bluuebunny/crossref_metadata_2025_split huggingface dataset:
ILiAD trial of levetiracetam
Authors: Sen Arjune , Mary Akinola , Tai Xin You , Mura Sergio , Galloway Joanne , Hallam Angela , Frangou Eleni , Love Sharon , Chan Jane , Koychev Ivan G , Geddes John , Manohar Sanjay , Symmonds Mkael , VanDerPutt Rohan , Thompson Sian , McShane Rupert , Husain Masud ,   https://www.ndcn.ox.ac.uk/research/oxford‐epilepsy‐research‐group
Published: December 2022

AbstractBackgroundThe increasingly appreciated intersection between epilepsy and Alzheimer’s disease offers potential therapeutic opportunity. We therefore initiated a pragmatic pilot study to explore whether the anti‐seizure medication levetiracetam might offer benefit to people with Alzheimer’s disease.MethodsThe Investigation of Levetiracetam in Alzheimer’s Disease (ILiAD) trial is a randomised, double‐blind, placebo‐controlled trial. ILiAD recruits people with mild to moderate Alzheimer’s disease who have not previously had a seizure and in whom a routine electroencephalogram is normal. The primary outcome is change in a touchscreen memory task. Secondary outcomes include effect on mood, alterations in quality of life and carer‐reported outcomes.ResultsILiAD plans to recruit 30 participants. To date, eight people have completed both arms of the study with no withdrawals from those enrolled. The COVID‐19 pandemic has had multiple severe impacts on both study recruitment and assessments. The primary outcome measure, in particular, has proved difficult to evaluate during the pandemic owing to many assessments being done remotely.ConclusionILiAD is a pilot study that is part of the vanguard of trials exploring the potential role of anti‐seizure medications, particularly levetiracetam, in people with Alzheimer’s disease. Further work seems important to better understand whether drugs specifically designed to modulate cortical excitability may offer improvement in cognition for those with neurodegenerative disorders.
Mediterranean diet and structural neuroimaging biomarkers of Alzheimer’s and cerebrovascular disease: a systematic review
Authors: Gregory Sarah , Ritchie Craig W. , Pullen Hannah , Shannon Oliver , Stevenson Emma , Muniz‐Terrera Graciela 
Published: December 2022

AbstractBackgroundAdherence to the Mediterranean diet (MedDiet) has been associated with better cognitive performance, lower incidence of dementia, stroke and lower Alzheimer’s disease (AD) biomarker burden (Scarmeas et al, 2018). Improving dietary patterns in at‐risk populations may improve brain health, reducing incidence of dementia and stroke (Lewis et al, 2014; Feigin et al, 2019). The aim of this systematic review was to evaluate the evidence base for the MedDiet in relation to hippocampal volume and white matter hyperintensity volume (WMHV) (PROSPERO Registration: CRD42021269620).MethodWe systematically searched for studies on MedDiet and hippocampal volume or WMHV in MedLine, EMBASE, CINAHL and PsycInfo. The review was carried out in line with PRISMA methodology. We included studies with adult participants in any setting, time or language. Searches were initially carried out between 21st July 2021 and 19th August 2021. Papers were screened independently by two authors against eligibility criteria. Data on participant demographics, MedDiet calculation and adherence, hippocampal volume and/or WMHV was extracted and narratively synthesised.ResultOf an initial 112 papers identified, six papers, enrolling 21,750 participants, were eligible for inclusion in the review. The mean age of participants in studies ranged from 53.8 years to 80.3 years and participants were healthy volunteers, had subjective cognitive decline, or dementia. All studies included in the review were cross‐sectional or cohort studies. Four studies reported on hippocampal volume, with inconclusive or no associations seen with MedDiet adherence. One study found a significant association between higher MedDiet adherence and lower WMHV, while two other studies found no significant associations.ConclusionOverall, these results highlight a gap in our knowledge about the associations between MedDiet and AD and cerebrovascular related structural neuroimaging findings. Future research is needed including increased frequency of dietary assessments, more sensitive and specific imaging outcomes and the inclusion of data from low‐ and middle‐income countries.
The EuroLaD‐EEG consortium: towards a global EEG platform for dementia, for seeking to reduce the regional impact of dementia
Authors: Parra‐Rodriguez Mario A , Prado Pavel , Moguilner Sebastian , Herzog Ruben A , Birba Agustina , Santamaría‐García Hernando A , Tagliazucchi Enzo , Reyes Pablo A , Cruzat Josefina A , García Adolfo M. , Whelan Robert , Lopera Francisco , Ochoa John F , Anghinah Renato , Ibáñez Agustin 
Published: December 2022

AbstractBackgroundThe value of Electroencephalography (EEG) to unveil pathophysiological signatures in neurodegenerative diseases that cause dementia has been recently highlighted. To grant EEG tools the necessary validity, reliability, and scalability to support the diagnosis of dementia globally, efforts will need to integrate knowledge developed by EEG labs across diverse countries and develop protocols that can be swiftly implemented by such labs to harmonize research and clinical practices. These are the aims of EuroLaD‐EEG, a consortium that brings together five Latin American (LAC) and five European countries to develop a harmonised EEG database (Aim 1) that can help improve dementia phenotyping and diagnosis (Aim 2).MethodsEuroLaD‐EEG has developed a global EEG database that comprises 1234 EEG recordings from groups of healthy adults (n=1223), patients with mild cognitive impairment (n=199), and with familial and sporadic variants of neurodegenerative diseases (e.g., AD and FTD) (n=501). We have recently published the harmonization pipeline that will allow EuroLaD‐EEG meet its Aim 1 (Prado et al., 2022, Int J Psychophysiol, 172, 24–38). We have now developed a multi‐feature multimodal approach that combines demographic, neuropsychological, fMRI and EEG data as inputs for a gradient boosting machine‐learning classifier. Multicentric data including those from underrepresented samples will enter such a classification algorithm towards our Aim 2.ResultsPreliminary results with a subsample from LAC (n=282) revealed high classification (AUC > 0.90 for all the classes) and robustness towards heterogeneity, sociodemographic variability, and missing data. We are now planning to combine data from European and LAC to explore sources of phenotypic variability linked to socio‐demographic and cultural factors.ConclusionBy broadening our understanding of dementia phenotypes, risk factors, and affordable diagnostic approaches, and adding new evidence on variability across developed and developing countries, the EEG will contribute unique evidence that will help enhance both dementia phenotyping and diagnostic strategies.
EEG in the Global Brain Consortium, aiming to strengthen linkages between neuroscientists across borders and disciplines to advance equitable solutions to priority health challenges worldwide
Authors: Valdes‐Sosa Pedro Antonio , Leon Maria Antonieta Bobes , Lopera Francisco , Li Min , Bosch‐Bayard Jorge , Bringas Maria Louisa , Valdes Mitchell 
Published: December 2022

AbstractBackgroundThe Global Brain Consortium https://globalbrainconsortium.org/ promotes the goals of open science and serves as a clearinghouse to interface synergistically with other initiatives.MethodTwo interacting projects are of interest here: 1) The Harmonized Multinational quantitative EEG norms (HarMNqEEG) project provides open data and software (www.biorxiv.org/content/10.1101/2022.01.12.476128v1) for the first batch‐free Developmental Equations obtained from 1564 EEG cross‐spectral from 9 countries, 12 devices, 14 studies. 2) The Biomarkers of Dementia for Global Health supports Electrophysiology PIA efforts.ResultAs a result of the two projects, we evaluated qEEG discrimination on samples from the Medellin Study. The groups to be distinguished were those without the Preseninin‐1 mutation sample, asymptomatic carriers, and symptomatic carriers. We show that Hermitian Riemannian qEEG descriptive parameters and the HarMNqEEG norms allow the elastic‐net robust classifier to accurate classification (Figure 1) with total AUC in the range of .91‐,93, and acceptable accuracies between groups (Figure 2).ConclusionTo our knowledge, this is the first report on the use of harmonized Riemannaian norms in the age‐adjusted classification of EEGs from this condition.
Lipidomic analysis of isogenic ApoE‐variant iPSC‐derived glia uncovers coupling between inflammatory signaling and lipid metabolism.
Authors: van der Kant Rik 
Published: December 2022

AbstractBackgroundApoE is the major genetic risk factor for Alzheimer’s disease and the major regulator of brain lipid metabolism. In the brain ApoE is primarily expressed in glia. How different damaging or protective ApoE variants exactly affects glial lipid metabolism, and/or how this correlates with inflammatory signaling is not known.MethodWe generated iPSC‐derived astrocytes and microglia from isogenic induced pluripotent stem cells (iPSC) with ApoE3/3 (reference), ApoE4/4 (increased risk), ApoE2/2 (decreased risk) and ApoEnull/null (control) genotypes. On these cells we performed unbiased lipidomics and transcriptional profiling to measure inflammatory pathways.ResultWe observed strong accumulation of stored lipids in human ApoE4/4, E2/2 and ApoEnull/null glia compared to ApoE3/3 glia. The composition of the exact species of accumulating lipids differed between ApoE4/4, E2/2 and Enull/null glia, and between astrocytes and microglia. At the transcriptional level, lipid accumulation in some genotypes was associated with increased proinflammatory signaling in astrocytes and microglia.ConclusionsApoE genotypes has a major effect on glial lipid metabolism and specific changes in lipid metabolism associate with inflammatory signaling pathways. Using lipid‐targeting interventions we are currently probing a causal relationship between altered lipid metabolism and downstream increases inflammatory signaling
Suppression of epileptiform activity by treatment with antiepileptic drugs or by genetic ablation of tau in aged human amyloid precursor protein transgenic mice
Authors: Das Melanie ,   Gladstone Institute of Neurological Disease
Published: December 2022

AbstractBackgroundNeural network dysfunction, including subclinical epileptiform activity, occurs in a substantial proportion of Alzheimer’s disease (AD) patients and related mouse models. Treatment with the anti‐epileptic drug levetiracetam (LEV) or genetically ablating the protein tau effectively reduces epileptiform activity and behavioral abnormalities in human amyloid precursor protein (hAPP) transgenic mice. These findings support the hypothesis that network dysfunction may promote cognitive deficits in AD. While LEV treatment and tau reduction have beneficial effects in young adult hAPP mice, it is not known whether there are similarly beneficial effects in aged mice, whose pathological condition may be more similar to that of AD. To address this gap, we tested the efficacy of LEV treatment and tau reduction in preventing or reversing network, immune and cognitive dysfunctions in aged hAPP mice.MethodWe treated 22–26‐month‐old, male hAPP mice and age‐ and sex‐matched wildtype (WT) controls with placebo or LEV for four months using chow formulations. To genetically ablate tau, we generated a cohort of male and female Mapt
+/+ and Mapt
–/– mice that did or did not express hAPP. Mice were assessed by electroencephalography (EEG) and behavior. Brain tissues were subjected to transcriptome analysis and immunohistochemistry.ResultsIntracranial EEG recordings revealed that placebo‐treated hAPP mice had aberrantly increased epileptiform activity as compared with placebo‐treated WT controls and that this neural network dysfunction was effectively suppressed by chronic LEV treatment or by tau ablation. Both manipulations reduced behavioral deficits detected in aged hAPP mice. Hippocampal levels of inflammation‐related transcripts were analyzed using a NanoString Neuroinflammation panel. Compared to WT mice, more inflammation‐related transcripts were increased than decreased in hAPP mice. LEV treatment reversed and tau ablation prevented the altered expression of many inflammation‐related genes in the hippocampus of hAPP mice. Immunolabeling tissues with an antibody against human Aβ revealed extensive amyloid deposition in aged hAPP mice but LEV treatment nor tau ablation changed the number or size of amyloid plaques.ConclusionLEV treatment and tau ablation reduce network, immune and cognitive dysfunctions, but not amyloid load, in aged hAPP mice. These findings demonstrate that LEV treatment and tau reduction counteract AD‐related pathophysiological abnormalities independent of age.
Mapping individualised patterns of atrophy in Alzheimer’s disease using neuroanatomical normative models
Authors: Verdi Serena , Kia Seyed Mostafa , Schott Jonathan M , Marquand Andre F , Cole James H ,   for The Alzhemer's Disease Neuroimaging Initiative
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) is highly heterogeneous, with marked individual differences in clinical presentation and aspects of its neurobiology. Neuroanatomical normative modelling is an emerging technique that reveals individual patterns of neuroanatomy by quantifying deviations from normative ranges (Verdi et al., 2021). Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied a hierarchical Bayesian regression (HBR) normative model to account for site effects (Kia et al., 2021). We assessed individual patterns of cortical thickness (CT) heterogeneity in AD patients, people with mild cognitive impairment (MCI), and healthy controls.MethodCT across 148 regions of interest (ROIs) was generated using FreeSurfer from 1492 T1‐weighted MRI scans across 63 sites. A reference HBR normative model was trained on a separate healthy dataset of 34,490 to index population variability, predicting CT at each ROI using age and sex. This generated CT z‐scores for each ROI, per participant. Here z‐scores < ‐1.96 were defined as outliers. Outliers were also summed across 148 ROIs to give a total outlier score per participant. The influence of the total outlier score on converting from MCI to AD within 3 years was tested using Cox proportional hazards regression.ResultAD subjects had higher total outlier scores than MCI and control participants (β=10.99,95%CI=[5.55,16.42], p<0.001), with marked differences in temporal regions. Total outlier score predicted memory performance (R2=0.39,p<0.001) and executive function (R2=0.35,p<0.001). Total outlier score was predicted by amyloid‐beta (R2=0.06,p<0.001) and phospho‐tau (R2=0.16,p<0.001). The patterns of neuroanatomical outliers varied markedly between AD patients (Fig.1); the parahippocampal gyrus had the highest rate of AD patients with outliers (47%). Outlier maps of AD patients matched age, sex, cognition and APOE4 genotype, illustrate spatially heterogeneous patterns of outliers (Fig.2). Greater within‐group dissimilarity was seen in AD patients, relative to MCI or control participants (Fig.3). Every 10 points of total outlier score contributed to an 31.4% risk of converting from MCI to AD within 3years (HR=1.028,95%CI=[1.016,1.039],p<0.001) (Fig.4).
ConclusionOur novel quantitative estimate of the neuroanatomical heterogeneity of CT suggests the impact of AD on the brain is not consistent between patients. Furthermore, quantify outliers in CT may help predict individuals with MCI at risk of converting to AD.
Exploration of the gut‐brain axis through metabolomics identifies serum propionic acid associated with higher cognitive decline in older persons
Authors: Neuffer Jeanne , González‐Domínguez Raúl , Lefèvre‐Arbogast Sophie , Low Dorrain Yanwen , Driollet Bénédicte , Helmer Catherine , Preez Andrea Du , de Lucia Chiara , Ruigrok Silvie R , Altendorfer Barbara , Aigner Ludwig , Lucassen Paul J. , Korosi Aniko , Thuret Sandrine , Manach Claudine , Pallàs Mercè , Urpi‐Sarda Mireia , Sánchez‐Pla Alex , Andres‐Lacueva Cristina , Samieri Cécilia 
Published: December 2022

AbstractBackgroundThe microbiome is involved in nutrient metabolism and releases metabolites that can influence cognitive aging, likely through the gut‐brain axis. Human studies, generally limited in number of metabolites and follow‐up, have been inadequate to identify early metabolic alterations leading to cognitive aging. The aim of this study was to investigate the association between circulating levels of a large number of microbial metabolites in plasma and cognitive decline.MethodsWe studied participants from the Three‐City study, a cohort study conducted in 3 French cities (Bordeaux, Dijon ad Montpellier). The subjects were free of dementia at the time of blood sampling and provided repeated measures of cognition over 12 subsequent years. We used a targeted metabolomic approach, combining ultra‐high performance liquid chromatography coupled to tandem mass spectrometry. We measured 77 circulating gut‐derived metabolites in a case‐control sample matched for age, sex and educational level, nested within the cohort. Associations of these metabolites to cognitive decline were investigated in the Bordeaux center (discovery sample, n = 418) using logistic regressions conditioned on matching variables. Associations with a P‐value corrected for multiple testing (False Discovery Rate [FDR]) ≤0.15 were tested for validation in the Dijon center (validation sample, n = 424). Models were subsequently adjusted for smoking, alcohol consumption and cardiometabolic health (body mass index, hypertension, hypercholesterolemia and diabetes).ResultsHigher serum levels of propionic acid, a short‐chain fatty acid, were associated with increased odds of cognitive decline (OR for 1 SD = 1.40 [95% CI 1.11, 1.75] in discovery, and = 1.26 [1.02, 1.55] in the validation stage). Associations were attenuated in the validation sample after multivariable adjustment, and additional analyses suggested mediation by hypercholesterolemia and diabetes. Moreover, propionic acid strongly correlated with blood glucose (r = 0.80) and with meat and cheese intakes (r>0.15) but not with fiber intake (r = 0.04).ConclusionThis exploratory study of the gut‐brain axis suggests a deleterious relationship between circulating propionic acid and cognitive decline. Our results suggest a very weak relation to pre‐biotic foods, but a possible link with processed foods, where propionic acid is often used as a preservative. Thus, the adverse impact of propionic acid on metabolism and cognition deserves further investigation.
Potential Reversal of Alzheimer’s Disease pathology by Antibody TB006 Targeting Galectin‐3, the Root Cause of Oligomerization of Amyloid Proteins
Authors: Rasool Suhail , Patel Pooja , Johansson Jenny , Voloboueva Ludmila , Lee Sangmi , Sun Jessica , Lan Xi , Ahmed Taufeeq , Sun Dongxu 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) is a chronic progressive neurodegenerative disorder caused by multiple pathogenic factors including Amyloid‐β (Aβ), phospho‐Tau (pTau), alpha‐synuclein, and ApoE4, etc. It is widely accepted that intermediate oligomeric forms, rather than monomers or mature fibrils, are more neurotoxic. Galectin‐3 (Gal‐3) was reported to be involved in Aβ oligomerization. Here, we show that Gal‐3 promotes oligomerization of Aβ and other pathogenic factors, and TB006, a monoclonal antibody targeting Gal‐3, acts as a possible treatment for AD by degrading neurotoxic oligomers.MethodWe used two anti‐Gal‐3 antibodies, our clinical lead TB006 and a mouse cross‐reactive surrogate, mTB001, to establish the benefits of Gal‐3 neutralization in AD in vitro and in vivo. The effects of mTB001 were tested in three AD mouse models (two transgenic mouse models (APPSwe, 5xFAD) and an Aβ42‐injected mouse model). After two‐week treatment, a spatial memory function test was conducted, followed by biochemical and immunohistochemical characterizations.ResultAmyloid aggregation is a hallmark of several neurodegenerative diseases (AD, PD and ALS) affecting the brain or peripheral tissues, whose intermediates (oligomers, protofibrils) and final mature fibrils display different toxicity. In vitro, Gal‐3 intrinsically and selectively promotes, while mTB001 and TB006 degrade, oligomerization of only pathogenic proteins like Aβ42/40, α‐synuclein, pTau and ApoE4, but not of normal proteins like normal Tau and ApoE2/3. Gal‐3 enhanced, while mTB001 blocked, Aβ42‐induced microglia activation. Additionally, Aβ42 and Gal‐3 synergistically induced, while mTB001 reversed, neuronal death. In vivo, in three mouse models of AD, cognitive deficits were strongly attenuated after just two weeks of mTB001 treatment. Mechanistically, Gal‐3 antibody blocked the initiating events in AD (Aβ aggregates), reduced inflammation and rescued neuronal damage. Furthermore, microhemorrhages, a potential safety liability seen in clinical stage drugs, were reduced.ConclusionPre‐clinical studies show that TB006 is an efficacious therapeutic entity through degradation of toxic oligomers and blocking or even reversing AD progression. Clinically, TB006 has shown a superior safety profile without any drug‐related adverse events in a nearly finished healthy volunteer trial. Promising efficacious data are expected in Q2/2022 from the ongoing phase I/II AD trial.
The Fractal Geometry of Alzheimer’s disease
Authors: Azizi Tahmineh 
Published: December 2022

AbstractBackgroundHuman brain is the most dynamic and varied system of the body. The brain is composed of neuron and glia. But how do they interact to generate emergent properties like memory, learning, emotion and sleep is little understood. Many such complex systems that exist in non‐linear dynamics are characterized by the fractal nature. The fractal dimension (FD) is a quantitative parameter that has been extensively used to analyze the complexity of structural and functional patterns of the human brain. The fractal dimension (FD) of the human brain quantifies the inherent complexity.MethodA non‐linear analysis called the Fractal Dimension (FD) has been performed to quantify the fractal complexity of AD. Our primary goal is to investigate FD to assess whether it can discriminate between different states of AD. We perform multi‐fractal analysis to discover whether AD and its states belong to class of multi‐fractal object for which a large number of scaling exponents are required to characterize their scaling structures. We plot the multi‐fractal spectra of the fMRI images to compare the width of the scaling exponent for each spectrum.ResultFrom FD analysis, we noticed that the fractal dimension increases with aging the AD, i.e. the complexity and self similarity of brain structure increases. According to our analysis, we have a wide range of exponents for AD fMRI images, which indicates different states of Alzheimer’s disease have multi‐fractal structure.ConclusionAs a result, fractal geometry can be considered as a computational framework to characterize different stages of AD and with further analysis, it can be used as a diagnostic tool to fight against Alzheimer’s disease.