bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cerebral amyloid angiopathy interacts with parenchymal beta‐amyloid to promote tau and cognitive decline
Authors: Rabin Jennifer S. , Nichols Emma , La Joie Renaud , Casaletto Kaitlin B , Palta Priya , Dams‐O'Connor Kristen , Kumar Raj G. , George Kristen M. , Satizabal Claudia L , Schneider Julie A , Pa Judy , Brickman Adam M. 
Published: December 2022

AbstractBackgroundPrior work has shown that cerebrovascular disease contributes to Alzheimer’s disease (AD) pathophysiology and progression toward AD dementia. Cerebral amyloid angiopathy (CAA) is a form of cerebrovascular pathology that results from the buildup of β‐amyloid (Aβ) in the vessel walls. CAA commonly co‐occurs with AD pathology and increases the risk of AD dementia. Here, we examined whether CAA influences tau deposition and cognitive decline, independently or synergistically with parenchymal Aβ burden. Secondarily, we examined whether tau burden mediates the association between CAA and cognitive decline.MethodWe included data from autopsied subjects recruited from one of three longitudinal clinical‐pathological cohort studies at Rush University. Participants completed annual cognitive evaluations and underwent brain autopsy. CAA pathology was rated as none, mild, moderate, or severe. We used linear regression and linear mixed models to test independent versus interactive effects of CAA and neuritic plaques on tau burden and cognitive decline. We used causal mediation models to examine whether tau mediates the association between CAA and cognitive decline at low and high neuritic plaque burden.ResultWe included 1722 autopsied subjects (mean age at baseline = 80.2+7.1; mean age at death = 8.9+6.7; 68% women). CAA interacted with neuritic plaques to promote tau burden and cognitive decline, such that those with more severe CAA and higher neuritic plaque burden exhibited greater tau and faster cognitive decline (Figures 1 and 2). Tau mediated the effect of CAA on cognitive decline among participants with high neuritic plaque burden. Specifically, increased tau pathology due to the presence of severe CAA led to a 5‐year decline in cognition that was 0.10 (95% CI: 0.03 ‐ 0.19) SD units greater than those with no CAA. A direct effect of CAA on cognitive decline (i.e., an effect not mediated by tau) was not significant in the low or high neuritic plaque groups (Figure 3).ConclusionThese results highlight the dynamic interplay between cerebrovascular and AD pathways in the progression of AD. The present findings have implications for AD clinical trials and therapeutic development, and further support the idea that improving and/or preserving the brain’s vasculature might be an effective target for AD prevention
Posterior hippocampal redundancy: A marker of non‐pathological brain aging
Authors: Blujus Jenna K , Oh Hwamee 
Published: December 2022

AbstractBackgroundSeveral neural mechanisms underlying brain resilience to Alzheimer’s disease (AD) have been proposed, including redundant neural connections between the posterior hippocampi and all other brain regions (pHipp‐redundancy), and global functional connectivity of the left frontal cortex (gLFC). It remains unclear whether these two mechanisms confer resilience to AD pathologies through similar or distinctive mechanisms. We examined if redundancy, measured through graph theory, underlies the neuroprotective effects of both pHipp‐redundancy and gLFC connectivity in the early stage of AD pathologies.MethodFrom the ADNI database, 370 CN and MCI participants were utilized. Aβ‐positivity (Aβ+) was defined as PET AV45 SUVR normalized to cerebellum greater than 1.11. Resting state data were preprocessed using fMRIprep (v20.2.6). Network graphs were constructed with 263 functional ROIs as nodes and z‐transformed correlations between each node as edges. Redundancy was calculated by summing the direct and indirect paths (path lengths=1‐4) between each hippocampal region (i.e., anterior and posterior hippocampal regions, bilaterally and LFC) and its 262 connections. Group differences (Aβ‐status, diagnosis) were computed in R using non‐parametric ANCOVA models with 10,000 permutations. Regression analyses were conducted to examine if Aβ‐status and diagnosis moderated the relationship between SUVR and redundancy. Models covaried for age, sex, education, and APOE4.ResultAcross CN and MCI, Aβ‐ had higher bilateral pHipp‐redundancy than Aβ+ (p’s<.034). Diagnosis significantly moderated the relationship between SUVR and left pHipp‐redundancy (β=0.112, p=.042). CN exhibited a stronger negative relationship between SUVR and left pHipp‐redundancy than MCI (p<.001). Finally, in CN, Aβ‐status significantly moderated the relationship between SUVR and right aHipp‐redundancy (β=0.358, p=.012), showing that in Aβ‐ CN, redundancy decreased with higher SUVR (p=.01), while in Aβ+ CN, redundancy remained the same as SUVRs increased. No relationships between Aβ‐status and redundancy, and interactions between SUVR and Aβ‐status or diagnosis, were significant in LFC.ConclusionTogether, these findings suggest that bilateral pHipp‐redundancy may reflect normal brain aging without Aβ, rather than resilience in pathological aging, and a distinctive mechanism of brain aging from that of gLFC connectivity in the progression of AD.
Hierarchical, multiclass prediction of Alzheimer’s clinical diagnosis using imputed, multimodal NACC data
Authors: Ren Yueqi , Shahbaba Babak , Stark Craig E. 
Published: December 2022

AbstractBackgroundEarly detection and diagnosis are critical for effective treatment of Alzheimer’s disease (AD). Statistical machine learning holds promise for disease prediction using large AD repositories, such as the National Alzheimer’s Coordinating Center (NACC) dataset. Past work has extensively explored binary classifications of AD diagnosis. Here, we extended this to address two major, remaining challenges: data imputation and multiclass classification (e.g., AD vs Mild Cognitive Impairment, MCI vs. Healthy Cognition, HC).MethodFor imputation, we tested single‐value (baseline), k‐NN, and Bayesian imputation on a subset of complete training data with artificially removed values (completely at random). Per modality of interest, a systematic search was conducted for the best input feature set to impute the missing values. The mean absolute deviation and mismatch rate between the imputed and true values were used to evaluate the methods on a held‐out test set. For classification, we then implemented both “flat” multiclass and hierarchical classification, an extension of multiclass classification that organizes classes into a tree, to predict clinical diagnosis using multimodal inputs. Several pipelines with combinations of imputation methods, classifiers, and input modalities were tested on different hierarchical classification strategies, e.g., HC vs [AD vs MCI], compared with the flat, multiclass baseline (AD vs MCI vs HC).ResultCompared to the baseline methods for both imputation and classification, the proposed alternatives performed better, as measured by the predetermined imputation and classification metrics evaluated on the test set. For imputation, behavioral and neuropsychiatric features were more easily and accurately imputed while ApoE genotype was more difficult to impute. For classification, using a combination of classifiers and input features in the hierarchy outperformed the baseline method and support the notion that select biomarkers are better able to characterize AD subpopulations within the hierarchy.ConclusionEstablishing a systematic imputation method tailored to AD biomarker modalities fills a critical gap in achieving more robust disease prediction. Building a hierarchical classifier parallels working through a differential diagnosis for AD, which offers greater translational value than binary classification of AD. In combination, these results form an important step toward developing reliable, holistic classifiers of AD disease status.
Incidence of Cognitive Decline 5 Years after Orthopaedic Surgery According to Method of Assessment
Authors: Atkins Kelly J , Evered Lisbeth A , Scott David A , Silbert Brendan S 
Published: December 2022

AbstractBackgroundOlder adults who undergo elective surgery may be at risk of an altered cognitive trajectory leading to long‐term decline. We investigated the incidence of cognitive decline in the elderly following elective non‐cardiac surgery five years post‐operatively and examined whether differences in classification criteria for cognitive outcomes resulted in different incidence rates.MethodWe prospectively studied older adults following orthopaedic surgery, alongside non‐surgical control participants. All participants completed a battery of neuropsychological tests before surgery and again five years postoperatively. We classified Postoperative Cognitive Dysfunction (POCD), (a change‐based construct historically used in anesthesiology and surgery) as a decline of two standard deviations (SD) on two or more cognitive tests compared to controls. We also assessed Neurocognitive Disorders (NCD) relative to change in controls, a term recently introduced to align cognitive disorders with community medicine. Major NCD was defined by a decline of two SD on any test, accompanied by a subjective memory complaint and observed decline in instrumental activities of daily living. Mild NCD was classified as a memory complaint and a decline of one SD on at least one test.ResultFrom an initial 300 participants enrolled, 227 participants (surgical = 199, non‐surgical control = 34) completed the five year follow‐up. Average (SD) follow‐up age was 74.8 (6. 6) years and 154 (67.8%) were female. We identified POCD at five years in 28 (14.2%), and major NCD in 38 (19.3%) participants. Mild NCD was more common, occurring in 81 (41.1%) participants. Cognitive decline five years postoperatively was associated with increasing age, whereas education history and anesthetic technique (spinal or GA) were not significantly associated. Further analyses will determine the role of cardiovascular risk factors.ConclusionWe found both overlap and differences in the incidence rate of cognitive decline according to the criteria used for classification. Regardless of classification criteria and nomenclature, we found higher rates of cognitive decline amongst non‐cardiac surgical patients compared to rates reported in the general population. Our findings provide support that even elective, non‐cardiac surgical procedures under anesthesia are associated with a faster rate of cognitive decline amongst older adults. Possible pathophysiological mechanisms, including cardiovascular factors, will be discussed.
Examining the Moderating Roles of Social Isolation and Social Technology Use in Health Disparities of Cognitive Impairment
Authors: Byrne Kaileigh A 
Published: December 2022

AbstractBackgroundThere are profound racial disparities in cognitive impairment and dementia. Black and rural older adults are nearly twice as likely to develop dementia compared to White and urban‐dwelling older adults, respectively. However, the way social factors affect these racial and rural‐urban disparities in dementia prevalence remains poorly understood. Social isolation is associated with poorer cognitive outcomes among older adults, yet social technology use may provide a means to reduce social isolation. This research examines how two social factors—social isolation and social technology use influence racial and rural disparities in cognitive impairment and dementia.MethodData was extracted from the 2014 to 2018 waves of the Health and Retirement Study (N = 5,358). Participants (aged 50‐102) completed survey measures of social isolation, loneliness, and frequency of online social communication (e.g., use of Facebook, Skype). The modified Telephone Interview for Cognitive Status was used to operationalize dementia. The validated TICS classification system was used to classify scores with a cognitive status of dementia (scores ≤6), cognitive impairment (score of 7‐11), or cognitively normal (scores ≥12). Data was analyzed using structural equation models.ResultAcross all groups, frequency of social technology use moderated the negative relationship between social isolation and cognitive impairment, controlling for age, education, gender, wealth, and general computer usage. More frequent social technology use was associated with cognitively normal status among older adults who reported greater degrees of social isolation. In terms of health disparities, the results revealed racial, but not rural‐urban, differences in the relationship between frequency of social technology use and cognitive status. Frequent social technology use was associated with improved cognitive status in Black American older adults but not White older adults, irrespective of their level of social isolation.ConclusionSocial technology may offer a means to mitigate cognitive decline; the potential benefit of such technology may be particularly promising among Black older adults.
Racial/Ethnic Disparities in Risk and Protective Factors of Dementia in the United States
Authors: Ferdows Nasim B. , Aranda Maria P. 
Published: December 2022

AbstractBackgroundRecent population‐based studies show decline in dementia incidence and prevalence in high‐income countries, suggesting that improved population cardiovascular health and rising levels of education in the past 25 years were associated with reduction of dementia risks. However, in the US, there is a variation in changes over time of educational attainment, prevalence and management of chronic diseases, and behaviors associated with poor cardiovascular health among racial/ethnic groups. This study examines the risk and protective factors associated with dementia and decomposes racial/ethnic disparities in factors associated with cognitive functioning.MethodWe performed a retrospective analysis of 3,495 older individuals (65+) in 2016 who participated in Harmonized Cognitive Assessment Protocol, linked to Health and Retirement Study to trace the individuals back to 2000. Using Mini‐Mental State Examination (MMSE), individuals were classified as demented vs normal. Risk factors included were cardiovascular factors, hearing loss, and history of being uninsured in midlife, and current smoking, depression, and physical inactivity. Protective factors included were educational attainment. Using Oaxaca‐Blinder decomposition, the relative contribution of different variables in explaining racial/ethnic disparities in cognitive functioning was evaluated.ResultAccounting for sociodemographic, mid‐, and later‐life characteristics, Blacks have higher odds of having dementia, following Hispanics and Whites. Higher levels of education and wealth were associated with lower odds of dementia. History of stroke and hearing loss during mid‐life, and depression and physical inactivity in late‐life were associated with higher odds of dementia. The decomposition shows that about 32% of Blacks and Whites difference in MMSE score was explained by demographics and later‐life characteristics, while nearly 68% of the difference remains unexplained. Comparing Whites and Hispanics, 70% of the difference in MMSE score was explained by demographics and later‐life characteristics, while nearly 30% of the difference remains unexplained.ConclusionBlacks and Hispanics are found to have a higher risk of dementia compared to whites. Accounting for demographics, mid‐ and later‐life risk and protective factors explain only one‐third of the difference in cognitive functioning between Blacks and Whites and nearly two‐thirds of the differences between Hispanics and Whites.
Longitudinal changes in brain glucose metabolism, astrocyte biomarkers and behavior in an APP/PS1 rat model
Authors: da Rocha Andreia Silva , Machado Luiza Santos , Soares Carolina , Ferreira Pamela C.L. , Bellaver Bruna , Kunach Peter , Rosa‐Neto Pedro , Green Kim N , Zimmer Eduardo R. ,   Model AD Consortium
Published: December 2022

AbstractBackgroundImaging and fluid biomarkers have helped to reconceptualize Alzheimer’s Disease (AD) as a continuum. However, the biological interpretation of each AD biomarker remains under investigation. In this context, animal models that mimic the AD dynamic biomarkers cascade model present high translational value and can be used to refine our interpretation of biomarker findings. In light of this, we longitudinally evaluated [18F]FDG‐PET imaging, cerebrospinal fluid (CSF) glial and immune biomarkers, and behavior in the TgF344‐AD rat, a model harboring human APP/PS1 mutations.MethodsTgF344‐AD rats and wild‐type littermates were longitudinally evaluated at 3, 6, 9, and 12 months of age. Rats underwent [18F]FDG‐microPET scans, behavioral tasks (Y‐maze and novel objective recognition) and CSF samplings. The [18F]FDG SUVr was calculated with pons as the reference region. CSF glial and immune markers were measured by multiplex ELISA. A cross‐sectional cohort was used to measure cortical glutamate uptake (ex‐vivo slices) at the same time points. Further examination of astrocyte proteins immunocontent was conducted at 9 months of age.ResultsAt 3, 6 and 12 months, no changes in [18F]FDG metabolism were found. At 9 months of age, we identified a significant cortical hypermetabolism in the TgF344‐AD and a decline in alternance during the Y‐maze task. CSF GFAP levels were elevated at 6 and 9 months of age, while CSF S100B was decreased at 9 months of age. Additionally, the cortical and hippocampal glutamate uptake and GFAP cortical immunocontent were increased at 9 and 12 months of age. The recognition memory and CSF inflammatory markers (sTREM2, IL‐6, TNF‐α, IL‐10) were not altered in any of the ages evaluated.ConclusionOur results suggest that the TgF344‐AD rat model is suitable for studying astrocytic adaptations during early stages of amyloidosis in the rat brain. These adaptations include cortical glucose hypermetabolism, fluid biomarker evidence of reactive astrogliosis, and spatial memory impairment with concurrent abnormalities in astrocyte glutamate uptake in the cortex and hippocampus. Due to the critical role of astrocytes in brain glucose handling, our findings suggest that astrocyte reactivity could be driving glucose hypermetabolism and memory impairment early in the disease course.
Characterization of chromosome 5q35 risk locus in African Ancestry population.
Authors: Nuytemans Karen , Rajabli Farid , Jean‐Francois Melissa , Adams Larry D. , Starks Takiyah D. , Whitehead Patrice L. , Kunkle Brian W. , Caban‐Holt Allison M , Cuccaro Michael L. , Vance Jeffery M. , Haines Jonathan L. , Reitz Christiane , Byrd Goldie S. , Beecham Gary W. , Vance Margaret A. ,   The NIA‐LOAD Family‐Based Study
Published: December 2022

AbstractBackgroundAs part of the Research in African American Alzheimer Disease Initiative (REAAADI) and Late‐Onset AD Family Study (LOAD), genotyping array and whole genome sequencing (WGS) data were generated for 51 families (160 affected and 318 unaffected). Multipoint linkage analyses identified a peak LOD score on chr5q35 (HLOD=3.20). Additionally, a suggestive locus flanking the 1‐LOD score was previously identified in an AA GWAS study (p‐value=2.6×10‐6) (Kunkle et al, 2019). Here, we further characterize this locus and its role in AD.MethodWe performed region‐wide association analysis in an independent REAAADI dataset of ∼240 cases and ∼650 controls to fine map the signal in the locus. Additionally, we analyzed the WGS data to prioritize variants in the consensus regions based on segregation with disease among affected individuals and rarity (MAF<0.01). All variants were annotated for putative function including protein changes for coding variants and evidence for regulatory activity (ENCODE, RoadMap Epigenome) and chromatin interactions (publicly available HiC and promoter capture C) for noncoding variants.ResultRegion‐wide association analysis identified two regions of rare (MAF∼0.01) variants downstream (p=3.0×10‐8) and upstream (p=3.7×10‐6) of the 1‐LOD linkage region. Segregation analysis using WGS data identified 111 rare variants (MAF<0.01) segregating with disease in the AD individuals of the family with the highest LOD score contributing to the linkage peak. These include a 3’UTR and synonymous variant in INSYN2B/FAM196B as well as a promoter variant in WWC1/KIBRA. Interestingly, four other AA families contributing to the chr5 linkage signal harbor different within‐family shared variants located in INSYN2B’s promoter or in enhancer regions with evidence for interaction with INSYN2B’s promoter. WWC1, expressed in astrocytes, was previously reported in AD context, whereas novel candidate INSYN2B encodes an inhibitory synaptic factor active in oligodendrocytes and neurons.ConclusionOur initial analyses provide evidence for two candidate genes contributing to AD genetics in the AA population. Additional work for functional validation of these candidates for AD is ongoing. This AA population‐specific finding shows the importance of diversifying population‐level genetic data to better understand the genetic determinants of AD on a global scale.
Trajectories of plasma Aβ42/40 among African Americans: Preliminary results from the African American Fighting Alzheimer’s in Midlife (AA‐FAIM) study
Authors: Van Hulle Carol A. , Zuelsdorff Megan , Koscik Rebecca Langhough , Ennis Gilda E. , Bouges Shenikqua , Fischer Barbara L. , Wyman Mary F. , Lambrou Nickolas H. , Johnson Adrienne L. , Umucu Emre , Salazar Hector , Chin Nathaniel A. , Meyer Matthew R. , Holubasch Mary S. , Kirmess Kris , Verghese Philip B. , West Tim , Venkatesh Venky , Yarasheski Kevin E. , Gleason Carey E. 
Published: December 2022

AbstractBackgroundAfrican Americans (AA) are under‐represented in Alzheimer’s disease (AD) biomarker research. Blood‐based biomarkers for AD offer the promise of greater diversity in research studies, but little is known about the performance of these biomarkers within an AA cohort. We examined the association between modifiable and non‐modifiable risk factors on the trajectory of plasma measures of Aβ42/40 in a large well‐characterized AA cohort.MethodN=318 AA participants enrolled in in African Americans Fighting Alzheimer’s in Mid‐Life (AA‐FAIM) provided 690 plasma samples. The ratio Ab42/40 was calculated from plasma Aβ40 and Aβ42 quantified by C2N Diagnostics (PrecivityAD™; Figure 1). Age range was 39 ‐ 87 years at baseline (see Table 1); 52% of the cohort provided ≥2 plasma samples. Mixed‐effects linear models were used to test for longitudinal change in Aβ42/40 where years since baseline was the measure of time (M= 4.13 years, range = 1 to 16 years). To determine if risk factors modified Aβ42/40 trajectory, we tested the interactions between time and the following AD risk factors: APOE genetic risk, cardiovascular factors measured at baseline plasma sample (blood pressure, BMI, total cholesterol), and amyloid PET positivity.ResultRaw Aβ42/40 values plotted against time are shown in Figure 2. None of the risk factors modified the trajectory of Aβ42/40 (p values ranged .22 to .84), which declined by approximately 1% per year over baseline (p <.001; Table 2). After accounting for longitudinal trajectory, Ab42/40 was 3% lower among APOE ε4 carriers, while higher baseline total cholesterol was associated with higher Aβ42/40. In a subset of participants with PiB‐PET visual ratings (N=35), amyloid positive participants (N=10) had 12% lower plasma Aβ42/40 values than amyloid negative participants (p<.001) after accounting for longitudinal trajectory.ConclusionThese initial analyses conducted exclusively in African Americans suggest that clinical risk factors (total cholesterol, APOE) can influence brain amyloid pathology, as determined using plasma Aβ42/40. More research is needed to fully characterize AD pathology and dementia risk in AAs. This research is imperative in light of the disproportionate burden of dementia in the AA community and the increasing use of biomarkers in research and clinical practice.