BackgroundNeuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD.Methods445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants.FindingsWe found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (β = 0.59), but then tau burden elevated relative to spread (β = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83).InterpretationTau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design.FundingThis research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund.

Background Driving is a complex behavior that may be affected by early changes in the cognition of older individuals. Early changes in driving behavior may include driving more slowly, making fewer and shorter trips, and errors related to inadequate anticipation of situations. Sensor systems installed in older drivers’ vehicles may detect these changes and may generate early warnings of possible changes in cognition. Method A naturalistic longitudinal design is employed to obtain continuous information on driving behavior that will be compared with the results of extensive cognitive testing conducted every 3 months for 3 years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data downloaded every 3 months when the cognitive tests are administered. Results Data processing and analysis will proceed through a series of steps including data normalization, adding information on external factors (weather, traffic conditions), and identifying critical features (variables). Traditional prediction modeling results will be compared with Recurring Neural Network (RNN) approach to produce Driver Behavior Indices (DBIs), and algorithms to classify drivers within age, gender, ethnic group membership, and other potential group characteristics. Conclusion It is well established that individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decrements. Current screening and evaluation services can test only a small number of individuals with cognitive concerns, missing many who need to know if they require treatment. Given the increasing number of sensors being installed in passenger vehicles and pick-up trucks and their increasing acceptability, reconfigured in-vehicle sensing systems could provide widespread, low-cost early warnings of cognitive decline to the large number of older drivers on the road in the U.S. The proposed testing and evaluation of a readily and rapidly available, unobtrusive in-vehicle sensing system could provide the first step toward future widespread, low-cost early warnings of cognitive change for this large number of older drivers in the U.S. and elsewhere.

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.

Theoretical frameworks have successfully guided researchers in implementing coaching interventions to effect dietary changes in adults for both prevention and management of chronic diseases. Three such frameworks include the Transtheoretical Model (TTM), Social Cognitive Theory (SCT), and the Theory of Integrative Nurse Coaching (TINC). This article introduces each theory, followed by an overview of the coaching interventions used to effect dietary behaviour changes within each theory. A condensed version of Turner's synthesis methodology is used to determine if a conceptual connection exists among the three models/theories. The condensed version includes synthesis preparation, synthesis (comparison of converging and diverging components), synthesis refinement (conceptual connection), and a concluding discussion of all three theories related to nursing practice. This synthesis will inform the focus of interventions that aim to promote dietary changes in adults at risk of developing sarcopenia.

Abstract Introduction Structural magnetic resonance imaging is a marker of gray matter health and decline that is sensitive to impaired cognition and Alzheimer's disease pathology. Prior work has shown that both amyloid β (Aβ) and tau biomarkers are related to cortical thinning, but it is unclear what unique influences they have on the brain. Methods Aβ pathology was measured with [18F] AV‐45 (florbetapir) positron emission tomography (PET) and tau was assessed with [18F] AV‐1451 (flortaucipir) PET in a population of 178 older adults, of which 123 had longitudinal magnetic resonance imaging assessments (average of 5.7 years) that preceded the PET acquisitions. Results In cross‐sectional analyses, greater tau PET pathology was associated with thinner cortices. When examined independently in longitudinal models, both Aβ and tau were associated with greater antecedent loss of gray matter. However, when examined in a combined model, levels of tau, but not Aβ, were still highly related to change in cortical thickness. Discussion Measures of tau PET are strongly related to gray matter atrophy and likely mediate relationships between Aβ and gray matter.

April 24, 2018April 10, 2018Free AccessIn Vivo [18F]-AV-1451 Tau-PET Imaging in Sporadic Creutzfeldt-Jakob Disease (P3.034)Gregory Day, Brian A. Gordon, Richard Perrin, Nigel Cairns, Helen Beaumont, Katherine Schwetye, Cole Ferguson, … Show All … , Namita Sinha, Robert Bucelli, Erik Musiek, Nupur Ghoshal, Maria Rosana Ponisio, Benjamin Vincent, Shruti Mishra, Kelley Jackson, John Morris, Tammie Benzinger, and Beau Ances Show FewerAuthors Info & AffiliationsApril 10, 2018 issue90 (15_supplement)https://doi.org/10.1212/WNL.90.15_supplement.P3.034 Letters to the Editor

Our previous studies demonstrated that the aerobic glycolysis (AG, non-oxidative part of brain glucose metabolism), a marker of metabolic functions involved in synaptic plasticity and neuroprotection, declines with age on the whole brain level. This decline is greatest in regions known to accumulate a high density of beta-amyloid plaques in Alzheimer's disease (AD). These observations suggest that there is a substantial age-related loss in metabolic brain reserve supporting synaptic plasticity and neuroprotection that may introduce a selective vulnerability to processes leading to AD pathology and cognitive decline. Neurofibrillary tau pathology is a marker of cell death and dysfunction but little is known about the relationship between regional AG and tau pathology in the human brain in vivo. Our previous tau PET imaging studies with AV-1451 demonstrated tau deposition in several brain regions, including enthorhinal, temporal, lateral occipital, and parietal cortex. Here we present our preliminary evaluation of the relationship between AG, metabolism, blood flow and tau deposition. Thirty five individuals (32 cognitively normal, 15 females, 53–88 years old) underwent PET studies using inhalation of 15O-CO and 15O-O2, and injection of 15O-water, 18F-fluorodeoxyglucose, and [18F]-AV-1451. AG, cerebral metabolic rate of glucose (CMRGlu) and oxygen (CMRO2), cerebral blood flow (CBF), and tau deposition were calculated and corrected for partial volume effects in regions of interest defined using FreeSurfer. Association between AG, CMRGlu, CMRO2, CBF and AV-1451 deposition was evaluated using linear regression models, both unadjusted and adjusted for age and gender. A negative correlation was demonstrated between tau deposition and AG in lateral occipital, inferior and superior parietal cortices, suggesting that higher AG levels are associated with less tau deposition. This association remained significant after adjusting for age and gender for lateral occipital (F1,31=8.632, p=0.006) and superior parietal (F1,31=12.367, p=0.001). Tau deposition correlated to CMRGlu in superior parietal cortex (F1,31=4.856; p=0.035). No correlation was demonstrated between tau deposition and CMRO2 and CBF. Our findings support the hypothesis that in regions known to accumulate AD pathology, higher levels of AG are associated with lower pathological burden, suggesting that high AG promotes resilience to progression of AD pathology.

Neurofibrillary tau pathology is a marker of neurodegeneration and can be evaluated using the PET tracer [18F]-AV-1451 (flortaucipir, T807). Many studies have added tau imaging to ongoing longitudinal cohorts. We wanted to evaluate whether longitudinal MRI scans could predict tau PET positivity in preclinical and symptomatic Alzheimer disease (AD). 87 cognitively normal (with CDR=0) and 14 cognitively impaired (CDR> 0, 9 CDR 0.5, 3 CDR 1, and 2 CDR 2) participants were drawn from studies on aging at Washington University in St. Louis. Participants had one or more MRI sessions preceding a visit where they acquired both a MRI scan and underwent PET imaging with AV-1451, with mean follow-up from first MRI of 5.3 (sd 2.3) yrs. A subset (n = 93) also underwent florbetapir beta-amyloid imaging. MRIs were processed using FreeSurfer to generate mean cortical thickness in each region of interest (ROI). PET data was converted to standardized uptake value ratios (SUVRs) normalized to the cerebellum and partial volume corrected. Global tau burden was estimated by the mean SUVR from entorhinal cortex, amygdala, inferior temporal cortex, and lateral occipital cortex ROIs. For each person, a slope estimating structural atrophy in each ROI was quantified by fitting all longitudinal MRI measurements in a generalized linear model (GLM). These slope estimates were then used to predict tau burden in a GLM while controlling for baseline age and gender. Participants who also had beta-amyloid imaging were fit into a second GLM, with an additional covariate of florbetapir mean cortical SUVR. Multiple comparisons were controlled using a false discovery rate. Antecedent cortical thinning was significantly associated with tau deposition throughout the cortex in the entire cohort (Figure 1). The effects were most prominent in the lateral temporal lobe and inferior parietal areas. These associations remained even after controlling for florbetapir levels (Figure 2) and were evident even in cognitively normal cohorts alone (Figure 3). Antecedent cortical thinning predicts current PET Tau in preclinical AD and symptomatic AD. This relationship holds in AD even after controlling for PET beta-amyloid burden. This may be useful for participant selection for tau PET imaging or clinical trials. Relationship between antecedent cortical atrophy and current PET Tau, controlling for baseline age and gender in cognitively normal and AD participants. Relationship between antecedent cortical atrophy and current PET Tau, controlling for baseline age, gender, and current florbetapir mean cortical SUVR in cognitively normal and AD participants. Relationship between antecedent cortical atrophy and current PET Tau, controlling for baseline age and gender in cognitively normal participants.

Utilizing [18F]-AV-1451 tau positron emission tomography (PET) as an Alzheimer disease (AD) biomarker will require identification of brain regions that are most important in detecting elevated tau pathology in preclinical AD. Here, we utilized an unsupervised learning, data-driven approach to identify brain regions whose tau PET is most informative in discriminating low and high levels of [18F]-AV-1451 binding. 84 cognitively normal participants who had undergone AV-1451 PET imaging were used in a sparse k-means clustering with resampling analysis to identify the regions most informative in dividing a cognitively normal population into high tau and low tau groups. The highest-weighted FreeSurfer regions of interest (ROIs) separating these groups were the entorhinal cortex, amygdala, lateral occipital cortex, and inferior temporal cortex, and an average SUVR in these four ROIs was used as a summary metric for AV-1451 uptake. We propose an AV-1451 SUVR cut-off of 1.25 to define high tau as described by imaging. This spatial distribution of tau PET is a more widespread pattern than that predicted by pathological staging schemes. Our data-derived metric was validated first in this cognitively normal cohort by correlating with early measures of cognitive dysfunction, and with disease progression as measured by β-amyloid PET imaging. We additionally validated this summary metric in a cohort of 13 Alzheimer disease patients, and showed that this measure correlates with cognitive dysfunction and β-amyloid PET imaging in a diseased population.

Neurofibrillary tau pathology is a marker of neurodegeneration and can be evaluated using the PET tracer [18F]-AV-1451 (flortaucipir, T807). Many studies have added tau imaging to ongoing longitudinal cohorts. We wanted to evaluate whether longitudinal MRI scans could predict tau PET positivity in preclinical and symptomatic Alzheimer disease (AD). 87 cognitively normal (with CDR=0) and 14 cognitively impaired (CDR> 0, 9 CDR 0.5, 3 CDR 1, and 2 CDR 2) participants were drawn from studies on aging at Washington University in St. Louis. Participants had one or more MRI sessions preceding a visit where they acquired both a MRI scan and underwent PET imaging with AV-1451, with mean follow-up from first MRI of 5.3 (sd 2.3) yrs. A subset (n = 93) also underwent florbetapir beta-amyloid imaging. MRIs were processed using FreeSurfer to generate mean cortical thickness in each region of interest (ROI). PET data was converted to standardized uptake value ratios (SUVRs) normalized to the cerebellum and partial volume corrected. Global tau burden was estimated by the mean SUVR from entorhinal cortex, amygdala, inferior temporal cortex, and lateral occipital cortex ROIs. For each person, a slope estimating structural atrophy in each ROI was quantified by fitting all longitudinal MRI measurements in a generalized linear model (GLM). These slope estimates were then used to predict tau burden in a GLM while controlling for baseline age and gender. Participants who also had beta-amyloid imaging were fit into a second GLM, with an additional covariate of florbetapir mean cortical SUVR. Multiple comparisons were controlled using a false discovery rate. Antecedent cortical thinning was significantly associated with tau deposition throughout the cortex in the entire cohort (Figure 1). The effects were most prominent in the lateral temporal lobe and inferior parietal areas. These associations remained even after controlling for florbetapir levels (Figure 2) and were evident even in cognitively normal cohorts alone (Figure 3). Antecedent cortical thinning predicts current PET Tau in preclinical AD and symptomatic AD. This relationship holds in AD even after controlling for PET beta-amyloid burden. This may be useful for participant selection for tau PET imaging or clinical trials.

Neurofibrillary tau pathology is a marker of neurodegeneration and can be evaluated using the PET tracer [18F]-AV-1451 (flortaucipir, T807). Many studies have added tau imaging to ongoing longitudinal cohorts. We wanted to evaluate whether longitudinal MRI scans could predict tau PET positivity in preclinical and symptomatic Alzheimer disease (AD). 87 cognitively normal (with CDR=0) and 14 cognitively impaired (CDR> 0, 9 CDR 0.5, 3 CDR 1, and 2 CDR 2) participants were drawn from studies on aging at Washington University in St. Louis. Participants had one or more MRI sessions preceding a visit where they acquired both a MRI scan and underwent PET imaging with AV-1451, with mean follow-up from first MRI of 5.3 (sd 2.3) yrs. A subset (n = 93) also underwent florbetapir beta-amyloid imaging. MRIs were processed using FreeSurfer to generate mean cortical thickness in each region of interest (ROI). PET data was converted to standardized uptake value ratios (SUVRs) normalized to the cerebellum and partial volume corrected. Global tau burden was estimated by the mean SUVR from entorhinal cortex, amygdala, inferior temporal cortex, and lateral occipital cortex ROIs. For each person, a slope estimating structural atrophy in each ROI was quantified by fitting all longitudinal MRI measurements in a generalized linear model (GLM). These slope estimates were then used to predict tau burden in a GLM while controlling for baseline age and gender. Participants who also had beta-amyloid imaging were fit into a second GLM, with an additional covariate of florbetapir mean cortical SUVR. Multiple comparisons were controlled using a false discovery rate. Antecedent cortical thinning was significantly associated with tau deposition throughout the cortex in the entire cohort (Figure 1). The effects were most prominent in the lateral temporal lobe and inferior parietal areas. These associations remained even after controlling for florbetapir levels (Figure 2) and were evident even in cognitively normal cohorts alone (Figure 3). Antecedent cortical thinning predicts current PET Tau in preclinical AD and symptomatic AD. This relationship holds in AD even after controlling for PET beta-amyloid burden. This may be useful for participant selection for tau PET imaging or clinical trials. Relationship between antecedent cortical atrophy and current PET Tau, controlling for baseline age and gender in cognitively normal and AD participants. Relationship between antecedent cortical atrophy and current PET Tau, controlling for baseline age, gender, and current florbetapir mean cortical SUVR in cognitively normal and AD participants. Relationship between antecedent cortical atrophy and current PET Tau, controlling for baseline age and gender in cognitively normal participants.

Background: Flortaucipir (tau) positron emission tomography (PET) binding distinguishes individuals with clinically well-established posterior cortical atrophy (PCA) due to Alzheimer disease (AD) from cognitively normal (CN) controls. However, it is not known whether tau-PET binding patterns differentiate individuals with PCA from those with amnestic AD, particularly early in the symptomatic stages of disease. Methods: Flortaucipir and florbetapir (β-amyloid) PET imaging were performed in individuals with early-stage PCA (N=5), amnestic AD dementia (N=22), and CN controls (N=47). Average tau and β-amyloid deposition were quantified using standard uptake value ratios and compared at a voxelwise level, controlling for age. Results: PCA patients [median age-at-onset, 59 (51 to 61) years] were younger at symptom onset than similarly staged individuals with amnestic AD [75 (60 to 85) years] or CN controls [73 (61 to 90) years; P =0.002]. Flortaucipir uptake was higher in individuals with early-stage symptomatic PCA versus those with early-stage amnestic AD or CN controls, and greatest in posterior regions. Regional elevations in florbetapir were observed in areas of greatest tau deposition in PCA patients. Conclusions and Relevance: Flortaucipir uptake distinguished individuals with PCA and amnestic AD dementia early in the symptomatic course. The posterior brain regions appear to be uniquely vulnerable to tau deposition in PCA, aligning with clinical deficits that define this disease subtype.

The e4 allele of apolipoprotein E (apoe4) is associated with increased risk of developing Alzheimer disease (AD). The purpose this study is to evaluate the effects of the e4 allele on longitudinal changes in cortical thickness, volume, and beta-amyloid accumulation as measured by magnetic resonance imaging (MRI) and positron emission tomography (PET) with Pittsburgh Compound B (PiB) in a cognitively normal population. Participants were drawn from ongoing studies on aging at Washington University in St. Louis. 249 participants who were cognitively normal (with Clinical Dementia Rating 0) at baseline underwent >= 2 serial PiB PET scans with mean follow-up of 4.9 (sd 2.2) yrs. 13 converted to CDR status > 0. 508 participants underwent >= 2 serial MRIs with mean follow-up of 5.5 (sd 3.1) years. Of these, 90 converted to CDR status > 0. Volumetric segmentation was performed using FreeSurfer to generate mean cortical thickness for each region of interest (ROI). PiB PET standardized uptake value ratios (SUVRs) were normalized to cerebellum cortex and partial volume corrected. ROI volumes were normalized to intracranial volume. Participants were categorized as apoe4 +/- based upon the presence of the apoe4 allele. Using a ROI-based analysis, linear mixed effects models were used to evaluate the role of apoe4 status on the rate of change of cortical thickness, volume, or PiB SUVR, while controlling for baseline age and gender. Presence of the apoe4 allele did not have an effect on longitudinal cortical thickness or volume in any anatomic region of interest. Presence of the apoe4 allele increased the rate of PiB accumulation throughout the brain. The age at which the rate of PiB accumulation diverged between apoe4 positive and negative individuals is earlier in certain brain regions (i.e. precuneus before the visual cortex).

The e4 allele of apolipoprotein E (apoe4) is associated with increased risk of developing Alzheimer disease (AD). The purpose this study is to evaluate the effects of the e4 allele on longitudinal changes in cortical thickness, volume, and beta-amyloid accumulation as measured by magnetic resonance imaging (MRI) and positron emission tomography (PET) with Pittsburgh Compound B (PiB) in a cognitively normal population. Participants were drawn from ongoing studies on aging at Washington University in St. Louis. 249 participants who were cognitively normal (with Clinical Dementia Rating 0) at baseline underwent >= 2 serial PiB PET scans with mean follow-up of 4.9 (sd 2.2) yrs. 13 converted to CDR status > 0. 508 participants underwent >= 2 serial MRIs with mean follow-up of 5.5 (sd 3.1) years. Of these, 90 converted to CDR status > 0. Volumetric segmentation was performed using FreeSurfer to generate mean cortical thickness for each region of interest (ROI). PiB PET standardized uptake value ratios (SUVRs) were normalized to cerebellum cortex and partial volume corrected. ROI volumes were normalized to intracranial volume. Participants were categorized as apoe4 +/- based upon the presence of the apoe4 allele. Using a ROI-based analysis, linear mixed effects models were used to evaluate the role of apoe4 status on the rate of change of cortical thickness, volume, or PiB SUVR, while controlling for baseline age and gender. Presence of the apoe4 allele did not have an effect on longitudinal cortical thickness or volume in any anatomic region of interest. Presence of the apoe4 allele increased the rate of PiB accumulation throughout the brain. The age at which the rate of PiB accumulation diverged between apoe4 positive and negative individuals is earlier in certain brain regions (i.e. precuneus before the visual cortex).

As with any dementia, Alzheimer's disease (AD) treatment relies on an accurate diagnosis. Regional atrophy is an early imaging biomarker for AD and may have a diagnostic utility. Using FreeSurfer segmentations in a normative cohort, we generated Individual Longitudinal Participant (ILP) reports at a single participant level. We then evaluated the ability of these reports to identify individuals at risk for AD. A Super Normal Cohort (SNC) was assembled from MRIs of cognitively normal individuals (n=196, age range=43-90) obtained from the Knight Alzheimer's Disease Research Center. The SNC exclude individuals with high levels of AD pathology (CSF and amyloid PET), and all subjects remained nondemented for at least three years after MRI collection. Freesurfer volumes were normalized to intra-cranial volume and then used to generate a LOESS weighted regression. This regression was then be used to generate age-adjusted regional volumetric z-scores presented in the ILP. To explicitly test the utility of the SNC, a classifier cohort (CC) was generated from a combination of the SNC and a population of participants likely to have AD based on clinical diagnosis and biomarker evaluation. The CC's z-scores were put through lasso multivariate analysis. Predicting potential AD in a given individuals based upon a single MR via lasso regression model yielded a 33 percent false negative rate amongst those individuals known to have AD while providing 17 percent false positive rate among those individuals in the SNC.