bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence and participant characteristics associated with subjective memory complaint: Results from the Maule Cohort
Authors: Oyarzun‐Gonzalez Ximena , Toro Pablo , Abner Erin L , Ferreccio Catterina 
Published: December 2020

AbstractBackgroundSubjective memory complaints (SMC) are common in later life and have been associated with increased risk of cognitive impairment and dementia. While there is much interest in SMC globally, no population‐based studies from South America have reported SMC prevalence.MethodData for this analysis was drawn from the Maule Cohort (MAUCO), a population‐based prospective cohort of Molina, Chile residents aged 35‐74 at baseline. MAUCO participants were stratified at age 60. Presence of SMC was determined by the questions “Does your memory fail frequently? Or Do you forget events, even recent, or some appointments?” Prevalence of SMC was estimated within age groups. Logistic regression was performed within age groups to evaluate factors associated with SMC.ResultsMost participants were female (56%), married (66%), with ≤ 8 years of education (49%), and reported good health (39%). There were 6,203 participants aged < 60, and 2,517 aged ≥ 60. Prevalence of SMC was 16% and 24%, respectively. Within age groups, characteristics of participants who reported SMC were different. Among those age < 60, those who reported SMC were more likely to use antidepressants, but this was not the case among the older group. In both age groups, those who reported SMC had significantly higher polypharmacy, higher anticholinergic burden, and higher use of benzodiazepines. Logistic regression analysis showed that for the age < 60 group, being female, having bad self‐reported health (OR=2.4; 95% CI 1.4‐4.3), depression (OR=1.5; 1.1‐1.9), major depressive syndrome on PHQ‐9 (OR=3.0; 2.2‐4.1) and MMSE score (OR=0.97; 0.94‐0.99) were significantly associated with SMC. However, in the older group, only the history of cancer (OR=2.0; 1.1‐3.8), major depressive syndrome on PHQ‐9 (OR=2.7; 1.6‐4.7), depressive symptoms on PHQ‐9 (OR 1.50; 1.03‐2.15), and MMSE score (OR=0.92; 0.89‐0.94) were associated with odds of SMC. In the adjusted models, neither polypharmacy, use of benzodiazepines, nor high anticholinergic burden were significant in any of the models for the younger or older groups.ConclusionSMC was common in both younger and older MAUCO participants. SMC may be associated with different factors in younger vs. older adults, but was associated with objective cognitive function (MMSE) in both groups.
Leveraging predicted gene expression data for recapitulation of gene coexpression network analysis associations with AD pathology and cognitive decline
Authors: Seto Mabel , Janve Vaibhav A. , Logsdon Benjamin A. , Mostafavi Sara , Dumitrescu Logan , Mahoney Emily R. , Gaiteri Chris , Schneider Julie A. , Bennett David A. , De Jager Philip L. , Hohman Timothy J. 
Published: December 2020

AbstractBackgroundGene co‐expression network (GCN) analysis is an approach in which biologically relevant modules can be identified from gene expression data, allowing for the elucidation of biological functions that are associated with Alzheimer’s disease (AD). Here, we evaluate the associations between generated from dorsolateral prefrontal cortex RNA sequencing (RNAseq) to validate previous reports (Mostafavi et al., 2018) and to identify novel module‐trait associations. As RNAseq data is often limited, we also apply an emerging technique to generate the same modules to provide a proof‐of‐concept for how transcriptomic reference panels can be leveraged to apply GCNs in the context of genome‐wide association analyses.MethodGenotype, neuropsychological data, autopsy measures of AD pathology, and RNAseq were obtained from the Religious Orders Study and Rush Memory and Aging Project. Global cognitive composite scores were calculated from 17 neuropsychological tests. Predicted gene expression data were generated using . Using 66 reported AD co‐expression modules (Logsdon et al. 2019; Mostafavi et al. 2018), we performed linear regression analyses assessing the association between the first principle component of the and cognitive decline and AD neuropathology. Covariates included age of death, sex, education, and post‐mortem interval. Correction for multiple comparisons was completed using the false discovery rate procedure.ResultWe recapitulated all reported associations. We also identified 15 novel associations with AD phenotypes using module definitions reported by Logsdon et al. Using predicted gene expression data, we replicated grey60 associations with tangles (p = 0.009) and cognitive decline (p = 0.004). The hub gene of grey60 was PAPOLA, which is a nominated target from AMP‐AD. PrediXcan analyses also recapitulated the m111 association with cognitive decline (p = 0.03, hub gene = TCF12). Both modules were enriched for transcriptional regulation genes, and higher gene expression in both modules was associated with slower cognitive decline.ConclusionPredicted gene expression can serve as a surrogate for recapitulating aspects of GCN analyses when RNAseq data is limited. Our findings provide additional evidence that gene networks involved in transcriptional regulation contribute to the neuropathology and cognitive decline observed in AD.
The evolution of brain atrophy across the disease spectrum of familial frontotemporal dementia
Authors: Staffaroni Adam M. , Goh Sheng‐Yang Matthew , Cobigo Yann , Ong Elise , Lee Suzee E. , Casaletto Kaitlin B. , Wolf Amy , Forsberg Leah K. , Ghoshal Nupur , Graff‐Radford Neill R. , Grossman Murray , Heuer Hilary W. , Hsiung Ging‐Yuek Robin , Kantarci Kejal , Knopman David S. , Kremers Walter K. , Mackenzie Ian R. , Miller Bruce L. , Pedraza Otto , Rascovsky Katya , Tartaglia Carmela , Wszolek Zbigniew , Kramer Joel H. , Kornak John , Boeve Bradley F. , Boxer Adam L. , Rosen Howard J. 
Published: December 2020

AbstractBackgroundFamilial frontotemporal dementia (f‐FTLD) is typically caused by mutations in one of three genes: microtubule‐associated protein tau (MAPT), progranulin (GRN), and a repeat expansion in the chromosome 9 open reading frame 72 (C9orf72) gene. Accurate characterization of the natural history of each mutation is important for clinical prognostication and clinical trial design, and it could shed light on disease biology. Such models have not been thoroughly developed using participants that represent all disease stages, with longitudinal data. We characterized the trajectory of atrophy in each gene by using longitudinal voxel‐wise analyses of gray matter volume, and we assessed whether functional independence declined in tandem.MethodF‐FTLD participants (n=100) with a known mutation (MAPT+ (n=28), GRN+ (n=33), C9orf72+ (n=39)) were grouped according to disease stage (CDR®+NACC FTLD module). We included participants with at least two structural MRIs at a given disease stage: presymptomatic (CDR®+NACC‐FTLD=0, n=57), mild/questionable (CDR®+NACC‐FTLD=0.5, n=15), and symptomatic (CDR®+NACC‐FTLD ≥1, n=28). We fitted longitudinal linear mixed effects models to extract mean atrophy rates in each lobe compared to longitudinal imaging from family members without mutations (n=60). All results presented below were significant at p<.001.ResultUsing the left frontal lobe as an exemplar, in the presymptomatic stage, MAPT mutation carriers showed the greatest rate of atrophy compared to controls (88 mm3/year more volume loss than controls), followed by GRN+ (65 mm3/year) and then C9orf72+ (49 mm3/year). In the mild/questionable stage, MAPT+ showed a greater divergence from controls (374 mm3/year) than did GRN+ (107 mm3/year) or C9orf72+ (223 mm3/year). In the symptomatic stage, MAPT+ again lost volume at the fastest rate (2,099 mm3/year), followed by GRN+ (1,360 mm3/year). C9orf72 expansion carriers showed a much slower rate of volume loss (115 mm3/year). Similar patterns were observed for other brain regions. In contrast to the imaging results, C9orf72+ exhibited similar rates of functional decline compared to GRN+ and MAPT+ at all levels of disease severity.ConclusionThe primary f‐FTLD genes show divergent atrophy trajectories as a function of disease stage, with C9orf72 expansion carriers exhibiting a slow degeneration throughout the disease course, possibly due to unique pathophysiological mechanisms.
Exploring genetic contributors to neuroprotection from AD pathologies: A genome‐wide association study
Authors: Seto Mabel , Mahoney Emily R. , Dumitrescu Logan , Engelman Corinne D. , Deming Yuetiva , Albert Marilyn S. , Johnson Sterling C. , Zetterberg Henrik , Blennow Kaj , Jefferson Angela L. , Hohman Timothy J. 
Published: December 2020

AbstractBackgroundPreclinical Alzheimer’s disease (AD) is a term describing individuals who harbor neuropathological hallmarks of AD but are asymptomatic. We hypothesize that common genetic variation contributes to neuroprotection from AD pathology. More specifically, we tested whether genetic variation modifies the association between AD pathology (measured by CSF biomarkers) and neurodegeneration (measured by hippocampal volume).MethodMRI measurements of hippocampal volume and CSF measures of amyloid (Aβ42) and tau were obtained from 1,073 individuals of European descent from four longitudinal aging cohort studies (age = 70.7 ± 8.7; female = 47%; normal cognition = 38%). Data were harmonized leveraging established procedures to account for differences in site, data acquisition, and processing. A genome‐wide association study was performed using mixed‐effects regression models to assess SNP x CSF biomarker interactions on hippocampal atrophy. Covariates included age, sex, population principal components, cohort, and time.ResultWe identified a locus that modifies the association between baseline CSF Aβ42 and hippocampal atrophy in an intronic region of the SEMA5B gene (index SNP = rs62263260; p = 1.97e‐8; MAF = 0.12; Figure 1). Carriers of the rs62263260 minor allele showed a faster rate of hippocampal atrophy, particularly among those harboring high levels of amyloid pathology. This variant is also an eQTL for SEMA5B in brain tissue (GTEx p = 4.80e‐4), where minor allele carriers express higher levels of SEMA5B, suggesting that lower SEMA5B expression may provide neuroprotection. Additionally, we identified a locus that modifies the association between baseline CSF p‐tau and hippocampal atrophy on chromosome 3 proximal to the SATB1 gene (index SNP = rs116216974; p = 1.62e‐8, MAF = 0.02%). Carriers of the rs116216974 minor allele had a slower rate of hippocampal atrophy in the presence of high baseline p‐tau pathology compared to non‐carriers. No eQTLs were reported for rs116216974.ConclusionWe identified two independent genetic loci that modify the association between AD biomarkers and neurodegeneration. SEMA5B is implicated in synapse elimination, and increased elimination may occur in the presence of amyloid pathology. SATB1 knockdown in mice is associated with increased microglial activity, suggesting that regulating the immune response to p‐tau may be important for neuroprotection. This study also demonstrates that identifying genetic factors contributing to neuroprotection from AD pathology may help elucidate mechanisms behind asymptomatic AD.
Engagement in social activities is related to connected speech and language outcomes in the Wisconsin Registry for Alzheimer's Prevention
Authors: Mueller Kimberly D. , Peters Cassandra C. , Hulle Carol A. , Koscik Rebecca L. , Jonaitis Erin M. , Betthauser Tobey J. , Chin Nathaniel A. , Hermann Bruce P. , Johnson Sterling C. 
Published: December 2020

AbstractBackgroundThere is growing interest in using digital biomarkers, like recorded spontaneous speech, as indicators of Alzheimer’s disease progression. Several studies have shown that changes in connected speech and language (CSL), including speech fluency markers and linguistic content, are associated with preclinical cognitive decline. Little is known about the relationships between CSL and the lifestyle factors that may be largely dependent upon it, particularly social participation. Social engagement (SE) (e.g., in activities such as informal social participation, volunteering) has been associated with multiple health indicators in aging. Our aim was to determine if SE at baseline, or change in SE, was related to declines in CSL measures that have been linked to cognitive decline. Sensitivity analyses determined if baseline CSL predicted baseline SE and change in SE.MethodLongitudinal CSL measures (Figure 1) were automatically extracted from picture description transcripts from Wisconsin Registry for Alzheimer’s Prevention participants (N=794). SE composite scores were created from selected Florida Cognitive Activities Scale items (Table 1). Statistics included t‐tests, chi‐square tests, ANCOVA, and linear mixed‐effects models with CSL as outcomes and baseline SE, and normalized change from baseline to most recent SE, as predictors.ResultTable 2 shows speech metrics and demographics of participants stratified by low, medium and high SE. Participants reporting “high” SE were more likely to be female, had higher baseline WRAT‐3 reading scores, and had lower depression scores. Participants reporting “low” SE expressed fewer content words, unique words, and total words than those with mid‐ or high SE. Positive change in SE was associated with slower age‐related change in speech fluency over time (Table 3, Figure 2). Sensitivity analyses indicated worse baseline speech fluency was significantly associated with higher baseline SE but also positive change in SE, adjusting for age, sex WRAT‐3 and depression (Table 4).ConclusionThis study shows that spontaneous speech metrics are positively associated with self‐reported social engagement in late middle age. Crucial next steps include determining if SE moderates the effect of amyloid, tau, and neurodegeneration on measures of cognition including speech. SE is a potentially modifiable lifestyle behavior that may have positive implications for improved outcomes in communication and cognitive function.
Lifetime stressful experiences and cognitive performance in African American and white older adults: New evidence from a population‐based cohort
Authors: Zuelsdorff Megan , Sonnega Amanda , Byrd DeAnnah R , Benton Susan Flowers , Turner Robert 
Published: December 2020

AbstractBackgroundGrowing evidence suggests that modifiable sociocontextual factors powerfully shape health including risk for Alzheimer's disease and related dementias (ADRD), and contribute substantially to well‐established racial disparities in cognitive aging. Stressful experiences cluster and accumulate across the lifespan, plausibly impacting brain health, but cognitive effects of lifetime adversity across diverse populations remain underexplored. We examined relationships between lifetime stressful events and cognition among African American and White older adults in the Health and Retirement Study (HRS).MethodThe study sample included non‐demented adults (N=8,222) aged 60 and older who provided cognitive and lifetime stress data at the 2006/08 and 2010/12 HRS waves. Cognitive outcomes included performance on a test of global cognition (Telephone Interview for Cognitive Status) and its immediate and delayed recall subscales. The key predictor of interest was a Lifetime Stress index score (sample range=0‐11 experiences). Mixed‐effects regression models assessed associations of lifetime stress with each cognitive outcome. Polynomial and three‐way interaction models explored potential (1) non‐linear associations between stress and cognition, and (2) moderation of those relationships by race.ResultAfrican Americans (N=1,015) were younger (M=71.7, SD=6.8) than whites (M=72.2, SD=6.3) and reported fewer years of education (p<0.001). Reported number of stressful life events reported (M=1.61, SD=1.45) did not vary by race. In adjusted models (Table 1, Model 2), a significant stress quadratic revealed that relationships with global cognition (p<0.001) and delayed recall (p=0.01) were non‐linear. Modification by African American race (Table 1, Model 3; Figure 1) was observed for global cognition (p=0.01) but not recall subscales (immediate: p=0.10; delayed: p=0.45).ConclusionWe found that lifetime stress is associated with poorer later‐life cognitive function; however, detriment is observed only at high levels of stress. African American and White HRS participants report very few stressful life events on average, but African Americans reporting many stressors showed exacerbated stressor‐associated dysfunction in global cognition. Our findings from this large, population‐based sample reaffirm the role for stress and stress‐adjacent experiences in cognitive aging, particularly among communities facing disproportionate ADRD burden. Expanding community‐specific, lifecourse‐based research and intervention strategies is a necessary next step toward understanding and mitigating disparity through targeted resource placement and stakeholder partnerships.
In a pre‐pivotal diagnostic study, β‐amyloid plaque detection in the lens of the eye in MCI and mild AD patients was used to classify subjects as normal, MCI, and mild AD using Sapphire II
Authors: Knowlton Newman , Hendrix Suzanne B. , Wilke Susanne , Nilan Dennis 
Published: December 2020

AbstractBackgroundThe Sapphire II platform is a clinical diagnostic device intended for aiding clinical evaluation and measurement of beta‐amyloid aggregation in anatomically defined regions of the anterior segment of the eye. It detects a specific fluorescent signature emission of ligand‐marked beta amyloid complex in the supranuclear region of the human lens. The current study results are Sapphire II scan to be used to classify patients as normal, MCI and mild Alzheimer’s disease and the utility of Sapphire II screening compared to b‐amyloid PET scans in MCI and Mild AD subjects.MethodA naïve Bayes classifier using a base model with the three most theoretically relevant parameters (τ1, τ2, φ). Sensitivity and specificity is assessed comparing the normal group to the collective MCI/Mild AD group. 48 participants; 28 MCI, 16 Mild AD patients and 4 Normal Control subjects were studied.ResultsThe Sapphire II naïve Bayes classifier with cross validation had sensitivity of 96%, specificity of 75%, and overall accuracy of 92%. Results based on 4 healthy controls only, with one of the control subjects tested positive in Sapphire II; additional testing on 10 healthy controls is in progressConclusionSapphire II offers a non‐invasive, safe, easy to use, community based inexpensive method for accurately classifying individuals as normal, MCI or mild AD dementia on the basis of the beta amyloid in the lens of the eye. Sapphire II may offer a practical alternative to PET amyloid scans for biomarker confirmed AD diagnosis. Evaluation of individual PET scans and cognitive testing suggests that Sapphire II is more sensitive than PET. ^Discussions with Dr. Tae Yeon Yoo, Ph.D. are gratefully acknowledged.
Detecting biological changes in longitudinal MRI scans of Alzheimer’s disease patients in the hippocampus region with deep learning
Authors: Dong Mengjin , Xie Long , Das Sandhitsu R. , Wolk David A. , Yushkevich Paul A. 
Published: December 2020

AbstractBackgroundAlzheimer's Disease (AD) is characterized by gradual loss of gray matter, particularly in the medial temporal lobe (MTL) and hippocampus. Longitudinal change in hippocampal volume on MRI is an effective biomarker to monitor disease progression in AD. However, neurodegenerative changes in the hippocampus on longitudinal MRI can be obscured by differences in MRI signal that are unrelated to disease progression, such as different amounts of head motion, noise, or MRI artifact. We hypothesize that a deep learning model can be trained to distinguish true biological changes from nonsystematic factors, leading to a more sensitive biomarker of disease progression.MethodA 3D convolutional neural network (CNN) was trained to predict the inter‐scan interval (in days) from pairs of rigidly co‐registered longitudinal T1‐weighted MRI scans. Scans trimmed to the hippocampus region were input in arbitrary time order, and the network had to infer which was the earlier scan and the interscan interval in days. A cohort of 666 ADNI participants was used for CNN training and 154 participants formed a held‐out test set. We tested the hypotheses that (a) CNN can correctly predict the temporal order of scans (indicating sensitivity to biological changes) and (b) that a measure of mismatch between actual interscan interval and interval predicted by a CNN trained on more impaired subjects (late MCI and AD) would differ between less impaired (controls + early MCI) and more impaired groups (indicating sensitivity to AD). The same hypotheses were also tested using a conventional technique for longitudinal change estimation, ALOHA (Das et al., 2012).ResultCNN was more accurate than ALOHA in inferring the temporal order of scans (Table 2, Figure 1) and to a lesser extent, inter‐scan interval (Table 3, Figure 2). Mismatch measure was greater for the less impaired than more impaired group for both CNN and ALOHA, with larger difference for CNN, potentially indicating greater sensitivity to disease.ConclusionCNN can accurately detect the temporal order of scans indicating sensitivity to neurodegeneration and ability to factor out non‐systematic changes. The CNN‐derived mismatch measure has the potential to serve as a disease progression biomarker for AD clinical trials.