Albert, Marilyn S.

Abstract Bioinformatics methods can be used to quantify mitochondrial DNA copy number from whole genome sequencing (WGS) data. We evaluated mitochondrial DNA copy number from human brain-derived WGS data using the fastMitoCalc tool. 341 Parkinson’s Disease cerebellum samples were compared with 74 age-matched controls from the North American Brain Expression Consortium. Parkinson’s Disease cerebellum had significantly higher mitochondrial DNA copy number compared with controls (P = 4.15e–7), and this effect was reproducible in four of five brain banks when analysis was restricted to each resource that contributed Parkinson’s Disease samples to this genetic dataset. Follow-on analyses of 128 Parkinson’s Disease cerebellum samples and 33 controls that had paired neuropathology data and clinical scores demonstrated a significant increase in mitochondrial DNA copy number with Unified Staging System for Lewy Body disorders stages and Unified Parkinson’s Disease Rating Scale (off meds) motor scores. Analysis of Lewy Body scores from ten brain regions showed cerebellum mitochondrial DNA copy number increased upon pathological infestation of α-synuclein aggregates in the brainstem and limbic system but did not increase after late-stage neocortical involvement. This genetics dataset supports previous observations of cerebellum activation in Parkinson’s Disease and suggests mitochondrial DNA copy number may increase to support this regional activation as a compensatory mechanism to pathology or motor symptoms.

Background: Cognitive change is an important factor in understanding dementia. Estimating effects of exposures on cognitive change requires choosing an analytical timescale, typically time on study or current age. There is limited consensus regarding timescale choice in epidemiologic cognitive aging research. Methods: Using a coordinated analytic approach in 10 cohorts of older adults, we evaluated whether estimated effects of two exposures on memory change differed depending on timescale (time on study or current age). We modeled effects of apolipoprotein-E (APOE) ε4 genotype (a time-invariant exposure) and diabetes (a potentially time-varying/acquired exposure evaluated at baseline) using mixed-effects models with linear and nonlinear time specifications for both timescales. Results: Among APOE ε4 carriers, model-estimated memory scores at baseline (time on study timescale) or at each cohort’s median baseline age (current age timescale) were lower, and the average rate of decline was faster than among APOE ε4 noncarriers. Model-estimated memory scores at baseline or at median baseline age were generally similar across baseline diabetes status, with variability across cohorts in the diabetes-memory change association. In some cohorts, trends in diabetes-memory change associations differed in direction across timescales. Conclusions: Timescale was largely inconsequential for estimated effects of APOE genotype, but yielded differences in estimated diabetes effects, raising questions about the appropriate scale. The current age scale may be problematic because diabetes was measured heterogeneously in age across individuals, a common issue in aging cohorts. Our work demonstrates approaches to evaluate alternative timescales, including in multicohort analyses, and highlights potential implications for estimated exposure effects on cognitive change.

AbstractBackgroundThe Uniform Data Set (UDS) neuropsychological battery, administered across Alzheimer’s Disease Centers (ADC), includes memory tests but lacks a list‐learning paradigm. ADCs often supplement the UDS with their own preferred list‐learning task. Given the importance of list‐learning for characterizing memory, we aimed to develop a harmonized memory score that incorporates UDS memory tests while allowing centers to contribute differing list‐learning tasks.MethodWe applied item‐banking confirmatory factor analysis to develop a composite memory score in 5,287 participants (mean age 67.1; SD = 12.2) recruited through 18 ADCs and four consortia (DiverseVCID, MarkVCID, ALLFTD, LEADS) who completed UDS memory tasks (used as linking‐items) and one of five list‐learning tasks. All analyses used linear regression. We tested whether memory scores were affected by which list‐learning task was administered. To assess construct validity, we tested associations of memory scores with demographics, disease severity (CDR Box Score), an independent memory task (TabCAT Favorites, n = 675), and hippocampal volume (n = 811). We compared performances between cognitively unimpaired (n = 279), AD‐biomarker+ MCI (n = 26), and AD‐biomarker+ dementia (n = 98). In a subsample with amyloid‐ and tau‐PET (n = 49), we compared memory scores from participants with positive vs negative scans determined using established quantitative cutoffs.ResultModel fit indices were excellent (e.g., CFI = 0.998) and factor loadings were strong (0.43‐0.93). Differences in list‐learning task had a negligible effect on scores (average Cohen’s d = 0.11). Higher memory scores were significantly (p’s<.001) correlated with younger age (β = ‐0.18), lower CDR Box Scores (β = ‐0.63), female sex (β = 0.12), higher education (β = 0.19), larger hippocampal volume (β = 0.42), and an independent memory task (β = 0.71, p<0.001). The memory composite declined in a stepwise fashion by diagnosis (cognitively unimpaired>MCI>AD dementia, p<0.001). On average, amyloid‐PET positivity was associated with lower composite scores, but was not statistically significant (β = ‐0.34; p = 0.25; d = 0.40). Tau‐PET positivity was associated with worse performance, demonstrating a large effect size (β = ‐0.75; p<0.002; d = 0.91).ConclusionThe harmonized memory score developed in a large national sample was stable regardless of contributing list‐learning task and its validity for cross‐cohort ADRD research is supported by expected associations with demographics, clinical measures, and Alzheimer’s biomarkers. A processing script will be made available to enhance cross‐cohort ADRD research.

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.

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.

AbstractBackgroundStructural variants range from simple loss or gain of genetic material to complex events that restructure entire chromosomes. This heterogeneity coupled with variant size greater than sequencing read‐length makes structural variant mapping from short‐read sequencing data difficult and error‐prone. Consequently, the role of structural variants is poorly explored in many phenotypes, including dementia.MethodWe used the GATK‐SV pipeline that combines four external structural variant mapping algorithms with machine‐learning to build high‐quality consensus structural variant calls. We applied GATK‐SV to short‐read whole‐genome sequencing data of 2,601 frontotemporal dementia‐amyotrophic lateral sclerosis spectrum (FTD/ALS) patients, 2,612 Lewy body dementia (LBD) patients, and 4,132 neurologically unaffected participants.ResultAfter stringent quality‐control, we performed genome‐wide association studies on 2,307 ALS/FTD patients versus 3,677 controls with 4,699 common structural variants and 2,355 LBD patients versus 3,700 controls with 4,889 common structural variants. In the FTD/ALS cohort, we identified well‐known risk variants at the C9orf72 (p‐value = 4.99×10‐18, OR = 14.47, 95% CI = 7.90–26.49) and MAPT loci (p‐value = 3.48×10‐6, OR = 0.77, 95% CI = 0.68–0.86) corroborating the ability of our pipeline to identify disease‐associated structural variants. Moreover, we discovered, replicated, and validated TPCN1 as a novel risk locus for LBD (p‐value = 9.18×10‐6, OR = 1.43, 95% CI = 1.22–1.67). Further, we identified rare exonic variants with known pathogenic or likely pathogenic effects, such as an SNCA gene duplication in LBD and a deletion of exons 1 and 2 in CHCHD10 in FTD/ALS. We additionally observed structural variants in regulatory regions, e.g. a deletion of a key PSEN2 enhancer, which resulted in an approximate 0.70 fold‐change in PSEN2 expression in LBD. Finally, we built an interactive web app where structural variants can be visualized and explored (https://ndru-ndrs-lng-nih.shinyapps.io/non_ad_dementias_sv_app/).ConclusionCommon and rare structural variants play a role in LBD and FTD/ALS. Our structural variant resource is publicly available and can be used to further explore the role of structural variants in LBD and FTD/ALS.

AbstractBackgroundHearing impairment is associated with cognitive decline but whether it is a cause or marker is unknown. We investigated the association of hearing impairment with brain volumes and 8‐year cognitive decline. Because the superior temporal gyrus (STG) is the location of the primary auditory cortex, we stratified results by STG volume to investigate if the association of hearing and cognition differed among participants with and without evidence of possible hearing‐related brain atrophy.MethodWe used data from 1195 community‐dwelling adults (72‐94 years, 61% female, 36% black) from the Atherosclerosis Risk in Communities Study. A composite cognitive score was created from 10 neuropsychological tests administered at 3 study visits spanning 8 years (2011‐13 to 2018‐19). Brain volumes were calculated from structural magnetic resonance imaging scans for 6 regions of interest. Pure tone air conduction hearing thresholds (frequencies 0.5‐4 kHz) were obtained in 2016‐17 and averaged, with better‐ear hearing impairment defined as an average >25 dB. Multivariable‐adjusted linear regression was used to estimate cross‐sectional differences in standardized brain volumes, adjusting for intracranial volume, demographic and clinical covariates. We estimated differences in annual rates of cognitive change by hearing impairment status adjusting for demographic and clinical covariates using linear mixed models; results were stratified by intracranial volume‐adjusted STG volume (below vs. equal to or greater than the median value).ResultThe mean STG volume difference comparing hearing impairment to normal hearing was ‐0.121 standard deviations (SD) (95% CI: ‐0.213, ‐0.028). Overall, the difference in the rate of cognitive decline associated with hearing impairment was ‐0.014 SD (‐0.023, ‐0.005). Hearing was more strongly associated with cognitive decline among participants with smaller STG volumes; rate difference, ‐0.014 SD (‐0.027, ‐0.002) compared to ‐0.008 (‐0.022, 0.006) for participants with larger STG volumes.ConclusionHearing impairment was associated with smaller brain volumes in the primary auditory region, but not with other regions. Our stratified analysis suggests that hearing treatment might be an important possible strategy to delay cognitive decline, even among participants with hearing‐related brain atrophy. Furthermore, the adverse cognitive effects of hearing impairment could potentially be mitigated if early hearing treatment can prevent STG atrophy.

AbstractBackgroundAlthough both age‐related and highly prevalent, little is known regarding the prevalence of hearing loss among persons with dementia (PwD). Current understanding is based on convenience samples primarily from specialized memory clinics. The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC‐NCS) is a large, prospective study of a population‐based cohort from 4 U.S. community sites with audiometric and neurocognitive testing and bi‐racial representation. We examined the prevalence of hearing loss and hearing aid use among older adults with cognitive impairment and whether cognitive status influences hearing aid use.MethodWe analyzed audiometric and hearing care data from ARIC‐NCS Visit 6 (2016‐2018). Participants underwent a full neurocognitive battery and audiometric evaluation at Visit 6. Participants with complete audiometric data and an adjudicated diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia were included in the analytical cohort (N=3,385). Differences in participant characteristics by cognitive status were descriptively compared using Chi‐square tests or one‐way ANOVAs. We performed a series of logistic regression models to estimate the odds of hearing aid non‐use by cognitive status.ResultPrevalence of hearing loss was greater with increasing cognitive impairment (cognitively normal:64.7%; MCI:71.3%; dementia:83.3%). Prevalence of hearing aid use among those with hearing loss and cognitive impairment varied by race (African Americans 7.2%; whites 32.8%). In a multivariable‐adjusted model, cognitive impairment was independently associated with higher odds of non‐use of hearing aids (MCI odds ratio (OR):1.4 (95%CI:1.0‐1.8); dementia OR:1.8 (95%CI:1.2‐2.9) versus cognitively normal). The strongest risk factor for non‐use of hearing aids was race, where African Americans have almost a 5 times higher odds of not using hearing aids compared to whites (95% CI:2.9‐7.4).ConclusionHearing loss is highly prevalent but vastly untreated among older adults with cognitive impairment, particularly African Americans, and cognitive impairment is independently associated with hearing aid use. These estimates are some of the first population‐based estimates of audiometric hearing loss among diverse older adults with adjudicated diagnoses of MCI or dementia. With increased calls to address ethnic/racial disparities, we must include hearing loss, as one of the most common co‐morbidities, in order to optimize health and well‐being among all PwD.