Posterior AD-type pathology: cognitive subtypes emerging from a cluster analysis

Heterogeneity of Alzheimer's disease identified by neuropsychological test profiling

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.

Clinical Screening for Posterior Cortical Atrophy

BACKGROUND

Posterior cortical atrophy (PCA) is a progressive neurologic syndrome that presents with complex visual deficits. Although PCA is most commonly a form of Alzheimer disease (AD), its early diagnosis is usually delayed due to a lack of understanding for how best to clinically screen for the syndrome.

OBJECTIVE

To identify neurobehavioral screening tasks for PCA-beyond simple visual constructions-that can be administered in clinic or at bedside.

METHOD

We compared the performance of 12 individuals who met neuroimaging-supported consensus criteria for PCA with that of 12 matched individuals with typical AD (tAD) and 24 healthy controls (HC) on clinic/bedside tasks measuring (a) complex figure copying, (b) Balint syndrome, (c) visual object agnosia, (d) color identification, (e) figure-ground discrimination, (f) global-local processing, (g) dressing apraxia, (h) ideomotor apraxia, and (i) Gerstmann syndrome.

RESULTS

All of the individuals with PCA were impaired on the figure-ground discrimination task compared with half of the tAD group and no HC. Approximately half of the PCA group had Balint syndrome, dressing apraxia, and ideomotor apraxia compared with none in the tAD group. Difficulty copying a complex figure, global-local processing impairment, and Gerstmann syndrome did not distinguish between the two dementia groups.

CONCLUSION

The figure-ground discrimination task can be used successfully as an overall screening measure for PCA, followed by specific tasks for Balint syndrome and dressing and limb apraxia. Findings reinforce PCA as a predominant occipitoparietal disorder with dorsal visual stream involvement and parietal signs with spatiomotor impairments.

Heterogeneity and Factorial Structure in Alzheimer's Disease: A Cognitive Perspective

BACKGROUND

Alzheimer's disease (AD) patients show heterogeneous cognitive profiles which suggest the existence of cognitive subgroups. A deeper comprehension of this heterogeneity could contribute to move toward a precision medicine perspective.

OBJECTIVE

In this study, we aimed 1) to investigate AD cognitive heterogeneity as a product of the combination of within- (factors) and between-patients (sub-phenotypes) components, and 2) to promote its assessment in clinical practice by defining a small set of critical tests for this purpose.

METHODS

We performed factor mixture analysis (FMA) on neurocognitive assessment results of N = 230 patients with a clinical diagnosis of AD. This technique allowed to investigate the structure of cognitive heterogeneity in this sample and to characterize the core features of cognitive sub-phenotypes. Subsequently, we performed a tests selection based on logistic regression to highlight the best tests to detect AD patients in our sample. Finally, the accuracy of the same tests in the discrimination of sub-phenotypes was evaluated.

RESULTS

FMA revealed a structure characterized by five latent factors and four groups, which were identifiable by means of a few cognitive tests and were mainly characterized by memory deficits with visuospatial difficulties ("Visuospatial AD"), typical AD cognitive pattern ("Typical AD"), less impaired memory ("Mild AD"), and language/praxis deficits with relatively spared memory ("Nonamnestic AD").

CONCLUSION

The structure of cognitive heterogeneity in our sample of AD patients, as studied by FMA, could be summarized by four sub-phenotypes with distinct cognitive characteristics easily identifiable in clinical practice. Clinical implications under the precision medicine framework are discussed.

Impaired visual search in posterior cortical atrophy vs. typical Alzheimer's disease

BACKGROUND

Posterior cortical atrophy (PCA) is a neurocognitive disorder characterized by difficulty localizing in space. Recognizing PCA is important because it is usually missed early in its course and may result from a number of neurological disorders other than Alzheimer's disease (AD).

OBJECTIVE

This study aimed to clarify whether impaired visual search tasks of spatial localization distinguished patients with PCA from those with other more typical dementias as well as from healthy control (HC) subjects.

METHODS

Twelve patients meeting neuroimaging-supported Consensus Criteria for PCA, 12 comparably advanced patients with amnestic-predominant typical AD (tAD), and 24 HC participants were compared on tests of untimed and timed visual search, spatial neglect, mental rotation, environmental orientation, visuospatial construction, and face recognition.

RESULTS

Only abnormalities in untimed and timed visual search and environmental orientation distinguished the PCA patients from both the tAD group and the HC group without also distinguishing the tAD patients from HC's. The PCA patients also had a tendency to greater difficulty scanning left hemispace compared to HC's. Visuospatial constructions, although worse in PCA, and face recognition were impaired in both dementia groups.

CONCLUSIONS

These findings support the concept of PCA as a disorder of spatial processing and localization, indicating that visual search tasks are particularly sensitive and specific for detecting PCA and distinguishing it from more typical dementia syndromes.

Benson's Disease or Posterior Cortical Atrophy, Revisited

BACKGROUND

D. Frank Benson and colleagues first described the clinical and neuropathological features of posterior cortical atrophy (PCA) from patients in the UCLA Neurobehavior Program.

OBJECTIVE

We reviewed the Program's subsequent clinical experience with PCA, and its potential for clarifying this relatively rare syndrome in comparison to the accumulated literature on PCA.

METHODS

Using the original criteria derived from this clinic, 65 patients with neuroimaging-supported PCA were diagnosed between 1995 and 2020.

RESULTS

On presentation, most had visual localization complaints and related visuospatial symptoms, but nearly half had memory complaints followed by symptoms of depression. Neurobehavioral testing showed predominant difficulty with visuospatial constructions, Gerstmann's syndrome, and Balint's syndrome, but also impaired memory and naming. On retrospective application of the current Consensus Criteria for PCA, 59 (91%) met PCA criteria with a modification allowing for "significantly greater visuospatial over memory and naming deficits." There were 37 deaths (56.9%) with the median overall survival of 10.3 years (95% CI: 9.6-13.6 years), consistent with a slow neurodegenerative disorder in most patients.

CONCLUSION

Together, these findings recommend modifying the PCA criteria for "relatively spared" memory, language, and behavior to include secondary memory and naming difficulty and depression, with increased emphasis on the presence of Gerstmann's and Balint's syndromes.

Neuropsychological Similarities and Differences Between Amnestic Alzheimer's Disease and its Non-Amnestic Variants

BACKGROUND

The neuropsychological recognition of early-onset Alzheimer's disease (AD) can be difficult because of non-amnestic variants such as logopenic variant primary progressive aphasia (lvPPA) and posterior cortical atrophy (PCA).

OBJECTIVE

This study evaluated the similarities and differences between typical amnestic AD (tAD) and lvPPA and PCA on a screening neuropsychological battery.

METHODS

We enrolled 51 patients meeting NIA-AA criteria for biomarker-supported AD (amnestic or non-amnestic) and having an age of onset of <65 years of age. Based on additional recommended clinical criteria for lvPPA and PCA, the early-onset AD patients were divided into three groups (28 tAD, 9 lvPPA, 14 PCA) of comparable age and dementia severity. We then analyzed their profiles on a focused, screening neuropsychological battery for early-onset AD.

RESULTS

In addition to greater variance on the Mini-Mental State Examination, the lvPPA and PCA variants had episodic memory impairment that did not significantly differ from the memory impairment in the tAD patients. Despite differences on language and visuospatial tasks, they did not significantly distinguish the lvPPA and PCA from tAD. The lvPPA group, however, was distinguishable by worse performance on measures reflecting working memory (digit span forward, memory registration).

CONCLUSIONS

On neuropsychological screening, all clinical early-onset AD subtypes may have memory impairments. Screening batteries for early-onset AD should also include measures of working memory, which is disproportionately decreased in lvPPA.

The Application of Unsupervised Clustering Methods to Alzheimer's Disease

Clustering is a powerful machine learning tool for detecting structures in datasets. In the medical field, clustering has been proven to be a powerful tool for discovering patterns and structure in labeled and unlabeled datasets. Unlike supervised methods, clustering is an unsupervised method that works on datasets in which there is no outcome (target) variable nor is anything known about the relationship between the observations, that is, unlabeled data. In this paper, we focus on studying and reviewing clustering methods that have been applied to datasets of neurological diseases, especially Alzheimer’s disease (AD). The aim is to provide insights into which clustering technique is more suitable for partitioning patients of AD based on their similarity. This is important as clustering algorithms can find patterns across patients that are difficult for medical practitioners to find. We further discuss the implications of the use of clustering algorithms in the treatment of AD. We found that clustering analysis can point to several features that underlie the conversion from early-stage AD to advanced AD. Furthermore, future work can apply semi-clustering algorithms on AD datasets, which will enhance clusters by including additional information.

Childhood Learning Disabilities and Atypical Dementia: A Retrospective Chart Review

Objective

To further our understanding of the association between self-reported childhood learning disabilities (LDs) and atypical dementia phenotypes (Atypical Dementia), including logopenic primary progressive aphasia (L-PPA), Posterior Cortical Atrophy (PCA), and Dysexecutive-type Alzheimer’s Disease (AD).

Methods

This retrospective case series analysis of 678 comprehensive neuropsychological assessments compared rates of self-reported LD between dementia patients diagnosed with Typical AD and those diagnosed with Atypical Dementia. 105 cases with neuroimaging or CSF data available and at least one neurology follow-up were identified as having been diagnosed by the neuropsychologist with any form of neurodegenerative dementia. These cases were subject to a consensus diagnostic process among three dementia experts using validated clinical criteria for AD and PPA. LD was considered Probable if two or more statements consistent with prior LD were documented within the Social & Developmental History of the initial neuropsychological evaluation.

Results

85 subjects (Typical AD n=68, Atypical AD n=17) were included in the final analysis. In logistic regression models adjusted for age, gender, handedness, education and symptom duration, patients with Probable LD, compared to patients without Probable LD, were significantly more likely to be diagnosed with Atypical Dementia vs. Typical AD (OR 13.1, 95% CI 1.3-128.4). All three of the L-PPA cases reporting a childhood LD endorsed childhood difficulty with language. By contrast, both PCA cases reporting Probable childhood LD endorsed difficulty with attention and/or math.

Conclusions

In people who develop dementia, childhood LD may predispose to atypical phenotypes. Future studies are required to confirm whether atypical neurodevelopment predisposes to regional-specific neuropathology in AD and other dementias.