bluuebunny/crossref_metadata_2025_split huggingface dataset:
Directed graph‐based longitudinal model for spatiotemporal dynamics of amyloid, tau, and neurodegeneration in the Alzheimer’s disease spectrum
Authors: Lee Wha Jin , Cho Hanna , Shin Jeong‐Hyeon , Lyoo Chul Hyoung , Seong Joon‐Kyung 
Published: December 2020

AbstractBackgroundβ amyloid deposition, pathological tau, and neurodegeneration are regarded as critical biomarkers to biologically define Alzheimer’s disease (AD) in living people. Development of tracers for positron emission tomography (PET) enables extracellular amyloid plaques and intraneuronal neurofibrillary tangles to be detected in vivo. Identifying in vivo spatiotemporal dynamics of those three biomarkers could be a key to understand the disease progression in Alzheimer’s continuum.MethodsWe recruited 74 healthy controls, 61 amnestic mild cognitive impairment patients, and 38 AD patients with T1‐weighted magnetic resonance image (MRI) and two PET scans ([18F]Flortaucipir for tau and [18F]Florbetaben for Aβ) with about two‐year follow‐up data. Longitudinal W‐scores were calculated from standardized uptake value ratios (SUVRs) for two PET data and cortical thicknesses for MRI data. All participants were aligned in the order of standardized baseline tau SUVRs using the frequency‐based tau spreading model. Partial correlations (PC) were then computed between every regional pair of baseline and follow‐up data for each biomarker within a time window involving a part of participants. Directed graphs were constructed based on the PCs for each biomarker by moving the time window through the temporal participant‐orders.ResultsAmyloid seemed to follow the Thal stage. With the early window most connections existed within neocortex, and the connections moved to allocortex. Tau also seemed to follow the Braak stage showing the connections advanced from entorhinal regions to neocortex as the subject window moves to late order. However, temporal domain of amyloid and tau connections within the same area were distinct each other. Especially for tau, we found that the network hubs varied temporarily and diameters of the temporal graphs seemed to increase substantially as the hub moves out of the medial temporal lobe. Neurodegeneration showed similar trends to tau with later temporal domain.ConclusionsIn this study, we suggested the in vivo temporal alterations of interregional affections for amyloid, tau, and neurodegeneration from asymptomatic to clinical AD. All biomarkers exhibited analogous trends to previous researches and the moments of appearances for each biomarker were different. To detect these peculiar spatiotemporal characteristics between biomarkers might be valuable to figure out AD progression.
Novel application of digital dementia phenotyping and risk classification for insurance and longevity risk modeling
Authors: Rao Anitha , Miller Benjamin , Kulman Tanzila , Pinho Paulo , Aggarwal Neelum T 
Published: December 2020

AbstractBackgroundAs the global prevalence of Alzheimer’s disease and related dementias (ADRD) continues to soar, risk bearing entities in both the public and private insurance and financial services sector will be faced to evaluate and estimate the cost of care, morbidity, and mortality for ADRD patients. Historically, insurance actuaries have evaluated ADRD from a homogenous risk perspective. Risk variability in dementia and multi‐morbid risk is not considered during actuarial insurance risk modeling practices across various types of insurance products including long term care insurance (LTCI), pension longevity risk, life insurance, and health insurance in the public and private sector.MethodIn a multi‐carrier insurance deployment, Neurocern Inc, a neuroinformatics and data analytics company, applied a novel method to collect neurobehavioral and morbidity risk attributes for potential ADRD patients who were applying for LTCI claims benefits. Utilizing Neurocern’s proprietary analytics, risk attributes were collected on each ADRD patient over a 10‐month time frame from carriers that represented over 1 million lives, and approximately more than $50B in claims exposure. Digital dementia phenotypes and risk classifications were developed using Neurocern’s predictive analytics.ResultA total of 228 patients (F=154, M=74) were assessed and the following cognitive domains were included: memory, visuospatial, behavioral, executive, language, and motor. Additional data such as functional status, claims data, and prescription data was collected on a subset of patients. MMSE and SPMSQ ranged between 1‐30 and 0‐10 respectively. Education level ranged from 8th grade to postgraduate level. Neurocern’s analytics created clustered risk classifications and the cost of care varied significantly between risk classes.ConclusionNeurocern’s predictive analytics created a first to market proprietary digital dementia risk classification score for insurance and longevity risk modeling. This research highlights the application of a multivariate ADRD actuarial risk modeling approach in insurance and longevity markets for estimating cost of care, morbidity, and mortality.
Altered cerebral vessel amplitude and oscillation frequencies in Alzheimer’s disease compatible with impaired amyloid clearance
Authors: Grimmer Timo , Kotliar Konstantin , Ortner Marion , Conradi Anna , Hacker Patricia , Hauser Christine , Günthner Roman , Muggenthaler Claudia , Förstl Hans , Diehl‐Schmid Janine , Schmaderer Christoph 
Published: December 2020

AbstractBackgroundRetinal vessels are similar to cerebral vessels in their structure and function. Using a non‐invasive in‐vivo technique, we demonstrated previously that retinal vessel response to flicker is more emphasized and delayed in patients with dementia due to Alzheimer’s disease (AD) compared to healthy controls (HC). Increasing evidence suggests that interstitial fluid of gray matter appears to flow outward via paravascular spaces which are located alongside cerebral vessels possibly being passively propulsed by vessels’ pulsatility. Impaired pulsatility resulting in impaired clearance of molecules such as beta‐amyloid may in parts explain amyloid deposition in the brain. Moderate low pulsatility frequencies of around 0.1 Hz have been reported as the driving force for paravascular drainage in mice just recently. We aimed to elucidate whether retinal vessels’ pulsatility in particular at low frequencies (0.05‐0.15 Hz) is changed in AD at the stage of dementia or mild cognitive impairment (MCI).MethodsThree groups of participants were examined by Dynamic Vessel Analyzer (IMEDOS Systems): 17 patients, 72.0 (62.0 – 79.0) y.o. [median (1st quartile – 3rd quartile)], with mild‐to‐moderate dementia due to probable AD ; 23 patients, 69.0 (61.0 – 71.0) y.o. with MCI due to AD, and 18 anamnestic healthy control subjects 66.5 (61.3 – 66.5) y.o. without cognitive impairment (HC).ResultsPower spectra of the temporal arterial curves differed between the groups. Especially at moderate low frequencies around 0.1 Hz (0.05 – 0.15 Hz) ADD and most MCI arterial oscillations, characterized by the normalized area under the power spectrum, prevailed over HC oscillations. Within the heart frequency range of 0.8 – 0.9 Hz retinal arterial pulsations in MCI and AD groups were significantly more emphasized as in the HC group.ConclusionsIn ADD and MCI power spectra of retinal arterial oscillations seem to shift from very low to moderate low frequencies. Interestingly, the latter frequencies correspond to those reported for lymphatic vessels in humans and those for paravascular drainage in mice. The emphasized retinal arterial pulsation at moderate low frequencies in ADD and MCI group would be compatible with the view of compensatory upregulation of paravascular drainage in AD and strengthen the amyloid clearance hypothesis.
Emerging beta‐amyloid pathology is associated with tau, synaptic, neurodegeneration and gray matter volume differences
Authors: Molinuevo Jose Luis , Milà‐Alomà Marta , Salvadó Gemma , Gispert Juan Domingo , Grau‐Rivera Oriol , Sala‐Vila Aleix , Sánchez‐Benavides Gonzalo , Arenaza‐Urquijo Eider M , González‐de‐Echávarri José Maria , Simon Maryline , Kollmorgen Gwendlyn , Zetterberg Henrik , Blennow Kaj , Suárez‐Calvet Marc ,   ALFA Study
Published: December 2020

AbstractBackgroundNew clinical trials, like the A3, are targeting participants with emerging amyloid pathology (between 20‐40 centiloids (CL). The aim of this study is to describe if there are detectable differences in tau, synaptic, inflammatory, neurodegeneration CSF markers and brain structure in participants with emerging amyloid pathology.MethodCSF Aß42, Aß40, t‐tau, p‐tau, neurogranin, GFAP, IL‐6, YKL‐40, sTREM2, NfL, S100B and α‐synuclein were measured with Elecsys® CSF assays and the Roche NeuroToolKit robust prototype assays in 303 cognitively unimpaired participants of the ALFA+ cohort. Participants also underwent APOE genotyping, structural MRI, as well as [18F]flutemetamol PET. Emerging amyloid pathology was defined in two different ways for checking results consistency: (1) Participants with less than 40 CL and a positive Aß42/40 ratio to be compared with those having less than 20 CL and a negative ratio (amyloid‐negative) and those with more than 40 CL and a positive ratio (amyloid‐positive). (2) Participants having between 20‐40 CL to be compared with those having less than 20 CL (amyloid‐negative) and more than 40 (amyloid‐positive). All CSF biomarker levels were compared between the emerging amyloid and its corresponding amyloid‐negative and ‐positive groups. SPM12 was used to seek for differences in gray matter volumes (GMv) among groups, after accounting for age, sex, APOE, education.Result89 and 16 participants fulfilled emergent amyloid criteria 1 and 2 respectively (demographics Table 1). Compared to the amyloid‐negative group, significantly increased levels of CSF p‐tau, t‐tau, neurogranin, and NfL could already be observed in the emerging amyloid group (both definitions, Figure 1a), whereas the remaining biomarkers only demonstrated increased abnormality in the amyloid‐positive group. Subjects with emerging amyloid pathology compared with the amyloid‐negative ones had greater GMv in the angular, supramarginal, fusiform, anterior temporal and medial frontal pole (Figure 1b). The association of the GMv differences and its interactions with the different biomarkers will also be presented.ConclusionThese results provide evidence that multiple biological pathways, such as tau, synaptic and neurodegenerative, are already altered in participants with emergent amyloid pathology, which also have greater gray matter volumes. Therefore, intervening very early in the Alzheimer’s continuum may be a priority.
Cerebrospinal fluid levels of SNAP‐25 and SYT1 in Alzheimer’s and Parkinson’s disease
Authors: Brinkmalm Ann , Larsson Victoria , Janelidze Shorena , Zetterberg Henrik , Blennow Kaj , Hansson Oskar 
Published: December 2020

AbstractBackgroundDisease‐related synaptic pathologies are common in neurodegenerative diseases, e.g. Alzheimer’s disease (AD), and Parkinson’s disease (PD). In AD, synapse loss appears to occur earlier in the disease process than the plaques or tangles and is more strongly correlated with cognitive decline. Recently it has become possible to study synaptic loss by quantifying synaptic proteins directly in cerebrospinal fluid (CSF). Increased CSF levels of the postsynaptic protein Neurogranin (Ng) in patients with AD or mild cognitive impairment have been shown in several studies. Interestingly, increased CSF Ng levels have not been observed in PD and other neurodegenerative diseases. Significantly elevated CSF levels of the presynaptic proteins GAP‐43, SNAP‐25, and synaptotagmin‐1 (SYT1) have also been found in patients with AD and MCI compared with controls. However, these studies need to be independently replicated in larger and more diverse cohorts, including other neurodegenerative diseases.MethodWe measured the CSF levels of SNAP‐25 and SYT1 in the prospective Swedish BioFINDER study, which included 1282 subjects, of which 553 were Ab‐negative controls, 195 Ab‐positive controls, 110 Ab‐negative cases with MCI, 137 Ab‐positive cases with MCI, 152 cases with AD with dementia and 135 cases with PD.ResultSNAP‐25 concentration in CSF was increased in AD patients with dementia compared with Ab‐negative controls and MCI patients (p<0.0001), but also compared with Ab‐positive controls. Further, the levels were also increased in Ab‐positive controls and Ab‐positive MCI patients compared with Ab‐negative controls (p<0.0001). In PD, there was a non‐significant trend to decreased levels compared to controls. SYT1 in CSF was increased in AD patients compared with Ab‐negative controls and MCI patients (p<0.0001). The levels were also increased in Ab‐positive controls (p<0.0001) and Ab‐positive cases with MCI compared with Ab‐negative controls (p <0.05). The levels were decreased in PD compared with controls (p <0.05). Group comparison of SNAP‐25 and SYT1 levels. (*p <= 0.05, ****: p <= 0.0001) are shown in figures.ConclusionCSF SNAP‐25 and SYT1 concentrations increase already during the preclinical stages of AD, and SNAP‐25 was further increased in AD dementia. In PD, the levels were decreased, especially for SYT1.
Differential involvement of limbic and paralimbic cortex in episodic memory processing in cognitive aging and neurodegeneration
Authors: Schaeverbeke Jolien , Gabel Silvy , Meersmans Karen , Adamczuk Katarzyna , Van Laere Koen , Dupont Patrick , Vandenberghe Rik 
Published: December 2020

AbstractBackgroundA key component of cognitive aging is episodic memory decline. Here we examined to which degree structural integrity of (para)limbic cortex and amyloid load contribute to normal episodic memory variation in subjects between 50 and 80 years old using mediation analysis. The main hypothesis was that the effect of age on episodic memory would be mediated through hippocampal volume.Method180 community‐recruited cognitively intact older adults belonging to the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F‐PACK) cohort had cognitive test scores within norms as inclusion criterion, genotyping (APOE ε4 and BDNF), MRI and [18F]flutemetamol‐PET. Factor analysis was applied to determine the latent structure in the neuropsychological dataset. The primary factor (variance explained: 23%, Eigenvalue: 2.26) mainly contained episodic memory test scores: Buschke selective reminding (loadings: learning: 0.83, delayed‐recall: 0.96) and Rey Auditory Verbal Learning Test (0.60). Structural T1‐weigthed MRI were processed using voxel‐based morphometry. Hippocampal, entorhinal, perirhinal and parahippocampal volumes were derived by intersecting the modulated gray matter with Brainnetome parcellations. Amyloid load was quantified in a composite neocortical volume on [18F]flutemetamol SUVR with cerebellar grey matter reference. Linear regressions or Mann‐Whitney U tests investigated associations with episodic memory, which were further analyzed with bootstrapped mediation (R‐package ‘lavaan’).ResultHigher age was negatively related to lower episodic memory scores (β=‐0.066, p<0.001), to lower hippocampal volume (β=‐0.005, p<0.001) and to lower entorhinal cortex volume (β=‐0.003, p<0.001). Lower hippocampal volume (β=3.80, p=0.0004) as well as entorhinal cortex volume (β=3.67, p<0.001) were related to lower episodic memory. There was no significant correlation of amyloid nor a genetic effect regarding age or episodic memory (p>0.12). Hence, we did not include amyloid or genotypes in further analyses. In the mediation analysis, hippocampal volume did not mediate the relation between age and episodic memory (Figure 1A). By contrast, entorhinal cortex volume did mediate the relation between age and episodic memory, however the direct path coefficient was also significant (Figure 1B). No significant indirect effects were found in the path analysis for the perirhinal cortex or parahippocampus (p>0.14).ConclusionThe effect of age on episodic memory is partly mediated by entorhinal rather than hippocampal volume in cognitive aging.
Localization and protein levels of YKL‐40 in postmortem brain of frontotemporal dementia and Alzheimer’s disease cases
Authors: Hok‐A‐Hin Yanaika S. , Hu William T. , Wouters Dorine , Boonkamp Lynn , Howell J. Christina , Rabano Alberto , Pijnenburg Yolande A.L. , Teunissen Charlotte E. , Hoozemans Jeroen J.M. , Del Campo Marta 
Published: December 2020

AbstractBackgroundLevels of the inflammatory protein YKL‐40 (Chitinase 3‐like I) are increased in CSF of patients with Frontotemporal dementia (FTD) and Alzheimer’s disease (AD), suggesting YKL‐40 is a potential CSF biomarker reflecting the ongoing neuroinflammatory process. How YKL‐40 is localized and expressed in the brain in various neurodegenerative diseases is still elusive. In this study, we assessed the presence and levels of YKL‐40 in post‐mortem brain tissue of non‐demented controls and dementia cases with different pathologies (FTD and AD). In addition, we addressed the correlation of YKL‐40 levels between post‐mortem tissue and ante‐mortem CSF.MethodThe presence of YKL‐40 was analyzed in post‐mortem frontal or temporal cortex of non‐demented controls (NDC, total n = 83), FTD patients (n = 90), and AD patients (n = 59) by immunohistochemistry, western blot or ELISA (see Table 1). In a subset of cases where paired ante‐mortem CSF was available, CSF YKL‐40 was also measured by ELISA (n = 9, time interval CSF and post‐mortem collection: 1,4 years).ResultYKL‐40 appeared to be mainly detected in astrocytes. YKL‐40 levels were similar between FTD or AD and non‐demented controls by either immunohistochemistry, western blot, or ELISA (p>0.05). No correlation between ante‐mortem CSF YKL‐40 and post‐mortem brain YKL‐40 was observed (r = ‐0.49; p>0.05). Interestingly, strong YKL‐40 immunoreactivity was observed in AD cases with an increased presence of cerebral amyloid angiopathy (CAA).ConclusionOur data suggest that CSF YKL‐40 changes do not mirror the overall pathological changes affected in FTD or AD. Increased presence of YKL‐40 in AD cases is strongly associated with the presence of CAA and most likely reflects the intense neuroinflammatory response associated with CAA.
Longitudinal changes in [18F]Flutemetamol load in cognitively intact APOE ε4 carriers vs noncarriers: Comparison of three reference regions
Authors: Luckett Emma Susanne , Schaeverbeke Jolien , Adamczuk Katarzyna , Van Laere Koen , Dupont Patrick , Vandenberghe Rik 
Published: December 2020

AbstractBackgroundWe use the Flemish Prevent AD Cohort KU Leuven (F‐PACK) to determine changes in amyloid load over a longitudinal period, and investigate the influence of APOE ε4 on these changes, comparing three reference regions.Method64 cognitively intact healthy F‐PACK participants (baseline age: 68 (55‐80), 30 carriers of APOE ε4) received a static [18F]Flutemetamol‐PET scan at a baseline visit (2010‐2015, acquisition window: 90‐120 minutes), as well as extensive neuropsychological testing (scores within published norms) and structural MRI scan. A follow‐up PET scan has been taken 3.4‐8.6 years after baseline in order to calculate changes in amyloid SUVRcomp in a neocortical composite volume of interest. Either subject‐specific cerebellar grey matter (CGM), or eroded subcortical white matter (ESWM), or pons was used as a reference region. Spearman’s correlation was used to determine the influence of baseline SUVRcomp on follow‐up SUVRcomp. APOE ε4 effects were determined using Wilcoxon matched pairs signed rank tests or Mann‐Whitney U‐tests, for the effects on absolute SUVRcomp and rate of change respectively. Rate of change was defined as absolute change divided by time interval.ResultThere was a significant correlation between baseline and follow‐up SUVRcomp for each of the reference regions (CGM: R = 0.69, p = 3.25e‐10; ESWM: R = 0.75, p = 1.14e‐12; pons: R = 0.75, p = 1.29e‐12). There was a significant increase in SUVRcomp at follow‐up, compared to baseline, in APOE ε4 carriers when using only the CGM or pons (CGM W = 118.5, p = 0.02; pons: W = 79, p = 0.003; ESWM: W = 208.5, p = 0.63). No significant differences were found between baseline and follow‐up in non‐carriers, nor in baseline values between carriers and non‐carriers. APOE ε4 carriers had a significantly higher follow‐up amyloid SUVRcomp compared to non‐carriers, only when using the CGM or pons (GCM: U = 658.5, p = 0.05; pons: U = 706.5, p = 0.008; ESWM: U = 586, p = 0.31). Rate of change was also significantly elevated in APOE ε4 carriers versus non‐carriers when using the CGM and pons (GCM: U = 680, p = 0.02; pons: U = 717.5, p = 0.005; ESWM: U = 560, p = 0.51).ConclusionAmyloid deposition and rate of change are enhanced by APOE ε4. Cerebellar grey matter and pons are the more suited reference regions to capture early differential effects of the APOE ε4 polymorphism on amyloid accumulation.
Classification of 18F‐flutemetamol scans using machine learning with neuropathology as standard of truth
Authors: Reinartz Mariska , Farrar Gill , Buckley Christopher , Smith Adrian , Thal Dietmar Rudolf , Dupont Patrick , Vandenberghe Rik 
Published: December 2020

AbstractBackgroundThere is a rising interest in machine learning for classification of images and lesions in medicine. A hurdle is the necessity for enough labeled cases based on an independent standard‐of‐truth. Here we applied linear support vector machine (SVM) to the phase 3 18F‐flutemetamol end‐of‐life study (GE067‐007), where 18F‐flutemetamol PET scans were available in close proximity to the time of autopsy and where brains were characterized in a standardized manner.MethodAs our primary analysis, we trained a leave‐one‐out SVM to discriminate between normal vs abnormal cases based on Bielschowsky silver staining (BSS) (the primary outcome measure of GE067‐007). As a secondary analysis, we also trained a classifier to discriminate between Aβ (Thal) phase 0‐1 vs phase 5. The dataset contained 29 normal and 72 abnormal cases according to BSS SoT and 17 phase 0‐1 and 44 phase 5 cases. To avoid bias, the number of cases was equated between classes (29 per class for BSS and 17 per class for Aβ). Selection of cases per class was performed randomly 50 times.ResultCompared to the BSS SoT, the classifier had a sensitivity of 84% and a specificity of 90% (accuracy 87%) (Figure 1). Compared to Aβ phase, the sensitivity and specificity was, respectively, 97% and 100% (accuracy 98%). The three discordant BSS SoT normal cases, all had Aβ phase 3 or higher. Overall, highest feature weights were in striatum, middle frontal gyrus, precuneus, middle temporal, and cingulate. When we selected the voxels with the 10% highest amplitudes of feature weights (Figure 2) and re‐ran the analysis against the BSS SoT, performance increased to 95% sensitivity and 98.8% specificity. When we trained the algorithm to distinguish Aβ phase 4 (n=21) or 3 (n=14) from 0‐1, accuracy decreased to 88.8% and 71.9% respectively. In a further analysis, Aβ phase 3 vs 4 classification had an accuracy of 62.4% (95% CI 60.8, 63.9) and for phase 4 vs 5 an accuracy of 60.3% (95% CI 58.4, 62.1).ConclusionThis study shows that SVM is able to classify 18F‐flutemetamol scans in a binary manner (normal vs abnormal) which closely corresponds to the neuropathology measures.