Literature DB >> 29627938

Longitudinal cognitive biomarkers predicting symptom onset in presymptomatic frontotemporal dementia.

Lize C Jiskoot1,2, Jessica L Panman1,2, Lauren van Asseldonk1, Sanne Franzen1, Lieke H H Meeter1, Laura Donker Kaat1,3, Emma L van der Ende1, Elise G P Dopper1, Reinier Timman4, Rick van Minkelen5, John C van Swieten1,6, Esther van den Berg1, Janne M Papma7.   

Abstract

INTRODUCTION: We performed 4-year follow-up neuropsychological assessment to investigate cognitive decline and the prognostic abilities from presymptomatic to symptomatic familial frontotemporal dementia (FTD).
METHODS: Presymptomatic MAPT (n = 15) and GRN mutation carriers (n = 31), and healthy controls (n = 39) underwent neuropsychological assessment every 2 years. Eight mutation carriers (5 MAPT, 3 GRN) became symptomatic. We investigated cognitive decline with multilevel regression modeling; the prognostic performance was assessed with ROC analyses and stepwise logistic regression.
RESULTS: MAPT converters declined on language, attention, executive function, social cognition, and memory, and GRN converters declined on attention and executive function (p < 0.05). Cognitive decline in ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) were predictive for conversion to non-fluent variant PPA, and decline on categorical fluency (p = 0.025) for an underlying MAPT mutation. DISCUSSION: Using longitudinal neuropsychological assessment, we detected a mutation-specific pattern of cognitive decline, potentially suggesting prognostic value of neuropsychological trajectories in conversion to symptomatic FTD.

Entities:  

Keywords:  Biomarkers; Cognition; Familial; Frontotemporal dementia; Longitudinal; Neuropsychological assessment; Presymptomatic

Mesh:

Substances:

Year:  2018        PMID: 29627938      PMCID: PMC5990575          DOI: 10.1007/s00415-018-8850-7

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   4.849


Introduction

Frontotemporal dementia (FTD) is a presenile neurodegenerative disorder, leading to a heterogeneous clinical presentation, involving behavioural (behavioural variant FTD; bvFTD) and/or language deterioration (primary progressive aphasia; PPA) [1]. FTD has an autosomal dominant pattern of inheritance in 30 percent of cases, with mutations in the progranulin (GRN) and microtubule-associated protein tau (MAPT) genes as its two main causes [2]. The cognitive profile of FTD varies depending on the clinical phenotype and the underlying genotype. Patients with bvFTD are characterized by deficits in executive function, social cognition and language, whereas memory and visuoconstruction are initially spared [3-5]. Non-fluent variant PPA (nfvPPA) patients show agrammatism and speech sound distortions, while semantic variant PPA (svPPA) patients experience deficits in confrontation naming and word comprehension [6]. GRN mutations often lead to a clinical diagnosis of bvFTD, nfvPPA or parkinsonism. In MAPT mutations, bvFTD is the main phenotype, and semantic and memory impairments can be prominent neuropsychological symptoms [7]. Research in familial FTD has demonstrated the presence of a presymptomatic stage in which subtle cognitive changes have been identified [8-12]. More specifically, cognitive decline can start as early as 8 years prior to estimated symptom onset and shows mutation-specific patterns, with GRN mutation carriers declining in memory, and MAPT mutation carriers declining in language, social cognition and memory [8, 10]. This suggests that cognitive measures could function as disease-tracking biomarkers in the presymptomatic stage. However, it is currently unknown what the long-term cognitive profiles of presymptomatic FTD mutations are, whether neuropsychological assessment can be used to track disease progression to the symptomatic stage, and what the prognostic value is of cognitive trajectories in the presymptomatic and early symptomatic stage of FTD. In this study, we investigated longitudinal cognitive decline on neuropsychological assessment in presymptomatic mutation carriers (MAPT or GRN) and controls from the same families within our longitudinal presymptomatic Dutch familial FTD Risk Cohort (FTD-RisC). Second, we assessed the difference in cognitive course between converters’ genotypes (i.e. MAPT vs. GRN) and phenotypes (i.e. bvFTD vs. nfvPPA) versus non-converters. Lastly, we investigated the prognostic value of neuropsychological trajectories in predicting symptom onset within 2–4 years.

Methods

Participants

In FTD-RisC, we follow healthy 50% at-risk family members from genetic FTD families on a 2-year basis. In the current study, we included 87 participants from MAPT or GRN families with study entries between December 2009 and January 2013 [8, 9, 13]. The follow-up period was 4 years, in which we acquired neuropsychological assessments at study entry, follow-up after 2 years and follow-up after 4 years. DNA genotyping (see “Procedure”) assigned participants either to the presymptomatic mutation carrier (n = 46; 31 GRN, 15 MAPT), or control group (n = 39; 29 GRN, 10 MAPT family members). We excluded two controls as they had cognitive disorders (≥ 2 SD below mean) on multiple domains, ultimately including 85 participants (46 mutation carriers, 37 controls; Fig. 1).
Fig. 1

Participant in- and exclusion and sample size per time point. Two controls were excluded as they had multiple cognitive disorders (≤ 2 SD below reference mean) on neuropsychological testing. Eight mutation carriers converted to clinical FTD within the study window. Their data were restructured, so that there were three time points: 4 years before symptom onset, 2 years before symptom onset and symptom onset. Four years before symptom onset, only data of six converters were available, as two mutation carriers converted between baseline and first follow-up. The data of converters were compared to, respectively, baseline, follow-up after 2 years and follow-up after 4 years in non-converters and healthy controls

Participant in- and exclusion and sample size per time point. Two controls were excluded as they had multiple cognitive disorders (≤ 2 SD below reference mean) on neuropsychological testing. Eight mutation carriers converted to clinical FTD within the study window. Their data were restructured, so that there were three time points: 4 years before symptom onset, 2 years before symptom onset and symptom onset. Four years before symptom onset, only data of six converters were available, as two mutation carriers converted between baseline and first follow-up. The data of converters were compared to, respectively, baseline, follow-up after 2 years and follow-up after 4 years in non-converters and healthy controls

Standard protocol approvals, registrations, and patient consents

Clinical investigators were blind for participants’ genetic status if they had not undergone predictive testing. In case of conversion to clinical FTD, we offered the patient and family members genetic counselling and unblinding of genetic status, to confirm the presence of the pathogenic mutation. At study entry, all participants gave written informed consent. The study was approved by the Medical and Ethical Review Committee of the Erasmus Medical Center.

Procedure

Every 2 years, participants underwent a standardized assessment consisting of a neuropsychological test battery, neurological examination, and MR imaging of the brain. DNA sequencing was performed at study entry. All participants were asymptomatic according to established diagnostic criteria for bvFTD [3] or PPA [6] at baseline. Knowledgeable informants were asked about cognitive and/or behavioural deterioration at each study visit by means of a structured interview and a well-validated questionnaire (Neuropsychiatric Inventory; NPI) [14].

Converters

Eight mutation carriers became symptomatic within the study time window (“converters”). Symptom onset was determined by means of the above mentioned assessment (anamnesis, MR imaging of the brain, neuropsychological assessment, heteroanamnestic information and unblinding of genetic status). Conversion was determined in a multidisciplinary consensus meeting of the Erasmus MC FTD Expertise Centre, involving neurologists (LDK, JCvsS), neuropsychologists (LCJ, JLP, SF, EvdB, JMP), medical doctors (LHM, ELvdE), as well as neuroradiologists, geriatricians, a clinical geneticist (RvM), and a care consultant. Six converters (5 MAPT, 1 GRN) presented with progressive behaviour deterioration, functional decline, and frontal and/or temporal lobe atrophy on MRI, fulfilling the international diagnostic consensus criteria of Rascovsky et al. [3] for bvFTD with definite FTLD pathology. Two converters (both GRN) presented with isolated language difficulties and no impairments in daily living activities, thereby fulfilling the diagnostic criteria for PPA of Gorno-Tempini et al. [6]. Both developed nfvPPA, as they showed a non-fluent, halting speech, with sound errors and agrammatism. See Supplementary Table 1 for demographic, clinical and neuropsychological data of the converters. We defined mutation carriers remaining without FTD symptoms as non-converters (n = 38; 28 GRN, 10 MAPT).

Neuropsychological assessment

We screened global cognitive functioning by means of the Mini-Mental State Examination [15] (MMSE) and frontal assessment battery [16] (FAB). Experienced neuropsychologists (LCJ, JLP, SF) administered neuropsychological tests within six cognitive domains: language, attention and mental processing speed, executive functioning, social cognition, memory, and visuoconstruction. We rated language with the 60-item Boston Naming Test (BNT) [17], verbal Semantic Association Test (SAT) [18], ScreeLing phonology [19], and categorical fluency [20]. We assessed attention and mental processing speed by means of Trail making Test (TMT)-A [21], Stroop Color-Word Test I and II [22], Wechsler Adult Intelligence Scale III (WAIS-III) Digit Span forwards [23], and Letter Digit Substitution Test (LDST) [24]. Executive functioning was evaluated using TMT-B [21], Stroop Color-Word Test III [22], WAIS-III Digit Span backwards [23], modified Wisconsin Card Sorting Test (WCST) concepts [25], letter fluency [20], and WAIS-III Similarities [23]. Happé cartoons [26] and Ekman Faces [27] measured social cognition. We assessed memory using the Dutch Rey Auditory Verbal Learning Test (RAVLT) [28] and Visual Association Test (VAT) [29]. We evaluated visuoconstruction by means of clock drawing [30] and WAIS-III Block Design [23]. Alternate forms were used at follow-up visits, when applicable (letter fluency, RAVLT, VAT). Depressive symptoms were rated with the Beck’s Depression Inventory (BDI) [31].

Study design

In converters, we restructured the three original time points within our study window (i.e. baseline, follow-up after 2 years, follow-up after 4 years) into the following three new time points (Fig. 1): 4 years before symptom onset: we used the data of the study visit 4 years before diagnosis. Analyses could were performed in six converters, as two (1 GRN, 1 MAPT—2 bvFTD) developed symptoms between baseline and first follow-up (i.e. at 2 years follow-up), and therefore no data 4 years prior to symptom onset were available. 2 years before symptom onset: we used the data of the study visit 2 years before diagnosis. Analyses included all eight converters. After symptom onset: we used the data of the diagnosis visit. Analyses included all eight converters. In non-converters and controls, we used the original time points: baseline (data were compared to “4 years before symptom onset” data of converters), follow-up after 2 years (data were compared to “2 years before symptom onset data of converters) and follow-up after 4 years (data were compared to “after symptom onset data of converters).

Statistical analysis

Statistical analyses were performed using SPSS Statistics 21.0 (IBM Corp., Armonk, NY) and GraphPad Prism 7 (La Jolla, California, USA), with the significance level at p < 0.05 (two-tailed) across all comparisons. We compared demographic data between MAPT mutation carriers, GRN mutation carriers and controls, and between converters, non-converters and controls by means of one-way ANOVAs. We performed Pearson Χ2 tests to investigate differences in sex. Longitudinal comparisons of clinical data were performed with repeated measures ANOVAs. We standardized all raw neuropsychological test scores by converting them into z-scores (i.e. individual test score minus the baseline mean of the controls, divided by the baseline SD of the controls) per time point, after which we calculated composite z-scores for the respective six cognitive domains by averaging the z-scores of the individual tests per domain. For the longitudinal comparisons we used multilevel linear regression modeling. This analysis corrects for bias when data absence is dependent on characteristics present in the model, and can therefore efficiently handle missing and unbalanced time points. There were two levels in the models: the participants constituted the upper level; their repeated measures the lower level. We ran two analyses to assess cognitive decline per mutation (1) and clinical status (2): We entered mutation status (MAPT mutation carrier, GRN mutation carrier or control), time (4 years before symptom onset, 2 years before symptom onset, and after symptom onset), and first-order interactions, with age, gender and educational level as covariates. We reran the analyses excluding the converters to exclude converters driving the cognitive decline in the mutation carrier groups; We split the converter group according to genotype (MAPT or GRN) and phenotype (bvFTD or nfvPPA) to investigate specific profiles of cognitive decline over time. We then entered clinical status (converter, non-converter or control), time, and first-order interactions, with age, gender and educational level as covariates. Third, to investigate the prognostic abilities of cognitive decline in discriminating between converters and non-converters, we determined the area under the curve (AUC) by receiver operating characteristic (ROC) analyses on the neuropsychological trajectories between visits. For this, we calculated deltas between test scores; one between 4 and 2 years before symptom onset and one between 2 years before symptom onset and symptom onset. Optimal cut-off levels were given by the highest Youden’s index [32]. Again, we split the converter group according to genotype (MAPT or GRN) and phenotype (bvFTD or nfvPPA). Next, we performed logistic regression analyses, taking group (converter vs. non-converter) as the dependent variable and the deltas (tests with significant diagnostic performance in abovementioned ROC analyses) as the independent variables. The models were selected with a forward stepwise method according to the likelihood ratio test and applying the standard p values for variable inclusion (0.05) and exclusion (0.10), with age, sex and education as covariates. Goodness of fit was evaluated with the HL Χ2 test. Nagelkerke R2 is reported as measure of effect size. We checked predictor variables for multicollinearity. All models were corrected for multiple comparisons (Bonferroni).

Results

Demographics

MAPT mutation carriers were significantly younger than GRN mutation carriers (p = 0.012; Table 1). The mean familial symptom onset age was lower in MAPT than in GRN mutation carriers and controls (both p < 0.001). There were no significant differences between groups regarding estimated years to symptom onset (p > 0.05). Longitudinal analyses demonstrated that MAPT mutation carriers declined significantly more than GRN mutation carriers and controls with regards to the MMSE (p = 0.014), and also developed more depressive symptoms (p = 0.028). FAB and NPI scores did not significantly change over time (p > 0.05). Converters, non-converters and controls did not differ regarding demographic variables, apart from a younger family onset in MAPT converters than GRN converters (p = 0.043) and non-converters (p = 0.001; Table 1). Both MAPT and GRN converters declined significantly with respect to MMSE score (p < 0.001) and they developed more neuropsychiatric symptoms in the form of higher BDI (p = 0.001) and NPI (p = 0.021) scores in comparison to non-converters and controls. FAB scores did not significantly change over time (p > 0.05).
Table 1

Demographics and clinical data

DemographicsHC (n = 39)MAPT carriers (n = 15)GRN carriers (n = 31)p value*MAPT converters (n = 5)GRN converters (n = 3)Non-converters (n = 38)p value**
Age at study entry, years49.1 ± 12.241.9 ± 10.052.1 ± 8.2 0.012 a 45.3 ± 8.554.9 ± 9.048.8 ± 10.30.704
Sex, female (%)20 (56%)7 (47%)20 (65%)0.5061 (20%)3 (100%)23 (60.5%)0.154
Education (Verhage)f5.2 ± 1.05.1 ± 1.65.7 ± 0.90.1026.0 ± 0.75.7 ± 0.65.4 ± 1.30.409
Onset age family, years59.0 ± 5.851.3 ± 6.761.0 ± 2.4< 0.001a,b48.0 ± 4.759.7 ± 0.058.8 ± 6.1 0.002 c,d
Estimated years to onset, years− 10.2 ± 11.2− 7.7 ± 9.6− 9.4 ± 7.90.690− 2.7 ± 4.0− 4.8 ± 9.0− 10.0 ± 8.50.335

Values indicate: mean ± standard deviation. Significant comparisons are displayed in bold

GRN progranulin, HC healthy control, MMSE Mini-Mental State Examination, FAB frontal assessment battery, BDI Beck’s depression inventory, NPI neuropsychiatric inventory

*p value represents result of overall ANOVA between MAPT mutation carriers, GRN mutation carriers and healthy controls

**p value represents result of overall ANOVA between MAPT converters, GRN converters, non-converters and HC

aSignificant post hoc test between MAPT and GRN mutation carriers

bSignificant post hoc test between MAPT mutation carriers and healthy controls

cSignificant post hoc test between converters and non-converters

dSignificant post hoc test between converters and healthy controls

eOnly data of MAPT converters available, therefore the p value represents the comparison between MAPT converters, non-converters and HC

fDutch educational system categorized into levels from 1 = less than 6 years of primary education to 7 = academic schooling (Verhage, 1964)

gData only available on follow-up visits

Demographics and clinical data Values indicate: mean ± standard deviation. Significant comparisons are displayed in bold GRN progranulin, HC healthy control, MMSE Mini-Mental State Examination, FAB frontal assessment battery, BDI Beck’s depression inventory, NPI neuropsychiatric inventory *p value represents result of overall ANOVA between MAPT mutation carriers, GRN mutation carriers and healthy controls **p value represents result of overall ANOVA between MAPT converters, GRN converters, non-converters and HC aSignificant post hoc test between MAPT and GRN mutation carriers bSignificant post hoc test between MAPT mutation carriers and healthy controls cSignificant post hoc test between converters and non-converters dSignificant post hoc test between converters and healthy controls eOnly data of MAPT converters available, therefore the p value represents the comparison between MAPT converters, non-converters and HC fDutch educational system categorized into levels from 1 = less than 6 years of primary education to 7 = academic schooling (Verhage, 1964) gData only available on follow-up visits

Longitudinal cognitive decline in MAPT and GRN mutation carriers

The whole group of MAPT mutation carriers declined significantly within the domains language, social cognition and memory compared with controls (Table 2; Fig. 1). This was reflected in lower scores on the BNT and categorical fluency, Happé cartoons, VAT and RAVLT delayed recall (Table 2). In the whole group of GRN mutation carriers, no longitudinal decline was found in comparison to controls. In comparison to GRN mutation carriers, MAPT mutation carriers declined significantly on the domains language (β = − 0.015, p < 0.001) and memory (β = − 0.016, p = 0.008), reflected in lower BNT (β = − 0.085, p = 0.01), SAT (β = − 0.027, p = 0.015), category fluency (β = − 0.107, p = 0.002), and RAVLT delayed recall (β = − 0.047, p = 0.001) scores. There were no cognitive domains or tests on which GRN mutation carriers declined more than MAPT mutation carriers (Table 2). By excluding the five MAPT converters from the analyses, none of the domain scores in MAPT mutation carriers continued to show significant decline over time in comparison to controls. Regarding individual tests, however, the decline on the RAVLT delayed recall remained significant (β = − 0.032, p = 0.023). The results did not change by excluding the three GRN converters from the analyses. In comparison to GRN, MAPT mutation carriers still declined more on language (β = − 0.010, p = 0.004), reflected in lower ScreeLing phonology (β = − 0.008, p = 0.024) and category fluency (β = − 0.007, p = 0.041). There was no cognitive decline in controls—but significant improvement was found on social cognition (Happé non-ToM and Ekman Faces) and memory (RAVLT immediate and delayed recall) (Table 2). The raw neuropsychological test scores per time point can be found in Supplementary Table 2.
Table 2

Cognitive trajectories in mutation carriers (converters, non-converters) and healthy controls

Domain testHealthy controls (n = 39)MAPT mutation carriers (n = 15)GRN mutation carriers (n = 31)
Baseline β p Baseline β p Baseline β p
Language0.0 ± 0.60.0000.9310.2 ± 0.6− 0.010 0.002 0.1 ± 0.70.0040.121
BNT53.4 ± 4.50.0260.10552.6 ± 5.3− 0.080 0.005 55.1 ± 3.70.0060.786
SAT27.8 ± 1.1− 0.0030.60427.9 ± 1.5− 0.0080.60427.5 ± 2.00.019 0.033 a
ScreeLing phonology23.5 ± 0.80.0010.73323.9 ± 0.3− 0.0050.19023.8 ± 0.5− 0.0010.863
Categorical fluency23.9 ± 4.90.0260.14126.5 ± 6.6− 0.087 0.006 23.4 ± 5.70.0210.424
Attention and processing speed0.0 ± 0.8− 0.0010.0840.3 ± 0.6− 0.0030.0960.1 ± 0.9− 0.0030.075
TMT part Ac31.8 ± 15.0− 0.0220.41626.1 ± 9.70.0650.19231.4 ± 12.20.0600.145
Stroop card Ic47.1 ± 8.00.039 0.011 43.2 ± 8.8− 0.0170.52945.0 ± 8.4− 0.0010.951
Stroop card IIc58.5 ± 10.60.0120.53954.9 ± 8.50.0270.47060.2 ± 13.20.0010.969
Digit Span forwards8.7 ± 1.90.0010.8719.0 ± 2.6− 0.0100.2949.4 ± 2.4− 0.0160.055
LDST34.5 ± 6.80.0010.89434.2 ± 4.7− 0.6360.69933.2 ± 7.40.0050.798
Executive function0.0 ± 0.70.0010.5050.3 ± 0.6− 0.0050.0650.2 ± 0.8− 0.0040.052
TMT part Bc67.8 ± 29.30.0520.49461.0 ± 28.50.0790.57072.2 ± 42.7− 0.0990.390
Stroop card IIIc93.7 ± 22.6− 0.087 0.021 83.8 ± 14.70.141 0.042 96.6 ± 26.20.0130.815
Digit span backwards6.1 ± 2.00.0080.1946.6 ± 1.80.0020.8776.6 ± 2.1− 0.0110.222
WCST concepts5.5 ± 0.90.0020.5925.6 ± 1.1− 0.0090.2965.80 ± 0.6− 0.0100.144
Letter fluency32.1 ± 9.90.134< 0.001b36.1 ± 14.3− 0.108 0.049 38.9 ± 12.0− 0.0620.173
Similarities24.8 ± 4.70.0060.64525.5 ± 4.7− 0.0340.12226.2 ± 5.0− 0.0110.556
Social cognition0.0 ± 0.80.0000.8780.2 ± 0.7− 0.009 0.007 0.3 ± 0.7− 0.0030.332
Happé ToM11.8 ± 3.40.0130.17212.6 ± 3.7− 0.044 0.011 12.9 ± 2.9− 0.0050.707
Happé non-Tom11.7 ± 2.90.020 0.013 12.4 ± 2.8− 0.036 0.017 13.0 ± 2.6− 0.0120.331
Ekman faces45.7 ± 6.40.038 0.009 47.0 ± 5.5− 0.0280.29347.10 ± 5.5− 0.0130.548
Memory0.0 ± 0.70.0000.8480.1 ± 1.3− 0.017< 0.001b0.1 ± 0.9− 0.0010.745
VAT11.8 ± 0.60.0010.74011.4 ± 1.6− 0.012 0.019 11.5 ± 0.90.0000.926
RAVLT imm. recall42.6 ± 9.80.157< 0.001b47.5 ± 9.7− 0.0760.09046.3 ± 10.6− 0.0150.686
RAVLT del. recall8.4 ± 3.20.050< 0.001b9.7 ± 3.9− 0.048< 0.001a,b9.4 ± 3.3− 0.0000.983
RAVLT recognition28.6 ± 2.10.0140.12729.0 ± 2.0− 0.0220.17629.2 ± 1.2− 0.0090.505
Visuoconstruction0.0 ± 0.8− 0.0010.656− 0.2 ± 0.7− 0.0050.2660.0 ± 1.00.0000.963
Block design36.5 ± 14.00.0340.30535.5 ± 20.8− 0.0060.91739.3 ± 18.5− 1.1640.246
Clock drawing12.6 ± 1.40.0030.45312.2 ± 1.3− 0.0090.28412.4 ± 1.80.0050.475

Values indicate: mean ± standard deviation; β represents estimate of change over time. Composite domain scores are z-scores, individual test scores are raw scores. Composite domain scores are expressed as z-scores, the individual test scores are raw scores. p values represent comparisons to healthy controls. Significant comparisons are displayed in bold

MAPT microtubule-associated protein tau, GRN progranulin, BNT Boston Naming Test, SAT semantic association test, TMT Trail making Test, WAIS Wechsler Adult Intelligence Scale, LDST letter digit substitution test, WCST Wisconsin card sorting test, ToM theory of mind, VAT visual association test, RAVLT Rey Auditory Verbal Learning Test, imm immediate, del delayed

aRemained significant after excluding converters from the analyses

bSurvived Bonferroni correction for multiple comparisons

cHigher scores and β weights indicate worse performance

Cognitive trajectories in mutation carriers (converters, non-converters) and healthy controls Values indicate: mean ± standard deviation; β represents estimate of change over time. Composite domain scores are z-scores, individual test scores are raw scores. Composite domain scores are expressed as z-scores, the individual test scores are raw scores. p values represent comparisons to healthy controls. Significant comparisons are displayed in bold MAPT microtubule-associated protein tau, GRN progranulin, BNT Boston Naming Test, SAT semantic association test, TMT Trail making Test, WAIS Wechsler Adult Intelligence Scale, LDST letter digit substitution test, WCST Wisconsin card sorting test, ToM theory of mind, VAT visual association test, RAVLT Rey Auditory Verbal Learning Test, imm immediate, del delayed aRemained significant after excluding converters from the analyses bSurvived Bonferroni correction for multiple comparisons cHigher scores and β weights indicate worse performance

Longitudinal cognitive decline in converters and non-converters

Converters with a MAPT mutation deteriorated significantly on all domains but visuoconstruction (Fig. 2a–d, f; Table 3). Within these domains, performances declined on BNT (p < 0.001), LDST (p = 0.035), Stroop I, II and III (I: p = 0.017; II: p < 0.001; III: p = 0.021), categorical fluency (p = 0.001), WAIS similarities (p < 0.001), Happé ToM (p = 0.011), and RAVLT immediate (p = 0.004) and delayed recall (p = 0.030). Converters with a GRN mutation deteriorated significantly on attention and mental processing speed, and executive function (Fig. 2b, c; Table 3). Within these domains, performances on TMT-B (p < 0.001), Stroop III (p < 0.001), WCST (p = 0.005), letter fluency (p = 0.012) and WAIS similarities (p < 0.001) deteriorated significantly over time. Converters with bvFTD had a similar pattern of cognitive decline as MAPT converters, with lower scores on social cognition, memory, language, attention and executive function (Table 3). Comparably, converters with nfvPPA had a similar pattern of cognitive decline as GRN converters, with lower scores on attention and executive function (Table 3). There were no differences in decline between converters with bvFTD and nfvPPA (Table 3). The raw neuropsychological test scores per time point can be found in Supplementary Table 3.
Fig. 2

Multilevel linear regression model displaying longitudinal decline (4 years, 2 years and after symptom onset) in composite domain z-score in the total group of converters (light green), MAPT converters (light blue dotted line), GRN converters (dark blue dotted line), non-converters (dark green) and healthy controls (black). Models are displayed per cognitive domain: a social cognition, b attention and mental processing speed, c executive functioning, d memory, e visuoconstruction, and f language. NB: the healthy controls have a mean z-score of zero by default as the z-scores of mutation carriers were based on that (raw score minus mean score of healthy controls, divided by the standard deviation of healthy controls). MAPT microtubule-associated protein tau, GRN progranulin

Table 3

Cognitive trajectories in MAPT, GRN, bvFTD and nfvPPA converters, and non-converters

Domain testMAPT converters (n = 5)GRN converters (n = 3)bvFTD converters (n = 6)nfvPPA converters (n = 2)Non-converters (= 38)
Baseline β p Baseline β p Baseline β p Baseline β p Baseline β p
Language0.1 ± 0.7− 0.028< 0.001a0.6 ± 0.2− 0.0070.2990.1 ± 0.7− 0.025< 0.001a0.6 ± 0.2− 0.0140.0610.1 ± 0.60.0020.408
BNT54.3 ± 6.9− 0.239< 0.001a57.5 ± 2.1− 0.0190.60454.3 ± 6.9− 0.224< 0.001a57.5 ± 2.1− 0.0330.39654.2 ± 4.2− 0.0010.960
SAT27.0 ± 1.4− 0.040 0.034 28.0 ± 1.40.0060.80527.0 ± 1.4− 0.0360.05228.0 ± 1.40.0000.99327.7 ± 2.00.0130.127
ScreeLing phonology24.0 ± 0.00.0020.61724.0 ± 0.0− 0.0110.11424.0 ± 0.00.0040.35824.0 ± 0.0− 0.017 0.018 23.8 ± 0.4− 0.0020.551
Categorical fluency25.8 ± 4.6− 0.250< 0.001a28.0 ± 2.8− 0.149 0.022 25.8 ± 4.6− 0.237< 0.001a28.0 ± 2.8− 0.170 0.015 24.0 ± 6.30.0140.546
Attention and mental processing speed0.3 ± 0.6− 0.010 0.006 0.2 ± 0.3− 0.013 0.005 0.3 ± 0.6− 0.010 0.004 0.2 ± 0.3− 0.013 0.006 0.1 ± 0.8− 0.0010.321
TMT part Ab20.0 ± 6.30.0670.44825.0 ± 8.50.0730.53920.0 ± 6.30.0650.44925.0 ± 8.50.0900.48331.1 ± 11.80.0510.181
Stroop card Ib44.0 ± 5.20.101 0.030 46.5 ± 6.40.0580.34944.0 ± 5.20.106 0.020 46.5 ± 6.40.0440.50344.4 ± 8.9− 0.0200.345
Stroop card IIb58.5 ± 7.60.331< 0.001a56.5 ± 0.70.186 0.006 57.5 ± 7.60.319< 0.001a56.5 ± 0.70.194 0.008 58.8 ± 12.9− 0.0320.217
Digit Span forwards9.5 ± 1.70.0100.6099.0 ± 0.0− 0.0380.1469.5 ± 1.70.0100.6019.0 ± 0.0− 0.0430.1199.3 ± 2.6− 0.0130.088
LDST34.8 ± 6.7− 0.100 0.012 35.0 ± 0.0− 0.0610.23534.8 ± 6.7− 0.098 0.011 35.0 ± 0.0− 0.0610.27033.3 ± 6.90.0040.809
Executive function0.6 ± 0.4− 0.018< 0.001a0.6 ± 0.1− 0.032<0.0010.6 ± 0.4− 0.020< 0.0010.6 ± 0.1− 0.029< 0.001a0.2 ± 0.8− 0.0010.515
TMT part Bb57.0 ± 27.00.472 0.038 48.0 ± 32.51.448 <0.001 a 57.0 ± 27.00.684 0.006 48.0 ± 32.50.921 0.010 71.2 ± 40.4− 0.1320.195
Stroop card IIIb87.5 ± 23.40.468< 0.001a86.5 ± 7.80.734 <0.001 a 87.5 ± 23.40.449< 0.001a86.5 ± 7.80.815< 0.001a93.7 ± 24.8− 0.0260.577
Digit span backwards8.0 ± 1.4− 0.0180.2845.5 ± 0.7− 0.0390.0828.0 ± 1.4− 0.0220.1865.5 ± 0.7− 0.0330.1726.5 ± 2.0− 0.0030.721
WCST concepts6.0 ± 0.0− 0.0150.1936.0 ± 0.0− 0.040 0.007 6.0 ± 0.0− 0.0210.0736.0 ± 0.0− 0.032 0.035 5.7 ± 0.8− 0.0060.323
Letter fluency35.8 ± 7.9− 0.1430.10145.5 ± 17.7− 0.328 0.010 35.8 ± 7.9− 0.1560.06645.5 ± 17.7− 0.339 0.013 37.9 ± 13.0− 0.0480.245
Similarities29.0 ± 1.2− 0.151< 0.001a29.0 ± 1.4− 0.175 <0.001 a 29.0 ± 1.2− 0.155< 0.001a29.0 ± 1.4− 0.175< 0.001a25.5 ± 4.00.0040.775
Social cognition0.0 ± 1.0− 0.022< 0.001a0.8 ± 0.1− 0.0120.1270.0 ± 1.0− 0.021< 0.001a0.8 ± 0.1− 0.0160.0710.3 ± 0.7− 0.0020.336
Happé ToM12.3 ± 5.1− 0.096 0.002 a 13.5 ± 2.10.0170.67212.3 ± 5.1− 0.078 0.012 13.5 ± 2.1− 0.0190.66912.8 ± 3.0− 0.0120.380
Happé non-Tom12.3 ± 2.4− 0.067 0.010 15.5 ± 0.7− 0.0410.21512.3 ± 2.4− 0.060 0.016 15.5 ± 0.7− 0.0620.08012.8 ± 2.7− 0.0120.267
Ekman faces43.5 ± 6.1− 0.089 0.023 50.0 ± 0.0− 0.175 0.001 a 43.5 ± 6.1− 0.118 0.003 50.0 ± 0.0− 0.127 0.024 47.3 ± 5.4− 0.0010.965
Memory− 1.0 ± 2.0− 0.050< 0.001a0.7 ± 0.80.0020.751− 1.0 ± 2.0− 0.044< 0.001a0.7 ± 0.8− 0.0050.5250.2 ± 0.8− 0.0020.473
VAT10.0 ± 2.4− 0.030 0.005 12.0 ± 0.00.0040.67510.0 ± 2.4− 0.027 0.011 12.0 ± 0.00.0000.98311.6 ± 0.8− 0.0020.705
RAVLT imm. recall42.5 ± 9.1− 0.241 0.001 a 54.5 ± 19.1− 0.1110.22642.5 ± 9.1− 0.210 0.003 54.5 ± 19.1− 0.1770.06746.7 ± 10.0− 0.0090.797
RAVLT del. recall7.5 ± 5.5− 0.085< 0.001a10.5 ± 5.00.0020.9517.5 ± 5.5− 0.080< 0.001a10.5 ± 5.0− 0.0020.9549.7 ± 3.2− 0.0090.359
RAVLT recognition27.3 ± 3.1− 0.037 0.005 30.0 ± 0.0− 0.0140.26627.3 ± 3.1− 0.036 0.004 30.0 ± 0.0− 0.0140.30829.3 ± 1.1− 0.0090.461
Visuoconstruction0.2 ± 0.8− 0.0090.2170.2 ± 0.2− 0.0100.3120.2 ± 0.8− 0.0080.2500.2 ± 0.2− 0.0130.237− 0.1 ± 1.00.0000.895
Block design51.0 ± 27.1− 0.2220.06432.0 ± 1.4− 0.1480.33351.0 ± 27.1− 0.235 0.042 32.0 ± 1.4− 0.1090.50337.1 ± 18.5− 0.0060.898
Clock drawing11.8 ± 2.1− 0.0020.87613.5 ± 0.7− 0.0140.45911.8 ± 2.1− 0.0010.96613.5 ± 0.7− 0.0230.28112.3 ± 1.60.0010.888

Values indicate: mean ± standard deviation; β represents estimate of change over time. Composite domain scores are z-scores, individual test scores are raw scores. Composite domain scores are expressed as z-scores, the individual test scores are raw scores. p values represent comparisons to non-converters. Significant comparisons are displayed in bold

MAPT microtubule-associated protein tau, GRN progranulin, bvFTD behavioural variant frontotemporal dementia, nfvPPA non-fluent variant primary progressive aphasia, BNT Boston Naming Test, SAT semantic association test, TMT Trail making Test, WAIS Wechsler Adult Intelligence Scale, LDST letter digit, substitution test, WCST Wisconsin card sorting test, ToM theory of mind, VAT visual association test, RAVLT Rey Auditory Verbal Learning Test, imm immediate, del delayed

aSurvived Bonferroni correction for multiple comparisons

bHigher scores and β weights indicate worse performance

Multilevel linear regression model displaying longitudinal decline (4 years, 2 years and after symptom onset) in composite domain z-score in the total group of converters (light green), MAPT converters (light blue dotted line), GRN converters (dark blue dotted line), non-converters (dark green) and healthy controls (black). Models are displayed per cognitive domain: a social cognition, b attention and mental processing speed, c executive functioning, d memory, e visuoconstruction, and f language. NB: the healthy controls have a mean z-score of zero by default as the z-scores of mutation carriers were based on that (raw score minus mean score of healthy controls, divided by the standard deviation of healthy controls). MAPT microtubule-associated protein tau, GRN progranulin Cognitive trajectories in MAPT, GRN, bvFTD and nfvPPA converters, and non-converters Values indicate: mean ± standard deviation; β represents estimate of change over time. Composite domain scores are z-scores, individual test scores are raw scores. Composite domain scores are expressed as z-scores, the individual test scores are raw scores. p values represent comparisons to non-converters. Significant comparisons are displayed in bold MAPT microtubule-associated protein tau, GRN progranulin, bvFTD behavioural variant frontotemporal dementia, nfvPPA non-fluent variant primary progressive aphasia, BNT Boston Naming Test, SAT semantic association test, TMT Trail making Test, WAIS Wechsler Adult Intelligence Scale, LDST letter digit, substitution test, WCST Wisconsin card sorting test, ToM theory of mind, VAT visual association test, RAVLT Rey Auditory Verbal Learning Test, imm immediate, del delayed aSurvived Bonferroni correction for multiple comparisons bHigher scores and β weights indicate worse performance

Classification between converters and non-converters

Between 4 and 2 years before symptom onset, the delta domain and individual neuropsychological test scores failed to distinguish significantly between converters and non-converters. Between 2 years before symptom onset and symptom onset decline on categorical fluency was predictive of an underlying MAPT mutation (p = 0.025; Table 4). Decline on ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) was predictive of conversion to nfvPPA (Table 4).
Table 4

ROC analyses on neuropsychological decline between 2 years before conversion and symptom onset in converters

Domain and individual neuropsychological testsbvFTD vs. nfvPPA convertersMAPT vs. GRN converters
AUC95% CI p Optimal ΔaSensitivity (%)Specificity (%)AUC95% CI p Optimal ΔbSensitivity (%)Specificity (%)
Language0.6670.29–1.000.5050.8670.51–1.000.101
BNT0.7080.34–1.000.4050.900.67–1.000.074
SAT0.6250.24–1.000.6170.8330.54–1.000.136
ScreeLing phonology1.0001.00–1.00 0.046 − 0.51001000.7000.21–1.000.371
Categorical fluency0.8330.53–1.000.1821.0001.00–1.00 0.025 − 6.5100100
Attention and mental processing speed0.7500.41–1.000.3170.6000.19–1.000.655
TMT part A0.5420.00–1.000.8680.500.05–0.951.000
Stroop card I0.5830.19–0.970.7390.6000.17–1.000.655
Stroop card II0.5830.12–1.000.7390.6670.22–1.000.456
Digit Span forwards WAIS-III0.7500.40–1.000.3170.6330.23–1.000.551
LDST0.6250.23–1.000.6170.6330.22–1.000.551
Executive function0.5830.19–0.980.7390.7330.36–1.000.297
TMT part B0.6670.29–1.000.6170.9000.64–1.000.121
Stroop card III0.8330.51–1.000.1820.6000.15–1.000.655
Digit span backwards WAIS-III0.5420.09–1.000.8680.5670.14–0.990.766
WCST concepts0.5000.10–0.901.0000.7000.32–1.000.371
Letter fluency1.0001.00–1.00 0.046 − 161001000.7670.36–1.000.233
Similarities WAIS-III0.6250.14–1.000.6170.5670.13–1.000.766
Social cognition0.5000.00–1.001.0000.6670.13–1.000.456
Happé ToM0.4580.00–1.000.8680.7000.21–1.000.371
Happé non-Tom0.5000.00–1.001.0000.6670.22–1.000.456
Ekman faces0.6670.15–1.000.5050.5670.07–1.000.766
Memory0.7500.41–1.000.3170.9330.75–1.000.053
VAT0.7920.45–1.000.2430.9330.75–1.000.053
RAVLT immediate recall0.6670.15–1.000.5050.6000.09–1.000.655
RAVLT delayed recall0.6670.27–1.000.5050.8670.58–1.000.101
RAVLT recognition0.7500.37–1.000.3170.9000.65–1.000.074
Visuoconstruction0.5830.19–0.980.7390.6000.19–1.000.655
Block design WAIS-III0.8080.35–1.000.4050.5000.07–0.931.000
Clock drawing0.6670.29–1.000.5050.6000.16–1.000.655

AUC area under the curve, CI confidence interval, bvFTD behavioural variant frontotemporal dementia, nfvPPA non-fluent variant frontotemporal dementia, MAPT microtubule-associated protein tau, GRN progranulin, BNT Boston Naming Test, SAT semantic association test, TMT Trail making Test, WAIS Wechsler Adult Intelligence Scale, LDST letter digit substitution test, WCST Wisconsin Card Sorting Test, ToM theory of mind, VAT visual association test, RAVLT Rey Auditory Verbal Learning Test

aNegative delta represents decline in test performance in nfvPPA vs. bvFTD (i.e. when a converter declines on this particular task, he/she is more likely to develop nfvPPA

bNegative delta represents decline in test performance in MAPT vs GRN (i.e. when a converter declines on this particular task, he/she is more likely to have a underlying MAPT mutation

ROC analyses on neuropsychological decline between 2 years before conversion and symptom onset in converters AUC area under the curve, CI confidence interval, bvFTD behavioural variant frontotemporal dementia, nfvPPA non-fluent variant frontotemporal dementia, MAPT microtubule-associated protein tau, GRN progranulin, BNT Boston Naming Test, SAT semantic association test, TMT Trail making Test, WAIS Wechsler Adult Intelligence Scale, LDST letter digit substitution test, WCST Wisconsin Card Sorting Test, ToM theory of mind, VAT visual association test, RAVLT Rey Auditory Verbal Learning Test aNegative delta represents decline in test performance in nfvPPA vs. bvFTD (i.e. when a converter declines on this particular task, he/she is more likely to develop nfvPPA bNegative delta represents decline in test performance in MAPT vs GRN (i.e. when a converter declines on this particular task, he/she is more likely to have a underlying MAPT mutation

Discussion

This study examined a large cohort of at-risk participants from GRN and MAPT FTD families by means of neuropsychological assessment during a 4-year follow-up. Within the study time window, eight mutation carriers became symptomatic. Converters with a MAPT and GRN mutation had mutual as well as gene-specific profiles of cognitive decline. Cognitive decline on categorical fluency between 2 years before conversion and symptom onset was predictive for an underlying MAPT mutation, and decline on ScreeLing phonology and letter fluency was predictive for conversion to nfvPPA. These results suggest that neuropsychological assessment could provide sensitive clinical biomarkers to identify and track FTD mutation carriers at-risk of converting to the symptomatic stage. These findings hold potential for improving early clinical diagnosis by identifying the most sensitive neuropsychological tests for conversion, and use in upcoming disease-modifying clinical trials. Following the MAPT mutation carriers over a 4-year period, we found significant decline in language, social cognition and memory. This is consistent with findings from previous presymptomatic familial FTD studies, in which both cross-sectional [9–11, 33] and longitudinal [8] decline was found. Specifically, in our first follow-up study [8], we demonstrated decline in the domains language, social cognition and memory 5–8 years before estimated symptom onset. It should be taken into account that this study made use of estimated onset as a proxy, instead of actual symptom onset as in the present study—but the similar profile of decline confirms the presence of early changes in these three domains. As in our previous study, the present results are largely driven by the converters. This could suggest that neuropsychological test scores remain static while mutation carriers are presymptomatic, and cognitive decline starts only near or at symptom onset [34-36], suggesting an explosive rather than gradual start of the symptomatic disease stage. Alternatively, we might be unable to pick up subtle cognitive changes in presymptomatic mutation carriers due to lack of power. Also, although well-validated, most of our neuropsychological tests were not developed for repeated administration in a preclinical population [37]. We therefore cannot rule out that familiarity and/or practice effects are obscuring subtle cognitive decline, a notion that seems to be underwritten by improvement in social cognition and memory in controls, but not mutation carriers. In our exploratory analyses in converters, we discovered both common as well as mutation-specific profiles of cognitive decline in MAPT and GRN. In both mutations, decline in attention, mental processing speed and executive function was found—while only converters with a MAPT mutation demonstrated decline on language, memory and social cognition. Previous studies in familial FTD also point to distinct profiles for MAPT and GRN [8, 10–12], and are largely consistent with our present findings. Another important aspect is the longitudinal tracking of the different clinical phenotypes. The similar patterns of cognitive decline in bvFTD as MAPT, and nfvPPA as GRN are related to the dominant genotype in each group (e.g. all nfvPPA converters have a GRN mutation). These findings suggest that neuropsychological assessment can be used to track the different mutations and phenotypes from the presymptomatic to the symptomatic stage, which is advantageous considering the need for good clinical endpoints in future disease-modifying trials. Extending the findings from our first follow-up study [8], we demonstrated significant decline on the RAVLT recall in presymptomatic MAPT mutation carriers. The additional finding that lower memory scores over time were also found in MAPT, and not GRN converters—suggesting a mutation-specific aetiology—corroborate this. Although memory loss has been described in GRN [38, 39], this is usually a later symptom, while episodic memory impairment has been found as the presenting and most prominent symptom in MAPT [7, 40, 41]. Interestingly, the Genetic Frontotemporal dementia Initiative (GENFI) consortium revealed hippocampal atrophy in presymptomatic MAPT from 15 years before estimated symptom onset [10], and as this medial temporal structure is critical for episodic memory processing [42] this offers a good explanation for our findings. In line with earlier studies [42, 43], we did find deficits in verbal recall but not visual associative memory. Semantically loaded tasks such as the RAVLT can be particularly more difficult than visual memory tasks like the VAT, as a result of the prominent semantic impairments seen early in MAPT-associated FTD [44]. Our results contribute to the present thinking that memory deficits can be an integral part of the clinical spectrum [42], and comprehensive memory tasks should therefore be incorporated in the standard diagnostic work-up. Knowing the cognitive profile of decline indicative for conversion is important to get more insight into the timing of clinical changes in the earliest disease stage. We found that conversion can be predicted based on cognitive decline in the 2 years prior to symptom onset, but not earlier. As the cognitive decline was part of the diagnostic process of determining conversion, this is not a surprising finding. However, it does suggest a more explosive disease development with cognitive decline accelerating rapidly in proximity of symptom onset, which is in line with evidence from a large familial Alzheimer’s disease cohort [45]. By selectively choosing tests within the domains that have prognostic abilities, the neuropsychological battery can be shortened, which would benefit patient burden and helps cutting healthcare expenses. Especially fluency tasks seem to be promising candidates, as they were able to distinguish accurately between future phenotype and underlying genotype. The latter is essential for patient stratification in future clinical trials targeting specific pathologies, and ideally these interventions should be applied in the presymptomatic stage [46]. Reliable phenotypic prediction furthermore optimizes the diagnostic process by shortening the current diagnostic delay [47], and is helpful for the patient, caregiver and clinician in knowing what disease presentation and course to expect. Verbal fluency tests are widely used in dementia diagnosis setting [48], and are affected in both presymptomatic [8, 11] and symptomatic FTD [49, 50]. Future research could additionally investigate the use of qualitative assessment of verbal fluency (e.g. clustering, switching between clusters), as recent research [49] points to differences between FTD and PPA subtypes—making this a promising application of verbal fluency for a precise clinical differentiation in presymptomatic and early stage FTD. Key strengths of our study constitute our longitudinal design, spanning a 4-year follow-up of at-risk participants from both MAPT and GRN families. Although our group of converters is currently small, this is the first study tracking FTD mutation carriers from the presymptomatic to symptomatic disease stage. Being aware of the caveats of small sample sizes and administering a large amount of neuropsychological tests with respect to statistical power, our results warrant replication in our cohort as well as larger international cohorts such as GENFI [10], in which with the passing of time more mutation carriers will approach symptom onset and/or convert to clinical FTD. The dropout rate is very low, creating balanced datasets across the three time points. Additionally, use of multilevel linear modeling further handles efficiently with missing data. Directions for future research entail the development of neuropsychological tasks more suited to administer in the presymptomatic phase (robust to ceiling effects) and repeated administration (robust to practice and able to measure small changes). More extensive quantification tools of behavioural functioning are also needed to capture the entire clinical spectrum of (presymptomatic) FTD, as well as assessment methods that rely less on the accuracy of informant report [37]. A disadvantage of the study is the fact that the neuropsychological assessment was part of the clinical assessment with which we determined conversion to the symptomatic stage. This has likely led to a circular reasoning, as we demonstrated that converters declined over time, while cognitive decline was considered a prerequisite for conversion. Ideally, the tests assessed in our study should not have been used in the diagnosis of conversion. However, in our multidisciplinary meeting, we followed the international consensus criteria for bvFTD [3] and PPA [6], using all available clinical information—e.g. MR imaging of the brain, anamnestic and heteroanamnestic information, behavioural and neuropsychiatric questionnaires, unblinding of genetic status—so that symptom onset did not solely depend on the neuropsychological assessment. Furthermore, as the multilevel model assumes a linear relationship between genetic status and cognitive decline over time, we could have missed non-linear effects over time. Lastly, the analyses on the non-converters and controls were performed using the original baseline and follow-up visits, regardless of, e.g. age and time to estimated symptom onset. It is possible that these analyses therefore lost some sensitivity to detect cognitive decline over time. However, as between-group analyses on age and estimated years to symptom onset in converters, non-converters, and controls did not show significant differences (respectively, p = 0.99 and p = 0.19), we believe this effect is minimal. Our study investigates longitudinal neuropsychological performance in a large cohort of at-risk individuals from genetic FTD families. We provide evidence of mutation-specific cognitive decline when moving from the presymptomatic into symptomatic stage, and of neuropsychological trajectories predicting symptom onset. These results suggest the potential biomarker value of neuropsychological assessment in both disease-monitoring and predicting conversion to clinical FTD. Below is the link to the electronic supplementary material. Supplementary material 1 (DOCX 66 kb) Supplementary material 2 (DOCX 16 kb)
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Authors:  Adam M Staffaroni; Lynn Bajorek; Kaitlin B Casaletto; Yann Cobigo; Sheng-Yang M Goh; Amy Wolf; Hilary W Heuer; Fanny M Elahi; Peter A Ljubenkov; Reilly Dever; John Kornak; Brian Appleby; Jessica Bove; Yvette Bordelon; Patrick Brannelly; Danielle Brushaber; Christina Caso; Giovanni Coppola; Christina Dheel; Bradford C Dickerson; Susan Dickinson; Sophia Dominguez; Kimiko Domoto-Reilly; Kelly Faber; Jessica Ferrall; Julie A Fields; Ann Fishman; Jamie Fong; Tatiana Foroud; Leah K Forsberg; Ralitza Gavrilova; Debra Gearhart; Behnaz Ghazanfari; Nupur Ghoshal; Jill Goldman; Jonathan Graff-Radford; Neill Graff-Radford; Ian Grant; Murray Grossman; Dana Haley; Ging-Yuek Hsiung; Edward D Huey; David J Irwin; David T Jones; Lynne Jones; Kejal Kantarci; Anna Karydas; Daniel I Kaufer; Diana R Kerwin; David S Knopman; Ruth Kraft; Walter K Kremers; Walter A Kukull; Irene Litvan; Diane Lucente; Codrin Lungu; Ian R Mackenzie; Miranda Maldonado; Masood Manoochehri; Scott M McGinnis; Emily McKinley; Mario F Mendez; Bruce L Miller; Namita Multani; Chiadi Onyike; Jaya Padmanabhan; Alex Pantelyat; Rodney Pearlman; Len Petrucelli; Madeline Potter; Rosa Rademakers; Eliana Marisa Ramos; Katherine P Rankin; Katya Rascovsky; Erik D Roberson; Emily Rogalski; Pheth Sengdy; Leslie M Shaw; Jeremy Syrjanen; M Carmela Tartaglia; Nadine Tatton; Joanne Taylor; Arthur Toga; John Q Trojanowski; Sandra Weintraub; Ping Wang; Bonnie Wong; Zbigniew Wszolek; Adam L Boxer; Brad F Boeve; Joel H Kramer; Howard J Rosen
Journal:  Alzheimers Dement       Date:  2019-05-11       Impact factor: 21.566

2.  The CBI-R detects early behavioural impairment in genetic frontotemporal dementia.

Authors:  Annabel Nelson; Lucy L Russell; Georgia Peakman; Rhian S Convery; Arabella Bouzigues; Caroline V Greaves; Martina Bocchetta; David M Cash; John C van Swieten; Lize Jiskoot; Fermin Moreno; Raquel Sanchez-Valle; Robert Laforce; Caroline Graff; Mario Masellis; Maria Carmela Tartaglia; James B Rowe; Barbara Borroni; Elizabeth Finger; Matthis Synofzik; Daniela Galimberti; Rik Vandenberghe; Alexandre de Mendonça; Chris R Butler; Alexander Gerhard; Simon Ducharme; Isabelle Le Ber; Isabel Santana; Florence Pasquier; Johannes Levin; Markus Otto; Sandro Sorbi; Jonathan D Rohrer
Journal:  Ann Clin Transl Neurol       Date:  2022-03-26       Impact factor: 5.430

3.  Neurofilament Light Chain Related to Longitudinal Decline in Frontotemporal Lobar Degeneration.

Authors:  Jiasi Vicky Zhang; David J Irwin; Kaj Blennow; Henrik Zetterberg; Edward B Lee; Leslie M Shaw; Katya Rascovsky; Lauren Massimo; Corey T McMillan; Alice Chen-Plotkin; Lauren Elman; Virginia M-Y Lee; Leo McCluskey; Jon B Toledo; Daniel Weintraub; David Wolk; John Q Trojanowski; Murray Grossman
Journal:  Neurol Clin Pract       Date:  2021-04

4.  Impairment of episodic memory in genetic frontotemporal dementia: A GENFI study.

Authors:  Jackie M Poos; Lucy L Russell; Georgia Peakman; Martina Bocchetta; Caroline V Greaves; Lize C Jiskoot; Emma L van der Ende; Harro Seelaar; Janne M Papma; Esther van den Berg; Yolande A L Pijnenburg; Barbara Borroni; Raquel Sanchez-Valle; Fermin Moreno; Robert Laforce; Caroline Graff; Matthias Synofzik; Daniela Galimberti; James B Rowe; Mario Masellis; Carmela Tartaglia; Elizabeth Finger; Rik Vandenberghe; Alexandre de Medonça; Fabrizio Tagliavini; Chris R Butler; Isabel Santana; Isabelle Le Ber; Alex Gerhard; Simon Ducharme; Johannes Levin; Adrian Danek; Markus Otto; Sandro Sorbi; Florence Pasquier; John C van Swieten; Jonathan D Rohrer
Journal:  Alzheimers Dement (Amst)       Date:  2021-05-13

5.  Recognition memory and divergent cognitive profiles in prodromal genetic frontotemporal dementia.

Authors:  Megan S Barker; Masood Manoochehri; Sandra J Rizer; Brian S Appleby; Danielle Brushaber; Sheena I Dev; Katrina L Devick; Bradford C Dickerson; Julie A Fields; Tatiana M Foroud; Leah K Forsberg; Douglas R Galasko; Nupur Ghoshal; Neill R Graff-Radford; Murray Grossman; Hilary W Heuer; Ging-Yuek Hsiung; John Kornak; Irene Litvan; Ian R Mackenzie; Mario F Mendez; Belen Pascual; Katherine P Rankin; Katya Rascovsky; Adam M Staffaroni; Maria Carmela Tartaglia; Sandra Weintraub; Bonnie Wong; Bradley F Boeve; Adam L Boxer; Howard J Rosen; Jill Goldman; Edward D Huey; Stephanie Cosentino
Journal:  Cortex       Date:  2021-03-19       Impact factor: 4.644

6.  Proposed research criteria for prodromal behavioural variant frontotemporal dementia.

Authors:  Megan S Barker; Reena T Gottesman; Masood Manoochehri; Silvia Chapman; Brian S Appleby; Danielle Brushaber; Katrina L Devick; Bradford C Dickerson; Kimiko Domoto-Reilly; Julie A Fields; Leah K Forsberg; Douglas R Galasko; Nupur Ghoshal; Jill Goldman; Neill R Graff-Radford; Murray Grossman; Hilary W Heuer; Ging-Yuek Hsiung; David S Knopman; John Kornak; Irene Litvan; Ian R Mackenzie; Joseph C Masdeu; Mario F Mendez; Belen Pascual; Adam M Staffaroni; Maria Carmela Tartaglia; Bradley F Boeve; Adam L Boxer; Howard J Rosen; Katherine P Rankin; Stephanie Cosentino; Katya Rascovsky; Edward D Huey
Journal:  Brain       Date:  2022-04-29       Impact factor: 15.255

7.  Early symptoms in symptomatic and preclinical genetic frontotemporal lobar degeneration.

Authors:  Tamara Paulo Tavares; Derek G V Mitchell; Kristy Kl Coleman; Brenda L Coleman; Christen L Shoesmith; Christopher R Butler; Isabel Santana; Adrian Danek; Alexander Gerhard; Alexandre de Mendonca; Barbara Borroni; Maria Carmela Tartaglia; Caroline Graff; Daniela Galimberti; Fabrizio Tagliavini; Fermin Moreno; Giovanni Frisoni; James Benedict Rowe; Johannes Levin; John Cornelis Van Swieten; Markus Otto; Matthis Synofzik; Raquel Sanchez-Valle; Rik Vandenberghe; Robert Jr Laforce; Roberta Ghidoni; Sandro Sorbi; Simon Ducharme; Mario Masellis; Jonathan Rohrer; Elizabeth Finger
Journal:  J Neurol Neurosurg Psychiatry       Date:  2020-08-07       Impact factor: 10.154

8.  Apathy in presymptomatic genetic frontotemporal dementia predicts cognitive decline and is driven by structural brain changes.

Authors:  Maura Malpetti; P Simon Jones; Kamen A Tsvetanov; Timothy Rittman; John C van Swieten; Barbara Borroni; Raquel Sanchez-Valle; Fermin Moreno; Robert Laforce; Caroline Graff; Matthis Synofzik; Daniela Galimberti; Mario Masellis; Maria Carmela Tartaglia; Elizabeth Finger; Rik Vandenberghe; Alexandre de Mendonça; Fabrizio Tagliavini; Isabel Santana; Simon Ducharme; Chris R Butler; Alexander Gerhard; Johannes Levin; Adrian Danek; Markus Otto; Giovanni B Frisoni; Roberta Ghidoni; Sandro Sorbi; Carolin Heller; Emily G Todd; Martina Bocchetta; David M Cash; Rhian S Convery; Georgia Peakman; Katrina M Moore; Jonathan D Rohrer; Rogier A Kievit; James B Rowe
Journal:  Alzheimers Dement       Date:  2020-12-14       Impact factor: 16.655

9.  The Revised Self-Monitoring Scale detects early impairment of social cognition in genetic frontotemporal dementia within the GENFI cohort.

Authors:  Hannah D Franklin; Lucy L Russell; Georgia Peakman; Caroline V Greaves; Martina Bocchetta; Jennifer Nicholas; Jackie Poos; Rhian S Convery; David M Cash; John van Swieten; Lize Jiskoot; Fermin Moreno; Raquel Sanchez-Valle; Barbara Borroni; Robert Laforce; Mario Masellis; Maria Carmela Tartaglia; Caroline Graff; Daniela Galimberti; James B Rowe; Elizabeth Finger; Matthis Synofzik; Rik Vandenberghe; Alexandre de Mendonça; Fabrizio Tagliavini; Isabel Santana; Simon Ducharme; Chris Butler; Alex Gerhard; Johannes Levin; Adrian Danek; Markus Otto; Sandro Sorbi; Isabelle Le Ber; Florence Pasquier; Jonathan D Rohrer
Journal:  Alzheimers Res Ther       Date:  2021-07-12       Impact factor: 6.982

10.  Neuropsychiatric Aspects in a Patient Diagnosed with Frontotemporal Dementia: Clinical Case of Low Incidence and Prevalence Disease in Colombia.

Authors:  Juliana Vergel Hernández; María Eugenia Barrera Robledo; Carlos Alberto Hurtado González; Carlos Steven Marmolejo Escobar; Sebastián Ospina Otalvaro; Juan David Sánchez Tobón; Pablo Miguel Arango de la Pava; Juan José Alvarez
Journal:  Case Rep Neurol       Date:  2021-07-08
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