Knopman, David S.

Importance Tau positron emission tomography (PET) allows in vivo detection of neurofibrillary tangles, a core neuropathologic feature of Alzheimer disease (AD). Objective To provide estimates of the frequency of tau PET positivity and its associated risk of clinical outcomes. Design, Setting, and Participants Longitudinal study using data pooled from 21 cohorts, comprising a convenience sample of 6514 participants from 13 countries, collected between January 2013 and June 2024. Cognitively unimpaired individuals and patients with a clinical diagnosis of mild cognitive impairment (MCI), AD dementia, or other neurodegenerative disorders were included. Exposures Tau PET with flortaucipir F 18, amyloid-β (Aβ) PET, and clinical examinations. Tau PET scans were visually rated as positive according to a US Food and Drug Administration– and European Medicines Agency–approved method, designed to indicate the presence of advanced neurofibrillary tangle pathology (Braak stages V-VI). Main Outcomes and Measures Frequency of tau PET positivity and absolute risk of clinical progression (eg, progression to MCI or dementia). Results Among the 6514 participants (mean age, 69.5 years; 50.5% female), median follow-up time ranged from 1.5 to 4.0 years. Of 3487 cognitively unimpaired participants, 349 (9.8%) were tau PET positive; the estimated frequency of tau PET positivity was less than 1% in those aged younger than 50 years, and increased from 3% (95% CI, 2%-4%) at 60 years to 19% (95% CI, 16%-24%) at 90 years. Tau PET positivity frequency estimates increased across MCI and AD dementia clinical diagnoses (43% [95% CI, 41%-46%] and 79% [95% CI, 77%-82%] at 75 years, respectively). Most tau PET–positive individuals (92%) were also Aβ PET positive. Cognitively unimpaired participants who were positive for both Aβ PET and tau PET had a higher absolute risk of progression to MCI or dementia over the following 5 years (57% [95% CI, 45%-71%]) compared with both Aβ PET–positive/tau PET–negative (17% [95% CI, 13%-22%]) and Aβ PET–negative/tau PET–negative (6% [95% CI, 5%-8%]) individuals. Among participants with MCI at the time of the tau PET scan, an Aβ PET–positive/tau PET–positive profile was associated with a 5-year absolute risk of progression to dementia of 70% (95% CI, 59%-81%). Conclusions and Relevance In a large convenience sample, a positive tau PET scan occurred at a nonnegligible rate among cognitively unimpaired individuals, and the combination of Aβ PET positivity and tau PET positivity was associated with a high risk of clinical progression in both preclinical and symptomatic stages of AD. These findings underscore the potential of tau PET as a biomarker for staging AD pathology.

AbstractBackgroundCortical structural changes in the temporal lobes including global and hippocampal volume loss and decrease in cortical thickness are well‐associated findings linked to cognitive decline in MCI and dementia patients. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method enabling assessment of tissue microstructural integrity at the axonal and dendritic level. We wished to determine whether changes in temporal cortex orientation dispersion index (ODI) & neurite density index (NDI) correlate with decreases in memory function.MethodThe MCALT_ADIR122 cortical atlas was used for ROI designation. NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. Participants (ages 60‐95 years) were cognitively unimpaired (CU) or had mild cognitive impairment (MCI). CU & MCI subjects were enrolled in the Mayo Clinic Study of Aging (MCSA) and underwent neuropsychological testing including 3 memory tests from which a composite memory z score was calculated. A generalized additive regression model was used to estimate z scores as a smooth function of ODI, NDI and cortical thickness or volume with adjustment for age, gender, education, MCSA cycle number, WMH and intracranial volume.ResultThe Table displays demographic data. Figures 1 and 2 show the relationship of NDI and ODI measures to memory z scores across participants in individual ROIs both before and after adjustment for cortical thickness (“structural MRI”) as well as for confounds listed above. Both higher cortical thickness and higher NDI values in the hippocampus and entorhinal cortex were associated with significantly higher memory z‐scores (p<0.001) (Figure 1). Higher ODI values in addition to greater cortical thickness in temporal lobe regions, including within the hippocampus, parahippocampal gyrus, entorhinal cortex and inferior temporal gyrus, were associated with higher memory z‐scores (Figure 2). These significant associations (p <=0.01) were maintained after adjusting for cortical thickness in all these regions except entorhinal cortex for ODI.ConclusionNODDI‐derived measures of microstructural integrity (NDI & ODI) within the temporal cortex may provide information about memory decline, beyond what cortical thickness analysis provides, and may be potentially useful for monitoring therapeutic effects of AD immunotherapy in the future.

AbstractBackgroundVascular contributions to cognitive impairment and dementia (VCID) are often comorbid with Alzheimer’s disease and increase the risk of dementia. Blood‐based biomarkers may be promising for identifying individuals at high risk for VCID due to small vessel disease (SVD).MethodWe included 1709 participants from the Mayo Clinic Study of Aging who had concurrent MRI, plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) measured on the HD‐X Simoa Quanterix platform, and clinical dementia rating scale (CDR). We categorized participants into SVD vs. not using WMH/TIV≥1.3% which corresponds to Fazekas>=2 cutoff and cognitively impaired (CI) vs. not using CDR≥0.5. We obtained four groups using SVD and cognitively normal and impaired classifications: cognitively unimpaired without SVD (CU), CU with SVD (Vas‐CU), CI with SVD (VCI), and CI without SVD (Non‐vas‐CI). Univariate and multivariable logistic regression models were used to obtain odds ratios, confidence intervals and ROC curves to evaluate the association between plasma markers and each disease group compared to CU. We also evaluated these analyses in amyloid positive and negative participants.ResultThere was a high proportion of CU (Vas‐CU/(CU+Vas‐CU)=18%) and CI (VCI/(VCI+ Non‐vas‐CI)=47%) participants with SVD in the population‐based sample. Higher plasma levels were associated with greater vascular burden and differed by amyloid status (Figure 1). ROC analyses showed that both NfL and GFAP provided discrimination between Vas‐CU and CU groups (AUC=0.83) as well as VCI and CU groups (AUC=0.88) (Figure 2, Table 1). Though GFAP and NfL are non‐specific and may also reflect non‐vascular damage, we found that these plasma markers did not clearly separate NonVas‐CI from the CU group in the overall cohort (AUC=0.69). When amyloid status was available, the discriminative power of NfL and GFAP in separating the 4 groups was very low in amyloid positive participants. On the other hand, NfL and GFAP separated Vas‐CU and VCI groups from CI reasonably well in the amyloid negative group.ConclusionPlasma biomarkers associated with SVD‐burden provided reliable discriminative power in predicting VCID, particularly in the absence of amyloid, suggesting their utility in the prognosis and stratification for clinical trials.

AbstractBackgroundQuantifying white matter using diffusion MRI (dMRI) has been proposed for measuring early microstructural tissue changes due to cerebral small vessel disease and aid in quantifying vascular contributions to cognitive impairment and dementia (VCID). Our goal was to compare the usefulness of longitudinal white matter changes in the commonly available diffusion MRI measures for VCID prevention trials.MethodWe included 718 participants over 50 years of age (mean age: 71.1(9.6) years) from the Mayo Clinic Study of Aging, a population‐based sample, with at least two dMRI scans and structural imaging. We computed the commonly available single‐shell dMRI measures (fractional anisotropy, mean diffusivity, and two MarkVCID measures ‐ free water and peak‐width skeletonized mean diffusivity [PSMD]) at each time point. We tested for voxel‐wise associations between dMRI markers and vascular risk measured by cardiovascular metabolic condition (CMC) and observed a region‐specific dependance across all dMRI measures. Using both global and regional dMRI measures, we (i) examined the longitudinal association of dMRI measures with cognition and (ii) computed sample size estimates for a hypothetical clinical trial. We also included white matter hyperintensities (WMH) and our previously proposed composite vascular white matter score (combination of WMH and fractional anisotropy of the genu) as a comparison.ResultVascular risk was associated with all single shell dMRI measures in the genu of the corpus callosum, which we included as a regional dMRI marker for comparison (Figure 1). All dMRI markers correlated with cognitive performance longitudinally (Table 1) and had comparable sample size estimates required for hypothetical VCID clinical trials (Figure 2). Further, global free water and the composite vascular white matter score had the smallest sample size estimates.ConclusionAll commonly used dMRI markers had significant frontal lobe changes due to vascular risk. Both global and regional corpus callosum dMRI markers were sensitive to longitudinal cognitive decline, suggesting their utility in measuring the slowing down of VCID. The composite vascular white matter score, global free water, and WMH show promise as VCID biomarkers. Further work is needed to validate these markers on multiple populations.

AbstractBackgroundThere has been a recent proliferation of various quantities based on single shell Diffusion Tensor Imaging (DTI) for capturing overall cerebrovascular health, especially Small Vessel Disease (SVD) as a single number. The existing literature has gaps in the comparison of these measures, so we evaluated them as predictors of both current and future White Matter Hyperintensity (WMH) as a proxy of SVD.MethodUsing baseline 3T MRI examinations (T1, DTI, FLAIR scans) of 598 participants (>60 years, amyloid negative, to limit to those on the SVD pathway) from the Mayo Clinic Study of Aging, we calculated five summary DTI quantities with varying degree of complexity. We estimated their partial R2 from cross‐sectional linear regression models and computed semi‐partial R2 from mixed models predicting WMH volume as a percentage of Total Intracranial Volume (TIV). All models were adjusted for age, sex, and scanner model, and the WMH and based were log‐transformed before fitting. We also conducted subset analyses with high (WMH+) vs. low (WMH‐) baseline WMH load (cut at 1.62%) to compare the performance of the measures in early vs. widespread WMH.ResultAll MD‐based quantities computed on the whole brain, including FWF, performed similarly to each other, but Genu FA underperformed at explaining WMH variance (Table 1). PSMD (skeletonized or atlas based) was more sensitive in WMH+ but dramatically less so in WMH‐. In WMH‐ and overall cohort, FWF and JHU MD (which is a simple averaging of MD in the JHU atlas) performed well.ConclusionAll MD‐based measures performed similarly to each other in the whole dataset but dichotomizing by WMH load showed interesting differences. PSMD measurements are driven by the extreme end (95th percentile) of the MD distribution and therefore more sensitive in WMH+. Genu FA, a regional measure, was not useful for predicting whole brain WMH change. We noticed some variation in how the quantities are affected by scanner model (GE Signa HDxt and Discovery 750) which needs broader investigation. Simply averaging MD over WM avoids additional processing and is more sensitive to WM degeneration that is not (yet) severe.

AbstractBackgroundCortical structural changes in the temporal lobes including global and hippocampal volume loss and decrease in cortical thickness are well‐associated findings linked to cognitive decline in MCI and dementia patients. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method enabling assessment of tissue microstructural integrity at the axonal and dendritic level. We wished to determine whether changes in temporal cortex orientation dispersion index (ODI) & neurite density index (NDI) correlate with decreases in memory function.MethodThe MCALT_ADIR122 cortical atlas was used for ROI designation. NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. Participants (ages 60‐95 years) were cognitively unimpaired (CU) or had mild cognitive impairment (MCI). CU & MCI subjects were enrolled in the Mayo Clinic Study of Aging (MCSA) and underwent neuropsychological testing including 3 memory tests from which a composite memory z score was calculated. A generalized additive regression model was used to estimate z scores as a smooth function of ODI, NDI and cortical thickness or volume with adjustment for age, gender, education, MCSA cycle number, WMH and intracranial volume.ResultThe Table displays demographic data. Figures 1 and 2 show the relationship of NDI and ODI measures to memory z scores across participants in individual ROIs both before and after adjustment for cortical thickness (“structural MRI”) as well as for confounds listed above. Both higher cortical thickness and higher NDI values in the hippocampus and entorhinal cortex were associated with significantly higher memory z‐scores (p<0.001) (Figure 1). Higher ODI values in addition to greater cortical thickness in temporal lobe regions, including within the hippocampus, parahippocampal gyrus, entorhinal cortex and inferior temporal gyrus, were associated with higher memory z‐scores (Figure 2). These significant associations (p <=0.01) were maintained after adjusting for cortical thickness in all these regions except entorhinal cortex for ODI.ConclusionNODDI‐derived measures of microstructural integrity (NDI & ODI) within the temporal cortex may provide information about memory decline, beyond what cortical thickness analysis provides, and may be potentially useful for monitoring therapeutic effects of AD immunotherapy in the future.