A data‐driven disease progression model of fluid biomarkers in genetic FTD. (31st December 2021)
- Record Type:
- Journal Article
- Title:
- A data‐driven disease progression model of fluid biomarkers in genetic FTD. (31st December 2021)
- Main Title:
- A data‐driven disease progression model of fluid biomarkers in genetic FTD
- Authors:
- van der Ende, Emma
Bron, Esther E.
Poos, Jackie M.
Jiskoot, Lize C.
Panman, Jessica L.
Papma, Janne M.
Wilke, Carlo
Synofzik, Matthis
Heller, Carolin
Swift, Imogen J.
Esteve, Aitana Sogorb
Bouzigues, Arabella
Borroni, Barbara
Sanchez‐Valle, Raquel
Moreno, Fermin
Graff, Caroline
Laforce, Robert
Galimberti, Daniela
Masellis, Mario
Tartaglia, Maria Carmela
Finger, Elizabeth
Vandenberghe, Rik
Rowe, James B.
Mendonca, Alexandre
Tagliavini, Fabrizio
Santana, Isabel
Ducharme, Simon
Butler, Christopher
Gerhard, Alexander
Levin, Johannes
Danek, Adrian
Otto, Markus
Pijnenburg, Yolande A.L.
Frisoni, Giovanni B.
Sorbi, Sandro
Ghidoni, Roberta
Niessen, Wiro J.
Rohrer, Jonathan D.
Klein, Stefan
van Swieten, John C
Venkatraghavan, Vikram
Seelaar, Harro
… (more) - Abstract:
- Abstract: Background: Several fluid biomarkers for genetic frontotemporal dementia (FTD) have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain (NfL) and phosphorylated neurofilament heavy chain (pNfH)), synapse dysfunction (neuronal pentraxin 2 (NPTX2)), gliosis (glial fibrillary acidic protein (GFAP)) and complement activation (C3b, C1q). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging in FTD and enable us to identify mutation carriers with prodromal or early‐stage FTD, which is especially important as pharmaceutical interventions emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic FTD using cross‐sectional data from the Genetic Frontotemporal dementia Initiative (GENFI). Method: 276 presymptomatic and 142 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 data 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 prior diagnostic information or biomarkerAbstract: Background: Several fluid biomarkers for genetic frontotemporal dementia (FTD) have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain (NfL) and phosphorylated neurofilament heavy chain (pNfH)), synapse dysfunction (neuronal pentraxin 2 (NPTX2)), gliosis (glial fibrillary acidic protein (GFAP)) and complement activation (C3b, C1q). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging in FTD and enable us to identify mutation carriers with prodromal or early‐stage FTD, which is especially important as pharmaceutical interventions emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic FTD using cross‐sectional data from the Genetic Frontotemporal dementia Initiative (GENFI). Method: 276 presymptomatic and 142 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 data 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 prior diagnostic information or biomarker cut‐off points. We estimated individual disease severity scores based on the position of subjects along the disease progression timeline through cross‐validation. Result: Cerebrospinal fluid (CSF) NPTX2 was the first detectable abnormal biomarker, followed by blood and CSF NfL, blood GFAP, blood pNfH and finally CSF C1q and C3b (Fig. 1). Biomarker orderings did not differ significantly between genetic subgroups. Estimated disease severity scores (Fig. 2) could distinguish symptomatic from presymptomatic carriers and non‐carriers with areas under the curve (AUC) of 0.84 and 0.90 respectively. The AUC to distinguish converters from non‐converting presymptomatic carriers was 0.85. Conclusion: In our data‐driven disease progression models of genetic FTD, NPTX2 and NfL were the first biomarkers to become abnormal. Further research should focus on their utility as candidate selection tools for pharmaceutical trials. Estimating disease stages using DEBM could enable us to identify presymptomatic carriers approaching symptom onset and track the efficacy of therapeutic interventions. … (more)
- Is Part Of:
- Alzheimer's & dementia. Volume 17(2021)Supplement 5
- Journal:
- Alzheimer's & dementia
- Issue:
- Volume 17(2021)Supplement 5
- Issue Display:
- Volume 17, Issue 5 (2021)
- Year:
- 2021
- Volume:
- 17
- Issue:
- 5
- Issue Sort Value:
- 2021-0017-0005-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-12-31
- Subjects:
- Alzheimer's disease -- Periodicals
Alzheimer Disease -- Periodicals
Dementia -- Periodicals
Démence
Maladie d'Alzheimer
Périodique électronique (Descripteur de forme)
Ressource Internet (Descripteur de forme)
616.83 - Journal URLs:
- http://www.sciencedirect.com/science/journal/15525260 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1002/alz.053497 ↗
- Languages:
- English
- ISSNs:
- 1552-5260
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0806.255333
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25828.xml