bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic evidence that the causal association of educational attainment with reduced risk of Alzheimer’s disease is driven by intelligence
Authors: Thorp Jackson G , Mitchell Brittany L , Gerring Zachary F , Ong Jue‐Sheng , Gharahkhani Puya , Derks Eske M , Lupton Michelle K 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) is predicted to affect 132 million people by 2050. Targeting modifiable lifestyle risk factors that are associated with an increased risk of AD could prevent a large proportion of dementia cases, allowing people to reach the end of their life dementia free. However, evidence obtained from observational studies does not take into account how risk factors are correlated with one another, and whether they causally contribute to increased AD risk. In this study, we determine whether the relationship between twelve previously speculated AD risk factors and AD susceptibility is consistent with causality using large‐scale genetic data (table 1).MethodWe conduct multivariable Mendelian Randomization (MR) analyses to identify causal risk factors of AD while controlling for genetic pleiotropy, using genetic instruments from the most well powered GWAS studies currently available. We also use GWAS‐by‐subtraction implemented with genomic structural equation modelling (genomic SEM) to understand the cognitive and non‐cognitive components of the causal association of EA on AD risk.ResultWe identified significant positive correlations between AD and physical activity and loneliness, and significant negative correlations with educational attainment (EA), intelligence and household income. Using GWAS‐by‐subtraction to partition EA into cognitive (intelligence) and noncognitive genetic factors, we showed a significant genetic correlation between AD and the cognitive factor, but not the noncognitive factor (figure 1).Univariable MR found EA, intelligence, household income and the cognitive factor to all be causally protective against AD. Multivariable MR analysis showed that higher intelligence lowers AD risk, independent of EA and household income. There was no evidence that EA lowers AD risk, independent of intelligence. In addition the cognitive (intelligence) component of EA decreased AD risk with no significant influence of the noncognitive factor (table 2).ConclusionFrom the risk factors tested only the cognitive component of EA (i.e., intelligence) is an independent causal risk factor for AD. To reduce incidence of AD this cognitive aspect of EA would need to be modified. It is questionable whether substantial modification of intelligence is achievable through simple interventions such as improving access to extended education.
Higher fiber‐tract myelin levels predict lower longitudinal rates of fibrillar tau independent of amyloid
Authors: Rubinski Anna , Franzmeier Nicolai , Dewenter Anna , Luan Ying , Smith Ruben , Strandberg Olof , Ossenkoppele Rik , Dichgans Martin , Hansson Oskar , Ewers Michael ,   Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: December 2022

AbstractBackgroundFibrillar tau progresses from initial epicenters of high tau accumulation to closely connected cortical regions during the course of Alzheimer’s disease (AD). Myelin ensheaths the interregional axonal connections, where ontogenetically late and thinly myelinated fibers are more susceptible to damage and may propel the propagation of fibrillar tau, as suggested by post‐mortem data (https://doi.org/10.1093/brain/awv236). Here we tested for the first time, in two independent samples of AD patients whether 1) regions connected to epicenters by more thickly myelinated fiber tracts show lower rates of tau‐PET accumulation, and 2) differences in regional amyloid‐PET levels explain the association between myelin and tau‐PET accumulation.MethodsWe included two independently recruited samples with longitudinal AV1451‐tau‐PET of amyloid‐PET positive non‐demented and demented individuals (ADNI: n = 123, mean FU = 1.53[0.69‐3.95] years; BioFINDER: n = 39, mean FU = 1.87[1.21‐2.78] years). Adopting our previously established connectivity‐based prediction approach (https://doi.org/10.1126/sciadv.abd1327), we first determined tau epicenters by selecting the top 10% ROIs with highest tau‐PET uptake. Next, we computed for each tau epicenter the connectivity‐based distance to the ROIs in the remainder of the brain, based on resting‐state fMRI data from the Human Connectome Project (HCP). To determine the myelin levels in the underlying fiber tracts, we reconstructed fiber‐tracts for each epicenter‐to‐ROI pair based on DWI data from HCP and extracted regional myelin‐water‐fraction (MWF) values for each tract from an overlaid myelin‐water‐imaging atlas (https://doi.org/10.1111/jon.12657). In order to test whether fiber tract myelination attenuates the connectivity‐based tau‐spreading, we tested the interaction between epicenter connectivity‐based distance and MWF in the corresponding fiber‐tracts on the rate of tau‐PET accumulation in the connected regions. In a sensitivity analysis restricted to the sufficiently powered ADNI‐sample, we controlled the interaction analysis for regional amyloid‐PET levels within target ROIs.ResultsWe found a significant interaction of connectivity‐based distance by fiber‐tract MWF on the rate of tau‐PET accumulation (ADNI: β = 2.08, p = 0.009; BioFINDER: β = 1.876, p = 0.028; Figure 1), such that regions connected by highly myelinated fiber‐tracts showed lower rates of connectivity‐dependent tau accumulation. When controlling for regional amyloid‐PET levels, the interaction remained significant (ADNI: β = 2.23, p = 0.006).ConclusionHigher fiber‐tract myelination is associated with lower rates of tau progression in AD, independent of beta‐amyloid.
Orthostatic hypo‐ and hyper‐tension are associated with cognitive decline: the S.AGES cohort
Authors: Strumia Mathilde , Vidal Jean‐Sebastien , Hanon Olivier , Rouch Laure 
Published: December 2022

AbstractBackgroundThe association between orthostatic hypotension (OHYPO) and cognition has reported conflicting results. Although orthostatic hypertension (OHYPER) is an emerging cardiovascular risk factor, only very few studies investigated its association with cognition. We aimed to assess the impact of OHYPO and OHYPER on cognitive performances in non‐institutionalized subjects aged ≥ 65 years.MethodThe S.AGES (Sujets Âgés) cohort followed for three years non‐institutionalized subjects aged ≥ 65 years without major neurocognitive impairment at inclusion. OHYPO was defined as a decrease in systolic blood pressure (SBP) of at least 20 mmHg and/or diastolic blood pressure (DBP) of at least 10 mmHg from a sitting to a standing position. In contrast, OHYPER was defined as an increase in SBP of at least 20 mmHg and/or DBP of at least 10 mmHg under the same measurement conditions. Cognition was assessed using the Mini‐Mental State Examination (MMSE). Linear mixed models were used for the analyses.ResultWe included 3,170 subjects (mean age 78 years, 56% women). 209 (6.5%) had OHYPO at inclusion and 226 (7.1%) had OHYPER. Over time, MMSE was on average 0.5 points lower in patients with OHYPO compared to those without OHYPO or OHYPER (adjusted β [IC95%] = ‐0.52 [‐0.97; ‐0.08], p = 0.021) after adjustment for age, sex, education, baseline body mass index, smoking, alcohol intake, atrial fibrillation, congestive heart failure, transient ischemic attack or stroke, coronary artery disease, type 2 diabetes, dyslipidemia, seated SBP/DBP and antihypertensive treatment. Similarly, patients with OHYPER had, on average, poorer cognitive performances over time compared to those without pathological blood pressure (BP) postural changes (adjusted β [IC95%] = ‐0.54 [‐0.98; ‐0.09], p = 0.017).ConclusionBoth OHYPO and OHYPER were associated with cognitive decline. Considering that BP postural changes are common in the elderly and easy to detect, orthostatic BP measurements could help identify patients with greater risk of cognitive impairment.
Evaluation of Longitudinal [18F]GTP1 Tau Burden Metrics in the Tauriel Phase II Study
Authors: Bohorquez Sandra Sanabria , Manser Paul T , Baker Suzanne L. , Blendstrup Mira , Pickthorn Karen , Teng Edmond 
Published: December 2022

AbstractBackgroundConventional measures of tau PET longitudinal change focus on SUVR. However, a small (n=57) observational [18F]GTP1 study including a broad range of Alzheimer’s disease (AD) participants suggested tau Extent and Load could measure disease progression over 12 months with greater precision than SUVR. We assess the performance of these metrics in a larger 73‐week study in prodromal‐to‐mild AD.MethodsWe analyzed 109 prodromal (pAD) and 180 mild (mAD) [18F]GTP1 scans in the semorinemab Phase 2 Tauriel study (NCT03289143). Quantification was performed using the cerebellum as reference. In a given ROI, extent was defined as the fraction of voxels above a scan‐specific threshold (mean cerebellar gray SUVR plus 2 standard deviations). Load was defined as Extant multiplied by the product of the mean SUVR of above‐threshold voxels. Analyses included the whole cortical gray (WCG), temporal meta‐ROI (excluding Braak 1/2, TMP), and Braak ROIs. As no treatment effects were observed with semorinemab, data were pooled across treatment and placebo arms. Relationships between endpoints were assessed with Spearman correlations (ρs), and endpoints changes were compared using Cohen’s D effect size (ES).ResultsAt baseline, a slightly higher correlation was observed between SUVR and Load (ρs=0.89‐0.97) than between SUVR and Extent (ρs=0.64‐0.91) partly due to the smaller dynamic range for Extent in high‐tau burden regions (Figure 1). Longitudinal changes were correlated and consistent across endpoints (Figure 2). Extent ES values were lower than SUVR and Load ES, which showed similar performance (Table 1). Prognostic associations with baseline WCG measures were similar in pAD and mAD for predominantly cognitive measures ADAS‐COG and RBANS. Weaker prognostic associations were observed for CDR‐SB and ADCS‐ADL incorporating functional status (Table 2).ConclusionHigher baseline tau burden was associated with faster clinical decline in pAD and mAD. There was not obvious advantage of using Extent or Load; [18F]GTP1 SUVR is a robust measurement for assessing longitudinal change in multi‐site clinical trials settings.Figure 1. Relationship between tau burden metrics.Figure 2. Relationship between change in tau burden.Table 1. Cohen’s D ES±95%CI of imaging endpoints change over 73 weeks.Table 2. Prognostic associations of baseline WCG tau burden measurements with cognitive change measures.
Understanding Alzheimer’s disease resilience at the cellular level
Authors: Castanho Isabel , Yeganeh Pourya Naderi , Hide Winston 
Published: December 2022

AbstractBackgroundUntil recently, postmortem observation of amyloid beta (Aβ) and tau neurofibrillary tangles was sufficient for a definitive diagnosis of AD. Observations of resilient subjects exhibiting Alzheimer's‐associated neuropathology but no dementia have challenged this concept. Understanding the molecular mechanisms of resilience can provide a powerful suite of targets for therapeutic interventions.MethodBuilding upon our studies of bulk brain transcriptional signatures of AD resilience, and in order to identify cell‐specific signatures, we have leveraged recently available single nucleus RNA‐seq data (n = 30) from the Religious Order Study and Memory and Aging Project (ROSMAP) to perform differential gene expression analyses. We classified individuals into AD, Resilience (RES), and Control (CTRL) using levels of Aβ plaques and neurofibrillary tangles, and presence/absence of cognitive impairment.ResultResilience signatures are shared between different cell types, but few are broadly distributed. Certain cell types show higher response to early events (e.g., excitatory neurons), while others seem to be particularly important in driving resilience to AD (e.g., inhibitory neurons and oligodendrocytes). Among cell‐specific differences, we noticed patterns where cells from the RES group had an opposing direction compared to AD and CTRL, suggesting protective events, or even resistance to AD neuropathology. For instance, in excitatory neurons, we identified 1,437 differentially expressed genes (DEGs) between RES/CTRL and 179 DEGs between AD/RES. CAMK2N1 (codes for an inhibitor of CaMKII, a synaptic protein pivotal in learning and memory) shows decreased expression between RES/AD and RES/CTRL. In contrast, in inhibitory neurons we identified 759 DEGs between RES/AD, and 46 DEGs in RES/CTRL. CRLF3 (encodes a cytokine receptor‐like factor thought to negatively regulate cell cycle progression, involved in neuronal morphology and synaptic vesicle biogenesis) exhibits increased expression in RES compared to AD and CTRL. For in silico cross‐validation, we determined if features identified as ‘markers of resilience’ were good predictors by comparing to the original diagnostic group. Our results suggest that oligodendrocytes are important drivers of AD resilience.ConclusionWe have identified cell‐specific gene expression signatures of AD resilience, suggesting inhibitory neurons and oligodendrocytes as critical drivers of AD resilience.
Subjective cognitive decline and clinical progression in the memory clinic: The value of longitudinal self‐ and informant‐report in the SCIENCe project
Authors: Dubbelman Mark A. , Sikkes Sietske A.M. , Ebenau Jarith L. , van Leeuwenstijn Mardou , Kroeze Lior A. , van Berckel Bart NM , Teunissen Charlotte E. , van Harten Argonde C. , van der Flier Wiesje M. 
Published: December 2022

AbstractBackgroundAmong memory clinic patients who report the experience of subjective cognitive decline (SCD), only a small percentage are in a preclinical stage of Alzheimer’s disease (AD). We aimed to investigate how longitudinal self‐ and informant report of SCD relate to AD biomarkers and clinical progression.MethodWe followed 409 individuals with SCD (63±9 years, n = 180 (44%) female, MMSE 27.7±4.6) from the SCIENCe project over time, with yearly visits (n observations = 1,436, 2.7±1.7 years follow‐up). At baseline, amyloid was measured in cerebrospinal fluid or using amyloid positron emission tomography scans (n = 328, 80%) and dichotomized into positive (n = 100, 30%) or negative for AD (n = 228). We assessed degree of subjective complaints using both self and informant‐reported Cognitive Change Index (CCI). Using linear mixed models with random intercepts and slopes, CCI‐self and CCI‐informant were related to time and amyloid. In Cox regressions, we investigated the association between dichotomized baseline CCI and clinical progression to MCI or dementia (progressors n = 25). Models were adjusted for age, sex and education.ResultAt baseline, CCI‐self (intercept [95% confidence interval (95%CI)] = 45.20 [33.94, 56.43]) were higher than CCI‐informant scores (intercept [95%CI] = 45.39 [32.59, 58.15]). CCI‐informant scores of amyloid positive participants increased over time (estimate [95%CI] = 1.8 [0.5, 3.1]) whereas they did not in amyloid negative participants (estimate [95%CI] = ‐0.6 [‐1.3, 0.2]; Table 1). CCI‐self scores decreased in amyloid negative, but not in amyloid positive participants, although the rates of change did not differ significantly from each other (amyloid‐time interaction = 1.0, 95% confidence interval (95%CI) = [‐0.3, 2.2]; Figure 1, Table 1). High baseline CCI‐informant (hazard ratio (HR) = 4.8, 95%CI = [1.1, 21.4]), but not CCI‐self (HR = 5.3, 95%CI = [0.7, 40.5]), was associated with a higher risk of clinical progression.ConclusionOur results highlight the value of longitudinal self and informant‐report in the measurement of SCD. We found an effect of amyloid positivity on change in informant‐reported CCI and informant report also predicted clinical progression. Rates of change in self‐reported CCI scores did not differ significantly between amyloid positive and negative participants, which may hint at a waning awareness among those individuals with SCD due to AD pathology. Our work implies that informant‐report may be especially valuable in longitudinal studies.
Contributions of remote, unsupervised dyadic subjective measures to identify older adults with Mild Cognitive Impairment
Authors: Nosheny Rachel L , Jin Chengshi , Knight Krissy N , Banh Timothy , Howell Taylor , Truran‐Sacrey Diana , Fockler Juliet , Bui Chau L , Gummadi Shilpa L , Santhakumar Jess , Ashford Miriam T. , Camacho Monica R , Flenniken Derek , Roberson Erik D , Morris John C. , Moulder Krista L. , Li Yan , Petersen Ronald C. , Stricker Nikki H. , Rabinovici Gil D. , Carrillo Maria C. , Neuhaus John , Mackin R Scott , Weiner Michael W. 
Published: December 2022

AbstractBackgroundDyadic (self and study partner) subjective reports of an individual’s recent cognitive and functional decline are an efficient approach to facilitate identification of older adults with, and at risk for, Mild Cognitive Impairment (MCI). Such methods can be easily adapted for remote administration, but few studies have investigated the ability of remotely‐collected, unsupervised dyadic subjective reports to accurately detect MCI and cognitive decline.MethodsIn 289 older adults enrolled in the Brain health Registry (BHR), with clinically‐confirmed diagnoses of Cognitively‐unimpaired (CU) or MCI, we identified the optimal combination of remote measures to accurately distinguish CU from MCI. We then externally validated our predictive model in 217 participants enrolled in a separate cohort, Validation of Online Methods to Predict Cognitive Decline (eVAL). Predictors included Cogstate Brief Battery One Card Learning (OCL) accuracy; self‐ and study partner‐reported memory concern (SMCs); performance on online adaptations of Everyday Cognition Scale (ECog, self‐ and study partner‐report versions), Geriatric Depression Scale Short Form (GDS); family history of AD, age, gender, and education. We calculated 10‐fold cross validated area under the ROC curves (cvAUC), 95% confidence intervals (CI), and the percentage of participants correctly classified (accuracy) for all models. Likelihood ratio (LR) tests were used to compare model fits.ResultsIn the BHR cohort, models including dyad‐report ECog, family history of AD, GDS, and Cogstate OCL scores distinguished CU from MCI with the highest accuracy (cvAUC = 0.90; 95% CI = 0.83, 0.92; accuracy = 85.5%). Models excluding study partner‐report ECog distinguished diagnostic groups with moderate accuracy (cvAUC = 0.83; 95% CI = 0.78, 0.85; accuracy = 75.9%) When applied to the validation cohort, the optimal training model including dyadic report performed with moderate accuracy (
Table 2
). In the validation cohort, inclusion of study partner (but not self) report SMC, in addition to dyadic‐report ECog, improved model fit (LR test p<0.01).ConclusionsRemotely‐collected dyadic subjective measures, along with other remote measures, accurately distinguish CU from MCI. Subjective cognitive and functional decline and concerns about memory problems independently contribute to diagnostic discrimination. Results support future utilization of remote dyadic subjective measures to efficiently identify older adults with MCI for prodromal AD clinical trials, and in clinical care settings.
Importance of accounting for regional differences in modifiable risk factors for Alzheimer’s disease and related dementias: The case for tailored interventions in California
Authors: Hoffmann Coles M , Nianogo Roch A , Rosenwohl‐Mack Amy , Yaffe Kristine , Carrasco Anna , Barnes Deborah E 
Published: December 2022

AbstractBackgroundWe previously estimated that 37% of Alzheimer’s disease and related dementias (ADRD) cases in the U.S. may be attributable to modifiable risk factors, and that the most important risk factors differ based on race/ethnicity, but it’s not known whether national estimates generalize to specific states or regions. The aim of the present study was to (1) compare the proportion of ADRD cases that are potentially attributable to modifiable risk factors in California, to the U.S., overall and by sex and race/ethnicity, and (2) to estimate how many cases are potentially preventable by reducing the prevalence of key modifiable risk factors by 25%.MethodParticipants included adults ≥18 years from the California (n = 9,836) and the U.S. (n = 378,615). We calculated population attributable risks (PARs) using prevalence data from the national and California Behavioral Risk Factor Surveillance Survey (BRFSS) and relative risks from recent meta‐analyses. We estimated individual and combined PARs for ADRD in California and compared them to our U.S. estimates.ResultsIn California, overall, 29% of ADRD cases were potentially attributable to the combination of 8 modifiable risk factors evaluated in this study, compared to 37% in the U.S. The top 3 ADRD risk factors were the same in California and the U.S., but their relative importance differed (low education [CA:15%; U.S.:12%], midlife obesity [CA:15%; U.S.:17.7%], and physical inactivity (CA:10%; U.S.:12%). The combined PAR was lower in California compared to the U.S. in men (CA:28%; U.S.:36%) and Blacks (CA: 30%; U.S.:40%), but was similar in women and other race/ethnic groups. This was primarily due to lower risk factor prevalence within these groups. Low education was especially important in the Hispanic population (CA:30%; U.S.:26%). The total number of ADRD cases currently attributable to combined risk factors was 199,246 in California and 2,287,683 in the U.S. If the combined risk factors were reduced by 25%, we could potentially prevent approximately 40,665 cases in California and 445,737 in the U.S.ConclusionThe potential impact of modifiable ADRD risk factors differed in California and the U.S., overall and within sex and race/ethnic groups, highlighting the importance of tailoring dementia risk reduction campaigns.