Frontotemporal lobar degeneration is the second most common type of early-onset dementia under the age of 65 years (Harvey et al., 2003). Its most common subtype, behavioral variant frontotemporal dementia (bvFTD), is characterized by detrimental changes in personality and behavior (Pressman and Miller, 2014). Patients can display both apathy and disinhibition, often combined with a lack of insight, and executive and socioemotional deficits (Schroeter et al., 2011; Schroeter et al., 2012). Despite striking and early symptoms, bvFTD patients are often (i.e. up to 50%) misdiagnosed as having a psychiatric illness rather than a neurodegenerative disease (Woolley et al., 2011).

In addition to the presence of symptoms, the diagnosis requires consideration of family history due to its frequent heritable component and examination of different neuroimaging modalities (Pressman and Miller, 2014; Bang et al., 2015; Schroeter et al., 2014; Schroeter et al., 2008). Whereas atrophy in frontoinsular areas only occurs in later disease stages, glucose hypometabolism in frontal, anterior cingulate, and anterior temporal regions visible with fluorodeoxyglucose positron emission tomography (FDG-PET) is already detectable from an early stage onwards (Bang et al., 2015; Diehl-Schmid et al., 2007). The fractional amplitude of low-frequency fluctuations (fALFF) is a resting-state functional magnetic resonance imaging (rsfMRI) derived measure with good test–retest reliability that closely correlates with FDG-PET (Aiello et al., 2015; Holiga et al., 2018; Deng et al., 2022). In frontotemporal dementia (FTD) patients, fALFF was reduced in inferior parietal, frontal lobes, and posterior cingulate cortex and holds great potential as MRI biomarker (Premi et al., 2014; Borroni et al., 2018). Low local fALFF activity in the left insula was linked to symptom deterioration (Day et al., 2013).

On a molecular level, frontotemporal lobar degeneration can be differentiated into three different subtypes based on abnormal protein deposition: tau (tau protein), transactive response DNA-binding protein with molecular weight 43 kDa (TDP-43), and FET (fused-in-sarcoma [FUS] and Ewing sarcoma [EWS] proteins, and TATA-binding protein-associated factor 15 [TAF15]) (Bang et al., 2015; Haass and Neumann, 2016). Whereas tau and TDP pathologies each occur in half of the bvFTD patients, FUS pathology is very rare (Whitwell et al., 2011). Several possible mechanisms are discussed in the literature for the spread of these proteins throughout the brain, from a selective neuronal vulnerability (i.e. specific neurons being inherently more susceptible to the underlying disease-related mechanisms) to prion-like propagation of the respective proteins (Walsh and Selkoe, 2016; Hock and Polymenidou, 2016). The latter entails that misfolded proteins accumulate and induce a self-perpetuating process so that protein aggregates can spread and amplify, leading to gradual dysfunction and eventually death of neurons and glial cells (Hock and Polymenidou, 2016). For example, tau can cause presynaptic dysfunction prior to loss of function or cell death (Zhou et al., 2017), whereas overexpression of TDP-43 leads to impairment of presynaptic integrity (Heyburn and Moussa, 2016). The role of FET proteins is not fully understood, although their involvement in gene expression suggests a mechanism of altered RNA processing (Svetoni et al., 2016).

Neuronal connectivity plays a key role in the spread of pathology as it is thought to transmit along neural networks. Supporting the notion, previous studies also found an association between tau levels and functional connectivity in functionally connected brain regions, for example across normal aging and Alzheimer’s disease (Franzmeier et al., 2019). Thereby, dopaminergic, serotonergic, glutamatergic, and GABAergic neurotransmission is affected. More specifically, current research indicates a deficit of neurons and receptors in these neurotransmitter systems (Hock and Polymenidou, 2016; Huey et al., 2006; Murley and Rowe, 2018). Furthermore, these deficits have been associated with clinical symptoms. For example, whereas GABAergic deficits have been associated with disinhibition, increased dopaminergic neurotransmission and altered serotonergic modulation of dopaminergic neurotransmission have been associated with agitated and aggressive behavior (Engelborghs et al., 2008; Murley et al., 2020). Another study related apathy to glucose hypometabolism in the ventral tegmental area, a hub of the dopaminergic network (Schroeter et al., 2011). Despite this compelling evidence of disease-related impairment at functional and molecular levels, the relationship between both remains poorly understood. It also remains unknown if the above neurotransmitter alterations reflect a disease-specific vulnerability of specific neuron populations or merely reflect a consequence of the ongoing neurodegeneration.

Based on the above findings, we hypothesize that the spatial distribution of fALFF and gray matter (GM) pathology in FTD will be related to the distribution of dopaminergic, serotonergic, and GABAergic neurotransmission. The aim of the current study was to gain novel insight into the disease mechanisms underlying functional and structural alterations in bvFTD by examining if there is a selective vulnerability of specific neurotransmitter systems. We evaluated the link between disease-related functional alterations and the spatial distribution of specific neurotransmitter systems and their underlying gene expression levels. In addition, we tested if these associations are linked to specific symptoms observed in this clinical population.

In the current study, we examined if there is a selective vulnerability of specific neurotransmitter systems in bvFTD to gain novel insight into the disease mechanisms underlying functional and structural alterations. More specifically, we evaluated if fALFF alterations in bvFTD co-localize with specific neurotransmitter systems. We found a significant spatial co-localization between fALFF alterations in patients and the in vivo derived distribution of specific receptors and transporters covering serotonergic, norepinephrinergic, and GABAergic neurotransmission. These fALFF–neurotransmitter associations were also observed at the mRNA expression level and their strength correlated with specific clinical symptoms. All of the observed co-localizations with in vivo derived neurotransmitter estimates were negative with lower fALFF values in bvFTD being associated with a higher density of the respective receptors and transporters in health. The directionality of these findings supports the notion of higher vulnerability of respective networks to disease-related alterations. These findings are also largely in line with previous research concerning FTD showing alterations in all of the respective neurotransmitter systems (Huey et al., 2006; Murley and Rowe, 2018).

The in vivo co-localization findings might also support the notion that propagation of proteins involved in bvFTD may align with specific neurotransmitter systems (Hock and Polymenidou, 2016). With regard to other brain disorders, linking functional connectivity with receptor density and expression, recent studies found an association between functional connectivity and receptor availability in schizophrenia, and an association between structural–functional decoupling and receptor gene expression in Parkinson’s disease (Zarkali et al., 2021; Horga et al., 2016). A potential mechanism for the selective vulnerability of specific neurotransmitter systems is the propagation of proteins along functionally connected networks that has been previously demonstrated for various neurodegenerative diseases (Zhou et al., 2012; Seeley et al., 2009). For example, in Alzheimer’s disease and normal aging, tau levels closely correlated with functional connectivity (Franzmeier et al., 2019). We found moderate to large AUC when using the strength of the identified co-localizations for differentiation between patients and HC suggesting that these findings may represent a measure of the affectedness of respective neurotransmitter systems. In bvFTD, neurodegeneration is thought to progress through the salience network involved in socioemotional tasks, which comprises the anterior cingulate and frontoinsular cortex, as well as the amygdala and the striatum (Bang et al., 2015; Hock and Polymenidou, 2016). The three neurotransmitter systems found to be deficient in our sample are relevant for the functioning of these structures (anterior cingulate cortex: e.g. serotonin and norepinephrine, Tian et al., 2017; Koga et al., 2020; amygdala: e.g. GABA and serotonin, Castro-Sierra et al., 2005; striatum: e.g. GABA, Semba et al., 1987). Although spread of misfolded proteins through the salience network provides a potential disease mechanism, further research of the exact mechanisms involved is needed.

For GMV, we did not find any significant co-localization with specific neurotransmitter systems. As the correlations with GMV showed a distinct pattern to fALFF and the variance explained by GMV in the observed fALFF–neurotransmitter associations was small, the observed associations with fALFF seem to be driven indeed by functional alterations and not by the underlying atrophy of respective regions. As propagation of misfolded proteins leads to a gradual dysfunction and eventually cell death (Hock and Polymenidou, 2016), some regions displaying high density of a specific neurotransmitter might suffer dysfunction (i.e. functional alterations), whereas others might already be exposed to cell death (i.e. structural alterations/atrophy). An interesting future direction might compose integration of structural connectivity as measured by diffusion tensor imaging. A study by Dopper et al., 2014 showed reduced fractional anisotropy in healthy individuals carrying mutations compared to non-carriers (Dopper et al., 2014). Given that there were structural connectivity differences even before disease onset, it would be of interest to re-examine structural connectivity differences between HC and patients (i.e. after disease onset). Repeating the neurotransmitter analyses might facilitate understanding of the underlying disease mechanism.

The strength of co-localization of fALFF with NET was correlated with VF and MMSE, both being impaired in patients with bvFTD (Schroeter et al., 2012; Diehl and Kurz, 2002; Schroeter et al., 2018). Thereby, a stronger negative co-localization (i.e. lower fALFF in patients in high-density regions in health) was moderately associated with decreased test performance. Similarly, a correlation between MMSE and NE plasma concentration has been previously reported in Alzheimer’s disease (Pillet et al., 2020). Combined, these findings point to a potentially more general role of norepinephrinergic neurotransmission in cognitive decline observed across different dementia syndromes. This interpretation is in line with the recently proposed role of the locus coeruleus, the source of norepinephrine in the brain, in regulating processes of learning, memory, and attention (Tsukahara and Engle, 2021). In contrast to the study by Murley et al., 2020 who reported an association of GABA concentrations in the inferior frontal gyrus in FTD with disinhibition, we did not find this association. Beside the use of different methodology, a potential explanation may constitute the use of different inhibition measures. Whereas we measured disinhibition using the FrSBe, Murley et al., 2020 used a stop-signal task.

Although, except for α1 and γ1 GABAa subunits, all of the co-localizations with fALFF identified with in vivo estimates were also significant at the respective mRNA gene expression level, we found correlation coefficients of both directionalities. Interestingly, whereas these correlations were solely negative for the in vivo derived maps, the correlations with gene expression profile maps were positive for NET, and negative for 5-HT1b, 5-HT2a, and β1 GABAa subunit. Thus, for NET, we observed higher fALFF values in bvFTD patients in areas with high mRNA gene expression in health, whereas for 5-HT1b, 5-HT2a, and β1 GABAa subunit we observed lower fALFF values in bvFTD patients in areas with high mRNA gene expression in health. One explanation for these seemingly contradictory findings is that mRNA gene expression seems to vary strongly between individuals. In our mRNA gene expression profile maps, the autocorrelation between mRNA donors was low for 5-HT1b, 5-HT2a, and α1 GABAa subunit, and NET, limiting the confidence in some of these findings. Additionally, the association of mRNA expression with protein products may also vary greatly between genes, being not associated at all or even negatively associated for some, and strongly correlated for others (Koussounadis et al., 2015; Moritz et al., 2019). Similarly, a previous study found the correspondence between receptor density and mRNA expression to be low (Hansen et al., 2022). Potential reasons for the lack of or even negative correlations may be a decoupling in time as well as that other levels of regulation overrode the transcriptional level (Koussounadis et al., 2015). We observed a similar phenomenon in our data with the correlation of neurotransmitter density maps with their underlying mRNA gene expression being weak for all neurotransmitters except β1 and γ1 GABAa subunits.

Our findings support the notion of fALFF as useful marker for assessing bvFTD-related decline in brain function. In line with previous literature in bvFTD, we observe fALFF reductions mainly in frontal and temporal lobes, but also in the parietal lobe (Premi et al., 2014; Borroni et al., 2018). These findings support the notion of fALFF being a useful marker of metabolic impairment (Bang et al., 2015; Diehl-Schmid et al., 2007). Moreover, we found a clear association of fALFF with several neurotransmitter systems pointing to a selective neurotransmitter vulnerability in bvFTD, as suggested in previous research (Huey et al., 2006; Murley and Rowe, 2018). In particular, the co-localization of fALFF with NET was associated with VF and MMSE, suggesting the sensitivity of fALFF to reflect modality-specific cognitive decline.

The current study was limited by the unavailability of medication information. Therefore, we were not able to control for its potential confounding effects. However, as bvFTD medication is typically restricted to serotonin reuptake inhibitors its effects should be primarily associated with availability of 5-HTT and directionally negate the effects of the disease. Furthermore, as the included PET maps were derived from healthy subjects, the applied approach only tests for co-localization of imaging changes with the non-pathological distribution of the respective neurotransmitter systems. Similarly, the reliability of the co-localization analyses is partly limited by the number of healthy volunteers used to derive the respective neurotransmitter average maps. Finally, the current study was limited by the availability of neurotransmitter maps included in the JuSpace toolbox.

To summarize, we found fALFF reductions in bvFTD to co-localize with the in vivo and ex vivo derived distribution of serotonergic, GABAergic, and norepinephrinergic neurotransmitter systems, pointing to a crucial vulnerability of these neurotransmitters. The strength of these associations was linked to some of the neuropsychological deficits observed in this disease. We propose a combination of spread of pathology through neuronal connectivity and more specifically, through the salience network, as a disease mechanism. Thereby, these findings provide novel insight into the mechanisms underlying the spatial constraints observed in progressive functional and structural alterations in bvFTD. Our data-driven method might even be used to generate new hypotheses for pharmacological intervention in neuropsychiatric diseases beyond this disorder.

The original data and their derivatives cannot be made publicly available as the study includes sensitive patient data and public data sharing was not covered in the informed consent. The original data supporting the findings of this study are available from the senior author (Matthias L. Schroeter) upon reasonable request. All derived statistical measures used here are available from the first author upon request. The software applied is publicly available at https://github.com/juryxy/JuSpace (JuSpace, Juryxy, 2023) and https://github.com/FAIR-CNS/MENGA (MENGA, Rizzo, 2016). The code for the main analyses is publicly available at https://github.com/liha-coding/Neurotransmitter-vulnerability-in-bvFTD (copy archived at Hahn, 2023). Processed data used for the creation of the figures are available as supplementary material.

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Author details

1. Lisa Hahn

   1. Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
   2. Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

   Contribution

   Formal analysis, Investigation, Visualization, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0167-3947

2. Simon B Eickhoff

   1. Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
   2. Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

   Contribution

   Conceptualization, Resources, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6363-2759

3. Karsten Mueller

   Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

   Contribution

   Conceptualization, Data curation, Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

4. Leonhard Schilbach

   1. LVR-Klinikum Düsseldorf, Düsseldorf, Germany
   2. Medical Faculty, Ludwig-Maximilians-Universität, München, Germany

   Contribution

   Conceptualization, Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

5. Henryk Barthel

   Department for Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany

   Contribution

   Conceptualization, Data curation, Funding acquisition, Writing – review and editing

   Competing interests

   received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Life Molecular Imaging and Novartis/AAA. The author has no other competing interests to declare

6. Klaus Fassbender

   Department of Neurology, Saarland University Hospital, Homburg, Germany

   Contribution

   Conceptualization, Data curation, Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3596-868X

7. Klaus Fliessbach

   1. Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
   2. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

   Contribution

   Conceptualization, Data curation, Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

8. Johannes Kornhuber

   Department of Psychiatry and Psychotherapy, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany

   Contribution

   Conceptualization, Data curation, Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

9. Johannes Prudlo

   1. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
   2. Department of Neurology, University Medicine Rostock, Rostock, Germany

   Contribution

   Conceptualization, Data curation, Funding acquisition, Writing – review and editing

   Competing interests

   No competing interests declared

10. Matthis Synofzik

    1. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
    2. Department of Neurodegenerative Diseases, Center of Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany

    Contribution

    Conceptualization, Data curation, Funding acquisition, Writing – review and editing

    Competing interests

    has received consulting fees from, and currently act as a consultant for Aviado Bio, Prevail, Servier, Reata and Orphazyme. They have received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from GenOrph. The author has no other competing interests to declare

11. Jens Wiltfang

    1. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
    2. Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Medical University Göttingen, Göttingen, Germany
    3. Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal

    Contribution

    Conceptualization, Data curation, Funding acquisition, Writing – review and editing

    Competing interests

    has received consulting fees from Boehringer-Ingelheim, F. Hoffmann-La Roche, Biogen, Immungenetics, Roboscreen and Abbott. They currently act as a consultant for Boehringer-Ingelheim, F. Hoffmann-La Roche, Biogen and Immungenetics, and hold a Leadership or fiduciary role at CSF Society, AGNP and DGLN. The author has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Pfizer, Janssen, MSD SHARP & DOHME, Amgen, Roche Pharma, Actelion Pharmaceutical, Guangzhou Glorylen Medicial Technology Co. (China), Bejing Yibai Science and Technology Ltd. The author has been issued the following patents; EP2095128B1 and EP3105589A1. The author has no other competing interests to declare

12. Janine Diehl-Schmid

    1. Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
    2. kbo-Inn-Salzach-Klinikum, Clinical Center for Psychiatry, Psychotherapy, Psychosomatic Medicine, Geriatrics and Neurology, Wasserburg/Inn, Germany

    Contribution

    Conceptualization, Data curation, Funding acquisition, Writing – review and editing

    Competing interests

    has received a speaker fee from Jansen and Roche. The author has no other competing interests to declare

13. FTLD Consortium

    Contribution

    Conceptualization, Data curation, Funding acquisition

    Competing interests

    No competing interests declared

14. Markus Otto

    1. Department of Neurology, Ulm University, Ulm, Germany
    2. Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany

    Contribution

    Conceptualization, Data curation, Funding acquisition, Writing – review and editing

    Competing interests

    has received grants from BMBF - FTLD consortium, moodmarker, ALS association and EU - MIRIADE. The author has received consulting fees from, and currently acts as a consultant for, BIOGEN, Axon and Roche. The author has been issued a patent for Foundation state Baden-Wuerttemberg, Beta Syn as Biomarker for neurodegenerative diseases. The author holds an unpaid leadership or fiduciary role at the German Society for CSF diagnostics and neurochemistry and the Society for CSF diagnostics and neurochemistry, and as a speaker at the FTLD consortium. The author is co-inventor of a patent application (PCT/EP2020/072559) for using beta-synuclein measurement in blood.The author has no other competing interests to declare

15. Juergen Dukart

    1. Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
    2. Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Contribution

    Conceptualization, Supervision, Methodology, Writing – review and editing

    Contributed equally with

    Matthias L Schroeter

    For correspondence

    j.dukart@fz-juelich.de

    Competing interests

    former employee of and current consultant for F.Hoffmann-La Roche

    "This ORCID iD identifies the author of this article:" 0000-0003-0492-5644

16. Matthias L Schroeter

    1. Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
    2. Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany

    Contribution

    Conceptualization, Data curation, Funding acquisition, Writing – review and editing

    Contributed equally with

    Juergen Dukart

    Competing interests

    No competing interests declared

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