bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clusterin is associated with Alzheimer’s disease biomarkers and cognitive scores in the pre‐symptomatic phase of the disease.
Authors: Dauar Marina Tedeschi , Picard Cynthia , Rosa‐Neto Pedro , Villeneuve Sylvia , Poirier Judes ,   Prevent‐AD Research Group
Published: December 2022

AbstractBackgroundClusterin (CLU) is one of the main genetic risk factors of late onset Alzheimer’s disease (AD), and different polymorphisms have been associated with the disease. A GWAS performed in a population isolate from eastern Canada has found the polymorphism rs11136000 of the CLU gene to be associated with increased risk for AD. For the present work, we used two different cohorts (the “at‐risk” pre‐symptomatic PREVENT‐AD and the symptomatic ROSMAP cohort) with the objective of exploring how the rs11136000 polymorphism is associated with clinical manifestations, biomarkers and neuropathology of AD at different disease stages.MethodIn the PREVENT‐AD cohort, ELISAs were used for Tau, phospho(181) Tau (p‐tau), and Aß CSF levels. Cognition was assessed with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Participants were followed for at least 4 years. In the autopsied‐confirmed ROSMAP cohort, Aß load and NFT density in the cortex were measured with immunocytochemistry, and cognition was assessed with the Mini‐Mental State Examination (MMSE). Participants were followed throughout their adult life, until death.ResultIn the cognitively unimpaired PREVENT‐AD cohort, participants who are APOE4 positive and non‐carriers for the rs11136000 T variant had lower CSF Aß1‐42 (p=0.01) and higher CSF p‐tau (p=0.027) (Fig 1). Additionally, participants who are APOE4 positive and have 2 copies of the CLU rs11136000 T variant display significantly higher coding scores (p=0.003), attention scores (p=0.015) and visuospatial/constructional score (p= 0.026) (Fig 2). However, participants who are APOE4 negative and are homozygous for the rs11136000 T variant have lower semantic fluency score (p=0.001), list recall score (p=0.038) and language score (p=0.007) (fig 2). In the ROSMAP cohort, there was no association of the CLU rs11136000 variant with risk of developing dementia, MMSE scores or Braak or CERAD scores.ConclusionOur results confirm the role of the CLU rs11136000 variant in the pathology of AD, particularly in the pre‐symptomatic phase of the disease when pathology begins to unfold.
Impact of pre‐analytical factors on blood‐based biomarkers of Alzheimer's disease
Authors: Kurz Carolin , Stöckl Laura , Schrurs Isabelle , Suridjan Ivonne , Guersel Selim , Bittner Tobias , Jethwa Alexander , Perneczky Robert 
Published: December 2022

AbstractBackgroundReliable blood‐based biomarkers (BBBMs) are urgently needed to allow for robust, cost‐effective pre‐screening of patients with suspected Alzheimer’s disease (AD) before referral for detailed assessments. We evaluated the effects of storage time and temperature, plastic tube types, and freeze/thaw (F/T) cycles in fresh, never frozen and previously frozen whole blood (WB) and plasma. Effects of anticoagulants and tube transfer were only studied in previously frozen plasma.MethodWB samples from patients with clinically suspected AD were collected in ethylenediaminetetraacetic acid (EDTA) tubes and stored at room temperature (RT) or 4°C for ≤24hrs as WB or plasma. Separated plasma was transferred into polypropylene (PP) tubes to evaluate the effects of tube transfer and F/T cycles, or into low‐density polyethylene (PE‐LD) tubes to assess the effect of tube type. In addition to EDTA, lithium heparin (Li‐Hep) and sodium citrate (NaCit) tubes were used and effects of anticoagulants evaluated. Plasma levels of phosphorylated‐tau (pTau) 217, pTau181, amyloid‐β 1–42 (Aβ42), amyloid‐β 1–40 (Aβ40), apolipoprotein E4 (ApoE4), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NFL) were measured using automated Elecsys® prototype immunoassays (cobas e 601 analyzer; all Roche Diagnostics International Ltd).ResultFor all BBBMs, pre‐analytical effects were comparable between fresh, never frozen and previously frozen samples. All BBBMs were stable for ≤24hrs at 4°C in WB and EDTA plasma; Aβ42, Aβ40, and ApoE4 were unstable if stored for >2hrs at RT. Up to five tube transfers, or two F/T cycles, and both tested plastic tube types were acceptable for all BBBMs. For all BBBMs, except Aβ42 and Aβ40, analyte levels were comparable between EDTA, Li‐Hep, and NaCit tubes. Aβ42 and Aβ40 were most sensitive to pre‐analytical sample handling and the effects could only be partially compensated by the Aβ42/Aβ40 ratio.ConclusionWe provide recommendations for an optimal handling protocol for blood collection and sample handling for analysis of BBBMs for AD based on measurement in fresh samples (Figure): WB and EDTA plasma should be stored at 4°C for ≤24hrs, while storage at RT should be avoided or limited to 2hrs maximum.
Robustness of CSF Aβ42/40 and Aβ42/P‐tau181 to detect AD related outcomes using fully automated immunoassays
Authors: Leuzy Antoine , Mattsson‐Carlgren Niklas , Cullen Nicholas , Stomrud Erik , Palmqvist Sebastian , La Joie Renaud , Iaccarino Leonardo , Zetterberg Henrik , Rabinovici Gil D. , Blennow Kaj , Janelidze Shorena , Hansson Oskar 
Published: December 2022

AbstractBackgroundAn obstacle to the broad implementation of CSF AD biomarkers is the identification of uniform cutoffs and measurement variability that can result in diagnostic uncertainty at the patient level. We aimed to determine the comparability of cut‐offs for CSF immunoassays for Aβ42/Aβ40 and Aβ42/P‐tau181 and to assess the effects of variability in CSF measurements on AD‐related outcomes (Aβ‐PET visual read and progression from MCI to AD dementia).MethodsWe studied 750 participants with/without cognitive impairment (CI) with CSF Aβ42/Aβ40 and Aβ42/P‐tau181 and Aβ‐PET from Swedish BioFINDER (n=172; 85 cognitively unimpaired (CU); 87 with CI), ADNI (n=318; 54 CU, 264 CI), and the UCSF Memory and Aging Center (n=260; 55 CU, 205 CI). Aβ‐PET was visually rated as normal/abnormal. Youden’s index (Aβ‐PET visual read as outcome) was used to identify cut‐offs for Aβ42/Aβ40 and Aβ42/P‐tau181. Using these, we calculated accuracy (percentage of correctly classified individuals). To identify a grey‐zone around cut‐points where there is a risk of misclassification, we calculated longitudinal variability of Aβ42/Aβ40 and Aβ42/P‐tau181 in Aβ‐negative CU individuals and then studied the effects of this variability on biomarker performance when predicting CSF status, Aβ‐PET visual read and MCI‐AD dementia conversion.ResultsSimilar cut‐offs were found for Aβ42/Aβ40 and Aβ42/P‐tau181 across cohorts; accuracies of about 90% were achieved for both measures. Longitudinal variability of Aβ42/Aβ40 and Aβ42/P‐tau181 in Aβ‐negative CU was 11.18% and 19.35%, respectively. Using these values, we estimated the robustness of Aβ42/Aβ40 and Aβ42/P‐tau181 by calculating the percentage of participants with >5% chance of having a different predicted outcome due to measurement variability following two CSF measurements close in time. On average, 8.71% of participants fell within this interval for Aβ42/Aβ40, compared with 4.45% for Aβ42/P‐tau181 using Aβ‐PET status as outcome (Figure 1A). Similar findings were observed using conversion to AD dementia (21.13% vs 13.13%) as outcome (Figure 1B).ConclusionsSimilar cutoffs could be applied to CSF immunoassays for Aβ42/Aβ40 and Aβ42/P‐tau181. Compared to Aβ42/Aβ40, Aβ42/P‐tau181 was more robust to the effects of measurement variability in terms of AD‐related outcomes. These findings suggest that Aβ42/P‐tau181 may be the preferred measure in clinical practice and trials.
Air pollution has a more deleterious effect on Alzheimer’s disease biomarkers in genetic predisposition to larger hippocampal volumes
Authors: Vilor‐Tejedor Natalia , Genius Patricia , Rodríguez‐Fernández Blanca , Minguillón Carolina , Crous‐Bou Marta , Suárez‐Calvet Marc , Milà‐Alomà Marta , Cirach Marta , Nieuwenhuijsen Mark , Sunyer Jordi , Fauria Karine , Kollmorgen Gwendlyn , Suridjan Ivonne , Wild Norbert , Esteller Manel , Zetterberg Henrik , Blennow Kaj , Molinuevo Jose Luis , Guigó Roderic , Navarro Arcadi , Gispert Juan Domingo ,   for the ALFA study
Published: December 2022

AbstractBackgroundGene‐environment interactions are important in understanding Alzheimer’s disease (AD) etiology. Current research is limited, possibly due to weak effects of individual genetic variants. We analysed interaction between genetics of hippocampal volume, environmental exposures and levels of AD biomarkers in cognitively unimpaired individuals at increased risk of AD.MethodA total of 319 cognitively unimpaired, middle‐age participants from the Alzheimer’s and Families (ALFA) study with data for genotyping, environmental exposures, and cerebrospinal fluid (CSF) biomarkers were included. Genome‐wide genotyping was performed using Infinium Neuro Consortium (NeuroChip) Array. Genetic variants that passed a quality control/imputation procedure were used to calculate polygenic risk scores (PRS) using PRSice version 2. Land use regression estimated residential exposure to particulate matter (PM2.5, PM10), and nitrogen dioxide (NO2). NeuroToolKit robust prototype assays and Elecsys® immunoassays (both Roche Diagnostics International Ltd, Rotkreuz, Switzerland) were used to measure CSF biomarkers, and amyloid positivity was defined as amyloid‐beta(Aβ)42/40 ratio <0.071. Associations between PRSs and environmental factors were investigated and estimated using multiple logistic/linear regression models adjusted for age and sex; CSF biomarkers were included as outcomes.ResultPRS‐hippocampal volume (HV)×PM10 and PRS‐HV×NO2 were significantly associated with p‐tau (p = 0.045 and p = 0.025, respectively) (Figure 1). Individuals at high genetic predisposition for larger hippocampal volumes had lower levels of p‐tau at low levels of air pollution compared to individuals at low/null genetic predisposition; as the level of exposure to PM10 and NO2 increased, higher values of p‐tau were observed compared to low‐risk individuals.ConclusionOur results showed that air pollution may have a deleterious effect on biological mechanisms of AD, in cognitively unimpaired individuals with higher genetic liability for larger hippocampal volumes. Further research is needed to elucidate the biological mechanism involved in such associations.
Macrophage Scavenger Receptor 1 in the CSF pre‐symptomatic with a parental history of AD and in the cortex of autopsy‐confirmed Alzheimer’s Disease cases.
Authors: Aumont‐Rodrigue Gabriel , Picard Cynthia , Rosa‐Neto Pedro , Miron Justin , Poirier Judes ,   PREVENT‐AD research Group
Published: December 2022

AbstractBackgroundThe macrophage scavenger receptor 1 (MSR1) also known as SCARA1, is a gene that encodes for a macrophage/microglia cell surface receptor. Its primary function is to mediate the endocytosis of modified (acetylated or oxidized) low density lipoproteins (LDLs)(Frenkel, Wilkinson et al. 2013). Interestingly, MSR1 has been found to bind to soluble β‐amyloid (Aβ) and it is thought that it participates to its clearance via a microglia‐mediated process (PrabhuDas, Baldwin et al. 2017). Using multiple cohorts covering a wide range of brain health stages, MSR1 gene expression and protein level alterations were investigated to map the associations between MSR1 and Alzheimer’s disease (AD) pathophysiology.MethodMSR1 CSF protein levels were assessed in the PREVENT‐AD (PRe‐symptomatic EValuation of Experimental or Novel Treatments for Alzheimer’s Disease) cohort which is composed of subjects with parental history of AD. MSR1 has been measured with a primer extension assay using Olink technology (J. Alz. Dis., In press). ELISA has been used to quantify the MSR1 protein levels in frontal cortex homogenates of 86 brains from the Douglas Bell Canada Brain Bank (DBCBB) whereas MSR1 mRNA prevalence was measured using Gene Chip Clarium D human microarray. All data compilation and statistical analysis has been made using JMP pro 15.1 software.ResultStrong correlations between MSR1 CSF protein levels and CSF AD biomarkers, notably phosphorylated Tau (R2=0.108; p=0.0007) and Aβ42 (R2=0.055; p=0.0175) have been found in the PREVENT‐AD cohort. An APOEε4‐independent correlation was observed between CSF MSR1 and APOE (R2=0.156; p˂0.0001) in these cognitively unaffected subjects. In autopsy‐confirmed cortical homogenates, MSR1 protein levels display negative correlations with both Aβ plaques (R2=0.035; p=0.1768) and neurofibrillary tangles (R2=0.136; p=0.0067). On the other hand, MSR1 mRNA levels of the same samples are not correlated with plaques (R2=0.008; p=0.5255) and tangles (R2=0.009; p=0.4971) density. Studies are underway to contrast MSR1 levels with amyloid‐42, p(181)tau and total tau in the same tissues.ConclusionMSR1 plays a significant role in the pathophysiology of AD and recent evidence suggests that elevated MSR1 protein observed in the early stages of AD are followed by a progressive decline that coincides with the emergence of Tau pathology.
Characterizing progressive speech changes in prodromal‐to‐mild Alzheimer’s disease using natural language processing
Authors: Robin Jessica , Xu Mengdan , Balagopalan Aparna , Novikova Jekaterina , Kahn Laura , Oday Abdi , Hejrati Mohsen , Hashemifar Somaye , Negahdar Mohammadreza , Simpson Bill , Teng Edmond 
Published: December 2022

AbstractBackgroundNovel automated tools for analyzing speech and language may provide new insights into Alzheimer’s disease (AD). Although speech and language changes occur in AD and other neurodegenerative diseases, current clinical assessments to monitor these symptoms can be burdensome and may have limited sensitivity. Through analyses of open‐ended naturalistic speech collected from a standardized clinical interview, we developed a novel measure to characterize progressive speech changes in AD.MethodsWe analyzed Clinical Dementia Rating (CDR) recordings from a subset of 101 participants (58F, 43M, mean age=69 years, SD=7) from the Tauriel trial of semorinemab in prodromal‐to‐mild AD. CDR recordings were collected at the baseline, 6‐month, 12‐month and 18‐month timepoints. Recordings were processed using the Winterlight speech analysis platform which generates >500 acoustic and linguistic features. After controlling for age, sex and level of education, we identified multiple features that had significant linear effects of time (indicating progressive longitudinal change). These speech features were combined into an unweighted composite speech score, which was compared with other clinical endpoints.ResultsThe novel speech composite score included six linguistic features (related to word duration, word frequency, syntactic depth, use of nouns, pronouns and particles) and three acoustic features (related to the power spectrum of the vocal recordings). When compared with clinical endpoints, the speech composite had a similar effect size for detecting longitudinal change (β=0.29) compared to the CDR‐Sum of Boxes (CDR‐SB; β=0.30) and Alzheimer’s Disease Assessment Scale‐Cognitive Subscale (ADAS‐Cog; β=0.22). Notably, it had a significantly greater longitudinal effect size compared to the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS; β=‐0.15, p<0.01) and the language subscales of the ADAS‐Cog measuring word finding difficulty (β=0.12, p<0.01) and spoken language ability (β=0.09, p<0.01).ConclusionsProgressive speech changes are detectable in early AD and measurable via automated language processing tools. Speech composite scores have the potential to be more sensitive measures of disease progression and/or treatment response for speech‐related symptoms in AD that do not contribute to additional patient burden. Further validation is needed to replicate these findings and confirm the clinical and neuropathological relevance of this novel measure.
The fluid biomarker landscape in genetic FTD
Authors: van Swieten John C ,   GENFI consortium
Published: December 2022

AbstractBackgroundThere is an increasing need for the use of fluid biomarkers in clinical management and future therapeutic trials of patients with genetic FTD.MethodSeveral fluid biomarkers have been investigated in the largest longitudinal cohort of patients with genetic FTD (GENFI; n > 1000) associated with mutations in the progranulin (GRN), MAPtau and C9orf72 gene. Concentration changes in neurofilament light and neurofilament high protein (NfL and pNfH), neuronal pentraxin (NPTX2), glial fibrillary acidic protein (GFAP), dipeptides, complement factors and miRNAs have been correlated with disease onset and progression, disease severity and grey matter volume loss in pre‐ and symptomatic carriers. Sequences of biomarker abnormalities were analyzed using discriminative event‐based modelling (DEBM).ResultA number of promising fluid biomarkers have been identified in all or in specific genetic subtypes of FTD, with a specific sequence of biomarker changes over time from pre‐ to symptomatic stage. The next step will bet he development of a multi‐modal prediction tool at individual level, which may improve patient stratification and track the efficacy of therapeutic interventions.ConclusionMajor scientific achievements have been made in fluid biomarker studies of the largest cohort of genetic FTD (GENFI).
Circadian age, chronological age, and Alzheimer’s dementia
Authors: Li Peng , Sun Haoqi , Gao Chenlu , Gao Lei , Yu Lei , Yang Jingyun , Bennett David A , Buchman Aron S , Hu Kun 
Published: December 2022

AbstractBackgroundIn older adults, circadian rhythms show alterations in multiple dimensions with aging and during Alzheimer’s dementia progression. We propose that circadian function may serve as a unique gauge of biological age (i.e., circadian age), and that individuals with greater circadian age than chronological age have increased risk of Alzheimer’s dementia.MethodWe constructed a regression model with chronological age as the predicting target. The model prediction was termed circadian age. A softplus activation function was used to ensure positivity. The model was optimized to minimize the mean‐squared prediction error while penalizing the covariance between chronological age and prediction error. Cosinor analysis, nonparametric analysis, uniform phase empirical mode decomposition, and detrended fluctuation analysis were performed on baseline actigraphy data of 882 participants (age: 80.1±7.3; female/male: 692/190) from the Rush Memory and Aging Project who were cognitively intact and were not taking sleep medications. These analyses resulted in 23 features for circadian daily activity patterns as model inputs. The optimal model was trained through cross‐validation for the penalization parameter and applied to follow‐up actigraphy data. We compared circadian age among participants at different cognitive stages, evaluated the longitudinal change of circadian age, and examined the association of circadian age with incident Alzheimer’s dementia.ResultChronological age explained 24.8% of the variance in circadian age. At analytical baseline, participants with Alzheimer’s dementia had significantly greater circadian–chronological age deviation (CCD) than cognitively normal participants (2.98±1.43 vs. ‐0.13±0.42 years, p=0.04). For each 1‐year increase in chronological age, circadian age increased by 1.05±0.06 years (p<0.001), suggesting accelerated circadian aging. Among baseline cognitively normal participants, greater CCD was associated with an increased risk of Alzheimer’s dementia independent from chronological age, sex, total daily activity, sleep fragmentation, vascular disease and risk factors, and depressive symptoms. For a 10‐year increase in CCD, the hazard ratio was 1.23 (95% CI: 1.06‐1.42).ConclusionCircadian daily patterns can be integrated to predict chronological age. Older circadian age than chronological age is an independent risk factor for Alzheimer’s dementia. Future work should refine the determination of health status for training dataset and examine whether circadian age links with endogenous circadian function.
Alzheimer’s Disease Patients, Especially ApoE4 Carriers, Have Significantly Reduced High‐density Lipoprotein Particle Size Revealed by Negative‐stained Transmission Electron Microscopy
Authors: Zheng Jack Jingyuan , Hong Brian V. , Agus Joanne , Guo Fei , Lebrilla Carlito B. , Jin Lee‐Way , Maezawa Izumi , Harvey Danielle J. , Zivkovic Angela M. 
Published: December 2022

AbstractBackgroundHigh density lipoproteins (HDL) are protective against a wide array of diseases and have recently also been found to be associated with reduced risk of Alzheimer’s Disease (AD). However, the amount of circulating HDL‐cholesterol does not correlate closely with function, explaining only about 40% of the variance in HDL’s ability to perform its primary role of cholesterol efflux. HDL particle composition, size and structure are important determinants of functional capacity, however little is known about HDL particle physical characteristics in AD patients, in particular whether there are apolipoprotein E (APOE) genotype‐dependent effects.MethodPlasma samples from a total of 172 APOE genotyped patients, n = 37 ApoE3/E3 and n = 34 ApoE3/E4 with diagnosed AD, n = 22 ApoE3/E3 and n = 18 ApoE3/E4 with diagnosed MCI, and n = 44 ApoE/E3 and n = 39 ApoE3/E4 age‐ and sex‐matched non‐AD controls were obtained from the UC Davis Alzheimer’s Disease Research Center biobank. HDL particles were isolated from plasma by sequential density‐adjusted ultracentrifugation followed by size‐exclusion chromatography. The size of HDL from each patient was characterized using negative‐stained transmission electron microscopy (NS‐TEM) followed by computational particle size analysis.ResultOn average, 34 TEM micrographs were obtained, and over 33,000 individual particles were selected and analyzed from each HDL sample using pre‐determined image quality and image selection criteria. The average particle size were compared between AD patients and controls stratified by APOE genotype. The mean particle diameter of HDL from MCI and AD patients was smaller compared to the control group (8.28 +/‐ 0.587, 8.30 +/‐ 0.662 vs. 8.84 +/‐ 0.587, respectively). The differences remained statistically significant when stratified by genotype. Both MCI and AD group had smaller HDL particle size compared to the control group in the ApoE3/E3 genotype (8.37 +/‐ 0.452, 8.48 +/‐ 0.613 vs. 8.90 +/‐ 0.602, respectively), and in the ApoE3/E4 genotype (8.17 +/‐ 0.707, 8.11 +/‐ 0.667 vs. 8.80 +/‐ 0.582, respectively).ConclusionThese results reveal that patients with Alzheimer’s dementia and mild cognitive impairment have disrupted HDL particle distribution, with smaller average HDL particle size, highlighting the need for further studies of lipoprotein metabolism in AD.