77 research outputs found
Radiation-induced alternative transcription and splicing events and their applicability to practical biodosimetry
Accurate assessment of the individual exposure dose based on easily accessible samples (e.g. blood) immediately following a radiological accident is crucial. We aimed at developing a robust transcription-based signature for biodosimetry from human peripheral blood mononuclear cells irradiated with different doses of X-rays (0.1 and 1.0 Gy) at a dose rate of 0.26 Gy/min. Genome-wide radiation-induced changes in mRNA expression were evaluated at both gene and exon level. Using exon-specific qRT-PCR, we confirmed that several biomarker genes are alternatively spliced or transcribed after irradiation and that different exons of these genes exhibit significantly different levels of induction. Moreover, a significant number of radiation-responsive genes were found to be genomic neighbors. Using three different classification models we found that gene and exon signatures performed equally well on dose prediction, as long as more than 10 features are included. Together, our results highlight the necessity of evaluating gene expression at the level of single exons for radiation biodosimetry in particular and transcriptional biomarker research in general. This approach is especially advisable for practical gene expression-based biodosimetry, for which primer-or probe-based techniques would be the method of choice
Exposure to Ionizing Radiation Triggers Prolonged Changes in Circular RNA Abundance in the Embryonic Mouse Brain and Primary Neurons
The exposure of mouse embryos in utero and primary cortical neurons to ionizing radiation
results in the P53-dependent activation of a subset of genes that is highly induced during brain
development and neuronal maturation, a feature that these genes reportedly share with circular
RNAs (circRNAs). Interestingly, some of these genes are predicted to express circular transcripts.
In this study, we validated the abundance of the circular transcript variants of four P53 target
genes (Pvt1, Ano3, Sec14l5, and Rnf169). These circular variants were overall more stable than
their linear counterparts. They were furthermore highly enriched in the brain and their transcript
levels continuously increase during subsequent developmental stages (from embryonic day 12 until
adulthood), while no further increase could be observed for linear mRNAs beyond post-natal day
30. Finally, whereas radiation-induced expression of P53 target mRNAs peaks early after exposure,
several of the circRNAs showed prolonged induction in irradiated embryonic mouse brain, primary
mouse cortical neurons, and mouse blood. Together, our results indicate that the circRNAs from these
P53 target genes are induced in response to radiation and they corroborate the findings that circRNAs
may represent bioma
Brain Radiation Information Data Exchange (BRIDE): Integration of experimental data from low-dose ionising radiation research for pathway discovery
Background: The underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies. Results: We describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology. Conclusions: BRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at:
The Complete Genome Sequence of Cupriavidus metallidurans Strain CH34, a Master Survivalist in Harsh and Anthropogenic Environments
Many bacteria in the environment have adapted to the presence of toxic heavy metals. Over the last 30 years, this heavy metal tolerance was the subject of extensive research. The bacterium Cupriavidus metallidurans strain CH34, originally isolated by us in 1976 from a metal processing factory, is considered a major model organism in this field because it withstands milli-molar range concentrations of over 20 different heavy metal ions. This tolerance is mostly achieved by rapid ion efflux but also by metal-complexation and -reduction. We present here the full genome sequence of strain CH34 and the manual annotation of all its genes. The genome of C. metallidurans CH34 is composed of two large circular chromosomes CHR1 and CHR2 of, respectively, 3,928,089 bp and 2,580,084 bp, and two megaplasmids pMOL28 and pMOL30 of, respectively, 171,459 bp and 233,720 bp in size. At least 25 loci for heavy-metal resistance (HMR) are distributed over the four replicons. Approximately 67% of the 6,717 coding sequences (CDSs) present in the CH34 genome could be assigned a putative function, and 9.1% (611 genes) appear to be unique to this strain. One out of five proteins is associated with either transport or transcription while the relay of environmental stimuli is governed by more than 600 signal transduction systems. The CH34 genome is most similar to the genomes of other Cupriavidus strains by correspondence between the respective CHR1 replicons but also displays similarity to the genomes of more distantly related species as a result of gene transfer and through the presence of large genomic islands. The presence of at least 57 IS elements and 19 transposons and the ability to take in and express foreign genes indicates a very dynamic and complex genome shaped by evolutionary forces. The genome data show that C. metallidurans CH34 is particularly well equipped to live in extreme conditions and anthropogenic environments that are rich in metals
Surgical management of Diabetic foot ulcers: A Tanzanian university teaching hospital experience
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Diabetic foot ulcers (DFUs) pose a therapeutic challenge to surgeons, especially in developing countries where health care resources are limited and the vast majority of patients present to health facilities late with advanced foot ulcers. A prospective descriptive study was done at Bugando Medical Centre from February 2008 to January 2010 to describe our experience in the surgical management of DFUs in our local environment and compare with what is known in the literature. Of the total 4238 diabetic patients seen at BMC during the period under study, 136 (3.2%) patients had DFUs. Males outnumbered females by the ratio of 1.2:1. Their mean age was 54.32 years (ranged 21-72years). Thirty-eight (27.9%) patients were newly diagnosed diabetic patients. The majority of patients (95.5%) had type 2 diabetes mellitus. The mean duration of diabetes was 8.2 years while the duration of DFUs was 18.34 weeks. Fourteen (10.3%) patients had previous history of foot ulcers and six (4.4%) patients had previous amputations. The forefoot was commonly affected in 60.3% of cases. Neuropathic ulcers were the most common type of DFUs in 57.4% of cases. Wagner's stage 4 and 5 ulcers were the most prevalent at 29.4% and 23.5% respectively. The majority of patients (72.1%) were treated surgically. Lower limb amputation was the most common surgical procedure performed in 56.7% of cases. The complication rate was (33.5%) and surgical site infection was the most common complication (18.8%). Bacterial profile revealed polymicrobial pattern and Staphylococcus aureus was the most frequent microorganism isolated. All the microorganisms isolated showed high resistance to commonly used antibiotics except for Meropenem and imipenem, which were 100% sensitive each respectively. The mean hospital stay was 36.24 ± 12.62 days (ranged 18-128 days). Mortality rate was 13.2%. Diabetic foot ulceration constitutes a major source of morbidity and mortality among patients with diabetes mellitus at Bugando Medical Centre and is the leading cause of non-traumatic lower limb amputation. A multidisciplinary team approach targeting at good glycaemic control, education on foot care and appropriate footware, control of infection and early surgical intervention is required in order to reduce the morbidity and mortality associated with DFUs. Due to polymicrobial infection and antibiotic resistance, surgical intervention must be concerned
De-Novo Discovery of Differentially Abundant Transcription Factor Binding Sites Including Their Positional Preference
Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open-source Java framework Jstacs and as a stand-alone application at http://www.jstacs.de/index.php/Dispom
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Language impairment in the genetic forms of behavioural variant frontotemporal dementia
Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.Copyright © The Author(s) 2022. Background:
Behavioural variant fronto-temporal dementia (bvFTD) is characterised by a progressive change in personality in association with atrophy of the frontal and temporal lobes. Whilst language impairment has been described in people with bvFTD, little is currently known about the extent or type of linguistic difficulties that occur, particularly in the genetic forms.
Methods:
Participants with genetic bvFTD along with healthy controls were recruited from the international multicentre Genetic FTD Initiative (GENFI). Linguistic symptoms were assessed using items from the Progressive Aphasia Severity Scale (PASS). Additionally, participants undertook the Boston Naming Test (BNT), modified Camel and Cactus Test (mCCT) and a category fluency test. Participants underwent a 3T volumetric T1-weighted MRI, with language network regional brain volumes measured and compared between the genetic groups and controls.
Results:
76% of the genetic bvFTD cohort had impairment in at least one language symptom: 83% C9orf72, 80% MAPT and 56% GRN mutation carriers. All three genetic groups had significantly impaired functional communication, decreased fluency, and impaired sentence comprehension. C9orf72 mutation carriers also had significantly impaired articulation and word retrieval as well as dysgraphia whilst the MAPT mutation group also had impaired word retrieval and single word comprehension. All three groups had difficulties with naming, semantic knowledge and verbal fluency. Atrophy in key left perisylvian language regions differed between the groups, with generalised involvement in the C9orf72 group and more focal temporal and insula involvement in the other groups. Correlates of language symptoms and test scores also differed between the groups.
Conclusions:
Language deficits exist in a substantial proportion of people with familial bvFTD across all three genetic groups. Significant atrophy is seen in the dominant perisylvian language areas and correlates with language impairments within each of the genetic groups. Improved understanding of the language phenotype in the main genetic bvFTD subtypes will be helpful in future studies, particularly in clinical trials where accurate stratification and monitoring of disease progression is required.We thank the research participants and their families for their contribution to the study. Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases—Project ID No 739510. The Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer’s Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the NIHR UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility, and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer’s Research UK. This work was also supported by the JPND GENFI-PROX grant (2019-02248; to JDR, MO, BB, CG, JvS and MS. [latter via DLR/DFG 01ED2008B]). JDR is supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). This work was also supported by the MRC UK GENFI grant (MR/M023664/1), the Bluefield Project and the JPND GENFI-PROX grant (2019-02248). Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases—Project ID No 739510. RC/CG are supported by a Frontotemporal Dementia Research Studentships in Memory of David Blechner funded through The National Brain Appeal (RCN 290173). MB is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). MB’s work is also supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. JCVS was supported by the Dioraphte Foundation grant 09-02-03-00, the Association for Frontotemporal Dementias Research Grant 2009, The Netherlands Organization for Scientific Research (NWO) grant HCMI 056-13-018, ZonMw Memorabel (Deltaplan Dementie, project number 733 051 042), Alzheimer Nederland and the Bluefield project. FM received funding from the Tau Consortium and the Center for Networked Biomedical Research on Neurodegenerative Disease (CIBERNED). RS-V is supported by an Alzheimer’s Research UK Clinical Research Training Fellowship (ARUK-CRF2017B-2), and has received funding from Fundació Marató de TV3, Spain (grant no. 20143810). CG received funding from JPND-Prefrontals VR Dnr 529-2014-7504, VR 2015-02926 and 2018-02754, the Swedish FTD Inititative-Schörling Foundation, Alzheimer Foundation, Brain Foundation and Stockholm County Council ALF. MM has received funding from a Canadian Institute of Health Research operating grant and the Weston Brain Institute and Ontario Brain Institute. JBR has received funding from the Welcome Trust (103838) and is supported by the Cambridge University Centre for Frontotemporal Dementia, the Medical Research Council (SUAG/051 G101400) and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014). EF has received funding from a CIHR grant #327387. DG received support from the EU Joint Programme—Neurodegenerative Disease Research (JPND) and the Italian Ministry of Health (PreFrontALS) grant 733051042. RV has received funding from the Mady Browaeys Fund for Research into Frontotemporal Dementia. MO has received funding from BMBF (FTLDc). JL received funding for this work by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198). Group authorship for the Genetic FTD Initiative (GENFI): Annabel Nelson: Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK. David L Thomas: Neuroimaging Analysis Centre, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, Queen Square, London, UK. Emily Todd: Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK. Hanya Benotmane: UK Dementia Research Institute at University College London, UCL Queen Square Institute of Neurology, London, UK. Jennifer Nicholas: Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK. Rachelle Shafei: Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK. Carolyn Timberlake: Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. Thomas Cope: Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK. Timothy Rittman: Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. Alberto Benussi: Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy. Enrico Premi: Stroke Unit, ASST Brescia Hospital, Brescia, Italy. Roberto Gasparotti: Neuroradiology Unit, University of Brescia, Brescia, Italy. Silvana Archetti: Biotechnology Laboratory, Department of Diagnostics, ASST Brescia Hospital, Brescia, Italy. Stefano Gazzina: Neurology, ASST Brescia Hospital, Brescia, Italy. Valentina Cantoni: Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy. Andrea Arighi: Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy. Chiara Fenoglio: Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy. Elio Scarpini: Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy. Giorgio Fumagalli: Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy. Vittoria Borracci: Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy. Giacomina Rossi: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. Giorgio Giaccone: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. Giuseppe Di Fede: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. Paola Caroppo: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. Pietro Tiraboschi: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. Sara Prioni: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. Veronica Redaelli: Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy. David Tang-Wai: The University Health Network, Krembil Research Institute, Toronto, Canada. Ekaterina Rogaeva: Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada. Miguel Castelo-Branco: Faculty of Medicine, University of Coimbra, Coimbra, Portugal. Morris Freedman: Baycrest Health Sciences, Rotman Research Institute, University of Toronto, Toronto, Canada. Ron Keren: The University Health Network, Toronto Rehabilitation Institute, Toronto, Canada. Sandra Black: Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada. Sara Mitchell: Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada. Christen Shoesmith: Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada. Robart Bartha: Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada; Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada. Rosa Rademakers: Center for Molecular Neurology, University of Antwerp. Jackie Poos: Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands. Janne M. Papma: Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands. Lucia Giannini: Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands. Rick van Minkelen: Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands. Yolande Pijnenburg: Amsterdam University Medical Centre, Amsterdam VUmc, Amsterdam, Netherlands. Benedetta Nacmias: Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy. Camilla Ferrari: Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy. Cristina Polito: Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, Nuclear Medicine Unit, University of Florence, Florence, Italy. Gemma Lombardi: Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy. Valentina Bessi: Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy. Michele Veldsman: Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK. Christin Andersson: Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. Hakan Thonberg: Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden. Linn Öijerstedt: Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet, Solna, Sweden; Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden. Vesna Jelic: Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden. Paul Thompson: Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK. Tobias Langheinrich: Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK; Manchester Centre for Clinical Neurosciences, Department of Neurology, Salford Royal NHS Foundation Trust, Manchester, UK. Albert Lladó: Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain. Anna Antonell: Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain. Jaume Olives: Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain. Mircea Balasa: Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain. Nuria Bargalló: Imaging Diagnostic Center, Hospital Clínic, Barcelona, Spain. Sergi Borrego-Ecija: Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain. Ana Verdelho: Department of Neurosciences and Mental Health, Centro Hospitalar Lisboa Norte—Hospital de Santa Maria & Faculty of Medicine, University of Lisbon, Lisbon, Portugal. Carolina Maruta: Laboratory of Language Research, Centro de Estudos Egas Moniz, Faculty of Medicine, University of Lisbon, Lisbon, Portugal. Catarina B. Ferreira: Laboratory of Neurosciences, Faculty of Medicine, University of Lisbon, Lisbon, Portugal. Gabriel Miltenberger: Faculty of Medicine, University of Lisbon, Lisbon, Portugal. Frederico Simões do Couto: Faculdade de Medicina, Universidade Católica Portuguesa. Alazne Gabilondo: Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain; Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain. Ana Gorostidi: Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain. Jorge Villanua: OSATEK, University of Donostia, San Sebastian, Gipuzkoa, Spain. Marta Cañada: CITA Alzheimer, San Sebastian, Gipuzkoa, Spain. Mikel Tainta: Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain. Miren Zulaica: Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain. Myriam Barandiaran: Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain; Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain. Patricia Alves: Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain; Department of Educational Psychology and Psychobiology, Faculty of Education, International University of La Rioja, Logroño, Spain. Benjamin Bender: Department of Diagnostic and Interventional Neuroradiology, University of Tübingen, Tübingen, Germany. Carlo Wilke: Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany; Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany. Lisa Graf: Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany. Annick Vogels: Department of Human Genetics, KU Leuven, Leuven, Belgium. Mathieu Vandenbulcke: Geriatric Psychiatry Service, University Hospitals Leuven, Belgium; Neuropsychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium. Philip Van Damme: Neurology Service, University Hospitals Leuven, Belgium; Laboratory for Neurobiology, VIB-KU Leuven Centre for Brain Research, Leuven, Belgium. Rose Bruffaerts: Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium; Biomedical Research Institute, Hasselt University, 3500 Hasselt, Belgium. Koen Poesen: Laboratory for Molecular Neurobiomarker Research, KU Leuven, Leuven, Belgium. Pedro Rosa-Neto: Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, Québec, Canada. Serge Gauthier: Alzheimer Disease Research Unit, McGill Centre for Studies in Aging, Department of Neurology & Neurosurgery, McGill University, Montreal, Québec, Canada. Agnès Camuzat: Sorbonne Université, Paris Brain Institute—Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France. Alexis Brice: Sorbonne Université, Paris Brain Institute—Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Reference Network for Rare Neurological Diseases (ERN-RND). Anne Bertrand: Sorbonne Université, Paris Brain Institute—Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Inria, Aramis project-team, F-75013, Paris, France; Centre pour l'Acquisition et le Traitement des Images, Institut du Cerveau et la Moelle, Paris, France. Aurélie Funkiewiez: Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Sorbonne Université, Paris Brain Institute – Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France. Daisy Rinaldi: Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Sorbonne Université, Paris Brain Institute—Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Département de Neurologie, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France. Dario Saracino: Sorbonne Université, Paris Brain Institute – Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Inria, Aramis project-team, F-75013, Paris, France; Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France. Olivier Colliot: Sorbonne Université, Paris Brain Institute—Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France; Inria, Aramis project-team, F-75013, Paris, France; Centre pour l'Acquisition et le Traitement des Images, Institut du Cerveau et la Moelle, Paris, France. Sabrina Sayah: Sorbonne Université, Paris Brain Institute—Institut du Cerveau—ICM, Inserm U1127, CNRS UMR 7225, AP-HP—Hôpital Pitié-Salpêtrière, Paris, France. Catharina Prix: Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany. Elisabeth Wlasich: Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany. Olivia Wagemann: Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany. Sandra Loosli: Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany. Sonja Schönecker: Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany. Tobias Hoegen: Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany. Jolina Lombardi: Department of Neurology, University of Ulm, Ulm. Sarah Anderl-Straub: Department of Neurology, University of Ulm, Ulm, Germany. Adeline Rollin: CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France. Gregory Kuchcinski: Univ Lille, France; Inserm 1172, Lille, France; CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France. Maxime Bertoux: Inserm 1172, Lille, France; CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France. Thibaud Lebouvier: Univ Lille, France; Inserm 1172, Lille, France; CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France. Vincent Deramecourt: Univ Lille, France; Inserm 1172, Lille, France; CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France. Beatriz Santiago: Neurology Department, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal. Diana Duro: Faculty of Medicine, University of Coimbra, Coimbra, Portugal. Maria João Leitão: Centre of Neurosciences and Cell Biology, Universidade de Coimbra, Coimbra, Portugal. Maria Rosario Almeida: Faculty of Medicine, University of Coimbra, Coimbra, Portugal. Miguel Tábuas-Pereira: Neurology Department, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal. Sónia Afonso: Instituto Ciencias Nucleares Aplicadas a Saude, Universidade de Coimbra, Coimbra, Portugal
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Motor symptoms in genetic frontotemporal dementia: developing a new module for clinical rating scales
Objective
To investigate the optimal method of adding motor features to a clinical rating scale for frontotemporal dementia (FTD).
Methods
Eight hundred and thirty-two participants from the international multicentre Genetic FTD Initiative (GENFI) study were recruited: 522 mutation carriers (with C9orf72, GRN and MAPT mutations) and 310 mutation-negative controls. A standardised clinical questionnaire was used to assess eight motor symptoms (dysarthria, dysphagia, tremor, slowness, weakness, gait disorder, falls and functional difficulties using hands). Frequency and severity of each motor symptom was assessed, and a principal component analysis (PCA) was performed to identify how the different motor symptoms loaded together. Finally, addition of a motor component to the CDR® plus NACC FTLD was investigated (CDR® plus NACC FTLD-M).
Results
24.3% of mutation carriers had motor symptoms (31.7% C9orf72, 18.8% GRN, 19.3% MAPT) compared to 6.8% of controls. Slowness and gait disorder were the commonest in all genetic groups while tremor and falls were the least frequent. Symptom severity scores were similar to equivalent physical motor examination scores. PCA revealed that all motor symptoms loaded together so a single additional motor component was added to the CDR® plus NACC FTLD to form the CDR® plus NACC FTLD-M. Individual global scores were more severe with the CDR® plus NACC FTLD-M, and no patients with a clinically diagnosed motor disorder (ALS/FTD-ALS or parkinsonism) were classified anymore as asymptomatic (unlike the CDR® plus NACC FTLD alone).
Conclusions
Motor features are present in mutation carriers at all disease stages across all three genetic groups. Inclusion of motor symptoms in a rating scale that can be used in future clinical trials will not only ensure a more accurate severity measure is recorded but that a wider spectrum of FTD phenotypes can be included in the same trial.National Institute for Health Research (NIHR) Queen Square Dementia Biomedical Research Unit and the University College London Hospitals Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility, and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. This work was also supported by the MRC UK GENFI grant (MR/M023664/1), the Italian Ministry of Health (CoEN015 and Ricerca Corrente), the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant, the Alzheimer's Society grant (AS-PG-16-007), the Bluefield Project and the JPND GENFI-PROX grant (2019-02248). MB is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). MB’s work was also supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. JDR is supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). JBR is funded by the Wellcome Trust (103838) and the National Institute for Health Research Cambridge Biomedical Research Centre. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198). RV’s work is supported by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie. Several authors of this publication (JCvS, MS, RSV, AD, MO, RV, JDR) are members of the European Reference Network for Rare Neurological Diseases (ERN-RND)—Project ID No 739510
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Differential impairment of cerebrospinal fluid synaptic biomarkers in the genetic forms of frontotemporal dementia
Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.Copyright © The Author(s) 2022. Background:
Approximately a third of frontotemporal dementia (FTD) is genetic with mutations in three genes accounting for most of the inheritance: C9orf72, GRN, and MAPT. Impaired synaptic health is a common mechanism in all three genetic variants, so developing fluid biomarkers of this process could be useful as a readout of cellular dysfunction within therapeutic trials.
Methods:
A total of 193 cerebrospinal fluid (CSF) samples from the GENetic FTD Initiative including 77 presymptomatic (31 C9orf72, 23 GRN, 23 MAPT) and 55 symptomatic (26 C9orf72, 17 GRN, 12 MAPT) mutation carriers as well as 61 mutation-negative controls were measured using a microflow LC PRM-MS set-up targeting 15 synaptic proteins: AP-2 complex subunit beta, complexin-2, beta-synuclein, gamma-synuclein, 14–3-3 proteins (eta, epsilon, zeta/delta), neurogranin, Rab GDP dissociation inhibitor alpha (Rab GDI alpha), syntaxin-1B, syntaxin-7, phosphatidylethanolamine-binding protein 1 (PEBP-1), neuronal pentraxin receptor (NPTXR), neuronal pentraxin 1 (NPTX1), and neuronal pentraxin 2 (NPTX2). Mutation carrier groups were compared to each other and to controls using a bootstrapped linear regression model, adjusting for age and sex.
Results:
CSF levels of eight proteins were increased only in symptomatic MAPT mutation carriers (compared with controls) and not in symptomatic C9orf72 or GRN mutation carriers: beta-synuclein, gamma-synuclein, 14–3-3-eta, neurogranin, Rab GDI alpha, syntaxin-1B, syntaxin-7, and PEBP-1, with three other proteins increased in MAPT mutation carriers compared with the other genetic groups (AP-2 complex subunit beta, complexin-2, and 14–3-3 zeta/delta). In contrast, CSF NPTX1 and NPTX2 levels were affected in all three genetic groups (decreased compared with controls), with NPTXR concentrations being affected in C9orf72 and GRN mutation carriers only (decreased compared with controls). No changes were seen in the CSF levels of these proteins in presymptomatic mutation carriers. Concentrations of the neuronal pentraxins were correlated with brain volumes in the presymptomatic period for the C9orf72 and GRN groups, suggesting that they become abnormal in proximity to symptom onset.
Conclusions:
Differential synaptic impairment is seen in the genetic forms of FTD, with abnormalities in multiple measures in those with MAPT mutations, but only changes in neuronal pentraxins within the GRN and C9orf72 mutation groups. Such markers may be useful in future trials as measures of synaptic dysfunction, but further work is needed to understand how these markers change throughout the course of the disease.NIHR UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility, and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd., funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK
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Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia
Copyright © 2022 The Authors. Introduction
We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD).
Methods
For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression.
Results:
We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants.
Discussion:
Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion.
Highlights:
1. We investigated brain network predictors of dementia symptom onset.
2. Frontotemporal dementia results in characteristic dynamic network patterns.
3. Alterations in network dynamics are associated with neuropsychological impairment.
4. Network dynamic changes predict symptomatic conversion in presymptomatic carriers.
5. Network dynamic changes are associated with longitudinal cognitive decline.Medical Research Council UK. Grant Numbers: MR/M023664/1, SUAG/092116768
JPND GENFI-PROX. Grant Number: DLR/BMBF 2019-02248
Munich Cluster for Systems Neurology. Grant Number: 390857198
National Institute for Health Research (NIHR) Biomedical Research Centre at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge. Grant Number: BRC-1215-20014
Cambridge Centre for Parkinson-plus. Grant Number: RG95450
Wellcome Trust. Grant Number: 22025
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