Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add more filters










Database
Language
Publication year range
1.
Immun Inflamm Dis ; 12(7): e1328, 2024 Jul.
Article in English | MEDLINE | ID: mdl-39031512

ABSTRACT

BACKGROUND: Studies have indicated a close association between dysbiosis of the gut microbiota and chronic sinusitis. However, the causal relationship between the gut microbiota and the risk of chronic sinusitis remains unclear. METHODS: Using genome-wide association study (GWAS) data for the gut microbiota and chronic sinusitis, we conducted a two-sample Mendelian randomization (MR) study to determine the potential causal relationship between the microbiota and chronic sinusitis. We employed the inverse variance-weighted (IVW) method as the primary analytical approach to estimate the effect. Additionally, sensitivity, heterogeneity, and pleiotropy analyses were conducted to evaluate the robustness of the results. Reverse MR analysis was also applied to investigate potential reverse causality. RESULTS: Through MR analysis, we identified 17 gut microbiota classifications that are closely associated with chronic sinusitis. However, after Bonferroni multiple correction, only class Bacilli (odds ratio: 0.785, 95% confidence interval: 0.677-0.911, p = .001, false discovery rate = 0.023) maintained a significant causal negative relationship with chronic sinusitis. Sensitivity analysis did not reveal any evidence of heterogeneity or horizontal pleiotropy. Reverse MR analysis found five gut microbiota classifications that are significantly associated with chronic sinusitis, but they were no longer significant after Bonferroni multiple correction. There was no evidence to suggest a reverse causal relationship between chronic sinusitis and class Bacilli. CONCLUSION: Specific gut microbiota predicted by genetics exhibit a potential causal relationship with chronic sinusitis, and class Bacilli may have a protective effect on chronic sinusitis.


Subject(s)
Gastrointestinal Microbiome , Genome-Wide Association Study , Mendelian Randomization Analysis , Sinusitis , Humans , Sinusitis/microbiology , Gastrointestinal Microbiome/genetics , Chronic Disease , Dysbiosis/microbiology , Polymorphism, Single Nucleotide
2.
Front Neurol ; 15: 1400557, 2024.
Article in English | MEDLINE | ID: mdl-38903171

ABSTRACT

Background: Currently, effective therapeutic drugs for age-related macular degeneration (AMD) are urgently needed, and it is crucial to explore new treatment targets. The proteome is indispensable for exploring disease targets, so we conducted a Mendelian randomization (MR) of the proteome to identify new targets for AMD and its related subtypes. Methods: The plasma protein level data used in this study were obtained from two large-scale studies of protein quantitative trait loci (pQTL), comprising 35,559 and 54,219 samples, respectively. The expression quantitative trait loci (eQTL) data were sourced from eQTLGen and GTEx Version 8. The discovery set for AMD data and subtypes was derived from the FinnGen study, consisting of 9,721 AMD cases and 381,339 controls, 5,239 wet AMD cases and 273,920 controls, and 6,651 dry AMD cases and 272,504 controls. The replication set for AMD data was obtained from the study by Winkler TW et al., comprising 14,034 cases and 91,234 controls. Summary Mendelian randomization (SMR) analysis was employed to assess the association between QTL data and AMD and its subtypes, while colocalization analysis was performed to determine whether they share causal variants. Additionally, chemical exploration and molecular docking were utilized to validate potential drugs targeting the identified proteins. Results: SMR and colocalization analysis jointly identified risk-associated proteins for AMD and its subtypes, including 5 proteins (WARS1, BRD2, IL20RB, TGFB1, TNFRSF10A) associated with AMD, 2 proteins (WARS1, IL20RB) associated with Dry-AMD, and 9 proteins (COL10A1, WARS1, VTN, SDF2, LBP, CD226, TGFB1, TNFRSF10A, CSF2) associated with Wet-AMD. The results revealed potential therapeutic chemicals, and molecular docking indicated a good binding between the chemicals and protein structures. Conclusion: Proteome-wide MR have identified risk-associated proteins for AMD and its subtypes, suggesting that these proteins may serve as potential therapeutic targets worthy of further clinical investigation.

3.
Auris Nasus Larynx ; 51(2): 365-370, 2024 Apr.
Article in English | MEDLINE | ID: mdl-37993362

ABSTRACT

OBJECTIVE: While numerous observational studies have indicated an association between lipids and Sudden Sensorineural Hearing Loss (SSNHL), it remains uncertain whether dyslipidemia serves as a causal risk factor for SSNHL. Our objective is to elucidate the potential causal relationship between lipid levels and SSNHL through Mendelian randomization analysis. METHODS: The primary and secondary lipid data used in this study were sourced from the UK Biobank (UKBB) and the Global Lipid Genetics Consortium results (GLGC), respectively. These datasets were obtained from large, publicly available genome-wide association studies (GWAS). The outcome data for sudden sensorineural hearing loss (SSNHL) were acquired from the Finnegan Biobank, consisting of 1491 cases and 196,592 controls. Subsequently, both single-variable Mendelian randomization (SVMR) and multivariate Mendelian randomization (MVMR) methods were employed to evaluate the causal relationship between lipids and the occurrence of SSNHL. RESULTS: Among the primary lipid data, SVMR analysis showed a significant correlation between high density lipoprotein cholesterol (HDL-C) (OR: 0.822, 95 %CI: 0.694-0.974, p = 0.023) and SSNHL, and triglycerides (TG) (OR: 0.997, 95 %CI: 0.836-1.188, p = 0.975), low density lipoprotein cholesterol (LDL-C) (OR: 1.067, 95 %CI: 0.861-1.322, p = 0.552) did not correlate with SSNHL. In the secondary lipid data, SVMR analysis showed that HDL-C (OR: 0.987, 95 %CI: 0.805-1.210, p = 0.903), TG (OR: 0.991, 95 %CI: 0.787-1.246, p = 0.937) and LDL-C (OR: 1.092, 95 % CI: 0.926-1.287, p = 0.294) did not correlate with SSNHL. MVMR analysis of the primary lipid data showed that HDL-cholesterol (OR: 0.755, 95 % CI: 0.596-0.956, p = 0.019) was significantly associated with SSNHL, while TG (OR: 0.808, 95 %CI: 0.611-1.068, p = 0.134) and LDL-C (OR: 1.146, 95 %CI: 0.869-1.511, p = 0.333) did not correlate with SSNHL, consistent with the results of SVMR. Inverse MR results showed that SSNHL did not correlate with TG (OR: 0.999, 95 %CI: 0.997-1.001, p = 0.835), HDL-C (OR: 1.001, 95 %CI: 0.998-1.003), LDL-C (OR: 0.999, 95 %CI: 0.997-1.002, p = 0.863). CONCLUSIONS: Mendelian randomization (MR) results suggest that decreased serum HDL-C levels are an independent risk factor for SSNHL. Monitoring and focusing on lipid levels may be of value in the prevention and treatment of SSNHL.


Subject(s)
Hearing Loss, Sensorineural , Mendelian Randomization Analysis , Humans , Cholesterol, LDL/genetics , Genome-Wide Association Study , Triglycerides , Risk Factors , Cholesterol, HDL/genetics , Hearing Loss, Sensorineural/genetics , Polymorphism, Single Nucleotide
SELECTION OF CITATIONS
SEARCH DETAIL
...