With a single molecule array method (Simoa, Quanterix), plasma NfL concentrations were measured in 99 subjects with AD at the stage of mild cognitive impairment (MCI-AD; n = 25) or at the stage of early dementia (ADD; n = 33), and in nondemented controls (n = 41); in all patients, the clinical diagnoses were in accordance with the results of the four core cerebrospinal fluid (CSF) biomarkers (amyloid β (Aβ)1-42, Aβ42/40, Tau, and pTau181), interpreted according to the Erlangen Score algorithm.
We re-examined our cohort of amnestic MCI, grouped according to cerebrospinal fluid (CSF) biomarkers, aiming at establishing their prognostic value for Alzheimer-type dementia and testing the hypothetical model of biomarkers sequence, based on the amyloid cascade.
We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up.
We included 768 patients (194 with subjective cognitive decline (SCD), 127 mild cognitive impairment (MCI), 309 Alzheimer's dementia (AD), and 138 non-AD) who were categorized as concordant-negative (n = 315, 41%), discordant (n = 97, 13%), or concordant-positive (n = 356, 46%) based on CSF and PET results.
We included 276 subjects with MCI (mean age 67 ± 8, 41% female, mean Mini-Mental State Examination 26.6 ± 2.4), baseline 3D T1-weighted structural MRI, baseline cerebrospinal fluid (CSF) biomarkers, and prospective clinical follow-up.
To examine the long-term performance of baseline cognitive, neuroimaging, and cerebrospinal fluid (CSF) biomarker-assisted prognosis in patients with mild cognitive impairment.
To compare the incremental diagnostic value of amyloid-PET and CSF (Aβ42, tau, and phospho-tau) in AD diagnosis in patients with mild cognitive impairment (MCI) or mild dementia, in order to improve the definition of diagnostic algorithm.
Thus, the goal of this study was to identify the combination of cerebrospinal fluid (CSF) biomarkers, MRI morphometry, FDG PET metabolism and neuropsychological test scores to that best differentiate between a sample of normal aging subjects and those with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative.
This study aims at providing a personalized MCI-to-AD conversion estimation by using a multipredictor nomogram that integrates neuroimaging features, cerebrospinal fluid (CSF) biomarker, and clinical assessments.
Thereafter, we focused on the four miRNAs that showed group differences and measured their content in neurally derived blood EVs isolated from 63 subjects: 16 patients with early stage dementia and a CSF Aβ42+ tau profile consistent with AD, 16 individuals with mild cognitive impairment (MCI) and an AD CSF profile, and 31 cognitively intact controls with normal CSF Aβ42+ tau levels.
The relative performance of semi-quantitative amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) markers in diagnosing Alzheimer's disease (AD) and predicting the cognitive evolution of patients with mild cognitive impairment (MCI) is still debated.
The progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers.
The present study investigated differences in EEG microstate topographies and parameters (duration, occurrence and contribution) between a large cohort of healthy elderly (n = 308) and memory clinic patients: subjective cognitive decline (SCD, n = 210); mild cognitive impairment (MCI, n = 230) and AD (n = 197) and how they correlate to conventional cerebrospinal fluid (CSF) markers of AD.
The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by <sup>18</sup>F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and <sup>18</sup>F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on <sup>18</sup>F-AV1451 brain uptake.
The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease.
The finding that amnestic MCI based on brief neuropsychological assessment is significantly associated with CSF biomarkers for cognitive decline and Alzheimer's disease is in accordance with longitudinal studies that find memory impairment; both in itself and especially in combination with other cognitive deficit to constitute a risk factor for subsequent cognitive decline and dementia.
The evaluation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD) (β-amyloid, t-tau, p-tau) can be used to estimate the risk of developing dementia in patients at the pre-clinical stages of AD, i.e. subjective cognitive decline (SCD) and mild cognitive impairment (MCI).
The diagnostic accuracy of CSF KLK8 was as good as that of core CSF biomarkers for AD (area under the curve (AUC)=0.89) and in case of MCI (AUC=0.97) even superior to CSF Aβ42.
The cerebrospinal fluid (CSF) biochemical markers (biomarkers) Amyloidβ 42 (Aβ<sub>42</sub>), total Tau (T-tau) and Tau phosphorylated at threonine 181 (P-tau<sub>181</sub>) have proven diagnostic accuracy for mild cognitive impairment and dementia due to Alzheimer's Disease (AD).
The Alzheimer's biomarkers in daily practice (ABIDE) project is designed to translate knowledge on diagnostic tests (magnetic resonance imaging [MRI], cerebrospinal fluid [CSF], and amyloid positron emission tomography [PET]) to daily clinical practice with a focus on mild cognitive impairment (MCI).
The aim of this study was to explore the associations of cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, phosphorylated tau) and other characteristics, including modifiable vascular factors, with the risk of progression to dementia among patients with MCI and normal CSF Aβ42.
The aim of this study was to estimate the potential incremental cost-effectiveness ratio of adding CSF biomarker testing to the standard diagnostic workup to determine the prognosis for patients with MCI.
The CSF biomarker statuses established by predefined cutoffs were highly concordant with PET classification in Alzheimer's Disease Neuroimaging Initiative (overall percent agreement: 89%-90%; area under the curves: 96%) and predicted greater 2-year clinical decline in patients with mild cognitive impairment.