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Objective To investigate the multifactorial processes underlying cognitive aging based on the hypothesis that multiple causal pathways and mechanisms (amyloid, vascular, and resilience) influence longitudinal cognitive decline in each individual through worsening brain health. Methods We identified 1,230 elderly subjects (aged ≥50 years) with an average of 4.9 years of clinical follow-up and with amyloid positron emission tomography, diffusion tensor imaging, and structural magnetic resonance imaging scans from the population-based Mayo Clinic Study of Aging. We examined imaging markers of amyloid and brain health (white matter microstructural integrity and cortical thinning), systemic vascular health preceding the imaging markers, and early to midlife intellectual enrichment to predict longitudinal cognitive trajectories. We used latent growth curve models for modeling longitudinal cognitive decline. Results All the pathways (amyloid, vascular, resilience) converged through their effects on cortical thinning and worsening cognition and together explained patterns in cognitive decline. Resilience and vascular pathways (aging process, sex differences, education/occupation, and systemic vascular health) had significant impact on white matter microstructural integrity. Education/occupation levels contributed to white matter integrity through systemic vascular health. Worsening white matter integrity contributed to significant cortical thinning and subsequently longitudinal cognitive decline. Baseline amyloidosis contributed to a significant proportion of cognitive decline that accelerated with longer follow-up times, and its primary impact was through cortical thinning. Interpretation We developed an integrated framework to help explain the dynamic and complex process of cognitive aging by considering key causal pathways. Such an approach is important for both better comprehension of cognitive aging processes and will aid in the development of successful intervention strategies. ANN NEUROL 2019;86:866-877.

BACKGROUND To operationalize the National Institute on Aging - Alzheimer's Association (NIA-AA) Research Framework for Alzheimer's Disease 6-stage continuum of clinical progression for persons with abnormal amyloid. METHODS The Mayo Clinic Study of Aging is a population-based longitudinal study of aging and cognitive impairment in Olmsted County, Minnesota. We evaluated persons without dementia having 3 consecutive clinical visits. Measures for cross-sectional categories included objective cognitive impairment (OBJ) and function (FXN). Measures for change included subjective cognitive impairment (SCD), objective cognitive change (ΔOBJ), and new onset of neurobehavioral symptoms (ΔNBS). We calculated frequencies of the stages using different cutoff points and assessed stability of the stages over 15 months. RESULTS Among 243 abnormal amyloid participants, the frequencies of the stages varied with age: 66 to 90% were classified as stage 1 at age 50 but at age 80, 24 to 36% were stage 1, 32 to 47% were stage 2, 18 to 27% were stage 3, 1 to 3% were stage 4 to 6, and 3 to 9% were indeterminate. Most stage 2 participants were classified as stage 2 because of abnormal ΔOBJ only (44-59%), whereas 11 to 21% had SCD only, and 9 to 13% had ΔNBS only. Short-term stability varied by stage and OBJ cutoff points but the most notable changes were seen in stage 2 with 38 to 63% remaining stable, 4 to 13% worsening, and 24 to 41% improving (moving to stage 1). INTERPRETATION The frequency of the stages varied by age and the precise membership fluctuated by the parameters used to define the stages. The staging framework may require revisions before it can be adopted for clinical trials. ANN NEUROL 2021;89:1145-1156.

Objective Recent availability of amyloid and tau positron emission tomography (PET) has provided us with a unique opportunity to measure the association of systemic vascular health with brain health after accounting for the impact of Alzheimer disease (AD) pathologies. We wanted to quantify early cerebrovascular health-related magnetic resonance imaging brain measures (structure, perfusion, microstructural integrity) and evaluate their utility as a biomarker for cerebrovascular health. Methods We used 2 independent samples (discovery, n = 390; validation, n = 1,035) of individuals, aged ≥ 60 years, along the cognitive continuum with imaging from the population-based sample of Mayo Clinic Study of Aging. We ascertained vascular health by summing up recently existing cardiovascular and metabolic conditions (CMC) from health care records (hypertension, hyperlipidemia, cardiac arrhythmias, coronary artery disease, congestive heart failure, diabetes mellitus, and stroke). Using multiple regression models, we quantified associations between CMC and brain health after accounting for age, sex, education/occupation, and AD burden (from amyloid and tau PET). Results Systemic vascular health was associated with medial temporal lobe thinning, widespread cerebral hypoperfusion, and loss of microstructural integrity in several white matter tracts including the corpus callosum and fornix. Further investigations suggested that microstructural integrity of the genu of the corpus callosum was suitable for assessing prodromal cerebrovascular health, had similar distributions in the discovery and independent validation datasets, and predicted cognitive performance above and beyond amyloid deposition. Interpretation Systemic vascular health has significant impact on brain structure and function. Quantifying prodromal cerebrovascular health-related brain measures that are independent of AD pathology-related changes has great utility for cognitive aging. Ann Neurol 2018;84:713-724.

Objective To investigate the associations between age, vascular health, and Alzheimer disease (AD) imaging biomarkers in an elderly sample. Methods We identified 430 individuals along the cognitive continuum aged >60 years with amyloid positron emission tomography (PET), tau PET, and magnetic resonance imaging (MRI) scans from the population-based Mayo Clinic Study of Aging. A subset of 329 individuals had fluorodeoxyglucose (FDG) PET. We ascertained presently existing cardiovascular and metabolic conditions (CMC) from health care records and used the summation of presence/absence of hypertension, hyperlipidemia, cardiac arrhythmias, coronary artery disease, congestive heart failure, diabetes mellitus, and stroke as a surrogate for vascular health. We used global amyloid from Pittsburgh compound B PET, entorhinal cortex tau uptake (ERC-tau) from tau-PET, and neurodegeneration in AD signature regions from MRI and FDG-PET as surrogates for AD pathophysiology. We dichotomized participants into CMC = 0 (CMC−) versus CMC > 0 (CMC+) and tested for age-adjusted group differences in AD biomarkers. Using structural equation models (SEMs), we assessed the impact of vascular health on AD biomarker cascade (amyloid leads to tau leads to neurodegeneration) after considering the direct and indirect age, sex, and apolipoprotein E effects. Results CMC+ participants had significantly greater neurodegeneration than CMC− participants but did not differ by amyloid or ERC-tau. The SEMs showed that (1) vascular health had a significant direct and indirect impact on neurodegeneration but not on amyloid; and (2) vascular health, specifically the presence of hyperlipidemia, had a significant direct impact on ERC-tau. Interpretation Vascular health had quantifiably greater impact on neurodegeneration in AD regions than on amyloid deposition. Longitudinal studies are warranted to clarify the relationship between tau deposition and vascular health. Ann Neurol 2017;82:706–718

Objective To investigate β-amyloid and tau depositions using Pittsburgh compound B (PiB) positron emission tomography (PET) and AV1451 tau PET imaging in aging multiple sclerosis (MS) patients. Methods Patients with MS (n = 16) and controls (n = 80) matched for age, sex, and APOE e4 status from the population-based Mayo Clinic Study of Aging who underwent PiB PET imaging were studied. Of these individuals, 12 patients with MS and 60 matching controls also underwent AV1451 tau PET. Cortical PiB and AV1451 standard uptake value ratios (SUVrs) from the entire cortex and previously determined Alzheimer disease (AD) signature regions in the same population were calculated for group comparisons and testing for associations with age. Results AD signature PiB SUVr (odds ratio [OR] [95% confidence interval (CI)] = 0.52 [0.27-0.98], p = 0.044), total cortical PiB SUVr (OR [95% CI] = 0.52 [0.28-0.99], p = 0.048), and the frequency of abnormal PiB SUVrs (OR [95% CI] = 0.10 [0.01-0.90], p = 0.040) were lower in MS than controls. Although AD-signature and total cortical AV1451 SUVrs were not different between the groups, the frequency of abnormal AV1451 SUVrs was higher (OR [95% CI] = 10.65 [1.10-103.35], p = 0.041) in MS than controls. The association of AD signature PiB SUVr with age was steeper in the controls compared to patients with MS (estimate [95% CI] = -0.14 [-0.023 to -0.006], p = 0.002). Similarly, the association of total cortical PiB SUVr with age was steeper in the controls compared to patients with MS (estimate [95% CI] = -0.13 [-0.021 to -0.005], p = 0.002). There was no difference in the association of AV1451 SUVr findings with age between the MS patients and controls. Interpretation Although both β-amyloid and tau are biomarkers of cognitive aging and AD, cortical β-amyloid deposition was lower in MS than age-matched controls, suggesting that some aspect of MS pathobiology retards the accumulation of β-amyloid but not the accumulation of tau. ANN NEUROL 2020;87:556-567.

To investigate the associations between age, vascular health, and Alzheimer disease (AD) imaging biomarkers in an elderly sample.We identified 430 individuals along the cognitive continuum aged60 years with amyloid positron emission tomography (PET), tau PET, and magnetic resonance imaging (MRI) scans from the population-based Mayo Clinic Study of Aging. A subset of 329 individuals had fluorodeoxyglucose (FDG) PET. We ascertained presently existing cardiovascular and metabolic conditions (CMC) from health care records and used the summation of presence/absence of hypertension, hyperlipidemia, cardiac arrhythmias, coronary artery disease, congestive heart failure, diabetes mellitus, and stroke as a surrogate for vascular health. We used global amyloid from Pittsburgh compound B PET, entorhinal cortex tau uptake (ERC-tau) from tau-PET, and neurodegeneration in AD signature regions from MRI and FDG-PET as surrogates for AD pathophysiology. We dichotomized participants into CMC = 0 (CMCCMCVascular health had quantifiably greater impact on neurodegeneration in AD regions than on amyloid deposition. Longitudinal studies are warranted to clarify the relationship between tau deposition and vascular health. Ann Neurol 2017;82:706-718.

Objective The new criteria for preclinical Alzheimer disease (AD) proposed 3 stages: abnormal levels of β-amyloid (stage 1), stage 1 plus evidence of brain injury (stage 2), and stage 2 plus subtle cognitive changes (stage 3). However, a large group of subjects with normal β-amyloid biomarkers have evidence of brain injury; we labeled them as the “suspected non-Alzheimer pathophysiology” (sNAP) group. The characteristics of the sNAP group are poorly understood. Methods Using the preclinical AD classification, 430 cognitively normal subjects from the Mayo Clinic Study of Aging who underwent brain magnetic resonance (MR), 18fluorodeoxyglucose (FDG), and Pittsburgh compound B positron emission tomography (PET) were evaluated for FDG PET regional volumetrics, MR regional brain volumetrics, white matter hyperintensity volume, and number of infarcts. We examined cross-sectional associations across AD preclinical stages, those with all biomarkers normal, and the sNAP group. Results The sNAP group had a lower proportion (14%) with apolipoprotein E e4 genotype than the preclinical AD stages 2 + 3. The sNAP group did not show any group differences compared to stages 2 + 3 of the preclinical AD group on measures of FDG PET regional hypometabolism, MR regional brain volume loss, cerebrovascular imaging lesions, vascular risk factors, imaging changes associated with α-synucleinopathy, or physical findings of parkinsonism. Interpretation Cognitively normal persons with brain injury biomarker abnormalities, with or without abnormal levels of β-amyloid, were indistinguishable on a variety of imaging markers, clinical features, and risk factors. The initial appearance of brain injury biomarkers that occurs in cognitively normal persons with preclinical AD may not depend on β-amyloidosis. ANN NEUROL 2013;73:472–480

Objectives To investigate the effect of intellectual and physical activity on biomarkers of Alzheimer’s disease (AD) pathophysiology and cognition in a non-demented elderly population. The biomarkers evaluated were brain Aβ-amyloid load via PIB-PET, neuronal dysfunction via FDG-PET and neurodegeneration via Structural-MRI.

Objective: A workgroup commissioned by the Alzheimer's Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer disease (AD). We performed a preliminary assessment of these guidelines. Methods: We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis, and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cutpoints. A group of 450 cognitively normal (CN) subjects from a population-based sample was used to develop cognitive cutpoints and to assess population frequencies of the different preclinical AD stages using different cutpoint criteria. Results: The new criteria subdivide the preclinical phase of AD into stages 1 to 3. To classify our CN subjects, 2 additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected non-AD pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cutpoints corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0, 16% stage 1, 12 % stage 2, 3% stage 3, and 23% SNAP. Interpretation: This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving only 3% unclassified. Future longitudinal validation of the criteria will be important ANN NEUROL 2012

Apolipoprotein E (APOE) e4 is the most important known genetic risk factor for typical late onset Alzheimer disease (AD). The lifetime risk of developing AD is increased and the age of onset of the disease is lowered with increasing number of APOE e4 alleles.1–4 Aβ1–42 and tau levels measured in cerebrospinal fluid (CSF) and atrophy seen on magnetic resonance imaging (MRI) are indicators of important disease-related pathological processes in AD. Low CSF Aβ1–42 reflects deposition of Aβ in plaques.5 High CSF t-tau levels reflect active axonal and neuronal damage.6 Atrophy seen on MRI is the direct result of loss of neurons, synapses, and dendritic arborization.7 In this paper, we use Structural Abnormality Index (STAND) scores as an indicator of severity of an AD-like pattern of atrophy on structural MRI. STAND scores were developed in our lab to condense the severity and location of AD-related atrophy on the 3-dimensional MRI scan into a single number.8 The effect of APOE genotype on neuronal pathology and amyloid load has been studied in autopsy specimens.9–13 Several in vivo CSF Aβ1–42 and t-tau studies,14–17 MRI studies,18–22 and fluorodeoxyglucose-positron emission tomography (PET) imaging studies23–25 have also studied the effect of APOE independently in each of these modalities. The first Alzheimer's Disease Neuroimaging Initiative (ADNI) CSF biomarker study also investigated the effect of APOE on CSF biomarkers, and found that Aβ1–42 concentration is lowest in subjects with 2 APOE e4 alleles and rises as the number of alleles decreases.26 However, there have not been in vivo studies that have investigated the influence of e4 allele on the surrogates of Aβ amyloid deposition and neuronal pathology together as measured by CSF and MRI in a cohort of subjects that spans the cognitive spectrum. The main aim of our paper was to evaluate the effect of APOE genotype on biomarkers of Aβ amyloid load and neuronal pathology by answering these questions: (1) How does APOE genotype effect CSF Aβ1–42 and t-tau levels and atrophy on MRI within each clinical group? (2) How does APOE genotype affect biomarker discrimination between different clinical groups (cognitively normal [CN], amnestic mild cognitive impairment [aMCI], AD)? (3) How much of the variability in the biomarkers is explained by clinical diagnosis versus APOE genotype? and (4) Does the relationship between continuous measures of cognitive performance and the biomarkers differ by APOE genotype?