Fluid and imaging biomarkers for Alzheimer's disease: Where we stand and where to head to

Henriques, Adriane Dallanora; Benedet, Andréa Lessa; Camargos, Einstein Francisco; Rosa‐Neto, Pedro; Nóbrega, Otávio Tolêdo

doi:10.1016/j.exger.2018.01.002

Cited by 42 publications

(37 citation statements)

References 117 publications

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“…Although not yet used routinely for clinical diagnosis, biomarkers in AD have been employed in large research trials for estimating risk, establishing a diagnosis of preclinical AD or mild cognitive impairment (MCI) due to AD pathology, measuring the progression of AD, and ultimately, for better understanding of the underlying pathophysiology 7 . In delirium, inflammatory, neurodegenerative, metabolic, and neurotransmitter-based biomarkers 3 have been investigated as potential research tools for risk stratification, diagnosis, monitoring, and prognosis, though none have yet been validated for clinical applications, such as diagnosis or monitoring of delirium.…”

Section: Biomarkers Of Delirium and Admentioning

confidence: 99%

Delirium and Alzheimer disease: A proposed model for shared pathophysiology

Fong

Vasunilashorn

Libermann

et al. 2019

Int J Geriat Psychiatry

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Section: Biomarkers Of Delirium and Admentioning

confidence: 99%

Delirium and Alzheimer disease: A proposed model for shared pathophysiology

Fong

Vasunilashorn

Libermann

et al. 2019

Int J Geriat Psychiatry

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“…For example, cognitive and behavioral biomarkers have been proposed to identify individuals at high-risk for conversion [11-13]. In addition, biomarkers based on brain imaging or measurements in bodily fluids have been identified (for recent reviews see [14, 15]). The latter groups of biomarkers have recently been organized into a generalizable research framework.…”

Section: Introductionmentioning

confidence: 99%

Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer’s disease progression that reinforces the 2018 NIA-AA research framework

Devanarayan¹,

Devanarayan

Llano

2018

Preprint

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The 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.

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“…(5). Very limited number of senile plaques positive for Aβ [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] were found in the temporal lobe (A) and parietal lobe (B). Neurofibrillary tangle was moderately found in the parahippocampal gyrus (Gallyas staining) (C) and was positive for AT8 staining for phosphorylated tau (D).…”

Section: Tau Accumulation In Andementioning

confidence: 99%

Amyloid-Negative Dementia in the Elderly is Associated with High Accumulation of Tau in the Temporal Lobes

Takeuchi¹,

Kikukawa²,

Saito³

et al. 2019

TOBEJ

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Background: We previously reported that among cases clinically diagnosed with Alzheimer’s disease, the proportion of amyloid beta (Aβ) -negative case increases in the elderly population. Tauopathy including Argyrophilic Grain Disease (AGD) and Neurofibrillary Tangle-Predominant Dementia (NFTPD), may be the leading causes of such dementia. Objective: To evaluate the involvement of tau, we studied tau accumulation in Amyloid-Negative Dementia Cases in the Elderly (ANDE) with Positron Emission Tomography (PET). Methods: Seven cases with slowly progressive dementia who were older than 80 years and were negative for Aβ were studied. In one case, autopsy obtained 2 years after the PET examination revealed neurofibrillary tangles limited around the parahippocampal gyrus. Four cases showed strong laterality in magnetic resonance imaging atrophy (clinical AGD), while the other three cases had no significant laterality in atrophy (clinical NFTPD). Age-corrected PET data of healthy controls (HC; n = 12) were used as control. Tau accumulation was evaluated with [11C]PBB3-PET. Results: High accumulation was found in the lateral temporal cortex in ANDE. In autopsy case, scattered neurofibrillary tangles were found in the parahippocampal gyrus. In addition, there was a very high accumulation of PBB3 in the large area of bilateral parietal lobes, although no corresponding tau component was found in the autopsied case. Conclusion: Relatively high burden of tau deposition was commonly observed in the lateral temporal cortex and parietal cortex of ANDE, part of which may explain dementia in these subjects. [11C]PBB3 may be useful in detecting tauopathy in ANDE.

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Fluid and imaging biomarkers for Alzheimer's disease: Where we stand and where to head to

Cited by 42 publications

References 117 publications

Delirium and Alzheimer disease: A proposed model for shared pathophysiology

Delirium and Alzheimer disease: A proposed model for shared pathophysiology

Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer’s disease progression that reinforces the 2018 NIA-AA research framework

Amyloid-Negative Dementia in the Elderly is Associated with High Accumulation of Tau in the Temporal Lobes

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