Boston Criteria v2.0 for Cerebral Amyloid Angiopathy Without Hemorrhage: An MRI-Neuropathologic Validation Study.

BACKGROUND AND OBJECTIVES: Updated criteria for the clinical-MRI diagnosis of cerebral amyloid angiopathy (CAA) have recently been proposed. However, their performance in individuals without symptomatic intracerebral hemorrhage (ICH) presentations is less defined. We aimed to assess the diagnostic performance of the Boston criteria version 2.0 for CAA diagnosis in a cohort of individuals ranging from cognitively normal to dementia in the community and memory clinic settings. METHODS: Fifty-four participants from the Mayo Clinic Study of Aging or Alzheimer's Disease Research Center were included if they had an antemortem MRI with gradient-recall echo sequences and a brain autopsy with CAA evaluation. Performance of the Boston criteria v2.0 was compared with v1.5 using histopathologically verified CAA as the reference standard. RESULTS: The median age at MRI was 75 years (interquartile range 65-80) with 28/54 participants having histopathologically verified CAA (i.e., moderate-to-severe CAA in at least 1 lobar region). The sensitivity and specificity of the Boston criteria v2.0 were 28.6% (95% CI 13.2%-48.7%) and 65.3% (95% CI 44.3%-82.8%) for probable CAA diagnosis (area under the receiver operating characteristic curve [AUC] 0.47) and 75.0% (55.1-89.3) and 38.5% (20.2-59.4) for any CAA diagnosis (possible + probable; AUC 0.57), respectively. The v2.0 Boston criteria were not superior in performance compared with the prior v1.5 criteria for either CAA diagnostic category. DISCUSSION: The Boston criteria v2.0 have low accuracy in patients who are asymptomatic or only have cognitive symptoms. Additional biomarkers need to be explored to optimize CAA diagnosis in this population.

Patterns of Early Neocortical Amyloid-ß Accumulation: A PET Population-Based Study.

The widespread deposition of amyloid-ß (Aß) plaques in late-stage Alzheimer disease is well defined and confirmed by in vivo PET. However, there are discrepancies between which regions contribute to the earliest topographic Aß deposition within the neocortex. Methods: This study investigated Aß signals in the perithreshold SUV ratio range using Pittsburgh compound B (PiB) PET in a population-based study cross-sectionally and longitudinally. PiB PET scans from 1,088 participants determined the early patterns of PiB loading in the neocortex. Results: Early-stage Aß loading is seen first in the temporal, cingulate, and occipital regions. Regional early deposition patterns are similar in both apolipoprotein ε4 carriers and noncarriers. Clustering analysis shows groups with different patterns of early amyloid deposition. Conclusion: These findings of initial Aß deposition patterns may be of significance for diagnostics and understanding the development of Alzheimer disease phenotypes.

Prescription Opioids and Brain Structure in Community-Dwelling Older Adults.

OBJECTIVE: To evaluate the associations between prescription opioid exposures in community-dwelling older adults and gray and white matter structure by magnetic resonance imaging. METHODS: Secondary analysis was conducted of a prospective, longitudinal population-based cohort study employing cross-sectional imaging of older adult (≥65 years) enrollees between November 1, 2004, and December 31, 2017. Gray matter outcomes included cortical thickness in 41 structures and subcortical volumes in 6 structures. White matter outcomes included fractional anisotropy in 40 tracts and global white matter hyperintensity volumes. The primary exposure was prescription opioid availability expressed as the per-year rate of opioid days preceding magnetic resonance imaging, with a secondary exposure of per-year total morphine milligram equivalents (MME). Multivariable models assessed associations between opioid exposures and brain structures. RESULTS: The study included 2185 participants; median (interquartile range) age was 80 (75 to 85) years, 47% were women, and 1246 (57%) received opioids. No significant associations were found between opioids and gray matter. Increased opioid days and MME were associated with decreased white matter fractional anisotropy in 15 (38%) and 16 (40%) regions, respectively, including the corpus callosum, posterior thalamic radiation, and anterior limb of the internal capsule, among others. Opioid days and MME were also associated with greater white matter hyperintensity volume (1.02 [95% CI, 1.002 to 1.036; P=.029] and 1.01 [1.001 to 1.024; P=.032] increase in the geometric mean, respectively). CONCLUSION: The duration and dose of prescription opioids were associated with decreased white matter integrity but not with gray matter structure. Future studies with longitudinal imaging and clinical correlation are warranted to further evaluate these relationships.

Influences of amyloid-ß and tau on white matter neurite alterations in dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-ß with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-ß, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-ß exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

Background: White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods: We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results: Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion: Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease.

Importance: Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives: To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants: This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures: Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results: Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = -0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = -0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance: Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.

Associations between vascular health, brain stiffness and global cognitive function.

Vascular brain injury results in loss of structural and functional connectivity and leads to cognitive impairment. Its various manifestations, including microinfarcts, microhaemorrhages and white matter hyperintensities, result in microstructural tissue integrity loss and secondary neurodegeneration. Among these, tissue microstructural alteration is a relatively early event compared with atrophy along the aging and neurodegeneration continuum. Understanding its association with cognition may provide the opportunity to further elucidate the relationship between vascular health and clinical outcomes. Magnetic resonance elastography offers a non-invasive approach to evaluate tissue mechanical properties, providing a window into the microstructural integrity of the brain. This retrospective study evaluated brain stiffness as a potential biomarker for vascular brain injury and its role in mediating the impact of vascular dysfunction on cognitive impairment. Seventy-five participants from the Mayo Clinic Study of Aging underwent brain imaging using a 3T MR imager with a spin-echo echo-planar imaging sequence for magnetic resonance elastography and T1- and T2-weighted pulse sequences. This study evaluated the effects of vascular biomarkers (white matter hyperintensities and cardiometabolic condition score) on brain stiffness using voxelwise analysis. Partial correlation analysis explored associations between brain stiffness, white matter hyperintensities, cardiometabolic condition and global cognition. Mediation analysis determined the role of stiffness in mediating the relationship between vascular biomarkers and cognitive performance. Statistical significance was set at P-values < 0.05. Diagnostic accuracy of magnetic resonance elastography stiffness for white matter hyperintensities and cardiometabolic condition was evaluated using receiver operator characteristic curves. Voxelwise linear regression analysis indicated white matter hyperintensities negatively correlate with brain stiffness, specifically in periventricular regions with high white matter hyperintensity levels. A negative association between cardiovascular risk factors and stiffness was also observed across the brain. No significant patterns of stiffness changes were associated with amyloid load. Global stiffness (µ) negatively correlated with both white matter hyperintensities and cardiometabolic condition when all other covariables including amyloid load were controlled. The positive correlation between white matter hyperintensities and cardiometabolic condition weakened and became statistically insignificant when controlling for other covariables. Brain stiffness and global cognition were positively correlated, maintaining statistical significance after adjusting for all covariables. These findings suggest mechanical alterations are associated with cognitive dysfunction and vascular brain injury. Brain stiffness significantly mediated the indirect effects of white matter hyperintensities and cardiometabolic condition on global cognition. Local cerebrovascular diseases (assessed by white matter hyperintensities) and systemic vascular risk factors (assessed by cardiometabolic condition) impact brain stiffness with spatially and statistically distinct effects. Global brain stiffness is a significant mediator between vascular disease measures and cognitive function, highlighting the value of magnetic resonance elastography-based mechanical assessments in understanding this relationship.

Performance of the Lumipulse plasma Aß42/40 and pTau181 immunoassays in the detection of amyloid pathology.

INTRODUCTION: This study evaluated the performance of the Lumipulse plasma beta-amyloid (Aß) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid-positron emission tomography (PET). METHODS: Plasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aß42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP-MS) assay for plasma Aß42/40 was also evaluated. Amyloid-PET status was the outcome measure. RESULTS: Lumipulse and IP-MS Aß42/40 exhibited the highest diagnostic accuracy for detecting an abnormal amyloid-PET (areas under the curve [AUCs] of 0.81 and 0.84, respectively). The Lumipulse and Simoa pTau181 assays exhibited lower performance (AUCs of 0.74 and 0.72, respectively). The Simoa Aß42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aß42/40 and pTau181 did not significantly improve performance over Aß42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71). DISCUSSION: The Lumipulse Aß42/40 assay showed similar performance to the IP-MS Aß42/40 assay for detection of an abnormal amyloid-PET; and both assays performed better than the two p-tau181 immunoassays. The Simoa Aß42/Aß40 assay was the least accurate at predicting an abnormal amyloid-PET status. Highlights: Lumipulse plasma Aß42/Aß40 AUC for abnormal amyloid-PET detection was 0.81.This performance was comparable to previously reported IP-MS and higher than Simoa.Performance of Alzheimer's disease blood biomarkers varies between assays.

Comparison of plasma biomarkers and amyloid PET for predicting memory decline in cognitively unimpaired individuals.

BACKGROUND: We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals. METHODS: We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E (APOE) ε4 genotype, amyloid PET, and plasma amyloid beta (Aß)42/40, phosphorylated tau (p-tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p-tau217. The outcome was a change in a memory composite measure. RESULTS: All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p-tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person-level prediction intervals were wide. DISCUSSION: Plasma p-tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.

Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes.

Background and Objectives: Alzheimer disease (AD) has a polygenic architecture, for which genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) influencing susceptibility. Polygenic risk score (PRS) approaches show promise for generating summary measures of inherited risk for clinical AD based on the effects of APOE and other GWAS hits. However, existing PRS approaches, based on traditional regression models, explain only modest variation in AD dementia risk and AD-related endophenotypes. We hypothesized that machine learning (ML) models of polygenic risk (ML-PRS) could outperform standard regression-based PRS methods and therefore have the potential for greater clinical utility. Methods: We analyzed combined data from the Mayo Clinic Study of Aging (n = 1,791) and the Alzheimer's Disease Neuroimaging Initiative (n = 864). An AD PRS was computed for each participant using the top common SVs obtained from a large AD dementia GWAS. In parallel, ML models were trained using those SV genotypes, with amyloid PET burden as the primary outcome. Secondary outcomes included amyloid PET positivity and clinical diagnosis (cognitively unimpaired vs impaired). We compared performance between ML-PRS and standard PRS across 100 training sessions with different data splits. In each session, data were split into 80% training and 20% testing, and then five-fold cross-validation was used within the training set to ensure the best model was produced for testing. We also applied permutation importance techniques to assess which genetic factors contributed most to outcome prediction. Results: ML-PRS models outperformed the AD PRS (r2 = 0.28 vs r2 = 0.24 in test set) in explaining variation in amyloid PET burden. Among ML approaches, methods accounting for nonlinear genetic influences were superior to linear methods. ML-PRS models were also more accurate when predicting amyloid PET positivity (area under the curve [AUC] = 0.80 vs AUC = 0.63) and the presence of cognitive impairment (AUC = 0.75 vs AUC = 0.54) compared with the standard PRS. Discussion: We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles. Further adaptations of the ML-PRS framework could help to close the gap of remaining unexplained heritability for AD and therefore facilitate more accurate presymptomatic and early-stage risk stratification for clinical decision-making.

Neurite-based white matter alterations in MAPT mutation carriers: A multi-shell diffusion MRI study in the ALLFTD consortium.

We assessed white matter (WM) integrity in MAPT mutation carriers (16 asymptomatic, 5 symptomatic) compared to 31 non-carrier family controls using diffusion tensor imaging (DTI) (fractional anisotropy; FA, mean diffusivity; MD) and neurite orientation dispersion and density imaging (NODDI) (neurite density index; NDI, orientation and dispersion index; ODI). Linear mixed-effects models accounting for age and family relatedness revealed alterations across DTI and NODDI metrics in all mutation carriers and in symptomatic carriers, with the most significant differences involving fronto-temporal WM tracts. Asymptomatic carriers showed higher entorhinal MD and lower cingulum FA and patterns of higher ODI mostly involving temporal areas and long association and projections fibers. Regression models between estimated time to or time from disease and DTI and NODDI metrics in key regions (amygdala, cingulum, entorhinal, inferior temporal, uncinate fasciculus) in all carriers showed increasing abnormalities with estimated time to or time from disease onset, with FA and NDI showing the strongest relationships. Neurite-based metrics, particularly ODI, appear to be particularly sensitive to early WM involvement in asymptomatic carriers.

Modeling the temporal evolution of plasma p-tau in relation to amyloid beta and tau PET.

INTRODUCTION: The timing of plasma biomarker changes is not well understood. The goal of this study was to evaluate the temporal co-evolution of plasma and positron emission tomography (PET) Alzheimer's disease (AD) biomarkers. METHODS: We included 1408 Mayo Clinic Study of Aging and Alzheimer's Disease Research Center participants. An accelerated failure time (AFT) model was fit with amyloid beta (Aß) PET, tau PET, plasma p-tau217, p-tau181, and glial fibrillary acidic protein (GFAP) as endpoints. RESULTS: Individual timing of plasma p-tau progression was strongly associated with Aß PET and GFAP progression. In the population, GFAP became abnormal first, then Aß PET, plasma p-tau, and tau PET temporal meta-regions of interest when applying cut points based on young, cognitively unimpaired participants. DISCUSSION: Plasma p-tau is a stronger indicator of a temporally linked response to elevated brain Aß than of tau pathology. While Aß deposition and a rise in GFAP are upstream events associated with tau phosphorylation, the temporal link between p-tau and Aß PET was the strongest. HIGHLIGHTS: Plasma p-tau progression was more strongly associated with Aß than tau PET. Progression on plasma p-tau was associated with Aß PET and GFAP progression. P-tau181 and p-tau217 become abnormal after Aß PET and before tau PET. GFAP became abnormal first, before plasma p-tau and Aß PET.

Mayo normative studies: regression-based normative data for ages 30-91 years with a focus on the Boston Naming Test, Trail Making Test and Category Fluency.

OBJECTIVE: Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample. METHOD: The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo's Older Americans Normative Studies (MOANS) norms. RESULTS: Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6-27% variance explained), sex (0-13%), and education (2-10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS. CONCLUSIONS: Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

Neuroimaging Characteristics of Hearing Loss in the Mayo Clinic Study of Aging.

OBJECTIVE: To investigate the association between standard pure tone and speech audiometry with neuroimaging characteristics reflective of aging and dementia in older adults. STUDY DESIGN: Prospective population-based study. SETTING: Single tertiary care referral center. METHODS: Participants from the Mayo Clinic Study of aging 60 years old or older with normal cognition or mild cognitive impairment, baseline neuroimaging, and a behavioral audiogram associated with neuroimaging were eligible for study. Imaging modalities included structural MRI (sMRI) and fluid-attenuated inversion recovery MRI (FLAIR-MRI; N = 605), diffusion tensor imaging MRI (DTI-MRI; N = 444), and fluorodeoxyglucose-positron emission tomography (FDG-PET; N = 413). Multivariable logistic and linear regression models were used to evaluate associations with neuroimaging outcomes. RESULTS: Mean (SD) pure tone average (PTA) was 33 (15) dB HL and mean (SD) word recognition score (WRS) was 91% (14). There were no significant associations between audiometric performance and cortical thinning assessed by sMRI. Each 10-dB increase in PTA was associated with increased likelihood of abnormal white-matter hyperintensity (WMH) from FLAIR-MRI (odds ratio 1.26, P = .02). From DTI-MRI, participants with <100% WRSs had significantly lower fractional anisotropy in the genu of the corpus callosum (parameter estimate [PE] -0.012, P = .008) compared to those with perfect WRSs. From FDG-PET, each 10% decrease in WRSs was associated with decreased uptake in the anterior cingulate cortex (PE -0.013, P = .001). CONCLUSION: Poorer audiometric performance was not significantly associated with cortical thinning but was associated with white matter damage relevant to cerebrovascular disease (increased abnormal WMH, decreased corpus callosum diffusion). These neuroimaging results suggest a pathophysiologic link between hearing loss and cerebrovascular disease.

Vascular risk, gait, behavioral, and plasma indicators of VCID.

INTRODUCTION: Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age. METHODS: In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles. RESULTS: VRFs and gait were associated with diffusion changes even in low age strata. All measures (VRFs, gait, behavioral, plasma GFAP, plasma NfL) were associated with white matter hyperintensities (WMHs) but mainly in intermediate and high age strata. DISCUSSION: Non-imaging indicators of VCID were related to WM damage and may aid in screening participants and assessing outcomes for VCID. HIGHLIGHTS: Non-imaging indicators of VCID can aid in prediction of MRI-measured WM damage but their importance differed by age. Vascular risk and gait measures were associated with early VCID changes measured using diffusion MRI. Plasma markers explained variability in WMH across age strata. Most non-imaging measures explained variability in WMH and vascular WM scores in intermediate and older age groups. The framework developed here can be used to evaluate new non-imaging VCID indicators proposed in the future.

Boston criteria v2.0 for cerebral amyloid angiopathy without hemorrhage: An MRI-neuropathological validation study.

BACKGROUND: Updated criteria for the clinical-MRI diagnosis of cerebral amyloid angiopathy (CAA) have recently been proposed. However, their performance in individuals without intracerebral hemorrhage (ICH) or transient focal neurological episodes (TFNE) is unknown. We assessed the diagnostic performance of the Boston criteria version 2.0 for CAA diagnosis in a cohort of individuals presenting without symptomatic ICH. METHODS: Fifty-four participants from the Mayo Clinic Study of Aging or Alzheimer's Disease Research Center were included if they had an antemortem MRI with gradient-recall echo sequences and a brain autopsy with CAA evaluation. Performance of the Boston criteria v2.0 was compared to v1.5 using histopathologically verified CAA as the reference standard. RESULTS: Median age at MRI was 75 years (IQR 65-80) with 28/54 participants having histopathologically verified CAA (i.e., moderate-to-severe CAA in at least 1 lobar region). The sensitivity and specificity of the Boston criteria v2.0 were 28.6% (95%CI: 13.2-48.7%) and 65.3% (95%CI: 44.3-82.8%) for probable CAA diagnosis (AUC 0.47) and 75.0% (55.1-89.3) and 38.5% (20.2-59.4) for any CAA diagnosis (possible + probable; AUC: 0.57), respectively. The v2.0 Boston criteria was not superior in performance compared to the prior v1.5 criteria for either CAA diagnostic category. CONCLUSIONS: The Boston criteria v2.0 have low accuracy in patients who are asymptomatic or only have cognitive symptoms.. Additional biomarkers need to be explored to optimize CAA diagnosis in this population.

Association of Cerebrovascular Imaging Biomarkers, Depression, and Anxiety, with Mild Cognitive Impairment.

The study included 1,738 Mayo Clinic Study of Aging participants (≥50 years old; 1,460 cognitively unimpaired and 278 with mild cognitive impairment (MCI)) and examined the cross-sectional association between cerebrovascular (CVD) imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) and Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) scores, as well as their association with MCI. High (abnormal) WMH burden was significantly associated with having BDI-II>13 and BAI > 7 scores, and both (CVD imaging biomarkers and depression/anxiety) were significantly associated with MCI when included simultaneously in the model, suggesting that both were independently associated with the odds of MCI.

Pathogenic variants in the Longitudinal Early-onset Alzheimer's Disease Study cohort.

INTRODUCTION: One goal of the Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40-64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants. METHODS: LEADS amyloid-positive early-onset Alzheimer's disease (EOAD) or negative early-onset non-AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar-age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study. RESULTS: Previously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases. DISCUSSION: Results suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases. HIGHLIGHTS: Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is a key resource for early-onset Alzheimer's genetic research.