Citations

Objective Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) differ in many respects. Here, we address the issue of possible differences in fibrillar amyloid pathology as measured by positron emission tomography (PET), which remains unresolved due to the lack of large‐scale comparative studies. Methods Three hundred ninety‐nine cognitively impaired participants younger than 65 years of age from the multicenter Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) and 450 cognitively impaired participants older than 65 years from the Alzheimer's Disease Neuroimaging Initiative (ADNI) underwent clinical assessment, brain magnetic resonance imaging (MRI), and amyloid PET and were included in this study. We compared amyloid PET outcomes (positivity rate based on visual read and quantified tracer uptake expressed as Centiloids [CLs]) between the 2 cohorts and studied their association with age, sex, APOE genotype, and cognition. Results The amyloid positivity rate was higher in LEADS (78%, 95% confidence interval [CI] = 74–82) than in ADNI (71%, 95% CI = 67–75, p = 0.02). Lower Mini‐Mental State Examination (MMSE) and APOE4 genotype increased the odds of amyloid positivity in both cohorts. Visually positive scans had higher CLs in LEADS (EOAD, mean = 95.3 ± 26.1) than in ADNI (LOAD, mean = 80.9 ± 36.8, p < 0.0001), predominantly in parietal cortex/precuneus, superior temporal, and frontal cortices. In amyloid‐positive patients, (1) CLs were higher in female patients in both cohorts; (2) APOE4 carriership was associated with lower CLs in EOAD, which was not observed in LOAD; and (3) correlations between CLs and MMSE scores were significantly stronger in EOAD than in LOAD. Interpretation Differences in the burden of amyloid pathology may contribute to differences in clinical and anatomic patterns in sporadic EOAD and LOAD, and have implications for optimizing therapeutic strategies in each group. ANN NEUROL 2025;98:236–248

Background Neuropsychiatric symptoms (NPS) are frequent in Alzheimer's disease (AD) dementia, but a higher NPS burden is found in dementia with Lewy bodies (DLB). Lewy body (LB) pathology frequently co-occurs with AD pathology and may not meet neuropathological criteria for DLB (ADLB). NPS trajectories over disease course in these subgroups is not well understood. Objective We investigated changes in NPS severity over time, at two time points, comparing clinicopathologically defined cohorts of AD (without LB), ADLB, DLB, and controls. Methods Cases with two available Neuropsychiatric Inventory-Questionnaire (NPIQ), at the time of enrollment and within 2.5 years of death, were selected from the Arizona Study of Aging and Neurodegenerative Disorders. Differences and rate of change in NPIQ scores were compared between AD (n = 75), ADLB (n = 48) DLB (n = 65), and controls (n = 32) with covariates for age, sex, and cognition. Results First NPIQ scores were highest in ADLB when compared to AD (p = 0.04) and controls (p = 0.01) but not different from DLB. A significant increase in NPS severity was observed in DLB and AD (p < 0.001) over a mean follow up time of 4.9 ± 3.0 years, and the rate of change was significantly greater in DLB when compared to other groups. Final NPIQ scores were highest in DLB when compared to AD (p = 0.03) but not ADLB, and in DLB, ADLB, and AD than controls ( all p < 0.001). Conclusions Early NPS burden as well as NPS severity progression rate, independently of cognitive status, might be useful clinical metrics and may help predict underlying pathological diagnoses.

Abstract INTRODUCTION Early‐onset and late‐onset Alzheimer's disease (EOAD and LOAD, respectively) have distinct clinical manifestations, with prior work based on small samples suggesting unique patterns of neurodegeneration. The current study performed a head‐to‐head comparison of cortical atrophy in EOAD and LOAD, using two large and well‐characterized cohorts (LEADS and ADNI). METHODS We analyzed brain structural magnetic resonance imaging (MRI) data acquired from 377 sporadic EOAD patients and 317 sporadicLOAD patients who were amyloid positive and had mild cognitive impairment (MCI) or mild dementia (i.e., early‐stage AD), along with cognitively unimpaired participants. RESULTS After controlling for the level of cognitive impairment, we found a double dissociation between AD clinical phenotype and localization/magnitude of atrophy, characterized by predominant neocortical involvement in EOAD and more focal anterior medial temporal involvement in LOAD. DISCUSSION Our findings point to the clinical utility of MRI‐based biomarkers of atrophy in differentiating between EOAD and LOAD, which may be useful for diagnosis, prognostication, and treatment. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset AD (LOAD) patients showed distinct and overlapping cortical atrophy patterns. EOAD patients showed prominent atrophy in widespread neocortical regions. LOAD patients showed prominent atrophy in the anterior medial temporal lobe. Regional atrophy was correlated with the severity of global cognitive impairment. Results were comparable when the sample was stratified for mild cognitive impairment (MCI) and dementia.

AbstractBackgroundAnti‐amyloid monoclonal antibody therapies for AD have documented plaque removal on amyloid PET scans. We evaluate the findings for amyloid PET, tau PET, FDG PET and volumetric MRI over the course the open label extension (OLE) for the DIAN‐TU gantenerumab treatment, compared to the last imaging obtained prior to the OLE (to evaluate for potential rebound effects) and in comparison to longitudinal imaging in the DIAN Observational study.MethodThis double‐blind, phase 2/3 trial (2012‐2019), followed by open‐label extension (OLE), investigated varying gantenerumab doses up to 1500 mg SQ q2 weeks [NCT NCT01760005]. We report long‐term amyloid‐plaque removal by PET and findings for metabolic FDG PET and tau PET, and additionally changes of atrophy on volumetric MRI. Imaging measures were secondary outcome analyses. Comparison is made between the treatment cohort and controls (DB placebo participants who didn’t enter OLE, plus external controls from the DIAN OBS). Estimated years to onset was included as a covariate. The gap period of ∼1 year is specifically analyzed to estimate any “rebound” effect on amyloid or tau accumulation or neurodegeneration. Volumetric MRI measures include hippocampal volumes, lateral ventricular volumes, and white matter hyperintensities.ResultIn participants who were asymptomatic at baseline and treated with gantenerumab (n = 53), amyloid‐plaque removal measured by PIB‐PET in Centiloids was dose‐dependent. Few participants had reached completely negative levels (below 24). No statistical significance was found for FDG PET, tau PET, or volumetric MRI, including hippocampal volumes. Impact of the gap period of ∼1 year (gap in treatment) on the rate of amyloid accumulation compared to the rate of accumulation predicted in observational studies of this cohort is under evaluation, as are the other imaging measures.ConclusionWhile no overall effect was observed in the total group for non‐amyloid measures, results suggest dose dependent clearance of amyloid plaque in asymptomatic DIAD mutation carriers following long‐term, high‐dose gantenerumab. The potential “rebound effect” of elevated amyloid accumulation for participants for whom there was a significant gap in therapy between the trial and the OLE is under evaluation and will be presented, as will the variables for FDG PET, tau PET, and volumetric MRI.

AbstractBackgroundMild Cognitive Impairment (MCI) is a pre‐dementia state where impaired cognitive domains (memory, executive, visuospatial processing, language) may predict underlying pathology, e.g. Alzheimer’s disease(AD), Lewy body (LB), and other. Delineating neuropathological heterogeneity in MCI and their associations with neuropsychological profiles are important in identifying individuals at risk of further deterioration. We aimed to characterize the neuropathological heterogeneity in cases with a diagnosis of MCI.MethodCases with a final consensus cognitive diagnosis of MCI (n = 128) prior to death were selected from the Arizona Study of Aging and Neurodegenerative disorders (AZSAND). Groups were divided into amnestic (aMCI) and non‐amnestic MCI (naMCI), single and multi‐domain impairment, and specific domain impairment (executive, language, visuospatial) was explored. Presence and severity of neuropathology including AD, LB, cerebral white matter rarefaction (CWMR), cerebral amyloid angiopathy (CAA), cerebral infarcts and microinfarcts (cortical and subcortical), TAR DNA‐binding protein 43 (TDP‐43), and apolipoprotein E (ApoE) status were compared between MCI subtypes.ResultThe number of cases meeting neuropathological criteria for AD was not different between aMCI (36.4%) and naMCI (22.6%) while co‐existent PD was less frequent in aMCI (19.5% vs 38.7%). When compared to naMCI (n = 31), the aMCI (n = 85) group had an older age of death (p = 0.001), less educational years (p = 0.04), a higher number of subcortical infarcts (p = 0.012), a higher regional density of neurofibrillary tangles (p = 0.027) and a lower density of LB (p = 0.015) in the temporal lobe, and CWMR in tended to be more severe in the frontal lobe (p = 0.052). Those with single domain aMCI had less CWMR (p = 0.001) compared to the multidomain. Within the naMCI group, those with single domain MCI had higher proportions of CAA (p = 0.042), and lower LB density (p = 0.019) compared to multidomain. CWMR was more severe (p = 0.026) inConclusionA high heterogeneity was observed between MCI subtypes. While AD pathology was similar between groups, regional anatomical differences were observed. Vascular pathology including subcortical infarcts, CWMR and CAA appear to be commonly associated with both aMCI and naMCI respectively while CWMR was associated with executive dysfunctions. CWMR, CAA and LBs appear to be more frequent in multidomain aMCI and naMCI respectively.

AbstractBackgroundLewy body (LB) diseases can present with overlapping prodromal, cognitive, motor, autonomic or neuropsychiatric symptoms. Intuitively, greater symptom severity should correlate with greater pathological burden, but this has not been consistently shown. LB pathology does not translate to clinical expression in Incidental LB disease. While several composite scores/toolkits utilize overlapping schemes for diagnosis, a composite data‐derived score to predict LB pathologic burden is lacking. We aimed to utilize an autopsy‐confirmed cohort, and validated, brief, and standardized clinical, functional, pathologic assessments, and machine learning (ML)/quantitative modeling techniques to identify clusters and importance rankings among assessments/measures to predict LB pathologic severity and density.MethodA total of 234 subjects with neuropathological finding of LB at autopsy in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) who were classified as Cognitively Unimpaired or Mild Cognitive Impairment after their first study clinical evaluation were included. Of these, 145 subjects had complete scores for 32 of 46 measures (clinical, cognitive, behavioral and functional) that were utilized as predictors of LB pathology. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). LB severity was assessed by the Unified Staging System for Lewy Body Disorders (USSLB). Several ML algorithms and quantitative prediction models were explored and compared: artificial neural network (ANN), partial least square regression (PLSR), support vector regression (SVR), relevance vector regression (RVR) and ensemble forest regression (EFR) with leave‐one‐out (LOO) scheme. Game‐theory based Shapley methods assessed the impact, including rankings, consistency and magnitude, of model predictors.ResultRVR predicted aggregate LB density with large effect size (R2 = 0.691, p<0.00001). ANN predicted USSLB severity stage with large effect size (R2 = 0.74, p<2.5e‐43). All other ML algorithms/models provided substantial prediction. Across all models, UPSIT was the most influential predictor (>65%), followed by Controlled Oral Word Association Test (COWAT) and age.ConclusionThese preliminary and exploratory results support the utilization of ML techniques/models to assess LB pathologic burden with key measures collected in relatively small samples. UPSIT was consistently ranked highest impactful among clinical and functional measures/predictors. Integrated together in ML/data‐derived composites, UPSIT, COWAT and other clinical characteristics may be of antemortem utility to predict USSLB stages.

Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. Through a modified‐Delphi approach and guideline‐development process (7374 publications were reviewed; 133 met inclusion criteria) an expert workgroup developed recommendations as steps in a patient‐centered evaluation process. This summary focuses on recommendations, appropriate for any practice setting, forming core elements of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes specialist recommendations. If clinicians use this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings. Highlights US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. This summary focuses on recommendations, appropriate for any practice setting, forming core elements of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes specialist recommendations. If clinicians use this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings.

Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or a related dementia (ADRD) are two decades old. This evidence‐based guideline was developed to empower all clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. An expert workgroup conducted a review of 7374 publications (133 met inclusion criteria) and developed recommendations as steps in an evaluation process. This summary briefly reviews core recommendations and details specialist recommendations of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes primary care recommendations. If clinicians use the recommendations in this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings. Highlights US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's disease (AD) or related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. This summary focuses on recommendations appropriate for specialty practice settings, forming key elements of a high‐quality, evidence‐supported evaluation process aimed at characterizing, diagnosing, and disclosing the patient's cognitive functional status, cognitive–behavioral syndrome, and likely underlying brain disease so that optimal care plans to maximize patient/care partner dyad quality of life can be developed; a companion article summarizes primary care recommendations. If clinicians use this guideline and health‐care systems provide adequate resources, outcomes should improve in most patients in most practice settings.

Abstract US clinical practice guidelines for the diagnostic evaluation of cognitive impairment due to Alzheimer's Disease (AD) or AD and related dementias (ADRD) are decades old and aimed at specialists. This evidence‐based guideline was developed to empower all—including primary care—clinicians to implement a structured approach for evaluating a patient with symptoms that may represent clinical AD/ADRD. As part of the modified Delphi approach and guideline development process (7374 publications were reviewed; 133 met inclusion criteria) an expert workgroup developed recommendations as steps in a patient‐centered evaluation process. The workgroup provided a summary of validated instruments to measure symptoms in daily life (including cognition, mood and behavior, and daily function) and to test for signs of cognitive impairment in the office. This article distills this information to provide a resource to support clinicians in the implementation of this approach in clinical practice. The companion articles provide context for primary care and specialty clinicians with regard to how to fit these instruments into the workflow and actions to take when integration of performance on these instruments with clinical profile and clinician judgment support potential cognitive impairment.