A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

Emma L. van der Ende; Esther E. Bron; Jackie M. Poos; Lize C. Jiskoot; Jessica L. Panman; Janne M. Papma; Lieke H. Meeter; Elise G.P. Dopper; Carlo Wilke; Matthis Synofzik; Carolin Heller; Imogen J. Swift; Aitana Sogorb-Esteve; Arabella Bouzigues; Barbara Borroni; Raquel Sanchez-Valle; Fermin Moreno; Caroline Graff; Robert Laforce; Daniela Galimberti; Mario Masellis; Maria Carmela Tartaglia; Elizabeth Finger; Rik Vandenberghe; James B. Rowe; Alexandre De Mendoncą; Fabrizio Tagliavini; Isabel Santana; Simon Ducharme; Christopher R. Butler; Alexander Gerhard; Johannes Levin; Adrian Danek; Markus Otto; Yolande A.L. Pijnenburg; Sandro Sorbi; Henrik Zetterberg; Wiro J. Niessen; Jonathan D. Rohrer; Stefan Klein; John C. Van Swieten; Vikram Venkatraghavan; Harro Seelaar; 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; Luisa Benussi; Valentina Bessi; Giuliano Binetti; Sandra Black; Martina Bocchetta; Sergi Borrego-Ecija; Jose Bras; Rose Bruffaerts; Marta Canãda; Valentina Cantoni; Paola Caroppo; David Cash; Miguel Castelo-Branco; Rhian Convery; Thomas Cope; Giuseppe Di Fede; Alina Diéz; Diana Duro; Chiara Fenoglio; Camilla Ferrari; 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; Tobias Hoegen; Begonã Indakoetxea; Vesna Jelic; Hans Otto Karnath; Ron Keren; Tobias Langheinrich; Maria Joaõ Leitaõ; Albert Lladó; Gemma Lombardi; Sandra Loosli; Carolina Maruta; Simon Mead; Gabriel Miltenberger; Rick Van Minkelen; Sara Mitchell; Katrina Moore; Benedetta Nacmias; Jennifer Nicholas; Linn Oïjerstedt; Jaume Olives; Sebastien Ourselin; Alessandro Padovani; Georgia Peakman; Michela Pievani; Cristina Polito; Enrico Premi; Sara Prioni; Catharina Prix; Rosa Rademakers; Veronica Redaelli; Tim Rittman; Ekaterina Rogaeva; Pedro Rosa-Neto; Giacomina Rossi; Martin Rosser; 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; Philip Van Damme; Mathieu Vandenbulcke; Michele Veldsman; Ana Verdelho; Jorge Villanua; Jason Warren; Ione Woollacott; Elisabeth Wlasich; Miren Zulaica

doi:10.1093/brain/awab382

A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

Emma L. van der Ende, Esther E. Bron, Jackie M. Poos, Lize C. Jiskoot, Jessica L. Panman, Janne M. Papma, Lieke H. Meeter, Elise G.P. Dopper, Carlo Wilke, Matthis Synofzik, Carolin Heller, Imogen J. Swift, Aitana Sogorb-Esteve, Arabella Bouzigues, Barbara Borroni, Raquel Sanchez-Valle, Fermin Moreno, Caroline Graff, Robert Laforce, Daniela GalimbertiMario Masellis, Maria Carmela Tartaglia, Elizabeth Finger, Rik Vandenberghe, James B. Rowe, Alexandre De Mendoncą, Fabrizio Tagliavini, Isabel Santana, Simon Ducharme, Christopher R. Butler, Alexander Gerhard, Johannes Levin, Adrian Danek, Markus Otto, Yolande A.L. Pijnenburg, Sandro Sorbi, Henrik Zetterberg, Wiro J. Niessen, Jonathan D. Rohrer, Stefan Klein, John C. Van Swieten, Vikram Venkatraghavan, Harro Seelaar^*, 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, Luisa Benussi, Valentina Bessi, Giuliano Binetti, Sandra Black, Martina Bocchetta, Sergi Borrego-Ecija, Jose Bras, Rose Bruffaerts, Marta Canãda, Valentina Cantoni, Paola Caroppo, David Cash, Miguel Castelo-Branco, Rhian Convery, Thomas Cope, Giuseppe Di Fede, Alina Diéz, Diana Duro, Chiara Fenoglio, Camilla Ferrari, 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, Tobias Hoegen, Begonã Indakoetxea, Vesna Jelic, Hans Otto Karnath, Ron Keren, Tobias Langheinrich, Maria Joaõ Leitaõ, Albert Lladó, Gemma Lombardi, Sandra Loosli, Carolina Maruta, Simon Mead, Gabriel Miltenberger, Rick Van Minkelen, Sara Mitchell, Katrina Moore, Benedetta Nacmias, Jennifer Nicholas, Linn Oïjerstedt, Jaume Olives, Sebastien Ourselin, Alessandro Padovani, Georgia Peakman, Michela Pievani, Cristina Polito, Enrico Premi, Sara Prioni, Catharina Prix, Rosa Rademakers, Veronica Redaelli, Tim Rittman, Ekaterina Rogaeva, Pedro Rosa-Neto, Giacomina Rossi, Martin Rosser, 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, Philip Van Damme, Mathieu Vandenbulcke, Michele Veldsman, Ana Verdelho, Jorge Villanua, Jason Warren, Ione Woollacott, Elisabeth Wlasich, Miren Zulaica

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

27 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	1805-1817
Number of pages	13
Journal	Brain
Volume	145
Issue number	5
DOIs	https://doi.org/10.1093/brain/awab382
Publication status	Published - 1 May 2022
Externally published	Yes

Keywords

Biomarker
Disease progression model
Event-based modelling
Frontotemporal dementia
Neurofilament light chain

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10.1093/brain/awab382Licence: CC BY-NC

Cite this

Ende, E. L. V. D., Bron, E. E., Poos, J. M., Jiskoot, L. C., Panman, J. L., Papma, J. M., Meeter, L. H., Dopper, E. G. P., Wilke, C., Synofzik, M., Heller, C., Swift, I. J., Sogorb-Esteve, A., Bouzigues, A., Borroni, B., Sanchez-Valle, R., Moreno, F., Graff, C., Laforce, R., ... Zulaica, M. (2022). A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia. Brain, 145(5), 1805-1817. https://doi.org/10.1093/brain/awab382

@article{aceff7fd0ac04a0baa1ff1b033af1cdc,

title = "A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia",

abstract = "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.",

keywords = "Biomarker, Disease progression model, Event-based modelling, Frontotemporal dementia, Neurofilament light chain",

author = "Ende, {Emma L. van der} and Bron, {Esther E.} and Poos, {Jackie M.} and Jiskoot, {Lize C.} and Panman, {Jessica L.} and Papma, {Janne M.} and Meeter, {Lieke H.} and Dopper, {Elise G.P.} and Carlo Wilke and Matthis Synofzik and Carolin Heller and Swift, {Imogen J.} and Aitana Sogorb-Esteve and Arabella Bouzigues and Barbara Borroni and Raquel Sanchez-Valle and Fermin Moreno and Caroline Graff and Robert Laforce and Daniela Galimberti and Mario Masellis and Tartaglia, {Maria Carmela} and Elizabeth Finger and Rik Vandenberghe and Rowe, {James B.} and {De Mendonc{\c a}}, Alexandre and Fabrizio Tagliavini and Isabel Santana and Simon Ducharme and Butler, {Christopher R.} and Alexander Gerhard and Johannes Levin and Adrian Danek and Markus Otto and Pijnenburg, {Yolande A.L.} and Sandro Sorbi and Henrik Zetterberg and Niessen, {Wiro J.} and Rohrer, {Jonathan D.} and Stefan Klein and {Van Swieten}, {John C.} and Vikram Venkatraghavan and Harro Seelaar and S{\'o}nia Afonso and Almeida, {Maria Rosario} and Sarah Anderl-Straub and Christin Andersson and Anna Antonell and Silvana Archetti and Andrea Arighi and Mircea Balasa and Myriam Barandiaran and Nuria Bargall{\'o} and Robart Bartha and Benjamin Bender and Alberto Benussi and Luisa Benussi and Valentina Bessi and Giuliano Binetti and Sandra Black and Martina Bocchetta and Sergi Borrego-Ecija and Jose Bras and Rose Bruffaerts and Marta Can{\~a}da and Valentina Cantoni and Paola Caroppo and David Cash and Miguel Castelo-Branco and Rhian Convery and Thomas Cope and {Di Fede}, Giuseppe and Alina Di{\'e}z and Diana Duro and Chiara Fenoglio and Camilla Ferrari and Ferreira, {Catarina B.} and Nick Fox and Morris Freedman and Giorgio Fumagalli and Alazne Gabilondo and Roberto Gasparotti and Serge Gauthier and Stefano Gazzina and Giorgio Giaccone and Ana Gorostidi and Caroline Greaves and Rita Guerreiro and Tobias Hoegen and Begon{\~a} Indakoetxea and Vesna Jelic and Karnath, {Hans Otto} and Ron Keren and Tobias Langheinrich and Leita{\~o}, {Maria Joa{\~o}} and Albert Llad{\'o} and Gemma Lombardi and Sandra Loosli and Carolina Maruta and Simon Mead and Gabriel Miltenberger and {Van Minkelen}, Rick and Sara Mitchell and Katrina Moore and Benedetta Nacmias and Jennifer Nicholas and Linn O{\"i}jerstedt and Jaume Olives and Sebastien Ourselin and Alessandro Padovani and Georgia Peakman and Michela Pievani and Cristina Polito and Enrico Premi and Sara Prioni and Catharina Prix and Rosa Rademakers and Veronica Redaelli and Tim Rittman and Ekaterina Rogaeva and Pedro Rosa-Neto and Giacomina Rossi and Martin Rosser and Beatriz Santiago and Elio Scarpini and Sonja Sch{\"o}necker and Elisa Semler and Rachelle Shafei and Christen Shoesmith and Miguel T{\'a}buas-Pereira and Mikel Tainta and Ricardo Taipa and David Tang-Wai and Thomas, {David L.} and Paul Thompson and Hakan Thonberg and Carolyn Timberlake and Pietro Tiraboschi and Emily Todd and {Van Damme}, Philip and Mathieu Vandenbulcke and Michele Veldsman and Ana Verdelho and Jorge Villanua and Jason Warren and Ione Woollacott and Elisabeth Wlasich and Miren Zulaica",

note = "Publisher Copyright: {\textcopyright} 2021 The Author(s). Published by Oxford University Press on behalf of the Guarantors of Brain.",

year = "2022",

month = may,

day = "1",

doi = "10.1093/brain/awab382",

language = "English",

volume = "145",

pages = "1805--1817",

journal = "Brain",

issn = "0006-8950",

publisher = "Oxford University Press",

number = "5",

}

Ende, ELVD, Bron, EE, Poos, JM, Jiskoot, LC, Panman, JL, Papma, JM, Meeter, LH, Dopper, EGP, Wilke, C, Synofzik, M, Heller, C, Swift, IJ, Sogorb-Esteve, A, Bouzigues, A, Borroni, B, Sanchez-Valle, R, Moreno, F, Graff, C, Laforce, R, Galimberti, D, Masellis, M, Tartaglia, MC, Finger, E, Vandenberghe, R, Rowe, JB, De Mendoncą, A, Tagliavini, F, Santana, I, Ducharme, S, Butler, CR, Gerhard, A, Levin, J, Danek, A, Otto, M, Pijnenburg, YAL, Sorbi, S, Zetterberg, H, Niessen, WJ, Rohrer, JD, Klein, S, Van Swieten, JC, Venkatraghavan, V, Seelaar, H, Afonso, S, Almeida, MR, Anderl-Straub, S, Andersson, C, Antonell, A, Archetti, S, Arighi, A, Balasa, M, Barandiaran, M, Bargalló, N, Bartha, R, Bender, B, Benussi, A, Benussi, L, Bessi, V, Binetti, G, Black, S, Bocchetta, M, Borrego-Ecija, S, Bras, J, Bruffaerts, R, Canãda, M, Cantoni, V, Caroppo, P, Cash, D, Castelo-Branco, M, Convery, R, Cope, T, Di Fede, G, Diéz, A, Duro, D, Fenoglio, C, Ferrari, C, Ferreira, CB, Fox, N, Freedman, M, Fumagalli, G, Gabilondo, A, Gasparotti, R, Gauthier, S, Gazzina, S, Giaccone, G, Gorostidi, A, Greaves, C, Guerreiro, R, Hoegen, T, Indakoetxea, B, Jelic, V, Karnath, HO, Keren, R, Langheinrich, T, Leitaõ, MJ, Lladó, A, Lombardi, G, Loosli, S, Maruta, C, Mead, S, Miltenberger, G, Van Minkelen, R, Mitchell, S, Moore, K, Nacmias, B, Nicholas, J, Oïjerstedt, L, Olives, J, Ourselin, S, Padovani, A, Peakman, G, Pievani, M, Polito, C, Premi, E, Prioni, S, Prix, C, Rademakers, R, Redaelli, V, Rittman, T, Rogaeva, E, Rosa-Neto, P, Rossi, G, Rosser, M, Santiago, B, Scarpini, E, Schönecker, S, Semler, E, Shafei, R, Shoesmith, C, Tábuas-Pereira, M, Tainta, M, Taipa, R, Tang-Wai, D, Thomas, DL, Thompson, P, Thonberg, H, Timberlake, C, Tiraboschi, P, Todd, E, Van Damme, P, Vandenbulcke, M, Veldsman, M, Verdelho, A, Villanua, J, Warren, J, Woollacott, I, Wlasich, E & Zulaica, M 2022, 'A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia', Brain, vol. 145, no. 5, pp. 1805-1817. https://doi.org/10.1093/brain/awab382

TY - JOUR

T1 - A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

AU - Ende, Emma L. van der

AU - Bron, Esther E.

AU - Poos, Jackie M.

AU - Jiskoot, Lize C.

AU - Panman, Jessica L.

AU - Papma, Janne M.

AU - Meeter, Lieke H.

AU - Dopper, Elise G.P.

AU - Wilke, Carlo

AU - Synofzik, Matthis

AU - Heller, Carolin

AU - Swift, Imogen J.

AU - Sogorb-Esteve, Aitana

AU - Bouzigues, Arabella

AU - Borroni, Barbara

AU - Sanchez-Valle, Raquel

AU - Moreno, Fermin

AU - Graff, Caroline

AU - Laforce, Robert

AU - Galimberti, Daniela

AU - Masellis, Mario

AU - Tartaglia, Maria Carmela

AU - Finger, Elizabeth

AU - Vandenberghe, Rik

AU - Rowe, James B.

AU - De Mendoncą, Alexandre

AU - Tagliavini, Fabrizio

AU - Santana, Isabel

AU - Ducharme, Simon

AU - Butler, Christopher R.

AU - Gerhard, Alexander

AU - Levin, Johannes

AU - Danek, Adrian

AU - Otto, Markus

AU - Pijnenburg, Yolande A.L.

AU - Sorbi, Sandro

AU - Zetterberg, Henrik

AU - Niessen, Wiro J.

AU - Rohrer, Jonathan D.

AU - Klein, Stefan

AU - Van Swieten, John C.

AU - Venkatraghavan, Vikram

AU - Seelaar, Harro

AU - Afonso, Sónia

AU - Almeida, Maria Rosario

AU - Anderl-Straub, Sarah

AU - Andersson, Christin

AU - Antonell, Anna

AU - Archetti, Silvana

AU - Arighi, Andrea

AU - Balasa, Mircea

AU - Barandiaran, Myriam

AU - Bargalló, Nuria

AU - Bartha, Robart

AU - Bender, Benjamin

AU - Benussi, Alberto

AU - Benussi, Luisa

AU - Bessi, Valentina

AU - Binetti, Giuliano

AU - Black, Sandra

AU - Bocchetta, Martina

AU - Borrego-Ecija, Sergi

AU - Bras, Jose

AU - Bruffaerts, Rose

AU - Canãda, Marta

AU - Cantoni, Valentina

AU - Caroppo, Paola

AU - Cash, David

AU - Castelo-Branco, Miguel

AU - Convery, Rhian

AU - Cope, Thomas

AU - Di Fede, Giuseppe

AU - Diéz, Alina

AU - Duro, Diana

AU - Fenoglio, Chiara

AU - Ferrari, Camilla

AU - Ferreira, Catarina B.

AU - Fox, Nick

AU - Freedman, Morris

AU - Fumagalli, Giorgio

AU - Gabilondo, Alazne

AU - Gasparotti, Roberto

AU - Gauthier, Serge

AU - Gazzina, Stefano

AU - Giaccone, Giorgio

AU - Gorostidi, Ana

AU - Greaves, Caroline

AU - Guerreiro, Rita

AU - Hoegen, Tobias

AU - Indakoetxea, Begonã

AU - Jelic, Vesna

AU - Karnath, Hans Otto

AU - Keren, Ron

AU - Langheinrich, Tobias

AU - Leitaõ, Maria Joaõ

AU - Lladó, Albert

AU - Lombardi, Gemma

AU - Loosli, Sandra

AU - Maruta, Carolina

AU - Mead, Simon

AU - Miltenberger, Gabriel

AU - Van Minkelen, Rick

AU - Mitchell, Sara

AU - Moore, Katrina

AU - Nacmias, Benedetta

AU - Nicholas, Jennifer

AU - Oïjerstedt, Linn

AU - Olives, Jaume

AU - Ourselin, Sebastien

AU - Padovani, Alessandro

AU - Peakman, Georgia

AU - Pievani, Michela

AU - Polito, Cristina

AU - Premi, Enrico

AU - Prioni, Sara

AU - Prix, Catharina

AU - Rademakers, Rosa

AU - Redaelli, Veronica

AU - Rittman, Tim

AU - Rogaeva, Ekaterina

AU - Rosa-Neto, Pedro

AU - Rossi, Giacomina

AU - Rosser, Martin

AU - Santiago, Beatriz

AU - Scarpini, Elio

AU - Schönecker, Sonja

AU - Semler, Elisa

AU - Shafei, Rachelle

AU - Shoesmith, Christen

AU - Tábuas-Pereira, Miguel

AU - Tainta, Mikel

AU - Taipa, Ricardo

AU - Tang-Wai, David

AU - Thomas, David L.

AU - Thompson, Paul

AU - Thonberg, Hakan

AU - Timberlake, Carolyn

AU - Tiraboschi, Pietro

AU - Todd, Emily

AU - Van Damme, Philip

AU - Vandenbulcke, Mathieu

AU - Veldsman, Michele

AU - Verdelho, Ana

AU - Villanua, Jorge

AU - Warren, Jason

AU - Woollacott, Ione

AU - Wlasich, Elisabeth

AU - Zulaica, Miren

PY - 2022/5/1

Y1 - 2022/5/1

N2 - 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.

AB - 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.

KW - Biomarker

KW - Disease progression model

KW - Event-based modelling

KW - Frontotemporal dementia

KW - Neurofilament light chain

UR - http://www.scopus.com/inward/record.url?scp=85131701248&partnerID=8YFLogxK

U2 - 10.1093/brain/awab382

DO - 10.1093/brain/awab382

M3 - Article

C2 - 34633446

AN - SCOPUS:85131701248

SN - 0006-8950

VL - 145

SP - 1805

EP - 1817

JO - Brain

JF - Brain

IS - 5

ER -

A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

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Keywords

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