bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Alzheimer Disease Plasma Biomarker pTau‐181 in Individuals of Diverse Admixed Ancestral Backgrounds
Authors: Grimmer Timo , Rajabli Farid , Garcia‐Serje Catherine , Arvizu Jamie , Larkin‐Gero Emma , Whitehead Patrice L. , Hamilton‐Nelson Kara L. , Adams Larry D. , Contreras Maricarmen , Sanchez Jose Javier , Tejada Sergio , Mena Pedro Ramon , Starks Takiyah D. , Cornejo‐Olivas Mario , Illanes‐Manrique Maryenela , Silva‐Vergara Concepcion , Cuccaro Michael L. , Vance Jeffery M. , Feliciano‐Astacio Briseida E. , Byrd Goldie S. , Beecham Gary W. , Haines Jonathan L. , Pericak‐Vance Margaret A. 
Published: December 2022

AbstractBackgroundPlasma proteins, including phosphorylated threonine‐181 of Tau (pTau181) are used as biomarkers for differential diagnosis and preclinical detection of Alzheimer disease (AD). However, observation and measurement of these biomarkers are mostly from individuals of non‐Hispanic, European ancestry. Given differences in AD risk, generalizability of these findings is not assured in individuals of diverse ancestry. This study evaluates the utility of plasma pTau181 in discriminating clinically diagnosed AD from cognitively intact, age‐matched controls in ancestrally diverse, admixed cohorts.MethodWe measured pTau181 with Simoa chemistry using the pTau181 AdvantageV2 on the Quanterix HD‐X. Our cohorts consisted of 642 African Americans (162 AD and 480 controls), 906 Puerto Ricans (385 AD and 521 controls), 149 Peruvians (49 AD and 100 controls), 60 Cubans (26 AD and 34 controls), 246 individuals of non‐Hispanic, European ancestry (22 AD and 224 controls), and 58 autopsy confirmed AD cases of European ancestry with plasma isolated from EDTA blood tubes. Samples were randomized, measurements performed in duplicate, and non‐parametric Kruskal‐Wallis tests used to detect differences in biomarker concentrations between cases and controls in each cohort.ResultMedian pTau levels in cases was higher than controls in all cohorts assayed: African Americans (2.30±1.14pg/mL vs 1.15±2.99pg/mL, pcorr=2.0x10‐27); Puerto Ricans (2.33±1.82pg/mL vs 1.44±1.21pg/mL, pcorr=8.2x10‐32); Peruvians (2.63±1.64pg/mL vs 2.13±1.42pg/mL, pcorr=0.02); Cubans (2.09±1.16pg/mL vs 1.35±0.67pg/mL, pcorr=0.02); and European ancestry (2.40pg/mL±0.78pg/mL vs 1.54pg/mL ±1.44pg/mL, pcorr=0.02). The pTau levels in the autopsy confirmed cases (2.96±2.29 pg/mL) were not significantly higher than AD cases in the other ancestries.ConclusionThis study suggests pTau181 as a biomarker is generalizable across genetic ancestries, though potential sex and age effects remain to be determined. Ultimately, combining genomic and biomarker data, including pTau181 and other AD related plasma biomarkers such as Aβ40 and Aβ42, from diverse individuals will increase understanding of genetic risk and refine clinical diagnoses in individuals of diverse ancestries.
Brain region‐specific metabolic signatures of Alzheimer’s disease
Authors: Batra Richa , Krumsiek Jan , Wang Xue , Allen Mariet , Wörheide Maria A. , Blach Colette , Bennett David A , Kastenmüller Gabi , Arnold Matthias , Ertekin‐Taner Nilufer , Kaddurah‐Daouk Rima 
Published: December 2022

AbstractBackgroundMetabolic dysregulation is one of the hallmarks of Alzheimer’s disease (AD). Alterations in metabolism have been associated with AD‐related comorbidities, cognitive decline, and AD brain pathology. Brain regions are differentially affected with AD neuropathology and exhibit metabolic heterogeneity. Therefore, to build a more comprehensive picture of metabolic impact of AD, region‐specific AD‐associated metabolic changes need to be determined.MethodWe profiled 344 brain samples from the Mayo Clinic brain bank using Metabolon’s untargeted metabolomics platform, covering 182 samples from the cerebellum (CER) and 162 samples from the temporal cortex (TCX). Generalized linear models were used to assess the association of metabolic profiles with AD. Models included confounder correction for age at death, sex, and number of APOE‐ε4 alleles. To extend this study to four more brain regions, we included results from previously published brain metabolomics studies based on samples from three independent cohorts, including dorsolateral prefrontal cortex (DLPFC) from ROS/MAP, parietal lobe (PTL) from Washington University School of Medicine (WUSM), inferior temporal gyrus (ITG) and middle frontal gyrus (MFG) from Baltimore Longitudinal Study of Aging (BLSA).ResultIn the Mayo cohort, a total of 190 out of the 658 metabolites were significantly associated with AD. Out of the 190, 127 metabolites associated only in the CER region, 37 metabolites associated only in the TCX region, and 26 metabolites were associated in both brain regions. There were no metabolites commonly regulated in all the 6 brain regions under investigation. DLPFC and CER had the highest overlap of 70 metabolites, followed by DLPFC and PTL with 64 metabolites, and CER and PTL with 47 metabolites. For functional interpretation of our findings, each metabolite was further categorized with a sub‐pathway annotation provided by Metabolon. 3 of the 88 pathways including methionine cycle, phospholipid metabolism, and glutathione metabolism, were commonly regulated in the six brain regions under investigation.ConclusionWe present a first global perspective on AD‐associated metabolic alterations across six brain regions. This study will pave the way to fill the gap in our understanding of region‐specific metabolic deregulations associated with AD pathophysiology.
Evaluation of A Direct Regional Reprojection Reconstruction Method to Improve Quantitation of Amyloid and Tau PET Images using 3D Printed Phantoms
Authors: Meehan Emily , Minhas Davneet S , Gogola Alexandra , Ghodadra Anish , Cohen Ann D , Tudorascu Dana L , Lopresti Brian J , Aizenstein Howard J , Kendro Steve , Mason Neale S , Klunk William E , Laymon Charles M 
Published: December 2022

AbstractBackgroundImage reconstruction and partial volume correction (PVC) techniques designed to account for the limited spatial resolution of PET are used inconsistently in amyloid and tau PET imaging, likely due to a lack of characterization of the techniques and their unknown effect on reliability. In this study, we aimed to test the accuracy and reliability of a variety of reconstruction and image‐based correction methods using 3D‐printed PET phantoms.MethodTwo phantoms modeled on the lateral temporal brain region of two human subjects (67‐year‐old male and 69‐year‐old female, both cognitively normal) were created using 3D‐printing technology (Formlabs Form 3). The phantoms had six thin‐walled chambers corresponding to inferior, middle, and superior temporal grey matter (GM) and white matter (WM). Phantoms were scanned (Siemens Biograph mCT) multiple times as chambers were filled with F‐18 solution to mimic various distributions of activity seen in amyloid‐positive, amyloid‐negative, or tau‐positive subjects. 16 scans were completed in total. Data from each 3‐hour scan were binned into 16 statistically equivalent frames and reconstructed with three techniques: FBP, OSEM, and TrueX, a manufacturer‐supplied method including point spread function modeling (Figure 1). Two image‐based correction techniques were also applied and evaluated: Geometric Mean Transfer Matrix (GTM) PVC and a novel Direct Regional Reprojection Reconstruction (DRRR) method, an iterative algorithm that reprojects images directly into regions‐of‐interest. To evaluate accuracy, fractional error of each region (F = M/T ‐ 1, where M is the measured regional value averaged over 16 frames and T is the true regional value) was calculated. To evaluate reliability, the coefficient of variation (CV) of M over all 16 frames in each scan was assessed for every region of the phantoms.ResultFractional errors (Figure 2) and CVs (Figure 3) are shown for each reconstruction and image‐based correction method. Uncorrected TrueX fractional error was not apparently improved relative to uncorrected FBP and OSEM fractional error. For all reconstructions, GTM and DRRR improved accuracy relative to uncorrected. For the FBP and OSEM reconstructions, GTM was more accurate than DRRR, but DRRR was more reliable than GTM.ConclusionDRRR is a promising novel method for PET quantification that improves accuracy without compromising reliability.
Higher cortical myelin is associated with worse performance on cognitive tests: Findings from the Alzheimer’s Disease Connectome Project
Authors: Kohli Akshay , Kecskemeti Steven R , Yang Kao Lee , Oh Jennifer M. , Nair Veena A. , Pasquesi Mary‐Elizabeth , Okonkwo Ozioma C. , Alexander Andrew L , Prabhakaran Vivek , Li Shi‐Jiang , Bendlin Barbara B. 
Published: December 2022

AbstractBackgroundBrain myelin is known to play an important role in maintaining optimal neuronal function, with deficits in myelin leading to worse performance on cognitive tests. The extent to which cortex‐specific myelin is associated with other cognitive domains, or is impacted by disease processes such as Alzheimer’s disease (AD), is unknown. Here we leverage MPnRAGE‐derived quantitative R1 (Kecskemeti et al., 2016; 2018), a metric sensitive to brain myelin, to assess the role of intracortical myelin in performance on tests of executive function (exec_func), working memory (working_mem), and processing speed (process_speed) in older adults who ranged from cognitively unimpaired to those with dementia.Method143 older adults (N=75 cognitively unimpaired, N=44 mild cognitive impairment, N=24 dementia) enrolled in the Alzheimer’s Disease Connectome Project underwent T1‐weighted (T1w) MPnRAGE MRI with motion‐correction and testing via the NIH Toolbox Cognitive Battery. Inherently registered quantitative R1 maps and T1w images were reconstructed at 1mm isotropic resolution. The image processing pipeline and composite regions of interest (ROIs) used for analysis can be viewed in Figure 1. Uncorrected standard scores were computed by the NIH Toolbox for each measure of exec_func (dimensional change card sort), working_mem (list sorting), and process_speed (pattern comparison). Multiple linear regression models were employed in R with test scores as the dependent variable, regional R1 as the predictor of interest, and age, sex, and education as covariates.ResultHigher R1 was associated with worse exec_func in regions that are affected in AD, including posterior cingulate (ß = ‐62.47, t(1,138) = ‐2.42, p = 0.017) and temporal cortices(ß = ‐123.05, t(1,138) = ‐2.77, p = 0.0064) ROIs. Additionally, higher R1 in temporal cortices was associated with worse working_mem (ß = ‐158.16, t(1,133) = ‐2.84, p = 0.0053) (Figure 2). There were no significant associations between process_speed and regional cortical R1.ConclusionUnexpectedly, higher regional cortical myelin (as indexed by R1) was associated with worse exec_func and working_mem, suggesting higher R1 may be indicative of a regional pathologic process. Future work will test the interactive relationships between amyloid and/or tau pathology and cortical myelin on cognitive performance.
GENE REPLACEMENT OF MUTANT PRESENILIN1 NORMALIZES GAMMA‐SECRETASE FUNCTION IN MODELS OF AUTOSOMAL DOMINANT ALZHEIMER'S DISEASE
Authors: Moore Ben David , Schaeffer Eric 
Published: December 2022

AbstractBackgroundParos Bio is developing an AAV gene therapy for the treatment of Autosomal Dominant Alzheimer’s Disease (ADAD), an early onset form of AD (onset at <65 years of age). ADAD is mainly caused by mutations in the presenilin 1 (PSEN1) gene, which encodes the catalytic subunit of γ‐secretase complex and is responsible for the cleavage of amyloid precursor protein (APP). This cleavage produces Aβ of varying lengths, with longer peptides like Aβ42 being more prone to aggregation than shorter peptides such as Aβ40. Of the >150 distinct, 100% penetrant PSEN1 mutations associated with ADAD, most lead to a partial or nearly complete loss of g‐secretase function, resulting in decreased production of Aβ40 and an increase in the ratio of Aβ42:Aβ40. Aggregation of Aβ peptides into amyloid plaques in the brain is a hallmark of ADAD.MethodParos Bio is employing a gene replacement approach to normalize g‐secretase function. Using an AAV vector, Paros has successfully expressed a functional copy of PSEN1 in mouse and patient‐derived cellular models of presenilin dysfunction.ResultWe have demonstrated that introduction of wildtype PSEN1 in mouse models and patient‐derived cell lines effectively normalizes g‐secretase function. Our AAV vector can be broadly distributed in brain tissue and provides attractive expression of PSEN1.ConclusionParos Bio has developed a vector that enables broad expression of WT PSEN1 and is capable of normalizing g‐secretase function in in vitro and in vivo models of ADAD.
Harmonizing machine learning imaging biomarkers – CDESH and the case for harmonization in both MR image and low‐dimensional (scalar) output space
Authors: Gunter Jeffrey L. , Cogswell Petrice M , Senjem Matthew L. , Kantarci Kejal , Knopman David S. , Petersen Ronald C. , Graff‐Radford Neill R. , Graff‐Radford Jonathan , Jack Clifford R. 
Published: December 2022

AbstractBackgroundIn 2018 we presented the Computational DESH (CDESH) metric (DOI:10.1016/j.nicl.2018.11.015), a machine learning measure of abnormal CSF space patterns commonly observed on MRI in Disproportionately Enlarged Subarachnoid‐space Hydrocephalus (DESH‐type) NPH. We have shown that CDESH positive individuals often have discordant CSF and PET amyloid measures (DOI:10.1016/j.jalz.2019.06.4921). Positive CDESH scores are predictive of cognitive decline (DOI:10.1016/j.neuroimage.2021.117899, DOI: 10.1212/WNL.0000000000008616). The score is calculated from regional CSF volumes in a sulcal atlas and within the ventricles using a support vector machine (SVM). The Mayo Clinic Study of Aging (MCSA) changed scanner platforms (GE to Siemens) and T1‐weighted image resolution (1.2mm x 1.05mm x 1.05mm to 0.8mm isotropic) in 2017. We refer to these as “isotropic” or “anisotropic” scans. Our objective was to assess the dependence of a machine learning method (specifically CDESH) to image input variation and, if necessary, determine what needed corrections.MethodAll data considered is from the MCSA or Mayo Clinic ADRC. The SVM was trained on anisotropic images with laboriously labelled ground truth. We resampled the isotropic data from a crossover study (N=112, typically scanned same‐day with both platforms/resolutions) to match the anisotropic resolution. Two approaches to correction were evaluated (Figure 1). In Figure 2 we compare of the score with and without correction cross‐sectionally in 998 MCSA participants. In Figure 3 we present longitudinal series from 23 participants with multiple scans using the isotropic resolution protocol and at least one prior anisotropic image.ResultsComparisons of data from the crossover study are presented in Figure 1. Matching voxel resolution to the data used to train the SVM is critical and a subsequent mild linear score adjustment may be warranted. Cross‐sectional comparisons (Figure 2) confirm improvement matching voxel resolution with a possible mild linear score adjustment. After matching voxel resolution CDESH score trajectories (Figure 3) are markedly more stable across this scanner/protocol change.ConclusionThe SVM‐based CDESH score is sensitive to voxel resolution. Corrections are needed in image processing and possibly in the scalar output score to achieve stability across protocol and scanner changes. The resulting correction supports coherent long timeseries data and longitudinal extension of previous work.
Characterization of a diverse Frontotemporal Dementia cohort, enriched for Caribbean Hispanic patients.
Authors: Martinez Anisley , Rajabli Farid , Gu Esther , Tejada Sergio , Acosta Heriberto , Baumel Bernard , Camargo Christian J , Sun Xiaoyan , Vance Jeffery M. , Cuccaro Michael L. , Pericak‐Vance Margaret A. , Nuytemans Karen 
Published: December 2022

AbstractBackgroundThe vast majority of biomedical data currently available for any disease is derived from studies in non‐Hispanic white (NHW) populations. Specifically, clinical information, genetic factors as well as biomarkers for frontotemporal dementia (FTD) have been studied predominantly in those NHW populations. To increase representation in biomedical research, we set out to enroll and characterize a diverse FTD patient cohort enriched for Caribbean Hispanic patients.MethodOur current cohort consists of 89 FTD patients (30% NHW, 67% Hispanic), with continuing enrollment from the University of Miami Hospital Neurology Department in Miami, FL and the Caribbean Center for the Study of Memory and Cognition in San Juan, PR. All patients were evaluated using NACC approved Uniform DataSet (UDS) or equivalent in their preferred language. For ∼65% of the cohort we also completed the NACC FTD module forms. We generated genotyping data (Illumina GDA+Neurobooster array) as well as whole genome sequencing and plasma biomarker data (Quanterix Simoa Neuroplex‐3; Ab40, Ab42, and total tau) for a subset of the cohort.ResultInitial genetic analyses showed none of the Hispanic patients are carriers of known FTD mutations originally identified in NHW patients, including the C9orf72 repeat expansion and reported pathogenic variants in MAPT or GRN. We did not identify a significant difference in age‐at‐onset or Clinical Dementia Rating scores at time of enrollment between NHW and Hispanic patients. Additionally, biomarker data on Aβ40/Aβ42 ratio and total tau levels in a subset of 22 FTD patients (∼12/10 Hispanic/NHW) did not show significantly different levels between patients of both ethnicities.ConclusionGenetic analyses of FTD in underrepresented population groups is necessary as genetic information from research in NHW is not always generalizable across race/ethnicity. We are currently working to expand our efforts to include identification of novel genetic risk factors for FTD in the Hispanic patients using whole genome sequencing, full evaluation of the Neuroplex as well as p‐tau181 and NfL biomarkers in the complete cohort and comparison of clinical presentations between ethnicities. The biomedical characterization of FTD across race/ethnicity will help the understanding of disease mechanisms in all patients ultimately preventing further health disparities.
The Collaboration and Harmonization of Digital Biomarkers for Alzheimer’s Research
Authors: Beattie Zachary T , Gothard Sarah , Barnes Lisa L. , Calloway Shayla , Gonzales Mitzi M , Jones Brian D , Kautz Tiffany F , Levey Allan I. , Mathews Julia J , Mulavelil Rachel , Phelps Brenna , Rosen Howard J. , Rozga Agata , Seshadri Sudha , Staffaroni Adam M. , Wasserman Dara K , Wise Amy B , Kaye Jeffrey A 
Published: December 2022

AbstractBackgroundAmong prominent unmet needs of the Alzheimer’s disease and related dementia (ADRD) research community is the ability to leverage opportunities to improve the assessments of persons with and at risk for ADRD. This vision can be realized by providing the tools and infrastructure to transform dementia assessment using remote sensing and digital technologies, pervasive computing, and wireless communications, all in concert with high dimensional data analytics. The Collaborative Aging Research using Technology (CART) initiative (carthome.org), a non‐proprietary, sharable end‐to‐end system for capturing and handling diverse kinds of digital data has been developed. The CART technology platform offers the opportunity to bring new assessment methodology and data types to NIA Alzheimer’s Disease Research Centers (ADRC) and related centers and transform the clinical research enterprise. Herein we report on progress in capturing digital data across multiple ADRC’s.MethodParticipants were recruited from affiliated studies at five NIA ADRC’s (Digital Technology Core at Oregon Health & Science University, Minority Aging Research Study at Rush University, Cognitive Empowerment Program at Emory University and Georgia Institute of Technology, ALLFTD study at University of California San Francisco, and a pilot study of Mexican Americans at University of Texas Health Science Center at San Antonio). Field technicians at each center installed the CART technology platform in the home of each participant.ResultA total of 195 research participants have been enrolled across the 5 centers and followed for a median of 19 months (range 1‐46). A summary of the center cohorts is provided in the table. The flexibility of the platform and its components has allowed it to successfully be adapted for research in each of these studies with diverse cohorts, use cases, and research aims. Attrition due to technology concerns has been very low (0.5%).ConclusionDigital biomarker and related data can be readily captured across diverse cohorts, research teams, and settings using a common platform. The largely passive, continuous, and objective data generated with this approach promises to improve the opportunity to create more quantitative and ecologically valid measurements for ADRD phenotypes within the ADRD research community and related research settings.
Exploring Inflammasome/Cytokine/Insulin cascade as converging landscape for AD, Schizophrenia(SCHIZO), and COVID‐19 syndrome: synthesis of evidence and Post‐hoc analysis of Ginsans‐115 RCT in treatment‐resistant‐schizophrenia
Authors: Carriere Autumn 
Published: December 2022

AbstractBackgroundAmid COVID‐19 pandemic, issue is raised: 1) whether AD and Very‐late‐onset‐schizophrenia‐like psychosis(VLOSL): “dementia praecox” have higher COVID‐19 risk;2)whether dysregulated cross‐talk of immunity and inflammation, in Inflammasome‐Cytokine‐insulin signaling cascade (IFCI) is the missing link for AD, VLOSL and COVID‐19.MethodOur objective is : 1) to conduct Pub‐med search for crucial role of inflammasome‐cytokine‐insulin cascade(IFCI) in AD, VLOSL and COVID‐10 burden; 2a)to examine using RCT data whether in schizophrenia, cognitive impairment correlates with insulin resistance(IR) and cardio‐metabolic risks (CMR);2b)whether Panax Ginseng, as prime executioner of IFCI, modifies IR,CMR in TRS.ResultIn Part1: our Pubmed search concludes Dementia syndrome carries higher mortality risk. A meta‐analysis of 634,338 COVID‐19 patients from 16 studies reveals that schizophrenia, and dementia, significantly increased risk of COVID‐19 mortality and severity. Cardio‐metabolic risk factors modify the link. A large Swedish cohort study and systematic review of 17studies found evidence of VLOSL carries higher risk of dementia. Aberrant IFCI correlated with COVID‐19 severity, but very few data is available for Long‐COVID‐19 syndrome. Effect sizes cannot be calculated due to sample heterogeneity. In Part 2: post‐hoc analysis of Ginsana‐115 (Boehringer‐Ingelheim‐Pharmaton,Switzerland) of 8‐week placebo‐controlled parallel group design in TRS subjects . Log‐IR(insulin resistance) scores significantly correlated with spatial processing (p = 0.017). Framingham‐Risk‐score correlated inversely with visual perception p = 0.040) and spatial processing (p = 0.029) and neurocognitive index (p = 0.090). Systolic blood pressure (sBP) correlated significantly and inversely with visual perception (p = 0.032),speed (p = 0.010),and spatial processing (p = 0.034), HDL correlated with memory score:p = 0.008. Brief‐Psychiatric‐Rating‐Scale:BPRS correlated significantly with executive reasoning (p = 0.047),memory (p = 0.021), and mental inflexibility (p = 0.026). Ginsana‐115 at 100‐mg/200‐mg significantly reduced FRS by 24.1% compared with 16.1%(P<0.05) and systolic blood pressure (P<0.05) and significantly improved lipid profile in raising HDL and lowering LDL. Ginsana‐115 : 100 mg and 200 mg oral dosage, significantly improved negative symptom of apathy akin to AD.ConclusionInflammasome‐Cytokine‐Insulin signaling (IFCI) appears to be the heuristic model integrating COVID‐19 syndrome, late‐onset schizophrenia overlapping with AD. Longitudinal studies are warranted to validate IFCI as the prime driver. The positive findings of Ginsana‐115 in TRS highlight the therapeutic Pandora box of Diet, drug leads and Exercise targeting specifically the IFCI landscape in COVID‐19 syndrome, AD and VLOSL.