Association of atopic dermatitis with autoimmune diseases: A bidirectional and multivariable two-sample mendelian randomization study

The relationship between autoimmune disorders and intracranial aneurysms in East Asian and European populations: a bidirectional and multivariable two-sample Mendelian randomization study

Background

It remains unclear about the pathogenesis of intracranial aneurysms (IAs) in the setting of autoimmune disorders (ADs). However, the underlying systemic inflammatory characteristics of ADs may affect IAs through shared inflammatory pathways. Therefore, this study was conducted to explore the relationship between ADs and IAs and assess causal effects.

Methods

In this study, 6 common ADs were included to explore their causal relationship with IAs. Besides, a bidirectional two-sample univariable Mendelian randomization (UVMR) analysis was performed. In addition, the primary analysis was performed by the inverse variance weighted (IVW) and Bayesian weighted Mendelian randomization (BWMR) method, and a series of sensitivity analyses were performed to assess the robustness of the results. Further, the data related to ADs and IAs were collected from open genome-wide association study studies (GWASs) and the Cerebrovascular Disease Knowledge Portal (CDKP) (including 11,084 cases and 311,458 controls), respectively. These analyses were conducted based on both the East Asian and European populations. Moreover, 6 ADs were subject to grouping according to connective tissue disease, inflammatory bowel disease, and thyroid disease. On that basis, a multivariate MR (MVMR1) analysis was further performed to explore the independent causal relationship between each AD and IAs, and an MVMR 2 analysis was conducted to investigate such potential confounders as smoking, alcohol consumption, and systolic blood pressure. Finally, these results were verified based on the data from another GWAS of IAs.

Results

The UVMR analysis results demonstrated that systemic lupus erythematosus (SLE) was associated with a high risk of IAs in the East Asian population (IVW OR, 1.06; 95%CI, 1.02-1.11; p = 0.0065, UVMR), which was supported by the results of BWMR (OR, 1.06; 95%CI, 1.02-1.11; p = 0.0067, BWMR), MVMR1 (OR, 1.06; 95%CI, 1.01-1.10; p = 0.015, MVMR1), MVMR2 (OR, 1.05; 95%CI, 1.00-1.11; p = 0.049, MVMR2), and sensitivity analyses. The results in the validation group also suggested a causal relationship between SLE and IAs (IVW OR, 1.04; 95% CI, 1.00-1.09; p = 0.046). The reverse MR analysis results did not reveal a causal relationship between IAs and ADs.

Conclusion

In this MR study, SLE was validated to be a risk factor for IAs in the East Asian population. Therefore, the management of IAs in patients with SLE should be highlighted to avoid stroke events.

Interplay between diabetes mellitus and atopic dermatitis

Inflammatory dermatoses such as atopic dermatitis (AD) have long been linked to the pathogenesis of diabetes mellitus. Indeed, numerous studies show an increased risk of diabetes mellitus in individuals with AD although lower prevalence of diabetes mellitus is also observed in few studies. Though the underlying mechanisms accounting for the reciprocal influence between these two conditions are still unclear, the complex interplay between diabetes mellitus and AD is attributable, in part, to genetic and environmental factors, cytokines, epidermal dysfunction, as well as drugs used for the treatment of AD. Proper management of one condition can mitigate the other condition. In this review, we summarize the evidence of the interaction between diabetes mellitus and AD, and discuss the possible underlying mechanisms by which these two conditions influence each other.

Psychological Distress and Meniere's Disease: A Bidirectional Two-Sample Mendelian Randomization Study

OBJECTIVE

This study is aim to explore the causal relationship between anxiety, depression, neuroticism, and Meniere's disease (MD).

STUDY DESIGN

Two-sample bidirectional Mendelian randomization (MR) analyses.

SETTING

IEU, FinnGen, CTG, and UKB databases.

METHODS

The genome-wide association studies data for anxiety, depression, neuroticism, and MD involved over 357,957 participants. MR was performed to explore relationships between anxiety, depression, neuroticism, and MD. Sensitivity analyses were performed to assess the robustness of the MR results. Reverse MR was used to exclude the possibility of reverse causality. Finally, multivariate MR was performed to explore the collinear relationships between neuroticism subclusters.

RESULTS

MR results showed that anxiety and depression are not causes of MD, nor does MD cause anxiety and depression. Elevated neuroticism sum score is a cause of anxiety, depression, and MD, but MD does not lead to an increase in the level of neuroticism sum score. Further analysis showed that the 5 subclusters of neuroticism often feel lonely, mood often goes up and down, often feel fed-up, feelings easily hurt, and sensitivity to environmental stress and adversity are causes of MD. Multivariate MR analysis results suggested that the 5 neuroticism subclusters have a collinear relationship.

CONCLUSION

Anxiety and depression are not causative factors of MD, and vice versa. Elevated neuroticism levels serve as a shared causative factor for anxiety, depression, and MD. Identification and effective management of neuroticism is a potential target for preventing and treating MD.

Prevalence of Severe Atopic Dermatitis and Comorbid Chronic Systemic Diseases Is Increasing in Korean Children and Adolescents

Severe atopic dermatitis (AD) is not a localized cutaneous disease, but a systemic disease that often accompanies comorbidities. In this nationwide population-based study, we aimed to analyze the prevalence of severe AD and chronic systemic diseases in Koreans aged ≤ 20 years between 2011 and 2019 using the data from the Korean Health Insurance Review and Assessment Service. Total AD and severe AD were defined according to the International Classification of Diseases-10 code L20. In children aged 6-20 years, the prevalence of severe AD significantly increased from 0.02% in 2011 to 0.04% in 2019 (P for trend < 0.001), with the ratio of severe AD to total AD increasing from 0.76% in 2011 to 1.10% in 2019 (P for trend < 0.001). The prevalence rates of severe AD significantly increased between 2011 and 2019 in children aged 6-12 years (P for trend < 0.05) and 13-18 years (P for trend < 0.001). Severe AD was more frequently found in males than in females each year (all P < 0.001, from 2011 to 2019). During the period from 2011 to 2019, the prevalence rate of chronic systemic diseases was higher in subjects with severe AD than in those without AD (P < 0.001) or with mild-to-moderate AD (P < 0.001). In conclusion, our results suggest that the prevalence of severe AD is increasing in Korean children and adolescents and is higher in males and older age groups. Moreover, severe AD is associated with chronic systemic diseases. Therefore, more attention should be paid to managing severe AD.

Multi-Omics Approach to Improved Diagnosis and Treatment of Atopic Dermatitis and Psoriasis

Psoriasis and atopic dermatitis fall within the category of cutaneous immune-mediated inflammatory diseases (IMIDs). The prevalence of IMIDs is increasing in industrialized societies, influenced by both environmental changes and a genetic predisposition. However, the exact immune factors driving these chronic, progressive diseases are not fully understood. By using multi-omics techniques in cutaneous IMIDs, it is expected to advance the understanding of skin biology, uncover the underlying mechanisms of skin conditions, and potentially devise precise and personalized approaches to diagnosis and treatment. We provide a narrative review of the current knowledge in genomics, epigenomics, and proteomics of atopic dermatitis and psoriasis. A literature search was performed for articles published until 30 November 2023. Although there is still much to uncover, recent evidence has already provided valuable insights, such as proteomic profiles that permit differentiating psoriasis from mycosis fungoides and β-defensin 2 correlation to PASI and its drop due to secukinumab first injection, among others.

The Causal Relationship Between Gastroesophageal Reflux Disease and Chronic Obstructive Pulmonary Disease: A Bidirectional Two-Sample Mendelian Randomization Study

Background

Gastroesophageal reflux disease (GERD) and Chronic Obstructive Pulmonary Disease (COPD) often coexist and have been associated in observational studies. However, the real potential causal relationship between GERD and COPD is unknown and not well established.

Methods

In this study, we conducted a bidirectional two-sample Mendelian randomization(MR) to estimate whether GERD and COPD are causal. The GERD genetic data is from summary level data of a genome-wide association (GWAS) meta-analysis (Ncases = 71,522, Ncontrol=26,079). The COPD GWAS are available from the FinnGen (Ncases=16,410, Ncontrol=283,589). MR-Egger regression, Weighted Median, and Inverse-variance weighted (IVW) were used for MR analysis from the R package "TwoSampleMR", and IVW was the dominant estimation method. Additionally, the MR pleiotropy residual sum and outlier (MR-PRESSO), Cochran Q statistic, and leave-one-out analysis were used to detect and correct for the effect of heterogeneity and horizontal pleiotropy.

Results

MR analysis indicated that GERD was causally associated with an increased risk of COPD (IVW odds ratio (OR): 1.3760, 95% confidence interval (CI): 1.1565-1.6371, P=0.0003), and vice versa (IVW OR: 1.1728, 95% CI:1.0613-1.2961, P=0.0018). The analyses did not reveal any pleiotropy or heterogeneity.

Conclusion

Our study revealed possible evidence for a bidirectional causal relationship between GERD and COPD. Implementing screening and preventive strategies for GERD in individuals with COPD, and vice versa, will be crucial in future healthcare management. Further studies are needed to elucidate the mechanisms underlying the causal relationship between GERD and COPD.

Toward Precision Medicine in Atopic Dermatitis Using Molecular-Based Approaches

Atopic dermatitis is the most common chronic inflammatory skin disorder, affecting up to 20% of children and 10% of adults in developed countries. The pathophysiology of atopic dermatitis is complex and involves a strong genetic predisposition and T-cell driven inflammation. Although our understanding of the pathology and drivers of this disease has improved in recent years, there are still knowledge gaps in the immune pathways involved. Therefore, advances in new omics technologies in atopic dermatitis will play a key role in understanding the pathogenesis of this burden disease and could develop preventive strategies and personalized treatment strategies. In this review, we discuss the latest developments in genetics, transcriptomics, epigenomics, proteomics, and metagenomics and understand how integrating multiple omics datasets will identify potential biomarkers and uncover nets of associations between several molecular levels.

Toward Precision Medicine in Atopic Dermatitis Using Molecular-Based Approaches

Atopic dermatitis is the most common chronic inflammatory skin disorder, affecting up to 20% of children and 10% of adults in developed countries. The pathophysiology of atopic dermatitis is complex and involves a strong genetic predisposition and T-cell driven inflammation. Although our understanding of the pathology and drivers of this disease has improved in recent years, there are still knowledge gaps in the immune pathways involved. Therefore, advances in new omics technologies in atopic dermatitis will play a key role in understanding the pathogenesis of this burden disease and could develop preventive strategies and personalized treatment strategies. In this review, we discuss the latest developments in genetics, transcriptomics, epigenomics, proteomics, and metagenomics and understand how integrating multiple omics datasets will identify potential biomarkers and uncover nets of associations between several molecular levels.

Rheumatoid arthritis and gastroesophageal reflux disease: a bidirectional and multivariable two-sample Mendelian randomization study

Aims/hypothesis: The association between gastroesophageal reflux disease (GERD) and rheumatoid arthritis (RA) has been reported by many observational studies in the Asian population. This study aimed to examine the bidirectional causal effects between GERD and RA by two-sample Mendelian randomization (MR) analyses using genetic evidence. Methods: Two-sample Mendelian randomization analyses were performed to determine the causal effect of GERD (129,080 cases vs. 602,604 control participants) on RA (6,236 cases vs. 147,221 control participants) and RA on GERD, respectively. The inverse-variance weighted (IVW) method was used as the primary analysis. Weighted median and MR-Egger regression were taken as supplementary analyses. Cochran's Q test evaluated the heterogeneity. Horizontal pleiotropy was detected by estimating the intercept term of MR-Egger regression. Furthermore, multivariable MR analyses were performed to exclude the influence of confounding factors, including the years of schooling, BMI, and time spent watching television, between GERD and RA. Result: Both univariate MR (UVMR) and multivariable MR (MVMR) provided valid evidence that RA was causally and positively influenced by GERD (UVMR: OR = 1.49, 95% CI = 1.25-1.76, p = 6.18*10-6; MVMR: OR = 1.69, 95% CI = 1.24-2.31, p = 8.62*10-4), whereas GERD was not influenced by RA (UVMR: OR = 1.03, 95% CI = 1.00-1.06, p = 0.042; MVMR: OR = 1.04, 95% CI = 1.00-1.07, p = 0.0271). Conclusion: Our comprehensive bidirectional MR analysis found that for the European population, GERD can induce the occurrence of RA (OR = 1.69, p < 0.00125), whereas RA only has no significant influence on GERD. In particular, patients with GERD are suffering a 69% increased risk of RA occurrence, which means GERD is a substantial risk factor for RA.

Modeling of horizontal pleiotropy identifies possible causal gene expression in systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with complex causes involving genetic and environmental factors. While genome-wide association studies (GWASs) have identified genetic loci associated with SLE, the functional genomic elements responsible for disease development remain largely unknown. Mendelian Randomization (MR) is an instrumental variable approach to causal inference based on data from observational studies, where genetic variants are employed as instrumental variables (IVs).

Methods

This study utilized a two-step strategy to identify causal genes for SLE. In the first step, the classical MR method was employed, assuming the absence of horizontal pleiotropy, to estimate the causal effect of gene expression on SLE. In the second step, advanced probabilistic MR methods (PMR-Egger, MRAID, and MR-MtRobin) were applied to the genes identified in the first step, considering horizontal pleiotropy, to filter out false positives. PMR-Egger and MRAID analyses utilized whole blood expression quantitative trait loci (eQTL) and SLE GWAS summary data, while MR-MtRobin analysis used an independent eQTL dataset from multiple immune cell types along with the same SLE GWAS data.

Results

The initial MR analysis identified 142 genes, including 43 outside of chromosome 6. Subsequently, applying the advanced MR methods reduced the number of genes with significant causal effects on SLE to 66. PMR-Egger, MRAID, and MR-MtRobin, respectively, identified 13, 7, and 16 non-chromosome 6 genes with significant causal effects. All methods identified expression of PHRF1 gene as causal for SLE. A comprehensive literature review was conducted to enhance understanding of the functional roles and mechanisms of the identified genes in SLE development.

Conclusions

The findings from the three MR methods exhibited overlapping genes with causal effects on SLE, demonstrating consistent results. However, each method also uncovered unique genes due to different modelling assumptions and technical factors, highlighting the complementary nature of the approaches. Importantly, MRAID demonstrated a reduced percentage of causal genes from the Major Histocompatibility complex (MHC) region on chromosome 6, indicating its potential in minimizing false positive findings. This study contributes to unraveling the mechanisms underlying SLE by employing advanced probabilistic MR methods to identify causal genes, thereby enhancing our understanding of SLE pathogenesis.