Cargando…

Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort

Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers...

Descripción completa

Detalles Bibliográficos
Autores principales: Bocchetta, Martina, Todd, Emily G, Bouzigues, Arabella, Cash, David M, Nicholas, Jennifer M, Convery, Rhian S, Russell, Lucy L, Thomas, David L, Malone, Ian B, Iglesias, Juan Eugenio, van Swieten, John C, Jiskoot, Lize C, Seelaar, Harro, Borroni, Barbara, Galimberti, Daniela, Sanchez-Valle, Raquel, Laforce, Robert, Moreno, Fermin, Synofzik, Matthis, Graff, Caroline, Masellis, Mario, Tartaglia, Maria Carmela, Rowe, James B, Vandenberghe, Rik, Finger, Elizabeth, Tagliavini, Fabrizio, de Mendonça, Alexandre, Santana, Isabel, Butler, Chris R, Ducharme, Simon, Gerhard, Alexander, Danek, Adrian, Levin, Johannes, Otto, Markus, Sorbi, Sandro, Le Ber, Isabelle, Pasquier, Florence, Rohrer, Jonathan D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036293/
https://www.ncbi.nlm.nih.gov/pubmed/36970046
http://dx.doi.org/10.1093/braincomms/fcad061
_version_ 1784911618797207552
author Bocchetta, Martina
Todd, Emily G
Bouzigues, Arabella
Cash, David M
Nicholas, Jennifer M
Convery, Rhian S
Russell, Lucy L
Thomas, David L
Malone, Ian B
Iglesias, Juan Eugenio
van Swieten, John C
Jiskoot, Lize C
Seelaar, Harro
Borroni, Barbara
Galimberti, Daniela
Sanchez-Valle, Raquel
Laforce, Robert
Moreno, Fermin
Synofzik, Matthis
Graff, Caroline
Masellis, Mario
Tartaglia, Maria Carmela
Rowe, James B
Vandenberghe, Rik
Finger, Elizabeth
Tagliavini, Fabrizio
de Mendonça, Alexandre
Santana, Isabel
Butler, Chris R
Ducharme, Simon
Gerhard, Alexander
Danek, Adrian
Levin, Johannes
Otto, Markus
Sorbi, Sandro
Le Ber, Isabelle
Pasquier, Florence
Rohrer, Jonathan D
author_facet Bocchetta, Martina
Todd, Emily G
Bouzigues, Arabella
Cash, David M
Nicholas, Jennifer M
Convery, Rhian S
Russell, Lucy L
Thomas, David L
Malone, Ian B
Iglesias, Juan Eugenio
van Swieten, John C
Jiskoot, Lize C
Seelaar, Harro
Borroni, Barbara
Galimberti, Daniela
Sanchez-Valle, Raquel
Laforce, Robert
Moreno, Fermin
Synofzik, Matthis
Graff, Caroline
Masellis, Mario
Tartaglia, Maria Carmela
Rowe, James B
Vandenberghe, Rik
Finger, Elizabeth
Tagliavini, Fabrizio
de Mendonça, Alexandre
Santana, Isabel
Butler, Chris R
Ducharme, Simon
Gerhard, Alexander
Danek, Adrian
Levin, Johannes
Otto, Markus
Sorbi, Sandro
Le Ber, Isabelle
Pasquier, Florence
Rohrer, Jonathan D
author_sort Bocchetta, Martina
collection PubMed
description Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. Three hundred eighty-seven mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). The w-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as ‘normal’ or ‘abnormal’ based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the ‘normal’ and ‘abnormal’ groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials.
format Online
Article
Text
id pubmed-10036293
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-100362932023-03-25 Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort Bocchetta, Martina Todd, Emily G Bouzigues, Arabella Cash, David M Nicholas, Jennifer M Convery, Rhian S Russell, Lucy L Thomas, David L Malone, Ian B Iglesias, Juan Eugenio van Swieten, John C Jiskoot, Lize C Seelaar, Harro Borroni, Barbara Galimberti, Daniela Sanchez-Valle, Raquel Laforce, Robert Moreno, Fermin Synofzik, Matthis Graff, Caroline Masellis, Mario Tartaglia, Maria Carmela Rowe, James B Vandenberghe, Rik Finger, Elizabeth Tagliavini, Fabrizio de Mendonça, Alexandre Santana, Isabel Butler, Chris R Ducharme, Simon Gerhard, Alexander Danek, Adrian Levin, Johannes Otto, Markus Sorbi, Sandro Le Ber, Isabelle Pasquier, Florence Rohrer, Jonathan D Brain Commun Original Article Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. Three hundred eighty-seven mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). The w-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as ‘normal’ or ‘abnormal’ based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the ‘normal’ and ‘abnormal’ groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials. Oxford University Press 2023-03-10 /pmc/articles/PMC10036293/ /pubmed/36970046 http://dx.doi.org/10.1093/braincomms/fcad061 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Bocchetta, Martina
Todd, Emily G
Bouzigues, Arabella
Cash, David M
Nicholas, Jennifer M
Convery, Rhian S
Russell, Lucy L
Thomas, David L
Malone, Ian B
Iglesias, Juan Eugenio
van Swieten, John C
Jiskoot, Lize C
Seelaar, Harro
Borroni, Barbara
Galimberti, Daniela
Sanchez-Valle, Raquel
Laforce, Robert
Moreno, Fermin
Synofzik, Matthis
Graff, Caroline
Masellis, Mario
Tartaglia, Maria Carmela
Rowe, James B
Vandenberghe, Rik
Finger, Elizabeth
Tagliavini, Fabrizio
de Mendonça, Alexandre
Santana, Isabel
Butler, Chris R
Ducharme, Simon
Gerhard, Alexander
Danek, Adrian
Levin, Johannes
Otto, Markus
Sorbi, Sandro
Le Ber, Isabelle
Pasquier, Florence
Rohrer, Jonathan D
Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
title Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
title_full Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
title_fullStr Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
title_full_unstemmed Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
title_short Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
title_sort structural mri predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the genetic frontotemporal dementia initiative cohort
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036293/
https://www.ncbi.nlm.nih.gov/pubmed/36970046
http://dx.doi.org/10.1093/braincomms/fcad061
work_keys_str_mv AT bocchettamartina structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT toddemilyg structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT bouziguesarabella structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT cashdavidm structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT nicholasjenniferm structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT converyrhians structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT russelllucyl structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT thomasdavidl structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT maloneianb structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT iglesiasjuaneugenio structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT vanswietenjohnc structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT jiskootlizec structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT seelaarharro structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT borronibarbara structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT galimbertidaniela structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT sanchezvalleraquel structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT laforcerobert structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT morenofermin structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT synofzikmatthis structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT graffcaroline structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT masellismario structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT tartagliamariacarmela structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT rowejamesb structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT vandenbergherik structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT fingerelizabeth structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT tagliavinifabrizio structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT demendoncaalexandre structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT santanaisabel structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT butlerchrisr structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT ducharmesimon structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT gerhardalexander structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT danekadrian structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT levinjohannes structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT ottomarkus structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT sorbisandro structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT leberisabelle structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT pasquierflorence structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT rohrerjonathand structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort
AT structuralmripredictsclinicalprogressioninpresymptomaticgeneticfrontotemporaldementiafindingsfromthegeneticfrontotemporaldementiainitiativecohort