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Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, GermanyGerman Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
Paris Brain Institute - Institut du Cerveau - Hôpital Pitié-Salpêtrière, Sorbonne Université, Paris, FranceCentre de référence des démences rares ou précoces, IM2A, Département de Neurologie, Hôpital Pitié-Salpêtrière, Paris, FranceDépartement de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
Department of Neurology, Ludwig-Maximilians-University, Munich, GermanyGerman Center for Neurodegenerative Diseases (DZNE), Munich, GermanyMunich Cluster for Systems Neurology (SyNergy), Munich, Germany
The BCFT is an interesting candidate test for familial FTD.
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It identified gene-specific impairment mechanisms and its neuroimaging correlates.
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Impaired BCFT performance occurs relatively late in the FTD disease process.
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Therefore its potential as cognitive test for trials in the early stage is limited.
Abstract
Objective
Sensitive cognitive markers are still needed for frontotemporal dementia (FTD). The Benson Complex Figure Test (BCFT) is an interesting candidate test, as it assesses visuospatial, visual memory, and executive abilities, allowing the detection of multiple mechanisms of cognitive impairment. To investigate differences in BCFT Copy, Recall and Recognition in presymptomatic and symptomatic FTD mutation carriers, and to explore its cognitive and neuroimaging correlates.
Method
We included cross-sectional data from 332 presymptomatic and 136 symptomatic mutation carriers (GRN, MAPT or C9orf72 mutations), and 290 controls in the GENFI consortium. We examined gene-specific differences between mutation carriers (stratified by CDR® NACC-FTLD score) and controls using Quade's / Pearson Χ2 tests. We investigated associations with neuropsychological test scores and grey matter volume using partial correlations and multiple regression models respectively.
Results
No significant differences were found between groups at CDR® NACC-FTLD 0–0.5. Symptomatic GRN and C9orf72 mutation carriers had lower Copy scores at CDR® NACC-FTLD ≥2. All three groups had lower Recall scores at CDR® NACC-FTLD ≥2, with MAPT mutation carriers starting at CDR® NACC-FTLD ≥1. All three groups had lower Recognition scores at CDR® NACC FTLD ≥2. Performance correlated with tests for visuoconstruction, memory, and executive function. Copy scores correlated with frontal-subcortical grey matter atrophy, while Recall scores correlated with temporal lobe atrophy.
Conclusions
In the symptomatic stage, the BCFT identifies differential mechanisms of cognitive impairment depending on the genetic mutation, corroborated by gene-specific cognitive and neuroimaging correlates. Our findings suggest that impaired performance on the BCFT occurs relatively late in the genetic FTD disease process. Therefore its potential as cognitive biomarker for upcoming clinical trials in presymptomatic to early-stage FTD is most likely limited.
Frontotemporal dementia (FTD) is one of the most prevalent forms of early-onset dementia. Its clinical profile is typically characterized by disturbances in behaviour (behavioural variant; bvFTD) and language (primary progressive aphasia; PPA), with cognitive deficits in executive function and social cognition commonly seen. In contrast, episodic memory and visuospatial abilities are relatively spared [
]. FTD has an autosomal dominant inheritance pattern in around a third of cases, with mutations in progranulin (GRN), microtubule-associated protein tau (MAPT), and chromosome 9 open reading frame 72 (C9orf72) the most common causes of familial FTD [
]. As the mutations cause brain atrophy in distinct as well as overlapping anatomical brain regions, the associated phenotypes are often rather heterogeneous [
]. The clinical presentation associated with GRN mutations includes bvFTD, nonfluent variant PPA, atypical parkinsonism, and corticobasal syndrome (CBS) [
]. The cognitive profile commonly shows executive dysfunction, speech and language disorders, amnestic deficits and apraxia, consistent with frontal, temporal and parietal lobe involvement [
]. The pattern of cognitive impairment is often widespread, including deficits in language, attention, mental processing speed, executive function and immediate memory recall [
In recent years, research in the familial FTD field has increasingly focussed on the presymptomatic stage, as the critical time-window for treatment most likely lies prior to overt symptom onset, when the pathological damage is still low. With promising therapeutic avenues leading to disease-modifying therapy trials, the identification of robust clinical biomarkers is of utmost importance [
]. Interestingly, previous neuropsychological studies show that subtle cognitive decline is present in the presymptomatic stage of FTD (up to 10 years prior to overt disease onset), with gene-specific cognitive profiles for GRN, MAPT and C9orf72 [
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the genetic frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis.
]. This suggests that presymptomatic neuropsychological assessment may provide sensitive cognitive markers indicative of disease, onset and progression.
One particular neuropsychological instrument, the Benson Complex Figure test (BCFT), is an interesting candidate for familial FTD. Being part of the National Alzheimer's Coordinating Centre (NACC) FTD-module neuropsychological battery [
], performance on the BCFT relies on multiple cognitive functions, including visuospatial abilities, visual memory, and executive functions such as organization and working memory. Most studies into the BCFT have looked into differences between patients with bvFTD, patients with AD, and healthy controls, demonstrating a trend for those with bvFTD to score lower on figure copying than controls [
Distinct neuroanatomical substrates and cognitive mechanisms of figure copy performance in Alzheimer’s disease and behavioral variant frontotemporal dementia.
Utility and neuroanatomical correlates of the FTLD-NACC neuropsychology module in the differential diagnosis of behavioural variant frontotemporal dementia and Alzheimer’s disease.
]. Moreover, poor figure copy correlated with specific cognitive mechanisms (i.e. spatial planning and working memory) and neuroanatomical atrophy substrates (i.e. dorsolateral prefrontal cortex) in bvFTD [
Distinct neuroanatomical substrates and cognitive mechanisms of figure copy performance in Alzheimer’s disease and behavioral variant frontotemporal dementia.
]. Until now, research into the BCFT in presymptomatic FTD has been lacking.
The aim of the present study was therefore to: 1) investigate cross-sectional differences in the BCFT (copy, recall and recognition) between presymptomatic FTD mutation carriers, symptomatic FTD mutation carriers and cognitively unimpaired controls; 2) explore associations between the BCFT and other neuropsychological tests, and 3) examine associations between the BCFT and grey matter (GM) volume. Additionally, we investigated normative data and relationships with age, sex and education from the cognitively unimpaired control group.
2. Method
2.1 Participants
We included baseline data of 758 participants from genetically confirmed FTD families with either a GRN or MAPT pathogenic variant, or C9orf72 repeat expansion, recruited within the GENFI 2 fifth data freeze between March 2015 and May 2019. We determined clinical status according to established diagnostic criteria [
World Federation of Neurology Research Group on motor neuron diseases. El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis.
] and a standardized clinical assessment, including medical and family history taking, extensive neuropsychological assessment covering the major cognitive domains (see Neuropsychological assessment below), and MR imaging of the brain [
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the genetic frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis.
]. The total sample consisted of 332 presymptomatic mutation carriers (GRN = 143; MAPT = 59; C9orf72 = 130), 136 symptomatic mutation carriers (GRN = 41; MAPT = 23; C9orf72 = 72), and 290 non-carriers that were used as reference group (GRN = 122; MAPT = 57; C9orf72 = 111). The clinical diagnoses in symptomatic mutation carriers were as follows: bvFTD (n = 91), PPA (n = 21), ALS or FTD-ALS (n = 15), PSP (n = 2), dementia not otherwise specified (n = 2), and other (n = 5). We administered the global CDR® NACC-FTLD global score [
] as a measure of disease severity. Knowledgeable informants answered questions about behavioural and cognitive symptoms as well as the participant's activities of daily living in a structured interview which included two questionnaires (Cambridge Behavioural Inventory – Revised (CBI-R) [
]. Unless presymptomatic mutation carriers had undergone predictive testing at their own request, the clinical investigators were blinded to their genetic status. We obtained written informed consent from all participants at study enrolment. Ethical committees at each research site approved the study. This study was conducted in accordance with the declaration of Helsinki.
Distinct neuroanatomical substrates and cognitive mechanisms of figure copy performance in Alzheimer’s disease and behavioral variant frontotemporal dementia.
] is part of the standardized GENFI neuropsychological battery and consists of 3 conditions: Copy (in which the figure has to be copied from an example – see Fig. 1), Recall (in which the figure has to be drawn from memory after a 10–15 min interval), and Recognition (in which the target figure has to be recognised amongst three distractor figures). Scoring follows the NACC FTD-criteria [
]. Total scores for both Copy and Recall range from 0 to 16; each of the eight elements can receive a maximum score of two when both accuracy and placement are correct. A bonus point – adding up to a maximum score of 17 – is given when the figure is well-drawn (i.e., each element must be accurately drawn, all elements must be properly placed, all elements must be drawn in proper proportions, all connections between elements must be clean, and no extraneous lines may be present). Recognition is either scored as correct (score 1) or incorrect (score 0).
Tabled
1Appendix 3. Neuroimaging correlates of the BCFT. Abbreviations: GRN, progranulin; MAPT, microtubule-associated protein tau; C9orf72, chromosome 9 open reading frame 72; BCFT, Benson Complex Figure Test; L, left; R, right. *only clusters >50 voxels were reported; **uncorrected p < 0.001.
Volumetric T1-weighted MR images were acquired on a 3 T scanner in 698 participants (Philips Achieva n = 191, Siemens Prisma n = 191, Siemens Trio n = 178, Siemens Skyra n = 136, GE Discovery MR750 n = 2). All images were subjected to strict visual quality control, after which 15 participants were excluded from further analysis due to inadequate image quality. The DICOM images were subsequently corrected for gradient nonlinearity distortions and converted to NifTI format. These images were then analysed using the standard Voxel-Based Morphometry (VBM) pipeline in Statistical Parametric Mapping 12 (SPM12; Functional Imaging Laboratory, University College London, London, UK; www.fil.ion.ucl.ac.uk/spm) implemented in Matlab R2018a (Mathworks, USA). In the first pre-processing step, the T1-weighted images were normalized to a template space and segmented into GM, white matter (WM) and cerebrospinal fluid (CSF), after which they were rigidly aligned. We calculated total intracranial volume (TIV) by adding GM, WM and CSF. Secondly, the segmentations were spatially normalized to a DARTEL template by applying the flow fields of all the individual scans. Images were smoothed using a 6 mm full width at half maximum (FWHM) isotropic Gaussian kernel. At every preprocessing step, images were visually inspected.
2.5 Statistical analysis
We performed statistical analyses using SPSS Statistics 25.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism 5 (La Jolla, California, USA). Alpha was set at 0.05 across all comparisons, unless otherwise specified, and two-tailed analyses were performed. We compared continuous demographic data between groups by means of one-way ANOVA with post hoc Bonferroni comparisons for normally distributed data, or Kruskal-Wallis tests with post hoc Mann-Whitney U tests in case of non-normally distributed data. Between-group differences in sex distribution were analysed using Pearson Χ2 tests. In our reference (healthy control) group, we calculated cumulative frequencies, percentile scores, and performance across age, sex and education for BCFT Copy, Recall and Recognition. We used Spearman rank correlations to explore the relationships between the BCFT Copy and Recall, and age and education. The square root of eta squared (√η2) was used to investigate the relationship between age and education, and BCFT Recognition. We explored the differences in BCFT Copy and Recall and sex by means of Mann-Whitney U tests, and sex differences in BCFT Recognition by means of a Pearson Χ2 test. As BCFT Copy and Recall scores were non-normally distributed, we examined gene-specific (GRN, MAPT, C9orf72) differences between presymptomatic mutation carriers (CDR® NACC-FTLD global score 0 and 0.5), symptomatic mutation carriers (CDR® NACC-FTLD global score ≥ 1) and controls by means of Quade's rank analysis of covariance – adjusting for the effect of age, sex, years of education, and family clustering. We performed Pearson Χ2 tests to compare BCFT Recognition scores between groups. We investigated associations between BCFT Copy and Recall with neuropsychological test scores per mutation by means of partial correlations, controlling for the effect of age, sex, years of education, and family clustering. We explored the relationship between each BCFT test score and GM volume by means of multiple regression models in SPM12 (University College London, London, UK). Age, sex, scanner and TIV were entered as covariates. We set the statistical threshold at p < 0.05, adjusted for multiple comparisons with familywise error (FWE) correction. The uncorrected statistical threshold was set at p < 0.001 (minimum cluster size ≥10 voxels).
3. Results
3.1 Demographic and clinical data
Demographic and clinical data are shown in Table 1. Controls were significantly younger than symptomatic mutation carriers (GRN U = 1655.5, MAPT U = 1374.5; C9orf72 U = 3190.5; all p < 0.001), while presymptomatic MAPT mutation carriers were younger than controls (U = 6043, p < 0.001). All presymptomatic mutation carriers were younger than symptomatic mutation carriers (p < 0.001). There were fewer females in the symptomatic C9orf72 group than in the control (Χ(1) = 9.69, p < 0.001) or presymptomatic groups (GRN X(1) = 13.21, MAPT X(1) = 7.18; C9orf72 X(1) = 9.40; all p < 0.007). Symptomatic GRN and symptomatic C9orf72 were lower educated than controls [F(6,751) = 5.74, p ≤0.001). MMSE scores were lower in symptomatic mutation carriers than in controls (GRN U = 949, MAPT U = 654; C9orf72 U = 1909; all p < 0.001) and all presymptomatic groups (all p < 0.001). No differences were found amongst the symptomatic or presymptomatic groups (all p > 0.05). CDR® NACC-FTLD scores were higher in symptomatic mutation carriers than in presymptomatic mutation carriers and controls (all p < 0.001), and presymptomatic mutation carriers also had higher CDR® NACC-FTLD scores than controls (GRN U = 15,660, MAPT U = 6380; C9orf72 U = 13,050; all p < 0.001). Behavioural symptoms were higher in symptomatic mutation carriers than in presymptomatic mutation carriers and controls (all p < 0.001), but also higher in presymptomatic C9orf72 mutation carriers compared to controls (CBI-R U = 12,625.5, p = 0.053; FRS U = 10,677.5, p < 0.001) and presymptomatic GRN mutation carriers (CBI-R U = 6121.5, p = 0.008; FRS U = 4967.5, p = 0.004).
Table 1Demographic and clinical data of the mutation carriers and controls. Values indicate: count (percentage) or mean (standard deviation). Abbreviations: GRN, progranulin; MAPT, microtubule-associated protein tau; C9orf72, chromosome 9 open reading frame 72; MMSE, Mini-Mental State Examination; CDR, clinical dementia rating; NACC, National Alzheimer's Coordinating Center; FTLD, frontotemporal lobar degeneration; CBI-R, Cambridge Behavioural Inventory – Revised; FRS, Frontotemporal Dementia Rating Scale; BCFT, Benson Complex Figure Test.
Appendix 2 shows the reference groups' cumulative frequencies (Appendix 2.1), percentile scores (Appendix 2.2), and performance across age, sex and education (Appendix 2.3) for the BCFT Copy, Recall and Recognition. Scores for Copy ranged between 9 and 17; scores for Recall ranged between 6 and 17. 94.5% of controls were able to identify the correct figure in the Recognition trial. Performance below 14 for the Copy trial and below 8 for the Recall trial would be considered outside the normal range (i.e. ≤5th percentile). Age (rs(288) = −0.09, p = 0.125) and education (rs(288) = 0.11, p = 0.068) were not significantly associated with BCFT Copy. However, there was a significant correlation between both age (rs(288) = −0.45, p < 0.001) and education (rs(288) = 0.13, p = 0.031) and BCFT Recall. There was a strong positive correlation between BCFT Recognition and age (√η2 = 0.88); the correlation with education was weak (√η2 = 0.26). Women had higher BCFT Copy scores than men (mean rank women: 153.9 vs. men: 133.87; U = 8829.5, p = 0.014), whereas there were no sex differences in Recall (U = 9233.5, p = 0.147). Also BCFT Recognition scores did not differ between males and females (X(1) = 1.40, p = 0.237).
3.3 Group differences of the BCFT
Figure 1 shows the group differences in the BCFT Copy, Recall and Recognition between GRN, MAPT and C9orf72 mutation carriers according to CDR® NACC-FTLD global score.
Fig. 1BCFT Copy, Recall and Recognition data stratified by CDR plus NACC FTLD global score (0, 0.5, 1, 2 and 3) in GRN, MAPT and C9orf72 mutation carriers. Boxplots (for BCFT Copy and Recall) visualize mean (with whiskers representing min-max) scores per clinical group. * p < 0.05. Abbreviations: BCFT, Benson Complex Figure Test; GRN, progranulin; MAPT, microtubule-associated protein tau; C9orf72, Chromosome 9 open reading frame 72; CDR, Clinical Dementia Rating Scale.
For the BCFT Copy, no significant differences were found between groups at CDR® NACC-FTLD global score = 0 [F(3,529) = 1.170, p = 0.321] or 0.5 [F(3,370) = 0.751, p = 0.522]. However, there were significant differences between groups at CDR® NACC-FTLD global score ≥ 1 [F(3,426) = 10.128, p < 0.001], with both GRN and C9orf72 mutation carriers having lower Copy scores than controls (p = 0.001 and p < 0.001, respectively). No differences were seen in the MAPT mutation group. Performing a sub-analysis in the CDR® NACC-FTLD global score ≥ 1 group (stratifying into scores of 1, 2 and 3) demonstrated significant differences from a score of 2 onwards in both GRN and C9orf72 (but not MAPT) mutation carriers: at CDR® NACC-FTLD global scores of both 2 and 3 GRN and C9orf72 mutation carriers had lower Copy scores than controls (all p < 0.001).
For the BCFT Recall, there were similarly no significant differences between groups at CDR® NACC-FTLD global score = 0 [F(3,529) = 2.390, p = 0.068] or 0.5 [F(3,370) = 1.279, p = 0.281]. However, significant differences were seen between groups at CDR® NACC-FTLD global score ≥ 1 [F(3,426) = 20.469, p < 0.001]: all mutation carrier groups (GRN, MAPT and C9orf72) had significantly lower Recall scores than controls (all p < 0.001). Performing additional sub-analyses in the CDR® plus NACC FTLD score ≥ 1 group (stratified into scores of 1, 2 and 3) demonstrated significant differences in the CDR® NACC-FTLD global score = 1 group in the MAPT mutation carriers only (lower Recall scores than controls: p = 0.024). At CDR® NACC-FTLD global scores of 2 and 3, all mutation carrier groups had lower Recall scores than controls (p-values for scores 2 and 3 respectively: GRN, p = 0.007, p < 0.001; MAPT, p = 0.065, p < 0.001; C9orf72, p = 0.024, p < 0.001). No significant differences at any time point were found between mutation carrier groups (GRN vs. MAPT, p = 0.872; MAPT vs. C9orf72, p = 0.608; C9orf72 vs. GRN, p = 1.000).
For the BCFT Recognition, there were no significant differences between groups at CDR® NACC-FTLD global score = 0 [X(3) = 2.982, p = 0.394] or 0.5 [X(3) = 4.381, p = 0.223]. Significant differences between groups were seen at CDR® NACC-FTLD global score ≥ 1 [X(3) = 52.924, p < 0.001], with all mutation carrier groups having significantly lower Recognition scores than controls (all p < 0.001), although no significant differences were found between mutation carrier groups (GRN vs. MAPT, p = 0.830; MAPT vs. C9orf72, p = 0.794; C9orf72 vs. GRN, p = 0.974). Additional sub-analyses in the CDR® NACC-FTLD global score ≥ 1 group (stratified into scores of 1, 2 and 3) demonstrated no significant differences at CDR® NACC-FTLD global score = 1, but significant differences were seen between all mutation carrier groups and controls at a score of 2 (GRN vs. control, p < 0.001; MAPT vs. control, p = 0.038; C9orf72 vs. controls, p < 0.001) and a score of 3 (all comparisons p < 0.001).
3.4 Cognitive correlates of the BCFT
Partial correlation coefficients between the BCFT Copy and Recall test score and other relevant neuropsychological tests within the GENFI battery are shown in Table 2. Irrespective of the underlying mutation, both BCFT Copy and Recall test scores correlated significantly with TMT part B and WASI Block Design (p < 0.05). FCSRT immediate and delayed recall also correlated significantly with both BCFT Copy and Recall in every genetic group (p < 0.01), apart from Copy in C9orf72 mutation carriers. In this mutation, but not in GRN and MAPT, significant correlations were found between BCFT Copy and Recall test scores and D-KEFS Color-Word Interference Test card III and the letter fluency test (p < 0.05).
Table 2Partial correlation coefficients (corrected for age, sex, years of education, and family clustering) in GRN, MAPT and C9orf72 mutation carriers between Benson Complex Figure Copy and Recall and other neuropsychological test scores. Significant correlations are displayed in bold; * p < 0.05, ** p < 0.01, *** p < 0.001. Abbreviations: BCFT, Benson Complex Figure Test; GRN, progranulin, MAPT, microtubule-associated protein tau; C9orf72, Chromosome 9 open reading frame 72; TMT, Trailmaking Test; FCSRT, Free and Cued Selective Reminding Test, D-KEFS, Delis-Kaplan Executive Function System; WASI, Wechsler Abbreviated Scale of Intelligence.
The relationships between BCFT Copy and Recall and GM volume are displayed in Fig. 2 and Appendix 3. VBM analyses demonstrated different structures to be involved in BCFT Copy depending on the mutation involved: in GRN mutation carriers worse performance correlated with GM atrophy of the left thalamus (p < 0.05 FWE corrected), in MAPT mutation carriers with atrophy of the right cerebellum, and in C9orf72 repeat expansion carriers with atrophy of the left middle frontal gyrus (both p < 0.001 uncorrected). In all mutation carriers, worse BCFT Recall score correlated with atrophy of the temporal lobe, especially the hippocampus (p < 0.05 FWE corrected). In MAPT mutation carriers there was additional involvement of the left temporal pole, whilst in GRN mutation carriers, there was also involvement outside of the temporal lobe, including the anterior cingulate, anterior insula, frontal and parietal lobes in particular (both p < 0.05 FWE corrected).
Fig. 2Neuroimaging correlates of the BCFT Copy and Recall. VBM analyses demonstrated lower scores in BCFT Copy (in green) and BCFT Recall (in blue) to be correlated with lower grey matter volume in GRN mutation carriers (top), MAPT mutation carriers (middle) and C9orf72 repeat expansion carriers (bottom). We set the statistical threshold at p < 0.05 (FWE-corrected) for GRN copy and all recall conditions, and p < 0.001 (uncorrected) for MAPT and C9orf72 copy. Abbreviations: L, left; GRN, progranulin; MAPT, microtubule-associated protein tau; C9orf72, chromosome 9 open reading frame 72. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
In this study of a large cohort of participants from genetic FTD families, we have shown lower scores compared to healthy controls in the BCFT Copy, Recall and Recognition abilities of symptomatic mutation carriers, with different profiles depending on the genetic mutation involved. GRN and C9orf72 – but not MAPT – mutation carriers had lower BCFT Copy performance at a CDR® NACC-FTLD global scores of 2 and 3 whereas all mutation carriers had lower BCFT Recall and Recognition scores than controls at those stages, with the addition of earlier impairment of Recall in MAPT mutation carriers (from CDR® NACC-FTLD global score of 1). Cognitive correlates of the BCFT Copy and Recall included tests for visuoconstruction, verbal memory, and executive function. Furthermore, lower BCFT Copy score was associated with atrophy of fronto-subcortical areas, while lower BCFT Recall score correlated with predominantly (medial) temporal lobe atrophy.
Our results demonstrate visuoconstructive deficits in FTD mutation carriers only from the moderate dementia stage onwards, reflected in lower BCFT Copy performance at CDR® NACC-FTLD global score of 2 and 3. This is in contrast with a previous study, that showed progressive decline in BCFT Copy after the CDR = 0.5 stage in patients with bvFTD [
], which does not include the behaviour and language domains, and therefore is likely less sensitive for early changes in FTD, i.e. patients with original CDR = 0.5 potentially score higher on the CDR® NACC-FTLD [
], which was used in our study. In our patient sample, BCFT Copy performance was not affected in asymptomatic and prodromal mutation carriers (i.e. CDR® NACC-FTLD global scores 0 and 0.5), which is in line with an earlier study that did not find visuoconstructive decline in presymptomatic mutation carriers [
]. Interestingly, our findings also suggest gene-specific patterns in BCFT Copy performance, in that both GRN and C9orf72 mutation carriers, but not MAPT mutation carriers, had lower scores than controls in the moderate to severe dementia stages. Deficits in visuoconstructive functioning have been described in both symptomatic GRN and C9orf72-related FTD previously [
]. A recent study into cognitive composites for familial FTD suggested BCFT Copy as part of the neuropsychological battery best discriminating C9orf72 mutation carriers from controls, whereas BCFT Recall was amongst the tests best differentiating MAPT mutation carriers from controls [
]. The latter, as well as our findings, confirms the presence of early memory decline in particularly MAPT mutations, as has also been found in previous studies [
], we only found significant differences in BCFT Recall (i.e. visual memory) from CDR® NACC-FTLD global score of 1. A potential explanation for this discrepancy could be the difference between performances on verbal versus visual memory tests. Because of the early semantic memory involvement in MAPT-related FTD [
], language-led tests could be more sensitive to change in the presymptomatic stage than visuoconstructive-mediated tests.
The cognitive and neuroimaging correlates of the BCFT Copy and Recall showed both cross-mutation as well as mutation-specific patterns. Irrespective of the underlying mutation, BCFT scores correlated with tests for visuoconstruction, verbal memory, and executive function, with stronger executive function involvement in C9orf72. These findings suggest two important aspects about the BCFT, namely that it – as previous research suggested [
Distinct neuroanatomical substrates and cognitive mechanisms of figure copy performance in Alzheimer’s disease and behavioral variant frontotemporal dementia.
Utility and neuroanatomical correlates of the FTLD-NACC neuropsychology module in the differential diagnosis of behavioural variant frontotemporal dementia and Alzheimer’s disease.
] – assess multiple cognitive functions, allowing the exploration of differential mechanisms of cognitive impairment in familial FTD, and also specifically taps into frontally-mediated skills in C9orf72. This is an interesting finding, as BCFT Copy performance indeed correlated with atrophy of the left middle frontal gyrus in this mutation. Although early atrophy of the thalamus and cerebellum is commonly regarded as the neuroimaging signature of C9orf72 [
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the genetic frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis.
], the associations we found with the thalamus (in GRN) and cerebellar (in MAPT) atrophy confirm that subcortical involvement is also present in the other two FTD genetic groups [
], and leads to lower visuoconstructive scores. In all mutation carriers, worse BCFT Recall score correlated with atrophy of the (medial) temporal lobe. This is not a surprising finding, given the pivotal role of the hippocampus in memory recall, and indeed previous studies into the Rey Complex Figure Test, similar to the BCFT, have related recall performance to medial temporal lobe structures including the hippocampus [
]. In MAPT mutation carriers there was specific involvement of the temporal pole. This finding coincides with the lower BCFT Recall performance relatively early in the disease process of this mutation, confirming MAPT-FTD as a predominantly temporal-predominant disease [
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the genetic frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis.
Key strengths of our study are the large sample sizes of presymptomatic and symptomatic GRN, MAPT and C9orf72 mutation carriers and non-carriers from the same families. Not only is the non-carrier group an ideal control group as they have the same genetic and social background as the mutation carriers, we were also able to generate new normative data and relationships with age, sex and education for the BCFT. Despite large numbers, some groups (especially MAPT mutation carriers) remain relatively small when dividing the sample according to CDR® NACC-FTLD global scores, so that replication in other familial FTD cohorts (e.g., ALLFTD, DINAD) is warranted. We were unable to detect any changes in the CDR® NACC-FTLD global score = 0.5 group, which might have been the result of the heterogeneous nature of this category, likely including mutation carriers without overt dementia symptoms as well as people with primary psychiatric disorders and early-stage PPA, in which it is difficult to detect clinical features [
]. Directions for future research include modifications to traditional scoring methods (i.e., accuracy and placement), such as incorporating process (e.g., direction and order of drawing) and/or digital scoring methods to increase test sensitivity in early disease stages [
] and to allow the measurement of the different cognitive processes that the BCFT relies on (i.e., visuospatial abilities, visual memory, and executive functions such as organization and working memory) but currently cannot be separated.
5. Conclusion
Our study showed lower BCFT Copy, Recall and Recognition performance in symptomatic FTD mutation carriers in comparison to non-carriers. We demonstrated copy deficits in symptomatic GRN and C9orf72 mutation carriers, whereas recall was affected in the early-symptomatic period in MAPT mutation carriers, suggesting differential mechanisms of cognitive impairment depending on the genetic mutation involved, which was corroborated by specific cognitive and neuroimaging correlates. Performance on this brief and easy-to-apply test may aid in differential diagnosis in genetic FTD, but its potential as candidate cognitive biomarker for upcoming clinical trials is most likely limited as impaired performance on the BCFT occurs relatively late in the genetic FTD disease process.
Funding
The Dementia Research Centre is supported by Alzheimer's Research UK, Alzheimer's Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the NIHR UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility, and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd., funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. JDR is supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). This work was also supported by the MRC UK GENFI grant (MR/M023664/1), the Bluefield Project, the JPND GENFI-PROX grant (2019–02248), the Dioraphte Foundation [grant numbers 09–02-00], the Association for Frontotemporal Dementias Research Grant 2009, The Netherlands Organization for Scientific Research (NWO) (grant HCMI 056–13-018), ZonMw Memorabel (Deltaplan Dementie; project numbers 733050103 and 733050813), JPND PreFrontAls Consortium (project number 733051042) and Instituto de Salud Carlos III, Spain, and FEDER funds (grant number 20/00448). JBR is supported by the Wellcome Trust (103838), Medical Research Council (SUAG092 G116768) and the NIHR Cambridge Biomedical Research Centre (BRC-1215 − 20014: the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care). This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198). JMP is supported by a fellowship award from Alzheimer Nederland (WE.15–2019.02). This work was conducted using the MRC Dementias Platform UK (MR/L023784/1 and MR/009076/1). For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
Declaration of Competing Interest
RSV has served in Advisory boards Meetings for Wave Life Sciences, Ionis and Novo Nordisk and received personal fees for participating in educational activities from Janssen, Roche Diagnostics, and Neuraxpharma and funding to her institution for research projects from Biogen and Sage Pharmaceuticals. The other authors declare that they have no competing interests.
Acknowledgements
We thank the research participants and their families for their contribution to GENFI. Some authors of this manuscript are members of the European Reference Network for Rare Neurological Diseases (project ID: 739510).
Appendix A. GENFI consortium authors
Arabella Bouzigues MSc,1 Martin N. Rossor MD FRCP,1 Nick C. Fox MD FRCP,1 Jason D. Warren PhD FRACP,1 Imogen J. Swift MSc,1 Rachelle Shafei MRCP,1 Carolin Heller BSc1, Emily Todd MSc,1 Ione Woollacott PhD,1 Henrik Zetterberg,1 Annabel Nelson BSc1, Rita Guerreiro PhD,2 Jose Bras PhD,2 David L. Thomas PhD,3 Simon Mead PhD,4 Lieke Meeter MD,5 Jessica Panman MSc,5 Rick van Minkelen PhD,6 Myriam Barandiaran PhD,7, 8 Begoña Indakoetxea MD,7, 8 Alazne Gabilondo MD,8 Mikel Tainta MD,8 Ana Gorostidi PhD,8 Miren Zulaica BSc8, Alina Díez MSc,8 Jorge Villanua MD PhD,9 Sergi Borrego-Ecija MD,10 Jaume Olives MSc,10 Albert Lladó PhD,10 Mircea Balasa PhD,10 Anna Antonell PhD,10 Nuria Bargallo PhD,11 Enrico Premi MD,12 Stefano Gazzina MD,13 Roberto Gasparotti MD,14 Silvana Archetti MBiolSci,15 Sandra Black MD,16 Sara Mitchell MD,16 Ekaterina Rogaeva PhD,17 Morris Freedman MD,18 Ron Keren MD,19 David Tang-Wai MD,20 Hakan Thonberg MD,21 Linn Öijerstedt MD,21, 22 Christin Andersson PhD,23 Vesna Jelic MD,24 Andrea Arighi MD,25, 26 Chiara Fenoglio PhD,25, 26 Elio Scarpini MD,25, 26 Giorgio Fumagalli MD,25, 26 Thomas Cope MRCP,27 Carolyn Timberlake BSc27, Timothy Rittman MRCP,27 Christen Shoesmith MD,28 Robart Bartha PhD,29, 30 Rosa Rademakers PhD,31 Carlo Wilke MD,32, 33 Hans-Otto Karnarth MD,34 Benjamin Bender MD,35 Rose Bruffaerts MD PhD,36 Philip Vandamme MD PhD,37 Mathieu Vandenbulcke MD PhD,38, 39 Catarina B. Ferreira MSc,40 Gabriel Miltenberger PhD,41 Carolina Maruta MPsych PhD,42 Ana Verdelho MD PhD,43 Sónia Afonso BSc44, Ricardo Taipa MD PhD,45 Paola Caroppo MD PhD,46 Giuseppe Di Fede MD PhD,46 Giorgio Giaccone MD,46 Sara Prioni PsyD,46 Veronica Redaelli MD,46 Giacomina Rossi MSc,46 Pietro Tiraboschi MD,46 Diana Duro NPsych,47 Maria Rosario Almeida PhD,47 Miguel Castelo-Branco MD PhD,47 Maria João Leitão BSc48, Miguel Tabuas-Pereira MD49, Beatriz Santiago MD49, Serge Gauthier MD50, Pedro Rosa-Neto MD PhD51, Michele Veldsman PhD52, Paul Thompson PhD53, Tobias Langheinrich MD53, Catharina Prix MD54, Tobias Hoegen MD54, Elisabeth Wlasich Mag. rer. Nat.54, Sandra Loosli MD54, Sonja Schonecker MD54, Sarah Anderl-Straub Dr.hum.biol Dipl.Psych55, Jolina Lombardi55, Nuria Bargalló MD PhD56, Alberto Benussi MD57, Valentina Cantoni57, Maxime Bertoux PhD58,59, Anne Bertrand MD PhD60, Alexis Brice MD PhD60, Agnès Camuzat60, Olivier Colliot PhD60, Sabrina Sayah60, Aurélie Funkiewiez60,61, Daisy Rinaldi60,61, Gemma Lombardi61, Benedetta Nacmias61, Dario Saracino60,61,62, Valentina Bessi63, Camilla Ferrari63, Marta Cañada64, Vincent Deramecourt65, Gregory Kuchcinski65, Thibaud Lebouvier65, Cristina Polito67, Adeline Rollin68.
1Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK2;Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, MI 49503, USA3;Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK4;MRC Prion Unit, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK5;Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands6;Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands7;Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain8;Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain9;OSATEK, University of Donostia, San Sebastian, Gipuzkoa, Spain10;Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain11;Imaging Diagnostic Center, Hospital Clínic, Barcelona, Spain12;Stroke Unit, ASST Brescia Hospital, Brescia, Italy13;Neurology, ASST Brescia Hospital, Brescia, Italy14;Neuroradiology Unit, University of Brescia, Brescia, Italy15;Biotechnology Laboratory, Department of Diagnostics, ASST Brescia Hospital, Brescia, Italy16;Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada17;Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada18;Baycrest Health Sciences, Rotman Research Institute, University of Toronto, Toronto, Canada19;The University Health Network, Toronto Rehabilitation Institute, Toronto, Canada20;The University Health Network, Krembil Research Institute, Toronto, Canada21;Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet, Solna, Sweden22;Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden23;Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden24;Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden25;Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy26;University of Milan, Centro Dino Ferrari, Milan, Italy27;Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK28;Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada29;Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada30;Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada31;Department of Neurosciences, Mayo Clinic, Jacksonville, Florida, USA32;Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany33;Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany34;Division of Neuropsychology, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany35;Department of Diagnostic and Interventional Neuroradiology, University of Tübingen, Tübingen, Germany36;Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium37;Neurology Service, University Hospitals Leuven, Belgium; Laboratory for Neurobiology, VIB-KU Leuven Centre for Brain Research, Leuven, Belgium38;Geriatric Psychiatry Service, University Hospitals Leuven, Belgium39;Neuropsychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium40;Laboratory of Neurosciences, Institute of Molecular Medicine, Faculty of Medicine, University of Lisbon, Lisbon, Portugal41;Faculty of Medicine, University of Lisbon, Lisbon, Portugal42;Laboratory of Language Research, Centro de Estudos Egas Moniz, Faculty of Medicine, University of Lisbon, Lisbon, Portugal43;Department of Neurosciences and Mental Health, Centro Hospitalar Lisboa Norte - Hospital de Santa Maria & Faculty of Medicine, University of Lisbon, Lisbon, Portugal44;Instituto Ciencias Nucleares Aplicadas a Saude, Universidade de Coimbra, Coimbra, Portugal45;Neuropathology Unit and Department of Neurology, Centro Hospitalar do Porto - Hospital de Santo António, Oporto, Portugal46;Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy47;Faculty of Medicine, University of Coimbra, Coimbra, Portugal; 48Centre of Neurosciences and Cell Biology, Universidade de Coimbra, Coimbra, Portugal; 49Neurology Department, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal; 50Alzheimer Disease Research Unit, McGill Centre for Studies in Aging, Department of Neurology & Neurosurgery, McGill University, Montreal, Québec, Canada; 51Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, Québec, Canada; 52Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK; 53Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK; 54Neurologische Klinik, Ludwig-Maximilians-Universität München, Munich, Germany; 55Department of Neurology, University of Ulm, Ulm, Germany; 56Imaging Diagnostic Center, Hospital Clínic, Barcelona, Spa; 57Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Italy; 58Inserm 1172, Lille, France; 59CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France; 60Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France; 61Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France; 62Inria, Aramis project-team, F-75013, Paris, France 63Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; 64CITA Alzheimer, San Sebastian, Gipuzkoa, Spain; 65University of Lille, France; 66School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; 67Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, Nuclear Medicine Unit, University of Florence, Florence, Italy; 68CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, France.
Appendix B. Cumulative frequencies, percentile scores, and performance across age, sex and education for the Benson Complex Figure Test (BCFT) in the reference (non-carrier) group (n = 290)
Tabled
1Appendix 2.1 – Cumulative frequencies for the BCFT Copy, Recall and Recognition in the reference group.
Presymptomatic cognitive and neuroanatomical changes in genetic frontotemporal dementia in the genetic frontotemporal dementia Initiative (GENFI) study: a cross-sectional analysis.
Distinct neuroanatomical substrates and cognitive mechanisms of figure copy performance in Alzheimer’s disease and behavioral variant frontotemporal dementia.
Utility and neuroanatomical correlates of the FTLD-NACC neuropsychology module in the differential diagnosis of behavioural variant frontotemporal dementia and Alzheimer’s disease.
World Federation of Neurology Research Group on motor neuron diseases. El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis.
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