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Abstract Mobility and cognition impairments are common in older adults, but neurodegenerative pathology contributions are unclear. We examined cross-temporal associations of Alzheimer’s Disease (AD)-specific and nonspecific neurodegenerative plasma biomarkers neurofilament light (NfL) with incident mobility and cognitive impairment in the Atherosclerosis Risk in Communities (ARIC) study. We hypothesized NfL would show stronger associations with mobility impairment than p-tau181 in a subset of 1,227 cognitively normal participants with biomarker data and no mobility impairment (mean age=75.5±5.0, 56% female, 23% Black) at visit 5 (2011-13). Participants were classified into five functional groups using data from up to four exams: no impairment (n = 587; referent), mobility impairment only (n = 266; gait speed< 0.8m/s), cognitive impairment only (n = 69; adjudicated dementia), dual impairment (n = 243; both) or decline-free death (n = 262) over a mean 6.3 years (0-11 years) of follow-up. A multinomial regression model estimated association of functional groups with p-tau-181 and NfL jointly, adjusted for cardiovascular and demographic factors, BMI, and kidney function. Relative prevalence ratios (RPR; 95% CI) are presented per one-unit higher log-base-2 transformed biomarker (doubling). For mobility and cognitive functional outcomes, p-tau-181 was more robustly supported [Mobility: RPR=1.36, (1.04,1.77); Cognitive: RPR=1.73, (1.10,2.70); Dual: RPR=1.78, (1.15,2.77)] than NfL [Mobility: RPR=1.14, (0.85,1.53); Cognitive: RPR=1.20, (0.70,2.05); Dual: RPR=1.65, (0.86,3.16)]; higher pTau-181 [RPR=1.60, (1.23,2.09)] and higher NfL [RPR=1.94, (1.39,2.71)] were associated with higher risk of decline-free death. A p-tau-181-x-NfL interaction term was not supported. Findings did not support NfL associations with functional outcomes with consideration of p-tau-181. AD blood biomarkers may help identify individuals at greater risk for multifaceted disability.

Abstract Blood-based biomarkers show promise as a noninvasive method for measuring Alzheimer’s disease pathology and neurodegeneration throughout the lifecourse. However, the relationship between longitudinal changes in these biomarkers and late-life brain morphology in community-dwelling populations requires further investigation. Between 2011 and 2013, 1,977 participants from the Atherosclerosis Risk in Communities Study received underwent 3 Tesla magnetic resonance imaging scans. Whole-brain cortical thickness was quantified by Freesurfer. Stored plasma samples collected in midlife (1993-95, mean age 59.0 years) and late-life (2011-13, mean age 76.8 years) from a subsample of 1,515 participants (60.7% female, 25.5% Black adults) were assayed in 2022 using Quanterix SiMoA. The assay quantified amyloid-β (Aβ)42/40, phosphorylated tau at threonine 181 (p-Tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Linear regression models estimated the association of blood-based biomarkers from midlife, late-life, and the change from midlife to late-life with cortical thickness in late-life. In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, higher midlife measures of p-Tau181 and increases from midlife to late-life in NfL and GFAP were associated with lower cortical thickness in late-life. Concurrent measures of p-Tau181, NfL, and GFAP were associated with lower cortical thickness in late-life and exhibited a stronger association among participants ≥75 years old compared to participants <75 years old. Additional longitudinal research is needed to determine whether blood-based biomarkers predict cortical thinning over time and may serve as an early indicator of accelerated brain atrophy.

Abstract Background Prospective investigations on blood biomarkers for Alzheimer's disease and related‐dementias (ADRDs) and cognitive impairment provide important insights into their clinical utility in early disease diagnosis and risk stratification, but have been primarily limited to AD pathologies (e.g. amyloid‐beta and hyperphosphorylated‐tau aggregation). Studies of biomarkers reflecting other pathogenic processes that contribute to ADRDs, especially in community‐based cohorts, are lacking. We examined associations of blood biomarkers reflecting glial and neuronal dysfunction and neuroinflammation, including soluble cluster of differentiation‐14 (sCD14), chitinase‐3‐like protein‐1 (YKL‐40), glial‐fibrillary acidic protein (GFAP), neurofilament‐light chain (NfL), total‐Tau, and Ubiquitin C‐terminal hydrolase L1 (UCH‐L1) with cognitive decline and incident dementia in ARIC study participants. Methods Blood biomarkers were measured in 1,864 ARIC Visit 3 (1993‐1995) participants using the Meso Scale Discovery assay (YKL‐40), the Quanterix Simoa Neurology 4‐Plex assay (total‐Tau, NfL, GFAP, UCH‐L1), and a commercial ELISA assay (sCD14, R&D Systems); global cognition z‐scores were derived from three cognitive tests (measuring memory, language, and executive function) administered up to six times over 25 years, and incident dementia cases were ascertained via in‐person cognitive assessments (expert‐adjudicated), informant‐based interviews, and hospitalization and death records through 2018. We used shared parameter models to simultaneously fit linear mixed‐effect models and proportional hazard models to estimate 25‐year cognitive decline and dementia rates separately for each biomarker (log‐base2‐transformed), adjusting for covariates (Table). Results Among 1,864 participants (mean±SD age:63±4.5 years, 60% female, 49% self‐reported Black), 27% developed dementia. Higher levels of each biomarker were associated with faster cognitive decline. All but UCH‐L1 were associated with elevated dementia risk (Table). For example, one standard deviation (SD) higher log‐base2 YKL‐40 was associated with ‐0.10 SD steeper 25‐year cognitive decline (95%CI:‐0.15,‐0.04) and 59% higher dementia hazard (hazard ratio (HR):1.59 (95%CI:1.20,2.10); likewise, sCD14 was associated with an additional cognitive decline of ‐0.06 (95%CI:‐0.11,‐0.01) and 38% higher dementia hazard (HR:1.38 (95%CI:1.08,1.76)). Conclusions Blood biomarkers reflecting neuropathological processes, including microglial activation, astrocytic reactivity, and neuronal degeneration, were associated with faster cognitive decline and increased dementia risk, suggesting that they may aid in risk stratification and intervention strategies for ADRDs. Future analyses will examine whether these associations differ by race and APOE‐ε4 s tatus.

Abstract Background Even among cognitively unimpaired (CU) older adults, specific patterns of neuropsychological performance impart differential risk for progression to Alzheimer's disease and related dementias (ADRD). Early identification in the prodromal phase may inform early intervention efforts. We used a data‐driven approach to classify neuropsychological phenotypes within CU older adults from the Atherosclerosis Risk in Communities (ARIC) study and tested for differences in ADRD and cerebrovascular outcomes. Method Participants included 4737 CU (via a previously published algorithm plus consensus diagnosis protocol) older adults (mean age=75.1 years, 60.8% female, 23.1% Black) with neuropsychological data from Visit 5 (2011‐2013) of the ARIC study. Latent profile analysis was leveraged to identify unique cognitive phenotypes using 10 demographically adjusted (age, sex/gender, education, race‐center, WRAT Reading) neuropsychological z‐scores. Cognitive phenotypes were then compared on demographics, depressive symptoms, and vascular risk factors (VRFs). In a subset with available neuroimaging and biofluid data ( n range=1102‐1678), white matter hyperintensity (WMH) and bilateral hippocampal (HV) volumes normalized for intracranial volume and plasma biomarkers (i.e., Aβ42/40, ptau181, NfL, and GFAP) were examined by phenotype. Phenotype comparisons adjusted for demographic variables, VRFs, and an indicator of kidney function (i.e., eGFR‐creatinine) for plasma biomarkers. We applied Tukey adjustment for pairwise comparisons. Result A 6‐class solution of cognitive phenotypes emerged as the best fitting model: Average Overall (28%), Low Overall/Very Low Memory (7%), Average Overall/Super Memory (11%), Subtle Low Overall/Low Executive (22%), Subtle Low Executive/High Memory (13%), and Average Overall/Low Memory (19%; Figure 1). Phenotypes differed on education, race, and word reading, despite prior adjustments for these variables when creating the neuropsychological z‐scores (Table 1). Additionally, phenotypes differed on depressive symptoms, VRFs, WMH, HV, Aβ42/40, and ptau181 (all p s < .05). The Subtle Low Overall/Low Executive group had the highest WMH volumes, the Subtle Low Executive/High Memory group had the lowest Aβ42/40, and the Low Overall/Very Low Memory group had the lowest HV and highest levels of plasma ptau181 (Table 2). Conclusion Cognitive heterogeneity is observed even among CU older adults, with lower executive performance associated with cerebrovascular changes and lower memory associated with certain AD‐related changes, possibly indicating risk for cognitive progression through distinct pathways.

Abstract Background The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) randomized trial ( n = 977;ClinicalTrials.gov:NCT03243422) demonstrated that hearing intervention slowed 3‐year cognitive decline by 48% among a subgroup of participants. To further investigate differences by treatment with respect to cognitive benefit, we tested the hypothesis that hearing intervention is associated with improved neurodegeneration blood biomarkers 3‐years post‐randomization and assessed whether combining biomarkers and cognitive results improved power in the trial design. Method The ACHIEVE study is a multicenter, parallel‐arm, randomized trial (hearing intervention vs health education control) on 3‐year cognitive decline among adults 70–84years with untreated hearing loss and without substantial cognitive impairment. Participants were recruited from two populations: (1) a long‐standing cardiovascular health observational study (Atherosclerosis Risk in Communities [ARIC]), and (2) de novo community volunteers. Plasma was collected in year 3 in a subsample ( n = 540) while ARIC participants ( n = 164) also had baseline plasma. Glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) neurodegenerative biomarkers were derived using the Alamar CNS protein panel. Regression models estimated the association of treatment with 3‐year biomarkers and global cognitive differences in the combined sample and by recruitment source and annualized change from baseline in the ARIC sample. We included a simple composite score of the standardized outcomes (Table 2). Result Among the subsample, baseline characteristics were balanced by treatment. There were no significant differences on 3‐year neurodegeneration biomarker levels by treatment in the combined (Table 1) or de novo groups (Table 2). Among ARIC participants, intervention resulted in lower 3‐year GFAP (mean:‐0.415;95%CI:‐0.712,‐0.118) and NfL (mean:‐0.349;95%CI:‐0.652,‐0.046) (Table 2). Annualized change from baseline analyses among ARIC participants (Table 3) revealed intervention was associated with a slower rate of cognitive decline (difference‐in‐means:0.059;95%CI:0.018,0.100) and a slower rate of increase in GFAP (difference‐in‐means: ‐0.060;95%CI:‐0.112,‐0.009). Differences in estimates suggest combined score, relative to cognition alone, may increase power in clinical trials that show a positive effect (ARIC subgroup: p = 0.02vs. 0.08[Table 2] and p = 0.0009vs.0.048[Table 3]). Conclusion Hearing intervention was associated with positive 3‐year effects on neurodegeneration blood biomarkers in ARIC participants which parallels cognitive decline results. Results provides objective evidence of brain changes following hearing intervention and potential signal of a more powerful combined outcome approach for future brain health clinical trials.

Abstract The Atherosclerosis Risk in Communities (ARIC) study started in 1987‐1989 (visit 1), when participants from four U.S. communities were 45‐64yo. Participants have been seen at up to 10 additional in‐person visits with annual/semi‐annual telephone calls to ascertain clinical events, hospitalizations, and other health outcomes. In 2011‐2013, at ARIC visit 5, the ARIC Neurocognitive Study (ARIC‐NCS) was initiated for surviving participants, incorporating neuropsychological assessments at multiple in‐person visits and informant interviews to support cognitive adjudication. A subset of participants have undergone brain MRI with measurement of brain volumes, cortical thickness, arterial disease and vascular lesions, with a smaller subset having brain florbetapir PET. Blood‐based Alzheimer's disease (AD) biomarkers are available at multiple visits along with extensive measurement of vascular risk factors, vascular markers, and ‐omic (e.g.genomic and proteomic) data. This presentation will focus on the available data in ARIC, the methods underlying its collection and subsequent analysis, and some of the primary contributions of this study to the field. With 37 years of follow‐up, a great strength of ARIC is the ability to evaluate risk factors in midlife; ARIC studies have supported an association of midlife hypertension, diabetes, physical inactivity, and other vascular risk factors with reduced dementia risk, even among those with increased genetic risk for dementia. ARIC studies have demonstrated associations between stroke and dementia, and have linked vascular risk factors with blood‐based and imaging biomarkers of AD‐related dementias. ARIC has demonstrated the importance of hearing loss in dementia risk, and a subset of ARIC participants were recruited into (and were those who most benefited from the intervention of) the ACHIEVE study of hearing aid use for reduction of dementia. Proteomic studies have identified markers of dementia risk when evaluated in midlife. Recently, ARIC data informed updated estimates on lifetime risk of dementia, where it was estimated that among individuals surviving beyond age 55, 42% would develop dementia over their lifetime through age 95. ARIC studies continue to focus on risk factors for dementia, particularly now in the oldest old, and on contributors to cognitive reserve and resilience. ARIC follows a model of data sharing and broad collaboration.

Abstract There is an urgent need to improve dementia ascertainment robustness in real-world studies assessing drug effects on dementia risk. We developed algorithms to dementia identification algorithms using Medicare claims (inpatient/outpatient/prescription) from 3318 Visit 5 (2011-2013) and 1828 Visit 6 (2016-2017) participants of the Atherosclerosis Risk in Communities (ARIC) Study, validated against ARIC's rigorous syndromic dementia classification. Algorithm performance was compared to existing algorithms (Jain, Bynum, Lee). We further evaluated algorithms effectiveness in a 20% random Medicare sample aged ≥70 years who initiating liraglutide or dipeptidyl peptidase 4 inhibitors (DPP4i) to assess 3-year adjusted risk difference (aRD) for dementia. Our incident dementia algorithm required two dementia diagnostic codes within 1-year, or one dementia code plus a new dementia prescription within 90 days. It achieved a positive predictive value (PPV) of 69.2%, specificity of 99.0%, and sensitivity of 34.6% (population prevalence: 8.8%), comparable to extant algorithms (PPV, 58.7–68.6%; sensitivity 25.5–40.4%). Prevalent dementia algorithm (without requiring incident diagnoses/prescriptions) demonstrated similar performance. In the Medicare sample, dementia risk ranged from 3.0% to 12.5%, aRD comparing liraglutide to DPP4i varied −1.2% to −3.6%, with our algorithm closely matching the Bynum algorithm. Algorithm selection significantly impacts treatment effect estimates, highlighting its importance in in pharmacoepidemiologic research.

Importance SARS-CoV-2 infection has been linked to neurotoxic effects and cognitive deficits. Objective To determine whether decreases in cognitive function were accelerated after SARS-CoV-2 infection compared with individuals not infected. Design, Setting, and Participants Multicenter, prospective cohort study from 2016 to 2022 among 3525 participants alive on March 1, 2020, and enrolled in The Atherosclerosis Risk in Communities (ARIC) study and the Collaborative Cohort of Cohorts for COVID-19 Research study who completed a prepandemic cognitive assessment and a pandemic-era assessment of SARS-CoV-2 infection. Final analyses performed in November 2024. Exposure SARS-CoV-2 infection determined via self-report of a positive SARS-CoV-2 test or health care professional diagnosis of COVID-19, a positive SARS-CoV-2 antinucleocapsid antibody response, or presence of an administrative code for COVID-19 on medical records. Main outcomes and measures A neuropsychological battery assessed multiple cognitive domains, and a cocalibrated confirmatory factor analysis generated factor scores for global cognitive function. The primary outcome was the rate of excess change in cognitive function. Results The 3525 eligible participants had a mean (SD) age of 80.8 (4.7) years, 2085 (59.1%) were female, 752 (21.4%) were Black, and 2773 (78.6%) were White. SARS-CoV-2 infection was detected among 307 participants (8.7%), 103 of whom (33.6%) were hospitalized. Among uninfected participants, the mean annualized change in cognitive function was −0.09 (95% CI, −0.13 to −0.04). Compared with this rate, change was faster (β = −0.06; 95% CI, −0.09 to −0.02) among participants hospitalized for infection, but not different from participants who were infected but not hospitalized (β = 0.00; 95% CI, −0.02 to 0.03). The association among participants hospitalized for infection was evident in the cognitive domains of memory and executive function, but not language. Conclusions and relevance This cohort study of older participants found accelerated decreases in cognition among individuals hospitalized for SARS-CoV-2 infection, but not nonhospitalized infection, in comparison with individuals not yet infected.

ImportanceMidlife vascular risk factors are associated with an elevated risk of dementia. However, the total contribution of vascular risk factors in midlife and late life with incident dementia is uncertain.ObjectiveTo quantify the proportion of incident dementia attributable to modifiable vascular risk factors measured in midlife and late life and to examine differences by apolipoprotein ε4 genotype, self-reported race, and sex.Design, Setting, and ParticipantsThis was a prospective cohort analysis of the Atherosclerosis Risk in Communities (ARIC) study using 33 years of follow-up (1987-2020). The setting included ARIC field centers (Jackson, Mississippi; Forsyth County, North Carolina; Minneapolis suburbs, Minnesota; Washington County, Maryland). Study baseline in Black and White participants with complete exposure and covariate data was set by age at risk factor measurement (45-54 years, 55-64 years, and 65-74 years). Data were analyzed from August 2023 to December 2024.ExposuresHypertension (systolic blood pressure [BP] ≥130 mm Hg, diastolic BP ≥80 mm Hg, or use of medication for BP), diabetes (fasting glucose ≥126 mg/dL, nonfasting glucose ≥200 mg/dL, self-reported physician’s diagnosis, or use of any diabetes medication), and current smoking (self-reported).Main Outcomes and MeasuresIncident dementia. Population attributable fractions were estimated by age 80 years, and separately after 80 years, from having at least 1 vascular risk factor by age at risk factor measurement.ResultsA total of 7731 participants were included in analysis of risk factors measured at age 45 to 54 years (4494 female [58%]; 2207 Black [29%]; 5524 White [71%]), 12 274 contributed to analysis of risk factors measured at age 55 to 64 years (6698 female [55%]; 2886 Black [24%]; 9388 White [76%]), and 6787 contributed to analysis of risk factors measured at age 65 to 74 years (3764 female [56%], 1375 Black [20%]; 5412 White [80%]). There were 801, 995, and 422 dementia cases by 80 years, respectively. The fraction of dementia by 80 years attributable to at least 1 vascular factor at age 45 to 54 years was 21.8% (95% CI, 14.3%-29.3%), at 55 to 64 years was 26.4% (95% CI, 19.1%-33.6%), and at 65 to 74 years was 44.0% (95% CI, 30.9%-57.2%). Attributable fractions for these factors were higher in apolipoprotein ε4 noncarriers at age 55 years and older (range, 33.3%-61.4%), Black individuals at age 45 years and older (range, 25.5%-52.9%), and female individuals at age 55 years and older (range, 29.2%-51.3%). Only 2% to 8% of dementia cases after 80 years were attributable to these factors.Conclusions and RelevanceResults of this cohort study suggest that between 22% and 44% of incident dementia cases by 80 years in the ARIC study were attributed to midlife and late-life vascular risk factors. Assuming causal relationships, maintaining optimal vascular health across the life course could mitigate a sizeable proportion of dementia risk by 80 years.

Introduction: Physical activity (PA) has been identified as a protective factor for dementia, but the mechanisms linking PA to brain health are unclear. To elucidate potential pathways linking PA to brain health, we tested the hypothesis that higher levels of late-life PA are associated with a lower burden of Alzheimer’s disease (AD) pathology, cerebrovascular disease, and neurodegeneration measured through brain imaging and plasma biomarkers. Methods: ARIC-NCS participants without dementia in 2011-13 and with measures of PA, 3T brain magnetic resonance imaging (MRI), and stored plasma samples were examined (n=1,771; mean age: 76.5 years; 40.5% male; 27.6% Black). Participants were classified as meeting or not meeting 2018 aerobic PA guidelines based on a standardized interviewer-administered questionnaire. MRI biomarkers included white matter hyperintensity (WMH) volume (cm 3 ), total brain volume (TBV) (cm 3 ), and cortical thickness (CT) (mm). Plasma biomarkers of the ratio of amyloid beta 42 to 40 (Aβ42/Aβ40), phosphorylated Tau-181 (p-Tau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured using Quanterix Simoa immunoassays. All biomarkers were standardized to measures in 2011-13 to facilitate comparisons. Covariate-adjusted linear regression models estimated cross-sectional associations of PA with MRI or plasma biomarkers. Covariate-adjusted linear mixed effects models quantified associations of PA with the 5-year rate of change in a subset of participants with MRI (n=669) or plasma (n=651) biomarkers at both baseline and follow-up from 2011-19 (median follow-up: 5.4 years). Results: Meeting versus not meeting aerobic PA guidelines was cross-sectionally associated with lower volumes of WMH (β = -0.16, 95% CI: -0.25, -0.07), higher TBV (β = 0.09; 95% CI: 0.05, 0.13), and lower plasma NfL (β = -0.102, 95% CI: -0.184, -0.021) ( Figure ). Late-life PA was not associated with 5-year rates of change in MRI or plasma biomarkers. Conclusions: Late-life PA was cross-sectionally associated with less neurodegeneration and cerebrovascular disease. Associations with 5-year changes in imaging and plasma biomarkers of AD pathology, cerebrovascular disease, or neurodegeneration were not statistically supported. Longitudinal biomarker studies with wearable devices that quantify other daily intensity-based movement metrics (e.g., light PA) and larger sample sizes are needed to further examine mechanisms linking PA to brain health.