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Clinical characterization of bvFTD due to FUS neuropathology.

ABSTRACT: In 2009, inclusions containing the fused in sarcoma (FUS) protein were identified as a third major molecular class of pathology underlying the behavioral variant frontotemporal dementia (bvFTD) syndrome. Due to the low prevalence of FUS pathology, few clinical descriptions have been published and none provides information about specific social-emotional deficits despite evidence for severe behavioral manifestations in this disorder. We evaluated a patient with bvFTD due to FUS pathology using a comprehensive battery of cognitive and social- emotional tests. A structural MRI scan and genetic tests for tau, progranulin, and FUS mutations were also performed. The patient showed preserved general cognitive functioning and superior working memory, but severe deficits in emotion attribution, sensitivity to punishment, and diminished capacity for interpersonal warmth and empathy. The gray matter atrophy pattern corresponded to this focal deficit profile, with preservation of dorsolateral fronto-parietal regions associated with executive functioning but severe damage to right worse than left frontoinsula, temporal pole, subgenual anterior cingulate, medial orbitofrontal cortex, amygdala, and caudate. This patient demonstrates the striking focality associated with FUS neuropathology in patients with bvFTD.

SUBMITTER: Lee SE

PROVIDER: S-EPMC3288419 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Clinical characterization of bvFTD due to FUS neuropathology.

Lee Suzee E SE Seeley William W WW Poorzand Pardis P Rademakers Rosa R Karydas Anna A Stanley Christine M CM Miller Bruce L BL Rankin Katherine P KP

Neurocase 20111107 4

In 2009, inclusions containing the fused in sarcoma (FUS) protein were identified as a third major molecular class of pathology underlying the behavioral variant frontotemporal dementia (bvFTD) syndrome. Due to the low prevalence of FUS pathology, few clinical descriptions have been published and none provides information about specific social-emotional deficits despite evidence for severe behavioral manifestations in this disorder. We evaluated a patient with bvFTD due to FUS pathology using a ...[more]

PMID: 22060063

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Project description:BackgroundMutations in the gene encoding the RNA-binding protein fused in sarcoma (FUS) can cause familial and sporadic amyotrophic lateral sclerosis (ALS) and rarely frontotemproal dementia (FTD). FUS accumulates in neuronal cytoplasmic inclusions (NCIs) in ALS patients with FUS mutations. FUS is also a major pathologic marker for a group of less common forms of frontotemporal lobar degeneration (FTLD), which includes atypical FTLD with ubiquitinated inclusions (aFTLD-U), neuronal intermediate filament inclusion disease (NIFID) and basophilic inclusion body disease (BIBD). These diseases are now called FUS proteinopathies, because they share this disease marker. It is unknown how FUS mutations cause disease and the role of FUS in FTD-FUS cases, which do not have FUS mutations. In this paper we report the development of somatic brain transgenic (SBT) mice using recombinant adeno-associated virus (rAAV) to investigate how FUS mutations lead to neurodegeneration.ResultsWe compared SBT mice expressing wild-type human FUS (FUSWT), and two ALS-linked mutations: FUSR521C and FUS?14, which lacks the nuclear localization signal. Both FUS mutants accumulated in the cytoplasm relative to FUSWT. The degree of this shift correlated with the severity of the FUS mutation as reflected by disease onset in humans. Mice expressing the most aggressive mutation, FUS?14, recapitulated many aspects of FUS proteinopathies, including insoluble FUS, basophilic and eosiniphilic NCIs, and other pathologic markers, including ubiquitin, p62/SQSTM1, ?-internexin, and the poly-adenylate(A)-binding protein 1 (PABP-1). However, TDP-43 did not localize to inclusions.ConclusionsOur data supports the hypothesis that ALS or FTD-linked FUS mutations cause neurodegeneration by increasing cyotplasmic FUS. Accumulation of FUS in the cytoplasm may retain RNA targets and recruit additional RNA-binding proteins, such as PABP-1, into stress-granule like aggregates that coalesce into permanent inclusions that could negatively affect RNA metabolism. Identification of mutations in other genes that cause ALS/FTD, such as C9ORF72, sentaxin, and angiogenin, lends support to the idea that defective RNA metabolism is a critical pathogenic pathway. The SBT FUS mice described here will provide a valuable platform for dissecting the pathogenic mechanism of FUS mutations, define the relationship between FTD and ALS-FUS, and help identify therapeutic targets that are desperately needed for these devastating neurodegenerative disorders.

Project description:BackgroundComputer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack validation against postmortem AD neuropathological data.ObjectiveTrain machine learning models to classify the presence or absence of autopsy-confirmed severe AD neuropathology using clinically available features.MethodsAD neuropathological status are assessed at postmortem for participants from the National Alzheimer's Coordinating Center (NACC). Clinically available features are utilized, including demographics, Apolipoprotein E(APOE) genotype, and cortical thicknesses derived from ante-mortem MRI scans encompassing AD meta regions of interest (meta-ROI). Both logistic regression and random forest models are trained to identify linearly and nonlinearly separable features between participants with the presence (N = 91, age-at-MRI = 73.6±9.24, 38 women) or absence (N = 53, age-at-MRI = 68.93±19.69, 24 women) of severe AD neuropathology. The trained models are further validated in an external data set against in vivo amyloid biomarkers derived from PET imaging (amyloid-positive: N = 71, age-at-MRI = 74.17±6.37, 26 women; amyloid-negative: N = 73, age-at-MRI = 71.59±6.80, 41 women).ResultsOur models achieve a cross-validation accuracy of 84.03% in classifying the presence or absence of severe AD neuropathology, and an external-validation accuracy of 70.14% in classifying in vivo amyloid positivity status.ConclusionsOur models show that clinically accessible features, including APOE genotype and cortical thinning encompassing AD meta-ROIs, are able to classify both postmortem confirmed AD neuropathological status and in vivo amyloid status with reasonable accuracies. These results suggest the potential utility of AD meta-ROIs in determining AD neuropathological status in living persons.

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Clinical characterization of bvFTD due to FUS neuropathology.

Publications

Clinical characterization of bvFTD due to FUS neuropathology.

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