bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a fast and versatile method for genome‐wide association studies of longitudinal data
Authors: Kleineidam Luca , Andrade Victor , Wagner Michael , Lambert Jean‐Charles , Ruiz Agustín , Ramirez Alfredo 
Published: December 2020

AbstractBackgroundApolipoprotein E ε4 shows a strong effect on the risk for developing Alzheimer’s disease (AD) but does not modulate the speed of cognitive decline after dementia onset. Accordingly, the influence of other genetic determinants might also change during the disease course of AD. To identify those determinants, methods are needed allowing for genome‐wide analysis of genetic effects using longitudinal data. Since the disease progression of AD, measured e.g as cognitive decline, may show a non‐linear trajectory over time, we developed a fast and flexible method for conducting genome‐wide association studies (GWAS).MethodWe extended the previously developed generalized least square approximation of linear mixed models (Rönnegard et al., 2016) to account for potential non‐linear trajectories. As GWAS studies usually combine results from different cohorts, this approach was combined with a partial derivative‐based meta‐analysis (Roshchupkin et al., 2016) that yields identical statistical power as pooled analysis but without the need of sharing individual participant data. To ensure suitability of our method, we conducted a Monte Carlo Simulation study generating data on 8000 participants with a non‐linear decline over 6 years of follow‐up and a 70% drop‐out rate. In each condition of the simulation study, we varied the number of cohorts providing the final sample size (1/5/40 studies), the minor allele frequency (MAF; 0.33/0.03) and the effect size of the genetic predictors on the longitudinal data. Thousand replications per condition were generated. Performance was compared to standard methods (i.e., full linear mixed models and invers‐variance‐weighted meta‐analysis).ResultCompared to a standard linear mixed model, our method was able to reduce, from several seconds to milliseconds, the computation time needed to calculate the association of one genetic variant with the longitudinal change. Our method producing unbiased effect estimates across all conditions. In case of less frequent variants (MAF = 0.03) and 40 studies, the standard invers‐variant weighted meta‐analysis showed higher type‐I‐error, but lower statistical power compared to the partial derivative‐based approach implemented in our method.ConclusionWe developed a fast and versatile method for longitudinal GWAS that maximizes power to detect genetic determinants of a wide range of different phenotypes in research on neurodegenerative diseases.
Clinical implications of white matter hyperintensities in patients with Alzheimer’s disease
Authors: Yang Hyun‐ju , Park Joon Hyuk 
Published: December 2020

AbstractBackgroundWhite matter hyperintensities (WMHs) are commonly found on the fluid‐attenuated inversion recovery (FLAIR) or T2‐weighted magnetic resonance imaging (MRI) in elderly people. Most recent studies have shown that increased volume of WMHs has been linked to both late life depression and functional impairment such as impaired mobility, gait and motor disturbance, and poor balance in elderly. In this analysis, we examined the relationship among depressive symptoms, physical disability, quality of life and WMH severity in Alzheimer`s disease (AD).MethodThe volume of WMHs were quantified using Lesion Segmentation Toolbox (LST). After then, the volume of WMHs were adjusted by the estimated intracranial volume, and we used a logarithmic transformation to produce normally distributed data. Because WMH distribution concerns three areas (juxtaventricular, periventricular, deep area), regression analyses were also used to identify the relationship between each WMH area and clinical symptoms in AD. All subjects underwent standardized clinical interviews and neurological and physical examinations to assess their cognitive (CERAD‐K), physical function (muscle mass index, grip strength, gait speed and timed up and go test), depressive symptoms (sGDS‐15) and quality of life (SF‐36).ResultIn 112 AD, the mean age was 80.5±7.1. WMH volume was associated with s‐GDS‐K score (P=0.005). After adjusting for sGDS‐K, MMSE‐KC‐Z score and Charlson Comorbidity Index, the degree of WMH volume were significantly associated with the muscle mass index (p=0.003), gait speed (p <0.001), and Korea frail index (p =0.016). Furthermore, social function (p=0.029), physical functioning (p<0.001), bodily pain (p=0.007), role physical (0.010), mental component score (0.028) and physical component score (p=0.001) were associated with the degree of WMHs.ConclusionGiven the greater volume of WMH among AD, and considering that loss of the personal and social life of older people, these results might be relevant to the main functional problems related to aging in AD.
Cognitive evolution of patients with mild Alzheimer’s disease can be predicted by circulatory microRNA expression profile
Authors: Dakterzada Faride , Piñol Gerard , Carnes Anna , Targa Adriano , Moncusi Anna , Benitez Ivan David , Huerto Raquel , Barbe Ferran 
Published: December 2020

AbstractBackgroundTo evaluate whether the expression profile of plasma microRNAs is able to predict the cognitive evolution of patients with early‐phase Alzheimer’s disease (AD).MethodThrough the Mini‐Mental State Examination (MMSE), we evaluated the cognitive level of 19 AD patients at the baseline and after two years of follow‐up. The patients were grouped according to the rate of decline in the MMSE score along the two years: those who lost less than 4 points (N = 8) and those who lost four or more points (N = 11). To assess the expression profile of circulating microRNAs, blood samples were collected at baseline and plasma was used for total RNA extraction. The extracted RNA was subjected to two 384‐well TaqMan® array cards.ResultWe found a profile of 17 microRNAs that were differentially expressed between the two groups. From those, 11 microRNAs had an increased expression in patients with higher cognitive decline while 6 microRNAs had a decreased expression in these patients compared with those with a mild cognitive decline (Image). Furthermore, we observed that a subset of three microRNAs provided a tool with AUC of 0.90 for predicting the severity of the cognitive decline.ConclusionThese preliminary results are indicating that the profile of circulating microRNAs could be a useful tool for predicting the cognitive evolution in patients with early‐stage AD. The results of this study need to be validated in an independent cohort.
FKBP51‐Hsp90 complex as a novel therapeutic target for Alzheimer’s disease
Authors: Wang Lisha , Pavlov Pavel F. , Kumar Rajnish , Winblad Bengt 
Published: December 2020

AbstractBackgroundAlzheimer’s disease (AD) is the most common form of dementia without effective treatments. FK506‐binding protein 51 (FKBP51) recently emerged as a possible therapeutic target for resolving both tau aggregation and insulin resistance in AD. FKBP51 in complex with its partner, molecular chaperone Hsp90, increases tau stability, thereby promoting tau aggregation [1, 2]. FKBP51 also regulates insulin resistance and altered glucose metabolism which represent early events that precede or accompany the development of AD [3, 4]. Our study aims to investigate the potential roles of FKBP51‐Hsp90 interaction inhibitors in AD.MethodsA large dataset of available compounds were investigated using AlphaScreen™ and in silico virtual screening techniques to evaluate their inhibition on FKBP51‐Hsp90 interactions. Two of the selected specific inhibitors, E8 and C674, were then applied to SH‐SY5Y cells to test their effects on neurite outgrowth, overexpressed tau levels and glucose uptake. Furthermore, insulin signaling pathways were compared between vehicle‐treated vs inhibitor‐treated AD specimens.ResultsCompounds E8 and C674 inhibit FKBP51‐Hsp90 interactions at sub‐micromolar concentrations. E8 and C674 enhance neurite elongation, reduce overexpressed tau levels, stimulate glucose uptake and regulate insulin resistance.ConclusionWe showed that inhibiting specific FKBP51‐Hsp90 interactions with small molecules provides novel therapeutic targets for AD. References: 1. Jinwal, UK, et al., J Neurosci, 2010. 30(2): p. 591‐9. 2. Blair, LJ, et al., J Clin Invest, 2013. 123(10): p. 4158‐69. 3. Pereira, MJ, et al., Metabolism, 2014. 63(9): p. 1198‐208. 4. Balsevich, G, et al., Nature Communications, 2017. 8(1): p. 1725.
MRI morphometric data as predictor of PET amyloid positivity: New insights using brain connectivity metrics and machine learning
Authors: Pereira Helena Rico , Ferreira Hugo Alexandre 
Published: December 2020

AbstractBackgroundThe presence of brain amyloid‐beta plaques is relevant for the diagnosis of Alzheimer’s Disease (AD) [1‐3]. However, positron emission tomography (PET), used to assess amyloid loading, is expensive and not widely available as other imaging modalities [2]. Therefore, the aim of this study was to assess if magnetic resonance imaging (MRI) morphometric data (volumes, areas and thicknesses) and derived brain connectivity metrics would predict PET amyloid positivity.MethodMRI and 18F‐florbetapir PET images, age, gender, Mini‐Mental State Examination (MMSE) scores, and corresponding diagnosis were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database at baseline (90 AD: 77 amyloid positive; 177 Mild Cognitive Impairment ‐ MCI: 130 amyloid positive; 122 Control: 72 amyloid positive). PET images were processed using PETSurfer to compute the relative Standardized Uptake Value (rSUV) values [5] to be used as labels to divide subjects into amyloid positive (rSUV > 1.1) and amyloid negative (rSUV < 1.1) regardless of diagnosis. Volumetric T1‐weighted MRI images were segmented and parcellated using FreeSurfer to obtain morphometric data of cortical and subcortical structures. These data were also used to derive graph theory connectivity (GTC) metrics, which translate relations between the morphometry of different brain regions. Then, all these data were used as features to obtain models for predicting amyloid positivity using various machine learning algorithms. A 10‐fold cross‐validation approach with a data split of 70% for training and 30% for testing was used.ResultThe combination of morphometric data and GTC metrics, demographic and MMSE score data was the model with the highest accuracy: 77.8%, AUC‐ROC=0.719 (CI95%=[0.633; 0.804]), NPV=76.9%, PPV=77.9% using a support vector machine algorithm. Using the morphometric data and GTC metrics only the model achieved an accuracy of 77.3%, AUC‐ROC=0.713 (CI95%=[0.627; 0.799]), NPV=66.7%, PPV=79.6%, whilst using morphometric data alone achieved an accuracy of 75.6%, AUC‐ROC=0.671 (CI95%=[0.583; 0.760]), NPV=64.7%, PPV=77.4%. .ConclusionWhile the relationship between brain atrophy and amyloid deposition has been reported previously [6], the results described here suggest that GTC increases the sensitivity in depicting the atrophy‐amyloid correlation. Additionally, results also suggest that volumetric T1‐weighted may provide additional information for predicting amyloid positivity and loading. References: See https://drive.google.com/file/d/11fIvB9QM2R61WXPrXqHlyXjlbP87_V4H/view.
Single bilateral injection of endothelin‐1 leads to temporary deficits in memory and synaptic dysfunction
Authors: Diwakar Latha , Chithanathan Keerthana , Tomar Deepika Singh , Gowaikar Ruturaj , Ravindranath Vijayalakshmi 
Published: December 2020

AbstractBackgroundCerebral small vessel disease (SVD) has gained prominence worldwide as a major factor for cognitive impairment seen in dementia. Micro infracts causing elusive changes in cognitive function clinically will not get diagnosed are found to be the main risk factor for SVD. We were interested in creating micro infarcts rather than a severe insult to replicate small vessel damage, so we opted for Intra cerebroventricular (ICV) bilateral stereotaxic injection of endothelin‐1 (ET‐1) into lateral ventricles. Sub cortical injections of ET‐1 in brain has been used in many studies to accomplish long lasting vasoconstriction and gradual reperfusion causing lesion. Therefore, we tried to overcome this by injecting into lateral ventricles allowing it to spread through cerebrospinal fluid.MethodET‐1 (Endothelin‐ 1) a 21 amino acid vasoconstricting peptide was injected bilaterally into lateral ventricles of C57 mice. Some animals were injected unilaterally to see whether there are any motor deficits. Expression of CD31, a marker of endothelial cells was done by immunohistochemistry to assess vasoconstriction. Contextual fear conditioning, object recognition and Morris water maze task was performed to examine associative learning and spatial memory deficits. Gait and rotarod was performed to examine if there are any motor deficits. Synaptic plasticity was evaluated as activity dependent protein translation was measured in synaptoneurosomes prepared from hippocampus.ResultThe obstruction in cerebral blood flow due to vasoconstriction caused by ET‐1 injection leads to deficits in associative learning and spatial memory after 7 days. There was no change in gait or rotarod performance indicating no effect on motor function. However, the behavioral dysfunction was temporary and reversed after 30 days of ET‐1 treatment once the blood flow was restored. These changes were demonstrated as drop in the activity dependent protein translation after 7 days of ET‐1 injection and raise after 30 days of treatment as it is an indicator for synaptic plasticity.ConclusionBilateral injection of ET‐1 leads to prominent associative and spatial memory deficit and decline in activity dependent protein translation in hippocampus. Still these defects are reversible once the blood flow is restored. Unilateral injection of ET‐1 did not show any motor dysfunction.
BDNF‐Met polymorphism on top of amyloid pathology predisposes for faster cognitive decline in cognitively normal elderly: The SCIENCe Project
Authors: van den Bosch Karlijn Antoinette , Verberk Inge M.W. , Ebenau Jarith , van der Lee Sven J. , Jansen Iris E. , Prins Niels D. , Scheltens Philip , Teunissen Charlotte E. , van Der Flier Wiesje 
Published: December 2020

AbstractBackgroundPrevious studies showed that in preclinical AD, the Brain‐derived neurotrophic factor (BNDF) Val66Met polymorphism Met was related to faster decline in episodic memory. We aimed to assess the joint associations of BDNF Val66Met polymorphism and amyloid positivity with decline over time in the main cognitive domains, and with risk of incident dementia in cognitively normal adults with subjective cognitive decline (SCD). Additionally, we explored the effect of BDNF plasma levels on cognitive decline.MethodWe included 688 individuals with SCD (59 ± 8y, 39%F, MMSE = 28 ± 2) from the Amsterdam Dementia Cohort (ADC) and the SCIENCe project, with repeated performance on neuropsychological tests available (average follow‐up: 1.6 ± 2.4y, median number of visits 2 ± 2, total datapoints 1660). Participants were grouped by a four‐level variable based on Met‐carrierschip (Met+) and decreased baseline CSF Abeta42 (A+), resulting in n = 39 (6%) Met+A+, n = 206 (30%) M+A‐, n = 76 (11%) Met‐A+, n = 367 (53%) Met‐A‐ (reference group). For a subgroup (n = 198) baseline plasma levels BDNF was measured by Simoa. Linear mixed models (LMM) were used to assess associations with cognitive decline. We evaluated the association with risk of dementia using Cox proportional hazard model. All analyses were adjusted for age, gender and education.ResultCompared to Met‐A‐, Met‐A+ showed a steeper decline on some tests for memory, attention and executive functioning, while Met+A+ showed steeper decline on almost all cognitive tests, covering global cognition, memory, language, attention and executive functioning (Table 1). Met+A‐ was not associated with steeper decline. Met+A+ (HR = 9.2; 95%CI: 2.9‐29.1) and Met‐A+ (HR = 6.6, 95%CI: 2.2‐19.7) were at increased risk of dementia compared to Met‐A‐ (HR – reference), whereas Met+A‐ (HR 1.3, 95%CI 0.3‐4.8) was not. Plasma levels of BDNF were not associated with cognitive decline.ConclusionAmong individuals with SCD, Met‐carriership on top of amyloid pathology is associated with faster cognitive decline over time, and associated with higher risk of dementia. These results imply that this group might benefit from more frequent clinical monitoring.
Behavioural characterization of a new Alzheimer′s disease mouse model
Authors: Camargo Luana Cristina , Schöneck Michael , Sangarapillai Nivethini , Honold Dominik , Schemmert Sarah , Langen Karl‐Josef , Kutzsche Janine , Willbold Dieter , Willuweit Antje 
Published: December 2020

AbstractBackgroundBesides a large variety of research on Alzheimer’s disease (AD), there are still open questions regarding its pathophysiology. In this context, the development of a new transgenic mouse model TAPS, a genetic combination of heterozygous APP‐PS1dE9 and TBA2.1 mice, was accomplished. The TBA2.1 line expresses truncated amyloid‐β (Q3‐42), which is post‐translationally modified to pyroglutamate amyloid‐β (pE‐Aβ). Since this species of Aβ has been shown to be particularly cytotoxic and induces neurodegeneration in transgenic mice, TAPS mice were developed to mimic the combined human pathology of AD with amyloidosis and neurodegeneration.MethodIn this study, both male and female animals (18‐19 months old) were subjected to four cognitive tests: The Novel Object Recognition test (ORT), the T‐maze spontaneous alternation test, the Contextual and Cued Fear Conditioning test and the Morris Water Maze (MWM). Four groups were evaluated: Wild Type (n = 9), APP‐PS1dE9 (n = 4), TBA2.1 (n = 6) and TAPS (n = 7). Additionally, immunofluorescent staining was performed against amyloid‐β (6E10) and reactive astroglia (GFAP) in animals between 6‐18 months.ResultIn the ORT, wild type mice showed increased exploration of novel objects in comparison to familiar ones. In contrast, TAPS mice explored novel and familiar objects similarly, indicating loss of object recognition memory. In the Cued Fear Conditioning test, TAPS mice showed a significantly lower performance, as well as significantly less alternation than the wild types in the T‐maze. In the MWM, TAPS mice took more time to find the platform than the Wild type on the last day of training, suggesting a spatial memory deficit. Amyloid‐β staining showed progressive plaque formation between 6‐18 months, with an earlier onset in TAPS, in comparison to the parental APP‐PS1dE9 mice. TBA2.1 mice showed only small aggregates in striatum. The plaque‐pattern in TAPS mice combined those of the parental lines, as they showed agreggates in all brain regions including the striatum. Amyloidosis was accompanied by increasing reactive astrogliosis over the same period.ConclusionIt can be concluded that the TAPS mice have, besides an increased plaque pathology in comparison to the parental lines, cognitive deficits in four different behavioural tests, which underlines their potential as a mouse model for pE‐Aβ dependent amyloidosis.
Deficiency in a fly ortholog of HS‐aging related gene, sulfonylurea receptor/SUR, increased vulnerability to neurodegeneration in drosophila models of Alzheimer’s disease
Authors: Sekiya Michiko , Quan Xiuming , Sakakibara Yasufumi , Chikamatsu Sachie , Iijima Koichi M. 
Published: December 2020

AbstractBackgroundHippocampal sclerosis of aging (HS‐aging) is a common senile dementia characterized by sever neuron loss and gliosis in the hippocampus, and clinically mimics Alzheimer’s disease (AD). Polymorphisms in GRN, TMEM106B and ABCC9 have previously shown the association with HS‐Aging. However, the mechanisms and a molecular link between HS‐aging and AD remain elusive. Sulfonylurea receptors (SURs: ABCC8/SUR1 and ABCC9/SUR2) are the regulatory subunits of ATP‐sensitive potassium channels that coordinate energetic status and intracellular Ca2
+ levels in various cells. Mutations in SURs causes diabetes and cardiovascular diseases, both of which are known AD risks. Interestingly, single nucleotide polymorphism that increases the mRNA levels of ABCC9/SUR2 has been associated with a risk for HS‐aging, suggesting that ABCC9/SUR2 might influence pathogenesis of AD as well as HS‐aging.MethodUsing Drosophila as a model, we asked whether deficiency in Sur, a fly ortholog of SURs, is protective or detrimental to neuronal integrity during aging and under neurodegenerative conditions.ResultWe found that Sur deficiency by itself did not affect age‐associated changes in neuronal function and integrity. In contrast, Sur deficiency significantly worsened behavioral deficits and neurodegeneration by impairing energy metabolism in a fly model of amyloid‐β42 toxicity. We also demonstrated that Sur deficiency significantly exacerbated tau‐mediated neurodegeneration and AD‐related tau phosphorylation.ConclusionThis study suggests that ABCC9/SUR2 plays neuroprotective roles in the pathogenesis of AD and that increased ABCC9/SUR2 might extend clinical onset of AD.
EEG biomarkers for the early diagnosis of DLB
Authors: Bonanni Laura 
Published: December 2020

AbstractBackgroundThe early detection and classification of Dementia with Lewy Bodies (DLB) are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose DLB in the early stages. Efforts are being made to diagnose DLB in the early stages. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in DLB. This talk reports results of a multicenter European study on the role of electroencephalogram as a biomarker based on signal processing to detect DLB in early stages and classify its severity.MethodEEG was recorded in 144 DLB, 116 AD and 65 controls from 7 Centers of the European DLB Consortium. Spectra, divided into delta, theta, pre‐alpha, alpha frequency bands were described by DF, DF variability (DFV), frequency prevalence (FP).ResultQuantitative EEG was characterized by specific abnormalities in posterior derivations. These include a pre‐alpha‐dominant frequency, either stable or intermixed with alpha/theta/delta activities in pseudoperiodic patterns, which together have a predictive value >90% for the diagnosis of DLB compared with AD. These specific EEG patterns also correlate positively with the severity of clinically observed cognitive fluctuations and are seen at the MCI stage.ConclusionIn DLB EEG abnormalities can be considered a biomarker for DLB even at the very early stages of the disease.