Disease-related cortical thinning in presymptomatic granulin mutation carriers

Automated brain segmentation and volumetry in dementia diagnostics: a narrative review with emphasis on FreeSurfer

Background

Dementia can be caused by numerous different diseases that present variable clinical courses and reveal multiple patterns of brain atrophy, making its accurate early diagnosis by conventional examinative means challenging. Although highly accurate and powerful, magnetic resonance imaging (MRI) currently plays only a supportive role in dementia diagnosis, largely due to the enormous volume and diversity of data it generates. AI-based software solutions/algorithms that can perform automated segmentation and volumetry analyses of MRI data are being increasingly used to address this issue. Numerous commercial and non-commercial software solutions for automated brain segmentation and volumetry exist, with FreeSurfer being the most frequently used.

Objectives

This Review is an account of the current situation regarding the application of automated brain segmentation and volumetry to dementia diagnosis.

Methods

We performed a PubMed search for “FreeSurfer AND Dementia” and obtained 493 results. Based on these search results, we conducted an in-depth source analysis to identify additional publications, software tools, and methods. Studies were analyzed for design, patient collective, and for statistical evaluation (mathematical methods, correlations).

Results

In the studies identified, the main diseases and cohorts represented were Alzheimer’s disease (n = 276), mild cognitive impairment (n = 157), frontotemporal dementia (n = 34), Parkinson’s disease (n = 29), dementia with Lewy bodies (n = 20), and healthy controls (n = 356). The findings and methods of a selection of the studies identified were summarized and discussed.

Conclusion

Our evaluation showed that, while a large number of studies and software solutions are available, many diseases are underrepresented in terms of their incidence. There is therefore plenty of scope for targeted research.

Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study

BACKGROUND

Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches.

METHODS

In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD.

RESULTS

In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01).

CONCLUSIONS

This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.

Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia

Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.

Brain Metabolic Profile in Presymptomatic GRN Carriers Throughout a 5-Year Follow-up

BACKGROUND AND OBJECTIVES

GRN variants are a frequent cause of familial frontotemporal dementia (FTD). Monitoring disease progression in asymptomatic carriers of genetic variants is a major challenge in delivering preventative therapies before clinical onset. This study aimed to assess the usefulness of fluorodeoxyglucose (FDG)-PET in identifying metabolic changes in presymptomatic GRN carriers (PS-GRN+) and to trace their longitudinal progression.

METHODS

Participants were longitudinally evaluated over 5 years in a prospective cohort study focused on GRN disease (Predict-PGRN). They underwent cognitive/behavioral assessment, plasma neurofilament measurement, brain MRI, and FDG-PET. Voxel-wise comparisons of structural and metabolic imaging data between 2 groups were performed for each time point. Longitudinal PET changes were evaluated with voxel-wise comparisons and the metabolic percent annual changes method. The association of regional brain metabolism with plasma neurofilament and cognitive changes was analyzed.

RESULTS

Among the 80 individuals enrolled in the study, 58 (27 PS-GRN+ and 31 noncarriers) were included in the analyses. Cross-sectional comparisons between PS-GRN+ and controls found a significant hypometabolism in the left superior temporal sulcus (STS) region (encompassing the middle and superior temporal gyri), approximately 15 years before the expected disease onset, without significant cortical atrophy. The longitudinal metabolic decline over the following 5 years peaked around the right STS in carriers (p < 0.001), without significantly greater volume loss compared with that in controls. Their estimated annualized metabolic decrease (-1.37%) was higher than that in controls (-0.21%, p = 0.004). Lower glucose uptake was associated with higher neurofilament increase (p = 0.003) and lower frontal cognitive scores (p = 0.014) in PS-GRN+.

DISCUSSION

This study detected brain metabolic changes in the STS region, preceding structural and cognitive alterations, thus contributing to the characterization of the pathochronology of preclinical GRN disease. Owing to the STS involvement in the perception of facially communicated cues, it is likely that its dysfunction contributes to social cognition deficits characterizing FTD. Overall, our study highlights brain metabolic changes as an early disease-tracking biomarker and proposes annualized percent decrease as a metric to monitor therapeutic response in forthcoming trials.

The role of neurofilament light in genetic frontotemporal lobar degeneration

Genetic frontotemporal lobar degeneration caused by autosomal dominant gene mutations provides an opportunity for targeted drug development in a highly complex and clinically heterogeneous dementia. These neurodegenerative disorders can affect adults in their middle years, progress quickly relative to other dementias, are uniformly fatal and have no approved disease-modifying treatments. Frontotemporal dementia, caused by mutations in the GRN gene which encodes the protein progranulin, is an active area of interventional drug trials that are testing multiple strategies to restore progranulin protein deficiency. These and other trials are also examining neurofilament light as a potential biomarker of disease activity and disease progression and as a therapeutic endpoint based on the assumption that cerebrospinal fluid and blood neurofilament light levels are a surrogate for neuroaxonal damage. Reports from genetic frontotemporal dementia longitudinal studies indicate that elevated concentrations of blood neurofilament light reflect disease severity and are associated with faster brain atrophy. To better inform patient stratification and treatment response in current and upcoming clinical trials, a more nuanced interpretation of neurofilament light as a biomarker of neurodegeneration is now required, one that takes into account its relationship to other pathophysiological and topographic biomarkers of disease progression from early presymptomatic to later clinically symptomatic stages.

Pre-symptomatic radiological changes in frontotemporal dementia: propagation characteristics, predictive value and implications for clinical trials

Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3-141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1-8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.

Structural brain splitting is a hallmark of Granulin-related frontotemporal dementia

Frontotemporal dementia associated with granulin (GRN) mutations presents asymmetric brain atrophy. We applied a Minimum Spanning Tree plus an Efficiency Cost Optimization approach to cortical thickness data in order to test whether graph theory measures could identify global or local impairment of connectivity in the presymptomatic phase of pathology, where other techniques failed in demonstrating changes. We included 52 symptomatic GRN mutation carriers (SC), 161 presymptomatic GRN mutation carriers (PSC) and 341 non-carriers relatives from the Genetic Frontotemporal dementia research Initiative cohort. Group differences of global, nodal and edge connectivity in (Minimum Spanning Tree plus an Efficiency Cost Optimization) graph were tested via Structural Equation Models. Global graph perturbation was selectively impaired in SC compared to non-carriers, with no changes in PSC. At the local level, only SC exhibited perturbation of frontotemporal nodes, but edge connectivity revealed a characteristic pattern of interhemispheric disconnection, involving homologous parietal regions, in PSC. Our results suggest that GRN-related frontotemporal dementia resembles a disconnection syndrome, with interhemispheric disconnection between parietal regions in presymptomatic phases that progresses to frontotemporal areas as symptoms emerge.

Dissemination in time and space in presymptomatic granulin mutation carriers: a GENFI spatial chronnectome study

The presymptomatic brain changes of granulin (GRN) disease, preceding by years frontotemporal dementia, has not been fully characterized. New approaches focus on the spatial chronnectome can capture both spatial network configurations and their dynamic changes over time. To investigate the spatial dynamics in 141 presymptomatic GRN mutation carriers and 282 noncarriers from the Genetic Frontotemporal dementia research Initiative cohort. We considered time-varying patterns of the default mode network, the language network, and the salience network, each summarized into 4 distinct recurring spatial configurations. Dwell time (DT) (the time each individual spends in each spatial state of each network), fractional occupacy (FO) (the total percentage of time spent by each individual in a state of a specific network) and total transition number (the total number of transitions performed by each individual in a specifict state) were considered. Correlations between DT, FO, and transition number and estimated years from expected symptom onset (EYO) and clinical performances were assessed. Presymptomatic GRN mutation carriers spent significantly more time in those spatial states characterised by greater activation of the insula and the parietal cortices, as compared to noncarriers (p < 0.05, FDR-corrected). A significant correlation between DT and FO of these spatial states and EYO was found, the longer the time spent in the spatial states, the closer the EYO. DT and FO significantly correlated with performances at tests tapping processing speed, with worse scores associated with increased spatial states' DT. Our results demonstrated that presymptomatic GRN disease presents a complex dynamic reorganization of brain connectivity. Change in both the spatial and temporal aspects of brain network connectivity could provide a unique glimpse into brain function and potentially allowing a more sophisticated evaluation of the earliest disease changes and the understanding of possible mechanisms in GRN disease.