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The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia.

Ramanan, S; Halai, AD; Garcia-Penton, L; Perry, AG; Patel, N; Peterson, KA; Ingram, RU; Storey, I; Cappa, SF; Catricala, E; et al. Ramanan, S; Halai, AD; Garcia-Penton, L; Perry, AG; Patel, N; Peterson, KA; Ingram, RU; Storey, I; Cappa, SF; Catricala, E; Patterson, K; Rowe, JB; Garrard, P; Ralph, MAL (2023) The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia. Alzheimers Res Ther, 15 (1). p. 219. ISSN 1758-9193 https://doi.org/10.1186/s13195-023-01350-2
SGUL Authors: Patel, Nikil

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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.

Item Type: Article
Additional Information: © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Keywords: Alzheimer’s disease, Frontotemporal dementia, Language, Network-based statistics, Voxel-based morphometry, Humans, Aphasia, Primary Progressive, Magnetic Resonance Imaging, Brain, Cognition, Linguistics, Brain, Humans, Aphasia, Primary Progressive, Magnetic Resonance Imaging, Cognition, Linguistics, Alzheimer's disease, Frontotemporal dementia, Language, Network-based statistics, Voxel-based morphometry, 11 Medical and Health Sciences
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Alzheimers Res Ther
ISSN: 1758-9193
Language: eng
Dates:
DateEvent
16 December 2023Published
8 November 2023Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
MC_UU_00005/18Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/R023883/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/N0235881/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
NIHR203312National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
A1699Rosetrees Trusthttp://dx.doi.org/10.13039/501100000833
MR/V031481/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
893329Horizon 2020http://dx.doi.org/10.13039/501100007601
SUAG/092 116768Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
GAP: 670428-30 BRAIN2MIND_NEUROCOMPEuropean Research Councilhttp://dx.doi.org/10.13039/501100000781
PubMed ID: 38102724
Web of Science ID: WOS:001125478500001
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/116033
Publisher's version: https://doi.org/10.1186/s13195-023-01350-2

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