Comparison of prefrontal atrophy and episodic memory performance in dysexecutive Alzheimer’s disease and behavioural-variant frontotemporal dementia

Alzheimer’s disease (AD) sometimes presents with prominent executive dysfunction and associated prefrontal cortex atrophy. The impact of such executive deficits on episodic memory performance as well as their neural correlates in AD, however, remains unclear. The aim of the current study was to investigate episodic memory and brain atrophy in AD patients with relatively spared executive functioning (SEF-AD; n = 12) and AD patients with relatively impaired executive functioning (IEF-AD; n = 23). We also compared the AD subgroups with a group of behavioral-variant frontotemporal dementia patients (bvFTD; n = 22), who typically exhibit significant executive deficits, and age-matched healthy controls (n = 38). On cognitive testing, the three patient groups showed comparable memory profiles on standard episodic memory tests, with significant impairment relative to controls. Voxel-based morphometry analyses revealed extensive prefrontal and medial temporal lobe atrophy in IEF-AD and bvFTD, whereas this was limited to the middle frontal gyrus and hippocampus in SEF-AD. Moreover, the additional prefrontal atrophy in IEF-AD and bvFTD correlated with memory performance, whereas this was not the case for SEF-AD. These findings indicate that IEF-AD patients show prefrontal atrophy in regions similar to bvFTD, and suggest that this contributes to episodic memory performance. This has implications for the differential diagnosis of bvFTD and subtypes of AD

Early-onset and late-onset Alzheimer’s disease are associated with distinct patterns of memory impairment

The goal of this study was to investigate the specific patterns of memory breakdown in patients suffering from early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD). Twenty EOAD patients, twenty LOAD patients, twenty matched younger controls, and twenty matched older controls participated in this study. All participants underwent a detailed neuropsychological assessment, an MRI scan, an FDG-PET scan, and AD patients had biomarkers as supporting evidence of both amyloïdopathy and neuronal injury. Results of the neuropsychological assessment showed that both EOAD and LOAD groups were impaired in the domains of memory, executive functions, language, praxis, and visuoconstructional abilities, when compared to their respective control groups. EOAD and LOAD groups, however, showed distinct patterns of memory impairment. Even though both groups were similarly affected on measures of episodic, short term and working memory, in contrast semantic memory was significantly more impaired in LOAD than in EOAD patients. The EOAD group was not more affected than the LOAD group in any memory domain. EOAD patients, however, showed significantly poorer performance in other cognitive domains including executive functions and visuoconstructional abilities. A more detailed analysis of the pattern of semantic memory performance among patient groups revealed that the LOAD was more profoundly impaired, in tasks of both spontaneous recall and semantic recognition. Voxel-Based Morphometry (VBM) analyses showed that impaired semantic performance in patients was associated with reduced gray matter volume in the anterior temporal lobe region, while PET-FDG analyses revealed that poorer semantic performance was associated with greater hypometabolism in the left temporoparietal region, both areas reflecting key regions of the semantic network. Results of this study indicate that EOAD and LOAD patients present with distinct patterns of memory impairment, and that a genuine semantic impairment may represent one of the clinical hallmarks of LOAD

Posterior cortical atrophy: a neuropsychological and neuroimaging study

This thesis investigates the neuroimaging and neuropsychological characteristics of Posterior Cortical Atrophy (PCA) which is most often caused by Alzheimer’s disease (AD) pathology. Posterior cortical atrophy describes a predominantly posterior pattern of atrophy and cognitive deficits. PCA has been poorly characterized and is likely to have been under-recognized. Using magnetic resonance imaging (MRI), patterns of cortical thickness were assessed in patients with pathologically-confirmed AD and different clinical presentations during life (including amnestic, visual and behavioural phenotypes). In addition to atrophy in the medial temporal lobe, tissue loss in posterior regions is indicative of AD pathology. Since medial temporal lobe atrophy is not specific to AD, posterior atrophy may aid distinction between AD and other dementias. Using easily-applied visual rating scales for medial temporal and posterior atrophy in patients with pathologically-confirmed AD and frontotemporal lobar degeneration (FTLD), it was shown that posterior atrophy ratings improve classification accuracy of AD from FTLD and controls. Cross-sectional and longitudinal image analysis techniques were used to characterize atrophy patterns in PCA compared with controls and typical amnestic AD. Whilst the cross-sectional analysis revealed differential patterns of tissue loss in these two groups, with PCA showing greatest atrophy in posterior parietal regions, and typical AD predominantly in medial temporal lobe regions, longitudinal results showed that at five years disease duration, both PCA and typical AD had global grey matter loss and cortical thinning compared with controls. The nature of visual deficits in PCA was assessed by administering detailed neuropsychological tests. The behavioural data showed that visual deficits were not uniformly affected in PCA, with considerable heterogeneity of visual impairments shown. Cortical thickness measures were used to assess atrophy patterns in PCA patients with predominant space versus object perception impairments, revealing overlap in cortical thinning patterns between these two PCA subgroups. In summary this thesis investigates the common and differential atrophy patterns of atypical AD presentations as well as the degree of heterogeneity of deficits which exist within the PCA presentation

Early Medial Temporal Atrophy Scale (EMTA)

186 p.[ES]La atrofia del lóbulo temporal medial puede ser medida a través del uso de escalas de atrofia visual tales como la escala de atrofia del lóbulo temporal medial (MTA). La escala MTA ha sido diseñada y validada para el estudio de pacientes con Enfermedad de Alzheimer moderada (EA). Sin embargo, la MTA no ha sido diseñada para medir los cambios de atrofia de bajo grado que ocurren en la etapa precoz y media del proceso de envejecimiento. El objetivo de este estudio fue desarrollar y validar una nueva MTA; La “Goiz” (en Euskera) GMTA o “Early” (en ingles) EMTA, una nueva escala diseñada para la valoración de la atrofia precoz del lóbulo temporal medial que tiene la capacidad de medir los cambios de atrofia de bajo grado.[EN]Medial temporal lobe atrophy can be measured through visual rating scales such us the medial temporal lobe atrophy scale (MTA). MTA has been designed and validated for the study of patients with mild to moderate Alzheimer disease (AD). However, MTA has not been designed to measure the low-grade atrophy changes that occur at the early and middle aging process. The aim of this study was develop and validate a new MTA; the early (“Goiz” in Basque language) medial temporal lobe atrophy scale (EMTA) that has the capability to measure the low-grade atrophy changes

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes that present significant differences in various brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal MRI to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer disease, schizophrenia, major depressive disorder, autism spectrum disorder, multiple sclerosis, as well as their potential in transdiagnostic settings. Subsequently, we summarize relevant machine learning methodologies and discuss an emerging paradigm which we call dimensional neuroimaging endophenotype (DNE). DNE dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into a low dimensional yet informative, quantitative brain phenotypic representation, serving as a robust intermediate phenotype (i.e., endophenotype) largely reflecting underlying genetics and etiology. Finally, we discuss the potential clinical implications of the current findings and envision future research avenues

Language impairment in frontotemporal lobar degeneration

The term frontotemporal lobar degeneration (FTLD) describes a heterogeneous group of neurodegenerative disorders associated with frontal and temporal lobe atrophy. Within this spectrum, two progressive aphasia syndromes, progressive nonfluent aphasia (PNFA) and semantic dementia (SD), are well described. FTLD is commonly a genetic disorder and mutations in two genes, microtubule-associated protein tau (MAPT) and progranulin (GRN) account for a large proportion of familial cases. A retrospective imaging study using cortical thickness measures shows involvement of the anteroinferior temporal lobes in SD and the left inferior frontal lobe/insula in PNFA. Studies of disease severity and of longitudinal imaging reveal spread through the left hemisphere and into the right hemisphere in both groups. A genetics and heritability study shows that PNFA can be familial, although much less than the behavioural variant of FTLD, and that this is often due to mutations in GRN. Differing patterns of atrophy are shown between different genetic mutations and also between different pathologies with the same clinical syndrome. Evidence from the neurological, neuropsychological, neuroanatomical, genetic and pathological features of the nonfluent aphasias suggests that there are at least three nonfluent aphasia syndromes: a disorder with motor speech impairment with or without agrammatism, a disorder with agrammatism but no apraxia of speech (found in patients with progranulin mutations) and a disorder without agrammatism or apraxia of speech but with word-finding pauses (consistent with descriptions of logopenic/phonological aphasia and pathologically associated with Alzheimer’s disease). Studies of specific deficits (single word processing, prosody, neologistic jargon, apraxia and behavioural symptoms) in the progressive aphasias provide further insight into the disease. This thesis therefore provides neurological, neuropsychological and imaging data with related genetic and pathological information that can provide greater insights into the natural history and classification, and therefore pathophysiological basis of the neurodegenerative disorders that cause primary progressive language impairment

Imaging Genetics and Biomarker Variations of Clinically Diagnosed Alzheimer's Disease

Indiana University-Purdue University Indianapolis (IUPUI)Neuroimaging biomarkers play a crucial role in our understanding of Alzheimer’s disease. Beyond providing a fast and accurate in vivo picture of the neuronal structure and biochemistry, these biomarkers make up a research framework, defined in a 2018 as the A(amyloid)/T(tau)/N(neurodegeneration) framework after three of the hallmarks of Alzheimer’s disease. I first used imaging measures of amyloid, tau and neurodegeneration to study clinically diagnosed Alzheimer’s disease. After dividing subjects into early (onset younger than 65) and late-onset (onset of 65 and older) amyloid-positive (AD) and amyloid-negative (nonAD) groups, I saw radically differing topographical distribution of tau and neurodegeneration. AD subjects with an early disease onset had a much more severe amyloid, tau and neurodegeneration than lateonset AD. In the nonAD group, neurodegeneration was found only in early-onset FDG PET data and in a nonAlzheimer’s-like MRI and FDG pattern for late-onset. The late-onset nonAD resembled that of limbic-predominant age-related TDP-43 encephalopathy. I next utilized an imaging genetics approach to associate genome-wide significant Alzheimer’s risk variants to structural (MRI), metabolic (FDG PET) and tau (tau PET) imaging biomarkers. Linear regression was used to select variants for each of the models and included a pooled sample, cognitively normal, mild cognitive impairment and dementia groups in order to fully capture the cognitive spectrum from normal cognition to the most severely impaired. Model selected variants were replicated using voxelwise regression in an exploratory analysis of spatial associations for each modality. For each imaging type, I replicated some associations to the biomarkers previously seen, as well as identified several novel associations. Several variants identified with crucial Alzheimer’s biomarkers may be potential future targets for drug interventions