Magnetic Resonance Imaging and Cerebrospinal Fluid Biomarker Clustering Defines Biological Subtypes of Alzheimer’s Disease
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background/Objectives: Alzheimer’s disease (AD) exhibits clinical and biological variability. This study aimed to identify MRI-defined subtypes reflecting distinct biological pathways of neurodegeneration and cognitive decline. Methods: We applied principal component analysis followed by k-means clustering (k = 3) on volumetric MRI data from 924 participants and validated clusters using cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, p-tau, CTRED, MAPres, glucose, CTWHITE). Results: Three major phenotypes emerged: (1) a tau/vascular limbic subtype with pronounced hippocampal and amygdala atrophy and elevated tau and CTRED levels; (2) a volume-preserved, low-amyloid subtype consistent with early-stage or cognitively resilient AD; and (3) a diffuse-atrophy subtype with high amyloid and tau burden and ventriculomegaly. Comparative analysis revealed progressive biological shifts from amyloid accumulation to tau aggregation and vascular compromise across these clusters. Conclusions: MRI-based clustering validated by CSF biomarkers delineates biologically meaningful AD endophenotypes. The results suggest a gradual cognitive decline driven by amyloid–tau–vascular interactions, supporting multimodal phenotyping as a practical approach for precision staging and intervention.
Source: Biomedicines
Authors: Rafail C. Christodoulou, Georgios Vamvouras, Maria Daniela Sarquis, Vasileia Petrou, Platon S. Papageorgiou, Ludwing Rivera, Celimar Morales, Gipsany Rivera, Evros Vassiliou, Elena E. Solomou, Sokratis G. Papageorgiou
Institutions: Stanford Medicine, Stanford University, National Technical University of Athens, Universidad de Carabobo, University of Ioannina, Children's Hospital Agia Sophia, American University of Antigua, Kean University, University of Patras, National and Kapodistrian University of Athens, Eginition Hospital
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4415616458
