Jack, Clifford R

Abstract INTRODUCTION We investigated the association between alpha‐synuclein (α‐syn) pathology and brain glucose metabolism across the cognitive spectrum of Alzheimer's disease (AD) co‐pathologies. METHODS Fluorodeoxyglucose positron emission tomography (FDG‐PET) data from 829 Alzheimer's Disease Neuroimaging Initiative participants (648 cognitively impaired [CI], 181 unimpaired [CU]) were compared between α‐syn seed amplification assay (SAA) positive and negative groups. Interactions with cerebrospinal fluid (CSF) AD biomarkers were examined. RESULTS SAA+ was associated with widespread hypometabolism among CI individuals, particularly in posterior cortical regions, independent of CSF amyloid and tau levels in the occipital lobes. Regional hypometabolism mediated the effect of α‐syn SAA on disease severity in CI individuals, independent of CSF amyloid and tau levels. There were no influences of SAA on FDG‐PET in CU individuals. DISCUSSION This study supports a model in which α‐syn aggregation influences metabolic dysfunction, which then influences clinical disease severity, independent of AD. SAA+ could help optimize participant selection and outcome measures for clinical trials in AD. Highlights α‐synuclein seed amplification positivity (SAA+) was associated with hypometabolism in cognitively impaired individuals. Hypometabolism mediated the influence of α‐synuclein on disease severity. Occipital hypometabolism in SAA+ was independent of cerebrospinal fluid levels of Alzheimer's disease pathology. These findings can optimize future clinical trials targeting α‐synuclein pathology.

Background: Cerebral microbleeds (CMBs) are associated with incident dementia, but the impact of specific CMB patterns is unclear. CMBs in lobar regions suggest cerebral amyloid angiopathy (CAA), which is sometimes accompanied by superficial siderosis (SS), while subcortical CMBs indicate hypertensive origins. This study investigates the association between CMB patterns and dementia risk in the community-based longitudinal Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS). Methods: All ARIC-NCS participants with a 3T research MRI at visit 5 (2011-13; aged 67-90) without intracerebral hemorrhage or dementia were included. CMB and SS presence and location were coded from T2* GRE sequences. Individuals were classified into one of four patterns: no CMBs, only subcortical, mixed (lobar and/or SS + subcortical), and only lobar and/or SS. Incident dementia diagnoses were defined by cognitive testing (in-person and telephone), informant interviews, and hospital discharge codes or death certificates. Cox proportional-hazards models assessed the association between the presence, patterns, and frequency of CMBs (0,1,2,3+), presence of SS, and incident dementia from visit 5 through 2020. Model covariates included demographics, vascular risk factors, and imaging markers of small vessel disease. Results: Among 1609 participants, 364 had CMBs (Table 1). Participants with CMBs tended to be older and female compared to those without CMBs. Compared to individuals with no CMBs, presence of any CMBs was associated with an increased risk of dementia (Table 2). Compared to individuals without CMBs, individuals with only lobar CMBs and/or SS had an increased risk of incident dementia, as did individuals with mixed CMBs, but individuals with subcortical-only did not. Participants with ≥3 CMBs of any variant had an increased risk of incident dementia vs no CMBs. Although SS was infrequent, its presence (vs no SS) was associated with an elevated risk of dementia. Conclusion: CMBs, particularly in a mixed or lobar and/or SS-only pattern, are linked to an increased risk of incident dementia. The number of recurrent CMBs and any SS also showed an increased dementia risk. These data support that dementia risk is high in individuals with a CAA-type CMB pattern, but also emphasize that a mixed pattern, not typical of CAA alone, is associated with a high risk of dementia. Further studies should evaluate mechanisms by which these different patterns contribute to dementia.

Background Mild cognitive impairment (MCI) represents a stage between cognitively normal and Alzheimer's disease. Despite much published research on MCI, there continues to be a knowledge gap of volumetric brain changes in MCI versus cognitively normal (CN) in racially diverse, community-based samples. Objective The study aimed to understand differences in volume of selected brain regions in individuals with MCI versus those who are cognitively normal. Methods This was a cross-sectional study with 1835 participants, which sampled all cognitively impaired participants (n = 667) and a subsample of cognitively normal participants from the ARIC neurocognitive study (ARIC-NCS). All individuals underwent a brain MRI. Two models (5 versus 22 regions of interest [ROI]) were built to analyze differences in brain volume between cognitively normal and MCI, and among 3 cognitive domains (memory, language, executive function). Using previous visits data, we estimated the standard deviations of 20-year cognitive decline equivalent to the difference in brain volume between MCI and CN. Results Every lobe was significantly smaller in individuals with MCI, with the largest difference observed in the temporal lobe. Moreover, there was a significant difference between MCI and CN in every subregion within the temporal lobe. The difference in volume between CN and MCI was equivalent to the total brain volume difference associated with a 1.24 standard deviation greater long-term cognitive decline. Conclusions Loss of volume in all cortical lobes, but particularly in the temporal lobe, was associated with MCI. Additionally, significant volume differences were observed in the temporal lobe in all three cognitive domains.

Abstract INTRODUCTION We aimed to compare gait between individuals with Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and cognitively unimpaired (CU) individuals and to evaluate the association between gait and regional amyloid beta (Aβ) burden in AD and DLB. METHODS We included 420 participants (70 AD, 70 DLB, 280 CU) in the Mayo Clinic Study of Aging (MCSA). Gait was assessed using a pressure‐sensor walkway. Aβ deposition was analyzed with Pittsburgh compound B (PiB) positron emission topography (PET). RESULTS The DLB group had reduced stride velocity, step length, and stride width variability, as well as increased double support percentage (%DS) and variability in step length, swing time, and step time compared to the AD and CU groups. Aβ burden was not associated with any gait outcomes. DISCUSSION This study provides additional evidence that gait differs between AD and DLB. Larger studies are needed to investigate associations between Aβ burden and gait outcomes in dementia. Highlights Gait was more impaired in dementia than in cognitively unimpaired (CU) controls. Compared with Alzheimer's disease (AD), Dementia with Lewy bodies (DLB) had more impaired pace, variability, and postural control. Step length and double support (%) distinguished DLB and AD with moderate accuracy.

Abstract INTRODUCTION Greater white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) are seen with transactive response DNA‐binding protein 43 (TDP‐43) pathology in frontotemporal lobar degeneration (FTLD‐TDP). WMH associations with TDP‐43 pathology in Alzheimer's disease (AD‐TDP) remain unclear. METHODS A total of 157 participants from Mayo Clinic Rochester with autopsy‐confirmed AD, known TDP‐43 status, and antemortem fluid‐attenuated inversion recovery (FLAIR) MRI were included. Vascular risk factors were assessed. A semi‐automated WMH segmentation‐quantification process produced total and regional WMH volumes. Penalized linear regression models adjusting for age at MRI analyzed TDP‐43 associations (status and typing) with WMHs. RESULTS TDP‐43‐positive status was not associated with WMH burden overall because opposite effects were seen based on AD‐TDP typing. Despite similar antemortem vascular risk factors and postmortem vascular pathologies, AD‐TDP type‐ α showed greater total and regional WMH burden (particularly in subcortical frontotemporal and basal ganglia regions) than TDP‐43 negatives and AD‐TDP type‐ β . DISCUSSION AD‐TDP types may have different WMH pathomechanisms, with type‐ α having associations more like FTLD‐TDP than AD. Highlights In transactive response DNA‐binding protein 43 (TDP‐43) pathology in Alzheimer's disease (AD‐TDP), TDP‐43 status alone is not associated with total or regional WMH burden AD‐TDP type‐ α shows greater total, frontotemporal subcortical, and basal ganglia white matter hyperintensities (WMHs) AD‐TDP type‐ β shows less total and subcortical occipital WMHs AD‐TDP type‐ α effect on WMH burden closely mimics the effects of frontotemporal lobar degeneration with TDP‐43 (FTLD‐TDP) rather than AD Different relationships of AD‐TDP types with WMHs suggest different pathomechanisms

Importance Although 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established cross-sectional biomarker of brain metabolism in dementia with Lewy bodies (DLB), the longitudinal change in FDG-PET has not been characterized. Objective To investigate longitudinal FDG-PET in prodromal DLB and DLB, including a subsample with autopsy data, and report estimated sample sizes for a hypothetical clinical trial in DLB. Design, Setting, and Participants Longitudinal case-control study with mean (SD) follow-up of 3.8 (2.3) years. Cases were recruited consecutively between 2007 and 2022 at a referral center and among the population. Patients with probable DLB or mild cognitive impairment with Lewy bodies (MCI-LB) were included. Individuals without cognitive impairment were included from a population-based cohort balanced on age and sex for comparison. All participants completed at least 1 follow-up assessment by design. Exposure Patients with MCI-LB and DLB. Main Outcomes and Measures Rate of change in FDG-PET was assessed as standardized uptake value ratios (SUVr). Clinical progression was assessed with the Clinical Dementia Rating Sum of Boxes (CDR-SB) score. Results Thirty-five patients with probable DLB, 37 patients with MCI-LB, and 100 individuals without cognitive impairment were included. The mean (SD) age of the DLB and MCI-LB groups combined (n = 72) was 69.6 (8.2) years; 66 patients (92%) were men and 6 (8%) were women. At follow-up, 18 participants (49%) with MCI-LB had progressed to probable DLB. Patients with MCI-LB had a faster decline in FDG-SUVr, compared with that of participants without cognitive impairment, in the posterior cingulate, occipital, parietal, temporal, and lateral frontal cortices. The same regions showed greater metabolic decline in patients with DLB than in participants without cognitive impairment, with the addition of anterior-middle cingulate, insula, and medial frontal orbital cortices. Rates of change in FDG-PET in these brain regions were combined into a region of interest (ROI) labeled longitudinal FDG-PET LB meta-ROI. The rate of change in FDG-SUVr in the meta-ROI correlated with the rate of change in CDR-SB, and sample size estimates were reported for potential clinical trials in DLB. Findings were confirmed in the subsample with neuropathologic confirmation (n = 20). Conclusions and Relevance This study found that brain hypometabolism begins to evolve during the prodromal stages of DLB with changes paralleling symptomatic progression. These data may inform clinical practice and trials planning to use FDG-PET for biologic staging, monitoring disease progression, and potentially assessing treatment response.

ABSTRACT Background and Purpose In idiopathic normal pressure hydrocephalus (iNPH) patients, cerebrospinal fluid (CSF) flow is typically evaluated with a cardiac‐gated two‐dimensional (2D) phase‐contrast (PC) MRI through the cerebral aqueduct. This approach is limited by the evaluation of a single location and does not account for respiration effects on flow. In this study, we quantified the cardiac and respiratory contributions to CSF movement at multiple intracranial locations using a real‐time 2D PC‐MRI and evaluated the diagnostic value of CSF dynamics biomarkers in classifying iNPH patients. Methods This study included 37 participants: 16 iNPH, 10 Alzheimer's disease (AD), and 11 cognitively unimpaired (CU) controls. Anatomical and real‐time (non‐gated) PC images were acquired in a 3T Philips scanner. CSF flow was assessed at the foramen magnum, fourth ventricle, Sylvian fissure, lateral ventricle, and cerebral aqueduct. We calculated three CSF dynamics biomarkers: mean velocity amplitude, cardiac signal power, and respiratory signal power. Biomarkers from each location were evaluated for classifying iNPH versus AD and CU using support vector machine (SVM). A p ‐value of 0.05 or less was considered statistically significant. Results The velocity amplitude and cardiac signal power were significantly reduced in iNPH compared to CU ( p < 0.005) and AD ( p < 0.05) at the lateral ventricle. The SVM model using biomarkers from the lateral ventricle performed significantly better at classifying iNPH than the other locations in terms of accuracy ( p < 0.005) and diagnostic odds ratio ( p < 0.05). Conclusion Evaluation of CSF movement beyond the cerebral aqueduct may aid in identifying patients with and understanding the pathophysiology of iNPH.

Abstract INTRODUCTION Diffusion‐weighted magnetic resonance imaging (dMRI) is sensitive to the microstructural properties of brain tissues and shows great promise in detecting the effects of degenerative diseases. However, many approaches analyze single measures averaged over regions of interest without considering the underlying fiber geometry. METHODS We propose a novel macrostructure‐informed normative tractometry (MINT) framework to investigate how white matter (WM) microstructure and macrostructure are jointly altered in mild cognitive impairment (MCI) and dementia. We compared MINT‐derived metrics with univariate diffusion tensor imaging (DTI) metrics to examine how fiber geometry may impact the interpretation of microstructure. RESULTS In two multisite cohorts from North America and India, we find consistent patterns of microstructural and macrostructural anomalies implicated in MCI and dementia; we also rank diffusion metrics' sensitivity to dementia. DISCUSSION We show that MINT, by jointly modeling tract shape and microstructure, has the potential to disentangle and better interpret the effects of degenerative disease on the brain's neural pathways. Highlights Changes in diffusion tensor imaging metrics may be due to macroscopic changes. Normative models encode normal variability of diffusion metrics in healthy controls. Variational autoencoder applied on tractography can learn patterns of fiber geometry. WM microstructure and macrostructure are modeled with multivariate methods. Transfer learning uses pretraining and fine‐tuning for increased efficiency.