Association between air pollution exposure and outpatient visits for dermatomyositis in a humid subtropical region of China: a time-series study.

In recent years, a growing number of studies have found that air pollution plays critical roles in the onset and development of autoimmune diseases, but few studies have shown an association between air pollutants and dermatomyositis (DM). We sought to investigate the relationship between short-term exposure to air pollution and outpatient visits for DM and to quantify the burden of DM due to exposure to air pollutants in Hefei, China. Daily records of hospital outpatient visits for DM, air pollutants and meteorological factors data in Hefei from January 1, 2018 to December 31, 2021 were obtained. We used a distributed lag non-linear model (DLNM) in conjunction with a generalized linear model (GLM) to explore the association between air pollution and outpatient visits for DM, and conducted stratified analyses by gender, age and season. Moreover, we used attributable fraction (AF) and attributable number (AN) to reflect the burden of disease. A total of 4028 DM clinic visits were recorded during this period. High concentration nitrogen dioxide (NO2) exposure was associated with increased risk of DM outpatient visits (relative risk (RR) 1.063, 95% confidence interval (CI) 1.015-1.114, lag 0-5). Intriguingly, exposure to high concentration ozone (O3) was associated with reduced risk of outpatient visits for DM (RR 0.974, 95% CI 0. 0.954-0.993, lag 0-6). The results of stratified analyses showed that the cold season (vs. warm season) were more susceptible to outpatient visits for DM associated with NO2 and O3 exposure. In addition, we observed that an increased risk of DM outpatient visits was attributable to high concentration NO2 exposure, while high concentration O3 exposure was associated with a decreased risk of DM outpatient visits. This study provided a scientific basis for the etiology research and health protection of DM.

Arthritis and incident pulmonary diseases in middle-aged and elderly Chinese: a longitudinal population-based study.

BACKGROUND: The coexistence of arthritis and pulmonary abnormalities has long been observed, but the causal inter-relationships among them are still uncertain especially in elderly adults. METHODS: We extracted data from The China Health and Retirement Longitudinal Study (CHARLS). A total of 7534 participants without chronic lung diseases or/and asthma at the baseline and have complete follow-up information were included. Multivariate Cox proportional hazards models were used to estimate the adjusted hazard ratios (HRs) for developing chronic lung diseases or asthma. We also utilized generalized linear models to examine the association between arthritis and baseline peak expiratory flow (PEF). RESULTS: During 50,615 and 51,975 person-years of follow-up, 629 and 188 participants incident chronic lung diseases and asthma, respectively. Compared to those without arthritis, participants with arthritis had a higher risk of chronic lung diseases (HR = 1.54, 95%CI = 1.31-1.81, P = 1.23 × 10-7) and asthma (HR = 1.70, 95%CI = 1.27-2.28, P = 3.78 × 10-4). Arthritis subjects demonstrated significantly lower PEF than those without arthritis [ß = - 11.85 (95%CI = - 17.56, - 6.14), P = 4.81 × 10-5]. The results were stable after excluding these participates who incident chronic lung diseases or asthma in the first 1 year of follow-up. CONCLUSION: Arthritis increased the risk of pulmonary diseases among middle-aged and elderly Chinese. Early detection and treatment of pulmonary abnormalities among arthritis patients could help decrease the mortality and reduce the global burden of arthritis. Key Points • The coexistence of arthritis and pulmonary abnormalities has long been observed, but whether arthritis status can trigger pulmonary disorders is still uncertain. • Arthritis status are associated with increased risk of pulmonary diseases (chronic lung diseases/asthma) among middle-aged and elderly Chinese. • Early detection and treatment of pulmonary abnormalities among arthritis patients could help decrease the mortality and reduce the global burden of arthritis.

Causal effect of polyunsaturated fatty acids on bone mineral density and fracture.

Background: Polyunsaturated fatty acids (PUFAs) are closely related to osteoporosis. To test their causal relationship, we conducted a Mendelian randomization (MR) analysis. Methods: We analyzed the causal relationship between four PUFAs measures, n-3 PUFAs (n-3), n-6 PUFAs (n-6), the ratio of n-3 PUFAs to total fatty acids (n-3 pct), and the ratio of n-6 PUFAs to n-3 PUFAs (n-6 to n-3), and five measures of osteoporosis, including estimated bone mineral density (eBMD), forearm (FA) BMD, femoral neck (FN) BMD, lumbar spine (LS) BMD, and fracture, using two-sample MR analysis. In order to verify the direct effect between PUFAs and BMD, we chose interleukin-6 (IL-6), tumor necrosis factor-ß (TNF-ß), and bone morphogenetic proteins 7 (BMP-7), three markers or cytokines strongly related to BMD, as possible confounding factors, and analyzed the possible causal relationships between them and PUFAs or BMD by MR. Inverse variance weighting (IVW), MR-Egger, weighted and weighted median were conducted. MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and MR-Egger regression methods were used to evaluate the potential pleiotropy of instrumental variables (IVs) and outliers were identified by MR-PRESSO. Cochran's Q statistic was used to detect the heterogeneity among IVs. Leave-one-out sensitivity analysis was used to find SNPs that have a significant impact on the results. All results were corrected by the Bonferroni correction. Results: The IVW results showed that n-3 PUFAs (OR = 1.030, 95% CI: 1.013, 1.047, P = 0.001) and n-6 PUFAs (OR = 1.053, 95% CI: 1.034, 1.072, P < 0.001) were positively correlated with eBMD, while n-6 to n-3 (OR = 0.947, 95% CI: 0.924, 0.970, P < 0.001) were negatively correlated with eBMD. These casual relationships still existed after Bonferroni correction. There were positive effects of n-3 PUFAs on FA BMD (OR = 1.090, 95% CI: 1.011, 1.176, P = 0.025) and LS BMD (OR = 1.056, 95% CI: 1.011, 1.104, P = 0.014), n-3 pct on eBMD (OR = 1.028, 95% CI: 1.002, 1.055, P = 0.035) and FA BMD (OR = 1.090, 95% CI: 1.011, 1.174, P = 0.025), n-6 to n-3 on LS BMD (OR = 1.071, 95% CI: 1.021, 1.124, P = 0.005); negative effects of n-3 pct on fracture (OR = 0.953, 95% CI: 0.918, 0.988, P = 0.009) and n-6 to n-3 on FA BMD (OR = 0.910, 95% CI: 0.837, 0.988, P = 0.025). However, these causal effects all disappeared after Bonferroni correction (all P > 0.0025). None of IL-6, TNF-ß, and BMP-7 had a causal effect on PUFA and BMD simultaneously (all P > 0.05). Conclusion: Evidence from this MR study supports the genetically predicted causal effects of n-3, n-6, n-3 pct, and n-6 to n-3 on eBMD. In addition, n-3 not only associate with FA BMD and LS BMD through its own level and n-6 to n-3, but also link to fracture through n-3 pct.

The effect of air pollution exposure on risk of outpatient visits for Sjogren's syndrome: A time-series study.

BACKGROUND: Emerging evidence showed that air pollutants are associated with development and recurrence of autoimmune disorders, but there is scarce evidence regarding the relationship between air pollutants and Sjogren's syndrome (SS). We sought to investigate whether air pollutants affect the risk of outpatient visits for SS and to quantify the burden of SS visits attributable to air pollution exposure in Hefei, China. METHODS: Daily data on outpatient visits for SS, air pollutants and meteorological data in Hefei, China, from January 1, 2015 to December 31, 2020 were obtained. A distributed lag non-linear model in conjunction with a generalized linear model were employed to assess the relationship between air pollution and SS outpatient visits. Stratified analyses were further performed by gender, age and season. Attributable fraction (AF) and attributable number (AN) were used to reflect disease burden. RESULTS: There were 4501 records of outpatient visits for SS. Exposure to PM2.5 was associated with increased risk of SS outpatient visits (relative risk (RR) = 1.218, 95% confidence interval (CI): 1.017-1.458, lag 0-14 day). An increase of 24 µg/m3 (interquartile range) in NO2 concentration was associated with 26.3% increase in the risk of SS outpatient visits (RR = 1.263, 95%CI: 1.105-1.445, lag 0-10 day). In contrast, exposure to O3 was associated with decreased risk of SS outpatient visits (RR = 0.692, 95%CI: 0.510-0.939, per 63 µg/m3 in O3 exposure, lag 0-27 day). Stratified analyses showed that females (vs. males) was more vulnerable to SS outpatient visits associated with NO2 and O3 exposure. SS patients aged ≥65 years (vs. aged <65 years) were susceptible to PM2.5 exposure. Exposure to PM2.5 or NO2 in the cold season was associated with higher risk of SS outpatient visits than that in the warm season. In addition, the AN (232, 95%CI: 119, 324) and AF (5.16%, 95%CI: 2.55%, 7.21%) of NO2 exposure were higher than those of PM2.5 exposure. CONCLUSION: PM2.5 and NO2 exposure are associated with increased risk of SS outpatient visits, while O3 exposure appears to be associated with decreased risk of SS outpatient visits. The effect of air pollutants exposure on risk of SS outpatients can be modified by age, gender and season. The burden of SS outpatient visits attributable to NO2 exposure is higher than those attributable to PM2.5 exposure.

Does smoking protect against developing osteoarthritis? Evidence from a genetically informed perspective.

OBJECTIVE: Cumulative evidence from observational studies showed an inverse association between smoking and osteoarthritis (OA), but this association could be confounded by obesity. This study aimed to decipher the causal effect of smoking on osteoarthritis risk from a genetically informed perspective. METHODS: We performed a two-sample univariable and multivariable MR to evaluate the independent effect of smoking on OA risk. Summary-level data were obtained from the largest available genome-wide association studies (GWASs) of smoking initiation, body mass index (BMI) and OA. Genetic variants predicted the exposure were selected as instruments from the respective GWAS. RESULTS: Genetically liability for smoking initiation had an effect estimate consistent with increased risk for overall OA (odds ratio (OR)=1.61, 95% confidence interval (CI)=1.43-1.81, P=7.50 × 10-15), hip OA (OR=1.62, 95%CI=1.29-2.02, P=2.93 × 10-5), knee OA (OR=1.54, 95%CI=1.29-1.84, P =1.80 × 10-6) and hip and/or knee OA (OR=1.56, 95%CI=1.34-1.80, P=3.63 × 10-9), respectively. We also found that genetic liability of BMI was significantly associated with OA risk and the OR per genetically predicted 1 kg/m2 increase of BMI ranged from 2.19 to 2.64. Additionally, multivariate MR analysis revealed a strong evidence for an effect of smoking initiation on the risk of overall OA (OR=1.45, 95%CI=1.31-1.61, P=3.69 × 10-12) and its subtypes after controlling for BMI. CONCLUSION: Our findings support an independent deleterious causal effect for smoking upon OA risk, which further strengthen the importance of smoking cessation interventions and obesity management in the general population, in order to lessen the huge burden of OA in the global aging era.

Environmental factors and risk of gout.

Gout is a chronic disease with inflammatory arthritis caused by monosodium urate (MSU) crystals deposition, an elevated serum urate level (hyperuricaemia) is the critical factor leading to MSU crystals deposition and promoting the progression of gout. The onset and development of gout is generally the result of multiple factors, such as diet, heredity and environmental factors. Although genetics and diet are thought to play as major factors, a growing body of research evidence has highlighted that environmental factors also play a significant role in the onset and exacerbation of gout. Recent studies have shown that air pollutants such as particulate matter, sulfur dioxide (SO2) and carbon monoxide (CO) may increase the risk of hospitalizations for gout, and that the changes in temperature and humidity may affect uric acid (UA) levels. There is also seasonal trend in gout. It has been demonstrated that environmental factors may induce or accelerate the production and release of pro-inflammatory mediators, causing an unbalance oxidative stress and systemic inflammation, and then participating in the overall process or a certain link of gout. Moreover, several environmental factors have shown the ability to induce the production urate and regulate the innate immune pathways, involving in the pathogenesis of gout. Nevertheless, the role of environmental factors in the etiology of gout remains unclear. In this review, we summarized the recent literatures and aimed to discuss the relationship between environmental factors (such as microclimate, season, ambient/indoor air pollution and extreme weather) and gout. We further discussed the inflammatory mechanisms of environmental factors and gout and the comprehensive effects of environmental factors on gout. We also made a prospect of the management and treatment of gout, with special consideration to environmental factors associated with gout.

No Genetic Causal Association Between Periodontitis and Arthritis: A Bidirectional Two-Sample Mendelian Randomization Analysis.

Objectives: Periodontitis (PD) has been linked to arthritis in previous epidemiological observational studies; however, the results are inconclusive. It remains unclear whether the association between PD and arthritis is causal. The purpose of this study was to investigate the causal association of PD with arthritis, including rheumatoid arthritis (RA) and osteoarthritis (OA). Methods: We performed a two-sample bidirectional Mendelian randomization (MR) analysis using publicly released genome-wide association studies (GWAS) statistics. The inverse-variance weighted (IVW) method was used as the primary analysis. We applied four complementary methods, including weighted median, weighted mode, MR-Egger regression and MR pleiotropy residual sum and outlier (MR-PRESSO) to detect and correct for the effect of horizontal pleiotropy. Results: Genetically determined PD did not have a causal effect on OA (OR = 1.06, 95% CI: 0.99-1.15, P = 0.09) and RA (OR = 0.99, 95% CI: 0.87-1.13, P = 0.89). Furthermore, we did not find a significant causal effect of arthritis on PD in the reverse MR analysis. The results of MR-Egger regression, Weighted Median, and Weighted Mode methods were consistent with those of the IVW method. Horizontal pleiotropy was unlikely to distort the causal estimates according to the sensitivity analysis. Conclusions: Our MR analysis reveals non-causal association of PD with arthritis, despite observational studies reporting an association between PD and arthritis.

Novel insight into the aetiology of rheumatoid arthritis gained by a cross-tissue transcriptome-wide association study.

BACKGROUND: Although genome-wide association studies (GWASs) have identified more than 100 loci associated with rheumatoid arthritis (RA) susceptibility, the causal genes and biological mechanisms remain largely unknown. METHODS: A cross-tissue transcriptome-wide association study (TWAS) using the unified test for molecular signaturestool was performed to integrate GWAS summary statistics from 58 284 individuals (14 361 RA cases and 43 923 controls) with gene-expression matrix in the Genotype-Tissue Expression project. Subsequently, a single tissue by using FUSION software was conducted to validate the significant associations. We also compared the TWAS with different gene-based methodologies, including Summary Data Based Mendelian Randomization (SMR) and Multimarker Analysis of Genomic Annotation (MAGMA). Further in silico analyses (conditional and joint analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA. RESULTS: We identified a total of 47 significant candidate genes for RA in both cross-tissue and single-tissue test after multiple testing correction, of which 40 TWAS-identified genes were verified by SMR or MAGMA. Among them, 13 genes were situated outside of previously reported significant loci by RA GWAS. Both TWAS-based and MAGMA-based enrichment analyses illustrated the shared genetic determinants among autoimmune thyroid disease, asthma, type I diabetes mellitus and RA. CONCLUSION: Our study unveils 13 new candidate genes whose predicted expression is associated with risk of RA, providing new insights into the underlying genetic architecture of RA.

Therapeutic Potential of Galectin-1 and Galectin-3 in Autoimmune Diseases.

Galectins are a highly conserved protein family that binds to ß-galactosides. Different members of this family play a variety of biological functions in physiological and pathological processes such as angiogenesis, regulation of immune cell activity, and cell adhesion. Galectins are widely distributed and play a vital role both inside and outside cells. They can regulate homeostasis and immune function in vivo through mechanisms such as apoptosis. Recent studies have indicated that galectins exhibit pleiotropic roles in inflammation. Furthermore, emerging studies have found that galectins are involved in the occurrence and development of autoimmune diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), type 1 diabetes (T1D), and systemic sclerosis (SSc) by regulating cell adhesion, apoptosis, and other mechanisms. This review will briefly discuss the biological characteristics of the two most widely expressed and extensively explored members of the galectin family, galectin-1 and galectin-3, as well as their pathogenetic and therapeutic roles in autoimmune diseases. This information may provide a novel and promising therapeutic target for autoimmune diseases.

Causal Effects of Gut Microbiome on Systemic Lupus Erythematosus: A Two-Sample Mendelian Randomization Study.

The observational association between gut microbiome and systemic lupus erythematosus (SLE) has been well documented. However, whether the association is causal remains unclear. The present study used publicly available genome-wide association study (GWAS) summary data to perform two-sample Mendelian randomization (MR), aiming to examine the causal links between gut microbiome and SLE. Two sets of MR analyses were conducted. A group of single nucleotide polymorphisms (SNPs) that less than the genome-wide statistical significance threshold (5 × 10-8) served as instrumental variables. To obtain a comprehensive conclusion, the other group where SNPs were smaller than the locus-wide significance level (1 × 10-5) were selected as instrumental variables. Based on the locus-wide significance level, the results indicated that there were causal effects of gut microbiome components on SLE risk. The inverse variance weighted (IVW) method suggested that Bacilli and Lactobacillales were positively correlated with the risk of SLE and Bacillales, Coprobacter and Lachnospira were negatively correlated with SLE risk. The results of weighted median method supported that Bacilli, Lactobacillales, and Eggerthella were risk factors for SLE and Bacillales and Coprobacter served as protective factors for SLE. The estimates of MR Egger suggested that genetically predicted Ruminiclostridium6 was negatively associated with SLE. Based on the genome-wide statistical significance threshold, the results showed that Actinobacteria might reduce the SLE risk. However, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) detected significant horizontal pleiotropy between the instrumental variables of Ruminiclostridium6 and outcome. This study support that there are beneficial or detrimental causal effects of gut microbiome components on SLE risk.

Non-Causal Effects of Asthma on COVID-19 Susceptibility and Severity.

Background: Asthma is observationally associated with an increased risk of COVID-19, but the causality remains unclear. We aim to determine whether there is a casual role of asthma in susceptibility to SARS-CoV-2 infection or COVID-19 severity. Methods: Instrumental variables (IVs) for asthma and moderate-to-severe asthma were obtained from publicly available summary statistics from the most recent and largest genome-wide association study (GWAS), including 394 283 and 57 695 participants of European ancestry, respectively. The corresponding data for COVID-19 susceptibility, hospitalization and severe-disease were derived from the COVID-19 Host Genetics Initiative GWAS meta-analysis of up to 1 683 768 individuals of European descent. Causality was inferred between correlated traits by Mendelian Randomization analyses. Inverse-variance weighted method was used as the primary MR estimates and multiple alternate approaches and several sensitivity analyses were also conducted. Results: Our MR analysis revealed no causal effects of asthma on COVID-19 susceptibility, hospitalization or severe disease, with odds ratio (OR) of 0.994 (95% CI: 0.962-1.027), 1.020 (95% CI: 0.955-1.089), and 0.929 (95% CI: 0.836-1.032), respectively. Furthermore, using genetic variants for moderate-to-severe asthma, a similar pattern of results was observed for COVID-19 susceptibility (OR: 0.988, 95% CI: 0.946-1.031), hospitalization (OR: 0.967, 95% CI: 0.906-1.031), and severe disease (OR: 0.911, 95% CI: 0.823-1.009). The association of asthma and moderate-to-severe asthma with COVID-19 was overall robust to sensitivity analyses. Conclusion: Genetically predicted asthma was not associated with susceptibility to, or severity of, COVID-19 disease, indicating that asthma is unlikely to be a causal factor in the development of COVID-19.