The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications
Open accessAbstract
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-tau181 and the Aβ1–42/ Aβ1–40 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 (FTLD), 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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MAPT carriers are associated largely with bvFTD, PPA, and FTD with parkinsonism.
“Genotype‐phenotype correlations showed that MAPT carriers are associated largely with bvFTD, PPA, and FTD with parkinsonism.”
From New developments of biofluid‐based biomarkers for routine diagnosis and disease trajectories in frontotemporal dementia (2022) · cites this paper as [34]
GRN carriers often present with FTLD-TDP A pathology and most patients have bvFTD clinical phenotype, though PPA has also been reported.
“GRN carriers often present with FTLD‐TDP A pathology and most patients have bvFTD clinical phenotype, though PPA has been also reported in these familial cases.”
From New developments of biofluid‐based biomarkers for routine diagnosis and disease trajectories in frontotemporal dementia (2022) · cites this paper as [34]
Most FTD variants have very poor genotype-phenotype correlations, but they are highly predictive of the underlying neuropathology.
“Most of these variants have very poor genotype–phenotype correlations, but they are highly predictive of the underlying neuropathology (Figure 1).”
From New developments of biofluid‐based biomarkers for routine diagnosis and disease trajectories in frontotemporal dementia (2022) · cites this paper as [34]
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Heritability in frontotemporal dementia: more missing pieces?
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The Scale for Emotional Blunting in Patients with Frontotemporal Dementia
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Self-citationClinical variability and onset age modifiers in an extended Belgian GRN founder family
Wauters, E., Mossevelde, S. V., Sleegers, K., van der Zee, J., Engelborghs, S., Sieben, A., Vandenberghe, R. R., Philtjens, S., den Broeck, M. V., Peeters, K., et al. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.03.007 · Cited by 25 · see citing works
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Self-citationTranscranial magnetic stimulation in patients with early cortical dementia: A pilot study
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Estimating the Age of the Most Common Italian GRN Mutation: Walking Back to Canossa Times
Benussi, L., Rademakers, R., Rutherford, N. J., Wojtas, A., Glionna, M., Paterlini, A., Albertini, V., Bettecken, T., Binetti, G. G., & Ghidoni, R. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-121306 · Cited by 17 · see citing works
Genetic Counseling for Frontotemporal Dementias
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Precision medicine of frontotemporal dementia from genotype to phenotype
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Huang, M., Modeste, E. S., Dammer, E. B., Merino, P., Taylor, G., Duong, D. M., Deng, Q., Holler, C. J., Gearing, M., Dickson, D. W., et al. (2020) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-01037-x · Cited by 100 · see citing works
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18F-MK-6240 tau-PET in genetic frontotemporal dementia
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Emerging genetic complexity and rare genetic variants in neurodegenerative brain diseases
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Proton Magnetic Resonance Spectroscopy in Common Dementias—Current Status and Perspectives
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Biomarkers in frontotemporal dementia: Current landscape and future directions
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Frontotemporal dementia. How to deal with its diagnostic complexity?
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Divergent Thinking Abilities in Frontotemporal Dementia: A Mini-Review
Fusi, G., Crepaldi, M., Colautti, L., Palmiero, M., Antonietti, A., Rozzini, L., & Rusconi, M. L. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.652543 · Cited by 14 · see citing works
Genetic study of young‐onset dementia using targeted gene panel sequencing in Taiwan
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Haploinsufficiency and Alzheimer’s Disease: The Possible Pathogenic and Protective Genetic Factors
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Ortner, M., Goldhardt, O., Diehl‐Schmid, J., Yakushev, I. Y., Lanz, K., Hedderich, D. M., Manuilova, E., Simon, M., Weinberger, J.-P., & Grimmer, T. (2022) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2022.27 · Cited by 9 · see citing works
Preclinical and Prodromal Frontotemporal Dementia: Challenges and Opportunities
Palacino, F., Manganotti, P., & Benussi, A. (2025) · International Journal of Translational Medicine · doi:10.3390/ijtm5040052 · Cited by 7 · see citing works
Cognitive reserve in individuals with frontotemporal dementia: a systematic review
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Influence of Chronic Administration of Sodium Nitrite on Morphofunctional State of Brain in Rats
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Diagnostic Evaluation of Dementia
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- Authors
- Gossye, H., Van Broeckhoven, C., & Engelborghs, S.
- Affiliations
- Vrije Universiteit Brussel (BE)
- Corresponding author
- Engelborghs, Sebastiaan
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2019-08-06
- Volume
- 13
- Pages
- 757-757
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC6691066
- OpenAlex
- W2956196072
- Cited by
- 34
- References
- 169
- Citations by year
- 2025: 5 · 2024: 4 · 2023: 3 · 2022: 6 · 2021: 11 · 2020: 4 · 2019: 1
- FWCI
- 4.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Fonds Wetenschappelijk Onderzoek
- Universiteit Antwerpen
- Vlaamse regering
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Neurology › Amyotrophic Lateral Sclerosis Research
- Keywords
- frontotemporal dementia, differential diagnosis, biomarkers, genetic screening, Alzheimer's disease, cerebrospinal fluid biomarkers, amyloid PET, FDG-PET, SPECT, neuroimaging, p-tau181, C9orf72, MAPT, gene regulatory networks, TBK1, CHMP2B, VCP, genotype-phenotype correlation, familial frontotemporal lobar degeneration, neurofilaments, tau PET, diffusion tensor imaging, atypical presentation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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