Paola Gilsanz

Background and ObjectivesAPOE ɛ4 is the strongest genetic risk factor for late-onset Alzheimer disease, while ɛ2 is associated with decreased risk. However, it is unclear how these genotypes relate...

Structured INTRODUCTION: Cognitive syndrome diagnosis (Normal, Mild Cognitive Impairment (MCI), Dementia) is important for summarizing disease status and predicting future progression. Machine learning approaches to classification might substitute for or complement clinical diagnosis but must be shown to have validity for these purposes. METHODS: A machine learning algorithm was trained in a previous study to reproduce clinical diagnosis of cognitive impairment [1]. We examined and compared concurrent validity (cross-sectional MRI measures of brain integrity) and predictive validity (longitudinal change in MRI measures of brain integrity and progression to a more impaired diagnosis/classification) of clinical diagnosis and algorithmic classification from the prior study. RESULTS: Clinical diagnosis and algorithmic classifications had robust associations with clinical and MRI outcomes and differences across diagnosis/classification types were minor. Algorithmically estimated probability of a Normal diagnosis had the strongest associations with cross-sectional and longitudinal MRI outcomes. Progression from Normal to MCI or Dementia was faster for Clinical diagnosis than Algorithmic classification but future rates of MRI measured brain degeneration were essentially the same in individuals with baseline clinical diagnosis and algorithmic classification of Normal cognition. DISCUSSION: Clinical diagnosis and algorithmic, machine learning based classification had robust and similar associations with independent validity criteria. Both forms of diagnosis/classification had utility for staging current brain degeneration and predicting future brain degeneration and clinical decline. This study demonstrates a validation design that can simultaneously evaluate the utility of both clinical diagnosis and algorithmic classification of cognitive impairment in a manner that improves understanding of both types of classification.

Introduction: Hypertension is a modifiable risk factor for dementia, but its contribution among Asian American ethnic groups remains understudied despite heterogeneity in cardiovascular risk factors. Methods: Participants were Kaiser Permanente Northern California members aged 60 to 90 years without prevalent dementia at baseline, surveyed between 2002 and 2009 [Chinese (n=4,848), Filipino (n=4,130), Japanese (n=2,786), South Asian (n=823), non-Latino White (n=123,593)]. We used ICD-codes to identify hypertension (assessed 5 y before baseline) and incident dementia through 2020. Within strata of race/ethnicity and baseline age group (60 to 75 and 75 to 90 y), we estimated adjusted and standardized 10-year dementia risk, risk ratios, risk differences, and population attributable fractions (PAFs) using pooled logistic regression, treating death as a censoring event. Results: Among Chinese, Filipino, Japanese, and non-Latino White participants aged 60 to 75 years, PAFs (95% CI) were 12% (−3% to 28%), 23% (4% to 40%), 9% (−7% to 27%), and 8% (5% to 10%), respectively. Effect estimates were null for these groups among participants aged 75 to 90. For South Asian participants, point estimates were consistent with protective associations among those aged 60 to 75 and harmful associations among those aged 75 to 90, although estimates were imprecise. Conclusion: Our findings suggest heterogeneity in the effect of hypertension on dementia risk across Asian American ethnic groups and by age.

Background: Depression has been associated with magnetic resonance imaging (MRI) measures of larger white matter hyperintensity (WMH) volumes and smaller cerebral grey matter volumes (GMV) in predominantly White samples. Recent findings suggest that some race/ethnicity groups may experience more severe health consequences due to depression when it is present compared with experience of depression in White samples. We investigated the association of depressive symptoms with WMH and GMV by race/ethnicity, using a continuous measure of depressive symptoms to more expansively capture participants’ experience of depression versus clinical diagnosis alone. Methods: A diverse sample of older, northern California Kaiser Healthy Aging and Diverse Life Experiences and Study of Healthy Aging in African Americans participants (n = 550) underwent MRI neuroimaging 2017-2022. Baseline depressive symptoms were measured in 2017 using the NIH PROMIS toolbox. We conducted a literature-informed Bayesian analysis, stratified by race/ethnicity, to examine the association between baseline depressive symptoms and post-baseline WMH and GMV. Results: Our sample was 14% Asian, 54% Black, 16% Latino, and 17% White. Overall, we did not observe an association between depressive symptoms and log(WMH) (0.06, 95% Credible Interval [CrI]: -0.09,0.22) or GMV (-0.74, 95% CrI: -1.62,0.16). In stratified analyses, 1 SD higher depressive symptoms were associated with larger log(WMH) volume (0.21, 95%CrI: 0.002,0.42) among Black participants and smaller GMV among Latino participants (-2.92, 95% CrI: -4.31,-1.52). Unexpectedly, depressive symptoms were associated with larger GMV in Asian participants (2.41, 95% CrI: 0.87,3.95). Discussion: More severe depressive symptoms were associated with MRI markers of brain aging among Black and Latino participants.

Objectives: Lifecourse socioeconomic conditions are important determinants of age-related cognitive decline and dementia. We extend this research by examining whether these associations hold for subjective cognitive decline (SCD), an early marker that may reflect dementia risk across socioeconomic contexts. Methods: In two multi-ethnic older-adult cohorts of long-term Kaiser Permanente Northern California members without prior dementia, we constructed dichotomous measures of financial, social, and cultural capital in childhood and late-life. SCD was measured using the psychometrically validated Everyday Cognition 12-item scale (ECog-12). Generalized linear models estimated associations of each lifecourse SES measure with SCD in the entire sample and stratified by sex/gender and race/ethnicity. Causal mediation analyses explored whether depressive symptoms (PROMIS Depression) mediated findings. All models adjusted for age and moderation models adjusted for sex/gender or race/ethnicity. Results: Low childhood (b = 0.098,95% CI: 0.056,0.140) and late-life (b = 0.080,95% CI: 0.051,0.110) financial capital, low childhood (b = 0.054,95% CI: 0.023,0.085) and late-life social capital (b = 0.062,95% CI: 0.018,0.107), and low late-life (b = 0.068,95% CI: 0.030,0.106) cultural capital were each independently associated with greater SCD. Low late-life cultural capital had the strongest negative impact among Black participants (b = 0.143,95% CI: 0.085,0.202). Depressive symptoms partially mediated associations of childhood and late-life financial and social capital with SCD, accounting for approximately 34-64% of the associations. Discussion: Multiple aspects of lifecourse SES contribute to SCD, with variation by sex/gender and race/ethnicity in lifecourse cultural capital. Depression may be a key pathway linking lifecourse SES disadvantage to SCD.

Background: Social isolation is a key social determinant of health, yet research on its relationship with functional impairment is limited. We compared functional impairment score trajectories of older adults who experienced social isolation versus those who did not, using 2 different statistical approaches to handle attrition due to dropout and death. Methods: Data were from 2 Northern California observational cohorts of people aged 50+ (n = 2476): Kaiser Healthy Aging and Different Life Experiences (KHANDLE) and Study of Healthy Aging in African Americans (STAR). We fit linear mixed effects models for functional impairment scores (sum of 12 items measuring basic activities of daily living [ADLs], instrumental ADLs, and mobility; range: 0-36) by baseline social isolation status (yes/no; 3-5 positive answers on 5 social contact items), adjusted for age and sex/gender. We estimated average marginal wave-specific differences in functional impairment scores, comparing approaches to address attrition. Results: At baseline, 30% of participants reported social isolation; the median functional impairment score was 2 (Q1, Q3 = 0, 5). Baseline functional impairment scores were 1.03 points (95% CI, 0.84-1.20) higher among participants experiencing social isolation versus not. At wave 4, this difference decreased to 0.80 (95% CI, 0.52-1.07) among those remaining in the study and increased to 1.16 (95% CI, 0.83-1.42) assuming attrition was eliminated. Dropout and death were higher among participants experiencing social isolation. Conclusion: In a diverse cohort of older adults, those experiencing social isolation tend to experience greater functional impairment, but differences in trajectories depend on how attrition is handled.

Latinx individuals’ educational experiences in the United States were shaped by structural and interpersonal discrimination, potentially contributing to disparities in dementia and related risk factors. Racial and ethnic school composition reflects resources and co-ethnic belonging. We used Health and Retirement Study data from 315 Latinx adults aged ≥50 years who reported their school racial/ethnic composition through 12th grade. We estimated associations between each composition type (1-year unit) and memory scores (0-20), depressive symptoms (0-8), and poor self-rated health (SRH; yes/no), adjusting for sociodemographic factors. Greater duration in schools serving majority Latinx students was not associated with memory (β = -0.01 [-0.09, 0.07]) or depressive symptoms (β = -0.03 [-0.09, 0.04]) but was associated with higher risk for poor SRH (RR = 1.05 [1.01, 1.08]). Greater duration in schools serving majority Black students was associated with lower memory (β = -0.16 [-0.31, -0.01]), more depressive symptoms (β = 0.18 [0.07, 0.29]), and higher risk for poor SRH (RR = 1.06 [1.00, 1.11]). Greater duration in schools serving majority White students was associated with higher memory scores (β = 0.09 [0.01, 0.16]), lower depressive symptoms (β = -0.05 [-0.11, 0.00]), and decreased risk for poor SRH (RR = 0.91 [0.87, 0.96]). Among Latinx adults, the impact of school composition varied by whether schools served other marginalized populations, reflecting countervailing influences. This article is part of a Special Collection on Latino Health.

Objectives: Cognitively, physically, and socially active lifestyles are important factors of healthy aging. Our objective is to leverage novel machine learning techniques in an ethnoracially diverse population to yield powerful, explainable models of modifiable lifestyle factors contributing to memory in older adults. Methods: Cross-sectional episodic memory was the outcome in the gradient-boosted tree models and SHAP (SHapley Additive exPlanations). Participants in the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) and the Study of Healthy Aging African Americans (STAR) made up the cohort (n = 2,245). Inputs included income, sex, age, education, ethnoracial groups, and 25 modifiable lifestyle factors, which were grouped into a triad of categories: leisure time activities (LTAs), physical metrics, and socialization. SHAP values indicated global feature importance and individual variability. Global importance, aggregated in each triad category, was leveraged for comparison of relative contributions to memory. Results: The global feature importance for predicting episodic memory over each of the triad categories was as follows: LTAs (0.225), physical metrics (0.169), and socialization (0.104). Each category outweighed income (0.042), ethnoracial groups (0.070), and education (0.093). LTAs had a greater importance value than sex (0.224) and age (0.203) for predicting episodic memory. Explanatory analysis depicted varying importance rankings on an individual basis. Discussion: The results confirm the importance of lifestyle variables and highlight the relative contributions of the triad categories to episodic memory in aging. This suggests that these categories may equal or surpass the importance of factors like sex, age, ethnoracial groups, and education, which are known to affect memory.

Previous research of associations between statins and Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) has been limited by short follow-up, small samples, and confounding. We aimed to estimate the association between the 1st statin prescription and incident AD/ADRD among members of a large population-based cohort of older adults. We used a cohort study design emulating a target trial using data from Kaiser Permanente Northern California (KPNC), an integrated health care delivery system. Participants were born before 1951 and KPNC members for 4+ years during 1997-2010. Embedded subsamples included sociodemographic and genetic data. Statin initiators were matched at first prescription ("baseline") with up to 5 "noninitiators" based on age and low-density lipoprotein cholesterol (LDL-C). Participants with extreme propensity scores were excluded. The outcome was time to incident AD/ADRD diagnosis, censoring, or the administrative end of study (December 31, 2020). Cox proportional hazard models were used to estimate hazard ratios for statin initiation on AD/ADRD incidence. Follow-up time was divided at the first year of follow-up to account for increased AD/ADRD detection in the first year due to increased interaction with the health care system after a statin prescription. Among eligible participants (n = 705,061), 264,294 individuals (37.5% of eligible participants) initiated any statin during 2001-2010 ("initiators"), of whom 249,613 (94.4%) were matched with 255,937 unique noninitiators to create the analytic sample (322,358 unique participants; mean age at baseline = 67.4 years; 55.1% female). The average follow-up was 11.8 years. In the first year after initiating statins, AD/ADRD diagnoses were elevated by 46% (hazard ratio [HR] = 1.46, 95% CI 1.42-1.53) compared with noninitiators. After 1 year, statin initiators experienced no difference in AD/ADRD incidence (full sample: HR = 1.00, 95% CI 0.99-1.01; subsample with survey covariates: HR = 1.01, 95% CI 0.98-1.06; subsample with survey and genetic covariates: HR = 0.97, 95% CI 0.91-1.07). Adjustment for sociodemographic covariates and apolipoprotein E e4 allele count did not materially change the findings. In this large emulated target trial, statin initiation was inconsistent with more than a 3% increase or decrease in the hazard of AD/ADRD after the first year of follow-up. This intent-to-treat analysis does not directly quantify effects of long-term exposure to statins. Associations in the first year likely reflect increased medical observation immediately after statin initiation. This emulated trial provides Class II evidence that statin initiation is not associated with AD/ADRD or AD incidence after the first year of follow-up.