Neural correlates of subjective cognitive decline in Alzheimer’s disease: a systematic review of structural and functional brain changes for early diagnosis and intervention - Marafioti, Giulia; Culicetto, Laura; Latella, Desirèe; Marra, Angela; Quartarone, Angelo; Lo Buono, Viviana (Frontiers in Aging Neuroscience, 2025)
BackgroundSubjective Cognitive Decline (SCD) is increasingly recognized as a preclinical stage of Alzheimer’s disease (AD), representing a critical window for early detection and intervention. Understanding the structural and functional neural changes in SCD can improve diagnosis, monitoring, and management of this early stage of disease.MethodsA systematic review was conducted using PubMed, Web of Science, and Scopus databases to identify studies examining neuroanatomical, neurofunctional, and neuroimaging findings in individuals with SCD. Inclusion criteria emphasized studies exploring SCD’s potential as an early biomarker for AD progression.ResultsA total of 2.283 studies were screened, with 17 meeting the inclusion criteria. Evidence indicates that SCD is associated with cortical thinning and reductions in gray matter volume (GMV), particularly in the hippocampus, entorhinal cortex, and medial temporal lobe. Functional imaging studies reveal disruptions in the default mode network (DMN), executive control networks (ECN), and sensorimotor networks (SMN), indicating both compensatory mechanisms and early dysfunction. Dynamic functional connectivity studies report reduced brain activity efficiency, while graph theory analyses show decreased network integration. Advanced neuroimaging techniques and machine learning (ML) approaches demonstrate significant promise in detecting subtle neural changes in SCD, with applications for early diagnosis and monitoring disease progression.ConclusionSCD represents a heterogeneous condition characterized by mixed compensatory and degenerative neural changes, marking a critical early stage in the AD continuum. Combining structural and functional brain alterations with advanced neuroimaging and ML methodologies provides valuable biomarkers for early detection. Future longitudinal and multimodal studies are essential to standardize methodologies, account for individual variability, and develop personalized interventions aimed at mitigating progression to dementia.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024616052, CRD42024616052.