Causal effect of hair color in atherosclerotic cardiovascular disease: a two-sample Mendelian randomization study

Background Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of morbidity and mortality worldwide. Early identification and intervention of individuals at risk are crucial for delaying disease progression. Human phenotypic characteristics, including hair color, have been associated with ASCVD risk. However, a direct causal link between hair color and ASCVD has not been established, particularly in the context of Mendelian randomization (MR) studies. Objective To investigate the causal relationship between hair color and ASCVD using a two-sample MR approach. Methods We applied a two-sample MR approach to generate unconfounded estimates from summary statistics of 10 independent, large meta-analyses of genome-wide association studies on hair color and ASCVD. The inverse variance-weighted (IVW) method was used as the primary approach to assess causality. Result Blonde hair was inversely associated with several ASCVDs, including atherosclerosis (AS) (OR: 0.72, P = 0.018), peripheral atherosclerosis (PAS) (OR: 0.72, P = 0.025), peripheral artery disease (PAD) (OR: 0.71, P = 0.013), coronary heart disease (CHD) (OR: 0.84, P = 0.042), and myocardial infarction (MI) (OR: 0.82, P = 0.03). Light brown hair showed a similar relationship with AS (OR: 0.71, P = 0.045), PAS (OR: 0.71, P = 0.044), and MI (OR: 0.86, P = 0.046), but no association with CHD or PAD. Red hair showed no significant association with ASCVD. Dark brown hair was linked to higher risks of CHD (OR: 1.10, P = 0.019) and MI (OR: 1.13, P = 0.011), while black hair was associated with increased risks of PAS (OR: 2.17, P = 0.032) and MI (OR: 1.47, P = 0.037). Conclusion This two-sample MR study identified a causal relationship between hair color and ASCVD. Light hair, particularly blonde, is associated with a lower risk of ASCVD, while dark hair, including dark brown and black, is associated with a higher risk. These findings may provide new insights for the early detection and risk stratification of ASCVD.