Mendelian randomization analysis reveals an independent causal relationship between four gut microbes and acne vulgaris
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ABSTRACT:
SUBMITTER: Wu Y
PROVIDER: S-EPMC10869500 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundAs an inflammatory skin condition, acne usually presents with a complex pathogenesis. Recent studies suggest that BMI may relate to the incidence of acne. Mendelian randomization is a statistical method that is used to evaluate the causal effects of exposure factors on outcome variables.MethodsWe applied the inverse-variance weighted (IVW) method to evaluate the causal effect as the primary analysis between BMI and acne in our two-sample Mendelian randomization study. We included 58 SNPs accounting for 2.5% (R2) of the BMI variation as instrumental variables (IVs) for BMI-acne causal estimations.ResultThe F-statistic obtained from the first stage of the MR regression model was 61. Importantly, the results from all three methods consistently indicated that an increase in BMI did not elevate the risk of acne, with each result reaching statistical significance. Cochran's Q test revealed no evidence of heterogeneity among the IV estimates for individual variants. Our I2 values suggested low heterogeneity, thereby reinforcing the reliability of the MR estimates. Additionally, the "leave-one-out" analysis confirmed that no single SNP disproportionately affected the IVW point estimate.ConclusionOur findings suggested that there is no causal relationship between BMI and acne.
| S-EPMC11877415 | biostudies-literature
Project description:Acne is a prevalent inflammatory disease in dermatology, and its pathogenesis may be associated with inflammation, immunity, and other mechanisms. It commonly manifests in young individuals and frequently imposes a heavy economic, physical, and psychological burden on patients. Gut microbes and blood metabolites, as significant immune and inflammatory regulators in the body, have been hypothesized to form the "neurocutaneous axis." Nonetheless, the precise causal relationships among the gut microbes, circulating blood metabolites, and acne development have yet to be elucidated. This study employed bidirectional two-sample Mendelian randomization (MR) to probe the causal impacts of 412 distinct gut microbes and 249 blood metabolites on acne. Single nucleotide polymorphisms (SNPs), which are closely associated with gut microbes and blood metabolites, were utilized as instrumental variables. This approach was taken to discern whether these elements serve as pathogenic or protective factors in relation to acne. Furthermore, a mediation analysis encompassing gut microbes, blood metabolites, and acne was conducted to explore potential correlations between gut microbes and blood metabolites, as well as their cumulative effects on acne. This was done to substantiate the notion of causality. Bidirectional two-sample MR analysis revealed 8 gut bacteria, 6 bacterial metabolic abundance pathways determined by birdshot, and 8 blood metabolites significantly associated with acne. The mediation MR analysis revealed 2 potential causal relationships, namely, Bifidobacterium-DHA-Acne and Bifidobacterium-Degree of Unsaturation-Acne. This study identified gut microbes and blood metabolites that are causally associated with acne. A potential causal relationship between gut microbes and blood metabolites was obtained via mediation analysis. These insights pave the way for the identification of new targets and the formulation of innovative approaches for the prevention and treatment of acne.
| S-EPMC11538280 | biostudies-literature
Project description: Not available
| S-BSST1516 | biostudies-other
Project description:BackgroundAcne is a common skin disorder that may be linked to metabolic dysfunction. However, the causal impact of blood metabolites on acne has not been thoroughly investigated.MethodsWe performed a metabolome-wide Mendelian randomization (MR) analysis on 486 blood metabolites and acne using a genome-wide association dataset. The study included preliminary inverse-variance weighted (IVW) analysis, multivariable MR analysis, linkage disequilibrium score (LDSC) analysis, and colocalization analysis, along with reverse MR to address potential reverse causation.ResultsOur analysis identified 12 metabolites significantly associated with acne. LDSC analysis revealed a genetic correlation between nonanoylcarnitine and acne. Colocalization analysis confirmed shared genetic variants, and metabolic pathway analysis implicated the arginine biosynthesis pathway and the selenocompound metabolism pathway in the development of acne.ConclusionThis study offers a comprehensive understanding of the causal relationships between plasma metabolites and acne. The findings provide insights into potential biomarkers and therapeutic targets for acne treatment, underscoring the need for further research.
| S-EPMC11686570 | biostudies-literature
Project description:BackgroundNumerous pertinent investigations have demonstrated a correlation between gut microflora (GM) and the occurrence of dementia. However, a causal connection between GM and dementia and its subtypes has not yet been clarified.ObjectiveTo explore the causal association between GM and dementia, including its subtypes, a two-sample Mendelian randomization (TSMR) analysis was used.MethodsOur data comes from the Genome-Wide Association Study (GWAS). The principal approach employed for the Mendelian randomization study was the inverse-variance weighted method, supplemented by four methods: MR-Egger, weighted median, simple mode, and weighted mode. This was followed by Cochrane's Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out as sensitivity analysis validation.ResultsTwenty-one GMs associated with any dementia, Alzheimer's disease, vascular dementia, Lewy body dementia, Parkinson's disease, and dementia under other disease classifications were derived from the analysis, and 21 passed sensitivity tests.ConclusionWe confirmed the causal relationship between GM and dementia and its subtypes, derived specific flora associated with increased or decreased risk of dementia, and provided new ideas for preventive, diagnostic, and therapeutic interventions for dementia mediated by gut microbiota.
| S-EPMC10822966 | biostudies-literature
Project description: Not available
| S-EPMC10507220 | biostudies-literature
Project description:BackgroundPrevious observational studies regarding the relationship between acne and prostate cancer have reported inconsistent results. As such studies are prone to biases, we conducted this Mendelian randomization (MR) analysis to better explore the causal association between acne and prostate cancer.MethodsThe genetic data for assessing acne were acquired from the largest genome-wide association study (GWAS) of acne by far, and the genetic data for assessing prostate cancer were acquired from the FinnGen consortium, UK Biobank, European Bioinformatics Institute, and IEU OpenGWAS project. We performed two-sample MR analyses using data from these GWASs followed by a meta-analysis to provide an overall evaluation. The primary MR methods used included inverse variance weighted, MR-Egger, and weighted median. Leave-one-out sensitivity tests, Cochran's Q tests, and MR-Egger intercept tests were used to bolster the robustness of the MR results.ResultsThrough MR combined with meta-analysis, our study found no genetic causal relationship between acne and prostate cancer (p=0.378; odds ratio=0.985; 95% confidence interval, 0.954-1.018). Sensitivity tests ensured the robustness of this result.ConclusionAcne should not be considered as a morbidity hazard factor for prostate cancer.
| S-EPMC11446721 | biostudies-literature
Project description:BackgroundPatients with DN (diabetic nephropathy) show remarkable variations in their gut microbiota composition. However, to date, no study has shown whether a causal relationship exists between gut microbiota composition and DN.MethodsHere, we performed a two-sample Mendelian randomization (MR) investigation for identifying causal associations of gut microbiota with DN. Gut microbiota genetic data were gathered from the recent genome-wide association study pooled data of the MiBioGen consortium, which included 24 cohorts and 18,340 individuals.ResultsIVW(Inverse variance weighting) revealed that Verrucomicrobia [odds ratio (OR) = 1.390; 95% confidence interval (CI) = 1.10-1.75; p = 0.005], Peptostreptococcaceae (OR = 1.284; 95% CI = 1.03-1.59; p = 0.012), Verrucomicrobiaceae (OR = 1.390; 95% CI = 1.10-1.75; p = 0.005), Akkermansia (OR = 1.390; 95% CI = 1.10-1.75; p = 0.005), Butyricimonas (OR = 1.261; 95% CI = 1.02-1.55; p = 0.031), Catenibacterium (OR = 1.278; 95% CI = 1.02-1.59; p = 0.030).ConclusionTwo-sample MR analysis identified 12 microbial taxa in gut microbiota (one of which is yet to be officially named) that showed significant causal associations with DN; 8 of these taxa significantly increased the risk of DN, while the remaining 4 taxa (including the one without an official name) reduced the risk of DN. The precise mechanisms influencing the interactions of gut microbiota with DN occurrence remain unclear; hence, additional investigations should be conducted to clarify these mechanisms.
| S-EPMC10792041 | biostudies-literature
Project description:BackgroundChildhood obesity (CO) is an increasing public health issue. Mounting evidence has shown that gut microbiota (GM) is closely related to CO. However, the causal association needs to be treated with caution due to confounding factors and reverse causation.MethodsData were obtained from the Microbiome Genome Consortium for GM as well as the Early Growth Genetics Consortium for childhood obesity and childhood body mass index (CBMI). Inverse variance weighted, maximum likelihood, weighted median, and MR.RAPS methods were applied to examine the causal association. Then replication dataset was used to validate the results and reverse Mendelian randomization analysis was performed to confirm the causal direction. Additionally, sensitivity analyses including Cochran's Q statistics, MR-Egger intercept, MR-PRESSO global test, and the leave-one-out analysis were conducted to detect the potential heterogeneity and horizontal pleiotropy.ResultsOur study found suggestive causal relationships between eight bacterial genera and the risk of childhood obesity (five for CO and four for CBMI). After validating the results in the replication dataset, we finally identified three childhood obesity-related GM including the genera Akkermansia, Intestinibacter, and Butyricimonas. Amongst these, the genus Akkermansia was both negatively associated with the risk of CO (OR = 0.574; 95% CI: 0.417, 0.789) and CBMI (β = -0.172; 95% CI: -0.306, -0.039).ConclusionsIn this study, we employed the MR approach to investigate the causal relationship between GM and CO, and discovered that the genus Akkermansia has a protective effect on both childhood obesity and BMI. Our findings may provide a potential strategy for preventing and intervening in CO, while also offering novel insights into the pathogenesis of CO from the perspective of GM.
| S-EPMC10427879 | biostudies-literature
Project description:BackgroundRecent research increasingly highlights a strong correlation between gut microbiota and the risk of gastrointestinal diseases. However, whether this relationship is causal or merely coincidental remains uncertain. To address this, a Mendelian randomization (MR) analysis was undertaken to explore the connections between gut microbiota and prevalent gastrointestinal diseases.MethodsGenome-wide association study (GWAS) summary statistics for gut microbiota, encompassing a diverse range of 211 taxa (131 genera, 35 families, 20 orders, 16 classes, and 9 phyla), were sourced from the comprehensive MiBioGen study. Genetic associations with 22 gastrointestinal diseases were gathered from the UK Biobank, FinnGen study, and various extensive GWAS studies. MR analysis was meticulously conducted to assess the causal relationship between genetically predicted gut microbiota and these gastrointestinal diseases. To validate the reliability of our findings, sensitivity analyses and tests for heterogeneity were systematically performed.ResultsThe MR analysis yielded significant evidence for 251 causal relationships between genetically predicted gut microbiota and the risk of gastrointestinal diseases. This included 98 associations with upper gastrointestinal diseases, 81 with lower gastrointestinal diseases, 54 with hepatobiliary diseases, and 18 with pancreatic diseases. Notably, these associations were particularly evident in taxa belonging to the genera Ruminococcus and Eubacterium. Further sensitivity analyses reinforced the robustness of these results.ConclusionsThe findings of this study indicate a potential genetic predisposition linking gut microbiota to gastrointestinal diseases. These insights pave the way for designing future clinical trials focusing on microbiome-related interventions, including the use of microbiome-dependent metabolites, to potentially treat or manage gastrointestinal diseases and their associated risk factors.
| S-EPMC10804519 | biostudies-literature