Oct 2026· npj Dementia· Vol 2· 0 citations· 75 references
Medicine
TL;DR
The study identified four cognitively derived subtypes of MCI, with strong associations observed for lifestyle and psychological factors, highlighting the potential value of personalised, early approaches to MCI management.
Abstract
Mild cognitive impairment (MCI) is heterogenous, but classification often overlooks regional variability. Cross-sectional data including 764 individuals from the Biomarker and Cognition study, Singapore, aged >50 years with MCI based on Montreal Cognitive Assessment normative cut-offs were utilised. Latent profile analyses utilising BIC thresholds were applied to demographically adjusted cognitive assessments. Hierarchical regression evaluated demographic, cardiometabolic, psychological, lifestyle and biomarker predictors of subtypes. Participants had a mean age of 62.72 ± 7.66, 59% females, 14.50 ± 3.44 education years. Four subtypes of MCI emerged; above-average performers (39.0%), multi-domain impaired (19.6%), visuospatial preserved (15.2%), and processing speed preserved (26.2%). Relative to multi-domain impaired, lower body mass index, alcohol consumption and better quality of life were associated with above-average performers and processing speed preserved membership. Greater grip strength and lower cardiometabolic burden were associated with visuospatial preserved membership. Plasma Aβ40 showed a preliminary, exploratory association with cluster membership. In conclusion, the study identified four cognitively derived subtypes of MCI, with strong associations observed for lifestyle and psychological factors. Hence, highlighting the potential value of personalised, early approaches to MCI management.
Objectives To examine whether intrinsic capacity impairment predicts incident dementia across three countries and to evaluate its value for risk stratification. Design : Harmonized multicohort study with individual participant data meta-analysis. Setting and participants Community-dwelling adults aged ≥50 years without...
Yu-Long Zhou, Ying-Zheng Guo· The Journal of Nutrition, He...· 0 citations
Routine non-cognitive data support moderate, well-calibrated MCI discrimination, but machine learning added little over regression, but this is an exploratory triage aid requiring external validation.
Ayuto Kodama, Takako Ohnuma, Kana Sasaki et al.· Geriatrics· 0 citations
BackgroundDementia prevention is a global health priority, yet most large-scale population studies come from Western settings. Japan, a rapidly aging society, provides a unique non-Western epidemiological context for characterizing cognitive decline.ObjectiveTo assess whether the Tohoku Medical Megabank (TMM) cohorts r...
Ryo Takano, John A. Moyer, Takashi Fukushima et al.· Journal of Alzheimer's Disea...· 0 citations
OBJECTIVES
Exposure to modifiable dementia risk factors (MDRFs) contributes substantially to dementia risk across the life course. Less is known about persistence and changes in these factors during mid- and later life and how they relate to early neurophysiological changes associated with dementia. This study examined...
Joanne Allen, Michelle Kelly, G. Livingston et al.· International Psychogeriatri...· 0 citations
OBJECTIVE
To examine whether a four-domain non-cognitive intrinsic capacity (IC) profile, excluding cognition to avoid exposure-outcome circularity, is associated with cognitive ageing across three international cohorts.
METHODS
We analysed harmonised CHARLS, ELSA, and HRS data from 26,022 adults aged ≥60 years (132,...
Wei-Ming Li, Qi-Qi Yang, Zhe Wang et al.· Archives of gerontology and...· 0 citations
Background Mild cognitive impairment (MCI) is clinically heterogeneous, yet most prognostic studies rely on binary conversion endpoints or expensive biomarkers unavailable in routine practice. Objective To identify trajectory classes of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) progression in MCI using latent...
Yeonsil Moon, S. W. Seo, Min-Young Noh et al.· Journal of Alzheimer's Disea...· 0 citations
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