Jack, Clifford R.

AbstractBackgroundFew normative data for computerized measures administered in unsupervised remote environments are available. We aimed to determine what variables to include in normative models for remote self‐administered assessments, develop normative data for measures administered through Mayo Test Drive (MTD, a multi‐device remote cognitive assessment platform) and evaluate application of norms.Method1240 adults ages 33‐100 (96% White) from the Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center met normative sample inclusion criteria that included a concordant Cognitively Unimpaired (CU) diagnosis (3 independent raters all diagnosed CU) and CDR = 0 (see Table 1 for sample characteristics). Raw test scores were converted to normalized scaled scores. We derived regression‐based normative data that adjusted for age, age2, sex and education (base model); alternative models are also provided (age+age2+sex; age+ age2). We evaluated whether additional model terms beyond the base model were needed using an a priori cut‐off of 1% variance improvement in adjusted R2 over and above the base model. We examined rates of low test performance defined as performance below ‐1 SD in independent validation samples (n = 167 concordant CU, n = 64 mild cognitive impairment (MCI), n = 14 dementia). Rates are considered significantly different than expected when 95% confidence intervals (CIs) do not include the expected 14.7% base rate frequency.ResultNo additional potential model terms met our a priori cut‐off for inclusion beyond the base model (see Table 2), including other quadratic and cubic terms or interactions, device type, response input type, potential session interference, and national area deprivation index (ADI available in subset; N = 776). Application of norms showed expected rates of low test performance among CU participants (95% CI includes expected base rate) and significantly greater than expected rates of low test performance for all variables in MCI (e.g., 62.5% for composite) and dementia (e.g., 71.4% for composite; see Table 3).ConclusionTypical normative models appear appropriate for remote self‐administered measures and are sensitive to cognitive impairment. Device type and response input did not explain enough variance to warrant inclusion in normative models but are important for individual level interpretation. Future work will improve representation of individuals from under‐represented groups.

AbstractBackgroundLimbic‐predominant age‐related TDP‐43 encephalopathy (LATE) is a neuropathologically‐defined disease, and it is frequently comorbid with Alzheimer’s disease neuropathological change (ADNC). However, the neurological syndrome associated with LATE neuropathological change (LATE‐NC) is not defined. We propose a set of clinical criteria for a limbic‐predominant amnestic neurodegenerative syndrome (LANS) that is highly associated with LATE‐NC. These criteria assess degree of certainty (highest, high, moderate, low) based on features that are measurable in vivo, including older age at evaluation, a mild clinical syndrome, impaired semantic knowledge, disproportionate hippocampal atrophy, limbic hypometabolism, absence of neocortical degeneration patterns and low likelihood of neocortical tau. We operationalized these criteria using two large datasets with clinical and pathologic outcomes.MethodWe screened autopsied patients from Mayo Clinic and ADNI cohorts and applied the LANS criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; ADNI, n = 53). We compared frequencies of neuropathological diagnoses across LANS likelihoods, compared longitudinal CDR‐SB trajectories across LANS likelihoods, and stratified ADNC/LATE‐NC patients according to their LANS likelihood and compared their longitudinal CDR‐SB trajectories to those with ADNC or LATE‐NC.ResultADNC, ADNC/LATE‐NC and LATE‐NC accounted for 35%, 37% and 4% of cases in the Mayo cohort, respectively, and 30%, 22%, and 9% of cases in the ADNI cohort, respectively (Fig. 1). ADNC cases had the lowest LANS likelihoods, LATE‐NC patients had the highest likelihoods, and ADNC/LATE‐NC patients had intermediate likelihoods. Patients with high LANS likelihoods had a milder and slower clinical course and more severe temporo‐limbic degeneration compared to those with low likelihoods (Fig. 2). ADNC/LATE‐NC patients with higher likelihoods had more temporo‐limbic degeneration and a slower rate of cognitive decline, and those with lower likelihoods had more lateral temporo‐parietal degeneration and a faster rate of cognitive decline (Fig. 3).ConclusionThe implementation of LANS criteria has implications for disambiguating the different driving etiologies of progressive amnestic presentations in older age to guide prognosis, treatment, and clinical trial design and enrollment. The development of in vivo biomarkers specific to TDP‐43 pathology are needed to further refine molecular associations between LANS and LATE‐NC and precise antemortem diagnoses of LATE.

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

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

Abstract Objective To assess the association of systolic and diastolic blood pressure (SBP and DBP) in recently menopausal women with white matter hyperintensity (WMH) volume later in life and determine whether short-term menopausal hormone therapy (mHT) modifies these associations. Methods Kronos Early Estrogen Prevention Study (KEEPS) was a multicenter, randomized, double-blinded, placebo-controlled 4-year mHT trial (oral conjugated equine estrogens or transdermal 17β-estradiol). KEEPS continuation was an observational follow-up of the participants 10 years after the end of mHT. The associations between KEEPS baseline blood pressure (BP) with KEEPS continuation WMH volume were examined adjusting for covariates in model 1 (age, total intracranial volume, study site, mHT type) and model 2 (additionally conventional CVD risk factors). Interaction terms (BP × mHT type) were added into the linear regression models. Results The mean ± SD ages of participants were 53 (±2) years at KEEPS baseline and 67 (±2) years at KEEPS continuation. Elevated BP at KEEPS baseline was associated with greater WMH volume measured 14 years later (model 1: SBP: β = 0.01 [95% CI, 0.001‐0.01] and DBP: β = 0.01 [95% CI, 0.003‐0.03]) and after additionally adjusting for CVD risk factors (model 2). We did not find any evidence that mHT versus placebo modified these associations. Topographically, higher BP was associated with greater periventricular WMH in the frontal and parietal lobes. Conclusion Our findings suggest the importance of maintaining normal BP in recently postmenopausal women with low CVD risk, irrespective of short-term mHT usage, to potentially reduce the risk of WMH later in life.

Abstract The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to optimize and validate biomarkers for clinical trials while sharing all data and biofluid samples with the global scientific community. ADNI has been instrumental in standardizing and validating amyloid beta (Aβ) and tau positron emission tomography (PET) imaging. ADNI data were used for the US Food and Drug Administration (FDA) approval of the Fujirebio and Roche Elecsys cerebrospinal fluid diagnostic tests. Additionally, ADNI provided data for the trials of the FDA‐approved treatments aducanumab, lecanemab, and donanemab. More than 6000 scientific papers have been published using ADNI data, reflecting ADNI's promotion of open science and data sharing. Despite its enormous success, ADNI has some limitations, particularly in generalizing its data and findings to the entire US/Canadian population. This introduction provides a historical overview of ADNI and highlights its significant accomplishments and future vision to pioneer “the clinical trial of the future” focusing on demographic inclusivity. Highlights The Alzheimer's Disease Neuroimaging Initiative (ADNI) introduced a novel model for public‐private partnerships and data sharing. It successfully validated amyloid and Tau PET imaging, as well as CSF and plasma biomarkers, for diagnosing Alzheimer's disease. ADNI generated and disseminated vital data for designing AD clinical trials.

Abstract The newly proposed revised criteria for diagnosis and staging of Alzheimer's disease (AD) by the Alzheimer's Association (AA) Workgroup represent a significant milestone in the field. These criteria offer objective measures for diagnosing and staging biological AD, bridging the gap between research and clinical care. Although implementation feasibility may vary across regions and settings, improving the availability and accuracy of biomarkers, especially plasma biomarkers, is expected to enhance the applicability of these criteria in clinical practice. The Fall 2023 Alzheimer's Association Research Roundtable (AARR) meeting served as a forum for gathering industry perspectives and feedback on these revised criteria, ensuring that the new criteria inform research, clinical trial design, and clinical care. In this article, we outline a summary of the newly proposed “Revised Criteria for Diagnosis and Staging of AD: AA Workgroup” and provide highlights from the AARR meeting in fall 2023. Highlights The Alzheimer's Association Research Roundtable (AARR) convened leaders from industry, academia, and government, to review the Revised Criteria for Diagnosis and Staging of AD: AA Workgroup , and gather industry perspectives and feedback on these revised criteria before its publication. The newly proposed revised criteria for diagnosis and staging of Alzheimer's disease (AD) by the AA's Workgroup represent a significant milestone, offering objective measures for the biological and staging of AD and bridging the gap between research and clinical care. Improving the availability and accuracy of biomarkers, especially blood‐based biomarkers (BBMs) is expected to improve clinical research and enhance the applicability of these criteria in clinical practice.

AbstractBackground and purposeLower left atrial (LA) function is associated with higher dementia risk and may be mechanistically linked through vascular brain injury, an established correlate for higher dementia risk. Using data from the Atherosclerosis Risk in Communities study, we assessed the cross‐sectional association between LA function and brain magnetic resonance imaging (MRI) markers of vascular brain injury.MethodsWe included 1488 participants who were free of prevalent dementia, stroke, or atrial fibrillation and who underwent a two‐dimensional echocardiogram and brain MRI in 2011–2013 (mean [± standard deviation] age 76 [± 5] years, 60% female, 27% Black). LA function measures (reservoir, conduit, contractile strain) were assessed in quartiles. Brain MRI measures included cerebral microbleeds, brain infarcts, and white matter hyperintensity (WMH) volume. Logistic regression was used for dichotomous outcomes. Linear regression was used for WMH volume.ResultsOverall, 343 (23%) and 344 participants (23%) had ≥1 cerebral microbleed or brain infarct. After multivariable adjustments, the lowest LA reservoir and conduit strain quartiles (vs. highest quartile) were associated with higher odds of the presence of ≥1 cerebral microbleed (odds ratios [95% confidence intervals] 1.78 [1.42–2.22] and 1.52 [1.22–1.90]). Compared to the highest quartile, participants in the lowest LA conduit strain quartile had 1.51 (95% confidence interval 1.22–1.88) times higher odds of having ≥1 brain infarct. Lower LA contractile strain was associated with lower odds of brain infarcts. No association with WMH volume was noted.ConclusionsWe found that LA reservoir and conduit strain were associated with cerebral microbleeds and brain infarcts. Lower LA function may be linked to dementia risk via vascular brain injury. Prospective studies are needed to confirm these findings.

Abstract INTRODUCTION A key goal of the Alzheimer's Disease NeuroImaging Initiative (ADNI) positron emission tomography (PET) Core is to harmonize quantification of β‐amyloid (Aβ) and tau PET image data across multiple scanners and tracers. METHODS We developed an analysis pipeline (Berkeley PET Imaging Pipeline, B‐PIP) for ADNI Aβ and tau PET images and applied it to PET data from other multisite studies. Steps include image pre‐processing, refacing, magnetic resonance imaging (MRI)/PET co‐registration, visual quality control (QC), quantification of tracer uptake, and standardization of Aβ and tau standardized uptake value ratios (SUVrs) across tracers. RESULTS Measurements from 10,105 cross‐sectional and longitudinal Aβ and tau PET scans acquired in several studies between 2010 and 2024 can be processed, harmonized, and directly merged across tracers and cohorts. DISCUSSION The B‐PIP developed in ADNI is a scalable image harmonization approach used in several observational studies and clinical trials that facilitates rigorous Aβ and tau PET quantification and data sharing. Highlights Quantitative results from ADNI Aβ and tau PET data are generated using a rigorous, scalable image processing pipeline This pipeline has been applied to PET data from several other large, multisite studies and trials Quantitative outcomes are harmonizable across studies and are shared with the scientific community