Primary progressive aphasia: From syndrome to disease

The Diagnostic Value of Language Screening in Primary Progressive Aphasia: Validation and Application of the Sydney Language Battery

PURPOSE

The three variants of primary progressive aphasia (PPA) differ in clinical presentation, underlying brain pathology, and clinical course, which stresses the need for early differentiation. However, brief cognitive tests that validly distinguish between all PPA variants are lacking. The Sydney Language Battery (SYDBAT) is a promising screening instrument that can be used as a first step in a comprehensive neuropsychological assessment to distinguish PPA subtypes, but evidence on its validity and reliability is to date limited. In the current study, the validation and diagnostic value of the SYDBAT are described for discriminating PPA subtypes as well as distinguishing PPA from mild cognitive impairment (MCI) or Alzheimer's dementia (AD).

METHOD

Forty-five patients with PPA (13 with semantic PPA, 20 with logopenic PPA, and 12 with nonfluent/agrammatic PPA), 25 MCI patients, 13 AD patients, and 50 cognitively unimpaired controls were included in this study. Both patients and controls completed the SYDBAT-NL (Dutch version). Performance on and predictive ability of the four subtests (i.e., Naming, Word Comprehension, Repetition, and Semantic Association) were assessed. In addition, construct validity and internal consistency were examined.

RESULTS

Different SYDBAT performance patterns were found across PPA and non-PPA patient groups. While a discriminant function analysis based on SYDBAT subtest scores could predict PPA subtype with 78% accuracy, it was more difficult to disentangle PPA from non-PPA patients based on SYDBAT scores alone. For assisting in clinical interpretation, simple rules were set up and translated into a diagnostic decision tree for subtyping PPA, which was capable of diagnosing a large proportion of the cases. Satisfying validity and reliability measures were found.

CONCLUSIONS

The SYDBAT is an easy-to-use and promising screen for assessing single-word language processes, which may contribute to the differential diagnostic process of PPA and the assessment of language impairment in MCI and AD. It can be easily implemented for initial screening of patients in a memory clinic.

Symptomatic, Genetic, and Mechanistic Overlaps between Autism and Alzheimer's Disease

Autism spectrum disorder (ASD) and Alzheimer's disease (AD) are neurodevelopmental and neurodegenerative disorders affecting two opposite ends of life span, i.e., childhood and old age. Both disorders pose a cumulative threat to human health, with the rate of incidences increasing considerably worldwide. In the context of recent developments, we aimed to review correlated symptoms and genetics, and overlapping aspects in the mechanisms of the pathogenesis of ASD and AD. Dementia, insomnia, and weak neuromuscular interaction, as well as communicative and cognitive impairments, are shared symptoms. A number of genes and proteins linked with both disorders have been tabulated, including MECP2, ADNP, SCN2A, NLGN, SHANK, PTEN, RELN, and FMR1. Theories about the role of neuron development, processing, connectivity, and levels of neurotransmitters in both disorders have been discussed. Based on the recent literature, the roles of FMRP (Fragile X mental retardation protein), hnRNPC (heterogeneous ribonucleoprotein-C), IRP (Iron regulatory proteins), miRNAs (MicroRNAs), and α-, β0, and γ-secretases in the posttranscriptional regulation of cellular synthesis and processing of APP (amyloid-β precursor protein) have been elaborated to describe the parallel and overlapping routes and mechanisms of ASD and AD pathogenesis. However, the interactive role of genetic and environmental factors, oxidative and metal ion stress, mutations in the associated genes, and alterations in the related cellular pathways in the development of ASD and AD needs further investigation.

How the speed of word finding depends on ventral tract integrity in primary progressive aphasia

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Noise words influence naming time, but not accuracy, more in PPA than in controls.

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Noise effect difference between PPA and controls reflects ventral tract integrity.

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The noise effect is smaller when ventral tract integrity is lower in the individuals with PPA.

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Simulations reveal that propagation of noise is reduced when tract integrity is low.

Primary progressive aphasia (PPA) is a clinical neurodegenerative syndrome with word finding problems as a core clinical symptom. Many aspects of word finding have been clarified in psycholinguistics using picture naming and a picture-word interference (PWI) paradigm, which emulates naming under contextual noise. However, little is known about how word finding depends on white-matter tract integrity, in particular, the atrophy of tracts located ventrally to the Sylvian fissure. To elucidate this question, we examined word finding in individuals with PPA and healthy controls employing PWI, tractography, and computer simulations using the WEAVER++ model of word finding. Twenty-three individuals with PPA and twenty healthy controls named pictures in two noise conditions. Mixed-effects modelling was performed on naming accuracy and reaction time (RT) and fixel-based tractography analyses were conducted to assess the relation between ventral white-matter integrity and naming performance. Naming RTs were longer for individuals with PPA compared to controls and, critically, individuals with PPA showed a larger noise effect compared to controls. Moreover, this difference in noise effect was differentially related to tract integrity. Whereas the noise effect did not depend much on tract integrity in controls, a lower tract integrity was related to a smaller noise effect in individuals with PPA. Computer simulations supported an explanation of this paradoxical finding in terms of reduced propagation of noise when tract integrity is low. By using multimodal analyses, our study indicates the significance of the ventral pathway for naming and the importance of RT measurement in the clinical assessment of PPA.

Clustering Analysis of FDG-PET Imaging in Primary Progressive Aphasia

Background: Primary progressive aphasia (PPA) is a clinical syndrome characterized by the neurodegeneration of language brain systems. Three main clinical forms (non-fluent, semantic, and logopenic PPA) have been recognized, but applicability of the classification and the capacity to predict the underlying pathology is controversial. We aimed to study FDG-PET imaging data in a large consecutive case series of patients with PPA to cluster them into different subtypes according to regional brain metabolism.

Methods: 122 FDG-PET imaging studies belonging to 91 PPA patients and 28 healthy controls were included. We developed a hierarchical agglomerative cluster analysis with Ward's linkage method, an unsupervised clustering algorithm. We conducted voxel-based brain mapping analysis to evaluate the patterns of hypometabolism of each identified cluster.

Results: Cluster analysis confirmed the three current PPA variants, but the optimal number of clusters according to Davies-Bouldin index was 6 subtypes of PPA. This classification resulted from splitting non-fluent variant into three subtypes, while logopenic PPA was split into two subtypes. Voxel-brain mapping analysis displayed different patterns of hypometabolism for each PPA group. New subtypes also showed a different clinical course and were predictive of amyloid imaging results.

Conclusion: Our study found that there are more than the three already recognized subtypes of PPA. These new subtypes were more predictive of clinical course and showed different neuroimaging patterns. Our results support the usefulness of FDG-PET in evaluating PPA, and the applicability of computational methods in the analysis of brain metabolism for improving the classification of neurodegenerative disorders.