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Peer-reviewedCC BY 4.0Alzheimer's Research & Therapy

Data-driven mapping of known and novel fluid biomarker progression profiles in genetic frontotemporal lobar degeneration

  • Julie F. H. De Houwer1
  • Wenjie Kang2
  • Renee van Buuren1
  • Liset de Boer1
  • Tine Swartenbroekx1
  • Ana Rajicic1
  • Arabella Bouzigues3
  • Lucy L. Russell3
  • Phoebe H. Foster3
  • Eve Ferry-Bolder3
  • John C. van Swieten1
  • Lize C. Jiskoot1
32 more authors
  • Raquel Sanchez-Valle4
  • Robert Laforce5
  • Caroline Graff6,7
  • Daniela Galimberti8,9
  • Rik Vandenberghe10,11,12
  • Alexandre de Mendonça13
  • Pietro Tiraboschi14
  • Isabel Santana15,16
  • Alexander Gerhard17,18
  • Johannes Levin19,20,21
  • Benedetta Nacmias22,23
  • Markus Otto24
  • Maxime Bertoux25
  • Thibaud Lebouvier25
  • Simon Ducharme26,27
  • Chris R. Butler28,29
  • Isabelle Le Ber30,31,32
  • Elizabeth Finger33
  • Maria Carmela Tartaglia34
  • Mario Masellis35
  • James B. Rowe36
  • Matthis Synofzik37,38
  • Fermin Moreno39,40
  • Barbara Borroni
  • Henrik Zetterberg3
  • Yolande A. L. Pijnenburg
  • Charlotte Teunissen
  • Jonathan D. Rohrer3
  • Stefan Klein2
  • Elise G. Dopper1
  • Esther E. Bron2
  • Harro Seelaar1
40 affiliations
  1. 1Department of Neurology and Alzheimer Centre, Erasmus MC University Medical Center, Dr. Molewaterplein 40, Rotterdam, 3015 GD The Netherlands
  2. 2Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, 3015 GD The Netherlands
  3. 3Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR UK
  4. 4Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Institut d’Investigacións Biomèdiques August Pi I Sunyer, Hospital Clínic, University of Barcelona, Barcelona, 08036 Spain
  5. 5Département des Sciences Neurologiques, Faculté de Médecine, Clinique Interdisciplinaire de Mémoire, CHU de Québec, Université Laval, QC, G1V 4G2 Canada
  6. 6Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Bioclinicum, Solna, 171 65 Sweden
  7. 7Unit for Hereditary Dementias, Theme Inflammation and Aging, Karolinska University Hospital, Solna, 171 76 Sweden
  8. 8Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, 20122 Italy
  9. 9Neurodegenerative Diseases Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, 20122 Italy
  10. 10Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, 3000 Belgium
  11. 11Neurology Service, University Hospitals Leuven, Leuven, 3000 Belgium
  12. 12Leuven Brain Institute, KU Leuven, Leuven, 3000 Belgium
  13. 13Faculty of Medicine, University of Lisbon, Lisbon, 1649-028 Portugal
  14. 14Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, 20133 Italy
  15. 15Neurology Service, Faculty of Medicine, University Hospital of Coimbra (HUC), University of Coimbra, Coimbra, 3004-531 Portugal
  16. 16Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, 3004-504 Portugal
  17. 17Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
  18. 18Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg, Essen, Germany
  19. 19Department of Neurology, Ludwig-Maximilians Universität München, 80802 Munich, Germany
  20. 20German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
  21. 21Munich Cluster of Systems Neurology (SyNergy), 81377 Munich, Germany
  22. 22Department of Neurofarba, University of Florence, Florence, 50139 Italy
  23. 23IRCCS Fondazione Don Carlo Gnocchi, Florence, 50139 Italy
  24. 24Department of Neurology, University of Ulm, Ulm, 45 89081 Germany
  25. 25Lille Neuroscience & Cognition U1172, University of Lille, CHU Lille, Inserm, 59000 France
  26. 26Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Québec H4H 1R3 Canada
  27. 27McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec H4H 1R3 Canada
  28. 28Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, OX3 7JX UK
  29. 29Department of Brain Sciences, Imperial College London, London, SW7 2AZ UK
  30. 30Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP-HP - Hôpital Pitié-Salpêtrière, Paris, 75013 France
  31. 31Centre de référence des démences rares ou précoces, Département de Neurologie, IM2A, AP-HP - Hôpital Pitié-Salpêtrière, Paris, 75013 France
  32. 32Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, 75013 France
  33. 33Department of Clinical Neurological Sciences, University of Western Ontario, London, ON N6A 3K7 Canada
  34. 34Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON M5G 1E8 Canada
  35. 35Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON M4N 3M5 Canada
  36. 36Department of Clinical Neurosciences, Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 3EB UK
  37. 37Division of Translational Genomics of Neurodegenerative Diseases, Hertie- Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, 72076 Tübingen, Germany
  38. 38Center for Neurodegenerative Diseases (DZNE), 72076 Tübingen, Germany
  39. 39Cognitive Disorders Unit, Department of Neurology, Hospital Universitario Donostia, San Sebastian, 20014 Spain
  40. 40Neurosciences Area, Group of Neurodegenerative Diseases, Biogipuzkoa Health Research Institute, San Sebastian, 20014 Spain
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Abstract

Introduction: Recent proteomic studies have identified both established and novel proteins in genetic frontotemporal lobar degeneration (FTLD). However, it remains unclear at what point in the disease these proteins deviate from normal levels and how their trajectories relate to one another. Defining the temporal sequence of protein abnormalities could not only improve disease staging but also help identify biomarkers most sensitive to early disease activity in pathogenic variant carriers. We aimed to apply discriminative event-based modelling (DEBM) to characterize the progression profiles of proteins identified in a previous cross-sectional proteomic analysis.

Methods: Building on our prior cross-sectional CSF proteomic analysis of genetic FTLD using a proximity extension assay, we selected the top ten significant proteins for each genetic group (C9orf72, GRN, MAPT). We then applied DEBM to characterize temporal dynamics of these proteins separately in each genetic group and evaluated their potential as early disease markers. To validate model performance, each individual was assigned a disease stage according to their position along the estimated disease timeline, based on protein levels and independent of clinical labels. Next, we assessed how well these stages discriminated symptomatic from presymptomatic carriers and non-carriers.

Results: Across all genetic groups, NfL consistently became abnormal before TPM3, although the earliest abnormal proteins differed between groups. In C9orf72, ELAVL4 is the first protein to become abnormal; in GRN SEMA3G and GRN, and in MAPT MMP-10. Estimated individual-level disease stage effectively distinguished symptomatic carriers from presymptomatic carriers and non-carriers, demonstrating high diagnostic accuracy (range AUC 0.74–0.98).

Conclusion: Our data-driven findings provide a temporal ordering of multiple CSF proteins, highlighting potential early biomarkers and disease dynamics in different forms of genetic FTLD. In addition, the model’s accurate estimation of disease stages underscores the value of DEBM for patient stratification, offering a promising tool to support clinical trial design.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s13195-026-02159-5.

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Cite

BibTeXRIS
BibTeX
@article{houwer2026datadriven,
  title = {{Data-driven mapping of known and novel fluid biomarker progression profiles in genetic frontotemporal lobar degeneration}},
  author = {Julie F. H. De Houwer and Wenjie Kang and Renee van Buuren and Liset de Boer and Tine Swartenbroekx and Ana Rajicic and Arabella Bouzigues and Lucy L. Russell and Phoebe H. Foster and Eve Ferry-Bolder and John C. van Swieten and Lize C. Jiskoot and Raquel Sanchez-Valle and Robert Laforce and Caroline Graff and Daniela Galimberti and Rik Vandenberghe and Alexandre de Mendonça and Pietro Tiraboschi and Isabel Santana and Alexander Gerhard and Johannes Levin and Benedetta Nacmias and Markus Otto and Maxime Bertoux and Thibaud Lebouvier and Simon Ducharme and Chris R. Butler and Isabelle Le Ber and Elizabeth Finger and Maria Carmela Tartaglia and Mario Masellis and James B. Rowe and Matthis Synofzik and Fermin Moreno and Barbara Borroni and Henrik Zetterberg and Yolande A. L. Pijnenburg and Charlotte Teunissen and Jonathan D. Rohrer and Stefan Klein and Elise G. Dopper and Esther E. Bron and Harro Seelaar},
  journal = {Alzheimer's Research \& Therapy},
  year = {2026},
  month = aug,
  doi = {10.1186/s13195-026-02159-5},
  url = {https://doi.org/10.1186/s13195-026-02159-5},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Data-driven mapping of known and novel fluid biomarker progression profiles in genetic frontotemporal lobar degeneration
AU  - Julie F. H. De Houwer
AU  - Wenjie Kang
AU  - Renee van Buuren
AU  - Liset de Boer
AU  - Tine Swartenbroekx
AU  - Ana Rajicic
AU  - Arabella Bouzigues
AU  - Lucy L. Russell
AU  - Phoebe H. Foster
AU  - Eve Ferry-Bolder
AU  - John C. van Swieten
AU  - Lize C. Jiskoot
AU  - Raquel Sanchez-Valle
AU  - Robert Laforce
AU  - Caroline Graff
AU  - Daniela Galimberti
AU  - Rik Vandenberghe
AU  - Alexandre de Mendonça
AU  - Pietro Tiraboschi
AU  - Isabel Santana
AU  - Alexander Gerhard
AU  - Johannes Levin
AU  - Benedetta Nacmias
AU  - Markus Otto
AU  - Maxime Bertoux
AU  - Thibaud Lebouvier
AU  - Simon Ducharme
AU  - Chris R. Butler
AU  - Isabelle Le Ber
AU  - Elizabeth Finger
AU  - Maria Carmela Tartaglia
AU  - Mario Masellis
AU  - James B. Rowe
AU  - Matthis Synofzik
AU  - Fermin Moreno
AU  - Barbara Borroni
AU  - Henrik Zetterberg
AU  - Yolande A. L. Pijnenburg
AU  - Charlotte Teunissen
AU  - Jonathan D. Rohrer
AU  - Stefan Klein
AU  - Elise G. Dopper
AU  - Esther E. Bron
AU  - Harro Seelaar
PY  - 2026
DA  - 2026/08/11
JO  - Alzheimer's Research & Therapy
DO  - 10.1186/s13195-026-02159-5
UR  - https://doi.org/10.1186/s13195-026-02159-5
AB  - Introduction: Recent proteomic studies have identified both established and novel proteins in genetic frontotemporal lobar degeneration (FTLD). However, it remains unclear at what point in the disease these proteins deviate from normal levels and how their trajectories relate to one another. Defining the temporal sequence of protein abnormalities could not only improve disease staging but also help identify biomarkers most sensitive to early disease activity in pathogenic variant carriers. We aimed to apply discriminative event-based modelling (DEBM) to characterize the progression profiles of proteins identified in a previous cross-sectional proteomic analysis.  Methods: Building on our prior cross-sectional CSF proteomic analysis of genetic FTLD using a proximity extension assay, we selected the top ten significant proteins for each genetic group (C9orf72, GRN, MAPT). We then applied DEBM to characterize temporal dynamics of these proteins separately in each genetic group and evaluated their potential as early disease markers. To validate model performance, each individual was assigned a disease stage according to their position along the estimated disease timeline, based on protein levels and independent of clinical labels. Next, we assessed how well these stages discriminated symptomatic from presymptomatic carriers and non-carriers.  Results: Across all genetic groups, NfL consistently became abnormal before TPM3, although the earliest abnormal proteins differed between groups. In C9orf72, ELAVL4 is the first protein to become abnormal; in GRN SEMA3G and GRN, and in MAPT MMP-10. Estimated individual-level disease stage effectively distinguished symptomatic carriers from presymptomatic carriers and non-carriers, demonstrating high diagnostic accuracy (range AUC 0.74–0.98).  Conclusion: Our data-driven findings provide a temporal ordering of multiple CSF proteins, highlighting potential early biomarkers and disease dynamics in different forms of genetic FTLD. In addition, the model’s accurate estimation of disease stages underscores the value of DEBM for patient stratification, offering a promising tool to support clinical trial design.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s13195-026-02159-5.
SN  - 1758-9193
ER  -