Journal of neurology · 2025
Data-driven subtypes of subjective cognitive decline: neuropsychological profiles, Alzheimer's disease biomarkers, and clinical trajectories.
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Mazzeo Salvatore, Boveri Sara, Bortolin Elisa, Bruschi Giulia, Girani Emanuele, Bombaci Alessandro, Pozzi Federico Emanuele, Corbari Maria Vittoria, Ambrogi Federico, Agosta Federica, Filippi Massimo, Salsone Maria, Alzheimer’s Disease Neuroimaging Initiative
Аннотация
OBJECTIVES: Subjective Cognitive Decline (SCD) is a heterogeneous condition recognized as the earliest manifestation of Alzheimer's disease (AD). We hypothesized that the heterogeneity of SCD may be synthesized in distinct subtypes.
METHODS: We analyzed data from the AD Neuroimaging Initiative (ADNI) database. For all participants, demographic variables, cognitive measures, APOE genotype, CSF biomarkers, brain MRI, and FDG-PET data were available. Participants underwent follow-up visits every 6 or 12 months.
RESULTS: 542 cognitively normal (CN), 346 SCD, and 423 early mild cognitive impairment (E-MCI) individuals were included. A data-driven approach based on cognitive measures identified three SCD clusters (k1, k2, k3) that performed differently in verbal memory (k2 outperformed all the groups and k3 showed the poorest performance, p < 0.001) and in executive function (k1 had the lowest scores, p = 0.006). Regarding CSF biomarkers, k2 exhibited lower p-tau (20.6 ± 9.2 vs. 24.2 ± 13.6, p = 0.03) and k3 had higher Aβ42 levels (1131.3 ± 379.8 vs. 942.87 ± 355.3, p = 0.01) compared to the E-MCI group, while there were no differences between k1 and E-MCI. Regarding brain FDG-PET, k1 demonstrated reduced uptake compared to CN, k2, and k3 (p < 0.001). During follow-up, k1 exhibited a higher rate of progression to MCI or dementia compared to k2 and k3 (Log-rank χ2 = 18.18, p = 0.0002) and a steeper decline in general cognition and long-term verbal memory compared to k2.
INTERPRETATION: We proposed a three-subgroup system classification for SCD, reflecting different cognitive profiles and longitudinal trajectories. Classifying individuals with SCD may enhance diagnostic pathways and inform personalized interventions.
METHODS: We analyzed data from the AD Neuroimaging Initiative (ADNI) database. For all participants, demographic variables, cognitive measures, APOE genotype, CSF biomarkers, brain MRI, and FDG-PET data were available. Participants underwent follow-up visits every 6 or 12 months.
RESULTS: 542 cognitively normal (CN), 346 SCD, and 423 early mild cognitive impairment (E-MCI) individuals were included. A data-driven approach based on cognitive measures identified three SCD clusters (k1, k2, k3) that performed differently in verbal memory (k2 outperformed all the groups and k3 showed the poorest performance, p < 0.001) and in executive function (k1 had the lowest scores, p = 0.006). Regarding CSF biomarkers, k2 exhibited lower p-tau (20.6 ± 9.2 vs. 24.2 ± 13.6, p = 0.03) and k3 had higher Aβ42 levels (1131.3 ± 379.8 vs. 942.87 ± 355.3, p = 0.01) compared to the E-MCI group, while there were no differences between k1 and E-MCI. Regarding brain FDG-PET, k1 demonstrated reduced uptake compared to CN, k2, and k3 (p < 0.001). During follow-up, k1 exhibited a higher rate of progression to MCI or dementia compared to k2 and k3 (Log-rank χ2 = 18.18, p = 0.0002) and a steeper decline in general cognition and long-term verbal memory compared to k2.
INTERPRETATION: We proposed a three-subgroup system classification for SCD, reflecting different cognitive profiles and longitudinal trajectories. Classifying individuals with SCD may enhance diagnostic pathways and inform personalized interventions.