Variant-specific vulnerability in metabolic connectivity and resting-state networks in behavioural variant of frontotemporal dementia

Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia

INTRODUCTION

Verbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease-specific semantic memory patterns. Here, we leveraged automated word-property analysis to capture neurocognitive markers of AD vis-à-vis behavioral variant frontotemporal dementia (bvFTD).

METHODS

Patients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group-level discrimination, patient-level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns.

RESULTS

Valid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group- and subject-level discrimination only in AD, also predicting executive outcomes. Disease-specific cortical thickness patterns were predicted by frequency in both disorders. Default-mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD.

DISCUSSION

Word-property analysis of fluency can boost AD characterization and diagnosis.

HIGHLIGHTS

We report novel word-property analyses of verbal fluency in AD and bvFTD. Standard valid response counts captured deficits and brain patterns in both groups. Specific word properties (e.g., frequency, granularity) were altered only in AD. Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD. Word-property analysis of fluency can boost AD characterization and diagnosis.

Functional and structural network changes related with cognition in semantic dementia longitudinally

Longitudinal changes in the white matter/functional brain networks of semantic dementia (SD), as well as their relations with cognition remain unclear. Using a graph-theoretic method, we examined the neuroimaging (T1, diffusion tensor imaging, functional MRI) network properties and cognitive performance in processing semantic knowledge of general and six modalities (i.e., object form, color, motion, sound, manipulation and function) from 31 patients (at two time points with an interval of 2 years) and 20 controls (only at baseline). Partial correlation analyses were carried out to explore the relationships between the network changes and the declines of semantic performance. SD exhibited aberrant general and modality-specific semantic impairment, and gradually worsened over time. Overall, the brain networks showed a decreased global and local efficiency in the functional network organization but a preserved structural network organization with a 2-year follow-up. With disease progression, both structural and functional alterations were found to be extended to the temporal and frontal lobes. The regional topological alteration in the left inferior temporal gyrus (ITG.L) was significantly correlated with general semantic processing. Meanwhile, the right superior temporal gyrus and right supplementary motor area were identified to be associated with color and motor-related semantic attributes. SD manifested disrupted structural and functional network pattern longitudinally. We proposed a hub region (i.e., ITG.L) of semantic network and distributed modality-specific semantic-related regions. These findings support the hub-and-spoke semantic theory and provide targets for future therapy.

Clinical relevance of disrupted topological organization of anatomical connectivity in behavioral variant frontotemporal dementia

Graph theory is a novel approach used to examine the balance of brain connectomes. However, the clinical relevance of white matter (WM) connectome changes in the behavioral variant frontotemporal dementia (bvFTD) is not well understood. We aimed to investigate the clinical relevance of WM topological alterations in bvFTD. Thirty patients with probable bvFTD and 30 healthy controls underwent diffusion tensor imaging, structural MRI, and neuropsychological assessment. WM connectivity between 90 brain regions was calculated and the graph approach was applied to capture the individual characteristics of the anatomical network. Voxel-based morphometry and tract-based spatial statistics were used to present the gray matter atrophy and disrupted WM integrity. The topological organization was disrupted in patients with bvFTD both globally and locally. Compared to controls, bvFTD data showed a different pattern of hub region distributions. Notably, the nodal efficiency of the right superior orbital frontal gyrus was associated with apathy and disinhibition. Topological measures may be potential image markers for early diagnosis and disease severity monitoring of bvFTD.

Depletion and activation of microglia impact metabolic connectivity of the mouse brain

AIM

We aimed to investigate the impact of microglial activity and microglial FDG uptake on metabolic connectivity, since microglial activation states determine FDG-PET alterations. Metabolic connectivity refers to a concept of interacting metabolic brain regions and receives growing interest in approaching complex cerebral metabolic networks in neurodegenerative diseases. However, underlying sources of metabolic connectivity remain to be elucidated.

MATERIALS AND METHODS

We analyzed metabolic networks measured by interregional correlation coefficients (ICCs) of FDG-PET scans in WT mice and in mice with mutations in progranulin (Grn) or triggering receptor expressed on myeloid cells 2 (Trem2) knockouts (^-/-) as well as in double mutant Grn^-/-/Trem2^-/- mice. We selected those rodent models as they represent opposite microglial signatures with disease associated microglia in Grn^-/- mice and microglia locked in a homeostatic state in Trem2^-/- mice; however, both resulting in lower glucose uptake of the brain. The direct influence of microglia on metabolic networks was further determined by microglia depletion using a CSF1R inhibitor in WT mice at two different ages. Within maps of global mean scaled regional FDG uptake, 24 pre-established volumes of interest were applied and assigned to either cortical or subcortical networks. ICCs of all region pairs were calculated and z-transformed prior to group comparisons. FDG uptake of neurons, microglia, and astrocytes was determined in Grn^-/- and WT mice via assessment of single cell tracer uptake (scRadiotracing).

RESULTS

Microglia depletion by CSF1R inhibition resulted in a strong decrease of metabolic connectivity defined by decrease of mean cortical ICCs in WT mice at both ages studied (6-7 m; p = 0.0148, 9-10 m; p = 0.0191), when compared to vehicle-treated age-matched WT mice. Grn^-/-, Trem2^-/- and Grn^-/-/Trem2^-/- mice all displayed reduced FDG-PET signals when compared to WT mice. However, when analyzing metabolic networks, a distinct increase of ICCs was observed in Grn^-/- mice when compared to WT mice in cortical (p < 0.0001) and hippocampal (p < 0.0001) networks. In contrast, Trem2^-/- mice did not show significant alterations in metabolic connectivity when compared to WT. Furthermore, the increased metabolic connectivity in Grn^-/- mice was completely suppressed in Grn^-/-/Trem2^-/- mice. Grn^-/- mice exhibited a severe loss of neuronal FDG uptake (- 61%, p < 0.0001) which shifted allocation of cellular brain FDG uptake to microglia (42% in Grn^-/- vs. 22% in WT).

CONCLUSIONS

Presence, absence, and activation of microglia have a strong impact on metabolic connectivity of the mouse brain. Enhanced metabolic connectivity is associated with increased microglial FDG allocation.

Neuroimaging in Dementia

OBJECTIVE

Neurodegenerative diseases are significant health concerns with regard to morbidity and social and economic hardship around the world. This review describes the state of the field of neuroimaging measures as biomarkers for detection and diagnosis of both slowly progressing and rapidly progressing neurodegenerative diseases, specifically Alzheimer disease, vascular cognitive impairment, dementia with Lewy bodies or Parkinson disease dementia, frontotemporal lobar degeneration spectrum disorders, and prion-related diseases. It briefly discusses findings in these diseases in studies using MRI and metabolic and molecular-based imaging (eg, positron emission tomography [PET] and single-photon emission computerized tomography [SPECT]).

LATEST DEVELOPMENTS

Neuroimaging studies with MRI and PET have demonstrated differential patterns of brain atrophy and hypometabolism in different neurodegenerative disorders, which can be useful in differential diagnoses. Advanced MRI sequences, such as diffusion-based imaging, and functional MRI (fMRI) provide important information about underlying biological changes in dementia and new directions for development of novel measures for future clinical use. Finally, advancements in molecular imaging allow clinicians and researchers to visualize dementia-related proteinopathies and neurotransmitter levels.

ESSENTIAL POINTS

Diagnosis of neurodegenerative diseases is primarily based on symptomatology, although the development of in vivo neuroimaging and fluid biomarkers is changing the scope of clinical diagnosis, as well as the research into these devastating diseases. This article will help inform the reader about the current state of neuroimaging in neurodegenerative diseases, as well as how these tools might be used for differential diagnoses.

Sex differences in effects of tDCS and language treatments on brain functional connectivity in primary progressive aphasia

Primary Progressive Aphasia (PPA) is a neurodegenerative disorder primarily affecting language functions. Neuromodulatory techniques (e.g., transcranial direct current stimulation, active-tDCS) and behavioral (speech-language) therapy have shown promising results in treating speech and language deficits in PPA patients. One mechanism of active-tDCS efficacy is through modulation of network functional connectivity (FC). It remains unknown how biological sex influences FC and active-tDCS or language treatment(s). In the current study, we compared sex differences, induced by active-tDCS and language therapy alone, in the default mode and language networks, acquired during resting-state fMRI in 36 PPA patients. Using a novel statistical method, the covariate-assisted-principal-regression (CAPs) technique, we found sex and age differences in FC changes following active-tDCS. In the default mode network (DMN): (1) men (in both conditions) showed greater FC in DMN than women. (2) men who received active-tDCS showed greater FC in the DMN than men who received language-treatment only. In the language network: (1) women who received active-tDCS showed significantly greater FC across the language network than women who received sham-tDCS. As age increases, regardless of sex and treatment condition, FC in language regions decreases. The current findings suggest active-tDCS treatment in PPA alters network-specific FC in a sex-dependent manner.

Identification of resting-state networks using dynamic brain perfusion SPECT imaging: A fSPECT case report

Connectivity studies with nuclear medicine systems are scarce in literature. They mainly employ PET imaging and group level analyses due to the low temporal resolution of PET and especially SPECT imaging. Our current study analyses connectivity at an individual level using dynamic SPECT imaging, which has been enabled by the improved temporal resolution performances provided by the 360°CZT cameras. We present the case of an 80-year-old man referred for brain perfusion SPECT imaging for cognitive disorders for whom a dynamic SPECT acquisition was performed utilizing a 360°CZT camera (temporal sampling of 15 frames × 3 s, 10 frames × 15 s, 14 frames × 30 s), followed by a conventional static acquisition of 15 m. Functional SPECT connectivity (fSPECT) was assessed through a seed correlation analysis and 5 well-known resting-state networks were identified: the executive, the default mode, the sensory motor, the salience, and the visual networks. This case report supports the feasibility of fSPECT imaging to identify well known resting-state networks, thanks to the novel properties of a 360°CZT camera, and opens the way to the development of more dedicated functional connectivity studies using brain perfusion SPECT imaging.

Disease specific and nonspecific metabolic brain networks in behavioral variant of frontotemporal dementia

Behavioral variant of frontotemporal dementia (bvFTD) is common among young-onset dementia patients. While bvFTD-specific multivariate metabolic brain pattern (bFDRP) has been identified previously, little is known about its temporal evolution, internal structure, effect of atrophy, and its relationship with nonspecific resting-state networks such as default mode network (DMN). In this multicenter study, we explored FDG-PET brain scans of 111 bvFTD, 26 Alzheimer's disease, 16 Creutzfeldt-Jakob's disease, 24 semantic variant primary progressive aphasia (PPA), 18 nonfluent variant PPA and 77 healthy control subjects (HC) from Slovenia, USA, and Germany. bFDRP was identified in a cohort of 20 bvFTD patients and age-matched HC using scaled subprofile model/principle component analysis and validated in three independent cohorts. It was characterized by hypometabolism in frontal cortex, insula, anterior/middle cingulate, caudate, thalamus, and temporal poles. Its expression in bvFTD patients was significantly higher compared to HC and other dementia syndromes (p < .0004), correlated with cognitive decline (p = .0001), and increased over time in longitudinal cohort (p = .0007). Analysis of internal network organization by graph-theory methods revealed prominent network disruption in bvFTD patients. We have further found a specific atrophy-related pattern grossly corresponding to bFDRP; however, its contribution to the metabolic pattern was minimal. Finally, despite the overlap between bFDRP and FDG-PET-derived DMN, we demonstrated a predominant role of the specific bFDRP. Taken together, we validated the bFDRP network as a diagnostic/prognostic biomarker specific for bvFTD, provided a unique insight into its highly reproducible internal structure, and proved that bFDRP is unaffected by structural atrophy and independent of normal resting state networks loss.

The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

Frontotemporal dementia (FTD) is a spectrum of clinical syndromes that affects personality, behavior, language, and cognition. The current diagnostic criteria recognize three main clinical subtypes: the behavioral variant of FTD (bvFTD), the semantic variant of primary progressive aphasia (svPPA), and the non-fluent/agrammatic variant of PPA (nfvPPA). Patients with FTD display heterogeneous clinical and neuropsychological features that highly overlap with those presented by psychiatric syndromes and other types of dementia. Moreover, up to now there are no reliable disease biomarkers, which makes the diagnosis of FTD particularly challenging. To overcome this issue, different studies have adopted metrics derived from magnetic resonance imaging (MRI) to characterize structural and functional brain abnormalities. Within this field, a growing body of scientific literature has shown that graph theory analysis applied to MRI data displays unique potentialities in unveiling brain network abnormalities of FTD subtypes. Here, we provide a critical overview of studies that adopted graph theory to examine the topological changes of large-scale brain networks in FTD. Moreover, we also discuss the possible role of information arising from brain network organization in the diagnostic algorithm of FTD-spectrum disorders and in investigating the neural correlates of clinical symptoms and cognitive deficits experienced by patients.

Brain metabolic connectivity reconfiguration in the semantic variant of primary progressive aphasia

Functional network-level alterations in the semantic variant of Primary Progressive Aphasia (sv-PPA) are relevant to understanding the clinical features and the neural spreading of the pathology. We assessed the effect of neurodegeneration on brain systems reorganization in early sv-PPA, using advanced brain metabolic connectivity approaches. Forty-four subjects with sv-PPA and forty-four age-matched healthy controls (HC) were included. We applied two multivariate approaches to [18F]FDG-PET data - i.e., sparse inverse covariance estimation and seed-based interregional correlation analysis - to assess the integrity of (i) the whole-brain metabolic connectivity and (ii) the connectivity of brain regions relevant for cognitive and behavioral functions. Whole-brain analysis revealed a global-scale connectivity reconfiguration in sv-PPA, with widespread changes in metabolic connections of frontal, temporal, and parietal regions. In comparison to HC, the seed-based analysis revealed a) functional isolation of the left anterior temporal lobe (ATL), b) decreases in temporo-occipital connections and contralateral homologous regions, c) connectivity increases to the dorsal parietal cortex from the spared posterior temporal cortex, d) a disruption of the large-scale limbic brain networks. In sv-PPA, the severe functional derangement of the left ATL may lead to an extensive connectivity reconfiguration, encompassing several brain regions, including those not yet affected by neurodegeneration. These findings support the hypothesis that in sv-PPA the focal vulnerability of the core region (i.e., ATL) can potentially drive the widespread cerebral connectivity changes, already present in the early phase.

A transdiagnostic review of neuroimaging studies of apathy and disinhibition in dementia

Apathy and disinhibition are common and highly distressing neuropsychiatric symptoms associated with negative outcomes in persons with dementia. This paper is a critical review of functional and structural neuroimaging studies of these symptoms transdiagnostically in dementia of the Alzheimer type, which is characterized by prominent amnesia early in the disease course, and behavioural variant frontotemporal dementia, characterized by early social-comportmental deficits. We describe the prevalence and clinical correlates of these symptoms and describe methodological issues, including difficulties with symptom definition and different measurement instruments. We highlight the heterogeneity of findings, noting however, a striking similarity of the set of brain regions implicated across clinical diagnoses and symptoms. These regions involve several key nodes of the salience network, and we describe the functions and anatomical connectivity of these brain areas, as well as present a new theoretical account of disinhibition in dementia. Future avenues for research are discussed, including the importance of transdiagnostic studies, measuring subdomains of apathy and disinhibition, and examining different units of analysis for deepening our understanding of the networks and mechanisms underlying these extremely distressing symptoms.

Exploring the functional role and neural correlates of K-complexes in isolated rapid eye movement sleep behavior disorder

Underlying neural mechanisms and cognitive implications of non-Rapid Eye Movement (NREM) sleep in isolated Rapid Eye Movement (REM) sleep behavior disorder (iRBD) are not yet fully elucidated. This study aims to evaluate brain metabolic connectivity of the anterior default mode network (ADMN) underlying a waveform that is an hallmark of NREM sleep, namely K-complex (KC) and their implication for neuropsychological functioning in iRBD patients. Combining polysomnographic and multivariate molecular imaging (FDG-PET) approaches may provide crucial insights regarding KCs role in the prodromal stages of synucleinopathies. We applied a seed-based interregional correlation analysis on FDG-PET data. iRBD patients with cognitive decline displayed a reduced KC density (KCd) in comparison to patients without cognitive impairments. KCd showed a significant positive correlation with global cognitive functioning, specifically with visuo-spatial and executive performances, two cognitive domains known to be relevant in predicting conversion into neurodegenerative disorders. Increased KCd was associated with a more preserved ADMN connectivity. Our study underlines the importance of NREM sleep in prodromal stages of synucleinopathies, and future investigations might clarify its role in iRBD.

Brain Molecular Connectivity in Neurodegenerative Conditions

Positron emission tomography (PET) allows for the in vivo assessment of early brain functional and molecular changes in neurodegenerative conditions, representing a unique tool in the diagnostic workup. The increased use of multivariate PET imaging analysis approaches has provided the chance to investigate regional molecular processes and long-distance brain circuit functional interactions in the last decade. PET metabolic and neurotransmission connectome can reveal brain region interactions. This review is an overview of concepts and methods for PET molecular and metabolic covariance assessment with evidence in neurodegenerative conditions, including Alzheimer’s disease and Lewy bodies disease spectrum. We highlight the effects of environmental and biological factors on brain network organization. All of the above might contribute to innovative diagnostic tools and potential disease-modifying interventions.

Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility

Frontotemporal lobar dementia (FTLD) is a clinically and pathologically complex disease. Advances in neuroimaging techniques have provided a specialized set of tools to investigate underlying pathophysiology and identify clinical biomarkers that aid in diagnosis, prognostication, monitoring, and identification of appropriate endpoints in clinical trials. In this chapter, we review data discussing the utility of neuroimaging biomarkers in sporadic FTLD, with an emphasis on current and future clinical applications. Among those modalities readily utilized in clinical settings, T1-weighted structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) are best supported in differential diagnosis and as targets for clinical trial endpoints. However, a number of nonclinical neuroimaging modalities, including diffusion tensor imaging and resting-state functional connectivity MRI, show promise as biomarkers to predict progression and as clinical trial endpoints. Other neuroimaging modalities, including amyloid PET, Tau PET, and arterial spin labeling MRI, are also discussed, though more work is required to establish their utility in FTLD in clinical settings.

Integrity of Neurocognitive Networks in Dementing Disorders as Measured with Simultaneous PET/Functional MRI

Functional MRI (fMRI) studies have reported altered integrity of large-scale neurocognitive networks (NCNs) in dementing disorders. However, findings on the specificity of these alterations in patients with Alzheimer disease (AD) and behavioral-variant frontotemporal dementia (bvFTD) are still limited. Recently, NCNs have been successfully captured using PET with ¹⁸F-FDG. Methods: Network integrity was measured in 72 individuals (38 male) with mild AD or bvFTD, and in healthy controls, using a simultaneous resting-state fMRI and ¹⁸F-FDG PET. Indices of network integrity were calculated for each subject, network, and imaging modality. Results: In either modality, independent-component analysis revealed 4 major NCNs: anterior default-mode network (DMN), posterior DMN, salience network, and right central executive network (CEN). In fMRI data, the integrity of the posterior DMN was found to be significantly reduced in both patient groups relative to controls. In the AD group the anterior DMN and CEN appeared to be additionally affected. In PET data, only the integrity of the posterior DMN in patients with AD was reduced, whereas 3 remaining networks appeared to be affected only in patients with bvFTD. In a logistic regression analysis, the integrity of the anterior DMN as measured with PET alone accurately differentiated between the patient groups. A correlation between indices of 2 imaging modalities was low overall. Conclusion: FMRI and ¹⁸F-FDG PET capture partly different aspects of network integrity. A higher disease specificity for NCNs as derived from PET data supports metabolic connectivity imaging as a promising diagnostic tool.