Modelling mobile-based technology adoption among people with dementia.

The work described in this paper builds upon our previous research on adoption modelling and aims to identify the best subset of features that could offer a better understanding of technology adoption. The current work is based on the analysis and fusion of two datasets that provide detailed information on background, psychosocial, and medical history of the subjects. In the process of modelling adoption, feature selection is carried out followed by empirical analysis to identify the best classification models. With a more detailed set of features including psychosocial and medical history information, the developed adoption model, using kNN algorithm, achieved a prediction accuracy of 99.41% when tested on 173 participants. The second-best algorithm built, using NN, achieved 94.08% accuracy. Both these results have improved accuracy in comparison to the best accuracy achieved (92.48%) in our previous work, based on psychosocial and self-reported health data for the same cohort. It has been found that psychosocial data is better than medical data for predicting technology adoption. However, for the best results, we should use a combination of psychosocial and medical data where it is preferable that the latter is provided from reliable medical sources, rather than self-reported.

Assessment of anesthetic gases in a central hospital.

INTRODUCTION: Adverse health effects related with chronic exposure to waste anesthetic gases remain controversial. Strict threshold values are recommended to minimize possible health risks. The objective of our study was to measure the concentration of waste anesthetic gases in different hospital settings in an 11-year period. MATERIALS AND METHODS: Six-monthly assessment of nitrous oxide, sevoflurane, and desflurane was made between 2005 and 2016 in different hospital departments. Trace gas analysis was performed by infrared spectroscopy. RESULTS: An anesthetic gas concentration above the upper limit of the threshold value was found in computed tomography/magnetic resonance imaging (CT/MRI) (45.5%), ambulatory operating room (34.5%), and in the burn unit (31.6%). Desflurane assessment was more frequently above the upper limit of threshold value (12.37%). DISCUSSION: In the CT/MRI department, the small number of air cycling per hour and the frequent use of a face mask with the associated risk of leakage may explain the results. In burn unit patients inhalatory route is also frequent. Desflurane is widely used for its rapid elimination and rapid recovery, which is compatible with the results. Being odorless, it may be connected to undetected escape. CONCLUSION: The places with more anesthetic agents exposure were the CT/MRI, the ambulatory operating room, and the burn unit. Desflurane was the anesthetic agent more frequently above the upper limit of threshold value. To complement environmental surveillance, it is essential to establish a health surveillance system for professionals exposed to anesthetic agents.

Sleep quality as predictor of BMI in non-depressed caregivers of people with dementia.

PURPOSE: Although most cross-sectional and longitudinal studies of children and adolescents have found a link between short duration of sleep and obesity, the literature related to adults provides a non-consensual framework. The aim of the present study was to examine the association between sleep quality and BMI in a population of caregivers looking after people suffering from dementia, with a view to identifying the moderating role of depressive symptoms in the relationship between sleep problems and BMI. METHODS: A total of 117 subjects took part in the study, filling in a Sociodemographic Questionnaire, the Pittsburgh Sleep Quality Index, the Eating behavior Questionnaire and The Center for Epidemiologic Studies-Depression. RESULTS: Depressive symptoms were greater in females than in males. The sample was divided into two subgroups based on depressive-symptom scores. Only within the subsample with low depressive symptoms, higher sleep disturbances influenced BMI positively. Within this subsample of participants with low depressive symptoms, the variables that seem to play a pivotal role in explaining a high BMI are: female gender, sleep problems, and diet quality, while within the subsample with high depressive symptoms only the female gender factor was found to influence BMI. CONCLUSIONS: Depressive symptoms seem to act as moderators in the relationship between sleep and BMI. They should be evaluated to identify the risk of high BMI, and to differentiate clinical intervention, at least in this population, which experiences the stress of caregiving chronically, though not suffering from clinical eating disorders. LEVEL OF EVIDENCE: Level II, cross-sectional study.

Correction to: Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer's disease resilience.

CORRECTION: The original version of this article [1] unfortunately contained a typographical error. The 'Alzheimer's Disease Neuroimaging Initiative' was erroneously included as 'Alzheimer's Disease Neuroimaging Initative' in the author list of the article.

Is poor sleep associated with obesity in older adults? A narrative review of the literature.

INTRODUCTION: To address the worldwide epidemic of obesity, a sizable literature implicates sleep problems in the onset of obesity in younger populations. However, less is known about how this process may operate among older adults, which is of concern, given demographic shifts that have resulted in a much higher proportion of developed nations around the world reaching late life. METHODS: We offer a current review of the literature studying older adults and examining associations between sleep quality and obesity in this population. We consider both subjective and objectively measured sleep as well as both cross-sectional and longitudinal studies offering stronger causal inference. RESULTS: We discuss seemingly contradictory literature showing that shorter sleep duration as well as longer sleep duration are associated with obesity risk, then review studies that tested for non-linear relationships and reported a U-shape pattern, suggesting that too much or too little sleep is detrimental. Besides sleep duration, we discuss evidence showing that other forms of sleep dysfunction related to night-time awakenings, REM sleep, slow-wave sleep, and daytime sleepiness, which are indicators of sleep quality, are also linked to obesity. Specific psychological and physiological mediators and moderators, suggesting possible mechanisms whereby sleep problems may affect obesity in older adults, are described. CONCLUSION: We conclude by discussing areas, where additional research could help clarify this association, considering such factors as medical comorbidities common in late life, and health-related behaviors that may stem from poor sleep (such as disordered eating behavior). Such insights will have great value for clinical practice. LEVEL OF EVIDENCE: Level V, narrative review.

Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer's disease resilience.

BACKGROUND: While age and the APOE ε4 allele are major risk factors for Alzheimer's disease (AD), a small percentage of individuals with these risk factors exhibit AD resilience by living well beyond 75 years of age without any clinical symptoms of cognitive decline. METHODS: We used over 200 "AD resilient" individuals and an innovative, pedigree-based approach to identify genetic variants that segregate with AD resilience. First, we performed linkage analyses in pedigrees with resilient individuals and a statistical excess of AD deaths. Second, we used whole genome sequences to identify candidate SNPs in significant linkage regions. Third, we replicated SNPs from the linkage peaks that reduced risk for AD in an independent dataset and in a gene-based test. Finally, we experimentally characterized replicated SNPs. RESULTS: Rs142787485 in RAB10 confers significant protection against AD (p value = 0.0184, odds ratio = 0.5853). Moreover, we replicated this association in an independent series of unrelated individuals (p value = 0.028, odds ratio = 0.69) and used a gene-based test to confirm a role for RAB10 variants in modifying AD risk (p value = 0.002). Experimentally, we demonstrated that knockdown of RAB10 resulted in a significant decrease in Aß42 (p value = 0.0003) and in the Aß42/Aß40 ratio (p value = 0.0001) in neuroblastoma cells. We also found that RAB10 expression is significantly elevated in human AD brains (p value = 0.04). CONCLUSIONS: Our results suggest that RAB10 could be a promising therapeutic target for AD prevention. In addition, our gene discovery approach can be expanded and adapted to other phenotypes, thus serving as a model for future efforts to identify rare variants for AD and other complex human diseases.

Family Member Deaths in Childhood Predict Systemic Inflammation in Late Life.

Biological and epidemiological evidence has linked early-life psychosocial stress with late-life health, with inflammation as a potential mechanism. We report here the association between familial death in childhood and adulthood and increased levels of high-sensitivity C-reactive protein (CRP), a marker of systemic inflammation. The Cache County Memory Study is a prospective study of persons initially aged 65 and older in 1995. In 2002, there were 1,955 persons in the study with data on CRP (42.3 percent male, mean [SD] age = 81.2 [5.8] years), linked with objective data on family member deaths. Using logistic regression, high (> 10 mg/L) versus low (≤ 10 mg/L) CRP was regressed on cumulative parental, sibling, spouse, and offspring deaths during childhood and during early adulthood, adjusted for family size in each period (percentage family depletion; PFD). Findings revealed PFD during childhood to be significantly associated with CRP (OR = 1.02, 95% CI [1.01, 1.04]). Individuals with two or more family deaths were 79 percent more likely to have elevated CRP than those with zero family deaths (OR = 1.79, 95% CI [1.07, 2.99]). Early adulthood PFD was not related to CRP. This study demonstrates a link between significant psychosocial stress in early life and immune-inflammatory functioning in late life, and suggests a mechanism explaining the link between early-life adversity and late-life health.

Personal Journal Keeping and Linguistic Complexity Predict Late-Life Dementia Risk: The Cache County Journal Pilot Study.

OBJECTIVES: We determined the feasibility of accessing personal journals and correlating markers of linguistic complexity with all-cause dementia and Alzheimer's disease (AD). METHOD: A stratified random sample of 215 older adults reported on lifetime journal writing habits. From 66 of these participants (49% of those with journals), digital photographs of journal text were transcribed then subjected to the Linguistic Inquiry Word Count program to measure linguistic complexity markers: Words per Sentence, Percentage of 6+ Letter Words, Cognitive Mechanics, Percentage of Unique Words, and Percentage of Words that are Numerals. AD diagnosis was made via in-depth clinical protocol. RESULTS: In the larger sample, ever being a journal writer significantly predicted a 53% reduction in all-cause dementia risk. In the subsample with transcribed writings, Percentage of 6+ Letter Words predicted AD and all-cause dementia risk, with all logistic regression models controlling for age, education, gender, and Latter-Day Saints affiliation. DISCUSSION: These data suggest the potential viability of adulthood language use as a predictive tool for late-life AD risk, both in the linguistic features and the practice of journal writing itself.

Modelling assistive technology adoption for people with dementia.

PURPOSE: Assistive technologies have been identified as a potential solution for the provision of elderly care. Such technologies have in general the capacity to enhance the quality of life and increase the level of independence among their users. Nevertheless, the acceptance of these technologies is crucial to their success. Generally speaking, the elderly are not well-disposed to technologies and have limited experience; these factors contribute towards limiting the widespread acceptance of technology. It is therefore important to evaluate the potential success of technologies prior to their deployment. MATERIALS AND METHODS: The research described in this paper builds upon our previous work on modelling adoption of assistive technology, in the form of cognitive prosthetics such as reminder apps and aims at identifying a refined sub-set of features which offer improved accuracy in predicting technology adoption. Consequently, in this paper, an adoption model is built using a set of features extracted from a user's background to minimise the likelihood of non-adoption. The work is based on analysis of data from the Cache County Study on Memory and Aging (CCSMA) with 31 features covering a range of age, gender, education and details of health condition. In the process of modelling adoption, feature selection and feature reduction is carried out followed by identifying the best classification models. FINDINGS: With the reduced set of labelled features the technology adoption model built achieved an average prediction accuracy of 92.48% when tested on 173 participants. CONCLUSIONS: We conclude that modelling user adoption from a range of parameters such as physical, environmental and social perspectives is beneficial in recommending a technology to a particular user based on their profile.

The Empowering Role of Mobile Apps in Behavior Change Interventions: The Gray Matters Randomized Controlled Trial.

BACKGROUND: Health education and behavior change programs targeting specific risk factors have demonstrated their effectiveness in reducing the development of future diseases. Alzheimer disease (AD) shares many of the same risk factors, most of which can be addressed via behavior change. It is therefore theorized that a behavior change intervention targeting these risk factors would likely result in favorable rates of AD prevention. OBJECTIVE: The objective of this study was to reduce the future risk of developing AD, while in the short term promoting vascular health, through behavior change. METHODS: The study was an interventional randomized controlled trial consisting of subjects who were randomly assigned into either treatment (n=102) or control group (n=42). Outcome measures included various blood-based biomarkers, anthropometric measures, and behaviors related to AD risk. The treatment group was provided with a bespoke "Gray Matters" mobile phone app designed to encourage and facilitate behavior change. The app presented evidence-based educational material relating to AD risk and prevention strategies, facilitated self-reporting of behaviors across 6 behavioral domains, and presented feedback on the user's performance, calculated from reported behaviors against recommended guidelines. RESULTS: This paper explores the rationale for a mobile phone-led intervention and details the app's effect on behavior change and subsequent clinical outcomes. Via the app, the average participant submitted 7.3 (SD 3.2) behavioral logs/day (n=122,719). Analysis of these logs against primary outcome measures revealed that participants who improved their high-density lipoprotein cholesterol levels during the study duration answered a statistically significant higher number of questions per day (mean 8.30, SD 2.29) than those with no improvement (mean 6.52, SD 3.612), t97.74=-3.051, P=.003. Participants who decreased their body mass index (BMI) performed significantly better in attaining their recommended daily goals (mean 56.21 SD 30.4%) than those who increased their BMI (mean 40.12 SD 29.1%), t80 = -2.449, P=.017. In total, 69.2% (n=18) of those who achieved a mean performance percentage of 60% or higher, across all domains, reduced their BMI during the study, whereas 60.7% (n=34) who did not, increased their BMI. One-way analysis of variance of systolic blood pressure category changes showed a significant correlation between reported efforts to reduce stress and category change as a whole, P=.035. An exit survey highlighted that respondents (n=83) reported that the app motivated them to perform physical activity (85.4%) and make healthier food choices (87.5%). CONCLUSIONS: In this study, the ubiquitous nature of the mobile phone excelled as a delivery platform for the intervention, enabling the dissemination of educational intervention material while simultaneously monitoring and encouraging positive behavior change, resulting in desirable clinical effects. Sustained effort to maintain the achieved behaviors is expected to mitigate future AD risk. TRIAL REGISTRATION: ClinicalTrails.gov NCT02290912; https://clinicaltrials.gov/ct2/show/NCT02290912 (Archived by WebCite at http://www.webcitation.org/6ictUEwnm).

Presenilin E318G variant and Alzheimer's disease risk: the Cache County study.

BACKGROUND: Alzheimer's disease is the leading cause of dementia in the elderly and the third most common cause of death in the United States. A vast number of genes regulate Alzheimer's disease, including Presenilin 1 (PSEN1). Multiple studies have attempted to locate novel variants in the PSEN1 gene that affect Alzheimer's disease status. A recent study suggested that one of these variants, PSEN1 E318G (rs17125721), significantly affects Alzheimer's disease status in a large case-control dataset, particularly in connection with the APOEε4 allele. METHODS: Our study looks at the same variant in the Cache County Study on Memory and Aging, a large population-based dataset. We tested for association between E318G genotype and Alzheimer's disease status by running a series of Fisher's exact tests. We also performed logistic regression to test for an additive effect of E318G genotype on Alzheimer's disease status and for the existence of an interaction between E318G and APOEε4. RESULTS: In our Fisher's exact test, it appeared that APOEε4 carriers with an E318G allele have slightly higher risk for AD than those without the allele (3.3 vs. 3.8); however, the 95 % confidence intervals of those estimates overlapped completely, indicating non-significance. Our logistic regression model found a positive but non-significant main effect for E318G (p = 0.895). The interaction term between E318G and APOEε4 was also non-significant (p = 0.689). CONCLUSIONS: Our findings do not provide significant support for E318G as a risk factor for AD in APOEε4 carriers. Our calculations indicated that the overall sample used in the logistic regression models was adequately powered to detect the sort of effect sizes observed previously. However, the power analyses of our Fisher's exact tests indicate that our partitioned data was underpowered, particularly in regards to the low number of E318G carriers, both AD cases and controls, in the Cache county dataset. Thus, the differences in types of datasets used may help to explain the difference in effect magnitudes seen. Analyses in additional case-control datasets will be required to understand fully the effect of E318G on Alzheimer's disease status.

Closer caregiver and care-recipient relationships predict lower informal costs of dementia care: The Cache County Dementia Progression Study.

INTRODUCTION: Identifying factors associated with lower dementia care costs is essential. We examined whether two caregiver factors were associated with lower costs of informal care. METHODS: A total of 271 care dyads of the Cache County Dementia Study were included. Estimates of informal costs were based on caregiver reports of time spent in care-related activities and inflation-adjusted 2012 Utah median hourly wages. Caregiver coping and emotional closeness with the care-recipient were assessed using the Ways of Coping Checklist-Revised and Relationship Closeness Scale, respectively. RESULTS: Higher closeness was associated with 24% lower costs (expß = 0.763 [95% confidence interval: 0.583-0.999]) in linear mixed models controlling for demographics and baseline dementia severity and duration. Problem-focused coping was not associated with informal costs (P = .354). DISCUSSION: Caregiver closeness, a potentially modifiable factor, predicted lower dementia informal care costs over time. Future studies examining the care environment in closer dyads may identify specific care-related behaviors or strategies that are associated with lower costs.

Assessing app quality through expert peer review: a case study from the gray matters study.

Health apps focused on inciting behavior change are becoming increasingly popular. Nevertheless, many lack underlying evidence base, scientific credibility and have limited clinical effectiveness. It is therefore important that apps are well-informed, scientifically credible, peer reviewed and evidence based. This paper presents the use of the Mobile App Rating Scale (MARS) to assess the quality of the Grey Matters app, a cross platform app to deliver health education material and track behavior change across multi-domains with the aim of reducing the risk of developing Alzheimer's disease. The Gray Matters app shows promising results following reviews from 5 Expert raters, achieving a mean overall MARS score of 4.45 ± 0.14. Future work will involve undertaking of a detailed content analysis of behavior change apps to identify common themes and features which may lead to the successful facilitation of sustained behavior change.

Technology adoption and prediction tools for everyday technologies aimed at people with dementia.

A wide range of assistive technologies have been developed to support the elderly population with the goal of promoting independent living. The adoption of these technology based solutions is, however, critical to their overarching success. In our previous research we addressed the significance of modelling user adoption to reminding technologies based on a range of physical, environmental and social factors. In our current work we build upon our initial modeling through considering a wider range of computational approaches and identify a reduced set of relevant features that can aid the medical professionals to make an informed choice of whether to recommend the technology or not. The adoption models produced were evaluated on a multi-criterion basis: in terms of prediction performance, robustness and bias in relation to two types of errors. The effects of data imbalance on prediction performance was also considered. With handling the imbalance in the dataset, a 16 feature-subset was evaluated consisting of 173 instances, resulting in the ability to differentiate between adopters and non-adopters with an overall accuracy of 99.42 %.

Family member deaths across adulthood predict Alzheimer's disease risk: The Cache County Study.

OBJECTIVES: Parental death during childhood, and offspring and spouse death during adulthood have individually been associated with faster cognitive decline and higher Alzheimer's disease (AD) risk in late life. However, the cumulative effect of childhood and adulthood family deaths on AD risk among different age cohorts has not been studied. METHODS: To examine these associations, this prospective cohort study uses a population-based sample of 4545 initially non-demented participants (56.7% female; age M = 75.0/SD = 6.9 years) observed at four triennial waves, linked with objective Utah Population Database data on cumulative mother, father, sibling, spouse, and offspring death experienced during childhood and adulthood. Cox regression modeled survival time from baseline interview to AD onset, as a function of family deaths during childhood or adulthood, among different age groups, along with gender and presence of ε4 allele at apolipoprotein E (APOE) polymorphic genetic locus. RESULTS: Age group significantly moderated the relationship between family death and AD; among persons aged 65-69 years at baseline (children of the Great Depression), those exposed to 3-4 deaths and 5+ deaths during adulthood exhibited a doubling of AD risk (adjusted hazard ratio, aHR = 2.25, p = .038, and aHR = 2.72, p = .029), while among persons aged 80 years and older, those exposed to 3-4 deaths during adulthood exhibited lower AD risk (HR = 0.539, p = 0.014). In a combined model of childhood and adulthood deaths, these findings persisted. CONCLUSIONS: Results suggest a cohort effect in the link between family member deaths during adulthood and AD risk later in life.

Dementia severity and the longitudinal costs of informal care in the Cache County population.

BACKGROUND: Dementia costs are critical for influencing healthcare policy, but limited longitudinal information exists. We examined longitudinal informal care costs of dementia in a population-based sample. METHODS: Data from the Cache County Study included dementia onset, duration, and severity assessed by the Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale (CDR), and Neuropsychiatric Inventory (NPI). Informal costs of daily care (COC) was estimated based on median Utah wages. Mixed models estimated the relationship between severity and longitudinal COC in separate models for MMSE and CDR. RESULTS: Two hundred and eighty-seven subjects (53% female, mean (standard deviation) age was 82.3 (5.9) years) participated. Overall COC increased by 18% per year. COC was 6% lower per MMSE-point increase and compared with very mild dementia, COC increased over twofold for mild, fivefold for moderate, and sixfold for severe dementia on the CDR. CONCLUSIONS: Greater dementia severity predicted higher costs. Disease management strategies addressing dementia progression may curb costs.

Population-based analysis of cholesteryl ester transfer protein identifies association between I405V and cognitive decline: the Cache County Study.

Cholesterol has been implicated in the pathogenesis of late-onset Alzheimer's disease (LOAD) and the cholesteryl ester transfer protein (CETP) is critical to cholesterol regulation within the cell, making CETP an Alzheimer's disease candidate gene. Several studies have suggested that CETP I405V (rs5882) is associated with cognitive function and LOAD risk, but findings vary and most studies have been conducted using relatively small numbers of samples. To test whether this variant is involved in cognitive function and LOAD progression, we genotyped 4486 subjects with up to 12 years of longitudinal cognitive assessment. Analyses revealed an average 0.6-point decrease per year in the rate of cognitive decline for each additional valine (p < 0.011). We failed to detect the association between CETP I405V and LOAD status (p < 0.28). We conclude that CETP I405V is associated with preserved cognition over time but is not associated with LOAD status.

Dementia caregivers' coping strategies and their relationship to health and well-being: the Cache County Study.

OBJECTIVES: Prior research identifies that psychological outcomes among dementia caregivers are associated with their use of coping strategies. Few studies have tested the association of coping and health longitudinally. METHOD: This study examined factors associated with the use of coping strategies over time and their associations with physical and mental health outcomes in a population-based sample of 226 dementia caregivers in Cache County, Utah, USA. Caregivers annually completed the Ways of Coping Checklist-Revised, the Beck Anxiety Inventory, and a health interview. Care-recipient cognitive and functional abilities were obtained using the Mini-Mental State Exam and the Clinical Dementia Rating. Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory. RESULTS: Caregivers most frequently identified providing care as a problem (37.6%). Linear mixed models of caregiver coping strategies found that the use of most strategies were stable except for increasing Avoidance among adult child caregivers (ß = 0.14, p = 0.048). On average, increased Wishful Thinking (ß = 2.48, p < 0.001) or Blames Self (ß = 1.06, p = 0.002) was associated with higher anxiety scores. Increased use of Blames Others among males (interaction, ß = 0.28, p = 0.02) and greater use of Wishful Thinking among younger caregivers (interaction, ß = -0.01, p = 0.01) were associated with more caregiver health conditions. Coping strategies were not associated with change in anxiety or health conditions over time. CONCLUSION: Our results emphasize the importance of caregiver coping strategies on caregiver health and well-being and may identify subgroups of persons at risk for worse outcomes.

Latent classes of course in Alzheimer's disease and predictors: the Cache County Dementia Progression Study.

OBJECTIVE: Several longitudinal studies of Alzheimer's disease (AD) report heterogeneity in progression. We sought to identify groups (classes) of progression trajectories in the population-based Cache County Dementia Progression Study (N = 328) and to identify baseline predictors of membership for each group. METHODS: We used parallel-process growth mixture models to identify latent classes of trajectories on the basis of Mini-Mental State Exam (MMSE) and Clinical Dementia Rating sum of boxes scores over time. We then used bias-corrected multinomial logistic regression to model baseline predictors of latent class membership. We constructed receiver operating characteristic curves to demonstrate relative predictive utility of successive sets of predictors. RESULTS: We fit four latent classes; class 1 was the largest (72%) and had the slowest progression. Classes 2 (8%), 3 (11%), and 4 (8%) had more rapid worsening. In univariate analyses, longer dementia duration, presence of psychosis, and worse baseline MMSE and Clinical Dementia Rating sum of boxes were associated with membership in class 2, relative to class 1. Lower education was associated with membership in class 3. In the multivariate model, only MMSE remained a statistically significant predictor of class membership. Receiver operating characteristic areas under the curve were 0.98, 0.88, and 0.67, for classes 2, 3, and 4 relative to class 1. CONCLUSIONS: Heterogeneity in AD course can be usefully characterized using growth mixture models. The majority belonged to a class characterized by slower decline than is typically reported in clinical samples. Class membership could be predicted using baseline covariates. Further study may advance our prediction of AD course at the population level and in turn shed light on the pathophysiology of progression.

Rarity of the Alzheimer disease-protective APP A673T variant in the United States.

IMPORTANCE: Recently, a rare variant in the amyloid precursor protein gene (APP) was described in a population from Iceland. This variant, in which alanine is replaced by threonine at position 673 (A673T), appears to protect against late-onset Alzheimer disease (AD). We evaluated the frequency of this variant in AD cases and cognitively normal controls to determine whether this variant will significantly contribute to risk assessment in individuals in the United States. OBJECTIVE: To determine the frequency of the APP A673T variant in a large group of elderly cognitively normal controls and AD cases from the United States and in 2 case-control cohorts from Sweden. DESIGN, SETTING, AND PARTICIPANTS: Case-control association analysis of variant APP A673T in US and Swedish white individuals comparing AD cases with cognitively intact elderly controls. Participants were ascertained at multiple university-associated medical centers and clinics across the United States and Sweden by study-specific sampling methods. They were from case-control studies, community-based prospective cohort studies, and studies that ascertained multiplex families from multiple sources. MAIN OUTCOMES AND MEASURES: Genotypes for the APP A673T variant were determined using the Infinium HumanExome V1 Beadchip (Illumina, Inc) and by TaqMan genotyping (Life Technologies). RESULTS: The A673T variant genotypes were evaluated in 8943 US AD cases, 10 480 US cognitively normal controls, 862 Swedish AD cases, and 707 Swedish cognitively normal controls. We identified 3 US individuals heterozygous for A673T, including 1 AD case (age at onset, 89 years) and 2 controls (age at last examination, 82 and 77 years). The remaining US samples were homozygous for the alanine (A673) allele. In the Swedish samples, 3 controls were heterozygous for A673T and all AD cases were homozygous for the A673 allele. We also genotyped a US family previously reported to harbor the A673T variant and found a mother-daughter pair, both cognitively normal at ages 72 and 84 years, respectively, who were both heterozygous for A673T; however, all individuals with AD in the family were homozygous for A673. CONCLUSIONS AND RELEVANCE: The A673T variant is extremely rare in US cohorts and does not play a substantial role in risk for AD in this population. This variant may be primarily restricted to Icelandic and Scandinavian populations.