Longitudinal multimodal MRI as prognostic and diagnostic biomarker in presymptomatic familial frontotemporal dementia

Research trends and hotspots for frontotemporal dementia from 2000 to 2022: a bibliometric analysis

Background

Frontotemporal dementia (FTD) is a neurodegenerative disease with clinical, pathological, and genetic heterogeneity. FTD is receiving increasing attention because it is the second leading cause of early-onset dementia after Alzheimer's disease. This study aimed to analyse the research trends and hotspots of FTD from 2000 to 2022 using bibliometrics.

Methods

Papers related to FTD from 2000 to 2020 were systematically searched through the Web of Science Core Collection (WOSCC). Citespace and Vosviewer software were used to visually analyse the retrieved data of countries/regions, institutions, journals, authors, references, and keywords. Microsoft Excel was used to generate the annual publications and growth trends.

Results

There were 10,227 papers included in the bibliometric analysis. The annual publication output on FTD has increased significantly from 2000 to 2022, with papers published in 934 academic journals and 87 countries/regions. The Journal of Alzheimer's Disease was the most popular, with 488 papers about FTD. The most productive countries/regions, institutions, and authors are the United States (n = 4,037), the University of California San Francisco (n = 687), and Miller, Bruce L. (n = 427), respectively. The article by Katya Rascovsky and her colleagues published on Brain in 2011 was the most cocited paper, with 625 citations. The research hotspots in this field were the clinical diagnostic criteria, subdivision, and pathological mechanism of FTD, such as tau protein, chromosome 17, progranulin, TDP-43, and C9orf72.

Conclusion

The future research direction is based on biomarkers and pathological mechanisms to diagnose and differential diagnose FTD from the aspects of behavior, neuropathology, neuroimaging, and serum markers.

Longitudinal cerebral perfusion in presymptomatic genetic frontotemporal dementia: GENFI results

INTRODUCTION

Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers.

METHODS

We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non-carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment.

RESULTS

Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset.

DISCUSSION

Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset.

HIGHLIGHTS

Gray matter perfusion declines in at-risk genetic frontotemporal dementia (FTD). Regional perfusion decline differs between at-risk genetic FTD subgroups . Hypoperfusion in the left thalamus is common across all presymptomatic groups. Converters exhibit greater right frontal hypoperfusion than non-converters past their expected conversion date. Cerebral hypoperfusion is a potential early biomarker of genetic FTD.

Neurite-based white matter alterations in MAPT mutation carriers: A multi-shell diffusion MRI study in the ALLFTD consortium

We assessed white matter (WM) integrity in MAPT mutation carriers (16 asymptomatic, 5 symptomatic) compared to 31 non-carrier family controls using diffusion tensor imaging (DTI) (fractional anisotropy; FA, mean diffusivity; MD) and neurite orientation dispersion and density imaging (NODDI) (neurite density index; NDI, orientation and dispersion index; ODI). Linear mixed-effects models accounting for age and family relatedness revealed alterations across DTI and NODDI metrics in all mutation carriers and in symptomatic carriers, with the most significant differences involving fronto-temporal WM tracts. Asymptomatic carriers showed higher entorhinal MD and lower cingulum FA and patterns of higher ODI mostly involving temporal areas and long association and projections fibers. Regression models between estimated time to or time from disease and DTI and NODDI metrics in key regions (amygdala, cingulum, entorhinal, inferior temporal, uncinate fasciculus) in all carriers showed increasing abnormalities with estimated time to or time from disease onset, with FA and NDI showing the strongest relationships. Neurite-based metrics, particularly ODI, appear to be particularly sensitive to early WM involvement in asymptomatic carriers.

Characterization of Progranulin Gene Mutations in Portuguese Patients with Frontotemporal Dementia

In Portugal, heterozygous loss-of-function mutations in the progranulin (GRN) gene account for approximately half of the genetic mediated forms of frontotemporal dementia (FTD). GRN mutations reported thus far cause FTD through a haploinsufficiency disease mechanism. Herein, we aim to unveil the GRN mutation spectrum, investigated in 257 FTD patients and 19 family members from the central/north region of Portugal using sequencing methods. Seven different pathogenic variants were identified in 46 subjects including 40 patients (16%) and 6 relatives (32%). bvFTD was the most common clinical presentation among the GRN mutation patients, who showed a global pattern of moderate-to-severe frontotemporoparietal deficits in the neuropsychological evaluation. Interestingly, two mutations were novel (p.Thr238Profs*18, p.Leu354Profs*16), and five were previously described, although three of them only in the Portuguese population, suggesting a population-specific GRN mutational spectrum. The subjects harboring a GRN mutation showed a significant reduction in serum PGRN levels, supporting the pathogenic nature of these variants. This work broadens the mutation spectrum of GRN and the identification of the underlying GRN mutations provided an accurate genetic counselling and allowed the enrolment of subjects with GRN mutations (both asymptomatic and symptomatic) in ongoing clinical trials, which is essential to test new drugs for the disease.

Longitudinal changes in qualitative aspects of semantic fluency in presymptomatic and prodromal genetic frontotemporal dementia

BACKGROUND

The semantic fluency test is one of the most widely used neuropsychological tests in dementia diagnosis. Research utilizing the qualitative, psycholinguistic information embedded in its output is currently underexplored in presymptomatic and prodromal genetic FTD.

METHODS

Presymptomatic MAPT (n = 20) and GRN (n = 43) mutation carriers, and controls (n = 55) underwent up to 6 years of neuropsychological assessment, including the semantic fluency test. Ten mutation carriers became symptomatic (phenoconverters). Total score and five qualitative fluency measures (lexical frequency, age of acquisition, number of clusters, cluster size, number of switches) were calculated. We used multilevel linear regression modeling to investigate longitudinal decline. We assessed the co-correlation of the qualitative measures at each time point with principal component analysis. We explored associations with cognitive decline and grey matter atrophy using partial correlations, and investigated classification abilities using binary logistic regression.

RESULTS

The interrater reliability of the qualitative measures was good (ICC = 0.75-0.90). There was strong co-correlation between lexical frequency and age of acquisition, and between clustering and switching. At least 4 years pre-phenoconversion, GRN phenoconverters had fewer but larger clusters (p < 0.001), and fewer switches (p = 0.004), correlating with lower executive function (r = 0.87-0.98). Fewer switches was predictive of phenoconversion, correctly classifying 90.3%. Starting at least 4 years pre-phenoconversion, MAPT phenoconverters demonstrated an increase in lexical frequency (p = 0.009) and a decline in age of acquisition (p = 0.034), correlating with lower semantic processing (r = 0.90). Smaller cluster size was predictive of phenoconversion, correctly classifying 89.3%. Increase in lexical frequency and decline in age of acquisition were associated with grey matter volume loss of predominantly temporal areas, while decline in the number of clusters, cluster size, and switches correlated with grey matter volume loss of predominantly frontal areas.

CONCLUSIONS

Qualitative aspects of semantic fluency could give insight into the underlying mechanisms as to why the "traditional" total score declines in the different FTD mutations. However, the qualitative measures currently demonstrate more fluctuation than the total score, the measure that seems to most reliably deteriorate with time. Replication in a larger sample of FTD phenoconverters is warranted to identify if qualitative measures could be sensitive cognitive biomarkers to identify and track mutation carriers converting to the symptomatic stage of FTD.

microRNA-based predictor for diagnosis of frontotemporal dementia

AIMS

This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis.

METHODS

We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls).

RESULTS

On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases.

CONCLUSIONS

The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.

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.

Frontotemporal Degeneration with Transactive Response DNA-Binding Protein Type C at the Anterior Temporal Lobe

The anatomical distribution of most neurodegenerative diseases shows considerable interindividual variations. In contrast, frontotemporal lobar degeneration with transactive response DNA-binding protein type C (TDP-C) shows a consistent predilection for the anterior temporal lobe (ATL). The relatively selective atrophy of ATL in TDP-C patients has highlighted the importance of this region for complex cognitive and behavioral functions. This review includes observations on 28 TDP-C patients, 18 with semantic primary progressive aphasia and 10 with other syndromes. Longitudinal imaging allowed the delineation of progression trajectories. At post-mortem examination, the pathognomonic feature of TDP-C consisted of long, thick neurites found predominantly in superficial cortical layers. These neurites may represent dystrophic apical dendrites of layer III and V pyramidal neurons that are known to play pivotal roles in complex cortical computations. Other types of frontotemporal lobar degeneration TDP, such as TDP-A and TDP-B, are not associated with long dystrophic neurites in the cerebral cortex, and do not show similar predilection patterns for ATL. Research is beginning to identify molecular, structural, and immunological differences between pathological TDP-43 in TDP-C versus TDP-A and B. Parallel investigations based on proteomics, somatic mutations, and genome-wide association studies are detecting molecular features that could conceivably mediate the selective vulnerability of ATL to TDP-C. Future work will focus on characterizing the distinctive features of the abnormal TDP-C neurites, the mechanisms of neurotoxicity, initial cellular targets within the ATL, trajectory of spread, and the nature of ATL-specific markers that modulate vulnerability to TDP-C. ANN NEUROL 2023;94:1-12.

Altered Anterior Insular Metabolic Connectivity in Asymptomatic MAPT P301L Carriers

BACKGROUND

The insula is the predominant brain region impaired in behavior variant frontotemporal dementia (bvFTD). However, structural and functional changes in the sub-insula in the asymptomatic stage of bvFTD are unknown.

OBJECTIVE

To describe structural and functional changes in insula subregions in asymptomatic carriers of the P301L mutation of the microtubule-associated protein tau (MAPT) gene and patients with bvFTD.

METHODS

Six asymptomatic MAPT P301L mutation carriers and 12 MAPT negative control subjects of the same pedigree were enrolled, along with 30 patients with a clinical diagnosis of bvFTD and 30 matched controls. All subjects underwent hybrid positron emission tomography/magnetic resonance imaging. Atlas-based parcellation using a fine-grained Brainnetome Atlas was conducted to assess gray matter (GM) volume, metabolism, and metabolic connectivity in the sub-insula (region of interest).

RESULTS

There was no significant GM atrophy or hypometabolism in insula subregions in asymptomatic MAPT P301L carriers, although decreased metabolic connectivity between vIa-middle temporal gyrus, vIa-temporal poles, dIa-middle temporal gyrus and dIa-temporal poles; and increased connectivity between vIa-orbitofrontal, vIa-dorsal lateral superior frontal gyrus, and dIa-orbitofrontal and dIa-dorsal lateral superior frontal gyrus were observed. Patients with bvFTD had significant atrophy and hypometabolism in all insula subregions and decreased metabolic connectivity in the whole brain, including vIa/dIa-middle temporal and vIa/dIa-temporal poles. The standardized uptake value ratios of vIa and dIa were negatively associated with behavioral disinhibition scale scores.

CONCLUSION

Metabolic connectivity is altered in vIa and dIa subregions of the sub-insula in MAPT P301L mutation carriers before the occurrence of atrophy, hypometabolism, and clinical symptoms.

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.

Neurodegenerative disease of the brain: a survey of interdisciplinary approaches

Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseases and this article reviews such approaches, with particular emphasis on tools and techniques drawn from physics, chemistry, artificial intelligence and psychology.

White-matter abnormalities in presymptomatic GRN and C9orf72 mutation carriers

A large proportion of familial frontotemporal dementia is caused by TAR DNA-binding protein 43 (transactive response DNA-binding protein 43 kDa) proteinopathies. Accordingly, carriers of autosomal dominant mutations in the genes associated with TAR DNA-binding protein 43 aggregation, such as Chromosome 9 open reading frame 72 (C9orf72) or progranulin (GRN), are at risk of later developing frontotemporal dementia. Brain imaging abnormalities that develop before dementia onset in mutation carriers may serve as proxies for the presymptomatic stages of familial frontotemporal dementia due to a genetic cause. Our study objective was to investigate brain MRI-based white-matter changes in predementia participants carrying mutations in C9orf72 or GRN genes. We analysed mutation carriers and their family member controls (noncarriers) from the University of British Columbia familial frontotemporal dementia study. First, a total of 42 participants (8 GRN carriers; 11 C9orf72 carriers; 23 noncarriers) had longitudinal T₁-weighted MRI over ∼2 years. White-matter signal hypointensities were segmented and volumes were calculated for each participant. General linear models were applied to compare the baseline burden and the annualized rate of accumulation of signal abnormalities among mutation carriers and noncarriers. Second, a total of 60 participants (9 GRN carriers; 17 C9orf72 carriers; 34 noncarriers) had cross-sectional diffusion tensor MRI available. For each participant, we calculated the average fractional anisotropy and mean, radial and axial diffusivity parameter values within the normal-appearing white-matter tissues. General linear models were applied to compare whether mutation carriers and noncarriers had different trends in diffusion tensor imaging parameter values as they neared the expected age of onset. Baseline volumes of white-matter signal abnormalities were not significantly different among mutation carriers and noncarriers. Longitudinally, GRN carriers had significantly higher annualized rates of accumulation (estimated mean: 15.87%/year) compared with C9orf72 carriers (3.69%/year) or noncarriers (2.64%/year). A significant relationship between diffusion tensor imaging parameter values and increasing expected age of onset was found in the periventricular normal-appearing white-matter region. Specifically, GRN carriers had a tendency of a faster increase of mean and radial diffusivity values and C9orf72 carriers had a tendency of a faster decline of fractional anisotropy values as they reached closer to the expected age of dementia onset. These findings suggest that white-matter changes may represent early markers of familial frontotemporal dementia due to genetic causes. However, GRN and C9orf72 mutation carriers may have different mechanisms leading to tissue abnormalities.

Longitudinal Brain Atrophy Rates in Presymptomatic Carriers of Genetic Frontotemporal Dementia

BACKGROUND AND OBJECTIVES

It is important to identify at what age brain atrophy rates in genetic frontotemporal dementia (FTD) start to accelerate and deviate from normal aging effects to find the optimal starting point for treatment. We investigated longitudinal brain atrophy rates in the presymptomatic stage of genetic FTD using normative brain volumetry software.

METHODS

Presymptomatic GRN, MAPT, and C9orf72 pathogenic variant carriers underwent longitudinal volumetric T1-weighted magnetic resonance imaging of the brain as part of a prospective cohort study. Images were automatically analyzed with Quantib® ND, which consisted of volume measurements (CSF and sum of gray and white matter) of lobes, cerebellum, and hippocampus. All volumes were compared with reference centile curves based on a large population-derived sample of nondemented individuals (n = 4,951). Mixed-effects models were fitted to analyze atrophy rates of the different gene groups as a function of age.

RESULTS

Thirty-four GRN, 8 MAPT, and 14 C9orf72 pathogenic variant carriers were included (mean age = 52.1, standard deviation = 7.2; 66% female). The mean follow-up duration of the study was 64 ± 33 months (median = 52; range 13-108). GRN pathogenic variant carriers showed a faster decline than the reference centile curves for all brain areas, though relative volumes remained between the 5th and 75th percentiles between the ages of 45 and 70 years. In MAPT pathogenic variant carriers, frontal lobe volume was already at the 5th percentile at age 45 years and showed a further decline between the ages 50 and 60 years. Temporal lobe volume started in the 50th percentile at age 45 years but showed fastest decline over time compared with other brain structures. Frontal, temporal, parietal, and cerebellar volume already started below the 5th percentile compared with the reference centile curves at age 45 years for C9orf72 pathogenic variant carriers, but there was minimal decline over time until the age of 60 years.

DISCUSSION

We provide evidence for longitudinal brain atrophy in the presymptomatic stage of genetic FTD. The affected brain areas and the age after which atrophy rates start to accelerate and diverge from normal aging slopes differed between gene groups. These results highlight the value of normative volumetry software for disease tracking and staging biomarkers in genetic FTD. These techniques could help in identifying the optimal time window for starting treatment and monitoring treatment response.

Neurodevelopmental effects of genetic frontotemporal dementia in young adult mutation carriers

While frontotemporal dementia (frontotemporal dementia) has been considered a neurodegenerative disease that starts in mid-life or later, it is now clearly established that cortical and subcortical volume loss is observed more than a decade prior to symptom onset and progresses with aging. To test the hypothesis that genetic mutations causing frontotemporal dementia have neurodevelopmental consequences, we have examined the youngest adults in the GENFI cohort of pre-symptomatic frontotemporal dementia mutation carriers who are between the ages of 19 and 30y. Structural brain differences and improved performance on some cognitive tests was found for MAPT and GRN mutation carriers relative to familial non-carriers, while smaller volumes were observed in C9orf72 repeat expansion carriers at a mean age of 26y. The detection of such early differences supports potential advantageous neurodevelopmental consequences of some frontotemporal dementia causing genetic mutations. These results have implications for design of therapeutic interventions for frontotemporal dementia. Future studies at younger ages are needed to identify specific early pathophysiologic or compensatory processes in the neurodevelopmental period.

Relationship between CSF tau biomarkers and structural brain MRI measures in frontotemporal lobar degeneration

BACKGROUND

Recently in the field neurodegenerative diseases increasing attention has been pointed to CSF biomarkers and their integration with neuroimaging (1). Frontotemporal lobar degeneration (FTLD) refers to a heterogeneous group of clinical syndromes with different underlying proteinopathies including tau pathology. CSF biomarkers have been proposed as diagnostic and prognostic factors. Aim of our study was to evaluate the relationship between CSF tau biomarkers and structural MRI brain measures in FTLD.

METHODS

We included early FTLD patient. All included patients underwent lumbar puncture to evaluate amyloid, total-tau (t-tau), phospho-tau 181 (p-tau); p-tau/t-tau ratio was also calculated; brain MRI was performed to estimate whole brain volume, volume of principal deep grey matter structures and regional cortical thickness.

RESULTS

Demographic characteristics of the 28 included patients were as follows: female/male: 9/19; mean ± SD age: 68.1 ± 7.8 years. The p-tau/t-tau ratio was significantly correlated with whole brain volume (r = 0.69; p: 0.001), left putamen volume (r = 0.55 p: 0.009), left pallidum volume (r = 0.41; p: 0.01), right accumbens area (r = 0.47; p: 0.02). P-tau/t tau ratio showed also a significant correlation with cortical thickness of left temporal lobe (r = 0.74; p: 0.001) and right lateral orbital frontal cortex (r = 0.45; p: 0.03). Linear regression showed a significant relationship between p-tau/t-tau ratio and left temporal pole (p = 0.01; r²: 0.60) and brain volume (p:0.002; r²: 0.56) after controlling for age and gender.

CONCLUSIONS

Our data suggest that CSF biomarkers, especially p-tau/t-tau ratio, could play a role as prognostic factor in FTLD. Further longitudinal investigations are needed to confirm these findings.

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.

Sensitivity of the Social Behavior Observer Checklist to Early Symptoms of Patients With Frontotemporal Dementia

BACKGROUND AND OBJECTIVES

Changes in social behavior are common symptoms of frontotemporal lobar degeneration (FTLD) and Alzheimer disease syndromes. For early identification of individual patients and differential diagnosis, sensitive clinical measures are required that are able to assess patterns of behaviors and detect syndromic differences in both asymptomatic and symptomatic stages. We investigated whether the examiner-based Social Behavior Observer Checklist (SBOCL) is sensitive to early behavior changes and reflects disease severity within and between neurodegenerative syndromes.

METHODS

Asymptomatic individuals and patients with neurodegenerative disease were selected from the multisite ALLFTD cohort study. In a sample of participants with at least 1 time point of SBOCL data, we investigated whether the Disorganized, Reactive, and Insensitive subscales of the SBOCL change as a function of disease stage within and between these syndromes. In a longitudinal subsample with both SBOCL and neuroimaging data, we examined whether change over time on each subscale corresponds to progressive gray matter atrophy.

RESULTS

A total of 1,082 FTLD pathogenic variant carriers and noncarriers were enrolled (282 asymptomatic, 341 behavioral variant frontotemporal dementia, 114 semantic and 95 nonfluent variant primary progressive aphasia, 137 progressive supranuclear palsy, and 113 Alzheimer disease syndrome). The Disorganized score increased between asymptomatic to very mild (p = 0.016, estimate = -1.10, 95% CI = -1.99 to -0.22), very mild to mild (p = 0.013, estimate = -1.17, 95% CI = -2.08 to -0.26), and mild to moderate/severe (p < 0.001, estimate = -2.00, 95% CI = -2.55 to -1.45) disease stages in behavioral variant frontotemporal dementia regardless of pathogenic variant status. Asymptomatic GRN pathogenic gene variant carriers showed more reactive behaviors (preoccupation with time: p = 0.001, estimate = 1.11, 95% CI = 1.06 to 1.16; self-consciousness: p = 0.003, estimate = 1.77, 95% CI = 1.52 to 2.01) than asymptomatic noncarriers (estimate = 1.01, 95% CI = 0.98 to 1.03; estimate = 1.31, 95% CI = 1.20 to 1.41). The Insensitive score increased to a clinically abnormal level in advanced stages of behavioral variant frontotemporal dementia (p = 0.003, estimate = -0.73, 95% CI = -1.18 to -0.29). Higher scores on each subscale corresponded with higher caregiver burden (p < 0.001). Greater change over time corresponded to greater fronto-subcortical atrophy in the semantic-appraisal and fronto-parietal intrinsically connected networks.

DISCUSSION

The SBOCL is sensitive to early symptoms and reflects disease severity, with some evidence for progression across asymptomatic and symptomatic stages of FTLD syndromes; thus, it may hold promise for early measurement and monitoring of behavioral symptoms in clinical practice and treatment trials.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the SBOCL is sensitive to early behavioral changes in FTLD pathogenic variants and early symptomatic individuals in a highly educated patient cohort.

Longitudinal Cognitive Changes in Genetic Frontotemporal Dementia Within the GENFI Cohort

BACKGROUND AND OBJECTIVES

Disease-modifying therapeutic trials for genetic frontotemporal dementia (FTD) are underway, but sensitive cognitive outcome measures are lacking. The aim of this study was to identify such cognitive tests in early stage FTD by investigating cognitive decline in a large cohort of genetic FTD pathogenic variant carriers and by investigating whether gene-specific differences are moderated by disease stage (asymptomatic, prodromal, and symptomatic).

METHODS

C9orf72, GRN, and MAPT pathogenic variant carriers as well as controls underwent a yearly neuropsychological assessment covering 8 cognitive domains as part of the Genetic FTD Initiative, a prospective multicenter cohort study. Pathogenic variant carriers were stratified according to disease stage using the global Clinical Dementia Rating (CDR) plus National Alzheimer's Coordinating Center (NACC) FTLD score (0, 0.5, or ≥1). Linear mixed-effects models were used to investigate differences between genetic groups and disease stages as well as the 3-way interaction between time, genetic group, and disease stage.

RESULTS

A total of 207 C9orf72, 206 GRN, and 86 MAPT pathogenic variant carriers and 255 controls were included. C9orf72 pathogenic variant carriers performed lower on attention, executive function, and verbal fluency from CDR plus NACC FTLD 0 onwards, with relatively minimal decline over time regardless of the CDR plus NACC FTLD score (i.e., disease progression). The cognitive profile in MAPT pathogenic variant carriers was characterized by lower memory performance at CDR plus NACC FTLD 0.5, with decline over time in language from the CDR plus NACC FTLD 0.5 stage onwards, and executive dysfunction rapidly developing at CDR plus NACC FTLD ≥1. GRN pathogenic variant carriers declined on verbal fluency and visuoconstruction in the CDR plus NACC FTLD 0.5 stage, with progressive decline in other cognitive domains starting at CDR plus NACC FTLD ≥1.

DISCUSSION

We confirmed cognitive decline in the asymptomatic and prodromal stage of genetic FTD. Specifically, tests for attention, executive function, language, and memory showed clear differences between genetic groups and controls at baseline, but the speed of change over time differed depending on genetic group and disease stage. This confirms the value of neuropsychological assessment in tracking clinical onset and progression and could inform clinical trials in selecting sensitive end points for measuring treatment effects as well as characterizing the best time window for starting treatment.

A Reproducible Deep-Learning-Based Computer-Aided Diagnosis Tool for Frontotemporal Dementia Using MONAI and Clinica Frameworks

Despite Artificial Intelligence (AI) being a leading technology in biomedical research, real-life implementation of AI-based Computer-Aided Diagnosis (CAD) tools into the clinical setting is still remote due to unstandardized practices during development. However, few or no attempts have been made to propose a reproducible CAD development workflow for 3D MRI data. In this paper, we present the development of an easily reproducible and reliable CAD tool using the Clinica and MONAI frameworks that were developed to introduce standardized practices in medical imaging. A Deep Learning (DL) algorithm was trained to detect frontotemporal dementia (FTD) on data from the NIFD database to ensure reproducibility. The DL model yielded 0.80 accuracy (95% confidence intervals: 0.64, 0.91), 1 sensitivity, 0.6 specificity, 0.83 F1-score, and 0.86 AUC, achieving a comparable performance with other FTD classification approaches. Explainable AI methods were applied to understand AI behavior and to identify regions of the images where the DL model misbehaves. Attention maps highlighted that its decision was driven by hallmarking brain areas for FTD and helped us to understand how to improve FTD detection. The proposed standardized methodology could be useful for benchmark comparison in FTD classification. AI-based CAD tools should be developed with the goal of standardizing pipelines, as varying pre-processing and training methods, along with the absence of model behavior explanations, negatively impact regulators' attitudes towards CAD. The adoption of common best practices for neuroimaging data analysis is a step toward fast evaluation of efficacy and safety of CAD and may accelerate the adoption of AI products in the healthcare system.

A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions.

Brainstem atrophy is linked to extrapyramidal symptoms in frontotemporal dementia

Extrapyramidal (EP) symptoms are a known feature in a subpopulation of patients with behavioral variant frontotemporal dementia (bvFTD). Concomitant EP symptoms with FTD-like neuropsychiatric symptoms are also core features in progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). This complicates the early diagnosis of these disorders. Our retrospective register study aimed to discover imaging (MRI and FDG-PET) biomarkers to differentiate PSP, CBD, and bvFTD patients with extrapyramidal symptoms (EP +) from bvFTD patients without EP symptoms (EP-). The records of 2751 patients were screened for the diagnoses and presence of EP symptoms. A total of 222 patients were submitted to imaging analysis and applicable imaging data were recovered from 139 patients. Neuroimaging data were analyzed using Freesurfer software. In the whole cohort, EP + patients showed lower volumes of gray matter compared to EP- patients in the putamen (p = 0.002), bilateral globus pallidum (p = 0.002, p = 0.042), ventral diencephalon (p = 0.002) and brain stem (p < 0.001). In the bvFTD subgroup, there was volumetric difference between EP + and EP− patients in the brain stem. FDG-PET scans in the bvFTD patient subgroup showed that EP + patients had comparative hypometabolism of the superior cerebellar peduncle (SCP) and the frontal lobes. We discovered that EP symptoms are linked to brainstem atrophy in bvFTD patients and the whole cohort. Also, evident hypometabolism in the SCP of bvFTD EP + patients was detected as compared to bvFTD EP− patients. This could indicate that the EP symptoms in these diseases have a more caudal origin in the brainstem than in Parkinson’s disease.

The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation

INTRODUCTION

While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterised based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorise individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories.

AREAS COVERED

This article reviews (1) the neuroimaging studies that propose single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) potential practical implications and (3) the limitations of current single-subject data interpretation models.

EXPERT OPINION

Classification studies in FTLD have demonstrated the feasibility of categorising individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.

Data-driven staging of genetic frontotemporal dementia using multi-modal MRI

Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high‐dimensional large‐scale population datasets to obtain individual scores of disease stage. We used cross‐sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting‐state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI‐obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre‐dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data‐driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.

White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation

BACKGROUND

Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets.

METHODS

To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data.

RESULTS

The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics.

CONCLUSIONS

Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.

Magnetic Resonance Imaging in Tauopathy Animal Models

The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer's disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.

Cognitive composites for genetic frontotemporal dementia: GENFI-Cog

Background

Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design.

Methods

A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72, 41 GRN, and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be).

Results

The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72, GRN, and MAPT). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period.

Discussion

We created gene-specific cognitive composite scores for C9orf72, GRN, and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-00958-0.

Sensitivity of arterial Spin labeling for characterization of longitudinal perfusion changes in Frontotemporal dementia and related disorders

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This study demonstrates the value of ASL for longitudinal monitoring of perfusion in FTD patients.

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Good agreement was found in repeat measures of CBF in patients and controls.

•

Transit times were not a significant source of error for the selected post labeling delay (2 s).

Background

Advances in the understanding of the pathophysiology of frontotemporal dementia (FTD) and related disorders, along with the development of novel candidate disease modifying treatments, have stimulated the need for tools to assess the efficacy of new therapies. While perfusion imaging by arterial spin labeling (ASL) is an attractive approach for longitudinal imaging biomarkers of neurodegeneration, sources of variability between sessions including arterial transit times (ATT) and fluctuations in resting perfusion can reduce its sensitivity. Establishing the magnitude of perfusion changes that can be reliably detected is necessary to delineate longitudinal perfusion changes related to disease processes from the effects of these sources of error.

Purpose

To assess the feasibility of ASL for longitudinal monitoring of patients with FTD by quantifying between-session variability of perfusion on a voxel-by-voxel basis.

Methods and materials

ASL data were collected in 13 healthy controls and 8 patients with FTD or progressive supra-nuclear palsy. Variability in cerebral blood flow (CBF) by single delay pseudo-continuous ASL (SD-pCASL) acquired one month apart were quantified by the coefficient of variation (CV) and intraclass correlation coefficient (ICC). Additionally, CBF by SD-pCASL and ATT by low-resolution multiple inversion time ASL (LowRes-pCASL) were compared to Hadamard encoded sequences which are able to simultaneously measure CBF and ATT with improved time-efficiency.

Results

Agreement of grey-matter perfusion between sessions was found for both patients and controls (CV = 10.8% and 8.3% respectively) with good reliability for both groups (ICC > 0.6). Intensity normalization to remove day-to-day fluctuations in resting perfusion reduced the CV by 28%. Less than 5% of voxels had ATTs above the chosen post labelling delay (2 s), indicating that the ATT was not a significant source of error. Hadamard-encoded perfusion imaging yielded systematically higher CBF compared to SD-pCASL, but produced similar transit-time measurements. Power analysis revealed that SD-pCASL has the sensitivity to detect longitudinal changes as low as 10% with as few as 10 patient participants.

Conclusion

With the appropriate labeling parameters, SD-pCASL is a promising approach for assessing longitudinal changes in CBF associated with FTD.

[18F]Flortaucipir PET Across Various MAPT Mutations in Presymptomatic and Symptomatic Carriers

OBJECTIVE

To assess the [18F]flortaucipir binding distribution across MAPT mutations in presymptomatic and symptomatic carriers.

METHODS

We compared regional [18F]flortaucipir binding potential (BPND) derived from a 130-minute dynamic [18F]flortaucipir PET scan in 9 (pre)symptomatic MAPT mutation carriers (4 with P301L [1 symptomatic], 2 with R406W [1 symptomatic], 1 presymptomatic L315R, 1 presymptomatic S320F, and 1 symptomatic G272V carrier) with 30 cognitively normal controls and 52 patients with Alzheimer disease.

RESULTS

[18F]Flortaucipir BPND images showed overall highest binding in the symptomatic carriers. This was most pronounced in the symptomatic R406W carrier in whom tau binding exceeded the normal control range in the anterior cingulate cortex, insula, amygdala, temporal, parietal, and frontal lobe. Elevated medial temporal lobe BPND was observed in a presymptomatic R406W carrier. The single symptomatic carrier and 1 of the 3 presymptomatic P301L carriers showed elevated [18F]flortaucipir BPND in the insula, parietal, and frontal lobe compared to controls. The symptomatic G272V carrier exhibited a widespread elevated cortical BPND, with at neuropathologic examination a combination of 3R pathology and encephalitis. The L315R presymptomatic mutation carrier showed higher frontal BPND compared to controls. The BPND values of the S320F presymptomatic mutation carrier fell within the range of controls.

CONCLUSION

Presymptomatic MAPT mutation carriers already showed subtle elevated tau binding, whereas symptomatic MAPT mutation carriers showed a more marked increase in [18F]flortaucipir BPND. Tau deposition was most pronounced in R406W MAPT (pre)symptomatic mutation carriers, which is associated with both 3R and 4R tau accumulation. Thus, [18F]flortaucipir may serve as an early biomarker for MAPT mutation carriers in mutations that cause 3R/4R tauopathies.

Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions

Neurodegenerative diseases (NDDs) are characterized by progressive neuronal loss, leading to dementia and movement disorders. NDDs broadly include Alzheimer's disease, frontotemporal lobar degeneration, parkinsonian syndromes, and prion diseases. There is an ever-increasing prevalence of mild cognitive impairment and dementia, with an accompanying immense economic impact, prompting efforts aimed at early identification and effective interventions. Neuroimaging is an essential tool for the early diagnosis of NDDs in both clinical and research settings. Structural, functional, and metabolic imaging modalities, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are widely available. They show encouraging results for diagnosis, monitoring, and treatment response evaluation. The current review focuses on the complementary role of various imaging modalities in relation to NDDs, the qualitative and quantitative utility of newer MRI techniques, novel radiopharmaceuticals, and integrated PET/MRI in the setting of NDDs.

MRI-guided histology of TDP-43 knock-in mice implicates parvalbumin interneuron loss, impaired neurogenesis and aberrant neurodevelopment in amyotrophic lateral sclerosis-frontotemporal dementia

Amyotrophic lateral sclerosis and frontotemporal dementia are overlapping diseases in which MRI reveals brain structural changes in advance of symptom onset. Recapitulating these changes in preclinical models would help to improve our understanding of the molecular causes underlying regionally selective brain atrophy in early disease. We therefore investigated the translational potential of the TDP-43Q331K knock-in mouse model of amyotrophic lateral sclerosis-frontotemporal dementia using MRI. We performed in vivo MRI of TDP-43Q331K knock-in mice. Regions of significant volume change were chosen for post-mortem brain tissue analyses. Ex vivo computed tomography was performed to investigate skull shape. Parvalbumin neuron density was quantified in post-mortem amyotrophic lateral sclerosis frontal cortex. Adult mutants demonstrated parenchymal volume reductions affecting the frontal lobe and entorhinal cortex in a manner reminiscent of amyotrophic lateral sclerosis-frontotemporal dementia. Subcortical, cerebellar and brain stem regions were also affected in line with observations in pre-symptomatic carriers of mutations in C9orf72, the commonest genetic cause of both amyotrophic lateral sclerosis and frontotemporal dementia. Volume loss was also observed in the dentate gyrus of the hippocampus, along with ventricular enlargement. Immunohistochemistry revealed reduced parvalbumin interneurons as a potential cellular correlate of MRI changes in mutant mice. By contrast, microglia was in a disease activated state even in the absence of brain volume loss. A reduction in immature neurons was found in the dentate gyrus, indicative of impaired adult neurogenesis, while a paucity of parvalbumin interneurons in P14 mutant mice suggests that TDP-43Q331K disrupts neurodevelopment. Computerized tomography imaging showed altered skull morphology in mutants, further suggesting a role for TDP-43Q331K in development. Finally, analysis of human post-mortem brains confirmed a paucity of parvalbumin interneurons in the prefrontal cortex in sporadic amyotrophic lateral sclerosis and amyotrophic lateral sclerosis linked to C9orf72 mutations. Regional brain MRI changes seen in human amyotrophic lateral sclerosis-frontotemporal dementia are recapitulated in TDP-43Q331K knock-in mice. By marrying in vivo imaging with targeted histology, we can unravel cellular and molecular processes underlying selective brain vulnerability in human disease. As well as helping to understand the earliest causes of disease, our MRI and histological markers will be valuable in assessing the efficacy of putative therapeutics in TDP-43Q331K knock-in mice.

Impairment of episodic memory in genetic frontotemporal dementia: A GENFI study

INTRODUCTION

We aimed to assess episodic memory in genetic frontotemporal dementia (FTD) with the Free and Cued Selective Reminding Test (FCSRT).

METHODS

The FCSRT was administered in 417 presymptomatic and symptomatic mutation carriers (181 chromosome 9 open reading frame 72 [C9orf72], 163 progranulin [GRN], and 73 microtubule-associated protein tau [MAPT]) and 290 controls. Group differences and correlations with other neuropsychological tests were examined. We performed voxel-based morphometry to investigate the underlying neural substrates of the FCSRT.

RESULTS

All symptomatic mutation carrier groups and presymptomatic MAPT mutation carriers performed significantly worse on all FCSRT scores compared to controls. In the presymptomatic C9orf72 group, deficits were found on all scores except for the delayed total recall task, while no deficits were found in presymptomatic GRN mutation carriers. Performance on the FCSRT correlated with executive function, particularly in C9orf72 mutation carriers, but also with memory and naming tasks in the MAPT group. FCSRT performance also correlated with gray matter volumes of frontal, temporal, and subcortical regions in C9orf72 and GRN, but mainly temporal areas in MAPT mutation carriers.

DISCUSSION

The FCSRT detects presymptomatic deficits in C9orf72- and MAPT-associated FTD and provides important insight into the underlying cause of memory impairment in different forms of FTD.

Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia

OBJECTIVE

Progranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.

METHODS

We included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.

RESULTS

Language functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.

CONCLUSION

Degeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.

Clinical and Neuroimaging Aspects of Familial Frontotemporal Lobar Degeneration Associated with MAPT and GRN Mutations

Numerous kindreds with familial frontotemporal lobar degeneration have been linked to mutations in microtubule-associated protein tau (MAPT) or progranulin (GRN) genes. While there are many similarities in the clinical manifestations and associated neuroimaging findings, there are also distinct differences. In this review, we compare and contrast the demographic/inheritance characteristics, histopathology, pathophysiology, clinical aspects, and key neuroimaging findings between those with MAPT and GRN mutations.

Classification using fractional anisotropy predicts conversion in genetic frontotemporal dementia, a proof of concept

Frontotemporal dementia is a highly heritable and devastating neurodegenerative disease. About 10–20% of all frontotemporal dementia is caused by known pathogenic mutations, but a reliable tool to predict clinical conversion in mutation carriers is lacking. In this retrospective proof-of-concept case-control study, we investigate whether MRI-based and cognition-based classifiers can predict which mutation carriers from genetic frontotemporal dementia families will develop symptoms (‘convert’) within 4 years. From genetic frontotemporal dementia families, we included 42 presymptomatic frontotemporal dementia mutation carriers. We acquired anatomical, diffusion-weighted imaging, and resting-state functional MRI, as well as neuropsychological data. After 4 years, seven mutation carriers had converted to frontotemporal dementia (‘converters’), while 35 had not (‘non-converters’). We trained regularized logistic regression models on baseline MRI and cognitive data to predict conversion to frontotemporal dementia within 4 years, and quantified prediction performance using area under the receiver operating characteristic curves. The prediction model based on fractional anisotropy, with highest contribution of the forceps minor, predicted conversion to frontotemporal dementia beyond chance level (0.81 area under the curve, family-wise error corrected P = 0.025 versus chance level). Other MRI-based and cognitive features did not outperform chance level. Even in a small sample, fractional anisotropy predicted conversion in presymptomatic frontotemporal dementia mutation carriers beyond chance level. After validation in larger data sets, conversion prediction in genetic frontotemporal dementia may facilitate early recruitment into clinical trials.

Microstructural and Cerebral Blood Flow Abnormalities in Subjective Cognitive Decline Plus: Diffusional Kurtosis Imaging and Three-Dimensional Arterial Spin Labeling Study

Objective: To explore microstructural and cerebral blood flow (CBF) abnormalities in individuals with subjective cognitive decline plus (SCD plus) using diffusional kurtosis imaging (DKI) and three-dimensional (3D) arterial spin labeling (ASL). Methods: Twenty-seven patients with SCD plus, 31 patients with amnestic mild cognitive impairment (aMCI), and 33 elderly controls (ECs) were recruited and underwent DKI and 3D ASL using a GE 3.0-T MRI. Mean kurtosis (MK), fractional anisotropy (FA), mean diffusivity (MD), and CBF values were acquired from 24 regions of interest (ROIs) in the brain, including the bilateral hippocampal (Hip) subregions (head, body, and tail), posterior cingulate cortex (PCC), precuneus, dorsal thalamus subregions (anterior nucleus, ventrolateral nucleus, and medial nucleus), lenticular nucleus, caput nuclei caudati, white matter (WM) of the frontal lobe, and WM of the occipital lobe. Pearson's correlation analysis was performed to assess the relationships among the DKI-derived parameters, CBF values, and key neuropsychological tests for SCD plus. Results: Compared with ECs, participants with SCD plus showed a significant decline in MK and CBF values, mainly in the Hip head and PCC, and participants with aMCI exhibited more significant abnormalities in the MK and CBF values than individuals with ECs and SCD plus in multiple regions. Combined MK values showed better discrimination between patients with SCD plus and ECs than that obtained using CBF levels, with areas under the receiver operating characteristic (ROC) curve (AUC) of 0.874 and 0.837, respectively. Similarly, the AUC in discriminating SCD plus from aMCI patients obtained using combined MK values was 0.823, which was also higher than the combined AUC of 0.779 obtained using CBF values. Moreover, MK levels in the left Hip (h) and left PCC positively correlated with the auditory verbal learning test-delayed recall (AVLT-DR) score in participants with SCD plus. By contrast, only the CBF value in the left Hip head positively correlated with the AVLT-DR score. Conclusions: Our results provide new evidence of microstructural and CBF changes in patients with SCD plus. MK may be used as an early potential neuroimaging biomarker and may be a more sensitive DKI parameter than CBF at the very early stage of Alzheimer's disease (AD).

Quantitative endophenotypes as an alternative approach to understanding genetic risk in neurodegenerative diseases

Endophenotypes, as measurable intermediate features of human diseases, reflect underlying molecular mechanisms. The use of quantitative endophenotypes in genetic studies has improved our understanding of pathophysiological changes associated with diseases. The main advantage of the quantitative endophenotypes approach to study human diseases over a classic case-control study design is the inferred biological context that can enable the development of effective disease-modifying treatments. Here, we summarize recent progress on biomarkers for neurodegenerative diseases, including cerebrospinal fluid and blood-based, neuroimaging, neuropathological, and clinical studies. This review focuses on how endophenotypic studies have successfully linked genetic modifiers to disease risk, disease onset, or progression rate and provided biological context to genes identified in genome-wide association studies. Finally, we review critical methodological considerations for implementing this approach and future directions.

Progression of Behavioral Disturbances and Neuropsychiatric Symptoms in Patients With Genetic Frontotemporal Dementia

IMPORTANCE

Behavioral disturbances are core features of frontotemporal dementia (FTD); however, symptom progression across the course of disease is not well characterized in genetic FTD.

OBJECTIVE

To investigate behavioral symptom frequency and severity and their evolution and progression in different forms of genetic FTD.

DESIGN, SETTING, AND PARTICIPANTS

This longitudinal cohort study, the international Genetic FTD Initiative (GENFI), was conducted from January 30, 2012, to May 31, 2019, at 23 multicenter specialist tertiary FTD research clinics in the United Kingdom, the Netherlands, Belgium, France, Spain, Portugal, Italy, Germany, Sweden, Finland, and Canada. Participants included a consecutive sample of 232 symptomatic FTD gene variation carriers comprising 115 with variations in C9orf72, 78 in GRN, and 39 in MAPT. A total of 101 carriers had at least 1 follow-up evaluation (for a total of 400 assessments). Gene variations were included only if considered pathogenetic.

MAIN OUTCOMES AND MEASURES

Behavioral and neuropsychiatric symptoms were assessed across disease duration and evaluated from symptom onset. Hierarchical generalized linear mixed models were used to model behavioral and neuropsychiatric measures as a function of disease duration and variation.

RESULTS

Of 232 patients with FTD, 115 (49.6%) had a C9orf72 expansion (median [interquartile range (IQR)] age at evaluation, 64.3 [57.5-69.7] years; 72 men [62.6%]; 115 White patients [100%]), 78 (33.6%) had a GRN variant (median [IQR] age, 63.4 [58.3-68.8] years; 40 women [51.3%]; 77 White patients [98.7%]), and 39 (16.8%) had a MAPT variant (median [IQR] age, 56.3 [49.9-62.4] years; 25 men [64.1%]; 37 White patients [94.9%]). All core behavioral symptoms, including disinhibition, apathy, loss of empathy, perseverative behavior, and hyperorality, were highly expressed in all gene variant carriers (>50% patients), with apathy being one of the most common and severe symptoms throughout the disease course (51.7%-100% of patients). Patients with MAPT variants showed the highest frequency and severity of most behavioral symptoms, particularly disinhibition (79.3%-100% of patients) and compulsive behavior (64.3%-100% of patients), compared with C9orf72 carriers (51.7%-95.8% of patients with disinhibition and 34.5%-75.0% with compulsive behavior) and GRN carriers (38.2%-100% with disinhibition and 20.6%-100% with compulsive behavior). Alongside behavioral symptoms, neuropsychiatric symptoms were very frequently reported in patients with genetic FTD: anxiety and depression were most common in GRN carriers (23.8%-100% of patients) and MAPT carriers (26.1%-77.8% of patients); hallucinations, particularly auditory and visual, were most common in C9orf72 carriers (10.3%-54.5% of patients). Most behavioral and neuropsychiatric symptoms increased in the early-intermediate phases and plateaued in the late stages of disease, except for depression, which steadily declined in C9orf72 carriers, and depression and anxiety, which surged only in the late stages in GRN carriers.

CONCLUSIONS AND RELEVANCE

This cohort study suggests that behavioral and neuropsychiatric disturbances differ between the common FTD gene variants and have different trajectories throughout the course of disease. These findings have crucial implications for counseling patients and caregivers and for the design of disease-modifying treatment trials in genetic FTD.

Emotion recognition of morphed facial expressions in presymptomatic and symptomatic frontotemporal dementia, and Alzheimer's dementia

BACKGROUND

The emotion recognition task (ERT) was developed to overcome shortcomings of static emotion recognition paradigms, by identifying more subtle deficits in emotion recognition across different intensity levels. In this study, we used the ERT to investigate emotion recognition deficits across the frontotemporal (FTD) and Alzheimer's Dementia (AD) spectrum.

METHODS

With the ERT, we assessed the recognition of facial emotional expressions (anger-disgust-fear-happiness-sadness-surprise) across four intensities (40-60-80-100%) in patients with behavioural variant FTD (bvFTD; n = 32), and AD (n = 32), presymptomatic FTD mutation carriers (n = 47) and controls (n = 49). We examined group differences using multilevel linear regression with age, sex and education level as covariates, and performed post hoc analyses on presymptomatic (MAPT, GRN and C9orf72) mutation carriers. Classification abilities were investigated by means of logistic regression.

RESULTS

Lowest ERT total scores were found in patients with bvFTD and AD, whereas equal highest performance was found in presymptomatic mutation carriers and controls. For all emotions, significantly lower subscores were found in patients with bvFTD than in presymptomatic mutation carriers and in controls (highest p value = 0.025). Patients with bvFTD performed lower than patients with AD on anger (p = 0.005) and a trend towards significance was found for a lower performance on happiness (p = 0.065). Task performance increased with higher emotional intensity, and classification was better at the lowest than at the highest intensity. C9orf72 mutation carriers performed worse on recognizing anger at the lowest intensity than GRN mutation carriers (p = 0.047) and controls (p = 0.038). The ERT differentiated between patients with bvFTD and controls, and between patients with AD and controls (both p < 0.001).

DISCUSSION

Our results demonstrate emotion recognition deficits in both bvFTD and AD, and suggest the presence of subtle emotion recognition changes in presymptomatic C9orf72-FTD. This highlights the importance of incorporating emotion recognition paradigms into standard neuropsychological assessment for early differential diagnosis, and as clinical endpoints in upcoming therapeutic trials.

Differential early subcortical involvement in genetic FTD within the GENFI cohort

BACKGROUND

Studies have previously shown evidence for presymptomatic cortical atrophy in genetic FTD. Whilst initial investigations have also identified early deep grey matter volume loss, little is known about the extent of subcortical involvement, particularly within subregions, and how this differs between genetic groups.

METHODS

480 mutation carriers from the Genetic FTD Initiative (GENFI) were included (198 GRN, 202 C9orf72, 80 MAPT), together with 298 non-carrier cognitively normal controls. Cortical and subcortical volumes of interest were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans. Mutation carriers were divided into three disease stages based on their global CDR® plus NACC FTLD score: asymptomatic (0), possibly or mildly symptomatic (0.5) and fully symptomatic (1 or more).

RESULTS

In all three groups, subcortical involvement was seen at the CDR 0.5 stage prior to phenoconversion, whereas in the C9orf72 and MAPT mutation carriers there was also involvement at the CDR 0 stage. In the C9orf72 expansion carriers the earliest volume changes were in thalamic subnuclei (particularly pulvinar and lateral geniculate, 9-10%) cerebellum (lobules VIIa-Crus II and VIIIb, 2-3%), hippocampus (particularly presubiculum and CA1, 2-3%), amygdala (all subregions, 2-6%) and hypothalamus (superior tuberal region, 1%). In MAPT mutation carriers changes were seen at CDR 0 in the hippocampus (subiculum, presubiculum and tail, 3-4%) and amygdala (accessory basal and superficial nuclei, 2-4%). GRN mutation carriers showed subcortical differences at CDR 0.5 in the presubiculum of the hippocampus (8%).

CONCLUSIONS

C9orf72 expansion carriers show the earliest and most widespread changes including the thalamus, basal ganglia and medial temporal lobe. By investigating individual subregions, changes can also be seen at CDR 0 in MAPT mutation carriers within the limbic system. Our results suggest that subcortical brain volumes may be used as markers of neurodegeneration even prior to the onset of prodromal symptoms.

Brain volumetric deficits in MAPT mutation carriers: a multisite study

OBJECTIVE

MAPT mutations typically cause behavioral variant frontotemporal dementia with or without parkinsonism. Previous studies have shown that symptomatic MAPT mutation carriers have frontotemporal atrophy, yet studies have shown mixed results as to whether presymptomatic carriers have low gray matter volumes. To elucidate whether presymptomatic carriers have lower structural brain volumes within regions atrophied during the symptomatic phase, we studied a large cohort of MAPT mutation carriers using a voxelwise approach.

METHODS

We studied 22 symptomatic carriers (age 54.7 ± 9.1, 13 female) and 43 presymptomatic carriers (age 39.2 ± 10.4, 21 female). Symptomatic carriers' clinical syndromes included: behavioral variant frontotemporal dementia (18), an amnestic dementia syndrome (2), Parkinson's disease (1), and mild cognitive impairment (1). We performed voxel-based morphometry on T1 images and assessed brain volumetrics by clinical subgroup, age, and mutation subtype.

RESULTS

Symptomatic carriers showed gray matter atrophy in bilateral frontotemporal cortex, insula, and striatum, and white matter atrophy in bilateral corpus callosum and uncinate fasciculus. Approximately 20% of presymptomatic carriers had low gray matter volumes in bilateral hippocampus, amygdala, and lateral temporal cortex. Within these regions, low gray matter volumes emerged in a subset of presymptomatic carriers as early as their thirties. Low white matter volumes arose infrequently among presymptomatic carriers.

INTERPRETATION

A subset of presymptomatic MAPT mutation carriers showed low volumes in mesial temporal lobe, the region ubiquitously atrophied in all symptomatic carriers. With each decade of age, an increasing percentage of presymptomatic carriers showed low mesial temporal volume, suggestive of early neurodegeneration.

Apathy in presymptomatic genetic frontotemporal dementia predicts cognitive decline and is driven by structural brain changes

Introduction

Apathy adversely affects prognosis and survival of patients with frontotemporal dementia (FTD). We test whether apathy develops in presymptomatic genetic FTD, and is associated with cognitive decline and brain atrophy.

Methods

Presymptomatic carriers of MAPT, GRN or C9orf72 mutations (N = 304), and relatives without mutations (N = 296) underwent clinical assessments and MRI at baseline, and annually for 2 years. Longitudinal changes in apathy, cognition, gray matter volumes, and their relationships were analyzed with latent growth curve modeling.

Results

Apathy severity increased over time in presymptomatic carriers, but not in non‐carriers. In presymptomatic carriers, baseline apathy predicted cognitive decline over two years, but not vice versa. Apathy progression was associated with baseline low gray matter volume in frontal and cingulate regions.

Discussion

Apathy is an early marker of FTD‐related changes and predicts a subsequent subclinical deterioration of cognition before dementia onset. Apathy may be a modifiable factor in those at risk of FTD.

CSF and Blood Biomarkers in Neuroinflammatory and Neurodegenerative Diseases: Implications for Treatment

Neuroinflammatory and neurodegenerative diseases are characterized by the interplay of a number of molecular pathways that can be assessed through biofluids, especially cerebrospinal fluid and blood. Accordingly, the definition and classification of these disorders will move from clinical and pathological to biological criteria. The consequences of this biomarker-based diagnostic and prognostic approach are highly relevant to the field of drug development. Indeed, in view of the availability of disease-modifying drugs, fluid biomarkers offer a unique opportunity for improving the quality and applicability of results from clinical trials. Herein, we discuss the benefits of using fluid biomarkers for patient stratification, target engagement, and outcome assessment, as well as the most recent developments in neuroinflammatory and neurodegenerative diseases.

Differential Diagnosis of Frontotemporal Dementia, Alzheimer's Disease, and Normal Aging Using a Multi-Scale Multi-Type Feature Generative Adversarial Deep Neural Network on Structural Magnetic Resonance Images

Methods: Alzheimer's disease and Frontotemporal dementia are the first and third most common forms of dementia. Due to their similar clinical symptoms, they are easily misdiagnosed as each other even with sophisticated clinical guidelines. For disease-specific intervention and treatment, it is essential to develop a computer-aided system to improve the accuracy of their differential diagnosis. Recent advances in deep learning have delivered some of the best performance for medical image recognition tasks. However, its application to the differential diagnosis of AD and FTD pathology has not been explored. Approach: In this study, we proposed a novel deep learning based framework to distinguish between brain images of normal aging individuals and subjects with AD and FTD. Specifically, we combined the multi-scale and multi-type MRI-base image features with Generative Adversarial Network data augmentation technique to improve the differential diagnosis accuracy. Results: Each of the multi-scale, multitype, and data augmentation methods improved the ability for differential diagnosis for both AD and FTD. A 10-fold cross validation experiment performed on a large sample of 1,954 images using the proposed framework achieved a high overall accuracy of 88.28%. Conclusions: The salient contributions of this study are three-fold: (1) our experiments demonstrate that the combination of multiple structural features extracted at different scales with our proposed deep neural network yields superior performance than individual features; (2) we show that the use of Generative Adversarial Network for data augmentation could further improve the discriminant ability of the network regarding challenging tasks such as differentiating dementia sub-types; (3) and finally, we show that ensemble classifier strategy could make the network more robust and stable.

Rates of Brain Atrophy Across Disease Stages in Familial Frontotemporal Dementia Associated With MAPT, GRN, and C9orf72 Pathogenic Variants

Importance

Several clinical trials are planned for familial forms of frontotemporal lobar degeneration (f-FTLD). Precise modeling of brain atrophy in f-FTLD could improve the power to detect a treatment effect.

Objective

To characterize regions and rates of atrophy in the 3 primary f-FTLD genetic groups (MAPT, GRN, and C9orf72) across all disease stages from asymptomatic to dementia.

Design, Setting, and Participants

This investigation was a case-control study of participants enrolled in the Advancing Research and Treatment for Frontotemporal Lobar Degeneration or Longitudinal Evaluation of Familial Frontotemporal Dementia studies. The study took place at 18 North American academic medical centers between January 2009 and September 2018. Participants with f-FTLD (n = 100) with a known pathogenic variant (MAPT [n = 28], GRN [n = 33], or C9orf72 [n = 39]) were grouped according to disease stage (ie, Clinical Dementia Rating [CDR] plus National Alzheimer's Coordinating Center [NACC] FTLD module). Included were participants with at least 2 structural magnetic resonance images at presymptomatic (CDR + NACC FTLD = 0 [n = 57]), mild or questionable (CDR + NACC FTLD = 0.5 [n = 15]), or symptomatic (CDR + NACC FTLD = ≥1 [n = 28]) disease stages. The control group included family members of known pathogenic variant carriers who did not carry the pathogenic variant (n = 60).

Main Outcomes and Measures

This study fitted bayesian linear mixed-effects models in each voxel of the brain to quantify the rate of atrophy in each of the 3 genes, at each of the 3 disease stages, compared with controls. The study also analyzed rates of clinical decline in each of these groups, as measured by the CDR + NACC FTLD box score.

Results

The sample included 100 participants with f-FTLD with a known pathogenic variant (mean [SD] age, 50.48 [13.78] years; 53 [53%] female) and 60 family members of known pathogenic variant carriers who did not carry the pathogenic variant (mean [SD] age, 47.51 [12.43] years; 36 [60%] female). MAPT and GRN pathogenic variants were associated with increased rates of volume loss compared with controls at all stages of disease. In MAPT pathogenic variant carriers, statistically significant regions of accelerated volume loss compared with controls were identified in temporal regions bilaterally in the presymptomatic stage, with global spread in the symptomatic stage. For example, mean [SD] rates of atrophy in the left temporal were -231 [47] mm3 per year during the presymptomatic stage, -381 [208] mm3 per year during the mild stage, and -1485 [1025] mm3 per year during the symptomatic stage (P < .05). GRN pathogenic variant carriers generally had minimal increases in atrophy rates between the presymptomatic and mild stages, with rapid increases in atrophy rates in the symptomatic stages. For example, in the right frontal lobes, annualized volume loss was -267 [81] mm3 per year in the presymptomatic stage and -182 [90] mm3 per year in the mild stage, but -1169 [555] mm3 per year in the symptomatic stage. Compared with the other groups, C9orf72 expansion carriers showed minimal increases in rate of volume loss with disease progression. For example, the mean (SD) annualized rates of atrophy in the right frontal lobe in C9orf72 expansion carriers was -272 (118) mm3 per year in presymptomatic stages, -310 (189) mm3 per year in mildly symptomatic stages, and -251 (145) mm3 per year in symptomatic stages.

Conclusions and Relevance

These findings are relevant to clinical trial planning and suggest that the mechanism by which C9orf72 pathogenic variants lead to symptoms may be fundamentally different from the mechanisms associated with other pathogenic variants.

Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) have a strong clinical, genetic and pathological overlap. This review focuses on the current understanding of structural, functional and molecular neuroimaging signatures of genetic FTD and ALS. We overview quantitative neuroimaging studies on the most common genes associated with FTD (MAPT, GRN), ALS (SOD1), and both (C9orf72), and summarize visual observations of images reported in the rarer genes (CHMP2B, TARDBP, FUS, OPTN, VCP, UBQLN2, SQSTM1, TREM2, CHCHD10, TBK1).

Early symptoms in symptomatic and preclinical genetic frontotemporal lobar degeneration

OBJECTIVES

The clinical heterogeneity of frontotemporal dementia (FTD) complicates identification of biomarkers for clinical trials that may be sensitive during the prediagnostic stage. It is not known whether cognitive or behavioural changes during the preclinical period are predictive of genetic status or conversion to clinical FTD. The first objective was to evaluate the most frequent initial symptoms in patients with genetic FTD. The second objective was to evaluate whether preclinical mutation carriers demonstrate unique FTD-related symptoms relative to familial mutation non-carriers.

METHODS

The current study used data from the Genetic Frontotemporal Dementia Initiative multicentre cohort study collected between 2012 and 2018. Participants included symptomatic carriers (n=185) of a pathogenic mutation in chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN) or microtubule-associated protein tau (MAPT) and their first-degree biological family members (n=588). Symptom endorsement was documented using informant and clinician-rated scales.

RESULTS

The most frequently endorsed initial symptoms among symptomatic patients were apathy (23%), disinhibition (18%), memory impairments (12%), decreased fluency (8%) and impaired articulation (5%). Predominant first symptoms were usually discordant between family members. Relative to biologically related non-carriers, preclinical MAPT carriers endorsed worse mood and sleep symptoms, and C9orf72 carriers endorsed marginally greater abnormal behaviours. Preclinical GRN carriers endorsed less mood symptoms compared with non-carriers, and worse everyday skills.

CONCLUSION

Preclinical mutation carriers exhibited neuropsychiatric symptoms compared with non-carriers that may be considered as future clinical trial outcomes. Given the heterogeneity in symptoms, the detection of clinical transition to symptomatic FTD may be best captured by composite indices integrating the most common initial symptoms for each genetic group.

Neuroimaging in Dementia: A Brief Review

Dementia is a clinical syndrome that manifests itself with impairment in cognitive functions owing to various neurodegenerative etiologies causing severe disability in the older population. Although the diagnosis is largely dependent on clinical examination, biomarkers can significantly aid in early diagnosis of dementia, especially in those without any clinical evidence of neurocognitive impairment. These biomarkers can be discovered in cerebrospinal fluid (CSF) or can be assessed by neuroimaging. Our goal was to discuss and assess the role of different neuroimaging techniques in the early diagnosis of relatively common etiologies of dementia. We used PubMed as search engines to look for helpful articles; most of the sources used were peer reviewed. We discussed the utility of various neuroimaging techniques, such CT, MRI, positron emission tomography (PET) scan, and single-photon emission computed tomography (SPECT), in the diagnosis of dementia. We concluded that various modern neuroimaging techniques prove to be very helpful in early identification, diagnosis, and differentiation between subtypes. However, the actual clinical utility of these tests in terms of their cost-effectivity and availability remains to be seen. Ongoing research is required to further develop biomarkers for early identification and monitor the progression of different etiologies of dementia.

Relevance of biomarkers across different neurodegenerative diseases

Background

The panel of fluid- and imaging-based biomarkers available for neurodegenerative disease research is growing and has the potential to close important gaps in research and the clinic. With this growth and increasing use, appropriate implementation and interpretation are paramount. Various biomarkers feature nuanced differences in strengths, limitations, and biases that must be considered when investigating disease etiology and clinical utility. For example, neuropathological investigations of Alzheimer’s disease pathogenesis can fall in disagreement with conclusions reached by biomarker-based investigations. Considering the varied strengths, limitations, and biases of different research methodologies and approaches may help harmonize disciplines within the neurodegenerative disease field.

Purpose of review

Along with separate review articles covering fluid and imaging biomarkers in this issue of Alzheimer’s Research and Therapy, we present the result of a discussion from the 2019 Biomarkers in Neurodegenerative Diseases course at the University College London. Here, we discuss themes of biomarker use in neurodegenerative disease research, commenting on appropriate use, interpretation, and considerations for implementation across different neurodegenerative diseases. We also draw attention to areas where biomarker use can be combined with other disciplines to understand issues of pathophysiology and etiology underlying dementia. Lastly, we highlight novel modalities that have been proposed in the landscape of neurodegenerative disease research and care.