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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Aging Neurosci.</journal-id>
<journal-title>Frontiers in Aging Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Aging Neurosci.</abbrev-journal-title>
<issn pub-type="epub">1663-4365</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnagi.2024.1382593</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Aging Neuroscience</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The pursuit for markers of disease progression in behavioral variant frontotemporal dementia: a scoping review to optimize outcome measures for clinical trials</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes" equal-contrib="yes">
<name><surname>Fieldhouse</surname> <given-names>Jay L. P.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author" corresp="yes" equal-contrib="yes">
<name><surname>van Paassen</surname> <given-names>Dirk N.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c002"><sup>&#x002A;</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
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<name><surname>van Engelen</surname> <given-names>Marie-Paule E.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<name><surname>De Boer</surname> <given-names>Sterre C. M.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<name><surname>Hartog</surname> <given-names>Willem L.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<name><surname>Braak</surname> <given-names>Simon</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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<contrib contrib-type="author">
<name><surname>Schoonmade</surname> <given-names>Linda J.</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
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<name><surname>Schouws</surname> <given-names>Sigfried N. T. M.</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<contrib contrib-type="author">
<name><surname>Krudop</surname> <given-names>Welmoed A.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<name><surname>Oudega</surname> <given-names>Mardien L.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<name><surname>Mutsaerts</surname> <given-names>Henk J. M. M.</given-names></name>
<xref ref-type="aff" rid="aff7"><sup>7</sup></xref>
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<contrib contrib-type="author">
<name><surname>Teunissen</surname> <given-names>Charlotte E.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff8"><sup>8</sup></xref>
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<contrib contrib-type="author">
<name><surname>Vijverberg</surname> <given-names>Everard G. B.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Pijnenburg</surname> <given-names>Yolande A. L.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff2"><sup>2</sup><institution>Amsterdam Neuroscience, Neurodegeneration</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Psychiatry, Amsterdam UMC Location VUmc</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff4"><sup>4</sup><institution>Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep &#x0026; Stress Program</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff5"><sup>5</sup><institution>Medical Library, Vrije Universiteit Amsterdam</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff6"><sup>6</sup><institution>GGZ inGeest Mental Health Care</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff7"><sup>7</sup><institution>Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<aff id="aff8"><sup>8</sup><institution>Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC Location VUmc</institution>, <addr-line>Amsterdam</addr-line>, <country>Netherlands</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0002"><p>Edited by: Jennifer S. Yokoyama, University of San Francisco, United States</p></fn>
<fn fn-type="edited-by" id="fn0003"><p>Reviewed by: Russell P. Sawyer, University of Cincinnati, United States</p><p>Claudia Duran-Aniotz, Adolfo Ib&#x00E1;&#x00F1;ez University, Chile</p><p>Emilie V. Brotherhood, University College London, London, United Kingdom</p></fn>
<corresp id="c001">&#x002A;Correspondence: Jay L. P. Fieldhouse, <email>j.fieldhouse@amsterdamumc.nl</email></corresp>
<corresp id="c002">Dirk N. van Paassen, <email>d.n.vanpaassen@amsterdamumc.nl</email></corresp>
<fn fn-type="equal" id="fn0001"><p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>09</day>
<month>05</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>16</volume>
<elocation-id>1382593</elocation-id>
<history>
<date date-type="received">
<day>05</day>
<month>02</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2024 Fieldhouse, van Paassen, van Engelen, De Boer, Hartog, Braak, Schoonmade, Schouws, Krudop, Oudega, Mutsaerts, Teunissen, Vijverberg and Pijnenburg.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Fieldhouse, van Paassen, van Engelen, De Boer, Hartog, Braak, Schoonmade, Schouws, Krudop, Oudega, Mutsaerts, Teunissen, Vijverberg and Pijnenburg</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>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.</p>
</license>
</permissions>
<abstract>
<p>Behavioral variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder characterized by diverse and prominent changes in behavior and personality. One of the greatest challenges in bvFTD is to capture, measure and predict its disease progression, due to clinical, pathological and genetic heterogeneity. Availability of reliable outcome measures is pivotal for future clinical trials and disease monitoring. Detection of change should be objective, clinically meaningful and easily assessed, preferably associated with a biological process. The purpose of this scoping review is to examine the status of longitudinal studies in bvFTD, evaluate current assessment tools and propose potential progression markers. A systematic literature search (in PubMed and <ext-link xlink:href="http://Embase.com" ext-link-type="uri">Embase.com</ext-link>) was performed. Literature on disease trajectories and longitudinal validity of frequently-used measures was organized in five domains: global functioning, behavior, (social) cognition, neuroimaging and fluid biomarkers. Evaluating current longitudinal data, we propose an adaptive battery, combining a set of sensitive clinical, neuroimaging and fluid markers, adjusted for genetic and sporadic variants, for adequate detection of disease progression in bvFTD.</p>
</abstract>
<kwd-group>
<kwd>literature review</kwd>
<kwd>cohort studies</kwd>
<kwd>longitudinal</kwd>
<kwd>assessment</kwd>
<kwd>outcome measures</kwd>
<kwd>clinical trials</kwd>
<kwd>disease progression</kwd>
</kwd-group>
<counts>
<fig-count count="2"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="170"/>
<page-count count="14"/>
<word-count count="13597"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Alzheimer's Disease and Related Dementias</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1</label>
<title>Introduction</title>
<p>Behavioral variant frontotemporal dementia (bvFTD), as part of the frontotemporal lobar degeneration (FTLD) spectrum, is a common cause of young-onset dementia (<xref ref-type="bibr" rid="ref60">Hogan et al., 2016</xref>). Prominent behavioral change is an important feature of bvFTD, including the core behavioral symptoms of disinhibition, apathy, loss of empathy, stereotypy and hyperorality (<xref ref-type="bibr" rid="ref138">Rascovsky et al., 2011</xref>). BvFTD shows highly variable disease progression (<xref ref-type="bibr" rid="ref29">Devenney et al., 2015</xref>). Such clinical, pathological and genetic heterogeneity complicates the pursuit for a reliable biomarker of disease progression in bvFTD (<xref ref-type="bibr" rid="ref111">Meeter et al., 2017</xref>). These different subtypes might require different methods to detect clinical and/or biological progression. However, most instruments used in bvFTD originate from the field of amnestic Alzheimer&#x2019;s disease and were designed for differential diagnosis with other neurodegenerative diseases, rather than monitor disease progression in bvFTD, let alone its specific subtypes. The fundamental behavioral component in the clinical phenotype of bvFTD calls for a more specific approach. Objective measurement of behavior is complex: behavior is context dependent, observing and reporting of behavior is subjective (to assessor and/or informant) and rarely recognized by the patient itself due to impaired insight (<xref ref-type="bibr" rid="ref123">Neary et al., 1998</xref>; <xref ref-type="bibr" rid="ref114">Mendez and Shapira, 2011</xref>). Furthermore, symptomatic overlap with primary psychiatric disorders (PPD), misdiagnosis and diagnostic delay all hamper an adequate characterization of the disease course in bvFTD (<xref ref-type="bibr" rid="ref169">Woolley et al., 2011</xref>).</p>
<p>A suitable marker for disease progression in bvFTD is highly relevant for both clinical trial design and monitoring disease in clinical practice. To sensitively detect (by)effects of disease modifying therapies, it is crucial to attribute disease severity at baseline (entry status) and measure clinical change during treatment. An ideal outcome measure provides objective, reliable and easy assessment of clinically relevant change that is associated with a biological process. Specificity of possible bvFTD diagnosis is low (<xref ref-type="bibr" rid="ref162">Vijverberg et al., 2016</xref>; <xref ref-type="bibr" rid="ref87">Krudop et al., 2017</xref>; <xref ref-type="bibr" rid="ref28">de Boer et al., 2023</xref>), and certain genetic mutations have been characterized by a typical disease profile, such as mild clinical symptoms and slow disease progression in C9ORF72 mutation carriers (<xref ref-type="bibr" rid="ref30">Devenney et al., 2014</xref>). Therefore, the identification of disease progression markers in longitudinal cohorts should focus on biomarker confirmed probable or definite bvFTD, preferably, stratifying for genetic mutation status. The purpose of this scoping review is to evaluate the available longitudinal data on clinical [global functioning, behavior, (social) cognition], neuroimaging and fluid biomarkers in bvFTD, in order to identify the most suitable measurements at present, as well as potential needs to be addressed.</p>
</sec>
<sec sec-type="methods" id="sec2">
<label>2</label>
<title>Methods</title>
<p>This scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [(<xref ref-type="bibr" rid="ref129">Page et al., 2021</xref>); <ext-link xlink:href="http://www.prisma-statement.org" ext-link-type="uri">www.prisma-statement.org</ext-link>]. A comprehensive search was performed in the bibliographic databases PubMed and <ext-link xlink:href="http://Embase.com" ext-link-type="uri">Embase.com</ext-link> from inception to September 5, 2022, in collaboration with a medical librarian (LS). Search terms included controlled terms (MeSH in PubMed and Emtree in Embase) as well as free text terms. The following terms were used (including all possible synonyms and closely related words) as index terms or free-text words: &#x201C;behavioral&#x201D; and &#x201C;frontotemporal dementia&#x201D; and &#x201C;longitudinal studies.&#x201D; The search was performed without date or language restrictions. Duplicate articles were excluded by a medical information specialist (LS) using Endnote X20.4 (Clarivate<sup>&#x2122;</sup>), following the Amsterdam Efficient Deduplication (AED) method and the Bramer-method (<xref ref-type="bibr" rid="ref18">Bramer et al., 2016</xref>; <xref ref-type="bibr" rid="ref127">Otten et al., 2019</xref>). The full search strategies for all databases can be found in <xref ref-type="sec" rid="sec28">Supplementary Table S1</xref>.</p>
<p>Two reviewers (JF and DP) screened all potentially relevant titles and abstracts for eligibility using Rayyan (<xref ref-type="bibr" rid="ref128">Ouzzani et al., 2016</xref>). Studies resulting from this literature search were included if they met both of the following criteria: (I) population of bvFTD; (II) multiple (follow-up) measurements in time or relevant (cross-sectional) associations with disease progression/severity, to incorporate promising tools currently lacking longitudinal evidence. Studies resulting from this literature search were excluded if they met one or more of the criteria: (I) case-reports; (II) animal studies; (III) reviews; (IIII) focus other than disease progression (e.g., diagnostics). If necessary, the full text article was checked for the eligibility criteria. Two reviewers (JF and DP) evaluated the overall methodological quality of the full text papers taking into account eligibility criteria of (I) high diagnostic accuracy [i.e., probable or definite bvFTD by international diagnostic criteria (<xref ref-type="bibr" rid="ref138">Rascovsky et al., 2011</xref>)]; (II) sample size; (III) follow-up time; (IIII) use of appropriate outcome measures, when weighing research evidence. Differences in judgement were resolved through a consensus procedure. Literature was organized in five domains: global functioning, behavior, (social) cognition, neuroimaging and fluid biomarkers. These domains were established during the selection procedure to provide structure in the process of identification, evaluation and reporting.</p>
</sec>
<sec sec-type="results" id="sec3">
<label>3</label>
<title>Results</title>
<p>The literature search generated a total of 4,931 articles: 2,245 in PubMed and 2,686 in Embase. After removing duplicates of articles that were selected from more than one database, 2,842 articles remained. The flow chart of the literature search and selection process is presented in <xref ref-type="fig" rid="fig1">Figure 1</xref> (<xref ref-type="bibr" rid="ref129">Page et al., 2021</xref>); <ext-link xlink:href="http://www.prisma-statement.org" ext-link-type="uri">www.prisma-statement.org</ext-link>. A total of 149 articles were included.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Flowchart of the search and selection procedure of studies.</p>
</caption>
<graphic xlink:href="fnagi-16-1382593-g001.tif"/>
</fig>
<sec id="sec4">
<label>3.1</label>
<title>Global functioning</title>
<p>Global rating scales serve as a solid instrument to stage disease severity regardless of underlying neurodegenerative pathology, in a relatively quick and easy manner. Many global dementia scales focus on cognition and do not capture the specific behavioral component in bvFTD. The Clinical Dementia Rating scale (CDR), developed for disease staging of dementia (<xref ref-type="bibr" rid="ref120">Morris, 1993</xref>), dominated FTD research for many years. By covering mainly Alzheimer&#x2019;s disease (AD)-related cognitive and functional domains, the CDR tends to underrate disease severity in bvFTD (<xref ref-type="bibr" rid="ref119">Mioshi et al., 2010</xref>). The adapted version of the CDR, FTLD-modified Clinical Dementia Rating scale (FTLD-CDR); (<xref ref-type="bibr" rid="ref84">Knopman et al., 2008</xref>), added domains of language and behavior to the original scale, accounting for the most prominent symptoms in bvFTD (<xref ref-type="bibr" rid="ref85">Knopman et al., 2011</xref>). Findings showed the FTLD-CDR demonstrated annual decline over years in genetic and sporadic FTD population (<xref ref-type="bibr" rid="ref84">Knopman et al., 2008</xref>; <xref ref-type="bibr" rid="ref117">Mioshi et al., 2017</xref>; <xref ref-type="bibr" rid="ref151">Staffaroni et al., 2019a</xref>,<xref ref-type="bibr" rid="ref152">b</xref>; <xref ref-type="bibr" rid="ref3">Anderl-Straub et al., 2021</xref>; <xref ref-type="bibr" rid="ref97">Lima-Silva et al., 2021</xref>). The FTLD-CDR score has been associated with bvFTD specific neuroimaging changes, such as frontotemporal blood flow and atrophy (<xref ref-type="bibr" rid="ref15">Borroni et al., 2010</xref>; <xref ref-type="bibr" rid="ref133">Premi et al., 2016</xref>). Therefore, the FLTD-CDR is currently commonly used for disease staging in bvFTD. However, with scores ranging from 0&#x2013;3, these global rating scales are unable to capture subtle changes, and several other rating scales assess global functioning more extensively. Frequently used scales that measure daily functioning and independence are the Basic Activities of Daily Living (BADL), the Instrumental ADL (IADL), the Disability Assessment for Dementia (DAD), and the Functional Activities questionnaire (FAQ) (<xref ref-type="bibr" rid="ref75">Katz et al., 1963</xref>; <xref ref-type="bibr" rid="ref94">Lawton and Brody, 1969</xref>; <xref ref-type="bibr" rid="ref131">Pfeffer et al., 1982</xref>; <xref ref-type="bibr" rid="ref52">G&#x00E9;linas et al., 1999</xref>). Overall, literature demonstrated these measures can detect functional decline in bvFTD over extensive follow-up time (1&#x2013;7&#x2009;years) (<xref ref-type="bibr" rid="ref84">Knopman et al., 2008</xref>; <xref ref-type="bibr" rid="ref118">Mioshi and Hodges, 2009</xref>; <xref ref-type="bibr" rid="ref124">O&#x2019;Connor et al., 2016</xref>; <xref ref-type="bibr" rid="ref152">Staffaroni et al., 2019b</xref>; <xref ref-type="bibr" rid="ref54">Giebel et al., 2021</xref>). With regard to behavioral subtypes, a profile of primarily apathy, compared to disinhibition, has been shown to negatively affect daily functioning (DAD) (<xref ref-type="bibr" rid="ref125">O&#x2019;Connor et al., 2017</xref>). However, functional autonomy is often preserved up to moderate disease stages, and therefore, FTD-specific scales incorporating the vast behavioral component in bvFTD are more appropriate. As a response, the FTD-Rating Scale (FTD-FRS) was developed to detect both functional dependence and behavioral changes (<xref ref-type="bibr" rid="ref119">Mioshi et al., 2010</xref>). Longitudinal studies on FTD-FRS captured a multi-domain deterioration over time in sporadic and genetic bvFTD (1&#x2013;5&#x2009;years) (<xref ref-type="bibr" rid="ref29">Devenney et al., 2015</xref>; <xref ref-type="bibr" rid="ref143">Schubert et al., 2016</xref>; <xref ref-type="bibr" rid="ref97">Lima-Silva et al., 2021</xref>). The longitudinal outcome measures with most research evidence are listed in <xref ref-type="table" rid="tab1">Table 1</xref>.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Longitudinal outcome measures with most research evidence in bvFTD.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="left" valign="top">Origin</th>
<th align="left" valign="top">Focus</th>
<th align="left" valign="top">Pro</th>
<th align="left" valign="top">Con</th>
<th align="left" valign="top">Features</th>
<th align="left" valign="top">Subtypes</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="7"><bold>Global functioning</bold></td>
</tr>
<tr>
<td align="left" valign="middle">FTLD-CDR</td>
<td align="left" valign="middle">FTD (adjusted)</td>
<td align="left" valign="middle">Global rating</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x2666;</td>
<td align="left" valign="middle">Low sensitivity</td>
<td align="left" valign="middle">Rating scale (CR-8)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">FTD-FRS</td>
<td align="left" valign="middle">FTD</td>
<td align="left" valign="middle">Multi-domain</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x2666;</td>
<td align="left" valign="middle">NB. variability</td>
<td align="left" valign="middle">Rating scale (IR-30)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7"><bold>Behavior</bold></td>
</tr>
<tr>
<td align="left" valign="middle">FBI</td>
<td align="left" valign="middle">(FT) Dementia</td>
<td align="left" valign="middle">Multi-domain</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">NB. variability</td>
<td align="left" valign="middle">Questionnaire (IR-24)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">CBI-R</td>
<td align="left" valign="middle">(FT) Dementia</td>
<td align="left" valign="middle">Multi-domain</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">NB. variability</td>
<td align="left" valign="middle">Questionnaire (IR-45)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">DAS</td>
<td align="left" valign="middle">Neurodegeneration</td>
<td align="left" valign="middle">Apathy (3D)</td>
<td align="left" valign="middle">&#x25CF; &#x2666;</td>
<td align="left" valign="middle">Lacking follow-up</td>
<td align="left" valign="middle">Questionnaire (PR-24)</td>
<td align="left" valign="middle">Undefined</td>
</tr>
<tr>
<td align="left" valign="middle">SRI</td>
<td align="left" valign="middle">FTLD</td>
<td align="left" valign="middle">Stereotypy</td>
<td align="left" valign="middle">&#x25CF; &#x2666;</td>
<td align="left" valign="middle">Limited follow-up</td>
<td align="left" valign="middle">Questionnaire (IR-5)</td>
<td align="left" valign="middle">Undefined</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7"><bold>(Social) cognition</bold></td>
</tr>
<tr>
<td align="left" valign="middle">ACE-R</td>
<td align="left" valign="middle">(AD) Dementia</td>
<td align="left" valign="middle">Multiple</td>
<td align="left" valign="middle">&#x25B2; &#x25CF;</td>
<td align="left" valign="middle">No social subtest</td>
<td align="left" valign="middle">Screener (PR-26)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">NPA composite scores</td>
<td align="left" valign="middle">Neuro-psychology</td>
<td align="left" valign="middle">Multiple</td>
<td align="left" valign="middle">&#x25B2; &#x25CF;</td>
<td align="left" valign="middle">Time-consuming</td>
<td align="left" valign="middle">Test battery (various)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">NIH-EXAMINER</td>
<td align="left" valign="middle">FTLD</td>
<td align="left" valign="middle">EF and behaviour</td>
<td align="left" valign="middle">&#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">Limited follow-up</td>
<td align="left" valign="middle">Computer tool (PR-6)</td>
<td align="left" valign="middle">Only genetic</td>
</tr>
<tr>
<td align="left" valign="middle">EK-60</td>
<td align="left" valign="middle">Neuro-psychiatry</td>
<td align="left" valign="middle">Emotion recognition</td>
<td align="left" valign="middle">&#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">Inconsistent FU</td>
<td align="left" valign="middle">Test (PR-60)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">IRI</td>
<td align="left" valign="middle">Neuro-psychology</td>
<td align="left" valign="middle">Empathy</td>
<td align="left" valign="middle">&#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">Lacking follow-up</td>
<td align="left" valign="middle">Questionnaire (IR-14)</td>
<td align="left" valign="middle">Mostly genetic</td>
</tr>
<tr>
<td align="left" valign="middle">RSMS</td>
<td align="left" valign="middle">Neuro-psychology</td>
<td align="left" valign="middle">Socio-emotional</td>
<td align="left" valign="middle">&#x25B2;&#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">Limited follow-up</td>
<td align="left" valign="middle">Questionnaire (IR-13)</td>
<td align="left" valign="middle">Mostly genetic</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7"><bold>Neuroimaging</bold></td>
</tr>
<tr>
<td align="left" valign="middle">MRI ROIs</td>
<td align="left" valign="middle">FTD diagnostics</td>
<td align="left" valign="middle">GM atrophy</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x2666;</td>
<td align="left" valign="middle">Relatively late</td>
<td align="left" valign="middle">Structural (volumetry)</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">DTI</td>
<td align="left" valign="middle">Neuro-radiology</td>
<td align="left" valign="middle">WM tract pathology</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x25A0; &#x2666;</td>
<td align="left" valign="middle">Time-consuming</td>
<td align="left" valign="middle">Structural (integrity)</td>
<td align="left" valign="middle">Mostly genetic</td>
</tr>
<tr>
<td align="left" valign="middle">FDG-PET</td>
<td align="left" valign="middle">FTD diagnostics</td>
<td align="left" valign="middle">Glucose metabolism</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x25A0;</td>
<td align="left" valign="middle">Low specificity</td>
<td align="left" valign="middle">Functional</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
<tr>
<td align="left" valign="middle">ASL</td>
<td align="left" valign="middle">Neuro-radiology</td>
<td align="left" valign="middle">Cerebral blood flow</td>
<td align="left" valign="middle">&#x25CF; &#x25A0;</td>
<td align="left" valign="middle">Limited follow-up</td>
<td align="left" valign="middle">Functional</td>
<td align="left" valign="middle">Genetic</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7"><bold>Fluid biomarkers</bold></td>
</tr>
<tr>
<td align="left" valign="middle">NfL (CSF/serum)</td>
<td align="left" valign="middle">Neuronal damage</td>
<td align="left" valign="middle">Neuro-inflammation</td>
<td align="left" valign="middle">&#x25B2; &#x25CF; &#x2666;</td>
<td align="left" valign="middle">Non specific</td>
<td align="left" valign="middle">CNS mechanism</td>
<td align="left" valign="middle">Genetic and sporadic</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Icons of research evidence: &#x25B2; decline over time; &#x25CF; correlated with disease severity; &#x25A0; early abnormalities; &#x2666; FTD-specific. FTLD-CDR, frontotemporal lobar degeneration modified Clinical Dementia Rating scale; FTD-FRS, Frontotemporal Dementia Rating Scale; FBI, Frontal Behavioral Inventory; CBI-R, Cambridge Behavioral Inventory Revised; DAS, Dimensional Apathy Scale; SRI, Stereotypy Rating Inventory; ACE-R, Addenbrook&#x2019;s Cognitive Examination Revised; NPA, neuropsychological assessment; NIH-EXAMINER, Neurobehavioral Evaluation &#x0026; Research; EK-60, Ekman 60-faces test; IRI, Interpersonal Reactivity Index; RSMS, Revised Self-Monitoring Scale; MRI, magnetic resonance imaging; ROIs, regions of interest; DTI, diffusion tensor imaging; FDG-PET, FDG Positron Emission Tomography; ASL, Arterial Spin Labelling; NfL, Neurofilament Light; CSF, cerebrospinal fluid; (bv)FTD, (behavioral variant) frontotemporal dementia; CR, clinician-rated measures (number of items); IR, informant-rated measure (number of items); PR, patient-rated measure (number of items); EF, executive functioning; GM, grey matter; WM, white matter.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec5">
<label>3.2</label>
<title>Behavior</title>
<sec id="sec6">
<label>3.2.1</label>
<title>Important aspects of behavior</title>
<p>Disease progression in bvFTD has been associated with various behavioral changes, from an increase in core features, e.g., decreased socio-emotional abilities and increased multi-dimensional apathy, to specific changes, e.g., increased fat preference and hypersensitivity to loud noises (<xref ref-type="bibr" rid="ref115">Midorikawa et al., 2016</xref>; <xref ref-type="bibr" rid="ref165">Wei et al., 2020</xref>; <xref ref-type="bibr" rid="ref2">Ahmed et al., 2021</xref>; <xref ref-type="bibr" rid="ref47">Foster et al., 2022</xref>), that correlate with FTD-specific progression measures (FTLD-CDR; FTD-FRS; atrophy rates). Alongside behavior, neuropsychiatric symptoms have been frequently reported, such as depression, anxiety, delusions and hallucinations (<xref ref-type="bibr" rid="ref24">Da Silva et al., 2021</xref>). For genetic bvFTD, longitudinal cohorts have described mutation-specific behavioral features that seem to be disease phase specified. In early-intermediate phases, MAPT carriers showed increased predominant behavioral symptoms and C9ORF72 carriers showed increased neuropsychiatric symptoms, where after plateauing takes place (<xref ref-type="bibr" rid="ref156">Tavares et al., 2020</xref>; <xref ref-type="bibr" rid="ref10">Benussi et al., 2021b</xref>). In late stage on the other hand, C9ORF72 carriers showed decreased reports of depression, whereas GRN carriers showed increased depression and anxiety. Furthermore, behavioral profiles have been associated with age of onset, biological sex and cognitive reserve. Specifically, early onset bvFTD presented with more behavioral symptoms, women showed greater frontotemporal atrophy burden with similar clinical characteristics, and there was a (positive) effect of educational level on rate of change in disinhibition (<xref ref-type="bibr" rid="ref98">Linds et al., 2015</xref>; <xref ref-type="bibr" rid="ref41">Fieldhouse et al., 2021</xref>; <xref ref-type="bibr" rid="ref67">Ill&#x00E1;n-Gala et al., 2021a</xref>). The concept of behavioral reserve, i.e., behavioral differences in response to a neuropathological burden, was proposed when individuals with less (negative) behavioral symptoms showed a steeper decline in frontotemporal atrophy (<xref ref-type="bibr" rid="ref81">Kim et al., 2022</xref>). Lastly, it is important to acknowledge the bvFTD phenocopy syndrome (phFTD) as a distinct entity from bvFTD. Apart from clinically mimicking bvFTD while lacking clear etiology, phFTD showed to be non-progressive over an extensive period of time (10+ years) (<xref ref-type="bibr" rid="ref31">Devenney et al., 2018</xref>).</p>
</sec>
<sec id="sec7">
<label>3.2.2</label>
<title>Behavioral measures</title>
<p>Simply rating the frequency of behavioral criteria and neuropsychiatric symptoms on a 5-point scale was sufficient to detect progression over time in genetic FTD (1&#x2013;7&#x2009;years) (<xref ref-type="bibr" rid="ref10">Benussi et al., 2021b</xref>). However, most frequently used informant-based questionnaires quantify behavioral change more comprehensively. The Neuropsychiatric Inventory (NPI), developed to evaluate psychopathology in AD (<xref ref-type="bibr" rid="ref23">Cummings et al., 1994</xref>), generally showed increased scores during follow-up in bvFTD (<xref ref-type="bibr" rid="ref98">Linds et al., 2015</xref>; <xref ref-type="bibr" rid="ref24">Da Silva et al., 2021</xref>). While parts of AD-oriented neuropsychiatric scales, such as the NPI and the Columbia University Scale for Psychopathology in Alzheimer&#x2019;s Disease (CUSPAD), predicted cognitive and functional decline in FTD (2.5&#x2009;years) (<xref ref-type="bibr" rid="ref141">Santacruz Escudero et al., 2019</xref>), associations with disease severity were inconsistent (<xref ref-type="bibr" rid="ref72">Josephs et al., 2011</xref>; <xref ref-type="bibr" rid="ref78">Kazui et al., 2016</xref>; <xref ref-type="bibr" rid="ref136">Ranasinghe et al., 2016</xref>) and the evidence as bvFTD-specific progression marker was insufficient. The Frontal Behavioral Inventory (FBI) covers a range of FTD-related functional and behavioral symptoms, resulting in a positive (e.g., impulsivity; hyperorality) and a negative symptom score (e.g., lack of empathy; apathy) (<xref ref-type="bibr" rid="ref79">Kertesz et al., 1997</xref>). Similar to the FBI, the Cambridge Behavioral Inventory-Revised (CBI-R) assesses frequency of FTD-related symptoms (<xref ref-type="bibr" rid="ref122">Nagahama et al., 2006</xref>; <xref ref-type="bibr" rid="ref164">Wear et al., 2008</xref>). Literature showed the FBI and the CBI-R to be sensitive to progression in sporadic and genetic bvFTD (C9ORF72) more consistently than the NPI, over varying follow-up time (1&#x2013;4&#x2009;years), despite one study stating comparable decline of FBI and NPI (<xref ref-type="bibr" rid="ref107">Marczinski et al., 2004</xref>; <xref ref-type="bibr" rid="ref16">Boutoleau-Bretonniere et al., 2012</xref>; <xref ref-type="bibr" rid="ref98">Linds et al., 2015</xref>; <xref ref-type="bibr" rid="ref124">O&#x2019;Connor et al., 2016</xref>; <xref ref-type="bibr" rid="ref44">Floeter et al., 2017</xref>; <xref ref-type="bibr" rid="ref139">Reus et al., 2018</xref>). A range of questionnaires that aim to evaluate single behavioral features, currently lacking limited longitudinal validation, may serve as promising progression markers, such as the Dimensional Apathy Scale (DAS) (<xref ref-type="bibr" rid="ref134">Radakovic and Abrahams, 2014</xref>), assessing three apathy subtypes in neurodegenerative populations, and the Stereotypy Rating Inventory (SRI) quantifying stereotypic and compulsive behaviors in FTLD (<xref ref-type="bibr" rid="ref147">Shigenobu et al., 2002</xref>). A cross-sectional study on apathy profiles during disease course of bvFTD, showed an increase of DAS scores, while distinguishing emotional apathy in early (&#x003C;5&#x2009;years) and executive apathy in later stages (&#x003E;5&#x2009;years), associated with distinct neurobiological substrates (<xref ref-type="bibr" rid="ref165">Wei et al., 2020</xref>). While one study reported no change of stereotypy over time, the SRI predicted progression of frontotemporal atrophy, institutionalization and death (<xref ref-type="bibr" rid="ref139">Reus et al., 2018</xref>; <xref ref-type="bibr" rid="ref57">Gossink et al., 2019</xref>) (<xref ref-type="table" rid="tab1">Table 1</xref>).</p>
</sec>
<sec id="sec8">
<label>3.2.3</label>
<title>Course of behavioral symptoms</title>
<p>During disease progression in bvFTD behavioral symptoms may vary, initial behaviors fade whilst new behaviors appear, showing behavioral trajectories are not linear (<xref ref-type="bibr" rid="ref34">Diehl-Schmid et al., 2006</xref>). The majority of longitudinal studies (including a clinico-pathological study) supported a crescendo-decrescendo trajectory of behavior in bvFTD, in which progressive and diverse behavioral disturbances were followed by dominating apathy (<xref ref-type="bibr" rid="ref21">Chow et al., 2012</xref>; <xref ref-type="bibr" rid="ref124">O&#x2019;Connor et al., 2016</xref>; <xref ref-type="bibr" rid="ref14">Borges et al., 2019</xref>; <xref ref-type="bibr" rid="ref22">Cosseddu et al., 2019</xref>). In detail, positive symptoms (such as disinhibition and perseverations) increased until intermediate phases, whereas negative symptoms (such as apathy and loss of empathy) increased throughout disease course. In addition, increased apathy predicted mortality, as stated in a principal component analysis using the Apathy Evaluation Scale (AES), NPI and CBI sub scores (<xref ref-type="bibr" rid="ref92">Lansdall et al., 2019</xref>). While one study did not report such behavioral inflection point during follow-up (<xref ref-type="bibr" rid="ref98">Linds et al., 2015</xref>), the relative reduction of positive symptoms may show improvement of behavioral scores over time (<xref ref-type="bibr" rid="ref84">Knopman et al., 2008</xref>). Similarly, neuropsychiatric symptoms showed to change over time, with symptoms of depression and anxiety in preclinical and prodromal phases, followed by delusions, hallucinations and euphoria in the symptomatic phase (<xref ref-type="bibr" rid="ref89">Lagan&#x00E0; et al., 2022</xref>).</p>
</sec>
</sec>
<sec id="sec9">
<label>3.3</label>
<title>(Social) cognition</title>
<sec id="sec10">
<label>3.3.1</label>
<title>Important aspects of cognition</title>
<p>In current international diagnostic criteria, the cognitive profile of bvFTD is characterized by executive deficits, with relative sparing of memory and visuospatial functioning (<xref ref-type="bibr" rid="ref138">Rascovsky et al., 2011</xref>). However, memory deficits have been increasingly recognized in bvFTD, at initial presentation and over time (<xref ref-type="bibr" rid="ref135">Ramanan et al., 2017</xref>). A minority of bvFTD (20%) may present with intact cognition at first visit, and thereafter, cognitive decline is variable (<xref ref-type="bibr" rid="ref61">Hornberger et al., 2008</xref>; <xref ref-type="bibr" rid="ref32">Diehl-Schmid et al., 2011</xref>; <xref ref-type="bibr" rid="ref29">Devenney et al., 2015</xref>). For genetic bvFTD, mutation-specific cognitive profiles and trajectories have been identified: characterized decline of confrontational naming, episodic and semantic memory in MAPT carriers, variable deficits (with frequent executive dysfunction) in GRN carriers, and a global and relatively stable profile (e.g., mildly slowed processing speed) in C9ORF72 carriers (<xref ref-type="bibr" rid="ref132">Poos et al., 2020</xref>; <xref ref-type="bibr" rid="ref6">Barker et al., 2021</xref>). Pathology-specific profiles point to impaired visual construction in tau-positive FTLD and confrontation naming in tau-negative FTLD, and linguistic deficits in FTLD-TDP (<xref ref-type="bibr" rid="ref59">Grossman et al., 2008</xref>; <xref ref-type="bibr" rid="ref77">Kawakami et al., 2021</xref>). Furthermore, multiple studies identified several protective factors of cognitive reserve, i.e., the resilience against neuropathological burden due to lifetime cognitive experiences. Proxies of cognitive reserve included educational level, occupational attainment, late-life social and leisure lifestyle, and specific occupation activities with social skills and cognitive control, which were associated to frontotemporal abnormalities on multiple imaging modalities, including involvement of areas associated to social functioning (prefrontal, anterior temporal and insula) (<xref ref-type="bibr" rid="ref35">Dodich et al., 2018</xref>; <xref ref-type="bibr" rid="ref103">Maiovis et al., 2018</xref>; <xref ref-type="bibr" rid="ref109">Massimo et al., 2019</xref>; <xref ref-type="bibr" rid="ref82">Kinney et al., 2021</xref>).</p>
</sec>
<sec id="sec11">
<label>3.3.2</label>
<title>Cognitive measures</title>
<p>Cognitive screeners are short, widely used and easily administered instruments to assess global cognition. In bvFTD, most frequently used cognitive screeners are the Mini-Mental State Examination [MMSE; (<xref ref-type="bibr" rid="ref46">Folstein et al., 1975</xref>)], the Frontal Assessment Battery [FAB; (<xref ref-type="bibr" rid="ref37">Dubois et al., 2000</xref>)] and, originated as extension of the MMSE, the Addenbrook&#x2019;s Cognitive Examination Revised [ACE-R; (<xref ref-type="bibr" rid="ref116">Mioshi et al., 2006</xref>)]. These screeners were not developed for bvFTD, and have proven to be effective in diagnosing or differentiating AD, by emphasizing memory and orientation (MMSE), executive functions (FAB) or briefly covering multiple domains (ACE-R). Literature demonstrated declines of MMSE, FAB and ACE-R total scores in bvFTD (<xref ref-type="bibr" rid="ref118">Mioshi and Hodges, 2009</xref>; <xref ref-type="bibr" rid="ref29">Devenney et al., 2015</xref>; <xref ref-type="bibr" rid="ref143">Schubert et al., 2016</xref>; <xref ref-type="bibr" rid="ref139">Reus et al., 2018</xref>), but a principal component analysis of these measures (reflecting global cognitive status) showed no association with mortality (<xref ref-type="bibr" rid="ref92">Lansdall et al., 2019</xref>). For MMSE in specific, rates of decline are known to be lacking or modest, and unrelated to frontotemporal changes on multiple neuroimaging modalities (<xref ref-type="bibr" rid="ref15">Borroni et al., 2010</xref>; <xref ref-type="bibr" rid="ref155">Tan et al., 2013</xref>; <xref ref-type="bibr" rid="ref133">Premi et al., 2016</xref>; <xref ref-type="bibr" rid="ref96">Leroy et al., 2021</xref>). Due to its comprehensive, yet feasible design, the ACE-R is a more valid cognitive progression screener for bvFTD, with marked rates of decline over follow-up (1&#x2013;5&#x2009;years) (<xref ref-type="bibr" rid="ref118">Mioshi and Hodges, 2009</xref>; <xref ref-type="bibr" rid="ref29">Devenney et al., 2015</xref>; <xref ref-type="bibr" rid="ref143">Schubert et al., 2016</xref>). Regarding single tests, the letter fluency detected decline over 18&#x2009;months in genetic bvFTD (mostly C9ORF72), associated to frontotemporal atrophy and FTLD-CDR progression (<xref ref-type="bibr" rid="ref42">Floeter et al., 2016</xref>, <xref ref-type="bibr" rid="ref44">2017</xref>; <xref ref-type="bibr" rid="ref1">Agarwal et al., 2019</xref>). However, given cognitive heterogeneity, combining multiple test scores into (executive functioning, language and memory) composites is known to increase sensitivity to change and ability to detect annual decline in bvFTD (<xref ref-type="bibr" rid="ref84">Knopman et al., 2008</xref>). A combination of ACE-R, executive function and IADL showed to differentiate progressive from non-progressive bvFTD (3&#x2009;years) (<xref ref-type="bibr" rid="ref62">Hornberger et al., 2009</xref>). Developed as a clinical trial endpoint, the Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research (NIH-EXAMINER), detected executive and behavioral decline over 18&#x2009;months in presymptomatic genetic FTD, and was associated with brain volume loss and FTLD-CDR (<xref ref-type="bibr" rid="ref151">Staffaroni et al., 2019a</xref>) (<xref ref-type="table" rid="tab1">Table 1</xref>). Promising digital tools may increase the sensitivity of cognitive assessment, such as semi-structured speech samples that captured decline of fluency and grammaticality (2&#x2009;years), associated with frontotemporal atrophy (<italic>N</italic>&#x2009;=&#x2009;14) (<xref ref-type="bibr" rid="ref4">Ash et al., 2019</xref>).</p>
</sec>
<sec id="sec12">
<label>3.3.3</label>
<title>Course of cognitive symptoms</title>
<p>Despite cognitive heterogeneity, disease progression in bvFTD has been marked by decline in executive functioning, memory, language and attention (1 to 8&#x2009;years) (<xref ref-type="bibr" rid="ref13">Blair et al., 2007</xref>; <xref ref-type="bibr" rid="ref167">Wicklund et al., 2007</xref>; <xref ref-type="bibr" rid="ref149">Smits et al., 2015</xref>; <xref ref-type="bibr" rid="ref135">Ramanan et al., 2017</xref>). The earliest stage was characterized by error insensitivity, slower response time and poor naming, while later stages showed deterioration in a range of executive functions, language and memory, visuo-construction and calculations (<xref ref-type="bibr" rid="ref136">Ranasinghe et al., 2016</xref>). If impaired at presentation, executive dysfunction was most potent predictor of progression, including grey matter atrophy, institutionalization and mortality (<xref ref-type="bibr" rid="ref61">Hornberger et al., 2008</xref>; <xref ref-type="bibr" rid="ref57">Gossink et al., 2019</xref>). Also, language impairment was associated with mortality (<xref ref-type="bibr" rid="ref51">Garcin et al., 2009</xref>). Studies reported specific patterns of (episodic) memory impairment, with temporal and spatial memory deficits in progressive bvFTD (<xref ref-type="bibr" rid="ref69">Irish et al., 2012</xref>), and a vulnerability for recent autobiographical memory over time, likely to reflect an encoding deficit rather than retrieval deficit (<xref ref-type="bibr" rid="ref70">Irish et al., 2018</xref>).</p>
</sec>
<sec id="sec13">
<label>3.3.4</label>
<title>Social cognition</title>
<p>Social cognition deficits are prominent and early features of bvFTD. Social cognition encompasses multiple processes of perceiving, interpreting and regulating social stimuli, including emotion recognition, theory of mind (understanding the cognitive or affective state of others) and social reasoning. Overall, social cognition tests have been well validated for diagnosing bvFTD, but literature on progression is limited. A longitudinal study on emotion recognition, assessed with the Ekman 60-faces test (<xref ref-type="bibr" rid="ref5">Aw et al., 2002</xref>), reported decline during follow-up (1.5&#x2009;years), with most rapid decline in bvFTD with marked atrophy (<xref ref-type="bibr" rid="ref88">Kumfor et al., 2014</xref>). However, other studies did not support this decline, reporting no change or improvement on the Ekman-60-faces over 3&#x2009;years (<xref ref-type="bibr" rid="ref93">Lavenu and Pasquier, 2005</xref>; <xref ref-type="bibr" rid="ref139">Reus et al., 2018</xref>). The addition of different intensities of emotions in the Emotion Recognition Task [ERT; (<xref ref-type="bibr" rid="ref80">Kessels et al., 2007</xref>)] showed to increase diagnostic sensitivity, even in presymptomatic C9ORF72 carriers (<xref ref-type="bibr" rid="ref71">Jiskoot et al., 2021</xref>), but longitudinal research is needed. Similarly, first studies on theory of mind (ToM), using different proxies, are inconclusive. One study showed no change of ToM within repeated measures of the Faux Pas test (3&#x2009;years) (<xref ref-type="bibr" rid="ref139">Reus et al., 2018</xref>), while performance on Reading the Mind in the Eyes test showed promising associations with disease severity, distinguishing impairment of affective ToM in mild stages from cognitive ToM in severe stages (<xref ref-type="bibr" rid="ref159">Torralva et al., 2015</xref>). Longitudinal assessment of sarcasm detection, assessed with The Awareness of Social Inference Test [TASIT; (<xref ref-type="bibr" rid="ref110">McDonald et al., 2003</xref>)], showed a decline in cases with marked atrophy only, indicating it is relatively spared in early stages (<xref ref-type="bibr" rid="ref88">Kumfor et al., 2014</xref>). Lastly, a cross-sectional study associated distinct social symptoms, as measured by the Social Impairment Rating Scale (SIRS), with three socially relevant (corticolimbic) networks to (<xref ref-type="bibr" rid="ref11">Bickart et al., 2014</xref>). However, this promising clinician-rated scale requires longitudinal validation. Inconsistent findings in social cognition trajectories highlight current hurdles in the methodology of social cognition assessment, such as possible floor effects due to early impairment and lack of systematic longitudinal multi-level assessment. Novel technologies may improve detection of gradual social cognition decline. Based on the phenomenon of &#x201C;emotional blunting,&#x201D; first results on physiological measures (e.g., altered skin conduction or eye gaze) in bvFTD are promising (<xref ref-type="bibr" rid="ref73">Joshi et al., 2014</xref>; <xref ref-type="bibr" rid="ref65">Hutchings et al., 2018</xref>; <xref ref-type="bibr" rid="ref148">Singleton et al., 2022</xref>). Implementation of biometry might capture objective processes related to social functioning (independent of cognitive or cultural factors), highlighting its potential value as (universal) clinical progression marker. Importantly, informant-rated questionnaires on impaired social behavior propose promising markers for progression (<xref ref-type="table" rid="tab1">Table 1</xref>) such as the Revised Self Monitoring Scale (RSMS) and the (modified) Interpersonal Reactivity Index (IRI) (<xref ref-type="bibr" rid="ref25">Davis, 1980</xref>, <xref ref-type="bibr" rid="ref26">1983</xref>; <xref ref-type="bibr" rid="ref47">Foster et al., 2022</xref>). Socioemotional sensitivity, assessed with the RSMS, showed decline over one year in sporadic and genetic bvFTD, associated to salience network atrophy and caregiver burden (<xref ref-type="bibr" rid="ref158">Toller et al., 2020</xref>). Yet, correlations between RSMS and social network abnormalities were not supportive, suggesting the true brain-behavior relationship requires further investigation (<xref ref-type="bibr" rid="ref157">Toller et al., 2022</xref>). Thus far, the IRI, assessing empathetic abilities, was only validated through cross-sectional associations with disease severity (FTLD-CDR) in symptomatic genetic bvFTD, as well as prodromal C9ORF72 carriers (<xref ref-type="bibr" rid="ref47">Foster et al., 2022</xref>).</p>
</sec>
</sec>
<sec id="sec14">
<label>3.4</label>
<title>Neuroimaging</title>
<p>Since bvFTD is marked by typical frontal and (anterior) temporal atrophy, hypometabolism or hypoperfusion (<xref ref-type="bibr" rid="ref138">Rascovsky et al., 2011</xref>), the use of neuroimaging offers an essential measure of disease progression. Neuroimaging techniques include a wide range of structural and functional modalities that quantify patterns of grey matter atrophy, white matter integrity, metabolism, perfusion, network connectivity and other processes associated with bvFTD.</p>
<sec id="sec15">
<label>3.4.1</label>
<title>Regional atrophy patterns</title>
<p>In general, structural magnetic resonance imaging (MRI) is able to detect frontotemporal grey matter (GM) atrophy patterns during disease progression of bvFTD, by means of quantitative techniques such as voxel-based morphometry (VBM) and deformation-based morphometry (DBM) (<xref ref-type="table" rid="tab1">Table 1</xref>). Whole brain atrophy and ventricular volume increased in both genetic and sporadic bvFTD, in several one-year follow-up studies and one six-month follow-up (<xref ref-type="bibr" rid="ref83">Knopman et al., 2009</xref>; <xref ref-type="bibr" rid="ref56">Gordon et al., 2010</xref>; <xref ref-type="bibr" rid="ref90">Lam et al., 2014</xref>; <xref ref-type="bibr" rid="ref42">Floeter et al., 2016</xref>; <xref ref-type="bibr" rid="ref146">Sheelakumari et al., 2018</xref>; <xref ref-type="bibr" rid="ref106">Manera et al., 2019</xref>; <xref ref-type="bibr" rid="ref55">Gordon et al., 2021</xref>). Over varying follow-up (from 6&#x2009;months to 2.5&#x2009;years), the increase of GM atrophy was associated with various validated clinical measures of disease progression, such as the CDR, CDR-FTD, MMSE, and, in neuropsychological testing, letter fluency scores (<xref ref-type="bibr" rid="ref56">Gordon et al., 2010</xref>; <xref ref-type="bibr" rid="ref42">Floeter et al., 2016</xref>; <xref ref-type="bibr" rid="ref152">Staffaroni et al., 2019b</xref>; <xref ref-type="bibr" rid="ref68">Ill&#x00E1;n-Gala et al., 2021b</xref>). Volumetric studies, with mostly extensive follow-up (2.5&#x2013;5&#x2009;years), showed fastest progression rates in the temporal lobe (compared with frontal), whereas distinctive regions such as the primary and sensory cortices remain spared (<xref ref-type="bibr" rid="ref144">Seeley et al., 2008</xref>; <xref ref-type="bibr" rid="ref48">Frings et al., 2012</xref>; <xref ref-type="bibr" rid="ref152">Staffaroni et al., 2019b</xref>; <xref ref-type="bibr" rid="ref166">Whitwell et al., 2020</xref>). However, since many years regional GM atrophy patterns are known to be heterogeneous in bvFTD, of which a cross-sectional study suggested at least four distinct (data-driven) subtypes (<xref ref-type="bibr" rid="ref86">Kril et al., 2005</xref>; <xref ref-type="bibr" rid="ref137">Ranasinghe et al., 2021</xref>). Regarding specific regions-of-interest (ROIs), one longitudinal study found a pattern of increased atrophy primarily in the pallidum, middle temporal gyrus, inferior frontal and middle orbitofrontal gyrus, cingulate gyrus and insula over one year (<xref ref-type="bibr" rid="ref3">Anderl-Straub et al., 2021</xref>). Other ROI-based studies stated the following regions of importance for longitudinal change: anterior cingulate, paracingulate, medial temporal, medial frontal and insular regions (1&#x2009;year) (<xref ref-type="bibr" rid="ref17">Brambati et al., 2007</xref>), the medial and lateral frontal lobes, insula, striatum and bilateral temporo-parietal regions (1&#x2009;year) (<xref ref-type="bibr" rid="ref12">Binney et al., 2017</xref>), and early and continuing orbitofrontal, anterior cingulate, temporal and subcortical, primarily striatal, regions (1&#x2013;4&#x2009;year) (<xref ref-type="bibr" rid="ref91">Landin-Romero et al., 2017</xref>). Specific regions have been correlated with decline on clinical measures, such as (left) striatum atrophy and the FTLD-CDR and FBI negative subscale (cross-sectional) (<xref ref-type="bibr" rid="ref100">Macfarlane et al., 2015</xref>), posterior parietal atrophy and loss of recent autobiographical memory over one year (<xref ref-type="bibr" rid="ref70">Irish et al., 2018</xref>), and olfactory bulb atrophy (specific to more severe disease stages) and olfactory dysfunction (loss of smell) over 1&#x2009;year (<xref ref-type="bibr" rid="ref19">Carnemolla et al., 2022</xref>).</p>
</sec>
<sec id="sec16">
<label>3.4.2</label>
<title>White matter integrity patterns</title>
<p>A relatively large amount of studies on diffusion tensor imaging (DTI), visualizing the microstructure of white matter (WM) tracts, concluded sensitive detection of WM changes in an early phase of the disease, over varying follow-up time (0.5 to 2.5&#x2009;years) (<xref ref-type="bibr" rid="ref101">Mahoney et al., 2015</xref>; <xref ref-type="bibr" rid="ref39">Elahi et al., 2017</xref>; <xref ref-type="bibr" rid="ref43">Floeter et al., 2018</xref>; <xref ref-type="bibr" rid="ref74">Kassubek et al., 2018</xref>; <xref ref-type="bibr" rid="ref152">Staffaroni et al., 2019b</xref>). DTI may detect bvFTD pathology before GM atrophy arises, and has been correlated with cognitive decline (cross-sectional ACE-R), contributing to its value as possible early and sensitive progression marker (<xref ref-type="bibr" rid="ref20">Chen and Kantarci, 2020</xref>) (<xref ref-type="table" rid="tab1">Table 1</xref>). More general, WM tract pathology can be measured by multiple techniques. It&#x2019;s microtructural integrity can be detected by diffusion-weighted imaging (DWI), of which DTI is a relevant modality as it enables the tracking of WM-fibers (tractography). Macro-structurally, WM pathology can be measured by structural MRI. Progression of WM microstructural disintegrity, as detected by DTI, showed fast rates in early bvFTD (1&#x2009;year) (<xref ref-type="bibr" rid="ref90">Lam et al., 2014</xref>). WM volume, as measured with structural MRI, manifested a steeper decline, especially in the temporal lobe, compared to early GM orbitofrontal and insula atrophy (1&#x2009;year, <italic>N</italic>&#x2009;=&#x2009;15) (<xref ref-type="bibr" rid="ref49">Frings et al., 2014</xref>). WM pathology has been correlated with a decline in executive functioning (1&#x2009;year) (<xref ref-type="bibr" rid="ref170">Yu and Lee, 2019</xref>), the presence of a MOPB-risk allele (<xref ref-type="bibr" rid="ref108">Massimo et al., 2021</xref>) and an increase of WM hyperintensities, both independent of and related to cortical atrophy (cross-sectional) (<xref ref-type="bibr" rid="ref66">Huynh et al., 2021</xref>). In contrast, one cross-sectional study on a clinically relevant outcome measure (Revised Self-Monitoring Scale), found that GM volumes of the right orbitofrontal cortex, not WM tract pathology (DWI), predicted socioemotional impairment (<xref ref-type="bibr" rid="ref157">Toller et al., 2022</xref>).</p>
</sec>
<sec id="sec17">
<label>3.4.3</label>
<title>Changes in metabolism, perfusion and network connectivity</title>
<p>A prospective study on glucose metabolism (fludeoxyglucose-positron emission tomography; FDG-PET) indicated a specific progression pattern over 1.5&#x2009;years, from decreased glucose uptake in frontal lobe(s), to parietal and temporal lobe(s), to whole frontal lobe hypometabolism (<xref ref-type="bibr" rid="ref33">Diehl-Schmid et al., 2007</xref>) (<xref ref-type="table" rid="tab1">Table 1</xref>). A genetic study on arterial spin labelling (ASL) in FTD patients, measuring cerebral blood flow (CBF), showed that a specific pattern of frontal, temporal, parietal and subcortical CBF decrease accompanied the clinical conversion from pre-symptomatic to symptomatic stages in MAPT and GRN mutation carriers over 2&#x2009;years (<xref ref-type="bibr" rid="ref36">Dopper et al., 2016</xref>). Multiple promising, yet cross-sectional, studies on single photon emission computer tomography (SPECT) reported a decrease in regional CBF in bilateral frontal cortices and right temporal cortices that correlated with several clinical measures, such as the FTLD-CDR, FTD-FRS, and cognitive reserve scales (<xref ref-type="bibr" rid="ref15">Borroni et al., 2010</xref>; <xref ref-type="bibr" rid="ref102">Maiovis et al., 2017</xref>, <xref ref-type="bibr" rid="ref103">2018</xref>), as well as specific brainstem hypoperfusion that associated with fast clinical progression in bvFTD (<xref ref-type="bibr" rid="ref95">Le Ber et al., 2006</xref>). Connectivity changes of the salience network (SN), related to the fundamental behavioral and socioemotional deficits in bvFTD, may be measured with functional MRI (fMRI). Although only reported in a small study with limited longitudinal data (8&#x2009;weeks), specific SN connectivity patterns (e.g., decreased right fronto-dorsal SN) were associated with increased apathy measured with FBI (<xref ref-type="bibr" rid="ref27">Day et al., 2013</xref>). While lacking longitudinal data, two small yet promising cross-sectional studies on disruption of sensory/auditory information processing, as measured by magnetoencephalography (MEG) analysis of cortical microcircuits, suggested these changes in frontotemporal networks may be a useful biomarker to detect (early) disease progression (2013, <italic>N</italic>&#x2009;=&#x2009;12, 2019, <italic>N</italic>&#x2009;=&#x2009;44) (<xref ref-type="bibr" rid="ref63">Hughes and Rowe, 2013</xref>; <xref ref-type="bibr" rid="ref145">Shaw et al., 2019</xref>).</p>
</sec>
<sec id="sec18">
<label>3.4.4</label>
<title>Other pathological processes</title>
<p>While studied in limited follow-up or cross-sectional designs, additional PET and MRI-based techniques, focusing on other pathological processes may hold promise as biomarkers of disease progression. First, a small prospective study (<italic>N</italic>&#x2009;=&#x2009;10) detected progression of tau-pathology by means of flortaucipir-PET in the frontotemporal region after 1.5&#x2009;months, and suggested that FTD-specific (tau) tracers could potentially be of superior value (<xref ref-type="bibr" rid="ref160">Tsai et al., 2019</xref>). Second, a couple of cross-sectional studies detected processes of synaptic loss (11C-UCB-J-PET, <italic>N</italic>&#x2009;=&#x2009;11) (<xref ref-type="bibr" rid="ref104">Malpetti et al., 2021</xref>, <xref ref-type="bibr" rid="ref105">2022</xref>), and reduced brain stiffness, which is hypothesized to occur prior to gliosis and cellular damage (magnetic resonance elastography, <italic>N</italic>&#x2009;=&#x2009;5) (<xref ref-type="bibr" rid="ref64">Huston et al., 2016</xref>). Both processes may be associated with early disease progression in bvFTD.</p>
</sec>
</sec>
<sec id="sec19">
<label>3.5</label>
<title>Fluid biomarkers</title>
<p>Most validated fluid biomarkers are primarily used to differentiate bvFTD from AD, other neurodegenerative disease, or PPD, without being able to accurately diagnose or sensitively monitor bvFTD itself. Current methods do not yet enable <italic>in vivo</italic> quantification of bvFTD pathologies, i.e., aggregation and accumulation of abnormal protein inclusions, primarily tau, TAR DNA-binding protein 43 (TDP-43) or FUS. However, the use of fluid biomarkers may reveal processes that lay closest to pathogenesis and progression of disease, and significant progress has been made. Genetic bvFTD, associated with mutation-related proteinopathies (tau in MAPT, and TDP-43 in GRN and C9ORF72), may serve as a solid base to predict underlying pathology and disease mechanisms. Since this is not yet possible in sporadic bvFTD, similar techniques may ultimately facilitate prediction of underlying pathology in the sporadic variant too. Detection of several fluid biomarkers, through cerebrospinal fluid (CSF) or, less invasive, through serum/plasma, may enable an evaluation of underlying proteinopathies and various downstream effects of neurodegeneration.</p>
<sec id="sec20">
<label>3.5.1</label>
<title>Biomarkers indicative of underlying proteinopathies</title>
<p>To date, no fluid biomarkers are known that enable specific detection of bvFTD. A first prospective study on a bvFTD specific proteinopathy related to progranulin (PGRN), which is a protective protein altered in GRN mutation carriers which results in pathological TDP-43 accumulation, showed no significant change in CSF or serum PGRN levels at one-year follow-up (<xref ref-type="bibr" rid="ref40">Feneberg et al., 2016</xref>). Despite apparent variability, PGRN concentrations did decrease in four out of five FTD patients, calling for further large scale investigation. Next to this, CSF amyloid-beta, which is typically decreased in AD, showed to decrease in both genetic and sporadic bvFTD over five year follow-up, and has been associated with higher mortality (<xref ref-type="bibr" rid="ref161">Vieira et al., 2019</xref>). Cross-sectional studies on other AD-related proteins showed alternations in bvFTD as well, such as plasma tau and the phosphorylated-tau/total-tau ratio (<xref ref-type="bibr" rid="ref45">Foiani et al., 2018</xref>; <xref ref-type="bibr" rid="ref112">Meeter et al., 2018</xref>). However, since these protein profiles are not specific to bvFTD, and did not correlate with important progression measures such as whole brain volume, GM atrophy, neurofilament light chain (NfL), or disease duration, they do not have much potential to measure disease progression (<xref ref-type="bibr" rid="ref45">Foiani et al., 2018</xref>; <xref ref-type="bibr" rid="ref112">Meeter et al., 2018</xref>).</p>
</sec>
<sec id="sec21">
<label>3.5.2</label>
<title>Downstream effects of neurodegeneration</title>
<p>Currently, the most promising fluid biomarker, measured in both CSF and serum, is neurofilament light chain (NfL), reflecting axonal damage (<xref ref-type="table" rid="tab1">Table 1</xref>). Longitudinal studies, with 9 to 12&#x2009;months follow-up, concluded levels of CSF or serum NfL increased over time, in both genetic and sporadic bvFTD (<xref ref-type="bibr" rid="ref99">Ljubenkov et al., 2018</xref>; <xref ref-type="bibr" rid="ref53">Gendron et al., 2022</xref>). Additionally, serum NfL was found to predict clinical conversion from a prodromal to a symptomatic phase in a genetic bvFTD cohort at one-year follow-up (<xref ref-type="bibr" rid="ref7">Benussi et al., 2021a</xref>). Increased CSF NfL, in both genetic and sporadic subtypes, has been associated with various progression measures, including CDR, cognition (executive functioning; neuropsychiatry unit cognitive assessment tool), behavioral symptoms (FBI), frontotemporal GM atrophy, WM tract pathophysiology, GABA-ergic deficit, and survival rates (<xref ref-type="bibr" rid="ref142">Scherling et al., 2014</xref>; <xref ref-type="bibr" rid="ref74">Kassubek et al., 2018</xref>; <xref ref-type="bibr" rid="ref154">Steinacker et al., 2018</xref>; <xref ref-type="bibr" rid="ref8">Benussi et al., 2020</xref>; <xref ref-type="bibr" rid="ref150">Spotorno et al., 2020</xref>; <xref ref-type="bibr" rid="ref163">Walia et al., 2022</xref>). Interestingly, when comparing genetic and sporadic subtypes, a large cross-sectional study concluded that serum NfL concentration is higher in genetic bvFTD (<xref ref-type="bibr" rid="ref9">Benussi et al., 2022</xref>). Another promising, less validated fluid biomarker is soluble triggering receptor expressed on myeloid cells 2 (sTREM2). Also interpreted as a more general response to neuronal injury, first cross-sectional results showed CSF sTREM2 levels increased during neuro-inflammation in familial bvFTD associated with GRN mutations (<italic>N</italic>&#x2009;=&#x2009;3) (<xref ref-type="bibr" rid="ref168">Woollacott et al., 2018</xref>). Contrarily, first cross-sectional results on glial fibrillary acidic protein (GFAP), suggesting to reflect reactive astrogliosis, showed less promising results as suitable progression marker in genetic and sporadic bvFTD, since merely small changes in serum concentration of GFAP were detected (cross-sectional) (<xref ref-type="bibr" rid="ref126">Oeckl et al., 2022</xref>). The neurotransmitter orexin A, known for regulation of various physiological functions (such as appetite and sleep), has been correlated with obsessive-compulsive (measured by SRI) and extrapyramidal symptoms, that may accompany disease progression (cross-sectional, <italic>N</italic>&#x2009;=&#x2009;40) (<xref ref-type="bibr" rid="ref140">Roveta et al., 2022</xref>). Lastly, specific metabolic changes were found in bvFTD (compared to controls), such as altered metabolites in a wide range of pathways (including amino acids, energy and carbohydrate, cofactor and vitamin, lipid and nucleotide) and increased fat preference, offering a new field to reveal possible physiological progression markers (<italic>N</italic>&#x2009;=&#x2009;30, <italic>N</italic>&#x2009;=&#x2009;20) (<xref ref-type="bibr" rid="ref121">Murley et al., 2020</xref>; <xref ref-type="bibr" rid="ref2">Ahmed et al., 2021</xref>). However, for all suggested fluid biomarkers, e.g., NfL, sTREM2, GFAP, Orexin A as well as metabolic features, longitudinal observations are needed and highly recommended, before they can be evaluated in their potential to track disease progression.</p>
</sec>
</sec>
</sec>
<sec sec-type="discussion" id="sec22">
<label>4</label>
<title>Discussion</title>
<p>The purpose of this scoping review was to provide an overview of longitudinal studies in bvFTD and evaluate current assessment tools to monitor disease progression. The clinical markers of progression with most research evidence included FTD-specific rating scales, informant-rated multi-domain behavioral measures, comprehensive cognitive screener or composite scores, and few social cognition tools. The neuroimaging markers of progression with most research evidence included modalities detecting volumetric grey matter atrophy and white matter pathology, and to a lesser extent hypometabolism and hypoperfusion. Regarding fluid biomarkers, NfL was most researched and most valid, clearly showing significant decline over time. While more (extensive) longitudinal research and/or more sensitive markers of progression are advised, we propose a multimodal approach in bvFTD. To acknowledge the multi-dimensional heterogeneity, as found in behavior, cognition, neuroimaging features and biofluid levels, a combined set of progression markers is recommended, adjusted to genetic and sporadic variants.</p>
<p>The central recommendations of this scoping review are listed in <xref ref-type="fig" rid="fig2">Figure 2</xref>. For future clinical trials, it is important to use outcome measures that are both easily administered and adequately detect clinically meaningful and biologically relevant changes in bvFTD. With regard to global functioning, the FTLD-CDR can be used for coarse staging, while the FTD-FRS offers a more sensitive measure for subtle changes and multiple domains. To anticipate on the complexity of behavioral change, i.e., heterogeneous profiles and inter-behavioral variability, the FBI or CBI-R are generally applicable due to their ability to aggregate the sum of behaviors, whereas separate specific scales (e.g., SRI or DAS) may be tailored to an individual&#x2019;s baseline profile. Since clinical trials intend to intervene in early and intermediate stages, characterized by relatively diverse behavioral symptoms, behavioral inflection points should be taken into account. For instance, a crescendo-decrescendo pattern, including dominating apathy (measured with DAS or sub scores of FBI or CBI) in late stages, must be considered while interpreting, and ultimately modify, change over time. Regarding cognition, the ACE-R can be used as a brief and feasible screener, along with IRI and/or RSMS questionnaires assessing social cognitive changes. Given the fundamental and consistent role of socio-emotional deficits in the clinical phenotype of bvFTD, accurate social cognition assessment is prioritized over domain composite scores. When optimized, social cognition testing may provide easily administered and clinically meaningful measures, ideally related to specific biological changes and respecting individual (social) behavioral reserve. However, present social cognition tools require further longitudinal, preferably cross-cultural, validation and improved psychometrics to overcome floor effects. Targeted progress should focus on structured multi-level (social perception, interpretation and regulation) and multi-modal (informant-rated and patient-recorded/biometric) assessment, able to objectify gradual decline of social cognition. For neuroimaging, we suggest an approach on group level and individual level. On the group level, important ROIs for longitudinal change have been identified in frontal (incl. orbitofrontal), temporal, limbic (incl. anterior cingulate and insula) and striatal regions, next to genotype-specific GM atrophy patterns. In addition, WM disintegration patterns (DTI) and CBF changes (ASL) enable earlier and more sensitive detection than GM atrophy. Considering the need to capture individual variation, we suggest ROIs corrected for baseline atrophy patterns to follow individual-specific progression profiles. This may be used for individual monitoring in clinical practice, as well as averaged ROI-change in clinical trials. While upcoming techniques hold promise for gene and pathology-specific fluid biomarkers, current longitudinal studies indicate NfL as most potent progression marker in bvFTD. Importantly, rapid developments in technology point to novel digital biomarkers. While these are promising, at present, literature mostly involves cross-sectional studies in AD. Examples are speech-based artificial intelligence (AI) applications predicting cognitive decline (<xref ref-type="bibr" rid="ref50">Fristed et al., 2022</xref>), biometric measures (e.g., skin conduction, pupillometry and eye-tracking patterns) reflecting social-emotional and/or linguistic deficits (<xref ref-type="bibr" rid="ref113">Mendez et al., 2018</xref>; <xref ref-type="bibr" rid="ref148">Singleton et al., 2022</xref>; <xref ref-type="bibr" rid="ref38">El Haj et al., 2024</xref>), AI-based imaging algorithms for longitudinal brain mapping (<xref ref-type="bibr" rid="ref130">P&#x00E9;rez-Millan et al., 2023</xref>), and proteomics technology detecting protein profiles (<xref ref-type="bibr" rid="ref76">Katzeff et al., 2022</xref>).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Central recommendations for a multi-modal approach and future research in bvFTD. <sup>&#x002A;</sup>SRI, Stereotypy Rating Inventory; DAS, Dimensional Apathy Scale; IRI, Interpersonal Reactivity Index; RSMS, Revised Self-Monitoring Scale; NPA, neuropsychological assessment; NIH-EXAMINER, Neurobehavioral Evaluation &#x0026; Research; sTREM, soluble triggering receptor expressed on myeloid cells 2; GFAP, glial fibrillary acidic protein.</p>
</caption>
<graphic xlink:href="fnagi-16-1382593-g002.tif"/>
</fig>
<p>Crucially, the majority of the large and leading studies on disease progression (of neuroimaging in particular) were predominantly performed in genetic cohorts of bvFTD (<xref ref-type="bibr" rid="ref152">Staffaroni et al., 2019b</xref>, <xref ref-type="bibr" rid="ref153">2022</xref>). Genetic mutation carriers enable monitoring from pre-symptomatic to symptomatic stage, making them ideal for precise monitoring of disease progression from a preclinical stage. In contrast, sporadic cases are typically diagnosed years after symptom onset, resulting in more advanced stages at time of identification. The scarceness of longitudinal studies on the sporadic variant logically implies that current recommendations are based on fewer validation studies performed within sporadic bvFTD. Moreover, sporadic cases are frequently less defined and based on clinical diagnosis, rather than underlying pathology, affecting diagnostic certainty. However, since 70 % of bvFTD cases is non-genetic (<xref ref-type="bibr" rid="ref58">Greaves and Rohrer, 2019</xref>), clearly this knowledge gap needs to be addressed. There is an urgent need for accurate phenotyping of sporadic bvFTD, identification and/or development of tailored outcome measures specific to sporadic cohorts, and proper stratification of patients in future clinical trials accordingly. This approach is essential for advancing our understanding of sporadic versus genetic bvFTD, and optimizing the effectiveness of therapeutic interventions across all variants of bvFTD.</p>
<p>Within this scoping review, there are multiple limitations to consider. A major challenge in interpretation and evaluation of findings was founded in the highly heterogeneous cohorts in bvFTD literature. Differences in patient populations (genetically undefined versus mutation-specific patients), follow-up time, study design (longitudinal follow-up versus cross-sectional associations with disease severity), and use of staging instruments less sensitive for bvFTD (e.g., traditional CDR) seriously complicated the comparative weighing of results. Due to this fact, meta-analysis was not possible, which would have further objectified and strengthened our findings. While the above-mentioned challenges are familiar in bvFTD literature, this scoping review also knows multiple strengths in the pursuit to overcome these obstacles. The systematic search of the vast literature (by means of extensive, inclusive search terms) was carried out in collaboration with a medical librarian, in accordance with evidence-based PRISMA standards, ensuring methodological rigor, and representing the status of literature in a complete and concise manner. The broad research question offered a comprehensive analysis of a wide spectrum of interdisciplinary domains, providing a relative comprehensive view of disease progression of value for future cohort development and trial design. Future research should focus on more extensive longitudinal follow-up for tool improvement and development, within large and well-defined cohorts, with regards to subtype, symptom onset and disease severity. Based on the present data we recommend to use a bvFTD-specific multi-modal battery to detect disease progression over time, including clinical, neuroimaging, and fluid biomarkers.</p>
</sec>
<sec sec-type="data-availability" id="sec23">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="author-contributions" id="sec24">
<title>Author contributions</title>
<p>JF: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. DP: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. M-Pv: Writing &#x2013; review &#x0026; editing. SBo: Writing &#x2013; review &#x0026; editing. WH: Writing &#x2013; review &#x0026; editing. SBr: Writing &#x2013; review &#x0026; editing. LS: Data curation, Methodology, Writing &#x2013; review &#x0026; editing. SS: Writing &#x2013; review &#x0026; editing. WK: Writing &#x2013; review &#x0026; editing. MO: Writing &#x2013; review &#x0026; editing. HM: Writing &#x2013; review &#x0026; editing. CT: Writing &#x2013; review &#x0026; editing. EV: Supervision, Writing &#x2013; review &#x0026; editing. YP: Funding acquisition, Supervision, Writing &#x2013; review &#x0026; editing.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="sec25">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Research of Alzheimer Center Amsterdam is part of the Neurodegeneration Research Program of Amsterdam Neuroscience. Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting Steun Alzheimercentrum Amsterdam. YP received funding from Stichting Dioraphte.</p>
</sec>
<sec sec-type="COI-statement" id="sec26">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="sec27">
<title>Publisher's note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec28">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fnagi.2024.1382593/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fnagi.2024.1382593/full#supplementary-material</ext-link></p>
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