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Heterogeneity of Alzheimer's disease identified by neuropsychological test profiling.

ABSTRACT: Alzheimer's disease (AD) is a highly heterogeneous disorder. Untangling this variability could lead to personalized treatments and improve participant recruitment for clinical trials. We investigated the cognitive subgroups by using a data-driven clustering technique in an AD cohort. People with mild-moderate probable AD from Taiwan was included. Neuropsychological test results from the Cognitive Abilities Screening Instrument were clustered using nonnegative matrix factorization. We identified two clusters in 112 patients with predominant deficits in memory (62.5%) and non-memory (37.5%) cognitive domains, respectively. The memory group performed worse in short-term memory and orientation and better in attention than the non-memory group. At baseline, patients in the memory group had worse global cognitive status and dementia severity. Linear mixed effect model did not reveal difference in disease trajectory within 3 years of follow-up between the two clusters. Our results provide insights into the cognitive heterogeneity in probable AD in an Asian population.

SUBMITTER: Nguyen TTT

PROVIDER: S-EPMC10553816 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Heterogeneity of Alzheimer's disease identified by neuropsychological test profiling.

Nguyen Truc Tran Thanh TTT Lee Hsun-Hua HH Huang Li-Kai LK Hu Chaur-Jong CJ Yeh Chih-Yang CY Yang Wei-Chung Vivian WV Lin Ming-Chin MC

PloS one 20231005 10

Alzheimer's disease (AD) is a highly heterogeneous disorder. Untangling this variability could lead to personalized treatments and improve participant recruitment for clinical trials. We investigated the cognitive subgroups by using a data-driven clustering technique in an AD cohort. People with mild-moderate probable AD from Taiwan was included. Neuropsychological test results from the Cognitive Abilities Screening Instrument were clustered using nonnegative matrix factorization. We identified ...[more]

PMID: 37797059

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Project description:ImportanceUndetected biological heterogeneity adversely impacts trials in Alzheimer's disease because rate of cognitive decline - and perhaps response to treatment - differs in subgroups. Recent results show that data-driven approaches can unravel the heterogeneity of Alzheimer's disease progression. The resulting stratification is yet to be leveraged in clinical trials.ObjectiveInvestigate whether image-based data-driven disease progression modelling could identify baseline biological heterogeneity in a clinical trial, and whether these subgroups have prognostic or predictive value.DesignScreening data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study collected between April 2014 and December 2017, and longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) observational study downloaded in February 2022 were used.SettingThe A4 Study is an interventional trial involving 67 sites in the US, Canada, Australia, and Japan. ADNI is a multi-center observational study in North America.ParticipantsCognitively unimpaired amyloid-positive participants with a 3-Tesla T1-weighted MRI scan. Amyloid positivity was determined using florbetapir PET imaging (in A4) and CSF Aβ(1-42) (in ADNI).Main outcomes and measuresRegional volumes estimated from MRI scans were used as input to the Subtype and Stage Inference (SuStaIn) algorithm. Outcomes included cognitive test scores and SUVr values from florbetapir and flortaucipir PET.ResultsWe included 1,240 Aβ+ participants (and 407 Aβ- controls) from the A4 Study, and 731 A4-eligible ADNI participants. SuStaIn identified three neurodegeneration subtypes - Typical, Cortical, Subcortical - comprising 523 (42%) individuals. The remainder are designated subtype zero (insufficient atrophy). Baseline PACC scores (A4 primary outcome) were significantly worse in the Cortical subtype (median = -1.27, IQR=[-3.34,0.83]) relative to both subtype zero (median=-0.013, IQR=[-1.85,1.67], P<.0001) and the Subcortical subtype (median=0.03, IQR=[-1.78,1.61], P=.0006). In ADNI, over a four-year period (comparable to A4), greater cognitive decline in the mPACC was observed in both the Typical (-0.23/yr; 95% CI, [-0.41,-0.05]; P=.01) and Cortical (-0.24/yr; [-0.42,-0.06]; P=.009) subtypes, as well as the CDR-SB (Typical: +0.09/yr, [0.06,0.12], P<.0001; and Cortical: +0.07/yr, [0.04,0.10], P<.0001).Conclusions and relevanceIn a large secondary prevention trial, our image-based model detected neurodegenerative heterogeneity predictive of cognitive heterogeneity. We argue that such a model is a valuable tool to be considered in future trial design to control for previously undetected variance.

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Heterogeneity of Alzheimer's disease identified by neuropsychological test profiling.

Publications

Heterogeneity of Alzheimer's disease identified by neuropsychological test profiling.

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