Central insights gained from the first cycle of AG041851 were that the combination of elevated amyloidosis and neurodegeneration greatly increased risk of clinical progression among both clinical normal and mildly impaired persons; and, a novel finding was the definition of an abnormal biomarker category characterized by positive neurodegeneration/neuronal injury biomarkers in the absence of amyloid. We labeled this category suspected non-Alzheimers pathophysiology (SNAP) on the assumption that it represented common non-AD pathologies - e.g., cerebrovascular disease, Lewy body disease, etc. Two modern diagnostic classification systems exist for Alzheimers disease (AD); the National Institute on Aging-Alzheimers Association (NIA-AA) and the International Working Group (IWG). SNAP is not addressed by either of these criteria, yet roughly of elderly clinically normal (CN) and mild cognitive impairment (MCI) persons fall into this category. In addition, neither the NIA-AA nor the IWG criteria include tau PET for classification. We recently led a large international group of senior investigators in proposing a new, descriptive classification scheme for AD biomarkers (Appendix). The seven most widely regarded AD biomarkers are used to create a 3-class biomarker classification scheme called the ATN system. In the ATN system, amyloid biomarkers are amyloid PET and CSF A?42 (denoted by A); tau biomarkers are tau PET and CSF p tau (denoted by T); and, neurodegeneration/neuronal injury biomarkers are FDG PET, anatomic MRI, and CSF t tau (denoted by N). Individuals are classified as positive or negative in each of the three categories leading to eight possible biomarker states (e.g., A-T-N-, A+T+N-, etc.). Neither the NIA-AA nor the IWG criteria categorize individuals in this way and neither addresses the implications of the eight different ATN biomarker permutations.
The aims of this renewal grant will focus on understanding the implications of categorizing individuals into these eight ATN classes. We will use amyloid PET to define A, tau PET to define T, and MRI cortical thickness to define N. Given the current emphasis on individuals who are clinically asymptomatic or have very early signs of cognitive impairment, we will concentrate on individuals who are CN and MCI at baseline.
Our aims are:
Aim 1 : To create fully imaged population-based cohorts of CN and MCI individuals aged 30?90 with baseline amyloid PET, tau PET, and MRI studies who will be followed clinically with visits every 15 months.
Aim 2 : To determine how clinical and demographic characteristics (e.g., age, sex, APOE, indicators of cerebrovascular disease, and baseline cognitive performance) vary across the eight ATN biomarker states.
Aim 3 : To estimate the age and sex specific prevalence rates of the eight ATN biomarker states.
Aim 4 : To determine the associations between the eight ATN biomarker states and cognitive or clinical outcomes and whether covariates (e.g., age, sex, APOE, and cerebrovascular disease) modify rates of cognitive decline.

Public Health Relevance

In this renewal application for AG041851, we proposed a new way of classifying individuals based on biomarkers used in Alzheimer's research. With this system, labeled ATN, Individuals are classified as positive or negative in each of three biomarker categories; amyloidosis (A), tau (T), neurodegeneration/neuronal injury (N), leading to eight possible biomarker states (e.g., A-T-N-, A+T+N-, etc.). We will use amyloid PET to define A, tau PET to define T, and MRI cortical thickness to define N in participants in the Mayo Clinic Study of Aging who are clinically normal or mildly impaired. Our aims focus on understanding the clinical and biological implications of categorizing individuals into these eight ATN states.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
2R01AG041851-06
Application #
9308121
Study Section
Clinical Neuroscience and Neurodegeneration Study Section (CNN)
Program Officer
Hsiao, John
Project Start
2012-04-01
Project End
2022-04-30
Budget Start
2017-05-15
Budget End
2018-04-30
Support Year
6
Fiscal Year
2017
Total Cost
$600,562
Indirect Cost
$190,585
Name
Mayo Clinic, Rochester
Department
Type
Other Domestic Non-Profits
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Jack Jr, Clifford R; Bennett, David A; Blennow, Kaj et al. (2018) NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement 14:535-562
Mielke, Michelle M; Hagen, Clinton E; Xu, Jing et al. (2018) Plasma phospho-tau181 increases with Alzheimer's disease clinical severity and is associated with tau- and amyloid-positron emission tomography. Alzheimers Dement 14:989-997
Wang, Qi; Guo, Lei; Thompson, Paul M et al. (2018) The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation1. J Alzheimers Dis 64:149-169
Ali, F; Whitwell, J L; Martin, P R et al. (2018) [18F] AV-1451 uptake in corticobasal syndrome: the influence of beta-amyloid and clinical presentation. J Neurol 265:1079-1088
Johnson, Derek R; Hunt, Christopher H; Nathan, Mark A et al. (2018) Pittsburgh compound B (PiB) PET imaging of meningioma and other intracranial tumors. J Neurooncol 136:373-378
Wennberg, Alexandra M V; Hagen, Clinton E; Edwards, Kelly et al. (2018) Association of antidiabetic medication use, cognitive decline, and risk of cognitive impairment in older people with type 2 diabetes: Results from the population-based Mayo Clinic Study of Aging. Int J Geriatr Psychiatry 33:1114-1120
Jack Jr, Clifford R; Wiste, Heather J; Schwarz, Christopher G et al. (2018) Longitudinal tau PET in ageing and Alzheimer's disease. Brain 141:1517-1528
Knopman, David S; Lundt, Emily S; Therneau, Terry M et al. (2018) Joint associations of ?-amyloidosis and cortical thickness with cognition. Neurobiol Aging 65:121-131
Vemuri, Prashanthi; Lesnick, Timothy G; Przybelski, Scott A et al. (2018) Development of a cerebrovascular magnetic resonance imaging biomarker for cognitive aging. Ann Neurol 84:705-716
Schwarz, Christopher G; Tosakulwong, Nirubol; Senjem, Matthew L et al. (2018) Considerations for Performing Level-2 Centiloid Transformations for Amyloid PET SUVR values. Sci Rep 8:7421

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