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.
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.
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.
Early Alzheimer's disease (AD) detection using cerebrospinal fluid (CSF) biomarkers has been recommended as enrichment strategy for trials involving mild cognitive impairment (MCI) patients.
Comparison of stable MCI and MCI that progressed to AD showed significantly higher levels in the CSF of MCI patients who progressed to AD, compared to stable MCI patients [SMD: 230.84 (12.54, 449.14), Z = 2.07, P = 0.04].
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.
In <i>post hoc</i> models examining cognitive status, CSF Aβ42 predicted Mini Mental State Examination (MMSE) scores in healthy elderly, whereas Aβ burden and CSF p-tau predicted MMSE scores in AD/MCI.
A cell-protective rather than a proinflammatory analyte profile predominates in the CSF in relation to neurodegeneration markers among MCI-AD patients.
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.
In the present retrospective observational study, we evaluated CSF biomarkers and neuropsychological data (also including NPS measured by the neuropsychiatric inventory-NPI) in a population of patients affected by MCI due to AD compared with mild to moderate AD patients.
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 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 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 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).
Prognostic models were developed by Cox regression with patient characteristics, MRI, and/or CSF biomarkers to predict clinical progression to MCI or dementia.
A total of 1,081 adults without dementia (375 healthy subjects and 706 individuals with mild cognitive impairment) were recruited from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to test the influence of BDNF Val66Met polymorphism on cognitive impairment, brain structure atrophy, and change in the levels of CSF biomarkers.
All MCI subjects with an available baseline CSF sample from ADNI-1 were included (n = 193), and assigned an ES between 0 and 4 based on their baseline CSF biomarker profile.
By combining classical CSF biomarkers with twelve novel markers, the area of the ROC curves (AUROCS) of distinguishing AD and MCI/AD converters from non-AD were 93% and 96%, respectively.