bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trajectories of cognitive activity from early to late life and risk of Alzheimer’s dementia in community‐dwelling older adults
Authors: Dhana Klodian , Rajan Kumar B , Zammit Andrea R , Wilson Robert S , Liu Xiaoran , Aggarwal Neelum T , Leurgans Sue E , Bennett David A , Barnes Lisa L 
Published: December 2021

AbstractBackgroundWe used a life‐course approach to investigate the relationship between trajectories of cognitive activity from early to late‐life with the risk of Alzheimer’s dementia and elucidate a critical age window during which cognitive activities may exert most of their favorable effects.MethodThe investigation was based on 1,817 older persons without dementia participating in the Rush Memory and Aging Project, a community‐based clinical‐pathologic study. Participants underwent annual clinical evaluations including questions about cognitive activity over the life‐course. Latent class trajectory analyses were used to develop trajectories of cognitive activity from childhood (6‐12y), young adult (18y), middle‐adult‐life (30‐40y), to late‐life (>65y). Clinical diagnosis of Alzheimer’s dementia was determined using standard criteria. Multivariable adjusted Cox proportional hazard models were used to estimate the hazard ratio(HR) and 95% confidence interval (CI) of trajectories of cognitive activity and Alzheimer’s dementia.ResultThe average age of study participants was 80 years, 75% were women, and the mean education was 15 years. We identified three groups of participants with distinct trajectories of cognitive activity from early to late‐life. The largest group of individuals (n=1,614, 88.8%) showed steady cognitive activity levels over time – we named this group “stable‐high.” The second group comprised 131 (7.2%) individuals who experienced an increase in cognitive activities after the age of 40 years –‐ the “moderate‐progressive‐increase.” The third group included 72 (4%) individuals who initially engaged in high cognitive activities in early life but then experienced a substantial decrease during middle‐age – the “marked‐decrease” group. During 10 years of follow‐up, 358 (19.7%) of the participants were clinically diagnosed with Alzheimer’s dementia. Compared to individuals in the marked‐decrease group, the risk of Alzheimer’s dementia was 44% lower (HR 0.56, 95%CI 0.37‐0.86) among individuals in the stable‐high group and 53% lower (HR 0.47, 95%CI 0.27‐0.83) in those in the moderate‐progressive‐increase group.ConclusionUsing the latent trajectory approach, we identified three distinct cognitive activity trajectories from early to late‐life. These trajectories were differently associated with the risk of Alzheimer’s dementia, suggesting that high cognitive activity starting in middle adult life is protective against Alzheimer’s dementia.
Sharper in the morning: Cognitive sundowning revealed with high‐frequency smartphone testing
Authors: Wilks Hannah M , Aschenbrenner Andrew J. , Gordon Brian A. , Balota David A. , Fagan Anne M. , Balls‐Berry Joyce E , Benzinger Tammie L.S. , Cruchaga Carlos , Morris John C. , Hassenstab Jason 
Published: December 2021

AbstractBackgroundIn Alzheimer’s disease (AD), patients and caregivers often report a pattern of increasing cognitive and behavioral difficulties in evening hours, known colloquially as “sundowning.” Here, we describe the first known attempt to capture circadian fluctuations in cognition in humans at risk for AD using a novel smartphone assessment that samples cognition rapidly and repeatedly over a 7‐day period. We hypothesized that cognitive sundowning would manifest among individuals with abnormal AD biomarkers, even in preclinical stages of AD.MethodsOlder adults (N=168, Ages 61‐94 years) were asked to complete 4 brief smartphone‐based testing sessions per day for 7 consecutive days at quasi random intervals throughout the day, from morning until evening. Tests included associate memory, processing speed, and visual working memory tasks (Figure 1). Cerebrospinal fluid biomarkers for beta amyloid (Ab42) and phosphorylated tau181 (ptau) were collected within ∼3 years of smartphone tests. Scores from morning hours (range ∼5am – 12pm) were averaged for comparison with averaged scores from evening hours (after 12pm). Mixed effect models evaluated time of day effects by CSF biomarker status and clinical status.ResultsParticipant characteristics are provided in Table 1. Models with terms for age, gender, education, APOE e4 status, and Clinical Dementia Rating™ Sum of Boxes tested the interaction between time of day and CSF ptau/Ab42 ratio in predicting cognition (Figure 2). Compared to those with normal biomarkers, participants with abnormal CSF ptau/Aβ42 ratio had worse associate memory (p=0.03) and processing speed performance (p=0.026) in evening hours. On processing speed, participants with abnormal ptau/Aβ42 ratios were slower by an average of 700ms in the evening compared to those with normal ptau/Aβ42 ratios tested in morning hours. When models were run in cognitively normal participants only, a similar pattern was observed, confirming the hypothesis that increasing loads of AD pathology result in worse cognitive performance in evening hours prior to symptom onset.ConclusionOur results provide the first known evidence of cognitive sundowning in preclinical and early symptomatic AD and suggest that time of day is an important consideration for studies of cognition in AD populations.
SavaDx, a novel plasma biomarker to detect Alzheimer’s disease, confirms mechanism of action of simufilam
Authors: Wang Hoau‐Yan , Pei Zhe , Xu Qiang , Brunelle Lynn A , Burns Lindsay H. , Thornton George Ben 
Published: December 2021

AbstractBackgroundThe diagnosis and management of Alzheimer’s disease (AD) would be greatly aided by sensitive, accurate and scalable biomarkers. SavaDx is proposed as a novel plasma diagnostic/biomarker candidate for Alzheimer’s disease. SavaDx detects altered filamin A, a previously described proteopathy in AD. SavaDx was evaluated as an exploratory endpoint in a clinical trial of simufilam, a drug candidate for AD that targets and reverses altered filamin A, the proteopathy detected by SavaDx.MethodSavaDx was evaluated in a multi‐center, randomized, controlled trial of simufilam completed in 2020. This Phase 2b study enrolled 64 patients with mild‐to‐moderate AD, MMSE 16 to 26 and CSF total tau/Aβ42 ratio ≥ 0.28. Patients were randomized (1:1:1) to placebo, 50 mg, or 100 mg b.i.d. oral simufilam for 28 days. CSF and blood samples were collected at baseline and Day 28. Plasma p‐tau181 was measured in duplicate by SIMOA®. Data with Coefficients of Variation >11% were repeated and excluded if >15% on repeat. Biomarker analyses were conducted blind to treatment. Day 1 and Day 28 samples for each patient were analyzed together. SavaDx, a non‐published investigational assay, was used to estimate altered filamin A levels in brain.ResultThis Phase 2b study met all co‐primary CSF biomarker endpoints, as previously reported. Simufilam 50 mg and 100 mg twice daily significantly improved eleven CSF biomarkers of AD pathology, neurodegeneration and neuroinflammation, baseline to Day 28 versus placebo. SavaDx values decreased 44% and 48% in the 50 and 100 mg arms, respectively, (p=0.02 and p=0.005 versus placebo) versus a 3% decrease in the placebo arm. Plasma p‐tau181 values decreased 15% and 17% in the 50 and 100 mg arms, respectively (both p<0.05), versus a 20% increase in placebo.ConclusionSavaDx detected treatment effects in a randomized, controlled trial of simufilam, a drug candidate that targets and reverses a critical proteopathy in AD. These data offer quantitative evidence of drug‐target engagement in patients, confirming simufilam’s mechanism of action. These data also suggest the use of the SavaDx assay to detect and monitor AD in plasma. This work was funded by NIA grants AG057329 and AG060878.
Forecasting progression of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) with digital twins
Authors: Bertolini Daniele , Loukianov Anton D. , Smith Aaron , Li‐Bland David , Pouliot Yannick , Walsh Jonathan R. , Fisher Charles K. 
Published: December 2021

AbstractBackgroundMachine learning models can leverage historical data to forecast disease progression. These predictions can be integrated in clinical trial design to reduce sample size or increase power, speeding up the evaluation of new drugs. This is especially critical in AD where trials face challenges with enrollment and where no new therapies have emerged in 18 years. Recently, there has been a shift towards evaluating drugs in earlier stages of the disease using Clinical Dementia Rating Sum‐of‐Boxes (CDR‐SB) as the primary endpoint. We present a model that includes CDR‐SB and spans a broad range of baseline disease severity from MCI to mild‐to‐moderate AD.MethodWe used nearly 7,000 clinical records from placebo arms of AD clinical trials (in the C‐Path Online Data Repository for AD) and from observational studies (in the AD Neuroimaging Initiative) to train Conditional Restricted Boltzmann Machines (CRBMs). A CRBM is a generative machine learning model that learns a multivariate distribution over the relevant variables, and is particularly suited to model clinical data. A CRBM generates Digital Twins ‐ synthetic clinical records with baseline characteristics matched to those of actual trial subjects describing their likely progression under standard‐of‐care (SOC) with/without placebo. These forecasts include all components of CDR‐SB, Alzheimer’s Disease Assessment Scale ‐ Cognitive Subscale (ADAS‐Cog11) and Mini Mental State Examination (MMSE), along with other variables including labs, vitals, and biomarker status. We evaluated Digital Twins on a held‐out portion of the dataset (not included in the training dataset), stratified by baseline ADAS‐Cog11. For each variable, the mean change from baseline +/‐ 95% confidence interval error at 3‐month intervals was estimated by drawing 100 Digital Twins for each subject and averaging over the population.ResultCRBM‐generated predictions of ADAS‐Cog11, MMSE, and CDR‐SB progression up to 18 months were consistent within 95% confidence intervals with actual data across all scores, timepoints, and cohorts.ConclusionDigital Twins accurately model MCI and AD subjects’ progression on SOC with/without placebo across a broad range of baseline disease severity, and can be integrated into clinical trials as prognostic scores to increase power or reduce sample size required to achieve desired power.
In vivo detection of changes related to cortical columnar organization across the AD continuum
Authors: Torso Mario , Hardingham Ian , Schwarz Adam J. , Chance Steven A 
Published: December 2021

AbstractBackgroundRecent studies have suggested intriguing biphasic trajectories of cortical structural changes in both sporadic and autosomal‐dominant Alzheimer’s disease (AD), namely decreased mean diffusivity (MD) and increased cortical thickness in cognitively normal, amyloid positive individuals, ahead of increases and decreases, respectively, in these parameters in cognitively impaired stages of the disease. To better understand these observations, we assessed novel diffusion tensor imaging (DTI) metrics that are correlated with disruption of cortical minicolumns ‐ the units of cortical microstructure. These have previously been shown to be associated with protein deposition and synaptic and neuronal loss. Such cytoarchitectural changes offer potential pathological markers before alterations at the macrostructural level.MethodTwenty‐four amyloid‐negative controls (CN‐), 28 amyloid‐positive controls (CN+), 46 amyloid‐positive subjects with Mild cognitive Impairment (MCI+) and 22 amyloid‐positive subjects with Alzheimer’s disease from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used. 3DT1 and DTI scans at 2 timepoints (baseline and 24‐month follow‐up) were used to calculate the cortical MD and three novel cortical diffusivity measures, namely: the angle between the radial minicolumnar direction and the principal diffusion direction (AngleR); the diffusion components perpendicular to the minicolumns (PerpPD), and the principal diffusion component parallel with the minicolumns (ParlPD). Mixed effect models were used to investigate cross‐sectional and longitudinal differences.ResultAt a whole‐brain level, the mixed effects models revealed a significant effect of diagnostic group in all the measures (all p‐values<0.001). The pairwise (Figure 1) comparisons showed AngleR differed between CN‐ and CN+ (p<0.005), between CN+ and MCI+ (p<0.005) and between CN+ and AD+ (p<0.001). PerpPD values were significantly different between CN‐ and MCI+ (p<0.05) and AD+ groups (p<0.001), CN+ and MCI+ (p<0.005) and AD+ groups (p<0.001) while differences between CN‐ and CN+ were not significant. No significant difference was found between the timepoints for any measures, although the direction of change indicated progression between the first and second assessments.ConclusionCortical diffusivity parameters reflecting cortical minicolumnar organization may provide a more sensitive and biologically interpretable measurement of cortex quality and microstructure across the AD continuum.
Neuropsychological test performance in former college and professional American football players
Authors: Culhane Julia E , Barr William , Wethe Jennifer , Banks Sarah J , Miller Justin B , Adler Charles , Balcer Laura , Bernick Charles B. , Palmisano Joseph , Tripodis Yorghos , Cummings Jeffrey L. , Reiman Eric M. , Shenton Martha E , Stern Robert A , Alosco Michael L 
Published: December 2021

AbstractBackgroundRepetitive head impacts from American football have been associated with long‐term cognitive symptoms. The late neuropsychological profiles of this population is not well‐characterized. Research has relied on retrospective informant reports and/or has been small samples of former professional players. We describe objective neuropsychological test performance in former college and professional American football players.MethodsMale (45‐74 years) former National Football League (n=107) and college football players (n=59) from the DIAGNOSE‐CTE Research Project completed a neuropsychological test battery, Functional Activities Questionnaire (FAQ) and Quick Dementia Rating Scale (QDRS). Neuropsychological test scores were converted to T‐scores using age, sex, and/or education‐adjusted normative data. T‐scores<35 defined impairment. Participants were enrolled across the spectrum of symptom severity (asymptomatic to dementia). Individuals without decisional capacity were excluded. Participants with missing data (n=4) and who scored <45 on Test of Memory Malingering Trial 2 (n=10) were excluded.Results108 (65.1%) identified as White and 53 (31.9%) as Black. Mean education years was 16.76 (SD=1.48). Fourteen (8.4%) and 6 (3.6%) reported diagnostic history of ADHD and learning disability, respectively. Average Montreal Cognitive Assessment score was 24.96 (SD=3.17); 85 (51.2%) scored <26. Impairment rates were highest for learning and episodic memory. On Neuropsychological Assessment Battery List Learning, 29.5% were impaired on Immediate recall, 36.1% on Short Delay, and 44.0% on Long Delay Recall. Impairment rates for Craft Story Immediate and Delayed Recall (Paraphrase) were 15.7% and 18.7%, respectively. 19.9% and 15.7% were impaired on learning and delayed recall of the Brief Visuospatial Memory Test‐Revised. Impairments were frequent on the Multilingual Naming Test (20.5%), Trail Making Test Parts B (19.3%) and A (18.1%), Animal Fluency (15.7%), and Number Span Backward (15.1%). Impairments were less common (<10%) for phonemic fluency, planning, basic attention, and visual‐perceptual abilities, Mean FAQ was 3.11 (SD=5.14); 23 (13.9%) had an FAQ >9. Based on QDRS scores, 66 (39.8%) had mild cognitive impairment, 44 (26.5%) mild dementia, and 6 (3.6%) moderate dementia.ConclusionsIn these former American football players, neuropsychological impairments were most frequent in episodic memory, followed by confrontation naming and executive function. Further research is needed to delineate this population’s unique neuropsychological profile.
Concordance between [18F] GTP1 PET and fluid tau biomarkers in the Tauriel phase II Study
Authors: Toth Balazs , Teng Edmond , Manser Paul T. , Bohorquez Sandra Sanabria , Schauer Stephen , Lee Julie , Blendstrup Mira , Pickthorn Karen , Wildsmith Kristin R. 
Published: December 2021

AbstractBackgroundThe Tauriel Study (NCT03289143) was a Phase 2 randomized, double‐blind, placebo‐controlled, parallel‐group clinical trial that assessed the safety and efficacy of semorinemab in patients with prodromal‐to‐mild Alzheimer’s disease. We examined the concordance of fluid tau biomarkers with Tau PET for the identification of patients with high tau burden at enrollment.MethodTau at baseline was assessed by [18F]GTP1 PET imaging and assays for multiple CSF and plasma tau indices, including pTau181 and mid‐domain tTau (Elecsys assays), tau peptides 2‐24 and 93‐105 (anti‐peptide capture mass‐spec assay), and phosphotau/unphosphorylated tau217 ratio (mass‐spec assay). The association between imaging and fluid tau levels were assessed with Spearman correlations. AUC, sensitivity and specificity are reported in the context of predicting tau burden with a single fluid biomarker, where ‘high tau’ is defined as GTP1 temporal meta‐ROI SUVR ≥1.3. Cutoffs were derived using Youden’s index.Result354 participants had both PET and plasma samples; 68 subjects had paired PET and CSF data. GTP1 significantly correlated with each fluid marker, highly with pT217 (r = 0.78), moderately with other CSF assays (r = 0.44 ‐ 0.56) and weakly with plasma tTau (r = 0.19) (Table 1). Discrimination was highest for CSF pTau217 ( AUC = 0.909). Specificity was 0.862 and 0.84 for pTau181 and pTau217 respectively, while sensitivity was 0.564 and 0.868 (Figure 1). Empirically defined cutoffs were 36.88 pg/mL for pTau181 and 0.052 for pT217.ConclusionBaseline Tau PET is shown to be prognostic for future cognitive decline and thus could be included in enrollment criteria for future clinical studies in AD. Alternative approaches include the use of fluid biomarkers for tau. While pTau181 and n‐terminal tau indices can only be optimized for either high specificity or high sensitivity, both can be concurrently optimized using pTau217, thus positioning it as a potential alternative marker for Tau pathology. Additional CSF and plasma tau indices are pending similar analyses.
Cognitive testing for early detection of Alzheimer's disease in people with Down syndrome: A systematic review and meta‐analysis
Authors: Nadeau Patricia Alves , Boller Benjamin 
Published: December 2021

AbstractBackgroundImproved health care for people with Down syndrome (DS) has resulted in an increase in their life expectancy therefore increasing comorbidities associated with age related problems in this population, the most frequent being Alzheimer's disease (AD). The development of brain lesions appears years before AD. Through this progressive neuronal loss, patients can firstly begin to have a perception of cognitive difficulties, i.e., a subjective cognitive decline (SCD). This preclinical phase ends with the onset of mild cognitive impairment (MCI) which is characterized by a set of cognitive symptoms. Knowing that people with DS have already pre‐existing cognitive deficits, screening at the preclinical and clinical stages of AD therefore cannot be done through traditional cognitive tests. The aim of this systematic review is to synthesis cognitive assessment for the diagnosis of AD, MCI or SCD in people with DS.MethodA meta‐analysis is in development. Articles were collected from Pubmed and Psychinfo databases through keywords related to three categories: 1) DS, 2) AD and 3) assessment. The inclusion criteria are studies 1) with participants over 18 years old with DS, 2) which assess cognitive abilities in the context of screening for AD or its early stages, 3) presenting the effect sizes or data allowing their calculation.ResultEighteen articles met the inclusion criteria. Fifty cognitive tests for the diagnosis of AD, MCI or SCD were found. From these tests, fourteen evaluated cognition through an informant questionnaire and thirty‐six directly evaluated the patient’s cognitive abilities.ConclusionTheoretical and practical implications of these results are discussed.
Clinical subtypes of frontotemporal dementia show different patterns of cortical atrophy
Authors: Fonov Vladimir S , Dadar Mahsa , Manera Ana Laura , Ducharme Simon , Collins Louis 
Published: December 2021

AbstractBackgroundFrontotemporal dementia (FTD) is a progressive neurodegenerative disorder associated with atrophy of the frontal and/or anterior temporal lobes, it is highly heterogeneous and represents about 5% of all cases of dementia and it is one of the most common causes of early‐onset dementia (Onyike and Diehl‐Schmid, 2013). FTD syndromes can be divided into three major groups: the behavioral variant (bvFTD) characterised by prominent early behavioral and personality changes, and the two language variants: the semantic variant (svFTD) and the non‐fluent primary progressive aphasia (pnfaFTD).MethodIn our study we used MRI scans from a frontotemporal lobar degeneration neuroimaging initiative (FTLDNI) database: 133 age and sex matched controls, 70 bvFTD, 36 svFTD and 30 pnfaFTD. Each scan was pre‐processed (Intensity normalization, N3, linear registration, brain masking); tissue classification was performed using BISON (Dadar 2020). All scans were then processed using FALCON (Fonov 2020) to extract its cortical surface anc calculate thickness. Statistical analysis was performed on vertex level.ResultFigure 1 shows relative cortical difference between groups relative to controls, Figure 2 shows areas of significant differences (FDR 1%): the decrease of cortical thickness in the bvFTD group was located in frontal lobes, bilaterally as well as the temporal poles (specially in medial frontal and dorsolateral prefrontal areas). In svFTD, however, cortical thinning is limited to the anterior and lateral temporal lobe, predominantly on the left side. Finally, pnfaFTD shows left sided cortical thinning in prefrontal and Broca’s areas.ConclusionThe identification of predicted patterns of atrophy in each FTD subtype supports the validity of FALCON as an accurate tool to measure cortical changes in neurodegenerative disease. FALCON could be a useful tool for the development of the biomarkers associated with disease and improve understanding of disease progression.