Ask your doctor if this is enough information to get you recovered from your aphasia. Your doctor better have read this and know the answer. It is your doctor's responsibility to get you 100% recovered, don't let them weasel their way out of that by quoting this craptastic saying; 'All strokes are different, all stroke recoveries are different.' If you doctor says that, you don't have a functioning stroke doctor. RUN AWAY!
The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia
Alzheimer's Research & Therapy volume 15, Article number: 219 (2023)
Abstract
Background
Clinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants.
Methods
Forty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes).
Results
Four behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant’s characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations.
Conclusions
Cognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.
Background
Primary progressive aphasias (PPA) are a heterogeneous group of neurodegenerative disorders of language [1, 2]. Three principal clinical variants are described: a semantic variant (svPPA or semantic dementia) displaying profound conceptual knowledge degradation and anterior temporal degeneration [3, 4], a nonfluent/agrammatic variant (nfvPPA) showing marked agrammatism and/or motor-speech difficulties with fronto-insular degeneration [5], and a logopenic variant (lvPPA) characterised by slowed spontaneous speech, phonological errors, and poor length-dependent sentence repetition, and left temporoparietal degeneration [6]. Within this taxonomy, associations between discrete symptoms and brain regions suggest relatively straightforward PPA characterisation; however, three emergent issues paint a more complex picture. First, PPAs show considerable clinical variation within, and overlap between, subtypes, with some features shared across distinct variants. Second, it is unclear why some patients present with additional, co-occurring non-linguistic cognitive impairments. Finally, we lack a full understanding of the neurobiological mechanisms underpinning cognitive-linguistic heterogeneity. Tackling these three issues is important to ensure diagnostic accuracy, identify potential behavioural/brain moderators of PPA disease phenotype, and to improve clinical trials design.
Language and semantic tests are central to the clinical characterisation of PPA. While marked and relatively selective conceptual knowledge degradation is most closely associated with svPPA [3, 7], approximately 40% of PPA cases show linguistic profiles falling between syndromic boundaries [7,8,9]. Particularly, disentangling nfvPPA from lvPPA on language performance alone can be challenging [10, 11]. Difficulties with word-finding, multisyllabic repetition, and lexical/phonological processing, typical of lvPPA, are also documented in nfvPPA [11,12,13,14,15]. Such overlaps emerge from partly dissociable neurocognitive substrates. For example, nfvPPA and lvPPA show compromised speech production but due to differential breakdowns in motor-speech/phonology/syntax vs. verbal working memory processing regions [11, 16,17,18]. Likewise, naming deficits may relate to disproportionate involvement of semantic (svPPA), phonological/motor-speech (nfvPPA), or phonological/working memory processing (lvPPA) regions [19]. These findings suggest that language profiles between syndromes vary in a graded, not absolute manner, closely reflecting involvement of different neurocognitive systems [7, 18, 20, 21]. Capturing such heterogeneity requires sensitive assessments capable of disentangling interdependencies at cognitive-neural process-levels to reveal shared/unique contributors. Currently, many measures used for PPA diagnostics derive metrics of overall aphasia severity and/or have limited range and depth of assessment [22,23,24]; therefore, they may poorly specify PPA type [10, 25] and breakdowns in corresponding neurocognitive systems [26]. As such, we require measures better suited to reveal process-level breakdowns common/unique to variants.
The second issue pertains to the status of non-linguistic cognition in PPA. Language and communication difficulties are central to lived experiences of PPA; unsurprisingly, these domains have received overwhelming research focus. Traditionally, non-linguistic difficulties were proposed to emerge either later with disease progression or as a by-product of primary aphasia [27]. Mounting evidence challenges this hypothesis to show general cognitive difficulties in early disease stages and at first clinic visit for many patients [28]. For example, transmodal semantic degradation in svPPA causes non-verbal semantic impairments even in early disease stages [29]. In nfvPPA, executive deficits often co-occur early with motor-speech difficulties [30]. LvPPA frequently displays non-linguistic cognitive difficulties such as nonverbal episodic memory, spatial orientation and working memory, and visuospatial processing [31,32,33,34,35,36,37]. In lvPPA, these deficits can emerge independent of disease severity, aphasia magnitude, and relate closely to encroachment of pathology into the temporoparietal cortex [20, 38, 39]. To understand PPA phenotypic heterogeneity, we need deeper investigation into non-linguistic dysfunction, its association with aphasia, and neurodegeneration profiles.
Finally, PPAs have been conceptualised as neural-network disorders where neurodegeneration spreads from syndrome-specific epicentres to functionally/structurally connected regions [40,41,42,43,44]. This account signals the need to evaluate concurrent changes to grey and white matter integrity to arrive at a comprehensive view of PPA clinico-anatomical changes. While grey matter correlates of PPA linguistic profiles are widely investigated [45], white matter changes and their relationship with linguistic/non-linguistic variation in PPA remain less understood. Previous work employing diffusion tensor imaging has revealed, in each variant, pronounced white matter changes to atrophy epicentres and their structurally connected regions [46,47,48,49,50]. Structural integrity between temporal, prefrontal, and parietal cortices further correlates with emergent language, behaviour, and episodic memory difficulties in PPA suggesting that clinical variability emerges from white matter damage beyond the language network [31, 51,52,53,54,55]. Diffusion tensor imaging, however, holds severe limitations in modelling crossing fibres (present in > 90% of white matter voxels) [56], thereby affecting false negative/positive results and interpretation of surrogate white matter integrity markers (e.g., fractional anisotropy, FA) [56, 57]. Addressing these limitations, we explored grey/white matter brain changes underlying PPA cognitive-linguistic heterogeneity, combining grey matter and contemporary white matter imaging analytic pipelines that reliably model intra-voxel directional white matter integrity.
Here, we make three advances towards an improved clinico-anatomical understanding of PPA phenotypic heterogeneity. First, we used multi-site data from PPA specialist clinics and a novel error-based assessment (Mini Linguistic State Examination; MLSE), designed for PPA, that holds proven sensitivity/specificity (> 95% accuracy) in characterising nuanced language profiles [58,59,60]. Compared to global performance scores, error patterns offer improved precision in revealing breakdowns in cognitive-linguistic processes and corresponding neural architectures [21, 61,62,63]. We also included an established general cognitive assessment (Addenbrooke’s Cognitive Examination-III, ACE-III) [64] showing demonstrable sensitivity to subtle non-linguistic cognitive changes in PPA [65]. Second, we modelled corresponding associations with grey/white matter integrity using whole-brain voxel-based morphometry (grey matter) and structural connectomic network-based statistics (white matter) derived from constrained spherical deconvolution-informed whole-brain tractography [57, 66,67,68,69]. The final advance is relating PPA phenotypic heterogeneity to breakdowns at the level of neurocognitive systems. Classic methods examining heterogeneity (e.g., group difference analyses) inadequately capture features cutting across diagnostic entities, within-group variability, and atypical/intermediate clinical presentations. Instead, multiple recent studies across a variety of neurological disorders have demonstrated the power of transdiagnostic multidimensional phenotypic geometries that (i) simultaneously model performance covariance patterns across groups/tests to uncover features shared between and specific to clinical entities and (ii) can help unpick process-level breakdowns contributing to overt test performance. This approach opens up a potentially powerful way to model clinical feature overlap by assimilating paradigmatic cases of each group, the graded variations within and between groups, and the many “mixed” cases presenting in the clinic, all within one multidimensional “geometry” [7, 20, 21, 70,71,72,73,74,75]. As these dimensions can reflect core neurocognitive systems, positioning individuals within this space further aids understanding of the blended mixture of damage to key neurocognitive systems that give rise to phenotypic similarity/differences [76]. In PPA, a number of studies have established this approach at the behavioural level [7, 20, 72], and so in this study, we take an important new step, by exploring how these multidimensional neurocognitive geometries map on to underlying neuroanatomy. To make progress towards translation and adoption of these frameworks into PPA clinical characterisation, we need to understand how emergent dimensions map on to common/different underlying brain systems. By combining a behaviour-brain dimensional mapping approach, we advance our current understanding of the genesis of PPA clinical heterogeneity and associated dysfunction of distributed neurocognitive systems.
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