The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging. To promote more extensive analyses, imaging data was designed to be compatible with other publicly available datasets. A cloud-based system enables access to interested researchers with blinded data available contingent upon completion of a data usage agreement and administrative approval. Data collection is ongoing and currently in its fifth year.

Furthering our understanding of the relationship between amyloidosis (Aβ), neurodegeneration (ND), and cognition is imperative for early identification and early intervention of Alzheimer's disease (AD). However, the subtle cognitive decline differentially associated with each biomarker-defined stage of preclinical AD has yet to be fully characterized. Recent work indicates that different components of memory performance (free and cued recall) may be differentially specific to memory decline in prodromal AD. We sought to examine the relationship between free and cued recall paradigms, in addition to global composites of memory, executive functioning, and processing speed in relation to stages of preclinical AD.

Anosognosia, or loss of insight of memory deficits, is a common and striking symptom in Alzheimer's disease (AD). Previous findings in AD dementia patients suggest that anosognosia is due to both functional metabolic changes within cortical midline structures involved in self-referential processes, as well as functional disconnection between these regions. The present study aims to extend these findings by investigating the neural correlates of anosognosia in the prodromal stage of AD. Here, we used regional brain metabolism (resting state 18-F fluorodeoxyglucose positron emission tomography (FDG-PET)) to unravel the metabolic correlates of anosognosia in subjects with amnestic mild cognitive impairment (aMCI) and subsequently resting state functional magnetic resonance imaging (rs-fMRI) to investigate the intrinsic connectivity disruption between brain regions. Thirty-one subjects (mean age: 74.1; Clinical Dementia Rating (CDR) global score: 0.5) with aMCI, and 251 cognitively normal (CN) older adults (mean age: 73.3; CDR: 0) were included as a reference group for behavioral and FDG data. An anosognosia index was obtained by calculating a discrepancy score between subjective and objective memory scores. All subjects underwent FDG-PET for glucose metabolism measurement, and aMCI subjects underwent additional rs-fMRI for intrinsic connectivity measurement. Voxel-wise correlations between anosognosia and neuroimaging data were conducted in the aMCI subjects. Subjects with aMCI had significantly decreased memory awareness as compared to the CN older adults. Greater anosognosia in aMCI subjects was associated with reduced glucose metabolism in the posterior cingulate (PCC) cortices and hippocampus. Intrinsic connectivity analyses revealed a significant association between anosognosia and attenuated functional connectivity between the PCC seed region and orbitofrontal cortex (OFC) as well as bilateral inferior parietal lobes (IPL). These findings provide further evidence that implicates cortical midline structures and hippocampus in the awareness of memory deficits. Investigating neuroimaging changes that co-vary with memory awareness may improve our ability to identify the cause of anosognosia and ultimately increase our chances for its treatment.

The default-mode network (DMN) is a distributed functional-anatomic network implicated in supporting memory. Current resting-state functional connectivity studies in humans remain divided on the exact involvement of medial temporal lobe (MTL) in this network at rest. Notably, it is unclear to what extent the MTL regions involved in successful memory encoding are connected to the cortical nodes of the DMN during resting state. Our findings using functional connectivity MRI analyses of resting-state data indicate that the parahippocampal gyrus (PHG) is the primary hub of the DMN in the MTL during resting state. Also, connectivity of the PHG is distinct from connectivity of hippocampal regions identified by an associative memory-encoding task. We confirmed that several hippocampal encoding regions lack significant functional connectivity with cortical DMN nodes during resting state. Additionally, a mediation analysis showed that resting-state connectivity between the hippocampus and posterior cingulate cortex--a major hub of the DMN--is indirect and mediated by the PHG. Our findings support the hypothesis that the MTL memory system represents a functional subnetwork that relates to the cortical nodes of the DMN through parahippocampal functional connections.

Proteinopathies are key elements in the pathogenesis of age-related neurodegenerative diseases, particularly Alzheimer's disease (AD), with the nature and location of the proteinopathy characterizing much of the disease phenotype. Susceptibility of brain regions to pathology may partly be determined by intrinsic network structure and connectivity. It remains unknown, however, how these networks inform the disease cascade in the context of AD biomarkers, such as beta-amyloid (Aβ), in clinically-normal older adults.The default-mode network (DMN), a prominent intrinsic network, is heavily implicated in AD due to its spatial overlap with AD atrophy patterns and tau deposition. We investigated the influence of baseline Aβ positron emission tomography (PET) signal and intrinsic DMN connectivity on DMN-specific cortical thinning in 120 clinically-normal older adults from the Harvard Aging Brain Study (73 ± 6 years, 58% Female, CDR = 0). Participants underwent11C Pittsburgh Compound-B (PiB) PET, 18F flortaucipir (FTP) PET, and resting-state MRI scans at baselineand longitudinal MRI (3.6 ± 0.96 scans; 5.04 ± 0.8 years). Linear mixed models tested relationships between baseline PiB and DMN connectivity on cortical thinning in a composite of DMN regions. Lower DMN connectivity was associated with faster cortical thinning, but only in those with elevated baseline PiB-PET signal. This relationship was network specific, in that the frontoparietal control network did not account for the observed association. Additionally, the relationship was independent of inferior temporal lobe FTP-PET signal. Our findings provide evidence that compromised DMN connectivity, in the context of preclinical AD, foreshadows neurodegeneration in DMN regions.

In the present study, we tested the hypothesis that higher amyloid-beta (Aβ) burden at baseline is associated with greater longitudinal decline in body mass index (BMI) in clinically normal adults. Participants from the Harvard Aging Brain Study (n = 312) and the Alzheimer's Disease Neuroimaging Initiative (n = 336) underwent Aβ positron emission tomography at baseline. BMI was assessed longitudinally over a median of >4 years. Linear mixed models showed that higher baseline Aβ burden was significantly associated with greater decline in BMI in both the Harvard Aging Brain Study (t = -1.93; p = 0.05) and Alzheimer's Disease Neuroimaging Initiative cohorts (t = -2.54; p = 0.01), after adjusting for covariates, including cognitive performance and depressive symptoms. In addition, the association of Aβ burden with longitudinal decline in BMI persisted in both cohorts after excluding participants with diabetes/endocrine disturbances and participants classified as underweight or obese (BMI <18.5 or >30). These findings suggest that decline in BMI in clinically normal adults may be an early manifestation related to cerebral amyloidosis that precedes objective cognitive impairment. Therefore, unintentional BMI decline in otherwise healthy individuals might alert clinicians to increased risk of Alzheimer's disease.

We identified a PSEN1 (presenilin 1) mutation carrier from the world's largest autosomal dominant Alzheimer's disease kindred, who did not develop mild cognitive impairment until her seventies, three decades after the expected age of clinical onset. The individual had two copies of the APOE3 Christchurch (R136S) mutation, unusually high brain amyloid levels and limited tau and neurodegenerative measurements. Our findings have implications for the role of APOE in the pathogenesis, treatment and prevention of Alzheimer's disease.

The ability to accurately judge memory efficiency (meta-memory monitoring) for newly learned (episodic) information, is decreased in older adults and even worse in Alzheimer's disease (AD), whereas no differences have been found for semantic meta-memory. The pathological substrates of this phenomenon are poorly understood. Here, we examine the association between meta-memory monitoring for episodic and semantic information to the two major proteinopathies in AD: amyloid (Aβ) and tau pathology in a group of cognitively unimpaired older adults. All participants underwent multi-tracer PET and meta-memory monitoring was assessed using a feeling-of-knowing (FOK) task for non-famous (episodic) and famous (semantic) face-name pairs. Whole brain voxel-wise correlations between meta-memory and PET data were conducted (controlling for memory), as well as confirmatory region-of-interest analyses. Participants had reduced episodic FOK compared to semantic FOK. Decreased episodic FOK was related to tauopathy in the medial temporal lobe regions, including the entorhinal cortex and temporal pole, whereas decreased semantic FOK was related to increased tau in regions associated with the semantic knowledge network. No association was found with Aβ-pathology. Alterations in the ability to accurately judge memory efficiency (in the absence of memory decline) may be a sensitive clinical indicator of AD pathophysiology in the pre-symptomatic phase.

Cerebral amyloid angiopathy (CAA) is a major cause of intracerebral hemorrhage and neurological decline in the elderly. CAA results in focal brain lesions, but the influence on global brain functioning needs further investigation. Here we study functional brain connectivity in patients with Dutch type hereditary CAA using resting state functional MRI. Twenty-four DNA-proven Dutch CAA mutation carriers (11 presymptomatic, 13 symptomatic) and 29 age-matched control subjects were included. Using a set of standardized networks covering the entire cortex, we assessed both within- and between-network functional connectivity. We investigated group differences using general linear models corrected for age, sex and gray matter volume. First, all mutation carriers were contrasted against control subjects and subsequently presymptomatic- and symptomatic mutation carriers against control subjects separately, to assess in which stage of the disease differences could be found. All mutation carriers grouped together showed decreased connectivity in the medial and lateral visual networks, default mode network, executive control and bilateral frontoparietal networks. Symptomatic carriers showed diminished connectivity in all but one network, and between the left and right frontoparietal networks. Presymptomatic carriers also showed diminished connectivity, but only in the frontoparietal left network. In conclusion, global brain functioning is diminished in patients with CAA, predominantly in symptomatic CAA and can therefore be considered to be a late consequence of the disease.

We determine whether diminished Learning Over Repeated Exposures (LORE) identifies subtle memory decrements in cognitively unimpaired (CU) older adults with Alzheimer's disease (AD) biomarker burden.

The integrated Alzheimer's Disease Rating Scale (iADRS) is a validated cognitive/functional composite that effectively captures cognitive and functional decline over a broad spectrum of disease. The clinical meaningfulness of change on iADRS can be supported by establishing an association with changes on important health outcome measures.

To reduce the rising incidence of clinical impairment due to Alzheimer disease, it is essential to define older adults at highest risk. Widowhood may be an unrecognized factor contributing to accelerated clinical progression along the Alzheimer disease pathway among cognitively unimpaired older adults.

Resting-state functional connectivity MRI (rs-fcMRI) is a non-invasive imaging technique that has come into increasing use to understand disrupted neural network function in neuropsychiatric disease. However, despite extensive study over the past 15 years, the development of rs-fcMRI as a biomarker has been impeded by a lack of reliable longitudinal rs-fcMRI measures. Here we focus on longitudinal change along the Alzheimer's disease (AD) trajectory and demonstrate the utility of Template Based Rotation (TBR) in detecting differential longitudinal rs-fcMRI change between higher and lower amyloid burden individuals with mildly impaired cognition. Specifically, we examine a small (N = 24), but densely sampled (~5 observations over ~3 years), cohort of symptomatic individuals with serial rs-fcMRI imaging and PiB-PET imaging for β-amyloid pathology. We observed longitudinal decline of the Default Mode and Salience network axis (DMN/SAL) among impaired individuals with high amyloid burden. No other networks showed differential change in high vs. low amyloid individuals over time. The standardized effect size of AD related DMN/SAL change is comparable to the standardized effect size of amyloid-related change on the mini-mental state exam (MMSE) and hippocampal volume (HV). Last, we show that the AD-related change in DMN/SAL connectivity is almost completely independent of change on MMSE or HV, suggesting that rs-fcMRI is sensitive to an aspect of AD progression that is not captured by these other measures. Together these analyses demonstrate that longitudinal rs-fcMRI using TBR can capture disease-relevant network disruption in a clinical population.

Positron emission tomography (PET) imaging now allows in vivo visualization of both neuropathologic hallmarks of Alzheimer disease (AD): amyloid-β (Aβ) plaques and tau neurofibrillary tangles. Observing their progressive accumulation in the brains of clinically normal older adults is critically important to understand the pathophysiologic cascade leading to AD and to inform the choice of outcome measures in prevention trials.

Alzheimer's disease (AD) heritability is enriched in glial genes, but how and when cell-type-specific genetic risk contributes to AD remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets. In an autopsy dataset spanning all stages of AD (n=1,457), astrocytic (Ast) ADPRS was associated with both diffuse and neuritic Aβ plaques, while microglial (Mic) ADPRS was associated with neuritic Aβ plaques, microglial activation, tau, and cognitive decline. Causal modeling analyses further clarified these relationships. In an independent neuroimaging dataset of cognitively unimpaired elderly (n=2,921), Ast-ADPRS were associated with Aβ, and Mic-ADPRS was associated with Aβ and tau, showing a consistent pattern with the autopsy dataset. Oligodendrocytic and excitatory neuronal ADPRSs were associated with tau, but only in the autopsy dataset including symptomatic AD cases. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

Alzheimer's disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes-aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)-are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau.

"Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology.

Advanced aging negatively impacts memory performance. Brain aging has been associated with shrinkage in medial temporal lobe structures essential for memory--including hippocampus and entorhinal cortex--and with deficits in default-mode network connectivity. Yet, whether and how these imaging markers are relevant to age-related memory deficits remains a topic of debate. Using a sample of 182 older (age 74.6 ± 6.2 years) and 66 young (age 22.2 ± 3.6 years) participants, this study examined relationships among memory performance, hippocampus volume, entorhinal cortex thickness, and default-mode network connectivity across aging. All imaging markers and memory were significantly different between young and older groups. Each imaging marker significantly mediated the relationship between age and memory performance and collectively accounted for most of the variance in age-related memory performance. Within older participants, default-mode connectivity and hippocampus volume were independently associated with memory. Structural equation modeling of cross-sectional data within older participants suggest that entorhinal thinning may occur before reduced default-mode connectivity and hippocampal volume loss, which in turn lead to deficits in memory performance.

There is a growing need in clinical research domains for direct comparability between amyloid-beta (Aβ) Positron Emission Tomography (PET) measures obtained via different radiotracers and processing methodologies. Previous efforts to provide a common measurement scale fail to account for non-linearities between measurement scales that can arise from these differences. We introduce a new application of distribution mapping, based on well established statistical orthodoxy, that we call Nonlinear Distribution Mapping (NoDiM). NoDiM uses cumulative distribution functions to derive mappings between Aβ-PET measurements from different tracers and processing streams that align data based on their location in their respective distributions.

Alzheimer's disease (AD) is one of the costliest diseases in the United States.