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BACKGROUND: Evidence for a potential link between air pollution and rheumatoid arthritis (RA) is inconsistent, and the modified effect of genetic susceptibility on the relationship between air pollution and RA has not been well studied. OBJECTIVE: Using a general population cohort from the UK Biobank, this study aimed to investigate the associations between various air pollutants and the risk of incident RA and to further estimate the impact of combined exposure to ambient air pollutants on the risk of developing RA under the modification effect of genetic predisposition. METHODS: A total of 342,973 participants with completed genotyping data and who were free of RA at baseline were included in the study. An air pollution score was constructed by summing the concentrations of each pollutant weighted by the regression coefficients with RA from single-pollutant models to assess the combined effect of air pollutants, including particulate matter (PM) with diameters ≤ 2.5 µm (PM2.5), between 2.5 and 10 µm (PM2.5–10), and ≤ 10 µm (PM10), as well as nitrogen dioxide (NO2) and nitrogen oxides (NOx). In addition, the polygenic risk score (PRS) of RA was calculated to characterize individual genetic risk. The Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of associations of single air pollutant, air pollution score, or PRS with incident RA. RESULTS: During a median follow-up time of 8.1 y, 2,034 incident events of RA were recorded. The HRs (95% CIs) of incident RA per interquartile range increment in PM2.5, PM2.5-10, PM10, NO2, and NOx were 1.07 (1.01, 1.13), 1.00 (0.96, 1.04), 1.01 (0.96, 1.07), 1.03 (0.98, 1.09), and 1.07 (1.02, 1.12), respectively. We also found a positive exposure-response relationship between air pollution score and RA risk (푝Trend = 0.000053). The HR(95% CI) of incident RA was 1.14 (1.00, 1.29) in the highest quartile group compared with the lowest quartile group of the air pollution score. Furthermore, the results of the combined effect of air pollution score and PRS on the RA risk showed that the risk of RA incidence in the highest genetic risk and air pollution score group was almost twice that of the lowest genetic risk and air pollution score group [incidence rate (IR) per 100,000 person-years: 98.46 vs. 51.19, and HR= 1.73 (95% CI: 1.39, 2.17) vs. 1 (reference)], although no statistically significant interaction between the air pollution and genetic risk for incident RA was found (푝Interaction >0.05). DISCUSSION: The results revealed that long-term combined exposure to ambient air pollutants might increase the risk of RA, particularly in those with high genetic risk. [ABSTRACT FROM AUTHOR]

The evolution of the SARS‐CoV‐2 new variants reported to be 70% more contagious than the earlier one is now spreading fast worldwide. There is an instant need to discover how the new variants interact with the host receptor (ACE2). Among the reported mutations in the Spike glycoprotein of the new variants, three are specific to the receptor‐binding domain (RBD) and required insightful scrutiny for new therapeutic options. These structural evolutions in the RBD domain may impart a critical role to the unique pathogenicity of the SARS‐CoV‐2 new variants. Herein, using structural and biophysical approaches, we explored that the specific mutations in the UK (N501Y), South African (K417N‐E484K‐N501Y), Brazilian (K417T‐E484K‐N501Y), and hypothetical (N501Y‐E484K) variants alter the binding affinity, create new inter‐protein contacts and changes the internal structural dynamics thereby increases the binding and eventually the infectivity. Our investigation highlighted that the South African (K417N‐E484K‐N501Y), Brazilian (K417T‐E484K‐N501Y) variants are more lethal than the UK variant (N501Y). The behavior of the wild type and N501Y is comparable. Free energy calculations further confirmed that increased binding of the spike RBD to the ACE2 is mainly due to the electrostatic contribution. Further, we find that the unusual virulence of this virus is potentially the consequence of Darwinian selection‐driven epistasis in protein evolution. The triple mutants (South African and Brazilian) may pose a serious threat to the efficacy of the already developed vaccine. Our analysis would help to understand the binding and structural dynamics of the new mutations in the RBD domain of the Spike protein and demand further investigation in in vitro and in vivo models to design potential therapeutics against the new variants. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relationship between metabolomic profiles, genome-wide polygenic risk scores (PRSs) and risk of rheumatoid arthritis (RA)., Methods: 143 nuclear magnetic resonance-based plasma metabolic biomarkers were measured among 93 800 participants in the UK Biobank. The Cox regression model was used to assess the associations between these metabolic biomarkers and RA risk, and genetic correlation and Mendelian randomisation analyses were performed to reveal their causal relationships. Subsequently, a metabolic risk score (MRS) comprised of the weighted sum of 17 clinically validated metabolic markers was constructed. A PRS was derived by assigning weights to genetic variants that exhibited significant associations with RA at a genome-wide level., Results: A total of 620 incident RA cases were recorded during a median follow-up time of 8.2 years. We determined that 30 metabolic biomarkers were potentially associated with RA, while no further significant causal associations were found. Individuals in the top decile of MRS had an increased risk of RA (HR 3.52, 95% CI: 2.80 to 4.43) compared with those below the median of MRS. Further, significant gradient associations between MRS and RA risk were observed across genetic risk strata. Specifically, compared with the low genetic risk and favourable MRS group, the risk of incident RA in the high genetic risk and unfavourable MRS group has almost elevated by fivefold (HR 6.10, 95% CI: 4.06 to 9.14)., Conclusion: Our findings suggested the metabolic profiles comprising multiple metabolic biomarkers contribute to capturing an elevated risk of RA, and the integration of genome-wide PRSs further improved risk stratification., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Evidence for a potential link between air pollution and rheumatoid arthritis (RA) is inconsistent, and the modified effect of genetic susceptibility on the relationship between air pollution and RA has not been well studied., Objective: Using a general population cohort from the UK Biobank, this study aimed to investigate the associations between various air pollutants and the risk of incident RA and to further estimate the impact of combined exposure to ambient air pollutants on the risk of developing RA under the modification effect of genetic predisposition., Methods: A total of 342,973 participants with completed genotyping data and who were free of RA at baseline were included in the study. An air pollution score was constructed by summing the concentrations of each pollutant weighted by the regression coefficients with RA from single-pollutant models to assess the combined effect of air pollutants, including particulate matter (PM) with diameters ≤ 2.5 μ m ( PM 2.5 ), between 2.5 and 10 μ m ( PM 2.5 - 10 ), and ≤ 10 μ m ( PM 10 ), as well as nitrogen dioxide ( NO 2 ) and nitrogen oxides ( NO x ). In addition, the polygenic risk score (PRS) of RA was calculated to characterize individual genetic risk. The Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of associations of single air pollutant, air pollution score, or PRS with incident RA., Results: During a median follow-up time of 8.1 y, 2,034 incident events of RA were recorded. The HRs (95% CIs) of incident RA per interquartile range increment in PM 2.5 , PM 2.5 - 10 , PM 10 , NO 2 , and NO x were 1.07 (1.01, 1.13), 1.00 (0.96, 1.04), 1.01 (0.96, 1.07), 1.03 (0.98, 1.09), and 1.07 (1.02, 1.12), respectively. We also found a positive exposure-response relationship between air pollution score and RA risk ( p Trend = 0.000053 ). The HR (95% CI) of incident RA was 1.14 (1.00, 1.29) in the highest quartile group compared with the lowest quartile group of the air pollution score. Furthermore, the results of the combined effect of air pollution score and PRS on the RA risk showed that the risk of RA incidence in the highest genetic risk and air pollution score group was almost twice that of the lowest genetic risk and air pollution score group [incidence rate (IR) per 100,000 person-years: 98.46 vs. 51.19, and HR = 1.73 (95% CI: 1.39, 2.17) vs. 1 (reference)], although no statistically significant interaction between the air pollution and genetic risk for incident RA was found ( p Interaction > 0.05 )., Discussion: The results revealed that long-term combined exposure to ambient air pollutants might increase the risk of RA, particularly in those with high genetic risk. https://doi.org/10.1289/EHP10710.