Acquired risk factors and incident atrial fibrillation according to age and genetic predisposition

Abstract

Background and aims: Atrial fibrillation (AF) is the most common sustained arrhythmia in adults. Investigations of risk factor profiles for AF according to age and genetic risk groups are essential to promote individualized strategies for the prevention and control of AF.

Methods: A total of 409 661 participants (mean age, 56 years; 46% men) free of AF at baseline and with complete information about risk factors were included from the UK Biobank cohort. The hazard ratios and population-attributable risk (PAR) percentages of incident AF associated with 23 risk factors were examined, including 3 social factors, 7 health behaviours, 6 cardiometabolic factors, 6 clinical comorbidities, and the genetic risk score (GRS), across 3 age groups (40-49, 50-59, and 60-69 years) and 3 genetic risk groups (low, moderate, and high GRS).

Results: After a follow-up of 5 027 587 person-years, 23 847 participants developed AF. Most cardiometabolic factors and clinical comorbidities showed a significant interaction with age, whereby the associations were generally strengthened in younger groups (Pinteraction < .002). However, only low LDL cholesterol, renal dysfunction, and cardiovascular disease showed a significant interaction with genetic risk, and the associations with these factors were stronger in lower genetic risk groups (Pinteraction < .002). Cardiometabolic factors consistently accounted for the largest number of incident AF cases across all age groups (PAR: 36.2%-38.9%) and genetic risk groups (34.0%-41.9%), with hypertension and overweight/obesity being the two leading modifiable factors. Health behaviours (PAR: 11.5% vs. 8.7%) and genetic risk factors (19.1% vs. 14.3%) contributed to more AF cases in the 40-49 years group than in the 60-69 years group, while the contribution of clinical comorbidities remained relatively stable across different age groups. The AF risk attributable to overall cardiometabolic factors (PAR: 41.9% in the low genetic risk group and 34.0% in the high genetic risk group) and clinical comorbidities (24.7% and 15.9%) decreased with increasing genetic risk. The impact of social factors on AF was relatively low across the groups by age and genetic risk.

Conclusions: This study provided comprehensive information about age- and genetic predisposition-related risk factor profiles for AF in a cohort of UK adults. Prioritizing risk factors according to age and genetic risk stratifications may help to achieve precise and efficient prevention of AF.

Keywords: Age; Atrial fibrillation; Genetic risk; Risk profile; UK Biobank.

Structured Graphical Abstract

Age-specific and genetic predisposition-specific associations of risk factor profiles with atrial fibrillation (AF). Population-attributable risk percentages of AF risk factors were presented for different age and genetic risk population groups.

Figure 1

Multivariable-adjusted hazard ratios (95% confidence intervals) of incident atrial fibrillation associated with risk factors in different age groups (A) and genetic risk groups (B). Models were adjusted for sex, age, ethnicity, and the use of lipid-lowering medication and were mutually adjusted for individual risk factors. Statistical significance was defined as a Bonferroni-corrected threshold of P < .002 (.05/23). LDL-C, low-density lipoprotein cholesterol; CRP, C-reactive protein; COPD, chronic obstructive pulmonary disease

Figure 2

Multivariable-adjusted hazard ratios (95% confidence intervals) of incident atrial fibrillation associated with risk scores in different age groups (A) and genetic risk groups (B). Models were adjusted for sex, age, ethnicity, the use of lipid-lowering medication and individual risk factors that were not included in the risk score. Statistical significance was defined using Bonferroni-corrected thresholds of P < .013 (.05/4)

Figure 3

Partial population-attributable risk percentages for incident atrial fibrillation associated with risk factors in different age groups (A) and genetic risk groups (B). Values are expressed as population-attributable risk percentages (95% confidence intervals). Models were adjusted for sex, age, ethnicity, and the use of lipid-lowering medication and were mutually adjusted for individual risk factors. Since this threshold for determining an increase in risk is 0, the risk factors with negative population-attributable risk percentages were excluded from the models and were truncated at the limit of 0. LDL-C, low-density lipoprotein cholesterol; CRP, C-reactive protein; COPD, chronic obstructive pulmonary disease

Figure 4

Partial population-attributable risk percentages for incident atrial fibrillation associated with combinations of risk factors by age group (A) and genetic risk group (B). Models were adjusted for sex, age, ethnicity, the use of lipid-lowering medication and individual risk factors that were not included in the risk score