Pike, James Russell

AbstractBackgroundBlood‐based biomarkers show promise as a noninvasive, inexpensive method for measuring Alzheimer’s disease pathology throughout the lifecourse. However, the predictive and classification accuracy of these biomarkers at different stages of the lifecourse and among diverse, community‐dwelling populations requires further investigation.MethodBetween 2014 and 2015, 329 dementia‐free participants from the Atherosclerosis Risk in Communities Study underwent brain magnetic resonance imaging (MRI) and florbetapir positron emission tomography (PET). Amyloid positivity was defined as a global cortex standardized uptake value ratio greater than 1.2. Stored plasma samples collected in midlife (1993‐95, mean age 58.5 years) and late‐life (2011‐13, mean age 76.2 years) from a subsample of 259 participants 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). Unadjusted and covariate‐adjusted logistic regression models estimated the association between plasma biomarkers from midlife and late‐life and amyloid positivity in late‐life. Unadjusted receiver operating characteristic curves documented the classification accuracy of the plasma biomarkers separately and collectively.ResultThe sample (Table 1) included 151 women (58.1%), 105 Black participants (40.4%), and 136 (52.3%) participants with amyloid positivity. In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, assays measured in midlife were not associated with amyloid positivity in late‐life (Table 2). However, late‐life measurements of Aβ42/40, p‐Tau181, and GFAP and change per decade from midlife to late‐life in p‐Tau181 and GFAP were associated with greater odds of amyloid positivity. The greatest classification accuracy (Figure 1) was achieved by using all assays measured in midlife and late‐life (AUC = 0.754), although the accuracy when using only late‐life measures was comparable (AUC = 0.737).ConclusionLate‐life plasma biomarkers of Alzheimer's disease neuropathology and astrogliosis were associated with late‐life amyloid positivity, but midlife plasma biomarkers obtained 16 to 20 years earlier did not exhibit a statistically significant association. Additional longitudinal research is needed to determine whether changes in plasma biomarkers measured before an individual is classified as amyloid positive can be used to identify individuals at risk of developing Alzheimer's disease.

AbstractBackgroundOlder adults with dual cognitive and mobility impairments have higher financial costs and poorer quality of life than adults with either impairment alone. Blood biomarkers of Alzheimer Disease (AD) pathology (Aβ42, Aβ40 and p‐tau181) and neurodegeneration (neurofilament light (NFL) and glial fibrillary acidic protein (GFAP)) may identify individuals at risk for both mobility and cognitive impairment and provide novel insights into mechanistic underpinnings.MethodBlood biomarkers (SiMoA Quanterix N4PE, p‐tau181 single‐plex) were available in a subsample of 1751 ARIC study participants at Visit 5 (V5, 2011‐13, mean age 76.2 years (5.3), 41% men, 28% Black); Aβ42 was reversed and adjusted for Aβ40 (‐Aβ42|40) for consistent directions of associations (higher=worse). Usual gait speed and cognitive status were assessed over 8 years at V5, V6 (2016‐17), and V7 (2017‐18). Participants were categorized by V5 impairment: mobility‐only (gait speed <0.8m/s, n=430), cognitive‐only (expert‐adjudicated dementia, n=38), dual (n=54), or neither (referent, n=1229). Multinomial regression models examined relative risk ratios (RRR) of V5 log‐transformed biomarkers with prevalent impairments and, among those with neither impairment at V5, incident impairments through V7. All models adjusted for V5 age, sex, self‐reported race (Black or White), renal function, and body mass index.ResultHigher levels of all biomarkers were associated with greater risk of prevalent impairment in mobility, cognitive, or dual domains (Figure A). Over 8‐years of follow‐up, incident impairments included 471 participants with only mobility impairments, 39 with only cognitive impairments, 55 with dual impairments, and 168 died without developing any impairment. All biomarkers were associated with incident dual impairment per IQR higher biomarker: p‐tau181 (RRR=2.54; 95% CI: 1.45, 4.44), ‐Aβ42|40 (RRR=1.66; 1.31, 2.09), NfL (RRR=2.69; 1.22, 5.91) and GFAP (RRR=2.13; 1.07, 4.25). P‐tau181, ‐Aβ42|40, and GFAP were also associated with incident cognitive‐only impairment, while P‐tau181, NFL and GFAP were associated with incident mobility‐only impairment. (Figure B).ConclusionBlood biomarkers of brain health may be useful tools for earlier identification of those at risk for cognitive, mobility, or dual declines, facilitating earlier targeted interventions. Potential differences in AD‐pathology versus neurodegeneration blood biomarker relationships with outcomes of mobility and cognition may help to identify more targeted interventions for both.

AbstractBackgroundMidlife vascular risk factors are associated with an increased risk of dementia. However, the overall contribution of modifiable vascular risk factors in midlife and late‐life to dementia remains unclear. In this study, we quantified population attributable fractions, which account for risk factor prevalence and strength of relative risks, of incident dementia from vascular risk factors measured in midlife and early late‐life.MethodWe used 33 years of prospective cohort data in the Atherosclerosis Risk in Communities Study. Incident dementia (community surveillance and algorithmic diagnosis with expert clinical adjudication) was ascertained from baseline (1987‐1989) through December 31, 2020. We quantified population attributable fractions of incident dementia by age 80 from the combination of hypertension (systolic blood pressure ≥130, diastolic blood pressure ≥80, or use of medication), diabetes (fasting glucose ≥126, non‐fasting glucose ≥200, self‐reported physician diagnosis of diabetes, or use of medication for diabetes/insulin), and self‐reported current cigarette smoking (at least one risk factor versus none) measured at different ages (45‐54 [n = 7,731], 55‐64 [n = 12,273]; 65‐74 [n = 6,660]). We also computed attributable fractions stratified by sex, apolipoprotein ε4 genotype, and self‐reported race.ResultThe prevalence of having one or more of the vascular risk factors was 61.6% (95% CI: 60.5, 62.7%) at age 45‐54 and increased to 77.5% (95% CI: 76.5, 78.5%) by age 65‐74. Population attributable fractions of dementia increased from 22.7% (95% CI: 15.3, 30.1%) for vascular risk factors measured at age 45‐54 to 45.4% (95% CI: 32.5, 58.3%) for vascular risk factors assessed at age 65‐74 (see Figure). Attributable fractions were larger in females, participants without apolipoprotein ε4 alleles, and Black participants (Figure).ConclusionBetween 23% to 45% of incident dementia cases by age 80 were attributed to a combination of hypertension, diabetes, or current smoking up through age 74. Attributable fractions for the combined impact of vascular risk varied by key demographics. Public health strategies targeting modifiable vascular risk factors could reduce dementia risk and increase healthy lifespan.

AbstractBackgroundPrior longitudinal studies among older adults have documented associations between hearing loss and changes in brain morphology. Whether interventions involving hearing aids can reduce age‐related atrophy is unknown. A substudy within the Aging and Cognitive Health Evaluation in Elders (ACHIEVE, Clinicaltrials.gov Identifier: NCT03243422) randomized controlled trial tested the effect of a best‐practices hearing intervention versus health education control on three‐year change in cortical thickness among older adults with hearing loss.MethodThe ACHIEVE study enrolled 977 community‐dwelling adults aged 70‐84 years at baseline (2018‐2019) with untreated hearing loss (better ear pure tone average [0.5‐4 kHz] ≥30 and <70 dB HL) and without substantial cognitive impairment from four sites across the U.S. (Jackson, MS, Forsyth County, NC, Minneapolis, MN, Washington County, MD). Participants were randomized to a hearing intervention (provision of hearing aids and related technologies, counseling, and education) or a health education control (individual sessions with a health educator covering topics relevant to chronic disease and disability prevention). Three‐dimensional magnetic resonance imaging was performed on 3 Tesla Siemens scanners in a subsample of 445 participants at the ACHIEVE baseline and three‐year follow‐up. Linear mixed effects models were used in intention‐to‐treat analyses to estimate three‐year change in cortical thickness. All models adjusted for baseline measures of hearing loss, recruitment source, site, age, sex, and education. Missing outcome and covariate data was imputed to mitigate bias caused by informative attrition.ResultAt baseline, 224 participants were women (50.3%), 52 participants were Black (11.7%), and the mean (SD) age was 76.4 (4.0) years old (Table 1). Compared to the health education control, the hearing intervention exhibited a nominally protective effect on three‐year change in average cortical thickness (Figure 1). The greatest effect size for cortical thickness was observed in the occipital lobe, while the smallest effect size was detected in the temporal lobe. Statistically significant effects were detected in the pars orbitalis, rostral anterior cingulate, posterior cingulate, and isthmus cingulate (Figure 2).ConclusionHearing aid use may reduce decline in cortical thickness among older adults. The effects of hearing aids may be greatest in regions other than those associated with the auditory cortex.

Importance Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure Plasma biomarkers of amyloid-β 42 to amyloid-β 40 (Aβ42:Aβ40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aβ42:Aβ40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 ( APOE ε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aβ42:Aβ40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers’ association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.

AbstractINTRODUCTIONThe contribution of neuropsychological assessments to risk assessment for incident dementia is underappreciated.METHODSWe analyzed neuropsychological testing results in dementia‐free participants in the Atherosclerosis Risk in Communities (ARIC) study. We examined associations of index domain–specific neuropsychological test performance with incident dementia using cumulative incidence curves and Cox proportional hazards models.RESULTSAmong 5296 initially dementia‐free participants (mean [standard deviation] age of 75.8 [5.1] years; 60.1% women, 22.2% Black) over a median follow‐up of 7.9 years, the covariate‐adjusted hazard ratio varied substantially depending on the pattern of domain‐specific performance and age, in an orderly manner from single domain language abnormalities (lowest risk) to single domain executive or memory abnormalities, to multidomain abnormalities including memory (highest risk).DISCUSSIONBy identifying normatively defined cognitive abnormalities by domains based on neuropsychological test performance, there is a conceptually orderly and age‐sensitive spectrum of risk for incident dementia that provides valuable information about the likelihood of progression.Highlights Domain‐specific cognitive profiles carry enhanced prognostic value compared to mild cognitive impairment. Single‐domain non‐amnestic cognitive abnormalities have the most favorable prognosis. Multidomain amnestic abnormalities have the greatest risk for incident dementia. Patterns of domain‐specific risks are similar by sex and race.

Purpose: Population-based evidence in the interrelationships among hearing, brain structure, and cognition is limited. This study aims to investigate the cross-sectional associations of peripheral hearing, brain imaging measures, and cognitive function with speech-in-noise performance among older adults. Method: We studied 602 participants in the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) brain magnetic resonance imaging (MRI) ancillary study, including 427 ACHIEVE baseline (2018–2020) participants with hearing loss and 175 Atherosclerosis Risk in Communities Neurocognitive Study Visit 6/7 (2016–2017/2018–2019) participants with normal hearing. Speech-in-noise performance, as outcome of interest, was assessed by the Quick Speech-in-Noise (QuickSIN) test (range: 0–30; higher = better). Predictors of interest included (a) peripheral hearing assessed by pure-tone audiometry; (b) brain imaging measures: structural MRI measures, white matter hyperintensities, and diffusion tensor imaging measures; and (c) cognitive performance assessed by a battery of 10 cognitive tests. All predictors were standardized to z scores. We estimated the differences in QuickSIN associated with every standard deviation ( SD ) worse in each predictor (peripheral hearing, brain imaging, and cognition) using multivariable-adjusted linear regression, adjusting for demographic variables, lifestyle, and disease factors (Model 1), and, additionally, for other predictors to assess independent associations (Model 2). Results: Participants were aged 70–84 years, 56% female, and 17% Black. Every SD worse in better-ear 4-frequency pure-tone average was associated with worse QuickSIN (−4.89, 95% confidence interval, CI [−5.57, −4.21]) when participants had peripheral hearing loss, independent of other predictors. Smaller temporal lobe volume was associated with worse QuickSIN, but the association was not independent of other predictors (−0.30, 95% CI [−0.86, 0.26]). Every SD worse in global cognitive performance was independently associated with worse QuickSIN (−0.90, 95% CI [−1.30, −0.50]). Conclusions: Peripheral hearing and cognitive performance are independently associated with speech-in-noise performance among dementia-free older adults. The ongoing ACHIEVE trial will elucidate the effect of a hearing intervention that includes amplification and auditory rehabilitation on speech-in-noise understanding in older adults. Supplemental Material: https://doi.org/10.23641/asha.25733679

AbstractBackgroundHearing loss is associated with greater cognitive decline and incident dementia. Whether hearing intervention could reduce cognitive decline in older adults with hearing loss is unknown.MethodThe ACHIEVE study is a randomized trial (NCT03243422) of 70‐84 year‐old adults with untreated hearing loss and free from substantial cognitive impairment that took place at four U.S. sites. Participants were recruited from two study populations: 1) a group of adults participating in a longstanding observational study of cardiovascular health (Atherosclerosis Risk in Communities [ARIC] study), and 2) a group of healthy de novo community volunteers. Participants were randomised (1:1) to hearing intervention (HI; audiological counseling and provision of hearing aids) or a successful aging health education control intervention (SA; sessions with a health educator on chronic disease prevention). The primary intention‐to‐treat endpoint was 3‐year change in a global cognition standardized factor score from a comprehensive neurocognitive battery.Result977 participants (238 ARIC, 739 de novo) underwent randomisation; 490 were assigned to HI and 487 to SA control. Participants from ARIC were older, had more risk factors for cognitive decline, and had lower baseline cognitive scores than the de novo group. In the primary analysis combining the ARIC and de novo groups, 3‐year cognitive change (in S.D. units) was not significantly different between HI and SA control (HI: ‐0·200 [95% CI: ‐0·256,‐0·144]; SA: ‐0·202 [‐0·258,‐0·145]; Difference 0·002 [‐0·077,0·081],p = 0·96). However, prespecified analyses demonstrated significant differences in the effect of HI on cognitive change between the ARIC and de novo group (p interaction = 0·010). In the ARIC group, HI was associated with a 48% reduction in 3‐year cognitive change compared to SA control (HI: ‐0·211 [‐0·349,‐0·073]; SA: ‐0·402 [‐0·536, ‐0·267]; Difference 0·191 [0·022,0·360,p = 0·027]). In the de novo group, cognitive change was not significantly different between HI and SA control (HI: ‐0·213 [‐0·277,‐0·148]; SA: ‐0·151 [‐0·215,‐0·087]; Difference ‐0·061 [‐0·151,0·028,p = 0·18]). The rate of cognitive change among control participants was observed to be 2.7‐fold faster in the ARIC versus de novo group.ConclusionHearing intervention may have a significant effect on reducing cognitive change over 3 years in populations of older adults at increased risk for cognitive decline.

AbstractBackgroundHearing loss is associated with cognitive decline and dementia. The ongoing ACHIEVE Study was the first randomized trial to test the effects of hearing treatment on three‐year cognitive change. The ACHIEVE – Brain Health Follow‐Up Study will extend follow‐up to six years post‐randomization to determine the long‐term and potentially nonlinear effects of hearing treatment vs. health education control with delayed treatment on dementia and cognitive decline.MethodsParticipants will be recruited from the 977 participants enrolled in the ACHIEVE Study. After Year 3, hearing intervention participants will continue to receive hearing care and the control group will be offered the hearing intervention. Co‐primary study outcomes will be cognitive decline and a composite of incident mild cognitive impairment (MCI)/probable dementia. Secondary outcomes include domain‐specific cognitive decline, brain structural changes on magnetic resonance imaging (MRI), and other functional outcomes (e.g., physical activity, social isolation). Power analyses for the co‐primary outcomes assumed an annual attrition rate of 10% and an immediate, lagged, or cumulative treatment effect.ResultsWhen comparing multi‐year cognitive decline (Table 1), in the scenario of a constant treatment effect that assumes a strong and immediate treatment effect, the benefit of extended follow‐up is not greater power, but additional information on the long‐term effects of hearing intervention. In a scenario of a lagged treatment effect, a two‐year lag in the treatment effect causes the Year 3 assessment to be severely underpowered (28%) but provides sufficient power (80%) at Year 6 despite attrition. In a scenario of a cumulative treatment effect that increases with time, analyses are similarly underpowered at Year 3 (65%) but not at Year 6 (82%). The same pattern is evident when estimating the power at Year 3 (57%) and Year 6 (80%) to detect incident MCI/probable dementia in a Cox regression model that assumes a protective hazard ratio of 0.70 (Figure 1).ConclusionAcross all non‐constant scenarios of potential treatment effect, six years of follow‐up increases precision and provides valuable information to better delineate long‐term cognitive trajectories. The ACHIEVE ‐ Brain Health Follow‐Up Study will be completed in 2025.

BACKGROUND: Cerebral microbleeds (CMBs) are associated with cognitive decline, but their importance outside of cerebral amyloid angiopathy and the mechanisms of their impact on cognition are poorly understood. We evaluated the cross-sectional association between CMB patterns and cerebral Aβ (amyloid-β) deposition, by florbetapir positron emission tomography. METHODS: The longitudinal ARIC study (Atherosclerosis Risk in Communities) recruited individuals from 4 US communities from 1987 to 1989. From 2012 to 2014, the ARIC-PET (Atherosclerosis Risk in Communities - Positron Emission Tomography) ancillary recruited 322 nondemented ARIC participants who completed 3T brain magnetic resonance imaging with T2*GRE as part of ARIC visit 5 to undergo florbetapir positron emission tomography imaging. Magnetic resonance imaging images were read for CMBs and superficial siderosis; on positron emission tomography, global cortical standardized uptake value ratio >1.2 was considered a positive Aβ scan. Multivariable logistic regression models evaluated CMB characteristics in association with Aβ positivity. Effect modification by sex, race, APOE status, and cognition was evaluated. RESULTS: CMBs were present in 24% of ARIC-PET participants. No significant associations were found between CMBs and Aβ positivity, but a pattern of isolated lobar CMBs or superficial siderosis was associated with over 4-fold higher odds of elevated Aβ when compared with those with no CMBs (odds ratio, 4.72 [95% CI, 1.16–19.16]). A similar elevated risk was not observed in those with isolated subcortical or mixed subcortical and either lobar CMBs or superficial siderosis. Although no significant interactions were found, effect estimates for elevated Aβ were nonsignificantly lower ( P >0.10, odds ratio, 0.4–0.6) for a mixed CMB pattern, and odds ratios were nonsignificantly higher for lobar-only CMBs for 4 subgroups: women (versus men); Black participants (versus White participants), APOE ε4 noncarriers (versus carriers), and cognitively normal (versus mild cognitive impairment). CONCLUSIONS: In this community-based cohort of nondemented adults, lobar-only pattern of CMBs or superficial siderosis is most strongly associated with brain Aβ, with no elevated risk for a mixed CMB pattern. Further studies are needed to understand differences in CMB patterns and their meaning across subgroups.