Patients with asthma have a higher risk of systemic lupus erythematosus: a systematic review and meta-analysis

Metabolomics identifies metabolite markers in plasma and extracellular vesicles within plasma in patients with asthma

BACKGROUND

Plasma and extracellular vesicles (EVs) derived from plasma are important sources of information regarding individual health. Metabolomic analysis of plasma and EVs may provide new methods for predicting disease occurrence. This study aims to analyze the metabolomic characteristics of plasma and plasma EVs in asthma patients.

METHODS

Plasma samples were collected from healthy individuals and asthma patients. EVs were isolated from the plasma using ultracentrifugation. The isolated EVs were characterized by nanoparticle tracking analysis and flow cytometry. Metabolomic analysis was performed using a liquid chromatography-mass spectrometry platform.

RESULTS

This study successfully extracted EVs from plasma samples. Metabolomic analysis revealed that the composition of differential metabolites in the plasma and EVs of asthma patients was similar. KEGG pathway analysis indicated that the number of upregulated metabolic pathways enriched with differential metabolites in the plasma EVs of asthma patients was significantly greater than that in the plasma samples. Pathways associated with the onset of asthma included asthma, systemic lupus erythematosus, glycerophospholipid metabolism, and autophagy - other, primarily involving the following five metabolites: PS(18:1(9Z)/18:2(9Z,12Z)), PC(18:1(9Z)e/2:0), PS(24:1(15Z)/22:2(13Z,16Z)), PE(22:4(7Z,10Z,13Z,16Z)/22:5(4Z,7Z,10Z,13Z,16Z)), and PE(16:0/20:3(8Z,11Z,14Z)). Receiver operating characteristic analysis results suggested that these five differential metabolites may serve as potential biomarkers for asthma.

CONCLUSION

We identified the metabolic characteristics of plasma and EVs in asthma patients, confirming that the metabolites in plasma EVs may serve as potential biomarkers for asthma. This finding not only enhances our understanding of the pathogenesis of asthma but also opens new avenues for targeted therapy.

De novo identification of complex traits associated with asthma

Introduction

Asthma is a heterogeneous inflammatory disease often associated with other complex phenotypes. Identifying asthma-associated diseases and uncovering the molecular mechanisms mediating their interaction can help detangle the heterogeneity of asthma. Network analysis is a powerful approach for untangling such inter-disease relationships.

Methods

Here, we integrated information on physical contacts between common single nucleotide polymorphisms (SNPs) and gene expression with expression quantitative trait loci (eQTL) data from the lung and whole blood to construct two tissue-specific spatial gene regulatory networks (GRN). We then located the asthma GRN (level 0) within each tissue-specific GRN by identifying the genes that are functionally affected by asthma-associated spatial eQTLs. Curated protein interaction partners were subsequently identified up to four edges or levels away from the asthma GRN. The eQTLs spatially regulating genes on levels 0-4 were queried against the GWAS Catalog to identify the traits enriched (hypergeometric test; FDR ≤ 0.05) in each level.

Results

We identified 80 and 82 traits significantly enriched in the lung and blood GRNs, respectively. All identified traits were previously reported to be comorbid or associated (positively or negatively) with asthma (e.g., depressive symptoms and lung cancer), except 8 traits whose association with asthma is yet to be confirmed (e.g., reticulocyte count). Our analysis additionally pinpoints the variants and genes that link asthma to the identified asthma-associated traits, a subset of which was replicated in a comorbidity analysis using health records of 26,781 asthma patients in New Zealand.

Discussion

Our discovery approach identifies enriched traits in the regulatory space proximal to asthma, in the tissue of interest, without a priori selection of the interacting traits. The predictions it makes expand our understanding of possible shared molecular interactions and therapeutic targets for asthma, where no cure is currently available.

Systemic Lupus Erythematosus Patients with DNASE1L3·Deficiency Have a Distinctive and Specific Genic Circular DNA Profile in Plasma

Cell-free (cf) extrachromosomal circular DNA (eccDNA) has a potential clinical application as a biomarker. Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a complex immunological pathogenesis, associated with autoantibody synthesis. A previous study found that SLE patients with deoxyribonuclease 1-like 3 (DNASE1L3) deficiency exhibit changes in the frequency of short and long eccDNA in plasma compared to controls. Here, using the DifCir method for differential analysis of short-read sequenced purified eccDNA data based on the split-read signal of the eccDNA on circulomics data, we show that SLE patients with DNASE1L3 deficiency have a distinctive profile of eccDNA excised by gene regions compared to controls. Moreover, this profile is specific; cf-eccDNA from the top 93 genes is detected in all SLE with DNASE1L3 deficiency samples, and none in the control plasma. The top protein coding gene producing eccDNA-carrying gene fragments is the transcription factor BARX2, which is involved in skeletal muscle morphogenesis and connective tissue development. The top gene ontology terms are ‘positive regulation of torc1 signaling’ and ‘chondrocyte development’. The top Harmonizome terms are ‘lymphopenia’, ‘metabolic syndrome x’, ‘asthma’, ‘cardiovascular system disease‘, ‘leukemia’, and ‘immune system disease’. Here, we show that gene associations of cf-eccDNA can serve as a biomarker in the autoimmune rheumatic diseases.

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

Background

Observational studies have suggested the association between atopic dermatitis (AD) and the risks of autoimmune diseases. It is still unclear, however, whether or in which direction causal relationships exist, because these associations could be confounded.

Objectives

Our study seeks to assess the possibility of AD as a cause of autoimmune diseases, and to estimate the magnitude of the causal effect.

Methods

Two-sample mendelian randomization (MR) analyses were performed using genome-wide association study (GWAS) summary-level statistics. Specifically, bidirectional MR analyses were conducted to examine the direction of association of AD with autoimmune diseases; multivariable MR analyses (MVMR1) were used to test the independence of causal association of AD with autoimmune diseases after controlling other atopic disorders (asthma and allergic rhinitis), while MVMR2 analyses were conducted to account for potential confounding factors such as smoking, drinking, and obesity. Genetic instruments for AD (Ncases=22 474) were from the latest GWAS meta-analysis. The GWAS summary data for asthma and allergic rhinitis were obtained from UK Biobank. The GWAS summary data for smoking, alcohol consumption, obesity and autoimmune diseases (alopecia areata, vitiligo, systemic lupus erythematosus, ankylosing spondylitis, rheumatoid arthritis, and type 1 diabetes) were selected from the largest GWASs available. Causal estimates were derived by the inverse-variance weighted method and verified through a series of sensitivity analyses.

Results

Genetically predicted AD linked to higher risks of rheumatoid arthritis (OR, 1.28; P=0.0068) (ORMVMR1, 1.65; P=0.0020) (ORMVMR2, 1.36; P<0.001), type 1 diabetes (OR, 1.37; P=0.0084) (ORMVMR1, 1.42; P=0.0155) (ORMVMR2, 1.45; P=0.002), and alopecia areata (OR, 1.98; P=0.0059) (ORMVMR1, 2.55; P<0.001) (ORMVMR2, 1.99; P=0.003) in both univariable and multivariable MR. These causal relationships were supported by sensitivity analyses. No causal effect of AD was identified in relation to systemic lupus erythematosus, vitiligo, and ankylosing spondylitis. Concerning the reverse directions, no significant association was noted.

Conclusion

The results of this MR study provide evidence to support the idea that AD causes a greater risk of rheumatoid arthritis, type 1 diabetes and alopecia areata. Further replication in larger samples is needed to validate our findings, and experimental studies are needed to explore the underlying mechanisms of these causal effects.

A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Rhizoma Dioscoreae Nipponicae in the Treatment of Asthma

Background

In this study, network pharmacological methods were used to analyze the targets of Rhizoma Dioscoreae Nipponicae (RDN) and investigate the potential underlying mechanism of RDN in the treatment of asthma.

Methods

Asthma-related targets were obtained from the GeneCards and DisGeNET databases. The bioactive components of RDN were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database, and the targets of these compounds were predicted using the BATMAN-TCM database. The network of RDN component targets was constructed using Cytoscape. A protein-protein interaction (PPI) network was constructed in Cytoscape to determine the potential targets of RDN for the treatment of asthma. The hub genes of RDN in the treatment of asthma were screened using network topological parameters. Gene ontology (GO) and the KEGG pathways were analyzed. Molecular docking and in vivo experiments were performed to validate the network pharmacology results.

Results

A total of four bioactive components and 55 targets were identified. The results of the enrichment analysis suggested that the treatment of asthma with RDN involved signaling pathways, such as those related to systemic lupus erythematosus, alcoholism, viral carcinogenesis, the cell cycle, prostate cancer, transcriptional misregulation in cancer, hepatitis B, thyroid hormone signaling, and PI3K-AKT signaling, as well as other signaling pathways. Molecular docking showed that the active components of RDN could stably bind to the predicted target. In vivo experiments showed that RDN could regulate the expression of target genes and inhibit the activation of the PI3K-AKT signaling pathway.

Conclusion

To a certain extent, this study reveals the potential bioactive components and molecular mechanisms of RDN in the treatment of asthma and provides new insights for the development of new drugs for asthma.

Atopic Dermatitis is a Risk Factor for Rheumatoid Arthritis: A Systematic Review and Meta-Analysis

BACKGROUND

It is still unclear whether patients with atopic dermatitis (AD) have an increased risk of developing rheumatoid arthritis (RA).

OBJECTIVE

We aimed to investigate the association between AD and risk of RA using systematic review and meta-analysis.

METHODS

We searched Medline and EMBASE up to April 2021 using search strategy, including terms for "atopic dermatitis" and "rheumatoid arthritis." Eligible cohort study must compare the incidence of RA between patients with AD and comparators without AD. Eligible case-control study must recruit cases with RA and controls without RA. Then, the study must compare the prevalence of AD between the groups. Point estimates with standard errors from each study were combined using the generic inverse variance method.

RESULTS

The meta-analysis found that AD patients had a significantly higher risk of incident RA than individuals without AD with a pooled odds ratio (OR) of 1.30 (95% confidence interval [CI], 1.17-1.44; I2, 48%). Subgroup analysis revealed a significantly higher risk of RA in cohort study subgroup (pooled OR, 1.37; 95% CI, 1.25-1.50; I2, 63%) but not case-control study subgroup (pooled OR, 0.99; 95% CI, 0.77-1.28; I2, 10%).

CONCLUSIONS

This study found a significantly higher risk of incident RA among AD patients.

The Association Between Asthma and Risk of Myasthenia Gravis: A Systematic Review and Meta-analysis

PURPOSE

This study aimed to investigate the association between asthma and risk of myasthenia gravis (MG) using the method of systematic review and meta-analysis.

METHODS

Potentially eligible studies were identified from Medline and EMBASE databases from inception to July 2020 using search strategy that comprised terms for "Asthma" and "Myasthenia Gravis". Eligible cohort study must consist of one cohort of individuals with asthma and another cohort of individuals without asthma. Then, the study must report relative risk (RR) with 95% confidence intervals (95% CIs) of incident MG between the groups. Eligible case-control studies must include cases with MG and controls without MG. Then, the study must explore their history of asthma. Odds ratio (OR) with 95% CIs of the association between asthma status and MG must be reported. Point estimates with standard errors were retrieved from each study and were combined together using the generic inverse variance method.

RESULTS

A total of 6,835 articles were identified. After two rounds of independent review by five investigators, two cohort studies and three case-control studies met the eligibility criteria and were included into the meta-analysis. Pooled analysis showed that asthma was significantly associated with risk of MG with the pooled risk ratio of 1.38 (95% CI 1.02-1.86). Funnel plot was symmetric, which was not suggestive of publication bias.

CONCLUSION

The current study found a significant association between asthma and increased risk of MG.