bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between polygenic risk score of Alzheimer’s disease and CSF amyloid beta 42 in a cohort of 70‐year‐olds from the general population
Authors: Zettergren Anna , Najar Jenna , Kern Silke , Hardy John , Guerreiro Rita , Bras Jose , Zetterberg Henrik , Blennow Kaj , Skoog Ingmar 
Published: December 2020

AbstractBackgroundRecently, it was reported that as much as 45% of cognitively normal 70‐year olds from the general population had pathological CSF levels of either amyloid beta or tau, and the APOE e4 allele was significantly more common among these individuals. However, very few studies have investigated the effect of non‐APOE polygenic risk score (PRS) for Alzheimer’s disease (AD) on CSF biomarkers in representative population‐based samples. The aim of the present study was thus to investigate the relation between AD‐PRS and CSF biomarkers for AD and neurodegeneration in a representative sample of 70‐year‐olds.MethodA total of 303 individuals belonging to the Gothenburg H70 Birth Cohort Studies were included in the study. Genotyping was performed using the NeuroChip (Illumina) and imputation was done with the Sanger imputation service using the reference panel of Haplotype Reference Consortium data (HRC1.1). A PRS was calculated based on the allele counts of 23 AD risk‐variants multiplied with effect sizes (β‐coefficients) from IGAP. CSF levels of amyloid beta 42, total‐tau, phosphorylated tau, neurogranin and neurofilament light were measured with ELISA. Linear regression models, adjusted for sex and APOE e4 status, were used to analyze the association between AD‐PRS and CSF biomarkers.ResultAn association was found between the AD‐PRS and amyloid beta 42 (p = 0.003), showing a decreasing level of the biomarker with an increasing level of the PRS. No associations were found between the AD‐PRS and any of the other biomarkers. When only including cognitively healthy individuals (CDR = 0; n = 247), the association with amyloid beta 42 was still significant (p = 0.03). There was an interaction between the AD‐PRS and APOE e4 status (p = 0.04); the association between the PRS and amyloid beta 42 was present in e4 carriers only.ConclusionOur results show that genetic risk for AD beyond the APOE locus is associated with CSF‐amyloid beta 42, but not with any of the other investigated CSF‐biomarkers, among cognitively healthy 70‐year‐olds recruited from the general population. This finding is in line with the amyloid cascade hypothesis, showing that changed levels of CSF amyloid beta 42 is one of the earliest biomarkers related to AD.
Decreased salivary lactoferrin levels are specific to Alzheimer’s disease
Authors: Sánchez Marta González , Bartolome Fernando , Antequera Desiree , Martín Verónica Puertas , Gonzalez Pilar , Gomez‐Grande Adolfo , Velasco Sara Llamas , Martín Alejandro Octavio Herrero San , Martinez David Andres Perez , Galende Alberto Villarejo , Atienza Mercedes , Palomar Miriam , Cantero Jose Luis , Perry George , Orive Gorka , Ibañez Borja , Bueno Hector , Fuster Valentin , Carro Eva 
Published: December 2020

AbstractBackgroundEfforts focused on developing new less invasive biomarkers for early Alzheimer’s disease (AD) diagnosis are substantial. Evidences of infectious pathogens in AD brains may suggest a deteriorated defensive system in AD pathology. Lactoferrin (Lf), one of the major antimicrobial peptides in saliva, is an important oral defensive system that may control pathogen dissemination. In previous results, we demonstrated reduced salivary Lf levels in AD patients.MethodTo assess the specificity and clinical utility of salivary Lf for AD diagnosis, we examine the relationship between salivary Lf and cerebral amyloid‐β (Aβ) load in two different cross‐sectional studies including patients with different neurodegenerative disorders. Participants underwent neurological and neuropsychological examination and saliva sampling, and amyloid‐ PET neuroimaging. Salivary Lf concentrations were measured using ELISA assay.ResultTwo prospective, cross‐sectional, multicenter studies were examined divided in two different cohorts. Study participants for cohort 1 were consecutively enrolled between 2014 and 2018 from the 12 de Octubre University Hospital Neurology Service in Madrid (Spain) and Pablo de Olavide University in Sevilla (Spain). Study participants for cohort 2 were consecutively enrolled between June 2017 and December 2018 as part of the Atherobrain ‐ Heart to Head (H2H) project. Salivary Lf levels were significantly lower in mild cognitive impairment (MCI) and AD patients compared to cognitively normal subjects and frontotemporal dementia (FTD) subjects. The diagnostic performance of salivary Lf in the cohort 1 had an under the curve [AUC] of 0·95 (0·911–0·992) for the differentiation of the MCI/AD group positive for amyloid – PET (PET+) versus healthy group, and 0·97 (0·924–1) versus the FTD group. In the cohort 2, salivary Lf had also an excellent diagnostic performance in the health control group versus prodromal AD comparison: AUC 0·94 (95% CI 0·876–0·989).ConclusionSalivary Lf has a very good diagnostic performance to detect AD, as reduced salivary Lf levels shown a clear association to amyloid‐positive biomarker profile. Our findings support the utility of salivary Lf as a non‐invasive and cost‐effective AD biomarker in clinical practice and clinical trials.
Dynamic PET imaging reduces sample sizes to detect longitudinal amyloid accumulation
Authors: Alves Isadora Lopes , Collij Lyduine , Heeman Fiona , Molinuevo Jose Luis , Schmidt Mark E , Lammertsma Adriaan A , Cash David M , Barkhof Frederik , Gispert Juan Domingo ,   the AMYPAD Consortium
Published: December 2020

AbstractBackgroundDetecting amyloid‐β plaque accumulation in individuals who are initially amyloid negative can help understand the earliest stages of Alzheimer’s disease (AD). This study aimed to determine sample sizes that would be needed to detect statistically significant longitudinal changes using semi‐ (standard uptake value ratios; SUVR) and quantitative (distribution volume ratios; DVR) PET measures at global and regional levels.Method[11C]PIB scans of 239 cognitively normal (CN) subjects (mean age 63.4 ± 9.3 years) in the OASIS‐3 data‐set, who underwent at least two PET scans, were included. Regional SUVR and DVR were extracted using a cortical composite as target, and cerebellar gray matter as reference region (PUP, https://github.com/ysu001/PUP). PET positivity was defined by Gaussian Mixture Modelling of the global SUVR (SUVR>1.16). Annual accumulation rates were calculated using linear regression, and sample sizes to detect a significant longitudinal change (alpha = 0.05; 1‐beta = 0.80) were determined with the sampsizepwr function in Matlab. The percentage of accumulators (rates of change >2SD of negative group) was also computed.ResultAs expected, rates of change were higher in subjects with positive PET at baseline, and APOE‐ε4 carriership increased accumulation rates in both negative and positive groups (Table 1). Using either metric, orbitofrontal and precuneus displayed the highest rates of change in the negative group. SUVR rendered higher accumulation rates than DVR, but also displayed higher variability. As a consequence, to detect 0.22% early accumulation (mean of negative group), global DVR required N = 584 compared with N = 917 for global SUVR (Figure 1). In addition, DVR classified 13% of subjects as accumulators compared with 9% for SUVR. Finally, precuneus and orbitofrontal regions classify more subjects as accumulators than global SUVR, i.e. 17 and 25%, respectively.ConclusionAs compared to SUVR, DVR can reduce the sample size needed to detect longitudinal amyloid changes by approximately 40% in amyloid negative populations. Additional improvements in statistical power can be achieved by focusing on precuneus and orbitofrontal regions.
Differential diagnosis of dementia combining web‐based cognitive testing and MRI
Authors: Rhodius‐ Meester Hanneke F.M. , Koikkalainen Juha , Paajanen Teemu , Mahdiani Shadi , Barkhof Frederik , Herukka Sanna‐Kaisa , Hänninen Tuomo , Ngandu Tiia , Kivipelto Miia , van Gils Mark , Hasselbalch Steen Gregers , Mecocci Patrizia , Remes Anne , Soininen Hilkka , Scheltens Philip , van Der Flier Wiesje , Lötjönen Jyrki 
Published: December 2020

AbstractBackgroundDifferential diagnostics in dementia is challenging. To date, the basic assessment still includes imaging of the brain and cognitive testing with pen and paper. Web‐based cognitive tests however hold potential for standardized and low‐cost screening in clinical workup. How they perform when combined with imaging of the brain is unknown. We therefore evaluated the accuracy of a new web‐based cognitive battery (Muistikko [1]) detecting different types of dementia, when combined with brain MRI, and compared this to traditional cognitive testing and MRI.MethodWe included 229 subjects from two memory clinic cohorts (PredictND and VPH‐DARE), consisting of 188 controls, 29 patients with Alzheimer’s dementia (AD), 7 with frontotemporal dementia (FTD) and 5 with vascular dementia (VaD) (Table 1). All patients performed a traditional cognitive test battery (consisting of MMSE, RAVLT, TMT‐A and B, Animal Fluency), web‐based cognitive testing and had MRI of the brain. Although Muistikko is composed of seven subtasks, only global cognitive score (GCS) was used as defined in [1]. From MRI, multiple imaging biomarkers were defined [2]. Disease‐state index classifier was developed from the predictors [2]. Cross‐validation was used to calculate balanced accuracy (BACC; average of sensitivities for each diagnostic group). Given the class imbalance, we also calculated prevalence corrected accuracy (PACC).ResultBACC was 66 % and PACC 64% when using the traditional cognitive test battery + MRI. Both BACC and PAC were 69 % when using the web‐based cognitive testing + MRI (Table 2). Of note, since we compare four diagnostic groups, BACC by guessing would be 25%.ConclusionThis study shows that combining web‐based cognitive tests with MRI data results in high accuracy when separating different types of dementia. The results were comparable with the standard traditional work‐up. Web‐based cognitive testing is therefore a promising tool to support the clinician in the daily challenge of differential diagnostics, especially when combined with MRI data. References: [1] Paajanen, S. et al. Detecting cognitive disorders using Muistikko web‐based cognitive test battery. Alzheimer’s & Dementia 13(7):Supplement,P234‐P235,2017 [2] Bruun, M. et al. Evaluating combinations of diagnostic tests to discriminate different dementia types. Alzheimers Dement 2018 Aug17;10:509‐51.
Examining centiloid quantification against visual assessment using [18F]flutemetamol PET
Authors: Collij Lyduine , Salvadó Gemma , Alves Isadora Lopes , Reimand Juhan , Wink Alle Meije , Zwan Marissa D. , Niñerola‐Baizán Aida , Perissinotti Andrés , Scheltens Philip , Farrar Gill , Buckley Christopher , Molinuevo Jose Luis , Barkhof Frederik , Van Berckel Bart N.M. , Gispert Juan Domingo ,   the ALFA study,   the AMYPAD consortium
Published: December 2020

AbstractBackgroundDetermining the presence of amyloid pathology in vivo is possible by visual read (VR) and quantification. VR is the method of reference for clinically assessing amyloid pathology, and guidelines are based on distinguishing positive scans from Alzheimer’s dementia patients from healthy controls negative scans. More quantitative approaches using cut‐off values also focused on identification of early amyloid pathology in preclinical populations. This study investigated whether a VR‐defined cut‐off would perform similarly to recently proposed Centiloid (CL) cut‐offs.Methods[18F]flutemetamol PET images of 352 cognitively unimpaired (CU) participants from the ALFA+ and 145 patients from the ADC cohort were included (Table 1). Scans were read by an experienced reader according to the product guidelines, collecting the number of positive regions (0‐5) and the final positive/negative classification. Tracer uptake was quantified with the standard CL pipeline. Using VR as the reference standard, previously proposed CL=12/30 cut‐offs were tested for sensitivity and specificity. In addition, a data‐driven cut‐off was determined using ROC analysis and the Youden Index.Results152 (30.6%) scans were read as positive. The CL=30 cut‐off resulted in 80.3% sensitivity and 100% specificity, while the CL=12 cut‐off greatly improved the sensitivity to 95.2% and kept a high specificity at 95.9%. Based on the ROC analysis, a CL=16 cut‐off was found, with both excellent sensitivity (93.9%) and specificity (98.2%) (AUC of .99, 95% CI: .989‐.998) (Figure 1). Mean CL values significantly increased with increasing number of visually positive regions (F=568.10, η
2=.85, p<.01, Figure 2, Table 2). Number of visually positive regions was related to age in the ALFA+ CU population (F=9.17, η
2=.12, p<.01).ConclusionUsing VR as reference standard, we found a similar CL cut‐off to that proposed by previous work using independent amyloid biomarkers (post‐mortem and CSF). These results illustrate that CL can be as sensitive as VR to early amyloid pathology. Importantly, these results could (at least partially) be attributed the level of experience of the reader and the inclusion of mainly cognitively unimpaired subjects. In addition, our results suggests that it can be of value to visually capture the extent of amyloid burden in addition to negative/positive classifications.
Regular physical activity is associated with greater cortical inhibition in middle‐aged adults: Findings from Barcelona Brain Health Initiative
Authors: España‐Irla Goretti , Albu Sergiu , Morris Timothy P , Redondo‐Camós María , Delgado‐Gallén Selma , Cattaneo Gabriele , Tormos‐Muñoz Josep M , Bartrés‐Faz David , Pascual‐Leone Alvaro ,   Barcelona Brain Health Initiative Group
Published: December 2020

AbstractBackgroundAging has been associated with changes in the mechanisms of brain plasticity, specifically with the reduction of motor cortex excitability and decreased effectiveness of mechanisms of cortical inhibition (Pascual‐Leone et al., 2011; Lissemore et al., 2018). Emerging evidence suggests that regular practice of physical activity, which can increase cardiorespiratory fitness (Sobol et al., 2016), may prevent age‐related decline in the mechanisms of brain plasticity (Gomes‐Osman et al., 2017). We therefore hypothesized that those who engage in more physical activity would have greater corticospinal excitability and more efficient cortical inhibition.MethodsSeventy‐eight healthy adults (39 women), between 41 and 65 years old were included in the study. The amount of physical activity was assessed using a self‐reported 5‐point Likert scale where 1 equalled sedentary and 5 equalled engagement in aerobic physical activity >3 hours/week. The peak respiratory oxygen uptake (VO2 peak), aerobic threshold (VT1) and anaerobic threshold (VT2) were measured by cardiopulmonary exercise test with ventilatory gas analyses. Transcranial magnetic stimulation was used to assess resting motor threshold, motor evoked potential (MEP) amplitude and long‐interval intracortical inhibition (LICI), a measure of cortical inhibition.ResultsSpearman’s rank correlation revealed that greater engagement in regular physical activity was associated with higher VO2 peak (ρ=.470, p = .001), VT1 (ρ=.371, p = .001) and VT2 (ρ=.414, p = .001), and higher amplitude of resting MEP (ρ=.287, p = .018). Mann‐Whitney U tests revealed higher MEP amplitude (p =.003) and more efficient LICI (p =.018) in the group who exercised >3 hours/week compared to the sedentary group.ConclusionsRegular physical activity in middle‐aged adults is related with better cardiorespiratory fitness, greater corticospinal excitability and more efficient cortical inhibitory mechanisms.
Hippocampal connectivity may predict cholinesterase inhibitors response in mild Alzheimer’s disease
Authors: Moraes Adriel Santos , Magalhaes Thamires Naela Cardoso , Lecce Natalie , Teixeira Camila Vieira de Ligo , de Campos Brunno , Rezende Thiago Junqueira Ribeiro , Talib Leda Leme , Forlenza Orestes Vicente , Cendes Fernando , Balthazar Marcio Luiz Figueredo 
Published: December 2020

AbstractBackgroundAlzheimer's disease (AD) is a neurodegenerative disease that has been related to impairment of cholinergic system1. Changes in the cholinergic pathways observed in AD would result in severe deterioration of memory3. The aim of this study is to evaluate whether cerebrospinal fluid (CSF) biomarkers (Aβ42, p‐Tau and t‐Tau), hippocampal volumes (HV) and Default Mode Network (DMN) functional connectivity (FC) could predict response to the available treatment.MethodWe evaluated 38 mild AD patients who was using cholinesterase inhibitors (AChEI) at therapeutic doses for, at least, 24 weeks. All subjects underwent clinical evaluation, neuropsychological assessment, MRI at 3 Tesla (Achieva Intera Philips) and CSF biomarkers before or shortly after the onset of cholinesterase inhibitors. They were reevaluated after a minimum period of 24 weeks. CSF biomarkers were evaluated INNOTEST® kits (Fujirebio). Hipoccampal Volumes we assessed by Fressurfer software. DMN functional connectivity was evaluated by UF2C software. Patients were classified according to the MMSE (Mini Mental Status Examination) score before and after the stable use of cholinesterases inhibitors. Patients who remained stable or improved in the MMSE were classified as ‘Responders”; and the others as “Non‐responders”. We performed logistic regression to assess prediction of the proposed biomarkers (CSF, HV and DMN FC).ResultLogistic regressions did not reveal any statistically significant results in relation to CSF or HV biomarkers. However, the complete model, containing predictors of DMN was significant (X
2 = 11,776, Nagelkerk R2 = 0,375, p = 0.008). Only right hippocampal connectivity predicted AChEI response (p= 0.017), showing that the higher the hippocampus FC, better the response to AChEI.ConclusionRight hippocampus FC could predict the response to AChEI in our model. However more controlled studies are needed for safer conclusion.
Plasmatic microRNA profile as biomarkers for the diagnosis of obstructive sleep apnea in Alzheimer’s disease patients
Authors: Carnes Anna , Piñol Gerard , Dakterzada Faride , Targa Adriano , Tahan Nuria , Moncusi Anna , Benitez Ivan David , Barbe Ferran 
Published: December 2020

AbstractBackgroundTo investigate the potential of microRNAs (miRNAs) as biomarkers for the diagnosis of obstructive sleep apnea (OSA) in Alzheimer’s disease patientsMethodIn this prospective, single‐center study (NCT02814045), patients were diagnosed with Alzheimer’s disease according to the National Institute on Aging ‐ Alzheimer’s Association (NIA‐AA) recommendations. In addition, OSA was defined as an apnea‐hypopnea index (AHI) >15 events/h according to overnight polysomnography (PSG). Blood samples were collected at the following morning, and then a RT‐qPCR Taqman Low‐Density Arrays of 768 miRNAs was performed.ResultThe cohort included 29 patients, from which 12 patients were diagnosed as non‐OSA (41.38%) and 17 as OSA (58.62%). The median (SD) age of the individuals was 75.8 (5.99) years and the majority was composed of women (96.6%). We observed a set of 9 miRNAs that provided a discriminatory model of the OSA risk profile. From these, 7 miRNAs were significantly correlated with the AHI, suggesting a role not only as biomarkers for the presence of OSA but also for its severity.ConclusionOur preliminary results suggest that there are a set of miRNAs that could be important biomarkers for the diagnosis of OSA in Alzheimer’s disease patients and for the evaluation of OSA severity in those patients. These results should be further confirmed in a validation cohort.
Identification of APOE phenotypes in microglia and neurons derived from isogenic hips cells: A study of the IMI ADAPTED consortium
Authors: Bahnassawy Lamiaa , Buchheit Johanna , Curado Marco Rocha , Ried Janina S. , Sáez María Eugenia , Nicolas Armel , Rao Francesco , Kaplan Charlotte , Mohler Eric G. , Lee Heyne , Untucht Christopher , Korffmann Juergen , Lakics Viktor , Cik Miroslav , Grezella Clara , Brustle Oliver , Peitz Michael , Mañes Santos , Ramaswamy Gayathri , Socorro Alfredo Cabrera , Bakker Margot H.M. , Reinhardt Peter 
Published: December 2020

AbstractBackgroundOne of the most prominent genetic risk factors for Alzheimer’s Disease (AD) is the Apolipoprotein E (APOE) ε4 allele. Unlike the “neutral” ε3 variant, or the protective ε2variant, the ε4 variant is strongly associated with late‐onset AD, albeit by mechanisms that are not well‐understood.MethodsTo shed light on the biology of APOE in the development of AD, as part of the IMI (Innovative Medicines Initiative) consortium “ADAPTED”, we acquired two human induced pluripotent stem cell (hiPSC) lines, that were isogenically modified to carry the alleles ε2/ε2, ε3/ε3, ε3/ε4, ε4/ε4, as well as a knockout line. Neurons and the phagocytic cells of the CNS, the microglia were differentiated from all ten lines and subjected to thorough phenotyping, including RNA‐seq and proteomics analysis.ResultsCortical neurons do not secrete apoE under normal conditions and treatment of these cells with microglia‐enriched factors and apoE increased their overall Abeta secretion, without significant differences between the various genotypes. Microglia, on the other hand, secrete large amounts of apoE in varying quantities depending on the APOE genotype. Additionally, microglia carrying the ε4/ε4 genotype have a significantly reduced phagocytic capacity compared to their ε3/ε3 counterparts. These observations were supported by whole transcriptome sequencing, which revealed major differences in inflammatory and phagocytic activity‐related gene expression between the different APOE genotypes.ConclusionsThis unique set of ten isogenic hiPSC lines enabled us to assess the cellular phenotypes in functional human neuronal cells. Microglia omics show changes in an array of AD‐relevant pathways, and being the main producers of apoE, these changes need to be understood in depth. Follow‐up experiments will validate candidate genes that might help design new therapies for APOE ε4 AD patients. Disclosure: This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115975. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This study was sponsored by AbbVie Deutschland GmbH & Co. KG. AbbVie contributed to the study design, research, and interpretation of data, writing, reviewing, and approving the abstract. Some authors are currently employed by AbbVie and may own AbbVie stock.