It is demonstrated that brain-PAD is a clinically meaningful, transdiagnostic biomarker of neurodegeneration that complements conventional volumetric measures like the BPF.
OBJECTIVE
To characterize spatiotemporal atrophy subtypes in biomarker-confirmed Alzheimer's disease (AD) and examine their cognitive, vascular, molecular, and longitudinal correlates.
METHODS
We applied Subtype and Stage Inference (SuStaIn) to baseline structural magnetic resonance imaging (MRI) from 484 amyloid-positive patients using 17 regional volumes. We compared subtype-specific cognition, cerebral small vessel disease burden, and post-baseline Mini-Mental State Examination (MMSE) trajectories; vascular risk factors and fluid biomarkers were exploratory. In a complete-case subset (45 patients; 134 observations), we compared SuStaIn with cerebrospinal fluid (CSF), plasma, hippocampal-volume, and combined-biomarker prognostic models.
RESULTS
A four-subtype solution was reproducible across cross-validation folds (Bhattacharyya coefficient, 0.93): Typical (55%), Parietal-predominant (18%), Limbic-predominant (14%), and Hippocampal-sparing (13%). Higher SuStaIn stages correlated with lower baseline MMSE scores (ρ = -0.56). The Parietal-predominant subtype showed earlier onset, executive and visuospatial dysfunction, and rapid MMSE decline. The Limbic-predominant subtype showed delayed-recall and naming deficits. The Hippocampal-sparing subtype showed relative delayed-recall preservation, the highest adjusted deep white matter hyperintensity burden, and the lowest adjusted perivascular space count. It also had a higher adjusted CSF t-tau/Aβ42 ratio than the Typical and Parietal-predominant subtypes. SuStaIn showed the best in-sample prognostic performance based on marginal R² (0.579; comparator range, 0.239-0.483) and AIC.
CONCLUSIONS
Biomarker-confirmed AD comprised internally reproducible atrophy trajectories with distinct cognitive, vascular, and molecular profiles. Spatiotemporal MRI may complement fluid biomarkers and conventional volumetry for patient stratification and prognosis. External validation is required to establish predictive generalizability.
Chen-Hui Mao, Yu-Yue Qiu, Bo Li et al.· NeuroImage· 0 citations
In cognitively unimpaired older adults, elevated blood p-tau217 was linked to faster shrinkage in AD-specific brain regions, whereas NfL and GFAP were associated with more widespread atrophy, with NfL also associated with accelerated WMH accumulation.
Martina Valletta, D. L. Vetrano, E. J. Laukka et al.· Annals of Neurology· 0 citations
In this large longitudinal sample of asymptomatic individuals, the Aβ-dominant biomarker component showed the strongest association with longitudinal GM atrophy and cognitive decline, beyond the effects of tau pathophysiology and neuroaxonal injury.
W. Pelkmans, R. Cacciaglia, Michalis Kassinopoulos et al.· Molecular Neurodegeneration· 0 citations
BAG is a reliable non-invasive marker of structural brain health sensitive to AD pathology and to modifiable AD risk and supports its relevance for early risk stratification and prevention-oriented research.
E. Kuhn, G. Antopoulos, L. Kleineidam et al.· medRxiv· 0 citations
ABSTRACT Parkinson's disease (PD) encompasses motor and neuropsychiatric symptoms (NPS) including depression, anxiety, and apathy. Cognitive subtypes—PD with mild cognitive impairment (PD‐MCI) and PD with dementia (PDD)—and the related Dementia with Lewy Bodies (DLB) exist within the spectrum of Lewy body disease (LBD). While NPS are a major comorbidity, established imaging biomarkers are not available, nor is the neuronal basis well known. Additionally, prevalence of NPS may be linked to cognitive status. The hippocampus is implicated in the development of NPS and may undergo microstructural changes that are not reflected in volume changes. High‐resolution diffusion tensor imaging (DTI) was used to identify hippocampal changes in LBD compared to healthy controls (HC) and examine the relationship with NPS within the LBD group, both through association with DTI measures as well as comparison of cognitive subgroups. The hippocampus was manually segmented in 38 LB spectrum participants (aged 58–87 years, 32% female) and 35 HC (aged 50–83 years, 54% female) on high‐resolution (1 × 1 × 1 mm3) DTI. The LBD group (LBD‐All) was divided into LBD‐Cognitively Impaired (LBD‐CI) and LBD‐Cognitively Unimpaired (LBD‐CU). Hippocampal volume, mean diffusivity (MD), and fractional anisotropy (FA) were extracted and compared across groups. Relationships between significantly different hippocampal measures and depression, anxiety, and apathy were explored within the LBD‐All group. Hippocampal FA was lower in LBD‐All relative to HC; however, no differences in MD or volume were observed. Hippocampal FA was positively associated with depression scores within LBD‐All. There were no differences in volume, MD, or FA between LBD‐CI and LBD‐CU. Lower hippocampal fractional anisotropy in the LBD spectrum relative to HC potentially reflects microstructure alterations; however, higher hippocampal FA in LBD with more severe depression suggests more complex microstructural changes such as altered synaptic density, Lewy neurite organization, or neuroplastic changes.
Alexandra S. Budd, K. Solar, Myrlene Gee et al.· Hippocampus· 0 citations
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by large-scale network disruption. While static functional connectivity (sFC) has been extensively studied, dynamic functional connectivity (dFC) and its discriminative value across the AD spectrum remain insufficiently understood. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data from 174 participants in the Alzheimer's Disease Neuroimaging Initiative, including cognitively normal (CN, n = 44), subjective memory concern (SMC, n = 24), early mild cognitive impairment (EMCI, n = 46), late MCI (LMCI, n = 30), and AD (n = 30), were analyzed to assess group differences in sFC, dFC, and graph-theoretical metrics, as well as their associations with cognition. A BrainNetCNN model was further employed to evaluate the classification performance of sFC, dFC, and their combined features. The results revealed that sFC decreased across MCI stages but increased in AD, whereas dFC variability was predominantly reduced in the pre-dementia groups and increased in AD, particularly in frontal and temporal regions. Several static graph-theoretical metrics were significantly correlated with Mini-Mental State Examination (MMSE) scores, while dFC provided complementary information. In classification tasks, dFC showed higher accuracy than sFC in binary and five-class tasks, and their integration achieved the highest accuracy (CN vs. SMC: 89.6%; five-class: 82.7%). These findings suggest that dFC may provide complementary imaging information for characterizing stage-related network alterations and differentiating diagnostic groups across the AD spectrum.
Rong Guo, Deyu Li, Xingxing Zhang et al.· Experimental Gerontology· 0 citations
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