Neuroanatomical correlations of visuospatial processing in primary progressive aphasia

Cognitive profiles in primary progressive aphasia variants: A cross-cultural Australian and Spanish investigation

BACKGROUND

The effect of cultural differences in neurodegenerative diseases is not well understood. We aimed to investigate the cognitive profiles of English- and Spanish-speaking individuals with primary progressive aphasia (PPA).

METHODOLOGY

A comparative cross-sectional study was conducted with 461 participants: 215 participants from Australia and 246 from Spain. The Australian cohort included 131 PPA patients: 37 nonfluent PPA (nfvPPA), 49 semantic PPA (svPPA), 45 logopenic (lvPPA) and 84 healthy controls (HC); the Spanish cohort had 162 PPA: 64 nfvPPA, 31 vsPPA, 67 lvPPA, and 84 HC. All participants completed the ACE-III and other tests assessing verbal working memory, attention/executive functioning, visuospatial constructional abilities and episodic memory. A subgroup of participants underwent structural brain MRI. Cognitive performance and neuroimaging were compared between groups.

RESULTS

The most salient differences between each variant and HC were similar in the Australian and Spanish cohort. However, the Spanish cohort scored lower than the Australian cohort in most cognitive tests evaluated (ACE-III total, attention, memory and visuospatial in nfvPPA; attention, memory, and visuospatial in svPPA; and memory, language, and visuospatial in lvPPA). Differences were particularly pronounced in the visuospatial subdomain among nonfluent variant PPA. Cortical thickness analysis showed the expected regional atrophy in each PPA variant, but with no greater atrophy in the Spanish cohort.

CONCLUSION

These findings revealed an impairment in other cognitive domains beyond language in PPA. However, Spanish patients exhibited more generalized cognitive involvement despite similar demographic and neuroimaging profiles, suggesting that cultural and resilience factors may influence PPA presentations.

Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study

BACKGROUND

Early detection of mild cognitive impairment (MCI), a transitional stage between normal aging and Alzheimer disease, is crucial for preventing the progression of dementia. Virtual reality (VR) biomarkers have proven to be effective in capturing behaviors associated with subtle deficits in instrumental activities of daily living, such as challenges in using a food-ordering kiosk, for early detection of MCI. On the other hand, magnetic resonance imaging (MRI) biomarkers have demonstrated their efficacy in quantifying observable structural brain changes that can aid in early MCI detection. Nevertheless, the relationship between VR-derived and MRI biomarkers remains an open question. In this context, we explored the integration of VR-derived and MRI biomarkers to enhance early MCI detection through a multimodal learning approach.

OBJECTIVE

We aimed to evaluate and compare the efficacy of VR-derived and MRI biomarkers in the classification of MCI while also examining the strengths and weaknesses of each approach. Furthermore, we focused on improving early MCI detection by leveraging multimodal learning to integrate VR-derived and MRI biomarkers.

METHODS

The study encompassed a total of 54 participants, comprising 22 (41%) healthy controls and 32 (59%) patients with MCI. Participants completed a virtual kiosk test to collect 4 VR-derived biomarkers (hand movement speed, scanpath length, time to completion, and the number of errors), and T1-weighted MRI scans were performed to collect 22 MRI biomarkers from both hemispheres. Analyses of covariance were used to compare these biomarkers between healthy controls and patients with MCI, with age considered as a covariate. Subsequently, the biomarkers that exhibited significant differences between the 2 groups were used to train and validate a multimodal learning model aimed at early screening for patients with MCI among healthy controls.

RESULTS

The support vector machine (SVM) using only VR-derived biomarkers achieved a sensitivity of 87.5% and specificity of 90%, whereas the MRI biomarkers showed a sensitivity of 90.9% and specificity of 71.4%. Moreover, a correlation analysis revealed a significant association between MRI-observed brain atrophy and impaired performance in instrumental activities of daily living in the VR environment. Notably, the integration of both VR-derived and MRI biomarkers into a multimodal SVM model yielded superior results compared to unimodal SVM models, achieving higher accuracy (94.4%), sensitivity (100%), specificity (90.9%), precision (87.5%), and F1-score (93.3%).

CONCLUSIONS

The results indicate that VR-derived biomarkers, characterized by their high specificity, can be valuable as a robust, early screening tool for MCI in a broader older adult population. On the other hand, MRI biomarkers, known for their high sensitivity, excel at confirming the presence of MCI. Moreover, the multimodal learning approach introduced in our study provides valuable insights into the improvement of early MCI detection by integrating a diverse set of biomarkers.

Atypical clinical variants of Alzheimer's disease: are they really atypical?

Alzheimer's disease (AD) is a neuropathological disorder defined by the deposition of the proteins, tau and β-amyloid. Alzheimer's disease is commonly thought of as a disease of the elderly that is associated with episodic memory loss. However, the very first patient described with AD was in her 50's with impairments in multiple cognitive domains. It is now clear that AD can present with multiple different non-amnestic clinical variants which have been labeled as atypical variants of AD. Instead of these variants of AD being considered "atypical," I propose that they provide an excellent disease model of AD and reflect the true clinical heterogeneity of AD. The atypical variants of AD usually have a relatively young age at onset, and they show striking cortical tau deposition on molecular PET imaging which relates strongly with patterns of neurodegeneration and clinical outcomes. In contrast, elderly patients with AD show less tau deposition on PET, and neuroimaging and clinical outcomes are confounded by other age-related pathologies, including TDP-43 and vascular pathology. There is also considerable clinical and anatomical heterogeneity across atypical and young-onset amnestic variants of AD which reflects the fact that AD is a disease that causes impairments in multiple cognitive domains. Future studies should focus on careful characterization of cognitive impairment in AD and consider the full clinical spectrum of AD, including atypical AD, in the design of research studies investigating disease mechanisms in AD and clinical treatment trials, particularly with therapeutics targeting tau.

Assessing processing speed and its neural correlates in the three variants of primary progressive aphasia with a non-verbal tablet-based task

Prior research has revealed distinctive patterns of impaired language abilities across the three variants of Primary Progressive Aphasia (PPA): nonfluent/agrammatic (nfvPPA), logopenic (lvPPA) and semantic (svPPA). However, little is known about whether, and to what extent, non-verbal cognitive abilities, such as processing speed, are impacted in PPA patients. This is because neuropsychological tests typically contain linguistic stimuli and require spoken output, being therefore sensitive to verbal deficits in aphasic patients. The aim of this study is to investigate potential differences in processing speed between PPA patients and healthy controls, and among the three PPA variants, using a brief non-verbal tablet-based task (Match) modeled after the WAIS-III digit symbol coding test, and to determine its neural correlates. Here, we compared performance on the Match task between PPA patients (n = 61) and healthy controls (n = 59) and across the three PPA variants. We correlated performance on Match with voxelwise gray and white matter volumes. We found that lvPPA and nfvPPA patients performed significantly worse on Match than healthy controls and svPPA patients. Worse performance on Match across PPA patients was associated with reduced gray matter volume in specific parts of the left middle frontal gyrus, superior parietal lobule, and precuneus, and reduced white matter volume in the left parietal lobe. To conclude, our behavioral findings reveal that processing speed is differentially impacted across the three PPA variants and provide support for the potential clinical utility of a tabled-based task (Match) to assess non-verbal cognition. In addition, our neuroimaging findings confirm the importance of a set of fronto-parietal regions that previous research has associated with processing speed and executive control. Finally, our behavioral and neuroimaging findings combined indicate that differences in processing speed are largely explained by the unequal distribution of atrophy in these fronto-parietal regions across the three PPA variants.

Diffusivity Changes in Posterior Cortical Atrophy and Logopenic Progressive Aphasia: A Longitudinal Diffusion Tensor Imaging Study

BACKGROUND

Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are associated with characteristic patterns of structural network degeneration. Little is known about longitudinal patterns of white matter tract degeneration in these phenotypes.

OBJECTIVE

To assess longitudinal patterns of white matter degeneration and identify phenotype specific cross-sectional and longitudinal diffusion tensor imaging (DTI) biomarkers in PCA and LPA.

METHODS

Twenty-five PCA, 22 LPA and 25 cognitively unimpaired (CU) individuals were recruited and underwent structural MRI that included a DTI sequence with a follow-up one year later. Cross-sectional and longitudinal mixed effects models were fit to assess the effects of diagnosis on baseline and annualized change in regional DTI metrics. Discriminatory power was investigated using the area under the receiver operating characteristic curves (AUROC).

RESULTS

PCA and LPA showed overlapping white matter degeneration profiles predominantly in the left occipital and temporal lobes, the posterior thalamic radiation and sagittal stratum at baseline, as well as the parietal lobe longitudinally. PCA showed degeneration in the occipital and parietal white matter, cross-sectionally and longitudinally, compared to CU, while LPA showed greater degeneration in the temporal and inferior parietal white matter and the inferior fronto-occipital fasciculus cross-sectionally, and in parietal white matter longitudinally compared to CU. Cross-sectionally, integrity of the inferior occipital white matter was best able to differentiate PCA from LPA, with an AUROC of 0.82.

CONCLUSION

These findings contribute to our understanding of white matter degeneration and support usage of DTI as a useful additional diagnostic biomarker for PCA and LPA.