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Updated: Jul 16, 2025
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Published on: April 23, 2021
Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI
Jeremy Lefort-Besnard1, Mikael Naveau2, Nicolas Delcroix2
1Normandie Univ, UNICAEN, INSERM, COMETE, Caen, France.
Abstract:
There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). An important line of research is whether neuropsychologically-defined subtypes have distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarker composition. In our study, we demonstrated that MCI participants of the ADNI database (N = 640) can be discriminated into 3 coherent neuropsychological subgroups. Our clustering approach revealed amnestic MCI, mixed MCI, and cluster-derived normal subgroups. Furthermore, classification modeling revealed that specific predictive features can be used to differentiate amnestic and mixed MCI from cognitively normal (CN) controls: CSF Aβ142 concentration for the former and CSF Aβ1-42 concentration, tau concentration as well as grey matter atrophy (especially in the temporal and occipital lobes) for the latter. In contrast, participants from the cluster-derived normal subgroup exhibited an identical profile to CN controls in terms of cognitive performance, brain structure, and CSF biomarker levels. Our comprehensive data analytics strategy provides further evidence that multimodal neuropsychological subtyping is both clinically and neurobiologically meaningful.
Insights
Researchers identified three distinct subgroups within mild cognitive impairment (MCI) using neuropsychological assessments. These subtypes show unique patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarkers, aiding clinical and biological understanding.
Area of Science:
- Neuroscience
- Neurology
- Biomarker Research
Background:
- Mild cognitive impairment (MCI) is increasingly recognized as heterogeneous.
- Understanding distinct MCI subtypes is crucial for targeted research and interventions.
- Neuropsychological profiles may correlate with underlying neurodegenerative patterns and biomarker changes.
Purpose of the Study:
- To determine if neuropsychologically-defined subtypes of MCI exhibit distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarkers.
- To identify specific predictive features differentiating MCI subtypes from cognitively normal (CN) controls.
Main Methods:
- Utilized data from 640 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.
- Applied clustering analysis to neuropsychological data to identify distinct MCI subgroups.
- Employed classification modeling to identify predictive features differentiating subgroups, including CSF Aβ1-42, tau, and grey matter atrophy.
Main Results:
- Successfully discriminated MCI participants into three coherent neuropsychological subgroups: amnestic MCI, mixed MCI, and a cluster-derived normal subgroup.
- Identified specific biomarkers distinguishing amnestic and mixed MCI from CN controls: CSF Aβ1-42 for amnestic MCI, and CSF Aβ1-42, tau, and temporal/occipital grey matter atrophy for mixed MCI.
- The cluster-derived normal subgroup showed cognitive, structural, and biomarker profiles indistinguishable from CN controls.
Conclusions:
- Multimodal neuropsychological subtyping of MCI is clinically and neurobiologically meaningful.
- Distinct MCI subtypes possess unique neurodegenerative signatures and CSF biomarker profiles.
- This subtyping approach enhances the understanding of MCI heterogeneity and progression.
