Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI

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 A beta 142 concentration for the former and CSF A beta 1-42 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. (c) 2023 Elsevier Inc. All rights reserved.

Automated summary

There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). In this study, MCI participants were divided into three neuropsychological subgroups. The study found specific predictive features that can differentiate different subgroups and cognitively normal individuals. The comprehensive data analytics strategy provides further evidence of the clinical and neurobiological significance of multimodal neuropsychological subtyping.