Citations

Abstract Introduction Sleep-disordered breathing (SDB) is a potentially modifiable risk factor for the prevention of dementia, of which Alzheimer’s disease (AD) is the most common cause. However, there is a lack of longitudinal evidence relating SDB to AD pathology >20 years later. We examined the association between late-midlife SDB and late-life brain β-amyloid (Aβ) deposition—a hallmark of AD—assessed approximately 23 years later. Methods The Atherosclerosis Risk in Communities (ARIC) Study is an ongoing prospective cohort study initiated in 1987. Participants at two ARIC sites (Washington County, Maryland; Minneapolis, Minnesota) with primarily White participants also completed polysomnography (PSG) in the Sleep Heart Health Study (SHHS) in 1995-98. SDB measures included apnea-hypopnea index (AHI; number of apneas + hypopneas with ≥3% oxygen desaturation/hour of sleep), arousal index, and percentage of total sleep time in apnea, in hypopnea, and with oxygen saturation < 90%. A subset of participants completed florbetapir positron emission tomography (PET) scans through several ARIC ancillary studies (2011-2025 including the ARIC Sleep-PET study). We defined Aβ deposition as a global standardized uptake value ratio (SUVR) >1.2 (vs. SUVR ≤1.2). We used Poisson regression with robust standard errors to estimate relative risk (RR) of Aβ deposition by SDB, adjusting for demographics and vascular risk factors, and applied inverse probability attrition weighting to account for selective drop-out. Results Among 186 dementia-free participants (mean age=59 years at PSG and 82 years at PET scan, 58% female, 98% White), every 10% increase in total sleep time in hypopnea was associated with higher risk of Aβ deposition (RR=1.40, 95% confidence interval [CI]: 1.03, 1.91). When compared to no SDB (AHI < 5), moderate to severe SDB (AHI ≥15) was associated with elevated Aβ deposition (RR=2.36, 95% CI: 1.22, 4.57); mild SDB (AHI 5 to < 15) was not (RR=1.05, 95% CI: 0.53, 2.07). Conclusion SDB in late midlife was associated with greater risk of Aβ deposition approximately 23 years later. SDB may play a role in the early stages of AD pathogenesis. Future longitudinal studies are needed to optimize strategies for screening and treating SDB for dementia prevention. Support (if any) Supported in part by RF1AG050745.

Abstract INTRODUCTION Prospective studies of blood‐based biomarkers reflecting pathogenic processes, other than Alzheimer‐specific pathologies, that contribute to dementia in diverse cohorts are lacking. METHODS We jointly fitted linear mixed‐effect models and proportional hazards models to examine associations of midlife glial fibrillary acidic protein (GFAP), chitinase‐3‐like protein 1 (YKL‐40), soluble cluster of differentiation‐14 (sCD14), neurofilament light chain (NfL), total tau (t‐tau), and ubiquitin C‐terminal hydrolase L1 (UCHL1) levels in serum (collected in 1993 to 1995) with cognitive decline and incident dementia (ascertained over 29 years through 2022) in the community‐based Atherosclerosis Risk in Communities Study. sCD14 and YKL‐40 were measured in 3082 participants and the other four biomarkers in 1766 participants. RESULTS Higher serum GFAP, YKL‐40, sCD14, and NfL were associated with faster cognitive decline and elevated dementia rate (e.g., 1 standard deviation [SD] higher log‐base2 YKL‐40 was associated with −0.11SD faster 25‐year cognitive decline (95% confidence interval [CI]: −0.15,−0.07) and 45% higher dementia hazard (hazard ratio [HR]: 1.45 [95% CI: 1.25, 1.68]). Higher t‐tau and UCHL1 were also associated with faster cognitive decline. DISCUSSION Midlife blood biomarkers reflecting glial and neuronal dysfunction and neuroinflammation are associated with early cognitive impairment.

Introduction: Diabetes, a modifiable risk factor for dementia, is thought to impart increased risk of dementia through cerebral small vessel disease. While the importance of diabetes in midlife is well-documented, the influence of different glycemic levels, duration of diabetes, and Alzheimer’s disease genetic risk (apolipoprotein [ APOE ] ε4 genotype) in late-life on dementia risk remains uncertain. This could have implications for individualized prevention strategies. In this study, we investigated whether a higher glycemic level and longer duration of diabetes in late-life is associated with a higher risk of dementia, and whether associations vary by APOE ε4 genotype. Methods: We performed a prospective cohort analysis with the Atherosclerosis Risk in Communities Study using up to 11 years of follow-up (baseline, 2011-2013). We defined diabetes as glycated hemoglobin A1c (HbA 1c ) ≥6.5%, self-reported physician diagnosis, or use of any diabetes medication. Among those with diabetes, we categorized participants as having a lower glycemic level (HbA 1c <7%) or higher level (HbA 1c ≥7%), and duration as short (<5 years) or long (≥5 years). We estimated hazard ratios (HR) for incident dementia by HbA 1c levels and by diabetes duration in separate multivariable-adjusted Cox regression models. We tested for statistical multiplicative interaction on the relative risk of dementia by fitting interaction terms between diabetes measures and APOE ε4 genotype in separate regression models. Results: In 5030 participants without dementia (mean age, 75.4 years; 58.6% female; 21% Black; 28% with diabetes), there were 1167 (23.2%) incident dementia cases over a median follow-up of 9.0 years. Compared to no diabetes, a lower glycemic level and higher level were both associated with elevated dementia risk ( P -trend <.0001; Table). A higher glycemic level was associated with an elevated risk of dementia relative to a lower level (HR=1.47 [95% CI: 1.22-1.77]; Table). Compared to no diabetes, both shorter duration and longer duration were associated with an increase in dementia risk ( P -trend <.0001; Table). Longer duration was associated with an increased risk of dementia relative to shorter duration (HR=1.57 [95% CI: 1.24-1.98]; Table). Associations for glycemic level and diabetes duration did not significantly differ by APOE ε4 genotype (all P >.05). Conclusions: Diabetes management in older adults that includes lower glycemic goals may help reduce dementia risk.

Objective We investigated potential racial disparities in the effects of audiometric hearing loss and its treatment on dementia and mortality among 3,602 older adults aged 68–89 years, 22% of whom were self-identified Black race. Methods Adjudicated all-cause dementia was determined using neurocognitive test data, proxy reports, and surveillance of hospital records and death certificates. Audiometric hearing loss, defined as the better-ear averaged pure-tone threshold (0.5–4 kHz), was categorized using clinical cutpoints. Multivariable-adjusted Cox proportional hazards models included hearing loss–race interaction terms. Results Dementia risk associated with moderate-to-severe hearing loss did not differ by race [Black participants: hazard ratio (HR): 1.66; 95% confidence interval (CI): 1.05, 2.61; White participants: HR: 1.71; 95% CI: 1.16, 2.51; P -interaction = 0.92]. However, moderate-to-severe hearing loss was associated with a 2.3-fold increase in mortality among Black participants only (95% CI: 1.17, 4.60). Conclusions Our findings emphasize the importance of including minoritized populations in hearing treatment research to build an evidence base for policy development and clinical decision-making. Hearing loss affects the health of both Black and White Americans. Racial disparities in hearing healthcare should be addressed to advance health equity for all older adults.

BACKGROUND: Cerebral microbleeds (CMBs) are associated with dementia, but the impact of specific microbleed patterns (with distinct pathophysiologies) is unclear. Lobar CMBs commonly result from cerebral amyloid angiopathy (sometimes with cortical superficial siderosis [cSS]), while subcortical microbleeds indicate a hypertensive cause. This study investigates the association of CMB presence, patterns, and frequency with dementia risk. METHODS: Participants from the ARIC-NCS (Atherosclerosis Risk in Communities-Neurocognitive Study), a community-based longitudinal cohort, with a 3T research magnetic resonance imaging scan at visit 5 (2011–2013) and without prior intracerebral hemorrhage or dementia were included. CMB and cSS presence and location were evaluated using a T2* gradient-recalled echo sequence. Each individual’s pattern of CMBs was classified as no CMBs, subcortical only, mixed (subcortical and lobar±cSS), lobar±cSS only, or cSS. Dementia adjudication was determined by blinded review of cognitive testing, informant interviews, and hospital discharge codes or death certificates (from follow-up visits and ongoing surveillance). Cox proportional hazards models assessed associations between CMBs and incident dementia through 2020, adjusted for demographics, vascular risk factors, and white matter hyperintensities. RESULTS: Among 1583 participants (mean age, 76 years; 24.7% cumulative dementia incidence over a median of 23.6 follow-up years), 361 had CMBs. Compared with individuals without CMBs, those with mixed (hazard ratio, 1.99 [95% CI, 1.40–2.83]) or lobar±cSS (hazard ratio, 1.96 [95% CI, 1.30–2.97]) CMB patterns had increased dementia risk, whereas individuals with a subcortical-only pattern did not (hazard ratio, 1.04 [95% CI, 0.78–1.39]). cSS presence (n=21; versus absence) showed an increased risk of dementia (hazard ratio, 2.57 [95% CI, 1.36–4.89]). Greater numbers of microbleeds across all CMB subtypes exhibited an increased risk of dementia. CONCLUSIONS: Lobar and mixed CMB patterns and increasing numbers of CMBs are associated with incident dementia. Certain CMB patterns have differential associations with dementia, but severe enough disease burden, regardless of CMB distribution, is associated with increased dementia risk.

Abstract INTRODUCTION Understanding comorbidities’ combined impacts on dementia risk may offer a more comprehensive understanding of individuals’ risk. Using machine‐learning, we grouped individuals with similar midlife risk profiles into clusters and explored associations with dementia risk. METHODS Participants without dementia at baseline (1987–1989) from the prospective Atherosclerosis Risk in Communities (ARIC) study were included (ages 45–64 years; N = 15,250). Using unsupervised hierarchical cluster analysis, nine clusters were created and defined based on 14 midlife morbidities. The associations with incident dementia ( N = 3272 cases, median follow‐up 25 years) and deaths ( N = 9099) were evaluated using time‐to‐event regression models. RESULTS Compared with the healthiest cluster (Cluster 1), Clusters 2 (smoking) (hazard ratio [HR](95% confidence interval [CI]) = 1.62 (1.08, 2.43)), 5 (obesity, diabetes, hypertension, and hypertriglyceridemia) (HR(95%CI) = 1.91 (1.35,2.70)), and 7/8 (atrial fibrillation/heart failure) (HR(95%CI) = 2.69 (1.59,4.57)) were associated with dementia. Accounting for competing risk of death in the Fine‐Gray subdistribution model negated the cluster‐dementia association. DISCUSSION Midlife morbidity clusters are important for dementia and mortality risk.

Introduction: Plasma biomarkers of Alzheimer’s disease (AD), including amyloid-β (Aβ42/Aβ40), phosphorylated tau (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) have shown strong reliability in predicting dementia risk. White matter hyperintensities (WMH) represent a major vascular contributor to dementia. We investigated how plasma biomarkers of AD interact with WMH on MRI to influence incident dementia risk. Methods: We included dementia-free participants from the Atherosclerosis Risk in Communities (ARIC) Study who underwent MRI and plasma biomarker assessment at Visit 5 (2011–2013). WMH was quantified and considered continuously (log-transformed and standardized), and in tertiles. Plasma biomarkers were log-base-2-transformed. Cox proportional hazards models were used to estimate dementia risk over 10 years associated with plasma biomarkers and WMH, independently and multiplicatively. Models were adjusted for demographic variables (age, sex, race, and education), vascular risk factors (hypertension, diabetes, smoking status, body mass index, and estimated glomerular filtration rate), and APOE ε4 status. Results: Among 1,538 participants (aged 67- 90 years, 29% Black), 30% ( N = 462) developed dementia over the 10-year follow-up period. For every doubling of plasma Aβ42/Aβ40 , indicating lower amyloid burden, dementia risk decreased, while doubling of p-tau 181 , NfL, and GFAP were each associated with increased dementia risk, in separate models; each of these associations was independent of WMH (Table 1). Additionally, dementia risk increased per SD increase in WMH, independent of each plasma biomarker. Although no multiplicative interaction terms reached statistical significance (p<0.05), there was suggestive evidence that Aβ42/Aβ40 and GFAP have smaller effect sizes on dementia risk in subgroups at the highest WMH tertile (p-interactions<0.10; see Table 2). Discussion: Plasma biomarkers and WMH independently predict dementia risk over 10 years, though there remained limited evidence of multiplicative effects. Plasma biomarkers may be less important for dementia risk in individuals who also have extensive WMH. These findings emphasize the importance of incorporating both AD-specific plasma markers as well as indicators of cerebral small vessel disease, such as WMH, into dementia risk profiling.