Examining the causal association between psoriasis and bladder cancer: A two-sample Mendelian randomization analysis

The causal relationship between androgenetic alopecia and serum uric acid: A bidirectional Mendelian randomization analysis

BACKGROUND

Despite numerous studies investigating the association between androgenetic alopecia (AGA) and serum uric acid (SUA), the causal relationship between AGA and SUA remains unknown.

METHODS

We utilized bidirectional Mendelian randomization (MR) to explore the causality between AGA and SUA. Our study chose single nucleotide polymorphisms associated with genome-wide significance (p < 5×10-8) for the exposure and showing low linkage disequilibrium (R2 < 0.001) as IVs. Various MR methods were employed to evaluate causality, including inverse-variance weighted (IVW), Weighted Median, MR-Egger, Weighted Mode and Simple Mode. Sensitivity analyses were performed to test the robustness of the results.

RESULTS

Using the IVW method, we did not find a significant causal relationship between AGA and SUA (OR = 1.00, 95% CI 0.99-1.01; p = 0.451). Similarly, the IVW method did not reveal evidence of causality between SUA and AGA (OR = 0.97, 95% CI = 0.91-1.03; p = 0.301). The results from other methods were consistent with those of the IVW approach.

CONCLUSION

The study did not identify a causal relationship between AGA and SUA. Future research should involve larger cohorts and advanced methods to validate the findings and explore the complex interactions between AGA and SUA levels in different populations.

Revealing an association between HPV and systemic lupus erythematosus: A bidirectional two-sample Mendelian randomization study

BACKGROUND

An increasing number of studies have focused on the association between Human papillomavirus (HPV) infection and systemic lupus erythematosus (SLE). However, current evidence is largely based on retrospective studies, which are susceptible to confounding factors and cannot establish causation.

METHODS

A bidirectional two-sample Mendelian randomization (MR) design was used to evaluate the causal relationship between HPV and SLE. Mononucleoside polymers (SNPS) with strong evidence for genome-wide association studies (GWAS) were selected from the HPV exposure dataset and used as an instrumental variable (IV) for this study. For the MR Analysis results, the MR-Egger intercept P test, MR-Presso global test, CochranQ test and leave-one test were used for sensitivity analysis.

RESULTS

Based on the evidence of MR Analysis, this study finally determined that there was no causal association between HPV16 and HPV18 and SLE.

CONCLUSIONS

Possible regulation of HPV infection is not significantly associated with regulation of SLE. These findings provide new insights into the underlying mechanisms of HPV and SLE and need to be validated by further studies.

New evidence that vitamin D prevents headache: a bidirectional two-sample Mendelian randomization analysis

BACKGROUND

Previous observational clinical studies and meta-analyses have yielded inconsistent results regarding the relationship between vitamin D and headache, and the causal relationship remains unclear. The aim of this study was to investigate the causal relationship between vitamin D and headache by bidirectional two-sample Mendelian randomisation (MR) analysis.

METHODS

The relationship between high levels of vitamin D and headache was investigated by two-sample MR analysis using publicly available genome-wide association study (GWAS) data. The primary method was inverse variance weighting (IVW), and secondary methods were weighted median and MR-Egger methods. No heterogeneity or horizontal multidirectionality was found in the MR results. The robustness and validity of the findings were assessed using the leave-behind method.

RESULTS

A significant causal relationship was found between high vitamin D levels and headache using the IVW method (OR = 0.848; p = 0.007; 95% CI = 0.752-0.956). However, in a reverse analysis, no evidence of a causal relationship between headache and high levels of vitamin D was found using the IVW method (OR = 1.001; p = 0.906; 95% CI = 0.994-1.006). Our MR analyses showed no significant horizontal multidimensionality or heterogeneity (p > 0.05). Sensitivity analyses confirmed that MR estimates were not affected by single nucleotide polymorphisms (SNPs). Confirmation that our results are robust and valid has been obtained by the leave-one-out method.

CONCLUSION

Our study suggests that high levels of vitamin D prevent the risk of headache. However, there is no evidence of a causal relationship between headache and high levels of vitamin D. Vitamin D may reduce the risk of headache.

Metagenomics reveals unique gut mycobiome biomarkers in psoriasis

PURPOSE

In present, the diagnosis of psoriasis is mainly based on the patient's typical clinical manifestations, dermoscopy and skin biopsy, and unlike other immune diseases, psoriasis lacks specific indicators in the blood. Therefore, we are required to search novel biomarkers for the diagnosis of psoriasis.

METHODS

In this study, we analyzed the composition and the differences of intestinal fungal communities composition between psoriasis patients and healthy individuals in order to find the intestinal fungal communities associated with the diagnosis of psoriasis. We built a machine learning model and identified potential microbial markers for the diagnosis of psoriasis.

RESULTS

The results of AUROC (area under ROC) showed that Aspergillus puulaauensis (AUROC = 0.779), Kazachstania africana (AUROC = 0.750) and Torulaspora delbrueckii (AUROC = 0.745) had high predictive ability (AUROC > 0.7) for predicting psoriasis, While Fusarium keratoplasticum (AUROC = 0.670) was relatively lower (AUROC < 0.7).

CONCLUSION

The strategy based on the prediction of intestinal fungal communities provides a new idea for the diagnosis of psoriasis and is expected to become an auxiliary diagnostic method for psoriasis.

Causal relationship between inflammatory skin diseases and breast cancer: A bidirectional Mendelian randomization study

INTRODUCTION

Prior research has explored the relationship between inflammatory skin disorders and breast cancer (BC), yet the causality of this association remains uncertain.

METHODS

Utilizing a bidirectional two-sample Mendelian randomization (MR) approach, this study aimed to elucidate the causal dynamics between various inflammatory skin conditions-namely acne, atopic dermatitis, psoriasis vulgaris, urticaria, and rosacea-and BC. Genetic variants implicated in these disorders were sourced from comprehensive genome-wide association studies representative of European ancestry. In the forward MR, BC was posited as the exposure, while the reverse MR treated each inflammatory skin disease as the exposure. A suite of analytical methodologies, including random effects inverse variance weighted (IVW), weighted median (WME), and MR-Egger, were employed to probe the causative links between inflammatory skin diseases and BC. Sensitivity analyses, alongside evaluations for heterogeneity and pleiotropy, were conducted to substantiate the findings.

RESULTS

The MR analysis revealed an increased risk of acne associated with BC (IVW: OR = 1.063, 95% CI = 1.011-1.117, p = 0.016), while noting a decreased risk of atopic dermatitis (AD) in BC patients (IVW: OR = 0.941, 95% CI = 0.886-0.999, p = 0.047). No significant associations were observed between BC and psoriasis vulgaris, urticaria, or rosacea. Conversely, reverse MR analyses detected no effect of BC on the incidence of inflammatory skin diseases. The absence of pleiotropy and the consistency of these outcomes strengthen the study's conclusions.

CONCLUSION

Findings indicate an elevated incidence of acne and a reduced incidence of AD in individuals with BC within the European population.

Genetic causal relationship between gut microbiota and basal cell carcinoma: A two-sample mendelian randomization study

OBJECTIVE

Research has previously established connections between the intestinal microbiome and the progression of some cancers. However, there is a noticeable gap in the literature in regard to using Mendelian randomisation (MR) to delve into potential causal relationships between the gut microbiota (GM) and basal cell carcinoma (BCC). Therefore, the purpose of our study was to use MR to explore the causal relationship between four kinds of GM (Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae) and BCC.

METHODS

We used genome-wide association study (GWAS) data and MR to explore the causal relationship between four kinds of GM and BCC. This study primarily employed the random effect inverse variance weighted (IVW) model for analysis, as complemented by additional methods including the simple mode, weighted median, weighted mode and MR‒Egger methods. We used heterogeneity and horizontal multiplicity to judge the reliability of each analysis. MR-PRESSO was mainly used to detect and correct outliers.

RESULTS

The random-effects IVW results showed that Bacteroides (OR = 0.936, 95% CI = 0.787-1.113, p = 0.455), Streptococcus (OR = 0.974, 95% CI = 0.875-1.083, p = 0.629), Proteobacteria (OR = 1.113, 95% CI = 0.977-1.267, p = 0.106) and Lachnospiraceae (OR = 1.027, 95% CI = 0.899-1.173, p = 0.688) had no genetic causal relationship with BCC. All analyses revealed no horizontal pleiotropy, heterogeneity or outliers.

CONCLUSION

We found that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae do not increase the incidence of BCC at the genetic level, which provides new insight for the study of GM and BCC.

The causal relationship between atopic dermatitis and brain cancer: A bidirectional Mendelian randomization study

BACKGROUND

Atopic dermatitis ranks among the prevalent skin disorders. Research has indicated a potential association with brain cancer. Yet, establishing a direct causal relationship between atopic dermatitis and brain cancer continues to be challenging.

MATERIALS AND METHODS

We extracted single nucleotide polymorphisms (SNPs) significantly associated with atopic dermatitis (sample size = 382 254) at a genome-wide level from a large Finnish Genome-Wide Association Study (GWAS) dataset (n cases = 15 208, n controls = 367 046). Summary data for 372 622 cases of brain cancer (n cases = 606, n controls = 372 016) were obtained via the IEU Open GWAS database. We employed the Inverse Variance Weighted (IVW) method as our primary analytical approach for Mendelian Randomization (MR) analysis. Additionally, heterogeneity was measured using Cochran's Q value, and horizontal pleiotropy was evaluated using MR-Egger 、Mendelian Randomization Pleiotropy RESidual Sum and Outlier and leave-one-out analyses.

RESULTS

The risk of brain cancer increases with the presence of atopic dermatitis, as evidenced by the odds ratios (ORs) and 95% confidence intervals (CIs),(OR = 1.0005; 95% CI = 1.0001, 1.0009; p = 0.0096). However, when conducting the analysis in reverse, no significant link was observed.

CONCLUSION

The findings from our study indicate a causative link between atopic dermatitis and brain cancer, highlighting the importance of conducting broader clinical investigations into their potential association going forward.