Botha, Hugo

AbstractFrom a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer’s disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer’s disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer’s disease from the normative cohort at the patient level, as well as between Alzheimer’s disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer’s disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer’s disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer’s disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer’s disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer’s disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer’s disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.

AbstractObjectivePrimary progressive apraxia of speech (PPAOS) is associated with imaging abnormalities in the lateral premotor cortex (LPC) and supplementary motor area (SMA). It is not known whether greater involvement of these regions in either hemisphere is associated with demographics, presenting, and/or longitudinal features.MethodsIn 51 prospectively recruited PPAOS patients who completed [18F]‐fluorodeoxyglucose (FDG) positron emission tomography (PET), we classified patients as left‐dominant, right‐dominant, or symmetric, based on visual assessment of the LPC and SMA on FDG‐PET. SPM and statistical analyses of regional metabolic values were performed. Diagnosis of PPAOS was made if apraxia of speech was present and aphasia absent. Thirteen patients completed ioflupane‐123I (dopamine transporter [DAT]) scans. We compared cross‐sectional and longitudinal clinicopathological, genetic, and neuroimaging characteristics across the three groups, with area under the receiver‐operating curve (AUROC) determined as a measure of effect size.ResultsIn all, 49% of the PPAOS patients were classified as left‐dominant, 31% as right‐dominant, and 20% as symmetric, which was supported by results from the SPM and regional analyses. There were no differences in baseline characteristics. Longitudinally, right‐dominant PPAOS showed faster rates of progression of ideomotor apraxia (AUROC 0.79), behavioral disturbances (AUROC 0.84), including disinhibition symptoms (AUROC 0.82) and negative behaviors (AUROC 0.82), and parkinsonism (AUROC 0.75) compared to left‐dominant PPAOS. Symmetric PPAOS showed faster rates of dysarthria progression compared to left‐dominant (AUROC 0.89) and right‐dominant PPAOS (AUROC 0.79). Five patients showed abnormal DAT uptake. Braak neurofibrillary tangle stage differed across groups (p = 0.01).ConclusionsPatients with PPAOS and a right‐dominant pattern of hypometabolism on FDG‐PET have the fastest rates of decline of behavioral and motor features.

Purpose: The purpose of this study was to describe, compare, and understand speech modulation capabilities of patients with varying motor speech disorders (MSDs) in a paradigm in which patients made highly cued attempts to speak faster or slower. Method: Twenty-nine patients, 12 with apraxia of speech (AOS; four phonetic and eight prosodic subtype), eight with dysarthria (six hypokinetic and two spastic subtype), and nine patients without any neurogenic MSD completed a standard motor speech evaluation where they were asked to repeat words and sentences, which served as their “natural” speaking rate. They were then asked to repeat lower complexity (counting 1–5; repeating “cat” and “catnip” 3 times each) and higher complexity stimuli (repeating “catastrophe” and “stethoscope” 3 times each and “My physician wrote out a prescription” once) as fast/slow as possible. Word durations and interword intervals were measured. Linear mixed-effects models were used to assess differences related to MSD subtype and stimuli complexity on bidirectional rate modulation capacity as indexed by word duration and interword interval. Articulatory accuracy was also judged and compared. Results: Patients with prosodic AOS demonstrated a reduced ability to go faster; while they performed similarly to patients with spastic dysarthria when counting, patients with spastic dysarthria were able to increase rate similar to controls during sentence repetition; patients with prosodic AOS could not and made increased articulatory errors attempting to increase rate. AOS patients made more articulatory errors relative to other groups, regardless of condition; however, their percentage of errors reduced with an intentionally slowed speaking rate. Conclusions: The findings suggest comparative rate modulation abilities in conjunction with their impact on articulatory accuracy may support differential diagnosis between healthy and abnormal speech and among subtypes of MSDs (i.e., type of dysarthria or AOS). Findings need to be validated in a larger, more representative cohort encompassing several types of MSDs. Supplemental Material: https://doi.org/10.23641/asha.22044632

Purpose: Prior studies have shown that communication-related participation restrictions in patients with degenerative disease do not always match clinician judgment or objective indices of symptom severity. Although there is a growing body of literature documenting that discrepancies between patients with dementia and their care partners' perception of participation restrictions exist, it is not known how care partner perceptions of communication participation restrictions specifically match or diverge from the patients' experiences, which may inform the use of care partner proxy in the context of degenerative diseases. Method: Thirty-eight patients with progressive neurologic conditions (progressive supranuclear palsy, corticobasal syndrome, and primary progressive aphasia or apraxia of speech) and, in most instances, focal cognitive-communication disorders were included. The patients and their accompanying care partners independently completed the Communicative Participation Item Bank, short form, a 10-question survey about communication participation restrictions in different contexts. Care partners were instructed to complete the form with their perception of the patient's experience. The difference between patient and care partner total scores were calculated and analyzed relative to clinical and demographic variables of interest. Results: Care partner ratings modestly tracked with patient experience and objective indices of symptom severity but did not exactly match patient ratings. The presence of aphasia increased, but did not fully account for, the likelihood of a discrepancy between care partner and patient ratings. Conclusion: Although careful consideration should be given prior to using care-partner report as a proxy for patient experience, it is worthwhile to include care partner ratings as a means of supporting conversations about differing perceptions, guiding joint intervention planning, and monitoring care-partner perceptions of change along with the implementation of supported conversation strategies.

Abstract Dysexecutive Alzheimer’s disease (dAD) manifests as a progressive dysexecutive syndrome without prominent behavioral features, and previous studies suggest clinico-radiological heterogeneity within this syndrome. We uncovered this heterogeneity using unsupervised machine learning in 52 dAD patients with multimodal imaging and cognitive data. A spectral decomposition of covariance between FDG-PET images yielded six latent factors (“eigenbrains”) accounting for 48% of variance in patterns of hypometabolism. These eigenbrains differentially related to age at onset, clinical severity, and cognitive performance. A hierarchical clustering on the eigenvalues of these eigenbrains yielded four dAD subtypes, i.e. “left-dominant,” “right-dominant,” “bi-parietal-dominant,” and “heteromodal-diffuse.” Patterns of FDG-PET hypometabolism overlapped with those of tau-PET distribution and MRI neurodegeneration for each subtype, whereas patterns of amyloid deposition were similar across subtypes. Subtypes differed in age at onset and clinical severity where the heteromodal-diffuse exhibited a worse clinical picture, and the bi-parietal had a milder clinical presentation. We propose a conceptual framework of executive components based on the clinico-radiological associations observed in dAD. We demonstrate that patients with dAD, despite sharing core clinical features, are diagnosed with variability in their clinical and neuroimaging profiles. Our findings support the use of data-driven approaches to delineate brain–behavior relationships relevant to clinical practice and disease physiology.

AbstractBackgroundResting state functional connectivity (rsfMRI) studies have shown functional network disruptions in logopenic progressive aphasia (LPA) (reduced connectivity within the left temporal language network) and posterior cortical atrophy (PCA) (reduced connectivity within ventral visual network). However, little is known about how these networks compare and how connectivity differs within and between networks in these atypical Alzheimer’s Disease (AD) phenotypes.MethodFifty‐nine amyloid‐positive PCA patients and eighty‐five amyloid‐positive LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent structural and resting state functional MRI. Spatially preprocessed data was analyzed using the CONN functional connectivity toolbox to explore the default mode network (DMN), salience, sensorimotor, left language, visual and memory networks, which were generated by averaging multiple regions‐of‐interest (ROI) within each network. The data was analyzed at both the voxel‐level and network‐level (ROI‐ROI).ResultVoxel‐level differences in functional connectivity between PCA and LPA were observed in all networks (p<0.05; cluster size, FWE=0.05). PCA showed reduced connectivity in the occipital lobe in visual and memory networks, parietal lobe in language and DMN, and sensorimotor strip in sensorimotor network, particularly on the right, compared to LPA. Conversely, LPA showed reduced connectivity in the frontal cortex in salience, memory, visual and sensorimotor networks, inferior parietal lobe in visual network, and anterior temporal pole and sensorimotor cortex in the language network, compared to PCA. Between network differences (p<0.05; cluster size, FDR=0.05) were observed between groups, with PCA showing reduced connectivity between the visual and sensorimotor networks, while LPA showed reduced connectivity between the language and sensorimotor networks. The DMN was anti‐correlated to the language network in PCA, while it was positively correlated to the language network in LPA. In both phenotypes, the DMN was anticorrelated with the salience network. The visual network in PCA showed connections to all networks, while in LPA, it was only connected to the salience, language and DMN.ConclusionThe atypical AD phenotypes were associated with multiple disruptions in connectivity, both within and between brain networks. Phenotype specific differences in connectivity patterns were noted in visual network for PCA and language network for LPA.