ArticleResearch square2026
Disentangling global atrophy burden from local structural patterns reveals clinically relevant heterogeneity in mild cognitive impairment.
Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Mild cognitive impairment (MCI) is a heterogeneous prodromal stage of Alzheimer's disease (AD). Imaging-based subtyping studies, however, often confound overall disease severity with local anatomical variation, limiting biological interpretability and clinical utility. We aimed to separate global neurodegenerative burden from local structural patterns and examine their clinical relevance in MCI. Methods: Baseline ADNI-1 data from 731 participants were analyzed, including 205 cognitively normal individuals, 351 with MCI, and 175 with AD. A global atrophy index (GAI) was constructed from whole-brain gray matter volume, white matter volume, cerebrospinal fluid volume, and mean cortical thickness to quantify overall neurodegenerative burden. Candidate regions of interest were screened in the full sample. Within MCI, regional measures were residualized against age, sex, education, and GAI to derive local structural features independent of global atrophy. Principal component analysis and unsupervised clustering were then used to identify subtypes. Associations with cognition, daily functioning, and neuropsychiatric symptoms were assessed using multivariable linear regression, and nested models were compared to quantify incremental explained variance (ΔR Results: The GAI showed a clear gradient across cognitively normal, MCI, and AD groups. After controlling for GAI, two reproducible local structural patterns were identified within MCI: a thalamic-subcortical subtype and a frontal-paralimbic subtype. Subtype differences remained associated with cognition and daily functioning after adjustment for demographic factors and GAI, whereas associations with neuropsychiatric symptoms were not significant or were markedly weaker. Adding PC-based continuous local residual features provided incremental explanatory value for ADAS-Cog13 and FAQ beyond models including subtype labels. Conclusions: MCI heterogeneity is not explained solely by global brain atrophy. Local structural patterns independent of overall neurodegenerative burden capture clinically meaningful variation and may improve imaging-based stratification in prodromal AD.
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