bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel circling SWAT for deep learning based diagnostic classification of Alzheimer’s disease: Application to metabolome data
Authors: Jo Taeho , Kim Junpyo , Bice Paula , Huynh Kevin , Wang Tingting , Meikle Peter J , Kaddurah‐Daouk Rima , Nho Kwangsik , Saykin Andrew J. 
Published: December 2022

AbstractBackgroundRecent advances in deep learning have allowed multi‐omics data to be used to detect early stages of Alzheimer's disease (AD). The metabolome, as the end‐product of biological cascades including the genome, transcriptome, and proteome, may have informative elements that could serve as potential AD biomarkers. We report a novel two‐step deep learning method to detect AD and progression using lipidomics data.MethodWe used serum‐based cross‐sectional lipidome data with 781 lipids from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) including 216 cognitively normal (CN), 635 MCI, and 382 dementia (AD). Phenotype influence scores (PIS) was derived by deep learning‐based circling Sliding Window Association Test approach (Circling SWAT) (Fig. 1‐A), an extension of SWAT (Jo et al., 2022) with correlation heatmap and dendrogram analysis for omics data with minimal features. We used convolutional neural networks (CNN) to classify AD from CN based on top‐scoring metabolites. The AD classification model was used to predict conversion of MCI to AD within two years using 146 MCI‐convertors who developed AD and 190 MCI‐Stable who did not develop AD over two years from baseline. We removed two deDE lipids, deDE(18:2) and deDE(20:4), because their associations with AD were driven mainly by AD‐related medication.ResultPhenotype influence scores (PIS) were calculated for each lipid using circling SWAT to determine their impacts on AD. The metabolites with the highest PIS were LPE(22:6), PC(39:5), and PC(15‐MHDA_22:6). When CNN was applied to the top 50 lipids by PIS, AD and CN classification accuracy was 73.6% (Fig. 1‐B), which was 5.1% higher than the accuracy obtained using only age, sex, and APOE ε4. For MCI conversion to AD, the AD/CN classifier accuracy was 69.9% or 8.8% higher than a model using only age, sex, and APOE ε4.ConclusionThe circling SWAT method appears promising for the analysis of lipidome data as it was able to identify several AD‐related lipids and predict disease progression.
Association between recollection and familiarity‐based memory measures and plasma biomarkers for Alzheimer’s disease
Authors: DiCalogero Michael , Lane Jacqueline , Kelley Melissa , Tropea Thomas F. , Shaw Leslie M. , Chen‐Plotkin Alice , Wolk David A. 
Published: December 2022

AbstractBackgroundNormal aging and preclinical Alzheimer’s Disease (AD) share common features, such as structural changes to medial temporal lobe regions and declining episodic memory. However, prior work suggests qualitative differences between AD‐related memory changes and those due to aging. Specifically, recollection‐based, or contextual, memory declines with both normal aging and AD. Alternatively, familiarity‐based, or item, memory is more specific to preclinical AD and atrophy in the perirhinal cortex. In the current analysis, we examined the relationship between these forms of memory with plasma biomarkers associated with AD and neurodegeneration.MethodAt the Penn Alzheimer’s Disease Research Center, 127 cognitively‐normal participants (age=73.12±6.62, 59% female, years of education=16.40±2.62, 80% Caucasian) completed an experimental memory paradigm assessing recollection and familiarity along with standard neuropsychological testing. In this paradigm, pictures of common objects were presented in 80 pairs at study and participants were told to pick the object they preferred. At test, 40 intact, 40 re‐arranged, and 40 novel object pairs were presented. Recollection was defined as the probability(intact)–probability(rearranged), while familiarity was defined as the probability(rearranged)/(1‐R). To account for differences in base rates of false alarms (‘‘old’’ responses to novel pairs), familiarity was calculated using a measure of discrimination (d’) derived from signal detection theory. Whole blood samples were collected in EDTA‐tubes, spun‐down, and stored at ‐80°C. Measures of glial fibrillary acidic protein (GFAP), neurofilament light chain (Nfl), and plasma tau (p‐Tau181) were generated with the Simoa HD‐X analyzer system.ResultFamiliarity correlated with GFAP (r(125) =‐0.24, p<0.05) (Figure 1) and NfL (r(125) =‐0.23, p<0.05) (Figure 2). Further, a partial correlation controlling for age and days between the experimental and plasma measure remained significant for GFAP (r(125)=‐0.25, p<0.05). Additionally, recollection correlated with Nfl (r(125) =‐0.25, p<0.05) (Figure 3). Correlations with standard neuropsychological tests revealed no significant results.ConclusionThis study reveals that within the normal aging spectrum, familiarity‐based memory correlates with molecular measures that have been associated with amyloid (GFAP), while both measures correlated with a non‐specific measure of neurodegeneration (NfL). This supports the notion that familiarity may be sensitive to preclinical AD.
Large‐Scale Network Dysfunction in Dementia with Lewy Bodies: Preliminary Results from an fMRI Connectomic Mapping Study
Authors: Kashyap Bhavani , Wyman‐Chick Kathryn A , Hanson Leah R , Sherman Samantha J , Svitak Aleta L , O'Keefe Lauren R , Chrenka Ella A , Sughrue Michael Edward , Rosenbloom Michael H 
Published: December 2022

AbstractBackgroundThe diagnosis of dementia with Lewy bodies (DLB) is often delayed in clinical practice. The sensitivity and specificity of structural MRI is suboptimal: a multisite study with autopsy confirmation demonstrated 64% sensitivity and 68% specificity for differentiating DLB from Alzheimer's Disease (AD; Harper et.al, 2016). There is an urgent need to develop additional reliable biomarkers for DLB. We describe resting state functional MRI (rsfMRI) results using an automated connectome mapping program (Infinitome).MethodParticipants meeting criteria for probable DLB (McKeith et al, 2017) aged between 40 ‐90 years with a MMSE >15 were recruited from a multidisciplinary dementia clinic in this cross‐sectional study. MRI imaging was performed using a 3T Siemens scanner. DTI (diffusion tensor imaging), rsfMRI and structural images were gathered and analyzed through Infinitome (Rosenbloom et al, 2021), a program that creates a machine learning‐based, subject‐specific version of the Human Connectome Project‐Multimodal Parcellation atlas based upon diffusion tractography structural connectivity.ResultTwenty‐six participants were contacted, of which 14 (54%) were consented and one withdrawn by the investigator. Of the 13 subjects that completed the study, 77% were male, 100% white and non‐Hispanic origin, with mean age 73.29 years (± 5.8), and average MMSE score 23.14 (±4.3). All participants demonstrated abnormal connectivity in regions involving visuospatial attention (areas 8Av, PGs, TE2a) and language processing (areas 55b, TGd, TGv; Table 1; Baker et al, 2018). Five parcellations were part of the extended default mode network (DMN) whereas one was part of the extended central executive network. Seven participants demonstrated changes in connectivity of area 46 (R & L; cognitive processing and mood) within the salience network (SN).ConclusionPreliminary findings suggest reduced connectivity in regions involved in visuospatial attention, language processing, and mood within in large‐scale networks such as the DMN and SN, consistent with previously published fMRI studies in DLB (Nicastro 2021; Schumacher 2018). The use of rsfMRI and connectome mapping may enable identification of a distinct radiological “signature” for DLB. Future research will evaluate rsfMRI features that distinguish DLB from AD.
Testing the association of resting‐state functional connectivity of the hippocampus and prefrontal cortex with AD‐vulnerable executive functions in periadolescent children
Authors: Zatkalik Abigail L , Phipps Connor J , Ramirez Meghan K , Sexton Jennifer N , Heller Abi , Behm Lillian , Nickolas Kristen , Maerlender Arthur C. , Phatak Vaishali S , Cramer Justin A. , Blair James , Murman Daniel L , Warren David E 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) is an insidious neurodegenerative disease that is frequently associated with deficits in both memory and executive functions (EFs). EFs consist of a diverse range of cognitive processes, including inhibition, working memory, and cognitive flexibility. In AD and other disorders, dysfunction in EFs can result in attention deficits, decreased inhibition, and impaired decision‐making abilities. EFs have been historically linked to the prefrontal regions of the brain, but recent studies of brain networks and their functional connectivity have broadened these links to include brain regions such as the hippocampus (Hc). Building upon prior work, the current project investigated the association between decision making and hippocampal resting state functional connectivity (rs‐FC) in periadolescent children.MethodA cohort of healthy periadolescent children aged 8‐13 (N = 80) was sampled from the ongoing NIA‐funded Polygenic Risk of Alzheimer’s Disease in Nebraska Kids (PRANK) study. PRANK participants completed an array of cognitive and behavioral measures, in addition to an MRI of the brain. Decision making ability was assessed via the NIH Toolbox Dimensional Change Card Sorting (DCCS) task. The rs‐FC between the Hc and regions of the prefrontal cortex (PFC) was measured, and its covariance with DCCS was assessed.Resultrs‐FC of the Hc covaried with performance on the DCCS in the left dorsolateral prefrontal cortex (dlPFC) and dorsal anterior cingulate cortex (dACC). These anatomical regions are in line with larger intrinsic brain networks, such as the frontoparietal network (FPN) and the cingulo‐opercular network (CON).ConclusionThese preliminary results suggest the Hc is associated with anatomical regions and intrinsic brain networks that are important for EFs. A better characterization of the process by which EF occurs within the brain may drive further research that can assess ways to limit the decline of these cognitive abilities associated with healthy aging or brain pathology such as AD.
APOE‐e4 Status Moderates Associations between Executive Function and Air Pollution Exposure in Older Men
Authors: Franz Carol E , Elman Jeremy A. , Fennema‐Notestine Christine , Whitsell Nathan , Wu Tsung‐Chin , Tu Xin M , Qin Yongmei Amy , Kremen William S. 
Published: December 2022

AbstractBackgroundAir pollution, which includes exposure to tiny particulate matter (PM2.5) and Nitrogen Dioxide (NO2) is a notable public health hazard. Exposure has adverse effects on multiple health outcomes as well as with increased risk of developing cognitive impairment and Alzheimer’s disease and related dementias. Although the primary cognitive focus in Alzheimer’s disease is memory, there is growing recognition of the importance of early executive function (EF) deficits as a risk indicator. In addition, there is some evidence of genetic susceptibility to pollution‐related cognitive decline. Few studies have strong measures of air pollution, EF, as well as APOE genotyping. We recently showed that APOE genotype was associated with significant decline in EF from middle to early old age among individuals who were cognitively unimpaired at baseline (Gustavson et al, 2022). Here we tested the hypothesis that the impact of air pollution on executive functions would be greater in APOE‐ε4+ carriers compared with APOE‐ε4‐ individuals.MethodWe examined associations between exposure in midlife and EF from midlife to early old age in ∼800 men from the Vietnam Era Twin Study of Aging. Measures included average PM2.5 and NO2 exposure in the three years prior to the time 1 (mean age 56; range 51‐61) assessment, and an executive function factor score at time 1 and time 2 (mean age 68; range 65‐72). GEE analyses adjusted for multiple health and lifestyle covariates, as well as the random effect of family.ResultCognitive performance declined over time from age 56 to age 68 (F = 439.38, p<0.0001). There were no main effects of air pollution on EF. Overall APOE‐ε4+ carriers had higher EF performance than non‐carriers (F = 5.43, p = 0.02). In addition, we found a significant PM2.5‐by‐APOE genotype interaction (F = 8.80, p = 0.003). Increased exposure to PM2.5 in midlife was related to lower executive function in APOE‐ε4 carriers, but not non‐carriers. The interaction with NO2 did not reach significance (F = 2.83, p = 0.09).ConclusionThese results indicate that midlife PM2.5 exposure in men is associated with poorer frontal‐executive function, and APOEε4 carriers are more susceptible to the deleterious effects of PM2.5.
APOE genotype and blood pressure influence global and regional cerebral blood flow in older adults post‐high lipid feeding
Authors: Ashford Nathaniel K , Farris Kristen M , Levendovszky Swati Rane , Hanson Angela J 
Published: December 2022

AbstractBackgroundBoth hypertension and the E4 allele of the APOE gene are known risk factors for Alzheimer’s disease (AD). We investigated the influence of these factors on global cerebral blood flow (CBF) and four prespecified areas (angular gyrus, hippocampus, posterior cingulate, temporal lobe) using arterial spin labeling (ASL) MRI both in fasting state and after ingestion of a high fat drink.MethodAfter fasting, 29 older adults (age 66.8 ± 4.1) underwent baseline and 1, 2, 3‐hour ASL MRI after ingestion of 1/2 cup heavy cream with comparable total and saturated fat to a high fat breakfast. We used pCASL MRI with background suppression to measure CBF in ml/100g/min. Imaging parameters were in accordance with the recommendations of ISMRM: label duration = 1.8 s, postlabeling delay = 2 s, labeling offset = 25‐30 mm, slices = 20, resolution = 3.5×3.5×5 mm3, SENSE‐factor = 2, TR/TE= 5000/18 ms. Finally, we acquired a reference scan (M0, 1 minute) identical to above scan but with TR = 10,000 ms and no labeling or background suppression. Statistical analyses included repeated measures ANOVA as well as cross‐sectional multiple regressions with robust estimators adjusting for age, E4 status, BMI, heart rate, systolic and diastolic blood pressure (DBP).ResultGlobal CBF decreased at 1‐, 2‐, and 3‐hours post‐lipid drink, compared to time 0 (RM ANOVA F=5.57, p=0.002). These findings were recapitulated in the posterior cingulate (F=3, p=0.036) and hippocampus (F=3.3, p= 0.025); this difference was not seen in the temporal lobe or angular gyrus. E4 genotype was significantly associated with lower global CBF at hour 2 and in three areas examined (Table). Additionally, higher DBP was associated with lower CBF globally and in all four areas (Table).ConclusionCBF decreased in response to lipid ingestion, both globally and in regions known to be important in AD, and this was exaggerated in individuals with the E4+ genotype and with elevated DBP. Further examination of E4 and blood pressure interactions are ongoing, as well as how these findings relate to cognitive performance.
3D chromatin structure in human macrophages and iPSC‐derived microglia identifies putative Alzheimer’s Disease risk genes
Authors: Bond Marielle L , Quiroga Ivana Yoseli , Sahasrabudhe Isha R , Won Hyejung , Phanstiel Douglas H 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) genome‐wide association studies (GWAS) identified 75 disease‐associated loci. The vast majority of risk variants are located in non‐coding genomic regions, suggesting a regulatory function (i.e. enhancer activity). Enhancers can regulate distal genes via DNA loops, bringing elements millions of base pairs away into close physical proximity in three‐dimensional (3D) space. Mapping 3D chromatin contact frequencies using Hi‐C can reveal enhancer‐promoter connections and assign disease‐associated variants to putative causal genes. Because enhancer and 3D chromatin structures are cell‐type specific, it is critical to map these features in the relevant cell type and biological context. Genetic risk factors for AD are located within microglia and macrophages chromatin‐accessible regions. The aim of this work was to map 3D chromatin structures in human microglia and macrophages and intersect them with AD GWAS to identify novel genes regulated by non‐coding AD risk variants.MethodWe performed deeply sequenced Hi‐C, RNA‐seq, ATAC‐seq, and Cut&Run targeting histone H3K27 acetylation to map regulatory networks in THP‐1 macrophages and human iPSC‐derived microglia‐like cells (IMGLs). Next, we performed differential analysis to identify cell‐type specific differences in 3D chromatin structure, enhancer activity, and gene expression. Finally, we intersected these regulatory networks with AD GWAS to identify variants that may disrupt these networks and reveal novel AD risk genes for further study.ResultWe identified 19,608 chromatin loops, 766 of which were specific to either cell type. These loops connected 14,413 enhancers (8,023 of which were cell‐type specific) to 7,548 genes (2,280 of which differed between cell types). Cell‐type specific regulatory features correlated with cell‐type specific gene expression. For example, a microglia‐specific loop connected a distal regulatory loci to the promoter of PER1, which was also upregulated in microglia and has a known role in circadian rhythm regulation, underscoring microglia’s known circadian‐regulated behavior.ConclusionWe identified cell‐type specific regulatory networks in human macrophages and microglia. While these networks exhibited similarities, we identified thousands of enhancer‐promoter connections that differed. Intersecting with AD GWAS enables us to identify cell‐type specific genes regulated by non‐coding AD risk variants and reveal novel regulatory connections that would be otherwise unknown.
The influence of Apolipoprotein E ε4 carrier status on posterior cingulate cortex thickness and learning
Authors: Slutsky‐Ganesh Alexis B , Park Kyoung Shin , Anderson Travis , Hugenschmidt Christina E , DuBois Samantha L , Vance Jarod C , Ueno Aiko , O'Brokta Megan M , Kibildis Samuel , Holder Hadassah , Labban Jeffrey D , Wideman Laurie , Etnier Jennifer L 
Published: December 2022

AbstractBackgroundThinning of the posterior cingulate cortex (PCC) is implicated in Alzheimer’s disease (AD). Though some evidence suggests ApolipoproteinE (APOE) ε4 carriers (ε4+) have thinner PCCs than non‐carriers (ε4‐), the evidence is conflicting and lacks association with learning outcomes relevant to AD.MethodA subset from an ongoing clinical trial (NIH/NIA: R01AG058919) was used for analyses and included 26 ε4+ (73% female, Agemean=55.81±5.53) and 42 ε4‐ (88% female, Agemean= 57.54±5.10), who were all cognitively normal, sedentary, and had a family history of AD. Genetic sampling was completed via passive drool. Structural MRI was completed to assess PCC cortical thickness, and the Rey Auditory Verbal Learning Task (AVLT) was used to assess learning. Brain segmentation was completed with Freesurfer’s automated pipeline, and left and right PCC cortical thickness was extracted for analysis. A learning over trials (LOT) composite score from the AVLT was calculated to represent learning. An analysis of covariance was completed to assess the effect of carrier status on left/right PCC thickness, controlling for age and sex. Linear regressions were completed to assess main effects and interaction of carrier status and left/right PCC thickness in predicting LOT when controlling for age and sex.Resultε4+ had less cortical thickness in the left PCC (F(1,64)=5.07, p=.03), but not the right PCC (p=.33), relative to ε4‐. Carrier status predicted LOT (Left: F(1,62)=10.37, p<.01; Right: F(1,62)=10.66, p<.01), however this was superseded by significant interactions between carrier status and PCC thickness predicting LOT (Left: F(1,62)=10.72, p<.01; Right: F(1, 62)=11.10, p<.01), with post‐hoc analyses demonstrating PCC thickness predicts LOT for ε4+ (Left:β=‐21.07, p=.04; Right:β=‐24.33, p<.01), but not ε4‐ (p’s>.09).ConclusionIn cognitively normal sedentary adults with a family history of AD, carrying the APOE ε4 allele was associated with a thinner left PCC. Further, thinner bilateral PCCs in ε4+ were associated with greater learning during the AVLT task. This suggests that ε4+ may have compensatory neural pathways to account for losses in the PCC, which temporarily bolster learning to delay the onset of AD. However, additional research is needed to continue understanding the neural mechanisms affected by carrying the APOE ε4 allele.
Investigating the associations between regional tau burden measured using [F18]‐MK6240 positron emission tomography, clinical and cognitive outcomes
Authors: Quenon Lisa , Gérard Thomas , Malotaux Vincent , Dricot Laurence , Lhommel Renaud , Colmant Lise , Ivanoiu Adrian , Hanseeuw Bernard J 
Published: December 2022

AbstractBackgroundThe recent development of positron emission tomography (PET) radiotracers for tau aggregates allows visualizing tau pathology in vivo. The aim of this study was to investigate the associations between regional tau‐PET binding, measured using [18F]‐MK6240, a promising second‐generation tau‐PET tracer, and clinical and cognitive outcomes.Method125 participants were recruited between June 2019 and April 2022 at the Memory Clinic of Saint‐Luc University Hospital. Each participant underwent [F18]‐MK6240 tau‐PET, MRI, cognitive assessment, and either lumbar punction or [F18]‐Flutemetamol amyloid‐PET. A visual read of tau‐PET images was performed according to the Braak stage classification. Tau‐PET imaging data were also quantitatively processed using PMOD‐Neuro tools and Freesurfer. Cognition was assessed using four composite scores evaluating memory, language, executive and visuospatial functions.ResultBraak 0 visual reads included 12 cognitively unimpaired, 7 SCI, 5 MCI due to AD (MCI AD), and 7 non‐AD patients (Fig.1). The number of MCI AD cases ranged from Braak 0 to Braak 5 categories, while the number of patients with AD dementia ranged from Braak 4 to Braak 6. Only 3 non‐AD cases had positive scans (1 APP Aβ‐, 1 FTLD, 1 PART). On average, in Braak 0‐2 cases, all cognitive composite scores were in the normal range (Fig.2). In Braak 3‐4 cases, only episodic memory was impaired, while in Braak 5‐6 cases all cognitive domains were impaired.ConclusionVisual Braak staging of [F18]‐MK6240 PET images matches clinical diagnosis of MCI, AD dementia and non‐AD dementia. Moreover, cases with neocortical temporal uptake (Braak 3‐4) accordingly presented isolated episodic memory, while cases with extensive neocortical uptake (Braak 5‐6) were impaired in almost all cognitive domains. Correlational analyses are currently ongoing to test whether the associations between regional tau burden and cognitive scores map onto established brain‐behavior relationships.