NIA commentary on the NIA-AA Research Framework: Towards a biological definition of Alzheimer’s disease

2018 ◽  
Vol 14 (4) ◽  
pp. 576-578 ◽  
Author(s):  
Nina Silverberg ◽  
Cerise Elliott ◽  
Laurie Ryan ◽  
Eliezer Masliah ◽  
Richard Hodes
Author(s):  
S.C Burnham ◽  
P.M. Coloma ◽  
Q.-X. Li ◽  
S. Collins ◽  
G. Savage ◽  
...  

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.


2018 ◽  
Vol 14 (4) ◽  
pp. 535-562 ◽  
Author(s):  
Clifford R. Jack ◽  
David A. Bennett ◽  
Kaj Blennow ◽  
Maria C. Carrillo ◽  
Billy Dunn ◽  
...  

1997 ◽  
Vol 9 (4) ◽  
pp. 381-388 ◽  
Author(s):  
Clive Ballard ◽  
Ian McKeith ◽  
Richard Harrison ◽  
John O'Brien ◽  
Peter Thompson ◽  
...  

Visual hallucinations (VH) are a core feature of dementia with Lewy bodies (DLB), but little is known about their phenomenology. A total of 73 dementia patients (42 DLB, 30 Alzheimer's disease [AD], 1 undiagnosed) in contact with clinical services were assessed with a detailed standardized inventory. DLB was diagnosed according to the criteria of McKeith and colleagues, AD was diagnosed using the NINCDS-ADRDA criteria. Autopsy confirmation has been obtained when possible. VH were defined using the definition of Burns and colleagues. Detailed descriptions of hallucinatory experiences were recorded. Annual follow-up interviews were undertaken. The clinical diagnosis has been confirmed in 18 of the 19 cases that have come to autopsy. A total of 93% of DLB patients and 27% of AD patients experienced VH. DLB patients were significantly more likely to experience multiple VH that persisted over follow-up. They were significantly more likely to hear their VH speak but there were no significant differences in the other phenomenological characteristics including whether the hallucinations moved, the time of day that they were experienced, their size, the degree of insight, and whether they were complete. VH may be more likely to be multiple, to speak, and to be persistent in DLB patients. These characteristics could potentially aid accurate diagnosis.


1994 ◽  
Vol 39 (5) ◽  
pp. 253-257 ◽  
Author(s):  
Kenneth Rockwood ◽  
Karen Stadnyk

We reviewed the findings of the Canadian Study of Health and Aging in the context of studies published between January 1986 and June 1993 that documented dementia and Alzheimer's disease prevalence. Studies were identified using a MEDLINE literature search. Additional references were selected from the bibliography of identified articles. Most reports of all types of dementia prevalence are within a narrow range for each of the age groups 65+, 75+ and 85+ years. By contrast, two recent reports on the prevalence of Alzheimer's disease have reported much higher estimates (10.3% and 15.3%) in the elderly (65+ years). A variety of threats to both validity and generalizability of the estimates are present in all studies. In community studies which employed clinical interviews most subjects were only mildly affected; the natural history of impairment of this group requires further study if the consequences of these findings are to be understood. There is important variability in the definition of the functional consequences of cognitive impairment in the elderly which affects both the diagnosis and staging of dementia.


2018 ◽  
Author(s):  
Priya Devanarayan ◽  
Viswanath Devanarayan ◽  
Daniel A. Llano ◽  

AbstractThe 2018 NIA-AA research framework proposes a classification system with beta-Amyloid deposition, pathologic Tau, and neurodegeneration (ATN) for the diagnosis and staging of Alzheimer’s Disease (AD). Data from the ADNI (AD neuroimaging initiative) database can be utilized to identify diagnostic signatures for predicting AD progression, and to determine the utility of this NIA-AA research framework. Profiles of 320 peptides from baseline cerebrospinal fluid (CSF) samples of 287 normal, mild cognitive impairment (MCI) and AD subjects followed over a 3-10 year period were measured via multiple reaction monitoring (MRM) mass spectrometry. CSF Aβ42, total-Tau (tTau), phosphorylated-Tau (pTau-181) and hippocampal volume were also measured. From these candidate markers, optimal diagnostic signatures with decision thresholds to separate AD and normal subjects were first identified via unbiased regression and tree-based algorithms. The best performing signature determined via cross-validation was then tested in an independent group of MCI subjects to predict future progression. This multivariate analysis yielded a simple diagnostic signature comprising CSF pTau-181 to Aβ42 ratio, MRI hippocampal volume and a novel PTPRN peptide, with a decision threshold on each marker. When applied to a separate MCI group at baseline, subjects meeting this signature criteria experience 4.3-fold faster progression to AD compared to a 2.2-fold faster progression using only conventional markers. This novel 4-marker signature represents an advance over the current diagnostics based on widely used marker, and is much easier to use in practice than recently published complex signatures. In addition, this signature reinforces the ATN construct from the 2018 NIA-AA research framework.DisclosuresViswanath Devanarayan is an employee of Charles River Laboratories, and as such owns equity in, receives salary and other compensation from Charles River Laboratories.Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.;Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.


2018 ◽  
Vol 14 (2) ◽  
pp. 261-262 ◽  
Author(s):  
David S. Knopman ◽  
Eric R. Siemers ◽  
Lisa J. Bain ◽  
James A. Hendrix ◽  
Maria C. Carrillo

Biomedicines ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 457 ◽  
Author(s):  
Vanesa Cantón-Habas ◽  
Manuel Rich-Ruiz ◽  
Manuel Romero-Saldaña ◽  
Maria del Pilar Carrera-González

Preventing the onset of dementia and Alzheimer’s disease (AD), improving the diagnosis, and slowing the progression of these diseases remain a challenge. The aim of this study was to elucidate the association between depression and dementia/AD and to identify possible relationships between these diseases and different sociodemographic and clinical features. In this regard, a case-control study was conducted in Spain in 2018–2019. The definition of a case was: A person ≥ 65 years old with dementia and/or AD and a score of 5–7 on the Global Deterioration Scale (GDS). The sample consisted of 125 controls; among the cases, 96 had dementia and 74 had AD. The predictor variables were depression, dyslipidemia, type 2 diabetes mellitus, and hypertension. The results showed that depression, diabetes mellitus, and older age were associated with an increased likelihood of developing AD, with an Odds Ratio (OR) of 12.9 (95% confidence interval (CI): 4.3–39.9), 2.8 (95% CI: 1.1–7.1) and 1.15 (95% CI: 1.1–1.2), respectively. Those subjects with treated dyslipidemia were less likely to develop AD (OR 0.47, 95% CI: 0.22–1.1). Therefore, depression and diabetes mellitus increase the risk of dementia, whereas treated dyslipidemia has been shown to reduce this risk.


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