What characterizes the exceptional cognition of superagers? A systematic review of multidomain biomarkers of successful cognitive aging.

BACKGROUND AND

OBJECTIVES

Substantial heterogeneity in cognitive aging trajectories has been observed among older adults, with some individuals maintaining exceptional cognitive function ("superagers" or "successful cognitive aging [SCA]"). The biological mechanisms underlying SCA remain unclear. This systematic review synthesizes current evidence on quantifiable SCA biomarkers to address this critical gap.

RESEARCH DESIGN AND

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we systematically searched PubMed, Scopus, PsycINFO, and Web of Science (up to December 2024). After screening 6,699 records, 62 studies met the inclusion criteria. Data from included studies were extracted, assessed for risk of bias, and synthesized for integrated findings.

RESULTS

We identified 34 SCA definitions, categorized them into three types, and analyzed biomarkers across six domains: (1) genetic/epigenetic biomarkers, (2) biofluid biomarkers, (3) histological biomarkers, (4) positron emission tomography biomarkers, (5) structural magnetic resonance imaging biomarkers, and (6) functional neuroimaging biomarkers. Integrated findings suggest that SCA is driven by unique multidomain biological mechanisms (e.g., young DNA methylation age, high von Economo neuron density, and efficient glucose metabolism, etc.), not merely resistance to age-related neuropathology such as amyloid-β and tau. Neuroimaging findings highlight the role of brain reserve, maintenance, and compensation on SCA, particularly within a newly defined "cingulate gyrus-medial temporal lobe-frontal cortex" brain signature.

DISCUSSION AND IMPLICATIONS: This systematic review advances our understanding of SCA's biological substrates, provides theoretical frameworks for future SCA biomarker research, and offers a foundation for future strategies to promote cognitive health in aging populations.