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Association of Vascular Aging Phenotypes with Adverse Clinical Outcomes in the Chinese Population: A Multicentre

Ting Xu1,2, Yucong Zhang1,2, Yi Zhou3

  • 1Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China.

Clinical Interventions in Aging
|April 3, 2025
PubMed

Insights

Vascular aging phenotypes predict clinical outcomes. Early vascular aging (EVA) increases risks for adverse events, while supernormal vascular aging (SUPERNOVA) shows protective effects, independent of traditional risk scores.

Area of Science:

  • Cardiovascular Medicine
  • Aging Research
  • Biostatistics

Background:

  • Vascular aging (VAg) is a critical determinant of cardiovascular health.
  • Understanding VAg phenotypes can refine risk prediction beyond chronological age (CA).

Purpose of the Study:

  • To investigate the clinical implications of VAg phenotypes.
  • To classify VAg into early (EVA), normal, and supernormal (SUPERNOVA) based on the difference between CA and vascular age (VA).

Main Methods:

  • Defined VA using multivariable linear regression with arterial parameters and risk factors in a cross-sectional cohort (n=15580).
  • Classified VAg phenotypes based on Δ-age percentiles.
  • Utilized Cox survival analysis in an independent prospective cohort (n=5316) to assess associations with adverse clinical outcomes.

Main Results:

  • Compared to normal VAg, EVA showed significantly increased risk for adverse outcomes (HR: 2.43) and cardiovascular events, including stroke and myocardial infarction.
  • SUPERNOVA phenotype demonstrated a decreased risk for adverse outcomes (HR: 0.75).
  • VAg phenotypes improved cardiovascular event prediction models, enhancing C-statistics.

Conclusions:

  • This study is the first to validate VAg phenotypes using multicentric data and external validation in China.
  • VAg phenotypes offer a potential tool for identifying individuals susceptible or resilient to vascular aging.
  • The findings highlight the clinical utility of VAg phenotypes in cardiovascular risk stratification.
Abstract

Keywords:
age-related diseasecarotid intima-media thicknesspulse wave velocityrisk assessmentvascular agevascular aging

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