bluuebunny/crossref_metadata_2025_split huggingface dataset:
Frequency of repetitive head impacts and influence on clinical variability among male patients with Alzheimer’s disease and frontotemporal dementia
Authors: Asken Breton M. , Tanner Jeremy A. , Soleimani‐Meigooni David N. , Knudtson Marguerite V. , Grinberg Lea T. , Miller Bruce L , Kramer Joel H. , Mez Jesse B. , Alosco Michael L , Rabinovici Gil D. 
Published: December 2023

AbstractBackgroundRepetitive head impacts (RHI) occur routinely in sports like American football (AmFootball) and are the most well‐established risk factor for chronic traumatic encephalopathy, a neurodegenerative tauopathy. However, RHI is not routinely evaluated in older adults with other suspected neurodegenerative diseases. The prevalence of RHI among older adults with neurodegenerative diseases and the influence on clinical symptoms is unknown.MethodsRHI was defined by AmFootball participation and analyzed based on frequency of any and “substantial” exposure (> 4 years). The Boston University Head Impact Exposure Assessment was administered to 195 older adult males at the UCSF Memory and Aging Center. Of these 106 (54%) were clinically normal (CN) participants in the Brain Aging Network for Cognitive Health (BRANCH) study and 89 (46%) were cognitively impaired participants from the Alzheimer’s Disease Research Center. Diagnostic groups included AD‐related phenotypes (“clinAD”; amnestic‐predominant MCI/dementia, logopenic PPA; N = 26) and frontotemporal dementia spectrum conditions (“FTD”; behavioral variant FTD, semantic PPA, nonfluent PPA; N = 46). Our aims were: 1) investigate frequency of prior RHI between diagnostic groups (chi square), 2) compare age of symptom onset between participants with and without prior RHI (ANOVA), and 3) evaluate associations between RHI and cognition within the largest single diagnostic group (bvFTD N = 20; ANCOVA adjusted for age and education). Cohen’s d effect sizes are reported.ResultsMales with clinAD (27%; χ2 = 8.3, p = .009; d = 0.53) and FTD (21%; χ2 = 5.6, p = .02, d = 0.40) were more likely than CN (7%) to have had substantial prior RHI. Prior RHI was associated with younger age of symptom onset (62.1±7.6 vs. 56.7±7.7 years old; p = .001, d = 0.69). This effect was stronger within clinAD (63.1±7.2 vs. 53.3±7.5; d = 1.3) than FTD (60.1±7.0 vs. 55.9±6.0; d = 0.54). In participants with bvFTD, those with prior RHI scored significantly worse on memory testing (w‐scores ‐2.6±1.1 vs. ‐1.1±1.2, p = .02, d = 1.4).ConclusionsRHI through AmFootball is more common in AD and FTD than healthy controls. Prior RHI may contribute to variability in age of symptom onset in both AD and FTD. Exposure to RHI may also partly explain why some participants with bvFTD, a classically nonamnestic syndrome, develop memory decline. Prior RHI should be routinely evaluated in neurodegenerative disease workups.
Building Stakeholder Consensus Regarding Disclosure of Individual Research Results in ADRD Research: A Delphi Study Protocol
Authors: Sankary Lauren R , Zelinsky Megan , Lerner Alan J. , Martinez Kathryn , Miller Justin B , Leverenz James B 
Published: December 2023

AbstractBackgroundInformed decisions to enroll in clinical investigations of Alzheimer’s disease and related dementias (ADRD) require careful consideration of complex risks and uncertain benefits. Decisions regarding scope of research participation and whether to receive information about biomarker status are complicated by lack of scientific consensus regarding biomarkers as surrogate end points for Alzheimer’s disease. This Delphi protocol aims to establish stakeholder consensus regarding the content and features of ethically optimal informed consent support for ADRD research.MethodThis consensus‐building Delphi protocol consists of three rounds of online surveys conducted with three stakeholder groups: Alzheimer’s disease research experts (including ethicists, research oversight specialists, and clinical trialists), Alzheimer’s disease research participants, and study partners of individuals enrolled in ADRD research. Participants will be administered questionnaires developed from a synthesis of researcher‐ and participant‐endorsed decisional needs identified in published literature and a decisional needs assessment conducted with support from an Alzheimer’s Association Research Grant. Participants will also be asked their views on the design, content, and implementation of a decision support tool. ≥70% agreement will be required to achieve consensus. Response rates, level of agreement, medians, interquartile ranges, and group rankings will be analyzed. Following each round of data collection, our research team will undertake qualitative content analysis of open‐ended responses and forum interactions.ResultThis protocol will develop consensus regarding priorities for decision support for ADRD research participants and the key features and content of ethically optimal informed consent support interventions. The Delphi technique is appropriate to develop consensus between diverse stakeholders because of its ability to offer anonymity to other participants and minimize bias.ConclusionFindings will contribute to the development of a digital health research infrastructure that is inclusive of diverse individuals and attentive to the needs of cognitively vulnerable patient populations and their caregivers.
Predicting of β‐amyloid Positivity Using Integer‐based Risk Scores with Blood‐based Biomarkers
Authors: Petersen Kellen K. , Nallapu Bhargav Teja , Grober Ellen , Lipton Richard B. , Davatzikos Christos , Ezzati Ali 
Published: December 2023

AbstractBackgroundβ‐amyloid (Aβ), a pathologic hallmark of Alzheimer’s disease (AD) is the target of recently FDA‐approved drugs. In trials and in practice, identifying individuals likely to be β‐amyloid positive (Aβ+) with accessible and affordable tests will be increasingly important. Blood‐based biomarkers (BBMs) have shown early promise in determining amyloid status. We aimed to develop machine learning‐based integer risk scores using BBMs and other accessible measures to predict Aβ positivity by PET in older, non‐demented (cognitively unimpaired or mild cognitive impairment) adults.MethodsWe used data from 722 individuals (72.1 ± 7.0 years old) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to develop integer risk scores for predicting Aβ positivity. The sample was divided into training (75%) and test (25%) sets. Variables were categorized as demographics (D: age, sex, and education), genetic information (G: APOE4 status), cognitive measures (C: ADAS‐Cog‐13 and MMSE), and plasma biomarkers of p‐Tau181(T) and neurofilament light (N: NfL). Feature‐sets were formed as hierarchically constructed combinations of these categorized variables (see Figure 1). Using the AutoScore algorithm, variables were ordered according to their Random Forest Gini Index and were iteratively included in the construction of logistic regression‐derived risk score models. Variables were included based on increases in Area Under the ROC Curves (AUCs).ResultsFour models were developed based on four feature‐sets. All models utilized age and APOE4 status and, when considered, all models retained ADAS‐Cog‐13, p‐Tau, and NfL. The best performing model corresponded to the DGCTN feature‐set with performance on the dedicated test set of AUC = 0.810 (C.I.: 0.745‐0.876). Using the DGCTN model on the test set, 97% of individuals with scores in the top quartile of possible risk score points were correctly identified as Aβ+.ConclusionsWe developed risk score models utilizing accessible and affordable measures to predict Aβ positivity. Plasma biomarkers improve performance of risk scores indicating their value. Applications include screening in clinical settings for therapeutic care and enrichment of clinical trials. These data can be used to optimize the efficient use of PET in determining eligibility for clinical trials and amyloid targeted therapies in practice.
Cross‐sectional investigation of synaptic markers Neurogranin and BACE1 in CSF from the AIBL study
Authors: Fowler Christopher J , Stoops Erik , Vanmechelen Eugeen , Vanbrabant Jeroen , Dewit Nele , Mauroo Kimberley , Rowe Christopher C , Fripp Jurgen , Li Qiao‐Xin , Bourgeat Pierrick , Collins Steven J , Martins Ralph N , Masters Colin L , Maruff Paul , Vanderstichele Hugo Marcel , Doecke James D 
Published: December 2023

AbstractBackgroundSynaptic disfunction is a feature of Alzheimer’s disease. Recent studies show both pre‐ and post‐synaptic termini proteins change in concentration in the CSF across the A/T/N framework. Here we investigate BACE1, neurogranin (Ng) and alpha‐synuclein, along with total‐tau (t‐tau) and amyloid‐β 1‐42 (Aβ42), in relation to PET‐amyloid status.MethodParticipants (n = 105) with CSF and matching PET‐amyloid scans from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were analysed for CSF synaptic markers BACE1, Ng and alpha‐synuclein using commercially available antibody assays (EUROIMMUN). BACE1 used ADx401 (5G7) and ADx402 (10B8) antibodies, Neurogranin trunc p75 used monoclonal ADx403 (ADxNGCI2) and ADx451 (ADxNGCT1) antibodies, and alpha‐synuclein used ADx301 and ADx302 antibodies. Total‐tau and Aβ42 were measured using the Roche Elecsys®. PET‐amyloid status was defined using a Centiloid of <25 as negative, and 25 or greater positive.ResultCross‐sectional changes in biomarker values between the PET‐amyloid negative and positive groups were seen for Ng (p<0.05), but not for BACE1 or alpha‐syn. The ratio of Ng/BACE1 improved separation between groups (p<0.001). Total‐tau displayed the greatest differentiation of a single biomarker (p = 2.7×10−10) and this separation was improved using a ratio of t‐tau/BACE1 (p = 3.2×10−12). For predicting PET‐amyloid status (adjusting for age, APOE e4 and gender), t‐tau (AUC: 0.87 [95%CI: 0.80‐0.95]) was slightly improved using the ratio of t‐tau/BACE1 (AUC: 0.90 [95%CI: 0.82‐0.97]) to the same degree as using t‐tau/Aβ42 (AUC: 0.90 [95%CI: 0.82‐0.97]), although this was not significant (p>0.05).ConclusionThis study saw within a PET‐amyloid positive subpopulation of AIBL an increase in neurogranin, a post‐synaptic marker. The presynaptic marker BACE1 alone was not changed in concentration, but when BACE1 was used in a ratio with t‐tau, a marker of neuronal degradation, the differentiation between amyloid negative and positive groups increased. The predictive ability between t‐tau/BACE1 and t‐tau/Aβ42 to estimate PET‐amyloid load is comparable and measurements incorporating BACE1 may provide an alternative to Aβ42‐based assays and the inherent variability associated with Aβ42 measurement between testing sites.
Neuropsychological assessment of financial skills in mild cognitive impairment, Alzheimer’s disease and frontotemporal dementia
Authors: Wong Stephanie , Rawson Georgina , Dixon Ann , Wei Grace , Piguet Olivier , Kumfor Fiona 
Published: December 2023

AbstractBackgroundThe capacity to handle money and personal finances is crucial for living independently. Cognitive decline can lead to financial mismanagement (e.g., forgetting to pay bills, overspending) and exploitation (e.g., falling for financial scams). While greater susceptibility to financial mismanagement and exploitation is commonly reported by carers of people with dementia, objective neuropsychological measures of these financial skills are scarce. It is also unclear whether profiles of change in financial skills vary across different stages and subtypes of dementia.MethodA normative sample of 112 healthy controls and individuals with mild cognitive impairment (MCI; n = 16), Alzheimer’s disease (AD; n = 7) or behavioural‐variant frontotemporal dementia (bvFTD; n = 18) completed a novel neuropsychological Test of Financial Skills (TOFS), which assessed performance across three key areas: everyday financial tasks, susceptibility to financial scams and financial goal planning. For all patients and controls, measures of dementia severity (Clinical Dementia Rating Scale) and general cognition (Addenbrooke’s Cognitive Examination, 3rd Ed.) were also collected.ResultRelative to controls, AD and bvFTD patients showed lower overall performance on the TOFS, whereas MCI patients did not differ significantly from controls. While AD and bvFTD patients showed similar levels of impairment on everyday financial tasks and financial goal planning, bvFTD patients performed significantly worse on the financial scams subtest. Across all participants, lower TOFS performance was associated with greater dementia severity and cognitive impairment.ConclusionOur results are consistent with previous studies of carer‐reported changes in financial mismanagement and exploitation in people with dementia. Notably, we found important differences in the areas of financial skills impacted by different stages and subtypes of dementia. These findings provide novel insights into the different factors that contribute to deficits in financial skills in people with dementia, highlight the importance of objective neuropsychological assessments in this area, and open avenues for targeted financial support strategies.
Levels of TDP‐43 from Plasma‐Derived Astrocyte Exosomes Accurately Differentiates Autopsy Verified LATE from AD
Authors: Rissman Robert A , Winston Charisse N. , Sukreet Sonal , Lynch Haley M , Lee Virginia M. M.‐Y. , Wilcock Donna M. , Nelson Peter T. 
Published: December 2023

AbstractBackgroundLimbic predominant age related TDP‐43 encephalopathy neuropathological change (LATE‐NC) is a neurodegenerative disease characterized brain disease that mimics Alzheimer’s disease (AD) clinically. LATE‐NC is difficult to diagnose antemortem using clinical information or biomarkers. Recent studies suggest concentrations of extracellular vesicle (EVs) protein cargo derived from neuronal and glial cells may serve as useful diagnostic biomarkers for AD and other neurodegenerative diseases. We developed a high throughout bioassay to detect TDP‐43 in plasma derived exosomes for identification of LATE and AD.MethodTDP‐43 was isolated from neuronal (NDEVs), astrocyte (ADEVs), and microglial derived extracellular vesicles (MDEVs) using antemortem plasma from participants with autopsy‐confirmed diagnoses, including many with LATE (n = 22). Quantified TDP‐43 concentrations were compared to the cohort that included healthy controls, mild cognitively impairment (MCI), and AD dementia (n = 42).ResultTDP‐43 was significantly elevated in plasma ADEVs derived from LATE‐NC subjects, with or without comorbid AD pathology. Measurable levels of TDP‐43 were also detected in EV‐depleted plasma; however, TDP‐43 levels were not significantly different between persons with and without eventual autopsy confirmed LATE‐NC. No correlation was observed between EV TDP‐43 levels with cognition‐based variables, sex, and APOE carrier status.ConclusionOur recently developed bioassay and levels of TDP‐43 in ADEVs may serve as a potential diagnostic tool to rapidly identify subjects with LATE‐NC for screening into clinical trials.
Dementia Burden in India and the Research Challenges
Authors: Ravindranath Vijayalakshmi , Sundarakumar Jonas S. 
Published: December 2023

AbstractLonger lifespan has led to increase in number of older persons in LMICs including India. By 2050, people older than 60 years will account for 19.1% of total population (∼360 million) in India. South Asian region would be a major contributor to new dementia cases in the world.Owing to their vast burden, public health efforts have focused on communicable diseases and reduced the burden. However, with growing incidence of cardiovascular diseases, diabetes and hypertension along with increasing longevity, there has been an epidemiological transition towards NCDs in terms of the overall disease burden. Increased prevalence of vascular risks and differential (yet to be identified) genetic susceptibility will impact dementia prevalence. Vast disparity exists between urban middle‐class and two‐thirds of India that live in villages. This disparity is seen in socio‐economic status, lifestyle, literacy as well as access to health care and modern technology. Well‐planned, harmonized, large‐scale studies are needed to identify risk and protective factors. As the impact of vascular risk factors in dementia is evident, understanding their complex interplay with diverse environment will help in devising public health measures to reduce risks through lifestyle interventions earlier in life course.South Asian countries, including India, that have recently invested in dementia research would benefit from joining global ADRD consortia providing access to technology and bi‐directional data sharing. Data sharing across the world is important to gain insights, which will in turn help in developing strategies to prevent or delay the onset of dementia.
Self‐reported physical activity levels do not predict brain beta amyloid levels in older cognitively normal adults over time
Authors: Slee Michael , Rainey‐Smith Stephanie R , Villemagne Victor L , Sohrabi Hamid R , Taddei Kevin , Ames David , Dore Vincent , Maruff Paul , Laws Simon M , Masters Colin L , Rowe Christopher C , Martins Ralph N , Erickson Kirk I. , Brown Belinda M 
Published: December 2023

AbstractBackgroundAnimal studies have consistently shown that physical activity reduces brain levels of beta‐amyloid (Aβ). However, human studies of physical activity and Alzheimer’s disease (AD)‐related brain biomarkers have produced somewhat inconsistent findings. To date, most human studies examining physical activity and Aβ have utilised cross‐sectional analyses and relatively small sample sizes. As brain Aβ is detectable decades prior to the onset of clinical symptoms, examination using longitudinal brain imaging is vital to provide insight into how ongoing physical activity levels impact the progression of AD. In addition, the causal direction of these relationships requires further investigation; some research suggests physical activity levels may decline prior to dementia diagnosis.MethodHabitual physical activity and Aβ measures were collected over 15 years from 731 cognitively normal older adults (60 years and over) participating in the Australian Imaging, Biomarkers and Lifestyle Study of Ageing. Physical activity was assessed via the self‐reported International Physical Activity Questionnaire and brain Aβ measures obtained via PET imaging. Regression modelling examined the cross‐sectional and longitudinal relationships between physical activity and brain Aβ. Moderation analyses examined the impact of apolipoprotein (APOE) ε4 carriage on the physical activity‐Aβ relationship. To further examine the causal nature of this relationship, the trajectory of physical activity levels for individuals as a predictor of either high or low Aβ brain load was also examined.ResultPhysical activity was not associated with brain Aβ at baseline (β = ‐0.001, p = 0.131) or over time (β = ‐0.101, p = 0.571). APOE ε4 status did not moderate the relationship between physical activity and brain Aβ over time (β = 0.04, p = 0.917). Brain Aβ levels were not associated with physical activity trajectory (β = ‐54.26, p = 0.590).ConclusionOur study did not identify a relationship between habitual physical activity and brain Aβ levels. Future longitudinal studies should examine middle‐aged participants to assess whether physical activity influences Aβ accumulation earlier in life.
Predictive Value of CSF Inflammatory Biomarkers in Alzheimer’s disease
Authors: Petersen Kellen K. , Nallapu Bhargav Teja , Grober Ellen , Lipton Richard B. , Ezzati Ali 
Published: December 2023

AbstractBackgroundA growing body of evidence suggests that neuroinflammation contributes actively to pathophysiology Alzheimer’s disease (AD) and promotes AD progression. The predictive value of neuroinflammatory biomarkers for disease‐staging or estimating disease progression is not well understood. In this study, we investigate the diagnostic (i.e., differentiating clinical stages of disease) and prognostic (estimating probability of cognitive decline) ability of inflammatory biomarkers in combination with conventional AD biomarkers.MethodsWe included 242 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who had CSF biomarkers of Aβ, tau, and inflammation. Outcome of interest was clinically meaningful cognitive decline (CMCD) as defined by an increase of ≥4 on the Alzheimer’s Disease Assessment Scale Cognitive Subscore 11 (ADAS‐11, scores 0‐70, higher scores indicate worse cognition). Predictor variables were categorized as demographics (D; age, sex, and education), genetic information such as APOE4 status (G), inflammatory biomarkers (I; see Table 1 for details), and cerebrospinal fluid (CSF) biomarkers of β‐amyloid (A), p‐Tau (P), and total Tau (T). Logistic regression was performed to investigate if grouped inclusion of eleven CSF inflammatory biomarkers as covariates in the models improved classification of baseline clinical diagnosis (CN, cognitively normal; MCI, mild cognitive impairment; Dementia) as well as classification of individuals with and without CMCD one year after baseline.ResultsAt 1‐year follow up, 25.6% experienced CMCD. Inclusion of inflammatory biomarkers improved classification of MCI vs Dementia for models base on DG (p = 0.039) and DGAPT (p = 0.016) feature‐sets. Addition of inflammatory biomarkers to model with DGAPT features, but not the DG model, improved predictive performance for CMCD in CN (p = 0.021) and MCI (p < 0.001) participants.ConclusionsAddition of CSF Inflammatory biomarkers to AD biomarkers can improve diagnostic accuracy of clinical disease stage. Furthermore, inflammatory biomarkers add incremental value to AD biomarkers for prediction of clinical course and cognitive decline.