Literature DB >> 31104279

Detecting biological heterogeneity patterns in ADNI amnestic mild cognitive impairment based on volumetric MRI.

Ali Ezzati1,2, Andrea R Zammit3, Christian Habeck4, Charles B Hall5, Richard B Lipton3,6,5.   

Abstract

There is substantial biological heterogeneity among older adults with amnestic mild cognitive impairment (aMCI). We hypothesized that this heterogeneity can be detected solely based on volumetric MRI measures, which potentially have clinical implications and can improve our ability to predict clinical outcomes. We used latent class analysis (LCA) to identify subgroups among persons with aMCI (n = 696) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI), based on baseline volumetric MRI measures. We used volumetric measures of 10 different brain regions. The subgroups were validated with respect to demographics, cognitive performance, and other AD biomarkers. The subgroups were compared with each other and with normal and Alzheimer's disease (AD) groups with respect to baseline cognitive function and longitudinal rate of conversion. Four aMCI subgroups emerged with distinct MRI patterns: The first subgroup (n = 404), most similar to normal controls in volumetric characteristics and cognitive function, had the lowest incidence of AD. The second subgroup (n = 230) had the most similar MRI profile to early AD, along with poor performance in memory and executive function domains. The third subgroup (n = 36) had the highest global atrophy, very small hippocampus and worst overall cognitive performance. The fourth subgroup (n = 26) had the least amount of atrophy, however still had poor cognitive function specifically in in the executive function domain. Individuals with aMCI who were clinically categorized within one group other showed substantial heterogeneity based on MRI volumetric measures.

Entities:  

Keywords:  Alzheimer’s disease; Amnestic MCI; Cognitive function; Latent class analysis; Volumetric MRI

Mesh:

Year:  2020        PMID: 31104279      PMCID: PMC7203761          DOI: 10.1007/s11682-019-00115-6

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


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