Jack, Clifford R

Background and purposeThe non‐fluent/agrammatic variant of primary progressive aphasia (agPPA) is a heterogeneous diagnosis wherein some individuals have apraxia of speech (AOS). When agPPA includes AOS, a tauopathy is the likely underlying pathology. Recently, [18F]AV‐1451 was developed for the in‐vivo assessment of tau. In this study, we compared patterns of tau tracer uptake in patients with agPPA with and without AOS.MethodsNine patients with agPPA (four without AOS) underwent tau positron emission tomography imaging with [18F]AV‐1451. Uptake of [18F]AV‐1451 was assessed as cortical to cerebellar crus ratio (standard uptake value ratio) in cortical regions of interest measured using the MCALT atlas and compared voxel‐wise in SPM12. Each patient was age‐ and sex‐matched to three controls.ResultsThe agPPA without AOS showed uptake in the left frontal and temporal lobes, whereas agPPA with AOS showed uptake in the bilateral supplementary motor areas, frontal lobes, precuneus and precentral gyrus relative to controls. The left precentral gyrus had uptake in agPPA with AOS relative to those without AOS.ConclusionsThis cross‐sectional study suggests that [18F]AV‐1451 uptake in the precentral gyrus is implicated in AOS in agPPA.

Background: There is accumulating evidence suggesting that diet may play a role in preventing or delaying cognitive decline and dementia, but the underlying biological mechanisms are not well understood. Objectives: To examine the cross-sectional associations of the Mediterranean diet (MeDi) and its components with 11 C-PiB-PET scan measures of amyloid-β (Aβ) deposition. Methods: The study consisted of 278 Mayo Clinic Study of Aging participants 70+ years old, who were cognitively unimpaired (CU) at the time of completion of the Food Frequency Questionnaire (FFQ) and when they underwent PET imaging. Adherence to the MeDi was assessed by computing the MeDi score for each participant. All scans were performed after the FFQ completion; median [IQR] time between FFQ and Aβ PET was 3.5 (1.4) years. Z-scores were created for component, macro- and micronutrients measured. Linear and logistic regression models were adjusted for age, sex, education, apolipoprotein E (APOE) ɛ4 allele carrier status, time interval between the FFQ completion and PET scan, and total energy intake. Results: Participants’ median age at FFQ was 77.7 years (55.8% men; 26.6% with an APOE ɛ4 allele). Higher MeDi score (linear regression slope (beta):–0.035, p = 0.012; per standard deviation increase), vegetable intake (beta:–0.043, p = 0.002), intake of vitamin A (beta:–0.041, p = 0.003) or β-carotene (beta: –0.039, p = 0.005) from food sources and moderate alcohol consumption (beta: –0.074, p = 0.03) were associated with lower 11 C-PiB standardized uptake value ratio. Conclusion: Findings are consistent with previous studies suggesting that higher adherence to a MeDi pattern and higher vegetable consumption are associated with better neuroimaging biomarker profile. Prospective studies are needed to validate current findings.

T1-weighted MRI has been extensively used to extract imaging biomarkers and build classification models for differentiating Alzheimer’s disease (AD) patients from healthy controls, but only recently have brain connectome networks derived from diffusion-weighted MRI been used to model AD progression and various stages of disease such as mild cognitive impairment (MCI). MCI, as a possible prodromal stage of AD, has gained intense interest recently, since it may be used to assess risk factors for AD. Little work has been done to combine information from both white matter and gray matter, and it is unknown how much classification power the diffusion-weighted MRI-derived structural connectome could provide beyond information available from T1-weighted MRI. In this paper, we focused on investigating whether diffusion-weighted MRI-derived structural connectome can improve differentiating healthy controls subjects from those with MCI. Specifically, we proposed a novel feature-ranking method to build classification models using the most highly ranked feature variables to classify MCI with healthy controls. We verified our method on two independent cohorts including the second stage of Alzheimer’s Disease Neuroimaging Initiative (ADNI2) database and the National Alzheimer’s Coordinating Center (NACC) database. Our results indicated that 1) diffusion-weighted MRI-derived structural connectome can complement T1-weighted MRI in the classification task; 2) the feature-rank method is effective because of the identified consistent T1-weighted MRI and network feature variables on ADNI2 and NACC. Furthermore, by comparing the top-ranked feature variables from ADNI2, NACC, and combined dataset, we concluded that cross-validation using independent cohorts is necessary and highly recommended.

AbstractThe Alzheimer's Association's Research Roundtable met in November 2017 to explore the new National Institute on Aging and the Alzheimer's Association Research Framework for Alzheimer's disease. The meeting allowed experts in the field from academia, industry, and government to provide perspectives on the new National Institute on Aging and the Alzheimer's Association Research Framework. This review will summarize the “A, T, N System” (Amyloid, Tau, and Neurodegeneration) using biomarkers and how this may be applied to clinical research and drug development. In addition, challenges and barriers to the potential adoption of this new framework will be discussed. Finally, future directions for research will be proposed.

Abstract In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six‐stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker‐based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker‐based research should not be considered a template for all research into age‐related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β‐amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

AbstractIntroductionWe examined and compared plasma phospho‐tau181 (pTau181) and total tau: (1) across the Alzheimer's disease (AD) clinical spectrum; (2) in relation to brain amyloid β (Aβ) positron emission tomography (PET), tau PET, and cortical thickness; and (3) as a screening tool for elevated brain Aβ.MethodsParticipants included 172 cognitively unimpaired, 57 mild cognitively impaired, and 40 AD dementia patients with concurrent Aβ PET (Pittsburgh compound B), tau PET (AV1451), magnetic resonance imaging, plasma total tau, and pTau181.ResultsPlasma total tau and pTau181 levels were higher in AD dementia patients than those in cognitively unimpaired. Plasma pTau181 was more strongly associated with both Aβ and tau PET. Plasma pTau181 was a more sensitive and specific predictor of elevated brain Aβ than total tau and was as good as, or better than, the combination of age and apolipoprotein E (APOE).DiscussionPlasma pTau181 may have utility as a biomarker of AD pathophysiology and as a noninvasive screener for elevated brain Aβ.

Abstract Introduction Neuroimaging modalities can measure different aspects of the disease process in Alzheimer's disease, although the relationship between these modalities is unclear. Methods We assessed subject‐level regional correlations between tau on [ 18 F]AV‐1451 positron emission tomography (PET), β amyloid on Pittsburgh compound B PET, hypometabolism on [ 18 F] fluorodeoxyglucose PET, and cortical thickness on magnetic resonance imaging in 96 participants with typical and atypical Alzheimer's disease presentations. We also assessed how correlations between modalities varied according to age, presenting syndrome, tau‐PET severity, and asymmetry. Results [ 18 F]AV‐1451 uptake showed the strongest regional correlation with hypometabolism. Correlations between [ 18 F]AV‐1451 uptake and both hypometabolism and cortical thickness were stronger in participants with greater cortical tau severity. In addition, age, tau asymmetry, and clinical diagnosis influenced the strength of the correlation between [ 18 F]AV‐1451 uptake and cortical thickness. Discussion These findings support a close relationship between tau and hypometabolism in Alzheimer's disease but show that correlations between neuroimaging modalities vary across participants.