Alzheimer Disease And Related Dementias Research Articles

Feasibility of Using a Novel, Multimodal Motor Function Assessment Platform With Machine Learning to Identify Individuals With Mild Cognitive Impairment.

Early identification of clinical conditions associated with Alzheimer disease and related dementias (ADRD) is vital for intervention. One promising early detection method is the use of instrumented assessment to identify subtle motor declines associated with ADRD. This pilot study sought to establish the feasibility of building a machine learning model to identify individuals with mild cognitive impairment (MCI) using motor function data obtained from an inexpensive, portable device. Our novel, multimodal motor function assessment platform integrates a depth camera, forceplate, and interface board. Healthy older adults (n=28) and older adults with MCI (n=19) were assessed during static balance, gait, and sit-to-stand activities in both single- and dual-task conditions. Three machine learning models (ie, support vector machine, decision trees, and logistic regression) were trained and tested with the goal of classification of MCI. Our best model was decision trees, which demonstrated an accuracy of 83%, a sensitivity of 0.83, a specificity of 1.00, and an F1 score of 0.83. The top features were extracted and ranked on importance. This study demonstrates the feasibility of building a machine learning model capable of identifying individuals with mild cognitive impairment using motor function data obtained with a portable, inexpensive, multimodal device.

Optimal cutoff scores of the Montreal Cognitive Assessment to detect mild cognitive impairment and dementia in Costa Rican older adults

ABSTRACT Background The burden of Alzheimer’s disease and related dementias (AD/ADRD) in Costa Rica is expected to become one of the highest in the region. Early detection will help optimize resources and improve primary care interventions. The Montreal Cognitive Assessment (MoCA) has shown good sensitivity for detecting mild cognitive impairment (MCI), but specificity varies depending on the population. This motivated the analysis of different cutoffs to minimize false-positive classifications in a Costa Rican sample for its use in clinical settings. Methods Data was analyzed from 516 memory clinic outpatients (148 cognitively normal, 260 MCI, 108 mild AD/ADRD; mean age 66.3 ± 10.8 years) who underwent complete neurological and neuropsychological assessment and were diagnosed by consensus. Optimal MoCA cutoff scores were identified using a multiple cutoff approach. Results Overall, a cutoff score of ≥ 23 showed better accuracy to distinguish between normal cognition (NC) and MCI (sensitivity 73%, specificity 83%). When analyzed by educational levels, a cutoff score of ≥ 21 showed better accuracy for ≤ 6 years (sensitivity 80%, specificity 76%), ≥23 for 7–12 years (sensitivity 86%, specificity 76%) and ≥ 24 for > 12 years (sensitivity 70%, specificity 85%). For distinguishing MCI from mild AD/ADRD, the optimal overall cutoff score was ≥ 15 (sensitivity 66%, specificity 85%). When stratified by years of education, cutoff scores of ≥ 14 showed better accuracy for ≤ 6 years (sensitivity 70%, specificity 88%), ≥15 for 7–12 years (sensitivity 46%, specificity 95%) and ≥ 17 for > 12 years (sensitivity 67%, specificity 93%). Conclusions A MoCA cutoff score of ≥ 23 in the Costa Rican population showed better diagnostic accuracy for detecting MCI and may reduce the false positive rate. Our findings may be helpful for primary care clinical settings and further referral criteria.

Intervention for the Management of Neuropsychiatric Symptoms to Reduce Caregiver Stress: Protocol for the Mindful and Self-Compassion Care Intervention for Caregivers of Persons Living With Dementia.

Stress related to Alzheimer disease and related dementias (ADRD) is common, particularly among those who care for persons with challenging behaviors and personality or mood changes. Mindfulness and self-compassion programs are efficacious for managing stress. The skills of mindfulness and self-compassion, however, must be integrated with behavioral management skills in order to effectively improve caregiver stress. In this study, we aimed to describe the development of the Mindful and Self-Compassionate Care (MASC) program, the first program that combines mindfulness and self-compassion with behavioral management skills to decrease caregiver stress, and its evaluation in the Supporting Our Caregivers in ADRD Learning (SOCIAL) study. Using the National Institutes of Health (NIH) stage model, we describe 3 phases of work encompassing NIH Stages 1A and 1B. In phase 1, we conducted 5 focus groups (N=28) of stressed individuals caring for persons with ADRD and challenging behaviors. Rapid data analysis informed the development of a 6-week online intervention. Phase 2 (NIH stage 1A) includes an open pilot (N>10) with optional exit interviews. Phase 3 (NIH stage 1B) is a feasibility randomized controlled trial of the intervention versus the Health Education Program control. Primary outcomes focus on feasibility with secondary outcomes encompassing acceptability, credibility, fidelity, and signals of preliminary efficacy. Phase 1 follows traditional recommendations for qualitative analyses (at the point of thematic saturation) which was achieved after 5 focus groups (N=28). For the phase 2 open pilot, up to 12 participants will be recruited. For the phase 3 feasibility study, recruitment of 80 caregivers will allow the assessment of feasibility benchmarks. Data for phase 1 included 5 focus groups. In phases 2 and 3, data collection will occur through REDCap (Research Electronic Data Capture; Vanderbilt University) surveys and an optional qualitative exit interview. Analyses will include hybrid inductive-deductive analyses for qualitative data and assessment of changes in our intervention targets and outcomes using t tests and correlation analyses. In phase 1, caregivers reported interest in a brief, online stress management program. Participants held misconceptions about mindfulness and self-compassion, but after detailed explanation thoughts, these skills could be helpful when directly linked to implementation during caregiving routines. Phases 2 and 3 will be completed by the end of 2025. We describe the protocol for the Supporting Our Caregivers in ADRD Learning study, as well as the development and feasibility testing of the Mindful and Self-Compassionate Care intervention. Future work will include a fully powered efficacy-effectiveness randomized controlled trial. ClinicalTrials NCT05847153; https://clinicaltrials.gov/study/NCT05847153; and ClinicalTrials.gov NCT06276023; https://clinicaltrials.gov/study/NCT06276023. DERR1-10.2196/58356.

Annual Wellness Visits and Early Dementia Diagnosis Among Medicare Beneficiaries

Early recognition of cognitive impairment is key to optimal dementia care. No previous research has examined the probability of developing mild cognitive impairment (MCI) or Alzheimer disease and related dementias (ADRD) at 5-year follow-up among older adult Medicare beneficiaries by receipt of an annual wellness visit (AWV). To assess the association of incident AWV with the first ADRD or MCI diagnosis among older adults with Medicare fee-for-service benefits. This retrospective population-based cohort study used 100% Texas fee-for-service Medicare data from 2015 to 2022. Participants comprised 549 516 community-dwelling Medicare beneficiaries aged 68 years or older in 2018, with complete Medicare fee-for-service Parts A and B and no Medicare Advantage plan enrollment for 2015 to 2018. Medicare AWVs. The first MCI or ADRD diagnosis (reported as MCI or ADRD diagnosis, MCI diagnosis, and ADRD diagnosis) from the AWV index date in 2018 through December 31, 2022. In this cohort study of 549 516 Medicare beneficiaries with no diagnosis of MCI or ADRD in 2015 to 2017 (mean [SD] age, 76.7 [6.6] years; 289 932 women [52.8%]), 66 433 (12.1%) had an incident AWV in 2018. Annual wellness visit recipients were more likely than those who did not receive an AWV to be female, to be non-Hispanic White (followed by Hispanic, non-Hispanic Black, and other), to have more education, to reside in a metropolitan area, to have more comorbidities, and to have a primary care professional in the 12 months before the AWV index date. After propensity score matching, AWV receipt was associated with a 21% increase in MCI diagnosis (hazard ratio, 1.21 [95% CI, 1.16-1.27]) and a 4% increase in ADRD diagnosis (hazard ratio, 1.04 [95% CI, 1.02-1.06]). The increase in MCI diagnosis associated with AWV was larger when the AWV was censored or treated as a time-dependent covariate in the follow-up period. These findings indicate that AWV recipients had a timelier first MCI diagnosis than those who did not receive an AWV, but first ADRD diagnosis differed little. This study suggests that the Medicare AWV health policy may increase MCI identification, prompting more specialized care.

The Alzheimer's Disease Neuroimaging Initiative Neuropathology Core: An update.

Biomarkers for Alzheimer's disease neuropathologic change (ADNC) have been instrumental in developing effective disease-modifying therapeutics. However, to prevent/treat dementia effectively, we require biomarkers for non-AD neuropathologies; for this, neuropathologic examinations and annotated tissue samples are essential. We conducted clinicopathologic correlation for the first 100 Alzheimer's Disease Neuroimaging Initiative (ADNI) Neuropathology Core (NPC) cases. Clinical syndromes in this cohort showed 95% sensitivity and 79% specificity for predicting high/intermediate ADNC, a 21% false positive rate, and a ∼44% false negative rate. In addition, 60% with high/intermediate ADNC harbored additional potentially dementing co-pathologies. These results suggest that clinical presentation imperfectly predicts ADNC and that accurate prediction of high/intermediate ADNC does not exclude co-pathology that may modify presentation, biomarkers, and therapeutic responses. Therefore, new biomarkers are needed for non-AD neuropathologies. The ADNI NPC supports this mission with well-characterized tissue samples (available through ADNI and the National Institute on Aging) and "gold-standard" diagnostic information (soon to include digital histology). The Alzheimer's Disease Neuroimaging Initiative (ADNI) Neuropathology Core (NPC) brain donation cohort now exceeds 200 cases. ADNI NPC data in National Alzheimer's Coordinating Center format are available through the Laboratory of Neuro Imaging. Digitized slide files from the ADNI NPC will be available in 2025. Requests for ADNI brain tissue samples can be submitted online for ADNI/National Institute on Aging evaluation. Clinical diagnoses of Alzheimer's disease (AD)/AD and related dementias (ADRD) do not always predict post mortem neuropathology. Neuropathology is essential for the development of novel AD/ADRD biomarkers.

Risk of Dementia Diagnosis After Injurious Falls in Older Adults

Emerging evidence suggests that mild cognitive impairment, which is a precursor to Alzheimer disease and related dementias (ADRD), places older adults at increased risk for falls. However, the risk that an older adult develops dementia after experiencing a fall is unknown. To determine the risk of new ADRD diagnosis after a fall in older adults. This retrospective cohort study examined Medicare Fee-for-Service data from 2014 to 2015, with follow-up data available for at least 1 year after the index encounter. Participants included adults aged 66 years and older who experienced a traumatic injury that resulted in an emergency department (ED) or inpatient encounter and did not have a preexisting diagnosis of dementia. Data analysis was performed from August 2023 to July 2024. Experiencing a fall compared with other mechanisms of injury, defined by International Classification of Diseases, Ninth Revision (ICD-9) and ICD-10 external cause of injury codes. The hazard of new ADRD diagnosis within 1 year of a fall, assessed by performing a Cox multivariable competing risk model that controlled for potential confounders while accounting for the competing risk of death. The study included 2 453 655 older adult patients who experienced a traumatic injury; 1 522 656 (62.1%) were female; 124 396 (5.1%) were Black and 2 232 102 (91.0%) were White; and the mean (SD) age was 78.1 (8.1) years. The mechanism of injury was a fall in 1 228 847 incidents (50.1%). ADRD was more frequently diagnosed within 1 year of a fall compared with other injury mechanisms (10.6% [129 910 of 1 228 847] vs 6.1% [74 799 of 1 224 808]; P < .001). The unadjusted hazard ratio (HR) of incident dementia diagnosis after a fall was 1.63 (95% CI, 1.61-1.64; P < .001). On multivariable Cox competing risk analysis, falling was independently associated with an increased risk of dementia diagnosis among older adults (HR, 1.21 [95% CI, 1.20-1.21]; P < .001) after controlling for patient demographics, medical comorbidities, and injury characteristics, while accounting for the competing risk of death. Among the subset of older adults without a recent skilled nursing facility admission, the HR was 1.27 (95% CI, 1.26-1.28; P < .001). In this cohort study, new ADRD diagnoses were more common after falls compared with other mechanisms of injury, with 10.6% of older adults being diagnosed with ADRD in the first year after a fall. To improve the early identification of ADRD, this study's findings suggest support for the implementation of cognitive screening in older adults who experience an injurious fall that results in an ED visit or hospital admission.

Ascertaining Out-of-Pocket Costs of Dementia Care: Feasibility Study of a Web-Based Weekly Survey.

Caring for a family member living with dementia is costly. A major contributor to care demands, and therefore to the costs, are the behavioral symptoms of dementia. Here, we examine the feasibility of ascertaining costs related to caregiving from weekly web-based surveys collected during a telehealth-based behavioral intervention study-Support via Technology: Living and Learning with Advancing Alzheimer Disease. This study aims to determine the feasibility and acceptability of using a web-based weekly survey to capture real-time data on out-of-pocket caregiving expenses and time commitments associated with dementia care. To examine relationships between behavioral symptoms, care partner reactivity, burden, and out-of-pocket dementia care costs. Feasibility was measured by accrual, retention, and data completion by participating care partners. Behavioral symptoms, care partner reactivity, and burden were collected before and after the intervention from 13 care partners. Weekly web-based surveys queried Support via Technology: Living and Learning with Advancing Alzheimer Disease care partners about their out-of-pocket costs associated with care-related activities. The surveys included questions on out-of-pocket costs care partners incurred from hospitalizations and emergency department use, primary care provider visits, use of paid in-home care or respite services, use of prescription medications, and use of over-the-counter medications. The surveys also queried the amount of time care partners devoted to these specific care-related activities. Out-of-pocket costs of dementia care were collected via a web-based weekly survey for up to 18 months. In-home assistance was the most frequently reported type of out-of-pocket care expense and the costliest. care partners who paid for in-home assistance or respite reported more behavioral and psychological symptoms of dementia behaviors, higher reactivity, and higher burden than those who did not. This novel web-based weekly survey-based approach offers lessons for designing and implementing future cost-focused studies and care partner-supportive telehealth-based interventions for Alzheimer disease and related dementias (ADRD). The results correspond with the existing understanding of ADRD in that high family-related out-of-pocket costs are a typical part of the caregiving experience, and those costs likely increase with dementia severity. The results may also offer potential insights to health systems and policy makers as they seek to implement telehealth-based and related interventions that seek to better support people living with ADRD and their family care partners. ClinicalTrials.gov NCT04335110; https://clinicaltrials.gov/ct2/show/NCT04335110.

Extracting Critical Information from Unstructured Clinicians' Notes Data to Identify Dementia Severity Using a Rule-Based Approach: Feasibility Study.

The severity of Alzheimer disease and related dementias (ADRD) is rarely documented in structured data fields in electronic health records (EHRs). Although this information is important for clinical monitoring and decision-making, it is often undocumented or "hidden" in unstructured text fields and not readily available for clinicians to act upon. We aimed to assess the feasibility and potential bias in using keywords and rule-based matching for obtaining information about the severity of ADRD from EHR data. We used EHR data from a large academic health care system that included patients with a primary discharge diagnosis of ADRD based on ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10 (International Statistical Classification of Diseases, Tenth Revision) codes between 2014 and 2019. We first assessed the presence of ADRD severity information and then the severity of ADRD in the EHR. Clinicians' notes were used to determine the severity of ADRD based on two criteria: (1) scores from the Mini Mental State Examination and Montreal Cognitive Assessment and (2) explicit terms for ADRD severity (eg, "mild dementia" and "advanced Alzheimer disease"). We compiled a list of common ADRD symptoms, cognitive test names, and disease severity terms, refining it iteratively based on previous literature and clinical expertise. Subsequently, we used rule-based matching in Python using standard open-source data analysis libraries to identify the context in which specific words or phrases were mentioned. We estimated the prevalence of documented ADRD severity and assessed the performance of our rule-based algorithm. We included 9115 eligible patients with over 65,000 notes from the providers. Overall, 22.93% (2090/9115) of patients were documented with mild ADRD, 20.87% (1902/9115) were documented with moderate or severe ADRD, and 56.20% (5123/9115) did not have any documentation of the severity of their ADRD. For the task of determining the presence of any ADRD severity information, our algorithm achieved an accuracy of >95%, specificity of >95%, sensitivity of >90%, and an F1-score of >83%. For the specific task of identifying the actual severity of ADRD, the algorithm performed well with an accuracy of >91%, specificity of >80%, sensitivity of >88%, and F1-score of >92%. Comparing patients with mild ADRD to those with more advanced ADRD, the latter group tended to contain older, more likely female, and Black patients, and having received their diagnoses in primary care or in-hospital settings. Relative to patients with undocumented ADRD severity, those with documented ADRD severity had a similar distribution in terms of sex, race, and rural or urban residence. Our study demonstrates the feasibility of using a rule-based matching algorithm to identify ADRD severity from unstructured EHR report data. However, it is essential to acknowledge potential biases arising from differences in documentation practices across various health care systems.

Oropharyngeal Dysphagia in Hospitalized Older Adults with Dementia: A Prospective Cohort Study

ObjectiveOropharyngeal dysphagia (dysphagia) is highly prevalent (up to 86%) in hospitalized patients with Alzheimer disease and related dementias (ADRD). This study aims to describe the management and clinical course of dysphagia in hospitalized patients with ADRD. DesignProspective observational cohort study. Setting and ParticipantsThe study was conducted across 10 hospitals within a large health system in New York. Participants were older adults with ADRD admitted to the medicine service and diagnosed with dysphagia to liquids on speech-language pathologist (SLP) assessment and were recruited between January and June 2023. MethodsBaseline characteristics [eg, dementia Functional Assessment Staging Tool (FAST)], dysphagia management (eg, prescribed diet), and clinical course (eg, dysphagia improvement, respiratory complications) were collected. ResultsOf patients with ADRD and dysphagia (n = 62), the average age was 86.5 and 66.1% were FAST Stage 7. On admission, 48.4% had pneumonia, 79.0% had delirium, and 69.4% were made nil per os (NPO) for aspiration risk. Of those who received SLP reassessment after diet initiation (n = 25), 76% demonstrated dysphagia improvement; 75% of patients with FAST stage 7 demonstrated improvement. Respiratory complications occurred in 21.0% of patients on the following diets: NPO, nasogastric tube feeding, dysphagia diets, and comfort feeds. In univariate analyses, hospital-acquired dehydration, no dysphagia improvement, and delirium were associated with respiratory complications. Conclusions and ImplicationsThe potential for dysphagia improvement in hospitalized patients with ADRD (even those with advanced dementia) highlights the critical need for standardizing reassessment. Further studies are needed to evaluate factors associated with respiratory complications in this population.

Case Definition for Diagnosed Alzheimer Disease and Related Dementias in Medicare

Lack of a US dementia surveillance system hinders efforts to support and address disparities among persons living with Alzheimer disease and related dementias (ADRD). To review diagnosis and prescription drug code ADRD identification algorithms to develop and implement case definitions for national surveillance. In this cross-sectional study, a systematic literature review was conducted to identify unique International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and prescription drug codes used by researchers to identify ADRD in administrative records. Code frequency of use, characteristics of beneficiaries identified by codes, and expert and author consensus around code definitions informed code placement into categories indicating highly likely, likely, and possible ADRD. These definitions were applied cross-sectionally to 2017 to 2019 Medicare fee-for-service (FFS) claims and Medicare Advantage (MA) encounter data to classify January 2019 Medicare enrollees. Data analysis was conducted from September 2022 to March 2024. ICD-10-CM and national drug codes in FFS claims or MA encounters. The primary outcome was counts and rates of beneficiaries meeting each case definition. Category-specific age, sex, race and ethnicity, MA enrollment, dual-eligibility, long-term care utilization, mortality, and rural residence distributions, as well as frailty scores and FFS monthly expenditures were also analyzed. Beneficiary characteristics were compared across categories, and age-standardized to minimize confounding by age. Of the 60 000 869 beneficiaries included (50 853 806 aged 65 years or older [84.8%]; 32 567 891 female [54.3%]; 5 555 571 Hispanic [9.3%]; 6 318 194 non-Hispanic Black [10.5%]; 44 384 980 non-Hispanic White [74.0%]), there were 4 312 496 (7.2%) with highly likely ADRD, 1 124 080 (1.9%) with likely ADRD, and 2 572 176 (4.3%) with possible ADRD, totaling more than 8.0 million with diagnostic evidence of at least possible ADRD. These beneficiaries were older, more frail, more likely to be female, more likely to be dual-eligible, more likely to use long-term care, and more likely to die in 2019 compared with beneficiaries with no evidence of ADRD. These differences became larger when moving from the possible ADRD group to the highly likely ADRD group. Mean (SD) FFS monthly spending was $2966 ($4921) among beneficiaries with highly likely ADRD compared with $936 ($2952) for beneficiaries with no evidence of ADRD. Differences persisted after age standardization. This cross-sectional study of 2019 Medicare beneficiaries identified more than 5.4 million Medicare beneficiaries with evidence of at least likely ADRD in 2019 using the diagnostic case definition. Pending validation against clinical and other methods of ascertainment, this approach can be adopted provisionally for national surveillance.

1365P Does cancer care differ for older adults with lung cancer living with and without Alzheimer disease and related dementias (ADRD)?

1365P Does cancer care differ for older adults with lung cancer living with and without Alzheimer disease and related dementias (ADRD)?

Whole exome sequencing analyses identified novel genes for Alzheimer's disease and related dementia.

The heritability of Alzheimer's disease (AD) is estimated to be 58%-79%. However, known genes can only partially explain the heritability. Here, we conducted gene-based exome-wide association study (ExWAS) of rare variants and single-variant ExWAS of common variants, utilizing data of 54,569 clinically diagnosed/proxy AD and related dementia (ADRD) and 295,421 controls from the UK Biobank. Gene-based ExWAS identified 11 genes predicting a higher ADRD risk, including five novel ones, namely FRMD8, DDX1, DNMT3L, MORC1, and TGM2, along with six previously reported ones, SORL1, GRN, PSEN1, ABCA7, GBA, and ADAM10. Single-variant ExWAS identified two ADRD-associated novel genes, SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. The druggability evidence suggests that DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets. Our study contributes to the current body of evidence on the genetic etiology of ADRD. Gene-based analyses of rare variants identified five novel genes for Alzheimer's disease and related dementia (ADRD), including FRMD8, DDX1, DNMT3L, MORC1, and TGM2. Single-variant analyses of common variants identified two novel genes for ADRD, including SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets.

Incidence of Alzheimer Disease and Related Dementias in Iran From 2010 to 2019.

This is the first comprehensive national and subnational epidemiological study reporting the incidence of Alzheimer disease and related dementias (ADRD) in Iran from 2010 to 2019 and predictions for 2024. We extracted age-standardized incidence stratified by sex and provinces from the Institute for Health Measurement and Evaluation (IHME). Arc Map GIS was used to report the geographical distribution, and the Cochran-Armitage test was used for prediction. Predictions showed that the incidence of ADRD would reach 118 (women) and 109 (men) cases per 100,000 population in Iran in 2024. The most increasing incidence from 2010 to 2019 was reported among women in Qom, while Yazd had the most incidences among men and women in 2019. The results showed an increase in the incidence of ADRD in Iran in recent years, and the increase in life expectancy and population aging can be considered as an influential factor.

Glycated Hemoglobin A1c Time in Range and Dementia in Older Adults With Diabetes

Individuals with diabetes commonly experience Alzheimer disease and related dementias (ADRD). Factors such as hypoglycemia, hyperglycemia, and glycemic variability have been associated with increased risk of ADRD. Traditional glycemic measures, such as mean glycated hemoglobin A1c (HbA1c), may not identify the dynamic and complex pathophysiologic factors in the association between diabetes and ADRD. The HbA1c time in range (TIR) is a previously developed measure of glycemic control that expresses HbA1c stability over time within specific ranges. This measure may inform the current understanding of the association between glucose levels over time and ADRD incidence. To examine the association between HbA1c TIR and incidence of ADRD in older veterans with diabetes. The study sample for this cohort study was obtained from administrative and health care utilization data from the Veterans Health Administration and Medicare from January 1, 2004, to December 31, 2018. Veterans 65 years or older with diabetes were assessed. Participants were required to have at least 4 HbA1c tests during the 3-year baseline period, which could start between January 1, 2005, and December 31, 2014. Data analysis was conducted between July and December 2023. Hemoglobin A1c TIR was calculated as the percentage of days during baseline in which HbA1c was in individualized target ranges based on clinical characteristics and life expectancy, with higher HbA1c TIR viewed as more favorable. The association between HbA1c TIR and ADRD incidence was estimated. Additional models considered ADRD incidence in participants who were above or below HbA1c target ranges most of the time. The study included 374 021 veterans with diabetes (mean [SD] age, 73.2 [5.8] years; 369 059 [99%] male). During follow-up of up to 10 years, 41 424 (11%) developed ADRD. Adjusted Cox proportional hazards regression models showed that lower HbA1c TIR was associated with increased risk of incident ADRD (HbA1c TIR of 0 to <20% compared with ≥80%: hazard ratio, 1.19; 95% CI, 1.16-1.23). Furthermore, the direction of out-of-range HbA1c levels was associated with incident ADRD. Having greater time below range (≥60%, compared with ≥60% TIR) was associated with significantly increased risk (hazard ratio, 1.23; 95% CI, 1.19-1.27). Findings remained significant after excluding individuals with baseline use of medications associated with hypoglycemia risk (ie, insulin and sulfonylureas) or with hypoglycemia events. In this study of older adults with diabetes, increased HbA1c stability within patient-specific target ranges was associated with a lower risk of ADRD. Lower HbA1c TIR may identify patients at increased risk of ADRD.

Visual Impairment, Eye Conditions, and Diagnoses of Neurodegeneration and Dementia

Vision and eye conditions are associated with increased risk for Alzheimer disease and related dementias (ADRDs), but the nature of the association and the underlying biological pathways remain unclear. If causal, vision would be an important modifiable risk factor with viable population-level interventions. To evaluate potentially causal associations between visual acuity, eye conditions (specifically cataracts and myopia), neuroimaging outcomes, and ADRDs. A cohort and 2-sample bidirectional mendelian randomization (MR) study was conducted using UK Biobank participants and summary statistics from previously published genome-wide association studies on cataract, myopia, and AD. The participants included in the analysis were aged 55 to 70 years without dementia at baseline (calendar years 2006 to 2010), underwent genotyping, and reported on eye conditions; a subset completed visual acuity examinations (n = 69 852-71 429) or brain imaging (n = 36 591-36 855). Data were analyzed from August 15, 2022, through November 28, 2023. Self-reported cataracts, visual acuity, and myopia measured by refraction error. ADRD, AD, and vascular dementia were identified from electronic medical records. Total and regional brain volumes were determined using magnetic resonance imaging. The sample included 304 953 participants (mean [SD] age, 62.1 (4.1) years; 163 825 women [53.72%]); 14 295 (4.69%) had cataracts and 2754 (3.86%) had worse than 20/40 vision. Cataracts (hazard ratio [HR], 1.18; 95% CI, 1.07-1.29) and myopia (HR, 1.35; 95% CI, 1.06-1.70) were associated with a higher hazard of ADRD. In MR analyses to estimate potential causal effects, cataracts were associated with increased risk of vascular dementia (inverse variance-weighted odds ratio [OR], 1.92; 95% CI, 1.26-2.92) but were not associated with increased dementia (OR, 1.21; 95% CI, 0.98-1.50). There were no associations between myopia and dementia. In MR for potential reverse causality, AD was not associated with cataracts (inverse variance-weighted OR, 0.99; 95% CI, 0.96-1.01). Genetic risk for cataracts was associated with smaller total brain (β = -597.43 mm3; 95% CI, -1077.87 to -117.00 mm3) and gray matter (β = -375.17 mm3; 95% CI, -680.10 to -70.24 mm3) volumes, but not other brain regions. In this cohort and MR study of UK Biobank participants, cataracts were associated with increased risk of dementia, especially vascular dementia, and reduced total brain volumes. These findings lend further support to the hypothesis that cataract extraction may reduce the risk for dementia.

Time to Dementia Diagnosis Among Veterans with Comorbid Insomnia and Depressive Episodes.

Older adults with heart failure are at elevated risk of Alzheimer's disease and related dementias (AD/ADRD). Research suggests that insomnia and depressive episodes contribute somewhat dissociable impacts on risk for AD/ADRD in this patient population, although the temporal ordering of effects is unknown. This study examined time to dementia diagnosis among patients with comorbid insomnia and/or depressive episodes in an epidemiological sample. Secondary data analyses were conducted using a cohort study of 203,819 Veterans with a primary admission diagnosis of heart failure in 129 VA Medical Centers. Patients with diagnoses of both insomnia and depressive episodes had the shortest time to a dementia diagnosis at both 1-year (Hazard ratio = 1.43, 95% CI [1.36, 1.51]) and 3-year follow-up time points (Hazard ratio = 1.40, 95% CI [1.34, 1.47]) versus patients with one or neither comorbidity. Individuals with both comorbidities had the shortest time to dementia onset. Screening for these comorbidities may help to identify patients at elevated risk of dementia who could benefit from enhanced monitoring or early intervention strategies for more rapid detection and management of dementia symptoms.

Alzheimer Disease and Related Dementia Following Hormone-Modulating Therapy in Patients With Breast Cancer

Hormone-modulating therapy (HMT) is a widely accepted treatment for hormone receptor-positive breast cancer, although its cognitive effects, including a potential link to Alzheimer disease and related dementias (ADRD), remain understudied. To investigate the association between HMT for breast cancer treatment and risk of developing ADRD in women aged 65 years or older. This cohort study used a comprehensive dataset from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database to identify patients who did and did not receive HMT treatment within 3 years after the initial diagnosis of breast cancer and assessed their risk of developing ADRD in later life. Individuals with a preexisting diagnosis of ADRD or receiving HMT before the diagnosis of breast cancer were excluded. This study was performed from June 2022 through January 2024. Receipt of HMT. Risk of ADRD associated with HMT; associations of risk with age, self-identified race, and HMT type. Risk was measured using hazard ratios (HRs) with 95% CIs and adjusted for potential confounders such as demographic, sociocultural, and clinical variables. Among 18 808 women aged 65 years and older diagnosed with breast cancer between 2007 and 2009 (1266 Black [6.7%], 16 526 White [87.9%], 1016 other [5.4%]), 12 356 (65.7%) received HMT within 3 years after diagnosis, while 6452 (34.3%) did not. The most common age group in both samples was the 75 to 79 years age group (HMT, 2721 women [22.0%]; no HMT, 1469 women [22.8%]), and the majority of women in both groups self-identified as White (HMT, 10 904 women [88.3%]; no HMT, 5622 women [87.1%]). During an average of 12 years of follow-up, 2926 (23.7%) of HMT users and 1802 (27.9%) of non-HMT users developed ADRD. HMT was associated with a 7% lower relative risk of ADRD overall (HR, 0.93; 95% CI, 0.88-0.98; P = .005). The association decreased with age and varied by race. The reduction in ADRD risk associated with HMT was greatest for women aged 65 to 74 years who self-identified as Black (HR, 0.76; 95% CI, 0.62-0.92). This association decreased among women aged 75 years or older (HR, 0.81; 95% CI, 0.67-0.98). Women aged 65 to 74 years who self-identified as White had an 11% relative risk reduction (HR, 0.89; 95% CI, 0.81-0.97), but the association disappeared for women aged 75 years or older (HR, 0.96; 95% CI, 0.90-1.02). Other races showed no significant association between HMT and ADRD. Age- and race-based associations also varied by HMT type. In this retrospective cohort study, hormone therapy was associated with protection against ADRD in women aged 65 years or older with newly diagnosed breast cancer; the decrease in risk was relatively greater for Black women and women under age 75 years, while the protective effect of HMT diminished with age and varied by race in women. When deciding to use HMT for breast cancer in women aged 65 years or more, clinicians should consider age, self-identified race, and HMT type in treatment decisions.

Disentangling the causal effects of education and participation bias on Alzheimer's disease using Mendelian Randomization.

People with university degrees have a lower incidence of Alzheimer's Disease (AD). However, the relationship between education and AD could be due to selection, collider, and ascertainment biases, such as lower familiarity with cognitive testing or the fact that those with degrees are more likely to participate in research. Here, we use two-sample Mendelian randomization (MR) to investigate the causal relationships between education, participation, and AD. We used genome-wide association study (GWAS) summary statistics for educational attainment, three different measures of participation, AD (clinically diagnosed AD), and AD/ADRD (clinical diagnosis and family history of AD and related dementias). Independent genome-wide significant single nucleotide polymorphisms (SNPs) were extracted from the exposure summary statistics and harmonized with the outcome SNPs. Fixed-effects inverse variance weighted meta-analysis was the primary MR method; Cochran's Q statistic and MR Egger intercept were used to test for heterogeneity and pleiotropy, and Radial-MR was used to identify outliers. Sensitivity analyses included MR Egger, Weighted Median, and Weighted mode. Bidirectional analyses were used to test if AD pathology affects participation and multivariable MR (MVMR) assessed independent exposure-outcome effects. Educational attainment reduced the risk of AD (OR IVW 95% CI= 0.70 [0.63, 0.79], p = 8e-10), and the results were robust based on sensitivity analyses. However, education increased the risk of AD/ADRD, though the results were not robust to sensitivity analyses (OR IVW 95% CI= 1.09 [1.02, 1.15], p = 0.006). Participation in MHQ reduced the odds of AD (OR IVW 95% CI= 0.325 [0.128, 0.326], p = 0.01). When adjusting for participation in MVMR, education remained associated with a reduced risk of AD (OR IVW 95% CI= 0.76 [0.62, 0.92], p = 0.006). Univariate MR analyses indicated that education and participation reduced the risk of AD. However, MR also suggested that education increased the risk of AD/ADRD, highlighting the inconsistencies between clinical and proxy diagnoses of AD, as proxy-AD may be affected by selection, collider, or ascertainment bias. MVMR indicated that participation is unlikely to explain the effect of education on AD identified in MR, and the protective effect of educational attainment may be due to other biological mechanisms, such as cognitive reserve.

Self-Explainable Graph Neural Network for Alzheimer Disease and Related Dementias Risk Prediction: Algorithm Development and Validation Study.

Alzheimer disease and related dementias (ADRD) rank as the sixth leading cause of death in the United States, underlining the importance of accurate ADRD risk prediction. While recent advancements in ADRD risk prediction have primarily relied on imaging analysis, not all patients undergo medical imaging before an ADRD diagnosis. Merging machine learning with claims data can reveal additional risk factors and uncover interconnections among diverse medical codes. The study aims to use graph neural networks (GNNs) with claim data for ADRD risk prediction. Addressing the lack of human-interpretable reasons behind these predictions, we introduce an innovative, self-explainable method to evaluate relationship importance and its influence on ADRD risk prediction. We used a variationally regularized encoder-decoder GNN (variational GNN [VGNN]) integrated with our proposed relation importance method for estimating ADRD likelihood. This self-explainable method can provide a feature-important explanation in the context of ADRD risk prediction, leveraging relational information within a graph. Three scenarios with 1-year, 2-year, and 3-year prediction windows were created to assess the model's efficiency, respectively. Random forest (RF) and light gradient boost machine (LGBM) were used as baselines. By using this method, we further clarify the key relationships for ADRD risk prediction. In scenario 1, the VGNN model showed area under the receiver operating characteristic (AUROC) scores of 0.7272 and 0.7480 for the small subset and the matched cohort data set. It outperforms RF and LGBM by 10.6% and 9.1%, respectively, on average. In scenario 2, it achieved AUROC scores of 0.7125 and 0.7281, surpassing the other models by 10.5% and 8.9%, respectively. Similarly, in scenario 3, AUROC scores of 0.7001 and 0.7187 were obtained, exceeding 10.1% and 8.5% than the baseline models, respectively. These results clearly demonstrate the significant superiority of the graph-based approach over the tree-based models (RF and LGBM) in predicting ADRD. Furthermore, the integration of the VGNN model and our relation importance interpretation could provide valuable insight into paired factors that may contribute to or delay ADRD progression. Using our innovative self-explainable method with claims data enhances ADRD risk prediction and provides insights into the impact of interconnected medical code relationships. This methodology not only enables ADRD risk modeling but also shows potential for other image analysis predictions using claims data.

Effect of gamification with a support partner to increase physical activity in older adults at risk for Alzheimer's disease: The STEP 4Life randomized clinical trial.

Physical activity is associated with reduced risk of cognitive and functional decline but scalable, sustainable interventions for populations at risk for Alzheimer's disease (AD) and AD and related dementias (ADRD) are lacking. A 12-week randomized-controlled trial was conducted with a 3-week follow-up using a national AD prevention registry (GeneMatch). The control group (n=50) set step goals and received daily feedback. The intervention group (n=44) also received a behaviorally designed game based on achieving step goals and reinforced by a support partner. Intervention participants (94 participants, mean age 70, 78% female) had greater change in mean daily step count than control of 1699 steps/day (95% confidence interval [CI], 1149-2249), P<0.0001, which was sustained in the follow-up period at 1219 steps/day (95% CI, 455-1983), P=0.0018. Carriers of the apolipoprotein E ε4 gene (high risk) did not perform differently than non-carriers; however, high self-reported risk perception was associated with higher activity. A gamified intervention was effective in promoting and sustaining higher physical activity in older adults at genetic risk for AD/ADRD. A simple game played with a support partner increased walking in older adults at risk for Alzheimer's disease (AD). The game also increased minutes of moderate-to-vigorous physical activity per day. Perception of lifelong AD risk was associated with increased activity but genetic risk (apolipoprotein E ε4+) was not. ClinicalTrials.gov: NCT05069155.