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.

Background: Microbleeds in the brain have been shown to occur in Alzheimer’s disease (AD), affecting approximately a third of subjects that present with typical dementia of the Alzheimer’s type (DAT). However, little is known about the frequency or distribution of microbleeds in subjects with AD that present with atypical clinical presentations. Objective: To determine whether the frequency and regional distribution of microbleeds in atypical AD differs from that observed in subjects with DAT, and to determine whether microbleeds in atypical AD are associated with age, demographics, or cognitive impairment. Methods: Fifty-five subjects with amyloid-β deposition on Pittsburgh compound B (PiB) PET who presented with predominant language (n = 37) or visuospatial/perceptual (n = 18) deficits underwent T2*weighted MRI. These subjects were compared to 41 PiB-positive subjects with DAT. Microbleeds were identified and assigned a lobar location. Results: The proportion of subjects with microbleeds did not differ between atypical AD (42%) and DAT (32%). However, atypical AD had larger numbers of microbleeds than DAT. In addition, the topographic distribution of microbleeds differed between atypical AD and DAT, with atypical AD showing the highest density of microbleeds in the frontal lobes. Among atypical AD, number of microbleeds was associated with age, but not gender or cognition. Microbleeds were more common in subjects with language (51%) versus visuospatial/perceptual deficits (22%). Conclusions: Microbleeds are relatively common in both DAT and atypical AD, although atypical AD subjects appear to be at particular risk for developing large numbers of microbleeds and for developing microbleeds in the frontal lobe.

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.