Literature DB >> 31388560

Rates of lobar atrophy in asymptomatic MAPT mutation carriers.

Qin Chen1,2, Bradley F Boeve3,4, Matthew Senjem1, Nirubol Tosakulwong5, Timothy G Lesnick5, Danielle Brushaber4,5, Christina Dheel3,4, Julie Fields6, Leah Forsberg3,4, Ralitza Gavrilova7, Debra Gearhart3,4, Jonathan Graff-Radford3,4, Neill R Graff-Radford8, Clifford R Jack1,4, David T Jones3,4, David S Knopman3,4, Walter K Kremers5, Maria Lapid6, Rosa Rademakers4,9, Jeremy Syrjanen5, Adam L Boxer10, Howie Rosen10, Zbigniew K Wszolek8, Kejal Kantarci1,4.   

Abstract

INTRODUCTION: The aim of this study was to investigate the rates of lobar atrophy in the asymptomatic microtubule-associated protein tau (MAPT) mutation carriers.
METHODS: MAPT mutation carriers (n = 14; 10 asymptomatic, 4 converters from asymptomatic to symptomatic) and noncarriers (n = 13) underwent structural magnetic resonance imaging and were followed annually with a median of 9.2 years. Longitudinal changes in lobar atrophy were analyzed using the tensor-based morphometry with symmetric normalization algorithm.
RESULTS: The rate of temporal lobe atrophy in asymptomatic MAPT mutation carriers was faster than that in noncarriers. Although the greatest rate of atrophy was observed in the temporal lobe in converters, they also had increased atrophy rates in the frontal and parietal lobes compared to noncarriers. DISCUSSION: Accelerated decline in temporal lobe volume occurs in asymptomatic MAPT mutation carriers followed by the frontal and parietal lobe in those who have become symptomatic. The findings have implications for monitoring the progression of neurodegeneration during clinical trials in asymptomatic MAPT mutation carriers.

Entities:  

Keywords:  Asymptomatic; Frontotemporal dementia; Longitudinal; MAPT; Magnetic resonance image

Year:  2019        PMID: 31388560      PMCID: PMC6675939          DOI: 10.1016/j.trci.2019.05.010

Source DB:  PubMed          Journal:  Alzheimers Dement (N Y)        ISSN: 2352-8737


Introduction

Frontotemporal lobar degeneration (FTLD) is a progressive clinical syndrome with several possible etiologies and with heterogeneous clinical features, including behavioral and language disorders, executive dysfunction, and impaired social cognition, while patients can also develop features of motor neuron disease, progressive supranuclear palsy or corticobasal syndrome [1]. About 30%-50% FTLD patients have an autosomal dominant pattern of inheritance [2], with many showing mutations in the microtubule-associated protein tau (MAPT) gene [3]. Mutations in the MAPT gene result in filamentous accumulation of hyperphosphorylated tau in neurons and glia leading to neurodegeneration, atrophy, white matter microstructure alterations, and metabolic changes years before the onset of clinical symptoms [3], [4], [5], [6], [7]. Families characterized by the presence of MAPT mutations can be investigated for early neurodegenerative changes and identifying biomarkers for tracking disease progression during potential disease-modifying therapies. Structural magnetic resonance imaging (MRI) has captured disease-specific neurodegeneration in patients with mild cognitive impairment (MCI) [8], [9], Alzheimer's disease [10], [11], Lewy body dementia [12], and in familial and sporadic FTLD [5], [13], [14], [15], [16]. Some cross-sectional studies have suggested that cortical degeneration can be detected with MRI years before symptom onset in asymptomatic MAPT mutation carriers [5], [14], [17], [18], [19], but others have not shown any significant cortical volumetric differences between MAPT mutation carriers and controls [7], [20]. Recently, two longitudinal studies from a cohort of asymptomatic MAPT mutation carriers have found atrophy in the hippocampus but no cortical atrophy was reported in longitudinal analysis during up to 4 years of follow-up [21], [22]. Up to date, little is known about the trajectory of progression of atrophy on longitudinal MRI in asymptomatic MAPT mutation carriers. In this study, we investigated the rates and trajectories of lobar atrophy on longitudinal MRI from asymptomatic stage to symptomatic stage in MAPT mutation carriers.

Methods

Participants

Participants in this study were enrolled in the Mayo Clinic Alzheimer's Disease Research Center and the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) studies at the Mayo Clinic site. LEFFTDS is a multisite study investigating the biomarkers of disease progression in familial FTLD mutation carriers. The present study included participants who screened positive for a mutation in MAPT and had been followed up between August 2006 and November 2018 at Mayo Clinic. Participants with MAPT mutations who had no clinical symptoms at baseline and underwent at least two follow-up evaluations were included (n = 14). Noncarriers from healthy first-degree relatives of the patients were included as the control group after DNA screening (n = 13). All participants were followed up prospectively with annual clinical examination at the time of MR examination, including a medical history review, mental status examination, a neurological examination by a clinician with FTLD expertise, and a neuropsychological examination. Participants were followed for a median of 9.2 years (range 2.0 to 11.7 years) and had at least 3 MRI scans, with a total of 166 MRI examinations. Of the 14 MAPT mutation carriers, 4 of them, all from a pallido-ponto-nigral degeneration (PPND) family with N279 K mutation [23], transitioned from asymptomatic stage to symptomatic stage during follow-up, which we refer to as converters. All converters were classified as MCI at the time of conversion, with two later developing features of mixed behavioral variant frontotemporal dementia and progressive supranuclear palsy (Richardson's syndrome), one developing behavioral variant frontotemporal dementia with parkinsonism and the other remaining MCI. The median age of symptom onset was 43.5 years with a range of 37–47 years, and the median follow-up interval was 9.7 years (range 8.7–11.7 years) for these four converters (typical for this PPND family). The remaining 10 MAPT mutation carriers (from 5 families) had no cognitive/behavioral/motor changes, which was corroborated by their informants and had an MMSE score of 30 throughout the median follow-up interval of 8.5 years (range 2.0–10.7 years), which we refer to as asymptomatic MAPT mutation carriers. The noncarriers did not differ from the asymptomatic MAPT mutation carriers and the converters on MMSE and DRS at baseline. The behavioral neurologist (B.F.B) who examined all the participants was blinded to the mutation status of all asymptomatic individuals regardless of mutation carrier status. None of the participants had structural lesions that could cause cognitive impairment or dementia, such as cortical infarction, subdural hematoma, or tumor, or had concurrent illness that would interfere with cognitive function other than FTLD on baseline and follow-up examinations. All converters described in this report have undergone clinical genetic testing and therefore they and their proxies, as well as the examining neurologist, are aware of their mutation status. Most of the asymptomatic mutation carriers included in this report have not undergone clinical genetic testing and are therefore not aware of their mutation status. Details regarding each person have intentionally been excluded to maintain confidentiality. Informed consent was obtained from all participants for participation in the studies, and after the three converters developed dementia, written assent was also obtained by their proxies. All procedures were approved by the Mayo Institutional Review Board.

MRI acquisition and process

All participants had volumetric MRI performed annually at 3T using an 8-channel phased array head coil (GE Healthcare, Milwaukee, WI) with a standard protocol. A 3D high-resolution T1-weighted magnetization-prepared rapid acquisition gradient echo (MPRAGE) was performed at each time point using following parameters: repetition time/echo time/inversion time = 2300/3/900 ms, flip angle 8°, in-plane resolution of 1.0 mm.

Region-level analysis

Baseline and annual changes in cortical volume were estimated for each participant. For the region-level analysis, we applied a fully automated in-house developed image-processing pipeline, using tensor-based morphometry with symmetric normalization (TBM-SyN) to compute the baseline lobar cortical volumes and changes over time in each participant [24]. For each participant, all their T1 structural MRI scans were iteratively coregistered to a mean image using a 6 degrees-of-freedom (6-DOF), followed by 9-DOF rigid body registration using SPM coregistration software [25] (www.fil.ion.ucl.ac.uk/spm). Then image intensity histograms across each participant's time series of images were normalized using an in-house developed differential bias correction algorithm [26]. The SyN diffeomorphic registration algorithm from ANTs software [26] was used to compute deformations between each pair of images, running the deformations explicitly in each direction, producing the Jacobian determinant images, and the “annualized” log of the Jacobian determinant from the deformation in each direction, to be parcellated into lobar regions of interest later. The voxel values of the Jacobian determinant image represent the expansion or contraction of each voxel over time, and those of the annualized log Jacobian determinant image can be thought of as analogous to an annualized percent change at each voxel. The SyN deformations were applied in each direction, respectively to the original bias corrected late and early images, to get the early image warped to the late, and the late image warped to the early image, and average them with their respective originals, resulting in a “synthetic late image” and a “synthetic early image.” We then segmented the synthetic early and late images into gray matter, white matter, and cerebrospinal fluid classes using SPM with our in-house developed template [27]. The discrete cosine deformations from the unified segmentation step were used to transform the in-house modified AAL atlas that included the frontal, temporal, parietal, and occipital region of interest labels from template space to the synthetic early and late image spaces, respectively [28].

Voxel-level analysis

To assess the rates of atrophy at the voxel level, we used only the first and last images for each participant and ran the TBM-SyN steps as detailed previously to produce an image of the annualized log of the Jacobian determinant over the largest possible time interval for each participant. These images were smoothed with a 6 mm full-width at half maximum Gaussian smoothing kernel.

Genetic analysis

Participants recruited into this study are part of known MAPT families. For each of the participants, we specifically sequence the exon harboring the known MAPT mutation observed in that family using previously published protocol [29]. Sequencing is also performed to detect variants in the following genes GRN, C9ORF72, TARDBP, PSEN1, PSEN2, and APP according to the LEFFTDS protocol. PCR amplicons were purified using the Multiscreen system (Millipore, Billerica, MA) and then sequenced in both directions using Big Dye chemistry following the manufacturer's protocol (Applied Biosystems, Foster City, CA). Sequence products were purified using the Montage system (Millipore) before being run on an Applied Biosystem 3730 DNA Analyzer. Sequence data were analyzed using either SeqScape (Applied Biosystem) or Sequencher software (Gene Codes, Ann Arbor, MI).

Statistical analysis

Baseline characteristics of converters with MAPT mutations were described with means, standard deviations, counts, and proportions. Baseline characteristics were compared among converters, asymptomatic MAPT mutation carriers and noncarriers using generalized linear mixed models (categorical variables), or linear mixed models (continuous variables), adjusting for age where appropriate and accounting for the family structure using random effects. Tukey contrasts were subsequently used for pairwise comparisons. Assessments of voxel-level results were corrected for multiple comparisons by requiring the corrected false discovery rate (FDR) to be < 0.05 and the uncorrected P < .001. We modeled the log of lobar cortical volumes to estimate rate of volume loss expressed as percentage per year using linear mixed-effect models with random intercepts to account for within-subject repeated-measures correlations nested in within-family correlations. This allowed for dependence in the repeated measures per subject and also dependence in family members. Families were assumed to be independent from each other. Because of the sample size restrictions, we were only able to use random intercepts in these models. Inclusion of random slopes and flex points would result in gross overfitting of the models and nonconvergence. We coded group (noncarriers, asymptomatic, or converter) using dummy variables with noncarrier as the reference and included two-way interactions for group × age at MRI scan. Because we were interested in specific individual lobar cortical volume change hypotheses and not a universal null hypothesis and did not want to inflate the probability of a type II error, we did not adjust for multiple comparisons in these analyses.

Results

The baseline characteristics of the converters, asymptomatic MAPT mutation carriers, and noncarriers are shown in Table 1. There were no differences between the 3 groups at baseline based on sex, education, age at initial MRI scan, and cognitive scores. The converters had more MRI scans compared to asymptomatic MAPT mutation carriers (P < .001) and noncarriers (P < .001), but there were no differences in follow-up time range among the 3 groups. At baseline, temporal and frontal lobe volumes were lower in converters compared to asymptomatic MAPT mutation carriers (P < .001) and noncarriers (P < .001). Similarly, parietal lobe volumes were also lower in converters compared to asymptomatic MAPT mutation carriers (P < .001) and noncarriers (P < .001). No significant difference in lobar volume was observed between asymptomatic MAPT mutation carriers and noncarriers at baseline.
Table 1

Baseline characteristics of participants and lobar cortical volumes

Noncarrier (N = 13)Asymptomatic (N = 10)Converter (N = 4)P value
No. female (%)7 (54)4 (40)2 (50).95
Education, year16 (2)17 (3)15 (3).34
Age at MRI scan, yr36 (12)31 (5)39 (3).21
MMSE30 (1)30 (0)30 (0).17
DRS total MOANS12 (2)11 (2)12 (1).90
AVLT delay recalled MOANS12 (4)11 (2)14 (1).82
No. of MRI scans5 (2)5 (2)11 (2)<.001
Follow-up, yr8 (3)7 (3)10 (1).49
Cortical volume at baseline (cm3)
 Frontal138 (8)142 (18)106 (11).001
 Temporal117 (7)126 (12)85 (7)<.001
 Parietal70 (7)71 (5)53 (2)<.001
 Occipital64 (8)65 (6)53 (2).09

NOTE. Data shown are n (%) or mean (SD).

P values are from linear mixed models adjusting for age at MRI, also accounting for within-family correlations, followed by Tukey contrasts for pairwise comparisons.

Abbreviations: MRI, magnetic resonance imaging; MMSE, Mini–Mental State Examination; DRS, Dementia Rating Scale; MOANS, Mayo's Older Americans Normative Studies; AVLT, Auditory-Verbal Learning Test.

Converter is statistically different from other groups.

Baseline characteristics of participants and lobar cortical volumes NOTE. Data shown are n (%) or mean (SD). P values are from linear mixed models adjusting for age at MRI, also accounting for within-family correlations, followed by Tukey contrasts for pairwise comparisons. Abbreviations: MRI, magnetic resonance imaging; MMSE, Mini–Mental State Examination; DRS, Dementia Rating Scale; MOANS, Mayo's Older Americans Normative Studies; AVLT, Auditory-Verbal Learning Test. Converter is statistically different from other groups. Fig. 1 shows the trajectories of change in lobar cortical volumes. The results of linear mixed-effects models are summarized in Table 2. Group × age at MRI scan interactions indicated that the converters had greater estimated annual rate of cortical atrophy in temporal (P < .001), frontal (P < .01), and parietal (P < .05) lobes compared to noncarriers. Similarly, the asymptomatic MAPT mutation carriers also had higher estimated annual rate of cortical atrophy in the temporal lobe than noncarriers (P < .01), but not in the frontal and parietal lobes. There was no difference in the estimated annual rate of occipital lobe cortical volume change among the 3 groups.
Fig. 1

Lobar volume plotted against age at MRI. Data point trajectories for individual MAPT mutation carriers (top panel) and the predicted volumes (cm3) from the mixed models for each group (bottom panel) are shown. The blue line represents for the asymptomatic group who remained asymptomatic during the course of the study; the red line represents for the asymptomatic MAPT mutation carriers who converted; the black line represents the noncarriers. The noncarriers are not plotted in the top panel to show the data from the MAPT mutation carriers with clarity. Abbreviations: MAPT, microtubule-associated protein tau; MRI, magnetic resonance imaging.

Table 2

Predicted annual change in lobar volumes from mixed-effects models with noncarriers as the reference group

Frontal
Temporal
Parietal
Occipital
Estimates (95% CI)Estimates (95% CI)Estimates (95% CI)Estimates (95% CI)
Intercept155.5 (144.3, 166.8)129.8 (121.8, 137.8)76.5 (71.5, 81.5)69.1 (65.0, 73.2)
Age at MRI scan−0.55 (−0.82, −0.27)−0.41 (−0.62, −0.19)−0.20 (−0.29, −0.10)−0.16 (−0.24, −0.09)
Asymptomatic12.8 (−5.23, 30.7)26.4 (13.6, 39.2)−1.10 (−8.62, 6.42)0.77 (−5.74, 7.29)
Converter6.37 (−17.0, 29.8)18.2 (1.66, 34.8)−6.63 (−17.0, 3.75)−7.03 (−15.6, 1.54)
Asymptomatic × age at MRI scan−0.26 (−0.69, 0.16)−0.53 (−0.86, −0.20)0.06 (−0.09, 0.21)0.01 (−0.10, 0.13)
Converter × age at MRI scan−0.89 (−1.41, −0.36)−1.21 (−1.63, −0.80)−0.22 (−0.40, −0.05)−0.07 (−0.21, 0.07)

NOTE. The noncarrier group regression equations contain the intercept and age at MRI terms. The asymptotic group equations add the “asymptotic” and “asymptotic × age at MRI scan” terms to the equation. The converter group equations instead add the “converter” and “converter × age at MRI scan” terms to the equation. These produce the predicted lines in Fig. 1. Because of the interactions in the models, age and group coefficients are not directly interpretable.

Abbreviations: CI, confidence interval; MRI, magnetic resonance imaging.

P < .001.

P < .05.

P < .01.

Lobar volume plotted against age at MRI. Data point trajectories for individual MAPT mutation carriers (top panel) and the predicted volumes (cm3) from the mixed models for each group (bottom panel) are shown. The blue line represents for the asymptomatic group who remained asymptomatic during the course of the study; the red line represents for the asymptomatic MAPT mutation carriers who converted; the black line represents the noncarriers. The noncarriers are not plotted in the top panel to show the data from the MAPT mutation carriers with clarity. Abbreviations: MAPT, microtubule-associated protein tau; MRI, magnetic resonance imaging. Predicted annual change in lobar volumes from mixed-effects models with noncarriers as the reference group NOTE. The noncarrier group regression equations contain the intercept and age at MRI terms. The asymptotic group equations add the “asymptotic” and “asymptotic × age at MRI scan” terms to the equation. The converter group equations instead add the “converter” and “converter × age at MRI scan” terms to the equation. These produce the predicted lines in Fig. 1. Because of the interactions in the models, age and group coefficients are not directly interpretable. Abbreviations: CI, confidence interval; MRI, magnetic resonance imaging. P < .001. P < .05. P < .01. Voxel-based analysis showed that the annualized rate of atrophy was localized to the bilateral anterior and medial temporal lobe, inferior frontal lobe, limbic cortex, cingulate gyrus, precuneus, precentral gyrus, as well as the supplementary motor areas in all MAPT mutation carriers compared to noncarriers (corrected FDR <0.05) (Fig. 2). Because the MAPT mutation carriers also included four converters with N279 K mutation carriers from the same PPND family, we performed voxel-based analysis after removing the converters. Greater atrophy rates were found in the bilateral anterior and medial temporal lobe and orbitofrontal cortex in asymptomatic MAPT mutation carriers compared to noncarriers excluding the four converters (P < .001, not corrected for multiple comparisons).
Fig. 2

Voxel-based analysis showed greater annualized rates of cortical atrophy in all MAPT mutation carriers compared to noncarriers. The results are shown at P < .05 after using the false discovery rate correction for multiple comparisons. Abbreviation: MAPT, microtubule-associated protein tau.

Voxel-based analysis showed greater annualized rates of cortical atrophy in all MAPT mutation carriers compared to noncarriers. The results are shown at P < .05 after using the false discovery rate correction for multiple comparisons. Abbreviation: MAPT, microtubule-associated protein tau.

Discussion

In this longitudinal study using 166 serial MRI scans, we report regional rates of atrophy in MAPT mutation carriers from the asymptomatic stage, four of whom became symptomatic during follow-up. In converters who became symptomatic during follow-up, we found that cortical atrophy was already present at baseline in the temporal, frontal, and parietal lobes, although they were asymptomatic at that time. On the other hand, no differences in lobar volumes were observed in asymptomatic MAPT mutation carriers at baseline, who remained asymptomatic during follow-up compared to noncarriers. Our longitudinal data showed that the trajectories of lobar cortical atrophy were fastest in the temporal lobe, followed by frontal and parietal lobes in converters compared to noncarriers as they aged. The asymptomatic MAPT mutation carriers also showed a faster rate of temporal lobe cortical atrophy than noncarriers. Taken together, our cross-sectional and longitudinal findings demonstrated a sequential pattern of lobar atrophy in MAPT mutation carriers throughout the disease course, indicating that the temporal lobe cortical volume began declining during the asymptomatic stage, with an acceleration of the rates of atrophy during development of symptoms, followed by the involvement of the frontal and parietal lobes and sparing of the occipital lobe. The temporal lobe cortical volumes declined in MAPT mutation carriers as early as the asymptomatic stage particularly in the bilateral medial temporal lobe on voxel-based analysis. This pattern is consistent with findings from previous cross-sectional MRI studies that demonstrate most prominent atrophy in the anteromedial temporal lobe and orbitofrontal cortex in asymptomatic MAPT mutation carriers [5], [14], [17]; however, others found no difference between asymptomatic MAPT mutation carriers and controls [7], [20]. Gray matter decline in the hippocampus in asymptomatic MAPT mutation carriers was found in a recent longitudinal voxel-based morphometry study during 2 years of follow-up [21]. Another study reported extensive gray matter volume loss mainly in temporal and frontal lobes in a converter group combining 5 MAPT mutation and 3 GRN mutation carriers but found no longitudinal gray matter volume loss in asymptomatic MAPT and GRN mutation carriers who did not convert compared with noncarriers [22]. In the present study, we found lower baseline temporal lobe cortical volumes in converters, who later became symptomatic during follow-up compared to noncarriers. On the contrary, in the asymptomatic MAPT mutation carriers who remained asymptomatic, the temporal lobe cortical volumes were not different form noncarriers at baseline on cross-sectional analysis. The discordance in the literature on temporal lobe atrophy in asymptomatic MAPT mutation carriers may be due to the differences in the proximity to the age of symptom onset in cross-sectional studies of different asymptomatic MAPT mutation carrier cohorts or the sensitivity of the image analysis algorithm to relatively small amount of change in gray matter volume. Early and accelerated rates of atrophy in the temporal lobe is a consistent finding in symptomatic carriers of MAPT mutations [13], [16], suggesting that brain structural changes continue to occur in the same set of regions that are affected early in the disease. In keeping with that, the greatest atrophy rates were observed in the temporal lobe cortex in asymptomatic MAPT mutation carriers compared to noncarriers, which accelerated in those who became symptomatic. Given the increasing number of studies demonstrating early temporal atrophy in MAPT mutation carriers [13], [14], [15], [16], our findings confirm and extend those reports and demonstrate early involvement of temporal lobe cortical atrophy in a longitudinal study design. In the present study, the finding that frontal lobes especially the orbitofrontal lobe cortex present starting from the asymptomatic stage only in converters compared to noncarriers and became more atrophic as the disease progressed is consistent with atrophy patterns reported in previous voxel-based morphometry studies of familial FTD [5]. The progressive involvement of the frontal lobes followed the involvement of the temporal lobes, and the motor cortices, including the primary and supplementary motor cortices, were also affected in the asymptomatic MAPT mutation carriers on voxel-based analysis. However, greater rates of atrophy in the primary and supplementary motor cortices in MAPT mutation carriers compared to noncarriers were no longer statistically significant after removing the converters with MAPT N279K mutations who became symptomatic during follow-up from the voxel-based analysis. Patients with MAPT N279K mutations have prominent motor symptoms early in the disease process [23], [30], [31], and therefore, involvement of the primary and supplementary motor cortices may be expected in this group, influencing the results of the voxel-based analysis [32], [33], [34], [35], [36]. In symptomatic MAPT mutation carriers, the frontal lobes were reported to have the fastest rates of atrophy, followed by the temporal and parietal lobes [37]. Taken together with our findings, the temporal progression of lobar atrophy may follow a sequential pattern in MAPT mutation carriers. Temporal lobe cortical atrophy occurs in the earliest stages during the asymptomatic stage. After the patients become symptomatic, the rates of atrophy may slow down in the temporal lobes but accelerates in the frontal lobes during the later stages of disease progression. Our data showed that parietal lobe cortical atrophy, especially in the precuneus, was present starting from the asymptomatic stage only in converters compared to noncarriers, but with relatively slower rates of atrophy than the temporal and frontal lobes. However, the rates of cortical atrophy in the parietal lobe were not different from asymptomatic MAPT mutation carriers compared to noncarriers. Thus, the parietal lobe cortical atrophy occurred later than temporal lobe involvement, but also years before symptom onset when asymptomatic MAPT mutation carriers approaching closely to the symptom onset age, and progressed slower than temporal and frontal lobe cortical atrophy. This pattern of parietal cortical lobe atrophy is consistent with findings reported in symptomatic MAPT mutation carriers [15]. The early involvement of parietal lobe was also found in an 1H MR spectroscopy study that demonstrated early metabolite abnormalities in the posterior cingulate and precuneus cortex in asymptomatic MAPT mutation carriers [6]. Similarly, mild glucose hypometabolism in the parietal lobes on PET was found in N279K MAPT mutation carriers from the same PPND family, along with ballooned neurons and abundant tau inclusions in the parietal cortex at autopsy [33]. The early involvement of the parietal lobe cortex, particularly the paralimbic regions such as the precuneus, but a relatively slow progression of atrophy in this region may be associated with the gradual involvement of limbic pathways that connect the anteromedial temporal lobe to the medial parietal cortex in patients with MAPT mutations who are approaching the symptomatic stage [38], [39]. One strength of our study was the large number of serial MRIs collected over 10 years and tracking of the disease progression from asymptomatic to symptomatic stage; however, the relatively small number of participants in each group was still a limitation. Although one of our previous cross-sectional studies had shown similar patterns atrophy across different submutation types in MAPT mutation carriers [16], there may be variability in the rates of atrophy within the asymptomatic MAPT mutation carriers across different specific mutations. Subtypes of MAPT mutation have been shown to cause different types of tauopathies. These are mutations inside exon 10 (i.e., N279K, P301L, and S305N) that tend to form four tandem microtubule-binding domain repeat (4R-tau) pathology relative to 3 repeat (3R tau) pathology [40], and mutations outside exon 10 (i.e., V337M and R406W) that tend to form mixed 3 R/4R tau pathology. The 4 converters in the present study all had N279K MAPT mutations, and their trajectories of lobar atrophy, such as the supplemental motor cortex involvement, may be specific to the suspected 4R-tau-associated neurodegeneration in N279K kindreds. Further studies are needed to characterize the trajectories of rates of brain atrophy across the different MAPT mutations. In summary, our data indicate a sequential pattern of regional cortical atrophy rates involving the temporal lobe cortex early on, followed by the frontal and parietal lobe cortices in MAPT mutation carriers as they transition from asymptomatic stage to symptomatic stage. Our findings support the clinical utility of using longitudinal regional volumes for monitoring the neurodegenerative disease progression in MAPT mutation carriers starting from the asymptomatic stage. Lobar cortical atrophy rates may also have a utility in clinical trials involving agents that potentially modify neurodegenerative disease pathology in asymptomatic MAPT mutation carriers. Systematic review: The authors reviewed the literature using traditional (e.g., PubMed) sources and meeting abstracts and presentations. Interpretation: Our findings provide details on a sequential pattern of regional cortical atrophy rates in microtubule-associated protein tau (MAPT) mutation carriers as they transition from asymptomatic stage to symptomatic stage. Future directions: The manuscript proposes a framework of using longitudinal regional volumes for monitoring the neurodegenerative disease progression in MAPT mutation carriers starting from the asymptomatic stage. Further studies are needed to characterize the trajectories of rates of brain atrophy across the different subtypes of MAPT mutation.
  39 in total

1.  Gray and white matter changes in presymptomatic genetic frontotemporal dementia: a longitudinal MRI study.

Authors:  Jessica L Panman; Lize C Jiskoot; Mark J R J Bouts; Lieke H H Meeter; Emma L van der Ende; Jackie M Poos; Rogier A Feis; Anneke J A Kievit; Rick van Minkelen; Elise G P Dopper; Serge A R B Rombouts; John C van Swieten; Janne M Papma
Journal:  Neurobiol Aging       Date:  2019-01-07       Impact factor: 4.673

2.  Structural and functional brain connectivity in presymptomatic familial frontotemporal dementia.

Authors:  Elise G P Dopper; Serge A R B Rombouts; Lize C Jiskoot; Tom den Heijer; J Roos A de Graaf; Inge de Koning; Anke R Hammerschlag; Harro Seelaar; William W Seeley; Ilya M Veer; Mark A van Buchem; Patrizia Rizzu; John C van Swieten
Journal:  Neurology       Date:  2013-02-06       Impact factor: 9.910

3.  Brain atrophy over time in genetic and sporadic frontotemporal dementia: a study of 198 serial magnetic resonance images.

Authors:  J L Whitwell; B F Boeve; S D Weigand; M L Senjem; J L Gunter; M C Baker; M DeJesus-Hernandez; D S Knopman; Z K Wszolek; R C Petersen; R Rademakers; C R Jack; K A Josephs
Journal:  Eur J Neurol       Date:  2015-02-12       Impact factor: 6.089

Review 4.  Frontotemporal dementia.

Authors:  Jee Bang; Salvatore Spina; Bruce L Miller
Journal:  Lancet       Date:  2015-10-24       Impact factor: 79.321

5.  Antemortem MRI based STructural Abnormality iNDex (STAND)-scores correlate with postmortem Braak neurofibrillary tangle stage.

Authors:  Prashanthi Vemuri; Jennifer L Whitwell; Kejal Kantarci; Keith A Josephs; Joseph E Parisi; Maria S Shiung; David S Knopman; Bradley F Boeve; Ronald C Petersen; Dennis W Dickson; Clifford R Jack
Journal:  Neuroimage       Date:  2008-05-20       Impact factor: 6.556

6.  MRI and pathology of REM sleep behavior disorder in dementia with Lewy bodies.

Authors:  Melissa E Murray; Tanis J Ferman; Bradley F Boeve; Scott A Przybelski; Timothy G Lesnick; Amanda M Liesinger; Matthew L Senjem; Jeffrey L Gunter; Gregory M Preboske; Val J Lowe; Prashanthi Vemuri; Brittany N Dugger; David S Knopman; Glenn E Smith; Joseph E Parisi; Michael H Silber; Neill R Graff-Radford; Ronald C Petersen; Clifford R Jack; Dennis W Dickson; Kejal Kantarci
Journal:  Neurology       Date:  2013-10-09       Impact factor: 9.910

7.  Patterns of atrophy differ among specific subtypes of mild cognitive impairment.

Authors:  Jennifer L Whitwell; Ronald C Petersen; Selamawit Negash; Stephen D Weigand; Kejal Kantarci; Robert J Ivnik; David S Knopman; Bradley F Boeve; Glenn E Smith; Clifford R Jack
Journal:  Arch Neurol       Date:  2007-08

8.  Rapidly progressive autosomal dominant parkinsonism and dementia with pallido-ponto-nigral degeneration.

Authors:  Z K Wszolek; R F Pfeiffer; M H Bhatt; R L Schelper; M Cordes; B J Snow; R L Rodnitzky; E C Wolters; F Arwert; D B Calne
Journal:  Ann Neurol       Date:  1992-09       Impact factor: 10.422

9.  Distinct profiles of brain atrophy in frontotemporal lobar degeneration caused by progranulin and tau mutations.

Authors:  Jonathan D Rohrer; Gerard R Ridgway; Marc Modat; Sebastien Ourselin; Simon Mead; Nick C Fox; Martin N Rossor; Jason D Warren
Journal:  Neuroimage       Date:  2010-01-04       Impact factor: 6.556

10.  Longitudinal white matter change in frontotemporal dementia subtypes and sporadic late onset Alzheimer's disease.

Authors:  Fanny M Elahi; Gabe Marx; Yann Cobigo; Adam M Staffaroni; John Kornak; Duygu Tosun; Adam L Boxer; Joel H Kramer; Bruce L Miller; Howard J Rosen
Journal:  Neuroimage Clin       Date:  2017-09-14       Impact factor: 4.881

View more
  10 in total

Review 1.  Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis.

Authors:  Suvi Häkkinen; Stephanie A Chu; Suzee E Lee
Journal:  Neurobiol Dis       Date:  2020-09-02       Impact factor: 5.996

2.  New directions in clinical trials for frontotemporal lobar degeneration: Methods and outcome measures.

Authors:  Adam L Boxer; Michael Gold; Howard Feldman; Bradley F Boeve; Susan L-J Dickinson; Howard Fillit; Carole Ho; Robert Paul; Rodney Pearlman; Margaret Sutherland; Ajay Verma; Stephen P Arneric; Brian M Alexander; Bradford C Dickerson; Earl Ray Dorsey; Murray Grossman; Edward D Huey; Michael C Irizarry; William J Marks; Mario Masellis; Frances McFarland; Debra Niehoff; Chiadi U Onyike; Sabrina Paganoni; Michael A Panzara; Kenneth Rockwood; Jonathan D Rohrer; Howard Rosen; Robert N Schuck; Holly D Soares; Nadine Tatton
Journal:  Alzheimers Dement       Date:  2020-01-06       Impact factor: 21.566

3.  Preventing amyotrophic lateral sclerosis: insights from pre-symptomatic neurodegenerative diseases.

Authors:  Michael Benatar; Joanne Wuu; Caroline McHutchison; Ronald B Postuma; Bradley F Boeve; Ronald Petersen; Christopher A Ross; Howard Rosen; Jalayne J Arias; Stephanie Fradette; Michael P McDermott; Jeremy Shefner; Christine Stanislaw; Sharon Abrahams; Stephanie Cosentino; Peter M Andersen; Richard S Finkel; Volkan Granit; Anne-Laure Grignon; Jonathan D Rohrer; Corey T McMillan; Murray Grossman; Ammar Al-Chalabi; Martin R Turner
Journal:  Brain       Date:  2022-03-29       Impact factor: 15.255

4.  P301S-hTau acetylates KEAP1 to trigger synaptic toxicity via inhibiting NRF2/ARE pathway: A novel mechanism underlying hTau-induced synaptic toxicities.

Authors:  Jia-Zhao Xie; Yao Zhang; Shi-Hong Li; Hui Wei; Hui-Ling Yu; Qiu-Zhi Zhou; Lin-Yu Wei; Dan Ke; Qun Wang; Ying Yang; Jian-Zhi Wang
Journal:  Clin Transl Med       Date:  2022-08

5.  Hierarchical spectral clustering reveals brain size and shape changes in asymptomatic carriers of C9orf72.

Authors:  Rose Bruffaerts; Dorothy Gors; Alicia Bárcenas Gallardo; Mathieu Vandenbulcke; Philip Van Damme; Paul Suetens; John C van Swieten; Barbara Borroni; Raquel Sanchez-Valle; Fermin Moreno; Robert Laforce; Caroline Graff; Matthis Synofzik; Daniela Galimberti; James B Rowe; Mario Masellis; Maria Carmela Tartaglia; Elizabeth Finger; Alexandre de Mendonça; Fabrizio Tagliavini; Chris R Butler; Isabel Santana; Alexander Gerhard; Simon Ducharme; Johannes Levin; Adrian Danek; Markus Otto; Jonathan D Rohrer; Patrick Dupont; Peter Claes; Rik Vandenberghe
Journal:  Brain Commun       Date:  2022-07-18

Review 6.  Recent advances in understanding frontotemporal degeneration.

Authors:  Barbara Borroni; Alberto Benussi
Journal:  F1000Res       Date:  2019-12-13

7.  Rates of Brain Atrophy Across Disease Stages in Familial Frontotemporal Dementia Associated With MAPT, GRN, and C9orf72 Pathogenic Variants.

Authors:  Adam M Staffaroni; Sheng-Yang M Goh; Yann Cobigo; Elise Ong; Suzee E Lee; Kaitlin B Casaletto; Amy Wolf; Leah K Forsberg; Nupur Ghoshal; Neill R Graff-Radford; Murray Grossman; Hilary W Heuer; Ging-Yuek R Hsiung; Kejal Kantarci; David S Knopman; Walter K Kremers; Ian R Mackenzie; Bruce L Miller; Otto Pedraza; Katya Rascovsky; M Carmela Tartaglia; Zbigniew K Wszolek; Joel H Kramer; John Kornak; Bradley F Boeve; Adam L Boxer; Howard J Rosen
Journal:  JAMA Netw Open       Date:  2020-10-01

8.  Brain volumetric deficits in MAPT mutation carriers: a multisite study.

Authors:  Stephanie A Chu; Taru M Flagan; Adam M Staffaroni; Lize C Jiskoot; Jersey Deng; Salvatore Spina; Liwen Zhang; Virginia E Sturm; Jennifer S Yokoyama; William W Seeley; Janne M Papma; Dan H Geschwind; Howard J Rosen; Bradley F Boeve; Adam L Boxer; Hilary W Heuer; Leah K Forsberg; Danielle E Brushaber; Murray Grossman; Giovanni Coppola; Bradford C Dickerson; Yvette M Bordelon; Kelley Faber; Howard H Feldman; Julie A Fields; Jamie C Fong; Tatiana Foroud; Ralitza H Gavrilova; Nupur Ghoshal; Neill R Graff-Radford; Ging-Yuek Robin Hsiung; Edward D Huey; David J Irwin; Kejal Kantarci; Daniel I Kaufer; Anna M Karydas; David S Knopman; John Kornak; Joel H Kramer; Walter A Kukull; Maria I Lapid; Irene Litvan; Ian R A Mackenzie; Mario F Mendez; Bruce L Miller; Chiadi U Onyike; Alexander Y Pantelyat; Rosa Rademakers; Eliana Marisa Ramos; Erik D Roberson; Maria Carmela Tartaglia; Nadine A Tatton; Arthur W Toga; Ashley Vetor; Sandra Weintraub; Bonnie Wong; Zbigniew K Wszolek; John C Van Swieten; Suzee E Lee
Journal:  Ann Clin Transl Neurol       Date:  2020-11-28       Impact factor: 5.430

9.  [18F]Flortaucipir PET Across Various MAPT Mutations in Presymptomatic and Symptomatic Carriers.

Authors:  Emma E Wolters; Janne M Papma; Sander C J Verfaillie; Denise Visser; Emma Weltings; Colin Groot; Emma L van der Ende; Lucia A A Giannini; Hayel Tuncel; Tessa Timmers; Ronald Boellaard; Maqsood Yaqub; Danielle M E van Assema; Dennis A Kuijper; Marcel Segbers; Annemieke J M Rozemuller; Frederik Barkhof; Albert D Windhorst; Wiesje M van der Flier; Yolande A L Pijnenburg; Philip Scheltens; Bart N M van Berckel; John C van Swieten; Rik Ossenkoppele; Harro Seelaar
Journal:  Neurology       Date:  2021-07-01       Impact factor: 9.910

10.  Long-Term Hydromethylthionine Treatment Is Associated with Delayed Clinical Onset and Slowing of Cerebral Atrophy in a Pre-Symptomatic P301S MAPT Mutation Carrier.

Authors:  Peter Bentham; Roger T Staff; Bjoern O Schelter; Helen Shiells; Charles R Harrington; Claude M Wischik
Journal:  J Alzheimers Dis       Date:  2021       Impact factor: 4.472

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.