Causal relationship between gut microbiota and psoriasis: a two-sample Mendelian randomization study

Causal relationship between gut microbiota and psoriasis: a two-sample 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 relationship between gut microbiota and psoriasis: a two-sample Mendelian randomization study Chongxiang Gao, Minghui Liu, Jian Ding This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3887794/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 Accumulating evidence from observational and experimental studies suggests a potential association between the gut microbiota (GM) and psoriasis, yet it remains obscure whether this connection is causal in nature. Methods By performing a two-sample Mendelian Randomization (MR) analysis of genome-wide association study (GWAS) summary statistics from the MiBioGen and FinnGen consortium, the causal association between GM and psoriasis was investigated, using methods of inverse variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode. Results The genus Eubacterium fissicatena group (odds ratio [OR]: 1.22, 95% confidential interval [CI], 1.09–1.36, P < 0.001) and genus Lactococcus (OR: 1.12, 95% CI: 1.00-1.25, P = 0.046) were identified as risk factors for psoriasis, while the genus Butyricicoccus (OR: 0.80, 95% CI: 0.64-1.00, P = 0.049), genus Faecalibacterium (OR: 0.84, 95% CI: 0.71–0.99, P = 0.035), genus Prevotella9 (OR: 0.88, 95% CI: 0.78–0.99, P = 0.040) exhibited protective effects against psoriasis. The sensitivity analysis did not provide any indications of pleiotropy or heterogeneity. Conclusions Our two-sample MR analysis provides novel evidence supporting the causality between GM and psoriasis. Comprehensive and multi-omics methods are warranted to unravel the contribution of GM to psoriasis pathogenesis, as well as its potential therapeutic implications. gut microbiota psoriasis gut-skin axis Mendelian randomization causal relationship Figures Figure 1 Introduction Psoriasis is a common immune-mediated, chronic, noninfectious, systemic inflammatory disease with no clear cause or cure ( 1 ). It can manifest in multiple phenotypes, the most common of which is plaque psoriasis, also known as psoriasis vulgaris ( 2 ). As a serious global problem, psoriasis affects all countries and all age groups, with prevalence ranging from 0.09% ( 3 ) to 11.43% ( 4 ), affecting at least 100 million people on a global scale. Psoriasis is a complex disease with a multifactorial pathophysiology, involving intricate interactions among genetic, immune, and environmental factors. There are many internal and external triggers, including trauma, infection, drugs, physical and chemical damage and stress ( 5 ). The sustained chronic inflammation caused by psoriasis is featured with pro-inflammatory cytokines, epidermal hyperplasia, and inflammatory infiltration composed of immune cells ( 6 ). A number of comorbidities is connected to psoriasis, including but not limited to obesity, cardiovascular disease, arthritis, inflammatory bowel disease (IBD), and depression. These conditions significantly worsen the quality of life for patients and impose substantial physical, emotional, and social burdens ( 2 ). The gut microbiota (GM) is known to have a significant impact on several aspects of host physiology, including regulation of energy metabolism and immune response, maintenance of intestinal epithelial integrity, and facilitation of neurobehavioral development ( 7 ). The impact of GM on overall bodily health may be both advantageous and disadvantageous, as evidenced by their interactions with the host organism. Revolutionary advancements have been achieved in the exploration of the human microbiome, with techniques such as 16S rDNA sequencing technology being extensively utilized for investigating GM ( 8 ). Mounting evidence shows a significant correlation between GM and psoriasis occurrence and development. Dysbiosis, defined as changes in the diversity and composition of GM, has been reported to be a possible cause for psoriasis recurrence ( 9 – 11 ). Preclinical studies have found that oral broad-spectrum antibiotic treatment can alleviate skin inflammation by downregulating the Th17 immune response in mice with imiquimod-induced psoriasis ( 12 ), providing evidence for the involvement of GM in psoriasis pathogenesis. Clinical research has demonstrated that antibiotic therapy ( 13 ), probiotic modulation of GM ( 14 ), or fecal microbial transplantation can induce remission in psoriatic skin lesions ( 15 ). However, the causal link between psoriasis and GM remains inconclusive as a result of inconsistent findings reported in prior research ( 7 ). Hence, it is imperative to do more research in order to examine the causative connection between GM and psoriasis, as well as to clarify the precise role of GM in the initiation of psoriasis. Mendelian randomization (MR) analysis is a commonly employed epidemiological method for examining potential causal relationships between exposures and outcomes ( 16 ). Two-sample Mendelian randomization (TSMR) analysis involves the utilization of single nucleotide polymorphisms (SNPs) obtained from separate genome-wide association studies (GWASs) as instrumental variables (IVs). This approach efficiently addresses the influence of confounding factors and reverse causation ( 17 ). In this study, we conducted a TSMR analysis with GWAS summary statistics retrieved from the MiBioGen and FinnGen consortium to evaluate the causation between GM composition and psoriasis. Methods Exposure data SNPs that served as IVs originated from the MiBioGen study, which is the biggest multi-ethnic genome-wide meta-analysis of GM. The GWAS dataset comprises 18,340 samples of 16S rRNA gene sequencing data obtained from 24 distinct cohorts from various populations. This dataset encompasses a comprehensive collection of 211 GM taxa, including 131 genera, 35 families, 20 orders, 16 classes, and 9 phyla ( 18 ). Outcome data The summary statistics pertaining to psoriasis were derived from the FinnGen consortium release 7. This dataset had a total of 6,995 individuals diagnosed with psoriasis and 299,128 individuals serving as controls. Covariate adjustments were performed to account for age, sex, genetic main components, and genotyping batch effects. Cases of psoriasis were recognized based on the diagnostic code L40 in the International Classification of Diseases, 10th Revision . Instrumental variable selection SNPs significantly related to GM were filtered at a genome-wide significance threshold (P < 1×10 –5 ) and chosen as potential IVs on the basis of existing MR research on GM ( 19 , 20 ). To ensure statistical independence, we conducted a linkage disequilibrium analysis with R 2 < 0.001 and a clumping distance of 10,000 kb using data from the European-based 1000 Genome Projects. Palindromic SNPs were excluded to guarantee the accuracy of strand orientation and allele coding. The F-statistic was computed to assess the presence of weak instrumental bias (F = beta 2 /se 2 ). A value of F greater than 10 was seen as an indication of the absence of substantial evidence supporting weak instrumental bias ( 20 ). All included IVs were inspected by PhenoScanner ( http://www.phenoscanner.medschl.cam.ac.uk/ ) to subsequently excluding any SNPs that exhibited associations with confounding factors. Statistical analysis Multiple MR methods were employed to assess the probable causative relationship between GM and psoriasis. These methods consisted of the inverse-variance weighted (IVW), MR-Egger regression, weighted mode, weighted median, and simple mode. The IVW method was predominantly utilized in order to establish causality by making the assumption of a shared causal influence of all IVs on the outcome through exposure. The MR-Egger regression method is used in the presence of horizontal pleiotropy, which arises when IVs impact the outcome through pathways unrelated to the exposure ( 21 ). The MR-PRESSO analysis was applied to identify the existence of horizontal pleiotropy as well. After removal of outliers, the causal effect was recalculated using the remaining IVs, which provides a more precise and robust estimation ( 22 ). Cochrane's Q test was carried out to evaluate heterogeneity among effect estimates of SNPs. The results of the MR analysis were visualized by scatter plots and funnel plots to facilitate data interpretation and identify potential outliers. To mitigate the potential influence of horizontal pleiotropy caused by a single SNP, we conducted a leave-one-out analysis wherein each SNP was sequentially removed. The packages Two-Sample-MR and MR-PRESSO in R version 4.1.3 are utilized for every statistical analysis. Results SNPs selection We identified 102, 178, 215, 375 and 1381 SNPs at the phylum, class, order, family and genus taxonomic levels respectively with a significance threshold of P 10. MR analyses The findings from the IVW analysis revealed significant associations between psoriasis and several genera, namely the genus Butyricicoccus , genus Eubacterium fissicatena group , genus Faecalibacterium , genus Lactococcus , genus Prevotella9 . The genus Eubacterium fissicatena group (OR: 1.22, 95% CI: 1.09–1.36, P < 0.001) and genus Lactococcus (OR: 1.12, 95% CI: 1.00-1.25, P = 0.046) were risk factors for psoriasis, while the genus Butyricicoccus (OR: 0.80, 95% CI: 0.64-1.00, P = 0.049), genus Faecalibacterium (OR: 0.84, 95% CI: 0.71–0.99, P = 0.035) and genus Prevotella9 (OR: 0.88, 95% CI: 0.78–0.99, P = 0.040) had protective effects on psoriasis (Table 1 ). The scatter plots to illustrate the correlations above are presented in Fig. 1 . Table S1 provides a list of the specific IVs involved in the MR analysis. The outcomes from all performed MR analyses are summarized in Table S2 . Table 1 MR analysis results of all five methods for significant taxa Group Bacterial taxa Method No.SNP P-value OR (95% CI) F-statistic Genus Eubacterium fissicatena group Inverse variance weighted 9 < 0.001 1.22 (1.09–1.36) 21.16 MR Egger 9 0.703 0.89 (0.50–1.58) Weighted median 9 0.005 1.24 (1.07–1.44) Simple mode 9 0.090 1.25 (1.00-1.56) Weighted mode 9 0.092 1.25 (0.99–1.57) Genus Butyricicoccus Inverse variance weighted 8 0.049 0.80 (0.64-1.00) 20.92 MR Egger 8 0.483 0.84 (0.52–1.34) Weighted median 8 0.074 0.77 (0.57–1.03) Simple mode 8 0.254 0.76 (0.50–1.17) Weighted mode 8 0.267 0.78 (0.52–1.17) Genus Faecalibacterium Inverse variance weighted 10 0.035 0.84 (0.71–0.99) 21.09 MR Egger 10 0.790 0.96 (0.69–1.32) Weighted median 10 0.154 0.85 (0.68–1.06) Simple mode 10 0.138 0.77 (0.56–1.05) Weighted mode 10 0.307 0.88 (0.69–1.11) Genus Lactococcus Inverse variance weighted 9 0.046 1.12 (1.00-1.25) 21.89 MR Egger 9 0.791 1.07 (0.65–1.78) Weighted median 9 0.285 1.09 (0.93–1.27) Simple mode 9 0.527 1.08 (0.86–1.35) Weighted mode 9 0.525 1.08 (0.87–1.33) Genus Prevotella9 Inverse variance weighted 15 0.040 0.88 (0.78–0.99) 20.97 MR Egger 15 0.642 0.92 (0.64–1.31) Weighted median 15 0.143 0.87 (0.73–1.05) Simple mode 15 0.420 0.88 (0.66–1.18) Weighted mode 15 0.367 0.88 (0.67–1.15) Sensitivity analyses The results of Cochran's Q test did not reveal any statistically significant heterogeneity ( Table S3 ). MR-Egger regression intercept analysis showed the absence of directional horizontal pleiotropy for GM in psoriasis ( Table S4 ). Upon a visual analysis of funnel plots ( Figure S1 ) and leave-one-out plots ( Figure S2 ), potential outliers were observed among the IVs of genus Lactococcus and genus Butyricicoccus . However, MR-PRESSO analysis did not detect any outliers in the outcomes ( Table S5 ). Consequently, the existence of horizontal pleiotropy was not detected between the selected IVs and psoriasis. Discussion An increasing amount of evidence suggests that GM plays a crucial part in regulating metabolism ( 23 ), immune system function ( 24 ), and intestinal permeability ( 25 ). It has been found to have a strong correlation with the onset and progression of several chronic multifactorial illnesses, such as psoriasis. This has led to the emergence of the gut-skin axis as a novel concept ( 10 ). When interacting with the host, GM generates a diverse array of metabolites. Among these, short-chain fatty acids (SCFAs) are the final products resulting from anaerobic fermentation of indigestible carbohydrates, such as dietary fiber, by gut microorganisms. The primary SCFAs produced are acetate, propionate, and butyrate ( 26 ). SCFAs not only serve as an energy source for colonic epithelial cells but also regulate glucose and lipid metabolism to control energy expenditure, maintain the integrity of the intestinal mucosa, and affect immune system and inflammatory responses ( 27 ). Notably, butyrate exhibits anti-inflammatory effects that contribute to preserving epithelial barrier function and preventing colitis ( 11 ). It additionally mitigates oxidative stress, modulates the equilibrium between Th17/Treg cells, and participates in the control of many inflammatory mediators including IL-6, IL-10, and IL-18 ( 7 ). Trimethylamine N-oxide (TMAO) is another metabolite synthesized by GM. It is derived through the conversion of trimethylamine, which is generated through the metabolic breakdown of choline, betaine, and carnitine by hepatic flavin monooxygenase. TMAO is involved in cholesterol metabolism and promotes atherosclerosis and plaque formation. Elevated concentrations of TMAO in the bloodstream have been identified as an independent risk factor for cardiovascular disease and are directly correlated with the incidence and mortality of acute coronary syndrome, stroke, and other serious cardiovascular complications ( 11 , 28 ). Based on available information, notable disparities in the diversity and composition of GM have been observed between persons with psoriasis and those without the condition. These discrepancies are defined by a state of dysbiosis, wherein there is a decrease in beneficial microorganisms and an increase in potentially detrimental ones ( 7 ). Multiple research studies have reported an elevation in Firmicutes and a decline in Bacteroidetes phyla in the GM of individuals with psoriasis in comparison to healthy individuals ( 29 ), which was also observed in our study. The ratio of Firmicutes to Bacteroidetes (F/B ratio) is considered as an important indicator of GM status. Research has shown that F/B ratio is positively correlated with the Psoriasis Area Severity Index ( 30 ), which measures the severity of psoriasis lesions. In addition, an imbalance in this ratio has been linked to various comorbidities including cardiovascular diseases, obesity, and insulin resistance ( 10 ). An alteration in GM can lead to a reduction in butyrate synthesis, thereby exacerbating the inflammatory response observed in psoriasis. Moreover, an increased F/B ratio may result in elevated production of TMAO, which could potentially increase the risk of cardiovascular complications and have adverse effects on the prognosis for patients with psoriasis. Furthermore, the dysregulation of GM can cause the periodic release of certain wall components, including lipopolysaccharides and lipoteichoic acid. These components have been proven to be potent pro-inflammatory agents that disrupt the integrity of the intestinal barrier and enhance gut permeability, ultimately contributing to the development of a condition known as "leaky gut syndrome" ( 31 ). This situation leads to the translocation of bacteria into the systemic circulation and induce the overexpression of pro-inflammatory cytokines, promoting an inflammatory state in the body and aggravates psoriasis ( 32 ). Based on the possible mechanisms mentioned above, we can reasonably explain the findings of our MR analysis in this study. Eubacterium fissicatena , also known as Faecalicatena fissicatena , is a member of the phylum Firmicutes with limited previous research. It has been reported that in a dextran sulfate sodium salt-induced colitis mouse model, E. Fissicatena is enriched in the intestines of mice with colitis. This enrichment was shown to exhibit a positive correlation with pro-inflammatory markers, while displaying a negative correlation with anti-inflammatory markers ( 33 ). E. Fissicatena shows a strong association with inflammatory cells in the colon, as well as disease activity index score and histology score, which reflect the activity and severity of colitis ( 34 , 35 ). The abundance of E. Fissicatena is elevated in obese mice induced by high-fat diet, which is strongly linked to the development of obesity and associated metabolic abnormalities. The inflammatory environment resulting from obesity is believed to accelerate the deterioration of ulcerative colitis ( 34 ). Additionally, a significant increase in the abundance of E. Fissicatena has been reported in individuals diagnosed with acute coronary syndrome, which exhibits a strong association with serum TMAO levels ( 28 ). This correlation may contribute to the observed elevated cardiovascular risk among individuals with psoriasis. Similarly, it has been found that Lactococcus proportion in the gut positively correlates with body weight, adiposity index, glucose intolerance, insulin resistance, and the expression of genes related to intestinal inflammation ( 36 ). The abundance of Lactococcus is positively associated with pro-inflammatory cytokines such as IL-6 and TNF-α, while exhibiting a negative correlation with the anti-inflammatory cytokines like IL-10 ( 37 ). These bacterial genera may conduce to the progression of psoriasis by facilitating inflammatory reactions. Butyricicoccus , which is noted for its ability to produce butyrate, has notably reduced abundance in GM of patients with IBD compared to healthy individuals, as well as in active Crohn's disease patients compared to non-active patients ( 38 ). Its reduced activity is closely associated with impaired intestinal epithelial barrier integrity ( 39 ) as well as weight-related indicators such as waist circumference and body mass index, and blood lipid parameters including low-density lipoprotein, triglycerides, and total cholesterol ( 40 ). Recent research highlights the importance of Butyricicoccus pullicaecorum in producing high concentrations of butyrate that play a protective role against colitis induced by trinitrobenzene sulfonic acid ( 38 ). Conflicting findings have been reported regarding the genus Faecalibacterium and Prevotella . While several studies have demonstrated an increase in the abundance of Faecalibacterium in the gut microbiome of psoriasis patients ( 41 , 42 ), a significant decrease has been observed in Faecalibacterium prausnitzii , which is known as one of the major producers of butyrate ( 43 ). The reduction has been found in both IBD and psoriasis vulgaris, with a more pronounced effect seen in patients with both conditions, supporting the existence of the gut-skin axis ( 43 , 44 ). As for Prevotella , although its high abundance has been identified in mice exhibiting a severe psoriasis-like phenotype ( 45 ), multiple studies have consistently reported decreased levels of Prevotella among psoriasis patients, suggesting that it may possess anti-inflammatory properties that enhance intestinal barrier function and reduce cecal inflammatory markers ( 46 , 47 ). The inconsistent outcomes could possibly be ascribed to the diverse immune effects observed in different species within the same genus. Studies have identified at least two phylotypes of F. prausnitzii , and the potential influence of other phylogroups and species within the genus cannot be disregarded due to variations in relative population abundance across different diseases ( 42 ). Likewise, Prevotella copri , a bacterium that has been found to decrease in psoriasis but rise in other inflammatory conditions such as ankylosing spondylitis and rheumatoid arthritis, has recently demonstrated its ability to stimulate colonic Th17 cells and induce arthritis in SKG mice. Conversely, another species belonging to the identical genus, Prevotella histicola , has been shown to inhibit collagen-induced arthritis in transgenic mice that express genes associated with susceptibility to rheumatoid arthritis. Thus, it can be inferred that the immunomodulatory effects of GM vary depending on the species involved and, in certain cases, may even differ based on the specific strain ( 48 ). The data we have obtained on the abundance of GM is restricted to the genus level due to the inherent limitations in resolution of 16S rRNA gene sequencing. Further investigations are required to confirm the specific roles played by different species. This study possesses multiple notable benefits. To the best of our current understanding, this work is the first to employ MR analysis in order to explore the potential causal association between GM and psoriasis. The utilization of MR analysis is a pertinent methodology for examining causal relationships, as it effectively addresses the issue of potential confounding factors. On the contrary, case-control studies have limitations in establishing the temporal sequence between the colonization of GM and the beginning of psoriasis due to the collection of fecal samples after the manifestation of the illness. In addition, the genetic variables utilized in this study were obtained from the most extensive GWAS meta-analysis currently accessible, ensuring the strength and dependability of the instruments applied in the research. Furthermore, we have discovered the existence of horizontal pleiotropy and mitigated its impact by the use of MR-PRESSO and MR-Egger regression intercept term tests, which signifies the robustness and reliability of our findings from a statistical standpoint. Our study also has some limitations. Given that the majority of participants in the GWAS meta-analysis are of European descent, caution should be exercised when generalizing results to individuals of non-European ancestry, and potential biases due to population stratification may still exist. Additionally, in order to incorporate more genetic variations as IVs for sensitivity analysis and horizontal pleiotropy testing, SNPs in the analysis had a relatively low significance threshold (P < 1×10 –5 ). Conclusion To summarize, our TSMR analysis evaluated the potential causal association between GM and psoriasis. We identified two bacterial genera that exhibited a positive correlation with psoriasis, while three bacterial genera showed a negative correlation. The possible mechanisms were discussed in combination with previous studies. Future investigations should employ comprehensive and multi-omics approaches to further unravel the contribution of GM to the pathogenesis of psoriasis and assess its safety and efficacy as a potential therapeutic strategy. Declarations Conflict of interest The authors affirm that the study was conducted without any potential conflicts of interest arising from commercial or financial relationships. Author Contribution CG and ML developed the project, conducted the data analysis and wrote the main manuscript text. JD developed the project and edited the manuscript. 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Front Cell Infect Microbiol 9. 10.3389/fcimb.2019.00007 Zhao Q, Yu J, Zhou H, Wang X, Zhang C, Hu J et al (2023) Intestinal dysbiosis exacerbates the pathogenesis of psoriasis-like phenotype through changes in fatty acid metabolism. Signal Transduct Target Ther 8:40. 10.1038/s41392-022-01219-0 Xiao S, Zhang G, Jiang C, Liu X, Wang X, Li Y et al (2021) Deciphering Gut Microbiota Dysbiosis and Corresponding Genetic and Metabolic Dysregulation in Psoriasis Patients Using Metagenomics Sequencing. Front Cell Infect Microbiol 11. 10.3389/fcimb.2021.605825 Shapiro J, Cohen NA, Shalev V, Uzan A, Koren O, Maharshak N (2019) Psoriatic patients have a distinct structural and functional fecal microbiota compared with controls. J Dermatol 46:595–603. 10.1111/1346-8138.14933 Rogier R, Ederveen T, Boekhorst J, Wopereis H, Scher JU, Manasson J et al (2017) Aberrant intestinal microbiota due to IL-1 receptor antagonist deficiency promotes IL-17- and TLR4-dependent arthritis. Microbiome 5:63. 10.1186/s40168-017-0278-2 Additional Declarations No competing interests reported. Supplementary Files FigureS1.tif FigureS2.tif SupplementaryTables.docx 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-3887794","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268745982,"identity":"62091ec9-0b94-4fdc-b731-0fa8fc839e30","order_by":0,"name":"Chongxiang Gao","email":"","orcid":"","institution":"Department of Urology, Xiangya Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Chongxiang","middleName":"","lastName":"Gao","suffix":""},{"id":268745983,"identity":"5fe59bff-181c-4b2a-92d8-334283be6044","order_by":1,"name":"Minghui Liu","email":"","orcid":"","institution":"Department of Urology, Xiangya Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Minghui","middleName":"","lastName":"Liu","suffix":""},{"id":268745984,"identity":"3d9f49ce-eaaf-411d-98eb-070197082335","order_by":2,"name":"Jian Ding","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDCCw0AsYQBiMR8DC7CxE6+FLY2BIQFIMRPScgDO4jEDa2EgpIXvOO/hFxYFdnkGN3K+Pfj4Y5s8HzMD44ePObi1SB7mS7OQMEgulpyRu91wRsJtwzZmBmbJmdtwazE4zGNmIGHAnNgvkbtNmifhNiNQCxszL2Et9YltEjnPQFrsidFi/EDC4DDQlhw2kJZEglokgbYAA/l44syeZ2aSM9JuJ7cxMzbj9Qvf+TPGnyX+VCduOJ78TOKDzW3b+e3NBz98xKMFCNikJUCUQAJMgLEBr3ogYP74AUTxHyCkcBSMglEwCkYqAACG5UwajAORyAAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Urology, Xiangya Hospital, Central South University","correspondingAuthor":true,"prefix":"","firstName":"Jian","middleName":"","lastName":"Ding","suffix":""}],"badges":[],"createdAt":"2024-01-22 11:32:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3887794/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3887794/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50143855,"identity":"e5f5d0f8-df2f-427f-8454-54e7120137df","added_by":"auto","created_at":"2024-01-25 07:43:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":80752,"visible":true,"origin":"","legend":"\u003cp\u003eLegend is not included with this version.\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3887794/v1/48dbdda420b06e086bc87875.png"},{"id":50182098,"identity":"f2823fb4-aea0-484c-b44f-6fc2af898a5d","added_by":"auto","created_at":"2024-01-25 18:52:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":453199,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3887794/v1/c65a7cae-b9c9-4398-8102-1841fe8f6527.pdf"},{"id":50143469,"identity":"49e81020-a92b-45ea-a621-b7d2be2b3956","added_by":"auto","created_at":"2024-01-25 07:35:57","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11679672,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3887794/v1/fc2c92f42c06be02db0e7982.tif"},{"id":50143470,"identity":"134a670b-21b0-4646-81f6-fd12638112b5","added_by":"auto","created_at":"2024-01-25 07:35:58","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13614384,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-3887794/v1/b3bf53b62f17982015fe3d27.tif"},{"id":50143467,"identity":"e3b95599-2361-41c8-9c65-e04ee2ba58dc","added_by":"auto","created_at":"2024-01-25 07:35:56","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":162804,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-3887794/v1/eaea3ec4ca37f18863e18232.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal relationship between gut microbiota and psoriasis: a two-sample Mendelian randomization study","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePsoriasis is a common immune-mediated, chronic, noninfectious, systemic inflammatory disease with no clear cause or cure (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It can manifest in multiple phenotypes, the most common of which is plaque psoriasis, also known as psoriasis vulgaris (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). As a serious global problem, psoriasis affects all countries and all age groups, with prevalence ranging from 0.09% (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) to 11.43% (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), affecting at least 100\u0026nbsp;million people on a global scale. Psoriasis is a complex disease with a multifactorial pathophysiology, involving intricate interactions among genetic, immune, and environmental factors. There are many internal and external triggers, including trauma, infection, drugs, physical and chemical damage and stress (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The sustained chronic inflammation caused by psoriasis is featured with pro-inflammatory cytokines, epidermal hyperplasia, and inflammatory infiltration composed of immune cells (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). A number of comorbidities is connected to psoriasis, including but not limited to obesity, cardiovascular disease, arthritis, inflammatory bowel disease (IBD), and depression. These conditions significantly worsen the quality of life for patients and impose substantial physical, emotional, and social burdens (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe gut microbiota (GM) is known to have a significant impact on several aspects of host physiology, including regulation of energy metabolism and immune response, maintenance of intestinal epithelial integrity, and facilitation of neurobehavioral development (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The impact of GM on overall bodily health may be both advantageous and disadvantageous, as evidenced by their interactions with the host organism. Revolutionary advancements have been achieved in the exploration of the human microbiome, with techniques such as 16S rDNA sequencing technology being extensively utilized for investigating GM (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Mounting evidence shows a significant correlation between GM and psoriasis occurrence and development. Dysbiosis, defined as changes in the diversity and composition of GM, has been reported to be a possible cause for psoriasis recurrence (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Preclinical studies have found that oral broad-spectrum antibiotic treatment can alleviate skin inflammation by downregulating the Th17 immune response in mice with imiquimod-induced psoriasis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), providing evidence for the involvement of GM in psoriasis pathogenesis. Clinical research has demonstrated that antibiotic therapy (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), probiotic modulation of GM (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), or fecal microbial transplantation can induce remission in psoriatic skin lesions (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, the causal link between psoriasis and GM remains inconclusive as a result of inconsistent findings reported in prior research (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Hence, it is imperative to do more research in order to examine the causative connection between GM and psoriasis, as well as to clarify the precise role of GM in the initiation of psoriasis.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) analysis is a commonly employed epidemiological method for examining potential causal relationships between exposures and outcomes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Two-sample Mendelian randomization (TSMR) analysis involves the utilization of single nucleotide polymorphisms (SNPs) obtained from separate genome-wide association studies (GWASs) as instrumental variables (IVs). This approach efficiently addresses the influence of confounding factors and reverse causation (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In this study, we conducted a TSMR analysis with GWAS summary statistics retrieved from the MiBioGen and FinnGen consortium to evaluate the causation between GM composition and psoriasis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExposure data\u003c/h2\u003e \u003cp\u003eSNPs that served as IVs originated from the MiBioGen study, which is the biggest multi-ethnic genome-wide meta-analysis of GM. The GWAS dataset comprises 18,340 samples of 16S rRNA gene sequencing data obtained from 24 distinct cohorts from various populations. This dataset encompasses a comprehensive collection of 211 GM taxa, including 131 genera, 35 families, 20 orders, 16 classes, and 9 phyla (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcome data\u003c/h2\u003e \u003cp\u003eThe summary statistics pertaining to psoriasis were derived from the FinnGen consortium release 7. This dataset had a total of 6,995 individuals diagnosed with psoriasis and 299,128 individuals serving as controls. Covariate adjustments were performed to account for age, sex, genetic main components, and genotyping batch effects. Cases of psoriasis were recognized based on the diagnostic code L40 in the \u003cem\u003eInternational Classification of Diseases, 10th Revision\u003c/em\u003e.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eInstrumental variable selection\u003c/h2\u003e \u003cp\u003eSNPs significantly related to GM were filtered at a genome-wide significance threshold (P\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u003csup\u003e\u0026ndash;5\u003c/sup\u003e) and chosen as potential IVs on the basis of existing MR research on GM (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). To ensure statistical independence, we conducted a linkage disequilibrium analysis with R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and a clumping distance of 10,000 kb using data from the European-based 1000 Genome Projects. Palindromic SNPs were excluded to guarantee the accuracy of strand orientation and allele coding. The F-statistic was computed to assess the presence of weak instrumental bias (F\u0026thinsp;=\u0026thinsp;beta\u003csup\u003e2\u003c/sup\u003e/se\u003csup\u003e2\u003c/sup\u003e). A value of F greater than 10 was seen as an indication of the absence of substantial evidence supporting weak instrumental bias (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). All included IVs were inspected by PhenoScanner (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.phenoscanner.medschl.cam.ac.uk/\u003c/span\u003e\u003cspan address=\"http://www.phenoscanner.medschl.cam.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to subsequently excluding any SNPs that exhibited associations with confounding factors.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eMultiple MR methods were employed to assess the probable causative relationship between GM and psoriasis. These methods consisted of the inverse-variance weighted (IVW), MR-Egger regression, weighted mode, weighted median, and simple mode. The IVW method was predominantly utilized in order to establish causality by making the assumption of a shared causal influence of all IVs on the outcome through exposure. The MR-Egger regression method is used in the presence of horizontal pleiotropy, which arises when IVs impact the outcome through pathways unrelated to the exposure (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The MR-PRESSO analysis was applied to identify the existence of horizontal pleiotropy as well. After removal of outliers, the causal effect was recalculated using the remaining IVs, which provides a more precise and robust estimation (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Cochrane's Q test was carried out to evaluate heterogeneity among effect estimates of SNPs. The results of the MR analysis were visualized by scatter plots and funnel plots to facilitate data interpretation and identify potential outliers. To mitigate the potential influence of horizontal pleiotropy caused by a single SNP, we conducted a leave-one-out analysis wherein each SNP was sequentially removed. The packages Two-Sample-MR and MR-PRESSO in R version 4.1.3 are utilized for every statistical analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSNPs selection\u003c/h2\u003e \u003cp\u003eWe identified 102, 178, 215, 375 and 1381 SNPs at the phylum, class, order, family and genus taxonomic levels respectively with a significance threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u003csup\u003e\u0026ndash;5\u003c/sup\u003e. A total of 2251 SNPs were selected as IVs, all of which had F-statistics\u0026thinsp;\u0026gt;\u0026thinsp;10.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMR analyses\u003c/h2\u003e \u003cp\u003eThe findings from the IVW analysis revealed significant associations between psoriasis and several genera, namely the genus \u003cem\u003eButyricicoccus\u003c/em\u003e, genus \u003cem\u003eEubacterium fissicatena group\u003c/em\u003e, genus \u003cem\u003eFaecalibacterium\u003c/em\u003e, genus \u003cem\u003eLactococcus\u003c/em\u003e, genus \u003cem\u003ePrevotella9\u003c/em\u003e. The genus \u003cem\u003eEubacterium fissicatena group\u003c/em\u003e (OR: 1.22, 95% CI: 1.09\u0026ndash;1.36, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and genus \u003cem\u003eLactococcus\u003c/em\u003e (OR: 1.12, 95% CI: 1.00-1.25, P\u0026thinsp;=\u0026thinsp;0.046) were risk factors for psoriasis, while the genus \u003cem\u003eButyricicoccus\u003c/em\u003e (OR: 0.80, 95% CI: 0.64-1.00, P\u0026thinsp;=\u0026thinsp;0.049), genus \u003cem\u003eFaecalibacterium\u003c/em\u003e (OR: 0.84, 95% CI: 0.71\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.035) and genus \u003cem\u003ePrevotella9\u003c/em\u003e (OR: 0.88, 95% CI: 0.78\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.040) had protective effects on psoriasis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The scatter plots to illustrate the correlations above are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e provides a list of the specific IVs involved in the MR analysis. The outcomes from all performed MR analyses are summarized in \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\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\u003eMR analysis results of all five methods for significant taxa\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacterial taxa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo.SNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF-statistic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEubacterium fissicatena group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.22 (1.09\u0026ndash;1.36)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e21.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.89 (0.50\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.24 (1.07\u0026ndash;1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.25 (1.00-1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.25 (0.99\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eButyricicoccus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.049\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.80 (0.64-1.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e20.92\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.84 (0.52\u0026ndash;1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.77 (0.57\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76 (0.50\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.78 (0.52\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFaecalibacterium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.84 (0.71\u0026ndash;0.99)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e21.09\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.69\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.85 (0.68\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.77 (0.56\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88 (0.69\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLactococcus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.12 (1.00-1.25)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e21.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.07 (0.65\u0026ndash;1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.09 (0.93\u0026ndash;1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.08 (0.86\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.08 (0.87\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrevotella9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInverse variance weighted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.88 (0.78\u0026ndash;0.99)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e20.97\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.64\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.87 (0.73\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88 (0.66\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88 (0.67\u0026ndash;1.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analyses\u003c/h2\u003e \u003cp\u003eThe results of Cochran's Q test did not reveal any statistically significant heterogeneity (\u003cb\u003eTable \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e). MR-Egger regression intercept analysis showed the absence of directional horizontal pleiotropy for GM in psoriasis (\u003cb\u003eTable S4\u003c/b\u003e). Upon a visual analysis of funnel plots (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) and leave-one-out plots (\u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e), potential outliers were observed among the IVs of genus \u003cem\u003eLactococcus\u003c/em\u003e and genus \u003cem\u003eButyricicoccus\u003c/em\u003e. However, MR-PRESSO analysis did not detect any outliers in the outcomes (\u003cb\u003eTable S5\u003c/b\u003e). Consequently, the existence of horizontal pleiotropy was not detected between the selected IVs and psoriasis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAn increasing amount of evidence suggests that GM plays a crucial part in regulating metabolism (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), immune system function (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), and intestinal permeability (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). It has been found to have a strong correlation with the onset and progression of several chronic multifactorial illnesses, such as psoriasis. This has led to the emergence of the gut-skin axis as a novel concept (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). When interacting with the host, GM generates a diverse array of metabolites. Among these, short-chain fatty acids (SCFAs) are the final products resulting from anaerobic fermentation of indigestible carbohydrates, such as dietary fiber, by gut microorganisms. The primary SCFAs produced are acetate, propionate, and butyrate (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). SCFAs not only serve as an energy source for colonic epithelial cells but also regulate glucose and lipid metabolism to control energy expenditure, maintain the integrity of the intestinal mucosa, and affect immune system and inflammatory responses (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Notably, butyrate exhibits anti-inflammatory effects that contribute to preserving epithelial barrier function and preventing colitis (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). It additionally mitigates oxidative stress, modulates the equilibrium between Th17/Treg cells, and participates in the control of many inflammatory mediators including IL-6, IL-10, and IL-18 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Trimethylamine N-oxide (TMAO) is another metabolite synthesized by GM. It is derived through the conversion of trimethylamine, which is generated through the metabolic breakdown of choline, betaine, and carnitine by hepatic flavin monooxygenase. TMAO is involved in cholesterol metabolism and promotes atherosclerosis and plaque formation. Elevated concentrations of TMAO in the bloodstream have been identified as an independent risk factor for cardiovascular disease and are directly correlated with the incidence and mortality of acute coronary syndrome, stroke, and other serious cardiovascular complications (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on available information, notable disparities in the diversity and composition of GM have been observed between persons with psoriasis and those without the condition. These discrepancies are defined by a state of dysbiosis, wherein there is a decrease in beneficial microorganisms and an increase in potentially detrimental ones (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Multiple research studies have reported an elevation in \u003cem\u003eFirmicutes\u003c/em\u003e and a decline in \u003cem\u003eBacteroidetes\u003c/em\u003e phyla in the GM of individuals with psoriasis in comparison to healthy individuals (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), which was also observed in our study. The ratio of \u003cem\u003eFirmicutes\u003c/em\u003e to \u003cem\u003eBacteroidetes\u003c/em\u003e (F/B ratio) is considered as an important indicator of GM status. Research has shown that F/B ratio is positively correlated with the Psoriasis Area Severity Index (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), which measures the severity of psoriasis lesions. In addition, an imbalance in this ratio has been linked to various comorbidities including cardiovascular diseases, obesity, and insulin resistance (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAn alteration in GM can lead to a reduction in butyrate synthesis, thereby exacerbating the inflammatory response observed in psoriasis. Moreover, an increased F/B ratio may result in elevated production of TMAO, which could potentially increase the risk of cardiovascular complications and have adverse effects on the prognosis for patients with psoriasis. Furthermore, the dysregulation of GM can cause the periodic release of certain wall components, including lipopolysaccharides and lipoteichoic acid. These components have been proven to be potent pro-inflammatory agents that disrupt the integrity of the intestinal barrier and enhance gut permeability, ultimately contributing to the development of a condition known as \"leaky gut syndrome\" (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This situation leads to the translocation of bacteria into the systemic circulation and induce the overexpression of pro-inflammatory cytokines, promoting an inflammatory state in the body and aggravates psoriasis (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the possible mechanisms mentioned above, we can reasonably explain the findings of our MR analysis in this study. \u003cem\u003eEubacterium fissicatena\u003c/em\u003e, also known as \u003cem\u003eFaecalicatena fissicatena\u003c/em\u003e, is a member of the phylum \u003cem\u003eFirmicutes\u003c/em\u003e with limited previous research. It has been reported that in a dextran sulfate sodium salt-induced colitis mouse model, \u003cem\u003eE. Fissicatena\u003c/em\u003e is enriched in the intestines of mice with colitis. This enrichment was shown to exhibit a positive correlation with pro-inflammatory markers, while displaying a negative correlation with anti-inflammatory markers (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). \u003cem\u003eE. Fissicatena\u003c/em\u003e shows a strong association with inflammatory cells in the colon, as well as disease activity index score and histology score, which reflect the activity and severity of colitis (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The abundance of \u003cem\u003eE. Fissicatena\u003c/em\u003e is elevated in obese mice induced by high-fat diet, which is strongly linked to the development of obesity and associated metabolic abnormalities. The inflammatory environment resulting from obesity is believed to accelerate the deterioration of ulcerative colitis (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Additionally, a significant increase in the abundance of \u003cem\u003eE. Fissicatena\u003c/em\u003e has been reported in individuals diagnosed with acute coronary syndrome, which exhibits a strong association with serum TMAO levels (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). This correlation may contribute to the observed elevated cardiovascular risk among individuals with psoriasis. Similarly, it has been found that \u003cem\u003eLactococcus\u003c/em\u003e proportion in the gut positively correlates with body weight, adiposity index, glucose intolerance, insulin resistance, and the expression of genes related to intestinal inflammation (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The abundance of \u003cem\u003eLactococcus\u003c/em\u003e is positively associated with pro-inflammatory cytokines such as IL-6 and TNF-α, while exhibiting a negative correlation with the anti-inflammatory cytokines like IL-10 (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). These bacterial genera may conduce to the progression of psoriasis by facilitating inflammatory reactions.\u003c/p\u003e \u003cp\u003e \u003cem\u003eButyricicoccus\u003c/em\u003e, which is noted for its ability to produce butyrate, has notably reduced abundance in GM of patients with IBD compared to healthy individuals, as well as in active Crohn's disease patients compared to non-active patients (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Its reduced activity is closely associated with impaired intestinal epithelial barrier integrity (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) as well as weight-related indicators such as waist circumference and body mass index, and blood lipid parameters including low-density lipoprotein, triglycerides, and total cholesterol (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Recent research highlights the importance of \u003cem\u003eButyricicoccus pullicaecorum\u003c/em\u003e in producing high concentrations of butyrate that play a protective role against colitis induced by trinitrobenzene sulfonic acid (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConflicting findings have been reported regarding the genus \u003cem\u003eFaecalibacterium\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e. While several studies have demonstrated an increase in the abundance of \u003cem\u003eFaecalibacterium\u003c/em\u003e in the gut microbiome of psoriasis patients (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), a significant decrease has been observed in \u003cem\u003eFaecalibacterium prausnitzii\u003c/em\u003e, which is known as one of the major producers of butyrate (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). The reduction has been found in both IBD and psoriasis vulgaris, with a more pronounced effect seen in patients with both conditions, supporting the existence of the gut-skin axis (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). As for \u003cem\u003ePrevotella\u003c/em\u003e, although its high abundance has been identified in mice exhibiting a severe psoriasis-like phenotype (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), multiple studies have consistently reported decreased levels of \u003cem\u003ePrevotella\u003c/em\u003e among psoriasis patients, suggesting that it may possess anti-inflammatory properties that enhance intestinal barrier function and reduce cecal inflammatory markers (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThe inconsistent outcomes could possibly be ascribed to the diverse immune effects observed in different species within the same genus. Studies have identified at least two phylotypes of \u003cem\u003eF. prausnitzii\u003c/em\u003e, and the potential influence of other phylogroups and species within the genus cannot be disregarded due to variations in relative population abundance across different diseases (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Likewise, \u003cem\u003ePrevotella copri\u003c/em\u003e, a bacterium that has been found to decrease in psoriasis but rise in other inflammatory conditions such as ankylosing spondylitis and rheumatoid arthritis, has recently demonstrated its ability to stimulate colonic Th17 cells and induce arthritis in SKG mice. Conversely, another species belonging to the identical genus, \u003cem\u003ePrevotella histicola\u003c/em\u003e, has been shown to inhibit collagen-induced arthritis in transgenic mice that express genes associated with susceptibility to rheumatoid arthritis. Thus, it can be inferred that the immunomodulatory effects of GM vary depending on the species involved and, in certain cases, may even differ based on the specific strain (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). The data we have obtained on the abundance of GM is restricted to the genus level due to the inherent limitations in resolution of 16S rRNA gene sequencing. Further investigations are required to confirm the specific roles played by different species.\u003c/p\u003e \u003cp\u003eThis study possesses multiple notable benefits. To the best of our current understanding, this work is the first to employ MR analysis in order to explore the potential causal association between GM and psoriasis. The utilization of MR analysis is a pertinent methodology for examining causal relationships, as it effectively addresses the issue of potential confounding factors. On the contrary, case-control studies have limitations in establishing the temporal sequence between the colonization of GM and the beginning of psoriasis due to the collection of fecal samples after the manifestation of the illness. In addition, the genetic variables utilized in this study were obtained from the most extensive GWAS meta-analysis currently accessible, ensuring the strength and dependability of the instruments applied in the research. Furthermore, we have discovered the existence of horizontal pleiotropy and mitigated its impact by the use of MR-PRESSO and MR-Egger regression intercept term tests, which signifies the robustness and reliability of our findings from a statistical standpoint.\u003c/p\u003e \u003cp\u003eOur study also has some limitations. Given that the majority of participants in the GWAS meta-analysis are of European descent, caution should be exercised when generalizing results to individuals of non-European ancestry, and potential biases due to population stratification may still exist. Additionally, in order to incorporate more genetic variations as IVs for sensitivity analysis and horizontal pleiotropy testing, SNPs in the analysis had a relatively low significance threshold (P\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u003csup\u003e\u0026ndash;5\u003c/sup\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTo summarize, our TSMR analysis evaluated the potential causal association between GM and psoriasis. We identified two bacterial genera that exhibited a positive correlation with psoriasis, while three bacterial genera showed a negative correlation. The possible mechanisms were discussed in combination with previous studies. Future investigations should employ comprehensive and multi-omics approaches to further unravel the contribution of GM to the pathogenesis of psoriasis and assess its safety and efficacy as a potential therapeutic strategy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors affirm that the study was conducted without any potential conflicts of interest arising from commercial or financial relationships.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCG and ML developed the project, conducted the data analysis and wrote the main manuscript text. JD developed the project and edited the manuscript. All authors made substantial contributions to the article and approved the submitted version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization (2016) Global report on psoriasis. 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Microbiome 5:63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40168-017-0278-2\u003c/span\u003e\u003cspan address=\"10.1186/s40168-017-0278-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"gut microbiota, psoriasis, gut-skin axis, Mendelian randomization, causal relationship","lastPublishedDoi":"10.21203/rs.3.rs-3887794/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3887794/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAccumulating evidence from observational and experimental studies suggests a potential association between the gut microbiota (GM) and psoriasis, yet it remains obscure whether this connection is causal in nature.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBy performing a two-sample Mendelian Randomization (MR) analysis of genome-wide association study (GWAS) summary statistics from the MiBioGen and FinnGen consortium, the causal association between GM and psoriasis was investigated, using methods of inverse variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe genus \u003cem\u003eEubacterium fissicatena group\u003c/em\u003e (odds ratio [OR]: 1.22, 95% confidential interval [CI], 1.09\u0026ndash;1.36, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and genus \u003cem\u003eLactococcus\u003c/em\u003e (OR: 1.12, 95% CI: 1.00-1.25, P\u0026thinsp;=\u0026thinsp;0.046) were identified as risk factors for psoriasis, while the genus \u003cem\u003eButyricicoccus\u003c/em\u003e (OR: 0.80, 95% CI: 0.64-1.00, P\u0026thinsp;=\u0026thinsp;0.049), genus \u003cem\u003eFaecalibacterium\u003c/em\u003e (OR: 0.84, 95% CI: 0.71\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.035), genus \u003cem\u003ePrevotella9\u003c/em\u003e (OR: 0.88, 95% CI: 0.78\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.040) exhibited protective effects against psoriasis. The sensitivity analysis did not provide any indications of pleiotropy or heterogeneity.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur two-sample MR analysis provides novel evidence supporting the causality between GM and psoriasis. Comprehensive and multi-omics methods are warranted to unravel the contribution of GM to psoriasis pathogenesis, as well as its potential therapeutic implications.\u003c/p\u003e","manuscriptTitle":"Causal relationship between gut microbiota and psoriasis: a two-sample Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-25 07:35:52","doi":"10.21203/rs.3.rs-3887794/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":"6d6c3221-0b00-4d9c-bc89-a8a9daac0b89","owner":[],"postedDate":"January 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-25T18:44:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-25 07:35:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3887794","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3887794","identity":"rs-3887794","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}