APOE4 Allele, Sex, and Dementia Risk in Parkinson’s Disease: Lessons From a Longitudinal Cohort

Introduction The effect of APOE4 allele on dementia risk is well established in Alzheimer’s disease and Parkinson’s disease (PD). However, it is unknown if sex modifies this relationship. We sought to determine the effect of sex on the relationship between APOE4 status and incident cognitive decline in PD. Methods Data from the prospectively collected longitudinal National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) and Neuropathology Data Set (NDS) were analyzed. The NACC develops and maintains data from approximately 29 National Institutes of Aging-funded Alzheimer's Disease Research Centers. Further details may be found at the NACC web site ( www.alz.washington.edu ). The visit at which diagnosis of PD was made was termed the baseline visit. All patients with a PD diagnosis but without dementia at the baseline visit were included in the analyses. Results Presence of APOE4 allele was associated with higher odds (OR = 7.4; P < .001) of subsequent diagnosis of dementia and with a faster time to developing dementia ( P = .04). Those with APOE4 allele were more likely to have neuropathology associated with Alzheimer’s disease than those without APOE4 allele. We did not find any difference by sex. There were no differences between Lewy body pathology or neuron loss in the substantia nigra between the 2 groups. Sex was not associated with dementia risk in PD (OR = 0.53, P = .15) or with the time to dementia onset ( P = .22). Sex did not modify the relationship between the APOE4 allele and dementia onset in PD patients ( P = .12) Conclusions APOE4 allele status in PD may be a predictor of cognitive decline in PD but does not appear to be modified by sex.

Derivation and Validation of an Algorithmic Classification of Early Cognitive Impairment

The long prodromal period for dementia pathology demands valid and reliable approaches to detect cases before clinically recognizable symptoms emerge, by which time it may be too late to effectively intervene. We derived and compared several algorithms for early cognitive impairment (ECI) using longitudinal data on 1704 BLSA participants. Algorithms were based on cognitive impairment in various combinations of memory and non-memory tests, and the CDR. The best-performing algorithm was defined based on 1SD below age-and race-specific means in Card Rotations or California Verbal Learning Test immediate recall, two tests that in prior work show the earliest declines prior to dementia onset. While this ECI algorithm showed low concordance with concurrent adjudicated MCI/dementia (AUC: 0.63, sensitivity: 0.54, specificity: 0.73), it was among the best predictors of progression to MCI/dementia (HR: 3.65, 95% CI: 1.69,7.87). This algorithm may be useful in epidemiologic work to evaluate risk factors for early cognitive impairment.

WLS-ILIAD: Initial Lifetime’s Impact on ADRD

Between 2021 and 2025, WLS will collect two new waves of data, which will capture detailed measures of cognitive change and dementia as the cohort reaches their early to mid 80s. In this session, I will provide an overview of the data that we’re collecting, as well as opportunities to explore early and mid-life determinants of cognitive change and dementia onset in this unique study. Compared to existing studies, the WLS offers some novel opportunities. First, it will provide one of the only opportunities to study how early and midlife life conditions and experiences, on data gathered prospectively, can shape cognitive trajectories and dementia in later life. Second, its unique sibling design provides significant analytic advantages, improving causal inference. Third, the study includes a large group of rural participants, allowing for closer examinations of how rural conditions may shape risk and resilience against cognitive decline and dementia in later life.

Cognitive Decline Over a 5-Year Period: The National Health and Aging Trends Study

The classification of Alzheimer’s disease and related dementia (ADRD) is important for understanding the progression of cognitive decline. This longitudinal study used data from the National Health and Aging Trends Study (NHATS). A sample of 3,287 eligible Medicare beneficiaries were included in the study. Nine cognitive profiles were examined from Waves 1 to 5 (2011-2015). Discriminant factor analysis was used to identify factors that differentiated across the cognitive profiles. Results showed that 1,076 had some measure of “possible” or “probable” dementia over the 5 years. In Wave 1, there were 104 self-reported ADRD diagnoses, and in Wave 5, there were 327 self-reported ADRD diagnoses. Social participation was an important factor in those that impairment reversed from probable to possible ADRD. Findings support previous evidence that certain activities may slow or reverse cognitive decline and can inform future studies exploring the causality of dementia onset.

Racial/Ethnic Differences in Trajectories of Dementia Onset

Racial and ethnic minority older adults—especially non-Latino Black and Latino older adults—continue to have a higher prevalence of dementia with longer delays in formal diagnosis compared to non-Latino Whites. Few studies have estimated racial/ethnic differences in trajectories of dementia onset using nationally representative data with representation from the three largest racial/ethnic groups in the U.S.: non-Latino White, non-Latino Black, and Latino older adults. Additionally, given the delays in formal diagnosis we rely on a measure of probable dementia that takes into account both formal diagnosis and cognitive function. Data from the National Health and Aging Trend Study (NHATS, 2011–2019) reveals three trajectories of dementia onset (early, late, and dementia-free) and we find that Latino and Black older adults are at greater risk for early dementia onset compared to non-Latino Whites. Our next step is to explore the role of social function for dementia disparities.

Detecting early signs of Alzheimer’s disease and related dementia onset from the EHR

As dementia is widely under-detected, a predictive model using electronic health records (EHR) could provide a method for early screening to implement preventive strategies. There is limited research on using EHR to identify persons with Alzheimer’s disease (AD) and related dementias (RD). In a data-driven approach, we used all ICD-9 diagnosis and CPT procedure codes from statewide inpatient, ambulatory surgery, and Medicare records, in addition to age at baseline and gender, to detect AD/RD from the Cache County Study on Memory in Aging (1995–2009). After removing participants diagnosed with dementia at baseline (n=335), 3882 (82%) Cache County Study participants could be linked to inpatient, ambulatory surgery, and/or Medicare EHR records; 484 (12.5%) of these 3882 had incident all-cause dementia, with 308 (7.9%) having AD/AD comorbid with RD; and 176 (4.5%) having RD without AD. We removed participant’s ICD-9 codes occurring after first AD/RD diagnoses. EHR features (~2000) along with gold-standard diagnoses as class labels were then used to train and detect AD and/or RD using a Gradient Boosting Trees machine learning algorithm. Models evaluated with nested cross-validation yielded AUCs of 0.70 for all-cause dementia, 0.69 for AD/AD comorbid with RD, and 0.67 for RD without AD. Key factors detecting AD/RD included age at enrollment, cardiovascular, metabolic, and kidney disease, and sleep disturbances, with feature importance varying by record type and time frame prior to dementia onset. Our findings suggest that a patient’s health status up to 12 years prior may be useful in identifying individuals at-risk for dementia development.

Oral Status and Dementia Onset: Mediation of Nutritional and Social Factors

Some modifiable risk factors for dementia are closely related to oral health. Although eating and speaking abilities are fundamental oral functions, limited studies have focused on the effect of malnutrition and lack of social interaction between oral health and dementia. We investigated the mediating effects of nutritional and social factors on the association between the number of teeth and the incidence of dementia. This 6-y cohort study used data from the Japan Gerontological Evaluation Study targeting older adults aged 65 y and above. The number of teeth (exposure) and covariates in 2010 (baseline survey), mediators (weight loss, vegetable and fruit intake, homeboundness, social network) in 2013, and the onset of dementia (outcome) between 2013 and 2016 were obtained. The Karlson–Holm–Breen mediation method was applied. A total of 35,744 participants were included (54.0% women). The mean age at baseline was 73.1 ± 5.5 y for men and 73.2 ± 5.5 y for women. A total of 1,776 participants (5.0%) had dementia during the follow-up period. There was a significant total effect of the number of teeth on the onset of dementia (hazard ratio, 1.14; 95% CI, 1.01–1.28). Controlling for nutritional and social mediators, the effect of the number of teeth was reduced to 1.10 (95% CI, 0.98–1.25), leaving an indirect effect of 1.03 (95% CI, 1.02–1.04). In the sex-stratified analysis, the proportion mediated by weight loss was 6.35% for men and 4.07% for women. The proportions mediated by vegetable and fruit intake and homeboundness were 4.44% and 4.83% for men and 8.45% and 0.93% for women, respectively. Furthermore, the proportion mediated by social networks was 13.79% for men and 4.00% for women. Tooth loss was associated with the onset of dementia. Nutritional and social factors partially mediated this association.

Reducing Your Risk of Alzheimer’s Dementia: Building a Better Brain as We Age

Alzheimer’ dementia is a large and growing public health problem. Of utmost importance for limiting the impact of the disease on society is the prevention of dementia, that is, delay onset either by years whereby death ensues prior to dementia onset. The Religious Orders Study and the Rush Memory and Aging Project are two harmonized cohort studies of aging and dementia that include organ donation at death. Ongoing since 1994 and 1997, respectively, we published on the association of numerous experiential, psychological, and medical risk factors for dementia, many of which are potentially modifiable. Here, selected findings are reviewed based on a presentation at the 2020 National Academy of Neuropsychology given virtually in Chicago in October of 2020.