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Aims The underlying mechanisms of atrial fibrillation (AF) are largely unknown. Inflammation may underlie atrial remodelling. Autoimmune diseases, related to increased systemic inflammation, may therefore be associated with new-onset AF. Methods and results Participants from the population-based UK Biobank were screened for rheumatic fever, gastrointestinal autoimmune diseases, autoimmune diseases targeting the musculoskeletal system and connective tissues, and neurological autoimmune diseases. Between 2006 and 2022, participants were followed for incident AF. Cox proportional hazards regression analyses were performed to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to quantify associations. 494 072 participants free from AF were included (median age 58.0 years, 54.8% women). After a median of 12.8 years, 27 194 (5.5%) participants were diagnosed with new-onset AF. Rheumatic fever without heart involvement (HR, 95% CI: 1.47, 1.26–1.72), Crohn’s disease (1.23, 1.05–1.45), ulcerative colitis (1.17, 1.06–1.31), rheumatoid arthritis (1.39, 1.28–1.51), polyarteritis nodosa (1.82, 1.04–3.09), systemic lupus erythematosus (1.82, 1.41–2.35), and systemic sclerosis (2.32, 1.57–3.44) were associated with a larger AF risk. In sex-stratified analyses, rheumatic fever without heart involvement, multiple sclerosis, Crohn’s disease, seropositive rheumatoid arthritis, psoriatic and enteropathic arthropathies, systemic sclerosis and ankylosing spondylitis were associated with larger AF risk in women, whereas only men showed a larger AF risk associated with ulcerative colitis. Conclusions Various autoimmune diseases are associated with new-onset AF, more distinct in women. Our findings elaborate on the pathophysiological differences in autoimmunity and AF risk between men and women.

Aims To investigate sex-specific longitudinal trajectories of various obesity-related measures and blood pressure at the population level and further assess the impact of these trajectories on new-onset atrial fibrillation (AF). Methods and results Participants with ≥2 repeated assessments for various risk factors from the population-based Rotterdam Study were included. Latent class linear mixed models were fitted to identify the potential classes. Cox proportional-hazard models were used to assess the association between risk factors’ trajectories and the risk of new-onset AF, with the most favourable trajectory as reference. Among 7367 participants (mean baseline age: 73 years, 58.8% women), after a median follow-up time of 8.9 years (interquartile range: 5.3–10.4), 769 (11.4%) participants developed new-onset AF. After adjustments for cardiovascular risk factors, persistent-increasing body mass index (BMI) trajectory carried a higher risk for AF [hazard ratio, 95% confidence interval: (1.39; 1.05–1.85) in men and (1.60; 1.19–2.15) in women], compared with the lower-and-stable BMI trajectory. Trajectories of elevated-and-stable waist circumference (WC) in women (1.53; 1.09–2.15) and elevated-and-stable hip circumference (HC) in men (1.83; 1.11–3.03) were associated with incident AF. For systolic blood pressure (SBP), the initially hypertensive trajectory carried the largest risk for AF among women (1.79; 1.21–2.65) and men (1.82; 1.13–2.95). Diastolic blood pressure trajectories were significantly associated with AF risk among women but not among men. Conclusion Longitudinal trajectories of weight, BMI, WC, HC, and SBP were associated with new-onset AF in both men and women. Diastolic blood pressure trajectories were additionally associated with AF in women. Our results highlight the importance of assessing long-term exposure to risk factors for AF prevention among men and women.

Aims While atrial fibrillation (AF) is suggested to induce a prothrombotic state, increasing thrombotic risk, it is also hypothesized that coagulation underlies AF onset. However, conclusive evidence is lacking. With this systematic review and meta-analysis, we aimed to summarize and combine the evidence on the associations between coagulation factors with AF in both longitudinal and cross-sectional studies. Methods and results We systematically searched for longitudinal cohort and cross-sectional studies investigating AF and thrombosis. For longitudinal studies, pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. For cross-sectional studies, we determined pooled standardized mean differences (SMDs) and 95% CIs. A total of 17 longitudinal and 44 cross-sectional studies were included. In longitudinal studies, we found significant associations between fibrinogen (HR 1.05, 95% CI 1.00–1.10), plasminogen activator inhibitor 1 (PAI-1) (HR 1.06, 95% CI 1.00–1.12), and D-dimer (HR 1.10, 95% CI 1.02–1.19) and AF incidence. In cross-sectional studies, we found significantly increased levels of fibrinogen (SMD 0.47, 95% CI 0.20–0,74), von Willebrand factor (SMD 0.96, 95% CI 0.28–1.66), P-selectin (SMD 0.31, 95% CI 0.08–0.54), ß-thromboglobulin (SMD 0.82, 95% CI 0.61–1.04), Platelet Factor 4 (SMD 0.42, 95% CI 0.12–0.7), PAI-1 (1.73, 95% CI 0.26–3.19), and D-dimer (SMD 1.74, 95% CI 0.36–3.11) in AF patients, as opposed to controls. Conclusion These findings suggest that higher levels of coagulation factors are associated with prevalent and incident AF. These associations are most pronounced with prevalent AF in cross-sectional studies. Limited evidence from longitudinal studies suggests a prothrombotic state underlying AF development.

Context Hyperglycemia and autonomic dysfunction are bidirectionally related. Objective We investigated the association of longitudinal evolution of heart rate variability (HRV) with incident type 2 diabetes (T2D) among the general population. Methods We included 7630 participants (mean age 63.7 years, 58% women) from the population-based Rotterdam Study who had no history of T2D and atrial fibrillation at baseline and had repeated HRV assessments at baseline and during follow-up. We used joint models to assess the association between longitudinal evolution of heart rate and different HRV metrics (including the heart rate–corrected SD of the normal-to-normal RR intervals [SDNNc], and root mean square of successive RR-interval differences [RMSSDc]) with incident T2D. Models were adjusted for cardiovascular risk factors. Bidirectional Mendelian randomization (MR) using summary-level data was also performed. Results During a median follow-up of 8.6 years, 871 individuals developed incident T2D. One SD increase in heart rate (hazard ratio [HR] 1.20; 95% CI, 1.09-1.33), and log(RMSSDc) (HR 1.16; 95% CI, 1.01-1.33) were independently associated with incident T2D. The HRs were 1.54 (95% CI, 1.08-2.06) for participants younger than 62 years and 1.15 (95% CI, 1.01-1.31) for those older than 62 years for heart rate (P for interaction Conclusion Autonomic dysfunction precedes development of T2D, especially among younger individuals, while MR analysis suggests no causal relationship. More studies are needed to further validate our findings.

Importance: Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide, with different epidemiological and pathophysiological processes for women vs men and a poorer prognosis for women. Further investigation of sex-specific risk factors associated with AF development in women is warranted. Objective: To investigate the linear and potential nonlinear associations between sex-specific risk factors and the risk of new-onset AF in women. Design, Setting, and Participants: This population-based cohort study obtained data from the 2006 to 2010 UK Biobank study, a cohort of more than 500 000 participants aged 40 to 69 years. Participants were women without AF and history of hysterectomy and/or bilateral oophorectomy at baseline. Median follow-up period for AF onset was 11.6 years, and follow-up ended on October 3, 2020. Exposures: Self-reported, sex-specific risk factors, including age at menarche, history of irregular menstrual cycle, menopause status, age at menopause, years after menopause, age at first live birth, years after last birth, history of spontaneous miscarriages, history of stillbirths, number of live births, and total reproductive years. Main Outcomes and Measures: The primary outcome was new-onset AF, which was defined by the use of International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code I48. Results: A total of 235 191 women (mean [SD] age, 55.7 [8.1] years) were included in the present study. During follow-up, 4629 (2.0%) women experienced new-onset AF. In multivariable-adjusted models, history of irregular menstrual cycle was associated with higher AF risk (hazard ratio [HR], 1.34; 95% CI, 1.01-1.79). Both early menarche (age 7-11 years; HR, 1.10 [95% CI, 1.00-1.21]) and late menarche (age 13-18 years; HR, 1.08 [95% CI, 1.00-1.17]) were associated with AF incidence. Early menopause (age 35-44 years; HR, 1.24 [95% CI, 1.10-1.39]) and delayed menopause (age ≥60 years; HR, 1.34 [95% CI, 1.10-1.78]) were associated with higher risk of AF. Compared with women with 1 to 2 live births, those with 0 live births (HR, 1.13; 95% CI, 1.04-1.24) or 7 or more live births (HR, 1.67; 95% CI, 1.03-2.70) both had significantly higher AF risk. Conclusions and Relevance: Results of this study suggest that irregular menstrual cycles, nulliparity, and multiparity were associated with higher risk of new-onset AF among women. The results highlight the importance of taking into account the reproductive history of women in devising screening strategies for AF prevention.

Background Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women. Methods Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into ‘single-documented AF episode’, ‘multiple-documented AF episodes’, or ‘long-standing persistent AF’. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis. Results We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as ‘single-documented AF episode’, 208 (1.5%) as ‘multiple-documented AF episodes’, and 57 (0.4%) as ‘long-standing persistent AF’. In men, we found poorer trajectories of weight and waist circumference preceding ‘long-standing persistent AF’ as compared to the other patterns. In women, we found worse trajectories of all risk factors between ‘long-standing persistent AF’ and the other patterns. Conclusion We developed a standardized method to classify AF patterns in the general population. Participants categorized as ‘long-standing persistent AF’ showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns. Graphical abstract

Background Sex differences and causality of the association between heart rate variability (HRV) and atrial fibrillation (AF) in the general population remain unclear. Methods 12,334 participants free of AF from the population-based Rotterdam Study were included. Measures of HRV including the standard deviation of normal RR intervals (SDNN), SDNN corrected for heart rate (SDNNc), RR interval differences (RMSSD), RMSSD corrected for heart rate (RMSSDc), and heart rate were assessed at baseline and follow-up examinations. Joint models, adjusted for cardiovascular risk factors, were used to determine the association between longitudinal measures of HRV with new-onset AF. Genetic variants for HRV were used as instrumental variables in a Mendelian randomization (MR) analysis using genome-wide association studies (GWAS) summary-level data. Results During a median follow-up of 9.4 years, 1302 incident AF cases occurred among 12,334 participants (mean age 64.8 years, 58.3% women). In joint models, higher SDNN (fully-adjusted hazard ratio (HR), 95% confidence interval (CI) 1.24, 1.04–1.47, p = 0.0213), and higher RMSSD (fully-adjusted HR, 95% CI 1.33, 1.13–1.54, p = 0.0010) were significantly associated with new-onset AF. Sex-stratified analyses showed that the associations were mostly prominent among women. In MR analyses, a genetically determined increase in SDNN (odds ratio (OR), 95% CI 1.60, 1.27–2.02, p = 8.36 × 10–05), and RMSSD (OR, 95% CI 1.56, 1.31–1.86, p = 6.32 × 10–07) were significantly associated with an increased odds of AF. Conclusion Longitudinal measures of uncorrected HRV were significantly associated with new-onset AF, especially among women. MR analyses supported the causal relationship between uncorrected measures of HRV with AF. Our findings indicate that measures to modulate HRV might prevent AF in the general population, in particular in women. Graphical abstract AF; atrial fibrillation, GWAS; genome-wide association study, IVW; inverse variance weighted, MR; Mendelian randomization, MR-PRESSO; MR-egger and mendelian randomization pleiotropy residual sum and outlier, RMSSD; root mean square of successive RR interval differences, RMSSDc; root mean square of successive RR interval differences corrected for heart rate, SDNN; standard deviation of normal to normal RR intervals, SDNNc; standard deviation of normal to normal RR intervals corrected for heart rate, WME; weighted median estimator. aRotterdam Study n=12,334 bHRV GWAS n=53,174 cAF GWAS n=1,030,836

Background: The potential bidirectional causal association between kidney function and atrial fibrillation (AF) remains unclear. Methods: We conducted a bidirectional two-sample Mendelian randomization (MR) analysis. From multiple genome-wide association studies (GWAS), we retrieved genetic variants associated with kidney function (estimated glomerular filtration rate based on creatinine (eGFRcreat), blood urea nitrogen (BUN), chronic kidney disease (CKD stage ≥G3): n = 1,045,620, eGFR based on cystatin C: n = 24,063-32,861, urine albumin-tocreatinine ratio (UACR), and microalbuminuria: n = 564,257), and AF (n = 1,030,836). The inverse-variance weighted method was used as our main analysis. Results: MR analyses supported a causal effect of CKD (n = 9 SNPs, odds ratio (OR): 1.10, 95% confidence interval (CI): 1.04–1.17, p-value = 1.97 × 10− 03), and microalbuminuria (n = 5 SNPs, OR: 1.26, 95% CI: 1.10–1.46, pvalue = 1.38 × 10− 03) on AF risk. We also observed a causal effect of AF on eGFRcreat (n = 97 SNPs, OR: 1.00, 95% CI: 1.00–1.00, p-value = 6.78 × 10− 03), CKD (n = 107 SNPs, OR: 1.06, 95% CI: 1.03–1.09, p-value = 2.97 × 10− 04), microalbuminuria (n = 83 SNPs, OR: 1.07, 95% CI: 1.04–1.09, p-value = 2.49 × 10− 08), and a suggestive causal effect on eGFRcys (n = 103 SNPs, OR: 0.99, 95% CI: 0.99–1.00, p-value = 4.61 × 10− 02). Sensitivity analyses, including weighted median estimator, MR-Egger, the MR pleiotropy residual sum and outlier test, and excluding genetic variants associated with possible confounders and/or horizontal mediators (myocardial infarction/coronary artery disease, heart failure) indicated that these findings were robust. Conclusions: Our results supported a bidirectional causal association between kidney function and AF. The shared genetic architecture between kidney dysfunction and AF might represent potential important therapeutic targets to prevent both conditions in the general population.

Sex differences and causality of the association between heart rate variability (HRV) and atrial fibrillation (AF) in the general population remain unclear.12,334 participants free of AF from the population-based Rotterdam Study were included. Measures of HRV including the standard deviation of normal RR intervals (SDNN), SDNN corrected for heart rate (SDNNc), RR interval differences (RMSSD), RMSSD corrected for heart rate (RMSSDc), and heart rate were assessed at baseline and follow-up examinations. Joint models, adjusted for cardiovascular risk factors, were used to determine the association between longitudinal measures of HRV with new-onset AF. Genetic variants for HRV were used as instrumental variables in a Mendelian randomization (MR) analysis using genome-wide association studies (GWAS) summary-level data.During a median follow-up of 9.4 years, 1302 incident AF cases occurred among 12,334 participants (mean age 64.8 years, 58.3% women). In joint models, higher SDNN (fully-adjusted hazard ratio (HR), 95% confidence interval (CI) 1.24, 1.04-1.47, p = 0.0213), and higher RMSSD (fully-adjusted HR, 95% CI 1.33, 1.13-1.54, p = 0.0010) were significantly associated with new-onset AF. Sex-stratified analyses showed that the associations were mostly prominent among women. In MR analyses, a genetically determined increase in SDNN (odds ratio (OR), 95% CI 1.60, 1.27-2.02, p = 8.36 × 10Longitudinal measures of uncorrected HRV were significantly associated with new-onset AF, especially among women. MR analyses supported the causal relationship between uncorrected measures of HRV with AF. Our findings indicate that measures to modulate HRV might prevent AF in the general population, in particular in women. AF; atrial fibrillation, GWAS; genome-wide association study, IVW; inverse variance weighted, MR; Mendelian randomization, MR-PRESSO; MR-egger and mendelian randomization pleiotropy residual sum and outlier, RMSSD; root mean square of successive RR interval differences, RMSSDc; root mean square of successive RR interval differences corrected for heart rate, SDNN; standard deviation of normal to normal RR intervals, SDNNc; standard deviation of normal to normal RR intervals corrected for heart rate, WME; weighted median estimator.

Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women.Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into 'single-documented AF episode', 'multiple-documented AF episodes', or 'long-standing persistent AF'. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis.We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as 'single-documented AF episode', 208 (1.5%) as 'multiple-documented AF episodes', and 57 (0.4%) as 'long-standing persistent AF'. In men, we found poorer trajectories of weight and waist circumference preceding 'long-standing persistent AF' as compared to the other patterns. In women, we found worse trajectories of all risk factors between 'long-standing persistent AF' and the other patterns.We developed a standardized method to classify AF patterns in the general population. Participants categorized as 'long-standing persistent AF' showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns.

Objective: To assess the sex-specific evolution of various anthropometric measures and the association of their longitudinal trajectories with new-onset atrial fibrillation (AF). Methods: Among 5266 men and 7218 women free of AF at baseline from the prospective population-based Rotterdam Study, each anthropometric measure was measured 1 to 5 times from 1989 to 2014. Anthropometric measures were standardized to obtain hazard ratios per 1 SD increase to enable comparison. Joint models were used to assess the longitudinal association between anthropometric measures and incident AF. Use of the joint models is a preferred method for simultaneous analyses of repeated measurements and survival data for conferring less biased estimates. Results: Mean (SD) age was 63.9 (8.9) years for men and 64.9 (9.8) years for women. Median follow-up time was 10.5 years. Longitudinal evolution of weight, height, waist circumference, hip circumference, and body mass index was associated with an increased risk of new-onset AF in both men and women. In joint models, larger height in men (hazard ratio [95% credible interval] per 1 SD, 1.27 [1.17 to 1.38]) and weight in women (1.24 [1.16 to 1.34]) showed the largest associations with AF. In joint models, waist to hip ratio was significantly associated with incident AF only in women (1.10 [1.03 to 1.18]). Conclusion: Considering the entire longitudinal trajectories in joint models, anthropometric measures were positively associated with an increased risk for new-onset AF among men and women in the general population. Increase in measure of central obesity showed a stronger association with increased risk of AF onset among women compared with men.