Frontotemporal dementia (FTD) is a highly heritable group of neurodegenerative disorders, with around 30% of patients having a strong family history. The majority of that heritability is accounted ...for by autosomal dominant mutations in the chromosome 9 open reading frame 72 (
C9orf72
), progranulin (
GRN
), and microtubule-associated protein tau (
MAPT
) genes, with mutations more rarely seen in a number of other genes. This review will discuss the recent updates in the field of genetic FTD. Age at symptom onset in genetic FTD is variable with recently identified genetic modifiers including
TMEM106B
(in
GRN
carriers particularly) and a polymorphism at a locus containing two overlapping genes
LOC101929163
and
C6orf10
(in
C9orf72
carriers). Behavioural variant FTD (bvFTD) is the most common diagnosis in each of the genetic groups, although in
C9orf72
carriers amyotrophic lateral sclerosis either alone, or with bvFTD, is also common. An atypical neuropsychiatric presentation is also seen in
C9orf72
carriers and family members of carriers are at greater risk of psychiatric disorders including schizophrenia and autistic spectrum disorders. Large natural history studies of presymptomatic genetic FTD are now underway both in Europe/Canada (GENFI—the Genetic FTD Initiative) and in the US (ARTFL/LEFFTDS study), collaborating together under the banner of the FTD Prevention Initiative (FPI). These studies are taking forward the validation of cognitive, imaging and fluid biomarkers that aim to robustly measure disease onset, staging and progression in genetic FTD. Grey matter changes on MRI and hypometabolism on FDG-PET are seen at least 10 years before symptom onset with white matter abnormalities seen earlier, but the pattern and exact timing of changes differ between different genetic groups. In contrast, tau PET has yet to show promise in genetic FTD. Three key fluid biomarkers have been identified so far that are likely to be helpful in clinical trials—CSF or blood neurofilament light chain levels (in all groups), CSF or blood progranulin levels (in
GRN
carriers) and CSF poly(GP) dipeptide repeat protein levels (in
C9orf72
carriers). Increased knowledge about genetic FTD has led to more clinical presymptomatic genetic testing but this has not yet been mirrored in the development of either an accepted FTD-specific testing protocol or provision of appropriate psychological support mechanisms for those living through the at-risk phase. This will become even more relevant as disease-modifying therapy trials start in each of the genetic groups over the next few years.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Frontotemporal dementia comprises a group of clinical syndromes that are characterised by progressive changes in behaviour, executive function, or language. The term frontotemporal lobar degeneration ...encompasses the neurodegenerative diseases that give rise to these clinical syndromes and involve proteinopathies associated with frontotemporal network dysfunction. Improvements in clinical, genetic, and molecular characterisation have provided new insights into frontotemporal dementia and frontotemporal lobar degeneration, with a much broader range of signs and symptoms at presentation than has been previously considered. Accurate and early diagnosis of frontotemporal dementia is now a possibility due to development of neuropsychological measures with a special focus on social cognition. Advances in plasma and CSF biomarkers, and innovations in structural and functional imaging, will prove useful for future clinical trials in people with frontotemporal dementia.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•A publicly available deep learning tool to segment the hypothalamus and its subunits.•Our tool outperforms inter-rater accuracy and approaches intra-rater precision level.•It can robustly generalise ...to unseen heterogeneous datasets.•It yields a rejection rate of less than 1% in a QC analysis performed on 675 scans.•It detects subtle subunit-specific hypothalamic atrophy in Alzheimer’s Disease.
Despite the crucial role of the hypothalamus in the regulation of the human body, neuroimaging studies of this structure and its nuclei are scarce. Such scarcity partially stems from the lack of automated segmentation tools, since manual delineation suffers from scalability and reproducibility issues. Due to the small size of the hypothalamus and the lack of image contrast in its vicinity, automated segmentation is difficult and has been long neglected by widespread neuroimaging packages like FreeSurfer or FSL. Nonetheless, recent advances in deep machine learning are enabling us to tackle difficult segmentation problems with high accuracy. In this paper we present a fully automated tool based on a deep convolutional neural network, for the segmentation of the whole hypothalamus and its subregions from T1-weighted MRI scans. We use aggressive data augmentation in order to make the model robust to T1-weighted MR scans from a wide array of different sources, without any need for preprocessing. We rigorously assess the performance of the presented tool through extensive analyses, including: inter- and intra-rater variability experiments between human observers; comparison of our tool with manual segmentation; comparison with an automated method based on multi-atlas segmentation; assessment of robustness by quality control analysis of a larger, heterogeneous dataset (ADNI); and indirect evaluation with a volumetric study performed on ADNI. The presented model outperforms multi-atlas segmentation scores as well as inter-rater accuracy level, and approaches intra-rater precision. Our method does not require any preprocessing and runs in less than a second on a GPU, and approximately 10 seconds on a CPU. The source code as well as the trained model are publicly available at https://github.com/BBillot/hypothalamus_seg, and will also be distributed with FreeSurfer.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Hexanucleotide repeat expansions in C9orf72 are a major cause of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). Understanding the disease mechanisms and a method ...for clinical diagnostic genotyping have been hindered because of the difficulty in estimating the expansion size. We found 96 repeat-primed PCR expansions: 85/2,974 in six neurodegenerative diseases cohorts (FTLD, ALS, Alzheimer disease, sporadic Creutzfeldt-Jakob disease, Huntington disease-like syndrome, and other nonspecific neurodegenerative disease syndromes) and 11/7,579 (0.15%) in UK 1958 birth cohort (58BC) controls. With the use of a modified Southern blot method, the estimated expansion range (smear maxima) in cases was 800–4,400. Similarly, large expansions were detected in the population controls. Differences in expansion size and morphology were detected between DNA samples from tissue and cell lines. Of those in whom repeat-primed PCR detected expansions, 68/69 were confirmed by blotting, which was specific for greater than 275 repeats. We found that morphology in the expansion smear varied among different individuals and among different brain regions in the same individual. Expansion size correlated with age at clinical onset but did not differ between diagnostic groups. Evidence of instability of repeat size in control families, as well as neighboring SNP and microsatellite analyses, support multiple expansion events on the same haplotype background. Our method of estimating the size of large expansions has potential clinical utility. C9orf72-related disease might mimic several neurodegenerative disorders and, with potentially 90,000 carriers in the United Kingdom, is more common than previously realized.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
OBJECTIVE:To investigate serum neurofilament light chain (NfL) concentrations in frontotemporal dementia (FTD) and to see whether they are associated with the severity of disease.
METHODS:Serum ...samples were collected from 74 participants (34 with behavioral variant FTD bvFTD, 3 with FTD and motor neuron disease and 37 with primary progressive aphasia PPA) and 28 healthy controls. Twenty-four of the FTD participants carried a pathogenic mutation in C9orf72 (9), microtubule-associated protein tau (MAPT; 11), or progranulin (GRN; 4). Serum NfL concentrations were determined with the NF-Light kit transferred onto the single-molecule array platform and compared between FTD and healthy controls and between the FTD clinical and genetic subtypes. We also assessed the relationship between NfL concentrations and measures of cognition and brain volume.
RESULTS:Serum NfL concentrations were higher in patients with FTD overall (mean 77.9 pg/mL SD 51.3 pg/mL) than controls (19.6 pg/mL SD 8.2 pg/mL; p < 0.001). Concentrations were also significantly higher in bvFTD (57.8 pg/mL SD 33.1 pg/mL) and both the semantic and nonfluent variants of PPA (95.9 and 82.5 pg/mL SD 33.0 and 33.8 pg/mL, respectively) compared with controls and in semantic variant PPA compared with logopenic variant PPA. Concentrations were significantly higher than controls in both the C9orf72 and MAPT subgroups (79.2 and 40.5 pg/mL SD 48.2 and 20.9 pg/mL, respectively) with a trend to a higher level in the GRN subgroup (138.5 pg/mL SD 103.3 pg/mL). However, there was variability within all groups. Serum concentrations correlated particularly with frontal lobe atrophy rate (r = 0.53, p = 0.003).
CONCLUSIONS:Increased serum NfL concentrations are seen in FTD but show wide variability within each clinical and genetic group. Higher concentrations may reflect the intensity of the disease in FTD and are associated with more rapid atrophy of the frontal lobes.
The development of our understanding of frontotemporal dementia (FTD) has gathered pace over the last 10 years. After taking a back seat to Alzheimer's disease for many years FTD has emerged as a ...significant group of heterogeneous diseases often affecting people under the age of 65. FTD has also been brought into the spotlight as the major disease entities of the group have clinical, genetic and pathological links to motor neuron disease/amyotrophic lateral sclerosis, indicating that they form a disease spectrum. In this review, we overview how the pathological concept of frontotemporal lobar degeneration (FTLD) and the clinical concept of FTD evolved and show that FTLD, once thought of as a single disorder, represents a heterogeneous group of diseases with overlapping clinical symptoms, multiple causative genes and varying underlying pathology. We also provide a brief summary of the clinical manifestations, summarize the major genetic aspects and describe the main pathological features seen in the different subtypes of FTLD. We also summarize the correlations that exist between clinical presentations and pathological variants. An overview of the main pathogenic mechanisms is also provided.
This beautifully illustrated, authoritative review provides an up to date overview of the field of frontotemporal lobar degenerations including clinical, genetic, neuropathological and mechanistic data.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Summary C9orf72 hexanucleotide repeat expansions are the most common cause of familial frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) worldwide. The clinical presentation is ...often indistinguishable from classic FTD or ALS, although neuropsychiatric symptoms are more prevalent and, for ALS, behavioural and cognitive symptoms occur more frequently. Pathogenic repeat length is in the hundreds or thousands, but the minimum length that increases risk of disease, and how or whether the repeat size affects phenotype, are unclear. Like in many patients with FTD and ALS, neuronal inclusions that contain TARDBP are seen, but are not universal, and the characteristic pathological finding is of dipeptide repeat (DPR) proteins, formed by unconventional repeat-associated non-ATG translation. Possible mechanisms of neurodegeneration include loss of C9orf72 protein and function, RNA toxicity, and toxicity from the DPR proteins, but which of these is the major pathogenic mechanism is not yet certain.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Accurately distinguishing between different degenerative dementias during life is challenging but increasingly important with the prospect of disease-modifying therapies. Molecular biomarkers of ...dementia pathology are becoming available, but are not widely used in clinical practice. Conversely, structural neuroimaging is recommended in the evaluation of cognitive impairment. Visual assessment remains the primary method of scan interpretation, but in the absence of a structured approach, diagnostically relevant information may be under-utilized. This definitive, multi-centre study uses post-mortem confirmed cases as the gold standard to: (i) assess the reliability of six visual rating scales; (ii) determine their associated pattern of atrophy; (iii) compare their diagnostic value with expert scan assessment; and (iv) assess the accuracy of a machine learning approach based on multiple rating scales to predict underlying pathology. The study includes T1-weighted images acquired in three European centres from 184 individuals with histopathologically confirmed dementia (101 patients with Alzheimer's disease, 28 patients with dementia with Lewy bodies, 55 patients with frontotemporal lobar degeneration), and scans from 73 healthy controls. Six visual rating scales (medial temporal, posterior, anterior temporal, orbito-frontal, anterior cingulate and fronto-insula) were applied to 257 scans (two raters), and to a subset of 80 scans (three raters). Six experts also provided a diagnosis based on unstructured assessment of the 80-scan subset. The reliability and time taken to apply each scale was evaluated. Voxel-based morphometry was used to explore the relationship between each rating scale and the pattern of grey matter volume loss. Additionally, the performance of each scale to predict dementia pathology both individually and in combination was evaluated using a support vector classifier, which was compared with expert scan assessment to estimate clinical value. Reliability of scan assessment was generally good (intraclass correlation coefficient > 0.7), and average time to apply all six scales was <3 min. There was a very close association between the pattern of grey matter loss and the regions of interest each scale was designed to assess. Using automated classification based on all six rating scales, the accuracy (estimated using the area under the receiver-operator curves) for distinguishing each pathological group from controls ranged from 0.86-0.97; and from one another, 0.75-0.92. These results were substantially better than the accuracy of any single scale, at least as good as expert reads, and comparable to previous studies using molecular biomarkers. Visual rating scores from magnetic resonance images routinely acquired as part of the investigation of dementias, offer a practical, inexpensive means of improving diagnostic accuracy.
The neurodegenerative disorder Alzheimer's disease is characterised by the formation of β-amyloid plaques and neurofibrillary tangles in the brain parenchyma, which cause synapse and neuronal loss. ...This leads to clinical symptoms, such as progressive memory deficits. Clinically, these pathological changes can be detected in the cerebrospinal fluid and with brain imaging, although reliable blood tests for plaque and tangle pathologies remain to be developed. Plaques and tangles often co-exist with other brain pathologies, including aggregates of transactive response DNA-binding protein 43 and Lewy bodies, but the extent to which these contribute to the severity of Alzheimer's disease is currently unknown. In this 'At a glance' article and poster, we summarise the molecular biomarkers that are being developed to detect Alzheimer's disease and its related pathologies. We also highlight the biomarkers that are currently in clinical use and include a critical appraisal of the challenges associated with applying these biomarkers for diagnostic and prognostic purposes of Alzheimer's disease and related neurodegenerative disorders, also in their prodromal clinical phases.
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