Clinical phenotypic variability in an Italian family bearing the IVS6+ 5_8delGTGA mutation in PGRN gene

Background Frontotemporal dementia (FTD) is a complex presenile disorder characterized by behavioural changes and executive functions, expression of fronto-temporal degeneration. Hereditary FTD accounts for 20-30% of cases and, in the past decade, mutations in the microtubule associated protein tau (MAPT)gene were identified as a main genetic causes of familial FTD. In 2006, mutations in the gene encoding progranulin (PGRN) were reported, to account for a wide part of the familial FTD cases. Clinically, an high phenotypic variability within and among the kindreds is reported in the familial FTD associated with PGRN mutations and occasionally the memory deficits are the first symptoms, resembling Alzheimer's disease (AD). We report an Italian family with dementia associated with a PGRN mutation characterized by a deletion of 4 base pairs inside the intron 6 of the gene, leading to haploin sufficiency In our kindred, all three affected patients carried the mutation, but presented very different clinical phenotypes, evoking FTD, AD and rapidly-progressive dementia mimicking prion disease. Methods Informations on the members of the first, second and third generations were obtained conducting interviews with relatives, while for the three patients studied, the clinical evidence of dementia symptoms and their characterization was documented directly with sequential neurological examinations, cognitive assessments and neuroimaging. Blood sample collection and DNA extraction from peripheral blood lymphocytes for genetic analysis were performed after written informed consent of the patients. Results In our pedigree, the PGRN mutated patients are affected by dementia with three different clinical pictures: FTD, AD and rapidly progressive dementia mimicking prion disease. Neuropsychological examinations supported these diagnoses, documenting generalized deficits of cortical functions in AD patient and deficits in executive functions and in language in FTD patient. Regarding neuroimaging, in the same two cases MRI results do not correspond to the clinical diagnosis. Conclusions These findings confirms the marked heterogeneity of the clinico-radiological features in patients with PGNR mutations and underline the need of considering mutations of this gene as causes of familial dementing diseases with atypical or uncommon features or discrepancies between the clinical and the neuroimaging findings

Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases

AbstractIn clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm2 and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD

Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases

In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt-Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann-Straussler-Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROl-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCID subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 mu m that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T-2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CID lesions: b 3000 s/mm(2) and TE 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and sublyping of sCJD. (C) 2014 The Authors. Published by Elsevier Inc

GEN-O-MA project: an Italian network studying clinical course and pathogenic pathways of moyamoya disease—study protocol and preliminary results

Background: GENetics of mOyaMoyA (GEN-O-MA) project is a multicenter observational study implemented in Italy aimed at creating a network of centers involved in moyamoya angiopathy (MA) care and research and at collecting a large series and bio-repository of MA patients, finally aimed at describing the disease phenotype and clinical course as well as at identifying biological or cellular markers for disease progression. The present paper resumes the most important study methodological issues and preliminary results. Methods: Nineteen centers are participating to the study. Patients with both bilateral and unilateral radiologically defined MA are included in the study. For each patient, detailed demographic and clinical as well as neuroimaging data are being collected. When available, biological samples (blood, DNA, CSF, middle cerebral artery samples) are being also collected for biological and cellular studies. Results: Ninety-eight patients (age of onset mean ± SD 35.5 ± 19.6 years; 68.4% females) have been collected so far. 65.3% of patients presented ischemic (50%) and haemorrhagic (15.3%) stroke. A higher female predominance concomitantly with a similar age of onset and clinical features to what was reported in previous studies on Western patients has been confirmed. Conclusion: An accurate and detailed clinical and neuroimaging classification represents the best strategy to provide the characterization of the disease phenotype and clinical course. The collection of a large number of biological samples will permit the identification of biological markers and genetic factors associated with the disease susceptibility in Italy

Разработка противотуманного стационарного светильника для автомагистралей

Современное дорожное освещение имеет ряд проблем, в числе которых низкая эффективность в условиях тумана. Улучшение качества освещения путем использования противотуманных светильников позволит повысить безопасность на дорогах и снизить усталость водителей. Существующие разработки противотуманных светильников не предусмотрены для работы в условиях Сибири, поэтому возникает необходимость разработки устойчивого дизайна противотуманного светильника. В работе описан процесс разработки дизайна стационарного противотуманного светильника, способного полноценно функционировать в условиях Сибири.Conventional road luminaire has a number of shortcomings and is ineffective in fog. By improving the quality of road lighting it will be possible to decrease the accident rate and drivers' fatigue. Existing fog lighting developments are not designed to be used in harsh conditions of Siberia, so a new luminaire design should be proposed. In this work is described the design process of a new stationary fog luminaire, adapted to the use in Siberia

Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the Genetic Frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis.

BACKGROUND: Frontotemporal dementia is a highly heritable neurodegenerative disorder. In about a third of patients, the disease is caused by autosomal dominant genetic mutations usually in one of three genes: progranulin (GRN), microtubule-associated protein tau (MAPT), or chromosome 9 open reading frame 72 (C9orf72). Findings from studies of other genetic dementias have shown neuroimaging and cognitive changes before symptoms onset, and we aimed to identify whether such changes could be shown in frontotemporal dementia. METHODS: We recruited participants to this multicentre study who either were known carriers of a pathogenic mutation in GRN, MAPT, or C9orf72, or were at risk of carrying a mutation because a first-degree relative was a known symptomatic carrier. We calculated time to expected onset as the difference between age at assessment and mean age at onset within the family. Participants underwent a standardised clinical assessment and neuropsychological battery. We did MRI and generated cortical and subcortical volumes using a parcellation of the volumetric T1-weighted scan. We used linear mixed-effects models to examine whether the association of neuropsychology and imaging measures with time to expected onset of symptoms differed between mutation carriers and non-carriers. FINDINGS: Between Jan 30, 2012, and Sept 15, 2013, we recruited participants from 11 research sites in the UK, Italy, the Netherlands, Sweden, and Canada. We analysed data from 220 participants: 118 mutation carriers (40 symptomatic and 78 asymptomatic) and 102 non-carriers. For neuropsychology measures, we noted the earliest significant differences between mutation carriers and non-carriers 5 years before expected onset, when differences were significant for all measures except for tests of immediate recall and verbal fluency. We noted the largest Z score differences between carriers and non-carriers 5 years before expected onset in tests of naming (Boston Naming Test -0·7; SE 0·3) and executive function (Trail Making Test Part B, Digit Span backwards, and Digit Symbol Task, all -0·5, SE 0·2). For imaging measures, we noted differences earliest for the insula (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume was 0·80% in mutation carriers and 0·84% in non-carriers; difference -0·04, SE 0·02) followed by the temporal lobe (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume 8·1% in mutation carriers and 8·3% in non-carriers; difference -0·2, SE 0·1). INTERPRETATION: Structural imaging and cognitive changes can be identified 5-10 years before expected onset of symptoms in asymptomatic adults at risk of genetic frontotemporal dementia. These findings could help to define biomarkers that can stage presymptomatic disease and track disease progression, which will be important for future therapeutic trials. FUNDING: Centres of Excellence in Neurodegeneration

White matter hyperintensities are seen only in GRN mutation carriers in the GENFI cohort

© 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).Genetic frontotemporal dementia is most commonly caused by mutations in the progranulin (GRN), microtubule-associated protein tau (MAPT) and chromosome 9 open reading frame 72 (C9orf72) genes. Previous small studies have reported the presence of cerebral white matter hyperintensities (WMH) in genetic FTD but this has not been systematically studied across the different mutations. In this study WMH were assessed in 180 participants from the Genetic FTD Initiative (GENFI) with 3D T1- and T2-weighed magnetic resonance images: 43 symptomatic (7 GRN, 13 MAPT and 23 C9orf72), 61 presymptomatic mutation carriers (25 GRN, 8 MAPT and 28 C9orf72) and 76 mutation negative non-carrier family members. An automatic detection and quantification algorithm was developed for determining load, location and appearance of WMH. Significant differences were seen only in the symptomatic GRN group compared with the other groups with no differences in the MAPT or C9orf72 groups: increased global load of WMH was seen, with WMH located in the frontal and occipital lobes more so than the parietal lobes, and nearer to the ventricles rather than juxtacortical. Although no differences were seen in the presymptomatic group as a whole, in the GRN cohort only there was an association of increased WMH volume with expected years from symptom onset. The appearance of the WMH was also different in the GRN group compared with the other groups, with the lesions in the GRN group being more similar to each other. The presence of WMH in those with progranulin deficiency may be related to the known role of progranulin in neuroinflammation, although other roles are also proposed including an effect on blood-brain barrier permeability and the cerebral vasculature. Future studies will be useful to investigate the longitudinal evolution of WMH and their potential use as a biomarker as well as post-mortem studies investigating the histopathological nature of the lesions.This work was funded by the UK Medical Research Council, the Italian Ministry of Health, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant (CoEN015). The Dementia Research Centre is supported by Alzheimer's Research UK, Brain Research Trust, and The Wolfson Foundation. This work was supported by the NIHR Queen Square Dementia Biomedical Research Unit and the NIHR UCL/H Biomedical Research Centre. JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). KD is supported by an Alzheimer's Society PhD Studentship (AS-PhD-2015-005). JBR is supported by the Wellcome Trust (103838) and the NIHR Cambridge Biomedical Research Centre. MM is supported by the Canadian Institutes of Health Research and the Ontario Research Fund. RL is supported by Réseau de médecine génétique appliquée, Fonds de recherche du Québec—Santé (FRQS). FT is supported by the Italian Ministry of Health. DG is supported by the Fondazione Monzino and Italian Ministry of Health, Ricerca Corrente. SS is supported by Cassa di Risparmio di Firenze (CRF 2013/0199) and the Ministry of Health RF-2010-2319722. SO is supported by the Engineering and Physical Sciences Research Council (EP/H046410/1, EP/J020990/1, EP/K005278), the Medical Research Council (MR/J01107X/1), the EU-FP7 project VPH-DARE@IT (FP7-ICT-2011-9-601055), and the National Institute for Health Research University College London Hospitals Biomedical Research Centre (NIHR BRC UCLH/UCL High Impact Initiative BW.mn.BRC10269). JvS is supported by The Netherlands Organisation for Health Research and Development Memorable grant (733050103) and Netherlands Alzheimer Foundation Memorable grant (733050103).info:eu-repo/semantics/publishedVersio

Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort

Brain atrophy as measured from structural MR images, is one of the primary imaging biomarkers used to track neurodegenerative disease progression. In diseases such as frontotemporal dementia or Alzheimer's disease, atrophy can be observed in key brain structures years before any clinical symptoms are present. Atrophy is most commonly captured as volume change of key structures and the shape changes of these structures are typically not analysed despite being potentially more sensitive than summary volume statistics over the entire structure. In this paper we propose a spatiotemporal analysis pipeline based on Large Diffeomorphic Deformation Metric Mapping (LDDMM) to detect shape changes from volumetric MRI scans. We applied our framework to a cohort of individuals with genetic variants of frontotemporal dementia and healthy controls from the Genetic FTD Initiative (GENFI) study. Our method, take full advantage of the LDDMM framework, and relies on the creation of a population specific average spatiotemporal trajectory of a relevant brain structure of interest, the thalamus in our case. The residuals from each patient data to the average spatiotemporal trajectory are then clustered and studied to assess when presymptomatic mutation carriers differ from healthy control subjects. We found statistical differences in shape in the anterior region of the thalamus at least five years before the mutation carrier subjects develop any clinical symptoms. This region of the thalamus has been shown to be predominantly connected to the frontal lobe, consistent with the pattern of cortical atrophy seen in the disease

Decision-making under risk: a graph-based network analysis using functional MRI

Adaptive behavior requires choosing effectively between options involving risks and potential rewards. Existing studies implicate lateral and medial prefrontal areas, striatum, insula, amygdala and parietal regions in specific aspects of decision-making. However, limited attention is given to how brain networks encode economic parameters in patterns of inter-regional interactions. Here, healthy participants underwent functional MRI while evaluating “mixed” gambles presenting potential gains, losses and associated outcome probabilities. Connectivity graphs were constructed from analyses of psychophysiological interactions across a comprehensive atlas of brain regions. Expected value correlated positively with activity within medial prefrontal and occipital cortices, and modulated effective connectivity across a network that extended substantially beyond these nodes. Value-sensitive effective connections were found to be arranged as a unitary, small world network in which medial and anterior–lateral prefrontal areas featured as hubs, characterized by dense connectivity and high shortest-path centrality. Further analyses revealed that the observed effective connectivity effects were more pertinent to dichotomous gain/loss comparisons than to continuous value determination. Factoring expected value into its constituent components, potential loss modulated connectivity across a subset of the value-sensitive network, whereas potential gain and outcome probability were not significantly embodied in functional interactions. Regional response non-linearity was excluded as an artifactual basis to the observed effects, and directionality inferences were confirmed by comparison of dynamic causal models. Our findings extend current literature demonstrating that the representation of value is dependent on distributed processing taking across a widespread network which feeds information into a limited set of integrative prefrontal nodes. This study also has more general paradigmatic implications for neuroeconomics, demonstrating the value of explicit modeling of inter-regional interactions for understanding the neural substrates of decisional processes