Przybelski, Scott A.

AbstractBackgroundWhite matter microstructure undergoes progressive changes during the life‐span but the neurobiological underpinnings related to aging and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging (NODDI), to investigate the microstructural alterations due to demographics, common age‐related pathological processes (amyloid, tau, and white matter hyperintensities (WMH)), and cognition. We also compared NODDI findings to the older Diffusion Tensor Imaging (DTI) model based findings.Method328 participants (264 cognitively unimpaired, 57 mild cognitive impairment (MCI), and 7 dementia with a mean age of 68.3 ±13.1 years) from the Mayo Clinic Study of Aging with multi‐shell diffusion imaging, FLAIR‐MRI as well as amyloid and tau PET scans were included in this study. White matter (WM) tract level diffusion measures (Figure 1) were calculated from DTI and NODDI. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, WMH, amyloid, and tau as predictors. Analyses were also performed with each dMRI measure as a predictor of cognitive outcomes.ResultAge and WMH were the strongest predictors of all WM diffusion measures with low associations with amyloid and tau (Figure 1). However, neurite density decrease from NODDI was observed with amyloidosis specifically in the temporal lobes (Figure 2). WM integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures (Table 1). All diffusion measures provided information about WM aging and WM disease processes and were associated with cognition.ConclusionNODDI and DTI are two different biophysical models that provide distinct information about variation in WM microstructural integrity. NODDI provides additional information about synaptic density, organization, and free water content which may aid in providing mechanistic insights into disease progression.

AbstractBackgroundWhite matter (WM) 11C‐Pittsburgh compound‐B (PiB) and 18F‐Flutemetamol (FMT) uptake is increasingly being used as a reference region to calculate the standard uptake value ratios (SUVr) in longitudinal amyloid‐β PET studies. PiB uptake is lower in WM hyperintensities (WMH) in older adults. Furthermore, WM PiB uptake increases with aging. Our objective was to determine whether a similar variation in WM uptake exists with an 18F‐ligand FMT.MethodA cohort of cognitively unimpaired (CU) older adults with median (range) age of 67 (61, 83) years (N=31), and younger adults with median (range) age of 38 (30, 48) years (N=30) from the community responding to a study advertisement underwent MRI, PiB and FMT PET. MRI‐FLAIR images were segmented into WMH and normal appearing white matter (NAWM) and registered to the T1‐weighted image. PiB and FMT PET images were registered to the T1‐weighted image. PiB and FMT SUVrs from the WMH and NAWM compartments were calculated using cerebellar crus uptake as a reference.ResultWMH PiB SUVr and NAWM PiB SUVr were lower in the younger compared to the older adults (p<0.001). WMH FMT SUVr and NAWM FMT SUVr were lower in younger compared to older adults (p<0.001). PiB SUVr was lower than FMT SUVr both in younger and older adults in both WMH and NAWM compartments (p<0.001). In both age groups, PiB SUVr and FMT SUVr in WMH was lower than NAWM (p<0.001). AUROC analysis demonstrated no difference between PiB versus FMT SUVr in differentiating WMH from NAWM in younger and older adults.ConclusionWMH and NAWM SUVRs are higher with FMT than PiB, however both PiB and FMT show a similar topographic pattern of uptake in the WM with higher uptake in NAWM compared to WMH. Aging is associated with a decrease in myelin integrity and increase of WMH volume. Higher WMH and NAWM PiB and FMT uptake in the older compared to younger adults suggests that additional aging‐related mechanisms are influencing WM PET tracer uptake. Age and WMH volume should be considered when WM uptake is used as a reference region for the evaluation of cortical uptake of both PiB and FMT.

AbstractBackgroundIsolated REM Sleep Behavior Disorder (iRBD) patients are known to be at high risk for developing an overt synucleinopathy – particularly Dementia with Lewy Bodies (DLB) and Parkinson’s Disease (PD). Reduced nigrostriatal uptake on 123I‐FP‐CIT SPECT reflects dopamine deficiency, which is common in the overt synucleinopathies. We sought to assess how 123I‐FP‐CIT SPECT imaging in iRBD changes longitudinally and whether an abnormal 123I‐FP‐CIT SPECT scan precedes and predicts future transition to an overt synucleinopathy.MethodParticipants with polysomnography‐confirmed iRBD from the Mayo Clinic Alzheimer’s Disease Research Center database +/‐ North American Prodromal Synucleinopathy (NAPS) Consortium who had two or more longitudinal 123I‐FP‐CIT SPECT scans and been followed prospectively for at least 24 months were included in this analysis. Striatonigral dopamine transporter uptake was evaluated semi‐quantitatively with 123I‐FP‐CIT SPECT using DaTQUANT software (GE Healthcare) to calculate z‐scores of putamen uptake.ResultThirty‐five iRBD participants (86% male) were evaluated prospectively (mean 62.5 ± 19.4 months) and underwent two or more 123I‐FP‐CIT SPECT scans at a minimum of 12 months intervals. Thirteen participants (37%) developed an overt synucleinopathy (11 DLB and 2 PD; phenoconverters) and 22 participants (63%) remained as iRBD (stable iRBD). Phenoconverters were older (mean 70.8 ± 7.0 vs 63.4 ± 6.0 years old) and had more negative DaTQUANT putamen z‐scores (mean ‐1.68 ± 1.42 vs ‐0.33 ± 1.52) than stable iRBD participants at baseline. Among phenoconverters, nine participants (69%) had one or more 123I‐FP‐CIT SPECT scans with DaTQUANT putamen z‐score of <‐2.0 prior to phenoconversion, and mean time from initial DaTQUANT putamen z‐score of <‐2.0 to phenoconversion was 36.8 ± 28.7 months. In stable RBD participants, eight participants (36%) showed a decline in DaTQUANT putamen z‐score of >1 between the most recent and the baseline scan, and four participants (18%) presented DaTQUANT putamen z‐score of <‐2.0 at the most recent scan.ConclusionThese findings suggest that a decline in putamen uptake on 123I‐FP‐CIT SPECT in iRBD serves as a predictor and a surrogate biomarker for progression of iRBD to an overt synucleinopathy.

AbstractBackgroundThere have been no standard definitions of successful cognitive aging (SA). Our goal was to apply different SA definitions to the 80+ population in the Mayo Clinic Study of Aging (MCSA) on the basis of (i) cross‐sectional vs longitudinal cognition (“Exceptionality” vs “Maintenance”) and (ii) memory vs global cognitive scores and explore the participant characteristics for each SA definition on the basis of baseline imaging markers and mid/late‐life health.MethodWe included 2157 participants from the MCSA, all ≥80 years at baseline and classified them into two SA definitions using memory z‐scores or global z‐scores: “Exceptionality” when high cognitive performance was observed (z‐scores ≥ 1 SD), “Maintenance” when cognitive function was preserved over time (Slope ≥ ‐0.1/year using mixed‐effect models). Our imaging markers were: PET‐based amyloid positivity (A+), MRI‐based neurodegeneration positivity (N+), WMH, FDG‐PET SUVR markers of resilience (anterior cingulate, ACC) and AD‐related areas (posterior cingulate). We also examined APOE4 status and other health characteristics. Group comparison was performed within each definition (e.g. exceptional vs non‐exceptional memory) using ANCOVA and binary logistic regressions with adjustments for age, sex, and education.ResultA lower number of participants met the “Exceptionality” criteria (10%: memory and 4%: global). A greater number met the “Maintenance” criteria (53%: memory and 32%: global). Less than 7% showed both “Exceptional” cognition and “Maintenance” over time. Participants across SA definitions were in general younger, more often women, with a higher education/occupation and less often APOE4 carriers. All SA groups showed higher ACC metabolism and lower N+ compared to the corresponding non‐SA group. More than 50% of the participants in the “Exceptional” groups were A+ (57%: memory, 50%: global). A+ frequency was significantly lower in the “Maintainers” (<42%). Better mid/late‐life health indicators were observed in the SA groups, including lower cardio‐metabolic conditions, higher mid‐life cognitive activities, lower depressive symptomatology, lower hypersomnolence and better self‐perception of health.ConclusionDifferent SA definitions identified mainly non‐overlapping 80+ groups that showed several common features including higher education/occupation, percent of women, better lifestyles, lower N+ frequency, and higher ACC metabolism. Lower A+ frequency was a key distinct feature of “Maintenance”.

AbstractBackgroundOptimizing software to measure Flortaucipir (AV‐1451) tau PET SUVR change‐over‐time is crucial for longitudinal observational studies and potential trials of anti‐tau agents. Ideal measurements should have good repeatability (low noise), and should clearly separate clinical cognitive groups.MethodWe compared 456 software methods varying in their use of: two major packages, each with cross‐sectional and longitudinal variants (FreeSurfer and an in‐house pipeline using SPM12, MCALT, and ANTs); three temporal‐lobe target regions (each with/without adjacent WM); seven reference regions; five PVC methods; and two statistics (mean vs. median). We used linear mixed‐effects models to compare methods using scans from 88 Mayo Clinic participants (46 cognitively impaired, 42 impaired, excluding those with symptoms inconsistent with the AD pathology imaged by Flortaucipir), each with three visits with PET and MRI. From these models, we calculated two criteria for each pipeline: relative measurement error (residual from the linear mixed model), and the t‐statistic for testing differences in group‐wise rates of change (which has a Cohen’s d interpretation of effect size for longitudinal data). We plotted both criteria orthogonally, then ranked methods overall according to the average of their ranks on both individual criteria.ResultMethods using the entorhinal cortex target region performed poorly in both criteria (Figure 1). The top 10 methods by the combined criteria (top‐left in Figure 2) all used the Mayo SPM12‐based pipeline with an eroded supratentorial WM (eSWM) or composite (eSWM + pons + cerebellum) reference region. Among them, 9/10 used the longitudinal variant, 8/10 used 2‐compartment PVC, and 7/10 used median. Altogether, our results favored SUVR methods with a longitudinal design (simultaneously calculating all time‐points), a temporal‐lobe meta‐ROI including adjacent WM, a composite reference region, 2‐class voxel‐based (Meltzer) PVC, and median statistics. Methods using GTM‐Tau PVC (Baker et al., Data in Brief, 2017) had the highest group separation but relatively large measurement error, giving them ranks 197 and 199 out of 456 with the joint (average rank) criteria.ConclusionCompared with popular FreeSurfer‐based methods (ranks 176, 258; Figure 2), our top‐ranked approaches approximately halved error in SUVR measurements while maintaining or improving group separation.

Hypertension is highly prevalent in the elderly population and microinfarcts are the most common vascular brain pathology identified in older adults at autopsy. We investigated the associations between systolic and diastolic blood pressures measured antemortem and the presence of microinfarcts at autopsy. Study subjects (n=302; age range=71-95) were participants in the population-based Mayo Clinic Study of Aging autopsy study, who had blood pressure measurements recorded during life. We investigated both cross-sectional systolic and diastolic blood pressure measurements at the baseline visit and the change in blood pressure (slope). Presence and location (subcortical or cortical) of chronic microinfarcts was abstracted from the autopsy reports. Of the 302 study subjects, 47 (16%) had cerebral microinfarcts, and, of those, 18 (38%) had subcortical microinfarcts and 29 (62%) had only cortical microinfarcts. The baseline blood pressures were not different between subjects with no microinfarcts, subcortical microinfarcts, and only cortical microinfarcts. In a logistic regression model including time between last blood pressure measurement and death, a greater decline in systolic [OR= 1.06 (1.01, 1.11); p=0.02]) and greater decline in diastolic [OR= 1.11 (1.02, 1.20); p=0.01] blood pressures were predictors of the presence of subcortical microinfarcts at autopsy. However, these variables were not associated with the presence of cortical microinfarcts. In conclusion, microinfarcts are common in the older adult population, and most of them are located in the cortex. A greater decline in both systolic and diastolic blood pressures and their association with subcortical microinfarcts, but not with cortical microinfarcts, may have implications for aggressive lowering of blood pressure in the elderly population.

Abstract Dementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α-synuclein aggregates, but many DLB cases show concurrent Alzheimer’s disease pathology in the form of amyloid-β plaques and tau neurofibrillary tangles. The first objective of this study was to investigate the effect of Alzheimer’s disease co-pathology on functional network changes within the default mode network (DMN) in DLB. Second, we studied how the distribution of tau pathology measured with PET relates to functional connectivity in DLB. Twenty-seven DLB, 26 Alzheimer’s disease and 99 cognitively unimpaired participants (balanced on age and sex to the DLB group) underwent tau-PET with AV-1451 (flortaucipir), amyloid-β-PET with Pittsburgh compound-B (PiB) and resting-state functional MRI scans. The resing-state functional MRI data were used to assess functional connectivity within the posterior DMN. This was then correlated with overall cortical flortaucipir PET and PiB PET standardized uptake value ratio (SUVr). The strength of interregional functional connectivity was assessed using the Schaefer atlas. Tau-PET covariance was measured as the correlation in flortaucipir SUVr between any two regions across participants. The association between region-to-region functional connectivity and tau-PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot- and cold spots) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot and cold spots. A reduction in posterior DMN connectivity correlated with overall higher cortical tau- (r = −0.39, P = 0.04) and amyloid-PET uptake (r = −0.41, P = 0.03) in the DLB group, i.e. patients with DLB who have more concurrent Alzheimer’s disease pathology showed a more severe loss of DMN connectivity. Higher functional connectivity between regions was associated with higher tau covariance in cognitively unimpaired, Alzheimer’s disease and DLB. Furthermore, higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher flortaucipir SUVrs in the target region, whereas higher functional connectivity to the tau cold spot (i.e. sensory-motor cortex) was related to lower flortaucipir SUVr in the target region. Our findings suggest that a higher burden of Alzheimer’s disease co-pathology in patients with DLB is associated with more Alzheimer’s disease-like changes in functional connectivity. Furthermore, we found an association between the brain’s functional network architecture and the distribution of tau pathology that has recently been described in Alzheimer’s disease. We show that this relationship also exists in patients with DLB, indicating that similar mechanisms of connectivity-dependent occurrence of tau pathology might be at work in both diseases.

ABSTRACT Background and Purpose Neurodegeneration of the substantia nigra in Lewy body disease is associated with iron deposition, which increases the magnetic susceptibility of the substantia nigra on MRI. Our objective was to measure iron deposition in the substantia nigra in patients with probable dementia with Lewy bodies (pDLB) and patients who are at risk for pDLB by quantitative susceptibility mapping (QSM). Methods Participants included pDLB ( n = 36), mild cognitive impairment with at least one core feature of DLB (MCI‐LB; n = 15), idiopathic rapid eye movement sleep behavior disorder (iRBD; n = 11), and an age‐and gender‐matched clinically unimpaired control group ( n = 102). QSM was derived from multi‐echo 3D gradient recalled echo MRI at 3T, and groups were compared on mean susceptibility values of the substantia nigra and its relation to parkinsonism severity. Results Patients with pDLB had higher susceptibility in the substantia nigra compared to controls ( p < 0.001) and MCI‐LB ( p = 0.043). The susceptibility of substantia nigra showed an increasing trend from controls to iRBD and MCI‐LB, and to pDLB ( p < 0.001). Parkinsonism severity was not associated with the mean susceptibility in the substantia nigra in the patient groups. Conclusions Our data suggested that QSM is sensitive to the increased magnetic susceptibility due to higher iron content in the substantia nigra in pDLB. The trend of increasing susceptibility from controls to iRBD and MCI‐LB, and to pDLB suggests that iron deposition in the substantia nigra starts to increase as early as the prodromal stage in DLB and continues to increase as the disease progresses, independent of parkinsonism severity.

Abstract White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.