Biomarkers.

Background: There is a strong link between tau and progression of Alzheimer's disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity-based tau spreading model in AD variants with distinct tau deposition patterns is crucial.

Biomarkers.

Background: Diagnosing sporadic early-onset AD (EOAD, age-at-onset<65) is challenging: in the multi-center Longitudinal Early-onset Alzheimer's Disease Study, ∼25% of patients with clinically diagnosed EOAD are amyloid-PET-negative. Here we used FDG-PET to characterize the heterogeneity of hypometabolic profiles in these patients and better identify underlying etiologies.

Method: Seventy-four amyloid-PET-negative patients with clinical diagnosis of sporadic EOAD (MCI or mild dementia stage) underwent FDG-PET.

Biomarkers.

Background: APOE-ɛ4 is a major risk factor for Alzheimer's disease (AD); its effects have been examined in late-onset AD (LOAD) but less so in early-onset AD (EOAD). In LOAD, APOE genotype has strong effects on episodic memory and medial temporal lobe (MTL) atrophy (Wolk & Dickerson, 2010). However, EOAD often presents with more cognitive impairments in executive function, language, and visuospatial abilities than memory.

Biomarkers.

Background: There is a significant need for biomarkers of neurodegenerative burden in Early-onset Alzheimer's disease (EOAD). Evidence suggests that levels of specific CSF biomarkers (e.g.

Biomarkers.

Background: Prior work has advanced our understanding of cortical atrophy in early-onset Alzheimer's disease (EOAD), but longitudinal data are sparse. Current longitudinal MRI studies point to progressive atrophy in cerebral cortex exhibiting a posterior-to-anterior gradient, but these studies include small samples with mostly amnestic EOAD. Here, we analyzed a large sample of sporadic EOAD patients from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) to test the central hypothesis that areas in our recently described EOAD signature (Touroutoglou et al.

Biomarkers.

Background: Understanding how early-onset Alzheimer's disease (EOAD) differs from typical late-onset AD (LOAD) is an important goal of AD research that may help increase the sensitivity of unique biomarkers for each phenotype. Building upon prior work based on small samples, here we leveraged two large, well-characterized natural history study cohorts of AD patients (LEADS and ADNI3) to test the hypothesis that EOAD patients would show more prominent lateral and medial parietal and lateral temporal cortical atrophy sparing the medial temporal lobe (MTL), whereas LOAD patients would show prominent MTL atrophy.

Method: We investigated differences in the spatial topography of cortical atrophy between EOAD and LOAD patients by analyzing structural MRI data collected from 211 patients with sporadic EOAD and 88 cognitively unimpaired (CU) participants from the LEADS cohort as well as 144 patients with LOAD and 365 CU participants from the ADNI3 cohort.

Biomarkers.

Background: Large-scale studies comparing sporadic early-onset AD (EOAD, age<65) and late-onset AD (LOAD, age≥65) are lacking. We compared amyloid-PET outcomes (positivity rate and amyloid burden) between patients clinically diagnosed with sporadic EOAD vs LOAD, leveraging data from the Longitudinal Early-Onset AD Study (LEADS) and the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI3).

Method: 731 patients meeting the 2011 NIA-AA criteria for AD dementia or MCI were included (505 early-onset from LEADS, 226 late-onset from ADNI3, Table 1).

Biomarkers.

Background: The relationship between CSF measures of Alzheimer disease (AD) pathologies and their neurodegenerative signatures is not fully understood. This study seeks to employ machine learning approaches on clinical MRI data to identify patterns associated with amyloid and tau, aiming to guide diagnosis and therapeutic interventions.

Method: We selected brain volumes that differed significantly between AD pathology and control groups.

Biomarkers.

Background: Neurodegeneration in sporadic early-onset Alzheimer disease (EOAD) is topographically heterogeneous, as suggested by variability in syndromic presentation. We performed an unsupervised clustering analysis of structural MRI data to identify anatomical subtypes of EOAD. We hypothesized that distinct clusters will be present but will: (1) share areas of overlap focused around posterior regions of our newly developed EOAD signature of cortical atrophy (Touroutoglou et al.

Developing Topics.

Background: Regional brain atrophy estimated from structural MRI is the most widely used measure of neurodegeneration in Alzheimer's disease (AD), Frontotemporal Lobar Degeneration (FTLD), and other dementias. Yet, traditional MRI-derived morphometric estimates are susceptible to measurement errors, posing a challenge for reliably detecting longitudinal atrophy, particularly over short intervals. We examined the utility of multiple accelerated MRI scans acquired in rapid succession (i.

Developing Topics.

Background: Early-onset Alzheimer's disease (EOAD) occurs before age 65 and has more diverse disease presentations than late-onset AD. To improve our understanding of phenotypic heterogeneity among EOAD individuals, we analyzed cognitive scores using data-driven statistical analysis.

Method: Baseline cognitive data from 286 sporadic EOAD individuals from the Longitudinal EOAD study (LEADS) were transformed to z-scores using data from 95 cognitively normal (CN) individuals.

Alzheimer's Imaging Consortium.

Background: There is a strong link between tau and progression of Alzheimer's disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity-based tau spreading model in AD variants with distinct tau deposition patterns is crucial.

Alzheimer's Imaging Consortium.

Background: Large-scale studies comparing sporadic early-onset AD (EOAD, age<65) and late-onset AD (LOAD, age = 65) are lacking. We compared amyloid-PET outcomes (positivity rate and amyloid burden) between patients clinically diagnosed with sporadic EOAD vs LOAD, leveraging data from the Longitudinal Early-Onset AD Study (LEADS) and the Alzheimer's Disease Neuroimaging Initiative 3 (ADNI3).

Method: 731 patients meeting the 2011 NIA-AA criteria for AD dementia or MCI were included (505 early-onset from LEADS, 226 late-onset from ADNI3, Table 1).

Alzheimer's Imaging Consortium.

Background: Diagnosing sporadic early-onset AD (EOAD, age-at-onset<65) is challenging: in the multi-center Longitudinal Early-onset Alzheimer's Disease Study, ∼25% of patients with clinically diagnosed EOAD are amyloid-PET-negative. Here we used FDG-PET to characterize the heterogeneity of hypometabolic profiles in these patients and better identify underlying etiologies.

Method: Seventy-four amyloid-PET-negative patients with clinical diagnosis of sporadic EOAD (MCI or mild dementia stage) underwent FDG-PET.

Alzheimer's Imaging Consortium.

Background: Understanding how early-onset Alzheimer's disease (EOAD) differs from typical late-onset AD (LOAD) is an important goal of AD research that may help increase the sensitivity of unique biomarkers for each phenotype. Building upon prior work based on small samples, here we leveraged two large, well-characterized natural history study cohorts of AD patients (LEADS and ADNI3) to test the hypothesis that EOAD patients would show more prominent lateral and medial parietal and lateral temporal cortical atrophy sparing the medial temporal lobe (MTL), whereas LOAD patients would show prominent MTL atrophy.

Method: We investigated differences in the spatial topography of cortical atrophy between EOAD and LOAD patients by analyzing structural MRI data collected from 211 patients with sporadic EOAD and 88 cognitively unimpaired (CU) participants from the LEADS cohort as well as 144 patients with LOAD and 365 CU participants from the ADNI3 cohort.

Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy.

Background: Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication.

Inflammatory Indices and Their Associations With Postoperative Delirium.

Background: Although the pathogenesis of delirium is poorly understood, increasing evidence supports a role for inflammation. Previously, individual inflammatory biomarkers have been associated with delirium. Aggregating biomarkers into an index may provide more information than individual biomarkers in predicting certain health outcomes (eg, mortality); however, inflammatory indices have not yet been examined in delirium.

Prediction of Postoperative Delirium in Older Adults from Preoperative Cognition and Occipital Alpha Power from Resting-State Electroencephalogram.

Background: Postoperative delirium is the most common complication following surgery among older adults, and has been consistently associated with increased mortality and morbidity, cognitive decline, and loss of independence, as well as markedly increased health-care costs. Electroencephalography (EEG) spectral slowing has frequently been observed during episodes of delirium, whereas intraoperative frontal alpha power is associated with postoperative delirium. We sought to identify preoperative predictors that could identify individuals at high risk for postoperative delirium, which could guide clinical decision-making and enable targeted interventions to potentially decrease delirium incidence and postoperative delirium-related complications.

Artificial intelligence classifies primary progressive aphasia from connected speech.

Neurodegenerative dementia syndromes, such as primary progressive aphasias (PPA), have traditionally been diagnosed based, in part, on verbal and non-verbal cognitive profiles. Debate continues about whether PPA is best divided into three variants and regarding the most distinctive linguistic features for classifying PPA variants. In this cross-sectional study, we initially harnessed the capabilities of artificial intelligence and natural language processing to perform unsupervised classification of short, connected speech samples from 78 pateints with PPA.

Differential Vulnerability of Hippocampal Subfields to Amyloid and Tau Deposition in the Lewy Body Diseases.

Background And Objectives: Alzheimer disease (AD) copathologies of β-amyloid and tau are common in the Lewy body diseases (LBD), dementia with Lewy bodies (DLB) and Parkinson disease (PD), and target distinct hippocampal subfields compared with Lewy pathology, including subiculum and CA1. We investigated the hypothesis that AD copathologies impact the pattern of hippocampal subregion volume loss and cognitive function in LBD.

Methods: This was a cross-sectional and longitudinal, single-center, observational cohort study.

Relationship between cortical brain atrophy, delirium, and long-term cognitive decline in older surgical patients.

In older patients, delirium after surgery is associated with long-term cognitive decline (LTCD). The neural substrates of this association are unclear. Neurodegenerative changes associated with dementia are possible contributors.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease.

Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A/T/N patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years).