The Cortical Signature of Alzheimer's Disease: Regionally Specific Cortical Thinning Relates to Symptom Severity in Very Mild to Mild AD Dementia and is Detectable in Asymptomatic Amyloid-Positive Individuals

TLDR

Alzheimer’s disease involves neurodegeneration of limbic and heteromodal cortical regions, yet it remains uncertain whether cortical thinning can be reliably measured across diverse cohorts, track symptom progression, or be detected before clinical onset. The authors mapped cortical thinning in mild AD to define regions of interest, then applied this hypothesis‑driven ROI set to additional subject samples. The study identifies a reproducible in‑vivo cortical thinning signature that mirrors known AD neuropathology, correlates with early symptom severity, is detectable in asymptomatic amyloid‑positive individuals, and demonstrates reliability and clinical validity as a potential imaging biomarker, offering a robust framework for neuropsychiatric research.

Abstract

Alzheimer's disease (AD) is associated with neurodegeneration in vulnerable limbic and heteromodal regions of the cerebral cortex, detectable in vivo using magnetic resonance imaging. It is not clear whether abnormalities of cortical anatomy in AD can be reliably measured across different subject samples, how closely they track symptoms, and whether they are detectable prior to symptoms. An exploratory map of cortical thinning in mild AD was used to define regions of interest that were applied in a hypothesis-driven fashion to other subject samples. Results demonstrate a reliably quantifiable in vivo signature of abnormal cortical anatomy in AD, which parallels known regional vulnerability to AD neuropathology. Thinning in vulnerable cortical regions relates to symptom severity even in the earliest stages of clinical symptoms. Furthermore, subtle thinning is present in asymptomatic older controls with brain amyloid binding as detected with amyloid imaging. The reliability and clinical validity of AD-related cortical thinning suggests potential utility as an imaging biomarker. This "disease signature" approach to cortical morphometry, in which disease effects are mapped across the cortical mantle and then used to define ROIs for hypothesis-driven analyses, may provide a powerful methodological framework for studies of neuropsychiatric diseases.