bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of SUPERBRAIN program in Amyloid PET positive mild dementia patient: Cognitive outcome, EEG and stool microbiome
Authors: Lee Eun Hye , Choi Seong Hye , Jeong Jee Hyang 
Published: December 2022

AbstractBackgroundThe effect of SUPERBRAIN (multi‐domain lifestyle intervention program), on the mild stage of AD positive mild stage of dementia for an 8‐week treatment in the cognitive function, EEG and stool microbiom outcome.MethodA total of 58 amnestic MCI or early stage of mild dementia patient (CDR 0.5‐1) with amyloid PET positive, were recruited. Patients were randomized to either three group of 1) Superbrain with Memory pack group, 2) Memory pack only group, 3) control group. Memory Pack is nutritional support that is supplied by Daesang Yuup that is specially designed for brain reinforcing formula such as choline, serine, glycine, etc. Cognitive training programs and exercise programs were conducted two persons in a group session twice in a week for the 8 week in the hospital. The primary outcome was the change in the total scale of index score of the Repeatable Battery for the Assessment of Neuropsychological Status (RBARNS) after 2 months of training. Analysis of covariance was used to compare the index score of the RBANS between the three groups.ResultThe age was 75.70 (5.26) in treatment group, 75.75 (5.80) for Memory pack only group, 75.00 (6.50) for control group (P value. 0.967). The baseline MMSE scores were 22. 38 (3.50) in treatment group, 20.75 (1.75) for Memory pack only group, 21.63(2.50) for control group (P value. 0.492). RBARNS score showed improvements in the total RBARNS scale index score (72(15.78) in Baseline to Fup 78.88(16.51) in the treatment group (P value 0.05) compared to Memory pack only (75.38(9.02) in Baseline to Fup 79.00(8.68) (P value 0.045) and control group (75.38(11.90) in Baseline to Fup 75.75(18.79) (0.970). The MMSE were significantly improved in both treatment group (22.38, 24.13; p = 0.013) and Memory pack only group(20.75,22.57, P = 0.045) as well but worsened in control group (21.63, 20.00 P = 0.142) compared to baseline. The CDR sum of box statistically worsened in the control group compared to treatment group and memory pack group.ConclusionCognitive improvement was evident even in this short term 8 weeks of multi‐domain intervention program of for AD dementia which needs further study for the long‐term outcome.
Integrating genetic correlation, polygenic risk scores, and Mendelian randomization to identify modifiable risk factors for Alzheimer’s disease
Authors: Andrews Shea J , Fulton‐Howard Brian , Bennett David A , Goate Alison 
Published: December 2022

AbstractBackgroundTo reduce the population prevalence of Alzheimer’s disease (AD), it is critical to identify risk factors that modify AD risk. Methods of causal inference that exploit genomic information, such as genetic correlation (rg), polygenic risk scores (PRS) and Mendelian randomization (MR), can overcome some of the limitations of observational studies such as confounding and reverse causation. Here we use rg, PRS, and MR to investigate causal associations between twenty‐two risk factors and eleven AD outcomes.MethodsUsing GWAS summary statistics, rg was estimated using GNOVA and bidirectional MR causal estimates using LHC‐MR. The exposures included alcohol intake, physical activity, lipid traits, blood pressure traits, diabetes, BMI, depression, insomnia, social isolation, smoking, diet, and education. The outcomes included AD, AD age of onset, hippocampal volume, CSF Aβ42, tau, and Ptau181 levels, and amyloid, tau, cerebrovascular neuropathology. PRS for the exposures were constructed using PRSice in ADGC (n = 25,431), ADNI (nmax = 1,718), and ROSMAP (nmax = 1,675), and their association with AD diagnosis, CSF biomarkers, PET imaging, MRI imaging, and neuropathology was evaluated.ResultsAfter accounting for multiple testing, 71, 1, and 38 trait pairs were significant in the rg, PRS, MR models respectively. The only significant trait pair identified across all three methods was a protective effect of higher educational attainment on AD (rg = ‐0.161, p = 3.78e‐14; bPRS [se] = ‐0.07 [0.014], p = 8.88e‐7; bMR [se] = ‐0.21 [0.042], p = 2.43e‐7). Seventeen trait pairs had both significant genetic correlations and causal MR estimates. In particular, increased cortical surface area was positively correlated with higher educational attainment (rg = 0.261, p = 1.46e‐18), with MR indicating that genetically predicted cortical surface area was causally associated with higher education (bMR [se] = 0.27 [0.042], p = 3.21e‐10), but not vice versa (bMR [se] = ‐0.09 [0.072], p = 0.224).ConclusionsWe evaluated causal relationships between risk factors and AD endophenotypes using genomic information. The protective effect of education on AD is supported by genetic correlation, PRS and MR, potentially due to increased cognitive resilience resulting from increased cortical surface area.
Broad‐ranging effects of APOE4 on cellular protein expression in neural precursors
Authors: Paul Pradip , Ramakrishna Sarayu , Ghose Vivek , Dey Gourav , Muddashetty Ravi S , Purushottam Meera , Viswanath Biju , Jain Sanjeev , Sud Reeteka 
Published: December 2022

AbstractBackgroundIt is increasingly becoming evident that ApoE4 isoform contributes to AD risk over the life course of individuals. Much remains unknown about the biological pathways that connect APOE4 genotype with the development of pathology that eventually leads to AD, nor do we know how early in life these cellular alterations begin. To answer these questions, we derived neural precursor cells (NPCs) from induced pluripotent stem cells (IPSCs) that were CRISPR‐edited at APOE locus (Ramakrishna et al. 2021; Schmid et al. 2019). We intended to characterize the protein expression landscape in the NPCs subsequent to targeted deletion of E4 from a parent IPSC line of APOE3/4 genotype.MethodsProtein isolates from NPCs were analyzed on the Thermo Scientific‐ Orbitrap Fusion instrument and the resulting Mass Spectrometer data was searched against a reference human protein database using Proteome Discoverer 2.2. Differentially expressed proteins (DEP) were determined from the protein abundance fold change values obtained for each protein. Proteins which showed >1.2‐fold difference with FDR adjusted P‐value < 0.05 were considered differentially expressed. DEPs were mapped to STRING database (v11.5) for retrieval of interacting proteins and functional enrichment.ResultsCRISPR‐editing of E4 from the parent line revealed 105 differential expressed proteins. Of these, 62 were upregulated, and 43 were downregulated. Further analysis of the DEPs via STRING database showed that these changes primarily affect pathways linked to RNA processing, plasma membrane repair, and cytoskeleton organization.ConclusionsOur primary motivation was to determine proteomic alterations with targeted deletion of E4. And indeed, we find the effects of E4 extend beyond proteins considered central to AD pathology. Knowing more about the protein interactions regulated by ApoE, in an isoform‐specific manner, has the potential to reveal novel drug targets. In future experiments, we intend to follow the DEPs identified here and the associated pathways through the course of neural differentiation.
In vivo biomarkers of arteriolosclerosis are associated with ADRD biomarkers
Authors: Rundle Melissa M. , Peavey Jeremy J. , Barcus Richard A. , Okonmah‐Obazee Stephanie E. , Espeland Mark A. , Sai Kiran K Solingapuram , Whitlow Christopher T. , Williams Benjamin J. , Craft Suzanne , Bateman James R. , Lockhart Samuel N. , Hughes Tim M. 
Published: December 2022

AbstractBackgroundBrain arteriolosclerosis, which involves thickening of the vessel wall and stenosis of arterioles, is one of the main pathologies of cerebral small vessel disease, and often co‐occurs with other pathology indicative of Alzheimer’s disease and related disorders (ADRD). A novel classifier of arteriolosclerosis, ARTS, was recently developed by the MarkVCID consortium for in vivo studies of arteriolosclerosis. We hypothesized that higher levels of arteriolosclerosis are associated with worse ADRD biomarker levels.Method109 participants from the Wake Forest Alzheimer’s Disease Research Center’s Clinical Core underwent clinical and cognitive evaluation, 3T brain MRI, and PiB (amyloid) PET (n=92). Participants were adjudicated by NIA‐AA criteria as having normal cognition (n=69), mild cognitive impairment (n=25), or dementia (n=15). Raw T1, FLAIR, and TOPUP and Eddy Current Corrected DTI images along with age and sex were inputs to a machine learning based classifier generating ARTS scores; higher ARTS indicates higher likelihood of arteriolosclerosis. For variables of interest, T1 MRI were processed (FreeSurfer v5.3) to calculate cortical gray matter (GM), hippocampal, and intracranial (ICV) volumes, and temporal meta‐ROI cortical thickness. White matter hyperintensity (WMH) volumes were calculated on FLAIR with LST in SPM12. NODDI were processed using AMICO to generate mean Free Water (FW) in hippocampus and global GM and white matter (WM). A set of AD‐sensitive cortical ROIs were used to extract mean PET SUVr signal. Separate multivariable general linear models (GLM) examined relationships between ARTS and variables of interest adjusted initially for age and total ICV (Table 1), and then again after adjusting for additional covariates (sex, race, education, APOE‐e4 carrier status, and clinical diagnosis).ResultAmong 109 participants (71±7 years, 60% women), ARTS ranged from ‐.80 to .29 (mean±SD = ‐.37±.20), suggesting a low overall likelihood of arteriolosclerosis in our sample. Higher ARTS was significantly associated with lower cortical thickness, higher WMH, higher WM FW, and greater amyloid deposition (Table 1). When adjusting for additional covariates, only amyloid no longer significantly associated with ARTS (p=0.19).ConclusionHigher ARTS scores are cross‐sectionally associated with other abnormalities in ADRD biomarkers. Future directions will examine the relationship between ARTS and Flortaucipir (tau) uptake.
Using Technology to Overcome the Challenges of COVID‐19 Pandemic in India: The DEMCARES Model of Virtual Intervention Delivery
Authors: Vaitheswaran Sridhar , Natarajan Nirupama , Ramanujam Vaishnavi , S Subashini , Venkatesan Shreenila , Srinivasan Nivedhitha , Nagarajan Gayathri , Balasubramanian Suhavana 
Published: December 2022

AbstractBackgroundThe COVID‐19 pandemic and associated restrictions have greatly affected the delivery of treatment and access to in‐person interventions for dementia, especially in low‐ and middle‐income countries such as India. Technology use could potentially help bring the above‐mentioned services to persons with dementia (PwD) and their caregivers in the safety of their homes. The aim of this study is to evaluate the dementia care services delivered by the Dementia Care in SCARF (DEMCARES) team in the densely populated city of Chennai in South India during the COVID‐19 pandemic.MethodsWe reviewed teleconsultation logs, records of dementia‐related services and interventions offered to both PwD and their caregivers at the DEMCARES clinic between July 2020 and December 2021 during the COVID‐19 pandemic. Moreover, we collected feedback from PwD and caregivers regarding virtually delivered dementia interventions and analyzed them to understand benefits, barriers, and facilitators.ResultsIn addition to in‐person outpatient clinic, teleconsultation for PwD and behavioral and psychological symptoms of dementia management training for caregivers through audio/videoconferencing was provided to those with access to technology. Interventions, such as STrAtegies for RelaTives (START) and Cognitive Stimulation Therapy (CST) that were originally delivered face‐to‐face, were adapted for virtual delivery to cater to the needs of persons with dementia and their caregivers in Chennai, India. Furthermore, dementia awareness course for caregivers and caregiver support groups were also conducted online. Feedback from PwD and their caregivers were largely positive, and the numbers reached were higher during the pandemic than before.ConclusionBeing situated in an urban setting, the DEMCARES team of professionals were able to reach many PwD and their caregivers who had access to technology. Despite some of its limitations, technology holds a great potential for providing uninterrupted treatment and interventions for dementia in addition to considerably improving access to care, especially during the pandemic.
Cell‐Level Transcriptomic Network Analysis Provides Insights into Distinct Biological Mechanisms for Alzheimer’s Disease Enabling Targeted Drug Repositioning
Authors: Sahelijo Nathan , Hu Junming , Priyadarshi Dhawal , Panitch Rebecca , Shen Li , Thompson Paul M , Saykin Andrew J. , Huang Heng , Nho Kwangsik , Crane Paul K. , Davatzikos Christos , Jun Gyungah R 
Published: December 2022

AbstractBackgroundThe phenotypic and genetic heterogeneity of Alzheimer’s disease (AD) complicates efforts to identify the underlying biological mechanisms. Cell‐specific biologically connected gene networks may explain some of the observed pathophysiological and cognitive heterogeneity, leading to more effective patient stratification and drug targeting strategies.MethodWe conducted cell‐level network analysis using single nuclei RNA‐sequencing data from post‐mortem prefrontal cortex areas of 24 AD and 24 control brains in the Religious Orders Study and Memory and Aging Project (ROSMAP) for discovery and 12 AD and 9 control brains in the South‐West Dementia Brain Bank study for validation. We selected the AD associated modules from the preserved modules with significant differences between AD cases and control brains. The mbPRS was validated by previously defined (1) distinct brain atrophy clusters, and (2) cognitively defined AD subgroups including AD‐Executive, AD‐Language, AD‐Memory, AD‐Visuospatial functioning, AD‐No Domains, and AD‐Multiple‐domains. We conducted an association test with each mbPRS using the assigned membership variable as a binary outcome in a logistic regression model. We identified existing drugs targeting genes from the top‐ranked modules for repurposing in AD therapeutics.ResultAmong 60 cell‐level modules, 12 modules were preserved in the validation set and significantly associated with AD (P<0.05). The mbPRSs for an astrocyte and an oligodendrocyte module M45 showed significant association with diffuse brain atrophy linked with proportionally lower executive functioning scores (PM2=7.40E‐5; PM45=2.12E‐4), and medial temporal atrophy likely representing early stages of AD (PM2=2.72E‐6; PM45=2.40E‐5). The mbPRS for M2 was significantly (PM2=2.72E‐2). Pathway analysis of the module gene sets revealed potential drug candidates for repositioning, including drugs targeting ApoE and IL1b pathways.ConclusionBy integrating genetics, cell‐level transcriptome networks, and endophenotypes of AD we confirmed cell‐level polygenic risk scores can stratify individuals into different target groups that are correlated with previously classified subgroups using cognitive functions and imaging biomarker data.
Retention of Participant and Study Partner Dyads in Alzheimer’s Disease Clinical Trials
Authors: Nuño Michelle M , Gillen Daniel L. , Grill Joshua 
Published: December 2022

AbstractBackgroundStudy retention is crucial to clinical trial success. Greater than expected dropout rates can lead to reduced power and biased results. Alzheimer’s disease (AD) trial success depends not only on participants but also on their study partners. We investigated whether study partner type was associated with the risk of dropout in large Phase 3 registration trials.MethodWe used data from two trials of bapineuzumab for patients with mild‐to‐moderate AD. Data were provided by the sponsor of the trials, Janssen Research & Development, LLC for use in these analyses. The co‐primary endpoints were the change from baseline to week 78 in the Disability Assessment for Dementia (DAD) and the 11‐item AD Assessment Scale (ADAS Cog‐11). We defined completers as participants with baseline and week 78 scores on ADAS Cog‐11 or DAD. Participants were excluded from our analyses if they did not declare a study partner type in the Resource Utilization in Dementia‐Lite (RUD‐Lite) or if they were missing ADAS Cog‐11 and DAD at baseline. Time‐to‐dropout was defined as the time from study enrollment to the time of the last visit during which ADAS Cog‐11 or DAD were conducted.ResultData were available for 1,234 participants in the non‐carrier study and 1,221 participants in the carrier study. Table 1 presents baseline characteristics for participants included in our analysis (n = 1,229 non‐carriers and n = 1,097 carriers). In both trials, we observed a higher proportion of participants enrolled with a spouse (non‐carriers: 817, 66.3%; carriers: 837, 76.3%). Approximately 75% of spousal dyads completed the non‐carrier trial, while 60% of adult‐child dyads and 54% of dyads with other study partners completed the trial. Differences in the proportion of completers were lower in the carrier study, with approximately 75%, 73%, and 70% of completers among spousal, adult child, and “other” dyads. The same trend for time‐to‐dropout can be seen in Figure 1.ConclusionWe found that a higher proportion of spousal dyads completed the trials compared to other dyad types. Understanding the factors driving these associations may help understand reasons for dropout and could lead to the development of retention strategies.
Impact of Mild Behavioral Impairment and Mild Cognitive Impairment on Risk for Dementia
Authors: Rouse Hillary J , Small Brent J , Ismail Zahinoor 
Published: December 2022

AbstractBackgroundThere has been a shift in research to explore early indicators associated with preclinical/prodromal dementia. Recent research highlights the importance of non‐cognitive factors, such as neuropsychiatric symptoms (NPS), as articulated in criteria for mild behavioral impairment (MBI). Previous research suggests MBI is a risk factor for dementia regardless of if one is cognitively healthy or diagnosed with mild cognitive impairment (MCI). The goal of this study is to examine risk for dementia subtypes based on the presence of MBI and/or MCI.MethodSecondary data analysis of participants (n = 17,289) from the National Alzheimer’s Coordinating Center who were cognitively healthy (n = 11,770) or diagnosed with MCI (n = 5,519). Risk for dementia, Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD) were examined using Cox proportional hazard models.ResultAlmost 25% of the entire sample met the operationalized diagnostic criteria for MBI (n = 4,274). The risk for dementia almost tripled among persons with MBI and increased by almost seven‐fold if they had MCI. Among persons with MBI, the risk for FTD was six times greater and the risk for DLB and AD was three times greater, compared to those without MBI. Additionally, for participants who had MCI, the risk for DLB was six times greater, the risk for AD was over nine times greater, and the risk for FTD was almost sixteen times greater, compared to those who were cognitively healthy. There was a significant interaction found between MBI and MCI status. For cognitively healthy older adults with MBI, the risk was almost eleven times greater for FTD, whereas for older adults with MCI and MBI, the risk was three times greater for DLB.ConclusionOlder adults with MBI and MCI are at an increased risk for all types of dementia. Additionally, cognitively healthy participants with MBI are found to have a greater risk for FTD, where participants with MCI and MBI had a greater risk for DLB. These results provide support for MBI as a prodromal state of all‐cause dementia, and highlight the importance of recognizing these symptoms across the spectrum of cognitive decline.
Genetic heterogeneity of four MCI/AD neuroanatomical dimensions discovered via deep learning
Authors: Wen Junhao , Cui Yuhan , Yang Zhijian , Bao Jingxuan , Chen Jiong , Erus Guray , Abdulkadir Ahmed , Mamourian Elizabeth , Singh Ashish , Yang Shu , Fan Yong , Saykin Andrew J. , Thompson Paul M , Jun Gyungah R , Ritchie Marylyn D. , Shen Li , Wolk David A. , Shou Haochang , Nasrallah Ilya M. , Davatzikos Christos 
Published: December 2022

AbstractBackgroundData‐driven unsupervised and semi‐supervised clustering methods have parsed neuroanatomical heterogeneity of Alzheimer's disease (AD) and/or mild cognitive impairment (MCI) into multidimensional neuroimaging representations (Vogel et al., 2021; Wen et al., 2021b, 2021a; Yang et al., 2021; Young et al., 2018; Zhang et al., 2016). However, whether this neuroanatomical heterogeneity is partly underpinned by genetic heterogeneity remains unanswered.MethodWhole‐genome sequencing (WGS) data were analyzed for individuals in the Alzheimer’s Disease Neuroimaging Initiative. WGS data underwent a standard genetic pipeline. This resulted in 1,487 participants (428 healthy controls, 489 MCI and 570 AD; age = 78.96 ± 7.72; 44.05% females) with 24,773,167 single nucleotide polymorphism (SNP). The deep learning Smile‐GAN model (Yang et al., 2021) generates expression scores (ES) across each of the four subtypes of MCI/AD (Fig. 2). The ES of each subtype were used as phenotypes in genome‐wide association studies (GWAS). Specifically, we performed multiple linear regressions controlling for age, sex, intracranial volume, disease diagnosis, and the first four genetic principle components using Plink (Purcell et al., 2007). We then performed clumping to define the independent significant variants (ISVs).ResultGWAS discovered 17 ISV‐ES pairwise associations. WGS data allowed us to identify four de no ISVs that were not included in dbSNP (Fig. 1). P1 and P4 detected similar AD‐related genetic variants (e.g., APOE, NECTIN2, and TOMM40, Fig. 1 and 2), but with opposite directions of effect, i.e., protective factors for P1 and risk factors for P4, consistent with respective patterns of neurodegeneration in these phenotypes. In particular, for rs429358 (APOE‐4), the P4 subtype had more C alleles (minor allele) than the P1 subtype (P‐value < 1e‐20). The four ISVs identified for P2 and P3 were not previously associated with any clinical trait.ConclusionThe current study identified genetic heterogeneity related to the expression of four MCI/AD subtypes previously defined via Smile‐GAN. Notably, our results confirmed previous findings that AD is genetically heterogeneous (Nacmias et al., 2018), identifying known genetic risk factors and several novel variants. Further research is needed to understand how these variants may affect AD pathophysiology and determine if any may provide a therapeutic target.