bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antihypertensive medication classes and the risk of dementia: A systematic review and network meta‐analysis
Authors: GHE den Brok Melina , van Dalen Jan Willem , Abdulrahman Hanna , van Middelaar Tessa , van Gool Willem A , van Charante Eric P Moll , Richard Edo 
Published: December 2020

AbstractBackgroundHypertension is an important risk factor for dementia. Specific antihypertensive medication (AHM) classes may lower dementia risk more effectively than others. We aim to systematically review and synthesize the evidence on differential associations between AHM classes and the risk of dementia, using network meta‐analysis.MethodEmbase, MEDLINE and the Cochrane library were searched from origin to December 2019. We included randomized controlled trials and prospective cohort studies, including non‐demented participants with ≥one year of follow‐up. Data were extracted following PRISMA guidelines. Data on individual AHM classes were pooled using random effects frequentist network meta‐analysis.ResultFifteen observational studies and seven RCTs were included. Dementia occurred in 19,600/649,790 (3.02%) individuals. In observational studies, treatment with calcium channel blockers (CCBs) and angiotensin II receptor blockers (ARBs) conveyed lower dementia risks than treatment with other antihypertensives: CCBs compared to ACE‐inhibitors (HR=0.84, 95%CI 0.74‐0.95), beta blockers (BB) (HR=0.83, 95%CI 0.73‐0.95) and diuretics (HR=0.89, 95%CI 0.78‐1.01); ARBs compared to ACE‐inhibitors (HR=0.88, 95%CI 0.81‐0.97), BB (HR=0.87, 95%CI 0.77‐0.99) and diuretics (HR=0.93, 95%CI 0.83‐1.05). There were too few RCTs to create a robust network based on randomized data but similar conclusions were suggested.ConclusionRecommending CCBs or ARBs as preferred first‐line antihypertensive treatment may significantly reduce the risk of dementia. If confirmed in randomized trials, these findings reflect a low‐cost and scalable opportunity to reduce dementia incidence world‐wide.
Fluid‐based biomarkers to facilitate clinical trial execution and interpretation
Authors: Zetterberg Henrik 
Published: December 2020

AbstractBackgroundMost clinical trials in dementia prevention or disease modification have failed to meet their primary outcomes. During recent years, improved fluid‐ and imaging‐based biomarkers for Alzheimer’s disease (AD) pathologies have been developed. These can be used to increase the likelihood that the included patient population carries the pathology that the treatment is intended to ameliorate. However, the approach can be costly and results in frequent screen failures. Here, improved recruitment strategies that employ staged testing, from simple blood tests as pre‐screening tools to cerebrospinal fluid (CSF) analysis and neuroimaging for final diagnosis, are described and discussed.MethodsThe literature on blood‐, CSF‐, and imaging‐based biomarkers for amyloid and tau pathologies, as well as neurodegeneration, was reviewed. A number of staged testing scenarios were developed.ResultsThe best‐established blood‐based biomarker for AD pathology is phosphorylated tau (P‐tau). Plasma P‐tau distinguishes AD patients from cognitively normal controls with areas under the curve (AUCs) above 90% and detects both tau and amyloid pathology, as determined by positron emission tomography (PET), with AUCs around 90%, already in pre‐dementia stages of the disease. This diagnostic performance exceeds that of plasma Aβ42/Aβ40 ratio. Plasma neurofilament light (NfL) concentration is increased in AD and correlates with neuroimaging evidence of neurodegeneration. Employing plasma P‐tau181 as a pre‐screening biomarker in the recruitment of patients to clinical trials of amyloid‐ or tau‐targeting therapies would reduce the number of screen failures by at least 50% and virtually remove the costs for negative PET examinations. Plasma NfL, being a general marker of neuronal injury, has the potential to detect side effects of drugs, e.g., clinically relevant encephalitis.ConclusionsWe propose that future clinical trials of drug candidates against AD‐related pathologies are designed so that a pre‐screening with plasma P‐tau takes place, increasing the likelihood that patients with AD pathology are included and subjected to costly but important examinations, such as amyloid and/or tau PET at baseline. In addition to yearly PET examinations, more frequent testing of blood biomarkers during the trial could also help identifying positive effects of the drug candidate (P‐tau and NfL), and side effects detrimental to neuronal health (NfL).
PET evidence of preclinical cerebellar amyloid plaque deposition in autosomal dominant Alzheimer's disease
Authors: Ghisays Valentina , Lopera Francisco , Goradia Dhruman D. , Protas Hillary D. , Malek‐Ahmadi Michael H. , Chen Yinghua , Devadas Vivek , Luo Ji , Lee Wendy , Brown Christopher T. , Baena Ana , Bocanegra Yamile , Guzman‐Velez Edmarie , Pardilla‐Delgado Enmanuelle , Vila‐Castelar Clara , Fuller Joshua T. , Hu Nan , Clayton David , Smith Jillian , Thomas Ronald G. , Toga Arthur W. , Alvarez Sergio , Rios‐Romenets Silvia , Langbaum Jessica B. , Chen Kewei , Su Yi , Tariot Pierre N. , Quiroz Yakeel T. , Reiman Eric M. ,   API ADAD Colombia Trial Group
Published: December 2020

AbstractBackgroundIn contrast to late onset Alzheimer’s disease (LOAD), the late clinical stages of autosomal dominant Alzheimer’s disease (ADAD) are associated with greater neuropathological evidence of cerebellar amyloid plaque (Aß) deposition. In this study, we used PET measurements of fibrillar Aß burden to characterize the presence and age at onset of cerebellar Aß deposition in cognitively unimpaired Presenilin‐1 (PSEN1) E280A mutation carriers from the world’s largest extended family with ADAD.MethodFlorbetapir and PiB PET data from two independent studies – API ADAD Colombia Trial (NCT01998841) and the Colombia‐Boston (COLBOS) longitudinal biomarker study were included. Template‐based cerebellar standard uptake value ratios (SUVR), using a known‐to‐be‐spared pontine reference region, were used to 1) compare 290 cognitively unimpaired 28‐56 year‐old mutation carriers and non‐carriers; 2) characterize associations among cerebellar‐to‐pontine SUVR and age, mean cortical SUVRs, and episodic memory performance; and 3) estimate the age at which cerebellar‐to‐pontine SUVRs begins to differ significantly in the carrier and non‐carrier groups.ResultCompared to non‐carriers, cognitively unimpaired carriers had higher cerebellar‐to‐pontine florbetapir and PiB SUVRs (p<.0001). Mean cortical SUVRs were positively correlated with age and negatively correlated with episodic memory performance (p<.05). SUVRs began to distinguish carriers from non‐carriers at age 34, 10 years before the carriers’ estimated age at mild cognitive impairment onset.ConclusionThis PET study provides evidence of cerebellar Aß plaque deposition in cognitively unimpaired mutation carriers starting years before their clinical onset. Additional studies are needed to clarify the impact of using a cerebellar versus pontine reference region on the power to detect and track ADAD progression, even in preclinical stages of this disorder.
β‐arrestin2 oligomers impair the clearance of pathological tau and increase tau aggregates
Authors: Woo JungA Alexa , Liu Tian , Fang Cenxiao , Castano Maria , Kee Teresa , Yrigoin Ksenia , Yan Yan , Cazzaro Sara , Matlack Jenet , Wang Xinming , Zhao Xingyu , Kang David E. , Liggett Stephen B. 
Published: December 2020

AbstractBackgroundFrontotemporal lobar degeneration (FTLD) is second only to Alzheimer’s disease as a cause of dementia, and we find the scaffolding protein β‐arrestin2 is elevated in human brains with this condition, and is responsible for accumulation of pathological tau tangles. Increased β‐arrestin2 impairs tau clearance and promotes tau aggregation by impeding the autophagy cargo carrier p62/SQSTM1. Such activity requires β‐arrestin2 in its oligomeric form, an assembly state that is not involved with receptor binding. Virus delivered gene therapy to the brain with dominant‐negative mutant β‐arrestin2s ablates pathologic tau in neurons of a mouse model of FTLD‐tau, revealing a new strategy to mitigate tauopathy by targeting β‐arrestin2 oligomerization.Methodmice: Arrb2−/−, tau P301S, and WT mice were all bred in the C57BL6 background. Patients samples: Frozen frontal cortex tissue samples were obtained from the Alzheimer’s Disease Research Center at Emory University. We used samples from FTLD‐tau diagnosed patients. Primary neuronal cultures, Proximity ligation assay (PLA), Immunocytochemistry and Immunohistochemistry, Sarkosyl extraction, Generation of rAAV9 and stereotaxic injections, Electrophysiology, and Atomic force Microscopy Imaging applications were used in this study.Resultβ‐arrestin2 levels in brains of FTLD‐tau patients and tau P301S transgenic mice were significantly increased. β‐arrestin2 increases tau stability without altering tau mRNA levels. Furthermore, genetic reduction of β‐arrestin2 mitigates tauopathy and synaptic dysfunction in tau P301S mice. β‐arrestin2 oligomerization is required for tau stability, and β‐arrestin2 oligomers increase tau levels by inhibiting self‐association of the autophagy cargo receptor p62/SQSTM1, impeding p62 autophagy flux. Hence, reduction of oligomerized β‐arrestin2 with virus encoding β‐arrestin2 mutants acting as dominant‐negatives markedly reduced tau‐laden neurofibrillary tangles in FTLD mice in vivo. Reducing β‐arrestin2 oligomeric status represents a new strategy to alleviate tau pathology in FTLD and related tauopathies.ConclusionBased on our findings, the effects of inhibiting β‐arrestin2 oligomerization would be expected to not only inhibit the development of new tau tangles, but also to clear existing tau accumulations due to this mechanism of enhancing tau clearance. Beyond tauopathy, it is conceivable that this strategy could also prove to be beneficial in other neurodegenerative diseases bearing proteinopathies that are cleared via p62.
Using a novel clinical prediction algorithm to enhance clinical trials in Alzheimer's disease
Authors: Stern Yaakov , Stallard Eric 
Published: December 2020

AbstractBackgroundThe course of Alzheimer’s disease (AD) is heterogenous, in part because of individual heterogeneity in the disease’s underlying biological changes. This heterogeneity can influence the efficacy and interpretation of clinical trials. We developed a Grade of Membershp (GoM) prediction model that can accurately predict time to important disease endpoints in individual patients. Here we present the model and discuss its implications for clinical trials in AD.MethodThe GoM model was developed in the Predictors 2 cohort. It incorporates 73 time‐varying categorical covariates spanning 11 measurement domains including cognition, function; psychiatric symptoms, motor signs/symptoms and APOE genotype. We then tested the model in the separate Predictors 1 data set, consisting of 252 patients with mild AD at first visit who were followed semi‐annually for up to 10 years. We applied the GoM model to data from each patient‘s first visit, which generates a baseline GoM status. We then generated predicted survival functions and used life table analyses to compare predicted and actual survival.ResultThe figure summarizes the actual survival curve for all patients, and the survival curves as predicted from the GoM model. The predictions fell well within the confidence intervals around the actual survival curve. We also divided the estimated survival into quintiles, and compared the predicted versus actual quintile‐specific survival curves. Again, the predictions generally fell well within the confidence intervals around the actual survival curves.ConclusionOur new GoM model, applied to an external population, generated accurate predictions of survival using only the data from the patient’s first visit. Any variable in the model can also be predicted, including specific cognitive and functional outcomes. The GoM model has great potential for the design and interpretation of clinical trials in three ways: 1) randomization can be optimized or evaluated by comparing the distribution of GoM status in control and treatment groups; 2) the model should predict disease progression well in the placebo group; individual deviations from model prediction in the treatment group could indicate specific treatment effects; 3) with sufficient validation, the model itself could be used in the place of a placebo group.
Asymmetry of plaque burden in amyloid mouse models
Authors: Biechele Gloria , Sacher Christian , Blume Tanja , Beyer Leonie , Sauerbeck Julia , Eckenweber Florian , Deussing Maximilian , Focke Carola , Parhizkar Samira , Lindner Simon , Gildehaus Franz Josef , von Ungern‐Sternberg Barbara , Baumann Karlheinz , Tahirovic Sabina , Kleinberger Gernot , Willem Michael , Haass Christian , Bartenstein Peter , Cumming Paul , Rominger Axel , Herms Jochen , Brendel Matthias 
Published: December 2020

AbstractBackgroundAsymmetries of neuropathology, including amyloid‐β (Aβ) burden, are a well‐known phenomenon in patients with Alzheimer’s disease (AD). Yet the occurrence of asymmetric Aβ deposition in amyloid mouse models of AD is scantly documented. Therefore, we first aimed to investigate Aβ‐asymmetries in a comprehensive study of five different amyloid mouse models examined by Aβ‐ small animal positron‐emission‐tomography (PET). Second, we assessed whether any such asymmetries have an association with microglial activation.Method523 historical cross‐sectional [18F]‐florbetaben Aβ‐PET scans of five different amyloid mouse models (AppNL‐G‐F
, APP‐SL70, PS2APP, APP/PS1, and APPswe) and 27 wild‐type mice were analyzed. 136 of these mice (four models) had also undergone contemporaneous [18F]‐GE‐180 18kDa translocator protein (TSPO)‐PET for microglial activation. The asymmetry index (AI) between the left and the right forebrain was calculated for both tracers. AI values outside the 95%/99% confidence intervals of wild‐type mice were defined as having moderate/strong asymmetry. We also analyzed the AI of Aβ‐PET as a function of age and in correlation with TSPO‐PET AI and calculated extrapolated sample sizes required for analyses of single and combined hemispheres.ResultModerate/strong asymmetries of Aβ deposition were identified in 40%/30% of transgenic mice, occurring most frequently in the PS2APP and AppNL‐G‐F
models (see Figure 1). A significant left dominance in PS2APP and a significant right hemispheric dominance in APPswe mice were observed for Aβ deposition. There was no age dependency of AI, but there was a significant correlation between AIs of Aβ‐PET and TSPO‐PET (all R > 0.3, all p < 0.05; Figure 2). Asymmetry was associated with higher variance of SUVR in single hemispheres, leading to higher required sample sizes for a given power (see Figure 3).ConclusionAsymmetry of plaque neuropathology occurs frequently in amyloid mouse models of AD, contributing importantly to variance of results in single hemispheres. Concomitant asymmetry of microglial activation indicates a neuroinflammatory component to hemispheric predominance of fibrillary amyloidosis. Important lateralized distribution of fibrillar plaques has likely been a confounding factor in previous studies with Aβ mouse models and is not sufficiently considered.
Association of plasma abeta and tau levels in relation to cognition and brain structure in a diverse community
Authors: DeCarli Charles , Erickson Kelsey , Farias Sarah Tomaszewski , Olichney John M , Johnson David K , Dugger Brittany N , Mungas Dan M , Fletcher Evan , Maillard Pauline , Maezawa Izumi , Jin Lee‐Way 
Published: December 2020

AbstractBackgroundEarly studies of mostly non‐Hispanic White groups suggest that plasma tau and abeta levels are associated with clinically relevant cognitive impairment. Given limited studies of more ethnically diverse communities, we chose to study 402 subjects from the UC Davis Alzheimer’s Disease Center.MethodThe subjects were diverse (14% White, 45% Black and 41% Hispanic), 61% women, average age of 76 + 7.3 years with 12 + 5 years of education with a spectrum of cognitive ability (66% cognitively normal, 19% MCI and 15% demented). Plasma samples were obtained within 0.3 + 0.8 years of cognitive and MRI assessments. Duplicate plasma samples were measured for tau, abeta 40 and 42 on a Quanterix SRX using SIMOA technology. Subjects with CV >20% or extreme values (>5 SD) were excluded. Analyses compared cross‐sectional associations between plasma abeta and tau levels and diagnosis adjusting for age, sex, race/ethnicity and education as well as associations with memory, executive function and structural MRI measures.ResultThe table summarizes mean values for Tau, abeta 40, 42 and the 42/40 ratio across diagnoses and race/ethnicity. Both abeta 42 and the 42/40 ratio differed significantly by clinical diagnosis. The abeta 42/40 ratio was significantly lower for non‐Hispanic whites than Blacks and Hispanics (Tukey HSD, p <0.05). Higher plasma tau levels were weakly negatively associated (beta =‐0.04 + 0.02, <0.05) whereas higher abeta 42/40 ratios were significantly positively associated (beta = 6.6 + 2.9, p =0.02) with executive function. Higher abeta 42/40 ratios were also significantly positively associated (beta = 7.1 + 3.4, p <0.05) with hippocampal and temporal lobe gray matter (beta = 146 + 46, p =0.002) volumes. Logistic regression predicting diagnostic category found that the abeta 42/40 ratio significantly differentiated the groups (chi sqr =17, p = 0.0002).ConclusionIn this study of diverse, community recruited individuals, plasma abeta 42 and the abeta 42/40 ratio were significant predictors of clinical diagnosis, cognition and MRI measures, indication that plasma levels of abeta measured have clinical implications in a diverse cohort where mixed pathologies are known to be common1. Reference: 1.Filshtein TJ, Dugger BN, Jin LW, et al. J Alzheimers Dis 2019.
Xerogenic medications as a predictor for dental health intervention in people with dementia
Authors: Tan Edwin CK , Lexomboon Duangjai , Häbel Henrike , Fastbom Johan , Eriksdotter Maria , Johnell Kristina , Sandborgh‐Englund Gunilla 
Published: December 2020

AbstractBackgroundOlder people with dementia often have poor oral health. Chronic use of xerogenic medications may contribute to adverse dental outcomes. The aim of our study was to investigate the impact of xerogenic medication classes on the predicted risk for dental health interventions in people with dementia.MethodThis was a population‐based register study involving the Swedish Dementia Registry (SveDem), the Swedish Prescribed Drug Register, the Swedish National Patient Register, and the Dental Health Register. Participants were persons with dementia who were registered in the SveDem at the time of their dementia diagnosis. The exposure was xerogenic medication classes used over the 3‐year period immediately preceding the date of dementia diagnosis (baseline). The primary outcome was the composite of number of tooth extractions and dental restorations during the 3‐year period after baseline. Secondary outcomes included the number of tooth extractions and number of dental restorations. Poisson regression models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between the exposure and outcomes. Analyses were adjusted for age, gender, Mini‐Mental State Examination, living arrangement, dementia disorder, average number of medications, Charlson’s comorbidity index, number of dental visits and number of teeth.ResultA total of 30955 people were included in the analysis. After adjusting for potential covariates, the use of urological drugs (IRR 1.16, 95% CI 1.04 – 1.28), proton pump inhibitors (IRR 1.13, 95% CI 1.04 – 1.23) and opioids (IRR 1.19, 95% CI 1.06 – 1.34) were significantly associated with the primary composite outcome.ConclusionThe use of specific classes of xerogenic medications was associated with an increased risk for tooth extractions and restorations in people with dementia. The risks and benefits of xerogenic medications, in the context of oral health, should be carefully assessed in this vulnerable population.
Accumulating and heterogeneous network‐knockout profiles in amnestic mild cognitive impairment and Alzheimer’s disease dementia
Authors: Nestor Sean M , Bratislav Misic , Ramirez Joel , Graham Simon J , Verhoeff Nicolaas Paul L.G. , Stuss Donald T , Masellis Mario , Black Sandra E ,   Alzheimer's Disease Neuroimaging Initiative
Published: December 2020

AbstractBackgroundLarge‐scale brain networks are disrupted in Alzheimer’s disease (AD). We posit that network disruption may be explained by additive and multifactor knockout of multiple networks (functional and structural) as opposed to a single system or set of subsystems. Here we test this hypothesis using a data‐driven structural covariance network analysis.MethodsDemographic, imaging and available biomarker data were downloaded from 77 normal controls (NC) (age= 72±6, M/F=33/44), 106 persons with amnestic mild cognitive impairment (MCI) (age= 73±8, M/F=70/36) and 42 persons with Alzheimer’s dementia (age=75±9, M/F=25/17) that participated in the Alzheimer’s Disease Neuroimaging Initiative 2.0. We used a multivariate covariance technique to isolate large‐scale grey matter networks that relate fiber tract microstructure derived at different stages of injury to vertex‐based cortical thickness maps. Cortical thickness was computed from 3.0 Telsa T1‐weighted MRI and tract‐based white matter microstructural measures were performed using diffusion tensor imaging; these data were submitted to a multivariate data‐driven analysis. Measures of network integrity (NII) were computed for each significant covariance network for all participants. Univariate models assessed the relationship between biomarkers, demographic variables and NIIs for each network. Network knockouts were defined as an NII <1.5 SD below the NC group average for a given network. Knockout combinations were characterized across individuals and average knockout numbers were compared between groups.ResultsEight network ensembles related to tract‐based connectivity or recapitulated functional network architecture. Degradation of these systems was additively and differentially linked to increased age, APOE e4 genotype and unique combinations of white matter hyperintensity volume, CSF markers (CSF amyloid and Tau protein levels) and hippocampal volume in MCI. Knockouts exponentially and significantly increased across groups: NC>MCI>AD (P<0.01). There were 64 unique network knockout combinations across all participants.ConclusionHeterogeneous pathological exposures may additively and differentially disrupt large‐scale networks, leading to many possible network knockout sequences that accumulate exponentially from MCI to AD. These findings may partially explain the endophenotypic heterogeneity in AD and should be assessed in other cohort samples.