Association between alopecia areata and cardiovascular disease: a systematic review and meta-analysis - Lu, Jiawei; Cao, Xuechen; Feng, Yifei; Yu, Yongkai; Lu, Yan (Frontiers in Immunology, 2025)
BackgroundAlopecia areata (AA) is a common autoimmune disorder causing patchy hair loss. Epidemiological observations and molecular studies collectively suggest an underrecognized interplay between AA and cardiovascular disease (CVD). However, the relationship between them remains controversial and requires further investigation.ObjectiveTo evaluate the association between AA and CVD through a meta-analysis of combinable results.MethodsWe systematically searched four databases (MEDLINE, Embase, Web of Science, and Cochrane Library) for relevant studies from inception to December 6, 2024. Studies included in the analysis were cohort or case-control studies that focused on the relationship between AA and CVD. Two independent reviewers extracted the data. The study quality was evaluated using the Newcastle-Ottawa Scale. A random-effects model was used for meta-analysis to calculate the odds ratio (OR) and 95% confidence intervals (CIs).ResultsOur search yielded five studies involving 238,270 AA patients from three countries. The meta-analysis revealed that AA patients had an increased OR (OR = 1.71; 95% CI: 1.0 to 2.92; p < 0.01) for CVD outcomes compared to the control group. Subgroup analysis revealed a stronger risk in patients with alopecia totalis or alopecia universalis (OR = 3.80; 95% CI: 1.65 to 8.73; p < 0.01). Associations were not observed between patch-type AA and CVD, nor between AA and ischemic stroke or myocardial infarction.ConclusionsThis meta-analysis suggests that AA patients, especially those with alopecia totalis or alopecia universalis, may have an elevated risk of developing CVD. Given the shared immunological mechanisms, systemic inflammation in AA may contribute to the development of atherosclerosis and increased cardiovascular risk. Further studies are needed to validate these findings and clarify the underlying mechanisms.