National Institute On Aging And Alzheimer's Association Research Articles

Symposium 08: Neuropsychological Considerations for Alzheimer's Disease Clinical Trials

Summary Abstract:The 2011 National Institute on Aging and Alzheimer's Association (NIA-AA) criteria for the diagnosis of Alzheimer's disease (AD) focused on clinical signs and symptoms to make a diagnosis of probable or possible AD. Under these criteria, emphasis was placed on gathering objective evidence of cognitive decline, which gave neuropsychologists a central role as diagnosticians in AD clinical trials. The release of the 2018 NIA-AA research framework put greater emphasis on the use of biomarkers, especially measures of amyloid, tau, and neurodegeneration, to define AD. Once AD is defined based on these biomarkers, it is staged via clinical signs and symptoms. Thus, the role of neuropsychologists has shifted from being central to diagnosis to a possibly more ancillary role of staging the disease once it is determined to be present. The move away from clinical signs towards biomarkers only became more prominent with the recent, controversial Food and Drug Administration approval of Aducanumab as an AD treatment based on evidence of change in biomarkers without clear evidence of clinical benefit. In this landscape, the fit of neuropsychologists in AD clinical trial research has become less clear.This symposium will address the role of neuropsychologists in modern AD clinical trial research. The presenters will highlight varied ways in which neuropsychologists can enrich and improve AD clinical trials. First, Dr. Dustin Hammers from Indiana University will discuss how neuropsychological methods can help us to understand which participants do, and perhaps more importantly, do not get enrolled in clinical trials. Second, Dr. Mirella Diaz-Santos from the University of California Los Angeles will summarize her work to enroll Hispanic individuals in the Human Connectome Project, improving inclusivity. Third, Dr. Tamar Gollan from the University of California San Diego will summarize her work on novel behavioral markers of AD risk discovered from the study of Spanish-English bilingual patients. Fourth, Dr. Andrew Kiselica from the University of Missouri will highlight psychometric considerations in interpreting clinically meaningfully change in AD clinical trials using data from the National Alzheimer's Coordinating Center. Fifth, Dr. Samantha John from the University of Nevada at Las Vegas will discuss the influence of race/ethnicity on how clinically meaningful change is defined using data from a diverse cohort.Dr. Kevin Duff will serve as discussant for this series of studies. He will highlight the important roles that neuropsychologists can play in improving AD clinical trial screening processes, expanding inclusion of diverse patients into trials, and enhancing interpretation of the clinical meaningfulness of trial results. He will also reflect on the future of neuropsychology's role in the AD clinical trial landscape and encourage audience questions and responses to the research presented.

How Helpful are Blood and Cerebrospinal Fluid Biomarkers for the Early Diagnosis of Alzheimer's Disease?

Early diagnosis of Alzheimer's disease (AD) relies on imaging and fluid biomarkers to objectively detect and quantitatively evaluate brain AD pathologies. Amyloid- and tau-PET scans recently enabled clinicians to make definitive diagnoses based on abnormal amyloid/tau deposition in the human brain. Since PET scans and blood-based biomarkers are mutually complementary, the identification of suitable blood-based biomarkers is essential for screening brain AD pathologies. According to the National Institute on Aging and Alzheimer's Association (NIA-AA) Research Framework published in 2018, AD is defined by its underlying pathologic processes, which can be diagnosed in vivo using suitable biomarkers. These biomarkers are categorized under the ATN classification system, including β amyloid deposition (A), pathologic tau (T), and neurodegeneration (N). Originally, all the ATN fluid biomarkers were assessed using cerebrospinal fluid, but currently these biomarkers can be quantified using blood samples. Among those blood-based ATN biomarkers, the plasma levels of Aβ42/40 ratio, p-tau, and neurofilament light chain (NfL) representing "A," "T," and "N" biomarkers, respectively, are useful in the early diagnosis of AD. However, further studies and additional data are required before utilizing these blood-based biomarkers as stand-alone diagnostic markers for AD.

Survey of Neuroanatomic Sampling and Staining Procedures in Alzheimer Disease Research Center Brain Banks.

The collection of post-mortem brain tissue has been a core function of the Alzheimer Disease Research Center's (ADRCs) network located within the United States since its inception. Individual brain banks and centers follow detailed protocols to record, store, and manage complex datasets that include clinical data, demographics, and when post-mortem tissue is available, a detailed neuropathological assessment. Since each institution often has specific research foci, there can be variability in tissue collection and processing workflows. While published guidelines exist for select diseases, such as those put forth by the National Institute on Aging and Alzheimer Association (NIA-AA), it is of importance to denote the current practices across institutions. To this end a survey was developed and sent to United States based brain bank leaders, collecting data on brain region sampling, including anatomic landmarks used, staining (including antibodies used), as well as whole-slide-image scanning hardware. We distributed this survey to 40 brain banks and obtained a response rate of 95% (38 / 40). Most brain banks followed guidelines defined by the NIA-AA, having H&E staining in all recommended regions and targeted region-based amyloid beta, tau, and alpha-synuclein immunohistochemical staining. However, sampling consistency varied related to key anatomic landmarks/locations in select regions, such as the striatum, periventricular white matter, and parietal cortex. This study highlights the diversity and similarities amongst brain banks and discusses considerations when amalgamating data/samples across multiple centers. This survey aids in establishing benchmarks to enhance dialogues on divergent workflows in a feasible way.

Alzheimer's Disease: Epidemiology and Clinical Progression.

Alzheimer’s disease (AD) is prevalent throughout the world and is the leading cause of dementia in older individuals (aged ≥ 65 years). To gain a deeper understanding of the recent literature on the epidemiology of AD and its progression, we conducted a review of the PubMed-indexed literature (2014–2021) in North America, Europe, and Asia. The worldwide toll of AD is evidenced by rising prevalence, incidence, and mortality due to AD—estimates which are low because of underdiagnosis of AD. Mild cognitive impairment (MCI) due to AD can ultimately progress to AD dementia; estimates of AD dementia etiology among patients with MCI range from 40% to 75% depending on the populations studied and whether the MCI diagnosis was made clinically or in combination with biomarkers. The risk of AD dementia increases with progression from normal cognition with no amyloid-beta (Aβ) accumulation to early neurodegeneration and subsequently to MCI. For patients with Aβ accumulation and neurodegeneration, lifetime risk of AD dementia has been estimated to be 41.9% among women and 33.6% among men. Data on progression from preclinical AD to MCI are sparse, but an analysis of progression across the three preclinical National Institute on Aging and Alzheimer’s Association (NIA-AA) stages suggests that NIA-AA stage 3 (subtle cognitive decline with AD biomarker positivity) could be useful in combination with other tools for treatment decision-making. Factors shown to increase risk include lower Mini-Mental State Examination (MMSE) score, higher Alzheimer’s Disease Assessment Scale (ADAS-cog) score, positive APOE4 status, white matter hyperintensities volume, entorhinal cortex atrophy, cerebrospinal fluid (CSF) total tau, CSF neurogranin levels, dependency in instrumental activities of daily living (IADL), and being female. Results suggest that use of biomarkers alongside neurocognitive tests will become an important part of clinical practice as new disease-modifying therapies are introduced.

Application guidelines and research progress of biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is an age-related neurodegenerative disorder. It is expected that the incidence of AD will increase exponentially in the coming decades. The clinical and research application of AD biomarkers has gone through a long process. At present, the clinical diagnostic criteria for AD mainly include the IWG-2 criteria developed by International Working Group (IWG), the NIA-AA criteria formulated by the National Institute on Aging and Alzheimer's Association (NIA-AA) and the "Guidelines for the Diagnosis and Treatment of Alzheimer's Disease in China (2020 version)" released by the Professional Committee on Alzheimer's Disease and Related Diseases of the Chinese Geriatric Health Care Association (Alzheimer's Disease Chinese, ADC). Cerebrospinal fluid biomarkers such as Aβ42, T-tau and P-tau are recognized as central biomarkers for AD, besides, the development of new molecules in other pathophysiological pathway that can be used as biomarkers for the diagnosis of AD have made great progress in the last decade. This article elaborates studies of the application guidelines of AD biomarkers and highlights the research progress of biomarkers in AD pathophysiological pathway.

Evaluation of the ATN model in a longitudinal memory clinic sample with different underlying disorders.

IntroductionTo evaluate the usefulness of the 2018 NIA‐AA (National Institute on Aging and Alzheimer's Association) research framework in a longitudinal memory clinic study with different clinical outcomes and underlying disorders.MethodsWe included 420 patients with mild cognitive impairment or subjective cognitive impairment. During the follow up, 27% of the patients converted to dementia, with the majority converting to Alzheimer's disease (AD) or mixed dementia. Based on the baseline values of the cerebrospinal fluid biomarkers, the patients were classified into one of the eight possible ATN groups (amyloid beta [Aβ] aggregation [A], tau aggregation reflecting neurofibrillary tangles [T], and neurodegeneration [N]).ResultsThe majority of the patients converting to AD and mixed dementia were in ATN groups positive for A (71%). The A+T+N+ group was highly overrepresented among converters to AD and mixed dementia. Patients converting to dementias other than AD or mixed dementia were evenly distributed across the ATN groupsDiscussionOur findings provide support for the usefulness of the ATN system to detect incipient AD or mixed dementia.

The Validation of Multifactor Model of Plasma Aβ 42 and Total-Tau in Combination With MoCA for Diagnosing Probable Alzheimer Disease.

Alzheimer disease (AD) has an insidious onset and heterogeneous clinical symptoms. The well-accepted biomarkers for clinical diagnosis of AD include β-amyloid (Aβ) deposition and pathologic tau level within cerebral spinal fluid (CSF) and imaging AD pathology such as positive emission tomography (PET) imaging of the amyloid-binding agent Pittsburgh compound B (PET-PiB). However, the high expense and invasive nature of these methods highly limit their wide usage in clinic practice. Therefore, it is imperious to develop less expensive and invasive methods, and plasma biomarkers are the premium targets. In the current study, we utilized a single-blind comparison method; all the probable AD cases met the core clinical National Institute on Aging and Alzheimer’s Association (NIA-AA) criteria and validated by PET-PiB. We used ultrasensitive immunomagnetic reduction (IMR) assays to measure plasma Aβ42 and total-tau (t-tau) levels, in combination with different variables including Aβ42 × t-tau value, Montreal Cognitive Assessment (MoCA), and Mini Mental State Examination (MMSE). We used logistic regression to analyze the effect of all these variables in the algorism. Our results showed that (1) plasma Aβ42 and t-tau are efficient biomarkers for AD diagnosis using IMR platform, whereas Aβ42 × t-tau value is more efficient for discriminating control and AD; (2) in the control group, Aβ42 level and age demonstrated strong negative correlation; Aβ42 × t-tau value and age demonstrated significant negative correlation; (3) in the AD group, t-tau level and MMSE score demonstrated strong negative correlation; (4) using the model that Aβ42, Aβ42 × t-tau, and MoCA as the variable to generate receiver operating characteristic (ROC) curve, cutoff value = 0.48, sensitivity = 0.973, specificity = 0.982, area under the curve (AUC) = 0.986, offered better categorical efficacy, sensitivity, specificity, and AUC. The multifactor model of plasma Aβ42 and t-tau in combination with MoCA can be a viable model separate health and AD subjects in clinical practice.

What is new within staging of care for people with dementia? The IDEAL schedule and other recent work.

This review provides an overview of recent progress within work centred around the 'International schedule for the integrated assessment and staging of care for dementia' (IDEAL schedule), and places it within the context of recent work around other staging models for dementia. The IDEAL schedule assesses the severity of dementia across seven dimensions. A 'Menu of care options' of recommended priorities for interventions accompanies the schedule. A user manual for the schedule has just been published. Other staging models for dementia include those based on biomarkers, such as in the recently published research framework for Alzheimer's disease by the National Institute on Aging and Alzheimer's Association (NIA-AA), or those based on specific aspects of dementia, principally cognitive impairment. The IDEAL schedule is a global staging model to guide the organization of dementia care. The schedule covers a range of domains that extend beyond cognitive functioning and include care needs; it is applicable to all types and stages of dementia; and can be used by any healthcare professional, both within clinical practice and research. The schedule is not in opposition to, or is even complementary to, other staging models for dementia.

Plasma metabolomics in early Alzheimer's disease patients diagnosed with amyloid biomarker

An untargeted metabolomics study has been carried out using plasma samples from patients with Mild Cognitive Impairment due to Alzheimer's disease patients (MCI-AD, n = 29) and healthy people (n = 29)). They have been classified following the National Institute on Aging and Alzheimer's Association (NIA-AA) recommendations and cerebrospinal fluid biomarkers. The analytical method was based on liquid chromatography coupled to high resolution mass spectrometry. The data process from the corresponding metabolic profiles retained 1158 molecular features in positive and 424 in negative ionization mode. Differences between metabolomic profiles from MCI-AD patients and healthy participants were investigated using a penalized logistic regression analysis (ElasticNet), and being able to select automatically the most informative variables (53 molecular features).From the molecular features selected for the elastic net models, 16 variables were preliminarily identified by The Human Metabolome Database (amino acids, lipids…). However, only 4 of these variables were tentatively identified by MS/MS and all ions fragmentation modes, being choline the only confirmed metabolite. Regarding their metabolic pathways, they could be involved in cholinergic system, energy metabolism, amino acids and lipids pathways. To conclude, this is a reliable approach to early AD mechanisms, and choline has been identified as a promising AD diagnosis metabolite. SignificanceThe untargeted analysis carried out in human plasma samples from early Alzheimer's disease patients and healthy individuals, and the use of sophisticated statistical tools, identified some metabolic pathways and plasma biomarkers. Preliminarily, cholinergic system, energy metabolism, and aminoacids and lipids pathways may be involved in early Alzheimer's disease development.

PREVALENCE OF NEUROPSYCHIATRIC SYMPTOMS ACROSS THE COGNITIVE SPECTRUM AND THEIR IMPACT ON FUTURE COGNITIVE DECLINE: Session 203

In the recently published National Institute on Aging and Alzheimer's Association (NIA-AA)’s Research Framework, the definition of Alzheimer's disease (AD) shifts from a syndromal to a biological entity, defined by underlying pathology as evidenced by the presence of AD biomarkers in vivo or on post-mortem examination (Jack et al., 2018, Alzheimers Dement. 2018 Apr;14(4):535-562). The new NIA-AA framework also describes syndromal staging of cognitive continuum to define research cohorts, independent of biomarker profile. With respect to mild cognitive impairment (MCI), the current framework differs from the 2011 NIA-AA definition in its reference to “neurobehavioral” symptoms, defined as symptoms attributable to mood or behavioral disorders, such as anxiety, depression, and apathy, which “commonly coexist and may be a prominent part of the presentation” (Table 3, Jack et al., 2018). We argue that neurobehavioural or neuropsychiatric symptoms (NPS) across the spectrum of AD disease should not be conceptualized as simply co-existing alongside cognitive impairment or attributable to mood or behavioural disorders. Rather, NPS are core features of neurodegenerative cognitive syndromes that may serve as prognostic indicators of outcome. This symposium will review the prevalence of NPS across the cognitive spectrum; namely in subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD), and highlight their association with AD biomarkers and contribution to future cognitive decline or disease progression in AD. Dr. Linda Mah will review the prevalence of neurobehavioural symptoms and their association with AD biomarkers and future cognitive decline in older adults who are cognitively unimpaired (CU) or who present with SCD, drawing from the extant literature and new data from an ongoing study of SCD. Dr. Krista L. Lanctôt will review the prevalence of NPS in mild neurocognitive disorder (NCD) and impact on progression. In addition, emerging evidence linking specific NPS with biomarkers of major NCD and the efficacy of interventions including pharmacologic, nonpharmacologic and neuromodulatory during this phase will be highlighted, with emphasis on recent findings. Dr. Corinne E. Fischer will review the prevalence and trajectory, clinical features and treatment approach to neuropsychiatric symptoms (NPS) in patients with established Alzheimer's disease. Particular emphasis will be placed on studies demonstrating the link between disease biomarkers and NPS disease burden, highlighting specific NPS such as apathy, aberrant sleep behavior, psychosis and depression.

18F PET with flutemetamol for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

18F-flutemetamol uptake by brain tissue, measured by positron emission tomography (PET), is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and the confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using some amyloid biomarkers tests like 18F-flutemetamol. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of 18F-flutemetamol to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated. To determine the DTA of the 18F-flutemetamol PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD) or any form of dementia at follow-up. The most recent search for this review was performed in May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches. We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of 18F-flutemetamol scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria. We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies. Progression from MCI to ADD was evaluated in 243 participants from two studies. The studies reported data on 19 participants with two years of follow-up and on 224 participants with three years of follow-up. Nine (47.4%) participants converted at two years follow-up and 81 (36.2%) converted at three years of follow-up.There were concerns about participant selection and sampling in both studies. The index test domain in one study was considered unclear and in the second study it was considered at low risk of bias. For the reference standard domain, one study was considered at low risk and the second study was considered to have an unclear risk of bias. Regarding the domains of flow and timing, both studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD at two years of follow-up had a sensitivity of 89% (95% CI 52 to 100) and a specificity of 80% (95% CI 44 to 97) by quantitative assessment by SUVR (n = 19, 1 study).Progression from MCI to ADD at three years of follow-up had a sensitivity of 64% (95% CI 53 to 75) and a specificity of 69% (95% CI 60 to 76) by visual assessment (n = 224, 1 study).There was no information regarding the other two objectives in this systematic review (SR): progression from MCI to other forms of dementia and progression to any form of dementia at follow-up. Due to the varying sensitivity and specificity for predicting the progression from MCI to ADD and the limited data available, we cannot recommend routine use of 18F-flutemetamol in clinical practice. 18F-flutemetamol has high financial costs; therefore, clearly demonstrating its DTA and standardising the process of the 18F-flutemetamol modality is important prior to its wider use.

18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

18F PET with florbetaben for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

18F PET with florbetaben for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).

Paths to Alzheimer's disease prevention: from modifiable risk factors to biomarker enrichment strategies.

Alzheimer's disease (AD) represents an increasing worldwide healthcare epidemic. Secondary preventive disease-modifying treatments under clinical development are considered most effective when initiated as early as possible in the pathophysiological course and progression of the disease. Major targets are to enhance clearance and to reduce cerebral accumulation of amyloid, decrease hyperphosphorylation of tau and the generation of neurofibrillary tangles, reduce inflammation, and finally progressive neurodegeneration. Comprehensive sets of biological markers are needed to characterize the pathophysiological mechanisms, indicate effects of treatment and to facilitate early characterisation and detection of AD during the prodromal or even at asymptomatic stages. No primary or secondary preventive treatments for AD have been approved. Epidemiological research, however, has provided evidence of specifically modifiable risk and protective factors. Among them are vascular, lifestyle and psychological risk factors that may act both independently and by potentiating each other. These factors may be substantially impacted by single or multi-domain strategies to prevent or postpone the onset of AD-related pathophysiology. Researchers have recently started the European Dementia Prevention Initiative (EDPI), an international consortium to improve strategies for preventing dementia. EDPI, in particular, includes the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) which aims at optimizing the early identification of subjects at increased risk of late-life cognitive deterioration, and at the evaluation of multi-domain intervention strategies. The ongoing discussion on new diagnostic criteria provided by the International Working Group (IWG), as well as by the recommendations summoned by the National Institute on Aging and Alzheimer's Association (NIA-AA) initiative, has inspired the creation of novel study designs and the definition of earlier target populations for trials in pre- and asymptomatic at-risk and prodromal stages of AD. As a result, a number of promising international prevention trials are currently ongoing. In this review, we critically discuss the main paths to AD prevention through control of modifiable risk factors and lifestyle changes. We will also review the role of biomarkers to identify subgroups of patients who would most likely benefit from secondary prevention strategies, and to evaluate the benefit of treatment in such patients.

Do NIA-AA criteria distinguish Alzheimer's disease from frontotemporal dementia?

BackgroundClinical criteria are important for improving diagnostic accuracy and ensuring comparability of patient cohorts in research studies. ObjectiveThe aim was to assess the National Institute on Aging and Alzheimer's Association (NIA-AA) criteria for Alzheimer's disease (AD) dementia in AD and frontotemporal lobar degeneration (FTLD). MethodsTwo hundred twelve consecutive patients with pathologically confirmed AD or FTLD who were clinically assessed in a specialist cognitive unit were identified. Fifty-five patients were excluded predominantly because of insufficient clinical information. Anonymized clinical data were rated against the NIA-AA criteria by raters who were blinded to clinical and pathologic diagnosis. ResultsThe NIA-AA AD dementia criteria had a sensitivity of 65.6% for probable and 79.5% for possible AD and a specificity of 95.2% and 94.0% for probable and possible, respectively. ConclusionIn patients with FTLD and predominantly early-onset AD, the NIA-AA AD dementia criteria have high specificity but lower sensitivity. The high specificity is due to the broad exclusion criteria.

Renovating Alzheimer's: "Constructive" Reflections on the New Clinical and Research Diagnostic Guidelines

The development of disease concepts for conditions such as Alzheimer's disease (AD) is an ongoing social process that evolves over time. The biomedical paradigm about AD that has informed our culture's understanding of brain aging for the past several decades is currently undergoing a major and timely renovation in the early 21st century. This evolution is reflected in new guidelines issued by the National Institute on Aging and Alzheimer's Association (NIA/AA) for the diagnosis of AD and related conditions that aim at helping researchers identify and eventually treat AD in its presymptomatic stages. The purpose of this article is to offer the scientific, clinical, and ethics communities a critical analysis of the implications of proposed guidelines and prompt deeper reflection about the lessons learned from these new efforts both in terms of their actual content and the cultural context in which they were issued and will be used. From a social-constructivist perspective, we explore the gradual 100-year evolution of AD and summarize the proposed NIA/AA guidelines within this historical context, enumerating what we see as their main benefits and limitations. We then consider the potential implications of these guidelines in the clinical setting, and explore shifts in our cultural paradigm about brain aging that might be engendered by the logic of the guidelines.