bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging the use of meta‐analysis summary statistics to improve gene expression prediction models
Authors: Mews Makaela , Naj Adam C. , Below Jennifer , Bush William S. 
Published: December 2022

AbstractBackgroundGenetically regulated gene expression as assessed via Transcriptome‐wide association studies (TWAS) can be used to elucidate the mechanistic basis Alzheimer’s Disease. A limitation of current TWAS approaches is the requirement for individual‐level datasets with both genotypes and gene expression measures to produce effective prediction models. We sought to improve the predictive performance of existing gene‐based models by leveraging easily accessible summary statistics that are powered by large sample sizes.MethodsBrain cis‐eQTL data produced from a large‐scale meta‐analysis was restricted to data from European‐descent individuals and samples taken from Brain‐Cortex (Average_N=2,547). The effect size estimates, and their standard errors from the individual cohorts (N=14) were used to re‐run a meta‐analysis excluding GTEx data via METAL.To perform gene‐based elastic‐net regressions using the produced summary statistics, the lassosum R package produced by Mak et al. 2017 was applied to genotype data from the 1,000 Genomes data (GRCh38) serving as a reference panel and GTEx_v8 genotype, normalized Brain‐Cortex gene expression, and covariate data (N=205) serving as a testing panel for model validation and dynamic selection of the optimal mixing/penalty parameters. The maximum R2 produced by this pipeline was compared to elastic‐net models generated by PredictDB using Brain‐Cortex GTEx_v8 data where the mixing parameter was set at 0.5.ResultsOur pipeline produced gene‐based models that had an improved predictive performance averaging 9.8% (SD: 7%) based on R2 over PredictDB models in 93.7% of genes tested (N=3,965) when restricting our pipeline to SNPs found in PredictDB. The optimal mixing parameter dramatically differed from PredictDB with a median of 0.009 highlighting the utility of including variants with small effects. Even restricting the mixing parameter to 0.5 for genes with a converged model, our pipeline outperformed PredictDB in 85% of genes (N=369). By examining expression prediction metrics to genes from the KEGG Alzheimer’s Disease pathway (hsa05010), our pipeline had improved performance in 100% of matched genes (N=30).ConclusionWe demonstrate improvement upon existing TWAS reference panels and increase gene‐expression predictive performance by leveraging the power of summary statistics. Our findings show AD association studies based on TWAS approaches may be improved by meta‐analysis reference panels.
Persistent neurological and cerebrovascular deficits following ischemic stroke in a transgenic mouse model of Alzheimer’s disease
Authors: Clary Briana L , Nwafor Divine C , Hernandez Chloe G , Golestanian Omid , Macom Rhiannon V , Brown Candice 
Published: December 2022

AbstractBackgroundTissue nonspecific alkaline phosphatase (TNAP) is one of the most abundant enzymes in brain cerebral microvessels, although its function in human health and disease remains less clear. Our lab has demonstrated that the loss of TNAP activity in cerebral microvessels is linked to diminished blood‐brain barrier function and decreased cerebrovascular integrity in mouse models of sepsis, ischemic stroke, and Alzheimer’s disease (AD). While it is widely known that stroke and AD are comorbid, the relationship between existing AD and its impact on outcomes following ischemic stroke is less clear. The goal of this study was to assess the impact of a moderate cortical ischemic stroke on post‐stroke sensorimotor deficits and AD‐like neuropathology in a mouse model of AD. We hypothesized that post‐stroke loss of TNAP activity is accompanied by a persistent loss of cerebral blood flow (CBF), exacerbated sensorimotor deficits, elevated neuroinflammation, and increased beta‐amyloid deposition.MethodMale and female APPSwID/iNOS‐/‐ (CVN‐AD) mice, 10‐12 months old, were subjected to a cortical photothrombotic stroke (AD+PTS) or sham (AD+sham) surgery and euthanized at seven days post‐stroke. Daily neurological scores, corner test, and rotarod were performed to assess sensorimotor deficits. CBF was assessed by laser speckle contrast imaging (LSCI) prior to euthanasia. Saline‐perfused and 4% paraformaldehyde fixed tissue sections underwent histological staining to quantify infarct volume, cerebral microvessel TNAP activity, and microhemorrhages. Immunostaining assessed astrogliosis, via glial fibrillary acidic protein (GFAP), microgliosis, via Iba‐1, and beta‐amyloid deposition.ResultIschemic stroke impaired performance on the corner test (p=0.0054) and rotarod (p=0.0138) in PTS+AD compared to sham+AD mice. At seven days post‐stroke CBF was diminished (p<0.0001) while Iba‐1 immunolabeling revealed increased microgliosis in the ipsilateral cortex (p<0.0001) and ipsilateral hippocampal CA1 (p=0.0022) in PTS+AD compared to sham+AD mice. A preliminary quantification of TNAP activity in the non‐infarcted ipsilateral hemisphere revealed a trending decrease in PTS+AD mice. No sex differences were observed.ConclusionSensorimotor deficits and microgliosis were increased while CBF was decreased at seven days post‐stroke in PTS+AD compared to sham+AD mice. These and other indices will be compared with age‐matched wild‐type mice in ongoing experiments.
Reducing the Effects of Aging on Cognition with Therapeutic Intervention of an Oral multi‐Nutrient combination (REACTION): Study Design and Baseline Results
Authors: Camargo Christian J , McInerney Katalina , Merritt Stacy S , Modjeski Marisa , Counotte Danielle , Rundek Tatjana 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) is the most common cause of dementia, and the risk of developing AD increases with age. Age‐related cognitive decline (ARCD) refers to the cognitive changes that can occur in individuals because of aging. Research suggests that the underlying mechanism behind ARCD is a loss of synaptic plasticity and altered dendritic spine morphology. Similarly, the cognitive changes in AD are also thought to arise from impaired synaptic plasticity and dendritic spine loss. Souvenaid, contains a specific combination of precursors and cofactors for phospholipid biosynthesis, and has shown beneficial effects on memory, cognition, and brain atrophy in prodromal AD. In addition, data from this previous study imply a stronger effect would be expected in participants at earlier stages of prodromal AD. To test the effect of Souvenaid in ARCD, the REACTION (Reducing the Effects of Aging on Cognition with Therapeutic Intervention of an Oral multi‐Nutrient combination) pilot study was developed.MethodREACTION1 is a 6‐month single‐center randomized, double‐blind placebo‐controlled pilot clinical trial. The study factors in local COVID‐19 restrictions and is conducted fully virtually. Participants will be aged 55‐89 with ARCD, and screened and randomized to the oral multi‐nutrient combination (Souvenaid) or placebo on a 1:1 basis.The main outcome of this trial is feasibility (recruitment rate and time, adherence rate and retention rate). Other outcomes include memory (e.g. Ray Verbal Learning Task), cognition (e.g. Oral Trail Making Test), and quality of life (e.g. Amsterdam IADL Questionnaire) outcome measures.ResultOf 141 inquiries over 7 months, 60 eligible participants were recruited. 54 were successfully screened for randomization. As of 3 Feb 2022, 47 participants have been randomized to placebo or Souvenaid (6 are awaiting randomization, 1 withdrew prior to randomization.) Detailed baseline characteristics of the study population will be presented at the meeting, including descriptive statistics on demographics and the inclusion criteria such as the RBANS, MoCA and SCD 9‐item brief screening tool score.ConclusionWith the rapidly growing prevalence of ARCD and limited pharmacological curative treatment options currently available, nutritional interventions may potentially play an important role to prevent or delay the onset of ARCD.1. Clinicaltrial.gov identifier: NCT04147624
Development and validation of AI‐based tools for brain amyloid‐β detection using MRI
Authors: Devanarayan Viswanath , Charil Arnaud , Nelson Todd , Qi Xin , Murali Leema , Reyderman Larisa , Irizarry Michael C , Koyama Akihiko , Dhadda Shobha 
Published: December 2022

AbstractBackgroundNon‐invasive methods for brain amyloid‐b (Ab) detection are needed for effective patient care, and for faster and more cost‐effective screening of patients in clinical trials. Using MRI and other patient screening data from internal clinical trials, we employ artificial intelligence (AI) algorithms to develop brain Aβ positivity detection tools and validate their performance in independent datasets.MethodTraining dataset included structural MRI and several cognitive assessments obtained during screening of 1960 patients from a clinical trial. Volumetric measures from 207 brain regions were generated by BioClinica using their proprietary imaging pipeline. Over 85% of these patients had mild cognitive impairment (MCI), and approximately 50% were Aβ positive based PET visual read (mostly using Florbetaben).Signatures for detecting brain Aβ positivity were derived via several AI algorithms such as Bayesian elastic‐net, neural network, regularized random forests, and stochastic gradient boosting. These models included demographics and clinical features, and the added value of ApoE and MRI features were assessed. Performance accuracy was first assessed via 10‐fold cross‐validation within the training set. Signatures from the best performing algorithm were evaluated in two independent test sets: a clinical trial cohort (n=1853) and an ADNI cohort (n=1092).ResultSignatures using cognitive assessments and demographics achieved 62.2% accuracy for detecting brain Aβ positivity when evaluated via cross‐validation, which improved to 75.2% when adding ApoE, and to 77.9% when including MRI.When tested in two independent cohorts, signatures with cognitive assessments and demographics achieved accuracy of 64.5% and 65.8% respectively, which improved to 71.9% and 74.3% when adding ApoE, to 76.7% and 77.5% when including MRI, and to 83.6% and 84.8% when considering 2/3 of the test‐sets that were predicted with high‐confidence (i.e., subjects predicted with > 70% probability as brain Aβ positive or negative).ConclusionThese results demonstrate the potential of non‐invasive AI tools based on cognitive assessments, ApoE and MRI for detecting brain Aβ positivity in clinical trials and patient care. Results reported here may be refined further using impending additional data prior to final presentation.
Relationship between clinician rated amyloid status and traditional AD biomarkers in cognitively healthy older adults
Authors: Green Zachary D. , Kueck Paul J. , John Casey S. , Vidoni Eric D , Burns Jeffrey M. , Morris Jill K. 
Published: December 2022

AbstractBackgroundAccumulating evidence suggests that Alzheimer’s Disease (AD) plasma biomarkers aid in screening for at‐risk individuals, tracking disease progression, and monitoring response to interventions. Plasma amyloid‐β (Aβ) and phosphorylated tau (pTau) have shown promise in predicting cerebral deposition of Aβ, while neurofilament light chain (NfL) serves as a more global marker of neurodegeneration. However, blood collection protocols often differ, and it is important to confirm the relationship between blood biomarker values and established neuroimaging markers for AD neuropathology.MethodHere, we examined which blood biomarkers could predict clinician rating of cerebral amyloid status. We leveraged available clinical, cognitive, and neuroimaging data for 140 cognitively healthy older adults (65+, mean 72 ± 6.4) who participated in the Alzheimer’s Prevention Program (APP) study and had blood specimens available. Participants were assessed by a trained clinician and neuropsychometric test battery to exclude the presence of MCI or dementia syndromes. Cerebral amyloid burden was measured by Florbetapir (18F) positron emission tomography and images were rated by three trained clinicians as “elevated” or “non‐elevated”. Biomarkers were measured in plasma collected in acid citrate dextrose (ACD) tubes using a Quanterix Simoa® HD‐X platform, and included NfL, Aβ42, Aβ40, and p‐tau181.ResultPlasma Aβ42/40 ratio was significantly lower in the “elevated” group than in the “non‐elevated” group (p < 0.001), while NfL (p =0.008) and p‐tau 181 (p = 0.001) were both significantly higher. Aβ42/40 ratio was able to discriminate the rating groups in a ROC analysis with an AUC of 0.835, significantly outperforming p‐tau 181 (AUC = 0.640) and NfL (AUC = 0.572).ConclusionDespite collecting samples with ACD rather than the traditional EDTA as an anti‐coagulant, expected group differences were observed. Our results suggest that Aβ42/40 ratio is useful in discriminating clinician‐rated elevated cerebral amyloid status, which has important implications regarding disclosure of blood biomarker results from different collection protocols in the context of AD risk.
Increased Bridging Characteristics in Social Networks are Associated with Increasing Amygdala Volume and Grey Matter Density
Authors: Manchella Mohit K. , Logan Paige E. , Perry Brea L , Peng Siyun , Risacher Shannon L. , Saykin Andrew J. , Apostolova Liana G. 
Published: December 2022

AbstractBackgroundSocial connectedness has been linked to decreased rates of cognitive decline particularly among older adults (Fratiglioni et al., 2004). Several studies have demonstrated that access to an expansive network of diverse, and loosely connected individuals (i.e., social bridging) plays a particularly unique role in conferring resilience against cognitive decline (Perry et al., 2021). We explored the association of social bridging with cortical atrophy measured by gray matter density (GMD) in cognitively normal (CN), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer’s Disease (AD) participants from the Social Networks and Alzheimer’s Disease (SNAD) at the Indiana Alzheimer Disease Research Center.MethodWe analyzed baseline data of 176 SNAD participants (63 CN, 54 SCD, 47 MCI, 12 AD). Social bridging metrics were collected via in‐person interviews of egocentric social network data. MCI and AD were combined into a cognitively impaired group, resulting in 3 diagnostic groups (CN, SCD, CI). Demographic and biomarker differences across groups were analyzed using ANOVA. Pooled linear regressions were run with ROIs as the dependent variables and diagnosis, age, sex, education, and social bridging as regressors. A voxel‐wise multiple linear regression of GMD images in SPM12 yielded statistical maps across the pooled sample.ResultTable 1 shows the demographic and biomarker comparisons of all groups. The linear regression showed greater social bridging was associated with larger left and right amygdala volume (both p=0.01), and trending larger left frontal thickness (p=0.055), and left and right insula thickness (both p=0.09). Figure 1 and Figure 2 show scatterplot distribution of significant and trending brain regions versus bridging by diagnostic group with regression p‐values and lines. Statistical maps show increasing social bridging is associated with increasing GMD lateralized to the left hemisphere with a frontotemporoparietal pattern (Figure 3).ConclusionWe found that the effects of particular social enrichment on GMD, such as social bridging, are localized to regions primarily involving motivation and emotion. The left lateralization suggests this hemisphere’s propensity for protection against cognitive decline via social mechanisms. Future work should investigate potential associations between social bridging and amyloid and tau deposition.
Implications of Response Patterns in Questions of Early Life Adverse Events as a Risk Factor for Lower Cognitive Function in the Multi‐Ethnic Study of Atherosclerosis
Authors: Culkin Margaret C. , Hughes Tim M. , Peavey Jeremy J. , Molina‐Henry Doris P. , Seeman Teresa E. , Merkin Sharon S. , Hayden Kathleen M. 
Published: December 2022

AbstractBackgroundEarly‐life disadvantage may increase the risk for later cognitive decline. Recently, other aspects of early‐life adversity (ELA) have received attention but their associations with cognitive decline in later life has not been widely studied. Due to the sensitivity of such questions and the potential for systematic bias, we examined (1) predictors of response patterns to ELA questions, and (2) among those who completed ELA questions, we examined whether responses were associated with cognitive decline in the Multi‐Ethnic Study of Atherosclerosis (MESA).MethodELA was self‐reported via a 7‐item telephone assessment of socioemotional and physical threat or deprivation at MESA annual follow‐up call in 2019. Descriptive statistics were grouped by completion status: not completed, partially completed, and fully completed. Continuous variables were compared across groups with t‐tests; categorical variables were compared with chi‐square tests. Cognitive function was measured using the Cognitive Abilities Screening Instrument (CASI) at MESA Exams 5 (2010‐2012) and 6 (2016‐2018). Multinomial logistic regression was used to determine predictors of completion group membership. Cognitive decline from Exam 5 to 6 by completion group was assessed using multivariable linear regression.ResultOf the 3,990 participants interviewed, the mean age was 59.2y (SD = 8.8), 55% were female, and 40% were White (n = 1,604), 13% Chinese (n = 508), 26% Black (n = 1,036), and 21% Hispanic/Latino (n = 842). The odds of partial response was higher for those born outside of the U.S. (2.17, CI 95%: 1.53‐3.09), and among participants who spoke Spanish (2.82, CI 95%: 1.74‐4.58) or Chinese (2.04, CI 95%: 1.08‐3.88) at baseline. Among participants with completed ELA (n = 3,173), one component of childhood adversity: how often was your household well‐organized/managed, was associated with better Exam 6 CASI score (β = 0.80, SE = 0.33; p = 0.015) adjusting for age, race, education, gender, language, years in the U.S., socio‐economic status (SES), and parental birthplace. There was no significant association between cognitive change from Exam 5 to Exam 6 and ELA completion.ConclusionFactors associated with acculturation including country of participant’s birth and language preference predicted completion status on questions of ELA. Future studies should be mindful of the potentially differential response patterns and the implications for interpretation when analyzing ELA data.
Inhibitory Control of Saccadic Eye Movements and Cognitive Impairment in Mild Cognitive Impairment
Authors: Opwonya Julius 
Published: December 2022

AbstractBackgroundMild cognitive impairment (MCI) may occur due to several forms of neurodegenerative diseases and non‐degenerative conditions and is associated with cognitive impairment that does not affect everyday activities. For a timely diagnosis of MCI to prevent progression to dementia, a screening tool of fast, low‐cost and easy access is needed. Recent research on eye movement hints it a potential application for the MCI screening. However, the precise extent of cognitive function decline and eye‐movement control alterations in patients with MCI is still unclear.MethodPatients with MCI (n = 79) and age‐matched cognitively healthy controls (HC) (n = 170) completed four saccadic eye‐movement paradigms: prosaccade (PS)/antisaccade (AS), Go/No‐go, and a battery of neuropsychological tests.ResultThe findings revealed significantly longer latency in patients with MCI than in HC during the PS task. Additionally, patients with MCI had a lower proportion of correct responses and a marked increase in inhibition errors for both PS/AS and Go/No‐go tasks. Furthermore, when patients with MCI made errors, they failed to self‐correct many of these inhibition errors. In addition to the increase in inhibition errors and uncorrected inhibition errors, patients with MCI demonstrated a trend toward increased correction latencies. We also showed a relationship between neuropsychological scores and correct and error saccade responses.ConclusionOur results demonstrate that, similar to patients with Alzheimer’s dementia (AD), patients with MCI generate a high proportion of erroneous saccades toward the prepotent target and fail to self‐correct many of these errors, which is consistent with an impairment of inhibitory control and error monitoring.
TRPM8 as a potential target in neurodegenerative diseases
Authors: Shikha Deep , Dalai Ritesh , Goswami Chandan 
Published: December 2022

AbstractBackgroundCholesterol is required by the neuronal cells for a normal brain functions as it affects membrane fluidity and ion channel functions by disrupting calcium homeostasis and neuronal loss1. Synthesis of cholesterol occurs in glial cells like astrocytes and get transported into neurons and intracellular organelles. Any deregulation in these transport leads to several neurodegenerative diseases2,3. TRPM8 cation channel has been found to contain conserved cholesterol binding motifs in its sequences that indicates its potential role in cholesterol mediated functions4.MethodConservation analysis of cholesterol binding motifs has been performed using CARC and CRAC sequences and docking of cholesterol with TRPM8 Cryo EM structure has been performed in Autodock. For in‐vitro studies, peripheral neurons were grown in cholesterol reduced condition. Co‐localization has been studied between TRPM8 and lipid‐raft marker by immunostaining.ResultTRPM8 has conserved cholesterol binding motifs in its structure. In‐vitro study shows that TRPM8 get localized on cholesterol enriched lipid‐raft on the plasma membrane more when cholesterol is reduced. The recruitment of TRPM8 protein also seems to increase in neuronal cell line after cholesterol reduction.ConclusionTRPM8 might have a cholesterol mediated role in neuronal cell dynamics which can be potential target for neurodegenerative diseases.
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