bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Interaction between APOE genotype and Type 2 diabetes on Cognitive and Neuropathology features
Authors: Karanth Shama D , Abner Erin L , Katsumata Yuriko 
Published: December 2023

AbstractBackgroundType 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) are common diseases in aging populations. Multiple large epidemiological studies suggest that T2DM is strongly associated with cognitive impairment and dementia. Prior studies suggest T2DM may be an important modifier of the relationship between AD and APOE, which is the strongest known genetic risk factor of AD.MethodWe obtained study data from the National Alzheimer’s Coordinating Center (NACC) and included 30,483 participants aged ≥60 years at baseline. T2DM status was determined based on any self‐reported diabetes diagnosis or anti‐diabetes treatment during annual assessments. To facilitate analysis, we created two binary variables to classify participants with regard to T2DM (presence or absence) and APOEε4 (carrier or non‐carrier) status. Cognitive domain scores for memory, attention, language and executive function were standardized using z‐scored neuropsychological tests administered at annual visits. Multivariable linear mixed‐effects models with a cross‐product interaction term between T2DM and APOEε4 status, including main effects, assessed whether the association of APOEε4 with domain‐specific cognitive change was modified by T2DM status. In the subset of participants who underwent autopsy (n = 5,663), we examined whether T2DM modified the association between APOEε4 and neuropathological features using multivariable logistic regression.ResultA significant interaction exists between T2DM and APOE genotype. APOEε4 carriers with T2DM had more rapid declines in attention, language, memory, and executive cognitive scores over time. APOEε4 non‐carriers with T2DM had lesser impairment compared to APOE ε4 carriers without T2DM. Among the autopsied participants, non‐APOE ε4 carriers with T2DM had larger odds of infarcts/lacunes and atherosclerosis. Compared to non‐APOE ε4 carriers without T2DM, APOE ε4 carriers with or without T2DM showed higher odds of AD neuropathological changes (ADNC), but lower odds of ADNC among non‐APOE ε4 carriers with T2DM.ConclusionT2DM modifies the association between APOE ε4 and cognitive decline and AD neuropathological features. T2DM in non‐APOE ε4 carriers increased the risk of infarcts/lacunes but not ADNC.
Blood‐based biomarkers for predicting treatment response in the Apathy in Dementia Methylphenidate Trial 2 randomized clinical trial
Authors: Tumati Shankar , Vieira Danielle , Bawa Kritleen Kaur , Andreazza Ana C. , Mintzer Jacobo , Scherer Roberta , Rosenberg Paul B. , van Dyck Christopher H , Padala Prasad R , Brawman‐Mintzer Olga , Porsteinsson Anton P. , Lerner Alan J. , Craft Suzanne , Levey Allan I. , Burke William J , Perin Jamie , Shade David , Herrmann Nathan , Lanctôt Krista L. 
Published: December 2023

AbstractBackgroundThe Apathy in Dementia Methylphenidate Trial 2 (ADMET 2) found that methylphenidate (MPH) was modestly efficacious is treating apathy in Alzheimer’s disease (AD) with 66% response (> = 4 point decrease on Neuropsychiatric Inventory – apathy (NPI‐A). Here, we evaluated if blood‐based biomarkers potentially associated with treatment‐limiting neuronal damage predicted the probability of treatment response.MethodADMET 2 participants with baseline and endpoint (6 month) NPI‐A and baseline concentrations of (i) neuronal damage: neurofilament light (NFL) and S‐100B, (ii) inflammation: interleukin (IL)‐6, IL‐10, Tumor Necrosis Factor‐alpha (TNFα), and (iii) oxidative stress: lipid hydroperoxide (LPH), 4‐hydroxynonenal (4‐HNE), 8‐isoprostane (8‐ISO) were included. Biomarkers were normalized by log transformation and pareto scaling. Univariate models examined whether each biomarker interacted with the treatment condition to predict a change of at least 2 points on the NPI‐A. Next, biomarkers with significant associations were included in a multivariate logistical regression model that was used to predict treatment response to MPH and placebo. The index score (difference between response probabilities for MPH and placebo) of each participant indicated their favourability for MPH treatment. Participants were grouped into quartiles by their index score with confidence intervals estimated using non‐parametric bootstrapping.ResultForty‐nine participants (placebo = 26, MPH = 23, age = 75.4 years (standard deviation [SD] = 7.6), 57% males, Mini Mental State Examination = 19.7 [SD = 4.6]) were included. MPH was more efficacious than placebo in those with higher baseline NFL (‐5.8, t = ‐3.1, p = 0.003), and less efficacious in those with higher LPH (2.0, t = 1.48, p = 0.15). Apathy worsened in participants with high TNFα (2.71, t = 1.94, p = 0.06) in both MPH and placebo groups. Participants in the top quartile of the biomarker index score (66.7% on MPH) were more likely to respond to MPH than placebo (index score = 0.58, 95%CI: 0.48, 0.69).ConclusionIndividuals with greater neuronal injury were more likely to respond to MPH, suggesting that MPH supplementation provides more benefit when neuronal injury is more severe. Combining blood biomarkers yielded a prediction score where participants with high NFL and low LPH levels were more likely to respond to MPH. This approach utilizes biomarkers to address heterogeneity in treatment response to MPH.
Cerebral perfusion and amyloidosis in the oldest‐old
Authors: Dutt Shubir , Woodworth Davis C. , Sajjadi S. Ahmad , Kawas Claudia H. , Corrada María M. M. , Nation Daniel A. 
Published: December 2023

AbstractBackgroundCerebrovascular contributions to cognitive aging and Alzheimer’s disease (AD) risk represent a growing field in aging research. Studies in the young‐old have demonstrated the critical role of vascular dysregulation (i.e., altered cerebral blood flow) in relation to cognitive decline prior to the appearance of amyloid/tau biomarkers. However, cerebral perfusion has not been well‐studied in the oldest‐old (ages 90 and over), a rapidly growing population that may provide unique insight into resilience and protective factors against dementia in later life. We characterized amyloid and cerebral perfusion profiles of cognitively normal (CN) and cognitively impaired without dementia (CIND) oldest‐old individuals.MethodParticipants were 97 dementia‐free older adults (70 CN and 27 CIND) from the 90+ Study who had available neuroimaging (T1‐MRI, ASL‐MRI, Florbetapir‐PET), demographic, and clinical data. We examined differences between CN and CIND in regional perfusion in areas associated with AD risk (medial temporal lobe, posterior cingulate, precuneus, frontal cortex, inferior parietal lobe) and in amyloid burden using linear regression models controlling for age, sex, education, APOE4 status, and vascular risk factors.ResultCN and CIND groups did not differ in the characteristics compared (Table 1). CIND participants had lower CBF in the posterior cingulate/precuneus than the CN group, but groups did not differ in posterior cingulate/precuneus amyloid SUVR (Figure 1). Additionally, CIND had lower CBF than CN in the inferior parietal lobe but higher CBF in the medial temporal lobe and orbitofrontal cortex (Figure 2).ConclusionCIND individuals had lower regional perfusion in the posterior cingulate/precuneus, but groups did not differ in amyloidosis, highlighting the relationship between cerebrovascular function and cognitive status in the oldest‐old independent of amyloidosis. Our findings complement previously reported posterior cingulate/precuneus hypoperfusion in younger‐old individuals with cognitive impairment and AD. Interestingly, we observed greater medial temporal/frontal perfusion in CIND than CN, similar to previous studies demonstrating initial hyperperfusion preceding hypoperfusion across the CN‐CIND‐Dementia spectrum. This may represent a compensatory vascular mechanism supporting cognition in individuals at greater risk of developing dementia. Future studies will further characterize this cohort with longitudinal perfusion analyses, neuropsychological correlates, and relationships between perfusion and other indices of cerebrovascular dysfunction.
The European Platform for Neurodegenerative Diseases (EPND)
Authors: Visser Pieter Jelle , Brookes Anthony J. , Scordis Phil , Bose Niranjan 
Published: December 2023

AbstractBackgroundBiomarker discovery, development, and validation are reliant on large‐scale analyses of high‐quality samples and data. However, discovery, access, and sharing of data and samples are hindered both by silos that limit collaboration, and by complex requirements for secure, legal, and ethical sharing. The European Platform for Neurodegenerative Diseases (EPND) project aims to address these challenges and accelerate biomarker discovery, development and validation, by building a scalable, sustainable platform for collaboration, data and sample sharing. In this presentation we will give an overview of the design of EPND and the achievements in the first year of this 5‐year project.MethodEPND is a multidisciplinary consortium of 29 public and private partners with expertise on data discovery, ethical, legal and regulatory aspects of data sharing, biomarker studies, stakeholder engagement and sustainability. EPND will leverage existing data and research infrastructures, including the Alzheimer’s Disease Data Initiative (ADDI) AD Workbench, which will allow the platform to connect to a global research network. EPND was launched in November 2021 and is funded by the Innovative Medicines Initiative (IMI, grant agreement number 101034344, epnd.org).ResultIn this first year of the project, the design of the data platform has been finalised. EPND has launched its Cohort Catalogue, which features information on participants, samples and data from 60+ neurodegeneration cohorts, spanning 17 countries and 13 disease areas, and involving over 155,000 patients. In addition to standardised operational procedures on sample selection, biobanking, and data harmonisation, we have also developed a white paper on legal, ethical and regulatory aspects of data and sample sharing. Finally, we have performed case studies on ATN biomarkers in plasma and blood in 350 patients with Alzheimer’s disease, Parkinson’s disease and Lewy body dementia.ConclusionWe initiated a multidisciplinary consortium with the goal to accelerate collaborative research into the discovery and validation of biomarkers, to support development of diagnostics and disease‐modifying therapies for AD and other neurodegenerative diseases.
The role of nurses in recruiting Filipino, Korean, and Hispanic/Latino participants to preclinical Alzheimer’s disease trials.
Authors: Tallakson Melanie B , Shin Hye‐Won , Duran Edwin , Sultzer David L , Grill Joshua D , Salazar Christian R. 
Published: December 2023

AbstractBackgroundThe factors that influence clinical trial participation in the Filipino, Korean and Hispanic/Latino communities remain poorly understood. Nurses are well positioned to play a dynamic role in the recruitment of underrepresented communities to preclinical Alzheimer’s disease (AD) trials. This study used a community‐based nursing partnership model to gain insights into whether and how nurses serve as key gatekeepers within these communities.MethodSixty in‐depth stakeholder interviews were conducted with 20 Hispanic/Latino, 20 Filipino, and 20 Korean American nurses via Zoom. Nurses were recruited through a unique collaboration between community‐based Filipino, Korean and Hispanic/Latino professional nursing organizations and academic investigators. A semi‐structured interview guide was used to collect sociodemographic information and to assess nurses’ research attitudes and perspectives regarding the recruitment of underrepresented community members to AD preclinical trials.ResultOverall, 63% of nurses had >20 years of clinical practice experience, 93% had a bachelors or graduate degree, 75% were fully employed, 14% were part‐time employed, 12% were retired, and 72% knew someone with a diagnosis of AD. Most Filipino (90%) and Korean (90%) nurses were not born in the US, as compared to Hispanic/Latino nurses (25%). Emergent themes were identified including the role of nurses as a (1) trusted source of health information, (2) patient advocate and community educator, and (3) liaison connecting key community stakeholders to AD trials. Commonalities in perspectives among the nursing groups about community members’ participation in trials included the role of familism in decision‐making, the need for strong family support, and reliance on family members, such as adult children, to communicate important health information. A notable difference between the nursing groups was that Hispanic/Latino nurses more often communicated in a non‐English (Spanish) language with patients as compared to Filipino and Korean nurses. All nursing groups, on average, exhibited positive attitudes towards research.ConclusionOur findings suggest that nurses can serve as a valuable vehicle for improving recruitment to preclinical AD clinical trials. Nurses are well positioned to engage with the community and provide culturally tailored patient, family, and community education.
Sequencing cortical microstructural changes along the Alzheimer’s disease continuum
Authors: Nir Talia M , Javid Shayan , Villalon‐Reina Julio E , Thomopoulos Sophia I , Salminen Lauren , Thompson Paul M , Jahanshad Neda 
Published: December 2023

AbstractBackgroundMicrostructural abnormalities likely precede macrostructural changes in the Alzheimer’s disease (AD) cascade. Diffusion MRI (dMRI) is sensitive to microstructural properties of brain tissue but few studies have evaluated dMRI measures in cortical gray matter where many early AD histopathological changes occur. Event‐based modeling (EBM) is a data‐driven approach for probabilistically sequencing cross‐sectional biomarkers in the order that they likely become abnormal. Here, we used EBM to examine the sequence of changes in cortical dMRI measures relative to more widely used amyloid, tau, brain volume, and cognitive biomarkers in two independent AD studies.MethodT1w, dMRI, and amyloid‐PET (FBB/FBP) data were analyzed in 461 ADNI3 participants and 188 OASIS3 participants (Figure 1A). Some ADNI3 participants also had tau‐PET (AV‐1451) and CSF pTAU‐181 and Aβ1‐42 data. In addition to DTI, novel single‐shell adaptations of multi‐shell models, NODDI‐DTI and MAP‐AMURA, were fit to the dMRI data. 10 mean cortical dMRI measures were extracted using FreeSurfer parcellated T1w‐images (Figure 1B). T1w cortical and hippocampal volumes were also extracted, and all MRI measures harmonized using ComBat. Mean cortical amyloid‐PET SUVRs were converted to centiloids. Associations between each of 17 biomarkers (Figure 1C) and cognitive impairment (CI –MCI+Dementia– vs CN) were tested in ADNI3. Significant biomarkers were included in an ADNI3 EBM to determine event ordering.The EBM was validated in OASIS3 and used to classify clinical diagnosis.ResultAll biomarkers except DTI FA showed significant differences between CN and CI ADNI3 participants (Figure 2A). ADNI3 EBM confirmed existing AD models: CSF amyloid abnormalities preceded PET, followed by CSF pTau, while cognitive and volumetric abnormalities occurred at later stages. Changes in all dMRI biomarkers preceded CSF or PET Tau, cognitive, and volumetric abnormalities (Figure 2B). Estimated disease stages in ADNI3 distinguish dementia from CN with an AUC = 0.96 (10‐fold cross‐validation). OASIS3 disease stages, estimated using ADNI3 biomarker distributions excluding CSF measures and tau‐PET, classified diagnosis with an AUC = 0.85 (Figure 3).ConclusionCortical microstructural measure abnormalities, including greater diffusivity, lower restriction and lower dispersion potentially due to neurite loss and lower dendritic arborization complexity, may precede those detectable with conventional T1w biomarkers.
Using Semi‐supervised Variational Autoencoder and Acute fMRI Changes to Predict Antidepressant Treatment Responses Among Older Adults with Depression
Authors: Wang Linghai , Lee Jihui , Mizuno Akiko , Wilson James D , Lamb Shannon , Gerlach Andrew , Wu Minjie , Aizenstein Howard J ,   Geriatric Psychiatry Neuroimaging
Published: December 2023

AbstractBackgroundLate‐life depression (LLD) has been consistently linked to an increased risk of dementia, with studies showing that older adults with depression have a two fold risk of developing dementia. Dementia has proven difficult to treat, yet depression has several viable treatment options, particularly antidepressants. However, the efficacy of antidepressants in LLD has proven modest as antidepressants typically achieve around a 50% remission rate and only after 4‐6 weeks of treatment. In this analysis, we investigate the effectiveness of combining fMRI data with deep learning for predicting antidepressant driven depression remission.MethodIn two LLD studies using venlafaxine (n = 51) and escitalopram or levomilnacipran (n = 29), resting state fMRI scans were collected at baseline and at day one of antidepressants. Region‐to‐region functional connectivity (FC) was calculated for each scan using the Shen50 atlas, and differential connectivity (DC) was calculated to compare baseline and day 1 FC. Clinical factors including age, race, education and cumulative illness burden and DC were used as input to a semi‐supervised variational autoencoder (VAE) to predict remission status at treatment end (Fig.1). Remission was encoded as a binary variable, defined as a final MADRS score of 10 or less after 12 weeks of treatment and subject to blinded clinician assessment. Monte Carlo cross‐validation over 30 repetitions was used to evaluate the model performance with 10% of the data held out for testing. The VAE was compared to a random forest classifier with the same cross validation methods using the area under the curve (AUC).ResultThe VAE achieved an average mean‐squared error of .005 and AUC of 0.87 on a held out test set during cross validation. The VAE outperformed the random forest classifier which achieved an average AUC of 0.68.ConclusionThe VAE using DC in fMRI scans between baseline and day one shows the potential in accurately identifying responders to antidepressants as early as in one day. Our results show that acute changes to functional networks triggered by a single dose of antidepressants are promising as a means to improve patient outcomes. These results can contribute to optimizing treatment for LLD in the future.
Microglial activation interacts with amyloid‐β to drive longitudinal tau tangle accumulation and cognitive decline
Authors: Povala Guilherme , Bellaver Bruna , Lussier Firoza Z , Ferreira Pamela C.L. , Ferrari‐Souza João Pedro , Leffa Douglas Teixeira , Aguzzoli Cristiano Schaffer , Zalzale Hussein , Soares Carolina , Abbas Sarah , Rohden Francieli , Tissot Cécile , Therriault Joseph , Bezgin Gleb , Servaes Stijn , Benedet Andrea Lessa , Stevenson Jenna , Rahmouni Nesrine , Cohen Annie , Lopez Oscar L. , Tudorascu Dana , Klunk William E , Villemagne Victor L , Karikari Thomas K , Zimmer Eduardo R , Rosa‐Neto Pedro , Pascoal Tharick Ali 
Published: December 2023

AbstractBackgroundActivation of microglial cells in the brain, more commonly known as neuroinflammation, has often been linked to the pathophysiology of Alzheimer’s disease (AD). However, how microglial activation is associated with longitudinal tau tangle accumulation and consequent cognitive decline is poorly understood. Here, we aimed to investigate whether baseline microglial activation impacts tau tangle deposition and cognitive decline in individuals across the AD continuum.MethodWe assessed 92 individuals from the TRIAD cohort (57 cognitively unimpaired and 35 cognitively impaired) with available baseline [11C]PBR28‐PET, a measure of microglial activation and [18F]NAV4694 Aβ‐PET, and longitudinal [18F]MK6240 Tau‐PET (mean follow‐up time = 1.93 years) and Mini‐Mental State Exam (MMSE) (mean follow‐up time = 1.84 years). We performed voxel‐wise associations using linear regressions accounting for age and sex and adjusted for multiple comparisons using Random Field Theory (RFT) (p < 0.05). We used the cuneus and superior temporal cortex as a composite ROI for [11C]PBR28‐PET and Aβ‐PET since these regions showed a higher association with longitudinal tau accumulation in the temporal meta‐ROI.ResultVoxel‐wise analysis showed that baseline levels of [11C]PBR28‐PET alone are not sufficient to predict longitudinal tau tangle accumulation (Fig. 1a). However, the interaction between [11C]PBR28‐PET levels and Aβ burden predicted an increased accumulation of tau tangle, mainly in the cuneus, inferior frontal and lateral occipital regions (Fig. 1b).Individuals with higher baseline [11C]PBR28‐PET and Aβ‐PET levels present higher rates of longitudinal tau accumulation in the temporal meta‐ROI (β = 0.36, t = 3.46, p = 0.0009; Fig. 1c). Similarly, while [11C]PBR28‐PET levels alone did not correlate with longitudinal changes in MMSE score (β = ‐0.17, t = ‐1.69, p = 0.10), a significant interaction between [11C]PBR28‐PET and Aβ‐PET levels on MMSE annual decline was observed (β = ‐0.24, t = ‐2.25, p = 0.028; Fig. 1d).ConclusionWe found that baseline levels of microglial activation was associated with longitudinal tau tangle accumulation and cognitive decline in individuals across the AD continuum in the presence of Aβ burden. Our results indicate that microglial activation might act potentiating the deleterious effects of Aβ on forthcoming tau tangle deposition.