1. A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia
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Ione O.C. Woollacott, Cristina Polito, Philip Van Damme, Mathieu Vandenbulcke, Rose Bruffaerts, Diana Duro, Chiara Fenoglio, David M. Cash, Maria Rosário Almeida, Sonja Schönecker, C. Ferreira, Sónia Afonso, Matthis Synofzik, Sara Prioni, Marta Cañada, Mikel Tainta, Miguel Tábuas-Pereira, Christin Andersson, Caroline Graff, Miguel Castelo-Branco, Enrico Premi, Håkan Thonberg, Fabrizio Tagliavini, Rachelle Shafei, Benjamin Bender, Ana Gorostidi, Maria João Leitão, Jennifer M. Nicholas, Elise G.P. Dopper, Silvana Archetti, Esther E. Bron, Ana Verdelho, Ron Keren, Isabel Santana, Christen Shoesmith, Pietro Tiraboschi, Sergi Borrego-Écija, Michela Pievani, Sandro Sorbi, Rick van Minkelen, Hans-Otto Karnath, Albert Lladó, Caroline V. Greaves, Jaume Olives, Alessandro Padovani, Miren Zulaica, Giuliano Binetti, Martin Rosser, Pedro Rosa-Neto, Vesna Jelic, Alexander Gerhard, Rosa Rademakers, Sandra E. Black, Wiro J. Niessen, Tobias Hoegen, Rhian S Convery, Janne M. Papma, Maria Carmela Tartaglia, Emily Todd, Adrian Danek, Rita Guerreiro, Robart Bartha, Linn Öijerstedt, Giuseppe Di Fede, Sebastien Ourselin, Núria Bargalló, James B. Rowe, Christopher C Butler, Giorgio G. Fumagalli, Valentina Bessi, Alberto Benussi, Nick C. Fox, Beatriz Santiago, Ekaterina Rogaeva, Alazne Gabilondo, Giacomina Rossi, Mircea Balasa, David L. Thomas, Benedetta Nacmias, Veronica Redaelli, Anna Antonell, Vikram Venkatraghavan, Jonathan D. Rohrer, Jackie M. Poos, Yolande A.L. Pijnenburg, Lieke H.H. Meeter, Carlo Wilke, Sandra V. Loosli, Elio Scarpini, Tobias Langheinrich, Alina Díez, Elisa Semler, Elizabeth Finger, Begoña Indakoetxea, Jessica L. Panman, Carolyn Timberlake, Gemma Lombardi, Luisa Benussi, Morris Freedman, Barbara Borroni, Ricardo Taipa, Johannes Levin, Thomas E. Cope, Paul M. Thompson, Giorgio Giaccone, Valentina Cantoni, Arabella Bouzigues, Jose Bras, Serge Gauthier, Andrea Arighi, Stefan Klein, Fermin Moreno, Markus Otto, Georgia Peakman, Emma L. van der Ende, David F. Tang-Wai, Sarah Anderl-Straub, Jason D. Warren, Alexandre de Mendonça, Camilla Ferrari, Elisabeth Wlasich, Catharina Prix, Michele Veldsman, Raquel Sánchez-Valle, Sara Mitchell, Carolina Maruta, Robert Laforce, Paola Caroppo, Jorge Villanua, Imogen J Swift, Harro Seelaar, Henrik Zetterberg, Simon Mead, Simon Ducharme, Myriam Barandiaran, Katrina M. Moore, John C. van Swieten, Gabriel Miltenberger, Mario Masellis, Timothy Rittman, Lize C. Jiskoot, Daniela Galimberti, Rik Vandenberghe, Carolin Heller, Stefano Gazzina, Aitana Sogorb-Esteve, Roberto Gasparotti, Martina Bocchetta, Neurology, Amsterdam Neuroscience - Neurodegeneration, Repositório da Universidade de Lisboa, Radiology & Nuclear Medicine, and Neurosurgery
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Oncology ,medicine.medical_specialty ,Medizin ,tau Proteins ,Disease ,medicine.disease_cause ,frontotemporal dementia ,biomarker ,disease progression model ,event-based modelling ,neurofilament light chain ,Biomarkers ,C9orf72 Protein ,Complement C1q ,Cross-Sectional Studies ,Disease Progression ,Glial Fibrillary Acidic Protein ,Humans ,Longitudinal Studies ,Mutation ,Frontotemporal Dementia ,diagnosis [Frontotemporal Dementia] ,Settore BIO/13 - Biologia Applicata ,C9orf72 ,Internal medicine ,Medicine ,ddc:610 ,genetics [C9orf72 Protein] ,genetics [Frontotemporal Dementia] ,business.industry ,medicine.disease ,Astrogliosis ,genetics [tau Proteins] ,Cohort ,Biomarker (medicine) ,Neurology (clinical) ,Sample collection ,business ,Frontotemporal dementia - Abstract
© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/ by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com, Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions., This study was supported in the Netherlands by two Memorabel grants from Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and Alzheimer Nederland; grant numbers 733050813,733050103 and 733050513), the Bluefield Project to Cure Frontotemporal Dementia, the Dioraphte foundation (grant number 1402 1300), the European Joint Programme—Neurodegenerative Disease Research and the Netherlands Organisation for Health Research and Development (PreFrontALS: 733051042, RiMod-FTD: 733051024); V.V. and S.K. have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 666992 (EuroPOND). E.B. was supported by the Hartstichting (PPP Allowance, 2018B011); in Belgium by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie; in the UK by the MRC UK GENFI grant (MR/M023664/1); J.D.R. 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); I.J.S. is supported by the Alzheimer’s Association; J.B.R. is supported by the Wellcome Trust (103838); in Spain by the Fundació Marató de TV3 (20143810 to R.S.V.); in Germany 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) and by grant 779357 ‘Solve-RD’ from the Horizon 2020 Research and Innovation Programme (to MS); in Sweden by grants from the Swedish FTD Initiative funded by the Schörling Foundation, grants from JPND PreFrontALS Swedish Research Council (VR) 529–2014-7504, Swedish Research Council (VR) 2015–02926, Swedish Research Council (VR) 2018–02754, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Swedish Demensfonden, Stohnes foundation, Gamla Tjänarinnor, Karolinska Institutet Doctoral Funding and StratNeuro. H.Z. is a Wallenberg Scholar.
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- 2022
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