Objective: Using a nationally representative cohort of medical claims data in Korea, this study aimed to analyze the association between the use of various anti-rheumatic agents and the risk of acute myocardial infarction (AMI) in patients with rheumatoid arthritis (RA). Methods: This nested case-control study used the Korean Health Insurance Review and Assessment data of 35,133 patients newly diagnosed with RA between 2011 and 2020. Incident AMI patients were identified and matched at a 1:4 ratio with randomly selected controls. The usage of anti-rheumatic agents was measured from the date of RA diagnosis to the index date and stratified based on exposure time and duration. The risk of AMI associated with each anti-rheumatic agent was estimated using conditional logistic regression, adjusted for comorbidities and concomitant drug use. Results: Of the 35,133 patients with RA, 484 were diagnosed with AMI. In total, 484 AMI patients and 1,924 controls with newly diagnosed RA were included in the analysis. Current exposure and long-term exposure to glucocorticoids (adjusted odds ratio [aOR]: 2.301, 95% confidence interval [CI]: 1.741~3.041; aOR: 1.792, 95% CI: 1.378~2.330) and leflunomide (aOR: 1.525, 95% CI: 1.196~1.944; aOR: 1.740, 95% CI: 1.372~2.207) were associated with an increased risk of AMI. Conclusion The study demonstrates a significant association between the current and long-term use of glucocorticoids and leflunomide and an increased risk of AMI in patients with RA. These findings underscore the importance of careful consideration of cardiovascular risks when selecting anti-rheumatic agents for RA treatment.

Objective: Using a nationally representative cohort of medical claims data in Korea, this study aimed to analyze the association between the use of various anti-rheumatic agents and the risk of acute myocardial infarction (AMI) in patients with rheumatoid arthritis (RA). Methods: This nested case-control study used the Korean Health Insurance Review and Assessment data of 35,133 patients newly diagnosed with RA between 2011 and 2020. Incident AMI patients were identified and matched at a 1:4 ratio with randomly selected controls. The usage of anti-rheumatic agents was measured from the date of RA diagnosis to the index date and stratified based on exposure time and duration. The risk of AMI associated with each anti-rheumatic agent was estimated using conditional logistic regression, adjusted for comorbidities and concomitant drug use. Results: Of the 35,133 patients with RA, 484 were diagnosed with AMI. In total, 484 AMI patients and 1,924 controls with newly diagnosed RA were included in the analysis. Current exposure and long-term exposure to glucocorticoids (adjusted odds ratio [aOR]: 2.301, 95% confidence interval [CI]: 1.741~3.041; aOR: 1.792, 95% CI: 1.378~2.330) and leflunomide (aOR: 1.525, 95% CI: 1.196~1.944; aOR: 1.740, 95% CI: 1.372~2.207) were associated with an increased risk of AMI. Conclusion The study demonstrates a significant association between the current and long-term use of glucocorticoids and leflunomide and an increased risk of AMI in patients with RA. These findings underscore the importance of careful consideration of cardiovascular risks when selecting anti-rheumatic agents for RA treatment.

Objective: Using a nationally representative cohort of medical claims data in Korea, this study aimed to analyze the association between the use of various anti-rheumatic agents and the risk of acute myocardial infarction (AMI) in patients with rheumatoid arthritis (RA). Methods: This nested case-control study used the Korean Health Insurance Review and Assessment data of 35,133 patients newly diagnosed with RA between 2011 and 2020. Incident AMI patients were identified and matched at a 1:4 ratio with randomly selected controls. The usage of anti-rheumatic agents was measured from the date of RA diagnosis to the index date and stratified based on exposure time and duration. The risk of AMI associated with each anti-rheumatic agent was estimated using conditional logistic regression, adjusted for comorbidities and concomitant drug use. Results: Of the 35,133 patients with RA, 484 were diagnosed with AMI. In total, 484 AMI patients and 1,924 controls with newly diagnosed RA were included in the analysis. Current exposure and long-term exposure to glucocorticoids (adjusted odds ratio [aOR]: 2.301, 95% confidence interval [CI]: 1.741~3.041; aOR: 1.792, 95% CI: 1.378~2.330) and leflunomide (aOR: 1.525, 95% CI: 1.196~1.944; aOR: 1.740, 95% CI: 1.372~2.207) were associated with an increased risk of AMI. Conclusion The study demonstrates a significant association between the current and long-term use of glucocorticoids and leflunomide and an increased risk of AMI in patients with RA. These findings underscore the importance of careful consideration of cardiovascular risks when selecting anti-rheumatic agents for RA treatment.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.