Genetically predicted levels of circulating cytokines and the risk of six immune skin diseases: a two-sample Mendelian randomization study.

Background: Circulating cytokines play a crucial role in the onset and progression of immune skin diseases. However, the causal relationships and the direction of causal effects require further investigation. Methods: Two-sample Mendelian randomization (MR) analyses were conducted to assess the causal relationships between 41 circulating cytokines and six immune skin diseases including alopecia areata, chloasma, hidradenitis suppurativa (HS), lichen planus (LP), seborrheic dermatitis, and urticaria, using summary statistics from genome-wide association studies. Reverse MR analyses was performed to test for the reverse causation. Pleiotropy and heterogeneity tests were conducted to assess the robustness of the findings. Results: Twelve unique cytokines showed a suggestive causal relationship with the risk of six immune skin diseases. Among them, the causal effects between 9 unique cytokines and immune skin diseases have strong statistical power. Additionally, the concentrations of six cytokines might be influenced by LP and urticaria. After Bonferroni correction, the following associations remained significant: the causal effect of beta-nerve growth factor on HS (odds ratio [OR] = 1.634, 95% confidence interval [CI] = 1.226-2.177, p = 7.97e-04), interleukin (IL)-6 on LP (OR = 0.615, 95% CI = 0.481-0.786, p = 1.04e-04), IL-4 on LP (OR = 1.099. 95% CI = 1.020-1.184, p = 1.26e-02), and IL-2 on urticaria (OR = 0.712, 95% CI = 0.531-0.955, p = 2.33e-02). Conclusion: This study provides novel perspectives on the relationship between circulating cytokines and immune skin diseases, potentially providing valuable insights into their etiology, diagnostic approaches, and treatment.

Gut microbiota and acne: A Mendelian randomization study.

BACKGROUND: Prior observational studies have identified a relationship between the composition of gut microbiota and the onset of acne. To ascertain the causal relationship underlying this association, we adopted the Mendelian randomization (MR) method, which offers a powerful approach to causal inference. METHODS: Summary statistics on gut microbiota and acne were obtained from the MiBioGen and FinnGen consortium, respectively. The causal relationship was assessed using multiple methods in a two-sample framework, including MR Egger, weighted median, inverse variance weighted (IVW), and weighted mode. Furthermore, the heterogeneity and horizontal pleiotropy analyses were conducted, along with the leave-one-out method. RESULTS: The IVW estimation indicated that Allisonella (odds ratio [OR] = 1.42, 95% confidence interval [CI] = 1.18-1.70, p = 0.0002) and Bacteroides (OR = 2.25, 95% CI = 1.48-3.42, p = 0.0001) have adverse effects on acne. By contrast, Ruminococcus torques group (OR = 0.41, 95% CI = 0.25-0.65, p = 0.0002) showed a beneficial effect on acne. In addition, Candidatus soleaferrea (OR = 0.75, 95% CI = 0.60-0.95, p = 0.0149), Eubacterium coprostanoligenes group (OR = 0.67, 95% CI = 0.47-0.95, p = 0.0230), Fusicatenibacter (OR = 0.71, 95% CI = 0.52-0.97, p = 0.02897), and Lactobacillus (OR = 0.72, 95% CI = 0.58-0.90, p = 0.0046) showed suggestive associations with acne. CONCLUSION: The present investigation suggests a causal effect of gut microbiota on acne.

Construction and validation of a prognostic model for colon adenocarcinoma based on bile acid metabolism-related genes.

Colon adenocarcinoma (COAD), one of the common clinical cancers, exhibits high morbidity and mortality, and its pathogenesis and treatment are still underdeveloped. Numerous studies have demonstrated the involvement of bile acids in tumour development, while the potential role of their metabolism in the tumor microenvironment (TME) has not been explored. A collection of 481 genes related to bile acid metabolism were obtained, and The Cancer Genome Atlas-based COAD risk model was developed using the least absolute shrinkage selection operator (LASSO) regression analysis. The Gene Expression Omnibus dataset was used to validate the results. The predictive performance of the model was verified using column line plots, principal component analysis and receiver operating characteristic curves. Then, we analysed the differences between the high- and low-risk groups from training set based on clinical characteristics, immune cell infiltration, immune-related functions, chemotherapeutic drug sensitivity and immunotherapy efficacy. Additionally, we constructed a protein-protein interaction network to screen for target genes, which were further investigated in terms of differential immune cell distribution. A total of 234 bile acids-related differentially expressed genes were obtained between normal and tumour colon tissues. Among them, 111 genes were upregulated and 123 genes were down-regulated in the tumour samples. Relying on the LASSO logistic regression algorithm, we constructed a model of bile acid risk score, comprising 12 genes: CPT2, SLCO1A2, CD36, ACOX1, CDKN2A, HADH, GABRD, LEP, TIMP1, MAT1A, SLC6A15 and PPARGC1A. This model was validated in the GEO-COAD set. Age and risk score were observed to be independent prognostic factors in patients with COAD. Genes related to bile acid metabolism in COAD were closely related to bile secretion, intestinal transport, steroid and fatty acid metabolism. Furthermore, the high-risk group was more sensitive to Oxaliplatin than the low-risk group. Finally, the three target genes screened were closely associated with immune cells. We identified a set of 12 genes (CPT2, SLCO1A2, CD36, ACOX1, CDKN2A, HADH, GABRD, LEP, TIMP1, MAT1A, SLC6A15, and PPARGC1A) associated with bile acid metabolism and developed a bile acid risk score model using LASSO regression analysis. The model demonstrated good predictive performance and was validated using an independent dataset. Our findings revealed that the bile acid risk score were independent prognostic factors in COAD patients.

The gut-lung axis: Mendelian randomization identifies a causal association between inflammatory bowel disease and interstitial lung disease.

BACKGROUND: Previous studies have suggested the association between interstitial lung disease (ILD) and inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC). OBJECTIVES: To examine the potential bidirectional causal relationship between IBD and ILD using the Mendelian randomization (MR) method. METHODS: We obtained the data from the genome-wide association studies (GWASs) in European individuals for IBD (25,042 cases and 34,915 controls) and ILD (21,806 cases and 196,986 controls) from the IEU GWAS database. We screened for instrumental variables based on the three assumptions of MR. The two-sample bidirectional MR analysis was performed using the inverse-variance weighted method and multiple sensitivity analyses. RESULTS: Genetic liability to IBD was significantly associated with an increased ILD risk (odds ratio (OR) = 1.20, 95% confidence interval (CI) = 1.17-1.24, p = 3.67E-33). When considering the IBD subtypes, ILD risk was associated with genetic liability to both CD (OR = 1.14, 95% CI = 1.10-1.17, p = 1.91E-17) and UC (OR = 1.16, 95% CI = 1.12-1.21, p = 3.51E-13). There was weak evidence for the effect of genetic liability to ILD on IBD (OR = 1.32, 95% CI = 0.99-1.76, p = 0.062), CD (OR = 1.25, 95% CI = 1.00-1.55, p = 0.046), and UC (OR = 1.47, 95%CI = 1.01-2.14, p = 0.046). CONCLUSION: The results indicate a strong causal effect of IBD (including CD and UC) on ILD.

Characterization of butyrate-metabolism in colorectal cancer to guide clinical treatment.

Colorectal cancer (CRC) is the third most prevalent one in the world among the most common malignant tumors. Numerous studies have shown that butyrate has demonstrated promise as an antitumor agent in a variety of human cancer types. However, butyrate remains understudied in CRC tumorigenesis and progression. In this study, we explored therapeutic strategies to treat CRC by examining the role of butyrate metabolism. First, from the Molecular Signature Database (MSigDB), we identified 348 butyrate metabolism-related genes (BMRGs). Next, we downloaded 473 CRC and 41 standard colorectal tissue samples from The Cancer Genome Atlas (TCGA) database and the transcriptome data of GSE39582 dataset from Gene Expression Omnibus (GEO) database. Then we evaluated the expression patterns of butyrate metabolism-related genes with difference analysis in CRC. Through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, a prognostic model was constructed based on differentially expressed BMRGs. In addition, we discovered an independent prognostic marker for CRC patients. According to the expression levels and coefficients of identified BMRGs, the risk scores of all CRC samples were calculated. Utilizing differentially expressed genes in the high- and low-risk groups, we also constructed a Protein-Protein Interaction (PPI) network to visualize the interactions between proteins. Through the results of PPI network, we screened out differentially expressed target butyrate metabolism-related genes from ten hub genes. Finally, we performed clinical correlation analysis, immune cell infiltration analysis, and mutation analysis for these target genes. One hundred and seventy three differentially expressed butyrate metabolism-related genes were screened out in all the CRC samples. The prognostic model was established with univariate Cox regression and LASSO regression analysis. CRC patients' overall survival was significantly lower in the high-risk group than in the low-risk group for both training and validation set. Among the ten hub genes identified from the PPI network, four target butyrate metabolism-related genes were identified containing FN1, SERPINE1, THBS2, and COMP, which might provide novel markers or targets for treating CRC patients. Eighteen butyrate metabolism-related genes were used to develop a risk prognostic model that could be helpful for doctors to predict CRC patients' survival rate. Using this model, it is beneficial to forecast the response of CRC patients to immunotherapy and chemotherapy, thus making it easier to custom tailor cancer chemotherapy and immunotherapy to the individual patient.

Meta-analysis of platelet-rich plasma therapy for anal fistula.

OBJECTIVE: To systematically evaluate the efficacy of platelet-rich plasma (PRP) in treating anal fistula. METHODS: PubMed, EMBASE, and Cochrane Library databases were systematically searched for randomized controlled studies (RCTs) and case-control studies published before June 2021 on evaluating the efficacy of platelet-rich plasma (PRP) in treating anal fistula. References of the journals were manually searched for relevant studies. Literature search, screening, data extraction, and bias assessment were carried out by two researcher independently. Stata13.0 and RevMan 5.3 software were used for statistical analysis of the cure rate and recurrence rate of anal fistula. RESULTS: A total of 6 case-control studies and 3 RCTs involving 289 patients were included. Meta-analysis showed that the pooled cure rate of all studies was 65% (95% CI 0.53-0.77), p = 0.000, and the pooled recurrence rate of all studies was 12% (95% CI 0.08-0.17). CONCLUSION: Platelet-rich plasma is safe and effective in treating anal fistula and should be promoted and further studied in clinical practice.