Hierarchical spectral clustering reveals brain size and shape changes in asymptomatic carriers of C9orf72

Supplementary data: fcac182_Supplementary_Data - https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/braincomms/4/4/10.1093_braincomms_fcac182/1/fcac182_supplementary_data.pdf?Expires=1665138780&Signature=oJFozMlNZiAmxd4~XZaq7YKd7waxislas45NEOp9AiZv-fUYr7X~LhZxFgvYXpCVINyQUQrXe0pgrm9L5kv7xdb0LltVuoEOjwb5uVveMyHMfuqTdCBsEzTVZidx9GuuOB79JsHNYHkUZPsXLiU8-lrosrTb3tasr8Mpv31u7ZVZT~4uGdUf06UsIRu7AEn4bfKf64iwudmFr1QyrLJkXMZm0uJ4e5kh8f7k6Xm~rZGqkaiphsQ~Oat4JHssfuCe5Wibgc4m~rMjQeOmutR3R7KicfH4j3xuab1mzCbf-H~~Ed5Yt8mtlMTsyDB3t-8z3dNVaS2aBrwCABvfa3G2yg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA (pdf file).GENFI consortium authors Sónia Afonso, Maria Rosario Almeida, Sarah Anderl-Straub, Christin Andersson, Anna Antonell, Silvana Archetti, Andrea Arighi, Mircea Balasa, Myriam Barandiaran, Nuria Bargalló, Robart Bartha, Benjamin Bender, Alberto Benussi, Sandra Black, Martina Bocchetta, Sergi Borrego-Ecija, Jose Bras, Marta Canada, Valentina Cantoni, Paola Caroppo, David Cash, Miguel Castelo-Branco, Rhian Convery, Thomas Cope, Giuseppe Di Fede, Alina Díez, Diana Duro, Chiara Fenoglio, Catarina B. Ferreira, Nick Fox, Morris Freedman, Giorgio Fumagalli, Alazne Gabilondo, Roberto Gasparotti, Serge Gauthier, Stefano Gazzina, Giorgio Giaccone, Ana Gorostidi, Caroline Greaves, Rita Guerreiro, Carolin Heller, Tobias Hoegen, Begoña Indakoetxea, Vesna Jelic, Lize Jiskoot, Hans-Otto Karnath, Ron Keren, Tobias Langheinrich, Maria João Leitão, Albert Lladó, Sandra Loosli, Carolina Maruta, Simon Mead, Lieke Meeter, Gabriel Miltenberger, Rick van Minkelen, Sara Mitchell, Katrina Moore, Jennifer Nicholas, Linn Öijerstedt, Jaume Olives, Sebastien Ourselin, Alessandro Padovani, Jessica Panman, Janne M. Papma, Georgia Peakman, Yolande Pijnenburg, Enrico Premi, Sara Prioni, Catharina Prix, Rosa Rademakers, Veronica Redaelli, Tim Rittman, Ekaterina Rogaeva, Pedro Rosa-Neto, Giacomina Rossi, Mar tin Rossor, Beatriz Santiago, Elio Scarpini, Sonja Schönecker, Elisa Semler, Rachelle Shafei, Christen Shoesmith, Miguel Tábuas-Pereira, Mikel Tainta, Ricardo Taipa, David Tang-Wai, David L Thomas, Paul Thompson, Hakan Thonberg, Carolyn Timberlake, Pietro Tiraboschi, Emily Todd, Michele Veldsman, Ana Verdelho, Jorge Villanua, Jason Warren, Carlo Wilke, Ione Woollacott, Elisabeth Wlasich, Henrik Zetterberg, Miren ZulaicaCopyright © The Author(s) 2022. Traditional methods for detecting asymptomatic brain changes in neurodegenerative diseases such as Alzheimer’s disease or frontotemporal degeneration typically evaluate changes in volume at a predefined level of granularity, e.g. voxel-wise or in a priori defined cortical volumes of interest. Here, we apply a method based on hierarchical spectral clustering, a graph-based partitioning technique. Our method uses multiple levels of segmentation for detecting changes in a data-driven, unbiased, comprehensive manner within a standard statistical framework. Furthermore, spectral clustering allows for detection of changes in shape along with changes in size. We performed tensor-based morphometry to detect changes in the Genetic Frontotemporal dementia Initiative asymptomatic and symptomatic frontotemporal degeneration mutation carriers using hierarchical spectral clustering and compared the outcome to that obtained with a more conventional voxel-wise tensor- and voxel-based morphometric analysis. In the symptomatic groups, the hierarchical spectral clustering-based method yielded results that were largely in line with those obtained with the voxel-wise approach. In asymptomatic C9orf72 expansion carriers, spectral clustering detected changes in size in medial temporal cortex that voxel-wise methods could only detect in the symptomatic phase. Furthermore, in the asymptomatic and the symptomatic phases, the spectral clustering approach detected changes in shape in the premotor cortex in C9orf72. In summary, the present study shows the merit of hierarchical spectral clustering for data-driven segmentation and detection of structural changes in the symptomatic and asymptomatic stages of monogenic frontotemporal degeneration.KU Leuven’s ‘Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie’

Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes

‡ GENFI investigators are listed at the end of the paper (ORCiD https://orcid.org/0000-0002-9477-1812 ): GENFI authors: In addition to members of GENFI who are co-authors, the following members are collaborators who have contributed to the study design, the recruitment of participants, and the processing of samples at their sites, sending the samples and providing corresponding demographic data of their participants, data analysis, and interpretation: David L. Thomas, Thomas Cope, Timothy Rittman, Alberto Benussi, Enrico Premi, Roberto Gasparotti, Silvana Archetti, Stefano Gazzina, Valentina Cantoni, Andrea Arighi, Chiara Fenoglio, Elio Scarpini, Giorgio Fumagalli, Vittoria Borracci, Giacomina Rossi, Giorgio Giaccone, Giuseppe Di Fede, Paola Caroppo, Pietro Tiraboschi, Sara Prioni, Veronica Radaaelli, David Tang-Wai, Ekaterina Rogaeva, Michel Castelo-Branco, Morris Freedman, Ron Keren, Sandra Black, Sara Mitchell, Christen Shoesmith, Robart Bartha, Rosa Rademakers, Jackie Poos, Janne M. Papma, Lucia Giannini, Rick van Minkelen, Yolande Pijnenburg, Benedetta Nacmias, Camilla Ferrari, Cristina Polito, Gemma Lombardi, Valentina Bessi, Michele Veldsman, Christin Andersson, Hakan Thonberg, Linn Öijerstedt, Vesna Jelic, Paul Thompson, Tobias Langheinrich, Albert Lladó, Anna Antonell, Jaume Olives, Mircea Balasa, Nuria Bargalló, Sergi Borrego-Écija, Ana Verdelho, Carolina Maruta, Catarina B. Ferreira, Gabriel Miltenberger, Frederico Simões do Couto, Alazne Gabilondo, Jorge Villanua, Marta Cañada, Mikel Tainta, Miren Zulaica, Myriam Barandiaran, Patricia Alves, Benjamin Bender, Carlo Wilke, Lisa Graf, Annick Vogels, Mathieu Vandenbulcke, Philip van Damme, Rose Buffaerts, Koen Poesen, Pedro Rosa-Neto, Serge Gauthier, Agnès Camuzat, Alexis Brice, Anne Bertrand, Aurélie Funkiewiez, Daisy Rinaldi, Dario Saracino, Olivier Colliot, Sabrina Sayah, Catharina Prix, Elisabeth Wlasich, Olivia Wagemann, Sandra Loosli, Sonja Schönecker, Tobias Hoegen, Jolina Lombardi, Sarah Anderl-Straub, Adeline Rollin, Gregory Kuchcinski, Maxime Bertoux, Thibaud Lebouvier, Vincent Deramecourt, Beatriz Santiago, Diana Duro, Maria João Leitão, Maria Rosario Almeida, Miguel Tábuas-Pereira, Sónia Afonso.Editor’s summary: Familial frontotemporal dementia (FTD) is caused by mutations in risk genes, most commonly C9orf72, MAPT, or GRN. Here, Sogorb-Esteve et al. used untargeted mass spectrometry of cerebrospinal fluid samples from presymptomatic and symptomatic carriers of these three risk genes to characterize distinct and shared proteomic alterations. Weighted gene coexpression network analysis allowed grouping FTD-dysregulated proteins into modules with high coexpression patterns, highlighting potentially dysregulated biological pathways, such as “core markers,” “synapse,” and “actin binding.” The expression of a subset of these modules was correlated with clinical scores. These results provide a useful resource for FTD research and disease marker development. —Daniela NeuhoferSupplementary Materials are available online at: https://www.science.org/doi/10.1126/scitranslmed.adm9654#supplementary-materials .We used an untargeted mass spectrometric approach, tandem mass tag proteomics, for the identification of proteomic signatures in genetic frontotemporal dementia (FTD). A total of 238 cerebrospinal fluid (CSF) samples from the Genetic FTD Initiative were analyzed, including samples from 107 presymptomatic (44 C9orf72, 38 GRN, and 25 MAPT) and 55 symptomatic (27 C9orf72, 17 GRN, and 11 MAPT) mutation carriers as well as 76 mutation-negative controls (“noncarriers”). We found shared and distinct proteomic alterations in each genetic form of FTD. Among the proteins significantly altered in symptomatic mutation carriers compared with noncarriers, we found that a set of proteins including neuronal pentraxin 2 and fatty acid binding protein 3 changed across all three genetic forms of FTD and patients with Alzheimer’s disease from previously published datasets. We observed differential changes in lysosomal proteins among symptomatic mutation carriers with marked abundance decreases in MAPT carriers but not other carriers. Further, we identified mutation-associated proteomic changes already evident in presymptomatic mutation carriers. Weighted gene coexpression network analysis combined with gene ontology annotation revealed clusters of proteins enriched in neurodegeneration and glial responses as well as synapse- or lysosome-related proteins indicating that these are the central biological processes affected in genetic FTD. These clusters correlated with measures of disease severity and were associated with cognitive decline. This study revealed distinct proteomic changes in the CSF of patients with genetic FTD, providing insights into the pathological processes involved in the disease. In addition, we identified proteins that warrant further exploration as diagnostic and prognostic biomarker candidates.Alzheimer's Association: ADSF-24-1284328-C; Göteborgs Läkaresällskap: GLS-988641; the Bluefield Project; Race Against Dementia: ARUK-RADF2021A-003; Swedish Research Council: 2023-00356; European Union’s Horizon Europe research and innovation programme: 22HLT07; Alzheimerfonden: AF-980746; Stiftelsen för Gamla Tjänarinnor: 2022-01324. This work was supported by a Race Against Dementia fellowship, supported by Alzheimer’s Research UK (ARUK-RADF2021A-003 to A.S.-E.) and 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 (to A.S.-E.). The Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer's Society, Brain Research UK, and the Wolfson Foundation. Coauthors of the manuscript were supported by the Gothenburg Medical Society (Göteborgs Läkaresällskap, #GLS-988641 to J.S.). H.Z. is a Wallenberg scholar and a distinguished professor at the Swedish Research Council supported by grants from the Swedish Research Council (#2023-00356, #2022-01018, and #2019-02397); the European Union’s Horizon Europe research and innovation programme under grant agreement no. 101053962; Swedish State Support for Clinical Research (#ALFGBG-71320); the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862); the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C); the European Partnership on Metrology, cofinanced from the European Union’s Horizon Europe Research and Innovation Programme and by the participating states (NEuroBioStand, #22HLT07); the Bluefield Project; Cure Alzheimer’s Fund; the Olav Thon Foundation; the Erling-Persson Family Foundation; Familjen Rönströms Stiftelse; Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270); the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 860197 (MIRIADE); the European Union Joint Programme—Neurodegenerative Disease Research (JPND2021-00694); the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre; and the UK Dementia Research Institute at UCL (UKDRI-1003). K.B. is supported by the Swedish Research Council (#2017-00915 and #2022-00732); the Swedish Alzheimer Foundation (#AF-930351, #AF-939721, and #AF-968270); Hjärnfonden, Sweden (#FO2017-0243 and #ALZ2022-0006); the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986 and #ALFGBG-965240); the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236); the Alzheimer’s Association 2021 Zenith Award (ZEN-21-848495); and the Alzheimer’s Association 2022-2025 grant (SG-23-1038904 QC). J.C.V.S. was supported by the Dioraphte Foundation grant 09-02-03-00, Association for Frontotemporal Dementias Research Grant 2009, Netherlands Organization for Scientific Research grant HCMI 056-13-018, ZonMw Memorabel (Deltaplan Dementie, project number 733 051 042), Alzheimer Nederland, and the Bluefield Project. F.M. received funding from the Tau Consortium and the Center for Networked Biomedical Research on Neurodegenerative Disease. R.S.-V. is supported by Alzheimer’s Research UK Clinical Research Training Fellowship (ARUK-CRF2017B-2) and has received funding from Fundació Marató de TV3, Spain (grant no. 20143810). D.G. received support from the EU Joint Programme–Neurodegenerative Disease Research and the Italian Ministry of Health (PreFrontALS) grant 733051042. C.G. received funding from EU Joint Programme–Neurodegenerative Disease Research-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. M.M. has received funding from a Canadian Institute of Health Research operating grant and the Weston Brain Institute and Ontario Brain Institute. J.B.R. has received funding from the Wellcome Trust (220258) and the Bluefield Project and is supported by the Cambridge University Centre for Frontotemporal Dementia, the Medical Research Council (MC_UU_00030/14; MR/T033371/1), and the National Institute for Health Research Cambridge Biomedical Research Centre (NIHR203312). E.F. has received funding from a Canadian Institute of Health Research grant #327387. RV has received funding from the Mady Browaeys Fund for Research into Frontotemporal Dementia. J.L. received funding for this work by the Deutsche Forschungsgemeinschaft German Research Foundation under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198). M.O. has received funding from Germany’s Federal Ministry of Education and Research (BMBF). J.D.R. is supported by the Bluefield Project and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and a Miriam Marks Brain Research UK Senior Fellowship. J.G. is supported by Alzheimerfonden (AF-980746) and Stiftelsen för Gamla tjänarinnor (2022-01324). Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases (ERN-RND) - Project ID no. 739510 to J.C.V.S., M.S., R.S.V., A.d.M., M.O., R.V., and J.D.R. This work was also supported by the EU Joint Programme—Neurodegenerative Disease Research GENFI-PROX grant (2019-02248, to J.D.R., M.O., B.B., C.G., J.C.V.S., and M.S.) and by the Clinician Scientist programme “PRECISE.net” funded by the Else Kröner-Fresenius-Stiftung (to M.S.)

Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia

Copyright © The Author(s) 2022. Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome.Canada First Research Excellence Fund, awarded to McGill University for the Healthy Brains for Healthy Lives initiative. B.M. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant RGPIN #017-04265) and from the Canada Research Chairs Program. S.D. receives salary support from the Fonds de Recherche du Québec—Santé (FRQS). G.S. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Fonds de recherche du Québec—Nature et Technologies (FRQNT). V.B. acknowledges support from the Fonds de recherche du Québec—Nature et Technologies (FRQNT). FTLDNI data collection and sharing was funded by the Frontotemporal Lobar Degeneration Neuroimaging Initiative (National Institutes of Health Grant R01 AG032306) and is coordinated through the University of California, San Francisco, Memory and Aging Center. FTLDNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California

Acute extrapyramidal disorder with bilateral reversible basal ganglia lesions in a diabetic uremic patient: diffusion-weighted imaging and spectroscopy findings

Acute movement disorders associated with bilateral lesions in the basal ganglia are increasingly described in patients affected by diabetes and uremia. Pathophysiology has not been utterly understood yet, but it is likely to be multifactorial, with both ischemic/microvascular and metabolic/toxic factors determining the lesions and symptoms. We have studied a uremic diabetic patient who was admitted in emergency after presenting choreic movements, in which CT and MR, including diffusion-weighted imaging and spectroscopy, showed bilateral symmetric basal ganglia lesions with regression at follow-up. This is the first report in the literature describing spectroscopic findings in this condition

New developments in cost modeling for the LHC computing

The increase in the scale of LHC computing during Run 3 and Run 4 (HL-LHC) will certainly require radical changes to the computing models and the data processing of the LHC experiments. The working group established by WLCG and the HEP Software Foundation to investigate all aspects of the cost of computing and how to optimise them has continued producing results and improving our understanding of this process. In particular, experiments have developed more sophisticated ways to calculate their resource needs, we have a much more detailed process to calculate infrastructure costs. This includes studies on the impact of HPC and GPU based resources on meeting the computing demands. We have also developed and perfected tools to quantitatively study the performance of experiments workloads and we are actively collaborating with other activities related to data access, benchmarking and technology cost evolution. In this contribution we expose our recent developments and results and outline the directions of future work