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Abstract Background White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer’s disease (AD) 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, AD 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 a population-based sample 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, automated 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

Abstract Background Post-acute sequelae of SARS-CoV-2 infection (PASC) symptoms have broad impact, and may affect individuals regardless of COVID-19 severity, socioeconomic status, race, ethnicity, or age. A prominent PASC symptom is cognitive dysfunction, colloquially referred to as “brain fog” and characterized by declines in short-term memory, attention, and concentration. Cognitive dysfunction can severely impair quality of life by impairing daily functional skills and preventing timely return to work. Methods RECOVER-NEURO is a prospective, multi-center, multi-arm, phase 2, randomized, active-comparator design investigating 3 interventions: (1) BrainHQ is an interactive, online cognitive training program; (2) PASC-Cognitive Recovery is a cognitive rehabilitation program specifically designed to target frequently reported challenges among individuals with brain fog; (3) transcranial direct current stimulation (tDCS) is a noninvasive form of mild electrical brain stimulation. The interventions will be combined to establish 5 arms: (1) BrainHQ; (2) BrainHQ + PASC-Cognitive Recovery; (3) BrainHQ + tDCS-active; (4) BrainHQ + tDCS-sham; and (5) Active Comparator. The interventions will occur for 10 weeks. Assessments will be completed at baseline and at the end of intervention and will include cognitive testing and patient-reported surveys. All study activities can be delivered in Spanish and English. Discussion This study is designed to test whether cognitive dysfunction symptoms can be alleviated by the use of pragmatic and established interventions with different mechanisms of action and with prior evidence of improving cognitive function in patients with neurocognitive disorder. If successful, results will provide beneficial treatments for PASC-related cognitive dysfunction. Trial registration ClinicalTrials.gov NCT05965739. Registered on July 25, 2023.

Abstract 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-β 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-β, 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-β 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.

Abstract This letter demonstrates the potential of novel cryptic proteins resulting from TAR DNA-binding protein 43 (TDP-43) dysfunction as markers of TDP-43 pathology in neurodegenerative diseases.

Abstract INTRODUCTION Age‐related and Alzheimer's disease (AD) dementia–related neurodegeneration impact brain health. While morphometric measures from T1‐weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker. METHODS We contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography. RESULTS Our study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age‐related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures. DISCUSSION These findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD. Highlights Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD). Free water fraction has higher sensitivity to normal brain aging. Free water fraction has stronger associations with early AD and regional tau deposition.

Abstract Background Uncovering the functional relevance underlying verbal declarative memory (VDM) genome-wide association study (GWAS) results may facilitate the development of interventions to reduce age-related memory decline and dementia. Methods We performed multi-omics and pathway enrichment analyses of paragraph (PAR-dr) and word list (WL-dr) delayed recall GWAS from 29,076 older non-demented individuals of European descent. We assessed the relationship between single-variant associations and expression quantitative trait loci (eQTLs) in 44 tissues and methylation quantitative trait loci (meQTLs) in the hippocampus. We determined the relationship between gene associations and transcript levels in 53 tissues, annotation as immune genes, and regulation by transcription factors (TFs) and microRNAs. To identify significant pathways, gene set enrichment was tested in each cohort and meta-analyzed across cohorts. Analyses of differential expression in brain tissues were conducted for pathway component genes. Results The single-variant associations of VDM showed significant linkage disequilibrium (LD) with eQTLs across all tissues and meQTLs within the hippocampus. Stronger WL-dr gene associations correlated with reduced expression in four brain tissues, including the hippocampus. More robust PAR-dr and/or WL-dr gene associations were intricately linked with immunity and were influenced by 31 TFs and 2 microRNAs. Six pathways, including type I diabetes, exhibited significant associations with both PAR-dr and WL-dr. These pathways included fifteen MHC genes intricately linked to VDM performance, showing diverse expression patterns based on cognitive status in brain tissues. Conclusions VDM genetic associations influence expression regulation via eQTLs and meQTLs. The involvement of TFs, microRNAs, MHC genes, and immune-related pathways contributes to VDM performance in older individuals.

Abstract INTRODUCTION This study aimed to assess whether social relationships in mid‐life reduce the risk of dementia related to amyloid burden. METHODS Participants in the Atherosclerosis Risk in Communities (ARIC) study were assessed for social support and isolation (visit 2; 1990–1992). A composite measure, “social relationships,” was generated. Brain amyloid was evaluated with florbetapir positron emission tomography (PET); (visit 5; 2012–2014). Incident dementia cases were identified following visit 5 through 2019 using ongoing surveillance. Relative contributions of mid‐life social relationships and elevated brain amyloid to incident dementia were evaluated with Cox regression models. RESULTS Among 310 participants without dementia, strong mid‐life social relationships were associated independently with lower dementia risk. Elevated late‐life brain amyloid was associated with greater dementia risk. DISCUSSION Although mid‐life social relationships did not moderate the relationship between amyloid burden and dementia, these findings affirm the importance of strong social relationships as a potentially protective factor against dementia.

Abstract Background Inclusions of TAR DNA-binding protein 43 kDa (TDP-43) has been designated limbic-predominant, age-related TDP-43 encephalopathy (LATE), with or without co-occurrence of Alzheimer’s disease (AD). Approximately, 30–70% AD cases present TDP-43 proteinopathy (AD-TDP), and a greater disease severity compared to AD patients without TDP-43 pathology. However, it remains unclear to what extent TDP-43 dysfunction is involved in AD pathogenesis. Methods To investigate whether TDP-43 dysfunction is a prominent feature in AD-TDP cases, we evaluated whether non-conserved cryptic exons, which serve as a marker of TDP-43 dysfunction in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD-TDP), accumulate in AD-TDP brains. We assessed a cohort of 192 post-mortem brains from three different brain regions: amygdala, hippocampus, and frontal cortex. Following RNA and protein extraction, qRT-PCR and immunoassays were performed to quantify the accumulation of cryptic RNA targets and phosphorylated TDP-43 pathology, respectively. Results We detected the accumulation of misspliced cryptic or skiptic RNAs of STMN2, KCNQ2, UNC13A, CAMK2B, and SYT7 in the amygdala and hippocampus of AD-TDP cases. The topographic distribution of cryptic RNA accumulation mimicked that of phosphorylated TDP-43, regardless of TDP-43 subtype classification. Further, cryptic RNAs efficiently discriminated AD-TDP cases from controls. Conclusions Overall, our results indicate that cryptic RNAs may represent an intriguing new therapeutic and diagnostic target in AD, and that methods aimed at detecting and measuring these species in patient biofluids could be used as a reliable tool to assess TDP-43 pathology in AD. Our work also raises the possibility that TDP-43 dysfunction and related changes in cryptic splicing could represent a common molecular mechanism shared between AD-TDP and FTLD-TDP.

Introduction: AD and CVD, which frequently co-occur, are leading causes of age-related cognitive decline. We assessed how demographic factors, socioeconomic status (SES) as indicated by education and occupation, vascular risk factors, and a range of biomarkers associated with both CVD (including white matter hyperintensities [WMH], diffusion MRI abnormalities, infarctions, and microbleeds) and AD (comprising amyloid-PET and tau-PET) collectively influence cognitive function. Methods: In this cross-sectional population study, structural equation models were utilized to understand these associations in 449 participants (mean age (SD) = 74.5 (8.4) years; 56% male; 7.5% cognitively impaired). Results: (1) Higher SES had a protective effect on cognition with mediation through the vascular pathway. (2) The effect of amyloid directly on cognition and through tau was 11-fold larger than the indirect effect of amyloid on cognition through WMH. (3) There is a significant effect of vascular risk on tau deposition. Discussion: The utilized biomarkers captured the impact of CVD and AD on cognition. The overall effect of vascular risk and SES on these biomarkers are complex and need further investigation.

Abstract INTRODUCTION This study evaluated the performance of the Lumipulse plasma beta‐amyloid (Aβ) 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 Aβ42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP‐MS) assay for plasma Aβ42/40 was also evaluated. Amyloid‐PET status was the outcome measure. RESULTS Lumipulse and IP‐MS Aβ42/40 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 Aβ42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aβ42/40 and pTau181 did not significantly improve performance over Aβ42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71) DISCUSSION The Lumipulse Aβ42/40 assay showed similar performance to the IP‐MS Aβ42/40 assay for detection of an abnormal amyloid‐PET; and both assays performed better than the two p‐tau181 immunoassays. The Simoa Aβ42/Aβ40 assay was the least accurate at predicting an abnormal amyloid‐PET status. Highlights Lumipulse plasma Aβ42/Aβ40 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.

Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18Fluorodeoxyglucose-positron emission tomography (FDG-PET) data from 39 patients with genetic FTLD, including 11 carrying the C9orf72 hexanucleotide expansion, 16 carrying a MAPT mutation and 12 carrying a GRN mutation. We performed a spectral covariance decomposition analysis between FDG-PET images to yield unbiased latent patterns reflective of whole brain patterns of metabolism (“eigenbrains” or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB-based predictions of genetic mutation and predominant clinical phenotype (i.e., behavior/personality, language, asymptomatic). Five EBs were significant and explained 58.52 % of the covariance between FDG-PET images. EBs indicative of hypometabolism in left frontotemporal and temporo-parietal areas distinguished GRN mutation carriers from other genetic mutations and were associated with predominant language phenotypes. EBs indicative of hypometabolism in prefrontal and temporopolar areas with a right hemispheric predominance were mostly associated with predominant behavioral phenotypes and distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 79.5 % and 76.9 % in predicting genetic status and predominant clinical phenotype, respectively. A small number of EBs explained a high proportion of covariance in patterns of network degeneration across FTLD-related genetic mutations. These EBs contained biological information relevant to the variability in the pathophysiological and clinical aspects of genetic FTLD, and for offering valuable guidance in complex clinical decision-making, such as decisions related to genetic testing.

Abstract Whether a relationship exists between cerebrovascular disease and Alzheimer’s disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer’s disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual’s amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = −0.07 to 0.07); early/late amyloid or tau timing explains

Objective To examine interactions between Neuropsychiatric symptoms (NPS) with Pittsburgh Compound B (PiB) and fluorodeoxyglucose positron emission tomography (FDG‐PET) in predicting cognitive trajectories. Methods We conducted a longitudinal study in the setting of the population‐based Mayo Clinic Study of Aging in Olmsted County, MN, involving 1581 cognitively unimpaired (CU) persons aged ≥50 years (median age 71.83 years, 54.0% males, 27.5% APOE ɛ4 carriers). NPS at baseline were assessed using the Neuropsychiatric Inventory Questionnaire (NPI‐Q). Brain glucose hypometabolism was defined as a SUVR ≤ 1.47 (measured by FDG‐PET) in regions typically affected in Alzheimer's disease. Abnormal cortical amyloid deposition was measured using PiB‐PET (SUVR ≥ 1.48). Neuropsychological testing was done approximately every 15 months, and we calculated global and domain‐specific (memory, language, attention, and visuospatial skills) cognitive z‐scores. We ran linear mixed‐effect models to examine the associations and interactions between NPS at baseline and z‐scored PiB‐ and FDG‐PET SUVRs in predicting cognitive z‐scores adjusted for age, sex, education, and previous cognitive testing. Results Individuals at the average PiB and without NPS at baseline declined over time on cognitive z‐scores. Those with increased PiB at baseline declined faster (two‐way interaction), and those with increased PiB and NPS declined even faster (three‐way interaction). We observed interactions between time, increased PiB and anxiety or irritability indicating accelerated decline on global z‐scores, and between time, increased PiB and several NPS (e.g., agitation) showing faster domain‐specific decline, especially on the attention domain. Conclusions NPS and increased brain amyloid deposition synergistically interact in accelerating global and domain‐specific cognitive decline among CU persons at baseline.

Abstract Background Advances in ultrasensitive detection of phosphorylated tau (p-tau) in plasma has enabled the use of blood tests to measure Alzheimer’s disease (AD) biomarker changes. Examination of postmortem brains of participants with antemortem plasma p-tau levels remains critical to understanding comorbid and AD-specific contribution to these biomarker changes. Methods We analyzed 35 population-based Mayo Clinic Study of Aging participants with plasma p-tau at threonine 181 and threonine 217 (p-tau181, p-tau217) available within 3 years of death. Autopsied participants included cognitively unimpaired, mild cognitive impairment, AD dementia, and non-AD neurodegenerative disorders. Global neuropathologic scales of tau, amyloid-β, TDP-43, and cerebrovascular disease were examined. Regional digital pathology measures of tau (phosphorylated threonine 181 and 217 [pT181, pT217]) and amyloid-β (6F/3D) were quantified in hippocampus and parietal cortex. Neurotransmitter hubs reported to influence development of tangles (nucleus basalis of Meynert) and amyloid-β plaques (locus coeruleus) were evaluated. Results The strongest regional associations were with parietal cortex for tau burden (p-tau181 R = 0.55, p = 0.003; p-tau217 R = 0.66, p

It is now widely known that research brain MRI, CT, and PET images may potentially be re-identified using face recognition, and this potential can be reduced by applying face-deidentification (“de-facing”) software. However, for research MRI sequences beyond T1-weighted (T1-w) and T2-FLAIR structural images, the potential for re-identification and quantitative effects of de-facing are both unknown, and the effects of de-facing T2-FLAIR are also unknown. In this work we examine these questions (where applicable) for T1-w, T2-w, T2*-w, T2-FLAIR, diffusion MRI (dMRI), functional MRI (fMRI), and arterial spin labelling (ASL) sequences. Among current-generation, vendor-product research-grade sequences, we found that 3D T1-w, T2-w, and T2-FLAIR were highly re-identifiable (96–98%). 2D T2-FLAIR and 3D multi-echo GRE (ME-GRE) were also moderately re-identifiable (44–45%), and our derived T2* from ME-GRE (comparable to a typical 2D T2*) matched at only 10%. Finally, diffusion, functional and ASL images were each minimally re-identifiable (0–8%). Applying de-facing with mri_reface version 0.3 reduced successful re-identification to ≤8%, while differential effects on popular quantitative pipelines for cortical volumes and thickness, white matter hyperintensities (WMH), and quantitative susceptibility mapping (QSM) measurements were all either comparable with or smaller than scan-rescan estimates. Consequently, high-quality de-facing software can greatly reduce the risk of re-identification for identifiable MRI sequences with only negligible effects on automated intracranial measurements. The current-generation echo-planar and spiral sequences (dMRI, fMRI, and ASL) each had minimal match rates, suggesting that they have a low risk of re-identification and can be shared without de-facing, but this conclusion should be re-evaluated if they are acquired without fat suppression, with a full-face scan coverage, or if newer developments reduce the current levels of artifacts and distortion around the face.

Abstract INTRODUCTION We examined associations between plasma‐derived biomarkers of Alzheimer's disease (AD) and neuropsychiatric symptoms (NPS) in community‐dwelling older adults. METHODS Cross‐sectional study involving 1005 persons ≥50 years of age (mean 74 years, 564 male, 118 cognitively impaired), who completed plasma‐derived biomarker (amyloid beta 42 [Aβ42]/Aβ40, phosphorylated tau 181 [p‐tau181], p‐tau217, total tau [t‐tau], neurofilament light [NfL]), and NPS assessment. RESULTS P‐tau181 (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.41–3.00, p

The clinical usefulness MRI biomarkers for aging and dementia studies relies on precise brain morphological measurements; however, scanner and/or protocol variations may introduce noise or bias. One approach to address this is post-acquisition scan harmonization. In this work, we evaluate deep learning (neural style transfer, CycleGAN and CGAN), histogram matching, and statistical (ComBat and LongComBat) methods. Participants who had been scanned on both GE and Siemens scanners (cross-sectional participants, known as Crossover (n = 113), and longitudinally scanned participants on both scanners (n = 454)) were used. The goal was to match GE MPRAGE (T1-weighted) scans to Siemens improved resolution MPRAGE scans. Harmonization was performed on raw native and preprocessed (resampled, affine transformed to template space) scans. Cortical thicknesses were measured using FreeSurfer (v.7.1.1). Distributions were checked using Kolmogorov-Smirnov tests. Intra-class correlation (ICC) was used to assess the degree of agreement in the Crossover datasets and annualized percent change in cortical thickness was calculated to evaluate the Longitudinal datasets. Prior to harmonization, the least agreement was found at the frontal pole (ICC = 0.72) for the raw native scans, and at caudal anterior cingulate (0.76) and frontal pole (0.54) for the preprocessed scans. Harmonization with NST, CycleGAN, and HM improved the ICCs of the preprocessed scans at the caudal anterior cingulate (>0.81) and frontal poles (>0.67). In the Longitudinal raw native scans, over- and under-estimations of cortical thickness were observed due to the changing of the scanners. ComBat matched the cortical thickness distributions throughout but was not able to increase the ICCs or remove the effects of scanner changeover in the Longitudinal datasets. CycleGAN and NST performed slightly better to address the cortical thickness variations between scanner change. However, none of the methods succeeded in harmonizing the Longitudinal dataset. CGAN was the worst performer for both datasets. In conclusion, the performance of the methods was overall similar and region dependent. Future research is needed to improve the existing approaches since none of them outperformed each other in terms of harmonizing the datasets at all ROIs. The findings of this study establish framework for future research into the scan harmonization problem.

Abstract Multi-compartment modelling of white matter microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) can provide information on white matter health through neurite density index and free water measures. We hypothesized that cerebrovascular disease, Alzheimer’s disease, and TDP-43 proteinopathy would be associated with distinct NODDI readouts of white matter damage which would be informative for identifying the substrate for cognitive impairment. We identified two independent cohorts with multi-shell diffusion MRI, amyloid and tau PET, and cognitive assessments: specifically, a population-based cohort of 347 elderly randomly sampled from the Olmsted county, Minnesota, population and a clinical research-based cohort of 61 amyloid positive Alzheimer’s dementia participants. We observed an increase in free water and decrease in neurite density using NODDI measures in the genu of the corpus callosum associated with vascular risk factors, which we refer to as the vascular white matter component. Tau PET signal reflective of 3R/4R tau deposition was associated with worsening neurite density index in the temporal white matter where we measured parahippocampal cingulum and inferior temporal white matter bundles. Worsening temporal white matter neurite density was associated with (antemortem confirmed) FDG TDP-43 signature. Post-mortem neuropathologic data on a small subset of this sample lend support to our findings. In the community-dwelling cohort where vascular disease was more prevalent, the NODDI vascular white matter component explained variability in global cognition (partial R2 of free water and neurite density = 8.3%) and MMSE performance (8.2%) which was comparable to amyloid PET (7.4% for global cognition and 6.6% for memory). In the AD dementia cohort, tau deposition was the greatest contributor to cognitive performance (9.6%), but there was also a non-trivial contribution of the temporal white matter component (8.5%) to cognitive performance. The differences observed between the two cohorts were reflective of their distinct clinical composition. White matter microstructural damage assessed using advanced diffusion models may add significant value for distinguishing the underlying substrate (whether cerebrovascular disease versus neurodegenerative disease caused by tau deposition or TDP-43 pathology) for cognitive impairment in older adults. Graphical abstract

Brain imaging research studies increasingly use “de-facing” software to remove or replace facial imagery before public data sharing. Several works have studied the effects of de-facing software on brain imaging biomarkers by directly comparing automated measurements from unmodified vs de-faced images, but most research brain images are used in analyses of correlations with cognitive measurements or clinical statuses, and the effects of de-facing on these types of imaging-to-cognition correlations has not been measured. In this work, we focused on brain imaging measures of amyloid (A), tau (T), neurodegeneration (N), and vascular (V) measures used in Alzheimer’s Disease (AD) research. We created a retrospective sample of participants from three age- and sex-matched clinical groups (cognitively unimpaired, mild cognitive impairment, and AD dementia, and we performed region- and voxel-wise analyses of: hippocampal volume (N), white matter hyperintensity volume (V), amyloid PET (A), and tau PET (T) measures, each from multiple software pipelines, on their ability to separate cognitively defined groups and their degrees of correlation with age and Clinical Dementia Rating (CDR)–Sum of Boxes (CDR-SB). We performed each of these analyses twice: once with unmodified images and once with images de-faced with leading de-facing software mri_reface, and we directly compared the findings and their statistical strengths between the original vs. the de-faced images. Analyses with original and with de-faced images had very high agreement. There were no significant differences between any voxel-wise comparisons. Among region-wise comparisons, only three out of 55 correlations were significantly different between original and de-faced images, and these were not significant after correction for multiple comparisons. Overall, the statistical power of the imaging data for AD biomarkers was almost identical between unmodified and de-faced images, and their analyses results were extremely consistent.

Background: Aging and dementia involve the disruption of brain molecular pathways leading to the alterations in tissue composition and gross morphology of the brain. Phenotypic and biomarker overlap between various etiologies of dementia supports a need for new modes of information to more accurately distinguish these disorders. Brain mechanical properties, which can be measured noninvasively by MR elastography, represent one understudied feature that are sensitive to neurodegenerative processes. In this study, we used two stiffness estimation schemes to test the hypothesis that different etiologies of dementia are associated with unique patterns of mechanical alterations across the cerebral cortex. Methods: MR elastography data were acquired for six clinical groups including amyloid-negative cognitively unimpaired (CU), amyloid-positive cognitively unimpaired (A + CU), amyloid-positive participants with mild cognitive impairment (A + MCI), amyloid-positive participants with Alzheimer’s clinical syndrome (A + ACS), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). Stiffness maps were computed using two neural network inversions with the objective to at least partially separate the parenchyma-specific and morphological effects of neurodegeneration on mechanical property estimates. A tissue-confined inversion algorithm was designed to obtain the best estimate of stiffness in the brain parenchyma itself, while a regionally-aware inversion algorithm was used to measure the tissue stiffness along with the surroundings. Mean stiffness of 15 bilateral gray matter cortical regions were considered for statistical analysis. First, we tested the hypothesis that cortical stiffness changes in the aging brain. Next, we tested the overall study hypothesis by first comparing stiffness in each clinical group to the CU group, and then comparing the clinical groups against one another. Finally, we assessed the spatial and statistical overlap between atrophy and stiffness changes for both inversions. Results: Cortical brain regions become softer with age for both inversions with larger effects observed using regionally-aware stiffness. Stiffness decreases in the range 0.010–0.027 kPa per year were observed. Pairwise comparisons of each clinical group with cognitively unimpaired participants demonstrated 5 statistically significant differences in stiffness for tissue-confined measurements and 19 statistically different stiffness changes for the regionally-aware stiffness measurements. Pairwise comparisons between clinical groups further demonstrated unique patterns of stiffness differences. Analysis of the atrophy-versus-stiffness relationship showed that regionally-aware stiffness measurements exhibit higher sensitivity to neurodegeneration with findings that are not fully explained by partial volume effects or atrophy. Conclusions: Both tissue-confined and regionally-aware stiffness estimates exhibited unique and complementary stiffness differences in various etiologies of dementia. Our results suggest that mechanical alterations measured by MRE reflect both tissue-specific differences as well as environmental effects. Multi-inversion schemes in MRE may provide new insights into the relationships between neuropathology and brain biomechanics.

Abstract Background Total tau protein (T-Tau) and neurofilament light chain (NfL) have emerged as candidate plasma biomarkers of neurodegeneration, but studies have not compared how these biomarkers cross-sectionally or longitudinally associate with cognitive and neuroimaging measures. We therefore compared plasma T-Tau and NfL as cross-sectional and longitudinal markers of (1) global and domain-specific cognitive decline and (2) neuroimaging markers of cortical thickness, hippocampal volume, white matter integrity, and white matter hyperintensity volume. Methods We included 995 participants without dementia who were enrolled in the Mayo Clinic Study of Aging cohort. All had concurrent plasma NfL and T-tau, cognitive status, and neuroimaging data. Follow-up was repeated approximately every 15 months for a median of 6.2 years. Plasma NfL and T-tau were measured on the Simoa-HD1 Platform. Linear mixed effects models adjusted for age, sex, and education examined associations between baseline z-scored plasma NfL or T-tau and cognitive or neuroimaging outcomes. Analyses were replicated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) among 387 participants without dementia followed for a median of 3.0 years. Results At baseline, plasma NfL was more strongly associated with all cognitive and neuroimaging outcomes. The combination of having both elevated NfL and T-tau at baseline, compared to elevated levels of either alone, was more strongly associated at cross-section with worse global cognition and memory, and with neuroimaging measures including temporal cortex thickness and increased number of infarcts. In longitudinal analyses, baseline plasma T-tau did not add to the prognostic value of baseline plasma NfL. Results using ADNI data were similar. Conclusions Our results indicate plasma NfL had better utility as a prognostic marker of cognitive decline and neuroimaging changes. Plasma T-tau added cross-sectional value to NfL in specific contexts. Trial registration Not applicable

It is well known that de-identified research brain images from MRI and CT can potentially be re-identified using face recognition; however, this has not been examined for PET images. We generated face reconstruction images of 182 volunteers using amyloid, tau, and FDG PET scans, and we measured how accurately commercial face recognition software (Microsoft Azure's Face API) automatically matched them with the individual participants’ face photographs. We then compared this accuracy with the same experiments using participants’ CT and MRI. Face reconstructions from PET images from PET/CT scanners were correctly matched at rates of 42% (FDG), 35% (tau), and 32% (amyloid), while CT were matched at 78% and MRI at 97-98%. We propose that these recognition rates are high enough that research studies should consider using face de-identification (“de-facing”) software on PET images, in addition to CT and structural MRI, before data sharing. We also updated our mri_reface de-identification software with extended functionality to replace face imagery in PET and CT images. Rates of face recognition on de-faced images were reduced to 0-4% for PET, 5% for CT, and 8% for MRI. We measured the effects of de-facing on regional amyloid PET measurements from two different measurement pipelines (PETSurfer/FreeSurfer 6.0, and one in-house method based on SPM12 and ANTs), and these effects were small: ICC values between de-faced and original images were > 0.98, biases were

Background The contribution of atrial cardiopathy to dementia risk is uncharacterized. We aimed to evaluate the association of atrial cardiopathy with incident dementia and potential mediation by atrial fibrillation (AF) and stroke. Methods and Results We conducted a prospective cohort analysis of participants in the ARIC (Atherosclerosis Risk in Communities) study attending visit 5 (2011–2013). We used Cox regression to determine the association between atrial cardiopathy and risk of dementia. Structural equation modeling methods were used to determine potential mediation by AF and/or stroke. Atrial cardiopathy was defined if ≥1 of the following at visit 5: P‐wave terminal force >5000 mV·ms in ECG lead V1, NT‐proBNP (N‐terminal pro–brain natriuretic peptide) >250 pg/mL or left atrial volume index ≥34 mL/m2 by transthoracic echocardiography. We repeated our analysis necessitating ≥2 markers to define atrial cardiopathy. The prevalence of atrial cardiopathy was 34% in the 5078 participants (mean age 75 years, 59% female, 21% Black adults), with 763 participants developing dementia. Atrial cardiopathy was significantly associated with dementia (adjusted HR, 1.35 [95% CI, 1.16–1.58]), with strengthening of the effect estimate when necessitating ≥2 biomarkers (adjusted HR, 1.54 [95% CI, 1.25–1.89]). There was an increased risk of dementia among those with atrial cardiopathy when excluding those with AF (adjusted HR, 1.31 [95% CI, 1.12–1.55]) or stroke (adjusted HR, 1.28 [95% CI, 1.09–1.52]). The proportion of the effect mediated by AF was 4% (P=0.005), and 9% was mediated by stroke (P=0.048). Conclusions Atrial cardiopathy was significantly associated with an increased risk of dementia, with only a small percent mediation of the effect by AF or stroke.

Abstract Although abnormal accumulation of amyloid in the brain is an early biomarker of Alzheimer’s disease (AD), wide variation in cognitive trajectories during life can be seen in the setting of brain amyloidosis, ranging from maintenance of normal function to progression to dementia. It is widely presumed that cognitive resilience (i.e., coping) to amyloidosis may be influenced by environmental, lifestyle, and inherited factors, but relatively little in specifics is known about this architecture. Here, we leveraged multimodal longitudinal data from a large, population-based sample of older adults to discover genetic factors associated with differential cognitive resilience to brain amyloidosis determined by positron emission tomography (PET). Among amyloid-PET positive older adults, the AD risk allele APOE ɛ4 was associated with worse longitudinal memory trajectories as expected, and was thus covaried in the main analyses. Through a genome-wide association study (GWAS), we uncovered a novel association with cognitive resilience on chromosome 8 at the MTMR7/CNOT7/ZDHHC2/VPS37A locus (p = 4.66 × 10–8, β = 0.23), and demonstrated replication in an independent cohort. Post-hoc analyses confirmed this association as specific to the setting of elevated amyloid burden and not explained by differences in tau deposition or cerebrovascular disease. Complementary gene-based analyses and publically available functional data suggested that the causative variant at this locus may tag CNOT7 (CCR4-NOT Transcription Complex Subunit 7), a gene linked to synaptic plasticity and hippocampal-dependent learning and memory. Pathways related to cell adhesion and immune system activation displayed enrichment of association in the GWAS. Our findings, resulting from a unique study design, support the hypothesis that genetic heterogeneity is one of the factors that explains differential cognitive resilience to brain amyloidosis. Further characterization of the underlying biological mechanisms influencing cognitive resilience may facilitate improved prognostic counseling, therapeutic application, and trial enrollment in AD.

White matter hyperintensities (WMH) are a common brain-imaging feature of cerebral small vessel disease. Here, the authors carry out a GWAS and followup analyses for WMH-volume, implicating several variants with potential for risk stratification and drug targeting.

Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adults at risk of cognitive decline. Using deep learning models augmented with a model-interpretation technique on data from 1432 Mayo Clinic Study of Aging participants, we identified a subset of brain structures that were most predictive of individualized cognitive trajectories and indicative of cognitively resilient vs. vulnerable individuals. Specifically, these structures explained why some participants were resilient to the deleterious effects of elevated brain amyloid and poor vascular health. Of these, medial temporal lobe and fornix, reflective of age and pathology-related degeneration, and corpus callosum, reflective of inter-hemispheric disconnection, accounted for 60% of the heterogeneity explained by the most predictive structures. Our results are valuable for identifying cognitively vulnerable individuals and for developing interventions for cognitive decline.

Abstract Objective To assess the relationships between MRI volumetry and [18F]flortaucipir PET of typical and atypical clinical phenotypes of Alzheimer’s disease, by genarian (age by decade). Methods Five‐hundred and sixty‐four participants including those with typical (n = 86) or atypical (n = 80) Alzheimer’s dementia and normal controls (n = 398) underwent apolipoprotein E genotyping, MRI, flortaucipir, and 11C‐PiB; all 166 Alzheimer’s participants were beta‐amyloid positive and all controls were beta‐amyloid negative. Grey matter volume and flortaucipir standard uptake value ratios were calculated for hippocampus, entorhinal cortex, and neocortex. Ratios of hippocampal‐to‐neocortical and entorhinal‐to‐neocortical volume and flortaucipir uptake were also calculated. Linear regression models assessed relationships among regional volume, flortaucipir uptake, and ratios and phenotypes, within three genarians (50–59, 60–69, and 70+). Voxel‐level analyses were also performed. Results For 50–59 greater medial temporal atrophy and flortaucipir uptake was observed in the typical compared with atypical phenotype. The typical phenotype also showed greater frontal neocortex uptake with the voxel‐level analysis. For 60–69 and 70+ there was greater hippocampal volume loss in the typical compared with atypical phenotype while only the 60–69, but not the 70+ group, showed a difference in hippocampal flortaucipir uptake. We also observed a pattern for higher neocortical flortaucipir uptake to correlate with younger age decade for both phenotypes. Interpretation MRI volumetry versus flortaucipir PET relationships differ across Alzheimer’s clinical phenotypes, and also within phenotype across age decades. This suggests that there is potential risk of masked effects by not accounting for genarian in participants with beta‐amyloid and tau‐positive biomarker defined Alzheimer’s disease.

Abstract Objective To examine the association of baseline elevated brain amyloid and neurodegeneration with changes in activities of daily living in participants without dementia (ND; i.e., cognitively unimpaired and participants with mild cognitive impairment) at baseline in the population‐based Mayo Clinic Study of Aging. Methods We included 1747 ND participants with 11C‐PiB PET and MR imaging in the study, with data on activities of daily living (as assessed by the Functional Activities Questionnaire (FAQ) and the Clinical Dementia Rating scale Sum of Boxes for functional domains (CDR‐SOB (functional)), with a median (range) of 4.3 (0.0–12.7) years of follow‐up. Abnormal (elevated; A+) 11C‐PiB‐PET retention ratio was defined as standardized uptake value ratio ≥ 1.48, and abnormal (reduced) AD signature cortical thickness as ≤ 2.68 mm (neurodegeneration; N+). Associations were examined with mixed effects models, adjusting for age, sex, education, apolipoprotein E ε4 allele carrier status, and global cognitive z‐score. Results Mean age (SD) was 71.4 years (10.1), 46.7% were females, 195 (11.2%) had A+N‐, 442 (25.3%) had A‐N+, and 339 (19.4%) had A+N+ biomarkers. The A+N+ group had the largest annualized change in the FAQ score from baseline (difference in annual change A+N+ vs. A‐N‐; ß (SE): 0.80 (0.07)); associations were substantially attenuated when a time‐varying global cognitive composite was included in the model (A+N+ vs. A‐N‐; ß (SE): 0.31 (0.05)). CDR‐SOB (functional) findings partly agreed with FAQ score findings. Interpretation The longitudinal increase in functional limitations is greater for individuals with abnormal neuroimaging biomarkers, especially for those with both elevated brain amyloid and neurodegeneration.

Our goal was to understand the complex relationship between age, sex, midlife risk factors, and early white matter changes measured by diffusion tensor imaging (DTI) and their role in the evolution of longitudinal white matter hyperintensities (WMH). We identified 1564 participants (1396 cognitively unimpaired, 151 mild cognitive impairment and 17 dementia participants) with age ranges of 30–90 years from the population-based sample of Mayo Clinic Study of Aging. We used computational causal structure discovery and regression analyses to evaluate the predictors of WMH and DTI, and to ascertain the mediating effect of DTI on WMH. We further derived causal graphs to understand the complex interrelationships between midlife protective factors, vascular risk factors, diffusion changes, and WMH. Older age, female sex, and hypertension were associated with higher baseline and progression of WMH as well as DTI measures (P ≤ 0.003). The effects of hypertension and sex on WMH were partially mediated by microstructural changes measured on DTI. Higher midlife physical activity was predictive of lower WMH through a direct impact on better white matter tract integrity as well as an indirect effect through reducing the risk of hypertension by lowering BMI. This study identified key risks factors, early brain changes, and pathways that may lead to the evolution of WMH.

Transactive response DNA-binding protein of ∼43 kDa (TDP-43), a primary pathologic substrate in tau-negative frontotemporal lobar degeneration (FTLD), is also often found in the brains of elderly individuals without FTLD and is a key player in the process of neurodegeneration in brains with and without FTLD. It is unknown how rates and trajectories of TDP-43-associated brain atrophy compare between these two groups. Additionally, non-FTLD TDP-43 inclusions are not homogeneous and can be divided into two morphologic types: type-α and neurofibrillary tangle-associated type-β. Therefore, we explored whether neurodegeneration also varies due to the morphologic type. In this longitudinal retrospective study of 293 patients with 843 MRI scans spanning over ∼10 years, we used a Bayesian hierarchical linear model to quantify similarities and differences between the non-FTLD TDP-43 (type-α/type-β) and FTLD-TDP (n = 68) in both regional volume at various timepoints before death and annualized rate of atrophy. Since Alzheimer’s disease (AD) is a frequent co-pathology in non-FTLD TDP-43, we further divided types α/β based on presence/absence of intermediate-high likelihood AD: AD-TDP type-β (n = 90), AD-TDP type-α (n = 104), and Pure-TDP (n = 31, all type-α). FTLD-TDP was associated with faster atrophy rates in the inferior temporal lobe and temporal pole compared to all non-FTLD TDP-43 groups. The atrophy rate in the frontal lobe was modulated by age with younger FTLD-TDP having the fastest rates. Older FTLD-TDP showed a limbic predominant pattern of neurodegeneration. AD-TDP type-α showed faster rates of hippocampal atrophy and smaller volumes of amygdala, temporal pole, and inferior temporal lobe compared to AD-TDP type-β. Pure-TDP was associated with slowest rates and less atrophy in all brain regions. The results suggest that there are differences and similarities in longitudinal brain volume loss between FTLD-TDP and non-FTLD TDP-43. Within FTLD-TDP age plays a role in which brain regions are the most affected. Additionally, brain atrophy regional rates also vary by non-FTLD TDP-43 type.

Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating local tissue magnetic susceptibility properties at every voxel. Iron deposition patterns are well studied in typical Alzheimer’s disease (tAD), but little is known about these patterns in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). Seventeen PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five-echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions-of-interest across the brain using the Mayo Clinic Adult Lifespan Template. Bayesian hierarchical models were fit per-region and per-hemisphere to compare PCA, LPA, 63 healthy controls, and 20 tAD patients. Strong evidence (posterior probability > 0.99) was observed for greater susceptibility in the middle occipital gyrus and amygdala in both LPA and PCA, and in the right inferior parietal, inferior temporal, and angular gyri in PCA and the caudate and substantia nigra in LPA compared to controls. Moderate evidence for greater susceptibility (posterior probability > 0.90) was also observed in the inferior occipital gyrus, precuneus, putamen and entorhinal cortex in both LPA and PCA, along with superior frontal gyrus in PCA and inferior temporal gyri, insula and basal ganglia in LPA, when compared to controls. Between phenotypic comparisons, LPA had greater susceptibility in the caudate, hippocampus, and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right superior frontal and middle temporal gyri compared to LPA. Both LPA and PCA showed moderate and strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions, while tAD showed greater susceptibility in the hippocampus and basal ganglia. This study proposes the possibility of unique iron profiles existing between LPA and PCA within cortical and subcortical structures. These changes match well with the disease-related changes of the clinical phenotypes, suggesting that QSM could be an informative candidate marker to study iron deposition in these patients.

Using positron emission tomography (PET)-derived amyloid and tau measurements from 1,495 participants, we explore the evolution of these values over time via an accelerated failure time (AFT) model. The AFT model assumes a shared pattern of progression, but one which is shifted earlier or later in time for each individual; an individual's time shift for amyloid and for tau are assumed to be linked. The resulting pattern for each outcome consists of an earlier indolent phase followed by sharp progression of the accumulation rate. APOE ε4 shifts the amyloid curve leftward (earlier) by 6.1 years, and the tau curve leftward by 2.6 years. Female sex shifts the amyloid curve leftward by 2.4 years and the tau curve leftward by 2.6 years. Per-person shifts (i.e., the individual's deviation from the population mean) for the onset of amyloid accumulation ranged from 13 years earlier to 13 years later (10th to 90th percentile) than average and 11 years earlier to 14 years later for tau, with an estimated correlation of 0.49. The average delay between amyloid increase and tau increase was 13.3 years.

Objective: To investigate whether APOE ε4 genotype—an established risk factor for dementia—is associated with earlier age at diagnosis in addition to increased risk overall and in secondary analysis by race and sex.Methods: We followed up 13,782 dementia-free individuals (n = 10,137 White, n = 3,645 Black, baseline age 60–66 years) in the Atherosclerosis Risk in Communities study for up to 30 years. Dementia was operationalized using standardized algorithms incorporating longitudinal cognitive change, proxy report, and hospital or death certificate dementia codes. We used a mixture of generalized gamma distributions to simultaneously estimate time to dementia, time to dementia-free death, and the proportion of individuals with dementia, by APOE ε4 status (≥1 vs. no alleles).Results: Median age of dementia onset among APOE ε4 carriers was 81.7 (Blacks) and 83.3 years (Whites) compared with 82.6 (Blacks) and 85.7 years (Whites) in non-APOE ε4 carriers (p > 0.05 Blacks; p < 0.01 Whites). Age of dementia diagnosis did not differ by sex in ε4 carriers, but among non-carriers, average age was earlier in males than females regardless of race. APOE ε4 carriers had on average a higher proportion of diagnoses; results did not differ by race or sex.Conclusions:APOE ε4 carrier status is associated with earlier age of dementia diagnosis with differences across race and sex. These findings clarify the causal role of APOE in dementia etiology, which could help better identify at-risk subgroups and may help facilitate better research trial recruitment and design.

Since tau PET tracers were introduced, investigators have quantified them using a wide variety of automated methods. As longitudinal cohort studies acquire second and third time points of serial within-person tau PET data, determining the best pipeline to measure change has become crucial. We compared a total of 415 different quantification methods (each a combination of multiple options) according to their effects on a) differences in annual SUVR change between clinical groups, and b) longitudinal measurement repeatability as measured by the error term from a linear mixed-effects model. Our comparisons used MRI and Flortaucipir scans of 97 Mayo Clinic study participants who clinically either: a) were cognitively unimpaired, or b) had cognitive impairments that were consistent with Alzheimer's disease pathology. Tested methods included cross-sectional and longitudinal variants of two overarching pipelines (FreeSurfer 6.0, and an in-house pipeline based on SPM12), three choices of target region (entorhinal, inferior temporal, and a temporal lobe meta-ROI), five types of partial volume correction (PVC) (none, two-compartment, three-compartment, geometric transfer matrix (GTM), and a tau-specific GTM variant), seven choices of reference region (cerebellar crus, cerebellar gray matter, whole cerebellum, pons, supratentorial white matter, eroded supratentorial WM, and a composite of eroded supratentorial WM, pons, and whole cerebellum), two choices of region masking (GM or GM and WM), and two choices of statistic (voxel-wise mean vs. median). Our strongest findings were: 1) larger temporal-lobe target regions greatly outperformed entorhinal cortex (median sample size estimates based on a hypothetical clinical trial were 520–526 vs. 1740); 2) longitudinal processing pipelines outperformed cross-sectional pipelines (median sample size estimates were 483 vs. 572); and 3) reference regions including supratentorial WM outperformed traditional cerebellar and pontine options (median sample size estimates were 370 vs. 559). Altogether, our results favored longitudinally SUVR methods and a temporal-lobe meta-ROI that includes adjacent (juxtacortical) WM, a composite reference region (eroded supratentorial WM + pons + whole cerebellum), 2-class voxel-based PVC, and median statistics.

Background White matter abnormalities are a common feature of aging and Alzheimer disease, and tend to be more severe among Black individuals. However, the extent to which white matter abnormalities relate to amyloid deposition, a marker of Alzheimer pathology, remains unclear. This cross‐sectional study examined the association of white matter abnormalities with cortical amyloid in a community sample of older adults without dementia and examined the moderating effect of race. Methods and Results Participants from the ARIC‐PET (Atherosclerosis Risk in Communities‐Positron Emission Tomography) study underwent brain magnetic resonance imaging, which quantified white matter hyperintensity volume and microstructural integrity using diffusion tensor imaging. Participants received florbetapir positron emission tomography imaging to measure brain amyloid. Associations between measures of white matter structure and elevated amyloid status were examined using multivariable logistic regression. Among 322 participants (43% Black), each SD increase in white matter hyperintensity volume was associated with a greater odds of elevated amyloid (odds ratio [OR], 1.37; 95% CI, 1.03–1.83) after adjusting for demographic and cardiovascular risk factors. In race‐stratified analyses, a greater white matter hyperintensity volume was more strongly associated with elevated amyloid among Black participants (OR, 2.00; 95% CI, 1.15–3.50), compared with White participants (OR, 1.29; 95% CI, 0.89–1.89). However, the race interaction was not statistically significant (P interaction=0.09). We found no association between white matter microstructure and elevated amyloid. Conclusions The results suggest a modest positive relationship between white matter hyperintensity and elevated amyloid in older adults without dementia. Although the results indicate that this association is nonsignificantly stronger among Black participants, these findings will need to be confirmed or refuted using larger multiracial cohorts.

Abstract The majority of the clinico-pathological variability observed in patients harboring a repeat expansion in the C9orf72-SMCR8 complex subunit (C9orf72) remains unexplained. This expansion, which represents the most common genetic cause of frontotemporal lobar degeneration (FTLD) and motor neuron disease (MND), results in a loss of C9orf72 expression and the generation of RNA foci and dipeptide repeat (DPR) proteins. The C9orf72 protein itself plays a role in vesicular transport, serving as a guanine nucleotide exchange factor that regulates GTPases. To further elucidate the mechanisms underlying C9orf72-related diseases and to identify potential disease modifiers, we performed an extensive RNA sequencing study. We included individuals for whom frontal cortex tissue was available: FTLD and FTLD/MND patients with (n = 34) or without (n = 44) an expanded C9orf72 repeat as well as control subjects (n = 24). In total, 6706 genes were differentially expressed between these groups (false discovery rate [FDR]

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Disproportionately enlarged subarachnoid-space hydrocephalus (DESH), characterized by tight high convexity CSF spaces, ventriculomegaly, and enlarged Sylvian fissures, is thought to be an indirect marker of a CSF dynamics disorder. The clinical significance of DESH with regard to cognitive decline in a community setting is not yet well defined. The goal of this work is to determine if DESH is associated with cognitive decline. Participants in the population-based Mayo Clinic Study of Aging (MCSA) who met the following criteria were included: age ≥ 65 years, 3T MRI, and diagnosis of cognitively unimpaired or mild cognitive impairment at enrollment as well as at least one follow-up visit with cognitive testing. A support vector machine based method to detect the DESH imaging features on T1-weighted MRI was used to calculate a “DESH score”, with positive scores indicating a more DESH-like imaging pattern. For the participants who were cognitively unimpaired at enrollment, a Cox proportional hazards model was fit with time defined as years from enrollment to first diagnosis of mild cognitive impairment or dementia, or as years to last known cognitively unimpaired diagnosis for those who did not progress. Linear mixed effects models were fit among all participants to estimate annual change in cognitive z scores for each domain (memory, attention, language, and visuospatial) and a global z score. For all models, covariates included age, sex, education, APOE genotype, cortical thickness, white matter hyperintensity volume, and total intracranial volume. The hazard of progression to cognitive impairment was an estimated 12% greater for a DESH score of +1 versus −1 (HR 1.12, 95% CI 0.97–1.31, p = 0.11). Global and attention cognition declined 0.015 (95% CI 0.005–0.025) and 0.016 (95% CI 0.005–0.028) z/year more, respectively, for a DESH score of +1 vs −1 (p = 0.01 and p = 0.02), with similar, though not statistically significant DESH effects in the other cognitive domains. Imaging features of disordered CSF dynamics are an independent predictor of subsequent cognitive decline in the MCSA, among other well-known factors including age, cortical thickness, and APOE status. Therefore, since DESH contributes to cognitive decline and is present in the general population, identifying individuals with DESH features may be important clinically as well as for selection in clinical trials.

Recent advances in automated face recognition algorithms have increased the risk that de-identified research MRI scans may be re-identifiable by matching them to identified photographs using face recognition. A variety of software exist to de-face (remove faces from) MRI, but their ability to prevent face recognition has never been measured and their image modifications can alter automated brain measurements. In this study, we compared three popular de-facing techniques and introduce our mri_reface technique designed to minimize effects on brain measurements by replacing the face with a population average, rather than removing it. For each technique, we measured 1) how well it prevented automated face recognition (i.e. effects on exceptionally-motivated individuals) and 2) how it altered brain measurements from SPM12, FreeSurfer, and FSL (i.e. effects on the average user of de-identified data). Before de-facing, 97% of scans from a sample of 157 volunteers were correctly matched to photographs using automated face recognition. After de-facing with popular software, 28-38% of scans still retained enough data for successful automated face matching. Our proposed mri_reface had similar performance with the best existing method (fsl_deface) at preventing face recognition (28-30%) and it had the smallest effects on brain measurements in more pipelines than any other, but these differences were modest.

Brain infarctions are closely associated with future risk of stroke and dementia. Our goal was to report (i) frequency and characteristics that differentiate symptomatic vs. silent brain infarctions (SBI) on MRI and (ii) frequency and location by vascular distribution (location of stroke by major vascular territories) in a population based sample. From Mayo Clinic Study of Aging, 347 participants (≥50 years) with infarcts detected on their first MRI were included. Infarct information was identified visually on a FLAIR MRI image and a vascular territory atlas was registered to the FLAIR image data in order to identify the arterial territory of infarction. We identified the subset with a clinical history of stroke based on medical chart review and used a logistic regression to evaluate the risk factors associated with greater probability of a symptomatic stroke vs. SBI. We found that 14% of all individuals with infarctions had a history of symptomatic stroke (Silent: n = 300, symptomatic: n = 47). Factors associated with a symptomatic vs. SBI were size which had an odds ratio of 3.07 (p < 0.001), greater frequency of hypertension (odds ratio of 4.12, p = 0.025) and alcohol history (odds ratio of 4.58, p = 0.012). The frequency of infarcts was greater in right hemisphere compared to the left for SBI. This was primarily driven by middle cerebral artery (MCA) infarcts (right = 60%, left = 40%, p = 0.005). While left hemisphere strokes are more common for symptomatic carotid disease and in clinical trials, right hemispheric infarcts may be more frequent in the SBI group.

Altered iron metabolism has been hypothesized to be associated with Alzheimer's disease pathology, and prior work has shown associations between iron load and beta amyloid plaques. Quantitative susceptibility mapping (QSM) is a recently popularized MR technique to infer local tissue susceptibility secondary to the presence of iron as well as other minerals. Greater QSM values imply greater iron concentration in tissue. QSM has been used to study relationships between cerebral iron load and established markers of Alzheimer's disease, however relationships remain unclear. In this work we study QSM signal characteristics and associations between susceptibility measured on QSM and established clinical and imaging markers of Alzheimer's disease. The study included 421 participants (234 male, median age 70 years, range 34–97 years) from the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center; 296 (70%) had a diagnosis of cognitively unimpaired, 69 (16%) mild cognitive impairment, and 56 (13%) amnestic dementia. All participants had multi-echo gradient recalled echo imaging, PiB amyloid PET, and Tauvid tau PET. Variance components analysis showed that variation in cortical susceptibility across participants was low. Linear regression models were fit to assess associations with regional susceptibility. Expected increases in susceptibility were found with older age and cognitive impairment in the deep and inferior gray nuclei (pallidum, putamen, substantia nigra, subthalamic nucleus) (betas: 0.0017 to 0.0053 ppm for a 10 year increase in age, p = 0.03 to

Background and Purpose: Patients with dementia with Lewy bodies (DLB) are characterized by hypometabolism in the parieto–occipital cortex and the cingulate island sign (CIS) on 18F-fluorodeoxyglucose (FDG) PET. Whether this pattern of hypometabolism is present as early as the prodromal stage of DLB is unknown. We investigated the pattern of hypometabolism in patients with mild cognitive impairment (MCI) who progressed to probable DLB compared to MCI patients who progressed to Alzheimer’s disease (AD) dementia and clinically unimpaired (CU) controls. Methods: Patients with MCI from the Mayo Clinic Alzheimer’s Disease Research Center who underwent FDG PET at baseline and progressed to either probable DLB (MCI-DLB; n = 17) or AD dementia (MCI-AD; n = 41) during follow-up, and a comparison cohort of CU controls (n = 100) were included. Results: Patients with MCI-DLB had hypometabolism in the parieto-occipital cortex extending into temporal lobes, substantia nigra and thalamus. When compared to MCI-AD, medial temporal and posterior cingulate metabolism were preserved in patients with MCI-DLB, accompanied by greater hypometabolism in the substantia nigra in MCI-DLB compared to MCI-AD. In distinguishing MCI-DLB from MCI-AD at the maximum value of Youden’s index, CIS ratio was highly specific (90%) but not sensitive (59%), but a higher medial temporal to substantia nigra ratio was both sensitive (94%) and specific (83%). Conclusion: FDG PET is a potential biomarker for the prodromal stage of DLB. A higher medial temporal metabolism and CIS ratio, and lower substantia nigra metabolism have additive value in distinguishing prodromal DLB and AD.

Abstract Demonstrating that treatments are clinically meaningful across the Alzheimer's disease (AD) continuum is critical for meeting our goals of accelerating a cure by 2025. While this topic has been a focus of several Alzheimer's Association Research Roundtable (AARR) meetings, there remains no consensus as to what constitutes a “clinically meaningful outcome” in the eyes of patients, clinicians, care partners, policymakers, payers, and regulatory bodies. Furthermore, the field has not come to agreement as to what constitutes a clinically meaningful treatment effect at each stage of disease severity. The AARR meeting on November 19–20, 2019, reviewed current approaches to defining clinical meaningfulness from various perspectives including those of patients and care partners, clinicians, regulators, health economists, and public policymakers. Participants discussed approaches that may confer clinical relevance at each stage of the disease continuum and fostered discussion about what should guide us in the future.

Abstract Introduction The aim of this study was to examine white matter hyperintensities (WMH) and fractional anisotropy (FA) in empirically derived incident mild cognitive impairment (MCI) subtypes. Methods We evaluated 188 participants with incident MCI in the Mayo Clinic Study of Aging (MCSA) identified as having one of four cluster‐derived subtypes: subtle cognitive impairment, amnestic, dysnomic, and dysexecutive. We used linear regression models to evaluate whole brain and regional WMH volumes. We examined fractional anisotropy (FA) on a subset of 63 participants with diffusion tensor imaging. Results Amnestic and dysexecutive subtypes had higher WMH volumes in differing patterns than cognitively unimpaired; the dysexecutive subtype had higher WMH than subtle cognitive impairment. There was widespread WM degeneration in long association and commissural fibers in the amnestic, dysnomic, and dysexecutive subtypes, and corpus callosum FA accounted for significant variability in global cognition. Discussion White matter changes likely contribute to cognitive symptoms in incident MCI.

Background: Limited information exists regarding the association between midlife lipid levels and late-life total and regional brain volumes. Methods: We studied 1872 participants in the longitudinal community-based Atherosclerosis Risk in Communities Neurocognitive Study. Serum lipid levels were measured in 1987–1989 (mean age, 53 ± 5 years). Participants underwent 3T brain MRI scans in 2011–2013. Brain volumes were measured using FreeSurfer image analysis software. Linear regression models were used to assess the associations between serum lipids and brain volumes modeled in standard deviation (SD) units, adjusting for potential confounders. Results: In adjusted analyses, one SD higher low-density lipoprotein cholesterol (LDL) levels were associated with larger total brain volumes (β 0.033, 95% CI 0.006–0.060) as well as larger volumes of the temporal (β 0.038, 95% CI 0.003–0.074) and parietal lobes (β 0.044, 95% CI 0.009–0.07) and Alzheimer disease-related region (β 0.048, 95% CI 0.048–0.085). Higher triglyceride levels were associated with smaller total brain volumes (β -0.033, 95% CI -0.060, -0.007). The associations between LDL levels and brain volumes were modified by age (P for interaction 53 years at baseline, and were attenuated after application of weights to account for informative attrition, although associations with the parietal and Alzheimer's disease-related region remained significant. High-density lipoprotein cholesterol was not associated with brain volumes. Conclusion: Higher LDL levels in late midlife were associated with larger brain volumes later in life, while higher triglyceride levels were associated with smaller brain volumes. These associations were driven by adults >53 years at baseline.

Background Atrial fibrillation (AF) is a risk factor for cognitive decline, possibly from silent brain infarction. Left atrial changes in structure or function (atrial cardiopathy) can lead to AF but may impact cognition independently. It is unknown if AF or atrial cardiopathy also acts on Alzheimer disease–specific mechanisms, such as deposition of β‐amyloid. Methods and Results A total of 316 dementia‐free participants from the ARIC (Atherosclerosis Risk in Communities) study underwent florbetapir positron emission tomography, electrocardiography, and 2‐dimensional echocardiography. Atrial cardiopathy was defined as ≥1: (1) left atrial volume index >34 mL/m2; (2) P‐wave terminal force >5000 µV×ms; and (3) serum NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) >250 pg/mL. Cross‐sectional associations between global cortical β‐amyloid (>1.2 standardized uptake value ratio) and adjudicated history of AF and atrial cardiopathy, each, were evaluated using multivariable logistic regression. Participants (mean age, 76 years) were 56% women and 42% Black individuals. Odds of elevated florbetapir standardized uptake value ratio were significantly increased among those with atrial cardiopathy (odds ratio, 1.81; 95% CI, 1.02–3.22) and doubled for those with enlarged left atrial volume index after adjustment for demographics/risk factors (95% CI, 1.04–4.61). There was no association between P‐wave terminal force or NT‐proBNP and elevated florbetapir standardized uptake value ratio, nor between AF and elevated standardized uptake value ratio. Conclusions Among healthy, nondemented community‐dwelling older individuals, we report an association between atrial cardiopathy, left atrial volume index, and elevated brain amyloid, by positron emission tomography, without a similar association in individuals with AF. Potential limitations include reverse causation and survival bias. Ongoing work will help determine if changes in cardiac structure and function precede or occur simultaneously with amyloid deposition.

Background The impact of the new 2017 American College of Cardiology/American Heart Association (ACC/AHA) hypertension guideline on dementia risk at the population level has not been evaluated. Methods and Results We studied dementia‐free participants in the ARIC (Atherosclerosis Risk in Communities) Study cohort in 1987 to 1989. Hypertension was defined by 2003 Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure and 2017 ACC/AHA guidelines using blood pressure measured at baseline. Dementia was defined using adjudicated consensus diagnoses, informant telephone interviews, and discharge codes from hospitalizations and death certificates. Cox regression estimated hazard ratios (HRs) for dementia and 95% CIs by hypertension categories, adjusting for confounders. Population attributable fraction of dementia was calculated by hypertension categories. Among 13 971 participants followed up for a median of 23 years, 1381 dementia cases were identified. Prevalence of hypertension was 34% and 48%, according to the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure and ACC/AHA criteria, respectively. HRs (95% CIs) compared with normal blood pressure, according to ACC/AHA categories, were 1.35 (1.12–1.61) for elevated blood pressure, 1.28 (1.07–1.52) for hypertension stage 1, and 1.36 (1.18–1.57) for hypertension stage 2. Population attributable fractions (95% CIs) of dementia from blood pressure categories were 3% (1%–5%), 3% (1%–5%), and 9% (4%–14%), respectively. Population attributable fractions (95% CIs) using the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure categories were 6% (3%–9%) for prehypertension, 0% (−2% to 2%) for hypertension stage 1, and 9% (5%–13%) for hypertension stage 2. Conclusions Risk of dementia increased across hypertension categories defined by ACC/AHA guidelines. The population impact on dementia incidence using ACC/AHA categories was similar to the impact of the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.