The Use of Multivariate Methods in the Identification of Subtypes of Alzheimer's Disease: A Comparison of Principal Components and Cluster Analysis

Armstrong, Richard A.; Wood, Lincoln C.; Myers, D.; Smith, C. U. M.

doi:10.1159/000106882

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…Our review shows that both hypothesis-driven and datadriven methods have been used for determining biological subtypes of AD. A number of early studies [6][7][8] used principal component analysis and other clustering methods on pathologic measures of senile plaques, neurofibrillary tangles (NFTs), and cerebral amyloid angiopathy (CAA). Later studies mainly focused on markers of tau pathology and neurodegeneration.…”

Section: Resultsmentioning

confidence: 99%

Biological subtypes of Alzheimer disease

2020

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ObjectiveTo test the hypothesis that distinct subtypes of Alzheimer disease (AD) exist and underlie the heterogeneity within AD, we conducted a systematic review and meta-analysis on AD subtype studies based on postmortem and neuroimaging data.MethodsEMBASE, PubMed, and Web of Science databases were consulted until July 2019.ResultsNeuropathology and neuroimaging studies have consistently identified 3 subtypes of AD based on the distribution of tau-related pathology and regional brain atrophy: typical, limbic-predominant, and hippocampal-sparing AD. A fourth subtype, minimal atrophy AD, has been identified in several neuroimaging studies. Typical AD displays tau-related pathology and atrophy both in hippocampus and association cortex and has a pooled frequency of 55%. Limbic-predominant, hippocampal-sparing, and minimal atrophy AD had a pooled frequency of 21%, 17%, and 15%, respectively. Between-subtype differences were found in age at onset, age at assessment, sex distribution, years of education, global cognitive status, disease duration, APOE ε4 genotype, and CSF biomarker levels.ConclusionWe identified 2 core dimensions of heterogeneity: typicality and severity. We propose that these 2 dimensions determine individuals' belonging to one of the AD subtypes based on the combination of protective factors, risk factors, and concomitant non-AD brain pathologies. This model is envisioned to aid with framing hypotheses, study design, interpretation of results, and understanding mechanisms in future subtype studies. Our model can be used along the A/T/N classification scheme for AD biomarkers. Unraveling the heterogeneity within AD is critical for implementing precision medicine approaches and for ultimately developing successful disease-modifying drugs for AD.

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Section: Resultsmentioning

confidence: 99%

Biological subtypes of Alzheimer disease

2020

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“…Cluster analysis has been used to profile and classify systems or taxonomies (Leonard & Droege, 2008;Sokal & Rohlf, 1962), and whilst it has consistently been applied in other disciplines, such as nanotechnology and cell biology (Armstrong et al, 1996;Johnson, 1997;Schweitzer & Renehan, 1997;Semmar et al, 2005;Winterstein et al, 2004), it has only recently been used successfully to investigate human movement characteristics (Clark, Barnes, Holton, et al, 2016b).…”

Section: Cluster Analysismentioning

confidence: 99%

Profiling Movement and Gait Quality Characteristics in Pre-School Children

Clark

Barnes

Swindell

et al. 2017

Journal of Motor Behavior

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There is a dearth of suitable metrics capable of objectively quantifying motor competence. Further, objective movement quality characteristics during free play have not been investigated in pre-school children. The aims of this study were to characterize children's free play physical activity and investigate how gait quality characteristics cluster with free play in pre-school children (3-5 years old). Sixty-one children (39 boys; 4.3 ± 0.7 years, 1.04 ± 0.05 m, 17.8 ± 3.2 kg) completed the movement assessment battery for children and took part in free play while wearing an ankle- and hip-mounted accelerometer. Characteristics of movement quality were profiled using a clustering algorithm. Spearman's rho and the Mann-Whitney U tests were used to assess relationships between movement quality characteristics and motor competence classification differences in integrated acceleration and spectral purity, respectively. Significant differences were found between motor competency classifications for spectral purity and integrated acceleration (p < .001). Spectral purity was hierarchically clustered with motor competence and integrated acceleration. Significant positive correlations were found between spectral purity, integrated acceleration and motor competence (p < .001). This is the first study to report spectral purity in pre-school children and the results suggest that the underlying frequency component of movement is clustered with motor competence.

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“…Previous researchers classified subtypes of AD using various methods such as clinical subtypes defined by diagnostic criteria [1][2][3][4][5]; atrophy subtypes assessed using magnetic resonance imaging [6][7][8][9][10][11]; etiological subtypes or molecular subtypes characterized by pathological levels of cerebrospinal fluid A␤ 1-42 , total tau, and phosphorylated tau [12,13]; and subtypes based on statistical analyses, such as latent class analysis of Mini-Mental Examination (MMSE) scores [14] and principal component analysis and cluster analysis of the distribution and abundance of senile plaques and neurofibrillary tangles in the brain [15,16]. Staging using assessment scales is another method of understanding AD pathology [17,18].…”

Section: Introductionmentioning

confidence: 99%

ABC Dementia Scale Classifies Alzheimer’s Disease Patients into Subgroups Characterized by Activities of Daily Living, Behavioral and Psychological Symptoms of Dementia, and Cognitive Function

Wada‐Isoe

Kikuchi

Umeda‐Kameyama

et al. 2020

JAD

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The course of Alzheimer's disease (AD) varies between individuals, and the relationship between cognitive and functional decline and the deterioration of behavioral and psychological symptoms of dementia (BPSD) is still poorly understood. Until recently, it was challenging to monitor subsequent changes in these symptoms because there was no single composite scale available that could simultaneously evaluate activities of daily living (ADL), BPSD, and cognitive function (CF) states. The present authors developed a new, brief assessment scale, the "ABC Dementia Scale" (ABC-DS), which is based on item response theory and facilitates concurrent measurement of ADL, BPSD, and CF states. We previously presented the reliability, construct validity, concurrent validity, and responsiveness of the ABC-DS. We obtained the evidence through three clinical trials featuring 1,400 subjects in total. In the present study, we performed a secondary analysis of the data obtained in the previous study. We conducted hierarchical cluster analyses that allowed us to classify 197 AD patients in terms of similarities regarding ADL, BPSD, and CF domain scores, as measured by the ABC-DS. Consequently, the scale identified subgroups of patients with global clinical dementia ratings of 1, 2, and 3. Considering our results in conjunction with the clinical experiences of the AD expert among the present authors regarding longitudinal changes in ADL, BPSD, and CF, we were able to propose potential progression pathways of AD in the form of a hypothetical roadmap.

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The Use of Multivariate Methods in the Identification of Subtypes of Alzheimer's Disease: A Comparison of Principal Components and Cluster Analysis

Cited by 5 publications

References 21 publications

Biological subtypes of Alzheimer disease

Biological subtypes of Alzheimer disease

Profiling Movement and Gait Quality Characteristics in Pre-School Children

ABC Dementia Scale Classifies Alzheimer’s Disease Patients into Subgroups Characterized by Activities of Daily Living, Behavioral and Psychological Symptoms of Dementia, and Cognitive Function

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