Identification of a Simple and Novel Cut-Point Based Cerebrospinal Fluid and MRI Signature for Predicting Alzheimer’s Disease Progression that Reinforces the 2018 NIA-AA Research Framework

2019 ◽  
Vol 68 (2) ◽  
pp. 537-550 ◽  
Author(s):  
Priya Devanarayan ◽  
Viswanath Devanarayan ◽  
Daniel A. Llano ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Disease Progression ◽  
Research Framework ◽  
Cut Point

scholarly journals APPLICATION OF THE NIA-AA RESEARCH FRAMEWORK: TOWARDS A BIOLOGICAL DEFINITION OF ALZHEIMER’S DISEASE USING CEREBROSPINAL FLUID BIOMARKERS IN THE AIBL STUDY

2019 ◽  
pp. 1-8
Author(s):  
S.C Burnham ◽  
P.M. Coloma ◽  
Q.-X. Li ◽  
S. Collins ◽  
G. Savage ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Primary Care Physicians ◽  
Verbal Learning ◽  
Sensitivity Analyses ◽  
Csf Biomarkers ◽  
Pathologic Change ◽  
Research Framework ◽  
Definition Of

BACKGROUND: The National Institute on Aging and Alzheimer’s Association (NIA-AA) have proposed a new Research Framework: Towards a biological definition of Alzheimer’s disease, which uses a three-biomarker construct: Aß-amyloid, tau and neurodegeneration AT(N), to generate a biomarker based definition of Alzheimer’s disease. OBJECTIVES: To stratify AIBL participants using the new NIA-AA Research Framework using cerebrospinal fluid (CSF) biomarkers. To evaluate the clinical and cognitive profiles of the different groups resultant from the AT(N) stratification. To compare the findings to those that result from stratification using two-biomarker construct criteria (AT and/or A(N)). DESIGN: Individuals were classified as being positive or negative for each of the A, T, and (N) categories and then assigned to the appropriate AT(N) combinatorial group: A-T-(N)-; A+T-(N)-; A+T+(N)-; A+T-(N)+; A+T+(N)+; A-T+(N)-; A-T-(N)+; A-T+(N)+. In line with the NIA-AA research framework, these eight AT(N) groups were then collapsed into four main groups of interest (normal AD biomarkers, AD pathologic change, AD and non-AD pathologic change) and the respective clinical and cognitive trajectories over 4.5 years for each group were assessed. In two sensitivity analyses the methods were replicated after assigning individuals to four groups based on being positive or negative for AT biomarkers as well as A(N) biomarkers. SETTING: Two study centers in Melbourne (Victoria) and Perth (Western Australia), Australia recruited MCI individuals and individuals with AD from primary care physicians or tertiary memory disorder clinics. Cognitively healthy, elderly NCs were recruited through advertisement or via spouses of participants in the study. PARTICIPANTS: One-hundred and forty NC, 33 MCI participants, and 27 participants with AD from the AIBL study who had undergone CSF evaluation using Elecsys® assays. INTERVENTION (if any): Not applicable. MEASUREMENTS: Three CSF biomarkers, namely amyloid β1-42, phosphorylated tau181, and total tau, were measured to provide the AT(N) classifications. Clinical and cognitive trajectories were evaluated using the AIBL Preclinical Alzheimer Cognitive Composite (AIBL-PACC), a verbal episodic memory composite, an executive function composite, California Verbal Learning Test – Second Edition; Long-Delay Free Recall, Mini-Mental State Examination, and Clinical Dementia Rating Sum of Boxes scores. RESULTS: Thirty-eight percent of the elderly NCs had no evidence of abnormal AD biomarkers, whereas 33% had biomarker levels consistent with AD or AD pathologic change, and 29% had evidence of non-AD biomarker change. Among NC participants, those with biomarker evidence of AD pathology tended to perform worse on cognitive outcome assessments than other biomarker groups. Approximately three in four participants with MCI or AD had biomarker levels consistent with the research framework’s definition of AD or AD pathologic change. For MCI participants, a decrease in AIBL-PACC scores was observed with increasing abnormal biomarkers; and increased abnormal biomarkers were also associated with increased rates of decline across some cognitive measures. CONCLUSIONS: Increasing biomarker abnormality appears to be associated with worse cognitive trajectories. The implementation of biomarker classifications could help better characterize prognosis in clinical practice and identify those at-risk individuals more likely to clinically progress, for their inclusion in future therapeutic trials.

scholarly journals High Resolution Discovery Proteomics Reveals Candidate Disease Progression Markers of Alzheimer’s Disease in Human Cerebrospinal Fluid

PLoS ONE ◽  
2015 ◽  
Vol 10 (8) ◽  
pp. e0135365 ◽  
Author(s):  
Ronald C. Hendrickson ◽  
Anita Y. H. Lee ◽  
Qinghua Song ◽  
Andy Liaw ◽  
Matt Wiener ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
High Resolution ◽  
Disease Progression ◽  
Human Cerebrospinal Fluid ◽  
Progression Markers

Neuroimaging and Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease

2017 ◽  
Author(s):  
Brian A. Gordon ◽  
Stephanie J.B. Vos ◽  
Anne M. Fagan
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Disease Progression ◽  
Amyloid Plaques ◽  
Blood Tests ◽  
Preclinical Phase ◽  
Disease Modifying Therapies ◽  
Cerebrospinal Fluid Biomarkers ◽  
Neuroimaging Techniques

Alzheimer’s disease is characterized by a long asymptomatic (preclinical) phase during which disease-related pathology accumulates in the absence of overt cognitive symptoms. The most prominent neuropathologies are extracellular amyloid plaques and intraneuronal neurofibrillary tangles. Until recently such pathology was observable only at autopsy. Now these, and other novel pathological markers, can be measured in living individuals using cerebrospinal fluid assays, blood tests, and neuroimaging techniques to track disease progression. Understanding changes in these biomarkers is critical for diagnosis, monitoring disease progression, and for the development of disease-modifying therapies. This chapter reviews the current scientific understanding regarding the use of biomarkers to assess Alzheimer’s disease pathology.

Tracking of Alzheimer's disease progression with cerebrospinal fluid tau protein phosphorylated at threonine 231

2001 ◽  
Vol 49 (4) ◽  
pp. 545-546 ◽  
Author(s):  
Harald Hampel ◽  
Katharina Buerger ◽  
Russell Kohnken ◽  
Stefan J. Teipel ◽  
Raymond Zinkowski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Disease Progression ◽  
Tau Protein

Effect of Genetic Risk Factors and Disease Progression on the Cerebrospinal Fluid Tau Levels in Alzheimer's Disease

1997 ◽  
Vol 45 (10) ◽  
pp. 1228-1231 ◽  
Author(s):  
Hiroyuki Arai ◽  
Masanori Terajima ◽  
Masakazu Miura ◽  
Susumu Higuchi ◽  
Taro Muramatsu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Disease Progression ◽  
Genetic Risk ◽  
Genetic Risk Factors

Cerebrospinal fluid A?42 is increased early in sporadic Alzheimer's disease and declines with disease progression

1999 ◽  
Vol 45 (4) ◽  
pp. 504-511 ◽  
Author(s):  
Malene Jensen ◽  
Johannes Schr�der ◽  
Mari Blomberg ◽  
Benita Engvall ◽  
Johannes Pantel ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Disease Progression ◽  
Sporadic Alzheimer’S Disease
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