception \u0026amp; contributed to acquisition;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCriteria 2\u003c/strong\u003e critically revised manuscript; \u003cstrong\u003eCriteria 3\u0026nbsp;\u003c/strong\u003egave final approval; \u003cstrong\u003eCriteria 4\u0026nbsp;\u003c/strong\u003eagrees to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFei Yan: Criteria 1\u0026nbsp;\u003c/strong\u003econtributed to conception \u0026amp; contributed to acquisition;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCriteria 2\u003c/strong\u003e critically revised manuscript; \u003cstrong\u003eCriteria 3\u0026nbsp;\u003c/strong\u003egave final approval; \u003cstrong\u003eCriteria 4\u0026nbsp;\u003c/strong\u003eagrees to be accountable for all aspects of work ensuring integrity and accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOusheng Liu: Criteria 1\u0026nbsp;\u003c/strong\u003econtributed to conception \u0026amp; contributed to acquisition;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCriteria 2\u003c/strong\u003e critically revised manuscript; \u003cstrong\u003eCriteria 3\u0026nbsp;\u003c/strong\u003egave final approval; \u003cstrong\u003eCriteria 4\u0026nbsp;\u003c/strong\u003eagrees to be accountable for all aspects of work ensuring integrity and accuracy.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their gratitude to the other participants in our group for their invaluable assistance throughout this study.\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that the research was conducted without any commercial or financial relationships that could be perceived as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmadori, F., Bardellini, E., Conti, G. \u0026amp; Majorana, A. 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Nutr.\u003c/em\u003e \u003cb\u003e100\u003c/b\u003e, 937\u0026ndash;941. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/s0007114508966113\u003c/span\u003e\u003cspan address=\"10.1017/s0007114508966113\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"OLP, OLK, OSCC, liposome, MR analysis","lastPublishedDoi":"10.21203/rs.3.rs-5310318/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5310318/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction and aims: \u003c/strong\u003eIn oral mucosal disease (OMD), oral squamous cell carcinoma(OSCC) and oral potentially malignant disorders(OPMD), such as oral lichen planus (OLP) and oral leukoplakia (OLK), have the most complex etiology and worst prognosis among all OMDs. The use of liposomes shows great potential in diagnosing, treating, and preventing the mentioned diseases. Using mendelian randomization to explore the correlation between liposomes and OPMD as well as oral cancer, aiming to enhance the potential impact of liposomal genetic variations on early detection and treatment of oral diseases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This Mendelian randomization study utilized data from 7174 GWAS participants from GeneRISK, Finland, examining 179 lipid species. SNPs associated with OSCC, OLP, and OLK were analyzed using the inverse variance weighted (IVW) method, weighted mode, weighted median (WM), and MR-Egger methods. Sensitivity analysis was conducted with Cochrane's Q test and MR-PRESSO.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e IVW analysis identified six liposome types associated with OSCC, 21 with OLP, and seven with OLK (p\u0026lt;0.05). Notable protective factors for OSCC included specific triacylglycerol, while OLK-related liposomes presented opposite risk factors. OLP-associated lipids included three risk-associated triglycerides. No heterogeneity or horizontal pleiotropy was detected, confirming the robustness of the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe study highlighted similarities in the metabolic components of the blood lipidome among OSCC, OLP, and OLK, though liposomes with identical structures exhibited differing effects on disease pathogenesis.The study revealed the protective and risk effects of liposomes on OLP, OLK, and OSCC, highlighting their dual nature. Related lipidomics support non-invasive disease identification in OPMD conditions, offering a potential strategy for targeted prevention and drug treatment.\u003c/p\u003e","manuscriptTitle":"A Mendelian Randomization Study for Liposome on oral potentially malignant disorders and oral squamous cell carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-26 13:56:46","doi":"10.21203/rs.3.rs-5310318/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":"90855ed3-6f4d-49fe-93b6-f3a1af2be1e9","owner":[],"postedDate":"November 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39996346,"name":"Biological sciences/Biochemistry/Lipidomics"},{"id":39996347,"name":"Biological sciences/Biochemistry/Lipids"}],"tags":[],"updatedAt":"2025-04-16T11:08:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-26 13:56:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5310318","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5310318","identity":"rs-5310318","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}