Association of Plasma Amyloid, P-Tau, GFAP, and NfL With CSF, Clinical, and Cognitive Features in Patients With Dementia With Lewy Bodies.

BACKGROUND AND OBJECTIVES: Plasma ß-amyloid-1-42/1-40 (Aß42/40), phosphorylated-tau (P-tau), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) have been widely examined in Alzheimer disease (AD), but little is known about their reflection of copathologies, clinical importance, and predictive value in dementia with Lewy bodies (DLB). We aimed to evaluate associations of these biomarkers with CSF amyloid, cognition, and core features in DLB. METHODS: This cross-sectional multicenter cohort study with prospective component included individuals with DLB, AD, and healthy controls (HCs), recruited from 2002 to 2020 with an annual follow-up of up to 5 years, from the European-Dementia With Lewy Bodies consortium. Plasma biomarkers were measured by single-molecule array (Neurology 4-Plex E kit). Amyloid status was determined by CSF Aß42 concentrations, and cognition was assessed by Mini-Mental State Examination (MMSE). Biomarker differences across groups, associations with amyloid status, and clinical core features were assessed by analysis of covariance. Associations with cognitive impairment and decline were assessed by linear regression and linear mixed-effects models. RESULTS: In our cohort consisting of 562 individuals (HC n = 89, DLB n = 342, AD n = 131; 250 women [44.5%], mean [SD] age of 71 [8] years), sex distribution did not differ between groups. Patients with DLB were significantly older, and had less years of education and worse baseline cognition than HC, but not AD. DLB participants stratified for amyloid status differed significantly in plasma Aß42/40 ratio (decreased in amyloid abnormal: ß = -0.008, 95% CI -0.016 to -0.0003, p = 0.01) and P-tau (increased in amyloid abnormal, P-tau181: ß = 0.246, 95% CI 0.011-0.481; P-tau231: ß = 0.227, 95% CI 0.035-0.419, both p < 0.05), but not in GFAP (ß = 0.068, 95% CI -0.018 to 0.153, p = 0.119), and NfL (ß = 0.004, 95% CI -0.087 to 0.096, p = 0.923) concentrations. Higher baseline GFAP, NfL, and P-tau concentrations were associated with lower MMSE scores in DLB, and GFAP and NfL were associated with a faster cognitive decline (GFAP: annual change of -2.11 MMSE points, 95% CI -2.88 to -1.35 MMSE points, p < 0.001; NfL: annual change of -2.13 MMSE points, 95% CI -2.97 to -1.29 MMSE points, p < 0.001). DLB participants with parkinsonism had higher concentrations of NfL (ß = 0.08, 95% CI 0.02-0.14, p = 0.006) than those without. DISCUSSION: Our study suggests a possible utility of plasma Aß42/40, P-tau181, and P-tau231 as a noninvasive biomarkers to assess amyloid copathology in DLB, and plasma GFAP and NfL as monitoring biomarkers for cognitive symptoms in DLB.

Visual associative learning to detect early episodic memory deficits and distinguish Alzheimer's disease from other types of dementia.

OBJECTIVE: We investigated how well a visual associative learning task discriminates Alzheimer's disease (AD) dementia from other types of dementia and how it relates to AD pathology. METHODS: 3,599 patients (63.9 ± 8.9 years old, 41% female) from the Amsterdam Dementia Cohort completed two sets of the Visual Association Test (VAT) in a single test session and underwent magnetic resonance imaging. We performed receiver operating curve analysis to investigate the VAT's discriminatory ability between AD dementia and other diagnoses and compared it to that of other episodic memory tests. We tested associations between VAT performance and medial temporal lobe atrophy (MTA), and amyloid status (n = 2,769, 77%). RESULTS: Patients with AD dementia performed worse on the VAT than all other patients. The VAT discriminated well between AD and other types of dementia (area under the curve range 0.70-0.86), better than other episodic memory tests. Six-hundred forty patients (17.8%) learned all associations on VAT-A, but not on VAT-B, and they were more likely to have higher MTA scores (odds ratios range 1.63 (MTA 0.5) through 5.13 for MTA ≥ 3, all p < .001) and to be amyloid positive (odds ratio = 3.38, 95%CI = [2.71, 4.22], p < .001) than patients who learned all associations on both sets. CONCLUSIONS: Performance on the VAT, especially on a second set administered immediately after the first, discriminates AD from other types of dementia and is associated with MTA and amyloid positivity. The VAT might be a useful, simple tool to assess early episodic memory deficits in the presence of AD pathology.

Optimizing cCOG, a Web-based tool, to detect dementia with Lewy Bodies.

Introduction: Distinguishing dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) is challenging due to overlapping presentations. We adapted a Web-based test tool, cCOG, by adding a visuospatial task and a brief clinical survey and assessed its ability to differentiate between DLB and AD. Methods: We included 110 patients (n = 30 DLB, n = 32 AD dementia, and n = 48 controls with subjective cognitive decline (SCD)). Full cCOG comprises six cognitive subtasks and a survey addressing self-reported DLB core and autonomic features. First, we compared cCOG cognitive tasks to traditional neuropsychological tasks for all diagnostic groups and clinical questions to validated assessments of clinical features in DLB only. Then, we studied the performance of cCOG cognitive tasks and clinical questions, separately and combined, in differentiating diagnostic groups. Results: cCOG cognitive tasks and clinical survey had moderate to strong correlations to standard neuropsychological testing (.61≤ r s ≤ .77) and to validated assessments of clinical features (.41≤ r s ≤ .65), except for fluctuations and REM-sleep behavior disorder (RBD) (r s = .32 and r s = .10). Full cCOG, including both cognitive tasks and brief survey had a diagnostic accuracy (acc) of 0.82 [95% CI 0.73-0.89], with good discrimination of DLB versus AD (acc 0.87 [0.76-0.95]) and DLB versus controls (acc 0.94 [0.86-0.98]). Conclusion: We illustrated that cCOG aids in distinguishing DLB and AD patients by using remote assessment of cognition and clinical features. Our findings pave the way to a funneled, harmonized diagnostic process among memory clinics and, eventually, a more timely and accurate diagnosis of DLB and AD.