bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuroinflammation, amyloid, NFT markers and initial cognitive status predict cognitive decline in MCI patients
Authors: Leng Fangda , Hinz Rainer , Gentleman Steve , Brooks David J. , Edison Paul 
Published: December 2021

AbstractBackgroundNeuroinflammation has been established as a key component of Alzheimer’s pathology. Numerous cross‐sectional studies have found associations between neuroinflammatory markers and neuronal damage in AD, suggesting neuroinflammation as a potential drive force of disease progression. However, there have been debate on whether neuroinflammation has a causal effect on disease progression. Here we questioned whether neuroinflammation is predictive of future cognitive decline in early stage of the disease.Method21 MCI patients were recruited and had baseline T1‐MRI and 11C‐PBR28 scans. Patients were followed up for at least one year (mean follow‐up period 3.1±1.3 years) and had mini‐mental state examinations (MMSE) at each visit. 19 of them had baseline 18F‐Flutemetamol PET, 11 had 18F‐AV1451 scans. 18F‐AV1451 and 11C‐PBR28 SUVR in the medial temporal lobe were measured, while PCA analyses were performed to evaluate uptakes in the neocortex for all 3 tracers. Principle components of temporal lobe volumetric measurements were computed as the neurodegeneration marker. A linear growth model was fitted for each subjects using all available time points, giving the intercept and slope of individual cognition trajectory. Age, intercept, 11C‐PBR28, and T1 MRI markers were then put into linear models to predict slope, and a backward model selection procedure was conducted. To further validate that neuroinflammation is not just a mediator of amyloid and tau pathologies, we further included amyloid and tau markers in the sub‐cohorts and inspected the final model.ResultThe average baseline MMSE was 28±1.9 in the study cohort and the average annual change of MMSE was ‐0.46. We found 11C‐PBR28 SUVR in neocortex and MMSE intercept, but not temporal cortical thickness, were predictive of the slope of MMSE decline. In subgroups where 18F‐Flutemetamol and 18F‐AV1451 SUVRs were included respectively, we found neocortical amyloid and tau load were also predictive of MMSE slope, while 11C‐PBR28 SUVR remained its significance in the models.ConclusionOur findings suggest that neuroinflammation is an independent factor that drives disease progression and cognitive decline in early stage of AD. Molecular imaging biomarkers may better predict patients’ outcome as they detect underlying biological processes.
Time perception in people living with Alzheimer's disease
Authors: Pai Ming‐Chyi 
Published: December 2021

AbstractBackgroundPeople may perceive time passed and the events happened in it from time to time. This is not only for the events happened outside the brains of the perceivers, but also for their thinking process. To sense the time lapsed as the time goes by is usually operated by a subconscious mechanism until confusion appears. The confusion may manifest as being not sure about something happened or not or something one has done or not, which occur very frequently in people living with Alzheimer's disease (AD). It may also play a role in spatial navigation, which relies on time and distance perceptions. The mechanism of time perception is complicated, and may involve several neural structures, including basal ganglia, insula, cerebellum, prefrontal lobes, and hippocampus. The aim of this study was to examine the perception of time in persons with mild AD, prodromal AD (prAD) and the cognitively unimpaired (CU).MethodWe invited people with mild AD, prAD and CU to participate in this study. We measured verbal time estimation in 10 seconds, 30 seconds, 60 seconds and time production in 10 seconds, 30 seconds, and 60 seconds. The participants were instructed to press a button on a device to measure time perception when they gauged each target of time had passed. The deviation from the correct response was recorded and compared among the three groups.ResultA total of 22 AD, 58 prAD and 142 CU persons completed the study. Their Mini‐Mental State Examination (MMSE) scores were on the average 22 (SD 4), 22 (5) and 28 (2). The time perception in terms of verbal estimation showed no difference among the three groups in 10 seconds, 30 seconds, or 60 seconds. Regarding time production, difference appeared between prAD and CU (10.8/7.9 [mean/S.D.] vs 7.7/5.4, p<0.01), and no difference was noted in any other group comparisons.ConclusionThe results provide an insightful information that short‐term time perception is of no difference among mild AD, prAD and CU. A study applying longer term time perception design is needed to show the difference and answer its role in spatial navigation or more complicated cognitive processes.
Recognition memory is impacted in atypical “non‐amnestic” Alzheimer’s disease
Authors: Putcha Deepti , Dev Sheena Isha , Carvalho Nicole , Dickerson Brad C. , Wong Bonnie 
Published: December 2021

AbstractBackgroundMemory encoding and retrieval deficits have increasingly been identified in atypical phenotypes of AD, including posterior cortical atrophy (PCA) and logopenic variant primary progressive aphasia (lvPPA), despite traditional assumptions that memory is spared in these groups. There is a critical need to better understand relationships between these encoding deficits and recognition memory performance. Here we aim to build on the current literature by investigating recognition memory performance across the atypical AD syndromic spectrum.MethodThirty‐seven amyloid‐positive patients with atypical syndromes of AD (14 PCA, 9 lvPPA, and 14 amnestic dysexecutive) were administered the California Verbal Learning Test (CVLT‐II‐SF). Recognition memory performance (d’) and Total Learning were calculated. Independent samples t‐tests were conducted to test the hypothesis that amnestic dysexecutive patients would show greater d’ impairment compared to non‐amnestic (PCA, lvPPA) groups. Bivariate correlations were conducted to determine if Total Learning was related to d’ performance. Whole‐cortex general linear models, thresholded at p<0.01, were conducted to determine where cortical atrophy was related to d’ and Total Learning across all participants.ResultRecognition memory was poor across both groups but trended toward worse in the amnestic dysexecutive group (mean d’=1.3) compared to the non‐amnestic group (mean d’=1.9; t=1.8, p=0.08). Total Learning was related to d’ in the non‐amnestic group (r=0.72, p=0.0002), but not in the amnestic dysexecutive group (p<0.7). In the full sample, cortical atrophy was related to Total Learning in a strongly left‐lateralized pattern in the medial parietal and lateral temporoparietal cortices, while atrophy in left>right anterior medial temporal cortices was related to d’.ConclusionRecognition memory is not spared in atypical phenotypes of AD traditionally thought to be “non‐amnestic,” such as PCA and lvPPA. In these groups, individuals who showed stronger learning did not show storage decay, while those who struggled to learn showed poor discriminability. In the amnestic dysexecutive group, recognition discriminability was impaired regardless of learning ability, suggesting clearer storage loss. Convergent evidence from this and our prior work (Wolk & Dickerson et al., 2011) shows that when encoding or storage is impaired in atypical or typical AD, it is due to neurodegeneration in common circuits subserving these memory processes.
Cognitive decline at middle age
Authors: Zhu Yingying , Zissimopoulos Julie M , Crimmins Eileen M 
Published: December 2021

AbstractBackgroundThere is no disease‐modifying treatment for Alzheimer’s Disease and Related Dementia (ADRD). However, its pathology may occur 20 years earlier than its symptoms. Therefore, understanding cognitive decline at middle age, which might be the starting point of dementia, may be particularly important for preventing or delaying the onset of dementia. This study quantified the population with fast rates of cognitive decline at middle age, explored the distribution of cognitive trajectories, and investigated demographic, health, and socioeconomic factors associated with cognitive deterioration for Americans.MethodWe utilized data from Health and Retirement Study (HRS) 1996 to 2014 and restricted the sample to respondents aged 50 to 64 with self‐reported cognitive score (scaling 0 to 27). We computed person‐specific slopes of changes in cognitive score over the study period (an average of 8 years) by running a linear regression of cognitive score on wave. Further, we defined fast rates of cognitive decline as 2 or more points decline (a slope equal to or below ‐2) in one’s cognitive score per wave. We identified persons with rapid cognitive decline . We further examined the distribution of slopes of individual cognitive trajectories over the whole study period. We utilized logistic regression to examine health and socioeconomic factors associated with rapidly declining cognition at middle age.ResultOverall, 8.7% of the population had rapidly declining cognitive function over the observation period. Being an ethnic minority (ORblack: 2.3 [95%CI: 2.0 – 2.7]), having a less than high school degree (OR: 1.7 [95%CI: 1.4 – 2]), having hypertension (OR: 1.2 [95%CI: 1.1 – 1.4]) and diabetes (OR: 1.5 [95%CI: 1.2 – 1.7], male, low income, not working or working in less cognitively demanding occupations were risk factors for experiencing fast speed of cognitive decline .ConclusionNine percent of the middle‐aged population experienced rapidly deteriorating cognitive abilities. Ethnic minorities, those with cardiovascular risk factors and lower socioeconomic status are more likely to develop rapidly declining cognition and are more vulnerable alleviating the burden of such a decline on their health and productivity.
Alzheimer’s disease spectrum profiled by CSF and imaging biomarkers: Tau PET best predicts cognitive decline
Authors: Bucci Marco , Chiotis Konstantinos , Nordberg Agneta K 
Published: December 2021

AbstractBackgroundThe concept of pathophysiologically profiling individuals based on their biomarker status for Aβ42 (A) or tau (T) deposition and neurodegeneration (N) is attracting interest in the Alzheimer’s disease research field. All three processes can be monitored by either cerebrospinal fluid (CSF) sampling or imaging (PET/MRI). We aimed to test the comparability of the CSF and imaging biomarkers in each AT(N) category and their ability to predict longitudinal cognitive decline.MethodA subset of data from 254 patients who had had PET investigations with amyloid‐β and tau tracers, and CSF sampling at the same time point, and a structural MRI within one year was selected from the Alzheimer’s Disease Neuroimaging Initiative trial data. The participants were grouped by clinical diagnosis at that time: cognitively normal (n=88), subjective memory concern (n=82), early (n=35) or late (n=31) mild cognitive impairment, and Alzheimer’s disease (n=18). Agreement between the modalities for A, T and N was assessed with Cohen’s Kappa statistic. Linear mixed‐effects models were used to predict subsequent decline in the episodic memory composite score.ResultBiomarkers for A in PET and CSF showed moderate agreement (Kappa=0.42‐64). Biomarkers for T in PET and CSF showed fair agreement (Kappa<0.40), except in the Alzheimer’s disease group where agreement was moderate (Kappa=0.64). The N biomarkers (CSF vs atrophy in MRI) showed evidence of discordance across all groups (Kappa<0.26). Baseline tau PET positivity predicted longitudinal decline in episodic memory irrespective of the p‐Tau181 (CSF) status (estimate=‐0.02, p≤0.05), but the same was not seen for isolated p‐Tau181 (CSF) positivity (estimate=0.00, p=0.58). Baseline tau and amyloid‐β PET positivity biomarkers predicted decline in episodic memory (estimate=‐0.02, p≤0.0001), but isolated amyloid‐β PET positivity did not (estimate=‐0.01, p=0.09). Isolated tau PET positivity was not observed in the absence of amyloid‐β PET positivity, with the exception of one participant with PET values close to the cutoff point.ConclusionWhile results for amyloid‐β are relatively similar using CSF or imaging, CSF and imaging results for tau and neurodegeneration are not interchangeable. Tau PET positivity was superior to phosphorylated tau and amyloid‐β PET in predicting cognitive decline in the Alzheimer’s disease continuum.
Developing a digital assistive tool for dementia patients and their caregivers: A qualitative study on needs, potential functions, practical requirements, user acceptance, and ethical considerations
Authors: Wichmann Lenka J , Reiff Nele , Zintl Sophie , Berking Matthias 
Published: December 2021

AbstractBackgroundDigital smartphone assistants for the care and support of people with dementia (PwD) have great potential due to the wide availability of smartphones and a growing number of users aged above 65. Research has mainly focused on the development of applications for only one user group (patients, caregivers, or relatives respectively), and with only one or a few functions included (Yousaf et al., 2020). A more integrative, multi‐user, and multifunctional application would be beneficial because it could be adapted to the users’ needs more flexibly. This qualitative interview study was the first step in a co‐creative process with a user‐centered approach aimed at developing a multifunctional digital assistant.MethodQualitative content analysis (Mayring, 2010) combining deductive and inductive techniques was applied to identify burdens, needs, functions, ethical considerations, and acceptance aspects. 14 semi‐structured interviews were conducted with three participant groups (relatives of PwD; caregivers and nursing staff; psychologists). Interviews were conducted via video conferences due to Covid‐19 restrictions. After the completion of all interviews, participants received several questionnaires on acceptance aspects (Technology Usage Inventory [TUI], acceptance rating of specific functions), and technological affinity (TA‐EG questionnaire) via letter. Interviews were transcribed verbatim with the software MAXQDA. Coding was done by two independent researchers. A coding frame was generated using the interview guide as a theoretical basis and the collected data for building inductive categories. The coding frame was pilot‐tested before the final analysis and intercoder reliability was sufficient (k=.81).
ResultPreliminary results showed that dealing with symptoms of dementia in everyday life was burdening. Emotional needs in patients and needs for additional care resources in relatives and caregivers were the most important unanswered needs. 53 functions were suggested in the areas: digital care, support, training, monitoring, navigation, leisure activities, and social contacts. Participants had ethical requirements (i.e. data protection, privacy, and autonomy) that if met, would enhance acceptance. Results on questionnaires showed positive attitudes towards, curiosity about, and no insecurity with regards to technology. The overall acceptability of suggested functions was high.ConclusionParticipants showed a large interest in the digital assistant. The importance of data protection was underlined.
Multiscale motor activity regulation and cognitive performance in middle‐aged adults: A cross‐sectional study using baseline data of UK Biobank Cohort
Authors: Li Peng , Ulsa Ma Cherrysse , Zheng Xi , Yang Hui‐Wen , Gao Lei , Hu Kun 
Published: December 2021

AbstractBackgroundMotor activity fluctuations in healthy young humans display robust temporal correlations across a wide range of time scales. The multiscale correlations are altered in elderly adults, and their changes are associated with cognitive decline and risk for Alzheimer’s disease. We sought to examine whether the multiscale regulation is associated with cognitive performance in middle age using a population‐based cohort.MethodWe analyzed motor activity recordings that were collected from 97,284 non‐demented participants [aged 39‐70 (mean±SD: 56.1±7.8) years old; female: 54,776 (56.3%)] in the UK Biobank. The detrended fluctuation analysis was performed to quantify temporal correlations at time scales ≤90 min (α1) and ≥2 h (α2; up to 10 h) according to previous studies. Participants also completed four neurocognitive tests, and poorer cognitive performance was characterized by longer reaction time (RT; for information processing speed), more errors made in the pairs matching test (for visual episodic memory), lower fluid intelligence (FI) score (for reasoning), or making incorrect first choice during the prospective memory (PM) test. Linear regression models (or logistic regression for PM) were used to examine the associations of each cognitive outcome with α1 and, separately α2, adjusted for ethnicity, college, social‐economic status, mental and behavioral disorders, diseases of the nervous system, and number of treatments/medications. The 95% confidence intervals (CI) were derived non‐parametrically based on 1,000 bootstrapped samples with replacement.ResultBoth α1 and α2 showed normal distributions: α1=0.99±0.05 (SD) and α2=0.91±0.11. There was a positive association between α1 and FI with 1‐SD decrease of α1 corresponding to a decrease of 0.03 in FI (95% CI 0.01—0.05) that was about the effect of being 2 years older. α2 was negatively associated with RT and positively associated with FI; for 1‐SD decrease in α2, participants took ln(1 ms) longer during RT, and FI decreased by 0.04 (95% CI 0.02—0.06), both equivalent to being ∼2.5‐3 years older.ConclusionMultiscale motor activity regulation is linked to cognitive performance of specific domains in the middle‐aged population. Further studies are required to establish the relevance of these domain‐specific associations to incident dementia in later life and to understand their underlying neurobiology.
Extraneous neuroimaging factors do not contribute to sex differences in flortaucipir signal: Analysis of skull binding and partial volume effects
Authors: Scott Matthew R. , Edwards Natalie C , Properzi Michael J , Jacobs Heidi I.L. , Price Julie C , Manning Lyssa K , Mayblyum Danielle V. , Rubinstein Zoe B. , Rentz Dorene M. , Johnson Keith A. , Sperling Reisa A. , Schultz Aaron P. , Buckley Rachel F. 
Published: December 2021

AbstractBackgroundClinically normal females exhibit greater [18]F‐flortaucipir (FTP) PET signal than males in both temporal and neocortices. It remains unclear whether sex differences in neocortical regions are primarily explained by technical variability issues. We aimed to investigate the contribution of signal spillover/off‐target skull binding to sex differences in FTP‐PET. Next, we explored partial volume effects (PVE) by simulating sex differences in smoothed FTP‐PET signal. Discerning sex differences in tau signal versus noise is pivotal to understanding sex differences in the pathology of Alzheimer’s disease and associated tauopathies.Method343 clinically normal (female=58%; mean[SD]=73.8[8.5] years) (female=38%; mean[SD]=76.9[7.3] years) participants from the Harvard Aging Brain Study and the Alzheimer’s Disease Neuroimaging Initiative underwent cross‐sectional FTP‐PET (standardized uptake value ratios [SUVrs]). For skull analyses, we created skull ROIs based on signal 12mm from the outer perimeter of voxels in FreeSurfer‐defined tau ROIs. Linear regression models estimated the main effects of sex across cortical tau ROIs while correcting for local skull binding. We simulated PVE by convolving group‐level SUVr means in each ROI with 6mm Gaussian kernels, and then compared the sexes with linear regression models post‐smoothing.ResultWidespread sex differences in skull binding were observed (Table 1). Covarying for skull binding ameliorated weaker sex differences in cortical FTP signal but did not impact the largest effects. Sex differences in PVE were observed in both female and male directions; no clear sex‐related biases in PVE were found to impact cortical tau sex differences except for the rostral middle frontal region (Figure 1).ConclusionOur findings suggest that sex differences in FTP‐PET are not solely attributed to skull ‘clouding’ or PVE, but rather support hypotheses of female‐related tau vulnerability. Nevertheless, as only two potential confounds were investigated, and gross morphology/volumetric issues remain a key concern, further investigation is needed to fully elucidate this phenomenon. Investigations of sex differences in longitudinal tau accumulation (a few preliminary reports already suggest faster rates in females) will add further support to the argument that noise properties inherent in FTP‐PET do not significantly contribute to sex differences in cortical tau signal.
Associations of central auditory processing with brain volumes in the aging and cognitive health evaluation in elders and the atherosclerosis risk in communities neurocognitive study
Authors: Jiang Kening , Albert Marilyn S , Coresh Josef , Couper David , Gottesman Rebecca F , Hayden Kathleen M , Jack Clifford R , Knopman David S , Mosley Thomas H , Pankow James , Pike James R , Reed Nicholas S , Sharrett Richey , Lin Frank R , Deal Jennifer A 
Published: December 2021

AbstractBackgroundPrior evidence has suggested associations between hearing loss and smaller brain volumes particularly in the temporal lobe where the primary auditory cortex is located, probably due to changes in cortical organization associated with reduced auditory stimulation. Evidence regarding associations of central auditory processing with brain volumes is relatively limited. The study aims to investigate cross‐sectional associations of central auditory processing with brain volumes in older adults.MethodWe studied 587 cognitively normal (Mini‐Mental State Exam ≥23 if high school degree or less and ≥25 if above high school degree) older adults (mean age: 77±4 years, 56% female, 17% black), including 426 with hearing loss from the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) baseline (2018‐19), which is an ancillary randomized controlled trial of the Atherosclerosis Risk in Communities (ARIC) Study and 161 with normal hearing, comparable age and cognitive status from the ARIC Visit 6/7 (2016‐17/2018‐19). Brain volumes were measured by magnetic resonance imaging (MRI) scans and were transformed to z‐scores. Central auditory processing was measured by the Quick Speech‐in‐Noise (QuickSIN) test. Total scores range from 0 to 30 with lower scores indicating worse speech‐in‐noise performance. Multivariable‐adjusted linear regression was used to estimate cross‐sectional differences in standardized brain volumes associated with differences in QuickSIN score. Models adjusted for age, sex, race, education, cohort, body mass index, smoking, hypertension, diabetes, stroke, intracranial volume, and pure‐tone average.ResultEvery 5‐point decrease in QuickSIN score (worse performance) was associated with smaller volumes of the temporal lobe (‐0.07SD, 95% CI: ‐0.13, ‐0.01). QuickSIN score was also associated with subregions of the temporal lobe related to auditory processing, memory and emotion, including amygdala (‐0.13SD, 95% CI: ‐0.21, ‐0.04), middle (‐0.08SD, 95% CI: ‐0.15, ‐0.00) and superior temporal gyri (‐0.08SD, 95% CI: ‐0.15, ‐0.01).ConclusionPoorer central auditory processing was associated with smaller temporal lobe volumes, including but not limited to subregions important for auditory processing. The ongoing collection of ACHIEVE data with longitudinal MRI data will facilitate understanding of association between hearing loss and brain atrophy as well as the potential promising effects of hearing treatment in mitigating brain aging.