bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi‐modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain
Authors: Bueichekú Elisenda , Diez Ibai Palacio , Gagliardi Geoffroy Pierre , Kim Chan‐Mi , Mimmack Kayden J. , Sepulcre Jorge , Vannini Patrizia 
Published: December 2023

AbstractBackgroundMnemonic anosognosia (i.e., unawareness) is a behavioral condition characterized by a lack of self‐awareness of objective memory decline. In the context of Alzheimer’s Disease (AD), unawareness may be a sign of predementia stages. It contributes to disease severity, symptomatology worsening, and caregiver burden and is a good predictor of clinical progression. Here, we use in‐vivo multi‐modal neuroimaging to profile the brain phenotype of individuals presenting altered self‐awareness of memory during aging.MethodsWe used amyloid‐ and tau‐PET (N = 335) and resting‐state fMRI (N = 713) data of individuals from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4)/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies (Table1A). The neurocognitive profile of unawareness was characterized using between‐groups comparisons (omnibus and post‐hoc analyses) of the objective (LM delayed memory, and FCSRT free and cued scores) and subjective (MACQ) memory measurements of individuals classified as unaware of their memory impairment, compared to aware, subjective‐complainers and control individuals. To characterize the cortical burden of amyloid and tau and their modulatory effect on functional connectivity networks, we applied whole‐brain voxel‐wise GLM analyses, region‐of‐interest associations, and graph‐theory metrics (e.g., degree centrality).ResultsUnaware and aware individuals perform worse than the control group in objective memory tests, while unaware individuals differ from aware but not from controls in MACQ (Table1B). The unaware group presents elevated amyloid and tau burden in midline core regions of the default mode network (DMN) compared to aware, complainer or control individuals (p‐value<0.05) (Figure1AB). Tau spreading in controls showed significant connectivity toward DMN and lateral and medial occipito‐parietal regions (Figure1C). Unawareness is characterized by an altered network connectivity pattern modulated by tau accumulation in which hyperconnectivity is observed mainly in midline DMN and posterior occipito‐parietal regions (p‐value<0.05) (Figure2A). Degree centrality revealed the main connectivity hubs altered by tau deposits in unaware individuals (e.g., posterior regions) (Figure2B).ConclusionsMnemonic anosognosia is an early behavioral biomarker of AD pathology. Unawareness of memory decline leads to distinct brain phenotype, characterized by increased amyloid and tau burden, along with functional network connectivity disruptions, in several areas of the self‐referential brain network, including the posterior cerebral cortex of the human brain.
Plasma Alzheimer’s disease biomarkers and intraindividual cognitive variability measured by ecological momentary assessment in adults with type 1 diabetes
Authors: Fonseca Luciana Mascarenhas , Kivisäkk Pia , Hawks Zoë W , Jung Laneé , Bulger Jane , Grinspoon Elizabeth , Janess Kamille , Weinstock Ruth S , Chhatwal Jasmeer P. , Beeri Michal S , Cleveland Michael , Germine Laura Thi , Chaytor Naomi Sage 
Published: December 2023

AbstractBackgroundOlder adults with type 1 diabetes (T1D) have elevated risk of Alzheimer’s disease and related dementias (ADRD) compared to non‐diabetic controls. Because of oscillations in blood glucose, individuals with T1D are also prone to physiological and cognitive fluctuations. Intraindividual cognitive variability (IICV), or within‐person standard deviation across cognitive tests, has been proposed as an alternative marker of early dementia. The aim of this study was to characterize the relationships between ADRD plasma biomarkers and IICV in adults with T1D via ecological momentary assessment (EMA) of cognition during regular daily activities.MethodAdults with T1D (age range 19‐84 yrs, mean = 48.9) who participated in the Glycemic Variability and Fluctuations in Cognitive Status in Adults with Type 1 Diabetes (GluCog) study and had available data on plasma β‐amyloid42/40, ptau181, NfL and GFAP levels measured using Quanterix assays were included in these analyses (N = 114). Cognition was assessed three times per day for 15 days. Within‐person measures of IICV were computed for each cognitive test after accounting for practice effects using multilevel modeling: Digit Symbol Matching reaction time (DSM‐RT; processing speed), Gradual Onset Continuous Performance Test d‐prime (GradCPT; cognitive control, attention), and Multiple Object Tracking accuracy (MOT; visual working memory). Multilinear regression models estimated associations between IICV and blood biomarkers, controlling for age, sex, education, person‐level mean cognition, and glucose variability (measured via continuous glucose monitoring).ResultsPTau181 and NfL were associated with IICV‐DSM‐RT (p<0.05). GFAP and β‐amyloid42/40 were not associated with any of the measures of cognitive variability investigated.ConclusionThese findings suggest that pTau181 and NfL are associated with cognitive variability measured via EMA in an adult sample at risk for ADRD. This is the first study to (i) investigate the association between plasma biomarkers of dementia and IICV measured via EMA and (ii) report plasma biomarker results in individuals with T1D. The results encourage future studies investigating diabetes‐related factors that may contribute to increased dementia risk.
Reduction of neuropsychiatric symptoms and associated caregiver distress using a tetrahydrocannabinol and melatonin combination in dementia due to Alzheimer’s disease
Authors: Tangarife Maria Alejandra , Gutierrez Evelyn , Sanchez Laura Tatiana , Arbelaez María Juanita , Rodriguez‐Soacha Diego , Shahnawaz Saadia S , Ghazaryan Varduhi , Delgado‐Murillo Laura , Naranjo Maria Paula , Venegas Margarita , García David Silva , Pujals Karen Y , De Jesus William Julio , Grimaldi Claudia , Lanctôt Krista L. , Hong L Elliot , Mukunda Ram 
Published: December 2023

AbstractBackgroundNeuropsychiatric symptoms (NPS) are features of Alzheimer’s Disease (AD) and a main cause of institutionalization. NPS in AD include agitation, depression, anxiety, elation, apathy, disinhibition, irritability, delusions, hallucinations and aberrant motor behavior. The onset of NPS worsens functional deficits by accelerating patients' cognitive decline and in 80% of cases increases caregiver burden and distress. NPS are difficult to treat and currently used medications have black‐box warnings, and weak evidence of efficacy in dementia patients. Here, we present preliminary data for improvement in NPI scores and NPI Caregiver Distress (NPI‐D) scores using IGC‐AD1, a combination of tetrahydrocannabinol (THC) and melatonin (IGC‐AD1).MethodTwelve patients with mild (15.38%) to moderate (84.6%) AD (NIA‐criteria, 10‐active, 2‐placebo, 81.5±5.5yrs, 69.2% women) participated in a three Cohort Phase‐1, MAD, safety and tolerability trial (IND146069, NCT04749563). In Cohort‐1, IGC‐AD1 was administered QD at 1ml for 14‐days (EOT). In Cohorts‐2 and 3, one ml BID and TID were administered respectively with a minimum of 4‐days washout between Cohorts. For all three Cohorts the NPI / NPI‐D were administered at baseline and EOT of each Cohort. Daily, solicited and non‐solicited adverse events (AEs) were monitored along with vital signs. A Wilcoxon matched‐pairs signed‐rank test (R‐Studio, dplyr) was used to independently compare differences between mean NPI and NPI‐D scores at baseline and EOT.ResultIn Cohort‐1 mean NPI at baseline and EOT was 31.5 and 14.8 respectively (mean difference = ‐16.7, v = 55, p = 0.003). In Cohort‐2 mean NPI at baseline and EOT was 22.2 and 12.4 respectively (mean difference = ‐9.8, v = 48, p = 0.021). In Cohort‐3 mean NPI at baseline and EOT was 16 and 7.9 respectively (mean difference = ‐8.1, v = 35, p = 0.010). We report similar improvements in NPI‐D. (Cohort‐1: mean difference = ‐7, v = 15, p = 0.031; Cohort‐2: mean difference = ‐6.3, v = 43, p = 0.009; Cohort‐3: mean difference = ‐3.4, v = 30, p = 0.053). No changes in concomitant medication were observed. No serious AEs, no deaths, and no dropouts due to AEs were reported.ConclusionGC‐AD1 was safe and well tolerated and is potentially efficacious in reducing NPS and associated caregiver distress, clinically and statistically, in AD as measured by the NPI, warranting a larger placebo‐controlled study.
A radiomic features study in 18F‐FDG‐PET images to classify Alzheimer Disease patients using machine learning algorithms
Authors: Hernández Cruz Moisés Ebenezer , Avendaño Estrada Arturo , Rodríguez Miguel Ángel Ávila 
Published: December 2023

AbstractBackgroundRadiomic features has demonstrate their utility to obtain important information in many diseases, specifically information about tissues or their metabolism that can be related to the diagnostic of a patient. In study of the Alzheimer Disease, there are some works in the use of radiomic features measured in Positron Emission Tomography (PET) images with [18F]fluorodeoxyglucose ([18F]FDG) to train machine learning algorithms and classify patients with and within the disease.MethodA sample of 50 [18F]FDG‐PET studies of patients with neurological disease suspected was used. All PET images were normalized to a brain atlas space and then radiomic features were measured in all volumes of these atlas. Then the most important features correlated with the diagnosis of the Alzheimer Disease were found and used to train different machine learning algorithms and predict the diagnostic of patients. The shipping diagnosis was used as the target for training, and the same process using the classification of an Alzheimer Disease software tool called PMOD as the target was made.ResultSome features that shows a correlation with the shipping diagnosis of patients and with the classification of the Alzheimer software tool PMOD were found. Most of them are features measured in parietal regions, and from a radiomic features family called Grey Level Co‐ocurrence Matrix. These features are related with tissue texture. Features with the most significant correlation with their shipping diagnosis and with PMOD classification were used to train machine learning algorithms and good results were obtained for both cases, with maximum accuracies of 0.91.ConclusionThe correlation analysis helped to improve the training process, obtaining acceptable performance results in the classification of patients using their shipping diagnosis and PMOD classifications as the target. Some of these features shows a clear difference in their values between Alzheimer and control patients, perhaps a bigger sample of patients is needed to be sure of the relation between the feature and the disease. The results in this study suggest that it is possible to find radiomic features that can help us in understanding and diagnosing of Alzheimer Disease.
Leveraging doppler ultrasound imaging to measure pulse wave velocity changes in a mouse model of arterial stiffening to elucidate molecular pathways underlying cerebral damage
Authors: Baggeroer Caroline E , Pietri Peter A , Santisteban Monica M , Harrison Fiona E. , Jefferson Angela L. 
Published: December 2023

AbstractBackgroundThe highly vascularized brain is particularly vulnerable to changes in pulsatility of blood flow. With age, elastin in arteries breaks down and is replaced by collagen, making arteries less compliant and resulting in arterial stiffening. Stiffening alters pulsatility, which can be measured by pulse wave velocity (PWV), and damages small capillary beds and the neurovascular unit (NVU). The NVU is essential for proper delivery of oxygen and nutrients to the brain. Human studies have demonstrated associations between increased arterial stiffness and biomarkers of Alzheimer’s disease (AD) and neurodegeneration. We adapted a doppler ultrasound imaging method previously only used in rats to measure PWV in a mouse model of arterial stiffening to advance our understanding of the molecular underpinnings of AD and neurodegeneration.Method7‐month‐old, C57BL/6, male and female mice underwent a carotid calcification surgery, where the carotid artery was exposed to 0.3 mol/L CaCl2 (or saline as a control) for 20 minutes. PWV was measured using doppler ultrasound imaging before and after surgery. Two weeks post‐surgery, mice underwent behavioral testing, including locomotor activity, elevated zero maze, Barnes maze, and nest building. Collagen, calcium, and elastin levels in the carotid artery were determined 4 weeks post‐surgery by immunohistochemistry.ResultPreliminary results demonstrate the carotid calcification surgery successfully increased PWV in mice three weeks post‐surgery. Surgery did not inhibit behavioral task performances two weeks post‐operative. Additional data collection is underway applying this method in two transgenic AD mouse models, APP/PSEN1 and P301S, which will include behavioral testing and histological assessment of NVU components, specifically endothelial cells (CD31/PECAM), pericytes (PDGRFb), and astrocytes (GFAP) in the hippocampus.ConclusionElucidating a clear molecular link between increased arterial stiffness and cognition is essential to understanding how age‐related changes in systemic blood flow may influence AD pathology and neurodegeneration. Our preliminary results demonstrate that doppler ultrasound imaging, previously only used in rats, can be applied in mice as a reliable measurement of PWV. We will leverage this model to test the hypothesis that increased PWV is associated with worse spatial learning and memory, impaired functioning of the NVU, and increased AD pathology.
Salivary beta amyloid 1‐42 (Aβ42) for the diagnosis of Alzheimer’s disease: a systematic review and meta‐analysis
Authors: Phillips Geraint A , Butchart Joseph , Hope Suzy , Taylor Gordon , Strain William David 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) neuropathology begins many years before dementia symptoms, however validated cerebrospinal fluid and neuroimaging biomarkers are not scalable to widespread use. Higher salivary beta amyloid 1‐42 (sAβ42) is associated with AD, but its clinical utility remains insufficiently evaluated. This systematic review and meta‐analysis quantifies and evaluates the diagnostic performance of sAβ42 in Alzheimer’s disease.MethodSearches were performed in Ovid MEDLINE, Embase, CENTRAL, PubMed and Web of Science for studies published between January 1, 2000, and March 20, 2022, quantifying sAβ42 in adults with and without AD. All AD diagnoses and criteria were included. Studies without separate AD and control groups and quantitative sAβ42 measurements were excluded. Risk of bias and applicability were evaluated using the QUADAS‐2 tool. Diagnostic performance was assessed by a random‐effects meta‐analysis. Standardised mean differences in sAβ42 levels and 95% confidence intervals in AD and control groups are reported.ResultTen of 373 identified articles and 1 study from citation searching were included. Studies unable to quantify sAβ42 (3) and duplicating subject data (2) were removed, leaving 6 studies comprising 264 AD and 463 control subjects for meta‐analysis. Average sAβ42 differentiated AD from controls (pooled weighted SMD 1.83, 95% CI 0.54‐3.12, p = 0.006). However, high sAβ42 variability and substantial heterogeneity (I2 = 97%) limit the reliability of results. Mean sAβ42 levels were higher in AD versus MCI (p<0.0001) and MCI versus controls (p<0.001) but did not differentiate Parkinson’s disease from AD or controls. Age, AD severity and apolipoprotein E status did not reliably correlate with sAβ42 levels.ConclusionAlzheimer’s disease was associated with significantly higher sAβ42 concentrations compared with controls. However, the reliability and applicability of study results are significantly limited by widespread risk of bias and inherent low GRADE of evidence.
More research needed on Music programs in Nursing Homes and Senior Living Centers
Authors: Moses‐Eisenstein Michelle 
Published: December 2023

AbstractBackgroundIn the United States, most dementia care is provided in senior living centers/nursing homes. For various reasons, the response to residents’ behavioral problems is often medications which can have various side effects.MethodWe conducted a literature review in Google Scholar and Pubmed on music programs in nursing homes and senior living centers in order to explore the utility of non‐pharmacological programs.ResultSeveral studies indicate that non‐pharmacological interventions such as music programs improve patient behaviors and can lead to a decrease in negative behaviors like agitation. One study found that individualized music programs are associated with reductions in behavioral and psychological symptoms of dementia and medication use. In another study of 4107 residents, Music and Memory program researchers found decreases in medication use and better behaviors. Music also improves memory in Alzheimer’s patients. Group music therapy can reduce depression among patients with dementia. A review of 25 Randomized Controlled Trials or Clinical Controlled Trials found most studies supported the argument that music programs improve mood, quality of life, and neuromotor performances. In particular, music can be customized to better suit the needs of the individual, as studies have shown the importance of selecting music connected to one’s social and national identity. Music programs in groups are also a great opportunity to facilitate social interaction.ConclusionThe literature supports the need for the arts for seniors however there is a need for larger, more systematic data. Further, there appears to be a research gap on how the lack of funding and reimbursement for music in nursing homes impacts access. For example, do residents have the same access depending on their location (e.g. urban/rural), primary language(s), and/or number of Medicaid beds? Do artists have the training on how to respond if residents become agitated or confused? People with dementia and their caregivers could benefit greatly from more equity in arts access as well as training for artists who want to better support seniors.
Improving gene expression prediction models through the use of meta‐analysis summary statistics
Authors: Mews Makaela , Naj Adam C. , Below Jennifer E. , Bush William S. 
Published: December 2023

AbstractBackgroundBy focusing on a gene‐level rather than a single‐variant basis, transcriptome‐wide association studies (TWAS) assess the role of genetically regulated gene expression in disease risk and improve statistical power by reducing the multiple testing burden by over a 100‐fold. A key limitation of current TWAS approaches is the requirement for dense individual‐level datasets with both genotypes and gene expression measures to produce effective expression prediction models. We sought to improve the statistical power of AD TWAS by leveraging easily accessible summary statistics taken from large‐scale expression quantitative trait loci (eQTL) meta‐analyses.MethodWe used eQTLGen Whole Blood cis‐eQTL data (N = 31,684) as our source of meta‐analysis summary statistics. To perform gene‐based elastic‐net regressions using the summary statistics, we used the lassosum R package (Mak et al. 2017) with 1000 Genomes data as a genomic reference and GTEx v8 genotype, normalized Whole Blood gene expression and covariate data (N = 670) as a testing panel for model validation and dynamic selection of the optimal mixing/penalty parameters. The SNP‐weights generated by our models were subsequently applied to AD meta‐analysis summary statistics from Kunkle et al. 2019 (AD Cases = 21,982; Controls = 44,944) and Bellenguez et al. 2022 (AD/ ‘proxy’ AD Cases = 111,326; Controls = 677,663) via S‐PrediXcan to assess whether predicted gene expression is associated with AD risk.ResultWe found on average a 3.3% (SD: 0.05%) significant improvement in the predictive performance for 93.3% of genes models (N = 2,787) when using the same SNPs as the PredictDB model. Using models with the restricted SNP set, we identified four genome‐wide significant gene expression models (CTDNEP, p = 3.2e‐9; STK4, p = 1.6e‐13; RPS14, p = 8.8e‐38; POLR1H, p = 5.6e‐45) using Kunkle et al. 2019 summary statistics relative to only one using the PredictDB model (FBXO46, p = 6.6e‐15). When applying the Bellenguez et al. 2022 summary statistics, which contains a broader AD phenotype thru the inclusion of ‘proxy’ cases, we identified 12 genome‐wide significant gene expression models (Range: CHRNA2, p = 2.6e‐8; SLC24A4, p = 4.5e‐16) associated with AD.ConclusionOur findings show AD association studies based on TWAS approaches may be improved by meta‐analysis reference panels.
A CLU/APOJ GWAS AD risk variant suppresses the astrocytic response to plaques and reduces axonal and neuritic damage in 5xFAD mice
Authors: Milinkeviciute Giedre , Tran Katelynn , Da Cunha Celia , Mendoza‐Arvilla Adrian , Garcia‐Agudo Laura Fernandez , Neumann Jonathan , Walker Amber , Kawauchi Shimako , Tenner Andrea J , LaFerla Frank , MacGregor Grant R , Green Kim N 
Published: December 2023

AbstractBackgroundGenome‐Wide Association Studies (GWAS) implicate clusterin (CLU, also known as apolipoprotein J) as a risk factor for late‐onset Alzheimer’s disease (LOAD), with elevated expression of CLU being associated with increased risk of LOAD. The region surrounding the SNP risk allele rs2279590 is poorly conserved within the mouse genome. Consequently, to model the effect of the rs2279590 risk allele on development of AD‐related pathology in mice we developed mice with a partially humanized allele of Clu.MethodCRISPR was used to substitute a 2kb region of human CLU (intron 7 to exon 9) containing the enhancer region and the rs2279590 SNP variant for the orthologous region of Clu within the C57BL/6J mouse genome. Clu‐rs2279590_h2kb mice were crossed with 5xFAD mice and aged to 4 and 12. Coronal brain sections were immunolabeled to visualize dense‐core plaques (ThioS), microglia (IBA1), astrocytes (S100β and GFAP), axonal (NfL) and neuritic (LAMP1) damage, confocal images of subiculum and cortical regions were taken and analyzed using Imaris software. In addition, brain Aβ and plasma NfL levels were quantified using meso scale discovery technology.Result5xFAD;Clu‐rs2279590_h2kb showed significantly reduced microglial density compared to 5xFAD mice in both brain areas at 4 months. By 12 months of age, microglial density was comparable between genotypes in cortex while in subiculum, elevated IBA1 cell density was observed in 5xFAD;Clu‐rs2279590_h2kb mice. Clu‐rs2279590_h2kb variant in 5xFAD background increased the density of S100β astrocytes in subiculum at 4 months and decreased the total S100β volume at 12 months. Reduced GFAP (reactive astrocytes) levels were found in cortex but not subiculum at 12 months. Despite comparable plaque load and insoluble Aβ42 levels, neuritic and axonal damage was decreased in the brain of 5xFAD;Clu‐rs2279590_h2kb compared to 5xFAD mice at 12 months. Plasma NfL was also significantly decreased.ConclusionDespite the minimal impact on Aβ plaque deposition, humanization of 2kb of Clu allele and introduction of rs2279590 risk SNP suppresses astrocytic response to plaques and is protective against axonal and neuritic damage which is mirrored by the reduced levels of plasma NfL.