Are biological aging metrics associated with increased risk of stroke and post-stroke all-cause mortality?
Multiple biological aging indicators, particularly the frailty index, are associated with increased stroke risk and post-stroke all-cause mortality, with bidirectional Mendelian randomization supporting a potential causal two-way relationship.
INTRODUCTION: Stroke is a major acute cerebrovascular disorder and a leading cause of disability and death, for which ageing is a key risk factor. However, individuals of the same chronological age differ markedly in cerebrovascular vulnerability. This study aimed to investigate the association between biological aging and stroke risk and prognosis using several validated aging metrics. METHODS: In NHANES 1999-2018, we derived the frailty index (FI), Klemera-Doubal age (KDMAge) and phenotypic age (PhenoAge) as alternative measures of biological aging. Logistic regression, tests for trend, restricted cubic splines and subgroup analyses were used to assess associations with stroke prevalence. Kaplan-Meier curves and Cox regression were applied to evaluate all-cause mortality among stroke survivors. In parallel, we conducted bidirectional two-sample Mendelian randomization (MR) using large genome-wide association studies to examine the potential causal effects of multiple biological aging indicators (four epigenetic age acceleration measures, telomere length, facial aging and FI) on stroke and its ischaemic subtypes, and the reverse effects of stroke on aging acceleration. RESULTS: Among 34,856 participants, higher FI, KDMAge and PhenoAge, as well as biological age acceleration, were associated with increased stroke risk; these associations remained significant in fully adjusted models. Dose-response analyses revealed non-linear relationships between biological aging metrics and stroke, with FI and PhenoAge showing J-shaped and KDMAge S-shaped patterns. In survival analyses of 1,167 stroke patients, PhenoAge acceleration and frailty status were significantly associated with reduced survival probability and higher all-cause mortality, whereas KDMAge acceleration showed weaker prognostic value. In MR analyses meta-analysing GIGASTROKE and MEGASTROKE, genetically predicted FI was associated with higher risk of stroke overall (OR = 1.57, 95 % CI: 1.36-1.83, p < 0.001) and with major ischaemic subtypes, while other aging clocks showed weaker or subtype-specific associations. Reverse MR indicated that stroke liability was associated with higher PhenoAge acceleration (OR = 1.54, 95 % CI: 1.12-2.12, p = 0.008), higher FI (OR = 1.11, 95 % CI: 1.05-1.17, p < 0.001) and accelerated facial aging (OR = 1.02, 95 % CI: 1.01-1.03, p = 0.001). CONCLUSION: In a nationally representative sample, multiple biological aging indicators were associated with stroke and post-stroke all-cause mortality, and bidirectional MR supported a potential two-way relationship between biological aging and stroke. Among the evaluated metrics, FI showed the most robust and consistent associations with stroke risk and survival and provided the clearest and most stable genetic evidence compatible with a causal effect on stroke and its ischaemic subtypes. These findings support the FI as a practical tool for capturing biological aging in stroke risk stratification and secondary prevention, a proposition that warrants testing in prospective and interventional studies..
Wang et al. (Mon,) studied this question.