Background Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma... Show moreBackground Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process. Methods Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 +/- 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 +/- 7.9; 45% female), AD patients (n = 57; age = 65.5 +/- 8.0; 39% female), and non-demented controls (n = 148; 61.3 +/- 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 +/- 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 +/- 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 +/- 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis. Results Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified. Conclusions We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts. Show less
Baakman, A.C.; Gavan, C.; Doeselaar, L. van; Kam, M. de; Broekhuizen, K.; Bajenaru, O.; ... ; Groeneveld, G.J. 2022
Aims Cholinesterase inhibitors (CEIs) have been shown to improve cognitive functioning in Alzheimer's disease (AD) patients, but are associated with multiple side effects and only 20-40% of the... Show moreAims Cholinesterase inhibitors (CEIs) have been shown to improve cognitive functioning in Alzheimer's disease (AD) patients, but are associated with multiple side effects and only 20-40% of the patients clinically improve. In this study, we aimed to investigate the acute pharmacodynamic (PD) effects of administration of a single dose of galantamine on central nervous system (CNS) functioning in mild to moderate AD patients and its potential to predict long-term treatment response. Methods This study consisted of a challenge and treatment phase. In the challenge phase, a single dose of 16 mg galantamine was administered to 50 mild to moderate AD patients in a double-blind, placebo-controlled cross-over fashion. Acute PD effects were monitored up to 5 hours after administration with use of the NeuroCart CNS test battery and safety and pharmacokinetics were assessed. In the treatment phase, patients were treated with open-label galantamine according to regular clinical care. After 6 months of galantamine treatment, patients were categorized as either responder or as non-responder based on their minimental state examination (MMSE), neuropsychiatric inventory (NPI) and disability assessment in dementia (DAD) scores. An analysis of covariance was performed to study the difference in acute PD effects during the challenge phase between responders and non-responders. Results A single dose of galantamine significantly reduced saccadic reaction time (-0.0099; 95% CI = -0.0195, -0.0003; P = .0430), absolute frontal EEG parameters in alpha (-14.9; 95% CI = -21.0, -8.3; P = .0002), beta (-12.6; 95% CI = -19.4, -5.3; P = .0019) and theta (-17.9; 95% CI = -25.0, -10.0; P = .0001) frequencies. Relative frontal (-1.669; 95% CI = -2.999, -0.339; P = .0156) and occipital (-1.856; 95% CI = -3.339, -0.372; P = .0166) EEG power in theta frequency and relative occipital EEG power in the gamma frequency (1.316; 95% CI = 0.158, 2.475; P = .0273) also increased significantly compared to placebo. Acute decreases of absolute frontal alpha (-20.4; 95% CI = -31.6, -7.47; P = .0046), beta (-15.7; 95% CI = -28.3, -0.93; P = .0390) and theta (-25.9; 95% CI = -38.4, -10.9; P = .0024) EEG parameters and of relative frontal theta power (-3.27%; 95% CI = -5.96, -0.58; P = .0187) on EEG significantly distinguished responders (n = 11) from non-responders (n = 32) after 6 months. Conclusions This study demonstrates that acute PD effects after single dose of galantamine are correlated with long-term treatment effects and that patients who demonstrate a reduction in EEG power in the alpha and theta frequency after a single administration of galantamine 16 mg will most likely respond to treatment. Show less
Vos, F. de; Schouten, T.M.; Koini, M.; Bouts, M.J.R.J.; Feis, R.A.; Lechner, A.; ... ; Rombouts, S.A.R.B. 2020
Anatomical magnetic resonance imaging (MRI), diffusion MRI and resting state functional MRI (rs-fMRI) have been used for Alzheimer's disease (AD) classification. These scans are typically used to... Show moreAnatomical magnetic resonance imaging (MRI), diffusion MRI and resting state functional MRI (rs-fMRI) have been used for Alzheimer's disease (AD) classification. These scans are typically used to build models for discriminating AD patients from control subjects, but it is not clear if these models can also discriminate AD in diverse clinical populations as found in memory clinics.To study this, we trained MRI-based AD classification models on a single centre data set consisting of AD patients (N = 76) and controls (N = 173), and used these models to assign AD scores to subjective memory complainers (N = 67), mild cognitive impairment (MCI) patients (N = 61), and AD patients (N = 61) from a multi-centre memory clinic data set. The anatomical MRI scans were used to calculate grey matter density, subcortical volumes and cortical thickness, the diffusion MRI scans were used to calculate fractional anisotropy, mean, axial and radial diffusivity, and the rs-fMRI scans were used to calculate functional connectivity between resting state networks and amplitude of low frequency fluctuations. Within the multi-centre memory clinic data set we removed scan site differences prior to applying the models.For all models, on average, the AD patients were assigned the highest AD scores, followed by MCI patients, and later followed by SMC subjects. The anatomical MRI models performed best, and the best performing anatomical MRI measure was grey matter density, separating SMC subjects from MCI patients with an AUC of 0.69, MCI patients from AD patients with an AUC of 0.70, and SMC patients from AD patients with an AUC of 0.86. The diffusion MRI models did not generalise well to the memory clinic data, possibly because of large scan site differences. The functional connectivity model separated SMC subjects and MCI patients relatively good (AUC = 0.66). The multimodal MRI model did not improve upon the anatomical MRI model.In conclusion, we showed that the grey matter density model generalises best to memory clinic subjects. When also considering the fact that grey matter density generally performs well in AD classification studies, this feature is probably the best MRI-based feature for AD diagnosis in clinical practice. Show less
Heinen, R.; Groeneveld, O.N.; Barkhof, F.; Bresser, J. de; Exalto, L.G.; Kuijf, H.J.; ... ; TRACE-VCI Study Grp 2020
IntroductionIt is unknown whether different types of small vessel disease (SVD), differentially relate to brain atrophy and if co-occurring Alzheimer's disease pathology affects this relation... Show moreIntroductionIt is unknown whether different types of small vessel disease (SVD), differentially relate to brain atrophy and if co-occurring Alzheimer's disease pathology affects this relation.MethodsIn 725 memory clinic patients with SVD (mean age 67 +/- 8 years, 48% female) we compared brain volumes of those with moderate/severe white matter hyperintensities (WMHs; n = 326), lacunes (n = 132) and cerebral microbleeds (n = 321) to a reference group with mild WMHs (n = 197), also considering cerebrospinal fluid (CSF) amyloid status in a subset of patients (n = 488).ResultsWMHs and lacunes, but not cerebral microbleeds, were associated with smaller gray matter (GM) volumes. In analyses stratified by CSF amyloid status, WMHs and lacunes were associated with smaller total brain and GM volumes only in amyloid-negative patients. SVD-related atrophy was most evident in frontal (cortical) GM, again predominantly in amyloid-negative patients.DiscussionAmyloid status modifies the differential relation between SVD lesion type and brain atrophy in memory clinic patients. Show less
Lee, S.J. van der; Conway, O.J.; Jansen, I.; Carrasquillo, M.M.; Kleineidam, L.; Akker, E. van den; ... ; GIFT Genetic Invest 2019
Self-perceived word-finding difficulties are common in aging individuals as well as in Alzheimer's Disease (AD). Language and speech deficits are difficult to objectify with neuropsychological... Show moreSelf-perceived word-finding difficulties are common in aging individuals as well as in Alzheimer's Disease (AD). Language and speech deficits are difficult to objectify with neuropsychological assessments. We therefore aimed to investigate whether amyloid, an early AD pathological hallmark, is associated with speech-derived semantic complexity. We included 63 individuals with subjective cognitive decline (age 64 ± 8, MMSE 29 ± 1), with amyloid status (positron emission tomography [PET] scans n = 59, or Aβ1-42 cerebrospinal fluid [CSF] n = 4). Spontaneous speech was recorded using three open-ended tasks (description of cookie theft picture, abstract painting and a regular Sunday), transcribed verbatim and subsequently, linguistic parameters were extracted using T-scan computational software, including specific words (content words, frequent, concrete and abstract nouns, and fillers), lexical complexity (lemma frequency, Type-Token-Ratio) and syntactic complexity (Developmental Level scale). Nineteen individuals (30%) had high levels of amyloid burden, and there were no differences between groups on conventional neuropsychological tests. Using multinomial regression with lin- guistic parameters (in tertiles), we found that high amyloid burden is associated with fewer concrete nouns (ORmiddle (95%CI): 7.6 (1.4–41.2), ORlowest: 6.7 (1.2–37.1)) and content words (ORlowest: 6.3 (1.0–38.1). In addition, we found an interaction for education between high amyloid burden and more abstract nouns. In conclusion, high amyloid burden was modestly associated with fewer specific words, but not with syntactic complexity, lexical complexity or conventional neuropsychological tests, suggesting that subtle spontaneous speech deficits might occur in preclinical AD. Show less
