Background
Frontotemporal dementia (FTD) is a clinically, genetically, and pathologically heterogeneous group of syndromes characterized by the degeneration of the frontal and temporal cortices [
1]. Up to 40% of FTD cases are genetic, with the most common cause being mutations of the microtubule-associated protein tau (MAPT) gene, especially in China. FTD is characterized by extensive tau pathology, and the most prevalent clinical phenotype is the behavioral variant of FTD (bvFTD) [
2,
3]. Increasing evidence has confirmed the presence of pathophysiological changes during the presymptomatic stage of genetic FTD [
4]. Families with a presence of MAPT mutations provide an ideal model to investigate brain structure and function during the presymptomatic stage and investigate the pathogenesis of FTD.
Over the last decade, several studies have reported the gray matter atrophy and white matter integrity loss in asymptomatic MAPT mutation carriers, although these changes are not common [
5]. It has been proposed that functional changes precede the occurrence of atrophy and thus may constitute one of the earliest features of neurodegeneration [
6]. The only two studies using
18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) have revealed local hypometabolism in presymptomatic MAPT mutation carriers, which is thought to reflect neuronal dysfunction [
7,
8]. However, increasingly, studies have advocated that brain function is not solely attributable to the nature of isolated regions or subnetworks connections. Rather, it emerges from the overall network organization of the brain as a whole, that is, the systematic balance of connectomes encompassing integration and segregation functions [
9]. To date, limited MRI studies in asymptomatic mutation carriers of genetic FTD families focused on regional functional connectivity, which has not allowed an understanding of how networks are embedded and interact within the complex brain system [
6,
10]. Metabolic network topology based on FDG-PET is considered a useful measure that reflects neuronal communication signaling at the network and whole-brain levels, and it can capture neural and synaptic activity more directly than can functional magnetic resonance imaging (fMRI) [
11]. However, the overall organization of the whole-brain network in presymptomatic MAPT mutation carriers remains poorly understood, which could help to elucidate the pathogenesis and allow monitoring of the earliest changes associated with FTD.
In the current study, we assessed the changes in the topological properties and connectome integrity in asymptomatic carriers and non-carriers of the same pedigree using graph theoretical analysis of 18F-FDG PET/MRI data. We aimed to explore the specific patterns of metabolism topology reconfiguration in MAPT mutation carriers before the onset of symptoms. We predicted that the local disruption of metabolic network topology would be present in asymptomatic MAPT subjects, whereas topology reconfiguration would maintain an efficient organization of the brain’s functional network.
Methods
Subjects
Eighteen asymptomatic participants were recruited from a family with an autosomal dominant P301L mutation in the MAPT gene through the frontotemporal lobar degeneration database, which was established at the Department of Neurology of Xuanwu Hospital, China. All participants underwent genetic screening, and six participants were found to be carriers of the mutation, and 12 were mutation-negative, who were used as controls in this study. Each participant underwent clinical interviews, physical examinations, neuropsychological assessments, and cerebral 18F-FDG PET/MRI. All subjects had been followed up prospectively with annual clinical examinations between September 2017 and October 2021 at Xuanwu Hospital. During the 4-year follow-up period, all subjects remained symptom-free, and none of them has developed any bvFTD symptoms or any other neurodegenerative disease.
We also identified 32 subjects seen at the Department of Neurology of Xuanwu Hospital, China, who fulfilled the 2011 consensus probable bvFTD criteria [
12]. All of these patients also underwent clinical interviews, physical examinations, neuropsychological assessments, genetic testing, and cerebral
18F-FDG-PET/MRI. Of these 32 bvFTD patients, five had MAPT mutations (one with a P301L mutation [c.1907C>T], one with a V337M mutation [c.2014G>A], one with the N296N mutation [c.1839T>C], one with the R5C mutation [c.13C>T], and one with the D54N mutation [c.160G>A]). In addition, a total of 33 participants from the database of individuals with normal cognition, which was established at the Department of Neurology of Xuanwu Hospital during the same period, were enrolled as controls. Each participant underwent the same neuropsychological assessments as the patients. The demographics of the subjects are shown in Table
1.
Table 1
Demographic and neuropsychiatric assessment data
Age | 49.00 ± 3.90 | 42.25 ± 9.206 | 59.13 ± 9.97 | 54.27 ± 11.17 | 0.19 | 0.07 |
Sex (male/female) | 3/3 | 7/5 | 16/16 | 15/18 | 0.99 | 0.81 |
Years of education | 8.67 ± 0.52 | 10.55 ± 3.80 | 10.79 ± 4.64 | 11.23 ± 3.35 | 0.25 | 0.69 |
MMSE | 28.67 ± 0.82 | 28.36 ± 2.06 | 12.54 ± 7.01 | 28.47 ± 2.17 | 0.92 | < 0.0001 |
MoCA | 26.50 ± 1.23 | 26.18 ± 3.06 | 9.323 ± 6.25 | 26.13 ± 3.40 | 0.68 | < 0.0001 |
AVLT: immediate recall | 23.83 ± 2.32 | 26.00 ± 7.32 | 8.15 ± 7.04 | 22.40 ± 5.25 | 0.94 | < 0.0001 |
AVLT: delayed recall | 8.67 ± 2.25 | 9.27 ± 3.16 | 1.74 ± 2.68 | 8.43 ± 3.48 | 0.71 | < 0.0001 |
BNT | 25.00 ± 1.00 | 24.90 ± 2.08 | 10.78 ± 6.52 | 25.38 ± 3.48 | 0.97 | < 0.0001 |
CDR | 0 ± 0 | 0 ± 0 | 1.76 ± 1.22 | 0 ± 0 | – | < 0.0001 |
NPI-Q | 0 (0–6) | 0 (0–1) | 24.13 ± 21.03 | 1.29 ± 4.53 | 0.89 | 0.0003 |
FBI | 0 (0–6) | 0 (0–2) | 23.78 ± 14.39 | 1.667 ± 4.082 | 0.84 | 0.001 |
MBI-C | 0 (0–14.25) | 0 (0–1) | 19.82 ± 15.25 | 2.20 ± 6.96 | 0.68 | 0.002 |
Neuropsychological assessments
The neuropsychological test battery consisted of widely used neuropsychological assessments that measure the cognitive function in the domains of memory, language, and behavioral abnormality. Global cognitive screening measures included the Mini-mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Clinical Dementia Rating (CDR) Scale. Word list memory was evaluated using Rey’s Auditory-Verbal Learning Test (AVLT). Language was measured using the Boston Naming Test (BNT). The severity of behavioral abnormality was assessed using the Frontal Behavior Inventory (FBI), the Neuropsychiatry Inventory Questionnaire (NPI-Q), and the Mild Behavioral Impairment Checklist (MBI-C).
PET/MRI acquisition parameters
All images were acquired on a hybrid 3.0 T time-of-flight PET/MRI scanner (SIGNA PET/MR, GE Healthcare, WI, USA) [
13]. PET and MRI data were acquired simultaneously using a vendor-supplied 19-channel head and neck union coil. Subjects were injected intravenously with l8F-FDG (3.7 MBq/kg) and underwent three-dimensional (3D) T1-weighted sagittal imaging and 18F-FDG-PET imaging 40 min later during the same session.
A 3D T1-weighted fast field echo sequence (repetition time [TR] = 6.9 ms, echo time [TE] = 2.98 ms, flip angle = 12°, inversion time = 450 ms, matrix size = 256 × 256, field of view = 256 × 256 mm
2, slice thickness = 1 mm, 192 sagittal slices with no gap, voxel size = 1 × 1 × 1 mm
3, and acquisition time = 4 min 48 s) was used for data acquisition. Static
18F-FDG-PET data were acquired using the scanning parameters of matrix size = 192 × 192, field of view = 350 × 350 mm
2, and pixel size = 1.82 × 1.82 × 2.78 mm
3 and included corrections for random coincidences, dead time, scatter, and photon attenuation. Attenuation correction was performed according to the brain MRI (atlas-based coregistration of two-point Dixon) [
14]. The default attenuation correction sequence was automatically prescribed and acquired as follows: LAVA-Flex (GE Healthcare) axial acquisition, TR = 4 ms, TE = 1.7 ms, slice thickness = 5.2 mm with a 2.6-mm overlap, 120 slices, pixel size = 1.95 × 2.93 mm, and acquisition time = 18 s.
Structural image preprocessing
Data were preprocessed using the Computational Anatomy Toolbox (CAT12) toolbox segment data pipeline implemented within Statistical Parametric Mapping 12 (SPM12,
www.fil.ion.ucl.ac.uk/spm). Structural MRI images were normalized to standard Montreal Neurological Institute (MNI) space using diffeomorphic anatomical registration through exponentiated lie algebra normalization as implemented in SPM12. The images were then smoothed using an 8-mm full-width half-maximum isotropic Gaussian kernel for all directions.
PET image preprocessing
PET images were preprocessed using SPM12, implemented in MATLAB (MathWorks, Natick, MA). After normalization of the structural MRI images, the transformation parameters determined by the T1-weighted image spatial normalization were applied to the co-registered PET images for PET spatial normalization. The images were then smoothed using an 8-mm full-width half-maximum Gaussian kernel for all directions. Finally, PET scan intensity normalization to the mean of the cerebellar gray matter was applied to create standardized uptake value ratio (SUVR) images.
Voxel-based analysis for structural MRI and FDG-PET
The preprocessed structural and 18F-FDG-PET SUVR image data were used to perform voxel-wise whole-brain comparisons between asymptomatic mutation carriers and non-carriers, the bvFTD patients and controls.
We used sparse inverse covariance estimation (SICE), which is a method previously validated by Huang et al. [
15]. A series of nodes (
N = 172) that represent the brain regions of interest (ROIs) for the connectivity analysis were selected to cover the whole brain [
16,
17]. The
18F-FDG-PET signal was extracted from each ROI in each subject to obtain subject × ROI matrices. The SICE algorithm was then applied to these matrices to generate metabolic connectivity matrices. Graph theory measures were computed from the metabolic connectivity matrices, and a bootstrapping procedure was performed to test for differences between the groups.
The most important nodes of the network (i.e., the hubs) were identified by selecting nodes with a participation coefficient that was one standard deviation higher than the mean degree centrality.
Default mode and salience networks: independent component analysis
Spatial independent component analysis (ICA) of the preprocessed FDG-PET images was performed using the GIFT toolbox (
http://mialab.mrn.org/software/). Imaging data from each subject were arranged in a sequence and whitened and reduced using principal component analysis. Then, an Infomax ICA algorithm, which minimizes mutual information, was used to estimate the independent spatial components [
18]. The GIFT software was used to estimate the optimal number of components, which were based on the assessment of the entropy rate of independent and identically distributed Gaussian random processes [
19]. To display the voxels that contributed most to the resulting spatial maps, voxel intensity values were converted into
z-scores, and image values were visualized using a threshold of > 1.96 [
18]. Finally, components of the default mode networks and salience networks were identified according to anatomical information [
18].
Statistical analyses
The GraphPad Prism software (version 8.3.0, GraphPad Software Inc., La Jolla, CA) was used to evaluate the statistical significance. Numerical variables are presented as means ± standard deviations or medians and ranges, depending on the normality of the distribution. Comparative analyses of numerical variables were performed using non-parametric Mann-Whitney tests between asymptomatic mutation carriers and non-carriers and Student’s t-tests between bvFTD patients and controls. Comparisons of categorical variables were analyzed using the chi-square or Fisher’s exact tests. The structural and 18F-FDG PET data were subjected to voxel-wise whole-brain two-sample t-tests based on the framework of a general linear model (GLM) in SPM12, with age and sex as covariates. In addition, total intracranial volume was also used as a covariate for structural data analysis. The brain regions with significant volume and FDG changes were determined using a voxel-threshold of p < 0.05 (familywise error [FWE]-corrected). The beta-coefficients of the two-sample t-test for gray matter volume and FDG metabolism were additionally calculated between carriers and non-carriers, and the effect size threshold was defined by beta > 0.8. For the comparison of network measures, we tested the statistical significance of the differences using non-parametric permutation tests with 5000 permutations based on the following methods: tests were performed by randomly permuting the subjects from both groups and calculating the differences in graph measures between the new randomized groups. This procedure was repeated 5000 times to obtain the distribution of between-group differences. The p-values were calculated as the fraction of the difference in distribution values that exceeded the difference value between the actual groups. For all analyses, a p-value < 0.05 indicated statistical significance. We performed multiple corrections using the false discovery rate for analyzing local metabolic connectivity changes.
Discussion
This study is the first to provide evidence that the topological organization of the metabolic brain network is altered in asymptomatic MAPT P301L subjects. Furthermore, asymptomatic MAPT P301L carriers have early involvement of medial prefrontal regions (vmPFC, orbitofrontal cortex, and ACC) and abnormally increased connectivity in task-related regions (DMN and SN), which may be a compensatory response to maintain the global efficiency of the brain network.
We detected aberrations of network topology and metabolic connectivity in asymptomatic MAPT carriers, which has not been specifically investigated before. Moreover, the alteration of the metabolic network topology in asymptomatic MAPT P301L mutation carriers was overlapped with those observed in bvFTD. These results revealed that disorders of neuronal connections were present in the presymptomatic stage of genetic FTD, which was in line with the previous study [
6,
20]. The atrophy and hypometabolism of the anterior cingulate cortex failed to be detected in our asymptomatic carriers, which was inconsistent with a previous study with six MAPT P301L mutation carriers from five families [
7]. The small sample size and genetic heterogeneity may contribute to this discrepancy. Notably, the anterior cingulate cortex was identified as the lost hub and decreased connectivity in our study, suggesting its involvement in asymptomatic MAPT mutation carriers. Regardless, our findings suggest that changes in the brain metabolic network are an early feature of genetic FTD. Additionally, applying the hybrid PET/MRI system allowed us to match anatomical and functional modalities in the same individual, which provided a comprehensive illustration of the subtle brain changes in asymptomatic mutation carriers. Moreover, a strength of our study is that we selected a large family to explore the effects of MAPT mutation in asymptomatic carriers compared with non-carriers, which minimizes the effects of interfamilial genetic variation on brain morphology and network organization [
21]. Taken together, these findings indicate that the topological properties and connectomics of metabolism networks may be a particularly sensitive and useful method for investigating and monitoring the earliest stages of FTD in individuals with this underlying genetic basis.
Our graph theory results identified lost hubs in the vmPFC, orbitofrontal cortex, and ACC and reconfigured hubs in the precuneus, posterior cingulate, and insula in asymptomatic mutation carriers. It is worth noting that the reduced connectivity observed was consistent with hub loss. The pattern of hub reorganization and reduced connectivity during the asymptomatic stage shows a large resemblance to the regions observed in sporadic bvFTD patients. Furthermore, the involvement of these regions corresponds with the pattern of neuropathology in FTD, in which the initial changes occur in the medial prefrontal cortex (mPFC), while the parietal lobe remains preserved [
22]. Accordingly, alterations in the personality and behaviors of bvFTD patients, such as emotional blunting, loss of empathy, and an inability to consider the thoughts and perspectives of others, arise because of the early degeneration of the mPFC [
23,
24]. Functional network alterations have been reported to follow a topological distribution, which suggests stepwise spreading [
25]. Reduced connectivity was evident only in the medial prefrontal regions in asymptomatic carriers but was apparent also in other brain regions in FTD patients, which indicates that the mPFC is implicated early in tau-mediated FTD. Correspondingly, this pattern of involvement is also in line with the characteristics of tau deposition identified in vivo using
18F-flortaucipir in asymptomatic MAPT P301L carriers [
26]. Above all, our findings suggest that the abnormalities of functional brain networks in MAPT carriers start in the medial prefrontal lobe during the pre-symptomatic phase and eventually spread into the other regions.
Furthermore, lesion effects are not always limited to circumscribed locations because of diaschisis affecting remotely connected sites; therefore, a resting-state network-based approach is needed to gain a better understanding of the structure-function relationships in the mPFC [
27]. We focused on specific vmPFC-linked networks (DMN) and ACC-linked networks (SN). Consistent with recently reported fMRI findings in asymptomatic granulin (GRN) carriers [
28,
29], our results revealed selectively increased connectivity within the DMN and SN during the presymptomatic stage but a reduction in FTD patients. The DMN and SN are involved in functions such as emotional processing and mentalizing/social cognition, which likely contribute to various critical features of FTD [
6,
23]. Increased task dependency of the DMN and SN connectivity profiles in asymptomatic MAPT carriers may represent a compensatory mechanism of brain plasticity in the presence of pathology that selectively targets neurons in the medial prefrontal areas. Although our results contrast with a previous study that found reduced DMN connectivity in asymptomatic MAPT carriers, we believe our findings are likely a feature of primary tauopathy [
6]. Discordance across studies may be attributed to the differences in disease-related stage and genetic subtypes of MAPT. Taken together, we speculate that the enhancement in the DMN and SN compensates for mPFC deficits by reconfiguration during the early stages of FTD, which contributes to the maintenance of efficient information transfer.
Accordingly, asymptomatic mutation carriers in our study showed normal global properties of brain network topology, which included global efficiency, hierarchy, local efficiency, and clustering coefficients, whereas bvFTD patients exhibited a breakdown of these global parameters. This suggests that mutation carriers maintain the information exchange efficiency of the overall brain network before the onset of symptoms, which may contribute to the preservation of cognition. Consistent with our findings, previous studies have revealed that global efficiency, which measures the ability of a network to transmit information at the global level, is associated with the degree of cognitive impairment [
30,
31]. Moreover, normal network efficiency and increased connectivity have been observed during prodromal phases, followed by decreases in global efficiency and local connectivity in symptomatic phases due to the dissipation of neural compensation [
32]. Two previous fMRI studies indicated that abnormally increased connectivity supports cognitive health in asymptomatic GRN carriers, whereas the specific pattern of network reorganization, especially those modulated by different genetic defects, remains elusive [
28,
29]. In our study, normal network efficiency may be attributed to the increased connectivity in the DMN and SN to compensate for the mPFC deficit. Furthermore, topology reconfiguration of the metabolic network may maintain efficient information processing, which may support cognitive well-being in MAPT mutation carriers before the onset of symptoms. In future studies, the distinct pattern of metabolic network reorganization requires confirmation in a larger cohort with different genetic profiles.
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