We aimed to examine the contribution of subjective cognitive decline (SCD) to reduce the number of β-amyloid (Aβ) positron emission tomography scans required for recruiting Aβ+ clinically normal individuals in clinical trials.

Computerized neuropsychological tests for early detection of Alzheimer's disease (AD) have attracted increasing interest. Memory for faces and proper names is a complex task because its association is arbitrary. It implicates associative occipito-temporal cerebral regions, which are disrupted in AD. The short form of the Face-Name Associative Memory Exam (FNAME-12), developed to detect preclinical and prodromal AD, asks individuals to learn the names and occupations associated with 12 faces. The current work advances this field by using voice recognition and touchscreen response format. The purpose of this study is to create the first self-administered episodic memory test, FACEmemory®, by adapting the FNAME-12 for tablet use with voice recognition, touchscreen answers, and automatic scoring. The test was minimally supervised by a psychologist to avoid technological problems during execution and scored manually to assess the reliability of the automatic scoring. The aims of the present study were (1) to determine whether FACEmemory® is a sensitive tool for the detection of cognitive impairment, (2) to examine whether performances on FACEmemory® are correlated with those on the S-FNAME (paper-and-pencil version with 16 images), and (3) to determine whether performances on FACEmemory® are related to AD biomarkers in the cerebrospinal fluid (CSF) (Aβ42, p-tau, and Aβ42/p-tau ratio).

To identify a parsimonious set of markers that optimally predicts subsequent clinical progression from normal to mild cognitive impairment (MCI).

Neuroimaging studies of autosomal dominant Alzheimer's disease (ADAD) enable characterization of the trajectories of cerebral amyloid-β (Aβ) and tau accumulation in the decades prior to clinical symptom onset. Longitudinal rates of regional tau accumulation measured with positron emission tomography (PET) and their relationship with other biomarker and cognitive changes remain to be fully characterized in ADAD.

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.

In the COVID-19 pandemic, older adults from vulnerable ethnoracial groups are at high risk of infection, hospitalization, and death. We aimed to explore the pandemic's impact on the well-being and cognition of older adults living in the United States (US), Argentina, Chile, Mexico, and Peru.

FACEmemory® is the first computerized, self-administered verbal episodic memory test with voice recognition. It can be conducted under minimal supervision and contains an automatic scoring system to avoid administrator errors. Moreover, it is suitable for discriminating between cognitively healthy and amnestic mild cognitive impairment (MCI) individuals, and it is associated with Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers. This study aimed to determine whether FACEmemory scoring is related to performance on classical memory tests and to AD biomarkers of brain magnetic resonance imaging (MRI) and CSF in patients with early-onset MCI (EOMCI).

Non-invasive diffusion-weighted imaging (DWI) to assess brain microstructural changes via cortical mean diffusivity (cMD) has been shown to be cross-sectionally associated with tau in cognitively normal older adults, suggesting that it might be an early marker of neuronal injury. Here, we investigated how regional cortical microstructural changes measured by cMD are related to the longitudinal accumulation of regional tau as well as to episodic memory decline in cognitively normal individuals harboring amyloid pathology.

The biological basis of cognitive impairment in parkinsonian diseases is believed to be multifactorial. We investigated the contribution of dopamine deficiency to cognition in Parkinson disease (PD) and dementia with Lewy bodies (DLB) with dopamine transporter (DAT) imaging.

Functional magnetic resonance imaging (fMRI) holds significant potential to aid in the development of early interventions to improve memory function, and to assess longitudinal change in memory systems in aging and early Alzheimer's disease (AD). However, the test-retest reliability of hippocampal activation and of "beneficial" deactivation in the precuneus has yet to be fully established during memory encoding tasks in older subjects. Using a mixed block and event-related face-name associative encoding paradigm, we assessed the reliability of hippocampal activation and default network deactivation over a 4- to 6-week interscan interval in 27 older individuals who were cognitively normal [Clinical Dementia Rating (CDR) Scale = 0; n = 18] or mildly impaired (CDR = 0.5; n = 9). Reliability was assessed in whole brain maps and regions of interest using both a full-task paradigm of six functional runs as well as an abbreviated paradigm of the first two functional runs, which would be advantageous for use in clinical trials. We found reliable hippocampal signal response across both block- and event-related designs in the right hippocampus. Comparable reliability in hippocampal activation was found in the full and the abbreviated paradigm. Similar reliability in hippocampal activation was observed across both CDR groups overall, but the CDR 0.5 group was more variable in left hippocampal activity. Task-related deactivation in the precuneus demonstrated much greater variability than hippocampal activation in all analyses. Overall, these results are encouraging for the utility of fMRI in "Proof of Concept" clinical trials investigating the efficacy of potentially therapeutic agents for treatment of age-related memory changes, cognitive impairment, and early AD.

Alzheimer's disease (AD) has been associated with functional alterations in a distributed network of brain regions linked to memory function, with a recent focus on the cortical regions collectively known as the default network. Posterior components of the default network, including the precuneus and posterior cingulate, are particularly vulnerable to early deposition of amyloid beta-protein, one of the hallmark pathologies of AD. In this study, we use in vivo amyloid imaging to demonstrate that high levels of amyloid deposition are associated with aberrant default network functional magnetic resonance imaging (fMRI) activity in asymptomatic and minimally impaired older individuals, similar to the pattern of dysfunction reported in AD patients. These findings suggest that amyloid pathology is linked to neural dysfunction in brain regions supporting memory function and provide support for the hypothesis that cognitively intact older individuals with evidence of amyloid pathology may be in early stages of AD.

Recent investigations that suggest selective attention (SA) is dependent on top-down control mechanisms lead to the expectation that individuals with high executive capacity (EC) would exhibit more robust neural indices of SA. This prediction was tested by using event-related potentials (ERPs) to examine differences in markers of information processing across 25 subjects divided into two groups based on high vs. average EC, as defined by neuropsychological test scores. Subjects performed an experimental task requiring SA to a specified color. In contrast to expectation, individuals with high and average EC did not differ in the size of ERP indices of SA: the anterior Selection Positivity (SP) and posterior Selection Negativity (SN). However, there were substantial differences between groups in markers of subsequent processing, including the anterior N2 (a measure of attentional control) and the P3a (an index of the orienting of attention). EC predicted speed of processing at both early and late attentional stages. Individuals with lower EC exhibited prolonged SN, P3a, and P3b latencies. However, the delays in carrying out SA operations did not account for subsequent delays in decision making, or explain excessive orienting and reduced attentional control mechanisms in response to stimuli that should have been ignored. SN latency, P3 latency, and the size of the anterior N2 made independent contributions to the variance of EC. In summary, our findings suggest that current views regarding the relationship between top-down control mechanisms and SA may need refinement.

Animal and human imaging research reported that the presence of cortical Alzheimer's Disease's (AD) neuropathology, beta-amyloid and neurofibrillary tau, is associated with altered neuronal activity and circuitry failure, together facilitating clinical progression. The locus coeruleus (LC), one of the initial subcortical regions harboring pretangle hyperphosphorylated tau, has widespread connections to the cortex modulating cognition. Here we investigate whether LC's in-vivo neuronal activity and functional connectivity (FC) are associated with cognitive decline in conjunction with beta-amyloid. We combined functional MRI of a novel versus repeated face-name paradigm, beta-amyloid-PET and longitudinal cognitive data of 128 cognitively unimpaired older individuals. We show that LC activity and LC-FC with amygdala and hippocampus was higher during novelty. We also demonstrated that lower novelty-related LC activity and LC-FC with hippocampus and parahippocampus were associated with steeper beta-amyloid-related cognitive decline. Our results demonstrate the potential of LC's functional properties as a gauge to identify individuals at-risk for AD-related cognitive decline.

Animal models of Alzheimer's disease have suggested that tau pathology propagation, facilitated by amyloid pathology, may occur along connected pathways. To investigate these ideas in humans, we combined amyloid scans with longitudinal data on white matter connectivity, hippocampal volume, tau positron emission tomography and memory performance in 256 cognitively healthy older individuals. Lower baseline hippocampal volume was associated with increased mean diffusivity of the connecting hippocampal cingulum bundle (HCB). HCB diffusivity predicted tau accumulation in the downstream-connected posterior cingulate cortex in amyloid-positive but not in amyloid-negative individuals. Furthermore, HCB diffusivity predicted memory decline in amyloid-positive individuals with high posterior cingulate cortex tau binding. Our results provide in vivo evidence that higher amyloid pathology strengthens the association between HCB diffusivity and tau accumulation in the downstream posterior cingulate cortex and facilitates memory decline. This confirms amyloid's crucial role in potentiating neural vulnerability and memory decline marking the onset of preclinical Alzheimer's disease.

Amyloid positron emission tomography (PET) data are commonly expressed as binary measures of cortical deposition. However, not all individuals with high cortical amyloid will experience rapid cognitive decline. Motivated by postmortem data, we evaluated a three-stage PET classification: low cortical; high cortical, low striatal; and high cortical, high striatal amyloid; hypothesizing this model could better reflect Alzheimer's dementia progression than a model based only on cortical measures.

Depressive symptoms are prevalent among older adults and may be early manifestations of Alzheimer disease (AD) before onset of mild cognitive impairment. However, it remains unclear whether worsening depressive symptoms in the presence of AD pathology are associated with cognitive decline in older adults.

Costs associated with early stages of Alzheimer's disease (AD; mild cognitive impairment [MCI] and mild dementia [MILD]) are understudied.

Although pathogenic variants in PSEN1 leading to autosomal-dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non-carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aβ compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre-symptomatic and symptomatic phases of disease as compared to CY, using both cross-sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ-secretase and the generation of toxic β-amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials.

Many of the Alzheimer's disease (AD) risk genes are specifically expressed in microglia and astrocytes, but how and when the genetic risk localizing to these cell types contributes to AD pathophysiology remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets and uncover the impact of cell-type-specific genetic risk on AD endophenotypes. In an autopsy dataset spanning all stages of AD (n = 1457), the astrocytic ADPRS affected diffuse and neuritic plaques (amyloid-β), while microglial ADPRS affected neuritic plaques, microglial activation, neurofibrillary tangles (tau), and cognitive decline. In an independent neuroimaging dataset of cognitively unimpaired elderly (n = 2921), astrocytic ADPRS was associated with amyloid-β, and microglial ADPRS was associated with amyloid-β and tau, connecting cell-type-specific genetic risk with AD pathology even before symptom onset. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

The Face Name Associative Memory Exam (FNAME) was introduced into the NIH Toolbox as part of the ARMADA study and establishes normative data for diverse participants, ages 64 to 85+, and proposes cutoff scores between biomarker positive versus negative (+/-) groups. The FNAME was administered to 257 participants across the clinical spectrum with 122 having amyloid biomarkers. Linear regression explored the association between demographics and FNAME and between amyloid (+/-) groups. Receiver operating characteristic curves (ROC) identified performance thresholds that best discriminated between biomarker (+/-) individuals. Lower FNAME scores occurred in males, older ages, Black/African Americans, Hispanics, and biomarker-positive participants. ROC analyses demonstrated acceptable accuracy (0.73 to 0.77) but only when combined with clinical status. The diagnostic discrimination of amyloid positivity was acceptable but not excellent, suggesting the FNAME may be a better screening indicator of clinical status rather than amyloid deposition in cognitively normal individuals. Normative data are provided.