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The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications

Within the wide range of neurodegenerative brain diseases, the differential diagnosis of frontotemporal dementia (FTD) frequently poses a challenge. Often, signs and symptoms are not characteristic of the disease and may instead reflect atypical presentations. Consequently, the use of disease biomar...

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Autores principales: Gossye, Helena, Van Broeckhoven, Christine, Engelborghs, Sebastiaan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691066/
https://www.ncbi.nlm.nih.gov/pubmed/31447625
http://dx.doi.org/10.3389/fnins.2019.00757
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author Gossye, Helena
Van Broeckhoven, Christine
Engelborghs, Sebastiaan
author_facet Gossye, Helena
Van Broeckhoven, Christine
Engelborghs, Sebastiaan
author_sort Gossye, Helena
collection PubMed
description Within the wide range of neurodegenerative brain diseases, the differential diagnosis of frontotemporal dementia (FTD) frequently poses a challenge. Often, signs and symptoms are not characteristic of the disease and may instead reflect atypical presentations. Consequently, the use of disease biomarkers is of importance to correctly identify the patients. Here, we describe how neuropsychological characteristics, neuroimaging and neurochemical biomarkers and screening for causal gene mutations can be used to differentiate FTD from other neurodegenerative diseases as well as to distinguish between FTD subtypes. Summarizing current evidence, we propose a stepwise approach in the diagnostic evaluation. Clinical consensus criteria that take into account a full neuropsychological examination have relatively good accuracy (sensitivity [se] 75–95%, specificity [sp] 82–95%) to diagnose FTD, although misdiagnosis (mostly AD) is common. Structural brain MRI (se 70–94%, sp 89–99%) and FDG PET (se 47–90%, sp 68–98%) or SPECT (se 36–100%, sp 41–100%) brain scans greatly increase diagnostic accuracy, showing greater involvement of frontal and anterior temporal lobes, with sparing of hippocampi and medial temporal lobes. If these results are inconclusive, we suggest detecting amyloid and tau cerebrospinal fluid (CSF) biomarkers that can indicate the presence of AD with good accuracy (se 74–100%, sp 82–97%). The use of P-tau(181) and the Aβ(1)(–)(42)/Aβ(1)(–)(40) ratio significantly increases the accuracy of correctly identifying FTD vs. AD. Alternatively, an amyloid brain PET scan can be performed to differentiate FTD from AD. When autosomal dominant inheritance is suspected, or in early onset dementia, mutation screening of causal genes is indicated and may also be offered to at-risk family members. We have summarized genotype–phenotype correlations for several genes that are known to cause familial frontotemporal lobar degeneration, which is the neuropathological substrate of FTD. The genes most commonly associated with this disease (C9orf72, MAPT, GRN, TBK1) are discussed, as well as some less frequent ones (CHMP2B, VCP). Several other techniques, such as diffusion tensor imaging, tau PET imaging and measuring serum neurofilament levels, show promise for future implementation as diagnostic biomarkers.
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spelling pubmed-66910662019-08-23 The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications Gossye, Helena Van Broeckhoven, Christine Engelborghs, Sebastiaan Front Neurosci Neuroscience Within the wide range of neurodegenerative brain diseases, the differential diagnosis of frontotemporal dementia (FTD) frequently poses a challenge. Often, signs and symptoms are not characteristic of the disease and may instead reflect atypical presentations. Consequently, the use of disease biomarkers is of importance to correctly identify the patients. Here, we describe how neuropsychological characteristics, neuroimaging and neurochemical biomarkers and screening for causal gene mutations can be used to differentiate FTD from other neurodegenerative diseases as well as to distinguish between FTD subtypes. Summarizing current evidence, we propose a stepwise approach in the diagnostic evaluation. Clinical consensus criteria that take into account a full neuropsychological examination have relatively good accuracy (sensitivity [se] 75–95%, specificity [sp] 82–95%) to diagnose FTD, although misdiagnosis (mostly AD) is common. Structural brain MRI (se 70–94%, sp 89–99%) and FDG PET (se 47–90%, sp 68–98%) or SPECT (se 36–100%, sp 41–100%) brain scans greatly increase diagnostic accuracy, showing greater involvement of frontal and anterior temporal lobes, with sparing of hippocampi and medial temporal lobes. If these results are inconclusive, we suggest detecting amyloid and tau cerebrospinal fluid (CSF) biomarkers that can indicate the presence of AD with good accuracy (se 74–100%, sp 82–97%). The use of P-tau(181) and the Aβ(1)(–)(42)/Aβ(1)(–)(40) ratio significantly increases the accuracy of correctly identifying FTD vs. AD. Alternatively, an amyloid brain PET scan can be performed to differentiate FTD from AD. When autosomal dominant inheritance is suspected, or in early onset dementia, mutation screening of causal genes is indicated and may also be offered to at-risk family members. We have summarized genotype–phenotype correlations for several genes that are known to cause familial frontotemporal lobar degeneration, which is the neuropathological substrate of FTD. The genes most commonly associated with this disease (C9orf72, MAPT, GRN, TBK1) are discussed, as well as some less frequent ones (CHMP2B, VCP). Several other techniques, such as diffusion tensor imaging, tau PET imaging and measuring serum neurofilament levels, show promise for future implementation as diagnostic biomarkers. Frontiers Media S.A. 2019-08-06 /pmc/articles/PMC6691066/ /pubmed/31447625 http://dx.doi.org/10.3389/fnins.2019.00757 Text en Copyright © 2019 Gossye, Van Broeckhoven and Engelborghs. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Gossye, Helena
Van Broeckhoven, Christine
Engelborghs, Sebastiaan
The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
title The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
title_full The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
title_fullStr The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
title_full_unstemmed The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
title_short The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
title_sort use of biomarkers and genetic screening to diagnose frontotemporal dementia: evidence and clinical implications
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691066/
https://www.ncbi.nlm.nih.gov/pubmed/31447625
http://dx.doi.org/10.3389/fnins.2019.00757
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