Purpose: The immunological response and adverse effects of antineutrophil cytoplasmic antibody-associated vasculitis (AAV) in patients receiving coronavirus disease-2019 (COVID-19) vaccines remain unclear. We aimed to evaluate the effects of these vaccines on AAV disease activity. Materials and Methods: We reviewed the medical records of 52 patients with AAV who had received at least second doses of the COVID-19 vaccine and evaluated their immunogenicity by measuring the anti-spike (S) antibody (Ab) titer levels using the Roche Elecsys® immunoassay. Responses to the Birmingham Vasculitis Activity Score (BVAS) tool and 36-Item Short Form Survey before and after vaccination were obtained to assess AAV disease activity. Vaccine reactivity was measured using a standardized questionnaire. Results: We enrolled 52 patients with AAV. No differences were found between those who received second and third doses of vaccination in terms of AAV type, disease activity, vaccine type, or the use of immunosuppressive agents, including steroids. The median anti-S Ab titer was 3967.0 after third doses compared to 419.0 after second doses (p=0.001). Except for mycophenolate mofetil (MMF), when immunosuppressants were administered in conjunction with steroids, the Ab titer was higher after the third vaccination than that after the second dose. The BVAS remained unchanged before and after second and third doses. No life-threatening adverse events were reported. Conclusion Although COVID-19 vaccine may not produce sufficient antibodies in patients taking MMF, the vaccine did not exacerbate disease activity or cause severe side effects. Therefore, COVID-19 vaccines should be considered in patients with AAV.

Purpose: The immunological response and adverse effects of antineutrophil cytoplasmic antibody-associated vasculitis (AAV) in patients receiving coronavirus disease-2019 (COVID-19) vaccines remain unclear. We aimed to evaluate the effects of these vaccines on AAV disease activity. Materials and Methods: We reviewed the medical records of 52 patients with AAV who had received at least second doses of the COVID-19 vaccine and evaluated their immunogenicity by measuring the anti-spike (S) antibody (Ab) titer levels using the Roche Elecsys® immunoassay. Responses to the Birmingham Vasculitis Activity Score (BVAS) tool and 36-Item Short Form Survey before and after vaccination were obtained to assess AAV disease activity. Vaccine reactivity was measured using a standardized questionnaire. Results: We enrolled 52 patients with AAV. No differences were found between those who received second and third doses of vaccination in terms of AAV type, disease activity, vaccine type, or the use of immunosuppressive agents, including steroids. The median anti-S Ab titer was 3967.0 after third doses compared to 419.0 after second doses (p=0.001). Except for mycophenolate mofetil (MMF), when immunosuppressants were administered in conjunction with steroids, the Ab titer was higher after the third vaccination than that after the second dose. The BVAS remained unchanged before and after second and third doses. No life-threatening adverse events were reported. Conclusion Although COVID-19 vaccine may not produce sufficient antibodies in patients taking MMF, the vaccine did not exacerbate disease activity or cause severe side effects. Therefore, COVID-19 vaccines should be considered in patients with AAV.

Purpose: The immunological response and adverse effects of antineutrophil cytoplasmic antibody-associated vasculitis (AAV) in patients receiving coronavirus disease-2019 (COVID-19) vaccines remain unclear. We aimed to evaluate the effects of these vaccines on AAV disease activity. Materials and Methods: We reviewed the medical records of 52 patients with AAV who had received at least second doses of the COVID-19 vaccine and evaluated their immunogenicity by measuring the anti-spike (S) antibody (Ab) titer levels using the Roche Elecsys® immunoassay. Responses to the Birmingham Vasculitis Activity Score (BVAS) tool and 36-Item Short Form Survey before and after vaccination were obtained to assess AAV disease activity. Vaccine reactivity was measured using a standardized questionnaire. Results: We enrolled 52 patients with AAV. No differences were found between those who received second and third doses of vaccination in terms of AAV type, disease activity, vaccine type, or the use of immunosuppressive agents, including steroids. The median anti-S Ab titer was 3967.0 after third doses compared to 419.0 after second doses (p=0.001). Except for mycophenolate mofetil (MMF), when immunosuppressants were administered in conjunction with steroids, the Ab titer was higher after the third vaccination than that after the second dose. The BVAS remained unchanged before and after second and third doses. No life-threatening adverse events were reported. Conclusion Although COVID-19 vaccine may not produce sufficient antibodies in patients taking MMF, the vaccine did not exacerbate disease activity or cause severe side effects. Therefore, COVID-19 vaccines should be considered in patients with AAV.

Background: Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders. Methods: We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex. Results: Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32–6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61–13.40) group.Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups. Conclusion Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.

Background: Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders. Methods: We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex. Results: Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32–6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61–13.40) group.Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups. Conclusion Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.

Background: Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders. Methods: We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex. Results: Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32–6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61–13.40) group.Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups. Conclusion Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.

Purpose: The immunological response and adverse effects of antineutrophil cytoplasmic antibody-associated vasculitis (AAV) in patients receiving coronavirus disease-2019 (COVID-19) vaccines remain unclear. We aimed to evaluate the effects of these vaccines on AAV disease activity. Materials and Methods: We reviewed the medical records of 52 patients with AAV who had received at least second doses of the COVID-19 vaccine and evaluated their immunogenicity by measuring the anti-spike (S) antibody (Ab) titer levels using the Roche Elecsys® immunoassay. Responses to the Birmingham Vasculitis Activity Score (BVAS) tool and 36-Item Short Form Survey before and after vaccination were obtained to assess AAV disease activity. Vaccine reactivity was measured using a standardized questionnaire. Results: We enrolled 52 patients with AAV. No differences were found between those who received second and third doses of vaccination in terms of AAV type, disease activity, vaccine type, or the use of immunosuppressive agents, including steroids. The median anti-S Ab titer was 3967.0 after third doses compared to 419.0 after second doses (p=0.001). Except for mycophenolate mofetil (MMF), when immunosuppressants were administered in conjunction with steroids, the Ab titer was higher after the third vaccination than that after the second dose. The BVAS remained unchanged before and after second and third doses. No life-threatening adverse events were reported. Conclusion Although COVID-19 vaccine may not produce sufficient antibodies in patients taking MMF, the vaccine did not exacerbate disease activity or cause severe side effects. Therefore, COVID-19 vaccines should be considered in patients with AAV.

Background: Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders. Methods: We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex. Results: Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32–6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61–13.40) group.Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups. Conclusion Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.