Different patterns of functional network reorganization across the variants of primary progressive aphasia: a graph-theoretic analysis.
ABSTRACT: Primary progressive aphasia (PPA) is a neurodegenerative syndrome with three main variants (nonfluent, logopenic, semantic) that are identified primarily based on language deficit profiles and are associated with neurotopographically distinct atrophic patterns. We used a graph-theoretic analytic approach to examine changes in functional network properties measured with resting-state fMRI in all three PPA variants compared with age-matched healthy controls. All three variants showed a more segregated network organization than controls. To better understand the changes underlying the increased segregation, we examined the distribution of functional "hubs". We found that while all variants lost hubs in the left superior frontal and parietal regions, new hubs were recruited in different areas across the variants. In particular, both logopenic and semantic variants recruited significant numbers of hubs in the right hemisphere. Importantly, these functional characteristics could not be fully explained by local volume changes. These findings indicate that patterns of functional connectivity can serve as further evidence to distinguish the PPA variants, and provide a basis for longitudinal studies and for investigating treatment effects. This study also highlights the utility of graph-theoretic approaches in understanding the brain's functional reorganization in response to neurodegenerative disease.
Project description:Background Primary progressive aphasia (PPA) is a neurodegenerative disorder characterized by a progressive decline of language functions. Its symptoms are grouped into three PPA variants: nonfluent PPA, logopenic PPA, and semantic PPA. Grammatical deficiencies differ depending on the PPA variant. Aims This study aims to determine the differences between PPA variants with respect to part of speech (POS) production and to identify morphological markers that classify PPA variants using machine learning. By fulfilling these aims, the overarching goal is to provide objective measures that can facilitate clinical diagnosis, evaluation, and prognosis. Method and Procedure Connected speech productions from PPA patients produced in a picture description task were transcribed, and the POS class of each word was estimated using natural language processing, namely, POS tagging. We then implemented a twofold analysis: (a) linear regression to determine how patients with nonfluent PPA, semantic PPA, and logopenic PPA variants differ in their POS productions and (b) a supervised classification analysis based on POS using machine learning models (i.e., random forests, decision trees, and support vector machines) to subtype PPA variants and generate feature importance (FI). Outcome and Results Using an automated analysis of a short picture description task, this study showed that content versus function words can distinguish patients with nonfluent PPA, semantic PPA, and logopenic PPA variants. Verbs were less important as distinguishing features of patients with different PPA variants than earlier thought. Finally, the study showed that among the most important distinguishing features of PPA variants were elaborative speech elements, such as adjectives and adverbs.
Project description:Previous studies indicate that repetition is affected in primary progressive aphasia (PPA), particularly in the logopenic variant, due to limited auditory-verbal short-term memory (avSTM). We tested repetition of phrases varied by length (short, long) and meaning (meaningful, non-meaningful) in 58 participants (22 logopenic, 19 nonfluent, and 17 semantic variants) and 21 healthy controls using a modified Bayles repetition test. We evaluated the relation between cortical thickness and repetition performance and whether sub-scores could discriminate PPA variants. Logopenic participants showed impaired repetition across all phrases, specifically in repeating long phrases and any phrases that were non-meaningful. Nonfluent, semantic, and healthy control participants only had difficulty repeating long, non-meaningful phrases. Poor repetition of long phrases was associated with cortical thinning in left temporo-parietal areas across all variants, highlighting the importance of these areas in avSTM. Finally, Bayles repetition phrases can assist classification in PPA, discriminating logopenic from nonfluent/semantic participants with 89% accuracy.
Project description:<h4>Objective</h4>Primary progressive aphasia (PPA) has been proposed to comprise 3 discrete clinical subtypes: semantic, agrammatic/nonfluent, and logopenic. Recent consensus recommendations suggest a diagnostic framework based primarily on clinical and neuropsychological findings to classify these variants. Our objective was to evaluate the extent to which patients with PPA would conform to the proposed tripartite system and whether the clustering pattern of elements of the linguistic profile suggests discrete clinical syndromes.<h4>Methods</h4>A total of 46 patients with PPA were prospectively recruited to the Cambridge Longitudinal Study of PPA. Sufficient data were collected to assess all consensus-proposed diagnostic domains. By comparing patients' performances against those of 30 age- and education-matched healthy volunteers, z scores were calculated, and values of 1.5 SDs outside control participants' means were considered abnormal. Raw test scores were used to undertake a principal factor analysis to identify the clustering pattern of individual measures.<h4>Results</h4>Of the patients, 28.3%, 26.1%, and 4.3% fitted semantic, nonfluent/agrammatic, and logopenic categories respectively, and 41.3% did not fulfill the diagnostic recommendations for any of the 3 proposed variants. There was no significant between-group difference in age, education, or disease duration. Furthermore, the outcome of the factor analysis was in keeping with discrete semantic and nonfluent/agrammatic syndromes but did not support a logopenic variant.<h4>Conclusion</h4>Taken together, the results of this prospective data-driven study suggest that although a substantial proportion of patients with PPA have neither the semantic nor the nonfluent variants, they do not necessarily conform to a discrete logopenic variant.
Project description:Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.
Project description:OBJECTIVES:The aim of this study was to identify whether the three main primary progressive aphasia (PPA) variants would show differential profiles on measures of visuospatial cognition. We hypothesized that the logopenic variant would have the most difficulty across tasks requiring visuospatial and visual memory abilities. METHODS:PPA patients (n=156), diagnosed using current criteria, and controls were tested on a battery of tests tapping different aspects of visuospatial cognition. We compared the groups on an overall visuospatial factor; construction, immediate recall, delayed recall, and executive functioning composites; and on individual tests. Cross-sectional and longitudinal comparisons were made, adjusted for disease severity, age, and education. RESULTS:The logopenic variant had significantly lower scores on the visuospatial factor and the most impaired scores on all composites. The nonfluent variant had significant difficulty on all visuospatial composites except the delayed recall, which differentiated them from the logopenic variant. In contrast, the semantic variants performed poorly only on delayed recall of visual information. The logopenic and nonfluent variants showed decline in figure copying performance over time, whereas in the semantic variant, this skill was remarkably preserved. CONCLUSIONS:This extensive examination of performance on visuospatial tasks in the PPA variants solidifies some previous findings, for example, delayed recall of visual stimuli adds value in differential diagnosis between logopenic variant PPA and nonfluent variant PPA variants, and illuminates the possibility of common mechanisms that underlie both linguistic and non-linguistic deficits in the variants. Furthermore, this is the first study that has investigated visuospatial functioning over time in the PPA variants. (JINS, 2018, 24, 259-268).
Project description:The primary progressive aphasias (PPA) are a heterogeneous group of language-led neurodegenerative diseases resulting from large-scale brain network degeneration. White matter (WM) pathways bind networks together, and might therefore hold information about PPA pathogenesis. Here we used diffusion tensor imaging and tract-based spatial statistics to compare WM tract changes between PPA syndromes and with respect to Alzheimer's disease and healthy controls in 33 patients with PPA (13 nonfluent/agrammatic PPA); 10 logopenic variant PPA; and 10 semantic variant PPA. Nonfluent/agrammatic PPA was associated with predominantly left-sided and anterior tract alterations including uncinate fasciculus (UF) and subcortical projections; semantic variant PPA with bilateral alterations in inferior longitudinal fasciculus and UF; and logopenic variant PPA with bilateral but predominantly left-sided alterations in inferior longitudinal fasciculus, UF, superior longitudinal fasciculus, and subcortical projections. Tract alterations were more extensive than gray matter alterations, and the extent of alteration across tracts and PPA syndromes varied between diffusivity metrics. These WM signatures of PPA syndromes illustrate the selective vulnerability of brain language networks in these diseases and might have some pathologic specificity.
Project description:Neuroimaging studies have described the brain alterations in primary progressive aphasia (PPA) variants (semantic, logopenic, nonfluent/agrammatic). However, few studies combined T1, FDG-PET, and diffusion MRI techniques to study atrophy, hypometabolism, and tract alterations across the three PPA main variants. We therefore explored a large early-stage cohort of semantic, logopenic and nonfluent/agrammatic variants (<i>N</i> = 86) and of 23 matched healthy controls with anatomical MRI (cortical thickness), FDG PET (metabolism) and diffusion MRI (white matter tracts analyses), aiming at identifying cortical and sub-cortical brain alterations, and confronting these alterations across imaging modalities and aphasia variants. In the semantic variant, there was cortical thinning and hypometabolism in anterior temporal cortices, with left-hemisphere predominance, extending toward posterior temporal regions, and affecting tracts projecting to the anterior temporal lobes (inferior longitudinal fasciculus, uncinate fasciculus) and tracts projecting to or running nearby posterior temporal cortices: (superior longitudinal fasciculus, inferior frontal-occipital fasciculus). In the logopenic variant metabolic alterations were more extensive than atrophy affecting mainly the left temporal-parietal junction and extending toward more anterior temporal cortices. Metabolic and tract data were coherent given the alterations of the left superior and inferior longitudinal fasciculus and the left inferior frontal-occipital fasciculus. In the nonfluent/agrammatic variant cortical thinning and hypometabolism were located in the left frontal cortex but Broca's area was only affected on metabolic measures. Metabolic and tract alterations were coherent as reflected by damage to the left uncinate fasciculus connecting with Broca's area. Our findings provide a full-blown statistically robust picture of brain alterations in early-stage variants of primary progressive aphasia which has implications for diagnosis, classification and future therapeutic strategies. They demonstrate that in logopenic and semantic variants patterns of brain damage display a non-negligible overlap in temporal regions whereas they are substantially distinct in the nonfluent/agrammatic variant (frontal regions). These results also indicate that frontal networks (combinatorial syntax/phonology) and temporal networks (lexical/semantic representations) constitute distinct anatomo-functional entities with differential vulnerability to degenerative processes in aphasia variants. Finally, the identification of the specific damage patterns could open an avenue for trans-cranial stimulation approaches by indicating the appropriate target-entry into the damaged language system.
Project description:Importance:The ability to predict the pathology underlying different neurodegenerative syndromes is of critical importance owing to the advent of molecule-specific therapies. Objective:To determine the rates of positron emission tomography (PET) amyloid positivity in the main clinical variants of primary progressive aphasia (PPA). Design, Setting, and Participants:This prospective clinical-pathologic case series was conducted at a tertiary research clinic specialized in cognitive disorders. Patients were evaluated as part of a prospective, longitudinal research study between January 2002 and December 2015. Inclusion criteria included clinical diagnosis of PPA; availability of complete speech, language, and cognitive testing; magnetic resonance imaging performed within 6 months of the cognitive evaluation; and PET carbon 11-labeled Pittsburgh Compound-B or florbetapir F 18 brain scan results. Of 109 patients referred for evaluation of language symptoms who underwent amyloid brain imaging, 3 were excluded because of incomplete language evaluations, 5 for absence of significant aphasia, and 12 for presenting with significant initial symptoms outside of the language domain, leaving a cohort of 89 patients with PPA. Main Outcomes and Measures:Clinical, cognitive, neuroimaging, and pathology results. Results:Twenty-eight cases were classified as imaging-supported semantic variant PPA (11 women [39.3%]; mean [SD] age, 64  years), 31 nonfluent/agrammatic variant PPA (22 women [71.0%]; mean [SD] age, 68  years), 26 logopenic variant PPA (17 women [65.4%]; mean [SD] age, 63  years), and 4 mixed PPA cases. Twenty-four of 28 patients with semantic variant PPA (86%) and 28 of 31 patients with nonfluent/agrammatic variant PPA (90%) had negative amyloid PET scan results, while 25 of 26 patients with logopenic variant PPA (96%) and 3 of 4 mixed PPA cases (75%) had positive scan results. The amyloid positive semantic variant PPA and nonfluent/agrammatic variant PPA cases with available autopsy data (2 of 4 and 2 of 3, respectively) all had a primary frontotemporal lobar degeneration and secondary Alzheimer disease pathologic diagnoses, whereas autopsy of 2 patients with amyloid PET-positive logopenic variant PPA confirmed Alzheimer disease. One mixed PPA patient with a negative amyloid PET scan had Pick disease at autopsy. Conclusions and Relevance:Primary progressive aphasia variant diagnosis according to the current classification scheme is associated with Alzheimer disease biomarker status, with the logopenic variant being associated with carbon 11-labeled Pittsburgh Compound-B positivity in more than 95% of cases. Furthermore, in the presence of a clinical syndrome highly predictive of frontotemporal lobar degeneration pathology, biomarker positivity for Alzheimer disease may be associated more with mixed pathology rather than primary Alzheimer disease.
Project description:Logopenic variant primary progressive aphasia (lvPPA) is the least well defined of the major primary progressive aphasia (PPA) syndromes. We assessed phoneme discrimination in patients with PPA (semantic, nonfluent/agrammatic, and logopenic variants) and typical Alzheimer's disease, relative to healthy age-matched participants. The lvPPA group performed significantly worse than all other groups apart from tAD, after adjusting for auditory verbal working memory. In the combined PPA cohort, voxel-based morphometry correlated phonemic discrimination score with grey matter in left angular gyrus. Our findings suggest that impaired phonemic discrimination may help differentiate lvPPA from other PPA subtypes, with important diagnostic and management implications.
Project description:Frontotemporal dementia (FTD) affects behavior, language, and personality. This study aims to explore functional connectivity changes in three FTD variants: behavioral (bvFTD), semantic (svPPA), and nonfluent variant (nfvPPA). Seventy-six patients diagnosed with FTD by international criteria and thirty-two controls were investigated. Functional connectivity from resting functional magnetic resonance imaging (fMRI) was estimated for the whole brain. Two types of analysis were done: network basic statistic and topological measures by graph theory. Several hubs in the limbic system and basal ganglia were compromised in the behavioral variant apart from frontal networks. Nonfluent variants showed a major disconnection with respect to the behavioral variant in operculum and parietal inferior. The global efficiency had lower coefficients in nonfluent variants than behavioral variants and controls. Our results support an extensive disconnection among frontal, limbic, basal ganglia, and parietal hubs.